Evaluation of a prototype artificial life model to simulate the interactions between the human immune system, human papillomavirus type 16 and therapeutic vaccines

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Pranata, B. Zulkifli, S.F. Santosa, A. Oktiviyari, Z. Zulfitri, Z. Hayati, M. Mudatsir, I. Ichsan, H. Harapan" "autores" => array:9 [ 0 => array:2 [ "nombre" => "A." "apellidos" => "Pranata" ] 1 => array:2 [ "nombre" => "B." "apellidos" => "Zulkifli" ] 2 => array:2 [ "nombre" => "S.F." "apellidos" => "Santosa" ] 3 => array:2 [ "nombre" => "A." "apellidos" => "Oktiviyari" ] 4 => array:2 [ "nombre" => "Z." "apellidos" => "Zulfitri" ] 5 => array:2 [ "nombre" => "Z." "apellidos" => "Hayati" ] 6 => array:2 [ "nombre" => "M." "apellidos" => "Mudatsir" ] 7 => array:2 [ "nombre" => "I." "apellidos" => "Ichsan" ] 8 => array:2 [ "nombre" => "H." 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Ossa, R.G. Sieben, M.C. Cervi, D.A.F.d.S. Lima, R. Santos, D.C. Aragon" "autores" => array:6 [ 0 => array:2 [ "nombre" => "R.P.-D.l." "apellidos" => "Ossa" ] 1 => array:2 [ "nombre" => "R.G." "apellidos" => "Sieben" ] 2 => array:2 [ "nombre" => "M.C." "apellidos" => "Cervi" ] 3 => array:2 [ "nombre" => "D.A.F.d.S." "apellidos" => "Lima" ] 4 => array:2 [ "nombre" => "R." "apellidos" => "Santos" ] 5 => array:2 [ "nombre" => "D.C." "apellidos" => "Aragon" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2445146022000358?idApp=UINPBA00004N" "url" => "/24451460/0000002300000002/v3_202302191848/S2445146022000358/v3_202302191848/en/main.assets" ] "en" => array:17 [ "idiomaDefecto" => true "cabecera" => "Original article" "titulo" => "Evaluation of a prototype artificial life model to simulate the interactions between the human immune system, human papillomavirus type 16 and therapeutic vaccines" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "125" "paginaFinal" => "138" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "M.E. Escobar-Ospina" "autores" => array:1 [ 0 => array:4 [ "nombre" => "M.E." "apellidos" => "Escobar-Ospina" "email" => array:1 [ 0 => "meescobaro@unal.edu.co" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "*" "identificador" => "cr0005" ] ] ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Departamento de Ingeniería-Sistemas y Computación, Universidad Nacional, Bogotá, Colombia" "identificador" => "af0005" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cr0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Evaluación de un prototipo de modelo de vida artificial para simular interacciones entre el sistema inmune humano, el virus del papiloma humano tipo 16 y vacunas terapéuticas" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "f0020" "etiqueta" => "Fig. 4" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr4.jpeg" "Alto" => 2353 "Ancho" => 1908 "Tamanyo" => 408823 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "al0020" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Trend observed in the lesions provoked by the virus in each of the experimental conditions. The graphs illustrate the behaviour of the different lesions caused by HPV16, comparing the trend observed in the lesion with each of the experiments carried out. (A) Trend in cancer conditions. (B) Trend in pre-cancer conditions. (C) Trend in CIN1 lesions. (D) Trend in CIN2 lesions. (E) Trend in CIN3 lesions. EXP-1: trend in patients not receiving vaccine; EXP-2: trend in patients receiving therapeutic vaccine with dendritic cells (DC) = 10 μg/mL; EXP-3: trend in patients receiving therapeutic vaccine DC = 100 μg/mL; EXP-4: trend in patients receiving therapeutic vaccine DC = 1000 μg/mL; EXP-5: trend in patients receiving therapeutic vaccine DC = 10 μg/mL with IL-2 adjuvant; EXP-6: trend in patients receiving therapeutic vaccine DC = 10 μg/mL with Poly I:C adjuvant as TLR3 ligand; EXP-7: trend in patients receiving therapeutic vaccine DC = 10 μg/mL with CpG adjuvant as TLR9 ligand." ] ] ] "textoCompleto" => "IntroductionThe prototype built based on the HPV16-ALIFE model can simulate the life of a virtual patient who, for several years, suffers the effects of infection caused by human papillomavirus type 16 (HPV16) in computational minutes. Based on this persistent viral infection, the model can simulate the development of low- and high-grade cervical lesions, including intraepithelial neoplasia (CIN), pre-cancer, and cancer. Such conditions can be treated with virtual therapeutic vaccines aimed at controlling related diseases that evolve in the host over time. The HPV16-ALIFE prototype can display an optimal vaccination schedule to match the simulated circumstances derived from its environment. Vaccine researchers could test different vaccination strategies and observe the effects caused to the virtual host over the short-, medium-, and long term, and thereby consider an alternative approach to define the most efficient treatment possible given the simulated conditions.Materials and methodsHPV16-ALIFE belongs to the class of artificial life models and its design is based on agent-based modelling and cellular automata. This model integrates the simulation of the human immune system, the HPV16 life cycle (detailed in our previous article<a class="elsevierStyleCrossRef" href="#bb0005">1</a>) and the effects caused by the challenge posed by certain therapeutic vaccines that seek to control lesions caused by the presence of this virus. The corresponding prototype has been developed with the NetLogo 5.3<a class="elsevierStyleCrossRef" href="#bb0010">2</a> programming tool, given that it enables complex environments to be modelled in order to simulate biological and social phenomena that are useful to support current biomedical research. Because of its extension, the description of the conceptualisation and the process of creating the artificial life model as such is part of a previous article.Simulation of experiments on the prototype can address both the evaluation of a therapeutic vaccine and the assessment of a drug treatment, either independently or simultaneously. Drug simulation involves activating or blocking one or more components associated with cytokines and Toll-like receptors (TLRs). Evaluating new therapeutic vaccines involves defining the desired specifications in terms of load, dose, and frequency of administration. It also implies activating certain components that will act as adjuvants, only when necessary.Based on the theories of complex systems and biological systems, and making use of artificial life tools, we have simulated the processes of this model based on the biological knowledge currently available. In this way, we have endeavoured to prevent the user from defining biased rules or generating conditions on the basis of their own prejudices or from including parameters that may be convenient from the computational point of view or from the experimental point of view.Model validationThe prototype developed contemplates 3 options to treat the patient's lesions: (1) delivery of a therapeutic vaccine, (2) delivery of blocking drugs, and (3) delivery system with immune checkpoint therapy against cancer, specifically the PD-1/PD-L1 axis. While the model can simulate these 3 treatment scenarios, given the space constraints in the publication, in this article we will concentrate on showcasing the tests performed with the first option.In order to evaluate the behaviour of this model and determine whether the finite nature of the simulation affects the results, some virtual tests have been run as an example, varying certain parameters according to the rules of the experiment. The aim of the proposed experiments is to observe the effect caused by the administration of a virtual therapeutic vaccine when there is a lesion stemming from persistent HPV16 infection. Similarly, it also seeks to demonstrate the responses produced by the simulated immune system (SIS). Therefore, groups of patients with persistent infection have been compared between those who do not receive treatment and those who are treated with therapeutic vaccines. In addition, the objective is to observe the conditions under which the therapeutic vaccine is more effective, which is why we have compared groups of patients with persistent infection, between those who receive a non-adjuvanted therapeutic vaccine and those who receive an adjuvanted therapeutic vaccine. In the latter group, 3 different kinds of adjuvants are evaluated with the purpose of observing how the effectiveness of the vaccine might vary with each. <a class="elsevierStyleCrossRef" href="#f0005">Fig. 1</a> illustrates the diagram of the corresponding experimental design.<elsevierMultimedia ident="f0005"></elsevierMultimedia>The virtual trials performed on the HPV16-ALIFE prototype are based on the conditions detailed below, and within the proposed experimental context, the terms specifically defined will be understood as having the following connotation:(a) Simulated patient: This term refers to the set of virtual components that represent the human immune system, including the effects resulting from its interaction with the HPV16 life cycle, as well as the events triggered by the release of doses of a therapeutic vaccine. A simulation running on the prototype makes it possible to observe how the infectious viral process experienced by a virtual patient evolves. Each of the simulations performed is followed for a pre-specified time of evolution; in this case in particular, it begins at week 1 and ends at week 1400. The corresponding data are displayed on the graphical user interface (GUI), in real time, on several monitors and trend graphs.It should be noted that this model allows the number of weeks during which a patient can evolve to be varied (this number will be determined by the end user). However, in the trials documented in this article, we worked with exactly 1400 weeks for all the simulated patients. The purpose of this is to be able to compare the results across patients and observe what happens to each of them over a period of 26 continuous years, counting from the first exposure to the virus. Within this period of time, several scenarios can be presented, taking into account that the lesions could progress and become evident 10 years after the first infection or be eliminated by the immune system after a period of time of up to 4 years.b) Sham therapeutic vaccine: This term applies to a given quantity of virtual autogenous dendritic cells (DC), loaded with E6/E7 antigens, which are administered to the sham patient. The delivery is performed through a virtual nanodevice, which releases and delivers each dose to the patient, assessing the proper timing and the maximum number of doses established by the model, in accordance with the conditions that emerge from the microenvironment. Considering the frequency and the maximum number of doses previously established in each type of experiment, the model will be able to administer the amount of doses equal to or less than the predetermined parameters. The decision taken by the model will depend on the characteristics reported by the simulated environment, and will halt delivery when the markers indicate that the lesions have been eliminated or when the maximum dosing limit determined by the researcher has been reached. In this model, the simulated therapeutic vaccine does not consider toxicity levels, route of administration, or adverse events resulting from its administration.c) It is assumed that the patients participating in each experiment correspond to confirmed cases of HPV16+, women who are sexually active, and who do not report any other simultaneous viral infection.d) The proposed experimental design is intended to observe the behaviours associated with viral oncoproteins E6 and E7, interleukin-12 (IL-12), and the cytotoxic T-lymphocyte (CTL) population. Some of the reasons for this selection stem from the following facts: (d1) cervical cancers express E6 and E7 proteins; their levels of expression induce activation of centrosome duplication and abnormal centrosome accumulation, and these processes that are active during carcinogenesis are associated with high-risk HPVs<a class="elsevierStyleCrossRef" href="#bb0015">3</a>; d2) IL-12 is an antitumor and antiviral cytokine, which not only inhibits tumour cell proliferation, but also induces clearance of virus-infected cells,<a class="elsevierStyleCrossRef" href="#bb0020">4</a> and d3) CTLs participate in adaptive immune responses and are key players in mediating immunity against pathogens and tumours.<a class="elsevierStyleCrossRef" href="#bb0025">5</a>Even though HPV16-ALIFE can run any number of simulations and combination of variables that the researcher requests to develop the precise example we are evaluating in this article, we have proposed the conditions detailed below.In the execution of the proposed experimental design, a total of 210 simulations were conducted, corresponding to 210 virtual patients. Out of this group, 30 patients do not receive vaccines; 90 patients are given therapeutic non-adjuvanted vaccines, and 90 patients are given therapeutic adjuvanted vaccines. The simulated therapy consists of an autogenous DC therapeutic vaccine, loaded with HPV16 E6 and E7 antigens. A maximum of 3 doses (Dosage parameter), at 2-week intervals between doses (Intervals-weeks parameter) is planned for all cases corresponding to patients to receive vaccination. However, the model will confirm the number of doses required and the specific week of administration necessary to effectively eliminate the patient's lesions. As regards the testing of non-adjuvanted vaccines, the load will vary between 10, 100, and 1000 μg/mL (antigen-loaded DCs parameter). As for adjuvanted vaccine testing, the load will be kept constant at 10 μg/mL (antigen-loaded DCs parameter) and the adjuvant will vary between IL-2 (Selector, Activate-cytokine = IL-2), Poly I:C as a ligand of TLR3 (Switch, TLR3 = on), and CpG as a TLR9 ligand (Switch, TLR9 = ON).When a therapy is planned in the prototype and the selector tools are used, the selected components will act as adjuvants for the therapeutic vaccine to be administered to the virtual patients. When a vaccine is not planned, but one or more selectors are switched on, the selected components will act within the model as a drug. Similarly, when a therapeutic vaccine is planned and TLR switches are used, they will act as adjuvants. When a vaccine is not planned, but a TLR switch is activated, the chosen component will act as a drug.We define “phase” as the set of initial states (active/inactive) associated with one or more viral proteins, which are stated prior to initiating a simulation. The experiments we performed in “phase I" started with all viral proteins in the active state (i.e., the protein switches on the GUI are set to the on state). The experiments we conducted in “phase II" started with the E7 protein in the inactive (OFF) state. The assays we performed in “phase III" started with the E6 protein in the inactive (OFF) state. Against this background, we conducted 7 types of experiments. Each experiment involved 30 virtual patients.The unit of time in the simulations corresponded to 1 week (1 tick = 7 days). However, for events in which the time fraction occurs in different measures, such as days, hours, minutes, seconds, or microseconds, this model converts the default unit of time and sets an equivalent within the procedure involved (i.e., 1 day = 24 h; 1 h = 60 min; 1 min = 60 s, and so on).To perform our example in particular, each simulation runs for 1400 continuous weeks. During this simulated time span, records are taken at weeks 48, 53, 156, 208, 208, 300, 500, and 1400. These specific weeks were selected for the following reasons:<ul class="elsevierStyleList" id="l0005"><li class="elsevierStyleListItem" id="li0005">•a) Week 48: The mean time taken for antibody recognition from primary detection of HPV16 DNA has been reported to be 10.5 months in cervical secretions and 19.1 months in serum. Loss of antibodies has been reported at 12 months in cervical secretions and 13.6 months in serum.<a class="elsevierStyleCrossRef" href="#bb0030">6</a></li><li class="elsevierStyleListItem" id="li0010">•b) Week 53: Between 1 and 2 years of exposure, HPV infections are cleared or suppressed through cell-mediated immunity to undetectable levels.<a class="elsevierStyleCrossRefs" href="#bb0035">7–10</a></li><li class="elsevierStyleListItem" id="li0015">•c) Week 156: Several studies have found that the average duration of HPV infection in women who were baseline HPV-negative ranges from 8.5 to 19.4 months.<a class="elsevierStyleCrossRefs" href="#bb0050">10–12</a> This control is included in our model, given that weeks 48 and 53 are within the previously controlled ranges.</li><li class="elsevierStyleListItem" id="li0020">•d) Week 208: Long-term infection is reported to develop over an average time of 5.1 years.<a class="elsevierStyleCrossRef" href="#bb0065">13</a></li><li class="elsevierStyleListItem" id="li0025">•e) Week 300: Several studies have demonstrated that women at high risk of developing HPV have abnormal cytology at 2 years or CIN3 at 4 years, following exposure to the virus.<a class="elsevierStyleCrossRefs" href="#bb0070">14–17</a></li><li class="elsevierStyleListItem" id="li0030">•f) Week 500: Cervical cancer has been reported to develop 10 years after the first exposure to the virus.<a class="elsevierStyleCrossRef" href="#bb0090">18</a></li><li class="elsevierStyleListItem" id="li0035">•g) Week 1400: We would like to observe whether cancer recurs after administering a therapeutic vaccine to the patient during the simulation in the years after the lesions arising from HPV infections have cleared up.<a class="elsevierStyleCrossRef" href="#bb0080">16</a></li></ul>During the execution of this particular example, for each of the weeks referred to above, we retrieved precise information derived from the corresponding data registry. This registry considers the results reported by HPV16-ALIFE regarding: (1) expression levels of viral proteins (E1, E2, E4, E5, E6, E7, L1, and L2); (2) disease transition states (infection %, mutation %, malignancy %, neoplasia %, ccin1%, ccin2%, ccin3%, pre-cancer %, and cancer %); (3) secretion levels of the cytokine IL-12, and (4) proliferation levels of the CTL population. Nonetheless, it must be pointed out that our model allows us to observe other behaviours, in addition to those proposed in this example. Moreover, this model makes it possible to observe behaviours associated with other cell populations, other cytokines, TLRs, and surface molecules. Therefore, it will be up to the investigator to decide which variables to follow depending on their individual interest.Data analysisThe average values of the data corresponding to the simulated patients, for each type of experiment, in each of the 3 scheduled phases, are generated from the records collected at the different control points (weeks 48, 53, 156, 208, 300, 500, and 1400). After that, the averages of the cycles that comprise each of the 3 established phases are generated and finally, the percentiles are calculated for the measurements taken. Based on the calculated percentiles, the trend analysis is carried out for the E6 and E7 viral oncoproteins, the IL-12 cytokine, and the CTL population, with the goal of demonstrating whether the SIS is activated and whether the virtual vaccine is capable of eliminating the lesions caused by HPV16.Functional logic implemented in the HPV16-ALIFE prototypeThe functional prototype developed considers both external and internal perspectives. The functional logic applied in this implementation process is summarised in <a class="elsevierStyleCrossRef" href="#f0010">Fig. 2</a> and described below.<elsevierMultimedia ident="f0010"></elsevierMultimedia>For each of the perspectives, this model determines the properties of the global and local dynamics, respectively. The global dynamics make it possible to establish the properties of the external microenvironment. The local dynamics enable the properties of the internal microenvironment to be defined. Thus, the external microenvironment is affected by the HPV16 life cycle and the control of therapeutic vaccines. The internal microenvironment is affected by the set of cell populations, TLRs, and cytokines. Given these circumstances, the interactions between components are constructed. Initially, the interactions that arise between the HPV16 life cycle and the different cell populations are designed and later, the interactions are designed that allow the necessary activity to be induced in order to trigger connectivity signals that produce links between TLRs and cytokines. In this way, a feedback process is set up between the global parameters and the control parameters. Next, the interactions are defined that arise between the therapeutic vaccines to be evaluated and the different cell populations, TLRs, and cytokines. Thus, a feedback process is established between control parameters and global parameters.HPV16-ALIFE defines a specific logic to set the affinity maturation level, as well as to enable possible interactions between cell populations. This model defines 3 categories of affinity maturation level; i.e., low, medium, and high. Bearing in mind that somatic hypermutation is a largely stochastic process, this model controls affinity maturation by generating randomisation that distinguishes the three degrees of maturation previously referenced.Information provided by the HPV16-ALIFE prototypeThe HPV16-ALIFE model makes it possible to track the behaviour of all the components that define it, in such a way that it is possible to observe both the evolution of the process associated with HPV16 infection and the SIS response that originates in the human host. This information can be visualised through the GUI (<a class="elsevierStyleCrossRef" href="#f0015">Fig. 3</a>), which consists of a main monitor and 166 secondary monitors, together with 9 trend graphs. Such tools enable the model's behaviour to be evaluated and analysed at any point in time. The information contained in each of these tools is described below.<ul class="elsevierStyleList" id="l0010"><li class="elsevierStyleListItem" id="li0040">•1) Main monitor: Each of the incorporated cell populations has a unique visual representation that distinguishes them from other populations and makes it easier for the user to observe their motility. The populations differentiated in this model include: B cells, germinal centre B cells, short-lived plasma cells, short-lived memory B cells, long-lived plasma cells, long-lived memory B cells, antibodies, plasmacytoid DCs, T cells, natural killer cells, CD4+ T cells, CD8+ T cells, cytotoxic T lymphocytes, memory CD8 T cells, keratinocytes, follicular DCs, T-helper (Th) type 1, Th type 2, follicular Th, Th type 9, Th type 17, Th type 22, regulatory T cells, and M1-type macrophages.</li><li class="elsevierStyleListItem" id="li0045">•2) Viral protein status monitors: Eight monitors record the expression levels of each of the early (E1, E2, E4, E5, E6, and E7) and late (L1–L2) viral proteins.</li><li class="elsevierStyleListItem" id="li0050">•3) Transition status monitors: Ten monitors display the percentage of cells indicating infection, mutation, pre-malignancy, malignancy, neoplasia, CIN1, CIN2, CIN3, pre-cancer, and cancer status, respectively.</li><li class="elsevierStyleListItem" id="li0055">•4) Cytokine monitors: Seventeen monitors display the activity status of the cytokines TNF, TGF, IFN, and MIF, together with their receptors.</li><li class="elsevierStyleListItem" id="li0060">•5) Interleukin monitors: The activity status of interleukins together with their receptors are displayed on 77 monitors.</li><li class="elsevierStyleListItem" id="li0065">•6) Growth factor monitors: Six monitors exhibit that activity status of each of the growth factors that have been incorporated (EGF, EGFR, G-CSF, GM-CSF, M-CSF, and VEGF).</li><li class="elsevierStyleListItem" id="li0070">•7) Proapoptotic protein monitors: Eight monitors display the status of activity of each of the proapoptotic proteins integrated (BAX, BAD, BAK, BCL-XL, BIM, BID, Fas, and FasL).</li><li class="elsevierStyleListItem" id="li0075">•8) Antiapoptotic protein monitors: Two monitors reveal the activity status of the antiapoptotic proteins incorporated (BCL-2, and MCL-1).</li><li class="elsevierStyleListItem" id="li0080">•9) TLR signalling pathway monitors: The activity status of the components that assemble the TLR signalling pathways is displayed on 38 monitors.</li><li class="elsevierStyleListItem" id="li0085">•10) Cell population graphs: Three trend graphs report the behaviour of each of the incorporated cell populations.</li><li class="elsevierStyleListItem" id="li0090">•11) Antibody graph: This graph depicts the trend reported by the different antibody isotypes expressed during the simulation (IgM, IgG, IgA, IgG1, IgG2, IgG3, and IgG4).</li><li class="elsevierStyleListItem" id="li0095">•12) HPV16 infection graph: This graph shows the trend of groups of cells with respect to the presence of the virus, over the course of time. These groups include: cells that are not infected by the virus (HPV16-), cells that are positive for HPV16 infection (HPV16+), cells that reflect disease progression (CIN1, CIN2, and CIN3), and cells that exhibit risk conditions (pre-cancer and cancer).</li><li class="elsevierStyleListItem" id="li0100">•13) Tumour suppressor graph: This graph shows the trend, both in activity and inactivity, of the incorporated tumour suppressors (p53, pRb, p21, and Tert).</li><li class="elsevierStyleListItem" id="li0105">•14) Invasive cancer biomarkers graph: This graph plots the trend of potential biomarkers associated with the risk of developing invasive cancer and metastasis.</li><li class="elsevierStyleListItem" id="li0110">•15) Immunostimulatory cytokines graph: This chart illustrates the trend in the behaviour of cytokines that have been found to be involved in cancer biology and are classified as tumour suppressor cytokines. These cytokines induce cell-mediated immunity and anti-tumour responses, but their continued expression can also promote chronic inflammatory processes that can trigger neoplasia.</li><li class="elsevierStyleListItem" id="li0115">•16) Immunoinhibitory cytokine graph: This graph depicts the trend in the behaviour of cytokines that have been found to be involved in cancer biology and are classified as immunoinhibitory cytokines. These cytokines induce humoral immunity.</li></ul><elsevierMultimedia ident="f0015"></elsevierMultimedia>Although this model considers a greater number of variables than the ones on the GUI of the prototype developed, the display of such information is limited by the available display space on the computer screen used (monitor size: 21.5 in.), which prevents all the variables of the model built from being displayed. However, the prototype developed does make it possible to replace some of the established monitors with others that you may wish.Results<a class="elsevierStyleCrossRef" href="#f0020">Fig. 4</a> illustrates that when simulated patients do not receive a therapeutic vaccine, the lesions caused by HPV16 tend to manifest the highest levels (see the dark blue trend line corresponding to EXP-1). However, when patients are treated with a therapeutic vaccine, the severity of the various HPV16 lesions decreases significantly (see trend lines for experiments EXP-2, EXP-3, EXP-4, EXP-5, EXP-6, and EXP-7). These results reveal that the therapeutic vaccines used in the experiments conducted are able to significantly control the cancer (<a class="elsevierStyleCrossRef" href="#f0020">Fig. 4</a> A), with even better results than in lesions that display lesser severity (<a class="elsevierStyleCrossRef" href="#f0020">Fig. 4</a> B–E).<elsevierMultimedia ident="f0020"></elsevierMultimedia><a class="elsevierStyleCrossRef" href="#f0025">Fig. 5</a> depicts that when simulated patients do not receive a therapeutic vaccine, the expression levels of the viral oncoproteins E6 (<a class="elsevierStyleCrossRef" href="#f0025">Fig. 5</a> C) and E7 (<a class="elsevierStyleCrossRef" href="#f0025">Fig. 5</a> D) tend to increase (see the dark blue trend line corresponding to EXP-1). In contrast, when a therapeutic vaccine is administered, the expression levels of these oncoproteins show a significant decrease (see trend lines for experiments EXP-2, EXP-3, EXP-4, EXP-5, EXP-6, and EXP-7).<elsevierMultimedia ident="f0025"></elsevierMultimedia>Furthermore, in all cases where a therapeutic vaccine was administered, the levels of proliferation of the CTL population (<a class="elsevierStyleCrossRef" href="#f0025">Fig. 5</a> B) tend to increase, as does the secretion of the cytokine IL-12 (<a class="elsevierStyleCrossRef" href="#f0025">Fig. 5</a> A). Both behaviours are indicative of a successful SIS response to the intervention of the therapeutic vaccines tested in this model.<a class="elsevierStyleCrossRef" href="#f0025">Fig. 5</a> A shows the IL-12 cytokine secretion levels reported in response to the challenge posed by each of the vaccination strategies tested in HPV16-ALIFE (EXP-2, EXP-3, EXP-4, EXP-5, EXP-6, and EXP-7). Of the seven types of experiments performed, type 4 (non-adjuvanted vaccine with DC load = 1000 μg/mL) yields the highest levels of secretion, and the type 1 experiment (EXP-1: no vaccine), the lowest levels of IL-12.<a class="elsevierStyleCrossRef" href="#f0025">Fig. 5</a> B demonstrates the behaviour of CTL population proliferation in response to each of the treatment strategies tested in HPV16-ALIFE (EXP-2, EXP-3, EXP-4, EXP-5, EXP-6, and EXP-7), which involve the delivery of a therapeutic vaccine to the virtual host. Of the 6 classes of experiments performed with a vaccine, experiment type 6 (EXP-6: vaccine with DC load = 10 μg/mL and Poly I:C adjuvant as TLR3 ligand) had the highest levels of cell proliferation in this population, while experiment type-5 (EXP-5: vaccine with DC load = 10 μg/mL and IL-2 adjuvant) had the lowest levels. Nevertheless, in all experiments involving the delivery of DC vaccines, increased levels of proliferation of the CTL population are observed.<a class="elsevierStyleCrossRef" href="#f0025">Figs. 5</a> C and D outline the behaviour of the expression of the HPV16 viral proteins E6 and E7, respectively, in this model for each of the experiments performed (EXP-1, EXP-2, EXP-3, EXP-4, EXP-5, EXP-6, and EXP-7). The highest expression levels of both E6 and E7 proteins are found in EXP-1; i.e., when the host does not receive a vaccine. In the other experiments, which involve the delivery of a DC vaccine, the expression levels of these proteins fall substantially.<a class="elsevierStyleCrossRef" href="#f0030">Fig. 6</a> represents the behaviour of the CTL population proliferation levels when challenged by the therapeutic adjuvanted vaccines simulated in the prototype developed. All the adjuvanted vaccines evaluated use the same DC load but different adjuvant. This figure also shows the trend that results when applying 1, 2, or 3 doses of the vaccine under evaluation, as established by the model according to the conditions of the simulated microenvironment.<elsevierMultimedia ident="f0030"></elsevierMultimedia>During the phase I experiments and when IL-2 was used as the adjuvant, this model applied a maximum of the 3 doses that were programmed at the start of the simulation. The highest level of CTL proliferation was observed when the host received all 3 doses. In both phase II and phase III, this model delivered a maximum of 2 of the 3 initially scheduled doses. When a TLR3 agonist was used as an adjuvant in phase i, this model only administered 2 of the 3 doses programmed. In phase II, this model delivered exactly 1 or 3, but never 2 doses. In phase III, this model administered a maximum of 3 doses. When a TLR9 agonist was used as an adjuvant, in all 3 phases of experiments carried out, a maximum of the 3 scheduled doses of the therapeutic vaccine under evaluation were applied. The highest level of proliferation of the CTL population was noted in the phase III experiments, particularly when the model delivered all three doses of the vaccine. Comparing the CTL population proliferation induced by the vaccines with the 3 types of adjuvants tested in this model, the TLR9 agonist (CpG) was found to induce the greatest proliferation on average; the TLR3 agonist (Poly I:C) induced the second highest level of proliferation, and IL-2, the third highest level of proliferation.Halloran et al.<a class="elsevierStyleCrossRef" href="#bb0095">19</a> define vaccine efficacy by disease susceptibility as the ratio of the relative risk of infection or disease in vaccinated individuals compared to unvaccinated individuals. Drawing on these concepts and using the data generated by each of the experiments run on the HPV16-ALIFE prototype, the rates are calculated for each of the 3 phases and for each type of lesion (CIN1, CIN2, CIN3, pre-cancer, and cancer).<a class="elsevierStyleCrossRef" href="#f0035">Fig. 7</a> A and B plot the trend in efficacy for the therapeutic vaccines tested without and with adjuvant, respectively, observed in the simulations performed. These graphs show the trend of the virtual patient group receiving the specific vaccine type in each of the phases, although the number of doses delivered in each case is not shown. Therefore, this data is provided in the corresponding analysis.<elsevierMultimedia ident="f0035"></elsevierMultimedia>Among the experiments performed with non-adjuvanted vaccines, in which the DC load varied between 10, 100, and 1000 μg/mL, in cancer conditions, the vaccine that reported the best average efficacy rate (97.16%) was the one with the DC load = 1000 μg/mL. Under pre-cancer conditions, the vaccine having the best average efficacy rate (74.83%) is the one with the DC load = 100 μg/mL. For CIN3 lesions, the vaccine reporting the best average efficacy rate (55.48%) corresponds to the vaccine with the DC load = 100 μg/mL.Considering the experiments performed with adjuvanted therapeutic vaccines, in which the DC load was kept constant at 10 μg/mL and the adjuvant varied, under cancer conditions, the vaccine with the best average efficacy rate (97.77%) was the one using IL-2 as adjuvant. In a scenario of pre-cancer, the vaccine with the best average efficacy rate (77.43%) was the one using IL-2 as the adjuvant. In CIN3 lesions, the vaccine with the best average efficacy (53.44%) was the one that used TLR9 as adjuvant.Analysing the data by each type of vaccine tested in the prototype, the most significant rate observed in cancer and pre-cancer conditions corresponded to the therapeutic vaccine using IL-2 as adjuvant. In contrast, the most significant rate observed in CIN3 lesions corresponded to the non-adjuvanted vaccines.When patients did not receive therapeutic vaccines (EXP-1), cervical cancer rates peaked at 18.86%. In contrast, when patients received any vaccination strategy (EXP-2, EXP-3, EXP-4, EXP-5, EXP-6, and EXP-7), cervical cancer rates fell significantly, reaching maximum rates between 0.48% and 3.12%, which varied depending on the specifics associated with each therapeutic vaccine being evaluated.In summary, among the “adjuvanted” therapeutic vaccines evaluated, the one that proved most effective in controlling cervical cancer was the one that included IL-2 as adjuvant. Of the “non-adjuvanted” therapeutic vaccines evaluated, the one that proved to be most effective in controlling the cervical cancer condition was the one that used the highest DC load. With our model, other events also became evident when the cancer was active. These events included: increased secretion of the IL-12 cytokine, greater proliferation of the CTL population, and declines in the expression levels of the viral oncoproteins E6 and E7. All of these phenomena occurred as a consequence of the effects mediated by therapeutic vaccines of autogenous DC loaded with E6/E7 antigens.DiscussionTo date, no other computational model has simulated interactions such as those proposed by HPV16-ALIFE with its three domains, making it difficult to compare our results with other computational works. We have therefore relied on specific clinical trials with real-world patients, in an attempt to compare the behaviour of individually observed components, inasmuch as we have not found a trial that can simultaneously evaluate all the components that integrate this model. However, this work is complex due to the same circumstances that other authors have already mentioned. Basically, comparing the results of several clinical studies is challenging, taking into account that they are conducted under differing characteristics of performance, sensitivity, and cut-off points, as well as differences in study design, definitions of seropositivity, analysis strategies,<a class="elsevierStyleCrossRef" href="#bb0100">20</a> and length of follow-up. Consequently, any comparison of the results obtained using our model against selected real clinical trials can only be made at the trend level.This means that we have focused on assessing the emerging behaviour of specific elements of the model that may be affected when mediated by a viral infection and/or a specific cancer treatment. We compared these emergent behaviours with the results of other authors that were obtained from clinical trials with living patients.Therefore, and in line with what has been explained in the results section, we analysed the trends observed in the simulations performed in HPV16-ALIFE with regard to the secretion of the cytokine IL-12, expression of the viral oncoproteins E6 and E7, the behaviour of the CTL population, and the efficacy of the simulated therapeutic vaccines. Finally, this information enabled us to discuss the results obtained from experiments applied to our prototype in comparison to those obtained from certain studies with groups of patients treated in real life.Discussion of the results observed in the artificial life model versus real-world clinical studies.The experiments performed in HPV16-ALIFE made it possible to simulate patients with the disease who did not receive vaccines, patients with the disease who received therapeutic vaccines without adjuvants, and patients with the disease who received therapeutic vaccines with adjuvants. Analyses of the results obtained provided us with trends consistent with some real-world clinical studies.The following clinical trials whose trend of results coincides with ours, were conducted by: (1) Rainone et al.<a class="elsevierStyleCrossRef" href="#bb0105">21</a> and Wang et al.,<a class="elsevierStyleCrossRef" href="#bb0110">22</a> regarding the behaviour of IL-12; (2) Wu et al.<a class="elsevierStyleCrossRef" href="#bb0115">23</a> and the trend observed in E6 and E7 protein expression levels, the increase in CTL population, and the specific protective immunity triggered against cervical cancer cells; (3) Chan et al.<a class="elsevierStyleCrossRef" href="#bb0120">24</a> and the behaviour of a TLR9 agonist; (4) Wick and Webb<a class="elsevierStyleCrossRef" href="#bb0125">25</a> and the behaviours of a TLR3 agonist and a TLR9 agonist, and (5) Lin et al.<a class="elsevierStyleCrossRef" href="#bb0130">26</a> and the evaluation of the performance of an IL-2 adjuvant.In their study, Rainone et al.<a class="elsevierStyleCrossRef" href="#bb0105">21</a> report that administration of antigen-loaded DC evoked a strong anti-tumour response in vivo, as demonstrated by a general activation of immunocompetent cells and release of Th1 cytokines. IL-12 and IFN-γ secretion was significantly increased in T cells co-cultured with antigen-loaded DCs compared to T cells co-cultured with unloaded DCs. Data from this study illustrate a specific activation of the immune system against breast cancer. The results in HPV16-ALIFE also demonstrated specific activation of the immune system against cervical cancer.Wang et al.<a class="elsevierStyleCrossRef" href="#bb0110">22</a> evaluate the immunotherapeutic potential of human DC loaded with HPV16-associated antigens. The results of this study demonstrated anti-tumour activity, in particular with respect to IL-12 upregulation and increased CTL population activity, following treatment with antigen-loaded DCs. DC loaded with HPV16 antigens report significant anti-tumour immunity in patients with cervical cancer. The results observed in HPV16-ALIFE indicate that treatment with autogenous DCs loaded with HPV16 E6/E7 antigens induces an immune response in patients with cervical cancer, which can be seen in the upregulation of IL-12, increased CTL activity, and a decrease in the cancer cell population.Meanwhile, in their study, Wu et al.<a class="elsevierStyleCrossRef" href="#bb0115">23</a> show that an HPV16 E6/E7 gene-modified DC vaccine can induce apoptosis of cancer cells by inducing CTL. The results observed in HPV16-ALIFE also reveal that following treatment with autogenous DC loaded with HPV16 E6/E7 antigens, there is a proliferation of CTL; this population, in turn, promotes apoptosis in cancer cells.In their study, Chang et al.<a class="elsevierStyleCrossRef" href="#bb0120">24</a> report that a TLR9 agonist (specifically CpG) enhances CTL responses and eradicates large tumours. The remarkable anti-tumour effects of recombinant lipoprotein E7 (rlipo-E7m) and CpG-ODN reflect the amplification of CTL responses and suppression of the tumour environment. The results observed in HPV16-ALIFE illustrate that autogenous DC vaccination with CpG (TLR9 ligand) adjuvant induces anti-tumour responses through the induction of antigen-specific CD8+ T cells and their subsequent differentiation into CTLs, which then participate in cancer cell reduction.Wick and Webb<a class="elsevierStyleCrossRef" href="#bb0125">25</a> evaluated a vaccine called Pentarix, based on a recombinant fusion protein containing E7 oncoproteins from 5 high-risk HPV genotypes. Among the genotypes studied, HPV16 is included together with a TLR3 agonist (Poly I:C) or a TLR9 agonist (CpG), to be delivered to mice in an immunisation strategy. This study demonstrates that the vaccine is able to elicit strong CD8 T-cell responses against the E7 antigen using the recombinant protein in combination with the TLR3 agonist (Poly I:C) or TLR9 agonist (CpG). The results attained in this study are consistent with the trends observed in the HPV16-ALIFE simulations.The objective as proposed by Lin et al.<a class="elsevierStyleCrossRef" href="#bb0130">26</a> in their study was to determine whether the potency of the DNA vaccine encoding the HPV16 E7 antigen can be enhanced by IL-2. They conclude that the link between IL-2 and the HPV16 E7 antigen significantly improves the potency of the DNA vaccine against E7-expressing tumours. The results observed in HPV16-ALIFE demonstrate that the highest rate of cancer and pre-cancer control is reported in autogenous DC vaccines loaded with E6/E7 antigens using IL-2 adjuvant.ConclusionsThe behaviours observed in this model reveal that the SIS responds to its constituent microenvironments, which are induced by the interactions between the immune system, the HPV16 life cycle, and the therapeutic vaccines. All therapeutic vaccines simulated in HPV16-ALIFE proved that the SIS has the ability to respond to them.This work shows that despite some gaps reported in the literature (e.g., identifying the cause of spontaneous regression in HPV or the mechanism by which plasma cells localise to the bone marrow, among others, are still unknown events), it is possible to simulate the behaviours of the 3 proposed domains in a single model, including: (1) components involved in the immune system; (2) responses that this system triggers against a persistent infection caused by HPV16 (which can induce cervical cancer), and (c) therapeutic vaccine strategies that seek to eradicate the disease. By linking all these components within the HPV16-ALIFE model through rules, interactions, checkpoints, states, and transitions, it becomes possible to simulate known actions and evaluate the emergence of patterns of behaviour. This model also has the capacity to stimulate and/or block critical points and induce the upregulation of specific cell populations. Based on this, HPV16-ALIFE offers the possibility of observing behaviours arising from these interactions, generated in an artificial life world, where the biases identified in animal models can probably be mitigated, and testing and primary evaluation times can be reduced.Despite the fact that issues related to the immune system and the HPV16 life cycle have yet to be clarified, the HPV16-ALIFE model allows us to observe this interaction and simulate test experiments that help to generate an initial approximation of the possible resulting behaviours, particularly in scenarios in which therapeutic vaccines are involved. Despite the fact that the previously documented tests recommend the use of autogenous DC therapeutic vaccines, this model enables us to propose other types of therapeutic vaccines, such as anti-PD1, and also to define the combined activation and inactivation states of some components that are part of the cytokine and TLR signalling pathways.The scope of the present work does not address establishing the effectiveness of the types of therapeutic vaccines used in the experiments tested. However, the results obtained do enable us to establish the type of vaccine that, at the individual and group levels, prove to be most effective for the model in controlling lesions arising from HPV16 infection, taking into account the conditions of the simulated microenvironment. This does not imply that the vaccine rated best in this model will prove to be equally effective in the real world. However, given the similarity observed between the trend reported by the simulated immune response and the real-world trials, it is possible to propose a different order of evaluation. This can be interpreted as a new evaluation guide when planning different trials to be applied to other models, whether virtual, animal, or human. Still, it must be tested in the real world. While the order of vaccine efficacy proposed by this model might serve as a guide, testing it in the real world is beyond the scope of this paper.Overall, the virtual experiments conducted with the HPV16-ALIFE model have shown a SIS that has reacted under both circumstances: when an infectious process caused by HPV16 is mediated and when a therapeutic vaccine is used as a treatment strategy. Notably, the responses observed in this model vary from experiment to experiment depending on the load, dose, frequency, and adjuvants used in each simulation. By evaluating the behaviour observed in our model in comparison with some previously reported clinical studies,<a class="elsevierStyleCrossRefs" href="#bb0105">21–26</a> it is apparent that HPV16-ALIFE generates behaviours similar to those reported by those authors in their real-life studies.FundingThere is no funding body nor has any grant been received.Conflict of InterestsThe author has no conflict of interests to declare." "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1851289" "titulo" => "Abstract" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "as0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "as0010" "titulo" => "Materials and methods" ] 2 => array:2 [ "identificador" => "as0015" "titulo" => "Results and conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1609735" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1851290" "titulo" => "Resumen" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "as0020" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "as0025" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "as0030" "titulo" => "Resultados y conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1609734" "titulo" => "Palabras Clave" ] 4 => array:2 [ "identificador" => "s0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "s0010" "titulo" => "Materials and methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "s0015" "titulo" => "Model validation" ] 1 => array:2 [ "identificador" => "s0020" "titulo" => "Data analysis" ] 2 => array:2 [ "identificador" => "s0025" "titulo" => "Functional logic implemented in the HPV16-ALIFE prototype" ] 3 => array:2 [ "identificador" => "s0030" "titulo" => "Information provided by the HPV16-ALIFE prototype" ] ] ] 6 => array:2 [ "identificador" => "s0035" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "s0040" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "s0045" "titulo" => "Conclusions" ] 9 => array:2 [ "identificador" => "s0050" "titulo" => "Funding" ] 10 => array:2 [ "identificador" => "s0055" "titulo" => "Conflict of Interests" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1609735" "palabras" => array:6 [ 0 => "Artificial life" 1 => "Artificial immune system" 2 => "Cervical cancer" 3 => "HPV16" 4 => "Simulation prototype" 5 => "Therapeutic vaccine" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras Clave" "identificador" => "xpalclavsec1609734" "palabras" => array:6 [ 0 => "Vida artificial" 1 => "sistema inmune artificial" 2 => "cáncer cérvix" 3 => "HPV16" 4 => "prototipo simulación" 5 => "vacuna terapéutica" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "ObjectiveTo evaluate the artificial life model that simulates behaviours based on interactions occurring between the human immune system, the life cycle of human papillomavirus type 16, and certain types of therapeutic vaccines through virtual experiments on the constructed prototype. Materials and methodsWe developed the HPV16-ALIFE prototype using artificial life techniques to be used as a virtual laboratory. To evaluate the model, we analysed the responses of the simulated immune system under two circumstances: when a persistent infection is present that originates from HPV16 and causes lesions, and when the nanodevice releases a dose as part of a therapeutic vaccination strategy. Performing virtual trials means we can produce results for subsequent analysis and comparison with real-world clinical data. Results and conclusionsThe simulations enabled us to observe the proliferation of different cell populations considered in the model, levels of viral protein expression and cytokine secretion, transition stages of the developing infectious process-, low- and high-grade intraepithelial lesions, pre-cancer, and cancer status. The virtual patients who did not receive vaccines developed cancer status with peak rates of 18.86%. The patients who received a vaccination strategy reported a significant decrease in their cancer status, with peak rates varying between 0.48% and 3.12%, according to the specifications associated with each vaccine evaluated. The simulated immune system proved responsive to the activity of the virus and the vaccine." "secciones" => array:3 [ 0 => array:2 [ "identificador" => "as0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "as0010" "titulo" => "Materials and methods" ] 2 => array:2 [ "identificador" => "as0015" "titulo" => "Results and conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "ObjetivoEvaluar el modelo de vida artificial que simula comportamientos basados en interacciones que emergen entre el sistema inmune humano, ciclo de vida del virus de papiloma humano tipo 16 y algunos tipos de vacunas terapéuticas, a través de experimentos virtuales que se corren sobre el prototipo construido. Materiales y métodosBajo técnicas de vida artificial desarrollamos el prototipo HPV16-ALIFE para ser utilizado como laboratorio virtual. Para evaluar el modelo, analizamos las respuestas del sistema inmune simulado en ambas circunstancias: cuando se presenta una infección persistente que se origina en HPV16 y causa lesiones, y cuando el nanodispositivo libera una dosis que hace parte de una estrategia de vacunación terapéutica. La ejecución de ensayos virtuales permite producir resultados para su posterior análisis y confrontación con datos clínicos del mundo real. Resultados y conclusionesLas simulaciones realizadas permitieron observar la proliferación de diferentes poblaciones celulares consideradas en el modelo, niveles de expresión de proteínas virales y secreción de citoquinas, estados de transición del proceso infeccioso en desarrollo, lesiones intraepiteliales de bajo y alto grado, condiciones de pre-cáncer y cáncer. Pacientes virtuales que no recibieron vacunas, desarrollaron condiciones de cáncer con tasas máximas de 18.86%. Pacientes que recibieron alguna estrategia de vacunación, reportaron un descenso significativo en su condición de cáncer, con tasas máximas que variaron entre 0.48% y 3.12%, según las especificaciones asociadas a cada vacuna en evaluación. El sistema inmune simulado mostró tener capacidad de respuesta ante la actividad del virus y la vacuna." "secciones" => array:3 [ 0 => array:2 [ "identificador" => "as0020" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "as0025" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "as0030" "titulo" => "Resultados y conclusiones" ] ] ] ] "multimedia" => array:7 [ 0 => array:8 [ "identificador" => "f0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1261 "Ancho" => 1660 "Tamanyo" => 265746 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "al0005" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Diagram of the experimental design of the HPV16-ALIFE prototype. This diagram represents the set of experiments run on the prototype developed. The simulated patients are confirmed HPV16 positive cases who do not report any other concomitant viral infection. Among the experiments performed, some patients receive vaccines and others do not. In the group of patients who are given vaccines, some of them receive non-adjuvanted vaccines (left side) while others receive adjuvanted vaccines (right side). Each rectangle in the diagram represents a type of experiment and the corresponding text states the particular load and the specific adjuvant that are simulated. The figure on the lower left-hand side represents the three phases scheduled to run. The green-coloured ovals represent the number of trials to be performed in phase I. The purple ovals indicate the number of tests to be performed in phase II. The orange-coloured ovals correspond to the number of tests conducted in phase iii. On the right side of the figure, the ellipses above the rectangles correspond to the total number of experiments performed, and the associated colour represents the phase in which these experiments are performed. DC: dendritic cells. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)" ] ] 1 => array:8 [ "identificador" => "f0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1193 "Ancho" => 1654 "Tamanyo" => 189412 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "al0010" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Functional logic implemented in the HPV16-ALIFE prototype. The figure summarises the logic with which the functional prototype of this model was developed. In the first instance, the exchange relationships between the various domains of the model can be seen. In the second instance, the key interactions are established that allow the definition of an appropriate feedback process between the components and the parameters (global and control). The left side of the figure represents the external perspective of the model and the right side, the internal perspective. The arrows determine the direction of the interactions that emerge between domains. The green arrows indicate that the interactions originate in the HPV16 life cycle. The yellow arrows indicate interactions that arise from therapeutic vaccines. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)" ] ] 2 => array:8 [ "identificador" => "f0015" "etiqueta" => "Fig. 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1029 "Ancho" => 1900 "Tamanyo" => 482896 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "al0015" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Graphical user interface (GUI) of the HPV16-ALIFE prototype. This image shows the standard GUI of the HPV16-ALIFE prototype on which the user can set the initial parameters and observe the evolution of its components during the simulation. A set of sliders and switches are available that allow the user to set the initial conditions prior to starting a simulation or during its execution. These criteria include: size of the initial progenitor cell population, previous state of the cells (healthy or infected), preliminary infection (chronic or acute), and certain vaccine specifications (load, dose, frequency, and adjuvants). The evolution of the simulation can be observed on a main monitor, 166 secondary monitors, and 9 trend graphs. In addition, there is a command centre area (bottom left of the image), where the model reports the week in which a vaccine dose is actually delivered." ] ] 3 => array:8 [ "identificador" => "f0020" "etiqueta" => "Fig. 4" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr4.jpeg" "Alto" => 2353 "Ancho" => 1908 "Tamanyo" => 408823 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "al0020" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Trend observed in the lesions provoked by the virus in each of the experimental conditions. The graphs illustrate the behaviour of the different lesions caused by HPV16, comparing the trend observed in the lesion with each of the experiments carried out. (A) Trend in cancer conditions. (B) Trend in pre-cancer conditions. (C) Trend in CIN1 lesions. (D) Trend in CIN2 lesions. (E) Trend in CIN3 lesions. EXP-1: trend in patients not receiving vaccine; EXP-2: trend in patients receiving therapeutic vaccine with dendritic cells (DC) = 10 μg/mL; EXP-3: trend in patients receiving therapeutic vaccine DC = 100 μg/mL; EXP-4: trend in patients receiving therapeutic vaccine DC = 1000 μg/mL; EXP-5: trend in patients receiving therapeutic vaccine DC = 10 μg/mL with IL-2 adjuvant; EXP-6: trend in patients receiving therapeutic vaccine DC = 10 μg/mL with Poly I:C adjuvant as TLR3 ligand; EXP-7: trend in patients receiving therapeutic vaccine DC = 10 μg/mL with CpG adjuvant as TLR9 ligand." ] ] 4 => array:8 [ "identificador" => "f0025" "etiqueta" => "Fig. 5" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr5.jpeg" "Alto" => 1500 "Ancho" => 2008 "Tamanyo" => 298679 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "al0025" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Comparison of trends observed between experiments on IL-12 cytokine, cytotoxic T lymphocyte (CTL) population, and E6 and E7 viral oncoproteins. The graphs display the behaviour of IL-12 cytokine secretion, E6 and E7 viral oncoprotein expression, and CTL population proliferation in conditions of persistent infection caused by HPV16, comparing the trend in evaluation against each of the experiments performed. (A) Trend in IL-12 secretion. (B) Trend in CTL population proliferation. (C) Trend levels of viral E6 oncoprotein expression. (D) Trend in viral oncoprotein E7 expression. EXP-1: trend in patients not receiving vaccine; EXP-2: trend in patients receiving therapeutic vaccine with dendritic cells (DC) = 10 μg/mL; EXP-3: trend in patients receiving therapeutic vaccine DC = 100 μg/mL; EXP-4: trend in patients receiving therapeutic vaccine DC = 1000 μg/mL; EXP-5: trend in patients receiving therapeutic vaccine DC = 10 μg/mL with adjuvant IL-2; EXP-6: trend in patients receiving therapeutic vaccine DC = 10 μg/mL with adjuvant Poly I:C as TLR3 ligand; EXP-7: trend in patients receiving therapeutic vaccine DC = 10 μg/mL with adjuvant." ] ] 5 => array:8 [ "identificador" => "f0030" "etiqueta" => "Fig. 6" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr6.jpeg" "Alto" => 1245 "Ancho" => 1654 "Tamanyo" => 188983 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "al0030" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Proliferation of cytotoxic T lymphocytes (CTL) from adjuvanted vaccines observed in the HPV16-ALIFE prototype. The blue line corresponds to the trend in phase I experiments (viral proteins in active state). The red line depicts the trend of phase II experiments (E7 protein in inactive state). The green line represents the trend of phase III experiments (E6 protein in an inactive state). At the bottom of the graph, each of the adjuvants tested (IL-2, Poly I:C as TLR3 ligand, CpG as TLR9 ligand) and the maximum number of doses actually applied by the model (1, 2 or 3 doses), according to the conditions of its environment, are indicated. DC: dendritic cells. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)" ] ] 6 => array:8 [ "identificador" => "f0035" "etiqueta" => "Fig. 7" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr7.jpeg" "Alto" => 2393 "Ancho" => 1571 "Tamanyo" => 473795 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "al0035" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Efficacy analyses of adjuvanted and non-adjuvanted vaccines tested in the HPV16-ALIFE prototype. The figure presents a comparison of the effect observed on the different lesions caused by HPV16 infection (CIN1, CIN2, CIN3, pre-cancer, and cancer) in the experiments run during the 3 planned phases. (A) The trend observed in the therapeutic vaccine experiments without adjuvants, with dendritic cell (DC) loads of 10, 100, and 1000 μg/mL. (B) The trend seen in the therapeutic vaccine experiments with adjuvant, with DC load of 10 μg/mL, with which 3 different adjuvants were tested: IL-2, Poly I:C as TLR3 ligand, and CpG as TLR9 ligand. The blue lines indicate the trend observed in CIN1 lesions. The yellow lines reflect the trend observed in CIN2 lesions. Green lines correspond to CIN3 lesions. The purple lines reflect the pre-cancer stage. The red lines depict the trend observed in cancer conditions. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bs0005" "bibliografiaReferencia" => array:26 [ 0 => array:3 [ "identificador" => "bb0005" "etiqueta" => "1." 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Evaluation of a prototype artificial life model to simulate the interactions between the human immune system, human papillomavirus type 16 and therapeutic vaccines

Evaluación de un prototipo de modelo de vida artificial para simular interacciones entre el sistema inmune humano, el virus del papiloma humano tipo 16 y vacunas terapéuticas

M.E. Escobar-Ospina

Corresponding author

meescobaro@unal.edu.co

Corresponding author.

Departamento de Ingeniería-Sistemas y Computación, Universidad Nacional, Bogotá, Colombia

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medium-&#44; and long term&#44; and thereby consider an alternative approach to define the most efficient treatment possible given the simulated conditions&#46;</p></span><span id="s0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0060">Materials and methods</span><p id="p0010" class="elsevierStylePara elsevierViewall">HPV16-ALIFE belongs to the class of artificial life models and its design is based on agent-based modelling and cellular automata&#46; This model integrates the simulation of the human immune system&#44; the HPV16 life cycle &#40;detailed in our previous article<a class="elsevierStyleCrossRef" href="#bb0005"><span class="elsevierStyleSup">1</span></a>&#41; and the effects caused by the challenge posed by certain therapeutic vaccines that seek to control lesions caused by the presence of this virus&#46; The corresponding prototype has been developed with the NetLogo 5&#46;3<a class="elsevierStyleCrossRef" href="#bb0010"><span class="elsevierStyleSup">2</span></a> programming tool&#44; given that it enables complex environments to be modelled in order to simulate biological and social phenomena that are useful to support current biomedical research&#46; Because of its extension&#44; the description of the conceptualisation and the process of creating the artificial life model as such is part of a previous article&#46;</p><p id="p0015" class="elsevierStylePara elsevierViewall">Simulation of experiments on the prototype can address both the evaluation of a therapeutic vaccine and the assessment of a drug treatment&#44; either independently or simultaneously&#46; Drug simulation involves activating or blocking one or more components associated with cytokines and Toll-like receptors &#40;TLRs&#41;&#46; Evaluating new therapeutic vaccines involves defining the desired specifications in terms of load&#44; dose&#44; and frequency of administration&#46; It also implies activating certain components that will act as adjuvants&#44; only when necessary&#46;</p><p id="p0020" class="elsevierStylePara elsevierViewall">Based on the theories of complex systems and biological systems&#44; and making use of artificial life tools&#44; we have simulated the processes of this model based on the biological knowledge currently available&#46; In this way&#44; we have endeavoured to prevent the user from defining biased rules or generating conditions on the basis of their own prejudices or from including parameters that may be convenient from the computational point of view or from the experimental point of view&#46;</p><span id="s0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0065">Model validation</span><p id="p0025" class="elsevierStylePara elsevierViewall">The prototype developed contemplates 3 options to treat the patient&#39;s lesions&#58; &#40;1&#41; delivery of a therapeutic vaccine&#44; &#40;2&#41; delivery of blocking drugs&#44; and &#40;3&#41; delivery system with immune checkpoint therapy against cancer&#44; specifically the PD-1&#47;PD-L1 axis&#46; While the model can simulate these 3 treatment scenarios&#44; given the space constraints in the publication&#44; in this article we will concentrate on showcasing the tests performed with the first option&#46;</p><p id="p0030" class="elsevierStylePara elsevierViewall">In order to evaluate the behaviour of this model and determine whether the finite nature of the simulation affects the results&#44; some virtual tests have been run as an example&#44; varying certain parameters according to the rules of the experiment&#46; The aim of the proposed experiments is to observe the effect caused by the administration of a virtual therapeutic vaccine when there is a lesion stemming from persistent HPV16 infection&#46; Similarly&#44; it also seeks to demonstrate the responses produced by the simulated immune system &#40;SIS&#41;&#46; Therefore&#44; groups of patients with persistent infection have been compared between those who do not receive treatment and those who are treated with therapeutic vaccines&#46; In addition&#44; the objective is to observe the conditions under which the therapeutic vaccine is more effective&#44; which is why we have compared groups of patients with persistent infection&#44; between those who receive a non-adjuvanted therapeutic vaccine and those who receive an adjuvanted therapeutic vaccine&#46; In the latter group&#44; 3 different kinds of adjuvants are evaluated with the purpose of observing how the effectiveness of the vaccine might vary with each&#46; <a class="elsevierStyleCrossRef" href="#f0005">Fig&#46; 1</a> illustrates the diagram of the corresponding experimental design&#46;</p><elsevierMultimedia ident="f0005"></elsevierMultimedia><p id="p0035" class="elsevierStylePara elsevierViewall">The virtual trials performed on the HPV16-ALIFE prototype are based on the conditions detailed below&#44; and within the proposed experimental context&#44; the terms specifically defined will be understood as having the following connotation&#58;</p><p id="p0040" class="elsevierStylePara elsevierViewall">&#40;a&#41; Simulated patient&#58; This term refers to the set of virtual components that represent the human immune system&#44; including the effects resulting from its interaction with the HPV16 life cycle&#44; as well as the events triggered by the release of doses of a therapeutic vaccine&#46; A simulation running on the prototype makes it possible to observe how the infectious viral process experienced by a virtual patient evolves&#46; Each of the simulations performed is followed for a pre-specified time of evolution&#59; in this case in particular&#44; it begins at week 1 and ends at week 1400&#46; The corresponding data are displayed on the graphical user interface &#40;GUI&#41;&#44; in real time&#44; on several monitors and trend graphs&#46;</p><p id="p0045" class="elsevierStylePara elsevierViewall">It should be noted that this model allows the number of weeks during which a patient can evolve to be varied &#40;this number will be determined by the end user&#41;&#46; However&#44; in the trials documented in this article&#44; we worked with exactly 1400&#8239;weeks for all the simulated patients&#46; The purpose of this is to be able to compare the results across patients and observe what happens to each of them over a period of 26 continuous years&#44; counting from the first exposure to the virus&#46; Within this period of time&#44; several scenarios can be presented&#44; taking into account that the lesions could progress and become evident 10&#8239;years after the first infection or be eliminated by the immune system after a period of time of up to 4 years&#46;</p><p id="p0050" class="elsevierStylePara elsevierViewall">b&#41; Sham therapeutic vaccine&#58; This term applies to a given quantity of virtual autogenous dendritic cells &#40;DC&#41;&#44; loaded with E6&#47;E7 antigens&#44; which are administered to the sham patient&#46; The delivery is performed through a virtual nanodevice&#44; which releases and delivers each dose to the patient&#44; assessing the proper timing and the maximum number of doses established by the model&#44; in accordance with the conditions that emerge from the microenvironment&#46; Considering the frequency and the maximum number of doses previously established in each type of experiment&#44; the model will be able to administer the amount of doses equal to or less than the predetermined parameters&#46; The decision taken by the model will depend on the characteristics reported by the simulated environment&#44; and will halt delivery when the markers indicate that the lesions have been eliminated or when the maximum dosing limit determined by the researcher has been reached&#46; In this model&#44; the simulated therapeutic vaccine does not consider toxicity levels&#44; route of administration&#44; or adverse events resulting from its administration&#46;</p><p id="p0055" class="elsevierStylePara elsevierViewall">c&#41; It is assumed that the patients participating in each experiment correspond to confirmed cases of HPV16<span class="elsevierStyleHsp" style=""></span>&#43;&#44; women who are sexually active&#44; and who do not report any other simultaneous viral infection&#46;</p><p id="p0060" class="elsevierStylePara elsevierViewall">d&#41; The proposed experimental design is intended to observe the behaviours associated with viral oncoproteins E6 and E7&#44; interleukin-12 &#40;IL-12&#41;&#44; and the cytotoxic T-lymphocyte &#40;CTL&#41; population&#46; Some of the reasons for this selection stem from the following facts&#58; &#40;<span class="elsevierStyleItalic">d1</span>&#41; cervical cancers express E6 and E7 proteins&#59; their levels of expression induce activation of centrosome duplication and abnormal centrosome accumulation&#44; and these processes that are active during carcinogenesis are associated with high-risk HPVs<a class="elsevierStyleCrossRef" href="#bb0015"><span class="elsevierStyleSup">3</span></a>&#59; <span class="elsevierStyleItalic">d2</span>&#41; IL-12 is an antitumor and antiviral cytokine&#44; which not only inhibits tumour cell proliferation&#44; but also induces clearance of virus-infected cells&#44;<a class="elsevierStyleCrossRef" href="#bb0020"><span class="elsevierStyleSup">4</span></a> and <span class="elsevierStyleItalic">d3</span>&#41; CTLs participate in adaptive immune responses and are key players in mediating immunity against pathogens and tumours&#46;<a class="elsevierStyleCrossRef" href="#bb0025"><span class="elsevierStyleSup">5</span></a></p><p id="p0065" class="elsevierStylePara elsevierViewall">Even though HPV16-ALIFE can run any number of simulations and combination of variables that the researcher requests to develop the precise example we are evaluating in this article&#44; we have proposed the conditions detailed below&#46;</p><p id="p0070" class="elsevierStylePara elsevierViewall">In the execution of the proposed experimental design&#44; a total of 210 simulations were conducted&#44; corresponding to 210 virtual patients&#46; Out of this group&#44; 30 patients do not receive vaccines&#59; 90 patients are given therapeutic non-adjuvanted vaccines&#44; and 90 patients are given therapeutic adjuvanted vaccines&#46; The simulated therapy consists of an autogenous DC therapeutic vaccine&#44; loaded with HPV16 E6 and E7 antigens&#46; A maximum of 3 doses &#40;Dosage parameter&#41;&#44; at 2-week intervals between doses &#40;Intervals-weeks parameter&#41; is planned for all cases corresponding to patients to receive vaccination&#46; However&#44; the model will confirm the number of doses required and the specific week of administration necessary to effectively eliminate the patient&#39;s lesions&#46; As regards the testing of non-adjuvanted vaccines&#44; the load will vary between 10&#44; 100&#44; and 1000&#8239;&#956;g&#47;mL &#40;antigen-loaded DCs parameter&#41;&#46; As for adjuvanted vaccine testing&#44; the load will be kept constant at 10&#8239;&#956;g&#47;mL &#40;antigen-loaded DCs parameter&#41; and the adjuvant will vary between IL-2 &#40;Selector&#44; Activate-cytokine&#8239;&#61;&#8239;IL-2&#41;&#44; Poly I&#58;C as a ligand of TLR3 &#40;Switch&#44; TLR3&#8239;&#61;&#8239;on&#41;&#44; and CpG as a TLR9 ligand &#40;Switch&#44; TLR9&#8239;&#61;&#8239;ON&#41;&#46;</p><p id="p0075" class="elsevierStylePara elsevierViewall">When a therapy is planned in the prototype and the selector tools are used&#44; the selected components will act as adjuvants for the therapeutic vaccine to be administered to the virtual patients&#46; When a vaccine is not planned&#44; but one or more selectors are switched on&#44; the selected components will act within the model as a drug&#46; Similarly&#44; when a therapeutic vaccine is planned and TLR switches are used&#44; they will act as adjuvants&#46; When a vaccine is not planned&#44; but a TLR switch is activated&#44; the chosen component will act as a drug&#46;</p><p id="p0080" class="elsevierStylePara elsevierViewall">We define &#8220;phase&#8221; as the set of initial states &#40;active&#47;inactive&#41; associated with one or more viral proteins&#44; which are stated prior to initiating a simulation&#46; The experiments we performed in &#8220;phase I&#34; started with all viral proteins in the active state &#40;i&#46;e&#46;&#44; the protein switches on the GUI are set to the on state&#41;&#46; The experiments we conducted in &#8220;phase II&#34; started with the E7 protein in the inactive &#40;OFF&#41; state&#46; The assays we performed in &#8220;phase III&#34; started with the E6 protein in the inactive &#40;OFF&#41; state&#46; Against this background&#44; we conducted 7 types of experiments&#46; Each experiment involved 30 virtual patients&#46;</p><p id="p0085" class="elsevierStylePara elsevierViewall">The unit of time in the simulations corresponded to 1 week &#40;1 tick&#8239;&#61;&#8239;7&#8239;days&#41;&#46; However&#44; for events in which the time fraction occurs in different measures&#44; such as days&#44; hours&#44; minutes&#44; seconds&#44; or microseconds&#44; this model converts the default unit of time and sets an equivalent within the procedure involved &#40;i&#46;e&#46;&#44; 1 day&#8239;&#61;&#8239;24&#8239;h&#59; 1&#8239;h&#8239;&#61;&#8239;60&#8239;min&#59; 1&#8239;min&#8239;&#61;&#8239;60&#8239;s&#44; and so on&#41;&#46;</p><p id="p0090" class="elsevierStylePara elsevierViewall">To perform our example in particular&#44; each simulation runs for 1400 continuous weeks&#46; During this simulated time span&#44; records are taken at weeks 48&#44; 53&#44; 156&#44; 208&#44; 208&#44; 300&#44; 500&#44; and 1400&#46; These specific weeks were selected for the following reasons&#58;<ul class="elsevierStyleList" id="l0005"><li class="elsevierStyleListItem" id="li0005"><span class="elsevierStyleLabel">&#8226;</span><p id="p0095" class="elsevierStylePara elsevierViewall">a&#41; Week 48&#58; The mean time taken for antibody recognition from primary detection of HPV16 DNA has been reported to be 10&#46;5&#8239;months in cervical secretions and 19&#46;1&#8239;months in serum&#46; Loss of antibodies has been reported at 12&#8239;months in cervical secretions and 13&#46;6&#8239;months in serum&#46;<a class="elsevierStyleCrossRef" href="#bb0030"><span class="elsevierStyleSup">6</span></a></p></li><li class="elsevierStyleListItem" id="li0010"><span class="elsevierStyleLabel">&#8226;</span><p id="p0100" class="elsevierStylePara elsevierViewall">b&#41; Week 53&#58; Between 1 and 2 years of exposure&#44; HPV infections are cleared or suppressed through cell-mediated immunity to undetectable levels&#46;<a class="elsevierStyleCrossRefs" href="#bb0035"><span class="elsevierStyleSup">7&#8211;10</span></a></p></li><li class="elsevierStyleListItem" id="li0015"><span class="elsevierStyleLabel">&#8226;</span><p id="p0105" class="elsevierStylePara elsevierViewall">c&#41; Week 156&#58; Several studies have found that the average duration of HPV infection in women who were baseline HPV-negative ranges from 8&#46;5 to 19&#46;4&#8239;months&#46;<a class="elsevierStyleCrossRefs" href="#bb0050"><span class="elsevierStyleSup">10&#8211;12</span></a> This control is included in our model&#44; given that weeks 48 and 53 are within the previously controlled ranges&#46;</p></li><li class="elsevierStyleListItem" id="li0020"><span class="elsevierStyleLabel">&#8226;</span><p id="p0110" class="elsevierStylePara elsevierViewall">d&#41; Week 208&#58; Long-term infection is reported to develop over an average time of 5&#46;1&#8239;years&#46;<a class="elsevierStyleCrossRef" href="#bb0065"><span class="elsevierStyleSup">13</span></a></p></li><li class="elsevierStyleListItem" id="li0025"><span class="elsevierStyleLabel">&#8226;</span><p id="p0115" class="elsevierStylePara elsevierViewall">e&#41; Week 300&#58; Several studies have demonstrated that women at high risk of developing HPV have abnormal cytology at 2&#8239;years or CIN3 at 4&#8239;years&#44; following exposure to the virus&#46;<a class="elsevierStyleCrossRefs" href="#bb0070"><span class="elsevierStyleSup">14&#8211;17</span></a></p></li><li class="elsevierStyleListItem" id="li0030"><span class="elsevierStyleLabel">&#8226;</span><p id="p0120" class="elsevierStylePara elsevierViewall">f&#41; Week 500&#58; Cervical cancer has been reported to develop 10&#8239;years after the first exposure to the virus&#46;<a class="elsevierStyleCrossRef" href="#bb0090"><span class="elsevierStyleSup">18</span></a></p></li><li class="elsevierStyleListItem" id="li0035"><span class="elsevierStyleLabel">&#8226;</span><p id="p0125" class="elsevierStylePara elsevierViewall">g&#41; Week 1400&#58; We would like to observe whether cancer recurs after administering a therapeutic vaccine to the patient during the simulation in the years after the lesions arising from HPV infections have cleared up&#46;<a class="elsevierStyleCrossRef" href="#bb0080"><span class="elsevierStyleSup">16</span></a></p></li></ul></p><p id="p0130" class="elsevierStylePara elsevierViewall">During the execution of this particular example&#44; for each of the weeks referred to above&#44; we retrieved precise information derived from the corresponding data registry&#46; This registry considers the results reported by HPV16-ALIFE regarding&#58; &#40;1&#41; expression levels of viral proteins &#40;E1&#44; E2&#44; E4&#44; E5&#44; E6&#44; E7&#44; L1&#44; and L2&#41;&#59; &#40;2&#41; disease transition states &#40;infection &#37;&#44; mutation &#37;&#44; malignancy &#37;&#44; neoplasia &#37;&#44; ccin1&#37;&#44; ccin2&#37;&#44; ccin3&#37;&#44; pre-cancer &#37;&#44; and cancer &#37;&#41;&#59; &#40;3&#41; secretion levels of the cytokine IL-12&#44; and &#40;4&#41; proliferation levels of the CTL population&#46; Nonetheless&#44; it must be pointed out that our model allows us to observe other behaviours&#44; in addition to those proposed in this example&#46; Moreover&#44; this model makes it possible to observe behaviours associated with other cell populations&#44; other cytokines&#44; TLRs&#44; and surface molecules&#46; Therefore&#44; it will be up to the investigator to decide which variables to follow depending on their individual interest&#46;</p></span><span id="s0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0070">Data analysis</span><p id="p0135" class="elsevierStylePara elsevierViewall">The average values of the data corresponding to the simulated patients&#44; for each type of experiment&#44; in each of the 3 scheduled phases&#44; are generated from the records collected at the different control points &#40;weeks 48&#44; 53&#44; 156&#44; 208&#44; 300&#44; 500&#44; and 1400&#41;&#46; After that&#44; the averages of the cycles that comprise each of the 3 established phases are generated and finally&#44; the percentiles are calculated for the measurements taken&#46; Based on the calculated percentiles&#44; the trend analysis is carried out for the E6 and E7 viral oncoproteins&#44; the IL-12 cytokine&#44; and the CTL population&#44; with the goal of demonstrating whether the SIS is activated and whether the virtual vaccine is capable of eliminating the lesions caused by HPV16&#46;</p></span><span id="s0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0075">Functional logic implemented in the HPV16-ALIFE prototype</span><p id="p0140" class="elsevierStylePara elsevierViewall">The functional prototype developed considers both external and internal perspectives&#46; The functional logic applied in this implementation process is summarised in <a class="elsevierStyleCrossRef" href="#f0010">Fig&#46; 2</a> and described below&#46;</p><elsevierMultimedia ident="f0010"></elsevierMultimedia><p id="p0145" class="elsevierStylePara elsevierViewall">For each of the perspectives&#44; this model determines the properties of the global and local dynamics&#44; respectively&#46; The global dynamics make it possible to establish the properties of the external microenvironment&#46; The local dynamics enable the properties of the internal microenvironment to be defined&#46; Thus&#44; the external microenvironment is affected by the HPV16 life cycle and the control of therapeutic vaccines&#46; The internal microenvironment is affected by the set of cell populations&#44; TLRs&#44; and cytokines&#46; Given these circumstances&#44; the interactions between components are constructed&#46; Initially&#44; the interactions that arise between the HPV16 life cycle and the different cell populations are designed and later&#44; the interactions are designed that allow the necessary activity to be induced in order to trigger connectivity signals that produce links between TLRs and cytokines&#46; In this way&#44; a feedback process is set up between the global parameters and the control parameters&#46; Next&#44; the interactions are defined that arise between the therapeutic vaccines to be evaluated and the different cell populations&#44; TLRs&#44; and cytokines&#46; Thus&#44; a feedback process is established between control parameters and global parameters&#46;</p><p id="p0150" class="elsevierStylePara elsevierViewall">HPV16-ALIFE defines a specific logic to set the affinity maturation level&#44; as well as to enable possible interactions between cell populations&#46; This model defines 3 categories of affinity maturation level&#59; i&#46;e&#46;&#44; low&#44; medium&#44; and high&#46; Bearing in mind that somatic hypermutation is a largely stochastic process&#44; this model controls affinity maturation by generating randomisation that distinguishes the three degrees of maturation previously referenced&#46;</p></span><span id="s0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0080">Information provided by the HPV16-ALIFE prototype</span><p id="p0155" class="elsevierStylePara elsevierViewall">The HPV16-ALIFE model makes it possible to track the behaviour of all the components that define it&#44; in such a way that it is possible to observe both the evolution of the process associated with HPV16 infection and the SIS response that originates in the human host&#46; This information can be visualised through the GUI &#40;<a class="elsevierStyleCrossRef" href="#f0015">Fig&#46; 3</a>&#41;&#44; which consists of a main monitor and 166 secondary monitors&#44; together with 9 trend graphs&#46; Such tools enable the model&#39;s behaviour to be evaluated and analysed at any point in time&#46; The information contained in each of these tools is described below&#46;<ul class="elsevierStyleList" id="l0010"><li class="elsevierStyleListItem" id="li0040"><span class="elsevierStyleLabel">&#8226;</span><p id="p0160" class="elsevierStylePara elsevierViewall">1&#41; <span class="elsevierStyleItalic">Main monitor&#58;</span> Each of the incorporated cell populations has a unique visual representation that distinguishes them from other populations and makes it easier for the user to observe their motility&#46; The populations differentiated in this model include&#58; B cells&#44; germinal centre B cells&#44; short-lived plasma cells&#44; short-lived memory B cells&#44; long-lived plasma cells&#44; long-lived memory B cells&#44; antibodies&#44; plasmacytoid DCs&#44; T cells&#44; natural killer cells&#44; CD4<span class="elsevierStyleHsp" style=""></span>&#43; T cells&#44; CD8<span class="elsevierStyleHsp" style=""></span>&#43; T cells&#44; cytotoxic T lymphocytes&#44; memory CD8 T cells&#44; keratinocytes&#44; follicular DCs&#44; T-helper &#40;Th&#41; type 1&#44; Th type 2&#44; follicular Th&#44; Th type 9&#44; Th type 17&#44; Th type 22&#44; regulatory T cells&#44; and M1-type macrophages&#46;</p></li><li class="elsevierStyleListItem" id="li0045"><span class="elsevierStyleLabel">&#8226;</span><p id="p0165" class="elsevierStylePara elsevierViewall">2&#41; <span class="elsevierStyleItalic">Viral protein status monitors&#58;</span> Eight monitors record the expression levels of each of the early &#40;E1&#44; E2&#44; E4&#44; E5&#44; E6&#44; and E7&#41; and late &#40;L1&#8211;L2&#41; viral proteins&#46;</p></li><li class="elsevierStyleListItem" id="li0050"><span class="elsevierStyleLabel">&#8226;</span><p id="p0170" class="elsevierStylePara elsevierViewall">3&#41; <span class="elsevierStyleItalic">Transition status monitors&#58;</span> Ten monitors display the percentage of cells indicating infection&#44; mutation&#44; pre-malignancy&#44; malignancy&#44; neoplasia&#44; CIN1&#44; CIN2&#44; CIN3&#44; pre-cancer&#44; and cancer status&#44; respectively&#46;</p></li><li class="elsevierStyleListItem" id="li0055"><span class="elsevierStyleLabel">&#8226;</span><p id="p0175" class="elsevierStylePara elsevierViewall">4&#41; <span class="elsevierStyleItalic">Cytokine monitors&#58;</span> Seventeen monitors display the activity status of the cytokines TNF&#44; TGF&#44; IFN&#44; and MIF&#44; together with their receptors&#46;</p></li><li class="elsevierStyleListItem" id="li0060"><span class="elsevierStyleLabel">&#8226;</span><p id="p0180" class="elsevierStylePara elsevierViewall">5&#41; <span class="elsevierStyleItalic">Interleukin monitors&#58;</span> The activity status of interleukins together with their receptors are displayed on 77 monitors&#46;</p></li><li class="elsevierStyleListItem" id="li0065"><span class="elsevierStyleLabel">&#8226;</span><p id="p0185" class="elsevierStylePara elsevierViewall">6&#41; <span class="elsevierStyleItalic">Growth factor monitors&#58;</span> Six monitors exhibit that activity status of each of the growth factors that have been incorporated &#40;EGF&#44; EGFR&#44; G-CSF&#44; GM-CSF&#44; M-CSF&#44; and VEGF&#41;&#46;</p></li><li class="elsevierStyleListItem" id="li0070"><span class="elsevierStyleLabel">&#8226;</span><p id="p0190" class="elsevierStylePara elsevierViewall">7&#41; <span class="elsevierStyleItalic">Proapoptotic protein monitors&#58;</span> Eight monitors display the status of activity of each of the proapoptotic proteins integrated &#40;BAX&#44; BAD&#44; BAK&#44; BCL-XL&#44; BIM&#44; BID&#44; Fas&#44; and FasL&#41;&#46;</p></li><li class="elsevierStyleListItem" id="li0075"><span class="elsevierStyleLabel">&#8226;</span><p id="p0195" class="elsevierStylePara elsevierViewall">8&#41; <span class="elsevierStyleItalic">Antiapoptotic protein monitors&#58;</span> Two monitors reveal the activity status of the antiapoptotic proteins incorporated &#40;BCL-2&#44; and MCL-1&#41;&#46;</p></li><li class="elsevierStyleListItem" id="li0080"><span class="elsevierStyleLabel">&#8226;</span><p id="p0200" class="elsevierStylePara elsevierViewall">9&#41; <span class="elsevierStyleItalic">TLR signalling pathway monitors&#58;</span> The activity status of the components that assemble the TLR signalling pathways is displayed on 38 monitors&#46;</p></li><li class="elsevierStyleListItem" id="li0085"><span class="elsevierStyleLabel">&#8226;</span><p id="p0205" class="elsevierStylePara elsevierViewall">10&#41; <span class="elsevierStyleItalic">Cell population graphs</span>&#58; Three trend graphs report the behaviour of each of the incorporated cell populations&#46;</p></li><li class="elsevierStyleListItem" id="li0090"><span class="elsevierStyleLabel">&#8226;</span><p id="p0210" class="elsevierStylePara elsevierViewall">11&#41; <span class="elsevierStyleItalic">Antibody graph</span>&#58; This graph depicts the trend reported by the different antibody isotypes expressed during the simulation &#40;IgM&#44; IgG&#44; IgA&#44; IgG1&#44; IgG2&#44; IgG3&#44; and IgG4&#41;&#46;</p></li><li class="elsevierStyleListItem" id="li0095"><span class="elsevierStyleLabel">&#8226;</span><p id="p0215" class="elsevierStylePara elsevierViewall">12&#41; <span class="elsevierStyleItalic">HPV16 infection graph</span>&#58; This graph shows the trend of groups of cells with respect to the presence of the virus&#44; over the course of time&#46; These groups include&#58; cells that are not infected by the virus &#40;HPV16-&#41;&#44; cells that are positive for HPV16 infection &#40;HPV16<span class="elsevierStyleHsp" style=""></span>&#43;&#41;&#44; cells that reflect disease progression &#40;CIN1&#44; CIN2&#44; and CIN3&#41;&#44; and cells that exhibit risk conditions &#40;pre-cancer and cancer&#41;&#46;</p></li><li class="elsevierStyleListItem" id="li0100"><span class="elsevierStyleLabel">&#8226;</span><p id="p0220" class="elsevierStylePara elsevierViewall">13&#41; <span class="elsevierStyleItalic">Tumour suppressor graph</span>&#58; This graph shows the trend&#44; both in activity and inactivity&#44; of the incorporated tumour suppressors &#40;p53&#44; pRb&#44; p21&#44; and Tert&#41;&#46;</p></li><li class="elsevierStyleListItem" id="li0105"><span class="elsevierStyleLabel">&#8226;</span><p id="p0225" class="elsevierStylePara elsevierViewall">14&#41; <span class="elsevierStyleItalic">Invasive cancer biomarkers graph</span>&#58; This graph plots the trend of potential biomarkers associated with the risk of developing invasive cancer and metastasis&#46;</p></li><li class="elsevierStyleListItem" id="li0110"><span class="elsevierStyleLabel">&#8226;</span><p id="p0230" class="elsevierStylePara elsevierViewall">15&#41; <span class="elsevierStyleItalic">Immunostimulatory cytokines graph</span>&#58; This chart illustrates the trend in the behaviour of cytokines that have been found to be involved in cancer biology and are classified as tumour suppressor cytokines&#46; These cytokines induce cell-mediated immunity and anti-tumour responses&#44; but their continued expression can also promote chronic inflammatory processes that can trigger neoplasia&#46;</p></li><li class="elsevierStyleListItem" id="li0115"><span class="elsevierStyleLabel">&#8226;</span><p id="p0235" class="elsevierStylePara elsevierViewall">16&#41; <span class="elsevierStyleItalic">Immunoinhibitory cytokine graph</span>&#58; This graph depicts the trend in the behaviour of cytokines that have been found to be involved in cancer biology and are classified as immunoinhibitory cytokines&#46; These cytokines induce humoral immunity&#46;</p></li></ul></p><elsevierMultimedia ident="f0015"></elsevierMultimedia><p id="p0240" class="elsevierStylePara elsevierViewall">Although this model considers a greater number of variables than the ones on the GUI of the prototype developed&#44; the display of such information is limited by the available display space on the computer screen used &#40;monitor size&#58; 21&#46;5&#8239;in&#46;&#41;&#44; which prevents all the variables of the model built from being displayed&#46; However&#44; the prototype developed does make it possible to replace some of the established monitors with others that you may wish&#46;</p></span></span><span id="s0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0085">Results</span><p id="p0245" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#f0020">Fig&#46; 4</a> illustrates that when simulated patients do not receive a therapeutic vaccine&#44; the lesions caused by HPV16 tend to manifest the highest levels &#40;see the dark blue trend line corresponding to EXP-1&#41;&#46; However&#44; when patients are treated with a therapeutic vaccine&#44; the severity of the various HPV16 lesions decreases significantly &#40;see trend lines for experiments EXP-2&#44; EXP-3&#44; EXP-4&#44; EXP-5&#44; EXP-6&#44; and EXP-7&#41;&#46; These results reveal that the therapeutic vaccines used in the experiments conducted are able to significantly control the cancer &#40;<a class="elsevierStyleCrossRef" href="#f0020">Fig&#46; 4</a> A&#41;&#44; with even better results than in lesions that display lesser severity &#40;<a class="elsevierStyleCrossRef" href="#f0020">Fig&#46; 4</a> B&#8211;E&#41;&#46;</p><elsevierMultimedia ident="f0020"></elsevierMultimedia><p id="p0250" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#f0025">Fig&#46; 5</a> depicts that when simulated patients do not receive a therapeutic vaccine&#44; the expression levels of the viral oncoproteins E6 &#40;<a class="elsevierStyleCrossRef" href="#f0025">Fig&#46; 5</a> C&#41; and E7 &#40;<a class="elsevierStyleCrossRef" href="#f0025">Fig&#46; 5</a> D&#41; tend to increase &#40;see the dark blue trend line corresponding to EXP-1&#41;&#46; In contrast&#44; when a therapeutic vaccine is administered&#44; the expression levels of these oncoproteins show a significant decrease &#40;see trend lines for experiments EXP-2&#44; EXP-3&#44; EXP-4&#44; EXP-5&#44; EXP-6&#44; and EXP-7&#41;&#46;</p><elsevierMultimedia ident="f0025"></elsevierMultimedia><p id="p0255" class="elsevierStylePara elsevierViewall">Furthermore&#44; in all cases where a therapeutic vaccine was administered&#44; the levels of proliferation of the CTL population &#40;<a class="elsevierStyleCrossRef" href="#f0025">Fig&#46; 5</a> B&#41; tend to increase&#44; as does the secretion of the cytokine IL-12 &#40;<a class="elsevierStyleCrossRef" href="#f0025">Fig&#46; 5</a> A&#41;&#46; Both behaviours are indicative of a successful SIS response to the intervention of the therapeutic vaccines tested in this model&#46;</p><p id="p0260" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#f0025">Fig&#46; 5</a> A shows the IL-12 cytokine secretion levels reported in response to the challenge posed by each of the vaccination strategies tested in HPV16-ALIFE &#40;EXP-2&#44; EXP-3&#44; EXP-4&#44; EXP-5&#44; EXP-6&#44; and EXP-7&#41;&#46; Of the seven types of experiments performed&#44; type 4 &#40;non-adjuvanted vaccine with DC load&#8239;&#61;&#8239;1000&#8239;&#956;g&#47;mL&#41; yields the highest levels of secretion&#44; and the type 1 experiment &#40;EXP-1&#58; no vaccine&#41;&#44; the lowest levels of IL-12&#46;</p><p id="p0265" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#f0025">Fig&#46; 5</a> B demonstrates the behaviour of CTL population proliferation in response to each of the treatment strategies tested in HPV16-ALIFE &#40;EXP-2&#44; EXP-3&#44; EXP-4&#44; EXP-5&#44; EXP-6&#44; and EXP-7&#41;&#44; which involve the delivery of a therapeutic vaccine to the virtual host&#46; Of the 6 classes of experiments performed with a vaccine&#44; experiment type 6 &#40;EXP-6&#58; vaccine with DC load&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL and Poly I&#58;C adjuvant as TLR3 ligand&#41; had the highest levels of cell proliferation in this population&#44; while experiment type-5 &#40;EXP-5&#58; vaccine with DC load&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL and IL-2 adjuvant&#41; had the lowest levels&#46; Nevertheless&#44; in all experiments involving the delivery of DC vaccines&#44; increased levels of proliferation of the CTL population are observed&#46;</p><p id="p0270" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#f0025">Figs&#46; 5</a> C and D outline the behaviour of the expression of the HPV16 viral proteins E6 and E7&#44; respectively&#44; in this model for each of the experiments performed &#40;EXP-1&#44; EXP-2&#44; EXP-3&#44; EXP-4&#44; EXP-5&#44; EXP-6&#44; and EXP-7&#41;&#46; The highest expression levels of both E6 and E7 proteins are found in EXP-1&#59; i&#46;e&#46;&#44; when the host does not receive a vaccine&#46; In the other experiments&#44; which involve the delivery of a DC vaccine&#44; the expression levels of these proteins fall substantially&#46;</p><p id="p0275" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#f0030">Fig&#46; 6</a> represents the behaviour of the CTL population proliferation levels when challenged by the therapeutic adjuvanted vaccines simulated in the prototype developed&#46; All the adjuvanted vaccines evaluated use the same DC load but different adjuvant&#46; This figure also shows the trend that results when applying 1&#44; 2&#44; or 3 doses of the vaccine under evaluation&#44; as established by the model according to the conditions of the simulated microenvironment&#46;</p><elsevierMultimedia ident="f0030"></elsevierMultimedia><p id="p0280" class="elsevierStylePara elsevierViewall">During the phase I experiments and when IL-2 was used as the adjuvant&#44; this model applied a maximum of the 3 doses that were programmed at the start of the simulation&#46; The highest level of CTL proliferation was observed when the host received all 3 doses&#46; In both phase II and phase III&#44; this model delivered a maximum of 2 of the 3 initially scheduled doses&#46; When a TLR3 agonist was used as an adjuvant in phase i&#44; this model only administered 2 of the 3 doses programmed&#46; In phase II&#44; this model delivered exactly 1 or 3&#44; but never 2 doses&#46; In phase III&#44; this model administered a maximum of 3 doses&#46; When a TLR9 agonist was used as an adjuvant&#44; in all 3 phases of experiments carried out&#44; a maximum of the 3 scheduled doses of the therapeutic vaccine under evaluation were applied&#46; The highest level of proliferation of the CTL population was noted in the phase III experiments&#44; particularly when the model delivered all three doses of the vaccine&#46; Comparing the CTL population proliferation induced by the vaccines with the 3 types of adjuvants tested in this model&#44; the TLR9 agonist &#40;CpG&#41; was found to induce the greatest proliferation on average&#59; the TLR3 agonist &#40;Poly I&#58;C&#41; induced the second highest level of proliferation&#44; and IL-2&#44; the third highest level of proliferation&#46;</p><p id="p0285" class="elsevierStylePara elsevierViewall">Halloran et al&#46;<a class="elsevierStyleCrossRef" href="#bb0095"><span class="elsevierStyleSup">19</span></a> define vaccine efficacy by disease susceptibility as the ratio of the relative risk of infection or disease in vaccinated individuals compared to unvaccinated individuals&#46; Drawing on these concepts and using the data generated by each of the experiments run on the HPV16-ALIFE prototype&#44; the rates are calculated for each of the 3 phases and for each type of lesion &#40;CIN1&#44; CIN2&#44; CIN3&#44; pre-cancer&#44; and cancer&#41;&#46;</p><p id="p0290" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#f0035">Fig&#46; 7</a> A and B plot the trend in efficacy for the therapeutic vaccines tested without and with adjuvant&#44; respectively&#44; observed in the simulations performed&#46; These graphs show the trend of the virtual patient group receiving the specific vaccine type in each of the phases&#44; although the number of doses delivered in each case is not shown&#46; Therefore&#44; this data is provided in the corresponding analysis&#46;</p><elsevierMultimedia ident="f0035"></elsevierMultimedia><p id="p0295" class="elsevierStylePara elsevierViewall">Among the experiments performed with non-adjuvanted vaccines&#44; in which the DC load varied between 10&#44; 100&#44; and 1000&#8239;&#956;g&#47;mL&#44; in cancer conditions&#44; the vaccine that reported the best average efficacy rate &#40;97&#46;16&#37;&#41; was the one with the DC load&#8239;&#61;&#8239;1000&#8239;&#956;g&#47;mL&#46; Under pre-cancer conditions&#44; the vaccine having the best average efficacy rate &#40;74&#46;83&#37;&#41; is the one with the DC load&#8239;&#61;&#8239;100&#8239;&#956;g&#47;mL&#46; For CIN3 lesions&#44; the vaccine reporting the best average efficacy rate &#40;55&#46;48&#37;&#41; corresponds to the vaccine with the DC load&#8239;&#61;&#8239;100&#8239;&#956;g&#47;mL&#46;</p><p id="p0300" class="elsevierStylePara elsevierViewall">Considering the experiments performed with adjuvanted therapeutic vaccines&#44; in which the DC load was kept constant at 10&#8239;&#956;g&#47;mL and the adjuvant varied&#44; under cancer conditions&#44; the vaccine with the best average efficacy rate &#40;97&#46;77&#37;&#41; was the one using IL-2 as adjuvant&#46; In a scenario of pre-cancer&#44; the vaccine with the best average efficacy rate &#40;77&#46;43&#37;&#41; was the one using IL-2 as the adjuvant&#46; In CIN3 lesions&#44; the vaccine with the best average efficacy &#40;53&#46;44&#37;&#41; was the one that used TLR9 as adjuvant&#46;</p><p id="p0305" class="elsevierStylePara elsevierViewall">Analysing the data by each type of vaccine tested in the prototype&#44; the most significant rate observed in cancer and pre-cancer conditions corresponded to the therapeutic vaccine using IL-2 as adjuvant&#46; In contrast&#44; the most significant rate observed in CIN3 lesions corresponded to the non-adjuvanted vaccines&#46;</p><p id="p0310" class="elsevierStylePara elsevierViewall">When patients did not receive therapeutic vaccines &#40;EXP-1&#41;&#44; cervical cancer rates peaked at 18&#46;86&#37;&#46; In contrast&#44; when patients received any vaccination strategy &#40;EXP-2&#44; EXP-3&#44; EXP-4&#44; EXP-5&#44; EXP-6&#44; and EXP-7&#41;&#44; cervical cancer rates fell significantly&#44; reaching maximum rates between 0&#46;48&#37; and 3&#46;12&#37;&#44; which varied depending on the specifics associated with each therapeutic vaccine being evaluated&#46;</p><p id="p0315" class="elsevierStylePara elsevierViewall">In summary&#44; among the &#8220;adjuvanted&#8221; therapeutic vaccines evaluated&#44; the one that proved most effective in controlling cervical cancer was the one that included IL-2 as adjuvant&#46; Of the &#8220;non-adjuvanted&#8221; therapeutic vaccines evaluated&#44; the one that proved to be most effective in controlling the cervical cancer condition was the one that used the highest DC load&#46; With our model&#44; other events also became evident when the cancer was active&#46; These events included&#58; increased secretion of the IL-12 cytokine&#44; greater proliferation of the CTL population&#44; and declines in the expression levels of the viral oncoproteins E6 and E7&#46; All of these phenomena occurred as a consequence of the effects mediated by therapeutic vaccines of autogenous DC loaded with E6&#47;E7 antigens&#46;</p></span><span id="s0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0090">Discussion</span><p id="p0320" class="elsevierStylePara elsevierViewall">To date&#44; no other computational model has simulated interactions such as those proposed by HPV16-ALIFE with its three domains&#44; making it difficult to compare our results with other computational works&#46; We have therefore relied on specific clinical trials with real-world patients&#44; in an attempt to compare the behaviour of individually observed components&#44; inasmuch as we have not found a trial that can simultaneously evaluate all the components that integrate this model&#46; However&#44; this work is complex due to the same circumstances that other authors have already mentioned&#46; Basically&#44; comparing the results of several clinical studies is challenging&#44; taking into account that they are conducted under differing characteristics of performance&#44; sensitivity&#44; and cut-off points&#44; as well as differences in study design&#44; definitions of seropositivity&#44; analysis strategies&#44;<a class="elsevierStyleCrossRef" href="#bb0100"><span class="elsevierStyleSup">20</span></a> and length of follow-up&#46; Consequently&#44; any comparison of the results obtained using our model against selected real clinical trials can only be made at the trend level&#46;</p><p id="p0325" class="elsevierStylePara elsevierViewall">This means that we have focused on assessing the emerging behaviour of specific elements of the model that may be affected when mediated by a viral infection and&#47;or a specific cancer treatment&#46; We compared these emergent behaviours with the results of other authors that were obtained from clinical trials with living patients&#46;</p><p id="p0330" class="elsevierStylePara elsevierViewall">Therefore&#44; and in line with what has been explained in the results section&#44; we analysed the trends observed in the simulations performed in HPV16-ALIFE with regard to the secretion of the cytokine IL-12&#44; expression of the viral oncoproteins E6 and E7&#44; the behaviour of the CTL population&#44; and the efficacy of the simulated therapeutic vaccines&#46; Finally&#44; this information enabled us to discuss the results obtained from experiments applied to our prototype in comparison to those obtained from certain studies with groups of patients treated in real life&#46;</p><p id="p0335" class="elsevierStylePara elsevierViewall">Discussion of the results observed in the artificial life model versus real-world clinical studies&#46;</p><p id="p0340" class="elsevierStylePara elsevierViewall">The experiments performed in HPV16-ALIFE made it possible to simulate patients with the disease who did not receive vaccines&#44; patients with the disease who received therapeutic vaccines without adjuvants&#44; and patients with the disease who received therapeutic vaccines with adjuvants&#46; Analyses of the results obtained provided us with trends consistent with some real-world clinical studies&#46;</p><p id="p0345" class="elsevierStylePara elsevierViewall">The following clinical trials whose trend of results coincides with ours&#44; were conducted by&#58; &#40;1&#41; Rainone et al&#46;<a class="elsevierStyleCrossRef" href="#bb0105"><span class="elsevierStyleSup">21</span></a> and Wang et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bb0110"><span class="elsevierStyleSup">22</span></a> regarding the behaviour of IL-12&#59; &#40;2&#41; Wu et al&#46;<a class="elsevierStyleCrossRef" href="#bb0115"><span class="elsevierStyleSup">23</span></a> and the trend observed in E6 and E7 protein expression levels&#44; the increase in CTL population&#44; and the specific protective immunity triggered against cervical cancer cells&#59; &#40;3&#41; Chan et al&#46;<a class="elsevierStyleCrossRef" href="#bb0120"><span class="elsevierStyleSup">24</span></a> and the behaviour of a TLR9 agonist&#59; &#40;4&#41; Wick and Webb<a class="elsevierStyleCrossRef" href="#bb0125"><span class="elsevierStyleSup">25</span></a> and the behaviours of a TLR3 agonist and a TLR9 agonist&#44; and &#40;5&#41; Lin et al&#46;<a class="elsevierStyleCrossRef" href="#bb0130"><span class="elsevierStyleSup">26</span></a> and the evaluation of the performance of an IL-2 adjuvant&#46;</p><p id="p0350" class="elsevierStylePara elsevierViewall">In their study&#44; Rainone et al&#46;<a class="elsevierStyleCrossRef" href="#bb0105"><span class="elsevierStyleSup">21</span></a> report that administration of antigen-loaded DC evoked a strong anti-tumour response in vivo&#44; as demonstrated by a general activation of immunocompetent cells and release of Th1 cytokines&#46; IL-12 and IFN-&#947; secretion was significantly increased in T cells co-cultured with antigen-loaded DCs compared to T cells co-cultured with unloaded DCs&#46; Data from this study illustrate a specific activation of the immune system against breast cancer&#46; The results in HPV16-ALIFE also demonstrated specific activation of the immune system against cervical cancer&#46;</p><p id="p0355" class="elsevierStylePara elsevierViewall">Wang et al&#46;<a class="elsevierStyleCrossRef" href="#bb0110"><span class="elsevierStyleSup">22</span></a> evaluate the immunotherapeutic potential of human DC loaded with HPV16-associated antigens&#46; The results of this study demonstrated anti-tumour activity&#44; in particular with respect to IL-12 upregulation and increased CTL population activity&#44; following treatment with antigen-loaded DCs&#46; DC loaded with HPV16 antigens report significant anti-tumour immunity in patients with cervical cancer&#46; The results observed in HPV16-ALIFE indicate that treatment with autogenous DCs loaded with HPV16 E6&#47;E7 antigens induces an immune response in patients with cervical cancer&#44; which can be seen in the upregulation of IL-12&#44; increased CTL activity&#44; and a decrease in the cancer cell population&#46;</p><p id="p0360" class="elsevierStylePara elsevierViewall">Meanwhile&#44; in their study&#44; Wu et al&#46;<a class="elsevierStyleCrossRef" href="#bb0115"><span class="elsevierStyleSup">23</span></a> show that an HPV16 E6&#47;E7 gene-modified DC vaccine can induce apoptosis of cancer cells by inducing CTL&#46; The results observed in HPV16-ALIFE also reveal that following treatment with autogenous DC loaded with HPV16 E6&#47;E7 antigens&#44; there is a proliferation of CTL&#59; this population&#44; in turn&#44; promotes apoptosis in cancer cells&#46;</p><p id="p0365" class="elsevierStylePara elsevierViewall">In their study&#44; Chang et al&#46;<a class="elsevierStyleCrossRef" href="#bb0120"><span class="elsevierStyleSup">24</span></a> report that a TLR9 agonist &#40;specifically CpG&#41; enhances CTL responses and eradicates large tumours&#46; The remarkable anti-tumour effects of recombinant lipoprotein E7 &#40;rlipo-E7m&#41; and CpG-ODN reflect the amplification of CTL responses and suppression of the tumour environment&#46; The results observed in HPV16-ALIFE illustrate that autogenous DC vaccination with CpG &#40;TLR9 ligand&#41; adjuvant induces anti-tumour responses through the induction of antigen-specific CD8<span class="elsevierStyleHsp" style=""></span>&#43; T cells and their subsequent differentiation into CTLs&#44; which then participate in cancer cell reduction&#46;</p><p id="p0370" class="elsevierStylePara elsevierViewall">Wick and Webb<a class="elsevierStyleCrossRef" href="#bb0125"><span class="elsevierStyleSup">25</span></a> evaluated a vaccine called Pentarix&#44; based on a recombinant fusion protein containing E7 oncoproteins from 5 high-risk HPV genotypes&#46; Among the genotypes studied&#44; HPV16 is included together with a TLR3 agonist &#40;Poly I&#58;C&#41; or a TLR9 agonist &#40;CpG&#41;&#44; to be delivered to mice in an immunisation strategy&#46; This study demonstrates that the vaccine is able to elicit strong CD8 T-cell responses against the E7 antigen using the recombinant protein in combination with the TLR3 agonist &#40;Poly I&#58;C&#41; or TLR9 agonist &#40;CpG&#41;&#46; The results attained in this study are consistent with the trends observed in the HPV16-ALIFE simulations&#46;</p><p id="p0375" class="elsevierStylePara elsevierViewall">The objective as proposed by Lin et al&#46;<a class="elsevierStyleCrossRef" href="#bb0130"><span class="elsevierStyleSup">26</span></a> in their study was to determine whether the potency of the DNA vaccine encoding the HPV16 E7 antigen can be enhanced by IL-2&#46; They conclude that the link between IL-2 and the HPV16 E7 antigen significantly improves the potency of the DNA vaccine against E7-expressing tumours&#46; The results observed in HPV16-ALIFE demonstrate that the highest rate of cancer and pre-cancer control is reported in autogenous DC vaccines loaded with E6&#47;E7 antigens using IL-2 adjuvant&#46;</p></span><span id="s0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0095">Conclusions</span><p id="p0380" class="elsevierStylePara elsevierViewall">The behaviours observed in this model reveal that the SIS responds to its constituent microenvironments&#44; which are induced by the interactions between the immune system&#44; the HPV16 life cycle&#44; and the therapeutic vaccines&#46; All therapeutic vaccines simulated in HPV16-ALIFE proved that the SIS has the ability to respond to them&#46;</p><p id="p0385" class="elsevierStylePara elsevierViewall">This work shows that despite some gaps reported in the literature &#40;e&#46;g&#46;&#44; identifying the cause of spontaneous regression in HPV or the mechanism by which plasma cells localise to the bone marrow&#44; among others&#44; are still unknown events&#41;&#44; it is possible to simulate the behaviours of the 3 proposed domains in a single model&#44; including&#58; &#40;1&#41; components involved in the immune system&#59; &#40;2&#41; responses that this system triggers against a persistent infection caused by HPV16 &#40;which can induce cervical cancer&#41;&#44; and &#40;c&#41; therapeutic vaccine strategies that seek to eradicate the disease&#46; By linking all these components within the HPV16-ALIFE model through rules&#44; interactions&#44; checkpoints&#44; states&#44; and transitions&#44; it becomes possible to simulate known actions and evaluate the emergence of patterns of behaviour&#46; This model also has the capacity to stimulate and&#47;or block critical points and induce the upregulation of specific cell populations&#46; Based on this&#44; HPV16-ALIFE offers the possibility of observing behaviours arising from these interactions&#44; generated in an artificial life world&#44; where the biases identified in animal models can probably be mitigated&#44; and testing and primary evaluation times can be reduced&#46;</p><p id="p0390" class="elsevierStylePara elsevierViewall">Despite the fact that issues related to the immune system and the HPV16 life cycle have yet to be clarified&#44; the HPV16-ALIFE model allows us to observe this interaction and simulate test experiments that help to generate an initial approximation of the possible resulting behaviours&#44; particularly in scenarios in which therapeutic vaccines are involved&#46; Despite the fact that the previously documented tests recommend the use of autogenous DC therapeutic vaccines&#44; this model enables us to propose other types of therapeutic vaccines&#44; such as anti-PD1&#44; and also to define the combined activation and inactivation states of some components that are part of the cytokine and TLR signalling pathways&#46;</p><p id="p0395" class="elsevierStylePara elsevierViewall">The scope of the present work does not address establishing the effectiveness of the types of therapeutic vaccines used in the experiments tested&#46; However&#44; the results obtained do enable us to establish the type of vaccine that&#44; at the individual and group levels&#44; prove to be most effective for the model in controlling lesions arising from HPV16 infection&#44; taking into account the conditions of the simulated microenvironment&#46; This does not imply that the vaccine rated best in this model will prove to be equally effective in the real world&#46; However&#44; given the similarity observed between the trend reported by the simulated immune response and the real-world trials&#44; it is possible to propose a different order of evaluation&#46; This can be interpreted as a new evaluation guide when planning different trials to be applied to other models&#44; whether virtual&#44; animal&#44; or human&#46; Still&#44; it must be tested in the real world&#46; While the order of vaccine efficacy proposed by this model might serve as a guide&#44; testing it in the real world is beyond the scope of this paper&#46;</p><p id="p0400" class="elsevierStylePara elsevierViewall">Overall&#44; the virtual experiments conducted with the HPV16-ALIFE model have shown a SIS that has reacted under both circumstances&#58; when an infectious process caused by HPV16 is mediated and when a therapeutic vaccine is used as a treatment strategy&#46; Notably&#44; the responses observed in this model vary from experiment to experiment depending on the load&#44; dose&#44; frequency&#44; and adjuvants used in each simulation&#46; By evaluating the behaviour observed in our model in comparison with some previously reported clinical studies&#44;<a class="elsevierStyleCrossRefs" href="#bb0105"><span class="elsevierStyleSup">21&#8211;26</span></a> it is apparent that HPV16-ALIFE generates behaviours similar to those reported by those authors in their real-life studies&#46;</p></span><span id="s0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0100">Funding</span><p id="p0405" class="elsevierStylePara elsevierViewall">There is no funding body nor has any grant been received&#46;</p></span><span id="s0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0105">Conflict of Interests</span><p id="p0410" class="elsevierStylePara elsevierViewall">The author has no conflict of interests to declare&#46;</p></span></span>"
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            1 => "Artificial immune system"
            2 => "Cervical cancer"
            3 => "HPV16"
            4 => "Simulation prototype"
            5 => "Therapeutic vaccine"
          ]
        ]
      ]
      "es" => array:1 [
        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Palabras Clave"
          "identificador" => "xpalclavsec1609734"
          "palabras" => array:6 [
            0 => "Vida artificial"
            1 => "sistema inmune artificial"
            2 => "c&#225;ncer c&#233;rvix"
            3 => "HPV16"
            4 => "prototipo simulaci&#243;n"
            5 => "vacuna terap&#233;utica"
          ]
        ]
      ]
    ]
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    "resumen" => array:2 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="as0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0010">Objective</span><p id="sp0040" class="elsevierStyleSimplePara elsevierViewall">To evaluate the artificial life model that simulates behaviours based on interactions occurring between the human immune system&#44; the life cycle of human papillomavirus type 16&#44; and certain types of therapeutic vaccines through virtual experiments on the constructed prototype&#46;</p></span> <span id="as0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0015">Materials and methods</span><p id="sp0045" class="elsevierStyleSimplePara elsevierViewall">We developed the HPV16-ALIFE prototype using artificial life techniques to be used as a virtual laboratory&#46; To evaluate the model&#44; we analysed the responses of the simulated immune system under two circumstances&#58; when a persistent infection is present that originates from HPV16 and causes lesions&#44; and when the nanodevice releases a dose as part of a therapeutic vaccination strategy&#46; Performing virtual trials means we can produce results for subsequent analysis and comparison with real-world clinical data&#46;</p></span> <span id="as0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0020">Results and conclusions</span><p id="sp0050" class="elsevierStyleSimplePara elsevierViewall">The simulations enabled us to observe the proliferation of different cell populations considered in the model&#44; levels of viral protein expression and cytokine secretion&#44; transition stages of the developing infectious process-&#44; low- and high-grade intraepithelial lesions&#44; pre-cancer&#44; and cancer status&#46; The virtual patients who did not receive vaccines developed cancer status with peak rates of 18&#46;86&#37;&#46; The patients who received a vaccination strategy reported a significant decrease in their cancer status&#44; with peak rates varying between 0&#46;48&#37; and 3&#46;12&#37;&#44; according to the specifications associated with each vaccine evaluated&#46; The simulated immune system proved responsive to the activity of the virus and the vaccine&#46;</p></span>"
        "secciones" => array:3 [
          0 => array:2 [
            "identificador" => "as0005"
            "titulo" => "Objective"
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          1 => array:2 [
            "identificador" => "as0010"
            "titulo" => "Materials and methods"
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          2 => array:2 [
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      "es" => array:3 [
        "titulo" => "Resumen"
        "resumen" => "<span id="as0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0030">Objetivo</span><p id="sp0055" class="elsevierStyleSimplePara elsevierViewall">Evaluar el modelo de vida artificial que simula comportamientos basados en interacciones que emergen entre el sistema inmune humano&#44; ciclo de vida del virus de papiloma humano tipo 16 y algunos tipos de vacunas terap&#233;uticas&#44; a trav&#233;s de experimentos virtuales que se corren sobre el prototipo construido&#46;</p></span> <span id="as0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0035">Materiales y m&#233;todos</span><p id="sp0060" class="elsevierStyleSimplePara elsevierViewall">Bajo t&#233;cnicas de vida artificial desarrollamos el prototipo HPV16-ALIFE para ser utilizado como laboratorio virtual&#46; Para evaluar el modelo&#44; analizamos las respuestas del sistema inmune simulado en ambas circunstancias&#58; cuando se presenta una infecci&#243;n persistente que se origina en HPV16 y causa lesiones&#44; y cuando el nanodispositivo libera una dosis que hace parte de una estrategia de vacunaci&#243;n terap&#233;utica&#46; La ejecuci&#243;n de ensayos virtuales permite producir resultados para su posterior an&#225;lisis y confrontaci&#243;n con datos cl&#237;nicos del mundo real&#46;</p></span> <span id="as0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0040">Resultados y conclusiones</span><p id="sp0065" class="elsevierStyleSimplePara elsevierViewall">Las simulaciones realizadas permitieron observar la proliferaci&#243;n de diferentes poblaciones celulares consideradas en el modelo&#44; niveles de expresi&#243;n de prote&#237;nas virales y secreci&#243;n de citoquinas&#44; estados de transici&#243;n del proceso infeccioso en desarrollo&#44; lesiones intraepiteliales de bajo y alto grado&#44; condiciones de pre-c&#225;ncer y c&#225;ncer&#46; Pacientes virtuales que no recibieron vacunas&#44; desarrollaron condiciones de c&#225;ncer con tasas m&#225;ximas de 18&#46;86&#37;&#46; Pacientes que recibieron alguna estrategia de vacunaci&#243;n&#44; reportaron un descenso significativo en su condici&#243;n de c&#225;ncer&#44; con tasas m&#225;ximas que variaron entre 0&#46;48&#37; y 3&#46;12&#37;&#44; seg&#250;n las especificaciones asociadas a cada vacuna en evaluaci&#243;n&#46; El sistema inmune simulado mostr&#243; tener capacidad de respuesta ante la actividad del virus y la vacuna&#46;</p></span>"
        "secciones" => array:3 [
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            "identificador" => "as0020"
            "titulo" => "Objetivo"
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          1 => array:2 [
            "identificador" => "as0025"
            "titulo" => "Materiales y m&#233;todos"
          ]
          2 => array:2 [
            "identificador" => "as0030"
            "titulo" => "Resultados y conclusiones"
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        ]
      ]
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          "en" => "<p id="sp0005" class="elsevierStyleSimplePara elsevierViewall">Diagram of the experimental design of the HPV16-ALIFE prototype&#46; This diagram represents the set of experiments run on the prototype developed&#46; The simulated patients are confirmed HPV16 positive cases who do not report any other concomitant viral infection&#46; Among the experiments performed&#44; some patients receive vaccines and others do not&#46; In the group of patients who are given vaccines&#44; some of them receive non-adjuvanted vaccines &#40;left side&#41; while others receive adjuvanted vaccines &#40;right side&#41;&#46; Each rectangle in the diagram represents a type of experiment and the corresponding text states the particular load and the specific adjuvant that are simulated&#46; The figure on the lower left-hand side represents the three phases scheduled to run&#46; The green-coloured ovals represent the number of trials to be performed in phase I&#46; The purple ovals indicate the number of tests to be performed in phase II&#46; The orange-coloured ovals correspond to the number of tests conducted in phase iii&#46; On the right side of the figure&#44; the ellipses above the rectangles correspond to the total number of experiments performed&#44; and the associated colour represents the phase in which these experiments are performed&#46; DC&#58; dendritic cells&#46; &#40;For interpretation of the references to colour in this figure legend&#44; the reader is referred to the web version of this article&#46;&#41;</p>"
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          "en" => "<p id="sp0010" class="elsevierStyleSimplePara elsevierViewall">Functional logic implemented in the HPV16-ALIFE prototype&#46; The figure summarises the logic with which the functional prototype of this model was developed&#46; In the first instance&#44; the exchange relationships between the various domains of the model can be seen&#46; In the second instance&#44; the key interactions are established that allow the definition of an appropriate feedback process between the components and the parameters &#40;global and control&#41;&#46; The left side of the figure represents the external perspective of the model and the right side&#44; the internal perspective&#46; The arrows determine the direction of the interactions that emerge between domains&#46; The green arrows indicate that the interactions originate in the HPV16 life cycle&#46; The yellow arrows indicate interactions that arise from therapeutic vaccines&#46; &#40;For interpretation of the references to colour in this figure legend&#44; the reader is referred to the web version of this article&#46;&#41;</p>"
        ]
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          "en" => "<p id="sp0015" class="elsevierStyleSimplePara elsevierViewall">Graphical user interface &#40;GUI&#41; of the HPV16-ALIFE prototype&#46; This image shows the standard GUI of the HPV16-ALIFE prototype on which the user can set the initial parameters and observe the evolution of its components during the simulation&#46; A set of sliders and switches are available that allow the user to set the initial conditions prior to starting a simulation or during its execution&#46; These criteria include&#58; size of the initial progenitor cell population&#44; previous state of the cells &#40;healthy or infected&#41;&#44; preliminary infection &#40;chronic or acute&#41;&#44; and certain vaccine specifications &#40;load&#44; dose&#44; frequency&#44; and adjuvants&#41;&#46; The evolution of the simulation can be observed on a main monitor&#44; 166 secondary monitors&#44; and 9 trend graphs&#46; In addition&#44; there is a command centre area &#40;bottom left of the image&#41;&#44; where the model reports the week in which a vaccine dose is actually delivered&#46;</p>"
        ]
      ]
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        "identificador" => "f0020"
        "etiqueta" => "Fig&#46; 4"
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          "en" => "<p id="sp0020" class="elsevierStyleSimplePara elsevierViewall">Trend observed in the lesions provoked by the virus in each of the experimental conditions&#46; The graphs illustrate the behaviour of the different lesions caused by HPV16&#44; comparing the trend observed in the lesion with each of the experiments carried out&#46; &#40;A&#41; Trend in cancer conditions&#46; &#40;B&#41; Trend in pre-cancer conditions&#46; &#40;C&#41; Trend in CIN1 lesions&#46; &#40;D&#41; Trend in CIN2 lesions&#46; &#40;E&#41; Trend in CIN3 lesions&#46; EXP-1&#58; trend in patients not receiving vaccine&#59; EXP-2&#58; trend in patients receiving therapeutic vaccine with dendritic cells &#40;DC&#41;&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL&#59; EXP-3&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;100&#8239;&#956;g&#47;mL&#59; EXP-4&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;1000&#8239;&#956;g&#47;mL&#59; EXP-5&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL with IL-2 adjuvant&#59; EXP-6&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL with Poly I&#58;C adjuvant as TLR3 ligand&#59; EXP-7&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL with CpG adjuvant as TLR9 ligand&#46;</p>"
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        "identificador" => "f0025"
        "etiqueta" => "Fig&#46; 5"
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        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr5.jpeg"
            "Alto" => 1500
            "Ancho" => 2008
            "Tamanyo" => 298679
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          "en" => "<p id="sp0025" class="elsevierStyleSimplePara elsevierViewall">Comparison of trends observed between experiments on IL-12 cytokine&#44; cytotoxic T lymphocyte &#40;CTL&#41; population&#44; and E6 and E7 viral oncoproteins&#46; The graphs display the behaviour of IL-12 cytokine secretion&#44; E6 and E7 viral oncoprotein expression&#44; and CTL population proliferation in conditions of persistent infection caused by HPV16&#44; comparing the trend in evaluation against each of the experiments performed&#46; &#40;A&#41; Trend in IL-12 secretion&#46; &#40;B&#41; Trend in CTL population proliferation&#46; &#40;C&#41; Trend levels of viral E6 oncoprotein expression&#46; &#40;D&#41; Trend in viral oncoprotein E7 expression&#46; EXP-1&#58; trend in patients not receiving vaccine&#59; EXP-2&#58; trend in patients receiving therapeutic vaccine with dendritic cells &#40;DC&#41;&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL&#59; EXP-3&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;100&#8239;&#956;g&#47;mL&#59; EXP-4&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;1000&#8239;&#956;g&#47;mL&#59; EXP-5&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL with adjuvant IL-2&#59; EXP-6&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL with adjuvant Poly I&#58;C as TLR3 ligand&#59; EXP-7&#58; trend in patients receiving therapeutic vaccine DC&#8239;&#61;&#8239;10&#8239;&#956;g&#47;mL with adjuvant&#46;</p>"
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            "imagen" => "gr6.jpeg"
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          "en" => "<p id="sp0030" class="elsevierStyleSimplePara elsevierViewall">Proliferation of cytotoxic T lymphocytes &#40;CTL&#41; from adjuvanted vaccines observed in the HPV16-ALIFE prototype&#46; The blue line corresponds to the trend in phase I experiments &#40;viral proteins in active state&#41;&#46; The red line depicts the trend of phase II experiments &#40;E7 protein in inactive state&#41;&#46; The green line represents the trend of phase III experiments &#40;E6 protein in an inactive state&#41;&#46; At the bottom of the graph&#44; each of the adjuvants tested &#40;IL-2&#44; Poly I&#58;C as TLR3 ligand&#44; CpG as TLR9 ligand&#41; and the maximum number of doses actually applied by the model &#40;1&#44; 2 or 3 doses&#41;&#44; according to the conditions of its environment&#44; are indicated&#46; DC&#58; dendritic cells&#46; &#40;For interpretation of the references to colour in this figure legend&#44; the reader is referred to the web version of this article&#46;&#41;</p>"
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          "en" => "<p id="sp0035" class="elsevierStyleSimplePara elsevierViewall">Efficacy analyses of adjuvanted and non-adjuvanted vaccines tested in the HPV16-ALIFE prototype&#46; The figure presents a comparison of the effect observed on the different lesions caused by HPV16 infection &#40;CIN1&#44; CIN2&#44; CIN3&#44; pre-cancer&#44; and cancer&#41; in the experiments run during the 3 planned phases&#46; &#40;A&#41; The trend observed in the therapeutic vaccine experiments without adjuvants&#44; with dendritic cell &#40;DC&#41; loads of 10&#44; 100&#44; and 1000&#8239;&#956;g&#47;mL&#46; &#40;B&#41; The trend seen in the therapeutic vaccine experiments with adjuvant&#44; with DC load of 10&#8239;&#956;g&#47;mL&#44; with which 3 different adjuvants were tested&#58; IL-2&#44; Poly I&#58;C as TLR3 ligand&#44; and CpG as TLR9 ligand&#46; The blue lines indicate the trend observed in CIN1 lesions&#46; The yellow lines reflect the trend observed in CIN2 lesions&#46; Green lines correspond to CIN3 lesions&#46; The purple lines reflect the pre-cancer stage&#46; The red lines depict the trend observed in cancer conditions&#46; &#40;For interpretation of the references to colour in this figure legend&#44; the reader is referred to the web version of this article&#46;&#41;</p>"
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              "identificador" => "bb0005"
              "etiqueta" => "1&#46;"
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                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "A growth model of human papillomavirus type 16 designed from cellular automata and agent-based models"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:2 [
                            0 => "M&#46;E&#46; Escobar-Ospina"
                            1 => "J&#46; G&#243;mez-Perdomo"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1016/j.artmed.2012.11.001"
                      "Revista" => array:6 [
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                        "fecha" => "2013"
                        "volumen" => "57"
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                      ]
                    ]
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                ]
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            1 => array:3 [
              "identificador" => "bb0010"
              "etiqueta" => "2&#46;"
              "referencia" => array:1 [
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                    0 => array:2 [
                      "titulo" => "NetLogo&#46; Center for Connected Learning and Computer-Based Modeling&#44; Northwestern University&#44; Evanston&#44; IL"
                      "autores" => array:1 [
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                  "host" => array:1 [
                    0 => array:1 [
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            2 => array:3 [
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                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Human papillomavirus type 16 E7 oncoprotein-induced abnormal centrosome synthesis is an early event in the evolving malignant phenotype"
                      "autores" => array:1 [
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                          "etal" => false
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                            0 => "S&#46; Duensing"
                            1 => "A&#46; Duensing"
                            2 => "C&#46;P&#46; Crump"
                            3 => "K&#46; M&#252;nger"
                          ]
                        ]
                      ]
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                  ]
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                        "fecha" => "2001"
                        "volumen" => "61"
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                        "link" => array:1 [
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                            "web" => "Medline"
                          ]
                        ]
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                    ]
                  ]
                ]
              ]
            ]
            3 => array:3 [
              "identificador" => "bb0020"
              "etiqueta" => "4&#46;"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Interleukin-12 gene adjuvant increases the immunogenicity of virus-like particles of human papillomavirus type 16 regional variant strain"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
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                            0 => "L&#46; Wei"
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                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1016/j.bjid.2013.05.015"
                      "Revista" => array:7 [
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                        "fecha" => "2014"
                        "volumen" => "18"
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                        "paginaInicial" => "65"
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                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/24120826"
                            "web" => "Medline"
                          ]
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                      ]
                    ]
                  ]
                ]
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              "identificador" => "bb0025"
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                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Regulation of the induction and function of cytotoxic T limphocytes by natural killer T cell"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:2 [
                            0 => "H&#46; Ito"
                            1 => "M&#46; Seishima"
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                      ]
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                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1155/2010/641757"
                      "Revista" => array:3 [
                        "tituloSerie" => "J Biomed Biotechnol"
                        "fecha" => "2010"
                        "itemHostRev" => array:3 [
                          "pii" => "S0091674920301913"
                          "estado" => "S300"
                          "issn" => "00916749"
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                      "titulo" => "Characterization of IgA response among women with incident HPV 16 infection"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
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Article information

ISSN: 24451460
Original language: English

DOI:10.1016/j.vacune.2022.06.001

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