A Genuinely Hybrid, Multiscale 3D Cancer Invasion and Metastasis Modelling Framework.

We introduce in this paper substantial enhancements to a previously proposed hybrid multiscale cancer invasion modelling framework to better reflect the biological reality and dynamics of cancer. These model updates contribute to a more accurate representation of cancer dynamics, they provide deeper insights and enhance our predictive capabilities. Key updates include the integration of porous medium-like diffusion for the evolution of Epithelial-like Cancer Cells and other essential cellular constituents of the system, more realistic modelling of Epithelial-Mesenchymal Transition and Mesenchymal-Epithelial Transition models with the inclusion of Transforming Growth Factor beta within the tumour microenvironment, and the introduction of Compound Poisson Process in the Stochastic Differential Equations that describe the migration behaviour of the Mesenchymal-like Cancer Cells. Another innovative feature of the model is its extension into a multi-organ metastatic framework. This framework connects various organs through a circulatory network, enabling the study of how cancer cells spread to secondary sites.

Uridine 5'-Diphospho-glucuronosyltransferase 1A3 (UGT1A3) Prediction of Hepatic Clearance of Organic Anion Transporting Polypeptide 1B3 (OATP1B3) Substrate Telmisartan by Glucuronidation Using In Vitro-In Vivo Extrapolation (IVIVE).

BACKGROUND AND OBJECTIVE: The prediction of pharmacokinetic parameters for drugs metabolised by cytochrome P450 enzymes has been the subject of active research for many years, while the application of in vitro-in vivo extrapolation (IVIVE) techniques for non-cytochrome P450 enzymes has not been thoroughly evaluated. There is still no established quantitative method for predicting hepatic clearance of drugs metabolised by uridine 5'-diphospho-glucuronosyltransferases (UGTs), not to mention those which undergo hepatic uptake. The objective of the study was to predict the human hepatic clearance for telmisartan based on in vitro metabolic stability and hepatic uptake results. METHODS: Telmisartan was examined in liver systems, allowing to estimate intrinsic clearance (CLint, in vitro) based on the substrate disappearance rate with the use of liquid chromatography tandem mass spectrometry (LC-MS/MS) technique. Obtained CLint, in vitro values were corrected for corresponding unbound fractions. Prediction of human hepatic clearance was made from scaled unbound CLint, in vitro data with the use of the well-stirred model, and finally referenced to the literature value of observed clearance in humans, allowing determination of the essential scaling factors. RESULTS: The in vitro scaled CLint, in vitro by UGT1A3 was assessed using three systems, human hepatocytes, liver microsomes, and recombinant enzymes. Obtained values were scaled and hepatic metabolism clearance was predicted, resulting in significant clearance underprediction. Utilization of the extended clearance concept (ECC) and hepatic uptake improved prediction of hepatic metabolism clearance. The scaling factors for hepatocytes, assessing the in vitro-in vivo difference, changed from sixfold difference to only twofold difference with the application of the ECC. CONCLUSIONS: The study showed that taking into consideration hepatic uptake of a drug allows us to obtain satisfactory scaling factors, hence enabling the prediction of in vivo hepatic glucuronidation from in vitro data.

Integrated multi-omics analysis and machine learning developed a prognostic model based on mitochondrial function in a large multicenter cohort for Gastric Cancer.

BACKGROUND: Gastric cancer (GC) is a common and aggressive type of cancer worldwide. Despite recent advancements in its treatment, the prognosis for patients with GC remains poor. Understanding the mechanisms of cell death in GC, particularly those related to mitochondrial function, is crucial for its development and progression. However, more research is needed to investigate the significance of the interaction between mitochondrial function and GC cell death. METHODS: We employed a robust computational framework to investigate the role of mitochondria-associated proteins in the progression of GC in a cohort of 1,199 GC patients. Ten machine learning algorithms were utilized and combined into 101 unique combinations. Ultimately, we developed a Mitochondrial-related-Score (MitoScore) using the machine learning model that exhibited the best performance. We observed the upregulation of LEMT2 and further explored its function in tumor progression. Mitochondrial functions were assessed by measuring mitochondrial ATP, mitochondrial membrane potential, and levels of lactate, pyruvate, and glucose. RESULTS: MitoScore showed significant correlations with GC immune and metabolic functions. The higher MitoScore subgroup exhibited enriched metabolic pathways and higher immune activity. Overexpression of LETM2 (leucine zipper and EF-hand containing transmembrane protein 2) significantly enhanced tumor proliferation and metastasis. LETM2 plays a role in promoting GC cell proliferation by activating the mTOR pathway, maintaining mitochondrial homeostasis, and promoting glycolysis. CONCLUSION: The powerful machine learning framework highlights the significant potential of MitoScore in providing valuable insights and accurate assessments for individuals with GC. This study also enhances our understanding of LETM2 as an oncogene signature in GC. LETM2 may promote tumor progression by maintaining mitochondrial health and activating glycolysis, offering potential targets for diagnosis, treatment, and prognosis of GC.

Three-Dimensional Cultivation a Valuable Tool for Modelling Canine Mammary Gland Tumour Behaviour In Vitro.

Cell cultivation has been one of the most popular methods in research for decades. Currently, scientists routinely use two-dimensional (2D) and three-dimensional (3D) cell cultures of commercially available cell lines and primary cultures to study cellular behaviour, responses to stimuli, and interactions with their environment in a controlled laboratory setting. In recent years, 3D cultivation has gained more attention in modern biomedical research, mainly due to its numerous advantages compared to 2D cultures. One of the main goals where 3D culture models are used is the investigation of tumour diseases, in both animals and humans. The ability to simulate the tumour microenvironment and design 3D masses allows us to monitor all the processes that take place in tumour tissue created not only from cell lines but directly from the patient's tumour cells. One of the tumour types for which 3D culture methods are often used in research is the canine mammary gland tumour (CMT). The clinically similar profile of the CMT and breast tumours in humans makes the CMT a suitable model for studying the issue not only in animals but also in women.

A novel simulation-based analysis of a stochastic HIV model with the time delay using high order spectral collocation technique.

The economic impact of Human Immunodeficiency Virus (HIV) goes beyond individual levels and it has a significant influence on communities and nations worldwide. Studying the transmission patterns in HIV dynamics is crucial for understanding the tracking behavior and informing policymakers about the possible control of this viral infection. Various approaches have been adopted to explore how the virus interacts with the immune system. Models involving differential equations with delays have become prevalent across various scientific and technical domains over the past few decades. In this study, we present a novel mathematical model comprising a system of delay differential equations to describe the dynamics of intramural HIV infection. The model characterizes three distinct cell sub-populations and the HIV virus. By incorporating time delay between the viral entry into target cells and the subsequent production of new virions, our model provides a comprehensive understanding of the infection process. Our study focuses on investigating the stability of two crucial equilibrium states the infection-free and endemic equilibriums. To analyze the infection-free equilibrium, we utilize the LaSalle invariance principle. Further, we prove that if reproduction is less than unity, the disease free equilibrium is locally and globally asymptotically stable. To ensure numerical accuracy and preservation of essential properties from the continuous mathematical model, we use a spectral scheme having a higher-order accuracy. This scheme effectively captures the underlying dynamics and enables efficient numerical simulations.

Assessment of human dermal absorption of flame retardant additives in polyethylene and polypropylene microplastics using 3D human skin equivalent models.

To overcome ethical and technical challenges impeding the study of human dermal uptake of chemical additives present in microplastics (MPs), we employed 3D human skin equivalent (3D-HSE) models to provide first insights into the dermal bioavailability of polybrominated diphenyl ether (PBDEs) present in MPs; and evaluated different factors influencing human percutaneous absorption of PBDEs under real-life exposure scenario. PBDEs were bioavailable to varying degrees (up to 8 % of the exposure dose) and percutaneous permeation was evident, albeit at low levels (≤0.1 % of the exposure dose). While the polymer type influenced the release of PBDEs from the studied MPs to the skin, the polymer type was less important in driving the percutaneous absorption of PBDEs. The absorbed fraction of PBDEs was strongly correlated (r2 = 0.88) with their water solubility, while the dermal permeation coefficient Papp of PBDEs showed strong association with their molecular weight and logKOW. More sweaty skin resulted in higher bioavailability of PBDEs from dermal contact with MPs than dry skin. Overall, percutaneous absorption of PBDEs upon skin contact with MPs was evident, highlighting, for the first time, the potential significance of the dermal pathway as an important route of human exposure to toxic additive chemicals in MPs.

Taurine activates the AKT-mTOR axis to restore muscle mass and contractile strength in human 3D in vitro models of steroid myopathy.

Steroid myopathy is a clinically challenging condition exacerbated by prolonged corticosteroid use or adrenal tumors. In this study, we engineered a functional three-dimensional (3D) in vitro skeletal muscle model to investigate steroid myopathy. By subjecting our bioengineered muscle tissues to dexamethasone treatment, we reproduced the molecular and functional aspects of this disease. Dexamethasone caused a substantial reduction in muscle force, myotube diameter and induced fatigue. We observed nuclear translocation of the glucocorticoid receptor (GCR) and activation of the ubiquitin-proteasome system within our model, suggesting their coordinated role in muscle atrophy. We then examined the therapeutic potential of taurine in our 3D model for steroid myopathy. Our findings revealed an upregulation of phosphorylated AKT by taurine, effectively countering the hyperactivation of the ubiquitin-proteasomal pathway. Importantly, we demonstrate that discontinuing corticosteroid treatment was insufficient to restore muscle mass and function. Taurine treatment, when administered concurrently with corticosteroids, notably enhanced contractile strength and protein turnover by upregulating the AKT-mTOR axis. Our model not only identifies a promising therapeutic target, but also suggests combinatorial treatment that may benefit individuals undergoing corticosteroid treatment or those diagnosed with adrenal tumors.

Measuring mechanical cues for modeling the stromal matrix in 3D cell cultures.

A breast-cancer tumor develops within a stroma, a tissue where a complex extracellular matrix surrounds cells, mediating the cancer progression through biomechanical and -chemical cues. Current materials partially mimic the stromal matrix in 3D cell cultures but methods for measuring the mechanical properties of the matrix at cell-relevant-length scales and stromal-stiffness levels are lacking. Here, to address this gap, we developed a characterization approach that employs probe-based microrheometry and Bayesian modeling to quantify length-scale-dependent mechanics and mechanical heterogeneity as in the stromal matrix. We examined the interpenetrating network (IPN) composed of alginate scaffolds (for adjusting mechanics) and type-1 collagen (a stromal-matrix constituent). We analyzed viscoelasticity: absolute-shear moduli (stiffness/elasticity) and phase angles (viscous and elastic characteristics). We determined the relationship between microrheometry and rheometry information. Microrheometry reveals lower stiffness at cell-relevant scales, compared to macroscale rheometry, with dependency on the length scale (10 to 100 µm). These data show increasing IPN stiffness with crosslinking until saturation (≃15 mM of Ca2+). Furthermore, we report that IPN stiffness can be adjusted by modulating collagen concentration and interconnectivity (by polymerization temperature). The IPNs are heterogeneous structurally (in SEM) and mechanically. Interestingly, increased alginate crosslinking changes IPN heterogeneity in stiffness but not in phase angle, until the saturation. In contrast, such changes are undetectable in alginate scaffolds. Our nonlinear viscoelasticity analysis at tumor-cell-exerted strains shows that only the softer IPNs stiffen with strain, like the stromal-collagen constituent. In summary, our approach can quantify the stromal-matrix-related viscoelasticity and is likely applicable to other materials in 3D culture.

Linear stability for a free boundary problem modeling the growth of tumor cord with time delay.

This paper was concerned with a free boundary problem modeling the growth of tumor cord with a time delay in cell proliferation, in which the cell location was incorporated, the domain was bounded in $ \mathbb{R}^2 $, and its boundary included two disjoint closed curves, one fixed and the other moving and a priori unknown. A parameter $ \mu $ represents the aggressiveness of the tumor. We proved that there exists a unique radially symmetric stationary solution for sufficiently small time delay, and this stationary solution is linearly stable under the nonradially symmetric perturbations for any $ \mu > 0 $. Moreover, adding the time delay in the model leads to a larger stationary tumor. If the tumor aggressiveness parameter is bigger, the time delay has a greater effect on the size of the stationary tumor, but it has no effect on the stability of the stationary solution.

Longtime evolution and stationary response of a stochastic tumor-immune system with resting T cells.

In this paper, we take the resting T cells into account and interpret the progression and regression of tumors by a predator-prey like tumor-immune system. First, we construct an appropriate Lyapunov function to prove the existence and uniqueness of the global positive solution to the system. Then, by utilizing the stochastic comparison theorem, we prove the moment boundedness of tumor cells and two types of T cells. Furthermore, we analyze the impact of stochastic perturbations on the extinction and persistence of tumor cells and obtain the stationary probability density of the tumor cells in the persistent state. The results indicate that when the noise intensity of tumor perturbation is low, tumor cells remain in a persistent state. As this intensity gradually increases, the population of tumors moves towards a lower level, and the stochastic bifurcation phenomena occurs. When it reaches a certain threshold, instead the number of tumor cells eventually enter into an extinct state, and further increasing of the noise intensity will accelerate this process.

Matrix confinement modulates 3D spheroid sorting and burst-like collective migration.

While it is known that cells with differential adhesion tend to segregate and preferentially sort, the physical forces governing sorting and invasion in heterogeneous tumors remain poorly understood. To investigate this, we tune matrix confinement, mimicking changes in the stiffness and confinement of the tumor microenvironment, to explore how physical confinement influences individual and collective cell migration in 3D spheroids. High levels of confinement lead to cell sorting while reducing matrix confinement triggers the collective fluidization of cell motion. Cell sorting, which depends on cell-cell adhesion, is crucial to this phenomenon. Burst-like migration does not occur for spheroids that have not undergone sorting, regardless of the degree of matrix confinement. Using computational Self-Propelled Voronoi modeling, we show that spheroid sorting and invasion into the matrix depend on the balance between cell-generated forces and matrix resistance. The findings support a model where matrix confinement modulates 3D spheroid sorting and unjamming in an adhesion-dependent manner, providing insights into the mechanisms of cell sorting and migration in the primary tumor and toward distant metastatic sites. STATEMENT OF SIGNIFICANCE: The mechanical properties of the tumor microenvironment significantly influence cancer cell migration within the primary tumor, yet how these properties affect intercellular interactions in heterogeneous tumors is not well understood. By utilizing calcium and calcium chelators, we dynamically alter collagen-alginate hydrogel stiffness and investigate tumor cell behavior within co-culture spheroids in response to varying degrees of matrix confinement. High confinement is found to trigger cell sorting while reducing confinement for sorted spheroids facilitates collective cell invasion. Notably, without prior sorting, spheroids do not exhibit burst-like migration, regardless of confinement levels. This work establishes that matrix confinement and intercellular adhesion regulate 3D spheroid dynamics, offering insights into cellular organization and migration within the primary tumor.

The influence of microwave ablation parameters on the positioning of trocar in different cancerous tissues: a numerical study.

The present study analyzed the microwave ablation of cancerous tumors located in six major cancer-prone organs and estimated the significance of input power and treatment time parameters in the apt positioning of the trocar into the tissue during microwave ablation. The present study has considered a three-dimensional two-compartment tumour-embedded tissue model. FEA based COMSOL Multiphysics software with inbuilt bioheat transfer, electromagnetic waves, heat transfer in solids and fluids, and laminar flow physics has been used to obtain the numerical results. Based on the mortality rates caused by cancer, the present study has considered six major organs affected by cancer, viz. lung, breast, stomach/gastric, liver, liver (with colon metastasis), and kidney for MWA analysis. The input power (100 W) and ablation times (4 minutes) with apt and inapt positioning of the trocar have been considered to compare the ablation volume of various cancerous tissues. The present study addresses one of the major problems clinicians face, i.e. the proper placement of the trocar due to poor imaging techniques and human error, resulting in incomplete tumor ablation and increased surgical procedures. The highest values of the ablation region have been observed for the liver, colon metastatic liver and breast cancerous tissues compared with other organs at the same operating conditions.

The present study has investigated the application of microwave ablation for cancer treatment in six major organs, specifically emphasizing the evaluation of ablation volume during the procedure. Using COMSOL-Multiphysics software, the study has investigated MWA of tumor embedded organs in the lung, breast, stomach, liver, and kidney. The positioning of the trocar, a crucial element in the treatment process, has been examined to address challenges in effectively ablating tumors.From the results, it has been revealed that liver, colon metastatic liver, and breast cancer tissues exhibited the largest areas of ablation volume compared with other organs.Organs like the breast and hepatic glands, characterized by lower heat capacity and density, have shown larger ablation zones. Trocar positioning significantly influenced the stomach, liver, and kidney, where improper placement led to notable increases in ablation volume, posing a risk of unintended damage to healthy tissue.Further, the study has concluded that precise trocar positioning plays a crucial role in optimizing microwave ablation. This precision has the potential to enhance the effectiveness of cancer treatments while minimizing harm to healthy tissue. The insights gained from this research offer valuable information for clinicians looking to enhance the precision of cancer therapies, ultimately aiming for improved outcomes for patients.

Dosing of Convalescent Plasma and Hyperimmune Anti-SARS-CoV-2 Immunoglobulins: A Phase I/II Dose-Finding Study.

BACKGROUND AND OBJECTIVE: During the COVID-19 pandemic, trials on convalescent plasma (ConvP) were performed without preceding dose-finding studies. This study aimed to assess potential protective dosing regimens by constructing a population pharmacokinetic (popPK) model describing anti-SARS-CoV-2 antibody titers following the administration of ConvP or hyperimmune globulins (COVIg). METHODS: Immunocompromised patients, testing negative for anti-SARS-CoV-2 spike antibodies despite vaccination, received a range of anti-SARS-CoV-2 antibodies in the form of COVIg or ConvP infusion. The popPK analysis was performed using NONMEM v7.4. Monte Carlo simulations were performed to assess potential COVIg and ConvP dosing regimens for prevention of COVID-19. RESULTS: Forty-four patients were enrolled, and data from 42 were used for constructing the popPK model. A two-compartment elimination model with mixed residual error best described the Nab-titers after administration. Inter-individual variation was associated to CL (44.3%), V1 (27.3%), and V2 (29.2%). Lean body weight and type of treatment (ConvP/COVIg) were associated with V1 and V2, respectively. Median elimination half-life was 20 days (interquartile range: 17-25 days). Simulations demonstrated that even monthly infusions of 600 mL of the ConvP or COVIg used in this trial would not achieve potentially protective serum antibody titers for > 90% of the time. However, as a result of hybrid immunity and/or repeated vaccination, plasma donors with extremely high antibody titers are now readily available, and a > 90% target attainment should be possible. CONCLUSION: The results of this study may inform future intervention studies on the prophylactic and therapeutic use of antiviral antibodies in the form of ConvP or COVIg. CLINICAL TRIAL REGISTRATION NUMBER: NL9379 (The Netherlands Trial Register).

Demonstrating Bioequivalence for Two Dose Strengths of Niraparib and Abiraterone Acetate Dual-Action Tablets Versus Single Agents: Utility of Clinical Study Data Supplemented with Modeling and Simulation.

BACKGROUND AND OBJECTIVE: The combination of niraparib and abiraterone acetate (AA) plus prednisone is under investigation for the treatment of patients with metastatic castration-resistant prostate cancer (mCRPC) and metastatic castration-sensitive prostate cancer (mCSPC). Regular-strength (RS) and lower-strength (LS) dual-action tablets (DATs), comprising niraparib 100 mg/AA 500 mg and niraparib 50 mg/AA 500 mg, respectively, were developed to reduce pill burden and improve patient experience. A bioequivalence (BE)/bioavailability (BA) study was conducted under modified fasting conditions in patients with mCRPC to support approval of the DATs. METHODS: This open-label randomized BA/BE study (NCT04577833) was conducted at 14 sites in the USA and Europe. The study had a sequential design, including a 21-day screening phase, a pharmacokinetic (PK) assessment phase comprising three periods [namely (1) single-dose with up to 1-week run-in, (2) daily dose on days 1-11, and (3) daily dose on days 12-22], an extension where both niraparib and AA as single-agent combination (SAC; reference) or AA alone was continued from day 23 until discontinuation, and a 30-day follow-up phase. Patients were randomly assigned in a parallel-group design (four-sequence randomization) to receive a single oral dose of niraparib 100 mg/AA 1000 mg as a LS-DAT or SAC in period 1, and patients continued as randomized into a two-way crossover design during periods 2 and 3 where they received niraparib 200 mg/AA 1000 mg once daily as a RS-DAT or SAC. The design was powered on the basis of crossover assessment of RS-DAT versus SAC. During repeated dosing (periods 2 and 3, and extension phase), all patients also received prednisone/prednisolone 5 mg twice daily. Plasma samples were collected for measurement of niraparib and abiraterone plasma concentrations. Statistical assessment of the RS-DAT and LS-DAT versus SAC was performed on log-transformed pharmacokinetic parameters data from periods 2 and 3 (crossover) and from period 1 (parallel), respectively. Additional paired analyses and model-based bioequivalence assessments were conducted to evaluate the similarity between the LS-DAT and SAC. RESULTS: For the RS-DAT versus SAC, the 90% confidence intervals (CI) of geometric mean ratios (GMR) for maximum concentration at a steady state (Cmax,ss) and area under the plasma concentration-time curve from 0-24 h at a steady state (AUC 0-24h,ss) were respectively 99.18-106.12% and 97.91-104.31% for niraparib and 87.59-106.69 and 86.91-100.23% for abiraterone. For the LS-DAT vs SAC, the 90% CI of GMR for AUC0-72h of niraparib was 80.31-101.12% in primary analysis, the 90% CI of GMR for Cmax,ss and AUC 0-24h,ss of abiraterone was 85.41-118.34% and 86.51-121.64% respectively, and 96.4% of simulated LS-DAT versus SAC BE trials met the BE criteria for both niraparib and abiraterone. CONCLUSIONS: The RS-DAT met BE criteria (range 80%-125%) versus SAC based on 90% CI of GMR for Cmax,ss and AUC 0-24h,ss. The LS-DAT was considered BE to SAC on the basis of the niraparib component meeting the BE criteria in the primary analysis for AUC 0-72h; abiraterone meeting the BE criteria in additional paired analyses based on Cmax,ss and AUC 0-24h,ss; and the percentage of simulated LS-DAT versus SAC BE trials meeting the BE criteria for both. GOV IDENTIFIER: NCT04577833.

Mathematical modeling of combined therapies for treating tumor drug resistance.

Drug resistance is one of the most intractable issues to the targeted therapy for cancer diseases. To explore effective combination therapy schemes, we propose a mathematical model to study the effects of different treatment schemes on the dynamics of cancer cells. Then we characterize the dynamical behavior of the model by finding the equilibrium points and exploring their local stability. Lyapunov functions are constructed to investigate the global asymptotic stability of the model equilibria. Numerical simulations are carried out to verify the stability of equilibria and treatment outcomes using a set of collected model parameters and experimental data on murine colon carcinoma. Simulation results suggest that immunotherapy combined with chemotherapy contributes significantly to the control of tumor growth compared to monotherapy. Sensitivity analysis is performed to identify the importance of model parameters on the variations of model outcomes.

Enhancement of skin tumor laser hyperthermia with Ytterbium nanoparticles: numerical simulation.

Laser hyperthermia therapy (HT) has emerged as a well-established method for treating cancer, yet it poses unique challenges in comprehending heat transfer dynamics within both healthy and cancerous tissues due to their intricate nature. This study investigates laser HT therapy as a promising avenue for addressing skin cancer. Employing two distinct near-infrared (NIR) laser beams at 980 nm, we analyze temperature variations within tumors, employing Pennes' bioheat transfer equation as our fundamental investigative framework. Furthermore, our study delves into the influence of Ytterbium nanoparticles (YbNPs) on predicting temperature distributions in healthy and cancerous skin tissues. Our findings reveal that the application of YbNPs using a Gaussian beam shape results in a notable maximum temperature increase of 5 °C within the tumor compared to nanoparticle-free heating. Similarly, utilizing a flat top beam alongside YbNPs induces a temperature rise of 3 °C. While this research provides valuable insights into utilizing YbNPs with a Gaussian laser beam configuration for skin cancer treatment, a more thorough understanding could be attained through additional details on experimental parameters such as setup, exposure duration, and specific implications for skin cancer therapy.

Combinatorial Cooperativity in miR200-Zeb Feedback Network can Control Epithelial-Mesenchymal Transition.

Carcinomas often utilize epithelial-mesenchymal transition (EMT) programs for cancer progression and metastasis. Numerous studies report SNAIL-induced miR200/Zeb feedback circuit as crucial in regulating EMT by placing cancer cells in at least three phenotypic states, viz. epithelial (E), hybrid (h-E/M), mesenchymal (M), along the E-M phenotypic spectrum. However, a coherent molecular-level understanding of how such a tiny circuit controls carcinoma cell entrance into and residence in various states is lacking. Here, we use molecular binding data and mathematical modeling to report that the miR200/Zeb circuit can essentially utilize combinatorial cooperativity to control E-M phenotypic plasticity. We identify minimal combinatorial cooperativities that give rise to E, h-E/M, and M phenotypes. We show that disrupting a specific number of miR200 binding sites on Zeb as well as Zeb binding sites on miR200 can have phenotypic consequences-the circuit can dynamically switch between two (E, M) and three (E, h-E/M, M) phenotypes. Further, we report that in both SNAIL-induced and SNAIL knock-out miR200/Zeb circuits, cooperative transcriptional feedback on Zeb as well as Zeb translation inhibition due to miR200 are essential for the occurrence of intermediate h-E/M phenotype. Finally, we demonstrate that SNAIL can be dispensable for EMT, and in the absence of SNAIL, the transcriptional feedback can control cell state transition from E to h-E/M, to M state. Our results thus highlight molecular-level regulation of EMT in miR200/Zeb circuit and we expect these findings to be crucial to future efforts aiming to prevent EMT-facilitated dissemination of carcinomas.

A Predictive Toxicokinetic Model for Nickel Leaching from Vascular Stents.

In vitro testing methods offer valuable insights into the corrosion vulnerability of metal implants and enable prompt comparison between devices. However, they fall short in predicting the extent of leaching and the biodistribution of implant byproducts under in vivo conditions. Physiologically based toxicokinetic (PBTK) models are capable of quantitatively establishing such correlations and therefore provide a powerful tool in advancing nonclinical methods to test medical implants and assess patient exposure to implant debris. In this study, we present a multicompartment PBTK model and a simulation engine for toxicological risk assessment of vascular stents. The mathematical model consists of a detailed set of constitutive equations that describe the transfer of nickel ions from the device to peri-implant tissue and circulation and the nickel mass exchange between blood and the various tissues/organs and excreta. Model parameterization was performed using (1) in-house-produced data from immersion testing to compute the device-specific diffusion parameters and (2) full-scale animal in situ implantation studies to extract the mammalian-specific biokinetic functions that characterize the time-dependent biodistribution of the released ions. The PBTK model was put to the test using a simulation engine to estimate the concentration-time profiles, along with confidence intervals through probabilistic Monte Carlo, of nickel ions leaching from the implanted devices and determine if permissible exposure limits are exceeded. The model-derived output demonstrated prognostic conformity with reported experimental data, indicating that it may provide the basis for the broader use of modeling and simulation tools to guide the optimal design of implantable devices in compliance with exposure limits and other regulatory requirements.

Effective vaccination strategies for human papillomavirus (HPV) infection and cervical cancer based on the mathematical model with a stochastic process.

Human papillomavirus (HPV) infection poses a significant risk to women's health by causing cervical cancer. In addition to HPV, cervical cancer incidence rates can be influenced by various factors, including human immunodeficiency virus and herpes, as well as screening policy. In this study, a mathematical model with stochastic processes was developed to analyze HPV transmission between genders and its subsequent impact on cervical cancer incidence. The model simulations suggest that both-gender vaccination is far more effective than female-only vaccination in preventing an increase in cervical cancer incidence. With increasing stochasticity, the difference between the number of patients in the vaccinated group and the number in the nonvaccinated group diminishes. To distinguish the patient population distribution of the vaccinated from the nonvaccinated, we calculated effect size (Cohen's distance) in addition to Student's t-test. The model analysis suggests a threshold vaccination rate for both genders for a clear reduction of cancer incidence when significant stochastic factors are present.