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ABSTRACTCell motility in response to environmental cues forms the basis of many developmental processes in multicellular organisms. One such environmental cue is an electric field (EF), which induces a form of motility known as electrotaxis. Electrotaxis has evolved in a number of cell types to guide wound healing, and has been associated with different cellular processes, suggesting that observed electrotactic behaviour is likely a combination of multiple distinct effects arising from the presence of an EF. In order to determine the different mechanisms by which observed electrotactic behaviour emerges, and thus to design EFs that can be applied to direct and control electrotaxis, researchers require accurate quantitative predictions of cellular responses to externally-applied fields. Here, we use mathematical modelling to formulate and parametrise a variety of hypothetical descriptions of how cell motility may change in response to an EF. We calibrate our model to observed data using synthetic likelihoods and Bayesian sequential learning techniques, and demonstrate that EFs bias cellular motility through only one of a selection of hypothetical mechanisms. We also demonstrate how the model allows us to make predictions about cellular motility under different EFs. The resulting model and calibration methodology will thus form the basis for future data-driven and model-based feedback control strategies based on electric actuation.SIGNIFICANCEElectrotaxis is attracting much interest and development as a technique to control cell migration due to the precision of electric fields as actuation signals. However, precise control of electrotactic migration relies on an accurate model of how cell motility changes in response to applied electric fields. We present and calibrate a parametrised stochastic model that accurately replicates experimental single-cell data and enables the prediction of input–output behaviour while quantifying uncertainty and stochasticity. The model allows us to elucidate and quantify how electric fields perturb the motile behaviour of the cell. This model and the associated simulation-based calibration methodology will be central to future developments in the control of electrotaxis.

Abstract Background Polychlorinated biphenyls (PCBs) are ubiquitous industrial chemicals that persist in the environment and in human fatty tissue. PCBs are related to a class of compounds known as dioxins, specifically 2,3,7,8-TCDD (tetrachloro-dibenzodioxin), which has been implicated as a cause of altered sex ratio, especially in relation to paternal exposures. Methods In the 1960's, serum specimens were collected from pregnant women participating in the Child Health and Development Study in the San Francisco Bay Area. The women were interviewed and their serum samples stored at -20°C. For this study, samples were thawed and a total of eleven PCBs were determined in 399 specimens. Secondary sex ratio, or sex ratio at birth, was evaluated as a function of maternal serum concentrations using log-binomial and logistic regression, controlling for hormonally active medications taken during pregnancy. Results The relative risk of a male birth decreased by 33% comparing women at the 90th percentile of total PCBs with women at the 10th percentile (RR = 0.67; 95% CI, 0.48–0.94; p = 0.02), or by approximately 7% for each 1 μg/L increase in total PCB concentration. Although some congener-specific associations with sex ratio were only marginally statistically significant, all nine PCB congeners with < 30% of samples below the LOQ showed the same direction of association, an improbable finding under the null hypothesis. Conclusion Maternal exposure to PCBs may be detrimental to the success of male sperm or to the survival of male embryos. Findings could be due to contaminants, metabolites or PCBs themselves.

Random walks and related spatial stochastic models have been used in a range of application areas, including animal and plant ecology, infectious disease epidemiology, developmental biology, wound healing and oncology. Classical random walk models assume that all individuals in a population behave independently, ignoring local physical and biological interactions. This assumption simplifies the mathematical description of the population considerably, enabling continuum-limit descriptions to be derived and used in model analysis and fitting. However, interactions between individuals can have a crucial impact on population-level behaviour. In recent decades, research has increasingly been directed towards models that include interactions, including physical crowding effects and local biological processes such as adhesion, competition, dispersal, predation and adaptive directional bias. In this article, we review the progress that has been made with models of interacting individuals. We aim to provide an overview that is accessible to researchers in application areas, as well as to specialist modellers. We focus particularly on derivation of asymptotically exact or approximate continuum-limit descriptions and simplified deterministic models of mean-field behaviour and resulting spatial patterns. We provide worked examples and illustrative results of selected models. We conclude with a discussion of current areas of focus and future challenges.

External (EL) and internal (IL) load are commonly used methods used to quantify training load in team sports. Playing time and playing position may influence the training loads for specific athletes throughout a season. The purpose of the current study was to evaluate the effect of athlete playing status and individual in-season practices on EL and IL across a collegiate women's basketball season. Female basketball athletes were classified as high-minute (HMA; ≥15 min/game) or low-minute (LMA; <15 min/game) and wore microsensors during 53 practices for a total of 583 data points. EL was obtained via an inertial measurement unit (IMU) device that contained a triaxial accelerometer to obtain three-dimensional positioning data. IL and strength training (ST) load were determined via session rating of perceived exertion (sRPE) to create a daily summated value. Descriptive statistics indicate that athletes experienced individual differences in EL, ST, and IL throughout the season. A growth model showed that HMAs experienced higher EL than LMAs at the start of the season for practices (90.21 AU). Across all athletes, IL increased across the season (40.11 AU) and for each 1 unit of change in EL, IL increased by 1.04 AU. Repeated measures correlations identified a large relationship between IL and EL (r = 0.51, p < 0.001). A location-scale model indicated that the within-person variability of IL across all athletes was 3.29 AU but was not due to athlete playing status. It is recommended to base in-season training on individual loads and game demands to promote athlete readiness and improved sport performance.

Background: The cardiovascular impact of cannabis use is incompletely understood. Although evidence links chronic use to an increased risk of disease and adverse cardiovascular events, few studies have investigated the acute effects of cannabis inhalation on subclinical dysfunction. Furthermore, it remains unknown how method of inhalation and cannabinoid profile modify risk. While controlling for inhalation method and the effects of either Δ-9-tetrahydrocannabinol (THC) or cannabidiol (CBD), we examined the acute cardiovascular effects of cannabis use on arterial stiffness, vascular endothelial responsiveness, and cardiac function, as markers of cardiovascular impairment., Methods and Results: Twenty-two young, healthy, cannabis users were assessed for arterial stiffness via pulse wave velocity, vascular endothelial function via brachial artery flow mediated dilation, and cardiac function via echocardiography, before and after (1) smoking THC-predominant cannabis (S-THC), (2) vaporizing THC-predominant THC (V-THC), and (3) vaporizing cannabidiol-predominant cannabis (V-CBD). S-THC and V-THC increased heart rate (S-THC: ∆17±15 bpm, V-THC: ∆16±16 bpm;both P <0.0001) and mean arterial pressure (S-THC: ∆7±6 mm Hg, V-THC: ∆5±5 mm Hg;both P <0.0001) whereas V-CBD did not (∆1±4 bpm, ∆3±4 mm Hg;both P >0.05). After inhalation, pulse wave velocity increased (S-THC: ∆0.29±0.75 m/s, V-THC: ∆0.42±0.74 m/s, V-CBD: ∆0.10±0.44 m/s; P =0.002) and diastolic function was reduced ([early/late ratio] S-THC: ∆-0.2±0.53, V-THC: ∆-0.33±58, V-CBD: ∆0.01±66; P =0.03). Differences in heart rate were related to changes in pulse wave velocity (r 2 =0.2; P =0.0002) and diastolic function (r 2 =0.26; P <0.0001). Inhalation method did not alter these cannabinoid-dependent responses., Conclusions: THC predominant, but not cannabidiol predominant, cannabis elicits increases in heart rate and blood pressure irrespective of inhalation method, which may increase arterial stiffness and reduce diastolic function. These findings implicate THC as a relevant factor for cannabis-related subclinical cardiovascular dysfunction., Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04693884.

Purpose: The distinct physical and environmental stressors of artistic swimming (previously termed synchronized swimming) result in unique hemodynamic stimuli. Given that the hemodynamic stress associated with participation in an exercise modality drives adaptation of the heart and central vasculature, artistic swimming may produce a distinct cardiovascular phenotype. Presumably, athletes competing at the highest levels also have greater training exposure and thus exhibit more adaptation. The purpose of this study was to characterize cardiovascular form and function across the competitive spectrum of artistic swimmers., Methods: Cardiovascular structure and function were compared in a cross-sectional study of healthy controls, varsity, and elite artistic swimmers, using pulse wave analysis, pulse wave velocity, and echocardiographic images both at rest and during isometric handgrip exercise., Results: Aortic stiffness was similar across all groups, as were characteristics of the decomposed aortic pressure waveform. At rest, both varsity and elite swimmers demonstrated similar systolic function compared with controls. However, peak left ventricular twist was greater in varsity and elites (controls: 8.0 ± 3.9, varsity: 12.8 ± 8.6, elites: 13.4 ± 3.9; both P < 0.02). Furthermore, elites demonstrated greater peak left ventricular radial strain (controls: 29.2 ± 9.9, varsity: 32.5 ± 10.3, elites: 53.9 ± 15.1; both P < 0.001) and longitudinal strain (controls: -16.9 ± 1.6, varsity: -16.5 ± 1.8, elites: -19.5 ± 3.2; both P < 0.04). In contrast to controls, both varsity and elite artistic swimmers demonstrated no change in peak late diastolic transmitral filling velocity (controls: Δ0.2 ± 0.04 m·s -1 , varsity: Δ0.06 ± 0.04 m·s -1 , elites: Δ0.05 ± 0.04 m·s -1 ) during isometric handgrip exercise (both P > 0.05), with elites demonstrating lower peak velocity than varsity swimmers ( P = 0.048), indicating preservation of diastolic function., Conclusions: Artistic swimmers demonstrate distinct cardiac physiology at rest and during isometric handgrip, with a greater extent of distinguishing features observed in those competing at the highest level of competition., (Copyright © 2024 by the American College of Sports Medicine.)

The SARS-CoV-2 pandemic has generated a considerable number of infections and associated morbidity and mortality across the world. Recovery from these infections, combined with the onset of large-scale vaccination, have led to rapidly-changing population-level immunological landscapes. In turn, these complexities have highlighted a number of important unknowns related to the breadth and strength of immunity following recovery or vaccination. Using simple mathematical models, we investigate the medium-term impacts of waning immunity against severe disease on immuno-epidemiological dynamics. We find that uncertainties in the duration of severity-blocking immunity (imparted by either infection or vaccination) can lead to a large range of medium-term population-level outcomes (i.e. infection characteristics and immune landscapes). Furthermore, we show that epidemiological dynamics are sensitive to the strength and duration of underlying host immune responses; this implies that determining infection levels from hospitalizations requires accurate estimates of these immune parameters. More durable vaccines both reduce these uncertainties and alleviate the burden of SARS-CoV-2 in pessimistic outcomes. However, heterogeneity in vaccine uptake drastically changes immune landscapes toward larger fractions of individuals with waned severity-blocking immunity. In particular, if hesitancy is substantial, more robust vaccines have almost no effects on population-level immuno-epidemiology, even if vaccination rates are compensatorily high among vaccine-adopters. This pessimistic scenario for vaccination heterogeneity arises because those few individuals that are vaccine-adopters are so readily re-vaccinated that the duration of vaccinal immunity has no appreciable consequences on their immune status. Furthermore, we find that this effect is heightened if vaccine-hesitants have increased transmissibility (e.g. due to riskier behavior). Overall, our results illustrate the necessity to characterize both transmission-blocking and severity-blocking immune time scales. Our findings also underline the importance of developing robust next-generation vaccines with equitable mass vaccine deployment., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Saad-Roy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

A fundamental feature of collective cell migration is phenotypic heterogeneity which, for example, influences tumour progression and relapse. While current mathematical models often consider discrete phenotypic structuring of the cell population, in-line with the 'go-or-grow' hypothesis (Hatzikirou et al., 2012; Stepien et al., 2018), they regularly overlook the role that the environment may play in determining the cells' phenotype during migration. Comparing a previously studied volume-filling model for a homogeneous population of generalist cells that can proliferate, move and degrade extracellular matrix (ECM) (Crossley et al., 2023) to a novel model for a heterogeneous population comprising two distinct sub-populations of specialist cells that can either move and degrade ECM or proliferate, this study explores how different hypothetical phenotypic switching mechanisms affect the speed and structure of the invading cell populations. Through a continuum model derived from its individual-based counterpart, insights into the influence of the ECM and the impact of phenotypic switching on migrating cell populations emerge. Notably, specialist cell populations that cannot switch phenotype show reduced invasiveness compared to generalist cell populations, while implementing different forms of switching significantly alters the structure of migrating cell fronts. This key result suggests that the structure of an invading cell population could be used to infer the underlying mechanisms governing phenotypic switching., Competing Interests: Declaration of competing interest The authors do not have any competing interests to declare., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Pathogens of the enterovirus genus, including poliovirus and coxsackieviruses, typically circulate in the summer months suggesting a possible positive association between warmer weather and transmission. Here we evaluate the environmental and demographic drivers of enterovirus transmission, as well as the implications of climate change for future enterovirus circulation. We leverage pre-vaccination era data on polio in the US as well as data on two enterovirus A serotypes in China and Japan that are known to cause hand, foot, and mouth disease. Using mechanistic modeling and statistical approaches, we find that enterovirus transmission appears positively correlated with temperature although demographic factors, particularly the timing of school semesters, remain important. We use temperature projections from Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate future outbreaks under late 21st-century climate change for Chinese provinces. We find that outbreak size increases with climate change on average, though results differ across climate models depending on the degree of wintertime warming. In the worst-case scenario, we project peak outbreaks in some locations could increase by up to 40%., (© 2024. The Author(s).)

Nonpharmaceutical interventions (NPIs) implemented during the COVID-19 pandemic have disrupted the dynamics of respiratory syncytial virus (RSV) on a global scale; however, the cycling of RSV subtypes in the pre- and post-pandemic period remains poorly understood. Here, we used a two subtype RSV model supplemented with epidemiological data to study the impact of NPIs on the two circulating subtypes, RSV-A and RSV-B. The model is calibrated to historic RSV subtype data from the United Kingdom and Finland and predicts a tendency for RSV-A dominance over RSV-B immediately following the implementation of NPIs. Using a global genetic dataset, we confirm that RSV-A has prevailed over RSV-B in the post-pandemic period, consistent with a higher R 0 for RSV-A. With new RSV infant monoclonals and maternal and elderly vaccines becoming widely available, these results may have important implications for understanding intervention effectiveness in the context of disrupted subtype dynamics., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Epithelial monolayers are some of the best-studied models for collective cell migration due to their abundance in multicellular systems and their tractability. Experimentally, the collective migration of epithelial monolayers can be robustly steered e.g. using electric fields, via a process termed electrotaxis. Theoretically, however, the question of how to design an electric field to achieve a desired spatiotemporal movement pattern is underexplored. In this work, we construct and calibrate an ordinary differential equation model to predict the average velocity of the centre of mass of a cellular monolayer in response to stimulation with an electric field. We use this model, in conjunction with optimal control theory, to derive physically realistic optimal electric field designs to achieve a variety of aims, including maximising the total distance travelled by the monolayer, maximising the monolayer velocity, and keeping the monolayer velocity constant during stimulation. Together, this work is the first to present a unified framework for optimal control of collective monolayer electrotaxis and provides a blueprint to optimally steer collective migration using other external cues., (© 2024. The Author(s).)

The spatiotemporal coordination and regulation of cell proliferation is fundamental in many aspects of development and tissue maintenance. Cells have the ability to adapt their division rates in response to mechanical constraints, yet we do not fully understand how cell proliferation regulation impacts cell migration phenomena. Here, we present a minimal continuum model of cell migration with cell cycle dynamics, which includes density-dependent effects and hence can account for cell proliferation regulation. By combining minimal mathematical modeling, Bayesian inference, and recent experimental data, we quantify the impact of tissue crowding across different cell cycle stages in epithelial tissue expansion experiments. Our model suggests that cells sense local density and adapt cell cycle progression in response, during G1 and the combined S/G2/M phases, providing an explicit relationship between each cell-cycle-stage duration and local tissue density, which is consistent with several experimental observations. Finally, we compare our mathematical model's predictions to different experiments studying cell cycle regulation and present a quantitative analysis on the impact of density-dependent regulation on cell migration patterns. Our work presents a systematic approach for investigating and analyzing cell cycle data, providing mechanistic insights into how individual cells regulate proliferation, based on population-based experimental measurements., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Many physical and biological systems rely on the progression of material through multiple independent stages. In viral replication, for example, virions enter a cell to undergo a complex process comprising several disparate stages before the eventual accumulation and release of replicated virions. While such systems may have some control over the internal dynamics that make up this progression, a challenge for many is to regulate behavior under what are often highly variable external environments acting as system inputs. In this work, we study a simple analog of this problem through a linear multicompartment model subject to a stochastic input in the form of a mean-reverting Ornstein-Uhlenbeck process, a type of Gaussian process. By expressing the system as a multidimensional Gaussian process, we derive several closed-form analytical results relating to the covariances and autocorrelations of the system, quantifying the smoothing effect discrete compartments afford multicompartment systems. Semianalytical results demonstrate that feedback and feedforward loops can enhance system robustness, and simulation results probe the intractable problem of the first passage time distribution, which has specific relevance to eventual cell lysis in the viral replication cycle. Finally, we demonstrate that the smoothing seen in the process is a consequence of the discreteness of the system, and does not manifest in systems with continuous transport. While we make progress through analysis of a simple linear problem, many of our insights are applicable more generally, and our work enables future analysis into multicompartment processes subject to stochastic inputs.

Background: Cell migration and invasion are well-coordinated processes in development and disease but remain poorly understood. We previously showed that highly migratory neural crest (NC) cells share a 45-gene panel with other cell invasion phenomena, including cancer. To identify critical genes of the 45-gene panel, we performed a high-throughput siRNA screen and used statistical and deep learning methods to compare NC- versus non-NC-derived human cell lines., Results: We find 14 out of 45 genes significantly reduces c8161 melanoma cell migration; only 4 are shared with HT1080 fibrosarcoma cells (BMP4, ITGB1, KCNE3, RASGRP1). Deep learning attention network analysis identified distinct cell-cell interaction patterns and significant alterations after BMP4 or RASGRP1 knockdown in c8161 cells. Addition of recombinant proteins to the culture media identified 5 out of the 10 known secreted molecules stimulate c8161 cell migration, including BMP4. BMP4 siRNA knockdown inhibited c8161 cell invasion in vivo and in vitro ; however, its addition to the culture media rescued c8161 cell invasion., Conclusion: A high-throughput screen and deep learning rapidly distilled a 45-gene panel to a small subset of genes that appear critical to melanoma cell invasion and warrant deeper in vivo functional analysis for their role in driving the neural crest.

Mycobacterium tuberculosis (M.tb.) infection leads to over 1.5 million deaths annually, despite widespread vaccination with BCG at birth. Causes for the ongoing tuberculosis endemic are complex and include the failure of BCG to protect many against progressive pulmonary disease. Host genetics is one of the known factors implicated in susceptibility to primary tuberculosis, but less is known about the role that host genetics plays in controlling host responses to vaccination against M.tb. Here, we addressed this gap by utilizing Diversity Outbred (DO) mice as a small animal model to query genetic drivers of vaccine-induced protection against M.tb. DO mice are a highly genetically and phenotypically diverse outbred population that is well suited for fine genetic mapping. Similar to outcomes in people, our previous studies demonstrated that DO mice have a wide range of disease outcomes following BCG vaccination and M.tb. challenge. In the current study, we used a large population of BCG-vaccinated/M.tb.-challenged mice to perform quantitative trait loci mapping of complex infection traits; these included lung and spleen M.tb. burdens, as well as lung cytokines measured at necropsy. We found sixteen chromosomal loci associated with complex infection traits and cytokine production. QTL associated with bacterial burdens included a region encoding major histocompatibility antigens that are known to affect susceptibility to tuberculosis, supporting validity of the approach. Most of the other QTL represent novel associations with immune responses to M.tb. and novel pathways of cytokine regulation. Most importantly, we discovered that protection induced by BCG is a multigenic trait, in which genetic loci harboring functionally-distinct candidate genes influence different aspects of immune responses that are crucial collectively for successful protection. These data provide exciting new avenues to explore and exploit in developing new vaccines against M.tb., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Herein, we examine the human exercise response following cannabis inhalation, taking into consideration varied cannabinoid concentrations and different inhalation methods. A semirandomized crossover study design was used, with measures of perceived exertion and physiological responses to submaximal and maximal exercise. Participants ( n = 14, 9 males 5 females) completed exercise after 1 ) smoking Δ-9-tetrahydrocannabinol (THC)-predominant cannabis (S-THC), 2 ) inhaling aerosol (vaporizing) from THC-predominant cannabis (V-THC), 3 ) inhaling aerosol from cannabidiol (CBD)-predominant cannabis (V-CBD), or 4 ) under control conditions. All exercise was performed on a cycle ergometer, with submaximal testing performed at 100 W followed by an evaluation of maximal exercise performance using an all-out 20-min time trial. Metabolism was characterized via the analysis of expired gases while subjective ratings of perceived exertion (RPE) were reported. During submaximal cycling, heart rate was higher during S-THC and V-THC compared with both control and V-CBD (all P < 0.02). During maximal exercise, V̇e was lower in V-THC compared with control, S-THC, and V-CBD (all P < 0.03), as was S-THC compared with control ( P < 0.05). Both V̇o 2 and RPE were similar between conditions during maximal exercise (both P > 0.1). Mean power output during the 20-min time trial was significantly lower in the S-THC and V-THC conditions compared with both control and V-CBD (all P < 0.04). Cannabis containing THC alters the physiological response to maximal and submaximal exercise, largely independent of the inhalation method. THC-containing cannabis negatively impacts vigorous exercise performance during a sustained 20-min effort, likely due to physiological and psychotropic effects. Inhalation of cannabis devoid of THC and primarily containing CBD has little physiological effect on the exercise response or performance. NEW & NOTEWORTHY Inhalation of cannabis containing THC alters physiological responses to both submaximal and maximal exercise and reduces mean power output during a 20-min time trial, regardless of whether it is inhaled as smoke or aerosol. In contrast, cannabis devoid of THC and predominantly containing CBD has no effect on physiological responses to exercise or performance.

When employing mechanistic models to study biological phenomena, practical parameter identifiability is important for making accurate predictions across wide ranges of unseen scenarios, as well as for understanding the underlying mechanisms. In this work, we use a profile-likelihood approach to investigate parameter identifiability for four extensions of the Fisher-Kolmogorov-Petrovsky-Piskunov (Fisher-KPP) model, given experimental data from a cell invasion assay. We show that more complicated models tend to be less identifiable, with parameter estimates being more sensitive to subtle differences in experimental procedures, and that they require more data to be practically identifiable. As a result, we suggest that parameter identifiability should be considered alongside goodness-of-fit and model complexity as criteria for model selection.

Collective electrotaxis is a phenomenon that occurs when a cellular collective, for example an epithelial monolayer, is subjected to an electric field. Biologically, it is well known that the velocity of migration during the collective electrotaxis of large epithelia exhibits significant spatial heterogeneity. In this work, we demonstrate that the heterogeneity of velocities in the electrotaxing epithelium can be accounted for by a continuum model of cue competition in different tissue regions. Having established a working model of competing migratory cues in the migrating epithelium, we develop and validate a reaction-convection-diffusion model that describes the movement of an epithelial monolayer as it undergoes electrotaxis. We use the model to predict how tissue size and geometry affect the collective migration of MDCK monolayers, and to propose several ways in which electric fields can be designed such that they give rise to a desired spatial pattern of collective migration. We conclude with two examples that demonstrate practical applications of the method in designing bespoke stimulation protocols., Competing Interests: Competing interests We declare we have no competing interests.

Abstract: Brown, FSA, Fields, JB, Jagim, AR, Baker, RE, and Jones, MT. Analysis of in-season external load and sport performance in women's collegiate basketball. J Strength Cond Res 38(2): 318-324, 2024-Quantifying and monitoring athlete workload throughout a competitive season is a means to manage player readiness. Therefore, the purpose of the current study was to quantify practice and game external loads and to assess the relationship between such loads and basketball-specific performance metrics across a women's collegiate basketball season. Thirteen National Collegiate Athletic Association Division I women basketball athletes (age 20.08 ± 1.55 years) wore Global Positioning Systems sensors equipped with triaxial accelerometers for 29 games and 66 practices during the 2019-20 season. A multivariate analysis of variance was used to assess differences in external load between high- and low-minute players and across quarters within games ( p < 0.05). Bivariate Pearson correlation coefficients were run to determine relationships between external loads and metrics of basketball performance. Findings indicated that high- and low-minute athletes experienced different loads during games and practices ( p < 0.001). External loads differed by quarter, such that player load (PL) was highest in Q4 ( p = 0.007), PL·min -1 was highest in Q1 and lowest in Q4 ( p < 0.001), and explosive ratio (i.e., ratio of PL and explosive efforts) was lowest in Q3 ( p = 0.45). Relationships existed between PL·min -1 and field goals ( r = 0.41; p = 0.02) and between the explosive ratio and free throws ( r = 0.377 p = 0.04). These results can be used to inform design of training sessions with the intent to prepare athletes for the demands of the competitive season. It is recommended that future research continue to explore the relationship of sport-specific performance metrics and athlete external load., (Copyright © 2023 National Strength and Conditioning Association.)

Cell competition is a process in multicellular organisms where cells interact with their neighbours to determine a "winner" or "loser" status. The loser cells are eliminated through programmed cell death, leaving only the winner cells to populate the tissue. Cell competition is context-dependent; the same cell type can win or lose depending on the cell type it is competing against. Hence, winner/loser status is an emergent property. A key question in cell competition is: how do cells acquire their winner/loser status? In this paper, we propose a mathematical framework for studying the emergence of winner/loser status based on a set of quantitative criteria that distinguishes competitive from non-competitive outcomes. We apply this framework in a cell-based modelling context, to both highlight the crucial role of active cell death in cell competition and identify the factors that drive cell competition., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Longitudinal tumour volume data from head-and-neck cancer patients show that tumours of comparable pre-treatment size and stage may respond very differently to the same radiotherapy fractionation protocol. Mathematical models are often proposed to predict treatment outcome in this context, and have the potential to guide clinical decision-making and inform personalised fractionation protocols. Hindering effective use of models in this context is the sparsity of clinical measurements juxtaposed with the model complexity required to produce the full range of possible patient responses. In this work, we present a compartment model of tumour volume and tumour composition, which, despite relative simplicity, is capable of producing a wide range of patient responses. We then develop novel statistical methodology and leverage a cohort of existing clinical data to produce a predictive model of both tumour volume progression and the associated level of uncertainty that evolves throughout a patient's course of treatment. To capture inter-patient variability, all model parameters are patient specific, with a bootstrap particle filter-like Bayesian approach developed to model a set of training data as prior knowledge. We validate our approach against a subset of unseen data, and demonstrate both the predictive ability of our trained model and its limitations., (© 2024. The Author(s).)

Bangladesh is currently experiencing the country's largest and deadliest dengue outbreak on record. This year's outbreak has been characterized by an early seasonal surge in cases, rapid geographic spread, and a high fatality rate. The alarming trends in dengue incidence and mortality this year is an urgent wake-up call for public health policymakers and researchers to pay closer attention to dengue dynamics in South Asia, to strengthen the surveillance system and diagnostic capabilities, and to develop tools and methods for guiding strategic resource allocation and control efforts., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed. Funding to pay the Open Access publication charges for this article was provided by the University of California, Berkeley (BEAR grant to ASM)., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Objective: The objective of this study was to determine hematologic changes of stored caprine whole blood in citrate phosphate dextrose adenine solution over a 28-day period., Sample: Ten 250-mL bags of whole blood were collected from 10 female Boer goats from Louisiana State University's Division of Laboratory Animal Medicine herd., Methods: 10 healthy blood donor goats were selected, and 250 mL of whole blood was drawn from each and stored at 2.78 °C. At the time of collection and every 7 days for a total of 28 days, samples were obtained from the blood bags to determine biochemical and hematologic values of collected blood. Only 5 of the 10 donors had baseline blood bag samples obtained for biochemical evaluation on day 0. At the end of 28 days, the remaining blood was submitted for aerobic and anaerobic culture., Results: Blood values remained within suitable limits for transfusion and below 1% hemolysis for up to 21 days in most samples. Packed cell volume did not change significantly from day 0 to day 28. Lactate significantly increased over the 28 days, though not as dramatically as expected on the basis of other blood storage studies. pH decreased due to anticoagulant acidity but did not drop below 7. Cultures were negative on all blood bags., Clinical Relevance: Changes over time are similar to that in other species, and caprine blood appears biochemically and hematologically stable for up to 21 days in storage. In vivo trials are needed for safety and efficacy.

Purpose: The purpose of the study was to investigate whether carbohydrate utilization is altered during exercise in overreached endurance athletes and examine the utility of continuous glucose monitors (CGM) to detect overreaching status., Methods: Eleven endurance athletes (M:8, F:3) completed a 5-week training block consisting of 1 week of reduced training (PRE), 3 weeks of high-intensity overload training (POST), and 1 week of recovery training (REC). Participants completed a Lamberts and Lambert Submaximal Cycling Test (LSCT) and 5 km time-trial at PRE, POST, and REC time points, 15 min following the ingestion of a 50 g glucose beverage with glucose recorded each minute via CGM., Results: Performance in the 5 km time-trial was reduced at POST (∆-7 ± 10 W, p = 0.04, η p 2  = 0.35) and improved at REC (∆12 ± 9 W from PRE, p = 0.01, η p 2  = 0.66), with reductions in peak lactate (∆-3.0 ± 2.0 mmol/L, p = 0.001, η p 2  = 0.71), peak HR (∆-6 ± 3 bpm, p < 0.001, η p 2  = 0.86), and Hooper-Mackinnon well-being scores (∆10 ± 5 a.u., p < 0.001, η p 2  = 0.79), indicating athletes were functionally overreached. The respiratory exchange ratio was suppressed at POST relative to REC during the 60% (POST: 0.80 ± 0.05, REC: 0.87 ± 0.05, p < 0.001, η p 2  = 0.74), and 80% (POST: 0.93 ± 0.05, REC: 1.00 ± 0.05, p = 0.003, η p 2  = 0.68) of HR-matched submaximal stages of the LSCT. CGM glucose was reduced during HR-matched submaximal exercise in the LSCT at POST (p = 0.047, η p 2  = 0.36), but not the 5 km time-trial (p = 0.07, η p 2  = 0.28) in overreached athletes., Conclusion: This preliminary investigation demonstrates a reduction in CGM-derived glucose and carbohydrate oxidation during submaximal exercise in overreached athletes. The use of CGM during submaximal exercise following standardized nutrition could be employed as a monitoring tool to detect overreaching in endurance athletes., (© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: The South African government employed various nonpharmaceutical interventions (NPIs) to reduce the spread of SARS-CoV-2. Surveillance data from South Africa indicates reduced circulation of respiratory syncytial virus (RSV) throughout the 2020-2021 seasons. Here, we use a mechanistic transmission model to project the rebound of RSV in the two subsequent seasons., Methods: We fit an age-structured epidemiological model to hospitalization data from national RSV surveillance in South Africa, allowing for time-varying reduction in RSV transmission during periods of COVID-19 circulation. We apply the model to project the rebound of RSV in the 2022 and 2023 seasons., Results: We projected an early and intense outbreak of RSV in April 2022, with an age shift to older infants (6-23 months old) experiencing a larger portion of severe disease burden than typical. In March 2022, government alerts were issued to prepare the hospital system for this potentially intense outbreak. We then assess the 2022 predictions and project the 2023 season. Model predictions for 2023 indicate that RSV activity has not fully returned to normal, with a projected early and moderately intense wave. We estimate that NPIs reduced RSV transmission between 15% and 50% during periods of COVID-19 circulation., Conclusions: A wide range of NPIs impacted the dynamics of the RSV outbreaks throughout 2020-2023 in regard to timing, magnitude, and age structure, with important implications in a low- and middle-income countries (LMICs) setting where RSV interventions remain limited. More efforts should focus on adapting RSV models to LMIC data to project the impact of upcoming medical interventions for this disease., Competing Interests: Anne von Gottberg, Cheryl Cohen, Jocelyn Moyes, and Sibongile Walaza acknowledge grants from Sanofi Pasteur, PATH, Bill & Melinda Gates Foundation, and SA‐Medical Research Council, The Centers for Disease Control and Prevention (US), and Wellcome Trust. Alexandra B. Hogan was previously engaged by Pfizer Inc. to advise on modeling RSV vaccination strategies for which she received no financial compensation. Ms. Hansen received contract‐based hourly fees from Sanofi outside of the submitted work., (© 2023 The Authors. Influenza and Other Respiratory Viruses published by John Wiley & Sons Ltd.)

Although the drivers of influenza have been well studied in high-income settings in temperate regions, many open questions remain about the burden, seasonality, and drivers of influenza dynamics in the tropics. In temperate climates, the inverse relationship between specific humidity and transmission can explain much of the observed temporal and spatial patterns of influenza outbreaks. Yet, this relationship fails to explain seasonality, or lack there-of, in tropical and subtropical countries. Here, we analyzed eight years of influenza surveillance data from 12 locations in Bangladesh to quantify the role of climate in driving disease dynamics in a tropical setting with a distinct rainy season. We find strong evidence for a nonlinear bimodal relationship between specific humidity and influenza transmission in Bangladesh, with highest transmission occurring for relatively low and high specific humidity values. We simulated influenza burden under current and future climate in Bangladesh using a mathematical model with a bimodal relationship between humidity and transmission, and decreased transmission at very high temperatures, while accounting for changes in population immunity. The climate-driven mechanistic model can accurately capture both the temporal and spatial variation in influenza activity observed across Bangladesh, highlighting the usefulness of mechanistic models for low-income countries with inadequate surveillance. By using climate model projections, we also highlight the potential impact of climate change on influenza dynamics in the tropics and the public health consequences., (© The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences.)

Objectives: Pet pigs are a species of growing medical interest, and evidence-based practices for blood transfusions are needed. The objectives of this study were to quantify the prevalence of 3 blood group (Bg) phenotypes ("A" and "A weak " resulting from EAA AA and EAA AO , "0" from EAA 00 , or "-" from EAA 00 or S SS alleles) in pet pigs and compare results using a human blood-typing card (EldonCard), standard saline agglutination (SSA), and polymerase chain reaction (PCR) sequencing., Design: Cross-sectional study., Setting: University veterinary teaching hospital., Animals: Ninety-seven pet pigs from Louisiana., Interventions: Blood was sampled from randomly selected pet pigs of various breeds, anticoagulated with EDTA, and typed using each investigated test according to the manufacturers' directions or standard laboratory technique. Samples for PCR analysis were stored at -80°C until analysis. Phenotypes were screened via EldonCard. Association between Bg and sex was investigated using chi-square test, with significance at P < 0.05. Kappa (κ) statistic was used to measure the level of agreement between the 3 tests., Measurements and Main Results: Pot-bellied pigs represented the majority (84.5%) of this population, with 52 (53.6%) males and 45 (46.4%) females. Genotypic frequencies were 30%, 30%, and 40% for "EAA AA ," "EAA AO ," and "EAA 00 ," respectively. Based on EldonCard, 38 phenotypes were classified as "A," 5 as "A weak ," and 54 as "0" or "-." Results were identical for Bg, with the 3 tested techniques in 90% (45/50) of samples. Agreement between EldonCard and PCR was almost perfect (49/50 [98%], κ = 0.959; P < 0.001). Agreement between SSA and PCR, and EldonCard and SSA was substantial (46/50 [92%], κ = 0.803, P < 0.001 and 93/97 [95.9%], κ = 0.764, P < 0.001, respectively)., Conclusions: The most common blood type was "0" or "-" (55.7%), followed by "A" (39.2%) and "A weak " (5.1%). There was strong agreement between EldonCard and PCR testing. EldonCard allowed for rapid and reliable phenotype identification ("A," "A weak ," and "0" or "-") and represents a clinically applicable laboratory method for blood typing in pet pigs., (© Veterinary Emergency and Critical Care Society 2022.)