Browse Articles

Mathematical insights into epidemic spread: A computational and numerical perspective

This study aims to investigate and analyze the dynamics of diarrhea infectious disease model. For this purpose, a classical diarrhea disease model is converted into the diffusive diarrhea epidemic model by including the diffusion terms in every compartment of the system. Basic assumptions of the proposed model are described for a vivid understanding of the model’s behavior. In addition, the pros and cons of the proposed model for short and long terms behavior of the diffusive system are presented. The system has two steady states, namely the disease-free equilibrium and endemic equilibrium points. The system is analyzed, analytically by ensuring the positivity, boundedness and local, and global stability at both the steady states. Moreover, the implicit nonstandard finite difference scheme is designed to extract the numerical solutions of the diffusive epidemic model. To ensure the reliability and efficacy of the numerical scheme, the positivity, consistency and both linear and nonlinear stabilities are presented by establishing some standard results. Simulated graphs are sketched to study the nonlinear behavior of the disease dynamics. All the graphs depict the positive, bounded and convergent behavior of the projected numerical scheme. Also, the numerical graphs reflect the role of the basic reproductive number, R0, in attaining the steady state. The article is closed by providing productive outcomes of the study.

A knowledge-based equation of daily work exposure

The objective of this study was to establish a predictive equation that expresses the daily work exposure as a function of variables that define complex work tasks. The equation was verified with data reported in reviewed publications. The ScienceDirect, PubMed, and ProQuest databases were searched using keywords related to variables that characterize intermittent tasks and those that describe muscle fatigue resulting from these tasks. Inclusion and exclusion criteria were established to focus on task characteristics and study participants. The primary criterion for accepting studies was a quantitative definition of the tasks performed, specifically concerning the level of force exerted over a specified period. Only studies involving healthy individuals aged 18–70 years that reported voluntary muscle contractions were deemed eligible. The adjustment of the prediction equation was based on the assumptions that for the same values of variables that characterize work, the exposure calculated by the equation is equivalent to musculoskeletal load, and that the level of musculoskeletal load at a given time determines the experimentally measured decrease in force capabilities. Thirty-seven datasets of independent variables (those that define work tasks) and dependent variable relevant to the decrease in force capabilities were accepted to establish the equation. Based on the comparison of dependent data from experimental studies with data obtained from calculations using independent variables, the equation that provided the best fit was identified. The correlation between the calculations and experimental results was found to be 0.72. The equation distinguishes work tasks by considering variables such as relative force, time of task, mean exposure, and the similarity of tasks performed throughout the daily work. It provides a tool for determining the work exposure associated with a specific set of tasks, which may cover the entire work shift or only parts of it.

Estimating the impact of missed colorectal cancer diagnoses on life expectancy in Minamisoma City following the 2011 triple disaster

Background After the 2011 Great East Japan Earthquake, participation in colorectal cancer (CRC) screening significantly decreased in Minamisoma City, Fukushima Prefecture. However, the long-term health effects of this decline in screening participation have not been quantified. This study aims to construct a model to evaluate the impact of post-disaster decreases in CRC screening participation on population health. Methods We utilized the population and CRC screening data targeting 40–74 years-old residents in Minamisoma City. We compared the actual screening participation in 2011 with projected participation rates based on pre-disaster levels to estimate the number of residents who missed screening due to the disaster. Based on national CRC screening performance data and stage-specific survival rates in Japan, we estimated the number of missed CRC cases and modeled the additional the loss of life expectancy (LLE) due to CRC resulting from a one-year delay in diagnosis. Results The estimated number of colorectal cancer cases that might have been missed due to decreased screening participation was 1.794 (95% uncertainty interval: 1.597 to 1.994) for men and 1.203 (0.931 to 1.491) for women. The missed detection opportunities estimated result in 0.428 (0.282 to 0.582) person-years [2.684 (1.793 to 3.604) years per 10,000 persons] and 0.229 (0.103 to 0.372) person-years [0.993 (0.450 to 1.608) years per 10,000 persons] of additional LLE for men and women, respectively. The estimated cost per life-year saved was 1.12×106 (0.81×106  to 1.62×106 yen for men and 3.65×106  (2.02×106  to 7.19×106 ) yen for women, respectively. Conclusions The calculated additional LLE due to missed CRC screening was relatively small but suggests preventive health services should be considered in disaster response planning. These findings provide a quantitative framework for evaluating health impacts of service disruptions.

Transcranial direct current simulation as an adjunctive treatment for treatment-resistant depression in hospitalized patients: A feasibility study protocol

Transcranial direct current stimulation (tDCS) is clinically effective in treating treatment-resistant depression (TRD), as measured by response, symptom improvement, and disease remission. However, the feasibility and underlying mechanism of tDCS treatment in individuals with TRD during acute psychiatric hospitalization remain poorly characterized. This paper outlines the protocol that aims to investigate the feasibility of implementing a 5-day tDCS treatment in hospitalized patients with TRD and secondarily explore the effects on depression and cognition, and neurophysiological mechanisms underlying tDCS. Current study will enroll ten participants who are diagnosed with TRD and are hospitalized in psychiatric units. Participants will receive a 5-day tDCS treatment protocol, with each treatment session lasting for 30 minutes, delivered twice daily, for a total of 10 stimulations over 5 days. The primary outcomes are the feasibility, acceptability, and tolerability of administering a 5-day tDCS treatment protocol in acutely hospitalized TRD patients. Exploratory outcomes pre- and post-tDCS include measures of depression (Montgomery-Asberg Depression Rating Scale (MADRS)) and cognition (Stroop Test, Revised Hopkins Verbal Learning Test (HVLT-R), Digital Symbol Coding Test (DSCT)), EEG changes in peak alpha frequency (PAF), and cerebral hemodynamic changes by functional near-infrared spectroscopy (fNIRS). This protocol would provide feasibility evidence for tDCS as an add-on to the standard of care treatment of TRD in hospitalized patients. Upon completion of the protocol, the preliminary effects of the 5-day tDCS treatment protocol regarding depression and cognitive symptoms and its neurophysiological mechanisms will be identified to guide the design and delivery of a randomized controlled study. Trial registration: National Institute of Health Clinicaltrials.gov (NCT06236711) and protocol ID: 23–003274.

Household cost of accessing contraceptive services among women in Urban communities in Ghana

Background In many developing nations, including Ghana, access to contraceptive services, remains a critical concern where urban areas face unique challenges in healthcare delivery. Despite various interventions, the financial burden of assessing these contraceptive services continues to hinder adoption by women especially those with economic challenges. This study explored the costs incurred by women seeking contraceptive services in urban communities by estimating the direct, indirect, and intangible costs in Ghana. Methods A facility-based cross-sectional study was conducted using the patient perspective; to gather data on direct medical and non-medical costs, indirect costs and intangible costs that were associated with women seeking contraceptive services. A structured questionnaire was used to collect data from three Planned Parenthood Association of Ghana (PPAG) facilities in the Accra metropolitan, Suame municipal and Sagnarigu districts in the Greater Accra, Ashanti, and Northern Regions respectively. A total of 125 women accessing contraceptive services were randomly selected and included in the study. Data was analyzed descriptively and reported in frequency tables, pie, and bar charts. All costs were reported in Ghana Cedi and US dollar. Results The average direct cost of contraceptive services was GHS 18.37 ± 22.11 (US$ 1.53 ± 1.84) per visit. This comprised an average direct medical cost of GHS 8.50 ± 7.18 (US$ 0.71 ± 0.60) and non-medical cost of GHS 9.84 ± 20.23 (US$ 0.82 ± 1.69). Clients, on average, lost 52.1 minutes due to traveling and waiting, resulting in an average productivity loss of GHS 1.62 per visit. The average economic cost of contraceptive service was GHS 19.99 (US$ 1.67) per patient. About 92% of the economic cost was made up of direct cost. 71.2% of respondents consulted their partners before accessing contraceptive services, and 94% believed that their decision to use contraceptives did not negatively affect their relationships, however, many reported pains during the procedure. Conclusion The study highlights the considerable direct and indirect costs associated with accessing modern contraceptive services, indicating a potential barrier to access when compared to daily minimum wage and prevailing economic conditions. Addressing these economic challenges is crucial for ensuring access to contraceptive services. Innovative strategies such as service delivery outreaches and deployment of digital health interventions to expand self-care is recommended to help reduce travel time to and from the service delivery point for contraceptive services.

Advancing knee adduction moment prediction for neuromuscular training via functional joint definitions and real–time simulation using OpenSim

Neuromuscular training to strengthen leg muscles is an important part of the treatment of musculoskeletal disorders and chronic diseases and preventing age–related muscle loss. This study evaluates different individualization approaches and their real–time implementation for OpenSim musculoskeletal models to estimate the external knee adduction moment during a leg–press exercise. A robotic neuromuscular training platform was utilized to perform isometric and dynamic leg extension exercises. Data were collected for 13 subjects using a 3D motion capture system and force plate measurements from the robotic training platform. Functional joint parameters, determined through dynamic reference movements, were integrated into the OpenSim models, allowing a personalized representation of the hip, knee, and ankle joints. This integration was compared with a conventional scaling method. The results indicate that the incorporation of functional joint axes can significantly enhance the accuracy of biomechanical simulations. These methods provide a real–time and a more precise estimate of the external knee adduction moment compared to conventional scaling approaches and underscore the importance of individualized model parameters in biomechanical research.

Resilience of deep aquifer microbial communities to seasonal hydrological fluctuations

The influence of seasonal variations in temperature and precipitation on subsurface biogeochemical processes remains poorly understood. In the Lavey-les-Bains thermal system in the Swiss Alps, annual variations in electrical conductivity are observed to depths of 500 m, suggesting a potential link to surface environmental changes. Here we show, through year-round analyses of stable water isotopes, noble gases, and conductivity, that seasonally varying contributions of shallow groundwater from the Rhône alluvial aquifer mix with deep groundwater. Despite vertically similar fluid geochemical compositions suggesting high hydrological connectivity, microbial communities exhibit significant depth-dependent variation with minimal seasonal change. This decoupling of dynamic water source partitioning and stable microbial community structure has not been previously observed and fills a critical gap in our understanding of geothermal systems and microbial life in the deep subsurface. At 200 m, the communities are dominated by sulfur-disproportionating Bacteria ( Dissulfurispira ) and Micrarchaeota, while at 500 m the major groups include sulfate- and iron-reducers and/or hydrogen-oxidizers (Thermales, Thermodesulfobacteriota, and Bathyarchaeota). Our study highlights the resilience of terrestrial subsurface microbial communities to temporal variations in water sources and fluid composition. We propose that intrinsic environmental properties—such as temperature—are more critical drivers of microbial community structure in hydrologically connected deep aquifers than seasonal hydrological changes.

A skin-interfaced wireless wearable device and data analytics approach for sleep-stage and disorder detection

Accurate identification of sleep stages and disorders is crucial for maintaining health, preventing chronic conditions, and improving diagnosis and treatment. Direct respiratory measurements, as key biomarkers, are missing in traditional wrist- or finger-worn wearables, which thus limit their precision in detection of sleep stages and sleep disorders. By contrast, this work introduces a simple, multimodal, skin-integrated, energy-efficient mechanoacoustic sensor capable of synchronized cardiac and respiratory measurements. The mechanical design enhances sensitivity and durability, enabling continuous, wireless monitoring of essential vital signs (respiration rate, heart rate and corresponding variability, temperature) and various physical activities. Systematic physiology-based analytics involving explainable machine learning allows both precise sleep characterization and transparent tracking of each factor’s contribution, demonstrating the dominance of respiration, as validated through a diverse range of human subjects, both healthy and with sleep disorders. This methodology enables cost-effective, clinical-quality sleep tracking with minimal user effort, suitable for home and clinical use.

The highly conserved intron of tyrosine tRNA is critical for ^m1 A58 modification and controls the integrated stress response

tRNA introns are a universally conserved feature of eukaryotic genomes, but the reason for their conservation has remained obscure. We have previously shown that a defect in the essential tRNA splicing endonuclease of yeast results in transcriptome remodeling, resembling that of the integrated stress response (ISR). In this study, we show that ISR activation in this mutant requires the canonical ISR components, including the collided ribosome sensor Gcn1. We further show that splicing of tyrosine tRNA, but not splicing of any of the other intron-containing tRNAs, controls the ISR. Using nanopore direct RNA sequencing, we show that the intron of tyrosine tRNA affects m1 A58 modification in the T arm loop of the mature tRNA. In support of these results, we show that deletion of either subunit of the enzyme that adds the m1 A58 modification also controls the ISR. Unlike the few intron-dependent modifications previously described, the intron-dependent m1 A58 modification site is distal from the intron and has a clear physiological impact. Finally, we survey the occurrence of tRNA introns in eukaryotic genomes and show that the tyrosine tRNA intron is more prevalent than any other tRNA intron. These data suggest that tRNA splicing is conserved in eukaryotes because hypomodified tyrosine tRNAs lead to collided ribosomes, resulting in stress to cell physiology.

Establishment of cell size–dependent growth rate via differential scaling of metabolite uptake and release

Metabolism fuels cell growth and functions. While it is well established that cellular growth rate scales with cell size, how cells alter their metabolism as they change size remains largely unexplored. Here, we conducted a systematic analysis of cell size–dependent metabolism across the NCI60 cancer cell line panel comprising a diverse range of cell sizes. We demonstrate that cellular metabolism and growth rate display 2/3 allometric scaling due to differential scaling of overall nutrient uptake and waste metabolite release with respect to cell size, with waste elimination decreasing less rapidly than nutrient uptake rate as cells grow larger. This results in cell size–dependent growth rate and predicts a maximum cell size where net nutrient uptake equals zero and cell enlargement ceases despite active metabolism. We experimentally confirm this prediction and identify that electron acceptor demand constrains cell enlargement as evidenced by depletion of intracellular aspartate and scaling of aspartate uptake, which is more than proportional to cell volume. Overall, these findings may have implications for understanding cell size homeostasis, developmental biology, and the design principles of living organisms.

Evolution of the real area of contact during laboratory earthquakes

Empirical slip-rate- and state-dependent friction laws and linear fracture mechanics constitute popular approaches to explaining earthquakes. However, the physics underlying friction laws remain elusive and fracture mechanics does not specify fault strength at the various conditions relevant to crustal faulting. Here, we introduce a physical constitutive framework that augments the traditional approaches by incorporating the real area of contact as the state variable. The physical model explains the dynamics of slow and fast ruptures on transparent materials, as well as the amount of light transmitted across the interface during laboratory ruptures. The constitutive framework elucidates the origin of empirical friction laws, and the simulated ruptures can be described by linear elastic fracture mechanics. Continuous measurements of the physical state variable or its proxies during seismic cycles emerge as a novel tool for probing natural faults and advancing our understanding of the earthquake phenomenon.

Endogenous competition and the underrealized reproduction of infectious diseases

Scientific inquiry about the transmissibility of infectious diseases is largely based on the basic reproduction number ( R 0 ) and its derivations. This paper describes a mechanism overlooked in most conventional analyses, in which a disease can endogenously “compete” with itself when multiple infectious individuals race to infect the same susceptible individual, thereby reducing the effective reproductive rate. Utilizing an empirically calibrated network epidemiological model of wild-type COVID-19 diffusion in its early pandemic, we show that the mechanism would be expected to reduce its reproductive rate by an average of 39%. Simulation experiments further identify different types of endogenous competition mechanisms and their relative effect sizes. We highlight the incorporation of endogenous competition mechanism as a necessary step in realistically modeling the reproduction process of infectious diseases.

Reinforcement generates systematic differences without heterogeneity

Inequality in outcomes may emerge through a reinforcement process in which stochastic variation in values is determined by prior values but may also originate in preexisting differences in unobserved factors. A common approach toward differentiating between these origins in longitudinal data is to attribute systematic differences between units—differences in means or differences proportional to a time-varying group average—to unobserved heterogeneity. We show that any longitudinal data with systematic differences can also be produced by a reinforcement-driven data generating process. This result reconciles findings in three distinct research areas—science of science, personal culture, and sexual networks—where reinforcement is a strong theoretical prior, yet longitudinal data analyses advance an explanation of interpersonal differences based on heterogeneity. Future studies may bound the role of heterogeneity and reinforcement from below by measuring fixed traits that systematically vary with the outcome and isolating random events that trigger emergent differences.

Light at night negatively affects mood in diurnal primate-like tree shrews via a visual pathway related to the perihabenular nucleus

To better understand the potential health threats and underlying visual pathways of long-term light at night (LAN) exposure, we adopted a widely accepted diurnal animal model tree shrew ( Tupaia belangeri chinensis ), which is a close relative to primates, and evaluated the deleterious effects of long-term LAN exposure. We used an early-night LAN paradigm that was established in mice to examine behavioral and physiological consequences in adult male tree shrews. We found that 3-wk LAN exposure significantly impaired the mood and long-term memory of tree shrews without affecting the general activity pattern. We identified retinal projections to the perihabenular nucleus (pHb), a crucial area in LAN-induced negative mood, and demonstrated that the pHb continues to innervate the nucleus accumbens (NAc) in tree shrews. Moreover, the pHb was required for the LAN effect on mood but not long-term memory. Transcriptomic profiling of brain tissues containing the NAc area revealed drastic changes of several depression-related genes in NAc neurons post-LAN treatment, suggesting that long-term exposure to nighttime light could result in lasting changes in tree shrews. Collectively, we present behavioral and neural structural evidence that LAN exerts depression-inducing effects in diurnal animals via a pHb-related visual pathway, which may facilitate the translation from laboratory findings of excessive LAN exposure to clinical applications in humans.

Projecting neurons from the lateral entorhinal cortex to the basolateral amygdala mediate the encoding of incidental odor–taste associations

Since our first steps in life, we are forming incidental associations between diverse stimuli across various sensory modalities that influence our future choices and facilitate adaptation to environmental fluctuations. Daily behavior is usually governed by indirect incidental associations among sensory cues that have never been explicitly paired with a reinforcer. This phenomenon, known as higher-order conditioning, can be systematically investigated in laboratory animals through specific behavioral paradigms such as sensory preconditioning protocols. In this study, using “Targeted Recombination in Active Populations” (TRAP2) transgenic mice, we have interrogated which are the brain areas orchestrating the encoding of associations between olfactory and gustatory stimuli and the expression of an aversive odor–taste sensory preconditioning paradigm. We identified neuronal ensembles within the basolateral amygdala specifically activated during odor–taste associations. To demonstrate the causal involvement of this brain region in our sensory preconditioning task, we inhibited it during the preconditioning phase (i.e., incidental associations) using a chemogenetic approach, which caused a clear impairment of the mediated responses. In addition, using retrograde tracers in the basolateral amygdala of TRAP2 mice, we observed that the projections from the lateral entorhinal cortex to the basolateral amygdala are particularly activated during odor–taste associations. Notably, the chemogenetic inhibition of this brain circuit impaired the mediated aversion performance in our sensory preconditioning task. Overall, these findings highlight the amygdala as a pivotal modulator of incidental associations during an aversive sensory preconditioning task and point toward a brain circuit crucially involved in these complex cognitive processes.

A proteomic signature of healthspan

The focus of aging research has shifted from increasing lifespan to enhancing healthspan to reduce the time spent living with disability. Despite significant efforts to develop biomarkers of aging, few studies have focused on biomarkers of healthspan. We developed a proteomics-based signature of healthspan [healthspan proteomic score (HPS)] using proteomic data from the Olink Explore 3072 assay in the UK Biobank Pharma Proteomics Project (53,018 individuals and 2,920 proteins). A lower HPS was associated with higher mortality risk and several age-related conditions, such as chronic obstructive pulmonary disease, diabetes, heart failure, cancer, myocardial infarction, dementia, and stroke. HPS showed superior predictive accuracy for these outcomes compared to other biological age measures. Proteins associated with HPS were enriched in hallmark pathways such as immune response, inflammation, cellular signaling, and metabolic regulation. The external validity was evaluated using the Essential Hypertension Epigenetics study with proteomic data also from the Olink Explore 3072 and complementary epigenetic data, making it a valuable tool for assessing healthspan and as a potential surrogate marker to complement existing proteomic and epigenetic biological age measures in geroscience-guided studies.

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Control of seed-to-seedling transition by an upstream open reading frame in <i>ABSCISIC ACID DEFICIENT2</i>

The start of seed germination is a major decision point in plant life cycle, which relies on seed stored mRNA. However, the underlying translational mechanism remains less illustrated. Here, we demonstrate that inhibiting translation using translation inhibitors and ribosome-defective mutants delays germination in Arabidopsis . Through comprehensive transcriptome deep sequencing (RNA-seq) and polysome profiling analyses, we elucidated the dynamic interplay of regulation at the transcriptional and translational levels during germination. We show that delayed germination in some ribosome-defective mutants is partially regulated by the gene ABSCISIC ACID DEFICIENT2 ( ABA2 ), with an upstream open reading frame (uORF) in the 5′ untranslated region that represses translation of the downstream ORF encoding ABA2. In addition, disrupting rice OsABA2 uORF inhibited preharvest sprouting (PHS). Furthermore, we found two main haplotypes for the uORF among rice cultivars that result in different OsABA2 expression levels, thus contributing to diverse PHS phenotypes. This work highlights the critical role of translational control and genetic variation in seed dormancy and germination, with implications for crop improvement.

Controlling DNA–RNA strand displacement kinetics with base distribution

DNA–RNA hybrid strand displacement underpins the function of many natural and engineered systems. Understanding and controlling factors affecting DNA–RNA strand displacement reactions is necessary to enable control of processes such as CRISPR-Cas9 gene editing. By combining multiscale modeling with strand displacement experiments, we show that the distribution of bases within the displacement domain has a very strong effect on reaction kinetics, a feature unique to DNA–RNA hybrid strand displacement. Merely by redistributing bases within a displacement domain of fixed base composition, we are able to design sequences whose reaction rates span more than four orders of magnitude. We extensively characterize this effect in reactions involving the invasion of dsDNA by an RNA strand, as well as the invasion of a hybrid duplex by a DNA strand. In all-DNA strand displacement reactions, we find a predictable but relatively weak sequence dependence, confirming that DNA–RNA strand displacement permits far more thermodynamic and kinetic control than its all-DNA counterpart. We show that oxNA, a recently introduced coarse-grained model of DNA–RNA hybrids, can reproduce trends in experimentally observed reaction rates. We also develop a simple kinetic model for predicting strand displacement rates. On the basis of these results, we argue that base distribution effects may play an important role in natural R-loop formation and in the function of the guide RNAs that direct CRISPR-Cas systems.

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