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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

The trade-off between parsimony and model complexity for understanding biomedical mechanisms from mathematical models

Mechanistic mathematical models have been used extensively to provide a deeper understanding of biological mechanisms, including unveiling the regulation of tumour growth and its response to various treatments. However, given the breadth of biological regulatory mechanisms, these models are frequently large and thus prone to potential issues with parameter identifiability. Statistical metrics like the Akaike and Bayesian information criteria can help identify a parsimonious model by balancing goodness of fit against model complexity. Yet simple models may fail to provide sufficient biological insight if they do not adequately capture known physiological processes or mechanisms. A modeller must therefore balance hypothesis generation and biological learning with model tractability. Here, we illustrate this balance using models of ovarian cancer growth and treatment response to cisplatin and immune checkpoint blockade in homologous recombination (HR)-deficient and HR-proficient immunocompetent mouse models. We develop a hierarchy of mathematical models of increasing complexity to describe tumour growth, treatment response, and immune dynamics. Our results highlight the limits of relying purely on statistical metrics for model selection, particularly when the goal is to obtain biological insight and underscore the importance of balancing model complexity to avoid overfitting and parameter unidentifiability.

systems biology↗

bioRxiv2026

m1A58 acts as a conformational checkpoint coupling human initiator tRNA maturation to translation initiation

tRNAs are characterized by extensive chemical modifications that influence tRNA fate. N1-methyladenosine at position 58 (m1A58) is a widespread core tRNA modification linked to physiological and pathological processes. However, how m1A58 coordinate tRNA folding and processing to ensure translational efficiency in mammalian cells remains largely unknown. Using acute dTAG-mediated degradation and CRISPR-Cas9 knockout, we identified initiator methionine tRNA (tRNAiMet) as selectively vulnerable to m1A58 loss, lacking the isodecoder buffering observed for most other tRNA isoacceptors. NMR analysis of the tRNAiMet showed that m1A58 stabilizes D/T-loop interactions, consistent with a maturation-competent conformation. In vitro processing assays further demonstrated that m1A58 promotes RNase P-mediated 5'-leader removal and RNase Z-mediated 3'-trailer cleavage, while La/SSB protects accumulated precursors. Disrupting this checkpoint impaired the assembly of the eIF2-containing 43S pre-initiation complex and global protein synthesis, which was substantially rescued by adding m1A58-modified tRNAiMet. Acute TRMT6 degradation elicited temporally coordinated gene-expression responses involving proteostasis, transport and signaling. Together, these findings establish m1A58 as a conformational checkpoint coupling human initiator-tRNA maturation to translation initiation and stress responses.

molecular biology↗

bioRxiv2026

A Metabolic Labeling Strategy for Tracking Protein Synthesis in Complex Biological Systems

Protein synthesis supports most biological processes. In the brain in particular, protein synthesis plays a critical role in physiological and pathological states. Here, we describe Tellurophene-Alkyne Cycloaddition-mediated Amino acid Tagging (TeACAT), a versatile strategy for fast, facile, and flexible tagging of newly synthesized proteins in mice. TeACAT is based on metabolic incorporation of the non-canonical amino acid TePhe into proteins by the endogenous protein synthesis machinery. Due to their high similarity, TePhe can efficiently replace canonical Phe without dietary or genetic manipulation. The subsequent bio-orthogonal reaction of TePhe with either fluorescent dyes or affinity handles enables both visualization and affinity enrichment of proteins synthesized during TePhe exposure. TeACAT is compatible with immunofluorescence for cell-type specific visualization of protein synthesis with subcellular resolution and can be used in conjunction with routine proteomics to identify and quantify newly synthesized proteins. Robust incorporation into the mouse proteome was observed on the scale of hours to days, allowing the interrogation of various biological processes. In summary, TeACAT enables the visualization and quantification of protein synthesis with minimal perturbation for biological discoveries.

molecular biology↗

bioRxiv2026

DIFFERENTIAL PHOTOSYNTHETIC RESPONSES TO GLUFOSINATE AMMONIUM IN TWO GRASS WEEDS: Lolium multiflorum AND Echinochloa crus-galli.

Background: Weed control is one of the main challenges in agriculture today, particularly due to the increasing occurrence of herbicide-resistant populations. Among the most problematic species are Lolium multiflorum (L.) and Echinochloa crus-galli (L.) Beauv., for which glyphosate-resistant populations have been reported. In this context, glufosinate ammonium has emerged as an alternative for their control; however, its efficacy may vary depending on species and photosynthetic metabolism. Objective: The objective of this study was to evaluate the differential sensitivity of ryegrass (C3) and barnyardgrass (C4) to ammonium glufosinate by analyzing physiological responses associated with leaf senescence and photosystem II activity. Methods: Visual injury, chlorophyll fluorescence, and ammonium accumulation were assessed. Results: Results revealed a differential response between species. Barnyardgrass exhibited earlier symptom onset and a greater reduction in the quantum yield of photosystem II ({Phi}PSII), whereas ryegrass showed a slower senescence process. These differences indicate a higher sensitivity of barnyardgrass to glufosinate ammonium, possibly associated with its C4 photosynthetic metabolism. Conclusions: It is concluded that the effectiveness of glufosinate ammonium depends on the type of photosynthetic metabolism and on the ability of each species to cope with herbicide-induced oxidative stress. This information contributes to optimizing glufosinate ammonium use and to the development of management strategies aimed at delaying the evolution of herbicide resistance.

plant biology↗

bioRxiv2026

Arterial Elastin Abundance, Rather Than Orthologue Origin, Modulates Medial Arterial Calcification in Matrix Gla Protein-Deficient Mice

Abstract Calcific deposits in the arterial media have been associated with a number of metabolic and genetic disorders including diabetes, chronic kidney disease and generalized arterial calcification of infancy. While medial calcification and physiologic hard tissue mineralization in the skeleton are both regulated by several common determinants, emerging data suggest that there might be fundamental differences in the mechanisms underlying these two processes. Objective: We previously demonstrated that elastin haploinsufficiency delays medial calcification in MGP-deficient mice. Here, using mice in which a human ELN transgene rescues mouse elastin deficiency, we investigated whether the origin and abundance of arterial elastin differentially affect the initiation and progression of medial calcification. Approach and Results: We pursued a transgenic approach to alter the arterial elastin scaffold in MGP-deficient mice. Our analyses of a humanized MGP-deficient model with 40% reduction of medial elastin content showed a complete absence of the early-stage vascular calcification. Additionally, we showed that mouse and human elastin orthologues affect vascular calcification in a comparable manner. Conclusion: Arterial elastin abundance, rather than orthologue origin, modulates the initiation and progression of medial calcification in MGP-deficient mice. A further reduction in arterial elastin beyond that achieved by elastin haploinsufficiency profoundly delays mineral deposition and maturation, whereas restoration of elastin abundance through transgenic human ELN expression restores arterial calcification.

cell biology↗

bioRxiv2026

VITAL-3D: Volumetric Single-Cell Quantification Reveals Microenvironment-Dependent Drug Responses in Breast Cancer

Preclinical drug evaluation relies heavily on two-dimensional (2D) monolayer assays, which fail to recapitulate the structural and functional complexity of the tumor microenvironment and may therefore misrepresent therapeutic efficacy. Here, we present VITAL (Volumetric Imaging-based Toxicity and Live Analysis), a high-throughput imaging platform that enables direct single-cell quantification of proliferation and cell death in both 2D and three-dimensional (3D) extracellular matrix (ECM) cultures using a 96-well format. By combining volumetric imaging with automated single-cell analysis, VITAL enables dynamic assessment of drug responses beyond conventional viability assays and EC measurements. Using breast cancer cell lines treated with anticancer agents, we systematically compared drug responses between 2D and 3D microenvironments. Although EC values were often comparable between culture formats, growth kinetics and concentrations required to induce complete growth arrest or net cell loss differed substantially in 3D cultures. In particular, drug concentrations required to induce net cell loss were consistently higher in 3D, revealing microenvironment-dependent survival responses that were not captured by EC alone. Furthermore, clinically expected subtype-specific responses, including tamoxifen sensitivity in ER-positive cells and olaparib sensitivity in BRCA1-mutant cells, were more accurately resolved under 3D culture conditions and extended treatment durations. Together, these findings demonstrate that growth-based, single-cell quantification provides a more comprehensive assessment of therapeutic efficacy than conventional endpoint measurements and establish VITAL as a scalable platform for physiologically relevant preclinical drug screening.

cancer biology↗

bioRxiv2026

The DYNAM-O Toolbox: Characterizing Individualized Neural Signatures in Sleep EEG

Conventional sleep electroencephalography (EEG) measures often rely on predefined bands, thresholds, and averages that incompletely capture transient oscillatory dynamics across an entire night. Here, we introduce the Dynamic Oscillation (DYNAM-O) Toolbox, an open-source, cross-platform (MATLAB, Python, and Rust) software package for data-driven characterization of individualized neural dynamics in sleep EEG. DYNAM-O identifies transient oscillations as time-frequency peaks on multitaper spectrograms using a novel multi-resolution procedure, computes intrinsic and sleep-state-dependent extrinsic features for each event, and represents the overnight distributions of tens of thousands of TF-peaks as feature histograms spanning oscillation frequency, slow oscillation power, and slow oscillation phase. This distributional representation preserves continuous brain-state variation that could be obscured by averaging within conventional sleep stages. The toolbox further provides Gaussian and spline basis-based dimensionality reduction, visualization, and whole-histogram statistical testing tools to support both exploratory and hypothesis-driven analyses. To demonstrate its use for group-level inference, we analyzed overnight C3-channel EEG from 133 adults (71 females, 72 males; ages 20-35 years) in the Cleveland Family Study. Whole-histogram and parameterized-mode analyses reproduced the established higher center frequency of fast-spindle activity in females and additionally revealed greater low-alpha transient oscillatory activity in females, a pattern outside the conventional sleep spindle range. By completing the analysis cycle from TF-peak extraction to statistical inference, DYNAM-O provides an accessible and interpretable framework for studying individualized sleep physiology and identifying subtle, reproducible electrophysiological patterns.

bioinformatics↗

bioRxiv2026

Antibody co-administration robustly improves proton therapy with radiosensitizing nanoparticles: a mathematical modeling study

Radiosensitizing nanoparticles represent a promising approach for enhancing the efficacy of proton radiotherapy; however, their performance is constrained by restricted penetration into tumor tissue, resulting in preferential perivascular accumulation. Here, we develop a spatially distributed mathematical model of a growing tumor undergoing proton therapy with intravenously administered radiosensitizing nanoparticles to investigate treatment optimization strategies. Using physiologically plausible parameter ranges informed by our own experimental measurements and published data, we demonstrate that co-administration of targeted nanoparticles with antibodies binding to the same tumor receptors can overcome transport-induced localization and promote a more uniform intratumoral redistribution of nanoparticles before irradiation. Population-level simulations across heterogeneous parameter sets suggest that moderate antibody doses consistently prolong tumor regrowth time, whereas higher antibody doses produce a pronounced and robust increase in tumor cure probability under a single high-dose irradiation regimen representative of preclinical settings. A key conceptual result of our analysis is the asymmetric risk associated with antibody co-administration. In contrast to antibody--drug conjugates, for which excessive dosing of unconjugated antibodies may severely compromise therapeutic efficacy, co-administration of antibodies with nanoparticle-based radiosensitizers constitutes a "safe-by-design" strategy with respect to tumor cell kill in the modeled single high-dose irradiation setting: although excessive antibody doses may yield suboptimal outcomes, they cannot reduce tumor cell kill below that achieved with targeted nanoparticles administered without antibodies. These findings identify antibody-mediated spatial redistribution of radiosensitizing nanoparticles as a favorable strategy that is expected to provide robust therapeutic benefit despite substantial variability in tumor characteristics.

cancer biology↗

bioRxiv2026

A Biophysical Platform for Electromechanical Stimulation of Engineered Cardiac Tissues

Human engineered cardiac tissues (ECTs) provide an in vitro model for studying human cardiac physiology and drug responses, but their performance remains limited by culture systems that do not fully reproduce the heart's electrical and mechanical environment. Electrical stimulation (ES) and mechanical stimulation (MS) have each been used to improve ECT function. Their combination, referred to as electromechanical stimulation (ES+MS), can provide further benefits. However, ES+MS depends not only on the presence of both cues but also on how they are coordinated in time. Here, we developed an incubator-compatible biophysical platform that delivers ES and MS independently or in combination, with programmable control over timing, amplitude, frequency, duration, and waveform. Calibration and dynamic characterization demonstrated tissue-relevant strain delivery, rapid and repeatable motion, and minimal attenuation and timing lag at the designated frequency of 1.5 Hz. We then compared four 6 h conditioning regimens: unstimulated control, ES alone, unsynchronized ES+MS, and synchronized ES+MS. We hypothesized that the synchronized ES+MS group, in which electrical excitation was aligned with peak externally applied strain, would produce the greatest increase in contractile force. Consistent with this hypothesis, synchronized ES+MS increased normalized twitch force by approximately 44% on average, whereas the other groups showed no comparable improvement. Twitch-timing metrics did not exhibit coordinated enhancement after 6 h, suggesting that the force increase reflects an adaptive biomechanical response rather than broad tissue maturation. These findings identify ES-MS timing as an important design parameter for ECT conditioning.

bioengineering↗

bioRxiv2026

Time-averaged and Time-varying Structure of the Gastric Network Revealed Through fMRI-Electrogastrogram Synchronization

The gastric network, comprised of brain regions whose activity synchronizes with the stomach's slow-wave rhythm, offers a unique window into the brain-body interaction involved in interoceptive processing. While previous work has established the existence of this network, its intrinsic organization and temporal unfolding remain poorly understood. Here, we reanalyzed resting-state fMRI-electrogastrogram data from 43 healthy adults of both sexes to characterize the time-averaged architecture and time-varying reconfiguration of the gastric network. We identified regions exhibiting phase-locked synchronization with the stomach slow electrical rhythm (0.05 Hz) and characterized cortical parcels comprising this network. Time-averaged graph-theoretical analysis revealed a fixed unimodal organization of functional communities, with primary visual, default mode network (DMN) and dorsal attention regions emerging as the principal time-averaged hubs. Next, we applied edge-centric functional connectivity (eFC) to capture the network state during transient high-amplitude "bursts". Time-varying community detection revealed communities whose compositions formed integrative combinations of DMN, visual, attentional and control elements. Edge-derived hubs shifted away from primary visual dominancy in the time-averaged analysis, and were instead directed by DMN regions, suggesting that moments of heightened connectivity in the network are coordinated by multisensory integration rather than passive sensory processing. These findings demonstrate that the gastric network is not merely a time-averaged, sensory-bound system, but rather a flexible and dynamically reconfiguring interoceptive network whose organization is selectively coordinated by transient cofluctuation events. This work provides a comprehensive network analysis of gastric-brain coupling and reveals a temporally structured mode of interoceptive integration that may support adaptive physiological and cognitive regulation.

neuroscience↗

bioRxiv2026

Molecular basis of AMPA receptor labeling by ligand-directed acyl imidazole chemistry in living neurons

Rational design of covalent protein-labeling reagents in complex biological environments requires a molecular-level understanding of how the protein microenvironment governs chemical reactivity; yet, such mechanistic details remain inaccessible to experimental methods alone. In living neurons, Ligand-Directed Acyl Imidazole (LDAI) chemistry has been used to label AMPA receptors as a traceless, affinity-based protein labeling method. Although LDAI labeling reagents have been optimized in the lab, the atomic details of their interactions with the protein and the underlying mechanism remain elusive. In this work, we combined Quantum Mechanical (QM) calculations and molecular dynamics (MD) simulations to propose a detailed reaction mechanism for AMPAR labeling by LDAI reagents and to clarify how the protein microenvironment governs reactivity. Although Lys residues are usually protonated at physiological pH and therefore less nucleophilic in water, our QM results show that Lys labeling is energetically more favorable than competing reactions with Ser or water. MD simulations reveal that PFQX ---the LDAI reagent precursor--- binds dynamically to the GluA2 AMPAR as an antagonist, inducing conformational changes that reshape the local environment of the acyl imidazole (AI) warhead, underscoring that ligand identity strongly affects labeling outcomes. We also identified intra and intermolecular hydrogen bond networks that may contribute to further immobilize and pre-organize the LDAI reagent. Moreover, the probe's chemical nature shapes its interactions with the Ligand Binding Domain (LBD), offering a plausible rationale for the previously experimentally observed ligand-dependent fluorescent response. Taken together, our results establish design principles for exploiting the reagent geometry and binding pocket hydrogen-bonding networks for the rational design of LDAI reagents.

biophysics↗

bioRxiv2026

From Bile Acids to a Gas-Producing Microbiome Phenotype: A Novel Mechanism of Host-Microbiome Communication

Background Microbiome-derived metabolites regulate host physiology, yet bacterial gaseous metabolites remain largely overlooked. Traditionally regarded as fermentation end-products, bacterial gases may act as biologically active mediators of host-microbiome communication. We hypothesized that bile acids regulate bacterial gaseous metabolism and influence host epithelial responses. Methods A high gas-producing clinical Escherichia coli isolate from a patient with moderately severe acute pancreatitis was cultured with selected primary and secondary bile acids. Gas production was assessed by pressure measurements, GC-TCD and GC-MS. Biological activity was evaluated by indirect exposure of Caco-2 and PANC-1 epithelial cells, followed by apoptosis/necrosis assays and whole-transcriptome RNA sequencing. Results Bile acids markedly reshaped bacterial gaseous metabolism. Cholic acid and deoxycholic acid promoted intense gas production, whereas chenodeoxycholic acid almost completely abolished it. Despite minimal apoptosis and necrosis, bacterial gaseous metabolites induced extensive transcriptional remodeling. Caco-2 cells showed stronger responses than PANC-1 cells, particularly to deoxycholic acid-derived gases, involving inflammatory signaling, extracellular matrix remodeling, epithelial plasticity, stress responses, and cancer-associated genes including PTGS2, MMP1, PLAUR, NR4A2, and SERPINE1. PANC-1 cells exhibited a more restricted response involving oxidative stress, proteostasis, and autophagy-associated pathways. Conclusions Our findings indicate that bacterial gases are a previously underrecognized class of microbiome-derived signaling molecules capable of modulating host gene expression independently of direct bacterial contact. We identify a gas-producing microbiome phenotype regulated by bile acid composition, linking microbial metabolism with epithelial signaling. These findings expand the concept of host-microbiome communication and provide a framework for investigating bacterial gaseous metabolites in intestinal and pancreatic diseases.

microbiology↗

bioRxiv2026

CD36 phosphorylation alters the thrombospondin binding site and reduces internal cavity accessibility and volume

The cluster of differentiation 36 (CD36) is a membrane protein with broad physiological roles in health and disease, and its function is regulated in part by phosphorylation. Experimental evidence shows that phosphorylation of Thr92 reduces CD36 affinity for thrombospondin-1 (TSP-1), binding of which initiates antiangiogenic signaling, whereas phosphorylation of Ser237 decreases CD36-mediated fatty acid uptake, with implications for energy metabolism. However, the only available crystal structure of CD36 lacks phosphorylation, and the molecular mechanisms by which phosphorylation regulates CD36 function remain largely unknown. This study provides an atomically detailed computational characterization of CD36 in unphosphorylated and dual phosphorylated states, using molecular dynamics simulations with a total sampling time of 30 microseconds in combination with Markov state models. We present, to our knowledge, the first evidence of a cryptic pocket on CD36 surface that is formed by phosphorylation. This cryptic surface pocket and a loop spanning residues 121-131 form a high affinity binding site for TSP-1 derived ligands, shifting their binding away from the canonical site. We propose that this altered binding provides a molecular basis for the disruption of antiangiogenic signaling upon CD36 phosphorylation. Additionally, our data indicate that, phosphorylation increases helicity and compaction within the helix-loop region spanning residues 296-331, narrowing one of the entrances to the internal cavity and reducing its overall volume. These conformational changes provide a potential mechanistic explanation for the decrease in fatty acid uptake upon CD36 phosphorylation. Our findings provide structural insights that may inform the future design of CD36 modulators and emphasize the importance of targeting phosphorylation induced CD36 conformations in angiogenic and metabolic diseases.

biophysics↗

bioRxiv2026

NAE1-Dependent Protein Neddylation Preserves Endothelial Identity and Vascular Integrity

Background: Endothelial dysfunction is a central driver of cardiovascular and inflammatory diseases, yet the post-translational mechanisms that preserve endothelial homeostasis remain incompletely understood. Protein neddylation, the covalent conjugation of a ubiquitin-like modifier, regulates diverse cellular processes, yet its physiological role in the vascular endothelium remains unknown. This study investigated whether protein neddylation is required to preserve endothelial identity and vascular homeostasis. Methods: We generated tamoxifen-inducible endothelial-specific Nae1 knockout mice to inhibit neddylation and combined bulk RNA sequencing, single-cell and single-nucleus transcriptomics, quantitative proteomics, biochemical analyses, and gain- and loss-of-function approaches to define the role of endothelial neddylation in vascular homeostasis and inflammatory injury. Results: Endothelial-specific Nae1 deletion caused rapid mortality associated with vascular leakage, platelet accumulation, inflammation, and multi-organ injury. Multi-omics analyses demonstrated profound loss of endothelial identity, characterized by suppression of core endothelial programs and activation of inflammatory, procoagulant, and pyroptotic pathways. Single-cell analyses revealed progressive endothelial dysfunction culminating in depletion of the endothelial population and remodeling of the vascular niche. Mechanistically, endothelial neddylation deficiency activated gasdermin D (GSDMD)- and gasdermin E (GSDME)-dependent pyroptosis, whereas dual inhibition of GSDMD and GSDME markedly attenuated inflammatory transcriptomic remodeling, vascular injury, hepatocyte death, immune cell infiltration, and platelet accumulation. Translational analyses demonstrated reduced endothelial neddylation in experimental endotoxemia and decreased expression of neddylation pathway components in human atherosclerosis and COVID-19 datasets. Conversely, restoration of endothelial neddylation partially reversed inflammatory endothelial transcriptomic reprogramming in vivo. Conclusions: NAE1-dependent protein neddylation is an essential regulator of endothelial identity and vascular integrity. Loss of endothelial neddylation promotes gasdermin-dependent pyroptosis and thrombo-inflammatory vascular injury, whereas restoration of the neddylation pathway mitigates inflammatory endothelial dysfunction. These findings identify endothelial neddylation as a fundamental mechanism maintaining vascular homeostasis and a potential therapeutic target for cardiovascular and inflammatory diseases.

pathology↗

bioRxiv2026

A mouse-adapted Staphylococcus aureus strain enables lifelong neonatal colonization and elicits a Th17-dominated immune response

The opportunistic pathogen Staphylococcus aureus persistently colonizes the anterior nares of up to 20% of the human population, yet there were no persistent mouse colonization models to study host-pathogen interaction. Using the mouse-adapted S. aureus strain JSNZ (CC88-MSSA), we established a neonatal S. aureus colonization model in C57BL/6N mice. Natural neonatal colonization was achieved by vertical transmission in a JSNZ-positive breeding colony. Offspring were followed for up to 69 weeks and found persistently colonized in the nose and cecum with high bacterial loads. Adult mice were colonized by intranasal inoculation of JSNZ; controls received PBS. The colonization patterns and the S. aureus-specific T cell responses were then monitored over a period of 28 days and compared between age-matched mice colonized as neonates or adults. The neonatal group remained persistently colonized in nose and gut with high bacterial densities. In contrast, mice colonized as adults had lower and declining bacterial loads in the nose. Some eliminated S. aureus from the nares, while all remained colonized in the gut. Neonatally colonized mice exhibited reduced nasal chemokine levels, which may have favored the prolonged S. aureus persistence. Ex vivo re-stimulation of cervical lymph node cells with an S. aureus antigen cocktail revealed a Th17-dominated antigen-specific T cell response in both colonized groups. The lymph node cells secreted large amounts of IL-17, but Th1-, Th2-associated and regulatory cytokines were also detected. The cytokine patterns were similar in both colonized groups except for IL-5, which was more abundant upon neonatal colonization. In conclusion, vertical transmission of the mouse-adapted S. aureus strain JSNZ reliably establishes persistent high-density neonatal colonization, providing a physiologically relevant model for the study of S. aureus host interactions. Route and timing of colonization do not fundamentally affect the T cell response to S. aureus.

immunology↗

bioRxiv2026

Test-Retest Reliability of Motor Evoked Potentials Across Eight Bilateral Lower-Limb Muscles

Objectives: Transcranial magnetic stimulation (TMS) is widely used to probe corticospinal excitability by eliciting motor evoked potential (MEP)s in targeted muscles, with MEP characteristics such as magnitude and latency reflecting the physiological state of the pathways being stimulated. Although numerous studies have examined MEP reliability in upper extremity muscles, less is known about the reliability of this measurement across the lower extremity. We hypothesized that inter-session, test-retest reliability of MEPs recorded simultaneously from multiple lower-limb muscles, from a single TMS location, would differ by muscle, stimulation intensity, and quantification method. Materials and Methods: Ten healthy participants (5 males, 5 females) completed three TMS sessions separated by atleast one week. At each session, the stimulation hotspot was identified using a five-location virtual grid anchored at the vertex, with electromyography (EMG) recorded from all eight muscles of interest at each grid location; the grid location producing the largest and most consistent MEPs in the tibialis anterior (TA), the primary target muscle, was selected as the stimulation site and held constant across all three sessions. MEPs were then recorded bilaterally from the TA, soleus, rectus femoris, and biceps femoris muscles at two stimulation intensities (110% and 120% resting motor threshold (RMT)). MEP size was quantified using mean rectified magnitude and peak-to-peak amplitude, and inter-session reliability was assessed using intraclass correlation coefficients (ICC). Bland-Altman analysis was used to characterize the range of measurement variability across all eight muscles. Results: MEP size differed across sessions, and reliability varied by muscle, intensity, and quantification method. The highest reliability was observed in the right TA, the muscle used to establish the stimulation hotspot, using mean rectified magnitude at 120% RMT. Reliability was comparatively lower in the seven non-target muscles recorded from the same fixed stimulation site, indicating that MEP consistency was not uniform across the lower-limb musculature. Conclusions: MEP reliability in the lower extremity depends heavily on the muscle, stimulation intensity, and quantification method used, and is highest in the muscle for which the stimulation site was optimized. These findings support the interpretation that coil positioning targeted to a specific muscle yields more consistent responses in that muscle than in others recorded from the same fixed site, and underscore the importance of careful muscle selection and hotspot optimization when designing TMS protocols for longitudinal or clinical lower-limb research.

neuroscience↗

bioRxiv2026

Multiscale modelling of drug-host-pathogen interaction: quantifying drug and immune contributions to treatment response

Background and Objective: Predicting treatment outcomes in infectious diseases requires accounting for the interplay between drug effects, pathogen dynamics, and host immunity. Integrating pharmacological and immunological approaches into a single simulation environment remains a fundamental challenge in both theory and practice. We aimed to develop and validate a multiscale in silico framework coupling these processes, and to quantify their respective contributions to bacterial clearance. Methods: We present the Drug-Host-Pathogen Interaction (DHPI) framework, combining three independent mechanistic components: a physiologically based pharmacokinetic model of drug disposition, a pharmacokinetic-pharmacodynamic model of drug-induced bacterial killing, and a stochastic agent-based model of the immune response. Continuous concentration profiles are time-averaged onto the agent-based time grid, assigned to bacterial phenotypic states, and converted into per-agent killing probabilities, so that drug-mediated and immune-mediated death events are recorded separately at each step. The framework was applied to simulate symptomatic pulmonary tuberculosis. Phenotype-specific drug-efficacy parameters were inferred using Approximate Bayesian Computation from historical clinical data on eight weeks of 600 mg rifampicin monotherapy, and validated against independent early bactericidal activity data over a disjoint time window. Results: The calibrated framework reproduced the observed decline in bacterial load, and matched reported early bactericidal activity over the first week. In a virtual cohort of symptomatic patients, drug-mediated killing accounted for 81-88% and immune-mediated killing for 12-19% of total bacterial elimination over the 60-day treatment course, while the dormant, granuloma-contained fraction rose from 0.20-0.29 in the first week to 0.85-0.89 at treatment completion. Over a follow-up of up to 50 years, patients reaching clinical cure had accumulated more memory lymphocytes during treatment than those progressing to clinical failure or death; moreover, the final outcome depended on the immune changes occurring during therapy rather than on the initial disease stage. Conclusions: The results show that the DHPI framework can reproduce treatment dynamics observed in patients and enable the analysis of how therapy reshapes host immune responses and subsequent disease trajectories. By explicitly representing drug-host-pathogen interactions, it provides a mechanistic basis for in silico treatment simulations and for the study of long-term immune consequences of antimicrobial therapy.

systems biology↗