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At least 109 records · Page 6Linked to original sources

bioRxiv2019

Multivoxel Pattern Analysis Reveals Dissociations Between Subjective Fear and Its Physiological Correlates

In studies of anxiety and other affective disorders, objectively measured physiological responses have commonly been used as a proxy for measuring subjective experiences associated with pathology. However, this commonly adopted biosignal approach has recently been called into question on the grounds that subjective experiences and objective physiological responses may dissociate. We performed machine-learning based analysis on functional magnetic resonance imaging (fMRI) data to assess this issue in the case of fear. Participants were presented with pictures of commonly feared animals in an fMRI experiment. Multivoxel brain activity decoders were trained to predict participants subjective fear ratings and their skin conductance reactivity, respectively. While subjective fear and objective physiological responses were correlated in general, the respective whole-brain multivoxel decoders for the two measures were not identical. Some key brain regions such as the amygdala and insula appear to be primarily involved in the prediction of physiological reactivity, while some regions previously associated with metacognition and conscious perception, including some areas in the prefrontal cortex, appear to be primarily predictive of the subjective experience of fear. The present findings are in support of the recent call for caution in assuming a one-to-one mapping between subjective sufferings and their putative biosignals, despite the clear advantages in the latters being objectively and continuously measurable in physiological terms.

neuroscience↗

bioRxiv2019

What do I do now? Intolerance of uncertainty is associated with discrete patterns of anticipatory physiological responding to different uncertain contexts

Heightened physiological responses to uncertainty are a common hallmark of anxiety disorders. Many separate studies have examined the relationship between individual differences in intolerance of uncertainty (IU) and physiological responses to uncertainty during different contexts. Despite this, little is known about the extent to which physiological responses during different uncertain contexts covary within individuals based on IU. Anticipatory physiological responses to uncertainty were assessed in three different contexts (associative threat learning, basic threat uncertainty, decision-making) within the same sample (n = 45). During these tasks, behavioural responses (i.e. reaction times, choices), skin conductance and corrugator supercilli activity were recorded. In addition, self-reported IU and trait anxiety were measured. IU made different contributions to the physiological measures during each task. IU was found to modulate both skin conductance and corrugator supercilii activity for the associative threat learning and decision-making contexts. However, trait anxiety was found to modulate corrugator supercilii activity during the basic threat uncertainty context. Ultimately, this research helps us further tease apart the role of IU in different uncertain contexts, which will be relevant for future IU-related models of psychopathology.

neuroscience↗

bioRxiv2019

Data-driven integration of hippocampal CA1 synapse physiology in silico

The anatomy and physiology of synaptic connections in rodent hippocampal CA1 have been exhaustively characterized in recent decades. Yet, the resulting knowledge remains disparate and difficult to reconcile. Here, we present a data-driven approach to integrate the current state-of-the-art knowledge on the synaptic anatomy and physiology of rodent hippocampal CA1, including axo-dendritic innervation patterns, number of synapses per connection, quantal conductances, neurotransmitter release probability, and short-term plasticity into a single coherent resource. First, we undertook an extensive literature review of paired-recordings of hippocampal neurons and compiled experimental data on their synaptic anatomy and physiology. The data collected in this manner is sparse and inhomogeneous due to the diversity of experimental techniques used by different labs, which necessitates the need for an integrative framework to unify these data. To this end, we extended a previously developed workflow for the neocortex to constrain a unifying in silico reconstruction of the synaptic physiology of CA1 connections. Our work identifies gaps in the existing knowledge and provides a complementary resource towards a more complete quantification of synaptic anatomy and physiology in the rodent hippocampal CA1 region.

neuroscience↗

bioRxiv2019

Plumage manipulation alters the integration of social behavior, physiology, internal microbiome, and fitness.

Signals often covary with physiological and behavioral traits to form an axis of integrated phenotypic variation associated with reproductive performance. This pattern of phenotypic integration could result from intrinsic between-individual differences that are causally related to signal production, physiology, and behavior. Alternatively, signal expression itself might generate dynamic feedback between physiology, behavior, and the experienced social environment, resulting in an integrated phenotype. Here, we manipulated the plumage of female tree swallows (Tachycineta bicolor) to decouple the expression of a social signal from any pre-existing behavioral or physiological differences. We collected a time series of physiological samples, monitored social interactions with a sensor network, and tracked reproductive performance. Relative to sham controls, dulled females experienced an altered social environment; overall, these females were visited more by conspecific females and less by males. Dulled females subsequently changed their own behavior by initiating fewer interactions and increasing nestling provisioning. These differences resulted in an altered internal microbiome and glucose levels and, ultimately, dulled females produced more offspring. Moreover, dulled females produced larger clutches than control females in the year after the manipulation. Thus, signal variation alone--independent from any pre-existing differences--had a sustained causal affect on a suite of integrated traits. This finding suggests that dynamic feedback may play an important role in coordinating an integrated signaling phenotype. Our results have implications for understanding how variation in signal expression arises and is maintained and the extent to which the information encoded in signals is contingent upon their use in a social environment.

zoology↗

bioRxiv2025

Linking arterial biomechanics, contractility, and microstructure: A novel platform for combined structure-function assessment in murine arteries under physiological conditions

BackgroundEx vivo characterization of arterial viscoelastic properties shows arterial stiffness and contractility to depend on both axial stretch and dynamic pressurization. While these arterial properties are the subject of extensive ex vivo research due to their relevance to vascular pathophysiology, only few experimental approaches mimic both physiological axial stretch and dynamic pressurization when characterizing arterial biomechanics, vasoreactivity, and tissue microstructure. To fill this gap, we developed a custom dynamic biaxial pressure myograph compatible with two-photon laser scanning microscopy (TPLSM). MethodsWe studied five murine carotid artery segments. Sample viscoelastic behaviour was characterized by quasi-static and dynamic pressurization experiments at and around physiological axial stretch, as well as quasi-static stretching at physiological pressures. In addition, vasoconstriction in response to 2 {micro}M phenylephrine was measured during dynamic pressurization and with axial loads that mimicked physiological conditions. Lastly, arterial collagen, elastin, and cell nuclei were imaged using TPLSM with the sample at physiological axial stretch and pressurized at 100 mmHg. ResultsThe setup enabled capture of the non-linear biaxial viscoelastic behaviour of the arterial wall as well as the viscoelastic stiffening with dynamic pressurization. Modulation of these characteristics upon stimulated smooth muscle contraction was also captured well. Moreover, the related ultrastructural properties of the collagen-elastin network as well as the transmural cell distribution, were recordable at corresponding loading conditions by TPLSM. ConclusionThe presented multi-modal characterization platform enables comprehensive ex vivo measurements under well-controlled in vivo-like loading conditions, for in-depth studies focusing on arterial stiffening. Our findings emphasize the need for controlling dynamic pressure and axial stretch conditions in investigating mechanistic and constitutive aspects of arterial stiffening.

bioengineering↗

bioRxiv2025

Phenotypic Characterization of Signature-Tagged Mutants Identifies Physiological Determinants of Vibrio vulnificus Fitness

Vibrio vulnificus is an opportunistic marine pathogen that causes severe wound-associated and systemic infections. Following entry into the host, the bacterium must rapidly adapt to host-associated stresses that differ substantially from those encountered in aquatic environments. However, the physiological functions supporting bacterial fitness during infection remain incompletely understood. Previously, we applied signature-tagged mutagenesis (STM) to identify genes required for V. vulnificus survival during host infection, revealing numerous loci that did not correspond to classical toxin-encoding genes. In the present study, we extended this genome-wide screen by linking STM-identified mutations to observable fitness-related phenotypes. Functional annotation revealed enrichment of genes associated with chemotaxis, flagellar motility, regulation, metabolism, and poorly characterized functions. Phenotypic analyses showed that many STM-derived mutants exhibited defects in swimming motility and altered colony surface properties. Bioluminescence imaging further revealed distinct patterns of impaired persistence and dissemination within host tissues, while several mutants displayed increased susceptibility to phagocytic stress in an HL-60-derived neutrophil model. Notably, some regulatory mutants affecting global signaling pathways exhibited impaired tissue dissemination despite retaining resistance to phagocytic stress, indicating the presence of fitness determinants that operate independently of classical surface-associated or cytotoxic traits. Together, these findings demonstrate that V. vulnificus fitness during infection depends on diverse physiological pathways beyond classical virulence factors, highlighting the value of phenotype-centered analyses for understanding bacterial adaptation in host-associated environments. ImportanceVibrio vulnificus causes rapidly progressive wound infections and septicemia, yet the bacterial functions that support fitness within host environments remain incompletely defined. While substantial effort has focused on canonical virulence factors and regulation, increasing evidence suggests that successful infection also depends on broader physiological adaptation. In this study, we link signature-tagged mutagenesis with systematic phenotypic analyses to define physiological determinants of V. vulnificus fitness during host-associated infection. Our results demonstrate that genes involved in motility, regulatory signaling, metabolism, and stress tolerance collectively shape bacterial persistence and dissemination in host tissues. Notably, we identify regulatory and metabolic determinants that influence fitness independently of classical surface-associated or cytotoxic traits, highlighting noncanonical pathways that contribute to pathogenic success. By integrating genome-wide screening with phenotype-centered analyses, this work advances understanding of how physiological adaptation underpins V. vulnificus infection and provides a framework for studying bacterial fitness alongside established concepts of bacterial virulence.

microbiology↗

bioRxiv2026

Integrated physiological markers of drought tolerance and yield stability in cotton under deficit irrigation

The selection of drought-resistant cotton genotypes with high productivity and improved water-use efficiency is an increasingly pressing challenge in arid and semi-arid cotton-growing regions, where climate variability is intensifying water scarcity. This study evaluated two widely cultivated cotton varieties in Texas, NG 4190 B3XF and ST 4990 B3XF, under full and moderate deficit irrigation to identify physiological markers associated with contrasting yield responses under water limitation. A comprehensive set of physiological traits was assessed, including plant water status, leaf gas exchange, carbon isotope composition ({delta}13C), total nitrogen and C/N ratio, chlorophyll fluorescence, light and CO{square} response curves, and canopy temperature. While no yield differences were observed under full irrigation, moderate water deficit resulted in stable seed and fiber yield in NG 4190, but significant yield reduction in ST 4990. Yield differences were not explained by instantaneous gas exchange or direct biochemical limitations of photosynthesis, but rather by integrated physiological behavior over time. Key discriminating traits included midday relative water content (RWC), photosynthetic light-response parameters ( and Pm), stomatal optimization parameter (g{square}), and {delta}13C. NG 4190 exhibited higher RWC, more negative {delta}13C, and higher g{square} values, indicating a less conservative stomatal regulation strategy that supported sustained carbon assimilation under water stress. These findings provide insight into the physiological mechanisms underlying cotton performance under drought and support the use of integrated physiological markers for the selection of resilient genotypes in water-limited environments.

plant biology↗

bioRxiv2026

Approaching the limit: Modeling the physiological bounds of playable space in football

AO_SCPLOWBSTRACTC_SCPLOWPitch control models quantify spatial dominance in football by estimating which player can arrive first at each pitch location, but they treat all players as equivalently capable regardless of preceding effort. We introduce physiology-aware pitch control (Phys-PC), a model-agnostic time-to-arrive correction that imposes two physiological capacity channels calibrated from tracking data: a transient recoverable burden capturing incomplete recovery from recent high-intensity efforts, and a cumulative non-recoverable drain accumulating across match play. Both channels reduce a bounded access scale that modulates kinematic TTA before any downstream pitch-control computation. All parameters are anchored to exercise-physiology benchmarks; no laboratory measurements are assumed. Applied to a 64-match international tournament, Phys-PC reveals structure that kinematic models cannot detect. In head-to-head races, the dominant burden channel shifts from transient to cumulative over the course of a match, with a transient resurgence in the final 15 minutes. These physiological asymmetries predict match outcomes: relative reserve advantage is associated with higher odds of winning ground challenges (OR = 1.20, p = 0.006; +4.2 pp), completing over-the-top passes past recovering defenders (OR = 1.45, p = 0.034; +8.3 pp), and progressing possession sequences into the final third (OR = 1.31, p = 0.013; +5.1 pp). At the player-profile level, an acute-cumulative decomposition of contested space access separates roles and individuals whose territorial reach is maintained through sustained positioning from those whose access is rebuilt through repeated high-intensity actions, providing a physiological lens on team tactical structure.

bioengineering↗

bioRxiv2026

Predictive Feature Engineering for Stress Detection using Physiological Signals, A Comparative Study

This paper presents a two-stage pipeline for implicit feature engineering in time series-based physiological stress detection using electrodermal activity (EDA) signals. In the first stage, we forecast three descriptive statistics of future EDA signals over short horizons (3, 5, and 10 seconds) based on a 60-second context window. In the second stage, a lightweight linear classifier detects stress from these predicted statistics. We evaluate three forecasting architectures spanning the domain expertise spectrum: a domain-specific bidirectional long short-term memory (BiLSTM) recurrent neural network, zero-shot and fine-tuned variants of Amazon Chronos T5 time series foundation model, and the Tabular Prior-data Fitted Network (TabPFN) applied to engineered physiological features. Experiments on the publicly available Wearable Stress and Affect Detection (WESAD) dataset, comprising chest-worn multimodal physiological signals from 15 subjects under baseline and stress conditions, use subject-independent 5-fold cross-validation and show that the domain-specific BiLSTM and TabPFN achieve comparable classification performance, with mean area under the receiver operating characteristic curve (AUC) values of 0.859-0.882 and 0.863-0.883 respectively. Both remain well ahead of the Chronos variants, which yield 0.629-0.777. Chronos models quickly reach performance saturation regardless of training depth, highlighting challenges in tokenizing continuous physiological time series. The proposed approach advances implicit feature engineering for wearable stress monitoring by leveraging forecasting as a powerful inductive bias, thereby improving robustness and providing insights into the limitations of the foundation model for physiological signals.

bioengineering↗

bioRxiv2026

What do satellite vegetation indices actually measure? Photosynthetic capacity rather than transient physiological function across 328 global FLUXNET sites

A direct empirical relationship between gross primary productivity (GPP) estimated by the eddy covariance method and satellite vegetation indices (VIs) has been widely observed across diverse ecosystems globally. Building on this observed covariation, VIs are frequently utilized as critical parameters - such as the fraction of absorbed photosynthetically active radiation (fPAR) - within light use efficiency (LUE) and greenness-based models for carbon cycle monitoring. However, actual canopy carbon assimilation is jointly governed by slowly evolving structural parameters and highly dynamic functional traits, such as physiological efficiency. The extent to which the macro-scale VI-GPP covariance is driven by structural scaffolding, and how this structural signal decouples from physiological function under environmental stress, remains to be systematically quantified. Here, we synthesized half-hourly eddy covariance measurements from 328 globally distributed sites and paired them with a rigorously angle-normalized Enhanced Vegetation Index (nadir view and fixed solar zenith angle at 30 degrees, EVI_SZA30). By applying a nonlinear light-response curve model across 54,720 high-frequency temporal windows, we mechanistically disentangled observed actual GPP (GPP_EC) into baseline photosynthetic capacity (P_c) and intrinsic quantum yield (alpha). Our results demonstrate that the macroscopic covariance between EVI_SZA30 and GPP_EC (R^2=0.554) is primarily driven by the index's robust ability to track structural capacity (P_c, R^2=0.538). In contrast, EVI_SZA30 exhibits limited sensitivity to high-frequency variations in functional traits like physiological efficiency (alpha, R^2=0.038). Particularly in water-limited biomes (e.g., open shrublands and woody savannas), intense environmental stress triggers rapid stomatal regulation while the physical canopy structure remains relatively stable. Consequently, the correlation between EVI and P_c becomes notably stronger than its correlation with actual GPP_EC, highlighting a pronounced structural-physiological decoupling. Because discrete overpasses by sun-synchronous polar-orbiting satellites face intrinsic temporal constraints in capturing sub-daily physiological down-regulation (e.g., midday photosynthetic depression), future monitoring paradigms could greatly benefit from the continuous, high-frequency observations provided by next-generation geostationary (GEO) satellites to bridge the gap between structural parameters and transient ecosystem function.

ecology↗

bioRxiv2026

Physiological robustness of MScanFit to simulated motor unit loss and remodelling

Introduction: MScanFit estimates motor unit number and size from compound muscle action potential (CMAP) scans, but its accuracy may depend on the physiological processes that shape motor unit loss and remodelling. We reproduced the general dynamic remodelling framework used in the original MScanFit simulation and expanded it to test MScanFit robustness across physiologically heterogeneous conditions. Methods: Generative computational models simulated CMAP scans from motor unit pools undergoing progressive loss from 160 to 5 surviving motor units. Twelve remodelling conditions combined denervation pattern (random or selective), reinnervation method (random, distributive, or size-weighted), and neuromuscular resilience (20% or 60%); two additional conditions modelled denervation without collateral reinnervation. MScanFit estimates were compared with the known motor unit numbers and mean motor unit sizes used to generate each scan. Results: MScanFit reproduced the principal behaviour reported in the original simulation and generally tracked progressive motor unit loss across heterogeneous remodelling conditions. However, motor unit number estimation (MUNE) error changed systematically with remodelling physiology. Selective denervation and distributive reinnervation increased error at several intermediate stages of motor unit loss, whereas 60% resilience produced greater error than 20% resilience at every stage after remodelling began. Motor unit size estimates also tracked the underlying increase in mean unit size, but their accuracy was more strongly affected by remodelling, particularly with 60% resilience and advanced motor unit loss. Conclusion: MScanFit motor unit number estimates were broadly robust to substantial motor unit loss and neuromuscular remodelling but were not physiologically invariant. Denervation and collateral reinnervation systematically influenced the magnitude and direction of estimation error, indicating that variation in MScanFit performance can arise from differences in the underlying motor unit population. These findings support MScanFit as a robust measure of motor unit loss across heterogeneous neuromuscular phenotypes and show that some of its estimation variability has a physiological basis.

neuroscience↗

bioRxiv2026

An SNRNP70-eGFP knock-in zebrafish line reveals the physiological localisation and dynamics of endogenous SNRNP70 during development

SNRNP70 is a core spliceosome RNA-binding protein best known for its essential role in nuclear pre-mRNA splicing. Although traditionally associated with nuclear RNA processing, previous studies have identified important extranuclear functions for SNRNP70 in neurons, including roles in mRNA stability, localisation, and axonal transport. Yet, much of our understanding of SNRNP70 localisation has relied on overexpression or transgenic approaches, leaving a critical gap in our knowledge of where endogenous SNRNP70 resides and how it behaves in living neurons under physiological expression conditions. Here, we address this limitation by establishing and validating a novel zebrafish SNRNP70-eGFP CRISPR knock-in line, enabling direct visualisation of the endogenous protein. eGFP was fused to the C-terminus of endogenous SNRNP70 while retaining the native 3' untranslated region, preserving key regulatory features of the endogenous locus. We demonstrate that the knock-in faithfully reports endogenous SNRNP70 expression and reveals widespread physiological localisation throughout the developing nervous system, including prominent enrichment within axonal and synaptic compartments. Crucially, live in vivo imaging reveals that endogenous SNRNP70 is dynamically localised within neuronal mRNP granules, providing direct evidence of its physiological behaviour in these structures without the confounding effects of protein overexpression. Proximity ligation analyses further demonstrates associations between endogenous SNRNP70 and PABPC1B, FUS, and UPF1, which are established neuronal mRNP granule components. Together, our work provides a validated genetic and imaging resource for investigating SNRNP70 at endogenous levels in the living nervous system. By overcoming key limitations of conventional transgenic and overexpression-based approaches, the SNRNP70-eGFP knock-in enables physiological analysis of SNRNP70 localisation and dynamics and reveals its prominent and dynamic organisation within neuronal mRNP granules. More broadly, this work highlights how endogenous fluorescent tagging can provide a versatile platform for resolving the spatial organisation of RNA-binding proteins in living neurons under physiological expression conditions and provide new insight into the regulation of neuronal mRNA fate.

neuroscience↗

bioRxiv2026

Physiological folate levels constrain nucleotide synthesis and increase dependence on nucleotide salvage

Proliferating cells must acquire nucleotides to support DNA replication, yet how cells meet these nucleotide demands for proliferation under physiological conditions remains understudied. Here, we investigated how physiological nutrient availability shapes nucleotide acquisition strategies in a mouse model of B-cell acute lymphoblastic leukemia (B-ALL). To assess how environmental nutrients impact nucleotide metabolism, we formulated a mouse plasma-like medium (MPM) that reproduces the circulating metabolite composition of plasma from mice with B-ALL and assessed how this influenced nucleotide metabolism relative to standard culture conditions, where nucleotide acquisition has historically been studied. We find that leukemia cells cultured in MPM acquire nucleotides through salvage pathways, and that select nucleotide salvage pathways are required for proliferation under physiological conditions. Of note, this dependency on nucleotide salvage in plasma-like conditions was not caused by precursor metabolite limitation for de novo synthesis. Instead, we found that physiological folate levels are insufficient to support deoxynucleotide triphosphate (dNTP) synthesis for genome replication, leading to DNA replication stress and impaired proliferation when nucleotide salvage is disrupted. Consistently, dietary folate restriction exacerbates the impaired leukemia progression phenotype of nucleotide salvage-deficient B-ALL cells. Together, these findings demonstrate that access to folates is an endogenous limitation for nucleotide synthesis in plasma-like nutrient conditions, increasing the relevance of nucleotide salvage pathways for leukemia progression. More broadly, this work highlights how micronutrient abundance can influence metabolic dependencies and reveals that folate levels shape nucleotide metabolism under physiological conditions.

cancer biology↗

bioRxiv2026

Physics-informed neural network for predicting myocardial mechanics from in vivo physiological measurements

Structural heart diseases (SHDs) are characterized by progressive myocardial remodeling, yet the tissue-level mechanical properties underlying this process cannot be measured directly in vivo. This limitation restricts the ability of conventional physiological measurements to fully characterize myocardial remodeling and disease progression. Here, we present a physics-informed neural network (PINN) framework that integrates constitutive biomechanics with organ-level physiological measurements to simultaneously infer myocardial biomechanical descriptors and predict physically consistent stress responses. By embedding a hyperelastic constitutive model within the learning process, the framework links physiological measurements with tissue-level mechanics while preserving biomechanical consistency. Using right ventricular remodeling in pulmonary hypertension (PH) as a representative model of SHDs, the proposed framework accurately reproduced nonlinear stress-stretch behavior and outperformed conventional data-driven machine learning approaches for stress prediction. Furthermore, incorporation of PINN-derived tissue-level descriptors with organ-level physiological measurements improved disease stratification and enhanced separation between control, mild, and severe PH remodeling states. These findings support physics-informed constitutive learning as an interpretable framework for integrating organ-level physiology with tissue-level biomechanics and establish a foundation for future biomechanics-informed characterization of myocardial remodeling across SHDs.

bioengineering↗

bioRxiv2020

"The stressed bird in the hand": Influence of sampling design on the physiological stress response in a free-living songbird

Despite the widely used application of standardized capture-handling protocols to collect blood and assess the physiological stress response, the effect of the actual sampling design (e.g. timing and the number of blood samples) often differs between studies, and the potential implications for the measured physiological endpoints remain understudied. We, therefore, experimentally tested the effects of repeated handling and multiple blood sampling on the stress response in wintering free-living great tits (Parus major). We modified a well-established sampling protocol of avian studies by adding either an additional blood sample or a "sham-manipulation" (i.e. handling associated with the blood sampling procedure without venepuncture), to disentangle the effects of handling stress and blood loss. We combined three different stress metrics along the endocrine-immune interface to investigate the acute short-term stress response: total corticosterone levels (CORT), the heterophil/lymphocyte ratio (H:L), and the Leukocyte Coping Capacity (LCC). Our study provided three key results: i) no relationship between CORT-levels, LCC and H:L, confirming that these three parameters represent different physiological endpoints within the stress response; ii) contrasting dynamics in response to stress by the measured parameters and iii) no difference in stress levels 30 minutes after capture due to one additional blood sampling or handling event. By optimising the sampling design, our results provide implications for animal welfare and planning experimental procedures on stress physiology in passerine species. Summary StatementWhen testing the short-term stress response in free living passerines, both - the scientist and the bird may be better off with a 15-minute stress protocol.

physiology↗

bioRxiv2021

Emotion Recognition in a Multi-Componential Framework: The Role of Physiology

Emotions are rich and complex experiences involving various behavioral and physiological responses. While many empirical studies have focused on discrete and dimensional representations of emotions, these representations do not fully reconcile with recent neuroscience studies that increasingly suggest a multi-process mechanism underlying emotional experience. Moreover, the latter view accords with psychological theories that consider emotions as multicomponent phenomena, such as appraisal theories. Although there is no complete consensus on the specific components of emotions and fundamental principles defining their organization, the Component Process Model (CPM) is well established framework describing an emotion as a dynamic process with five major highly interrelated components: cognitive appraisal, expression, motivation, physiology and feeling. Yet, few studies have systematically investigated a range of discrete emotions through this full multi-componential view. In the present study, we therefore elicited various emotions during movie watching and measured their manifestation across these components. Our primary goal was to investigate the relationship between physiological measures and the theoretically defined components of emotions. In addition, we also investigated whether discrete emotions could be predicted from information provided by the multicomponent response patterns, as well as the specific contributions of each component in such predictions. Results suggest that physiological features are interrelated to all other components of emotion, but the least significant predictors for emotion classification. Overall, emotion prediction was significantly higher when classifiers were trained with all five components. The findings therefore support a description of emotion as a dynamic multicomponent process, in which the emergence of a conscious feeling state requires the integration of all the components.

physiology↗

bioRxiv2023

CD38 assigns physiological function to soluble uric acid

Excessive elevation or reduction of soluble uric acid (sUA) levels has been linked to some of pathological states, raising another subject that sUA at physiological levels may be essential for the maintenance of health. Yet, the fundamental physiological functions and molecular targets of sUA remain largely unknown. Using enzyme assays and in vitro and in vivo metabolic assays, we demonstrate that sUA directly inhibits the hydrolase and cyclase activities of CD38 via a reversible non-competitive mechanism, thereby limiting nicotinamide adenine dinucleotide (NAD+) degradation. CD38 inhibition is restricted to sUA in purine metabolism, and a structural comparison using methyl analogs of sUA such as caffeine metabolites shows that 1,3-dihydroimidazol-2-one is the main functional group. Moreover, sUA at physiological levels prevents crude lipopolysaccharide (cLPS)-induced systemic inflammation and monosodium urate (MSU) crystal-induced peritonitis in mice by interacting with CD38. Together, this study unveils an unexpected physiological role for sUA in controlling NAD+ availability and innate immunity through CD38 inhibition, providing a new perspective on sUA homeostasis and purine metabolism.

physiology↗

bioRxiv2024

Development and Characterization of a 2D Porcine Colonic Organoid Model for Studying Intestinal Physiology and Barrier Function

The porcine colon epithelium plays a crucial role in nutrient absorption, ion transport, and barrier function. However ethical concerns necessitate the development of alternatives to animal models for its study. The objective of this study was to develop and characterise a two-dimensional (2D) in vitro model of porcine colonic organoids that closely mimics native colon tissue, thereby supporting in vitro research in gastrointestinal physiology, pathology, and pharmacology. Porcine colonic crypts were isolated and cultured in three-dimensional (3D) organoid systems, which were subsequently disaggregated to form 2D monolayers on transwell inserts. The integrity of the monolayers was evaluated through the measurement of transepithelial electrical resistance (TEER) and electron microscopy. The functional prerequisites of the model were evaluated through the measurement of the mRNA expression of key ion channels and transporters, using quantitative RT-PCR. Ussing chamber experiments were performed to verify physiological activity. The 2D monolayer displayed robust TEER values and retained structural characteristics, including microvilli and mucus-secreting goblet cells, comparable to those observed in native colon tissue. Gene expression analysis revealed no significant differences between the 2D organoid model and native tissue with regard to critical transporters. Ussing chamber experiments demonstrated physiological responses that were consistent with those observed in native colonic tissue. In conclusion, 2D porcine colonic organoid model can be recommended as an accurate representation of the physiological and functional attributes of the native colon epithelium. This model offers a valuable tool for investigating intestinal barrier properties, ion transport, and the pathophysiology of gastrointestinal diseases, while adhering to the 3R principles.

physiology↗