Frontiers in Physiology

Hypermobile Ehlers-Danlos Syndrome (hEDS) is a genetic connective tissue disorder characterized by hypermobile joints, chronic pain, fatigue, brain fog, orthostatic intolerance, and GI symptoms and dysmotility. Its heterogeneous presentation contributes to poor quality of life, inappropriate interventions, and prolonged diagnostic delays, often up to 10 years. This study primarily aimed to determine if physiological signals captured by a medical-grade wrist wearable could characterize autonomic patterns in hEDS and relate them to symptoms. Individuals with hEDS (n=30) and healthy controls (n=28) wore a medical grade smartwatch for 30 days, collecting continuous heart rate variability, activity, oxygen saturation, and blood pressure, alongside initial baseline symptom and quality-of-life surveys. Individuals with hEDS showed greater instability and variability in both systolic and diastolic blood pressure as well as the HRV metric LF/HF ratio, in comparison to healthy controls (p-values: 0.04, 0.02, 0.02). During sleep, metrics of parasympathetic activity (HRV measures: HF power, pNN50, RMSSD) trended lower in hEDS than healthy in comparison. As expected, survey domains assessing physiologic symptoms and quality-of-life were significantly worse in the hEDS cohort (p-values < 0.05). Notably, autonomic metrics correlated with GI symptoms in the hEDS cohort (Spearman's {rho} range: 0.38-0.60), and psychological symptoms in the healthy cohort (Spearman's {rho} range: -0.47-0.41). Principal component analysis (PCA) of physiologic and symptom features clearly separated groups, supporting distinct physiologic profiles. Combination of GI symptom index and wearable monitoring show promise as a hybrid screening approach that could substantially shorten the time to diagnosis in this population.

Circulating stem and progenitor cells (SPCs), including mesenchymal stromal cells (MSCs) and hematopoietic stem/progenitor cells (HSPCs), are mobilised after tissue injury but their temporal behaviour after hemorrhagic shock (HS) and relationship to cytokine milieus and outcome remain unclear. In a prospective observational cohort at JPN Apex Trauma Centre, AIIMS, New Delhi we studied 100 participants: 50 trauma patients with hemorrhagic shock and traumatic brain injury (HS index group), 25 trauma patients without HS, and 25 minor-injury controls. Peripheral blood was collected at admission (day 0) for all groups and additionally at days 3, 7 and 14 for the HS group. PBMCs were phenotyped by flow cytometry (HSPC markers: CD45, CD123, CD38, CD34; MSC markers: CD105, CD73, CD90) and serum SDF-1, VEGF-A, EGF, GRO- and GRO-{beta}, GM-CSF and G-CSF were measured by ELISA; group and time effects were evaluated with mixed-effects models and correlations by Spearman tests (two-tailed p<0.05). At admission, trauma patients without HS had significantly higher MSC and HSPC-like populations versus controls (p<0.0001). In the HS cohort SPC percentages rose modestly at day 0-3 then declined sharply by days 7-14 (time effect p<0.0001); non-survivors exhibited significantly higher early SPC and cytokine levels that persisted until death while survivors showed an early rise followed by decline (outcome and time interaction p<0.0001). All cytokines were up-regulated in trauma groups, peaked at day 0-3 in HS patients, and correlated positively with SPC counts (notably SDF-1, VEGF-A, G-CSF, Gro- and GM-CSF; Spearman p<0.05); higher early SPC and cytokine signatures associated with greater organ dysfunction (higher SOFA) and with timing of sepsis. These findings indicate that trauma provokes an early SPC and cytokine response that in HS is followed by later decline, and that persistent early elevation predicts worse outcomes, suggesting serial SPC and cytokine profiling may have prognostic value and identify an early therapeutic window for regenerative or immunomodulatory interventions.

Cerebral blood flow (CBF) control is essential for normal brain function and is disrupted in pathological conditions. Arterial diameters are tightly regulated to provide on demand increases in blood flow in regions of neuronal activity. Pericytes (PCs) exhibit robust myogenic tone and may also respond to neuronal activity to fine-tune local resistance and blood flow. Thus, mural control of microcirculatory resistance may extend beyond arteries and arterioles. Yet, PCs electrophysiology and contractility have not been thoroughly characterized, and this prohibits an integrated view of brain blood flow control. In this study, we develop a detailed mathematical model of mural cell electrophysiology, Ca2+ dynamics and biomechanics. The model is informed by electrophysiological data in smooth muscle cells (SMCs) or PCs and predictions are compared against pressure-induced responses in isolated arterioles and capillaries, respectively. Simulations recapitulate myogenic constrictions and examine differences in contractile dynamics as we move from arterioles to proximal and distal capillaries. In arteriole-to-capillary transitional (ACT) zone PCs, increased mechanosensitivity, more Ca2+ influx through non-selective cation (NSC) channels and/or a higher sensitivity of the contractile apparatus to Ca2+ can compensate for reduced L-type voltage-operated (VOCC) Ca2+ influx and allow for robust constrictions at the lower operating pressures of capillaries relative to the arterioles. A significant Ca2+ influx through NSC relative to VOCC, however, can decouple the PCs contractile apparatus from electrical signaling. Vasoactivity to chemomechanical stimuli along the arteriole to capillary axis is progressively driven by VOCC-independent Ca2+ influx and Ca2+ sensitization with slow kinetics. The proposed cell model can form the basis for detailed multiscale and multicellular models that will examine physiological function at a single vessel or vascular network levels and investigate CBF control in health and in disease. Key pointsO_LIA mural cell model of electrophysiology, calcium (Ca2+) dynamics and biomechanics is informed by data and adapted for modeling cerebral arteriole smooth muscle cells and capillary pericytes. C_LIO_LIIon channel activities are characterized by patch-clamp electrophysiology in isolated cerebral smooth muscle cell and pericytes, and capillary and arteriole electromechanical responses to transmural pressure changes are assessed using novel ex vivo preparations. C_LIO_LIMyogenic constrictions in arterioles can be reproduced by pressure-induced non-selective cation channel (NSC) activation that depolarizes the cell, opens L-type Ca2+ channels (VOCCs) and increases Ca2+ influx. C_LIO_LIRobust myogenic constrictions in arteriole-to-capillary transition (ACT) zone pericytes may reflect significant Ca2+ influx through NSC, increased mechanosensitivity, or higher sensitivity of the contractile apparatus to Ca2+, potentially compensating for reduced VOCC density relative to arteriolar smooth muscle. C_LIO_LIA significant contribution of NSC relative to VOCC in Ca2+ influx, can decouple the contractile apparatus from electrical signaling. C_LIO_LIThe model shows how gradients in ionic activities, mechanosensitivity and/or Ca2+ sensitivity can alter contractile phenotype and electromechanical coupling along the arteriole to capillary continuum. C_LIO_LIThe proposed model can form the basis for detailed multiscale and multicellular models that will investigate cerebral blood flow control in health and in disease. C_LI

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia worldwide and is strongly associated with increased risks of stroke, heart failure, and mortality. Traditional methods to predict AF and prognostic its associated risks often fail to capture the full complexity of AF patterns, limiting their predictive accuracy. In spite of the improvements achieved by machine learning (ML) techniques, state-of-the-art AF-focused predictors do not generally incorporate longitudinal data, reducing their capacity to model the dynamic and evolving nature of individual behaviors and physiological indicators over time. The absence of a longitudinal perspective restricts understanding of how AF risk develops and changes across prognostic windows. This study addresses these limitations by developing superior ML models tailored to predict adverse events within a longitudinal Portuguese cohort of individuals with AF. The work targets six clinical endpoints: stroke, all-cause death, cardiovascular death, heart failure hospitalizations, inpatient visits, and acute coronary syndrome. The predictors yielded an AUC of 0.65 for 1-year stroke prediction, outperforming CHA2DS_2-VASc (0.59). For all-cause mortality prediction, the models achieved an AUC of 0.78 against the 0.72 reference of GARFIELD-AF. In addition to predictive advances, the study identifies determinants of AF-related risks and introduces a prototype decision-support tool for clinical use.

With metabolic disease on the rise across the globe, the devices that can provide precise and reliable estimates of energy expenditure and macronutrient oxidation can play a critical role in the development and evaluation of therapeutic regimes and wearable technologies that can be used outside of the laboratory. Whereas, metabolic carts can provide short-term (minutes to hours) metabolic measurements, whole-room calorimeters enable long-duration (hours to days) metabolic assessment, providing insights into how metabolism changes in response to meals, activity, sleep, etc. Obtaining accurate metabolic measurement via whole-room calorimetry, however, requires rigorous methods for calibration and quality assurance. To date most room calorimeters have been tuned to assess energy expenditure over long periods of time, i.e. 24-hours. Here we present novel calibration and signal processing techniques and recommendations that aim to improve the utility of metabolic chambers for use over different measurement epochs. This work serves as both a transparent description of our hardware, validation procedures, and data processing approaches.

General anesthetics enable invasive experimentation but can affect cardiovascular and respiratory physiology, biasing preclinical outcomes. We compared five anesthetic regimens in adult male Wistar rats, tribromoethanol (TBE, 250 mg/kg i.p.), chloral hydrate (CH, 400 mg/kg i.p.), ketamine-xylazine (KX, 80/10 mg/kg i.p.), thiopental (TP, 80 mg/kg i.p.), and isoflurane (ISO, 4% induction, 2% maintenance), to investigate integrated cardiorespiratory and biochemical markers. Femoral arterial catheterization allowed continuous blood pressure (BP) and derived heart rate (HR) recordings, while ventilation was assessed through pletysmography at baseline (awake), during induction, and recovery phases of anesthesia. Variability was evaluated in the time and frequency domains, including HR, systolic blood pressure (SBP), and spontaneous baroreflex sensitivity. In an independent cohort of rats, butyrylcholinesterase (BChE), CK-MB, cTnI, and LDH were measured. Baseline BP was unchanged by TBE and TP, whereas all anesthetics affected HR. Minute ventilation and breathing frequency were reduced with all agents, while tidal volume decreased with KX and TBE only. LDH and cTnI were unaffected, BChE was reduced by KX, TBE, and ISO, and CK-MB increased with CH and KX. Variability analysis showed that all anesthetics depressed pulse-interval and SBP variability and shifted spectral power toward higher frequencies, while baroreflex sensitivity and effectiveness were consistently reduced. During recovery, KX and TP restored most variability indices, whereas CH, TBE, and ISO showed persistent suppression. These findings highlight distinct profiles of cardiovascular depression and biomarker responses across anesthetics and underscore the importance of accounting for autonomic variability when selecting different anesthetics in experimental protocols. HighlightsO_LIFive anesthetic regimens were tested in rats. C_LIO_LIAll anesthetics reduced ventilation, and KX and TBE also reduced tidal volume. C_LIO_LICH and KX increased CKMB, while KX, TBE and ISO reduced BChE. C_LIO_LIAll anesthetics reduced blood pressure variability and baroreflex sensitivity. C_LIO_LIVariability recovered with TP and KX, whereas CH, TBE and ISO showed persistent suppression. C_LI

Structured AbstractO_ST_ABSBackgroundC_ST_ABSAtrial fibrillation (AF) is maintained by complex dynamics, clinically characterised by bursting periods of organization and disorganization in intracardiac electrograms. We have previously postulated that cardiac conduction behaves like a critical system, where phase shift from organised rhythm to AF is a phase transition at the critical point. We thus hypothesized that using multifractal analysis of AF electrograms could potentially quantify non-stationary fluctuations, revealing novel mechanistic insights into the cardiac critical system and examine potential clinically relevant markers of AF dynamics, phenotype and treatment response. ObjectivesTo determine whether multifractal analysis of AF electrograms can (i) Distinguish paroxysmal (PAF0 and non-paroxysmal AF (NPAF), (ii) predict response to pharmacologic modulation, and (iii) identify imminent spontaneous termination, thereby acting as marker of proximity to criticality along complex system phase spectrum. MethodsWe analysed >1.4 million seconds of high-density bipolar electrograms from 106 patients (paroxysmal n{approx}52, non-paroxysmal n{approx}54) undergoing left atrial mapping with a 24-bipole HD-Grid catheter at standardized sites (RENEWAL AF-ANZCTR ACTRN12619001172190)). Multifractal analysis using the Wavelet Transform Modulus Maxima Method (WTMM) was applied to a burst-energy observable to derive log-normal multifractal parameters c (support dimension), c (spectrum location), and c2 (fluctuations). Hierarchical mixed-effects models accounted for channels nested within locations within patients. A flecainide sub-study (n=15) provided paired pre-/post-infusion recordings, and 27 spontaneous termination events in 15 patients were analysed using 60-s pre-termination windows. Spatial texture of c2 was quantified by variogram-derived correlation length and sill. ResultsAF electrograms exhibited robust multifractality confirming multifractal fluctuations as an intrinsic property of AF. Non-paroxysmal AF showed significantly reduced fluctuations versus paroxysmal AF (c2: {beta}=-0.01, p=0.001), indicating a paradoxical loss of fluctuations with disease progression. Flecainide selectively increased fluctuations in paroxysmal AF ({Delta}c2 = +0.04, p<0.01; {Delta}c = +0.06, p<0.01) but had no significant effect on fluctuations (c2) in non-paroxysmal AF, revealing phenotype-dependent drug response. Immediately prior to spontaneous AF termination, fluctuations increased significantly compared with sustained AF (c2: 0.198 vs 0.181, p=0.024). Spatial variogram analysis revealed heterogenous patterns in paroxysmal AF, whereas non-paroxysmal AF displayed a homogenised, flattened fluctuations landscape. ConclusionsAtrial fibrillation exhibits robust multifractal dynamics rather than random electrical activity. Reduced fluctuations characterizes non-paroxysmal AF, whereas higher fluctuations is observed in paroxysmal AF, during flecainide modulation, and immediately prior to spontaneous termination. These findings suggest that multifractal fluctuations (c2) reflects the dynamical state of AF and may serve as a quantitative biomarker of disease progression, pharmacologic responsiveness, and proximity to termination. CONDENSED ABSTRACTTAtrial fibrillation (AF) exhibits multifractal electrogram fluctuations that vary with disease stage, pharmacologic responsiveness, and proximity to spontaneous termination. In this study, multifractal fluctuations (c2) was higher in paroxysmal than non-paroxysmal AF, increased selectively with flecainide in paroxysmal AF, and rose immediately before spontaneous termination. These findings identify c2 as a quantitative marker of AF progression, and imminent reorganization. Clinically, multifractal analysis may enhance intra-procedural assessment of AF phenotype, guide drug selection, and improve recognition of transitions toward sinus rhythm, and connects AF with concepts of criticality and phase transitions.

Background: Sleep problems are common in older people and have been associated with increased fall risk, but the mechanisms underlying this relationship remain unclear. Gait quality reflects balance control and neurological function and may provide insight into pathways linking sleep health and falls. Methods: Data from 758 community-dwelling older people ([&ge;]65 years; mean age 75.8 years, 69.3% women) were analysed. Sleep problems were assessed at baseline using a self-reported item (Patient Health Questionnaire-9, question 3). Daily-life gait quality and habitual walking speed were derived from one week of wearable sensor monitoring. Falls and injurious falls were prospectively recorded over 12 months. Associations between sleep problems, gait quality, and fall incidence were examined using regression models adjusted for demographic, pain and cognitive factors, and use of sleeping medication. Results: Sleep problems were reported by 43.9% of participants. Sleep problems were not associated with habitual walking speed, but were associated with lower gait quality in daily life (adjusted {beta} = -0.15, 95% CI -0.27 to -0.03). Participants reporting sleep problems had higher incidence rates of total falls (adjusted IRR = 1.42, 95% CI 1.07 to 1.90) and injurious falls (adjusted IRR = 1.50, 95% CI 1.07 to 2.10). Conclusions: Self-reported sleep problems were associated with impaired real-world gait quality and substantially higher rates of falls and injurious falls in older people. These findings suggest that sleep problems may increase fall risk by altering balance control rather than by reducing walking speed. Sleep should be considered when managing fall risk, and fall risk should be considered in older people with sleep complaints.

Background: Patient-ventilator synchrony, an essential prerequisite for non-invasive mechanical ventilation, requires an accurate matching of every phase of the respiration between patient and the ventilator. Methods: We developed a long short-term memory (LSTM)-based model that can predict the inspiratory and expiratory time of the patient. This model consisted of two hidden layers, each with eight LSTM units, and was trained using a dataset of approximately 27000 of 500-ms-long flow signals that captured both inspiratory and expiratory events. Results: The LSTM model achieved 97% accuracy and F1 score in the test data, and the average trigger error was less than 2.20%. In the first trial, 10 volunteers were enrolled. In "Compliance" mode, 78.6% of the triggering by the LSTM model was compatible with neuronal respiration, which was higher than Auto-Trak model (74.2%). Auto-Trak model performed marginally better in the modes of pressure support = 5 and 10 cmH2O. Considering the success in the first clinical trial, we further tested the models by including five patients with acute respiratory distress syndrome (ARDS). The LSTM model exhibited 60.6% of the triggering in the 33%-box, which is better than 49.0% of Auto-Trak model. And the PVI index of the LSTM model was significantly less than Auto-Trak model (36.5% vs 52.9%). Conclusions: Overall, the LSTM model performed comparable to, or even better than, Auto-Trak model in both latency and PVI index. While other mathematical models have been developed, our model was effectively embedded in the chip to control the triggering of ventilator. Trial registration: Approval Number: 2023ZDSYLL348-P01; Approval Date: 28/09/2023. Clinical Trial Registration Number: ChiCTR2500097446; Registration Date: 19/02/2025.

BackgroundMaternal protein restriction results in a 28% reduction in nephrogenic cells and nephron units in rodent offspring by the 17th day of gestation compared to adequate protein intake. AimsThe present study investigates the association between growth factor expression and some developmental pathways that contribute to nephron reduction during embryonic and fetal development. Experimental DesignPregnant C57BL/6-Tg and C57BL/6J mice were assigned to either normal protein intake (NP-17%) or low protein intake (LP-6%) groups. Body weight of male offspring and kidney growth factor expression were assessed on gestation days (GD) 14 and 18. ResultsOn GD 14, LP pups exhibited a 4% higher body mass (0.1035 g) compared to NP pups (0.0995 g, p = 0.005). By GD 18, LP pups demonstrated a 4% decrease in body mass (0.939 g, p = 0.03) and a 10% increase in the number of cells per metanephric cap area. Three genes (Csf2, Il1b, Il2) were downregulated, while seven genes (Bmp2, Csf3, Fgf8, Gdnf, Bmp7, Fgf3, Ntf3) were upregulated. By GD 14, phagophores and autophagosomes in the ureteric bud increased by 197%, with further increases observed by GD 18. Bcl-2 expression increased significantly in ureteric bud cells, and mTOR activity was elevated by GD 18. ConclusionEarly gestational protein restriction modifies renal growth factor gene expression, influencing cell proliferation and autophagy, and may contribute to reduced nephron numbers by the 18th day of gestation. HIGHLIGHTSO_LIThis study examines the effects of a low-protein diet during pregnancy in mice and demonstrates a significant reduction in embryo-fetal body weight between gestational days 14 and 18. C_LIO_LIProtein restriction induces a distinct cellular pattern in the mesonephros, with a 21% increase in CAP cells at gestational day 14 (GD14), followed by a decrease by gestational day 18 (GD18) compared to offspring from mothers on a normal protein diet. C_LIO_LIAdditionally, increased expression levels of key growth factors essential for kidney development were observed at GD 14, comparing LP with NP intake during pregnancy. C_LIO_LISeven genes were upregulated (Gdnf, Bmp2, Bmp7, Tgf, Fgf8, Fgf3, Csf3, Ntf3), while three genes were downregulated (Csf2, Il1b, Il2). C_LIO_LIOverall, these findings indicate that gene regulation, autophagy, and mTOR signaling mechanisms significantly influence nephron numbers in response to gestational protein restriction beyond the 18th day of gestation. C_LI

Patient-specific four-chamber electromechanical models provide a physics-constrained framework for investigating whole-heart cardiac physiology and disease mechanisms. Identifying which model parameters impact whole-heart function is important for understanding cellular-, tissue-, and organ-scale determinants of cardiac performance and for calibrating patient-specific models. However, previous global sensitivity analyses of cardiac electromechanical models have typically been performed on a single heart, and systematic evaluation of how parameter influence compares across anatomically different subjects remains limited. We created four-chamber electromechanical models using cardiac MRI from five healthy subjects (n = 5). The models simulated atrial and ventricular cellular electrophysiology, calcium dynamics, and active contraction, with heterogeneous fibre orientation, transversely isotropic tissue mechanics, pericardial constraint, and a closed-loop cardiovascular system providing physiological boundary conditions. In total, 46 parameters described the integrated model. Using Gaussian process emulators, we performed multi-scale global sensitivity analysis to evaluate the relative contribution of model parameters to left and right atrial and ventricular function. Across all anatomies, the most influential parameters were systemic and pulmonary resistances, ventricular end-diastolic pressures, and the venous reference pressure, highlighting the dominant role of haemodynamic loading conditions in governing pressure- and volume-based outputs. A chamber-level analysis of atrioventricular coupling revealed a phase-dependent pattern. Atrial pressures were predominantly governed by global haemodynamic parameters (> 90% of total sensitivity), atrial filling volumes showed substantial ventricular influence ({approx}40-55% across anatomies), and atrial end-systolic volumes were primarily determined by intrinsic atrial parameters ({approx}60-65%). These patterns were consistent across subjects despite differences in anatomy. We show that, in healthy male subjects, inter-individual anatomical variation does not substantially change the ranking of dominant parameters. This work provides a repeatable modelling and sensitivity analysis framework and establishes a benchmark reference for whole-heart electromechanical modelling in healthy hearts. Author summaryComputational models of the heart can simulate cardiac physiology in unprecedented detail, but these models contain many parameters whose influence on predicted function is not fully understood. We built patient-specific four-chamber heart models from MRI scans of five healthy subjects and used statistical methods to systematically test how 46 model parameters affect simulated cardiac performance. Across all five subjects, we found that the haemodynamic loading parameters, including systemic and pulmonary vascular resistance, ventricular filling pressures, and the venous reference pressure, consistently had the greatest influence on the model outputs, regardless of differences in individual heart anatomy. This finding suggests that in healthy resting conditions, the boundary conditions of the cardiovascular system, rather than individual differences in heart geometry or electrical properties, are the primary drivers of whole-heart function. We also found a structured coupling pattern between the upper and lower heart chambers, where global haemodynamic parameters dominate atrial pressure regulation, ventricular mechanics shape atrial filling, and intrinsic atrial properties control atrial emptying. This work provides a benchmark dataset of five anatomically detailed heart models and a sensitivity analysis framework to guide calibration of future cardiac digital twin models.

AimsGenome-wide association studies have identified numerous cardiac transcription factors in association with atrial fibrillation. Amongst these transcription factors, the paired-like homeodomain transcription factor 2 (PITX2) is the strongest genetic risk variant associated with atrial fibrillation. However, the downstream mechanisms of PITX2 are not completely understood. Here, we explore the role of PITX2 in oxidative metabolism and stress as a unifying mechanism of arrhythmogenesis. Methods and resultsTo identify PITX2 mechanisms, we performed transcriptomic analysis in Pitx2c-deficient neonatal rat atrial myocytes. We identify oxidative phosphorylation as the top dysregulated pathway and direct transcriptional targets lie in mitochondrial electron transport chain complexes I and IV. Using the Seahorse Extracellular Flux Analyzer, we identified a functional decrease in oxidative metabolism in Pitx2c-deficient cardiomyocytes. As electron transport chain complexes I and IV may generate reactive oxygen species (ROS) under mitochondrial dysfunction, we quantified mitochondrial specific ROS using MitoSOX and observed an increase in mitochondrial specific ROS in Pitx2c-deficient cardiomyocytes. We additionally assessed spontaneous cardiomyocyte calcium cycling using Fluo-8AM and observed an increased frequency of pro-arrhythmogenic mechanisms including early and delayed afterdepolarizations as inferred through calcium traces. Further, we identified sarcomere disassembly including a potential role of PITX2 in regulating Titin, where Pitx2c-deficient cardiomyocytes display Titin mis-localization within the sarcomeres. To assess whether ROS drives these phenotypes, we treated neonatal rat atrial myocytes with N-acetylcysteine, a potent ROS scavenger, and observed decreased early and delayed afterdepolarizations, as well as restoration of Titin localization. ConclusionPITX2C maintains atrial metabolism and redox balance; the loss of PITX2C results in reduced oxidative metabolism and an elevation in oxidative stress that ramifies cardiomyocyte dysfunction. Treatment with antioxidant restores AF-associated phenotypes including abnormal calcium cycling and sarcomere disassembly in Pitx2c-deficient atrial cardiomyocytes. TRANSLATIONAL PERSPECTIVEGenetic variants close to the PITX2 gene associate most strongly with atrial fibrillation. This study reveals a mechanistic link between multiple AF-associated phenotypes and mitochondrial dysfunction with subsequent accumulation of reactive oxygen species downstream of PITX2. Importantly, metabolic therapies and reducing oxidative stress may present a potential clinical strategy to reverse and prevent functional and structural remodelling related to AF.

BackgroundIn patients requiring respiratory support, clinicians rely on physical exam, radiologic, laboratory, and ventilator-derived measures for the provision of sufficient support while minimizing ventilator and "work of breathing" induced lung injury. Point of care lung ultrasound (LUS) is a widely available tool in hospital and clinic environments. To date, LUS has not been used to evaluate lung strain. MethodsWe collected LUS images in four anesthetized, neuromuscularly blocked, and mechanically ventilated pigs being used for another experiment. A feature tracking tool was developed which tracked echo-bright lung structures in ten second clips obtained in triplicate of the right and left, upper and lower lung fields using tidal volumes of 4, 6, 8, 10, and 12 mL/kg. Pleural lines were manually drawn and a program for quantifying lung strain developed with assistance from Anthropic Claude Artificial Intelligence tool. Structures were identified in inspiratory and expiratory frames and tracked bidirectionally with median strain per frame used for calculations. ResultsTriplicate measures of lung ultrasound images in four pigs had a median coefficients of variation of 35% (23-47% IQR) and linear modeling of strain with tidal volumes of 4-12 mL/kg showed positive correlation with R2 value ranging from 0.89 to 0.97. Strain measurements were similar after bronchial administration of 1.5M hydrochloric acid. ConclusionsRegional lung strain quantification using LUS is a viable and potentially useful tool for respiratory support management.

Objectives: Cardiovascular disease (CVD) is a leading cause of mortality and disability in older populations. This study aimed to identify CVD risk factors in community-dwelling older adults and to examine whether frailty-related factors (sarcopenia and nutritional status) interact with chronic kidney disease (CKD). Methods: This cross-sectional study included 307 community-dwelling Japanese adults aged [&ge;]65 years between September 2024 and March 2025. CVD history was assessed based on self-reported physician diagnoses obtained through a structured questionnaire. Lifestyle-related factors included hypertension, diabetes, dyslipidemia, and body mass index (BMI). Frailty-related factors included sarcopenia (Asian Working Group for Sarcopenia 2019 criteria), nutritional status (Mini Nutritional Assessment-Short Form), and physical activity (International Physical Activity Questionnaire-Short Form). CKD was defined using the estimated glomerular filtration rate (eGFR): non-CKD ([&ge;]60 mL/min/1.73 m2) and CKD (<60 mL/min/1.73 m2). Multivariable logistic regression identified independent correlates of CVD, and interactions between CKD and frailty-related factors were tested. Results: The prevalence of CVD was 17.9%. Independent correlates included CKD (aOR 5.0), hypertension (aOR 4.0), male sex (aOR 3.1), undernutrition (aOR 2.7), sarcopenia (aOR 2.7), and low physical activity (aOR 2.5). No significant interactions were observed between CKD and sarcopenia (p = 0.70) or nutritional status (p = 0.40). Conclusions: CKD, sarcopenia, undernutrition, and low physical activity were independently associated with CVD, with no interaction between CKD and frailty factors. These findings suggest that integrated management addressing both renal function and frailty-related factors may be important for CVD prevention in older adults.

Background: Deep brain stimulation (DBS) is a treatment option for Parkinson disease (PD). However, the effect of DBS on the arterial pressure (AP) remains unexplored. We aimed to develop an artificial baroreflex system for treating orthostatic hypotension (OH) due to central baroreflex failure in patients with PD. To achieve this, we developed an appropriate algorithm after estimating the dynamic responses of the AP to DBS using a white noise system identification method. Methods: We randomly performed DBS while measuring the AP tonometrically in 3 trials involving 3 patients with PD treated with DBS. We calculated the frequency response of the AP to the DBS using a fast Fourier transform algorithm. Finally, the feedback correction factors were determined via numerical simulation. Results: The frequency responses of the systolic AP to random DBS were identifiable in all 3 trials, and the steady state gain was 8.24 mmHg/STM. Based on these results, the proportional correction factor was set to 0.12, and the integral correction factor was set to 0.018. The computer simulation revealed that the system could quickly and effectively attenuate a sudden AP drop induced by external disturbances such as head-up tilting. Conclusion: An artificial baroreflex system with DBS may be a novel therapeutic approach for OH caused by central baroreflex failure.

Objective: Skin sympathetic nerve activity (SKNA) has emerged as a promising non-invasive surrogate measure of sympathetic drive, but its relevant physiological characteristics remain ill-defined. This observational study aims to investigate its regulatory patterns during rest and Valsalva maneuver (VM) in healthy participants. Method: Using a two-layer strategy integrating signal analysis and physiological modelling, we analyzed data recorded from 41 subjects performing repeated VMs. The observational layer includes time-domain feature comparisons using linear mixed-effect models, and time-varying spectral coherence analysis. The mechanistic layer proposes a mathematical model to investigate whether baroreflex and respiratory modulation are sufficient to reproduce the observed HR and average SKNA (aSKNA) dynamics. Main Results: Mean integrated SKNA (iSKNA) showed more significant change than HRV for VM induced effects. We also found mean iSKNA increase during VM varies with BMI and sex. The coherence analysis indicated that iSKNA strongly synchronized with EDR under resting conditions. The proposed model successfully reproduced main characteristics of aSKNA dynamics, yielding a high median Pearson correlation coefficient of 0.80 ([Q1, Q3] = [0.60, 0.91]). In contrast, HR dynamics were only partially captured, with a median PCC of 0.37 ([Q1, Q3] = [0.16, 0.55]). These results likely suggest SKNA provides a more direct representation of sympathetic burst dynamics during VM in healthy subjects. Significance: This study provides convergent evidence that SKNA reflects known autonomic regulatory influences in healthy subjects. These findings strengthen the physiological interpretability of SKNA while clarifying its appropriate use as a practical biomarker of sympathetic function.

PurposeObstructive sleep apnea (OSA) is a common comorbidity in heart failure (HF) patients with prevalence increasing as HF severity worsens. While CPAP/BiPAP has been shown to reduce disease burden and mortality in the general HF population, it is unclear whether these benefits extend to patients with left ventricular assist devices (LVADs). We sought to determine whether OSA affects long-term survival in newly implanted LVAD patients and whether CPAP/BiPAP treatment confers mortality benefits. MethodsThis single-center retrospective study included patients who underwent LVAD implantation between January 2007 and February 2022. Recipients were stratified by OSA status (OSA vs No-OSA), and those with OSA were further categorized based on CPAP/BiPAP compliance. Comparative statistics and Kaplan-Meier survival analyses were performed, with log-rank tests used to compare groups and assess survival differences. A Cox proportional hazards model was conducted to evaluate the association between risk factors and survival among patients with OSA and No-OSA. ResultsBefore LVAD implantation, patients with OSA had higher body mass index, hypertension, and a higher rate of implantable cardioverter-defibrillator placement than those without OSA. OSA was not associated with increased postoperative complications. Although survival did not differ significantly between OSA and No-OSA patients (p=0.33), CPAP/BiPAP-compliant OSA patients had significantly better survival than noncompliant patients (p=0.0099). ConclusionsLVAD patients with OSA who consistently use CPAP/BiPAP have better survival than those who do not. CPAP/BiPAP is a simple, low-risk treatment that can reduce mortality in this population. Therefore, increased perioperative screening for OSA should be considered for patients receiving LVADs. Multicenter studies are needed to confirm our findings further.

Aims: Responses to remote pulmonary artery pressure data vary across programs. We evaluated SMART-HF, a structured pulmonary artery diastolic pressure (PAD)-guided workflow, in a community heart failure cohort. Methods: We retrospectively analysed adults with heart failure and an implanted pulmonary artery pressure sensor managed with SMART-HF. Pulmonary artery diastolic pressure (PAD) was calculated from prespecified 14-day windows at baseline, 90 days, and 6 months. Two hemodynamic management performance indices (HMPI) were prespecified: the 6-Month Delta HMPI (PAD reduction >2 mmHg from baseline) and the 90-Day Target HMPI (PAD [&le;]20 mmHg at 90 days). Exploratory analyses evaluated patients with baseline PAD >20 mmHg. Results: Of 37 patients, 36 had paired 90-day and 29 had paired 6-month windows. Mean PAD decreased from 18.3 +/- 7.0 to 16.1 +/- 6.3 mmHg at 90 days and from 18.8 +/- 6.8 to 15.5 +/- 5.8 mmHg at 6 months (both P < 0.001). The 90-Day Target HMPI was achieved in 26/36 (72.2%) and the 6-Month Delta HMPI in 19/29 (65.5%) [95% CI 45.7-82.1]. In the exploratory subgroup (baseline PAD >20 mmHg), mean PAD changes were -2.9 +/- 3.6 mmHg at 90 days (n = 19; P = 0.002) and -4.9 +/- 4.9 mmHg at 6 months (n = 15; P = 0.002). Conclusions: SMART-HF was associated with improved ambulatory pulmonary artery diastolic pressure control at 90 days and 6 months. Exploratory subgroup findings support further evaluation in patients with elevated baseline pulmonary artery diastolic pressure.

BackgroundChronic exposure to high-altitude hypoxia imposes sustained cardiovascular stress, yet hemodynamic adaptation among healthy high-altitude dwellers is heterogeneous and remains poorly characterized. This study aimed to identify distinct hemodynamic phenotypes in a healthy high-altitude population using unsupervised machine learning and to evaluate their association with multi-system subclinical target organ damage. MethodsThis cross-sectional study enrolled 694 healthy adults permanently residing at [&ge;]3300 m on the Qinghai-Tibet Plateau. Unsupervised K-means clustering was performed on nine hemodynamic variables, including peripheral and central blood pressures, augmentation index (AIx), pulse pressure amplification ratio (pPP/cPP), and systolic pressure amplification (pSBP-cSBP). Differences across phenotypes in carotid intima-media thickness (IMT), estimated glomerular filtration rate (eGFR), left ventricular mass index (LVMI), and pulse wave velocity (PWV) were assessed using one-way ANOVA with Bonferroni-corrected post-hoc tests. ResultsThree distinct hemodynamic phenotypes were successfully identified. The C2 (Balanced Adaptation) phenotype (n = 245) demonstrated the most favorable hemodynamic profile, characterized by the lowest blood pressure and augmentation index (AIx) values, along with the highest peripheral-to-central pulse pressure ratio (pPP/cPP). The C1 (Vascular Stress) phenotype (n = 267) presented with normal peripheral systolic blood pressure (125.9 {+/-} 11.3 mmHg) but exhibited markedly elevated wave reflection indices, including the highest heart rate-adjusted augmentation index (AIx@HR75: 31.9 {+/-} 9.7%) and the lowest pPP/cPP ratio (1.29 {+/-} 0.08). The C3 (High-Load Decompensation) phenotype (n = 182) displayed significantly elevated blood pressures and the greatest overall hemodynamic load. Regarding target organ damage, a clear gradient was observed across the three phenotypes. The C3 phenotype showed the highest carotid intima-media thickness (IMT: 1.162 {+/-} 0.23 mm) and left ventricular mass index (LVMI: 69.18 {+/-} 40.73 g/m{superscript 2}). Conversely, the C2 phenotype exhibited the highest estimated glomerular filtration rate (eGFR: 97.38 {+/-} 16.38 mL/min/1.73m{superscript 2}) and the lowest IMT (0.994 {+/-} 0.26 mm). The C1 phenotype consistently displayed intermediate values for all organ damage indicators. After Bonferroni correction, all pairwise comparisons for LVMI and pulse wave velocity (PWV) reached statistical significance (all P < 0.05). ConclusionsHealthy high-altitude individuals manifest three distinct hemodynamic phenotypes arrayed along a cardiovascular risk continuum. The novel Vascular Stress (C1) phenotype represents a "masked" high-risk state characterized by normal peripheral blood pressure but elevated arterial stiffness and wave reflection, challenging sole reliance on brachial pressure for risk assessment. This phenotype-based stratification provides a framework for precision prevention and early intervention in high-altitude populations.

Continuous, non-invasive cardiovascular monitoring is limited by the superficial sensing depth of Photoplethysmography (PPG), which is susceptible to peripheral artifacts. This study evaluates a wearable dual-modality prototype integrating dryelectrode Impedance Plethysmography (IPG) and PPG within a smartwatch form factor. Results from a pilot study (N=2) demonstrate that IPG signals exhibit a temporal lead over PPG across ventral and dorsal sites, supporting its greater penetration depth. During brachial artery modulation, IPG showed superior sensitivity to arterial recovery on the ventral forearm. Furthermore, 60-minute napping sessions revealed that while PPG remained morphologically stable, IPG signals underwent significant evolution, capturing distinct pulsewave archetypes. These findings suggest that wearable IPG provides a high-fidelity window into deep systemic hemodynamics typically reserved for clinical instrumentation.