Hasil untuk "Physiology"

Jitesh Joshi, Youngjun Cho

Remote physiological sensing using camera-based technologies offers transformative potential for non-invasive vital sign monitoring across healthcare and human-computer interaction domains. Although deep learning approaches have advanced the extraction of physiological signals from video data, existing methods have not been sufficiently assessed for their robustness to domain shifts. These shifts in remote physiological sensing include variations in ambient conditions, camera specifications, head movements, facial poses, and physiological states which often impact real-world performance significantly. Cross-dataset evaluation provides an objective measure to assess generalization capabilities across these domain shifts. We introduce Target Signal Constrained Factorization module (TSFM), a novel multidimensional attention mechanism that explicitly incorporates physiological signal characteristics as factorization constraints, allowing more precise feature extraction. Building on this innovation, we present MMRPhys, an efficient dual-branch 3D-CNN architecture designed for simultaneous multitask estimation of photoplethysmography (rPPG) and respiratory (rRSP) signals from multimodal RGB and thermal video inputs. Through comprehensive cross-dataset evaluation on five benchmark datasets, we demonstrate that MMRPhys with TSFM significantly outperforms state-of-the-art methods in generalization across domain shifts for rPPG and rRSP estimation, while maintaining a minimal inference latency suitable for real-time applications. Our approach establishes new benchmarks for robust multitask and multimodal physiological sensing and offers a computationally efficient framework for practical deployment in unconstrained environments. The web browser-based application featuring on-device real-time inference of MMRPhys model is available at https://physiologicailab.github.io/mmrphys-live

Birgit Nierula, Mustafa Tevfik Lafci, Anna Melnik et al.

Proxemics, the study of spatial behavior, is fundamental to social interaction and increasingly relevant for virtual reality (VR) applications. While previous research has established that users respond to personal space violations in VR similarly as in real-world settings, phase-specific physiological responses and the modulating effects of facial expressions remain understudied. We investigated physiological and subjective responses to personal space violations by virtual avatars, to understand how threatening facial expressions and interaction phases (approach vs. standing) influence these responses. Sixteen participants experienced a 2x2 factorial design manipulating Personal Space (intrusion vs. respect) and Facial Expression (neutral vs. angry) while we recorded skin conductance response (SCR), heart rate variability (HRV), and discomfort ratings. Personal space boundaries were individually calibrated using a stop-distance procedure. Results show that SCR responses are significantly higher during the standing phase compared to the approach phase when personal space was violated, indicating that prolonged proximity within personal space boundaries is more physiologically arousing than the approach itself. Angry facial expressions significantly reduced HRV, reflecting decreased parasympathetic activity, and increased discomfort ratings, but did not amplify SCR responses. These findings demonstrate that different physiological modalities capture distinct aspects of proxemic responses: SCR primarily reflects spatial boundary violations, while HRV responds to facial threat cues. Our results provide insights for developing comprehensive multi-modal assessments of social behavior in virtual environments and inform the design of more realistic avatar interactions.

Pragya Singh, Ritvik Budhiraja, Pankaj Jalote et al.

Physiological signals hold immense potential for ubiquitous emotion monitoring, presenting numerous applications in emotion recognition. However, harnessing this potential is hindered by significant challenges, particularly in the collection of annotations that align with physiological changes since the process hinges heavily on human participants. In this work, we set out to study human participant perspectives in the emotion data collection procedure. We conducted a lab-based emotion data collection study with 37 participants using 360 degree virtual reality video stimulus followed by semi-structured interviews with the study participants. Our findings presented that intrinsic factors like participant perception, experiment design nuances, and experiment setup suitability impact their emotional response and annotation within lab settings. Drawing from our findings and prior research, we propose recommendations for incorporating participant context into annotations and emphasizing participant-centric experiment designs. Furthermore, we explore current emotion data collection practices followed by AI practitioners and offer insights for future contributions leveraging physiological emotion data.

Lingwei Zhu, Zheng Chen, Yukie Nagai et al.

This paper adds to the growing literature of reinforcement learning (RL) for healthcare by proposing a novel paradigm: augmenting any predictor with Rule-based RL Layer (RRLL) that corrects the model's physiologically impossible predictions. Specifically, RRLL takes as input states predicted labels and outputs corrected labels as actions. The reward of the state-action pair is evaluated by a set of general rules. RRLL is efficient, general and lightweight: it does not require heavy expert knowledge like prior work but only a set of impossible transitions. This set is much smaller than all possible transitions; yet it can effectively reduce physiologically impossible mistakes made by the state-of-the-art predictor models. We verify the utility of RRLL on a variety of important healthcare classification problems and observe significant improvements using the same setup, with only the domain-specific set of impossibility changed. In-depth analysis shows that RRLL indeed improves accuracy by effectively reducing the presence of physiologically impossible predictions.

Yenho Chen, Maxwell A. Xu, James M. Rehg et al.

The effectiveness of self-supervised learning (SSL) for physiological time series depends on the ability of a pretraining objective to preserve information about the underlying physiological state while filtering out unrelated noise. However, existing strategies are limited due to reliance on heuristic principles or poorly constrained generative tasks. To address this limitation, we propose a pretraining framework that exploits the information structure of a dynamical systems generative model across multiple time-series. This framework reveals our key insight that class identity can be efficiently captured by extracting information about the generative variables related to the system parameters shared across similar time series samples, while noise unique to individual samples should be discarded. Building on this insight, we propose PULSE, a cross-reconstruction-based pretraining objective for physiological time series datasets that explicitly extracts system information while discarding non-transferrable sample-specific ones. We establish theory that provides sufficient conditions for the system information to be recovered, and empirically validate it using a synthetic dynamical systems experiment. Furthermore, we apply our method to diverse real-world datasets, demonstrating that PULSE learns representations that can broadly distinguish semantic classes, increase label efficiency, and improve transfer learning.

Daniel Zielasko, Ben Rehling, Bernadette von Dawans et al.

Extended exposure to virtual reality environments can induce motion sickness, often referred to as cybersickness, which may lead to physiological stress responses and impaired cognitive performance. This study investigates the aftereffects of VR-induced motion sickness with a focus on physiological stress markers and working memory performance. Using a carousel simulation to elicit cybersickness, we assessed subjective discomfort (SSQ, FMS), physiological stress (salivary cortisol, alpha-amylase, electrodermal activity, heart rate), and cognitive performance (n-Back task) over a 90-minute post-exposure period. Our findings demonstrate a significant increase in both subjective and physiological stress indicators following VR exposure, accompanied by a decline in working memory performance. Notably, delayed symptom progression was observed in a substantial proportion of participants, with some reporting peak symptoms up to 90 minutes post-stimulation. Salivary cortisol levels remained elevated throughout the observation period, indicating prolonged stress recovery. These results highlight the need for longer washout phases in XR research and raise safety concerns for professional applications involving post-exposure task performance.

Mansi Sharma, Alexandre Duchevet, Florian Daiber et al.

Unexpected events can impair attention and delay decision-making, posing serious safety risks in high-risk environments such as aviation. In particular, reactions like startle and surprise can impact pilot performance in different ways, yet are often hard to distinguish in practice. Existing research has largely studied these reactions separately, with limited focus on their combined effects or how to differentiate them using physiological data. In this work, we address this gap by distinguishing between startle and surprise events based on physiological signals using machine learning and multi-modal fusion strategies. Our results demonstrate that these events can be reliably predicted, achieving a highest mean accuracy of 85.7% with SVM and Late Fusion. To further validate the robustness of our model, we extended the evaluation to include a baseline condition, successfully differentiating between Startle, Surprise, and Baseline states with a highest mean accuracy of 74.9% with XGBoost and Late Fusion.

Yazdan Izadi, Majid Nabipour, Gholamhassan Ranjbar

Abstract Fodder production in saline environments requires salt-tolerant plants. This study investigated the potential of the halophyte Salicornia persica ecotypes as a fodder crop under seawater salinity by examining its physiological and biochemical responses. The effects of varying salinity levels [control (0.96 dS.m−1), and 10, 20, and 40 dS.m−1, achieved by diluting Persian Gulf water] on growth, yield, stomatal exchange rate, photosynthetic traits, and qualitative fodder characteristics were evaluated. Three S. persica accessions collected in Iran (Central Plateau, Urmia, and Bushehr) were included. The results showed that, among the tested ecotypes, Central Plateau and Urmia exhibited the most desirable interaction with the 10 dS.m−1 salinity treatment, highlighting a beneficial combination of ecotype and salinity level. Regarding growth characteristics, plant height and forage yield were highest at 10 dS.m−1 and lowest at 40 dS.m−1 salinity. In terms of forage quality, the Bushehr accession under non-stress conditions and the Central Plateau accession at 20 dS.m−1 exhibited the highest nitrogen and crude protein percentages. The 10 and 20 dS.m−1 salinity treatments displayed more favorable forage quality profiles, whereas the 40 dS.m−1 treatment resulted in elevated fiber and Acid Detergent Fiber (ADF) percentages, potentially reduces fodder palatability for livestock. These findings suggest that the Central Plateau and Urmia ecotypes demonstrate significant potential for forage production in saline environments. These ecotypes are a promising option for cultivation in coastal areas, particularly with irrigation using Persian Gulf seawater at a salinity of 10–20 dS.m−1.

Vladimir Vinarsky, Stefania Pagliari, Bacel Aldabash et al.

Abstract Cardiac diseases are fueled by extracellular matrix (ECM) remodelling. Together with the altered ECM chemical composition, the mechanical turmoil associated with ECM maladaptive remodelling in the pathological heart drives the shuttling of Yes Associated Protein 1 (YAP1) into cardiomyocyte (CM) nuclei that results either in cell cycle re-entry or cardiomyocyte hypertrophy. The mechanism of YAP1 reactivation and factors driving qualitatively different cellular outcomes is not well understood. Here we employed mechanical actuation as a proxy reproducing ECM remodelling in vitro to trigger YAP1 nuclear shuttling in contractile cardiomyocytes derived from human embryonic and induced pluripotent stem cells (hPSCs). By using hPSC lines in which YAP1 expression has been genetically depleted, super-resolution microscopy and electrophysiological measurements, we show that ECM-triggered nuclear presence of endogenous YAP1 contributes to cardiomyocyte maturation, participates in the formation and alignment of myofibrils, as well as in the maturation of their electrophysiological properties and calcium dynamics. We eventually exploit engineered heart tissues (EHTs) to demonstrate that the net effect of YAP1 deficiency in cardiomyocytes is the inability to respond to physiological stimuli by compensatory growth that results in reduced force development. These results suggest that the re-activation of endogenous YAP1 following ECM maladaptive remodelling promotes cardiomyocyte contractility by restructuring the sarcomere apparatus and the maturation of electrophysiological properties via transcriptionally dependent and independent mechanisms.

Zhongsheng Zhang, Zhongsheng Zhang, Zhongsheng Zhang et al.

Light strongly influences the carbon (C) metabolism of seaweed through both algal carbon content and organic carbon release, thereby driving the carbon cycling of coastal oceans. However, the response of seaweed organic carbon release to varying light intensities remains an underexplored area of research. This study aimed to fill this gap by analyzing the effects of four different light intensities (5, 50, 200, and 500 μmol m–2 s–1) on the growth, carbon content, and organic carbon release of two strains (W28–42 and WO15-4) of Pyropia haitanensis. The results showed that as light intensity increased, both strains experienced an initial rise in growth rate followed by a decline, with the highest growth observed at 200 μmol m–2 s–1. Simultaneously, tissue C content increased with light intensity, whereas the nitrogen (N) and phosphorus (P) contents exhibited decreasing trends. This led to increases in the C:N and C:P ratios, indicating that high light intensity may enhance C fixation and suppress the absorption of N and P. Of particular interest was the difference in organic carbon release between the two strains. The W28–42 strain’s rate of dissolved organic carbon (DOC) release increased significantly with light intensity, whereas the WO15–4 strain’s DOC release rate remained unaffected by variations in light intensity. The particulate organic carbon (POC) release rates of both strains increased under higher light intensity, with the W28–42 strain showing a more substantial increase than the WO15–4 strain. This study demonstrates that the release of DOC by P. haitanensis exhibits distinct strain-specific responses to variations in light intensity, a result that may be attributed to differences in photosynthetic physiology and genetic makeup. These insights provide a foundation for enhancing the efficiency of fishery carbon sinks through the manipulation of light intensity.

Maximilien Lora, H. A. Ménard, Anastasia Nijnik et al.

ABSTRACT Low dose methotrexate (LD‐MTX) remains the gold standard in rheumatoid arthritis (RA) therapy. Multiple mechanisms on a variety of immune cells contribute to the anti‐inflammatory effects of LD‐MTX. Inflammatory signaling is deeply implicated in hematopoiesis by regulating hematopoietic stem and progenitor cell (HSPC) fate decisions; raising the question of whether HSPC are also modulated by LD‐MTX. This is the first study to characterize the effects of LD‐MTX on HSPC. CD34+ HSPC were isolated from healthy donors' non‐mobilized peripheral blood. Resting and/or cycling HSPCs were treated with LD‐MTX [dose equivalent to that used in RA patients]. Flow cytometry was performed to assess HSPC viability, cell cycle, surface abundance of reduced folate carrier 1 (RFC1), proliferation, reactive oxygen species (ROS) levels, DNA double‐strand breaks, p38 activation, and CD34+ subpopulations. HSPC clonogenicity was tested in colony‐forming cell assays. Our results indicate that in cycling HSPC, membrane RFC1 is upregulated and, following LD‐MTX treatment, they accumulate more intracellular MTX than resting HSPC. In cycling HSPC, LD‐MTX inhibits HSPC expansion by promoting S‐phase cell‐cycle arrest, increases intracellular HSPC ROS levels and DNA damage, and reduces HSPC viability. Those effects involve the activation of the p38 MAPK pathway and are rescued by folinic acid. The effects of LD‐MTX are more evident in CD34+ CD38High progenitors. In non‐cycling HSPC, LD‐MTX also reduces the proliferative response while preserving their clonogenicity. In summary, HSPC uptake LD‐MTX differentially according to their cycling state. In turn, LD‐MTX results in reduced proliferation and the preservation of HSPC clonogenicity.

Atau Tanaka, David Fierro, Francesco Di Maggio et al.

We present an update on the EAVI physiological interface, a wireless, microcontroller based hardware design for the acquisition of bioelectrical signals. The system has been updated to process electroencephalogram brain signals in addition to muscle electromyogram. The hardware/firmware system interfaces with host software carrying out feature extraction and signal processing. Recent advances in electronics have made physiological computing applications practical and feasible. However, there is a gap between high end biomedical equipment and consumer DIY solutions. The hardware design we present here bridges this gap, and combines a specialized biosignal acquisition chip mated with a general-purpose microcontroller. It is based on the Texas Instruments ADS129x family a single chip integrated solution for high quality biosignal amplification and digitization. It serves as analogue front end via programmable gain amplifiers to a 24bit delta-sigma analog-digital converter. The microcontroller is the STMicroelectronics STM32F427, a Cortex-M4 family microcontroller with floating point unit . In addition to EMG acquisition, the board includes a Kionix KX122 three-axis accelerometer. The TI and Kionix sensing chipts communicate with the ST microcontroller over an I2C digital serial bus. The board communicates with the host computer or rest of the music system wirelessly over Bluetooth LE 4.2 using an ST SPBTLE-1S transceiver. The board can also communicate over USB where it registers with the host as a class compliant audio and MIDI device. Audio and physiological signals are treated in the same signal processing chain using the OWL framework. The demo will show multichannel EMG, and single channel EEG. We call this hybridization ''ExG''. We will present documentation of the EAVI board used in the lab and on stage, in user studies with neuro-diverse musicians and trained instrumentalists, as well as in performance with the experimental all-female band, Chicks on Speed.

Zhifeng Wang, Wanxuan Wu, Chunyan Zeng

Most affective computing tasks still rely heavily on traditional methods, with few deep learning models applied, particularly in multimodal signal processing. Given the importance of stress monitoring for mental health, developing a highly reliable and accurate affective computing model is essential. In this context, we propose a novel model, for affective state prediction using physiological signals. PhysioFormer model integrates individual attributes and multimodal physiological data to address interindividual variability, enhancing its reliability and generalization across different individuals. By incorporating feature embedding and affective representation modules, PhysioFormer model captures dynamic changes in time-series data and multimodal signal features, significantly improving accuracy. The model also includes an explainability model that uses symbolic regression to extract laws linking physiological signals to affective states, increasing transparency and explainability. Experiments conducted on the Wrist and Chest subsets of the WESAD dataset confirmed the model's superior performance, achieving over 99% accuracy, outperforming existing SOTA models. Sensitivity and ablation experiments further demonstrated PhysioFormer's reliability, validating the contribution of its individual components. The integration of symbolic regression not only enhanced model explainability but also highlighted the complex relationships between physiological signals and affective states. Future work will focus on optimizing the model for larger datasets and real-time applications, particularly in more complex environments. Additionally, further exploration of physiological signals and environmental factors will help build a more comprehensive affective computing system, advancing its use in health monitoring and psychological intervention.

Kaixin Ji, Danula Hettiachchi, Flora D. Salim et al.

Information access systems are getting complex, and our understanding of user behavior during information seeking processes is mainly drawn from qualitative methods, such as observational studies or surveys. Leveraging the advances in sensing technologies, our study aims to characterize user behaviors with physiological signals, particularly in relation to cognitive load, affective arousal, and valence. We conduct a controlled lab study with 26 participants, and collect data including Electrodermal Activities, Photoplethysmogram, Electroencephalogram, and Pupillary Responses. This study examines informational search with four stages: the realization of Information Need (IN), Query Formulation (QF), Query Submission (QS), and Relevance Judgment (RJ). We also include different interaction modalities to represent modern systems, e.g., QS by text-typing or verbalizing, and RJ with text or audio information. We analyze the physiological signals across these stages and report outcomes of pairwise non-parametric repeated-measure statistical tests. The results show that participants experience significantly higher cognitive loads at IN with a subtle increase in alertness, while QF requires higher attention. QS involves demanding cognitive loads than QF. Affective responses are more pronounced at RJ than QS or IN, suggesting greater interest and engagement as knowledge gaps are resolved. To the best of our knowledge, this is the first study that explores user behaviors in a search process employing a more nuanced quantitative analysis of physiological signals. Our findings offer valuable insights into user behavior and emotional responses in information seeking processes. We believe our proposed methodology can inform the characterization of more complex processes, such as conversational information seeking.

Meilinah Hidayat, Janice Natalia, Ardo Sanjaya et al.

High sodium intake infuences the development of chronic kidney disease (CKD). Various factors can infuence sodium consumption, one of which is impaired taste perception. This study aims to evaluate factors infuencing taste disorders and the impact of high intake of sodium, saliva, and zinc, especially in CKD patients. The method used involved searching for articles using Google Scholar, PubMed, EBSCO, and ProQuest search engines. The inclusion, exclusion criteria, and journal selection method, using Problem/Population, Intervention, Comparison, Outcome form and Prisma Flow Diagram, focused on experimental studies in the last ten years (2013-2023) with specifc search keywords. A total of 28 suitable articles matched the criteria. The results revealed three sub-themes: (A) Factors afecting sodium intake: Taste disorder/dysgeusia in CKD, (B) Efect of zinc on sodium intake or CKD, and (C) Efect of sodium on CKD. This study discusses the three most signifcant factors that infuence taste distortion: salt intake, saliva quality, and zinc defciency, besides old age. Taste disorders due to old age can be overcome with education and behavior planning. The habit of high sodium intake and saliva quality can be improved by reducing sodium intake, while the management of zinc defciency is addressed through supplementation. In summary, tasting disorders in CKD are strongly infuenced by high intake of sodium, saliva, and zinc defciency.

Zhuravleva Larisa

The principle of differentiated technologies is to process fields in accordance with the actual needs of agricultural crops at each specific point of the field. The purpose of the work was to analyze the effectiveness of the use of differentiated fertilization technologies in the cultivation of winter wheat of the Moskovskaya variety. Field research was carried out according to three options: without the use of fertilizers, the application of fertilizers by a single norm and by differentiated technology. The use of fertilizers using traditional fertilization technology allowed for an increase in yield of almost 32% compared to the control (without fertilizers).With the use of differentiated technologies, the yield increased by 82%.

Liza R. Moscovice, Birgit Sobczak, Taru Niittynen et al.

Although best known for its established role in mediating parturition and lactation, the highly-conserved neuropeptide hormone oxytocin also mediates a range of social and stress-buffering processes across mammalian species. Measurements of peripheral oxytocin in plasma have long been considered the gold standard, but there is increasing interest in developing methods to detect oxytocin non-invasively in saliva. Here we present an analytical and biological validation of a novel method to measure salivary oxytocin (sOXT) in an under-studied research group: farm animals. Given their similarities with humans in physiology and brain, methods that can identify valued social contexts and social relationships for farm animals and investigate their function have implications for clinical research as well as for animal welfare science. However, current methods to measure sOXT vary greatly in terms of sample collection, pre-measurement processing and measurement and more rigorous standardization and validation of methods is critical to determine the utility of sOXT as a biomarker of salient social events and related emotions. We optimized a method for extracting sOXT in pigs and horses and measured sOXT in extracted samples using a commercially available enzyme-immunoassay. Extracted samples were within acceptable ranges for precision (CVs < 15.2%), parallelism and recovery (94%–99%) in both species. Salivary oxytocin increased in samples collected during birth in pigs (Friedmans, p = 0.02) and horses (Wilcoxon, p = 0.02). Salivary oxytocin tended to decrease in sows after a 90-min separation from their piglets (Wilcoxon, p = 0.08). We conclude that sOXT can be reliably linked to physiological events that are mediated by the oxytocinergic system in farm animals, but that more research is needed to determine whether sOXT is a reliable trait marker for more general oxytocin system activation in response to salient social events. Future research should characterize how individual attributes and salivary parameters influence sOXT measurement and should emphasize reporting of analytical and biological validations to increase acceptance of non-invasive methods.

Jenni Gårdstedt-Berghog, Jenni Gårdstedt-Berghog, Aimon Niklasson et al.

ObjectivesTo explore the timing of menarche, postmenarcheal growth, and to investigate the impact of various variables on menarcheal age and postmenarcheal and pubertal growth.Study DesignThis longitudinal community population-based study analyzed pubertal growth and menarcheal age in 793 healthy term-born Swedish girls, a subset of the GrowUp1990Gothenburg cohort. The timing of menarche and postmenarcheal growth was related to variables from the Quadratic-Exponential-Pubertal-Stop (QEPS) growth model, birth characteristics, and parental height. Multivariable models were constructed for clinical milestones; at birth, age 7 years, pubertal growth onset, and midpuberty.ResultsMenarche aligned with 71.6% (18.8) of the QEPS model's specific pubertal growth function, at a mean age of 13.0 (1.3) years, ranging from 8.2 to 17.2 years. Postmenarcheal growth averaged 8.0 (4.9) cm, varying widely from 0.2 to 31.1 cm, decreasing with later menarche. Significant factors associated with menarcheal age included height at 7 years, childhood body-mass index, parental height, and QEPS-derived pubertal growth variables. Multivariable models demonstrated increasing explanatory power for each milestone, explaining 1% of the variance in menarcheal age at birth, 8% at age 7 years, 44% at onset of pubertal growth, and 45% at midpuberty.ConclusionsThis study underscores the strong link between pubertal growth and age at menarche. Data available at start of puberty explain 44% of the variation in menarcheal age, apparent on average 3.2 years before menarche. In addition, the study shows a previously seldom noticed wide variation in postmenarcheal height gain from 0.2 to 31.1 cm.

Himeshwari Verma, Devpriya Lakra, Vyom Agarwal

Introduction: HIV (Human Immunodeficiency Virus) continues to be a major global public health issue with no cure. Vitamin D is a fat-soluble hormone that is majorly involved in the classical function of calcium and phosphorus hemostasis and bone mineralization as well as non-classical functions of immune modulation in various viral and autoimmune diseases. A combination of both traditional risk factors, HIV- specific and antiretroviral therapy (ART)-specific contributors leave HIV-infected persons (PLHIV) at a greater risk for low 25-OH-Vitamin D levels and frank vitamin D deficiency. Aims and Setting: The current study was conducted to assess and characterize the prevalence of Vitamin D deficiency in PLHIV-on-ART attending a tertiary care hospital and assess the factors that may be affecting it. Methods: 95 PLHIV registered at an ART center were selected over a period of 6 months based on Inclusion and Exclusion criteria. Flow cytometry estimation of CD4 count and ELISA based quantitative assessment of serum 25-OH Vitamin D3 were done along with detailed clinical examination. P<0.05 was considered to be statistically significant. Results: About half of the PLHIV assessed were deficient in vitamin D. Severe vitamin D deficiency was noted in one-fourth of subjects. Serum vitamin D levels were significantly less in subjects on ZLN regime compared to TLE regime. No significant difference was found between vitamin D deficiency and duration of treatment, different treatment regimens or differing CD4 counts. No significant association of serum levels of Vitamin D with duration of treatment or varying CD4 count was found. Conclusion: There is greater prevalence of subnormal levels of Vitamin D in PLHIV on ART. ZLN regime appears to have a negative impact on Vitamin D levels in comparison to TLE regimen. More research needs to be done to further evaluate the physiology of Vitamin D in PLHIV on ART.

Hamid Ghaderi, Brandon Foreman, Amin Nayebi et al.

Determining clinically relevant physiological states from multivariate time series data with missing values is essential for providing appropriate treatment for acute conditions such as Traumatic Brain Injury (TBI), respiratory failure, and heart failure. Utilizing non-temporal clustering or data imputation and aggregation techniques may lead to loss of valuable information and biased analyses. In our study, we apply the SLAC-Time algorithm, an innovative self-supervision-based approach that maintains data integrity by avoiding imputation or aggregation, offering a more useful representation of acute patient states. By using SLAC-Time to cluster data in a large research dataset, we identified three distinct TBI physiological states and their specific feature profiles. We employed various clustering evaluation metrics and incorporated input from a clinical domain expert to validate and interpret the identified physiological states. Further, we discovered how specific clinical events and interventions can influence patient states and state transitions.