Regulation of autonomic arousal during infancy is critical for the development of self-regulation, socioemotional development and cognitive functioning. High frequency heart rate variability (HF-HRV), a key indicator of parasympathetic nervous system function, supports physiological regulation and emerging behaviors that foster social engagement during this critical developmental period. However, research on HF-HRV has largely been confined to controlled settings with highly resourced populations, limiting its applicability to culturally and contextually diverse populations. This study presents a protocol for collecting HF-HRV data from one-month-old infants in remote and low-resource field contexts, specifically, the Rohingya camps and surrounding host communities in Cox’s Bazar, Bangladesh. We present a three-step process to address challenges inherent to working in such contexts while ensuring ecological validity and cultural sensitivity, navigating logistical challenges, and optimizing data quality. Data quality metrics in 148 infants showed high usability, with 86% of data being usable when infants were held by their mothers (joint condition), and 80% when they were alone (solo condition). Aligning with theoretical expectations, higher respiratory sinus arrythmia (RSA, extracted from HRV) was negatively correlated with behavioral arousal (e.g., more alert, exhibiting motor activity) in both conditions. RSA also remained stable across 30-second segments within each baseline condition, indicating no systematic change in mean RSA levels across time. This study demonstrates a scalable, ethical approach to collecting HRV data in remote field settings, providing a foundation for exploring how early autonomic development intersects with proximal processes such as caregiving across diverse cultural contexts. This protocol aims to advance equity and inclusivity in developmental psychophysiology while maintaining rigorous scientific standards.

IntroductionTransorbital Penetrating Intracranial Injury (TOPI) is one of the rare cases of traumatic brain injury. The major cause of TOPI is the missiles such as bullets in the war. Non-missile foreign bodies such as iron rods, wood, nails, and needles are even more rare. 1-3Penetrating Brain Injuries are associated with high mortality and morbidity due to damage to important structures such as major vessels, and brainstem, as well as risk of infection. Vascular injury or injury to the brainstem might be fatal. The risk of infection is increased in the case of a wooden foreign body, although infection almost always occurs in delayed treatment. However, early treatment with surgical and nonsurgical approaches can reduce chances of infection and hemorrhage, therefore morbidity and mortality significantly. 3Here we present a unique case of transorbital penetrating intracranial injury caused by a wooden foreign body. Despite the complexity of such injury, our case demonstrated a successful clinical outcome with no long-term morbidity or mortality. This case report was prepared in line with SCARE guidelines. 4

TITLE: HYDRANCEPHALY IN NEONATE WITH PRENATAL EXPOSURE TO ALCOHOL DURING PREGNANCY

We review the impact of the cuts in indirect costs for research on academic publishing.

The present work investigates the passive cooling capabilities of CuO nanoparticle-enhanced phase change materials (CPCMs), revealing that the orientation of the thermal energy storage system significantly influences the thermal behaviour and melting characteristics of CPCMs, ultimately affecting heat dissipation. Conventional shapes like rectangular or cylindrical enclosures do not effectively optimize heat transfer and phase change processes. Selecting a curved-quadrilateral sector as the encapsulation shape addresses these issues by enhancing heat transfer efficiency, promoting uniform melting, and optimizing the phase change process. Experimental validation confirms model accuracy, demonstrating minimal discrepancies between predicted and observed data. The results reveal that increasing the inclination angle leads to longer melting fraction durations. Furthermore, the concentration of CuO nanoparticles in PCMs significantly influences thermal conductivity and melting rates. The analysis of a CPCM3 reveals critical insights that in the early stage, rapid melting occurs near the heat source, resulting in a 150% performance improvement. This is followed by an intermediate stage where natural convection further enhances melting, yielding a 140% increase in liquid fraction. Eventually, as the PCM transitions predominantly to liquid, performance stabilizes at a 50% improvement. These findings emphasize the importance of enclosure geometry and orientation in PCM-based thermal management systems, particularly for energy storage and passive cooling applications.

Modular batteries offer substantial advantages to battery energy storage applications, including prolonged battery lifespan and enhanced fault-tolerance. Focusing on DC structures, scalable battery power modules can be interconnected in series and/or in parallel in order to adjust the capacity and voltage of the battery system to the requirements of the application. Selecting the optimal modular configuration is crucial for maximising the advantages of modularity. Therefore, this article presents a methodology designed for evaluating the fault-tolerance and reliability of all possible battery configurations, and provides a comparative analysis including also the controllability, flexibility and voltage amplification capability factors. The Parallel configuration is identified as the optimal solution for low voltage applications. Nevertheless, due to its low amplification capability, the Parallel-Series architecture should be adopted for applications with higher voltage requirements. In this regard, efforts should focus on maximising the number of parallel connected battery power modules, employing a high-gain DC-DC converter.

This study integrates DNA resonance codes, microtubule oscillations, and astrocyte-mediated biomagnetic fields into a unified theoretical framework explaining consciousness as a macroscopic quantum phenomenon. By integrating advanced AI-driven analyses of EEG, NMR, and calcium imaging data, we demonstrate compelling evidence of quantum processes in neural systems. Key findings include: (1) nuclear spins in phosphate molecules (Posner clusters) acting as stable qubits with prolonged coherence times; (2) DNA resonance codes (1-10 THz) modulating neural activity via frequency-locking with microtubule vibrations; and (3) astrocyte-generated biomagnetic fields suppressing decoherence, thereby enabling sustained quantum states in neurons despite the warm, wet environment of the brain. Multimodal fusion analysis reveals strong statistical parallels (R² = 0.79-0.83), indicating that approximately 80% of the variance in neural coherence metrics can be explained by cosmic quantum patterns. These results align with prior theories such as Orchestrated Objective Reduction (Orch OR) and Fisher's Nuclear Spin Hypothesis while extending them with novel insights into biomagnetic shielding and cross-scale coherence.

The evolution of the universe has traditionally been modeled through linear frameworks, yet emerging evidence suggests that non-linear self-organization plays a crucial role in shaping cosmic structures. This study proposes a novel mathematical model of cosmic self-organization, incorporating machine learning techniques to analyze large-scale astronomical datasets from Gaia and ALMA. Using Random Forest regression, we uncover hidden non-linear patterns governing the distribution of matter and energy, indicating the presence of an intrinsic "cosmic code" that dictates galactic evolution. Our findings reveal that non-linear AI models significantly outperform traditional linear regression in predicting astrophysical phenomena, reinforcing the hypothesis that the universe follows a structured yet self-organizing mathematical framework. These insights provide a new direction for computational astrophysics, suggesting that future studies should explore deep learning models and real-time cosmic simulations to further validate this framework.

Recommender systems (RSs) aim to streamline navigation through vast product repositories, with personalization as a critical development. However, modeling user preferences remains challenging due to their dynamic and complexity. Cross-domain learning (CDL) has emerged as a promising approach to enhance personalization by leveraging inter-domain knowledge. Despite advancements, modeling inter-domain knowledge is difficult due to the semantic heterogeneity of participating domains. This paper presents a cross-domain recommendation (CDR) framework and evaluates its effectiveness on 'Book-Movie' item pairs, leveraging books as auxiliary data to enhance movie recommendations. Books offer richer contextual insights into users' cognitive states, thereby addressing legacy challenges such as data sparsity and the cold-start problem. Using pre-trained models such as RoBERTa and DistilBERT, we propose a novel approach for inter-domain knowledge modeling, leveraging the capability of generative models to effectively capture inter-domain knowledge and transfer it to achieve a higher level of personalization in the target domain. RoBERTa, fine-tuned on book data, effectively captures contextual relationships and bridging semantic gaps between domains, whereas DistilBERT captures deep semantic relationships between the textual content of the book and movie domains. Evaluation metrics include LRAP, cross-entropy loss, and precision. RoBERTa outperformed DistilBERT, achieving \textit{LRAP} (0.908), \textit{cross-entropy} (0.269), and \textit{precision} (0.96). Similarity measures, including \textit{domain overlap} (0.992), \textit{domain generalization} (0.7895), \textit{pairwise difference on Genre} (1.418), and \textit{Exact Match Ratio} (0.60) highlight strong alignment between book and movie genres. This work emphasizes a multi-label classification strategy and novel algorithm for cross-domain knowledge modeling, offering a robust solution for CDR challenges with effective trade-off metrics.

Nitrogen is a crucial macronutrient for plant growth, supplied in agroecosystems primarily as nitrate and ammonium. However, inefficient nitrogen use causes significant environmental losses in wheat, where only 48% of applied nitrogen is converted into biomass, but stabilized ammonium-based fertilization offers a promising strategy to reduce losses and enhance sustainability. Ammonium nutrition can confer agronomic benefits, including improved grain quality and stress tolerance in wheat, but high ammonium concentrations can be toxic, impairing plant growth and triggering physiological and molecular defense responses. This study aimed to investigate ammonium tolerance within a diverse panel of hexaploid winter wheat ( Triticum aestivum L.) accessions from the Gediflux collection. Hydroponic screening revealed that while most wheat varieties preferred ammonium-nitrate, few genotypes exhibited superior biomass production under ammonium-rich conditions. RNA-seq analysis of two contrasting genotypes—one tolerant and one susceptible—uncovered distinct gene regulation patterns in the tolerant cultivar. Notably, at the leaf level, genes encoding chlorophyll-binding proteins and Rubisco were significantly upregulated, potentially enhancing photosynthetic capacity and biomass yield. Additionally, key genes involved in abscisic acid signaling, including PYL4, PYL5, and PYL6, were upregulated, suggesting a crucial role in chloroplast protection and stress adaptation. To mitigate ammonium toxicity, the tolerant cultivar downregulated ammonium transport and storage-related genes, such as AMT2, CAP1, and TIP2;3, indicating a controlled ammonium homeostasis mechanism that limits excessive uptake and vacuolar sequestration. In roots, auxin-responsive genes were predominantly upregulated in the tolerant cultivar, with ARF6, ARF10, ARF16, and ARF17 potentially contributing to root system reorganization for improved ammonium tolerance. Ammonium nutrition significantly influenced transcriptional regulation across roots and leaves, with the tolerant genotype exhibiting a stronger root response and increased involvement in trichome morphogenesis, shoot development, hormonal signaling, and stress adaptation. K-means clustering identified differentially expressed transcription factors, including bZIP and WRKY-domain TFs associated with stress signaling, as well as nitrogen metabolism-related TFs such as ERF2 and HRE1. These findings provide novel insights into the molecular mechanisms underlying ammonium tolerance in wheat, highlighting potential targets for breeding varieties with enhanced nitrogen use efficiency and stress resilience.

Title:Granulomatosis with Polyangiitis Following COVID-19 Infection and Pfizer-BioNTech Vaccination Authors:Alyssa Kang, DO. Jefferson Einstein Montgomery Hospital Alyssa.kang@jeffereson.eduShivani Modi, MD. Jefferson Einstein Montgomery Hospital Shivani.modi@jefferson.edu   Kibo Yoon, MD. Cleveland Clinic yoonk2@ccf.orgKey Clinical Message: COVID-19 infection and the administration of the COVID-19 vaccine both have the potential to trigger an immunogenic response that can uncover a pre-existing vasculitis. This is a case of granulomatosis with polyangiitis that manifested with progressive episodes of hemoptysis after receiving the Pfizer-BioNTech vaccine and contracting COVID-19 3 months later.Introduction:In August 2021, the U.S. Food and Drug Administration approved the first COVID-19 vaccine known as Pfizer-BioNTech. Over the subsequent months, the global rollout of the vaccine was associated with significant decreases in COVID-19 morbidity and mortality. However, recent research has reported cases of immunologic complications following both vaccination and COVID-19 infection.Granulomatosis with polyangiitis (GPA) is a systemic small- and medium-vessel vasculitis typically characterized by necrotizing granulomas in the respiratory tract, necrotizing glomerulonephritis, and the presence of antineutrophil cytoplasmic antibodies (ANCA). Recent studies have identified neutrophil extracellular traps (NETs)—web-like structures released by activated neutrophils—as playing a key role in the pathogenesis of vasculitis, including GPA. Furthermore, both COVID-19 and the Pfizer-BioNTech vaccine have been shown to increase NET formation, potentially linking the two as contributing factors in the development or unmasking of GPA. This case report discusses a unique case of a 41-year-old male who developed GPA following COVID-19 infection shortly after receiving the second dose of the Pfizer-BioNTech vaccine.Case History/examination:A 41-year-old Caucasian male with a history of recurrent sinus infections, obesity, and alcohol abuse presented with a 3-week history of hemoptysis, arthralgias, and a petechial rash over the bilateral lower extremities. He reported no personal or family history of autoimmune diseases. His vaccination history included receiving the second dose of the Pfizer-BioNTech vaccine approximately 15 months prior. Three months after vaccination, he contracted COVID-19, after which he developed persistent sinusitis symptoms which he managed with over-the-counter medications. During the two weeks preceding hospitalization, he developed progressive arthralgias that began in his feet and ankles and later involved his wrists and hands, as well as a petechial rash over the anterior shins and oral aphthous ulcers.Differential diagnosis, investigations and treatment:Upon presentation, the patient was hypoxic with an oxygen saturation of 84% and was placed on 3L oxygen via nasal cannula. A computed tomography pulmonary embolism study revealed multifocal ground-glass opacities and a reverse halo sign, suggesting alveolar hemorrhage (Figure 1). Initial lab results showed an elevated creatinine of 1.73 mg/dL (baseline 1.26 mg/dL), a positive rheumatoid factor (RF) of 41 U/mL, negative antinuclear antibody (ANA), and positive c-ANCA and proteinase 3 (PR3) antibodies. The respiratory viral panel was negative. A renal biopsy demonstrated necrotizing glomerulonephritis, confirming the diagnosis of GPA.The patient was treated with rituximab and pulse steroid therapy. He later received a second dose of rituximab and transitioned from steroids to avacopan, a C5a receptor inhibitor that has been shown to be as effective as prednisone therapy according to the ADVOCATE trial.5Discussion:COVID-19 has been associated with increased formation of neutrophil extracellular traps (NETs), which are comprised of inflammatory proteins with the potential to precipitate vasculitis. They have also been reported to contain enzymes from all types of neutrophil granules including proteinase 3 (PR3).3 ANCA in GPA reacts with PR3 which leads to de-granulation and damage of endothelial cells.1 Thus, there may be an association between an increased concentration of NETs and a predisposition to the development or diagnosis of GPA. SARS-CoV2 spike proteins in vaccines have been shown to evoke the release of NETs4, and this suggests that contracting COVID-19 within a certain timeframe after receiving the vaccine may lead to a synergistic increase in the formation of NETs. The immune response triggered by the combination of the vaccine and subsequent COVID-19 infection may create a “double hit”, resulting in a surge of NETs that could predispose an individual to the development or the unmasking of a pre-existing inflammatory condition like GPA.The “double-hit” hypothesis implies that the combined effects of the vaccine and the viral infection might tip the balance in individuals with a subclinical predisposition to autoimmunity or incite the onset of an inflammatory disease like GPA. Indeed, emerging case reports have detailed instances of ANCA-associated vasculitis following COVID-19 or even post-vaccination, although such events remain rare. More broadly, the interplay between NETosis and autoimmune activation is supported by both in vitro studies and investigations in patients with severe COVID-19, where NET-derived components are elevated and correlate with markers of vascular injury and inflammation.6This hypothesis is further underpinned by observations that heightened NET formation has been associated with various autoimmune disorders. NETs expose and modify self-antigens, such as PR3, thereby facilitating a break in immune tolerance and potentially triggering a pathogenic autoimmune response. In GPA, the exposure to a high burden of NETs may lead not only to enhanced autoantigen presentation but also to an amplification of the inflammatory cascade that damages blood vessels.7,8 Consequently, in individuals who have been recently vaccinated with SARS-CoV-2 spike protein–based vaccines, contracting COVID-19 may represent a precarious “perfect storm” that results in a marked increase in NETosis—potentially predisposing them to the de novo development of GPA or unmasking a previously latent condition.This case highlights a possible connection between the Pfizer-BioNTech COVID-19 vaccine, COVID-19 infection, and the development of GPA. While further research is needed to understand the exact mechanisms by which COVID-19 and vaccination may trigger or unmask autoimmune diseases, this case underscores the importance of screening for vasculitis in patients who experience prolonged sinus infections and symptoms following COVID-19 infection. Understanding the interplay between COVID-19, the vaccine, and immune system dysregulation may guide clinicians in early diagnosis and treatment of such conditions.Author Contributions:Alyssa Kang: conceptualization, data curation, formal analysis, investigation, methodology, supervision, validation, visualization, writing – original draft, writing – review and editing.   Shivani Modi: writing – original draft, writing – review and editing.Kibo Yoon: writing – review and editing.Acknowledgements: NoneFunding: No funding was used for this case report.Ethics Statement:As a case report with the patient’s signed consent, no other ethical review was required.Consent:Written informed consent was obtained from the patient for the publication of this case report.Conflicts of Interest:The authors declare no conflicts of interest.

Phosphate, fractures and frustration – A Missed Diagnosis of Oncogenic Osteomalacia Leading to Multisystem ComplicationDr Ryan Wilson – GMC: 8007097Dr Lydia Sturridge GMC: 4528829Frimley Health Foundation TrustFrimley Park Hospital Portsmouth Road Frimley, Camberley Surrey GU16 7UJ United KingdomAuthor contribution statementDr. Ryan Michael Wilson (Corresponding Author) Frimley Park Hospital NHS Foundation Trust, Emergency Medicine, Portsmouth Road, Frimley, Frimley, UK GU16 7UJ Email: ryanwilson9998@gmail.com ORCID iD: 0009-0004-1783-7402 Contributions: Project administration, writing – original draft, writing – review and editing.Dr. Lydia Sturridge Frimley Park Hospital NHS Foundation Trust, Emergency Medicine, Portsmouth Road, Frimley, Frimley, UK GU16 7UJ Email: lydia.sturridge@nhs.net Contributions: Writing – review and editing.Consent:Written informed consent was obtained from the patient for publication of this case report in accordance with the journal’s patient consent policy.Key clinical message:Persistent hypophosphataemia must prompt thorough evaluation. This case highlights the severe, multi-system consequences of delayed recognition of oncogenic osteomalacia. Early biochemical assessment, imaging, and multidisciplinary involvement are critical to avoid misdiagnosis and prevent irreversible complications such as skeletal fragility and cardiomyopathy.Introduction:Oncogenic osteomalacia, or tumour-induced osteomalacia (TIO), is a rare paraneoplastic syndrome caused by renal phosphate wasting due to excess fibroblast growth factor 23 (FGF23) secreted by phosphaturic mesenchymal tumours (PMTs). Resulting in hypophosphataemia, osteomalacia, muscular weakness, and bone pain¹, this condition is often misdiagnosed due to nonspecific symptoms and the difficulty in locating the tumour².This report details the prolonged diagnostic journey of a 44-year-old mechanic whose symptoms were misattributed to mechanical causes. It underscores the importance of an early biochemical assessment, imaging, and multidisciplinary collaboration to prevent late-stage complications.Case history and examination:Chronic pain, progressive weakness, and height loss are unusual in a 44-year-old male. Delayed diagnosis resulted from a failure to consider symptoms holistically and a postponed biochemical workup. Despite a history of worsening functional decline, his symptoms were repeatedly attributed to mechanical osteoarthritis and chronic pain syndrome due to a previous road traffic accident years prior. His analgesic regime consisted of oral morphine, amitriptyline, naproxen, and gabapentin.Multiple medical professionals could not identify a diagnosis that, if recognized earlier, could have prevented skeletal deterioration and cardiac involvement. This case highlights the need to investigate persistent hypophosphataemia and adopt a multisystem approach to avoid mistaking metabolic bone disease for chronic pain.This gentleman, X, first sought medical attention for worsening exertional dyspnoea, with paroxysmal nocturnal dyspnoea and bilateral lower-limb swelling over approximately six months. His partner also noted increasing fatigue, even on mild exertion. Initially, such symptoms were attributed to hypertension and deconditioning; however, the severity of this raised concerns for a systemic illness.His initial cardiovascular assessment revealed a blood pressure of 155/105, and an N-terminal Pro-B type Natriuretic peptide (BNP) of greater than 2000 ng/L. An electrocardiogram (ECG) yielded a left ventricular hypertrophy (LVH) pattern, with associated T-Wave inversion in the anterolateral distribution. Moreover, a transthoracic echocardiogram (TTE) confirmed a dilated left ventricle at 6.3 cm, with an ejection fraction of roughly 30%, consistent with a diagnosis of dilated cardiomyopathy (DCM). Given the emerging links between phosphate metabolism and myocardial function³, this was an early opportunity to formally assess his phosphate levels.At the same time, his ‘arthritic’ pain was worsening – namely in his back, hips, and ankles – necessitating the use of crutches to ambulate. Four years prior to his presentation in the clinic, he had suffered a road traffic accident, leading to assumptions that such discomfort was related to injuries and subsequent arthritic change. Despite this, he deteriorated from this perspective; with arthritis severe enough in his right ankle to consider fusion surgery. At this time, no further metabolic bone assessment was considered.Differential diagnoses, investigation and treatment:

Title

This work develops the foundations of particle dynamics within an \emph{Expanded Theory of Relativity} that unifies special relativity with quantum wave dynamics. The framework rests on three postulates: the principle of relativity; a principle of maximal spatiotemporal symmetry; and a \emph{Regularity Postulate} requiring that the composition of two finite inertial motions yields a finite operational relative velocity. By promoting time to a three-dimensional vector subspace, the theory separates into two coupled projections: \emph{Pole dynamics}, which recovers the Lorentzian interval, and \emph{Flag dynamics}, which describes the evolution of the time vector's orientation via a unit-quaternion rotor field $\Psi$. Rather than assuming a Lorentzian signature axiomatically, we demonstrate that the temporal sign branch is fixed by enforcing the Regularity Postulate. Furthermore, since the six- and four-dimensional metrics are found to coincide along the physical worldline, the internal temporal frame must be transported without generating spurious kinetic energy. This geometric compatibility condition yields a universal covariant transport law $D_\tau \Psi = 0$. Without imposing quantization axioms, this law reproduces the Klein--Gordon, Dirac, and Proca equations depending on the chosen linear representation. In this context, $\hbar$ is identified as a geometric stiffness scale converting internal temporal rotation into external translation. The theory distinguishes itself by deriving these distinct dynamics from a single unified field equation, where particle spin arises from the algebraic carrier space rather than independent axioms.

Background: The research team previously found that interleukin-19 (IL-19) was associated with atopic dermatitis (AD) by single-cell RNA sequencing. However, little is known about its cellular sources, targets, functions, and underlying mechanisms. Objective: This study investigated the roles and mechanisms of IL-19 in AD. Methods: The role of IL-19 in AD was analysed in skin lesions and serum samples of patients with AD, IL-19 knockout (IL-19 KO) mice and immortalized human keratinocyte cell line (HaCaT) cells stimulated with different inflammatory factors. Results: The expression of IL-19 significantly increased in skin lesions of patients with AD and the MC903-induced AD mouse model, with keratinocytes (KCs) identified as the primary source. Notably, the expression of IL-20Rα/IL-20Rβ receptor subunits varied across different skin regions. IL-19 knockout mice exhibited significantly lower severities of dermatitis and eosinophil infiltration in the ear compared with wild-type mice. Mechanistic investigations revealed that upregulation of IL-19 in AD exacerbated the dysfunction of KC by promoting the phosphorylation of STAT (signal transducer and activator of transcription axis) 3 and STAT6, specifically characterized by reduced production of barrier proteins and increased secretion of epithelial-derived pro-inflammatory factors. Additionally, IL-19 was found to promote Th2/Th17 polarization of CD4+ T cells and increase M2 macrophage markers. Finally, IL-19 amplified IL-4/IL-13 biological effects as a cofactor. Conclusion: Overall, this study was the first to outline the cell-specific role of IL-19 in AD and the potential for targeting IL-19 in the treatment of both immune and non-immune cell-mediated inflammation in AD.

Endemic species are valuable models for understanding evolutionary processes and species adaptation in isolated environments. The Helan Shan pika (Ochotona argentata), endemic to a small region in the Helan Shan of China, represents a unique case of a species with a restricted distribution that is vulnerable to anthropogenic threats and rapid environmental changes. Despite its endangered status, genomic research on O. argentata remains limited. In this study, we present a high-quality genome assembly of O. argentata with high genome contiguity and gene-space completeness. The assembly reveals that 41.28% of the genome consists of repetitive sequences and a total of 24,374 annotated genes. We identified gene families that have undergone significant expansion or contraction, particularly those related to protein synthesis, metabolism, and other functions potentially linked to adaptation in high-altitude environments.. Genome synteny analysis revealed strong conservation between the O. argentata genome and the previously sequenced American pika (Ochotona princeps) genome, while also allowing us to characterize its sex chromosomes. Additionally, population demography analysis indicated a notable population decline in O. argentata approximately 300,000 to 500,000 years ago, coinciding with the mid-Pleistocene glacial period. Furthermore, we identified an increased genetic load in O. argentata compared to pika species with broader distribution ranges, indicating a consequence of inbreeding, likely driven by its highly restricted range and low genetic diversity. Our study provides the first comprehensive genomic resource for O. argentata, essential for understanding the evolutionary processes underlying endemism and conservation needs of the endangered Helan Shan pika.

Ticks are important vectors of zoonotic pathogens, and the presence of these pathogens can be influenced by factors such as the tick microbiome, which, conversely, is shaped by environmental conditions and the presence of tick-borne pathogens, as demonstrated in several studies conducted under controlled conditions. However, the extent of these influences under natural ecological conditions remains underexplored. In this study, we investigated the diversity of the microbiome and the prevalence of pathogens in Ixodes ricinus nymphs across three distinct Belgian ecoregions: Sandy Loam, Condroz, and Ardennes. Using real-time quantitative PCR (qPCR) and Oxford Nanopore 16S rRNA sequencing, we assessed how geography and pathogen presence influence tick-associated microbial communities. Our results revealed significant regional differences in microbiome composition and pathogen prevalence. Borrelia burgdorferi sensu lato (s.l.) was most prevalent in the Ardennes, while Anaplasma phagocytophilum was more common in the Sandy Loam region. Endosymbionts such as Midichloria mitochondrii and Spiroplasma ixodetis also exhibited distinct geographic distributions. Network analysis identified potential pathogen-microbiota interactions, with certain bacterial taxa showing positive or negative associations with specific pathogens. Moreover, microbiome composition was influenced not only by ecoregion but also by pathogens such as Rickettsia helvetica, suggesting that its colonization may actively shape microbial community structure, potentially through competition or facilitation mechanisms. Additionally, microbiome network robustness varied across ecoregions, highlighting the role of ecological context in shaping microbial interactions within ticks. These findings underscore the complex interplay between geography, pathogen presence, and microbial diversity in ticks, emphasizing the need to consider ecological variability when studying tick-borne disease dynamics. Understanding these interactions could inform microbiome-based strategies for vector control and disease prevention.

Background: Obesity can lead to increased levels of anxiety and depression. Given the increasing prevalence of obesity worldwide, insight into the psychological and socioeconomic elements associated with obesity is crucial for the development of effective therapeutic strategies. This study aimed to investigate the association between obesity and anxiety and depression while examining the moderating effects of physical activity and socioeconomic factors. Methods: In this cross-sectional study, 111 obese and overweight participants were included in Shariati Teaching Hospital. Weight and height measurements were used to calculate BMI. Anxiety and depression scores were measured using the Hospital Anxiety and Depression Scale (HADS) score, and physical activity levels were determined using Metabolic Equivalent (MET) scores. Data on socioeconomic characteristics were collected via questionnaires. The data were analyzed using structural equation modeling with SPSS and AMOS software. Results: Among the participants, 81.98% were women, with a mean age of 40.65 years. A positive association was observed between anxiety and obesity (β = -0.201, p = 0.036). Physical activity was not significantly correlated with BMI (p = 0.827) and was not found to mediate the relationship between anxiety, depression, and obesity. However, substance use moderated the effect between chronic diseases and anxiety (β = 0.402, p ≤ 0.001). In contrast, socioeconomic disadvantage showed a protective moderation of the interaction between mental and physical health (β = -0.885, p = 0.021). Conclusion: This study explores the intricate relationship between obesity, mental health, and socio-economic factors. While anxiety showed a positive correlation with obesity, physical activity did not act as a mediating factor. However, substance use and socio-economic status played significant moderating roles, indicating that effective obesity management may require interventions that address both mental health and socio-economic challenges. Conventional measures of physical activity may not adequately account for the particular hazards and demands associated with these factors.

We introduce the Prime Density function, a novel logistic-cubic closed-form approximation to the standard normal cumulative distribution function (CDF). Existing approximations either lack analytic simplicity and invertibility or compromise accuracy, particularly in distribution tails. To overcome these limitations, the Prime Density function employs a logistic sigmoid function with a cubic polynomial argument. Parameters were rigorously optimized through a hybrid global-local procedure combining Differential Evolution and Nelder-Mead methods, minimizing maximum absolute error and root-mean-square deviation across the real line. Our optimized approximation achieves a maximum absolute error below 1.7 × 10 −4 , surpassing classical logistic and rivaling complex rational approximations. The function maintains analytical invertibility, differentiability, and symbolic simplicity, providing distinct computational advantages for real-time analytics, symbolic computation, and resource-limited hardware. Empirical evaluations across diverse datasets-including environmental pollutant indices (PM2.5 AQI), financial returns (S&P 500), and biomedical markers (glucose and triglycerides)-demonstrate the Prime Density function's superior empirical flexibility and precision compared to traditional approximations. The results position the Prime Density function as a practical, rigorously validated, and computationally efficient alternative, effectively bridging analytic simplicity and high-performance demands.

This paper addresses the output consensus problem for heterogeneous multi-agent systems (HMAS) with Denial-of-Service (DoS) attacks under stochastic switching topologies. The stochastic switching communication network among agents is modeled as a time-varying directed graph governed by Bernoulli process. Taking into account the weight of the historical triggering data and corresponding triggering error, a novel dynamic memory event-triggered mechanism (DMETM) is proposed and it can reduce the number of event-triggered to realize significant communication savings. Consider the impact of DoS attacks, a distributed local full-state feedback controller is designed to ensure that the output state of the followers can track the leader. Rely on the Lyapunov theory, it is certificated that output consensus for HMAS can be guaranteed. Finally, the effectiveness and progressiveness of the proposed control scheme are verified by a simulation example.

Rationale: Diabetes mellitus poses a substantial global health burden, necessitating novel therapeutic strategies. Astragalus membranaceus (AM), a traditional Chinese medicinal herb, has demonstrated potential in alleviating diabetic symptoms. This study aimed to investigate the mechanism of AM (root) extract in ameliorating diabetes and identify its bioactive components through advanced metabolomic and data-mining approaches. Methods: Untargeted metabolomics utilizing liquid chromatography-high resolution mass spectrometry (LC-HRMS), combined with quantitative spectrum-effect relationship analysis (QSERA), was applied to analyze AM (root) extract administered in oral experiments using the Leprdb/db mouse model. The AntDAS (Automatic Data Analysis Strategy) platform enabled screening of bioactive compounds from LC-HRMS fingerprints under heavily interfered background conditions. Molecular efficacy predictions for diabetes alleviation were derived via QSERA modeling. Results: 56 bioactive compounds associated with diabetic remediation were identified. Specific adjusting efficacies of bioactive compound on mouse diabetes were predicted by QSERA, proving that astragalus polysaccharide (APS) is the main medicinal component alleviating mouse diabetes and it may be as a potential insulin sensitizer for treating type II diabetes of human. Conclusion: Integrating LC-HRMS-based metabolomics and QSERA provides a systematic strategy to elucidate the pharmacodynamic basis of AM (root) extract, advancing the clinical translation of traditional Chinese medicine resources for diabetes management.

The human brain continuously forms predictions about the unfolding sensory environment, relying on contextual information to anticipate upcoming events while remaining sensitive to unexpected changes. This study examined how pupil-linked phasic arousal, a putative proxy for the locus coeruleus-norepinephrine system, reflects the interplay between tonal surprisal (unexpectedness) and precision (reliability of the inferred context) in dynamic auditory contexts. Twenty-eight participants passively listened to stochastic tone sequences transitioning between periods of low-entropy (informative context) and high-entropy (less informative context). We quantified tone-by-tone surprisal and precision using Bayesian modeling. Pupil dilation responses revealed sensitivity to both surprisal and precision, showing that arousal tracks momentary deviations and the stability of contextual predictions. Analyses of context boundaries showed that transitions between distinct low-entropy environments (LE-dLE) evoked significant pupil dilation, whereas shifts between low- and high-entropy environments (LE-HE, HE-LE) did not. These findings indicate that pupil-linked arousal primarily responds to salient contextual shifts involving stable environments rather than to changes in entropy per se. The results emphasize the role of the locus coeruleus–norepinephrine system in adaptive model updating during passive listening and demonstrate the brain’s continuous monitoring of uncertainty to navigate dynamic auditory environments.

As children’s use of mobile devices continues to concern researchers, society finds itself in a digital domain where such innovations are growing very rapidly. This article is concerned with the so-called virtual autism, which develops in children at the age of 2 months to 5 years of age, due to the excessive use of screens. Such over usage of screen leads children towards developing virtual environment and such children start behaving in similar manner as autistic children like unable to speak, socializing problems etc. This study highlights the importance of scaring children from screens and encouraging them to engage in positive activities and then examines the causes and possible consequences of Virtual Autism. Excessive screen exposure in young children is linked to behavioral patterns resembling autism, termed virtual autism. This study explores how prolonged digital engagement affects speech development and social interactions, highlighting potential risks and the need for alternative activities. Understanding these effects can help parents and educators adopt strategies to reduce screen dependence and promote healthier cognitive and social development in children. Child development specialists view the age between two months and five years as most opportune to learn very complex body skills like speaking language, coordinating body parts and relating with other people. These developments take place within the environment through sights, sounds, and interaction with others. Too much of screen especially where children are concerned at this stage can be injurious to these development outliers and in like manner thereby eliciting an ailment dubbed ‘Virtual Autism.’

Generative AI, particularly Large Language Models (LLMs) like ChatGPT, have shown impressive capabilities in producing human-like text. However, a challenge remains: while LLMs excel at generating content, they often lack a strong grounding in real-world knowledge, which can lead to inaccuracies or generic responses. To address this, Retrieval-Augmented Generation (RAG) was introduced—a technique that significantly enhances the performance and reliability of generative AI by integrating external information into the response generation process.What is Retrieval-Augmented Generation (RAG)?At its core, Retrieval-Augmented Generation (RAG) is a system that combines two powerful techniques: retrieving information from external sources and grounding to generate  content based on that information. Instead of producing responses based on a static knowledge base, RAG systems dynamically retrieve pertinent data from a variety of sources—such as databases, knowledge repositories, or document systems—and integrate it into the content creation process.In simple terms, RAG is about giving systems the ability to source specific data (e.g., company reports, technical manuals, or public documents) to ensure that the generated output is not only informative but also relevant to the specific context at hand. This grounding data helps improve the quality and accuracy of the generated responses, making it especially valuable for complex enterprise environments.How Does RAG Work?1. Retrieval of Relevant InformationThe first phase of RAG involves gathering relevant information from external data sources. This could include searching through: Knowledge bases and repositories Internal documents (e.g., reports, presentations, manuals) Databases or content management systems2. Pre-Processing the Retrieved DataOnce the data is retrieved, it undergoes pre-processing. This step includes tasks such as: Tokenization: Breaking down the data into smaller, digestible units that can be more easily understood by a system. Stemming: Reducing words to their root forms for better comprehension and consistency (e.g., "running" to "run"). Stop word removal: Eliminating common, non-contributory words (e.g., “and”, “the”) to streamline the dataset and focus on meaningful content. 3. Grounding After pre-processing, the relevant data is then passed into the LLM, which generates a contextual response. This phase is where the value of RAG comes into play. Instead of merely generating content based on general patterns or broad data, the LLM uses the specific, retrieved data to create highly accurate, context-aware responses that directly address the query or task at hand. By grounding the response in real, relevant data, RAG ensures that the generated content is both precise and appropriate, avoiding the potential pitfalls of incorrect or irrelevant answers.