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Metabologenomics-guided bioprospecting of blue amazon microbial resources toward drug discovery

Association between COMISA and cardiovascular disease: Evidence from the TURKAPNE registry

Background Comorbid insomnia and obstructive sleep apnea (COMISA) is increasingly recognized as a distinct clinical entity, yet its relationship with cardiovascular disease (CVD) remains incompletely understood. We aimed to investigate the association between COMISA and CVD in a large clinical sleep cohort. Methods Using data from the TURKAPNE registry, we analyzed 12,715 adults referred for sleep evaluation and classified participants into four mutually exclusive sleep phenotypes: neither OSA nor insomnia (n = 910), insomnia only (n = 388), OSA only (n = 8,142), and COMISA (n = 3,275). The prevalence of CVD was compared across groups. Multivariable logistic regression models were used to examine associations between COMISA and CVD after adjustment for age, sex, body mass index, education level, smoking status, airway disease, diabetes mellitus, and psychiatric comorbidity. Results The prevalence of COMISA was higher among individuals with CVD compared with those without CVD (31.6% vs. 22.7%; p < 0.001). In contrast, the distribution of insomnia alone and OSA alone showed only minor differences by CVD status. In multivariable analysis, CVD was independently associated with COMISA (odds ratio 1.108, 95% confidence interval 1.006–1.220; p = 0.038), although the magnitude of this association was modest. Female sex, diabetes, airway disease, psychiatric disease, lower educational status, and current smoking were also independently associated with COMISA. Conclusion In this large registry-based cohort, COMISA was more prevalent among individuals with CVD, supporting the concept that it represents a clinically distinct phenotype with an increased cardiometabolic burden. However, the modest effect size suggests that COMISA is influenced by a broader interplay of behavioral and metabolic factors.

A qualitative study on the experiences of health behavior decision-making and support needs among older adults with osteoporotic fractures

Development and preliminary experimental evaluation of a venturi-based slurry jet erosion test rig for comparative study of ductile and brittle materials

Slurry erosion significantly affects the durability of fluid-handling components in hydroelectric, mining, petroleum, and chemical industries. This study presents the design and preliminary laboratory-scale evaluation of a Venturi-based slurry jet erosion test rig capable of introducing dry erosive particles into a flowing liquid stream without the use of pressurised or vacuum systems. The erosion behaviour of brass (ductile) and cast iron (brittle) was investigated under varying particle sizes, slurry concentrations, and impingement angles using river sand as the erodent. Results showed maximum erosion of brass at 30° due to dominant plastic deformation, whereas cast iron exhibited peak erosion at 90° due to brittle fracture mechanisms. Kinetic energy threshold values required for erosion initiation were estimated for both materials and correlated with experimental observations. Qualitative surface morphology analysis using scanning electron microscopy supported the identification of distinct erosion mechanisms governing the ductile and brittle material responses. The developed apparatus demonstrated reasonably consistent operation and repeatable comparative erosion behaviour under the selected experimental conditions, indicating its suitability for controlled slurry erosion testing and comparative evaluation of ductile and brittle engineering materials without the need for pressurised particle delivery systems.

Second-order analysis for high strength steel frame design accounting for strain harder effect and local buckling

Crystal structure of a closed ternary complex of a HNA Reverse Transcriptase in complex with a HNA/DNA duplex

1,5-Anhydrohexitol nucleic acid (HNA) is a promising xeno nucleic acid (XNA) for applications such as aptamers and catalysts, due to its favourable physico-chemical properties. Realizing this potential requires efficient and high-fidelity polymerases capable of processing HNA. A key component are HNA reverse transcriptases that convert HNA into DNA, an essential step in standard SELEX workflows. Although HNA reverse transcriptases have been generated by directed evolution, structural insight is essential to guide further enzyme engineering. Here, we report the 2.8 Å crystal structure of the engineered HNA reverse transcriptase KOD-H4, derived from the B-family DNA polymerase of Thermococcus kodakarensis , captured in a closed ternary complex with dATP, a 3’-terminated primer and a mixed HNA/DNA template. Compared to a previously reported open ternary KOD-H4 structure, the presented structure adopts a more closed conformation with increased finger and thumb domain closure and formation of a canonical Watson–Crick–Franklin base pair at the insertion site. Direct downstream nucleotides show more distorted base pairing and one HNA residue transits from the unusual 1 C 4 conformation it adopted in the open complex to the 4 C 1 hexitol sugar conformation. These findings demonstrate that KOD-H4 can form a closed, pre-catalytic complex resembling that of the wildtype enzyme with natural substrates, and reveal state-dependent conformational flexibility of HNA. Such flexibility should be considered in the design and optimization of enzymes that process HNA.

Categorization-driven perceptual learning changes perceived similarity in the naturalistic domain of skin lesion diagnosis

Abstract Prior work suggests that category learning can reshape perception by shifting perceived similarity among instances. Most evidence comes from artificial stimuli and small category sets. We examined perceptual change in a complex, real-world task: classifying benign and cancerous skin lesions. Medically naive participants rated pairwise similarity among instances from 10 categories before and after comparison-based training with > 500 examples. Training increased perceived similarity for same-category pairs (within-category compression) and decreased it for different-category pairs (between-category expansion). The magnitude of perceptual change predicted generalization to novel instances: greater compression was associated with higher post-training accuracy, and greater expansion with lower false-alarm rates. A label-overlap manipulation showed no differential change, arguing against strategic label retrieval. These findings indicate that perceptual learning systematically reshapes category representations and perceptual experience—promoting within-category compression and between-category expansion—in a challenging, naturally structured domain.

DiSCoKit: An open-source toolkit for deploying live LLM experiences in survey research

In scientific studies of human-AI interaction dynamics, researchers often need to present participants with opportunities to interact with live large-language models (LLMs). However, technical and practical challenges (from survey platform limitations and logging chat data to manipulating AI behaviors for experimental designs) often inhibit survey-based deployment of AI stimuli. We developed DiSCoKit—an open-source toolkit for deploying live LLM experiences (e.g., ones based on models delivered through Microsoft Azure portal) through JavaScript-enabled survey platforms (e.g., Qualtrics). We describe the toolkit’s scientific motivation, architecture, and operation. We also offer an example of toolkit deployment and customization, along with discussing its possibilities and limitations. Altogether, DiSCoKit gives researchers a flexible, secure, scalable solution for deploying naturalistic LLM stimulus experiences through online surveys.

FakeDiverse a curated multi-source news corpus for context-aware fake news detection using BERT and DeBERTa

Abstract The rapid growth of online media has accelerated the circulation of misinformation, posing serious risks to public trust, social stability, and democratic processes. Detecting fake news remains a challenging task, particularly because traditional machine learning approaches such as Support Vector Machines and Naïve Bayes rely on shallow linguistic cues and often fail to recognize sarcasm, implicit tone, or evolving writing styles. Earlier deep learning models, including CNNs and LSTMs, provide modest improvements but continue to struggle with long text and shifting topical contexts. This study examines the effectiveness of two transformer-based architectures—BERT and DeBERTa—for identifying fake news using only textual information from headlines and article bodies. To enhance generalization, news articles from ten publicly available datasets are consolidated into a single corpus namely FakeDiverse, that exposes the models to a broader spectrum of linguistic patterns. MinHash similarity along with Locality Sensitive Hashing algorithm has been employed to evaluate the lexical redundancy within the FakeDiverse corpus as a post hoc analysis. Class imbalance between real and fake news is addressed through a weighted cross-entropy loss function, ensuring that minority-class instances are adequately represented during training. FakeDiverse dataset is split in the ratio of 80:20 for training and testing, and subsequently the models BERT and DeBERTA are trained on the training set and evaluated using the test sets. Experimental results demonstrate that both the models capture contextual nuances effectively, with BERT achieving 98% accuracy and DeBERTa reaching 99%. The findings demonstrate that BERT and DeBERTa achieves strong performance on FakeDiverse corpus, and cross-dataset evaluation shows that models have challenges to generalize unseen data distribution thereby highlighting the need for enhanced generalization strategies as well as domain adaptation.

It would be really great if I had greater confidence and ability there: Understanding the primary care physician experience with nutrition in training, clinical practice, and interprofessional collaboration

Background Primary care physicians (PCPs) are on the front lines of health promotion and disease prevention, yet evidence supports a longstanding gap in physicians’ capacity to counsel about diet, a key factor in patient health and chronic disease risk. Momentum to address the nutrition training needs of physicians is growing; however, challenges PCPs experience due to inadequate training are further complicated by clinical practice barriers. This study seeks to better understand the complex problem PCPs face addressing nutrition with patients to inform potential solutions. Methods and findings This qualitative study takes a design thinking approach to understanding the problem by learning from PCPs about their experience, challenges, and priorities addressing nutrition with patients. Findings from semi-structured interviews with 32 PCPs revealed that while they value nutrition and believe they have an important role in addressing diet with patients, their role as a generalist in addressing nutrition lacks clarity. PCPs describe learning their current approach to nutrition primarily outside of formal medical training, resulting in variability and inconsistency in approaches and recommendations and general frustrations about their ability to give actionable guidance. While registered dietitians (RDs) are often viewed as valuable support for patients, PCPs describe multiple challenges to RD utilization and subsequently at times may be the only ones with the opportunity to address diet with patients. Additional system- and societal-level barriers, such as time limitations and the food environment, further complicate PCPs’ experiences advising patients about nutrition. Main limitations of this study are limited generalizability from recruiting graduates of a single medical school and PCPs with greater interest in nutrition or more frustration with their current approach to nutrition may have been more likely to participate. Conclusions Our results support the need to clearly define a realistic role for PCPs as generalists addressing nutrition. Clarified expectations in turn can inform nutrition training of physicians and guiding frameworks and strategies for giving practical, evidence-based nutrition guidance. PCPs also need increased support through access to resources, strategies to improve RD collaboration, and attention to system- and societal-level challenges influencing dietary interventions in primary care.

Overcoming the data desert: generative AI techniques for synthesising anonymised deployment logs in regulated public sectors

Bacterial vaginosis in early pregnancy and birth outcomes: Evidence from a prospective cohort in the middle belt of Ghana

Background Bacterial vaginosis (BV) is highly prevalent in women of African origin and has been associated with adverse birth outcomes (ABO), particularly preterm birth (PTB). However, evidence from sub-Saharan Africa remains limited, and while a previous study conducted in this area examined the prevalence of BV, its impact on pregnancy outcomes was not assessed. This study assessed the prevalence and risk factors of BV in early pregnancy and examined its association with ABO in the middle belt of Ghana. Methods This analysis was nested within a prospective cohort of pregnant women in the Kintampo North Municipality and Kintampo South District. Pregnant women <20 weeks’ gestational age were screened, consented, enrolled and followed through delivery until one year after birth. At enrolment, sociodemographic, behavioural, and obstetric data were collected, along with biological samples, including vaginal swabs for Gram staining and Nugent scoring. BV status was categorized as BV-negative (0–6) or BV-positive (7–10) and ABO included PTB (<37 weeks), low birthweight (LBW < 2.5 kg), and foetal loss. Data were double-entered in REDCap and analysed in R. Associations between BV and ABO were assessed using chi-square tests, and logistic regression was used to identify risk factors for BV. Results Of 1,180 pregnant women enrolled, 355 (30.1%) were BV-positive. PTB (9.9% vs. 8.7%; p = 0.50), LBW (13.8% vs. 12.0%; p = 0.39), and foetal loss (4.5% vs. 2.8%; p = 0.14) were all higher among BV-positive women, but none reached statistical significance. Younger age and unmarried status were associated with BV. Unmarried women (AOR 1.63; 95% CI: 1.20–2.22) and those reporting one sexual encounter per week (AOR 1.55; 95% CI: 1.01–2.37) had increased odds of BV. Conclusions BV is highly prevalent in early pregnancy in this Ghanaian cohort, particularly among younger and unmarried women, but was not significantly associated with ABO. Targeted screening among high-risk groups is necessary, and future molecular approaches may better characterise BV subtypes linked to ABO in African settings.

Design and development of 19-DOF responsive SMA-based exoskeleton for rehabilitation

Concordant RNA-protein evidence and human tissue metabolomics prioritize UPP1-associated nucleotide remodeling in prostate cancer

Prostate cancer (PCa) is characterized by molecular heterogeneity and metabolic reprogramming, but the relationships among transcriptomic, proteomic, and metabolic signals remain incompletely defined. Here, we present a human-centered, cross-dataset analysis of public RNA, protein, and metabolomics data in PCa. We analyzed RNA and protein profiles from PC3 parental and drug-resistant cells together with an independent human matched tissue metabolomics dataset from Metabolomics Workbench (ST000784). RNA-protein overlap analysis identified seven genes that were significant at both layers, including five concordantly upregulated genes: UPP1 , IGF2R , FLNC , DSP , and PLEC . Among these, UPP1 provided the most direct metabolic interpretation because it encodes uridine phosphorylase 1, an enzyme linked to pyrimidine salvage. Independent ST000784 matched prostate tissue metabolomics supported broader nucleotide metabolism remodeling, including significant changes in N-carbamoyl-L-aspartate, guanosine monophosphate, and adenosine 3,5-cyclic monophosphate. In contrast, uracil was not significantly altered and uridine 5’-monophosphate showed only a trend after multiple-testing correction. Repeated stratified cross-validation showed that UPP1-containing candidate gene sets achieved high within-layer AUC values in RNA and protein data, while nested statistical benchmark models also performed strongly. These results prioritize a UPP1-associated nucleotide remodeling hypothesis in PCa, but do not establish causal regulation of metabolite abundance or clinical diagnostic utility. Future matched multi-omics and perturbation experiments are required.

Understanding the Markov decision process for reinforcement learning in robotics perception

A cross-domain deep learning framework for remaining useful life prediction in industrial applications

Accurate prediction of Remaining Useful Life (RUL) is critical for predictive maintenance and minimizing downtime in industrial systems. This paper presents a cross-domain deep learning framework based on a hybrid Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN–BiLSTM) architecture. Unlike domain-specific models that require handcrafted features, the proposed framework extracts local degradation features through CNN layers and captures long-term dependencies via BiLSTM networks. The model is evaluated on three heterogeneous datasets: construction machinery, continuous casting machines, and lithium-ion batteries. Experimental results show that CNN–BiLSTM consistently outperforms baselines, achieving up to 22% lower RMSE compared to GRU and 30–50% lower RMSE compared to traditional models. On the construction dataset, it achieves an MAE of 48.2 hours and RMSE of 67.1 hours ( R 2  = 0.88), outperforming GRU by 20%. For the casting dataset, the model attains an MAE of 87.6 tons and RMSE of 113.9 tons ( R 2  = 0.87), surpassing Random Forest by over 35%. On the battery dataset, CNN–BiLSTM reduces the MAE to 49.6 cycles and RMSE to 72.8 cycles ( R 2  = 0.89), while also achieving the lowest Timeliness Score (27.5) and PHM08 Score (192.4). Cross-domain experiments are evaluated under two settings: zero-shot transfer, where the model is trained on one source domain and directly tested on a different target domain without using labeled target-domain samples, and fine-tuned transfer, where 20% of labeled target-domain samples are used to update only the fully connected layers while keeping the CNN and BiLSTM layers frozen. The zero-shot results reflect the effect of domain shift, while the fine-tuned results show that lightweight transfer adaptation reduces RMSE by 25–40% across domains. These findings indicate cross-domain adaptability under limited target-domain supervision rather than fully unsupervised cross-domain generalization. These results highlight the feasibility of a unified CNN–BiLSTM framework for scalable, cross-domain RUL estimation and its suitability for real-world prognostic applications.

The analgesic effect of ultrasound-guided fascia hydrorelease around the artery for myofascial neck pain: a prospective single-arm interventional study

Myofascial pain syndrome (MPS) is a major cause of chronic neck pain, with tissue ischemia implicated as a contributing factor. This prospective, single-arm interventional study evaluated the analgesic effect of ultrasound-guided fascia hydrorelease (US-FHR) performed around arteries supplying the neck in patients with chronic neck MPS. Thirteen adults (median age 53.0 years; 38.5% female) underwent US-FHR targeting the perivascular fascia of either the transverse cervical or dorsal scapular artery using 2 mL of normal saline. Pain intensity was assessed by visual analog scale (VAS) at rest and during movement; disability by the 5-item Pain Disability Index, Japanese version (PDI-5-J); and arterial blood flow volume before and after the procedure. The primary outcome, pain VAS during movement, decreased from 49.0 mm (interquartile range [IQR], 44.5–64.0) at baseline to 22.0 mm (IQR, 14.5–31.5) at 15 min and 22.0 mm (IQR, 14.0–34.0) at 1 week (Hodges-Lehmann median difference, 30.5 mm [95% CI, 24.5 to 36.5] and 28.5 mm [95% CI, 18.5 to 37.0]; both P < 0.001). Pain VAS at rest improved from 21.0 mm (IQR, 13.0–43.5) to 8.0 mm at 15 min and 1 week (median difference, 14.5 mm [95% CI, 9.0 to 24.0; P = 0.001] and 13.5 mm [95% CI, 6.0 to 21.0; P = 0.007]). PDI-5-J decreased from 17.0 (IQR, 10.5–23.0) to 13.0 (IQR, 4.0–17.5) at 1 week (median difference, 5 [95% CI, 2–8; P = 0.004]). Blood flow volume increased from 11.2 mL/min (IQR, 4.5–14.4) to 17.2 mL/min (IQR, 6.1–23.7) immediately after US-FHR (median difference, + 4.1 mL/min [95% CI, + 2.5 to +8.9; P = 0.001]), although transient. One patient experienced transient bleeding that was promptly controlled. In this single-arm feasibility study, US-FHR around the target artery was simple and safe to perform and was associated with reduced neck pain. Because the study lacked a control group, these preliminary findings should be regarded as hypothesis-generating and require confirmation in controlled trials; they may also inform the future evaluation of MPS in other anatomical regions. Trial registration: UMIN Clinical Trials Registry, UMIN000053612.

Functional node layout in Metroidvania game worlds: A complex network analysis

This study investigates how the spatial structure of Metroidvania game worlds relates to the layout of key functional nodes. Using Hollow Knight, Prince of Persia: The Lost Crown, and Blasphemous 2 as case studies, the maps were transformed into graph structures based on spatial data compiled from gameplay observation, in-game maps, community maps, and verification through gameplay videos. On the basis of this graph representation, the study adapts the Nearest Neighbor Index by replacing Euclidean distance with network shortest-path distance in order to evaluate the distribution patterns of save points, teleport points, and boss points. It further employs multi-source k-hop reachability analysis to measure service coverage and redundancy. Finally, closeness centrality and betweenness centrality are calculated on the full network, and Spearman rank correlation is used to test the association between functional areas and centrality. The results reveal clear differences in the structural roles of functional nodes across the three games. In Hollow Knight and The Lost Crown, save points are relatively dispersed, weakly coupled with centrality, and function as a distributed safety net. In Blasphemous 2, save points exhibit higher small-radius coverage and redundancy and are more strongly aligned with central positions, indicating a hub-like stronghold structure. Teleport systems likewise reflect different design strategies, ranging from exploration-oriented sparse layouts to later-stage mobility optimization. Boss points in all three games generally remain structurally isolated, showing low overlap and weak centrality association. These findings suggest that differences in the placement of save points, teleport points, and boss points reflect distinct structural design strategies, and that network analysis can provide a quantitative basis for evaluating and optimizing such layouts in level design.

Fecal carriage of ESBL and Carbapenemase-producing Enterobacteriaceae, and its associated factors among hospital and non-hospital janitors at the University of Gondar, Northwest Ethiopia: A comparative cross-sectional study

Background Extended-spectrum beta-lactamase (ESBL) and carbapenemase-producing Enterobacteriaceae (CPE) pose a critical public health threat. Janitors are routinely exposed to contaminated environments and may act as a reservoir for these resistant bacteria, particularly in resource-limited settings like Ethiopia, where data on this subject are scarce. Objective The aim of this study was to assess fecal carriage rates of ESBL-PE, CPE and its associated factors among hospital and non-hospital janitors at the University of Gondar (UoG), Northwest Ethiopia. Methods A comparative cross-sectional study was conducted from June 15 to September 25, 2025, at the UoG. A total of 385 janitors (203 hospital and 182 non-hospital) were selected using stratified and simple random sampling techniques. Data on socio-demographic and associated factors were collected using a semi-structured questionnaire. Stool samples were collected aseptically and cultured on MacConkey agar. Antimicrobial resistance (AMR) patterns were determined by the Kirby-Bauer disk diffusion method following Clinical and Laboratory Standards Institute (CLSI) 2024 guidelines. The ESBL and carbapenemase production were confirmed using the combination disk and modified Carbapenem inactivation methods, respectively. Quality control was ensured by using standard reference strains. Data analysis was performed using SPSS version 27.0, employing chi-square tests and logistic regression. A p -value of <0.05 was considered statistically significant. Result Among the 385 stool samples, a total of 416 Enterobacteriaceae isolates were recovered, 229 from hospital janitors and 187 from non-hospital janitors. The overall fecal carriage rates among janitors were 83 (21.6%) for ESBL-PE and 14 (3.6%) for CPE. Hospital janitors had significantly higher carriage rate than non-hospital janitors for both ESBL-PE (28.6% vs. 13.7%, p  < 0.001) and CPE (5.9% vs. 1.1%, p  = 0.012), respectively. Escherichia coli was the predominant ESBL-producer. Significant risk factors identified for ESBL-PE colonization included lack of hand hygiene at home, history of antibiotic use, and urinary tract infection for hospital janitors, and age ≥ 40 years and history of non-prescription antibiotic use were for non-hospital janitors. Conclusion and recommendations This high carriage rates of ESBL-PE and CPE, identify janitors as a significant reservoir for resistant bacteria. We recommend integrating janitors into national AMR surveillance programs and strengthening infection prevention and control and antimicrobial stewardship training.

Catastrophe mechanism and early warning indicators of seepage erosion-induced water inrush in karst cavities

Seepage-erosion-induced water inrush in karst cavities is a typical form of water-inrush disaster in karst tunnels. It is governed not only by the spatial distribution of karst cavities and hydraulic recharge conditions, but also by the particle-size gradation and composition of the cavity fill. During seepage erosion, fill particles are progressively transported by flowing water, which may trigger a sudden water-inrush catastrophe. To reveal the catastrophe mechanism and establish early-warning indicators, this study employs the Smoothed Particle Hydrodynamics (SPH) method to simulate the evolution of seepage-erosion-induced water inrush under different particle-size gradations, cavity confining stresses, and seepage velocities. The inflection point of the cumulative particle loss rate is used as an indicator of catastrophic transition. The relationships among particle-size gradation, confining stress, seepage velocity, and particle loss rate at the transition point are then analyzed to determine early-warning thresholds. The results show that fill-particle loss is positively correlated with both seepage velocity and confining stress. When the content of fine particles, such as rock cuttings and fine sand, exceeds 60%, the inflection point corresponds to a seepage velocity of 1.6 m/s and a confining stress of 2.6 MPa, with an early-warning particle-loss range of 8%−15%. When the content of coarse particles, such as coarse sand and gravel, exceeds 40%, the inflection point corresponds to a seepage velocity of 3.0 m/s and a confining stress of 4.5 MPa, with an early-warning particle-loss threshold of approximately 45%.