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A magneto-responsive nanomesh biosensor for simultaneous mechanical stimulation and electrochemical detection
Use of proper orthogonal decomposition and machine learning for efficient blood flow prediction in cerebral saccular aneurysms
Suicide literacy and stigma among undergraduate students in Pokhara, Nepal: A cross-sectional study
Background Suicide is a major global public health concern, with stigma and low suicide literacy posing significant barriers to prevention and intervention. Despite increasing suicide rates and concerns about suicidal ideation, limited studies have assessed suicide stigma and literacy among young adults in Nepal. Objective This study examines suicide literacy and stigma among undergraduate students and its associated factors. Methods A cross-sectional study was conducted among 597 randomly selected undergraduate students in Pokhara Metropolitan City, Nepal, using the Literacy of Suicide Scale (LOSS-SF) and the Stigma of Suicide Scale (SOSS-SF). Descriptive statistics, independent t-tests, and ANOVA were used to analyze socio-demographic differences. Results The mean suicide literacy score was 4.83 ± 2.07, revealing significant knowledge gaps, particularly in suicide risk factors and misconceptions. Stigma levels were high, with “pathetic” (42.4%), “immoral” (41.7%), and “stupid” (40.5%) being commonly endorsed descriptors. The average scores were 23.15 (SD ± 13.12) for SOSS-stigma, 10.10 (SD ± 3.89) for glorification, and 13.12 (SD ± 4.28) for isolation/depression. Females had higher isolation (p = 0.001) and literacy scores (p = 0.023), while males exhibited greater glorification tendencies (p < 0.001). Adults (≥20 years) had significantly higher stigma, isolation, and literacy scores than adolescents (p < 0.05). Higher isolation and literacy scores were observed among students living with family (p < 0.05) and third-year students (p < 0.01). Maternal literacy and employment were associated with higher glorification scores (p < 0.05). Conclusion These findings underscore the urgent need for suicide literacy programs and stigma-reduction initiatives in Nepalese educational institutions. Addressing misconceptions and fostering help-seeking behaviors through culturally sensitive interventions could enhance suicide prevention efforts.
Thermodynamics-inspired high-entropy oxide synthesis
Abstract High-entropy oxide (HEO) thermodynamics transcend temperature-centric approaches, spanning a multidimensional landscape where oxygen chemical potential plays a decisive role. Here, we experimentally demonstrate how controlling the oxygen chemical potential coerces multivalent cations into divalent states in rock salt HEOs. We construct a preferred valence phase diagram based on thermodynamic stability and equilibrium analysis, alongside a high throughput enthalpic stability map derived from atomistic calculations leveraging machine learning interatomic potentials. We identify and synthesize seven equimolar, single-phase rock salt compositions incorporating Mn, Fe, or both, as confirmed by X-ray diffraction and fluorescence. Energy-dispersive X-ray spectroscopy confirms homogeneous cation distribution, whereas X-ray absorption fine structure analysis reveals predominantly divalent Mn and Fe states, despite their inherent multivalent tendencies. Ultimately, we introduce oxygen chemical potential overlap as a key complementary descriptor for predicting HEO stability and synthesizability. Although we focus on rock salt HEOs, our methods are chemically and structurally agnostic, providing a broadly adaptable framework for navigating HEOs thermodynamics and enabling a broader compositional range with contemporary property interest.
PM2.5 risk perception and associated with sociodemographic factors in urban Thailand
DE-HRNet: Detail enhanced high-resolution network for human pose estimation
Scale variation is a challenge in human pose estimation. The scale variations of human body are related to the accuracy and robustness of posture estimation. For example, the prediction accuracy of smaller joints (such as ankles and wrists) is less than that of larger joints (such as head and shoulders). To address the impact of scale variations across parts of the human body on the positioning of key points. In this paper, we propose a Detail Enhanced High-Resolution Network (DE-HRNet), which can efficiently extract local detail features and mitigate the impact of scale variations for human pose estimation. First, we propose a Detail Enhancement Module (DEM) to relearn the lost low-level detailed features and enhance the model’s ability to capture delicate local features, which is crucial for improving the accuracy of scale-varying keypoints. Second, we introduce an ultra-lightweight dynamic sampler - dySample, which is used to replace nearest up-sampling. It aims to reduce the loss of detail information from low-resolution features during up-sampling, while simultaneously preserving finer local representations for high resolution, it can be beneficial in improving the robustness of the model in dealing with scale-varying keypoints. On the COCO test-dev2017 and MPII valid datasets, our method achieved 75.6 AP and 90.7 PCKh@0.5, respectively, compared to High-Resolution Network (HRNet), it improved by 0.7 and 0.4 points. In comparison with the other works, the proposed method has performed well in the scale variation.
Single-strand DNA is the link between neutrophil extracellular traps and thrombin
Selective ubiquitination of drug-like small molecules by the ubiquitin ligase HUWE1
Abstract The ubiquitin system regulates eukaryotic physiology by modifying myriad substrate proteins. Substrate specificity and the assembly of ubiquitin signals are determined by ubiquitin ligases, some of which also modify non-protein biomolecules. Here we expand this substrate realm, revealing that the human ligase HUWE1 can target drug-like small molecules. We demonstrate that compounds previously reported as HUWE1 inhibitors present substrates of their target ligase. Compound ubiquitination is driven by the canonical catalytic cascade, linking ubiquitin to the compound’s primary amino group. In vitro, the modification is selectively catalyzed by HUWE1, allowing the compounds to compete with protein substrates. We establish cellular detection methods, confirming HUWE1 promotes — but does not exclusively drive — compound ubiquitination in cells. Converting the existing compounds into specific HUWE1 substrates or inhibitors thus requires enhanced specificity. More broadly, our findings open avenues for harnessing the ubiquitin system to transform exogenous small molecules into novel chemical modalities within cells.
Enhanced separation of oil in water emulsions using PVDF composite membranes reinforced with graphene oxide doped titania and silica nanoparticles
Proxies for use in biochar decay models: Hydropyrolysis, electric conductivity, and H/Corg molar ratio
Biochar is a carbon-rich material produced via pyrolysis that is increasingly recognized for its role in carbon sequestration, particularly through its application in agriculture and materials. However, accurately predicting the long-term persistence of biochar in the environment remains challenging. While incubation trials have been widely used to assess biochar degradation, their extrapolation beyond centennial timescales is uncertain. In this study, we evaluate the consistency between three physicochemical characterization methods that are considered as proxies for biochar persistence—hydropyrolysis (HyPy), solid-state electric conductivity (SEC), and elemental analysis to obtain molar hydrogen:carbon ratios. We produced 42 biochars from straw and wood using a continuously operated pilot-scale auger reactor at temperatures ranging from 400 to 800 °C under otherwise constant pyrolysis conditions. We then systematically analyzed the elemental composition, SEC and the fraction of biochar carbon that is resistant to HyPy (BCHyPy). Hydropyrolysis eliminates all free and covalently bound non-aromatic species and all aromatic species consisting of up to seven fused rings. Our results confirm that BCHyPy content increases with pyrolysis temperature and stabilizes above 600–680 °C, reaching >90% of total carbon in high-temperature biochars. Similarly, SEC increased exponentially with pyrolysis severity, correlating strongly with BCHyPy and H/C molar ratio. The latter has so far been used to predict biochar persistence. Our findings from a controlled temperature series of biochars highlight that SEC and BCHyPy could be useful proxies for parameterizing multi-pool decay models of biochars produced in practice.
Shared metabolism between a bacterial and fungal species that reside in the human gut
The fungal species Candida albicans and the bacterium Enterococcus faecalis are members of the human gut microbiome. To explore the range of interactions between these two species, we utilized dual RNA-sequencing to transcriptionally profile both C. albicans and E. faecalis during coculture (compared with monoculture controls) under two conditions: 1) an in vitro setting that mimics certain features of the gut environment and 2) a gnotobiotic mouse gut model. RNA-seq analysis revealed a large number of gene expression changes induced by one species in the presence of the other. More specifically, both species highly upregulate citrate-metabolizing genes during coculture: C. albicans upregulates CIT1 (citrate synthase) which produces citrate, while E. faecalis upregulates its cit operon, which breaks down citrate. In vitro analysis showed directly that citrate cross-feeding (production of citrate by C. albicans and breakdown by E. faecalis) enhances growth of E. faecalis . A main byproduct of citrate metabolism in E. faecalis is formate, a short chain fatty acid toxic to fungi. Our RNA profiling revealed that C. albicans upregulates three formate dehydrogenases (FDHs) during coculture; we show that the FDH genes confer a growth advantage to C. albicans when E. faecalis (or simply formate) is present. These findings reveal a metabolically driven cycle between C. albicans and E. faecalis in the mouse gut and in vitro, where cross-feeding of citrate and detoxification of formate facilitates the growth of both species when they are cultured together.
Mepolizumab alters gene regulatory networks of nasal airway type-2 and epithelial inflammation in urban children with asthma
Correction: Prediction of the functional outcome of intensive inpatient rehabilitation after stroke using machine learning methods
Improving attachment style clustering with ROCKET and CatBoost: Insights from EEG analysis
Understanding attachment styles is essential in psychology and neuroscience, yet predicting them using objective neural data remains challenging. This study explores the use of machine learning (ML) models and EEG analysis to improve attachment style classification. We analyzed EEG data from 27 university students (ages 20–35) with attachment styles categorized as secure, avoidant, anxious, or fearful-avoidant, assessed using the ECR-R questionnaire. EEG features were extracted using the ROCKET algorithm, followed by Principal Component Analysis (PCA) for dimensionality reduction. The CatBoost algorithm was used for prediction, with a two-stage data pruning approach to enhance accuracy. Our model showed a strong relationship between the number of EEG epochs and predictive accuracy, with Secure and Fearful-Avoidant attachment styles being predicted most reliably. Anxious and Avoidant styles exhibited greater variability, reflecting their complex neural signatures. These findings support the idea that attachment exists on a spectrum rather than as fixed categories, influenced by life experiences, emotional regulation, and social context. The results reinforce the dimensional nature of attachment and highlight the trade-off between model accuracy and computational efficiency. This study demonstrates the potential of ML-driven EEG analysis in predicting attachment styles, offering new possibilities for psychological assessment. By identifying overlapping neural signatures, our findings highlight attachment as a dynamic rather than static process, which could inform clinical interventions and future research on neural markers of attachment.
SHP2 genetic variants in NSML-associated RASopathies disrupt the PZR–IRX transcription factor signaling axis
Noonan syndrome with multiple lentigines (NSML) is a rare autosomal dominant disorder caused by mutations in PTPN11 (protein tyrosine phosphatase nonreceptor type 11) which encodes for the protein tyrosine phosphatase, SHP2. Approximately 85% of NSML patients develop hypertrophic cardiomyopathy (HCM). Here, we show that SHP2 is recruited to tyrosyl phosphorylated protein-zero related (PZR) in NSML mice. This recruitment is required for the Iroquois homeobox (IRX) transcription factors 3 and 5 to suppress BMP10 which negatively regulates postnatal cardiac growth. The protein expression of IRX3 and IRX5 was elevated in hypertrophied NSML hearts. IRX3 and IRX5 upregulation was rescued in NSML mice harboring a knock-in mutation of PZR that fails to become tyrosyl phosphorylated and recruit SHP2. NSML mice treated with low-dose dasatinib also exhibited normalized IRX3 and IRX5 expression levels. Consistent with this, BMP10 expression levels were reduced in NSML mice and rescued in PZR tyrosyl phosphorylation-deficient and low-dose dasatinib-treated NSML mice. A crystal structure of the tandem SH2 domains of SHP2 bound to tyrosyl phosphorylated PZR reveals that recruitment constrains the open SHP2 conformation to facilitate cellular-Src (c-Src) binding. Disruption of c-Src binding to SHP2 abolished IRX activation and failure to suppress BMP10. Hence, NSML-associated SHP2 genetic variants disrupt IRX transcription factor signaling to BMP10, implicating this axis as a target for RASopathy-associated HCM.
Nanofiber-interwoven gel membranes with tunable 3D-interconnected transport channels for efficient CO2 separation
Abstract Mixed matrix membranes (MMMs) capable of breaking the permeability-selectivity trade-off suffer from the inefficient and disconnected bulky transport channels as well as inferior interfacial compatibility between nanomaterials and polymers. Herein, we propose an original photothermal-triggered in-situ gelation approach to elaborate an original class of MMMs, termed nanofiber-interwoven gel membranes (NIGMs) that feature tunable 3D-interconnected ultrafast transport channels and highly-selective CO2-philic gel for boosting CO2 separation performance. The key design of NIGMs lies in leveraging dual functions of CNT-interwoven skeleton: (1) serving as a photothermal confined reactor that rapidly triggers in-situ gelation of highly-selective CO2-philic gel without phase separation-induced interfacial defects to construct defect-free and thickness-controllable NIGMs; (2) functioning as a 3D-interconnected continuous skeleton for providing ultrafast CO2 transport channels. By orchestrating the distribution and configuration of interwoven nanofibers, the NIGMs possess a boosted CO2 permeance of 211.0 GPU increased by 1558% over polymeric gel counterparts and an ultrahigh CO2/N2 and CO2/CH4 selectivity of up to 151 and 47 respectively. Our work offers a paradigm shift in developing advanced MMMs beyond gas separation.
Mortality risk factors in chest trauma patients in a level one trauma center in southern Iran
Research on the U-shaped relationship between marketization process and corporate capital structure: Evidence from Chinese listed companies
This paper explores the U-shaped relationship between marketization and corporate capital structure using panel data from Chinese listed firms (2012–2021). Applying fixed effects and nonlinear regressions, we find that as marketization increases, leverage first declines and then rises, confirming a robust U-shaped pattern. In early reforms, improved institutions reduce debt reliance; in advanced stages, enhanced capital markets facilitate debt access. Additionally, state-owned equity weakens this relationship, while fixed asset proportion strengthens it. The findings enrich capital structure theory under institutional transition and offer policy and strategic insights for emerging markets.
Broad neutralizing antibody response of a monomeric spike–based SARS-CoV-2 bivalent vaccine against diverse variants
severeacute respiratory syndrome coronavirus 2 (SARS-CoV-2) bivalent vaccines show potential against variants but lack a full understanding of the immunological mechanisms that drive broadly neutralizing antibodies (bnAbs). This study explored the immunogenicity of a bivalent vaccine in rhesus macaques, containing spike (S) proteins from the prototype (S prototype ) and chimeric S protein (S 1628x ). The vaccine induced bnAbs against multiple variants, including challenging subvariants like EG.1, BA.2.86, and JN.1. The monomeric S protein exposed less accessible regions within the receptor-binding domain (RBD) “inner face” and “NTD face” and subdomains 1, eliciting a diverse array of bnAbs against various Omicron subvariants. Notably, antibodies targeting the conserved RBD inner face, such as 4A5, showed potent neutralization across all tested variants. Structural analyses provide insights into the broad protectiveness of these vaccine-elicited nAbs. This study underscores the potential of bivalent vaccines with monomeric spike proteins to confer broad-spectrum immunity, offering a promising direction for future SARS-CoV-2 universal vaccine design.