Browse Articles

A high-performance hydrogel platform enabling dual anti-miR-21 and TGF-β1 delivery to improve arterial plaque stability and enhance therapeutic angiogenesis outcomes

Dupilumab attenuates the expression of TSLP and IL-8 induced by dsRNA and IL-4/IL-13 co-stimulation in human small airway epithelial cells

Background The interaction between viral components and type 1 or type 2 cytokines during asthma exacerbations in the airway epithelium may contribute to worsening inflammation. However, these interactions in the small airway epithelium—particularly those involving alarmins (TSLP, IL-25, and IL-33) and IL-8—remain unclear. Dupilumab, a biologic agent used in severe asthma, blocks IL-4 receptor alpha (IL-4Rα) and may offer therapeutic benefits in virus-induced asthma exacerbations. In this study, we evaluate the effects of double-stranded RNA (dsRNA), in combination with various cytokines and dupilumab, on the Human Small Airway Epithelial Cells (HSAECs) line. Methods Primary HSAECs were preincubated with dsRNA to induce the gene and protein expression of alarmins and IL-8. To evaluate the effects of cytokines on dsRNA-induced alarmin and IL-8 expression, various type 1 and type 2 cytokines were co-stimulated with dsRNA. Dupilumab was used as a pretreatment prior to co-stimulation with dsRNA and IL-4 or IL-13. Gene expression of TSLP, IL-25, IL-33, and IL-8 was assessed by quantitative PCR, and protein expression was evaluated by Western Blotting. Results dsRNA significantly increased the expression of TSLP and IL-8. IL-4 and IL-13 further enhanced dsRNA-induced TSLP and IL-8 gene and protein expression. In contrast, TNF-α reduced dsRNA-induced TSLP expression but enhanced IL-8 gene and protein expression. Dupilumab attenuated the expression of TSLP and IL-8 induced by co-stimulation with dsRNA and IL-4 or IL-13 in HSAECs. Conclusion In the microenvironment of small airway epithelial cells, particularly during viral infections, the presence of IL-4 or IL-13 may enhance the expression of TSLP and IL-8. Dupilumab attenuates this expression, potentially offering additional benefits in the treatment of asthma, especially during virus-induced asthma exacerbations.

Climate policy portfolios that accelerate emission reductions

Abstract The corpus of national climate policies continues to grow - but to what effect? Using data on 3,917 policy instruments across 43 OECD countries and major emerging economies from 2000-2022, we show that national climate policy portfolios specializing in instrument types and sectors are associated with faster reductions in fossil CO 2 emission intensity. Supported by exemplar country case studies, we also provide quantitative evidence that the effectiveness of climate policy is amplified by long-term emission reduction targets and the presence of dedicated governmental bodies including ministries and intergovernmental organisations. The cumulative effect of all climate policy portfolios over our study period amounts to 3.1 GtCO 2 fewer emissions in 2022 relative to a no-policy counterfactual - substantially less than what’s needed to stay on track for the Paris Agreement goals.

Peripheral and central auditory dysfunction in tinnitus with clinically normal hearing

Abstract Tinnitus is the perception of ringing in the ear without an external source and occurs even in individuals with clinically normal hearing thresholds. This suggests there may be an undetected auditory dysfunction present. Two main mechanisms that could explain this phenomenon are ultra-high frequency hearing loss (> 8 kHz) and cochlear synaptopathy, which can disrupt both peripheral and central auditory processing. While ultrahigh frequency (UHF) audiometry is increasingly used in tinnitus assessment, the study aims to bridge the gap by systematic integration of measures of central auditory processing (TFS-AF and AMD) with clinically valid peripheral assessment (UHF) to characterise both peripheral and central deficits in tinnitus with normal hearing. The case-control study compared 28 patients with tinnitus and 28 age- and gender-matched controls. The individuals with tinnitus were assessed for tinnitus severity using the Tinnitus Functional Index (TFI). The measures included UHF audiometry (9–20 kHz), TFS-AF, and AMD tasks. The diagnostic accuracy was evaluated using the Receiver Operating Characteristic (ROC) curve, along with regression and Bland-Altman analyses. Tinnitus individuals differed across all measures (TFS-AF, AMD, and UHF) from the control group. indicating a disrupted temporal processing ability. Bland-Altman plots revealed systematic biases: TFS-AF values were consistently higher than UHF thresholds, while AMD scores were lower. UHF audiometry demonstrated superior diagnostic accuracy in classifying individuals with normal hearing who have tinnitus (96.43%). In terms of clinical utility, UHF may offer higher sensitivity in detecting tinnitus in individuals with normal hearing. Systemic biases between measures suggest the presence of independent peripheral/central deficits in individuals with normal hearing who have tinnitus.

GC-MS based bioactive profiling of Phyllanthus niruri and its antibacterial potential through experimental and computational studies

Objective The study aimed to evaluate the antibacterial potential of Phyllanthus niruri by identifying its bioactive compounds through GC–MS, assessing their in vitro antibacterial efficacy, and validating their interactions with bacterial target proteins through molecular docking and pharmacokinetic analyses. Methods Methanolic extracts were prepared and fractionated into petroleum ether (PSF), chloroform (CSF), carbon tetrachloride (CTF), ethyl acetate (ESF), methanol (MSF), and aqueous (AQF) fractions using the Kupchan method. Phytochemical screening, total phenolic content (TPC), and total flavonoid content (TFC) were determined spectrophotometrically. GC–MS analysis identified volatile constituents in the methanol extract. Antibacterial activity was evaluated against nine bacterial strains using the disc diffusion assay, Minimum Inhibitory Concentration (MIC), and Minimum Bactericidal Concentration (MBC) tests. Molecular docking (PyRx), ADMET (pkCSM), and drug-likeness (SwissADME) analyses were performed to assess pharmacological suitability. Results Phytochemical screening confirmed the presence of major secondary metabolites such as flavonoids, tannins, and phenolics. The methanol fraction (MSF) exhibited the highest TPC (119.10 ± 0.11 µg GAE/g) and TFC (128.01 ± 0.11 µg QE/g), followed by the ethyl acetate fraction (TPC = 102.06 ± 0.11 µg GAE/g; TFC = 109.09 ± 0.21 µg QE/g). GC–MS profiling revealed 75 compounds, including 3,4-dimethoxy-dl-phenylalanine (13.24 µg/mL), benzeneacetamide (3,4-dimethoxy-, 13.24 µg/mL), and 3-(3,4-dimethoxyphenyl)-propionic acid (13.24 µg/mL). In vitro assays demonstrated that the methanolic and ethyl acetate fractions exhibited the strongest antibacterial activity, with inhibition zones of 33.2 ± 0.96 mm and 15.1 ± 0.52 mm against Escherichia coli and Staphylococcus aureus , respectively. MIC values ranged from 62.5 µg/mL to 250 µg/mL, and MBC/MIC ratios ≤ 4 confirmed potent bactericidal activity. Molecular docking revealed strong ligand protein affinities, with benzeneacetamide (–9.4 kcal/mol) and 3-(3,4-dimethoxyphenyl)-propionic acid (–8.7 kcal/mol) showing the highest binding energies toward DNA gyrase and penicillin-binding protein 1B (PBP1B). ADMET and SwissADME analyses indicated favorable gastrointestinal absorption, no hepatotoxicity, and compliance with Lipinski’s rule of five. Conclusion Phyllanthus niruri , particularly its polar fractions, possesses potent antibacterial phytochemicals validated through GC–MS, in vitro , and in silico studies. These findings establish its potential as a promising natural source for the development of novel antimicrobial drugs.

Stress vesicles link epidermal mechanotransduction to stem cell differentiation

Cytoplasmic TDP-43 leads to early behavioral impairments without neurodegeneration in a serotonergic neuron-specific C. elegans model

Cardiovascular risk among middle-aged Japanese adults with atopic dermatitis: A nested case–control study

Background and objective The increasing prevalence of atopic dermatitis (AD) has raised concerns about whether individuals with AD require specific cardiovascular disease (CVD) prevention strategies. This study investigated the association between AD and CVD among middle-aged adults. Methods We conducted a nested case–control study using data from the Kyoto Claim Database (April 2013–March 2023) among individuals aged 40–59 years who were followed for ≥ 3 years. Cases were patients with first-onset CVD (hospitalization for ischemic heart disease or stroke), whereas controls had no history of CVD. AD was defined by an ICD-10 code (L20) plus a topical corticosteroid (TCS) prescription. For each case, 10 controls were matched on age, sex, index month, hypertension, diabetes, dyslipidemia, hyperuricemia, and use of anticoagulant or antiplatelet agents. Logistic regression was used to assess associations between CVD and AD prevalence or severity. Results We identified 2,757 CVD cases, including 1,247 with ischemic heart disease and 1,563 with stroke (median age 53 years [interquartile range, 49–56]; 2,031 [73.7%] male). Comorbidities included hypertension in 1,430 (51.9%), diabetes in 583 (21.1%), dyslipidemia in 1,018 (36.9%), hyperuricemia in 307 (11.1%), and anticoagulant or antiplatelet prescriptions in 377 (13.7%). The median follow-up period was 60 months. After matching, 2,672 cases and 26,720 controls were compared. AD was diagnosed in 66 cases (2.5%) and 728 controls (2.7%), with no significant association between AD and CVD (odds ratio [OR], 0.90; 95% confidence interval, 0.69–1.16). Regarding AD severity, 3 cases (0.1%) and 76 controls (0.3%) were in the top 10% of average monthly TCS dose (≥37.8 g/month); 28 cases (1.0%) and 352 controls (1.3%) received class 1 TCS; and 14 cases (0.5%) and 144 controls (0.5%) received systemic treatment (immunosuppressants or biologics). AD severity was not associated with CVD risk (ORs: 0.39 [0.10–1.05], 0.79 [0.53–1.15], and 0.97 [0.53–1.62], respectively). A limitation of this study was potential misclassification of AD status due to the nature of claims data. Conclusion Among adults aged 40–59 years, AD was not significantly associated with an increased risk of CVD onset, even in severe cases. Targeted CVD screening for patients with AD may not be necessary; however, comprehensive management of standard CVD risk factors remains essential, as in the general population.

Spatial heterogeneity and subtypes of functional connectivity development in youth

Hydrothermal carbonization derived hydrochar from industrial waste as an efficient adsorbent for toxic dye removal and process optimization

Stress hyperglycemia ratio predicts adverse outcomes in emergency department patients with upper gastrointestinal bleeding

Introduction Upper gastrointestinal bleeding (UGIB) is a common emergency condition with substantial morbidity. Early identification of patients at risk for adverse outcomes is essential for timely management. The stress hyperglycemia ratio (SHR) adjusts admission glucose for baseline glycemic control and may better reflect acute physiological stress than absolute glucose levels. We aimed to determine whether SHR predicts critical outcomes in emergency department (ED) patients with UGIB. Methods We retrospectively analyzed 345 adults with endoscopically confirmed UGIB at a tertiary medical center. SHR was computed as admission glucose divided by estimated average glucose from hemoglobin A1c. Multivariable logistic regression assessed associations between SHR and outcomes: intensive care unit (ICU) admission, blood transfusion, rebleeding, acute kidney injury (AKI), acute respiratory failure (ARF), in-hospital mortality, procedural intervention, and esophageal variceal (EV) bleeding. Predictive performance was compared with the complete Rockall score (CRS) and Glasgow-Blatchford score using receiver operating characteristic curves. Results Elevated SHR was independently associated with higher risks of ICU admission (adjusted odds ratio [aOR] = 2.10, P < 0.001), transfusion (aOR = 6.30, P < 0.001), rebleeding (aOR = 1.75, P = 0.04), AKI (aOR = 1.79, P < 0.001), and ARF (aOR = 1.96, P = 0.01). SHR moderately predicted transfusion (area under the curve [AUC] = 0.716) and ICU admission (AUC = 0.637), outperforming the CRS for both. Adding SHR to CRS improved transfusion prediction (ΔAUC = 7.2%, P = 0.02). Patients with SHR > 1.9 had significantly higher rates of ICU admission, transfusion, organ dysfunction, and EV bleeding. SHR remained predictive in both diabetic and nondiabetic subgroups. No significant association was observed between SHR and mortality or procedural intervention. Conclusion SHR was independently associated with adverse outcomes in UGIB, especially ICU admission and transfusion. As a simple, rapidly available marker that adjusts for baseline glycemic control, it may complement existing risk scores and support early, pre-endoscopic risk stratification in the ED, and warrants validation in prospective studies.

Author Correction: Tectonic–astronomical interactions in shaping late Paleozoic climate and organic carbon burial

Computation of topological relations with 3-SRM

Abstract Topological relation models are fundamental to spatial databases and GIS, providing a basis for reasoning about how spatial objects relate. Existing binary frameworks such as RCC-8 and the 9-Intersection Model effectively describe relations between two regions but cannot capture the global structure of configurations involving three spatial entities. To overcome this limitation, we propose a formally defined ternary intersection calculus, the Three-Simple-Region Model (3-SRM), for computing topological relations among three simple regions in 2D space. The model is constructed on the basis of three 3x3 matrices $$9I_A$$ , $$9I_B$$ , and $$9I_C$$ . The configuration of $$9I_A$$ , $$9I_B$$ , and $$9I_C$$ results in a total of 16 topological relations. The identified topological relations in 2D space among three spatial regions are disjoint, meet, covers, covered-by, equal, contain, inside, overlap, between, in-between, outer, inner, meet-inside, inside-meet, exterior meet, and boundary exterior meet. The model characterizes each triadic relation by rigorously evaluating the emptiness patterns of all interior–boundary–exterior intersections among the three regions, providing a natural extension of traditional binary frameworks while maintaining their fundamental topological semantics.

LOTUS: A low-cost time-lapse automated imaging system for spatio-temporal analysis of microbial colony or biofilm development

The proliferation of low-cost single-board computers and 3D printers has considerably accelerated open science. In the life sciences, for both research and educational purposes, there is a growing trend to develop affordable imaging systems rather than purchasing specialized commercial instruments. However, existing solutions often lack diversity of imaging modes or adequate throughput. To fill this gap, we developed LOTUS, a low-cost (~$550 USD) automated imaging system built from 3-D printed components that integrates motorized sample positioning with interchangeable light-emitting diodes (LED) sources and optical filters for spatio-temporal analysis of microbial colony or biofilm development. LOTUS images up to nine samples at fixed time intervals (e.g., 20 min) in four modes: bright-field transillumination (biomass), bright-field epi-illumination (morphology), and dual-color epi-fluorescence (gene expression or other types of reporter analysis). Validation experiments demonstrated stable and reproducible timing and positioning accuracy over 3 days and homogeneity of LED illumination and captured images enabling semi-quantitative analysis. We demonstrated LOTUS capabilities by imaging E. coli biofilms expressing fluorescent reporter proteins (GFPmut2 and mCherry) over 5 days and tracking fluorescence intensity dynamics following sub-MIC ampicillin treatment. LOTUS represents a versatile and cost-effective semi-quantitative platform for parallel monitoring of colony or biofilm development and fluorescent reporter expression pattern. This open-source system makes automated time-lapse live imaging accessible for research and educational applications.

Meta-amplified dark-field interferometric scattering microscopy

Abstract Label-free optical detection of nanometer-scale bioparticles is highly desirable for noninvasive biological studies but challenging due to the weak scattering signals that are difficult to distinguish from the illumination background. Interferometric scattering microscopy (iSCAT) has enabled high-sensitivity imaging by detecting the interference between the particle’s scattered light and a reference beam. However, enhancing the detection sensitivity and the image contrast for small particles continues to be a challenge in iSCAT. Here, we introduce meta-amplified dark-field interferometric scattering microscopy (MAD-iSCAT), which leverages a plasmonic metasurface to drastically enhance nanoparticle detection sensitivity in iSCAT. By employing a metasurface comprising sub-diffraction plasmonic meta-atom arrays, MAD-iSCAT generates bright radiation modes that intensely scatter light toward the far field in the presence of a detection nanoparticle, substantially amplifying the sensitivity. In the absence of a nanoparticle, the metasurface produces minimal background due to the dark collective mode, resulting in improved image contrast. We present a theoretical analysis of amplified interferometric imaging using designed metasurfaces and experimentally demonstrate enhancements in contrast and signal-to-noise ratio for detecting dielectric nanoparticles, exosomes, and proteins. Our approach offers broad applications in label-free biosensing and optical mass spectrometry, enabling significantly improved throughput and sensitivity.

The impact of exercise self-efficacy, self-esteem and physical activity on body fat percentage changes in adolescents during fat loss interventions

Abstract The prevalence of obesity among adolescents poses significant health threats. This study examines the predictive influence of self-efficacy (ESE), self-esteem (SE), and moderate-to-vigorous physical activity (MVPA) on the effectiveness of interventions aimed at reducing body fat percentage (BFP) among adolescents. A total of 100 adolescents were randomly assigned to the intervention group (IG) or the control group (CG). Baseline assessments measuring body composition, psychological indicators, and physical activity levels were conducted prior to the intervention. Intervention effects and group differences were evaluated using t-tests. Hierarchical regression models were constructed, using post-intervention BFP as the dependent variable (controlling for baseline). Following a 12-week structured intervention that included aerobic exercise, resistance training, and caloric restriction, The IG showed a reduction in BFP of 2.75% ± 1.90%, an increase in ESE of 12.14 ± 6.13 points, and an increase in SE of 8.58 ± 4.40 points. Hierarchical regression analysis in the IG revealed that increases in SE and MVPA were both significantly associated with negative changes in BFP (SE: β = -0.159, P  < 0.001; MVPA: β = -0.079, P  = 0.046). In the CG, no significant associations were found between changes in psychological factors and BFP after controlling for baseline levels. These findings underscore the pivotal role of psychological determinants in the effectiveness of weight loss interventions and suggest the need for an integrated approach that considers both physical activity and mental health to effectively manage obesity among adolescents.

A wearable monitoring system for running gait analysis by diffusion transformer

Conventional wearable monitoring devices often suffer from insufficient data accuracy and low posture recognition rates, making them inadequate for the demands of professional sports health monitoring. To address these issues, this study proposes a wearable monitoring system for running gait analysis based on the Diffusion Transformer (DiT). The system aims to achieve high-precision running posture recognition and real-time motion monitoring through multi-sensor data fusion and advanced deep learning architecture. First, a wearable system was developed using a nine-axis Micro-Electro-Mechanical System (MEMS) inertial sensor and an UltraWide Band (UWB) positioning module. Data quality was enhanced through sensor calibration, noise compensation, and an adaptive filtering algorithm. Then, a DiT-LSTM running posture recognition model was constructed by integrating the DiT with a Long Short-Term Memory (LSTM) network to perform posture recognition within the wearable system. Experimental results show that on the Human3.6M dataset, the DiT-LSTM model achieved an accuracy of 97.54%, a precision of 97.61%, a recall of 97.73%, an F1-score of 97.58%, and an Area Under the Curve (AUC) of 98.61%. On the HumanEva dataset, the model attained an accuracy of 96.39%, a precision of 96.47%, a recall of 96.8%, an F1-score of 96.92%, and an AUC of 97.9%, all outperforming other algorithms. The complexity assessment showed that DiT-LSTM reached 14.7 GFLOPs on the Human3.6M dataset, with a per-epoch training time of 62.3 seconds, while its per-sample inference latency was only 9.4 ms, meeting real-time monitoring requirements. In the UWB-based position drift correction experiment, Sample 1 achieved mean errors of 0.637 m, 0.581 m, and 0.349 m on the X/Y/Z axes, with corresponding RMSE values of 0.041 m, 0.023 m, and 0.025 m, demonstrating high positioning accuracy and stability. By combining multimodal sensors with the DiT-LSTM model, the study offers reliable technical support for running gait analysis, injury prevention, and personalized training guidance.

The E3 ligases Itch and WWP2 regulate autoimmune neuroinflammation by controlling TH2 to TH17 cell conversion via interleukin-4-STAT5 axis in mice

Abstract Multiple sclerosis (MS) is a neurodegenerative autoimmune disease primarily mediated by T helper 17 (T H 17) cells. We previously showed that Itch/WWP2 double knockout (DKO) T cells produce high levels of type 2 cytokines, driving spontaneous autoinflammation. Here, we report that DKO T H 2-high carrying autoantigen-specific TCR (2D2) develop atypical spontaneous experimental autoimmune encephalomyelitis (EAE), with CD4 + T cells simultaneously producing IL-4 and GM-CSF, directly causing neuroinflammation. Unexpectedly, IL-4 deletion in DKO T H 2-high 2D2 mice exacerbates T H 17-driven classical EAE, indicating a T H 2 to T H 17 conversion. Furthermore, we show that the JAK3/STAT5 signaling pathway is critical for maintaining T H 2 lineage stability by modulating Blimp1 and c-Maf thereby suppressing T H 17 differentiation. Importantly, we find that this phenomenon can also be observed in dupilumab-treated patients with atopic dermatitis who develop psoriasis. Thus, our findings uncover the molecular antagonism and plasticity in the T H 2 and T H 17 cell programs and identify potential therapeutic targets for modulating T H 2 and T H 17 cell responses in autoimmune diseases.

Stable operation of a network-based multi-algorithm earthquake early warning system: the Korea meteorological administration platform

User experience and safety of generative AI-based mental health chatbots: Scoping review protocol

Introduction Mental health problems constitute a significant global health challenge due to their rising prevalence and substantial treatment gap. Digital Mental Health Interventions (DMHIs) including mental health chatbots have emerged as promising solutions due to their effectiveness and scalability. Recent advances in Generative Artificial Intelligence (GenAI) have improved the conversational abilities of these chatbots, further amplifying their potential. However, despite instances of inadvertent harm stemming from the unpredictable nature of GenAI, little attention has been paid to user experience and safety of these chatbots. Objective This proposed review will explore existing research on GenAI-based mental health chatbots. Specifically, it aims to identify and describe current chatbots, focusing on user experience, safety and risk mitigation strategies. Methods The review will follow the Joanna Briggs Institute (JBI) guidelines for conducting scoping reviews. It will also adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review (PRISMA-ScR). A systematic database search of Medline (PubMed), Scopus, PsycINFO, ACM Digital Library, and IEEE Xplore will be conducted. The database search will be complimented by research-based search engines (Google Scholar and Consensus). Studies focusing on the development, evaluation or implementation of GenAI-based mental health chatbots will be included without limitations to specific disorders or population groups. Two independent reviewers will perform screening and data extraction. The analysis will include descriptive summary and thematic analysis, with results presented in tabular, graphical, and narrative formats. Conclusion This review will provide a comprehensive overview of GenAI-based mental health chatbots while identifying innovative practices and knowledge gaps relating to user experience and safety. Findings will inform the ethical development, evaluation and implementation of GenAI-based mental health interventions.