Browse Articles

Intelligent glucose management in hospitalized patients: Short-term glucose and adverse events prediction

The management of blood glucose in hospitalized patients is confined to retrospective interventions, preventing healthcare professionals from predicting patients’ blood glucose levels and potential adverse events in advance. This study employs a deep learning model, specifically a Stacked Attention-Gated Recurrent Unit (SA-GRU) network, to forecast short-term blood glucose (BG) levels and predict adverse events in hospitalized patients, assisting clinicians in making clinical decisions. We collect continuous glucose monitoring(CGM) data from 196 hospitalized patients with type 2 diabetes, and by constructing and training this deep learning model, we predict blood glucose levels and adverse events.The model’s predictions are then compared with the actual CGM data, and different evaluation metrics are used to assess the predictions of blood glucose levels and adverse events. Additionally, experiments were conducted on another publicly available type 2 diabetes dataset. On our collected data, for the 30-minute prediction, the root mean square error (RMSE) and mean absolute relative difference (MARD) of blood glucose are 4.27 ± 0.31 mg/dL and 1.77% ± 0.08%, respectively, with an adverse event classification accuracy of 98.57% ± 0.11%. For the 60-minute prediction, the RMSE and MARD of blood glucose are 10.46 ± 0.55 mg/dL and 4.59% ± 0.22%, respectively, with an adverse event classification accuracy of 95.74% ± 0.33%. Similar positive results were obtained on another publicly available dataset. The proposed model demonstrates accurate predictions for blood glucose values and adverse events in the next 30 and 60 minutes.

Single-cell alternative polyadenylation analysis reveals mechanistic insights of COVID-19-associated neurological and psychiatric effects

COVID-19 is associated with increased risks of neurological and psychiatric sequelae. Alternative polyadenylation (APA) is ubiquitous in human genes, resulting in mRNA diversity, and has been validated to play a pivotal regulatory role in the onset and progression of a variety of diseases, including viral infections. Here, we analyzed the APA usage across different cell types in frontal cortex cells from non-viral control group and COVID-19 patients, and identified functionally related APA events in COVID-19. According to our study, the poly(A) site (PAS) usage is different among cell types and following SARS-COV-2 infection. Moreover, we found the genes with significant PAS level changes affected pathways related to RNA splicing, and neuronal development and function, suggesting that survivors of COVID-19 will have a high risk of these diseases and that alternative splicing functions cause these changes. Additionally, APA usage and its correlation with gene expression levels varied across genes, some prefer short isoform that is more stable to produce more proteins, while others may be regulated by different mechanisms. A total of 267 risk genes targeted by microRNAs for common neurological and psychiatric disorders were found to undergo significant changes in APA following infection. In conclusion, our comprehensive analysis of APA in neural cells from COVID-19 patients at the single-cell level elucidated changes in APA levels in the brains of SARS-COV-2-infected patients and confirmed that these changes impair the function of the nervous system, providing important insights for COVID-19-associated sequelae.

A scoping review of interventions to prevent and treat adverse events during treatment of rifampin-susceptible tuberculosis

Background Treatment-related adverse events are one of the leading barriers to tuberculosis treatment completion but have not been the focus of late-phase clinical trials. We performed a scoping review to identify interventions to improve the safety and tolerability of rifampin-susceptible tuberculosis. Our objective was to determine what interventions have been evaluated to prevent or manage adverse events, as well as what research is underway. Methods and findings We searched Embase, PubMed, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science from 1970 to December 2024 using a broad set of terms regarding adverse events, as well as citation searches to identify additional studies in topic areas that were not well-represented in the initial title search. To identify research in progress we searched Clintrials.gov, Cochrane reviews, and International Clinical Trials Registry Platform for trials reported to be active between January 2015 to April 2025. Of 7314 titles reviewed, 119 papers were available and eligible for this scoping review: 37 (31%) evaluated changes in the tuberculosis treatment regimen, 55 (46%) evaluated other interventions to prevent adverse events, and 27 (23%) evaluated treatment of adverse events. Only 7 studies reported enrollment of children < 12 years old. Of the 49 clinical trials, 20 (41%) had sample sizes < 50 participants/arm. Notable gaps in research in this field: uncertainty about the safety of pyrazinamide, lack of research on prevention and management of nausea/vomiting, uncertainty about the impact of hepatoprotectants, and lack of inclusion of children. Of the 8 study proposals that appear to be in progress, five were for a single topic: isoniazid dosing based on N-actyltransferase-2 status. Conclusions There has been considerable research on improving the safety and tolerability of tuberculosis treatment, but its impact is limited by under-powered studies, the lack of inclusion of key subgroups, and important gaps in the research portfolio (uncertainties about the safety of pyrazinamide and the efficacy of hepatoprotectants, lack of research on ways to manage and prevent treatment-related nausea). It is concerning that the research pipeline for interventions to improve safety and tolerability appears to be quite limited Our review has identified promising interventions that may make treatment better tolerated, and hence, more effective.

Isolation and characterization of the phytopathogenic fungus Ilyonectria liriodendri from persimmon as a new susceptible host

Several members of the fungal genus Ilyonectria primarily infect plants through the roots and basal stem, causing ‘black foot’ diseases, predominantly in woody plants such as grapevine ( Vitis spp.) and walnut ( Juglans regia ). In 2021, four Ilyonectria liriodendri isolates were cultured from the necrotized roots of Diospyros virginiana plants in Eger, Hungary. The isolates were identified by sequencing the ITS, β-tubulin, and partial histone H3 genes. The obtained sequences were used for phylogenetic analysis through multiple sequence alignment and the construction of a Maximum Likelihood tree, which revealed that all four isolates belonged to the species Ilyonectria liriodendri . The macro- and micromorphological variations, as well as the differences in exoenzyme production of the isolates suggested that they represent a somewhat diverse set of the same taxon. To prove their association with the symptoms observed in the host plants, the roots of one-year-old D. virginiana plants were artificially infected with conidial suspensions of the isolates according to Koch’s postulates. After 90 days of incubation in a greenhouse, 16 out of 20 inoculated plants showed necrosis in the taproots, while mock-inoculated plants remained symptomless. Necroses developed in the roots of the infected plants, and the inoculated fungi were reisolated, reinforcing their pathogenicity against D. virginiana . To the best of our knowledge, this is the first report of I. liriodendri causing disease in persimmon.

Prepared for the expected but unready for the unexpected: Unmet distractor expectations slow braking responsiveness but improve lane-keeping precision in a virtual driving simulation

Driving requires attentional control mechanisms to enhance the detection of driving-relevant objects and to mitigate interference from distractors. While distractor suppression can be proactively engaged when distracting events are expected, this mechanism also comes along with both costs and benefits, affecting responsiveness and accuracy even in their temporary absence. We explored the effect of distractor expectations on driving performance. Through an immersive driving simulator, participants (N = 24) performed an adapted version of the Distractor Context Manipulation (DCM) paradigm. They navigated a circuit and promptly pressed the brake pedal whenever a road sign-like target appeared, under three different conditions: a Pure Block without distractors, and two Mixed Blocks, featuring frequent irrelevant distractors (67% of trials) differing in perceptual complexity (Feature Search vs. Conjunction Search). We measured braking RTs and lane-keeping precision. Results showed that Mixed Blocks delayed braking RTs, even when distractors were temporarily absent, with the magnitude of this delay scaling with the perceptual similarity between target and distractors. Conversely, the same mechanism improved lane-keeping precision when neither targets nor distractors were present. Our findings suggest that distractor expectations modulate driving performance, entailing a trade-off between responsiveness and precision that depends on the characteristics of the distractor context.

An integrated framework for multi-feature fusion and intelligent recognition of design elements: Challenges and solutions

Visual design element recognition and analysis play a critical role in various applications, ranging from creative design to cultural artifact preservation. However, existing methods often struggle with accurately identifying and understanding complex, multimodal design elements in real-world scenarios. To address this, we propose an integrated model that combines the Swin Transformer for precise image segmentation, multi-scale feature fusion for robust type recognition, and a multimodal large language model (LLM) for fine-grained image understanding. Experimental results on ETHZ Shape Classes, ImageNet, and COCO datasets demonstrate that the proposed model outperforms state-of-the-art methods, achieving 88.6% segmentation accuracy and a 92.3% F1 score in multimodal tasks. These findings highlight the model’s potential as an effective tool for advanced design element recognition and analysis. The source code for this study can be viewed at this url: https://github.com/LIU-WENBO/Multi-Feature-Design-Elements-Recognition .

Collaborative and co-Ordinated action for Medication Safety (COMS): Experience-based co-design of an intervention blueprint to improve general practice and community pharmacy collaboration

Poor communication is a key causal factor of medication safety incidents. Collaboration between community pharmacy (CP) and general practice (GP) staff is essential but hindered by multiple barriers. This study applied an Experience-Based Co-Design (EBCD) approach, incorporating Systems Thinking for Everyday Work (STEW), to develop interventions for improving collaboration and communication on medication safety across the GP-CP interface. A sequential study design was undertaken, including: 1) an experience gathering phase to understand the communication of medication safety issues across the GP-CP interface, involving online focus groups and interviews with 27 GP and CP staff; and 2) two online EBCD workshops with 21 participants, including patients and primary care staff, to generate and prioritise interventions for improving medication safety communication and collaboration. Focus groups, interviews and workshops were audio-recorded, transcribed, and thematically analysed. Three key touchpoints for communication and collaboration on medication safety issues were identified: medication errors, medication changes, and potential patient safety concerns. An absence of shared communication approaches and the prioritisation of medication safety issues, one way communication tools, lack of understanding of professional roles and of incident reporting processes were barriers to communication and collaboration. Facilitators included GP pharmacist-community pharmacist relationships, face-to-face interactions and staff continuity. Five key interventions were suggested: development/modification of an electronic two-way communication tool between GP and CP; centralisation and sharing of patient records; interprofessional education; co-location of general practices and community pharmacies; and a toolkit for improving medication safety across the GP-CP interface. Participants agreed that a toolkit to address key communication and collaboration issues arising at multiple touchpoints should be prioritised for development and discussions led to refinement of ideas and production of a toolkit blueprint. Further research is required to refine toolkit resources, establish an implementation pathway, and evaluate its effectiveness to support adoption and improvements in medication safety.

Genetic association of microRNA-146a polymorphisms with the severity of coronary artery lesions in acute myocardial infarction

Background Polymorphisms situated within the microRNA-146a gene have been extensively reported to fulfill a crucial regulatory function in controlling inflammatory responses and modulating gene expression. More recently, these specific genetic variants have also been implicated in the pathogenesis of coronary artery lesions; nevertheless, the current body of available evidence remains notably sparse. Objectives To investigate the characteristics of the microRNA-146a gene polymorphisms rs2431697, rs57095329, and rs2910164, and their association with the severity of coronary artery lesions. Materials and methods This comparative cross-sectional study included patients with acute myocardial infarction (AMI) and a control group, recruited from two hospitals in Can Tho City, Vietnam, between October 2023 and May 2025. All participants underwent clinical evaluation and coronary angiography. Subsequently, the microRNA-146a gene polymorphisms-rs2431697, rs57095329, and rs2910164-were analyzed using gene sequencing. Results A total of 249 patients were included in the AMI group and 249 in the control group. The mean age of the patient cohort (66.65 ± 10.89 years) was similar to that of the controls (66.67 ± 14.12 years). Analysis of the rs2910164 polymorphism showed a lower frequency of the GG genotype in the AMI group compared with the control group (14.9% vs. 20.9%, p < 0.05), and all three SNPs met Hardy–Weinberg equilibrium criteria. Among patients with AMI, 30.5% had three-vessel coronary artery disease, and severe stenosis (≥90% luminal narrowing) was present in 78.3% of cases. Multivariate analysis demonstrated that the rs2431697 CC + TC genotype (OR = 0.10), the rs2910164 GG + CG genotype (OR = 3.23), diabetes mellitus (OR = 5.14), dyslipidemia (OR = 4.01), smoking (OR = 5.16), NT-proBNP ≥ 300 pg/mL (OR = 8.69), a GRACE score > 140 (OR = 10.82), and a TIMI score > 4 (OR = 6.50) were independent predictors of severe coronary stenosis (p < 0.05). Conclusion Patients with acute myocardial infarction had a lower prevalence of the GG genotype of the rs2910164 polymorphism compared with the control group. The rs2910164 polymorphism of microRNA-146a -particularly genotypes carrying the G allele-along with a history of diabetes mellitus, dyslipidemia, smoking, NT-proBNP ≥ 300 pg/mL, a GRACE score > 140, and a TIMI score > 4 were identified as independent predictors of severe coronary artery stenosis. In contrast, the rs2431697 polymorphism with genotypes carrying the C allele was found to be a protective factor.

Persistence of human enteric viruses in artificial and human saliva

Enteric viruses, such as Adenovirus 41 (AdV41) and Coxsackievirus B3 (CVB3), are significant contributors to gastrointestinal infections, particularly among young children and immunocompromised individuals. While fecal-oral transmission is the primary route of infection, emerging evidence indicates that saliva may also function as a reservoir for these viruses, posing a potential risk for oral transmission. Previous studies have primarily focused on the decay of viruses in aqueous matrices, like wastewater and freshwater, but the persistence of these viruses in human saliva remains underexplored. This study aimed to investigate the persistence of AdV41 and CVB3 in both human and artificial saliva under various conditions, including the presence of fecal particles and specific oral bacteria. Our findings demonstrated that human saliva significantly reduced viral stability compared to artificial saliva, with marked reductions in viral titers observed within 24–48 hours. Particularly, the presence of fecal particles in both saliva types extended CVB3 viral persistence, suggesting a protective effect due to particle adsorption. However, AdV41 demonstrated an opposite trend when in the presence of fecal particles, suggesting virus-specific differences in how particulate matter influences stability. Additionally, specific oral bacteria, such as Streptococcus mutans , significantly enhanced CVB3 stability, with a mean viral recovery of 23.2% of the viral titer after 24 hours in the presence of the bacteria compared to 0.7% in their absence ( p  = 0.001). This study shows complex interactions between viruses, oral bacteria, and fecal particles within the oral environment, emphasizing the need for further research on oral viral persistence and transmission dynamics. Understanding these mechanisms behind viral persistence in saliva can inform public health strategies aimed at mitigating the risk of transmission.

Monitoring deformation of seasonally frozen Yellow River bank soil: A synergetic application of the SBAS InSAR approach

The riverbanks of the Inner Mongolia reach of the Yellow River face persistent risks of deformation and collapse due to freeze-thaw cycles and hydrodynamic forces. However, most existing studies have concentrated on urban land subsidence or the stability of hydraulic structures, while long-term and multi-reach systematic monitoring of this seasonally frozen and meandering section remains scarce. Based on Sentinel-1A satellite data, this study employs the Small Baseline Subset InSAR (SBAS-InSAR) technique to derive the spatiotemporal characteristics of riverbank deformation, integrates channel migration information to examine the spatial relationship between channel evolution and bank deformation, and conducts long-term deformation pattern analyses in representative reaches. The results indicate that the riverbanks in this section are generally stable, with 96.5% of monitoring points showing an average annual deformation rate within ±30 mm/a. Nevertheless, significant deformation was detected in some areas between the Bayangaole and Toudaoguai hydrological stations, dominated by uplift and strongly influenced by river water level fluctuations. Subsidence primarily occurred along the outer banks of meander bends, where loose bank structures pose potential stability risks. Specifically, in the Shisifenzi area, the average annual deformation rate ranged from −20.1 to 24.8 mm/a, with subsidence concentrated at meander crests and cultivated land, potentially affecting levee stability and farmland safety. In the Wenbuhao area, rates ranged from −18.7 to 19.5 mm/a, with subsidence concentrated along the eastern riverbank, indicating localized erosion risks, while uplift mainly occurred in farmland farther from the river. This study reveals the differentiated response characteristics of various reaches under hydrodynamic forces and demonstrates that SBAS-InSAR is effective for monitoring riverbank deformation in complex environments. The findings provide reliable technical support for riverbank hazard prevention and the protection of riverfront infrastructure in seasonally frozen regions.

Inappropriate treatment of hospital-acquired infections and associated factors among admitted adults in Wolaita Zone hospitals, Southern Ethiopia: A multi-center cross-sectional study

Background Hospital-acquired infections (HAIs) are a global health concern. Inappropriate treatment of HAIs worsens their impact, contributing to increased antimicrobial resistance, higher healthcare costs, and heightened morbidity and mortality. However, evidence on inappropriate treatment of HAIs in resource-constrained settings remains limited. The aim of this study was to assess the prevalence and associated factors of inappropriate treatment of HAIs among admitted adults in Wolaita Zone hospitals, Southern Ethiopia. Methods A multicenter cross-sectional study was conducted in selected hospitals in the Wolaita Zone from 28 October 2024–25 February 2025, enrolling 280 patients with HAIs. Data were collected via structured face-to-face interviews and medical record review. Data were entered in EpiData 4.6 and analyzed in SPSS 25. A binary logistic regression model was employed to examine the associations between the outcome variable and explanatory variables, with statistical significance determined at a p-value < 0.05. Results The mean (± SD) age of participants was 41.25 ± 12.5 years. Pneumonia was the most frequently diagnosed HAI (133, 47.5%). Streptococcus species, Staphylococcus aureus , and Klebsiella pneumoniae were the predominant pathogens isolated. The overall prevalence of inappropriate treatment of HAI was 53.6% (95% CI: 47.5–59.5). The odds of inappropriate treatment of HAI were significantly higher in the presence of comorbidity (AOR = 2.69, 95% CI: 1.45–5.01; p = 0.002 ) and among patients treated in the surgical ward (AOR = 2.75, 95% CI: 1.32–5.74; p = 0.007 ). Conversely, culture testing (AOR = 0.34, 95% CI: 0.15–0.74; p = 0.007 ) and provision of clinical pharmacy service (AOR = 0.28, 95% CI: 0.13–0.60; p = 0.001 ) were associated with reduced odds of inappropriate treatment of HAIs. Conclusions The prevalence of inappropriate treatment of HAIs among admitted adults in the current study settings was high. Comorbidities, treatment ward type, culture testing, and the provision of clinical pharmacy services were significantly associated with inappropriate treatment. Clinicians should give particular attention to patients with comorbidities and those receiving care in surgical wards. Health facilities should enhance microbiological diagnostic services to promote evidence-based therapy. Additionally, clinical pharmacy services should be expanded across hospital wards to support efforts in reducing inappropriate treatment of HAIs. These findings underscore the urgent need for multifaceted interventions to improve patient care and combat antimicrobial resistance in this setting.

DNA barcode data of Japanese species of flesh flies (Diptera: Sarcophagidae: Sarcophaginae)

Capture records of <i>Blattella nipponica</i> Asahina (Blattodea: Ectobiidae) in Aomori Prefecture, Japan

mGluR4–NPDC1 complex mediates α-synuclein fibril-induced neurodegeneration

Robust Fall Army Worm detection in maize using multimodal RGB and thermal image fusion

Abstract Effective pest and disease detection plays a crucial role in minimizing crop losses and improving decision-making in precision agriculture. Among the most destructive pests affecting maize crops globally is the Fall Army Worm (FAW), known for its rapid spread and high impact on yield. Existing detection practices often rely on manual scouting, which can be inefficient, labour intensive and prone to human error. This study proposes a novel deep learning based framework for the automatic classification of FAW infested and healthy maize crops by integrating RGB and thermal image modalities. The core objective is to enhance detection accuracy through multimodal image fusion. A hybrid DNN-ViT model is introduced, combining two complimentary pipelines: (i) feature-level fusion, where CNN extracted features from RGB and thermal images are fused and classified using a Deep Neural Network (DNN) and (ii) image-level fusion, where a 6 channel RGB-thermal image is directly processed using a modified Vision Transformer (ViT). Experimental results demonstrate that the fused model achieved superior performance with an accuracy of 0.98, precision, recall and F1-score of 0.98 and AUC-ROC of 0.98 on the test set, outperforming models trained on RGB-only, thermal-only and unfused data. The ablation study confirms the effectiveness of multimodal fusion, with the no-fusion model showing significantly lower performance (accuracy-0.60 and AUC-ROC-0.67). This work highlights the benefits of integrating complementary data sources for robust crop health monitoring. Future research will explore enhanced fusion strategies, environmental robustness and field level deployment to validate the model’s practical applicability.

Germline epigenome editing identifies H3K9me3 as a mediator of intergenerational DNA methylation recovery in mice

Solanum tuberosum glucan synthase-like 05 is involved in root-knot nematode Meloidogyne hapla parasitism

Calcium channel blockers increase the risk of aortic aneurysm and dissection

Deep learning-based joint analysis of diabetic retinopathy and glaucoma in retinal fundus images

Multi-scale classification decodes the complexity of the human E3 ligome

Abstract E3 ubiquitin ligases are vital enzymes that define the ubiquitin code in cells. Beyond promoting protein degradation to maintain cellular health, they also mediate non-degradative processes like DNA repair, signaling, and immunity. Despite their therapeutic potential, a comprehensive framework for understanding the relationships among diverse E3 ligases is lacking. Here, we classify the “human E3 ligome”—an extensive set of catalytic human E3s—by integrating multi-layered data, including protein sequences, domain architectures, 3D structures, functions, and expression patterns. Our classification is based on a metric-learning paradigm and uses a weakly supervised hierarchical framework to capture authentic relationships across E3 families and subfamilies. It extends the categorization of E3s into RING, HECT, and RBR classes, including non-canonical mechanisms, successfully explains their functional segregation, distinguishes between multi-subunit complexes and standalone enzymes, and maps E3s to substrates and potential drug interactions. Our analysis provides a global view of E3 biology, opening strategies for drugging E3-substrate networks, including drug repurposing and designing specific E3 handles.