Noninvasive assessment of glymphatic system alterations as potential biomarkers for predicting overall survival in glioma.

Objective: In this retrospective study, authors aimed to evaluate the glymphatic function alterations associated with glioma and explore the prognostic value of these alterations by calculating the index for diffusivity along the perivascular space (ALPS index).

Methods: The authors utilized data from the publicly available University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) dataset, which includes 501 adult patients with histopathologically confirmed diffuse glioma, per the 2021 WHO classification, who underwent preoperative MRI, initial tumor resection, and tumor genetic testing at a single medical center from 2015 to 2021.The ALPS index was calculated from diffusivity maps for noninvasive glymphatic system (GS) analysis.

Efficacy of the Conventional Rehabilitation Robot and bio-Signal Feedback-Based Rehabilitation Robot on Upper-Limb Function in Patients with Stroke: A Systematic Review and Network Meta-Analysis.

BackgroundWith the development of modern biomedical engineering, bio-signal feedback-based robots, such as electromyography (EMG)-based and brain-computer interface (BCI)-based rehabilitation robot, have emerged beyond conventional designs. However, their comparative effectiveness for improving upper limb function in stroke patients remains unassessed.ObjectiveTo evaluate the comparative effectiveness and ranking of the conventional rehabilitation robot and bio-signal feedback-based rehabilitation robot in improving upper limb function in stroke patients.

Towards Semantically Faithful Diffusion Representation for Generalizable Retinal Image Segmentation.

Retinal image segmentation is essential for analyzing retinal structures like vessels and diagnosing retinopathy. However, the inherent intricacy of the retina, along with annotation scarcity and data heterogeneity, presents prevalent challenges in creating accurate and generalizable deep learning models. Diffusion models, while initially developed for image generation, have recently shown great promise for visual perception by leveraging the learned internal representations.

White-Rot Fungal Pretreatment for High-Performance Bamboo-Derived Carbon-Based Supercapacitor Electrodes.

Bamboo, as a rapidly renewable biomass material, has garnered significant attention in contemporary research due to its cost effectiveness as a viable source for supercapacitor electrode materials. However, untreated bamboo as an electrode material often leads to poor connectivity and uneven pore distribution. This study introduces a novel approach by using bamboo-derived biological carbon as a conductive substrate, subjecting it to carbonization through white-rot fungal pretreatment to enhance the pore structure and then loading it with nano-MnO sheets via a hydrothermal process.

Characteristics of Japanese encephalitis virus infection in NCG-hSTAT2+/+ mice: a novel model for studying neurological symptoms and immune response.

Japanese encephalitis virus (JEV), a leading cause of viral encephalitis in Asia and the Western Pacific, is regulated by type I interferon (IFN) signaling pathway, in which STAT2 is critical. However, STAT2's exact role in JEV-mediated IFN evasion remains unclear. Existing murine models of JEV infection predominantly employ high viral titers to induce encephalitis and primarily use immunocompetent or IFN receptor-deficient mice, limiting their utility for studying JEV's IFN evasion mechanisms.

Calculating Veterinary Clinical Pathology Reference Intervals for Research at the Integrated Research Facility, NIAID: A Practical Application of Data Partitioning and Statistical Methodology.

The veterinary research community requires statistically robust reference intervals in which to contextualize the results of laboratory tests obtained in research studies. While published reference intervals are available for veterinary clinical practice, they typically do not account for differences in animal husbandry, variations in analytical equipment, and the diverse range of species encountered in a research setting. In addition, existing guidelines for statistical calculation of reference intervals do not address commonly encountered issues with data quality, sample size, research-induced population biases, and other impediments.

Lessons from the coronavirus disease 2019 pandemic: Investigating the bidirectional relationship between coronavirus disease 2019 and migraine based on the MECH-HK cohort study.

Background: Although the coronavirus disease 2019 (COVID-19) pandemic has ended, its impact on patients with migraine has revealed critical gaps in understanding how migraine interacts with respiratory infections. Exploring this bidirectional relationship is essential for improving migraine management and protecting vulnerable populations during future outbreaks.

Objectives: To examine (1) the impact of migraine on COVID-19 manifestations and the risk of post-acute sequelae of COVID-19 (PASC), and (2) the effect of COVID-19 infection on migraine features.

The changes of immune function after neuroblastoma chemotherapy and the prediction of potential immune targets.

Background: High-dose chemotherapy for neuroblastoma is often intolerable for children, and its effectiveness is difficult to determine. Immunotherapy has become a popular research focus as a potential treatment. Therefore, identifying effective immune targets and drug synergistic chemotherapy against neuroblastoma is crucial.

EndoRD-GS: Robust Deformable Endoscopic Scene Reconstruction via Gaussian Splatting.

Real-time and realistic reconstruction of 3D dynamic surgical scenes from surgical videos is a novel and unique tool for surgical planning and intraoperative guidance. The 3D Gaussian splatting (GS), with its high rendering speed and reconstruction fidelity, has recently emerged as a promising technique for surgical scene reconstruction. However, existing GS-based methods still have two obvious shortcomings for realistic reconstruction.

A Dual-Band Smart Window with Electrical-Thermal Control for Visible and Near-Infrared Light Modulation.

Polymer dispersed liquid crystal (PDLC) exhibits excellent electro-optical properties for displays and smart windows but lacks sufficient near-infrared modulation for full solar management. Herein, a composite film with dual electrical-thermal control is designed for this purpose, which integrates PDLC film as an electrochromic layer and tungsten-doped vanadium dioxide (W/VO) coating as a thermochromic layer. The composite film not only facilitates active regulation of visible light through electrical control, but also enables the modulation of near-infrared light via phase transitions in response to temperature changes.

Mechanism of CaCO3 efficiently promoting hydrogen production by Clostridium butyricum BJ-10.

Aims: This study aims to explore the effect of adding CaCO3 on the hydrogen production by the fermentation of Clostridium butyricum (C. butyricum) BJ-10 and the mechanism of promoting hydrogen production by C. butyricum.

[Clinical and Ultrasound Manifestations of Immune Checkpoint Inhibitor-Associated Enterocolitis:Report of One Case].

Immune checkpoint inhibitor-associated enterocolitis is an immune-related adverse reaction during tumor treatment with immune checkpoint inhibitors(such as PD-1/PD-L1 inhibitors and CTLA-4 inhibitors).In this article,we present the clinical data and ultrasound manifestations of a patient with immune checkpoint inhibitor-associated enterocolitis,aiming to share diagnostic and therapeutic insights.

DialogueLLM: Context and emotion knowledge-tuned large language models for emotion recognition in conversations.

Large language models (LLMs) and their variants have shown extraordinary efficacy across numerous downstream natural language processing tasks. Despite their remarkable performance in natural language generating, LLMs lack a distinct focus on the emotion understanding domain. As a result, using LLMs for emotion recognition may lead to suboptimal and inadequate precision.

SuperEdgeGO: Edge-supervised graph representation learning for enhanced protein function prediction.

Understanding the functions of proteins is of great importance for deciphering the mechanisms of life activities. To date, there have been over 200 million known proteins, but only 0.2% of them have well-annotated functional terms.

Sign language recognition based on dual-channel star-attention convolutional neural network.

To enhance effective communication between individuals with hearing impairments and those without, numerous researchers have developed a variety of sign language recognition technologies. However, in practical applications, sign language recognition devices must balance portability, energy consumption, cost, and user comfort, while vision-based sign language recognition must confront the challenge of model stability. Addressing these challenges, this study proposes an economical and stable dual-channel star-attention convolutional neural network (SACNN) deep learning network model based on computer vision technology.

Taming large vision model for medical image segmentation via Dual Visual Prompt Tuning.

This paper presents Dual Visual Prompt Tuning (DVPT), an innovative strategy to enhance the performance of the Segment Anything Model (SAM) for medical image segmentation. While SAM demonstrates robust generalization in natural image segmentation, its effectiveness in medical tasks is hindered by the distinct characteristics of medical targets, the presence of noise and artifacts, and insufficient task-specific data for fine-tuning. Moreover, the manual-prompting paradigm applied in SAM make it laborious when adapted to medical domain.

Discovery of influenza-like virus clades in invertebrates and the evolutionary history and host-shifting events of Orthomyxoviridae in metazoans.

Epidemics are often initiated by emerging and re-emerging infectious diseases caused by viruses of animal origin. It is thus important to identify the reservoirs of potentially zoonotic viruses and understand the dynamics of their host shifts. The flu viruses belong to the virus family Orthomyxoviridae, which also contains Isavirus, Quaranjavirus, and Thogotovirus.

Compassion fatigue and transition shock of internship nursing students.

Background: Transition shock experienced by nursing students during the middle and later stages of their clinical internships can significantly influence their post-graduation career decisions. Compassion fatigue, prevalent among interns, may exacerbate this transition shock. This study aims to investigate the current status of compassion fatigue and transition shock among nursing students in the middle and late phases of their internships and explore the correlation between these two phenomena.

Systematic review and meta-analysis of deep learning for MSI-H in colorectal cancer whole slide images.

This meta-analysis evaluated diagnostic performance of deep learning (DL) algorithms using whole slide images (WSIs) for detecting microsatellite instability-high (MSI-H) in colorectal cancer (CRC). PubMed, Embase, and Web of Science were searched until January 2025. Nineteen studies comprising 33,383 samples were included.

Learning homeomorphic image registration via conformal-invariant hyperelastic regularisation.

Deformable image registration is a fundamental task in medical image analysis and plays a crucial role in a wide range of clinical applications. Recently, deep learning-based approaches have been widely studied for deformable medical image registration and achieved promising results. However, existing deep learning image registration techniques do not theoretically guarantee topology-preserving transformations.

Awareness of the risk of monkeypox among men having sex with men: a cross-sectional survey in Chongqing, China.

Background: Monkeypox (Mpox) was declared a public health emergency by World Health Organization (WHO) in 2024. This study aimed to identify subpopulations of men who have sex with men (MSM) in Chongqing, China, who may perceive themselves to be at risk of Mpox infection.

Methods: In September 2023, a cross-sectional online survey was conducted with the support of non-governmental organizations (NGOs).

High-Dose Aumolertinib for Untreated EGFR-Variant Non-Small Cell Lung Cancer With Brain Metastases: The ACHIEVE Phase 2 Nonrandomized Clinical Trial.

Importance: Central nervous system (CNS) metastases remain a significant challenge in the management of EGFR-variant non-small cell lung cancer (NSCLC).

Objective: To evaluate the activity and safety of high-dose aumolertinib in patients with untreated EGFR-variant NSCLC and brain metastases.

Design, Setting, And Participants: This was a phase 2 nonrandomized clinical trial conducted at 10 centers in China.

Predicting mucosal healing in Crohn's disease: development of a deep-learning model based on intestinal ultrasound images.

Objective: Predicting treatment response in Crohn's disease (CD) is essential for making an optimal therapeutic regimen, but relevant models are lacking. This study aimed to develop a deep learning model based on baseline intestinal ultrasound (IUS) images and clinical information to predict mucosal healing.

Methods: Consecutive CD patients who underwent pretreatment IUS were retrospectively recruited at a tertiary hospital.

Towards Reliable AR-Guided Surgical Navigation: Interactive Deformation Modeling with Data-Driven Biomechanics and Prompts.

In augmented reality (AR)-guided surgical navigation, preoperative organ models are superimposed onto the patient's intraoperative anatomy to visualize critical structures such as vessels and tumors. Accurate deformation modeling is essential to maintain the reliability of AR overlays by ensuring alignment between preoperative models and the dynamically changing anatomy. While finite element (FE) methods offer physically plausible modeling, their high computational cost limits intraoperative applicability.

Formation and Development of Pore Structure in Transitional ShaleInsights from Thermal Simulation Experiments on the Shanxi Formation Shale in the Ordos Basin.

Transitional shale gas reservoirs have become a new field of shale gas exploration in China. However, the formation and evolution of shale pores, particularly the organic matter (OM) nanopores, in this type of shale are still unclear. Simulation experiments with a typical transitional shale were conducted, and field emission scanning electron microscopy (FE-SEM) and low pressure CO and N adsorption (COGA/NGA) were used to characterize the shale pore structure.