Integration analysis of miRNA-mRNA uncovers the mechanisms of ochratoxin A-induced hepatotoxicity.

Ochratoxin A (OTA), the most toxic member of the ochratoxin family, is frequently detected in contaminated food and beverages, posing substantial health risks to both humans and animals, particularly due to its hepatotoxic effects. Although OTA is known to cause liver damage, the precise molecular mechanisms driving its toxicity remain poorly understood. In this study, we explored the hepatotoxic effects of OTA using LO2 cells and zebrafish models, combining miRNA and mRNA analyses to uncover the underlying mechanisms.

Hy-DeFake: Hypergraph neural networks for detecting fake news in online social networks.

Nowadays social media is the primary platform for people to obtain news and share information. Combating online fake news has become an urgent task to reduce the damage it causes to society. Existing methods typically improve their fake news detection performances by utilizing textual auxiliary information (such as relevant retweets and comments) or simple structural information (i.

Evaluation of the management of rotator cuff injuries utilising superparamagnetic iron oxide tracking stem cells.

Background: The ultrastructure of the tendon-bone interface (TBI) is inherently complex. After arthroscopic reconstruction, it is often replaced by disorganized scar tissue, which increases the risk of re-tearing.Stem cell therapies offer a promising approach to regenerate the original tissue structure and enhance the healing environment.

Readily Visualized Perfluorooctanoic Acid Detection Using a Small Molecule Chemosensor.

Mounting concerns regarding per-/poly-fluoroalkyl substances (PFAS) on human health are focusing attention on trace level PFAS detection in aqueous environments. Here we report a readily prepared small molecule, 2,6-bis(3,5-diethyl-1H-pyrrol-2-yl)pyridine (receptor 1), that displays high binding affinities (logKa = 4.9-6.

Integration of Hyperspectral Imaging and Deep Learning for Discrimination of Fumigated Lilies and Prediction of Quality Indicator Contents.

The lily, valued for its edibility and medicinal properties, is rich in essential nutrients. However, storage conditions and sulfur fumigation during processing can degrade key nutrients like polysaccharides, phenols, and sulfur dioxide. To address this, we applied a deep learning model combined with hyperspectral imaging for the rapid prediction of nutrient quality.

The virome investigation of the globally endangered Eld's deer (Rucervus eldii) on Hainan Island, China.

Eld's deer (Rucervus eldii) is a rare and globally endangered tropical Southeast Asian deer species. There is no research on pathogens in Eld's deer in Hainan, China. This study aimed to understand the virus diversity and novel viruses in Eld's deer, and provided important epidemiological baseline information for conservation of this endangered species.

The sex-specific difference in age-related aortic regional morphological changes.

Background: This study aims to investigate the influence of sex on age-related changes in aortic morphology using computed tomography (CT) imaging.

Method: Patients who underwent contrast-enhanced chest and abdominal CT between July 2021 and April 2022 were enrolled and stratified into six groups. Sex-specific comparisons of body surface area (BSA)-adjusted aortic diameters and tortuosity were performed across different groups.

Energy-efficient train timetable optimization for tram system under multi-signal priority strategies.

Energy-efficient operation is an effective approach for diminishing the operational expenses and carbon emissions of the tram system. Tram operation strategies and signal priority play a vital role in energy-efficient train timetable optimization. However, the impact of trams on road traffic efficiency has limited consideration in traditional optimization methods.

Semi-analytical dynamic modeling and impact mechanism analysis of a hard-coating cylindrical shell with arbitrary circular perforations.

In this paper, an innovative axial domain decomposition method, which uniquely integrates axial and circumferential perforation parameters, is developed for semi-analytical modeling of free vibration of a hard-coating cylindrical shell with arbitrary axial and circumferential perforations, based on the Love's first-order shear deformation theory and Rayleigh-Ritz method. The concept of this method is to decompose the shell into two types of domains at the upper and lower axial boundaries of the circular perforations. The generalized semi-analytical formulas of the perforated composite shell can be derived by assembling the separated energy expressions of each domain.

Machine Learning Models With Prognostic Implications for Predicting Gastrointestinal Bleeding After Coronary Artery Bypass Grafting and Guiding Personalized Medicine: Multicenter Cohort Study.

Background: Gastrointestinal bleeding is a serious adverse event of coronary artery bypass grafting and lacks tailored risk assessment tools for personalized prevention.

Objective: This study aims to develop and validate predictive models to assess the risk of gastrointestinal bleeding after coronary artery bypass grafting (GIBCG) and to guide personalized prevention.

Methods: Participants were recruited from 4 medical centers, including a prospective cohort and the Medical Information Mart for Intensive Care IV (MIMIC-IV) database.

Correction: Chen et al. Transcriptome Analysis of Larvae Exposed to a Semi-Lethal Dose of Vermistatin. 2025, , 31.

In the original publication [...

An Intervertebral Disc (IVD) Regeneration Model Using Human Nucleus Pulposus Cells (iHNPCs) and Annulus Fibrosus Cells (iHAFCs).

Intervertebral disc (IVD) degeneration (IVDD), primarily caused by nucleus pulposus (NP) dehydration, leads to low back pain. While current treatments focus on symptom management or surgical intervention, tissue engineering using IVD-derived cells, biofactors, and scaffolds offers a promising regenerative approach. Here, human NP cells (NPCs) and annulus fibrosus cells (AFCs) are immortalized with human telomerase reverse transcriptase (hTERT), generating immortalized NPCs (iHNPCs) and AFCs (iHAFCs).

Strain Engineering the Optoelectronic and HER Behavior of MoS/ZnO Heterojunction: A DFT Investigation.

The rational design of heterojunctions by coupling two or more two-dimensional (2D) materials is regarded as a feasible strategy to efficiently enhance photocatalytic-hydrogen performance by capturing solar energy to address the increasing global energy crisis. In this work, a functional MoS/ZnO heterojunction is proposed based on first-principles simulation. Our results reveal that the photogenerated electrons and holes in the MoS/ZnO heterojunction follow a specific Z-scheme pathway, highly facilitating redox reactions and optimizing optical properties in the visible-light region.

Dual Targeting of Neuropilin-1 and Glucose Transporter for Efficient Fluorescence Imaging of Cancer.

Purpose: Early diagnosis and complete resection of cancer are pivotal for enhancing patient survival rates and prognosis. However, a significant current challenge lies in the lack of specific imaging probes for the identifying various tumor types. The expression levels of neuropilin-1 (NRP1) and glucose transporter 1 (GLUT1) in most tumors, including breast cancer, are closely linked to tumor proliferation and metastasis.

Single-cell immune aging clocks reveal inter-individual heterogeneity during infection and vaccination.

Aging affects human immune system functionality, increasing susceptibility to immune-mediated diseases. While gene expression programs accurately reflect immune function, their relationship with biological immune aging and health status remains unclear. Here we developed robust, cell-type-specific aging clocks (sc-ImmuAging) for the myeloid and lymphoid immune cell populations in circulation within peripheral blood mononuclear cells, using single-cell RNA-sequencing data from 1,081 healthy individuals aged from 18 to 97 years.

Laparoscopic Extended Segmentectomy VII Guided by the Right Hepatic Vein: Precise Surgical Planning with a Three-Dimensional Liver Model.

Background: Laparoscopic extended segmentectomy VII is a technically challenging procedure owing to a lack of clear anatomical landmarks and difficulty in determining the cutting plane (Wang in J Am Coll Surg 238:321-330, 2024; Liu in Surg Oncol 38:101575, 2021). On the basis of precise surgical planning, we present a laparoscopic extended segmentectomy VII guided by the right hepatic vein.

Patient And Methods: A 65 year-old male patient presented with a right hepatic mass.

Weakly Supervised Object Localization With Progressive Activation Diffusion.

Weakly supervised object localization (WSOL) aims to locate objects with only image-level labels. Previous works mainly follow the framework of class activation map (CAM), which discovers the objects by estimating the contribution of each pixel position to the category prediction. However, most of them overlook the pixel-level spatial and semantic contextual correlation, resulting in: 1) limited activation ranges that only highlight the most discriminative parts rather than the entire object and 2) low activation values for some foreground parts, especially regions near the boundary between foreground and background.

Synbiotic yacon juice fermented by Lactiplantibacillus plantarum QS7T attenuates dextran sodium sulfate-induced ulcerative colitis in mice.

Ulcerative colitis (UC) is a prevalent inflammatory bowel disease associated with abnormal immune responses to commensal bacteria. The study investigated the effects of synbiotic yacon juice fermented by Lactiplantibacillus plantarum QS7T (FYJ) on ameliorating UC and modulating gut microbiota in a dextran sodium sulfate (DSS)-induced colitis mouse model. FYJ intervention significantly improved body weight and colon length, reduced the disease activity index and histopathological scores, and effectively alleviated colon tissue damage compared with treatments with L.

RBM39 promotes hepatocarcinogenesis by regulating RFX1's alternative splicing and subsequent activation of integrin signaling pathway.

Alternative splicing (AS) is crucial for tumor cells as it regulates protein expression and produces various protein isoforms, which can have diverse or even opposing roles in tumor growth and metastasis. Despite its significance, the role of AS and related splicing factors, particularly splicing-related messenger ribonucleoproteins (mRNPs), in hepatocarcinogenesis, is poorly understood. High-throughput transcriptome sequencing of HCC patients revealed that the spliceosome pathway might play a significant role in HCC development.

GDP-Net: Global dependency-enhanced Dual-domain Parallel Network for Ring Artifact Removal.

In Computed Tomography (CT) imaging, the ring artifacts caused by the inconsistent detector response can significantly degrade the reconstructed images, having negative impacts on the subsequent applications. The new generation of CT systems based on photon-counting detectors are affected by ring artifacts more severely. The flexibility and variety of detector responses make it difficult to build a well-defined model to characterize the ring artifacts.

TRTST: Arbitrary High-Quality Text-Guided Style Transfer with Transformers.

Text-guided style transfer aims to repaint a content image with the target style described by a text prompt, offering greater flexibility and creativity compared to traditional image-guided style transfer. Despite the potential, existing text-guided style transfer methods often suffer from many issues, including insufficient visual quality, poor generalization ability, or a reliance on large amounts of paired training data. To address these limitations, we leverage the inherent strengths of transformers in handling multimodal data and propose a novel transformer-based framework called TRTST that not only achieves unpaired arbitrary text-guided style transfer but also significantly improves the visual quality.

Metric Learning-Based Subspace Clustering.

The self-expressive strategy has shown excellent capabilities in realizing low-dimensional representations of high-dimensional data for subspace clustering algorithms. The existing designs, however, are formulated on the linearization assumptions of the data, neglecting the precise characterization of linear relationships within samples. Considering that real-world data adheres to diverse distribution forms, it becomes impractical to first treat the samples as existing in a uniform linear space before finding an appropriate manifold space.

Learning the Optimal Discriminant SVM With Feature Extraction.

Subspace learning and Support Vector Machine (SVM) are two critical techniques in pattern recognition, playing pivotal roles in feature extraction and classification. However, how to learn the optimal subspace such that the SVM classifier can perform the best is still a challenging problem due to the difficulty in optimization, computation, and algorithm convergence. To address these problems, this paper develops a novel method named Optimal Discriminant Support Vector Machine (ODSVM), which integrates support vector classification with discriminative subspace learning in a seamless framework.

Real-World Low-Dose CT Image Denoising by Patch Similarity Purification.

Reducing the radiation dose in CT scanning is important to alleviate the damage to the human health in clinical scenes. A promising way is to replace the normal-dose CT (NDCT) imaging by low-dose CT (LDCT) imaging with lower tube voltage and tube current. This often brings severe noise to the LDCT images, which adversely affects the diagnosis accuracy.

Fine-Grained Visual Text Prompting.

Vision-Language Models (VLMs), such as CLIP, excel in zero-shot image-level visual understanding but struggle with object-based tasks requiring precise localization and recognition. Visual prompts, like colorful boxes or circles, are suggested to enhance local perception. However, these methods often include irrelevant and noisy pixels, leading to suboptimal performance.