Quercetin ameliorates renal injury by promoting UCP1-mediated alleviation of lipid accumulation in diabetic kidney disease.

Background: Diabetic kidney disease (DKD) represents a common microvascular complication associated with diabetes. Research suggests that lipid accumulation contributes to lipotoxicity, exacerbating kidney injury in DKD. Quercetin (QCT), a flavonoid derived from specific fruits and vegetables, has shown potential in mitigating DKD progression; however, its precise protective mechanisms remain to be explored.

Chelerythrine alleviates inflammation and angiogenesis in a mouse rosacea model via suppressing the NF-κB/p38 MAPK/STAT3 pathways.

Introduction: Rosacea is a chronic inflammatory skin condition marked by excessive M1 macrophage polarization and angiogenesis, resulting in erythema and tissue inflammation. Despite available treatments, many patients experience recurrent flare-ups. This study explores chelerythrine, a bioactive component of Phellodendri Chinensis Cortex, for its therapeutic potential in rosacea through modulation of NF-κB, p38 MAPK and STAT3 signaling, inflammation, and vascular regulation.

Unraveling bladder cancer-related circRNA biomarkers: a hybrid model combining deep learning and statistics.

Circular RNAs (circRNAs), a class of gene expression regulators with closed loop structures, have been implicated in the pathogenesis of various diseases, including bladder cancer (BC). Their stability in and presence in body fluids suggest potential as diagnostic and prognostic biomarkers. This study employed an ensemble model integrating deep learning, feature selection, and statistical analysis to identify BC-associated circRNA biomarkers from RNA-sequencing data of 454 BC patients and 19 healthy controls.

Progression from GOLD A/B to GOLD E: a claims analysis of patients with COPD newly initiating inhaled therapy.

Background: Chronic obstructive pulmonary disease (COPD) is a progressive disease associated with substantial morbidity and mortality. Acute COPD exacerbations are a primary driver of significant burden and contribute to disease progression.

Methods: This retrospective, observational cohort study used the Optum Clinformatics Data Mart database to identify patients with COPD who were classified as Global Initiative for Chronic Obstructive Lung Disease (GOLD) A/B0 or A/B1 based on exacerbation history (i.

Semaglutide promotes bone marrow-derived progenitor cell flux toward an anti-inflammatory and pro-regenerative profile in high-risk patients: the SEMA-VR CardioLink-15 trial.

Background And Aims: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) reduce major atherosclerotic cardiovascular events in individuals living with either diabetes or obesity. Since the turnover of vascular regenerative (VR) stem and progenitor cells has been demonstrated to modulate vessel repair and atherothrombotic risk, this study aimed to determine the effect of the GLP-1RA semaglutide on the levels of circulating VR cells.

Methods: SEMA-VR CardioLink-15 was a randomized translational trial of usual care vs.

Vascular regenerative deficiencies in people with elevated lipoprotein(a): the Lp(a)-VRCE CardioLink-16 translational study.

Aims: Lipoprotein(a) [Lp(a)] is a causal risk factor for atherosclerotic cardiovascular disease (ASCVD); however, the relationship between Lp(a) and the capacity for vascular repair remains unclear. Depletion of vascular regenerative (VR) progenitor cells has been shown to be a novel indicator of compromised vascular repair in people living with cardiometabolic disorders. The purpose of this study was to determine if elevated levels of Lp(a) modify VR cell content properties.

Application of Comprehensive Geriatric Assessment (CGA) in assessment, management and Prognosis of Older adults Patients with Sarcopenia: A Review of Research Progress and Practice.

Summary：This review explores the critical role of Comprehensive Geriatric Assessment (CGA) in managing sarcopenia in the older adults.It highlights the usage of CGA across physical, functional, cognitive, psychological, and social assessments, providing a unique approach to older adults care. Background：The paper shows the growing prevalence of sarcopenia with age and its significant health implications, including increased mortality rates and diminished quality of life.

The corrosion mechanism of printed circuit boards affected by haze atmospheric particles.

As high-density electronic devices face increasing failure rates in polluted environments, understanding particulate-induced corrosion has become crucial. However, the combined effects of particle size, composition, and humidity on printed circuit boards (PCB) corrosion remain poorly understood. This study systematically investigates the corrosion behavior of PCB induced by atmospheric particulate matter under smog conditions.

A practical photocatalytic strategy for radical (deuterio)difluoromethylation using imidazolium reagents.

The difluoromethyl group (CFH) has garnered significant interest in medicinal chemistry owing to its unique biochemical and physicochemical properties. Its deuterated counterpart (CFD), building on the established utility of CFH, exhibits multifaceted potential for advancing biomedical research and therapeutic development. While the incorporation of the difluoromethyl group (CFH) into drug molecules has matured, efficient installation of its deuterated counterpart (CFD) remains a formidable challenge in medicinal chemistry.

Quantification of post-COVID-19 symptoms and pulmonary functional capacity in children with COVID-19.

Background: Children with coronavirus disease 2019 (COVID-19) present with mild but persistent pulmonary disease. Limited studies have explored post-infection aerobic capacity and quantification of symptoms. This study aimed to quantify post-COVID-19 fatigue, dyspnea, and pulmonary functional capacity while exploring associated factors.

MKMGCN-DDI: Predicting Drug-Drug Interactions via Magnetic Graph Convolutional Network With Multiple Kernels.

Polypharmacy is a common means of clinical treatments, but detecting drug-drug interactions (DDIs) behind unexpected effects can be costly and faces clinical limitations. Recently, graph neural networks (GNNs) have demonstrated encouraging performance in predicting DDIs. However, most studies overlook the comprehensive aspects of DDIs, such as the coexistence of types of pharmacological changes and the asymmetric roles of drugs.

Multi-Modal Multi-Kernel Graph Learning for Autism Prediction and Biomarker Discovery.

Graph learning-based multi-modal integration and classification is one of the most challenging tasks for disease prediction. To effectively offset the negative impact among modalities in the process of multi-modal integration and heterogeneous information extractions from graphs, we propose a novel method called Multi-modal Multi-Kernel Graph Learning (MMKGL). To solve the problem of negative impact among modalities, we propose a multi-modal graph embedding module to construct a multi-modal graph.

Automated Recognition and Analysis of Escape Response in Caenorhabditis Elegans.

Significant progress in medical research in recent years has led to the successful treatment of numerous illnesses. Unfortunately, effective treatments for several neurological disorders-particularly those affecting motor neurons-remain elusive, not only significantly impairing patients' quality of life but also placing a substantial financial burden on both individuals and society. To address this gap, scientists are focusing on model organisms to unravel pathogenic mechanisms and develop treatment strategies.

Spore-inspired inhalation drug delivery system for asthma therapy.

The delivery efficiency of drugs in the lung is crucial for inhaled therapies targeting pulmonary diseases. However, current inhalation carriers face challenges overcoming pulmonary barriers, leading to insufficient delivery efficiency. To tackle this limitation, we have developed a "spore-inspired" strategy.

Comparative analysis of antioxidant activity and accelerated collagen expression of human skin fibroblasts with gelatin hydrolysates from different sources.

Gelatin hydrolysates have been extensively used as nutraceutical agents, exhibiting significant biological activity. This study aimed to compare the antioxidant activity and enhancement of collagen expression in human skin fibroblast (HDF-α) cells treated with gelatin hydrolysates from different sources. Results indicate that the gelatin hydrolysates exhibited remarkable DPPH·, ABTS· and OH· scavenging capabilities.

MEGDTA: multi-modal drug-target affinity prediction based on protein three-dimensional structure and ensemble graph neural network.

Background: Drug development is a time-consuming and costly endeavor, and utilizing computer-aided methods to predict drug-target affinity (DTA) can significantly accelerate this process. The key to accurate DTA prediction lies in selecting appropriate computational models to effectively extract features from drug molecular structures and target protein structures. Existing methods usually ignore the features of the protein three-dimensional structure.

ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Impression Generation on Multi-institution and Multi-system Data.

Achieving clinical level performance and widespread deployment for generating radiology impressions encounters a giant challenge for conventional artificial intelligence models tailored to specific diseases and organs. Concurrent with the increasing accessibility of radiology reports and advancements in modern general AI techniques, the emergence and potential of deployable radiology AI exploration have been bolstered. Here, we present ChatRadio-Valuer, the first general radiology diagnosis large language model for localized deployment within hospitals and being close to clinical use for multi-institution and multi-system diseases.

OFD1 inhibition induces BRCAness to create a therapeutic vulnerability to PARP inhibition in pancreatic cancer.

BRCAness is a homologous recombination repair (HRR) deficiency phenotype mimicking BRCA1/2 loss, leading to PARP inhibitor sensitivity in BRCA-associated cancers including pancreatic cancer. However, how to induce BRCAness in BRCA-proficient tumors remains unclear. We identify OFD1 as a positive regulator of BRCA1 in human pancreatic cancer cells and specimens, with its overexpression correlating with poor prognosis.

Integration of Spatiotemporal Dynamics and Structural Connectivity for Automated Epileptogenic Zone Localization in Temporal Lobe Epilepsy.

Accurate localization of the epileptogenic zone (EZ) is essential for surgical success in temporal lobe epilepsy. While stereoelectroencephalography (SEEG) and structural magnetic resonance imaging (MRI) provide complementary insights, existing unimodal methods fail to fully capture epileptogenic brain activity, and multimodal fusion remains challenging due to data complexity and surgeon-dependent interpretations. To address these issues, we proposed a novel multimodal framework to improve EZ localization with SEEG-drived electrophysiology with structural connectivity in temporal lobe epilepsy.

Correction: Identification of hub genes within the CCL18 signaling pathway in hepatocellular carcinoma through bioinformatics analysis.

[This corrects the article DOI: 10.3389/fonc.2024.

Nucleotide-level circRNA-RBP binding sites prediction based on hybrid encoding scheme and enhanced feature extraction.

Circular RNAs (circRNAs) influence gene activity and cell behavior by binding to specific RNA binding proteins (RBPs), which is crucial in various diseases. Few approaches achieve nucleotide-resolution accuracy in circRNA-RBP binding sites prediction, and they commonly overlook the positional information of nucleotides as well as the interaction between deep and shallow features within the model. Here, we propose circdpb, a deep learning-based framework, to predict circRNA-RBP binding sites with nucleotide-level precision.

Efficacy and safety of enhanced recovery after surgery protocol on liver transplantation: A meta-analysis.

Background: Enhanced recovery after surgery (ERAS), a multidisciplinary and multimodal perioperative care protocol, has been widely used in several surgical fields. However, the effect of this care protocol on liver transplant recipients with end-stage liver disease remains unclear.

Aim: To compare the clinical outcomes of the ERAS protocol and standard care (SC) for liver transplant recipients with end-stage liver disease.

Identifying low-risk breast cancer patients for axillary biopsy exemption: a multimodal preoperative predictive model.

Background: As the most prevalent female malignancy worldwide, breast cancer frequently involves axillary lymph node metastasis (ALNM), which critically affects therapeutic algorithms. Current guidelines mandate preoperative ultrasound-guided axillary biopsy for suspicious lymph nodes, potentially exposing some low-risk patients with negative results to invasive risks. To optimize the utilization of biopsy, this study established a multimodal predictive framework that preoperatively assesses axillary lymph node (ALN) status, thereby triaging candidates for ultrasound-guided axillary biopsy.

pH-Responsive Self-Assembled Upconversion Photosensitizer and RSL3 Synergistically Induce Tumor Ferroptosis.

The activatable upconversion photosensitizer is a type of photosensitizer that can be activated in the tumor microenvironment (TEM) to achieve precise photodynamic therapy. As an inducer of ferroptosis, it is difficult for RSL3 to target tumor cells accurately and may be toxic to normal tissues. Thus, we developed a pH-responsive self-assembled near-infrared upconversion photosensitizer (Re-NPs) and encapsulated RSL3 drugs (RSL3@Re-NPs) to induce ferroptosis synergistically.

Multi-task machine learning reveals the functional neuroanatomy fingerprint of mental processing.

Mental processing delineates the functions of human mind encompassing a wide range of motor, sensory, emotional, and cognitive processes, each of which is underlain by the neuroanatomical substrates. Identifying accurate representation of functional neuroanatomy substrates of mental processing could inform understanding of its neural mechanism. The challenge is that it is unclear whether a specific mental process possesses a 'functional neuroanatomy fingerprint', i.