Anti-epileptic effect of saikosaponin a by inhibiting ferroptosis via the IL-17/Akt/ERK signaling pathway in the temporal lobe epilepsy model.

Saikosaponin A (SSa), a triterpenoid saponin isolated from Astragalus membranaceus, possesses multiple pharmacological properties, including anticonvulsant, antiepileptic, and anti-inflammatory activities. This study aimed to elucidate the molecular mechanisms by which SSa exerts therapeutic effects in temporal lobe epilepsy (TLE), with a particular focus on the involvement of ferroptosis pathways. In a kainic acid-induced TLE mouse model, electroencephalography (EEG) was used to monitor seizure frequency.

An artificial intelligence cloud platform for OCT-based retinal anomalies screening system in real clinical environments.

Millions of individuals worldwide suffer from retinal anomalies, which can lead to irreversible vision loss. However, the number of ophthalmologists is highly mismatched with the population base in China, especially in many rural and underdeveloped towns. To tackle these challenges, this paper developed an Artificial Intelligence Cloud Platform for OCT-based Retinal Anomalies Screening (AI-PORAS), which is capable of detecting 15 retinal anomalies in OCT images to enhance remote diagnostic efficiency.

A novel prognostic signature integrating disulfidptosis- and ferroptosis-related genes in acute myeloid leukemia.

Acute myeloid leukemia is a highly heterogeneous hematopoietic malignancy, and we constructed a prognostic signature combining disulfidptosis-related genes and ferroptosis-related genes to predict the prognosis, immunotherapy response, and drug sensitivity of acute myeloid leukemia (AML) patients. The TCGA-LAML datasets underwent random partitioning into training and validation sets. Subsequently, a prognostic risk signature was formulated using the least absolute shrinkage and selection operator algorithm.

Analysis of microbial composition in different dry skin areas of Beijing women.

Introduction: The composition of the skin microbiota is shaped by the interaction of multiple factors, with area-specific changes and physiological characteristics in the skin having the most profound impact. The back of the hand and lower leg are two dry areas of human skin. Whether their microbial compositions are consistent, as well as the changes in skin microbiota at these two areas among individuals with dry skin, warrant further discussion.

Impact of rainy season on approach trajectories in high-altitude airport terminal maneuvering area: a clustering analysis.

Ensuring airspace safety is crucial for the efficient operation of aviation, especially at high-altitude airports where challenging weather and geographic conditions significantly increase operational complexity. With the widespread use of ADS-B data, flight monitoring has improved, providing detailed insights into aircraft trajectories. This study investigates the impact of weather variations on trajectory patterns in Terminal Maneuvering Area (TMA) at high-altitude airports during the rainy season, applying daily clustering analysis of ADS-B data combined with meteorological conditions, while further exploring the synergistic effects of other contributing factors such as air traffic control strategies and traffic density.

Amine-Rich Nanoparticle Liquids Enabling Efficient and Durable CO Membrane Separation.

Membrane separation has emerged as a sustainable solution to reduce CO emissions. However, it often struggles to achieve a balance between high CO selectivity and permeability, limiting its industrial applications. Herein, nanoparticle liquids are introduced to membrane separation to tackle this problem.

Study on the influence of carboxyethyl chitosan concentration on composite fouling characteristics: Experiments, functional group analysis, and molecular dynamics simulations.

To explore the scale inhibition characteristics of carboxyethyl chitosan (CEC) on composite fouling, this study employed experimental methods, functional group analysis, and molecular dynamics simulations to investigate the effects of CEC at different concentrations on the inhibition of AlO and CaCO composite fouling. The experimental results demonstrate that CEC, obtained through functional group substitution, serves as an environmentally friendly scale inhibitor capable of altering the morphology of composite fouling. Moreover, the scale inhibition efficiency of CEC improves with increasing inhibitor concentration.

Genome-Wide Identification and Characterization of Annexin Gene Family in Vitis vinifera and Functional Analysis of VvANN8 Under Salt Stress.

Grapes are economically significant fruit trees cultivated globally, but they are often affected by various abiotic stresses. Plant annexins are a class of calcium-dependent phospholipid-binding proteins that play crucial roles in regulating plant growth, development, and stress responses. However, the functions of grape annexins (VvANNs) remain relatively poorly understood.

Inhibition of epithelial cell YAP-TEAD/LOX signaling attenuates pulmonary fibrosis in preclinical models.

Idiopathic pulmonary fibrosis (IPF) is a progressive and lethal disease characterized by excessive extracellular matrix deposition. Current IPF therapies slow disease progression but do not stop or reverse it. The (myo)fibroblasts are thought to be the main cellular contributors to excessive extracellular matrix production in IPF.

Transformer optimization with meta learning on pathology images for breast cancer lymph node micrometastasis.

Lymph node micro-metastasis represents the initial stage of breast cancer spread or metastasis. However, the limited size of these hidden lesions restricts dataset expansion, presenting a significant challenge for manual examination and conventional deep learning techniques. By harnessing the power of meta-learning on limited datasets, we developed a novel network named MetaTrans, equipped with a 34-category dataset (MT-MCD) to effectively pinpoint micro-metastases in lymph nodes from pathological images.

Hederagenin's uric acid-lowering effects in hyperuricemic mice: Mechanistic insights from molecular docking and in vivo analysis.

This study explored the uric acid-lowering effects of hederagenin (HD) through molecular docking analysis and a chronic hyperuricemia (HUA) mouse model. Molecular docking was performed to evaluate HD's interactions key urate-regulating proteins, including xanthine oxidase (XOD), ABCG2, OAT1, URAT1, and GLUT9. To establish a chronic HUA model, mice were fed a yeast-adenine diet supplemented with potassium oxonate.

Task Augmentation-Based Meta-Learning Segmentation Method for Retinopathy.

Deep learning (DL) requires large amounts of labeled data, which is extremely time-consuming and laborintensive to obtain for medical image segmentation tasks. Metalearning focuses on developing learning strategies that enable quick adaptation to new tasks with limited labeled data. However, rich-class medical image segmentation datasets for constructing meta-learning multi-tasks are currently unavailable.

Structure-threshold relationship in food aroma molecules: Insights from S-curve method, molecular docking, and dynamics simulations.

This study investigates structure-odor threshold relationships of aroma compounds using integrated S-curve analysis, molecular docking, and dynamics simulations. Molecular docking revealed odor thresholds were independent of binding energies but sensitive to structural variations, which altered receptor interaction pattern: eugenol formed hydrogen bonds with SER183, while its isomer isoeugenol preferentially bound TYR260. Similarly, phenylethyl alcohol established TYR278 hydrogen bonding absent in phenylethyl aldehyde.

Electronic Microenvironment Regulation of Bismuth-salophen Single-site Catalysts for Enhanced Selectivity in CO Electrolysis to Formic Acid.

Electrocatalytic CO reduction reactions (CORR) hold significant industrial potential, with Bi-based catalysts demonstrating notable advantages in promoting the formation of formic acid (HCOOH). Despite progress, developing selective and efficient catalysts for CORR remains challenging. In this study, Bi single-site catalysts (SSCs) is designed modified with various electronegative groups (─F, ─H, and ─OMe (─OCH)) to improve the CORR selectivity of Bi through atomic-level microenvironment tuning.

Molecular dynamics simulations for the sensitivity and moisture adsorption on the surface of a novel cocrystal: CL-20/DNAN.

Context: Cocrystals are recognized as an effective strategy to mitigate the high sensitivity of energetic materials. In this paper, we use molecular dynamics (MD) to simulate the binding energies and XRD of CL-20/DNAN cocrystals with different ratios to prove that there is a new type of cocrystal structure between CL-20 and DNAN. To further investigate the effect of moisture absorption on the storage safety of cocrystals, this paper simulates the adsorption process of water molecules on the (0 0 1), (0 1 0), (1 0 0) crystal surfaces, respectively.

Clinical and pathological characteristics and treatment of gastric cancer during pregnancy.

Background: This study was conducted to investigate the clinical and pathological characteristics of patients with pregnancy-associated gastric cancer.

Materials And Methods: A retrospective study was performed on nine patients with pregnancy-associated gastric cancer. The clinical data were analyzed.

USP18 is a key regulator of immune function in mouse midbrain microglia.

Aims: Ubiquitin-specific peptidase 18 (USP18) is an important member of the deubiquitinating enzyme family, which has received much attention in recent years for its role in microglia regulation. The aim of this study was to investigate the role of USP18 in midbrain and its potential molecular mechanisms.

Methods: In this study, we assessed behavioural phenotypes and pathological changes by adeno-associated virus (AAV)-mediated midbrain-specific USP18 high-expression mouse model.

Multi-stage network for single image deblurring based on dual-domain window mamba.

Multi-stage methods have been proven effective and widely used in image deblurring research. These methods, usually designed based on Convolutional Neural Networks (CNNs) or Vision Transformers (ViTs), have limitations, including the inability to capture global contextual information and a quadratic increase in computational complexity as image resolution. Additionally, although current methods have incorporated frequency domain information, they do not sufficiently explore the interrelationships of different frequencies.

Efficient and scalable construction of clinical variable networks for complex diseases with RAMEN.

Understanding the interplay among clinical variables-such as demographics, symptoms, and laboratory results-and their relationships with disease outcomes is critical for advancing diagnostics and understanding mechanisms in complex diseases. Existing methods fail to capture indirect or directional relationships, while existing Bayesian network learning methods are computationally expensive and only infer general associations without focusing on disease outcomes. Here we introduce random walk- and genetic algorithm-based network inference (RAMEN), a method for Bayesian network inference that uses absorbing random walks to prioritize outcome-relevant variables and a genetic algorithm for efficient network refinement.

A positive feedback loop of OTUD1 and c-Jun driven by leptin expedites stemness maintenance in ovarian cancer.

Cancer stem cells (CSCs) are closely associated with drug resistance and recurrence in ovarian cancer patients. Although leptin is a high-risk factor for ovarian cancer and promotes stemness maintenance, a therapeutic strategy that counteracts the downstream signaling pathway of leptin remains elusive. Herein, the deubiquitinase OTUD1 was identified as a critical regulator of leptin in maintaining OCSCs properties.

Multimodal machine learning enables AI chatbot to diagnose ophthalmic diseases and provide high-quality medical responses.

Chatbot-based multimodal AI holds promise for collecting medical histories and diagnosing ophthalmic diseases using textual and imaging data. This study developed and evaluated the ChatGPT-powered Intelligent Ophthalmic Multimodal Interactive Diagnostic System (IOMIDS) to enable patient self-diagnosis and self-triage. IOMIDS included a text model and three multimodal models (text + slit-lamp, text + smartphone, text + slit-lamp + smartphone).

Deciphering olfactory receptor binding mechanisms: a structural and dynamic perspective on olfactory receptors.

Olfactory receptors, classified as G-protein coupled receptors (GPCRs), have been a subject of scientific inquiry since the early 1950s. Historically, investigations into the sensory mechanisms of olfactory receptors were often confined to behavioral characteristics in model organisms or the expression of related proteins and genes. However, with the development of cryo-electron microscopy techniques, it has gradually become possible to decipher the specific structures of olfactory receptors in insects and humans.

Laser-chemical composite manufacturing of biomimetic stepped armor functional metal surface with wear resistance and anti-icing characteristics.

Superhydrophobic surfaces have been demonstrated to exhibit excellent anti-icing effects, but they are susceptible to the loss of ice repellency as a result of external impacts. This paper proposes a novel bionic armour structure that combines an armour structure with an arrowroot bionic structure. A composite method combining laser etching and chemical modification was employed to achieve superhydrophobicity on the surface of the aluminium alloy.

Efficacy of laparoscopic cardiectomy combined with side overlap anastomosis for the treatment of terminal achalasia.

To investigate the safety and short-term effectiveness of laparoscopic-assisted cardiectomy with side-overlap esophagogastric reconstruction for the treatment of terminal or end-stage achalasia, patients with end-stage achalasia treated with laparoscopic-assisted cardiectomy with side-overlap esophagogastric reconstruction were retrospectively enrolled. The clinical data, surgical data and follow-up were analyzed. Among twenty-five patients enrolled, the achalasia type St was present in 12 (48%) patients, type Sg in 9 (36%), and type aSg in 4 (16%).