MSC-derived exosomes improve endometrial fibrosis via the lncRNA IGF2R/ miR-143-5p/AQP8 axis.

Background: Endometrial injury (EI) is frequently associated with intrauterine adhesions, endometrial thinning, amenorrhea, and infertility. In recent years, stem cells and their exosomes have been shown to have significant tissue repair efficacy. However, the role and probable mechanism of human umbilical cord mesenchymal stem cells (hUMSC-Exo) in endometrial healing remains unclear.

Exosomes Derived From Human Mesenchymal Stem Cells Mitigate Follicular Interstitial Cell Ferroptosis via the miR-26a-5p/PTEN/GPX4 Axis in Rats with Chemotherapy-Induced Premature Ovarian Insufficiency.

Background: Premature ovarian insufficiency (POI) is a persistent condition in young women characterized by early follicular development disorders and reduced fertility. Research has found that exosomes derived from human umbilical mesenchymal stem cells (hUCMSC-Exo) have significant tissue repair effects. This study aims to investigate the therapeutic effect and potential molecular mechanism of hUCMSC-Exo on POI.

An algorithm for detecting cow lameness based on ensemble learning of keypoint motion features.

Lameness has significant effects on the health, welfare, and productivity of dairy cows. Common challenges in farm environments, such as uneven lighting and occlusion, reduce the accuracy of keypoint detection, which in turn affects the precise extraction of motion features. Moreover, a single motion feature is often insufficient to comprehensively reflect lameness behavior.

Relative Binding Free Energy Methods Based on the Alchemical Transformation Framework: An Effective Strategy for Predicting the Umami Recognition Threshold of Umami Peptide Derivatives.

Umami peptides integrating both flavor and nutritional properties possess numerous derivatives that pose challenges for prediction using absolute free energy prediction tools and peptide classification models. While relative binding free energy (RBFE) methods based on the alchemical transformation framework have demonstrated excellent performance in drug activity prediction, their application in taste activity prediction remains unexplored. Through scientific literature analysis, 611 umami peptides and derivatives were systematically organized and cataloged with their structures and recognition thresholds then clustered into eight clusters.

Decoding Handwriting Trajectories from Intracortical Brain Signals for Brain-to-Text Communication.

The potential to decode handwriting trajectories from brain signals has yet to be fully explored in clinical brain-computer interfaces (BCIs). Here, intracortical neural signals are recorded from a paralyzed individual during attempted handwriting of complex characters. An innovative decoding framework is introduced to address both shape and temporal distortions between neural activity and movement, effectively resolving the misalignment issue commonly encountered in clinical BCIs due to the lack of accurate movement labels.

Enhanced Online Continuous Brain-Control by Deep Learning-Based EEG Decoding.

Objective: A growing amount of deep learning models for motor imagery (MI) decoding from electroencephalogram (EEG) have demonstrated their superiority over traditional machine learning approaches in offline dataset analysis. However, current online MI-based brain-computer interfaces (BCIs) still predominantly adopt machine learning decoders while falling short of high BCI performance. Yet, the generalization and advantages of deep learning-based EEG decoding in realistic BCI systems remain far unclear.

Astragaloside IV improves the quality of in vitro postovulatory aged oocytes by decreasing oxidative stress in mice.

Ovulated oocytes deteriorate rapidly if not fertilized within the optimal timeframe, known as postovulatory aging. Astragaloside IV (AS-IV), an active ingredient of Astragalus membranaceus, has been demonstrated to have anti-aging and antioxidant effects. However, it has not been elucidated whether AS-IV mitigates in vitro postovulatory oocyte aging.

Comparative analysis of -glucan, phenolic compounds, and targeted metabolomics in whole-grain highland barley varieties: Effects of cooking-induced changes.

This study examines the phytochemical profiles and antioxidant activities of highland barley varieties with white, blue, and black seed coat colors, focusing on the effects of cooking methods on black barley. Among the varieties, black barley, particularly Xiongzhang type, showed high concentrations of anthocyanins, proanthocyanidins, flavonoids, and phenolics, all of which are associated with enhanced antioxidant activities. Metabolomic profiling revealed significant biochemical diversity across the barley samples closely linked to seed coat color.

Artificial intelligence-assisted endobronchial ultrasound for differentiating between benign and malignant thoracic lymph nodes: a meta-analysis.

Background: Endobronchial ultrasound (EBUS) is a widely used imaging modality for evaluating thoracic lymph nodes (LNs), particularly in the staging of lung cancer. Artificial intelligence (AI)-assisted EBUS has emerged as a promising tool to enhance diagnostic accuracy. However, its effectiveness in differentiating benign from malignant thoracic LNs remains uncertain.

Umami_IP: An integrated model and explanatory analysis for quantitative prediction of Umami recognition threshold.

Umami peptides have gained considerable attention due to high nutritional value and distinct flavor. However, because of experimental complexity and time cost, the identification of umami peptides encounters obstacles. Based on the recognition threshold documented in TastePeptidesDB (http://tastepeptides-meta.

Effect of electroacupuncture on hypertensive and sympathetic excitability mechanism mediated by the paraventricular nucleus of the hypothalamus in spontaneous hypertensive rats.

Objective: To investigate the mechanism of electroacupuncture of sympathetic nerve activity and blood pressure reduction in the hypothalamic paraventricular nucleus (PVN) of spontaneous hypertensive rats (SHRs).

Methods: A total of 64 male SHRs were divided into four groups: model, sham-operated (Sham), electro-acupuncture (EA), and N-methyl-D-aspartate receptor antagonist and electroacupuncture (NRA + EA). In addition, 16 Wistar-Kyoto rats were used as controls.

Adipose-derived stem cells extracellular vesicles enhance diabetic wound healing via CCN2/PI3K/AKT pathway: therapeutic potential and mechanistic insights.

Background: Adipose-derived stem cells extracellular vesicles (ADSCs-EVs) hold significant promise in tissue repair and regeneration. While they have been reported to enhance diabetic wound healing, the precise mechanisms remain unclear.

Methods: ADSCs-EVs were isolated via ultracentrifugation and characterized through transmission electron microscopy, Western blot, and nanoparticle tracking analysis.

Dynamic Instance-level Graph Learning Network of Intracranial Electroencephalography Signals for Epileptic Seizure Prediction.

Brain-computer interface (BCI) technology is emerging as a valuable tool for diagnosing and treating epilepsy, with deep learning-based feature extraction methods demonstrating remarkable progress in BCI-aided systems. However, accurately identifying causal relationships in temporal dynamics of epileptic intracranial electroencephalography (iEEG) signals remains a challenge. This paper proposes a Dynamic Instance-level Graph Learning Network (DIGLN) for seizure prediction using iEEG signals.

MindGPT: Interpreting What You See With Non-Invasive Brain Recordings.

Decoding of seen visual contents with non-invasive brain recordings has important scientific and practical values. Efforts have been made to recover the seen images from brain signals. However, most existing approaches cannot faithfully reflect the visual contents due to insufficient image quality or semantic mismatches.

Structural basis of human cytomegalovirus neutralization by gB AD-5-specific potent antibodies.

Human cytomegalovirus (hCMV) poses a severe threat to fetuses, newborns, and immunocompromised individuals. No approved vaccines and limited treatment options are current medical challenges. Here, we analyze the human B cell responses to glycoprotein B (gB) in three top hCMV neutralizers from a cohort of 283 individuals with latent-infected hCMV.

Dynamic and low-dimensional modeling of brain functional connectivity on Riemannian manifolds.

Modeling brain functional connectivity (FC) is key in investigating brain functions and dysfunctions. FC is typically quantified by symmetric positive definite (SPD) matrices that are located on a Riemannian manifold rather than the regular Euclidean space, whose modeling faces three challenges. First, FC can be time-varying and the temporal dynamics of FC matrix time-series need to be modeled within the constraint of the SPD Riemannian manifold geometry, which remains elusive.

deficiency exacerbates LPS‑induced lung injury in lung‑on‑a‑chip and mouse models.

The oncogene lung cancer metastasis‑related protein 1 () is associated with neoplastic diseases and conditional knockout affects cell homeostasis. In the present study, the role of in lipopolysaccharide (LPS)‑induced acute lung injury (ALI) was investigated. Firstly, wild‑type C57BL/6 mice were used to establish an LPS‑induced ALI model via intratracheal injection of LPS, and the expression of was examined at 24, 48, 72 and 96 h after injury.

DSCT: a novel deep-learning framework for rapid and accurate spatial transcriptomic cell typing.

Unraveling complex cell-type-composition and gene-expression patterns at the cellular spatial resolution is crucial for understanding intricate cell functions in the brain. In this study, we developed Deep Neural Network-based Spatial Cell Typing (DSCT)-an innovative framework for spatial cell typing within spatial transcriptomic data sets. This approach utilizes a synergistic integration of an enhanced gene-selection strategy and a lightweight deep neural network for data training, offering a more rapid and accurate solution for the analysis of spatial transcriptomic data.

A Habenula Neural Biomarker Simultaneously Tracks Weekly and Daily Symptom Variations during Deep Brain Stimulation Therapy for Depression.

Objective: Deep brain stimulation (DBS) targeting the lateral habenula (LHb) is a promising therapy for treatment-resistant depression (TRD) but its clinical effect has been variable, which can be improved by adaptive DBS (aDBS) guided by a neural biomarker of depression symptoms. Existing neural biomarkers, however, cannot simultaneously track slow and fast symptom dynamics, do not sufficiently respond to stimulation parameters, and lack neurobiological interpretability, which hinder their use in developing aDBS.

Methods: We conducted a study on one TRD patient who achieved remission following a 41-week LHb DBS treatment, during which we assessed slow symptom variations using weekly clinical ratings and fast variations using daily self-reports.

Electrophysiological Abnormalities Associated With Sustained Attention in Children With Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder.

This study investigates electrophysio- logical abnormalities in children with Attention-Deficit/ Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) during sustained attention tasks, focusing on vigilance and inhibitory control, and explores associations between neural markers and attentional performance.Children with ADHD (n = 30), ASD (n = 23), and typically developing (TD) children (n = 31) completed a Test of Variables of Attention (TOVA) task while electroencephalography (EEG) was recorded. Event-related potentials (ERPs: P1, N2, P3) and event-related desynchronization/synchronization (ERD/ERS: theta ERS, alpha ERD, beta ERS) were measured and compared across groups.

A Closed-Loop Tactile Stimulation Training Protocol for Motor Imagery-Based BCI: Boosting BCI Performance for BCI-Deficiency Users.

Background: Brain-computer interfaces (BCIs) enable users to control and communicate with the external environment. However, a significant challenge in BCI research is the occurrence of "BCI-illiteracy" or "BCI-deficiency", where a notable percentage of users (estimated at 15 to 30%) are unable to achieve successful BCI control. For those users, they are struggling to generate stable and distinguishable brain activity patterns, which are essential for BCI control.

Human motor cortex encodes complex handwriting through a sequence of stable neural states.

How the human motor cortex (MC) orchestrates sophisticated sequences of fine movements such as handwriting remains a puzzle. Here we investigate this question through Utah array recordings from human MC during attempted handwriting of Chinese characters (n = 306, each consisting of 6.3 ± 2.

A wheat tandem kinase and NLR pair confers resistance to multiple fungal pathogens.

Tandem kinase proteins underlie the innate immune systems of cereal plants, but how they initiate plant immune responses remains unclear. This report identifies wheat protein wheat tandem NBD 1 (WTN1), a noncanonical nucleotide-binding leucine-rich repeat (NLR) receptor featuring tandem nucleotide binding adaptor shared by APAF-1, plant R proteins, and CED-4 (NB-ARC) domains, required for WTK3-mediated disease resistance. Both WTK3 and its allelic variant Rwt4-known for conferring resistance to wheat powdery mildew and blast, respectively-are capable of recognizing the blast effector PWT4.