Evaluation of the causal relationship between 28 circulating biomarkers and osteoarthritis : a bidirectional Mendelian randomization study.

Aims: Circulating biochemistry markers are commonly used to monitor and detect disease-induced dysfunctions including osteoarthritis (OA). However, the causal nature of this relationship is nevertheless largely unknown, due to unmeasured confounding factors from observational studies. We aimed to reveal the causal relationship between 28 circulating biochemistry markers and OA pathogenesis.

Advancing Sports Cardiology: Integrating Artificial Intelligence with Wearable Devices for Cardiovascular Health Management.

Sports cardiology focuses on athletes' cardiovascular health, yet sudden cardiac death remains a significant concern despite preventative measures. Prolonged physical activity leads to notable cardiovascular adaptations, known as the athlete's heart, which can resemble certain pathological conditions, complicating accurate diagnoses and potentially leading to serious consequences such as unnecessary exclusion from sports or missed treatment opportunities. Wearable devices, including smartwatches and smart glasses, have become prevalent for monitoring health metrics, offering potential clinical applications for sports cardiologists.

Solution-Processed Quantum Dot Micropatterns: From Liquid Manipulation to High-Performance Quantum Dot Light-Emitting Diode Devices.

Micropatterning quantum dots (QDs) is a key process for making high-performance quantum dot light-emitting diodes (QLEDs), which have shown advantages in lighting and displays. So far, various solution processes have been developed for fabricating micropatterned QDs, where both uniform distribution and well-defined edges are desirable. Very recently, with the flourishing of near-eye displays, high-resolution QD micropatterns appear particularly attractive, which regretfully have progressed poorly due to the extremely complicated liquid dynamics at microscale.

DD-HGNN: Drug-Disease Association Prediction Via General Hypergraph Neural Network With Hierarchical Contrastive Learning and Cross Attention Learning.

The research on identifying drug-disease associations (DDAs) is widely used in scenarios such as drug development, clinical decision-making, and drug repurposing, holding significant biological and medical significance. Existing methods for drug-disease association prediction have achieved decent performance, they primarily rely on simplistic drug-disease association graphs or similarity graphs. These methods often struggle to capture the high-order correlations of complex multimodal data, limiting their ability to handle the complexity of data associations effectively.

Use of deep learning-based high-resolution magnetic resonance to identify intracranial and extracranial symptom-related plaques.

This study aims to develop a deep learning model using high-resolution vessel wall imaging (HR-VWI) to differentiate symptom-related intracranial and extracranial plaques, which is crucial for stroke treatment and prevention. We retrospectively analyzed HR-VWI data from 235 patients, dividing them into a training set (n = 156) and a testing set (n = 79). Using T1-weighted and contrast-enhanced T1WI images, we constructed five deep learning models and selected the best-performing DenseNet 201 model to extract features.

Discovery of the Clinical Candidate as a Highly Potent and Selective ATR Inhibitor.

ATR is one of the key DNA damage response (DDR) regulatory factors to maintain genome stability. ATR inhibition induces DNA damage accumulation and apoptosis in DDR kinase mutation or deficiency cancer cells through synthetic lethality, making it a promising target for treatment of cancers with DDR defects. Herein, we describe the discovery and preclinical evaluation of , a highly potent and selective novel ATR inhibitor, with favorable ADME, safety pharmacology, and pharmacokinetics profiles.

Tracking spin flip-flop dynamics of surface molecules with quantum dissipation theory.

The integration of scanning tunneling microscopy (STM) and electron spin resonance spectroscopy with voltage pulses is an emerging technique to probe the local spin dynamics of surface-adsorbed molecules. However, in experiments, the detection of real-time spin dynamics is severely hampered by the limited temporal resolution of STM electronics, and the associated theoretical investigations are still in their early stages due to various challenges in numerical simulations. In this work, we employ the highly accurate hierarchical equations of motion method to characterize the spin states and track the real-time coherent flip-flop spin dynamics in a surface-adsorbed hydrogenated Ti dimer.

Fermentation Ameliorates Physicochemical Properties, Physiological Activity, and Volatile and Non-Volatile Compounds of Mango Juice: Preliminary Results at Laboratory Scale.

is a strain predominantly used for juice production because of its excellent fermentation characteristics and strong acid production capacity. However, the influence of on the quality of mango juice has not yet been determined. Therefore, the effects of FJG1530 on the physicochemical properties, physiological activity, and volatile and non-volatile compounds of mango juice were extensively examined in this study.

[Research on emotion recognition in electroencephalogram based on independent component analysis-recurrence plot and improved EfficientNet].

To accurately capture and effectively integrate the spatiotemporal features of electroencephalogram (EEG) signals for the purpose of improving the accuracy of EEG-based emotion recognition, this paper proposes a new method combining independent component analysis-recurrence plot with an improved EfficientNet version 2 (EfficientNetV2). First, independent component analysis is used to extract independent components containing spatial information from key channels of the EEG signals. These components are then converted into two-dimensional images using recurrence plot to better extract emotional features from the temporal information.

A Novel 3D Magnetic Resonance Imaging Registration Framework Based on the Swin-Transformer UNet+ Model with 3D Dynamic Snake Convolution Scheme.

Transformer-based image registration methods have achieved notable success, but they still face challenges, such as difficulties in representing both global and local features, the inability of standard convolution operations to focus on key regions, and inefficiencies in restoring global context using the decoder. To address these issues, we extended the Swin-UNet architecture and incorporated dynamic snake convolution (DSConv) into the model, expanding it into three dimensions. This improvement enables the model to better capture spatial information at different scales, enhancing its adaptability to complex anatomical structures and their intricate components.

Metabolic insights into gut microbiota in the pharmacology of natural medicines.

Natural medicines (NMs) demonstrate distinct advantages in the clinical management of chronic diseases. Recent years have seen growing recognition of the gut microbiota's role in the efficacy and synergy of NMs, providing new impetus for elucidating the material basis and mechanisms of NMs and their path toward modernization. A fundamental question that has emerged is how NM-microbiota interactions integrate into the multi-target holistic mechanisms of NMs, the answer to which may also illuminate new avenues for drug discovery.

OfWRKY17-OfC3H49 module responding to high ambient temperature delays flowering via inhibiting expression in .

Ambient temperature is a pivotal factor in the regulation of the flowering process in plants. In this study, we found that high ambient temperature exerts an inhibitory effect on the flowering of "Sjigui". However, the underlying molecular mechanisms remain not fully understood.

MOSPD1 facilitates fatty acid metabolism and gastric cancer progression by promoting the MAPK pathway.

Background: Motile sperm domain containing 1 (MOSPD1) is overexpressed in colorectal, prostate, and breast cancers, but its role in gastric cancer (GC) progression remains unclear.

Methods: The effect of MOSPD1 was evaluated using cell viability, colony formation, wound healing, and Transwell assays. Triglyceride and lipid levels were measured in GC cells.

Effects of Protein Intake on Cognitive Function in Chinese Older Adults: A 10-Year Follow-Up Study.

Background: As the global population ages, there is an increasing prevalence of mild cognitive impairment and dementia. Protecting and preserving cognitive function in older adults has become a critical public health concern.

Methods: This study utilized data from four phases of the Chinese Longitudinal Healthy Longevity Survey conducted from 2008 to 2018, encompassing a total of 2454 participants.

Advances and applications of genome-edited animal models for severe combined immunodeficiency.

Severe combined immunodeficiency disease (SCID), characterized by profound immune system dysfunction, can lead to life-threatening infections and death. Animal models play a pivotal role in elucidating biological processes and advancing therapeutic strategies. Recent advances in gene-editing technologies, including zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), CRISPR/Cas9, and base editing, have significantly enhanced the generation of SCID models.

TGF-β signaling orchestrates cancer-associated fibroblasts in the tumor microenvironment of human hepatocellular carcinoma: unveiling insights and clinical significance.

Liver cancer, specifically hepatocellular carcinoma (HCC), stands out as one of the most formidable solid tumors, characterized by a dauntingly low survival rate. At the forefront of the tumor microenvironment (TME) orchestrating the initiation and advancement of HCC are cancer-associated fibroblasts (CAFs). TGF-β, widely recognized as a potent activator of CAFs, not only regulates their activity but also assumes a pivotal role in the metastatic journey of the tumor.

The characterization of in regulation of flower size through tuning cell expansion genes.

Flower appearance stands as a key characteristic of flowering plants and is closely linked to their ornamental value. Phytohormone Gibberellin (GA), essential for plant growth and development are widely reported for expansion in flower. DELLA proteins are known to negatively regulate GA signaling and influences plant growth and development through the regulation of cell expansion.

Novel biomarkers: the RUNX family as prognostic predictors in colorectal cancer.

While biomarkers have been shown to enhance the prognosis of patients with colorectal cancer (CRC) compared to conventional treatments, there is a pressing need to discover novel biomarkers that can assist in assessing the prognostic impact of immunotherapy and in formulating individualized treatment plans. The RUNX family, consisting of RUNX1, RUNX2, and RUNX3, has been recognized as crucial regulators in developmental processes, with dysregulation of these genes also being implicated in tumorigenesis and cancer progression. In our present study, we demonstrated a crucial regulatory role of RUNX in CD8T and CD103CD8T cell-mediated anti-tumor response within the tumor microenvironment (TME) of human CRC.

Tumor Vaccine Exploiting Membranes with Influenza Virus-Induced Immunogenic Cell Death to Decorate Polylactic Coglycolic Acid Nanoparticles.

Immunogenic cell death (ICD) of tumor cells, which is characterized by releasing immunostimulatory "find me" and "eat me" signals, expressing proinflammatory cytokines and providing personalized and broad-spectrum tumor antigens draws increasing attention in developing a tumor vaccine. In this study, we aimed to investigate whether the influenza virus (IAV) is efficient enough to induce ICD in tumor cells and an extra modification of IAV components such as hemeagglutinin (HA) will be helpful for the ICD-induced cells to elicit robust antitumor effects; in addition, to evaluate whether the membrane-engineering polylactic coglycolic acid nanoparticles (PLGA NPs) simulating ICD immune stimulation mechanisms hold the potential to be a promising vaccine candidate, a mouse melanoma cell line (B16-F10 cell) was infected with IAV rescued by the reverse genetic system, and the prepared cells and membrane-modified PLGA NPs were used separately to immunize the melanoma-bearing mice. IAV-infected tumor cells exhibit dying status, releasing high mobility group box-1 (HMGB1) and adenosine triphosphate (ATP), and exposing calreticulin (CRT), IAV hemeagglutinin (HA), and tumor antigens like tyrosinase-related protein 2 (TRP2).

RNA-Targeting CRISPR/CasRx system relieves disease symptoms in Huntington's disease models.

Background: HD is a devastating neurodegenerative disorder caused by the expansion of CAG repeats in the HTT. Silencing the expression of mutated proteins is a therapeutic direction to rescue HD patients, and recent advances in gene editing technology such as CRISPR/CasRx have opened up new avenues for therapeutic intervention.

Methods: The CRISPR/CasRx system was employed to target human HTT exon 1, resulting in an efficient knockdown of HTT mRNA.

Appraising the Effects of Gut Microbiota on Insomnia Risk Through Genetic Causal Analysis.

BackgroundInsomnia is a common neurological disorder that exhibits connections with the gut microbiota; however, the exact causal relationship remains unclear. MethodsWe conducted a Mendelian randomization (MR) study to systematically evaluate the causal effects of genus-level gut microbiota on insomnia risk in individuals of European ancestry. Summary-level datasets on gut microbiota were sourced from the genome-wide association study (GWAS) of MiBioGen, while datasets on insomnia were obtained from the GWAS of Neale Lab and FinnGen.

Integrative analyses of mendelian randomization and bioinformatics reveal casual relationship and genetic links between COVID-19 and knee osteoarthritis.

Background: Clinical and epidemiological analyses have found an association between coronavirus disease 2019 (COVID-19) and knee osteoarthritis (KOA). Infection with COVID-19 may increase the risk of developing KOA.

Objectives: This study aimed to investigate the potential causal relationship between COVID-19 and KOA using Mendelian randomization (MR) and to explore the underlying mechanisms through a systematic bioinformatics approach.

Assessing the ecological effects of the World's Largest Forestry Eco-engineering: Three-North Protective Forest Program within the initially scheduled range from 1978 to 2022.

China's Three-North Protective Forest Program (TNP) is the world's most ambitious afforestation project (ongoing from 1978 to 2050), which aims to increase forest coverage through afforestation and reforestation, protect agriculture, reduce soil erosion, and control desertification. Although TNP has been ongoing for 45 years, its rationales and effects remain uncertain. Here, we conducted a range-wide assessment of TNP by analyzing data from >10,000 scenes of satellite images and >50,000 field survey plots.