BCLAF1 Regulates Osteoarthritic Cartilage Degradation Through Interaction with LAMTOR2.

Osteoarthritis (OA) is a progressive degenerative joint disorder with cartilage degradation as the primary cause of joint pain and loss of joint function. B-cell lymphoma-2-associated transcription factor 1 (BCLAF1) is a key regulator of apoptosis and serves as a signal transducer of the NFκB and Hif-1α pathways, both of which are involved in osteoarthritic cartilage degradation. However, whether BCLAF1 contributes to the pathogenesis of OA remains unclear.

β-CD@AgNPs with peroxisase-like activity for colorimetric determination of chiral tryptophan.

Different enantiomer forms of amino acids play different roles in multifarious fields, and improper use will cause irreversible effects. Therefore, the identification of chiral amino acids is a vital issue in the field of pharmaceutical analysis. Herein, a chiral sensing system of β-cyclodextrin coated silver nanoparticle (β-CD@AgNPs) with peroxidase-like activity was designed for the fast and efficient colorimetric identification of tryptophan (Trp) enantiomers based on the difference in binding capacity between D/L-Trp and β-CD.

Mesenchymal stem cell-derived exosomes as a promising cell-free therapy for knee osteoarthritis.

Osteoarthritis (OA), as a degenerative disease, leads to high socioeconomic burdens and disability rates. The knee joint is typically the most affected and is characterized by progressive destruction of articular cartilage, subchondral bone remodeling, osteophyte formation and synovial inflammation. The current management of OA mainly focuses on symptomatic relief and does not help to slow down the advancement of disease.

PdMo nanoflowers for endogenous/exogenous-stimulated nanocatalytic therapy.

The clinical application of reactive oxygen species (ROS)-mediated tumor treatment has been critically limited by inefficient ROS generation. Herein, we rationally synthesized and constructed the three-dimensional PdMo nanoflowers through a one-pot solvothermal reduction method for elaborately regulated peroxidase-like enzymatic activity and glutathione peroxidase-like enzymatic activity, to promote oxidation ROS evolvement and antioxidation glutathione depletion for achieving intensive ROS-mediated tumor therapy. The three-dimensional superstructure composed of two-dimensional nanosheet subunits can solve the issues by avoiding the appearance of tightly stacked crystalline nanostructures.

Deep Learning-Based H-Score Quantification of Immunohistochemistry-Stained Images.

Immunohistochemistry (IHC) is a well-established and commonly used staining method for clinical diagnosis and biomedical research. In most IHC images, the target protein is conjugated with a specific antibody and stained using diaminobenzidine (DAB), resulting in a brown coloration, whereas hematoxylin serves as a blue counterstain for cell nuclei. The protein expression level is quantified through the H-score, calculated from DAB staining intensity within the target cell region.

Osteosarcoma Explorer: A Data Commons With Clinical, Genomic, Protein, and Tissue Imaging Data for Osteosarcoma Research.

Purpose: Osteosarcoma research advancement requires enhanced data integration across different modalities and sources. Current osteosarcoma research, encompassing clinical, genomic, protein, and tissue imaging data, is hindered by the siloed landscape of data generation and storage.

Materials And Methods: Clinical, molecular profiling, and tissue imaging data for 573 patients with pediatric osteosarcoma were collected from four public and institutional sources.

-like factor 5 activates chick intestinal stem cell and promotes mucosal repair after impairment.

The mucosal renewal, which depends on the intestinal stem cell (ISC) activity, is the foundation of mucosal repairment. Importantly, activation of reserve ISCs (rISCs) plays a vital role in initiating mucosal repair after injury. However, the underlying regulatory mechanism of rISCs activation in chickens remains unclear.

ScopeViewer: A Browser-Based Solution for Visualizing Spatial Transcriptomics Data.

Motivation: Spatial transcriptomics (ST) enables a high-resolution interrogation of molecular characteristics within specific spatial contexts and tissue morphology. Despite its potential, visualization of ST data is a challenging task due to the complexities in handling, sharing and visualizing large image datasets together with molecular information.

Results: We introduce ScopeViewer, a browser-based software designed to overcome these challenges.

A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization.

Microscopic examination of pathology slides is essential to disease diagnosis and biomedical research. However, traditional manual examination of tissue slides is laborious and subjective. Tumor whole-slide image (WSI) scanning is becoming part of routine clinical procedures and produces massive data that capture tumor histologic details at high resolution.

Spiroligomer-Based Macrocycles for Atomically Precise Membranes.

Here, we report a new class of peptidomimetic macrocycles with well-defined three-dimensional structures and low conformational flexibility. They are assembled from fused-ring spiro-ladder oligomers (spiroligomers) by modular solid-phase synthesis. Two-dimensional nuclear magnetic resonance confirms their shape persistency.

Spatial Transcriptomics Arena (STAr): an Integrated Platform for Spatial Transcriptomics Methodology Research.

The emerging field of spatially resolved transcriptomics (SRT) has revolutionized biomedical research. SRT quantifies expression levels at different spatial locations, providing a new and powerful tool to interrogate novel biological insights. An essential question in the analysis of SRT data is to identify spatially variable (SV) genes; the expression levels of such genes have spatial variation across different tissues.

Association between resting-state functional brain connectivity and gene expression is altered in autism spectrum disorder.

Gene expression covaries with brain activity as measured by resting state functional magnetic resonance imaging (MRI). However, it is unclear how genomic differences driven by disease state can affect this relationship. Here, we integrate from the ABIDE I and II imaging cohorts with datasets of gene expression in brains of neurotypical individuals and individuals with autism spectrum disorder (ASD) with regionally matched brain activity measurements from fMRI datasets.

Development of Fmoc-Protected Bis-Amino Acids toward Automated Synthesis of Highly Functionalized Spiroligomers.

We report the fluorenylmethoxycarbonyl (Fmoc) protection of functionalized bis-amino acid building blocks using a temporary Cu complexation strategy, together with an efficient multikilogram-scale synthesis of bis-amino acid precursors. This allows the synthesis of stereochemically and functionally diverse spiroligomers utilizing solid-phase Fmoc/tBu chemistry to facilitate the development of applications. Four tetramers were assembled on a semiautomated microwave peptide synthesizer.

Using Unmanned Aerial Vehicle-Based Multispectral Image Data to Monitor the Growth of Intercropping Crops in Tea Plantation.

Aboveground biomass (AGB) and leaf area index (LAI) are important indicators to measure crop growth and development. Rapid estimation of AGB and LAI is of great significance for monitoring crop growth and agricultural site-specific management decision-making. As a fast and non-destructive detection method, unmanned aerial vehicle (UAV)-based imaging technologies provide a new way for crop growth monitoring.

Prediction of Drought-Induced Components and Evaluation of Drought Damage of Tea Plants Based on Hyperspectral Imaging.

Effective evaluation of physiological and biochemical indexes and drought degree of tea plant is an important technology to determine the drought resistance ability of tea plants. At present, the traditional detection method of tea drought stress is mainly based on physiological and biochemical detection, which is not only destructive to tea plants, but also time-consuming and laborious. In this study, through simulating drought treatment of tea plant, hyperspectral camera was used to obtain spectral data of tea leaves, and three machine learning models, namely, support vector machine (SVM), random forest (RF), and partial least-squares (PLS) regression, were used to model malondialdehyde (MDA), electrolyte leakage (EL), maximum efficiency of photosystem II (), soluble saccharide (SS), and drought damage degree (DDD) of tea leaves.

Using UAV image data to monitor the effects of different nitrogen application rates on tea quality.

Background: Accurate and efficient evaluation of the effect of nitrogen application rate on tea quality is of great significance for nitrogen management in a tea garden. However, previous methods were all through soil or leaf sampling, using biochemical methods for laboratory testing. These methods are not only less one-time detection samples, but also time-consuming, laborious and inefficient.

Src Homology 2 Domain-Containing Protein Tyrosine Phosphatase Promotes Inflammation and Accelerates Osteoarthritis by Activating β-Catenin.

Osteoarthritis (OA) is a chronic articular disease characterized by cartilage degradation, subchondral bone remodeling and osteophyte formation. Src homology 2 domain-containing protein tyrosine phosphatase (SHP2) has not been fully investigated in the pathogenesis of OA. In this study, we found that SHP2 expression was significantly increased after interleukin-1β (IL-1β) treatment in primary mouse chondrocytes.

Pristimerin Suppresses RANKL-Induced Osteoclastogenesis and Ameliorates Ovariectomy-Induced Bone Loss.

Osteoporosis is characterized by bone loss and destruction of trabecular architecture, which greatly increases the burden on the healthcare system. Excessive activation of osteoclasts is an important cause of osteoporosis, and suppression of osteoclastogenesis is helpful for the treatment of osteoporosis. Pristimerin, a natural compound, possesses numerous pharmacological effects via inactivating the NF-κB and MAPK pathways, which are closely related to osteoclastogenesis process.

A deep learning-based model for screening and staging pneumoconiosis.

This study aims to develop an artificial intelligence (AI)-based model to assist radiologists in pneumoconiosis screening and staging using chest radiographs. The model, based on chest radiographs, was developed using a training cohort and validated using an independent test cohort. Every image in the training and test datasets were labeled by experienced radiologists in a double-blinded fashion.

The immune vulnerability landscape of the 2019 Novel Coronavirus, SARS-CoV-2.

The outbreak of the 2019 Novel Coronavirus (SARS-CoV-2) rapidly spread from Wuhan, China to more than 150 countries, areas, or territories, causing staggering numbers of infections and deaths. In this study, bioinformatics analyses were performed on 5,568 complete genomes of SARS-CoV-2 virus to predict the T cell and B cell immunogenic epitopes of all viral proteins, which formed a systematic immune vulnerability landscape of SARS-CoV-2. The immune vulnerability and genetic variation profiles of SARS-CoV were compared with those of SARS-CoV and MERS-CoV.

Developing and Using a Data Commons for Understanding the Molecular Characteristics of Germ Cell Tumors.

Germ cell tumors (GCTs) are a rare disease, but they account for 15% of all malignancies diagnosed during adolescence. The biological mechanisms underpinning their development are only starting to be explored. Current GCT treatment may be associated with significant toxicity.

Development of a Data Model and Data Commons for Germ Cell Tumors.

Germ cell tumors (GCTs) are considered a rare disease but are the most common solid tumors in adolescents and young adults, accounting for 15% of all malignancies in this age group. The rarity of GCTs in some groups, particularly children, has impeded progress in treatment and biologic understanding. The most effective GCT research will result from the interrogation of data sets from historical and prospective trials across institutions.