An MRI-pathology foundation model for noninvasive diagnosis and grading of prostate cancer.

Prostate cancer is a leading health concern for men, yet current clinical assessments of tumor aggressiveness rely on invasive procedures that often lead to inconsistencies. There remains a critical need for accurate, noninvasive diagnosis and grading methods. Here we developed a foundation model trained on multiparametric magnetic resonance imaging (MRI) and paired pathology data for noninvasive diagnosis and grading of prostate cancer.

Identification of linear B-cell epitopes on the gE envelope protein of varicella-zoster virus.

Varicella-zoster virus (VZV) is a highly infectious DNA virus with an envelope. It is the pathogen causing varicella and herpes zoster. The glycoprotein E (gE) envelope protein, a primary target for VZV diagnostic reagents and vaccines, is highly immunogenic and plays a critical role in the pathogenicity of VZV.

Co-Delivery of Ca-MOF and Mg-MOF Using Nanoengineered Hydrogels to Promote In Situ Mineralization and Bone Defect Repair: In Vitro and In Vivo Analysis.

Severe bone defects resulting from traumatic injuries or infections are severe skeletal deficiencies that are unable to regenerate on their own. Despite their effectiveness, current treatments including allografts and artificial bone substitutes, have several drawbacks. This includes poor osseointegration, low biocompatibility and biodegradability, limited cell infiltration, and adverse side effects arising from drug-loaded substitutes.

InstructSee: Instruction-Aware and Feedback-Driven Multimodal Retrieval with Dynamic Query Generation.

In recent years, cross-modal retrieval has garnered significant attention due to its potential to bridge heterogeneous data modalities, particularly in aligning visual content with natural language. Despite notable progress, existing methods often struggle to accurately capture user intent when queries are expressed through complex or evolving instructions. To address this challenge, we propose a novel cross-modal representation learning framework that incorporates an instruction-aware dynamic query generation mechanism, augmented by the semantic reasoning capabilities of large language models (LLMs).

Dual functionality of MDM2 in PROTACs expands the horizons of targeted protein degradation.

The evolution of targeted protein degradation (TPD) has been significantly propelled by the advent of proteolysis-targeting chimeras (PROTACs), which utilize heterobifunctional molecules to facilitate the ubiquitination-mediated degradation of previously "undruggable" proteins. Mouse double minute 2 (MDM2), which is often overexpressed in various diseases and plays a crucial role in regulating key pathways like p53, emerges as an exemplary candidate for therapeutic exploitation within the TPD realm, serving both as an intrinsic E3 ligase and as a direct protein of interest (POI). By harnessing MDM2's inherent E3 ligase activity, PROTACs have been designed to efficiently degrade specific POIs, achieving substantial success in both in vitro and in vivo studies.

Orbital Hybridization Modulation via Ni Atom Decoration in Phosphotungstic Acid Cluster Cocatalyst for Optimized Photocatalytic Hydrogen Evolution Kinetics.

Regulating the hydrogen adsorption and desorption behavior on the cocatalyst surface can effectively improve the performance of photocatalytic hydrogen production. While platinum-group materials excel in optimizing Fermi levels and proton reduction kinetics, their practical application is hindered by economic and scalability constraints. Herein, a novel Ni atom decorated phosphotungstic acid cluster (PTA-Ni) is developed as a cocatalyst integrated with graphitic carbon nitride (GCN) for photocatalytic hydrogen evolution.

Machine Learning Integrating Surface Features and Crystal Similarity for Exploring 2D Materials.

The property prediction of two-dimensional (2D) materials has been constrained to specific systems or the highly self-similar Computational 2D Materials Database (C2DB) due to limited data availability and inadequate feature extraction. These challenges impede extrapolated predictions and large-scale exploitation across diverse databases. We developed a model named crystal surface and cluster network (CCSN) that integrates crystal surface and cluster features while leveraging transfer learning from bulk material databases to enhance model performance.

Thoracic Paravertebral Block with Liposomal Bupivacaine Versus Plain Bupivacaine in Patients Undergoing Thoracoscopic Lung Resection: A Randomized Controlled Study.

Background: The effectiveness of a thoracic paravertebral blockade with liposomal bupivacaine for thoracic surgery pain management is not well examined. This study compared the effects of liposomal bupivacaine and plain bupivacaine on a thoracic paravertebral blockade in adult patients undergoing video-assisted thoracoscopic surgery (VATS).

Methods: Consenting participants (114) scheduled for VATS were randomly assigned to thoracic paravertebral blockade at T4-5 and T7-8 levels with 20 mL (266 mg) liposomal bupivacaine (LB) or 20 mL (37.

CPS1-promoted the progression of lung adenocarcinoma via suppressing ammonia induced the activation of ROS/AMPK/P53/LKB1 signaling pathway.

This study aims to explore how CPS1 influences the progression of lung adenocarcinoma by affecting the ammonia-induced ROS/AMPK/P53/LKB1 signaling pathway. Bioinformatics analysis was conducted to identify differential gene expression in lung adenocarcinoma patients. A549 cells were infected with control (NC) or CPS1 knockdown (CPS1-KD) lentivirus.

An energy-embodied paralleled liquid manipulation for equipment-free, quantitative multiplexed liver function monitoring.

Comprehensive liver function monitoring is vital for liver damage diagnoses. However, multiplexed testing with clinical accuracy often requires paralleled liquid manipulation to avoid reagent interference and nonspecific adsorption, making it restricted to centralized facilities and specialists. Here, we report an equipment-free, quantitative, and multiplexed point-of-care testing (POCT), the energy-embodied POCT (EE-POCT).

Buried interface anchoring with silane coupling agents for low voltage loss and high-efficiency wide-bandgap perovskite solar cells.

Perovskite tandem solar cells (TSCs) hold substantial promise for surpassing the efficiency limits of single-junction solar cells. Nevertheless, achieving high open-circuit voltage (V) in wide-bandgap perovskite devices remains a challenge due to significant V-losses. Here, we introduce a heterogeneous interface anchoring strategy aimed at enhancing interfacial properties by incorporating a silane coupling agent between the perovskite and hole transport layers.

Screening and Characterization of B-Cell Epitopes of Porcine Respiratory Coronavirus Receptor Binding Domain Using Monoclonal Antibodies.

The spike (S) glycoprotein of porcine respiratory coronavirus (PRCV) plays a critical role in viral entry, with its receptor binding domain (RBD) on the S1 subunit responsible for interacting with the host receptor porcine aminopeptidase N. In this study, the PRCV RBD protein was successfully expressed, and a monoclonal antibody (mAb), 2E6, was produced using hybridoma technology. The specificity of 2E6 was confirmed by western blot and indirect immunofluorescence assay (IFA).

A Study to Evaluate the Potential Role and Clinical Application Value of Long Noncoding RNA CASC Family Members in Colorectal Cancer Based on Transcriptomic Data.

Long noncoding RNA (lncRNA) CASC, crucial in colorectal cancer (CRC) progression, remains largely unexplored despite its potential. The CRC data comes from The Cancer Genome Atlas (TCGA) database. The limma package was used to screen differentially expressed genes (DEGs), intersecting with CASC genes that yielded key hub lncRNAs.

Widefield Imaging Reveals Distinct Whole-Cortex Dynamics During Anesthetic-Induced Unconsciousness.

Background: Anesthesia-induced loss of consciousness (LOC) is associated with alterations in cortical synchronization and desynchronization in various cortical regions. However, the precise spatiotemporal dynamics across the entire cortex and their role in the LOC remain unclear. This study utilized advanced imaging techniques to investigate these cortical dynamics under the action of different anesthetics.

Associate Everything Detected: Facilitating Tracking-by-Detection to the Unknown.

Multi-object tracking (MOT) emerges as a pivotal and highly promising branch in the field of computer vision. Classical closed-vocabulary MOT (CV-MOT) methods aim to track objects of predefined categories. Recently, some open-vocabulary MOT (OV-MOT) methods have successfully addressed the problem of tracking unknown categories.

Efficacy and Safety of Extending Dosing Interval of Stapokibart in Patients with Atopic Dermatitis.

Stapokibart is a novel anti-interleukin-4 receptor α subunit monoclonal antibody approved for moderate-to-severe atopic dermatitis (AD) in adults. To evaluate the feasibility of extending dosing interval of stapokibart based on efficacy response in AD. In this ongoing, multicenter, open-label, single-arm trial (NCT06116565), stapokibart 300 mg was administered subcutaneously every 2 weeks (Q2W) for 12 weeks, followed by dosing interval adjustments at weeks 12 and 36.

Efficient Inverted Perovskite Solar Cells Utilizing Inorganic Composite Multiple Electron Transport Layers.

Electron transport layers (ETLs) featuring optimal film coverage and favorable electronic properties play a critical role in high-performance perovskite solar cells (PSCs). In contrast to organic ETLs, which have high material costs, inorganic metal oxide ETLs are considered promising alternatives for efficient inverted PSCs because of their low cost, high carrier mobility, and excellent stability. However, fabricating high-quality top inorganic ETLs that preserve the active perovskite layer remains a challenge.

Adding value to botanical resources: Metabolic network analysis along with high-resolution bioassays screening and UHPLC-qToF-high-resolution MS/MS profiling detail the pharmacological potential of underexplored Latin-American plants.

Healthcare services are challenged by an increased incidence of diseases and a decline in new drugs being brought to market. Thus, there is renewed interest in drug discovery from plants. This paper focused on enhancing the value of a small but diverse botanical resource of 45 Latin-American plant species, mostly from Mexican origin, through untargeted metabolomics, metabolic network analysis and parallel-in-vitro-bioactivity screening.

Engineering next-generation smart delivery materials for dentistry.

Over the last two decades, the healthcare field has witnessed exponential growth in the applications of stimuli-responsive biomaterials for diverse therapeutic purposes. This has led to the development of numerous smart dental biomaterials tailored for the precise and on-demand delivery of therapeutic agents. By leveraging the specific exogenous and endogenous stimuli, these smart materials fine-tune their physicochemical properties to improve the clinical efficacy of the therapeutic agents and mitigate their side effects.

Synergistic moxifloxacin detection: AgNPs/GO electrochemical immunosensor with oriented antibody immobilization.

Moxifloxacin (MXF), a broad-spectrum fluoroquinolone antibiotic, is widely used in human and veterinary medicine. However, its overuse leads to environmental residues and antimicrobial resistance, posing significant health risks. Herein, a label-free electrochemical immunosensor was developed for ultrasensitive MXF detection using silver nanoparticle-graphene oxide nanocomposites (AgNPs/GO).

ED: Explicit Data-Level Debiasing for Deepfake Detection.

Learning intrinsic bias from limited data has been considered the main reason for the failure of deepfake detection with generalizability. Apart from the discovered content and specific-forgery bias, we reveal a novel spatial bias, where detectors inertly anticipate observing structural forgery clues appearing at the image center, also can lead to the poor generalization of existing methods. We present ED4, a simple and effective strategy, to address aforementioned biases explicitly at the data level in a unified framework rather than implicit disentanglement via network design.

Patient-Reported Outcomes in Adults with Moderate-to-Severe Atopic Dermatitis Treated with Stapokibart over 52 weeks: A Post Hoc Analysis of a Phase 3 Trial.

Introduction: Atopic dermatitis (AD) significantly impairs quality of life and requires long-term management. This post hoc analysis aimed to evaluate the effect of stapokibart (an anti-IL-4Rα antibody) on patient-reported outcomes (PROs) in adults with moderate-to-severe AD from a phase 3 trial (NCT05265923).

Methods: Eligible patients were randomized 1:1 to receive stapokibart 300 mg (loading dose 600 mg) (n = 251) or placebo (n = 249) every 2 weeks (Q2W) for 16 weeks.

Bacterial Foreignization Nanosystem Elicits Multi-Phenotypic T Cells for Antitumor Immunity.

T lymphocytes are pivotal targets in clinical cancer immunotherapy; however, tumor cells frequently evade the T-cell attacks by altering the intrinsic immunogenicity manifested as adjuvanticity, antigenicity, and reactogenicity. Here, a bacterial outer membrane vesicle (OMVs)-based nanosystem is presented to elicit robust T-cell responses by reshaping tumor immunogenicity. OMVs are engineered with vesicular stomatitis virus G-protein that facilitates the fusion of OMVs with tumor cells, leading to tumor "foreignization" and adjuvanticity augment.

Research on predicting the risk level of coal mine roof accident based on machine learning.

Coal mine roof accidents are one of the main types of accidents leading to the decline of coal mine safety productivity, accounting for about 20% of the total number of coal mine safety accidents on average each year. In order to safeguard the safety and health of the workers and reduce the probability of the decline of productivity, the coal mine risks should be made known and controlled by certain technical means. This study proposes and constructs a novel and practical method for predicting the risk level of coal mine roof accidents.