Hot-Spot-Guided Generative Deep Learning for Drug-Like PPI Inhibitor Design.

Protein-protein interactions (PPIs) are essential therapeutic targets, yet their large and relatively flat interfaces hinder the development of small-molecule inhibitors. Traditional computational approaches rely heavily on existing chemical libraries or expert heuristics, restricting exploration of novel chemical space. To address these challenges, we present Hot2Mol, a generative deep learning framework for the de novo design of target-specific and drug-like PPI inhibitors.

Decision Tree Modeling to Predict Myopia Progression in Children Treated with Atropine: Toward Precision Ophthalmology.

: Myopia is a growing global health concern, especially among school-aged children in East Asia. Topical atropine is a key treatment for pediatric myopia control, but individual responses vary, with some children showing rapid progression despite higher doses. This retrospective observational study aims to develop an interpretable machine learning model to predict individualized treatment responses and support personalized clinical decisions, based on data collected over a 3-year period without a control group.

MicroRNA-126 as an endogenous molecule for hypoxic/ischemic tolerance in neuroprotection.

Hypoxic and ischaemic brain injuries are notable contributors to neurological disability and mortality, posing major global public health challenges. Notably, microRNA-126 (miR-126) has emerged as a key regulator in the complex pathophysiology of stroke. Hypoxic/ischaemic (HI) preconditioning upregulates miR-126, offering protection against HI brain injury.

TACE Combined with Lenvatinib-PD-1 Versus TACE Monotherapy as Conversion Therapy Before Liver Resection in Unresectable Hepatocellular Carcinoma: A Retrospective, Propensity Score Matching Study.

Background: Transarterial chemoembolization (TACE) combined with Lenvatinib plus programmed death-1 inhibitor (PD-1 inhibitor) is recommended for unresectable hepatocellular carcinoma (uHCC), and it has increased the probability of successful conversion. Our aim was to compare the clinical benefits of TACE combined with Lenvatinib-PD-1 inhibitor versus TACE monotherapy as conversion therapy for patients with uHCC who subsequently underwent liver resection (LR).

Materials And Methods: This retrospective study included 213 uHCC patients who underwent LR after receiving either TACE combined with Lenvatinib plus PD-1 inhibitor (combination group, n=109) or TACE monotherapy (monotherapy group, n=104).

Multiple semantic prompt for rehearsal-free continual learning.

Deep neural networks have achieved impressive achievements in many applications while suffering from catastrophic forgetting, which refers to drastic degradation in performance on former tasks when training on novel ones. Continual learning aims to address the issue. A simple but effective solution is to replay a subset of previous data, while it increases memory costs and may violate data privacy.

Construction of a checkpoint inhibitor-related pneumonia diagnostic model based on exhaled nitric oxide: a prospective observational study.

Background: Checkpoint inhibitor-related pneumonia (CIP) is a complication of immune checkpoint inhibitors (ICIs) with high mortality. There is still a lack of effective biomarkers to identify CIP. Exhaled nitric oxide (eNO), an airway inflammatory marker, can be obtained by non-invasive methods, but its value in CIP is unknown.

Mechanosensitive nuclear checkpoint: nuclear envelope as a sensor of chromosomal instability and driver of cell fate.

The nuclear envelope (NE) is a dynamic, mechanosensitive structure that functions as a protective barrier for the genome and serves as a checkpoint responding to external stimuli. It plays a critical role in maintaining genomic stability and regulating cell fate. This review synthesizes recent research highlighting the role of NE as a mechanical checkpoint in ensuring accurate chromosome segregation, regulating cell cycle progression, and contributing to cancer development.

Decoupling of nanoindentation residual stress field in single-crystalline 4H-SiC via micro-Raman spectroscopy.

This Letter presents a combined analytical and experimental method to effectively decouple the radial and tangential residual stress fields induced by Berkovich nanoindentation in single-crystalline 4H-SiC using micro-Raman spectroscopy. By integrating the Raman stress characterization model with Yoffe's expanding cavity model, precise extraction of individual residual stress components around the indentation region is realized. Through the vertical backscattering micro-Raman mapping of the E phonon mode, we systematically investigate the residual stress distribution near the indentation.

Research Progress on Phytochemicals from Mulberry with Neuroprotective Effects: A Review.

With the intensification of the population aging worldwide, neurological disorders (NDs) are seriously threatening human society. Mulberry, a traditional economic crop, is a significant medicinal plant. Increasing evidence suggests that phytochemicals from mulberry play critical roles in the prevention and treatment of NDs.

Transcriptome Analysis Reveals the Molecular Mechanisms for Mycorrhiza-Enhanced Drought Tolerance in Maize by Regulating the Ca Signaling Pathway.

With the continuous change of climate, drought stress has emerged as the primary constraint on crop growth, posing a significant threat to the stability of global grain reserves. Arbuscular mycorrhizal fungi (AMF), as a kind of widely distributed root endophytes, enhance the drought tolerance of maize ( L.) through regulating the physiological and molecular responses.

Using implementation science to define the model and outcomes for improving quality in NEST360, a multicountry alliance for reducing newborn mortality in sub-Saharan Africa.

Background: Improving small and sick newborn care (SSNC) is crucial in resource-limited settings. Newborn Essential Solutions and Technologies (NEST360), a multicountry alliance, aims to reduce newborn mortality through evidence-based interventions. NEST360 developed a multipronged approach to improving quality.

A deep learning-based multimodal medical imaging model for breast cancer screening.

In existing breast cancer prediction research, most models rely solely on a single type of imaging data, which limits their performance. To overcome this limitation, the present study explores breast cancer prediction models based on multimodal medical images (mammography and ultrasound images) and compares them with single-modal models. We collected medical imaging data from 790 patients, including 2,235 mammography images and 1,348 ultrasound images, and conducted a comparison using six deep learning classification models to identify the best model for constructing the multimodal classification model.

Bioinformatics-based identification of mirdametinib as a potential therapeutic target for idiopathic pulmonary fibrosis associated with endoplasmic reticulum stress.

The molecular link between endoplasmic reticulum stress (ERS) and idiopathic pulmonary fibrosis (IPF) remains elusive. Our study aimed to uncover core mechanisms and new therapeutic targets for IPF. By analyzing gene expression profiles from the Gene Expression Omnibus (GEO) database, we identified 1519 differentially expressed genes (DEGs) and 11 ERS-related genes (ERSRGs) diagnostic for IPF.

GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models.

T cell receptors (TCRs) play a crucial role in numerous immunotherapies targeting tumor cells. However, their acquisition and optimization present significant challenges, involving laborious and time-consuming wet lab experimental resource. Deep generative models have demonstrated remarkable capabilities in functional protein sequence generation, offering a promising solution for enhancing the acquisition of specific TCR sequences.

Calibration and Validation of the CSM-CROPGRO-Peanut Model Under Mulched Drip Irrigation Conditions in Xinjiang.

In order to explore the applicability of the peanut growth simulation model CSM-CROPGRO-Peanut under conditions of mulched drip irrigation in Xinjiang, and to determine the optimal scenario for parameter estimation and model validation, field experiments were conducted in 2022 and 2023 on the water and nitrogen regulation of peanut. Based on the water requirements during the stages of peanut growth, three irrigation levels (low, medium, and high) and two nitrogen application levels (100% N and 50% N) were set, resulting in six treatments. An additional control treatment (CK) with a medium irrigation level and no nitrogen application was also included.

Preclinical models of immune checkpoint inhibitors-related interstitial pneumonia for anti-PD1 tumor immunotherapy.

Immune-related adverse reactions (irAEs) are common adverse reactions after immune checkpoint inhibitor treatment, impacting the universality and continued use of immunotherapy. Currently, preclinical models to investigate the mechanisms underlying these adverse effects are inadequate. This study aims to develop both in vitro and in vivo models of irAEs to advance basic research on these adverse reactions.

Cs-Induced Se/S Ratio Variation to Regulate Energy Band Structure for Efficient Sb(S,Se) Bulk Heterojunction Solar Cells.

As an emerging photovoltaic material, antimony selenosulfide (Sb(S,Se)) has attracted considerable attention and research enthusiasm. However, the current solution-processed Sb(S,Se) layers suffer from severe unfavorable energy band structure problems attributed to the vertical gradient-variable Se/S atomic ratio, making it a challenging and prospective subject. Herein, a novel and convenient alkali metal Cs-induced Se/S atomic ratio variation strategy has been developed for the first time to regulate Sb(S,Se) energy band structure through hydrothermal-processed CdS nanorod-arrays (NAs)/Sb(S,Se) bulk heterojunction (BHJ) films.

The Potential of SHAP and Machine Learning for Personalized Explanations of Influencing Factors in Myopic Treatment for Children.

The rising prevalence of myopia is a significant global health concern. Atropine eye drops are commonly used to slow myopia progression in children, but their long-term use raises concern about intraocular pressure (IOP). This study uses SHapley Additive exPlanations (SHAP) to improve the interpretability of machine learning (ML) model predicting end IOP, offering clinicians explainable insights for personalized patient management.

Genetic Tendency Analysis and Comprehensive Antioxidant Activity Evaluation of Leaves and Flowers of Loquat F Generation.

Loquat leaves, flowers, and other organs contain abundant antioxidant substances, which have wide applications in medicine, health, and food industries. This study aims to provide theoretical guidance for loquat hybrid parent and combination selection and a basis for high-quality loquat strain screening and development. For comprehensive antioxidant profiling, we used "Ninghaibai" and "Oobusa" loquat and their F generation as experimental materials to determine the total phenol, flavonoid, DPPH, ABTS, and FRAP content in the leaves and flowers of 56 strains.

Genome-wide identification of UDP-glycosyltransferases involved in flavonol glycosylation induced by UV-B irradiation in Eriobotrya japonica.

Flavonol glycosides are secondary metabolites important for plant development and stress defense such as UV-B irradiation. UDP-glycosyltransferase (UGT) catalyzes the last step in the biosynthesis of flavonol glycosides. Eriobotrya japonica is abundant in flavonol glycosides, but UGTs responsible for accumulation of flavonol glycosides remain unknown.

Engineering aortic valves via transdifferentiating fibroblasts into valvular endothelial cells without using viruses or iPS cells.

The technology of induced pluripotent stem cells (iPSCs) has enabled the conversion of somatic cells into primitive undifferentiated cells via reprogramming. This approach provides possibilities for cell replacement therapies and drug screening, but the potential risk of tumorigenesis hampers its further development and application. How to generate differentiated cells such as valvular endothelial cells (VECs) has remained a major challenge.