Multi-scale comparison of the formation mechanisms in landscape genes of traditional villages.

The relationship between traditional village landscape genes and the geographical environment is closely intertwined, exhibiting notable spatial differences and cultural characteristics during scale transformations. To effectively elucidate the formation mechanisms of these landscape genes, it is essential to construct a multi-scale analytical framework that integrates multiple dimensions. This paper address these challenges by expanding the sample selection range and combining both qualitative and quantitative analyses of landscape genes across various scales.

Discovery of novel BfmR inhibitors restoring carbapenem susceptibility against carbapenem-resistant by structure-based virtual screening and biological evaluation.

The emergence and spread of pose a severe threat to public health, highlighting the urgent need for the next generation of therapeutics due to its increasing resistance to existing antibiotics. BfmR, a response regulator modulating virulence and antimicrobial resistance, shows a promising potential as a novel antimicrobial target. Developing BfmR inhibitors may propel a new therapeutic direction for intractable infection of resistant strains.

Kumujan B suppresses TNF-α-induced inflammatory response and alleviates experimental colitis in mice.

Treatments of inflammatory bowel disease (IBD) are diverse, but their efficacy is limited, and it is therefore urgent to find better therapies. Controlling mucosal inflammation is a must in IBD drug treatment. The occurrence of anti-tumor necrosis factor α (TNF-α) monoclonal antibodies has provided a safer and more efficacious therapy.

A flexible data-free framework for structure-based drug design with reinforcement learning.

Contemporary structure-based molecular generative methods have demonstrated their potential to model the geometric and energetic complementarity between ligands and receptors, thereby facilitating the design of molecules with favorable binding affinity and target specificity. Despite the introduction of deep generative models for molecular generation, the atom-wise generation paradigm that partially contradicts chemical intuition limits the validity and synthetic accessibility of the generated molecules. Additionally, the dependence of deep learning models on large-scale structural data has hindered their adaptability across different targets.

Multi-Dimensional Comparison of the Impact Mechanism of the Self-Rated Health Status of Urban and Rural Residents in Chinese Social Environments.

Self-rated health status (SRHS) reflects individuals' social environment, and the difference between urban and rural areas in China further highlights the impact of social environment on health. This paper aimed to systematically analyze and compare the impact mechanism of the SRHS of urban and rural residents from multiple dimensions, i.e.

Double-Balanced Loss for Imbalanced Colorectal Lesion Classification.

Colorectal cancer has a high incidence rate in all countries around the world, and the survival rate of patients is improved by early detection. With the development of object detection technology based on deep learning, computer-aided diagnosis of colonoscopy medical images becomes a reality, which can effectively reduce the occurrence of missed diagnosis and misdiagnosis. In medical image recognition, the assumption that training samples follow independent identical distribution (IID) is the key to the high accuracy of deep learning.

Boosting Protein-Ligand Binding Pose Prediction and Virtual Screening Based on Residue-Atom Distance Likelihood Potential and Graph Transformer.

The past few years have witnessed enormous progress toward applying machine learning approaches to the development of protein-ligand scoring functions. However, the robust performance and wide applicability of scoring functions remain a big challenge for increasing the success rate of docking-based virtual screening. Herein, a novel scoring function named RTMScore was developed by introducing a tailored residue-based graph representation strategy and several graph transformer layers for the learning of protein and ligand representations, followed by a mixture density network to obtain residue-atom distance likelihood potential.

Structural view on the role of the TRD loop in regulating DNMT3A activity: a molecular dynamics study.

DNA methyltransferase 3A (DNMT3A) has been regarded as a potential epigenetic target for the development of cancer therapeutics. A number of DNMT3A inhibitors have been reported, but most of them do not have good potency, high selectivity and/or low cytotoxicity. It has been suggested that a non-conserved region around the target recognition domain (TRD) loop is implicated in the DNMT3A activity under the allosteric regulation of the ATRX-DNMT3-DNMT3L (ADD) domain, but the molecular mechanism of the regulation of the TRD loop on the DNMT3A activity needs to be elucidated.

Organic Compound Synthetic Accessibility Prediction Based on the Graph Attention Mechanism.

Accurate estimation of the synthetic accessibility of small molecules is needed in many phases of drug discovery. Several expert-crafted scoring methods and descriptor-based quantitative structure-activity relationship (QSAR) models have been developed for synthetic accessibility assessment, but their practical applications in drug discovery are still quite limited because of relatively low prediction accuracy and poor model interpretability. In this study, we proposed a data-driven interpretable prediction framework called GASA (Graph Attention-based assessment of Synthetic Accessibility) to evaluate the synthetic accessibility of small molecules by distinguishing compounds to be easy- (ES) or hard-to-synthesize (HS).

White-Light Endoscopic Colorectal Lesion Detection Based on Improved YOLOv5.

As an effective tool for colorectal lesion detection, it is still difficult to avoid the phenomenon of missed and false detection when using white-light endoscopy. In order to improve the lesion detection rate of colorectal cancer patients, this paper proposes a real-time lesion diagnosis model (YOLOv5x-CG) based on YOLOv5 improvement. In this diagnostic model, colorectal lesions were subdivided into three categories: micropolyps, adenomas, and cancer.

Spiroarborin, an -Clerodane Homodimer from as an Inhibitor of the Eleven-Nineteen Leukemia (ENL) Protein by Targeting the YEATS Domain.

A spiro -clerodane homodimer with a rare 6/6/6/6/6-fused pentacyclic scaffold, spiroarborin (), together with four new monomeric analogues (-), were isolated from . Their structures were elucidated by comprehensive spectroscopic data analysis, quantum-chemical calculations, and X-ray diffraction. A plausible biosynthetic pathway of was proposed, and a biomimetic synthesis of its derivative was accomplished.

Origin and Enrichment of Vanadium in the Lower Cambrian Black Shales, South China.

The Lower Cambrian black shales of the Sansui vanadium deposits, located in South China, host a thin accumulation of Ni, Mo, V, and platinum group of elements (PGE). However, among them, the origin of V-bearing deposits remains controversial. To characterize the enrichment process of V-bearing deposits, samples of the mineralized layer and surrounding rocks from the Sansui area, South China, were investigated through bulk geochemical analysis and scanning electron microscopy (SEM) and energy dispersive spectrometry (EDS) analyses.

Novel clerodane-type diterpenoid Cintelactone A suppresses lipopolysaccharide -induced inflammation by promoting ubiquitination, proteasomal degradation of TRAF6.

Cellular inflammation is the underlying cause of several diseases and development of a safe and effective anti-inflammatory drug is need-of-the hour for treatment of diseases like lung inflammation. Callicarpa integerrima Champ. is a well-known herbal medicine with hemostatic and anti-inflammatory functions.

CovalentInDB: a comprehensive database facilitating the discovery of covalent inhibitors.

Inhibitors that form covalent bonds with their targets have traditionally been considered highly adventurous due to their potential off-target effects and toxicity concerns. However, with the clinical validation and approval of many covalent inhibitors during the past decade, design and discovery of novel covalent inhibitors have attracted increasing attention. A large amount of scattered experimental data for covalent inhibitors have been reported, but a resource by integrating the experimental information for covalent inhibitor discovery is still lacking.

PROTAC-DB: an online database of PROTACs.

Proteolysis-targeting chimeras (PROTACs), which selectively degrade targeted proteins by the ubiquitin-proteasome system, have emerged as a novel therapeutic technology with potential advantages over traditional inhibition strategies. In the past few years, this technology has achieved substantial progress and two PROTACs have been advanced into phase I clinical trials. However, this technology is still maturing and the design of PROTACs remains a great challenge.

Application of Deep Learning for Early Screening of Colorectal Precancerous Lesions under White Light Endoscopy.

Methods: We collected and sorted out the white light endoscopic images of some patients undergoing colonoscopy. The convolutional neural network model is used to detect whether the image contains lesions: CRC, colorectal adenoma (CRA), and colorectal polyps. The accuracy, sensitivity, and specificity rates are used as indicators to evaluate the model.

Luteolin-7-methylether from Leonurus japonicus inhibits estrogen biosynthesis in human ovarian granulosa cells by suppression of aromatase (CYP19).

Leonurus japonicus (motherwort) has been widely used to treat gynecological disorders, in which estrogen is often dysregulated, for a long time in China and other Asian countries. However, the chemical constituents and mechanisms underlying the activity of this medicinal plant are not fully understood. Seventeen of forty-six tested natural products from L.

Comprehensive Evaluation of Fourteen Docking Programs on Protein-Peptide Complexes.

A large number of protein-protein interactions (PPIs) are mediated by the interactions between proteins and peptide segments binding partners, and therefore determination of protein-peptide interactions (PpIs) is quite crucial to elucidate important biological processes and design peptides or peptidomimetic drugs that can modulate PPIs. Nowadays, as a powerful computation tool, molecular docking has been widely utilized to predict the binding structures of protein-peptide complexes. However, although a number of docking programs have been available, the systematic study on the assessment of their performance for PpIs has never been reported.

Combined strategies in structure-based virtual screening.

The identification and optimization of lead compounds are inalienable components in drug design and discovery pipelines. As a powerful computational approach for the identification of hits with novel structural scaffolds, structure-based virtual screening (SBVS) has exhibited a remarkably increasing influence in the early stages of drug discovery. During the past decade, a variety of techniques and algorithms have been proposed and tested with different purposes in the scope of SBVS.

Triterpenoids from : A Class of Sensitizers of FLC-Resistant to Fluconazole.

Fungal drug resistance is a major health threat, and reports of clinical resistance worldwide are becoming increasingly common. In a research program to discover new molecules to help overcome this problem, 14 new lanostane-type triterpenoids, gibbosicolids A-G (-) and gibbosic acids I-O (-), were isolated from the fruiting bodies of , along with seven known triterpenoid derivatives. These compounds featured high levels of oxidation, epimerization, and γ-lactonization.

Premnafulvol A: A Diterpenoid with a 6/5/7/3-Fused Tetracyclic Core and Its Biosynthetically Related Analogues from Premna fulva.

Premnafulvol A (1), a unique diterpenoid featuring a 6/5/7/3-fused tetracyclic carbon skeleton, with three biosynthetically related analogues, premnafulvols B-D (2-4), were isolated from the aerial parts of Premna fulva. Structures of 1-4 were established by a combination of extensive spectroscopic analyses, quantum chemical calculations, and X-ray crystallography. Plausible biosynthetic pathways of 1-4 were proposed.

Cirsitakaoside isolated from Premna szemaoensis reduces LPS-induced inflammatory responses in vitro and in vivo.

Cirsitakaoside is a natural compound isolated from Premna szemaoensis. However, the anti-inflammatory effects of cirsitakaoside are poorly understood. We investigated the anti-inflammatory action of cirsitakaoside in lipopolysaccharide (LPS)-stimulated macrophages and mice in vivo.