It was found that using surnames as genetical markers in rural Russian populations gives adequate results under conditions of working on the area not extending over the territory of 2 or 3 adjacent regions. Schematic drawings of genetic landscapes in 4 regions of the Kirov district and in 2 regions of the Adyg district are presented. Analysis of anomalous features of equidistant lines has been performed.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Spreading dynamics of information on online social networks.
Proc Natl Acad Sci U S A
January 2025
Department of Statistics and Data Science, College of Science, Southern University of Science and Technology, Shenzhen 518055, China.
Social media is profoundly changing our society with its unprecedented spreading power. Due to the complexity of human behaviors and the diversity of massive messages, the information-spreading dynamics are complicated, and the reported mechanisms are different and even controversial. Based on data from mainstream social media platforms, including WeChat, Weibo, and Twitter, cumulatively encompassing a total of 7.
View Article and Find Full Text PDFSickle Cell Anemia and Inflammation: A Review of Stones and Landmarks Paving the Road in the Last 25 Years.
Hematol Rep
January 2025
Laboratory of Immunobiology and Immunogenetics, Post Graduation Program in Genetics and Molecular Biology (PPGBM), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre 91501-970, Brazil.
A quarter of a century ago, sickle cell disease (SCD) was mainly viewed as a typical genetic disease inherited as a classical Mendelian trait. Therefore, the main focus concerning SCD was on diagnosis, meaning, genotyping, and identification of homozygous and heterozygous individuals carrying the relevant HbS mutant allele. Nowadays, it is well established that sickle cell disease is indeed the result of homozygosis for the HbS variant, although this single feature is not capable of explaining the highly diverse clinical presentation of SCD.
View Article and Find Full Text PDFBulk and single-cell transcriptome revealed the metabolic heterogeneity in human glioma.
Heliyon
January 2025
Department of Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China.
Background: Emerging perspectives on tumor metabolism reveal its heterogeneity, a characteristic yet to be fully explored in gliomas. To advance therapies targeting metabolic processes, it is crucial to uncover metabolic differences and identify distinct metabolic subtypes. Therefore, we aimed to develop a classification system for gliomas based on the enrichment levels of four key metabolic pathways: glutaminolysis, glycolysis, the pentose phosphate pathway, and fatty acid oxidation.
View Article and Find Full Text PDFCharacterization of a 4'-O-rhamnosyltransferase and de novo biosynthesis of bioactive steroidal triglycosides from Paris polyphylla.
Plant Commun
January 2025
Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, P. R. China. Electronic address:
Steroidal saponins in Paris polyphylla featuring complicated sugar chains exhibit notable biological activities, but the sugar chain biosynthesis is still not fully understood. Here, we identified a 4'-O-rhamnosyltransferase (UGT73DY2) from P. polyphylla, which catalyzes the 4'-O-rhamnosylation of polyphyllins V and VI, producing dioscin and pennogenin 3-O-β-chacotrioside, respectively.
View Article and Find Full Text PDFMfgnn: Multi-Scale Feature-Attentive Graph Neural Networks for Molecular Property Prediction.
J Comput Chem
January 2025
College of Medical Information Engineering, Guangdong Pharmaceutical University, Guangzhou, Guangdong, China.
In the realm of artificial intelligence-driven drug discovery (AIDD), accurately predicting the influence of molecular structures on their properties is a critical research focus. While deep learning models based on graph neural networks (GNNs) have made significant advancements in this area, prior studies have primarily concentrated on molecule-level representations, often neglecting the impact of functional group structures and the potential relationships between fragments on molecular property predictions. To address this gap, we introduce the multi-scale feature attention graph neural network (MfGNN), which enhances traditional atom-based molecular graph representations by incorporating fragment-level representations derived from chemically synthesizable BRICS fragments.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!