It is widely suggested that a eukaryotic mRNA typically contains one translation start site and encodes a single functional protein product. However, according to current points of view on translation initiation mechanisms, eukaryotic ribosomes can recognize several alternative translation start sites and the number of experimentally verified examples of alternative translation is growing rapidly. Also, the frequent occurrence of alternative translation events and their functional significance are supported by the results of computational evaluations. The functional role of alternative translation and its contribution to eukaryotic proteome complexity are discussed.
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http://dx.doi.org/10.1002/bies.20771 | DOI Listing |
Sci Rep
December 2024
Department of Life Sciences, College of Life Sciences, National Chung Hsing University, Kuo Kuang Rd., Taichung, 402, Taiwan.
Hepatocellular carcinoma (HCC) constitutes 90% of liver cancer cases and ranks as the third leading cause of cancer-related mortality, necessitating urgent development of alternative therapies. Lactoferrin (LF), a natural iron-binding glycoprotein with reported anticancer effects, is investigated for its potential in liver cancer treatment, an area with limited existing studies. This study focuses on evaluating LF's anti-liver cancer effects on HCC cells and assessing the preventive efficacy of oral LF administration in a murine model.
View Article and Find Full Text PDFMol Cancer
December 2024
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Background: Posttranslational modifications (PTMs) play critical roles in hepatocellular carcinoma (HCC). However, the locations of PTM-modified sites across protein secondary structures and regulatory patterns in HCC remain largely uncharacterized.
Methods: Total proteome and nine PTMs (phosphorylation, acetylation, crotonylation, ubiquitination, lactylation, N-glycosylation, succinylation, malonylation, and β-hydroxybutyrylation) in tumor sections and paired normal adjacent tissues derived from 18 HCC patients were systematically profiled by 4D-Label free proteomics analysis combined with PTM-based peptide enrichment.
Int J Biol Macromol
December 2024
Faculty of Medical Engineering, National University of Science and Technology Politehnica Bucharest, Gheorghe Polizu 1-7, 011061 Bucharest, Romania; Advanced Polymer Materials Group, University Politehnica of Bucharest, Gheorghe Polizu 1-7, 011061 Bucharest, Romania; ebio-Hub Research Centre, University Politehnica of Bucharest-Campus, Iuliu Maniu 6, 061344 Bucharest, Romania. Electronic address:
Multiple myeloma (MM), a hematological malignancy which affects the monoclonal plasma cells in the bone marrow, is in rising incidence around the world, accounting for approximately 2 % of newly diagnosed cancer cases in the US, Australia, and Western Europe. Despite the progress made in the last few years in the available therapeutic options (e.g.
View Article and Find Full Text PDFInt J Med Inform
December 2024
Chongqing Cancer Multiomics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing 400030, China. Electronic address:
Background: With advancements in healthcare, traditional VTE risk assessment tools are increasingly insufficient to meet the demands of high-quality care, underscoring the need for innovative and specialized assessment methods.
Objective: Owing to the remarkable success of machine learning in supervised learning and disease prediction, our objective is to develop a reliable and efficient model for assessing VTE risk by leveraging the fundamental data and clinical characteristics of colorectal cancer patients within our medical facility.
Methods: Six commonly used machine learning algorithms were utilized in our study to predict the occurrence of VTE in patients with rectal cancer.
EBioMedicine
December 2024
Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Nanhu Brain-Computer Interface Institute, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory of Precision Psychiatry, Hangzhou, 310003, China; Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China; Brain Research Institute of Zhejiang University, Hangzhou, 310058, China; MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University School of Medicine, Hangzhou, 310058, China; Department of Psychology and Behavioral Sciences, Graduate School, Zhejiang University, Hangzhou, 310058, China. Electronic address:
Background: Increasing evidence suggests a complex interplay between psychiatric disorders and metabolic dysregulations. However, most research has been limited to specific disorder pairs, leaving a significant gap in our understanding of the broader psycho-metabolic nexus.
Methods: This study leveraged large-scale cohort data and genome-wide association study (GWAS) summary statistics, covering 8 common psychiatric disorders and 43 metabolic traits.
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