Root-knot nematodes (RKNs) of the genus Meloidogyne pose the most significant threats to global food security due to their destructive nature as plant-parasitic nematodes. Although significant attention has been devoted to investigating the gene transcription profiling of RKNs, our understanding of the translational landscape of RKNs remains limited. In this study, we elucidated the translational landscape of Meloidogyne incognita through the integration of translatome, transcriptome and quantitative proteome analyses. Our findings revealed numerous previously unannotated translation events and refined the genome annotation. By investigating the genome-wide translational dynamics of M. incognita during parasitism, we revealed that the genes of M. incognita undergo parasitic stage-specific regulation at the translational level. Interestingly, we identified 470 micropeptides (containing fewer than 100 amino acids) with the potential to function as effectors. Additionally, we observed that the effector-coding genes in M. incognita exhibit higher translation efficiency (TE). Further analysis suggests that M. incognita has the potential to regulate the TE of effector-coding genes without simultaneous alterations in their transcript abundance, facilitating effector synthesis. Collectively, our study provides comprehensive datasets and explores the genome-wide translational landscape of M. incognita, shedding light on the contributions of translational regulation during parasitism.
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Nat Cancer
January 2025
Dept. of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany.
The diagnostic landscape of brain tumors integrates comprehensive molecular markers alongside traditional histopathological evaluation. DNA methylation and next-generation sequencing (NGS) have become a cornerstone in central nervous system (CNS) tumor classification. A limiting requirement for NGS and methylation profiling is sufficient DNA quality and quantity, which restrict its feasibility.
View Article and Find Full Text PDFNeural Netw
January 2025
School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom.
Learning from data streams that emerge from nonstationary environments has many real-world applications and poses various challenges. A key characteristic of such a task is the varying nature of the underlying data distributions over time (concept drifts). However, the most common type of data stream learning approach are ensemble approaches, which involve the training of multiple base learners.
View Article and Find Full Text PDFInt J Surg
January 2025
Department of Radiotherapy, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Cancer Hospital of Dalian University of Technology, Shenyang, China.
Gastro Hep Adv
September 2024
Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Background And Aims: Steatotic liver disease (SLD) is the most common chronic liver disease strongly associated with metabolic dysfunction, but its pathogenesis remains incompletely understood. Exploring plasma circulating metabolites may help in elucidating underlying mechanisms and identifying new biomarkers for SLD.
Methods: We examined cross-sectionally the association between plasma metabolites and SLD as well as liver enzymes using data from 4 population-based cohort studies (Rotterdam study, Avon Longitudinal Study of Parents and Children, The Insulin Resistance Atherosclerosis Family Study, and Study of Latinos).
Stem Cell Res Ther
January 2025
Department of Pulmonary and Critical Care Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Chronic pulmonary diseases pose a prominent health threat globally owing to their intricate pathogenesis and lack of effective reversal therapies. Nowadays, lung transplantation stands out as a feasible treatment option for patients with end-stage lung disease. Unfortunately, the use of this this option is limited by donor organ shortage and severe immunological rejection reactions.
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