TADB2.0 (http://bioinfo-mml.sjtu.edu.cn/TADB2/) is an updated database that provides comprehensive information about bacterial type II toxin-antitoxin (TA) loci. Compared with the previous version, the database refined and the new data schema is employed. With the aid of text mining and manual curation, it recorded 6193 type II TA loci in 870 replicons of bacteria and archaea, including 105 experimentally validated TA loci. In addition, the newly developed tool TAfinder combines the homolog searches and the operon structure detection, allowing the prediction for type II TA pairs in bacterial genome sequences. It also helps to investigate the genomic context of predicted TA loci for putative virulence factors, antimicrobial resistance determinants and mobile genetic elements via alignments to the specific public databases. Additionally, the module TAfinder-Compare allows comparing the presence of the given TA loci across the close relative genomes. With the recent updates, TADB2.0 might provide better support for understanding the important roles of type II TA systems in the prokaryotic life activities.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753263 | PMC |
http://dx.doi.org/10.1093/nar/gkx1033 | DOI Listing |
Ital J Pediatr
January 2025
Polistudium SRL, Milan, Italy.
Background: The PalliPed project is a nationwide, observational, cross-sectional study designed with the aim of providing a constantly updated national database for the census and monitoring of specialized pediatric palliative care (PPC) activities in Italy. This paper presents the results of the first monitoring phase of the PalliPed project, which was developed through the PalliPed 2022-2023 study, to update current knowledge on the provision of specialized PPC services in Italy.
Methods: Italian specialized PPC centers/facilities were invited to participate and asked to complete a self-reporting, ad-hoc, online survey regarding their clinical activity in 2022-2023, in the revision of the data initially collected in the first PalliPed study of 2021.
Updates Surg
January 2025
Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
Clinical risk prediction models are ubiquitous in many surgical domains. The traditional approach to develop these models involves the use of regression analysis. Machine learning algorithms are gaining in popularity as an alternative approach for prediction and classification problems.
View Article and Find Full Text PDFExpert Opin Biol Ther
January 2025
State Key Laboratory of Respiratory Disease, Joint International Research Laboratory of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, P.R. China.
Introduction: Clinical experience with anti-interleukin (IL)-5 biologic therapies for severe asthma has been increasing, alongside deeper and broader research focusing on the role of IL-5 and the IL-5 targeted mepolizumab. This review aims to provide an update of the evidence on the role of IL-5 and mepolizumab, with discussions of the benefits of mepolizumab and its future potential, to promote the comprehension of the pathophysiology and therapeutic approaches to asthma.
Areas Covered: For this narrative review, we conducted a database search in PubMed and Embase using the keywords 'IL-5' and 'mepolizumab,' focusing on randomized controlled trials and real-world studies up to September 2024.
J Clin Nurs
January 2025
The Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel.
Background: Patient self-care is established as improving outcomes, yet acute care in hospitals is provided such that patients tend to be passive recipients of care. Little is known about the extent and type of patient participation in treatment care tasks in acute hospital settings.
Aims: To map and synthesise available literature on self-performance of care tasks in acute hospital settings.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!