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| http://dx.doi.org/10.3389/fpsyg.2024.1259845 | DOI Listing |
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Linking Fire, Food Webs, and Fish in Stream Ecosystems.
Ecosystems
January 2025
Oregon State University, Department of Forest Ecosystems & Society, Corvallis, Oregon USA.
Unlabelled: As wildfire regimes shift, resource managers are concerned about potential threats to aquatic ecosystems and the species they support, especially fishes. However, predicting fish responses can be challenging because wildfires affect aquatic ecosystems via multiple pathways. Application of whole-ecosystem approaches, such as food web modeling, can act as heuristic tools that offer valuable insights that account for these different mechanisms.
View Article and Find Full Text PDFIdentification of CD8+ Immunogenic Peptides for Vaccine Design against Nipah Virus in Humans.
Iran J Public Health
December 2024
School of Biotechnology, Shri Mata Vaishno Devi University, Katra, India.
Background: Nipah virus is a pathogenic virus of ruinous zoonotic potential with inflated rate of mortality in humans.
Methods: Considering the emerging threat of this pandemic virus, the present investigation amid to design vaccine by using the bioinformatics tools such as host and virus codon usage analysis, CD8+ peptide prediction, immunogenicity/allergenicity/toxicity, MHC-I allele binding prediction and subsequent population coverage and MHC-I-peptide docking analysis.
Results: In this study (conducted in 2022 at School of Biotechnology, Katra, India), a set of 11 peptides of the structural proteins of Nipah Virus were predicted and recognized by the set of MHC-I alleles that are expressed in 92% of the global human population.
HRP-integrated CRISPR-Cas12a biosensor for rapid point-of-care detection of Langya henipavirus.
iScience
December 2024
Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), School of Laboratory Medicine, Chongqing Medical University, 1 Xueyuan Road, Chongqing 400016, China.
Global pandemic has emphasized the needs for advanced pathogen diagnosis in dealing with newly emerged infectious threats, including the Langya henipavirus (LayV). LayV, as an emerging zoonotic pathogen, has potential to cause pandemic, but lacks of rapid diagnostic tools, particularly at point-of-care level. Here, we leveraged the merits of CRISPR-Cas12a biosensing and established a highly sensitive LayV detection method.
View Article and Find Full Text PDFDevelopment of an immunodiagnostic assay for the detection of .
Turk J Biol
August 2024
Department of Agricultural Sciences and Technology, Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan.
Background/aim: (SCMV; genus and family ), poses a significant threat to global sugarcane cultivars, including those in Pakistan. The aim of this study was to develop a rapid and effective diagnostic tool for detection of SCMV, enabling timely implementation of control measures to mitigate potential yield losses.
Materials And Methods: The study focused on the in silico analysis, physicochemical properties, immunogenicity, and subcellular localization of the SCMV coat protein (CP).
Artificial intelligence in antimicrobial stewardship: a systematic review and meta-analysis of predictive performance and diagnostic accuracy.
Eur J Clin Microbiol Infect Dis
January 2025
Department of Biomedical Sciences for Health, University of Milan, Via Pascal 36, 20133, Milan, Italy.
The increasing threat of antimicrobial resistance has prompted a need for more effective antimicrobial stewardship programs (AMS). Artificial intelligence (AI) and machine learning (ML) tools have emerged as potential solutions to enhance decision-making and improve patient outcomes in AMS. This systematic review and meta-analysis aims to evaluate the impact of AI in AMS and to assess its predictive performance and diagnostic accuracy.
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