Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jtos.2024.05.001 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Decoding the chicken gastrointestinal microbiome.
BMC Microbiol
January 2025
School of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, UK.
Metataxonomic studies have underpinned a vast understanding of microbial communities residing within livestock gastrointestinal tracts, albeit studies have often not been combined to provide a global census. Consequently, in this study we characterised the overall and common 'core' chicken microbiota associated with the gastrointestinal tract (GIT), whilst assessing the effects of GIT site, bird breed, age and geographical location on the GIT resident microbes using metataxonomic data compiled from studies completed across the world. Specifically, bacterial 16S ribosomal DNA sequences from GIT samples associated with various breeds, differing in age, GIT sites (caecum, faeces, ileum and jejunum) and geographical location were obtained from the Sequence Read Archive and analysed using the MGnify pipeline.
View Article and Find Full Text PDFLeveraging Segment Anything Model (SAM) for Weld Defect Detection in Industrial Ultrasonic B-Scan Images.
Sensors (Basel)
January 2025
Phillip M. Drayer Electrical Engineering Department, Lamar University, Beaumont, TX 77705, USA.
Automated ultrasonic testing (AUT) is a critical tool for infrastructure evaluation in industries such as oil and gas, and, while skilled operators manually analyze complex AUT data, artificial intelligence (AI)-based methods show promise for automating interpretation. However, improving the reliability and effectiveness of these methods remains a significant challenge. This study employs the Segment Anything Model (SAM), a vision foundation model, to design an AI-assisted tool for weld defect detection in real-world ultrasonic B-scan images.
View Article and Find Full Text PDFInnovative breast cancer detection using a segmentation-guided ensemble classification framework.
Biomed Eng Lett
January 2025
Electronics and Communication Engineering, IFET College of Engineering, Villupuram, Tamilnadu India.
Unlabelled: Breast cancer (BC) remains a significant global health issue, necessitating innovative methodologies to improve early detection and diagnosis. Despite the existence of intelligent deep learning models, their efficacy is often limited due to the oversight of small-sized masses, leading to false positive and false negative outcomes. This research introduces a novel segmentation-guided classification model developed to increase BC detection accuracy.
View Article and Find Full Text PDFLow-input redoxomics facilitates global identification of metabolic regulators of oxidative stress in the gut.
Signal Transduct Target Ther
January 2025
National Clinical Research Center for Geriatrics, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Oxidative stress plays a crucial role in organ aging and related diseases, yet the endogenous regulators involved remain largely unknown. This work highlights the importance of metabolic homeostasis in protecting against oxidative stress in the large intestine. By developing a low-input and user-friendly pipeline for the simultaneous profiling of five distinct cysteine (Cys) states, including free SH, total Cys oxidation (Sto), sulfenic acid (SOH), S-nitrosylation (SNO), and S-glutathionylation (SSG), we shed light on Cys redox modification stoichiometries and signaling with regional resolution in the aging gut of monkeys.
View Article and Find Full Text PDFIntegrative multi-omics analysis reveals the contribution of neoVTX genes to venom diversity of Synanceia verrucosa.
BMC Genomics
December 2024
Center for Evolution and Conservation Biology, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China.
Background: Animal venom systems are considered as valuable model for investigating the molecular mechanisms underlying phenotypic evolution. Stonefish are the most venomous and dangerous fish because of severe human envenomation and occasionally fatalities, whereas the genomic background of their venom has not been fully explored compared with that in other venomous animals.
Results: In this study, we followed modern venomic pipelines to decode the Synanceia verrucosa venom components.
Want 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!