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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011591 | PMC |
| http://dx.doi.org/10.21037/atm.2019.09.124 | DOI Listing |
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Exploring the Potential of Genome-Wide Hybridization Capture Enrichment for Forensic DNA Profiling of Degraded Bones.
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Australian Centre for Ancient DNA, The Environment Institute, School of Biological Sciences, The University of Adelaide, Adelaide, SA 5000, Australia.
Unlabelled: In many human rights and criminal contexts, skeletal remains are often the only available samples, and they present a significant challenge for forensic DNA profiling due to DNA degradation. Ancient DNA methods, particularly capture hybridization enrichment, have been proposed for dealing with severely degraded bones, given their capacity to yield results in ancient remains.
Background/objectives: This paper aims to test the efficacy of genome-wide capture enrichment on degraded forensic human remains compared to autosomal STRs analysis.
Population Structure Based on Microsatellite Length Polymorphism, Antifungal Susceptibility Profile, and Enzymatic Activity of Clinical Isolates in Russia.
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January 2025
Kashkin Research Institute of Medical Mycology, North-Western State Medical University Named after I.I. Mechnikov, 191015 Saint Petersburg, Russia.
is an emerging multidrug-resistant fungal pathogen causing nosocomial transmission and invasive infections with high mortality. This study aimed to investigate the genetic relationships, enzymatic activities, and drug-resistance profiles of isolates to evaluate the population and epidemiological diversity of candidiasis in Russia. A total of 112 clinical isolates of were analyzed from May 2017 to March 2023 in 18 hospitals across Saint Petersburg, the Leningrad Region, and Moscow.
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Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.
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View Article and Find Full Text PDFWhen multiple instance learning meets foundation models: Advancing histological whole slide image analysis.
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Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Southern Medical University, Guangzhou, China. Electronic address:
Deep multiple instance learning (MIL) pipelines are the mainstream weakly supervised learning methodologies for whole slide image (WSI) classification. However, it remains unclear how these widely used approaches compare to each other, given the recent proliferation of foundation models (FMs) for patch-level embedding and the diversity of slide-level aggregations. This paper implemented and systematically compared six FMs and six recent MIL methods by organizing different feature extractions and aggregations across seven clinically relevant end-to-end prediction tasks using WSIs from 4044 patients with four different cancer types.
View Article and Find Full Text PDFObjectives: To assess if ProMisE classifier molecular subtypes are associated with differing survival outcomes in uterine carcinosarcoma (UCS) and compare these outcomes to endometrioid endometrial cancer (EEC) tumors.
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