More than twenty years ago the reverse vaccinology paradigm came to light trying to design new vaccines based on the analysis of genomic information in order to select those pathogen peptides able to trigger an immune response. In this context, focusing on the proteome of Trypanosoma cruzi, we investigated the link between the probabilities for pathogen peptides to be presented on a cell surface and their distance from human self. We found a reasonable but, as far as we know, undiscovered property: the farther the distance between a peptide and the human-self the higher the probability for that peptide to be presented on a cell surface. We also found that the most distant peptides from human self bind, on average, a broader collection of HLAs than expected, implying a potential immunological role in a large portion of individuals. Finally, introducing a novel quantitative indicator for a peptide to measure its potential immunological role, we proposed a pool of peptides that could be potential epitopes and that can be suitable for experimental testing. The software to compute peptide classes according to the distance from human self is free available at http://www.iasi.cnr.it/~dsantoni/nullomers.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721184 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0243285 | PLOS |
Cureus
December 2024
Department of Diagnostic Imaging and Radiotherapy, Kulliyyah of Allied Health Sciences, International Islamic University Malaysia, Kuantan Campus, Kuantan, MYS.
In abdominal X-ray examinations, radiosensitive organs such as the gonads within or near the imaging region are at risk of radiation exposure. Minimizing the dose to these organs is crucial to reducing unnecessary radiation. This study utilized optically stimulated luminescence dosimeters (OSLDs) to measure the radiation dose to the male gonads at varying kilovoltage peak (kVp) settings while keeping the milliampere-seconds (mAs) constant across different radiographic projections.
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School of Economics and Management, Anhui University of Chinese Medicine, Hefei, China.
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Pabellón Nacional de la Biodiversidad, Departamento de Zoología, Instituto de Biología Universidad Nacional Autónoma de México Ciudad de México Mexico.
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Department of Plastic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Objective: Post-surgical lip symmetry assessment is a key indicator of cleft repair success. Traditional methods rely on distances between anatomical landmarks, which are impractical for video analysis and overlook texture and appearance. We propose an artificial intelligence (AI) approach to automate this process, analyzing lateral lip morphology for a quantitative symmetry evaluation.
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National Centre for Healthcare Research & Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy.
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