The influence of data evaluation parameters on qualitative and quantitative results of untargeted shotgun profiling of enzymatic and nonenzymatic post-translational modifications (PTMs) was investigated in a model of bovine whey protein α-lactalbumin heated with lactose. Based on the same raw data, individual adjustments to the protein database and enzyme settings of PEAKS studio software increased the identification rate from 27 unmodified peptides to 48 and from 322 peptides in total to 535. The qualitative and quantitative reproducibility was also assessed based on 18 measurements of one sample across three batches. A total of 570 peptides were detected. While 89 peptides were identified in all measurements, the majority of peptides (161) were detected only once and mostly based on nonindicative spectra. The reproducibility of label-free quantification (LFQ) in six measurements of the same sample was similar after processing the data by either the PTM algorithm or the LFQ algorithm. In both cases, about one-third of the peptides showed a coefficient of variation of above 20%. However, the LFQ algorithm increased the number of quantified peptides from 75 to 179. Data are available at the PRIDE Archive with the data set identifier PXD050363.
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HGG Adv
January 2025
Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Québec, Canada; Department of Human Genetics, McGill University, Montréal, Québec, Canada; 5 Prime Sciences Inc, Montréal, Quebec, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada; Department of Medicine, McGill University, Montréal, Québec, Canada; Department of Twin Research, King's College London, London, UK. Electronic address:
Identifying novel, high-yield drug targets is challenging and often results in a high failure rate. However, recent data indicates that leveraging human genetic evidence to identify and validate these targets significantly increases the likelihood of success in drug development. Two recent papers from Open Targets claimed that around half of FDA-approved drugs had targets with direct human genetic evidence.
View Article and Find Full Text PDFPathogens
January 2025
Plant Omics Laboratory, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Robert Sobukwe Road, Bellville 7535, South Africa.
head blight (FHB) is a major disease affecting wheat production worldwide, caused by multiple species. In this study, seven strains were isolated from wheat fields across the Western Cape region of South Africa and identified through phylogenetic analysis. The strains were classified into three species complexes: the species complex (FGSC), species complex (FIESC), and species complex (FTSC).
View Article and Find Full Text PDFPathogens
January 2025
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, UK.
The domestic dog () is a competent host for () infection but no ante mortem diagnostic tests have been fully validated for this species. The aim of this study was to compare the performance of ante mortem diagnostic tests across samples collected from dogs considered to be at a high or low risk of sub-clinical infection. We previously tested a total of 164 dogs at a high risk of infection and here test 42 dogs at a low risk of infection and 77 presumed uninfected dogs with a combination of cell-based and/or serological diagnostic assays previously described for use in non-canid species.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Psychological and Cognitive Sciences, Tsinghua University, Beijing 100084, China.
The objective identification of depression using physiological data has emerged as a significant research focus within the field of psychiatry. The advancement of wearable physiological measurement devices has opened new avenues for the identification of individuals with depression in everyday-life contexts. Compared to other objective measurement methods, wearables offer the potential for continuous, unobtrusive monitoring, which can capture subtle physiological changes indicative of depressive states.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Optical Engineering, Utsunomiya University, 7-2-1 Yoto, Utsunomiya 321-8585, Japan.
We describe the various steps of a gas imaging algorithm developed for detecting, identifying, and quantifying gas leaks using data from a snapshot infrared spectral imager. The spectral video stream delivered by the hardware allows the system to combine spatial, spectral, and temporal correlations into the gas detection algorithm, which significantly improves its measurement sensitivity in comparison to non-spectral video, and also in comparison to scanning spectral imaging. After describing the special calibration needs of the hardware, we show how to regularize the gas detection/identification for optimal performance, provide example SNR spectral images, and discuss the effects of humidity and absorption nonlinearity on detection and quantification.
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