A simple, manual method for predicting the highest intensity charge states (HICS) of denatured protein ions generated by electrospray ionization based on inspection of the proteins' amino acid sequence is proposed. The HICS is accurately predicted by identifying groupings of nearby basic amino acids in the positive mode or acidic amino acid residues in the negative mode. The method assumes that the likelihood of having more than one charge per group becomes less likely due to Coulombic repulsion of like charges. It is shown empirically that a spacing of at least three noncharged residues is required between charged amino acids for the charge state with the highest intensity. Verification of this method is presented, and its limitations are identified. It is fast, inexpensive, and provides similar, although less detailed, information as state-of-the-art methods that rely on computational calculations. With a few exceptions, the highest intensity charge states were predicted to an average of one charge state of the experimental data. For those proteins whose HICS were not accurately estimated, the experimental values fell short of the predictions. Upon reduction of the disulfide bonds of these proteins, the experimental HICS became closer to the predicted values, suggesting that charging lower than the prediction can be attributed to conformational inflexibility of those proteins.
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PLoS One
January 2025
Department of Developmental Epileptology, Institute of Physiology, Czech Academy of Sciences, Prague, Czech Republic.
Seizures elicited by corneal 6-Hz stimulation are widely acknowledged as a model of temporal lobe seizures. Despite the intensive research in rodents, no studies hint at this model in developing animals. We focused on seven age groups of both male and female rats.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Computer Science, National Textile University, Faisalabad, Pakistan.
Accurate diagnosis of pancreatic cancer using CT scan images is critical for early detection and treatment, potentially saving numerous lives globally. Manual identification of pancreatic tumors by radiologists is challenging and time-consuming due to the complex nature of CT scan images and variations in tumor shape, size, and location of the pancreatic tumor also make it challenging to detect and classify different types of tumors. Thus, to address this challenge we proposed a four-stage framework of computer-aided diagnosis systems.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
USC Keck School of Medicine, Los Angeles, CA, USA.
Background: Human Apolipoprotein (APOE) has three isoforms, ε2, ε3, and ε4 among which ε4 (APOE4) confers the highest risk for late-onset Alzheimer's disease (AD). APOE4 is also the most prone to aggregate among APOE isoforms. Current evidence strongly suggests that APOE aggregation leads to neuronal dysfunction and eventually to AD.
View Article and Find Full Text PDFFront Fungal Biol
December 2024
Water Systems and Biotechnology Institute, Faculty of Natural Sciences and Technology, Riga Technical University, Riga, Latvia.
The growing demand for novel enzyme producers to meet industrial and environmental needs has driven interest in lignocellulose-degrading fungi. In this study, lignocellulolytic enzyme production capabilities of environmental fungal isolates collected from boreal coniferous and nemoral summer green deciduous forests were investigated, using Congo Red, ABTS, and Azure B as indicators of cellulolytic and ligninolytic enzyme productions. Through qualitative and quantitative assays, the study aimed to identify promising species for lignocellulose-degrading enzyme secretion and assess their potential for biotechnological applications.
View Article and Find Full Text PDFFront Endocrinol (Lausanne)
January 2025
Department of Endocrinology, Huai'an Hospital Affiliated to Xuzhou Medical University and Huai'an Second People's Hospital, Huai'an, Jiangsu, China.
Objectives: To examine the association between the age at onset of diabetes and the risk of all-cause mortality in a population of individuals diagnosed with type 2 diabetes mellitus (T2DM) and to identify risk factors associated with all-cause mortality in young-onset T2DM (YOD) patients in China.
Methods: This study utilized a cohort of 9759 patients who were diagnosed with T2DM and who were registered and enrolled in the National Basic Public Health Service Management Program in Qinghe District (now Qingjiangpu District) and Huai'an District, Huai'an City, Jiangsu Province, China. The patients were observed from November 2013 to July 2014, and all-cause mortality data were obtained by comprehensive matching with the Huai'an City Resident Mortality Database as of December 31, 2019.
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