We present a protein database search engine for the automatic identification of peptide and protein sequences using the recently introduced method of two-dimensional partial covariance mass spectrometry (2D-PC-MS). Because the 2D-PC-MS measurement reveals correlations between fragments stemming from the same or consecutive decomposition processes, the first-of-its-kind 2D-PC-MS search engine is based entirely on the direct matching of the pairs of theoretical and the experimentally detected correlating fragments, rather than of individual fragment signals or their series. We demonstrate that the high structural specificity afforded by 2D-PC-MS fragment correlations enables our search engine to reliably identify the correct peptide sequence, even from a spectrum with a large proportion of contaminant signals. While for peptides, the 2D-PC-MS correlation-matching procedure is based on complementary and internal ion correlations, the identification of intact proteins is entirely based on the ability of 2D-PC-MS to spatially separate and resolve the experimental correlations between complementary fragment ions.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/acs.analchem.1c00895 | DOI Listing |
Am J Med
January 2025
the University of Nevada, Reno School of Medicine, Reno, NV. Electronic address:
Background: A wide array of products in the category of complementary or alternative medicine products for cardiovascular disease and prevention are readily available on online retail platforms. However, a critical assessment of these products including their therapeutic claims has not been previously performed.
Methods: "Heart failure supplement" and similar terms were entered into the Amazon.
J Med Internet Res
December 2024
Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé - LIMICS, Inserm, Université Sorbonne Paris-Nord, Sorbonne Université, Paris, France.
Background: Artificial intelligence (AI) applied to real-world data (RWD; eg, electronic health care records) has been identified as a potentially promising technical paradigm for the pharmacovigilance field. There are several instances of AI approaches applied to RWD; however, most studies focus on unstructured RWD (conducting natural language processing on various data sources, eg, clinical notes, social media, and blogs). Hence, it is essential to investigate how AI is currently applied to structured RWD in pharmacovigilance and how new approaches could enrich the existing methodology.
View Article and Find Full Text PDFPLoS One
January 2025
School of Mechanical and Automotive Engineering, Anhui Polytechnic University, Wuhu, China.
In order to solve the problem of poor adaptability and robustness of the rule-based energy management strategy (EMS) in hybrid commercial vehicles, leading to suboptimal vehicle economy, this paper proposes an improved dung beetle algorithm (DBO) optimized multi-fuzzy control EMS. First, the rule-based EMS is established by dividing the efficient working areas of the methanol engine and power battery. The Tent chaotic mapping is then used to integrate strategies of cosine, Lévy flight, and Cauchy Gaussian mutation, improving the DBO.
View Article and Find Full Text PDFFront Public Health
December 2024
Institute of Psychology, University of Debrecen, Debrecen, Hungary.
Introduction: The positive impact of youth sport on physical, mental and social health has been highlighted in several research which reinforces further investigations concerning the reasons for dropout of athletes. As one of the most emergent difficulties in youth sports is to prevent athletes from dropping out, it is important to explore what factors play important part in this process. The purpose of this study was to identify barriers and challenges related to sport persistence and dropout.
View Article and Find Full Text PDFPopul Health Metr
December 2024
Bioinformatics Group, Defense Institute of Physiology and Allied Sciences, Defense Research and Development Organization, Lucknow Road, Timarpur, Delhi, India.
Seasonal variations in the environment induce observable changes in the human physiological system and manifest as various clinical symptoms in a specific human population. Our earlier studies predicted four global severe seasonal sensitive comorbid lifestyle diseases (SCLDs), namely, asthma, obesity, hypertension, and fibrosis. Our studies further indicated that the SCLD category of the human population may be maladapted or unacclimatized to seasonal changes.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!