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Background: Persistent symptoms extending beyond the acute phase of SARS-CoV-2 infection, known as Post-COVID condition (PCC), continue to impact many individuals years after the COVID-19 pandemic began. This highlights an urgent need for a deeper understanding and effective treatments. While significant progress has been made in understanding the acute phase of COVID-19 through omics-based approaches, the proteomic alterations linked to the long-term effects of the infection remain underexplored. This study aims to investigate these proteomic changes and develop a method for stratifying disease severity., Methods: Using Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH-MS) technology, we performed comprehensive proteomic profiling of blood samples from 65 PCC patients. Both plasma and pellet (cellular components) fractions were analyzed to capture a wide array of proteomic changes associated with PCC., Results: Proteomic profiling revealed distinct differences between symptomatic and asymptomatic PCC patients. In the plasma fraction, symptomatic patients exhibited significant upregulation of proteins involved in coagulation, immune response, oxidative stress, and various metabolic processes, while certain immunoglobulins and proteins involved in cellular stress responses were downregulated. In the pellet fraction, symptomatic patients showed upregulation of proteins related to immune response, coagulation, oxidative stress, and metabolic enzymes, with downregulation observed in components of the complement system, glycolysis enzymes, and cytoskeletal proteins. A key outcome was the development of a novel severity scale based on the concentration of identified proteins, which correlated strongly with the clinical symptoms of PCC. This scale, derived from unsupervised clustering analysis, provides precise quantification of PCC severity, enabling effective patient stratification., Conclusions: The identified proteomic alterations offer valuable insights into the molecular mechanisms underlying PCC, highlighting potential biomarkers and therapeutic targets. This research supports the development of tailored clinical interventions to alleviate persistent symptoms, ultimately enhancing patient outcomes and quality of life. The quantifiable measure of disease severity aids clinicians in understanding the condition in individual patients, facilitating personalized treatment plans and accurate monitoring of disease progression and response to therapy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: The ongoing issues with post-COVID conditions (PCC), where symptoms persist long after the initial infection, highlight the need for research into blood lipid changes in these patients. While most studies focus on the acute phase of COVID-19, there's a significant lack of information on the lipidomic changes that occur in the later stages of the disease. Addressing this knowledge gap is critical for understanding the long-term effects of COVID-19 and could be key to developing personalized treatments for those suffering from PCC., Methods: We employed untargeted lipidomics to analyze plasma samples from 147 PCC patients, assessing nearly 400 polar lipids. Data mining (DM) and machine learning (ML) tools were utilized to decode the results and ascertain significant lipidomic patterns., Results: The study uncovered substantial changes in various lipid subclasses, presenting a detailed profile of the polar lipid fraction in PCC patients. These alterations correlated with ongoing inflammation and immune response. Notably, there were elevated levels of lysophosphatidylglycerols (LPGs) and phosphatidylethanolamines (PEs), and reduced levels of lysophosphatidylcholines (LPCs), suggesting these as potential lipid biomarkers for PCC. The lipidomic signatures indicated specific anionic lipid changes, implicating antimicrobial peptides (AMPs) in inflammation. Associations between particular medications and symptoms were also suggested. Classification models, such as multinomial regression (MR) and random forest (RF), successfully differentiated between symptomatic and asymptomatic PCC groups using lipidomic profiles., Conclusions: The study's groundbreaking discovery of specific lipidomic disruptions in PCC patients marks a significant stride in the quest to comprehend and combat this condition. The identified lipid biomarkers not only pave the way for novel diagnostic tools but also hold the promise to tailor individualized therapeutic strategies, potentially revolutionizing the clinical approach to managing PCC and improving patient care., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Common bean (Phaseolus vulgaris L.) is the most important grain legume for direct human consumption. Proteomic studies in legumes have increased significantly in the last years but few studies have been performed to date in P. vulgaris. We report here a proteomic analysis of bean seeds by two-dimensional electrophoresis (2-DE). Three different protein extraction methods (TCA-acetone, phenol and the commercial clean-up kit) were used taking into account that the extractome can have a determinant impact on the level of quality of downstream protein separation and identification. To demonstrate the quality of the 2-DE analysis, a selection of 50 gel spots was used in protein identification by mass spectrometry (MALDI-TOF MS and MALDI-TOF/TOF). The results showed that a considerable proportion of spots (70%) were identified in spite of incomplete genome/protein databases for bean and other legume species. Most identified proteins corresponded to storage protein, carbohydrate metabolism, defense and stress response, including proteins highly abundant in the seed of P. vulgaris such as the phaseolin, the phytohemagglutinin and the lectin-related α-amylase inhibitor., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Low expression of the CD3zeta chain has been reported in patients with cancer and it has been suggested that tumor-derived factors are involved in its downregulation. The expression of CD3zeta chain was measured in T-cell lines from patients with gastric adenocarcinoma and healthy volunteers and grown in vitro for several months and, hence, in the absence of any tumor-derived factors. T-cell lines of mucosal origin were obtained by Herpesvirus saimiri transformation from gastric cancer patients. The expression of CD3zeta and CD3epsilon was measured by flow cytometry and Western-blot analysis. Calcium mobilization and apoptosis rate were also measured. The levels of CD3zeta, but not CD3epsilon, chain on the cell surface were significantly reduced in T-cell lines derived from patients with gastric cancer when cultured in the absence of IL-2. Western-blot analysis of total cell extracts or lipid raft fractions confirmed this finding. Calcium mobilization, a measure of signal transduction, was reduced in T cell lines from patients with gastric cancer. We conclude that T cells from patients with cancer express lower levels of CD3zeta. This downregulation is not caused by a direct effect of tumor-derived factors but, rather, it appears to be inherent to the patient cells. The low CD3zeta expression would render T lymphocytes unable to control the growth of tumor cells.