BACKGROUND: Despite secondary prevention with aspirin, patients with stable cardiovascular disease (CVD) remain at elevated long-term risk of major adverse cardiovascular events. The Cardiovascular Outcomes in People Using Anticoagulant Strategies (COMPASS) double-blind, randomized clinical trial demonstrated that aspirin plus low-dose rivaroxaban (COMPASS regime) significantly decreased the incidence of major adverse cardiovascular events by 24% compared with aspirin alone. However, the mechanisms underlying these potential synergistic/nonantithrombotic effects remain elusive. Extracellular vesicles (EVs) are crucial messengers regulating a myriad of biological/pathological processes and are highly implicated in CVD. OBJECTIVES: We hypothesized that circulating EV profiles reflect the cardioprotective properties of the COMPASS regime. METHODS: A cohort of stable CVD patients (N = 40) who participated in the COMPASS trial and were previously randomized to receive aspirin were prospectively recruited and assigned a revised regimen of open-label aspirin plus rivaroxaban. Blood samples were obtained at baseline (aspirin only) and 6-month follow-up. Plasma EV concentration, size, and origin were analyzed by nanoparticle tracking analysis and flow cytometry. EVs were enriched by ultracentrifugation for proteomic analysis. RESULTS: The COMPASS regime fundamentally altered small (<200 nm) and large (200-1000 nm) EV concentration and size compared with aspirin alone. Crucially, levels of platelet-derived and myeloperoxidase-positive EVs became significantly decreased at follow-up. Comparative proteomic characterization further revealed a significant decrease in highly proinflammatory protein expression at follow-up. CONCLUSION: The observed changes in EV subpopulations, together with the differential protein expression profiles, suggest amelioration of an underlying proinflammatory and prothrombotic state upon dual therapy, which may be of clinical relevance toward understanding the fundamental mechanism underlying the reported superior cardiovascular outcomes associated with this antithrombotic regimen.

• MeSH
• Aspirin * administration & dosage   therapeutic use   adverse effects   MeSH
• Double-Blind Method MeSH
• Extracellular Vesicles * metabolism   drug effects   MeSH
• Platelet Aggregation Inhibitors * administration & dosage   adverse effects   therapeutic use   MeSH
• Factor Xa Inhibitors * administration & dosage   adverse effects   therapeutic use   MeSH
• Cardiovascular Diseases * blood   prevention & control   drug therapy   MeSH
• Drug Therapy, Combination * MeSH
• Middle Aged MeSH
• Humans MeSH
• Inflammation Mediators blood   MeSH
• Prospective Studies MeSH
• Proteomics methods   MeSH
• Rivaroxaban * administration & dosage   MeSH
• Aged MeSH
• Thrombosis blood   prevention & control   drug therapy   MeSH
• Treatment Outcome MeSH
• Inflammation blood   MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Randomized Controlled Trial MeSH

INTRODUCTION: Amyloid precursor protein (APP) undergoes striking changes following traumatic brain injury (TBI). Considering its role in the control of gene expression, we investigated whether APP regulates transcription and translation following TBI. METHODS: We assessed brain morphology (n = 4-9 mice/group), transcriptome (n = 3 mice/group), proteome (n = 3 mice/group), and behavior (n = 17-27 mice/group) of wild-type (WT) and APP knock-out (KO) mice either untreated or 10-weeks following TBI. RESULTS: After TBI, WT mice displayed transcriptional programs consistent with late stages of brain repair, hub genes were predicted to impact translation and brain proteome showed subtle changes. APP KO mice largely replicated this transcriptional repertoire, but showed no transcriptional nor translational response to TBI. DISCUSSION: The similarities between WT mice following TBI and APP KO mice suggest that developmental APP deficiency induces a condition reminiscent of late stages of brain repair, hampering the control of gene expression in response to injury. HIGHLIGHTS: 10-weeks after TBI, brains exhibit transcriptional profiles consistent with late stage of brain repair. Developmental APP deficiency maintains brains perpetually in an immature state akin to late stages of brain repair. APP responds to TBI by changes in gene expression at a transcriptional and translational level. APP deficiency precludes molecular brain changes in response to TBI.

• MeSH
• Amyloid beta-Protein Precursor * genetics   MeSH
• Disease Models, Animal MeSH
• Brain * metabolism   pathology   MeSH
• Mice, Inbred C57BL MeSH
• Mice, Knockout MeSH
• Mice MeSH
• Brain Injuries * metabolism   genetics   pathology   MeSH
• Proteome * metabolism   MeSH
• Proteomics MeSH
• Transcriptome * MeSH
• Brain Injuries, Traumatic * metabolism   genetics   pathology   MeSH
• Animals MeSH
• Check Tag
• Male MeSH
• Mice MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

There is growing interest in the role of extracellular vesicles (EVs) in neonatal pathology. This study aimed to characterise circulating EVs following preterm birth. This single-centre prospective observational study included cord and postnatal plasma from preterm (n = 101) and full-term infants (n = 66). EVs were analysed using nanoparticle tracking analysis, flow cytometry, proteomics and procoagulant activity assay. We found changes in the concentration, size, cellular origin and proteomic content of circulating EVs in preterm infants during perinatal adaptation. To understand if these changes were related to prematurity or normal adaptation to extrauterine life, they were also investigated in term infants. There was a dramatic increase in the concentration of small and large EVs on Day 3 in the preterm group; specific subsets of platelet (CD42b+ and CD62P+), endothelial (VEGFR2) and tissue factor EVs were elevated. Differentially expressed proteins relating to haemostasis, pulmonary physiology and immunity were identified between Day 1 and 3 in preterm infants. These changes have never previously been described in a large cohort of preterm infants and differ from healthy term infants. These findings have major implications for future neonatal EV studies, particularly the timing of sample collection. Further work is required to understand the clinical implications of this unique EV profile following preterm birth.

• MeSH
• Extracellular Vesicles * metabolism   MeSH
• Adaptation, Physiological * MeSH
• Humans MeSH
• Infant, Premature * blood   MeSH
• Infant, Newborn MeSH
• Prospective Studies MeSH
• Proteomics methods   MeSH
• Pregnancy MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Infant, Newborn MeSH
• Pregnancy MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Observational Study MeSH

Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease often associated with underlying inflammatory bowel disease (IBD). This study investigates how PSC predisposes individuals to altered inflammatory immune responses compared with IBD alone. A case-control study was conducted with a cohort of 75 patients, including 16 with PSC (14 with concomitant IBD), 39 with IBD alone, and 20 controls. Serum bile acid profile, proteomic analysis, and immune-related gene expression in the colon tissue were examined. Colonic tissue from PSC patients exhibited up-regulation of immune regulation and inflammatory signaling mRNA markers, including LGR5, IL-8, CCL2, COX2, TWIST1, and SNAIL. Additionally, PSC patients displayed a distinct proinflammatory serum proteomic signature and moderate elevation of some bile acids, such as glycochenodeoxycholic acid (GCDCA). Co-incubation of human-derived monocytes with GCDCA partially replicated the inflammatory profile observed in PSC. These findings suggest that circulating bile acids modulate the peripheral immune system proinflammatory response, contributing to the unique PSC phenotype.

• MeSH
• Adult MeSH
• Inflammatory Bowel Diseases * immunology   complications   blood   genetics   MeSH
• Colon metabolism   immunology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Monocytes immunology   metabolism   MeSH
• Proteomics methods   MeSH
• Cholangitis, Sclerosing * immunology   blood   complications   genetics   MeSH
• Case-Control Studies MeSH
• Bile Acids and Salts * blood   immunology   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Interferon‐induced transmembrane proteins (IFITMs) are frequently overexpressed in cancer cells, including cervical carcinoma cells, and play a role in the progression of various cancer types. However, their mechanisms of action remain incompletely understood. In the present study, by employing a combination of surface membrane protein isolation and quantitative mass spectrometry, it was comprehensively described how the IFITM1 protein influences the composition of the cervical cancer cell surfaceome. Additionally, the effects of interferon‐γ on protein expression and cell surface exposure were evaluated in the presence and absence of IFITM1. The IFITM1‐regulated membrane and membrane‐associated proteins identified are involved mainly in processes such as endocytosis and lysosomal transport, cell‐cell and cell‐extracellular matrix adhesion, antigen presentation and the immune response. To complement the proteomic data, gene expression was analyzed using reverse transcription‐quantitative PCR to distinguish whether the observed changes in protein levels were attributable to transcriptional regulation or differential protein dynamics. Furthermore, the proteomic and gene expression data are supported by functional studies demonstrating the impact of the IFITM1 and IFITM3 proteins on the adhesive, migratory and invasive capabilities of cervical cancer cells, as well as their interactions with immune cells.

• MeSH
• Cell Adhesion MeSH
• Antigens, Differentiation * metabolism   genetics   MeSH
• Phenotype MeSH
• Interferon-gamma pharmacology   metabolism   MeSH
• Humans MeSH
• Membrane Proteins * metabolism   genetics   MeSH
• Cell Line, Tumor MeSH
• Uterine Cervical Neoplasms * pathology   genetics   metabolism   immunology   MeSH
• Cell Movement MeSH
• RNA-Binding Proteins * metabolism   genetics   MeSH
• Proteome * MeSH
• Proteomics methods   MeSH
• Gene Expression Regulation, Neoplastic MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Cardiovascular diseases are associated with an altered cardiomyocyte metabolism. Because of a shortage of human heart tissue, experimental studies mostly rely on alternative approaches including animal and cell culture models. Since the use of isolated primary cardiomyocytes is limited, immortalized cardiomyocyte cell lines may represent a useful tool as they closely mimic human cardiomyocytes. This study is focused on the AC16 cell line generated from adult human ventricular cardiomyocytes. Despite an increasing number of studies employing AC16 cells, a comprehensive proteomic, bioenergetic, and oxygen-sensing characterization of proliferating vs. differentiated cells is still lacking. Here, we provide a comparison of these two stages, particularly emphasizing cell metabolism, mitochondrial function, and hypoxic signaling. Label-free quantitative mass spectrometry revealed a decrease in autophagy and cytoplasmic translation in differentiated AC16, confirming their phenotype. Cell differentiation led to global increase in mitochondrial proteins [e.g. oxidative phosphorylation (OXPHOS) proteins, TFAM, VWA8] reflected by elevated mitochondrial respiration. Fatty acid oxidation proteins were increased in differentiated cells, whereas the expression levels of proteins associated with fatty acid synthesis were unchanged and glycolytic proteins were decreased. There was a profound difference between proliferating and differentiated cells in their response to hypoxia and anoxia-reoxygenation. We conclude that AC16 differentiation leads to proteomic and metabolic shifts and altered cell response to oxygen deprivation. This underscores the requirement for proper selection of the particular differentiation state during experimental planning.NEW & NOTEWORTHY Proliferating and differentiated AC16 cell lines exhibit distinct proteomic and metabolic profiles with critical implications for experimental design. Proliferating cells predominantly utilize glycolysis and are highly sensitive to hypoxia, whereas differentiated cells display enhanced mitochondrial biogenesis, oxidative phosphorylation, and resistance to anoxia-reoxygenation. These findings provide novel insights into the metabolic adaptations during differentiation and highlight the necessity of selecting the appropriate cellular stage to ensure accurate experimental outcomes.

• MeSH
• Cell Differentiation * physiology   MeSH
• Cell Line MeSH
• Energy Metabolism MeSH
• Cell Hypoxia physiology   MeSH
• Myocytes, Cardiac * metabolism   MeSH
• Humans MeSH
• Mitochondrial Proteins metabolism   MeSH
• Mitochondria * metabolism   MeSH
• Oxidative Phosphorylation MeSH
• Cell Proliferation MeSH
• Proteomics methods   MeSH
• Signal Transduction * physiology   MeSH
• Mitochondria, Heart * metabolism   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Protein misfolding diseases, including α1-antitrypsin deficiency (AATD), pose substantial health challenges, with their cellular progression still poorly understood1-3. We use spatial proteomics by mass spectrometry and machine learning to map AATD in human liver tissue. Combining Deep Visual Proteomics (DVP) with single-cell analysis4,5, we probe intact patient biopsies to resolve molecular events during hepatocyte stress in pseudotime across fibrosis stages. We achieve proteome depth of up to 4,300 proteins from one-third of a single cell in formalin-fixed, paraffin-embedded tissue. This dataset reveals a potentially clinically actionable peroxisomal upregulation that precedes the canonical unfolded protein response. Our single-cell proteomics data show α1-antitrypsin accumulation is largely cell-intrinsic, with minimal stress propagation between hepatocytes. We integrated proteomic data with artificial intelligence-guided image-based phenotyping across several disease stages, revealing a late-stage hepatocyte phenotype characterized by globular protein aggregates and distinct proteomic signatures, notably including elevated TNFSF10 (also known as TRAIL) amounts. This phenotype may represent a critical disease progression stage. Our study offers new insights into AATD pathogenesis and introduces a powerful methodology for high-resolution, in situ proteomic analysis of complex tissues. This approach holds potential to unravel molecular mechanisms in various protein misfolding disorders, setting a new standard for understanding disease progression at the single-cell level in human tissue.

• MeSH
• alpha 1-Antitrypsin metabolism   MeSH
• Single-Cell Analysis MeSH
• alpha 1-Antitrypsin Deficiency * pathology   metabolism   genetics   MeSH
• Phenotype MeSH
• Hepatocytes metabolism   pathology   MeSH
• Liver Cirrhosis pathology   metabolism   MeSH
• Liver pathology   metabolism   MeSH
• Humans MeSH
• Disease Progression MeSH
• Proteome * analysis   metabolism   MeSH
• Proteomics * methods   MeSH
• Unfolded Protein Response MeSH
• Machine Learning MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Proteomics is nowadays increasingly becoming part of the routine clinical practice of diagnostic laboratories, especially due to the advent of advanced mass spectrometry techniques. This review focuses on the application of proteomic analysis in the identification of pathological conditions in a hospital setting, with a particular focus on the analysis of protein biomarkers. In particular, the main purpose of the review is to highlight the challenges associated with the identification of specific disease-causing proteins, given their complex nature and the variety of posttranslational modifications (PTMs) they can undergo. PTMs, such as phosphorylation and glycosylation, play critical roles in protein function but can also lead to diseases if dysregulated. Proteomics plays an important role especially in various medical fields ranging from cardiology, internal medicine to hemato-oncology emphasizing the interdisciplinary nature of this field. Traditional methods such as electrophoretic or immunochemical methods have been mainstay in protein detection; however, these techniques are limited in terms of specificity and sensitivity. Examples include the diagnosis of multiple myeloma and the detection of its specific protein or amyloidosis, which relies heavily on these conventional methods, which sometimes lead to false positives or inadequate disease monitoring. Mass spectrometry in this respect emerges as a superior alternative, providing high sensitivity and specificity in the detection and quantification of specific protein sequences. This technique is particularly beneficial for monitoring minimal residual disease (MRD) in the diagnosis of multiple myeloma where traditional methods fall short. Furthermore mass spectrometry can provide precise typing of amyloid proteins, which is crucial for the appropriate treatment of amyloidosis. This review summarizes the opportunities for proteomic determination using mass spectrometry between 2012 and 2024, highlighting the transformative potential of mass spectrometry in clinical proteomics and encouraging its wider use in diagnostic laboratories.

• MeSH
• Amyloidosis * diagnosis   MeSH
• Biomarkers analysis   MeSH
• Mass Spectrometry * methods   MeSH
• Humans MeSH
• Multiple Myeloma * diagnosis   MeSH
• Protein Processing, Post-Translational MeSH
• Proteomics * methods   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH

Recent advances in protein 3D structure prediction using deep learning have focused on the importance of amino acid residue-residue connections (i.e., pairwise atomic contacts) for accuracy at the expense of mechanistic interpretability. Therefore, we decided to perform a series of analyses based on an alternative framework of residue-residue connections making primary use of the TOP2018 dataset. This framework of residue-residue connections is derived from amino acid residue pairing models both historic and new, all based on genetic principles complemented by relevant biophysical principles. Of these pairing models, three new models (named the GU, Transmuted and Shift pairing models) exhibit the highest observed-over-expected ratios and highest correlations in statistical analyses with various intra- and inter-chain datasets, in comparison to the remaining models. In addition, these new pairing models are universally frequent across different connection ranges, secondary structure connections, and protein sizes. Accordingly, following further statistical and other analyses described herein, we have come to a major conclusion that all three pairing models together could represent the basis of a universal proteomic code (second genetic code) sufficient, in and of itself, to "encode" for both protein folding mechanisms and protein-protein interactions.

• MeSH
• Amino Acids * chemistry   genetics   MeSH
• Databases, Protein MeSH
• Humans MeSH
• Models, Molecular * MeSH
• Proteins * chemistry   genetics   metabolism   MeSH
• Proteomics * MeSH
• Protein Folding * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Developing methodological approaches for discovering novel pathways is a key challenge in the life science research. Biological pathways are regulated-in higher eukaryotes-by a vast diversity of linear peptide motifs that mediate combinatorial specificity in signal transduction pathways. The E3 ubiquitin ligase component (MDM2) is such a protein that interacts with target proteins containing linear motifs such as p53. Drug leads, such as Nutlin-3, that bind to the MDM2 hydrophobic pocket mimic p53 and can release p53 from MDM2 control and this can lead to cell death. However, these drug leads act allosterically, having agonist effects on MDM2's functions and there are other proteins whose steady state levels can be altered by Nutlin-3. As cell density can alter the proliferation state of cell populations, we examined the impact of Nutlin-3 on levels of newly synthesized proteins using pulse-SILAC mass spectrometry. The data demonstrate that at differing cell densities or population-wide proliferation rates, different newly synthesized proteins dominate the proteome landscape in a Nutlin-3 dependent manner. These data further confirm that the cell state in a population of cells can in turn impact on the MDM2 signalling landscape. This methodology forms a blueprint for biomarker discovery using clinical samples that can detect changes in the synthesis rate of proteins in cell populations treated with specific agents. Broader implications highlight tools that can be used to study allosteric regulation of protein-drug combinations.

• MeSH
• Imidazoles * pharmacology   MeSH
• Humans MeSH
• Tumor Suppressor Protein p53 metabolism   MeSH
• Piperazines * pharmacology   MeSH
• Cell Proliferation drug effects   MeSH
• Proteome * metabolism   MeSH
• Proteomics methods   MeSH
• Proto-Oncogene Proteins c-mdm2 metabolism   MeSH
• Signal Transduction drug effects   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH