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Partial remission (PR) occurs in only half of people with new-onset type 1 diabetes (T1D) and corresponds to a transient period characterized by low daily insulin needs, low glycemic fluctuations and increased endogenous insulin secretion. While identification of people with newly-onset T1D and significant residual beta-cell function may foster patient-specific interventions, reliable predictive biomarkers of PR occurrence currently lack. We analyzed the plasma of children with new-onset T1D to identify biomarkers present at diagnosis that predicted PR at 3 months post-diagnosis. We first performed an extensive shotgun proteomic analysis using Liquid Chromatography-Tandem-Mass-Spectrometry (LCMS/MS) on the plasma of 16 children with new-onset T1D and quantified 98 proteins significantly correlating with Insulin-Dose Adjusted glycated hemoglobin A1c score (IDAA1C). We next applied a series of both qualitative and statistical filters and selected protein candidates that were associated to pathophysiological mechanisms related to T1D. Finally, we translationally verified several of the candidates using single-shot targeted proteomic (PRM method) on raw plasma. Taken together, we identified plasma biomarkers present at diagnosis that may predict the occurrence of PR in a single mass-spectrometry run. We believe that the identification of new predictive biomarkers of PR and ß-cell function is key to stratify people with new-onset T1D for ß-cell preservation therapies.

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Protein electrophoresis (PEP) is an important tool in mammals to characterize specific dysproteinemias and detect acute and chronic inflammatory responses. In reptiles, PEP is the gold standard method for globulin fraction determination and albumin measurement. In this study, preliminary reference intervals were established for serum PEP in 22 clinically healthy adult Roti Island snake-necked turtles (Chelodina mccordi), a critically endangered species, kept in captivity and sampled over two monsoon seasons. The species has a prominent prealbumin fraction and ß-globulins were the dominant globulin fraction. Significant differences between females and males were found in prealbumin (P < 0.01), albumin (P = 0.02), α1-globulin (P = 0.05) and γ-globulin (P = 0.01). Gravid females had significantly lower total protein (P < 0.01), prealbumin (P < 0.01), albumin (P < 0.01) and albumin:globulin ratio (P = 0.01). These preliminary reference intervals should aid in clinical investigation in this species as well as further research studies seeking to understand the application of PEP in reptilian species.

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Leopard sharks (Triakis semifasciata) are temperate, Eastern Pacific elasmobranchs popular in public aquariums. Blood analysis is commonly used for assessing animal health, yet reference values have not been established for this species. This study analyzed T. semifasciata population data to characterize blood reference values for a collection of T. semifasciata housed at a public aquarium. Twenty-one captive leopard sharks were sampled. Blood was collected during annual health examinations from sedated animals. After collection, blood samples were anticoagulated with lithium heparin, and hematocrit and plasma biochemistry values were analyzed. The minimum-maximum ranges were hematocrit 11-31%, buffy coat 1-2%, glucose 4.94-9.38 mM/L, sodium 244-272 mM/L, potassium 3.7-5.5 mM/L, chloride 214-246 mM/L, aspartate aminotransferase 5-31 U/L, creatine kinase 36-1,136 U/L, calcium 3.65-3.95 mM/L, phosphorus 1.13-2.23 mM/L, total protein 21-38 g/L, and total CO2 12-18 mM/L. The values identified will contribute to a better understanding of captive leopard shark physiology and to improved veterinary care for captive leopard sharks. Further research can examine the validity of machines like the Vetscan VS2, which will expand the resources available to care professionals.

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BACKGROUND: The severe course of COVID-19 causes cardiovascular injuries, although the mechanisms involved are still not fully recognized, linked, and understood. Their characterization is of great importance with the establishment of the conception of post-acute sequelae of COVID-19, referred to as long COVID, where blood clotting and endothelial abnormalities are believed to be the key pathomechanisms driving circulatory system impairment. METHODS: The presented study investigates temporal changes in plasma proteins in COVID-19 patients during hospitalization due to SARS-CoV-2 infection and six months after recovery by targeted SureQuant acquisition using PQ500 panel. RESULTS: In total, we identified 167 proteins that were differentially regulated between follow-up and hospitalization, which functionally aggregated into immune system activation, complement and coagulation cascades, interleukins signalling, platelet activation, and extracellular matrix organization. Furthermore, we found that temporal quantitative changes in acute phase proteins correlate with selected clinical characteristics of COVID-19 patients. CONCLUSIONS: In-depth targeted proteome investigation evidenced substantial changes in plasma protein composition of patients during and recovering from COVID-19, evidencing a wide range of functional pathways induced by SARS-CoV-2 infection. In addition, we show that a subset of acute phase proteins, clotting cascade regulators and lipoproteins could have clinical value as potential predictors of long-term cardiovascular events in COVID-19 convalescents.

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Retinal artery occlusion (RAO), which is positively correlated with acute ischemic stroke (IS) and results in severe visual impairment, lacks effective intervention drugs. This study aims to perform integrated analysis using UK Biobank plasma proteome data of RAO and IS to identify potential targets and preventive drugs. A total of 7191 participants (22 RAO patients, 1457 IS patients, 8 individuals with both RAO and IS, and 5704 healthy age-gender-matched controls) were included in this study. Unique 1461 protein expression profiles of RAO, IS, and the combined data set, extracted from UK Biobank Plasma proteomics projects, were analyzed using both differential expression analysis and elastic network regression (Enet) methods to identify shared key proteins. Subsequent analyses, including single cell type expression assessment, pathway enrichment, and druggability analysis, were conducted for verifying shared key proteins and discovery of new drugs. Five proteins were found to be shared among the samples, with all of them showing upregulation. Notably, adhesion G-protein coupled receptor G1 (ADGRG1) exhibited high expression in glial cells of the brain and eye tissues. Gene set enrichment analysis revealed pathways associated with lipid metabolism and vascular regulation and inflammation. Druggability analysis unveiled 15 drug candidates targeting ADGRG1, which demonstrated protective effects against RAO, especially troglitazone (-8.5 kcal/mol). Our study identified novel risk proteins and therapeutic drugs associated with the rare disease RAO, providing valuable insights into potential intervention strategies.

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Leptospirosis, a notifiable endemic disease in Malaysia, has higher mortality rates than regional dengue fever. Diverse clinical symptoms and limited diagnostic methods complicate leptospirosis diagnosis. The demand for accurate biomarker-based diagnostics is increasing. This study investigated the plasma proteome of leptospirosis patients with leptospiraemia and seroconversion compared with dengue patients and healthy subjects using isobaric tags for relative and absolute quantitation (iTRAQ)-mass spectrometry (MS). The iTRAQ analysis identified a total of 450 proteins, which were refined to a list of 290 proteins through a series of exclusion criteria. Differential expression in the plasma proteome of leptospirosis patients compared to the control groups identified 11 proteins, which are apolipoprotein A-II (APOA2), C-reactive protein (CRP), fermitin family homolog 3 (FERMT3), leucine-rich alpha-2-glycoprotein 1 (LRG1), lipopolysaccharide-binding protein (LBP), myosin-9 (MYH9), platelet basic protein (PPBP), platelet factor 4 (PF4), profilin-1 (PFN1), serum amyloid A-1 protein (SAA1), and thrombospondin-1 (THBS1). Following a study on a verification cohort, a panel of eight plasma protein biomarkers was identified for potential leptospirosis diagnosis: CRP, LRG1, LBP, MYH9, PPBP, PF4, SAA1, and THBS1. In conclusion, a panel of eight protein biomarkers offers a promising approach for leptospirosis diagnosis, addressing the limitations of the "one disease, one biomarker" concept.

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Given recent technological advances in proteomics, it is now possible to quantify plasma proteomes in large cohorts of patients to screen for biomarkers and to guide the early diagnosis and treatment of depression. Here we used CatBoost machine learning to model and discover biomarkers of depression in UK Biobank data sets (depression n = 4,479, healthy control n = 19,821). CatBoost was employed for model construction, with Shapley Additive Explanations (SHAP) being utilized to interpret the resulting model. Model performance was corroborated through 5-fold cross-validation, and its diagnostic efficacy was evaluated based on the area under the receiver operating characteristic (AUC) curve. A total of 45 depression-related proteins were screened based on the top 20 important features output by the CatBoost model in six data sets. Of the nine diagnostic models for depression, the performance of the traditional risk factor model was improved after the addition of proteomic data, with the best model having an average AUC of 0.764 in the test sets. KEGG pathway analysis of 45 screened proteins showed that the most significant pathway involved was the cytokine-cytokine receptor interaction. It is feasible to explore diagnostic biomarkers of depression using data-driven machine learning methods and large-scale data sets, although the results require validation.

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Polyhexamethylene guanidine (PHMG) is a positively charged polymer used as a disinfectant that kills microbes but can cause pulmonary fibrosis if inhaled. After the long-term risks were confirmed in South Korea, it became crucial to measure toxicity through diverse surrogate biomarkers, not only proteins, especially after these hazardous chemicals had cleared from the body. These biomarkers, identified by their biological functions rather than simple numerical calculations, effectively explained the imbalance of pulmonary surfactant caused by fibrosis from PHMG exposure. These long-term studies on children exposed to PHMG has shown that blood protein indicators, primarily related to apolipoproteins and extracellular matrix, can distinguish the degree of exposure to humidifier disinfectants (HDs). We defined the extreme gradient boosting models and computed reflection scores based on just ten selected proteins, which were also verified in adult women exposed to HD. The reflection scores successfully discriminated between the HD-exposed and unexposed groups in both children and adult females (AUROC: 0.957 and 0.974, respectively) and had a strong negative correlation with lung function indicators. Even after an average of more than 10 years, blood is still considered a meaningful specimen for assessing the impact of environmental exposure to toxic substances, with proteins providing in identifying the pathological severity of such conditions.

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INTRODUCTION: Depressive symptoms are a common concomitant of cerebral small vessel disease (CSVD), of which pathogenesis requires more study. White matter microstructural abnormalities and proteomic alternation have been widely reported regarding depression in the elderly with CSVD. Exploring the relationship between cerebral white matter microstructural alterations and serum proteins may complete the explanation of molecular mechanisms for the findings from neuroimaging research of CSVD combined with depressive symptoms. METHODS: An untargeted proteomics approach based on mass spectrometry was used to obtain serum proteomic profiles, which were clustered into co-expression protein modules. White matter microstructural integrity was measured using the FMRIB Software Library (FSL) and MATLAB to analyze diffusion tensor imaging (DTI) data and calculate the differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) for 50 regions of interest (ROI). Integrating the proteome with the DTI results, weighted gene co-expression analysis (WGCNA) was used to identify protein modules related to white matter microstructural alterations, and the proteins of the corresponding modules were analyzed for functional enrichment through bioinformatics techniques. RESULTS: DTI measurements were analCerebral small vessel disease (CSVD); Depression; Diffusion tensor imaging (DTI); Proteomics; Inflammationyzed between individuals with CSVD and depressive symptoms (CSVD+D) (n = 24) and those without depressive symptoms (CSVD-D) (n = 35). Results showed an overall increase in MD, AD, and RD within the left hemisphere of the CSVD+D group, suggesting widespread loss of white matter integrity and axonal demyelination, including left superior longitudinal fasciculus (SLF), left posterior corona radiata (PCR) and right external capsule (EC). We identified two protein modules associated with DTI diffusivity, and functional enrichment analyses revealed that complement and coagulation cascades and immune responses participate in the alternation of white matter microstructure in the CSVD+D group. CONCLUSION: The results suggested immune- and inflammation-related mechanism was associated with white matter microstructure changes in CSVD with depressive symptoms.

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The sequalae of periodontitis include irreversible degradation of tooth-supporting structures and circulatory spread of inflammatory mediators. However, the serum protein profile in periodontitis is not well described, which is partly attributable to the limited number of studies based on large and well-characterized periodontitis cohorts. This study aims to identify novel, circulating inflammation-related proteins associated with periodontitis within the PerioGene North case-control study, which includes 478 cases with severe periodontitis and 509 periodontally healthy controls. The serum concentrations of high-sensitivity C-reactive protein (hs-CRP) and a panel of 45 inflammation-related proteins were analyzed using targeted proteomics. A distinguishable serum protein profile was evident in periodontitis cases. The protein pattern could separate cases from controls with a sensitivity of 0.81 and specificity of 0.81 (area under the curve = 0.87). Adjusted levels for hs-CRP and 24 of the 45 proteins were different between cases and controls. High levels of hs-CRP and matrix metalloproteinase-12, and low levels of epidermal growth factor (EGF) and oxidized low-density lipoprotein receptor 1 (OLR-1) were detected among the cases. Furthermore, the levels of C-C motif chemokine-19, granulocyte colony-stimulating factor-3 (CSF-3), interleukin-7 (IL-7), and hs-CRP were significantly higher in cases with a high degree of gingival inflammation. The levels of CSF-3 and tumor necrosis factor ligand superfamily member-10 TNFSF-10 were higher in cases with many deep periodontal pockets. The PerioGene North study includes detailed clinical periodontal data and uncovers a distinct serum protein profile in periodontitis. The findings of lower EGF and OLR-1 among the cases are highlighted, as this has not been presented before. The role of EGF and OLR-1 in periodontitis pathogenesis and as possible future biomarkers should be further explored.

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Plasma-derived extracellular vesicles (pEVs) are a potential source of diseased biomarker proteins. However, characterizing the pEV proteome is challenging due to its relatively low abundance and difficulties in enrichment. This study presents a streamlined workflow to identify EV proteins from cancer patient plasma using minimal sample input. Starting with 400 µL of plasma, we generated a comprehensive pEV proteome using size exclusion chromatography (SEC) combined with HiRIEF prefractionation-based mass spectrometry (MS). First, we compared the performance of HiRIEF and long gradient MS workflows using control pEVs, quantifying 2076 proteins with HiRIEF. In a proof-of-concept study, we applied SEC-HiRIEF-MS to a small cohort (12) of metastatic lung adenocarcinoma (LUAD) and malignant melanoma (MM) patients. We also analyzed plasma samples from the same patients to study the relationship between plasma and pEV proteomes. We identified and quantified 1583 proteins in cancer pEVs and 1468 proteins in plasma across all samples. While there was substantial overlap, the pEV proteome included several unique EV markers and cancer-related proteins. Differential analysis revealed 30 DEPs in LUAD vs the MM group, highlighting the potential of pEVs as biomarkers. This work demonstrates the utility of a prefractionation-based MS for comprehensive pEV proteomics and EV biomarker discovery. Data are available via ProteomeXchange with the identifiers PXD039338 and PXD038528.

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Plasma proteomics is a precious tool in human disease research but requires extensive sample preparation in order to perform in-depth analysis and biomarker discovery using traditional data-dependent acquisition (DDA). Here, we highlight the efficacy of combining moderate plasma prefractionation and data-independent acquisition (DIA) to significantly improve proteome coverage and depth while remaining cost-efficient. Using human plasma collected from a 20-patient COVID-19 cohort, our method utilizes commonly available solutions for depletion, sample preparation, and fractionation, followed by 3 liquid chromatography-mass spectrometry/MS (LC-MS/MS) injections for a 360 min total DIA run time. We detect 1321 proteins on average per patient and 2031 unique proteins across the cohort. Differential analysis further demonstrates the applicability of this method for plasma proteomic research and clinical biomarker identification, identifying hundreds of differentially abundant proteins at biological concentrations as low as 47 ng/L in human plasma. Data are available via ProteomeXchange with the identifier PXD047901. In summary, this study introduces a streamlined, cost-effective approach to deep plasma proteome analysis, expanding its utility beyond classical research environments and enabling larger-scale multiomics investigations in clinical settings. Our comparative analysis revealed that fractionation, whether the samples were pooled or separate postfractionation, significantly improved the number of proteins quantified. This underscores the value of fractionation in enhancing the depth of plasma proteome analysis, thereby offering a more comprehensive landscape for biomarker discovery in diseases such as COVID-19.

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Background: Physical activity has been associated with preventing the development of type 2 diabetes and atherosclerotic cardiovascular disease. However, our understanding of the precise molecular mechanisms underlying these effects remains incomplete and good biomarkers to objectively assess physical activity are lacking. Methods: We analyzed 3072 serum proteins in 26 men, normal weight or overweight, undergoing 12 weeks of a combined strength and endurance exercise intervention. We estimated insulin sensitivity with hyperinsulinemic euglycemic clamp, maximum oxygen uptake, muscle strength, and used MRI/MRS to evaluate body composition and organ fat depots. Muscle and subcutaneous adipose tissue biopsies were used for mRNA sequencing. Additional association analyses were performed in samples from up to 47,747 individuals in the UK Biobank, as well as using two-sample Mendelian randomization and mice models. Results: Following 12 weeks of exercise intervention, we observed significant changes in 283 serum proteins. Notably, 66 of these proteins were elevated in overweight men and positively associated with liver fat before the exercise regimen, but were normalized after exercise. Furthermore, for 19.7 and 12.1% of the exercise-responsive proteins, corresponding changes in mRNA expression levels in muscle and fat, respectively, were shown. The protein CD300LG displayed consistent alterations in blood, muscle, and fat. Serum CD300LG exhibited positive associations with insulin sensitivity, and to angiogenesis-related gene expression in both muscle and fat. Furthermore, serum CD300LG was positively associated with physical activity and negatively associated with glucose levels in the UK Biobank. In this sample, the association between serum CD300LG and physical activity was significantly stronger in men than in women. Mendelian randomization analysis suggested potential causal relationships between levels of serum CD300LG and fasting glucose, 2 hr glucose after an oral glucose tolerance test, and HbA1c. Additionally, Cd300lg responded to exercise in a mouse model, and we observed signs of impaired glucose tolerance in male, but not female, Cd300lg knockout mice. Conclusions: Our study identified several novel proteins in serum whose levels change in response to prolonged exercise and were significantly associated with body composition, liver fat, and glucose homeostasis. Serum CD300LG increased with physical activity and is a potential causal link to improved glucose levels. CD300LG may be a promising exercise biomarker and a therapeutic target in type 2 diabetes. Funding: South-Eastern Norway Regional Health Authority, Simon Fougners Fund, Diabetesforbundet, Johan Selmer Kvanes' legat til forskning og bekjempelse av sukkersyke. The UK Biobank resource reference 53641. Australian National Health and Medical Research Council Investigator Grant (APP2017942). Australian Research Council Discovery Early Career Award (DE220101226). Research Council of Norway (Project grant: 325640 and Mobility grant: 287198). The Medical Student Research Program at the University of Oslo. Novo Nordisk Fonden Excellence Emerging Grant in Endocrinology and Metabolism 2023 (NNF23OC0082123). Clinical trial number: clinicaltrials.gov: NCT01803568.

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Amyotrophic lateral sclerosis as a fatal neurodegenerative disease currently lacks effective therapeutic agents. Thus, finding new therapeutic targets to drive disease treatment is necessary. In this study, we utilized brain and plasma proteins as genetic instruments obtained from genome-wide association studies to conduct a Mendelian randomization analysis to identify potential drug targets for amyotrophic lateral sclerosis. Additionally, we validated our results externally using other datasets. We also used Bayesian co-localization analysis and phenotype scanning. Furthermore, we constructed a protein-protein interaction network to elucidate potential correlations between the identified proteins and existing targets. Mendelian randomization analysis indicated that elevated levels of ANO5 (OR = 1.30; 95 % CI, 1.14-1.49; P = 1.52E-04), SCFD1 (OR = 3.82; 95 % CI, 2.39-6.10; P = 2.19E-08), and SIGLEC9 (OR = 1.05; 95% CI, 1.03-1.07; P = 4.71E-05) are associated with an increased risk of amyotrophic lateral sclerosis, with external validation supporting these findings. Co-localization analysis confirmed that ANO5, SCFD1, and SIGLEC9 (coloc.abf-PPH4 = 0.848, 0.984, and 0.945, respectively) shared the same variant with amyotrophic lateral sclerosis, further substantiating potential role of these proteins as a therapeutic target. There are interactive relationships between the potential proteins and existing targets of amyotrophic lateral sclerosis. Our findings suggested that elevated levels of ANO5, SCFD1, and SIGLEC9 are connected with an increased risk of amyotrophic lateral sclerosis and might be promising therapeutic targets. However, further exploration is necessary to fully understand the underlying mechanisms involved.

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OBJECTIVES: The biuret method is frequently used to determine serum total protein. On the other hand refractometer, a quicker and less expensive option, is available to determine serum total protein. However, there is no study conducted in Ethiopia to compare serum total protein measurement in veterinary settings. Therefore, this study was conducted to compare the serum total protein concentration measurement in cattle and goats obtained by the biuret method and refractometer. RESULTS: Serum samples from 60 cattle and 60 goats were assayed by both methods and data were analyzed with a paired t-test, Pearson's correlation, and Bland-Altman plots. There was a strong positive correlation between the total protein values determined with the refractometer and the biuret method in cattle (r = 0.93) and goats (r = 0.97). There were no significant differences (p > 0.05) in the protein values measured with the refractometer and those evaluated with the biuret method in both species. Bland-Altman plots showed that biases indicating the analytic and user error were 8.33% in both species which is below the acceptable total error (< 10%). Thus, refractometer can be used in place of biuret method since it is valid enough to measure serum total protein in cattle and goats.

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Background: Control of buffalo flies (Haematobia irritans exigua, BFs) relies mainly on chemical methods; however, resistance to insecticides is widespread in BF populations. Breeding for resistance to BFs represents a possible alternative, but direct phenotyping of animals is laborious and often inaccurate. The availability of reliable diagnostic biomarker(s) to identify low BF carrier cattle would facilitate rapid and accurate selection for genetic improvement. However, limited information is available regarding differences amongst cattle in host responses to BF infestation. Methods: This study investigated the variation in Brangus cattle serum proteomic profiles before (naïve) and after peak BF exposure, in low (LF) and high BF burden (HF) cattle. Cattle were phenotyped for susceptibility based on BF counts on multiple dates using visual and photographic techniques. The relative abundance of serum proteins in cattle before and after exposure to BFs was analysed using sequential window acquisition of all theoretical fragment ion mass spectrometry (SWATH-MS). Results: Exposure to BFs elicited similar responses in HF and LF cattle, with 79 and 70 proteins, respectively, showing significantly different abundances post exposure as compared to their relevant naïve groups. The comparison of serum samples from naïve HF and LF cattle identified 44 significantly differentially abundant (DA) proteins, while 37 significantly DA proteins were identified from the comparison between HF and LF cattle post-exposure to BFs. Proteins with higher abundance in naïve LF cattle were enriched in blood coagulation mechanisms that were sustained after exposure to BFs. Strong immune response mechanisms were also identified in naïve LF cattle, whereas these responses developed in HF cattle only after exposure to BF. High BF cattle also showed active anticoagulation mechanisms in response to BF exposure, including downregulation of coagulation factor IX and upregulation of antithrombin-III, which might facilitate BF feeding. Conclusion: Underlying differences in the abundance of proteins related to blood coagulation and immune response pathways could potentially provide indirect indicators of susceptibility to BF infestation and biomarkers for selecting more BF-resistant cattle.

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Current genome-wide association studies (GWAS) of plasma proteomes provide additional possibilities for finding new drug targets for inflammatory dermatoses. We performed proteome-wide Mendelian randomization (MR) and colocalization analyses to identify novel potential drug targets for inflammatory dermatoses. We performed MR and colocalization analysis using genetic variation as instrumental variables to determine the causal relationship between circulating plasma proteins and inflammatory dermatoses. 5 plasma proteins were found to be causally associated with dermatitis eczematosa, SLE, urticaria and psoriasis using cis-pQTLs as instrumental variables, but not found in AD and LP. 19 candidate genes with high colocalization evidence were identified. These potential drug targets still require more research and rigorous validation in future trials.

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BACKGROUND & AIMS: Plant-based diets are associated with a lower risk of chronic diseases. Large-scale proteomics can identify objective biomarkers of plant-based diets, and improve our understanding of the pathways that link plant-based diets to health outcomes. This study investigated the plasma proteome of four different plant-based diets [overall plant-based diet (PDI), provegetarian diet, healthful plant-based diet (hPDI), and unhealthful plant-based diet (uPDI)] in the Atherosclerosis Risk in Communities (ARIC) Study and replicated the findings in the Framingham Heart Study (FHS) Offspring cohort. METHODS: ARIC Study participants at visit 3 (1993-1995) with completed food frequency questionnaire (FFQ) data and proteomics data were divided into internal discovery (n = 7690) and replication (n = 2543) data sets. Multivariable linear regression was used to examine associations between plant-based diet indices (PDIs) and 4955 individual proteins in the discovery sample. Then, proteins that were internally replicated in the ARIC Study were tested for external replication in FHS (n = 1358). Pathway overrepresentation analysis was conducted for diet-related proteins. C-statistics were used to predict if the proteins improved prediction of plant-based diet indices beyond participant characteristics. RESULTS: In ARIC discovery, a total of 837 diet-protein associations (PDI = 233; provegetarian = 182; hPDI = 406; uPDI = 16) were observed at false discovery rate (FDR) < 0.05. Of these, 453 diet-protein associations (PDI = 132; provegetarian = 104; hPDI = 208; uPDI = 9) were internally replicated. In FHS, 167/453 diet-protein associations were available for external replication, of which 8 proteins (PDI = 1; provegetarian = 0; hPDI = 8; uPDI = 0) replicated. Complement and coagulation cascades, cell adhesion molecules, and retinol metabolism were over-represented. C-C motif chemokine 25 for PDI and 8 proteins for hPDI modestly but significantly improved the prediction of these indices individually and collectively (P value for difference in C-statistics<0.05 for all tests). CONCLUSIONS: Using large-scale proteomics, we identified potential candidate biomarkers of plant-based diets, and pathways that may partially explain the associations between plant-based diets and chronic conditions.

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The objective of this study was to assess the effects of the exposure to daily maximum and temperature-humidity index (THI) and to daily THI fluctuations (∆THI = maximum THI-minimum THI) at exposure periods comprising 2 d before birth to birth (-2 d), birth date (0 d), birth to 2 d of age (+2 d), and birth to 7 d of age (+7 d) on serum total proteins (STP), transfer of passive immunity (TPI), and the occurrence of scours and respiratory disease. A total of 841 Holstein heifer calves were retrospectively observed from -2 d until 65 d of age. Colostrum quality was assessed using a colostrometer to ensure a minimum globulin concentration of 52 mg/mL in the colostrum fed to the study calves. Two temperature and relative humidity sensors were installed at the calf yard. Maximum, minimum, and ∆THI values were obtained for each exposure period, and thermal exposure categories were defined as heat stress (HS: maximum THI > 70 units; non-HS: THI ≤ 70 units) and ∆THI (low < 20 units, medium ≥ 20 to ≤30 units, high > 30). The TPI was classified as poor (STP < 5.1 g/dL), fair (5.1 and 5.7 g/dL), good (>5.7 and 6.1 g/dL), and excellent (≥6.1 g/dL). Associations between the thermal exposure categories and the study outcomes were examined using ANOVA, logistic regression, and survival analyses. No differences in STP at -2 d were observed between HS and non-HS calves (6.83 ±â€…0.05 vs. 6.91 ±â€…0.05 g/dL), whereas HS-exposed calves at 0 d tended to have lower STP compared with non-HS calves (6.82 ±â€…0.05 vs. 6.92 ±â€…0.05 g/dL). Calves exposed to small ∆THI at 0 d had greater STP compared with calves exposed to medium ∆THI (7.00 ±â€…0.06 vs. 6.75 ±â€…0.05 g/dL). No association was found between HS, and ∆THI categories and the TPI category. The odds of scours were about 2 times greater in HS calves compared with non-HS calves at all exposure periods. In addition, HS calves were affected by scours between 9 and 15 d earlier than non-HS calves. Furthermore, high ∆THI favored the development of respiratory problems compared with medium and low ∆THI. Assessment of extreme THI values and THI fluctuations provides a research opportunity for assessing thermal stress in dairy heifer calves raised in dry climate.

The effects of the exposure to daily maximum temperature-humidity index (THI) and daily THI fluctuations (∆THI, maximum­minimum THI) around birth (−2 d, birth date [0 d], +2 d, and +7 d) on serum total protein (STP) and health of preweaned Holstein heifers were evaluated. Heifer calves exposed to small ∆THI (<20 units) at 0 d had greater STP compared with medium ∆THI (≥20 to ≤30 units). At all exposure periods, heat stress (THI > 70 units) increased the occurrence of scours at earlier age, whereas small and large ∆THI favored the presentation of scours and respiratory disease, respectively.

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Plasma proteins involved in coagulation and fibrinolysis are essential to hemostasis. Consequently, their circulating levels and functionality are critical in bleeding and thrombosis development. Well-established laboratory tests to assess these are available; however, said tests do not allow high multiplicity, require large volumes of plasma and are often costly. A novel technology to quantify plasma proteins is quantitative protein mass spectrometry (QPMS). Aided by stable isotope-labeled internal standards a large number of proteins can be quantified in one single analytical run requiring <30 µL of plasma. This provides an opportunity to improve insight in the etiology and prognosis of bleeding and thrombotic disorders, in which the balance between different proteins plays a crucial role. This manuscript aims to give an overview of the QPMS potential applications in thrombosis and hemostasis research (quantifying the 38 proteins assigned to coagulation and fibrinolysis by the KEGG database), but also to explore the potential and hurdles if designed for clinical practice. Advantages and limitations of QPMS are described and strategies for improved analysis are proposed, using as an example the test requirements for antithrombin. Application of this technology in the future could represent a step towards individualized patient care.

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