OBJECTIVE: The brain TXA(2) and PGI(2) levels in a new rodent model of impact acceleration diffuse brain injury alone and with hypotention and hyperthermia in combination were observed to look into the relationship between TXA(2), PGI(2) levels and different types of head injury. METHODS: Thirty-two SD rats were randomized into sham, head injury alone, secondary insult alone and head injury with secondary insult groups. At 4 hours after injury or experiment, all the rats were decapitated and their brains were sampled for radioimmunoassay (RIA) measurement. RESULTS: Compared with that of sham group there were no changes in TXA(2) and PGI(2) levels in injury alone group while there was a significant augmentation in PGI(2) level in insult alone group. Both TXA(2) and PGI(2) level in injury with secondary insult group increased significantly in comparison with that of sham at 4 hours postimpact. CONCLUSIONS: PGI(2) providing energy and precursors to the injured tissue and producing some vasoactive arachidonic products, especially TXA(2), is closely connected to the severity of brain damage.

OBJECTIVE: To study the changes of brain TXA(2) and PGI(2) levels in a new rodent model of impact acceleration diffuse brain injury with hypotention and hypoxia and the effect of diaspirin cross linked hemoglobin solution (DCLHb) on brain TXA(2) and PGI(2) levels. METHODS: Thirty-two male SD rats were randomized into sham, head injury alone, head injury with secondary insults and injury with insults followed by DCLHb administration groups. Animals were physiologically monitored throughout the experiment and the prostanoids were measured via radioimmunoassay (RIA). RESULTS: There were no changes in TXB(2) and 6-keto-PGF1alpha (stable metabolites of TXA(2) and PGI(2)) levels in injury alone group while TXB(2) level in secondary insults group elevated significantly and both TXB(2) and 6-keto-PGF1alpha levels in injury with insults followed by DCLHb administration augmented significantly in comparison with the corresponding value of sham at 4 h postimpact. CONCLUSIONS: The only increase in TXA(2) level in secondary insults rats suggests that there may be both thrombotic episodes and vasoconstriction leading to focal increase in micro-circulatory resistance which contributes to a decreased focal cerebral blood flow (CBF). And it is hypothesed that DCLHb may exert its protective properties through increasing PGI(2) production in injured brain by affecting CBF and cerebral perfusion pressure (CPP).

BACKGROUND: We aimed to compare the diagnostic accuracy of the Alere Triage Cardio3 Tropinin I (TnI) assay (Alere, Inc., USA) and the PathFast cTnI-II (Mitsubishi Chemical Medience Corporation, Japan) against the central laboratory assay Singulex Erenna TnI assay (Singulex, USA). METHODS: Using the Markers in the Diagnosis of Acute Coronary Syndromes (MIDAS) study population, we evaluated the ability of three different assays to identify patients with acute myocardial infarction (AMI). The MIDAS dataset, described elsewhere, is a prospective multicenter dataset of emergency department (ED) patients with suspected acute coronary syndrome (ACS) and a planned objective myocardial perfusion evaluation. Myocardial infarction (MI) was diagnosed by central adjudication. RESULTS: The C-statistic with 95% confidence intervals (CI) for diagnosing MI by using a common population (n=241) was 0.95 (0.91-0.99), 0.95 (0.91-0.99), and 0.93 (0.89-0.97) for the Triage, Singulex, and PathFast assays, respectively. Of samples with detectable troponin, the absolute values had high Pearson (R(P)) and Spearman (R(S)) correlations and were R(P)=0.94 and R(S)=0.94 for Triage vs Singulex, R(P)=0.93 and R(S)=0.85 for Triage vs PathFast, and R(P)=0.89 and R(S)=0.73 for PathFast vs Singulex. CONCLUSIONS: In a single comparative population of ED patients with suspected ACS, the Triage Cardio3 TnI, PathFast, and Singulex TnI assays provided similar diagnostic performance for MI.
Acute Coronary Syndrome/*diagnosis ; Biomarkers/analysis ; Emergency Service, Hospital ; Humans ; Laboratories/standards ; Myocardial Infarction/diagnosis ; *Point-of-Care Systems ; Prospective Studies ; Reagent Kits, Diagnostic ; Sensitivity and Specificity ; Troponin I/*analysis

BACKGROUND: Our objective was to evaluate the accuracy of cardiovascular disease (CVD) risk score classification by direct LDL cholesterol (dLDL-C), calculated LDL cholesterol (cLDL-C), and non-HDL cholesterol (non-HDL-C) compared to classification by reference measurement procedures (RMPs) performed at the CDC. METHODS: Weexamined 175 individuals, including 138 with CVD or conditions that may affect LDL-C measurement. dLDL-C measurements were performed using Denka, Kyowa, Sekisui, Serotec, Sysmex, UMA, and Wako reagents. cLDL-C was calculated by the Friedewald equation, using each manufacturer's direct HDL-C assay measurements, and total cholesterol and triglyceride measurements by Roche and Siemens (Advia) assays, respectively. RESULTS: For participants with triglycerides <2.26 mmol/L (<200 mg/dL), the overall misclassification rate for the CVD risk score ranged from 5% to 17% for cLDL-C methods and 8% to 26% for dLDL-C methods when compared to the RMP. Only Wako dLDL-C had fewer misclassifications than its corresponding cLDL-C method (8% vs 17%; P<0.05). Non-HDL-C assays misclassified fewer patients than dLDL-C for 4 of 8 methods (P<0.05). For participants with triglycerides > or =2.26 mmol/L (> or =200 mg/dL) and <4.52 mmol/L (<400 mg/dL), dLDL-C methods, in general, performed better than cLDL-C methods, and non-HDL-C methods showed better correspondence to the RMP for CVD risk score than either dLDL-C or cLDL-C methods. CONCLUSIONS: Except for hypertriglyceridemic individuals, 7 of 8 dLDL-C methods failed to show improved CVD risk score classification over the corresponding cLDL-C methods. Non-HDL-C showed overall the best concordance with the RMP for CVD risk score classification of both normal and hypertriglyceridemic individuals.
Cardiovascular Diseases ; Cholesterol ; Cholesterol, LDL ; Humans ; Indicators and Reagents ; Triglycerides

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics com-munity. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry (LC–MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED’s database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results.

The Division of Cancer Prevention of the National Cancer Institute (NCI) and the Office of Disease Prevention of the National Institutes of Health co-sponsored the Translational Advances in Cancer Prevention Agent Development Meeting on August 27 to 28, 2020. The goals of this meeting were to foster the exchange of ideas and stimulate new collaborative interactions among leading cancer prevention researchers from basic and clinical research; highlight new and emerging trends in immunoprevention and chemoprevention as well as new information from clinical trials; and provide information to the extramural research community on the significant resources available from the NCI to promote prevention agent development and rapid translation to clinical trials. The meeting included two plenary talks and five sessions covering the range from pre-clinical studies with chemo/immunopreventive agents to ongoing cancer prevention clinical trials. In addition, two NCI informational sessions describing contract resources for the preclinical agent development and cooperative grants for the Cancer Prevention Clinical Trials Network were also presented.

The Division of Cancer Prevention of the National Cancer Institute (NCI) and the Office of Disease Prevention of the National Institutes of Health co-sponsored the Translational Advances in Cancer Prevention Agent Development Meeting on August 27 to 28, 2020. The goals of this meeting were to foster the exchange of ideas and stimulate new collaborative interactions among leading cancer prevention researchers from basic and clinical research; highlight new and emerging trends in immunoprevention and chemoprevention as well as new information from clinical trials; and provide information to the extramural research community on the significant resources available from the NCI to promote prevention agent development and rapid translation to clinical trials. The meeting included two plenary talks and five sessions covering the range from pre-clinical studies with chemo/immunopreventive agents to ongoing cancer prevention clinical trials. In addition, two NCI informational sessions describing contract resources for the preclinical agent development and cooperative grants for the Cancer Prevention Clinical Trials Network were also presented.

Pregnane X receptor (PXR) is a ligand-activated nuclear receptor that transcriptionally upregulates drug-metabolizing enzymes [e.g., cytochrome P450 3A4 (CYP3A4)] and transporters. Although the regulation of PXR target genes is well-characterized, less is known about the regulation of PXR protein level. By screening an RNAi library, we identified the F-box-only protein 44 (FBXO44) as a novel E3 ligase for PXR. PXR abundance increases upon knockdown of FBXO44, and, inversely, decreases upon overexpression of FBXO44. Further analysis revealed that FBXO44 interacts with PXR, leading to its ubiquitination and proteasomal degradation, and we determined that the F-box associated domain of FBXO44 and the ligand binding domain of PXR are required for the functional interaction. In summary, FBXO44 regulates PXR protein abundance, which has downstream consequences for CYP3A4 levels and drug-drug interactions. The results of this study provide new insight into the molecular mechanisms that regulate PXR protein level and activity and suggest the importance of considering how modulating E3 ubiquitin ligase activities will affect PXR-mediated drug metabolism.