The diabetes-linked transcription factor Pax4 is expressed in human pancreatic islets and is activated by mitogens and GLP-1

We previously demonstrated that the transcription factor Pax4 is important for β-cell replication and survival in rat islets. Herein, we investigate Pax4 expression in islets of non-diabetic and diabetic donors, its regulation by mitogens, glucose and the incretin GLP-1 and evaluate its effect on human islet proliferation. Pax4 expression was increased in islets derived from Type 2 diabetic donors correlating with hyperglycaemia. In vitro studies on non diabetic islets demonstrated that glucose, betacellulin, activin A, GLP-1 and insulin increased Pax4 mRNA levels. Glucose-induced Pax4 expression was abolished by the inhibitors LY294002, PD98050 or H89. Surprisingly, increases in Pax4 expression did not prompt a surge in human islet cell replication. Furthermore, expression of the proliferation marker gene Id2 remained unaltered. Adenoviral-mediated expression of human Pax4 resulted in a small increase in Bcl-xL expression while Id2 transcript levels and cell replication were unchanged in human islets. In contrast, overexpression of mouse Pax4 induced human islet cell proliferation. Treatment of islets with 5-Aza-2′-deoxycytidine induced Pax4 without stimulating Bcl-xL and Id2 expression. Human Pax4 DNA binding activity was found to be lower than that of the mouse homologue. Thus, human pax4 gene expression is epigenetically regulated and induced by physiological stimuli through the concerted action of multiple signalling pathways. However, it is unable to initiate the transcriptional replication program likely due to post-translational modifications of the protein. The latter highlights fundamental differences between human and rodent islet physiology and emphasizes the importance of validating results obtained with animal models in human tissue

Prothrombinase-Induced Clotting Time to Measure Drug Concentrations of Rivaroxaban, Apixaban, and Edoxaban in Clinical Practice: A Cross-Sectional Study.

Prothrombinase-induced clotting time (PiCT) is proposed as a rapid and inexpensive laboratory test to measure direct oral anticoagulant (DOAC) drug levels. In a prospective, multicenter cross-sectional study, including 851 patients, we aimed to study the accuracy of PiCT in determining rivaroxaban, apixaban, and edoxaban drug concentrations and assessed whether clinically relevant drug levels could be predicted correctly. Citrated plasma samples were collected, and the Pefakit® PiCT was utilized. Ultra-high performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to measure drug concentrations. Cut-off levels were established using receiver-operating characteristics curves. We calculated sensitivities and specificities with respect to clinically relevant drug concentrations. Spearman's correlation coefficient between PiCT and drug concentrations was 0.85 in the case of rivaroxaban (95% CI 0.82, 0.88), 0.66 for apixaban (95% CI 0.60, 0.71), and 0.78 for edoxaban (95% CI 0.65, 0.86). The sensitivity to detect clinically relevant drug concentrations was 85.1% in the case of 30 µg L-1 (95% CI 82.0, 87.7; specificity 77.9; 72.1, 82.7), 85.7% in the case of 50 µg L-1 (82.4, 88.4; specificity 77.3; 72.5, 81.5), and 85.1% in the case of 100 µg L-1 (80.9, 88.4; specificity 73.2%; 69.1, 76.9). In conclusion, the association of PiCT with DOAC concentrations was fair, and the majority of clinically relevant drug concentrations were correctly predicted

Cardiovascular risk prediction - a systems medicine approach

Background Guidelines for the prevention of cardiovascular disease (CVD) have recommended the assessment of the total CVD risk by risk scores. Current risk algorithms are low in sensitivity and specificity and they have not incorporated emerging risk markers for CVD. We suggest that CVD risk assessment can be still improved. We have developed a long-term risk prediction model of cardiovascular mortality in patients with stable coronary artery disease (CAD) based on newly available machine learning and on an extended dataset of new biomarkers.Methods 2953 participants of the Ludwigshafen Risk and Cardiovascular Health (LURIC) study were included. 184 laboratory and 21 demographic markers were ranked according to their contribution to risk of cardiovascular (CV) mortality using different data mining approaches. A self-learning bioinformatics workflow, including seven different machine learning algorithms, was developed for CV risk prediction. The study population was stratified into patients with and without significant CAD. Thereby, significant CAD was defined as a lumen narrowing of 50 or more in at least one of the coronary segments or a history of definite myocardial infarction. The machine learning models in both subpopulations were compared with established CV risk assessment tools.Results After a follow-up of 10 years, 603 (20.4%) patients died of cardiovascular causes. 95% patients without CAD deceased within ten years and 247 (13.2 %) patients with CAD within 5 years. Overall and in patients without CAD, NT-proBNP (N-terminal pro B-type natriuretic peptide), TnT (Troponin T), estimated cystatin c based GFR (glomerular filtration rate) and age were the highest ranked predictors, while in patients with CAD, NT-proBNP, GFR, CT-proAVP (C-terminal pro arginine vasopressin) and TNT were highest predictive. In the comparison with the FRS, PROCAM and ESC risk scores, the machine learning workflow produced more accurate and robust CV mortality prediction in patients without CAD. Equivalent CV risk prediction was obtained in the CAD subpopulation in comparison with the Marschner risk score. Overall, the existing algorithms in general tend to assign more patients into the medium risk groups, while the machine learning algorithms tend to have a clearer risk/no risk assignment. The framework is available upon request.Conclusion We have developed a fully automated and self-validating computational framework of machine learning techniques using an extensive database of clinical, routinely and non-routinely measured laboratory data. Our framework predicts long-term CV mortality at least as accurate as existing CVD risk scores. A combination of four highly ranked biomarkers and the random forest approach showed the best predictive results. Moreover, a dynamic computational model has several advantages over static CVD risk prediction tools: it is freeware, transparent, variable, transferable and expandable to any population, types of events and time frames

Determination of Anti-Xa Inhibitor Plasma Concentrations Using a Universal Edoxaban Calibrator

A universal calibrator for the determination of all anti-Xa inhibitors would support laboratory processes. We aimed to test the clinical performance of an anti-Xa assay utilizing a universal edoxaban calibrator to determine clinically relevant concentrations of all anti-Xa inhibitors. Following a pilot study, we enrolled 553 consecutive patients taking rivaroxaban, edoxaban, or apixaban from nine study centers in a prospective cross-sectional study. The Technochrom$^{®}$ anti-Xa assay was conducted using the Technoview$^{®}$ edoxaban calibrator. Using ultra-high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS), anti-Xa inhibitor drug concentrations were determined. Sensitivities and specificities to detect three clinically relevant drug concentrations (30 µgL$^{-1}$, 50 µgL$^{-1}$, 100 µgL$^{-1}$) were determined. Overall, 300 patients treated with rivaroxaban, 221 with apixaban, and 32 with edoxaban were included. The overall correlation coefficient (r$_{s}$) was 0.95 (95% CI 0.94, 0.96). An area under the receiver operating characteristic curve of 0.96 for 30 µgL$^{-1}$, 0.98 for 50 µgL$^{-1}$, and 0.99 for 100 µgL$^{-1}$ was found. The sensitivities were 92.3% (95% CI 89.2, 94.6), 92.7% (89.4, 95.1), and 94.8% (91.1, 97.0), respectively (specificities 82.2%, 93.7%, and 94.4%). In conclusion, the clinical performance of a universal, edoxaban-calibrated anti-Xa assay was solid and most drug concentrations were predicted correctly

Accuracy of a Single, Heparin-Calibrated Anti-Xa Assay for the Measurement of Rivaroxaban, Apixaban, and Edoxaban Drug Concentrations: A Prospective Cross-Sectional Study

Background: Applying a single anti-Xa assay, calibrated to unfractionated heparin to measure rivaroxaban, apixaban, and edoxaban would simplify laboratory procedures and save healthcare costs. Aim: We hypothesized that a heparin-calibrated anti-Xa assay would accurately measure rivaroxaban, apixaban, and edoxaban drug concentrations and correctly predict clinically relevant drug levels. Methods: This analysis is part of the Simple-Xa study, a prospective multicenter cross-sectional study conducted in clinical practice. Patients treated with rivaroxaban, apixaban, or edoxaban were included. Anti-Xa activity was measured using the Siemens INNOVANCE® Heparin assay. Drug concentrations were determined using ultra-high performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Cut-off levels were determined in a derivation dataset (50% of patients) and sensitivities and specificities were calculated in a verification dataset (50% of patients). Results: Overall, 845 patients were available for analysis. Correlation coefficients (r s ) between the heparin-calibrated anti-Xa assay and drug concentrations were 0.97 (95% CI 0.97, 0.98) for rivaroxaban, 0.96 (0.96, 0.97) for apixaban, and 0.96 (0.94, 0.99) for edoxaban. The area under the receiver operating characteristics curve (ROC) was 0.99 for all clinically relevant drug concentrations. In the verification dataset, the sensitivity was 94.2% (95% CI 90.8-96.6) for 30 μg L-1, 95.8% (92.4-98.0) for 50 μg L-1, and 98.7% (95.5-99.9) for 100 μg L-1. Specificities were 86.3% (79.2-91.7), 89.8% (84.5-93.7), and 88.7% (84.2-92.2), respectively. Conclusion: In a large prospective study in clinical practice, a strong correlation of heparin-calibrated anti-Xa measurements with LC-MS/MS results was observed and clinically relevant drug concentrations were predicted correctly. Keywords: anti-Xa assay; diagnostic accuracy; direct oral anticoagulants; laboratory monitoring; rivaroxaban

Identification of a stable complex between a [NiFe]‐hydrogenase catalytic subunit and its maturation protease

Salmonella enterica serovar Typhimurium has the ability to use molecular hydrogen as a respiratory electron donor. This is facilitated by three [NiFe]‐hydrogenases termed Hyd‐1, Hyd‐2, and Hyd‐5. Hyd‐1 and Hyd‐5 are homologous oxygen‐tolerant [NiFe]‐hydrogenases. A critical step in the biosynthesis of a [NiFe]‐hydrogenase is the proteolytic processing of the catalytic subunit. In this work, the role of the maturation protease encoded within the Hyd‐5 operon, HydD, was found to be partially complemented by the maturation protease encoded in the Hyd‐1 operon, HyaD. In addition, both maturation proteases were shown to form stable complexes, in vivo and in vitro, with the catalytic subunit of Hyd‐5. The protein–protein interactions were not detectable in a strain that could not make the enzyme metallocofactor

Frequency and type of drug-related side effects necessitating treatment discontinuation in the Swiss Inflammatory Bowel Disease Cohort.

BACKGROUND AND AIM Systematic analyses of inflammatory bowel disease (IBD) drug-related side effects necessitating treatment cessation in large cohorts of patients with IBD are scarce. We aimed to assess the frequency and type of drug-related side effects requiring drug cessation in patients included in the Swiss IBD Cohort. PATIENTS AND METHODS A retrospective review was performed of data from the Swiss IBD Cohort physician questionnaires documenting a treatment cessation for the following drug categories: aminosalicylates, topical and systemic steroids, thiopurines, methotrexate, tumor necrosis factor-antagonists, and calcineurin inhibitors (tacrolimus, cyclosporine). RESULTS A total of 3192 patients were analyzed, of whom 1792 (56.1%) had Crohn's disease, 1322 (41.4%) had ulcerative colitis, and 78 (2.5%) had IBD unclassified. Of 3138 patients treated with IBD drugs, 2129 (67.8%) presented with one or several drug-related side effects necessitating drug cessation. We found a significant positive correlation between the number of concomitantly administered IBD drugs and the occurrence of side effects requiring drug cessation (P<0.001). Logistic regression modeling identified Crohn's disease diagnosis [odds ratio (OR)=1.361, P=0.017], presence of extraintestinal manifestations (OR=2.262, P<0.001), IBD-related surgery (OR=1.419, P=0.006), and the increasing number of concomitantly used IBD drugs [OR=2.007 (P<0.001) for two concomitantly used IBD drugs; OR=3.225 (P<0.001) for at least three concomitantly used IBD drugs] to be associated significantly with the occurrence of IBD drug-related adverse events that necessitated treatment cessation. CONCLUSION Physicians should keep in mind that the number of concomitantly administered IBD drugs is the main risk factor for drug-related adverse events necessitating treatment cessation