Drug-induced acute myocardial infarction: identifying 'prime suspects' from electronic healthcare records-based surveillance system.

BACKGROUND: Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are being used in 'real-world' settings. OBJECTIVE: To describe a strategy that identifies potentially drug-induced acute myocardial infarction (AMI) from a large international healthcare data network. METHODS: Post-marketing safety surveillance was conducted in seven population-based healthcare databases in three countries (Denmark, Italy, and the Netherlands) using anonymised demographic, clinical, and prescription/dispensing data representing 21,171,291 individuals with 154,474,063 person-years of follow-up in the period 1996-2010. Primary care physicians' medical records and administrative claims containing reimbursements for filled prescriptions, laboratory tests, and hospitalisations were evaluated using a three-tier triage system of detection, filtering, and substantiation that generated a list of drugs potentially associated with AMI. Outcome of interest was statistically significant increased risk of AMI during drug exposure that has not been previously described in current literature and is biologically plausible. RESULTS: Overall, 163 drugs were identified to be associated with increased risk of AMI during preliminary screening. Of these, 124 drugs were eliminated after adjustment for possible bias and confounding. With subsequent application of criteria for novelty and biological plausibility, association with AMI remained for nine drugs ('prime suspects'): azithromycin; erythromycin; roxithromycin; metoclopramide; cisapride; domperidone; betamethasone; fluconazole; and megestrol acetate. LIMITATIONS: Although global health status, co-morbidities, and time-invariant factors were adjusted for, residual confounding cannot be ruled out. CONCLUSION: A strategy to identify potentially drug-induced AMI from electronic healthcare data has been proposed that takes into account not only statistical association, but also public health relevance, novelty, and biological plausibility. Although this strategy needs to be further evaluated using other healthcare data sources, the list of 'prime suspects' makes a good starting point for further clinical, laboratory, and epidemiologic investigation

Eley–Rideal, the Other Mechanism

ISSN:1022-5528ISSN:1572-902

Effects of Cyclic Tensile Strain on Chondrocyte Metabolism: A Systematic Review

Chondrocytes reorganize the extracellular matrix of articular cartilage in response to externally applied loads. Thereby, different loading characteristics lead to different biological responses. Despite of active research in this area, it is still unclear which parts of the extracellular matrix adapt in what ways, and how specific loading characteristics affect matrix changes. This review focuses on the influence of cyclic tensile strain on chondrocyte metabolism in vitro. It also aimed to identify anabolic or catabolic chondrocyte responses to different loading protocols. The key findings show that loading cells up to 3% strain, 0.17 Hz, and 2 h, resulted in weak or no biological responses. Loading between 3-10% strain, 0.17-0.5 Hz, and 2-12 h led to anabolic responses; and above 10% strain, 0.5 Hz, and 12 h catabolic events predominated. However, this review also discusses that various other factors are involved in the remodeling of the extracellular matrix in response to loading, and that parameters like an inflammatory environment might influence the biological response

Soil exchange rates of COS and CO18O differ with the diversity of microbial communities and their carbonic anhydrase enzymes

Differentiating the contributions of photosynthesis and respiration to the global carbon cycle is critical for improving predictive climate models. Carbonic anhydrase (CA) activity in leaves is responsible for the largest biosphere-atmosphere trace gas fluxes of carbonyl sulfide (COS) and the oxygen-18 isotopologue of carbon dioxide (CO18O) that both reflect gross photosynthetic rates. However, CA activity also occurs in soils and will be a source of uncertainty in the use of COS and CO18O as carbon cycle tracers until process-based constraints are improved. In this study, we measured COS and CO18O exchange rates and estimated the corresponding CA activity in soils from a range of biomes and land use types. Soil CA activity was not uniform for COS and CO2, and patterns of divergence were related to microbial community composition and CA gene expression patterns. In some cases, the same microbial taxa and CA classes catalyzed both COS and CO2 reactions in soil, but in other cases the specificity towards the two substrates differed markedly. CA activity for COS was related to fungal taxa and β-D-CA expression, whereas CA activity for CO2 was related to algal and bacterial taxa and α-CA expression. This study integrates gas exchange measurements, enzyme activity models, and characterization of soil taxonomic and genetic diversity to build connections between CA activity and the soil microbiome. Importantly, our results identify kinetic parameters to represent soil CA activity during application of COS and CO18O as carbon cycle tracers