Application of Hansch’s Model to Capsaicinoids and Capsinoids: A Study Using the Quantitative Structure−Activity Relationship. A Novel Method for the Synthesis of Capsinoids

We describe a synthetic approach for two families of compounds, the capsaicinoids and capsinoids, as part of a study of the quantitative relationship between structure and activity

Circulating microRNA Profiles during the Bovine Oestrous Cycle

Up to 50% of ovulations go undetected in modern dairy herds due to attenuated oestrus behavior and a lack of high-accuracy methods for detection of fertile oestrus. This significantly reduces overall herd productivity and constitutes a high economic burden to the dairy industry. MicroRNAs (miRNAs) are ubiquitous regulators of gene expression during both health and disease and they have been shown to regulate different reproductive processes. Extracellular miRNAs are stable and can provide useful biomarkers of tissue function; changes in circulating miRNA profiles have been reported during menstrual cycles. This study sought to establish the potential of circulating miRNAs as biomarkers of oestrus in cattle. We collected plasma samples from 8 Holstein-Friesian heifers on days Days 0, 8 and 16 of an oestrous cycle and analysed small RNA populations on each Day using two independent high-throughput approaches, namely, Illumina sequencing (n = 24 samples) and Qiagen PCR arrays (n = 9 sample pools, 3-4 samples / pool). Subsequently, we used RT-qPCR (n = 24 samples) to validate the results of high-throughput analyses, as well as to establish the expression profiles of additional miRNAs previously reported to be differentially expressed during reproductive cycles. Overall, we identified four miRNAs (let-7f, miR-125b, miR-145 and miR-99a-5p), the plasma levels of which distinctly increased (up to 2.2-fold, P < 0.05) during oestrus (Day 0) relative to other stages of the cycle (Days 8 and 16). Moreover, we identified several hundred different isomiRs and established their relative abundance in bovine plasma. In summary, our results reveal the dynamic nature of plasma miRNAs during the oestrous cycle and provide evidence of the feasibility of using circulating miRNAs as biomarkers of reproductive function in livestock in the future

Diagnostic value of late gadolinium enhancement at cardiovascular magnetic resonance to distinguish arrhythmogenic right ventricular cardiomyopathy from differentials

Background: While late gadolinium enhancement (LGE) is proposed as a diagnostic criterion for arrhythmogenic right ventricular cardiomyopathy (ARVC), the potential of LGE to distinguish ARVC from differentials remains unknown. We aimed to assess the diagnostic value of LGE for ARVC diagnosis. Methods: We included 132 subjects (60% male, 47 ± 11 years) who had undergone cardiac magnetic resonance imaging with LGE assessment for ARVC or ARVC differentials. ARVC was diagnosed as per 2010 Task Force Criteria (n = 55). ARVC differentials consisted of familial/genetic dilated cardiomyopathy (n = 25), myocarditis (n = 13), sarcoidosis (n = 20), and amyloidosis (n = 19). The diagnosis of all differentials was based on the most current standard of reference. The presence of LGE was evaluated using a 7-segment right ventricle (RV) and 17-segment left ventricle (LV) model. Subsequently, we assessed LGE patterns for every patient individually for fulfilling LV- and/or RV-LGE per Padua criteria, independent of their clinical diagnosis (i.e. phenotype). Diagnostic values were analyzed using sensitivity and specificity for any RV-LGE, any LV-LGE, RV-LGE per Padua criteria, and prevalence graphs for LV-LGE per Padua criteria. The optimal integration of LGE for ARVC diagnosis was determined using classification and regression tree analysis. Results: One-third (38%) of ARVC patients had RV-LGE, while half (51%) had LV-LGE. RV-LGE was less frequently observed in ARVC vs non-ARVC patients (38% vs 58%, p = 0.034) leading to a poor discriminatory potential (any RV-LGE: sensitivity 38%, specificity 42%; RV-LGE per Padua criteria: sensitivity 36%, specificity 44%). Compared to ARVC patients, non-ARVC patients more often had LV-LGE (91% vs 51%, p < 0.001) which was also more globally distributed (median 9 [interquartile range (IQR): 3–13] vs 0 [IQR: 0–3] segments, p < 0.001). The absence of anteroseptal and absence of extensive (≥5 segments) mid-myocardial LV-LGE, and absence of moderate (≥2 segments) mid-myocardial LV-LGE predicted ARVC with good diagnostic performance (sensitivity 93%, specificity 78%). Conclusion: LGE is often present in ARVC differentials and may lead to false positive diagnoses when used without knowledge of LGE patterns. Moderate RV-LGE without anteroseptal and mid-myocardial LV-LGE is typically observed in ARVC

Scaling relationships based on partition coefficients and body sizes have similarities and interactions

The LC50 of compounds with a similar biological effect, at a given exposure period, is frequently plotted log-log against the octanol-water partition coefficient and a straight line is fitted for interpolation purposes. This is also frequently done for physiological properties, such as the weight-specific respiration rate, as function of the body weight of individuals. This paper focuses on the remarkable observation that theoretical explanations for these relationships also have strong similarities. Both can be understood as result of the covariation of the values of parameters of models of a particular type for the underlying processes, while this covariation follows logically from the model structure. The one-compartment model for the uptake and elimination of compounds by organisms is basic to the BioConcentration Factor (BCF), or the partition coefficient; the standard Dynamic Energy Budget model is basic to the (ultimate) body size. The BCF is the ratio of the uptake and the elimination rates; the maximum body length is the ratio of the assimilation (i.e. uptake of resources) and the maintenance (i.e. use of resources) rates. This paper discusses some shortcomings of descriptive approaches and conceptual aspects of theoretical explanations. The strength of the theory is in the combination of why metabolic transformation depends both on the BCF and the body size. We illustrate the application of the theory with several data sets from the literature