Correlation weighting of valence shells in QSAR analysis of toxicity

In the rainbow trout (Oncorhynchus mykiss), we studied the acute toxicity LC(50)-96 h of 274 organic pesticides with a wide variety of molecular structures. Optimization of correlation weights of local and global graph invariants (OCWLGI) gave quantitative structure-activity relationships (QSARs) for predicting toxicity. We used a labeled hydrogen-filled graph (LHFG) to elucidate the molecular structure. We also used the extended connectivity of zero ((0)EC(k)), first ((1)EC(k)), and second ((2)EC(k)) order, numbers of path lengths 2 (P2(k)) and 3 (P3(k)) starting from a given vertex in the LHFG, and valence shells of second order (S2(k)). S2(k) is the sum of the degree of vertices at distance 2 from a given vertex k. The presence of three-, five-, and six-member cycles and hydrogen bond indices suggested they might be used as global LHFG invariants. We applied this method to a broad set of pesticides, to predict toxicity for the trout. The best model used weighted S2(k) and global LHFG invariants. Statistical characteristics of this model are as follows: n=233, r(2)=0.7689, r(2)(pred)=0.7688, s=0.75, F=769 (training set); n=41, r(2)=0.6421, r(2)(pred)=0.4241, s=1.14, F=70 (test set).     

Measurements of insulin responses as predictive markers of pancreatic beta-cell mass in normal and beta-cell-reduced lean and obese Göttingen minipigs in vivo

At present, the best available estimators of beta-cell mass in humans are those based on measurement of insulin levels or appearance rates in the circulation. In several animal models, these estimators have been validated against beta-cell mass in lean animals. However, as many diabetic humans are obese, a correlation between in vivo tests and beta-cell mass must be evaluated over a range of body weights to include different levels of insulin sensitivity. For this purpose, obese (n = 10) and lean (n = 25) G?ttingen minipigs were studied. Beta-cell mass had been reduced (n = 16 lean, n = 5 obese) with a combination of nicotinamide (67 mg/kg) and streptozotocin (125 mg/kg), acute insulin response (AIR) to intravenous glucose and/or arginine was tested, pulsatile insulin secretion was evaluated by deconvolution (n = 30), and beta-cell mass was determined histologically. AIR to 0.3 (r(2) = 0.4502, P < 0.0001) or 0.6 g/kg glucose (r(2) = 0.6806, P < 0.0001), 67 mg/kg arginine (r(2) = 0.5730, P < 0.001), and maximum insulin concentration (r(2) = 0.7726, P < 0.0001) were all correlated to beta-cell mass when evaluated across study groups, and regression lines were not different between lean and obese groups except for AIR to 0.3 g/kg glucose. Baseline pulse mass was not significantly correlated to beta-cell mass across the study groups (r(2) = 0.1036, NS), whereas entrained pulse mass did show a correlation across groups (r(2) = 0.4049, P < 0.001). This study supports the use of in vivo tests of insulin responses to evaluate beta-cell mass over a range of body weights in the minipig. Extensive stimulation of insulin secretion by a combination of glucose and arginine seems to give the best correlation to beta-cell mass.     

Application of long-range order to predict unfolding rates of two-state proteins

Predicting the experimental unfolding rates of two-state proteins and models describing the unfolding rates of these proteins is quite limited because of the complexity present in the unfolding mechanism and the lack of experimental unfolding data compared with folding data. In this work, 25 two-state proteins characterized by Maxwell et al. (Protein Sci 2005;14:602–616) using a consensus set of experimental conditions were taken, and the parameter long-range order (LRO) derived from their three-dimensional structures were related with their experimental unfolding rates ln(k(u)). From the total data set of 30 proteins used by Maxwell et al. (Protein Sci 2005;14:602–616), five slow-unfolding proteins with very low unfolding rates were considered to be outliers and were not included in our data set. Except all beta structural class, LRO of both the all-alpha and mixed-class proteins showed a strong inverse correlation of r = -0.99 and -0.88, respectively, with experimental ln(k(u)). LRO shows a correlation of -0.62 with experimental ln(k(u)) for all-beta proteins. For predicting the unfolding rates, a simple statistical method has been used and linear regression equations were developed for individual structural classes of proteins using LRO, and the results obtained showed a better agreement with experimental results.     

The convergent validity between two objective methods for quantifying training load in young taekwondo athletes

Various studies used objective heart rate (HR)-based methods to assess training load (TL). The common methods were Banister's Training Impulse (TRIMP; weights the duration using a weighting factor) and Edwards' TL (a summated HR zone score). Both the methods use the direct physiological measure of HR as a fundamental part of the calculation. To eliminate the redundancy of using various methods to quantify the same construct (i.e., TL), we have to verify if these methods are strongly convergent and are interchangeable. Therefore, the aim of this study was to investigate the convergent validity between Banister's TRIMP and Edwards' TL used for the assessment of internal TL. The HRs were recorded and analyzed during 10 training weeks of the preseason period in 10 male Taekwondo (TKD) athletes. The TL was calculated using Banister's TRIMP and Edwards' TL. Pearson product moment correlation coefficient was used to evaluate the convergent validity between the 2 methods for assessing TL. Very large to nearly perfect relationships were found between individual Banister's TRIMP and Edwards' TL (r values from 0.80 to 0.99; p < 0.001). Pooled Banister's TRIMP and pooled Edwards' TL (pooled data n = 284) were nearly largely correlated (r = 0.89; p < 0.05; 95% confidence interval: 0.86-0.91). In conclusion, these findings suggest that these 2 objective methods, measuring a similar construct, are interchangeable.