A Quantitative Method using Near Infrared Imaging Spectroscopy for Determination of Surface Composition of Tablet Dosage Forms: an Example of Spirolactone Tablets

In this work, near infrared (NIR) imaging spectroscopy was employed in the study of the distribution of the active pharmaceutical ingredient (API) spironolactone and its excipients in tablets. Analyses were performed using 50 mu m spatial resolution to analyze 16 mm(2) of each standard tablet. Interval partial least squares models were used for API and excipients quantification in every pixel in order to obtain concentration maps for each compound. It was obtained errors of quantification between 0.49 and 1.26% when performed the cross-validation using spectral average of each tablet. These calibration models were used to predict individual concentration of each compound in the tablet, in every pixel. The average concentration of all pixels, for each compound yield errors, was between 0.05 and 1.06%. These results indicate that the models were able to quantify all compounds in each pixel. This approach is necessary since it is not possible to know the real concentration of each compound in the pixels.2381570157

Multivariate curve resolution of pH gradient flow injection mixture analysis with correction of the Schlieren effect

Multivariate curve resolution using alternating least squares (MCR-ALS) was used to quantify ascorbic (AA) and acetylsalicylic (ASA) acids in four pharmaceutical samples using a flow injection analysis (FIA) system with pH gradient and a diode array (DAD) spectrometer as a detector. Four different pharmaceutical drugs were analyzed, giving a data array of dimensions 51 x 291 x 61, corresponding respectively to number of samples, FIA times and spectral wavelengths. MCR-ALS was applied to these large data sets using different constraints to have optimal resolution and optimal quantitative estimations of the two analytes (AA and ASA). Since both analytes give an acid-basic pair of species contributing to the UV recorded signal, at least four components sholuld be proposed to model AA and ASA in synthetic mixture samples. Moreover, one additional component was needed to resolve accurately the Schlieren effect and another additional component was also needed to model the presence of possible interferences (like caffeine) in the commercial drugs tablets, giving therefore a total number of 6 independent components needed. The best quantification relative errors were around 2% compared to the reference values obtained by HPLC and by the oxidation-reduction titrimetric method, for ASA and AA respectively. In this work, the application of MCR-ALS allowed for the first time the full resolution of the FIA diffusion profile due to the Schlieren effect as an independent signal contribution, suggesting that the proposed MCR-ALS method allows for its accurate correction in FIA-DAD systems.133677478

State history and economic development: evidence from six millennia

The presence of a state is one of the most reliable historical predictors of social and economic development. In this article, we complete the coding of an extant indicator of state presence from 3500 BCE forward for almost all but the smallest countries of the world today. We outline a theoretical framework where accumulated state experience increases aggregate productivity in individual countries but where newer or relatively inexperienced states can reach a higher productivity maximum by learning from the experience of older states. The predicted pattern of comparative development is tested in an empirical analysis where we introduce our extended state history variable. Our key finding is that the current level of economic development across countries has a hump-shaped relationship with accumulated state history

Evolution of Chagas’ disease in Brazil. Epidemiological perspective and challenges for the future: a critical review

Aims: This paper aimed to provide a critical review of the evolution of Chagas’ disease in Brazil, its magnitude, historical development and management, and challenges for the future. Methods: A literature search was performed using PubMed, SciELO and Google Scholar and throughout collected articles’ references. Narrative analysis was structured around five main themes identified: vector transmission, control program, and transfusion, oral and congenital transmission. Results: In Brazil, the Chagas’ disease Control Program was fully implemented in the 1980s, when it reached practically all the endemic areas, and in 1991, the Southern Cone Initiative was created, aiming to eliminate the disease transmission through eliminating the Triatoma infestans and controlling blood banks. As a result, the prevalence of chagasic donors in blood banks reduced from 4.4% in the 80s to 0.2% in 2005. In 2006, PAHO certified the interruption of transmission of Chagas’ disease through this vector in Brazil. However, there are still challenges, such as the domiciliation of new vector species, the need for medical care of the infected individuals, the prevention of alternative mechanisms of transmission, the loss of political concern regarding the disease and, the weakening of the control program. Conclusion: Despite the progress towards control, there are still many challenges ahead to maintain and expand such control and minimise the risk of re-emergence

Evolving neural network optimization of cholesteryl ester separation by reversed-phase HPLC

Cholesteryl esters have antimicrobial activity and likely contribute to the innate immunity system. Improved separation techniques are needed to characterize these compounds. In this study, optimization of the reversed-phase high-performance liquid chromatography separation of six analyte standards (four cholesteryl esters plus cholesterol and tri-palmitin) was accomplished by modeling with an artificial neural network–genetic algorithm (ANN-GA) approach. A fractional factorial design was employed to examine the significance of four experimental factors: organic component in the mobile phase (ethanol and methanol), column temperature, and flow rate. Three separation parameters were then merged into geometric means using Derringer’s desirability function and used as input sources for model training and testing. The use of genetic operators proved valuable for the determination of an effective neural network structure. Implementation of the optimized method resulted in complete separation of all six analytes, including the resolution of two previously co-eluting peaks. Model validation was performed with experimental responses in good agreement with model-predicted responses. Improved separation was also realized in a complex biological fluid, human milk. Thus, the first known use of ANN-GA modeling for improving the chromatographic separation of cholesteryl esters in biological fluids is presented and will likely prove valuable for future investigators involved in studying complex biological samples

Predicting sample size required for classification performance

<p>Abstract</p> <p>Background</p> <p>Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target.</p> <p>Methods</p> <p>We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method.</p> <p>Results</p> <p>A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p < 0.05).</p> <p>Conclusions</p> <p>This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.</p

The Genomics of Speciation in Drosophila: Diversity, Divergence, and Introgression Estimated Using Low-Coverage Genome Sequencing

In nature, closely related species may hybridize while still retaining their distinctive identities. Chromosomal regions that experience reduced recombination in hybrids, such as within inversions, have been hypothesized to contribute to the maintenance of species integrity. Here, we examine genomic sequences from closely related fruit fly taxa of the Drosophila pseudoobscura subgroup to reconstruct their evolutionary histories and past patterns of genic exchange. Partial genomic assemblies were generated from two subspecies of Drosophila pseudoobscura (D. ps.) and an outgroup species, D. miranda. These new assemblies were compared to available assemblies of D. ps. pseudoobscura and D. persimilis, two species with overlapping ranges in western North America. Within inverted regions, nucleotide divergence among each pair of the three species is comparable, whereas divergence between D. ps. pseudoobscura and D. persimilis in non-inverted regions is much lower and closer to levels of intraspecific variation. Using molecular markers flanking each of the major chromosomal inversions, we identify strong crossover suppression in F1 hybrids extending over 2 megabase pairs (Mbp) beyond the inversion breakpoints. These regions of crossover suppression also exhibit the high nucleotide divergence associated with inverted regions. Finally, by comparison to a geographically isolated subspecies, D. ps. bogotana, our results suggest that autosomal gene exchange between the North American species, D. ps. pseudoobscura and D. persimilis, occurred since the split of the subspecies, likely within the last 200,000 years. We conclude that chromosomal rearrangements have been vital to the ongoing persistence of these species despite recent hybridization. Our study serves as a proof-of-principle on how whole genome sequencing can be applied to formulate and test hypotheses about species formation in lesser-known non-model systems