Determination and Validation of Nimesulide in Pharmaceutical Formulation by Near Infrared Spectroscopy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The determination of nimesulide in pharmaceutical formulation in the range of 10.38 to 39.47% m/m using near infrared spectroscopy and multivariate calibration based on partial least squares (PLS) and net analyte signal (NAS) was studied and validated by establishing its figures of merit. Suitable results were obtained, with limit of detection of 0.61%, limit quantification of 2.03%, accuracy estimated as root mean square error of prediction (RMSEP) of 1.05%, mean selectivity of 0.006, sensitivity of 0.004%, inverse analytical sensitivity of (0.20%)(-1) and signal-to-noise ratio of 181. In addition, it was obtained relative errors lower than 10% that are acceptable values for quality control of this drug. These results indicate that the proposed method can be used in pharmaceutical industries as an alternative to standard analytical procedures.211019291936Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)International Institute of Pharmaceutical Researches (IIPF)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Alterations in Task-Related Brain Activation in Children, Adolescents and Young Adults at Familial High-Risk for Schizophrenia or Bipolar Disorder - A Systematic Review.

Children, adolescents, and young adults with at least one first-degree relative [familial high-risk (FHR)] with either schizophrenia (SZ) or bipolar disorder (BD) have a one-in-two risk of developing a psychiatric disorder. Here, we review functional magnetic resonance imaging (fMRI) studies which examined task-related brain activity in young individuals with FHR-SZ and FHR-BD. A systematic search identified all published task-related fMRI studies in children, adolescents, and young adults below an age of 27 years with a first-degree relative with SZ or BD, but without manifest psychotic or affective spectrum disorder themselves. The search identified 19 cross-sectional fMRI studies covering four main cognitive domains: 1) working memory (n = 3), 2) cognitive control (n = 4), 3) reward processing (n = 3), and 4) emotion processing (n = 9). Thirteen studies included FHR-BD, five studies included FHR-SZ, and one study included a pooled FHR group. In general, task performance did not differ between the respective FHR groups and healthy controls, but 18 out of the 19 fMRI studies revealed regional alterations in task-related activation. Brain regions showing group differences in peak activation were regions associated with the respective task domain and showed little overlap between FHR-SZ and FHR-BD. The low number of studies, together with the low number of subjects, and the substantial heterogeneity of employed methodological approaches within the domain of working memory, cognitive control, and reward processing impedes finite conclusions. Emotion processing was the most investigated task domain in FHR-BD. Four studies reported differences in activation of the amygdala, and two studies reported differences in activation of inferior frontal/middle gyrus. Together, these studies provide evidence for altered brain processing of emotions in children, adolescents, and young adults at FHR-BD. More studies of higher homogeneity, larger sample sizes and with a longitudinal study design are warranted to prove a shared or specific FHR-related endophenotypic brain activation in young first-degree relatives of individuals with SZ or BD, as well as to pinpoint specific alterations in brain activation during cognitive-, emotional-, and reward-related tasks

Asymmetric Dispersal and Colonization Success of Amazonian Plant-Ants Queens

The dispersal ability of queens is central to understanding ant life-history evolution, and plays a fundamental role in ant population and community dynamics, the maintenance of genetic diversity, and the spread of invasive ants. In tropical ecosystems, species from over 40 genera of ants establish colonies in the stems, hollow thorns, or leaf pouches of specialized plants. However, little is known about the relative dispersal ability of queens competing for access to the same host plants. We used empirical data and inverse modeling—a technique developed by plant ecologists to model seed dispersal—to quantify and compare the dispersal kernels of queens from three Amazonian ant species that compete for access to host-plants. We found that the modal colonization distance of queens varied 8-fold, with the generalist ant species (Crematogaster laevis) having a greater modal distance than two specialists (Pheidole minutula, Azteca sp.) that use the same host-plants. However, our results also suggest that queens of Azteca sp. have maximal distances that are four-sixteen times greater than those of its competitors. We found large differences between ant species in both the modal and maximal distance ant queens disperse to find vacant seedlings used to found new colonies. These differences could result from interspecific differences in queen body size, and hence wing musculature, or because queens differ in their ability to identify potential host plants while in flight. Our results provide support for one of the necessary conditions underlying several of the hypothesized mechanisms promoting coexistence in tropical plant-ants. They also suggest that for some ant species limited dispersal capability could pose a significant barrier to the rescue of populations in isolated forest fragments. Finally, we demonstrate that inverse models parameterized with field data are an excellent means of quantifying the dispersal of ant queens

The Brain Matures with Stronger Functional Connectivity and Decreased Randomness of Its Network

We investigated the development of the brain's functional connectivity throughout the life span (ages 5 through 71 years) by measuring EEG activity in a large population-based sample. Connectivity was established with Synchronization Likelihood. Relative randomness of the connectivity patterns was established with Watts and Strogatz' (1998) graph parameters C (local clustering) and L (global path length) for alpha (∼10 Hz), beta (∼20 Hz), and theta (∼4 Hz) oscillation networks. From childhood to adolescence large increases in connectivity in alpha, theta and beta frequency bands were found that continued at a slower pace into adulthood (peaking at ∼50 yrs). Connectivity changes were accompanied by increases in L and C reflecting decreases in network randomness or increased order (peak levels reached at ∼18 yrs). Older age (55+) was associated with weakened connectivity. Semi-automatically segmented T1 weighted MRI images of 104 young adults revealed that connectivity was significantly correlated to cerebral white matter volume (alpha oscillations: r = 33, p<01; theta: r = 22, p<05), while path length was related to both white matter (alpha: max. r = 38, p<001) and gray matter (alpha: max. r = 36, p<001; theta: max. r = 36, p<001) volumes. In conclusion, EEG connectivity and graph theoretical network analysis may be used to trace structural and functional development of the brain

Neotropical ant-plant Triplaris americana attracts Pseudomyrmex mordax ant queens during seedling stages

The association between the myrmecophyte Triplaris and ants of the genus Pseudomyrmex is an often-reported example of mutualism in the Neotropics. The ants colonize the hollow stems of their hosts, and in exchange, the plants benefit from a reduced degree of herbivory. The previous studies have shown that workers can discriminate their host from other plants, including a closely related species. Little is known about how queens locate their host during the colonization process, but it has been suggested that host recognition is mediated by volatiles. Since queens of Pseudomyrmex mordax colonize their hosts during the seedling stage, we hypothesized that queens would discriminate leaves of seedlings from adult plants. To evaluate our hypothesis, we used a two-sided olfactometer, to test the preference of queens towards different leaf and plant ages of Triplaris americana. Virgin queens of Pseudomyrmex mordax preferred seedlings over adult plants, as well as plant leaves over empty controls, showing no discrimination for leaf age. Our results suggest that the volatiles virgin queens recognize are either produced or are more abundant at the early growing stage of the host when colonization is crucial for the host's survival. © 2017, The Author(s)

Tutorial: Multivariate Classification for Vibrational Spectroscopy in Biological Samples

Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, have been successful methods for studying the interaction of light with biological materials and facilitating novel cell biology analysis. Spectrochemical analysis is very attractive in disease screening and diagnosis, microbiological studies and forensic and environmental investigations because of its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyze biologically derived spectrochemical data to obtain accurate and reliable results. Multivariate classification comprises discriminant analysis and class-modeling techniques where multiple spectral variables are analyzed in conjunction to distinguish and assign unknown samples to pre-defined groups. The requirement for such protocols is demonstrated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical for extracting important information and visualizing it in a readily interpretable form. Hereby, we have provided a tutorial for multivariate classification analysis of vibrational spectroscopy data (FTIR, Raman and near-IR) highlighting a series of critical steps, such as preprocessing, data selection, feature extraction, classification and model validation. This is an essential aspect toward the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental