Automated hippocampal segmentation in 3D MRI using random undersampling with boosting algorithm

Pattern Analysis and Applications - The automated identification of brain structure in Magnetic Resonance Imaging is very important both in neuroscience research and as a possible clinical...     

Atrazine Inhalation Causes Neuroinflammation,Apoptosis and Accelerating Brain Aging

Background: exposure to environmental contaminants has been linked to an increased risk of neurological diseases and poor outcomes. Chemical name of Atrazine (ATR) is 6-chloro-N-ethyl-N′-(1-methylethyl)-1,3,5-triazine-2,4-diamine, and it is the most commonly used broad-spectrum herbicide in agricultural crops. Several studies have demonstrated that ATR has the potential to be harmful to the brain’s neuronal circuits. Until today nobody has explored the effect of ATR inhalation on young and aged mice. Methods: young and aged mice were subject to 25 mg of ATR in a vehicle made with saline and 10% of Dimethyl sulfoxide (DMSO) every day for 28 days. At the end of experiment different behavioral test were made and brain was collected. Results: exposure to ATR induced the same response in terms of behavioral alterations and motor and memory impairment in mice but in aged group was more marked. Additionally, in both young and aged mice ATR inhalations induced oxidative stress with impairment in physiological antioxidant response, lipid peroxidation, nuclear factor kappa-light-chain-enhancer of activated B cells (nf-κb) pathways activation with consequences of pro-inflammatory cytokines release and apoptosis. However, the older group was shown to be more sensitive to ATR inhalation. Conclusions: our results showed that aged mice were more susceptible compared to young mice to air pollutants exposure, put in place a minor physiologically response was seen when exposed to it.     

The Antimalarial Mefloquine Shows Activity against Mycobacterium abscessus,Inhibiting Mycolic Acid Metabolism

Some nontuberculous mycobacteria (NTM) are considered opportunistic pathogens. Nevertheless, NTM infections are increasing worldwide, becoming a major public health threat. Furthermore, there is no current specific drugs to treat these infections, and the recommended regimens generally lack efficacy, emphasizing the need for novel antibacterial compounds. In this paper, we focused on the essential mycolic acids transporter MmpL3, which is a well-characterized target of several antimycobacterial agents, to identify new compounds active against Mycobacterium abscessus (Mab). From the crystal structure of MmpL3 in complex with known inhibitors, through an in silico approach, we developed a pharmacophore that was used as a three-dimensional filter to identify new putative MmpL3 ligands within databases of known drugs. Among the prioritized compounds, mefloquine showed appreciable activity against Mab (MIC = 16 μg/mL). The compound was confirmed to interfere with mycolic acids biosynthesis, and proved to also be active against other NTMs, including drug-resistant clinical isolates. Importantly, mefloquine is a well-known antimalarial agent, opening the possibility of repurposing an already approved drug, which is a useful strategy to reduce the time and cost of disclosing novel drug candidates.     

Co-Ultra PEALut Enhances Endogenous Repair Response Following Moderate Traumatic Brain Injury

This study aimed to assess the neuro-regenerative properties of co-ultramicronized PEALut (Glialia^®), composed of palmitoylethanolamide (PEA) and the flavonoid luteolin (Lut), in an in vivo model of traumatic brain injury (TBI) and patients affected by moderate TBI. An increase in neurogenesis was seen in the mice at 72 h and 7 d after TBI. The co-ultra PEALut treatment helped the neuronal reconstitution process to restore the basal level of both novel and mature neurons; moreover, it induced a significant upregulation of the neurotrophic factors, which ultimately led to progress in terms of memory recall during behavioral testing. Moreover, our preliminary findings in a clinical trial suggested that Glialia^® treatment facilitated neural recovery on working memory. Thus, co-ultra PEALut (Glialia^®) could represent a valuable therapeutic agent for intensifying the endogenous repair response in order to better treat TBI.     

Data representations and generalization error in kernel based learning machines

This paper focuses on the problem of how data representation influences the generalization error of kernel based learning machines like support vector machines (SVM) for classification. Frame theory provides a well founded mathematical framework for representing data in many different ways. We analyze the effects of sparse and dense data representations on the generalization error of such learning machines measured by using leave-one-out error given a finite amount of training data. We show that, in the case of sparse data representations, the generalization error of an SVM trained by using polynomial or Gaussian kernel functions is equal to the one of a linear SVM. This is equivalent to saying that the capacity of separating points of functions belonging to hypothesis spaces induced by polynomial or Gaussian kernel functions reduces to the capacity of a separating hyperplane in the input space. Moreover, we show that, in general, sparse data representations increase or leave unchanged the generalization error of kernel based methods. Dense data representations, on the contrary, reduce the generalization error in the case of very large frames. We use two different schemes for representing data in overcomplete systems of Haar and Gabor functions, and measure SVM generalization error on benchmarked data sets.     

Resistant Starch Made from Banana Starch by Autoclaving and Debranching

Resistant starches (RS) were prepared from banana starch by debranching with pullulanase for different times and after autoclaving treatment. The different treatments produced seven RS products, which were tested with respect to available starch (AS), RS and in vitro hydrolysis rate. The control sample (without debranching) had the highest AS (80.5%) and the lowest RS content (9.1%). The samples debranched for 5 h and longer did not show significant differences (α = 0.05) in AS (approximately 72%) and RS (approximately 18%). The RS values obtained in the samples prepared were twice as high as that of the control sample. However, the sample debranched for the longest time had the highest hydrolysis rate, demonstrating that this product has a high digestion rate. Banana starch is a good source for RS preparation by autoclaving due to its high RS content and can be an alternative source in developing countries for obtaining a nutraceutic ingredient for functional food preparation.     

Isolation and characterization of Mexican chayote tuber (Sechium edule Sw.) starch

Starch was isolated from Mexican chayote tubers (Sechium edule Sw.) and the yield, physicochemical, rheological, and molecular characteristics were investigated. Commercial potato was used for comparison. Starch yield was 49% with a purity of 89.1%. AM content of chayote tuber starch was 26.3%. Birefringence was shown in chayote tuber starch and granules had diverse shapes such as spherical, oval, and polygonal, with size between 10 and 25 µm. B‐type XRD pattern was shown by chayote tuber starch. Chayote tuber starch had higher peak viscosity (PV) than potato starch and the maximum PV for chayote tuber starch was obtained at lower temperature. Flow properties of chayote tuber starch showed higher hysteresis than potato at the same concentration. In chayote tuber and potato starches, G′ > G″ at both temperatures. Chayote tuber starch presented slightly lower gelatinization temperatures, but slightly higher enthalpy of gelatinization than potato starch, and similar retrogradation rate (due to the enthalpy value of the phase transition) were found in both tuber starches. Chayote tuber starch presented higher Mw and Rz values than potato starch. Chayote tuber could be an alternative for starch isolation with specific physicochemical and molecular characteristics.     

Carbon Clustering in Low-Temperature Bainite

The bainitic ferrite phase formed at temperatures below 573 K (300 °C) in high-carbon high-silicon steels holds an amount of carbon well above that expected from the thermodynamic paraequilibrium with austenite. Diffraction experiments have shown that the ferrite lattice is sufficiently Zener-ordered to possess a tetragonal symmetry, which allows the structures to be supersaturated in carbon. It could be expected that carbon undergoes ordering beyond that indicated by the Zener-ordering temperature as in the early stages of tempering of Fe-based martensites. This study examines the formation of cluster arrangements of carbon within bainitic ferrite and their relationship to the tetragonal distortion.