Type 2 diabetes mellitus in obesity promotes prolongation of cardiomyocyte contractile function, impaired Ca2+ handling and protein carbonylation damage.

AIMS: To investigate whether the obesity associated to T2DM presented cardiomyocyte myocardial contractility dysfunction due to damage in Ca2+ handling, concomitantly with increased biomarkers of oxidative stress. METHODS: Male Wistar rats were randomized into two groups: control (C): fed with standard diet; and obese (Ob) that fed a saturated high-fat. After the characterization of obesity (12 weeks), the Ob animals were submitted to T2DM induction with a single dose of intraperitoneal (i.p.) injection of streptozotocin (30 mg/kg). Thus, remained Ob rats that were characterized as to the presence (T2DMOb; n = 8) and/or absence (Ob; n = 10) of T2DM. Cardiac remodeling was measured by post-mortem morphological, isolated cardiomyocyte contractile function, as well as by intracellular Ca2+-handling analysis. RESULTS: T2DMOb presented a significant reduction of all fat pads, total body fat and adiposity index. T2DMOb group presented a significant increase in protein carbonylation and superoxide dismutase (SOD) activity, respectively. T2DMOb promoted elevations in fractional shortening (15.6 %) and time to 50 % shortening (5.8 %), respectively. Time to 50 % Ca2+ decay was prolonged in T2DMOb, suggesting a possible impairment in Ca2+recapture and/or removal. CONCLUSION: Type 2 diabetes mellitus in obesity promotes prolongation of cardiomyocyte contractile function with protein carbonylation damage and impaired Ca2+ handling.

Computer-Aided Ankle Ligament Injury Diagnosis from Magnetic Resonance Images Using Machine Learning Techniques.

Ankle injuries caused by the Anterior Talofibular Ligament (ATFL) are the most common type of injury. Thus, finding new ways to analyze these injuries through novel technologies is critical for assisting medical diagnosis and, as a result, reducing the subjectivity of this process. As a result, the purpose of this study is to compare the ability of specialists to diagnose lateral tibial tuberosity advancement (LTTA) injury using computer vision analysis on magnetic resonance imaging (MRI). The experiments were carried out on a database obtained from the Vue PACS-Carestream software, which contained 132 images of ATFL and normal (healthy) ankles. Because there were only a few images, image augmentation techniques was used to increase the number of images in the database. Following that, various feature extraction algorithms (GLCM, LBP, and HU invariant moments) and classifiers such as Multi-Layer Perceptron (MLP), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Random Forest (RF) were used. Based on the results from this analysis, for cases that lack clear morphologies, the method delivers a hit rate of 85.03% with an increase of 22% over the human expert-based analysis.

Mammogram Image Enhancement Techniques for Online Breast Cancer Detection and Diagnosis.

Breast cancer is the type of cancer with the highest incidence and global mortality of female cancers. Thus, the adaptation of modern technologies that assist in medical diagnosis in order to accelerate, automate and reduce the subjectivity of this process are of paramount importance for an efficient treatment. Therefore, this work aims to propose a robust platform to compare and evaluate the proposed strategies for improving breast ultrasound images and compare them with state-of-the-art techniques by classifying them as benign, malignant and normal. Investigations were performed on a dataset containing a total of 780 images of tumor-affected persons, divided into benign, malignant and normal. A data augmentation technique was used to scale up the corpus of images available in the chosen dataset. For this, novel image enhancement techniques were used and the Multilayer Perceptrons, k-Nearest Neighbor and Support Vector Machines algorithms were used for classification. From the promising outcomes of the conducted experiments, it was observed that the bilateral algorithm together with the SVM classifier achieved the best result for the classification of breast cancer, with an overall accuracy of 96.69% and an accuracy for the detection of malignant nodules of 95.11%. Therefore, it was found that the application of image enhancement methods can help in the detection of breast cancer at a much earlier stage with better accuracy in detection.

Edge2Analysis: A Novel AIoT Platform for Atrial Fibrillation Recognition and Detection.

Atrial fibrillation (AF) is a serious medical condition of the heart potentially leading to stroke, which can be diagnosed by analyzing electrocardiograms (ECG). Technologies of Artificial Intelligence of Things (AIoT) enable smart abnormality detection by analyzing streaming healthcare data from the sensor end of users. Analyzing streaming data in the cloud leads to challenges of response latency and privacy issues, and local inference by a model deployed on the user end brings difficulties in model update and customization. Therefore, we propose an AIoT Platform with AF recognition neural networks on the sensor edge with model retraining ability on a resource-constrained embedded system. To this aim, we proposed to combine simple but effective neural networks and an ECG feature selection strategy to reduce computing complexity while maintaining recognition performance. Based on the platform, we evaluated and discussed the performance, response time, and requirements for model retraining in the scenario of AF detection from ECG recordings. The proposed lightweight solution was validated with two public datasets and an ECG data stream simulation on an ATmega2560 processor, proving the feasibility of analysis and training on edge.

Computer-assisted Parkinson's disease diagnosis using fuzzy optimum- path forest and Restricted Boltzmann Machines.

Parkinson's disease (PD) is a progressive neurodegenerative illness associated with motor skill disorders, affecting thousands of people, mainly elderly, worldwide. Since its symptoms are not clear and commonly confused with other diseases, providing early diagnosis is a challenging task for traditional methods. In this context, computer-aided assistance is an alternative method for a fast and automatic diagnosis, accelerating the treatment and alleviating an excessive effort from professionals. Moreover, the most recent studies proposing a solution to this problem lack in computational efficiency, prediction power, reliability among other factors. Therefore, this work proposes a Fuzzy Optimum Path Forest for automated PD identification, which is based on fuzzy logic and graph-based framework theory. Experiments consider a dataset composed of features extracted from hand-drawn images using Restricted Boltzmann Machines, and results are compared with baseline models such as Support Vector Machines, KNN, and the standard OPF classifier. Results show that the proposed model outperforms the baselines in most cases, suggesting the Fuzzy OPF as a viable alternative to deal with PD detection problems.

Planning forest restoration within private land holdings with conservation co-benefits at the landscape scale.

Forest loss is mainly due to the conversion of forest to agriculture, mostly in private lands. Forest restoration is a global priority, yet restoration targets are ambitious and budget-limited. Therefore, assessing the outcome of alternative decisions on land-use within private lands is paramount to perform cost-effective restoration. We present a novel framework that incorporates spatial planning for forest restoration within private lands with conservation co-benefits at the landscape scale. As a case study, we used three real landscapes of 10.000 ha with differing amounts of forest cover in the Atlantic Forest region of Brazil, and three hypothetical animal species with different dispersal abilities. We estimated the total amount of forest that landholders must restore to comply with the Native Vegetation Protection Law, which requires landholders to reforest 20% of their land within a 20-year time frame. We compared the cost-effectiveness of five restoration strategies based on the improvement in habitat availability and restoration costs. The most cost-effective strategy depends on a landscape's initial amount of forest cover and the species of concern. We revealed that spatial planning for restoration in private lands increased habitat availability up to 12 times more than random restoration, which was always the least cost-effective strategy. Cost-effective large-scale restoration in Brazil depends on public policies that assist landholders to comply with the law and on prioritizing areas for restoration within private lands. We show that by adding habitat availability as target in spatial prioritization, benefits for biodiversity can be hastened at low additional cost, even in real world scenarios with severe spatial constraints. Despite constraints, spatially planned restoration for law compliance in Brazil increased landscape permeability by creating corridors and stepping stones. Our framework should be used to plan restoration in Brazilian private lands and can be customized for other regions worldwide.

Synthesis and biological evaluation of benzothiazin-4-ones: a possible new class of acetylcholinesterase inhibitors.

A series of nineteen benzothiazin-4-ones from N-(3-aminopropyl) piperidine, 4-(2-aminoethyl)morpholine or 1-(2-aminoethyl)piperidine, aliphatic or aromatic aldehyde and thiosalicylic acid, were synthesized in good yields by multicomponent one-pot reactions. The solvent was toluene and this efficient procedure afforded the desired heterocycles in 5 h. Identification and characterization were achieved by NMR and GC-MS techniques. In vitro AChE activities of all compounds were evaluated in cerebral cortex and hippocampus of rats and in general, the results in cortex were more promising than hippocampus. The benzothiazinone 5Bd showed the best AChE inhibition activity IC50 8.48 µM (cortex) and IC50 39.80 µM (hippocampus). The cytotoxicity of seven compounds in MCR-5 human fibroblast cell by SRB test in 24 h were evaluated and 5Bd suggest preliminary safety, showing no cytotoxicity at 100 µM. Finally, these important findings could be a starting point for the development of new AChE inhibitors agents and will provide the basis for new studies.

Early hematopoietic stem cell transplantation in a patient with severe mucopolysaccharidosis II: A 7 years follow-up.

Mucopolysaccharidosis type II (MPS II - Hunter syndrome) is an X-linked lysosomal storage disorder caused by a deficiency in the enzyme iduronate-2 sulfatase (I2S), leading to the accumulation of the glycosaminoglycans, affecting multiple organs and systems. Enzyme replacement therapy does not cross the blood brain barrier, limiting results in neurological forms of the disease. Another option of treatment for severe MPS, hematopoietic stem cell transplantation (HSCT) has become the treatment of choice for the severe form of MPS type I, since it can preserve neurocognition when performed early in the course of the disease. To date, only few studies have examined the long-term outcomes of HSCT in patients with MPS II. We describe the seven-year follow-up of a prenatally diagnosed MPS II boy with positive family history of severe MPS form, submitted to HSCT with umbilical cord blood cells at 70 days of age. Engraftment after 30 days revealed mixed chimerism with 79% donor cells; after 7 years engraftment remains at 80%. I2S activity 30 days post-transplant was low in plasma and normal in leukocytes and the same pattern is observed to date. At age 7 years growth charts are normal and he is very healthy, although mild signs of dysostosis multiplex are present, as well as hearing loss. The neuropsychological evaluation (Wechsler Intelligence Scale for Children - Fourth Edition - WISC-IV), disclosed an IQ of 47. Despite this low measured IQ, the patient continues to show improvements in cognitive, language and motor skills, being quite functional. We believe that HSCT is a therapeutic option for MPS II patients with the severe phenotype, as it could preserve neurocognition or even halt neurodegeneration, provided strict selection criteria are followed.

Synthetic 2-aryl-3-((piperidin-1-yl)ethyl)thiazolidin-4-ones exhibit selective in vitro antitumoral activity and inhibit cancer cell growth in a preclinical model of glioblastoma multiforme.

Glioblastoma multiforme (GBM) is the worst form of primary brain tumor, which has a high rate of infiltration and resistance to radiation and chemotherapy, resulting in poor prognosis for patients. Recent studies show that thiazolidinones have a wide range of pharmacological properties including antimicrobial, anti-inflammatory, anti-oxidant and anti-tumor. Here, we investigate the effect antiglioma in vitro of a panel of sixteen synthetic 2-aryl-3-((piperidin-1-yl)ethyl)thiazolidin-4-ones where 13 of these decreased the viability of glioma cells 30-65% (100 µM) compared with controls. The most promising compounds such as 4d, 4l, 4m and 4p promoted glioma reduction of viability greater than 50%, were further tested at lower concentrations (12.5, 25, 50 and 100 µM). Also, the data showed that the compounds 4d, 4l, 4m and 4p induced cell death primarily through necrosis and late apoptosis mechanisms. Interestingly, none of these 2-aryl-3-((piperidin-1-yl)ethyl)thiazolidin-4-ones were cytotoxic for primary astrocytes, which were used as a non-transformed cell model, indicating selectivity. Our results also show that the treatment with sub-therapeutic doses of 2-aryl-3-((piperidin-1-yl)ethyl)thiazolidin-4-ones (4d, 4l and 4p) reduced in vivo glioma growth as well as malignant characteristics of implanted tumors such as intratumoral hemorrhage and peripheral pseudopalisading. Importantly, 2-aryl-3-((piperidin-1-yl)ethyl)thiazolidin-4-ones treatment did not induce mortality or peripheral damage to animals. Finally, 2-aryl-3-((piperidin-1-yl)ethyl)thiazolidin-4-ones also changed the nitric oxide metabolism which may be associated with reduced growth and malignity characteristics of gliomas. These data indicates for the first time the therapeutic potential of synthetic 2-aryl-3-((piperidin-1-yl)ethyl)thiazolidin-4-ones to GBM treatment.

Poor retention in early care increases risk of mortality in a Brazilian HIV-infected clinical cohort.

Retention in early HIV care has been associated with decreased mortality and improved viral suppression, however the consequences of poor retention in early care in Brazil remain unknown. We assessed the effect of poor retention on mortality in a Brazilian HIV-infected clinical cohort. The analysis included ART-naïve, HIV-infected adults linked to care at the Instituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz between 2000 and 2010, who did not become pregnant nor participate in a clinical trial during the first two years in care (early care). Poor retention in early care was defined as less than 3 out of 4 six-month intervals with a CD4 or HIV-1 RNA laboratory result during early care. Cox proportional hazards models were used to identify factors associated with mortality, and Kaplan-Meier plots were used to describe the survival probability for participants with poor retention versus good retention. Among 1054 participants with a median (interquartile range) follow-up time of 4.2 years (2.6, 6.3), 20% had poor retention in early care and 8% died. Poor retention in early care [adjusted hazard ratio (aHR) 3.09; 95% CI 1.65-5.79], AIDS defining illness (aHR 1.95; 95% CI 1.20-3.18) and lower education (aHR 2.33; 95% CI 1.45-3.75) were associated with increased mortality risk. Our findings highlight the importance of adopting strategies to improve retention in early HIV care.

Retention in Early Care at an HIV Outpatient Clinic in Rio de Janeiro, Brazil, 2000-2013.

Retention in early HIV care has been associated with virologic suppression and improved survival, but remains understudied in Brazil. We estimated retention in early HIV care for the period 2000-2013, and identified socio-demographic and clinical factors associated with good retention in an urban cohort from Rio de Janeiro, Brazil. Antiretroviral therapy-naïve, HIV-infected persons ≥18 years old linked to care between 2000 and 2011 were included. Retention in the first 2 years post-linkage (i.e. early care) was defined by the proportion of 6-month intervals with ≥1 HIV laboratory result. "Good" retention was defined as ≥1 HIV laboratory result recorded in at least three intervals. Overall, 80 % of participants met criteria for good retention and retention significantly improved over the study period. Older age, higher education level and early antiretroviral therapy initiation were associated with good retention. Efforts to improve retention in early care in this population should target younger and less-educated HIV-infected persons.