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.

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.

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.