BackgroundAlzheimer’s disease (AD), one of the major causes of dementia, is an overwhelming neurodegenerative disease that particularly affects the brain, leading to memory loss and impairment of language and judgment capacity. The aim of the present study was to investigate the antioxidant and anticholinesterase properties of the leaves of Elatostema papillosum (EPL) and correlate with their phytochemical profiles, which are relevant to the treatment of AD.MethodsThe dried coarse powder of EPL was extracted with 80% methanol (EPL-M80) by cold extraction method. The resultant EPL-M80 was assessed for acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitory activity by the Ellman method. The antioxidant activity was determined by DPPH (1, 1-diphenyl-2-picrylhydrazyl) and hydroxyl radical scavenging assays. Quantitative phytochemical (phenolic and flavonoid contents) analysis of endogenous substances in EPL-M80 was performed by standard spectrophotometric methods.ResultsEPL-M80 significantly (p < 0.05) inhibited AChE and BChE activity with IC50 of 165.40 ± 4.01 and 213.81 ± 3.57 μg/mL, respectively in a dose-dependent manner. Additionally, EPL-M80 exhibited strong radical scavenging activity against DPPH (IC50 = 32.35 ± 0.68 μg/mL) and hydroxyl radical (IC50 = 19.67 ± 1.42 μg/mL) when compared to that of standards. EPL-M80 was found to be rich in phenolic (23.74 mg gallic acid equivalent/g of dry extract) and flavonoid (31.18 mg quercetin equivalent/g of dry extract) content. Furthermore, a positive correlation (p < 0.001) was observed between the total phenolics and antioxidant as well as the anticholinesterase potential.ConclusionsThe marked inhibition of AChE and BChE, and potent antioxidant activity of the leaves of Elatostema papillosum highlight its potential to provide an effective treatment for AD.

BackgroundT-cell infiltrates may persist in muscle tissue of polymyositis (PM) and dermatomyositis (DM) patients despite aggressive immunosuppressive treatment. Here, we investigated to what extent persistent T cells in affected muscle were FOXP3+, a marker for regulatory T cells (Tregs), or CD244+, a marker for CD28null T cells, and whether their presence correlated to clinical outcome. The sensitivity of CD28null T cells towards glucocorticoid and Treg-mediated immunosuppression was also investigated.MethodsMuscle biopsies from 16 newly diagnosed or untreated patients with PM/DM were investigated by immunohistochemistry for expression of CD3, FOXP3 and CD244 before and after treatment with glucocorticoids and immunosuppressive agents. For clinical evaluation, serum levels of creatine kinase, muscle performance (FI and MMT8), disease activity (MITAX) and disability (HAQ) were measured. In vitro suppressive effects of glucocorticoids and Tregs on T-cell activation were measured by CD69 upregulation.ResultsBefore treatment, CD244+ cells were present at higher proportions compared to FOXP3+ cells in the inflamed muscle. Following treatment, FOXP3+ cell numbers decreased while CD244+ cells persisted. Patients with impaired muscle function (<75 % FI) post-treatment had higher levels of CD244+ cells in the follow-up biopsy compared to those with FI >75 %. MITAX and HAQ correlated with the number of CD244+ cells post-treatment. CD4+CD28null T cells displayed lower sensitivity towards both glucocorticoid and Treg-mediated immunosuppression in vitro compared to their CD28+ counterparts.ConclusionsPoor outcome in patients with myositis following immunosuppressive therapy was linked to persistence of CD244+ (CD28null) T cells in muscle tissue, suggesting their resistance against immunosuppression. A relative loss of regulatory T cells could also contribute to poor clinical outcome given their recently ascribed role in muscle tissue regeneration.

Detecting emotion from facial expression has become an urgent need because of its immense applications in artificial intelligence such as human-computer collaboration, data-driven animation, human-robot communication etc. Since it is a demanding and interesting problem in computer vision, several works had been conducted regarding this topic. The objective of this research is to develop a facial expression recognition system based on convolutional neural network with data augmentation. This approach enables to classify seven basic emotions consist of angry, disgust, fear, happy, neutral, sad and surprise from image data. Convolutional neural network with data augmentation leads to higher validation accuracy than the other existing models (which is 96.24%) as well as helps to overcome their limitations.

Objective. Inflammatory T cell infiltrates in the skeletal muscle tissue of patients with polymyositis are dominated by CD28-negative effector (CD28 null ) T cells of both the CD4 and CD8 lineage. These cells are potentially cytotoxic, and the aim of the present study was to develop a fully autologous cell culture system in which to investigate the functional contribution of such CD28 null T cells to myotoxicity.Methods. In vitro cocultures of autologous skeletal muscle cells and T cell subsets obtained from 5 polymyositis patients were performed. Myotoxicity of T cells was quantified by calcein release and flow cytometric analyses. T cell degranulation was blocked with concanamycin A. Specific blocking of perforin, cytokines, and HLA was performed using antibodies.Results. Both CD41CD28 null and CD81CD28 null T cells induced more muscle cell death than did their CD281 counterparts. Differentiated muscle cells (myotubes) were more sensitive to T cell-mediated cell death than were their precursors (myoblasts). Both CD81 and CD41 CD28 null T cells displayed perforin polarization toward muscle cells and secreted higher levels of granzyme B and interferon-g (IFNg) in coculture than did CD281 T cells. The myotoxic effects of CD28 null T cells were reduced upon the blocking of perforin, cytokines, and HLA. Addition of IFNg or tumor necrosis factor did not induce skeletal muscle cell death in the absence of T cells; however, it did up-regulate HLA expression on muscle cells.Conclusion. Myotoxicity of CD41 and CD81 CD28 null T cells is mediated by directed perforindependent killing and can be further influenced by IFNg-induced HLA expression on muscle cells. The data suggest that CD28 null T cells are key effector cells that contribute to the muscle cell damage in polymyositis.

This paper proposes a process of Handwritten Character Recognition to recognize and convert images of individual Bangla handwritten characters into electronically editable format, which will create opportunities for further research and can also have various practical applications. The dataset used in this experiment is the BanglaLekha-Isolated dataset [1]. Using Convolutional Neural Network, this model achieves 91.81% accuracy on the alphabets (50 character classes) on the base dataset, and after expanding the number of images to 200,000 using data augmentation, the accuracy achieved on the test set is 95.25%. The model was hosted on a web server for the ease of testing and interaction with the model. Furthermore, a comparison with other machine learning approaches is presented.

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Background Dietary supplements (DS) are products that improve the overall health and well-being of individuals and reduce the risk of disease. Evidence indicates a rising prevalence of the use of these products worldwide especially among the age group 18–23 years. Aim The study investigates the tendencies and attitudes of Bangladeshi undergraduate female students towards dietary supplements (DS). Methods A three-month (March 2018-May 2018) cross-sectional face-to-face survey was conducted in undergraduate female students in Chittagong, Bangladesh using a pre-validated dietary supplement questionnaire. The study was carried among the four private and three public university students of different disciplines in Chittagong to record their prevalent opinions and attitudes toward using DS. The results were documented and analyzed by SPSS version 22.0. Results Ninety two percent (N = 925, 92.0%) of the respondents answered the survey questions. The prevalence of DS use was high in undergraduate female students. The respondents cited general health and well-being (n = 102, 11.0%) and physician recommendation (n = 101, 10.9%) as a reason for DS use. Majority of the students (n = 817, 88.3%) used DS cost monthly between USD 0.12 and USD 5.90. Most of the students (n = 749, 81.0%) agreed on the beneficial effect of DS and a significant portion (n = 493, 53.3%) recommended for a regular use of DS. Highly prevalent use of dietary supplements appeared in Chittagonian undergraduate female students. They were tremendously positive in using DS. The results demonstrate an increasing trend of using DS by the undergraduate females for both nutritional improvement and amelioration from diseases. Conclusion Dietary supplements prevalence was so much higher in students of private universities as compared to students of public universities. Likewise, maximal prevalence is indicated in pharmacy department compared to other departments. Students preferred brand products, had positive opinions and attitudes towards dietary supplements.

A novel coronavirus (COVID-19), which has become a great concern for the world, was identified first in Wuhan city in China. The rapid spread throughout the world was accompanied by an alarming number of infected patients and increasing number of deaths gradually. If the number of infected cases can be predicted in advance, it would have a large contribution to controlling this pandemic in any area. Therefore, this study introduces an integrated model for predicting the number of confirmed cases from the perspective of Bangladesh. Moreover, the number of quarantined patients and the change in basic reproduction rate (the R0-value) can also be evaluated using this model. This integrated model combines the SEIR (Susceptible, Exposed, Infected, Removed) epidemiological model and neural networks. The model was trained using available data from 250 days. The accuracy of the prediction of confirmed cases is almost between 90% and 99%. The performance of this integrated model was evaluated by showing the difference in accuracy between the integrated model and the general SEIR model. The result shows that the integrated model is more accurate than the general SEIR model while predicting the number of confirmed cases in Bangladesh.