Ferulic acid is a simple phenolic acid found mainly in cereals and grains, used as an antioxidant and food preservative. Recent evidence suggests that ferulic acid possess anti-inflammatory, ...anti-diabetic, anticancer, and cardioprotective properties. Several investigations also have shown that ferulic acid rich food might prevent hypertension. As a potent scavenger of free radicals (ROS, reactive oxygen species), ferulic acid attenuates oxidative stress, which is responsible for lowering elevated blood-pressure through improved endothelial function and increased bioavailability of the nitric oxide in the arterial vasculature. This review article describes the role of ferulic acid in the pathophysiology of vascular dysfunction and hypertension along with highlighted the merit of further scientific and clinical exploration.
Diabetes, also known as chronic illness, is a group of metabolic diseases due to a high level of sugar in the blood over a long period. The risk factor and severity of diabetes can be reduced ...significantly if the precise early prediction is possible. The robust and accurate prediction of diabetes is highly challenging due to the limited number of labeled data and also the presence of outliers (or missing values) in the diabetes datasets. In this literature, we are proposing a robust framework for diabetes prediction where the outlier rejection, filling the missing values, data standardization, feature selection, K-fold cross-validation, and different Machine Learning (ML) classifiers (k-nearest Neighbour, Decision Trees, Random Forest, AdaBoost, Naive Bayes, and XGBoost) and Multilayer Perceptron (MLP) were employed. The weighted ensembling of different ML models is also proposed, in this literature, to improve the prediction of diabetes where the weights are estimated from the corresponding Area Under ROC Curve (AUC) of the ML model. AUC is chosen as the performance metric, which is then maximized during hyperparameter tuning using the grid search technique. All the experiments, in this literature, were conducted under the same experimental conditions using the Pima Indian Diabetes Dataset. From all the extensive experiments, our proposed ensembling classifier is the best performing classifier with the sensitivity, specificity, false omission rate, diagnostic odds ratio, and AUC as 0.789, 0.934, 0.092, 66.234, and 0.950 respectively which outperforms the state-of-the-art results by 2.00 % in AUC. Our proposed framework for the diabetes prediction outperforms the other methods discussed in the article. It can also provide better results on the same dataset which can lead to better performance in diabetes prediction. Our source code for diabetes prediction is made publicly available.
Global vaccination coverage is an urgent need to recover the recent pandemic COVID-19. However, people are concerned about the safety and efficacy of this vaccination program. Thus, it has become ...crucial to examine the knowledge, attitude, and hesitancy towards the vaccine. An online cross-sectional survey was conducted among university students of Bangladesh. Total of 449 university students participated. Most of these students used the internet (34.74%), social media (33.41%), and electronic media (25.61%) as a source of COVID-19 vaccine information. Overall, 58.13% and 64.81% of university students reported positive knowledge and attitude towards the COVID-19 vaccine. 54.34% of these students agreed that the COVID-19 vaccine is safe and effective. 43.88% believed that the vaccine could stop the pandemic. The Spearman’s Rank correlation determined the positive correlation between knowledge and attitude. The negative correlation was determined between positive knowledge and hesitancy, and positive attitude and hesitancy. University students with positive knowledge and attitude showed lower hesitancy. Multiple logistic regression analyses determined the university type and degree major as the predictors of knowledge, whereas only degree major was the predictor of attitudes. 26.06% of the study population showed their hesitancy towards the vaccine. University type and degree major were also determined as predictors of this hesitancy. They rated fear of side effects (87.18%) and lack of information (70.94%) as the most reasons for the hesitancy. The findings from this study can aid the ongoing and future COVID-19 vaccination plan for university students. The national and international authorities can have substantial information for a successful inoculation campaign.
Immune response in COVID-19: A review Chowdhury, Mohammad Asaduzzaman; Hossain, Nayem; Kashem, Mohammod Abul ...
Journal of infection and public health,
11/2020, Volume:
13, Issue:
11
Journal Article
Peer reviewed
Open access
The immune system protects against viruses and diseases and produces antibodies to kill pathogens. This review presents a brief overview of the immune system regarding its protection of the human ...body from COVID-19; illustrates the process of the immune system, how it works, and its mechanism to fight virus; and presents information on the most recent COVID-19 treatments and experimental data. Various types of potential challenges for the immunes system are also discussed. At the end of the article, foods to consume and avoid are suggested, and physical exercise is encouraged. This article can be used worldwide as a state of the art in this critical moment for promising alternative solutions related to surviving the coronavirus.
Trajectory-based writing system refers to writing a linguistic character or word in free space by moving a finger, marker, or handheld device. It is widely applicable where traditional pen-up and ...pen-down writing systems are troublesome. Due to the simple writing style, it has a great advantage over the gesture-based system. However, it is a challenging task because of the non-uniform characters and different writing styles. In this research, we developed an air-writing recognition system using three-dimensional (3D) trajectories collected by a depth camera that tracks the fingertip. For better feature selection, the nearest neighbor and root point translation was used to normalize the trajectory. We employed the long short-term memory (LSTM) and a convolutional neural network (CNN) as a recognizer. The model was tested and verified by the self-collected dataset. To evaluate the robustness of our model, we also employed the 6D motion gesture (6DMG) alphanumeric character dataset and achieved 99.32% accuracy which is the highest to date. Hence, it verifies that the proposed model is invariant for digits and characters. Moreover, we publish a dataset containing 21,000 digits; which solves the lack of dataset in the current research.
Turmeric, a globally cultivated spice, holds significance in medicine, and cosmetics, and is also a very popular ingredient in South Asian cuisine. A study involving 53 turmeric genotypes evaluated ...for rhizome yield and related traits at Spices Research Center, Bogura, Bangladesh over three years (2019-22). A randomized complete block design was followed with two replications. ANOVA revealed significant trait variations among genotypes. Genotype T0015 emerged as the highest yielder at 28.04 t/ha. High heritability (0.58-0.99) and genetic advance characterized plant height (PH), mother rhizome weight (WMR), primary and secondary finger weights (WPF and WSF), and yield per plant (YPP) across seasons. Genetic gain (GG) was prominent in these traits. Genotypic and phenotypic coefficient variations (GCV and PCV) (6.24-89.46 and 8.18-90.88, respectively) across three years highlighted mother rhizome weight's importance followed by numbers of primary finger (NPF), and WPF. Positive and significant correlations, especially with PH, WMR, WPF, and YPP, emphasized their relevance to fresh yield (FY). Multiple linear regression identified PH, number of mother rhizome (NMR) and WMR as key contributors, explaining 37-79% of FY variability. Cluster analysis grouped genotypes into five clusters with maximum distance observed between clusters II and III. The geometric adaptability index (GAI) assessed adaptability and superiority, revealing nine genotypes outperforming the best existing cultivar. Genotype T0117 as the top performer based on GAI, followed by T0103 and T0094. Mean rank analysis favoured T0121 as the best performer, succeeded by T0117, T0082 and T0106. The top ten genotypes (T0015, T0061, T0082, T0085, T0094, T0103, T0106, T0117, T0121 and T0129) were identified as superior based on yield and overall ranking, warranting further evaluation. These findings may induce a window for improving turmeric research and ultimately play a role in enhancing its cultivation and productivity.
Obesity, insulin resistance, hypertension and fatty liver, together termed metabolic syndrome, are key risk factors for cardiovascular disease. Chronic feeding of a diet high in saturated fats and ...simple sugars, such as fructose and glucose, induces these changes in rats. Naturally occurring compounds could be a cost-effective intervention to reverse these changes. Flavonoids are ubiquitous secondary plant metabolites; naringin gives the bitter taste to grapefruit. This study has evaluated the effect of naringin on diet-induced obesity and cardiovascular dysfunction in high carbohydrate, high fat-fed rats. These rats developed increased body weight, glucose intolerance, increased plasma lipid concentrations, hypertension, left ventricular hypertrophy and fibrosis, liver inflammation and steatosis with compromised mitochondrial respiratory chain activity. Dietary supplementation with naringin (approximately 100 mg/kg/day) improved glucose intolerance and liver mitochondrial dysfunction, lowered plasma lipid concentrations and improved the structure and function of the heart and liver without decreasing total body weight. Naringin normalised systolic blood pressure and improved vascular dysfunction and ventricular diastolic dysfunction in high carbohydrate, high fat-fed rats. These beneficial effects of naringin may be mediated by reduced inflammatory cell infiltration, reduced oxidative stress, lowered plasma lipid concentrations and improved liver mitochondrial function in rats.
To measure the efficacy of school-based nutrition education on dietary diversity of the adolescent girls in Bangladesh.
A matched, pair-cluster randomized controlled trial was conducted from July ...2019 to September 2020. Randomization was done to select intervention and control schools. There were 300 participants (150 in the intervention and 150 in the control arm) at baseline. We randomly selected our study participants (adolescent girls) from grades six, seven, and eight of each school. Our intervention components included parents' meetings, eight nutrition education sessions, and the distribution of information, education, and communication materials. An hour-long nutrition education session was provided using audio-visual techniques in a class of intervention school once a week by trained staffs of icddr,b for two months. Data on dietary diversity, anthropometry, socio-economic and morbidity status, a complete menstrual history, and haemoglobin status of adolescent girls were collected at recruitment and after five months of intervention. We calculated the mean dietary diversity score of adolescent girls at baseline and at the endline. As the dietary diversity score was incomparable between the control and intervention arm at baseline, we performed the difference-in-difference analysis to assess the effect of the intervention.
Mean age of the adolescent girls was 12.31 years and 12.49 years in the control and intervention arms respectively. Percentages of consumption of organ meat, vitamin A-rich fruits and vegetables, legumes, nuts, and seeds were higher in the intervention arm than in the control arm at the end-line. The mean dietary diversity score remained unchanged in the control arm at 5.55 (95% CI: 5.34-5.76) at baseline and 5.32 (95% CI: 5.11-5.54) at the endline. After the intervention, mean dietary diversity increased from 4.89 (95% CI: 4.67-5.10) at baseline to this mean was 5.66 (95% CI: 5.43-5.88) at the endline. Result from the difference-in-difference analysis revealed that the mean dietary diversity was likely to increase by 1 unit due to intervention.
The shorter duration of the intervention in our study could not show whether it could change the behavior of adolescent girls in increasing dietary diversity through school-based nutrition education, but it showed a pathway for increasing dietary diversity at school. We recommend including more clusters and other food environment elements in retesting to increase precision and acceptability.
This study was registered with ClinicalTrials.gov, trial registration no: NCT04116593. https://clinicaltrials.gov/ct2/show/NCT04116593.
The antidiabetic drug canagliflozin is reported to possess several cardioprotective effects. However, no studies have investigated protective effects of canagliflozin in isoprenaline (ISO)-induced ...cardiac oxidative damage-a model mimicking sympathetic nervous system (SNS) overstimulation-evoked cardiac injuries in humans. Therefore, we investigated protective effects of canagliflozin in ISO-induced cardiac oxidative stress, and their underlying molecular mechanisms in Long-Evans rat heart and in HL-1 cardiomyocyte cell line. Our data showed that ISO administration inflicts pro-oxidative changes in heart by stimulating production of reactive oxygen species (ROS) and reactive nitrogen species (RNS). In contrast, canagliflozin treatment in ISO rats not only preserves endogenous antioxidants but also reduces cardiac oxidative stress markers, fibrosis and apoptosis. Our Western blotting and messenger RNA expression data demonstrated that canagliflozin augments antioxidant and anti-inflammatory signaling involving AMP-activated protein kinase (AMPK), Akt, endothelial nitric oxide synthase (eNOS), nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1). In addition, canagliflozin treatment attenuates pro-oxidative, pro-inflammatory and pro-apoptotic signaling mediated by inducible nitric oxide synthase (iNOS), transforming growth factor beta (TGF-β), NADPH oxidase isoform 4 (Nox4), caspase-3 and Bax. Consistently, canagliflozin treatment improves heart function marker in ISO-treated rats. In summary, we demonstrated that canagliflozin produces cardioprotective actions by promoting multiple antioxidant and anti-inflammatory signaling.
Although automated Skin Lesion Classification (SLC) is a crucial integral step in computer-aided diagnosis, it remains challenging due to variability in textures, colors, indistinguishable ...boundaries, and shapes.
This article proposes an automated dermoscopic SLC framework named Dermoscopic Expert (DermoExpert). It combines the pre-processing and hybrid Convolutional Neural Network (hybrid-CNN). The proposed hybrid-CNN has three distinct feature extractor modules, which are fused to achieve better-depth feature maps of the lesion. Those single and fused feature maps are classified using different fully connected layers, then ensembled to predict a lesion class. In the proposed pre-processing, we apply lesion segmentation, augmentation (geometry- and intensity-based), and class rebalancing (penalizing the majority class’s loss and merging additional images to the minority classes). Moreover, we leverage transfer learning from the pre-trained models. Finally, we deploy the weights of our DermoExpert to a possible web application.
We evaluate our DermoExpert on the ISIC-2016, ISIC-2017, and ISIC-2018 datasets, where the DermoExpert has achieved the area under the receiver operating characteristic curve (AUC) of 0.96, 0.95, and 0.97, respectively. The experimental results improve the state-of-the-art by the margins of 10.0% and 2.0%, respectively, for the ISIC-2016 and ISIC-2017 datasets in terms of AUC. The DermoExpert also outperforms by 3.0% for the ISIC-2018 dataset concerning a balanced accuracy.
Since DermoExpert provides better classification outcomes on three different datasets, leading to a better recognition tool to assist dermatologists. Our source code and segmented masks for the ISIC-2018 dataset will be available as a public benchmark for future improvements.
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•Proposing a hybrid-CNN classifier for multiple skin diseases recognition.•Precisely segmenting skin lesion although the presence of hair fibers and other artifacts.•Class-rebalancing, transfer learning, and augmentation for a generic model, as tiny datasets are being used.•State of the art results on ISIC-16 (2-class), ISIC-17 (3-class), and ISIC-18 (7-class).•Development of a possible web application, deploying our trained model’s weights.
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