Optimization of an ultrasound-assisted extraction method to obtain gallic acid-rich extracts from mango seed kernels.

Gallic acid is a widely recognized bioactive compound that falls under the category of secondary polyphenolic metabolites and is fairly found in mango fruit waste, specifically in mango seed kernel (MSK). This study aimed to adopt a green extraction approach to extract this valuable compound via ultrasound-assisted extraction (UAE) without using organic solvents but only water to obtain hazard-free extracts, and the cost of extraction can be minimal. pH (2-8), solvent ratio (20-60 mL/g), temperature (30-60°C) and time (30-60 min) of extraction were the independent variables used for extraction optimization. Single-factor experiments to obtain working ranges for selected extraction variables were carried out. A central composite design using response surface methodology was used to determine the optimum condition to obtain the maximum yield of gallic acid from MSK. The optimized extraction conditions were 3.9 pH, 36.25 mL/g solvent ratio, and 39.4°C of extraction temperature for 21.3 min. As a result, the optimized yield was 5.76 ± 0.41 mg/g, which was comparably equal to and/or better than the other solvent extraction systems. The results showed that gallic acid could efficiently be extracted via UAE under these optimal conditions. It is safer than extraction systems involving hazardous solvents that can be feasibly used for its nutraceutical and therapeutic applications.

Hyperspectral identification of oil adulteration using machine learning techniques.

Food adulteration is a global concern, drawing attention from safety authorities due to its potential health risks. Detecting and categorizing oil adulteration is crucial for consumer safety and food industry integrity. This research explores hyperspectral imaging (HSI) analysis to identify substandard oil adulteration at different stages. Using the non-destructive HSI Specim Fx 10 system, a method for precise and easy imaging-based fraud detection and classification was proposed. The 670 oil samples, including pure (Almond, Mustard, Coconut, Olive) and adulterated (Sunflower, Castor, Liquid Paraffin), were analyzed. The Savitzky-Golay filter preprocessed the images to remove noise and smooth spectral signatures. The oils were identified using various machine learning approaches, including Support Vector Machines, Logistic Regression, Linear Discriminant Analysis, Random Forests, Decision Trees, K-Nearest Neighbors, and Naïve Bayes with Linear Discriminant Analysis excelling in identification. Performance parameters, including precision, recall, F1-score, and overall accuracy, were calculated. The proposed method achieved a validation accuracy of 100%, outperforming numerous state-of-the-art approaches. This study introduces a robust pipeline for effective oil adulteration detection, offering a significant advancement in food safety and quality control.

m6A-Finder: Detecting m6A methylation sites from RNA transcriptomes using physical and statistical properties based features.

N6-methyladenosine (m6A) is one of the abundant post-transcription modification in cellular RNA. It regulates different biological processes, such as, protein synthesis, X-chromosome inactivation, cell stability, cell-reprogramming and miRNA regulation etc. Most recently, various studies claimed that mutations in m6A sites are linked with various diseases, such as, brain-tumor, heart attack, obesity and cancer. The correct identification of m6A sites is essential to overcome these diseases. However, the state-of-the-art predictors face many challenges for precise detection of m6A sites. Even for model organisms, such as Saccharomyces cerevisiae, the detection of m6A sites is difficult due to complex patterns surrounding the m6A sites. These patterns are not widely understood and lead to non-discriminative features for detecting m6A sites. To overcome this problem, we propose a novel predictor called m6A-Finder that creates features based on global and local sequence order. The global sequence order is captured by physical properties based features, while the local sequence order is captured by the statistical features. The fusion of these features results in high dimensional vector which lead to over-fitting, to solve this problem, we use mRMR algorithm to remove redundant features. The proposed technique is evaluated on the most widely used Saccharomyces cerevisiae species dataset. Overall, the m6A-Finder achieved an accuracy of 82.02%, the sensitivity of 82.10%, specificity of 81.94% and a Matthew correlation coefficient value of +0.64.

Severe diarrhoea due to use of P2Y12 inhibitor ticagrelor: a rarely reported adverse event.

Ticagrelor is a part of dual antiplatelet therapy (DAPT) which has proven benefits in patients with acute coronary syndrome especially in those undergoing percutaneous coronary intervention (PCI). However, like most other drugs, it can lead to undesired and adverse effects such as dyspnoea, easy bruising and gastrointestinal bleeding. We present a case of 70-year-old woman who developed diarrhoea following initiation of DAPT comprising of aspirin and ticagrelor following PCI. After excluding more common causes, it was attributed to ticagrelor administration and completely resolved after it was replaced with another oral antiplatelet agent. On follow-up, the patient reported complete resolution of symptoms.

Sequenced application of glutathione as an antioxidant with an organic biostimulant improves physiological and metabolic adaptation to salinity in wheat.

Globally, salinity threatens the agricultural crops productivity by inhibiting plant growth and development through osmotic stress and ionic cytotoxicity. The polygenic nature of salinity offers several pragmatic shotgun approaches to improve salinity tolerance. The present study investigated the potential of glutathione (GSH; 1 mM) as an antioxidant and moringa leaf extract (MLE; 3%) as an organic biostimulant applied in sequence as seed priming and foliar spray on wheat growth, physiology and metabolic adaptation under saline conditions (9.16 dS m-1). Plants without any treatment and water spray (H2O) were considered controls. Salinity induced osmotic stress reduced the plant tissue water status and photosynthetic performance, and perturbed ionic (K+/Na+, Ca2+/Na+, K++Ca2+/Na+) and hormonal (IAA, GA3, zeatin, ABA) homeostasis, consequently affected growth and yield in wheat. Sequenced applied MLE and/or GSH improved osmotic stress tolerance by stabilizing membrane integrity and decreasing electrolyte leakage. These positive results were owed to enhanced endogenous GSH and ascorbate levels. Improved tissue water status was attributed to increased osmotic adjustment, better ionic and hormonal homeostasis contributed to improving photosynthetic efficiency and growth under salinity. Exogenously applied MLE and GSH sequences improved grain yield, which was attributed to the maintenance of green leaf area and delayed senescence associated with an increase in photosynthetic pigments and chlorophyll fluorescence traits. In crux, exogenous applied MLE and/or GSH can be the best physiological strategy to reduce the deleterious effects of salinity and improve physiological and metabolic adaptation in wheat under saline field conditions.

In Vivo Screening and Antidiabetic Potential of Polyphenol Extracts from Guava Pulp, Seeds and Leaves.

The present study investigates the antidiabetic potential of polyphenol extracts purified from guava pulp, seeds and leaves using an in vivo experiment on albino rats. The polyphenols from guava pulp, seeds and leaves were extracted using methanol solvent and the sonication method while being evaluated by total phenolic contents and radical scavenging activity assay. The proximate composition of powders revealed that ash, protein and total sugars were significantly (p < 0.05) higher in leaves and seeds, while vitamin C was highest in pulp. Total phenolic and antioxidant activities were highest in pulp followed by leaves and seeds. The findings of feed intake and body gain revealed that the supplementation of polyphenols, especially from pulp, significantly (p < 0.05) increased the feed intake, which resulted in increased body weight. Moreover, total cholesterol (TC) and low-density lipoprotein (LDL) levels were significantly (p < 0.05) decreased, while the level of high-density lipoprotein (HDL) was increased in groups fed with polyphenols from guava pulp compared to both (+ive and -ive) control groups. Furthermore, blood glucose and triglycerides were significantly (p < 0.05) decreased in supplemented groups compared to the control group of diabetes mice, which resulted in the inhibition of α-amylase and glucose transport. Besides this, packed cell volume (PCV), mean corpuscular volume (MCV), hemoglobin, red blood cells (RBCs), white blood cells (WBCs) and platelet levels were increased significantly (p < 0.05) in pulp's extract followed by leaves and seeds compared to both control groups. Overall, the antidiabetic potential of different extracts was in the following order: pulp > leaves > seeds. The findings suggest the feasibility of adding 200-250 mg/kg.bw of polyphenol extracts of pulp as an alternative to diabetic drugs.

Factors Affecting the Choice of a Career in the Field of Surgery Among Medical Students of Karachi.

Introduction Medical students choose to pursue their careers based on multiple internal and external factors. These factors, in turn, not only affect their personal future but the overall status of the health care system of their country. A recent decline in the interest of medical students towards the surgical career is being observed and, therefore, the factors influencing their choice need to be evaluated. We aimed to identify these factors in medical students of a public sector university of Karachi. Methods A cross-sectional study was conducted at Dow Medical College from April 2018 to May 2018. A pre-tested questionnaire was administered to a sample of 250 students. Besides sociodemographic factors, the choice of career was identified and the factors that influenced it were assessed. Students' opinions were collected using a Likert scale. Data were entered and analyzed using the IBM Statistical Package for the Social Sciences 23.0 (IBM, NY, USA). Frequencies were calculated for individual variables. The chi-square test was used to measure statistical differences between categorical variables and a p-value of <0.05 was considered to be significant. Results In this study, 224 out of 250 questionnaires were returned with complete data, yielding a response rate of 89.6%. We found that 48.2% of students reported a desire to pursue a career in surgery. Students whose fathers were more qualified and belonged to the field of health care were more likely to pick a surgical career (p-value of 0.034 and 0.039, respectively). Students who were willing to pursue a path in surgery more often thought that the social standing of surgeons had its importance (p=0.037). These students also agreed that high salary has a role to play in affecting the choice of career (p=0.023). The most common factors that encouraged students for the choice of a surgical career included the practical implication of skills (57.4%) followed by an academic interest in the field (53.7%), and high income (42.6%). The most common discouraging factors included lifestyle and long working hours (56.9%), followed by less academic interest (31%). Conclusion Our study provides a valuable insight into the factors that influence the choice of medical students for pursuing a career in surgery. We also identified the factors that demotivated them from doing so. In our opinion, better incorporation of surgery into the curriculum, proper attention given to students during their surgical rotation and restructuring of the surgical training program are some of the ways that may improve the interest of students in the field of surgery.