Metabolic alterations play a crucial role in glioma development and progression and can be detected even before the appearance of the fatal phenotype. We have compared the circulating metabolic fingerprints of glioma patients versus healthy controls, for the first time, in a quest to identify a panel of small, dysregulated metabolites with potential to serve as a predictive and/or diagnostic marker in the clinical settings. High-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMAS-NMR) was used for untargeted metabolomics and data acquisition followed by a machine learning (ML) approach for the analyses of large metabolic datasets. Cross-validation of ML predicted NMR spectral features was done by statistical methods (Wilcoxon-test) using JMP-pro16 software. Alanine was identified as the most critical metabolite with potential to detect glioma with precision of 1.0, recall of 0.96, and F1 measure of 0.98. The top 10 metabolites identified for glioma detection included alanine, glutamine, valine, methionine, N-acetylaspartate (NAA), γ-aminobutyric acid (GABA), serine, α-glucose, lactate, and arginine. We achieved 100% accuracy for the detection of glioma using ML algorithms, extra tree classifier, and random forest, and 98% accuracy with logistic regression. Classification of glioma in low and high grades was done with 86% accuracy using logistic regression model, and with 83% and 79% accuracy using extra tree classifier and random forest, respectively. The predictive accuracy of our ML model is superior to any of the previously reported algorithms, used in tissue- or liquid biopsy-based metabolic studies. The identified top metabolites can be targeted to develop early diagnostic methods as well as to plan personalized treatment strategies.

Objective: To assess the discrepancy among and within low- and middle-income countries (LMICs) regarding PPE availability, use, and satisfaction. Methods: The study population consisted of healthcare workers from LMICs who partook in the questionnaire survey from March 1, 2020, until April 15, 2020. Results: In the bivariate analysis, gender (P = 0.05), HCWs (P < 0.01), and level of care (P < 0.01) were associated with the public or private sector (P < 0.05). Using multivariate analysis, PPE factors were associated with the health sector (p < 0.05). The multivariate logistic regression model determined a Pearson's χ2 value of 706.736 (df = 726, P = −0.689) and a c-statistic of 0.592, indicating a good model. Conclusion: In LMICs, huge discrepancies are present in PPE provision to HCWs, especially among the public healthcare sectors. Efforts at national and international levels ought to be addressed to protect frontline HCWs at higher risk of contracting COVID-19.

Background: Predatory publishing is an exploitative fraudulent open-access publishing model. Most predatory journals do not follow policies that are set forth by organizations including the World Association of Medical Editors (WAME), the Committee on Publication Ethics (COPE), the Council of Science Editors (CSE), and the International Committee of Medical Journal Editors (ICMJE). Jeffrey Beall, an associate professor at the University of Colorado Denver and a librarian at Auraria Library, coined the term ‘predatory journals’ to describe pseudo-journals. Our literature review has highlighted that predatory journal authorship is not limited to early-career researchers only. Majority of authors are unfamiliar with practices in pseudo journals despite publishing manuscripts. Methodology: For the purpose of this review, a systematic literature search was carried in October 2019 of the following databases: (1) Web of Science (all databases), (2) ERIC, and (3) LISTA. All stages of the review process included access to the search results and full articles for review and consequent analysis. Articles were added after screening fulltext articles by meeting the inclusion criteria and meeting none of the exclusion criteria. As there were a high number of articles reporting findings on predatory journals, they were further screened re-evaluating them for any deviations from the theme of this study. Relevant material published within the last five years was used. Results: After a thorough review, 63,133 were located using the Boolean logic. After reviewing 63 abstracts and titles for relevance, 9 articles were included in the literature review. Four themes are concerned with the results of the synthesis that demarcate legitimate and predatory publications. They include factors: (1) Related to the journal, (2) Academic and professional, (3) Dissemination, and (4) Personal. Conclusion: Our literature review found that there is a lack of one single definition for predatory journals. We believe that it is essential for potential authors and young researchers to have clear guidelines and make demarcations of potential journals that seem dubious. Moreover, the authors’ selection of publishers should be modified to control the risks of tainting ‘open-access’ publishing with fraudulent journals. The academic and research community ought to revise their criteria and recognize high quality and author journals as opposed to ‘predatory’ journals. Research mentorship, realigning research incentives, and education is vital to decrease the impact of predatory publishing in the near future.

Severe acute respiratory syndrome called COVID-19, was declared as global health emergency and a pandemic due to its worldwide distribution and frightful spread. Patients are presented with severe respiratory illness along with thrombotic disorders. Elevated d-dimer level (>2000ng/ml) is a potentialpredictive biomarker of the disease outcome and prognosis. The objective of the present study isto find the association ofhigh d-dimer levels and mortality rate in COVID-19 patients to establish the optimal cutoff value for use in clinical setting. Methods: Present study enrolled 318COVID-19 patients admitted to Mayo Hospital, Lahore, Pakistan and confirmed by RT-PCR. On admission d-dimer levelof enrolled patients was measured by fluorescence immuno assay and reported in ng/ml. The enrolled subjects were divided in groupsbased on their age, gender, on admission d-dimer levels (<2000ng/ml and >2000ng/ml), outcome (survivors, non-survivors) and variant (α, β, and γ). Wilcoxon test was used to check the d-dimer level difference in survivor and non-survivor group. Results:81%patients (257/316) died and were categorized as non-survivors while 19% (61/318) were discharged after recovery and were categorized as survivors. Mean d-dimer levelfor survivor group was 2070ng/ml (±3060ng/ml) whereas for non-survivor group was 8010ng/ml (±5404ng/ml) and mean difference was statistically significant (p<0.05).D-dimer level washighest (upto 20,000ng/ml) in second wave(β-variant) as compared to other two wavesand caused highest number of deaths (n=163). Conclusion: Present study reports the d-dimer levels (>2000ng/ml)are strongly associated withhigh mortality rate in COVID-19 patients.

Objectives:  The main objective of the study was to analyze the efficacy of Depo-medrole injection in post-operative pain relief after lumbar discectomy. Material and Methods: This study was conducted in the Neurosurgery department of Mayo Hospital KEMU, Lahore during March 2018 to September 2018. The data was collected from 50 patients of lumbar discectomy randomly into two groups. One was operated patients and in group 2 patients were injected with local Depo-med role after lumbar discectomy. We studied the efficacy of Depo-med role injection in the second group. Pain intensity was measured using VAS from the whole sample at two weeks, four weeks, three months and last at one year post operatively. Results: Data were collected from 50 patients. These patients were divided into two groups, 25 in group one and 25 in group two. The mean age of group one was 30.14 ± 8.15 and for group two was 29.82 ± 7.16. Both groups neither contrasted by age (p = 0.187) nor as indicated by term of side effects (p = 0.639) at the season of operation. Conclusion: The usage of low dose Depo-med role decreased an abrupt lumbago and pain leg after surgery effectively. But it needs more observations due to small nonrandomized sample.