Estimation of Nonalcoholic Fatty Liver Disease in Patients with Normal BMI on Ultrasound

Background: Non-Alcoholic fatty liver disease is common in adults and it is increasing in patients with normal BMI in Asian countries. Non-alcoholic fatty liver disease (NAFLD) occurs not only in obese individuals but also in non-obese ones. The association between NAFLD and metabolic events in a non-obese population is also evident.. Objective: To estimate nonalcoholic fatty liver disease in patients with normal BMI on ultrasound. Methodology: Analytical Cross-sectional prospective study in which 59 patients were enrolled in the research. All the patient’s data had been composed from indoor of hospital, outdoor of hospital, DHA Medical Center, Lahore. After well-versed consent, data was composed through ultrasound machine. The data, such as patient characteristics, hypertension, impaired fasting glucose, were extracted from medical records, and statistical analysis was performed. Results: The present study is retrospective cross sectional observational study.60 patients (29males 49.2% 31 female 50.8%) were enrolled in this study. According to abdominal ultrasonography, 72.9% of patients with normal BMI were diagnosed to have Non-alcoholic fatty liver disease and identified to have fatty changes in the liver. Conclusion: In our study we estimated that nonalcoholic fatty liver disease was present in patients with normal body mass index by imaging the echotexture of liver on ultrasound. Having increased echogenicity, due to poor diet and other associated diseases such as high blood pressure, impaired fasting glucose and low HDL cholesterol patients were getting NAFLD. Keywords: Nonalcoholic fatty liver disease (NAFLD), Body Mass Index (BMI), Ultrasonography (USG). DOI: 10.7176/JHMN/92-03 Publication date:August 31st 202

Medicinal Biospecificity of Ginger and Its Efficacious Bioactive Compounds in the Context of Its Biological Activities Against Predominant Health Issues: Current Study and New Avenues

There is a multitude of life-threatening and widespread health issues worldwide, regarding weak immunity, severe inflammation, viral infections, bacterial infections as well as antimicrobial resistance (AMR), high free radicals generation, and cancer. Ginger, a perennial plant of the Zingiberaceae family with several authentic nutritional and medicinal values used in many countries as traditional medicine. That is why, the study was designed to highlight recent studies about medicinally most efficacious bio-active compounds of ginger along their biological significance related to immuno-stimulatory, anti-inflammatory, anti-viral, anti-bacterial, anti-oxidant, and anti-cancer effects. Our study also recognized future gaps in research. The study included professional research data under duration from 2001-2022 appearing in books and scholarly journals, collected from scientific database platforms via PubMed, Web of Science, Google Scholar, Springer Nature, Science Direct and Scopus. The present study includes the medicinal effects of almost 44 most influential ginger compounds like phenolics, terpenoids, flavonoids, and vinyllyl ketonic compounds etc. Our results revealed the strong alleviating effects of gingerols, shogaols, paradols, and polyphenols. Moreover, the ginger essential oil has proven to be very effective both for antiviral and antibacterial activity. However, no data is available in previous literature for components of ginger involved in immuno-stimulatory, effects. There is also a need to explore components for antibacterial activity. However, research has been conducted on ginger for only a few viruses despite its strong alleviating effects. Besides this, more study is needed to comprehend the comprehensive mechanism of action (especially at the molecular level) regarding the anti-bacterial and anti-viral activity of ginger and its constituents

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.