Deciphering the putative bioactive metabolites and the underlying mechanism of Juniperus horizontalis Moench (Creeping juniper) in the treatment of inflammation using network pharmacology and molecular docking.

Objectives To investigate the chemical composition of the alcoholic extract from creeping juniper leaves using HPLC-MS/MS and to elucidate its potential anti-inflammatory mechanism through network-based pharmacology analysis to collectively enable a systematic exploration of the chemical composition, mechanism of action, and therapeutic potential of the alcoholic extract from creeping juniper leaves, providing valuable insights into its suitability as an anti-inflammatory agent.Methods Chemical profiling of the alcoholic extract of creeping juniper leaves using HPLC-MS/MS and revealing its anti-inflammatory mechanism using network-based pharmacology. Further, isolation of some of the identified biomarkers, assessment of their ex-vivo anti-inflammatory activity, and determination of their binding to pro-inflammatory cytokines using molecular docking and dynamics.Key findings Thirty-seven compounds were annotated and forwarded to network pharmacology analysis which revealed that the highest interactions were exhibited by quercetin, cosmosiin, myricetin, amentoflavone, hyperoside, isorhamnetin, and quercitrin whereas the most enriched inflammatory targets were IL-2, PGF, VEGFA, and TNFs. PI3K-Akt signaling pathway, arachidonic acid metabolism, and MAPK signaling pathway were found to be the most enriched ones. Six hit compounds were isolated and identified as hyperoside, quercetrin, cupressuflavone, hinokiflavone, amentoflavone, and quercetin. The isolated compounds showed strong anti-inflammatory activity against TNF-alpha, IL-6, and IL-1 beta, and molecular docking and dynamics simulation showed that quercetin, quercitrin, and hyperoside had the least binding energy with TNF-alpha, IL-6, and IL-1B, respectively.Conclusions Creeping juniper may reduce inflammation based on the suggested multi-compounds and multi-pathways, and that provided the basis for creeping juniper use as a potential anti-inflammatory drug

Nutrigenomic effect of conjugated linoleic acid on growth and meat quality indices of growing rabbit.

Conjugated linoleic acid was detected in rabbit caecotrophs, due to the presence of microbial lipid activity in rabbit cecum. However, the effect of CLA as a functional food in growing rabbit is not well established. Therefore, this study was conducted to determine the effect of CLA on production, meat quality, and its nutrigenomic effect on edible parts of rabbit carcass including skeletal muscle, liver, and adipose tissue. Therefore, seventy five weaned V-Line male rabbits, 30 days old, were randomly allocated into three dietary treatments receiving either basal control diet, diet supplemented with 0.5% (CLAL), or 1% CLA (CLAH). Total experimental period (63 d) was segmented into 7 days adaptation and 56 days experimental period. Dietary supplementation of CLA did not alter growth performance, however, the fat percentage of longissimus lumborum muscle was decreased, with an increase in protein and polyunsaturated fatty acids (PUFA) percentage. Saturated fatty acids (SFA) and mono unsaturated fatty acids (MUFA) were not increased in CLA treated groups. There was tissue specific sensing of CLA, since subcutaneous adipose tissue gene expression of PPARA was downregulated, however, CPT1A tended to be upregulated in liver of CLAL group only (P = 0.09). In skeletal muscle, FASN and PPARG were upregulated in CLAH group only (P ≤0.01). Marked cytoplasmic vacuolation was noticed in liver of CLAH group without altering hepatocyte structure. Adipocyte size was decreased in CLA fed groups, in a dose dependent manner (P <0.01). Cell proliferation determined by PCNA was lower (P <0.01) in adipose tissue of CLA groups. Our data indicate that dietary supplementation of CLA (c9,t11-CLA and t10,c12- CLA) at a dose of 0.5% in growing rabbit diet produce rabbit meat rich in PUFA and lower fat % without altering growth performance and hepatocyte structure

Epidemiological characterization of viral etiological agents of the central nervous system infections among hospitalized patients in Egypt between 2016 and 2019

Abstract Viral infections of the central nervous system (CNS) are common worldwide and result in considerable morbidity and mortality associated with neurologic illness. Until now, there have been no epidemiologic data regarding viruses causing aseptic meningitis, encephalitis, and CNS infections in Egypt. We investigated 1735 archived cerebrospinal fluid samples collected from Egyptian patients between 2016 and 2019 and performed molecular characterization for infection for12 different viruses: herpes simplex viruses 1 and 2 (HSV-1 and HSV-2), varicella-zoster virus (VZV), Epstein–Barr virus (EBV), cytomegalovirus (CMV), human herpesviruses 6 and 7 (HHV-6 and HHV-7), human enteroviruses (HEVs), human parechovirus (HPeV), parvovirus B19 (B19V), adenovirus (AdV), and mumps virus (MuV). All included samples were negative for bacterial infection. Our results indicated a relatively high prevalence of viral infection, with HEVs being the most prevalent viruses, followed by HSV-1, EBV, and then HSV-2. The highest prevalence was among male patients, peaking during the summer. Data obtained from this study will contribute to improving the clinical management of viral infections of the CNS in Egypt

Comparison of SARS-Cov-2 omicron variant with the previously identified SARS-Cov-2 variants in Egypt, 2020–2022: insight into SARS-Cov-2 genome evolution and its impact on epidemiology, clinical picture, disease severity, and mortality

Abstract Background The o severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic has killed millions of people and caused widespread concern around the world. Multiple genetic variants of SARS-CoV-2 have been identified as the pandemic continues. Concerns have been raised about high transmissibility and lower vaccine efficacy against omicron. There is an urgent need to better describe how omicron will impact clinical presentation and vaccine efficacy. This study aims at comparing the epidemiologic, clinical, and genomic characteristics of the omicron variant prevalent during the fifth wave with those of other VOCs between May 2020 and April 2022. Methods Epidemiological data were obtained from the National Electronic Diseases Surveillance System. Secondary data analysis was performed on all confirmed COVID-19 patients. Descriptive data analysis was performed for demographics and patient outcome and the incidence of COVID-19 was calculated as the proportion of SARS-CoV-2 confirmed patients out of the total population of Egypt. Incidence and characteristics of the omicron cohort from January- April 2022, were compared to those confirmed from May 2020-December 2021. We performed the whole-genome sequencing of SARS-CoV-2 on 1590 specimens using Illumina sequencing to describe the circulation of the virus lineages in Egypt. Results A total of 502,629 patients enrolled, including 60,665 (12.1%) reported in the fifth wave. The incidence rate of omicron was significantly lower than the mean of incidences in the previous subperiod (60.1 vs. 86.3/100,000 population, p < 0.001). Symptoms were reported less often in the omicron cohort than in patients with other variants, with omicron having a lower hospitalization rate and overall case fatality rate as well. The omicron cohort tended to stay fewer days at the hospital than did those with other variants. We analyzed sequences of 2433 (1590 in this study and 843 were obtained from GISAID platform) Egyptian SARS-CoV-2 full genomes. The first wave that occurred before the emergence of global variants of concern belonged to the B.1 clade. The second and third waves were associated with C.36. Waves 4 and 5 included B.1.617.2 and BA.1 clades, respectively. Conclusions The study indicated that Omicron-infected patients had milder symptoms and were less likely to be hospitalized; however, patients hospitalized with omicron had a more severe course and higher fatality rates than those hospitalized with other variants. Our findings demonstrate the importance of combining epidemiological data and genomic analysis to generate actionable information for public health decision-making