METHODS: The data from the Global Burden of Diseases Study 2019 (GBD 2019) results were used. Absolute incidence and death number, and age-standardized incidence and mortality rate (ASIR and ASMR) of NTDM in China and ASEAN were extracted. The estimated annual percentage change (EAPC) and join-point regression in the rates quantified the trends. Nonlinear regression (second order polynomial) was used to explore the association between SDI and ASRs.
RESULTS: The ASIR of NTDM increased in China, Philippines, Singapore and Brunei, at a speed of an average 4.15% (95% CI 3.83-4.47%), 2.15% (1.68-2.63%), 1.03% (0.63-1.43%), and 0.88% (0.60-1.17%) per year. Uptrends of ASIR of NTDM in recent years were found in China (2014-2017, APC = 10.4%), Laos (2005-2013, APC = 3.9%), Malaysia (2010-2015, APC = 4.3%), Philippines (2015-2019, APC = 4.2%), Thailand (2015-2019, APC = 2.4%), and Vietnam (2014-2017, APC = 3.2%, all P
AIM OF THE STUDY: The primary aim of this review is to document the plants and natural products that are used as foods and medicines in Egypt, in general, and in Sinai, in particular, with a focus on those with demonstrated anticancer activities. The documented traditional uses of these plants are described, together with their chemical and pharmacological activities and the reported outcomes of clinical trials against cancer.
MATERIALS AND METHODS: A literature search was performed to identify texts describing the medicinal plants that are cultivated and grown in Egypt, including information found in textbooks, published articles, the plant list website (http://www.theplantlist.org/), the medicinal plant names services website (http://mpns.kew.org/mpns-portal/), and web databases (PubMed, Science Direct, and Google Scholar).
RESULTS AND DISCUSSION: We collected data for most of the plants cultivated or grown in Egypt that have been previously investigated for anticancer effects and reported their identified bioactive elements. Several plant species, belonging to different families and associated with 67 bioactive compounds, were investigated as potential anticancer agents (in vitro studies). The most potent cytotoxic activities were identified for the families Asteraceae, Lamiaceae, Chenopodiaceae, Apocynaceae, Asclepiadaceae, Euphorbiaceae, Gramineae, and Liliaceae. The anticancer activities of some species, such as Punica granatum L., Nerium oleander L., Olea europea L., Matricaria chamomilla L., Cassia acutifolia L., Nigella sativa L., Capsicum frutescens L., Withania somnifera L., and Zingiber officinale Roscoe, have been examined in clinical trials. Among the various Egyptian plant habitats, we found that most of these plants are grown in the North Sinai, New-Delta, and Giza Governorates.
CONCLUSION: In this review, we highlight the role played by Egyptian flora in current medicinal therapies and the possibility that these plants may be examined in further studies for the development of anticancer drugs. These bioactive plant extracts form the basis for the isolation of phytochemicals with demonstrated anticancer activities. Some active components derived from these plants have been applied to preclinical and clinical settings, including resveratrol, quercetin, isoquercetin, and rutin.
METHODS: A literature search was performed for the screening of natural and derived bio-active compounds which showed potent antiviral activity against coronaviruses using published articles, patents, clinical trials website (https://clinicaltrials.gov/) and web databases (PubMed, SCI Finder, Science Direct, and Google Scholar).
RESULTS: Through the screening for natural products with antiviral activities against different types of the human coronavirus, extracts of Lycoris radiata (L'Hér.), Gentiana scabra Bunge, Dioscorea batatas Decne., Cassia tora L., Taxillus chinensis (DC.), Cibotium barometz L. and Echinacea purpurea L. showed a promising effect against SARS-CoV. Out of the listed compound Lycorine, emetine dihydrochloride hydrate, pristimerin, harmine, conessine, berbamine, 4`-hydroxychalcone, papaverine, mycophenolic acid, mycophenolate mofetil, monensin sodium, cycloheximide, oligomycin and valinomycin show potent activity against human coronaviruses. Additionally, it is worth noting that some compounds have already moved into clinical trials for their activity against COVID-19 including fingolimod, methylprednisolone, chloroquine, tetrandrine and tocilizumab.
CONCLUSION: Natural compounds and their derivatives could be used for developing potent therapeutics with significant activity against SARS-COV-2, providing a promising frontline in the fighting against COVID-19.
METHODS: We utilized data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium, involving approximately 9,269 cases and 12,530 controls of European descent, to evaluate associations between pancreatic cancer risk and genetically predicted plasma n-6 PUFA levels. Conventional MR analyses were performed using individual-level and summary-level data.
RESULTS: Using genetic instruments, we did not find evidence of associations between genetically predicted plasma n-6 PUFA levels and pancreatic cancer risk [estimates per one SD increase in each PUFA-specific weighted genetic score using summary statistics: linoleic acid odds ratio (OR) = 1.00, 95% confidence interval (CI) = 0.98-1.02; arachidonic acid OR = 1.00, 95% CI = 0.99-1.01; and dihomo-gamma-linolenic acid OR = 0.95, 95% CI = 0.87-1.02]. The OR estimates remained virtually unchanged after adjustment for covariates, using individual-level data or summary statistics, or stratification by age and sex.
CONCLUSIONS: Our results suggest that variations of genetically determined plasma n-6 PUFA levels are not associated with pancreatic cancer risk.
IMPACT: These results suggest that modifying n-6 PUFA levels through food sources or supplementation may not influence risk of pancreatic cancer.
METHODS: We conducted a gene-environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I-III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case-control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics.
RESULTS: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10-6) was observed in the meta-analysis (P GxE = 1.2 ×10-6, P Joint = 4.2 ×10-7).
CONCLUSIONS: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans.
IMPACT: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.
METHODS: To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples).
RESULTS: We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction.
CONCLUSIONS: By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.