and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEWThe GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs).FINDINGS In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCEThe results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

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In type 1 diabetic children, deficient levels of 25(OH)D are associated with high levels of HbA1c, circulatory cytokines and antibody markers.

Background: Lead (Pb) is observed in all areas of the environment, mainly derived from human operations such as mining, processing, and burning fossil fuels. Pb toxicity is one of the most prevalent causes of human hepatotoxicity. The available chelator drugs used now have many adverse effects and therefore the world is looking for natural and secure alternatives. Methods: Here, we evaluated the hepatoprotective role of the oral administration (1 g/kg b.w.) of the lyophilized Beta vulgaris juice (BVJ) against Pb-induced rat hepatotoxicity. We also examined the possible synergistic hepatoprotective impact of the combination between BVJ and 2,3-dimercaptosuccinic acid (DMSA, the currently approved drug for Pbtoxicity). The evaluation depends on the ability of BVJ, DMSA, or their combination (BVJ-DMSA) to reduce serum and hepatic Pb level and to avoid oxidative stress and inflammation caused by Pb. The level of lipid peroxidation, reduced glutathione (GSH), total antioxidant capacity, and the activity of the antioxidant enzymes were quantified. In addition, the level of interleukin (IL)-6, nitric oxide (NO), DNA fragmentation, and liver histology were studied. Results: The results showed that BVJ contained considerable amounts of betalains, vitamin C, and various types of phenolic compounds. Therefore, BVJ displayed a significant (p < 0.05) preventive influence on the elevation of Pb levels in blood and liver as well as the hepatic DNA fragmentation. In addition, it significantly (p < 0.05) improved most of the studied antioxidant and inflammatory markers in the Pb-intoxicated rats. However, the combined extract (BVJ-DMSA) revealed synergistic (combination index < 1) activities in most of the tested parameters. The histopathological results verified the biochemical findings of this research.

Different metabolic disorders were identified in this cohort, which caused different types of epilepsy, especially myoclonic seizures and infantile spasms.

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Background Breast cancer heterogeneity is an essential element that plays a role in the therapy response variability and the patient’s outcome. This highlights the need for more precise subtyping methods that focus not only on tumor cells but also investigate the profile of stromal cells as well as immune cells. Objectives To mine publicly available transcriptomic breast cancer datasets and reanalyze their transcriptomic profiling using unsupervised clustering in order to identify novel subsets in molecular subtypes of breast cancer, then explore the stromal and immune cells profile in each subset using bioinformatics and systems immunology approaches. Materials and Methods Transcriptomic data from 1,084 breast cancer patients obtained from The Cancer Genome Atlas (TCGA) database were extracted and subjected to unsupervised clustering using a recently described, multi-step algorithm called Iterative Clustering and Guide-gene Selection (ICGS). For each cluster, the stromal and immune profile was investigated using ESTIMATE and CIBERSORT analytical tool. Clinical outcomes and differentially expressed genes of the characterized clusters were identified and validated in silico and in vitro in a cohort of 80 breast cancer samples by immunohistochemistry. Results Seven unique sub-clusters showed distinct molecular and clinical profiles between the well-known breast cancer subtypes. Those unsupervised clusters identified more homogenous subgroups in each of the classical subtypes with a different prognostic profile. Immune profiling of the identified clusters showed that while the classically activated macrophages (M1) are correlated with the more aggressive basal-like breast cancer subtype, the alternatively activated macrophages (M2) showed a higher level of infiltration in luminal A and luminal B subtypes. Indeed, patients with higher levels of M1 expression showed less advanced disease and better patient outcomes presented as prolonged overall survival. Moreover, the M1 high basal-like breast cancer group showed a higher expression of interferon-gamma induced chemokines and guanylate-binding proteins (GBPs) involved in immunity against microbes. Conclusion Adding immune profiling using transcriptomic data can add precision for diagnosis and prognosis and can cluster patients according to the available modalities of therapy in a more personalized approach.