Age-Specific Cancer Mortality in the US During the COVID-19 Pandemic, March to December 2020.

BACKGROUND: It is important to understand the impact of the COVID-19 pandemic on cancer death rates in 2020 in the US. We estimated whether there were larger-than-expected changes in cancer mortality rates from March to December 2020 after accounting for temporal and seasonal patterns using data from January 2011 to February 2020 by cancer type and age. METHODS: We obtained death counts and underlying causes of death by cancer type, month/year (2011-2020), and age group from the National Center for Health Statistics and population estimates from the US Census Bureau. Poisson regression was used to test for significant changes in cancer death rates from March to December 2020 compared with prior years. RESULTS: After accounting for temporal trends and seasonal patterns, total cancer death rates were significantly lower than expected during March to December 2020 among 55- to 64-year-olds and ≥75-year-olds, but not in other age groups. Cancer death rates were 2% lower than expected from March to June among 55- to 64-year-olds and 2% to 3% lower from March to July and December among ≥75-year-olds. Among ≥75-year-olds, colorectal cancer death rates were lower from March to June [rate ratios (RR) = 0.94-0.96; P < 0.05]; however, lung cancer death rates were 5% lower across each month (all RRs = 0.95; P < 0.05). CONCLUSIONS: In the US, cancer death rates based on the underlying cause of death were broadly similar to expected rates from March to December 2020. However, cancer death rates were lower than expected among 55- to 64-year-olds and ≥75-year-olds, likely due to COVID-19 as a competing cause of death. IMPACT: Cancer mortality rates from 2020 should be interpreted with caution.

MedicaidJS: a FAIR approach to real-time drug analytics.

Motivation: As prescription drug prices have drastically risen over the past decade, so has the need for real-time drug tracking resources. In spite of increased public availability to raw data sources, individual drug metrics remain concealed behind intricate nomenclature and complex data models. Some web applications, such as GoodRX, provide insight into real-time drug prices but offer limited interoperability. To overcome both obstacles we pursued the direct programmatic operation of the stateless Application Programming interfaces (HTTP REST APIs) maintained by the Food and Drug Administration (FDA), Medicaid, and National Library of Medicine. These data-intensive resources represent an opportunity to develop Software Development Kits (SDK) to streamline drug metrics without downloads or installations, in a manner that addresses the FAIR principles for stewardship in scientific data-Findability, Accessibility, Interoperability, and Reusability. These principles provide a guideline for continual stewardship of scientific data. Results: MedicaidJS SDK was developed to orchestrate API calls to three complementary data resources: Medicaid (data.medicaid.gov), Food and Drug Administration (open.fda.gov), and the National Library of Medicine RxNorm (lhncbc.nlm.nih.gov/RxNav). MedicaidJS synthesizes response data from each platform into a zero-footprint JavaScript modular library that provides data wrangling, analysis, and generation of embeddable interactive visualizations. The SDK is served on github with live examples on observableHQ notebooks. It is freely available and can be embedded into web applications as modules returning structured JSON data with standardized identifiers. Availability and implementation: Open source code publicly available at https://github.com/episphere/medicaid, live at episphere.github.io/medicaid, supplementary interactive Observable Notebooks at observablehq.com/@medicaidsdk/medicaidsdk.

Effects of Phytochemicals on Blood Pressure and Neuroprotection Mediated Via Brain Renin-Angiotensin System.

BACKGROUND: The renin-angiotensin system (RAS) in the brain plays a crucial role in maintaining blood pressure as well as neuroprotection. This study compared the effects of curcumin, quercetin, and saponin on blood pressure, the brain RAS, and cholinergic system using perindopril, an angiotensin converting enzyme inhibitor (ACEI), as a positive control. METHODS: Five-week-old male mice were stabilized and randomly assigned into a control group (n = 8), three phytochemical-treated groups (curcumin (n = 8), quercetin (n = 8), and saponin (n = 8)), and a positive control group (n = 8). The groups treated with the phytochemical were orally administered daily at a dose of 50 mg/kg body weight of phytochemicals. During the experiments, the weight and dietary intakes were measured regularly. After experiments, the brain tissue was homogenized and centrifuged for an additional assay. The concentrations of ACE, angiotensin II (AngII), and aldosterone levels were measured, and the mRNA expressions of renin and ACE were measured. As biomarkers of neuroprotection, the concentrations of acetylcholine(Ach) as well as the concentration and activity of acetylcholine esterase (AChE) were measured. RESULTS: After 4 weeks of treatment, the perindopril group showed the lowest blood pressure. Among the groups treated with the phytochemicals, treatment with curcumin and saponin significantly reduced blood pressure, although such effect was not as high as that of perindopril. Among phytochemicals, curcumin treatment significantly inhibited the concentration and activity of ACE, concentration of AngII, and mRNA expression of ACE. All phytochemical treatments significantly increased the concentration of ACh. The levels of AChE activity in groups exposed to curcumin or saponin (not quercetin) were significantly inhibited, Conclusion: Curcumin administration in rats reduced blood pressure by blocking the brain RAS components and protected the cholinergic system in brain by inhibiting the activity of AChE.