Tubular Secretory Solute Clearance and HIV Infection

BackgroundTubular secretion is an important kidney function responsible for the clearance of numerous medications, including antibiotics and antivirals. It is unknown whether persons living with HIV have lower secretion compared with HIV-uninfected persons, which might predispose them to the risk of progressive kidney disease or adverse drug events.Setting and methodsWe evaluated a panel of 6 endogenous secretory solutes in 199 women living with HIV (WLWH) and 100 women without HIV enrolled in the Women's Interagency HIV Study. Secretory clearance was estimated as the urine-to-plasma ratio of each solute, with adjustment for urine tonicity. Using multivariable linear regression analysis, we compared differences in levels of secretory solute clearance between women with and without HIV and evaluated characteristics associated with secretion.ResultsWLWH were older (median 40 vs. 38 years) but had similar estimated glomerular filtration rate (eGFR, 96 vs. 100 mL/minute/1.73 m 2 ) compared with those without HIV. African American and Latino race, diabetes, diastolic blood pressure, smoking, hepatitis C, peak HIV viral load, and current and nadir CD4 count were associated with differences in clearance of at least 1 marker after multivariable adjustment. The secretory clearance of 3 solutes (cinnamoylglycine, kynurenic acid, and pyridoxic acid) were on average 10%-15% lower among WLWH compared with those without HIV independent of eGFR, albuminuria and chronic kidney disease risk factors, including HCV, and injection drug use.ConclusionsHIV is associated with reduced secretion among women with preserved eGFR. The implications of these findings for drug dosing and adverse events need to be evaluated

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Acalabrutinib in management of chronic lymphocytic leukemia: An Indian perspective

Abstract The treatment landscape of chronic lymphocytic leukemia (CLL) has witnessed immense changes in the past decade. Several newer target therapies and their combinations with anti‐CD 20 therapies have got approval for management of CLL in the treatment‐naïve and relapsed/refractory setting. Also, the availability of newer diagnostic techniques has helped differentiate the disease into high‐ and low‐risk CLL which acts not just as a prognostic marker but also helps decide the best drug management that can be administered to the patients. Targeted therapy has largely overtaken chemoimmunotherapy in the management of CLL, except for a small subset of the population (young and fit with IGHV mutation). However, with targeted therapy, there is also an issue of previously uncommon treatment‐emergent adverse events, the duration of therapy, and financial toxicity. The aim of this review article is to gather results from all landmark CLL trials and discuss the feasibility of incorporating Acalabrutinib in the CLL landscape from an Indian perspective

Patient-reported Effects of Fedratinib, an Oral, Selective Inhibitor of Janus Kinase 2, on Myelofibrosis-related Symptoms and Health-related Quality of Life in the Randomized, Placebo-controlled, Phase III JAKARTA Trial

Patients with myelofibrosis (MF) experience an array of symptoms that impair health-related quality of life (HRQoL). Fedratinib, an oral, selective Janus-kinase 2 (JAK2) inhibitor, was investigated in the randomized, placebo-controlled, phase III JAKARTA study in adult patients with intermediate- or high-risk JAK-inhibitor-naïve MF. The effect of fedratinib 400 mg/d on patient-reported MF symptoms and HRQoL in JAKARTA was assessed. Participants completed the modified Myelofibrosis Symptom Assessment Form (MFSAF v2.0), which evaluates 6 key MF symptoms (night sweats, early satiety, pruritus, pain under ribs on the left side, abdominal discomfort, bone/muscle pain). The modified MFSAF v2.0 was completed during the first 6 treatment cycles and at end of cycle 6 (EOC6). Symptom response was a ≥50% improvement from baseline in total symptom score (TSS). Overall HRQoL was assessed by EQ-5D-3L health utility index (HUI) score. The MFSAF-evaluable population comprised 91/96 patients randomized to fedratinib 400 mg and 85/96 patients randomized to placebo. Mean baseline TSS was 17.6 and 14.7 for fedratinib and placebo, respectively, and mean EQ-5D-3L HUI was 0.70 and 0.72. Fedratinib elicited statistically significant and clinically meaningful improvements in TSS from baseline versus placebo at all postbaseline visits. Symptom response rates at EOC6 were 40.4% with fedratinib and 8.6% with placebo (OR 7.0 [95% CI, 2.9-16.9]; P < 0.001), and a significantly higher proportion of fedratinib-treated patients achieved clinically meaningful improvement from baseline on the EQ-5D-3L HUI at EOC6 (23.2% versus 6.5%; P = 0.002). Fedratinib provided clinically meaningful improvements in MF symptoms and overall HRQoL versus placebo in patients with JAK-inhibitor-naïve MF

Proceedings of Intelligent Computing and Technologies Conference

This proceeding contains articles on the various research ideas of the academic community and practitioners presented at the Intelligent Computing and Technologies Conference (ICTCon2021). ICTCon2021 was jointly organized by Assam Science and Technology University (ASTU), and Central Institute of Technology Kokrajhar (CITK) on March 15th–16th, 2021. Conference Title: Intelligent Computing and Technologies ConferenceConference Acronym: ICTCon2021Conference Date: 15–16 March 2021Conference Location: Online (Virtual Mode)Conference Organizers: Assam Science and Technology University (ASTU) and Central Institute of Technology Kokrajhar (CITK)