Bioavailability of dissolved and crushed single tablets of bictegravir, emtricitabine, tenofovir alafenamide in healthy adults: the SOLUBIC randomized crossover study.

BACKGROUND: Crushing or dissolving bictegravir/tenofovir alafenamide/emtricitabine (BIC/TAF/FTC) tablets is not recommended because there are no data supporting this practice. METHODS: A crossover, randomized trial in healthy adults (NCT04244448) investigated the bioavailability of two off-label uses of BIC/TAF/FTC (50/200/25 mg), dissolved in water or crushed in apple compote, compared with the solid tablet. Pharmacokinetic (PK) parameters were estimated from sequential intensive plasma antiretroviral concentrations over a 72 h period post dose. Bioequivalence was met if the 90% CIs of the geometric least-squares means ratios comparing BIC/TAF/FTC exposures (AUC and Cmax) from the experimental phases were within 80%-125% of the reference. RESULTS: Eighteen subjects participated in each of the three phases. Dissolved tablet Cmax geometric mean ratio (90% CI) for BIC/TAF/FTC was 105% (93-119)/97% (87-108)/96% (74-124), respectively. Dissolved tablet AUC geometric mean ratio (90% CI) for BIC/TAF/FTC was 111% (100-122)/100% (94 to 105)/99% (81 to 120), respectively. Crushed tablet Cmax geometric mean ratio (90%) CI for BIC/TAF/FTC was 110% (97 to 124)/70% (63-78)/66% (51-85), respectively. Crushed tablet AUC geometric mean ratio (90%) CI for BIC/TAF/FTC was 107% (96-118)/86% (82-91)/84% (69-103), respectively. CONCLUSIONS: Crushing BIC/TAF/FTC tablets may lead to suboptimal emtricitabine and tenofovir alafenamide drug exposures. Dissolving BIC/TAF/FTC in water may be acceptable if the tablet cannot be swallowed whole.

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems.

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures.

Case Report: Co-infection with SARS-CoV-2 and influenza H1N1 in a patient with acute respiratory distress syndrome and a pulmonary sarcoidosis.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and has been a global public health concern. Co-infection of SARS-CoV-2 and other respiratory syndrome has been rarely reported. We report coinfection of SARS-CoV-2 and 2009 H1N1 Influenza strain in a French patient with pneumonia leading to acute respiratory distress syndrome.  The patient also had a medical history of pulmonary sarcoidosis with a restrictive ventilatory syndrome, which would be a supplementary risk to develop a poor outcomes. This case highlights the possible coinfection of two severe SARS-CoV-2 and influenza H1N1 viruses, which presents a higher risk to extend the care duration. The overlapping clinical features of the two respiratory syndromes is a challenge, and awareness is required to recommend an early differential diagnosis.