Seven new phenylspirodrimanes, named stachybotrins D-F (1, 3, 4), stachybocins E and F (5, 6), and stachybosides A and B (7, 8), and four known compounds (2, 9-11), were isolated from the sponge-derived fungus Stachybotrys chartarum MXH-X73. Their structures were determined by detailed analysis of spectroscopic data. The absolute configurations of 1-8 were determined by chemical hydrolysis and modified Mosher's and Marfey's methods. All compounds were tested in an anti-HIV activity assay, and compound 1 showed an inhibitory effect on HIV-1 replication by targeting reverse transcriptase. Further study exhibited that 1 could block NNRTIs-resistant strains (HIV-1RT-K103N, HIV-1RT-L100I,K103N, HIV-1RT-K103N,V108I, HIV-1RT-K103N,G190A, and HIV-1RT-K103N,P225H) as well as wild-type HIV-1 (HIV-1wt) with EC50 values of 7.0, 23.8, 13.3, 14.2, 6.2, and 8.4 μM, respectively.

Reactivation of the latent HIV-1 reservoir is a first step toward triggering reservoir decay. Here, we investigated the impact of the BAF complex inhibitor pyrimethamine on the reservoir of people living with HIV-1 (PLWH). Twenty-eight PLWH on suppressive antiretroviral therapy were randomized (1:1:1:1 ratio) to receive pyrimethamine, valproic acid, both, or no intervention for 14 days. The primary end point was change in cell-associated unspliced (CA US) HIV-1 RNA at days 0 and 14. We observed a rapid, modest, and significant increase in (CA US) HIV-1 RNA in response to pyrimethamine exposure, which persisted throughout treatment and follow-up. Valproic acid treatment alone did not increase (CA US) HIV-1 RNA or augment the effect of pyrimethamine. Pyrimethamine treatment did not result in a reduction in the size of the inducible reservoir. These data demonstrate that the licensed drug pyrimethamine can be repurposed as a BAF complex inhibitor to reverse HIV-1 latency in vivo in PLWH, substantiating its potential advancement in clinical studies.

The number of pharmacokinetic (PK) models of meropenem is increasing. However, the daily role of these PK models in the clinic remains unclear, especially for critically ill patients. Therefore, we evaluated the published meropenem models on real-world ICU data to assess their suitability for use in clinical practice. All models were built in NONMEM and evaluated using prediction and simulation-based diagnostics for the ability to predict the subsequent meropenem concentrations without plasma concentrations (a priori), and with plasma concentrations (a posteriori), for use in therapeutic drug monitoring (TDM). Eighteen PopPK models were included for evaluation. The a priori fit of the models, without the use of plasma concentrations, was poor, with a prediction error (PE)% of the interquartile range (IQR) exceeding the ±30% threshold. The fit improved when one to three concentrations were used to improve model predictions for TDM purposes. Two models were in the acceptable range with an IQR PE% within ±30%, when two or three concentrations were used. The role of PK models to determine the starting dose of meropenem in this population seems limited. However, certain models might be suitable for TDM-based dose adjustment using two to three plasma concentrations.

No abstract

No abstract