Two HIV-1 Variants Resistant to Small Molecule CCR5 Inhibitors Differ in How They Use CCR5 for Entry

HIV-1 variants resistant to small molecule CCR5 inhibitors recognize the inhibitor-CCR5 complex, while also interacting with free CCR5. The most common genetic route to resistance involves sequence changes in the gp120 V3 region, a pathway followed when the primary isolate CC1/85 was cultured with the AD101 inhibitor in vitro, creating the CC101.19 resistant variant. However, the D1/86.16 escape mutant contains no V3 changes but has three substitutions in the gp41 fusion peptide. By using CCR5 point-mutants and gp120-targeting agents, we have investigated how infectious clonal viruses derived from the parental and both resistant isolates interact with CCR5. We conclude that the V3 sequence changes in CC101.19 cl.7 create a virus with an increased dependency on interactions with the CCR5 N-terminus. Elements of the CCR5 binding site associated with the V3 region and the CD4-induced (CD4i) epitope cluster in the gp120 bridging sheet are more exposed on the native Env complex of CC101.19 cl.7, which is sensitive to neutralization via these epitopes. However, D1/86.16 cl.23 does not have an increased dependency on the CCR5 N-terminus, and its CCR5 binding site has not become more exposed. How this virus interacts with the inhibitor-CCR5 complex remains to be understood

Quinine, an old anti-malarial drug in a modern world: role in the treatment of malaria

Quinine remains an important anti-malarial drug almost 400 years after its effectiveness was first documented. However, its continued use is challenged by its poor tolerability, poor compliance with complex dosing regimens, and the availability of more efficacious anti-malarial drugs. This article reviews the historical role of quinine, considers its current usage and provides insight into its appropriate future use in the treatment of malaria. In light of recent research findings intravenous artesunate should be the first-line drug for severe malaria, with quinine as an alternative. The role of rectal quinine as pre-referral treatment for severe malaria has not been fully explored, but it remains a promising intervention. In pregnancy, quinine continues to play a critical role in the management of malaria, especially in the first trimester, and it will remain a mainstay of treatment until safer alternatives become available. For uncomplicated malaria, artemisinin-based combination therapy (ACT) offers a better option than quinine though the difficulty of maintaining a steady supply of ACT in resource-limited settings renders the rapid withdrawal of quinine for uncomplicated malaria cases risky. The best approach would be to identify solutions to ACT stock-outs, maintain quinine in case of ACT stock-outs, and evaluate strategies for improving quinine treatment outcomes by combining it with antibiotics. In HIV and TB infected populations, concerns about potential interactions between quinine and antiretroviral and anti-tuberculosis drugs exist, and these will need further research and pharmacovigilance

Interleukin-7 and Toll-like receptor 7 induce synergistic B cell and T cell activation.

OBJECTIVES: To investigate the potential synergy of IL-7-driven T cell-dependent and TLR7-mediated B cell activation and to assess the additive effects of monocyte/macrophages in this respect. METHODS: Isolated CD19 B cells and CD4 T cells from healthy donors were co-cultured with TLR7 agonist (TLR7A, Gardiquimod), IL-7, or their combination with or without CD14 monocytes/macrophages (T/B/mono; 1 : 1 : 0,1). Proliferation was measured using 3H-thymidine incorporation and Ki67 expression. Activation marker (CD19, HLA-DR, CD25) expression was measured by FACS analysis. Immunoglobulins were measured by ELISA and release of cytokines was measured by Luminex assay. RESULTS: TLR7-induced B cell activation was not associated with T cell activation. IL-7-induced T cell activation alone and together with TLR7A synergistically increased numbers of both proliferating (Ki67+) B cells and T cells, which was further increased in the presence of monocytes/macrophages. This was associated by up regulation of activation markers on B cells and T cells. Additive or synergistic induction of production of immunoglobulins by TLR7 and IL-7 was associated by synergistic induction of T cell cytokines (IFNγ, IL-17A, IL-22), which was only evident in the presence of monocytes/macrophages. CONCLUSIONS: IL-7-induced CD4 T cell activation and TLR7-induced B cell activation synergistically induce T helper cell cytokine and B cell immunoglobulin production, which is critically dependent on monocytes/macrophages. Our results indicate that previously described increased expression of IL-7 and TLR7 together with increased numbers of macrophages at sites of inflammation in autoimmune diseases like RA and pSS significantly contributes to enhanced lymphocyte activation

Diagnostic stewardship for blood cultures in the emergency department: A multicenter validation and prospective evaluation of a machine learning prediction tool

Summary: Background: Overuse of blood cultures (BCs) in emergency departments (EDs) leads to low yields and high numbers of contaminated cultures, accompanied by increased diagnostics, antibiotic usage, prolonged hospitalization, and mortality. We aimed to simplify and validate a recently developed machine learning model to help safely withhold BC testing in low-risk patients. Methods: We extracted data from the electronic health records (EHR) for 44.123 unique ED visits with BC sampling in the Amsterdam UMC (locations VUMC and AMC; the Netherlands), Zaans Medical Center (ZMC; the Netherlands), and Beth Israel Deaconess Medical Center (BIDMC; United States) in periods between 2011 and 2021. We trained a machine learning model on the VUMC data to predict blood culture outcomes and validated it in the AMC, ZMC, and BIDMC with subsequent real-time prospective evaluation in the VUMC. Findings: The model had an Area Under the Receiver Operating Characteristics curve (AUROC) of 0.81 (95%-CI = 0.78–0.83) in the VUMC test set. The most important predictors were temperature, creatinine, and C-reactive protein. The AUROCs in the validation cohorts were 0.80 (AMC; 0.78–0.82), 0.76 (ZMC; 0.74–0.78), and 0.75 (BIDMC; 0.74–0.76). During real-time prospective evaluation in the EHR of the VUMC, it reached an AUROC of 0.76 (0.71–0.81) among 590 patients with BC draws in the ED. The prospective evaluation showed that the model can be used to safely withhold blood culture analyses in at least 30% of patients in the ED. Interpretation: We developed a machine learning model to predict blood culture outcomes in the ED, which retained its performance during external validation and real-time prospective evaluation. Our model can identify patients at low risk of having a positive blood culture. Using the model in practice can significantly reduce the number of blood culture analyses and thus avoid the hidden costs of false-positive culture results. Funding: This research project was funded by the Amsterdam Public Health – Quality of Care program and the Dutch “Doen of Laten” project (project number: 839205002)