Person:

Reddy, Krishna

Cyclic AMP- (cAMP) and calcium-dependent agonists stimulate chloride secretion through the coordinated activation of distinct apical and basolateral membrane channels and ion transporters in mucosal epithelial cells. Defects in the regulation of Cl– transport across mucosal surfaces occur with cystic fibrosis and V. cholerae infection and can be life threatening. Here we report that secramine B, a small molecule that inhibits activation of the Rho GTPase Cdc42, reduced cAMP-stimulated chloride secretion in the human intestinal cell line T84. Secramine B interfered with a cAMP-gated and Ba2+-sensitive K+ channel, presumably KCNQ1/KCNE3. This channel is required to maintain the membrane potential that sustains chloride secretion. In contrast, secramine B did not affect the Ca2+-mediated chloride secretion pathway, which requires a separate K+ channel activity from that of cAMP. Pirl1, another small molecule structurally unrelated to secramine B that also inhibits Cdc42 activation in vitro, similarly inhibited cAMP-dependent but not Ca2+-dependent chloride secretion. These results suggest that Rho GTPases may be involved in the regulation of the chloride secretory response and identify secramine B an inhibitor of cAMP-dependent K+ conductance in intestinal epithelial cells.

Among critically ill patients with lower respiratory tract (LRT)-confirmed influenza, we retrospectively observed worse 28-day clinical outcomes in upper respiratory tract (URT)-negative versus URT-positive subjects. This finding may reflect disease progression and highlights the need for influenza testing of both URT and LRT specimens to improve diagnostic yield and possibly inform prognosis.

Background: HIV-associated tuberculosis (TB) co-infection remains an enormous burden to international public health. Post-mortem studies have highlighted the high proportion of HIV-positive adults admitted to hospital with TB. Determine TB-LAM and Xpert MTB/RIF assays can substantially increase diagnostic yield of TB within one day of hospital admission. However, it remains unclear if this approach can impact clinical outcomes. The STAMP trial aims to test the hypothesis that the implementation a urine-based screening strategy for TB can reduce all cause-mortality among HIV-positive patients admitted to hospital when compared to current, sputum-based screening. Methods: The trial is a pragmatic, individually randomised, multi-country (Malawi and South Africa) clinical trial with two study arms (1:1 recruitment). Unselected HIV-positive patients admitted to medical wards, irrespective of presentation, meeting the inclusion criteria and giving consent will be randomized to screening for TB using either: (i) ‘standard of care’- testing of sputum using the Xpert MTB/RIF assay (Xpert) or (ii) ‘intervention’- testing of sputum using Xpert and testing of urine using (a) Determine TB-LAM lateral-flow assay and (b) Xpert following concentration of urine by centrifugation. Patients will be excluded if they have received TB treatment in the previous 12 months, if they have received isoniazid preventive therapy in the last 6 months, if they are aged <18 years or they live outside the pre-specified geographical area. Results will be provided to the responsible medical team as soon as available to inform decisions regarding TB treatment. Both the study and routine medical team will be masked to study arm allocation. 1300 patients will be enrolled per arm (equal numbers at the two trial sites). The primary endpoint is all-cause mortality at 56 days. An economic analysis will be conducted to project long-term outcomes for shorter-term trial data, including cost-effectiveness. Discussion This pragmatic trial assesses an intervention to reduce the high mortality caused by HIV-associated TB, which could feasibly be scaled up in high-burden settings if shown to be efficacious and cost-effective. We discuss the challenges of designing a trial to assess the impact on mortality of laboratory-based TB screening interventions given frequent initiation of empirical treatment and a failure of several previous clinical trials to demonstrate an impact on clinical outcomes. We also elaborate on the practical and ethical issues of ‘testing a test’ in general. Trial registration ISRCTN Registry (ISRCTN71603869) prospectively registered 08 May 2015; the South African National Controlled Trials Registry (DOH-27-1015-5185) prospectively registered October 2015.

BACKGROUND: Individual-level simulation models are valuable tools for comparing the impact of clinical or public health interventions on population health and cost outcomes over time. However, a key challenge is ensuring that outcome estimates correctly reflect real-world impacts. Calibration to targets obtained from randomized trials may be insufficient if trials do not exist for populations, time periods, or interventions of interest. Observational data can provide a wider range of calibration targets but requires methods to adjust for treatment-confounder feedback. We propose the use of the parametric g-formula to estimate calibration targets and present a case-study to demonstrate its application.

METHODS: We used the parametric g-formula applied to data from the HIV-CAUSAL Collaboration to estimate calibration targets for 7-y risks of AIDS and/or death (AIDS/death), as defined by the Center for Disease Control and Prevention under 3 treatment initiation strategies. We compared these targets to projections from the Cost-Effectiveness of Preventing AIDS Complications (CEPAC) model for treatment-naïve individuals presenting to care in the following year ranges: 1996 to 1999, 2000 to 2002, or 2003 onwards.

RESULTS: The parametric g-formula estimated a decreased risk of AIDS/death over time and with earlier treatment. The uncalibrated CEPAC model successfully reproduced targets obtained via the g-formula for baseline 1996 to 1999, but over-estimated calibration targets in contemporary populations and failed to reproduce time trends in AIDS/death risk. Calibration to g-formula targets improved CEPAC model fit for contemporary populations.

CONCLUSION: Individual-level simulation models are developed based on best available information about disease processes in one or more populations of interest, but these processes can change over time or between populations. The parametric g-formula provides a method for using observational data to obtain valid calibration targets and enables updating of simulation model inputs when randomized trials are not available.