Performance of empirical and model-based classifiers for detecting sucrase-isomaltase inhibition using the 13 C-sucrose breath test.

Background: Environmental enteric dysfunction (EED) is a syndrome characterized by epithelial damage including blunting of the small intestinal villi and altered digestive and absorptive capacity which may negatively impact linear growth in children. The 13 C-sucrose breath test ( 13 C-SBT) has been proposed to estimate sucrase-isomaltase (SIM) activity, which is thought to be reduced in EED. We previously showed how various summary measures of the 13 C-SBT breath curve reflect SIM inhibition. However, it is uncertain how the performance of these classifiers is affected by test duration. Methods: We leveraged SBT data from a cross-over study in 16 adults who received 0, 100, and 750 mg of Reducose, a natural SIM inhibitor. We evaluated the performance of a pharmacokinetic-model-based classifier, ρ , and three empirical classifiers (cumulative percent dose recovered at 90 minutes (cPDR90), time to 50% dose recovered, and time to peak dose recovery rate), as a function of test duration using receiver operating characteristic curves. We also assessed the sensitivity, specificity, and accuracy of consensus classifiers. Results: Test durations of less than 2 hours generally failed to accurately predict later breath curve dynamics. The cPDR90 classifier had the highest area-under-the-curve and, by design, was robust to shorter test durations. For detecting mild SIM inhibition, ρ had a higher sensitivity. Conclusions: We recommend SBT tests run for at least a 2-hour duration. Although cPDR90 was the classifier with highest accuracy and robustness to test duration in this application, concerns remain about its sensitivity to misspecification of CO 2 production rate. More research is needed to assess these classifiers in target populations.

A Model-Based 13C-Sucrose Breath Test Diagnostic for Gut Function Disorders Characterized by a Loss of Sucrase-Isomaltase Enzymatic Activity.

BACKGROUND: Environmental enteric dysfunction (EED) causes malnutrition in children in low-resource settings. Stable-isotope breath tests have been proposed as noninvasive tests of altered nutrient metabolism and absorption in EED, but uncertainty over interpreting the breath curves has limited their use. The activity of sucrose-isomaltase, the glucosidase enzyme responsible for sucrose hydrolysis, may be reduced in EED. We previously developed a mechanistic model describing the dynamics of the 13C-sucrose breath test (13C-SBT) as a function of underlying metabolic processes. OBJECTIVES: This study aimed to determine which breath test curve dynamics are associated with sucrose hydrolysis and with the transport and metabolism of the fructose and glucose moieties and to propose and evaluate a model-based diagnostic for the loss of activity of sucrase-isomaltase. METHODS: We applied the mechanistic model to 2 sets of exploratory 13C-SBT experiments in healthy adult participants. First, 19 participants received differently labeled sucrose tracers (U-13C fructose, U-13C glucose, and U-13C sucrose) in a crossover study. Second, 16 participants received a sucrose tracer accompanied by 0, 100, and 750 mg of Reducose, a sucrase-isomaltase inhibitor. We evaluated a model-based diagnostic distinguishing between inhibitor concentrations using receiver operator curves, comparing with conventional statistics. RESULTS: Sucrose hydrolysis and the transport and metabolism of the fructose and glucose moieties were reflected in the same mechanistic process. The model distinguishes these processes from the fraction of tracer exhaled and an exponential metabolic process. The model-based diagnostic performed as well as the conventional summary statistics in distinguishing between no and low inhibition [area under the curve (AUC): 0.77 vs. 0.66-0.79] and for low vs. high inhibition (AUC 0.92 vs. 0.91-0.99). CONCLUSIONS: Current summary approaches to interpreting 13C breath test curves may be limited to identifying only gross gut dysfunction. A mechanistic model-based approach improved interpretation of breath test curves characterizing sucrose metabolism.

The biting rate of Aedes aegypti and its variability: A systematic review (1970-2022).

BACKGROUND: Transmission models have a long history in the study of mosquito-borne disease dynamics. The mosquito biting rate (MBR) is an important parameter in these models, however, estimating its value empirically is complex. Modeling studies obtain biting rate values from various types of studies, each of them having its strengths and limitations. Thus, understanding these study designs and the factors that contribute to MBR estimates and their variability is an important step towards standardizing these estimates. We do this for an important arbovirus vector Aedes aegypti. METHODOLOGY/PRINCIPAL FINDINGS: We perform a systematic review using search terms such as 'biting rate' and 'biting frequency' combined with 'Aedes aegypti' ('Ae. aegypti' or 'A. aegypti'). We screened 3,201 articles from PubMed and ProQuest databases, of which 21 met our inclusion criteria. Two broader types of studies are identified: human landing catch (HLC) studies and multiple feeding studies. We analyze the biting rate data provided as well as the methodologies used in these studies to characterize the variability of these estimates across temporal, spatial, and environmental factors and to identify the strengths and limitations of existing methodologies. Based on these analyses, we present two approaches to estimate population mean per mosquito biting rate: one that combines studies estimating the number of bites taken per gonotrophic cycle and the gonotrophic cycle duration, and a second that uses data from histological studies. Based on one histological study dataset, we estimate biting rates of Ae. aegypti (0.41 and 0.35 bite/mosquito-day in Thailand and Puerto Rico, respectively). CONCLUSIONS/SIGNIFICANCE: Our review reinforces the importance of engaging with vector biology when using mosquito biting rate data in transmission modeling studies. For Ae. aegypti, this includes understanding the variation of the gonotrophic cycle duration and the number of bites per gonotrophic cycle, as well as recognizing the potential for spatial and temporal variability. To address these variabilities, we advocate for site-specific data and the development of a standardized approach to estimate the biting rate.

Validity of Self-Reported Mosquito Bites to Assess Household Mosquito Abundance in Six Communities of Esmeraldas Province, Ecuador.

Mosquito-borne diseases are a global burden; however, current methods of evaluating human-mosquito contact rates are expensive and time consuming. Validated surveys of self-reported mosquito bites may be an inexpensive way to determine mosquito presence and bite exposure level in an area, but this remains untested. In this study, a survey of self-reported mosquito bites was validated against household mosquito abundance from six communities in Esmeraldas, Ecuador. From February 2021 to July 2022, households were interviewed monthly, and five questions were used to ask participants how often they were bitten by mosquitoes at different times during the day. At the same time, adult mosquitoes were collected using a Prokopack aspirator. Species were identified and counted. Survey responses were compared with the total number of mosquitoes found in the home using negative binomial regression. More frequent self-reported mosquito bites were significantly associated with higher numbers of collected adult mosquitoes. These associations were driven by the prevalence of the dominant genera, Culex. These results suggest that surveys of perceived mosquito bites relate to actual mosquito presence, making them a potentially useful tool for determining the impact of vector-control interventions on community perceptions of risk but less useful for assessing the risk of nondominant species such as Aedes aegypti. Further work is needed to examine the robustness of these results in other contexts.

Long-term projections of the impacts of warming temperatures on Zika and dengue risk in four Brazilian cities using a temperature-dependent basic reproduction number.

For vector-borne diseases the basic reproduction number [Formula: see text], a measure of a disease's epidemic potential, is highly temperature-dependent. Recent work characterizing these temperature dependencies has highlighted how climate change may impact geographic disease spread. We extend this prior work by examining how newly emerging diseases, like Zika, will be impacted by specific future climate change scenarios in four diverse regions of Brazil, a country that has been profoundly impacted by Zika. We estimated a [Formula: see text], derived from a compartmental transmission model, characterizing Zika (and, for comparison, dengue) transmission potential as a function of temperature-dependent biological parameters specific to Aedes aegypti. We obtained historical temperature data for the five-year period 2015-2019 and projections for 2045-2049 by fitting cubic spline interpolations to data from simulated atmospheric data provided by the CMIP-6 project (specifically, generated by the GFDL-ESM4 model), which provides projections under four Shared Socioeconomic Pathways (SSP). These four SSP scenarios correspond to varying levels of climate change severity. We applied this approach to four Brazilian cities (Manaus, Recife, Rio de Janeiro, and São Paulo) that represent diverse climatic regions. Our model predicts that the [Formula: see text] for Zika peaks at 2.7 around 30°C, while for dengue it peaks at 6.8 around 31°C. We find that the epidemic potential of Zika will increase beyond current levels in Brazil in all of the climate scenarios. For Manaus, we predict that the annual [Formula: see text] range will increase from 2.1-2.5, to 2.3-2.7, for Recife we project an increase from 0.4-1.9 to 0.6-2.3, for Rio de Janeiro from 0-1.9 to 0-2.3, and for São Paulo from 0-0.3 to 0-0.7. As Zika immunity wanes and temperatures increase, there will be increasing epidemic potential and longer transmission seasons, especially in regions where transmission is currently marginal. Surveillance systems should be implemented and sustained for early detection.

Mechanistic inference of the metabolic rates underlying [Formula: see text]C breath test curves.

Carbon stable isotope breath tests offer new opportunities to better understand gastrointestinal function in health and disease. However, it is often not clear how to isolate information about a gastrointestinal or metabolic process of interest from a breath test curve, and it is generally unknown how well summary statistics from empirical curve fitting correlate with underlying biological rates. We developed a framework that can be used to make mechanistic inference about the metabolic rates underlying a 13C breath test curve, and we applied it to a pilot study of 13C-sucrose breath test in 20 healthy adults. Starting from a standard conceptual model of sucrose metabolism, we determined the structural and practical identifiability of the model, using algebra and profile likelihoods, respectively, and we used these results to develop a reduced, identifiable model as a function of a gamma-distributed process; a slower, rate-limiting process; and a scaling term related to the fraction of the substrate that is exhaled as opposed to sequestered or excreted through urine. We demonstrated how the identifiable model parameters impacted curve dynamics and how these parameters correlated with commonly used breath test summary measures. Our work develops a better understanding of how the underlying biological processes impact different aspect of 13C breath test curves, enhancing the clinical and research potential of these 13C breath tests.