Estimating biotic integrity to capture existence value of freshwater ecosystems.

The US Environmental Protection Agency (EPA) uses a water quality index (WQI) to estimate benefits of proposed Clean Water Act regulations. The WQI is relevant to human use value, such as recreation, but may not fully capture aspects of nonuse value, such as existence value. Here, we identify an index of biological integrity to supplement the WQI in a forthcoming national stated preference survey that seeks to capture existence value of streams and lakes more accurately within the conterminous United States (CONUS). We used literature and focus group research to evaluate aquatic indices regularly reported by the EPA's National Aquatic Resource Surveys. We chose an index that quantifies loss in biodiversity as the observed-to-expected (O/E) ratio of taxonomic composition because focus group participants easily understood its meaning and the environmental changes that would result in incremental improvements. However, available datasets of this index do not provide the spatial coverage to account for how conditions near survey respondents affect their willingness to pay for its improvement. Therefore, we modeled and interpolated the values of this index from sampled sites to 1.1 million stream segments and 297,071 lakes across the CONUS to provide the required coverage. The models explained 13 to 36% of the variation in O/E scores and demonstrate how modeling can provide data at the required density for benefits estimation. We close by discussing future work to improve performance of the models and to link biological condition with water quality and habitat models that will allow us to forecast changes resulting from regulatory options.

Pathogen Detection Using Metagenomic Next-Generation Sequencing of Plasma Samples from Patients with Sepsis in Uganda.

Metagenomic sequencing is a promising new method for pathogen detection. We aimed to detect pathogens from archived plasma using metagenomic sequencing in a previously well-characterized cohort of 254 predominantly HIV-infected patients with sepsis in Uganda. We used Illumina sequencing and the Chan Zuckerberg ID metagenomics platform to sequence and identify pathogens. On average, each plasma sample yielded 3,404,737 ± 2,201,997 reads (mean ± standard deviation), of which 220,032 ± 416,691 (6.3% ± 8.6%) were identified as nonhuman reads. Using a background model filter, 414 genus-specific pathogen identifications were found in the 254 samples. Nineteen pathogens were previously detected positive by quantitative PCR (qPCR), compared to sequencing, which demonstrated 30.2% sensitivity and 99.5% specificity. Sensitivity was higher for viral pathogens than nonviral pathogens (37% versus 5%). For example, HIV viremia was detected in 69% of samples using qPCR, and sequencing revealed 70% sensitivity and 92% specificity. There were 75 genus-specific potential pathogens identified by sequencing in this cohort, including hepatitis B and Epstein-Barr virus (EBV), among several others. qPCR showed a prevalence of hepatitis B and EBV viremia of 17% and 45%, respectively. In-hospital mortality was associated with a lower qPCR threshold cycle value for EBV (adjusted odds ratio, 0.85; P < .001) but not for hepatitis B or HIV. In conclusion, a broad range of potential pathogens were identified by metagenomic sequencing in patients with sepsis in Uganda. Unexpectedly high rates of hepatitis B and EBV viremia were found. Whether these viral infections in HIV patients with sepsis are clinically important requires further study. IMPORTANCE The use of next-generation sequencing (NGS) in blood samples is an emerging technology for clinical microbiology labs. In this work, we performed NGS on plasma samples from a well-characterized cohort, where all samples had been previously tested by PCR for 43 pathogens. Therefore, we could compare sequencing performance against that of PCR and identify clinical correlates. A broad range of potential pathogens were identified by metagenomic sequencing in patients with sepsis in Uganda, particularly viruses, which we confirmed by PCR. In addition to HIV viremia, unexpectedly high rates of hepatitis B and EBV viremia were found, which may have important clinical implications.

Cadence-based Classification of Minimally Moderate Intensity During Overground Walking in 21- to 40-Year-Old Adults.

BACKGROUND: A walking cadence of ≥100 steps/min corresponds to minimally moderate intensity, absolutely defined as ≥3 metabolic equivalents (METs). This threshold has primarily been calibrated during treadmill walking. There is a need to determine the classification accuracy of this cadence threshold to predict intensity during overground walking. METHODS: In this laboratory-based cross-sectional investigation, participants (N = 75, 49.3% women, age 21-40 y) performed a single 5-minute overground (hallway) walking trial at a self-selected preferred pace. Steps accumulated during each trial were hand tallied and converted to cadence (steps/min). Oxygen uptake was measured using indirect calorimetry and converted to METs. The classification accuracy (sensitivity, specificity, overall accuracy, and positive predictive value) of ≥100 steps/min to predict ≥3 METs was calculated. RESULTS: A cadence threshold of ≥100 steps/min yielded an overall accuracy (combined sensitivity and specificity) of 73.3% for predicting minimally moderate intensity. Moreover, for individuals walking at a cadence ≥100 steps/min, the probability (positive predictive value) of achieving minimally moderate intensity was 80.3%. CONCLUSIONS: Although primarily developed using treadmill-based protocols, a cadence threshold of ≥100 steps/min for young adults appears to be a valid heuristic value (evidence-based, rounded, practical) associated with minimally moderate intensity during overground walking performed at a self-selected preferred pace.