Smoothing spline assessment of the accuracy of enteric hydrogen and methane production measurements from dairy cattle using various sampling schemes.

Estimating daily enteric hydrogen (H2) and methane (CH4) emitted from dairy cattle using spot sampling techniques requires accurate sampling schemes. These sampling schemes determine the number of daily samplings and their intervals. This simulation study assessed the accuracy of daily H2 and CH4 emissions from dairy cattle using various sampling schemes for gas collection. Gas emission data were available from a crossover experiment with 28 cows fed twice daily at 80% to 95% of the ad libitum intake, and an experiment that used a repeated randomized block design with 16 cows twice daily fed ad libitum. Gases were sampled every 12 to 15 min for 3 consecutive days in climate respiration chambers. Feed was fed in 2 equal portions per day in both experiments. Per individual cow-period combination, generalized additive models were fitted to all diurnal H2 and CH4 emission profiles. Per profile, the models were fitted using the generalized cross-validation, REML, REML while assuming correlated residuals, and REML while assuming heteroscedastic residuals. The areas under the curve (AUC) of these 4 fits were numerically integrated over 24 h to compute the daily production and compared with the mean of all data points, which was considered the reference. Next, the best of the 4 fits was used to evaluate 9 different sampling schemes. This evaluation determined the average predicted values sampled at 0.5, 1, and 2 h intervals starting at 0 h from morning feeding, at 1 and 2 h intervals starting at 0.5 h from morning feeding, at 6 and 8 h intervals starting at 2 h from morning feeding, and at 2 unequally spaced intervals with 2 or 3 samples per day. Sampling every 0.5 h was needed to obtain daily H2 productions not different from the selected AUC for the restricted feeding experiment, whereas less frequent sampling had predictions varying from 47% to 233% of the AUC. For the ad libitum feeding experiment, sampling schemes had H2 productions from 85% to 155% of the corresponding AUC. For the restricted feeding experiment, daily CH4 production needed samplings every 2 h or shorter, or 1 h or shorter, depending on sampling time after feeding, whereas sampling scheme did not affect CH4 production for the twice daily ad libitum feeding experiment. In conclusion, sampling scheme had a major impact on predicted daily H2 production, particularly with restricted feeding, whereas daily CH4 production was less severely affected by sampling scheme.

Hospital sewage treatment facilities witness the fighting against the COVID-19 pandemic.

Real-time evaluation of the fighting activities during a sudden unknown disaster like the COVID-19 pandemic is a critical challenge for control. This study demonstrates that the temporal variations of effluents from hospital sewage treatment facilities can be used as an effective indicator for such evaluation. Taking a typical infection-suffering city in China as an example, we found that there was an obvious decrease in effluent ammonia and COD concentrations in line with the start of city lockdown, and its temporal variations well indicated the major events happened during the pandemic control. Notably, the lagging period between the change point of effluent residual chlorine and the change points of COD and ammonia concentration coincided with a period in which there was a deficiency in local medical resources. In addition, the diurnal behavior of effluents from designated hospitals has varied significantly at different stages of the pandemic development. The effluent ammonia peaks shifted from daytime to nighttime after the outbreak of the COVID-19 pandemic, suggesting a high workload of the designated hospitals in fighting the rapidly emerging pandemic. This work well demonstrates the necessary for data integration at the wastewater-medical service nexus and highlights an unusual role of the effluents from hospital sewage treatment facilities in revealing the status of fighting the pandemic, which helps to control the pandemic.

Near-road Vehicle Emissions Air Quality Monitoring for Exposure Modeling.

Exposure to vehicular emissions has been linked to numerous adverse health effects. In response to the arising concerns, near-road monitoring is conducted to better characterize the impact of mobile source emissions on air quality and exposure in the near-road environment. An intensive measurement campaign measured traffic-related air pollutants (TRAPs) and related data (e.g., meteorology, traffic, regional air pollutant levels) in Atlanta, along one of the busiest highway corridors in the US. Given the complexity of the near-road environment, the study aimed to compare two near-road monitors, located in close proximity to each other, to assess how observed similarities and differences between measurements at these two sites inform the siting of other near-road monitoring stations. TRAP measurements, including carbon monoxide (CO) and nitrogen dioxide (NO2), are analyzed at two roadside monitors in Atlanta, GA located within 325m of each other. Both meteorological and traffic conditions were monitored to assess the temporal impact of these factors on traffic-related pollutant concentrations. The meteorological factors drove the diurnal variability of primary pollutant concentration more than traffic count. In spite of their proximity, while the CO and NO2 concentrations were correlated with similar diurnal variations, pollutant concentrations at the two closely sited monitors differed, likely due to the differences in the siting characteristics reducing the dispersion of the primary emissions out of the near-road environment. Overall, the near-road TRAP concentrations at all sites were not as elevated as seen in prior studies, supporting that decreased vehicle emissions have led to significant reductions in TRAP levels, even along major interstates. Further, the differences in the observed levels show that use of single near-road observations will not capture pollutant levels representative of the local near-road environment and that additional approaches (e.g., air quality models) are needed to characterize exposures.

Circadian variation of salivary immunoglobin A, alpha-amylase activity and mood in response to repeated double-poling sprints in hypoxia.

PURPOSE: To assess the circadian variations in salivary immunoglobin A (sIgA) and alpha-amylase activity (sAA), biomarkers of mucosal immune function, together with mood during 2 weeks of repeated sprint training in hypoxia (RSH) and normoxia (RSN). METHODS: Over a 2-week period, 17 competitive cross-country skiers performed six training sessions, each consisting of four sets of five 10-s bouts of all-out double-poling under either normobaric hypoxia (FiO2: 13.8%, 3000 m) or normoxia. The levels of sIgA and sAA activity and mood were determined five times during each of the first (T1) and sixth (T6) days of training, as well as during days preceding (baseline) and after the training intervention (follow-up). RESULTS: With RSH, sIgA was higher on T6 than T1 (P = 0.049), and sAA was increased on days T1, T6, and during the follow-up (P < 0.01). With RSN, sIgA remained unchanged and sAA was elevated on day T1 only (P = 0.04). Similarly, the RSH group demonstrated reduced mood on days T1, T6, and during the follow-up, while mood was lowered only on T1 with RSN (P < 0.01). CONCLUSIONS: The circadian variation of sIgA and sAA activity, biomarkers of mucosal immune function, as well as mood were similar on the first day of training when repeated double-poling sprints were performed with or without hypoxia. Only with RSH did the levels of sIgA and sAA activity rise with time, becoming maximal after six training sessions, when mood was still lowered. Therefore, six sessions of RSH reduced mood, but did not impair mucosal immune function.

The Mucosal Immune Function Is Not Compromised during a Period of High-Intensity Interval Training. Is It Time to Reconsider an Old Assumption?

Purpose: The aim of the study was to evaluate the mucosal immune function and circadian variation of salivary cortisol, Immunoglobin-A (sIgA) secretion rate and mood during a period of high-intensity interval training (HIIT) compared to long-slow distance training (LSD). Methods: Recreational male runners (n = 28) completed nine sessions of either HIIT or LSD within 3 weeks. The HIIT involved 4 × 4 min of running at 90-95% of maximum heart rate interspersed with 3 min of active recovery while the LSD comprised of continuous running at 70-75% of maximum heart rate for 60-80 min. The psycho-immunological stress-response was investigated with a full daily profile of salivary cortisol and immunoglobin-A (sIgA) secretion rate along with the mood state on a baseline day, the first and last day of training and at follow-up 4 days after the last day of training. Before and after the training period, each athlete's running performance and peak oxygen uptake (V·O2peak) was determined with an incremental exercise test. Results: The HIIT resulted in a longer time-to-exhaustion (P = 0.02) and increased V·O2peak compared to LSD (P = 0.01). The circadian variation of sIgA secretion rate showed highest values in the morning immediately after waking up followed by a decrease throughout the day in both groups (P < 0.05). With HIIT, the wake-up response of sIgA secretion rate was higher on the last day of training (P < 0.01) as well as the area under the curve (AUCG) higher on the first and last day of training and follow-up compared to the LSD (P = 0.01). Also the AUCG for the sIgA secretion rate correlated with the increase in V·O2peak and running performance. The AUCG for cortisol remained unaffected on the first and last day of training but increased on the follow-up day with both, HIIT and LSD (P < 0.01). Conclusion: The increased sIgA secretion rate with the HIIT indicates no compromised mucosal immune function compared to LSD and shows the functional adaptation of the mucosal immune system in response to the increased stress and training load of nine sessions of HIIT.