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In the United States, humans spend the majority of their time indoors, where they are exposed to the microbiome of the built environment (BE) they inhabit. Despite the ubiquity of microbes in BEs and their potential impacts on health and building materials, basic questions about the microbiology of these environments remain unanswered. We present a study on the impacts of geography, material type, human interaction, location in a room, seasonal variation, and indoor and microenvironmental parameters on bacterial communities in offices. Our data elucidate several important features of microbial communities in BEs. First, under normal office environmental conditions, bacterial communities do not differ on the basis of surface material (e.g., ceiling tile or carpet) but do differ on the basis of the location in a room (e.g., ceiling or floor), two features that are often conflated but that we are able to separate here. We suspect that previous work showing differences in bacterial composition with surface material was likely detecting differences based on different usage patterns. Next, we find that offices have city-specific bacterial communities, such that we can accurately predict which city an office microbiome sample is derived from, but office-specific bacterial communities are less apparent. This differs from previous work, which has suggested office-specific compositions of bacterial communities. We again suspect that the difference from prior work arises from different usage patterns. As has been previously shown, we observe that human skin contributes heavily to the composition of BE surfaces. IMPORTANCE Our study highlights several points that should impact the design of future studies of the microbiology of BEs. First, projects tracking changes in BE bacterial communities should focus sampling efforts on surveying different locations in offices and in different cities but not necessarily different materials or different offices in the same city. Next, disturbance due to repeated sampling, though detectable, is small compared to that due to other variables, opening up a range of longitudinal study designs in the BE. Next, studies requiring more samples than can be sequenced on a single sequencing run (which is increasingly common) must control for run effects by including some of the same samples in all of the sequencing runs as technical replicates. Finally, detailed tracking of indoor and material environment covariates is likely not essential for BE microbiome studies, as the normal range of indoor environmental conditions is likely not large enough to impact bacterial communities.

Summary: Background: Research has shown children disproportionately gain excess weight over the summer months (vs. school months), with stronger effects for children with obesity. However, the question has not been investigated among children receiving care in paediatric weight management (PWM) programs. Objective: To test for seasonal variability in weight change among youth with obesity in PWM care enrolled in the Pediatric Obesity Weight Evaluation Registry (POWER). Method: Longitudinal evaluation of a prospective cohort from 2014 to 2019 among youth in 31 PWM programs. Change in percentage of the 95th percentile for BMI (%BMIp95) was compared by quarter. Results: Participants (N = 6816) were primarily ages 6–11 (48%), female (54%), 40% non‐Hispanic White, 26% Hispanic and 17% Black, and 73% had severe obesity. Children were enrolled on average 424.9 ± 401.5 days. Participants reduced their %BMIp95 every season, but compared with Quarter 3 (July–September), reductions were significantly greater in Q1 (Jan‐March, b = −0.27, 95%CI −0.46, −0.09), Q2 (April–June, b = −0.21, CI −0.40, −0.03), and Q4 (October–December, b = −0.44, CI −0.63, −0.26). Conclusion and Relevance: Across 31 clinics nationwide, children reduced their %BMIp95 every season, but reductions were significantly smaller during the summer quarter. While PWM successfully mitigated excess weight gain during every period, summer remains a high‐priority time. [ABSTRACT FROM AUTHOR]

Deserts are considered 'below-ground dominated', yet little is known about the impact of rising CO2 in combination with natural weather cycles on long-term dynamics of root biomass. This study quantifies the temporal dynamics of fine-root production, loss and standing crop in an intact desert ecosystem exposed to 10 yr of elevated CO2., We used monthly minirhizotron observations from 4 yr (2003-2007) for two dominant shrub species and along community transects at the Nevada Desert free-air CO2 enrichment Facility. Data were synthesized within a Bayesian framework that included effects of CO2 concentration, cover type, phenological period, antecedent soil water and biological inertia (i.e. the influence of prior root production and loss)., Elevated CO2 treatment interacted with antecedent soil moisture and had significantly greater effects on fine-root dynamics during certain phenological periods. With respect to biological inertia, plants under elevated CO2 tended to initiate fine-root growth sooner and sustain growth longer, with the net effect of increasing the magnitude of production and mortality cycles., Elevated CO2 interacts with past environmental (e.g. antecedent soil water) and biological (e.g. biological inertia) factors to affect fine-root dynamics, and such interactions are expected to be important for predicting future soil carbon pools. [ABSTRACT FROM AUTHOR]

Deserts are considered 'below-ground dominated', yet little is known about the impact of rising CO(2) in combination with natural weather cycles on long-term dynamics of root biomass. This study quantifies the temporal dynamics of fine-root production, loss and standing crop in an intact desert ecosystem exposed to 10 yr of elevated CO(2). We used monthly minirhizotron observations from 4 yr (2003-2007) for two dominant shrub species and along community transects at the Nevada Desert free-air CO(2) enrichment Facility. Data were synthesized within a Bayesian framework that included effects of CO(2) concentration, cover type, phenological period, antecedent soil water and biological inertia (i.e. the influence of prior root production and loss). Elevated CO(2) treatment interacted with antecedent soil moisture and had significantly greater effects on fine-root dynamics during certain phenological periods. With respect to biological inertia, plants under elevated CO(2) tended to initiate fine-root growth sooner and sustain growth longer, with the net effect of increasing the magnitude of production and mortality cycles. Elevated CO(2) interacts with past environmental (e.g. antecedent soil water) and biological (e.g. biological inertia) factors to affect fine-root dynamics, and such interactions are expected to be important for predicting future soil carbon pools., (© 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.)