Temporal and spatial stability of ammonia-oxidizing archaea and bacteria in aquarium biofilters

Nitrifying biofilters are used in aquaria and aquaculture systems to prevent accumulation of ammonia by promoting rapid conversion to nitrate via nitrite. Ammonia-oxidizing archaea (AOA), as opposed to ammonia-oxidizing bacteria (AOB), were recently identified as the dominant ammonia oxidizers in most freshwater aquaria. This study investigated biofilms from fixed-bed aquarium biofilters to assess the temporal and spatial dynamics of AOA and AOB abundance and diversity. Over a period of four months, ammonia-oxidizing microorganisms from six freshwater and one marine aquarium were investigated at 4-5 time points. Nitrogen balances for three freshwater aquaria showed that active nitrification by aquarium biofilters accounted for >= 81-86% of total nitrogen conversion in the aquaria. Quantitative PCR (qPCR) for bacterial and thaumarchaeal ammonia monooxygenase (amoA) genes demonstrated that AOA were numerically dominant over AOB in all six freshwater aquaria tested, and contributed all detectable amoA genes in three aquarium biofilters. In the marine aquarium, however, AOB outnumbered AOA by three to five orders of magnitude based on amoA gene abundances. A comparison of AOA abundance in three carrier materials (fine sponge, rough sponge and sintered glass or ceramic rings) of two three-media freshwater biofilters revealed preferential growth of AOA on fine sponge. Denaturing gel gradient electrophoresis (DGGE) of thaumarchaeal 16S rRNA genes indicated that community composition within a given biofilter was stable across media types. In addition, DGGE of all aquarium biofilters revealed low AOA diversity, with few bands, which were stable over time. Nonmetric multidimensional scaling (NMDS) based on denaturing gradient gel electrophoresis (DGGE) fingerprints of thaumarchaeal 16S rRNA genes placed freshwater and marine aquaria communities in separate clusters. These results indicate that AOA are the dominant ammonia-oxidizing microorganisms in freshwater aquarium biofilters, and that AOA community composition within a given aquarium is stable over time and across biofilter support material types

Articles Occupancy Modeling of Woodpeckers: Maximizing Detections for Multiple Species with 3 Multiple Spatial Scales 4 5

Abstract 10 Numerous forest birds benefit from woodpecker presence or have similar habitat requirements. 11 Monitoring populations of forest woodpeckers can be useful for management decisions regarding 12 these and other forest species. Usefulness of monitoring efforts depends on methods employed 13 and the quality of resulting parameter estimates. Estimating the proportion of area occupied by a 14 species can be an attractive and affordable alternative to abundance or survival estimates. The 15 purpose of this study was to assess the distribution and area of occupancy for pileated 16 woodpeckers (Drycopus pileatus) and American three-toed woodpeckers (Picoides dorsalis) in 17 north-central Idaho, and to compare occupancy estimates using silent point counts, playback 18 surveys, and playback surveys that incorporated estimates of detection probability (p). We used 19 a hierarchical multi-scale framework that allowed estimation of occupancy at two spatial scales 20 and applied a removal design such that repeat visits to sampling stations was not necessary to 21 estimate p. The initial naïve estimate of occupancy (using presence-absence data) for pileate

Exposure to secondhand smoke, exclusive breastfeeding and infant adiposity at age 5 months in the Healthy Start study

Background: Infant adiposity may be influenced by several environmental risk factors, but few studies have explored these interactions. Objective: To examine the interaction between exposure to secondhand smoke and breastfeeding exclusivity on adiposity at age 5 months. Methods: We studied 813 mother-offspring pairs from the longitudinal Healthy Start study. Fat mass and fat-free mass were measured by air displacement plethysmography. Linear regression analyses were used to estimate the association between household smokers (none, any) with fat mass, fat-free mass, percent fat mass, weight-for-age z-score, weight-for-length z-score and BMI-for-age z-score as separate outcomes. Interaction terms between household smokers and breastfeeding exclusivity (<5 months, ≥5 months) were added to separate models. Results: The combination of exposure to secondhand smoke and a lack of exclusive breastfeeding was associated with increased adiposity at age 5 months. For example, within the not exclusively breastfed strata, exposure to secondhand smoke was associated with increased fat mass (0.1 kg; 95% CI: 0.0–0.2; P = 0.05). Conversely, within the exclusively breastfed strata, there was virtually no difference in fat mass between exposed and non-exposed infants (coefficient: −0.1; 95% CI: −0.3–0.1; P = 0.25). Conclusions: Our findings may inform new public health strategies with potential relevance for both smoking cessation and obesity prevention

Predictors of Infant Body Composition at 5 Months of Age: The Healthy Start Study

Objective To examine associations of demographic, perinatal, and infant feeding characteristics with offspring body composition at approximately 5 months of age. Study design We collected data on 640 mother/offspring pairs from early pregnancy through approximately 5 months of age. We assessed offspring body composition with air displacement plethysmography at birth and approximately 5 months of age. Linear regression analyses examined associations between predictors and fat-free mass, fat mass, and percent fat mass (adiposity) at approximately 5 months. Secondary models further adjusted for body composition at birth and rapid infant growth. Results Greater prepregnant body mass index and gestational weight gain were associated with greater fat-free mass at approximately 5 months of age, but not after adjustment for fat-free mass at birth. Greater gestational weight gain was also associated with greater fat mass at approximately 5 months of age, independent of fat mass at birth and rapid infant growth, although this did not translate into increased adiposity. Greater percent time of exclusive breastfeeding was associated with lower fat-free mass (-311 g; P < .001), greater fat mass (+224 g; P < .001), and greater adiposity (+3.51%; P < .001). Compared with offspring of non-Hispanic white mothers, offspring of Hispanic mothers had greater adiposity (+2.72%; P < .001) and offspring of non-Hispanic black mothers had lower adiposity (-1.93%; P < .001). Greater adiposity at birth predicted greater adiposity at approximately 5 months of age, independent of infant feeding and rapid infant growth. Conclusions There are clear differences in infant body composition by demographic, perinatal, and infant feeding characteristics, although our data also show that increased adiposity at birth persists through approximately 5 months of age. Our findings warrant further research into implications of differences in infant body composition

Exploring the association between maternal prenatal multivitamin use and early infant growth: The Healthy Start Study

Background: Prenatal multivitamin supplementation is recommended to improve offspring outcomes, but effects on early infant growth are unknown. Objectives: We examined whether multivitamin supplementation in the year before delivery predicts offspring mass, body composition and early infant growth. Methods: Multivitamin use was assessed longitudinally in 626 women from the Healthy Start Study. Offspring body size and composition was measured with air displacement plethysmography at birth (<3 days) and postnatally (median 5.2 months). Separate multiple linear regressions assessed the relationship of weeks of daily multivitamin use with offspring mass, body composition and postnatal growth, after adjustment for potential confounders (maternal age, race, pre-pregnant body mass index; offspring gestational age at birth, sex; breastfeeding exclusivity). Results: Maternal multivitamin use was not related to offspring mass or body composition at birth, or rate of change in total or fat-free mass in the first 5 months. Multivitamin use was inversely associated with average monthly growth in offspring percent fat mass (β = −0.009, p = 0.049) between birth and postnatal exam. Offspring of non-users had a monthly increase in percent fat mass of 3.45%, while offspring at the top quartile of multivitamin users had a monthly increase in percent fat mass of 3.06%. This association was not modified by exclusive breastfeeding. Conclusions: Increased multivitamin use in the pre-conception and prenatal periods was associated with a slower rate of growth in offspring percent fat mass in the first 5 months of life. This study provides further evidence that in utero nutrient exposures may affect offspring adiposity beyond birth

Blood pressure during pregnancy, neonatal size and altered body composition: The Healthy Start study

Objective: The objective of this study is to estimate associations between changes in maternal arterial pressure during normotensive pregnancies and offspring birth weight and body composition at birth. Study Design: Prospective study of 762 pregnant normotensive Colorado women, recruited from outpatient obstetrics clinics. Repeated arterial pressure measurements during pregnancy were averaged within the second and third trimesters, respectively. Multivariable regression models estimated associations between second to third trimester changes in arterial pressure and small-for-gestational-age birth weight, fat mass, fat-free mass and percent body fat. Results: A greater second to third trimester increase in maternal arterial pressure was associated with greater odds of small-for-gestational-age birth weight. Greater increases in maternal diastolic blood pressure were associated with reductions in offspring percent body fat (-1.1% in highest vs lowest quartile of increase, 95% confidence interval: -1.9%, -0.3%). Conclusion: Mid-to-late pregnancy increases in maternal arterial pressure, which do not meet clinical thresholds for hypertension are associated with neonatal body size and composition

Proinflammatory Diets during Pregnancy and Neonatal Adiposity in the Healthy Start Study

Objective: To evaluate the association between dietary inflammatory index (DII) scores during pregnancy and neonatal adiposity. Study design: The analysis included 1078 mother–neonate pairs in Healthy Start, a prospective prebirth cohort. Diet was assessed using repeated 24-hour dietary recalls. DII scores were obtained by summing nutrient intakes, which were standardized to global means and multiplied by inflammatory effect scores. Air displacement plethysmography measured fat mass and fat-free mass within 72 hours of birth. Linear and logistic models evaluated the associations of DII scores with birth weight, fat mass, fat-free mass, and percent fat mass, and with categorical outcomes of small- and large-for-gestational age. We tested for interactions with prepregnancy BMI and gestational weight gain. Results: The interaction between prepregnancy BMI and DII was statistically significant for birth weight, neonatal fat mass, and neonatal percent fat mass. Among neonates born to obese women, each 1-unit increase in DII was associated with increased birth weight (53 g; 95% CI, 20, 87), fat mass (20 g; 95% CI, 7-33), and percent fat mass (0.5%; 95% CI, 0.2-0.8). No interaction was detected for small- and large-for-gestational age. Each 1-unit increase in DII score was associated a 40% increase in odds of a large-for-gestational age neonate (1.4; 95% CI, 1.0-2.0; P =.04), but not a small-for-gestational age neonate (1.0; 95% CI, 0.8-1.2; P =.80). There was no evidence of an interaction with gestational weight gain. Conclusions: Our findings support the hypothesis that an increased inflammatory milieu during pregnancy may be a risk factor for neonatal adiposity. Trial registration: Clinicaltrials.gov: NCT02273297

Characterizing the weight-glycemia phenotypes of type 1 diabetes in youth and young adulthood

Introduction Individuals with type 1 diabetes (T1D) present with diverse body weight status and degrees of glycemic control, which may warrant different treatment approaches. We sought to identify subgroups sharing phenotypes based on both weight and glycemia and compare characteristics across subgroups. Research design and methods Participants: with T1D in the SEARCH study cohort (n=1817, 6.0-30.4 years) were seen at a follow-up visit >5 years after diagnosis. Hierarchical agglomerative clustering was used to group participants based on five measures summarizing the joint distribution of body mass index z-score (BMIz) and hemoglobin A1c (HbA1c) which were estimated by reinforcement learning tree predictions from 28 covariates. Interpretation of cluster weight status and glycemic control was based on mean BMIz and HbA1c, respectively. Results: The sample was 49.5% female and 55.5% non-Hispanic white (NHW); mean±SD age=17.6±4.5 years, T1D duration=7.8±1.9 years, BMIz=0.61±0.94, and HbA1c=76±21 mmol/mol (9.1±1.9)%. Six weight-glycemia clusters were identified, including four normal weight, one overweight, and one subgroup with obesity. No cluster had a mean HbA1c <58 mmol/mol (7.5%). Cluster 1 (34.0%) was normal weight with the lowest HbA1c and comprised 85% NHW participants with the highest socioeconomic position, insulin pump use, dietary quality, and physical activity. Subgroups with very poor glycemic control (ie, ≥108 mmol/mol (≥12.0%); cluster 4, 4.4%, and cluster 5, 7.5%) and obesity (cluster 6, 15.4%) had a lower proportion of NHW youth, lower socioeconomic position, and reported decreased pump use and poorer health behaviors (overall p<0.01). The overweight subgroup with very poor glycemic control (cluster 5) showed the highest lipids and blood pressure (p<0.01). Conclusions: There are distinct subgroups of youth and young adults with T1D that share weight-glycemia phenotypes. Subgroups may benefit from tailored interventions addressing differences in clinical care, health behaviors, and underlying health inequity. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ