An Examination of Demographic Associations Predicting Success in the Children\u27s Healthcare of Atlanta\u27s Strong4Life Program

BACKGROUND: The purpose of this study was to explore demographic associations and their predictive value of effective weight maintenance among participants in the Children\u27s Healthcare of Atlanta [CHOA] Strong4Life program for children and youth ages 2 to 20. METHODS: Analyses are based on the Strong4Life clinic data collected by Strong4Life from 2010 through 2014. Participants of the program fell into the 85th percentile and above for Body Mass Index (BMI). Descriptive tests, comparison of means, and logistic regression analyses were run to determine if patterns in the data examining demographic characteristics of the sample and their relationship to successful weight management were statistically significant. RESULTS: Logistic regression findings indicate that ethnicity (OR=2.737, CI: 1.273-5.892) p =0.01 is a predictor of successful weight management (n=324). Stong4Life defined program success as a decrease in BMI z-score of 0.04. While gender, race, baseline weight, asthma and pre-diabetes status were examined; statistical tests did not detect significant variations among the participants. Overall, the Strong4Life program is successful as seen by the p value\u3c 0.001. CONCLUSIONS: Findings from this study are important for childhood obesity programs because tailoring strategies that align with unique segments of the population maximize their potential reach. Obesity research is required to advance intervention development that is sensitive to patterns and distinctions that exist among subpopulations. These findings are important for prevention of childhood obesity efforts and promotion of multidisciplinary approaches to combat obesity world-wide

Educator Recruitment and Retention in Maine

The goal of this study was to generally replicate the study that was conducted in 2001 to describe and understand the declining teacher and administrator workforce in Maine and to consider policy implications and options

Response to Intervention and Multi-Tiered Systems of Support in Maine Schools: Portraits of Promising Practices

In 2020, the Maine Legislature commissioned this follow-up study to more deeply examine promising practices of Response to Intervention / multi-tiered system of supports behavior programs in Maine Schools

Late childhood interpersonal callousness and conduct problem trajectories interact to predict adult psychopathy

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135659/1/jcpp12598_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135659/2/jcpp12598.pd

Using anthropometric and performance characteristics to predict selection in junior UK Rugby League players.

Research examining the factors influencing selection within talented junior Rugby League players is limited. The aims of this study were firstly to determine whether differences existed for anthropometric and performance characteristics between regional and national selection in high performance UK junior Rugby League players, and secondly to identify variables that discriminated between these selection levels. Regional representative (n=1172) selected junior players (aged 13-16 years) undertook an anthropometric and fitness testing battery with players split according to selection level (i.e., national, regional). MANCOVA analyses, with age and maturation controlled, identified national players as having lower sum of 4 skinfolds scores compared to regional players, and also performed significantly better on all physical tests. Stepwise discriminant analysis identified that estimated maximum oxygen uptake (VO2max), chronological age, body mass, 20 m sprint, height, sum of 4 skinfolds and sitting height discriminated between selection levels, accounting for 28.7% of the variance. This discriminant analysis corresponded to an overall predictive accuracy of 63.3% for all players. These results indicate that performance characteristics differed between selection levels in junior Rugby League players. However, the small magnitude of difference between selection levels suggests that physical qualities only partially explain higher representative selection. The monitoring and evaluation of such variables, alongside game related performance characteristics, provides greater knowledge and understanding about the processes and consequences of selection, training and performance in youth sport

Neural response to monetary loss among youth with disruptive behavior disorders and callous-unemotional traits in the ABCD study

Etiological models highlight reduced punishment sensitivity as a core risk factor for disruptive behavior disorders (DBD) and callous-unemotional (CU) traits. The current study examined neural sensitivity to the anticipation and receipt of loss, one key aspect of punishment sensitivity, among youth with DBD, comparing those with and without CU traits. Data were obtained from the Adolescent Brain and Cognitive Development (ABCD)SM Study (N = 11,874; Mage = 9.51; 48% female). Loss-related fMRI activity during the monetary incentive delay task was examined across 16 empirically-derived a priori brain regions (e.g., striatum, amygdala, insula, anterior cingulate cortex, medial prefrontal cortex) and compared across the following groups: (1) typically developing (n = 693); (2) DBD (n = 995), subdivided into those (3) with CU traits (DBD + CU, n = 198), and (4) without CU traits (DBD-only, n = 276). Latent variable modeling was also employed to examine network-level activity. There were no significant between-group differences in brain activity to loss anticipation or receipt. Null findings were confirmed with and without covariates, using alternative grouping approaches, and in dimensional models. Network-level analyses also demonstrated comparable activity across groups during loss anticipation and receipt. Findings suggest that differences in punishment sensitivity among youth with DBD are unrelated to loss anticipation or receipt. More precise characterizations of other aspects punishment sensitivity are needed to understand risk for DBD and CU traits

Pan-viral serology implicates enteroviruses in acute flaccid myelitis.

Since 2012, the United States of America has experienced a biennial spike in pediatric acute flaccid myelitis (AFM)1-6. Epidemiologic evidence suggests non-polio enteroviruses (EVs) are a potential etiology, yet EV RNA is rarely detected in cerebrospinal fluid (CSF)2. CSF from children with AFM (n = 42) and other pediatric neurologic disease controls (n = 58) were investigated for intrathecal antiviral antibodies, using a phage display library expressing 481,966 overlapping peptides derived from all known vertebrate and arboviruses (VirScan). Metagenomic next-generation sequencing (mNGS) of AFM CSF RNA (n = 20 cases) was also performed, both unbiased sequencing and with targeted enrichment for EVs. Using VirScan, the viral family significantly enriched by the CSF of AFM cases relative to controls was Picornaviridae, with the most enriched Picornaviridae peptides belonging to the genus Enterovirus (n = 29/42 cases versus 4/58 controls). EV VP1 ELISA confirmed this finding (n = 22/26 cases versus 7/50 controls). mNGS did not detect additional EV RNA. Despite rare detection of EV RNA, pan-viral serology frequently identified high levels of CSF EV-specific antibodies in AFM compared with controls, providing further evidence for a causal role of non-polio EVs in AFM

Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives