Humans are able to modulate digit forces as a function of position despite changes in digit placement that might occur from trial to trial or when changing grip type for object manipulation. Although this phenomenon is likely to rely on sensing the position of the digits relative to each other and the object, the underlying mechanisms remain unclear. To address this question, we asked subjects (n = 30) to match perceived vertical distance between the center of pressure (CoP) of the thumb and index finger pads (d_y) of the right hand (“reference” hand) using the same hand (“test” hand). The digits of reference hand were passively placed collinearly (d_y = 0 mm). Subjects were then asked to exert different combinations of normal and tangential digit forces (F_n and F_tan, respectively) using the reference hand and then match the memorized d_y using the test hand. The reference hand exerted F_tan of thumb and index finger in either same or opposite direction. We hypothesized that, when the tangential forces of the digits are produced in opposite directions, matching error (1) would be biased toward the directions of the tangential forces; and (2) would be greater when the remembered relative contact points are matched with negligible digit force production. For the test hand, digit forces were either negligible (0.5–1 N, 0 ± 0.25 N; Experiment 1) or the same as those exerted by the reference hand (Experiment 2).Matching error was biased towards the direction of digit tangential forces: thumb CoP was placed higher than the index finger CoP when thumb and index finger F_tan were directed upward and downward, respectively, and vice versa (p < 0.001). However, matching error was not dependent on whether the reference and test hand exerted similar or different forces. We propose that the expected sensory consequence of motor commands for tangential forces in opposite directions overrides estimation of fingertip position through haptic sensory feedback.

National and state organizations have developed policies calling upon afterschool programs (ASPs, 3–6 pm) to serve a fruit or vegetable (FV) each day for snack, while eliminating foods and beverages high in added-sugars, and to ensure children accumulate a minimum of 30 min/d of moderate-to-vigorous physical activity (MVPA). Few efficacious and cost-effective strategies exist to assist ASP providers in achieving these important public health goals. This paper reports on the design and conceptual framework of Making Healthy Eating and Physical Activity (HEPA) Policy Practice in ASPs, a 3-year group randomized controlled trial testing the effectiveness of strategies designed to improve snacks served and increase MVPA in children attending community-based ASPs. Twenty ASPs, serving over 1800 children (6–12 years) will be enrolled and match-paired based on enrollment size, average daily min/d MVPA, and days/week FV served, with ASPs randomized after baseline data collection to immediate intervention or a 1-year delayed group. The framework employed, STEPs (Strategies To Enhance Practice), focuses on intentional programming of HEPA in each ASPs' daily schedule, and includes a grocery store partnership to reduce price barriers to purchasing FV, professional development training to promote physical activity to develop core physical activity competencies, as well as ongoing technical support/assistance. Primary outcome measures include children's accelerometry-derived MVPA and time spend sedentary while attending an ASP, direct observation of staff HEPA promoting and inhibiting behaviors, types of snacks served, and child consumption of snacks, as well as, cost of snacks via receipts and detailed accounting of intervention delivery costs to estimate cost-effectiveness.

Background: Time series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide an opportunity to compare different time series models for predictive power.

Results: We applied ARIMA and Random Forest time series models to incidence data of outbreaks of highly pathogenic avian influenza (H5N1) in Egypt, available through the online EMPRES-I system. We found that the Random Forest model outperformed the ARIMA model in predictive ability. Furthermore, we found that the Random Forest model is effective for predicting outbreaks of H5N1 in Egypt.

Conclusions: Random Forest time series modeling provides enhanced predictive ability over existing time series models for the prediction of infectious disease outbreaks. This result, along with those showing the concordance between bird and human outbreaks (Rabinowitz et al. 2012), provides a new approach to predicting these dangerous outbreaks in bird populations based on existing, freely available data. Our analysis uncovers the time-series structure of outbreak severity for highly pathogenic avian influenza (H5N1) in Egypt.

Background: Many studies used the older ActiGraph (7164) for physical activity measurement, but this model has been replaced with newer ones (e.g., GT3X+). The assumption that new generation models are more accurate has been questioned, especially for measuring lower intensity levels. The low-frequency extension (LFE) increases the low-intensity sensitivity of newer models, but its comparability with older models is unknown. This study compared step counts and physical activity collected with the 7164 and GT3X + using the Normal Filter and the LFE (GT3X+N and GT3X+LFE, respectively).

Findings: Twenty-five adults wore 2 accelerometer models simultaneously for 3Âdays and were instructed to engage in typical behaviors. Average daily step counts and minutes per day in nonwear, sedentary, light, moderate, and vigorous activity were calculated. Repeated measures ANOVAs with post-hoc pairwise comparisons were used to compare mean values. Means for the GT3X+N and 7164 were significantly different in 4 of the 6 categories (p < .05). The GT3X+N showed 2041 fewer steps per day and more sedentary, less light, and less moderate than the 7164 (+25.6, -31.2, -2.9 mins/day, respectively). The GT3X+LFE showed non-significant differences in 5 of 6 categories but recorded significantly more steps (+3597 steps/day; p < .001) than the 7164.

Conclusion: Studies using the newer ActiGraphs should employ the LFE for greater sensitivity to lower intensity activity and more comparable activity results with studies using the older models. Newer generation ActiGraphs do not produce comparable step counts to the older generation devices with the Normal filter or the LFE.

Background: The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods.

Methods: Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step.

Results: The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with APOE and GAB2 SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included APOE and GAB2 SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling.

Conclusions: With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.

Background: Little research has explored who responds better to an automated vs. human advisor for health behaviors in general, and for physical activity (PA) promotion in particular. The purpose of this study was to explore baseline factors (i.e., demographics, motivation, interpersonal style, and external resources) that moderate intervention efficacy delivered by either a human or automated advisor.

Methods: Data were from the CHAT Trial, a 12-month randomized controlled trial to increase PA among underactive older adults (full trial N = 218) via a human advisor or automated interactive voice response advisor. Trial results indicated significant increases in PA in both interventions by 12 months that were maintained at 18-months. Regression was used to explore moderation of the two interventions.

Results: Results indicated amotivation (i.e., lack of intent in PA) moderated 12-month PA (d = 0.55, p < 0.01) and private self-consciousness (i.e., tendency to attune to one’s own inner thoughts and emotions) moderated 18-month PA (d = 0.34, p < 0.05) but a variety of other factors (e.g., demographics) did not (p > 0.12).

Conclusions: Results provide preliminary evidence for generating hypotheses about pathways for supporting later clinical decision-making with regard to the use of either human- vs. computer-delivered interventions for PA promotion.

Background: Glioblastoma is the most aggressive primary central nervous tumor and carries a very poor prognosis. Invasion precludes effective treatment and virtually assures tumor recurrence. In the current study, we applied analytical and bioinformatics approaches to identify a set of microRNAs (miRs) from several different human glioblastoma cell lines that exhibit significant differential expression between migratory (edge) and migration-restricted (core) cell populations. The hypothesis of the study is that differential expression of miRs provides an epigenetic mechanism to drive cell migration and invasion.

Results: Our research data comprise gene expression values for a set of 805 human miRs collected from matched pairs of migratory and migration-restricted cell populations from seven different glioblastoma cell lines. We identified 62 down-regulated and 2 up-regulated miRs that exhibit significant differential expression in the migratory (edge) cell population compared to matched migration-restricted (core) cells. We then conducted target prediction and pathway enrichment analysis with these miRs to investigate potential associated gene and pathway targets. Several miRs in the list appear to directly target apoptosis related genes. The analysis identifies a set of genes that are predicted by 3 different algorithms, further emphasizing the potential validity of these miRs to promote glioblastoma.

Conclusions: The results of this study identify a set of miRs with potential for decreased expression in invasive glioblastoma cells. The verification of these miRs and their associated targeted proteins provides new insights for further investigation into therapeutic interventions. The methodological approaches employed here could be applied to the study of other diseases to provide biomedical researchers and clinicians with increased opportunities for therapeutic interventions.

Background: Peanut consumption favorably influences satiety. This study examined the acute effect of peanut versus grain bar preloads on postmeal satiety and glycemia in healthy adults and the long-term effect of these meal preloads on body mass in healthy overweight adults.

Methods: In the acute crossover trial (n = 15; 28.4 ± 2.9 y; 23.1 ± 0.9 kg/m²), the preload (isoenergetic peanut or grain bar with water, or water alone) was followed after 60 min with ingestion of a standardized glycemic test meal. Satiety and blood glucose were assessed immediately prior to the preload and to the test meal, and for two hours postmeal at 30-min intervals. In the parallel-arm, randomized trial (n = 44; 40.5 ± 1.6 y, 31.8 ± 0.9 kg/m²), the peanut or grain bar preload was consumed one hour prior to the evening meal for eight weeks. Body mass was measured at 2-week intervals, and secondary endpoints included blood hemoglobin A1c and energy intake as assessed by 3-d diet records collected at pre-trial and trial weeks 1 and 8.

Results: Satiety was elevated in the postprandial period following grain bar ingestion in comparison to peanut or water ingestion (p = 0.001, repeated-measures ANOVA). Blood glucose was elevated one hour after ingestion of the grain bar as compared to the peanut or water treatments; yet, total glycemia did not vary between treatments in the two hour postprandial period. In the 8-week trial, body mass was reduced for the grain bar versus peanut groups after eight weeks (−1.3 ± 0.4 kg versus −0.2 ± 0.3 kg, p = 0.033, analysis of covariance). Energy intake was reduced by 458 kcal/d in the first week of the trial for the grain bar group as compared to the peanut group (p = 0.118). Hemoglobin A1c changed significantly between groups during the trial (−0.25 ± 0.07% and −0.18 ± 0.12% for the grain bar and peanut groups respectively, p = 0.001).

Conclusions: Compared to an isoenergetic peanut preload, consumption of a grain bar preload one hour prior to a standardized meal significantly raised postmeal satiety. Moreover, consumption of the grain bar prior to the evening meal was associated with significant weight loss over time suggesting that glycemic carbohydrate ingestion prior to meals may be a weight management strategy.

Background: Health information exchange (HIE) is an important tool for improving efficiency and quality and is required for providers to meet Meaningful Use certification from the United States Centers for Medicare and Medicaid Services. However widespread adoption and use of HIE has been difficult to achieve, especially in settings such as smaller-sized physician practices and federally qualified health centers (FQHCs). We assess electronic data exchange activities and identify barriers and benefits to HIE participation in two underserved settings.

Methods: We conducted key-informant interviews with stakeholders at physician practices and health centers. Interviews were recorded, transcribed, and then coded in two waves: first using an open-coding approach and second using selective coding to identify themes that emerged across interviews, including barriers and facilitators to HIE adoption and use.

Results: We interviewed 24 providers, administrators and office staff from 16 locations in two states. They identified barriers to HIE use at three levels—regional (e.g., lack of area-level exchanges; partner organizations), inter-organizational (e.g., strong relationships with exchange partners; achieving a critical mass of users), and intra-organizational (e.g., type of electronic medical record used; integration into organization’s workflow). A major perceived benefit of HIE use was the improved care-coordination clinicians could provide to patients as a direct result of the HIE information. Utilization and perceived benefit of the exchange systems differed based on several practice- and clinic-level factors.

Conclusions: The adoption and use of HIE in underserved settings appears to be impeded by regional, inter-organizational, and intra-organizational factors and facilitated by perceived benefits largely at the intra-organizational level. Stakeholders should consider factors both internal and external to their organization, focusing efforts in changing modifiable factors and tailoring HIE efforts based on all three categories of factors. Collective action between organizations may be needed to address inter-organizational and regional barriers. In the interest of facilitating HIE adoption and use, the impact of interventions at various levels on improving the use of electronic health data exchange should be tested.

Background: To examine the influence of ethnicity on liver transaminases among adolescents with type 2 diabetes mellitus (T2DM).

Methods: A retrospective medical chart review of 57 (30 males and 27 females) newly diagnosed patients with T2DM. Ethnicity was determined by self-report and height, weight, body mass index (BMI) and glycosylated hemoglobin (HbA1c) were obtained using standard clinical procedures. Fasting levels of alanine aminotransaminase (ALT) and aspartate aminotransferase (AST) were collected prior to the initiation of any therapy.

Results: Age, gender, height, weight, BMI, and HbA1c did not differ between ethnic groups. Compared to African-Americans, Hispanics had significantly higher ALT (23.9 ± 3.4 vs. 107.8 ± 20.3, p=0.002) and AST (17.7 ± 2.5 vs. 71.1 ± 15.7, p<0.001) and were significantly more likely to have ALT values above the upper limit of normal (20% vs. 71%, p=0.005) and twice the upper limit of normal (0% vs. 39%, p=0.05) as well as AST values above the upper limit of normal (0% vs. 53%, p=0.002). No differences in ALT or AST were found between Hispanics and non-Hispanic whites or between African-Americans and non-Hispanic whites.

Conclusions: These preliminary findings suggest that Hispanic children with T2DM may be at higher risk for developing non-alcoholic fatty liver disease and indicate that a comprehensive hepatic evaluation is warranted in this population. Future studies that incorporate more precise and proximal measures of liver health are warranted in this population.