White coat color of a Black Angus calf attributed to an occurrence of the delR217 variant of \u3ci\u3eMITF\u3c/i\u3e

A white calf, with minimal pigmented markings, was born to two registered Black Angus parents. Given the possibility of an unknown recessive or de novo dominant mutation, whole-genome sequencing was conducted on the trio of individuals. A 3-bp in-frame deletion in MITF was identified; this mutation was unique to the calf but identical to the delR217 variant reported in both humans and murine models of Waardenburg syndrome type 2A and Tietz syndrome. Given the coat color phenotype and identity of the mutation, our data support that this calf represents the first instance of this recurring MITF mutation in cattle

Effect of Nitrogen Application Timing on Corn Production Using Subsurface Drip Irrigation

The use of subsurface drip irrigation (SDI) in row-crop agriculture is increasing because of potential increases in water and nutrient use efficiency. Research-based information is needed to manage N applications through SDI systems in field corn (Zea-mays L.) production. This study was conducted to assess the effect of different in-season SDI system N application timings on corn production and residual soil N03-N at the University of Nebraska-Lincoln West Central Research and Extension Center in North Platte, Neb, on a Cozad silt loam (fine-silty, mixed, mesic Fluventic Haplustoll). We evaluated the effect of three N application timing methods (varying percentages of the total N rate [48% of total N] applied at the VIO, VT, and R3 growth stages, in addition to uniform N applications [52% of total NJ over all treatments at preplant, planting, and V14 growth stage) at two N application rates (University of Nebraska-Lincoln [UNL] recommended rate and the UNL rate minus 20%) on corn grain and biomass yield and end-of-study distribution of residual soil N03-N. In 2006, there were no significant differences in corn grain yields between the two N application rates. In 2007, the grain yield under the UNL.recommended N rate was significantly higher (190 kg ha-1) than the UNL-minus-20%N rate. The average grain yield for this study was close to the predicted yields (based on average 5-year historic yields + a 5% yield increase), indicating that ,orn production under SDI is satisfactory. In 2006 and 2007, grain yield and biomass production for the N application timing treatments were not significantly different (P \u3e 0.05). The application of 13% of the total N at as late as R3 did not result in decreased yields. The lack of response to differentN application timing treatments indicates that there is flexibility in N application timing for corn production under SDI. The distribution of N03-N in the 0- to 0.9-m and 0.9- to 1.8-m soil profiles was not significantly different among all the treatments

Effect of Nitrogen Application Timing on Corn Production Using Subsurface Drip Irrigation

The use of subsurface drip irrigation (SDI) in row-crop agriculture is increasing because of potential increases in water and nutrient use efficiency. Research-based information is needed to manage N applications through SDI systems in field corn (Zea-mays L.) production. This study was conducted to assess the effect of different in-season SDI system N application timings on corn production and residual soil N03-N at the University of Nebraska-Lincoln West Central Research and Extension Center in North Platte, Neb, on a Cozad silt loam (fine-silty, mixed, mesic Fluventic Haplustoll). We evaluated the effect of three N application timing methods (varying percentages of the total N rate [48% of total N] applied at the VIO, VT, and R3 growth stages, in addition to uniform N applications [52% of total NJ over all treatments at preplant, planting, and V14 growth stage) at two N application rates (University of Nebraska-Lincoln [UNL] recommended rate and the UNL rate minus 20%) on corn grain and biomass yield and end-of-study distribution of residual soil N03-N. In 2006, there were no significant differences in corn grain yields between the two N application rates. In 2007, the grain yield under the UNL.recommended N rate was significantly higher (190 kg ha-1) than the UNL-minus-20%N rate. The average grain yield for this study was close to the predicted yields (based on average 5-year historic yields + a 5% yield increase), indicating that ,orn production under SDI is satisfactory. In 2006 and 2007, grain yield and biomass production for the N application timing treatments were not significantly different (P \u3e 0.05). The application of 13% of the total N at as late as R3 did not result in decreased yields. The lack of response to differentN application timing treatments indicates that there is flexibility in N application timing for corn production under SDI. The distribution of N03-N in the 0- to 0.9-m and 0.9- to 1.8-m soil profiles was not significantly different among all the treatments

Diagnosing Bias in the Inverse Probability of Treatment Weighted Estimator Resulting from Violation of Experimental Treatment Assignment

Inverse probability of treatment weighting (IPTW) is frequently used to estimate the causal effects of treatments and interventions. The consistency of the IPTW estimator relies not only on the well-recognized assumption of no unmeasured confounders (Sequential Randomization Assumption or SRA), but also on the assumption of experimentation in the assignment of treatment (Experimental Treatment Assignment or ETA). In finite samples, violations in the ETA assumption can occur due simply to chance; certain treatments become rare or non-existent for certain strata of the population. Such practical violations of the ETA assumption occur frequently in real data, and can result in significant bias in the IPTW estimator of causal effects. This manuscript presents a diagnostic tool for assessing the bias in the IPTW estimator due to violation of the ETA assumption. The Diagnostic of ETA Bias (DEB), implemented in a public R routine, relies on parametric bootstrap sampling from an estimated data-generating distribution. The article presents results of simulations to assess the performance and applications of the diagnostic and to investigate the extent of ETA bias in a range of contexts. In addition, results are presented from two data examples drawn from the treatment of HIV infection, in which DEB is used to assess the ETA bias of the IPTW estimator

Manipulation of length and lexicality localizes the functional neuroanatomy of phonological processing in adult readers

In a previous study of single word reading, regions in the left supramarginal gyrus and left angular gyrus showed positive BOLD activity in children but significantly less activity in adults for high-frequency words. This developmental decrease may reflect decreased reliance on phonological processing for familiar stimuli in adults. Therefore, in the present study, variables thought to influence phonological demand (string length and lexicality) were manipulated. Length and lexicality effects in the brain were explored using both ROI and whole-brain approaches. In the ROI analysis, the supramarginal and angular regions from the previous study were applied to this study. The supramarginal region showed a significant positive effect of length, consistent with a role in phonological processing, whereas the angular region showed only negative deflections from baseline with a strong effect of lexicality and other weaker effects. At the whole-brain level, varying effects of length and lexicality and their interactions were observed in 85 regions throughout the brain. The application of hierarchical clustering analysis to the BOLD time course data derived from these regions revealed seven clusters, with potentially revealing anatomical locations. Of note, a left angular gyrus region was the sole constituent of one cluster. Taken together, these findings in adult readers (1) provide support for a widespread set of brain regions affected by lexical variables, (2) corroborate a role for phonological processing in the left supramarginal gyrus, and (3) do not support a strong role for phonological processing in the left angular gyrus

Spectrum of the Dirac operator coupled to two-dimensional quantum gravity

We implement fermions on dynamical random triangulation and determine numerically the spectrum of the Dirac-Wilson operator D for the system of Majorana fermions coupled to two-dimensional Euclidean quantum gravity. We study the dependence of the spectrum of the operator (epsilon D) on the hopping parameter. We find that the distributions of the lowest eigenvalues become discrete when the hopping parameter approaches the value 1/sqrt{3}. We show that this phenomenon is related to the behavior of the system in the 'antiferromagnetic' phase of the corresponding Ising model. Using finite size analysis we determine critical exponents controlling the scaling of the lowest eigenvalue of the spectrum including the Hausdorff dimension d_H and the exponent kappa which tells us how fast the pseudo-critical value of the hopping parameter approaches its infinite volume limit.Comment: 26 pages, Latex + 23 eps figs, extended analysis of the spectrum, added figure

A Smartwatch Step-Counting App for Older Adults: Development and Evaluation Study

Background: Older adults who engage in physical activity can reduce their risk of mobility impairment and disability. Short amounts of walking can improve quality of life, physical function, and cardiovascular health. Various programs have been implemented to encourage older adults to engage in physical activity, but sustaining their motivation continues to be a challenge. Ubiquitous devices, such as mobile phones and smartwatches, coupled with machine-learning algorithms, can potentially encourage older adults to be more physically active. Current algorithms that are deployed in consumer devices (eg, Fitbit) are proprietary, often are not tailored to the movements of older adults, and have been shown to be inaccurate in clinical settings. Step-counting algorithms have been developed for smartwatches, but only using data from younger adults and, often, were only validated in controlled laboratory settings. Objective: We sought to develop and validate a smartwatch step-counting app for older adults and evaluate the algorithm in free-living settings over a long period of time. Methods: We developed and evaluated a step-counting app for older adults on an open-source wrist-worn device (Amulet). The app includes algorithms to infer the level of physical activity and to count steps. We validated the step-counting algorithm in the lab (counting steps from a video recording, n=20) and in free-living conditions—one 2-day field study (n=6) and two 12-week field studies (using the Fitbit as ground truth, n=16). During app system development, we evaluated 4 walking patterns: normal, fast, up and down a staircase, and intermittent speed. For the field studies, we evaluated 5 different cut-off values for the algorithm, using correlation and error rate as the evaluation metrics. Results: The step-counting algorithm performed well. In the lab study, for normal walking (R2=0.5), there was a stronger correlation between the Amulet steps and the video-validated steps; for all activities, the Amulet’s count was on average 3.2 (2.1%) steps lower (SD 25.9) than the video-validated count. For the 2-day field study, the best parameter settings led to an association between Amulet and Fitbit (R2=0.989) and 3.1% (SD 25.1) steps lower than Fitbit, respectively. For the 12-week field study, the best parameter setting led to an R2 value of 0.669. Conclusions: Our findings demonstrate the importance of an iterative process in algorithm development before field-based deployment. This work highlights various challenges and insights involved in developing and validating monitoring systems in real-world settings. Nonetheless, our step-counting app for older adults had good performance relative to the ground truth (a commercial Fitbit step counter). Our app could potentially be used to help improve physical activity among older adults