Measured Oxygen Consumption During Pediatric Cardiac Catheterization is More Accurate than Assumed Oxygen Consumption.

When calculating cardiac index (C.I.) by the Fick method, oxygen consumption (VO2) is often unknown, so assumed values are typically used. This practice introduces a known source of inaccuracy into the calculation. Using a measured VO2 (mVO2) from the CARESCAPE E-sCAiOVX module provides an alternative that may improve accuracy of C.I. calculations. Our aim is to validate this measurement in a general pediatric catheterization population and compare its accuracy with assumed VO2 (aVO2). mVO2 was recorded for all patients undergoing cardiac catheterization with general anesthesia and controlled ventilation during the study period. mVO2 was compared to the reference VO2 (refVO2) determined by the reverse Fick method using cardiac MRI (cMRI) or thermodilution (TD) as a reference standard for measurement of C.I. when available. 193 VO2 measurements were obtained, including 71 with a corresponding cMRI or TD measure of cardiac index for validation. mVO2 demonstrated satisfactory concordance and correlation with the TD- or cMRI-derived refVO2 (ρc = 0.73, r2 = 0.63) with a mean bias of - 3.2% (SD ± 17.3%). Assumed VO2 demonstrated much weaker concordance and correlation with refVO2 (ρc = 0.28, r2 = 0.31) with a mean bias of + 27.5% (SD ± 30.0%). Subgroup analysis of patients < 36 months of age demonstrated that error in mVO2 was not significantly different from that observed in older patients. Many previously reported prediction models for assuming VO2 performed poorly in this younger age range. Measured oxygen consumption using the E-sCAiOVX module is significantly more accurate than assumed VO2 when compared to TD- or cMRI-derived VO2 in a pediatric catheterization lab.

The Influence of Gender Categories and Gender Stereotypes on Young Children's Generalizations of Biological and Behavioral Characteristics.

We examined the influence of categorization and stereotyping on young children's (N = 96; 39 to 71 months of age) use of gender to make generalizations regarding novel biological and behavioral characteristics. Participants were asked to sort pictures of children according to either gender, common gender stereotypes, or shirt color. Then participants performed a triad inductive reasoning task. Children in the Stereotype condition consistently generalized on the basis of gender, but performance was inconsistent in the absence of stereotyping. Results are discussed in relation to variability in early gender cognition.

Use of Virtual Reality for Pediatric Cardiac Critical Care Simulation.

Simulation is a key component of training in the pediatric cardiac intensive care unit (CICU), a complex environment that lends itself to virtual reality (VR)-based simulations. However, VR has not been previously described for this purpose. Two simulations were developed to test the use of VR in simulating pediatric CICU clinical scenarios, one simulating junctional ectopic tachycardia and low cardiac output syndrome, and the other simulating acute respiratory failure in a patient with suspected coronavirus disease 2019. Six attending pediatric cardiac critical care physicians were recruited to participate in the simulations as a pilot test of VR's feasibility for educational and practice improvement efforts in this highly specialized clinical environment. All participants successfully navigated the VR environment and met the critical endpoints of the two clinical scenarios. Qualitative feedback was overall positive with some specific critiques regarding limited realism in some mechanical aspects of the simulation. This is the first described use of VR in pediatric cardiac critical care simulation.

A process-based approach to understanding and managing triggered seismicity.

There is growing concern about seismicity triggered by human activities, whereby small increases in stress bring tectonically loaded faults to failure. Examples of such activities include mining, impoundment of water, stimulation of geothermal fields, extraction of hydrocarbons and water, and the injection of water, CO2 and methane into subsurface reservoirs1. In the absence of sufficient information to understand and control the processes that trigger earthquakes, authorities have set up empirical regulatory monitoring-based frameworks with varying degrees of success2,3. Field experiments in the early 1970s at the Rangely, Colorado (USA) oil field4 suggested that seismicity might be turned on or off by cycling subsurface fluid pressure above or below a threshold. Here we report the development, testing and implementation of a multidisciplinary methodology for managing triggered seismicity using comprehensive and detailed information about the subsurface to calibrate geomechanical and earthquake source physics models. We then validate these models by comparing their predictions to subsequent observations made after calibration. We use our approach in the Val d'Agri oil field in seismically active southern Italy, demonstrating the successful management of triggered seismicity using a process-based method applied to a producing hydrocarbon field. Applying our approach elsewhere could help to manage and mitigate triggered seismicity.

Brain Penetrable Inhibitors of Ceramide Galactosyltransferase for the Treatment of Lysosomal Storage Disorders.

Metachromatic leukodystrophy (MLD) is a rare, genetic lysosomal storage disorder caused by the deficiency of arylsulfatase A enzyme, which results in the accumulation of sulfatide in the lysosomes of the tissues of central and peripheral nervous systems, leading to progressive demyelination and neurodegeneration. Currently there is no cure for this disease, and the only approved therapy, hematopoietic stem cell transplant, has limitations. We proposed substrate reduction therapy (SRT) as a novel approach to treat this disease, by inhibiting ceramide galactosyltransferase enzyme (UGT8). This resulted in the identification of a thienopyridine scaffold as a starting point to initiate medicinal chemistry. Further optimization of hit compound 1 resulted in the identification of brain penetrable, orally bioavailable compound 19, which showed efficacy in the in vivo pharmacodynamic models, indicating the potential to treat MLD with UGT8 inhibitors.

Modeling missing pedigree in single-step genomic BLUP.

The objective was to compare methods of modeling missing pedigree in single-step genomic BLUP (ssGBLUP). Options for modeling missing pedigree included ignoring the missing pedigree, unknown parent groups (UPG) based on A (the numerator relationship matrix) or H (the unified pedigree and genomic relationship matrix), and metafounders. The assumptions for the distribution of estimated breeding values changed with the different models. We simulated data with heritabilities of 0.3 and 0.1 for dairy cattle populations that had more missing pedigrees for animals of lesser genetic merit. Predictions for the youngest generation and UPG solutions were compared with the true values for validation. For both traits, ssGBLUP with metafounders provided accurate and unbiased predictions for young animals while also appropriately accounting for genetic trend. Accuracy was least and bias was greatest for ssGBLUP with UPG for H for the trait with heritability of 0.3 and with UPG for A for the trait with heritability of 0.1. For the trait with heritability of 0.1 and UPG for H, the UPG accuracy (SD) was -0.49 (0.12), suggesting poor estimates of genetic trend despite having little bias for validations on young, genotyped animals. Problems with UPG estimates were likely caused by the lesser amount of information available for the lower heritability trait. Hence, UPG need to be defined differently based on the trait and amount of information. More research is needed to investigate accounting for UPG in A22 to better account for missing pedigrees for genotyped animals.

International bull evaluations by genomic BLUP with a prediction population.

The purpose of this study was to determine whether multi-country genomic evaluation can be accomplished by multiple-trait genomic best linear unbiased predictor (GBLUP) without sharing genotypes of important animals. Phenotypes and genotypes with 40k SNP were simulated for 25,000 animals, each with 4 traits assuming the same genetic variance and 0.8 genetic correlations. The population was split into 4 subpopulations corresponding to 4 countries, one for each trait. Additionally, a prediction population was created from genotyped animals that were not present in the individual countries but were related to each country's population. Genomic estimated breeding values were computed for each country and subsequently converted to SNP effects. Phenotypes were reconstructed for the prediction population based on the SNP effects of a country and the prediction animals' genotypes. The prediction population was used as the basis for the international evaluation, enabling bull comparisons without sharing genotypes and only sharing SNP effects. The computations were such that SNP effects computed within-country or in the prediction population were the same. Genomic estimated breeding values were calculated by single-trait GBLUP for within-country and multiple-trait GBLUP for multi-country predictions. The true accuracy for the prediction population with reconstructed phenotypes was at most 0.02 less than the accuracy with the original data. The differences increased when countries were assumed unequally sized. However, accuracies by multiple-trait GBLUP with the prediction population were always greater than accuracies from any single within-country prediction. Multi-country genomic evaluations by multiple-trait GBLUP are possible without using original genotypes at a cost of lower accuracy compared with explicitly combining countries' data.

Modeling pedigree accuracy and uncertain parentage in single-step genomic evaluations of simulated and US Holstein datasets.

The objective of this study was to model differences in pedigree accuracy caused by selective genotyping. As genotypes are used to correct pedigree errors, some pedigree relationships are more accurate than others. These accuracy differences can be modeled with uncertain parentage models that distribute the paternal (maternal) contribution across multiple sires (dams). In our case, the parents were the parent on record and an unknown parent group to account for pedigree relationships that were not confirmed through genotypes. Pedigree accuracy was addressed through simulation and through North American Holstein data. Data were simulated to be representative of the dairy industry with heterogeneous pedigree depth, pedigree accuracy, and genotyping. Holstein data were obtained from the official evaluation for milk, fat, and protein. Two models were compared: the traditional approach, assuming accurate pedigrees, and uncertain parentage, assuming variable pedigree accuracy. The uncertain parentage model was used to add pedigree relationships for alternative parents when pedigree relationships were not certain. The uncertain parentage model included 2 possible sires (dams) when the sire (dam) could not be confirmed with genotypes. The 2 sires (dams) were the sire (dam) on record with probability 0.90 (0.95) and the unknown parent group for the birth year of the sire (dam) with probability 0.10 (0.05). An additional set of assumptions was tested in simulation to mimic an extensive dairy production system by using a sire probability of 0.75, a dam probability of 0.85, and the remainder attributed to the unknown parent groups. In the simulation, small bias differences occurred between models based on pedigree accuracy and genotype status. Rank correlations were strong between traditional and uncertain parentage models in simulation (≥0.99) and in Holstein (≥0.99). For Holsteins, the estimated breeding value differences between models were small for most animals. Thus, traditional models can continue to be used for dairy genomic prediction despite using genotypes to improve pedigree accuracy. Those genotypes can also be used to discover maternal parentage, specifically maternal grandsires and great grandsires when the dam is not known. More research is needed to understand how to use discovered maternal pedigrees in genetic prediction.

Tuning the Amount of Oxygen Vacancies in Sputter-Deposited SnOx films for Enhancing the Performance of Perovskite Solar Cells.

This work demonstrates the effect of oxygen vacancies in SnOx thin films on the performance of perovskite solar cells. Various SnOx films with different amounts of oxygen vacancies were deposited by sputtering at different substrate temperatures (25-300 °C). The transmittance of the films decreased from 82 to 66 % with increasing deposition temperature from 25 to 300 °C. Both X-ray photoelectron spectroscopy and electron-spin resonance spectroscopy confirmed that a higher density of oxygen vacancies was created within the SnOx film at a high substrate temperature, which caused narrowing of the SnOx bandgap from 4.1 (25 °C) to 3.74 eV (250 °C). Combined ultraviolet photoelectron spectroscopy and UV/Vis spectroscopy showed an excellent conduction band position alignment between the methylammonium lead iodide perovskite layer (3.90 eV) and the SnOx electron transport layer deposited at 250 °C (3.92 eV). As a result, a significant enhancement of the open-circuit voltage from 0.82 to 1.0 V was achieved, resulting in an increase of the power conversion efficiency of the perovskite solar cells from 11 to 14 %. This research demonstrated a facile approach for controlling the amount of oxygen vacancies in SnOx thin films to achieve a desirable energy alignment with the perovskite absorber layer for enhanced device performance.

Intrinsic DNA binding properties demonstrated for lineage-specifying basic helix-loop-helix transcription factors.

During development, transcription factors select distinct gene programs, providing the necessary regulatory complexity for temporal and tissue-specific gene expression. How related factors retain specificity, especially when they recognize the same DNA motifs, is not understood. We address this paradox using basic helix-loop-helix (bHLH) transcription factors ASCL1, ASCL2, and MYOD1, crucial mediators of lineage specification. In vivo, these factors recognize the same DNA motifs, yet bind largely different genomic sites and regulate distinct transcriptional programs. This suggests that their ability to identify regulatory targets is defined either by the cellular environment of the partially defined lineages in which they are endogenously expressed, or by intrinsic properties of the factors themselves. To distinguish between these mechanisms, we directly compared the chromatin binding properties of this subset of bHLH factors when ectopically expressed in embryonic stem cells, presenting them with a common chromatin landscape and cellular components. We find that these factors retain distinct binding sites; thus, specificity of binding is an intrinsic property not requiring a restricted landscape or lineage-specific cofactors. Although the ASCL factors and MYOD1 have some distinct DNA motif preference, it is not sufficient to explain the extent of the differential binding. All three factors can bind inaccessible chromatin and induce changes in chromatin accessibility and H3K27ac. A reiterated pattern of DNA binding motifs is uniquely enriched in inaccessible chromatin at sites bound by these bHLH factors. These combined properties define a subclass of lineage-specific bHLH factors and provide context for their central roles in development and disease.

Implications of SNP weighting on single-step genomic predictions for different reference population sizes.

We investigated the importance of SNP weighting in populations with 2,000 to 25,000 genotyped animals. Populations were simulated with two effective sizes (20 or 100) and three numbers of QTL (10, 50 or 500). Pedigree information was available for six generations; phenotypes were recorded for the four middle generations. Animals from the last three generations were genotyped for 45,000 SNP. Single-step genomic BLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) were used to estimate genomic EBV using a genomic relationship matrix (G). The WssGBLUP performed better in small genotyped populations; however, any advantage for WssGBLUP was reduced or eliminated when more animals were genotyped. WssGBLUP had greater resolution for genome-wide association (GWA) as did increasing the number of genotyped animals. For few QTL, accuracy was greater for WssGBLUP than ssGBLUP; however, for many QTL, accuracy was the same for both methods. The largest genotyped set was used to assess the dimensionality of genomic information (number of effective SNP). The number of effective SNP was considerably less in weighted G than in unweighted G. Once the number of independent SNP is well represented in the genotyped population, the impact of SNP weighting becomes less important.

Technical note: Impact of pedigree depth on convergence of single-step genomic BLUP in a purebred swine population.

In genomic evaluations, it is desirable to have low computing cost while retaining high accuracy of evaluation for young animals. When the population is large but only few animals have phenotypes, especially for low heritability traits, the convergence rate of BLUP or single-step genomic BLUP (ssGBLUP) can be very slow. This study investigates the effect of pedigree truncation on convergence rate and solutions of ssGBLUP for data exhibiting slow convergence. The data consisted of 216,000, 221,000, 732,000, and 579,000 phenotypes on 4 traits. Heritabilities were less than 0.1 for 2 traits and greater than 0.2 for the other 2 traits. The full pedigree consisted of 2.4 million animals. Genotypes were available for 33,000 animals and consisted of 60,000 SNP. Two bivariate animal models were fit using pedigree-based BLUP or ssGBLUP. Either a regular or the algorithm for proven and young (APY) inverse was used for the genomic relationship matrix. Different pedigree depths were analyzed including full pedigree and 1 to 5 ancestral generations. Pedigree depths were defined as n ancestral generations for animals with phenotypes. The number of animals in the reduced pedigrees varied from 226,000 and 760,000 for 1 generation to 228,000 and 767,000 for 5 generations. Genomic EBV (GEBV) for genotyped animals had correlations greater than 0.99 between runs with the full and reduced pedigrees with 2 to 5 generations. A single generation of pedigree was not sufficient to obtain the same GEBV as full pedigree. The convergence rate was the worst with the full pedigree and generally improved with reduced pedigrees. Using ssGBLUP with the APY inverse improved convergence without affecting accuracy. Reducing pedigrees and the APY are important tools to reduce the computational cost in the implementation of ssGBLUP.

Randomized Trial of Intelligent Sensor System for Early Illness Alerts in Senior Housing.

OBJECTIVES: Measure the clinical effectiveness and cost effectiveness of using sensor data from an environmentally embedded sensor system for early illness recognition. This sensor system has demonstrated in pilot studies to detect changes in function and in chronic diseases or acute illnesses on average 10 days to 2 weeks before usual assessment methods or self-reports of illness. DESIGN: Prospective intervention study in 13 assisted living (AL) communities of 171 residents randomly assigned to intervention (n=86) or comparison group (n=85) receiving usual care. METHODS: Intervention participants lived with the sensor system an average of one year. MEASUREMENTS: Continuous data collected 24 hours/7 days a week from motion sensors to measure overall activity, an under mattress bed sensor to capture respiration, pulse, and restlessness as people sleep, and a gait sensor that continuously measures gait speed, stride length and time, and automatically assess for increasing fall risk as the person walks around the apartment. Continuously running computer algorithms are applied to the sensor data and send health alerts to staff when there are changes in sensor data patterns. RESULTS: The randomized comparison group functionally declined more rapidly than the intervention group. Walking speed and several measures from GaitRite, velocity, step length left and right, stride length left and right, and the fall risk measure of functional ambulation profile (FAP) all had clinically significant changes. The walking speed increase (worse) and velocity decline (worse) of 0.073 m/s for comparison group exceeded 0.05 m/s, a value considered to be a minimum clinically important difference. No differences were measured in health care costs. CONCLUSIONS: These findings demonstrate that sensor data with health alerts and fall alerts sent to AL nursing staff can be an effective strategy to detect and intervene in early signs of illness or functional decline.

Smek promotes corticogenesis through regulating Mbd3's stability and Mbd3/NuRD complex recruitment to genes associated with neurogenesis.

The fate of neural progenitor cells (NPCs) during corticogenesis is determined by a complex interplay of genetic or epigenetic components, but the underlying mechanism is incompletely understood. Here, we demonstrate that Suppressor of Mek null (Smek) interact with methyl-CpG-binding domain 3 (Mbd3) and the complex plays a critical role in self-renewal and neuronal differentiation of NPCs. We found that Smek promotes Mbd3 polyubiquitylation and degradation, blocking recruitment of the repressive Mbd3/nucleosome remodeling and deacetylase (NuRD) complex at the neurogenesis-associated gene loci, and, as a consequence, increasing acetyl histone H3 activity and cortical neurogenesis. Furthermore, overexpression of Mbd3 significantly blocked neuronal differentiation of NPCs, and Mbd3 depletion rescued neurogenesis defects seen in Smek1/2 knockout mice. These results reveal a novel molecular mechanism underlying Smek/Mbd3/NuRD axis-mediated control of NPCs' self-renewal and neuronal differentiation during mammalian corticogenesis.

Genetic variance and covariance and breed differences for feed intake and average daily gain to improve feed efficiency in growing cattle.

Feed costs are a major economic expense in finishing and developing cattle; however, collection of feed intake data is costly. Examining relationships among measures of growth and intake, including breed differences, could facilitate selection for efficient cattle. Objectives of this study were to estimate genetic parameters for growth and intake traits and compare indices for feed efficiency to accelerate selection response. On-test ADFI and on-test ADG (TESTADG) and postweaning ADG (PWADG) records for 5,606 finishing steers and growing heifers were collected at the U.S. Meat Animal Research Center in Clay Center, NE. On-test ADFI and ADG data were recorded over testing periods that ranged from 62 to 148 d. Individual quadratic regressions were fitted for BW on time, and TESTADG was predicted from the resulting equations. We included PWADG in the model to improve estimates of growth and intake parameters; PWADG was derived by dividing gain from weaning weight to yearling weight by the number of days between the weights. Genetic parameters were estimated using multiple-trait REML animal models with TESTADG, ADFI, and PWADG for both sexes as dependent variables. Fixed contemporary groups were cohorts of calves simultaneously tested, and covariates included age on test, age of dam, direct and maternal heterosis, and breed composition. Genetic correlations (SE) between steer TESTADG and ADFI, PWADG and ADFI, and TESTADG and PWADG were 0.33 (0.10), 0.59 (0.06), and 0.50 (0.09), respectively, and corresponding estimates for heifers were 0.66 (0.073), 0.77 (0.05), and 0.88 (0.05), respectively. Indices combining EBV for ADFI with EBV for ADG were developed and evaluated. Greater improvement in feed efficiency can be expected using an unrestricted index versus a restricted index. Heterosis significantly affected each trait contributing to greater ADFI and TESTADG. Breed additive effects were estimated for ADFI, TESTADG, and the efficiency indices.

Selection of core animals in the Algorithm for Proven and Young using a simulation model.

The Algorithm for Proven and Young (APY) enables the implementation of single-step genomic BLUP (ssGBLUP) in large, genotyped populations by separating genotyped animals into core and non-core subsets and creating a computationally efficient inverse for the genomic relationship matrix (G). As APY became the choice for large-scale genomic evaluations in BLUP-based methods, a common question is how to choose the animals in the core subset. We compared several core definitions to answer this question. Simulations comprised a moderately heritable trait for 95,010 animals and 50,000 genotypes for animals across five generations. Genotypes consisted of 25,500 SNP distributed across 15 chromosomes. Genotyping errors and missing pedigree were also mimicked. Core animals were defined based on individual generations, equal representation across generations, and at random. For a sufficiently large core size, core definitions had the same accuracies and biases, even if the core animals had imperfect genotypes. When genotyped animals had unknown parents, accuracy and bias were significantly better (p ≤ .05) for random and across generation core definitions.

Using Embedded Sensors in Independent Living to Predict Gait Changes and Falls.

This study explored using Big Data, totaling 66 terabytes over 10 years, captured from sensor systems installed in independent living apartments to predict falls from pre-fall changes in residents' Kinect-recorded gait parameters. Over a period of 3 to 48 months, we analyzed gait parameters continuously collected for residents who actually fell ( n = 13) and those who did not fall ( n = 10). We analyzed associations between participants' fall events ( n = 69) and pre-fall changes in in-home gait speed and stride length ( n = 2,070). Preliminary results indicate that a cumulative change in speed over time is associated with the probability of a fall ( p < .0001). The odds of a resident falling within 3 weeks after a cumulative change of 2.54 cm/s is 4.22 times the odds of a resident falling within 3 weeks after no change in in-home gait speed. Results demonstrate using sensors to measure in-home gait parameters associated with the occurrence of future falls.

Genetic evaluations for growth heat tolerance in Angus cattle.

The objectives were to assess the impact of heat stress and to develop a model for genetic evaluation of growth heat tolerance in Angus cattle. The American Angus Association provided weaning weight (WW) and yearling weight (YW) data, and records from the Upper South region were used because of the hot climatic conditions. Heat stress was characterized by a weaning (yearling) heat load function defined as the mean temperature-humidity index (THI) units greater than 75 (70) for 30 (150) d prior to the weigh date. Therefore, a weaning (yearling) heat load of 5 units corresponded to 80 (75) for the corresponding period prior to the weigh date. For all analyses, 82,669 WW and 69,040 YW were used with 3 ancestral generations in the pedigree. Univariate models were a proxy for the Angus growth evaluation, and reaction norms using 2 B-splines for heat load were fit separately for weaning and yearling heat loads. For both models, random effects included direct genetic, maternal genetic, maternal permanent environment (WW only), and residual. Fixed effects included a linear age covariate, age-of-dam class (WW only), and contemporary group for both models and fixed regressions on the B-splines in the reaction norm. Direct genetic correlations for WW were strong for modest heat load differences but decreased to less than 0.50 for large differences. Reranking of proven sires occurred for only WW direct effects for the reaction norms with extreme heat load differences. Conversely, YW results indicated little effect of heat stress on genetic merit. Therefore, weaning heat tolerance was a better candidate for developing selection tools. Maternal heritabilities were consistent across heat loads, and maternal genetic correlations were greater than 0.90 for nearly all heat load combinations. No evidence existed for a genotype × environment interaction for the maternal component of growth. Overall, some evidence exists for phenotypic plasticity for the direct genetic effects of WW, but traditional national cattle evaluations are likely adequately ranking sires for nonextreme environmental conditions.

Regional and seasonal analyses of weights in growing Angus cattle.

This study evaluated the impact of region and season on growth in Angus seed stock. To assess geographic differences, the United States was partitioned into 9 regions based on similar climate and topography related to cow-calf production. Seasonal effects were associated with the month that animals were weighed. The American Angus Association provided growth data, and records were assigned to regions based on the owner's zip code. Most Angus cattle were in the Cornbelt, Lower Plains, Rocky Mountain, Upper Plains, and Upper South regions, with proportionally fewer Angus in Texas compared with the national cow herd. Most calves were born in the spring, especially February and March. Weaning weights (WW; = 49,886) and yearling weights (YW; = 45,168) were modeled with fixed effects of age-of-dam class (WW only), weigh month, region, month-region interaction, and linear covariate of age. Random effects included contemporary group nested within month-region combination and residual. The significant month-region interaction ( < 0.0001) was expected because of the diverse production environments across the country and cyclical fluctuations in forage availability. Additionally, significant seasonal contrasts existed for several regions. Fall-born calves were heavier ( < 0.01) than spring-born calves in the hot and humid Lower South region coinciding with fall being the primary calving season. The North and Upper Plains regions had heavier, spring-born calves ( < 0.01), more than 90% spring calving, and colder climates. Interestingly, no seasonal WW or YW differences existed between spring- and fall-born calves in the upper South region despite challenging environmental conditions. Angus seed stock producers have used calving seasons to adapt to the specific environmental conditions in their regions and to optimize growth in young animals.

Mother-Child Conversation and Children's Social Understanding During Middle Childhood.

The authors investigated the relationship between mother-child conversation and children's social understanding during middle childhood. Thirty-eight mother-child pairs participated, including a younger group (5-7 years old) and an older group (8-10 years old). Children completed 2 measures of social understanding and mothers and children discussed 4 stories involving social dilemmas. Results indicated that compared to the younger group, the older group (a) performed better on both measures of social understanding and (b) produced more basic mental talk (i.e., talk about beliefs, emotions, personality traits, and desires), and more advanced mental talk (i.e., talk about contrasting perspectives, recursion and relationship between mental states, and advanced emotions). Mothers of older children also produced more basic and advanced mental talk. Mothers' advanced mental talk predicted both children's social understanding and children's advanced mental talk.