Corn Nitrogen Nutrition Index Prediction Improved by Integrating Genetic, Environmental, and Management Factors with Active Canopy Sensing Using Machine Learning

Accurate nitrogen (N) diagnosis early in the growing season across diverse soil, weather, and management conditions is challenging. Strategies using multi-source data are hypothesized to perform significantly better than approaches using crop sensing information alone. The objective of this study was to evaluate, across diverse environments, the potential for integrating genetic (e.g., comparative relative maturity and growing degree units to key developmental growth stages), environmental (e.g., soil and weather), and management (e.g., seeding rate, irrigation, previous crop, and preplant N rate) information with active canopy sensor data for improved corn N nutrition index (NNI) prediction using machine learning methods. Thirteen site-year corn (Zea mays L.) N rate experiments involving eight N treatments conducted in four US Midwest states in 2015 and 2016 were used for this study. A proximal RapidSCAN CS-45 active canopy sensor was used to collect corn canopy reflectance data around the V9 developmental growth stage. The utility of vegetation indices and ancillary data for predicting corn aboveground biomass, plant N concentration, plant N uptake, and NNI was evaluated using singular variable regression and machine learning methods. The results indicated that when the genetic, environmental, and management data were used together with the active canopy sensor data, corn N status indicators could be more reliably predicted either using support vector regression (R2 = 0.74–0.90 for prediction) or random forest regression models (R2 = 0.84–0.93 for prediction), as compared with using the best-performing single vegetation index or using a normalized difference vegetation index (NDVI) and normalized difference red edge (NDRE) together (R2 < 0.30). The N diagnostic accuracy based on the NNI was 87% using the data fusion approach with random forest regression (kappa statistic = 0.75), which was better than the result of a support vector regression model using the same inputs. The NDRE index was consistently ranked as the most important variable for predicting all the four corn N status indicators, followed by the preplant N rate. It is concluded that incorporating genetic, environmental, and management information with canopy sensing data can significantly improve in-season corn N status prediction and diagnosis across diverse soil and weather conditions.

The MacArthur-Bates CDI-III for Spanish-speaking Children

Parent report measures have been shown to be effective, valid and cost-effective means for obtaining information about early child language development. There are several measures available in multiple languages for children below the age of 3. There has been a need for such measures for older children. This study presents the development of a Spanish version of the MacArthur-Bates Communicative Development Inventory-III for children 2 ½ to 4 years of age. A total of 571 families of monolingual Spanish-speaking children from a diverse socio-economic group were asked to fill out the parent report measure in order to obtain a norming sample. Data are presented by age and socio-economic groups that show developmental growth curves for vocabulary production and sentence complexity. Norming tables that show variability by ages are presented. Additional information is given for a General Concepts section. This study presents a new parent report instrument that can be used both clinically and for research purposes.

Providing Validity Evidence for Ignite by Hatch

The authors of this study seek to provide practitioners with evidence to support the instructional value of Ignite by Hatch, a digital learning game designed for preschool children. Analyses were conducted using the entire population of three- and four-year-old children who used Ignite during the 2020-2021 academic year (n = 29,417) and included the use of descriptive statistics to explore patterns of growth and the Rasch measurement model to explore item difficulty. This chapter also features a preliminary crosswalk establishing the alignment between the domains, subdomains, and games presented within the Ignite game environment and the learning goals provided by the North Carolina Foundations for Early Learning and Development framework. Results suggest strong preliminary evidence in support of the instructional value of Ignite by Hatch. Further research is recommended to understand how knowledge and skill acquisition within the game environment translate to developmental growth outside of the gaming environment.

The regeneration factors ERF114 and ERF115 act as transducers of mechanical cues to developmental pathways

Plants show an unparalleled regenerative capacity, allowing them to survive severe stress conditions, such as injury, herbivory attack and harsh weather conditions. This potential not only replenishes tissues and restores damaged organs, but can also give rise to whole plant bodies, highlighting the intertwined nature of development and regeneration. It suggests that regeneration and developmental processes respond to the same upstream signals, but how a cell knows which of the two processes to engage is currently unknown. Here, we demonstrate that next to being regulators of regeneration, ETHYENE RESPONSE FACTOR 114 (ERF114) and ERF115 govern developmental growth in the absence of wounding or injury. Increased ERF114 and ERF115 activity is correlated with enhanced xylem maturation and lateral root formation, whereas their knockout results in a decrease in lateral roots and xylem connectivity following grafting. Moreover, we provide evidence that mechanical cues contribute to ERF114 and ERF115 expression in correlation with BZR1 mediated brassinosteroid signaling under both regenerative and developmental conditions. Antagonistically, negative regulation of cell wall extensibility via cell wall-associated mechanosensory FERONIA signaling suppresses their expression under both conditions. Our data suggest a molecular framework in which mechanical perturbations too great to be compensated by adaptive cell wall remodeling results in strong ERF114 and ERF115 expression, switching their role from developmental to regenerative regulators.

A large-scale transgenic RNAi screen identifies transcription factors that modulate myofiber size in Drosophila

Myofiber atrophy occurs with aging and in many diseases but the underlying mechanisms are incompletely understood. Here, we have used >1,100 muscle-targeted RNAi interventions to comprehensively assess the function of 447 transcription factors in the developmental growth of body wall skeletal muscles in Drosophila. This screen identifies new regulators of myofiber atrophy and hypertrophy, including the transcription factor Deaf1. Deaf1 RNAi increases myofiber size whereas Deaf1 overexpression induces atrophy. Consistent with its annotation as a Gsk3 phosphorylation substrate, Deaf1 and Gsk3 induce largely overlapping transcriptional changes that are opposed by Deaf1 RNAi. The top category of Deaf1-regulated genes consists of glycolytic enzymes, which are suppressed by Deaf1 and Gsk3 but are upregulated by Deaf1 RNAi. Similar to Deaf1 and Gsk3 overexpression, RNAi for glycolytic enzymes reduces myofiber growth. Altogether, this study defines the repertoire of transcription factors that regulate developmental myofiber growth and the role of Gsk3/Deaf1/glycolysis in this process.

Genome-Wide Association Study And Polygenic Risk Scores Of Serum Dheas Levels In A Chilean Children Cohort

Background Adrenarche reflects the developmental growth of the adrenal zona reticularis, which produces increasing adrenal androgen secretion (e.g., DHEA/DHEAS) from ages ~5-15 years. We hypothesized that the study of the genetic determinants associated with variations in serum DHEAS during adrenarche might detect genetic variants influencing the rate or timing of this process. Subjects and methods Genome-wide genotyping was performed in participants of the Chilean pediatric GOCS cohort (n=788). We evaluated the genetic determinants of DHEAS levels at genome-wide level and in targeted genes associated with steroidogenesis. To corroborate our findings, we evaluated a polygenic risk score for age at pubarche, based upon the discovered variants, in children from the same cohort. Results We identified one significant variant at the genome-wide level in the full cohort, close to the GALR1 gene (P = 3.81x10 -8). In addition, variants suggestive of association (P &lt;1x10 -5) were observed in PRLR, PITX1, PTPRD, NR1H4, and BCL11B. Stratifying by sex, we found variants suggestive of association in SERBP1 and CAMTA1/VAMP3 for boys and near ZNF98, TRPC6, and SULT2A1 for girls. We also found significant reductions in age at pubarche in those children with higher polygenic risk scores for greater DHEAS based on these newly identified variants. Conclusions Our results disclose one variant associated with DHEAS concentrations at the level of GWAS significance, and several variants with suggestive association, which may be involved in the genetic regulation of adrenarche.

The Relationship between Hemoglobin Concentration and Physical Growth and Development of Toddlers Age 2-5 Years in Malacca Village, Sumedang, West Java, Indonesia

Stunting is a chronic nutritional problem caused by insufficient nutritional intake for a long time and can disrupt growth and development. Besides affecting physical growth, stunting can also affect haemoglobin levels. Stunting children have lower haemoglobin levels than non-stunting toddlers. This study aims to determine the relationship between haemoglobin concentration and physical and developmental growth in children aged two years - 5 years in Malaka Village, Sumedang, West Java. This study used an Analytical Observational design with a cross-sectional study approach. The number of samples is 64 respondents. Sample selection was made by purposive sampling. Data collection was taken by measuring height and weight and using the Denver Developmental Screening Test II. Data is processed using the chi-square statistical test with a significance level of p (α) = 0.05. The analysis results show no correlation between haemoglobin concentration and physical growth and development in children with a significance value of p> 0.05. It can be concluded that there is no significant relationship between haemoglobin concentration and physical and developmental growth in Infants 2 years - 5 years in Malaka Village, Sumedang. For further research, more respondents and better measurement tools are needed to improve the accuracy of the research results. Key words: haemoglobin concentration, physical and developmental growth.

Overexpression of HOP2 induces developmental defects and compromises growth in Arabidopsis

HOMOLOGOUS PAIRING 2 (HOP2) is a predominantly meiotic protein that plays a pivotal role in homologous chromosome pairing in organisms as diverse as yeast and mammals. While generating HOP2::GFP reporter lines, we identified two Arabidopsis T-DNA insertion mutants, stunted1(std1) and stunted2 (std2) that exhibit pleiotropic phenotypes, including fasciated stems, altered phyllotaxy, floral organ defects, reduced fecundity, and an overall reduction in growth properties. TAIL-PCR followed by sequencing revealed several insertions near genes, but genotyping showed that none of the insertions are causal. Analysis the std mutants by qRT-PCR, and analysis of dexamethasone inducible HOP2 transgenic plants demonstrated that the std phenotypes are associated with ectopic/overexpression of HOP2. Based on the postulated mechanisms of HOP2 action, we speculate on how overexpression leads to these developmental/growth defects.

A Systemic View of Carbohydrate Metabolism in Rice to Facilitate Productivity

Carbohydrate metabolism is an important biochemical process related to developmental growth and yield-related traits. Due to global climate change and rapid population growth, increasing rice yield has become vital. To understand whole carbohydrate metabolism pathways and find related clues for enhancing yield, genes in whole carbohydrate metabolism pathways were systemically dissected using meta-transcriptome data. This study identified 866 carbohydrate genes from the MapMan toolkit and the Kyoto Encyclopedia of Genes and Genomes database split into 11 clusters of different anatomical expression profiles. Analysis of functionally characterized carbohydrate genes revealed that source activity and eating quality are the most well-known functions, and they each have a strong correlation with tissue-preferred clusters. To verify the transcriptomic dissection, three pollen-preferred cluster genes were used and found downregulated in the gori mutant. Finally, we summarized carbohydrate metabolism as a conceptual model in gene clusters associated with morphological traits. This systemic analysis not only provided new insights to improve rice yield but also proposed novel tissue-preferred carbohydrate genes for future research.

The role of genetics in fetal programming of adult cardiometabolic disease

Disturbances affecting early development have broad repercussions on the individual’s health during infancy and adulthood. Multiple observational studies throughout the years have shown that alterations of fetal growth are associated with increased cardiometabolic disease risks. However, the genetic component of this association only started to be investigated in the last 40 years, when single genes with distinct effects were investigated. Birth weight (BW), commonly reported as the outcome of developmental growth, has been estimated to be 20% to 60% heritable. Through Genome-Wide Association (GWA) meta-analyses, 190 different loci have been identified being associated with BW, and while many of these loci designate genes involved in glucose and lipid metabolism, with clear ties to fetal development, the role of others is not yet understood. In addition, due to its influence over the intrauterine environment, the maternal genotype also plays an important part in the determination of offspring BW, with the same loci having independent effects of different magnitude or even direction. There is still much to uncover regarding the genetic determinants of BW and the interactions between maternal, offspring, and even paternal genotype. To fully understand these, diverse and novel cohorts from multiple ancestries collecting extensive neonatal phenotype will be needed. This review compiles, chronologically, the main findings in the investigation of the genetics of BW.