Assessing molecular doping efficiency in organic semiconductors with reactive Monte Carlo.

The addition of molecular dopants into organic semiconductors (OSCs) is a ubiquitous augmentation strategy to enhance the electrical conductivity of OSCs. Although the importance of optimizing OSC-dopant interactions is well-recognized, chemically generalizable structure-function relationships are difficult to extract due to the sensitivity and dependence of doping efficiency on chemistry, processing conditions, and morphology. Computational modeling for an integrated OSC-dopant design is an attractive approach to systematically isolate fundamental relationships, but requires the challenging simultaneous treatment of molecular reactivity and morphology evolution. We present the first computational study to couple molecular reactivity with morphology evolution in a molecularly doped OSC. Reactive Monte Carlo is employed to examine the evolution of OSC-dopant morphologies and doping efficiency with respect to dielectric, the thermodynamic driving for the doping reaction, and dopant aggregation. We observe that for well-mixed systems with experimentally relevant dielectric constants, doping efficiency is near unity with a very weak dependence on the ionization potential and electron affinity of OSC and dopant, respectively. At experimental dielectric constants, reaction-induced aggregation is observed, corresponding to the well-known insolubility of solution-doped materials. Simulations are qualitatively consistent with a number of experimental studies showing a decrease of doping efficiency with increasing dopant concentration. Finally, we observe that the aggregation of dopants lowers doping efficiency and thus presents a rational design strategy for maximizing doping efficiency in molecularly doped OSCs. This work represents an important first step toward the systematic integration of molecular reactivity and morphology evolution into the characterization of multi-scale structure-function relationships in molecularly doped OSCs.

Weighted single step GWAS reveals genomic regions associated with economic traits in Murrah buffaloes.

The objective of the present study was to identify genomic regions influencing economic traits in Murrah buffaloes using weighted single step Genome Wide Association Analysis (WssGWAS). Data on 2000 animals, out of which 120 were genotyped using a double digest Restriction site Associated DNA (ddRAD) sequencing approach. The phenotypic data were collected from NDRI, India, on growth traits, viz., body weight at 6M (month), 12M, 18M and 24M, production traits like 305D (day) milk yield, lactation length (LL) and dry period (DP) and reproduction traits like age at first calving (AFC), calving interval (CI) and first service period (FSP). The biallelic genotypic data consisted of 49353 markers post-quality check. The heritability estimates were moderate to high, low to moderate, low for growth, production, reproduction traits, respectively. Important genomic regions explaining more than 0.5% of the total additive genetic variance explained by 30 adjacent SNPs were selected for further analysis of candidate genes. In this study, 105 genomic regions were associated with growth, 35 genomic regions with production and 42 window regions with reproduction traits. Different candidate genes were identified in these genomic regions, of which important are OSBPL8, NAP1L1 for growth, CNTNAP2 for production and ILDR2, TADA1 and POGK for reproduction traits.

Perspectives on preparedness for pediatric emergencies after residency: A needs assessment.

Background: General emergency physicians provide most pediatric emergency care in the United States yet report more challenges managing emergencies in children than adults. Recommendations for standardized pediatric emergency medicine (PEM) curricula to address educational gaps due to variations in pediatric exposure during emergency medicine (EM) training lack learner input. This study surveyed senior EM residents and recent graduates about their perceived preparedness to manage pediatric emergencies to better inform PEM curricula design. Methods: In 2021, senior EM residents and graduates from the classes of 2020 and 2019 across eight EM programs with PEM rotations at the same children's hospital were recruited and surveyed electronically to assess perceived preparedness for 42 pediatric emergencies and procedures by age: infants under 1 year, toddlers, and children over 4 years. Preparedness was reported on a 5-point Likert scale with 1 or 2 defined as "unprepared." A chi-square test of independence compared the proportion of respondents unprepared to manage each condition across age groups, and a p-value < 0.05 demonstrated significance. Results: The response rate was 53% (129/242), with a higher response rate from senior residents (65%). Respondents reported feeling unprepared to manage more emergency conditions in infants compared to other age groups. Respondents felt least prepared to manage inborn errors of metabolism and congenital heart disease, with 45%-68% unprepared for these conditions across ages. A heat map compared senior residents to recent graduates. More graduates reported feeling unprepared for major trauma, impending respiratory failure, and pediatric advanced life support algorithms. Conclusions: This study, describing the perspective of EM senior residents and recent graduates, offers unique insights into PEM curricular needs during EM training. Future PEM curricula should target infant complaints and conditions with lower preparedness scores across ages. Other centers training EM residents could use our findings and methods to bolster PEM curricula.

Genetic improvement of economic traits in Murrah buffalo using significant SNPs from genome-wide association study.

GWAS helps to identify QTL and candidate genes of specific traits. Buffalo breeding has primarily focused on milk production, but its negative correlation with reproduction traits resulted in unfavorable decline of reproductive performance among buffaloes. A genome wide scan was performed on a total of 120 Murrah buffaloes genotyped by ddRAD sequencing for 13 traits related to female fertility, production, and growth. The identified 25 significant single nucleotide polymorphisms (SNPs) (P <1×106) are associated with age at first calving (AFC), age at first service (AFS), period from calving to 1st Artifical Insemination (AI), service period (SP) and 6 month body weight (6M). Fifteen genetic variants overlapped with different QTL regions of reported studies. Among the associated loci, outstanding candidate genes for fertility, including AQP1, TRNAE-CUC, NRIP1, CPNE4, and VOPP1, have effect in different fertility traits. AQP1 gene is expressed in ovulatory phase and various stages of pregnancy. TRNAE-CUC gene is associated with AFC and number . of calvings after 4 years of age. Glycogen content-associated gene CPNE4 regulates muscle glycogen and is upregulated during early pregnancy. NRIP1 generegulates ovulation, corpus luteum at pregnancy, and mammary gland development. The objective is to identify potential genomic regions and genetic variants associated with economic traits and to select the most significant SNP which have positive effect on all the traits.

Reduced representation approach for identification of genome-wide SNPs and their annotation for economically important traits in Indian Tharparkar cattle.

The present study was carried out in Tharparkar cattle for identification of genome-wide SNPs and microsatellites, and then annotate the identified high-quality SNPs to milk production, fertility, carcass, adaptability and immune response of economically important traits. A total of 146,011 SNPs were identified with respect to Bos taurus reference genome which are indicus specific, out of which 10,519 SNPs were found to be novel. Similarly, a total of 87,047 SNPs were identified with respect to Bos indicus reference genome. After final annotation of SNPs identified with respect to Bos indicus reference genome, 2871 SNPs were found to be associated in 383 candidate genes having to do with milk production, fertility, carcass, immune response and adaptability traits. Following that, 2571 microsatellites were identified. The information mined from the data might be of importance for the future breed improvement programs, conservation efforts and for enhancing the SNPs density of the existing bovine SNP chips.