Probabilistic prediction of segmental body composition in Iranian children and adolescents.

BACKGROUND: Adolescents' body composition is considered an important measure to evaluate health status. An examination of any of the segmental compartments by anthropometric indices is a more usable method than direct methods. OBJECTIVES: To propose a method based on the network approach for predicting segmental body composition components in adolescent boys and girls using anthropometric measurements. METHODS: A dual-energy X-ray absorptiometry (DXA) dataset in the south of Iran, including 476 adolescents (235 girls and 241 boys) with a range of 9-18 years, was obtained. Several anthropometric prediction models based on the network approach were fitted to the training dataset (TRD 80%) using bnlearn, an R add-in package. The best fitted models were applied to the validation dataset (VAD 20%) to assess the prediction accuracy. RESULTS: Present equations consisting of age, weight, height, body mass index (BMI), and hip circumference accounted for 0.85 (P < 0.001) of the variability of DXA values in the corresponding age groups of boys. Similarly, reasonable estimates of DXA values could be obtained from age, weight, height, and BMI in girls over 13 years, and from age, weight, height, BMI, and waist circumference in girls under 13 years, respectively, of 0.77 and 0.83 (P < 0.001). Correlations between robust Gaussian Bayesian network (RGBN) predictions and DXA measurements were highly significant, averaging 0.87 for boys and 0.82 for girls (P < 0.001). CONCLUSIONS: The results revealed that, based on the present study's predictive models, adolescents' body composition might be estimated by input anthropometric information. Given the flexibility and modeling of the present method to test different motivated hypotheses, its application to body compositional data is highly appealing.

Following the Trace of HVS II Mitochondrial Region Within the Nine Iranian Ethnic Groups Based on Genetic Population Analysis.

The Iranian gene pool is seen as an important human genetic resource for investigating the region connecting Mesopotamia and the Iranian plateau. The main objective of this study was to explore gene flow in nine Iranian ethnic/subpopulation groups (402 samples) by examining mtDNA HVS2 sequence variations. This then allowed us to detect mtDNA HVS2 sequence mutations in two independent thalassemia and cystic fibrosis patient sample groups. The patient groups did not explicitly belong to any of the aforementioned nine subpopulations. Across all subpopulations, the haplogroups B4a1c3a, H2a2a1, N10b, H2a2a2, and J1 were seen to be predominant. High haplogroup diversities along with admixture of the exotic groups were observed in this study. The Arab subpopulation was shown to be independent from the others. It was revealed that there is a far distant relationship between Arab and Azeri groups. The thalassemia patient group, represented an almost random sample of most Iranian ethnic groups, and revealed few significant differences (P < 0.05) in their HVS2 sequence. It turned out that the IVS II-I (G → A) mutation in the thalassemia ß-globin gene was highly significant. Since the thalassemia patients in the present study represent many unique haplotypes, we can begin to comprehend the importance of mtDNA with this disease and the necessity for more studies in this context.

Genome-Wide Characterization and Expression Analysis of Fatty acid Desaturase Gene Family in Poplar.

Fatty acid desaturases (FADs) modulate carbon-carbon single bonds to form carbon-carbon double bonds in acyl chains, leading to unsaturated fatty acids (UFAs) that have vital roles in plant growth and development and their response to environmental stresses. In this study, a total of 23 Populus trichocarpaFAD (PtFAD) candidates were identified from the poplar genome and clustered into seven clades, including FAB2, FAD2, FAD3/7/8, FAD5, FAD6, DSD, and SLD. The exon-intron compositions and conserved motifs of the PtFADs, clustered into the same clade, were considerably conserved. It was found that segmental duplication events are predominantly attributable to the PtFAD gene family expansion. Several hormone- and stress-responsive elements in the PtFAD promoters implied that the expression of the PtFAD members was complicatedly regulated. A gene expression pattern analysis revealed that some PtFAD mRNA levels were significantly induced by abiotic stress. An interaction proteins and gene ontology (GO) analysis indicated that the PtFADs are closely associated with the UFAs biosynthesis. In addition, the UFA contents in poplars were significantly changed under drought and salt stresses, especially the ratio of linoleic and linolenic acids. The integration of the PtFAD expression patterns and UFA contents showed that the abiotic stress-induced PtFAD3/7/8 members mediating the conversion of linoleic and linolenic acids play vital roles in response to osmotic stress. This study highlights the profiles and functions of the PtFADs and identifies some valuable genes for forest improvements.

Non-extensive thermodynamic entropy to predict the dynamics behavior of COVID-19.

The current world observations in COVID-19 are hardly tractable as a whole, making situations of information to be incompleteness. In pandemic era, mathematical modeling helps epidemiological scientists to take informing decisions about pandemic planning and predict the disease behavior in the future. In this work, we proposed a non-extensive entropy-based model on the thermodynamic approach for predicting the dynamics of COVID-19 disease. To do so, the epidemic details were considered into a single and time-dependent coefficients model. Their four constraints, including the existence of a maximum point were determined analytically. The model was worked out to give a log-normal distribution for the spread rate using the Tsallis entropy. The width of the distribution function was characterized by maximizing the rate of entropy production. The model predicted the number of daily cases and daily deaths with a fairly good agreement with the World Health Organization (WHO) reported data for world-wide, Iran and China over 2019-2020-time span. The proposed model in this work can be further calibrated to fit on different complex distribution COVID-19 data over different range of times.

Genetic analysis of sexual size dimorphism in Markhoz goat.

Genetic bases of sexual size dimorphism (SSD) in Markhoz goat (5268 kids descended from 242 sires and 1499 dams) were unraveled as it was thought that sex-specific genetic mechanism is in the place governing SSD of birth weight (BW), weaning weight at 90 days of age (WW_90d), and post-weaning weights at 6 (W6), 9 (W9), and 12 (W12) months of age. Male kids excelled for BW, WW_90d, W6, W9, and W12 than their female counterparts in the tune of 10, 17, 14, 17, and 23%, respectively. Estimates of sexual dimorphism levels (expressed as M/F) were 1.09, 1.17, 1.14, 1.17, and 1.23 for BW, WW_90d, W6, W9, and W12, respectively, which indicated relatively low levels of sexual size dimorphism in the studied traits. Though the additive genetic, residual and phenotypic variances were higher in males than females, for mostly all studied traits, but the heritability estimates for all traits except birth weight were higher in females. Differences in direct and maternal effects between male and female kids indicated that body weights traits could be treated as separate trait for male and female kids. Cross-sex genetic correlations revealed that almost all ages, genetic correlations between the two sexes, were high, and the lowest estimate (0.88) was for W6, which highlighted this trait as the most dimorphic trait in this breed. High and positive genetic correlations between the sexes indicated that selection for body weight in males would result in a correlated response in females and vice versa and, consequently, would prevent phenotypic divergence.

Bayesian estimate of genetic parameters for growth traits in Lori Bakhtiari sheep.

The information of birth (10,017 records), weaning (9439 records), 6 months (7669 records), 9 months (4536 records), and yearling weights (417 records) collected from 1989 to 2016 by the Lori Bakhtiari (Sholi) sheep breeding station located in Shahrekord were used to estimate the genotypic and phenotypic parameters of growth traits of Lori Bakhtiari sheep. The components of variance and genetic parameters were estimated by the Bayesian statistical method based on the Gibbs sampling technique due to the high accuracy of this method. Factors including birth year, lamb sex, birth type, and maternal age at lambing have significant effects on all of these traits (P < 0.01) and were considered fixed effects in the statistical model for estimation of genetic parameters. Lamb weight at weaning was used as a covariate in the model. Based on the models with the lowest Akaike information criterion, direct heritability for birth, weaning, 6-month, 9-month, and yearling weights were 0.36, 0.18, 0.21, 0.27, and 0.32, respectively. The moderate heritability obtained for the studied traits pointed up the effectiveness of selection in genetic improvement, but the environmental conditions should be improved for better performance of weight traits.

WITHDRAWN:Identification of bovine uterine transcriptomic hub genes using Bayesian network algorithms.

Ahead of Print article withdrawn by publisher.

An Investigation on the Expression Level of Interleukin 10 (IL-10) in the Healthy and Mastitic Holstein Cows and the Bioinformatics Analysis of Nucleosome Profile.

Cytokines are immune regulators that play an essential role in regulating immune response against various infections. The present study focused on the possible association between the expression level of Interleukin 10 (IL-10) in blood and milk samples of 25 healthy and 25 mastitic cows in Fars province, Iran, using a quantitative real-time PCR assay. The experimental groups were categorized according to the number of calvings. The expression level of IL-10 was significantly higher in the blood and milk samples of mastitic cows compared to the healthy ones. Concomitant to increasing the number of calving, a numerical elevation in the expression of IL-10 in blood was observed (P < 0.05). The bioinformatics analysis of IL-10 gene revealed the promoter, exon-intron regions, and nucleosome profile. The nucleosome occupancy site was finally predicted using NUPOP software. Our result indicated that the promoter was not exactly placed in the nucleosome region, which was finally aimed to predict the position and expression of IL-10 gene in the mastitic cows.

Genetic variance components of the growth curve for Isfahan indigenous chicken.

BACKGROUND: Being able to model a growth curve using three or four non-linear functional parameters could help explain the growth phenomenon in a precise way and would allow the comparison of an animal's development rate, optimize management and feeding strategies and guide animal production strategies. OBJECTIVE: The goal of this study was to estimate the genetic parameters of growth traits of Isfahan indigenous chicken in Iran and to determine the best non-linear model describing the growth curve. METHODS: The prediction of additive genetic parameters was performed using the REML method by WOMBAT. Direct heritability of the studied traits and genetic correlations between them were obtained. The Logistic, Gompertz, von Bertalanffy, Brody, Negative exponential, Weibull, Janoschek and Bridges models were compared based on the coefficient of determination (R2 ), mean square error (MSE) and akaike information criterion. RESULTS: The Gompertz model was identified as the best model for describing the growth curve for Isfahan native chicken. The heritability of maturity weights (A), initial weight (B) and maturity rate (K) parameters were 0.223 ± 0.002, 0.016 ± 0.005 and 0.087 ± 0.001, respectively. CONCLUSION: This study shows that Isfahan indigenous chicken has the genetic potential for improving growth and reproduction based on their desirable heritabilities and correlations using appropriate models.

Gene network reveals LASP1, TUBA1C, and S100A6 are likely playing regulatory roles in multiple sclerosis.

Introduction: Multiple sclerosis (MS), a non-contagious and chronic disease of the central nervous system, is an unpredictable and indirectly inherited disease affecting different people in different ways. Using Omics platforms genomics, transcriptomics, proteomics, epigenomics, interactomics, and metabolomics database, it is now possible to construct sound systems biology models to extract full knowledge of the MS and recognize the pathway to uncover the personalized therapeutic tools. Methods: In this study, we used several Bayesian Networks in order to find the transcriptional gene regulation networks that drive MS disease. We used a set of BN algorithms using the R add-on package bnlearn. The BN results underwent further downstream analysis and were validated using a wide range of Cytoscape algorithms, web based computational tools and qPCR amplification of blood samples from 56 MS patients and 44 healthy controls. The results were semantically integrated to improve understanding of the complex molecular architecture underlying MS, distinguishing distinct metabolic pathways and providing a valuable foundation for the discovery of involved genes and possibly new treatments. Results: Results show that the LASP1, TUBA1C, and S100A6 genes were most likely playing a biological role in MS development. Results from qPCR showed a significant increase (P < 0.05) in LASP1 and S100A6 gene expression levels in MS patients compared to that in controls. However, a significant down regulation of TUBA1C gene was observed in the same comparison. Conclusion: This study provides potential diagnostic and therapeutic biomarkers for enhanced understanding of gene regulation underlying MS.