Associations of Transcription Factor 21 Gene Polymorphisms with the Growth and Body Composition Traits in Broilers.

This study aims to identify molecular marker loci that could be applied in broiler breeding programs. In this study, we used public databases to locate the Transcription factor 21 (TCF21) gene that affected the economically important traits in broilers. Ten single nucleotide polymorphisms were detected in the TCF21 gene by monoclonal sequencing. The polymorphisms of these 10 SNPs in the TCF21 gene were significantly associated (p < 0.05) with multiple growth and body composition traits. Furthermore, the TT genotype of g.-911T>G was identified to significantly increase the heart weight trait without affecting the negative traits, such as abdominal fat and reproduction by multiple methods. Thus, it was speculated that the g.-911T>G identified in the TCF21 gene might be used in marker-assisted selection in the broiler breeding program.

Genome-wide association studies for growth traits in broilers.

BACKGROUND: The identification of markers and genes for growth traits may not only benefit for marker assist selection /genomic selection but also provide important information for understanding the genetic foundation of growth traits in broilers. RESULTS: In the current study, we estimated the genetic parameters of eight growth traits in broilers and carried out the genome-wide association studies for these growth traits. A total of 113 QTNs discovered by multiple methods together, and some genes, including ACTA1, IGF2BP1, TAPT1, LDB2, PRKCA, TGFBR2, GLI3, SLC16A7, INHBA, BAMBI, APCDD1, GPR39, and GATA4, were identified as important candidate genes for rapid growth in broilers. CONCLUSIONS: The results of this study will provide important information for understanding the genetic foundation of growth traits in broilers.

[Three-dimensional spine morphology measuring technology for daily surface monitoring].

In order to conduct surface monitoring of the three-dimensional spine morphology of the human body in daily life, a spine morphology measuring method using "single camera, multi-view" to construct stereo vision is proposed. The images of the back of the human body with landmarks of spinous process are captured from multiple angles by moving a single camera, and based on the "Zhang Zhengyou calibration method" and the triangulation principle of binocular stereo vision, the spatial conversion matrices corresponding to each other between all images and the 3D coordinates of the landmarks are calculated. Then the spine evaluation angle used to evaluate the spine morphology is further calculated. The tests' results showed that the spine evaluation angle error of this method is within ±3°, and the correlation between the results and the X-ray film Cobb angles is 0.871. The visual detection algorithm used in this paper is non-radioactive, and because only one camera is used in the measurement process and there is no need to pre-set the camera's shooting pose, the operation is simple. The research results of this article can be used in a mobile phone-based intelligent detection system, which will be suitable for the group survey of scoliosis in communities, schools, families and other occasions, as well as for the long-term follow-up of confirmed patients. This will provide a reference for doctors to diagnose the condition, predict the development trend of the condition, and formulate treatment plans.

Haplotype-based genome-wide association studies for carcass and growth traits in chicken.

There have been several genome-wide association study (GWAS) reported for carcass, growth, and meat traits in chickens. Most of these studies have been based on single SNPs GWAS. In contrast, haplotype-based GWAS reports have been limited. In the present study, 2 Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF) and genotyped with the chicken 60K SNP chip were used to perform a haplotype-based GWAS. The lean and fat chicken lines were selected for abdominal fat content for 11 yr. Abdominal fat weight was significantly different between the 2 lines; however, there was no difference for body weight between the lean and fat lines. A total of 132 haplotype windows were significantly associated with abdominal fat weight. These significantly associated haplotype windows were primarily located on chromosomes 2, 4, 8, 10, and 26. Seven candidate genes, including SHH, LMBR1, FGF7, IL16, PLIN1, IGF1R, and SLC16A1, were located within these associated regions. These genes may play important roles in the control of abdominal fat content. Two regions on chromosomes 3 and 10 were significantly associated with testis weight. These 2 regions were previously detected by the single SNP GWAS using this same resource population. TCF21 on chromosome 3 was identified as a potentially important candidate gene for testis growth and development based on gene expression analysis and the reported function of this gene. TCF12, which was previously detected in our SNP by SNP interaction analysis, was located in a region on chromosome 10 that was significantly associated with testis weight. Six candidate genes, including TNFRSF1B, PLOD1, NPPC, MTHFR, EPHB2, and SLC35A3, on chromosome 21 may play important roles in bone development based on the known function of these genes. In addition, several regions were significantly associated with other carcass and growth traits, but no candidate genes were identified. The results of the present study may be helpful in understanding the genetic mechanisms of carcass and growth traits in chickens.

Advanced Hand Gesture Prediction Robust to Electrode Shift with an Arbitrary Angle.

Recent advances in myoelectric controlled techniques have made the surface electromyogram (sEMG)-based sensing armband a promising candidate for acquiring bioelectric signals in a simple and convenient way. However, inevitable electrode shift as a non-negligible defect commonly causes a trained classifier requiring continuous recalibrations. In this study, a novel hand gesture prediction is firstly proposed; it is robust to electrode shift with arbitrary angle. Unlike real-time recognition which outputs target gestures only after the termination of hand motions, our proposed advanced prediction can provide the same results, even before the completion of signal collection. Moreover, by combining interpolated peak location and preset synchronous gesture, the developed simplified rapid electrode shift detection and correction at random rather than previous fixed angles are realized. Experimental results demonstrate that it is possible to achieve both electrode shift detection with high precision and gesture prediction with high accuracy. This study provides a new insight into electrode shift robustness which brings gesture prediction a step closer to practical applications.

Genome-wide association study for plasma very low-density lipoprotein concentration in chicken.

The plasma very low-density lipoprotein (VLDL) concentration is an effective blood biochemical indicator that could be used to select lean chicken lines. In the current study, we used Genome-wide association study (GWAS) method to detect SNPs with significant effects on plasma VLDL concentration. As a result, 38 SNPs significantly associated with plasma VLDL concentration were identified using at least one of the three mixed linear model (MLM) packages, including GRAMMAR, EMMAX and GEMMA. Nearly, all these SNPs with significant effects on plasma VLDL concentration (except Gga_rs16160897) have significantly different allele frequencies between lean and fat lines. The 1-Mb regions surrounding these 38 SNPs were extracted, and twelve important regions were obtained after combining the overlaps. A total of 122 genes in these twelve important regions were detected. Among these genes, LRRK2, ABCD2, TLR4, E2F1, SUGP1, NCAN, KLF2 and RAB8A were identified as important genes for plasma VLDL concentration based on their basic functions. The results of this study may supply useful information to select lean chicken lines.

Age- and Parkinson's disease-related evaluation of gait by General Tau Theory.

The degeneration of postural control in the elderly and patients with Parkinson's disease (PD) can be debilitating and may lead to increased fall risk. This study evaluated the changes in postural control during gait affected by PD and aging using a new method based on the General Tau Theory. Fifteen patients with PD, 11 healthy old adults (HOs), and 15 healthy young adults (HYs) were recruited. Foot trajectories of each participant were monitored during walking by a three-camera Optotrak Certus(®) motion capture system. The anteroposterior direction of foot movement during stepping was analyzed by tau-G and tau-J guidance strategies. Two linear regression analyses suggested that the tau of the step-gap was strongly coupled onto the tau-J guidance during walking. The regression slope K could estimate the coupling ratio in the tau-coupling equation which reflects the performance of postural control during gait. The mean K value for the PD group, which was highest among the three groups, was approximately 0.5. Therefore, participants in the PD group walked with the poorest postural control and exhibited a relatively hard contact with the endpoint during stepping when compared with those in the HO and HY groups. The HY and HO groups obtained mean K values significantly lower than 0.5, which indicated that the gait was well controlled and ended at low speed with low deceleration. However, the HO group showed a decreased tendency for postural control, in which the mean K value was significantly higher than that of the HY group. The K value was moderately positively correlated with the double support time and negatively correlated with the stride length and walking speed. The tau-J coupling ratio can provide additional insight into gait disturbances and may serve as a reliable, objective, and quantitative tool to evaluate dynamic postural control during walking.

[Research of contour analysis on endoscopy navigation].

In this paper, a new method of contour analysis is presented to find path in endoscopy navigation. At first, edge detection is used to endoscope image. Then we do skeleton extraction and connect the edge skeleton to contours by grouping criteria. At last we can get navigation information by analyzing the contours. Experiments show that this algorithm has good precision and stability.