Assistive robotic device: evaluation of intelligent algorithms

Assistive robotic devices can be used to help people with upper body disabilities gaining more autonomy in their daily life. Although basic motions such as positioning and orienting an assistive robot gripper in space allow performance of many tasks, it might be time consuming and tedious to perform more complex tasks. To overcome these difficulties, improvements can be implemented at different levels, such as mechanical design, control interfaces and intelligent control algorithms. In order to guide the design of solutions, it is important to assess the impact and potential of different innovations. This paper thus presents the evaluation of three intelligent algorithms aiming to improve the performance of the JACO robotic arm (Kinova Robotics). The evaluated algorithms are 'preset position', 'fluidity filter' and 'drinking mode'. The algorithm evaluation was performed with 14 motorized wheelchair's users and showed a statistically significant improvement of the robot's performance.Comment: 4 page

Rare Variants of Putative Candidate Genes Associated With Sporadic Meniere's Disease in East Asian Population

Objectives: The cause of Meniere's disease (MD) is unclear but likely involves genetic and environmental factors. The aim of this study was to investigate the genetic basis underlying MD by screening putative candidate genes for MD. Methods: Sixty-eight patients who met the diagnostic criteria for MD of the Barany Society were included. We performed targeted gene sequencing using next generation sequencing (NGS) panel composed of 45 MD-associated genes. We identified the rare variants causing non-synonymous amino acid changes, stop codons, and insertions/deletions in the coding regions, and excluded the common variants with minor allele frequency >0.01 in public databases. The pathogenicity of the identified variants was analyzed by various predictive tools and protein structural modeling. Results: The average read depth for the targeted regions was 1446.3-fold, and 99.4% of the targeted regions were covered by 20 or more reads, achieving the high quality of the sequencing. After variant filtering, annotation, and interpretation, we identified a total of 15 rare heterozygous variants in 12 (17.6%) sporadic patients. Among them, four variants were detected in familial MD genes (DTNA, FAM136A, DPT), and the remaining 11 in MD-associated genes (PTPN22, NFKB1, CXCL10, TLR2, MTHFR, SLC44A2, NOS3, NOTCH2). Three patients had the variants in two or more genes. All variants were not detected in our healthy controls (n = 100). No significant differences were observed between patients with and without a genetic variant in terms of sex, mean age of onset, bilaterality, the type of MD, and hearing threshold at diagnosis. Conclusions: Our study identified rare variants of putative candidate genes in some of MD patients. The genes were related to the formation of inner ear structures, the immune-associated process, or systemic hemostasis derangement, suggesting the multiple genetic predispositions in the development of MD

Novel associations for hypothyroidism include known autoimmune risk loci

Hypothyroidism is the most common thyroid disorder, affecting about 5% of the general population. Here we present the first large genome-wide association study of hypothyroidism, in 2,564 cases and 24,448 controls from the customer base of 23andMe, Inc., a personal genetics company. We identify four genome-wide significant associations, two of which are well known to be involved with a large spectrum of autoimmune diseases: rs6679677 near _PTPN22_ and rs3184504 in _SH2B3_ (p-values 3.5e-13 and 3.0e-11, respectively). We also report associations with rs4915077 near _VAV3_ (p-value 8.3e-11), another gene involved in immune function, and rs965513 near _FOXE1_ (p-value 3.1e-14). Of these, the association with _PTPN22_ confirms a recent small candidate gene study, and _FOXE1_ was previously known to be associated with thyroid-stimulating hormone (TSH) levels. Although _SH2B3_ has been previously linked with a number of autoimmune diseases, this is the first report of its association with thyroid disease. The _VAV3_ association is novel. These results suggest heterogeneity in the genetic etiology of hypothyroidism, implicating genes involved in both autoimmune disorders and thyroid function. Using a genetic risk profile score based on the top association from each of the four genome-wide significant regions in our study, the relative risk between the highest and lowest deciles of genetic risk is 2.1

Low Digit Ratio Predicts Early Age at Menarche in Colombian Schoolgirls

Background:  The ratio between the lengths of the second and fourth fingers (digit ratio: 2D : 4D), a purported negative correlate of prenatal androgen exposure, has been inversely related to age at menarche. However, a recent study found high digit ratios in carriers of a single variant in the LIN28B gene, which has been linked to delayed menarche. Methods:  We investigated the association of digit ratio and age at menarche in 299 pre‐menarcheal girls aged 5–12 years who participated in a longitudinal cohort study in Bogotá, Colombia. Finger lengths were measured at baseline and the occurrence of menarche was periodically ascertained over a median 32 months of follow‐up. We used time‐to‐event analysis to estimate median ages at menarche as well as hazard ratios for menarche according to tertiles of the digit ratio for each hand. Results:  Estimated median age at menarche was lower for girls in the lowest digit ratio tertile of the right hand compared with those in the highest (12.0 vs. 12.3 years; P ‐value = 0.04). After adjustment for baseline age, height‐ and body mass index‐for‐age z ‐scores, the hazard of menarche was 86% higher in girls of the lowest digit ratio tertile (hazard ratio 1.9 [95% confidence interval 1.2, 2.9]) compared with those in the highest digit ratio tertile of the right hand. No significant associations were found with the left hand. Conclusions:  Digit ratio was positively associated with age at menarche in this longitudinal investigation, consistent with results from a recent gene‐linkage study.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93549/1/j.1365-3016.2012.01310.x.pd

Analyse de la variation intra- et inter-populationnelle : application de deux méthodes craniométriques sur des collections amérindiennes-canadiennes

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

A signature motif mediating selective interactions of BCL11A with the NR2E/F subfamily of orphan nuclear receptors

Despite their physiological importance, selective interactions between nuclear receptors (NRs) and their cofactors are poorly understood. Here, we describe a novel signature motif (F/YSXXLXXL/Y) in the developmental regulator BCL11A that facilitates its selective interaction with members of the NR2E/F subfamily. Two copies of this motif (named here as RID1 and RID2) permit BCL11A to bind COUP-TFs (NR2F1;NR2F2;NR2F6) and Tailless/TLX (NR2E1), whereas RID1, but not RID2, binds PNR (NR2E3). We confirmed the existence of endogenous BCL11A/TLX complexes in mouse cortex tissue. No interactions of RID1 and RID2 with 20 other ligand-binding domains from different NR subtypes were observed. We show that RID1 and RID2 are required for BCL11A-mediated repression of endogenous γ-globin gene and the regulatory non-coding transcript Bgl3, and we identify COUP-TFII binding sites within the Bgl3 locus. In addition to their importance for BCL11A function, we show that F/YSXXLXXL/Y motifs are conserved in other NR cofactors. A single FSXXLXXL motif in the NR-binding SET domain protein NSD1 facilitates its interactions with the NR2E/F subfamily. However, the NSD1 motif incorporates features of both LXXLL and FSXXLXXL motifs, giving it a distinct NR-binding pattern in contrast to other cofactors. In summary, our results provide new insights into the selectivity of NR/cofactor complex formation

Current evidence for a modulation of low back pain by human genetic variants

The manifestation of chronic back pain depends on structural, psychosocial, occupational and genetic influences. Heritability estimates for back pain range from 30% to 45%. Genetic influences are caused by genes affecting intervertebral disc degeneration or the immune response and genes involved in pain perception, signalling and psychological processing. This inter-individual variability which is partly due to genetic differences would require an individualized pain management to prevent the transition from acute to chronic back pain or improve the outcome. The genetic profile may help to define patients at high risk for chronic pain. We summarize genetic factors that (i) impact on intervertebral disc stability, namely Collagen IX, COL9A3, COL11A1, COL11A2, COL1A1, aggrecan (AGAN), cartilage intermediate layer protein, vitamin D receptor, metalloproteinsase-3 (MMP3), MMP9, and thrombospondin-2, (ii) modify inflammation, namely interleukin-1 (IL-1) locus genes and IL-6 and (iii) and pain signalling namely guanine triphosphate (GTP) cyclohydrolase 1, catechol-O-methyltransferase, μ opioid receptor (OPMR1), melanocortin 1 receptor (MC1R), transient receptor potential channel A1 and fatty acid amide hydrolase and analgesic drug metabolism (cytochrome P450 [CYP]2D6, CYP2C9)