5 research outputs found

    Passive coordination of hind limb joints through multi-joint muscles

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    PASSIVE COORDINATION OF HIND LIMB JOINTS THROUGH MULTI-JOINT MUSCLES Violet Campbell, Andrew Sawatsky, Walter Herzog Human Performance Lab, University of Calgary, Kinesiology Program, University of Calgary [email protected]   INTRODUCTION Studies in cats measuring muscle lengths using joint angles show a clear correlation between the movements at the hip, knee, and ankle joints [2]. This correlation could be explained to 70% by a covariance plane between the hip, knee, and ankle joint angles [1]. It has been suggested that the multi-joint muscles may be the origin of the passive limb mechanics [1,4]. EMG recordings show that during cat locomotion, activation of the muscles extending the knee occurs 30-70msec after the knee extension begins; thus the onset of knee extension seems to be controlled passively by the extensor muscles [3]. Furthermore, it has been said that muscles directly change joint angles [4]. The purpose of this study was to examine the effects of multi-joint muscles on the passive joint alignment in the rabbit hind limb. We hypothesize that the hip, knee, and ankle joint angles in the rabbit hind limb are coordinated by passive forces and the passive joint alignment is controlled primarily by the multi-joint muscles. METHODS Five New Zealand white rabbit cadavers were used. The joints were marked with bone pins, and the condyles of the femur were held and the hip joint was passively moved through its range of motion while associated changes in knee and ankle joint angles were measured. Hind limb joint movements were recorded using high speed video. Individual video frames were then extracted and digitized manually to obtain the hip, knee and ankle joint angles. Variance was approximately ±5Âș for each of the joint angles in repeat trials of the same animal. The multi-joint muscles including the biceps femoris, rectus femoris, semitendinosus, plantaris, medial and lateral gastrocnemius, extensor digitorum longus and tensor fascia latae were selectively cut in three hind-limbs, and in a different order for each leg, to identify the contribution of each muscle to the passive coordination of the hind-limb joints.   RESULTS Before any muscles were cut 80-99% of the variability of the knee and ankle joint angles was explained by variations in the hip angle. As multi-joint muscles were cut sequentially the correlation between hip, knee, and ankle joint angles decreased, and was eventually completely lost (Figure 1).   Figure 1. Passive ankle angles (degrees) as a function of   hip angles throughout the entire flexion movement and analyzed every 5˚. The data are from three trials of one rabbit’s hind limb. Blue points (± 1SE) represent the intact leg, orange represents the medial and lateral gastrocnemius removed, and the pink points represent the plantaris was removed in addition to the two heads of the gastrocnemius. DISCUSSION AND CONCLUSIONS Removal of selected two joint muscles changed the relationship between passive hip and knee and between passive hip and ankle angles. For example, when removing the gastrocnemius and plantaris muscles, hip motion did not result in any change in the ankle angle, illustrating that all passive force transmission between the two joints hinges crucially on the two-joint triceps surae muscles (Figure 1). In order to identify the precise contribution of each two-joint muscle to passive force transmission across the rabbit hind limb, multiple experiments with different order of cutting the muscles would have to be implemented. Such an extensive experiment was not possible within the framework of this summer. REFERENCES Bosco, et al.  J Neurophysiol. 76:715-726, 1996.Goslow  et al.  J Morphol. 141:1-42, 1973.Miller et al. Brain Res. 91:217-237, 1975. Shen & Poppele J Neurophysiol. 74:2266-2280, 1995

    Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

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    Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∌38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

    Multiple loci on 8q24 associated with prostate cancer susceptibility

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    Previous studies have identified multiple loci on 8q24 associated with prostate cancer risk. We performed a comprehensive analysis of SNP associations across 8q24 by genotyping tag SNPs in 5,504 prostate cancer cases and 5,834 controls. We confirmed associations at three previously reported loci and identified additional loci in two other linkage disequilibrium blocks (rs1006908: per-allele OR = 0.87, P = 7.9 x 10(-8); rs620861: OR = 0.90, P = 4.8 x 10(-8)). Eight SNPs in five linkage disequilibrium blocks were independently associated with prostate cancer susceptibility

    Identification of seven new prostate cancer susceptibility loci through a genome-wide association study

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    Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. To identify common PrCa susceptibility alleles, we have previously conducted a genome-wide association study in which 541, 129 SNPs were genotyped in 1,854 PrCa cases with clinically detected disease and 1,894 controls. We have now evaluated promising associations in a second stage, in which we genotyped 43,671 SNPs in 3,650 PrCa cases and 3,940 controls, and a third stage, involving an additional 16,229 cases and 14,821 controls from 21 studies. In addition to previously identified loci, we identified a further seven new prostate cancer susceptibility loci on chromosomes 2, 4, 8, 11, and 22 (P=1.6×10−8 to P=2.7×10−33)

    Scripture and reform

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