Vector field statistical analysis of kinematic and force trajectories

When investigating the dynamics of three-dimensional multi-body biomechanical systems it is often difficult to derive spatiotemporally directed predictions regarding experimentally induced effects. A paradigm of ‘non-directed’ hypothesis testing has emerged in the literature as a result. Non-directed analyses typically consist of ad hoc scalar extraction, an approach which substantially simplifies the original, highly multivariate datasets (many time points, many vector components). This paper describes a commensurately multivariate method as an alternative to scalar extraction. The method, called ‘statistical parametric mapping’ (SPM), uses random field theory to objectively identify field regions which co-vary significantly with the experimental design. We compared SPM to scalar extraction by re-analyzing three publicly available datasets: 3D knee kinematics, a ten-muscle force system, and 3D ground reaction forces. Scalar extraction was found to bias the analyses of all three datasets by failing to consider sufficient portions of the dataset, and/or by failing to consider covariance amongst vector components. SPM overcame both problems by conducting hypothesis testing at the (massively multivariate) vector trajectory level, with random field corrections simultaneously accounting for temporal correlation and vector covariance. While SPM has been widely demonstrated to be effective for analyzing 3D scalar fields, the current results are the first to demonstrate its effectiveness for 1D vector field analysis. It was concluded that SPM offers a generalized, statistically comprehensive solution to scalar extraction's over-simplification of vector trajectories, thereby making it useful for objectively guiding analyses of complex biomechanical systems.     

Production of huitlacoche, Ustilago maydis: timing inoculation and controlling pollination

Huitlacoche is the name given to young, fleshy, edible galls that form when ears of Zea mays are infected by Ustilago maydis. Huitlacoche is processed and sold fresh at markets in Mexico. Interest has increased recently in producing U. maydis as a specialty mushroom in the United States. Silk-channel inoculation methods developed to evaluate common smut resistance in maize can be used to produce huitlacoche commercially. This research assessed the effects of time of inoculation and preventing pollination on the severity of ear galls and yield of huitlacoche produced by inoculating silks with U. maydis. Yield of huitlacoche and severity of ear galls were closely related, as was evident from highly significant linear or curvilinear regressions. Severity and yield were greatest when ears were inoculated 4-8 d after the mid-silk growth stage. Ear galls were 5-15% more severe and yield of huitlacoche was 18-150% greater on ears that were not pollinated, compared to those that were pollinated. Maximum yield of huitlacoche was 131 g ear(-1) from unpollinated male-sterile field corn inoculated 6 d after the mid-silk growth stage and 92 g ear(-1) from detasseled sweet corn inoculated 6 d after mid-silk. About 25% of the total weight of ears consisted of marketable huitlacoche when yields were highest. Quality of huitlacoche was not affected by time of inoculation or pollination treatments, but quality of huitlacoche harvested 12-14 d after inoculation was unacceptable primarily due to lack of teliospores, which affected color and flavor.     

Acid-sensing ion channel 3 mediates peripheral anti-hyperalgesia effects of acupuncture in mice inflammatory pain

Background  

Peripheral tissue inflammation initiates hyperalgesia accompanied by tissue acidosis, nociceptor activation, and inflammation mediators. Recent studies have suggested a significantly increased expression of acid-sensing ion channel 3 (ASIC3) in both carrageenan- and complete Freund's adjuvant (CFA)-induced inflammation. This study tested the hypothesis that acupuncture is curative for mechanical hyperalgesia induced by peripheral inflammation.     

Protein structure similarity from principle component correlation analysis

Background  

Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD) in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities.     

Radial force distribution changes associated with tangential force production in cylindrical grasping, and the importance of anatomical registration

Radial force (F(r)) distributions describe grip force coordination about a cylindrical object. Recent studies have employed only explicit F(r) tasks, and have not normalized for anatomical variance when considering F(r) distributions. The goals of the present study were (i) to explore F(r) during tangential force production tasks, and (ii) to examine the extent to which anatomical registration (i.e. spatial normalization of anatomically analogous structures) could improve signal detectability in F(r) data. Twelve subjects grasped a vertically oriented cylindrical handle (diameter=6 cm) and matched target upward tangential forces of 10, 20, and 30 N. F(r) data were measured using a flexible pressure mat with an angular resolution of 4.8°, and were registered using piecewise-linear interpolation between five manually identified points-of-interest. Results indicate that F(r) was primarily limited to three contact regions: the distal thumb, the distal fingers, and the fingers' metatacarpal heads, and that, while increases in tangential force caused significant increases in F(r) for these regions, they did not significantly affect the F(r) distribution across the hand. Registration was found to substantially reduce between-subject variability, as indicated by both accentuated F(r) trends, and amplification of the test statistic. These results imply that, while subjects focus F(r) primarily on three anatomical regions during cylindrical grasp, inter-subject anatomical differences introduce a variability that, if not corrected for via registration, may compromise one's ability to draw anatomically relevant conclusions from grasping force data.     

Assessing the significance of pedobarographic signals using random field theory

Traditional pedobarographic statistical analyses are conducted over discrete regions. Recent studies have demonstrated that regionalization can corrupt pedobarographic field data through conflation when arbitrary dividing lines inappropriately delineate smooth field processes. An alternative is to register images such that homologous structures optimally overlap and then conduct statistical tests at each pixel to generate statistical parametric maps (SPMs). The significance of SPM processes may be assessed within the framework of random field theory (RFT). RFT is ideally suited to pedobarographic image analysis because its fundamental data unit is a lattice sampling of a smooth and continuous spatial field. To correct for the vast number of multiple comparisons inherent in such data, recent pedobarographic studies have employed a Bonferroni correction to retain a constant family-wise error rate. This approach unfortunately neglects the spatial correlation of neighbouring pixels, so provides an overly conservative (albeit valid) statistical threshold. RFT generally relaxes the threshold depending on field smoothness and on the geometry of the search area, but it also provides a framework for assigning p values to suprathreshold clusters based on their spatial extent. The current paper provides an overview of basic RFT concepts and uses simulated and experimental data to validate both RFT-relevant field smoothness estimations and RFT predictions regarding the topological characteristics of random pedobarographic fields. Finally, previously published experimental data are re-analysed using RFT inference procedures to demonstrate how RFT yields easily understandable statistical results that may be incorporated into routine clinical and laboratory analyses.     

Conditional random pattern model for copy number aberration detection

Background  

DNA copy number aberration (CNA) is very important in the pathogenesis of tumors and other diseases. For example, CNAs may result in suppression of anti-oncogenes and activation of oncogenes, which would cause certain types of cancers. High density single nucleotide polymorphism (SNP) array data is widely used for the CNA detection. However, it is nontrivial to detect the CNA automatically because the signals obtained from high density SNP arrays often have low signal-to-noise ratio (SNR), which might be caused by whole genome amplification, mixtures of normal and tumor cells, experimental noise or other technical limitations. With the reduction in SNR, many false CNA regions are often detected and the true CNA regions are missed. Thus, more sophisticated statistical models are needed to make the CNAs detection, using the low SNR signals, more robust and reliable.     

Knee and Hip Joint Kinematics Predict Quadriceps and Hamstrings Neuromuscular Activation Patterns in Drop Jump Landings

PurposeThe purpose was to assess if variation in sagittal plane landing kinematics is associated with variation in neuromuscular activation patterns of the quadriceps-hamstrings muscle groups during drop vertical jumps (DVJ).MethodsFifty female athletes performed three DVJ. The relationship between peak knee and hip flexion angles and the amplitude of four EMG vectors was investigated with trajectory-level canonical correlation analyses over the entire time period of the landing phase. EMG vectors consisted of the {vastus medialis(VM),vastus lateralis(VL)}, {vastus medialis(VM),hamstring medialis(HM)}, {hamstring medialis(HM),hamstring lateralis(HL)} and the {vastus lateralis(VL),hamstring lateralis(HL)}. To estimate the contribution of each individual muscle, linear regressions were also conducted using one-dimensional statistical parametric mapping.ResultsThe peak knee flexion angle was significantly positively associated with the amplitudes of the {VM,HM} and {HM,HL} during the preparatory and initial contact phase and with the {VL,HL} vector during the peak loading phase (p<0.05). Small peak knee flexion angles were significantly associated with higher HM amplitudes during the preparatory and initial contact phase (p<0.001). The amplitudes of the {VM,VL} and {VL,HL} were significantly positively associated with the peak hip flexion angle during the peak loading phase (p<0.05). Small peak hip flexion angles were significantly associated with higher VL amplitudes during the peak loading phase (p = 0.001). Higher external knee abduction and flexion moments were found in participants landing with less flexed knee and hip joints (p<0.001).ConclusionThis study demonstrated clear associations between neuromuscular activation patterns and landing kinematics in the sagittal plane during specific parts of the landing. These findings have indicated that an erect landing pattern, characterized by less hip and knee flexion, was significantly associated with an increased medial and posterior neuromuscular activation (dominant hamstrings medialis activity) during the preparatory and initial contact phase and an increased lateral neuromuscular activation (dominant vastus lateralis activity) during the peak loading phase.