KINEMATIC ANALYSIS OF THE UPPER LIMB AT DIFFERENT IMPACT HEIGHTS IN BASEBALL BATTING

The purpose of this study was to investigate the change in the upper limb motion to three different hitting areas of the strike zone: high, middle, and low. Subjects were ten right-handed male skilled batters of a university baseball team. Data were collected using a three dimensional automatic motion analysis system (Vicon 612). The joint angles of the upper limbs were computed. Comparison of the hitting in the high area vs. low area revealed that to hit the ball in the low area the batter more extended his left elbow, and flexed more his both shoulders and horizontal adduction angle of the left shoulder was large at the phase of the Left upper arm parallel (LUP). At the impact phase he flexed his left elbow more, adduction angle of the left shoulder was small in the case of the high area than the case of the low area. The opposite tendency to the high area was observed in the case of the low area

ADJUSTMENT OF THE LOWER LIMB MOTION AT DIFFERENT IMPACT HEIGHTS IN BASEBALL BATTING

The purpose of this study was to investigate the change in the lower limb motion to three different hitting areas of the strike zone: high, middle, and low. Subjects were 10 right-handed male skilled batters of a university baseball team. Data were collected using a three dimensional automatic motion analysis system (Vicon 612). Joint angles of the lower limbs were computed. Comparison of the hitting in the high area vs. low area revealed that to hit the ball in the low area the batter adjusted the motion of the hip joint by regulating the flexion-extension angle of the both hips from the phase of the Swing start to the phase of the Impact. After that the phase of the Left upper arm parallel abduction angle of the right hip was smaller in case of the high, middle areas than the of the low area, and abduction angle of the left hip was larger in case of the high, middle areas than the low area

A 120-Mpc Periodicity in the Three-Dimensional Distribution of Galaxy Superclusters

Using a new compilation of available data on galaxy clusters and superclusters we present evidence for a quasiregular three-dimensional network of rich superclusters and voids, with the regions of high density separated by about 120 Mpc. We calculate the power spectrum for clusters of galaxies; it has a peak on the wavelength equal to the step of the network; the excess in the amplitude of the spectrum over that of the cold dark matter model is by a factor of 1.4. The probability that the spectrum can be formed within the framework of the standard cosmogony is very small. If the cluster distribution reflects the distribution of all matter (luminous and dark), then there must exists some hithero unknown process that produces regular structure on large scales.Comment: Tex, 6 pages, 2 PostScript figures embedded, accepted by Nature on November 19, 199

Steps toward the power spectrum of matter. I.The mean spectrum of galaxies

We calculate the mean power spectrum of galaxies using published power spectra of galaxies and clusters of galaxies. On small scales we use the power spectrum derived from the 2-dimensional distribution of APM galaxies, on large scales we use power spectra derived from 3-dimensional data for galaxy and cluster samples. Spectra are reduced to real space and to the amplitude of the power spectrum of APM galaxies. Available data indicate the presence of two different populations in the nearby Universe. Clusters of galaxies sample a relatively large region in the Universe where rich, medium and poor superclusters are well represented. Their mean power spectrum has a spike on scale 120 h^{-1}Mpc, followed by an approximate power-law spectrum of index n = -1.9 towards small scales. The power spectrum found from LCRS and IRAS 1.2 Jy surveys is flatter around the maximum, which may represent regions of the Universe with medium-rich and poor superclusters.Comment: LaTex (sty files added), 35 pages, 5 PostScript figures and Table with mean power spectrum embedded, Astrophysical Journal (accepted

Large-scale periodicity in the distribution of QSO absorption-line systems

The spatial-temporal distribution of absorption-line systems (ALSs) observed in QSO spectra within the cosmological redshift interval z = 0.0--4.3 is investigated on the base of our updated catalog of absorption systems. We consider so called metallic systems including basically lines of heavy elements. The sample of the data displays regular variations (with amplitudes ~ 15 -- 20%) in the z-distribution of ALSs as well as in the eta-distribution, where eta is a dimensionless line-of-sight comoving distance, relatively to smoother dependences. The eta-distribution reveals the periodicity with period Delta eta = 0.036 +/- 0.002, which corresponds to a spatial characteristic scale (108 +/- 6) h(-1) Mpc or (alternatively) a temporal interval (350 +/- 20) h(-1) Myr for the LambdaCDM cosmological model. We discuss a possibility of a spatial interpretation of the results treating the pattern obtained as a trace of an order imprinted on the galaxy clustering in the early Universe.Comment: AASTeX, 13 pages, with 9 figures, Accepted for publication in Astrophysics & Space Scienc

Scaling Study of Pure Gauge Lattice QCD by Monte Carlo Renormalization Group Method

The scaling behavior of pure gauge SU(3) in the region $\beta=5.85 - 7.60$ is examined by a Monte Carlo Renormalization Group analysis. The coupling shifts induced by factor 2 blocking are measured both on 32$^4$ and 16$^4$ lattices with high statistics. A systematic deviation from naive 2-loop scaling is clearly seen. The mean field and effective coupling constant schemes explain part, but not all of the deviation. It can be accounted for by a suitable change of coupling constant, including a correction term ${\cal O}(g^7)$ in the 2-loop lattice $\beta$-function. Based on this improvement, $\sqrt{\sigma}/\Lambda_{\overline {MS}}^{n_f=0}$ is estimated to be $2.2(\pm 0.1)$ from the analysis of the string tension $\sigma$.Comment: 4 pages of A4 format including 7-postscript figure

Identification of disease-causing genes using microarray data mining and gene ontology

Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods: We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results: The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions: The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene Ontology information. It predicts marker genes for colon, DLBCL and prostate cancer with a high accuracy. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help in the search for a cure for cancers

Head-to-head comparison of (R)-[11C]verapamil and [18F]MC225 in non-human primates, tracers for measuring P-glycoprotein function

Purpose P-glycoprotein (P-gp) function is altered in several brain disorders; thus, it is of interest to monitor the P-gp function in vivo using PET. (R)-[11C]verapamil is considered the gold standard tracer to measure the P-gp function; however, it presents some drawbacks that limit its use. New P-gp tracers have been developed with improved properties, such as [18F]MC225. This study compares the characteristics of (R)-[11C]verapamil and [18F]MC225 in the same subjects. Methods: Three non-human primates underwent 4 PET scans: 2 with (R)[11C]verapamil and 2 with [18F]MC225, at baseline and after P-gp inhibition. The 30-min PET data were analyzed using 1-Tissue Compartment Model (1-TCM) and metabolite corrected plasma as input function. Tracer kinetic parameters at baseline and after inhibition were compared. Regional differences and simplified methods to quantify the P-gp function were also assessed. Results At baseline, [18F]MC225 VT values were higher, and k2 values were lower than those of (R)-[11C]verapamil, whereas K1 values were not significantly different. After inhibition, VT values of the 2 tracers were similar; however, (R)-[11C]verapamil K1 and k2 values were higher than those of [18F]MC225. Significant regional differences between tracers were found at baseline, which disappeared after inhibition. The positive slope of the SUV-TAC was positively correlated to the K1 and VT of both tracers. Conclusion [18F]MC225 and (R)-[11C]verapamil show comparable sensitivity to measure the P-gp function in non-humanprimates. Moreover, this study highlights the 30-min VT as the best parameter to measure decreases in the P-gp function with both tracers. [18F]MC225 may become the first radiofluorinated tracer able to measure decreases and increases in the P-gp function due to its higher baseline VT

Understanding signaling cascades in melanoma

Understanding regulatory pathways involved in melanoma development and progression has advanced significantly in recent years. It is now appreciated that melanoma is the result of complex changes in multiple signaling pathways that affect growth control, metabolism, motility and the ability to escape cell death programs. Here we review the major signaling pathways currently known to be deregulated in melanoma with an implication to its development and progression. Among these pathways are Ras, B-Raf, MEK, PTEN, phosphatidylinositol-3 kinase (PI3Ks) and Akt which are constitutively activated in a significant number of melanoma tumors, in most cases due to genomic change. Other pathways discussed in this review include the [Janus kinase/signal transducer and activator of transcription (JAK/STAT), transforming growth factor-beta pathways which are also activated in melanoma, although the underlying mechanism is not yet clear. As a paradigm for remodeled signaling pathways, melanoma also offers a unique opportunity for targeted drug development.Fil: Lopez Bergami, Pablo Roberto. Sanford-burnham Medical Research Institute; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Fitchmann, B. Sanford-burnham Medical Research Institute; Estados UnidosFil: Ronai, Ze´ev. Sanford-burnham Medical Research Institute; Estados Unido