BIOMECHANICAL EFFECT OF JUMPING SPEED ON THE PYRAMIDING BOX HOPS

The purpose of this study was to compare three different jumping speeds (60 bpm, 75 bpm and 90 bpm) while performing pyramiding box hops in order to investigate the optimal rate for post-injured athletes in the return to sport phase of rehabilitation. Twelve healthy, competitive male athletes with specialty in jump were recruited from track and field team. Kinematical and kinetic data of lower extremities were collected via three-dimensional motion analysis system and two force plateforms. One-way ANOVA (SPSS) was used to determine difference among rates. Less hip adduction, knee valgus and knee valgus/varus moments were found at the rate of 90 bpm. Therefore, performing pyramiding box hops at the rate of 90 bpm may be more pertinent for post-injured athletes with ACL injury

miR-638 is a new biomarker for outcome prediction of non-small cell lung cancer patients receiving chemotherapy.

MicroRNAs (miRNAs), a class of small non-coding RNAs, mediate gene expression by either cleaving target mRNAs or inhibiting their translation. They have key roles in the tumorigenesis of several cancers, including non-small cell lung cancer (NSCLC). The aim of this study was to investigate the clinical significance of miR-638 in the evaluation of NSCLC patient prognosis in response to chemotherapy. First, we detected miR-638 expression levels in vitro in the culture supernatants of the NSCLC cell line SPC-A1 treated with cisplatin, as well as the apoptosis rates of SPC-A1. Second, serum miR-638 expression levels were detected in vivo by using nude mice xenograft models bearing SPC-A1 with and without cisplatin treatment. In the clinic, the serum miR-638 levels of 200 cases of NSCLC patients before and after chemotherapy were determined by quantitative real-time PCR, and the associations of clinicopathological features with miR-638 expression patterns after chemotherapy were analyzed. Our data helped in demonstrating that cisplatin induced apoptosis of the SPC-A1 cells in a dose- and time-dependent manner accompanied by increased miR-638 expression levels in the culture supernatants. In vivo data further revealed that cisplatin induced miR-638 upregulation in the serum derived from mice xenograft models, and in NSCLC patient sera, miR-638 expression patterns after chemotherapy significantly correlated with lymph node metastasis. Moreover, survival analyses revealed that patients who had increased miR-638 levels after chemotherapy showed significantly longer survival time than those who had decreased miR-638 levels. Our findings suggest that serum miR-638 levels are associated with the survival of NSCLC patients and may be considered a potential independent predictor for NSCLC prognosis

Pseudogap, Superconducting Energy Scale, and Fermi Arcs in Underdoped Cuprate Superconductors

Through the measurements of magnetic field dependence of specific heat in $La_{2-x}Sr_xCuO_4$ in zero temperature limit, we determined the nodal slope $v_\Delta$ of the quasiparticle gap. It is found that $v_\Delta$ has a very similar doping dependence of the pseudogap temperature $T^*$ or value $\Delta_p$. Meanwhile the virtual maximum gap at ($\pi,0$) derived from $v_\Delta$ is found to follow the simple relation $\Delta_q=0.46k_BT^*$ upon changing the doping concentration. This strongly suggests a close relationship between the pseudogap and superconductivity. It is further found that the superconducting transition temperature is determined by both the residual density of states of the pseudogap phase and the nodal gap slope in the zero temperature limit, namely, $T_c \approx \beta v_\Delta \gamma_n(0)$, where $\gamma_n(0)$ is the extracted zero temperature value of the normal state specific heat coefficient which is proportional to the size of the residual Fermi arc $k_{arc}$. This manifests that the superconductivity may be formed by forming a new gap on the Fermi arcs near nodes below $T_c$. These observations mimic the key predictions of the SU(2) slave boson theory based on the general resonating-valence-bond (RVB) picture.Comment: 6 pages, 6 figures, to be published in Phys. Rev.

MeInfoText 2.0: gene methylation and cancer relation extraction from biomedical literature

<p>Abstract</p> <p>Background</p> <p>DNA methylation is regarded as a potential biomarker in the diagnosis and treatment of cancer. The relations between aberrant gene methylation and cancer development have been identified by a number of recent scientific studies. In a previous work, we used co-occurrences to mine those associations and compiled the MeInfoText 1.0 database. To reduce the amount of manual curation and improve the accuracy of relation extraction, we have now developed MeInfoText 2.0, which uses a machine learning-based approach to extract gene methylation-cancer relations.</p> <p>Description</p> <p>Two maximum entropy models are trained to predict if aberrant gene methylation is related to any type of cancer mentioned in the literature. After evaluation based on 10-fold cross-validation, the average precision/recall rates of the two models are 94.7/90.1 and 91.8/90% respectively. MeInfoText 2.0 provides the gene methylation profiles of different types of human cancer. The extracted relations with maximum probability, evidence sentences, and specific gene information are also retrievable. The database is available at <url>http://bws.iis.sinica.edu.tw:8081/MeInfoText2/</url>.</p> <p>Conclusion</p> <p>The previous version, MeInfoText, was developed by using association rules, whereas MeInfoText 2.0 is based on a new framework that combines machine learning, dictionary lookup and pattern matching for epigenetics information extraction. The results of experiments show that MeInfoText 2.0 outperforms existing tools in many respects. To the best of our knowledge, this is the first study that uses a hybrid approach to extract gene methylation-cancer relations. It is also the first attempt to develop a gene methylation and cancer relation corpus.</p