Field distribution of epidural electrical stimulation

Epidural electrical stimulation has been applied in clinics for many years. However, there is still a concern about possible injury to spinal nerves. This study investigated electrical field and current density distribution during direct epidural electrical stimulation. Field distribution models were theoretically deduced, while the distribution of potentials and current were analyzed. The current density presented an increase of 70-80%, with one peak value ranging from -85 degrees to 85 degrees between the two stimulated poles. The effect of direct epidural electrical stimulation is mainly on local tissue surrounding the electrodes, concentrated around the two stimulated positions.postprin

A dynamic prediction model for intraoperative somatosensory evoked potential monitoring

This study proposed a support vector regression model applied in prediction of intraoperative somatosensory evoked potential changes associated with physiological and anesthetic changes. This model was developed from probability distribution and support vector machines. The predicted results showed that observed and predicted SEP has similar variation trend with different values, with acceptable errors. With this prediction model, changes of SEP in correlation with non-surgical factors were estimated. Not only the prediction accuracy of SEP has been improved, but also provides the reliability of the classification. It will be helpful to develop an intelligent monitor model based expert system that can make a reliable decision for the potential spinal injury.published_or_final_versio

Trial-to-trial latency variability of somatosensory evoked potentials as a prognostic indicator for surgical management of cervical spondylotic myelopathy

published_or_final_versio

Usefulness of time-frequency patterns of somatosensory evoked potentials in identification of the location of spinal cord injury

postprin

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

PIP5KIβ Selectively Modulates Apical Endocytosis in Polarized Renal Epithelial Cells

Localized synthesis of phosphatidylinositol 4,5-bisphosphate [PtdIns(4,5)P2] at clathrin coated pits (CCPs) is crucial for the recruitment of adaptors and other components of the internalization machinery, as well as for regulating actin dynamics during endocytosis. PtdIns(4,5)P2 is synthesized from phosphatidylinositol 4-phosphate by any of three phosphatidylinositol 5-kinase type I (PIP5KI) isoforms (α, β or γ). PIP5KIβ localizes almost exclusively to the apical surface in polarized mouse cortical collecting duct cells, whereas the other isoforms have a less polarized membrane distribution. We therefore investigated the role of PIP5KI isoforms in endocytosis at the apical and basolateral domains. Endocytosis at the apical surface is known to occur more slowly than at the basolateral surface. Apical endocytosis was selectively stimulated by overexpression of PIP5KIβ whereas the other isoforms had no effect on either apical or basolateral internalization. We found no difference in the affinity for PtdIns(4,5)P2-containing liposomes of the PtdIns(4,5)P2 binding domains of epsin and Dab2, consistent with a generic effect of elevated PtdIns(4,5)P2 on apical endocytosis. Additionally, using apical total internal reflection fluorescence imaging and electron microscopy we found that cells overexpressing PIP5KIβ have fewer apical CCPs but more internalized coated structures than control cells, consistent with enhanced maturation of apical CCPs. Together, our results suggest that synthesis of PtdIns(4,5)P2 mediated by PIP5KIβ is rate limiting for apical but not basolateral endocytosis in polarized kidney cells. PtdIns(4,5)P2 may be required to overcome specific structural constraints that limit the efficiency of apical endocytosis. © 2013 Szalinski et al

Resonances in J/ψ→ϕπ+π−J/\psi \to \phi \pi ^+\pi ^- and ϕK+K−\phi K^+K^-

A partial wave analysis is presented of $J/\psi \to \phi \pi ^+\pi ^-$ and $\phi K^+K^-$ from a sample of 58M $J/\psi$ events in the BES II detector. The $f_0(980)$ is observed clearly in both sets of data, and parameters of the Flatt\' e formula are determined accurately: $M = 965 \pm 8$ (stat) $\pm 6$ (syst) MeV/c$^2$, $g_1 = 165 \pm 10 \pm 15$ MeV/c$^2$, $g_2/g_1 = 4.21 \pm 0.25 \pm 0.21$. The $\phi \pi \pi$ data also exhibit a strong $\pi \pi$ peak centred at $M = 1335$ MeV/c$^2$. It may be fitted with $f_2(1270)$ and a dominant $0^+$ signal made from $f_0(1370)$ interfering with a smaller $f_0(1500)$ component. There is evidence that the $f_0(1370)$ signal is resonant, from interference with $f_2(1270)$. There is also a state in $\pi \pi$ with $M = 1790 ^{+40}_{-30}$ MeV/c$^2$ and $\Gamma = 270 ^{+60}_{-30}$ MeV/c$^2$; spin 0 is preferred over spin 2. This state, $f_0(1790)$, is distinct from $f_0(1710)$. The $\phi K\bar K$ data contain a strong peak due to $f_2'(1525)$. A shoulder on its upper side may be fitted by interference between $f_0(1500)$ and $f_0(1710)$.Comment: 17 pages, 6 figures, 1 table. Submitted to Phys. Lett.

Measurement of the Branching Fraction of J/psi --> pi+ pi- pi0

Using 58 million J/psi and 14 million psi' decays obtained by the BESII experiment, the branching fraction of J/psi --> pi+ pi- pi0 is determined. The result is (2.10+/-0.12)X10^{-2}, which is significantly higher than previous measurements.Comment: 9 pages, 8 figures, RevTex

Search for K_S K_L in psi'' decays

K_S K_L from psi'' decays is searched for using the psi'' data collected by BESII at BEPC, the upper limit of the branching fraction is determined to be B(psi''--> K_S K_L) < 2.1\times 10^{-4} at 90% C. L. The measurement is compared with the prediction of the S- and D-wave mixing model of the charmonia, based on the measurements of the branching fractions of J/psi-->K_S K_L and psi'-->K_S K_L.Comment: 5 pages, 1 figur

First Measurements of eta_c Decaying into K^+K^-2(pi^+pi^-) and 3(pi^+pi^-)

The decays of eta_c to K^+K^-2(pi^+pi^-) and 3(pi^+pi^-) are observed for the first time using a sample of 5.8X10^7 J/\psi events collected by the BESII detector. The product branching fractions are determined to be B(J/\psi-->gamma eta_c)*B(eta_c-->K^+K^-pi^+pi^-pi^+pi^-)=(1.21+-0.32+- 0.23)X10^{-4}$,B(J/\psi-->gamma eta_c)*B(eta_c-->K^{*0}\bar{K}^{*0}pi^+pi^-)= (1.29+-0.43+-0.32)X10^{-4}$, and (J/\psi-->gamma eta_c)* B(eta_c-->pi^+pi^-pi^+pi^-pi^+pi^-)= (2.59+-0.32+-0.48)X10^{-4}. The upper limit for eta_c-->phi pi^+pi^-pi^+pi^- is also obtained as B(J/\psi-->gamma eta_c)*B(eta_c--> phi pi^+pi^-pi^+pi^-)< 6.03 X10^{-5} at the 90% confidence level.Comment: 11 pages, 4 figure