Birth weight and risk of ischemic heart disease: A Mendelian randomization study

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Liver Enzymes and Risk of Ischemic Heart Disease and Type 2 Diabetes Mellitus: A Mendelian Randomization Study

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Interleukin-2 Confers Cardioprotection by Inhibiting Mitochondrial Permeability Transition Pore

In the present study, we determined whether interleukin-2 (IL-2) confers cardioprotection by inhibiting mitochondria permeability transition pore (MPTP) opening. In isolated rat hearts subject to 30 min ischemia and 120 min reperfusion (IR), IL-2 (50 U/ml) decreased the infarct size and LDH release, effects blocked by a selective kappa-opioid receptor antagonist, Nor-BNI (5 microM) or an opener of MPTP, atractyloside (Atr, 20 microM). In isolated ventricular myocytes subjected to anoxia and reoxygenation (AR), which reduced both the amplitude of the electrically induced [Ca2+]i transient and diastolic [Ca2+]i, IL-2 attenuated the AR-induced alterations and their effects were abolished by Atr. In addition, IL-2 attenuated the reduction in calcein fluorescence in myocytes subject to AR and reduced calcium-induced swelling in mitochondria of rat hearts subjected to IR, which were similar to effect of inhibitor of MPTP. The observations indicated that IL-2 confers cardioprotection by inhibiting the MPTP opening.published_or_final_versio

Fine Structure Discussion of Parity-Nonconserving Neutron Scattering at Epithermal Energies

The large magnitude and the sign correlation effect in the parity non-conserving resonant scattering of epithermal neutrons from $^{232}$Th is discussed in terms of a non-collective $2p-1h$ local doorway model. General conclusions are drawn as to the probability of finding large parity violation effects in other regions of the periodic table.Comment: 6 pages, Tex. CTP# 2296, to appear in Z. Phys.

A new method to assess spatial variations of outdoor thermal comfort: Onsite monitoring results and implications for precinct planning

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Emotional Fuzzy Sliding-Mode Control for Unknown Nonlinear Systems

[[abstract]]The brain emotional learning model can be implemented with a simple hardware and processor; however, the learning model cannot model the qualitative aspects of human knowledge. To solve this problem, a fuzzy-based emotional learning model (FELM) with structure and parameter learning is proposed. The membership functions and fuzzy rules can be learned through the derived learning scheme. Further, an emotional fuzzy sliding-mode control (EFSMC) system, which does not need the plant model, is proposed for unknown nonlinear systems. The EFSMC system is applied to an inverted pendulum and a chaotic synchronization. The simulation results with the use of EFSMC system demonstrate the feasibility of FELM learning procedure. The main contributions of this paper are (1) the FELM varies its structure dynamically with a simple computation; (2) the parameter learning imitates the role of emotions in mammalians brain; (3) by combining the advantage of nonsingular terminal sliding-mode control, the EFSMC system provides very high precision and finite-time control performance; (4) the system analysis is given in the sense of the gradient descent method.[[notice]]補正完

Regulators of complement activity mediate inhibitory mechanisms through a common C3b‐binding mode

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Self-Reported Occupational Exposure to HIV and Factors Influencing its Management Practice: A Study of Healthcare Workers in Tumbi and Dodoma Hospitals, Tanzania.

Blood borne infectious agents such as hepatitis B virus (HBV), hepatitis C virus (HCV) and human immune deficiency virus (HIV) constitute a major occupational hazard for healthcare workers (HCWs). To some degree it is inevitable that HCWs sustain injuries from sharp objects such as needles, scalpels and splintered bone during execution of their duties. However, in Tanzania, there is little or no information on factors that influence the practice of managing occupational exposure to HIV by HCWs. This study was conducted to determine the prevalence of self-reported occupational exposure to HIV among HCWs and explore factors that influence the practice of managing occupational exposure to HIV by HCWs in Tanzania. Self-administered questionnaire was designed to gather information of healthcare workers' occupational exposures in the past 12 months and circumstances in which these injuries occurred. Practice of managing occupational exposure was assessed by the following questions: Nearly half of the HCWs had experienced at least one occupational injury in the past 12 months. Though most of the occupational exposures to HIV were experienced by female nurses, non-medical hospital staff received PEP more frequently than nurses and doctors. Doctors and nurses frequently encountered occupational injuries in surgery room and labor room respectively. HCWs with knowledge on the possibility of HIV transmission and those who knew whom to contact in event of occupational exposure to HIV were less likely to have poor practice of managing occupational exposure. Needle stick injuries and splashes are common among HCWs at Tumbi and Dodoma hospitals. Knowledge of the risk of HIV transmission due to occupational exposure and knowing whom to contact in event of exposure predicted practice of managing the exposure. Thus provision of health education on occupational exposure may strengthen healthcare workers' practices to manage occupational exposure

Tracking Target Signal Strengths on a Grid using Sparsity

Multi-target tracking is mainly challenged by the nonlinearity present in the measurement equation, and the difficulty in fast and accurate data association. To overcome these challenges, the present paper introduces a grid-based model in which the state captures target signal strengths on a known spatial grid (TSSG). This model leads to \emph{linear} state and measurement equations, which bypass data association and can afford state estimation via sparsity-aware Kalman filtering (KF). Leveraging the grid-induced sparsity of the novel model, two types of sparsity-cognizant TSSG-KF trackers are developed: one effects sparsity through $\ell_1$-norm regularization, and the other invokes sparsity as an extra measurement. Iterative extended KF and Gauss-Newton algorithms are developed for reduced-complexity tracking, along with accurate error covariance updates for assessing performance of the resultant sparsity-aware state estimators. Based on TSSG state estimates, more informative target position and track estimates can be obtained in a follow-up step, ensuring that track association and position estimation errors do not propagate back into TSSG state estimates. The novel TSSG trackers do not require knowing the number of targets or their signal strengths, and exhibit considerably lower complexity than the benchmark hidden Markov model filter, especially for a large number of targets. Numerical simulations demonstrate that sparsity-cognizant trackers enjoy improved root mean-square error performance at reduced complexity when compared to their sparsity-agnostic counterparts.Comment: Submitted to IEEE Trans. on Signal Processin

Pleiotropic functions of the tumor- and metastasis-suppressing Matrix Metalloproteinase-8 in mammary cancer in MMTV-PyMT transgenic mice

Matrix metalloproteinase-8 (MMP-8; neutrophil collagenase) is an important regulator of innate immunity which has onco-suppressive actions in numerous tumor types