Semiparametric Normal Transformation Models for Spatially Correlated Survival Data

There is an emerging interest in modeling spatially correlated survival data in biomedical and epidemiological studies. In this paper, we propose a new class of semiparametric normal transformation models for right censored spatially correlated survival data. This class of models assumes that survival outcomes marginally follow a Cox proportional hazard model with unspecified baseline hazard, and their joint distribution is obtained by transforming survival outcomes to normal random variables, whose joint distribution is assumed to be multivariate normal with a spatial correlation structure. A key feature of the class of semiparametric normal transformation models is that it provides a rich class of spatial survival models where regression coefficients have population average interpretation and the spatial dependence of survival times is conveniently modeled using the transformed variables by flexible normal random fields. We study the relationship of the spatial correlation structure of the transformed normal variables and the dependence measures of the original survival times. Direct nonparametric maximum likelihood estimation in such models is practically prohibited due to the high dimensional intractable integration of the likelihood function and the infinite dimensional nuisance baseline hazard parameter. We hence develop a class of spatial semiparametric estimating equations, which conveniently estimate the population-level regression coefficients and the dependence parameters simultaneously. We study the asymptotic properties of the proposed estimators, and show that they are consistent and asymptotically normal. The proposed method is illustrated with an analysis of data from the East Boston Ashma Study and its performance is evaluated using simulations

Testing the Correlation for Clustered Categorical and Censored Discrete Time‐to‐Event Data When Covariates Are Measured without/with Errors

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92373/1/1541-0420.00004.pd

Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

Long short-term memory (LSTM) based acoustic modeling methods have recently been shown to give state-of-the-art performance on some speech recognition tasks. To achieve a further performance improvement, in this research, deep extensions on LSTM are investigated considering that deep hierarchical model has turned out to be more efficient than a shallow one. Motivated by previous research on constructing deep recurrent neural networks (RNNs), alternative deep LSTM architectures are proposed and empirically evaluated on a large vocabulary conversational telephone speech recognition task. Meanwhile, regarding to multi-GPU devices, the training process for LSTM networks is introduced and discussed. Experimental results demonstrate that the deep LSTM networks benefit from the depth and yield the state-of-the-art performance on this task.Comment: submitted to ICASSP 2015 which does not perform blind review

Involvement of the JNK/FOXO3a/Bim Pathway in Neuronal Apoptosis after Hypoxic-Ischemic Brain Damage in Neonatal Rats.

c-Jun N-terminal kinase (JNK) plays a key role in the regulation of neuronal apoptosis. Previous studies have revealed that forkhead transcription factor (FOXO3a) is a critical effector of JNK-mediated tumor suppression. However, it is not clear whether the JNK/FOXO3a pathway is involved in neuronal apoptosis in the developing rat brain after hypoxia-ischemia (HI). In this study, we generated an HI model using postnatal day 7 rats. Fluorescence immunolabeling and Western blot assays were used to detect the distribution and expression of total and phosphorylated JNK and FOXO3a and the pro-apoptotic proteins Bim and CC3. We found that JNK phosphorylation was accompanied by FOXO3a dephosphorylation, which induced FOXO3a translocation into the nucleus, resulting in the upregulation of levels of Bim and CC3 proteins. Furthermore, we found that JNK inhibition by AS601245, a specific JNK inhibitor, significantly increased FOXO3a phosphorylation, which attenuated FOXO3a translocation into the nucleus after HI. Moreover, JNK inhibition downregulated levels of Bim and CC3 proteins, attenuated neuronal apoptosis and reduced brain infarct volume in the developing rat brain. Our findings suggest that the JNK/FOXO3a/Bim pathway is involved in neuronal apoptosis in the developing rat brain after HI. Agents targeting JNK may offer promise for rescuing neurons from HI-induced damage

Characterisation of fresh extruded rice with added soybean protein isolate

Incorporating proteins into gluten-free foods can often improve their nutritional value. Plant-based proteins are often used as a good source of protein due to their easy absorption in the body and low environmental impact. The utilization of Soy Protein Isolate (SPI) in an extruded food product aimed to examine the impact of SPI on the physicochemical characteristics of Fresh Extruded Rice (FER) in this study. We used rheological techniques and thermal analysis to determine the suitability of the extrusion process and the loss of heating mass. The microstructure, textural properties, sensory evaluation and rice taste analyser scores of FER were determined. A new gluten-free food product was produced and its quality was improved by the addition of SPI. When the content of SPI was 3%, the microstructure and texture properties showed that the FER had medium hardness, good elasticity and cohesion, which was better than paddy rice in food quality analysis. In the extrusion process, SPI has the potential to enhance not only the rheological, thermogravimetric, microstructure, and texture properties of FER, but also serve as a dietary supplement to elevate the sensory experience of FER

The role of IL-6/JAK2/STAT3 signaling pathway in cancers

Interleukin-6 (IL-6) is a pleiotropic cytokine involved in immune regulation. It can activate janus kinase 2 (JAK2)-signal transducer and activator of transcription 3 (STAT3) signaling pathway. As one of the important signal transduction pathways in cells, JAK2/STAT3 signaling pathway plays a critical role in cell proliferation and differentiation by affecting the activation state of downstream effector molecules. The activation of JAK2/STAT3 signaling pathway is involved in tumorigenesis and development. It contributes to the formation of tumor inflammatory microenvironment and is closely related to the occurrence and development of many human tumors. This article focuses on the relationship between IL-6/JAK2/STAT3 signaling pathway and liver cancer, breast cancer, colorectal cancer, gastric cancer, lung cancer, pancreatic cancer and ovarian cancer, hoping to provide references for the research of cancer treatment targeting key molecules in IL-6/JAK2/STAT3 signaling pathway

Caught in the Crossfire: Fears of Chinese-American Scientists

The US leadership in science and technology has greatly benefitted from immigrants from other countries, most notably from China in the recent decades. However, feeling the pressure of potential federal investigation since the 2018 launch of the China Initiative under the Trump administration, Chinese-origin scientists in the US now face higher incentives to leave the US and lower incentives to apply for federal grants. Analyzing data pertaining to institutional affiliations of more than 2.3 million scientific papers, we find a steady increase in the return migration of Chinese-origin scientists from the US back to China. We also conducted a survey of Chinese-origin scientists employed by US universities in tenure or tenure-track positions (n=1300), with results revealing general feelings of fear and anxiety that lead them to consider leaving the US and/or stop applying for federal grants.Comment: 16 pages, 2 figure

Vented Methane-air Explosion Overpressure Calculation—A simplified approach based on CFD

This paper presents new correlations developed through numerical simulations to estimate peak overpressures for vented methane-air explosions in cylindrical enclosures. A series of experimental tests are carried out first and the results are used to validate the numerical models developed with the commercial CFD software FLACS. More than 350 simulations consisting of 16 enclosure scales, 12 vent area to enclosure roof area ratios, 8 gas equivalence ratios and 9 vent activation pressures are then carried out to develop the Vented Methane-air Explosion Overpressure Calculation (VMEOC) correlations. Parameters associated with burning velocity and turbulence generation, oscillatory combustion and flame instabilities in vented gas explosion are taken into account in the development of new correlations. Comparing to CFD simulations, the VMEOC correlations provide a faster way to estimate the peak overpressure of a vented explosion. Additionally, it is proved in this study that the VMEOC correlations are easier to use and more accurate than the equations given in the up-to-date industrial standard- NFPA-68 2013 edition