Risk Factors for Ventilator Dependency Following Coronary Artery Bypass Grafting

Background: Ventilator dependency following coronary artery bypass grafting (CABG) is often associated with significant morbidity and mortality. However, few reports have focused on the independent risk factors for ventilator dependency following CABG. This study aimed to evaluate the independent risk factors for ventilator dependency following coronary artery bypass grafting (CABG). Methods: The relevant pre-, intra- and post-operative data of patients without a history of chronic obstructive pulmonary disease undergoing isolated CABG from January 2003 to December 2008 in our center were retrospectively analyzed. Elapsed time between CABG and extubation of more than 48 hours was defined as postoperative ventilator dependency (PVD). Results: The incidence of PVD was 13.8% (81/588). The in-hospital mortality in the PVD group was significantly higher than that in the non-PVD group (8.6% versus 2.4%, p=0.0092). Besides the length of ICU and hospital stay, PVD correlated with negative respiratory outcomes. The independent risk factors for PVD were preoperative congestive heart failure (OR=2.456, 95%CI 1.426-6.879), preoperative hypoalbuminemia (OR=1.353, 95%CI 1.125-3.232), preoperative arterial oxygen partial pressure (PO2) (OR=0.462, 95%CI 0.235-0.783) and postoperative anaemia (OR=1.541, 95%CI 1.231-3.783). Conclusions: Preoperative congestive heart failure, preoperative hypoalbuminemia, low preoperative PO2 and postoperative anaemia were identified as four independent risk factors for ventilator dependency following CABG

Assessing the Effectiveness of Direct Data Merging Strategy in Long-Term and Large-Scale Pharmacometabonomics

Because of the extended period of clinic data collection and huge size of analyzed samples, the long-term and large-scale pharmacometabonomics profiling is frequently encountered in the discovery of drug/target and the guidance of personalized medicine. So far, integration of the results (ReIn) from multiple experiments in a large-scale metabolomic profiling has become a widely used strategy for enhancing the reliability and robustness of analytical results, and the strategy of direct data merging (DiMe) among experiments is also proposed to increase statistical power, reduce experimental bias, enhance reproducibility and improve overall biological understanding. However, compared with the ReIn, the DiMe has not yet been widely adopted in current metabolomics studies, due to the difficulty in removing unwanted variations and the inexistence of prior knowledges on the performance of the available merging methods. It is therefore urgently needed to clarify whether DiMe can enhance the performance of metabolic profiling or not. Herein, the performance of DiMe on 4 pairs of benchmark datasets was comprehensively assessed by multiple criteria (classification capacity, robustness and false discovery rate). As a result, integration/merging-based strategies (ReIn and DiMe) were found to perform better under all criteria than those strategies based on single experiment. Moreover, DiMe was discovered to outperform ReIn in classification capacity and robustness, while the ReIn showed superior capacity in controlling false discovery rate. In conclusion, these findings provided valuable guidance to the selection of suitable analytical strategy for current metabolomics

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity

Crosstalk between Spinal Astrocytes and Neurons in Nerve Injury-Induced Neuropathic Pain

Emerging research implicates the participation of spinal dorsal horn (SDH) neurons and astrocytes in nerve injury-induced neuropathic pain. However, the crosstalk between spinal astrocytes and neurons in neuropathic pain is not clear. Using a lumbar 5 (L5) spinal nerve ligation (SNL) pain model, we testified our hypothesis that SDH neurons and astrocytes reciprocally regulate each other to maintain the persistent neuropathic pain states. Glial fibrillary acidic protein (GFAP) was used as the astrocytic specific marker and Fos, protein of the protooncogene c-fos, was used as a marker for activated neurons. SNL induced a significant mechanical allodynia as well as activated SDH neurons indicated by the Fos expression at the early phase and activated astrocytes with the increased expression of GFAP during the late phase of pain, respectively. Intrathecal administration of c-fos antisense oligodeoxynucleotides (ASO) or astroglial toxin L-α-aminoadipate (L-AA) reversed the mechanical allodynia, respectively. Immunofluorescent histochemistry revealed that intrathecal administration of c-fos ASO significantly suppressed activation of not only neurons but also astrocytes induced by SNL. Meanwhile, L-AA shortened the duration of neuronal activation by SNL. Our data offers evidence that neuronal and astrocytic activations are closely related with the maintenance of neuropathic pain through a reciprocal “crosstalk”. The current study suggests that neuronal and non-neuronal elements should be taken integrally into consideration for nociceptive transmission, and that the intervention of such interaction may offer some novel pain therapeutic strategies

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

<p>Abstract</p> <p>Background</p> <p>Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists.</p> <p>Results</p> <p>Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan – the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (<it>P</it>) derived from widely used simple <it>t</it>-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent <it>P</it>-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on <it>P</it>-value ranking is an expected mathematical consequence of the high variability of the <it>t</it>-values; the more stringent the <it>P</it>-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations.</p> <p>Conclusion</p> <p>We recommend the use of FC-ranking plus a non-stringent <it>P </it>cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the <it>P</it>-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and <it>P</it>-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the <it>P </it>criterion balances sensitivity and specificity.</p

Advances in Molecular Quantum Chemistry Contained in the Q-Chem 4 Program Package

A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller–Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube

Monitoring dynamics and driving forces of lake changes in different seasons in Xinjiang using multi-source remote sensing

Lakes are important for ensuring the development of the regional economy and ecological security. Based on MODIS and Landsat TM/OLI remote sensing images captured in 2005-2015 and a Combined Water Index (CWI), this paper extracted information on changes in the temporal and spatial characteristics and driving forces for lake areas in Xinjiang during past 11 years in different seasons (April, July and September). The results showed that over this time period, the area of the lakes exhibited an increasing trend. The largest surface area usually occurred in April, and the lowest value was measured in September. The lake shrinkage area in Xinjiang occurred mainly in Northern Xinjiang and the northeastern region of Southern Xinjiang, whereas the lake expansion area was concentrated in Eastern Xinjiang. Seasonal changes in Manas, Kanas, Barkol, Arkatag, Arik and Ebinur Lakes showed higher trends. Extracted the lake area based on the MODIS and TM/OLI image were analyzed, and both had a good corresponding relationship. The minimum R2 was 0.548, and maximum RMSE was 44.1km2. Therefore, it was feasible to use MODIS to extract lake area. These changes in lake area resulted from both natural factors and human activities, and coupled effects greatly accelerated local environmental changes