Involvement of the Cav3.2 T-type calcium channel in thalamic neuron discharge patterns

<p>Abstract</p> <p>Background</p> <p>Mice that have defects in their low-threshold T-type calcium channel (T-channel) genes show altered pain behaviors. The changes in the ratio of nociceptive neurons and the burst firing property of reticular thalamic (RT) and ventroposterior (VP) neurons in Cav3.2 knockout (KO) mice were studied to test the involvement of thalamic T-channel and burst firing activity in pain function.</p> <p>Results</p> <p>Under pentobarbital or urethane anesthesia, the patterns of tonic and burst firings were recorded in functionally characterized RT and VPL neurons of Cav3.2 KO mice. Many RT neurons were nociceptive (64% under pentobarbital anesthesia and 50% under urethane anesthesia). Compared to their wild-type (WT) controls, fewer nociceptive RT neurons were found in Cav3.2 KO mice. Both nociceptive and tactile RT neurons showed fewer bursts in Cav3.2 KO mice. Within a burst, RT neurons of Cav3.2 KO mice had a lower spike frequency and less-prominent accelerando-decelerando change. In contrast, VP neurons of Cav3.2 KO mice showed a higher ratio of bursts and a higher discharge rate within a burst than those of the WT control. In addition, the long-lasting tonic firing episodes in RT neurons of the Cav3.2 KO had less stereotypic regularity than their counterparts in WT mice.</p> <p>Conclusions</p> <p>RT might be important in nociception of the mouse. In addition, we showed an important role of Cav3.2 subtype of T-channel in RT burst firing pattern. The decreased occurrence and slowing of the bursts in RT neurons might cause the increased VP bursts. These changes would be factors contributing to alternation of pain behavior in the Cav3.2 KO mice.</p

Modelling the overdiagnosis of breast cancer due to mammography screening in women aged 40 to 49 in the United Kingdom

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the original work is properly cited

Evaluating cardiovascular risk in chronic kidney disease patients: a biomarker approach

Cardiovascular disease (CVD) is a major cause of morbidity and mortality in chronic kidney disease (CKD) patients. This study aimed to determine the roles of CVD biomarkers in CKD patients. This was a case-control study which recruited consecutive patients with stage 2-4 CKD patients with and without CVD. Serum levels of highly-sensitive C reactive protein (hs-CRP), cystatin C (CysC), asymmetrical dimetylarginine (ADMA) and symmetrical dimethylarginine (SDMA) were measured. Sixty two stage 2-4 CKD patients with a mean age of 60.3 ± 10.4 years were recruited. Twenty three (37.1%) of them had CVD. Those CKD patients with CVD were older (64.1±8.0 vs 58.1± 1.1, p0.05). There were no differences in their mean serum levels of hs-CRP, CysC, ADMA and SDMA. Risk factors including age, diabetes mellitus, hypertension and renal functions were still the most important CVD risk factors in CKD patients

Interfaces: The Next NDE Challenge

Nondestructive evaluation, as practiced in the 1960’s, attempted to detect (but was often unable to characterize) the existence of defects in engineering structures. Qualitative criteria were used in the assessment of defect significance and the determination of accept/reject decisions. Advances in elasto-plastic fracture mechanics during the 1970’s focused attention upon the defect size and orientation- if these could be measured, then fracture mechanics was capable of quantitative structural integrity evaluation. The papers presented in this conference series during the 1980’s trace the considerable advances of quantitative nondestructive evaluation in satisfying this measurement need. Nowadays, for monolithic materials with well defined fracture toughness, the overconservative rejection criteria of the past are beginning to be replaced by “retirement for cause” concepts

Security of data science and data science for security

In this chapter, we present a brief overview of important topics regarding the connection of data science and security. In the first part, we focus on the security of data science and discuss a selection of security aspects that data scientists should consider to make their services and products more secure. In the second part about security for data science, we switch sides and present some applications where data science plays a critical role in pushing the state-of-the-art in securing information systems. This includes a detailed look at the potential and challenges of applying machine learning to the problem of detecting obfuscated JavaScripts

Evaluation of multiple variate selection methods from a biological perspective: a nutrigenomics case study

Genomics-based technologies produce large amounts of data. To interpret the results and identify the most important variates related to phenotypes of interest, various multivariate regression and variate selection methods are used. Although inspected for statistical performance, the relevance of multivariate models in interpreting biological data sets often remains elusive. We compare various multivariate regression and variate selection methods applied to a nutrigenomics data set in terms of performance, utility and biological interpretability. The studied data set comprised hepatic transcriptome (10,072 predictor variates) and plasma protein concentrations [2 dependent variates: Leptin (LEP) and Tissue inhibitor of metalloproteinase 1 (TIMP-1)] collected during a high-fat diet study in ApoE3Leiden mice. The multivariate regression methods used were: partial least squares “PLS”; a genetic algorithm-based multiple linear regression, “GA-MLR”; two least-angle shrinkage methods, “LASSO” and “ELASTIC NET”; and a variant of PLS that uses covariance-based variate selection, “CovProc.” Two methods of ranking the genes for Gene Set Enrichment Analysis (GSEA) were also investigated: either by their correlation with the protein data or by the stability of the PLS regression coefficients. The regression methods performed similarly, with CovProc and GA performing the best and worst, respectively (R-squared values based on “double cross-validation” predictions of 0.762 and 0.451 for LEP; and 0.701 and 0.482 for TIMP-1). CovProc, LASSO and ELASTIC NET all produced parsimonious regression models and consistently identified small subsets of variates, with high commonality between the methods. Comparison of the gene ranking approaches found a high degree of agreement, with PLS-based ranking finding fewer significant gene sets. We recommend the use of CovProc for variate selection, in tandem with univariate methods, and the use of correlation-based ranking for GSEA-like pathway analysis methods

Variable Pathogenicity Determines Individual Lifespan in Caenorhabditis elegans

A common property of aging in all animals is that chronologically and genetically identical individuals age at different rates. To unveil mechanisms that influence aging variability, we identified markers of remaining lifespan for Caenorhabditis elegans. In transgenic lines, we expressed fluorescent reporter constructs from promoters of C. elegans genes whose expression change with age. The expression levels of aging markers in individual worms from a young synchronous population correlated with their remaining lifespan. We identified eight aging markers, with the superoxide dismutase gene sod-3 expression being the best single predictor of remaining lifespan. Correlation with remaining lifespan became stronger if expression from two aging markers was monitored simultaneously, accounting for up to 49% of the variation in individual lifespan. Visualizing the physiological age of chronologically-identical individuals allowed us to show that a major source of lifespan variability is different pathogenicity from individual to individual and that the mechanism involves variable activation of the insulin-signaling pathway

Quality of Life and Related Factors among HIV-Positive Spouses from Serodiscordant Couples under Antiretroviral Therapy in Henan Province, China

OBJECTIVE: To describe the quality of life and related factors in HIV-positive spouses undergoing ART from discordant couples. METHODS: A cross-sectional study was conducted among 1,009 HIV-positive spouses from serodiscordant couples in Zhumadian, Henan Province, between October 1, 2008 and March 31, 2009. HIV-positive spouses were interviewed by local health professionals. Quality of life was evaluated by WHOQOL (Chinese Version). A multiple linear regression model was used to analyze the related factors. RESULTS: The majority of subjects were female (56.39%), had received a high school education (44%), were of Han ethnicity (98.41%), and were farmers (90.09%); the median time period of receiving ART was 3.92 years. The physical, psychological, social, and environmental QOL scores of the subjects were 12.91±1.95, 12.35±1.80, 13.96±2.43, and 12.45±1.91 respectively. The multiple linear regression model identified the physical domain related factors to be CD4 count, educational level, and occupation; psychological domain related factors include age, educational level, and reported STD symptom; social domain related factors included education level; and environmental domain related factors included education level, reported STD symptoms, and occupation. CONCLUSION: Being younger, a farmer, having a lower level of education, a reported STD symptom, or lower CD4 count, could decrease one's quality of life, suggesting that the use of blanket ART programs alone may not necessarily improve quality of life. Subjects received lower scores in the psychological domain, suggesting that psychological intervention may also need to be strengthened

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT