Generalised joint regression for count data: a penalty extension for competitive settings

We propose a versatile joint regression framework for count responses. The method is implemented in the R add-on package GJRM and allows for modelling linear and non-linear dependence through the use of several copulae. Moreover, the parameters of the marginal distributions of the count responses and of the copula can be specified as flexible functions of covariates. Motivated by competitive settings, we also discuss an extension which forces the regression coefficients of the marginal (linear) predictors to be equal via a suitable penalisation. Model fitting is based on a trust region algorithm which estimates simultaneously all the parameters of the joint models. We investigate the proposal’s empirical performance in two simulation studies, the first one designed for arbitrary count data, the other one reflecting competitive settings. Finally, the method is applied to football data, showing its benefits compared to the standard approach with regard to predictive performance

Src Dependent Pancreatic Acinar Injury Can Be Initiated Independent of an Increase in Cytosolic Calcium

Several deleterious intra-acinar phenomena are simultaneously triggered on initiating acute pancreatitis. These culminate in acinar injury or inflammatory mediator generation in vitro and parenchymal damage in vivo. Supraphysiologic caerulein is one such initiator which simultaneously activates numerous signaling pathways including non-receptor tyrosine kinases such as of the Src family. It also causes a sustained increase in cytosolic calcium- a player thought to be crucial in regulating deleterious phenomena. We have shown Src to be involved in caerulein induced actin remodeling, and caerulein induced changes in the Golgi and post-Golgi trafficking to be involved in trypsinogen activation, which initiates acinar cell injury. However, it remains unclear whether an increase in cytosolic calcium is necessary to initiate acinar injury or if injury can be initiated at basal cytosolic calcium levels by an alternate pathway. To study the interplay between tyrosine kinase signaling and calcium, we treated mouse pancreatic acinar cells with the tyrosine phosphatase inhibitor pervanadate. We studied the effect of the clinically used Src inhibitor Dasatinib (BMS-354825) on pervanadate or caerulein induced changes in Src activation, trypsinogen activation, cell injury, upstream cytosolic calcium, actin and Golgi morphology. Pervanadate, like supraphysiologic caerulein, induced Src activation, redistribution of the F-actin from its normal location in the sub-apical area to the basolateral areas, and caused antegrade fragmentation of the Golgi. These changes, like those induced by supraphysiologic caerulein, were associated with trypsinogen activation and acinar injury, all of which were prevented by Dasatinib. Interestingly, however, pervanadate did not cause an increase in cytosolic calcium, and the caerulein induced increase in cytosolic calcium was not affected by Dasatinib. These findings suggest that intra-acinar deleterious phenomena may be initiated independent of an increase in cytosolic calcium. Other players resulting in acinar injury along with the Src family of tyrosine kinases remain to be explored. © 2013 Mishra et al

Conducting High-Value Secondary Dataset Analysis: An Introductory Guide and Resources

Secondary analyses of large datasets provide a mechanism for researchers to address high impact questions that would otherwise be prohibitively expensive and time-consuming to study. This paper presents a guide to assist investigators interested in conducting secondary data analysis, including advice on the process of successful secondary data analysis as well as a brief summary of high-value datasets and online resources for researchers, including the SGIM dataset compendium (www.sgim.org/go/datasets). The same basic research principles that apply to primary data analysis apply to secondary data analysis, including the development of a clear and clinically relevant research question, study sample, appropriate measures, and a thoughtful analytic approach. A real-world case description illustrates key steps: (1) define your research topic and question; (2) select a dataset; (3) get to know your dataset; and (4) structure your analysis and presentation of findings in a way that is clinically meaningful. Secondary dataset analysis is a well-established methodology. Secondary analysis is particularly valuable for junior investigators, who have limited time and resources to demonstrate expertise and productivity

Physio-chemical characterization of three-component co-amorphous systems generated by a melt-quench method

The purpose of this work was to evaluate the possibility of creating a ternary co-amorphous system and to determine how the properties of a co-amorphous material are altered by the addition of a selected third component. Piroxicam and indomethacin form a stable co-amorphous with the Tg above room temperature. The third component added was selected based on tendency to crystallise (benzamide, caffeine) or form amorphous (acetaminophen, clotrimazole) on cooling. Generated co-amorphous systems were characterised with TGA, HSM, DSC, FTIR, and XRD. Stable ternary co-amorphous systems were successfully generated, which was confirmed using XRD, DSC and FTIR analysis. In all cases, Tg of the ternary system was lower than the Tg of the binary system, although higher than that of the individual third compound. Upon storage for 4 weeks all created ternary systems showed significantly smaller variation in Tg compared to the binary system. Stable three-component co-amorphous systems can be generated via melt quench method using either a crystalline or amorphous third component. Addition of third component can alter the Tg of co-amorphous system and in all cases created more stable co-amorphous system upon storage. Physical parameters may not be sufficient in predicting the resulting Tg, therefore knowledge of chemical interaction must be brought into equation as well

The effect of body mass index on global brain volume in middle-aged adults: a cross sectional study

BACKGROUND: Obesity causes or exacerbates a host of medical conditions, including cardiovascular, pulmonary, and endocrine diseases. Recently obesity in elderly women was associated with greater risk of dementia, white matter ischemic changes, and greater brain atrophy. The purpose of this study was to determine whether body type affects global brain volume, a marker of atrophy, in middle-aged men and women. METHODS: T1-weighted 3D volumetric magnetic resonance imaging was used to assess global brain volume for 114 individuals 40 to 66 years of age (average = 54.2 years; standard deviation = 6.6 years; 43 men and 71 women). Total cerebrospinal fluid and brain volumes were obtained with an automated tissue segmentation algorithm. A regression model was used to determine the effect of age, body mass index (BMI), and other cardiovascular risk factors on brain volume and cognition. RESULTS: Age and BMI were each associated with decreased brain volume. BMI did not predict cognition in this sample; however elevated diastolic blood pressure was associated with poorer episodic learning performance. CONCLUSION: These findings suggest that middle-aged obese adults may already be experiencing differentially greater brain atrophy, and may potentially be at greater risk for future cognitive decline

Effect of vitamin D supplementation on bone health parameters of healthy young Indian women

Summary There is a huge prevalence of hypovitaminosis D in the Indian population. We studied the efficacy and safety of oral vitamin D supplementation in apparently healthy adult women. Monthly cholecalciferol given orally, 60,000 IU/month during summers and 120,000 IU/month during winters, safely increases 25-hydroxyvitamin D (25 (OH)D) levels to near normal levels. Introduction There is a huge burden of hypovitaminosis D in the Indian population. The current recommendation for vitamin D supplementation is not supported by sufficient evidence. Methods Study subjects included 100 healthy adult women of reproductive age group from hospital staff. They wer

Quantitative estimation of tissue blood flow rate

The rate of blood flow through a tissue (F) is a critical parameter for assessing the functional efficiency of a blood vessel network following angiogenesis. This chapter aims to provide the principles behind the estimation of F, how F relates to other commonly used measures of tissue perfusion, and a practical approach for estimating F in laboratory animals, using small readily diffusible and metabolically inert radio-tracers. The methods described require relatively nonspecialized equipment. However, the analytical descriptions apply equally to complementary techniques involving more sophisticated noninvasive imaging. Two techniques are described for the quantitative estimation of F based on measuring the rate of tissue uptake following intravenous administration of radioactive iodo-antipyrine (or other suitable tracer). The Tissue Equilibration Technique is the classical approach and the Indicator Fractionation Technique, which is simpler to perform, is a practical alternative in many cases. The experimental procedures and analytical methods for both techniques are given, as well as guidelines for choosing the most appropriate method

Significance analysis of microarray for relative quantitation of LC/MS data in proteomics

<p>Abstract</p> <p>Background</p> <p>Although fold change is a commonly used criterion in quantitative proteomics for differentiating regulated proteins, it does not provide an estimation of false positive and false negative rates that is often desirable in a large-scale quantitative proteomic analysis. We explore the possibility of applying the Significance Analysis of Microarray (SAM) method (PNAS 98:5116-5121) to a differential proteomics problem of two samples with replicates. The quantitative proteomic analysis was carried out with nanoliquid chromatography/linear iron trap-Fourier transform mass spectrometry. The biological sample model included two <it>Mycobacterium smegmatis </it>unlabeled cell cultures grown at pH 5 and pH 7. The objective was to compare the protein relative abundance between the two unlabeled cell cultures, with an emphasis on significance analysis of protein differential expression using the SAM method. Results using the SAM method are compared with those obtained by fold change and the conventional <it>t</it>-test.</p> <p>Results</p> <p>We have applied the SAM method to solve the two-sample significance analysis problem in liquid chromatography/mass spectrometry (LC/MS) based quantitative proteomics. We grew the pH5 and pH7 unlabelled cell cultures in triplicate resulting in 6 biological replicates. Each biological replicate was mixed with a common ¹⁵N-labeled reference culture cells for normalization prior to SDS/PAGE fractionation and LC/MS analysis. For each biological replicate, one center SDS/PAGE gel fraction was selected for triplicate LC/MS analysis. There were 121 proteins quantified in at least 5 of the 6 biological replicates. Of these 121 proteins, 106 were significant in differential expression by the <it>t</it>-test (<it>p </it>< 0.05) based on peptide-level replicates, 54 were significant in differential expression by SAM with Δ = 0.68 cutoff and false positive rate at 5%, and 29 were significant in differential expression by the <it>t</it>-test (<it>p </it>< 0.05) based on protein-level replicates. The results indicate that SAM appears to overcome the false positives one encounters using the peptide-based <it>t</it>-test while allowing for identification of a greater number of differentially expressed proteins than the protein-based <it>t</it>-test.</p> <p>Conclusion</p> <p>We demonstrate that the SAM method can be adapted for effective significance analysis of proteomic data. It provides much richer information about the protein differential expression profiles and is particularly useful in the estimation of false discovery rates and miss rates.</p

Laser-directed hierarchical assembly of liquid crystal defects and control of optical phase singularities

Topological defect lines are ubiquitous and important in a wide variety of fascinating phenomena and theories in many fields ranging from materials science to early-universe cosmology, and to engineering of laser beams. However, they are typically hard to control in a reliable manner. Here we describe facile erasable “optical drawing” of self-assembled defect clusters in liquid crystals. These quadrupolar defect clusters, stabilized by the medium's chirality and the tendency to form twisted configurations, are shaped into arbitrary two-dimensional patterns, including reconfigurable phase gratings capable of generating and controlling optical phase singularities in laser beams. Our findings bridge the studies of defects in condensed matter physics and optics and may enable applications in data storage, singular optics, displays, electro-optic devices, diffraction gratings, as well as in both optically- and electrically-addressed pixel-free spatial light modulators