Exact Hybrid Covariance Thresholding for Joint Graphical Lasso

This paper considers the problem of estimating multiple related Gaussian graphical models from a $p$-dimensional dataset consisting of different classes. Our work is based upon the formulation of this problem as group graphical lasso. This paper proposes a novel hybrid covariance thresholding algorithm that can effectively identify zero entries in the precision matrices and split a large joint graphical lasso problem into small subproblems. Our hybrid covariance thresholding method is superior to existing uniform thresholding methods in that our method can split the precision matrix of each individual class using different partition schemes and thus split group graphical lasso into much smaller subproblems, each of which can be solved very fast. In addition, this paper establishes necessary and sufficient conditions for our hybrid covariance thresholding algorithm. The superior performance of our thresholding method is thoroughly analyzed and illustrated by a few experiments on simulated data and real gene expression data

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Validation of learning style measures: implications for medical education practice

It is unclear which learners would most benefit from the more individualised, student-structured, interactive approaches characteristic of problem-based and computer-assisted learning. The validity of learning style measures is uncertain, and there is no unifying learning style construct identified to predict such learners. Objective  This study was conducted to validate learning style constructs and to identify the learners most likely to benefit from problem-based and computer-assisted curricula. Methods  Using a cross-sectional design, 3 established learning style inventories were administered to 97 post-Year 2 medical students. Cognitive personality was measured by the Group Embedded Figures Test, information processing by the Learning Styles Inventory, and instructional preference by the Learning Preference Inventory. The 11 subscales from the 3 inventories were factor-analysed to identify common learning constructs and to verify construct validity. Concurrent validity was determined by intercorrelations of the 11 subscales. Results  A total of 94 pre-clinical medical students completed all 3 inventories. Five meaningful learning style constructs were derived from the 11 subscales: student- versus teacher-structured learning; concrete versus abstract learning; passive versus active learning; individual versus group learning, and field-dependence versus field-independence. The concurrent validity of 10 of 11 subscales was supported by correlation analysis. Medical students most likely to thrive in a problem-based or computer-assisted learning environment would be expected to score highly on abstract, active and individual learning constructs and would be more field-independent. Conclusions  Learning style measures were validated in a medical student population and learning constructs were established for identifying learners who would most likely benefit from a problem-based or computer-assisted curriculum.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72443/1/j.1365-2929.2006.02476.x.pd

A biophysical model of cell adhesion mediated by immunoadhesin drugs and antibodies

A promising direction in drug development is to exploit the ability of natural killer cells to kill antibody-labeled target cells. Monoclonal antibodies and drugs designed to elicit this effect typically bind cell-surface epitopes that are overexpressed on target cells but also present on other cells. Thus it is important to understand adhesion of cells by antibodies and similar molecules. We present an equilibrium model of such adhesion, incorporating heterogeneity in target cell epitope density and epitope immobility. We compare with experiments on the adhesion of Jurkat T cells to bilayers containing the relevant natural killer cell receptor, with adhesion mediated by the drug alefacept. We show that a model in which all target cell epitopes are mobile and available is inconsistent with the data, suggesting that more complex mechanisms are at work. We hypothesize that the immobile epitope fraction may change with cell adhesion, and we find that such a model is more consistent with the data. We also quantitatively describe the parameter space in which binding occurs. Our results point toward mechanisms relating epitope immobility to cell adhesion and offer insight into the activity of an important class of drugs.Comment: 13 pages, 5 figure

Demographic, risk behaviour and personal network variables associated with prevalent hepatitis C, hepatitis B, and HIV infection in injection drug users in Winnipeg, Canada

BACKGROUND: Previous studies have used social network variables to improve our understanding of HIV transmission. Similar analytic approaches have not been undertaken for hepatitis C (HCV) or B (HBV), nor used to conduct comparative studies on these pathogens within a single setting. METHODS: A cross-sectional survey consisting of a questionnaire and blood sample was conducted on injection drug users in Winnipeg between December 2003 and September 2004. Logistic regression analyses were used to correlate respondent and personal network data with HCV, HBV and HIV prevalence. RESULTS: At the multivariate level, pathogen prevalence was correlated with both respondent and IDU risk network variables. Pathogen transmission was associated with several distinct types of high-risk networks formed around specific venues (shooting galleries, hotels) or within users who are linked by their drug use preferences. Smaller, isolated pockets of IDUs also appear to exist within the larger population where behavioural patterns pose a lesser risk, unless or until, a given pathogen enters those networks. CONCLUSION: The findings suggest that consideration of both respondent and personal network variables can assist in understanding the transmission patterns of HCV, HBV, and HIV. It is important to assess these effects for multiple pathogens within one setting as the associations identified and the direction of those associations can differ between pathogens

Orbital swelling as a first symptom in breast carcinoma diagnosis: a case report

<p>Abstract</p> <p>Introduction</p> <p>The frequency of intra-orbital metastasis in systemic cancer is a controversial topic. Of all metastatic tumors to the orbit of the eye, breast carcinoma is considered to be the most prevalent. Orbital findings typically present themselves after the diagnosis of the primary tumor, with an average delay of three to six years. In spite of that, this study reports a case in which orbital manifestation was the initial symptom in breast carcinoma diagnosis.</p> <p>Case presentation</p> <p>A 66-year-old Italian Caucasian woman presented with a swelling located on the lower orbit of her right eye.</p> <p>Conclusions</p> <p>Previous cases report orbital manifestations discovered secondary to breast cancer. This case demonstrates that orbital symptoms may be the primary presentation of the disease. Orbital metastasis originating from breast cancer predicts widespread metastatic disease in other organs. In the presence of an ambiguous infiltrative orbital process, diagnostic examination of the breast is recommended.</p

A thyroid hormone regulated asymmetric responsive centre is correlated with eye migration during flatfish metamorphosis

Flatfish metamorphosis is a unique post-embryonic developmental event in which thyroid hormones (THs) drive the development of symmetric pelagic larva into asymmetric benthic juveniles. One of the eyes migrates to join the other eye on the opposite side of the head. Developmental mechanisms at the basis of the acquisition of flatfish anatomical asymmetry remain an open question. Here we demonstrate that an TH responsive asymmetric centre, determined by deiodinase 2 expression, ventrally juxtaposed to the migrating eye in sole (Solea senegalensis) correlates with asymmetric cranial ossification that in turn drives eye migration. Besides skin pigmentation that is asymmetric between dorsal and ventral sides, only the most anterior head region delimited by the eyes becomes asymmetric whereas the remainder of the head and organs therein stay symmetric. Sub-ocular ossification is common to all flatfish analysed to date, so we propose that this newly discovered mechanism is universal and is associated with eye migration in all flatfish.Fundacao para a Ciencia e Tecnologia (FCT) [SFRH/BPD/66808/2009, IF/01274/2014]; FCT [SFRH/BPD/79105/2011, SFRH/BPD/89889/2012, PTDC/MAR/115005/2009, PEst-C/MAR/LA0015/2011, UID/Multi/04326/2013, Pest-OE/EQB/LA0023/2013, UID/BIM/04773/2013]; European Regional Development Fund through COMPETE; INIA; EU [RTA2013-00023-C02-01

An ensemble of epoch-wise empirical Bayes for few-shot learning

Ministry of Education, Singapore under its Academic Research Funding Tier