LC-N2G: a local consistency approach for nutrigenomics data analysis.

BACKGROUND: Nutrigenomics aims at understanding the interaction between nutrition and gene information. Due to the complex interactions of nutrients and genes, their relationship exhibits non-linearity. One of the most effective and efficient methods to explore their relationship is the nutritional geometry framework which fits a response surface for the gene expression over two prespecified nutrition variables. However, when the number of nutrients involved is large, it is challenging to find combinations of informative nutrients with respect to a certain gene and to test whether the relationship is stronger than chance. Methods for identifying informative combinations are essential to understanding the relationship between nutrients and genes. RESULTS: We introduce Local Consistency Nutrition to Graphics (LC-N2G), a novel approach for ranking and identifying combinations of nutrients with gene expression. In LC-N2G, we first propose a model-free quantity called Local Consistency statistic to measure whether there is non-random relationship between combinations of nutrients and gene expression measurements based on (1) the similarity between samples in the nutrient space and (2) their difference in gene expression. Then combinations with small LC are selected and a permutation test is performed to evaluate their significance. Finally, the response surfaces are generated for the subset of significant relationships. Evaluation on simulated data and real data shows the LC-N2G can accurately find combinations that are correlated with gene expression. CONCLUSION: The LC-N2G is practically powerful for identifying the informative nutrition variables correlated with gene expression. Therefore, LC-N2G is important in the area of nutrigenomics for understanding the relationship between nutrition and gene expression information.

Effect on urine specific gravity of the addition of glucose to urine samples of dogs and cats.

OBJECTIVE: To evaluate effects of the addition of glucose to dog and cat urine on urine specific gravity (USG) and determine whether glucosuria affects assessment of renal concentrating ability. SAMPLE: Urine samples from 102 dogs and 59 cats. PROCEDURES: Urine for each species was pooled to create samples with various USGs. Glucose was added to an aliquot of each USG pool (final concentration, 2,400 mg/dL), and serial dilutions of the glucose-containing aliquot were created for each pool. The USG then was measured in all samples. The difference in USG attributable to addition of glucose was calculated by subtracting the USG of the unaltered sample from the USG of the sample after the addition of glucose. The relationship between the difference in USG and the USG of the unaltered, undiluted sample was evaluated by the use of linear regression analysis. RESULTS: Addition of glucose to urine samples increased the USG. There was a significant relationship between USG of the undiluted sample and the difference in USG when glucose was added to obtain concentrations of 300, 600, 1,200, and 2,400 mg/dL in canine urine and concentrations of 600, 1,200, and 2,400 mg/dL in feline urine. The more concentrated the urine before the addition of glucose, the less change there was in the USG. Changes in USG attributable to addition of glucose were not clinically important. CONCLUSIONS AND CLINICAL RELEVANCE: Substantial glucosuria resulted in minimal alterations in specific gravity of canine and feline urine samples. Thus, USG can be used to assess renal concentrating ability even in samples with glucosuria.

A radiographic analysis of the abnormal hallux interphalangeus angle range: Considerations for surgeons performing Akin osteotomies.

PURPOSE: This study is aimed to determine the abnormal radiological hallux interphalangeus angle (HIA) range, which can assist surgeons in determining the required bone resection in an Akin osteotomy of the proximal phalanx of the great toe. METHODS: Radiographs of 141 feet were analyzed. The mean HIA and range were calculated. RESULTS: The prevalence of hallux valgus interphalangeus (HVI) deformity was 78% (110/141). The mean HIA was 13.5° ± 4.5° (1.4-24.4). Fifty percent had abnormal HIA values of 10-15°, 40% had values of 15-20°, and 10% had greater than 20°. A large proportion of patients with HVI deformities may need greater than the standard 2-3-mm bone wedge removal during Akin osteotomy. CONCLUSION: The high prevalence and wide range of HVI deformities should alert surgeons to the possibility that greater than 3-mm bone wedge resections may be required. Level of Evidence: Level IV.

Melanoma Explorer: a web application to allow easy reanalysis of publicly available and clinically annotated melanoma omics data sets.

Validating newly discovered biomarkers in large, publicly available data sets is often difficult and requires specialized computer programming skills. Melanoma Explorer is a web application that enables easy interrogation of melanoma omics data sets that are freely available in online data repositories with a point-and-click interface. Two use cases are demonstrated. First, the relationship of lysozyme mRNA expression is shown to be prognostic in two independent gene expression microarray data sets. Second, a figure from a journal article showing the relationship of tumour thickness and miR-382 abundance is reproduced. Melanoma Explorer is demonstrated to be a useful tool for reproducing results of published studies and providing additional evidence for biomarkers in independent data sets.

bcGST-an interactive bias-correction method to identify over-represented gene-sets in boutique arrays.

MOTIVATION: Gene annotation and pathway databases such as Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes are important tools in Gene-Set Test (GST) that describe gene biological functions and associated pathways. GST aims to establish an association relationship between a gene-set of interest and an annotation. Importantly, GST tests for over-representation of genes in an annotation term. One implicit assumption of GST is that the gene expression platform captures the complete or a very large proportion of the genome. However, this assumption is neither satisfied for the increasingly popular boutique array nor the custom designed gene expression profiling platform. Specifically, conventional GST is no longer appropriate due to the gene-set selection bias induced during the construction of these platforms. RESULTS: We propose bcGST, a bias-corrected GST by introducing bias-correction terms in the contingency table needed for calculating the Fisher's Exact Test. The adjustment method works by estimating the proportion of genes captured on the array with respect to the genome in order to assist filtration of annotation terms that would otherwise be falsely included or excluded. We illustrate the practicality of bcGST and its stability through multiple differential gene expression analyses in melanoma and the Cancer Genome Atlas cancer studies. AVAILABILITY AND IMPLEMENTATION: The bcGST method is made available as a Shiny web application at http://shiny.maths.usyd.edu.au/bcGST/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Patient specific pointer tool for corrective osteotomy: Quality of symmetry based planning and case study of ulnar reconstruction surgery.

Malunion after forearm fractures are described to appear in 2% to 10% of cases. Reconstructive surgeries ensure adequate anatomical repositioning. Their importance derives from the fact that malunion can often lead to severe pain as well as deformities causing loss of function and aesthetic issues not only in the forearm, but also the wrist and elbow joint. In this paper a clinical case will be presented using a Patient Specific Instrument (PSI) as navigational aid for reconstructive surgery after malunion of a proximal ulnar fracture combined with allograft surgery of the radial head and radial condyle due to chronic traumatic radial head luxation (Monteggia fracture). A planning method based on symmetry is described and evaluated on twelve Computed Tomographic (CT) data sets of intact forearms. The absolute point to point deviation at distal end of the ulnar styloid process was used as a characteristic value for accuracy evaluation. It is 7.9±4.9mm when using only the proximal end of the ulna for registration. The simulated change of ulnar variance is -1.4±1.9mm. Design and concept of the PSI are proven in a clinical trial.

Design considerations for patient-specific surgical templates for total hip arthroplasty with respect to acetabular cartilage.

Patient-specific instruments (PSIs) are clinically used to support the surgeon during a planned intervention. The planning is typically done based on volumetric image data from medical imaging systems, e.g. computed tomography (CT). The PSI uses the known surface structure of a bone for orientation during the intervention. Some surfaces of human bone are covered with a layer of cartilage which is hardly visible in clinically applied CT-imaging. This experimental study investigates ten different PSI designs and their effect to the overall accuracy when neglecting the cartilage in the design process. Therefore, a model of an acetabulum is used to simulate the use case of PSI in total hip arthroplasty. The concept of the different designs is to create structural elasticities in the PSI to avoid shifting of the whole instrument and rather have a small part of it deformed by cartilage. A needle array structure, for instance, should also be able to oust or penetrate remaining soft tissue in the acetabulum.

A multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer types.

Cancer research continues to highlight the extensive genetic diversity that exists both between and within tumors. This intrinsic heterogeneity poses one of the central challenges to predicting patient clinical outcome and the personalization of treatments. Despite progress in some individual tumor types, it is not yet possible to prospectively, accurately classify patients by expected survival. One hypothesis proposed to explain this is that the prognostic classifiers developed to date are insufficiently sensitive and specific; however it is also possible that patients are not equally easy to classify by any given biomarker. We demonstrate in a cohort of 45 AJCC stage III melanoma patients that clinico-pathologic biomarkers can identify those patients that are most likely to be misclassified by a molecular biomarker. The process of modelling the classifiability of patients was then replicated in a cohort of 49 stage II breast cancer patients and 53 stage III colon cancer patients. A multi-step procedure incorporating this information not only improved classification accuracy but also indicated the specific clinical attributes that had made classification problematic in each cohort. These findings show that, even when cohorts are of moderate size, including features that explain the patient-specific performance of a prognostic biomarker in a classification framework can improve the modelling and estimation of survival.

Identification, Review, and Systematic Cross-Validation of microRNA Prognostic Signatures in Metastatic Melanoma.

In metastatic melanoma, it is vital to identify and validate biomarkers of prognosis. Previous studies have systematically evaluated protein biomarkers or mRNA-based expression signatures. No such analyses have been applied to microRNA (miRNA)-based prognostic signatures. As a first step, we identified two prognostic miRNA signatures from publicly available data sets (Gene Expression Omnibus/The Cancer Genome Atlas) of global miRNA expression profiling information. A 12-miRNA signature predicted longer survival after surgery for resection of American Joint Committee on Cancer stage III disease (>4 years, no sign of relapse) and outperformed American Joint Committee on Cancer standard-of-care prognostic markers in leave-one-out cross-validation analysis (error rates 34% and 38%, respectively). A similar 15-miRNA biomarker derived from The Cancer Genome Atlas miRNA-seq data performed slightly worse (39%) than these current biomarkers. Both signatures were then assessed for replication in two independent data sets and subjected to systematic cross-validation together with the three other miRNA-based prognostic signatures proposed in the literature to date. Five miRNAs (miR-142-5p, miR-150-5p, miR-342-3p, miR-155-5p, and miR-146b-5p) were reproducibly associated with patient outcome and have the greatest potential for application in the clinic. Our extensive validation approach highlighted among multiple independent cohorts the translational potential and limitations of miRNA signatures, and pointed to future directions in the analysis of this emerging class of markers.