A questionnaire elicitation of surgeons' belief about learning within a surgical trial

PMID: 23145113 [PubMed - indexed for MEDLINE] PMCID: PMC3493499 Free PMC ArticlePeer reviewedPublisher PD

Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data

Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathophysiological boundaries of these phenotypes are unclear, limiting treatment stratification. Machine learning can identify groups with similar features using multidimensional data. Here, to classify MS subtypes based on pathological features, we apply unsupervised machine learning to brain MRI scans acquired in previously published studies. We use a training dataset from 6322 MS patients to define MRI-based subtypes and an independent cohort of 3068 patients for validation. Based on the earliest abnormalities, we define MS subtypes as cortex-led, normal-appearing white matter-led, and lesion-led. People with the lesion-led subtype have the highest risk of confirmed disability progression (CDP) and the highest relapse rate. People with the lesion-led MS subtype show positive treatment response in selected clinical trials. Our findings suggest that MRI-based subtypes predict MS disability progression and response to treatment and may be used to define groups of patients in interventional trials

A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis

In this paper we propose a novel method for the segmentation of longitudinal brain MRI scans of patients suffering from Multiple Sclerosis. The method builds upon an existing cross-sectional method for simultaneous whole-brain and lesion segmentation, introducing subject-specific latent variables to encourage temporal consistency between longitudinal scans. It is very generally applicable, as it does not make any prior assumptions on the scanner, the MRI protocol, or the number and timing of longitudinal follow-up scans. Preliminary experiments on three longitudinal datasets indicate that the proposed method produces more reliable segmentations and detects disease effects better than the cross-sectional method it is based upon

Self-avoiding walks and connective constants

The connective constant $\mu(G)$ of a quasi-transitive graph $G$ is the asymptotic growth rate of the number of self-avoiding walks (SAWs) on $G$ from a given starting vertex. We survey several aspects of the relationship between the connective constant and the underlying graph $G$. $\bullet$ We present upper and lower bounds for $\mu$ in terms of the vertex-degree and girth of a transitive graph. $\bullet$ We discuss the question of whether $\mu\ge\phi$ for transitive cubic graphs (where $\phi$ denotes the golden mean), and we introduce the Fisher transformation for SAWs (that is, the replacement of vertices by triangles). $\bullet$ We present strict inequalities for the connective constants $\mu(G)$ of transitive graphs $G$, as $G$ varies. $\bullet$ As a consequence of the last, the connective constant of a Cayley graph of a finitely generated group decreases strictly when a new relator is added, and increases strictly when a non-trivial group element is declared to be a further generator. $\bullet$ We describe so-called graph height functions within an account of "bridges" for quasi-transitive graphs, and indicate that the bridge constant equals the connective constant when the graph has a unimodular graph height function. $\bullet$ A partial answer is given to the question of the locality of connective constants, based around the existence of unimodular graph height functions. $\bullet$ Examples are presented of Cayley graphs of finitely presented groups that possess graph height functions (that are, in addition, harmonic and unimodular), and that do not. $\bullet$ The review closes with a brief account of the "speed" of SAW.Comment: Accepted version. arXiv admin note: substantial text overlap with arXiv:1304.721

Wheat Domestication Accelerated Evolution and Triggered Positive Selection in the β-Xylosidase Enzyme of Mycosphaerella graminicola

Plant cell wall degrading enzymes (PCWDEs) of plant pathogens are receiving increasing interest for their potential to trigger plant defense reactions. In an antagonistic co-evolutionary arms race between host and pathogen, PCWDEs could be under strong selection. Here, we tested the hypothesis that PCWDEs in the fungal wheat pathogen Mycosphaerella graminicola have been positively selected by analyzing ratios of non-synonymous and synonymous nucleotide changes in the genes encoding these enzymes. Analyses of five PCWDEs demonstrated that one (β-xylosidase) has been under strong positive selection and experienced an accelerated rate of evolution. In contrast, PCWDEs in the closest relatives of M. graminicola collected from wild grasses did not show evidence for selection or deviation from a molecular clock. Since the genealogical divergence of M. graminicola from these latter species coincided with the onset of agriculture, we hypothesize that the recent domestication of the host plant and/or agricultural practices triggered positive selection in β-xylosidase and that this enzyme played a key role in the emergence of a host-specialized pathogen

Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable

<p>Abstract</p> <p>Background</p> <p>By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Naïve Bayes and other machine learning algorithms we are able to distinguish between two classes of protein sequences: those folding to highly-designable conformations, or those folding to poorly- or non-designable conformations.</p> <p>Results</p> <p>First, we generate all possible compact lattice conformations for the specified shape (a hexagon or a triangle) on the 2D triangular lattice. Then we generate all possible binary hydrophobic/polar (H/P) sequences and by using a specified energy function, thread them through all of these compact conformations. If for a given sequence the lowest energy is obtained for a particular lattice conformation we assume that this sequence folds to that conformation. Highly-designable conformations have many H/P sequences folding to them, while poorly-designable conformations have few or no H/P sequences. We classify sequences as folding to either highly – or poorly-designable conformations. We have randomly selected subsets of the sequences belonging to highly-designable and poorly-designable conformations and used them to train several different standard machine learning algorithms.</p> <p>Conclusion</p> <p>By using these machine learning algorithms with ten-fold cross-validation we are able to classify the two classes of sequences with high accuracy – in some cases exceeding 95%.</p

Association between Carotid Plaque Characteristics and Cerebral White Matter Lesions: One-Year Follow-Up Study by MRI

Objective: To prospectively assess the relation between carotid plaque characteristics and the development of new cerebral white matter lesions (WMLs) at MRI. Methods: Fifty TIA/stroke patients with ipsilateral 30-69% carotid stenosis underwent MRI of the plaque at baseline. Total plaque volume and markers of vulnerability to thromboembolism (lipid-rich necrotic core [LRNC] volume, fibrous cap [FC] status, and presence of intraplaque hemorrhage [IPH]) were assessed. All patients also underwent brain MRI at baseline and after one year. Ipsilateral cerebral WMLs were quantified with a semiautomatic method. Results: Mean WML volume significantly increased over a one-year period (6.52 vs. 6.97 mm3, P = 0.005). WML volume at baseline and WML progression did not significantly differ (P>0.05) between patients with 30-49% and patients with 50-69% stenosis. There was a significant correlation between total plaque volume and baseline ipsilateral WML volume (Spearman ¿ = 0.393, P = 0.005). There was no significant correlation between total plaque volume and ipsilateral WML progression. There were no significant associations between LRNC volume and WML volume at baseline and WML progression. WML volume at baseline and WML progression did not significantly differ between patients with a thick and intact FC and patients with a thin and/or ruptured FC. WML volume at baseline and WML progression also did not significantly differ between patients with and without IPH. Conclusion: The results of this study indicate that carotid plaque burden is significantly associated with WML severity, but that there is no causal relationship between carotid plaque vulnerability and the occurrence of WMLs. © 2011 Kwee et al

Метод лабораторного определения параметров устройства гидроимпульсного воздействия

Дана стаття описує лабораторний метод, що визначає: мету, умови, обсяг і порядок проведення досліджень параметрів пристрою гідроімпульсної дії.This article describes the laboratory method that defines: the purpose, conditions, effort and procedure of the researching the device settings of hydroimpulsive impact

The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE).

In pharmacoepidemiology, routinely collected data from electronic health records (including primary care databases, registries, and administrative healthcare claims) are a resource for research evaluating the real world effectiveness and safety of medicines. Currently available guidelines for the reporting of research using non-randomised, routinely collected data - specifically the REporting of studies Conducted using Observational Routinely collected health Data (RECORD) and the Strengthening the Reporting of OBservational studies in Epidemiology (STROBE) statements - do not capture the complexity of pharmacoepidemiological research. We have therefore extended the RECORD statement to include reporting guidelines specific to pharmacoepidemiological research (RECORD-PE). This article includes the RECORD-PE checklist (also available on www.record-statement.org) and explains each checklist item with examples of good reporting. We anticipate that increasing use of the RECORD-PE guidelines by researchers and endorsement and adherence by journal editors will improve the standards of reporting of pharmacoepidemiological research undertaken using routinely collected data. This improved transparency will benefit the research community, patient care, and ultimately improve public health