Clustering consistency in neuroimaging data analysis

Clustering techniques have been applied to neuroscience data analysis for decades. New algorithms keep being developed and applied to address different problems. However, when it comes to the applications of clustering, it is often hard to select the appropriate algorithm and evaluate the quality of clustering results due to the unknown ground truth. It is also the case that conclusions might be biased based on only one specific algorithm because each algorithm has its own assumption of the structure of the data, which might not be the same as the real data. In this paper, we explore the benefits of integrating the clustering results from multiple clustering algorithms by a tunable consensus clustering strategy and demonstrate the importance and necessity of consistency in neuroimaging data analysis

Measurement of Intraspinal Pressure After Spinal Cord Injury: Technical Note from the Injured Spinal Cord Pressure Evaluation Study.

Intracranial pressure (ICP) is routinely measured in patients with severe traumatic brain injury (TBI). We describe a novel technique that allowed us to monitor intraspinal pressure (ISP) at the injury site in 14 patients who had severe acute traumatic spinal cord injury (TSCI), analogous to monitoring ICP after brain injury. A Codman probe was inserted subdurally to measure the pressure of the injured spinal cord compressed against the surrounding dura. Our key finding is that it is feasible and safe to monitor ISP for up to a week in patients after TSCI, starting within 72 h of the injury. With practice, probe insertion and calibration take less than 10 min. The ISP signal characteristics after TSCI were similar to the ICP signal characteristics recorded after TBI. Importantly, there were no associated complications. Future studies are required to determine whether reducing ISP improves neurological outcome after severe TSCI

PMD143 Economic Analysis Of Evarrest® Sealant Matrix Compared With Standard Of Care In Severe Soft Tissue Surgical Bleeding: An Italian Hospital Perspective

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Investigation of SHG in new scandium borate with three cations by the Kurtz-Perry method

This work is dedicated to study the optical properties of scandium borates with the general formula RExPrySc2+z(BO3)4 (x + y + z = 2, RE = Nd, Sm, Tb, Tm, Yb), grown by the TSSG method. The structure, absorption and luminescence of these crystals have been investigated

Paradigm of tunable clustering using binarization of consensus partition matrices (Bi-CoPaM) for gene discovery

Copyright @ 2013 Abu-Jamous et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Clustering analysis has a growing role in the study of co-expressed genes for gene discovery. Conventional binary and fuzzy clustering do not embrace the biological reality that some genes may be irrelevant for a problem and not be assigned to a cluster, while other genes may participate in several biological functions and should simultaneously belong to multiple clusters. Also, these algorithms cannot generate tight clusters that focus on their cores or wide clusters that overlap and contain all possibly relevant genes. In this paper, a new clustering paradigm is proposed. In this paradigm, all three eventualities of a gene being exclusively assigned to a single cluster, being assigned to multiple clusters, and being not assigned to any cluster are possible. These possibilities are realised through the primary novelty of the introduction of tunable binarization techniques. Results from multiple clustering experiments are aggregated to generate one fuzzy consensus partition matrix (CoPaM), which is then binarized to obtain the final binary partitions. This is referred to as Binarization of Consensus Partition Matrices (Bi-CoPaM). The method has been tested with a set of synthetic datasets and a set of five real yeast cell-cycle datasets. The results demonstrate its validity in generating relevant tight, wide, and complementary clusters that can meet requirements of different gene discovery studies.National Institute for Health Researc

A structured review of outcome measures for the assessment of rehabilitation interventions for spinal cord injury

OBJECTIVES:To review the measurement properties of outcome measures of function or mobility currently used in the context of spinal cord injury (SCI). METHODS: A keyword search of multiple databases to identify original papers. Papers were reviewed where they had included an evaluation, of people with SCI, of the psychometric properties of an outcome measure, which included functional or mobility domains.Information was extracted concerning item generation, ease and intended method of use and scale properties, in particular: reliability, validity and responsiveness. Conclusions were reached concerning the psychometric properties of each instrument. RESULTS:Eight outcome measures were identified (plus adapted versions). Five had originally been developed specifically for evaluating patients with SCI (chiefly reflecting clinicians' perspectives), the remaining three had not. The psychometric properties of the instruments varied, with some mixed/contradictory evidence likely relating to differing study sample sizes, characteristics and variable quality. Instruments also varied in stated purpose or emphasis.CONCLUSION:In addition to weighing evidence concerning measurement properties, users need to consider the stated purpose and item content of instruments in relation to their specific aims. With regard to the former, while reviewed instruments had some flaws, the Spinal cord Independence Measure (revised version III), Quadriplegia Index of Function (Short-form), Needs Assessment Checklist and SIP68 appeared the best, despite limited evidence of their responsiveness.

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

Exploration of distance metrics in consensus clustering analysis of FMRI data

Clustering techniques have gained great popularity in neuroscience data analysis especially in analysing data from complex experiment paradigm where it is hard to apply traditional model-based method. However, when employing clustering analysis, many clustering algorithms are available nowadays and even with an individual clustering algorithm, choices like parameter settings and distance metrics are very likely to have impacts on the final clustering results. In our previous work, we have demonstrated the benefits of integrating clustering results from multiple clustering algorithms, which provides more stable, reproducible, and complete clustering solutions. In this paper, we aim to further inspect the possible influences from the choices of distance metrics in clustering analysis

Linear and nonlinear optical properties of trigonal borate crystals K7MIn2-xYbx(B5O10)3 (M = Ca, Sr, Ba; x=0…2) with isolated B5O10 units

Noncentrosymmetric borates K7MIn2−xYbx(B5O10)3 (M = Ca, Sr, Ba; x = 0…2) were synthesized by the solid state reaction and the crystals were successfully grown by the top seeded solution growth method using the K2O-B2O3-MF2 flux. According to Rietveld refinement, the crystal structure belongs to the noncentrosymmetric R32 space group. Also, the octahedrally coordinated In atoms are located at wide ranges ∼8 Å which may be promising for phosphor and laser applications. Samples with ytterbium show a characteristic emission band in the range of 950–1050 nm related to the 2F5/2 → 2F7/2 transition of Yb3+ ions that is commonly used for laser generation. IR, Raman and absorption spectra were obtained for the samples as well. The short cut edge of UV absorption, SHG intensity comparable with KDP and low concentration quenching of luminescence suggest that the K7MIn2−xYbx(B5O10)3 borates are promising self-frequency doubling materials

Impact of Scottish vocational qualifications on residential child care : have they fulfilled the promise?

This article will present findings from a doctoral study exploring the impact of 'SVQ Care: Promoting Independence (level III)' within children's homes. The study focuses on the extent to which SVQs enhance practice and their function within a 'learning society'. A total of 30 staff were selected from seven children's homes in two different local authority social work departments in Scotland. Each member of staff was interviewed on four separate occasions over a period of 9 months. Interviews were structured using a combination of repertory grids and questions. Particular focus was given to the assessment process, the extent to which SVQs enhance practice and the learning experiences of staff. The findings suggest that there are considerable deficiencies both in terms of the SVQ format and the way in which children's homes are structured for the assessment of competence. Rather than address the history of failure within residential care, it appears that SVQs have enabled the status quo to be maintained whilst creating an 'illusion' of change within a learning society