Behavioral Recovery and Early Decision Making in Patients with Prolonged Disturbance in Consciousness after Traumatic Brain Injury

The extent of behavioral recovery that occurs in patients with traumatic disorders of consciousness (DoC) following discharge from the acute care setting has been under-studied and increases the risk of overly pessimistic outcome prediction. The aim of this observational cohort study was to systematically track behavioral and functional recovery in patients with prolonged traumatic DoC following discharge from the acute care setting. Standardized behavioral data were acquired from 95 patients in a minimally conscious (MCS) or vegetative state (VS) recruited from 11 clinic sites and randomly assigned to the placebo arm of a previously completed prospective clinical trial. Patients were followed for 6 weeks by blinded observers to determine frequency of recovery of six target behaviors associated with functional status. The Coma Recovery Scale-Revised and Disability Rating Scale were used to track reemergence of target behaviors and assess degree of functional disability, respectively. Twenty percent (95% confidence interval [CI]: 13-30%) of participants (mean age 37.2; median 47 days post-injury; 69 men) recovered all six target behaviors within the 6 week observation period. The odds of recovering a specific target behavior were 3.2 (95% CI: 1.2-8.1) to 7.8 (95% CI: 2.7-23.0) times higher for patients in MCS than for those in VS. Patients with preserved language function ("MCS+") recovered the most behaviors (p ≤ 0.002) and had the least disability (p ≤ 0.002) at follow-up. These findings suggest that recovery of high-level behaviors underpinning functional independence is common in patients with prolonged traumatic DoC. Clinicians involved in early prognostic counseling should recognize that failure to emerge from traumatic DoC before 28 days does not necessarily portend unfavorable outcome

Induced pluripotent stem cell-derived cardiac progenitors differentiate to cardiomyocytes and form biosynthetic tissues.

The mammalian heart has little capacity to regenerate, and following injury the myocardium is replaced by non-contractile scar tissue. Consequently, increased wall stress and workload on the remaining myocardium leads to chamber dilation, dysfunction, and heart failure. Cell-based therapy with an autologous, epigenetically reprogrammed, and cardiac-committed progenitor cell source could potentially reverse this process by replacing the damaged myocardium with functional tissue. However, it is unclear whether cardiac progenitor cell-derived cardiomyocytes are capable of attaining levels of structural and functional maturity comparable to that of terminally-fated cardiomyocytes. Here, we first describe the derivation of mouse induced pluripotent stem (iPS) cells, which once differentiated allow for the enrichment of Nkx2-5(+) cardiac progenitors, and the cardiomyocyte-specific expression of the red fluorescent protein. We show that the cardiac progenitors are multipotent and capable of differentiating into endothelial cells, smooth muscle cells and cardiomyocytes. Moreover, cardiac progenitor selection corresponds to cKit(+) cell enrichment, while cardiomyocyte cell-lineage commitment is concomitant with dual expression of either cKit/Flk1 or cKit/Sca-1. We proceed to show that the cardiac progenitor-derived cardiomyocytes are capable of forming electrically and mechanically coupled large-scale 2D cell cultures with mature electrophysiological properties. Finally, we examine the cell progenitors' ability to form electromechanically coherent macroscopic tissues, using a physiologically relevant 3D culture model and demonstrate that following long-term culture the cardiomyocytes align, and form robust electromechanical connections throughout the volume of the biosynthetic tissue construct. We conclude that the iPS cell-derived cardiac progenitors are a robust cell source for tissue engineering applications and a 3D culture platform for pharmacological screening and drug development studies

Investigation of the influence of rail hardness on the wear of rail and wheel materials under dry conditions (ICRI wear mapping project)

Some railway managers and practitioners fear that introducing premium rail materials will have a detrimental effect on the wheels of trains that use the line. A review of relevant investigations across all scales in the laboratory, and in the field has been carried out. This showed that, as rail hardness increases, its wear, and overall system wear reduces. Wheel wear does increase with increasing rail hardness, but only for wheels running on rails that are softer than them. Similar trends were observed in all studies, so it seems that the fears were unfounded. While the wear trends appear well characterised some issues have been identified. One relates to the varying work hardening capability of wheel and rail materials. Often only bulk hardness is quoted, but work hardening can increase material surface hardness by up to 2.5 times and make materials that were initially softer, harder than the opposing material. Another related issue is test length. It is essential that enough cycles are applied such that the materials reach steady state wear, i.e., the point at which work hardening has reached its limit. In previous work it is not always clear that steady state wear has been reached. Some gaps have been identified in the current knowledge base, the largest of which is the failure to determine which mechanisms lead to the wear trends seen. Analysis of recent work on different clad layers on rail discs and premium rail materials allowed some of these gaps to be addressed. Results indicated that opposing wheel material hardened to the same level independent of rail hardness. Wheel wear is therefore stress driven under the conditions used, and dictated by the wheel material properties only. At higher slip levels relationships become less clear, but here temperature and therefore hot hardness is most influential and is as yet uncharacterised

Twin disc assessment of wear regime transitions and rolling contact fatigue in R400HT – E8 pairs

Twin disc tests were carried out to evaluate the wear resistance and Rolling Contact Fatigue (RCF) of premium R400HT rail samples in contact with E8 wheel samples. The wear rate and friction coefficient were correlated with the frictional work expended at the contact interface (the Tgamma approach). Accelerated RCF tests were also carried out on the premium R400HT rail and the results were compared to those obtained for standard R260 rail. The wear rates of rail samples were consistently lower than those reported in the literature for other contacting pairs in which the rail material studied is softer than R400HT. Also, the energy needed for the transition from the moderate to severe wear regime significantly increased for the hardened rail. Fatigue cracks were shallower for R400HT when compared with standard rail material. Hardened rails also showed lower mean spacing between fatigue cracks. This new information can be used to improve wear simulations of wheels and rails by using more realistic wear equations

The effect of organelle discovery upon sub-cellular protein localisation.

Prediction of protein sub-cellular localisation by employing quantitative mass spectrometry experiments is an expanding field. Several methods have led to the assignment of proteins to specific subcellular localisations by partial separation of organelles across a fractionation scheme coupled with computational analysis. Methods developed to analyse organelle data have largely employed supervised machine learning algorithms to map unannotated abundance profiles to known protein–organelle associations. Such approaches are likely to make association errors if organelle-related groupings present in experimental output are not included in data used to create a protein–organelle classifier. Currently, there is no automated way to detect organelle-specific clusters within such datasets. In order to address the above issues we adapted a phenotype discovery algorithm, originally created to filter image-based output for RNAi screens, to identify putative subcellular groupings in organelle proteomics experiments. We were able to mine datasets to a deeper level and extract interesting phenotype clusters for more comprehensive evaluation in an unbiased fashion upon application of this approach. Organelle-related protein clusters were identified beyond those sufficiently annotated for use as training data. Furthermore, we propose avenues for the incorporation of observations made into general practice for the classification of protein–organelle membership from quantitative MS experiments. Biological significance Protein sub-cellular localisation plays an important role in molecular interactions, signalling and transport mechanisms. The prediction of protein localisation by quantitative mass-spectrometry (MS) proteomics is a growing field and an important endeavour in improving protein annotation. Several such approaches use gradient-based separation of cellular organelle content to measure relative protein abundance across distinct gradient fractions. The distribution profiles are commonly mapped in silico to known protein–organelle associations via supervised machine learning algorithms, to create classifiers that associate unannotated proteins to specific organelles. These strategies are prone to error, however, if organelle-related groupings present in experimental output are not represented, for example owing to the lack of existing annotation, when creating the protein–organelle mapping. Here, the application of a phenotype discovery approach to LOPIT gradient-based MS data identifies candidate organelle phenotypes for further evaluation in an unbiased fashion. Software implementation and usage guidelines are provided for application to wider protein–organelle association experiments. In the wider context, semi-supervised organelle discovery is discussed as a paradigm with which to generate new protein annotations from MS-based organelle proteomics experiments. This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012]

Low temperature and cost-effective growth of vertically aligned carbon nanofibers using spin-coated polymer-stabilized palladium nanocatalysts

We describe a fast and cost-effective process for the growth of carbon nanofibers (CNFs) at a temperature compatible with complementary metal oxide semiconductor technology, using highly stable polymer-Pd nanohybrid colloidal solutions of palladium catalyst nanoparticles (NPs). Two polymer-Pd nanohybrids, namely poly(lauryl methacrylate)-block-poly((2-acetoacetoxy) ethyl methacrylate)/Pd (LauMA(x)-b-AEMA(y)/Pd) and polyvinylpyrrolidone/Pd were prepared in organic solvents and spin-coated onto silicon substrates. Subsequently, vertically aligned CNFs were grown on these NPs by plasma enhanced chemical vapor deposition at different temperatures. The electrical properties of the grown CNFs were evaluated using an electrochemical method, commonly used for the characterization of supercapacitors. The results show that the polymer-Pd nanohybrid solutions offer the optimum size range of palladium catalyst NPs enabling the growth of CNFs at temperatures as low as 350 degrees C. Furthermore, the CNFs grown at such a low temperature are vertically aligned similar to the CNFs grown at 550 degrees C. Finally the capacitive behavior of these CNFs was similar to that of the CNFs grown at high temperature assuring the same electrical properties thus enabling their usage in different applications such as on-chip capacitors, interconnects, thermal heat sink and energy storage solutions

Executive function profiles of preschool children with Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder: a systematic review

Background: Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are both associated with differences in Executive Functioning (EF). There is lack of clarity around the specificity or overlap of EF differences in early childhood when both disorders are first emerging. Method: This systematic review aims to delineate preschool EF profiles by examining studies comparing the EF profiles of children with and without ASD or ADHD. Five electronic databases were systematically searched (last search in May 2022) to identify published, quantitative studies of global and specific EF (Inhibition, Shifting, Working Memory, Planning and Attentional Control), comparing children aged 2-6 with a diagnosis of ASD or ADHD to peers without ASD or ADHD. Results: Thirty-one empirical studies (10 ADHD and 21 ASD studies) met criteria for inclusion. EF profiles in preschool ASD were characterised by consistent Shifting, and, in most cases, Inhibition impairments. ADHD studies consistently reported impairments in Inhibition and Planning, and in most cases Working Memory. Findings with regards to sustained Attention and Shifting in ADHD and Working Memory and Planning in ASD were mixed. Conclusions: Overall, current evidence indicates overlap but also some specificity in EF impairments in preschool ASD and ADHD. There were differences in the degree to which individual domains were impaired, with Shifting more consistently impaired in ASD, and Inhibition, Working Memory and Planning in ADHD. Methodological issues and differences in methods of outcome measurement could potentially underlie mixed findings, as informant-based measures revealed more robust EF impairments than laboratory-based tasks