A Trade-Off between Somatosensory and Auditory Related Brain Activity during Object Naming But Not Reading.

The parietal operculum, particularly the cytoarchitectonic area OP1 of the secondary somatosensory area (SII), is involved in somatosensory feedback. Using fMRI with 58 human subjects, we investigated task-dependent differences in SII/OP1 activity during three familiar speech production tasks: object naming, reading and repeatedly saying "1-2-3." Bilateral SII/OP1 was significantly suppressed (relative to rest) during object naming, to a lesser extent when repeatedly saying "1-2-3" and not at all during reading. These results cannot be explained by task difficulty but the contrasting difference between naming and reading illustrates how the demands on somatosensory activity change with task, even when motor output (i.e., production of object names) is matched. To investigate what determined SII/OP1 deactivation during object naming, we searched the whole brain for areas where activity increased as that in SII/OP1 decreased. This across subject covariance analysis revealed a region in the right superior temporal sulcus (STS) that lies within the auditory cortex, and is activated by auditory feedback during speech production. The tradeoff between activity in SII/OP1 and STS was not observed during reading, which showed significantly more activation than naming in both SII/OP1 and STS bilaterally. These findings suggest that, although object naming is more error prone than reading, subjects can afford to rely more or less on somatosensory or auditory feedback during naming. In contrast, fast and efficient error-free reading places more consistent demands on both types of feedback, perhaps because of the potential for increased competition between lexical and sublexical codes at the articulatory level

Validity and repeatability of three in-shoe pressure measurement systems

In-shoe pressure measurement devices are used in research and clinic to quantify plantar foot pressures. Various devices are available, differing in size, sensor number and type; therefore accuracy and repeatability. Three devices (Medilogic, Tekscan and Pedar) were examined in a 2 day×3 trial design, quantifying insole response to regional and whole insole loading. The whole insole protocol applied an even pressure (50-600kPa) to the insole surface for 0-30s in the Novel TruBlue™ device. The regional protocol utilised cylinders with contact surfaces of 3.14 and 15.9cm(2) to apply pressures of 50 and 200kPa. The validity (% difference and Root Mean Square Error: RMSE) and repeatability (Intra-Class Correlation Coefficient: ICC) of the applied pressures (whole insole) and contact area (regional) were outcome variables. Validity of the Pedar system was highest (RMSE 2.6kPa; difference 3.9%), with the Medilogic (RMSE 27.0kPa; difference 13.4%) and Tekscan (RMSE 27.0kPa; difference 5.9%) systems displaying reduced validity. The average and peak pressures demonstrated high between-day repeatability for all three systems and each insole size (ICC≥0.859). The regional contact area % difference ranged from -97 to +249%, but the ICC demonstrated medium to high between-day repeatability (ICC≥0.797). Due to the varying responses of the systems, the choice of an appropriate pressure measurement device must be based on the loading characteristics and the outcome variables sought. Medilogic and Tekscan were most effective between 200 and 300kPa; Pedar performed well across all pressures. Contact area was less precise, but relatively repeatable for all systems

headspace - Australia's innovation in youth mental health: who are the clients and why are they presenting?

OBJECTIVES: To provide the first national profile of the characteristics of young people (aged 12-25 years) accessing headspace centre services - the Australian Government's innovation in youth mental health service delivery - and investigate whether headspace is providing early service access for adolescents and young adults with emerging mental health problems. DESIGN AND PARTICIPANTS: Census of all young people accessing a headspace centre across the national network of 55 centres comprising a total of 21 274 headspace clients between 1 January and 30 June 2013. MAIN OUTCOME MEASURES: Reason for presentation, Kessler Psychological Distress Scale, stage of illness, diagnosis, functioning. RESULTS: Young people were most likely to present with mood and anxiety symptoms and disorders, self-reporting their reason for attendance as problems with how they felt. Client demographic characteristics tended to reflect population-level distributions, although clients from regional areas and of Aboriginal and Torres Strait Islander background were particularly well represented, whereas those who were born outside Australia were underrepresented. CONCLUSION: headspace centres are providing a point of service access for young Australians with high levels of psychological distress and need for care in the early stages of the development of mental disorder

Wave intensity analysis and its application to the coronary circulation.

Wave intensity analysis (WIA) is a technique developed from the field of gas dynamics that is now being applied to assess cardiovascular physiology. It allows quantification of the forces acting to alter flow and pressure within a fluid system, and as such it is highly insightful in ascribing cause to dynamic blood pressure or velocity changes. When co-incident waves arrive at the same spatial location they exert either counteracting or summative effects on flow and pressure. WIA however allows waves of different origins to be measured uninfluenced by other simultaneously arriving waves. It therefore has found particular applicability within the coronary circulation where both proximal (aortic) and distal (myocardial) ends of the coronary artery can markedly influence blood flow. Using these concepts, a repeating pattern of 6 waves has been consistently identified within the coronary arteries, 3 originating proximally and 3 distally. Each has been associated with a particular part of the cardiac cycle. The most clinically relevant wave to date is the backward decompression wave, which causes the marked increase in coronary flow velocity observed at the start of the diastole. It has been proposed that this wave is generated by the elastic re-expansion of the intra-myocardial blood vessels that are compressed during systolic contraction. Particularly by quantifying this wave, WIA has been used to provide mechanistic and prognostic insight into a number of conditions including aortic stenosis, left ventricular hypertrophy, coronary artery disease and heart failure. It has proven itself to be highly sensitive and as such a number of novel research directions are encouraged where further insights would be beneficial

Outstanding Issues in Solar Dynamo Theory

The magnetic activity of the Sun, as manifested in the sunspot cycle, originates deep within its convection zone through a dynamo mechanism which involves non-trivial interactions between the plasma and magnetic field in the solar interior. Recent advances in magnetohydrodynamic dynamo theory have led us closer towards a better understanding of the physics of the solar magnetic cycle. In conjunction, helioseismic observations of large-scale flows in the solar interior has now made it possible to constrain some of the parameters used in models of the solar cycle. In the first part of this review, I briefly describe this current state of understanding of the solar cycle. In the second part, I highlight some of the outstanding issues in solar dynamo theory related to the the nature of the dynamo $\alpha$-effect, magnetic buoyancy and the origin of Maunder-like minima in activity. I also discuss how poor constraints on key physical processes such as turbulent diffusion, meridional circulation and turbulent flux pumping confuse the relative roles of these vis-a-vis magnetic flux transport. I argue that unless some of these issues are addressed, no model of the solar cycle can claim to be ``the standard model'', nor can any predictions from such models be trusted; in other words, we are still not there yet.Comment: To appear in "Magnetic Coupling between the Interior and the Atmosphere of the Sun", eds. S.S. Hasan and R.J. Rutten, Astrophysics and Space Science Proceedings, Springer-Verlag, Heidelberg, Berlin, 200

Estimating the material properties of heel pad sub-layers using inverse finite element analysis

Detailed information about the biomechanical behaviour of plantar heel pad tissue contributes to our understanding of load transfer when the foot impacts the ground. The objective of this work was to obtain the hyperelastic and viscoelastic material properties of heel pad sub-layers (skin, micro-chamber and macro-chamber layers) in-vivo. An anatomically detailed 3D Finite Element model of the human heel was used to derive the sub-layer material properties. A combined ultrasound imaging and motorised platform system was used to compress heel pad and to create input data for the Finite Element model. The force-strain responses of the heel pad and its sub-layers under slow compression (5mm/s) and rapid loading-hold-unloading cycles (225mm/s), were measured and hyperelastic and viscoelastic properties of the three heel pad sub-layers were estimated by the model. The loaded (under ~315N) thickness of the heel pad was measured from MR images and used for hyperelastic model validation. The capability of the model to predict peak plantar pressure was used for further validation. Experimental responses of the heel pad under different dynamic loading scenarios (loading-hold-unloading cycles at 141mm/s and sinusoidal loading with maximum velocity of 300mm/s) were used to validate the viscoelastic model. Good agreement was achieved between the predicted and experimental results for both hyperelastic (<6.4% unloaded thickness, 4.4% maximum peak plantar pressure) and viscoelastic (Root Mean Square errors for loading and unloading periods <14.7%, 5.8% maximum force) simulations. This paper provides the first definition of material properties for heel pad sub-layers by using in-vivo experimental force-strain data and an anatomically detailed 3D Finite Element model of the heel

Wave intensity analysis and its application to the coronary circulation.

Wave intensity analysis (WIA) is a technique developed from the field of gas dynamics that is now being applied to assess cardiovascular physiology. It allows quantification of the forces acting to alter flow and pressure within a fluid system, and as such it is highly insightful in ascribing cause to dynamic blood pressure or velocity changes. When co-incident waves arrive at the same spatial location they exert either counteracting or summative effects on flow and pressure. WIA however allows waves of different origins to be measured uninfluenced by other simultaneously arriving waves. It therefore has found particular applicability within the coronary circulation where both proximal (aortic) and distal (myocardial) ends of the coronary artery can markedly influence blood flow. Using these concepts, a repeating pattern of 6 waves has been consistently identified within the coronary arteries, 3 originating proximally and 3 distally. Each has been associated with a particular part of the cardiac cycle. The most clinically relevant wave to date is the backward decompression wave, which causes the marked increase in coronary flow velocity observed at the start of the diastole. It has been proposed that this wave is generated by the elastic re-expansion of the intra-myocardial blood vessels that are compressed during systolic contraction. Particularly by quantifying this wave, WIA has been used to provide mechanistic and prognostic insight into a number of conditions including aortic stenosis, left ventricular hypertrophy, coronary artery disease and heart failure. It has proven itself to be highly sensitive and as such a number of novel research directions are encouraged where further insights would be beneficial

A structural connectivity convergence zone in the ventral and anterior temporal lobes: Data-driven evidence from structural imaging

The hub-and-spoke model of semantic cognition seeks to reconcile embodied views of a fully distributed semantic network with patient evidence, primarily from semantic dementia, who demonstrate modality-independent conceptual deficits associated with atrophy centred on the ventrolateral anterior temporal lobe. The proponents of this model have recently suggested that the temporal cortex is a graded representational space where concepts become less linked to a specific modality as they are processed farther away from primary and secondary sensory cortices and towards the ventral anterior temporal lobe. To explore whether there is evidence that the connectivity patterns of the temporal lobe converge in its ventral anterior end the current study uses three dimensional Laplacian eigenmapping, a technique that allows visualisation of similarity in a low dimensional space. In this space similarity is encoded in terms of distances between data points. We found that the ventral and anterior temporal lobe is in a unique position of being at the centre of mass of the data points within the connective similarity space. This can be interpreted as the area where the connectivity profiles of all other temporal cortex voxels converge. This study is the first to explicitly investigate the pattern of connectivity and thus provides the missing link in the evidence that the ventral anterior temporal lobe can be considered a multi-modal graded hub

Towards the identification of essential genes using targeted genome sequencing and comparative analysis

BACKGROUND: The identification of genes essential for survival is of theoretical importance in the understanding of the minimal requirements for cellular life, and of practical importance in the identification of potential drug targets in novel pathogens. With the great time and expense required for experimental studies aimed at constructing a catalog of essential genes in a given organism, a computational approach which could identify essential genes with high accuracy would be of great value. RESULTS: We gathered numerous features which could be generated automatically from genome sequence data and assessed their relationship to essentiality, and subsequently utilized machine learning to construct an integrated classifier of essential genes in both S. cerevisiae and E. coli. When looking at single features, phyletic retention, a measure of the number of organisms an ortholog is present in, was the most predictive of essentiality. Furthermore, during construction of our phyletic retention feature we for the first time explored the evolutionary relationship among the set of organisms in which the presence of a gene is most predictive of essentiality. We found that in both E. coli and S. cerevisiae the optimal sets always contain host-associated organisms with small genomes which are closely related to the reference. Using five optimally selected organisms, we were able to improve predictive accuracy as compared to using all available sequenced organisms. We hypothesize the predictive power of these genomes is a consequence of the process of reductive evolution, by which many parasites and symbionts evolved their gene content. In addition, essentiality is measured in rich media, a condition which resembles the environments of these organisms in their hosts where many nutrients are provided. Finally, we demonstrate that integration of our most highly predictive features using a probabilistic classifier resulted in accuracies surpassing any individual feature. CONCLUSION: Using features obtainable directly from sequence data, we were able to construct a classifier which can predict essential genes with high accuracy. Furthermore, our analysis of the set of genomes in which the presence of a gene is most predictive of essentiality may suggest ways in which targeted sequencing can be used in the identification of essential genes. In summary, the methods presented here can aid in the reduction of time and money invested in essential gene identification by targeting those genes for experimentation which are predicted as being essential with a high probability

The Test Your Memory for Mild Cognitive Impairment (TYM-MCI)

BACKGROUND: To validate a short cognitive test: the Test Your Memory for Mild Cognitive Impairment (TYM-MCI) in the diagnosis of patients with amnestic mild cognitive impairment or mild Alzheimer’s disease (aMCI/AD). METHODS: Two hundred and two patients with mild memory problems were recruited. All had ‘passed’ the Mini-Mental State Examination (MMSE). Patients completed the TYM-MCI, the Test Your Memory test (TYM), MMSE and revised Addenbrooke’s Cognitive Examination (ACE-R), had a neurological examination, clinical diagnostics and multidisciplinary team review. RESULTS: As a single test, the TYM-MCI performed as well as the ACE-R in the distinction of patients with aMCI/AD from patients with subjective memory impairment with a sensitivity of 0.79 and specificity of 0.91. Used in combination with the ACE-R, it provided additional value and identified almost all cases of aMCI/AD. The TYM-MCI correctly classified most patients who had equivocal ACE-R scores. Integrated discriminant improvement analysis showed that the TYM-MCI added value to the conventional memory assessment. Patients initially diagnosed as unknown or with subjective memory impairment who were later rediagnosed with aMCI/AD scored poorly on their original TYM-MCI. CONCLUSION: The TYM-MCI is a powerful short cognitive test that examines verbal and visual recall and is a valuable addition to the assessment of patients with aMCI/AD. It is simple and cheap to administer and requires minimal staff time and training.JBR was supported by the Wellcome Trust (103838)