Age-at-first-registration and heterogeneity in affective psychoses

Background: Previous research into age of onset in affective disorders has produced conflicting results. This paper examines the influence of heterogeneity on the age-at-first-registration distribution for the ICD-9 diagnostic group 'affective psychosis'. Method: For 1979-1991, data for age-at-first-registration for 4985 individuals diagnosed with affective psychosis (ICD-9 296.x) were extracted from a name-linked mental health register. These data were divided into (i) '296.1 only', a category used to code unipolar depression (males = 700; females = 1321); and (ii) '296 other', all 296 cases other than 296.1 (males = 1280; females = 1684). Inception rates for each 5-year age division were adjusted for the background population age-structure as a rate per 100 000 population. Results: The age-at-first-registration distribution for affective psychosis has a wide age range, with women outnumbering men. There is a near-linear increase in inception rates for both men and women with 296.1 only, while the bulk of those with affective psychoses (296 other) have an inverted U-shaped age distribution. Males have an earlier modal age-at-first-registration for 296 other compared to females. Conclusion: The heterogeneity in terms of subtypes and sex in affective psychosis clouds the interpretation of age-at-first-registration. Separating those with unipolar psychotic depression from other subclassifications and differentiating by sex may provide clues to factors that precipitate the onset of affective psychosis.

Dynamic breast MRI: Image registration and its impact on enhancement curve estimation

A novel algorithm for performing registration of dynamic contrast-enhanced (DCE) MRI data of the breast is presented. It is based on an algorithm known as iterated dynamic programming originally devised to solve the stereo matching problem. Using artificially distorted DCE-MRI breast images it is shown that the proposed algorithm is able to correct for movement and distortions over a larger range than is likely to occur during routine clinical examination. In addition, using a clinical DCE-MRI data set with an expertly labeled suspicious region, it is shown that the proposed algorithm significantly reduces the variability of the enhancement curves at the pixel level yielding more pronounced uptake and washout phases.

Identifying and discriminating among lucerne cultivars using plant morphological characters

The use of morphological data obtained from field (plot test) and glasshouse trials to identify and discriminate among four Iranian and two New Zealand lucerne (Medicago sativa L.) cultivars was investigated, following guidelines established by the International Union for the Protection of New Varieties of Plants (UPOV) for cultivar registration and the Organisation for Economic Co-operation and Development (OECD) for seed certification. Data were collected for terminal leaflet length, width and ratio, angle of stem growth, date of first flowering, stem height at first flowering, flower colour, cutting recovery height, and disease scores. None of these characters were sufficient to identify or discriminate among the six cultivars. The results indicate a need to find cost-effective and efficient laboratory techniques to enhance the assessment of distinctness of lucerne cultivars (UPOV) and for determining cultivar purity for lucerne seed certification (OECD).

An electrical heart model incorporating real geometry and motion

Abstract—This paper describes an electrical model of the ventricles incorporating real geometry and motion. Cardiac geometry and motion is obtained from segmentations of multipleslice MRI time sequences. A static heart model developed previously is deformed to match the observed geometry using a novel shape registration algorithm. The resulting electrocardiograms and body surface potential maps are compared to a static simulation in the resting heart. These results demonstrate that introducing motion into the cardiac model modifies the ECG during the T wave at peak contraction of the ventricles.