2,995 research outputs found
Stability of a pure electron plasma in cylindrical geometry Progress report
Stability of cylindrical cold plasma consisting of electron
Significance of the Adrenals and the Testes for the Production of Testosterone (T) and Androstenedione (A) during Male Infancy
Contribution of the adrenal gland to the production of androstenedione and testosterone during the first two years of life
Androstenedione and testosterone were measured in whole adrenal glands of 56 previously healthy boys who died suddenly between birth and 2 yr of age. In each adrenal gland, the concentration of androstenedione considerably exceeded that of testosterone. The highest concentrations were found during the first week of life (median, 295 ng/g; range, 98- 320 ng/g). Thereafter, values decreased rapidly until the end of the first year of life (median, 10 ng/g; range, 4.4-22.7 ng/g). Adrenal testosterone concentrations averaged 15% of those of androstenedione in the same gland and similarly decreased until the end of the first year. The decrease of adrenal androgen concentrations paralleled the involution of the fetal adrenal zone. A close correlation existed between the concentration of androstenedione in adrenal tissue and plasma. However, no correlation existed between adrenal and plasma testosterone. When the adrenals and testes of the same infant were compared, there was 10 times more androstenedione in the adrenals than in the testes during the first 2 yr of life. The testes contained more testosterone than the adrenals only during the first 4 months. Thus, in infant boys the adrenals are the main source of androstenedione during the first 2 yr. After the sixth month of life, they also are the main source of testosterone
Testosterone and androstenedione concentrations in human testis and epididymis during the first two years of life
Testosterone and androstenedione were measured in testicular and epididymal tissue of 37 previously healthy infants between 1 and 24 months of age who died suddenly. In half of the patients elevated plasma levels of cortisol and androstenedione suggested preterminal stress. Plasma testosterone levels, however, did not differ from those in healthy infants. Testicular testosterone concentrations were maximal in boys from 1-3 months of age (median, 36.6 ng/g; range, 7-380 ng/g) with peak values similar to those found in pubertal or even adult testes. Thereafter testicular testosterone concentrations decreased and after the age of 6 months all values were below 12.5 ng/g, which corresponds to the low normal range of older prepubertal boys. Plasma testosterone and testicular testosterone correlated significantly (P less than 0.001). On average the testicular concentrations were 36.4 times higher than the corresponding plasma concentrations. Testicular androstenedione was low but correlated significantly with testicular testosterone (P less than 0.001). Epididymal testosterone concentrations were surprisingly high (1-3 months: median, 10.3 ng/g; range, 4-42.7 ng/g) and averaged 30% of the testicular testosterone concentration. Thus, epididymal testosterone concentrations were significantly higher than the circulating plasma testosterone levels, indicating the capacity of the infant epididymis to accumulate androgens. These findings suggest that high local testosterone concentrations during early infancy are important not only for the testis itself but particularly for the developing epididymi
Estrone and estradiol concentrations in human ovaries, testes, and adrenals during the first two years of life
To determine the origin of estrogens in infant blood, we measured estrone (E1) and estradiol (E2) in the gonads of 50 girls and 64 boys who died suddenly between birth and 2 yr of age as well as in the adrenals of 18 of these infant girls and 16 of the boys. In the adrenals, E1 [median, 2.8 ng/g (10.4 pmol/g); range, 1.1-4.8 ng/g (4.1- 17.8 pmol/g)] and E2 [median, 3.0 ng/g (10.9 pmol/g); range, 1.2-5.3 ng/g (4.4-19.5 pmol/g)] were found in similar concentrations and were independent of age and sex. In the gonads, E2 was the major estrogen, but the concentrations differed markedly between the sexes; E2 exceeded E1 almost 10-fold in the ovaries and 2-fold in the testes. On the average, the gonads of the infant girls had 5 times more E2 and 2 times more E1 than those of the boys. As in plasma, E2 concentrations were highest in the ovaries of 1- to 6-month-old girls [median, 10.5 ng/g (38.5 pmol/g); range, 1.1-55.1 ng/g (4.0-202.0 pmol/g)] and in testes of 1- to 3-month-old boys [median, 1.8 ng/g (6.6 pmol/g); range, 0.6- 6.4 ng/g (2.3-23.5 pmol/g)]. Ovarian E2 concentrations declined to less than 3.0 ng/g (11.0 pmol/g) by the end of the first year of life, and testicular E2 declined to less than 1.0 ng/g (3.7 pmol/g) after only 6 months of age. Gonadal estrogen concentrations paralleled changes in gonadal morphology. Ovarian weights varied in a pattern of rise and fall similar to that of ovarian E2 concentrations; the biggest ovaries contained multiple macroscopic cysts. Testicular E2 closely correlated with Leydig cell development and testicular testosterone concentrations. We infer, therefore, that the surge of plasma E2 in infant girls originates from ovarian follicles and that of boys from testicular Leydig cells, and that these both occur as a result of the postnatal surge in gonadotropin secretion. The basal plasma E1 and E2 pool, however, is derived from the adrenals and remains at a comparatively constant level in both sexe
Bayesian Detection of Clusters and Discontinuities in Disease Maps. (REVISED, February 1999)
An interesting epidemiological problem is the analysis of geographical variation in rates of disease incidence or mortality. One goal of such an analysis is to detect clusters of elevated (or lowered) risk in order to identify unknown risk factors regarding the disease. We propose a nonparametric Bayesian approach for the detection of such clusters based on Green's (1995) reversible jump MCMC methodology. The prior model assumes that geographical regions can be combined in clusters with constant relative risk within a cluster. The number of clusters, the location of the clusters and the risk within each cluster is unknown. This specification can be seen as a change-point problem of variable dimension in irregular, discrete space. We illustrate our method through an analysis of oral cavity cancer mortality rates in Germany and compare the results with those obtained by the commonly used Bayesian disease mapping method of Besag, York and Mollie (1991)
Transition from van-der-Waals to H Bonds dominated Interaction in n-Propanol physisorbed on Graphite
Multilayer sorption isotherms of 1-propanol on graphite have been measured by
means of high-resolution ellipsometry within the liquid regime of the adsorbed
film for temperatures ranging from 180 to 260 K. In the first three monolayers
the molecules are oriented parallel to the substrate and the growth is roughly
consistent with the Frenkel-Halsey-Hill-model (FHH) that is obeyed in
van-der-Waals systems on strong substrates. The condensation of the fourth and
higher layers is delayed with respect to the FHH-model. The fourth layer is
actually a bilayer. Furthermore there is indication of a wetting transition.
The results are interpreted in terms of hydrogen-bridge bonding within and
between the layers.Comment: 4 pages, 3 figure
Modelling categorical covariates in Bayesian disease mapping by partition structures
We consider the problem of mapping the risk from a disease using a series of regional counts of observed and expected cases, and information on potential risk factors. To analyse this problem from a Bayesian viewpoint we propose a methodology, which extends a spatial partition model by including categorical covariate information. Such an extension allows to detect clusters in the residual variation, reflecting further, possibly unobserved, covariates. The methodology is implemented by means of reversible jump Markov chain Monte Carlo sampling. An application is presented, in order to illustrate and compare our proposed extensions with a purely spatial partition model. Here we analyse a well-known dataset on lip cancer incidence in Scotland
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