Volume estimation of biological objects by systematic sections

The absolute volume of biological objects is often estimated stereologically from an exhaustive set of systematic sections. The usual volume estimator is the sum of the section contents times the distance between sections. For systematic sectioning with a random start, it has been recently shown that is unbiased when m, the ratio between projected object length and section distance, is an integer number (Cruz-Orive 1985). As this quantity is no integer in the real world, we have explored the properties of in the general and realistic situation m . The unbiasedness of under appropriate sampling conditions is demonstrated for the arbitrary compact set in 3 dimensions by a rigorous proof. Exploration of further properties of for the general triaxial ellipsoid leads to a new class of non-elementary real functions with common formal structure which we denote as np-functions. The relative mean square error (CE ²) of in ellipsoids is an oscillating differentiable np-function, which reduces to the known result CE ²= 1/(5m ⁴) for integer m. As a biological example the absolute volumes of 10 left cardiac ventricles and their internal cavities were estimated from systematic sections. Monte Carlo simulation of replicated systematic sectioning is shown to be improved by using m instead of m . In agreement with the geometric model of ellipsoids with some added shape irregularities, mean empirical CE was proportional to m ^–1.36 and m^–1.73 in the cardiac ventricle and its cavity. The considerable variance reduction by systematic sectioning is shown to be a geometric realization of the principle of antithetic variates.     

Statistical techniques for detection of major genes in animal breeding data

Summary Statistical techniques for detection of major loci and for making inferences about major locus parameters such as genotypic frequencies, effects and gene action from field-collected data are presented. In field data, major genotypic effects are likely to be masked by a large number of environmental differences in addition to additive and nonadditive polygenic effects. A graphical technique and a procedure for discriminating among genetic hypotheses based on a mixed model accounting for all these factors are proposed. The methods are illustrated by using simulated data.Journal Paper No. J-12733 of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa. Project No. 1901     

Long-term survival of Legionella pneumophila serogroup 1 under low-nutrient conditions and associated morphological changes

Abstract Extended survival of Legionella pneumophila , using both a clinical and an environmental isolate, was studied in drinking water, creek water, and estuarine water microcosms. Legionella populations were monitored by acridine orange direct counts (AODC) and viable count on buffered charcoal yeast extract agar amended with alpha-ketoglutarate (BCYEα). Initial colony counts of the clinical isolate in drinking and creek water microcosms were 2 × 10⁸ cfu/ml and, after incubation for 1.5 years, the plate counts decreased to 3 × 10⁶ cfu/ml. The AODC counts, however, did not change significantly. The clinical isolate in estuarine water decreased in plate counts to 10² (cfu/ml) over the same period. After incubation for 1.5 years at 15°C in the microcosms, Legionella plate counts of creek and drinking water decreased by two logs. Direct microscopic examination of aliquots removed from all microcosms revealed the presence of small bacilli, large bacilli and rare filamentous cells. The environmental isolate demonstrated only one colony morphology upon culture on BCYEα. Interestingly, after four months incubation in the microcosm, upon plating the clinical isolate on BCYEα, two distinct colony types were evident. Examination by immunofluorescent staining employing a monoclonal antibody against L. pneumophila revealed both bacillus and filamentous forms. The total cellular proteins of both morphotypes were examined by sodium dodecyl sulfate polyacrylyamide gel electrophoresis (SDS-PAGE), demonstrating identical protein patterns. Those Legionella cells remaining culturable during 1.5 years of incubation grew rapidly when transferred to BCYEα. Incubation was continued and it was found that some strains of L. pneumophila serogroup 1 can remain viable for longer than 2.4 years under low-nutrient conditions.     

Characterization of a Ca-dependent maxi K channel in the apical membrane of a cultured renal epithelium (JTC-12.P3)

Summary A Ca and potential-dependent K channel of large unit conductance was detected in the apical membrane of JTC-12.P3 cells, a continuous epithelial cell line of renal origin. The open probability of the channel is dependent on membrane potential and cytoplasmic-free Ca concentration. At cell-free configuration of the membrane patch, the open probability shows a bell-shaped behavior as function of membrane potential, which decreases at larger depolarization. With increasing Ca concentration, the width of the bell-shaped curve increases and the maximum shifts into the hyperpolarizing direction. For the first time the kinetics of this channel was analyzed under cell-attached conditions. In this case the kinetics could sufficiently be described by a simple open-closed behavior. The channel has an extremely small open probability at resting potential, which increases exponentially with depolarization. The low probability induces an uncertainty about the actual number of channels in the membrane patch. The number of channels is estimated by kinetic analysis. It is discussed that this K channel is essential for the repolarization of the membrane potential during electrogenic sodium-solute cotransport across the apical membrane.     

Survival ofPseudomonas syringae pv.lachrymans with cucumber roots

Summary Survival ofPseudomonas syringae pv.lachrymans with seedling cucumber roots, root washings, rhizosphere soil, and nonrhizosphere soil was determined 7–8 days after the soil surface was watered with a cell suspension of the bacterium. Plants were in pots in the green-house and soil was not sterilized. Survival was best with roots and root washings, next best in rhizosphere soil, and poor in nonrhizosphere soil.     

Global asymptotic stability of the size distribution in probabilistic models of the cell cycle

Probabilistic models of the cell cycle maintain that cell generation time is a random variable given by some distribution function, and that the probability of cell division per unit time is a function only of cell age (and not, for instance, of cell size). Given the probability density, f(t), for time spent in the random compartment of the cell cycle, we derive a recursion relation for _n(x), the probability density for cell size at birth in a sample of cells in generation n. For the case of exponential growth of cells, the recursion relation has no steady-state solution. For the case of linear cell growth, we show that there exists a unique, globally asymptotically stable, steady-state birth size distribution, _*(x). For the special case of the transition probability model, we display _*(x) explicitly.This work was supported by the National Science Foundation under grants MCS8301104 (to J.J.T.) and MCS8300559 (to K.B.H.), and by the National Institutes of Health under grant GM27629 (to J.J.T.).     

Dependent competing risks: a stochastic process model

Analyses of human mortality data classified according to cause of death frequently are based on competing risk theory. In particular, the times to death for different causes often are assumed to be independent. In this paper, a competing risk model with a weaker assumption of conditional independence of the times to death, given an assumed stochastic covariate process, is developed and applied to cause specific mortality data from the Framingham Heart Study. The results generated under this conditional independence model are compared with analogous results under the standard marginal independence model. Under the assumption that this conditional independence model is valid, the comparison suggests that the standard model overestimates by 4% the effect on life expectancy at age 30 due to the hypothetical elimination of cancer and by 7% the effect for cardiovascular/cerebrovascular disease. By age 80 the overestimates were 11% for cancer and 16% for heart disease. These results suggest the importance of avoiding the marginal independence assumption when appropriate data are available — especially when focusing on mortality at advanced ages.