The metabolic clearance of progesterone in the pregnant rat: absence of a physiological role for the lung

The metabolic clearance rate (MCR) of progesterone is among the highest for all steroid hormones studied, yet it is difficult to apportion this high MCR to specific organ contributions. The isolated lung has been shown to metabolize progesterone, and since this tissue receives the entire cardiac output, potentially it could make a major contribution to the overall MCR. This possibility was examined in the present study by measuring lung extraction of [3H]progesterone under steady-state conditions in the intact pregnant rat. Anesthetized rats (n = 6) were infused with [3H]progesterone via a femoral vein for 100 min on Day 16 of pregnancy. After the onset of steady state (40 min), four blood samples were obtained at 20-min intervals from the right ventricle and from the aorta, and the concentrations of [3H]progesterone and its metabolites were determined. Throughout the sampling period, mean arterial pressure and heart rate remained stable (two-way analysis of variance), as did the production rate (3.76 +/- 0.35 mg/day; mean +/- SEM) and the MCR (34.8 +/- 3.5 ml/min) of progesterone. Despite this high rate of clearance, there was no difference between the concentration of [3H]progesterone in arterial and right ventricular blood, indicating no net extraction of progesterone during passage through the lung. Furthermore, there was no change in the concentration of either lipid-soluble or aqueous-soluble [3H]progesterone metabolites during trans-lung passage. These observations demonstrate that the lung does not contribute to the MCR of progesterone when measured under physiological and steady-state conditions. Therefore, the relationship, MCR (ml/min) = whole-body extraction (%) x cardiac output (ml/min), is upheld for progesterone in the rat.     

Combined monte carlo and molecular dynamics simulation of fully hydrated dioleyl and palmitoyl-oleyl phosphatidylcholine lipid bilayers

We have applied a new equilibration procedure for the atomic level simulation of a hydrated lipid bilayer to hydrated bilayers of dioleyl-phosphatidylcholine (DOPC) and palmitoyl-oleyl phosphatidylcholine (POPC). The procedure consists of alternating molecular dynamics trajectory calculations in a constant surface tension and temperature ensemble with configurational bias Monte Carlo moves to different regions of the configuration space of the bilayer in a constant volume and temperature ensemble. The procedure is applied to bilayers of 128 molecules of POPC with 4628 water molecules, and 128 molecules of DOPC with 4825 water molecules. Progress toward equilibration is almost three times as fast in central processing unit (CPU) time compared with a purely molecular dynamics (MD) simulation. Equilibration is complete, as judged by the lack of energy drift in 200-ps runs of continuous MD. After the equilibrium state was reached, as determined by agreement between the simulation volume per lipid molecule with experiment, continuous MD was run in an ensemble in which the lateral area was restrained to fluctuate about a mean value and a pressure of 1 atm applied normal to the bilayer surface. Three separate continuous MD runs, 200 ps in duration each, separated by 10,000 CBMC steps, were carried out for each system. Properties of the systems were calculated and averaged over the three separate runs. Results of the simulations are presented and compared with experimental data and with other recent simulations of POPC and DOPC. Analysis of the hydration environment in the headgroups supports a mechanism by which unsaturation contributes to reduced transition temperatures. In this view, the relatively horizontal orientation of the unsaturated bond increases the area per lipid, resulting in increased water penetration between the headgroups. As a result the headgroup-headgroup interactions are attenuated and shielded, and this contributes to the lowered transition temperature.     

Cytosine deaminase as a substrate-dependent negative selectable marker in Brassica napus

The enzyme cytosine deaminase, encoded by the codA gene, catalyzes the deamination of the non- toxic compound 5-fluorocytosine (5-FC) to the highly toxic compound 5-fluorouracil (5-FU). Cytosine deaminase activity is not found in higher plants and Brassica napus seedlings are unaffected by the presence of 5-FC in the growth medium. In codA-transformed B. napus seedlings, expression of cytosine deaminase results in a reduction of root and hypocotyl lengths, and a severe suppression of true leaf development. This phenotype is dependent on the presence of the 5-FC substrate and no effects are seen in plants grown in the absence of the substrate or in sibling plants lacking the transgene. The codA transformants have been assessed over three generations of growth and in each generation the transgene is stably inherited and confers the same 5-FC-sensitive phenotype. Transfer of 5-FC-sensitive seedlings to soil results in the restoration of normal growth in up to 100% of the seedlings. These results indicate that codA is a versatile dominant marker gene that can be used effectively in B. napus for substrate-dependent negative selection. Received: 24 June 1999 / Accepted: 22 July 1999     

Thermodynamic benchmark study using Biacore technology

A total of 22 individuals participated in this benchmark study to characterize the thermodynamics of small-molecule inhibitor-enzyme interactions using Biacore instruments. Participants were provided with reagents (the enzyme carbonic anhydrase II, which was immobilized onto the sensor surface, and four sulfonamide-based inhibitors) and were instructed to collect response data from 6 to 36 degrees C. van't Hoff enthalpies and entropies were calculated from the temperature dependence of the binding constants. The equilibrium dissociation and thermodynamic constants determined from the Biacore analysis matched the values determined using isothermal titration calorimetry. These results demonstrate that immobilization of the enzyme onto the sensor surface did not alter the thermodynamics of these interactions. This benchmark study also provides insights into the opportunities and challenges in carrying out thermodynamic studies using optical biosensors.     

Rapid Evaluation of Least-Squares and Minimum-Evolution Criteria on Phylogenetic Trees

We present fast new algorithms for evaluating trees with respectto least squares and minimum evolution (ME), the most commonlyused criteria for inferring phylogenetic trees from distancedata. The new algorithms include an optimal O(N2) time algorithmfor calculating the edge (branch or internode) lengths on atree according to ordinary or unweighted least squares (OLS);an O(N3) time algorithm for edge lengths under weighted leastsquares (WLS) including the Fitch-Margoliash method; and anoptimal O(N4) time algorithm for generalized least-squares (GLS)edge lengths (where N is the number of taxa in the tree). TheME criterion is based on the sum of edge lengths. Consequently,the edge lengths algorithms presented here lead directly toO(N2), O(N3), and O(N4) time algorithms for ME under OLS, WLS,and GLS, respectively. All of these algorithms are as fast asor faster than any of those previously published, and the algorithmsfor OLS and GLS are the fastest possible (with respect to orderof computational complexity). A major advantage of our new methodsis that they are as well adapted to multifurcating trees asthey are to binary trees. An optimal algorithm for determiningpath lengths from a tree with given edge lengths is also developed.This leads to an optimal O(N2) algorithm for OLS sums of squaresevaluation and corresponding O(N3) and O(N4) time algorithmsfor WLS and GLS sums of squares, respectively. The GLS algorithmis time-optimal if the covariance matrix is already inverted.The speed of each algorithm is assessed analytically—thespeed increases we calculate are confirmed by the dramatic speedincreases resulting from their implementation in PAUP* 4.0.The new algorithms enable far more extensive tree searches andstatistical evaluations (e.g., bootstrap, parametric bootstrap,or jackknife) in the same amount of time. Hopefully, the fastalgorithms for WLS and GLS will encourage the use of these criteriafor evaluating trees and their edge lengths (e.g., for approximatedivergence time estimates), since they should be more statisticallyefficient than OLS.     

What can we teach Drosophila? What can they teach us?

A number of single gene mutations dramatically reduce the ability of fruit flies to learn or to remember. Cloning of the affected genes implicated the adenylyl cyclase second-messenger system as key in learning and memory. The expression patterns of these genes, in combination with other data, indicates that brain structures called mushroom bodies are crucial for olfactory learning. However, the mushroom bodies are not dedicated solely to olfactory processing; they also mediate higher cognitive functions in the fly, such as visual context generalization. Molecular genetic manipulations, coupled with behavioral studies of the fly, will identify rudimentary neural circuits that underly multisensory learning and perhaps also the circuits that mediate more-complex brain functions, such as attention.     

Drosophila memory: will Orb(2) predict the future?

Genetically tractable organisms with relatively simple nervous systems offer a realistic platform to understand how and where memories are formed and stored in defined neural circuits. Recent work in Drosophila provides promise that this analysis may soon reach the resolution of identifiable synapses.