Permanence of single-species stage-structured models

In this paper, we consider population survival by using single-species stage-structured models. As a criterion of population survival, we employ the mathematical notation of permanence. Permanence of stage-structured models has already been studied by Cushing (1998). We generalize his result of permanence, and obtain a condition which guarantees that population survives. The condition is applicable to a wide class of stage-structured models. In particular, we apply our results to the Neubert-Caswell model, which is a typical stage-structured model, and obtain a condition for population survival of the model.The research is partially supported by the Ministry of Education, Science and Culture, Japan, under Grant in Aid for Scientific Research (A) 13304006.     

The biological clock: the bodyguard of temporal homeostasis

In order for any organism to function properly, it is crucial that it be table to control the timing of its biological functions. An internal biological clock, located, in mammals, in the suprachiasmatic nucleus of the hypothalamus (SCN), therefore carefully guards this temporal homeostasis by delivering its message of time throughout the body. In view of the large variety of body functions (behavioral, physiological, and endocrine) as well as the large variety in their preferred time of main activity along the light:dark cycle, it seems logical to envision different means of time distribution by the SCN. In the present review, we propose that even though it presents a unimodal circadian rhythm of general electrical and metabolic activity, the SCN seems to use several sorts of output connections that are active at different times along the light: dark cycle to control the rhythmic expression of different body functions. Although the SCN is suggested to use diffusion of synchronizing factors in the rhythmic control of behavioral functions, it also needs neuronal connections for the control of endocrine functions. The distribution of the time-of-day message to neuroendocrine systems is either directly onto endocrine neurons or via intermediate neurons located in specific SCN targets. In addition, the SCN uses its connections with the autonomic nervous system for spreading its time-of-day message, either by setting the sensitivity of endocrine glands (i.e., thyroid, adrenal, ovary) or by directly controlling an endocrine output (i.e., melatonin synthesis). Moreover, the SCN seems to use different neurotransmitters released at different times along the light: dark cycle for each of the different connection types presented. Clearly, the temporal homeostasis of endocrine functions results from a diverse set of biological clock outputs.     

Molecular modeling of dipeptide and its analogous systems with water

Intermolecular hydrogen-bond interactions in the monohydrated complexes of formamide, N-methylacetamide and glycylglycine have been studied using ab initio and DFT methods. The geometries were optimized using second-order Møller–Plesset perturbation theory and the B3LYP DFT functional with the 6-311++G** basis set. It is observed that hydrogen-bond interactions at the carbonyl group of the peptide moiety are stronger than those at the amino group of the formamide and N-methylacetamide molecules. Because of the presence of cyclic hydrogen-bonding interactions in glycylglycine, the interaction at the amino group is higher than at the carbonyl. The ¹³C and ¹⁵N NMR shielding values were calculated for the non-hydrated and monohydrated complexes. Condensed Fukui functions have also been calculated for non-hydrated formamide, N-methylacetamide and glycylglycine molecules at the B3LYP/6-311++G** level of theory, and the results are discussed.Figure Structure of hydrated glycylglycine dipeptide     

Use of Ψ<Superscript>α</Superscript>-ETOs in the unified treatment of electronic attraction,electric field and electric field gradient multicenter integrals of screened Coulomb potentials over Slater orbitals

In this study, using complete orthonormal sets of -ETOs (where =1, 0, –1, –2, ...)introduced by the author, a large number of series expansion formulae for the multicenter electronic attraction (EA), electric field (EF) and electric field gradient (EFG) integrals of the Yukawa-like screened Coulomb potentials (SCPs) is presented through the new central and noncentral potentials and the overlap integrals with the same screening constants. The final results obtained are valid for arbitrary locations of STOs and their parameters.An erratum to this article can be found at     

Matching unrelated stimuli with same discriminative functions: training order effects

Previous research has shown that after training simple discriminations (A1+/A2−, B1+/B2−), bringing these tasks under conditional control (J1–A1, J2–A2) leads to transfer of discriminative control (J1+/J2−) and to generalized matching on the basis of same discriminative functions (e.g. J1–B1, J2–B2). The same occurs when conditional discriminations are trained (D1–E1, D2–E2; F1–G1, F2–G2). When the subjects are then trained to demonstrate correct relations (D1–E1, D2–E2) when given X1 and to demonstrate incorrect relations when given X2 (XD–E), transfer of discriminative control (X1+/X2−) and generalized matching on the basis of same discriminative functions emerges (e.g. X1F1–G1, X2F1–G2). The present study investigated if these performances are dependent on the training and/or testing order. In Experiment 1, the lower-order contingency tasks were trained before the higher-order contingency tasks (A1+/A2−, B1+/B2− before J–A, and D–E, F–G before XD–E). Half the subjects received the J–B test before the more complex XF–G test (Condition A), while for the other subjects, this testing order was reversed (Condition B). Finally, all subjects received additional tests in which they were given the opportunity to demonstrate the discriminative properties of the J and X stimuli (J1+/J2−, X1+/X2−), and to match the A, J, and X stimuli with newly introduced stimuli of same discriminative properties (e.g. J1-POLITE, J2-RUDE). Experiment 2 was the same except that the training order was reversed (J–A before A1+/A2−, B1+/B2−, and XD–E before D–E, F–G). The results were affected by the training order but not by the testing order. Transfer of discriminative functions and generalized matching on the basis of same functions only occurred reliably when the lower-order contingency tasks were trained first. A stimulus-control account of the data is offered.     

Improved protein-ligand docking using GOLD

The Chemscore function was implemented as a scoring function for the protein-ligand docking program GOLD, and its performance compared to the original Goldscore function and two consensus docking protocols, "Goldscore-CS" and "Chemscore-GS," in terms of docking accuracy, prediction of binding affinities, and speed. In the "Goldscore-CS" protocol, dockings produced with the Goldscore function are scored and ranked with the Chemscore function; in the "Chemscore-GS" protocol, dockings produced with the Chemscore function are scored and ranked with the Goldscore function. Comparisons were made for a "clean" set of 224 protein-ligand complexes, and for two subsets of this set, one for which the ligands are "drug-like," the other for which they are "fragment-like." For "drug-like" and "fragment-like" ligands, the docking accuracies obtained with Chemscore and Goldscore functions are similar. For larger ligands, Goldscore gives superior results. Docking with the Chemscore function is up to three times faster than docking with the Goldscore function. Both combined docking protocols give significant improvements in docking accuracy over the use of the Goldscore or Chemscore function alone. "Goldscore-CS" gives success rates of up to 81% (top-ranked GOLD solution within 2.0 A of the experimental binding mode) for the "clean list," but at the cost of long search times. For most virtual screening applications, "Chemscore-GS" seems optimal; search settings that give docking speeds of around 0.25-1.3 min/compound have success rates of about 78% for "drug-like" compounds and 85% for "fragment-like" compounds. In terms of producing binding energy estimates, the Goldscore function appears to perform better than the Chemscore function and the two consensus protocols, particularly for faster search settings. Even at docking speeds of around 1-2 min/compound, the Goldscore function predicts binding energies with a standard deviation of approximately 10.5 kJ/mol.     

The contribution of ancestry,chance, and past and ongoing selection to adaptive evolution

The relative contributions of ancestry, chance, and past and ongoing election to variation in one adaptive (larval feeding rate) and one seemingly nonadaptive (pupation height) trait were determined in populations ofDrosophila melanogaster adapting to either low or high larval densities in the laboratory. Larval feeding rates increased rapidly in response to high density, and the effects of ancestry, past selection and chance were ameliorated by ongoing selection within 15–20 generations. Similarly, in populations previously kept at high larval density, and then switched to low larval density, the decline of larval feeding rate to ancestral levels was rapid (15-20 generations) and complete, providing support for a previously stated hypothesis regarding the costs of faster feeding inDrosophila larvae. Variation among individuals was the major contributor to variation in pupation height, a trait that would superficially appear to be nonadaptive in the environmental context of the populations used in this study because it did not diverge between sets of populations kept at low versus high larval density for many generations. However, the degree of divergence among populations (FST) for pupation height was significantly less than expected for a selectively neutral trait, and we integrate results from previous studies to suggest that the variation for pupation height among populations is constrained by stabilizing selection, with a flat, plateau-like fitness function that, consequently, allows for substantial phenotypic variation within populations. Our results support the view that the genetic imprints of history (ancestry and past selection) in outbreeding sexual populations are typically likely to be transient in the face of ongoing selection and recombination. The results also illustrate the heuristic point that different forms of selection-for example directional versus stabilizing selection—acting on a trait in different populations may often not be due to differently shaped fitness functions, but rather due to differences in how the fitness function maps onto the actual distribution of phenotypes in a given population. We discuss these results in the light of previous work on reverse evolution, and the role of ancestry, chance, and past and ongoing selection in adaptive evolution.     

Predictive Validity of Discriminant Analysis for Genetic Data

We examined the predictive validity of the results using discriminant analysis to distinguish statistically among two or more populations with a large sample of random amplified polymorphic DNA (RAPD) loci, but a small sample of genotypes from each population. We compared and contrasted results from randomized data with results from real data of three studies by 100 randomized shuffling of genotypes into various populations. We generally obtained substantial differences between results from randomized data compared to those from the real data in several characteristics of discriminant analysis. We showed that a high level of correctly classified percentage is also obtainable in the analysis of randomized data, mainly with a low number of populations. However, the correctly classified percentage obtained from the real data was generally significantly higher than the percentage obtained from the randomized data. We suggested that the high level of real differences in allele frequencies of the RAPD polymorphic loci clearly distinguished the various populations and that the populations differ significantly in their RAPD contents in accordance with ecological heterogeneity. We obtained either no or a low level of difference between the correct classification rate obtained by the leaving-one-out procedure and that obtained from the original data, attributed to a low number of loci selected by the stepwise method. The results strengthen and support our conclusion and lead us to focus on the discriminant analysis by selecting only low numbers of discriminating variables.     

Primary cilium—is it an osteocyte's strain‐sensing flowmeter?

With few exceptions, the non-cycling cells in a vast range of animals including humans have a non-motile primary cilium that extends from the mother centriole of the pair of centrioles in their centrosomes located between their Golgi apparatuses and nuclei. It has very recently been shown that the primary cilium of a dog or a mouse embryonic kidney cell is a fluid flowmeter studded with heterodimeric complexes of mechanoreceptors linked to Ca(2+)-permeable cation channels that when the cilium is bent can send Ca(2+) signals into the cell and beyond to neighboring cells through gap junctions. More than 30 years ago, osteocytes were reported also to have primary cilia, but this was promptly ignored or forgotten. Osteocytes are the bones' strain sensors, which measure skeletal activity from the effects of currents of extracellular fluid caused by their bones being bent and squeezed during various activities such as walking and running. Since bending a kidney cell's primary cilium can send a Ca(2+) wave surging through itself and its neighbors, the bending of an osteocyte's primary cilium by sloshing extracellular fluid is likely to do the same thing and thus be involved in measuring and responding to bone strain.     

Survival analysis in clinical trials: past developments and future directions

The field of survival analysis emerged in the 20th century and experienced tremendous growth during the latter half of the century. The developments in this field that have had the most profound impact on clinical trials are the Kaplan-Meier (1958, Journal of the American Statistical Association 53, 457-481) method for estimating the survival function, the log-rank statistic (Mantel, 1966, Cancer Chemotherapy Report 50, 163-170) for comparing two survival distributions, and the Cox (1972, Journal of the Royal Statistical Society, Series B 34, 187-220) proportional hazards model for quantifying the effects of covariates on the survival time. The counting-process martingale theory pioneered by Aalen (1975, Statistical inference for a family of counting processes, Ph.D. dissertation, University of California, Berkeley) provides a unified framework for studying the small- and large-sample properties of survival analysis statistics. Significant progress has been achieved and further developments are expected in many other areas, including the accelerated failure time model, multivariate failure time data, interval-censored data, dependent censoring, dynamic treatment regimes and causal inference, joint modeling of failure time and longitudinal data, and Baysian methods.