Cosmological parameters from the clustering of AGN

We attempt to put constraints on different cosmological and biasing models by combining the recent clustering results of X-ray sources in the local ($z\le 0.1$) and distant universe ($z\sim 1$).Comment: 9 pages, 3 figures, to be published in the proceedings of the ''2nd Hellenic Cosmology Workshop'', Athens 2001, eds, Manolis Plionis & Spiros Kotsaki

Redistribution of Actin during Assembly and Reassembly of the Contractile Ring in Grasshopper Spermatocytes

Cytokinesis in animal cells requires the assembly of an actomyosin contractile ring to cleave the cell. The ring is highly dynamic; it assembles and disassembles during each cell cleavage, resulting in the recurrent redistribution of actin. To investigate this process in grasshopper spermatocytes, we mechanically manipulated the spindle to induce actin redistribution into ectopic contractile rings, around reassembled lateral spindles. To enhance visualization of actin, we folded the spindle at its equator to convert the remnants of the partially assembled ring into a concentrated source of actin. Filaments from the disintegrating ring aligned along reorganizing spindle microtubules, suggesting that their incorporation into the new ring was mediated by microtubules. We tracked incorporation by speckling actin filaments with Qdots and/or labeling them with Alexa 488-phalloidin. The pattern of movement implied that actin was transported along spindle microtubules, before entering the ring. By double-labeling dividing cells, we imaged actin filaments moving along microtubules near the contractile ring. Together, our findings indicate that in one mechanism of actin redistribution, actin filaments are transported along spindle microtubule tracks in a plus-end–directed fashion. After reaching the spindle midzone, the filaments could be transported laterally to the ring. Notably, actin filaments undergo a dramatic trajectory change as they enter the ring, implying the existence of a pulling force. Two other mechanisms of actin redistribution, cortical flow and de novo assembly, are also present in grasshopper, suggesting that actin converges at the nascent contractile ring from diffuse sources within the cytoplasm and cortex, mediated by spindle microtubules

Mapping quantitative trait loci (QTL) in sheep. I. A new male framework linkage map and QTL for growth rate and body weight

A male sheep linkage map comprising 191 microsatellites was generated from a single family of 510 Awassi-Merino backcross progeny. Except for ovine chromosomes 1, 2, 10 and 17, all other chromosomes yielded a LOD score difference greater than 3.0 between the best and second-best map order. The map is on average 11% longer than the Sheep Linkage Map v4.7 male-specific map. This map was employed in quantitative trait loci (QTL) analyses on body-weight and growth-rate traits between birth and 98 weeks of age. A custom maximum likelihood program was developed to map QTL in half-sib families for non-inbred strains (QTL-MLE) and is freely available on request. The new analysis package offers the advantage of enabling QTL × fixed effect interactions to be included in the model. Fifty-four putative QTL were identified on nine chromosomes. Significant QTL with sex-specific effects (i.e. QTL × sex interaction) in the range of 0.4 to 0.7 SD were found on ovine chromosomes 1, 3, 6, 11, 21, 23, 24 and 26

Expert consensus document: A 'diamond' approach to personalized treatment of angina.

In clinical guidelines, drugs for symptomatic angina are classified as being first choice (β-blockers, calcium-channel blockers, short-acting nitrates) or second choice (ivabradine, nicorandil, ranolazine, trimetazidine), with the recommendation to reserve second-choice medications for patients who have contraindications to first-choice agents, do not tolerate them, or remain symptomatic. No direct comparisons between first-choice and second-choice treatments have demonstrated the superiority of one group of drugs over the other. Meta-analyses show that all antianginal drugs have similar efficacy in reducing symptoms, but provide no evidence for improvement in survival. The newer, second-choice drugs have more evidence-based clinical data that are more contemporary than is available for traditional first-choice drugs. Considering some drugs, but not others, to be first choice is, therefore, difficult. Moreover, double or triple therapy is often needed to control angina. Patients with angina can have several comorbidities, and symptoms can result from various underlying pathophysiologies. Some agents, in addition to having antianginal effects, have properties that could be useful depending on the comorbidities present and the mechanisms of angina, but the guidelines do not provide recommendations on the optimal combinations of drugs. In this Consensus Statement, we propose an individualized approach to angina treatment, which takes into consideration the patient, their comorbidities, and the underlying mechanism of disease

What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology

Stochastic resonance is said to be observed when increases in levels of unpredictable fluctuations—e.g., random noise—cause an increase in a metric of the quality of signal transmission or detection performance, rather than a decrease. This counterintuitive effect relies on system nonlinearities and on some parameter ranges being “suboptimal”. Stochastic resonance has been observed, quantified, and described in a plethora of physical and biological systems, including neurons. Being a topic of widespread multidisciplinary interest, the definition of stochastic resonance has evolved significantly over the last decade or so, leading to a number of debates, misunderstandings, and controversies. Perhaps the most important debate is whether the brain has evolved to utilize random noise in vivo, as part of the “neural code”. Surprisingly, this debate has been for the most part ignored by neuroscientists, despite much indirect evidence of a positive role for noise in the brain. We explore some of the reasons for this and argue why it would be more surprising if the brain did not exploit randomness provided by noise—via stochastic resonance or otherwise—than if it did. We also challenge neuroscientists and biologists, both computational and experimental, to embrace a very broad definition of stochastic resonance in terms of signal-processing “noise benefits”, and to devise experiments aimed at verifying that random variability can play a functional role in the brain, nervous system, or other areas of biology

Spatial correlations in a redshift survey of apm galaxy clusters

We have constructed a new catalog of rich clusters of galaxies by applying an objective selection algorithm to the APM Galaxy Survey. We have measured redshifts for 173 clusters from this catalog leading to a redshift survey of over 200 rich APM clusters with z ≲ 0.1 when we include published redshifts. The mean space density for this subsample is n̄ = 2.4 × 10-5 h3 Mpc 3 ,2i.e., about four times the mean space density of R ≥ 1 Abell clusters. The spatial correlation function for our redshift sample can be approximated by ξcc(s) = (r0/s)2 with r0 = 12.9 ± 1.4 h-1 Mpc. The correlation length for the 93 richest clusters in our sample is r0 = 14 ± 4 h-1 Mpc. These results are consistent with the amplitude for ξcc expected in the standard cold dark matter model on scales ≲10 h-1 Mpc and are lower than the amplitude (r0 ∼ 25 h-1 Mpc) found by Bahcall and Soneira from the Abell catalog. However, our results indicate more clustering than expected in the standard cold dark matter model on scales ≲ 10 h-1 Mpc. We argue that the APM cluster catalog is more homogeneous than the Abell sample, and we demonstrate that our redshift-space correlation function is free from spurious large-scale anisotropies and is compatible with small (≳500 km s-1) cluster peculiar velocities

The Apm Galaxy Survey IV: Redshifts of Rich Clusters of Galaxies

We present redshifts for a sample of 229 clusters selected from the APM Galaxy Survey, 189 of which are new redshift determinations. Non-cluster galaxy redshifts have been rejected from this sample using a likelihood ratio test based on the projected and apparent magnitude distributions of the cluster fields. We test this technique using cluster fields in which redshifts have been measured for more than 10 galaxies. Our redshift sample is nearly complete and has been used in previous papers to study the three dimensional distribution of rich clusters of galaxies. 157 of the clusters in our sample are listed in the Abell catalogue or supplement, and the remainder are new cluster identifications