Configurational Entropy and Diffusivity of Supercooled Water

We calculate the configurational entropy S_conf for the SPC/E model of water for state points covering a large region of the (T,rho) plane. We find that (i) the (T,rho) dependence of S_conf correlates with the diffusion constant and (ii) that the line of maxima in S_conf tracks the line of density maxima. Our simulation data indicate that the dynamics are strongly influenced by S_conf even above the mode-coupling temperature T_MCT(rho).Comment: Significant update of reference

Eye–hand coupling is not the cause of manual return movements when searching

When searching for a target with eye movements, saccades are planned and initiated while the visual information is still being processed, so that subjects often make saccades away from the target and then have to make an additional return saccade. Presumably, the cost of the additional saccades is outweighed by the advantage of short fixations. We previously showed that when the cost of passing the target was increased, by having subjects manually move a window through which they could see the visual scene, subjects still passed the target and made return movements (with their hand). When moving a window in this manner, the eyes and hand follow the same path. To find out whether the hand still passes the target and then returns when eye and hand movements are uncoupled, we here compared moving a window across a scene with moving a scene behind a stationary window. We ensured that the required movement of the hand was identical in both conditions. Subjects found the target faster when moving the window across the scene than when moving the scene behind the window, but at the expense of making larger return movements. The relationship between the return movements and movement speed when comparing the two conditions was the same as the relationship between these two when comparing different window sizes. We conclude that the hand passing the target and then returning is not directly related to the eyes doing so, but rather that moving on before the information has been fully processed is a general principle of visuomotor control

Nanoscale Dynamics of Phase Flipping in Water near its Hypothesized Liquid-Liquid Critical Point

Achieving a coherent understanding of the many thermodynamic and dynamic anomalies of water is among the most important unsolved puzzles in physics, chemistry, and biology. One hypothesized explanation imagines the existence of a line of first order phase transitions separating two liquid phases and terminating at a novel "liquid-liquid" critical point in a region of low temperature ($T \approx 250 \rm{K}$) and high pressure ($P \approx 200 \rm{MPa}$). Here we analyze a common model of water, the ST2 model, and find that the entire system flips between liquid states of high and low density. Further, we find that in the critical region crystallites melt on a time scale of nanoseconds. We perform a finite-size scaling analysis that accurately locates both the liquid-liquid coexistence line and its associated liquid-liquid critical point.Comment: 22 pages, 5 figure

Pentachlorophenol Induction of the Pseudomonas aeruginosa mexAB-oprM Efflux Operon: Involvement of Repressors NalC and MexR and the Antirepressor ArmR

Pentachlorophenol (PCP) induced expression of the NalC repressor-regulated PA3720-armR operon and the MexR repressor-controlled mexAB-oprM multidrug efflux operon of Pseudomonas aeruginosa. PCP's induction of PA3720-armR resulted from its direct modulation of NalC, the repressor's binding to PA3720-armR promoter-containing DNA as seen in electromobility shift assays (EMSAs) being obviated in the presence of this agent. The NalC binding site was localized to an inverted repeat (IR) sequence upstream of PA3720-armR and overlapping a promoter region whose transcription start site was mapped. While modulation of MexR by the ArmR anti-repressor explains the upregulation of mexAB-oprM in nalC mutants hyperexpressing PA3720-armR, the induction of mexAB-oprM expression by PCP is not wholly explainable by PCP induction of PA3720-armR and subsequent ArmR modulation of MexR, inasmuch as armR deletion mutants still showed PCP-inducible mexAB-oprM expression. PCP failed, however, to induce mexAB-oprM in a mexR deletion strain, indicating that MexR was required for this, although PCP did not modulate MexR binding to mexAB-oprM promoter-containing DNA in vitro. One possibility is that MexR responds to PCP-generated in vivo effector molecules in controlling mexAB-oprM expression in response to PCP. PCP is an unlikely effector and substrate for NalC and MexAB-OprM - its impact on NalC binding to the PA3720-armR promoter DNA occurred only at high µM levels - suggesting that it mimics an intended phenolic effector/substrate(s). In this regard, plants are an abundant source of phenolic antimicrobial compounds and, so, MexAB-OprM may function to protect P. aeruginosa from plant antimicrobials that it encounters in nature

Why Can't Rodents Vomit? A Comparative Behavioral, Anatomical, and Physiological Study

The vomiting (emetic) reflex is documented in numerous mammalian species, including primates and carnivores, yet laboratory rats and mice appear to lack this response. It is unclear whether these rodents do not vomit because of anatomical constraints (e.g., a relatively long abdominal esophagus) or lack of key neural circuits. Moreover, it is unknown whether laboratory rodents are representative of Rodentia with regards to this reflex. Here we conducted behavioral testing of members of all three major groups of Rodentia; mouse-related (rat, mouse, vole, beaver), Ctenohystrica (guinea pig, nutria), and squirrel-related (mountain beaver) species. Prototypical emetic agents, apomorphine (sc), veratrine (sc), and copper sulfate (ig), failed to produce either retching or vomiting in these species (although other behavioral effects, e.g., locomotion, were noted). These rodents also had anatomical constraints, which could limit the efficiency of vomiting should it be attempted, including reduced muscularity of the diaphragm and stomach geometry that is not well structured for moving contents towards the esophagus compared to species that can vomit (cat, ferret, and musk shrew). Lastly, an in situ brainstem preparation was used to make sensitive measures of mouth, esophagus, and shoulder muscular movements, and phrenic nerve activity-key features of emetic episodes. Laboratory mice and rats failed to display any of the common coordinated actions of these indices after typical emetic stimulation (resiniferatoxin and vagal afferent stimulation) compared to musk shrews. Overall the results suggest that the inability to vomit is a general property of Rodentia and that an absent brainstem neurological component is the most likely cause. The implications of these findings for the utility of rodents as models in the area of emesis research are discussed. © 2013 Horn et al

Explorative data analysis of MCL reveals gene expression networks implicated in survival and prognosis supported by explorative CGH analysis

<p>Abstract</p> <p>Background</p> <p>Mantle cell lymphoma (MCL) is an incurable B cell lymphoma and accounts for 6% of all non-Hodgkin's lymphomas. On the genetic level, MCL is characterized by the hallmark translocation t(11;14) that is present in most cases with few exceptions. Both gene expression and comparative genomic hybridization (CGH) data vary considerably between patients with implications for their prognosis.</p> <p>Methods</p> <p>We compare patients over and below the median of survival. Exploratory principal component analysis of gene expression data showed that the second principal component correlates well with patient survival. Explorative analysis of CGH data shows the same correlation.</p> <p>Results</p> <p>On chromosome 7 and 9 specific genes and bands are delineated which improve prognosis prediction independent of the previously described proliferation signature. We identify a compact survival predictor of seven genes for MCL patients. After extensive re-annotation using GEPAT, we established protein networks correlating with prognosis. Well known genes (CDC2, CCND1) and further proliferation markers (WEE1, CDC25, aurora kinases, BUB1, PCNA, E2F1) form a tight interaction network, but also non-proliferative genes (SOCS1, TUBA1B CEBPB) are shown to be associated with prognosis. Furthermore we show that aggressive MCL implicates a gene network shift to higher expressed genes in late cell cycle states and refine the set of non-proliferative genes implicated with bad prognosis in MCL.</p> <p>Conclusion</p> <p>The results from explorative data analysis of gene expression and CGH data are complementary to each other. Including further tests such as Wilcoxon rank test we point both to proliferative and non-proliferative gene networks implicated in inferior prognosis of MCL and identify suitable markers both in gene expression and CGH data.</p

Estimating Marginal Healthcare Costs Using Genetic Variants as Instrumental Variables: Mendelian Randomization in Economic Evaluation

Accurate measurement of the marginal healthcare costs associated with different diseases and health conditions is important, especially for increasingly prevalent conditions such as obesity. However, existing observational study designs cannot identify the causal impact of disease on healthcare costs. This paper explores the possibilities for causal inference offered by Mendelian Randomization, a form of instrumental variable analysis that uses genetic variation as a proxy for modifiable risk exposures, to estimate the effect of health conditions on cost. Well-conducted genome-wide association studies provide robust evidence of the associations of genetic variants with health conditions or disease risk factors. The subsequent causal effects of these health conditions on cost can be estimated by using genetic variants as instruments for the health conditions. This is because the approximately random allocation of genotypes at conception means that many genetic variants are orthogonal to observable and unobservable confounders. Datasets with linked genotypic and resource use information obtained from electronic medical records or from routinely collected administrative data are now becoming available, and will facilitate this form of analysis. We describe some of the methodological issues that arise in this type of analysis, which we illustrate by considering how Mendelian Randomization could be used to estimate the causal impact of obesity, a complex trait, on healthcare costs. We describe some of the data sources that could be used for this type of analysis. We conclude by considering the challenges and opportunities offered by Mendelian Randomization for economic evaluation

Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

BACKGROUND: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. METHODS: We analyzed similar to 250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.Peer reviewe

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations withP <5 x 10(-8)in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P <5 x 10(-8)) in the discovery samples. Ten novel SNVs, including rs12616219 nearTMEM182, were followed-up and five of them (rs462779 inREV3L, rs12780116 inCNNM2, rs1190736 inGPR101, rs11539157 inPJA1, and rs12616219 nearTMEM182) replicated at a Bonferroni significance threshold (P <4.5 x 10(-3)) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, inCCDC141and two low-frequency SNVs inCEP350andHDGFRP2. Functional follow-up implied that decreased expression ofREV3Lmay lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.Peer reviewe