Pain catastrophising predicts alcohol hangover severity and symptoms

Alcohol hangover is a cause of considerable social and economic burden. Identification of predictors of alcohol hangover severity have the potential to contribute to reductions in costs associated with both absenteeism/presenteeism and health care. Pain catastrophising (PC) is the tendency to ruminate and describe a pain experience in more exaggerated terms. The current study examines the possibility that this cognitive coping strategy may influence experience of alcohol hangover. The aims of the current study were to (1) examine the relationship between hangover severity and PC, (2) explore and identify discreet factors within the Acute Hangover Scale (AHS) and (3) explore whether independent factors/dimensions of acute hangover are differentially predicted by PC. A retrospective survey (n = 86) was conducted in which participants completed the Acute Hangover Scale (AHS); the Pain Catastrophising Scale (PCS); a questionnaire pertaining to the amount of alcohol consumed; and a demographic information questionnaire. Regression analyses showed a significant relationship between PC and hangover severity scores and demonstrated that PC was, in fact, a stronger predictor of perceived hangover severity than estimated peak blood alcohol concentrations (eBACs). Factor analysis of the AHS scale, resulted in the identification of two distinct symptom dimensions; ‘Headache and thirst’, and ‘Gastric and cardiovascular’ symptoms. Regression analyses showed that both eBAC and PCS score were significantly associated with ‘Headache and thirst’. However, only PCS score was associated with ‘Gastric and cardiovascular’ symptoms. These novel findings implicate a role for cognitive coping strategies in self-reports of alcohol hangover severity, and may have implications for understanding behavioural response to hangover, as well as suggesting that hangover and PC may be important factors mediating the motivation to drink and/or abuse alcohol, with potential implications in addiction research. Furthermore, these findings suggest that distinct alcohol hangover symptoms may be associated with different mechanisms underlying the experience of alcohol hangover

Variability in Laboratory vs. Field Testing of Peak Power, Torque, and Time of Peak Power Production Among Elite Bicycle Motocross Cyclists

The aim of this study was to ascertain the variation in elite male BMX cyclists’ peak power, torque and time of power production during laboratory and fieldbased testing. Eight male elite BMX riders volunteered for the study and each rider completed 3 maximal sprints using both an SRM ergometer in the laboratory, and a portable SRM power meter on an Olympic standard indoor BMX track. The results revealed a significantly higher peak power (p = < 0.001, 34 ± 9 %) and reduced time of power production (p = < 0.001, 105 ± 24 %) in the field tests when compared to laboratory derived values. Torque was also reported to be lower in the laboratory tests, but not to an accepted level of significance (p = 0.182, 6 ± 8 %).These results suggest that field based testing may be a more effective and accurate measure of a BMX rider’s peak power, torque and time of power production

Collapse of a Bose gas: kinetic approach

We have analytically explored temperature dependence of critical number of particles for the collapse of a harmonically trapped attractively interacting Bose gas below the condensation point by introducing a kinetic approach within the Hartree-Fock approximation. The temperature dependence obtained by this easy approach is consisted with that obtained from the scaling theory.Comment: Brief Report, 4 pages, 1 figure, Accepted in Pramana-Journal of Physic

Accuracy of Intravenous and Enteral Preparations Involving Small Volumes for Paediatric Use: A Review

Background: Children often need to be administered very small volumes of medicines that are authorised for use in adults. Neonatal drug delivery is particularly challenging and doses are often immeasurable with the equipment currently available. Aim: To summarise research to date on the accuracy of intravenous and enteral medicine preparation requiring small volumes (<0.1mL), with a focus on paediatric use and to identify areas for further work. Method: Twenty-three publications were identified for the narrative review via: Web of Science (1950-2016), Cumulative Index to Nursing and Allied Health Literature (1976-2016), Excerpta Medica Database (1974-2016) and International Pharmaceutical Abstracts (1970-2016) searches. Nine additional papers were identified through backward citation tracking and a further 17 were included from the personal knowledge of the review team. Results: Measurement of volumes (<0.1mL), for enteral and intravenous dosing, account for 25% of medicine manipulations within paediatric hospitals. Inaccuracies are described throughout the literature with dose administration errors attributed to technique, calculation, dilution and problems associated with equipment. Whilst standardised concentrations for intravenous infusion and drug concentrations which avoid measurement of small volumes would ameliorate problems, further work is needed to establish accurate methods for handling small volumes during the administration of medicines to children and risk minimisation strategies to support staff involved are also necessary. Conclusion: This review has revealed a paucity of information on the clinical outcomes from problems in measuring small volumes for children and highlighted the need for further work to eliminate this source of inaccurate dosing and potential for medication error

Serial optical coherence microscopy for label-free volumetric histopathology

The observation of histopathology using optical microscope is an essential procedure for examination of tissue biopsies or surgically excised specimens in biological and clinical laboratories. However, slide-based microscopic pathology is not suitable for visualizing the large-scale tissue and native 3D organ structure due to its sampling limitation and shallow imaging depth. Here, we demonstrate serial optical coherence microscopy (SOCM) technique that offers label-free, high-throughput, and large-volume imaging of ex vivo mouse organs. A 3D histopathology of whole mouse brain and kidney including blood vessel structure is reconstructed by deep tissue optical imaging in serial sectioning techniques. Our results demonstrate that SOCM has unique advantages as it can visualize both native 3D structures and quantitative regional volume without introduction of any contrast agents

Paradigm of tunable clustering using binarization of consensus partition matrices (Bi-CoPaM) for gene discovery

Copyright @ 2013 Abu-Jamous et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Clustering analysis has a growing role in the study of co-expressed genes for gene discovery. Conventional binary and fuzzy clustering do not embrace the biological reality that some genes may be irrelevant for a problem and not be assigned to a cluster, while other genes may participate in several biological functions and should simultaneously belong to multiple clusters. Also, these algorithms cannot generate tight clusters that focus on their cores or wide clusters that overlap and contain all possibly relevant genes. In this paper, a new clustering paradigm is proposed. In this paradigm, all three eventualities of a gene being exclusively assigned to a single cluster, being assigned to multiple clusters, and being not assigned to any cluster are possible. These possibilities are realised through the primary novelty of the introduction of tunable binarization techniques. Results from multiple clustering experiments are aggregated to generate one fuzzy consensus partition matrix (CoPaM), which is then binarized to obtain the final binary partitions. This is referred to as Binarization of Consensus Partition Matrices (Bi-CoPaM). The method has been tested with a set of synthetic datasets and a set of five real yeast cell-cycle datasets. The results demonstrate its validity in generating relevant tight, wide, and complementary clusters that can meet requirements of different gene discovery studies.National Institute for Health Researc

Mapping species distributions: A comparison of skilled naturalist and lay citizen science recording

To assess the ability of traditional biological recording schemes and lay citizen science approaches to gather data on species distributions and changes therein, we examined bumblebee records from the UK’s national repository (National Biodiversity Network) and from BeeWatch. The two recording approaches revealed similar relative abundances of bumblebee species but different geographical distributions. For the widespread common carder (Bombus pascuorum), traditional recording scheme data were patchy, both spatially and temporally, reflecting active record centre rather than species distribution. Lay citizen science records displayed more extensive geographic coverage, reflecting human population density, thus offering better opportunities to account for recording effort. For the rapidly spreading tree bumblebee (Bombus hypnorum), both recording approaches revealed similar distributions due to a dedicated mapping project which overcame the patchy nature of naturalist records. We recommend, where possible, complementing skilled naturalist recording with lay citizen science programmes to obtain a nation-wide capability, and stress the need for timely uploading of data to the national repository

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

What have we done to animal health planning

Animal health planning has been widely promoted to farmers in many countries as a way to improve the health and welfare of their animals and contribute to other societal goals such as reducing greenhouse gas emissions. Although these benefits have been demonstrated and promoted widely there are still farmers who have not engaged in the active process of health planning and those that do not think it is a worthwhile process. Through the novel approach of examining animal health planning adoption using a stage behavioural model, the individual stages of adoption (from awareness to maintenance) were analysed using literature and primary data collected in an online survey. Results of the study show that there needs to be clarity on what animal health planning is and that awareness of it in the UK may not be as high as might be expected. These prerequisites need to be tackled before further barriers including improved data on the costs and benefits of health planning and quality of the base plan can be addressed. This paper demonstrates that behavioural stage models provide a valuable framework to study the whole process of behavioural adoption and can help identify barriers at each stage of the process, allowing advisors and extension officers to design effective interventions that will encourage farmers to actively health plan