In Synch but Not in Step: Circadian Clock Circuits Regulating Plasticity in Daily Rhythms

The suprachiasmatic nucleus (SCN) is a network of neural oscillators that program daily rhythms in mammalian behavior and physiology. Over the last decade much has been learned about how SCN clock neurons coordinate together in time and space to form a cohesive population. Despite this insight, much remains unknown about how SCN neurons communicate with one another to produce emergent properties of the network. Here we review the current understanding of communication among SCN clock cells and highlight a collection of formal assays where changes in SCN interactions provide for plasticity in the waveform of circadian rhythms in behavior. Future studies that pair analytical behavioral assays with modern neuroscience techniques have the potential to provide deeper insight into SCN circuit mechanisms

A New Method for Assessing the Resiliency of Large, Complex Networks

Designing resilient and reliable networks is a principle concern of planners and private firms. Traffic congestion whether recurring or as the result of some aperiodic event is extremely costly. This paper describes an alternative process and a model for analyzing the resiliency of networks that address some of the shortcomings of more traditional approaches – e.g., the four-step modeling process used in transportation planning. It should be noted that the authors do not view this as a replacement to current approaches but rather as a complementary tool designed to augment analysis capabilities. The process that is described in this paper for analyzing the resiliency of a network involves at least three steps: 1. assessment or identification of important nodes and links according to different criteria 2. verification of critical nodes and links based on failure simulations and 3. consequence. Raster analysis, graph-theory principles and GIS are used to develop a model for carrying out each of these steps. The methods are demonstrated using two, large interdependent networks for a metropolitan area in the United States.

Detection of bearing failure in mechanical devices using neural networks

We present a novel time-domain method for the detection of faulty bearings that has direct applicability to monitoring the health of the turbo pumps on the Space Shuttle Main Engine. A feed-forward neural network was trained to detect modelled roller bearing faults on the basis of the periodicity of impact pulse trains. The network's performance was dependent upon the number of pulses in the network's input window and the signal-to-noise ratio of the input signal. To test the model's validity, we fit the model's parameters to an actual vibration signal generated by a faulty roller element bearing and applied the network trained on this model to detect faults in actual vibration data. When this network was tested on the actual vibration data, it correctly identified the vibration signal as a fault condition 76 percent of the time

Photoperiodism in Hamsters: Abrupt Versus Gradual Changes in Day Length Differentially Entrain Morning and Evening Circadian Oscillators

In studies of photoperiodism, animals typically are transferred abruptly from a long (e.g., 16 h light per day [16L]) to a short (8L) photoperiod, and circadian oscillators that regulate pineal melatonin secretion are presumed to reentrain rapidly to the new photocycle. Among rats and Siberian hamsters, however, reentrainment rates vary depending on whether additional darkness is added to morning or evening, and a subset of hamsters (nonresponders) fails ever to reentrain normally to short photoperiods. The authors assessed whether several short-day responses occurred at different rates when darkness was extended into morning versus evening hours and the effectiveness of abrupt versus gradual shortening in day lengths (DLs). Entrainment patterns of photoresponsive hamsters also were compared to those of photononresponsive hamsters. Responsive hamsters transferred on a single day from 16L to 8L underwent more rapid gonadal regression, weight loss, decreases in follicle-stimulating hormone titers, and expansion of nocturnal locomotor activity when darkness was added to morning versus evening. When the dark phase was extended gradually by 8 h over 16 weeks, short-day responses occurred at the same rate whether darkness was appended to morning or evening or was added symmetrically. Darkness added to evening promoted more rapid short-day responses when it was added gradually rather than abruptly, despite the fact that average DLs were significantly shorter for the latter group. Among nonresponders, morning extensions of darkness transiently increased activity duration, whereas evening extensions did not. Gradual and abrupt decreases in DL differentially affect entrainment of evening and morning circadian oscillators. The authors argue for the incorporation of simulated natural photoperiods in studies of photoperiodism.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66702/2/10.1177_074873049701200204.pd

Use of record-linkage to handle non-response and improve alcohol consumption estimates in health survey data: a study protocol

<p>Introduction: Reliable estimates of health-related behaviours, such as levels of alcohol consumption in the population, are required to formulate and evaluate policies. National surveys provide such data; validity depends on generalisability, but this is threatened by declining response levels. Attempts to address bias arising from non-response are typically limited to survey weights based on sociodemographic characteristics, which do not capture differential health and related behaviours within categories. This project aims to explore and address non-response bias in health surveys with a focus on alcohol consumption.</p> <p>Methods and analysis: The Scottish Health Surveys (SHeS) aim to provide estimates representative of the Scottish population living in private households. Survey data of consenting participants (92% of the achieved sample) have been record-linked to routine hospital admission (Scottish Morbidity Records (SMR)) and mortality (from National Records of Scotland (NRS)) data for surveys conducted in 1995, 1998, 2003, 2008, 2009 and 2010 (total adult sample size around 40 000), with maximum follow-up of 16 years. Also available are census information and SMR/NRS data for the general population. Comparisons of alcohol-related mortality and hospital admission rates in the linked SHeS-SMR/NRS with those in the general population will be made. Survey data will be augmented by quantification of differences to refine alcohol consumption estimates through the application of multiple imputation or inverse probability weighting. The resulting corrected estimates of population alcohol consumption will enable superior policy evaluation. An advanced weighting procedure will be developed for wider use.</p> <p>Ethics and dissemination: Ethics approval for SHeS has been given by the National Health Service (NHS) Multi-Centre Research Ethics Committee and use of linked data has been approved by the Privacy Advisory Committee to the Board of NHS National Services Scotland and Registrar General. Funding has been granted by the MRC. The outputs will include four or five public health and statistical methodological international journal and conference papers.</p&gt

Optimal Moments for the Analysis of Peculiar Velocity Surveys

We present a new method for the analysis of peculiar velocity surveys which removes contributions to velocities from small scale, nonlinear velocity modes while retaining information about large scale motions. Our method utilizes Karhunen--Lo\`eve methods of data compression to construct a set of moments out of the velocities which are minimally sensitive to small scale power. The set of moments are then used in a likelihood analysis. We develop criteria for the selection of moments, as well as a statistic to quantify the overall sensitivity of a set of moments to small scale power. Although we discuss our method in the context of peculiar velocity surveys, it may also prove useful in other situations where data filtering is required.Comment: 25 Pages, 3 figures. Submitted to Ap

Patient-specific CFD models for intraventricular flow analysis from 3D ultrasound imaging : comparison of three clinical cases

Background: As the intracardiac flow field is affected by changes in shape and motility of the heart, intraventricular flow features can provide diagnostic indications. Ventricular flow patterns differ depending on the cardiac condition and the exploration of different clinical cases can provide insights into how flow fields alter in different pathologies. Methods: In this study, we applied a patient-specific computational fluid dynamics model of the left ventricle and mitral valve, with prescribed moving boundaries based on transesophageal ultrasound images for three cardiac pathologies, to verify the abnormal flow patterns in impaired hearts. One case (P1) had normal ejection fraction but low stroke volume and cardiac output, P2 showed low stroke volume and reduced ejection fraction, P3 had a dilated ventricle and reduced ejection fraction. Results: The shape of the ventricle and mitral valve, together with the pathology influence the flow field in the left ventricle, leading to distinct flow features. Of particular interest is the pattern of the vortex formation and evolution, influenced by the valvular orifice and the ventricular shape. The base-to-apex pressure difference of maximum 2 mmHg is consistent with reported data. Conclusion: We used a CFD model with prescribed boundary motion to describe the intraventricular flow field in three patients with impaired diastolic function. The calculated intraventricular flow dynamics are consistent with the diagnostic patient records and highlight the differences between the different cases. The integration of clinical images and computational techniques, therefore, allows for a deeper investigation intraventricular hemodynamics in patho-physiology. (C) 2016 Elsevier Ltd. All rights reserved