Automated Detection of Infectious Disease Outbreaks in Hospitals: A Retrospective Cohort Study

Susan Huang and colleagues describe an automated statistical software, WHONET-SaTScan, its application in a hospital, and the potential it has to identify hospital infection clusters that had escaped routine detection

Imaging of Functional Connectivity in the Mouse Brain

Functional neuroimaging (e.g., with fMRI) has been difficult to perform in mice, making it challenging to translate between human fMRI studies and molecular and genetic mechanisms. A method to easily perform large-scale functional neuroimaging in mice would enable the discovery of functional correlates of genetic manipulations and bridge with mouse models of disease. To satisfy this need, we combined resting-state functional connectivity mapping with optical intrinsic signal imaging (fcOIS). We demonstrate functional connectivity in mice through highly detailed fcOIS mapping of resting-state networks across most of the cerebral cortex. Synthesis of multiple network connectivity patterns through iterative parcellation and clustering provides a comprehensive map of the functional neuroarchitecture and demonstrates identification of the major functional regions of the mouse cerebral cortex. The method relies on simple and relatively inexpensive camera-based equipment, does not require exogenous contrast agents and involves only reflection of the scalp (the skull remains intact) making it minimally invasive. In principle, fcOIS allows new paradigms linking human neuroscience with the power of molecular/genetic manipulations in mouse models

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

International criteria for electrocardiographic interpretation in athletes: Consensus statement.

Sudden cardiac death (SCD) is the leading cause of mortality in athletes during sport. A variety of mostly hereditary, structural or electrical cardiac disorders are associated with SCD in young athletes, the majority of which can be identified or suggested by abnormalities on a resting 12-lead electrocardiogram (ECG). Whether used for diagnostic or screening purposes, physicians responsible for the cardiovascular care of athletes should be knowledgeable and competent in ECG interpretation in athletes. However, in most countries a shortage of physician expertise limits wider application of the ECG in the care of the athlete. A critical need exists for physician education in modern ECG interpretation that distinguishes normal physiological adaptations in athletes from distinctly abnormal findings suggestive of underlying pathology. Since the original 2010 European Society of Cardiology recommendations for ECG interpretation in athletes, ECG standards have evolved quickly, advanced by a growing body of scientific data and investigations that both examine proposed criteria sets and establish new evidence to guide refinements. On 26-27 February 2015, an international group of experts in sports cardiology, inherited cardiac disease, and sports medicine convened in Seattle, Washington (USA), to update contemporary standards for ECG interpretation in athletes. The objective of the meeting was to define and revise ECG interpretation standards based on new and emerging research and to develop a clear guide to the proper evaluation of ECG abnormalities in athletes. This statement represents an international consensus for ECG interpretation in athletes and provides expert opinion-based recommendations linking specific ECG abnormalities and the secondary evaluation for conditions associated with SCD

Talking Less during Social Interactions Predicts Enjoyment: A Mobile Sensing Pilot Study

Can we predict which conversations are enjoyable without hearing the words that are spoken? A total of 36 participants used a mobile app, My Social Ties, which collected data about 473 conversations that the participants engaged in as they went about their daily lives. We tested whether conversational properties (conversation length, rate of turn taking, proportion of speaking time) and acoustical properties (volume, pitch) could predict enjoyment of a conversation. Surprisingly, people enjoyed their conversations more when they spoke a smaller proportion of the time. This pilot study demonstrates how conversational properties of social interactions can predict psychologically meaningful outcomes, such as how much a person enjoys the conversation. It also illustrates how mobile phones can provide a window into everyday social experiences and well-being

On gene dosage balance in protein complexes: a comment on Semple JI, Vavouri T, Lehner B. A simple principle concerning the robustness of protein complex activity to changes in gene expression.

A comment on Semple JI, Vavouri T, Lehner B. A simple principle concerning the robustness of protein complex activity to changes in gene expression. BMC Syst Biol. 2008;2:

Physical and land-cover variables influence ant functional groups and species diversity along elevational gradients

Of particular importance in shaping species assemblages is the spatial heterogeneity of the environment. The aim of our study was to investigate the influence of spatial heterogeneity and environmental complexity on the distribution of ant functional groups and species diversity along altitudinal gradients in a temperate ecosystem (Pyrenees Mountains). During three summers, we sampled 20 sites distributed across two Pyrenean valleys ranging in altitude from 1,009 to 2,339 m by using pitfall traps and hand collection. The environment around each sampling points was characterized by using both physical and land-cover variables. We then used a self-organizing map algorithm (SOM, neural network) to detect and characterize the relationship between the spatial distribution of ant functional groups, species diversity, and the variables measured. The use of SOM allowed us to reduce the apparent complexity of the environment to five clusters that highlighted two main gradients: an altitudinal gradient and a gradient of environmental closure. The composition of ant functional groups and species diversity changed along both of these gradients and was differently affected by environmental variables. The SOM also allowed us to validate the contours of most ant functional groups by highlighting the response of these groups to the environmental and land-cover variables