Toward optimal display of physiologic status in critical care: I. Recreating bedside displays from archived physiologic data

BACKGROUND: Physiologic data display is essential to decision making in critical care. Current displays echo first-generation hemodynamic monitors dating to the 1970s and have not kept pace with new insights into physiology or the needs of clinicians who must make progressively more complex decisions about their patients. The effectiveness of any redesign must be tested before deployment. Tools that compare current displays with novel presentations of processed physiologic data are required. Regenerating conventional physiologic displays from archived physiologic data is an essential first step. OBJECTIVES: The purposes of the study were to (1) describe the SSSI (single sensor single indicator) paradigm that is currently used for physiologic signal displays, (2) identify and discuss possible extensions and enhancements of the SSSI paradigm, and (3) develop a general approach and a software prototype to construct such "extended SSSI displays" from raw data. RESULTS: We present Multi Wave Animator (MWA) framework-a set of open source MATLAB (MathWorks, Inc., Natick, MA, USA) scripts aimed to create dynamic visualizations (eg, video files in AVI format) of patient vital signs recorded from bedside (intensive care unit or operating room) monitors. Multi Wave Animator creates animations in which vital signs are displayed to mimic their appearance on current bedside monitors. The source code of MWA is freely available online together with a detailed tutorial and sample data sets.

Postreperfusion cardiac arrest and resuscitation during orthotopic liver transplantation: dynamic visualization and analysis of physiologic recordings

We recently reported on the Multi Wave Animator (MWA), a novel open-source tool with capability of recreating continuous physiologic signals from archived numerical data and presenting them as they appeared on the patient monitor. In this report, we demonstrate for the first time the power of this technology in a real clinical case, an intraoperative cardiopulmonary arrest following reperfusion of a liver transplant graft. Using the MWA, we animated hemodynamic and ventilator data acquired before, during, and after cardiac arrest and resuscitation. This report is accompanied by an online video that shows the most critical phases of the cardiac arrest and resuscitation and provides a basis for analysis and discussion. This video is extracted from a 33-min, uninterrupted video of cardiac arrest and resuscitation, which is available online. The unique strength of MWA, its capability to accurately present discrete and continuous data in a format familiar to clinicians, allowed us this rare glimpse into events leading to an intraoperative cardiac arrest. Because of the ability to recreate and replay clinical events, this tool should be of great interest to medical educators, researchers, and clinicians involved in quality assurance and patient safety.

Screening and testing for endocrine disruption in fish-biomarkers as "signposts," not "traffic lights," in risk assessment

Biomarkers are currently best used as mechanistic "signposts" rather than as "traffic lights" in the environmental risk assessment of endocrine-disrupting chemicals (EDCs). In field studies, biomarkers of exposure [e.g., vitellogenin (VTG) induction in male fish] are powerful tools for tracking single substances and mixtures of concern. Biomarkers also provide linkage between field and laboratory data, thereby playing an important role in directing the need for and design of fish chronic tests for EDCs. It is the adverse effect end points (e.g., altered development, growth, and/or reproduction) from such tests that are most valuable for calculating adverseNOEC (no observed effect concentration) or adverseEC10 (effective concentration for a 10% response) and subsequently deriving predicted no effect concentrations (PNECs). With current uncertainties, biomarkerNOEC or biomarkerEC10 data should not be used in isolation to derive PNECs. In the future, however, there may be scope to increasingly use biomarker data in environmental decision making, if plausible linkages can be made across levels of organization such that adverse outcomes might be envisaged relative to biomarker responses. For biomarkers to fulfil their potential, they should be mechanistically relevant and reproducible (as measured by interlaboratory comparisons of the same protocol). VTG is a good example of such a biomarker in that it provides an insight to the mode of action (estrogenicity) that is vital to fish reproductive health. Interlaboratory reproducibility data for VTG are also encouraging; recent comparisons (using the same immunoassay protocol) have provided coefficients of variation (CVs) of 38-55% (comparable to published CVs of 19-58% for fish survival and growth end points used in regulatory test guidelines). While concern over environmental xenoestrogens has led to the evaluation of reproductive biomarkers in fish, it must be remembered that many substances act via diverse mechanisms of action such that the environmental risk assessment for EDCs is a broad and complex issue. Also, biomarkers such as secondary sexual characteristics, gonadosomatic indices, plasma steroids, and gonadal histology have significant potential for guiding interspecies assessments of EDCs and designing fish chronic tests. To strengthen the utility of EDC biomarkers in fish, we need to establish a historical control database (also considering natural variability) to help differentiate between statistically detectable versus biologically significant responses. In conclusion, as research continues to develop a range of useful EDC biomarkers, environmental decision-making needs to move forward, and it is proposed that the "biomarkers as signposts" approach is a pragmatic way forward in the current risk assessment of EDCs.

Impact of environmental estrogens on Yfish considering the diversity of estrogen signaling.

Research on endocrine disruption in fish has been dominated by studies on estrogen-active compounds which act as mimics of the natural estrogen, 17β-estradiol (E2), and generally exert their biological actions by binding to and activation of estrogen receptors (ERs). Estrogens play central roles in reproductive physiology and regulate (female) sexual differentiation. In line with this, most adverse effects reported for fish exposed to environmental estrogens relate to sexual differentiation and reproduction. E2, however, utilizes a variety of signaling mechanisms, has multifaceted functions and targets, and therefore the toxicological and ecological effects of environmental estrogens in fish will extend beyond those associated with the reproduction. This review first describes the diversity of estrogen receptor signaling in fish, including both genomic and non-genomic mechanisms, and receptor crosstalk. It then considers the range of non-reproductive physiological processes in fish that are known to be responsive to estrogens, including sensory systems, the brain, the immune system, growth, specifically through the growth hormone/insulin-like growth factor system, and osmoregulation. The diversity in estrogen responses between fish species is then addressed, framed within evolutionary and ecological contexts, and we make assessments on their relevance for toxicological sensitivity as well as ecological vulnerability. The diversity of estrogen actions raises questions whether current risk assessment strategies, which focus on reproductive endpoints, and a few model fish species only, are protective of the wider potential health effects of estrogens. Available - although limited - evidence nevertheless suggests that quantitative environmental threshold concentrations for environmental protection derived from reproductive tests with model fish species are protective for non-reproductive effects as well. The diversity of actions of estrogens across divergent physiological systems, however, may lead to and underestimation of impacts on fish populations as their effects are generally considered on one functional process only and this may underrepresent the impact on the different physiological processes collectively.

A linguistically informed autosomal STR survey of human populations residing in the Greater Himalayan Region

The greater Himalayan region demarcates two of the most prominent linguistic phyla in Asia: Tibeto-Burman and Indo-European. Previous genetic surveys, mainly using Y-chromosome polymorphisms and/or mitochondrial DNA polymorphisms suggested a substantially reduced geneflow between populations belonging to these two phyla. These studies, however, have mainly focussed on populations residing far to the north and/or south of this mountain range, and have not been able to study geneflow patterns within the greater Himalayan region itself. We now report a detailed, linguistically informed, genetic survey of Tibeto-Burman and Indo-European speakers from the Himalayan countries Nepal and Bhutan based on autosomal microsatellite markers and compare these populations with surrounding regions. The genetic differentiation between populations within the Himalayas seems to be much higher than between populations in the neighbouring countries. We also observe a remarkable genetic differentiation between the Tibeto-Burman speaking populations on the one hand and Indo-European speaking populations on the other, suggesting that language and geography have played an equally large role in defining the genetic composition of present-day populations within the Himalayas.

M-Functionals of Multivariate Scatter

This survey provides a self-contained account of M-estimation of multivariate scatter. In particular, we present new proofs for existence of the underlying M-functionals and discuss their weak continuity and differentiability. This is done in a rather general framework with matrix-valued random variables. By doing so we reveal a connection between Tyler's (1987) M-functional of scatter and the estimation of proportional covariance matrices. Moreover, this general framework allows us to treat a new class of scatter estimators, based on symmetrizations of arbitrary order. Finally these results are applied to M-estimation of multivariate location and scatter via multivariate t-distributions.

Global diversity, population stratification and selection of human copy number variation

In order to explore the diversity and selective signatures of duplication and deletion human copy number variants (CNVs), we sequenced 236 individuals from 125 distinct human populations. We observed that duplications exhibit fundamentally different population genetic and selective signatures than deletions and are more likely to be stratified between human populations. Through reconstruction of the ancestral human genome, we identify megabases of DNA lost in different human lineages and pinpoint large duplications that introgressed from the extinct Denisova lineage now found at high frequency exclusively in Oceanic populations. We find that the proportion of CNV base pairs to single nucleotide variant base pairs is greater among non-Africans than it is among African populations, but we conclude that this difference is likely due to unique aspects of non-African population history as opposed to differences in CNV load.

On The Breakdown Properties of some Multivariate M-Functionals

For probability distributions on ℝq, a detailed study of the breakdown properties of some multivariate M-functionals related to Tyler's [Ann. Statist. 15 (1987) 234] ‘distribution-free’ M-functional of scatter is given. These include a symmetrized version of Tyler's M-functional of scatter, and the multivariate t M-functionals of location and scatter. It is shown that for ‘smooth’ distributions, the (contamination) breakdown point of Tyler's M-functional of scatter and of its symmetrized version are 1/q and inline image, respectively. For the multivariate t M-functional which arises from the maximum likelihood estimate for the parameters of an elliptical t distribution on ν ≥ 1 degrees of freedom the breakdown point at smooth distributions is 1/(q + ν). Breakdown points are also obtained for general distributions, including empirical distributions. Finally, the sources of breakdown are investigated. It turns out that breakdown can only be caused by contaminating distributions that are concentrated near low-dimensional subspaces.