Background: Emotion dysregulation has been implicated in the negative outcomes following trauma exposure. A proposed biomarker of emotion dysregulation, respiratory sinus arrhythmia (RSA), has demonstrated associations with trauma-related phenomena, such as the fear-potentiated startle (FPS) response. The current study aimed to examine the prospective association between emotion dysregulation and RSA and FPS several years following trauma exposure.
Methods: Participants were 131 women exposed to a campus mass shooting on February 14, 2008. Pre-shooting emotion dysregulation was assessed in 2006-2008. Startle response, measured by orbicularis oculi electromyography (EMG), and RSA were gathered during an FPS paradigm conducted from 2012 to 2015.
Results: No significant associations among emotion dysregulation, RSA, and FPS emerged among the full sample. However, emotion dysregulation predicted FPS during both acquisition (r = 0.40, p < 0.05) and extinction (r = 0.57, p < 0.01) among individuals with high resting RSA.
Conclusions: Findings suggest that pre-shooting emotion dysregulation is a potent predictor of FPS several years following potential trauma exposure, and this association varies by RSA level. Results emphasize the importance of examining autonomic regulation in the association between emotion dysregulation and recovery from trauma exposure.
High false alarm rates in the ICU decrease quality of care by slowing staff response times while increasing patient delirium through noise pollution. The 2015 PhysioNet/Computing in Cardiology Challenge provides a set of 1250 multi-parameter ICU data segments associated with critical arrhythmia alarms, and challenges the general research community to address the issue of false alarm suppression using all available signals. Each data segment was 5 minutes long (for real time analysis), ending at the time of the alarm. For retrospective analysis, we provided a further 30 seconds of data after the alarm was triggered. A total of 750 data segments were made available for training and 500 were held back for testing. Each alarm was reviewed by expert annotators, at least two of whom agreed that the alarm was either true or false. Challenge participants were invited to submit a complete, working algorithm to distinguish true from false alarms, and received a score based on their program's performance on the hidden test set. This score was based on the percentage of alarms correct, but with a penalty that weights the suppression of true alarms five times more heavily than acceptance of false alarms. We provided three example entries based on well-known, open source signal processing algorithms, to serve as a basis for comparison and as a starting point for participants to develop their own code. A total of 38 teams submitted a total of 215 entries in this year's Challenge. This editorial reviews the background issues for this challenge, the design of the challenge itself, the key achievements, and the follow-up research generated as a result of the Challenge, published in the concurrent special issue of Physiological Measurement. Additionally we make some recommendations for future changes in the field of patient monitoring as a result of the Challenge.
by
Juan A. Contreras-Vite;
Silvia Cruz-Rangel;
José J. De Jesus-Perez;
Iván A. Arechiga Figueroa;
Aldo A. Rodriguez-Menchaca;
Patricia Perez-Cornejo;
Harrison Hartzell Jr.;
Jorge Arreola
TMEM16A (ANO1), the pore-forming subunit of calcium-activated chloride channels, regulates several physiological and pathophysiological processes such as smooth muscle contraction, cardiac and neuronal excitability, salivary secretion, tumour growth and cancer progression. Gating of TMEM16A is complex because it involves the interplay between increases in intracellular calcium concentration ([Ca 2+ ] i ), membrane depolarization, extracellular Cl − or permeant anions and intracellular protons. Our goal here was to understand how these variables regulate TMEM16A gating and to explain four observations. (a) TMEM16A is activated by voltage in the absence of intracellular Ca 2+ . (b) The Cl − conductance is decreased after reducing extracellular Cl − concentration ([Cl − ] o ). (c) I Cl is regulated by physiological concentrations of [Cl − ] o . (d) In cells dialyzed with 0.2 μM [Ca 2+ ] i , Cl − has a bimodal effect: at [Cl − ] o < 30 mM TMEM16A current activates with a monoexponential time course, but above 30 mM, [Cl − ] o I Cl activation displays fast and slow kinetics. To explain the contribution of V m , Ca 2+ and Cl − to gating, we developed a 12-state Markov chain model. This model explains TMEM16A activation as a sequential, direct, and V m -dependent binding of two Ca 2+ ions coupled to a V m -dependent binding of an external Cl − ion, with V m -dependent transitions between states. Our model predicts that extracellular Cl − does not alter the apparent Ca 2+ affinity of TMEM16A, which we corroborated experimentally. Rather, extracellular Cl − acts by stabilizing the open configuration induced by Ca 2+ and by contributing to the V m dependence of activation.
Purpose: To develop and validate the Pediatric Risk Estimation Score for Children Using Extracorporeal Respiratory Support (Ped-RESCUERS). Ped-RESCUERS is designed to estimate the in-hospital mortality risk for children prior to receiving respiratory extracorporeal membrane oxygenation (ECMO) support. Methods: This study used data from an international registry of patients aged 29 days to less than 18 years who received ECMO support from 2009 to 2014. We divided the registry into development and validation datasets by calendar date. Candidate variables were selected for model inclusion if the variable independently changed the mortality risk by at least 2 % in a Bayesian logistic regression model with in-hospital mortality as the outcome. We characterized the model’s ability to discriminate mortality with the area under curve (AUC) of the receiver operating characteristic. Results: From 2009 to 2014, 2458 non-neonatal children received ECMO for respiratory support, with a mortality rate of 39.8 %. The development dataset contained 1611 children receiving ECMO support from 2009 to 2012. The model included the following variables: pre-ECMO pH, pre-ECMO arterial partial pressure of carbon dioxide, hours of intubation prior to ECMO support, hours of admission at ECMO center prior to ECMO support, ventilator type, mean airway pressure, pre-ECMO use of milrinone, and a diagnosis of pertussis, asthma, bronchiolitis, or malignancy. The validation dataset included 438 children receiving ECMO support from 2013 to 2014. The Ped-RESCUERS model from the development dataset had an AUC of 0.690, and the validation dataset had an AUC of 0.634. Conclusions: Ped-RESCUERS provides a novel measure of pre-ECMO mortality risk. Future studies should seek external validation and improved discrimination of this mortality prediction tool.
Clinical data management systems typically provide caregiver teams with useful information, derived from large, sometimes highly heterogeneous, data sources that are often changing dynamically. Over the last decade there has been a significant surge in interest in using these data sources, from simply reusing the standard clinical databases for event prediction or decision support, to including dynamic and patient-specific information into clinical monitoring and prediction problems. However, in most cases, commercial clinical databases have been designed to document clinical activity for reporting, liability, and billing reasons, rather than for developing new algorithms. With increasing excitement surrounding 'secondary use of medical records' and 'Big Data' analytics, it is important to understand the limitations of current databases and what needs to change in order to enter an era of 'precision medicine.' This review article covers many of the issues involved in the collection and preprocessing of critical care data. The three challenges in critical care are considered: compartmentalization, corruption, and complexity. A range of applications addressing these issues are covered, including the modernization of static acuity scoring; online patient tracking; personalized prediction and risk assessment; artifact detection; state estimation; and incorporation of multimodal data sources such as genomic and free text data.
by
Charles T. Quinn;
Eric P. Smith;
Shahriar Arbabi;
Paramjit K. Khera;
Christopher J. Lindsell;
Omar Niss;
Clinton Joiner;
Robert S. Franco;
Robert M. Cohen
Hemolysis is a key feature of sickle cell anemia (HbSS). Direct quantitation of hemolysis could be used as an objective outcome in clinical trials of new therapeutics for HbSS and would also enable better human studies of the pathogenesis of complications of HbSS that are ostensibly hemolysis-related, such as pulmonary hypertension. However, contemporary human studies in HbSS have used only surrogate markers of hemolysis rather than direct measurements of RBC survival. We directly quantified hemolysis in HbSS by measuring survival of an age cohort of RBCs labeled with a stable isotope, administered orally as 15N-glycine, a metabolic precursor of heme. The atomic excess of 15N in heme extracted from blood was monitored by mass spectrometry over time. We performed 13 labeling experiments in 11 individuals with HbSS. Mean RBC survival was 31.9 days (range 14.1–53.6). Both HbF level, a known determinant of hemolysis, and absolute reticulocyte count (ARC), an index of the marrow’s response to hemolysis, correlated with directly measured RBC survival (r = 0.61, P < 0.002; r = −0.84, P < 0.001). However, commonly used biochemical surrogates of hemolysis (LDH, AST, bilirubin, and plasma free hemoglobin) did not correlate with directly measured RBC survival. These biochemical surrogates should be interpreted cautiously, at best, in clinical trials and human physiologic studies in HbSS. ARC was the best correlate of total hemolysis, but only 70% of the variation in RBC survival was reflected in this marker. If greater accuracy is required in human studies, 15N-glycine RBC labeling can directly and accurately quantify hemolysis. Am. J. Hematol. 91:1195–1201, 2016.
Here, we investigated whether hyperglycemia and/or free fatty acids (palmitate, PAL) affect the expression level of bone morphogenic protein 4 (BMP4), a proatherogenic marker, in endothelial cells and the potential role of BMP4 in diabetic vascular complications. To measure BMP4 expression, human umbilical vein endothelial cells (HUVECs) were exposed to high glucose concentrations and/or PAL for 24 or 72 h, and the effects of these treatments on the expression levels of adhesion molecules and reactive oxygen species (ROS) were examined. BMP4 loss-of-function status was achieved via transfection of a BMP4-specific siRNA. High glucose levels increased BMP4 expression in HUVECs in a dose-dependent manner. PAL potentiated such expression. The levels of adhesion molecules and ROS production increased upon treatment with high glucose and/or PAL, but this effect was negated when BMP4 was knocked down via siRNA. Signaling of BMP4, a proinflammatory and pro-atherogenic cytokine marker, was increased by hyperglycemia and PAL. BMP4 induced the expression of inflammatory adhesion molecules and ROS production. Our work suggests that BMP4 plays a role in atherogenesis induced by high glucose levels and/or PAL.
The sarcomere, the fundamental unit of muscle contraction, is a highly-ordered complex of hundreds of proteins. Despite decades of genetics work, the functional relationships and the roles of those sarcomeric proteins in animal behaviors remain unclear. In this paper, we demonstrate that optogenetic activation of the motor neurons that induce muscle contraction can facilitate quantitative studies of muscle kinetics in C. elegans. To increase the throughput of the study, we trapped multiple worms in parallel in a microfluidic device and illuminated for photoactivation of channelrhodopsin-2 to induce contractions in body wall muscles. Using image processing, the change in body size was quantified over time. A total of five parameters including rate constants for contraction and relaxation were extracted from the optogenetic assay as descriptors of sarcomere functions. To potentially relate the genes encoding the sarcomeric proteins functionally, a hierarchical clustering analysis was conducted on the basis of those parameters. Because it assesses physiological output different from conventional assays, this method provides a complement to the phenotypic analysis of C. elegans muscle mutants currently performed in many labs; the clusters may provide new insights and drive new hypotheses for functional relationships among the many sarcomere components.
by
Chengyu Liu;
David Springer;
Qiao Li;
Benjamin Moody;
Ricardo Abad Juan;
Francisco J. Chorro;
Francisco Castells;
Jose Millet Roig;
Ikaro Silva;
Alistair E.W. Johnson;
Zeeshan Syed;
Samuel E. Schmidt;
Chrysa D. Papadaniil;
Leontios Hadjileontiadis;
Hosein Naseri;
Ali Moukadem;
Alain Dieterlen;
Christian Brandt;
Hong Tang;
Maryam Samieinasab;
Mohammad Reza Samieinasab;
Reza Sameni;
Roger G. Mark;
Gari Clifford
In the past few decades, analysis of heart sound signals (i.e. the phonocardiogram or PCG), especially for automated heart sound segmentation and classification, has been widely studied and has been reported to have the potential value to detect pathology accurately in clinical applications. However, comparative analyses of algorithms in the literature have been hindered by the lack of high-quality, rigorously validated, and standardized open databases of heart sound recordings. This paper describes a public heart sound database, assembled for an international competition, the PhysioNet/Computing in Cardiology (CinC) Challenge 2016. The archive comprises nine different heart sound databases sourced from multiple research groups around the world.
It includes 2435 heart sound recordings in total collected from 1297 healthy subjects and patients with a variety of conditions, including heart valve disease and coronary artery disease. The recordings were collected from a variety of clinical or nonclinical (such as in-home visits) environments and equipment. The length of recording varied from several seconds to several minutes. This article reports detailed information about the subjects/patients including demographics (number, age, gender), recordings (number, location, state and time length), associated synchronously recorded signals, sampling frequency and sensor type used.
We also provide a brief summary of the commonly used heart sound segmentation and classification methods, including open source code provided concurrently for the Challenge. A description of the PhysioNet/CinC Challenge 2016, including the main aims, the training and test sets, the hand corrected annotations for different heart sound states, the scoring mechanism, and associated open source code are provided. In addition, several potential benefits from the public heart sound database are discussed.
P2X purinergic receptors are plasma membrane ATP-dependent cation channels that are broadly distributed in the mammalian tissues. P2RX2 is a modulator of auditory sensory hair cell mechanotransduction and plays an important role in hair cell tolerance to noise. In this study, we demonstrate for the first time in vitro and in cochlear neuroepithelium, that P2RX2 possesses the ATPase activity. We observed that the P2RX2 V60L human deafness mutation alters its ability to bind ATP, while the G353R has no effect on ATP binding or hydrolysis. A non-hydrolysable ATP assay using HEK293 cells suggests that ATP hydrolysis plays a significant role in the opening and gating of the P2RX2 ion channel. Moreover, the results of structural modeling of the molecule was in agreement with our experimental observations. These novel findings suggest the intrinsic ATPase activity of P2RX2 and provide molecular insights into the channel opening.