Site-Specific Effects of PECAM-1 on Atherosclerosis in LDL Receptor-Deficient Mice

Objective—Atherosclerosis is a vascular disease that involves lesion formation at sites of disturbed flow under the influence of genetic and environmental factors. Endothelial expression of adhesion molecules that enable infiltration of immune cells is important for lesion development. Platelet/endothelial cell adhesion molecule-1 (PECAM-1; CD31) is an adhesion and signaling receptor expressed by many cells involved in atherosclerotic lesion development. PECAM-1 transduces signals required for proinflammatory adhesion molecule expression at atherosusceptible sites; thus, it is predicted to be proatherosclerotic. PECAM-1 also inhibits inflammatory responses, on which basis it is predicted to be atheroprotective. Methods and Results—We evaluated herein the effect of PECAM-1 deficiency on development of atherosclerosis in LDL receptor– deficient mice. We found that PECAM-1 has both proatherosclerotic and atheroprotective effects, but that the former dominate in the inner curvature of the aortic arch whereas the latter dominate in the aortic sinus, branching arteries, and descending aorta. Endothelial cell expression of PECAM-1 was sufficient for its atheroprotective effects in the aortic sinus but not in the descending aorta, where the atheroprotective effects of PECAM-1 also required its expression on bone marrow–derived cells. Conclusion—We conclude that PECAM-1 influences initiation and progression of atherosclerosis both positively and negatively, and that it does so in a site-specific manner. (Arterioscler Thromb Vasc Biol. 2008;28:1996-2002

Development and Pilot of a Checklist for Management of Acute Liver Failure in the Intensive Care Unit

Introduction Acute liver failure (ALF) is an ideal condition for use of a checklist. Our aims were to develop a checklist for the management of ALF in the intensive care unit (ICU) and assess the usability of the checklist among multiple providers. Methods The initial checklist was developed from published guidelines and expert opinion. The checklist underwent pilot testing at 11 academic liver transplant centers in the US and Canada. An anonymous, written survey was used to assess the usability and quality of the checklist. Written comments were used to improve the checklist following the pilot testing period. Results We received 81 surveys involving the management of 116 patients during the pilot testing period. The overall quality of the checklist was judged to be above average to excellent by 94% of users. On a 5-point Likert scale, the majority of survey respondents agreed or agreed strongly with the following checklist characteristics: the checklist was easy to read (99% agreed/agreed strongly), easy to use (97%), items are categorized logically (98%), time to complete the checklist did not interfere with delivery of appropriate and safe patient care (94%) and was not excessively burdensome (92%), the checklist allowed the user the freedom to use his or her clinical judgment (80%), it is a useful tool in the management of acute liver failure (98%). Web-based and mobile apps were developed for use of the checklist at the point of care. Conclusion The checklist for the management of ALF in the ICU was shown in this pilot study to be easy to use, helpful and accepted by a wide variety of practitioners at multiple sites in the US and Canada

Longitudinal Profiles of Girls' Irritable, Defiant and Antagonistic Oppositional Symptoms: Evidence for Group Based Differences in Symptom Severity

Three subdimensions of ODD symptoms have been proposed -angry/irritable (IR), argumentative/defiant (DF) and antagonism (AN). This study tested whether longitudinal symptom trajectories could be identified by these subdimensions. Group-based trajectory analysis was used to identify developmental trajectories of IR, DF and AN symptoms. Multi-group trajectory analysis was then used to identify how subdimension trajectories were linked together over time. Data were drawn from the Pittsburgh Girls Study (PGS; N = 2450), an urban community sample of girls between the ages of five--eight at baseline. We included five waves of annual data across ages five-13 to model trajectories. Three trajectories were identified for each ODD subdimension: DF and AN were characterized by high, medium and low severity groups; IR was characterized by low, medium stable, and high increasing groups. Multi-trajectory analysis confirmed these subdimensions were best linked together based on symptom severity. We did not identify girls' trajectory groups that were characterized predominantly by a particular subdimension of ODD symptoms. Membership in more severe symptom groups was significantly associated with worse outcomes five years later. In childhood and early adolescence girls with high levels of ODD symptoms can be identified, and these youth are characterized by a persistently elevated profile of IR, DF and AN symptoms. Further studies in clinical samples are required to examine the ICD-10 proposal that ODD with irritability is a distinct or more severe form of ODD

Interobserver agreement for neonatal seizure detection using multichannel EEG

Objective To determine the interobserver agreement (IOA) of neonatal seizure detection using the gold standard of conventional, multichannel EEG. Methods A cohort of full-term neonates at risk of acute encephalopathy was included in this prospective study. The EEG recordings of these neonates were independently reviewed for seizures by three international experts. The IOA was estimated using statistical measures including Fleiss' kappa and percentage agreement assessed over seizure events (event basis) and seizure duration (temporal basis). Results A total of 4066 h of EEG recordings from 70 neonates were reviewed with an average of 2555 seizures detected. The IOA was high with temporal assessment resulting in a kappa of 0.827 (95% CI: 0.769–0.865; n = 70). The median agreement was 83.0% (interquartile range [IQR]: 76.6–89.5%; n = 33) for seizure and 99.7% (IQR: 98.9–99.8%; n = 70) for nonseizure EEG. Analysis of events showed a median agreement of 83.0% (IQR: 72.9–86.6%; n = 33) for seizures with 0.018 disagreements per hour (IQR: 0.000–0.090 per hour; n = 70). Observers were more likely to disagree when a seizure was less than 30 sec. Overall, 33 neonates were diagnosed with seizures and 28 neonates were not, by all three observers. Of the remaining nine neonates with contradictory EEG detections, seven presented with low total seizure burden. Interpretation The IOA is high among experts for the detection of neonatal seizures using conventional, multichannel EEG. Agreement is reduced when seizures are rare or have short duration. These findings support EEG-based decision making in the neonatal intensive care unit, inform EEG interpretation guidelines, and provide benchmarks for seizure detection algorithms.Peer reviewe

Red Galaxy Growth and the Halo Occupation Distribution

We have traced the past 7 Gyr of red galaxy stellar mass growth within dark matter halos. We have determined the halo occupation distribution, which describes how galaxies reside within dark matter halos, using the observed luminosity function and clustering of 40,696 0.2<z<1.0 red galaxies in Bootes. Half of 10^{11.9} Msun/h halos host a red central galaxy, and this fraction increases with increasing halo mass. We do not observe any evolution of the relationship between red galaxy stellar mass and host halo mass, although we expect both galaxy stellar masses and halo masses to evolve over cosmic time. We find that the stellar mass contained within the red population has doubled since z=1, with the stellar mass within red satellite galaxies tripling over this redshift range. In cluster mass halos most of the stellar mass resides within satellite galaxies and the intra-cluster light, with a minority of the stellar mass residing within central galaxies. The stellar masses of the most luminous red central galaxies are proportional to halo mass to the power of a third. We thus conclude that halo mergers do not always lead to rapid growth of central galaxies. While very massive halos often double in mass over the past 7 Gyr, the stellar masses of their central galaxies typically grow by only 30%.Comment: Accepted for publication in the ApJ. 34 pages, 22 Figures, 5 Table

External validation of a bifactor model of oppositional defiant disorder

Dimensions of irritability and defiant behavior, though correlated within the structure of ODD, convey separable developmental risks through adolescence and adulthood. Irritability predicts depression and anxiety, whereas defiant behavior is a precursor to antisocial outcomes. Previously we demonstrated that a bifactor model comprising irritability and defiant behavior dimensions, in addition to a general factor, provided the best-fitting structure of ODD symptoms in five large datasets. Herein we extend our previous work by externally validating the bifactor model of ODD using multiple regression and multivariate behavior genetic analyses. We used parent ratings of DSM IV ODD symptoms, and symptom dimensions for ADHD (i.e., inattention and hyperactivity−impulsivity), conduct disorder (CD), depression/dysthymia, and generalized anxiety disorder (GAD) from 846 6−18-year-old twin pairs. We found that the ODD irritability factor was associated only with depression/dysthymia and GAD and the ODD defiant behavior factor was associated only with inattention, hyperactivity−impulsivity, and CD, whereas the ODD general factor was associated with all five symptom dimensions. Multivariate behavior genetic analyses found all five symptom dimensions shared genetic influences in common with the ODD general, irritability, and defiant behavior factors. In contrast, the defiant behavior factor shared genetic influences uniquely with inattention and hyperactivity−impulsivity, whereas the irritability factor shared genetic influences uniquely with depression/dysthymia and GAD, but not vice versa. This suggests that genes that influence irritability in early childhood also predispose to depression and anxiety in adolescence and adulthood. These multivariate genetic findings also support the external validity of the three ODD dimensions at the etiological level. Our study provides additional support for subtyping ODD based on these symptom dimensions, as in the revisions in the ICD-11, and suggests potential mechanisms underlying the development from ODD to behavioral or affective disorders

A standardised assessment scheme for conventional EEG in preterm infants

Objective: To develop a standardised scheme for assessing normal and abnormal electroencephalography (EEG) features of preterm infants. To assess the interobserver agreement of this assessment scheme. Methods: We created a standardised EEG assessment scheme for 6 different post-menstrual age (PMA) groups using 4 EEG categories. Two experts, not involved in the development of the scheme, evaluated this on 24 infants &lt;32 weeks gestational age (GA) using random 2 hour EEG epochs. Where disagreements were found, the features were checked and modified. Finally, the two experts independently evaluated 2 hour EEG epochs from an additional 12 infants &lt;37 weeks GA. The percentage of agreement was calculated as the ratio of agreements to the sum of agreements plus disagreements. Results: Good agreement in all patients and EEG feature category was obtained, with a median agreement between 80% and 100% over the 4 EEG assessment categories. No difference was found in agreement rates between the normal and abnormal features (p = 0.959). Conclusions: We developed a standard EEG assessment scheme for preterm infants that shows good interobserver agreement. Significance: This will provide information to Neonatal Intensive Care Unit (NICU) staff about brain activity and maturation. We hope this will prove useful for many centres seeking to use neuromonitoring during critical care for preterm infants