Assessment of Neighborhood Poverty, Cognitive Function, and Prefrontal and Hippocampal Volumes in Children

IMPORTANCE

The association between poverty and unfavorable cognitive outcomes is robust, but most research has focused on individual household socioeconomic status (SES). There is increasing evidence that neighborhood context explains unique variance not accounted for by household SES.

OBJECTIVE

To evaluate whether neighborhood poverty (NP) is associated with cognitive function and prefrontal and hippocampal brain structure in ways that are dissociable from household SES.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used a baseline sample of the ongoing longitudinal Adolescent Brain Cognitive Development (ABCD) Study. The ABCD Study will follow participants for assessments each year for 10 years. Data were collected at 21 US sites, mostly within urban and suburban areas, between September 2019 and October 2018. School-based recruitment was used to create a participant sample reflecting the US population. Data analysis was conducted from March to June 2019.

MAIN OUTCOMES AND MEASURES

NP and household SES were included as factors potentially associated with National Institutes of Health Toolbox Cognitive Battery subtests and hippocampal and prefrontal (dorsolateral prefrontal cortex [DLPFC], dorsomedial PFC [DMPFC], superior frontal gyrus [SFG]) volumes. Independent variables were first considered individually and then together in mixed-effects models with age, sex, and intracranial volume as covariates. Structural equation modeling (SEM) was used to assess shared variance in NP to brain structure and cognitive task associations. The tested hypotheses were formulated after data collection.

RESULTS

A total of 11 875 children aged 9 and 10 years (5678 [47.8%] girls) were analyzed. Greater NP was associated with lower scores across all cognitive domains (eg, total composite: β = -0.18; 95% CI, -0.21 to -0.15; P < .001) and with decreased brain volume in the DLPFC (eg, right DLPFC: β = -0.09; 95% CI, -0.12 to -0.07; P < .001), DMPFC (eg, right DMPC: β = -0.07; 95% CI, -0.09 to -0.05; P < .001), SFG (eg, right SFG: β = -0.05; 95% CI, -0.08 to -0.03; P < .001), and right hippocampus (β = -0.04; 95% CI, -0.06 to -0.01; P = .01), even when accounting for household income. Greater household income was associated with higher scores across all cognitive domains (eg, total composite: β = 0.30; 95% CI, 0.28 to 0.33; P < .001) and larger volume in all prefrontal and hippocampal brain regions (eg, right hippocampus: β = 0.04; 95% CI, 0.02 to 0.07; P < .001) even when accounting for NP. The SEM model was a good fit across all cognitive domains, with prefrontal regions being associated with NP relations to language (picture vocabulary: estimate [SE], -0.03 [0.01]; P < .001; oral reading: estimate [SE], -0.02 [0.01]; P < .001), episodic memory (picture sequence: estimate [SE], -0.02 [0.01]; P = .008), and working memory (dimensional card sort: estimate [SE], -0.02 [0.01]; P = .001; flanker inhibitory control: estimate [SE], -0.01 [0.01]; P = .01; list sorting: estimate [SE], -0.03 [0.01]; P < .001) and hippocampal regions being associated with NP associations with language (picture vocabulary: estimate [SE], -0.01 [0.004]; P < .001) and episodic memory (picture sequence: estimate [SE], -0.01 [0.004]; P < 0.001).

CONCLUSIONS AND RELEVANCE

In this study, NP accounted for unique variance in cognitive function and prefrontal and right hippocampal brain volume. These findings demonstrate the importance of including broader environmental influences when conceptualizing early life adversity.

Statistical Guidelines for Handling Missing Data in Traumatic Brain Injury Clinical Research

Missing data is a persistent and unavoidable problem in even the most carefully designed traumatic brain injury (TBI) clinical research. Missing data patterns may result from participant dropout, non-compliance, technical issues, or even death. This review describes the types of missing data that are common in TBI research, and assesses the strengths and weaknesses of the statistical approaches used to draw conclusions and make clinical decisions from these data. We review recent innovations in missing values analysis (MVA), a relatively new branch of statistics, as applied to clinical TBI data. Our discussion focuses on studies from the International Traumatic Brain Injury Research (InTBIR) initiative project: Transforming Research and Clinical Knowledge in TBI (TRACK-TBI), Collaborative Research on Acute TBI in Intensive Care Medicine in Europe (CREACTIVE), and Approaches and Decisions in Acute Pediatric TBI Trial (ADAPT). In addition, using data from the TRACK-TBI pilot study (n = 586) and the completed clinical trial assessing valproate (VPA) for the treatment of post-traumatic epilepsy (n = 379) we present real-world examples of typical missing data patterns and the application of statistical techniques to mitigate the impact of missing data in order to draw sound conclusions from ongoing clinical studies.

Neuroimaging of individual differences: A latent variable modeling perspective

Neuroimaging data is being increasingly utilized to address questions of individual difference. When examined with task-related fMRI (t-fMRI), individual differences are typically investigated via correlations between the BOLD activation signal at every voxel and a particular behavioral measure. This can be problematic because: 1) correlational designs require evaluation of t-fMRI psychometric properties, yet these are not well understood; and 2) bivariate correlations are severely limited in modeling the complexities of brain-behavior relationships. Analytic tools from psychometric theory such as latent variable modeling (e.g., structural equation modeling) can help simultaneously address both concerns. This review explores the advantages gained from integrating psychometric theory and methods with cognitive neuroscience for the assessment and interpretation of individual differences. The first section provides background on classic and modern psychometric theories and analytics. The second section details current approaches to t-fMRI individual difference analyses and their psychometric limitations. The last section uses data from the Human Connectome Project to provide illustrative examples of how t-fMRI individual differences research can benefit by utilizing latent variable models.

Comparing Plasma Phospho Tau, Total Tau, and Phospho Tau-Total Tau Ratio as Acute and Chronic Traumatic Brain Injury Biomarkers

Importance

Annually in the United States, at least 3.5 million people seek medical attention for traumatic brain injury (TBI). The development of therapies for TBI is limited by the absence of diagnostic and prognostic biomarkers. Microtubule-associated protein tau is an axonal phosphoprotein. To date, the presence of the hypophosphorylated tau protein (P-tau) in plasma from patients with acute TBI and chronic TBI has not been investigated.

Objective

To examine the associations between plasma P-tau and total-tau (T-tau) levels and injury presence, severity, type of pathoanatomic lesion (neuroimaging), and patient outcomes in acute and chronic TBI.

Design, Setting, and Participants

In the TRACK-TBI Pilot study, plasma was collected at a single time point from 196 patients with acute TBI admitted to 3 level I trauma centers (<24 hours after injury) and 21 patients with TBI admitted to inpatient rehabilitation units (mean [SD], 176.4 [44.5] days after injury). Control samples were purchased from a commercial vendor. The TRACK-TBI Pilot study was conducted from April 1, 2010, to June 30, 2012. Data analysis for the current investigation was performed from August 1, 2015, to March 13, 2017.

Main Outcomes and Measures

Plasma samples were assayed for P-tau (using an antibody that specifically recognizes phosphothreonine-231) and T-tau using ultra-high sensitivity laser-based immunoassay multi-arrayed fiberoptics conjugated with rolling circle amplification.

Results

In the 217 patients with TBI, 161 (74.2%) were men; mean (SD) age was 42.5 (18.1) years. The P-tau and T-tau levels and P-tau-T-tau ratio in patients with acute TBI were higher than those in healthy controls. Receiver operating characteristic analysis for the 3 tau indices demonstrated accuracy with area under the curve (AUC) of 1.000, 0.916, and 1.000, respectively, for discriminating mild TBI (Glasgow Coma Scale [GCS] score, 13-15, n = 162) from healthy controls. The P-tau level and P-tau-T-tau ratio were higher in individuals with more severe TBI (GCS, ≤12 vs 13-15). The P-tau level and P-tau-T-tau ratio outperformed the T-tau level in distinguishing cranial computed tomography-positive from -negative cases (AUC = 0.921, 0.923, and 0.646, respectively). Acute P-tau levels and P-tau-T-tau ratio weakly distinguished patients with TBI who had good outcomes (Glasgow Outcome Scale-Extended GOS-E, 7-8) (AUC = 0.663 and 0.658, respectively) and identified those with poor outcomes (GOS-E, ≤4 vs >4) (AUC = 0.771 and 0.777, respectively). Plasma samples from patients with chronic TBI also showed elevated P-tau levels and a P-tau-T-tau ratio significantly higher than that of healthy controls, with both P-tau indices strongly discriminating patients with chronic TBI from healthy controls (AUC = 1.000 and 0.963, respectively).

Conclusions and Relevance

Plasma P-tau levels and P-tau-T-tau ratio outperformed T-tau level as diagnostic and prognostic biomarkers for acute TBI. Compared with T-tau levels alone, P-tau levels and P-tau-T-tau ratios show more robust and sustained elevations among patients with chronic TBI.

The Role of Psychometrics in Individual Differences Research in Cognition: A Case Study of the AX-CPT

Investigating individual differences in cognition requires addressing questions not often thought about in standard experimental designs, especially regarding the psychometric properties of the task. Using the AX-CPT cognitive control task as a case study example, we address four concerns that one may encounter when researching the topic of individual differences in cognition. First, we demonstrate the importance of variability in task scores, which in turn directly impacts reliability, particularly when comparing correlations in different populations. Second, we demonstrate the importance of variability and reliability for evaluating potential failures to replicate predicted correlations, even within the same population. Third, we demonstrate how researchers can turn to evaluating psychometric properties as a way of evaluating the feasibility of utilizing the task in new settings (e.g., online administration). Lastly, we show how the examination of psychometric properties can help researchers make informed decisions when designing a study, such as determining the appropriate number of trials for a task.

Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis

Background

Traumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge.

Methods and findings

The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2).

Conclusions

TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust method for patient stratification and treatment planning targeting identified biomarkers in future clinical trials in TBI patients.

Trial Registration

ClinicalTrials.gov Identifier NCT01565551

Screening for Post-Traumatic Stress Disorder in a Civilian Emergency Department Population with Traumatic Brain Injury

Post-traumatic stress disorder (PTSD) is a condition associated with traumatic brain injury (TBI). While the importance of PTSD and TBI among military personnel is widely recognized, there is less awareness of PTSD associated with civilian TBI. We examined the incidence and factors associated with PTSD 6 months post-injury in a civilian emergency department population using measures from the National Institute of Neurological Disorders and Stroke TBI Common Data Elements Outcome Battery. Participants with mild TBI (mTBI) from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot study with complete 6-month outcome batteries (n = 280) were analyzed. Screening for PTSD symptoms was conducted using the PTSD Checklist-Civilian Version. Descriptive measures are summarized and predictors for PTSD were examined using logistic regression. Incidence of screening positive for PTSD was 26.8% at 6 months following mTBI. Screening positive for PTSD was significantly associated with concurrent functional disability, post-concussive and psychiatric symptomatology, decreased satisfaction with life, and decreased performance in visual processing and mental flexibility. Multi-variable regression showed injury mechanism of assault (odds ratio [OR] 3.59; 95% confidence interval [CI] 1.69-7.63; p = 0.001) and prior psychiatric history (OR 2.56; 95% CI 1.42-4.61; p = 0.002) remained significant predictors of screening positive for PTSD, while education (per year OR 0.88; 95% CI 0.79-0.98; p = 0.021) was associated with decreased odds of PTSD. Standardized data collection and review of pre-injury education, psychiatric history, and injury mechanism during initial hospital presentation can aid in identifying patients with mTBI at risk for developing PTSD symptoms who may benefit from closer follow-up after initial injury care.

Plasma Anti-Glial Fibrillary Acidic Protein Autoantibody Levels during the Acute and Chronic Phases of Traumatic Brain Injury: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot Study

We described recently a subacute serum autoantibody response toward glial fibrillary acidic protein (GFAP) and its breakdown products 5-10 days after severe traumatic brain injury (TBI). Here, we expanded our anti-GFAP autoantibody (AutoAb[GFAP]) investigation to the multicenter observational study Transforming Research and Clinical Knowledge in TBI Pilot (TRACK-TBI Pilot) to cover the full spectrum of TBI (Glasgow Coma Scale 3-15) by using acute (<24 h) plasma samples from 196 patients with acute TBI admitted to three Level I trauma centers, and a second cohort of 21 participants with chronic TBI admitted to inpatient TBI rehabilitation. We find that acute patients self-reporting previous TBI with loss of consciousness (LOC) (n = 43) had higher day 1 AutoAb[GFAP] (mean ± standard error: 9.11 ± 1.42; n = 43) than healthy controls (2.90 ± 0.92; n = 16; p = 0.032) and acute patients reporting no previous TBI (2.97 ± 0.37; n = 106; p < 0.001), but not acute patients reporting previous TBI without LOC (8.01 ± 1.80; n = 47; p = 0.906). These data suggest that while exposure to TBI may trigger the AutoAb[GFAP] response, circulating antibodies are elevated specifically in acute TBI patients with a history of TBI. AutoAb[GFAP] levels for participants with chronic TBI (average post-TBI time 176 days or 6.21 months) were also significantly higher (15.08 ± 2.82; n = 21) than healthy controls (p < 0.001). These data suggest a persistent upregulation of the autoimmune response to specific brain antigen(s) in the subacute to chronic phase after TBI, as well as after repeated TBI insults. Hence, AutoAb[GFAP] may be a sensitive assay to study the dynamic interactions between post-injury brain and patient-specific autoimmune responses across acute and chronic settings after TBI.

Association of a common genetic variant within ANKK1 with six-month cognitive performance after traumatic brain injury

Genetic association analyses suggest that certain common single nucleotide polymorphisms (SNPs) may adversely impact recovery from traumatic brain injury (TBI). Delineating their causal relationship may aid in development of novel interventions and in identifying patients likely to respond to targeted therapies. We examined the influence of the (C/T) SNP rs1800497 of ANKK1 on post-TBI outcome using data from two prospective multicenter studies: the Citicoline Brain Injury Treatment (COBRIT) trial and Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot). We included patients with ANKK1 genotyping results and cognitive outcomes at six months post-TBI (n = 492: COBRIT n = 272, TRACK-TBI Pilot n = 220). Using the California Verbal Learning Test Second Edition (CVLT-II) Trial 1-5 Standard Score, we found a dose-dependent effect for the T allele, with T/T homozygotes scoring lowest on the CVLT-II Trial 1-5 Standard Score (T/T 45.1, C/T 51.1, C/C 52.1, ANOVA, p = 0.008). Post hoc testing with multiple comparison-correction indicated that T/T patients performed significantly worse than C/T and C/C patients. Similar effects were observed in a test of non-verbal processing (Wechsler Adult Intelligence Scale, Processing Speed Index). Our findings extend those of previous studies reporting a negative relationship of the ANKK1 T allele with cognitive performance after TBI. In this study, we demonstrate the value of pooling shared clinical, biomarker, and outcome variables from two large datasets applying the NIH TBI Common Data Elements. The results have implications for future multicenter investigations to further elucidate the role of ANKK1 in post-TBI outcome.

Diffusion tensor imaging for outcome prediction in mild traumatic brain injury: a TRACK-TBI study

We evaluated 3T diffusion tensor imaging (DTI) for white matter injury in 76 adult mild traumatic brain injury (mTBI) patients at the semiacute stage (11.2±3.3 days), employing both whole-brain voxel-wise and region-of-interest (ROI) approaches. The subgroup of 32 patients with any traumatic intracranial lesion on either day-of-injury computed tomography (CT) or semiacute magnetic resonance imaging (MRI) demonstrated reduced fractional anisotropy (FA) in numerous white matter tracts, compared to 50 control subjects. In contrast, 44 CT/MRI-negative mTBI patients demonstrated no significant difference in any DTI parameter, compared to controls. To determine the clinical relevance of DTI, we evaluated correlations between 3- and 6-month outcome and imaging, demographic/socioeconomic, and clinical predictors. Statistically significant univariable predictors of 3-month Glasgow Outcome Scale-Extended (GOS-E) included MRI evidence for contusion (odds ratio [OR] 4.9 per unit decrease in GOS-E; p=0.01), ≥1 ROI with severely reduced FA (OR, 3.9; p=0.005), neuropsychiatric history (OR, 3.3; p=0.02), age (OR, 1.07/year; p=0.002), and years of education (OR, 0.79/year; p=0.01). Significant predictors of 6-month GOS-E included ≥1 ROI with severely reduced FA (OR, 2.7; p=0.048), neuropsychiatric history (OR, 3.7; p=0.01), and years of education (OR, 0.82/year; p=0.03). For the subset of 37 patients lacking neuropsychiatric and substance abuse history, MRI surpassed all other predictors for both 3- and 6-month outcome prediction. This is the first study to compare DTI in individual mTBI patients to conventional imaging, clinical, and demographic/socioeconomic characteristics for outcome prediction. DTI demonstrated utility in an inclusive group of patients with heterogeneous backgrounds, as well as in a subset of patients without neuropsychiatric or substance abuse history.

Transforming research and clinical knowledge in traumatic brain injury pilot: multicenter implementation of the common data elements for traumatic brain injury

Traumatic brain injury (TBI) is among the leading causes of death and disability worldwide, with enormous negative social and economic impacts. The heterogeneity of TBI combined with the lack of precise outcome measures have been central to the discouraging results from clinical trials. Current approaches to the characterization of disease severity and outcome have not changed in more than three decades. This prospective multicenter observational pilot study aimed to validate the feasibility of implementing the TBI Common Data Elements (TBI-CDEs). A total of 650 subjects who underwent computed tomography (CT) scans in the emergency department within 24 h of injury were enrolled at three level I trauma centers and one rehabilitation center. The TBI-CDE components collected included: 1) demographic, social and clinical data; 2) biospecimens from blood drawn for genetic and proteomic biomarker analyses; 3) neuroimaging studies at 2 weeks using 3T magnetic resonance imaging (MRI); and 4) outcome assessments at 3 and 6 months. We describe how the infrastructure was established for building data repositories for clinical data, plasma biomarkers, genetics, neuroimaging, and multidimensional outcome measures to create a high quality and accessible information commons for TBI research. Risk factors for poor follow-up, TBI-CDE limitations, and implementation strategies are described. Having demonstrated the feasibility of implementing the TBI-CDEs through successful recruitment and multidimensional data collection, we aim to expand to additional study sites. Furthermore, interested researchers will be provided early access to the Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) data set for collaborative opportunities to more precisely characterize TBI and improve the design of future clinical treatment trials. (ClinicalTrials.gov Identifier NCT01565551.).

Quantitative CT improves outcome prediction in acute traumatic brain injury

The admission noncontrast head computed tomography (CT) scan has been demonstrated to be one of several key early clinical and imaging features in the challenging problem of prediction of long-term outcome after acute traumatic brain injury (TBI). In this study, we employ two novel approaches to the problem of imaging classification and outcome prediction in acute TBI. First, we employ the novel technique of quantitative CT (qCT) image analysis to provide more objective, reproducible measures of the abnormal features of the admission head CT in acute TBI. We show that the incorporation of quantitative, rather than qualitative, CT features results in a significant improvement in prediction of the 6-month Extended Glasgow Outcome Scale (GOS-E) score over a wide spectrum of injury severity. Second, we employ principal components analysis (PCA) to demonstrate the interdependence of certain predictive variables. Relatively few prior studies of outcome prediction in acute TBI have used a multivariate approach that explicitly takes into account the potential covariance among clinical and CT predictive variables. We demonstrate that several predictors, including midline shift, cistern effacement, subdural hematoma volume, and Glasgow Coma Scale (GCS) score are related to one another. Rather than being independent features, their importance may be related to their status as surrogate measures of a more fundamental underlying clinical feature, such as the severity of intracranial mass effect. We believe that objective computational tools and data-driven analytical methods hold great promise for neurotrauma research, and may ultimately have a role in image analysis for clinical care.

Independent component analysis of DTI reveals multivariate microstructural correlations of white matter in the human brain

It has recently been demonstrated that specific patterns of correlation exist in diffusion tensor imaging (DTI) parameters across white matter tracts in the normal human brain. These microstructural correlations are thought to reflect phylogenetic and functional similarities between different axonal fiber pathways. However, this earlier work was limited in three major respects: (1) the analysis was restricted to only a dozen selected tracts; (2) the DTI measurements were averaged across whole tracts, whereas metrics such as fractional anisotropy (FA) are known to vary considerably within single tracts; and (3) a univariate measure of correlation was used. In this investigation, we perform an automated multivariate whole-brain voxel-based study of white matter FA correlations using independent component analysis (ICA) of tract-based spatial statistics computed from 3T DTI in 53 healthy adult volunteers. The resulting spatial maps of the independent components show voxels for which the FA values within each map co-vary across individuals. The strongest FA correlations were found in anatomically recognizable tracts and tract segments, either singly or in homologous pairs. Hence, ICA of DTI provides an automated unsupervised decomposition of the normal human brain into multiple separable microstructurally correlated white matter regions, many of which correspond to anatomically familiar classes of white matter pathways. Further research is needed to determine whether whole-brain ICA of DTI represents a novel alternative to tractography for feature extraction in studying the normal microstructure of human white matter as well as the abnormal white matter microstructure found in neurological and psychiatric disorders.

Microstructural correlations of white matter tracts in the human brain

The purpose of this study is to investigate whether specific patterns of correlation exist in diffusion tensor imaging (DTI) parameters across different white matter tracts in the normal human brain, and whether the relative strengths of these putative microstructural correlations might reflect phylogenetic and functional similarities between tracts. We performed quantitative DTI fiber tracking on 44 healthy adult volunteers to obtain tract-based measures of mean diffusivity (MD), fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) from four homologous pairs of neocortical association pathways (arcuate fasciculi, inferior fronto-occipital fasciculi, inferior longitudinal fasciculi, and uncinate fasciculi bilaterally), a homologous pair of limbic association pathways (left and right dorsal cingulum bundles), and a homologous pair of cortical-subcortical projection pathways (left and right corticospinal tracts). From the resulting inter-tract correlation matrices, we show that there are statistically significant correlations of DTI parameters between tracts, and that there are statistically significant variations among these inter-tract correlations. Furthermore, we observe that many, but by no means all, of the strongest correlations are between homologous tracts in the left and right hemispheres. Even among homologous pairs of tracts, there are wide variations in the degree of coupling. Finally, we generate a data-driven hierarchical clustering of the fiber pathways based on pairwise FA correlations to demonstrate that the neocortical association pathways tend to group separately from the limbic pathways at trend-level statistical significance, and that the projection pathways of the left and right corticospinal tracts comprise the most distant outgroup with high confidence (p<0.01). Hence, specific patterns of microstructural correlation exist between tracts and may reflect phylogenetic and functional similarities between tracts. The study of these microstructural relationships between white matter pathways might aid research on the genetic basis and on the behavioral effects of axonal connectivity, as well as provide a revealing new perspective with which to investigate neurological and psychiatric disorders.

Effect of yeast culture on in vitro fermentation of a high-concentrate or high-fiber diet using equine fecal inoculum in a Daisy II incubator

Two experiments were conducted to evaluate the use of a closed system, fermentation apparatus (Daisy II incubator) and determine the effects of a yeast culture (YC) preparation (Saccharomyces cerevisiae) on in vitro microbial populations, diet digestion, and fermentation patterns in horses. In Exp. 1, 4 mature horses were fed a pelleted concentrate and alfalfa cubes in a 50:50 (%, as-fed) ratio. Fecal samples were taken from each horse to form the inoculum and placed in 4 separate incubation vessels. Twenty nylon bags (10 with 0.25 g and 10 with 0.50 g of the total mixed diet) were placed in each vessel, and in vitro fermentation was carried out for 48 h to determine DM, NDF, and ADF digestibility. In Exp. 2, fecal samples were taken from 4 mature horses consuming either a high-concentrate (HC) or high-fiber (HF) diet. Filter bags containing the HC or HF diet were added to the 4 incubation vessels along with their respective inoculums. Yeast culture was added to 2 of the vessels containing the HC or HF diet, whereas the other 2 vessels served as controls. Vessels were incubated as in Exp. 1 with samples taken at 24 and 48 h. Filter bags were used to determine DM, NDF, ADF, and OM digestibility, whereas vessel fluid was analyzed for lactate, ammonia, VFA, and microbial concentrations. Results of Exp. 1 indicated that DM, NDF, and ADF digestibility were greater (P < 0.05), whereas the corresponding CV was lower (P < 0.05) for the 0.25- vs. the 0.50-g sample size. In Exp. 2, YC tended (P = 0.10) to decrease ammonia concentrations in the HF diet and increased (P < 0.05) acetate production in the HC diet when compared with the control. There were no effects of YC on pH, lactate, or the measured microbial populations, as well as DM, NDF, or ADF digestibility. The results did, however, show that in vitro and in vivo DM digestibility estimates were similar within a diet. Data from Exp. 1 indicated that the 0.25-g sample size provides a more accurate estimate of DM digestibility with less variation. Although YC had little, if any, effect in Exp. 2, the results indicated that the Daisy II incubator does provide valid estimates of total tract DM digestibility in the horse. These data provide further evidence that this process would be an effective and practical means of approximating the digestibility of diets with varying concentrate to forage ratios.

A facet approach to extending the normative component of the theory of reasoned action

Using facet theory, this study addresses the weak explanatory power of normative influence in theories of reasoned action or planned behaviour. A broad normative construct is hypothesized as being characterized by two facets--social unit and behavioural modality--each of which is examined in relation to recreational drug use. A questionnaire was developed from the facets and administered to undergraduate students. Data (N = 181) were analysed using Smallest Space Analysis (SSA). The results suggest that the facets provide an adequate description of the normative construct and that personal and social normative beliefs, behavioural norms and behavioural intentions can be distinguished empirically. The results also lend partial support to Ajzen's (1988; Ajzen & Fishbein, 1977) principle of compatibility. Implications for how social influence is operationalized and conceptualized are also discussed.

Antisense oligonucleotides as research tools

The use of antisense oligonucleotides as both research tools and therapeutic molecules has emerged as a powerful alternative to small molecule inhibitors. Antisense oligonucleotides are short pieces of chemically modified DNA designed to hybridize to specific mRNA sequences present in the target gene. The oligonucleotide interaction with the targeted mRNA can lead to inhibition in the translation of the protein encoded by the targeted transcript through a variety of reasonably well-characterized mechanisms (1-3).

Intercellular adhesion molecule-1 suppression in skin by topical delivery of anti-sense oligonucleotides

We topically applied 20 nucleotide phosphorothioate intercellular adhesion molecule-1 anti-sense oligodeoxynucleotide in a cream formulation. It effectively inhibited tumor necrosis factor-alpha-induced expression of intercellular adhesion molecule-1 in human skin transplanted on severe compromised immunodeficient mice. The effects were concentration dependent, sequence specific, and resulted from reduction of intercellular adhesion molecule-1 mRNA levels in the skin. Intravenous administration of the drug did not show pharmacologic effects, probably due to insufficient drug concentrations in skin. Topical delivery, however, produced a rapid and a significantly higher accumulation of oligodeoxynucleotide in the epidermis and dermis. The results strongly suggest that topically applied anti-sense oligonucleotides can be delivered to target sites in the skin and may be of considerable value in the treatment of psoriasis and other inflammatory skin disorders.

Inhibition of antigen-induced eosinophilia and late phase airway hyperresponsiveness by an IL-5 antisense oligonucleotide in mouse models of asthma

Chronic airway eosinophilia is associated with allergic asthma and is mediated in part by secretion of IL-5 from allergen-specific Th2 lymphocytes. IL-5 is a known maturation and antiapoptotic factor for eosinophils and stimulates release of nascent eosinophils from bone marrow into the peripheral circulation. An antisense oligonucleotide found to specifically inhibit IL-5 expression in vitro was observed to significantly reduce experimentally induced eosinophilia in vivo, in both the murine OVA lung challenge and allergic peritonitis models. Intravenous administration resulted in sequence-dependent inhibition of eosinophilia coincident with reduction of IL-5 protein levels, supporting an antisense mechanism of action. Potent suppression of lung eosinophilia was observed up to 17 days after cessation of oligonucleotide dosing, indicating achievement of prolonged protection with this strategy. Furthermore, sequence-specific, antisense oligonucleotide-mediated inhibition of Ag-mediated late phase airway hyperresponsiveness was also observed. These data underscore the potential utility of an antisense approach targeting IL-5 for the treatment of asthma and eosinophilic diseases.

Pharmacology of antisense oligonucleotide inhibitors of protein expression

The dramatic increase in recent years of both the amount and rate of accumulation of novel genomic sequence information has generated enormous opportunities for the development of new classes of drugs. For these opportunities to be fully capitalized upon, investigators must choose molecular targets for drug development that are likely to yield attractive therapeutic profiles. This will require rapid and effective determination of gene functions in multiple cellular settings. The development of antisense oligonucleotides as specific inhibitors of gene expression should allow such determination of gene function. In addition, the antisense oligonucleotides themselves will likely prove useful as drugs. In this review, we discuss some of the issues surrounding the use of antisense oligonucleotides as research tools to help elucidate gene function, and highlight some of the approaches that can be taken to generate and use effective antisense reagents.

In vivo distribution and metabolism of a phosphorothioate oligonucleotide within rat liver after intravenous administration

In the rat, the liver represents a major site of phosphorothioate oligodeoxynucleotide deposition after i.v. administration. For this reason, we examined the intracellular fate of ISIS 1082, a 21-base heterosequence phosphorothioate oligodeoxynucleotide, isolated from parenchymal and nonparenchymal cell types after systemic dosing using established perfusion and separation techniques followed by CGE. Isolated cells were further fractionated into nuclear, cytosolic and membrane constituents to assess the intracellular localization, distribution and metabolic profiles as a function of time and dose. After a 10-mg/kg i.v. bolus, intracellular drug levels where maximal after 8 hr and diminished significantly thereafter, suggesting an active efflux mechanism or metabolism. Nonparenchymal (i.e., Kupffer and endothelial) cells contained approximately 80% of the total organ cellular dose, and this was equivalently distributed between the two cell types, while the remaining 20% was associated with hepatocytes. Nonparenchymal cells contained abundant nuclear, cytosolic and membrane drug levels over a wide dose range. In contrast, at doses of less than 25 mg/kg, hepatocytes contained significantly less drug with no detectable nuclear-association. Doses at or above 25 mg/kg appeared to saturate nonparenchymal cell types, whereas hepatocytes continued to accumulate drug in all cellular compartments, including the nucleus. Our results suggest that although pharmacokinetic parameters vary as a function of hepatic cell type, significant intracellular delivery can be readily achieved in the liver after systemic administration.

Role and function within managed care organizations: opportunities for nurse managers

Health care systems are facing rapid changes, moving from a fee-for-service environment to managed care. These changes are impacting nursing, eliminating current jobs and creating new opportunities in the field of managed care. Nurses must take a critical look at their current positions and determine what their contributions will be to improving the system of care. It is imperative that nurses move to leadership positions in managed care to represent the needs of patients and providers at the boardroom table. The purpose of this article is to give an insider's view of traditional and nontraditional roles for nurses within managed care organizations, and to challenge nurses to seize the opportunity to participate in designing the health care delivery system of the future.

New skills sets needed to navigate managed care

Nurse managers in the late 1990s and the 21st century may find themselves working for a managed care organization, and certainly will find themselves employed in a managed health care environment. The roles and opportunities are many for managers who have the right combination of skills and knowledge. Understanding managed care language and strategies in synergy, with a creative leadership approach, enables nurse managers to move successfully from acute care to the new world now unfolding.

Surface-relief diffraction gratings recorded by multiple-beam coherent phase exposure

Surface-relief hexagonal-array diffraction gratings have been produced by three-beam coherent exposure. Collimated light was used in an attempt to produce a uniform relief profile over the total area of a 7.6-cm plate coated with a positive photoresist. The resulting gratings were reproduced in nickel by an electroforming process and analyzed by atomic force microscopy. The topography of the gratings was found to be that predicted by theory. The results obtained show that the gratings were of uniform profile over their total area.

Long-Term History of Chesapeake Bay Anoxia

Stratigraphic records from four sediment cores collected along a transect across the Chesapeake Bay near the mouth of the Choptank River were used to reconstruct a 2000-year history of anoxia and eutrophication in the Chesapeake Bay. Variations in pollen, diatoms, concentration of organic carbon, nitrogen, sulfur, acid-soluble iron, and an estimate of the degree of pyritization of iron indicate that sedimentation rates, anoxic conditions and eutrophication have increased in the Chesapeake Bay since the time of European settlement.

Siderophore electrochemistry: relation to intracellular iron release mechanism

Previous studies have shown that there is a major difference between the iron release mechanism of enterobactin, a catechol-based siderophore, and that of the hydroxamate-based siderophores such as ferrichrome. For ferric enterobactin there is an esterase that hydrolyzes the ligand during iron release. In contrast, iron is released by the hydroxamate-based siderophores and the ligands are reused in subsequent iron transport. It has been suggested that release of iron by hydroxamates occurs by reduction to the ferrous complex, a process that does not occur for ferric enterobactin. Cyclic voltammograms of ferrichrome A and ferrioxamine B exhibit reversible one-electron waves with pH-independent formal potentials (Ef-vs. the normal hydrogen electrode) -446 and -454 mV, respectively, within the range of physiological reductants. Ferric enterobactin also shows a reversible one-electron wave (at pH greater than 10) with Ef = -986 mV vs. the normal hydrogen electrode. From the pH dependence of this potential we estimate a reduction potential of -750 mV at pH 7. In sharp contrast to the value for the ferric hydroxamates, this value is well below the range of physiological reducing agents. The results demonstrate that the observed hydrolysis of enterobactin is a necessary prerequisite to in vivo release of iron from the siderophore via ferric ion reduction.