Perinatal neurosteroid levels influence GABAergic interneuron localization in adult rat prefrontal cortex

Neurosteroids are a class of steroids synthesized de novo in the brain, several of which are potent modulators of GABAA receptor function. In developing brain GABAA receptor, stimulation plays a trophic role. Cortical levels of the GABAergic neurosteroid 3α-hydroxy-5α-pregnan-20-one (3α,5α-THP) vary dramatically across development; during the second week of life, elevated levels of 3α,5α-THP are associated with decreased GABAA receptor function. To determine whether alteration of endogenous 3α,5α-THP levels during development alters GABAergic interneurons in prefrontal cortex (PFC) at maturity, rat pups were exposed to 3α,5α-THP (10 mg/kg) on postnatal day 1 (P1), P2, and P5. On P80, frontal cortex tissue was assayed for GABAergic cell localization (parvalbumin and calbindin immunoreactivity), agonist-dependent [3H] dizocilpine (MK-801) binding to NMDA receptors in cortical homogenates, muscimol-mediated 36Cl- influx into synaptoneurosomes, and 3α,5α-THP levels. The localization of parvalbumin-labeled cells was markedly altered; the ratio of cell number in the deep layers (V-VI) versus superficial layers (I-III) of adult PFC increased twofold in animals exposed to 3α,5α-THP on P1 or P5. Relative microtubule-associated protein-2 and calbindin immunoreactivity were not altered by perinatal 3α,5α-THP administration. Agonist-dependent [3H]MK-801 binding was decreased in PFC but not parietal cortex homogenates, whereas muscimolmediated 36Cl- influx and 3α,5α-THP levels were unchanged in frontal cortex of adult males exposed to 3α,5α-THP on P5. These data are consistent with a change in the distribution of a subset of interneurons in response to neurosteroid exposure and suggest that GABAergic neurosteroids are critical for normal development of GABAergic systems in the PFC

Outbreaks: Protecting Americans From Infectious Diseases 2015

Infectious diseases -- most of which are preventable -- disrupt the lives of millions of Americans each year. But the country does not sufficiently invest in basic protections that could help avoid significant numbers of outbreaks and save billions of dollars in unnecessary healthcare costs. U.S. investments in infectious disease prevention ebb and flow, where there is a major ramp up when a new eminent threat emerges, but then falls back when the problem seems contained.In the most recent example last year, the Ebola outbreak resulted in ephemeral attention and emergency supplemental funding to backfill gaps in the nation's ability to respond. But, lags in even emergency funding processes meant much of the support came too late to address immediate needs in states and in Africa. And the funding was not at a sufficient level to shore up ongoing gaps, leaving the United States still vulnerable for when the next emerging threat arises.Fighting infectious disease requires constant vigilance. Policies and resources must be in place to allow scientists and public health and medical experts to have the tools they need to: control ongoing outbreaks -- such as HIV/AIDS, antibiotic-resistant superbugs and foodborne illnesses; detect new or reemerging outbreaks -- such as Middle East Respiratory Syndrome Coronavirus (MERS-CoV), measles and avian flu; and monitor for potential bioterrorist threats -- such as anthrax or smallpox

Hippocampal shape and volume changes with antipsychotics in early stage psychotic illness

Progression of hippocampal shape and volume abnormalities has been described in psychotic disorders such as schizophrenia. However it is unclear how specific antipsychotic medications influence the development of hippocampal structure. We conducted a longitudinal, randomized, controlled, multisite, double-blind study involving 14 academic medical centers (United States 11, Canada 1, Netherlands 1, and England 1). 134 first-episode psychosis (receiving either haloperidol or olanzapine) patients and 51 healthy controls were treated and followed up for up to 104 weeks using magnetic resonance imaging and large-deformation high-dimensional brain mapping of the hippocampus. Changes in hippocampal volume and shape metrics (i.e., percentage of negative surface vertex slopes, and surface deformation) were evaluated. Mixed-models analysis did not show a significant group-by-time interaction for hippocampal volume. However, the cumulative distribution function of hippocampal surface vertex slopes showed a notable left shift with haloperidol treatment compared to olanzapine treatment and to controls. Olanzapine treatment was associated with a significantly lower percentage of large magnitude negative surface vertex slopes compared to haloperidol treatment (p=0.004). Surface deformation maps however did not localize any hippocampal regions that differentially contracted over time with olanzapine treatment, after FDR correction. These results indicate that surface analysis provides supplementary information to volumetry in detecting differential treatment effects of the hippocampus. Our results suggest that olanzapine is associated with less longitudinal hippocampal surface deformation than haloperidol, however the hippocampal regions affected appear to be variable across patients

Outbreaks: Protecting Americans From Infectious Diseases 2014

This report examines a range of infectious disease concerns. The report highlights a series of 10 indicators in each state that, taken collectively, offer a composite snapshot of strengths and vulnerabilities across the health system. These indicators help illustrate the types of policy fundamentals that are important to have in place not just to prevent the spread of disease in the first place but also to detect, diagnose and respond to outbreaks. In addition, the report examines key areas of concern in the nation's ability to prevent and control infectious diseases and offers recommendations for addressing these gaps. The Outbreaks report provides the public, policymakers and a broad and diverse set of groups involved in public health and the healthcare system with an objective, nonpartisan, independent analysis of the status of infectious disease policies; encourages greater transparency and accountability of the system; and recommends ways to assure the public health and healthcare systems meet today's needs and work across borders to accomplish their goals

Two-stage empirical likelihood for longitudinal neuroimaging data

Longitudinal imaging studies are essential to understanding the neural development of neuropsychiatric disorders, substance use disorders, and the normal brain. The main objective of this paper is to develop a two-stage adjusted exponentially tilted empirical likelihood (TETEL) for the spatial analysis of neuroimaging data from longitudinal studies. The TETEL method as a frequentist approach allows us to efficiently analyze longitudinal data without modeling temporal correlation and to classify different time-dependent covariate types. To account for spatial dependence, the TETEL method developed here specifically combines all the data in the closest neighborhood of each voxel (or pixel) on a 3-dimensional (3D) volume (or 2D surface) with appropriate weights to calculate adaptive parameter estimates and adaptive test statistics. Simulation studies are used to examine the finite sample performance of the adjusted exponential tilted likelihood ratio statistic and TETEL. We demonstrate the application of our statistical methods to the detection of the difference in the morphological changes of the hippocampus across time between schizophrenia patients and healthy subjects in a longitudinal schizophrenia study.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS480 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Factor Structure of the Barriers to Physical Activity Scale for Youth with Visual Impairments

Youth with visual impairments (VI) often experience unique barriers to physical activity (PA) compared to their sighted peers (Armstrong et al., 2018). A psychometrically sound scale for assessing barriers to PA for youth with VI is needed to facilitate research. The purpose of this paper was to confirm the ability of the previously identified three-factor structure of the Physical Activity Barriers Questionnaire for youth with Visual Impairments (PABQ-VI) to produce scores considered to be valid and reliable (Armstrong et al., 2020; Armstrong et al., 2018) that perform equally well across age, VI severity, and gender. Our results supported the three-factor structure and that the PABQ-VI produces scores considered valid and reliable. Mean, variance, and correlation differences were found in personal, social, and environmental barriers for age and VI severity, but not gender. Researchers can use the PABQ-VI to test and evaluate ways to reduce barriers for this population

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data

Results of phase 3 of the CATIE schizophrenia trial

Objective—The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study examined the comparative effectiveness of antipsychotic treatments for individuals with chronic schizophrenia. Patients who had discontinued antipsychotic treatment in phases 1 and 2 were eligible for phase 3, in which they selected one of nine antipsychotic regimens with the help of their study doctor. We describe the characteristics of the patients who selected each treatment option and their outcomes. Method—Two hundred and seventy patients entered phase 3. The open-label treatment options were monotherapy with oral aripiprazole, clozapine, olanzapine, perphenazine, quetiapine, risperidone, ziprasidone, long-acting injectable fluphenazine decanoate, or a combination of any two of these treatments. Results—Few patients selected fluphenazine decanoate (n=9) or perphenazine (n=4). Similar numbers selected each of the other options (range 33–41). Of the seven common choices, those who selected clozapine and combination antipsychotic treatment were the most symptomatic, and those who selected aripiprazole and ziprasidone had the highest body mass index. Symptoms improved for all groups, although the improvements were modest for the groups starting with relatively mild levels of symptoms. Side effect profiles of the medications varied considerably but medication discontinuations due to intolerability were rare (7% overall). Conclusions—Patients and their doctors made treatment selections based on clinical factors, including severity of symptoms, response to prior treatments, and physical health status. Fluphenazine decanoate was rarely used among those with evidence of treatment non-adherence and clozapine was underutilized for those with poor previous response. Combination antipsychotic treatment warrants further study

Adjusted Exponentially Tilted Likelihood with Applications to Brain Morphology

In this paper, we develop a nonparametric method, called adjusted exponentially tilted likelihood, and apply it to the analysis of morphometric measures. The adjusted exponential tilting estimator is shown to have the same first order asymptotic properties as that of the original exponentially tilted likelihood. The adjusted exponentially tilted likelihood ratio statistic is applied to test linear hypotheses of unknown parameters, such as the associations of brain measures (e.g., cortical and subcortical surfaces) with covariates of interest, such as age, gender, and gene. Simulation studies show that the adjusted exponential tilted likelihood ratio statistic performs as well as the t-test when the imaging data are symmetrically distributed, while it is superior when the imaging data have skewed distribution. We demonstrate the application of our new statistical methods to the detection of statistically significant differences in the morphology of the hippocampus between two schizophrenia groups and healthy subjects