Examining the relationship between anxiety and regional brain volumes in the National Alzheimer's Coordinating Center uniform, imaging, and biomarker datasets.

Anxiety has been associated with a greater risk of Alzheimer's disease (AD). Existing research has identified structural differences in regional brain tissue in participants with anxiety, but results have been inconsistent. We sought to determine the association between anxiety and regional brain volumes, and the moderation effect of APOE ε4. Using data from participants in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set, with complete imaging (MRI) and biomarker data (n = 1533), multiple linear regression estimated the adjusted effect of anxiety on 30 structural MRI regions. The moderation effect of APOE ε4 on the relation between structural MRI regions and anxiety was assessed as was the moderation effect of cognitive status. False discovery rate was used to adjust for multiple comparisons. After controlling for intracranial volume, age, sex, years of education, race, Hispanic ethnicity, and cognitive status, seven MRI regions demonstrated lower volumes among participants with anxiety: total cerebrum gray matter volume, right hippocampus volume, hippocampal volume (total), right and left frontal lobe cortical gray matter volume, and right and total temporal lobe cortical gray matter volume. Findings suggest that anxiety is associated with significant atrophy in multiple brain regions, with corresponding ventricular enlargement. Future research should investigate if anxiety-related changes to brain morphology contribute to greater AD risk.

Absence of relationship between serum cortisol and critical illness in premature infants.

BACKGROUND: Inadequate cortisol production in response to critical illness in extremely preterm infants may exacerbate poor outcomes. Despite commonly measuring cortisol concentration and administering hydrocortisone for presumed adrenal insufficiency, the relationship between serum cortisol concentration and illness severity remains unclear in this unique population. OBJECTIVE: To determine the relationship between cortisol concentrations and illness severity as measured by the Score for Neonatal Acute Physiology II, neonatal Sequential Organ Failure Assessment and Vasoactive-Inotropic Score in premature infants. DESIGN/METHODS: This retrospective, single-center cohort study included preterm infants born <30 weeks gestational age admitted to a level IV neonatal intensive care unit (NICU) between June 2011 and July 2018, who had a serum cortisol obtained for clinical indications before 36 weeks PMA. Demographic data were collected on infants and mothers. Nine clinical variables were identified a priori that could potentially modify cortisol concentration including critical illness. Univariate and multivariable analyses determined the relationship between cortisol concentration and each of these variables. RESULTS: A total of 224 preterm infants with pretreatment serum cortisol concentration met criteria for inclusion. The median (IQR) gestational age at birth was 25 weeks (24, 26) and at cortisol measurement was 26 weeks (25, 28). The median cortisol was 13.3 ug/dL. Non-survivors had the highest values. Cortisol concentration did not correlate with any of the selected illness severity scores. CONCLUSIONS: Cortisol concentrations in extremely preterm infants did not correlate with illness severity regardless of gestational age. Further studies are needed to identify clinically useful mediators of adrenal dysfunction and to guide clinical management.

A Bayesian framework for the analysis of systems biology models of the brain.

Systems biology models are used to understand complex biological and physiological systems. Interpretation of these models is an important part of developing this understanding. These models are often fit to experimental data in order to understand how the system has produced various phenomena or behaviour that are seen in the data. In this paper, we have outlined a framework that can be used to perform Bayesian analysis of complex systems biology models. In particular, we have focussed on analysing a systems biology of the brain using both simulated and measured data. By using a combination of sensitivity analysis and approximate Bayesian computation, we have shown that it is possible to obtain distributions of parameters that can better guard against misinterpretation of results, as compared to a maximum likelihood estimate based approach. This is done through analysis of simulated and experimental data. NIRS measurements were simulated using the same simulated systemic input data for the model in a 'healthy' and 'impaired' state. By analysing both of these datasets, we show that different parameter spaces can be distinguished and compared between different physiological states or conditions. Finally, we analyse experimental data using the new Bayesian framework and the previous maximum likelihood estimate approach, showing that the Bayesian approach provides a more complete understanding of the parameter space.

Substance abuse attitudes and policies in US rehabilitation training programs: a comparison of 1985 and 2000.

OBJECTIVE: To assess and compare the attitudes, beliefs, and policies of physical medicine and rehabilitation (PM&R) training programs toward substance abuse and tobacco use over the last 15 years. DESIGN: A blinded questionnaire was sent to all US rehabilitation medicine training program directors. Results were compared with a survey conducted in 1985. SETTING: US PM&R residency training programs with inpatient rehabilitation training. PARTICIPANTS: Training directors or their designated agents. INTERVENTION: A 35-item questionnaire was mailed between November 1999 and April 2000 to the 81 US training programs identified by the American Board of Physical Medicine and Rehabilitation as having rehabilitation training programs with inpatient rehabilitation units. Responses were pooled by our Survey Research Center to preserve anonymity. Training programs that did not respond received additional mailings and telephone calls to improve the response rate. MAIN OUTCOME MEASURES: Chi-square analysis to assess changes in responses with time. RESULTS: Forty-six of the 79 (58%) eligible training programs responded (1 program had merged, 1 did not provide inpatient rehabilitation). Programs were located in cities ranging from less than 100,000 (n = 2) to greater than a million inhabitants (n = 18). Eighty percent (37/46) of the respondents were "concerned or very concerned" about their patients' alcohol and drug use, and 69% routinely assessed patients for alcohol and drug use compared with only 25% in 1985 (P <.00001). Almost all respondents (43/46) supported written guidelines to prohibit alcohol and drug use by patients in the rehabilitation unit. Eighty-three percent had a prohibition policy, and 72% had written guidelines. Both of those rates represent increases from the 1985 response rates of 65% and 45%, respectively. Ambivalence persisted about appropriate treatment programs for persons with disabilities: in 1985, 51% of the respondents agreed that a person with a disability could be treated appropriately in a substance abuse program designed for persons without a disability; in 2000, the percentage had increased to 64%. All respondents believed that tobacco use is an addiction, but only 25% of their units offered tobacco cessation services to patients on their rehabilitation unit. CONCLUSION: The survey results are encouraging. Since 1985, not only have substance abuse issues been recognized, but also systemic institutionalized approaches (eg, regular screening, written guidelines) have increased markedly. Tobacco is now uniformly accepted as an addiction, but screening and access to cessation programs are similar to that available for alcohol and drug treatment programs 15 years ago.