Glucose metabolism and radiodensity of abdominal adipose tissue: A 5-year longitudinal study in a large PET cohort.

OBJECTIVE: 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) allows noninvasive assessment of glucose metabolism and radiodensity in visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). We aimed to address the effects of ageing and metabolic factors on abdominal adipose tissue. DESIGN, PATIENTS AND MEASUREMENTS: We retrospectively analyzed data from 435 healthy men (mean 42.8 years) who underwent a health check-up programme twice, at baseline and the 5-year follow-up. The mean standardized uptake value (SUV) was measured using SAT and VAT and divided by the liver SUV. The mean Hounsfield units (HU) of the SAT and VAT were measured from the CT scans. The effects of clinical variable clusters on SUVR were investigated using Bayesian hierarchical modelling; metabolic cluster (BMI, waist-to-hip ratio, fat percentage, muscle percentage*-1, HOMA-IR), blood pressure (systolic, diastolic), glucose (fasting plasma glucose level, HbA1c) and C-reactive protein. RESULTS: All the clinical variables changed during the 5-year follow-up period. The SUVR and HU of the VAT increased during follow-up; however, those of the SAT did not change. SUVR and HU were positively correlated with both VAT and SAT. SAT and VAT SUVR were negatively associated with metabolic clusters. CONCLUSIONS: Ageing led to increased glucose metabolism and radiodensity in VAT, but not in SAT. VAT may reflect the ageing process more directly than SAT. Glucose metabolism was higher and radiodensity was lower in VAT than in SAT, probably owing to differences in gene expression and lipid density. Both glucose metabolism and radiodensity of VAT and SAT reflect metabolic status.

Everything, altogether, all at once: Addressing data challenges when measuring speech intelligibility through entropy scores.

When investigating unobservable, complex traits, data collection and aggregation processes can introduce distinctive features to the data such as boundedness, measurement error, clustering, outliers, and heteroscedasticity. Failure to collectively address these features can result in statistical challenges that prevent the investigation of hypotheses regarding these traits. This study aimed to demonstrate the efficacy of the Bayesian beta-proportion generalized linear latent and mixed model (beta-proportion GLLAMM) (Rabe-Hesketh et al., Psychometrika, 69(2), 167-90, 2004a, Journal of Econometrics, 128(2), 301-23, 2004c, 2004b; Skrondal and Rabe-Hesketh 2004) in handling data features when exploring research hypotheses concerning speech intelligibility. To achieve this objective, the study reexamined data from transcriptions of spontaneous speech samples initially collected by Boonen et al. (Journal of Child Language, 50(1), 78-103, 2023). The data were aggregated into entropy scores. The research compared the prediction accuracy of the beta-proportion GLLAMM with the normal linear mixed model (LMM) (Holmes et al., 2019) and investigated its capacity to estimate a latent intelligibility from entropy scores. The study also illustrated how hypotheses concerning the impact of speaker-related factors on intelligibility can be explored with the proposed model. The beta-proportion GLLAMM was not free of challenges; its implementation required formulating assumptions about the data-generating process and knowledge of probabilistic programming languages, both central to Bayesian methods. Nevertheless, results indicated the superiority of the model in predicting empirical phenomena over the normal LMM, and its ability to quantify a latent potential intelligibility. Additionally, the proposed model facilitated the exploration of hypotheses concerning speaker-related factors and intelligibility. Ultimately, this research has implications for researchers and data analysts interested in quantitatively measuring intricate, unobservable constructs while accurately predicting the empirical phenomena.

Alterations in type 2 dopamine receptors across neuropsychiatric conditions: A large-scale PET cohort.

PURPOSE: Aberrant dopaminergic function is linked with motor, psychotic, and affective symptoms, but studies have typically compared a single patient group with healthy controls. METHODS: Here, we investigated the variation in striatal (caudate nucleus, nucleus accumbens, and putamen) and thalamic type 2 dopamine receptor (D2R) availability using [11C]raclopride positron emission tomography (PET) data from a large sample of 437 humans including healthy controls, and subjects with Parkinson's disease (PD), antipsychotic-naïve schizophrenia, severe violent behavior, pathological gambling, depression, and overweight. We analyzed regional group differences in D2R availability. We also analyzed the interregional correlation in D2R availability within each group. RESULTS: Subjects with PD showed the clearest decline in D2R availability. Overall, the groups showed high interregional correlation in D2R availability, while this pattern was weaker in violent offenders. Subjects with schizophrenia, pathological gambling, depression, or overweight did not show clear changes in either the regional receptor availability or the interregional correlation. CONCLUSION: We conclude that the dopaminergic changes in neuropsychiatric conditions might not only affect the overall receptor availability but also how coupled regions are across people. The region-specific receptor availability more profoundly links to the motor symptoms, while the between-region coupling might be disrupted in violence.