History of early life adversity is associated with increased food addiction and sex-specific alterations in reward network connectivity in obesity.

Background:Neuroimaging studies have identified obesity-related differences in the brain's resting state activity. An imbalance between homeostatic and reward aspects of ingestive behaviour may contribute to obesity and food addiction. The interactions between early life adversity (ELA), the reward network and food addiction were investigated to identify obesity and sex-related differences, which may drive obesity and food addiction. Methods:Functional resting state magnetic resonance imaging was acquired in 186 participants (high body mass index [BMI]: ≥25: 53 women and 54 men; normal BMI: 18.50-24.99: 49 women and 30 men). Participants completed questionnaires to assess ELA (Early Traumatic Inventory) and food addiction (Yale Food Addiction Scale). A tripartite network analysis based on graph theory was used to investigate the interaction between ELA, brain connectivity and food addiction. Interactions were determined by computing Spearman rank correlations, thresholded at q < 0.05 corrected for multiple comparisons. Results:Participants with high BMI demonstrate an association between ELA and food addiction, with reward regions playing a role in this interaction. Among women with high BMI, increased ELA was associated with increased centrality of reward and emotion regulation regions. Men with high BMI showed associations between ELA and food addiction with somatosensory regions playing a role in this interaction. Conclusions:The findings suggest that ELA may alter brain networks, leading to increased vulnerability for food addiction and obesity later in life. These alterations are sex specific and involve brain regions influenced by dopaminergic or serotonergic signalling

A new accuracy measure based on bounded relative error for time series forecasting

Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising commonly used accuracy measures, a special review is made on the symmetric mean absolute percentage error. Moreover, a new accuracy measure called the Unscaled Mean Bounded Relative Absolute Error (UMBRAE), which combines the best features of various alternative measures, is proposed to address the common issues of existing measures. A comparative evaluation on the proposed and related measures has been made with both synthetic and real-world data. The results indicate that the proposed measure, with user selectable benchmark, performs as well as or better than other measures on selected criteria. Though it has been commonly accepted that there is no single best accuracy measure, we suggest that UMBRAE could be a good choice to evaluate forecasting methods, especially for cases where measures based on geometric mean of relative errors, such as the geometric mean relative absolute error, are preferred

Resting-state fMRI using passband balanced steady-state free precession

OBJECTIVE: Resting-state functional MRI (rsfMRI) has been increasingly used for understanding brain functional architecture. To date, most rsfMRI studies have exploited blood oxygenation level-dependent (BOLD) contrast using gradient-echo (GE) echo planar imaging (EPI), which can suffer from image distortion and signal dropout due to magnetic susceptibility and inherent long echo time. In this study, the feasibility of passband balanced steady-state free precession (bSSFP) imaging for distortion-free and high-resolution rsfMRI was investigated. METHODS: rsfMRI was performed in humans at 3 T and in rats at 7 T using bSSFP with short repetition time (TR = 4/2.5 ms respectively) in comparison with conventional GE-EPI. Resting-state networks (RSNs) were detected using independent component analysis. RESULTS AND SIGNIFICANCE: RSNs derived from bSSFP images were shown to be spatially and spectrally comparable to those derived from GE-EPI images with considerable intra- and inter-subject reproducibility. High-resolution bSSFP images corresponded well to the anatomical images, with RSNs exquisitely co-localized to the gray matter. Furthermore, RSNs at areas of severe susceptibility such as human anterior prefrontal cortex and rat piriform cortex were proved accessible. These findings demonstrated for the first time that passband bSSFP approach can be a promising alternative to GE-EPI for rsfMRI. It offers distortion-free and high-resolution RSNs and is potentially suited for high field studies.published_or_final_versio

Brain resting-state functional MRI connectivity: Morphological foundation and plasticity

postprin

Mitochondrial aminoacyl-tRNA synthetases trigger unique compensatory mechanisms in neurons

\ua9 The Author(s) 2023. Published by Oxford University Press. Mitochondrial aminoacyl-tRNA synthetase (mt-ARS) mutations cause severe, progressive, and often lethal diseases with highly heterogeneous and tissue-specific clinical manifestations. This study investigates the molecular mechanisms triggered by three different mt-ARS defects caused by biallelic mutations in AARS2, EARS2, and RARS2, using an in vitro model of human neuronal cells. We report distinct molecular mechanisms of mitochondrial dysfunction among the mt-ARS defects studied. Our findings highlight the ability of proliferating neuronal progenitor cells (iNPCs) to compensate for mitochondrial translation defects and maintain balanced levels of oxidative phosphorylation (OXPHOS) components, which becomes more challenging in mature neurons. Mutant iNPCs exhibit unique compensatory mechanisms, involving specific branches of the integrated stress response, which may be gene-specific or related to the severity of the mitochondrial translation defect. RNA sequencing revealed distinct transcriptomic profiles showing dysregulation of neuronal differentiation and protein translation. This study provides valuable insights into the tissue-specific compensatory mechanisms potentially underlying the phenotypes of patients with mt-ARS defects. Our novel in vitro model may more accurately represent the neurological presentation of patients and offer an improved platform for future investigations and therapeutic development

Semiautomated and automated algorithms for analysis of the carotid artery wall on computed tomography and sonography: a correlation study.

Objectives—The purpose of this study was to compare automated and semiautomated algorithms for analysis of carotid artery wall thickness and intima-media thickness on multidetector row computed tomographic (CT) angiography and sonography, respectively, and to study the correlation between them. Methods—Twenty consecutive patients underwent multidetector row CT angiographic and sonographic analysis of carotid arteries (mean age, 66 years; age range, 59–79 years). The intima-media thickness of the 40 carotid arteries was measured with novel and dedicated automated software analysis and by 4 observers who manually calculated the intima-media thickness. The carotid artery wall thickness was automatically estimated by using a specific algorithm and was also semiautomatically quantified. The correlation between groups was calculated by using the Pearson ρ statistic, and scatterplots were calculated. We evaluated intermethod agreement using Bland-Altman analysis. Results—By comparing automated carotid artery wall thickness, automated intima-media thickness, semiautomated carotid artery wall thickness, and semiautomated intima-media thickness analyses, a statistically significant association was found, with the highest values obtained for the association between semiautomated and thickness analyses(Pearson ρ = 0.9; 95% confidence interval, 0.82–0.95; P = 0.0001). The lowest values were obtained for the association between semiautomated intima-media thickness and automated carotid artery wall thickness analyses (Pearson ρ = 0.44; 95% confidence interval, 0.15–0.66; P = 0.0047). In the Bland-Altman analysis, the better results were obtained by comparing the semiautomated and automated algorithms for the study of intima-media thickness, with an interval of –16.1% to +43.6%. Conclusions—The results of this preliminary study showed that carotid artery wall thickness and intima-media thickness can be studied with automated software, although the CT analysis needs to be further improved

A randomized clinical trial of the immunogenicity of 7-valent pneumococcal conjugate vaccine compared to 23-valent polysaccharide vaccine in frail, hospitalized elderly

Background: Elderly people do not mount strong immune responses to vaccines. We compared 23-valent capsular polysaccharide (23vPPV) alone versus 7-valent conjugate (PCV7) vaccine followed by 23vPPV 6 months later in hospitalized elderly. Methods: Participants were randomized to receive 23vPPV or PCV7-23vPPV. Antibodies against serotypes 3, 4, 6A, 6B, 9V, 14, 18C, 19A, 19F, 23F were measured by enzyme-linked immunosorbent (ELISA) and opsonophagocytic (OPA) assays at baseline, 6 months and 12 months. Results: Of 312 recruited, between 40% and 72% of subjects had undetectable OPA titres at baseline. After one dose, PCV7 recipients had significantly higher responses to serotypes 9V (both assays) and 23F (OPA only), and 23vPPV recipients had significantly higher responses to serotype 3 (ELISA), 19F and 19A (OPA only). In subjects with undetectable OPA titres at baseline, a proportionately greater rise in OPA titre (P<0.01) was seen for all serotypes after both vaccines. The GMT ratio of OPA was significantly higher at 12 months in the PCV7-23vPPV group for serotypes 6A, 9V, 18C and 23F. OPA titre levels for these serotypes increased moderately after 6 months, whereas immunity waned in the 23vPPV only arm. Conclusion: We did not show overwhelming benefit of one vaccine over the other. Low baseline immunity does not preclude a robust immune response, reiterating the importance of vaccinating the frail elderly. A schedule of PCV7-23vPPV prevents waning of antibody, suggesting that both vaccines could be useful in the elderly. Follow up studies are needed to determine persistence of immunity. Trial Registration: The Australian Clinical Trials Registry ACTRN12607000387426 © 2014 MacIntyre et al

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein