Whole brain morphologic features improve the predictive accuracy of IDH status and VEGF expression levels in gliomas.

Glioma is a systemic disease that can induce micro and macro alternations of whole brain. Isocitrate dehydrogenase and vascular endothelial growth factor are proven prognostic markers and antiangiogenic therapy targets in glioma. The aim of this study was to determine the ability of whole brain morphologic features and radiomics to predict isocitrate dehydrogenase status and vascular endothelial growth factor expression levels. This study recruited 80 glioma patients with isocitrate dehydrogenase wildtype and high vascular endothelial growth factor expression levels, and 102 patients with isocitrate dehydrogenase mutation and low vascular endothelial growth factor expression levels. Virtual brain grafting, combined with Freesurfer, was used to compute morphologic features including cortical thickness, LGI, and subcortical volume in glioma patient. Radiomics features were extracted from multiregional tumor. Pycaret was used to construct the machine learning pipeline. Among the radiomics models, the whole tumor model achieved the best performance (accuracy 0.80, Area Under the Curve 0.86), while, after incorporating whole brain morphologic features, the model had a superior predictive performance (accuracy 0.82, Area Under the Curve 0.88). The features contributed most in predicting model including the right caudate volume, left middle temporal cortical thickness, first-order statistics, shape, and gray-level cooccurrence matrix. Pycaret, based on morphologic features, combined with radiomics, yielded highest accuracy in predicting isocitrate dehydrogenase mutation and vascular endothelial growth factor levels, indicating that morphologic abnormalities induced by glioma were associated with tumor biology.

Shared and differing functional connectivity abnormalities of the default mode network in mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease (AD) and mild cognitive impairment (MCI) both show abnormal resting-state functional connectivity (rsFC) of default mode network (DMN), but it is unclear to what extent these abnormalities are shared. Therefore, we performed a comprehensive meta-analysis, including 31 MCI studies and 20 AD studies. MCI patients, compared to controls, showed decreased within-DMN rsFC in bilateral medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC), precuneus/posterior cingulate cortex (PCC), right temporal lobes, and left angular gyrus and increased rsFC between DMN and left inferior temporal gyrus. AD patients, compared to controls, showed decreased rsFC within DMN in bilateral mPFC/ACC and precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC between DMN and right dorsolateral prefrontal cortex. Conjunction analysis showed shared decreased rsFC in mPFC/ACC and precuneus/PCC. Compared to MCI, AD had decreased rsFC in left precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC in right temporal lobes. MCI and AD share a decreased within-DMN rsFC likely underpinning episodic memory deficits and neuropsychiatric symptoms, but differ in DMN rsFC alterations likely related to impairments in other cognitive domains such as language, vision, and execution. This may throw light on neuropathological mechanisms in these two stages of dementia.

Association of insulin resistance with the accumulation of saturated intramyocellular lipid: A comparison with other fat stores.

It has been shown using proton magnetic resonance spectroscopy (1H MRS) that, in a group of females, whole-body insulin resistance was more closely related to accumulation of saturated intramyocellular lipid (IMCL) than to IMCL concentration alone. This has not been investigated in males. We investigated whether age- and body mass index-matched healthy males differ from the previously reported females in IMCL composition (measured as CH2:CH3) and IMCL concentration (measured as CH3), and in their associations with insulin resistance. We ask whether saturated IMCL accumulation is more strongly associated with insulin resistance than other ectopic and adipose tissue lipid pools and remains a significant predictor when these other pools are taken into account. In this group of males, who had similar overall insulin sensitivity to the females, IMCL was similar between sexes. The males demonstrated similar and even stronger associations of IMCL with insulin resistance, supporting the idea that a marker reflecting the accumulation of saturated IMCL is more strongly associated with whole-body insulin resistance than IMCL concentration alone. However, this marker ceased to be a significant predictor of whole-body insulin resistance after consideration of other lipid pools, which implies that this measure carries no more information in practice than the other predictors we found, such as intrahepatic lipid and visceral adipose tissue. As the marker of saturated IMCL accumulation appears to be related to these two predictors and has a much smaller dynamic range, this finding does not rule out a role for it in the pathogenesis of insulin resistance.

Exercise improves surrogate measures of liver histological response in metabolic dysfunction-associated steatotic liver disease.

BACKGROUND AND AIMS: Exercise is recommended for the management of metabolic dysfunction-associated steatotic liver disease (MASLD), yet effects on liver histology remain unknown, especially without significant weight loss. We aimed to examine changes in surrogate measures of liver histological response with exercise training. METHODS: We conducted a post hoc pooled analysis of three randomised controlled trials (duration: 12-20 weeks) comparing aerobic exercise interventions with controls. The primary outcome measure was a ≥30% relative reduction in (MRI-measured) liver fat, as a surrogate measure of liver histological response (the threshold necessary for fibrosis improvement). Secondary outcome measures were changes in other biomarkers of liver fibrosis, anthropometry, body composition and aerobic fitness. RESULTS: Eighty-eight adults (exercise: 54, control: 34; male: 67%) were included with mean (SD) age 51 (11) years and body mass index 33.3 (5.2) kg/m2. Following the intervention, exercise had ~5-fold (OR [95%CI]: 4.86 [1.72, 13.8], p = .002) greater odds of ≥30% relative reduction in MRI-measured liver fat compared with control. This paralleled the improvements in anthropometry (waist and hip circumference reduction), body composition (body fat, visceral and subcutaneous adipose tissue) and aerobic fitness (V̇O2peak, ventilatory threshold and exercise capacity). Importantly, these effects were independent of clinically significant body weight loss (<3% body weight). CONCLUSION: Exercise training led to clinically meaningful improvements in surrogate serum- and imaging-based measures of liver histological change, without clinically meaningful body weight reduction. These data reinforce the weight-neutral benefit of exercise training and suggest that aerobic training may improve liver fibrosis in patients with MASLD.

Multivariate patterns of brain functional connectome associated with COVID-19-related negative affect symptoms.

Severe mental health problems with the representation of negative affect symptoms (NAS) have been increasingly reported during the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to explore the multivariate patterns of brain functional connectome predicting COVID-19-related NAS. This cohort study encompassed a group of university students to undergo neuroimaging scans before the pandemic, and we re-contacted participants for 1-year follow-up COVID-related NAS evaluations during the pandemic. Regularized canonical correlation analysis was used to identify connectome-based dimensions of NAS to compute pairs of canonical variates. The predictive ability of identified functional connectome to NAS dimensional scores was examined with a nested cross-validation. Two dimensions (i.e. mode stress and mode anxiety) were related to distinct patterns of brain functional connectome (r2 = 0.911, PFDR = 0.048; r2 = 0.901, PFDR = 0.037, respectively). Mode anxiety was characterized by high loadings in connectivity between affective network (AFN) and visual network (VN), while connectivity of the default mode network with dorsal attention network (DAN) were remarkably prominent in mode stress. Connectivity patterns within the DAN and between DAN and VN, ventral attention network, and AFN was common for both dimensions. The identified functional connectome can reliably predict mode stress (r = 0.37, MAE = 5.1, p < 0.001) and mode anxiety (r = 0.28, MAE = 5.4, p = 0.005) in the cross-validation. Our findings provide new insight into multivariate dimensions of COVID-related NAS, which may have implications for developing network-based biomarkers in psychological interventions for vulnerable individuals in the pandemic.

Social intelligence mediates the protective role of resting-state brain activity in the social cognition network against social anxiety.

Background: Social intelligence refers to an important psychosocial skill set encompassing an array of abilities, including effective self-expression, understanding of social contexts, and acting wisely in social interactions. While there is ample evidence of its importance in various mental health outcomes, particularly social anxiety, little is known on the brain correlates underlying social intelligence and how it can mitigate social anxiety. Objective: This research aims to investigate the functional neural markers of social intelligence and their relations to social anxiety. Methods: Data of resting-state functional magnetic resonance imaging and behavioral measures were collected from 231 normal students aged 16 to 20 years (48% male). Whole-brain voxel-wise correlation analysis was conducted to detect the functional brain clusters related to social intelligence. Correlation and mediation analyses explored the potential role of social intelligence in the linkage of resting-state brain activities to social anxiety. Results: Social intelligence was correlated with neural activities (assessed as the fractional amplitude of low-frequency fluctuations, fALFF) among two key brain clusters in the social cognition networks: negatively correlated in left superior frontal gyrus (SFG) and positively correlated in right middle temporal gyrus. Further, the left SFG fALFF was positively correlated with social anxiety; brain-personality-symptom analysis revealed that this relationship was mediated by social intelligence. Conclusion: These results indicate that resting-state activities in the social cognition networks might influence a person's social anxiety via social intelligence: lower left SFG activity → higher social intelligence → lower social anxiety. These may have implication for developing neurobehavioral interventions to mitigate social anxiety.

Abnormal large-scale brain functional network dynamics in social anxiety disorder.

AIMS: Although static abnormalities of functional brain networks have been observed in patients with social anxiety disorder (SAD), the brain connectome dynamics at the macroscale network level remain obscure. We therefore used a multivariate data-driven method to search for dynamic functional network connectivity (dFNC) alterations in SAD. METHODS: We conducted spatial independent component analysis, and used a sliding-window approach with a k-means clustering algorithm, to characterize the recurring states of brain resting-state networks; then state transition metrics and FNC strength in the different states were compared between SAD patients and healthy controls (HC), and the relationship to SAD clinical characteristics was explored. RESULTS: Four distinct recurring states were identified. Compared with HC, SAD patients demonstrated higher fractional windows and mean dwelling time in the highest-frequency State 3, representing "widely weaker" FNC, but lower in States 2 and 4, representing "locally stronger" and "widely stronger" FNC, respectively. In State 1, representing "widely moderate" FNC, SAD patients showed decreased FNC mainly between the default mode network and the attention and perceptual networks. Some aberrant dFNC signatures correlated with illness duration. CONCLUSION: These aberrant patterns of brain functional synchronization dynamics among large-scale resting-state networks may provide new insights into the neuro-functional underpinnings of SAD.

Quantitative Imaging Reveals Steatosis and Fibroinflammation in Multiple Organs in People With Type 2 Diabetes: A Real-World Study.

We aimed to determine the extent of multiorgan fat accumulation and fibroinflammation in individuals living with type 2 diabetes. We deeply phenotyped individuals with type 2 diabetes (134 from secondary care, 69 from primary care) with multiorgan, quantitative, multiparametric MRI and compared with 134 matched control individuals without diabetes and 92 control individuals with normal weight. We examined the impact of diabetes duration, obesity status, and glycemic control. Ninety-three of the individuals with type 2 diabetes were reevaluated at 7 months (median). Multiorgan abnormalities were more common in individuals with type 2 diabetes (94%) than in age- and BMI-matched healthy individuals or healthy individuals with normal weight. We demonstrated a high burden of combined steatosis and fibroinflammation within the liver, pancreas, and kidneys (41%, 17%, and 10%) associated with visceral adiposity (73%) and poor vascular health (82%). Obesity was most closely associated with advanced liver disease, renal and visceral steatosis, and multiorgan abnormalities, while poor glycemic control was associated with pancreatic fibroinflammation. Pharmacological therapies with proven cardiorenal protection improved liver and vascular health unlike conventional glucose-lowering treatments, while weight loss or improved glycemic control reduced multiorgan adiposity (P ≤ 0.01). Quantitative imaging in people with type 2 diabetes highlights widespread organ abnormalities and may provide useful risk and treatment stratification.

Diagnostic utility of electrocardiogram for screening of cardiac injury on cardiac magnetic resonance in post-hospitalised COVID-19 patients: A prospective multicenter study.

BACKGROUND: The role of ECG in ruling out myocardial complications on cardiac magnetic resonance (CMR) is unclear. We examined the clinical utility of ECG in screening for cardiac abnormalities on CMR among post-hospitalised COVID-19 patients. METHODS: Post-hospitalised patients (n = 212) and age, sex and comorbidity-matched controls (n = 38) underwent CMR and 12­lead ECG in a prospective multicenter follow-up study. Participants were screened for routinely reported ECG abnormalities, including arrhythmia, conduction and R wave abnormalities and ST-T changes (excluding repolarisation intervals). Quantitative repolarisation analyses included corrected QT (QTc), corrected QT dispersion (QTc disp), corrected JT (JTc) and corrected T peak-end (cTPe) intervals. RESULTS: At a median of 5.6 months, patients had a higher burden of ECG abnormalities (72.2% vs controls 42.1%, p = 0.001) and lower LVEF but a comparable cumulative burden of CMR abnormalities than controls. Patients with CMR abnormalities had more ECG abnormalities and longer repolarisation intervals than those with normal CMR and controls (82% vs 69% vs 42%, p < 0.001). Routinely reported ECG abnormalities had poor discriminative ability (area-under-the-receiver-operating curve: AUROC) for abnormal CMR, AUROC 0.56 (95% CI 0.47-0.65), p = 0.185; worse among female than male patients. Adding JTc and QTc disp improved the AUROC to 0.64 (95% CI 0.55-0.74), p = 0.002, the sensitivity of the ECG increased from 81.6% to 98.0%, negative predictive value from 84.7% to 96.3%, negative likelihood ratio from 0.60 to 0.13, and reduced sex-dependence variabilities of ECG diagnostic parameters. CONCLUSION: Post-hospitalised COVID-19 patients have more ECG abnormalities than controls. Normal ECGs, including normal repolarisation intervals, reliably exclude CMR abnormalities in male and female patients.