Resting-state cerebral blood flow and functional connectivity abnormalities in depressed patients with childhood maltreatment: Potential biomarkers of vulnerability?

AIM: Childhood maltreatment (CM) is an important risk factor for major depressive disorder (MDD). This study aimed to explore the specific effect of CM on cerebral blood flow (CBF) and brain functional connectivity (FC) in MDD patients. METHODS: A total of 150 subjects were collected including 55 MDD patients with CM, 34 MDD patients without CM, 19 healthy controls (HC) with CM, and 42 HC without CM. All subjects completed MRI scans and neuropsychological tests. Two-way analysis of covariance was used to detect the main and interactive effects of disease and CM on CBF and FC across subjects. Then, partial correlation analyses were conducted to explore the behavioral significance of altered CBF and FC in MDD patients. Finally, a support vector classifier model was applied to differentiate MDD patients. RESULTS: MDD patients represented increased CBF in bilateral temporal lobe and decreased CBF in right visual cortex. Importantly, significant depression-by-CM interactive effects on CBF were primarily located in the frontoparietal regions, including orbitofrontal cortex (OFC), lateral prefrontal cortex (PFC), and parietal cortex. Moreover, significant FC abnormalities were seen in OFC-PFC and frontoparietal-visual cortex. Notably, the abnormal CBF and FC were significantly associated with behavioral performance. Finally, a combination of altered CBF and FC behaved with a satisfactory classification ability to differentiate MDD patients. CONCLUSIONS: These results highlight the importance of frontoparietal and visual cortices for MDD with CM experience, proposing a potential neuroimaging biomarker for MDD identification.

Characterization of neutrophil extracellular traps related gene pair for predicting prognosis in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant disease with a high incidence rate, high mortality and poor prognosis. Neutrophil extracellular traps (NETs), as an extracellular reticular structure, promote the development and progression of cancer in the tumor microenvironment, and have a promising prospect as a prognostic indicator. In the present study, we elucidated the prognostic value of NET-related genes. METHODS: The NETs gene pair of The Cancer Genome Atlas cohort was constructed by least absolute shrinkage and selection operator analysis. Samples from the International Cancer Genome Consortium were performed to verify its feasibility. Kaplan-Meier analysis was used to compare the overall survival (OS) rate of the two subgroups. The independent predictors of OS were determined by univariate and multivariate Cox analysis. Furthermore, Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway were analyzed by gene set enrichment analysis. The single sample gene set enrichment analysis method was performed to deplore the relationship of risk score with tumor immune microenvironment. The GSE149614 dataset was applied as single cell RNA level validation. PCR was performed to the detect mRNA expression profiles of NETs-related genes. RESULTS: Our analysis of the NETs-related model provides a promising prospect as a prognostic indicator. The OS of high-risk group patients was significantly reduced. The risk score was an important independent predictor of HCC prognosis. The Nomogram model suggested a favorable classification performance. The drug resistance and sensitivity of tumor cells to chemotherapeutics was significantly correlated with the prognostic gene expression. The immune status of the two risk groups showed a marked difference. CONCLUSIONS: The novel prognostic gene pair and immune landscape could predict the prognosis of HCC patients and provide a new understanding of immunotherapy in HCC.

Dyslipidemia induced large-scale network connectivity abnormality facilitates cognitive decline in the Alzheimer's disease.

BACKGROUND: Although lipid metabolite dysfunction contributes substantially to clinical signs and pathophysiology of Alzheimer's disease (AD), how dyslipidemia promoting neuropathological processes and brain functional impairment subsequently facilitates the progression of AD remains unclear. METHODS: We combined large-scale brain resting-state networks (RSNs) approaches with canonical correlation analysis to explore the accumulating effects of lipid gene- and protein-centric levels on cerebrospinal fluid (CSF) biomarkers, dynamic trajectory of large-scale RSNs, and cognitive performance across entire AD spectrum. Support vector machine model was used to distinguish AD spectrum and pathway analysis was used to test the influences among these variables. RESULTS: We found that the effects of accumulation of lipid-pathway genetic variants and lipoproteins were significantly correlated with CSF biomarkers levels and cognitive performance across the AD spectrum. Dynamic trajectory of large-scale RSNs represented a rebounding mode, which is characterized by a weakened network cohesive connector role and enhanced network incohesive provincial role following disease progression. Importantly, the fluctuating large-scale RSNs connectivity was significantly correlated with the summative effects of lipid-pathway genetic variants and lipoproteins, CSF biomarkers, and cognitive performance. Moreover, SVM model revealed that the lipid-associated twenty-two brain network connections represented higher capacity to classify AD spectrum. Pathway analysis further identified dyslipidemia directly influenced brain network reorganization or indirectly affected the CSF biomarkers and subsequently caused cognitive decline. CONCLUSIONS: Dyslipidemia exacerbated cognitive decline and increased the risk of AD via mediating large-scale brain networks integrity and promoting neuropathological processes. These findings reveal a role for lipid metabolism in AD pathogenesis and suggest lipid management as a potential therapeutic target for AD.

Disrupted intrinsic functional brain topology in patients with major depressive disorder.

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

Impaired robust interhemispheric function integration of depressive brain from REST-meta-MDD database in China.

BACKGROUND: Recently, functional homotopy (FH) architecture, defined as robust functional connectivity (FC) between homotopic regions, has been frequently reported to be altered in MDD patients (MDDs) but with divergent locations. METHODS: In this study, we obtained resting-state functional magnetic resonance imaging (R-fMRI) data from 1004 MDDs (mean age, 33.88 years; age range, 18-60 years) and 898 matched healthy controls (HCs) from an aggregated dataset from 20 centers in China. We focused on interhemispheric function integration in MDDs and its correlation with clinical characteristics using voxel-mirrored homotopic connectivity (VMHC) devised to inquire about FH patterns. RESULTS: As compared with HCs, MDDs showed decreased VMHC in visual, motor, somatosensory, limbic, angular gyrus, and cerebellum, particularly in posterior cingulate gyrus/precuneus (PCC/PCu) (false discovery rate [FDR] q < 0.002, z = -7.07). Further analysis observed that the reduction in SMG and insula was more prominent with age, of which SMG reflected such age-related change in males instead of females. Besides, the reduction in MTG was found to be a male-special abnormal pattern in MDDs. VMHC alterations were markedly related to episode type and illness severity. The higher Hamilton Depression Rating Scale score, the more apparent VMHC reduction in the primary visual cortex. First-episode MDDs revealed stronger VMHC reduction in PCu relative to recurrent MDDs. CONCLUSIONS: We confirmed a significant VMHC reduction in MDDs in broad areas, especially in PCC/PCu. This reduction was affected by gender, age, episode type, and illness severity. These findings suggest that the depressive brain tends to disconnect information exchange across hemispheres.

Collateral circulation detected by arterial spin labeling predicts outcome in acute ischemic stroke.

BACKGROUND: Robust collateral circulation is strongly associated with good outcomes in acute ischemic stroke (AIS). AIMS: To determine whether collateral circulation detected by arterial spin labeling (ASL) magnetic resonance imaging could predict good clinical outcome in AIS patients with 90 days follow-up. MATERIALS AND METHODS: Total 58 AIS patients with anterior circulation stroke were recruited. Collateral circulation was defined as arterial transit artifact in ASL images. Modified Rankin Scale (mRS), the Barthel Index, and National Institutes of Health Stroke Scale (NIHSS) were employed to evaluate neurological function for the baseline and 90 days follow-up. The percent changes of these scores were also calculated, respectively. Finally, a support vector classifier model of machine learning and receiver operating characteristic curve were employed to estimate the power of ASL collaterals (ASLcs) predicting the clinical outcome. RESULTS: Patients with ASLcs represented higher rate of good outcome (83.30% vs. 31.25%, p < .001) and lower follow-up mRS scores (p < .001), when compared to patients without ASLcs. There were significant differences for percent changes of mRS scores and NIHSS scores between these two groups. Further, the presence of ASLcs could predict good clinical outcome (OR, 1.54; 95% CI, 1.10-2.16), even after controlling for baseline NIHSS scores. The SVC model incorporating baseline NIHSS scores and ASLcs had significant predictive effect (accuracy, 79.3%; AUC, 0.806) on clinical prognosis for AIS patients. DISCUSSION: We targeted on the non-invasive assessment of collateral circulation using ASL technique and found that patients with ASLcs were more likely to have a good clinical outcome after AIS. This finding is of guiding significance for treatment selection and prognostic prediction. CONCLUSIONS: Early ASLcs assessment provides a good powerful tool to predict clinical outcome for AIS patients with 90 days follow-up.

Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

Identification of microRNA-9 linking the effects of childhood maltreatment on depression using amygdala connectivity.

Childhood maltreatment (CM) is regarded as an important risk factor for major depressive disorder (MDD). However, the neural links corresponding to the process of early CM experience producing brain alterations and then leading to depression later remain unclear. To explore the neural basis of the effects of CM on MDD and the potential role of microRNA-9 (miR-9) in these processes, we recruited 40 unmedicated MDD patients and 34 healthy controls (HCs) to complete resting-state fMRI scans and peripheral blood miR-9 tests. The neural substrates of CM, miR-9, and depression, as well as their interactive effects on intrinsic amygdala functional connectivity (AFC) networks were investigated in MDD patients. Two-step mediation analysis was separately employed to explore whether AFC strength mediates the association among CM severity, miR-9 levels, and depression. A support vector classifier (SVC) model of machine learning was used to distinguish MDD patients from HCs. MDD patients showed higher miR-9 levels that were negatively correlated with CM scores and depressive severity. Overlapping effects of CM, miR-9, and depressive severity on bilateral AFC networks in MDD patients were primarily located in the prefrontal-striatum pathway and limbic system. The connection of amygdala to prefrontal-limbic circuits could mediate the effects of CM severity on the miR-9 levels, as well as the impacts of miR-9 levels on the severity of depression in MDD patients. Furthermore, the SVC model, which integrated miR-9 levels, CM severity, and AFC strength in prefrontal-limbic regions, had good power in differentiating MDD patients from HCs (accuracy 85.1%). MiR-9 may play a crucial role in the process of CM experience-produced brain changes targeting prefrontal-limbic regions and that subsequently leads to depression. The present neuroimaging-epigenetic results provide new insight into our understanding of MDD pathophysiology.

Spatio-temporal graph convolutional network for diagnosis and treatment response prediction of major depressive disorder from functional connectivity.

The pathophysiology of major depressive disorder (MDD) has been explored to be highly associated with the dysfunctional integration of brain networks. It is therefore imperative to explore neuroimaging biomarkers to aid diagnosis and treatment. In this study, we developed a spatiotemporal graph convolutional network (STGCN) framework to learn discriminative features from functional connectivity for automatic diagnosis and treatment response prediction of MDD. Briefly, dynamic functional networks were first obtained from the resting-state fMRI with the sliding temporal window method. Secondly, a novel STGCN approach was proposed by introducing the modules of spatial graph attention convolution (SGAC) and temporal fusion. A novel SGAC was proposed to improve the feature learning ability and special anatomy prior guided pooling was developed to enable the feature dimension reduction. A temporal fusion module was proposed to capture the dynamic features of functional connectivity between adjacent sliding windows. Finally, the STGCN proposed approach was utilized to the tasks of diagnosis and antidepressant treatment response prediction for MDD. Performances of the framework were comprehensively examined with large cohorts of clinical data, which demonstrated its effectiveness in classifying MDD patients and predicting the treatment response. The sound performance suggests the potential of the STGCN for the clinical use in diagnosis and treatment prediction.

Desynchronized Functional Activities Between Brain White and Gray Matter in Major Depression Disorder.

BACKGROUND: Alterations in gray matter (GM) have been recognized as playing an important role in the neurobiological mechanism underlying major depressive disorder (MDD) and antidepressant responses. However, little is known about white matter (WM) connectivity in MDD, leaving an incomplete understanding of the pathophysiology of the disorder. PURPOSE: To examine the functional connectivity (FC) of WM, GM, and WM-GM in MDD patients and explore the relationship between FC and antidepressant response. STUDY TYPE: Longitudinal study. SUBJECTS: In all, 129 MDD patients and 89 healthy controls (HC). FIELD STRENGTH/SEQUENCE: Whole-brain blood oxygen level-dependent (BOLD) single-shot echo planar imaging was acquired at 3.0T. ASSESSMENT: At baseline, all participants received Hamilton depression rating scale (HAMD) assessment and an fMRI scan. After 2- and 8-week antidepressant treatment, patients completed the HAMD again. The HAMD reductive rate of 2- and 8-weeks were calculated. STATISTICAL TESTS: The comparisons of age, education, HAMD scores, and FC values (false discovery rate correction) between patients and controls were calculated with a two-sample t-test. The chi-square test was employed to compare the differences of gender between these two groups. Correlations between FC and HAMD, as well as the reductive rate of HAMD, were analyzed with Pearson or Spearman correlation. Receiver operator curve analysis was performed to predict the antidepressant response. RESULTS: Compared to HC, MDD patients exhibited widespread decreases in FC of WM-GM. Furthermore, 28 GM regions and 11 WM bundles had lower connectivity in MDD patients. At baseline, four FC of WM-GM showed negative correlations with the HAMD scores. Six FC of WM-GM correlated with the 2-week reductive rate of HAMD. Moreover, FC in GM, WM, and WM-GM also exhibited significantly positive correlations with an 8-week reductive rate of HAMD. DATA CONCLUSION: The FC of WM-GM was decreased in MDD and may play a role in its pathophysiology and antidepressant responses. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 2.

CircDYM ameliorates depressive-like behavior by targeting miR-9 to regulate microglial activation via HSP90 ubiquitination.

Circular RNAs (circRNAs), highly expressed in the central nervous system, are involved in various regulatory processes and implicated in some pathophysiology. However, the potential role of circRNAs in psychiatric diseases, particularly major depressive disorder (MDD), remains largely unknown. Here, we demonstrated that circular RNA DYM (circDYM) levels were significantly decreased both in the peripheral blood of patients with MDD and in the two depressive-like mouse models: the chronic unpredictable stress (CUS) and lipopolysaccharide (LPS) models. Restoration of circDYM expression significantly attenuated depressive-like behavior and inhibited microglial activation induced by CUS or LPS treatment. Further examination indicated that circDYM functions as an endogenous microRNA-9 (miR-9) sponge to inhibit miR-9 activity, which results in a downstream increase of target-HECT domain E3 ubiquitin protein ligase 1 (HECTD1) expression, an increase of HSP90 ubiquitination, and a consequent decrease of microglial activation. Taken together, the results of our study demonstrate the involvement of circDYM and its coupling mechanism in depression, providing translational evidence that circDYM may be a novel therapeutic target for depression.

Hypoxia-inducible factor-prolyl hydroxylase inhibitor ameliorates myopathy in a mouse model of chronic kidney disease.

Muscle wasting and diminished physical performance contribute to the morbidity and mortality of chronic kidney disease (CKD), for which no curative therapy exists. Accumulating evidence indicates that impaired angiogenesis occurs in the muscles of CKD models. Therefore, proangiogenesis therapy is considered a potentially effective strategy for limiting CKD-associated myopathy. Hypoxia-inducible factor (HIF)-prolyl hydroxylase inhibitor (HIF-PHI) stabilizes HIF and enhances muscle angiogenesis during acute ischemia; however, little evidence was available from CKD models. Here, we assessed whether pharmacological activation of HIF by MK-8617 (MK), a novel orally active HIF-PHI, improves CKD-associated myopathy. Mice were divided into sham or CKD groups, and CKD mice were subdivided into CKD + vehicle or MK treatment groups (1.5, 5, or 12.5 mg/kg for 12 wk). In CKD mice, skeletal muscle mass, mitochondrial amount, and exercise capacity decreased compared with sham mice. Compared with the CKD + vehicle group, low (1.5 mg/kg) and medium (5 mg/kg) doses of MK, but not the high dose (12.5 mg/kg), significantly restored these changes and was accompanied by incremental increases in HIF-1α. Furthermore, increased capillary density and area were observed in a MK dose-dependent manner, which is likely related to an improved VEGF response in the skeletal muscle of CKD mice. In addition, macrophage and proinflammatory cytokines, including monocyte chemoattractant protein 1, TNF-α, and IL-6, significantly increased in the high-dose MK group. These results indicate that HIF-PHI provides a potential therapeutic strategy to improve CKD-associated myopathy.

Immunity factor contributes to altered brain functional networks in individuals at risk for Alzheimer's disease: Neuroimaging-genetic evidence.

Clusterin (CLU) is recognized as a secreted protein that is related to the processes of inflammation and immunity in the pathogenesis of Alzheimer's disease (AD). The effects of the risk variant of the C allele at the rs11136000 locus of the CLU gene are associated with variations in the brain structure and function. However, the relationship of the CLU-C allele to architectural disruptions in resting-state networks in amnestic mild cognitive impairment (aMCI) subjects (i.e., individuals with elevated risk of AD) remains relatively unknown. Using resting-state functional magnetic resonance imaging and an imaging genetic approach, this study investigated whether individual brain functional networks, i.e., the default mode network (DMN) and the task-positive network, were modulated by the CLU-C allele (rs11136000) in 50 elderly participants, including 26 aMCI subjects and 24 healthy controls. CLU-by-aMCI interactions were associated with the information-bridging regions between resting-state networks rather than with the DMN itself, especially in cortical midline regions. Interestingly, the complex communications between resting-state networks were enhanced in aMCI subjects with the CLU rs11136000 CC genotype and were modulated by the degree of memory impairment, suggesting a reconstructed balance of the resting-state networks in these individuals with an elevated risk of AD. The neuroimaging-genetic evidence indicates that immunity factors may contribute to alterations in brain functional networks in aMCI. These findings add to the evidence that the CLU gene may represent a potential therapeutic target for slowing disease progression in AD.

Impacts of Related Risk Factors on the Efficacy of Interventional Treatment Towards Intractable Postpartum Hemorrhage.

Objective: To investigate the risk factors that impact the efficacy of interventional treatment of intractable postpartum hemorrhage (IPH). Study Design: A total of 64 IPH patients were admitted and received interventional treatment at First Hospital of Shanxi Medical University from January 2012 to September 2014, among whom 57 cases were successfully treated (bleeding stopped), while 7 cases failed. The clinical data of the success group and the failure group were observed for the multivariate analysis of the possible reasons that might cause hemostatic failure. Results: The univariate analysis of each suspected factor of hemostatic failure showed that history of uterine scar, combined use of uterotonics, uterine inertia, and placenta exhibited statistically significant differences between the 2 groups (p<0.05); the multivariate logistic regression analysis showed that history of uterine scar and combined use of uterotonics were the risk factors for the interventional treatment failure of IPH, with OR values of 11.23 (95% CI 1.26~100.22) and 12.83 (95% CI 1.05-156.34), respectively. Conclusion: History of uterine scar and combined use of uterotonics were the risk factors for interventional treatment failure of IPH.

Clinical efficacy of percutaneous transluminal renal artery stenting for the treatment of renovascular hypertension associated with Takayasu arteritis.

BACKGROUND: This study aims to observe and analyze the clinical efficacy of interventional therapy for patients with Takayasu arteritis (TA) experiencing renovascular hypertension (RH). METHODS: Eight TA patients with RH underwent percutaneous transluminal renal artery stenting (PTRAS). Patients were followed up 1, 6, 12, and 24 months postoperatively for levels of blood pressure, number of antihypertensive drugs being taken, levels of serum creatinine, and the presence of renal artery restenosis. RESULTS: All 8 patients were successfully followed up 1, 6, and 12 months postoperatively, but 1 was lost to follow-up at 24 months. All patients had significantly lower average blood pressure levels compared with those at baseline (P < 0.05); treatment efficacy rates (recovery or improvement) at 1, 6, 12, and 24 months were 94%, 90%, 80%, and 80%, respectively. The average number of antihypertensive drugs being taken was 3.5 at baseline, 1.0 at 1 month, 0.5 at 6 months, 1.0 at 12 months, and 1.5 at 24 months. Serum creatinine levels during the follow-up period were not significantly different from those at the baseline. No patient developed renal artery restenosis during the follow-up period. CONCLUSIONS: PTRAS is a safe and effective treatment for TA-associated RH, with a high technical success rate and a low complication rate. This interventional therapy can effectively control TA-related hypertension and can also preserve and even improve kidney function.

Age- and gender-related dispersion of brain networks across the lifespan.

The effects of age and gender on large-scale resting-state networks (RSNs) reflecting within- and between-network connectivity in the healthy brain remain unclear. This study investigated how age and gender influence the brain network roles and topological properties underlying the ageing process. Ten RSNs were constructed based on 998 participants from the REST-meta-MDD cohort. Multivariate linear regression analysis was used to examine the independent and interactive influences of age and gender on large-scale RSNs and their topological properties. A support vector regression model integrating whole-brain network features was used to predict brain age across the lifespan and cognitive decline in an Alzheimer's disease spectrum (ADS) sample. Differential effects of age and gender on brain network roles were demonstrated across the lifespan. Specifically, cingulo-opercular, auditory, and visual (VIS) networks showed more incohesive features reflected by decreased intra-network connectivity with ageing. Further, females displayed distinctive brain network trajectory patterns in middle-early age, showing enhanced network connectivity within the fronto-parietal network (FPN) and salience network (SAN) and weakened network connectivity between the FPN-somatomotor, FPN-VIS, and SAN-VIS networks. Age - but not gender - induced widespread decrease in topological properties of brain networks. Importantly, these differential network features predicted brain age and cognitive impairment in the ADS sample. By showing that age and gender exert specific dispersion of dynamic network roles and trajectories across the lifespan, this study has expanded our understanding of age- and gender-related brain changes with ageing. Moreover, the findings may be useful for detecting early-stage dementia.

Dynamic functional network connectivity and its association with lipid metabolism in Alzheimer's disease.

AIMS: The study aims to examine the changing trajectory characteristics of dynamic functional network connectivity (dFNC) and its correlation with lipid metabolism-related factors across the Alzheimer's disease (AD) spectrum populations. METHODS: Data from 242 AD spectrum subjects, including biological, neuroimaging, and general cognition, were obtained from the Alzheimer's Disease Neuroimaging Initiative for this cross-sectional study. The study utilized a sliding-window approach to assess whole-brain dFNC, investigating group differences and associations with biological and cognitive factors. Abnormal dFNC was used in the classification of AD spectrum populations by support vector machine. Mediation analysis was performed to explore the relationships between lipid-related indicators, dFNC, cerebrospinal fluid (CSF) biomarkers, and cognitive performance. RESULTS: Significant group difference concerning were observed in relation to APOE-ε4 status, CSF biomarkers, and cognitive scores. Two reoccurring connectivity states were identified: state-1 characterized by frequent but weak connections, and state-II characterized by less frequent but strong connections. Pre-AD subjects exhibited a preference for spending more time in state-I, whereas AD patients tended remain in state-II for longer periods. Group difference in dFNC was primarily found between AD and non-AD participants within each state. The dFNC of state-I yielded strong power to distinguish AD from other groups compared with state-II. APOE-ε4+, high polygenic score, and high serum lipid group were strongly associated with network disruption between association cortex system and sensory cortex system that characterized elevation of cognitive function, which may suggest a compensatory mechanism of dFNC in state-I, whereas differential connections of state-II mediated the relationships between APOE-ε4 genotype and CSF biomarkers, and cognitive indicators. CONCLUSION: The dysfunction of dFNC temporal-spatial patterns and increased cognition in individuals with APOE-ε4, high polygenic score, and higher serum lipid levels shed light on the lipid-related mechanisms of dynamic network reorganization in AD.

Transarterial chemoembolization combined with radiofrequency ablation for medium and large hepatocellular carcinoma: insufficient ablation is associated with intrahepatic distant metastasis and extrahepatic metastasis.

Purpose: To compare the prognosis of complete and insufficient ablation of transarterial chemoembolization (TACE) combined with radiofrequency ablation (RFA) in treating medium and large hepatocellular carcinoma (HCC) and to explore the differences in recurrence patterns between the two groups. Patients and methods: Patients´ medical records and imaging data of patients with confirmed HCC from January 2014 to January 2022 were collected. These patients were divided into 2 groups: complete ablation (n=172) and insufficient ablation (n=171). Overall survival (OS) and progression-free survival (PFS) were estimated by the Kaplan-Meier curve and the log-rank test was used to compared. Fisher's exact test was used to compare recurrence patterns between the two groups. Results: The median OS time was 72.8 months (95%CI:69.5-76.1) and 62.0 months (95%CI: 55.3-68.7) in the complete and insufficient ablation groups, respectively. The median PFS time in the complete ablation group was 67.8 months (95% CI: 65.2-70.4) and 38.6 months (95%CI: 29.8-47.4) in the insufficient ablation group. The OS and PFS rates of the complete ablation group were significantly better than those of the insufficient ablation group (P<0.001). In the complete ablation group, 25(41%) patients experienced local tumor progression(LTP), 36(59%) experienced intrahepatic distant progression(IDP), and 0(0%) experienced extrahepatic progression (EP). In the insufficient ablation group, 51 (32.1%) patients experienced LTP, 96 (60.4%) experienced IDP, and 12 (7.5%) experienced EP. The progression patterns of the two groups were statistically significant (P=0.039). Conclusion: Insufficient ablation indicates a poor survival outcome of TACE combined with RFA for medium and large HCC and can promote intrahepatic distant and extrahepatic metastasis.

Occipital connectivity networks mediate the neural effects of childhood maltreatment on depressive symptoms in major depressive disorder.

BACKGROUND: Childhood maltreatment (CM) is a well-established risk factor for major depressive disorder (MDD). The neural mechanisms linking childhood maltreatment experiences to changes in brain functional networks and the onset of depression are not fully understood. METHODS: In this study, we enrolled 66 patients with MDD and 31 healthy controls who underwent resting-state fMRI scans and neuropsychological assessments. We employed multivariate linear regression to examine the neural associations of CM and depression, specifically focusing on the bilateral occipital functional connectivity (OFC) networks relevant to MDD. Subsequently, a two-step mediation analysis was conducted to assess whether the OFC network mediated the relationship between CM experiences and the severity of depression. RESULTS: Our study showed that patients with MDD exhibited reduced OFC strength, particularly in the occipito-temporal, parietal, and premotor regions. These reductions were negatively correlated with CM scores and the severity of depression. Notably, the overlapping regions in the bilateral OFC networks, affected by both CM experiences and depressive severity, were primarily observed in the bilateral cuneus, left angular and calcarine, as well as the right middle frontal cortex and superior parietal cortex. Furthermore, the altered strengths of the OFC networks were identified as positive mediators of the impact of CM history on depression symptoms in patients with MDD. CONCLUSION: We have demonstrated that early exposure to CM may increase vulnerability to depression by influencing the brain's network. These findings provide new insights into understanding the pathological mechanism underlying depressive symptoms induced by CM.

MicroRNA-124 influenced depressive symptoms via large-scale brain connectivity in major depressive disorder patients.

This study aimed to investigate the neurobiological mechanisms by which microRNA 124 (miR-124) is involved in major depressive disorder (MDD). We enrolled 53 untreated MDD patients and 38 healthy control (HC) subjects who completed behavior assessments and resting-state functional MRI (rs-fMRI) scans. MiR-124 expression levels were detected in the peripheral blood of all participants. We determined that miR-124 levels could influence depressive symptoms via disrupted large-scale intrinsic intra- and internetwork connectivity, including the default mode network (DMN)-DMN, dorsal attention network (DAN)-salience network (SN), and DAN-cingulo-opercular network (CON). This study deepens our understanding of how miR-124 dysregulation contributes to depression.