Local structural and functional MRI markers of compulsive behaviors and obsessive-compulsive disorder diagnosis within striatum-based circuits.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a classic disorder on the compulsivity spectrum, with diverse comorbidities. In the current study, we sought to understand OCD from a dimensional perspective by identifying multimodal neuroimaging patterns correlated with multiple phenotypic characteristics within the striatum-based circuits known to be affected by OCD. METHODS: Neuroimaging measurements of local functional and structural features and clinical information were collected from 110 subjects, including 51 patients with OCD and 59 healthy control subjects. Linked independent component analysis (LICA) and correlation analysis were applied to identify associations between local neuroimaging patterns across modalities (including gray matter volume, white matter integrity, and spontaneous functional activity) and clinical factors. RESULTS: LICA identified eight multimodal neuroimaging patterns related to phenotypic variations, including three related to symptoms and diagnosis. One imaging pattern (IC9) that included both the amplitude of low-frequency fluctuation measure of spontaneous functional activity and white matter integrity measures correlated negatively with OCD diagnosis and diagnostic scales. Two imaging patterns (IC10 and IC27) correlated with compulsion symptoms: IC10 included primarily anatomical measures and IC27 included primarily functional measures. In addition, we identified imaging patterns associated with age, gender, and emotional expression across subjects. CONCLUSIONS: We established that data fusion techniques can identify local multimodal neuroimaging patterns associated with OCD phenotypes. The results inform our understanding of the neurobiological underpinnings of compulsive behaviors and OCD diagnosis.

Imbalance in functional and structural connectivity underlying goal-directed and habitual learning systems in obsessive-compulsive disorder.

An imbalance between the goal-directed and habitual learning systems has been proposed to underlie compulsivity in obsessive-compulsive disorder (OCD). In addition, the overall balance between these systems may be influenced by stress hormones. We examined the multimodal networks underlying these dual learning systems. Both functional and structural measures indicated reduced connectivity within the goal-directed subnetwork (FC: P = 0.042; SC-FN: P = 0.014) and reduced connectivity between the goal-directed and habitual subnetworks (FC: P = 0.014; SC-FA: P = 0.052), but no differences within the habitual subnetwork in patients with OCD compared with controls. Path modeling indicated that anatomical connectivity in the goal-directed subnetwork influenced compulsive symptoms (R2 = 0.41), whereas functional connectivity within the habit subnetwork and between goal-directed and habitual subnetworks influenced obsessive symptoms (R2 = 0.63). In addition, the relationship between anatomical connectivity in the goal-directed subnetwork and compulsion was moderated by the stress hormone ACTH (adrenocorticotropic hormone), such that at low levels of ACTH greater connectivity resulted in lower compulsion, but at high levels of ACTH this relationship was reversed. These results provide new insights into the neural correlates of the imbalance between dual learning systems, and their relationship with symptom dimensions in patients with OCD. It may further support the reconceptualization of OCD as "compulsive-obsessive disorder," with a greater focus on the transdiagnostic dimension of compulsivity.

Imaging characteristics of ovarian sclerosing stromal tumor.

OBJECTIVES: This study was designed to evaluate the specific imaging features of ovarian sclerosing stromal tumor (SST), improve its accuracy as well as the specificity of imaging diagnosing, and prevent overestimation of malignancy to reduce unnecessary surgical procedures. METHODS: Eight patients with magnetic resonance imaging (MRI) and six with computed tomography (CT) images were analyzed in this retrospective observational study. All the cases were confirmed by postoperative pathological examination as those of ovarian SST. Imaging and pathological features were also evaluated. RESULTS: All the 14 masses displayed cystic and solid components with outer surface of tumors contained a capsular and complete smooth rim. Eight tumors of MRI exhibited "lake-island" sign on T2 weighted imaging (T2WI). Two of the 6 CT cases displayed a flaky calcification. One case showed as a multiloculated cystic mass with irregularly thickened septae and the tumor wall. The solid components in other 13 masses were comb- or wheel-like enhanced. After injection of contrast agent, the solid components in 8 cases (57.1%) appeared as early enhancement, whereas the other 6 cases (42.9%) appeared as progressive enhanced, and the cystic components of all the cases had no enhancement in the whole course. Vascular flow signals or/and marked enhancement of the blood vessels were found in 12 lesions (85.7%). Pathological examination demonstrated pseudolobule patterns, round to spindle shaped cells, collagenous areas, edematous hypocellular areas and prominent vasculatures. CONCLUSIONS: The results demonstrated that MRI with "lake-island" signs on T2WI and MRI/CT dynamic enhancement could potentially play a critical role in facilitating appropriate diagnosis preoperatively.

Topologic Reorganization of White Matter Connectivity Networks in Early-Blind Adolescents.

Blindness studies are important models for the comprehension of human brain development and reorganization, after visual deprivation early in life. To investigate the global and local topologic alterations and to identify specific reorganized neural patterns in early-blind adolescents (EBAs), we applied diffusion tensor tractography and graph theory to establish and analyze the white matter connectivity networks in 21 EBAs and 22 age- and sex-matched normal-sighted controls (NSCs). The network profiles were compared between the groups using a linear regression model, and the associations between clinical variables and network profiles were analyzed. Graph theory analysis revealed "small-world" attributes in the structural connection networks of both EBA and NSC cohorts. The EBA cohort exhibited significant lower network density and global and local efficiency, as well as significantly elevated shortest path length, compared to the NSC group. The network efficiencies were markedly reduced in the EBA cohort, with the largest alterations in the default-mode, visual, and limbic areas. Moreover, decreased regional efficiency and increased nodal path length in some visual and default-mode areas were strongly associated with the period of blindness in EBA cohort, suggesting that the function of these areas would gradually weaken in the early-blind brains. Additionally, the differences in hub distribution between the two groups were mainly within the occipital and frontal areas, suggesting that neural reorganization occurred in these brain regions after early visual deprivation during adolescence. This study revealed that the EBA brain structural network undergoes both convergent and divergent topologic reorganizations to circumvent early visual deprivation. Our research will add to the growing knowledge of underlying neural mechanisms that govern brain reorganization and development, under conditions of early visual deprivation.

A novel protein AXIN1-295aa encoded by circAXIN1 activates the Wnt/ß-catenin signaling pathway to promote gastric cancer progression.

BACKGROUND: Circular RNA (circRNA), a subclass of non-coding RNA, plays a critical role in cancer tumorigenesis and metastasis. It has been suggested that circRNA acts as a microRNA sponge or a scaffold to interact with protein complexes; however, its full range of functions remains elusive. Recently, some circRNAs have been found to have coding potential. METHODS: To investigate the role of circRNAs in gastric cancer (GC), parallel sequencing was performed using five paired GC samples. Differentially expressed circAXIN1 was proposed to encode a novel protein. FLAG-tagged circRNA overexpression plasmid construction, immunoblotting, mass spectrometry, and luciferase reporter analyses were applied to confirm the coding potential of circAXIN1. Gain- and loss-of-function studies were conducted to study the oncogenic role of circAXIN1 and AXIN1-295aa on the proliferation, migration, invasion, and metastasis of GC cells in vitro and in vivo. The competitive interaction between AXIN1-295aa and adenomatous polyposis coli (APC) was investigated by immunoprecipitation analyses. Wnt signaling activity was observed using a Top/Fopflash assay, real-time quantitative RT-PCR, immunoblotting, immunofluorescence staining, and chromatin immunoprecipitation. RESULTS: CircAXIN1 is highly expressed in GC tissues compared with its expression in paired adjacent normal gastric tissues. CircAXIN1 encodes a 295 amino acid (aa) novel protein, which was named AXIN1-295aa. CircAXIN1 overexpression enhances the cell proliferation, migration, and invasion of GC cells, while the knockdown of circAXIN1 inhibits the malignant behaviors of GC cells in vitro and in vivo. Mechanistically, AXIN1-295aa competitively interacts with APC, leading to dysfunction of the "destruction complex" of the Wnt pathway. Released ß-catenin translocates to the nucleus and binds to the TCF consensus site on the promoter, inducing downstream gene expression. CONCLUSION: CircAXIN1 encodes a novel protein, AXIN1-295aa. AXIN1-295aa functions as an oncogenic protein, activating the Wnt signaling pathway to promote GC tumorigenesis and progression, suggesting a potential therapeutic target for GC.

Reversible splenial lesion syndrome with mental disorders as only manifestation.

BACKGROUND: Reversible splenial lesion syndrome (RESLES) was reported to be associated with variable entities. However, much less is known about the cases in which the mental disorders act as the only manifestation. METHOD: Total ten patients of RESLES were obtained in this retrospective study from Shenzhen Kangning Hospital. T1-fluid attenuated inversion recovery (T1-FLAIR), T2-weighted images, T2-FLAIR, diffusion-weighted images and apparent diffusion coefficient map were performed on all the patients. Clinical manifestations, laboratory examination results, magnetic resonance imaging (MRI) findings, treatments and outcomes were analyzed. RESULT: All patients showed different mental disorders as the only manifestation. There were two cases of alcohol abuse, one of Asperger's syndrome with malnutrition, one of infection and one of invasive pituitary adenoma. The other cases were diagnosis as major depressive disorder, dissociative and conversion disorders, undifferentiated somatoform disorder, unspecified psychosis and bipolar disorder, respectively. Three patients were completely recovered while the clinical symptoms of rest seven patients partially recovered at the follow-up three months later. Oval-shaped lesion centered on the splenial of corpus callosum (SCC) was observed in all patients using MRI. The lesions of SCC of all patients were completely resolved within five weeks. CONCLUSIONS: We found that RESLES might only showed mental symptoms. On the one hand, for the patients with acute mental disorders, clinicians should be alert to the possibility of RESLES caused by physical disease. On the other hand, we suggest that mental disorder might be a precipitating factor of RESLES.

Clinical characteristics and neuroimaging findings of seven patients with Dyke Davidoff Masson syndrome.

BACKGROUND: DDMS is a rare disease diagnosed by clinical and radiological characteristics. But the complexity of radiological and clinical manifestations of DDMS has become a challenge diagnostically. To date, the reported cases with DDMS had highly varied clinical manifestations including seizures, contralateral hemiplegia/hemiparesis, facial asymmetry, mental retardation, etc. In addition to typical clinical findings, some new characteristics have been recently added to the spectrum of DDMS. However, few cases have been reported to be associated with neuropsychiatric symptoms according to the literature. This study aimed to investigate the neuropsychiatric manifestations associated with Dyke-Davidoff-Masson syndrome (DDMS) and related imaging findings. METHODS: This study included 7 patients diagnosed with DDMS between 2014 and 2020. The clinical characteristics, neuropsychiatric manifestations, and radiological results were retrospectively evaluated. RESULTS: Seven patients (five males and two females) with a mean age of 28.0 ± 9.73 (range 15.0-41.0) years were included. Five patients were admitted to the psychiatric unit due to psychological and behavioral disorders. Two patients were referred to the neurology unit mainly due to epilepsy. Six patients had epileptic seizures, 4 had hemiplegia, 3 had mental retardation, 2 patients had external ear deformities, and 2 had facial asymmetry. Neuropsychiatric symptoms were presented in 6 (85.7 %) cases. Cases 2-6 developed affective disorders. Deficits in verbal communication, impairment of social interaction, lack of insight, adulia and hypobulia appeared in cases 1-4. Schizophrenia with apathy, and epileptic schizoid psychosis were observed in cases 4 and 5 respectively. Case 6 had behavioral disorders, hyperactivity, tic disorder, mental retardation, anxiety, catatonic symptoms and suicidal tendency. Case 7 had seizures and mental retardation, and no psychiatric symptoms were presented. Radiological examinations showed unilateral cerebral atrophy, enlarged lateral ventricles, and various compensatory hypertrophy of the skull in all cases. The midline structure has shifted to the affected side in 5(71.4 %) cases. Atrophy of the basal ganglia or brain stem was observed in 4(57.1 %) cases. CONCLUSIONS: The hallmark imaging manifestations of DDMS facilitated the diagnosis in most cases. This study illustrated that a variety of psychoneurotic disorders and ear abnormalities were correlated with DDMS.

Reduced coupling between global signal and cerebrospinal fluid inflow in patients with depressive disorder: A resting state functional MRI study.

BACKGROUND: Depressed patients often suffer from sleep disturbance, which has been recognized to be responsible for glymphatic dysfunction. The purpose of this study was to investigate the coupling strength of global blood­oxygen-level-dependent (gBOLD) signals and cerebrospinal fluid (CSF) inflow dynamics, which is a biomarker for glymphatic function, in depressed patients and to explore its potential relationship with sleep disturbance by using resting-state functional MRI. METHODS: A total of 138 depressed patients (112 females, age: 34.70 ± 13.11 years) and 84 healthy controls (29 females, age: 36.6 ± 11.75 years) participated in this study. The gBOLD-CSF coupling strength was calculated to evaluate glymphatic function. Sleep disturbance was evaluated using the insomnia items (item 4 for insomnia-early, item 5 for insomnia-middle, and item 6 for insomnia-late) of The 17-item Hamilton Depression Rating Scale for depressed patients, which was correlated with the gBOLD-CSF coupling strength. RESULTS: The depressed patients exhibited weaker gBOLD-CSF coupling relative to healthy controls (p = 0.022), possibly due to impairment of the glymphatic system. Moreover, the gBOLD-CSF coupling strength correlated with insomnia-middle (r = 0.097, p = 0.008) in depressed patients. Limitations This study is a cross-sectional study. CONCLUSION: Our findings shed light on the pathophysiology of depression, indicating that cerebral waste clearance system deficits are correlated with poor sleep quality in depressed patients.

Connectome architecture modulates the gray matter atrophy in major depression disorder patients with diverse suicidal ideations.

Gray matter (GM) atrophy is well documented in patients with major depressive disorder (MDD), but its underlying mechanism remains unknown. This study aimed to examine the GM atrophy in MDD patients with diverse suicidal ideations (SIs) and to explore whether those alterations were driven by connections. GM volume was estimated in 163 patients with recurrent MDD (comprising 122 with SI [MDDSI] and 41 without SI [MDDNSI]) and 134 health controls (HCs). A two-sample t-test was used to identify GM volume abnormalities in MDD patients and their subgroups. Functional connectivity was computed between pairs of aberrant GM in both patients and HCs, which were further compared with the connectivity of random brain regions. A permutation test was performed to assess its significance. Propensity score matching (PSM) was further performed to validate the main results. Compared with HCs, the MDDNSI group exhibited GM atrophy in 24 regions, with the largest effect sizes found in the frontal and parietal lobes, while the MDDSI group exhibited more widespread GM atrophy involving 49 regions, with the largest effect sizes in the frontal lobe, parietal lobe, temporal lobe, and the limbic system. Furthermore, patients and HCs exhibited significantly increased functional connectivity between regions with GM atrophy compared with randomly selected regions (p < 0.05). PSM analysis presented similar results to the main analysis. MDD patients had diverse GM atrophy features according to their SI tendency. Moreover, connectome architecture modulates the GM atrophy in MDD patients, implying the possibility that connections drive these pathological changes.

Reduced myelin content in bipolar disorder: A study of inhomogeneous magnetization transfer.

BACKGROUND: Previous neuroimaging and pathological studies have found myelin-related abnormalities in bipolar disorder (BD), which prompted the use of magnetic resonance (MR) imaging technology sensitive to neuropathological changes to explore its neuropathological basis. We holistically investigated alterations in myelin within BD patients by inhomogeneous magnetization transfer (ihMT), which is sensitive and specific to myelin content. METHODS: Thirty-one BD and 42 healthy controls (HC) were involved. Four MR metrics, i.e., ihMT ratio (ihMTR), pseudo-quantitative ihMT (qihMT), magnetization transfer ratio and pseudo-quantitative magnetization transfer (qMT), were compared between groups using analysis methods based on whole-brain voxel-level and white matter regions of interest (ROI), respectively. RESULTS: The voxel-wise analysis showed significantly inter-group differences of ihMTR and qihMT in the corpus callosum. The ROI-wise analysis showed that ihMTR, qihMT, and qMT values in BD group were significantly lower than that in HC group in the genu and body of corpus callosum, left anterior limb of the internal capsule, left anterior corona radiate, and bilateral cingulum (p < 0.001). And the qihMT in genu of corpus callosum and right cingulum were negatively correlated with depressive symptoms in BD group. LIMITATIONS: This study is based on cross-sectional data and the sample size is limited. CONCLUSION: These findings suggest the reduced myelin content of anterior midline structure in the bipolar patients, which might be a critical pathophysiological feature of BD.

Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning.

The present study aims to identify suicide risks in major depressive disorders (MDD) patients from structural MRI (sMRI) data using deep learning. In this paper, we collected the sMRI data of 288 MDD patients, including 110 patients with suicide ideation (SI), 93 patients with suicide attempts (SA), and 85 patients without suicidal ideation or attempts (NS). And we developed interpretable deep neural network models to classify patients in three tasks including SA-versus-SI, SA-versus-NS, and SI-versus-NS, respectively. Furthermore, we interpreted the models by extracting the important features that contributed most to the classification, and further discussed these features or ROI/brain regions.

Unbalanced amygdala communication in major depressive disorder.

BACKGROUND: Previous studies suggested an association between functional alteration of the amygdala and typical major depressive disorder (MDD) symptoms. Examining whether and how the interaction between the amygdala and regions/functional networks is altered in patients with MDD is important for understanding its neural basis. METHODS: Resting-state functional magnetic resonance imaging data were recorded from 67 patients with MDD and 74 age- and sex-matched healthy controls (HCs). A framework for large-scale network analysis based on seed mappings of amygdala sub-regions, using a multi-connectivity-indicator strategy (cross-correlation, total interdependencies (TI), Granger causality (GC), and machine learning), was employed. Multiple indicators were compared between the two groups. The altered indicators were ranked in a supporting-vector machine-based procedure and associated with the Hamilton Rating Scale for Depression scores. RESULTS: The amygdala connectivity with the default mode network and ventral attention network regions was enhanced and that with the somatomotor network, dorsal frontoparietal network, and putamen regions in patients with MDD was reduced. The machine learning analysis highlighted altered indicators that were most conducive to the classification between the two groups. LIMITATIONS: Most patients with MDD received different pharmacological treatments. It is difficult to illustrate the medication state's effect on the alteration model because of its complex situation. CONCLUSION: The results indicate an unbalanced interaction model between the amygdala and functional networks and regions essential for various emotional and cognitive functions. The model can help explain potential aberrancy in the neural mechanisms that underlie the functional impairments observed across various domains in patients with MDD.

Suicide risk stratification among major depressed patients based on a machine learning approach and whole-brain functional connectivity.

BACKGROUND: Suicide risk stratification and individual-level prediction among major depressive disorder (MDD) is important but unrecognized. Here, we construct models to detect suicidality in MDD using machine learning (ML) and whole-brain functional connectivity (FC). METHODS: A cross-sectional assessment was conducted on 200 subjects, including 126 MDD with high suicide risk (HSR; 73 patients with suicidal ideation [SI], 53 patients with suicidal attempts [SA]), 36 patients with low suicide risk (LSR) and 38 healthy controls (HCs). Whole-brain FC features were calculated, the least absolute shrinkage and selection operator (LASSO) method was used for feature selection. A support vector machine (SVM) was performed to build models to distinguish MDD from HCs, and for suicide risk stratification among MDD. Leave-one-out cross-validation (LOOCV) was performed for validation. RESULTS: The models constructed using SVM on whole-brain FC had powerful classification efficiency in screening MDD from HCs (accuracy = 88.50 %), and in suicide risk stratification among MDD patients (with accuracy = 84.56 % and 74.60 % in classifying patients with HSR or LSR, and SA or SI, respectively). Subsequent analysis demonstrated that intra-network dysconnectivity in the sensorimotor network and inter-network dysconnectivity between the default and dorsal attention network could characterize HSR and SA in MDD, separately. LIMITATIONS: This study was a single center cohort study without external validation. CONCLUSION: These findings indicate ML approaches are useful in suicide risk stratification among MDD based on whole-brain FC, which may help to identify individuals with different suicide risks in MDD and provide an individual-level prediction.

Enhanced putamen functional connectivity underlies altered risky decision-making in age-related cognitive decline.

Risky decision-making is critical to survival and development, which has been compromised in elderly populations. However, the neural substrates of altered financial risk-taking behavior in aging are still under-investigated. Here we examined the intrinsic putamen network in modulating risk-taking behaviors of Balloon Analogue Risk Task in healthy young and older adults using resting-state fMRI. Compared with the young group, the elderly group showed significantly different task performance. Based on the task performance, older adults were further subdivided into two subgroups, showing young-like and over-conservative risk behaviors, regardless of cognitive decline. Compared with young adults, the intrinsic pattern of putamen connectivity was significantly different in over-conservative older adults, but not in young-like older adults. Notably, age-effects on risk behaviors were mediated via the putamen functional connectivity. In addition, the putamen gray matter volume showed significantly different relationships with risk behaviors and functional connectivity in over-conservative older adults. Our findings suggest that reward-based risky behaviors might be a sensitive indicator of brain aging, highlighting the critical role of the putamen network in maintaining optimal risky decision-making in age-related cognitive decline.

Shared and specific neurobiology in bipolar disorder and unipolar disorder: Evidence based on the connectome gradient and a transcriptome-connectome association study.

BACKGROUND: Distinguishing bipolar disorder (BD) and unipolar disorder (UD) remains challenging. To identify the common and diagnosis-specific neuropathological alterations and their potential molecular mechanisms in patients with UD and BD (with a current depressive episode). METHODS: Resting-state functional magnetic resonance imaging was obtained from 279 participants (95 BD patients, 107 UD patients and 77 health controls). Connectome gradients analysis was performed to explore the shared and diagnosis-specific gradient alterations in BD and UD. The Allen Human Brain Atlas data was used to explore the potential gene mechanisms of the gradient alterations. RESULTS: BD and UD had shared hierarchical disorganisation, including downgrading and contraction from the unimodal sensory networks (vision and sensorimotor) to the transmodal cognitive networks (limbic, frontoparietal, dorsal attention, and default) (all P < 0.05, FDR corrected) in gradient 1 and gradient 2. The BD patients had specific connectome gradient dysfunction in the subcortical network. Moreover, the hierarchical disorganisation was closely correlated with profiles of gene expression specific to the neuroglial cells in the prefrontal cortex in BD and UD, while the most correlated gene ontology biological processes and function were concentrated in synaptic signalling, calcium ion binding, and transmembrane transporter activity. CONCLUSION: These findings reveal the shared and diagnosis-specific neurobiological mechanism underlying BD and UD patients, which advances our understanding of the neuromechanisms of these disorders.

Microstructural deficits of the thalamus in major depressive disorder.

Macroscopic structural abnormalities in the thalamus and thalamic circuits have been implicated in the neuropathology of major depressive disorder. However, cytoarchitectonic properties underlying these macroscopic abnormalities remain unknown. Here, we examined systematic deficits of brain architecture in depression, from structural brain network organization to microstructural properties. A multi-modal neuroimaging approach including diffusion, anatomical and quantitative MRI was used to examine structural-related alternations in 56 patients with depression compared with 35 age- and sex-matched controls. The seed-based probabilistic tractography showed multiple alterations of structural connectivity within a set of subcortical areas and their connections to cortical regions in patients with depression. These subcortical regions included the putamen, thalamus and caudate, which are predominantly involved in the limbic-cortical-striatal-pallidal-thalamic network. Structural connectivity was disrupted within and between large-scale networks, including the subcortical network, default-mode network and salience network. Consistently, morphometric measurements, including cortical thickness and voxel-based morphometry, showed widespread volume reductions of these key regions in patients with depression. A conjunction analysis identified common structural alternations of the left orbitofrontal cortex, left putamen, bilateral thalamus and right amygdala across macro-modalities. Importantly, the microstructural properties, longitudinal relaxation time of the left thalamus was increased and inversely correlated with its grey matter volume in patients with depression. Together, this work to date provides the first macro-micro neuroimaging evidence for the structural abnormalities of the thalamus in patients with depression, shedding light on the neuropathological disruptions of the limbic-cortical-striatal-pallidal-thalamic circuit in major depressive disorder. These findings have implications in understanding the abnormal changes of brain structures across the development of depression.

Identification of suicidality in patients with major depressive disorder via dynamic functional network connectivity signatures and machine learning.

Major depressive disorder (MDD) is a severe brain disease associated with a significant risk of suicide. Identification of suicidality is sometimes life-saving for MDD patients. We aimed to explore the use of dynamic functional network connectivity (dFNC) for suicidality detection in MDD patients. A total of 173 MDD patients, including 48 without suicide risk (NS), 74 with suicide ideation (SI), and 51 having attempted suicide (SA), participated in the present study. Thirty-eight healthy controls were also recruited for comparison. A sliding window approach was used to derive the dFNC, and the K-means clustering method was used to cluster the windowed dFNC. A linear support vector machine was used for classification, and leave-one-out cross-validation was performed for validation. Other machine learning methods were also used for comparison. MDD patients had widespread hypoconnectivity in both the strongly connected states (states 2 and 5) and the weakly connected state (state 4), while the dysfunctional connectivity within the weakly connected state (state 4) was mainly driven by suicidal attempts. Furthermore, dFNC matrices, especially the weakly connected state, could be used to distinguish MDD from healthy controls (area under curve [AUC] = 82), and even to identify suicidality in MDD patients (AUC = 78 for NS vs. SI, AUC = 88 for NS vs. SA, and AUC = 74 for SA vs. SI), with vision-related and default-related inter-network connectivity serving as important features. Thus, the dFNC abnormalities observed in this study might further improve our understanding of the neural substrates of suicidality in MDD patients.

Grey Matter Hypertrophy and Atrophy in Early-Blind Adolescents: A Surface-Based Morphometric Study.

Objective: This study is aimed at exploring the regional changes in brain cortical morphology (thickness, volume, and surface area) in the early-blind adolescents (EBAs) by using the surface-based morphometric (SBM) method. Methods: High-resolution structural T1-weighted images (T1WI) of 23 early-blind adolescents (EBAs) and 21 age- and gender-matched normal-sighted controls (NSCs) were acquired. Structural indices, including cortical thickness (CT), cortical volume (CV), and surface area (SA), were analyzed by using FreeSurfer software, and the correlations between structural indices and the blindness duration were computed by Pearson correlation analysis. Results: Compared to controls, EBAs had significantly reduced CV and SA mainly in the primary visual cortex (V1) and decreased CV in the left vision-related cortices (r-MFC). There were no regions that EBAs had a significantly larger CV or SA than NSCs. EBAs had significantly increased CT in the V1 and strongly involved the visual cortex (right lateral occipital gyrus, LOG.R) and the left superior temporal gyrus (STG.L), while it had decreased CT in the left superior parietal lobule (SPL.L) and the right lingual gyrus (LING.R). Additionally, no correlation was found between cortical morphometric measures and clinical variables in the EBA group. Conclusions: SBM is a useful method for detecting human brain structural abnormalities in blindness. The results showed that these structural abnormalities in the visual cortex and visual-related areas outside the occipital cortex in the EBAs not only may be influenced by neurodevelopment, degeneration, plasticity, and so on but also involved the interaction of these factors after the early visual deprivation.

PAD4-dependent citrullination of nuclear translocation of GSK3ß promotes colorectal cancer progression via the degradation of nuclear CDKN1A.

Peptidylarginine deiminase 4 (PAD4), a Ca2+-dependent enzyme, catalyzes the conversion of arginine to citrulline and has been strongly associated with many malignant tumors. However, the molecular mechanisms of PAD4 in the development and progression of colorectal cancer (CRC) remain unclearly defined. In our study, PAD4 expression was increased in CRC tissues and cells, and was closely related to tumor size, lymph node metastasis. Moreover, the transcription factor KLF9 directly bound to PADI4 gene promoter, leading to overexpression of PAD4 in CRC cells, which augmented cell growth and migration. We revealed that PAD4 interacted with and citrullinated glycogen synthase kinase-3ß (GSK3ß) in CRC cells, and GSK3ß Arg-344 was the dominating PAD4-citrullination site. Furthermore, IgL2 and catalytic domains of PAD4 directly bound to the kinase domain of GSK3ß in CRC cells. Mechanistically, PAD4 promoted the transport of GSK3ß from the cytoplasm to the nucleus, thereby increasing the ubiquitin-dependent proteasome degradation of nuclear cyclin-dependent kinase inhibitor 1 (CDKN1A). Our study is the first to reveal the details of a critical PAD4/GSK3ß/CDKN1A signaling axis for CRC progression, and provides evidence that PAD4 is a potential diagnosis biomarker and therapeutic target in CRC.

Myelin deficits in patients with recurrent major depressive disorder: An inhomogeneous magnetization transfer study.

PURPOSES: The recently developed myelin imaging method, inhomogeneous magnetization transfer (ihMT), is a surrogate measure of myelin content. The goal of the current study was to investigate alterations in myelin integrity in patients with recurrent major depressive disorder (rMDD). METHODS: Fifty-two patients with rMDD (36 female and 16 male) and 42 healthy controls (HC, 29 female and 13 male) were included. Two ihMT indices, quantitative ihMT (qihMT) and quantitative MT (qMT), were estimated from the ihMT data. A 50 white matter atlas was used to extract the regional quantitative values for each subject. The differences in qihMT and qMT values between the rMDD and HC groups were compared by a general linear model. Pearson correlation analyses were conducted to investigate associations between the significantly altered ihMT indices and clinical measures (Hamilton Depression Rating Scale scores and disease duration) in rMDD group. RESULTS: The rMDD group showed significantly lower qihMT values in the fornix, left anterior limb of internal capsule, and left sagittal stratum, and lower qMT values in the fornix and left anterior limb of internal capsule than those of the HC group (p < 0.05, false discovery rate corrected). Both the qihMT and qMT values in the fornix of patients with rMDD were negatively correlated with disease duration (qihMT: r = -0.478, p < 0.001, Bonferroni corrected; qMT: r = -0.433, p = 0.001, Bonferroni corrected). CONCLUSION: Our findings suggested that rMDD is associated with myelin impairment in the fornix, left anterior limb of internal capsule, and left sagittal stratum. In addition, this disruption of myelin integrity in the fornix could be cumulative as the disease progresses.