Object detection in frame-based vision systems often faces the problem of significant performance degradation under challenging conditions due to the inherent sensing limitations of conventional cameras. Event cameras, with their advantages of high temporal resolution and sparse data output, offer a promising solution for addressing the performance degradation problem. However, due to the asynchronous and sparse nature of event data, event camera–based detection methods generally exhibit lower accuracy than their image-based counterparts. Therefore, effectively fusing data from both event and frame-based cameras represents the main challenge. To this end, this study introduces a hierarchical fusion enhancement network (FENET) designed to achieve more robust object detection through complementary multimodal fusion. First, to address the problem of underutilization of event timescales in conventional dense representations, this study designs an innovative, learnable multi-timescale event preprocessing module. This module generates temporal aggregation frames (TAFs) by leveraging event data from a spectrum of intervals, ranging from standard RGB exposure times down to finer timescales. This approach ensures the comprehensive capture and clear delineation of the target's structure, thereby enhancing the integrity of the visual information. Furthermore, a two-branch adaptive enhanced cross-modal aggregation module (ECAM), which guides the adaptive fusion of features from both modalities by first self-enhancing the features of each, is employed. The main goal of the ECAM is to achieve efficient feature aggregation by combining global context with local spatial information, subsequently using the aggregated features to steer the adaptive fusion process. Finally, by recognizing the scarcity of large-scale, high-quality annotated datasets for event-based object detection, the DSEC-D dataset comprising 60 sequences, with a total of 70,739 images and over 250,000 labels, is manually constructed. Extensive experimental results demonstrate that the proposed FENET can successfully overcome the perceptual limitations of conventional cameras. Notably, the proposed FENET surpasses current RGB-event fusion schemes, achieving an 8.6% improvement in the mAP50 metric and a 3.7% improvement in the mAP50:95 metric over the FRN baseline. We have released the code and the dataset at https://github.com/wkydawang/FENET.

Disorganized thinking is a prominent feature of schizophrenia that becomes persistent in the presence of treatment resistance. Disruption of the default mode network (DMN), which regulates self-referential thinking, is now a well-established feature of schizophrenia. However, we do not know if DMN disruption affects disorganization and contributes to treatment-resistant schizophrenia (TRS). This study investigated the DMN in 48 TRS, 76 non-TRS, and 64 healthy controls (HC) using a spatiotemporal approach with resting-state functional magnetic resonance imaging. We recovered DMN as an integrated network using multivariate group independent component analysis and estimated its loading coefficient (reflecting spatial prominence) and Shannon Entropy (reflecting temporal variability). Additionally, voxel-level analyses were conducted to examine network homogeneity and entropy within the DMN. We explored the relationship between DMN measures and disorganization using regression analysis. TRS had higher spatial loading on population-level DMN pattern, but lower entropy compared to HC. Non-TRS patients showed intermediate DMN alterations, not significantly differing from either TRS or HC. No voxel-level differences were noted between TRS and non-TRS, emphasizing the continuum between the two groups. DMN's loading coefficient was higher in patients with more severe disorganization. TRS may represent the most severe end of a spectrum of spatiotemporal DMN dysfunction in schizophrenia. While excessive spatial contribution of the DMN (high loading coefficient) is specifically associated with disorganization, both excessive spatial contribution and exaggerated temporal stability of DMN are features of schizophrenia that become more pronounced with refractoriness to first-line treatments.

AIM: To assess the alterations in the resting-state function connections between the two cerebral hemispheres in patients with optic neuritis (ON) and healthy controls (HCs). METHODS: A total of 12 ON patients (six males and six females) and 12 HCs (six males and six females) who were highly matched for sex, age, and educational level were recruited. They underwent functional magnetic resonance imaging (fMRI), testing and brain activities were assessed using the degree centrality (DC) method. Correlation analysis between the mean DC values in specific brain areas and behavior performances was analyzed as well. Linear correlations between A anxiety scale (AS) and depression scale (DS) values and DC values in brain regions of patients with ON were also analyzed. RESULTS: The areas that showed a higher DC value in ON patients were the right angular gyrus and bilateral precuneus, while the left insula and left superior temporal gyrus (LSTG) were regions that presented a lower DC value in ON patients. A receiver operating characteristic (ROC) curve analysis confirmed the accuracy of the area under the curve (AUC) assessment. Linear analysis showed anxiety scale (AS) and depression scale (DS) values in the left insula were both negatively correlated with DC values, while best corrected visual acuity logMAR-R (BCVA logMAR-R) showed a negative correlation with DC in the LSTG. CONCLUSION: The study explores altered brain activities of specific regions in patients with ON. The results provide clues for revealing the underlying mechanism of ON development.

AIM: To analyze whether alterations of voxel mirror homology connectivity (VMHC) values, as determined by resting-state functional magnetic resonance imaging (rs-fMRI), occur in cerebral regions of patients with hypertensive retinopathy (HR) and to determine the relationship between VMHC values and clinical characteristics in patients with HR. METHODS: Twenty-one patients with HR and 21 age-matched healthy controls (HCs) were assessed by rs-fMRI scanning. The functional connectivity between the hemispheres of the cerebrum was assessed by measuring VMHC, with the ability of VMHC to distinguish between the HR and HC groups assessed using receiver operating characteristic (ROC) curve analysis. Differences in the demographic and clinical characteristics of the HR and HC groups were analyzed by independent sample t-tests. The relationship between average VMHC in several brain areas of HR patients and clinical features was determined using Pearson correlation analysis. RESULTS: Mean VMHC values of the bilateral cuneus gyrus (BA19), bilateral middle orbitofrontal gyrus (BA47), bilateral middle temporal gyrus (BA39) and bilateral superior medial frontal gyrus (BA9) were lower in the HR than in the HC group. CONCLUSION: VMHC values can predict the development of early HR, prevent the transformation of hypertensive microangiopathy, and provide useful information explaining the changes in neural mechanism associated with HR.

Schizophrenia is associated with widespread gray matter reduction. This is influenced by the underlying connectivity, resulting in covarying patterns of structural changes that are more pronounced in treatment-resistant individuals. However, it remains uncertain whether a distinct network of brain regions, with specific neurotransmitter basis, forms the substrate for treatment resistance in schizophrenia. We investigated the structural covariance networks (SCN) in 198 individuals; 55 with treatment-resistant schizophrenia (TRS) and 79 without TRS (non-TRS) in active symptomatic phase, and 64 healthy controls (HC) using Calhoun’s Source-Based Morphometry. We mapped the putative neurotransmitter basis of the SCNs using a PET-based chemoarchitectural atlas. Twelve independent components (i.e., SCNs) were identified. A prefrontal-limbic SCN had lower gray matter volume (GMV) in TRS compared to HC and non-TRS (F = 7.757, p < 0.001, FDR-corrected). Spatial correlation with chemoarchitectural atlas revealed predominant contributions from serotonergic [5HT1b and 5HT2a], glutamatergic [mGluR5], histaminergic [H3], and opioid [MOR] receptors for this TRS-related SCN (all pspin-permutation < 0.05, FDR-corrected). A different SCN comprised of dorsal fronto-temporal and parieto-occipital regions, not associated with any specific neurotransmitter distribution, exhibited reduced GMV in both TRS and non-TRS groups vs. HC (F = 7.239, p < 0.001, FDR-corrected). Amidst the generic GMV reduction that is shared with non-TRS patients, patients with TRS have specific prefrontal-limbic structural deficits with a unique non-dopaminergic chemoarchitecture. These findings indicate a putative molecular and structural basis for poor treatment response, guiding the development of second- and third-line pharmacotherapies for TRS.

Refractory suicidal command hallucinations in major depressive episode with psychotic features constitute an acute clinical emergency, often unresponsive to multiple antipsychotics and electroconvulsive therapy (ECT), leaving clinicians with limited life-saving options. Stereotactic lesioning, as a last-resort intervention, may have some utility in such case; however, its long-term efficacy and the extent to which it depends on postoperative pharmacotherapy are not yet fully understood. A 20-year-old female with major depressive episode with psychotic features experienced 10–12 daily suicidal command hallucinations (with 4 suicide attempts within 1 week), refractory to 3 antipsychotics (Aripiprazole, Olanzapine, Risperidone) and 12 sessions of ECT (Montgomery-Asberg Depression Rating Scale [MADRS]: 30, Hoffman auditory hallucination score [Hoffman]: 25). Stereotactic bilateral lesioning of the anterior limb of the internal capsule and cingulate gyrus (SALIC-CG) resulted in a marked alleviation of symptoms within 1 week (MADRS: 7, Hoffman: 0). Notably, symptoms recurred 1 month postoperatively following antipsychotic discontinuation (MADRS: 22, Hoffman: 20) but resolved rapidly upon reintroducing Risperidone, with sustained remission at 6 months (MADRS: 6, Hoffman: 0) under continuous pharmacotherapy. This case offers preliminary evidence that stereotactic lesioning may act as a key intervention for alleviating symptoms in patients with psychotic major depressive episode—specifically those with intractable suicidal command hallucinations that do not respond to all conventional treatments. Critically, it underscores that postoperative long-term antipsychotic maintenance is not merely adjunctive but essential to preserve surgical benefits, establishing a “surgery + long-term pharmacotherapy” paradigm with direct implications for managing high-risk refractory cases. It is not a clinical trial, clinical trial number: not applicable.

Brain functional hypernetworks that can characterize the complex and multivariate interactions among multiple brain regions have been widely used in the diagnosis and prediction of brain diseases. However, there are few studies on the structure and dynamics of brain functional hypernetworks. Such studies can help to explore how the important functional features of brain functional hypernetworks characterize the working and pathological mechanisms of the human brain. Therefore, this article introduces the hypernetwork null model to analyze the dependencies between the features of interest. Specifically, first, based on the original brain functional hypernetwork, this article proposed the optimized hyper dK-series algorithm with hyperedges to construct null models that preserved the different node attributes and hyperedge attributes of the original brain functional hypernetwork, respectively. Next, based on the original hypernetwork model and the null model, multiple node attributes and hyperedge attributes were respectively introduced. Then, the level of similarity and correlation between the topological attributes of the original brain functional hypernetwork and the topological attributes of the brain functional hypernetwork null model were calculated to analyze the dependencies between the features of interest. The results showed that there were differences in the level of dependence between the features of interest. Node degree is the main dependency attribute for multiple metrics. Hyperedge degree, node degree-dependent redundancy coefficient, and hyperedge degree-dependent redundancy coefficient are partial dependency attributes for some metrics. The dependency attributes and level of dependency are the same for the hypernetwork clustering coefficients—HCC2 and HCC3. This indicates that the node degree is redundant with respect to other attributes, while the hyperedge degree, node degree-dependent redundancy coefficient, and hyperedge degree-dependent redundancy coefficient perhaps contain other topology information. In addition, there is redundancy between HCC2 and HCC3. Therefore, the effects of these redundant attributes need to be considered when performing network analysis.

Background: Schizophrenia is a complex disorder characterized by disruptions in cognition, behavior, and emotions. Extensive research has uncovered alterations in a single modality (either the brain structure or function) in schizophrenia. However, the limitation is that a single modality could not offer a synchronous result between the brain structure and function because of different samples. Here, a multiparametric approach is essential to understand the common and distinct alterations between the brain structure and function in schizophrenia. Methods: We analyzed structural and functional magnetic resonance imaging data from 146 participants (72 individuals with schizophrenia and 74 healthy controls). Individual morphological similarity and functional connectivity gradients were computed using a nonlinear dimensionality reduction technique with diffusion map embedding. Furthermore, to understand how the alterations may be related to genetic underpinnings, gene expression enrichment analyses were conducted using Allen Brain Human Atlas and GOrilla. Results: Compared with controls, patients with schizophrenia had reduced scores on the principal functional gradient of the visual network and elevated scores on the principal functional gradient of the limbic network, the frontoparietal control network, and the default mode network. Additionally, the main functional gradient in individuals with schizophrenia showed compression along the primary axis compared to the healthy control group. These changes were linked to genes involved in synaptic signaling and neuronal development. Conclusions: These results indicate connectome gradient dysfunction in schizophrenia and its linkage with gene expression profiles, supporting widespread network-level abnormalities. The integration of neuroimaging provides insight into the neurobiological underpinnings and potential biomarkers for treatment evaluation in this disorder.

The primate cerebral cortex, characterized by its complex structural geometry, underlies advanced cognitive functions and represents a defining feature distinguishing primates from other mammals. However, cross-species patterns of cortical geometry and the links between human cortical geometry and transcriptional architecture remain poorly understood. We developed a geometry-based cross-species cortical alignment framework to systematically investigate the similarities and differences in structural connectivity and cortical expansion characteristics among macaques, chimpanzees, and humans, and additionally explored the transcriptional underpinnings of human cortical geometry. Our analysis revealed conserved spatial patterns of cortical geometric features across species, providing the foundation for constructing a cross-species structural common space to support the alignment framework. We found that primary sensory, somatomotor, and face-selective regions exhibited high structural connectivity similarity across species, whereas prefrontal and parietal association cortices displayed significant divergence. We also identified disproportionate cortical expansion in the default mode network, with a consistent expansion trend across different evolutionary lineages in primates. Furthermore, neuroimage-transcription analysis indicated that cortical geometric features were correlated with transcriptional profiles enriched in neurodevelopmental and connectivity-related pathways. These results highlight a conserved yet hierarchically differentiated organization of the cerebral cortex in primates, providing new insights into the biological basis of human brain evolution.

Neuroimaging studies have revealed disturbances in brain functional connectivity (FC) after one night of sleep deprivation (SD). These researches explored the alterations of FC using classical regions of interest (ROI)-based analysis or functional connectivity density. However, these methods need for a priori information about the selected ROIs and a specific correlation threshold to define a connection between two ROIs or voxels, which may bring inconsistent results. In the present study, we adopted a data-driven, whole brain voxel-based graph-theoretical approach, intrinsic connectivity distribution (ICD) analysis, to examine changes of brain connectivity after SD in 52 normal young subjects without any prior knowledge. The cross-hemisphere ICD (ch-ICD) analysis was also performed to discover the effect of SD on cerebral lateralization. We found that sleep-deprived subjects showed significant reduced ICD in default mode network (DMN) and limbic network, and increased ICD in sensorimotor network. Furthermore, after SD, the ICD in the right precuneus showed significant correlation with psychomotor vigilance test (PVT) performance following the stepwise regression analysis after Bonferroni correction (ICD = 0.43 - 0.62*10% fast reaction time + 0.31*the standard deviation of reaction time, p = 0.0012). Follow-up seed-based FC analyses in the right precuneus revealed decreased FC to regions in DMN, visual network, ventral attentional network and frontal-parietal network. Nevertheless, no striking difference of ch-ICD was found following SD. In conclusion, these findings suggested that DMN, especially precuneus may be hubs of FC disturbances associated with vigilance after SD, and may provide new insights into the intervention for SD.

Background: Major depressive disorder (MDD) and schizophrenia (SZ) are serious psychiatric disorders that, despite exhibiting different diagnostic criteria, exhibit significant overlap regarding the biological and clinical features of affected patients. While prior evidence has shown that interhemispheric functional connectivity (FC) is abnormal in MDD and SZ, the particular similarities and differences that unify and characterize MDD and SZ regarding these interhemispheric FC patterns remain to be characterized. This study was thus designed to conduct an in-depth analysis of MDD- and SZ-related patterns of interhemispheric FC. Methods: This study enrolled MDD patients, SZ patients, and normal control (NC) individuals (n = 36 each). Resting -state functional MRI (rs-fMRI) studies of these patients were conducted, after which voxel-mirrored homotopic connectivity (VMHC) was used to analyze the preprocesses rs-fMRI data. The VMHC values in these different values were then compared through one-way ANOVAs and post hoc analyses. Results: Significant differences were observed in both the striatum and middle frontal gyrus (MFG) when comparing these three groups. Through pairwise comparisons, MDD patients but not SZ patients exhibited reduced MFG VMHC values relative to the NC individuals. Conversely, striatum VMHC values significantly increased in SZ patients relative to NC individuals and MDD patients. Conclusion: These results support the interhemispheric functional disconnection hypothesis as a basis for the pathogenesis of MDD and SZ. The observed differences in interhemispheric FC in the MFG and striatum of MDD and SZ patients will offer a neuroimaging basis that can aid in the differential diagnosis of these debilitating conditions.

The anterior cingulate cortex (ACC) is a heterogeneous region of the brain's limbic system that regulates cognitive and emotional processing, and is frequently implicated in schizophrenia. This study aims to characterize resting-state functional connectivity (rsFC) profiles of three subregions of ACC in patients with first-episode schizophrenia and healthy controls. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were collected from 60 first-episode schizophrenia (FES) patients and 60 healthy controls (HC), and the subgenual ACC (sgACC), pregenual ACC (pgACC), and dorsal ACC (dACC) were selected as seed regions from the newest automated anatomical labeling atlas 3 (AAL3). Seed-based rsFC maps for each ACC subregion were generated and compared between the two groups. The results revealed that compared to the HC group, the FES group showed higher rsFC between the pgACC and bilateral lateral orbitofrontal cortex (lOFC), and lower rsFC between the dACC and right posterior OFC (pOFC), the medial prefrontal gyrus (MPFC), and the precuneus cortex (PCu). These findings point to a selective functional dysconnectivity of pgACC and dACC in schizophrenia and provide more accurate information about the functional role of the ACC in this disorder.

AIM:To study functional brain abnormalities in patients with eye trauma (ET) and to discuss the pathophysiological mechanisms of ET. METHODS:Totally 31 ET patients and 31 healthy controls (HCs) were recruited. The age, gender, and educational background characteristics of the two groups were similar. After functional magnetic resonance imaging (fMRI) scanning, the subjects' spontaneous brain activity was evaluated with the functional connectivity (FC) method. Receiver operating characteristic (ROC) curve analysis was used to classify the data. Pearson's correlation analysis was used to explore the relationship between FC values in specific brain regions and clinical behaviors in patients with ET. RESULTS:Significantly increased FC between several regions was identified including the medial prefrontal cortex (MPFC) and left hippocampus formations (HF), the MPFC and left inferior parietal lobule (IPL), the left IPL and left medial temporal lobe (MTL), the left IPL and right MTL, and the right IPL and left MTL. No decreased region-to-region connectivity was detected in default mode network (DMN) sub-regions in patients with ET. Compared with HCs, ET patients exhibited significantly increased FC between several paired DMN regions, as follows: posterior cingulate cortex (PCC) and right HF (HF.R, t=2.196, P=0.032), right inferior parietal cortices (IPC.R) and left MTL (MTL.L, t=2.243, P=0.029), and right MTL (MTL.R) and HF.R (t=2.236, P=0.029). CONCLUSION:FC values in multiple brain regions of ET patients are abnormal, suggesting that these brain regions in ET patients may be dysfunctional, which may help to reveal the pathophysiological mechanisms of ET.

Background Resting-state functional magnetic resonance imaging (fMRI) studies have shown altered brain activity in major depressive disorder (MDD) and schizophrenia (SZ). Despite differing diagnoses, SZ and MDD share similar features. However, functional brain activity similarities and differences between SZ and MDD remain unclear. Methods Participants with MDD, SZ, and normal controls (n=36 each) underwent resting-state fMRI scans. Amplitude of low-frequency fluctuations (ALFF) was used to analyze the preprocessed rs-fMRI data. One-way ANOVAs and post hoc analyses compared ALFF values in different brain regions. Pearson correlation analysis examined associations with clinical symptoms. Results Comparison among the three groups revealed significant differences in ALFF values within the left superior parietal cortex (L-SPC) and bilateral striatum. Through pairwise comparisons, patients with SZ but not patients with MDD were found to exhibit increased striatum ALFF values relative to NC individuals, but decreased in MDD. Meanwhile, L-SPC ALFF values were significantly increased in patients with SZ relative to both normal control individuals and patients with MDD, while no differences in these values were observed between the normal control and MDD groups. The Pearson correlation analyses showed significant positive correlations between ALFF in the striatum and PANSS positive score, but no significant correlation with other symptom severity in SZ and MDD. Conclusion These findings support the hypothesis of alterations in brain functional activity as a fundamental component of the pathogenesis of MDD and SZ. The observed differences in functional brain activity in the superior parietal cortex and striatum between MDD and SZ provide a neuroimaging basis that can contribute to the differential diagnosis of these debilitating conditions.

BACKGROUND:The basal ganglia are a complex of interconnected subcortical structures located beneath the mammalian cerebral cortex. The degeneration of dopaminergic neurons in the basal ganglia is the primary pathological feature of Parkinson's disease. Due to a lack of integrated analysis of multiomics datasets across multiple basal ganglia brain regions, very little is known about the regulatory mechanisms of this area. FINDINGS:We utilized high-throughput transcriptomic and epigenomic analysis to profile over 270,000 single-nucleus cells to create a cellular atlas of the basal ganglia, characterizing the cellular composition of 4 regions of basal ganglia in adult macaque brain, including the striatum, substantia nigra (SN), globus pallidum, and amygdala. We found a distinct epigenetic regulation on gene expression of neuronal and nonneuronal cells across regions in basal ganglia. We identified a cluster of SN-specific astrocytes associated with neurodegenerative diseases and further explored the conserved and primate-specific transcriptomics in SN cell types across human, macaque, and mouse. Finally, we integrated our epigenetic landscape of basal ganglia cells with human disease heritability and identified a regulatory module consisting of candidate cis-regulatory elements that are specific to medium spiny neurons and associated with schizophrenia. CONCLUSIONS:In general, our macaque basal ganglia atlas provides valuable insights into the comprehensive transcriptome and epigenome of the most important and populous cell populations in the macaque basal ganglia. We have identified 49 cell types based on transcriptomic profiles and 47 cell types based on epigenomic profiles, some of which exhibit region specificity, and characterized the molecular relationships underlying these brain regions.

To evaluate the dynamic evolution process of overall brain health in liver transplantation (LT) recipients, we employed a deep learning–based neuroanatomic biomarker to measure longitudinal changes of brain structural patterns before and 1, 3, and 6 months after surgery. Because of the ability to capture patterns across all voxels from a brain scan, the brain age prediction method was adopted. We constructed a 3D-CNN model through T1-weighted MRI of 3609 healthy individuals from 8 public datasets and further applied it to a local dataset of 60 LT recipients and 134 controls. The predicted age difference (PAD) was calculated to estimate brain changes before and after LT, and the network occlusion sensitivity analysis was used to determine the importance of each network in age prediction. The PAD of patients with cirrhosis increased markedly at baseline (+ 5.74 years) and continued to increase within one month after LT (+ 9.18 years). After that, the brain age began to decrease gradually, but it was still higher than the chronological age. The PAD values of the OHE subgroup were higher than those of the no-OHE, and the discrepancy was more obvious at 1-month post-LT. High-level cognition-related networks were more important in predicting the brain age of patients with cirrhosis at baseline, while the importance of primary sensory networks increased temporarily within 6-month post-LT. The brain structural patterns of LT recipients showed inverted U-shaped dynamic change in the early stage after transplantation, and the change in primary sensory networks may be the main contributor. • The recipients’ brain structural pattern showed an inverted U-shaped dynamic change after LT. • The patients’ brain aging aggravated within 1 month after surgery, and the subset of patients with a history of OHE was particularly affected. • The change of primary sensory networks is the main contributor to the change in brain structural patterns.

Schizophrenia and depression are psychiatric disorders with overlapping clinical and biological features. This study aimed to identify common and distinct neuropathological mechanisms in schizophrenia and depression patients using resting-state functional magnetic resonance imaging (fMRI). The study included 28 patients with depression (DEP), 29 patients with schizophrenia (SCH), and 30 healthy control subjects (HC). Intrinsic connectivity contrast (ICC) was used to identify functional connectivity (FC) changes at the whole-brain level, and significant ICC differences were found in the bilateral orbitofrontal cortex (OFC) across all three groups. Further seed-based FC analysis indicated that compared to the DEP and HC groups, the FC between bilateral OFC and medial prefrontal cortex (MPFC), right anterior insula, and right middle frontal gyrus were significantly lower in the SCH group. Additionally, the FC between right OFC and left thalamus was decreased in both patient groups compared to the HC group. Correlation analysis showed that the FC between OFC and MPFC was positively correlated with cognitive function in the SCH group. These findings suggest that OFC connectivity plays a critical role in the pathophysiology of schizophrenia and depression and may provide new insights into the potential neural mechanisms underlying these two disorders.

To explore the salience network(SN) functional alterations in schizophrenia and depression, resting-state functional magnetic resonance imaging (rs-fMRI) data from 29 patients with schizophrenia (SCH), 28 patients with depression (DEP) and 30 healthy controls(HC) were obtained. The SN was derived from data-driven group independent component analysis (gICA). ANCOVA and post hoc tests were performed to discover the FC differences of SN between groups. The ANCOVA demonstrated a significant group effect in FC with right inferior and middle temporal gyrus (ITG and MTG), left caudate, and right precentral gyrus. Post-hoc analyses revealed an opposite altered FC pattern between SN and right ITG and MTG for both patient groups. The DEP group showed a reduced FC between SN and right ITG and MTG compared with HC whereas the SCH group showed an increased FC. In addition, the SCH group showed decreased FC between SN and left caudate, and enhanced FC between SN and right precentral gyrus compared to the other two groups. Our findings suggest distinct FC of SN in schizophrenia and depression, supporting that the resting-state FC pattern of SN may be a transdiagnostic difference between depression and schizophrenia and may play a critical role in the pathogenesis of these two disorders.

铁死亡(ferroptosis)是2012年新发现的一种非凋亡的细胞死亡形式,其实质是依赖铁离子的活性氧(reactive oxygen species,ROS)和脂质氢过氧化物蓄积导致的线粒体形态改变和细胞膜磷脂过氧化损伤.铁死亡与许多肾脏疾病的病理生理进程密切相关.然而铁死亡参与肾脏疾病损伤的分子生物学机制尚缺乏系统和深入的认识.针对铁死亡的调控机制、研究进展及其在肾脏相关疾病中的作用作一综述,以期为肾脏疾病的治疗提供新思路、新靶点.

OBJECTIVE:Some static network studies have suggested that the community structure in the brains of ADHD patients is altered. However, ADHD is now increasingly regarded as a disorder of neural dynamics, but the dynamic reconstruction of brain communities in ADHD patients is far from being understood.METHOD:Forty-two ADHD patients and fifty healthy controls participated in this study. We constructed a multilayer network model and calculated several metrics for quantifying community reconstruction at different levels. Results: Regardless of the level of research, the flexibility and cohesion of the ADHD patients were significantly higher than those of controls. In addition, the frontal lobe of ADHD patients presented a phenomenon of increasing peripheral areas and decreasing core areas.CONCLUSION:Our results indicate that ADHD patients do have abnormalities in dynamic community structure. These evidences provide a new perspective that advances the present understanding of the dynamic organizational principles of communities in ADHD.