Experimental Mode-Pairing Measurement-Device-Independent Quantum Key Distribution without Global Phase Locking.

In the past two decades, quantum key distribution networks based on telecom fibers have been implemented on metropolitan and intercity scales. One of the bottlenecks lies in the exponential decay of the key rate with respect to the transmission distance. Recently proposed schemes mainly focus on achieving longer distances by creating a long-arm single-photon interferometer over two communication parties. Despite their advantageous performance over long communication distances, the requirement of phase locking between two remote lasers is technically challenging. By adopting the recently proposed mode-pairing idea, we realize high-performance quantum key distribution without global phase locking. Using two independent off-the-shelf lasers, we show a quadratic key-rate improvement over the conventional measurement-device-independent schemes in the regime of metropolitan and intercity distances. For longer distances, we also boost the key rate performance by 3 orders of magnitude via 304 km commercial fiber and 407 km ultralow-loss fiber. We expect this ready-to-implement high-performance scheme to be widely used in future intercity quantum communication networks.

Inhibiting mitochondrial inflammation through Drp1/HK1/NLRP3 pathway: A mechanism of alpinetin attenuated aging-associated cognitive impairment.

Mitochondrial inflammation triggered by abnormal mitochondrial division and regulated by the Drp1/HK1/NLRP3 pathway is correlated with the progression of aging-associated cognitive impairment (AACI). Alpinetin is a novel flavonoid derived from Zingiberaceae that has many bioactivities such as antiinflammation and anti-oxidation. However, whether alpinetin alleviates AACI by suppressing Drp1/HK1/NLRP3 pathway-inhibited mitochondrial inflammation is still unknown. In the present study, D-galactose (D-gal)-induced aging mice and BV-2 cells were used, and the effects of alpinetin on learning and memory function, neuroprotection and activation of the Drp1/HK1/NLRP3 pathway were investigated. Our data indicated that alpinetin significantly alleviated cognitive dysfunction and neuronal damage in the CA1 and CA3 regions of D-gal-treated mice. Moreover, D-gal-induced microglial activation was markedly reduced by alpinetin by inhibiting the Drp1/HK1/NLRP3 pathway-suppressed mitochondrial inflammation, down-regulating the levels of p-Drp1 (s616), VDAC, NLRP3, ASC, Cleaved-caspase 1, IL-18, and IL-1ß, and up-regulating the expression of HK1. Furthermore, after Drp1 inhibition by Mdivi-1 in vitro, the inhibitory effect of alpinetin on Drp1/HK1/NLRP3 pathway was more evident. In summary, the current results implied that alpinetin attenuated aging-related cognitive deficits by inhibiting the Drp1/HK1/NLRP3 pathway and suppressing mitochondrial inflammation, suggesting that the inhibition of the Drp1/HK1/NLRP3 pathway is one of the mechanisms by which alpinetin attenuates AACI.

The Role of Regulated Programmed Cell Death in Osteoarthritis: From Pathogenesis to Therapy.

Osteoarthritis (OA) is a worldwide chronic disease that can cause severe inflammation to damage the surrounding tissue and cartilage. There are many different factors that can lead to osteoarthritis, but abnormally progressed programmed cell death is one of the most important risk factors that can induce osteoarthritis. Prior studies have demonstrated that programmed cell death, including apoptosis, pyroptosis, necroptosis, ferroptosis, autophagy, and cuproptosis, has a great connection with osteoarthritis. In this paper, we review the role of different types of programmed cell death in the generation and development of OA and how the different signal pathways modulate the different cell death to regulate the development of OA. Additionally, this review provides new insights into the radical treatment of osteoarthritis rather than conservative treatment, such as anti-inflammation drugs or surgical operation.

Ultrasonography and contrast-enhanced ultrasound for activity assessment in 115 patients with carotid involvement of Takayasu arteritis.

OBJECTIVES: To evaluate the efficacy of ultrasound and contrast-enhanced ultrasound (CEUS) in disease activity assessment of Takayasu arteritis (TA) with carotid involvement. METHODS: This is a cohort study of 115 patients of TA with carotid involvement. We investigated correlations between clinical data, sonographic features, and CEUS enhancement at the site most prominent lesion of each patient. Disease activity was assessed by the National Institute of Health Kerr criteria. Sonographic findings were compared with follow-up examinations. CEUS was repeated after a 3-7 months interval in 35 patients to evaluate change of CEUS enhancement after treatment. RESULTS: Extensiveness of CEUS enhancement at most prominent carotid lesions had significant correlations with disease activity by the Kerr criteria (P < .001). The specificity of extensive enhancement for indicating active disease was 95%, while sensitivity was 67%. Patients with active disease showed greater arterial wall thickness and more prominent reduction of arterial wall thickness after treatment. Most of the patients (68%) with subsided active disease after treatment featured decrease of CEUS enhancement. CONCLUSIONS: Extensiveness of enhancement by CEUS and arterial wall thickness by ultrasonography may be useful markers for initial and follow-up assessment of disease activity of TA with common carotid artery involvement.

Rigorous calibration of homodyne detection efficiency for continuous-variable quantum key distribution.

We propose a rigorous calibration method for homodyne detection efficiency, which combines all the factors that affect detection efficiency to calibrate together through the actual homodyne detection. With this method, the transmittance converted from electronic noise in the one-time calibration method of the shot noise can be attributed to the detection inefficiency. Thus, a trusted detection noise-free model for continuous-variable quantum key distribution (CV-QKD) can be established, which simplifies the calibration of shot noise while having the same performance as the trusted detection noise model. We demonstrate this calibration method with a balanced detector based on a transimpedance amplifier. Experimental results show that detection efficiency will be overestimated if the integration factor of the detector is overlooked. The overestimation of the detection efficiency leads to an underestimation of modulation variance and excess noise when the modulation variance is monitored by the balanced detector, which opens security loopholes. Our method may prove a necessary method in the calibration of detection efficiency for CV-QKD.

Dissolved oxygen control strategies for water treatment: a review.

Dissolved oxygen (DO) is one of the most important water quality factors. Maintaining the DO concentration at a desired level is of great value to both wastewater treatment plants (WWTPs) and aquaculture. This review covers various DO control strategies proposed by researchers around the world in the past 20 years. The review focuses on published research related to determination and control of DO concentrations in WWTPs in order to improve control accuracy, save aeration energy, improve effluent quality, and achieve nitrogen removal. The strategies used for DO control are categorized and discussed through the following classification: classical control such as proportional-integral-derivative (PID) control, advanced control such as model-based predictive control, intelligent control such as fuzzy and neural networks, and hybrid control. The review also includes the prediction and control strategies of DO concentration in aquaculture. Finally, a critical discussion on DO control is provided. Only a few advanced DO control strategies have achieved successful implementation, while PID controllers are still the most widely used and effective controllers in engineering practice. The challenges and limitations for a broader implementation of the advanced control strategies are analyzed and discussed.

Field Test of Twin-Field Quantum Key Distribution through Sending-or-Not-Sending over 428 km.

Quantum key distribution endows people with information-theoretical security in communications. Twin-field quantum key distribution (TF-QKD) has attracted considerable attention because of its outstanding key rates over long distances. Recently, several demonstrations of TF-QKD have been realized. Nevertheless, those experiments are implemented in the laboratory, and therefore a critical question remains about whether the TF-QKD is feasible in real-world circumstances. Here, by adopting the sending-or-not-sending twin-field QKD (SNS-TF-QKD) with the method of actively odd parity pairing (AOPP), we demonstrate a field-test QKD over 428 km of deployed commercial fiber and two users are physically separated by about 300 km in a straight line. To this end, we explicitly measure the relevant properties of the deployed fiber and develop a carefully designed system with high stability. The secure key rate we achieved breaks the absolute key rate limit of repeaterless QKD. The result provides a new distance record for the field test of both TF-QKD and all types of fiber-based QKD systems. Our work bridges the gap of QKD between laboratory demonstrations and practical applications and paves the way for an intercity QKD network with measurement-device-independent security.

Experimentally Verified Approach to Nonentanglement-Breaking Channel Certification.

Ensuring the nonentanglement-breaking (non-EB) property of quantum channels is crucial for the effective distribution and storage of quantum states. However, a practical method for direct and accurate certification of the non-EB feature is highly desirable. Here, we propose and verify a realistic source based measurement device independent certification of non-EB channels. Our method is resilient to repercussions on the certification from experimental conditions, such as multiphotons and imperfect state preparation, and can be implemented with an information incomplete set. We achieve good agreement between experimental outcomes and theoretical predictions, which is validated by the expected results of the ideal semiquantum signaling game, and accurately certify the non-EB channels. Furthermore, our approach is highly robust to effects from noise. Therefore, the proposed approach can be expected to play a significant role in the design and evaluation of realistic quantum channels.

Corrigendum to: Negligible effect of vitamin D supplementation on exacerbation in patients with chronic obstructive pulmonary disease: meta-analysis.

[This corrects the article , PMID: 37841773.].

Role of lipid metabolism gene KLF4 in osteoarthritis.

INTRODUCTION: Osteoarthritis (OA) is a common degenerative disease of joints, which can appear in almost any joint of the body. Therefore, the widespread occurrence of this disease has a huge impact on the lives of patients around the world. As an important part of metabolism, lipid metabolism is closely related to the occurrence and development of osteoarthritis. METHOD: We screened UGCG and KLF4 based on weighted co-expression network analysis (WGCNA) and SVM-REF analysis. The data from Gene Expression Omnibus (GEO) and single-cell data verified the expression of these two genes. We analyzed KLF4-related genes and established a diagnosis model of OA related to lipid metabolism through the least absolute shrinkage and selection operator (LASSO) analysis. RT-PCR was used to verify the expression of KLF4 in osteoarthritis. RESULTS: Ten important lipid metabolism related genes (LMRGs) in OA were obtained. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that they are involve in the formation of immune microenvironment in osteoarthritis. CIBERSORT analysis revealed that there were significant differences in the immune microenvironment between osteoarthritis patients and normal controls. RT-PCR results showed that the expression of KLF4 in OA samples was lower than that in normal samples. The diagnostic model can be used to diagnose OA patients well. CONCLUSIONS: Overall, we demonstrated the potential relationship between the abnormal lipid metabolism and the pathological process of OA. Finally, we identified KLF4 as our significant LMRG and constructed a KLF4-related scoring model to accurately diagnose OA. In conclusion, therapy strategies targeting on regulating lipid metabolism may become a key factor in treating OA. Key Points (a) We identified the significant LMRG KLF4 and constructed a novel KLF4-related scoring model for the accuracy diagnosis of OA. (b) The potential relationship between lipid metabolism and the immune microenvironment in OA was demonstrated in our research. (c) The relationship of lipid metabolism and OA has been further improved in our research and provided novel insight for the diagnosis and therapy for OA patients.

Identifying the prognosis implication, immunotherapy response prediction value, and potential targeted compound inhibitors of integrin subunit α3 (ITGA3) in human cancers.

The integrin subunit α3 (ITGA3) is a member of the integrin alpha chain protein family, which could promote progression, metastasis, and invasion in some cancers. Still, its function in the tumor microenvironment (TME), cancer prognosis, and immunotherapy remains unclear. A multifaceted analysis of ITGA3 in pan-cancer utilizing various databases and online web tools revealed ITGA3 was aberrantly expressed in tumor tissues and upregulated in most cancers, which may be related to ITGA3 genomic alterations and methylation modification. In addition, ITGA3 was significantly correlated with the poor or better prognosis of cancer patients, immune-related pathways in hallmark, immune infiltration, and immune checkpoints, revealing a biological function of ITGA3 in the tumor progression, tumor microenvironment, and tumor immunity. We also found that ITGA3 could predict the response to tumor immunotherapy based on cytokine-treated samples and immunotherapy cohorts. ITGA3 may participate in shaping and regulating the tumor microenvironment to affect the tumor immune response, which was a promising immunotherapy response predictive biomarker and potential therapeutic target to work synergistically with cancer immunotherapy to boost the response and efficacy. Finally, potential targeted compound inhibitors and sensitive drugs were screened using databases ConnectivityMap (CMap) and CellMiner, and AutoDock Tools was used for molecular docking.

Ferritin-mediated mitochondrial iron homeostasis is essential for the survival of hematopoietic stem cells and leukemic stem cells.

Iron metabolism plays a crucial role in cell viability, but its relationship with adult stem cells and cancer stem cells is not fully understood. The ferritin complex, responsible for intracellular iron storage, is important in this process. We report that conditional deletion of ferritin heavy chain 1 (Fth1) in the hematopoietic system reduced the number and repopulation capacity of hematopoietic stem cells (HSCs). These effects were associated with a decrease in cellular iron level, leading to impaired mitochondrial function and the initiation of apoptosis. Iron supplementation, antioxidant, and apoptosis inhibitors reversed the reduced cell viability of Fth1-deleted hematopoietic stem and progenitor cells (HSPCs). Importantly, leukemic stem cells (LSCs) derived from MLL-AF9-induced acute myeloid leukemia (AML) mice exhibited reduced Fth1 expression, rendering them more susceptible to apoptosis induced by the iron chelation compared to normal HSPCs. Modulating FTH1 expression using mono-methyl fumarate increased LSCs resistance to iron chelator-induced apoptosis. Additionally, iron supplementation, antioxidant, and apoptosis inhibitors protected LSCs from iron chelator-induced cell death. Fth1 deletion also extended the survival of AML mice. These findings unveil a novel mechanism by which ferritin-mediated iron homeostasis regulates the survival of both HSCs and LSCs, suggesting potential therapeutic strategies for blood cancer with iron dysregulation.

Negligible effect of vitamin D supplementation on exacerbation in patients with chronic obstructive pulmonary disease: meta-analysis.

Introduction: The focus of this meta-analysis was how vitamin D supplementation influences exacerbations in patients with chronic obstructive pulmonary disease (COPD) and vitamin D deficiency (VDD). Materials and methods: Cochrane Library, Web of Science, Embase, and PubMed databases have been systematically searched in an attempt to collect randomized controlled trials related to vitamin D supplementation in COPD patients with VDD published in English available by July 2022. Primary outcome indicators included the mean number of exacerbation and rate of exacerbation. Secondary outcome indicators included forced expiratory volume in the first second (FEV1), FEV1/forced vital capacity (FVC) ratio, and serum 25-hydroxyvitamin D (25(OH)D) concentration. Results: Five studies involving 522 COPD patients with VDD (defined as 25(OH)D < 50 nmol/L) were included, among them 61 were severely deficient in vitamin D (25(OH)D < 25 nmol/L). The results showed that vitamin D supplementation did not decrease the mean number of exacerbation (standardized mean difference (SMD): - 0.10, 95% CI: - 0.29 to 0.09) and the rate of exacerbation (relative risk (RR): 0.89, 95% CI: 0.76 to 1.04, P = 0.179). Also, its effect on FEV1 (SMD: - 0.06, 95% CI: - 0.30 to 0.17) and FEV1/FVC (SMD: -0.10, 95% CI: - 0.48 to 0.27) remained negligible. However, it could increase the serum 25(OH)D concentration (SMD: 2.44, 95 CI%: 2.20 to 2.68, P < 0.001). Conclusions: The effects of vitamin D supplementation on decreasing exacerbation and improving pulmonary function were not significant.

Motor Imagery EEG Decoding Based on Multi-scale Hybrid Networks and Feature Enhancement.

Motor Imagery (MI) based on Electroencephalography (EEG), a typical Brain-Computer Interface (BCI) paradigm, can communicate with external devices according to the brain's intentions. Convolutional Neural Networks (CNN) are gradually used for EEG classification tasks and have achieved satisfactory performance. However, most CNN-based methods employ a single convolution mode and a convolution kernel size, which cannot extract multi-scale advanced temporal and spatial features efficiently. What's more, they hinder the further improvement of the classification accuracy of MI-EEG signals. This paper proposes a novel Multi-Scale Hybrid Convolutional Neural Network (MSHCNN) for MI-EEG signal decoding to improve classification performance. The two-dimensional convolution is used to extract temporal and spatial features of EEG signals and the one-dimensional convolution is used to extract advanced temporal features of EEG signals. In addition, a channel coding method is proposed to improve the expression capacity of the spatiotemporal characteristics of EEG signals. We evaluate the performance of the proposed method on the dataset collected in the laboratory and BCI competition IV 2b, 2a, and the average accuracy is at 96.87%, 85.25%, and 84.86%, respectively. Compared with other advanced methods, our proposed method achieves higher classification accuracy. Then we use the proposed method for an online experiment and design an intelligent artificial limb control system. The proposed method effectively extracts EEG signals' advanced temporal and spatial features. Additionally, we design an online recognition system, which contributes to the further development of the BCI system.

Deep Learning-Enhanced Internet of Things for Activity Recognition in Post-Stroke Rehabilitation.

Wearable sensors provide a more effective means of activity monitoring and management by recording patients' daily activity data for assessing their daily function and rehabilitation progress, as well as providing a convenient and practical solution for human activity recognition (HAR). However, during the motor rehabilitation of stroke patients, sensors provide vast amounts of high-dimensional data that are large and complex. To enhance the accuracy of activity monitoring and identification, as well as address the limitations of real-time processing, data visualization, and tracking in conventional monitoring approaches, it is essential to perform valid data processing and analysis. This paper combines deep learning models to explore the potential relationships and patterns between data to build an intelligent post-stroke rehabilitation system. This paper proposes a novel framework aimed at accurately recognizing activities performed by stroke patients. Our approach leverages a data fusion mechanism based on multiple sensors to construct a fusion tensor and employs a bidirectional long and short-term memory (BiLSTM) network enhanced with an attention mechanism. This network effectively captures temporal patterns and long-term dependencies within the data, resulting in improved performance for wearable sensor-based activity classification. Furthermore, we introduce an enhanced loss function to optimize the learning process. To assess the performance of the proposed model algorithm, two benchmark datasets were employed. These datasets served as the basis for evaluating and comparing the baseline method as well as other proposed methods. The experimental results clearly demonstrated that the proposed model outperformed the compared methods, indicating its superior performance in activity recognition.

Dynamic pruning group equivariant network for motor imagery EEG recognition.

Introduction: The decoding of the motor imaging electroencephalogram (MI-EEG) is the most critical part of the brain-computer interface (BCI) system. However, the inherent complexity of EEG signals makes it challenging to analyze and model them. Methods: In order to effectively extract and classify the features of EEG signals, a classification algorithm of motor imagery EEG signals based on dynamic pruning equal-variant group convolutional network is proposed. Group convolutional networks can learn powerful representations based on symmetric patterns, but they lack clear methods to learn meaningful relationships between them. The dynamic pruning equivariant group convolution proposed in this paper is used to enhance meaningful symmetric combinations and suppress unreasonable and misleading symmetric combinations. At the same time, a new dynamic pruning method is proposed to dynamically evaluate the importance of parameters, which can restore the pruned connections. Results and Discussion: The experimental results show that the pruning group equivariant convolution network is superior to the traditional benchmark method in the benchmark motor imagery EEG data set. This research can also be transferred to other research areas.

The role of exosomes and their enhancement strategies in the treatment of osteoarthritis.

With the increasingly prominent problem of population aging, osteoarthritis (OA), which is closely related to aging, has become a serious illness affecting the lives and health of elderly individuals. However, effective treatments are still lacking. OA is typically considered a low-grade inflammatory state. The inflammatory infiltration of macrophages, neutrophils, T cells, and other cells is common in diseased joints. These cells create the inflammatory environment of OA and are involved in the onset and progression of the disease. Exosomes, a type of complex vesicle containing abundant RNA molecules and proteins, play a crucial role in the physiological and pathological processes of an organism. In comparison to other therapeutic methods such as stem cells, exosomes have distinct advantages of precise targeting and low immunogenicity. Moreover, research and techniques related to exosomes are more mature, indicating a promising future in disease treatment. Many studies have shown that the impact of exosomes on the inflammatory microenvironment directly or indirectly leads to the occurrence of various diseases. Furthermore, exosomes can be helpful in the management of illnesses. This article provides a comprehensive review and update on the research of exosomes, a type of extracellular vesicle, in the treatment of OA by modulating the inflammatory microenvironment. It also combines innovative studies on the modification of exosomes. In general, the application of exosomes in the treatment of OA has been validated, and the introduction of modified exosome technology holds potential for enhancing its therapeutic efficacy.

Effect of multidisciplinary health education based on lifestyle medicine on menopausal syndrome and lifestyle behaviors of menopausal women: A clinical controlled study.

Background: Menopausal women may experience menopausal syndrome and long-term effects caused by low estrogen levels, such as senile dementia and osteoporosis in the elderly. Most menopausal women may have misconceptions about menopause and low use of pharmacological interventions. These misconceptions may damage the quality of life and miss the critical period for preventing senile diseases. Thus, enhancing the awareness of menopausal women regarding psychosocial and physical changes through health education programs was a way to improve positive attitudes toward menopause and make further treatment options. Objectives: This study aimed to evaluate the effect of multidisciplinary health education based on lifestyle medicine on menopausal syndrome and lifestyle behaviors of menopausal women. Methods: The study was conducted in several hospitals in Chongqing, China. The two groups were from different hospitals with similar medical levels in order to reduce information contamination. It was designed as a clinical controlled trial in which the intervention group (n = 100) and control group (n = 87) were matched for age, age at menarche, menopausal symptoms and drug use status at enrollment. Women in the intervention group received multidisciplinary health education based on lifestyle medicine for 2 months while those in the control group received routine outpatient health guidance. Menopausal syndrome, physical activity and dietary status of participants were assessed before and after the intervention. Paired t-tests and Independent-sample t-tests were adopted for comparison within and between groups, respectively, in the normal variables. Wilcoxon signed-rank tests and Mann-Whitney U tests were adopted for comparison within and between group, respectively, in the abnormal variables. Categorical variables were tested using Pearson's χ2. P-value < 0.05 was statistically significant in statistical tests. Results: Post intervention testing indicated that menopausal syndrome of participants was significantly improved in the intervention group compared to the control group (P < 0.001). Between-group comparison showed a significant improvement of weekly energy expenditure of total physical activity (P = 0.001) and participation in exercise (P < 0.001) in the intervention group compared to the control group after the intervention. The dietary status of participants was significantly improved in the intervention group compared to the control group (P < 0.001). In the intervention group, the menopausal syndrome of participants improved more in the hormone drug group than in the non-hormone group (P = 0.007), as did the control group (P = 0.02). In the hormone drug group, the physical activity (P = 0.003) and dietary status (P = 0.001) mproved more in the intervention group than in the control group. Conclusions: The multidisciplinary health education based on lifestyle medicine was effective in improving the menopausal syndrome and healthy lifestyle behaviors of menopausal women. Studies with extended observation period and larger sample size are in need to evaluate the long-term scale-up effects of the multidisciplinary health education.

Effects of Roflumilast on Patients with Chronic Obstructive Pulmonary Disease Treated with Inhaled Corticosteroid/Long-Acting ß2 Agonist: A Meta-analysis.

Objective: Roflumilast is a novel therapeutic drug for chronic obstructive pulmonary disease (COPD). This study was designed to evaluate the efficacy and safety of roflumilast combining inhaled corticosteroid (ICS)/long-acting ß2 agonist (LABA) in treating COPD patients through the meta-analysis. Methods: Randomized controlled trials of roflumilast combining ICS/LABA in treating patients with severe and profound COPD were searched from PubMed, Cochrane Library, and Embase databases from their establishment to February 2022. The quality of included studies was assessed by Cochrane risk bias assessment tool. The main outcomes of these studies should include at least one of the following clinical outcome indicators: forced expiratory volume in one second (FEV1), exacerbation rate, and adverse events (AEs) such as diarrhea, nasopharyngitis, and headache. Results: Six articles were included in the study, including 9,715 patients. Meta-analysis revealed that compared with placebo, roflumilast gained superiority for severe COPD patients treated with ICS/LABA combinations in FEV1 before bronchodilator administration (MD = 46.62, 95% CI (30.69, 62.55), P < 0.00001), FEV1 after bronchodilator administration (MD = 45.62, 95% CI (34.95, 56.28), P < 0.00001), and COPD exacerbation rate (RR = 0.90, 95% CI (0.87, 0.94), P = 0.001). In terms of safety, the incidence of diarrhea, headache, nausea, weight loss, back pain, loss of appetite, and insomnia was notably higher in the roflumilast group than in the placebo group. Conclusion: Roflumilast is suggested to be significantly effective for severe COPD patients with ICS/LABA combination therapy, which reduces the exacerbation rate but also leads to PDE4 inhibitor-related adverse reactions.

Brain Structural Correlates of Dispositional Insight and the Mediation Role of Neuroticism in Young Adults.

Studies on the neural correlates of episodic insight have made significant progress in the past decades. However, the neural mechanisms underlying dispositional insight are largely unknown. In the present study, we recruited forty-four young, healthy adults and performed several analyses to reveal the neural mechanisms of dispositional insight. Firstly, a voxel-based morphometry (VBM) technique was used to explore the structural brain mechanisms of dispositional insight. We found that dispositional insight was significantly and negatively correlated with the regional gray matter volume (rGMV) in the left thalamus (TLM.L), right temporoparietal junction (TPJ.R), and left dorsal medial prefrontal cortex (DMPFC.L). Secondly, we performed a seed-based resting-state functional connectivity (RSFC) analysis to complement the findings of VBM analysis further. The brain regions of TLM.L, DMPFC.L, and TPJ.R were selected as seed regions. We found that dispositional insight was associated with altered RSFC between the DMPFC.L and bilateral TPJ, between the TPJ.R and left dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, DMPFC.L, TPJ.L, right insula, and right cerebellum. Finally, a mediation analysis found that the personality of neuroticism partially mediated the relationship between the brain region of TLM.L and dispositional insight. These findings imply that dispositional insight has a specific functional and structural neural mechanism. The personality of neuroticism may play a pivotal role in the processes of dispositional insight.