Development of an α-synuclein positron emission tomography tracer for imaging synucleinopathies.

Synucleinopathies are characterized by the accumulation of α-synuclein (α-Syn) aggregates in the brain. Positron emission tomography (PET) imaging of synucleinopathies requires radiopharmaceuticals that selectively bind α-Syn deposits. We report the identification of a brain permeable and rapid washout PET tracer [18F]-F0502B, which shows high binding affinity for α-Syn, but not for Aß or Tau fibrils, and preferential binding to α-Syn aggregates in the brain sections. Employing several cycles of counter screenings with in vitro fibrils, intraneuronal aggregates, and neurodegenerative disease brain sections from several mice models and human subjects, [18F]-F0502B images α-Syn deposits in the brains of mouse and non-human primate PD models. We further determined the atomic structure of the α-Syn fibril-F0502B complex by cryo-EM and revealed parallel diagonal stacking of F0502B on the fibril surface through an intense noncovalent bonding network via inter-ligand interactions. Therefore, [18F]-F0502B is a promising lead compound for imaging aggregated α-Syn in synucleinopathies.

Functional overlap between the mammalian Sar1a and Sar1b paralogs in vivo.

Proteins carrying a signal peptide and/or a transmembrane domain enter the intracellular secretory pathway at the endoplasmic reticulum (ER) and are transported to the Golgi apparatus via COPII vesicles or tubules. SAR1 initiates COPII coat assembly by recruiting other coat proteins to the ER membrane. Mammalian genomes encode two SAR1 paralogs, SAR1A and SAR1B. While these paralogs exhibit ~90% amino acid sequence identity, it is unknown whether they perform distinct or overlapping functions in vivo. We now report that genetic inactivation of Sar1a in mice results in lethality during midembryogenesis. We also confirm previous reports that complete deficiency of murine Sar1b results in perinatal lethality. In contrast, we demonstrate that deletion of Sar1b restricted to hepatocytes is compatible with survival, though resulting in hypocholesterolemia that can be rescued by adenovirus-mediated overexpression of either SAR1A or SAR1B. To further examine the in vivo function of these two paralogs, we genetically engineered mice with the Sar1a coding sequence replacing that of Sar1b at the endogenous Sar1b locus. Mice homozygous for this allele survive to adulthood and are phenotypically normal, demonstrating complete or near-complete overlap in function between the two SAR1 protein paralogs in mice. These data also suggest upregulation of SAR1A gene expression as a potential approach for the treatment of SAR1B deficiency (chylomicron retention disease) in humans.

Aging and comprehensive molecular profiling in acute myeloid leukemia.

Acute myeloid leukemia (AML) is an aging-related and heterogeneous hematopoietic malignancy. In this study, a total of 1,474 newly diagnosed AML patients with RNA sequencing data were enrolled, and targeted or whole exome sequencing data were obtained in 94% cases. The correlation of aging-related factors including age and clonal hematopoiesis (CH), gender, and genomic/transcriptomic profiles (gene fusions, genetic mutations, and gene expression networks or pathways) was systematically analyzed. Overall, AML patients aged 60 y and older showed an apparently dismal prognosis. Alongside age, the frequency of gene fusions defined in the World Health Organization classification decreased, while the positive rate of gene mutations, especially CH-related ones, increased. Additionally, the number of genetic mutations was higher in gene fusion-negative (GF-) patients than those with GF. Based on the status of CH- and myelodysplastic syndromes (MDS)-related mutations, three mutant subgroups were identified among the GF- AML cohort, namely, CH-AML, CH-MDS-AML, and other GF- AML. Notably, CH-MDS-AML demonstrated a predominance of elderly and male cases, cytopenia, and significantly adverse clinical outcomes. Besides, gene expression networks including HOXA/B, platelet factors, and inflammatory responses were most striking features associated with aging and poor prognosis in AML. Our work has thus unraveled the intricate regulatory circuitry of interactions among different age, gender, and molecular groups of AML.

Transcriptome-based molecular subtypes and differentiation hierarchies improve the classification framework of acute myeloid leukemia.

The current classification of acute myeloid leukemia (AML) relies largely on genomic alterations. Robust identification of clinically and biologically relevant molecular subtypes from nongenomic high-throughput sequencing data remains challenging. We established the largest multicenter AML cohort (n = 655) in China, with all patients subjected to RNA sequencing (RNA-Seq) and 619 (94.5%) to targeted or whole-exome sequencing (TES/WES). Based on an enhanced consensus clustering, eight stable gene expression subgroups (G1-G8) with unique clinical and biological significance were identified, including two unreported (G5 and G8) and three redefined ones (G4, G6, and G7). Apart from four well-known low-risk subgroups including PML::RARA (G1), CBFB::MYH11 (G2), RUNX1::RUNX1T1 (G3), biallelic CEBPA mutations or -like (G4), four meta-subgroups with poor outcomes were recognized. The G5 (myelodysplasia-related/-like) subgroup enriched clinical, cytogenetic and genetic features mimicking secondary AML, and hotspot mutations of IKZF1 (p.N159S) (n = 7). In contrast, most NPM1 mutations and KMT2A and NUP98 fusions clustered into G6-G8, showing high expression of HOXA/B genes and diverse differentiation stages, from hematopoietic stem/progenitor cell down to monocyte, namely HOX-primitive (G7), HOX-mixed (G8), and HOX-committed (G6). Through constructing prediction models, the eight gene expression subgroups could be reproduced in the Cancer Genome Atlas (TCGA) and Beat AML cohorts. Each subgroup was associated with distinct prognosis and drug sensitivities, supporting the clinical applicability of this transcriptome-based classification of AML. These molecular subgroups illuminate the complex molecular network of AML, which may promote systematic studies of disease pathogenesis and foster the screening of targeted agents based on omics.

Multi-hierarchy Network Configuration Can Predict Brain States and Performance.

The brain is a hierarchical modular organization that varies across functional states. Network configuration can better reveal network organization patterns. However, the multi-hierarchy network configuration remains unknown. Here, we propose an eigenmodal decomposition approach to detect modules at multi-hierarchy, which can identify higher-layer potential submodules and is consistent with the brain hierarchical structure. We defined three metrics: node configuration matrix, combinability, and separability. Node configuration matrix represents network configuration changes between layers. Separability reflects network configuration from global to local, whereas combinability shows network configuration from local to global. First, we created a random network to verify the feasibility of the method. Results show that separability of real networks is larger than that of random networks, whereas combinability is smaller than random networks. Then, we analyzed a large data set incorporating fMRI data from resting and seven distinct tasking conditions. Experiment results demonstrates the high similarity in node configuration matrices for different task conditions, whereas the tasking states have less separability and greater combinability between modules compared with the resting state. Furthermore, the ability of brain network configuration can predict brain states and cognition performance. Crucially, derived from tasks are highlighted with greater power than resting, showing that task-induced attributes have a greater ability to reveal individual differences. Together, our study provides novel perspectives for analyzing the organization structure of complex brain networks at multi-hierarchy, gives new insights to further unravel the working mechanisms of the brain, and adds new evidence for tasking states to better characterize and predict behavioral traits.

Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability.

The functional connectivity (FC) graph of the brain has been widely recognized as a ``fingerprint'' that can be used to identify individuals from a group of subjects. Research has indicated that individual identification accuracy can be improved by eliminating the impact of shared information among individuals. However, current research extracts not only shared information of inter-subject but also individual-specific information from FC graphs, resulting in incomplete separation of shared information and fingerprint information among individuals, leading to lower individual identification accuracy across all functional magnetic resonance imaging (fMRI) states session pairs and poor cognitive behavior prediction performance. In this paper, we propose a method to enhance inter-subject variability combining conditional variational autoencoder (CVAE) network and sparse dictionary learning (SDL) module. By embedding fMRI state information in the encoding and decoding processes, the CVAE network can better capture and represent the common features among individuals and enhance inter-subject variability by residual. Our experimental results on Human Connectome Project (HCP) data show that the refined connectomes obtained by using CVAE with SDL can accurately distinguish an individual from the remaining participants. The success accuracies reached 99.7 % and 99.6 % in the session pair rest1-rest2 and reverse rest2-rest1, respectively. In the identification experiment involving task-task combinations carried out on the same day, the identification accuracies ranged from 94.2 % to 98.8 %. Furthermore, we showed the Frontoparietal and Default networks make the most significant contributions to individual identification and the edges that significantly contribute to individual identification are found within and between the Frontoparietal and Default networks. Additionally, high-level cognitive behaviors can also be better predicted with the obtained refined connectomes, suggesting that higher fingerprinting can be useful for resulting in higher behavioral associations. In summary, our proposed framework provides a promising approach to use functional connectivity networks for studying cognition and behavior, promoting a deeper understanding of brain functions.

K-t PCA accelerated in-plane balanced steady-state free precession phase-contrast (PC-SSFP) for all-in-one diastolic function evaluation.

PURPOSE: Diastolic function evaluation requires estimates of early and late diastolic mitral filling velocities (E and A) and of mitral annulus tissue velocity (e'). We aimed to develop an MRI method for simultaneous all-in-one diastolic function evaluation in a single scan by generating a 2D phase-contrast (PC) sequence with balanced steady-state free precession (bSSFP) contrast (PC-SSFP). E and A could then be measured with PC, and e' estimated by valve tracking on the magnitude images, using an established deep learning framework. METHODS: Our PC-SSFP used in-plane flow-encoding, with zeroth and first moment nulling over each TR. For further acceleration, different k-t principal component analysis (PCA) methods were investigated with both retrospective and prospective undersampling. PC-SSFP was compared to separate balanced SSFP cine and PC-gradient echo acquisitions in phantoms and in 10 healthy subjects. RESULTS: Phantom experiments showed that PC-SSFP measured accurate velocities compared to PC-gradient echo (r = 0.98 for a range of pixel-wise velocities -80 cm/s to 80 cm/s). In subjects, PC-SSFP generated high SNR and myocardium-blood contrast, and excellent agreement for E (limits of agreement [LOA] 0.8 ± 2.4 cm/s, r = 0.98), A (LOA 2.5 ± 4.1 cm/s, r = 0.97), and e' (LOA 0.3 ± 2.6 cm/s, r = 1.00), versus the standard methods. The best k-t PCA approach processed the complex difference data and substituted in raw k-space data. With prospective k-t PCA acceleration, higher frame rates were achieved (50 vs. 25 frames per second without k-t PCA), yielding a 13% higher e'. CONCLUSION: The proposed PC-SSFP method achieved all-in-one diastolic function evaluation.

Tricuspid valve flow measurement using a deep learning framework for automated valve-tracking 2D phase contrast.

PURPOSE: Tricuspid valve flow velocities are challenging to measure with cardiovascular MR, as the rapidly moving valvular plane prohibits direct flow evaluation, but they are vitally important to diastolic function evaluation. We developed an automated valve-tracking 2D method for measuring flow through the dynamic tricuspid valve. METHODS: Nine healthy subjects and 2 patients were imaged. The approach uses a previously trained deep learning network, TVnet, to automatically track the tricuspid valve plane from long-axis cine images. Subsequently, the tracking information is used to acquire 2D phase contrast (PC) with a dynamic (moving) acquisition plane that tracks the valve. Direct diastolic net flows evaluated from the dynamic PC sequence were compared with flows from 2D-PC scans acquired in a static slice localized at the end-systolic valve position, and also ventricular stroke volumes (SVs) using both planimetry and 2D PC of the great vessels. RESULTS: The mean tricuspid valve systolic excursion was 17.8 ± 2.5 mm. The 2D valve-tracking PC net diastolic flow showed excellent correlation with SV by right-ventricle planimetry (bias ± 1.96 SD = -0.2 ± 10.4 mL, intraclass correlation coefficient [ICC] = 0.92) and aortic PC (-1.0 ± 13.8 mL, ICC = 0.87). In comparison, static tricuspid valve 2D PC also showed a strong correlation but had greater bias (p = 0.01) versus the right-ventricle SV (10.6 ± 16.1 mL, ICC = 0.61). In most (8 of 9) healthy subjects, trace regurgitation was measured at begin-systole. In one patient, valve-tracking PC displayed a high-velocity jet (380 cm/s) with maximal velocity agreeing with echocardiography. CONCLUSION: Automated valve-tracking 2D PC is a feasible route toward evaluation of tricuspid regurgitant velocities, potentially solving a major clinical challenge.

Serum level of galectin-9 as a potential biomarker for high risk of malignancy in dermatomyositis.

OBJECTIVES: Galectin-9, as immune checkpoint protein, plays a role in regulating autoimmunity and tumour immunity. Therefore, we explored the pathophysiological link between galectin-9 and malignancy in cancer-related DM (CRDM). METHODS: Serum galectin-9 were quantified via enzyme-linked immunosorbent assay, and its association with serological indices was evaluated using Spearman analysis. Receiver operating characteristic (ROC) analysis was utilized to determine the cut-off value of galectin-9. RESULTS: Serum levels of galectin-9 were significantly higher in DM patients [23.38 (13.85-32.57) ng/ml] than those in healthy controls (HCs) [6.81 (5.42-7.89) ng/ml, P < 0.0001], and were positively correlated with the cutaneous dermatomyositis disease area severity index activity (CDASI-A) scores (rs=0.3065, P = 0.0172). DM patients with new-onset and untreated cancer (new-CRDM) [31.58 (23.85-38.84) ng/ml] had higher levels of galectin-9 than those with stable and treated cancer (stable-CRDM) [17.49 (10.23-27.91) ng/ml, P = 0.0288], non-cancer-related DM (non-CRDM) [21.05 (11.97-28.02) ng/ml, P = 0.0258], and tumour patients without DM [7.46 (4.90-8.51) ng/ml, P < 0.0001]. Serum galectin-9 levels significantly decreased [27.79 (17.04-41.43) ng/ml vs 13.88 (5.15-20.37) ng/ml, P = 0.002] after anti-cancer treatment in CRDM patients. The combination of serum galectin-9 and anti-transcriptional intermediary factor 1-γ (anti-TIF1-γ) antibody (AUC = 0.889, 95% CI 0.803-0.977) showed the highest predictive value for the presence of cancer in DM. CONCLUSION: Increased galectin-9 levels were related to tumor progression in CRDM, and galectin-9 was downregulated upon cancer treatment. Monitoring serum galectin-9 levels and anti-TIF1-γ antibodies might be an attractive strategy to achieve tumour diagnosis and predict CRDM outcome.

Isoliquiritigenin limits inflammasome activation of macrophage via docking into Syk to alleviate murine non-alcoholic fatty liver disease.

Isoliquiritigenin (ISL) is a chalcone-type flavonoid derived from the root of licorice with antioxidant, anti-inflammatory, anti-tumour and neuroprotective properties. ISL has been proven to downregulate the productions of IL-1ß, TNF-α and IL-6 by macrophages. However, detailed molecular mechanisms of this modulation remain elusive. Here, ISL suppressed Syk phosphorylation and CD80, CD86, IL-1ß, TNF-α and IL-6 expressions in lipopolysaccharide-stimulated macrophages ex vivo. ApoC3-transgenic (ApoC3TG) mice had more activated macrophages. ISL was also able to downregulate the inflammatory activities of macrophages from ApoC3TG mice. Administration of ISL inhibited Syk activation and inflammatory activities of macrophages in ApoC3TG mice in vivo. The treatment of ISL further alleviated MCD-induced non-alcoholic fatty liver disease (NAFLD) in wild-type and ApoC3TG mice, accompanied by less recruitment and activation of liver macrophages. Due to the inhibition of Syk phosphorylation, ISL-treated macrophages displayed less production of cytoplasmic ROS, NLRP3, cleaved-GSDMD and cleaved-IL-1ß, suggesting less inflammasome activation. Finally, the molecular docking study demonstrated that ISL bound to Syk directly with the Kd of 1.273 × 10-8 M. When the Syk expression was knocked down by its shRNA, the inhibitory effects of ISL on activated macrophages disappeared, indicating that Syk was at least one of key docking-molecules of ISL. Collectively, ISL could alleviate MCD-induced NAFLD in mice involved with the inhibition of macrophage inflammatory activity by the blockade of Syk-induced inflammasome activation.

Sex differences in mortality and liver-related events in non-alcoholic fatty liver disease: A systematic review and meta-analysis.

BACKGROUND & AIMS: Many systematic reviews explore the association of non-alcoholic fatty liver disease (NAFLD) with mortality, but none of them explores sex-based differences in detail. We aimed to assess whether NAFLD is associated with cause-specific mortality, all-cause mortality, and cancer incidence in both men and women. METHODS: The PubMed, Embase, and Medline databases were searched from inception through April 2023 for eligible studies. We separately pooled relative risks (RRs) for men and women using a random effects model. Subsequently, the RRs and 95% CIs (confidence intervals) in each study were used to calculate the women-to-men ratio of RRs (RRR). Furthermore, subgroup analyses were performed to explore the robustness of outcomes. The random-effects model was employed to conduct sensitivity analyses to determine the impact of specific studies on the overall findings. RESULTS: The meta-analysis included nine cohort studies comprising 557 614 patients with NAFLD were chosen. Women were 44% more likely than men to get cancer among those with NAFLD (RRR: 1.44; 95% CI: 1.02-2.04; p = .039). However, no sex-related differences were observed between NAFLD and all-cause mortality (RRR: 1.06; 95% CI: 0.56-2.01; p = .861), liver-related mortality (RRR: 1.06; 95% CI: 0.02-69.82; p = .977), cardiovascular mortality (RRR: 1; 95% CI: 0.65-1.53; p = .987) and liver cancer (RRR: 0.76; 95% CI: 0.43-1.36; p = .36). CONCLUSIONS: There may be sex variations between NAFLD and the risk of cancer, with the connection being stronger in females than in males.

Bioinformatics analysis reveals the potential common genes and immune characteristics between atrial fibrillation and periodontitis.

BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) and periodontitis, both classified under chronic inflammatory diseases, share common etiologies, including genetic factors and immune pathways. However, the exact mechanisms are still poorly understood. This study aimed to explore the potential common genes and immune characteristics between AF and periodontitis. METHODS: Gene expression datasets for AF and periodontitis were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis was used to identify common genes in the training set. Functional analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, were conducted to elucidate the underlying mechanisms. Hub genes were further screened based on expression levels, receiver operating characteristic (ROC) curves, and least absolute shrinkage and selection operator (LASSO) regression. Then, based on the expression levels and ROC values of the hub genes in the validation set, the target genes were identified. Finally, immune cell infiltration analysis was performed on the AF and periodontitis datasets in the training set using the "CIBERSORT" R package. The relationships between target genes, infiltrating immune cells, and inflammatory factors were also investigated. In addition, AF susceptibility, atrial fibrosis, inflammatory infiltration, and RGS1 protein expression in rat models of periodontitis were assessed through in vivo electrophysiology experiments, Masson's trichrome staining, hematoxylin-eosin staining, immunohistochemistry, and western blotting, respectively. RESULTS: A total of 21 common genes were identified between AF and periodontitis among the differentially expressed genes. After evaluating gene expression levels, ROC curves, and LASSO analysis, four significant genes between AF and periodontitis were identified, namely regulator of G-protein signaling 1 (RGS1), annexin A6 (ANXA6), solute carrier family 27 member 6 (SLC27A6), and ficolin 1 (FCN1). Further validation confirmed that RGS1 was the optimal shared target gene for AF and periodontitis. Immune cell infiltration analysis revealed that neutrophils and T cells play an important role in the pathogenesis of both diseases. RGS1 showed a significant positive correlation with activated memory CD4 T cells and gamma-delta T cells and a negative correlation with CD8 T cells and regulatory T cells in both training sets. Moreover, RGS1 was positively correlated with classical pro-inflammatory cytokines IL1ß and IL6. In periodontitis rat models, AF susceptibility, atrial fibrosis, and inflammatory infiltration were significantly increased, and RGS1 expression in the atrial tissue was upregulated. CONCLUSION: A common gene between AF and periodontitis, RGS1 appears central in linking the two conditions. Immune and inflammatory responses may underlie the interaction between AF and periodontitis.

Capsaicin combined with stem cells improved mitochondrial dysfunction in PIG3V cells, an immortalized human vitiligo melanocyte cell line, by inhibiting the HSP70/TLR4/mTOR/FAK signaling axis.

BACKGROUND: Vitiligo is a common autoimmune skin disease. Capsaicin has been found to exert a positive effect on vitiligo treatment, and mesenchymal stem cells (MSCs) are also confirmed to be an ideal cell type. This study aimed to explore the influence of capsaicin combined with stem cells on the treatment of vitiligo and to confirm the molecular mechanism of capsaicin combined with stem cells in treating vitiligo. METHODS AND RESULTS: PIG3V cell proliferation and apoptosis were detected using CCK-8 and TUNEL assays, MitoSOX Red fluorescence staining was used to measure the mitochondrial ROS level, and JC-1 staining was used to detect the mitochondrial membrane potential. The expression of related genes and proteins was detected using RT‒qPCR and Western blotting. Coimmunoprecipitation was used to analyze the protein interactions between HSP70 and TLR4 or between TLR4 and mTOR. The results showed higher expression of HSP70 in PIG3V cells than in PIG1 cells. The overexpression of HSP70 reduced the proliferation of PIG3V cells, promoted apoptosis, and aggravated mitochondrial dysfunction and autophagy abnormalities. The expression of HSP70 could be inhibited by capsaicin combined with MSCs, which increased the levels of Tyr, Tyrp1 and DCT, promoted the proliferation of PIG3V cells, inhibited apoptosis, activated autophagy, and improved mitochondrial dysfunction. In addition, capsaicin combined with MSCs regulated the expression of TLR4 through HSP70 and subsequently affected the mTOR/FAK signaling pathway CONCLUSIONS: Capsaicin combined with MSCs inhibits TLR4 through HSP70, and the mTOR/FAK signaling pathway is inhibited to alleviate mitochondrial dysfunction and autophagy abnormalities in PIG3V cells.

Abnormal dynamic reconfiguration of the large-scale functional network in schizophrenia during the episodic memory task.

Episodic memory deficits are the core feature in schizophrenia (SCZ). Numerous studies have revealed abnormal brain activity associated with this disorder during episodic memory, however previous work has only relied on static analysis methods that treat the brain as a static monolithic structure, ignoring the dynamic features at different time scales. Here, we applied dynamic functional connectivity analysis to functional magnetic resonance imaging data during episodic memory and quantify integration and recruitment metrics to reveal abnormal dynamic reconfiguration of brain networks in SCZ. In the specific frequency band of 0.06-0.125 Hz, SCZ showed significantly higher integration during encoding and retrieval, and the abnormalities were mainly in the default mode, frontoparietal, and cingulo-opercular modules. Recruitment of SCZ was significantly higher during retrieval, mainly in the visual module. Interestingly, interactions between groups and task status in recruitment were found in the dorsal attention, visual modules. Finally, we observed that integration was significantly associated with memory performance in frontoparietal regions. Our findings revealed the time-varying evolution of brain networks in SCZ, while improving our understanding of cognitive decline and other pathophysiologies in brain diseases.

Gender effects on the controllability of hemispheric white matter networks.

Male and female adults exhibited significant group differences in brain white matter (WM) asymmetry and WM network controllability. However, gender differences in controllability of hemispheric WM networks between males and females remain to be determined. Based on 1 principal atlas and 1 replication atlas, this work characterized the average controllability (AC) and modal controllability (MC) of hemispheric WM network based on 1 principal dataset and 2 replication datasets. All results showed that males had higher AC of left hemispheric networks than females. And significant hemispheric asymmetry was revealed in regional AC and MC. Furthermore, significant gender differences in the AC asymmetry were mainly found in regions lie in the frontoparietal network, and the MC asymmetry was found in regions involving auditory and emotion process. Finally, we found significant associations between regional controllability and cognitive features. Taken together, this work could provide a novel perspective for understanding gender differences in hemispheric WM asymmetry and cognitive function between males and females.

Altered higher-order coupling between brain structure and function with embedded vector representations of connectomes in schizophrenia.

It has been shown that the functional dependency of the brain exists in both direct and indirect regional relationships. Therefore, it is necessary to map higher-order coupling in brain structure and function to understand brain dynamic. However, how to quantify connections between not directly regions remains unknown to schizophrenia. The word2vec is a common algorithm through create embeddings of words to solve these problems. We apply the node2vec embedding representation to characterize features on each node, their pairwise relationship can give rise to correspondence relationships between brain regions. Then we adopt pearson correlation to quantify the higher-order coupling between structure and function in normal controls and schizophrenia. In addition, we construct direct and indirect connections to quantify the coupling between their respective functional connections. The results showed that higher-order coupling is significantly higher in schizophrenia. Importantly, the anomalous cause of coupling mainly focus on indirect structural connections. The indirect structural connections play an essential role in functional connectivity-structural connectivity (SC-FC) coupling. The similarity between embedded representations capture more subtle network underlying information, our research provides new perspectives for understanding SC-FC coupling. A strong indication that the structural backbone of the brain has an intimate influence on the resting-state functional.

Abnormal information interaction in multilayer directed network based on cross-frequency integration of mild cognitive impairment and Alzheimer's disease.

Mild cognitive impairment (MCI) and Alzheimer's disease (AD) have been reported to result in abnormal cross-frequency integration. However, previous studies have failed to consider specific abnormalities in receiving and outputting information among frequency bands during integration. Here, we investigated heterogeneity in receiving and outputting information during cross-frequency integration in patients. The results showed that during cross-frequency integration, information interaction first increased and then decreased, manifesting in the heterogeneous distribution of inter-frequency nodes for receiving information. A possible explanation was that due to damage to some inter-frequency hub nodes, intra-frequency nodes gradually became new inter-frequency nodes, whereas original inter-frequency nodes gradually became new inter-frequency hub nodes. Notably, damage to the brain regions that receive information between layers was often accompanied by a strengthened ability to output information and the emergence of hub nodes for outputting information. Moreover, an important compensatory mechanism assisted in the reception of information in the cingulo-opercular and auditory networks and in the outputting of information in the visual network. This study revealed specific abnormalities in information interaction and compensatory mechanism during cross-frequency integration, providing important evidence for understanding cross-frequency integration in patients with MCI and AD.

Predictive Role of Preoperative Nutritional Status on Early Postoperative Outcomes in Different-Aged Patients Undergoing Heart Valve Surgery.

OBJECTIVES: The authors sought to elucidate the role and predictive effects of preoperative nutritional status on postoperative outcomes across different age groups undergoing heart valve surgery. DESIGN: A retrospective study with intergroup comparison, receiver operating characteristic curve analysis, and logistic regression analysis. SETTING: A hospital affiliated with a medical university. PARTICIPANTS: Three thousand nine hundred five patients undergoing heart valve surgery between October 2016 and December 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients were categorized into 3 age subgroups: young (aged 18-44 years), middle-aged (aged 45-59 years), and older (aged ≥60 years) adults. The Nutritional Risk Index (NRI), Prognostic Nutritional Index, and Controlling Nutritional Status scores were evaluated. Young adults with an NRI <99 experienced a significantly higher rate of prolonged intensive care unit stay (28.3% v 4.1%, p < 0.001), with a relative risk of 4.58 (95% CI: 2.04-10.27). Similarly, young adults with an NRI <97 had a significantly increased occurrence of mortality within 30 days after surgery (6.3% v 0.2%, p < 0.001), with a relative risk of 41.11 (95% CI: 3.19-529.48). CONCLUSIONS: In patients who undergo heart valve surgery, early postoperative outcomes can be influenced by nutritional status before the surgery. In the young-adult group, NRI <99 and NRI <97 effectively could predict prolonged intensive care unit stay and 30-day mortality, respectively.

Exploring the effect of disc displacement on the risk and severity of condylar erosion in adult temporomandibular disorder patients: A CBCT and MRI study.

OBJECTIVE: The objective of the study was to investigate the relationship between types of disc displacement (DD) diagnosed by magnetic resonance imaging (MRI), and the risk (presence or absence) and severity of condylar erosion (CE) graded using cone-beam computed tomography (CBCT) in adult Temporomandibular disorders (TMD) patients. METHODS: A total of 353 TMD patients (283 females, 70 males) underwent MRI scans to categorise DD as normal (NA), anterior displacement with reduction (ADDR), or anterior displacement without reduction (ADDNR). CE severity was graded on a scale of 0-3 (absence, mild, moderate or severe) using CBCT. To establish the plausibility and cut-off points for CE diagnosis, the severity of CE was then further divided into three classifications: Grade 0 versus 1 + 2 + 3; Grades 0 + 1 versus 2 + 3; Grades 0 + 1 + 2 versus 3. Logistic regression analysis was performed, adjusting for age, gender and joint correlation. RESULTS: ADDNR significantly increased the risk of CE compared with NA (OR = 10.04, 95% CI: [6.41, 15.73]) and showed a significant increase in CE severity across all classifications (ORs = 10.04-18.95). The effects of ADDNR were significant in both genders (p < .001) and had a greater impact in females. ADDR was predominantly associated with mild CE. CONCLUSIONS: ADDNR significantly increased the risk and severity of CE independent of gender when compared to NA, whereas ADDR was mainly associated with mild CE. Slight cortical discontinuity may represent a subclinical diagnosis requiring further investigation.

Visualization Analysis of Artificial Intelligence Literature in Forensic Research.

OBJECTIVES: To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database, to explore research hotspots and developmental trends. METHODS: A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the literature measuring tool CiteSpace. The authors, institution, country (region), title, journal, keywords, cited references and other information of relevant literatures were analyzed. RESULTS: A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries (regions) were identified, with the number of articles published showing an increasing trend year by year. Among them, the United States had the highest number of publications and China ranked the second. Academy of Forensic Science had the highest number of publications among the institutions. Forensic Science International, Journal of Forensic Sciences, International Journal of Legal Medicine ranked high in publication and citation frequency. Through the analysis of keywords, it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technology for sex and age estimation, cause of death analysis, postmortem interval estimation, individual identification and so on. CONCLUSIONS: It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research. Exploring the combination of advanced artificial intelligence technologies with forensic research will be a hotspot and direction for future research.