An Attention-Based Hemispheric Relation Inference Network for Perinatal Brain Age Prediction.

Brain anatomical age is an effective feature to assess the status of the brain, such as atypical development and aging. Although some deep learning models have been developed for estimating infant brain age, the performance of these models was unsatisfactory because few of them considered the developmental characteristics of brain anatomy during the perinatal period-the most rapid and complex developmental stage across the lifespan. The present study proposed an attention-based hemispheric relation inference network (HRINet) that takes advantage of the nature of brain structural lateralization during early development. This model captures the inter-hemispheric relationship using a graph attention mechanism and transmits lateralization information as features to describe the interactive development between bilateral hemispheres. The HRINet was used to estimate the brain age of 531 preterm and full-term neonates from the Developing Human Connectome Project (dHCP) database based on two metrics (mean curvature and sulcal depth) characterizing the folding morphology of the cortex. Our results showed that the HRINet outperformed other benchmark models in fitting the perinatal brain age, with mean absolute error of 0.53 and determination coefficient of 0.89. We also verified the generalizability of the HRINet on an extra independent dataset collected from the Gansu Provincial Maternity and Child-care Hospital. Furthermore, by applying the best-performing model to an independent dataset consisting of 47 scans of preterm infants at term-equivalent age, we showed that the predicted age was significantly lower than the chronological age, suggesting a delayed development of premature brains. Our results demonstrate the effectiveness and generalizability of the HRINet in estimating infant brain age, providing promising clinical applications for assessing neonatal brain maturity.

Disrupted dynamic brain functional connectivity in male cocaine use disorder: Hyperconnectivity, strongly-connected state tendency, and links to impulsivity and borderline traits.

Cocaine use is a major public health problem with serious negative consequences at both the individual and societal levels. Cocaine use disorder (CUD) is associated with cognitive and emotional impairments, often manifesting as alterations in brain functional connectivity (FC). This study employed resting-state functional magnetic resonance imaging (rs-fMRI) to examine dynamic FC in 38 male participants with CUD and 31 matched healthy controls. Using group spatial independent component analysis (group ICA) combined with sliding window approach, we identified two recurring distinct connectivity states: the strongly-connected state (state 1) and weakly-connected state (state 2). CUD patients exhibited significant increased mean dwell and fraction time in state 1, and increased transitions from state 2 to state 1, demonstrated significant strongly-connected state tendency. Our analysis revealed abnormal FC patterns that are state-dependent and state-shared in CUD patients. This study observed hyperconnectivity within the default mode network (DMN) and between DMN and other networks, which varied depending on the state. Furthermore, after adjustment for multiple comparisons, we found significant correlations between these altered dynamic FCs and clinical measures of impulsivity and borderline personality disorder. The disrupted FC and repetitive effects of precuneus and angular gyrus across correlations suggested that they might be the important hub of neural circuits related behaviorally and mentally in CUD. In summary, our study highlighted the potential of these disrupted FC as neuroimaging biomarkers and therapeutic targets, and provided new insights into the understanding of the neurophysiologic mechanisms of CUD.

Relay Annulation of Ammonium Ylides with Oxindole-Derived α,ß-Unsaturated Ketimines: Catalytic Construction of Spiro-polycyclic Oxindoles.

An ammonium ylide-based relay annulation was disclosed, which uses DABCO as the catalyst and oxindole-derived α,ß-unsaturated ketimines and γ-bromo-crotonates as the starting materials. This method enables the rapid assembly of a series of structurally novel spiro-polycyclic oxindoles containing a bicyclo[4.1.0]heptane moiety through simultaneous generation of three new bonds and two rings in one step under mild reaction conditions.

Profiling cortical morphometric similarity in perinatal brains: Insights from development, sex difference, and inter-individual variation.

The topological organization of the macroscopic cortical networks important for the development of complex brain functions. However, how the cortical morphometric organization develops during the third trimester and whether it demonstrates sexual and individual differences at this particular stage remain unclear. Here, we constructed the morphometric similarity network (MSN) based on morphological and microstructural features derived from multimodal MRI of two independent cohorts (cross-sectional and longitudinal) scanned at 30-44 postmenstrual weeks (PMW). Sex difference and inter-individual variations of the MSN were also examined on these cohorts. The cross-sectional analysis revealed that both network integration and segregation changed in a nonlinear biphasic trajectory, which was supported by the results obtained from longitudinal analysis. The community structure showed remarkable consistency between bilateral hemispheres and maintained stability across PMWs. Connectivity within the primary cortex strengthened faster than that within high-order communities. Compared to females, male neonates showed a significant reduction in the participation coefficient within prefrontal and parietal cortices, while their overall network organization and community architecture remained comparable. Furthermore, by using the morphometric similarity as features, we achieved over 65 % accuracy in identifying an individual at term-equivalent age from images acquired after birth, and vice versa. These findings provide comprehensive insights into the development of morphometric similarity throughout the perinatal cortex, enhancing our understanding of the establishment of neuroanatomical organization during early life.

How Mycobacterium tuberculosis builds a home: Single-cell analysis reveals M. tuberculosis ESX-1-mediated accumulation of anti-inflammatory macrophages in infected mouse lungs.

Mycobacterium tuberculosis (MTB) infects and replicates in lung mononuclear phagocytes (MNPs) with astounding ability to evade elimination. ESX-1, a type VII secretion system, acts as a virulence determinant that contributes to MTB's ability to survive within MNPs, but its effect on MNP recruitment and/or differentiation remains unknown. Here, using single-cell RNA sequencing, we studied the role of ESX-1 in MNP heterogeneity and response in mice and murine bone marrow-derived macrophages (BMDM). We found that ESX-1 is required for MTB to recruit diverse MNP subsets with high MTB burden. Further, MTB induces an anti-inflammatory signature in MNPs and BMDM in an ESX-1 dependent manner. Similarly, spatial transcriptomics revealed an upregulation of anti-inflammatory signals in MTB lesions, where monocyte-derived macrophages concentrate near MTB-infected cells. Together, our findings suggest that MTB ESX-1 mediates the recruitment and differentiation of anti-inflammatory MNPs, which MTB can infect and manipulate for survival.

1,5-Hydrogen atom transfer of α-iminyl radical cations: a new platform for relay annulation for pyridine derivatives and axially chiral heterobiaryls.

The exploitation of new reactive species and novel transformation modes for their synthetic applications have significantly promoted the development of synthetic organic methodology, drug discovery, and advanced functional materials. α-Iminyl radical cations, a class of distonic ions, exhibit great synthetic potential for the synthesis of valuable molecules. For their generation, radical conjugate addition to α,ß-unsaturated iminium ions represents a concise yet highly challenging route, because the in situ generated species are short-lived and highly reactive and they have a high tendency to cause radical elimination (ß-scission) to regenerate the more stable iminium ions. Herein, we report a new transformation mode of the α-iminyl radical cation, that is to say, 1,5-hydrogen atom transfer (1,5-HAT). Such a strategy can generate a species bearing multiple reactive sites, which serves as a platform to realize (asymmetric) relay annulations. The present iron/secondary amine synergistic catalysis causes a modular assembly of a broad spectrum of new structurally fused pyridines including axially chiral heterobiaryls, and exhibits good functional group tolerance. A series of mechanistic experiments support the α-iminyl radical cation-induced 1,5-HAT, and the formation of several radical species in the relay annulations. Various synthetic transformations of the reaction products demonstrate the usefulness of this relay annulation protocol for the synthesis of significant molecules.

Mycobacterium tuberculosis resides in lysosome-poor monocyte-derived lung cells during chronic infection.

Mycobacterium tuberculosis (Mtb) infects lung myeloid cells, but the specific Mtb-permissive cells and host mechanisms supporting Mtb persistence during chronic infection are incompletely characterized. We report that after the development of T cell responses, CD11clo monocyte-derived cells harbor more live Mtb than alveolar macrophages (AM), neutrophils, and CD11chi monocyte-derived cells. Transcriptomic and functional studies revealed that the lysosome pathway is underexpressed in this highly permissive subset, characterized by less lysosome content, acidification, and proteolytic activity than AM, along with less nuclear TFEB, a regulator of lysosome biogenesis. Mtb infection does not drive lysosome deficiency in CD11clo monocyte-derived cells but promotes recruitment of monocytes that develop into permissive lung cells, mediated by the Mtb ESX-1 secretion system. The c-Abl tyrosine kinase inhibitor nilotinib activates TFEB and enhances lysosome functions of macrophages in vitro and in vivo, improving control of Mtb infection. Our results suggest that Mtb exploits lysosome-poor lung cells for persistence and targeting lysosome biogenesis is a potential host-directed therapy for tuberculosis.

Aberrant dynamic functional connectivity of thalamocortical circuitry in major depressive disorder. / é‡åº¦æŠ‘éƒéšœç¢æ‚£è€ ä¸˜è„‘çš®å±‚çŽ¯è·¯çš„åŠ¨æ€åŠŸèƒ½è¿žæŽ¥å¼‚å¸¸.

Thalamocortical circuitry has a substantial impact on emotion and cognition. Previous studies have demonstrated alterations in thalamocortical functional connectivity (FC), characterized by region-dependent hypo- or hyper-connectivity, among individuals with major depressive disorder (MDD). However, the dynamical reconfiguration of the thalamocortical system over time and potential abnormalities in dynamic thalamocortical connectivity associated with MDD remain unclear. Hence, we analyzed dynamic FC (dFC) between ten thalamic subregions and seven cortical subnetworks from resting-state functional magnetic resonance images of 48 patients with MDD and 57 healthy controls (HCs) to investigate time-varying changes in thalamocortical FC in patients with MDD. Moreover, dynamic laterality analysis was conducted to examine the changes in functional lateralization of the thalamocortical system over time. Correlations between the dynamic measures of thalamocortical FC and clinical assessment were also calculated. We identified four dynamic states of thalamocortical circuitry wherein patients with MDD exhibited decreased fractional time and reduced transitions within a negative connectivity state that showed strong correlations with primary cortical networks, compared with the HCs. In addition, MDD patients also exhibited increased fluctuations in functional laterality in the thalamocortical system across the scan duration. The thalamo-subnetwork analysis unveiled abnormal dFC variability involving higher-order cortical networks in the MDD cohort. Significant correlations were found between increased dFC variability with dorsal attention and default mode networks and the severity of symptoms. Our study comprehensively investigated the pattern of alteration of the thalamocortical dFC in MDD patients. The heterogeneous alterations of dFC between the thalamus and both primary and higher-order cortical networks may help characterize the deficits of sensory and cognitive processing in MDD.

Rich Club Reorganization in Nurses Before and After the Onset of Occupational Burnout: A Longitudinal MRI Study.

BACKGROUND: Studies on potential disruptions in rich club structure in nursing staff with occupational burnout are lacking. Moreover, existing studies on nurses with burnout are limited by their cross-sectional design. PURPOSE: To investigate rich club reorganization in nursing staff before and after the onset of burnout and the underlying impact of anatomical distance on such reconfiguration. STUDY TYPE: Prospective, longitudinal. POPULATION: Thirty-nine hospital nurses ( 23.67 ± 1.03 $$ 23.67\pm 1.03 $$ years old at baseline, 24.67 ± 1.03 $$ 24.67\pm 1.03 $$ years old at a follow-up within 1.5 years, 38 female). FIELD STRENGTH/SEQUENCE: Magnetization-prepared rapid gradient-echo and gradient-echo echo-planar imaging sequences at 3.0 T. ASSESSMENT: The Maslach Burnout Inventory and Symptom Check-List 90 testing were acquired at each MRI scan. Rich club structure was assessed at baseline and follow-up to determine whether longitudinal changes were related to burnout and to changes in connectivities with different anatomical distances (short-, mid-, and long range). STATISTICAL TESTS: Chi-square, paired-samples t, two-sample t, Mann-Whitney U tests, network-based statistic, Spearman correlation analysis, and partial least squares regression analysis. Significance level: Bonferroni-corrected P < 0.05 $$ P<0.05 $$ . RESULTS: In nurses who developed burnout: 1) Strengths of rich club, feeder, local, short-, mid-, and long-range connectivities were significantly decreased at follow-up compared with baseline. 2) At follow-up, strengths of above connectivities and that between A5m.R and dlPu.L were significantly correlated with emotional exhaustion (r ranges from -0.57 to -0.73) and anxiety scores (r = -0.56), respectively. 3) Longitudinal change (follow-up minus baseline) in connectivity strength between A5m.R and dlPu.L reflected change in emotional exhaustion score (r = 0.87). Longitudinal changes in strength of connectivities mainly involving parietal lobe were significantly decreased in nurses who developed burnout compared with those who did not. DATA CONCLUSION: In nurses after the onset of burnout, rich club reorganization corresponded to significant reductions in strength of connectivities with different anatomical distances. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Modular Assembly of 2-Aminoaniline Derivatives by Merging Hydroxylamine-Passerini and Hetero-Cope Rearrangement.

A metal-free three-component protocol that combines a hydroxylamine-Passerini reaction and hetero-Cope rearrangement was realized, which enables the modular assembly of a wide range of structurally new and interesting 2-aminoanilines bearing an α-hydroxyamide substructure.

Development of an indirect ELISA against Orf virus using two recombinant antigens, partial B2L and F1L.

Orf is a highly contagious viral disease affecting goats and sheep. It is caused by Orf virus (ORFV) and has caused severe economic losses to the global goat industry, including in China. In this study, an indirect ELISA method for recombinant proteins based on truncated dominant antigenic epitopes of B2L and F1L genes of ORFV was established. A series of conditions and its performance were comprehensively evaluated. The optimized ELISA reaction conditions were: the optimal coating amount of antigen was 0.25 µg/mL, 5% skim milk powder was closed for 1 h, the optimal dilution of serum was 1:200, the optimal incubation time of the rabbit anti-goat IgG was 1:8000, the optimal color development time of TMB was 15 mins, and the threshold value of negative-positive was 0.358. The method specifically detects anti-ORFV antibodies and does not cross-react with positive sera for other common goat pathogenic bacteria antiserum. ORFV-positive sera were still positive after 1:512 dilution, with intra-batch coefficient of variation (CV) between 7.1% and 9.5% and inter-batch CV between 5.0% and 7.6%; 51% (92/180) of immunized goat serum samples were tested positive and 14.44% (14/63) of non-immunized goat serum samples were positive. The results show that the indirect ELISA antibody assay established in this study has good specificity, sensitivity and reproducibility, and provides a technical tool for clinical ORFV serum antibody detection and epidemiological investigation.

Improving brain age prediction with anatomical feature attention-enhanced 3D-CNN.

Currently, significant progress has been made in predicting brain age from structural Magnetic Resonance Imaging (sMRI) data using deep learning techniques. However, despite the valuable structural information they contain, the traditional engineering features known as anatomical features have been largely overlooked in this context. To address this issue, we propose an attention-based network design that integrates anatomical and deep convolutional features, leveraging an anatomical feature attention (AFA) module to effectively capture salient anatomical features. In addition, we introduce a fully convolutional network, which simplifies the extraction of deep convolutional features and overcomes the high computational memory requirements associated with deep learning. Our approach outperforms several widely-used models on eight publicly available datasets (n = 2501), with a mean absolute error (MAE) of 2.20 years in predicting brain age. Comparisons with deep learning models lacking the AFA module demonstrate that our fusion model effectively improves overall performance. These findings provide a promising approach for combining anatomical and deep convolutional features from sMRI data to predict brain age, with potential applications in clinical diagnosis and treatment, particularly for populations with age-related cognitive decline or neurological disorders.

Fine-grained features characterize hippocampal and amygdaloid change pattern in Parkinson's disease and discriminate cognitive-deficit subtype.

AIMS: To extract vertex-wise features of the hippocampus and amygdala in Parkinson's disease (PD) with mild cognitive impairment (MCI) and normal cognition (NC) and further evaluate their discriminatory efficacy. METHODS: High-resolution 3D-T1 data were collected from 68 PD-MCI, 211 PD-NC, and 100 matched healthy controls (HC). Surface geometric features were captured using surface conformal representation, and surfaces were registered to a common template using fluid registration. The statistical tests were performed to detect differences between groups. The disease-discriminatory ability of features was also tested in the ensemble classifiers. RESULTS: The amygdala, not the hippocampus, showed significant overall differences among the groups. Compared with PD-NC, the right amygdala in MCI patients showed expansion (anterior cortical, anterior amygdaloid, and accessory basal areas) and atrophy (basolateral ventromedial area) subregions. There was notable atrophy in the right CA1 and hippocampal subiculum of PD-MCI. The accuracy of classifiers with multivariate morphometry statistics as features exceeded 85%. CONCLUSION: PD-MCI is associated with multiscale morphological changes in the amygdala, as well as subtle atrophy in the hippocampus. These novel metrics demonstrated the potential to serve as biomarkers for PD-MCI diagnosis. Overall, these findings from this study help understand the role of subcortical structures in the neuropathological mechanisms of PD cognitive impairment.

Defect Engineering of 2D Semiconductors for Dual Control of Emission and Carrier Polarity.

2D transition metal dichalcogenides (TMDCs) are considered as promising materials in post-Moore technology. However, the low photoluminescence quantum yields (PLQY) and single carrier polarity due to the inevitable defects during material preparation are great obstacles to their practical applications. Here, an extraordinary defect engineering strategy is reported based on first-principles calculations and realize it experimentally on WS2 monolayers by doping with IIIA atoms. The doped samples with large sizes possess both giant PLQY enhancement and effective carrier polarity modulation. Surprisingly, the high PL emission maintained even after one year under ambient environment. Moreover, the constructed p-n homojunctions shows high rectification ratio (≈2200), ultrafast response times and excellent stability. Meanwhile, the doping strategy is universally applicable to other TMDCs and dopants. This smart defect engineering strategy not only provides a general scheme to eliminate the negative influence of defects, but also utilize them to achieve desired optoelectronic properties for multifunctional applications.

Vapor growth of V-doped MoS2 monolayers with enhanced B-exciton emission and broad spectral response.

Dynamically engineering the optical and electrical properties in two-dimensional (2D) materials is of great significance for designing the related functions and applications. The introduction of foreign-atoms has previously been proven to be a feasible way to tune the band structure and related properties of 3D materials; however, this approach still remains to be explored in 2D materials. Here, we systematically demonstrate the growth of vanadium-doped molybdenum disulfide (V-doped MoS2) monolayers via an alkali metal-assisted chemical vapor deposition method. Scanning transmission electron microscopy demonstrated that V atoms substituted the Mo atoms and became uniformly distributed in the MoS2 monolayers. This was also confirmed by Raman and X-ray photoelectron spectroscopy. Power-dependent photoluminescence spectra clearly revealed the enhanced B-exciton emission characteristics in the V-doped MoS2 monolayers (with low doping concentration). Most importantly, through temperature-dependent study, we observed efficient valley scattering of the B-exciton, greatly enhancing its emission intensity. Carrier transport experiments indicated that typical p-type conduction gradually arisen and was enhanced with increasing V composition in the V-doped MoS2, where a clear n-type behavior transited first to ambipolar and then to lightly p-type charge carrier transport. In addition, visible to infrared wide-band photodetectors based on V-doped MoS2 monolayers (with low doping concentration) were demonstrated. The V-doped MoS2 monolayers with distinct B-exciton emission, enhanced p-type conduction and broad spectral response can provide new platforms for probing new physics and offer novel materials for optoelectronic applications.

Solidification of municipal solid waste incineration fly ash with alkali-activated technology.

Alkali-activation is effective municipal solid waste incineration fly ash (MSWIFA) solidification/stabilization (S/S) technology. Percolation and migration of heavy metals in MSWIFA S/S matrix is a complicated and slow process. Here, several alkali-activated MSWIFA samples are selected to comparatively investigate the long-term leaching behavior and environmental availability of Pb, Zn and Cd when exposed in different erosion environment. Acid environment posed the more serious destroy to MSWIFA S/S matrices. RAC demonstrated that potential risk level of heavy metals is higher in acid rain environment, and Cd, Zn showed the prominent risk. When soaked in acid rain solution, the surface of alkali-activated MSWIFA S/S matrices was cracked seriously and a large number of hardened slurry peeled off. However, more stable structural properties and lower heavy metal leachability can be found in alkali-activated MSWIFA/aluminosilicate. The immobilization efficiency of Pb, Zn and Cd were all above 99.0%. Microstructure and morphology results indicated that there is new phase Friedel's salts generated and much more amorphous substance such as C-(A)-S-H gel with incorporation of aluminosilicate, which all contributed much to the formation of compact and stable microstructure, then significantly facilitated the encapsulation of heavy metal. These findings will provide theoretical basis and new insight for resource utilization and security landfill of MSWIFA.

A fully integrated, standalone stretchable device platform with in-sensor adaptive machine learning for rehabilitation.

Post-surgical treatments of the human throat often require continuous monitoring of diverse vital and muscle activities. However, wireless, continuous monitoring and analysis of these activities directly from the throat skin have not been developed. Here, we report the design and validation of a fully integrated standalone stretchable device platform that provides wireless measurements and machine learning-based analysis of diverse vibrations and muscle electrical activities from the throat. We demonstrate that the modified composite hydrogel with low contact impedance and reduced adhesion provides high-quality long-term monitoring of local muscle electrical signals. We show that the integrated triaxial broad-band accelerometer also measures large body movements and subtle physiological activities/vibrations. We find that the combined data processed by a 2D-like sequential feature extractor with fully connected neurons facilitates the classification of various motion/speech features at a high accuracy of over 90%, which adapts to the data with noise from motion artifacts or the data from new human subjects. The resulting standalone stretchable device with wireless monitoring and machine learning-based processing capabilities paves the way to design and apply wearable skin-interfaced systems for the remote monitoring and treatment evaluation of various diseases.

An attention-based multi-modal MRI fusion model for major depressive disorder diagnosis.

Objective.Major depressive disorder (MDD) is one of the biggest threats to human mental health. MDD is characterized by aberrant changes in both structure and function of the brain. Although recent studies have developed some deep learning models based on multi-modal magnetic resonance imaging (MRI) for MDD diagnosis, the latent associations between deep features derived from different modalities were largely unexplored by previous studies, which we hypothesized may have potential benefits in improving the diagnostic accuracy of MDD.Approach.In this study, we proposed a novel deep learning model that fused both structural MRI (sMRI) and resting-state MRI (rs-fMRI) data to enhance the diagnosis of MDD by capturing the interactions between deep features extracted from different modalities. Specifically, we first employed a brain function encoder (BFE) and a brain structure encoder (BSE) to extract the deep features from fMRI and sMRI, respectively. Then, we designed a function and structure co-attention fusion (FSCF) module that captured inter-modal interactions and adaptively fused multi-modal deep features for MDD diagnosis.Main results.This model was evaluated on a large cohort and achieved a high classification accuracy of 75.2% for MDD diagnosis. Moreover, the attention distribution of the FSCF module assigned higher attention weights to structural features than functional features for diagnosing MDD.Significance.The high classification accuracy highlights the effectiveness and potential clinical of the proposed model.

Probing the Twist-Controlled Interlayer Coupling in Artificially Stacked Transition Metal Dichalcogenide Bilayers by Second-Harmonic Generation.

Interlayer coupling plays a critical role in the electronic band structures and optoelectronic properties of van der Waals (vdW) materials and heterostructures. Here, we utilize optical second-harmonic generation (SHG) measurements to probe the twist-controlled interlayer coupling in artificially stacked WSe2/WSe2 homobilayers and WSe2/WS2 and WSe2/MoS2 heterobilayers with a postannealing procedure. In the large angle twisted WSe2/WSe2 and WSe2/WS2, the angular dependence of the SHG intensity follows the interference relations up to angles above 10°. For lower angles, the SHG is significantly suppressed. Furthermore, for the twisted WSe2/MoS2 the SHG intensity largely deviates from the coherent superposition model and shows consistent quenching for all the stacking angles. The suppressed SHG in twisted transition metal dichalcogenide (TMDC) bilayers is predominantly attributed to the interlayer coupling between the two adjacent monolayers. The evolution of the interlayer Raman mode in WSe2 demonstrates that the interlayer coupling in the twisted WSe2/WSe2 and WSe2/WS2 is highly angle-dependent. Alternatively, the interlayer coupling generally exists in the twisted WSe2/MoS2, regardless of the different angles. The interlayer coupling is further confirmed by the quenching and red-shift of the photoluminescence of WSe2 in the twisted TMDC bilayers. Combined with density functional theory calculations, we reveal that the stacking-angle-modulated interlayer coupling originates from the variation of the interlayer spacing and the binding energy in the twisted TMDC bilayers.

Age of Bilingual Onset Shapes the Dynamics of Functional Connectivity and Laterality in the Resting-State.

Bilingualism is known to enhance cognitive function and flexibility of the brain. However, it is not clear how bilingual experience affects the time-varying functional network and whether these changes depend on the age of bilingual onset. This study intended to investigate the bilingual-related dynamic functional connectivity (dFC) based on the resting-state functional magnetic resonance images, including 23 early bilinguals (EBs), 30 late bilinguals (LBs), and 31 English monolinguals. The analysis identified two dFC states, and LBs showed more transitions between these states than monolinguals. Moreover, more frequent left-right switches were found in functional laterality in prefrontal, lateral temporal, lateral occipital, and inferior parietal cortices in EBs compared with LB and monolingual cohorts, and the laterality changes in the anterior superior temporal cortex were negatively correlated with L2 proficiency. These findings highlight how the age of L2 acquisition affects cortico-cortical dFC pattern and provide insight into the neural mechanisms of bilingualism.