Prdm1 positively regulates liver Group 1 ILCs cancer immune surveillance and preserves functional heterogeneity.

Group 1 innate lymphoid cells (ILCs) comprise conventional natural killer (cNK) cells and type 1 innate lymphoid cells (ILC1s). The main functions of liver cNK cells and ILC1s not only include directly killing target cells but also regulating local immune microenvironment of the liver through the secretion of cytokines. Uncovering the intricate mechanisms by which transcriptional factors regulate and influence the functions of liver cNK cells and ILC1s, particularly within the context of liver tumors, presents a significant opportunity to amplify the effectiveness of immunotherapies against liver malignancies. Using Ncr1-drived conditional knockout mouse model, our study reveals the regulatory role of Prdm1 in shaping the composition and maturation of cNK cells. Although Prdm1 did not affect the killing function of cNK cells in an in vivo cytotoxicity model, a significant increase in cancer metastasis was observed in Prdm1 knockout mice. Interferon-gamma (IFN-γ), granzyme B, and perforin secretion decreased significantly in Prdm1-deficient cNK cells and liver ILC1s. Single-cell RNA sequencing (scRNA-seq) data also provided evidences that Prdm1 maintains functional subsets of cNK cells and liver ILC1s and facilitates communications between cNK cells, liver ILC1s, and macrophages. The present study unveiled a novel regulatory mechanism of Prdm1 in cNK cells and liver ILC1s, showing promising potential for developing innovative immune therapy strategies against liver cancer.

Gapr for large-scale collaborative single-neuron reconstruction.

Whole-brain analysis of single-neuron morphology is crucial for unraveling the complex structure of the brain. However, large-scale neuron reconstruction from terabyte and even petabyte data of mammalian brains generated by state-of-the-art light microscopy is a daunting task. Here, we developed 'Gapr' (Gapr accelerates projectome reconstruction) that streamlines deep learning-based automatic reconstruction, 'automatic proofreading' that reduces human workloads at high-confidence sites, and high-throughput collaborative proofreading by crowd users through the Internet. Furthermore, Gapr offers a seamless user interface that ensures high proofreading speed per annotator, on-demand conversion for handling large datasets, flexible workflows tailored to diverse datasets and rigorous error tracking for quality control. Finally, we demonstrated Gapr's efficacy by reconstructing over 4,000 neurons in mouse brains, revealing the morphological diversity in cortical interneurons and hypothalamic neurons. Here, we present Gapr as a solution for large-scale single-neuron reconstruction projects.

Advances in the Synthesis and Physiological Metabolic Regulation of Nicotinamide Mononucleotide.

Nicotinamide mononucleotide (NMN), the direct precursor of nicotinamide adenine dinucleotide (NAD+), is involved in the regulation of many physiological and metabolic reactions in the body. NMN can indirectly affect cellular metabolic pathways, DNA repair, and senescence, while also being essential for maintaining tissues and dynamic metabolic equilibria, promoting healthy aging. Therefore, NMN has found many applications in the food, pharmaceutical, and cosmetics industries. At present, NMN synthesis strategies mainly include chemical synthesis and biosynthesis. Despite its potential benefits, the commercial production of NMN by organic chemistry approaches faces environmental and safety problems. With the rapid development of synthetic biology, it has become possible to construct microbial cell factories to produce NMN in a cost-effective way. In this review, we summarize the chemical and biosynthetic strategies of NMN, offering an overview of the recent research progress on host selection, chassis cell optimization, mining of key enzymes, metabolic engineering, and adaptive fermentation strategies. In addition, we also review the advances in the role of NMN in aging, metabolic diseases, and neural function. This review provides comprehensive technical guidance for the efficient biosynthesis of NMN as well as a theoretical basis for its application in the fields of food, medicine, and cosmetics.

Biochemical characterization, biosynthesis mechanism, and functional evaluation of selenium-enriched Aspergillus oryzae A02.

The synthesis mechanisms and function evaluation of selenium(Se)-enriched microorganism remain relatively unexplored. This study unveils that total Se content within A. oryzae A02 mycelium soared to an impressive 8462 mg/kg DCW, surpassing Se-enriched yeast by 2-3 times. Selenium exists in two predominant forms within A. oryzae A02: selenoproteins (SeMet 32.1 %, SeCys 14.4 %) and selenium nanoparticles (SeNPs; 53.5 %). The extensive quantitative characterization of the elemental composition, surface morphology, and size of SeNPs on A. oryzae A02 mycelium significantly differs from those reported for other microorganisms. Comparative RNA-Seq analysis revealed the upregulation of functional genes implicated in selenium transformation, activating multiple potential pathways for selenium reduction. The assimilatory and dissimilatory reductions of Se oxyanions engaged numerous parallel and interconnected pathways, manifesting a harmonious equilibrium in overall Se biotransformation in A. oryzae A02. Furthermore, selenium-enriched A. oryzae A02 was observed to primarily upregulate peroxisome activity while downregulating estrogen 2-hydroxylase activity in mice hepatocytes, suggesting its potential in fortifying antioxidant physiological functions and upholding metabolic balance.

Neuromedin U receptor 1 deletion leads to impaired immunotherapy response and high malignancy in colorectal cancer.

Colorectal cancer (CRC) exhibits significant heterogeneity, impacting immunotherapy efficacy, particularly in immune desert subtypes. Neuromedin U receptor 1 (NMUR1) has been reported to perform a vital function in immunity and inflammation. Through comprehensive multi-omics analyses, we have systematically characterized NMUR1 across various tumors, assessing expression patterns, genetic alterations, prognostic significance, immune infiltration, and pathway associations at both the bulk sequencing and single-cell scales. Our findings demonstrate a positive correlation between NMUR1 and CD8+ T cell infiltration, with elevated NMUR1 levels in CD8+ T cells linked to improved immunotherapy outcomes in patients with CRC. Further, we have validated the NMUR1 expression signature in CRC cell lines and patient-derived tissues, revealing its interaction with key immune checkpoints, including lymphocyte activation gene 3 and cytotoxic T-lymphocyte-associated protein 4. Additionally, NMUR1 suppression enhances CRC cell proliferation and invasiveness. Our integrated analyses and experiments open new avenues for personalized immunotherapy strategies in CRC treatment.

Bioinformatics and experimental approach identify lipocalin 2 as a diagnostic and prognostic indicator for lung adenocarcinoma.

BACKGROUND: lipocalin 2 (LCN2) is a secreted glycoprotein that plays key roles in tumorigenesis and progression. Interestingly, LCN2 appears to have a contradictory function in developing lung adenocarcinoma (LUAD). Thus, we intend to explore the role of LCN2 in LUAD through bioinformatics and experimental validation. METHODS: LCN2 expression of LUAD was investigated in the TCGA, TIMER and HPA databases. The relationship between LCN2 and prognosis was investigated by KM plotter, TCGA and GEO databases. GO, KEGG and protein-protein interactions network analysis were conducted to investigate the potential mechanism of LCN2. The relevance of LCN2 to cancer-immune infiltrates was investigated in the TCGA and TIMER databases. Quantitative reverse transcription PCR, western blot and enzyme-linked immunosorbent assay were performed to identify the expression level of LCN2 in cells and serum samples. The CCK-8, wound healing and transwell assay were used to confirm the effect of LCN2 on cell proliferation, migration and invasion in LUAD. The receiver operating characteristic curve was utilized to assess the diagnostic efficiency of LCN2 further. RESULTS: LCN2 expression was significantly upregulated in LUAD (P < 0.05), and was correlated with the clinical stage, tumor size, lymph node metastasis and distant metastasis (P < 0.05). There was a high correlation between high LCN2 and worse prognosis in LUAD. Functional network analysis suggested that LCN2 was associated with multiple signal pathways in cancers, such as JAK-STAT, TNF, NF-κB, HIF-1 and PI3K-Akt signal pathways. In addition, the knockdown of LCN2 significantly inhibited the ability of cell proliferation, migration and invasion. Immune infiltration analysis indicated that LCN2 is associated with multiple immune cell infiltration. Notably, LCN2 demonstrated high diagnostic efficiency for LUAD (AUC = 0.818, P < 0.05), especially for stage III-IV patients could reach 0.895. CONCLUSIONS: LCN2 as an oncogenic glycoprotein promotes the cancer progression related to immune infiltrates, which might be a potential diagnostic and prognostic marker in LUAD.

Autism spectrum disorders detection based on multi-task transformer neural network.

Autism Spectrum Disorders (ASD) are neurodevelopmental disorders that cause people difficulties in social interaction and communication. Identifying ASD patients based on resting-state functional magnetic resonance imaging (rs-fMRI) data is a promising diagnostic tool, but challenging due to the complex and unclear etiology of autism. And it is difficult to effectively identify ASD patients with a single data source (single task). Therefore, to address this challenge, we propose a novel multi-task learning framework for ASD identification based on rs-fMRI data, which can leverage useful information from multiple related tasks to improve the generalization performance of the model. Meanwhile, we adopt an attention mechanism to extract ASD-related features from each rs-fMRI dataset, which can enhance the feature representation and interpretability of the model. The results show that our method outperforms state-of-the-art methods in terms of accuracy, sensitivity and specificity. This work provides a new perspective and solution for ASD identification based on rs-fMRI data using multi-task learning. It also demonstrates the potential and value of machine learning for advancing neuroscience research and clinical practice.

Diagnostic efficacy of virtual organ computer-assisted analysis in measuring the volume ratio of subchorionic hematoma with serum progesterone.

BACKGROUND: Subchorionic hematoma (SCH) is a common complication in early pregnancy characterized by the accumulation of blood between the uterine wall and the chorionic membrane. SCH can lead to adverse pregnancy outcomes such as miscarriage, preterm birth, and other complications. Early detection and accurate assessment of SCH are crucial for appropriate management and improved pregnancy outcomes. AIM: To evaluate the diagnostic efficacy of virtual organ computer-assisted analysis (VOCAL) in measuring the volume ratio of SCH to gestational sac (GS) combined with serum progesterone on early pregnancy outcomes in patients with SCH. METHODS: A total of 153 patients with SCH in their first-trimester pregnancies between 6 and 11 wk were enrolled. All patients were followed up until a gestational age of 20 wk. The parameters of transvaginal two-dimensional ultrasound, including the circumference of SCH (Cs), surface area of SCH (Ss), circumference of GS (Cg), and surface area of GS (Sg), and the parameters of VOCAL with transvaginal three-dimensional ultrasound, including the three-dimensional volume of SCH (3DVs) and GS (3DVg), were recorded. The size of the SCH and its ratio to the GS size (Cs/Cg, Ss/Sg, 3DVs/3DVg) were recorded and compared. RESULTS: Compared with those in the normal pregnancy group, the adverse pregnancy group had higher Cs/Cg, Ss/Sg, and 3DVs/3DVg ratios (P < 0.05). When 3DVs/3DVg was 0.220, the highest predictive performance predicted adverse pregnancy outcomes, resulting in an AUC of 0.767, and the sensitivity, specificity were 70.2%, 75% respectively. VOCAL measuring 3DVs/3DVg combined with serum progesterone gave a diagnostic AUC of 0.824 for early pregnancy outcome in SCH patients, with a high sensitivity of 82.1% and a specificity of 72.1%, which showed a significant difference between AUC. CONCLUSION: VOCAL-measured 3DVs/3DVg effectively quantifies the severity of SCH, while combined serum progesterone better predicts adverse pregnancy outcomes.

Ce-4f as an electron-modulation reservoir weakening Fe-O bond to induce iron vacancies in CeFevNi hydroxide for enhancing oxygen evolution reaction.

Designing novel rare-earth-transition metal composites is at the forefront of electrocatalyst research. However, the modulation of transition metal electronic structures by rare earths to induce vacancy defects and enhance electrochemical performance has rarely been reported. In this study, we systematically investigate the mechanism by which Ce-4f electron modulation weakens the Fe-O bond, thereby altering the electronic structure in CeFevNi hydroxide to improve oxygen evolution reaction (OER) performance. Theoretical calculations and experimental characterizations reveal that Ce-4f orbitals function as electron-modulation reservoirs, capable not only of retaining or donating electrons but also of influencing the material's electronic structure. Moreover, Ce-4f bands optimize the Fe lower Hubbard bands (LHB) and O-2p bands, leading to weakened Fe-O bonds and the formation of cationic vacancies. This change results in the upshift of the d-band center at the active sites, favoring the reaction energy barrier for oxygen intermediates in the OER process. The synthesized catalyst demonstrated an overpotential of 201 mV at 10 mA cm-2 and a lifetime exceeding 200 h at 100 mA cm-2 under alkaline conditions. This work offers a proof-of-concept for the application of the mechanism of rare earth-induced transition metal vacancy defects, providing a general guideline for the design and development of novel highly efficient catalysts.

Acid etching-induced nanocutting of LaNiO3 transplanting self-assembled photodiode array-like LaNiO3/N,P-RGO nanoreactor for efficient photocatalytic hydrogen evolution.

Nanoscale graphene-semiconductor composite photocatalysts with fascinating properties in the photocatalytic hydrogen evolution have inspired numerous interests in broad research fields. The architectures with efficient light response and promoting charge separation at the interface between reduced graphene oxide (RGO) and semiconductor are critical, yet synthesizing them remains a formidable challenge. Herein, the photodiode array-like LaNiO3/N,P-RGO (LNO/N,P-RGO) nanoreactor was constructed using an innovative strategy of acid etching-induced nanocutting self-assembly. Ammonium dihydrogen phosphate working as both a nitrogen phosphorus co-dopant and an acid etching reagent, cuts perovskite LaNiO3 (LNO) nanoparticles into nanorods, which are bonded evenly on the nitrogen phosphorus co-doped reduced graphene oxide (N,P-RGO) to form an n-n semiconductor heterojunction LNO/N,P-RGO as a photodiode array-like nanoreactor via hydrothermal treatment. The photodiode array-like nanostructure exposes more active sites that are conducive to light absorption. The robust Ni-C and P-O bonds promote the narrowing of space-charge region at the interface by UV irradiation, thereby improving the transport of photogenerated carriers by visible light irradiation. The LNO/N,P-RGO nanoreactor exhibits excellent photocatalytic hydrogen evolution performance with a yield of up to 354 µmol g-1 h-1 under UV-visible light, which is 50 times higher than that of pure perovskite LNO, and it also displays favorable recycling stability.

Can environmental policies improve marine ecological efficiency? Examining China's Ecological Civilization Pilot Zones.

Terrestrial ecosystems can benefit from environmental protection policies; however, their impact on marine ecological efficiency deserves further exploration. This study uses China's Ecological Civilization Pilot Zone (ECZ) policy as an example of a quasi-natural experimental study, with data from 11 coastal provinces in China from 2006 to 2019 as the initial sample. First, a Super-SBM model considers undesired outputs to measure marine eco-efficiency, while a synthetic control method (SCM) investigates the effect of environmental regulations on marine eco-efficiency. The results show that ECZ policies can promote marine eco-efficiency and the effect mechanisms of these policies are discussed from national and regional perspectives. This study contributes to the current literature by theoretically evaluating the impact of ECZ policies on the marine environment in coastal areas, enriching the mechanism of integrated environmental policies on marine ecological protection, and providing references for formulating and implementing environmental policies.

Maternal diabetes and risk of attention-deficit/hyperactivity disorder in offspring in a multinational cohort of 3.6 million mother-child pairs.

Previous studies report an association between maternal diabetes mellitus (MDM) and attention-deficit/hyperactivity disorder (ADHD), often overlooking unmeasured confounders such as shared genetics and environmental factors. We therefore conducted a multinational cohort study with linked mother-child pairs data in Hong Kong, New Zealand, Taiwan, Finland, Iceland, Norway and Sweden to evaluate associations between different MDM (any MDM, gestational diabetes mellitus (GDM) and pregestational diabetes mellitus (PGDM)) and ADHD using Cox proportional hazards regression. We included over 3.6 million mother-child pairs between 2001 and 2014 with follow-up until 2020. Children who were born to mothers with any type of diabetes during pregnancy had a higher risk of ADHD than unexposed children (pooled hazard ratio (HR) = 1.16, 95% confidence interval (CI) = 1.08-1.24). Higher risks of ADHD were also observed for both GDM (pooled HR = 1.10, 95% CI = 1.04-1.17) and PGDM (pooled HR = 1.39, 95% CI = 1.25-1.55). However, siblings with discordant exposure to GDM in pregnancy had similar risks of ADHD (pooled HR = 1.05, 95% CI = 0.94-1.17), suggesting potential confounding by unmeasured, shared familial factors. Our findings indicate that there is a small-to-moderate association between MDM and ADHD, whereas the association between GDM and ADHD is unlikely to be causal. This finding contrast with previous studies, which reported substantially higher risk estimates, and underscores the need to reevaluate the precise roles of hyperglycemia and genetic factors in the relationship between MDM and ADHD.

Microalgae as future food: Rich nutrients, safety, production costs and environmental effects.

The improvement of food security and nutrition has attracted wide attention, and microalgae as the most promising food source are being further explored. This paper comprehensively introduces basic and functional nutrients rich in microalgae by elaborated tables incorporating a wide variety of studies and summarizes factors influencing their accumulation effects. Subsequently, multiple comparisons of nutrients were conducted, indicating that microalgae have a high protein content. Moreover, controllable production costs and environmental friendliness prompt microalgae into the list that contains more promising and reliable future food. However, microalgae and -based foods approved and sold are limited strictly, showing that safety is a key factor affecting dietary consideration. Notably, sensory profiles and ingredient clarity play an important role in improving the acceptance of microalgae-based foods. Finally, based on the bottleneck in the microalgae food industry, suggestions for its future development were discussed.

Improved neural network with multi-task learning for Alzheimer's disease classification.

Alzheimer's disease(AD) poses a significant challenge due to its widespread prevalence and the lack of effective treatments, highlighting the urgent need for early detection. This research introduces an enhanced neural network, named ADnet, which is based on the VGG16 model, to detect Alzheimer's disease using two-dimensional MRI slices. ADNet incorporates several key improvements: it replaces traditional convolution with depthwise separable convolution to reduce model parameters, replaces the ReLU activation function with ELU to address potential issues with exploding gradients, and integrates the SE(Squeeze-and-Excitation) module to enhance feature extraction efficiency. In addition to the primary task of MRI feature extraction, ADnet is simultaneously trained on two auxiliary tasks: clinical dementia score regression and mental state score regression. Experimental results demonstrate that compared to the baseline VGG16, ADNet achieves a 4.18% accuracy improvement for AD vs. CN classification and a 6% improvement for MCI vs. CN classification. These findings highlight the effectiveness of ADnet in classifying Alzheimer's disease, providing crucial support for early diagnosis and intervention by medical professionals. The proposed enhancements represent advancements in neural network architecture and training strategies for improved AD classification.

High-throughput mapping of single-neuron projection and molecular features by retrograde barcoded labeling.

Deciphering patterns of connectivity between neurons in the brain is a critical step toward understanding brain function. Imaging-based neuroanatomical tracing identifies area-to-area or sparse neuron-to-neuron connectivity patterns, but with limited throughput. Barcode-based connectomics maps large numbers of single-neuron projections, but remains a challenge for jointly analyzing single-cell transcriptomics. Here, we established a rAAV2-retro barcode-based multiplexed tracing method that simultaneously characterizes the projectome and transcriptome at the single neuron level. We uncovered dedicated and collateral projection patterns of ventromedial prefrontal cortex (vmPFC) neurons to five downstream targets and found that projection-defined vmPFC neurons are molecularly heterogeneous. We identified transcriptional signatures of projection-specific vmPFC neurons, and verified Pou3f1 as a marker gene enriched in neurons projecting to the lateral hypothalamus, denoting a distinct subset with collateral projections to both dorsomedial striatum and lateral hypothalamus. In summary, we have developed a new multiplexed technique whose paired connectome and gene expression data can help reveal organizational principles that form neural circuits and process information.

Development and evaluation of a human CD47/HER2 bispecific antibody for Trastuzumab-resistant breast cancer immunotherapy.

The treatment for trastuzumab-resistant breast cancer (BC) remains a challenge in clinical settings. It was known that CD47 is preferentially upregulated in HER2+ BC cells, which is correlated with drug resistance to trastuzumab. Here, we developed a novel anti-CD47/HER2 bispecific antibody (BsAb) against trastuzumab-resistant BC, named IMM2902. IMM2902 demonstrated high binding affinity, blocking activity, antibody-dependent cellular cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP), and internalization degradation effects against both trastuzumab-sensitive and trastuzumab-resistant BC cells in vitro. The in vivo experimental data indicated that IMM2902 was more effective than their respective controls in inhibiting tumor growth in a trastuzumab-sensitive BT474 mouse model, a trastuzumab-resistant HCC1954 mouse model, two trastuzumab-resistant patient-derived xenograft (PDX) mouse models and a cord blood (CB)-humanized HCC1954 mouse model. Through spatial transcriptome assays, multiplex immunofluorescence (mIFC) and in vitro assays, our findings provided evidence that IMM2902 effectively stimulates macrophages to generate C-X-C motif chemokine ligand (CXCL) 9 and CXCL10, thereby facilitating the recruitment of T cells and NK cells to the tumor site. Moreover, IMM2902 demonstrated a high safety profile regarding anemia and non-specific cytokines release. Collectively, our results highlighted a novel therapeutic approach for the treatment of HER2+ BCs and this approach exhibits significant anti-tumor efficacy without causing off-target toxicity in trastuzumab-resistant BC cells.

Effects of sequential vs single pneumococcal vaccination on cardiovascular diseases among older adults: a population-based cohort study.

BACKGROUND: Recommendations around the use of 23-valent pneumococcal polysaccharide vaccine (PPSV23) and 13-valent pneumococcal conjugate vaccine (PCV13) seldom focus on potential benefits of vaccine on comorbidities. We aimed to investigate whether sequential vaccination with PCV13 and PPSV23 among older adults would provide protection against cardiovascular diseases (CVD) compared with using a single pneumococcal vaccine. METHODS: We conducted a Hong Kong-wide retrospective cohort study between 2012 and 2020. Adults aged ≥65 years were identified as receiving either a single or sequential dual vaccination and followed up until the earliest CVD occurrence, death or study end. To minimize confounding, we matched each person receiving a single vaccination to a person receiving sequential vaccination according to their propensity scores. We estimated the hazard ratio (HR) of CVD risk using Cox regression and applied structural equation modelling to test whether the effect of sequential dual vaccination on CVD was mediated via the reduction in pneumonia. RESULTS: After matching, 69 390 people remained in each group and the median (interquartile range) follow-up time was 1.89 (1.55) years. Compared with those receiving a single vaccine, those receiving sequential dual vaccination had a lower risk of CVD [HR (95% CI): 0.75 (0.71, 0.80), P < 0.001]. Post-hoc mediation analysis showed strong evidence that the decreased CVD risk was mediated by the reduction in all-cause pneumonia. CONCLUSIONS: Sequential dual pneumococcal vaccination was associated with lower risk of CVD compared with single-dose PCV13 or PPSV23 in older adults. Such additional CVD benefits should be considered when making decisions about pneumococcal vaccination.

Nitrated T cell epitope linked vaccine targeting CD47 elicits antitumor immune responses and acts synergistically with vaccine targeting PDL1.

Despite the clinical breakthrough made by immune checkpoint blockades (ICB) in cancer immunotherapy, immunosuppressed tumor microenvironment (TME) remains a major impediment in the efficacy of ICB immunotherapy. In this study, we constructed a Nitrated T cell epitope (NitraTh) linked vaccine targeting CD47, namely CD47-NitraTh. CD47-NitraTh could repress the progression of tumor by inducing tumor-specific immune response. Furthermore, combination vaccination with CD47-NitraTh and PDL1-NitraTh could reconstruct tumor associated macrophage, enhance macrophage-mediated phagocytosis for tumor cells, and promote the activation of tumor infiltrating T cells. Notably, by activating chemokine signaling pathway, NitraTh based vaccines reversed immunosuppressed TME, resulting in improved therapeutic outcome for tumor. With the advantage of reversing immunosuppressed TME, NitraTh based vaccine seems an optimal immunotherapy strategy for patients who are not sensitive to antibody based ICB.

Resolving heterogeneity in dynamics of synchronization stability within the salience network in autism spectrum disorder.

BACKGROUND: Heterogeneity in resting-state functional connectivity (FC) are one of the characteristics of autism spectrum disorder (ASD). Traditional resting-state FC primarily focuses on linear correlations, ignoring the nonlinear properties involved in synchronization between networks or brain regions. METHODS: In the present study, the cross-recurrence quantification analysis, a nonlinear method based on dynamical systems, was utilized to quantify the synchronization stability between brain regions within the salience network (SN) of ASD. Using the resting-state functional magnetic resonance imaging data of 207 children (ASD/typically-developing controls (TC): 105/102) in Autism Brain Imaging Data Exchange database, we analyzed the laminarity and trapping time differences of the synchronization stability between the ASD subtype derived by a K-means clustering analysis and the TC group, and examined the relationship between synchronization stability and the severity of clinical symptoms of the ASD subtypes. RESULTS: Based on the synchronization stability within the SN of ASD, we identified two subtypes that showed opposite changes in synchronization stability relative to the TC group. In addition, the synchronization stability of ASD subtypes 1 and 2 can predict the social interaction and communication impairments, respectively. CONCLUSIONS: These findings reveal that ASD subgroups with different patterns of synchronization stability within the SN appear distinct clinical symptoms, and highlight the importance of exploring the potential neural mechanism of ASD from a nonlinear perspective.