Based on Immune Microenvironment and Genomic Status, Exploring Immunotherapy in Advanced Hidradenocarcinoma: A Retrospective Analysis.

There are no standard treatment guidelines for hidradenocarcinoma, and the immune microenvironment and genomic data are very limited. Thus, in this study the immune microenvironment and genomic indicators in hidradenocarcinoma was investigated, and immunotherapy for hidradenocarcinoma was initially explored. Forty-seven hidradenocarcinoma patients were retrospectively collected. Immunohistochemical staining was performed to identify CD3/CD8+ T cells and programmed death ligand-1 expression. In total, 89.4% and 10.6% of samples had Immunoscores of 0-25% and 25-70%. Tumour proportion score distribution was as follows: tumour proportion score < 1% in 72.4%, 1-5% in 17.0%, and > 5% in 10.6%. Combined positive score distribution was as follows: combined positive score < 1 in 63.8%, 1-5 in 14.9%, and > 5 in 21.3%. Next-generation sequencing revealed that TP53 (33%), PI3KCA (22%), and ERBB3 (22%) were the most frequently mutated genes. The PI3K-Akt signalling pathway, growth, and MAPK signalling pathways were significantly enriched. Five patients had a low TMB (< 10 muts/Mb), and 9 patients had MSS. Three patients treated with immune combined with chemotherapy achieved significant tumour regression, and the progression-free survival was 28.8 months. In conclusion, the hidradenocarcinoma immune microenvironment tends to be noninflammatory. Evidence-based targets for targeted therapy are lacking. Immunotherapy combined with chemotherapy may be better for most advanced hidradenocarcinoma patients with a noninflammatory microenvironment.

A clinical and computed tomography-based nomogram to predict the outcome in patients with anterior circulation large vessel occlusion after endovascular mechanical thrombectomy.

PURPOSE: To explore the positive predictors of the clinical outcome in acute ischemic stroke (AIS) patients with anterior circulation large vessel occlusion (ACLVO) after endovascular mechanical thrombectomy (EMT) at a 90-day follow-up, and to establish a nomogram model to predict the clinical outcome. MATERIALS AND METHODS: AIS patients with ACLVO detected by multimodal Computed Tomography imaging who underwent EMT were collected. Patients were divided into the favorable and the unfavorable groups according to the 90-day modified Rankin Scale (mRS) score. Univariate and multivariate analyses were performed to investigate predictors of the favorable outcome (mRS of 0-2). A nomogram model for predicting the clinical outcome after EMT was drawn, and the receiver operating characteristic (ROC) curve was used to evaluate its predictive value. RESULTS: Totally 105 patients including 65 patients in the favorable group and 40 in the unfavorable group were enrolled. Multivariate logistic regression analysis showed that admission National Institute of Health Stroke scale (NIHSS) score [0.858 (95% CI 0.778-0.947)], ACLVO at M2 [20.023 (95% CI 2.204-181.907)] and infarct core (IC) volume [0.943 (95% CI 0.917-0.969)] was positively correlated with favorable outcome. The accuracy of the nomogram model in predicting the outcome was 0.923 (95% CI 0.870-0.976), with a cutoff value of 119.6 points. The area under the ROC curve was 0.848 (95% CI 0.780-0.917; sensitivity, 79.7%; specificity, 90.0%). CONCLUSION: A low Admission NIHSS score, ACLVO at M2, and a small IC volume were positive predictors for favorable outcome. The nomogram model may well predict the outcome in AIS patients with ACLVO after EMT.

Csn5 inhibits autophagy by regulating the ubiquitination of Atg6 and Tor to mediate the pathogenicity of Magnaporthe oryzae.

Csn5 is subunit 5 of the COP9 signalosome (CSN), but the mechanism by which it strictly controls the pathogenicity of pathogenic fungi through autophagy remains unclear. Here, we found that Csn5 deficiency attenuated pathogenicity and enhanced autophagy in Magnaporthe oryzae. MoCSN5 knockout led to overubiquitination and overdegradation of MoTor (the core protein of the TORC1 complex [target of rapamycin]) thereby promoted autophagy. In addition, we identified MoCsn5 as a new interactor of MoAtg6. Atg6 was found to be ubiquitinated through linkage with lysine 48 (K48) in cells, which is necessary for infection-associated autophagy in pathogenic fungi. K48-ubiquitination of Atg6 enhanced its degradation and thereby inhibited autophagic activity. Our experimental results indicated that MoCsn5 promoted K48-ubiquitination of MoAtg6, which reduced the MoAtg6 protein content and thus inhibited autophagy. Aberrant ubiquitination and autophagy in ΔMocsn5 led to pleiotropic defects in the growth, development, stress resistance, and pathogenicity of M. oryzae. In summary, our study revealed a novel mechanism by which Csn5 regulates autophagy and pathogenicity in rice blast fungus through ubiquitination.

Acquisition of 2C-like totipotency through defined maternal-effect factors.

Fully grown oocytes have the natural ability to transform two terminally differentiated gametes into a totipotent zygote representing acquisition of totipotency. This process wholly depends on maternal-effect factors (MFs). MFs stored in the eggs are therefore likely to be able to induce cellular reprogramming to a totipotency state. Here we report the generation of totipotent-like stem cells from mESCs using 4MFs Hsf1, Zar1, Padi6 and Npm2, designated as MFiTLSCs. MFiTLSCs exhibited unique and inherent capability to differentiate into embryonic and extraembryonic derivatives. Transcriptomic analysis revealed that MFiTLSCs are enriched with 2-cell-specific genes that appear to synergistically induce a transcriptional repressive state, in that parental genomes are remodelled to a poised transcriptional repression state while totipotency is established following fertilization. This method to derive MFiTLSCs could help advance understanding of fate determinations of totipotent stem cells in a physiological context and establish a foundation for development of oocyte biology-based reprogramming technology.

Low-cost dual-energy CBCT by spectral filtration of a dual focal spot X-ray source.

Dual-energy cone beam computed tomography (DE-CBCT) has been shown to provide more information and improve performance compared to a conventional single energy spectrum CBCT. Here we report a low-cost DE-CBCT by spectral filtration of a carbon nanotube x-ray source array. The x-ray photons from two focal spots were filtered respectively by a low and a high energy filter. Projection images were collected by alternatively activating the two beams while the source array and detector rotated around the object, and were processed by a one-step materials decomposition and reconstruction method. The performance of the DE-CBCT scanner was evaluated by imaging a water-equivalent plastic phantom with inserts containing known densities of calcium or iodine and an anthropomorphic head phantom with dental implants. A mean energy separation of 15.5 keV was achieved at acceptable dose rates and imaging time. Accurate materials quantification was obtained by materials decomposition. Metal artifacts were reduced in the virtual monoenergetic images synthesized at high energies. The results demonstrated the feasibility of high quality DE-CBCT imaging by spectral filtration without using either an energy sensitive detector or rapid high voltage switching.

A carbon nanotube x-ray source array designed for a new multisource cone beam computed tomography scanner.

Cone beam computed tomography (CBCT) is known to suffer from strong scatter and cone beam artifacts. The purpose of this study is to develop and characterize a rapidly scanning carbon nanotube (CNT) field emission x-ray source array to enable a multisource CBCT (ms-CBCT) image acquisition scheme which has been demonstrated to overcome these limitations. A CNT x-ray source array with eight evenly spaced focal spots was designed and fabricated for a medium field of view ms-CBCT for maxillofacial imaging. An external multisource collimator was used to confine the radiation from each focal spot to a narrow cone angle. For ms-CBCT imaging, the array was placed in the axial direction and rapidly scanned while rotating continuously around the object with a flat panel detector. The x-ray beam profile, temporal and spatial resolutions, energy and dose rate were characterized and evaluated for maxillofacial imaging. The CNT x-ray source array achieved a consistent focal spot size of 1.10 ± 0.04 mm × 0.84 ± 0.03 mm and individual beam cone angle of 2.4°±0.08 after collimation. The x-ray beams were rapidly switched with a rising and damping times of 0.21 ms and 0.19 ms, respectively. Under the designed operating condition of 110 kVp and 15 mA, a dose rate of 8245µGy s-1was obtained at the detector surface with the inherent Al filtration and 2312µGy s-1with an additional 0.3 mm Cu filter. There was negligible change of the x-ray dose rate over many operating cycles. A ms-CBCT scan of an adult head phantom was completed in 14.4 s total exposure time for the imaging dose in the range of that of a clinical CBCT scanner. A spatially distributed CNT x-ray source array was designed and fabricated. It has enabled a new multisource CBCT to overcome some of the main inherent limitations of the conventional CBCT.

Tracheal computed tomography radiomics model for prediction of the Omicron variant of severe acute respiratory syndrome coronavirus 2.

OBJECTIVES: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly contagious, fast-spreading, and insidious. Most patients present with normal findings on lung computed tomography (CT). The current study aimed to develop and validate a tracheal CT radiomics model to predict Omicron variant infection. MATERIALS AND METHODS: In this retrospective study, a radiomics model was developed based on a training set consisting of 157 patients with an Omicron variant infection and 239 healthy controls between 1 January and 30 April 2022. A set of morphological expansions, with dilations of 1, 3, 5, 7, and 9 voxels, was applied to the trachea, and radiomic features were extracted from different dilation voxels of the trachea. Logistic regression (LR), support vector machines (SVM), and random forests (RF) were developed and evaluated; the models were validated on 67 patients with the Omicron variant and on 103 healthy controls between 1 May and 30 July 2022. RESULTS: Logistic regression with 12 radiomic features extracted from the tracheal wall with dilation of 5 voxels achieved the highest classification performance compared with the other models. The LR model achieved an area under the curve of 0.993 (95% confidence interval [CI]: 0.987-0.998) in the training set and 0.989 (95% CI: 0.979-0.999) in the validation set. Sensitivity, specificity, and accuracy of the model for the training set were 0.994, 0.946, and 0.965, respectively, whereas those for the validation set were 0.970, 0.952, and 0.959, respectively. CONCLUSION: The tracheal CT radiomics model reliably identified the Omicron variant of SARS-CoV­2, and may help in clinical decision-making in future, especially in cases of normal lung CT findings.

Improving the accuracy of bone mineral density using a multisource CBCT.

Multisource cone beam computed tomography CBCT (ms-CBCT) has been shown to overcome some of the inherent limitations of a conventional CBCT. The purpose of this study was to evaluate the accuracy of ms-CBCT for measuring the bone mineral density (BMD) of mandible and maxilla compared to the conventional CBCT. The values measured from a multi-detector CT (MDCT) were used as substitutes for the ground truth. An anthropomorphic adult skull and tissue equivalent head phantom and a homemade calibration phantom containing inserts with varying densities of calcium hydroxyapatite were imaged using the ms-CBCT, the ms-CBCT operating in the conventional single source CBCT mode, and two clinical CBCT scanners at similar imaging doses; and a clinical MDCT. The images of the anthropomorphic head phantom were reconstructed and registered, and the cortical and cancellous bones of the mandible and the maxilla were segmented. The measured CT Hounsfield Unit (HU) and Greyscale Value (GV) at multiple region-of-interests were converted to the BMD using scanner-specific calibration functions. The results from the various CBCT scanners were compared to that from the MDCT. Statistical analysis showed a significant improvement in the agreement between the ms-CBCT and MDCT compared to that between the CBCT and MDCT.

Automated pancreatic segmentation and fat fraction evaluation based on a self-supervised transfer learning network.

Accurate segmentation of the pancreas from abdominal computed tomography (CT) images is challenging but essential for the diagnosis and treatment of pancreatic disorders such as tumours and diabetes. In this study, a dataset with 229 sets of high-resolution CT images was generated and annotated. We proposed a novel 3D segmentation model named nnTransfer (nonisomorphic transfer learning) net, which employs generative model structure for self-supervision to facilitate the network's learning of image attributes from unlabelled data. The effectiveness for pancreas segmentation of nnTransfer was assessed using the Hausdorff distance (HD) and Dice similarity coefficient (DSC) on the dataset. Additionally, a histogram analysis with local thresholding was used to achieve automated whole-volume measurement of pancreatic fat (fat volume fraction, FVF). The proposed technique performed admirably on the dataset, with DSC: 0.937 ± 0.019 and HD: 2.655 ± 1.479. The mean pancreas volume and FVF of the pancreas were 91.95 ± 23.90 cm3 and 12.67 % ± 9.84 %, respectively. The nnTransfer functioned flawlessly and autonomously, facilitating the use of the FVF to evaluate pancreatic disease, particularly in patients with diabetes.

SP-141 targets Trs85 to inhibit rice blast fungus infection and functions as a potential broad-spectrum antifungal agent.

Rice blast is a devastating disease worldwide, threatening rice production and food security. The blast fungus Magnaporthe oryzae invades the host via the appressorium, a specialized pressure-generating structure that generates enormous turgor pressure to penetrate the host cuticle. However, owing to ongoing evolution of fungicide resistance, it is vitally important to identify new targets and fungicides. Here, we show that Trs85, a subunit of the transport protein particle III complex, is essential for appressorium-mediated infection in M. oryzae. We explain how Trs85 regulates autophagy through Ypt1 (a small guanosine triphosphatase protein) in M. oryzae. We then identify a key conserved amphipathic α helix within Trs85 that is associated with pathogenicity of M. oryzae. Through computer-aided screening, we identify a lead compound, SP-141, that affects autophagy and the Trs85-Ypt1 interaction. SP-141 demonstrates a substantial capacity to effectively inhibit infection caused by the rice blast fungus while also exhibiting wide-ranging potential as an antifungal agent with broad-spectrum activity. Taken together, our data show that Trs85 is a potential new target and that SP-141 has potential for the control of rice blast. Our findings thus provide a novel strategy that may help in the fight against rice blast.

Shared atypical spontaneous brain activity pattern in early onset schizophrenia and autism spectrum disorders: evidence from cortical surface-based analysis.

Schizophrenia and autism spectrum disorders (ASD) were considered as two neurodevelopmental disorders and had shared clinical features. we hypothesized that they have some common atypical brain functions and the purpose of this study was to explored the shared brain spontaneous activity strength alterations in early onset schizophrenia (EOS) and ASD in the children and adolescents with a multi-center large-sample study. A total of 171 EOS patients (aged 14.25 ± 1.87), 188 ASD patients (aged 9.52 ± 5.13), and 107 healthy controls (aged 11.52 ± 2.82) had scanned with Resting-fMRI and analyzed surface-based amplitude of low-frequency fluctuations (ALFF). Results showed that both EOS and ASD had hypoactivity in the primary sensorimotor regions (bilateral primary and early visual cortex, left ventral visual stream, left primary auditory cortex) and hyperactivity in the high-order transmodal regions (bilateral SFL, bilateral DLPFC, right frontal eye fields), and bilateral thalamus. EOS had more severe abnormality than ASD. This study revealed shared functional abnormalities in the primary sensorimotor regions and the high-order transmodal regions in EOS and ASD, which provided neuroimaging evidence of common changes in EOS and ASD, and may help with better early recognition and precise treatment for EOS and ASD.

The Improvement in Function of Poststroke Spasticity by Vibrational and Heated Stone-Needle Therapy and Meridian Dredging Exercise: A Randomized, Controlled, Preliminary Trial.

BACKGROUND: Poststroke spasticity (PSS) is a common complication of stroke. Current PSS treatments have been linked to high costs, lack of long-term effectiveness, and undesirable side effects. Vibrational and heated stone-needle therapy (VHS) has not been utilized to treat PSS, and its safety and effectiveness have yet to be proven by high-quality clinical research. OBJECTIVE: The aim of this study was to determine the effectiveness of VHS combined with meridian dredging exercise (MDE) in patients with PSS. METHODS: One hundred participants with stroke were included and randomly assigned to a treatment group (VHS plus MDEs) and a control group (MDEs alone). Patients in both groups were treated for 4 weeks. The primary outcome measures were the Modified Ashworth Scale (MAS) and Fugl-Meyer Assessment (FMA), while the secondary outcome measures were the Activity of Daily Living (ADL) Scale and Stroke-Specific Quality of Life Scale (SS-QOL). The evaluations were at baseline (T0) at 4 weeks of treatment (T1) and at 12 weeks of follow-up without treatment (T2). RESULTS: At T1 and T2, there were significant differences in MAS between the two groups (p = 0.001). From the perspective of distribution, the VHS plus MDE group had significant changes, and the group-time interactions of upper and lower extremities in FMA, ADL, and SS-QOL were statistically significant (p < 0.001), indicating that patients' symptoms improved after treatment. But the overall effect size is small, especially the effect size of improvement in SS-QOL at T1. CONCLUSION: VHS in combination with MDE can consistently alleviate PSS, enhance limb function, and improve the quality of life of patients with PSS. But we need to optimize the device further and observe the improvement of patients for a more extended period.Spastik nach Schlaganfall (PSS; post-stroke spasticity) ist eine häufige Komplikation des Schlaganfalls. Gegenwärtige PSS-Behandlungen sind mit hohen Kosten, mangelnder langfristiger Wirksamkeit und unerwünschten Nebenwirkungen in Verbindung gebracht worden. Vibrierende und erhitzte Steinnadeln (VHS) sind bisher nicht zur Behandlung des PSS eingesetzt worden, und der Nachweis ihrer Sicherheit und Wirksamkeit durch hochwertige klinische Forschung steht noch aus.Beurteilung der Wirksamkeit von vibrierenden und erhitzten Steinnadeln (VHS) in Kombination mit Meridian-Ausbagger-Übungen (MDE) bei Patienten mit PSS.100 Patienten mit Schlaganfall wurden eingeschlossen und per Randomisierung auf eine Behandlungsgruppe (VHS plus MDEs) und eine Kontrollgruppe (nur MDE) aufgeteilt. In beiden Gruppen wurden die Patienten 4 Wochen lang behandelt. Die primären Messinstrumente waren die Modified Ashworth Scale (MAS) und das Fugl-Meyer Assessment (FMA), als sekundäre Messinstrumente wurden die Activity of Daily Living Scale (ADL) und die Stroke-Specific Quality of Life Scale (SS-QOL) erhoben. Die Beurteilungszeitpunkte waren bei Baseline (T0) nach 4 Wochen Behandlung (T1) und nach 12 Wochen Nachbeobachtung ohne Behandlung (T2).Bei T1 und T2 bestanden signifikante Unterschiede bei der MAS zwischen den Gruppen (p = 0.001). Aus der Perspektive der Distribution zeigte die "VHS plus MDE"-Gruppe signifikante Veränderungen, und die Gruppe*Zeit-Interaktionen der oberen and unteren Extremitäten bei FMA, ADL und SS-QOL waren statistisch signifikant (p < 0.001), was darauf hindeutet, dass die Beschwerden der Patienten sich nach der Behandlung besserten. Die Effektstärke ist allerdings gering, insbesondere die der SS-QOL-Verbesserung bei T1.Die Anwendung von vibrierenden und erhitzten Steinnadeln in Kombination mit Meridian-Ausbagger-Übungen kann PSS durchgängig lindern, die Funktion der Extremitäten verbessern und die Lebensqualität der Patienten mit PSS erhöhen. Jedoch muss das Produkt weiter optimiert werden, und die Verbesserungen bei den Patienten müssen über einen längeren Zeitraum beobachtet werden.

Large-scale pancreatic cancer detection via non-contrast CT and deep learning.

Pancreatic ductal adenocarcinoma (PDAC), the most deadly solid malignancy, is typically detected late and at an inoperable stage. Early or incidental detection is associated with prolonged survival, but screening asymptomatic individuals for PDAC using a single test remains unfeasible due to the low prevalence and potential harms of false positives. Non-contrast computed tomography (CT), routinely performed for clinical indications, offers the potential for large-scale screening, however, identification of PDAC using non-contrast CT has long been considered impossible. Here, we develop a deep learning approach, pancreatic cancer detection with artificial intelligence (PANDA), that can detect and classify pancreatic lesions with high accuracy via non-contrast CT. PANDA is trained on a dataset of 3,208 patients from a single center. PANDA achieves an area under the receiver operating characteristic curve (AUC) of 0.986-0.996 for lesion detection in a multicenter validation involving 6,239 patients across 10 centers, outperforms the mean radiologist performance by 34.1% in sensitivity and 6.3% in specificity for PDAC identification, and achieves a sensitivity of 92.9% and specificity of 99.9% for lesion detection in a real-world multi-scenario validation consisting of 20,530 consecutive patients. Notably, PANDA utilized with non-contrast CT shows non-inferiority to radiology reports (using contrast-enhanced CT) in the differentiation of common pancreatic lesion subtypes. PANDA could potentially serve as a new tool for large-scale pancreatic cancer screening.

Inhibitor screening for volume-sensitive LRRC8A chloride channel.

Leucine-rich repeat-containing protein 8 A (LRRC8A) protein is a critical member of volume-regulated anion channels. It plays a critical roles in the regulation of cellular volume and involves in the development of diseases like osteoarthritis. Screening of lead compounds to modulate its function may provide potential therapeutics of related diseases. Here, we employ virtual screening techniques and molecular dynamics (MD) simulation to screen potential inhibitors against LRRC8A. LRRC8A was regarded as the drug target to investigate potential compounds from the ZINC15 database via molecular docking. The final compound was selected among the top 10 Autodock Vina score (-8.8 Kcal/mol) with the ZINC ID ZINC000018195627 after druggability prediction. The docked complex from the virtual screening was subjected to MD simulation to analyze the stability of the LRRC8A protein-ligand complex, with parameters including root mean square deviation, root mean square fluctuation and radius of gyration. Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method was further employed to predict the binding free energies from MD simulation trajectory. Our study provides insightful analysis for the potential compound to modulate LRRC8A and lay the foundation of therapeutics development against osteoarthritis.Communicated by Ramaswamy H. Sarma.

Machine learning-based early diagnosis of autism according to eye movements of real and artificial faces scanning.

Background: Studies on eye movements found that children with autism spectrum disorder (ASD) had abnormal gaze behavior to social stimuli. The current study aimed to investigate whether their eye movement patterns in relation to cartoon characters or real people could be useful in identifying ASD children. Methods: Eye-tracking tests based on videos of cartoon characters and real people were performed for ASD and typically developing (TD) children aged between 12 and 60 months. A three-level hierarchical structure including participants, events, and areas of interest was used to arrange the data obtained from eye-tracking tests. Random forest was adopted as the feature selection tool and classifier, and the flattened vectors and diagnostic information were used as features and labels. A logistic regression was used to evaluate the impact of the most important features. Results: A total of 161 children (117 ASD and 44 TD) with a mean age of 39.70 ± 12.27 months were recruited. The overall accuracy, precision, and recall of the model were 0.73, 0.73, and 0.75, respectively. Attention to human-related elements was positively related to the diagnosis of ASD, while fixation time for cartoons was negatively related to the diagnosis. Conclusion: Using eye-tracking techniques with machine learning algorithms might be promising for identifying ASD. The value of artificial faces, such as cartoon characters, in the field of ASD diagnosis and intervention is worth further exploring.

Prevalence of co-occurring severe depression and psychotic symptoms in college students and its relationship with childhood maltreatment.

BACKGROUND: It has been demonstrated that childhood maltreatment (CM) is associated with an increased risk of depression and psychotic symptoms. However, there is still a lack of studies on the prevalence of co-occurring severe depression and psychotic symptoms (CSDPS) and the association between CM and CSDPS among college students. OBJECTIVE: We aim to investigate the prevalence and demographic distribution of CSDPS among Chinese college students and to examine its relationship with CM. PARTICIPANTS AND SETTING: A total of 7351 college students aged 18 and above completed the survey. Finally, 6854 valid questionnaires were included for further analysis. METHODS: The Childhood Trauma Questionnaire and the item for witnessing domestic violence were used to assess the CM. The Prodromal Questionnaire-16 and the depression subscale of the Depression Anxiety and Stress-21 scale were used to assess psychotic symptoms and depressive symptoms. RESULTS: The prevalence of CSDPS was 1.47 % among the college students. The multivariate logistic regression analysis showed that emotional abuse and emotional neglect were associated with an increased risk of CSDPS (all p < 0.05). The risk of CSDPS was dramatically increased for individuals who had experienced ≥3 types of CM (OR = 22.929, p < 0.001), as compared to those who had experienced 1-2 types of CM (OR = 4.452, p < 0.001) and those without the experience of CM. CONCLUSION: CM was found to be associated with an increased risk of CSDPS among the college students. Notably, experiencing more types of CM was also associated with a higher risk of CSDPS.

The enteric nervous system deficits in autism spectrum disorder.

Gastrointestinal (GI) disorders are common comorbidities in individuals with autism spectrum disorder (ASD), and abnormalities in these issues have been found to be closely related to the severity of core behavioral deficits in autism. The enteric nervous system (ENS) plays a crucial role in regulating various aspects of gut functions, including gastrointestinal motility. Dysfunctional wiring in the ENS not only results in various gastrointestinal issues, but also correlates with an increasing number of central nervous system (CNS) disorders, such as ASD. However, it remains unclear whether the gastrointestinal dysfunctions are a consequence of ASD or if they directly contribute to its pathogenesis. This review focuses on the deficits in the ENS associated with ASD, and highlights several high-risk genes for ASD, which are expressed widely in the gut and implicated in gastrointestinal dysfunction among both animal models and human patients with ASD. Furthermore, we provide a brief overview of environmental factors associated with gastrointestinal tract in individuals with autism. This could offer fresh perspectives on our understanding of ASD.