Article
Neurosciences
Fanchao Meng, Fenghua Li, Shuxian Wu, Tingyu Yang, Zhou Xiao, Yujian Zhang, Zhengkui Liu, Jianping Lu, Xuerong Luo
Summary: This study found that using eye-tracking techniques with machine learning algorithms could be promising for identifying ASD in children. Attention to human-related elements was positively related to the diagnosis, while fixation time for cartoons was negatively related to the diagnosis.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Clinical Neurology
Jiajun Zhang, Shuanfeng Fang, Yin Yao, Fei Li, Qiang Luo
Summary: This study used a normative model of brain structure to explain the heterogeneity of Autism Spectrum Disorder (ASD). By analyzing the association between brain structure and social symptoms, the study identified four distinct subtypes of ASD with different patterns of brain volume deviations. Subtyping improved the accuracy of ASD classification and may provide insights into the underlying mechanisms of ASD.
JOURNAL OF AFFECTIVE DISORDERS
(2023)
Article
Biochemistry & Molecular Biology
Ting Luo, Si-si Chen, Ye Ruan, Hua-ying Chen, Yu-mei Chen, Ya-min Li, Wen Zhou
Summary: Autism spectrum disorder (ASD) is a complex disease with unclear etiology. Studies have shown that ferroptosis, a form of cell death, is related to ASD progression, but the mechanism behind it is still unknown. Valproic acid (VPA) was found to induce ferroptosis in neurons, and the activation of the PI3K/Akt pathway was inhibited by VPA and other ferroptosis inducers. DDIT4, a protein, was found to play a role in promoting ferroptosis and inhibiting neuronal viability through the PI3K/Akt pathway. In mice with ASD, high levels of oxidative stress and ferroptosis markers were observed, along with increased DDIT4 expression and decreased expression levels of GPX4, p-PI3K, and p-Akt. Knockdown of DDIT4 expression reduced ferroptosis and improved abnormal behaviors in mice with ASD, indicating that DDIT4, the PI3K/Akt pathway, and ferroptosis play important roles in autism.
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
(2023)
Article
Microbiology
Wenjuan Wang, Pengcheng Fu
Summary: The study explores the associations between gut microbiota and autism spectrum disorder (ASD) by analyzing data from different studies. A predictive model based on machine learning algorithm is established to identify potential biomarkers for ASD diagnosis. The results show high accuracy in predicting ASD using gut microbiota, and suggest considering influencing factors in microbial transplantation or dietary therapy.
Article
Genetics & Heredity
Lichun Liu, Yongxing Lai, Zhidong Zhan, Qingxian Fu, Yuelian Jiang
Summary: In this study, the relationship between autism and ferroptosis was explored, and a ferroptosis score model was provided to predict the molecular subtypes and immune infiltration cell profiles of children with autism.
FRONTIERS IN GENETICS
(2022)
Article
Neurosciences
Azadeh Kushki, Robyn E. Cardy, Sina Panahandeh, Mahan Malihi, Christopher Hammill, Jessica Brian, Alana Iaboni, Margot J. Taylor, Russell Schachar, Jennifer Crosbie, Paul Arnold, Elizabeth Kelley, Muhammad Ayub, Robert Nicolson, Stelios Georgiades, Jason P. Lerch, Evdokia Anagnostou
Summary: The study discovered associations between social communication abilities and distributed cortical and subcortical networks implicated in social behaviors, language, attention, memory, and executive functions, as well as three data-driven, diagnosis-agnostic subgroups based on the patterns of association in these networks.
Article
Computer Science, Information Systems
Fengkai Ke, Huanping Liu, Mingcheng Zhou, Rui Yang, Hui-Min Cao
Summary: By analyzing different subgroups of the ASD dataset and using a Random Forest model for classification, the classification accuracy was improved. The study found that different features are closely related to functions of speech, emotion, auditory, and visual information processing, which may help explain symptoms in ASD patients.
Article
Multidisciplinary Sciences
Masud Rabbani, Munirul M. Haque, Dipranjan Das Dipal, Md Ishrak Islam Zarif, Anik Iqbal, Amy Schwichtenberg, Naveen Bansal, Tanjir Rashid Soron, Syed Ishtiaque Ahmed, Sheikh Iqbal Ahamed
Summary: This study aimed to evaluate the behavioral patterns of children with ASD during and after the COVID-19 lockdown, and found that support in the areas of problematic behavior could mitigate future risks.
SCIENTIFIC REPORTS
(2021)
Article
Psychiatry
Michael Davidovitch, Dorit Shmueli, Ran Shmuel Rotem, Aviva Mimouni Bloch
Summary: Most physicians indicated a moderate/significant increase in the incidence of ASD, with over half believing that an ASD diagnosis is given despite inconclusive evaluations in over 10% of clinical assessments. Clinicians perceive both ASD and ADHD as over-diagnosed disorders.
Article
Biology
Olga Fajarda, Joao Rafael Almeida, Sara Duarte-Pereira, Raquel M. Silva, Jose Luis Oliveira
Summary: A large amount of microarray datasets have been produced to identify differentially expressed genes and gene expression signatures, which can contribute to disease diagnosis, prognosis, and therapeutic response. However, most datasets have limited statistical power due to their small sample sizes. To address this issue, we propose a methodology that merges microarray datasets and uses statistical methods along with supervised machine learning algorithms to identify gene expression signatures. This methodology has been validated in heart failure and autism spectrum disorder datasets, achieving high classification accuracy.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biology
Yibin Wang, Haixia Long, Qianwei Zhou, Tao Bo, Jianwei Zheng
Summary: This study proposes a position-aware graph-convolution-network-based model for the diagnosis of Autism Spectrum Disorder (ASD), with superior accuracy and interpretability. The model utilizes a time-series encoder for feature extraction and a connectivity generator to model the correlation with long-range dependencies. It also adopts a position embedding technique to differentiate brain nodes with different locations and employs a rarefying method for reducing dimensionality complexity. The experiments conducted on Autism Brain Imaging Data Exchange demonstrate state-of-the-art performance and provide potential biomarkers for ASD clinical diagnosis.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Chuanchuan Wang, Weixuan Chen, Yishan Jiang, Xiao Xiao, Qianhui Zou, Jiarui Liang, Yu Zhao, Qianxu Wang, Tian Yuan, Rui Guo, Xuebo Liu, Zhigang Liu
Summary: Autism Spectrum Disorder (ASD) symptoms may be improved through modulation of gut microbiota. This study investigated the effects of a synbiotic treatment on an ASD-like mouse model, and found that it rectified social impairments, attenuated inflammatory cytokine expressions, protected gut barrier integrity, and altered gut microbiota composition. The synbiotic treatment elevated beneficial metabolites and upregulated genes associated with their synthesis. Overall, the synbiotic combination mitigated ASD-related social impairments through regulation of the gut-brain axis.
Article
Behavioral Sciences
Orly Kerub, Eric J. Haas, Gal Meiri, Natalya Bilenko, Hagit Flusser, Analya Michaelovski, Ilan Dinstein, Nadav Davidovitch, Idan Menashe
Summary: The prevalence of autism spectrum disorder (ASD) is continuously rising worldwide, with significant differences in ASD rates among different ethnic and socioeconomic groups. A study comparing Bedouin and Jewish toddlers in southern Israel found that while both groups were equally identified in the ASD screening, Bedouin toddlers were less likely to complete the diagnosis process due to higher loss-to-follow-up rates and slower diagnosis process. Facilitating ASD diagnosis for the Bedouin population will help identify more toddlers with ASD.
Editorial Material
Microbiology
Maude M. David
Summary: Autism spectrum disorder (ASD) is a complex disorder influenced by genetic and environmental factors. Studies have suggested a role of the gut microbiome in modulating ASD phenotype, but results remain inconsistent. Future research will require new experimental methodologies to better understand this relationship.
Article
Pediatrics
Pamela High, Ellen J. Silver, Ruth E. K. Stein, Nancy Roizen, Marilyn Augustyn, Nathan Blum
Summary: The objective of this study was to determine the proportion of children referred to academic medical centers with concerns about autism spectrum disorders (ASDs) who received a probable ASD diagnosis. The study found that two thirds of children referred with concerns about ASD were diagnosed with ASD. Children under 4 years old diagnosed as ASD- had more language delay and less cognitive impairment and socialization concerns compared to their ASD+ peers. Children over 4 years old diagnosed as ASD- were more likely to have attention-deficit/hyperactivity disorder (ADHD) and learning disability with normal cognition compared to their ASD+ peers.
ACADEMIC PEDIATRICS
(2022)
Article
Oncology
Ran Li, Lei Zhang, Zhiqiang Qin, Yunfei Wei, Zhonglei Deng, Chen Zhu, Jingyuan Tang, Long Ma
EXPERIMENTAL CELL RESEARCH
(2019)
Article
Cell Biology
Ran Li, Qian-wei Xing, Xiao-lu Wu, Lei Zhang, Min Tang, Jing-yuan Tang, Jing-zi Wang, Peng Han, Shang-qian Wang, Wei Wang, Wei Zhang, Guo-ping Zhou, Zhi-qiang Qin
CELL DEATH & DISEASE
(2019)
Article
Oncology
Qianwei Xing, Ran Li, Aiming Xu, Zhiqiang Qin, Jinyuan Tang, Lei Zhang, Min Tang, Peng Han, Wei Wang, Chao Qin, Mulong Du, Wei Zhang
Review
Oncology
Zuo-you Ding, Ran Li, Qi-jie Zhang, Yi Wang, Yi Jiang, Qing-yang Meng, Qiu-lei Xi, Guo-hao Wu
Article
Environmental Sciences
Lei Zhang, Zhiqiang Qin, Ran Li, Shangqian Wang, Wei Wang, Min Tang, Wei Zhang
ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY
(2019)
Review
Andrology
Lei Zhang, Xian Gao, Ran Li, Kedong Li, Bianjiang Liu, Jie Li, Wei Zhang, Min Tang
TRANSLATIONAL ANDROLOGY AND UROLOGY
(2020)
Article
Immunology
Ran Li, Zuoyou Ding, Peng Jin, Shishuang Wu, Ge Jiang, Rufang Xiang, Wenfang Wang, Zhen Jin, Xiaoyang Li, Kai Xue, Xiaolu Wu, Junmin Li
Summary: The prognosis of acute myeloid leukemia is closely related to changes in immune response. The immune-17 signature established in this study may be a useful model for evaluating AML survival outcomes and improving treatment selection.
FRONTIERS IN IMMUNOLOGY
(2021)
Article
Cell Biology
Kai Xue, Ji-Chuan Wu, Xi-Ya Li, Ran Li, Qun-ling Zhang, Jin-Jia Chang, Yi-Zhen Liu, Chun-Hui Xu, Jia-Ying Zhang, Xiao-Jian Sun, Juan J. Gu, Wei-Jian Guo, Lan Wang
Summary: The study demonstrated that chidamide showed therapeutic effects in rituximab/chemotherapy resistant B-cell lymphoma by inhibiting cell growth, inducing cell death, and activating autophagy pathway. Chidamide targeted BTG1 and FOXO1 genes, regulating autophagy and cell cycle, and enhanced the efficacy when combined with cisplatin in a synergistic manner. These findings provide a theoretical and mechanistic basis for further evaluation of chidamide-based treatment in relapsed and refractory B-cell lymphoma patients.
CELL DEATH & DISEASE
(2021)
Article
Multidisciplinary Sciences
Xiaolu Wu, Ran Li, Qu Xu, Feng Liu, Yue Jiang, Min Zhang, Meiling Tong
Summary: This study aimed to identify potential biomarkers for severe asthma. Through the analysis of gene expression data, researchers identified a set of genes that were associated with metabolism and immune-related processes. Some of these genes were validated to have higher expression levels in severe asthma patients. Network analysis further revealed transcription factors that may be involved in the development of asthma. Additionally, certain drugs were found to interact with these genes and were negatively associated with gene expression.
SCIENTIFIC REPORTS
(2022)
Article
Oncology
Ran Li, Shishuang Wu, Xiaolu Wu, Ping Zhao, Jingyi Li, Kai Xue, Junmin Li
Summary: The study established a prognostic model based on IRL signature for predicting AML patients' overall survival, demonstrating its reliability and effectiveness. The prognostic model, in conjunction with clinical features via a nomogram, improved prognostic accuracy and identified the potential roles of monocytes and metabolism pathways in AML progression.
Article
Cell Biology
Zuoyou Ding, Ran Li, Jun Han, Diya Sun, Lei Shen, Guohao Wu
Summary: This study constructed a prognostic model based on immune-related lncRNAs (IRLs) for predicting overall survival and response to immune checkpoint inhibitors (ICIs) in gastric cancer patients. The IRL signature could distinguish different risk patients and a nomogram efficiently predicted overall survival. Tumor microenvironment and mutation status partially explained the predictive capability of the IRL signature.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Ran Li, Xiaolu Wu, Ping Zhao, Kai Xue, Junmin Li
Summary: The study finds that HDAC11 is aberrantly expressed in multiple types of cancer and is associated with prognosis and tumor immunity. HDAC11 is also correlated with tumor mutational burden, microsatellite instability, and drug sensitivity. These findings provide clues for further understanding of the key role of HDAC11 in multiple cancers.
Article
Oncology
Ran Li, Xiaolu Wu, Kai Xue, Junmin Li
Summary: ITGAL is highly expressed in acute myeloid leukemia and is associated with poor prognosis. It is correlated with age and cytogenetic risk classifications, but not with AML driver gene mutations. Functional analysis reveals that ITGAL is involved in the production and metabolic process of cytokines. Additionally, ITGAL is closely related to the number of MDSCs and cytokine production.
CANCER CELL INTERNATIONAL
(2022)
Article
Oncology
Ran Li, Kai Xue, Junmin Li
Summary: FGF13 is lowly expressed in AML patients and its elevated expression is associated with prolonged survival. It is closely related to the bone marrow microenvironment, T cell count, immune checkpoint genes, and cytokines. Overexpression of FGF13 inhibits AML cell growth and prolongs the survival of recipient mice.
FRONTIERS OF MEDICINE
(2022)