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  1. Article ; Online: Do obstructive sleep apnea and chronic obstructive pulmonary disease overlap coincidently or intrinsically?

    Xie, Jiang

    Heart & lung : the journal of critical care

    2019  Volume 48, Issue 5, Page(s) 466

    Language English
    Publishing date 2019-05-13
    Publishing country United States
    Document type Letter
    ZDB-ID 193129-5
    ISSN 1527-3288 ; 0147-9563
    ISSN (online) 1527-3288
    ISSN 0147-9563
    DOI 10.1016/j.hrtlng.2019.05.002
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    Zs.A 1035: Show issues Location:
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  2. Article: 咖啡因治疗早产儿呼吸暂停相关基因多态性的研究进展.

    Xie, Jiang-Biao / Lin, Xin-Zhu

    Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics

    2022  Volume 24, Issue 7, Page(s) 832–837

    Abstract: Apnea of prematurity (AOP) is one of the common diseases in preterm infants. The main cause of AOP is immature development of the respiratory control center. If AOP is not treated timely and effectively, it will lead to respiratory failure, hypoxic brain ...

    Title translation Recent research on gene polymorphisms related to caffeine therapy in preterm infants with apnea of prematurity.
    Abstract Apnea of prematurity (AOP) is one of the common diseases in preterm infants. The main cause of AOP is immature development of the respiratory control center. If AOP is not treated timely and effectively, it will lead to respiratory failure, hypoxic brain injury, and even death in severe cases. Caffeine is the first choice for the treatment of AOP, but its effectiveness varies in preterm infants. With the deepening of AOP research, more and more genetic factors have been confirmed to play important roles in the pathogenesis and treatment of AOP; in particular, the influence of single nucleotide polymorphism on the efficacy of caffeine has become a research hotspot in recent years. This article reviews the gene polymorphisms that affect the efficacy of caffeine, in order to provide a reference for individualized caffeine therapy. Citation.
    MeSH term(s) Apnea/drug therapy ; Apnea/genetics ; Caffeine/therapeutic use ; Humans ; Infant ; Infant, Newborn ; Infant, Newborn, Diseases ; Infant, Premature ; Infant, Premature, Diseases ; Polymorphism, Single Nucleotide
    Chemical Substances Caffeine (3G6A5W338E)
    Language Chinese
    Publishing date 2022-07-26
    Publishing country China
    Document type Journal Article ; Review
    ISSN 1008-8830
    ISSN 1008-8830
    DOI 10.7499/j.issn.1008-8830.2203134
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  3. Article ; Online: Single-Cell Differentiation Trajectory Inference Algorithm with Iterative Feature Selection

    HE Hongjian, YIN Yiting, XIE Jiang

    Jisuanji kexue yu tansuo, Vol 17, Iss 7, Pp 1609-

    2023  Volume 1621

    Abstract: The construction of cell differentiation trajectories from single-cell transcriptomic data or proteomic data by single-cell trajectory inference methods can help to understand the developmental process of normal tissues or provide pathologically relevant ...

    Abstract The construction of cell differentiation trajectories from single-cell transcriptomic data or proteomic data by single-cell trajectory inference methods can help to understand the developmental process of normal tissues or provide pathologically relevant information. However, the accuracy and robustness of current single-cell trajectory inference algorithms are still a challenge, one of the reasons is the noise caused by the detection of a large number of unrelated genes in single-cell sequencing. In order to solve this problem, a trajectory inference method iterTIPD (iterative trajectory inference based on probability distribution) based on iterative feature selection is proposed. Its innovation lies in iteratively applying feature selection methods widely used for screening differentially expressed genes to linear or branching single-cell RNA sequencing data, and improving the accuracy and robustness of cell pseudotime ordering by selecting the gene subset that contributes the most to the constructed differentiation trajectory. Experimental results on four scRNA-seq datasets show that iterTIPD can effectively improve the accuracy and robustness of the single-cell trajectory inference algorithm. IterTIPD also improves the performance of other trajectory inference algorithms, proving generalization of iterTIPD. The differentiation trajectory of neural stem cells is reconstructed by iterTIPD algorithm, and the comparison shows that the differentiation trajectory is highly consistent with the known neural stem cell differentiation trajectory. Meanwhile, Top2a and Gja1 may be novel markers defining activated neural stem cell subpopulations.
    Keywords single-cell rna sequencing ; differential gene expression ; single-cell differentiation trajectory inference ; iterative feature selection ; bioinformatics ; Electronic computers. Computer science ; QA75.5-76.95
    Subject code 571
    Language Chinese
    Publishing date 2023-07-01T00:00:00Z
    Publisher Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Association between malnutrition and surgical site wound infection among spinal surgery patients: A meta-analysis.

    Xie, Jiang / Du, Yuxuan / Tan, Zejiu / Tang, Hao

    International wound journal

    2023  Volume 20, Issue 10, Page(s) 4061–4068

    Abstract: A surgical site infection (SSI) is one of the most common complications of spinal surgery. Malnutrition has also been linked to SSI after other surgical procedures. However, whether malnutrition is a risk factor for SSI after spinal surgery remains ... ...

    Abstract A surgical site infection (SSI) is one of the most common complications of spinal surgery. Malnutrition has also been linked to SSI after other surgical procedures. However, whether malnutrition is a risk factor for SSI after spinal surgery remains controversial. Therefore, we performed a meta-analysis to comprehensively evaluate the relationship between malnutrition and SSI. Relevant studies of the correlation between malnutrition and SSI were retrieved from the Cochrane Library, EMBASE, PubMed, Web of Science, China National Knowledge Infrastructure and Wanfang Data from database inception to 21 May 2023. Two reviewers independently assessed the included studies, and a meta-analysis was performed using STATA 17.0 software. A total of 24 articles with 179 388 patients were included: 3919 and 175 469 cases comprised the SSI and control groups, respectively. The meta-analysis results showed that malnutrition significantly increased the SSI incidence (odds ratio, 1.811; 95% confidence interval, 1.512-2.111; p < 0.001). These results suggest that patients with malnutrition are at higher risk for SSI after surgery. However, because of significant differences in sample sizes among studies, and because some studies had limitations to their methodological quality, further validation of these results by additional high-quality studies with larger sample sizes is necessary.
    MeSH term(s) Humans ; Surgical Wound Infection/epidemiology ; Surgical Wound Infection/etiology ; Surgical Wound Infection/surgery ; Spine/surgery ; Risk Factors ; Neurosurgical Procedures ; Malnutrition
    Language English
    Publishing date 2023-06-30
    Publishing country England
    Document type Meta-Analysis ; Journal Article
    ZDB-ID 2170920-8
    ISSN 1742-481X ; 1742-4801
    ISSN (online) 1742-481X
    ISSN 1742-4801
    DOI 10.1111/iwj.14297
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  5. Article: Values of prognostic nutritional index for predicting Kawasaki disease: a systematic review and meta-analysis.

    Zhong, Xiaoling / Xie, Yu / Wang, Hui / Chen, Guihua / Yang, Taoyi / Xie, Jiang

    Frontiers in nutrition

    2024  Volume 11, Page(s) 1305775

    Abstract: Objective: This systematic review and meta-analysis aimed to evaluate the relationship between the prognostic nutritional index (PNI) and intravenous immunoglobulin (IVIG) resistance and coronary artery lesion (CAL) in Kawasaki disease (KD).: Methods!# ...

    Abstract Objective: This systematic review and meta-analysis aimed to evaluate the relationship between the prognostic nutritional index (PNI) and intravenous immunoglobulin (IVIG) resistance and coronary artery lesion (CAL) in Kawasaki disease (KD).
    Methods: The relevant literature was searched on PubMed, Embase, Cochrane Library, Web of Science, and Google Scholar up to August 5, 2023. A pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under curve (AUC) were calculated to assess the predicted values of PNI in KD patients with IVIG resistance and CAL.
    Results: A total of 8 articles containing 10 studies involving 7,047 participants were included. The pooled results revealed a pooled sensitivity of 0.44 (0.25-0.65), a pooled specificity of 0.87 (0.73-0.94), a pooled PLR of 3.4 (2.0-5.9), a pooled NLR of 0.65 (0.48-0.87), a pooled DOR of 5.26 (2.76-10.02), and a pooled AUC of 0.75 (0.71-0.78) in the diagnosis of KD with CAL. The pooled results suggested that a pooled sensitivity was 0.69 (0.60-0.77), specificity was 0.76 (0.69-0.82), PLR was 2.9 (2.1-4.1), NLR was 0.40 (0.29-0.56), DOR was 7.27 (3.89-13.59), and AUC was 0.79 (0.75-0.82) in the diagnosis of KD with IVIG resistance. The combined results revealed the pooled sensitivity was 0.63 (0.58-0.67), specificity was 0.82 (0.80-0.83), PLR was 3.09 (1.06-8.98), NLR was 0.38 (0.07-2.02), DOR was 8.23 (0.81-83.16) in differentiating KD from febrile patients. These findings demonstrated low sensitivity and relatively high specificity of PNI for KD, KD-CAL, and IVIG-resistant KD.
    Conclusion: In conclusion, this study was the first systematic review and meta-analysis of the diagnostic value of PNI in KD with IVIG resistance and CAL. The results suggested that PNI could be used as biomarkers for distinguish KD, KD with CAL, and KD with IVIG resistance.
    Language English
    Publishing date 2024-02-02
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2776676-7
    ISSN 2296-861X
    ISSN 2296-861X
    DOI 10.3389/fnut.2024.1305775
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  6. Article ; Online: Causal effects of gut microbiota on autism spectrum disorder: A two-sample mendelian randomization study.

    Chen, Yajun / Xue, Yan / Jia, Lang / Yang, Menghan / Huang, Gelin / Xie, Jiang

    Medicine

    2024  Volume 103, Issue 9, Page(s) e37284

    Abstract: There is increasing evidence that alterations in gut microbiota (GM) composition are associated with autism spectrum disorder (ASD), but no reliable causal relationship has been established. Therefore, a 2-sample Mendelian randomization (MR) study was ... ...

    Abstract There is increasing evidence that alterations in gut microbiota (GM) composition are associated with autism spectrum disorder (ASD), but no reliable causal relationship has been established. Therefore, a 2-sample Mendelian randomization (MR) study was conducted to reveal a potential causal relationship between GM and ASD. Instrumental variables for 211 GM taxa were obtained from genome-wide association studies (GWAS) and Mendelian randomization studies to estimate their impact on ASD risk in the iPSYCH-PGC GWAS dataset (18,382 ASD cases and 27,969 controls). Inverse variance weighted (IVW) is the primary method for causality analysis, and several sensitivity analyses validate MR results. Among 211 GM taxa, IVW results confirmed that Tenericutes (P value = .0369), Mollicutes (P value = .0369), Negativicutes (P value = .0374), Bifidobacteriales (P value = .0389), Selenomonadales (P value = .0374), Bifidobacteriaceae (P value = .0389), Family XIII (P value = .0149), Prevotella7 (P value = .0215), Ruminococcaceae NK4A214 group (P value = .0205) were potential protective factors for ASD. Eisenbergiella (P value = .0159) was a possible risk factor for ASD. No evidence of heterogeneous, pleiotropic, or outlier single-nucleotide polymorphism was detected. Additionally, further sensitivity analysis verified the robustness of the above results. We confirm a potential causal relationship between certain gut microbes and ASD, providing new insights into how gut microbes mediate ASD. The association between them needs to be further explored and will provide new ideas for the prevention and treatment of ASD.
    MeSH term(s) Humans ; Gastrointestinal Microbiome/genetics ; Autism Spectrum Disorder/genetics ; Genome-Wide Association Study ; Mendelian Randomization Analysis ; Causality ; Clostridiales ; Firmicutes
    Language English
    Publishing date 2024-02-28
    Publishing country United States
    Document type Journal Article
    ZDB-ID 80184-7
    ISSN 1536-5964 ; 0025-7974
    ISSN (online) 1536-5964
    ISSN 0025-7974
    DOI 10.1097/MD.0000000000037284
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    Ua VI Zs.171: Show issues Location:
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  7. Article ; Online: Osteosarcoma neutrophil extracellular trap network-associated gene recurrence and metastasis model.

    Tang, Hao / Xie, Jiang / Du, Yu-Xuan / Tan, Ze-Jiu / Liang, Zhuo-Tao

    Journal of cancer research and clinical oncology

    2024  Volume 150, Issue 2, Page(s) 48

    Abstract: Osteosarcoma (OS) is the most common malignancy in children and adolescents and has a high probability of recurrence and metastasis. A growing number of studies have shown that neutrophil extracellular traps (NETs) are strongly associated with cancer ... ...

    Abstract Osteosarcoma (OS) is the most common malignancy in children and adolescents and has a high probability of recurrence and metastasis. A growing number of studies have shown that neutrophil extracellular traps (NETs) are strongly associated with cancer metastasis, but in osteosarcoma, genes associated with NETs that promote osteosarcoma recurrence and metastasis remain to be explored. We systematically investigated the gene expression patterns of NETs in OS samples from the GEO database. NETs molecular typing was evaluated based on NETs expression profiles, and the association between NETs molecular subtypes and immune microenvironment and metastatic features were explored. Ultimately, we constructed a signature model and column line graph associated with metastasis prediction and screened possible potential drugs for metastatic osteosarcoma. We established two different molecular subtypes of NETs, which showed significant differences in metastatic status, metastasis time, tumor immune microenvironment, and biological effects. We also constructed a NETs-related gene metastasis signature(NRGMS) to assess the expression pattern of NETs in patients to predict metastatic recurrence in osteosarcoma patients. We screened for TOMM40 and FH associated with metastatic recurrence in osteosarcoma patients. Overall, this study constructs a predictive model for osteosarcoma metastasis of NETs-related genes, which is expected to provide new insights into the metastasis of osteosarcoma.
    MeSH term(s) Adolescent ; Child ; Humans ; Extracellular Traps/genetics ; Osteosarcoma/genetics ; Databases, Factual ; Neoplasms, Second Primary ; Bone Neoplasms/genetics ; Tumor Microenvironment/genetics
    Language English
    Publishing date 2024-01-29
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 134792-5
    ISSN 1432-1335 ; 0171-5216 ; 0084-5353 ; 0943-9382
    ISSN (online) 1432-1335
    ISSN 0171-5216 ; 0084-5353 ; 0943-9382
    DOI 10.1007/s00432-023-05577-2
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  8. Article ; Online: DRTerHGAT: A drug repurposing method based on the ternary heterogeneous graph attention network.

    He, Hongjian / Xie, Jiang / Huang, Dingkai / Zhang, Mengfei / Zhao, Xuyu / Ying, Yiwei / Wang, Jiao

    Journal of molecular graphics & modelling

    2024  Volume 130, Page(s) 108783

    Abstract: Drug repurposing is an effective method to reduce the time and cost of drug development. Computational drug repurposing can quickly screen out the most likely associations from large biological databases to achieve effective drug repurposing. However, ... ...

    Abstract Drug repurposing is an effective method to reduce the time and cost of drug development. Computational drug repurposing can quickly screen out the most likely associations from large biological databases to achieve effective drug repurposing. However, building a comprehensive model that integrates drugs, proteins, and diseases for drug repurposing remains challenging. This study proposes a drug repurposing method based on the ternary heterogeneous graph attention network (DRTerHGAT). DRTerHGAT designs a novel protein feature extraction process consisting of a large-scale protein language model and a multi-task autoencoder, so that protein features can be extracted accurately and efficiently from amino acid sequences. The ternary heterogeneous graph of drug-protein-disease comprehensively considering the relationships among the three types of nodes, including three homogeneous and three heterogeneous relationships. Based on the graph and the extracted protein features, the deep features of the drugs and the diseases are extracted by graph convolutional networks (GCN) and heterogeneous graph node attention networks (HGNA). In the experiments, DRTerHGAT is proven superior to existing advanced methods and DRTerHGAT variants. DRTerHGAT's powerful ability for drug repurposing is also demonstrated in Alzheimer's disease.
    Language English
    Publishing date 2024-04-24
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1396450-1
    ISSN 1873-4243 ; 1093-3263
    ISSN (online) 1873-4243
    ISSN 1093-3263
    DOI 10.1016/j.jmgm.2024.108783
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    Zs.A 3491: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (2.OG)
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  9. Article ; Online: Association between blood ethylene oxide levels and the prevalence of periodontitis: evidence from NHANES 2013-2014.

    Xue, Yan / Tang, Yujing / Ren, Zhengyun / Linke, Li / Liu, Yanjun / Xie, Jiang

    Clinical oral investigations

    2024  Volume 28, Issue 5, Page(s) 293

    Abstract: Background: The study aimed to establish a link between blood ethylene oxide (EO) levels and periodontitis, given the growing concern about EO's detrimental health effects.: Materials and methods: The study included 1006 adults from the 2013-2014 ... ...

    Abstract Background: The study aimed to establish a link between blood ethylene oxide (EO) levels and periodontitis, given the growing concern about EO's detrimental health effects.
    Materials and methods: The study included 1006 adults from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) dataset. We assessed periodontitis prevalence across groups, used weighted binary logistic regression and restricted cubic spline fitting for HbEO-periodontitis association, and employed Receiver Operating Characteristic (ROC) curves for prediction.
    Results: In the periodontitis group, HbEO levels were significantly higher (40.57 vs. 28.87 pmol/g Hb, P < 0.001). The highest HbEO quartile showed increased periodontitis risk (OR = 2.88, 95% CI: 1.31, 6.31, P = 0.01). A "J"-shaped nonlinear HbEO-periodontitis relationship existed (NL-P value = 0.0116), with an inflection point at ln-HbEO = 2.96 (EO = 19.30 pmol/g Hb). Beyond this, ln-HbEO correlated with higher periodontitis risk. A predictive model incorporating sex, age, education, poverty income ratio, alcohol consumption, and HbEO had 69.9% sensitivity and 69.2% specificity. The model achieved an area under the ROC curve of 0.761.
    Conclusions: These findings suggest a correlation between HbEO levels and an increased susceptibility to periodontitis.
    MeSH term(s) Humans ; Nutrition Surveys ; Male ; Periodontitis/epidemiology ; Periodontitis/blood ; Female ; Ethylene Oxide/blood ; Prevalence ; Adult ; Middle Aged ; Risk Factors ; United States/epidemiology ; Aged ; Cross-Sectional Studies
    Chemical Substances Ethylene Oxide (JJH7GNN18P)
    Language English
    Publishing date 2024-05-02
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 1364490-7
    ISSN 1436-3771 ; 1432-6981
    ISSN (online) 1436-3771
    ISSN 1432-6981
    DOI 10.1007/s00784-024-05690-7
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    Zs.A 4788: Show issues Location:
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  10. Article ; Online: MGNR: A Multi-Granularity Neighbor Relationship and Its Application in KNN Classification and Clustering Methods.

    Xie, Jiang / Xiang, Xuexin / Xia, Shuyin / Jiang, Lian / Wang, Guoyin / Gao, Xinbo

    IEEE transactions on pattern analysis and machine intelligence

    2024  Volume PP

    Abstract: In the real world, data distributions often exhibit multiple granularities. However, the majority of existing neighbor-based machine-learning methods rely on manually setting a single-granularity for neighbor relationships. These methods typically handle ...

    Abstract In the real world, data distributions often exhibit multiple granularities. However, the majority of existing neighbor-based machine-learning methods rely on manually setting a single-granularity for neighbor relationships. These methods typically handle each data point using a single-granularity approach, which severely affects their accuracy and efficiency. This paper adopts a dual-pronged approach: it constructs a multi-granularity representation of the data using the granular-ball computing model, thereby boosting the algorithm's time efficiency. It leverages the multi-granularity representation of the data to create tailored, multi-granularity neighborhood relationships for different task scenarios, resulting in improved algorithmic accuracy. The experimental results convincingly demonstrate that the proposed multi-granularity neighbor relationship effectively enhances KNN classification and clustering methods. The source code has been publicly released and is now accessible on GitHub at https://github.com/xjnine/MGNR.
    Language English
    Publishing date 2024-05-13
    Publishing country United States
    Document type Journal Article
    ISSN 1939-3539
    ISSN (online) 1939-3539
    DOI 10.1109/TPAMI.2024.3400281
    Database MEDical Literature Analysis and Retrieval System OnLINE

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