Publications by authors named "Meng-Li Zheng"

Background: The exact molecular mechanism of esophageal squamous cell carcinoma (ESCC) is still unknown, and the prognosis of ESCC has not been significantly improved.

Objective: To understand the molecular mechanism of ESCC, differential modules (DMs) and key genes were identified through conducting analysis on the differential co-expression network (DCN) based on the gene expression profiles of ESCC and protein-protein interaction (PPI) data.

Materials And Methods: First, gene expression profiles of ESCC and PPI data recruiting and preprocessing were conducted; then, a DCN was constructed based on the gene co-expression and gene differential expression in ESCC; in the following, candidate DMs were mined from DCN through a systemic module searching strategy, and significance analysis was performed on candidate DMs to identify DMs; moreover, significant genes contained in the DMs were analyzed to identify the underlying biomarkers for ESCC.

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Objective: The objective of this paper was to reveal hub pathways in primary mediastinal B-cell lymphoma (PMBL) based on multiple pathway crosstalk networks (PCNs) and give insight for its pathological mechanism.

Materials And Methods: Based on gene expression data, pathway data and protein-protein interaction data, background PCN (BPCN) and tumor PCN (TPCN) of PMBL were constructed. The rank product algorithm was implemented to identify hub pathways of BPCN and TPCN.

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Purpose: The purpose of this study was to explore the pathway cross-talks and key pathways in non-small cell lung cancer (NSCLC) to better understand the underlying pathological mechanism.

Methods: Integrated gene expression data, pathway data and protein-protein interaction (PPI) data were assessed to identify the pathway regulatory interactions in NSCLC, and constructed the background and disease pathway crosstalk networks, respectively. In this work, the attractor method was implemented to identified the differential pathways, and the rank product (RP) algorithm was used to determine the importance of pathways.

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Purpose: The objective of this study was to identify seed pathway cross-talks in non-small cell lung carcinoma (NSCLC), and to reveal potential pathological mechanism at molecular level systematically.

Methods: Differentially expressed genes (DEGs) between NSCLC and normal controls were identified using quantile- adjusted conditional maximum likelihood (QCML) method. Subsequently, differential pathways (DPs) enriched by DEGs were determined according to the Ingenuity Pathways Analysis )IPA) pathways and Fisher's exact test.

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In our study, we aimed to profile a panel microRNAs (miRNAs) as potential biomarkers for the early diagnosis of pulmonary tuberculosis (PTB) and to illuminate the molecular mechanisms in the development of PTB. Firstly, gene expression profile of E-GEOD-49951 was downloaded from ArrayExpress database, and quantile-adjusted conditional maximum likelihood method was utilized to identify statistical difference between miRNAs of Mycobacterium tuberculosis (MTB)-infected individuals and healthy subjects. Furthermore, in order to assess the performance of our methodology, random forest (RF) classification model was utilized to identify the top 10 miRNAs with better Area Under The Curve (AUC) using 10-fold cross-validation method.

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Background & Objective: Malignant tumors spread and metastasize in the majority of the organs, but are very rare in skeletal muscles. This study was conducted to explore the effect of organic microenvironment of skeletal muscles on the proliferation of pulmonary large cell carcinomas with different metastatic potential and to investigate the mechanism of the rarity of metastases in skeletal muscles.

Methods: Primary culture of newborn Wistar rat skeletal muscle cells was established, and the murine skeletal muscle conditioned medium(MMCM)was prepared to test its effect in vitro on pulmonary large cell carcinomas with different metastatic potential (PLA-801C with lower potential and PLA-801D with relatively higher potential) by MTT assay.

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