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Search Results (9)
  • Open Access


    A novel prognostic gene signature, nomogram and immune landscape based on tanshinone IIA drug targets for hepatocellular carcinoma: Comprehensive bioinformatics analysis and in vitro experiments


    BIOCELL, Vol.47, No.7, pp. 1519-1535, 2023, DOI:10.32604/biocell.2023.027026

    Abstract Background: Tanshinone IIA, one of the main ingredients of Danshen, is used to treat hepatocellular carcinoma (HCC). However, potential targets of the molecule in the therapy of HCC are unknown. Methods: In this study, we collected the tanshinone IIA targets from public databases for investigation. We screened differentially expressed genes (DEGs) across HCC and normal tissues using mRNA expression profiles from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression models were used to identify and construct the prognostic gene signature. Results: Finally, we discovered common genes across tanshinone IIA… More >

  • Open Access


    Determination of the Postmortem Interval Using Fiber Bragg Grating Sensors

    M. Adjailia1, H. Derbal Habak2,*, Y. Hamaizi1, H. Triki1

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.3, pp. 831-844, 2023, DOI:10.32604/fdmp.2022.022162

    Abstract Fiber Bragg grating (FBG) sensors are often used in monitoring activities and to ensure that environmental parameters satisfy industrial requirements. They offer crucial safety measures in the early detection of hazards due to their greatly reduced size, low weight, flexibility, and immunity to electromagnetic interference. These characteristics make FBGs suitable also for use in relation to the human body for in vivo measurements and long-term monitoring. In this study, recent developments are presented with regard to the utilization of these sensors to measure the so-called post-mortem interval (PMI). Such developments rely on numerical simulations based on the Matlab software and… More >

  • Open Access


    Development and Validation of a Nomogram Model to Predict the Prognosis of Intrahepatic Cholangiocarcinoma

    Yi Chen1,#, Liyun Huang1,#, Zuwu Wei1, Xiaoling Liu1, Lihong Chen1,2,*, Bin Wang1,2,*

    Oncologie, Vol.24, No.2, pp. 329-340, 2022, DOI:10.32604/oncologie.2022.022521

    Abstract Background: The effective method for predicting prognosis of ICC is still lack. This study aims to establish and verify an effective prognostic nomogram model for intrahepatic cholangiocarcinoma (ICC) after partial hepatectomy. Materials and Methods: A nomogram model was developed in a cohort of 127 patients from January 2015 to December 2019. General clinical characteristics including preoperative physical examination data and postoperative pathological features were obtained. The independent risk factors identified by univariate and multivariate COX proportional hazards regression models were used to construct nomogram model. Predictive accuracy and discriminative ability were determined using a concordance index and a calibration curve.… More >

  • Open Access


    Weighted gene co-expression network analysis identifies a novel immune-related gene signature and nomogram to predict the survival and immune infiltration status of breast cancer


    BIOCELL, Vol.46, No.7, pp. 1661-1673, 2022, DOI:10.32604/biocell.2022.018023

    Abstract Breast cancer is one of the most common cancers in the world and seriously threatens the health of women worldwide. Prognostic models based on immune-related genes help to improve the prognosis prediction and clinical treatment of breast cancer patients. In the study, we used weighted gene co-expression network analysis to construct a co-expression network to screen out highly prognostic immune-related genes. Subsequently, the prognostic immune-related gene signature was successfully constructed from highly immune-related genes through COX regression and LASSO COX analysis. Survival analysis and time receiver operating characteristic curves indicate that the prognostic signature has strong predictive performance. And we… More >

  • Open Access


    A novel prognostic target-gene signature and nomogram based on an integrated bioinformatics analysis in hepatocellular carcinoma


    BIOCELL, Vol.46, No.5, pp. 1261-1288, 2022, DOI:10.32604/biocell.2022.018427

    Abstract There is currently no effective solution to the problem of poor prognosis and recurrence of HCC. The technology of immunotherapy and prognosis of genetic material has made continuous progress in recent years. In the study, a 5-gene signature was established for the prognosis of HCC through biological information, and the immune infiltration of HCC patients was studied. After studied HCC patients’ immune infiltration, the paper screened the differential target genes of miR-126-3p in HCC downloaded from TCGA database, and uses WGCNA method to select the modular genes highly relevant to M2 macrophage. Then we use LASSO and COX regression analysis… More >

  • Open Access


    WGCNA and LASSO algorithm constructed an immune infiltration-related 5-gene signature and nomogram to improve prognosis prediction of hepatocellular carcinoma


    BIOCELL, Vol.46, No.2, pp. 401-415, 2022, DOI:10.32604/biocell.2022.016989

    Abstract Hepatocellular carcinoma (HCC) is a common immunogenic malignant tumor. Although the new strategies of immunotherapy and targeted therapy have made considerable progress in the treatment of HCC, the 5-year survival rate of patients is still very low. The identification of new prognostic signatures and the exploration of the immune microenvironment are crucial to the optimization and improvement of molecular therapy strategies. We studied the potential clinical benefits of the inflammation regulator miR-93-3p and mined its target genes. Weighted gene co-expression network analysis (WGCNA), univariate and multivariate COX regression and the LASSO COX algorithm are employed to identify prognostic-related genes and… More >

  • Open Access


    Construction and validation of prognostic model based on autophagy-related lncRNAs in gastric cancer


    BIOCELL, Vol.46, No.1, pp. 97-109, 2022, DOI:10.32604/biocell.2021.015608

    Abstract Gastric cancer (GC) is one of the most common cancer worldwide. Although emerging evidence indicates that autophagy-related long non-coding RNA (lncRNA) plays an important role in the progression of GC, the prognosis of GC based on autophagy is still deficient. The Cancer Genome of Atlas stomach adenocarcinoma (TCGA-STAD) dataset was downloaded and separated into a training set and a testing set randomly. Then, 24 autophagy-related lncRNAs were found strongly associated with the survival of the TCGA-STAD dataset. 11 lncRNAs were selected to build the risk score model through the least absolute shrinkage and selection operator (LASSO) regression. Every patient got… More >

  • Open Access


    A Nomogram for Predicting Lateral Lymph Node Metastasis in Cases of Papillary Thyroid Micro-Carcinoma with Suspected Lymph Node Metastasis

    Yu Xiao1, Peng Zhou2, Yizi Zheng1, Chang Zheng1, Guowen Liu1, Weixiang Liu3,*

    Oncologie, Vol.23, No.2, pp. 219-228, 2021, DOI:10.32604/Oncologie.2021.016480

    Abstract The elevation for lateral lymph node metastasis (LLNM) plays an important role in therapeutic decision-making for thyroid carcinoma. A reliable forecasting model for LLNM in patients with papillary thyroid micro-carcinoma (PTMC) is needed, using clinicopathological characteristics. A total of 576 PTMC patients with suspicious lateral cervical lymph node (II, III, IV or V region) metastasis and known clinicopathological variables were randomly collected at Shenzhen Second People’s Hospital. Cervical lymph node status of every patient was assessed by ultrasonography (US). The patients in this cohort study underwent thyroidectomy and lateral neck lymph node dissection. Univariate analysis and logistic regression analysis were… More >

  • Open Access


    Development of an Ultrasonic Nomogram for Preoperative Prediction of Castleman Disease Pathological Type

    Xinfang Wang1, Lianqing Hong2, Xi Wu3, Jia He3, Ting Wang3,4,*, Hongbo Li5, Shaoling Liu6

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 141-154, 2019, DOI:10.32604/cmc.2019.06030

    Abstract An ultrasonic nomogram was developed for preoperative prediction of Castleman disease (CD) pathological type (hyaline vascular (HV) or plasma cell (PC) variant) to improve the understanding and diagnostic accuracy of ultrasound for this disease. Fifty cases of CD confirmed by pathology were gathered from January 2012 to October 2018 from three hospitals. A grayscale ultrasound image of each patient was collected and processed. First, the region of interest of each gray ultrasound image was manually segmented using a process that was guided and calibrated by radiologists who have been engaged in imaging diagnosis for more than 5 years. In addition,… More >

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