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BACKGROUND@#Small cell lung cancer (SCLC) is characterized by poor differentiation, high malignancy and rapid growth fast, short double time, early and extensive metastatic malignancy. In clinical, chemotherapy is the main treatment method, while resistance to multiple chemotherapy drugs in six to nine months has been a major clinical challenge in SCLC treatment. Therefore, It has important clinical value to building SCLC aninimal model which is similar to patients with SCLC. Animal model of xenotransplantation (PDX) from the patients with small cell lung cancer can well retain the characteristics of primary tumor and is an ideal preclinical animal model. The study is aimed to establish SCLC PDX animal model and induce the chemoresistance model to help to study the mechanism of chemoresistance and individual treatment.@*METHODS@#Fresh surgical excision or puncture specimens from SCLC patients were transplanted into B-NSGTM mice subcutaneous tissues with severe immunodeficiency in one hour after operation the B-NSGTM mice subcutaneous in 1 hour, and inject chemotherapy drugs intraperitoneally after its tumor growed to 400 mm³ with EP which is cisplatin 8 mg/kg eight days and etoposide 5 mg/kg every two days until 8 cycles. Measure the tumor volum and mice weights regularly, then re-engrafted the largest tumor and continue chemotherapy.@*RESULTS@#Nine cases were conducted for B-NSG mice modeling. Three of nine cases could be engrafted to new B-NSG mice at least two generation. The SCLC PDX animal models have been established successfully. After adopting chemotherapy drugs, the chemoresistance PDX models have been established. High homogeneity was found between xenograft tumor and patient's tumor in histopathology, immunohistochemical phenotype (Syn, CD56, Ki67).@*CONCLUSIONS@#The SCLC PDX animal model and the chemoresistance PDX animal model have been successfully constructed, the success rate is 33%, which provides a platform for the clinical research, seeking for biological markers and choosing individual treatment methods of SCLC.
Subject(s)
Animals , Female , Humans , Antineoplastic Combined Chemotherapy Protocols , Pharmacology , Cisplatin , Disease Models, Animal , Drug Resistance, Neoplasm , Etoposide , Interleukin Receptor Common gamma Subunit , Genetics , Lung Neoplasms , Drug Therapy , Metabolism , Pathology , Mice, Inbred BALB C , Mice, Inbred NOD , Mice, Knockout , Mice, SCID , Small Cell Lung Carcinoma , Drug Therapy , Metabolism , Pathology , Transplantation, Heterologous , Methods , Xenograft Model Antitumor AssaysABSTRACT
Alzheimer's disease (AD) is a typical neurodegenerative disease, which is clinically manifested as amnesia, loss of language ability and self-care ability, and so on. So far, the cause of the disease has still been unclear and the course of the disease is irreversible, and there has been no cure for the disease yet. Hence, early prognosis of AD is important for the development of new drugs and measures to slow the progression of the disease. Mild cognitive impairment (MCI) is a state between AD and healthy controls (HC). Studies have shown that patients with MCI are more likely to develop AD than those without MCI. Therefore, accurate screening of MCI patients has become one of the research hotspots of early prognosis of AD. With the rapid development of neuroimaging techniques and deep learning, more and more researchers employ deep learning methods to analyze brain neuroimaging images, such as magnetic resonance imaging (MRI), for early prognosis of AD. Hence, in this paper, a three-dimensional multi-slice classifiers ensemble based on convolutional neural network (CNN) and ensemble learning for early prognosis of AD has been proposed. Compared with the CNN classification model based on a single slice, the proposed classifiers ensemble based on multiple two-dimensional slices from three dimensions could use more effective information contained in MRI to improve classification accuracy and stability in a parallel computing mode.
Subject(s)
Humans , Alzheimer Disease , Diagnosis , Brain , Diagnostic Imaging , Cognitive Dysfunction , Deep Learning , Neural Networks, Computer , Neuroimaging , PrognosisABSTRACT
Recent studies heve demonstrated that Akkermansia muciniphila (A.muciniphila) plays an important role in human health and disease , including regulating the development of the immune system and the metabolic phenotype of the host.This article reviews the research progress on A.muciniphila in recent years, focusing on the basic characteristics , the influencing factors of colonization , and the underlying mechanism of maintaining intestinal homeostasis of A.muciniphila.Additionally, the article summarizes the potential association between A.muciniphila and the chronic metabolic diseases such as obesity , atherosclerosis,diabetes mellitus and infectious diseases.The perspect of A.muciniphila as a new generation of probiotics in clinical medicine and the challenge for its industrialization are also discussed in the article .
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In recent years, researchers have introduced various methods in many domains into medical image processing so that its effectiveness and efficiency can be improved to some extent. The applications of generative adversarial networks (GAN) in medical image processing are evolving very fast. In this paper, the state of the art in this area has been reviewed. Firstly, the basic concepts of the GAN were introduced. And then, from the perspectives of the medical image denoising, detection, segmentation, synthesis, reconstruction and classification, the applications of the GAN were summarized. Finally, prospects for further research in this area were presented.
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Objective To investigate the association between the polymorphisms of apolipoprotein M gene (ApoM) and the risk for cerebral infarction in Han population in northern China.Methods The polymorphisms of ApoM gene were identified by PCR-DNA sequencing analysis and were subsequently detected by PCR-RFLP in 560 patients with cerebral infarction and 550 control subjects in northern China. Statistic analysis was conducted using the SPSS 10.0 program. The linkage disequilibrium (LD) was analyzed by EH and SHEsis softwares. Results Three single nucleotide polymorphisms were found in intron 1 and intron 5 of ApoM gene. The frequencies of GA+AA genotype and A allele of rs805264, GT +TT genotype and T allele of rs707922, CA+AA genotype and A allel of rs707921 were significantly higher in the patients (33.8% and 17.9%, 34.5% and 18.3%, 33.4% and 17.8%, respectively) than in controls (21.1% and 11.2%, 21.8 % and 11.5%, 20.9% and 11.1%, respectively). The LD was found in rs805264, rs707922 and rs707921 of ApoM gene (χ2=2595.03, P<0.01). There was strong LD between each pair of the three markers (D′=0.972 to 0.992). Multiple logistic regression analysis revealed that the A-T-A haplotype of the ApoM gene was an independent risk factor for cerebral infarction (OR=1.780;95%CI=1.333-2.376, P<0.01). Conclusions GA genotype and A allele of rs805264, GT genotype and T allele of rs707922, CA genotype and A allele of rs707921 may be genetic risk factors for cerebral infarction. A-T-A haplotype of ApoM gene may be a susceptible genotype of cerebral infarction.
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Objective:To study protective e ects of ginsenoside Rg1,Rb1 on cultured CHO cell injure induced by beta-amyloid protein 25-35(A?25-35).Methods:MTT assay was used to measure the cell viability after incubated with 40?mol/L A?25-35 for 24h and ginsenoside Rg1,Rb1 added into substratum.The e ect of anti-apoptosis of ginsenoside Rg1 and Rb1 were assayed through ow cytometric analysis.Results:Compare with the control group,the cellular activity was decreased(P