基于广义对偶犹豫模糊粗糙集的疾病预诊断

在现实疾病预诊断过程中,医疗数据往往呈现出大规模性和动态增长等特征。本文为应对疾病预诊断中的医学不确定性数据分析问题,在对偶犹豫模糊信息系统下研究了双论域粗糙集模型。基于所建立的双论域理论模型,本文发展了基于双论域对偶犹豫模糊粗糙集的疾病预诊断方法,并进行了实例分析,以此来验证所构建方法的高效性。

Roles of syndecan-1, bcl6 and p53 in diagnosis and prognostication of immunoproliferative small intestinal disease

AIM： To evaluate roles of syndecan-1, bcl6 and p53 in diagnosis and prognostication of immunoproliferative small intestinal disease （IPSID） and to study profiles of kappa （κ） and lambda （λ） light chains and IgA heavy chain. METHODS： The study consisted of 11 cases of IPSID and similar number of controls which included 11 of normal intestinal mucosa and 11 of high grade B cell lymphoma of ileum. The parameters analyzed included clinical profiles, biochemical and other laboratory investigations, radiologic and histological findings including immunohistochemistry. RESULTS： All IPSID cases had demonstrable serum IgA heavy chain and heavy mucosal plasma cell infiltration. According to Galian＇s histological staging, there were 4 patients with stage A and 7 with stage B. κ and ;λ light chains were over-expressed in 7 patients; 1 stage A patient had H pylori-positive active gastritis and eradication of H pylori led to disease remission. Stage A biopsies had higher expression for syndecan-1, while stage B had higher expression for bcl6 and p53. Syndecan-1,κ and λ light chains and IgA heavy chain showed inverse relationship with bcl6 and p53. All patients were treated with doxycycline. CHOP regime was added in 5 patients who developed frank lymphoma. Three died of the disease due to extensive organ infiltration. CONCLUSION： Certain immunomarkers like syndecan-1,κ and λ light chains and IgA heavy chain could be of much help in identifying early stage IPSID. Stage B IPSID showed higher expression for bcl6 and p53 than stage A IPSID. bcl6 and p53 expressions correlated with a more advanced disease stage and aggressive tumour behavior.

The Use of Postoperative Serum HS-AFP and GGTⅡfor Judgment of the Prognosis for Hepatocellular Carcinoma patients

OBJECTIVE To investigate the clinical value of hepatoma-specific alpha-fetoprotein （HS-AFP） and gamma-glutamyltransferase Ⅱ （GGT Ⅱ） for judgment of postoperative prognosis of patients with hepatocellular carcinoma （HCC）. METHODS HS-AFP was separated and determined using native polyacrylamide electrophoresis with a discontinuous buffer system and Western blots. GGT Ⅱ was separated with native polyacrylamide electrophoresis with a discontinuous buffer system and detected by enzyme staining. Forty cases with HCC underwent serial determination of HS-AFP and GGT Ⅱ before and after radical excision. The correlations were analyzed between the two indices and survival time. RESULTS In the 40 cases with HCC, before radical excision the positive rates of HS-AFP and GGT II were 57.5% and 67.5% respectively, with the positive rate of combined HS-AFP and GGT Ⅱ reaching 80.0%. After operation, the recurrence and metastasis rate in the groups with positive HS-AFP and GGT Ⅱ were 90.9% and 58.8% respectively, while in the groups with negative HS-AFP and GGT Ⅱ the rates were 20.7% and 26.1% respectively. Recurrence and metastasis occurred in all cases with both postoperative positive HS-AFP and GGT Ⅱ but only in 9.5% of the cases in whom both postoperative HS-AFP and GGT Ⅱ were negative. Univariate analysis revealed that postoperative HS-AFP and GGT Ⅱ were related to the prognosis in HCC. CONCLUSION Postoperative serum HS-AFP and GGT Ⅱ are very useful in predicting the prognosis of HCC patients.

Role of genetics in the diagnosis and prognosis of Crohn's disease

Considering the epidemiological, genetic and immunological data, we can conclude that the inflammatory bowel diseases are heterogeneous disorders of multifactorial etiology in which hereditability and environment interact to produce the disease. It is probable that patients have a genetic predisposition for the development of the disease coupled with disturbances in immunoregulation. Several genes have so far been related to the diagnosis of Crohn's disease. These genes are related to innate pattern recognition receptors, to epithelial barrier homeostasis and maintenance of epithelial barrier integrity, to autophagy and to lymphocyte differentiation. So far, the strongest and most replicated associations with Crohn's disease have been demonstrated with NOD2 , IL23R and ATG16L1 genes. Many genes have so far been implicated in the prognosis of Crohn's disease and many attempts have been made for classification of genetic profiles in Crohn's disease.CARD15 seems to be not only a susceptibility gene, but also a disease-modifier gene for Crohn's disease. Enriching our understanding of Crohn's disease genetics is of value, but when combining genetic data with functional data the outcome could be of major importance to clinicians.

Role of genetics in the diagnosis and prognosis of Crohn's disease

Considering epidemiological,genetic and immunological data,we can conclude that the inflammatory bowel diseases are heterogeneous disorders of multifactorial etiology in which hereditability and environment interact to produce the disease.It is probable that patients have a genetic predisposition for the development of the disease coupled with disturbances in immunoregulation.Several genes have been so far related to the diagnosis of Crohn's disease.Those genes are related to innate pattern recognition receptors,to epithelial barrier homeostasis and maintenance of epithelial barrier integrity,to autophagy and to lymphocyte differentiation.So far,the most strong and replicated associations with Crohn's disease have been done with NOD2,IL23R and ATG16L1 genes.Many genes have so far been implicated in prognosis of Crohn's disease and many attempts have been made to classify genetic profiles in Crohn's disease.CARD15 seems not only a susceptibility gene,but also a disease-modifier gene for Crohn's disease.Enriching our understanding on Crohn's disease genetics is important but when combining genetic data with functional data the outcome could be of major importance to clinicians.

Aortic arch calcification on chest X-ray combined with coronary calcium score show additional benefit for diagnosis and outcome in patients with angina

Background The coronary artery calcium （CAC） and aortic arch calcification （AoAC） are individually associated with cardiovascular disease and outcome. This study investigated the predictive value of AoAC combined with CAC for cardiovascular diagnosis and outcome in patients with angina. Methods A total of 2018 stable angina patients who underwent chest X-ray and cardiac multi-detector computed tomography were followed up for four years to assess adverse events, which were categorized as cardiac death, stroke, myocardial infarction, or repeated revascularization. The extent of AoAC on chest X-ray was graded on a scale from 0 to 3. Results During the four years of fol- low-up, 620 patients were treated by coronary stenting and 153 （7%） adverse events occurred. A higher grade of AoAC was associated with a higher CAC score. Cox regression showed that the CAC score, but not AoAC, were associated with adverse events. In patients with CAC score 〈 400, AoAC showed an additive predictive value in detecting significant coronary artery disease （CAD）. A gradual increases in the risk of adverse events were noted if AoAC was present in patients with similar CAC score. Conclusions As AoAC is strongly correlated with the CAC score regardless of age or gender, careful evaluation of CAD would be required in patients with AoAC on conventional chest X-rays.

DiagData： A Tool for Generation of Fuzzy Inference System

In this paper, it described the architecture of a tool called DiagData. This tool aims to use a large amount of data and information in the field of plant disease diagnostic to generate a disease predictive system. In this approach, techniques of data mining are used to extract knowledge from existing data. The data is extracted in the form of rules that are used in the development of a predictive intelligent system. Currently, the specification of these rules is built by an expert or data mining. When data mining on a large database is used, the number of generated rules is very complex too. The main goal of this work is minimize the rule generation time. The proposed tool, called DiagData, extracts knowledge automatically or semi-automatically from a database and uses it to build an intelligent system for disease prediction. In this work, the decision tree learning algorithm was used to generate the rules. A toolbox called Fuzzygen was used to generate a prediction system from rules generated by decision tree algorithm. The language used to implement this software was Java. The DiagData has been used in diseases prediction and diagnosis systems and in the validation of economic and environmental indicators in agricultural production systems. The validation process involved measurements and comparisons of the time spent to enter the rules by an expert with the time used to insert the same rules with the proposed tool. Thus, the tool was successfully validated, providing a reduction of time.