Matriks Jordan Dan Aplikasinya Pada Sistem Linier Waktu Diskrit

Matrix is diagonalizable (similar with matrix diagonal) if and only if the sum of geometric multiplicities of its eigenvalues is n.If we search for an upper triangular form that is nearly diagonal as possible but is still attainable by similarity for every matrix, especially the sum of geometric multiplicities of its eigenvalues is less than n, the result is the Jordan canonical form, which is denoted by , and . In this paper, will be described how to get matrix S(in order to get matrix ) by using generalized eigenvector. In addition, it will also describe the Jordan canonical form and its properties, and some observation and application on discrete time linear system

Is Peri-Operative Steroid Replacement Therapy Necessary for the Pituitary Adenomas Treated with Surgery? A Systematic Review and Meta Analysis

<div><p>Background</p><p>Patients with pituitary adenomas usually receive “stress dose” steroids in the peri-operative peroids. Though randomized controlled trials(RCT) have not been performed to assess the necessity of steroid coverage, there are several studies that explained the changes of adrenal function during peri-operative peroids. The aim of the present study is to investigate whether it is necessary to employ conventional peri-operative glucocorticoid replacement therapy to all the patients undergoing surgery.</p><p>Methods</p><p>We searched studies addressing peri-operative steroids coverage for pituitary adenomas in the Web of Science, Medline and the Cochrane Library. Then we extracted studies about peri-operative morning serum cortisol(MSC) levels, morbidity of early postoperative adrenal insufficiency, postoperative diabetes insipidus, relationships between MSC levels and adrenal integrity. We used RevMan Software to combine the results for meta-analysis. We used fixed-effects models for there was no significant heterogeneity existed.</p><p>Findings</p><p>There are 18 studies from 11 countries published between 1987 and 2013 including 1224 patients. The postoperative serum cortisol levels were significantly increased compared with the preoperative one in hypothalamic-pituitary-adrenal axis(HPAA) functions preserved patients(P<0.00001). The morbidity of early postoperative adrenal insufficiency ranged from 0.96% to 12.90%, with the overall morbidity of 5.55%(41/739). There was no significant differences of early postoperative diabetes insipidus between no supplementation patients and in supplementation patients(P=0.82). Conversely, there may be some disadvantages of high levels of cortisols such as high incidence of osteopenia and bone derangement and even the increased mortality rate. The patients with MSC levels of less than 60 nmol/l at 3 days after operation is considered as adrenal insufficient and more than 270 nmol/l as adrenal sufficient. To patients with MSC levels of 60–270 nmol/l, we need more clinical data to establish further cortisol supplementation criteria.</p></div

Overview of 18 included studies.

<p><b>Abbreviation</b>: M(Age distribution column): Mean age; GH: Growth Hormone secreting adenomas; PRL: Prolactin secreting adenomas; NF: Non functioning adenomas</p><p>Overview of 18 included studies.</p

The predictive value of early postoperative MSC levels for HPAA integrity assessment.

<p>Abbreviation: ITT: Insulin tolerance test; SST: Short synacthen test; CST: Cortrosyn stimulation test; Time:Time when the serum cortisol levels measured.</p><p>The predictive value of early postoperative MSC levels for HPAA integrity assessment.</p

The morbidity of postoperative early adrenal insufficiency in patients with normal preoperative MSC levels.

<p>The morbidity of postoperative early adrenal insufficiency in patients with normal preoperative MSC levels.</p

A Highly Efficient Gene Expression Programming (GEP) Model for Auxiliary Diagnosis of Small Cell Lung Cancer

<div><p>Background</p><p>Lung cancer is an important and common cancer that constitutes a major public health problem, but early detection of small cell lung cancer can significantly improve the survival rate of cancer patients. A number of serum biomarkers have been used in the diagnosis of lung cancers; however, they exhibit low sensitivity and specificity.</p><p>Methods</p><p>We used biochemical methods to measure blood levels of lactate dehydrogenase (LDH), C-reactive protein (CRP), Na⁺, Cl^-, carcino-embryonic antigen (CEA), and neuron specific enolase (NSE) in 145 small cell lung cancer (SCLC) patients and 155 non-small cell lung cancer and 155 normal controls. A gene expression programming (GEP) model and Receiver Operating Characteristic (ROC) curves incorporating these biomarkers was developed for the auxiliary diagnosis of SCLC.</p><p>Results</p><p>After appropriate modification of the parameters, the GEP model was initially set up based on a training set of 115 SCLC patients and 125 normal controls for GEP model generation. Then the GEP was applied to the remaining 60 subjects (the test set) for model validation. GEP successfully discriminated 281 out of 300 cases, showing a correct classification rate for lung cancer patients of 93.75% (225/240) and 93.33% (56/60) for the training and test sets, respectively. Another GEP model incorporating four biomarkers, including CEA, NSE, LDH, and CRP, exhibited slightly lower detection sensitivity than the GEP model, including six biomarkers. We repeat the models on artificial neural network (ANN), and our results showed that the accuracy of GEP models were higher than that in ANN. GEP model incorporating six serum biomarkers performed by NSCLC patients and normal controls showed low accuracy than SCLC patients and was enough to prove that the GEP model is suitable for the SCLC patients.</p><p>Conclusion</p><p>We have developed a GEP model with high sensitivity and specificity for the auxiliary diagnosis of SCLC. This GEP model has the potential for the wide use for detection of SCLC in less developed regions.</p></div

Histopathologic test of SCLC patients.

<p>A. hematoxylin-eosin staining of biopsy specimen slice. B. CD56(+) findings in immunohistochemical method. C. Syn (+) findings in immunohistochemical method. D.TTF-1(+) findings in immunohistochemical method</p

The flowchart of the GEP modeling in this study.

<p>The flowchart of the GEP modeling in this study.</p

SCLC detection rate of GEP model 1 and model 2.

<p>CC = Correlation Coefficient; MSE = Mean Squared Error; RAE = Root Mean Squared Error; MAE = Mean Absolute Error; RSE = Relative Squared Error.</p><p>SCLC detection rate of GEP model 1 and model 2.</p

Parameter settings for the GEP algorithm.

<p>Parameter settings for the GEP algorithm.</p