肿瘤的过诊断和过治疗

长期以来,为减少肿瘤的死亡率一直强调"早期诊断和早期治疗"。但迄今病理学并不能够回答多早期的"癌"性病变一定会不可逆的向前发展,恶性生长、转移,直至夺人性命。很多看似"癌"性的病变可长期稳定,甚至消退,在患者因其它原因死亡前不因"癌"而就诊。医学影像技术的进步和医疗福利的提高,很多人群经常进行体检和肿瘤的筛查,从而查出很多早期癌患。本文以乳腺癌、肺癌、前列腺癌和甲状腺癌为例,就这种筛查导致的多诊断出的"癌"和由其导致的不必要的治疗,做一简要回顾分析。

Nonlinear online process monitoring and fault diagnosis of condenser based on kernel PCA plus FDA

A novel online process monitoring and fault diagnosis method of condenser based on kernel principle component analysis （KPCA） and Fisher discriminant analysis （FDA） is presented. The basic idea of this method is： First map data from the original space into high-dimensional feature space via nonlinear kernel function and then extract optimal feature vector and discriminant vector in feature space and calculate the Euclidean distance between feature vectors to perform process monitoring. Similar degree between the present discriminant vector and optimal discriminant vector of fault in historical dataset is used for diagnosis. The proposed method can effectively capture the nonlinear relationship among process variables. Simulating results of the turbo generator＇s fault data set prove that the proposed method is effective.

Nonlinear Statistical Process Monitoring and Fault Detection Using Kernel ICA

A novel nonlinear process monitoring and fault detection method based on kernel independent component analysis(ICA) is proposed.The kernel ICA method is a two-phase algorithm:whitened kernel principal component(KPCA) plus ICA.KPCA spheres data and makes the data structure become as linearly separable as possible by virtue of an implicit nonlinear mapping determined by kernel.ICA seeks the projection directions in the KPCA whitened space,making the distribution of the projected data as non-gaussian as possible.The application to the fluid catalytic cracking unit(FCCU) simulated process indicates that the proposed process monitoring method based on kernel ICA can effectively capture the nonlinear relationship in process variables.Its performance significantly outperforms monitoring method based on ICA or KPCA.

On-line Fault Diagnosis in Industrial Processes Using Variable Moving Window and Hidden Markov Model

An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction step, by which wavelet transform and principal component analysis are used to capture the inherent characteristics from process measurements, followed by a similarity assessment step using hidden Markov model (HMM) for pattern comparison. In most previous cases, a fixed-length moving window was employed to track dynamic data, and often failed to capture enough information for each fault and sometimes even deteriorated the diagnostic performance. A variable moving window, the length of which is modified with time, is introduced in this paper and case studies on the Tennessee Eastman process illustrate the potential of the proposed method.

Diagnosis and management of postural orthostatic tachycardia syndrome：A brief review

Postural orthostatic tachycardia syndrome （POTS） has been recognized since at least 1940.A review of the literature identifies differences in the definition for this condition and wide variations in treatment and outcomes.This syndrome appears to describe a group of conditions with differing pathophysiology,which requires treatment tailored to the true underlying disorder.Patients need to be fully evaluated to guide treatment.Further research is required to effectively classify the range of underlying pathophysioiogy that can produce this syndrome and to guide optimal management.

Sister Mary Joseph's nodule as a first sign of pancreatic cancer

Sister Mary Joseph's nodule(SMJN) refers to a metastatic tumor of the umbilicus.It is a rare entity which arises from a malignancy in the intra-abdominal cavity.We herein describe a patient who presented with SMJN as his first sign of pancreatic cancer.It is an even more unusual case of SMJN.We therefore,suggest that pancreatic cancer should be included in the differential diagnosis when an umbilical mass is found.With the progress made in surgical procedures and other modalities,an early diagnosis will dramatically improve the prognosis of the patients.

Combination Method of Principal Component Analysis and Support Vector Machine for On-line Process Monitoring and Fault Diagnosis

On-line monitoring and fault diagnosis of chemical process is extremely important for operation safety and product quality. Principal component analysis (PCA) has been widely used in multivariate statistical process monitoring for its ability to reduce processes dimensions. PCA and other statistical techniques, however, have difficulties in differentiating faults correctly in complex chemical process. Support vector machine (SVM) is a novel approach based on statistical learning theory, which has emerged for feature identification and classification. In this paper, an integrated method is applied for process monitoring and fault diagnosis, which combines PCA for fault feature extraction and multiple SVMs for identification of different fault sources. This approach is verified and illustrated on the Tennessee Eastman benchmark process as a case study. Results show that the proposed PCA-SVMs method has good diagnosis capability and overall diagnosis correctness rate.

Comparison between different reconstruction routes in esophageal squamous cell carcinoma

AIM:To compare postoperative complications and prognosis of esophageal squamous cell carcinoma patients treated with different routes of reconstruction. METHODS:After obtaining approval from the Medical Ethics Committee of the Sun Yat-Sen University Cancer Center, we retrospectively reviewed data from 306 consecutive patients with histologically diagnosed esophageal squamous cell carcinoma who were treated between 2001 and 2011. All patients underwent radical McKeown-type esophagectomy with at least two-field lymphadenectomy. Regular follow-up was performed in our outpatient department. Postoperative complica-tions and long-term survival were analyzed by treatment modality, baseline patient characteristics, and operative procedure. Data from patients treated via the retrosternal and posterior mediastinal routes were compared. RESULTS:The posterior mediastinal and retrosternal reconstruction routes were employed in 120 and 186 patients, respectively. Pulmonary complications were the most common complications experienced during the postoperative period (46.1% of all patients; 141/306). Compared to the retrosternal route, the posterior mediastinal reconstruction route was associated with a lower incidence of anastomotic stricture (15.8% vs 27.4%, P = 0.018) and less surgical bleeding (242.8 ± 114.2 mL vs 308.2 ± 168.4 mL, P < 0.001). The median survival time was 26.8 mo (range:1.6-116.1 mo). Upon uni/multivariate analysis, a lower preoperative albumin level (P = 0.009) and a more advanced pathological stage (pT; P = 0.006; pN; P < 0.001) were identified as independent factors predicting poor prognosis. The reconstruction route did not influence prognosis (P = 0.477). CONCLUSION:The posterior mediastinal route of reconstruction reduces incidence of postoperative complications but does not affect survival. This route is recommended for resectable esophageal squamous cell carcinoma.

Prognosis of gestational choriocarcinoma diagnosed incidentally during laparoscopy for a presumed cornual pregnancy:a report of five cases

The clinical presentations of gestational choriocarcinoma vary markedly, and a misdiagnosis could be made in atypical patients if simply relying on clinical features. Laparoscopic resection of uterine mass lesion is rarely used in gestational choriocarcinoma diagnosis because of the fear of heavy blood loss and distant metastasis. Five patients who were preoperatively diagnosed as having cornual pregnancy underwent laparoscopic resection of mass lesion and then proved to have gestational choriocarcinoma based on pathological examinations. Chemotherapy was started within two days after surgery, and the rate of complete remission was 100%. The mean follow-up time was 29.8±19.1 months, and no patient showed signs of relapse. Laparoscopic resection of uterine mass followed by timely postoperative chemotherapy may be an effective and safe way to obtain pathologic results in patients with suspected gestational choriocarcinoma.

Mutation of cytotoxin-associated gene A affects expressions of antioxidant proteins of Helicobacter pylori

AIM: To determine if disruption of the cagA gene of Helicobacter pylori (H pylori) has an effect on the expression of other proteins at proteome level. METHODS: Construction of a cagA knock out mutant Hp27 _△cagA (cagA -) via homologous recombination with the wild-type strain Hp27 (cagA+) as a recipient was performed. The method of sonication-urea-CHAPS-DTT was employed to extract bacterial proteins from both strains. Soluble proteins were analyzed by two-dimensional electrophoresis (2-DE). Images of 2-DE gels were digitalized and analyzed. Only spots that had a statistical signif icance in differential expression were selected and analyzed by matrix-assisted laser desorption/ionizationtime of flight mass spectrometry (MALDI-TOF-MS). Biological information was used to search protein database and identify the biological function of proteins. RESULTS: The proteome expressions between wild-type strain and isogenic mutant with the cagA gene knocked-out were compared. Five protein spots with high abundance in bacteria proteins of wild-type strains, down-regulated or absently expressed in bacteria proteins of mutants, were identified and analyzed. From a quantitative point of view, the identified proteins are related to the cagA gene and important antioxidant proteins of H pylori , including alkyl hydroperoxide reductase (Ahp), superoxide dismutase (SOD) and modulator of drug activity (Mda66), respectively, suggesting that cagA is important to maintain the normal activity of antioxidative stress and ensure H pylori persistent colonization in the host. CONCLUSION: cagA gene is relevant to the expressions of antioxidant proteins of H pylori, which may be a novel mechanism involved in H pylori cagA pathogenesis.

Analysis of superheater's pipe wall overtemperature by fault tree diagnose

After research on a 2000t/h subcritical forced-circulation balanced ventilation were applied boiler and the structure and operation of its auxiliary system builds up this heat transfer model of a superheater's pipe wall and analyze the effect of primary factors on the overtemperature of the pipe wall. Fault tree structure was used to uncover the multiplayer logic between the overtemperature of the superheater's pipe wall and the faults.

Fault Detection and Diagnosis of a Gearbox in Marine Propulsion Systems Using Bispectrum Analysis and Artificial Neural Networks

A marine propulsion system is a very complicated system composed of many mechanical components.As a result,the vibration signal of a gearbox in the system is strongly coupled with the vibration signatures of other components including a diesel engine and main shaft.It is therefore imperative to assess the coupling effect on diagnostic reliability in the process of gear fault diagnosis.For this reason,a fault detection and diagnosis method based on bispectrum analysis and artificial neural networks (ANNs) was proposed for the gearbox with consideration given to the impact of the other components in marine propulsion systems.To monitor the gear conditions,the bispectrum analysis was first employed to detect gear faults.The amplitude-frequency plots containing gear characteristic signals were then attained based on the bispectrum technique,which could be regarded as an index actualizing forepart gear faults diagnosis.Both the back propagation neural network (BPNN) and the radial-basis function neural network (RBFNN) were applied to identify the states of the gearbox.The numeric and experimental test results show the bispectral patterns of varying gear fault severities are different so that distinct fault features of the vibrant signal of a marine gearbox can be extracted effectively using the bispectrum,and the ANN classification method has achieved high detection accuracy.Hence,the proposed diagnostic techniques have the capability of diagnosing marine gear faults in the earlier phases,and thus have application importance.

Feature selection for chemical process fault diagnosis by artificial immune systems

With the Industry 4.0 era coming, modern chemical plants will be gradually transformed into smart factories, which sets higher requirements for fault detection and diagnosis(FDD) to enhance operation safety intelligence. In a typical chemical process, there are hundreds of process variables. Feature selection is a key to the efficiency and effectiveness of FDD. Even though artificial immune system has advantages in adaptation and independency on a large number of fault samples, antibody library construction used to be based on experience. It is not only time consuming, but also lack of scientific foundation in fault feature selection, which may deteriorate the FDD performance of the AIS. In this paper, a fault antibody feature selection optimization(FAFSO) algorithm is proposed based on genetic algorithm to optimize the fault antibody features and the antibody libraries' thresholds simultaneously. The performance of the proposed FAFSO algorithms is illustrated through the Tennessee Eastman benchmark problem.

Fault Prediction Based on Dynamic Model and Grey Time Series Model in Chemical Processes

This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is introduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to retrieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.

Psychological burden of food allergy

One fifth of the population report adverse reactions to food. Reasons for these symptoms are heterogeneous, varying from food allergy, food intolerance, irritable bowel syndrome to somatoform or other mental disorders. Literature reveals a large discrepancy between truly diagnosed food allergy and reports of food allergy symptoms by care seekers. In most studies currently available the characterization of patient groups is incomplete, because they did not distinguish between immunologic reactions and other kinds of food reactions. In analysing these adverse reactions, a thorough physical and psychological diagnostic approach is important. In our qualitative review, we present those diagnostic measures that are evidenced-based as well as clinically useful, and discuss the various psychological dimensions of adverse reactions to food. It is important to acknowledge the complex interplay between body and mind： Adults and children suffering from food allergy show impaired quality of life and a higher level of stress and anxiety. Pavlovian conditioning of adverse reactions plays an important role in maintaining symptoms. The role of personality, mood, or anxiety in food reactions is debatable. Somatoform disorders ought to be identified early to avoid lengthy and fiustrating investigations. A future task will be to improve diagnostic algorithms, to describe psychological aspects in clearly characterised patient subgroups, and to develop strategies for an optimized management of the various types of adverse reactions to food.

Small intestine bacterial overgrowth and irritable bowel syndrome-related symptoms:Experience with Rifaximin

AIM： TO estimate the prevalence of small intestinal bacterial overgrowth （SIBO） in our geographical area （Western Sicily, Italy） by means of an observational study, and to gather information on the use of locally active, non-absorbable antibiotics for treatment of SIBO.METHODS： Our survey included 115 patients fulfilling the Rome II criteria for diagnosis of irritable bowel syndrome （IBS）; a total of 97 patients accepted to perform a breath test with lactulose （BTLact）, and those who had a positive test, received Rifaximin （Normix , Alfa Wassermann） 1200 mg/d for 7 d; 3 wk after the end of treatment, the BTLact was repeated.RESULTS： Based on the BTLact results, SIBO was present in about 56% of IBS patients, and it was responsible for some IBS-related symptoms, such as abdominal bloating and discomfort, and diarrhoea. 1-wk treatment with Rifaximin turned the BTLact to negative in about 50% of patients and significantly reduced the symptoms, especially in those patients with an alternated constipation/diarrhoea-variant IBS. CONCLUSION： SIBO should be always suspected in patients with IBS, and a differential diagnosis is done by means of a ＂breath test＂. Rifaximin may represent a valid approach to the treatment of SIBO.

Fault diagnosis and process monitoring using a statistical pattern framework based on a self-organizing map

A multivariate method for fault diagnosis and process monitoring is proposed. This technique is based on a statistical pattern(SP) framework integrated with a self-organizing map(SOM). An SP-based SOM is used as a classifier to distinguish various states on the output map, which can visually monitor abnormal states. A case study of the Tennessee Eastman(TE) process is presented to demonstrate the fault diagnosis and process monitoring performance of the proposed method. Results show that the SP-based SOM method is a visual tool for real-time monitoring and fault diagnosis that can be used in complex chemical processes.Compared with other SOM-based methods, the proposed method can more efficiently monitor and diagnose faults.

Synthetic Intelligent Fault Diagnosis Technology for Complex Process

A fault diagnosis method of knowledge based fuzzy neural network is proposed for complex process, which is hard to develop practical mathematical model. Fault detection is performed through a knowledge based system, where fault detection heuristic rules have been generated from deep and shallow knowledge of the process. The fuzzy neural network performs the fault diagnosis task. This method does not need practical mathematical models of objects, so it is a strong implement for complex process.

Diagnostic and Therapeutic Cold Knife Conization for Cervical Intraepithelial Neoplasia

OBJECTIVE of using cold （CIN）. METHODS To evaluate the diagnostic and therapeutic efficacy knife conization for cervical intraepithelial neoplasia We retrospectively analyzed 186 cases with CIN diagnosed and treated in our hospital; compared the histologic diagnoses from cervical conization and from colposcopic multiple punch biopsies, and then evaluated their postoperative histologic findings and clinical outcomes. RESULTS Of the 186 cases, there was a correlation in histologic findings between cervical conization and colposcopic multiple punch biopsies in 138 cases （74.2%）, and there was no correlation in the other 48 cases （25.8%）. Incomplete excision was performed in 8 cases （4.3%）, but the failure rate was only 1.1%; the cure rate was 98.9%. Five cases with early invasive cancer were found. Eleven patients underwent subsequent hysterectomy. The main complications associated with conization were hemorrhage and cervical stenosis. Bleeding occurred in 8 （4.3%） of the patients, and cervical stenosis occurred in 3 （1.6%）. CONCLUSION Cervical intraepithelial neoplasia was diagnosed more accurately using conization than by colposcopic multiple punch biopsies. Conization can also play an important role in the treatment for CIN. If properly performed, the procedure has a low risk of complications. It can provide an accurate histologic representation of the disease process, and be curative in most cases.

New aspects in celiac disease

Celiac disease (CD) is a common autoimmune disorder characterized by an immune response to ingested gluten and has a strong HLA association with HLA- DQ2 and HLA-DQ8 molecules, but human HLA-DQ risk factors do not explain the entire genetic susceptibility to gluten intolerance. CD is caused by the lack of immune tolerance (oral tolerance) to wheat gluten. In this sense, the expression of soluble HLA-G in CD is of special interest because the molecule plays an important role in the induction of immune tolerance. The enhanced expression of soluble HLA-G found in CD may be part of a mechanism to restore the gluten intolerance. In this editorial, we review recent progress in understanding CD in relation to its prevalence, diagnosis and possible mechanisms of pathogenesis.