Acute phase serum amyloid A in ovarian cancer as an important component of proteome diagnostic profiling

In the context of serum amyloid A (SAA) identification as ovarian cancer marker derived by SELDI‐MS, its serum levels were measured by immunoassay in different stages of ovarian cancer, in benign gynecological tumors, and in healthy controls. In addition, SELDI‐TOF‐MS spectra were obtained by protocol optimized for the SAA peak intensity. SELDI data on small proteins (5.5–17.5 kDa) and SAA immunoassay data were combined with cancer antigen (CA)125 data in order to study the classification accuracy between cancer and noncancer by support vector machine (SVM), logistic regression, and top scoring pair classifiers. Although an addition of SAA immunoassay data to CA125 data did not significantly improve cancer/noncancer discrimination, SVM applied to combined biomarker data (CA125 and SAA immunoassay variables plus 48 SELDI peak variables) yielded the best classification rate (accuracy 95.2% vs. 86.2% for CA125 alone). Notably, most of discriminatory peaks selected by the classifiers have significant correlation with the major known peaks of SAA (11.7 kDa) and transthyretin (13.9 kDa). Acute phase serum amyloid A (A‐SAA) was proved to be an important member of cancer discriminatory protein profile. Among the eight known ovarian cancer SELDI profile components, A‐SAA is the most relevant to molecular pathogenesis of cancer and it has the highest degree of up‐regulation in disease.     

A feedforward–feedback glucose control strategy for type 1 diabetes mellitus

As the “artificial pancreas” becomes closer to reality, automated insulin delivery based on real-time glucose measurements becomes feasible for people with diabetes. This paper is concerned with the development of novel feedforward–feedback control strategies for real-time glucose control and type 1 diabetes. Improved post-meal responses can be achieved by a pre-prandial snack or bolus, or by reducing the glucose setpoint prior to the meal. Several feedforward–feedback control strategies provide attractive alternatives to the standard meal insulin bolus and are evaluated in simulations using a physiological model.     

Identification of Apolipoprotein AI as a serum biomarker of chronic kidney disease in liver transplant recipients, using proteomic techniques

Chronic kidney disease (CKD) is a common complication post‐orthotopic liver transplantation (OLT). Development of CKD is detected by monitoring serum urea and creatinine, however disease can occasionally be at an advanced stage before they become abnormal. Therefore, more accurate parameters are required. In order to identify novel biomarkers of CKD, serum was obtained from 47 OLT recipients with CKD (glomerular filtration rate <60 mL/min) and 23 with normal renal function (glomerular filtration rate >90 mL/min). Using the proteomic technique SELDI‐TOF‐MS, three protein biomarkers (55.6 kDa, 9.5 kDa and 11.4 kDa) were identified that, together, could stratify patients into cases or controls with a sensitivity and specificity of 93.6 and 91.3%, respectively. The area under the curve was 0.94. The primary splitter of the groups at 55.6 kDa was an alternative version of a molecule at 27.8 kDa, which was subsequently identified by 1‐D SDS‐PAGE and LC‐ESI‐MS/MS to be Apolipoprotein AI. Protein expression was shown to be reduced in CKD, by both ELISA (p = 0.057) and Western blot analysis (p = 0.003). Apolipoprotein AI is a novel, accurate marker of CKD post‐OLT. It does require further validation in a large, more diverse patient population but could potentially improve detection of CKD.     

Implementation and evaluation of a decision support system for type II diabetes

A decision support system for the management of oral hypoglycaemic therapy in type II diabetes was evaluated. The ruleset contained therein forms the basis of a prototype computer programme, but in order to assess the robustness of the individual rules, it was decided it was necessary to use a paper-based form of the ruleset. A nurse with no previous experience of managing type II diabetes was trained to use the system and then undertook the exclusive management of half of all new type II diabetics, from a district population of 300 000, over a 16-month period. General practices within this area were divided into two groups, study and control, matching for size, geographical area and standards of existing diabetes care. Patients (n = 102) from the study group practices were then assigned to her care. Those patients (n = 116) in the control group of practices were treated according to their normal procedures. The decision support system for oral hypoglycaemic therapy was based on the following criteria: the current type of treatment (six levels); current glycaemic control (HbA₁ and FBS) — whether improving, steady or worsening; and weight — %IBW, whether rising, steady or falling. Each of these parameters was carefully defined on the basis of established practice and clinical experience. Patients after initial education were seen at their usual clinic by the nurse only, on a monthly basis, until satisfactory glycaemic control was established and thereafter reviewed 3 monthly. She was also responsible for ensuring the organisation of Diabetes Annual Review procedures. The medical records of the control group patients were examined at the end of the study and data on glycaemic control and Annual Reviews extracted. In the study group 98% patients achieved HbA₁ levels within the normal range and all patients had full annual reviews performed. The control practices achieved much poorer degrees of metabolic control (P < 0.01) and completed fewer annual reviews. The study group did not demonstrate a significantly increased frequency of clinical hypoglycaemia consequent upon better blood sugar control. No exceptions to the ruleset, as initially defined, were detected. In conclusion, this decision support system was successful at achieving standards of diabetes control and care equal to or better than conventional structures of diabetes care. Implementation of such a system, on a simple computer platform, could greatly assist and possibly improve diabetes management in general practice.     

Feedback and feedforward control in the context of model predictive control with application to the management of type 1 diabetes mellitus

A unified formulation of feedback and feedforward control is given in the context of model predictive control. The ideas are illustrated by the management of type 1 diabetes mellitus although the general principles apply, mutatis mutandis, to other scenarios and problems.     

Evaluation of a hypermedia document as a learning tool

This paper describes a classroom‐based experimental evaluation of an electronic history 'book' presented in a hypermedia environment. It was compared with a paper‐based version of the same material. Observations of children's activities and interactions revealed that they had few problems using the hypermedia document as an information source and also rated it more positively, in terms of ease of use, than those children using the paper‐based version. However, no significant differences were found between the two groups in the number of questions children completed and answered correctly, their interest in the material, and task difficulty. The implications of these findings and the role of evaluation in determining the educational value of computer‐based activities are discussed.     

Large-scale protein identification of human urine proteome by multi-dimensional LC and MS/MS

Urine is a human specimen that is easily obtained non-invasively for clinical diagnosis. We attempted to enhance the resolution of current human urine proteomes and construct a comprehensive reference database for advanced studies, such as the discovery of biomarkers for renal diseases. Multi-dimensional LC-MS/MS was coupled with de novo sequencing and database matching. The proposed approach improved the identification of not only the proteins, but also the post-translational sites of urinary proteins. We identified 165, 200 and 259 unique gene products in the urine proteomes from males, females and pregnant women, respectively. When all of the results were combined and the redundancies removed, a total of 1095 distinct peptides were identified. Of these, 1016 peptides were associated with 334 unique gene products. In this study, over 100 gene products, including some disease-related proteins, were detected in urine for the first time by proteomic approaches. Various proteins with novel post-translational hydroxylation were identified using the MASCOT program and de novo sequencing. All proteins with peptide information were summarized into a comprehensive urine protein database. We believe that this comprehensive urine proteome database will assist in the identification of urinary proteins/polypeptides whose spectra are difficult to interpret in the discovery of urinary biomarkers.     

Prostate cancer serum biomarker discovery through proteomic analysis of alpha‐2 macroglobulin protein complexes

Alpha‐2 macroglobulin (A2M) functions as a universal protease inhibitor in serum and is capable of binding various cytokines and growth factors. In this study, we investigated if immunoaffinity enrichment and proteomic analysis of A2M protein complexes from human serum could improve detection of biologically relevant and novel candidate protein biomarkers in prostate cancer. Serum samples from six patients with androgen‐independent, metastatic prostate cancer and six control patients without malignancy were analyzed by immunoaffinity enrichment of A2M protein complexes and MS identification of associated proteins. Known A2M substrates were reproducibly identified from patient serum in both cohorts, as well as proteins previously undetected in human serum. One example is heat shock protein 90 alpha (HSP90α), which was identified only in the serum of cancer patients in this study. Using an ELISA, the presence of HSP90α in human serum was validated on expanded test cohorts and found to exist in higher median serum concentrations in prostate cancer (n = 18) relative to control (n = 13) patients (median concentrations 50.7 versus 27.6 ng/mL, respectively, p = 0.001). Our results demonstrate the technical feasibility of this approach and support the analysis of A2M protein complexes for proteomic‐based serum biomarker discovery.     

Evaluation of a decision support system for credit management decisions

This study was conducted to evaluate the effectiveness of a decision support system (DSS) for credit management. This study formed a part of a larger initiative to assess the effectiveness of IT-based credit management processes at the State Bank of India (SBI). Such a study was necessitated since credit appraisal has emerged to become a critical sub-function in Indian banks in view of growing incidence of non-performing assets. The DSS that we assessed was a credit appraisal system developed in Quattro Pro® at SBI. This system helps in the analysis of balance sheets, calculation of financial ratios, cash flow analysis, future projections, sensitivity analysis and risk evaluation as per SBI norms. We used a strong quasi-experimental design, called the Solomon's four-group design, for our assessment. In our experiment, managers of SBI who attended training programs at the SBI training college, were the subjects. The experiment consisted of measurements that were taken as pre- and post-tests. An experimental intervention was applied between the pre-tests and the post-tests. The intervention, or stimulus, consisted of DSS training and use. There were four groups in our experiment. The stimulus remained constant as we took care to ensure that the course contents as well as the instructors remained the same during the course of our experiment. Two were experimental groups and two were the control groups. All four groups underwent training in credit management between the pre- and post-tests. Results from our research show that while the DSS is effective, improvements need to be made in the methodology to assess such improvements. Moreover, such assessment frameworks, while being adequate from a DSS-centric viewpoint, do not respond to the assessment of a DSS in an organizational setting. In our concluding section, we have discussed how this evaluative framework can be strengthened to initiate an activity that will allow the long-term, and possibly the only meaningful, evaluation framework for such a system.     

基于多层次综合评价系统的教学质量评价系统的设计

探讨将模糊评判法应用于评价系统,并以高职教师教学质量评价系统设计为例,阐述多层次综合评价系统的应用.     

Automatic information timeliness assessment of diabetes web sites by evidence based medicine

Studies on health domain have shown that health websites provide imperfect information and give recommendations which are not up to date with the recent literature even when their last modified dates are quite recent. In this paper, we propose a framework which assesses the timeliness of the content of health websites automatically by evidence based medicine. Our aim is to assess the accordance of website contents with the current literature and information timeliness disregarding the update time stated on the websites.