A rapid identification system for metallothionein proteins using expert system

Metallothioneins (MT) are low molecular weight proteins mostly rich in cysteine residues with high metal content. Generally, MT proteins are responsible for regulating the intracellular supply of biologically essential metal ions and they protect cells from the deleterious effects of non-essential polarizable transition and post-transition metal ions. Due to their biological importance, proper characterization of MT is necessary. Here we describe a computer program (ID3 algorithm, a part of Artificial Intelligence) developed using available data for the rapid identification of MT. Tissue samples contains several low molecular weight proteins with different physical, chemical and biological characteristics. The described software solution proposes to categorize MT proteins without aromatic amino acids and high metal content. The proposed solution can be expanded to other types of proteins with specific known characteristics.     

A fuzzy expert system for the optimization of glutamic acid production

A fuzzy expert system was developed to allow the effective use of semi-quantitative or imprecise information in the determination of the optimal operating conditions of a fermentation process. The system incorporated fuzzy relations representing both the trends of experimental data and semi-quantitative information obtained from the literature. The inference method used consisted primarily of search and reasoning based on fuzzy set theory. The resulting expert system incorporated a generalized inference engine designed to deal with various types of fermentation processes, it only being necessary to alter the knowledge database in order to adapt the system to process modifications. The construction of the knowledge database from experimental data or semi-quantitative information was designed to be carried out semi-automatically using a graphic computer tool.The expert system was applied to the optimization of glutamic acid production by fermentation. The optimal conditions predicted by the expert system were found experimentally to give maximum production.List of Symbols A, B names of objects - A _i , B _i linguistic level of A and B, respectively - E₁, E₂ ordinary sets - I depth of search for inference - I _M maximum of I - M, X, Y names of sets - R ₁, R ₂ fuzzy relations - P_total g amount of glutamic acid production - Pen⁺ h penicillin addition time - S_vp1 h^–1 specific rate of glutamic acid production in 1st production phase - S_vp2 h^–1 specific rate of glutamic acid production in 2nd production phase - T _growth h growth period - T _lag h lag time - T _plag h lag time of production defined in Fig. 6 - T _p1 h period of 1st production - T _p2 h period of 2nd production - T _total h total production time - X _p g average cell mass of production phase - x, y, z real numbers - max(x, y) or x y maximum of x and y - min(x, y) or x y minimum of x and y     

A real-time database/models base/expert system in predictive microbiology

Summary This paper describes the development and operation of a database/models base/expert system funded by the Ministry of Agriculture, Fisheries and Food in the UK. As part of an on-going coordinated program on predictive microbiology, the system being established involves storage of data and models relevant to changes in populations of food-borne pathogens under given conditions. The system is due to be completed by March 1994.     

Colonic lesion expert system. Performance evaluation

A computer-based expert system for diagnosing colonic sections as normal, adenoma or adenocarcinoma is described, along with an evaluation of its performance. On the basis of its knowledge base, consisting of the values of diagnostic clues and their associated certainty factors for the possible diagnoses, the system will suggest the diagnosis for new cases presented to it. Using the data provided for 16 diagnostic clues, the system arrived at correct diagnoses for all cases of normal colon, for 49 of 50 cases of adenoma and for 48 of 49 cases of adenocarcinoma. Sample outputs from the expert system are presented and discussed, and the effects of possible alterations in the data base are considered.     

城市污水土地处理专家系统研究

在进行污水土地处理适宜性调查和研究基础上,应用ＴｕｒｂｏＰｒｏｌｏｇ和Ｃ程序语言建立了污水土地处理专家系统（ＬＴＥＳ）．通过测试表明,该系统能对土地处理系统的进水水质、场地适宜性、出水目标等指标进行快速准确的判断和预测,解决了污水土地处理的选址、处理工艺类型选择等问题,是科学设置污水生态工程的重要工具．     

Colonic lesion expert system. Evaluation of sensitivity

In a previous study, an expert system using visually assessed diagnostic clues for diagnosing colonic tissue as normal, adenoma or adenocarcinoma arrived at diagnoses agreeing with the evaluation by pathologists ("correct diagnoses") for all 49 cases of normal colon, for 49 of 50 cases of adenoma and for 48 of 49 cases of adenocarcinoma. The present study examined the robustness and sensitivity of the expert system to changes in the knowledge base, to changes in criteria specified by the user and to missing information. Alternative rules for combining certainty factors are discussed.     

A microcomputer system for video image analysis and diagnostic microdensitometry

A system for microdensitometry based on a microcomputer, video digitizer and solid-state camera has been developed. Image analysis and densitometry are achieved with convenient control over image editing and calibration. The linear photometric properties of the imaging device enable measurements of high accuracy. The system has proven to give rapid and repeatable performance for determining DNA content distribution from measurements of Feulgen-stained cell nuclei. The results show that a practical image analysis microdensitometer can be designed using a readily available microcomputer. The low cost and simple operation are of benefit for diagnostic applications in which flow cytometry is not possible, the time required for microscope photometry is too great or an automated image analyzer and support staff are not available.     

Hybrid expert system aiding design of post-mining regions restoration

Reclamation as one of the stages in the life cycle of a mine is realized using different techniques and technology adapted to the unique characteristics for any given mining institution. Restoration of terrain from open-cast mining is influenced by many factors and processes; the results are open to interpretation and are not predictable. Most of the aforementioned factors have qualitative characteristics. The number and complex connections among these factors make the analysis of post-mining terrain restoration expensive and time-consuming. Therefore the automation of the decision making is desirable. In this paper, a fuzzy decision support system design is proposed for the restoration of post-mining regions. The system was applied to the testing of decision making concerning the direction of revitalization in an open-cast mining institution in Zator community, southern Poland. The considered gravel mine has worked since 1951 and belongs to the Cracow Aggregate Exploitation Company.     

Stabilizing blood glucose with a novel medical expert system

In health, metabolism is elegantly coordinated. Failure of an underlying process (as occurs in diabetes) disrupts the coordination and impacts on the global status of the affected individual. It takes a medical expert to intervene and restore order. Chaotic processes prevail at all times in biological systems and their behaviour in sickness degenerates between medical interventions. We have explored the use of an expert system to substitute for the physician between interventions and demonstrated its ability to maintain order and thus significantly improve control of blood glucose.     

Predicting drug metabolism--an evaluation of the expert system METEOR

The paper begins with a discussion of the goals of metabolic predictions in early drug research, and some difficulties toward this objective, mainly the various substrate and product selectivities characteristic of drug metabolism. The major in silico approaches to predict drug metabolism are then classified and summarized. A discrimination is, thus, made between 'local' and 'global' systems. In its second part, an evaluation of METEOR, a rule-based expert system used to predict the metabolism of drugs and other xenobiotics, is reported. The published metabolic data of ten substrates were used in this evaluation, the overall results being discussed in terms of correct vs. disputable (i.e., false-positive and false-negative) predictions. The predictions for four representative substrates are presented in detail (Figs. 1-4), illustrating the interest of such an evaluation in identifying where and how predictive rules can be improved.     

Braindex--an expert system for the diagnosis of brain death

An IBM PC-based system was developed as a decision-supporting system for the diagnosis of brain death. Braindex has been realized with the expert system Tool PC-Plus, and includes a knowledge base containing 300 rules organized in 8 frames. Both forward chaining and backward chaining are used in the inference engine. Braindex also includes a text archive and a lexicon. The data of 42 brain death patients are stored in the data bank (300 parameter per patient). The system is presently in the first stage of clinical application.     

CASSIOPE: An expert system for conserved regions searches

Background  

Understanding genome evolution provides insight into biological mechanisms. For many years comparative genomics and analysis of conserved chromosomal regions have helped to unravel the mechanisms involved in genome evolution and their implications for the study of biological systems. Detection of conserved regions (descending from a common ancestor) not only helps clarify genome evolution but also makes it possible to identify quantitative trait loci (QTLs) and investigate gene function.     

A new cancer diagnostic system based on a CDK profiling technology

A series of molecular pathological investigations of the molecules that stimulate the cyclin dependent kinases (CDK1, 2, 4, and 6) have led to enormous accumulation of knowledge of the clinical significance of these molecules for cancer diagnosis. However, the molecules have yet to be applied to clinical cancer diagnosis, as there is no available technology for application of the knowledge in a clinical setting. We hypothesized that the direct measurement of CDK activities and expressions (CDK profiling) might produce clinically relevant values for the diagnosis. This study investigated the clinical relevance of CDK profiling in gastrointestinal carcinoma tissues by using originally developed expression and activity analysis methods. We have established novel methods and an apparatus for analyzing the expression and activities of the CDK molecules in lysate of tumor tissue in a clinical setting, and examined 30 surgically dissected gastrointestinal carcinomas and corresponding normal mucosal specimens. We demonstrate here that remarkably elevated CDK2 activity is evident in more than 70% of carcinoma tissues. Moreover, a G1-CDK activity profiling accurately mirrored the differences in proliferation between tumor and normal colonic tissues. Our results suggest that CDK profiling is a potent molecular-clinical approach to complement the conventional pathological diagnosis, and to further assist in the individualized medications.     

An expert system for interpretation of X-ray fluorescence spectra

The complexity of X-ray fluorescence (XRF) spectra has lead to a number of computerised interpretation and element identification systems being developed and reported in the literature. In practice, however, human operators can generally perform the task better. The system outlined here uses a strategy based upon the recorded experience of experts, and employs an expert system with fuzzy logic to analyse and interpret XRF spectra. The aim has been to develop and implement a heuristically based scheme able to perform XRF qualitative analysis efficiently and effectively. Future developments and improvements to the system are discussed.     

MKES Tools: A microbial kinetics expert system for developing and assessing food production systems

Summary MKES Tools is a microbial kinetics expert system for developing food production systems and assessing product safety. The specific information required as input are: (1) a flowchart of the production system, (2) the factors affecting the survival and growth of food-borne pathogens and (3) the ranges of variation for each factor's parameters. With this information, MKES Tools simulates the growth and survival of pathogenic microorganisms when subjected to many different factor/parameter situations. The responses obtained are then used to estimate the significance of each factor's parameters.Reference to a brand or firm name does not constute endorsement by the US Department of Agriculture over others of a similar nature not mentioned.     

An application of an expert system to potentiometric stripping analysis

In this paper, a potentiometric stripping analysis (PSA) system controlled by an expert system, designed and constructed by us, is examined for the analysis of cadmium, lead and copper. PSA has gained a place in trace metal analysis, with many applications of this technique reported in the past decade. The simpler equipment required and lack of organic interference have made this technique an alternative method to the well established anodic stripping voltammetric (ASV) procedure. The expert system not only provides direct equipment control but also interprets the results based on its knowledge base and provides adjustments of the experimental parameters to optimize the analysis. The selected expert system builder, Crystal, is an extremely simple programming environment, the instruction being almost in the form of standard English. This allows the user to build up a knowledge base without the need for great computing skill.