[Application of the information theory and linear programming for the determination of optimal sets of symptoms].
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Diagnosis↗
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Results for “Programming, Linear”
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[Attempt at pig fattening using linear programmed all-concentrate feed in comparison with a DLG-standard all-concentrate feed].
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Animal Feed↗
[Minimum requirements of amino acids in feed mixtures for pigs following linear programming].
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Amino Acids↗
[Prospects of linear programming applied to the biomedical field].
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Mathematics↗
Determination of antibody affinity by ELISA with a non-linear regression program. Evaluation of linearized approximations.
ELISA experiments based on competition between immobilized and soluble antibody for soluble antigen, and on the formation of a ternary complex of immobilized antibody, antigen and soluble antibody were used by Hoylaerts et al. (J. Immunol. Methods 126 (1990) 253-261) for the determination of dissociation constants. The dissociation constant was taken from linearized plots according to a theory that required several approximations. The effect of these approximations on the resulting dissociation constants has been investigated using two computer programs, CBEIA-C and CBEIA-S. Since most approximations that have to be made for linearization can be avoided by non-linear regression, the programs provide a more reliable basis for calculation of the dissociation constant. Experiments measuring formation of a ternary complex were found to be unsuitable for affinity determination.
Animals↗
Solving linear integer programming problems by a novel neural model.
The paper deals with integer linear programming problems. As is well known, these are extremely complex problems, even when the number of integer variables is quite low. Literature provides examples of various methods to solve such problems, some of which are of a heuristic nature. This paper proposes an alternative strategy based on the Hopfield neural network. The advantage of the strategy essentially lies in the fact that hardware implementation of the neural model allows for the time required to obtain a solution so as not depend on the size of the problem to be solved. The paper presents a particular class of integer linear programming problems, including well-known problems such as the Travelling Salesman Problem and the Set Covering Problem. After a brief description of this class of problems, it is demonstrated that the original Hopfield model is incapable of supplying valid solutions. This is attributed to the presence of constant bias currents in the dynamic of the neural model. A demonstration of this is given and then a novel neural model is presented which continues to be based on the same architecture as the Hopfield model, but introduces modifications thanks to which the integer linear programming problems presented can be solved. Some numerical examples and concluding remarks highlight the solving capacity of the novel neural model.
Linear Models↗
ISMOD: an all-subsets regression program for generalized linear models. II. Program guide and examples.
This paper describes a system written to carry out regression analyses under certain generalized linear models that are widely used in biomedical research. These include continuous response models such as the Weibull, log logistic, log normal and Cox proportional hazards models used in survival analysis, and also discrete Poisson, binomial and multinomial response regression models. The system fits models, generates residuals and other diagnostic output, and also has an all-subsets regression feature. This paper describes the ISMOD system and presents examples of its application; Part I describes the models implemented and gives statistical background.
Biometry↗
Recursive modeling of ambulatory health care settings.
Previous work dealing with the planning of outpatient health care has primarily used either linear programming or simulation. Linear programs are rather severe abstractions of reality. Simulation models are more realistic but are very expensive and do not necessarily identify optimal solutions. This paper discusses a recursive optimization-stimulation approach, which takes advantage of the best features of both methods while minimizing the disadvantages of each method used alone. A mixed integer program generates staffing and facility plans, thus reducing the number of alternatives requiring analysis via simulation. The simulation model then evaluates the acceptability of alternative plans, considering detailed information and complex relationships omitted from the optimization model. The method is used in a hypothetical example based on data from a variety of sources. The results from the example demonstrate the value of the recursive method; however, they are not to be used in a general context.
Ambulatory Care↗
[Optimized linear temperature programming for capillary gas chromatography by the method of gridding search].
Linear temperature programming of capillary gas chromatography was optimized by using a new method of gridding search. A point of gridding demonstrated a condition of temperature programmed and the resolution and the retention time were optimized at all gridding points. With a new design of calculation, the method not only considered directly all components that were separated, but the velocity of calculation was improved also. Twenty-one compounds of alkanes, alcohols, halo-hydrocarbons and aromatic hydrocarbons, of which Kovats Indexes are varying from 600 to 1,000, were separated by this new method on an OV-101 column under linear temperature programming. Good results were obtained. The time for optimizing the 21 compounds was less than 1 min.
Alkanes↗
FEXPAC: a program for linear discriminant classification.
A new program for feature extraction and two-class classification utilizing the Fisher linear discriminant function model has been developed. It is intended as a tool in multivariate data analysis, and is especially suited for the design and storage of linear classifiers from training data sets.
Classification↗
Metabolic adaptation of Escherichia coli during temperature-induced recombinant protein production: 2. Redirection of metabolic fluxes.
The impact of temperature-induced synthesis of human basic fibroblast growth factor (hFGF-2) in high-cell-density cultures of recombinant Escherichia coli was studied by estimating metabolic flux variations. Metabolic flux distributions in E. coli were calculated by means of a stoichiometric network and linear programming. After the temperature upshift, a substantially elevated energy demand for synthesis of hFGF-2 and heat shock proteins resulted in a redirection of metabolic fluxes. Catabolic pathways like the Embden-Meyerhof-Parnas pathway and the tricarboxylic acid (TCA) cycle showed significantly enhanced activities, leading to reduced flux to growth-associated pathways like the pentose phosphate pathway and other anabolic pathways. Upon temperature upshift, an excess of NADPH was produced in the TCA cycle by isocitrate dehydrogenase. The metabolic model predicted the involvement of a transhydrogenase generating additional NADH from NADPH, thereby increasing ATP regeneration in the respiratory chain. The influence of the temperature upshift on the host's metabolism was investigated by means of a control strain harboring the "empty" parental expression vector. The metabolic fluxes after the temperature upshift were redirected similarly to the production strain; the effects, however, were observed to a lesser extent and with different time profiles.
Adaptation, Biological↗
Biomechanical implications of lateral pterygoid contribution to biting and jaw opening in humans.
The contributions of the lateral pterygoid muscle to a variety of different tasks were analysed by a linear programming mode based on the equations for static equilibrium in three dimensions and containing 12 muscles. The model was used to study lateral pterygoid activity at maximum bite force (MBF) for changes in (i) the direction and point of application of the bite force, (ii) the orientation of the masseter and medial pterygoid muscles and (iii) the slope of the articular eminence (glenoid slope). The effects on MBF of removing one or both lateral pterygoids were also examined. Lateral pterygoid provided a very important indirect contribution to some clenching forces. Under some conditions removing one lateral pterygoid muscle (simulating guarding an injured muscle) halved the MBF. Its activity at MBF was reduced as masseter was tilted more forward, the glenoid slope was made more horizontal and the bite force was made more vertical. The muscle helped to oppose (balance) the horizontal reaction forces at the bite point and joints, which potentially pushed the condyle backward. A balancing muscle is now defined as one (like lateral pterygoid) whose activity increases the output force by far more than its direct contribution to that force. In a larger model containing 16 muscles, every muscle was most active when its line of action was parallel to the output force. Finally, in a model which divided lateral pterygoid into superior and inferior heads, activity suddenly switched from the superior head to the inferior head when the angle of opening changed from 120 degrees (forward from the vertical) to 140 degrees.
Biomechanical Phenomena↗
A regression-like approach to developing a severity index for EMS patients.
An approach to constructing a severity index for emergency medical services patients with cardiac-related problems is developed. The procedure is based on two linear programming models and produces a set of weights which can be added to estimate the severity of a patient's condition. A set of patients independent of the set used to derive the weights was ranked with respect to severity by a set of physicians who were also independent of the model development process. The average value for Spearman's rank order correlation coefficient (rho) between a ranking based on the severity weights and the physicians was 0.6897. The average value of rho calculated over all possible pairs of the physician rankings was 0.6859. Thus, the ranking based on the severity weights correlated as well with the physicians ranking as did the physician rankings among themselves.
Computer Simulation↗
Efficient MILP formulations for the optimal synthesis of chromatographic protein purification processes.
The use of recombinant proteins has increased greatly in recent years, as well as the techniques used for their purification. The selection of an efficient process to purify proteins is a major bottleneck found when trying to scale up results obtained in the laboratory to a large-scale industrial process. One of the main challenges in the synthesis of downstream purification stages in biotechnological processes is the appropriate selection and sequencing of chromatographic steps. The objective of this work is to develop mixed integer linear programming models for the synthesis of protein purification processes. Models for each chromatographic technique rely on physicochemical data of a protein mixture, which contains the desired product and provide information on its potential purification. Formulations that are based on convex hull representations are proposed to calculate the minimum number of steps from a set of chromatographic techniques that must achieve a specified purity level and alternatively to maximize purity for a given number of steps. The proposed models are tested in several examples with experimental data and present time reductions of up to three orders of magnitude when compared to big-M formulations.
Biotechnology↗
Addressing the challenges to immunization practice with an economic algorithm for vaccine selection.
The biotechnology revolution is producing a growing bounty of new vaccines which pose difficult choices in selecting among many products. Some major public and private purchasers of vaccine may offer individual physicians and clinics their choice in assembling vaccine inventories. Others might purchase only a limited stock of products that would satisfactorily immunize a typical child. In either case, current vaccine selection decisions are based principally on purchase price alone without systematic consideration of other factors of fiscal consequence. As a potential tool for decision making, we developed an economic algorithm for vaccine selection that would minimize the overall costs of disease control through immunization by considering: (1) purchase price, (2) number of doses needed, (3) preparation time, (4) route of administration, (5) cold storage needs, (6) shelf life, (7) earliest age of full immunity, (8) adverse events frequency, and (9) efficacy of protection. To demonstrate the algorithm, variables (1) to (4) above were incorporated into a pilot binary-integer linear programming model that satisfied the recommended immunization schedule for diphtheria, tetanus, pertussis, Haemophilus influenzae b, and hepatitis B, using eleven vaccines (DTaP, DTaP-Hib, Hib, HepB and Hib-HepB) from four manufacturers. Five (or six) opportunities to vaccinate were modeled at (1), 2, 4, 6, 12-18, and 60 months of life, assuming US$40 per clinic visit, $15 per injection, and $0.50 per minute of nurse preparation time. Vaccine costs were varied using actual March and September 1997 US Federal vaccine prices, as well as estimates for unpriced new vaccines. Over 16,000 distinct vaccine stocking lists by vaccine type and brand were possible. Including a 1-month visit, the lowest-cost 'solution' of the algorithm was $529.41 per child in the March cost-assumption case, and $490.32 in the September one (both included four doses of DTaP-Hib, three HepB, and one DTaP). Without a 1-month visit, the lowest-cost solution in the March case cost $486.67 (four DTaP, two Hib-HepB, one DTaP-Hib, and one HepB), while the September case cost $450.32 (four DTaP-Hib, three HepB, and one DTaP). Ensuring at least one product was selected from each of the four manufacturers increased costs about $13.00, and the needed injections rose from eight to nine. The most economical selection of vaccines to use cannot be intuitively predicted, as permutations are large and solutions are sensitive to minor changes in costs and constraints. A transparent, objective selection method that weighs the economic value of distinguishing features among competing vaccines might offer the 'best value' to vaccine purchasers, while also creating strong market incentives for continuing innovation and competition in the vaccine industry.
Adolescent↗
Optimal synthesis of protein purification processes.
There has been an increasing interest in the development of systematic methods for the synthesis of purification steps for biotechnological products, which are often the most difficult and costly stages in a biochemical process. Chromatographic processes are extensively used in the purification of multicomponent biotechnological systems. One of the main challenges in the synthesis of purification processes is the appropriate selection and sequencing of chromatographic steps that are capable of producing the desired product at an acceptable cost and quality. This paper describes mathematical models and solution strategies based on mixed integer linear programming (MILP) for the synthesis of multistep purification processes. First, an optimization model is proposed that uses physicochemical data on a protein mixture, which contains the desired product, to select a sequence of operations with the minimum number of steps from a set of candidate chromatographic techniques that must achieve a specified purity level. Since several sequences that have the minimum number of steps may satisfy the purity level, it is possible to obtain the one that maximizes final purity. Then, a second model that may use the total number of steps obtained in the first model generates a solution with the maximum purity of the product. Whenever the sequence does not affect the final purity or more generally does not impact the objective function, alternative models that are of smaller size are developed for the optimal selection of steps. The models are tested in several examples, containing up to 13 contaminants and a set of 22 candidate high-resolution steps, generating sequences of six operations, and are compared to the current synthesis approaches.
Biotechnology↗
Serial 13C-based flux analysis of an L-phenylalanine-producing E. coli strain using the sensor reactor.
With the aid of the recently developed Sensor reactor system, a series of three subsequent (13)C labeling experiments was performed mirroring the l-phenylalanine (l-Phe) production phase of a recombinant E. coli strain that was cultivated under industry-like conditions in a 300 L bioreactor. On the basis of the data from NMR labeling analysis, three subsequent flux patterns were successfully derived monitoring the l-Phe formation during an observation window from 14 to 23.3 h process time. Linear programming was performed to identify optimal flux patterns for l-Phe formation. Additionally, flux sensitivity analysis was used to identify the most promising metabolic engineering target. As a result, high rates of phosphoenolpyruvate (PEP) to pyruvate (PYR) conversion were identified as the most important reason for deterioration of the l-Phe/glucose yield from 20 to finally 11 mol %. Considering the characteristics of the enzyme kinetics involved, the working hypothesis was formulated that phosphoenolpyruvate synthase activity was increasingly hampered by rising oxaloacetate and 2-oxoglutarate concentrations, while at the same time pyruvate kinase activity arose due to activation by fructose 1,6-diphosphate. Hence, pps overexpression should be performed to optimize the existing production strain.
Bioreactors↗
Where efficiency saves lives: a linear programme for the optimal allocation of health care resources in developing countries.
Morbidity and mortality are directly influenced by the available health care budget. In addition, the optimal allocation of this scarce resource to the different strata of the health care system depends on the health care priorities. This paper presents a linear programming model in order to analyse the impact of changes of the health care budget and the goal system of the health care system on the optimal allocation to preventive and curative medicine. The model demonstrates that the current resource allocation in developing countries is inefficient. This calls for a new emphasis on preventive medicine and primary care in the political processes in developing countries.
Adolescent↗