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PubMed1988

Matching between feline left ventricle and arterial load: optimal external power or efficiency.

We tested the hypothesis that the feline left ventricle normally works at optimal external power as opposed to optimal efficiency by (re)analyzing data from five isolated, blood-perfused cat hearts and 39 open-thorax cats. In the isolated hearts, we measured pump function, external steady power, myocardial oxygen consumption, and efficiency. Optimal external power and optimal efficiency were found at different left ventricular outputs (6.94 +/- 0.33 and 8.35 +/- 0.37 ml/s, respectively; P less than 0.001). In the in situ cat hearts the working point was found at an output of 4.72 +/- 0.32 ml/s, whereas optimal external power was found at 4.84 +/- 0.26 ml/s. These values were not significantly different. Assuming that the point of optimal efficiency was located at the same fraction of the maximal unloaded left ventricular output (Fmax) as in the isolated hearts, i.e., 0.7, we found the point of optimal efficiency for the in situ heart at a flow of 5.83 +/- 0.32 ml/s, which was significantly different (P less than 0.001) from the flow in the working point. Our data therefore indicate that the left ventricle in the open-thorax cat is matched to the arterial load such that its external power output rather than efficiency is optimized.

Algorithms↗

PubMedDate not supplied

Evaluation of nonlinear optimization for scheduling of follow-up cystoscopies to detect recurrent bladder cancer. The Bladder Cancer follow-up Group.

Standard recommendations for patients who have had superficial bladder cancer are inspection by cystoscopy quarterly for a year or two after tumor removal, then half-yearly and yearly. The authors assessed the potential for improvement in scheduling cystoscopies according to probabilistic optimization techniques. Eight hypothetical practices were created, based on retrospective analysis of 918 bladder-cancer-patient charts. Standard and alternative recommendations for the interval to next cystoscopy were compared. The alternatives were derived from patient-specific predictions of future tumor risks (based on the patient's prior recurrence rate and tumor stage and grade) and a nonlinear optimization approach to allocation of the same number of cystoscopies as were available for standard follow-up. The optimization proposed longer intervals between visits for low-risk patients and shorter intervals for high-risk patients. Overall, optimization reduced expected tumor detection delays by 30%, from 12.6 to 8.7 weeks. When optimization intervals were shorter than standard, cancer was found more often at subsequent cystoscopies (34% vs 27%, p less than 0.05), suggesting that the optimization was a better predictor of cancer recurrence. If reduction in tumor-detection delay is the goal of follow-up for recurrent cancers, then urologists can improve monitoring by using probabilistic optimization methods for scheduling cystoscopies. Further understanding of the accuracy of predictive models for bladder-cancer recurrence rates is desirable. Subsequently, the optimization method developed here may be tested prospectively.

Aftercare↗

PubMed1975

Application of modified Rosenbrock's method for optimization of nutrient media used in microorganism culturing.

The Rosenbrock's procedure has been modified for optimization of nutrient medium composition and has been found to be less tedious than the Box-Wilson method, especially for larger numbers of optimized parameters. Its merits are particularly obvious with multiparameter optimization where the gradient method, so far the only one employed in microbiology from a variety of optimization methods (e.g., refs, 9 and 10), becomes impractical because of the excessive number of experiments required. The method suggested is also more stable during optimization than the gradient methods which are very sensitive to the selection of steps in the direction of the gradient and may thus easily shoot out of the optimized region. It is also anticipated that other direct search methods, particularly simplex design, may be easily adapted for optimization of medium composition. It is obvious that direct search methods may find an application in process improvement in antibiotic and related industries.

Culture Media↗

PubMed1992

Time optimality in the control of human movements.

In a simulation study the control of maximally fast goal directed movements has been analyzed. For a simple linear model it is shown that the presence of a third input block reduces the movement duration. The time optimal size of the third block depends on the ratio of a neuromuscular time constant (first-order lag) and movement time. As a second step a non-linear muscle model was simulated. By an optimization of input parameters it was found that the time optimal input, as expected, switches between maximal agonist and maximal antagonist activation. As for the linear model, a third phase was required for an optimal movement. It was found that the third phase serves to compensate the slowly decaying antagonist force. Also an input similar to experimentally found activation patterns was simulated. This input contains a silent period between the first two bursts and the second and the third burst have submaximal amplitudes. This input led to a near time optimal movement with a duration 9% larger than the minimal duration but with largely reduced muscle forces. This suggests that a criterion is minimized which also takes into account the effort spent. Including gravity in the model indicates optimality of a silent period between the third phase and a final agonist activity to resist gravity. When assuming different dynamics for agonist and antagonist, the optimal switch times for agonist and antagonist no longer coincide, also after the three block pattern some extra activity is required to obtain a cancellation of the slowly decaying force in agonist and antagonist.

Biological Clocks↗

PubMed1990

DESIGN: computerized optimization of experimental design for estimating Kd and Bmax in ligand binding experiments. II. Simultaneous analysis of homologous and heterologous competition curves and analysis blocking and of "multiligand" dose-response surfaces.

We have developed a computer program, DESIGN, for optimization of ligand binding experiments to minimize the "average" uncertainty in all unknown parameters. An earlier report [G. E. Rovati, D. Rodbard, and P. J. Munson (1988) Anal. Biochem. 174, 636-649] described the application of this program to experiments involving a single homologous or heterologous dose-response curve. We now present several advanced features of the program DESIGN, including simultaneous optimization of two or more binding competition curves optimization of a "multiligand" experiment. Multiligand designs are those which use combinations of two (or more) ligands in each reaction tube. Such designs are an important and natural extension of the popular method of "blocking experiments" where an additional ligand is used to suppress one or more classes of sites. Extending the idea of a dose-response curve, the most general multiligand design would result in a "dose-response surface". One can now optimize the design not only for a single binding curve, but also for families of curves and for binding surfaces. The examples presented in this report further demonstrate the power and utility of the program DESIGN and the nature of D-optimal designs in the context of more complex binding experiments. We illustrate D-optimal designs involving one radioligand and two unlabeled ligands; we consider one example of homogeneous and several examples of heterogeneous binding sites. Further, to demonstrate the virtues of the dose-response surface experiment, we have compared the optimal surface design to the equivalent design restricted to traditional dose-response curves. The use of DESIGN in conjunction with multiligand experiments can improve the efficiency of estimation of the binding parameters, potentially resulting in reduction of the number of observations needed to obtain a desired degree of precision in representative cases.

Binding Sites↗

PubMed1987

A dynamic optimization technique for predicting muscle forces in the swing phase of gait.

The muscle force sharing problem was solved for the swing phase of gait using a dynamic optimization algorithm. For comparison purposes the problem was also solved using a typical static optimization algorithm. The objective function for the dynamic optimization algorithm was a combination of the tracking error and the metabolic energy consumption. The latter quantity was taken to be the sum of the total work done by the muscles and the enthalpy change during the contraction. The objective function for the static optimization problem was the sum of the cubes of the muscle stresses. To solve the problem using the static approach, the inverse dynamics problem was first solved in order to determine the resultant joint torques required to generate the given hip, knee and ankle trajectories. To this effect the angular velocities and accelerations were obtained by numerical differentiation using a low-pass digital filter. The dynamic optimization problem was solved using the Fletcher-Reeves conjugate gradient algorithm, and the static optimization problem was solved using the Gradient-restoration algorithm. The results show influence of internal muscle dynamics on muscle control histories vis a vis muscle forces. They also illustrate the strong sensitivity of the results to the differentiation procedure used in the static optimization approach.

Algorithms↗

PubMed1992

Optimization of 3D radiation therapy with both physical and biological end points and constraints.

A new optimization model is described and its clinical usefulness is demonstrated. The optimization technique was developed to allow computer optimization of 3-dimensional radiation therapy plans with biological models of tumor and normal tissue response to radiation as well as with scores based on physical dose. The emphasis was placed on the optimization model, which should describe, as closely as possible, the goal of the radiation treatment, which is eradication of the tumor while sparing normal tissues. Since the statement of the goals may vary from case to case, a technique that allows a variety of objective functions and types of constraints was developed. The optimization algorithm is capable of handling nonlinear and even discrete score (objective) functions and constraints and effectively explores the vast space of feasible solutions in a relatively short time (minutes of MicroVax 3200 CPU time). An example of computer optimization of radiation therapy of a chordoma of the sphenoid bone using x-ray and proton beams is shown and compared with the best plans achieved by an experienced planner. Directions for future development of the algorithm, allowing optimization of beam orientation, are presented.

Chordoma↗

PubMed2025

Optimizing participant and community engagement in cancer genomic sequencing research.

PURPOSE: We describe strategies implemented across research centers of the Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network to optimize engagement of participants and communities in cancer genomics research. We also present consensus definitions of engagement and engagement optimization, informed by our shared experiences in the Network. METHODS: Key informant interviews and a document review identified engagement and optimization strategies across PE-CGS research centers. Findings were synthesized using qualitative content analysis. Consensus on definitions of engagement and optimization were developed through iterative review by PE-CGS members. RESULTS: PE-CGS research centers adopted tailored strategies based on community needs and scientific gaps. Engagement strategies included community-based efforts (eg, advisory boards and newsletters) and participant-focused approaches (eg, enhanced informed consent and decision support tools). Optimization strategies leveraged scientific methods (eg, randomized controlled trials and surveys) to evaluate engagement. Engagement was described as the sustained and meaningful interactions between researchers, participants, and communities. Optimization was described as the application of scientific methods to refine and improve engagement and research processes and outcomes. CONCLUSION: Engagement and optimization strategies have informed research planning, conduct, and dissemination across PE-CGS. These approaches and definitions provide a foundation for developing evidence-based practices to strengthen participant and community involvement in cancer genomics research.

Humans↗

PubMed1988

Epidemiology of infantile hydrocephalus in Sweden. Reduced optimality in prepartum, partum and postpartum conditions. A case-control study.

The optimality concept developed by Prechtl was adopted to investigate a population-based series of infantile hydrocephalus (IH). The results were compared with those from a control series of newborns. The case series comprised 128 IH children born at term and 50 born preterm, and the control series 269 and 176, respectively. Cases with a prenatal cause of IH, as compared with those with a perinatal cause and controls, had significantly increased risk of IH by reduced optimality in the prepartum period. Peaks in the flow of non-optimal items in the prenatal group were repeated abortions or perinatal death in previous pregnancies, maternal disorder and twin birth. The profile of reduced optimality in term IH cases of undefined cause was similar to that of term cases with a prenatal cause. All IH cases had significantly increased reduced optimality in the postpartum period compared with controls. The increase was massive in cases where IH was of perinatal cause, with peaks in items of acidosis, apnea, respiratory treatment, infection and cerebral irritation. Reduced optimality in partum conditions did not discriminate between IH of pre- and perinatal cause. Reduced optimality in the prepartum, partum and postpartum periods in IH children, as compared with those with cerebral palsy syndromes, was nearly identical to that of hemiplegic, and significantly lower than that of diplegic and dyskinetic, cerebral palsy.

Female↗

PubMed2026

Theseus: fast and optimal affine-gap sequence-to-graph alignment.

MOTIVATION: Sequence-to-graph alignment is a central problem in bioinformatics, with applications in multiple sequence alignment (MSA) and pangenome analysis, among others. However, current algorithms for optimal affine-gap alignment impose high memory and computational requirements, limiting their scalability to aligning long sequences to complex graphs. Practical solutions partially address this problem using heuristic strategies that ultimately trade off optimality for speed. RESULTS: This work presents Theseus, a novel, fast, and optimal affine-gap sequence-to-graph alignment algorithm. Theseus leverages similarities between genomic sequences to accelerate the alignment computation and reduces the overall memory requirements without compromising optimality. To that end, Theseus processes only a subset of the dynamic programming cells, using a sparse-data strategy that enables efficient sequence-to-graph alignment. Moreover, our algorithm supports optimal affine-gap alignment on arbitrary directed graphs, including those with cycles. We evaluate Theseus on two key problems: MSA and pangenome read mapping. For MSA, we compare it against SPOA, abPOA, and POASTA. Theseus is 1.6× to 17.6× faster than POASTA, and 7.3× faster, on average, than SPOA, both optimal aligners. Compared with abPOA, Theseus ensures optimality and scales to the largest problems. For pangenome read mapping, we benchmark Theseus against the alignment stage of the mapping tool vg map, along with the alignment kernels of SPOA, abPOA, and POASTA. Theseus outperforms the other methods, showing a 1.9× to 16.9× speedup on short reads. Moreover, Theseus is 1.5× to 36.3× faster than vg when aligning against synthetic cyclic graphs. AVAILABILITY AND IMPLEMENTATION: Theseus code and documentation are publicly available at https://github.com/albertjimenezbl/theseus-lib.

Algorithms↗

PubMed2026

Dispositional optimism and open-label placebo responses in hair cortisol concentrations and psychological distress-A randomized controlled trial.

Open-label placebo (OLP) treatments show beneficial effects on various health-related outcomes, but studies investigating OLP effects on physiological measures remain scarce. This randomized controlled trial examined the effect of a 4-week OLP intervention on psychological distress and hair cortisol concentrations (HCC) in 202 healthy university students preparing for mandatory oral exams and whether dispositional optimism moderates the OLP effects. Participants were randomly assigned to an OLP or control group. Psychological distress was repeatedly assessed via negative affect, test anxiety, and subjective stress. HCC was measured before and within the intervention. Treatment expectations were additionally examined in interaction with optimism. Results show that OLPs significantly reduced psychological distress and HCC compared to the controls. Optimism moderated the OLP effect on HCC, with less optimistic individuals demonstrating the strongest reduction, independent of expectation. Optimism did not moderate OLP effects in psychological distress. However, the OLP effect on psychological distress depended on the three-way interaction of group, optimism, and expectation. The results suggest that OLPs alleviate the psychophysiological impact of a real-life stressor and indicate that optimism and expectation differently shape psychological and physiological OLP responses. These findings are discussed within the framework of the interactionist perspective.

Humans↗

PubMed2026

A reinforcement learning-enhanced fuzzy multi-objective equilibrium optimization framework for multiple sequence alignment.

Multiple sequence alignment (MSA) is a fundamental task in bioinformatics, underpinning comparative genomics, structural analysis, and evolutionary inference. However, MSA remains a challenging multi-objective optimization problem due to the need to simultaneously maximize alignment accuracy, preserve conserved regions, and control gap proliferation, particularly in large and heterogeneous sequence collections. In this work, we propose MOFSACEO-MSA, a novel hybrid optimization framework for multiple sequence alignment that integrates a fuzzy multi-objective evaluation scheme with the Equilibrium Optimizer (EO) and a Soft Actor-Critic (SAC)-based adaptive control mechanism. The proposed framework formulates MSA as a dynamic multi-objective optimization problem, in which alignment quality is assessed using complementary residue-level and column-level criteria, including Sum-of-Pairs score, column conservation, entropy, and gap statistics. Fuzzy membership functions are employed to harmonize competing objectives into a unified optimization landscape, while EO provides robust global exploration. To further enhance adaptability, SAC dynamically regulates key EO parameters during the search process, enabling an effective balance between exploration and exploitation across datasets of varying size and heterogeneity. Extensive experiments werew conducted on diverse biological sequence datasets, with a primary focus on RNA benchmarks, including structured families from Rfam, large-scale repositories from RNAcentral and GenBank, and organism-specific tRNA datasets from GtRNAdb. Comparative evaluations against classical alignment tools (ClustalW, MAFFT, MUSCLE, PRANK, KAlign, and T-Coffee), metaheuristic methods (SAGA, Sequoya and EAFSA), and a reinforcement learning-based approach (RLALIGN) demonstrate that MOFSACEO-MSA consistently achieves competitive or superior Sum-of-Pairs scores while significantly reducing gap proportions and maintaining compact alignment lengths. Notably, the proposed framework exhibits improved robustness on large and highly heterogeneous datasets, where existing methods often suffer from excessive gap insertion or unstable convergence. Overall, MOFSACEO-MSA provides a flexible and extensible optimization paradigm that effectively bridges evolutionary search and reinforcement learning for high-quality multiple sequence alignment, with demonstrated effectiveness on challenging RNA alignment tasks.

Sequence Alignment↗

PubMed1987

Optimal design of vertebrate and insect sarcomeres.

This paper offers a model for the normalized length-tension relation of a muscle fiber based upon sarcomere design. Comparison with measurements published by Gordon et al. ('66) shows an accurate fit as long as the inhomogeneity of sarcomere length in a single muscle fiber is taken into account. Sequential change of filament length and the length of the cross-bridge-free zone leads the model to suggest that most vertebrate sarcomeres tested match the condition of optimal construction for the output of mechanical energy over a full sarcomere contraction movement. Joint optimization of all three morphometric parameters suggests that a slightly better (0.3%) design is theoretically possible. However, this theoretical sarcomere, optimally designed for the conversion of energy, has a low normalized contraction velocity; it provides a poorer match to the combined functional demands of high energy output and high contraction velocity than the real sarcomeres of vertebrates. The sarcomeres in fish myotomes appear to be built suboptimally for isometric contraction, but built optimally for that shortening velocity generating maximum power. During swimming, these muscles do indeed contract concentrically only. The sarcomeres of insect asynchronous flight muscles contract only slightly. They are not built optimally for maximum output of energy across the full range of contraction encountered in vertebrate sarcomeres, but are built almost optimally for the contraction range that they do in fact employ.

Animals↗

PubMed1991

Five-year survival for cisplatin-based chemotherapy versus single-agent melphalan in patients with advanced ovarian cancer and optimal debulking surgery.

The purpose of this study was to evaluate 5-year survival and 5-year progression-free survival in previously untreated patients with advanced ovarian cancer treated with single-agent melphalan in which very few patients underwent optimal debulking surgery (less than 2 cm residual) as compared with the patients treated with Cisplatin-based chemotherapy in which most patients underwent optimal debulking surgery. Significant increases in 5-year survival and 5-year progression-free survival were noted as we changed from the melphalan trial, in which only 14% underwent optimal debulking surgery, to PAC-H, in which 57% and the PAC trial in which 90%, respectively, underwent optimal debulking surgery. However, for those patients whose tumors were optimally debulked in the three trials, there were no statistically significant differences in median survival, median progression-free survival, 5-year survival, or 5-year progression-free survival in those patients treated with melphalan, PAC-H, or PAC. Without optimal debulking surgery, Cisplatin-based multiagent chemotherapy offered a small survival advantage. These results are similar to that reported by Gruppo Interregionale Cooperativo Oncologico Ginecologia, in which survival curves were identical for all the subgroups of chemotherapy regimens for those patients with residual disease less than 2 cm at the onset of chemotherapy whether they received (1) cyclophosphamide; (2) cyclophosphamide and Adriamycin; (3) cyclophosphamide, Adriamycin, and Cisplatin; (4) cyclophosphamide, Adriamycin, and hexamethylmelamine; (5) Cisplatin and cyclophosphamide; (6) low-dose Cisplatin; (7) high-dose Cisplatin; or (8) carboplatin.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed1990

Evolutionary optimization and neural network models of behavior.

One of the main challenges to the adaptionist program in general and the use of optimization models in behavioral and evolutionary ecology, in particular, is that organisms are so constrained by ontogeny and phylogeny that they may not be able to attain optimal solutions, however those are defined. This paper responds to the challenge through the comparison of optimality and neural network models for the behavior of an individual polychaete worm. The evolutionary optimization model is used to compute behaviors (movement in and out of a tube) that maximize a measure of Darwinian fitness based on individual survival and reproduction. The neural network involves motor, sensory, energetic reserve and clock neuronal groups. Ontogeny of the neural network is the change of connections of a single individual in response to its experiences in the environment. Evolution of the neural network is the natural selection of initial values of connections between groups and learning rules for changing connections. Taken together, these can be viewed as "design parameters". The best neural networks have fitnesses between 85% and 99% of the fitness of the evolutionary optimization model. More complicated models for polychaete worms are discussed. Formulation of a neural network model for host acceptance decisions by tephritid fruit flies leads to predictions about the neurobiology of the flies. The general conclusion is that neural networks appear to be sufficiently rich and plastic that even weak evolution of design parameters may be sufficient for organisms to achieve behaviors that give fitnesses close to the evolutionary optimal fitness, particularly if the behaviors are relatively simple.

Animals↗

PubMed1989

The optimism bias and traffic accident risk perception.

Research suggests that people are excessively and unrealistically optimistic when judging their driving competency and accident risk. In this study, college-age drivers compared their risk of being involved in a variety of described traffic accidents relative to their peers. They also rated each of the accidents along a number of dimensions hypothesized as being related to optimism. In addition, subjects provided global estimates of their driving safety, skill, and accident likelihood. Significant optimism was evident for both the accidents and the global ratings. Optimism increased with driving experience and marginally with age. Those with more driving experience considered human factors to be more important in accident causation; those assigning more importance to human factors also rated themselves as more skillful drivers. For the specific accidents, perceived controllability was a strong predictor of optimism. The findings for controllability are interpreted in terms of other recent data and hypothesized explanations of the optimism bias. In general, it appears that optimism arises because people persistently overestimate the degree of control that they have over events.

Accidents, Traffic↗

PubMed1984

Comparison of optimal scalar electrocardiographic, orthogonal electrocardiographic and vectorcardiographic criteria for diagnosing inferior and anterior myocardial infarction.

A scalar electrocardiogram (ECG), orthogonal ECG and vectorcardiogram (VCG) were recorded in 46 normal persons, 38 patients with inferior myocardial infarction (MI) and 22 patients with anterior MI proved at cardiac catheterization. The diagnostic information provided by the scalar ECG, orthogonal ECG and VCG was quantitatively analyzed and the optimal criteria for diagnosing inferior and anterior MI exhibited by each method were identified. The optimal scalar electrocardiographic, orthogonal electrocardiographic and vectorcardiographic criteria, respectively, are: For inferior MI: initial superior duration in lead aVF greater than 30 ms (sensitivity 63%, specificity 100%), superior/inferior amplitude ratio in lead Y greater than or equal to 0.2 (sensitivity 63%, specificity 96%), initial superior duration greater than 29 ms or initial superior distance greater than 0.4 mV in the frontal plane loop (sensitivity 68%, specificity 100%). For anterior MI: initial anterior duration in lead V2 less than 20 ms or initial anterior duration in lead V3 less than 25 ms (sensitivity 91%, specificity 100%), anterior/posterior duration ratio in lead Z less than 0.3 (sensitivity 73%, specificity 98%), initial anterior duration less than 15 ms in the transverse plane loop (sensitivity 64%, specificity 98%). There were no significant differences among the performances of the optimal scalar ECG, orthogonal ECG and the VCG for diagnosing inferior MI. However, the performance of the optimal scalar ECG was superior to that of the optimal orthogonal ECG and the optimal VCG for diagnosing anterior MI (chi-square = 5.20, p less than 0.02 and chi-square = 7.14, p greater than 0.01, respectively).

Adult↗

PubMed1978

Experimental optimization of the detection limit of one-step solid-phase radioimmunoassay.

The minimal detection limit and the conditions of maximal sensitivity of a one-step solid-phase inhibition radioimmunoassay for human immunoglobulin A have been determined by application of statistical methods of experimental optimization. The choice of the optimal combination of qualitative variables, such as the origin of the antibody and the nature of the solid phase, was made by the study of a covariable under non-optimal conditions of the quantitative variables, such as the amount of antibody. The covariable was the avidity of the antibody, which is expected to have a large influence on the sensitivity. Only the difference in avidity between two immunosorbents with cellulose or Sepharose as solid-phase material proved to be statistically significant, and further study was done with cellulose. The experimental optimization of the sensitivity as a function of five quantitative variables yielded a reduction of the detection limit by a factor 5.6 (from 23.5 to 4.2 ng IgA). The variables determining the amount of insolubilized antibody in the assay had the largest influence on the value of the detection limit. The conditions of optimal sensitivity did agree with the predictions by a physical model of radioimmunoassay. The results are discussed in relation to the assay parameters such as the amount and the avidity of the insolubilized antibody and the initial percentage of binding, and in relation with theoretical optimization of the sensitivity.

Animals↗