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PubMed1995

A variable target intensity-restrained global optimization (VARTIGO) procedure for determining three-dimensional structures of polypeptides from NOESY data: application to gramicidin-S.

A global optimization method for intensity-restrained structure refinement, based on variable target function (VTF) analysis, is illustrated using experimental data on a model peptide, gramicidin-S (GS) dissolved in DMSO. The method (referred to as VARTIGO for variable target intensity-restrained global optimization) involves minimization of a target function in which the range of NOE contacts is gradually increased in successive cycles of optimization in dihedral angle space. Several different starting conformations (including all-trans) have been tested to establish the validity of the method. Not all optimizations were successful, but these were readily identifiable from their large NOE R-factors. We also show that it is possible to simultaneously optimize the rotational correlation time along with the dihedral angles. The structural features of GS thus obtained from the successful optimizations are in excellent agreement with the available experimental data. A comparison is made with structures generated from an intensity-restrained single target function (STF) analysis. The results on GS suggest that VARTIGO refinement is capable of yielding better quality structures. Our work also underscores the need for a simultaneous analysis of different NOE R-factors in judging the quality of optimized structures. The NOESY data on GS in DMSO appear to provide evidence for the presence of two orientations for the ornithine side chain, in fast exchange. The NOESY spectra for this case were analyzed using a relaxation rate matrix which is a weighted average of the relaxation rate matrices for the individual conformations.

Amino Acid Sequence↗

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↗

PubMed1994

Tissue heterogeneity effects in treatment plan optimization.

PURPOSE: There is general agreement that tissue density correction factors improve the accuracy of dose calculations. However, there is disagreement over the proper heterogeneity correction algorithm and a lack of clinical experience in using them. Therefore, there has not been widespread implementation of density correction factors into clinical practice. Furthermore, the introduction of optimized conformal therapy leads to new and radically different treatment techniques outside the clinical experience of the physician. It is essential that the effects of tissue density corrections are understood so that these types of treatments can be safely delivered. METHODS AND MATERIALS: In this paper, we investigate the effect of tissue density corrections on optimized conformal type treatment planning in the thorax region. Specifically, we study the effects on treatment plans optimized without type treatment planning in the thorax region. Specifically, we study the effects on treatment plans optimized without tissue density corrections, when those corrections are applied to the resulting dose distributions. These effects are compared for two different conformal techniques. RESULTS: This study indicates that failure to include tissue density correction factors results in an increased dose of approximately 5-15%. This is consistent with published studies using conventional treatment techniques. Additionally, the high-dose region of the dose distribution expands laterally into the uninvolved lung and other normal structures. The use of dose-volume histograms to compare these distributions demonstrates that treatment plans optimized without tissue density corrections lead to an increased dose to uninvolved normal structures. This increase in dose often violates the constraints used to determine the optimal solution. CONCLUSIONS: The neglect of tissue density correction factors can result in a 5-15% increase in the delivered dose. In addition, suboptimal dose distributions are produced. To benefit from the advantages of optimized conformal therapy in the thorax, tissue density correction factors should be used.

Carcinoma↗

PubMed1994

Optimizing the time course of brachytherapy and other accelerated radiotherapeutic protocols.

PURPOSE: It is likely that early-responding tissues, such as tumors, repair sublethal damage more rapidly than do late-responding tissues. This difference can be exploited to design protocols with a significantly improved therapeutic advantage for accelerated radiotherapeutic regimens, including brachytherapy. METHODS AND MATERIALS: The time course of potential protocols is computer optimized, maximizing the therapeutic difference between tumor-control probability (TCP), and normal-tissue complication probability (NTCP). These quantities are evaluated with the linear-quadratic model, using clinically derived parameters. The optimization is performed by individually adjusting doses in different parts of the treatment, maximizing the therapeutic advantage. In the main calculations, half times for damage repair were T1/2(late) = 4 h, T1/2(early) = 0.5 h. Two component (fast/slow) repair processes were also investigated. RESULTS: Protocols determined by optimization have significantly greater therapeutic advantage than continuous low-dose rate (CLDR) protocols of the same overall dose and time. The optimized protocols are either (a) acute-dose/gap/CLDR/gap/acute-dose; or (b) a series of acute doses separated by 3-4 h. As a typical example, results are given for 60 Gy/120 h CLDR brachytherapy, which is assumed to give NTCP = 0.2 and TCP = 0.8. Under our assumptions, optimized regimes, with the same overall time and dose, produce an NTCP of approximately 0.11 and TCP of approximately 0.83, a significant therapeutic gain over CLDR. CONCLUSION: Difference in repair rates between early- and late-responding tissues can be exploited to produce clinically practical protocols that are significantly superior to current regimens. Such optimized protocols produce slightly better tumor control than CLDR with the same overall dose and time, significantly less late damage, and similar early normal-tissue sequellae. Temporal optimization, thus, promises to be a powerful tool in designing better treatment protocols.

Animals↗

PubMed1995

Treatment planning optimization for multiple arcs stereotactic radiosurgery using a linear accelerator.

PURPOSE: Multiarc stereotactic radiosurgery is a technique used to irradiate an intracranial tumor with minimal damage to the surrounding normal tissue. The purpose of this paper is to present a method for and the results from optimizing three dimensional (3D) treatment dose for multiarc stereotactic radiosurgery. METHODS AND MATERIALS: The normal procedure for a physician-physicist team designing a treatment plan for multiarc stereotactic radiosurgery is the trial-and-error approach of changing the collimator size and the isocenter of radiation by viewing the isodose curves on a two dimensional (2D) computed tomography (CT) or magnetic resonance imaging (MRI) image plane. Not only is this time consuming, but the resulting treatment plan is not optimal in most, if not all, cases. One reason for such nonconformal isodose curves is that the same collimator size is used for all arcs. However, it is very difficult to determine manually the different collimator sizes for different arcs. A derivative free optimization method is used to optimize the collimator size for each arc, as well as the 3D coordinates of the isocenter(s). RESULTS: One spherical and two ellipsoidal artificial tumors, and one actual tumor, were used to show the utilities of the optimization process. The 90% isodose curves resulting from optimization conform very well with the tumor; whereas the 90% isodose curves from the conventional method either do not envelop the entire tumor when the collimator size is too small, or a large volume of normal tissue is also irradiated by the 90% dose when the next larger collimator size is used. CONCLUSIONS: When the collimator size for each arc and the location of the isocenters(s) are optimized in a multiarc stereotactic surgery treatment plan, the 90% isodose curve conforms to the tumor much better than when the same collimator size is used for all arcs.

Algorithms↗

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↗

PubMed1994

Optimal radiographic magnification for portal imaging.

Two approaches to estimate the optimal radiographic magnification for a TV camera-based portal imaging system and portal films have been used. The first approach optimizes signal transfer while the second optimizes signal-to-noise ratio (SNR) transfer. In order to perform these optimization calculations, the physical characteristics of the imaging system (modulation transfer function and noise power spectrum) as well as the sizes of the radiation sources of our medical linear accelerators have been measured. Using these data, the optimal magnification considering signal transfer alone (M signal) has been calculated to range between 2.0 and 2.3 for the TV camera-based imaging system and is about 1.0 for portal films. Conversely, the optimal magnification considering SNR transfer (MSNR) has been calculated to range between 1.5 and 1.7 for the TV camera-based imaging system and is about 1.0 for portal films. The results suggest that most portal imaging systems are operated close to their optimal radiographic magnification.

Humans↗

PubMed1995

The moderating effect of optimism on the relation between hassles and somatic complaints.

The relations between hassles, dispositional optimism, and prospective reports of physical symptoms were examined in a group of 90 Hong Kong undergraduates. Given that most hassle scales are confounded by physical and psychological symptomatology, a decontaminated scale specifically tailored to the experiences of college students was used. Multiple regression analyses indicated that hassle scores and the interaction of hassles and optimism uniquely and reliably predicted symptom reporting. Optimism, however, did not reliably predict symptom reports when effects of hassles and the interaction of hassles and optimism were controlled. Inspection of the interaction showed that optimism predicted symptom scores only at high levels of hassles. The underlying mechanisms were discussed in the light of previous data linking optimism and adaptational outcomes via coping. It was suggested that further pursuit of the connection between optimism and coping in relation to measures of life stress would be worthwhile.

Adaptation, Psychological↗

PubMed1993

Choice of optimality criteria for the design of crossbreeding experiments.

Crossbreeding experiments carried out over several generations and analyzed using genetic models including additive, dominance, and epistatic effects deserve careful planning. Designs should be optimized with respect to the specific aim of the experiment. Using an experiment with guinea pigs as an example, designs were optimized for three different criteria: D-optimality, where the determinant of the variance-covariance matrix of all parameters in the genetic model is minimized, DS-optimality, where a specific subset of parameters is of special interest and the respective determinant is minimized, and DA-optimality, where a linear function or a set of linear functions of the parameters in the model is of interest. The linear function used in this particular case relates to the comparison of a composite line of two breeds and a rotational crossbreeding system at equilibrium. The designs produced by a sequential design algorithm depend very much on the optimality criterion. Designs that are optimal for the comparison of composites and rotations are very inefficient for the estimation of the whole set of parameters in the model or the specific subset of special interest in this case. Assuming that the underlying genetic model is correct, composites and rotations at equilibrium may be compared extremely efficiently using only crosses arising in the first three generations of crossbreeding.

Algorithms↗

PubMedDate not supplied

Optimism and coping with a breast cancer symptom.

This study was conducted to assess whether optimism was associated with less delay and anxiety in seeking care for breast cancer symptoms, expectations about such care seeking, and the likelihood of having breast cancer. The influence of optimism on delay and anxiety through expectations about care seeking or likelihood of breast cancer was also examined. Participants (N = 135) with breast cancer symptoms and no history of cancer were interviewed at a surgery clinic. Optimism was associated with less delay and anxiety in care seeking and with expectations of desirable outcomes of care seeking. After controlling for expectations about care seeking, the relationship of optimism and anxiety became nonsignificant. Adjusting for differences in occupational status, the relationship of optimism and delay was nonsignificant. Thus, optimism may influence anxiety in care seeking for breast cancer symptoms through situation-specific expectations. The influence of optimism on delay may be confounded with socioeconomic factors.

Adaptation, Psychological↗

PubMed1995

Serum thyrotropin in primary hypothyroidism. A possible predictor of optimal daily levothyroxine dose in primary hypothyroidism.

BACKGROUND: Pretreatment thyrotropin levels may be a reliable predictor of the optimal daily dose of levothyroxine sodium in patients with primary hypothyroidism. However, the older method of serum thyrotropin determination, with the reference range of less than 1 to 8 mU/L, has given way to a newer, supersensitive thyrotropin assay, with a reference range of 0.5 to 5.0 mU/L. Thus, at present, the previously established relationship between the levothyroxine dose and the pretreatment serum thyrotropin concentration may not be reliable in predicting the optimal daily dose of levothyroxine. METHODS: We reassessed the relationship between the optimal daily levothyroxine dose and the pretreatment serum thyrotropin concentration as determined by the newer assay in 192 consecutive patients with primary hypothyroidism referred to an endocrinology clinic over a period of 4 years. RESULTS: The optimal daily dose of levothyroxine sodium ranged from 25 to 225 micrograms, with most patients (65%) requiring 100 to 150 micrograms/d and a median dose of 125 micrograms. Multiple regression analysis documented a significant curvilinear correlation between the mean pretreatment serum thryrotropin concentration and the optimal daily levothyroxine dose for individual groups divided according to available tablet strengths (r = .994, P < .001). A simple linear regression was also significant (r = .92, P < .001), although with an intercept much higher than the minimum levothyroxine sodium dose of 25 micrograms/d. However, the relationships markedly improved when the linear regressions were determined separately for two further subgroups at the median daily dose of 125 micrograms, providing equations to predict even the smallest optimal daily dose of levothyroxine. CONCLUSION: Pretreatment thyrotropin levels determined by new assays may also provide a useful guideline in determining the optimal daily maintenance dose of levothyroxine in patients with primary hypothyroidism.

Adult↗

PubMed1993

Concepts of optimality and efficiency in biology and medicine from the viewpoint of philosophy of science.

If everything happens strictly according to the natural laws, which meet extremum principles, in what way can the possibility for life be characterised, so that the optimization processes of evolution can take place? Is it legitimate to "enlarge" the natural laws by certain laws of conservation? The question then arises of which are the new conservation quantities that are introduced by life itself? The concept of genidentity, which must not be confused with the biological concept of genes, is introduced and used to characterise the interface between animate and inanimate systems by the principle of conservation of genidentity. It thus becomes clear that animate systems can differ in the way and in how reliably they achieve their goal of self-preservation. The abundance of possibilities to be or not to be able to reach this goal offers the necessary scope in which the notion of a postulated assumed optimization in the theory of evolution is conceivable. The conservation principle of genidentical systems creates the possibility of evolutionary optimization by ranking these systems. An optimal lifespan of an individual genidentical system refers to the conservation principle of genidentical systems on a second supra-individual level (species). The optimization of the growth of a species needs the conservation of a genidentical system on a third level (symbiotic systems). The ranking of genidentical systems onto ever higher levels--so that the higher conservation principles always impose restrictions on the ones below--would come to an end when the minimization of raw materials and energy consumption limits all possible and available resources. Since the spectrum extending between opposite goals lies within the range of possible means of optimization, supposedly evolutionary goals of optimization are always attributed to nature by the observer.

Biological Evolution↗

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↗