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Multicriteria optimization of biochemical systems by linear programming: application to production of ethanol by Saccharomyces cerevisiae.

In this study we present a method for simultaneous optimization of several metabolic responses of biochemical pathways. The method, based on the use of the power law formalism to obtain a linear system in logarithmic coordinates, is applied to ethanol production by Saccharomyces cerevisiae. Starting from an experimentally based kinetic model, we translated it to its power law equivalent. With this new model representation, we then applied the multiobjective optimization method. Our intent was to maximize ethanol production and minimize each of the internal metabolite concentrations. To ensure cell viability, all optimizations were carried out under imposed constraints. The different solutions obtained, which correspond to alternative patterns of enzyme overexpression, were implemented in the original model. We discovered few discrepancies between the S-system-optimized steady state and the corresponding optimized state in the original kinetic model, thus demonstrating the suitability of the S-system representation as the basis for the optimization procedure. In all optimized solutions, the ATP level reached its maximum and any increase in its activity positively affected the optimization process. This work illustrates that in any optimization study no single criteria is of general application being the multiobjective and constrained task the proper way to address it. It is concluded that the proposed multiobjective method can serve to carry out, in a single study, the general pattern of behavior of a given metabolic system with regard to its control and optimization.

Algorithms↗

Usefulness of atrioventricular delay optimization using Doppler assessment of mitral inflow in patients undergoing cardiac resynchronization therapy.

This study evaluated the utility of atrioventricular (AV) optimization using Doppler echocardiography in patients who undergo cardiac resynchronization therapy (CRT). AV optimization in patients who undergo CRT is performed inconsistently, with few data supporting its utility. Data were collected from 215 patients in New York Heart Association class III or IV heart failure (66% ischemic) who underwent AV optimization <30 days after implantation from 1999 to 2003. All patients arrived with AV delay programmed at the time of their CRT procedures (100 to 120 ms). AV delay was optimized using Doppler mitral inflow data to target stage I diastolic filling. Baseline clinical characteristics, AV delay, and diastolic functional stage were recorded. The mean follow-up period was 23 months. Five hundred patients underwent CRT, 215 of whom underwent AV optimization <30 days after implantation. Baseline mean age was 66 +/- 12 years, left ventricular (LV) ejection fraction 19 +/- 8%, LV end-diastolic dimension 6.5 +/- 1 cm, LV end-systolic dimension 5.5 +/- 1 cm, QRS duration 166 +/- 27 ms, and time to AV optimization 2.5 +/- 4 days. Baseline and final AV delay means were 120 +/- 25 and 135 +/- 40 ms, respectively (p = 0.0001). In 40% of patients (86 of 215), final AV delay settings were >140 ms. Left atrial diameter and AV block predicted patients in whom AV delay settings >140 ms were optimal. There was no difference in mortality in patients with final AV delays of >140 ms. In conclusion, AV optimization in patients who underwent CRT resulted in final AV delay settings of >140 ms in 40% of patients. AV delay optimization based on Doppler echocardiographic determination of optimal diastolic filling is useful and safe in patients who undergo CRT.

Aged↗

Optimization of solid-phase extraction using artificial neural networks in combination with experimental design for determination of resveratrol by capillary zone electrophoresis in wines.

Solid-phase extraction (SPE) is often used for preconcentration of analytes from biological samples. Such an analytical step requires optimization for obtaining reliable results. Optimization in analytical chemistry is traditionally still often done with relaxation method, when an optimal value of a single variable is searched for (single variable approach (SVA)). However, if the optimized procedure is complex, there is a danger not to find the real optimum by SVA. Therefore, more advanced optimization approaches should be applied-multivariable approach (MVA). Applying MVA optimization and finding the real optimum, better experimental conditions are obtained and thus, time, chemicals and analytical procedure cost can be served. Nowadays, using artificial neural networks (ANN's) in combination with MVA is rapidly expanding. In this work, the optimization of SPE using relaxation method (SVA) and optimization by ANN's in combination with experimental design (MVA) are compared and latter approach is practically illustrated. Advantages of MVA over SVA for optimization are discussed. The prediction of the optimal SPE conditions for determination cis- and trans-resveratrol in Australian wines by capillary zone electrophoresis is described and the improvement of efficiency of SPE using MVA is confirmed.

Chemical Fractionation↗

A comparison between derivation optimization and Cz'-FPz for posterior tibial P37 somatosensory evoked potential intraoperative monitoring.

OBJECTIVE: To compare P37 derivation optimization to Cz'-FPz. METHODS: After induction in 120 patients, monitoring derivations optimized by mapping FPz, Cz, Cz', Pz, C4', C2', C1' and C3'-mastoid to determine the P37 and N37 maximums for use as inputs 1 and 2 were compared to Cz'-FPz. This was repeated later in 35 surgeries. RESULTS: Eleven optimal derivations occurred and usually differed between sides. Input 1 was Cz', Pz, Cz, iCi', or Ci' and input 2 was Cc', FPz, Ci' or Pz. Even the most frequent Cz'-Cc' derivation was optimal for both sides of an individual in only 17% and this was true for Cz'-FPz in only 4%. Optimization produced higher amplitudes than Cz'-FPz (P<0.001). The ratio was [squareroot of 2] : 1 in 61% of patients and > or =2:1 in 28%, approximately halving or quartering averaging times. Optimization assessed decussation, disclosing non-decussation in one patient while Cz'-FPz did not. Alterations of P37 topography that reduced initially optimal derivation amplitude and made a different derivation optimal were demonstrated by repeat optimization in 13 of 35 patients, preventing misinterpretation in one. While also affected, Cz'-FPz neither detected nor adjusted for potentially misleading topographic changes. CONCLUSIONS: Higher amplitudes, decussation assessment and topographic adjustment make P37 derivation optimization superior to Cz'-FPz for monitoring this highly variable potential.

Adolescent↗

Development of methods for beam angle optimization for IMRT using an accelerated exhaustive search strategy.

PURPOSE: The purpose of this article is to explore the use of the accelerated exhaustive search strategy for developing and validating methods for optimizing beam orientations for intensity-modulated radiation therapy (IMRT). Combining beam-angle optimization (BAO) with intensity distribution optimization is expected to improve the quality of IMRT treatment plans. However, BAO is one of the most difficult problems to solve adequately because of the huge hyperspace of possible beam configurations (e.g., selecting 7 of 36 uniformly spaced coplanar beams would require the intercomparison of 8,347,680 IMRT plans). METHODS AND MATERIALS: An "influence vector" (IV) approximation technique for high-speed estimation of IMRT dose distributions was used in combination with a fast gradient search algorithm (Newton's method) for IMRT optimization. In the IV approximation, it is assumed that the change in intensity of a ray (or bixel) proportionately changes dose along the ray. Evidence is presented that the IV approximation is valid for BAO. The scatter contribution at points away from the ray is accounted for fully in IMRT optimization after the optimum beam orientation has been determined. IVs for all candidate beam angles are generated before the start of optimization. For all subsets of beams selected from a given pool of beams (e.g., 5 of 24 uniformly spaced beams), the distribution of planning scores for the best and the worst plans, optimum angle distributions, dose distributions, and dose-volume histograms (DVH) were analyzed for one prostate and two lung cancer cases. The results of the exhaustive search technique were used to develop a "multiresolution" search strategy. In this approach, a smaller number of beams (e.g., three) is first used to explore the hyperspace of solutions to determine the most preferred and the least preferred directions. The results of such exploration are then used as a starting point for determining an optimum configuration comprising a larger number of beams (e.g., seven). This two-step process is considerably faster than full exhaustive search. The question to be answered was whether the two methods lead to the same or similar solutions. The results of exhaustive search and multiresolution approaches were also compared with a previously published approach that used beam's-eye-view dosimetrics (BEVD). RESULTS: The relative ranks of plans optimized by an accurate dose calculation method were highly correlated with those of the plans optimized by the fast calculation method (i.e., using the IV approximation), which suggests that an approximate dose calculation algorithm can be used effectively for ranking of plans during BAO. We found that dose distributions and DVH of many beam configurations within a specified subset from a given pool of beams (e.g., 5 of 18) may be clinically indistinguishable and acceptable. Their optimized IMRT scores fall in a narrow range, although beam configurations and dose distributions may be different. We used the frequency distributions as a function of beam angles for the best 100 and the worst 100 plans to determine the most and the least preferred beam angles. We found that the most and the least preferred angle distributions for 3 of 18 configurations were very similar to those for 5, 6, 7, or 8 of 18 or 24 configurations, but the size of the search space was much smaller for the 3 of 18 case. Using fewer than three beams was discovered to be inadequate. This information was used to select the most preferred angles and eliminate the least preferred ones before searching for the optimum angles for the remaining beams. For the cases we studies, the multiresolution strategy produced very similar results to the full exhaustive search. Based on the observation that the worst plans had at least one parallel-opposed pair of beams and virtually all of the best plans had none, we were able to further reduce the size of the search space dramatically by using a pool of only nonparallel-opposed equispaced beams (i.e., 7 of 19 instead of 7 of 36). Another observation was that the probability of finding an optimum configuration in a smaller beam pool is substantially lower than in a larger pool (e.g., 5 of 18 vs. 5 of 24). The implication of this BAO is not very important when a large number of beams (nine or more) is used and vice versa. Our results showed that the plans with fewer but optimally placed beams could be as good as or better than plans using a larger number of unoptimized or uniformly placed beams. CONCLUSION: Exhaustive search with fast IMRT algorithms provides a novel and realistic approach to study the characteristics of IMRT dose distributions as a function of beam angles and to design practical BAO strategies for IMRT planning.

Algorithms↗

Interactively exploring optimized treatment plans.

PURPOSE: A new paradigm for treatment planning is proposed that embodies the concept of interactively exploring the space of optimized plans. In this approach, treatment planning ignores the details of individual plans and instead presents the physician with clinical summaries of sets of solutions to well-defined clinical goals in which every solution has been optimized in advance by computer algorithms. METHODS AND MATERIALS: Before interactive planning, sets of optimized plans are created for a variety of treatment delivery options and critical structure dose-volume constraints. Then, the dose-volume parameters of the optimized plans are fit to linear functions. These linear functions are used to show in real time how the target dose-volume histogram (DVH) changes as the DVHs of the critical structures are changed interactively. A bitmap of the space of optimized plans is used to restrict the feasible solutions. The physician selects the critical structure dose-volume constraints that give the desired dose to the planning target volume (PTV) and then those constraints are used to create the corresponding optimized plan. RESULTS: The method is demonstrated using prototype software, Treatment Plan Explorer (TPEx), and a clinical example of a patient with a tumor in the right lung. For this example, the delivery options included 4 open beams, 12 open beams, 4 wedged beams, and 12 wedged beams. Beam directions and relative weights were optimized for a range of critical structure dose-volume constraints for the lungs and esophagus. Cord dose was restricted to 45 Gy. Using the interactive interface, the physician explored how the tumor dose changed as critical structure dose-volume constraints were tightened or relaxed and selected the best compromise for each delivery option. The corresponding treatment plans were calculated and compared with the linear parameterization presented to the physician in TPEx. The linear fits were best for the maximum PTV dose and worst for the minimum PTV dose. Based on the root-mean-square error between the fit values and their corresponding data values, the linear fit appears to be adequate, although higher order polynomials could give better results. Some of the variance in fit is due to the stochastic nature of the simulated annealing optimization algorithm, which does not reproduce the exact same results in repetitions of the same calculation. Using a directed search algorithm for plan optimization should produce better parameter fits and, therefore, better predictions of plan characteristics by TPEx. CONCLUSIONS: Using TPEx, the physician can easily select the optimum plan for a patient, with no imposed arbitrary definition of the "best" plan. More importantly, the physician can readily see what can be achieved for the patient with a given delivery technique. There is no more uncertainty about whether or not a better plan exists. By comparing the "best" plans for different delivery options (e.g., three-dimensional conformal radiotherapy versus intensity-modulated radiation therapy), the physician can gauge the clinical benefits of greater technical complexity. However, before the TPEx process can be clinical useful, faster computers and/or algorithms are needed and more studies are needed to better model the spaces of optimized solutions.

Algorithms↗

Esophagus sparing with IMRT in lung tumor irradiation: an EUD-based optimization technique.

PURPOSE: The aim of this study was to evaluate (1) the use of generalized equivalent uniform dose (gEUD) to optimize dose escalation of lung tumors when the esophagus overlaps the planning target volume (PTV) and (2) the potential benefit of further dose escalation in only the part of the PTV that does not overlap the esophagus. METHODS AND MATERIALS: The treatment-planning computed tomography (CT) scans of patients with primary lung tumors located in different regions of the left and right lung were used for the optimization of beamlet intensity modulated radiation therapy (IMRT) plans. In all cases, the PTV overlapped part of the esophagus. The dose in the PTV was maximized according to 7 different primary cost functions: 2 plans that made use of mean dose (MD) (the reference plan, in which the 95% isodose surface covered the PTV and a second plan that had no constraint on the minimum isodose), 3 plans based on maximizing gEUD for the whole PTV with ever increasing assumptions for tumor aggressiveness, and 2 plans that used different gEUD values in 2 simultaneous, overlapping target volumes (the whole PTV and the PTV minus esophagus). Beam arrangements and NTCP-based costlets for the organs at risk (OARs) were kept identical to the original conformal plan for each case. Regardless of optimization method, the relative ranking of the resulting plans was evaluated in terms of the absence of cold spots within the PTV and the final gEUD computed for the whole PTV. RESULTS: Because the MD-optimized plans lacked a constraint on minimum PTV coverage, they resulted in cold spots that affected approximately 5% of the PTV volume. When optimizing over the whole PTV volume, gEUD-optimized plans resulted in higher equivalent uniform PTV doses than did the reference plan while still maintaining normal-tissue constraints. However, only under the assumption of extremely aggressive tumors could cold spots in the PTV be avoided. Generally, high-level overall results are obtained when optimization in the whole PTV is also associated with a second simultaneous optimization in the PTV minus overlapping portions of the esophagus. CONCLUSIONS: Intensity modulated radiation therapy optimizations that utilize gEUD-based cost functions for the PTV and NTCP-based constraints for the OARs result in increased doses to large portions of the PTV in cases where the PTV overlaps the esophagus, while still maintaining (and confining to the overlap region) minimum dose coverage equivalent to the homogeneous PTV optimization cases.

Carcinoma, Non-Small-Cell Lung↗

Hand span influences optimal grip span in male and female teenagers.

PURPOSE: To determine if there is an optimal grip span for determining the maximum handgrip strength in male and female teenagers, and if the optimal grip span was related to hand span. If they are related then the second aim was to derive a mathematic equation relating hand span and optimal grip span. METHODS: One hundred healthy teenage boys (15.1 +/- 1.1 y) and 106 girls (15.4 +/- 1.3 y) were evaluated (age range, 13-18 y). Each hand was randomly tested on 10 occasions using 5 different grip spans, allowing a 1-minute rest between attempts. The hand span was measured from the tip of the thumb to the tip of the small finger with the hand opened as wide as possible. RESULTS: The results showed that an optimal grip span to determine the maximum handgrip strength was identified for both genders, and the optimal grip span and hand span correlated in both genders. CONCLUSIONS: The results suggest that there is an optimal grip span to which the dynamometer should be adjusted when measuring handgrip strength in teenagers. The optimal grip span was influenced by hand span in both genders. For males the optimal grip span can be derived from the equation y = x/7.2 + 3.1 cm, and for females from the equation y = x/4 + 1.1 cm. where y is the optimal grip span and x is the hand-span. These equations may improve the reliability and accuracy of the results and may guide clinicians and researchers in selecting the optimal grip span on the hand dynamometer when measuring handgrip strength in teenagers.

Adolescent↗

Early clinical experience with anatomy-based inverse planning dose optimization for high-dose-rate boost of the prostate.

PURPOSE: To present an exhaustive dosimetric comparison between three geometric optimization methods and our inverse-planning simulated annealing (IPSA) algorithm, with two different prescriptions for high-dose-rate (HDR) boost of the prostate. The objective of this analysis was to quantify the dosimetric advantages of the IPSA algorithm compared with more standard geometric optimizations. METHODS AND MATERIALS: Between September 1999 and June 2001, 34 patients were treated to a dose of 40-44 Gy by external pelvic fields, followed by an HDR boost of 18 Gy in 3 fractions. The first 4 patients were treated with HDR using geometric optimization, and anatomy-based inverse-planning dose optimization was used for the remaining 30 patients. We retrospectively used the data from these 30 patients to create HDR dose distributions according to five different dose optimization protocols, including our IPSA algorithm. The various geometric optimization procedures differed in the way the dwell positions were activated and plan normalization was performed. Dose-volume histograms from all these plans were analyzed and multiple implant quality indexes extracted. RESULTS: The IPSA algorithm provided better clinical tumor volume prescription dose coverage than did the geometric optimizations. The average prostate volume receiving 100% of the prescribed dose (V100) was 96.3% and 94.5% for IPSA with two different prescriptions compared with 92.1%, 92.6%, and 88.8% for the three geometric optimization schemes. The average urethra V150 value was 0.0% and 0.7% for IPSA with two different prescriptions, and the three geometric optimization protocols generated average values of 22.9%, 33.9%, and 38.8%. The bladder and rectal dose-volume histograms were similar, although the latest version of the IPSA algorithm slightly decreases the dose to these organs at risk because of organ-specific dose constraints included in the objective function. CONCLUSION: We found that planning an HDR prostate boost could be performed in a fast, secure, and effective manner with the IPSA algorithm. We demonstrated that our inverse-planning algorithm produces superior HDR plans than more conventional geometric optimizations for adenocarcinoma of the prostate. The organs at risk protection included in the objective function is a major feature of the algorithm and should allow us to escalate the HDR dose to the prostate without increasing undesirable side effects.

Adenocarcinoma↗

Multi-objective optimization in radiotherapy: applications to stereotactic radiosurgery and prostate brachytherapy.

Treatment planning for radiation therapy is a multi-objective optimization process. Here we present a machine intelligent scheme for treatment planning based on multi-objective decision analysis (MODA) and genetic algorithm (GA) optimization. Multi-objective ranking strategies are represented in the L(p) metric under the displaced ideal model. Goal setting, protocol satisficing and fuzzy ranking of objective importance can be incorporated into the decision scheme to assimilate clinical decision making. For distance measures in the L(p) metric, a dynamic gauge function is defined based on the state energy of the decision system, which is assumed to undergo thermodynamic cooling with iteration time. The MODA scheme interacts with a robust GA engine, which adaptively evolves in the multi-modal landscape that defines the treatment plan quality. A conventionally challenging case of stereotactic radiosurgery of a brain lesion was selected for GA optimization. The resulting dose distributions are compared to human-developed plans, which are commonly regarded as clinically relevant and empirically optimal. The GA-optimized plans achieve substantially better sparing of critical normal neuroanatomy surrounding the brain lesion while respecting the preset constraints on tumor dose uniformity. In addition, machine optimization tends to produce novel treatment strategies which complements expert knowledge. The run time for producing an optimal plan is considerably shorter than the typical planning time for human experts, thus GA can also be used to aid the human treatment planning process. In prostate brachytherapy, MODA-GA was specifically applied to non-ideal conditions in which typical surgical uncertainties in seed implant positioning occur, where noisy objectives were introduced into the optimization scheme. The noisy system is found to be manageable by MODA-GA at uncertainty levels corresponding to reasonably proficient surgery teams. In contrast, noisy objectives would be very difficult to explore by human expert planners. Potential use of noisy optimization with time series analysis is being explored for error-corrective computer guidance in the operating room for prostate seed implantation. In conclusion, the combination of MODA and GA optimization offers both a solution to practical treatment planning tasks and the potential for real time applications in radiotherapy.

Algorithms↗

The future of optimism.

Recent theoretical discussions of optimism as an inherent aspect of human nature converge with empirical investigations of optimism as an individual difference to show that optimism can be a highly beneficial psychological characteristic linked to good mood, perseverance, achievement, and physical health. Questions remain about optimism as a research topic and more generally as a societal value. Is the meaning of optimism richer than its current conceptualization in cognitive terms? Are optimism and pessimism mutually exclusive? What is the relationship between optimism and reality, and what are the costs of optimistic beliefs that prove to be wrong? How can optimism be cultivated? How does optimism play itself out across different cultures? Optimism promises to be one of the important topics of interest to positive social science, as long as it is approached in an even-handed way.

Attitude↗

CA125 levels are a weak predictor of optimal cytoreductive surgery in patients with advanced epithelial ovarian cancer.

The utility of preoperative CA125 to predict optimal primary tumor cytoreduction in patients with advanced (stages IIIC and IV) epithelial ovarian cancer is controversial. In this paper, we retrospectively review patients with stage IIIC and IV epithelial ovarian cancer who underwent primary cytoreductive surgery from 1989 to 2001. Ninety-nine patients were identified and included in the analysis. All patients had preoperative CA125 levels measured. Operative and pathology reports were reviewed. Optimal cytoreduction was defined as largest volume of residual disease < 1 cm in maximal dimension. Mean values were compared with t-test on a log scale when needed. The optimal cut-point for discriminating between those with vs. without optimal cytoreduction was determined using the receiver operator curve (ROC) method. Optimal cytoreduction was achieved in 73% of patients. Among patients with optimal cytoreductive status the mean CA125 level was 569, while among patients with suboptimal cytoreduction the mean CA125 level was 1520 (P < 0.007). A CA125 level of 912 was identified as the optimal cut-point to distinguish the two groups. Using this CA125 level, the sensitivity of this test in predicting optimal cytoreduction was 58% and the specificity was 54%. The positive predictive value of CA125 for optimal cytoreduction was 78% and the negative predictive value was 31%. We conclude that CA125 level is a weak positive and negative predictor of optimal cytoreductive surgery in patients with advanced epithelial ovarian cancer. The CA125 level should not be used as a primary predictor of the outcome of cytoreductive surgery and should be viewed in the context of all other preoperative features.

Adult↗

A flexible optimization tool for hyperthermia treatments with RF phased array systems.

In hyperthermia treatments performed with a radio-frequency phased array, the main issue to apply the excitation amplitudes and phases of the applicators for which tumour heating is optimal, i.e. the maximal therapeutic gain without unwanted side effects. Due to the complex interaction of the radiated EM-field and the patient's tissues, it is very difficult to find these optimal excitation (amplitude and phase) parameters by intuition. Calculation of the EM-field distribution within the patient can aid in finding the optimal excitation setting. However, this remains a difficult task because of the degrees of freedom available (2n - 1, with n the number of applicators in the array) and because a large temperature elevation may occur at healthy tissue sites resulting in unwanted side effects, e.g. pain or healthy tissue damage. Therefore, determining the excitation amplitudes and phases yielding optimal tumour heating can be done effectively only by application of a computerized optimization procedure. Optimization of the temperature distribution in the patient requires detailed knowledge of the thermal tissue parameters. Techniques for determining these properties are not commonly available and the use of averaged values for parameters like the tissue perfusion is expected to introduce large errors for individual patient treatment planning. As a consequence, the SAR distribution, being proportional to the temperature increase at treatment start, is more often selected for optimization. The 'optimized' excitation amplitudes and phases are found by maximization of a certain SAR ratio. Several propositions for this SAR ratio have been reported in the literature, e.g. the ratio of the SAR at the tumour site and the SAR at sites where unwanted side effects may occur. However, the definition of these ratios does not constrain the SAR value at these tissue locations to a safe value. In this paper, a tool for the optimization of the SAR distribution including the specification of constraints is presented. The tool focuses on the definition of the average SAR as a function of the excitation amplitudes and phases in a volume of arbitrary size (e.g. the tumour volume or the whole patient volume). These functions can be applied in either customized or commercially available optimization routines and they enable the definition of constraints for the average SAR in a certain volume. The described tool is illustrated for a patient case, showing the flexibility and easy application of the tool.

Hyperthermia, Induced↗

A geometry based optimization algorithm for conformal external beam radiotherapy.

A geometric solution of the problem of optimal orientation of beams in conformal external radiotherapy is presented. The method uses geometric derived quantities which consider the intersection volume between organs at risk (OAR) and the beam shape. In comparison to previous geometric methods a true 3D volume computation is used which takes into account beam divergence, concave shapes, as well as treatment settings such as individual beam shaping by blocks or multi-leaf collimators. For standard dosimetric cost functions used by dose optimization algorithms a corresponding set of geometric objective functions is proposed. We compare the correlations between geometric and dosimetric cost functions for two clinical cases, a prostate and a head tumour case. A correlation is observed for the prostate case, whereas for the head case it is less pronounced due to the larger part of overlapping volumes between the beams which cannot be considered by the used objectives. In comparison to not-optimized beam directions the dose distribution is significantly better for the beam directions found by the optimization of a geometric multi-objective cost function. An optimal dose distribution can easily be achieved using the geometric model. This is shown by comparing for the two cases the dose-volume histograms (DVH) of manually optimized plans by experienced planners and the DVHs of the geometrically found optimal solutions. In comparison to the manually optimized plans the solutions found by the geometric method significantly reduce the average dose in the OARs and NT, while maintaining the same PTV coverage. The optimization requires only a few seconds and could be used to improve the performance of inverse planning algorithms in radiotherapy for the determination of the optimal direction of beams.

Algorithms↗

On near-optimal alignments of biological sequences.

A near-optimal alignment between a pair of sequences is an alignment whose score lies within the neighborhood of the optimal score. We present an efficient method for representing all alignments whose score is within any given delta from the optimal score. The representation is a compact graph that makes it easy to impose additional biological constraints and select one desirable alignment from the large set of alignments. We study the combinatorial nature of near-optimal alignments, and define a set of "canonical" near-optimal alignments. We then show how to enumerate near-optimal alignments efficiently in order of their score, and count their number. When applied to comparisons of two distantly related proteins, near-optimal alignments reveal that the most conserved regions among the near-optimal alignments are the highly structured regions in the proteins. We also show that by counting the number of near optimal alignments as a function of the distance from the optimal score, we can select a good set of parameters that best constraints the biologically relevant alignments.

Algorithms↗

Applicability and limitations of optimal biomass allocation models: a test of two species from fertile and infertile habitats.

BACKGROUND AND AIMS: The practical applicability of optimal biomass allocation models is not clear. Plants may have constraints in the plasticity of their root : leaf ratio that prevent them from regulating their root : leaf ratio in the optimal manner predicted by the models. The aim of this study was to examine the applicability and limitations of optimal biomass allocation models and to test the assumption that regulation of the root : leaf ratio enables maximization of the relative growth rate (RGR). METHODS: Polygonum cuspidatum from an infertile habitat and Chenopodium album from a fertile habitat were grown under a range of nitrogen availabilities. The biomass allocation, leaf nitrogen concentration (LNC), RGR, net assimilation rate (NAR), and leaf area ratio (LAR) of each species were compared with optimal values determined using an optimal biomass allocation model. KEY RESULTS: The root : leaf ratio of C. album was smaller than the optimal ratio in the low-nitrogen treatment, while it was almost optimal in the high-nitrogen treatment. In contrast, the root : leaf ratio of P. cuspidatum was close to the optimum under both high- and low-nitrogen conditions. Owing to the optimal regulation of the root : leaf ratio, C. album in the high-nitrogen treatment and P. cuspidatum in both treatments had LNC and RGR (with its two components, NAR and LAR) close to their optima. However, in the low-nitrogen treatment, the suboptimal root : leaf ratio of C. album led to a smaller LNC than the optimum, which in turn resulted in a smaller NAR than the optimum and RGR than the theoretical maximum RGR. CONCLUSIONS: The applicability of optimal biomass allocation models is fairly high, although constraints in the plasticity of biomass allocation could prevent optimal regulation of the root : leaf ratio in some species. The assumption that regulation of the root : leaf ratio enables maximization of RGR was supported.

Biomass↗

Coping and optimism in relation to dental health behaviour--a study among Finnish young adults.

Our aim in this paper was to investigate active coping in relation to optimism, dental health behavior and self-reported dental health among 31-yr-old men and women born in Northern Finland in 1966. Connecting coping strategies and optimism with health behavior is an unexplored approach in dentistry, even though both coping strategies and optimism are known to be associated with many health outcomes. The data were based on a postal questionnaire, which was sent to the Northern Finland 1966 Birth Cohort at age 31 yr (n = 11 541). The number of replies was 8690, with a 75.3% response rate. Active coping was measured using the Ways of Coping Checklist and optimism using a revised Life Orientation Test. Prevalence proportion ratios were estimated by applying a log-binomial regression models. The results showed a correlation between active coping and optimism. Both active coping and optimism were related to different dental health behaviors. The effect of active coping on dental health behavior disappeared by adjusting for optimism, education and gender. The results support the previous findings that active coping acts as a mediator between optimism and health. Optimism was also related to self-reported dental health, which supports the comprehensiveness of optimism as a determinant for health.

Adaptation, Psychological↗

Sub-optimal proton pump inhibitor dosing is prevalent in patients with poorly controlled gastro-oesophageal reflux disease.

BACKGROUND: Proton pump inhibitors are the most potent drug treatment for gastro-oesophageal reflux disease. Pre-meal dosing maximizes efficacy while sub-optimal dose timing may limit efficacy. AIM: To determine the prevalence of sub-optimal proton pump inhibitor dosing in a community-based gastro-oesophageal reflux disease population. MATERIALS AND METHODS: One hundred patients on proton pump inhibitors referred for persistent gastro-oesophageal reflux disease symptoms were questioned about their proton pump inhibitor dosing habits and classified as optimal or sub-optimal dosers. Optimal dosers took proton pump inhibitors with or up to 60 min before meals. Sub-optimal dosers took proton pump inhibitors >60 min before meals, after meals, as needed, or at bedtime. RESULTS: Forty-six percent dosed optimally. Fifty-four percent dosed sub-optimally with 21 of 54 (39%) dosing >60 min before meals, 16 (30%) after meals, 15 (28%) at bedtime and two (4%) as needed. Only 6% of the subjects on once-daily proton pump inhibitor regimens and 33% of subjects taking proton pump inhibitors two- to three times daily dosed in a manner that maximized acid suppression (15-30 min before a meal). CONCLUSIONS: In this study, 54% of patients dosed proton pump inhibitors sub-optimally and only 12% dosed in a manner that maximized acid suppression. As sub-optimal proton pump inhibitor dose timing can limit efficacy, patients with refractory symptoms should be asked about dose timing to avoid inappropriate and costly dose escalations.

2-Pyridinylmethylsulfinylbenzimidazoles↗