words maximumPolysaccharide utilisation loci (PUL) are regions within bacterial genomes that encode all the necessary machinery for the cleavage of particular carbohydrates. For the Bacteroidetes phylum, prediction of PUL from genomic data alone involves the identification of carbohydrate-active enzymes (CAZymes) co-localised with susCD gene pairs. Here we present the open prediction of PUL in 5414 public Bacteroidetes genomes, and an open-source pipeline to reproduce or extend the results.
Purpose:
Determine equivalent Organ at Risk (OAR) tolerance dose (TD) constraints for MV x‐rays and particle therapy.
Methods:
Equivalent TD estimates for MV x‐rays are determined from an isoeffect, regression‐analysis of published and in‐house constraints for various fractionation schedules (n fractions). The analysis yields an estimate of (α/β) for an OAR. To determine equivalent particle therapy constraints, the MV x‐ray TD(n) values are divided by the RBE for DSB induction (RBEDSB) or cell survival (RBES). Estimates of (RBEDSB) are computed using the Monte Carlo Damage Simulation, and estimates of RBES are computed using the Repair‐Misrepair‐Fixation (RMF) model. A research build of the RayStation™ treatment planning system implementing the above model is used to estimate (RBEDSB) for OARs of interest in 16 proton therapy patient plans (head and neck, thorax, prostate and brain).
Results:
The analysis gives an (α/β) estimate of about 20 Gy for the trachea and heart and 2–4 Gy for the esophagus, spine, and brachial plexus. Extrapolation of MV x‐ray constraints (n = 1) to fast neutrons using RBEDSB = 2.7 are in excellent agreement with clinical experience (n = 10 to 20). When conventional (n > 30) x‐ray treatments are used as the reference radiation, fast neutron RBE increased to a maximum of 6. For comparison to a constant RBE of 1.1, the RayStation™ analysis gave estimates of proton RBEDSB from 1.03 to 1.33 for OARs of interest.
Conclusion:
The presented system of models is a convenient formalism to synthesize from multiple sources of information a set of self‐consistent plan constraints for MV x‐ray and hadron therapy treatments. Estimates of RBEDSB from the RayStation™ analysis differ substantially from 1.1 and vary among patients and treatment sites. A treatment planning system that incorporates patient and anatomy‐specific corrections in proton RBE would create opportunities to increase the therapeutic ratio.
The research build of the RayStation used in the study was made available to the University of Washington free of charge. RaySearch Laboratories did not provide any monetary support for the reported studies.
Purpose: A biologically motivated scheme to guide the determination of individualized dose distributions is developed from the Poisson tumor control probability (TCP) and linear‐quadratic (LQ) survival model. The method combines clinical experience, in the form of a reference treatment, with possibly patient‐specific information to help circumvent well‐known issues associated with outcome modeling. To illustrate the approach, isoeffect doses for populations of prostate cancer patients are compared. Method and Materials: Monte Carlo methods are used to sample prostate cancer radiosensitivity parameters derived from clinical data in ways that mimic two treatment planning scenarios. In the first scenario, the dose distribution needed to achieve the same TCP in all patients is estimated. In the second scenario, the distribution of doses needed to achieve the same distribution of TCP values in the patient population as a reference treatment (37 daily fractions of 2 Gy) is determined. Results: For 28 to 40 daily fractions, uncertainties associated with population‐averaged radiosensitivity parameters correspond to about a 20% uncertainty in the fraction size needed to achieve the same TCP. However, the fraction size needed to achieve the same distribution of clinical outcomes as 37 daily fractions of 2 Gy can be estimated to within 3% for 5 to 50 daily fractions. Conclusion: To achieve the same TCP in all prostate cancer patients requires very accurate (a priori) estimates of radiosensitivity parameters. However, the fraction size needed to achieve the same distribution of TCP values among a patient population with an alternate fractionation schedule can be accurately estimated without the need for patient‐specific information. When combined with information from predictive assays or functional and biological imaging, the proposed method has the potential to determine patient‐specific dose distributions for use in commercially available inverse planning software.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.