Selection of adequate optimization criteria in chromatographic separations.
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ABSTRACT:
SUBMITTER: Vanbel PF
PROVIDER: S-EPMC2694924 | biostudies-other | 2009 Jul
REPOSITORIES: biostudies-other
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Project description:Identifying genes with the largest expression changes (gene selection) to characterize a given condition is a popular first step to drive exploration into molecular mechanisms and is, therefore, paramount for therapeutic development. Reproducibility in the sciences makes it necessary to emphasize objectivity and systematic repeatability in biological and informatics analyses, including gene selection. With these two characteristics in mind, in previous works our research team has proposed using multiple criteria optimization (MCO) in gene selection to analyze microarray datasets. The result of this effort is the MCO algorithm, which selects genes with the largest expression changes without user manipulation of neither informatics nor statistical parameters. Furthermore, the user is not required to choose either a preference structure among multiple measures or a predetermined quantity of genes to be deemed significant a priori. This implies that using the same datasets and performance measures (PMs), the method will converge to the same set of selected differentially expressed genes (repeatability) despite who carries out the analysis (objectivity). The present work describes the development of an open-source tool in RStudio to enable both: (1) individual analysis of single datasets with two or three PMs and (2) meta-analysis with up to five microarray datasets, using one PM from each dataset. The capabilities afforded by the code include license-free portability and the possibility to carry out analyses via modest computer hardware, such as personal laptops. The code provides affordable, repeatable, and objective detection of differentially expressed genes from microarrays. It can be used to analyze other experiments with similar experimental comparative layouts, such as microRNA arrays and protein arrays, among others. As a demonstration of the capabilities of the code, the analysis of four publicly-available microarray datasets related to Parkinson´s Disease (PD) is presented here, treating each dataset individually or as a four-way meta-analysis. These MCO-supported analyses made it possible to identify MMP9 and TUBB2A as potential PD genetic biomarkers based on their persistent appearance across each of the case studies. A literature search confirmed the importance of these genes in PD and indeed as PD biomarkers, which evidences the code´s potential.
| S-EPMC8794188 | biostudies-literature
Project description:BackgroundThe National Lung Screening Trial (NLST) used risk factors for lung cancer (e.g., ≥30 pack-years of smoking and <15 years since quitting) as selection criteria for lung-cancer screening. Use of an accurate model that incorporates additional risk factors to select persons for screening may identify more persons who have lung cancer or in whom lung cancer will develop.MethodsWe modified the 2011 lung-cancer risk-prediction model from our Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to ensure applicability to NLST data; risk was the probability of a diagnosis of lung cancer during the 6-year study period. We developed and validated the model (PLCO(M2012)) with data from the 80,375 persons in the PLCO control and intervention groups who had ever smoked. Discrimination (area under the receiver-operating-characteristic curve [AUC]) and calibration were assessed. In the validation data set, 14,144 of 37,332 persons (37.9%) met NLST criteria. For comparison, 14,144 highest-risk persons were considered positive (eligible for screening) according to PLCO(M2012) criteria. We compared the accuracy of PLCO(M2012) criteria with NLST criteria to detect lung cancer. Cox models were used to evaluate whether the reduction in mortality among 53,202 persons undergoing low-dose computed tomographic screening in the NLST differed according to risk.ResultsThe AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCO(M2012) criteria had improved sensitivity (83.0% vs. 71.1%, P<0.001) and positive predictive value (4.0% vs. 3.4%, P=0.01), without loss of specificity (62.9% and. 62.7%, respectively; P=0.54); 41.3% fewer lung cancers were missed. The NLST screening effect did not vary according to PLCO(M2012) risk (P=0.61 for interaction).ConclusionsThe use of the PLCO(M2012) model was more sensitive than the NLST criteria for lung-cancer detection.
| S-EPMC3929969 | biostudies-literature
Project description:BackgroundFor sentinel lymph node biopsy (SLNB) in patients with breast cancer, the dual tracer of blue dye and radioisotope with the 10% rule that all nodes with radioactive count of 10% or more of the hottest node ex vivo should be removed is widely accepted. However, the cut-off point of radioactivity is being questioned for possibly excessive removal of negative nodes.MethodsTo compare different percentile rules and optimize the criteria for identifying SLNs, we established a database which prospectively collected the radioactivity, status of blue dye and the pathological results of each SLN in breast cancer patients who successfully underwent SLNB with a combination of methylene blue and radioisotope.ResultsA total of 2,529 SLNs from 1,039 patients were identified from August 2010 to August 2019. 16.4% (414/2,529) positive nodes were removed at a cost of 83.6% (2115/2,529) negative nodes removed excessively. Up to 17.9% (375/2,115) negative nodes were removed as radioactively hot nodes without blue staining. By gradually increasing the threshold by each 10%, the number of negative nodes identified reduced by 18.2% (385/2,115) with only three node-positive patients (1.0%) missed to be identified using the "40% + blue" rule. In patients with ≥ 2 SLNs removed, 12.3% (238/1,942) negative nodes avoided unnecessary removal with only 0.8% (2/239) positive patients missed with the "hottest two + blue" rule.ConclusionsOur data indicated that the "40% + blue" rule or the "hottest two + blue" rule for SLNB with the dual tracer of blue dye and radioisotope may be considered as a potential alternative rule to minimize extra nodes resected. Nonetheless, it should be validated by prospective trials with long-term follow-up.
| S-EPMC7744718 | biostudies-literature
Project description:Background Despite the availability of guidelines for the performance of transcatheter aortic valve implantation (TAVI), current treatment pathways vary between countries and institutions, which impact on the mean duration of postprocedure hospitalization. Methods and Results This was a prospective, multicenter registry of 502 patients to validate the appropriateness of discharge timing after transfemoral TAVI, using prespecified risk criteria from FAST-TAVI (Feasibility and Safety of Early Discharge After Transfemoral [TF] Transcatheter Aortic Valve Implantation), based on hospital events within 1-year after discharge. The end point-a composite of all-cause mortality, vascular access-related complications, permanent pacemaker implantation, stroke, cardiac rehospitalization, kidney failure, and major bleeding-was reached in 27.0% of patients (95% CI, 23.3-31.2) within 1 year after intervention; 7.5% (95% CI, 5.5-10.2) had in-hospital complications before discharge and 19.6% (95% CI, 16.3-23.4) within 1 year after discharge. Overall mortality within 1 year after discharge was 7.3% and rates of cardiac rehospitalization 13.5%, permanent pacemaker implantation 4.2%, any stroke 1.8%, vascular-access-related complications 0.7%, life-threatening bleeding 0.7%, and kidney failure 0.4%. Composite events within 1 year after discharge were observed in 18.8% and 24.3% of patients with low risk of complications/early (≤3 days) discharge and high risk and discharged late (>3 days) (concordant discharge), respectively. Event rate in patients with discordant discharge was 14.3% with low risk but discharged late and increased to 50.0% in patients with high risk but discharged in ≤3 days. Conclusions The FAST-TAVI risk assessment provides a tool for appropriate, risk-based discharge that was validated with the 1-year event rate after transfemoral TAVI. Registration URL: https://www.ClinicalTrials.gov; Unique identifier: NCT02404467.
| S-EPMC7792272 | biostudies-literature
Project description:In current diagnostic criteria for implant-associated bone- and joint infections, phenotypically identical low-virulence bacteria in two intraoperative cultures are usually required. Using whole-genome sequencing, we have further characterized three phenotypically different Staphylococcus capitis isolated from one prosthetic joint infection, highlighting the challenges in defining microbiological criteria for low-virulence prosthetic joint infections.
| S-EPMC6367199 | biostudies-literature
Project description:Microsphere hydroxyapatite (HAp) is widely used in various biomedical and chromatographic applications. The work described in this manuscript focuses on a dissolution precipitation method for production of HAp microspheres. This method overcomes certain drawbacks of conventional preparation methods used for HAp preparation, which produce polydisperse particles and are time-consuming and expensive. In the present work, the calcium carbonate (calcite) particles were directly and rapidly converted into HAp microspheres using an inexpensive dissolution precipitation method. The effects of the reaction temperature, time, and mechanical stirring rates were studied, and the reaction parameters were optimized. As confirmed by the XRD studies, the higher reaction temperature and time promote complete HAp conversion, while calcite residues were observed for lower temperatures and times. SEM images show the influence of reaction parameters on the surface microstructure of the microspheres produced. It was observed that the HAp microspheres undergo disintegration at a higher stirring rate. The reaction parameters optimized in this work were ideal for preparing HAp microspheres. The resultant HAp particles were utilized as matrices for chromatographic separation of protein mixtures.
| S-EPMC9288468 | biostudies-literature
Project description:Biological process enrichment is a widely used metric for evaluating the quality of multiprotein modules. In this study, we examine possible optimization criteria for detecting homologous multiprotein modules and quantify their effects on biological process enrichment. We find that modularity, linear density, and module size are the most important criteria considered, complementary to each other, and that graph theoretical attributes account for 36% of the variance in biological process enrichment. Variations in protein interaction similarity within module pairs have only minor effects on biological process enrichment. As random modules increase in size, both biological process enrichment and modularity tend to improve, although modularity does not show this upward trend in modules with size at most 50 proteins. To adjust for these trends, we recommend a size correction based on random sampling of modules when using biological process enrichment or other attributes to evaluate module boundaries. Characteristics of homologous multiprotein modules optimized for each of the optimization criteria are examined.
| S-EPMC3696829 | biostudies-other
Project description:To investigate how using different sets of decision criteria impacts the quality of intensity modulated radiation therapy (IMRT) plans obtained by multiobjective optimization.A multiobjective optimization evolutionary algorithm (MOEA) was used to produce sets of IMRT plans. The MOEA consisted of two interacting algorithms: (i) a deterministic inverse planning optimization of beamlet intensities that minimizes a weighted sum of quadratic penalty objectives to generate IMRT plans and (ii) an evolutionary algorithm that selects the superior IMRT plans using decision criteria and uses those plans to determine the new weights and penalty objectives of each new plan. Plans resulting from the deterministic algorithm were evaluated by the evolutionary algorithm using a set of decision criteria for both targets and organs at risk (OARs). Decision criteria used included variation in the target dose distribution, mean dose, maximum dose, generalized equivalent uniform dose (gEUD), an equivalent uniform dose (EUD(alpha,beta) formula derived from the linear-quadratic survival model, and points on dose volume histograms (DVHs). In order to quantatively compare results from trials using different decision criteria, a neutral set of comparison metrics was used. For each set of decision criteria investigated, IMRT plans were calculated for four different cases: two simple prostate cases, one complex prostate Case, and one complex head and neck Case.When smaller numbers of decision criteria, more descriptive decision criteria, or less anti-correlated decision criteria were used to characterize plan quality during multiobjective optimization, dose to OARs and target dose variation were reduced in the final population of plans. Mean OAR dose and gEUD (a = 4) decision criteria were comparable. Using maximum dose decision criteria for OARs near targets resulted in inferior populations that focused solely on low target variance at the expense of high OAR dose. Target dose range, (D(max) - D(min)), decision criteria were found to be most effective for keeping targets uniform. Using target gEUD decision criteria resulted in much lower OAR doses but much higher target dose variation. EUD(alpha,beta) based decision criteria focused on a region of plan space that was a compromise between target and OAR objectives. None of these target decision criteria dominated plans using other criteria, but only focused on approaching a different area of the Pareto front.The choice of decision criteria implemented in the MOEA had a significant impact on the region explored and the rate of convergence toward the Pareto front. When more decision criteria, anticorrelated decision criteria, or decision criteria with insufficient information were implemented, inferior populations are resulted. When more informative decision criteria were used, such as gEUD, EUD(alpha,beta), target dose range, and mean dose, MOEA optimizations focused on approaching different regions of the Pareto front, but did not dominate each other. Using simple OAR decision criteria and target EUD(alpha,beta) decision criteria demonstrated the potential to generate IMRT plans that significantly reduce dose to OARs while achieving the same or better tumor control when clinical requirements on target dose variance can be met or relaxed.
| S-EPMC3125078 | biostudies-other
Project description:BackgroundIn Kuwait, 21 residency training programs were offered in the year 2011; however, no data is available regarding the criteria of selecting residents for these programs. This study aims to provide information about the importance of these criteria.MethodsA self-administered questionnaire was used to collect data from members (e.g. chairmen, directors, assistants …etc.) of residency programs in Kuwait. A total of 108 members were invited to participate. They were asked to rate the importance level (scale from 1 to 5) of criteria that may affect the acceptance of an applicant to their residency programs. Average scores were calculated for each criterion.ResultsOf the 108 members invited to participate, only 12 (11.1%) declined to participate. Interview performance was ranked as the most important criteria for selecting residents (average score: 4.63/5.00), followed by grade point average (average score: 3.78/5.00) and honors during medical school (average score: 3.67/5.00). On the other hand, receiving disciplinary action during medical school and failure in a required clerkship were considered as the most concerning among other criteria used to reject applicants (average scores: 3.83/5.00 and 3.54/5.00 respectively). Minor differences regarding the importance level of each criterion were noted across different programs.ConclusionsThis study provided general information about the criteria that are used to accept/reject applicants to residency programs in Kuwait. Future studies should be conducted to investigate each criterion individually, and to assess if these criteria are related to residents' success during their training.
| S-EPMC3552967 | biostudies-literature
Project description:The aim of this study was to evaluate the genetic component of the locomotor jumping ability, via a wearable accelerometer sensor, and to estimate the genetic correlation with performance in competition, to introduce such criteria in selection schema. A sample of 1,056 young 3-year-old horses were equipped with a 3-dimensional accelerometer during a free jumping test, in regular breeding shows from 2015 to 2017. Seven variables were extracted from the dorso-ventral acceleration curve for the last three jumps over a double bar obstacle of 1.15 m for the front pole and 1.20 m for the back pole with a 1.20 m spread. Variables were the peaks of forelimbs, hindlimbs, and landing acceleration, the duration between peaks at take-off, the peak of forelimb acceleration and start of jump, jump duration and duration between the beginning of the impact of forelimbs and the peak at landing. During breeding shows, judges scored balance, strength, style, and reactivity for free jumping and jumping tests under saddle. Jumping competition results were recorded by logarithm of the sum of points earned in each competition. All horses in official competitions were included, i.e., 160,257 horses born in 1997 with a total of 649,491 annual performances. An animal mixed model with complete pedigree over four generations (353,236 horses) were used with fixed effects of jumping test location and date, morning/afternoon, gender, month of birth, rank of jump for accelerometric data, effect of year of competition, combined with age and gender for competition results. As a result, jump duration was the most heritable and repeatable for jump variables: h 2 = 0.16 (0.06), r = 0.52 (0.02), while accelerations were moderately heritable (h 2 = 0.05-0.09, r = 0.39-0.51). Judgement scores were heritable: 0.21 (0.07)-0.33 (0.09) and were highly correlated. Scores during free jumping were genetically correlated to jump duration: 0.71 (0.15)-0.88 (0.16). Both jump duration and judgement scores were genetically correlated to competition performance: 0.59 (0.13) for jump duration, from 0.60 (0.11) to 0.77 (0.12) for scores. Jump duration and judgement scores can be used as early selection criteria. The advantage of the accelerometric measurement is its objectivity and the ease of recording.
| S-EPMC7248255 | biostudies-literature