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PubMed2025

Assessment of genomic prediction capabilities of transcriptome data in a barley multi-parent RIL population.

Low-cost and high-throughput RNA sequencing data for barley RILs achieved GP performance comparable to or better than traditional SNP array datasets when combined with parental whole-genome sequencing SNP data. The field of genomic selection (GS) is advancing rapidly on many fronts including the utilization of multi-omics datasets with the goal of increasing prediction ability and becoming an integral part of an increasing number of breeding programs ensuring future food security. In this study, we used RNA sequencing (RNA-Seq) data to perform genomic prediction (GP) on three related barley RIL populations. We investigated the potential of increasing prediction ability by combining genomic and transcriptomic datasets, adding whole-genome sequencing (WGS) SNP data, functional annotation-based filtering, and empirical quality filtering. Our RNA-Seq data were generated cost-efficiently using small-footprint plant cultivation, high-throughput RNA extraction, and Library preparation miniaturization. We also examined sequencing depth reduction as an additional cost-saving measure. We used fivefold cross-validation to evaluate the prediction ability of the gene expression dataset, the RNA-Seq SNP dataset, and the consensus SNP dataset between the RNA-Seq and parental WGS data, resulting in prediction abilities between 0.73 and 0.78. The consensus SNP dataset performed best, with five out of eight traits performing significantly better compared to a 50K SNP array, which served as a benchmark. The advantage of the consensus SNP dataset was most prominent in the inter-population predictions, in which the training and validation sets originated from different RIL sub-populations. We were therefore able to not only show that RNA-Seq data alone are able to predict various complex traits in barley using RILs, but also that the performance can be further increased with WGS data for which the public availability will steadily increase.

Hordeum↗
PubMed2005

Differences in total medical costs across the SSRIs for the treatment of depression and anxiety.

There is growing evidence that adherence to the recommended duration of antidepressant therapy results in reduced medical costs compared with nonadherence, and that the likelihood of adhering to therapy is not equivalent across the selective serotonin reuptake inhibitors (SSRIs). As such, the purpose of this study was to assess differences in 6-month medical costs between paroxetine controlled-release (CR) and immediate-release (IR) SSRI agents in a retrospective analysis of patients initiating SSRI therapy identified from the Integrated Healthcare Information Services National Managed Care Benchmark Database during a 2.5-year time frame. Inferential analyses were performed to evaluate differences in 6-month medical costs, controlling for differences in age, sex, utilization of psychiatric specialty care services, titration, pre-period costs, and comorbidity measures. Of the 146 075 patients included in this study, approximately 7% received paroxetine CR. Approximately 29.5% of patients had an anxiety disorder diagnosis; 26.0% had a depression-only diagnosis; and 13.2% had comorbid anxiety and depression. The 6-month medical costs were 244 US dollars lower for patients initiating with paroxetine CR compared with the average medical costs for patients receiving IR SSRIs. Paroxetine CR also had the lowest medical costs compared with each individual SSRI evaluated. After log transformation of costs and adjustment for baseline covariates, the aggregated IR SSRIs were associated with 8.7% higher 6-month medical costs than paroxetine CR (P <.001) and even greater costs after stratifying by diagnosis: 12.5% higher costs in patients with anxiety, 14.3% higher costs in patients with depression, and 15.9% higher costs in patients with comorbid anxiety and depression (P <.001 for all). Each individual IR SSRI was also associated with significantly higher medical costs than paroxetine CR, irrespective of diagnosis. As demonstrated, medical costs over a 6-month time frame were significantly greater for IR SSRIs versus paroxetine CR, even after adjusting for background characteristics and stratifying by diagnosis. Future studies should measure rates of adherence in relation to medical outcomes over an expanded time frame.

Adolescent↗
PubMed1998

Outcomes management for interventional cardiology.

In the evolution of quality assessment activities in interventional cardiology, outcomes management has become the benchmark for demonstrating optimal care. The high volume of interventional cardiology procedures performed each year mandates that efficient, high-quality and cost-effective patient care be delivered to all patients with cardiovascular disease. Although the interventional cardiology procedures represent only a snap shot of the patient's management of coronary artery disease, a long-term plan for positive outcomes is required. A multidisciplinary approach to outcomes management facilitates institutions to be competitive in today's health care market.

Benchmarking↗
PubMed1998

Using videotaped benchmarks to improve the self-assessment ability of family practice residents.

PURPOSE: To address methodologic and statistical problems of previous studies of self-assessment by exposing participants to relevant standards, anchoring rating scales, and providing practice in the use of the assessment tool. METHOD: Fifty first- and second-year family practice residents performed a ten-minute patient interview with a difficult communication problem. Following each interview, the resident and two experts independently evaluated the resident's communication skills. The resident was then shown a videotape of four performances (ranging in quality from poor to good) of the same scenario. The resident evaluated the communication skills displayed in each performance and then reevaluated his or her own performance. RESULTS: The correlation between experts' evaluations and residents' self-evaluations was moderate immediately after the interview (r = 0.38) but increased significantly after the residents viewed the videotape (r = 0.52). This effect was more pronounced for first-year residents (0.22 to 0.45) than for second-year residents (0.53 to 0.65), although the difference was not significant. Post-hoc analysis revealed that neither initial nor post-benchmark self-assessment ability was related to the ability to accurately evaluate the benchmarks in a manner consistent with the experts. CONCLUSIONS: The ability to self-assess does not seem strongly tied to the ability to assess the performances of others on the same task. Nonetheless, providing a set of benchmarks against which trainees can compare their own performances improves their ability to self-evaluate even if the qualities of the benchmarks are not explicitly identified.

Adult↗
PubMed2004

An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks.

This paper presents a simple sequential growing and pruning algorithm for radial basis function (RBF) networks. The algorithm referred to as growing and pruning (GAP)-RBF uses the concept of "Significance" of a neuron and links it to the learning accuracy. "Significance" of a neuron is defined as its contribution to the network output averaged over all the input data received so far. Using a piecewise-linear approximation for the Gaussian function, a simple and efficient way of computing this significance has been derived for uniformly distributed input data. In the GAP-RBF algorithm, the growing and pruning are based on the significance of the "nearest" neuron. In this paper, the performance of the GAP-RBF learning algorithm is compared with other well-known sequential learning algorithms like RAN, RANEKF, and MRAN on an artificial problem with uniform input distribution and three real-world nonuniform, higher dimensional benchmark problems. The results indicate that the GAP-RBF algorithm can provide comparable generalization performance with a considerably reduced network size and training time.

Algorithms↗
PubMed1999

Evaluation of a novel molecular vibration-based descriptor (EVA) for QSAR studies: 2. Model validation using a benchmark steroid dataset.

The EVA molecular descriptor derived from calculated molecular vibrational frequencies is validated for use in QSAR studies. EVA provides a conformationally sensitive but, unlike 3D-QSAR methods such as CoMFA, superposition-free descriptor that has been shown to perform well with a wide range of datasets and biological endpoints. A detailed study is made using a benchmark steroid dataset with a training/test set division of structures. Intensive statistical validation tests are undertaken including various forms of crossvalidation and repeated random permutation testing. Latent variable score plots show that the distribution of structures in reduced dimensional space can be rationalized in terms of activity classes and that EVA is sensitive to structural inconsistencies. Together, the findings indicate that EVA is a statistically robust means of detecting structure-activity correlations with performance entirely comparable to that of analogous CoMFAs. The EVA descriptor is shown to be conformationally sensitive and as such can be considered to be a 3D descriptor but with the advantage over CoMFA that structural superposition is not required. EVA has the property that in certain situations the conformational sensitivity can be altered through the appropriate choice of the EVA sigma parameter.

Models, Molecular↗
PubMed2001

Generalized comparative modeling (GENECOMP): a combination of sequence comparison, threading, and lattice modeling for protein structure prediction and refinement.

An improved generalized comparative modeling method, GENECOMP, for the refinement of threading models is developed and validated on the Fischer database of 68 probe-template pairs, a standard benchmark used to evaluate threading approaches. The basic idea is to perform ab initio folding using a lattice protein model, SICHO, near the template provided by the new threading algorithm PROSPECTOR. PROSPECTOR also provides predicted contacts and secondary structure for the template-aligned regions, and possibly for the unaligned regions by garnering additional information from other top-scoring threaded structures. Since the lowest-energy structure generated by the simulations is not necessarily the best structure, we employed two structure-selection protocols: distance geometry and clustering. In general, clustering is found to generate somewhat better quality structures in 38 of 68 cases. When applied to the Fischer database, the protocol does no harm and in a significant number of cases improves upon the initial threading model, sometimes dramatically. The procedure is readily automated and can be implemented on a genomic scale.

Algorithms↗
PubMed2006

MUSTANG: a multiple structural alignment algorithm.

Multiple structural alignment is a fundamental problem in structural genomics. In this article, we define a reliable and robust algorithm, MUSTANG (MUltiple STructural AligNment AlGorithm), for the alignment of multiple protein structures. Given a set of protein structures, the program constructs a multiple alignment using the spatial information of the C(alpha) atoms in the set. Broadly based on the progressive pairwise heuristic, this algorithm gains accuracy through novel and effective refinement phases. MUSTANG reports the multiple sequence alignment and the corresponding superposition of structures. Alignments generated by MUSTANG are compared with several handcurated alignments in the literature as well as with the benchmark alignments of 1033 alignment families from the HOMSTRAD database. The performance of MUSTANG was compared with DALI at a pairwise level, and with other multiple structural alignment tools such as POSA, CE-MC, MALECON, and MultiProt. MUSTANG performs comparably to popular pairwise and multiple structural alignment tools for closely related proteins, and performs more reliably than other multiple structural alignment methods on hard data sets containing distantly related proteins or proteins that show conformational changes.

Algorithms↗
PubMedDate not supplied

Underground measurements of radioactivity.

The exceptional sensitivity of gamma-ray spectrometry in underground laboratories has increasing application because of the important science and technology that it allows to be studied. Early work focused on rare fundamental phenomena, e.g. double beta decay, but a growing number of underground measurements is being performed in fields such as environmental monitoring, surveillance of nuclear activities, benchmarking of other physical techniques and materials selection for equipment which require materials with extremely low levels of radioactivity. This report describes the state of the art in underground gamma-ray spectrometry. Backgrounds of HPGe-detectors at various underground laboratories are presented and compared. Improved techniques and detectors are described and needs of deep underground facilities for higher sensitivity measurements are discussed.

Journal Article↗
PubMed2001

The pursuit of excellence is not optional in the voluntary sector, it is essential.

This paper outlines the continuous improvement journey of a voluntary organisation. The significant level of organisational growth and improving quality of services described is clearly linked to the organisation's commitment to improvement. One of the approaches used in adopting a total quality culture was the EFQM model, specifically interpreted for the voluntary sector. Until recently such an approach would have been considered alien to the sector, not least because of its origins in the business community. This article contradicts this assumption. Issues addressed include how the improvement process is driven, the use of performance measurement, external verification and the difficulties in accessing sector appropriate benchmark data. It is suggested that the pursuit of excellence is no longer optional for the voluntary sector, it is essential.

Activities of Daily Living↗
PubMed2006

Explaining differences between hospitals in number of organ donors.

The shortage of donor organs calls for a careful examination of all improvement options. In this study, 80 Dutch hospitals were compared. They provided 868 donors in a 5-year period, constituting 91% of all donors in that period in The Netherlands. Multilevel regression analysis was used to explain the differences between hospitals. Potential explanatory variables were hospital-specific mortality statistics, donor policy and structural hospital characteristics. Of all donors, 81% came from one quarter of the hospitals, mainly larger hospitals. A strong relationship was found between the number of donors and hospital-specific mortality statistics. Hospitals with a neurosurgery department had additional donors. Seven hospitals systematically underperformed over a period of 5 years. If these hospitals were to increase their donor efficiency to their expected value, it would lead to an increase of 10% in the number of donors. Most donors are found in large hospitals, implying that resources to improve donor-recruitment should be channelled to larger hospitals. This study presents an efficient strategy toward a benchmark for hospitals of their organ donation rates. Some larger hospitals performed less well than others. This suggests that there is still room for improvement. There is no evidence for large undiscovered and unused pools of donor organs.

Hospitals↗
PubMedDate not supplied

The European practice database (EPD): results of the study in thte North-East of Italy.

The survey, realized in 2002-03 in the North-East of Italy, describes renal care in dialysis services. A questionnaire, structured at European level, was sent to all dialysis centres by mail. The questionnaire was returned from 21 centres (61.8%) and related satellite units. Results show nonhomogeneity in renal care. Some important results were: low use of peritoneal dialysis (18%), compared to the rest of Europe, elevated presence of older people on haemodialysis, reduced percentage of patients on transplantation waiting list, diffused use of isolation for HCV positive patients, high use of AV fistulae (84%), low employment of renal technicians, absence of renal dieticians and social workers and nurses performing prevalently direct care. Data can be used for different goals: benchmarking activities, selection of deeper research topics and development of more oriented continuous education activities.

Adolescent↗
PubMed2003

Soft learning vector quantization.

Learning vector quantization (LVQ) is a popular class of adaptive nearest prototype classifiers for multiclass classification, but learning algorithms from this family have so far been proposed on heuristic grounds. Here, we take a more principled approach and derive two variants of LVQ using a gaussian mixture ansatz. We propose an objective function based on a likelihood ratio and derive a learning rule using gradient descent. The new approach provides a way to extend the algorithms of the LVQ family to different distance measure and allows for the design of "soft" LVQ algorithms. Benchmark results show that the new methods lead to better classification performance than LVQ 2.1. An additional benefit of the new method is that model assumptions are made explicit, so that the method can be adapted more easily to different kinds of problems.

Costs and Cost Analysis↗