980 resultados para Testing machine
Resumo:
Microsatellite instability (MSI) testing in clinics is becoming increasingly widespread; therefore, there is an urgent need for methodology standardization and the availability of quality control. This study is aimed to assess the interlaboratory reproducibility of MSI testing in archive samples by using a panel of 5 recently introduced, mononucleotide repeats (MNR). The quality control involved 8 European institutions. Participants were supplied with DNA extracted from 15 archive colon carcinoma samples and from the corresponding normal tissues. Every group was asked to assess the MSI status of the samples by using the BAT25, BAT26, NR21, NR24, and NR27 mononucleotide markers. Four institutions repeated the analysis using the NCI reference panel to confirm the results obtained with the MNR markers. The overall concordance among institutions for MSI analyses at single locus level was 97.7% when using the MNR panel and 95.0% with the NCI one. The laboratories obtained a full agreement in scoring the MSI status of each patient sample, both using the mononucleotide and the NCI marker sets. With the NCI marker set, however, concordance was lowered to 85.7% when considering the MSI-Low phenotype. Concordance between the 2 panels in scoring the MSI status of each sample was complete if no discrimination was made between MSI-Stable and MSI-L, whereas it dropped to 76.7% if MSI-L was considered. In conclusion, the use of the MNR panel seems to be a robust approach that yields a very high level of reproducibility. The results obtained with the 5 MNR are diagnostically consistent with those obtained by the use of the NCI markers, except for the MSI-Low phenotype.
Resumo:
Imatinib is the standard of care for patients with advanced metastatic gastrointestinal stromal tumors (GIST), and is also approved for adjuvant treatment in patients at substantial risk of relapse. Studies have shown that maximizing benefit from imatinib depends on long-term administration at recommended doses. Pharmacokinetic (PK) and pharmacodynamic factors, adherence, and drug-drug interactions can affect exposure to imatinib and impact clinical outcomes. This article reviews the relevance of these factors to imatinib's clinical activity and response in the context of what has been demonstrated in chronic myelogenous leukemia (CML), and in light of new data correlating imatinib exposure to response in patients with GIST. Because of the wide inter-patient variability in drug exposure with imatinib in both CML and GIST, blood level testing (BLT) may play a role in investigating instances of suboptimal response, unusually severe toxicities, drug-drug interactions, and suspected non-adherence. Published clinical data in CML and in GIST were considered, including data from a PK substudy of the B2222 trial correlating imatinib blood levels with clinical responses in patients with GIST. Imatinib trough plasma levels <1100ng/mL were associated with lower rates of objective response and faster development of progressive disease in patients with GIST. These findings have been supported by other analyses correlating free imatinib (unbound) levels with response. These results suggest a future application for imatinib BLT in predicting and optimizing therapeutic response. Nevertheless, early estimates of threshold imatinib blood levels must be confirmed prospectively in future studies and elaborated for different patient subgroups.
Resumo:
Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.
Resumo:
This paper presents a webservice architecture for Statistical Machine Translation aimed at non-technical users. A workfloweditor allows a user to combine different webservices using a graphical user interface. In the current state of this project,the webservices have been implemented for a range of sentential and sub-sententialaligners. The advantage of a common interface and a common data format allows the user to build workflows exchanging different aligners.
Resumo:
PURPOSE: To assess the inter/intraobserver variability of apparent diffusion coefficient (ADC) measurements in treated hepatic lesions and to compare ADC measurements in the whole lesion and in the area with the most restricted diffusion (MRDA). MATERIALS AND METHODS: Twenty-five patients with treated malignant liver lesions were examined on a 3.0T machine. After agreeing on the best ADC image, two readers independently measured the ADC values in the whole lesion and in the MRDA. These measurements were repeated 1 month later. The Bland-Altman method, Spearman correlation coefficients, and the Wilcoxon signed-rank test were used to evaluate the measurements. RESULTS: Interobserver variability for ADC measurements in the whole lesion and in the MRDA was 0.17 x 10(-3) mm(2)/s [-0.17, +0.17] and 0.43 x 10(-3) mm(2)/s [-0.45, +0.41], respectively. Intraobserver limits of agreement could be as low as [-0.10, +0.12] 10(-3) mm(2)/s and [-0.20, +0.33] 10(-3) mm(2)/s for measurements in the whole lesion and in the MRDA, respectively. CONCLUSION: A limited variability in ADC measurements does exist, and it should be considered when interpreting ADC values of hepatic malignancies. This is especially true for the measurements of the minimal ADC.
Resumo:
The McIsaac scoring system is a tool designed to predict the probability of streptococcal pharyngitis in children aged 3 to 17 years with a sore throat. Although it does not allow the physician to make the diagnosis of streptococcal pharyngitis, it enables to identify those children with a sore throat in whom rapid antigen detection tests have a good predictive value.
Resumo:
ABSTRACT: BACKGROUND: Local adaptation can drive the divergence of populations but identification of the traits under selection remains a major challenge in evolutionary biology. Reciprocal transplant experiments are ideal tests of local adaptation, yet rarely used for higher vertebrates because of the mobility and potential invasiveness of non-native organisms. Here, we reciprocally transplanted 2500 brown trout (Salmo trutta) embryos from five populations to investigate local adaptation in early life history traits. Embryos were bred in a full-factorial design and raised in natural riverbeds until emergence. Customized egg capsules were used to simulate the natural redd environment and allowed tracking the fate of every individual until retrieval. We predicted that 1) within sites, native populations would outperform non-natives, and 2) across sites, populations would show higher performance at 'home' compared to 'away' sites. RESULTS: There was no evidence for local adaptation but we found large differences in survival and hatching rates between sites, indicative of considerable variation in habitat quality. Survival was generally high across all populations (55% +/- 3%), but ranged from 4% to 89% between sites. Average hatching rate was 25% +/- 3% across populations ranging from 0% to 62% between sites. CONCLUSION: This study provides rare empirical data on variation in early life history traits in a population network of a salmonid, and large-scale breeding and transplantation experiments like ours provide powerful tests for local adaptation. Despite the recently reported genetic and morphological differences between the populations in our study area, local adaptation at the embryo level is small, non-existent, or confined to ecological conditions that our experiment could not capture.
Resumo:
Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale-Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<0.0001). Training with one data set and testing with another demonstrated stability between data sets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome.
Resumo:
The feasibility of opportunistic screening of urogenital infections with Chlamydia trachomatis was assessed in a cross-sectional study in 2012, in two cantons of south-western Switzerland: Vaud and Valais. Sexually active persons younger than 30 years, not tested for C. trachomatis in the last three months, were invited for free C. trachomatis testing by PCR in urine or self-applied vaginal swabs. Of 2,461 consenting participants, 1,899 (77%) were women and all but six (0.3%) submitted a sample. Forty-seven per cent of female and 25% of male participants were younger than 20 years. Overall, 134 (5.5%) of 2,455 tested participants had a positive result and were followed up. Seven per cent of all candidates for screening were not invited, 10% of invited candidates were not eligible, 15% of the eligible candidates declined participation, 5% of tested participants testing positive were not treated, 29% of those treated were not retested after six months and 9% of those retested were positive for C. trachomatis. Opportunistic C. trachomatis testing proved technically feasible and acceptable, at least if free of charge. Men and peripheral rural regions were more difficult to reach. Efforts to increase testing and decrease dropout at all stages of the screening procedure are necessary.
Resumo:
Current nuclear medicine techniques for the localization of inflammatory processes are based on injection of 111In labelled autologous granulocytes which need to be isolated and radiolabelled in vitro before reinjection. A new technique is presented here that obviates the need for cell isolation by the direct intravenous injection of a granulocyte specific 123I labelled monoclonal antibody. In this publication the basic parameters of the antibody granulocyte interaction are described. Antibody binding does not inhibit vital functions of the granulocytes, such as chemotaxis and superoxide generation. Scatchard analysis of binding data reveals an apparent affinity of the antibody for granulocytes of 6.8 X 10(9) l/mol and approximately 7.1 X 10(4) binding sites per cell. Due to the high specificity of the antibody, the only expected interference is from CEA producing tumors.
Resumo:
This paper discusses the role of deterministic components in the DGP and in the auxiliary regression model which underlies the implementation of the Fractional Dickey-Fuller (FDF) test for I(1) against I(d) processes with d ∈ [0, 1). This is an important test in many economic applications because I(d) processess with d & 1 are mean-reverting although, when 0.5 ≤ d & 1,, like I(1) processes, they are nonstationary. We show how simple is the implementation of the FDF in these situations, and argue that it has better properties than LM tests. A simple testing strategy entailing only asymptotically normally distributed tests is also proposed. Finally, an empirical application is provided where the FDF test allowing for deterministic components is used to test for long-memory in the per capita GDP of several OECD countries, an issue that has important consequences to discriminate between growth theories, and on which there is some controversy.