Results 251 to 260 of about 18,112,323 (302)
Accurate and noninvasive prostate cancer detection using plasma‐derived extracellular vesicle RNA
Plasma extracellular vesicles were captured with WGA‐conjugated magnetic beads and profiled for RNA biomarkers. A three‐RNA panel (NM_024955, NR_047469, and NR_002564) distinguished prostate cancer from healthy controls and benign prostatic hyperplasia, supporting a simple, noninvasive approach to improve prostate cancer detection.
Hanping Wei, Haoran Wu, Wei Feng
wiley +1 more source
Identification of (20R)‐protopanaxadiol from Panax ginseng as a novel anti‐SARS‐CoV‐2 compound
We established a noninfectious BAC‐based SARS‐CoV‐2 replicon that enables antiviral screening under BSL‐2 conditions. Using this platform, we screened 373 food‐derived compounds and identified (20R)‐protopanaxadiol from Panax ginseng as a novel inhibitor of SARS‐CoV‐2 RNA replication, highlighting the value of safe replicon systems for antiviral ...
Midori Takeda +4 more
wiley +1 more source
Evolution‐guided yeast complementation reveals functional differences in human PSPH variants
Ancient genomes can help guide which human genetic variants are tested experimentally. This study applies that idea to PSPH, a gene involved in serine biosynthesis, and uses high‐throughput yeast complementation to compare variant function. The findings reveal measurable differences among selected alleles and illustrate the value of evolution‐guided ...
Mauricio Campa‐Álvarez +6 more
wiley +1 more source
We report the first β‐glucosidase with demonstrated hydrolytic activity on an N‐linked glycopyranoside. The enzyme, native to maize, was biochemically characterised for this novel reaction, and structural modelling of the enzyme–substrate complex revealed several clues to the underlying reduced catalytic rate relative to its native O‐glycopyranoside ...
Hani Gharabli +3 more
wiley +1 more source
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Improvement of mixed predictors in linear mixed models
Journal of Applied Statistics, 2020In this paper, we introduce stochastic-restricted Liu predictors which will be defined by combining in a special way the two approaches followed in obtaining the mixed predictors and the Liu predictors in the linear mixed models. Superiorities of the linear combination of the new predictor to the Liu and mixed predictors are done in the sense of mean ...
Özge Kuran, M. Revan Özkale
openaire +2 more sources
2014
Chapter Preview . We give a general discussion of linear mixed models and continue by illustrating specific actuarial applications of this type of model. Technical details on linear mixed models follow: model assumptions, specifications, estimation techniques, and methods of inference.
Antonio, K., Zhang, Y.
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Chapter Preview . We give a general discussion of linear mixed models and continue by illustrating specific actuarial applications of this type of model. Technical details on linear mixed models follow: model assumptions, specifications, estimation techniques, and methods of inference.
Antonio, K., Zhang, Y.
openaire +3 more sources
2020
This chapter introduces linear mixed models, which have wide applicability in small area estimation due to their flexibility to combining different types of information and explaining sources of errors. Three of the most used fitting methods are presented under two parametrizations.
Domingo Morales +3 more
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This chapter introduces linear mixed models, which have wide applicability in small area estimation due to their flexibility to combining different types of information and explaining sources of errors. Three of the most used fitting methods are presented under two parametrizations.
Domingo Morales +3 more
openaire +2 more sources
Local Influence in Linear Mixed Models
Biometrics, 1998The linear mixed model has become an important tool in modelling, partially due to the introduction of the SAS procedure MIXED, which made the method widely available to practising statisticians. Its growing popularity calls for data-analytic methods to check the underlying assumptions and robustness. Here, the problem of detecting influential subjects
Lesaffre, Emmanuel, Verbeke, Geert
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