Strategies for high-throughput sample analysis

2014 ◽  
pp. 18-33 ◽  
Author(s):  
Maria AM Fitzgerald
Keyword(s):  
High Throughput ◽  
Sample Analysis

Hydrophilic interaction chromatography-tandem mass spectrometry based on an amide column for the high-throughput quantification of metformin in rat plasma

RSC Advances ◽  
2015 ◽  
Vol 5 (123) ◽  
pp. 101386-101392 ◽  
Author(s):  
Rong Shi ◽  
Xining Xu ◽  
Jiasheng Wu ◽  
Tianming Wang ◽  
Yuanyuan Li ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
High Throughput ◽  
Rat Plasma ◽  
Pharmacokinetic Studies ◽  
Tandem Mass ◽  
Sample Analysis ◽  
Hydrophilic Interaction ◽  
Chromatography Tandem Mass Spectrometry ◽  
Highly Sensitive

A simple, highly sensitive, specific, reproducible, and high-throughput Amide-HILIC-MS/MS assay to quantify metformin in rat plasma was established and successfully applied for sample analysis to support pharmacokinetic studies.

scholarly journals AB0003 HLA-ALLELES IN SUSCEPTIBILITY TO SYSTEMIC AND OLIGOARTICULAR JUVENILE IDIOPATHIC ARTHRITIS IN THE BELARUSIAN POPULATION

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1036.1-1037
Author(s):  
H. Yatskiu ◽  
A. Sukalo ◽  
R. Goncharova
Keyword(s):  
Juvenile Idiopathic Arthritis ◽  
High Throughput ◽  
Complex Trait ◽  
Negative Association ◽  
Classification Criteria ◽  
Hla Typing ◽  
Sample Analysis ◽  
Hla Alleles ◽  
Systemic Jia ◽  
Oligoarticular Juvenile Idiopathic Arthritis

Background:Juvenile idiopathic arthritis (JIA) is a complex trait, the most common rheumatic disease in children. Considering clinical heterogeneity of the disease, the genetic background of particular JIA subtypes may also vary significantly.Objectives:This work was aimed to reveal characteristic patterns of HLA associations within 11 loci for two clinically different forms of JIA in the Belarusian population.Methods:24 patients diagnosed with systemic JIA, 24 patients with oligoarticular JIA and 24 healthy controls were included into the study. The JIA patients were divided into subgroups according to IIAR classification criteria. High-throughput HLA typing was performed using TruSight HLA v2 Sequencing Panel (Illumina) on MiSeq system. Sample analysis was performed using Assign TruSight HLA v2.0 software.Results:DQA1*05:01:01 and DQB1*02:01:01 alleles showed protective effect against both systemic (p = 0.007; OR=0.08; 95% CI=[0.009–0.65] and p = 0.01; OR=0.09; 95% CI=[0.01–0.83]) and oliarticular JIA (p = 0.026; OR=0.16; 95% CI=[0.03–0.79] and p = 0.046; OR=0.2; 95% CI=[0.04–1.00], while for DRB1*03:01 negative association was revealed only for systemic JIA (p = 0.03; OR=0.11; 95% CI=[0.01–0.88]). At the same time the DQB1*04:02:01 (p=0.026; OR=5.88; 95% CI=[1.20–28.72]) and DRB1*08:01:01 (p=0.07; OR=3.94; 95% CI=[1.01–15.39]) allele frequencies were significantly higher in patients with oligoarthritis but not systemic JIA when compared with controls.Conclusion:High-throughput HLA typing revealed distinct HLA-alleles associated with different JIA subtypes in the Belarusian population as well as some alleles protective both for oligoartricular and systemic JIA.Disclosure of Interests:None declared

scholarly journals Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis

BMC Genomics ◽  
2012 ◽  
Vol 13 (1) ◽  
pp. 43 ◽  
Author(s):  
Jing Tu ◽  
Qinyu Ge ◽  
Shengqin Wang ◽  
Lei Wang ◽  
Beili Sun ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Sample Analysis

Assessing Functional Language in School-Aged Children Using Language Sample Analysis

2020 ◽  
Vol 5 (3) ◽  
pp. 622-636
Author(s):  
John Heilmann ◽  
Alexander Tucci ◽  
Elena Plante ◽  
Jon F. Miller
Keyword(s):  
Computer Hardware ◽  
School Age Children ◽  
Functional Language ◽  
School Age ◽  
Clinical Use ◽  
Sample Analysis ◽  
Validity And Reliability ◽  
Language Sample Analysis ◽  
Accuracy And Repeatability ◽  
Language Sample

Purpose The goal of this clinical focus article is to illustrate how speech-language pathologists can document the functional language of school-age children using language sample analysis (LSA). Advances in computer hardware and software are detailed making LSA more accessible for clinical use. Method This clinical focus article illustrates how documenting school-age student's communicative functioning is central to comprehensive assessment and how using LSA can meet multiple needs within this assessment. LSA can document students' meaningful participation in their daily life through assessment of their language used during everyday tasks. The many advances in computerized LSA are detailed with a primary focus on the Systematic Analysis of Language Transcripts (Miller & Iglesias, 2019). The LSA process is reviewed detailing the steps necessary for computers to calculate word, morpheme, utterance, and discourse features of functional language. Conclusion These advances in computer technology and software development have made LSA clinically feasible through standardized elicitation and transcription methods that improve accuracy and repeatability. In addition to improved accuracy, validity, and reliability of LSA, databases of typical speakers to document status and automated report writing more than justify the time required. Software now provides many innovations that make LSA simpler and more accessible for clinical use. Supplemental Material https://doi.org/10.23641/asha.12456719

Issues in Language Sample Collection and Analysis With Children Using AAC

2014 ◽  
Vol 23 (2) ◽  
pp. 65-74 ◽  
Author(s):  
Gail Van Tatenhove
Keyword(s):  
Clinical Practice ◽  
Augmentative And Alternative Communication ◽  
Language Production ◽  
Expressive Language ◽  
Sample Analysis ◽  
Alternative Communication ◽  
Sample Collection ◽  
Speech Language Pathologists ◽  
Language Sample Analysis ◽  
Language Sample

Language sample analysis is considered one of the best methods of evaluating expressive language production in speaking children. However, the practice of language sample collection and analysis is complicated for speech-language pathologists working with children who use augmentative and alternative communication (AAC) devices. This article identifies six issues regarding use of language sample collection and analysis in clinical practice with children who use AAC devices. The purpose of this article is to encourage speech-language pathologists practicing in the area of AAC to utilize language sample collection and analysis as part of ongoing AAC assessment.

154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction

2007 ◽  
Vol 177 (4S) ◽  
pp. 52-53
Author(s):  
Stefano Ongarello ◽  
Eberhard Steiner ◽  
Regina Achleitner ◽  
Isabel Feuerstein ◽  
Birgit Stenzel ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mass Spectrometry ◽  
High Throughput ◽  
Mass Spectrometry Data ◽  
Cancer Prediction
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