Dataset Information

Effective High-Throughput Blood Pooling Strategy before DNA Extraction for Detection of Malaria in Low-Transmission Settings.

ABSTRACT: In the era of (pre) elimination setting, the prevalence of malaria has been decreasing in most of the previously endemic areas. Therefore, effective cost- and time-saving validated pooling strategy is needed for detection of malaria in low transmission settings. In this study, optimal pooling numbers and lowest detection limit were assessed using known density samples prepared systematically, followed by genomic DNA extraction and nested PCR. Pooling strategy that composed of 10 samples in 1 pool, 20 µl in 1 sample, was optimal, and the parasite density as low as 2 p/µl for both falciparum and vivax infection was enough for detection of malaria. This pooling method showed effectiveness for handling of a huge number of samples in low transmission settings (<9% positive rate). The results indicated that pooling of the blood samples before DNA extraction followed by usual nested PCR is useful and effective for detection of malaria in screening of hidden cases in low-transmission settings.

SUBMITTER: Nyunt MH

PROVIDER: S-EPMC4977795 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Publications

Effective High-Throughput Blood Pooling Strategy before DNA Extraction for Detection of Malaria in Low-Transmission Settings.

Nyunt Myat Htut MH Kyaw Myat Phone MP Thant Kyaw Zin KZ Shein Thinzer T Han Soe Soe SS Zaw Ni Ni NN Han Jin-Hee JH Lee Seong-Kyun SK Muh Fauzi F Kim Jung-Yeon JY Cho Shin-Hyeong SH Lee Sang-Eun SE Yang Eun-Jeong EJ Chang Chulhun L CL Han Eun-Taek ET

The Korean journal of parasitology 20160630 3

In the era of (pre) elimination setting, the prevalence of malaria has been decreasing in most of the previously endemic areas. Therefore, effective cost- and time-saving validated pooling strategy is needed for detection of malaria in low transmission settings. In this study, optimal pooling numbers and lowest detection limit were assessed using known density samples prepared systematically, followed by genomic DNA extraction and nested PCR. Pooling strategy that composed of 10 samples in 1 poo ...[more]

PMID: 27417078

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Project description:BackgroundA key goal of drug discovery is to increase the throughput of small molecule screens without sacrificing screening accuracy. High-throughput screening (HTS) in drug discovery involves testing a large number of compounds in a biological assay to identify active compounds. Normally, molecules from a large compound library are tested individually to identify the activity of each molecule. Usually a small number of compounds are found to be active, however the presence of false positive and negative testing errors suggests that this one-drug one-assay screening strategy can be significantly improved. Pooling designs are testing schemes that test mixtures of compounds in each assay, thereby generating a screen of the whole compound library in fewer tests. By repeatedly testing compounds in different combinations, pooling designs also allow for error-correction. These pooled designs, for specific experiment parameters, can be simply and efficiently created using the Shifted Transversal Design (STD) pooling algorithm. However, drug screening contains a number of key constraints that require specific modifications if this pooling approach is to be useful for practical screen designs.ResultsIn this paper, we introduce a pooling strategy called poolHiTS (Pooled High-Throughput Screening) which is based on the STD algorithm. In poolHiTS, we implement a limit on the number of compounds that can be mixed in a single assay. In addition, we show that the STD-based pooling strategy is limited in the error-correction that it can achieve. Due to the mixing constraint, we show that it is more efficient to split a large library into smaller blocks of compounds, which are then tested using an optimized strategy repeated for each block. We package the optimal block selection algorithm into poolHiTS. The MATLAB codes for the poolHiTS algorithm and the corresponding decoding strategy are also provided.ConclusionWe have produced a practical version of STD algorithm for pooled drug screens. This pooling strategy provides both assay compression and error-correction capabilities that can both accelerate and reduce the overall cost of HTS in drug discovery.

Project description:The availability of annotated corpora has facilitated the application of machine learning algorithms to concept extraction from clinical notes. However, high expenditure and labor are required for creating the annotations. A potential alternative is to reuse existing corpora from other institutions by pooling with local corpora, for training machine taggers. In this paper we have investigated the latter approach by pooling corpora from 2010 i2b2/VA NLP challenge and Mayo Clinic Rochester, to evaluate taggers for recognition of medical problems. The corpora were annotated for medical problems, but with different guidelines. The taggers were constructed using an existing tagging system MedTagger that consisted of dictionary lookup, part of speech (POS) tagging and machine learning for named entity prediction and concept extraction. We hope that our current work will be a useful case study for facilitating reuse of annotated corpora across institutions.We found that pooling was effective when the size of the local corpus was small and after some of the guideline differences were reconciled. The benefits of pooling, however, diminished as more locally annotated documents were included in the training data. We examined the annotation guidelines to identify factors that determine the effect of pooling.The effectiveness of pooling corpora, is dependent on several factors, which include compatibility of annotation guidelines, distribution of report types and size of local and foreign corpora. Simple methods to rectify some of the guideline differences can facilitate pooling. Our findings need to be confirmed with further studies on different corpora. To facilitate the pooling and reuse of annotated corpora, we suggest that - i) the NLP community should develop a standard annotation guideline that addresses the potential areas of guideline differences that are partly identified in this paper; ii) corpora should be annotated with a two-pass method that focuses first on concept recognition, followed by normalization to existing ontologies; and iii) metadata such as type of the report should be created during the annotation process.

Dataset Information

Effective High-Throughput Blood Pooling Strategy before DNA Extraction for Detection of Malaria in Low-Transmission Settings.

Publications

Effective High-Throughput Blood Pooling Strategy before DNA Extraction for Detection of Malaria in Low-Transmission Settings.

Similar Datasets

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