Evidence map›Paper›PMID 27234395›Full record

ArticleTranslational respiratory medicine2013

Standardization developments for large scale biobanks in smoking related diseases - a model system for blood sample processing and storage.

Johan Malm, Thomas E Fehniger, Pia Danmyr, Ákos Végvári, Charlotte Welinder, Henrik Lindberg, Paul Upton, Stephanie Carter, Roger Appelqvist, Karin Sjödin and 5 more

Abstract read
In one paragraph

Article in Translational respiratory medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Johan MalmDepartment of Laboratory Medicine, Section for Clinical Chemistry, Lund University, Skåne University Hospital in Malmö, Malmö, 205 02, Sweden.
Thomas E FehnigerClinical Protein Science & Imaging, Biomedical Center, Dept. of Measurement Technology and Industrial Electrical Engineering, Lund University, BMC C13, 221 84, Lund, Sweden.
Pia DanmyrRegion Skåne R&D Center, Region Skåne, 221 85, Lund, Sweden.
Ákos VégváriClinical Protein Science & Imaging, Biomedical Center, Dept. of Measurement Technology and Industrial Electrical Engineering, Lund University, BMC C13, 221 84, Lund, Sweden.
Charlotte WelinderDepartment of Oncology, Clinical Sciences, Lund University, 221 85, Lund, Sweden.
Henrik LindbergRegion Skåne Biobank, Skåne University Hospital, 221 85, Lund, Sweden.
Paul UptonThermo Fisher Scientific, Stafford House, 1 Boundary Park, Hemel Hempstead, Hertfordshire, HP2 7GE, UK.
Stephanie CarterThermo Fisher Scientific, Rochester, MA, 14625, USA.
Roger AppelqvistClinical Protein Science & Imaging, Biomedical Center, Dept. of Measurement Technology and Industrial Electrical Engineering, Lund University, BMC C13, 221 84, Lund, Sweden.
Karin SjödinRegion Skåne R&D Center, Region Skåne, 221 85, Lund, Sweden.
Elisabet WieslanderDepartment of Oncology, Clinical Sciences, Lund University, 221 85, Lund, Sweden.
Magnus DahlbäckRespiratory and Inflammation Therapy Area, Astra Zeneca R&D, 431 83, Mölndal, Sweden.
Melinda RezeliClinical Protein Science & Imaging, Biomedical Center, Dept. of Measurement Technology and Industrial Electrical Engineering, Lund University, BMC C13, 221 84, Lund, Sweden.
David ErlingeDepartment of Cardiology, Lund University, Skåne University Hospital, 221 85, Lund, Sweden.
György Marko-VargaClinical Protein Science & Imaging, Biomedical Center, Dept. of Measurement Technology and Industrial Electrical Engineering, Lund University, BMC C13, 221 84, Lund, Sweden. gyorgy.marko-varga@elmat.lth.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiobank samples stored in biobanks give researchers and respiratory healthcare institutions access to datasets of analytes valuable for both diagnostic and research practices. The usefulness of these samples in clinical decision-making is highly dependent on their quality and integrity. New procedures that better preserve sample integrity and reduce degradation are being developed to meet the needs of both present and future biobanking. Hereby we present an automatic sample workflow scheme that is designed to handle high numbers of blood samples.

methodsBlood fractions are aliquoted, heat sealed using novel technology, and stored in 384 tube high-density sample arrays.

resultsThe newly developed 384 biobank rack system is especially suited for preserving identical small aliquots. We provide data on robotic processing of clinical samples at -80°C, following initial processing, analysis and shipping between laboratories throughout Europe. Subsequent to unpacking, re-sorting, and storage at these sites, the samples have been returned for analysis. Biomarker analysis of 13 common tests in the clinical chemistry unit of the hospital provides evidence of qualitative and stable logistics using the 384-sample tube system.

conclusionsThis technology development allows rapid access to a given sample in the frozen archive while maintaining individual sample integrity with sample tube confinement and quality management.

Indexed as

BiobankBiomarkersRespiratory diseasesRoboticsStandardization

Identifiers

PMID27234395
PMCPMC6733428

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.