Evidence map›Paper›PMID 25563515›Full record

ArticleBMC genomics2014

Time-course human urine proteomics in space-flight simulation experiments.

Hans Binder, Henry Wirth, Arsen Arakelyan, Kathrin Lembcke, Evgeny S Tiys, Vladimir A Ivanisenko, Nikolay A Kolchanov, Alexey Kononikhin, Igor Popov, Evgeny N Nikolaev and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.5field-weighted citation impact, top 4% of its field
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

13 citing papers in PubMed, 41 citations in OpenAlex.

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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

12 authors at 7 institutions in 3 countries.

Hans Binder
Henry Wirth
Arsen Arakelyan
Kathrin Lembcke
Evgeny S Tiys
Vladimir A Ivanisenko
Nikolay A Kolchanov
Alexey Kononikhin
Igor Popov
Evgeny N Nikolaev
Lyudmila Pastushkova
Irina M Larina
Leipzig University · DESiberian Branch of the Russian Academy of Sciences · RUInstitute of Biomedical Problems · RUInstitute of Biochemical Physics NM Emanuel · RUInstitute of Energy Problems of Chemical Physics · RUMoscow Institute of Physics and Technology · RUNational Academy of Sciences of Armenia · AM

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong-term space travel simulation experiments enabled to discover different aspects of human metabolism such as the complexity of NaCl salt balance. Detailed proteomics data were collected during the Mars105 isolation experiment enabling a deeper insight into the molecular processes involved.

resultsWe studied the abundance of about two thousand proteins extracted from urine samples of six volunteers collected weekly during a 105-day isolation experiment under controlled dietary conditions including progressive reduction of salt consumption. Machine learning using Self Organizing maps (SOM) in combination with different analysis tools was applied to describe the time trajectories of protein abundance in urine. The method enables a personalized and intuitive view on the physiological state of the volunteers. The abundance of more than one half of the proteins measured clearly changes in the course of the experiment. The trajectory splits roughly into three time ranges, an early (week 1-6), an intermediate (week 7-11) and a late one (week 12-15). Regulatory modes associated with distinct biological processes were identified using previous knowledge by applying enrichment and pathway flow analysis. Early protein activation modes can be related to immune response and inflammatory processes, activation at intermediate times to developmental and proliferative processes and late activations to stress and responses to chemicals.

conclusionsThe protein abundance profiles support previous results about alternative mechanisms of salt storage in an osmotically inactive form. We hypothesize that reduced NaCl consumption of about 6 g/day presumably will reduce or even prevent the activation of inflammatory processes observed in the early time range of isolation. SOM machine learning in combination with analysis methods of class discovery and functional annotation enable the straightforward analysis of complex proteomics data sets generated by means of mass spectrometry.

Indexed as

Space FlightAdultArtificial IntelligenceAstronautsComputer SimulationHumansMaleProteomeProteomicsUrineProteome

Identifiers

PMID25563515
PMCPMC4303941
OpenAlexW1595057305

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.