Evidence map›Paper›PMID 28708412›Full record

ArticleAstrobiology2017

Digital Holographic Microscopy, a Method for Detection of Microorganisms in Plume Samples from Enceladus and Other Icy Worlds.

Manuel Bedrossian, Chris Lindensmith, Jay L Nadeau

Abstract read
In one paragraph

Article in Astrobiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. The Ladder of Life Detection.Astrobiology · 2018
    Article
  9. Article
  10. Article
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

3 authors.

Manuel Bedrossian1 Graduate Aerospace Laboratories (GALCIT) and Medical Engineering, California Institute of Technology , Pasadena, California.
Chris Lindensmith2 Jet Propulsion Laboratory, California Institute of Technology , Pasadena, California.
Jay L Nadeau1 Graduate Aerospace Laboratories (GALCIT) and Medical Engineering, California Institute of Technology , Pasadena, California.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detection of extant microbial life on Earth and elsewhere in the Solar System requires the ability to identify and enumerate micrometer-scale, essentially featureless cells. On Earth, bacteria are usually enumerated by culture plating or epifluorescence microscopy. Culture plates require long incubation times and can only count culturable strains, and epifluorescence microscopy requires extensive staining and concentration of the sample and instrumentation that is not readily miniaturized for space. Digital holographic microscopy (DHM) represents an alternative technique with no moving parts and higher throughput than traditional microscopy, making it potentially useful in space for detection of extant microorganisms provided that sufficient numbers of cells can be collected. Because sample collection is expected to be the limiting factor for space missions, especially to outer planets, it is important to quantify the limits of detection of any proposed technique for extant life detection. Here we use both laboratory and field samples to measure the limits of detection of an off-axis digital holographic microscope (DHM). A statistical model is used to estimate any instrument's probability of detection at various bacterial concentrations based on the optical performance characteristics of the instrument, as well as estimate the confidence interval of detection. This statistical model agrees well with the limit of detection of 10

Identifiers

PMID28708412
PMCPMC5610429

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.