Evidence map›Paper›PMID 35301348›Full record

ArticleScientific reports2022

Species identification of silks by protein mass spectrometry reveals evidence of wild silk use in antiquity.

Boyoung Lee, Elisabete Pires, A Mark Pollard, James S O McCullagh

Open access · greenAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 51% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

4 authors at 1 institution in 1 country.

Boyoung LeeDepartment of Chemistry, University of Oxford, Mansfield Road, Oxford, OX1 3TA, UK. bo0lee@outlook.com.
Elisabete PiresDepartment of Chemistry, University of Oxford, Mansfield Road, Oxford, OX1 3TA, UK.
A Mark PollardResearch Laboratory for Archaeology and the History of Art, University of Oxford, 1 South Parks Road, Oxford, OX1 3TG, UK.
James S O McCullaghDepartment of Chemistry, University of Oxford, Mansfield Road, Oxford, OX1 3TA, UK. james.mccullagh@chem.ox.ac.uk.
University of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Silk has been a luxurious commodity throughout modern human history and sericulture has played an important role in ancient global trade as well as technological and cultural developments. Archaeological findings suggest that prior to domestication of the mulberry silkworm (Bombyx mori) silks were obtained from a range of silk-producing moth species with regional specificity. However, investigating the origins of sericulture is difficult as classification of silks by species-type has proved technically challenging. We therefore investigated a range of methods for solubilising modern and archaeological silks and developed a mass spectrometry-based proteomics method that was able to successfully differentiate modern Bombyx, Antheraea, and Samia-produced silks down to the species level. We subsequently analysed archaeological silk materials excavated from the ancient city of Palmyra. Solubilisation behaviour and proteomic analysis provided evidence that the Palmyra silks were constructed from wild silk derived from Antheraea mylitta, the Indian Tasar silkworm. We believe this is the first species-level biochemical evidence that supports archaeological theories about the production and trade of Indian wild silks in antiquity.

Indexed as

BombyxMothsAnimalsMass SpectrometryProteomicsSilkSilk

Identifiers

PMID35301348
PMCPMC8931077
OpenAlexW4220929102

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.