Evidence map›Paper›PMID 30612036›Full record

ArticleiScience2019

Profiling Single Cancer Cells with Volatolomics Approach.

Mamatha Serasanambati, Yoav Y Broza, Abraham Marmur, Hossam Haick

Open access · goldAbstract read
In one paragraph

Article in iScience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Observational
  5. Observational
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Profiles of Volatile Biomarkers Detect Tuberculosis from Skin.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021
    Article
  12. Induced volatolomics of pathologies.Nature reviews. Chemistry · 2021
    Review
  13. Sample Introduction Method in Gas Chromatography.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2021
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
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.

Mamatha SerasanambatiDepartment of Chemical Engineering, Technion - Israel Institute of Technology, Technion City, Haifa 3200003, Israel.
Yoav Y BrozaDepartment of Chemical Engineering, Technion - Israel Institute of Technology, Technion City, Haifa 3200003, Israel.
Abraham MarmurDepartment of Chemical Engineering, Technion - Israel Institute of Technology, Technion City, Haifa 3200003, Israel.
Hossam HaickDepartment of Chemical Engineering, Technion - Israel Institute of Technology, Technion City, Haifa 3200003, Israel; Russell Berries Nanotechnology Institute, Technion - Israel Institute of Technology, Technion City, Haifa 3200003, Israel; Technion Integrated Cancer Center, The Ruth and Bruce Rappaport Faculty of Medicine, 1 Efron St. Bat Galim, Haifa 3525433, Israel. Electronic address: hhossam@technion.ac.il.
Technion – Israel Institute of Technology · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell analysis is a rapidly evolving to characterize molecular information at the individual cell level. Here, we present a new approach with the potential to overcome several key challenges facing the currently available techniques. The approach is based on the identification of volatile organic compounds (VOCs), viz. organic compounds having relatively high vapor pressure, emitted to the cell's headspace. This concept is demonstrated using lung cancer cells with various p53 genetic status and normal lung cells. The VOCs were analyzed by gas chromatography combined with mass spectrometry. Among hundreds of detected compounds, 18 VOCs showed significant changes in their concentration levels in tumor cells versus control. The composition of these VOCs was found to depend, also, on the sub-molecular structure of the p53 genetic status. Analyzing the VOCs offers a complementary way of querying the molecular mechanisms of cancer as well as of developing new generation(s) of biomedical approaches for personalized screening and diagnosis.

Indexed as

Analytical ChemistryBiological SciencesCancer Systems BiologySensor

Identifiers

PMID30612036
PMCPMC6319329
OpenAlexW2904608049

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.