Evidence map›Paper›PMID 33954952›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2021

Analytical Methodologies for Lipidomics in Hemp Plant.

Andrea Cerrato, Anna Laura Capriotti, Carmela Maria Montone, Sara Elsa Aita, Giuseppe Cannazza, Cinzia Citti, Susy Piovesana, Laganà Aldo

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Nutrients and Bioactive Compounds fromInternational journal of molecular sciences · 2025
    Review
  2. Analysis of Polar Lipids in Hemp (Molecules (Basel, Switzerland) · 2022
    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

8 authors.

Andrea CerratoDepartment of Chemistry, Università di Roma "La Sapienza", Rome, Italy.
Anna Laura CapriottiDepartment of Chemistry, Università di Roma "La Sapienza", Rome, Italy.
Carmela Maria MontoneDepartment of Chemistry, Università di Roma "La Sapienza", Rome, Italy. carmelamaria.montone@uniroma1.it.
Sara Elsa AitaDepartment of Chemistry, Università di Roma "La Sapienza", Rome, Italy.
Giuseppe CannazzaDepartment of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Cinzia CittiDepartment of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Susy PiovesanaDepartment of Chemistry, Università di Roma "La Sapienza", Rome, Italy.
Laganà AldoDepartment of Chemistry, Università di Roma "La Sapienza", Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The chemical composition of Cannabis sativa L. has been extensively studied for tens of years, but little is known about its lipidome. This chapter describes an analytical workflow for polar lipid determination in hemp. After extraction, lipids are enriched and isolated by graphitized carbon black sorbent, and the isolated lipid is analyzed by liquid chromatography (LC) coupled with high resolution mass spectrometry, leading to identification of many lipid species. We have developed a semi-automated platform using commercially available Lipostar software for lipid identification. Our approach affords the identification of 189 polar lipids in hemp extract, including sulfolipids and phospholipids. The number of the identified lipid species is by far the highest ever reported for Cannabis sativa.

Indexed as

Automation, LaboratoryCannabisChromatography, High Pressure LiquidLipidomicsLipidsMass SpectrometryPhospholipidsSoftwareLipidsPhospholipidssulfolipidsCannabis sativaGraphitized carbon blackLipidomicsLipostarPhospholipidsSulfolipids

Identifiers

PMID33954952

What OpenQuestion holds

Textmetadata
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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.