Evidence map›Paper›PMID 30800340›Full record

ArticleRoyal Society open science2019

A yeast metabolome-based model for an ecotoxicological approach in the management of lignocellulosic ethanol stillage.

Luca Roscini, Lorenzo Favaro, Laura Corte, Lorenzo Cagnin, Claudia Colabella, Marina Basaglia, Gianluigi Cardinali, Sergio Casella

Abstract read
In one paragraph

Article in Royal Society open science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Metabolomic and Proteomic Changes inInternational journal of molecular sciences · 2022
    Article
  2. Article
  3. Article
  4. 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.

Luca RosciniDepartment of Pharmaceutical Sciences-Microbiology, CEMIN, Centre of Excellence on Nanostructured Innovative Materials, University of Perugia, Perugia, Italy.
Lorenzo FavaroDepartment of Agronomy Food Natural resources Animals and Environment (DAFNAE), University of Padova, Legnaro, Italy.ORCID 0000-0002-5650-4422
Laura CorteDepartment of Pharmaceutical Sciences-Microbiology, CEMIN, Centre of Excellence on Nanostructured Innovative Materials, University of Perugia, Perugia, Italy.
Lorenzo CagninDepartment of Agronomy Food Natural resources Animals and Environment (DAFNAE), University of Padova, Legnaro, Italy.
Claudia ColabellaDepartment of Pharmaceutical Sciences-Microbiology, CEMIN, Centre of Excellence on Nanostructured Innovative Materials, University of Perugia, Perugia, Italy.
Marina BasagliaDepartment of Agronomy Food Natural resources Animals and Environment (DAFNAE), University of Padova, Legnaro, Italy.
Gianluigi CardinaliDepartment of Pharmaceutical Sciences-Microbiology, CEMIN, Centre of Excellence on Nanostructured Innovative Materials, University of Perugia, Perugia, Italy.
Sergio CasellaDepartment of Agronomy Food Natural resources Animals and Environment (DAFNAE), University of Padova, Legnaro, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lignocellulosic bioethanol production results in huge amounts of stillage, a potentially polluting by-product. Stillage, rich in heavy metals and, mainly, inhibitors, requires specific toxicity studies to be adequately managed. To this purpose, we applied an FTIR ecotoxicological bioassay to evaluate the toxicity of lignocellulosic stillage. Two weak acids and furans, most frequently found in lignocellulosic stillage, have been tested in different mixtures against three

Indexed as

FTIRlignocellulosic stillagemodellingSaccharomyces cerevisiaestress response

Identifiers

PMID30800340
PMCPMC6366221

What OpenQuestion holds

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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.