Evidence map›Paper›PMID 40140476›Full record

ArticleScientific reports2025

Pilot-scale high-consistency mechanical refining improves enzymatic saccharification of lignocellulosic feedstock.

Liliane Pires Andrade, Maria Isabel Rodrigues, Mário Tyago Murakami, George Jackson de Moraes Rocha

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

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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.

Liliane Pires AndradeBrazilian Center for Research in Energy and Materials, Brazilian Biorenewables National Laboratory (LNBR), Campinas, SP, Brazil.
Maria Isabel RodriguesProtimiza Consulting and Training in Experimental Design and Process Optimization, Campinas, SP, Brazil.
Mário Tyago MurakamiBrazilian Center for Research in Energy and Materials, Brazilian Biorenewables National Laboratory (LNBR), Campinas, SP, Brazil. mario.murakami@lnbr.cnpem.br.
George Jackson de Moraes RochaBrazilian Center for Research in Energy and Materials, Brazilian Biorenewables National Laboratory (LNBR), Campinas, SP, Brazil. george.rocha@lnbr.cnpem.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The natural recalcitrance of lignocellulosic biomass poses a major challenge for biorefineries aiming to convert these materials into fuels, chemicals, and polymers. This study explored the impact of pilot-scale high-consistency mechanical refining on the enzymatic depolymerization of lignocellulosic biomass when associated with low-severity hydrothermal (HPTB) and steam explosion (SEPTB) pretreatments, 180 °C for 15 min and 190 °C for 10 min respectively. Under industrially relevant conditions and using sugarcane bagasse as model lignocellulosic feedstock, we observed that the mechanical refining had a distinct effect on the fiber morphology depending on the pretreatment process. While statistical analyses indicated no correlation between refining parameters and saccharification efficiency for HPTB, an 8% increase in glucose release was observed for SEPTB with mechanical refining. Scanning electron microscopy revealed enhanced fiber morphology and delamination in SEPTB material after mechanical refining, suggesting increased porosity and accessibility for enzymes. Furthermore, distinct chemical compositions were observed between HPTB and SEPTB materials, aligning with the distinct responses to mechanical refining. These findings highlight the potential of combining mechanical refining with steam explosion pretreatment to improve the enzymatic depolymerization of lignocellulosic biomass, advancing the current knowledge on the application and challenges of high-consistency mechanical refining in lignocellulosic biorefineries.

Indexed as

CellulaseLigninBiomassCelluloseGlucoseHydrolysisPilot ProjectsSaccharumSteambagasseCellulaseCelluloseGlucoseLigninlignocelluloseSteamEnzymatic saccharificationFiber morphologyMechanical refiningPilot-scaleSugarcane bagasse

Identifiers

PMID40140476
PMCPMC11947289

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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.