Evidence map›Paper›PMID 39893176›Full record

ReviewNature communications2025

Advances in lignocellulosic feedstocks for bioenergy and bioproducts.

Daniel B Sulis, Nathalie Lavoine, Heike Sederoff, Xiao Jiang, Barbara M Marques, Kai Lan, Carlos Cofre-Vega, Rodolphe Barrangou, Jack P Wang

Abstract readReview
In one paragraph

Review in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing 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

46 citing papers in PubMed.

  1. Synthetic and systems biotechnology · 2026
    Article
  2. Review
  3. Screening and ARTP mutagenesis-based breeding of high-cellulase-producing strains.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2026
    Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Precision Lignocellulosic Biorefinery: Process Regulation From Corn Stover to Products.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  12. Review
  13. Review
  14. Nanomaterial Integration at Liquid-Liquid Interfaces for Green Catalysis.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. 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

9 authors.

Daniel B SulisTreeCo, Raleigh, NC, USA.ORCID http://orcid.org/0000-0002-6657-9567
Nathalie LavoineDepartment of Forest Biomaterials, North Carolina State University, Raleigh, NC, USA.ORCID http://orcid.org/0000-0002-8259-4070
Heike SederoffDepartment of Plant and Microbial Biology, North Carolina State University, Raleigh, NC, USA.ORCID http://orcid.org/0000-0002-0960-9678
Xiao JiangDepartment of Forest Biomaterials, North Carolina State University, Raleigh, NC, USA.ORCID http://orcid.org/0000-0001-7659-2004
Barbara M MarquesTreeCo, Raleigh, NC, USA.ORCID http://orcid.org/0000-0002-1427-6556
Kai LanDepartment of Forest Biomaterials, North Carolina State University, Raleigh, NC, USA.ORCID http://orcid.org/0000-0002-4622-6326
Carlos Cofre-VegaTreeCo, Raleigh, NC, USA.
Rodolphe BarrangouTreeCo, Raleigh, NC, USA. rbarran@ncsu.edu.ORCID http://orcid.org/0000-0002-0648-3504
Jack P WangTreeCo, Raleigh, NC, USA. jpwang@ncsu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lignocellulose, an abundant renewable resource, presents a promising alternative for sustainable energy and industrial applications. However, large-scale adoption of lignocellulosic feedstocks faces considerable obstacles, including scalability, bioprocessing efficiency, and resilience to climate change. This Review examines current efforts and future opportunities for leveraging lignocellulosic feedstocks in bio-based energy and products, with a focus on enhancing conversion efficiency and scalability. It also explores emerging biotechnologies such as CRISPR-based genome editing informed by machine learning, aimed at improving feedstock traits and reducing the environmental impact of fossil fuel dependence.

Indexed as

BiofuelsBiotechnologyLigninBiomassClimate ChangeGene EditingMachine LearningBiofuelsLigninlignocellulose

Identifiers

PMID39893176
PMCPMC11787297

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.