Evidence map›Paper›PMID 41112526›Full record

ArticleJournal of manufacturing science and engineering2025

Data-Driven Optimization of Bioink Formulations for Extrusion-Based Bioprinting: A Predictive Modeling Approach.

Rokeya Sarah, Riley Rohauer, Kory Schimmelpfennig, Shah M Limon, Christopher L Lewis, Ahasan Habib

Abstract read
In one paragraph

Article in Journal of manufacturing science and engineering, 2025. 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. Review
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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

6 authors.

Rokeya SarahDepartment of Sustainable Product Design and Architecture, Keene State College, 229 Main Street, Keene, NH 03435.
Riley RohauerDepartment of Biomedical Engineering, Rochester Institute of Technology, 70 Lomb Memorial Drive, Rochester, NY 14623.
Kory SchimmelpfennigDepartment of Manufacturing and Mechanical Engineering Technology, Rochester Institute of Technology, 70 Lomb Memorial Drive, Rochester, NY 14623.
Shah M LimonDepartment of Engineering, Slippery Rock University, 104 E Vincent Science Center, Slippery Rock, PA 16075.
Christopher L LewisDepartment of Manufacturing and Mechanical Engineering Technology, Rochester Institute of Technology, 70 Lomb Memorial Drive, Rochester, NY 14623.
Ahasan HabibDepartment of Manufacturing and Mechanical Engineering Technology, Rochester Institute of Technology, 70 Lomb Memorial Drive, Rochester, NY 14623.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The field of tissue engineering has significantly advanced with the development of extrusion-based bioprinting. This technique utilizes shear forces to generate filaments for fabricating intricate structures. The printability and structural integrity of bioprinted constructs rely heavily on the rheological properties of bioinks, particularly viscosity, which varies with the shear rate for non-Newtonian materials. Since the shear rate at the nozzle tip fluctuates during extrusion, it is essential to understand how bioink composition influences this behavior. This study investigates the rheological behavior of ALGEC bioinks, a novel formulation composed of ALginate, GElatin, and 2,2,6,6-Tetramethylpiperidine 1-oxyl (TEMPO)-oxidized nanofibrillated cellulose (TO-NFC). The bioinks were prepared with varying concentrations: alginate (0-5.25%), gelatin (0-5.25%), and TO-NFC (0-1.5%), with a maximum total solid content of 8%. Viscosity was conducted over shear rates ranging from 0.1 to 100 s

Indexed as

3D bioprintingadditive manufacturingadvanced materials and processingbiomedical manufacturingCAD/CAM/CAEhydrogelmachine learningmultiple regressionpolynomial fitprint-parametersrapid prototyping and solid freeform fabrication

Identifiers

PMID41112526
PMCPMC12533942

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Registered trials

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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.