Evidence map›Paper›PMID 41928986›Full record

ArticlebioRxiv : the preprint server for biology2026

Gradient Multinozzle 3D Printing.

Luca Rosalia, Soham Sinha, Jonathan D Weiss, Senming Hsia, Fredrik S Solberg, Amit Sharir, Masufumi Shibata, Jianyi Du, Katelyn Mosle, Dominic Rütsche and 10 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

Luca RosaliaDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0000-0002-7214-7859
Soham SinhaDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0000-0001-8598-0543
Jonathan D WeissDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.
Senming HsiaDepartment of Mechanical Engineering, University of California Irvine, Irvine, CA, 92697, United States.
Fredrik S SolbergDepartment of Mechanical Engineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0009-0005-9737-0095
Amit SharirDepartment of Cardiothoracic Surgery, School of Medicine, Stanford University, Stanford, CA, 94035, United States.ORCID 0009-0008-2049-3179
Masufumi ShibataDepartment of Cardiothoracic Surgery, School of Medicine, Stanford University, Stanford, CA, 94035, United States.
Jianyi DuDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0000-0001-9838-6308
Katelyn MosleDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.
Dominic RütscheDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0000-0001-6394-201X
Zi Chang RaoDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0009-0009-9430-4331
Tony TamBasic Science and Engineering Initiative, Children's Heart Center, Stanford University, Stanford, CA, 94035, United States.ORCID 0000-0002-0288-5434
Trenton RankinNew Human Research, Palo Alto, CA, 94306, United States.
Qiuling WangDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.
Christian M WilliamsDepartment of Materials Science and Engineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0009-0004-1326-5275
John H KlichDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0000-0002-9285-1018
Alexander K ReedDepartment of Cardiothoracic Surgery, School of Medicine, Stanford University, Stanford, CA, 94035, United States.ORCID 0000-0002-5235-9483
Eric A AppelDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0000-0002-2301-7126
Michael MaDepartment of Cardiothoracic Surgery, School of Medicine, Stanford University, Stanford, CA, 94035, United States.
Mark A Skylar-ScottDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, United States.ORCID 0000-0003-3496-7124

Funding

Trillion cell culture to fuel organ biofabricationDP2HL168563 · NHLBI · STANFORD UNIVERSITY · PI SKYLAR-SCOTT, MARK A. · 2022 to 2025
$2.4M
NHLBI NIH HHS DP2 HL168563
6 · The paper itself

Abstract

Direct ink writing is compatible with an expansive materials palette. While enabling diverse applications, this materials versatility brings significant bottlenecks in ink formulation, often requiring the mixing, printing, and testing of dozens to hundreds of ink compositions over the course of a project. To accelerate ink-space exploration, we introduce gradient embedded multinozzle (GEM) printheads that combine the high-throughput parallelized printing of multinozzles with combinatorial ink mixing. These printheads allow simultaneous mixing of two-, three-, and four-input inks which are distributed to printer nozzles to create complex 3D structures with graded compositions of inks. Using a two-way GEM printhead, we validate cell compatibility by printing scaffolds containing various concentrations of fibroblasts and observing non-linear compaction behaviours. We next test a three-way GEM multinozzle to print ten compositions of di- and multi-functionalized poly(ethylene-glycol) diacrylate hydrogel tri-leaflet valves, optimizing for stiffness, swelling ratio, and toughness. Our GEM multinozzles are compatible with open-source printers and either pressure- or volume-driven extrusion systems and promise to accelerate iterative ink design and testing.

Identifiers

PMID41928986
PMCPMC13042057

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.