Evidence map›Paper›PMID 40894802›Full record

ArticlebioRxiv : the preprint server for biology2025

Synthetic Mucus Biomaterials Enable Localized Therapeutic Antibody Delivery in Inflammatory Bowel Disease.

Taj Yeruva, Sydney Yang, Michele Kaluzienski, Rebecca Louisthelmy, Shadin Doski, Katharina Maisel, Gregg A Duncan

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

7 authors.

Taj YeruvaFischell Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
Sydney YangFischell Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
Michele KaluzienskiFischell Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
Rebecca LouisthelmyFischell Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
Shadin DoskiFischell Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
Katharina MaiselFischell Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
Gregg A DuncanFischell Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.

Funding

Understanding alterations to mucus composition and function in asthmaR01HL160540 · NHLBI · UNIV OF MARYLAND, COLLEGE PARK · PI Gregg Duncan · 2022 to 2026
$2.1M
Synthetic mucus for local therapeutic deliveryR21EB030834 · NIBIB · UNIV OF MARYLAND, COLLEGE PARK · PI DUNCAN, GREGG, MAISEL, KATHARINA · 2021 to 2022
$382k
NHLBI NIH HHS R01 HL160540NIBIB NIH HHS R21 EB030834
6 · The paper itself

Abstract

Inflammatory bowel disease (IBD) is a chronic condition characterized by recurrent gastrointestinal inflammation that requires long-term therapeutic intervention. While anti-TNF-α monoclonal antibodies (mAbs) are effective in maintaining remission in IBD, systemic delivery is associated with immunosuppression, poor targeting efficiency, and high cost. To address these limitations, we developed a synthetic mucin-based hydrogel for localized delivery of TNF-α-targeting mAbs. Mucins are heavily glycosylated biopolymers that naturally bind antimicrobial and anti-inflammatory proteins, making them well-suited for local biologic drug delivery at mucosal sites. Synthetic mucin-based hydrogels were formed by crosslinking mucin harvested from porcine small intestine with a 4-arm PEG-thiol and loaded with mAbs to evaluate biocompatibility, antibody release kinetics, and therapeutic efficacy.

Identifiers

PMID40894802
PMCPMC12393339

What OpenQuestion holds

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LicenceCC BY-NC
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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.