Evidence map›Paper›PMID 40617875›Full record

ArticleCommunications biology2025

A modular fluorescent camera unit for wound imaging.

Maryam Tebyani, Gordon Keller, Wan Shen Hee, Prabhat Baniya, Alex Spaeth, Tiffany Nguyen, Harika Dechiraju, Anthony Gallegos, Héctor Carrión, Derek Hamersly and 11 more

Abstract read
In one paragraph

Article in Communications 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

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

21 authors.

Maryam TebyaniDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA. mtebyani@ucsc.edu.ORCID http://orcid.org/0000-0001-5477-2805
Gordon KellerDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
Wan Shen HeeDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.ORCID http://orcid.org/0000-0002-0871-8530
Prabhat BaniyaDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.ORCID http://orcid.org/0000-0002-5041-3407
Alex SpaethDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.ORCID http://orcid.org/0000-0003-0702-3945
Tiffany NguyenDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
Harika DechirajuDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
Anthony GallegosDepartment of Dermatology, School of Medicine, University of California Davis, Sacramento, CA, USA.
Héctor CarriónDepartment of Computer Science and Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.ORCID http://orcid.org/0009-0004-5750-2551
Derek HamerslySanta Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz, CA, USA.
Cristian HernandezDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
Alexie BarbeeDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.ORCID http://orcid.org/0009-0008-9446-3722
Hao-Chieh HsiehDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
Elham AslankoohiDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
Hsin-Ya YangDepartment of Dermatology, School of Medicine, University of California Davis, Sacramento, CA, USA.ORCID http://orcid.org/0000-0002-5325-494X
Narges NorouziDepartment of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, CA, USA.
Min ZhaoDepartment of Dermatology, School of Medicine, University of California Davis, Sacramento, CA, USA.ORCID http://orcid.org/0000-0002-2500-3035
Alexander SherSanta Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz, CA, USA.ORCID http://orcid.org/0000-0001-6655-6456
R Rivkah IsseroffDepartment of Dermatology, School of Medicine, University of California Davis, Sacramento, CA, USA.ORCID http://orcid.org/0000-0001-7813-0858
Marco RolandiDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA. mrolandi@ucsc.edu.ORCID http://orcid.org/0000-0001-7898-2479
Mircea TeodorescuDepartment of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, USA. mteodore@ucsc.edu.ORCID http://orcid.org/0000-0001-7085-5248

Funding

United States Department of Defense | Defense Advanced Research Projects Agency (DARPA) D20AC00003
6 · The paper itself

Abstract

Advanced imaging tools are revolutionizing the diagnosis, treatment, and monitoring of medical conditions, offering unprecedented insights into live cell behavior and biophysical markers. We introduce a modular, hand-held fluorescent microscope featuring rapid set-up and sub-millimeter resolution for real-time biological analysis. We apply our system to map pH and nitric oxide (NO), biomarkers central to wound healing, in subcutaneous wounds. Using machine learning to cluster pH reveals spatiotemporal trends, including a concentric gradient peaking at the center and stabilization at the wound edge. NO clustering shows high-concentration structures that decrease in size but intensify as healing progresses from hemostasis to proliferation, enabling prediction of the healing day and re-epithelialization. These biomarker mappings offer insights poised to inform future wound healing studies. This research lays the groundwork for integrating the modular imaging unit with bioelectronic devices in closed-loop feedback systems, using machine learning to guide optimal wound treatment and accelerate healing.

Indexed as

Wound HealingAnimalsBiomarkersHumansHydrogen-Ion ConcentrationMachine LearningMiceMicroscopy, FluorescenceNitric OxideBiomarkersNitric Oxide

Identifiers

PMID40617875
PMCPMC12228714

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.