Evidence map›Paper›PMID 41872457›Full record

ArticleNpj imaging2026

pan-ASLM: Axially Swept Light Sheet Microscopy for Fast and High-Resolution Imaging of Expanded Samples.

Hannahmariam T Mekbib, Lasse Pærgård Andersen, Shuwen Zhang, Jonathan Gulcicek, Yuan Tian, Jack R Ross, Mark D Lessard, Joerg Bewersdorf

Abstract read
In one paragraph

Article in Npj imaging, 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

8 authors.

Hannahmariam T MekbibDepartment of Biomedical Engineering, Yale University, New Haven, CT, USA.
Lasse Pærgård AndersenDepartment of Cell Biology, Yale School of Medicine, New Haven, CT, USA.
Shuwen ZhangDepartment of Cell Biology, Yale School of Medicine, New Haven, CT, USA.
Jonathan Gulcicekpanluminate Inc., New Haven, CT, USA.
Yuan TianDepartment of Cell Biology, Yale School of Medicine, New Haven, CT, USA.
Jack R RossDepartment of Physics, Yale University, New Haven, CT, USA.
Mark D LessardDepartment of Cell Biology, Yale School of Medicine, New Haven, CT, USA.
Joerg BewersdorfDepartment of Biomedical Engineering, Yale University, New Haven, CT, USA. joerg.bewersdorf@yale.edu.

Funding

Yale Cooperative Hematology Specialized Core CenterU54DK106857 · NIDDK · YALE UNIVERSITY · PI JOHN HWA, Diane S Krause · 2015 to 2026
$9.7M
A 3D super-resolved platform for rapid and highly multiplexed proteomicsR44MH128999 · NIMH · PANLUMINATE INC. · PI M'SAAD, ONS · 2024 to 2025
$1.9M
Development of a sample preparation protocol for 3D kidney ultrastructural analysis and immunolabeling by light microscopyR43DK137685 · NIDDK · PANLUMINATE INC. · PI M'SAAD, ONS · 2023 to 2023
$274k
NIDDK NIH HHS R43DK137685NIDDK NIH HHS U54 DK106857NIMH NIH HHS R44MH128999Novo Nordisk Fonden NNF20OC0059893
6 · The paper itself

Abstract

Expansion microscopy, a super-resolution fluorescence microscopy technique in which samples are expanded up to ~8000 times (after 20-fold expansion) their original volume, places high demands on the microscopes used to image the expanded samples. To reveal nanoscale cellular ultrastructure in meaningful sample volumes, the instruments need to feature a large field of view and working distance. Simultaneously, they need to offer a high three-dimensional resolution to avoid counteracting the resolution improvement achieved by the expansion process. Here, we present pan-ASLM, a high resolution, large field-of-view light-sheet microscope developed for expanded samples, based on the Axially Swept Light Sheet Microscopy (ASLM) technique. pan-ASLM allows imaging over a 640 x 640 µm

Identifiers

PMID41872457
PMCPMC13009474

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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.