Evidence map›Paper›PMID 42086049›Full record

ArticleCell reports methods2026

DRIFT-EM enables direct wafer retrieval of ultrathin serial sections for large-volume electron microscopy.

Nelson Medina, Joseph V Gogola, Kevin Boergens, Fuming Yang, Yaron Meirovitch, Jeff W Lichtman, Narayanan Kasthuri, Gregg Wildenberg

Abstract read
In one paragraph

Article in Cell reports methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Nelson MedinaMRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge CB2 0QH, MA, UK; Department of Neurobiology, The University of Chicago, Chicago IL 60637, USA; Argonne National Laboratory, Biosciences Division, Lemont IL 60439, USA.
Joseph V GogolaDepartment of Neurobiology, The University of Chicago, Chicago IL 60637, USA; Argonne National Laboratory, Biosciences Division, Lemont IL 60439, USA; Department of Medicine, The University of Chicago, Chicago IL 60637, USA.
Kevin BoergensDepartment of Neurobiology, The University of Chicago, Chicago IL 60637, USA; Department of Physics, University of Illinois Chicago, Chicago IL 60607, USA.
Fuming YangDepartment of Molecular and Cellular Biology, Harvard University, Cambridge MA 02138, USA.
Yaron MeirovitchDepartment of Molecular and Cellular Biology, Harvard University, Cambridge MA 02138, USA.
Jeff W LichtmanDepartment of Molecular and Cellular Biology, Harvard University, Cambridge MA 02138, USA.
Narayanan KasthuriDepartment of Neurobiology, The University of Chicago, Chicago IL 60637, USA; Argonne National Laboratory, Biosciences Division, Lemont IL 60439, USA.
Gregg WildenbergDepartment of Neurobiology, The University of Chicago, Chicago IL 60637, USA; Argonne National Laboratory, Biosciences Division, Lemont IL 60439, USA. Electronic address: gwildenberg@uchicago.edu.

Funding

BRAIN CONNECTS: Photoemission Electron Microscopy for ConnectomicsU01NS136401 · NINDS · UNIVERSITY OF CHICAGO · PI Kevin Michael Boergens, Narayanan Kasthuri · 2024 to 2026
$4.1M
NINDS NIH HHS U01 NS136401
6 · The paper itself

Abstract

Large-volume serial electron microscopy (vEM) has transformed neuroscience by enabling reconstructions of neural circuits at synaptic resolution. Approaches to collecting libraries of ultrathin sections required for producing vEM datasets have been devised (e.g., automated tape-collecting ultramicrotome [ATUM], MagC, and GAUSS-EM), which has advanced the scalability of vEM in distinct ways, yet widespread adoption remains constrained by cost, hardware requirements, or infrastructure demands. Here, we introduce direct retrieval by ionizer-facilitated transfer for electron microscopy (DRIFT-EM), a low-cost and easily implemented platform designed to broaden access to direct wafer-based collection of ultrathin sections. Off-the-shelf static ionizers clear newly cut sections from the knife edge, a thermoplastic boundary confines sections, and an open-source software pipeline automates region of interest identification to guide imaging. DRIFT-EM achieves section packing densities comparable to established magnetic methods, with minimal setup cost and maintenance. Its modular style, 3D-printed components, and open design facilitate integration with other vEM workflows, helping lower barriers to creating connectomes.

Indexed as

MicrotomyVolume Electron MicroscopyAnimalsSoftwarebrain mappingconnectomicsCP: biotechnologyCP: imaginglarge-volume serial electron microscopyultramicrotomyvEM

Identifiers

PMID42086049
PMCPMC13282653

What OpenQuestion holds

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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.