Evidence map›Paper›PMID 30534610›Full record

ArticleCommunications biology2018

Automated adherent cell elimination by a high-speed laser mediated by a light-responsive polymer.

Yohei Hayashi, Junichi Matsumoto, Shohei Kumagai, Kana Morishita, Long Xiang, Yohei Kobori, Seiji Hori, Masami Suzuki, Toshiyuki Kanamori, Kazuhiro Hotta and 1 more

Abstract read
In one paragraph

Article in Communications biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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

11 authors.

Yohei HayashiiPS Cell Advanced Characterization and Development Team, RIKEN Bioresource Research Center, 3-1-1 Koyadai, Tsukuba, Ibaraki 305-0074 Japan.
Junichi MatsumotoKataoka Corporation, 140 Tsukiyama-cho, Kuze, Minami-ku, Kyoto 601-8203 Japan.
Shohei Kumagai3Meijo University, 1-501 Shiogamaguchi, Tenpaku, Nagoya 468-8502 Japan.
Kana Morishita4Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba Central 5th, 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565 Japan.
Long XiangiPS Portal, Inc., 448-5 Kajii-cho, Kamigyo-ku, Kyoto 602-0841 Japan.
Yohei KoboriiPS Portal, Inc., 448-5 Kajii-cho, Kamigyo-ku, Kyoto 602-0841 Japan.
Seiji HoriiPS Portal, Inc., 448-5 Kajii-cho, Kamigyo-ku, Kyoto 602-0841 Japan.
Masami SuzukiKataoka Corporation, 140 Tsukiyama-cho, Kuze, Minami-ku, Kyoto 601-8203 Japan.
Toshiyuki Kanamori4Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba Central 5th, 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565 Japan.
Kazuhiro Hotta3Meijo University, 1-501 Shiogamaguchi, Tenpaku, Nagoya 468-8502 Japan.
Kimio Sumaru4Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba Central 5th, 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565 Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional cell handling and sorting methods require manual labor, which decreases both cell quality and quantity. To purify adherent cultured cells, cell purification technologies that are high throughput without dissociation and can be utilized in an on-demand manner are expected. Here, we developed a Laser-induced, Light-responsive-polymer-Activated, Cell Killing (LiLACK) system that enables high-speed and on-demand adherent cell sectioning and purification. This system employs a visible laser beam, which does not kill cells directly, but induces local heat production through the

Identifiers

PMID30534610
PMCPMC6286311

What OpenQuestion holds

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Registered trials

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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.