Evidence map›Paper›PMID 37333319›Full record

ArticlebioRxiv : the preprint server for biology2023

A semiconductor 96-microplate platform for electrical-imaging based high-throughput phenotypic screening.

Shalaka Chitale, Wenxuan Wu, Avik Mukherjee, Herbert Lannon, Pooja Suresh, Ishan Nag, Christina M Ambrosi, Rona S Gertner, Hendrick Melo, Brendan Powers and 10 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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

20 authors.

Shalaka Chitale
Wenxuan Wu
Avik Mukherjee
Herbert Lannon
Pooja Suresh
Ishan Nag
Christina M Ambrosi
Rona S Gertner
Hendrick Melo
Brendan Powers
Hollin Wilkins
Henry Hinton
Mickey Cheah
Zachariah Boynton
Alexander Alexeyev
Duane Sword
Markus Basan
Hongkun Park
Donhee Ham
Jeffrey Abbott

Funding

Elucidating physiology of dormant bacteria to combat antibiotic persistenceR35GM137895 · NIGMS · HARVARD MEDICAL SCHOOL · PI Markus Thomas Basan · 2020 to 2026
$3.2M
NIGMS NIH HHS R35 GM137895
6 · The paper itself

Abstract

Profiling compounds and genetic perturbations via high-content imaging has become increasingly popular for drug discovery, but the technique is limited to endpoint images of fixed cells. In contrast, electronic-based devices offer label-free, functional information of live cells, yet current approaches suffer from low-spatial resolution or single-well throughput. Here, we report a semiconductor 96-microplate platform designed for high-resolution real-time impedance "imaging" at scale. Each well features 4,096 electrodes at 25 µm spatial resolution while a miniaturized data interface allows 8× parallel plate operation (768 total wells) within each incubator for enhanced throughputs. New electric field-based, multi-frequency measurement techniques capture >20 parameter images including tissue barrier, cell-surface attachment, cell flatness, and motility every 15 min throughout experiments. Using these real-time readouts, we characterized 16 cell types, ranging from primary epithelial to suspension, and quantified heterogeneity in mixed epithelial and mesenchymal co-cultures. A proof-of-concept screen of 904 diverse compounds using 13 semiconductor microplates demonstrates the platform's capability for mechanism of action (MOA) profiling with 25 distinct responses identified. The scalability of the semiconductor platform combined with the translatability of the high dimensional live-cell functional parameters expands high-throughput MOA profiling and phenotypic drug discovery applications.

Identifiers

PMID37333319
PMCPMC10274629

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.