Evidence map›Paper›PMID 37645977›Full record

ArticlebioRxiv : the preprint server for biology2023

A Hybrid Transistor with Transcriptionally Controlled Computation and Plasticity.

Yang Gao, Yuchen Zhou, Xudong Ji, Austin J Graham, Christopher M Dundas, Ismar E Miniel Mahfoud, Bailey M Tibbett, Benjamin Tan, Gina Partipilo, Ananth Dodabalapur and 2 more

Abstract readPreprint
PubMed Full text at PMC Publisher
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

12 authors.

Yang GaoMcKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
Yuchen ZhouDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, 78712, USA.
Xudong JiDepartment of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA.
Austin J GrahamMcKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
Christopher M DundasMcKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
Ismar E Miniel MahfoudMcKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
Bailey M TibbettMcKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
Benjamin TanMicroelectronics Research Center, The University of Texas at Austin, Austin, TX, 78758, USA.
Gina PartipiloMcKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
Ananth DodabalapurDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, 78712, USA.
Jonathan RivnayDepartment of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA.
Benjamin K KeitzMcKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.

Funding

Harnessing Electroactive Bacteria for Microbial Redox CatalysisR35GM133640 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI KEITZ, BENJAMIN KEITH · 2019 to 2023
$1.9M
NIGMS NIH HHS R35 GM133640
6 · The paper itself

Abstract

Organic electrochemical transistors (OECTs) are ideal devices for translating biological signals into electrical readouts and have applications in bioelectronics, biosensing, and neuromorphic computing. Despite their potential, developing programmable and modular methods for living systems to interface with OECTs has proven challenging. Here we describe hybrid OECTs containing the model electroactive bacterium

Identifiers

PMID37645977
PMCPMC10462107

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.