Evidence map›Paper›PMID 32511415›Full record

ArticlebioRxiv : the preprint server for biology2020

Integrated sample inactivation, amplification, and Cas13-based detection of SARS-CoV-2.

Jon Arizti-Sanz, Catherine A Freije, Alexandra C Stanton, Chloe K Boehm, Brittany A Petros, Sameed Siddiqui, Bennett M Shaw, Gordon Adams, Tinna-Solveig F Kosoko-Thoroddsen, Molly E Kemball and 9 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2020. 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

19 authors.

Jon Arizti-SanzBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Catherine A FreijeBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Alexandra C StantonBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Chloe K BoehmBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Brittany A PetrosBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Sameed SiddiquiBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Bennett M ShawBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Gordon AdamsBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Tinna-Solveig F Kosoko-ThoroddsenBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Molly E KemballBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Robin GrossIntegrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD, USA.
Loni WronkaNational Biodefense Analysis and Countermeasures Center, Fort Detrick, MD, USA.
Katie CavinessNational Biodefense Analysis and Countermeasures Center, Fort Detrick, MD, USA.
Lisa E HensleyIntegrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD, USA.
Nicholas H BergmanNational Biodefense Analysis and Countermeasures Center, Fort Detrick, MD, USA.
Bronwyn L MacInnisBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Jacob E LemieuxBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Pardis C SabetiBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
Cameron MyhrvoldBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.

Funding

Medical Scientist Training ProgramT32GM007753 · NIGMS · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI WALENSKY, LOREN DAVID · 1985 to 2021
$50.0M
NIGMS NIH HHS T32 GM007753
6 · The paper itself

Abstract

The COVID-19 pandemic has highlighted that new diagnostic technologies are essential for controlling disease transmission. Here, we develop SHINE (SHERLOCK and HUDSON Integration to Navigate Epidemics), a sensitive and specific integrated diagnostic tool that can detect SARS-CoV-2 RNA from unextracted samples. We combine the steps of SHERLOCK into a single-step reaction and optimize HUDSON to accelerate viral inactivation in nasopharyngeal swabs and saliva. SHINE's results can be visualized with an in-tube fluorescent readout - reducing contamination risk as amplification reaction tubes remain sealed - and interpreted by a companion smartphone application. We validate SHINE on 50 nasopharyngeal patient samples, demonstrating 90% sensitivity and 100% specificity compared to RT-PCR with a sample-to-answer time of 50 minutes. SHINE has the potential to be used outside of hospitals and clinical laboratories, greatly enhancing diagnostic capabilities.

Identifiers

PMID32511415
PMCPMC7265687

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.