Evidence map›Paper›PMID 25184623›Full record

ArticleIntegrative biology : quantitative biosciences from nano to macro2014

Organ-targeted high-throughput in vivo biologics screen identifies materials for RNA delivery.

Tsung-Yao Chang, Peng Shi, Joseph D Steinmeyer, Itthi Chatnuntawech, Paul Tillberg, Kevin T Love, Peter M Eimon, Daniel G Anderson, Mehmet Fatih Yanik

Abstract read
In one paragraph

Article in Integrative biology : quantitative biosciences from nano to macro, 2014. 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
2.3field-weighted citation impact, top 13% of its field
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, 29 citations in OpenAlex.

  1. Article
  2. Fish Capsules: A System for High-Throughput Screening of Combinatorial Drugs.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Article
  3. Article
  4. Frontiers in oncology · 2017
    Review
  5. Article
  6. Article
  7. 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

9 authors at 2 institutions in 3 countries.

Tsung-Yao ChangDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. yanik@mit.edu.
Peng Shi
Joseph D Steinmeyer
Itthi Chatnuntawech
Paul Tillberg
Kevin T Love
Peter M Eimon
Daniel G Anderson
Mehmet Fatih Yanik
Massachusetts Institute of Technology · USCity University of Hong Kong · HK

Funding

Generating transplantable neurons by in vivo combinatorial screening of transcripDP1NS082101 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI YANIK, MEHMET FATIH · 2012 to 2015
$3.2M
Development of on-chip ultra high-throughput whole-animal assay technologiesDP2OD002989 · OD · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI YANIK, MEHMET FATIH · 2007 to 2007
$2.5M
HIGH-THROUGHPUT IN VIVO SUBCELLULAR-RESOLUTION VERTEBRATE SCREENING PLATFORMR01NS073127 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI YANIK, MEHMET FATIH · 2010 to 2014
$2.0M
NIH HHS DP2 OD002989NIH HHS DP2OD002989NINDS NIH HHS DP1 NS082101NINDS NIH HHS R01 NS073127
6 · The paper itself

Abstract

Therapies based on biologics involving delivery of proteins, DNA, and RNA are currently among the most promising approaches. However, although large combinatorial libraries of biologics and delivery vehicles can be readily synthesized, there are currently no means to rapidly characterize them in vivo using animal models. Here, we demonstrate high-throughput in vivo screening of biologics and delivery vehicles by automated delivery into target tissues of small vertebrates with developed organs. Individual zebrafish larvae are automatically oriented and immobilized within hydrogel droplets in an array format using a microfluidic system, and delivery vehicles are automatically microinjected to target organs with high repeatability and precision. We screened a library of lipid-like delivery vehicles for their ability to facilitate the expression of protein-encoding RNAs in the central nervous system. We discovered delivery vehicles that are effective in both larval zebrafish and rats. Our results showed that the in vivo zebrafish model can be significantly more predictive of both false positives and false negatives in mammals than in vitro mammalian cell culture assays. Our screening results also suggest certain structure-activity relationships, which can potentially be applied to design novel delivery vehicles.

Indexed as

AnimalsBiological ProductsCentral Nervous SystemDrug Delivery SystemsFemaleLipidsLuminescent ProteinsMicrofluidicsMicroscopy, FluorescenceRatsRats, Sprague-DawleyRed Fluorescent ProteinRNAZebrafishBiological ProductsLipidsLuminescent ProteinsRed Fluorescent ProteinRNA

Identifiers

PMID25184623
PMCPMC4350364
OpenAlexW2106200559

What OpenQuestion holds

Textmetadata
LicenceTDM
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.