Evidence map›Paper›PMID 37219704›Full record

ReviewDrug delivery and translational research2023

Innate immune regulations and various siRNA modalities.

Anju Kaushal

Open access · bronzeAbstract readReview
In one paragraph

Review in Drug delivery and translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
4.8field-weighted citation impact, top 5% 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

29 citing papers in PubMed, 31 citations in OpenAlex.

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  12. Zerlasiran for Lipoprotein(a) Reduction: Mechanisms, Evidence, and Future Directions.Cardiovascular & hematological disorders drug targets · 2026
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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

1 author at 1 institution in 1 country.

Anju KaushalNew Zealand Organization for Quality-Member, Auckland, New Zealand. anjukaushal186@hotmail.com.ORCID 0000-0002-0902-5461
Statistics New Zealand · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNAi therapeutics are designed to produce the precise silencing effects against the gene-linked diseases which were known to be untreatable in the past. The highly immunostimulatory nature of siRNA enhances the off-target effects and easily get attacked by nucleases; hence, their modulation is essentially required for accurate alterations to be made in the structures to intensify the pharmacological attributes. The phosphonate modifications act as shield against undue phosphorylation effects, and the molecular changes in ribose sugar lowers the level of immunogenicity and increases the binding efficacy. When bases are substituted with virtual/or pseudo bases, they eventually reduce the off-target effects. These changes modulate the nucleic acid sensors and control the hyper-activation of innate immune response. Various modification designs based on STC (universal pattern), ESC, ESC + (advanced patterns) and disubstrate have been explored to silence the gene expression of various diseases e.g., hepatitis, HIV, influenza, RSV, CNV and acute kidney injury. This review describes the various innovative siRNA therapeutics and their implications on the developed immune regulations to silence the disease effects. siRNA causes the silencing effects through RISC processing. The innate immune signalling is induced by both TLR-dependent and TLR-independent pathways. Modification chemistries are utilized to modulate the immune response.

Indexed as

Immunity, InnateSignal TransductionRNA, Small InterferingRNA, Small InterferingGene silencingInnate immune immune responseRNAisiRNA modification

Identifiers

PMID37219704
PMCPMC10204684
OpenAlexW4377564795

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.