Evidence map›Paper›PMID 37258924›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

A Web-Based Method for the Identification of IL6-Based Immunotoxicity in Vaccine Candidates.

Anjali Dhall, Sumeet Patiyal, Neelam Sharma, Salman Sadullah Usmani, Gajendra P S Raghava

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
6.7field-weighted citation impact, top 3% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
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  4. Frontiers in immunology · 2024
    Article
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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

5 authors at 1 institution in 1 country.

Anjali Dhall *Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
Sumeet Patiyal *Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
Neelam SharmaDepartment of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
Salman Sadullah UsmaniDepartment of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.
Gajendra P S RaghavaDepartment of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India. raghava@iiitd.ac.in.
Indraprastha Institute of Information Technology Delhi · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interleukin 6 (IL6) is a major pro-inflammatory cytokine that plays a pivotal role in both innate and adaptive immune responses. In the past, a number of studies reported that high level of IL6 promotes the proliferation of cancer, autoimmune disorders, and cytokine storm in COVID-19 patients. Thus, it is extremely important to identify and remove the antigenic regions from a therapeutic protein or vaccine candidate that may induce IL6-associated immunotoxicity. In order to overcome this challenge, our group has developed a computational tool, IL6pred, for discovering IL6-inducing peptides in a vaccine candidate. The aim of this chapter is to describe the potential applications and methodology of IL6pred. It sheds light on the prediction, designing, and scanning modules of IL6pred webserver and standalone package ( https://webs.iiitd.edu.in/raghava/il6pred/ ).

Indexed as

COVID-19VaccinesCytokinesHumansInterleukin-6InternetCytokinesInterleukin-6VaccinesCytokinesIL6-inducing peptidesImmunotoxicityTherapeutic peptidesVaccine candidate

Identifiers

PMID37258924
OpenAlexW4378801539

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.