Evidence map›Paper›PMID 34641752›Full record

ReviewCritical reviews in biotechnology2022

Recent developments in systems biology and genetic engineering toward design of vaccines for TB.

Yogendra Singh, Gillian Beamer, Xingmin Sun, Pratyoosh Shukla

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Critical reviews in biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Yogendra SinghBacterial Pathogenesis Laboratory, Department of Zoology, University of Delhi, Delhi, India.
Gillian BeamerDepartment of Infectious Disease and Global Health, Tufts University, North Grafton, MA, USA.
Xingmin SunDepartment of Molecular Medicine, College of Medicine (COM), University of South Florida, Tampa, FL, USA.
Pratyoosh ShuklaEnzyme Technology and Protein Bioinformatics Laboratory, Department of Microbiology, Maharshi Dayanand University, Rohtak, India.ORCID 0000-0002-9307-4126

Funding

Multivalent vaccines against Clostridium difficile infectionR01AI132711 · NIAID · UNIVERSITY OF SOUTH FLORIDA · PI Xingmin Sun, Shifeng Wang · 2017 to 2026
$3.3M
Novel polymer biomaterials combating C. difficile infectionR01AI149852 · NIAID · UNIVERSITY OF SOUTH FLORIDA · PI CAI, JIANFENG, SUN, XINGMIN · 2019 to 2023
$1.9M
NIAID NIH HHS R01 AI132711NIAID NIH HHS R01 AI149852
6 · The paper itself

Abstract

Tuberculosis (TB) is one of the most prevalent diseases worldwide. The currently available Bacillus Calmette-Guérin vaccine is not sufficient in protecting against pulmonary TB. Although many vaccines have been evaluated in clinical trials, but none of them yet has proven to be more successful. Thus, new strategies are urgently needed to design more effective TB vaccines. The emergence of new technologies will undoubtedly accelerate the process of vaccine development. This review summarizes the potential and validated applications of emerging technologies, including: systems biology (genomics, proteomics, and transcriptomics), genetic engineering, and other computational tools to discover and develop novel vaccines against TB. It also discussed that the significant implementation of these approaches will play crucial roles in the development of novel vaccines to cure and control TB.

Indexed as

Mycobacterium tuberculosisTuberculosisTuberculosis VaccinesGenetic EngineeringHumansSystems BiologyTuberculosis Vaccinesbioinformaticsgenetic engineeringgenomicsMycobacterium tuberculosisproteomicssystems biology

Identifiers

PMID34641752
PMCPMC11208086

What OpenQuestion holds

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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.