Evidence map›Paper›PMID 40847664›Full record

ArticleIndian dermatology online journal2025

Understanding Autoimmune Response Mechanisms in Leprosy.

Vinay Kumar Pathak, Itu Singh, Shoor Vir Singh, Utpal Sengupta

Abstract read
In one paragraph

Article in Indian dermatology online journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Vinay Kumar PathakStanley Browne Laboratory, The Leprosy Mission Community Hospital, Delhi, India.ORCID 0000-0002-5364-6281
Itu SinghStanley Browne Laboratory, The Leprosy Mission Community Hospital, Delhi, India.ORCID 0000-0003-0596-8566
Shoor Vir SinghDepartment of Biotechnology, GLA University, Mathura, UP, India.
Utpal SenguptaStanley Browne Laboratory, The Leprosy Mission Community Hospital, Delhi, India.ORCID 0000-0002-1177-1076

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

abstractLeprosy is a persistent granulomatous disease that occurs due to Mycobacterium leprae infection. Leprosy primarily affects peripheral nerves, skin, and mucous membranes. Reactions in leprosy are immunological complications that may occur at any stage of disease progression, irrespective of treatment status. This review explores the potential link between M. leprae infection and autoimmune responses, emphasizing the role of immune dysregulation in leprosy reactions. We have delineated a comprehensive exploration of reactions in leprosy within the framework of autoimmunity, drawing insights from previously documented research. Biotic elements, including bacteria, might be associated with an imbalance in the host's homeostatic mechanism, leading to an autoimmune response. Mycobacteria have been reported for their potential to modulate host immune responses in both humans and experimental animal models. Pathogens can induce autoimmunity via molecular mimicry during the initiation of the disorder, and they may promote chronic pathologies with inflammation and/or superantigens, prompted by the loss of immunological tolerance to self-antigens, which can lead to systemic or organ-specific damage. Autoimmune manifestations in leprosy are triggered by the impairment of the regulatory mechanisms of the host due to M. leprae infection. Leprosy reactions are influenced by autoimmune processes triggered by M. leprae infection. Understanding the immunological interactions between the pathogen and the host may provide insights into disease management and therapeutic strategies.

Indexed as

Identifiers

PMID40847664
PMCPMC12419686

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Registered trials

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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.