Evidence map›Paper›PMID 31913313›Full record

ArticleScientific reports2020

Origin of tuberculosis in the Paleolithic predicts unprecedented population growth and female resistance.

Pere-Joan Cardona, Martí Català, Clara Prats

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. A Comparative Study on Visual Detection ofDiagnostics (Basel, Switzerland) · 2023
    Article
  7. Article
  8. Article
  9. Review
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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

3 authors.

Pere-Joan CardonaUnitat de Tuberculosi Experimental, Institut de Recerca Germans Trias i Pujol (IGTP), Universitat Autònoma de Barcelona, CIBERES, Badalona, Catalonia, Spain. pj.cardona@gmail.com.
Martí CatalàComparative Medicine and Bioimage Centre of Catalonia (CMCiB). Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, Badalona, Catalonia, Spain.
Clara PratsEscola Superior d'Agricultura de Barcelona, Departament de Física, Universitat Politècnica de Catalunya (UPC)-BarcelonaTech, Castelldefels, Catalonia, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current data estimate the origin of Mycobacterium tuberculosis complex (MtbC) infection around 73,000 years before the common era (BCE), and its evolution to "modern" lineages around 46,000 BCE. Being MtbC a major killer of humanity, the question is how both species could persist. To answer this question, we have developed two new epidemiological models (SEIR type), adapted to sex dimorphism and comparing coinfection and superinfection for different MtbC lineages. We have attributed a higher resistance/tolerance to females to explain the lower incidence noted in this sex, a better health status in the Paleolithic compared to the Neolithic, and a higher dissemination of "modern" lineages compared to "ancient" ones. Our findings show the extraordinary impact caused by "modern" lineages, provoking the extinction of the groups infected. This could only be overcomed by an unprecedented population increase (x20 times in 100 years) and helped with the protection generated by previous infection with "ancient" lineages. Our findings also suggest a key role of female resistance against MtbC. This data obliges us to rethink the growth population parameters in the Paleolithic, which is crucial to understanding the survival of both MtbC and humans, and to decipher the nature of human female resistance against TB.

Indexed as

Models, TheoreticalPopulation GrowthArchaeologyCell LineageFemaleHumansMaleMycobacterium tuberculosisPhylogenySex FactorsTuberculosis

Identifiers

PMID31913313
PMCPMC6949267

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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.