Evidence map›Paper›PMID 36846776›Full record

ArticleFrontiers in microbiology2023

Retrospective analysis of

Ying Liu, Tao Zhang, Shen-Bo Chen, Yan-Bing Cui, Shu-Qi Wang, Hong-Wei Zhang, Hai-Mo Shen, Jun-Hu Chen

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2023. 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

8 authors.

Ying LiuNational Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention (Chinese Center for Tropical Diseases Research), Shanghai, China.
Tao ZhangAnhui Provincial Center for Disease Control and Prevention, Hefei, China.
Shen-Bo ChenNational Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention (Chinese Center for Tropical Diseases Research), Shanghai, China.
Yan-Bing CuiNational Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention (Chinese Center for Tropical Diseases Research), Shanghai, China.
Shu-Qi WangAnhui Provincial Center for Disease Control and Prevention, Hefei, China.
Hong-Wei ZhangHenan Provincial Center for Disease Control and Prevention, Zhengzhou, China.
Hai-Mo ShenNational Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention (Chinese Center for Tropical Diseases Research), Shanghai, China.
Jun-Hu ChenNational Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention (Chinese Center for Tropical Diseases Research), Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In malaria-free countries, imported cases are challenging because interconnections with neighboring countries with higher transmission rates increase the risk of parasite reintroduction. Establishing a genetic database for rapidly identifying malaria importation or reintroduction is crucial in addressing these challenges. This study aimed to examine genomic epidemiology during the pre-elimination stage by retrospectively reporting whole-genome sequence variation of 10 Methods: The samples were collected during the last few inland outbreaks from 2011 to 2012 when China implemented a malaria control plan. After next-generation sequencing, we completed a genetic analysis of the population, explored the geographic specificity of the samples, and examined clustering of selection pressures. We also scanned genes for signals of positive selection. Results: China's inland populations were highly structured compared to the surrounding area, with a single potential ancestor. Additionally, we identified genes under selection and evaluated the selection pressure on drug-resistance genes. In the inland population, positive selection was detected in some critical gene families, including Discussion: Our data provides an opportunity to investigate the molecular epidemiology of pre-elimination inland malaria populations, which exhibited lower selection pressure on invasion and immune evasion genes than neighbouring areas, but increased drug resistance in low transmission settings. Our results revealed that the inland population was severely fragmented with low relatedness among infections, despite a higher incidence of multiclonal infections, suggesting that superinfection or co-transmission events are rare in low-endemic circumstances. We identified selective signatures of resistance and found that the proportion of susceptible isolates fluctuated in response to the prohibition of specific drugs. This finding is consistent with the alterations in medication strategies during the malaria elimination campaign in inland China. Such findings could provide a genetic basis for future population studies, assessing changes in other pre-elimination countries.

Indexed as

China inlanddrug resistancehaplotype-based detectingmalariaPlasmodium vivaxpositive selection

Identifiers

PMID36846776
PMCPMC9948256

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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.