Evidence map›Paper›PMID 28502018›Full record

ArticleParasitology research2017

Evolutionary processes in populations of Cryptosporidium inferred from gp60 sequence data.

Juan C Garcia-R, David T S Hayman

Abstract read
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In one paragraph

Article in Parasitology research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 32% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Food and waterborne parasitology · 2021
    Review
  5. Absence ofParasitology · 2021
    Article
  6. Article
  7. 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

2 authors at 1 institution in 1 country.

Juan C Garcia-RMolecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, Private Bag, 11 222, Palmerston North, 4442, New Zealand. j.c.garciaramirez@massey.ac.nz.
David T S HaymanMolecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, Private Bag, 11 222, Palmerston North, 4442, New Zealand.
Massey University · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cryptosporidiosis is one of the most common human infectious diseases globally. The gp60 gene has been adopted as a key marker for molecular epidemiological investigations into this protozoan disease because of the capability to characterize genotypes and detect variants within Cryptosporidium species infecting humans. However, we know relatively little about the potential spatial and temporal variation in population demography that can be inferred from this gene beyond that it is recognized to be under selective pressure. Here, we analyzed the genetic variation in time and space within two putative populations of Cryptosporidium in New Zealand to infer the processes behind the patterns of sequence polymorphism. Analyses using Tajima's D, Fu, and Li's D* and F* tests show significant departures from neutrality in some populations and indicate the selective maintenance of alleles within some populations. Demographic analyses showed distortions in the pattern of the genetic variability caused by high recombination rates and population expansion, which was observed in case notification data. Our results showed that processes acting on populations that have similar effects can be distinguished from one another and multiple processes can be detected acting at the same time. These results are significant for prediction of the parasite dynamics and potential mechanisms of long-term changes in the risk of cryptosporidiosis in humans.

Indexed as

Genetic VariationAllelesAnimalsBiological EvolutionCryptosporidiosisCryptosporidiumFecesGenotypeHumansMolecular EpidemiologyNew ZealandPolymorphism, GeneticDemographyExpansionNew ZealandRecombinationSelection

Identifiers

PMID28502018
OpenAlexW2613131408

What OpenQuestion holds

Textmetadata
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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.