Evidence map›Paper›PMID 34947853›Full record

ReviewLife (Basel, Switzerland)2021

Usefulness of Microbiome for Forensic Geolocation: A Review.

Christian Haarkötter, María Saiz, Xiomara Gálvez, María Isabel Medina-Lozano, Juan Carlos Álvarez, José Antonio Lorente

Abstract readReview
In one paragraph

Review in Life (Basel, Switzerland), 2021. 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
–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

7 citing papers in PubMed.

  1. Review
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  7. Review
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

6 authors.

Christian HaarkötterLaboratory of Genetic Identification, Department of Legal Medicine, Toxicology and Physical Anthropology, Faculty of Medicine, University of Granada, 18016 Granada, Spain.ORCID 0000-0002-4419-4631
María SaizLaboratory of Genetic Identification, Department of Legal Medicine, Toxicology and Physical Anthropology, Faculty of Medicine, University of Granada, 18016 Granada, Spain.
Xiomara GálvezLaboratory of Genetic Identification, Department of Legal Medicine, Toxicology and Physical Anthropology, Faculty of Medicine, University of Granada, 18016 Granada, Spain.
María Isabel Medina-LozanoLaboratory of Genetic Identification, Department of Legal Medicine, Toxicology and Physical Anthropology, Faculty of Medicine, University of Granada, 18016 Granada, Spain.
Juan Carlos ÁlvarezLaboratory of Genetic Identification, Department of Legal Medicine, Toxicology and Physical Anthropology, Faculty of Medicine, University of Granada, 18016 Granada, Spain.
José Antonio LorenteLaboratory of Genetic Identification, Department of Legal Medicine, Toxicology and Physical Anthropology, Faculty of Medicine, University of Granada, 18016 Granada, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Forensic microbiomics is a promising tool for crime investigation. Geolocation, which connects an individual to a certain place or location by microbiota, has been fairly well studied in the literature, and several applications have been found. The aim of this review is to highlight the main findings in this field, including the current sample storage, DNA extraction, sequencing and data analysis techniques that are being used, and its potential applications in human trafficking and ancient DNA studies. Second, the challenges and limitations of forensic microbiomics and geolocation are emphasised, providing recommendations for the establishment of this tool in the forensic science community.

Indexed as

forensic microbiologyforensic sciencegeolocationmicrobiomemicrobiota

Identifiers

PMID34947853
PMCPMC8707258

What OpenQuestion holds

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LicenceCC BY
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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.