Evidence map›Paper›PMID 36424398›Full record

ArticleScientific reports2022

Rapid diagnosis of malaria by chemometric peak-free LIBS of trace biometals in blood.

Wayua Deborah Musyoka, Angeyo Hudson Kalambuka, Dehayem-Massop Alix, Kaduki Kenneth Amiga

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 42% 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
4 · The record

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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 at 1 institution in 1 country.

Wayua Deborah MusyokaDepartment of Physics, Faculty of Science and Technology, University of Nairobi, P. O. Box 30197-00100, Nairobi, Kenya.
Angeyo Hudson KalambukaDepartment of Physics, Faculty of Science and Technology, University of Nairobi, P. O. Box 30197-00100, Nairobi, Kenya. hkalambuka@uonbi.ac.ke.
Dehayem-Massop AlixDepartment of Physics, Faculty of Science and Technology, University of Nairobi, P. O. Box 30197-00100, Nairobi, Kenya.
Kaduki Kenneth AmigaDepartment of Physics, Faculty of Science and Technology, University of Nairobi, P. O. Box 30197-00100, Nairobi, Kenya.
University of Nairobi · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Laser Induced Breakdown Spectroscopy (LIBS) trace atomic species of diseased biofluids are subtle (peak-free) in complex spectra. Trace analysis requires a considerable push in analytical strategy. Enabling LIBS with chemometrics can help identify, extract, analyze and interpret the trace species' spectral signatures to give an insight on the biophysiological status of the bodies from which the biofluids originate. We report on the trace quantitative performance of peak-free LIBS enabled by chemometrics modelling using principal components analysis (PCA) for direct artificial neural network (ANN)-based analysis of Cu, Zn, Fe and Mg in Plasmodium falciparum-infected blood in the context of rapid spectral diagnosis of malaria utilizing the biometals as the disease biomarkers. Only one standard is required in this method-to delineate the analyte spectral regions (feature selection) and to test for accuracy. Based on the alteration of the biometal levels and their multivariate and correlational patterns in cultured blood, peripheral finger blood drops dried directly on Nucleopore membrane filters was accurately discriminated as either malaria-infected or healthy. Further the morphological evolution of Plasmodium was accurately predicted using spectral features of the biometals wherein high negative correlations between Fe (- 0.775) and Zn (- 0.881) and high positive correlations between Cu (0.892) and Mg (0.805) with parasitemia were observed. During the first 96 h of malaria infection Cu increases profoundly (from 328 to 1999 ppb) while Fe, Zn and Mg decrease (from 1206 to 674 ppb), (from 1523 to 499 ppb) and (from 23,880 to 19,573 ppb) respectively. Compared with healthy, Plasmodium falciparum-infected blood has high Cu but low levels of Fe, Zn and Mg. Cu and Zn are highly (≥ 0.9) positively correlated while Fe and Cu as well as Zn and Cu are highly (≥ 0.9) negatively correlated. Chemometric peak-free LIBS showed the potential for direct rapid malaria diagnostics in blood based on the levels, alterations and multivariate associations of the trace biometals which are used as biomarkers of the disease.

Indexed as

MalariaTrace ElementsChemometricsHumansNeural Networks, ComputerSpectrum AnalysisTrace Elements

Identifiers

PMID36424398
PMCPMC9691717
OpenAlexW4309918436

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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.