Evidence map›Paper›PMID 39340375›Full record

ArticleJournal of water and health2024

Application of miniaturized most probable number method for bacterial detection in water samples: detection of multi-drug-resistant

Noor Andryan Ilsan, Siti Nurfajriah, Maulin Inggraini, Ni Putu Ratna Ayu Krishanti, Melda Yunita, Sipriyadi, Reza Anindita, Tzu-Wen Huang

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Article in Journal of water and health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Noor Andryan IlsanDepartment of Medical Laboratory Technology, STIKes Mitra Keluarga, Bekasi City, West Java Province, Indonesia E-mail: noor.andryan@stikesmitrakeluarga.ac.id.ORCID https://orcid.org/0000-0002-9907-8750
Siti NurfajriahDepartment of Medical Laboratory Technology, STIKes Mitra Keluarga, Bekasi City, West Java Province, Indonesia.
Maulin InggrainiDepartment of Medical Laboratory Technology, STIKes Mitra Keluarga, Bekasi City, West Java Province, Indonesia.
Ni Putu Ratna Ayu KrishantiResearch Center for Applied Zoology, National Research and Innovation Agency, Soekarno Science and Techno Park, Jl. Raya Bogor KM 46, Cibinong, Bogor, West Java Province 16911, Indonesia.
Melda YunitaDepartment of Medical Education, Faculty of Medicine, Pattimura University, Ambon, Maluku, Indonesia.
SipriyadiDepartment of Biology, Faculty of Mathematics and Natural Sciences, Bengkulu University, Bengkulu City, Indonesia.
Reza AninditaDepartment of Pharmacy, STIKes Mitra Keluarga, Bekasi City, West Java Province, Indonesia.
Tzu-Wen HuangGraduate Institute of Medical Sciences, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.

Funding

Badan Riset dan Inovasi Nasional 164/IV/KS/11/2023
6 · The paper itself

Abstract

The detection of bacterial contamination in drinking water is essential for monitoring the spread of foodborne diseases. We developed a simple, portable, and low-cost method of mini most probable number (mini MPN) to semi-enumerate bacterial suspension in water as a drinking water analogue. In this study, there is no significant difference between mini MPN and the standard method, technique plate count (TPC), at 10 and 100 CFU/ml

Indexed as

Drinking WaterDrug Resistance, Multiple, BacterialAnimalsRalstoniaWater MicrobiologyDrinking Watercoliformdrinking watermini most probable numbertechnique plate count

Identifiers

PMID39340375

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.