Evidence map›Paper›PMID 29789757›Full record

ArticleJournal of cleaner production2018

Locally produced lactic acid bacteria for pathogen inactivation and odor control in fecal sludge.

Emmanuel Alepu Odey, Zifu Li, Xiaoqin Zhou, Yichang Yan

Abstract read
In one paragraph

Article in Journal of cleaner production, 2018. 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. 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

4 authors.

Emmanuel Alepu OdeySchool of Energy and Environmental Engineering, Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing Xueyuan 30, Beijing 100083, PR China.
Zifu LiSchool of Energy and Environmental Engineering, Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing Xueyuan 30, Beijing 100083, PR China.
Xiaoqin ZhouSchool of Energy and Environmental Engineering, Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing Xueyuan 30, Beijing 100083, PR China.
Yichang YanSchool of Energy and Environmental Engineering, Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing Xueyuan 30, Beijing 100083, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Providing safe fecal sludge (FS) sanitation has remained an important goal of global communities because of the high risks imposed on human health of the exposure to un-sanitized FS. This study used lactic acid fermentation as a pre-treatment technology to evaluate the sanitization effect of lactic acid bacteria (LAB) on FS. A combination of fermented rice flour and brown sugar was used as the medium to prepare LAB, and fecal coliforms were used as the indicator organisms. The addition of a LAB suspension grown in fermented rice flour and brown sugar to FS was studied to evaluate the survival of fecal coliforms. The pH decreased during ongoing lactic acid fermentation after the addition of the LAB suspension. The results revealed that fecal coliforms in reactors containing 1:1 and 2:1 w/w of FS and LAB suspension decreased to half of the initial concentration within seven days of the treatment process in comparison with that of the control reactor. Viable plate counts of 0.6 × 10

Indexed as

Brown sugarColiform bacteriaFecal sludgeFermented rice flourLactic acid bacteria

Identifiers

PMID29789757
PMCPMC5890381

What OpenQuestion holds

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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.