Evidence map›Paper›PMID 25944755›Full record

ArticleEnvironmental monitoring and assessment2015

Pattern of multiresistant to antimicrobials and heavy metal tolerance in bacteria isolated from sewage sludge samples from a composting process at a recycling plant in southern Brazil.

Karina Heck, Évilin Giordana De Marco, Mariana Wanderlei Duarte, Sabrina Pinto Salamoni, Sueli Van Der Sand

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Article in Environmental monitoring and assessment, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

5 authors.

Karina HeckDepartmento de Microbiologia, Immunologia e Parasitologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Évilin Giordana De Marco
Mariana Wanderlei Duarte
Sabrina Pinto Salamoni
Sueli Van Der Sand

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The composting process is a viable alternative for the recycling of household organic waste and sewage sludge generated during wastewater treatment. However, this technique can select microorganisms resistant to antimicrobials and heavy metals as a result of excess chemicals present in compost windrow. This study evaluates the antimicrobial multiresistant and tolerance to heavy metals in bacteria isolated from the composting process with sewage sludge. Fourteen antimicrobials were used in 344 strains for the resistance profile and four heavy metals (chromium, copper, zinc, and lead) for the minimum biocide concentration assay. The strains used were from the sewage sludge sample (beginning of the process) and the compost sample (end of the process). Strains with higher antimicrobial and heavy metal profile were identified by 16S rRNA gene sequencing. The results showed a multiresistant profile in 48 % of the strains, with the highest percentage of strains resistant to nitrofurantoin (65 %) and β-lactams (58 %). The strains isolated from the sewage sludge and the end of the composting process were more tolerant to copper, with a lethal dose of approximately 900 mg L(-1) for about 50 % of the strains. The genera that showed the highest multiresistant profile and increased tolerance to the metals tested were Pseudomonas and Ochrobactrum. The results of this study may contribute to future research and the revision and regulation of legislation on sewage sludge reuse in soils.

Indexed as

Waste Disposal, FluidAdaptation, PhysiologicalAnti-Infective AgentsBacteriaBrazilCopperDrug Resistance, MicrobialEnvironmental MonitoringMetals, HeavyRecyclingRNA, Ribosomal, 16SSewageSoilZincAnti-Infective AgentsCopperMetals, HeavyRNA, Ribosomal, 16SSewageSoilZinc

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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.