Evidence map›Paper›PMID 40618018›Full record

ArticleBMC microbiology2025

Design, construction and efficiency analysis of bagasse-based charcoal packed horizontal lab-scale wetland for the removal of antibiotic-resistant bacteria.

Misbah Batool Aslam, Talmeez U R Rehman, Amina Farrukh Alavi, Abdul Haleem, Abdul Haq, Safia Ahmed, Wasim Sajjad, Mohammed Bourhia, Ousman B Mahamat, Khalid S Almaary and 1 more

Abstract read
In one paragraph

Article in BMC microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

11 authors.

Misbah Batool AslamDepartment of Biological Sciences, National University of Medical Sciences, The Mall Rawalpindi, Rawalpindi, 46000, Pakistan.
Talmeez U R RehmanDepartment of Microbiology, Quaid-I-Azam University, Islamabad, 45320, Pakistan.
Amina Farrukh AlaviDepartment of Microbiology, Quaid-I-Azam University, Islamabad, 45320, Pakistan.
Abdul HaleemDepartment of Microbiology, Quaid-I-Azam University, Islamabad, 45320, Pakistan.
Abdul HaqPeshawar Laboratories Complex, Pakistan Council of Scientific and Industrial Research, Peshawar, 25120, Pakistan.
Safia AhmedDepartment of Microbiology, Quaid-I-Azam University, Islamabad, 45320, Pakistan.
Wasim SajjadState Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China.
Mohammed BourhiaLaboratory of Biotechnology and Natural Resources Valorization, Faculty of Sciences, Ibn Zohr University, Agadir, 80060, Morocco.
Ousman B MahamatNational Federation of Associations of Medical Practitioners in Chad (FENAPMT), Ministry of Health, N'Djamena, Republic of Chad.
Khalid S AlmaaryDepartment of Botany and Microbiology, College of Science, King Saud University, P. O. BOX 2455, Riyadh, 11451, Saudi Arabia.
Mahwish AliDepartment of Biological Sciences, National University of Medical Sciences, The Mall Rawalpindi, Rawalpindi, 46000, Pakistan. mahwish.ali@numspak.edu.pk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic-resistant bacteria (ARB) pose a significant and growing threat to public health, particularly in wastewater environments where they can persist and propagate, exacerbating the global antibiotic resistance crisis. Conventional wastewater treatment methods often fall short in effectively removing ARB and associated contaminants, creating an urgent need for innovative and sustainable solutions. This research addresses this critical gap by investigating the use of a lab-scale horizontal subsurface flow constructed wetland (CW) planted with Typha latifolia and Phragmites australis to enhance domestic wastewater treatment. Biochar was selected as the substrate medium due to its high adsorption capacity and ability to support microbial communities that contribute to contaminant degradation. The CW system was operated at a flow rate of 3.8 US gallons/day and a moderate organic loading rate, with influent concentrations of 698 mg/L for chemical oxygen demand (COD), 376 mg/L for biological oxygen demand (BOD), 43 mg/L for nitrogen and 51 mg/L for sulfate. The results showed that the removal efficiencies of various physiochemical parameters were 53%, 57%, 81%, 80%, and 81% for total dissolved solids (TDS), COD, BOD, total nitrogen and total sulphate, respectively. Importantly, antibiotic-resistant bacteria were reduced by 99%, highlighting the system's capability to mitigate the spread of multidrug-resistant (MDR) strains. Screening for antibiotic-resistant β-lactamase genes revealed that blaTEM was detected in 50% of MDR isolates from influent samples, while blaCTX-M was absent in both influent and effluent. These findings emphasize the potential of constructed wetlands with biochar as a sustainable and cost-effective solution for addressing the dual challenges of environmental pollution and antibiotic resistance. This study provides critical insights into the development of advanced wastewater treatment technologies to combat emerging public health threats.

Indexed as

BacteriaCelluloseCharcoalDrug Resistance, BacterialWater PurificationWetlandsAnti-Bacterial AgentsBiodegradation, EnvironmentalBiological Oxygen Demand AnalysisPoaceaeTyphaceaeWastewaterAnti-Bacterial AgentsbiocharCelluloseCharcoalWastewaterAntibiotic resistant bacteriaAntibiotic resistant genesBiocharConstructed wetland (CW)Domestic waste

Identifiers

PMID40618018
PMCPMC12228385

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.