AI Article Synopsis

  • * A study on the Iskar River in Bulgaria analyzed bacterial communities and resistance profiles before and after a large WWTP's discharge, finding significant variations in community compositions over time and location, particularly around specific antibiotic resistance genes.
  • * Although the presence of some ARGs was noted, the overall risk to human health assessed was low, indicating a need for ongoing monitoring of microbial communities and antibiotic resistance in surface waters.

Article Abstract

Waste Water Treatment Plants (WWTP) aim to reduce contamination in effluent water; however, studies indicate antimicrobial resistance genes (ARGs) persist post-treatment, potentially leading to their spread from human populated areas into the environment. This study evaluated the impact of a large WWTP serving 125,000 people on the Iskar River in Bulgaria, by characterizing the spatial and short-term temporal dynamics in bacterial community dynamics and resistance profiles of the surface water. Pairs of samples were collected biweekly on four dates from two different locations, one about 800 m after the WWTP effluents and the other 10 km downstream. Taxonomic classification revealed the dominance of and , notably the genera , , , , and . The taxonomic structure corresponded with both lentic and lotic freshwater habitats, with exhibiting a significant decrease over the study period. Principal Coordinate Analysis revealed statistically significant differences in bacterial community composition between samples collected on different dates. Differential abundance analysis identified notable enrichment of and There were shifts within the enriched or depleted bacterial taxa between early and late sampling dates. High relative abundance of the genes , , , (macrolides); , , , and (tetracyclines); and (sulphonamides); and , (beta-lactams) were detected, with trends of increased presence in the latest sampling dates and in the location closer to the WWTP. Of note, genes conferring resistance to carbapenems OXA-58 and IMP-33-like were identified. Co-occurrence analysis of ARGs and mobile genetic elements on putative plasmids showed few instances, and the estimated human health risk score (0.19) according to MetaCompare2.0 was low. In total, 29 metagenome-assembled genomes were recovered, with only a few harbouring ARGs. This study enhances our understanding of freshwater microbial community dynamics and antibiotic resistance profiles, highlighting the need for continued ARGs monitoring.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11207046PMC
http://dx.doi.org/10.3390/microorganisms12061250DOI Listing

Publication Analysis

Top Keywords

short-term temporal
8
dynamics bacterial
8
iskar river
8
river bulgaria
8
bacterial community
8
community dynamics
8
resistance profiles
8
samples collected
8
sampling dates
8
metagenomic investigation
4

Similar Publications

Neural deterioration and compensation in visual short-term memory among individuals with amnestic mild cognitive impairment.

Alzheimers Dement

January 2025

Guangdong Provincial Key Laboratory of Brain Function and Disease, Center for Brain and Mental Well-Being, Department of Psychology, Sun Yat-sen University, Guangzhou, China.

Introduction: Visual short-term memory (VSTM) is a critical indicator of Alzheimer's disease (AD), but whether its neural substrates could adapt to early disease progression and contribute to cognitive resilience in amnestic mild cognitive impairment (aMCI) has been unclear.

Methods: Fifty-five aMCI patients and 68 normal controls (NC) performed a change-detection task and underwent multimodal neuroimaging scanning.

Results: Among the atrophic brain regions in aMCI, VSTM performance correlated with the volume of the right prefrontal cortex (PFC) but not the medial temporal lobe (MTL), and this correlation was mainly present in patients with greater MTL atrophy.

View Article and Find Full Text PDF

Inland river runoff variability is pivotal for maintaining regional ecological stability. Daily flow forecasting in arid regions is crucial in understanding water body ecological processes and promoting healthy river ecology. Precise daily runoff forecasting serves as a cornerstone for ecological evaluation, management, and decision-making.

View Article and Find Full Text PDF

Addressing the issues of inadequate information exchange among subsequences in the operational time series of water injection pumps, leading to low accuracy and high false alarm rates in anomaly detection, this paper proposes a multidimensional time series anomaly detection method for water injection pump operations, leveraging Long Short-Term Memory Autoencoder augmented with Attention Mechanism (LSTMA-AE) and mechanistic constraints. The LSTMA-AE framework encompasses three primary modules: a Time Feature Extraction Module (Encoder), an Attention Layer, and a Data Reconstruction Module (Decoder). The Encoder captures temporal dependencies and features within the input sequences, mapping the input data into a higher-dimensional space.

View Article and Find Full Text PDF

Prcis: Trabecular cutting minimally invasive glaucoma surgery like bent ab interno needle goniectomy (BANG) when performed in baseline aqueous angiography identified low aqueous humor outflow regions, results in greater success of intraocular pressure reduction.

Purpose: To study the efficacy of Bent Ab Interno Needle Goniectomy (BANG) in high versus low aqueous humor outflow (AHO) regions as determined by Aqueous Angiography(AA) in patients with primary open angle glaucoma (POAG).

Methods: A prospective, single-centre, pilot, randomized control trial recruited 30 eyes of 30 patients of POAG and visually significant cataract (45-80 y) and were randomised into two groups ("A": BANG performed in the high-flow regions and "B": BANG performed in the low-flow regions) of 15 each.

View Article and Find Full Text PDF

Accurate energy demand forecasting is critical for efficient energy management and planning. Recent advancements in computing power and the availability of large datasets have fueled the development of machine learning models. However, selecting the most appropriate features to enhance prediction accuracy and robustness remains a key challenge.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!