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Antibiotic resistance represents a growing public health threat, with airborne drug-resistant strains being especially alarming due to their ease of transmission and association with severe respiratory infections. The respiratory microbiome plays a pivotal role in maintaining respiratory health, influencing the dynamics of antibiotic resistance among airborne pathogenic microorganisms. In this context, this review proposes the exploration of the complex interplay between the respiratory microbiota and antimicrobial resistance, highlighting the implications of microbiome diversity in health and disease. Moreover, strategies to mitigate antibiotic resistance, including stewardship programs, alternatives to traditional antibiotics, probiotics, microbiota restoration techniques, and nanotechnology-based therapeutic interventions, are critically presented, setting an updated framework of current management options. Therefore, through a better understanding of respiratory microbiome roles in antibiotic resistance, alongside emerging therapeutic strategies, this paper aims to shed light on how the global health challenges posed by multi-drug-resistant pathogens can be addressed. © 2025 by the authors.

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Healthcare-associated infections (HAIs), previously known as nosocomial infections, represent a significant threat to healthcare systems worldwide, prolonging patient hospital stays and the duration of antimicrobial therapy. One of the most serious consequences of HAIs is the increase in the rate of antibiotic resistance (AR) generated by the prolonged, frequent, and sometimes incorrect use of antibiotics, which leads to the selection of resistant bacteria, making treatment difficult and expensive, with direct consequences for the safety of patients and healthcare personnel. Therefore, timely and accurate diagnosis of HAIs is mandatory to develop appropriate infection prevention and control practices (IPC) and new therapeutic strategies. This review aimed to present the prevalence, risk factors, current diagnosis, including artificial intelligence (AI) and machine learning approaches, future perspectives in combating HAIs causative bacteria (phage therapy, microbiome-based interventions, and vaccination), and HAIs surveillance strategies. Also, we discussed the latest findings regarding the relationships of AR with climate change and environmental pollution in the context of the One Health approach. Phage therapy is an emerging option that can offer an alternative to ineffective antibiotic treatments for antibiotic-resistant bacteria causing HAIs. Clinical trials dealing with vaccine development for resistant bacteria have yielded conflicting results. Two promising strategies, fecal microbiota transplantation and probiotic therapy, proved highly effective against recurrent Clostridium difficile infections and have been shown to reduce HAI incidence in hospitalized patients undergoing antibiotic therapy. Artificial intelligence and machine learning systems offer promising predictive capabilities in processing large volumes of clinical, microbiological, and patient data but require robust data integration. Our paper argues that HAIs are still a global challenge, requiring stringent IPC policies, computer vision, and AI-powered tools. Despite promising avenues like integrated One Health approaches, optimized phage therapy, microbiome-based interventions, and targeted vaccine development, several knowledge gaps in clinical efficacy, standardization, and pathogen complexity remain to be answered.

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Healthcare-associated infections (HAIs), previously known as nosocomial infections, represent a significant threat to healthcare systems worldwide, prolonging patient hospital stays and the duration of antimicrobial therapy. One of the most serious consequences of HAIs is the increase in the rate of antibiotic resistance (AR) generated by the prolonged, frequent, and sometimes incorrect use of antibiotics, which leads to the selection of resistant bacteria, making treatment difficult and expensive, with direct consequences for the safety of patients and healthcare personnel. Therefore, timely and accurate diagnosis of HAIs is mandatory to develop appropriate infection prevention and control practices (IPC) and new therapeutic strategies. This review aimed to present the prevalence, risk factors, current diagnosis, including artificial intelligence (AI) and machine learning approaches, future perspectives in combating HAIs causative bacteria (phage therapy, microbiome-based interventions, and vaccination), and HAIs surveillance strategies. Also, we discussed the latest findings regarding the relationships of AR with climate change and environmental pollution in the context of the One Health approach. Phage therapy is an emerging option that can offer an alternative to ineffective antibiotic treatments for antibiotic-resistant bacteria causing HAIs. Clinical trials dealing with vaccine development for resistant bacteria have yielded conflicting results. Two promising strategies, fecal microbiota transplantation and probiotic therapy, proved highly effective against recurrent Clostridium difficile infections and have been shown to reduce HAI incidence in hospitalized patients undergoing antibiotic therapy. Artificial intelligence and machine learning systems offer promising predictive capabilities in processing large volumes of clinical, microbiological, and patient data but require robust data integration. Our paper argues that HAIs are still a global challenge, requiring stringent IPC policies, computer vision, and AI-powered tools. Despite promising avenues like integrated One Health approaches, optimized phage therapy, microbiome-based interventions, and targeted vaccine development, several knowledge gaps in clinical efficacy, standardization, and pathogen complexity remain to be answered. © The Author(s) 2025.

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Hedera helix L. contains phytochemicals with good biological properties which are beneficial to human health and can be used to protect plants against different diseases. The aim of this research was to find the most suitable extraction method and the most favorable parameters for the extraction of different bioactive compounds from ivy leaves. Different extraction methods, namely microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE), and conventional heating extraction (CHE), were used. The most suitable method for the extraction of saponins is MAE with an extraction efficiency of 58%, while for carbohydrates and polyphenols, the best results were achieved via UAE with an extraction efficiency of 61.7% and 63.5%, respectively. The antioxidant activity (AA) of the extracts was also determined. The highest AA was obtained via UAE (368.98 +/- 9.01 mu mol TR/gDM). Better results were achieved at 50( degrees)C for 10 min of extraction, using 80% ethanol in water as solvent. In order to evaluate their in vitro cytotoxicity, the extracts richest in bioactive compounds were tested on NCTC fibroblasts. Their influence on the DNA content of RAW 264.7 murine macrophages was also tested. Until 200 mu g/mL, the extracts obtained via UAE and MAE were cytocompatible with NCTC fibroblasts at 48 h of treatment. Summarizing the above, both MAE and UAE can be employed as green and efficient methods for producing extracts rich in bioactive compounds, exhibiting strong antioxidant properties and good noncytotoxic activity.

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To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction (PPI) networks integrating the top-ranked host factors, the drug target proteins and directed PPI data. We analyzed the networks to identify drug targets and combinations thereof that offer efficient control over the host factors. We validated our findings against clinical studies data and bioinformatics studies. Our method offers a new insight into the molecular details of the disease and into potentially new therapy targets for it. Our approach for drug repurposing is significant beyond COVID-19 and may be applied also to other diseases.

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Background: Romania is one of the European countries reporting very high antimicrobial resistance (AMR) rates and consumption of antimicrobials. We aimed to characterize the AMR profiles and clonality of 304 multi-drug resistant (MDR) Acinetobacter baumannii (Ab) and Pseudomonas aeruginosa (Pa) strains isolated during two consecutive years (2018 and 2019) from hospital settings, hospital collecting sewage tanks and the receiving wastewater treatment plants (WWTPs) located in the main geographical regions of Romania. Methods: The strains were isolated on chromogenic media and identified by MALDI-TOF-MS. Antibiotic susceptibility testing and confirmation of ESBL- and CP- producing phenotypes and genotypes were performed. The genetic characterization also included horizontal gene transfer experiments, whole-genome sequencing (WGS), assembling, annotation and characterization. Results: Both clinical and aquatic isolates exhibited high MDR rates, especially the Ab strains isolated from nosocomial infections and hospital effluents. The phenotypic resistance profiles and MDR rates have largely varied by sampling point and geographic location. The highest MDR rates in the aquatic isolates were recorded in Galati WWTP, followed by Bucharest. The Ab strains harbored mostly bla(OX)(A-)(23), bla(OXA-)(24), bla(SHV), bla(TEM) and bla(GES), while Pa strains bla(IMP), bla(VIM), bla(NDM), bla(V)(EB), bla(GES) and bla(TEM), with high variations depending on the geographical zone and the sampling point. The WGS analysis revealed the presence of antibiotic resistance genes (ARGs) to other antibiotic classes, such as aminoglycosides, tetracyclines, sulphonamides, fosfomycin, phenicols, trimethoprim-sulfamethoxazole as well as class 1 integrons. The molecular analyses highlighted: (i) The presence of epidemic clones such as ST2 for Ab and ST233 and ST357 for Pa; (ii) The relatedness between clinical and hospital wastewater strains and (iii) The possible dissemination of clinical Ab belonging to ST2 (also proved in the conjugation assays for bla(OX)(A-)(23) or bla(OX)(A-)(72) genes), ST79 and ST492 and of Pa strains belonging to ST357, ST640 and ST621 in the wastewaters. Conclusion: Our study reveals the presence of CP-producing Ab and Pa in all sampling points and the clonal dissemination of clinical Ab ST2 strains in the wastewaters. The prevalent clones were correlated with the presence of class 1 integrons, suggesting that these isolates could be a significant reservoir of ARGs, being able to persist in the environment.

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The aim of this study was to establish the best ultrasound assisted extraction (UAE) conditions of saponins from Hedera helix L. leaves and to evaluate the in vitro biocompatibility of the extracts richest in saponins. Different parameters, such as extraction time, temperature, ultrasound power, solvent to plant material ratio, and solvent concentration, were investigated. The most efficient extraction conditions were a temperature of 50 degrees C, an ultrasound amplitude of 40%, an extraction time of 60 min, a plant material to solvent ratio of 1:20 (w:v), and 80% ethanol as solvent. In vitro cytotoxicity of the extracts richest in saponins and their influence on the DNA content of L929 (NCTC) fibroblasts were tested. Until 200 mu g/mL, the studied extracts were cytocompatible with L929 fibroblast cell lines at 48 h of treatment. These in vitro cell culture results provide useful information for further applications of Hedera helix extracts in a pharmaceutical field.

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In this paper we describe the transmission of a multi-drug resistant Klebsiella pneumoniae ST101 clone from hospital to wastewater and its persistence after chlorine treatment. Water samples from influents and effluents of the sewage tank of an infectious diseases hospital and clinical strains collected from the intra-hospital infections, during a period of 10 days prior to wastewater sampling were analyzed. Antibiotic resistant K. pneumoniae strains from wastewaters were recovered on selective media. Based on antibiotic susceptibility profiles and PCR analyses of antibiotic resistance (AR) genetic background, as well as whole-genome sequencing (Illumina MiSeq) and subsequent bioinformatic analyses, 11 ST101 K. pneumoniae strains isolated from hospital wastewater influent, wastewater effluent and clinical sector were identified as clonally related. The SNP and core genome analyses pointed out that five strains were found to be closely related (with <= 18 SNPs and identical cgMLST profile). The strains belonging to this clone harbored multiple acquired AR genes [bla(CTX-M-)(15), bla(OXA-)(48), bla(OXA-)(1), bla(SHV-)(106), bla(TEM-)(150), aac(3)-IIa, aac(6 ')-Ib-cr, oqxA10, oqxB17, fosA, catB3, dfrA14, tet(D)] and chromosomal mutations involved in AR (Delta mgrB, Delta ompK35, amino acid substitutions in GyrA Ser83Tyr, Asp87Asn, ParC Ser80Tyr). Twenty-nine virulence genes involved in iron acquisition, biofilm and pili formation, adherence, and the type six secretion system - T6SS-III were identified. Our study proves the transmission of MDR K. pneumoniae from hospital to the hospital effluent and its persistence after the chlorine treatment, raising the risk of surface water contamination and further dissemination to different components of the trophic chain, including humans.