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.

Background: Antimicrobial resistance (AMR) is a major public health concern. Urinary tract infections (UTIs) account for up to 85–90% of community-acquired cases. The COVID-19 pandemic disrupted healthcare access and may have influenced resistance patterns. In this context, we retrospectively evaluated the antibiotic resistance dynamics of various bacterial strains isolated between 2019 and 2023 in a hospital unit; Methods: A total of 8217 clinical specimens (urine, wound secretions, sputum, pharyngeal exudate, nasal exudate, tracheal secretions, vaginal and cervical secretions, puncture fluids, purulent secretions, blood, ear secretions, eye secretions) were processed using standard microbiological techniques. Pathogen identification and susceptibility testing were performed with the VITEK 2 Compact system, following CLSI guidelines. Results: Following the analysis of 8217 clinical samples collected over a five-year period (2019–2023), a total of 2900 microorganisms were isolated and identified. Among these, the most frequently encountered were E. coli strains, with 1204 isolates. Urine cultures represented 71.3% of all processed samples. Out of these 5860 urine cultures, 1530 (26%) were positive. The resistance of E. coli strains to ampicillin (48–55.2%), trimethoprim/sulfamethoxazole (22.9–34%), and ciprofloxacin (21.4–31.5%) remained high throughout the period. ESBL-producing strains peaked at 17.6% in 2020, with multidrug resistance rates ranging from 14% to 22.4%. Conclusions: E. coli strains displayed persistently high resistance to ampicillin, trimethoprim/sulfamethoxazole, and ciprofloxacin, with peaks in ESBL production and multidrug resistance during the COVID-19 pandemic. These trends underscore the importance of continuous surveillance and antibiotic stewardship, with direct implications for empirical UTI therapy and broader strategies to mitigate the public health impact of antimicrobial resistance.

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.

Background: As far as 80% of people diagnosed with multiple sclerosis (MS) experience disabling symptoms in the course of the disease, such as spasticity and neuropathic pain. As first-line symptomatic therapy is associated with important adverse reactions, cannabinoids have become increasingly popular among patients with MS. This review intends to provide an overview of the evidence of the role of cannabinoids in treating symptoms related to MS and to encourage further research on this matter. Areas of Uncertainty: To date, the evidence supporting the role of cannabis and its derivatives in alleviating the MS-related symptoms comes only from studies on experimental models of demyelination. To the best of our knowledge, relatively few clinical trials inquired about the therapeutic effects of cannabinoids on patients with MS, with variable results. Data Sources: We conducted a literature search through PubMed and Google Scholar from the beginning until 2022. We included articles in English describing the latest findings regarding the endocannabinoid system, the pharmacology of cannabinoids, and their therapeutic purpose in MS. Results: Evidence from preclinical studies showed that cannabinoids can limit the demyelination process, promote remyelination, and have anti-inflammatory properties by reducing immune cell infiltration of the central nervous system in mice with experimental autoimmune encephalomyelitis. Moreover, it has been established that experimental autoimmune encephalomyelitis mice treated with cannabinoids experienced a significant reduction of symptoms and slowing of the disease progression. Given the complexity of human immune and nervous systems, cannabinoids did not have the anticipated effects on human subjects. However, data obtained from clinical trials showed some beneficial results of cannabinoids as a single or as add-on therapy in reducing the spasticity and pain related to MS. Conclusion: Considering their various mechanisms of action and good tolerability, cannabinoids remain an interesting therapy for spasticity and chronic pain related to MS.

Background/Objectives: Healthcare-associated infections (HAIs), particularly those caused by multidrug-resistant (MDR) bacteria, remain a major challenge for Romanian hospitals. This study aimed to evaluate the epidemiological burden of MDR-related HAIs and to characterize the distribution of MDR bacterial isolates and their antimicrobial resistance patterns over four consecutive semesters in a Romanian tertiary care hospital. Methods: A retrospective study was conducted using data from the Electronic Registry of HAIs, clinical observation sheets, and microbiology laboratory records. An epidemiological analysis was performed on patients diagnosed with MDR-related HAIs, while a separate microbiological analysis included all MDR bacterial isolates identified during the study period. Descriptive and comparative statistical analyses were applied to assess temporal trends, pathogen distribution, and resistance profiles. Results: Of the 327 HAIs identified, 56 cases (17.13%) were caused by MDR bacteria. Most MDR-HAIs originated from the Intensive Care Unit (≈60%), with Acinetobacter baumannii and Klebsiella spp. as the predominant pathogens. Overall mortality among patients with MDR-HAIs was high (51.79%), particularly in infections caused by A. baumannii and K. pneumoniae. Microbiological analysis of MDR isolates (n = 406) revealed consistently high resistance rates to ciprofloxacin, cefepime, and ceftazidime, exceeding 95% in 2023–2024, while resistance to carbapenems surpassed 90% by the end of the study period. Temporal variability in MDR burden was observed across semesters, suggesting an influence of clinical and institutional factors. Conclusions: MDR-related HAIs represent a significant and persistent problem in Romanian acute-care hospitals, particularly in Intensive Care Units. The dominance of carbapenem-resistant A. baumannii and extended-spectrum beta-lactamase-producing and carbapenem-resistant Klebsiella spp. highlights the urgent need for strengthened antimicrobial stewardship, enhanced microbiological surveillance, and reinforced infection prevention strategies.