The human gut microbiota is considered a well-known complex ecosystem composed of distinct microbial populations, playing a significant role in most aspects of human health and wellness. Several factors such as infant transitions, dietary habits, age, consumption of probiotics and prebiotics, use of antibiotics, intestinal comorbidities, and even metabolic diseases may continously alter microbiota diversity and function. The study of vegan diet–microbiota interactions is a rapidly evolving field, since plenty of research has been focused on the potential effects of plant-based dietary patterns on the human gut microbiota. It has been reported that well-planned vegan diets and their associated components affect both the bacterial composition and metabolic pathways of gut microbiota. Certain benefits associated with medical disorders but also limitations (including nutritional deficiencies) have been documented. Although the vegan diet may be inadequate in calorific value, it is rich in dietary fiber, polyphenols, and antioxidant vitamins. The aim of the present study was to provide an update of the existing knowledge on nutritional status of vegan diets and the influence of their food components on the human gut microbiota and health.

Changes in hospitals’ daily practice due to COVID-19 pandemic may have an impact on antimicrobial resistance (AMR). We aimed to assess this possible impact as captured by the Greek Electronic System for the Surveillance of Antimicrobial Resistance (WHONET-Greece). Routine susceptibility data of 17,837 Gram-negative and Gram-positive bacterial isolates from blood and respiratory specimens of hospitalized patients in nine COVID-19 tertiary hospitals were used in order to identify potential differences in AMR trends in the last three years, divided into two periods, January 2018–March 2020 and April 2020–March 2021. Interrupted time-series analysis was used to evaluate differences in the trends of non-susceptibility before and after the changes due to COVID-19. We found significant differences in the slope of non-susceptibility trends of Acinetobacter baumannii blood and respiratory isolates to amikacin, tigecycline and colistin; of Klebsiella pneumoniae blood and respiratory isolates to meropenem and tigecycline; and of Pseudomonas aeruginosa respiratory isolates to imipenem, meropenem and levofloxacin. Additionally, we found significant differences in the slope of non-susceptibility trends of Staphylococcus aureus isolates to oxacillin and of Enterococcus faecium isolates to glycopeptides. Assessing in this early stage, through surveillance of routine laboratory data, the way a new global threat like COVID-19 could affect an already ongoing pandemic like AMR provides useful information for prompt action.

Antimicrobial resistance (AMR) poses a critical global health threat. Wastewater surveillance has recently emerged as a valuable public health tool for monitoring AMR in communities and healthcare settings. This narrative review comprehensively examines the role of hospital wastewater surveillance (HWWS) in monitoring antimicrobial resistance. Methods to detect resistant bacteria and antimicrobial resistance genes (ARGs) in wastewater systems, ranging from culture-based techniques to advanced molecular approaches, including polymerase chain reaction (PCR) and next-generation sequencing (NGS), are explored. The review synthesizes data on key antimicrobial resistance genes commonly detected in hospital effluents and explores how HWWS contributes to understanding the dynamics of resistance within healthcare settings. Furthermore, it identifies methodological challenges and inconsistencies in data reporting and outlines necessary standardization steps to enhance the effectiveness of HWWS programs. Opportunities for integrating HWWS with clinical and public health frameworks are presented, emphasizing the need for robust metadata and transparent reporting. This review provides a comprehensive approach to HWWS strategies, which could complement robust infection control and antibiotic stewardship interventions to combat AMR.

Onychomycosis is considered as one of the major public health problems with a global distribution associated with geographic, demographic and environmental factors, underlying comorbidities and immunodeficiency disorders. This study was conducted to investigate the etiological agents of onychomycosis, in Northwestern Greece during a 7-year period. The study population included 1095 outpatients with clinically suspected onychomycosis that presented to the University Hospital of Ioannina, NW Greece (2011–2017). Samples were examined for causative fungi, and mycological identification was established using standard mycological methods. Demographic data of each patient, comorbidities, localization of infection and history of previous fungal infection were collected. Onychomycosis was diagnosed in 317 of the 1095 suspected cases (28.9%) and the most frequently isolated pathogens were yeasts (50.8%) followed by dermatophytes (36.9%) and non-dermatophyte molds (NDMs) (12.3%). Dermatophytes were mostly involved in toenail onychomycosis (90.6%) and more commonly affected males than females (57.3% vs. 42.7%), while the predominantly isolated pathogen was Τrichophyton rubrum (74.4%) followed by Τrichophyton interdigitale (21.4%). Candida albicans was the most prevalent isolated yeast (82%), whereas among the cases with onychomycosis due to NDMs, Aspergillus spp. were isolated as the principal species (59%). Continuous monitoring should be performed in order to identify possible trends and shifts in species isolation rates and to evaluate the impact of onychomycosis among the general population and high-risk groups.

The emergence of multidrug-resistant bacteria is undoubtedly one of the most serious global health threats. One response to this threat that has been gaining momentum over the past decade is ‘phage therapy’. According to this, lytic bacteriophages are used for the treatment of bacterial infections, either alone or in combination with antimicrobial agents. However, to ensure the efficacy and broad applicability of phage therapy, several challenges must be overcome. These challenges encompass the development of methods and strategies for the host range manipulation and bypass of the resistance mechanisms developed by pathogenic bacteria, as has been the case since the advent of antibiotics. As our knowledge and understanding of the interactions between phages and their hosts evolves, the key issue is to define the host range for each application. In this article, we discuss the factors that affect host range and how this determines the classification of phages into different categories of action. For each host range group, recent representative examples are provided, together with suggestions on how the different groups can be used to combat certain types of bacterial infections. The available methodologies for host range expansion, either through sequential adaptation to a new pathogen or through genetic engineering techniques, are also reviewed.

Several SARS-CoV-2 variants have emerged and early detection for monitoring their prevalence is crucial. Many identification strategies have been implemented in cases where sequencing data for confirmation is pending or not available. The presence of B.1.1.318 among prevalent variants was indicated by an unusual amplification pattern in various RT-qPCR commercial assays. Positive samples for SARS-CoV-2, as determined using the Allplex SARS-CoV-2 Assay, the Viasure SARS-CoV-2 Real Time Detection Kit and the GeneFinder COVID-19 Plus RealAmp Kit, presented a delay or failure in the amplification of the N gene, which was further investigated. Whole-genome sequencing was used for variant characterization. The differences between the mean Ct values for amplification of the N gene vs. other genes were calculated for each detection system and found to be at least 14 cycles. Sequencing by WGS revealed that all the N gene dropout samples contained the B.1.1.318 variant. All the isolates harbored three non-synonymous mutations in the N gene, which resulted in four amino acid changes (R203K, G204R, A208G, Met234I). Although caution should be taken when the identification of SARS-CoV-2 variants is based on viral gene amplification failure, such patterns could serve as a basis for rapid and cost-effective screening, functioning as indicators of community circulation of specific variants, requiring subsequent verification via sequencing.