Carbapenemase-producing Enterobacterales (CPE) represent an important threat to global health, resulting in an urgent issue in clinical settings. CPE often exhibit a multidrug-resistant (MDR) phenotype, thus reducing the antimicrobial armamentarium, with few antibiotics retaining residual antimicrobial activity against these pathogens. Carbapenemases are divided into three classes (A, B, and D) according to the Ambler classification system. Among these, KPC (class A), NDM, VIM, IMP (class B), and OXA-48-like (class D) represent the most important carbapenemases in terms of diffusion and clinical impact. CPE diffusion has been observed worldwide, with current endemicity in multiple territories around the world. In this context, the clonal spread and plasmid-mediated transmission of carbapenemases have contributed to the global spread of CPE worldwide and to the diffusion of carbapenemases among different Enterobacterales species. In recent years, novel molecules showing excellent in vitro and in vivo activity have been developed against CPE. However, the recent emergence of novel traits of resistance to these molecules has already been reported in several cases, mitigating the initial promising results. This review aims to provide an updated description of the major classes of carbapenemases, their global distribution, and future perspectives to limit the diffusion of CPEs.

Recently Candida auris has emerged as a multi-resistant fungal pathogen, with a significant clinical impact, and is able to persist for a long time on human skin and hospital environments. It is a critical issue on the WHO fungal priority list and therefore it is fundamental to reinforce hospital surveillance protocols to limit nosocomial outbreaks. The purpose of this study was to apply Fourier transform infrared spectroscopy (FT-IR) to investigate the phylogenetic relationships among isolated strains from a C. auris outbreak at the University Intensive Care Unit of a Tertiary University hospital in Turin (Italy). To calculate a clustering cut-off, intra- and inter-isolate, distance values were analysed. The data showed the presence of a major Alfa cluster and a minor Beta cluster with a defined C. auris clustering cut-off. The results were validated by an external C. auris strain and Principal Component and Linear Discriminant Analyses. The application of FT-IR technology allowed to obtain important information about the phylogenetic relationships between the analysed strains, defining for the first time a “not WGS-based” clustering cut-off with a statistical–mathematical approach. FT-IR could represent a valid alternative to molecular methods for the rapid and cost-saving typing of C. auris strains with important clinical implications.

Respiratory infections, particularly of the upper airways, play an important role in human pathologies, with them being the most common cause of disease in both children and adults, with a relevant impact on healthcare systems. Pathogen identification is particularly important in critical patients, with molecular assays being the most used methods. Herein, the molecular epidemiology of respiratory viruses in Northwestern Italy was studied by using an upper respiratory tract syndromic panel over a period of eight years, from January 2016 to December 2023, in order to evaluate the impact of the COVID-19 pandemic in this particular geographic area. Overall, over the study period, 22,270 tests were performed; in particular, 12,882 were performed in pediatric patients and 9388 in the adult population. Based on the analysis of the epidemiological trends, the complete disappearance of some viruses during the restriction periods was observed, as well as their resumption soon afterward; in particular, positive rates of Influenza A and B and Respiratory Syncytial Virus decreased at the end of 2020 and during 2021, whereas only Respiratory Syncytial Virus increased at the end of 2021. As expected, this study evidenced the relevant modifications that occurred in the typical epidemiology of respiratory viruses throughout the periods before, during, and after the COVID-19 pandemic and supported the role of syndromic panels in the diagnostic workflow of common respiratory infections.

Antimicrobial resistance (AMR) represents one of the most urgent global health threats, significantly impacting patient outcomes, healthcare systems, and economic sustainability. Rapid and accurate antimicrobial susceptibility testing (AST) are essential to guide targeted therapy, reduce inappropriate antimicrobial use, and support antimicrobial stewardship programs. However, conventional phenotypic AST methods, including broth microdilution, disk diffusion, agar dilution, and gradient strip tests, remain labor-intensive and require prolonged turnaround times, often delaying optimal therapeutic decisions. Although automated commercial platforms such as VITEK 2, BD Phoenix, MicroScan WalkAway, and Sensititre ARIS have improved laboratory workflow and standardization, they still rely on culture-based approaches and typically require 16–36 h to generate minimum inhibitory concentration (MIC) results. In recent years, several innovative rapid phenotypic AST technologies have emerged, aiming to significantly shorten the time to susceptibility results while maintaining high accuracy. This review provides an overview of currently available rapid automated phenotypic platforms for MIC determination, including VITEK^® Reveal™, ASTar, FASTinov^®AST, QuickMIC^®, and the Accelerate Pheno^® system. These systems employ advanced technologies such as volatile organic compound detection, flow cytometry, microfluidics, real-time imaging, and morphokinetic cellular analysis to deliver susceptibility results within a few hours directly from positive blood cultures. We summarize their technical principles, antibiotics and pathogens included, performances, and current limitations. Overall, the implementation of rapid phenotypic AST tools has the potential to substantially improve clinical decisions, optimize antimicrobial therapy, and contribute to fight AMR.

Recently Candida auris has emerged as a multi-resistant fungal pathogen, with a significant clinical impact, and has become a critical issue in WHO fungal priority list, due to its unique ability to persist for long time on human skin and hospital environments. It is therefore fundamental to reinforce hospital surveillance protocols to limit nosocomial outbreaks. The study purpose was the Fourier-Transform Infrared Spectroscopy (FT-IR) application to investigate the phylogenetic relationships between isolated strains within the C. auris outbreak at the university Intensive Care Unit of a Tertiary University hospital in Turin (Italy). In order to calculate a clustering cut-off, intra- and inter-isolates distance values were analysed. Data showed the presence of a major cluster Alfa and a minor cluster Beta with a defined C. auris clustering cut-off. The results were validated by an external C. auris strain and Principal Component and Linear Discriminant Analysis. The application of FT-IR technology had allowed to obtain important information about the phylogenetic relationships between the analysed strains, defining for the first time a “not WGS-based” clustering cut-off with a statistical-mathematical approach. FT-IR could represent a valid alternative to molecular methods for rapid and cost saving typing of C. auris strains with important clinical implications.

Background: Lung transplantation is a life-saving option for patients with end-stage respiratory diseases, but risk of infections remains critical for ensuring long-term organ function. This study aimed to assess immune recovery in lung transplant recipients by measuring IFN-γ levels using the QuantiFERON Monitor Test (QFM). Results were correlated with episodes of infection and organ rejection to explore the assay’s predictive potential. Methods: A retrospective study was conducted on 15 lung transplant recipients at the Lung Transplant Centre of Turin (Città della Salute e della Scienza di Torino, Italy) between December 2019 and January 2023. Patients were divided into a High Infection (HI) group (with >3 infections) and Low Infection (LI) group (with ≤3 infections). QFM assays were performed after 18 months post-transplant. Results: HI patients had lower QFM levels compared to LI (68.84 ± 21.98 vs. 380.54 ± 104.64 UI/mL, p = 0.033). A QFM value <89.5 UI/mL was associated with increased infection risk (p < 0.05). Patients with lower QFM levels also exhibited higher rates of MRSA bacteremia during hospitalization (50% HI vs. 0% LI, p = 0.04). No differences were observed in acute or chronic rejection rates, but LI patients showed more frequent alveolar neutrophilia at the fourth month post-transplant (0% HI vs. 55.5% LI, p = 0.04). Conclusion: lower QFM values were associated with higher infection risk, highlighting the assay’s potential for immune monitoring. In this study, a QFM value of 89.5 UI/mL showed good predictive accuracy for infections beyond 18 months. Further studies are needed to refine QFM’s role in post-transplant care.