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Abstract Tuberculosis (TB) is one of the deadliest infectious disorders in the world. To effectively TB manage, an essential step is to gain insight into the lineage of Mycobacterium tuberculosis (MTB) and the distribution of drug resistance. Although the Campania region is declared a cluster area for the infection, to contribute to the effort to understand TB evolution and transmission, still poorly known, we have generated a dataset of 159 genomes of MTB strains, from Campania region collected during 2018–2021, obtained from the analysis of whole genome sequence. The results show that the most frequent MTB lineage is the 4 according for 129 strains (81.11%). Regarding drug resistance, 139 strains (87.4%) were classified as multi susceptible, while the remaining 20 (12.58%) showed drug resistance. Among the drug-resistance strains, 8 were isoniazid-resistant MTB, 4 multidrug-resistant MTB, while only one was classified as pre-extensively drug-resistant MTB. This dataset expands the existing available knowledge on drug resistance and evolution of MTB, contributing to further TB-related genomics studies to improve the management of this disease.

This case report describes the identification of Ochrobactrum anthropi (O.a.), from a positive blood culture using MALDI-TOF spectrometry system. According to the information availed this is the first case in AORN Sant’Anna and San Sebastiano, Caserta, Campania, Italy. This microbe is moderately pathogenic and hazardous, with the potential to cause hospital-acquired infections. It is recommended that it be included in hospital “germ alerts”.

The nasopharyngeal tract contains a complex microbial community essential to maintaining host homeostasis. Recent studies have shown that SARS-CoV-2 infection changes the microbial composition of the nasopharynx. Still, little is known about how it affects the fungal microbiome, which could provide valuable insights into disease pathogenesis. Nasopharyngeal swabs were collected from 55 patients, during three distinct COVID-19 waves that occurred in the Campania Region (southern Italy). An RNA-seq-based analysis was performed to evaluate changes in mycobiota diversity, showing variations depending on the disease’s severity and the sample collection wave. The phyla Basidiomycota and Ascomycota were shown to have higher abundance in patients with severe symptoms. Furthermore, the diversity of the fungal population was greater in the second wave. Conclusion: According to our research, COVID-19 induces significant dysbiosis of the fungal microbiome, which may contribute to disease pathogenesis, and understanding its underlying mechanisms could contribute to developing effective treatments.

Background Cancer immunotherapy has revolutionized cancer treatment. However, considering the limited success of immunotherapy to only some cancer types and patient cohorts, there is an unmet need for developing new treatments that will result in higher response rates in patients with cancer. Immunoglobulin-like transcript 2 (ILT2), a LILRB family member, is an inhibitory receptor expressed on a variety of immune cells including T cells, natural killer (NK) cells and different myeloid cells. In the tumor microenvironment, binding of class I MHC (in particular HLA-G) to ILT2 on immune cells mediates a strong inhibitory effect, which manifests in inhibition of antitumor cytotoxicity of T and NK cells, and prevention of phagocytosis of the tumor cells by macrophages.Methods We describe here the development and characteristics of BND-22, a novel, humanized monoclonal antibody that selectively binds to ILT2 and blocks its interaction with classical MHC I and HLA-G. BND-22 was evaluated for its binding and blocking characteristics as well as its ability to increase the antitumor activity of macrophages, T cells and NK cells in various in vitro, ex vivo and in vivo systems.Results Collectively, our data suggest that BND-22 enhances activity of both innate and adaptive immune cells, thus generating robust and comprehensive antitumor immunity. In humanized mice models, blocking ILT2 with BND-22 decreased the growth of human tumors, hindered metastatic spread to the lungs, and prolonged survival of the tumor-bearing mice. In addition, BND-22 improved the antitumor immune response of approved therapies such as anti-PD-1 or anti-EGFR antibodies.Conclusions BND-22 is a first-in-human ILT2 blocking antibody which has demonstrated efficient antitumor activity in various preclinical models as well as a favorable safety profile. Clinical evaluation of BND-22 as a monotherapy or in combination with other therapeutics is under way in patients with cancer.Trial registration number NCT04717375.

Bacterial co-infection in COVID-19 patients significantly contributes to the worsening of the prognosis based on morbidity and mortality. Information on the co-infection profile in such patients could help to optimize treatment. The purpose of this study was to describe bacterial co-infections associated with microbiological, clinical, and laboratory data to reduce or avoid a secondary infection. A retrospective cohort study was conducted at Sant’Anna and San Sebastiano Hospital from January 2020 to December 2021. Bacterial co-infection was detected in 14.3% of the COVID-19-positive patients. The laboratory findings on admission showed significant alterations in the median D-dimer, C-reactive protein, interleukin-6, and lactate dehydrogenase values compared to normal values. All inflammatory markers were significantly elevated. The most common pathogens isolated from blood cultures were E. faecalis and S. aureus. Instead, the high prevalence of respiratory tract infections in the COVID-19 patients was caused by P. aeruginosa (41%). In our study, 220 (82.4%) of the COVID-19 patients received antimicrobial treatment. Aminoglycosides and β-lactams/β-lactamase inhibitors showed the highest resistance rates. Our results showed that older age, underlying conditions, and abnormal laboratory parameters can be risk factors for co-infection in COVID-19 patients. The antibiotic susceptibility profile of bacterial pathogen infection provides evidence on the importance, for the clinicians, to rationalize and individualize antibiotic usage.

In the world of structural design, in most cases, there is a need to control the shape of structural elements and—at the same time—the performance that each one can achieve. With the evolution of structural analysis tools, nowadays it is possible not only to have an immediate investigation of the structure’s performance, but also to search for the best shape by imposing geometric constraints. The aim of this paper is to present an innovative methodology called the performative structural design optimization (PSDO) method, based on the use of algorithm-aided design (AAD). The proposed approach deals with an emptied voided beam; starting from the parameterization of a large-span beam, the search method for the most performing shape is accomplished by multi-objective evolutionary algorithms (MOEAs). The obtained results are characterized by a double optimization: the structure achieved by the hypervolume estimation algorithm for multi-objective optimization (HypE Reduction) (OCTOPUS) represents the starting shape for the application of form-finding, giving so the possibility to obtain different feasible solutions from a single study and to choose the best one in terms of structural behavior.