Giulia Gatti

Accurate hepatitis B virus (HBV) DNA quantification is essential for assessing viral replication and monitoring antiviral therapy. This retrospective method-comparison study evaluated the Bosphore HBV Quantification Kit against the Aptima HBV Quant Assay using 130 residual anonymized EDTA-plasma specimens, comprising 110 comparator-positive and 20 comparator-negative samples. Categorical agreement was assessed using positive, negative, and overall percent agreement (PPA, NPA, and OPA), while quantitative agreement was evaluated using a predefined ±0.5 log₁₀ IU/mL criterion, Bland–Altman analysis, Passing–Bablok regression, and Lin’s concordance correlation coefficient (CCC). PPA was 100% (110/110; 95% confidence interval [CI], 96.70–100.00%), NPA was 95.0% (19/20; 95% CI, 75.13–99.87%), and OPA was 99.23% (129/130; 95% CI, 95.79–99.98%). One confirmed qualitative discordance was observed. Overall, 109/110 paired numerical results (99.1%; 95% CI, 95.04–99.98%) were within ±0.5 log₁₀ IU/mL. Bland–Altman analysis showed a mean bias of +0.124 log₁₀ IU/mL, Passing–Bablok regression yielded Y = 0.107 + 1.019X, and Lin’s CCC was 0.991. The Bosphore assay demonstrated high categorical and quantitative agreement with the comparator across the HBV DNA concentration range evaluated, supporting its potential suitability for quantitative HBV DNA testing within the analytical workflow assessed in this study.

Background/Objectives: Modifiable dietary and lifestyle factors may contribute to gut microbiota variation but are often evaluated separately. This pilot study examined four exposures across complementary microbiome domains and used association magnitude and uncertainty to inform longitudinal study design. Methods: Twenty healthy adults (10 females and 10 males) provided a fresh-stool specimen and completed the exposure questionnaire on the day of specimen production. Exposures comprised Mediterranean diet adherence, ultra-processed food consumption frequency, physical activity, and sleep characteristics. Microbiome outcomes comprised independently recalculated OTU-level Shannon diversity (primary outcome) and Pielou’s evenness, genus-level Bray–Curtis and Aitchison distances, centered log-ratio coordinates of eight prespecified genera, and the natural-log-transformed Prevotella/Bacteroides ratio. Associations were evaluated using age- and sex-adjusted linear regression and permutational multivariate analysis of variance, with false-discovery-rate control, influence diagnostics, and robustness analyses. Scenario-based sample-size calculations were restricted to age- and sex-adjusted cross-sectional linear regression models. Results: Complete exposure and microbiome data were available for all participants. No association was supported after false-discovery-rate correction. However, the observed effect estimates were not uniformly negligible: maximum partial R² values were 0.140 across the alpha-diversity models, 0.210 for the UPF–Akkermansia association, and 0.108 for the Prevotella/Bacteroides log-ratio, whereas the maximum marginal R² for overall community composition was 0.0649. Estimates were imprecise and participant-sensitive, and robustness analyses did not alter the overall interpretation. Conservative scenarios for age- and sex-adjusted cross-sectional regression models, based on assumed partial R² values of 0.03–0.05, yielded planning benchmarks of 275–465 analyzable participants, or 306–582 enrolled participants assuming 10–20% unusable observations. Conclusions: This pilot does not establish the absence of diet–microbiota or lifestyle–microbiota relationships. Instead, it provides a reproducible framework for prioritizing hypotheses and planning adequately powered longitudinal studies using repeated, temporally aligned exposure and microbiome measurements.

Pre-analytical variables, including specimen transport media, may influence the performance of molecular assays used for respiratory pathogen detection. Universal Biomolecular Medium (UBM™) has been developed to support nucleic acid preservation and molecular testing, but evidence regarding its analytical compatibility with routinely used molecular platforms remains limited. We conducted a retrospective paired comparison of UBM™ against conventional transport and lysis media across multiple molecular platforms to evaluate the post-collection analytical compatibility of UBM. Residual respiratory specimens positive for SARS-CoV-2, influenza A virus, influenza B virus, respiratory syncytial virus, human rhinovirus, human metapneumovirus, Haemophilus influenzae, Mycoplasma pneumoniae, and Bordetella pertussis were analyzed. Paired aliquots generated from the same specimen were tested using the Allplex™ SARS-CoV-2/FluA/FluB/RSV Assay, Xpert^® Xpress CoV-2/Flu/RSV plus, Panther Fusion^® SARS-CoV-2/Flu A/B/RSV Assay, and selected Allplex™ respiratory panels. Analytical agreement and cycle threshold (Ct) values were compared using paired statistical analyses and Bland–Altman methods. UBM demonstrated complete qualitative concordance with comparator media across all evaluated targets and platforms, yielding 100% positive, negative and overall agreement. Although statistically significant Ct differences were observed for selected target–platform combinations, these shifts were generally small and did not affect qualitative result interpretation. Internal control performance remained stable across media. These findings support the post-collection analytical compatibility of UBM™ with the evaluated molecular workflows.

Acute infectious gastroenteritis (AIG) is caused by diverse bacterial and viral enteric pathogens with overlapping clinical presentations, limiting conventional pathogen-directed workflows. This retrospective before–after study evaluated the diagnostic, microbiological, operational, and economic impact of multiplex molecular syndromic testing for AIG within a regional hub-and-spoke laboratory network in Italy. Two 19-month periods were compared: a pre-implementation period based on conventional diagnostics and a post-implementation period using multiplex syndromic panels as first-line tests. Diagnostic investigations totalled 25,574 before and 24,509 after implementation. Overall test positivity increased from 5.43% to 11.59% (p < 0.001), with significant increases for bacterial and viral targets. Pathogen detection events increased from 1388 to 2839, including broader detection of Campylobacter spp., Shigella spp./enteroinvasive Escherichia coli (EIEC), Yersinia enterocolitica, Aeromonas spp., Astrovirus, Sapovirus, and Norovirus genogroups. Mean turnaround time decreased from 63 to 47 h from sample collection and from 56 to 41 h from laboratory check-in. Although direct diagnostic costs increased moderately, total laboratory costs decreased when personnel costs were included, and cost per diagnostic detection declined from €233.80 to €120.86. Multiplex syndromic testing improved microbiological detection, diagnostic efficiency, turnaround time, and laboratory organisation in routine AIG diagnosis.

Sexually transmitted infections (STIs) remain a major global public health concern, with more than one million new cases acquired daily and increasing antimicrobial resistance compromising effective control strategies. Rapid, accurate and multiplex molecular diagnostics are therefore essential to support timely clinical management and public health surveillance. This study evaluated the analytical and clinical performance of the cartridge-based STANDARD™ M10 STI Panel (SD Biosensor, Republic of Korea), a fully automated, random-access real-time PCR assay capable of detecting eight STI-related pathogens within approximately 64 min. A total of 150 residual clinical specimens were retrospectively analysed, including vaginal, rectal, urethral and oropharyngeal swabs, as well as seminal fluids, and results were compared with those obtained using the Allplex™ STI Essential Assay (Seegene, Republic of Korea), which shares six common targets. The STANDARD™ M10 STI Panel demonstrated high diagnostic accuracy, with sensitivity ranging from 89.5% to 100%, specificity from 98.2% to 100% and overall accuracy between 98% and 100%. Agreement between the two assays was almost perfect, with Cohen’s κ values ranging from 0.91 to 1.00. Analytical sensitivity was further confirmed through verification of the limits of detection using quantified reference standards. Although validated for urine samples, the assay also showed robust performance on alternative clinical matrices, particularly vaginal swabs. Overall, these findings indicate that the STANDARD™ M10 STI Panel represents a reliable and practical tool for STI diagnosis, combining rapid turnaround time, minimal hands-on requirements and broad pathogen coverage in both centralized and near-patient testing settings.

Introduction: The implementation of advanced technologies and algorithms for diagnosis and genome analysis has made a fundamental contribution to pathogens’ identification and investigation. Methods: The study of non-tuberculous mycobacteria (NTM) benefited from a next-generation sequencing (NGS) approach, making it possible to describe sequences of rare pathogens. This study identified 20 diagnostically unknown isolates as Mycobacterium saskatchewanense ST 691, an environmental NTM. The isolates were sequenced on two different platforms to compare their throughput and to investigate shared and unique single nucleotide polymorphism (SNP) counts, phylogeny based on concatenated 16S, hsp65, and rpoB genes, and core-genome multilocus sequence typing (MLST), in order to broaden the current knowledge of Mycobacterium saskatchewanense . Results: Principal component analysis on the three genes combined with the mutations’ annotation suggests that rpoB may serve as a suitable marker to distinguish M. saskatchewanense from other NTM. Discussion: Our results show that frontier studies performed using NGS can help in overcoming the limits of traditional diagnostic assays and deepen the knowledge on rare and uncommon NTM that are raising clinical concern.

The COVID-19 pandemic has significantly impacted human society at many levels, from public health to economics and transports, highlighting the need of approaches integrating all available information to better understand and model similar phenomena, also in order to develop early detection and responses. In this paper we show the result of an analysis of COVID-19 pandemic in the metropolitan area of Bologna, Italy, integrating an epidemiological mathematical model, SARS-CoV-2 virus quantification in wastewater, clinical hospitalization, vaccination campaign, virus geno-typization and human mobility data in the period 2020-2022. We were able to follow the evolution of epidemic, observing the effect of vaccination and other factors that produced significant changes in hospitalizations. Moreover, by considering a mathematical model of COVID-19 epidemics spread, with parameters selected partly from literature and partly adapted to the local situation on a weekly basis, we identified a strict relation between human mobility at mesoscopic level and a sociability rate (related to model reproduction number) revealing the mutual impact of health issues on human activity and viceversa.

The freshwater environment is suitable for nontuberculous mycobacteria (NTMs) growth. Their high adaptability represents a considerable risk for sanitary water systems, which are a potential vector for NTMs transmission. This study investigated the occurrence of NTMs, such as Mycobacterium saskatchewanense, in hospital water systems to support the surveillance and control of potentially pathogenic NTMs. We analyzed 722 ultrapure dialysis fluid samples from Emilia Romagna Dialysis Services. Among these, 35 samples were found to be positive for M. saskatchewanense. The strains were characterized using whole-genome sequencing (WGS) and variability analysis was carried out along the whole M. saskatchewanense genome. This investigation revealed the exclusive presence of M. saskatchewanense in these dialysis machines, with low genetic variability among all strains (with a low number of different alleles: <15). The strong similarity among the strain groups was also confirmed in the WGS-based ML tree, with very few significant nodes, and no clusters were identified. This research highlights the necessity of implementing surveillance protocols and investigating any potential link to human infections, as well as stressing the urgency of enhancing surveillance and infection control measures.

Staphylococcus argenteus, identified in 2006, represents a challenging case of bacterial taxonomic identification because of its high similarity to Staphylococcus aureus. In this context, neither mass spectrometry (MS) nor 16S gene analysis cannot precisely reveal the difference between the two species. In our study, the sensitivity to antibiotics of S. argenteus isolated from blood culture was tested, and the investigation of the bacterial genome was performed by Multi-Locus Sequence Typing (MLST) and Whole-Genome Next-Generation Sequencing (WG-NGS). The pathogen was identified as ST2250 and presented perfectly matched resistance genes, namely aph(3′)-III, mgrA, and sepA, whereas the virulence gene detected was scn. Two plasmids were found: the pSAS plasmid, belonging to the family of Inc18, and plasmid pN315, belonging to the Rep3 group. The epidemiological distribution and the spread of S. argenteus infection are scarcely documented, particularly when associated with sepsis. Therefore, a correct taxonomy identification, antibiogram, and resistance gene analysis may help in acquiring knowledge about this bacterium and implement its detection and treatment.