Emanuela G. Azara

Background: Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers, largely due to late diagnosis and the lack of reliable non-invasive biomarkers. Altered trace element homeostasis has been implicated in tumor biology and systemic inflammation, but comprehensive metallomic profiling in PDAC is still limited. Methods: Using inductively coupled plasma mass spectrometry (ICP-MS), we quantified 20 serum and 15 urinary metals in 71 PDAC patients and 69 matched controls. Statistical analyses included univariate Wilcoxon testing, correlation with systemic inflammatory indices (NLR, MLR, SIRI, AISI, HGB/RDW, PCT), and multivariate chemometric modeling (PCA-LDA). K-means clustering was applied to identify patient subgroups with distinct biochemical signatures. Results: PDAC patients showed significantly elevated urinary antimony, chromium, cadmium, and vanadium, whereas controls exhibited higher serum selenium, zinc, barium, vanadium, and cobalt (all p < 10⁻⁵). The PCA-LDA model achieved 99% classification accuracy (Monte Carlo cross-validation, 1000 iterations), highlighting complementary diagnostic contributions of serum and urinary profiles. Serum selenium was inversely associated with SIRI and NLR, while urinary cobalt correlated positively with NLR. Clustering revealed three PDAC subgroups with different inflammatory and metallomic patterns, suggesting underlying biological heterogeneity. Conclusions: PDAC is characterized by opposite serum-urine metal signatures, indicating altered absorption-excretion dynamics. Selenium depletion may represent a protective biomarker, whereas urinary cobalt excretion reflects systemic inflammation. This integrative ICP-MS–chemometric approach provides a promising diagnostic tool for improving early detection and patient stratification in clinical practice.

The aim is better to understand and critically explore and present the available data from observational studies on the pathogenetic role of the microbiome in the development of rheumatoid arthritis (RA). The electronic databases PubMed, Scopus, and Web of Science were screened for the relevant literature published in the last ten years. The primary outcomes investigated included the influence of the gut microbiome on the pathogenesis and development of rheumatoid arthritis, exploring the changes in microbiota diversity and relative abundance of microbial taxa in individuals with RA and healthy controls (HCs). The risk of bias in the included literature was assessed using the GRADE criteria. Ten observational studies were identified and included in the qualitative assessment. A total of 647 individuals with RA were represented in the literature, in addition to 16 individuals with psoriatic arthritis (PsA) and 247 HCs. The biospecimens comprised fecal samples across all the included literature, with 16S rDNA sequencing representing the primary method of biological analyses. Significant differences were observed in the RA microbiome compared to that of HCs: a decrease in Faecalibacterium, Fusicatenibacter, Enterococcus, and Megamonas and increases in Eggerthellales, Collinsella, Prevotella copri, Klebsiella, Escherichia, Eisenbergiella, and Flavobacterium. There are significant alterations in the microbiome of individuals with RA compared to HCs. This includes an increase in Prevotella copri and Lactobacillus and reductions in Collinsella. Collectively, these alterations are proposed to induce inflammatory responses and degrade the integrity of the intestinal barrier; however, further studies are needed to confirm this relationship.