Concomitant administration of multiple drugs frequently causes severe pharmacokinetic or pharmacodynamic drug–drug interactions (DDIs) resulting in the possibility of enhanced toxicity and/or treatment failure. The activity of cytochrome P450 (CYP) 3A4 and P-glycoprotein (P-gp), a drug efflux pump sharing localization and substrate affinities with CYP3A4, is a critical determinant of drug clearance, interindividual variability in drug disposition and clinical efficacy, and appears to be involved in the mechanism of numerous clinically relevant DDIs, including those involving dexamethasone. The recent increase in the use of high doses of dexamethasone during the COVID-19 pandemic have emphasized the need for better knowledge of the clinical significance of drug–drug interactions involving dexamethasone in the clinical setting. We therefore aimed to review the already published evidence for various DDIs involving dexamethasone in vitro in cell culture systems and in vivo in animal models and humans.

The incidence of pulmonary embolism (PE) is high during severe Coronavirus Disease 2019 (COVID-19). We aimed to identify predictive and prognostic factors of PE in non-ICU hospitalized COVID-19 patients. In the retrospective multicenter observational CLOTVID cohort, we enrolled patients with confirmed RT-PCR COVID-19 who were hospitalized in a medicine ward and also underwent a CT pulmonary angiography for a PE suspicion. Baseline data, laboratory biomarkers, treatments, and outcomes were collected. Predictive and prognostics factors of PE were identified by using logistic multivariate and by Cox regression models, respectively. A total of 174 patients were enrolled, among whom 86 (median [IQR] age of 66 years [55–77]) had post-admission PE suspicion, with 30/86 (34.9%) PE being confirmed. PE occurrence was independently associated with the lack of long-term anticoagulation or thromboprophylaxis (OR [95%CI], 72.3 [3.6–4384.8]) D-dimers ≥ 2000 ng/mL (26.3 [4.1–537.8]) and neutrophils ≥ 7.0 G/L (5.8 [1.4–29.5]). The presence of these two biomarkers was associated with a higher risk of PE (p = 0.0002) and death or ICU transfer (HR [95%CI], 12.9 [2.5–67.8], p < 0.01). In hospitalized non-ICU severe COVID-19 patients with clinical PE suspicion, the lack of anticoagulation, D-dimers ≥ 2000 ng/mL, neutrophils ≥ 7.0 G/L, and these two biomarkers combined might be useful predictive markers of PE and prognosis, respectively.

Sjögren syndrome (SS) is an autoimmune disease characterized by chronic inflammatory infiltrates in the salivary and lacrimal glands. Mucosal-associated invariant T (MAIT) cells are a subset of innate-like T-cells, predominantly found in mucosal tissues with crucial role in epithelial homeostasis. Thus, MAIT cells may be implicated in mucosal alterations of SS patients. Activation markers, inflammatory and cytotoxic cytokines were examined in 23 SS patients and compared to 23 healthy controls (HC). Tissular MAIT cells in salivary gland (SG) biopsies were also analyzed. Circulating MAIT cells were decreased in SS patients with a higher expression of CD69 and a higher CD4/CD8 ratio of MAIT cells. MAIT cells showed a higher production of IFNγ, TNFα and GzB in SS compare to HC. Tissular MAIT cells were present within inflamed SG of SS patients, while they were absent in SG of HC. Overall, circulating MAIT cells are decreased in the peripheral blood of SS albeit producing higher amounts of IFNγ, TNFα, and GzB. Tissular MAIT cells are detected in salivary glands from SS with a proinflammatory tissular cytokine environment. MAIT cells with abnormal phenotype, functions and tissular homeostasis may contribute to epithelial damage in SS.

Auto-immune and inflammatory diseases are heterogenous in their clinical manifestations and prognosis, even among individuals presenting with the same pathology. Understanding the immunological alterations involved in their pathogenesis provides valuable insights in different clinical phenotypes and treatment responses. Immunophenotyping could lead to significant improvements in diagnosis, monitoring, initial treatment decisions and follow-up in autoimmune and inflammatory diseases. Mass cytometry provides measurement of over 40 simultaneous cellular parameters at single-cell resolution, and therefore holds immense potential to evaluate complex cellular systems and for high-dimensional single-cell analysis. The high dimensionality of mass cytometry provides better coverage of immune populations dynamics, with sufficient power to identify rare cell types compared to flow cytometry. In this comprehensive review, we explore how mass cytometry findings contributed in the past decade to a deeper understanding of the cellular actors involved in systemic auto-immune and auto-inflammatory diseases with their respective therapeutic and prognostic impact. We also delve into the bioinformatical approaches applied to mass cytometry to analyze the high volumes of data generated, as well as the impact of the use of complementary single cell RNA sequencing, and their spatial modalities. Our analysis highlights the fact that mass cytometry captures major information on cell populations providing insights on the complex pathogenesis of autoimmune diseases. Future research designs could include mass cytometry findings in association to other -omics to stratify patients in adequate therapeutic arms and provide advancements in personalized therapies in the field of auto-immune and inflammatory diseases.

Diagnosis, prognostic assessment, and monitoring disease activity in patients with large vessel vasculitis (LVV) can be challenging. Early recognition of LVV and treatment adaptation is essential because vascular complications (aneurysm, dilatations, ischemic complications) or treatment related side effects can occur frequently in these patients. 18-fluorodeoxyglucose positron emission tomography/computed tomography (2-[18F]FDG-PET/CT) is increasingly used to diagnose, follow, and evaluate treatment response in LVV. In this review, we aimed to summarize the current evidence on the value of 2-[18F]FDG-PET/CT for diagnosis, follow, and treatment monitoring in LVV.