This study aims to screen for IgG antibodies against Toxoplasma gondii (T. gondii) in the sera of 155 newly diagnosed Human Immunodeficiency Virus (HIV) positive patients under surveillance in Greek Infectious Disease Units. Additionally, risk factors based on patient demographics were examined, and a comparative evaluation of commercially available serological methods was conducted. Three methods were employed to detect IgG antibodies against T. gondii: Enzyme-Linked Immunosorbent Assay (ELISA), Indirect Immunofluorescence Antibody Test (IFAT), and Western Blot (WB), which was used as a reference here. Forty-nine sera samples were true-positive for IgG antibodies against T. gondii, resulting in a 31.61% positivity rate, and the immunoassay test statistical reliability analysis resulted in higher IFAT accuracy (90.97%) compared to ELISA (76.26%). Furthermore, statistical analysis of demographic and immunological data included in the study placed female and foreign/non-Greek individuals at 2.24 (p = 0.0009) and 2.34 (p = 0.0006) times higher risk of positive T. gondii IgG testing compared to their male and Greek counterparts, respectively. Our findings on positivity rates and comparative serology underscore the importance of early and suitable screening measures for newly diagnosed HIV+ patients to mitigate the life-threatening outcomes that may arise from a potential subsequent T. gondii activation.

Background: The spatiotemporal profiling of molecular transmission clusters (MTCs) using viral genomic data can effectively identify transmission networks in order to inform public health actions targeting SARS-CoV-2 spread. Methods: We used whole genome SARS-CoV-2 sequences derived from ten European regions belonging to eight countries to perform phylogenetic and phylodynamic analysis. We developed dedicated bioinformatics pipelines to identify regional MTCs and to assess demographic factors potentially associated with their formation. Results: The total number and the scale of MTCs varied from small household clusters identified in all regions, to a super-spreading event found in Uusimaa-FI. Specific age groups were more likely to belong to MTCs in different regions. The clustered sequences referring to the age groups 50–100 years old (y.o.) were increased in all regions two weeks after the establishment of the lockdown, while those referring to the age group 0–19 y.o. decreased only in those regions where schools’ closure was combined with a lockdown. Conclusions: The spatiotemporal profiling of the SARS-CoV-2 MTCs can be a useful tool to monitor the effectiveness of the interventions and to reveal cryptic transmissions that have not been identified through contact tracing.

Predictive tools provide a unique opportunity to explain the observed differences in outcome between patients of the COVID-19 pandemic. The aim of this study was to associate individual demographic and clinical characteristics with disease severity in COVID-19 patients and to highlight the importance of machine learning (ML) in disease prognosis. The study enrolled 344 unvaccinated patients with confirmed SARS-CoV-2 infection. Data collected by integrating questionnaires and medical records were imported into various classification machine learning algorithms, and the algorithm and the hyperparameters with the greatest predictive ability were selected for use in a disease outcome prediction web tool. Of 111 independent features, age, sex, hypertension, obesity, and cancer comorbidity were found to be associated with severe COVID-19. Our prognostic tool can contribute to a successful therapeutic approach via personalized treatment. Although at the present time vaccination is not considered mandatory, this algorithm could encourage vulnerable groups to be vaccinated.

The evolving pandemic of Coronavirus Disease 2019 has posed a substantial health risk worldwide. However, there is a paucity of data regarding the clinical course and the therapeutic management of patients with chronic kidney disease and COVID-19 infection. To date, most evidence has come from renal transplantation, with about 45 patients reported thus far, and the current data from the ERA-EDTA (ERACODA) registry for transplanted patients and patients on Renal Replacement Therapy (RRT); as for those with glomerular diseases, data are lacking. Herein, we report the case of a 62-year-old patient with severe membranoproliferative glomerulonephritis who had been receiving a high burden of immunosuppression until four months before the COVID-19 infection. He developed severe disease with acute respiratory failure requiring mechanical ventilation. After treatment with hydroxychloroquine and azithromycin, despite his low chances, he gradually recovered and survived. To the best of our knowledge, this is one of the few reported patients with glomerulonephritis who had COVID-19 Besides our single case with glomerulonephritis early during the disease outbreak, the very low prevalence of COVID-19 infection in the country’s transplant recipients (0.038%) and dialysis patients (0.24%) reflects the impact of the rapid implementation of social distancing rules as well as of preventive measures for disease control in the hospitals and dialysis units in our country.

A serological screening was conducted to detect IgG antibodies against Leishmania infantum (L. infantum) in newly diagnosed human immunodeficiency virus (HIV) patients in Greece. The study also examined potential risk factors and the agreement of commercially available serological methods. IgG antibodies against L. infantum were detected using enzyme-linked immunosorbent assay (ELISA), indirect immunofluorescence antibody test (IFAT), and Western blot (WB). Out of 155 samples, 14 (9.0%) tested positive for IgG antibodies against L. infantum using at least two methods. Statistical analysis showed substantial agreement between WB and IFAT methods (Cohen’s kappa = 0.75) but moderate overall agreement among the three methods (Fleiss’ kappa = 0.42). Additionally, HIV+ intravenous drug users faced 3.55 times (p = 0.025) higher risk of testing positive for L. infantum IgG, positing that anthroponotic transmission between these patients is a plausible hypothesis based on existing literature. Non-invasive and cost-effective techniques are preferred to detect asymptomatic infections, and leishmaniasis screening should be conducted immediately after HIV diagnosis in endemic regions to enable prophylactic treatment for leishmaniasis in addition to antiretroviral therapy. To maximize sensitivity, performing at least two different serological methods for each patient is recommended.

COVID-19 has caused millions of deaths globally; however, the characterization of molecular biomarkers of severe disease remains of great scientific importance. The aim of this study was to capture the transcriptional differences of the whole blood gene expression between COVID-19 patients with mild and severe disease, using Next Generation Sequencing technologies, on admission and after 7 days. The genes which were differentially expressed in severe compared to mild patients were used for Gene Ontology (GO) enrichment analysis. Gene expression data were used to estimate the cell abundance of 22 immune cell types via digital cytometry. GO terms related to the response to molecules of bacterial origin, such as intestine-derived lipopolysaccharide (LPS), were enriched, among other dysregulated pathways, which are well described as paramount mechanisms of severe manifestations of COVID-19. The neutrophil population increased in patients with severe disease, whereas the monocyte, CD8⁺ T cell, and activated Natural Killer (NK) cell populations were depleted. These cell population dynamics are also indicative of severe COVID-19 and intestinal bacterial translocation. This study elucidates the molecular basis of severe COVID-19 and highlights intestinal bacterial translocation as a potential driver of severe disease.