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Aims: The contribution of SARS-CoV-2 infection on lung damage and the effect of vaccination on either containing the number of deaths or mitigating lung damage has not been systematically investigated., Methods: Post-mortem analysis was performed among consecutive in-patients with COVID-19 deceased in the Province of Trieste (2020-2022). The outcomes of the study were (i) rates of in-hospital mortality, (ii) contribution of COVID-19 to death, (iii) histological extent of lung injury and (iv) impact of vaccination., Results: A total of 1038 consecutive hospitalized patients who died with SARS-CoV-2 infection were autopsied and deep histological analysis of the lungs was performed in a randomly selected sample of 508 cases. Among them, SARS-CoV-2 infection was (a) the cause of death (n = 90), (b) contributing to death (n = 304) and (c) an accompanying feature (n = 114). The incidence of SARS-CoV-2 infection as the primary cause of mortality decreased over time (23.8% in 2020, 20.9% in 2021 and 7.9% in 2022). On multivariable analysis, vaccination (any dose) was independently associated with lower rates of death related to SARS-CoV-2 infection (HR .15, p < .001), after adjusting for other independent predictors. A total of 172 patients were vaccinated at least with two doses at the time of death: 93% triple-vaccinated, 7% double-vaccinated. On histological analysis, vaccinated patients had a greater frequency of pneumonia severity score 0 and 1 (20.3% vs. 5.4% and 20.9% vs. 7.7%, p < .001, respectively), and a substantially lower proportion of pneumonia severity score 3 (26.2% vs. 55.1%, p < .001) compared to unvaccinated patients., Conclusions: COVID-19 vaccination has substantially reduced rates of death related to SARS-CoV-2 infection over time and may have the ability to mitigate lung damage., (© 2024 The Author(s). European Journal of Clinical Investigation published by John Wiley & Sons Ltd on behalf of Stichting European Society for Clinical Investigation Journal Foundation.)

Background: The identification of the most appropriate targeted therapies for advanced cancers is challenging. We performed a molecular profiling of metastatic solid tumors utilizing a comprehensive next-generation sequencing (NGS) assay to determine genomic alterations' type, frequency, actionability, and potential correlations with PD-L1 expression., Methods: A total of 304 adult patients with heavily pretreated metastatic cancers treated between January 2019 and March 2021 were recruited. The CLIA-/UKAS-accredit Oncofocus assay targeting 505 genes was used on newly obtained or archived biopsies. Chi-square, Kruskal-Wallis, and Wilcoxon rank-sum tests were used where appropriate. Results were significant for P < .05., Results: A total of 237 tumors (78%) harbored potentially actionable genomic alterations. Tumors were positive for PD-L1 in 68.9% of cases. The median number of mutant genes/tumor was 2.0 (IQR: 1.0-3.0). Only 34.5% were actionable ESCAT Tier I-II with different prevalence according to cancer type. The DNA damage repair (14%), the PI3K/AKT/mTOR (14%), and the RAS/RAF/MAPK (12%) pathways were the most frequently altered. No association was found among PD-L1, ESCAT, age, sex, and tumor mutational status. Overall, 62 patients underwent targeted treatment, with 37.1% obtaining objective responses. The same molecular-driven treatment for different cancer types could be associated with opposite clinical outcomes., Conclusions: We highlight the clinical value of molecular profiling in metastatic solid tumors using comprehensive NGS-based panels to improve treatment algorithms in situations of uncertainty and facilitate clinical trial recruitment. However, interpreting genomic alterations in a tumor type-specific manner is critical., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Endometriosis is a gynecological disease characterized by the presence of endometrial tissue in abnormal locations, leading to severe symptoms, inflammation, pain, organ dysfunction, and infertility. Surgical removal of endometriosis lesions is crucial for improving pain and fertility outcomes, with the goal of complete lesion removal. This study aimed to analyze the location and expression patterns of poly (ADP-ribose) polymerase 1 (PARP-1), epithelial cell adhesion molecule (EpCAM), and folate receptor alpha (FRα) in endometriosis lesions and evaluate their potential for targeted imaging., Methods: Gene expression analysis was performed using the Turku endometriosis database (EndometDB). By immunohistochemistry, we investigated the presence and distribution of PARP-1, EpCAM, and FRα in endometriosis foci and adjacent tissue. We also applied an ad hoc platform for the analysis of images to perform a quantitative immunolocalization analysis. Double immunofluorescence analysis was carried out for PARP-1 and EpCAM, as well as for PARP-1 and FRα, to explore the expression of these combined markers within endometriosis foci and their potential simultaneous utilization in surgical treatment., Results: Gene expression analysis revealed that PARP-1, EpCAM, and FOLR1 (FRα gene) are more highly expressed in endometriotic lesions than in the peritoneum, which served as the control tissue. The results of the immunohistochemical study revealed a significant increase in the expression levels of all three biomarkers inside the endometriosis foci compared to the adjacent tissues. Additionally, the double immunofluorescence analysis consistently demonstrated the presence of PARP-1 in the nucleus and the expression of EpCAM and FRα in the cell membrane and cytoplasm., Conclusion: Overall, these three markers demonstrate significant potential for effective imaging of endometriosis. In particular, the results emphasize the importance of PARP-1 expression as a possible indicator for distinguishing endometriotic lesions from adjacent tissue. PARP-1, as a potential biomarker for endometriosis, offers promising avenues for further investigation in terms of both pathophysiology and diagnostic-therapeutic approaches., (© 2024. The Author(s).)

Viral infections are one of the most common triggers of Systemic Lupus Nephritis (SLE) flare-ups. COVID-19 pneumonia can be severe in patients affected by SLE representing a risk factor for lupus nephritis flare. We report the case of a 28-year-old woman with a history of lupus nephritis (LN), who relapsed with severe nephritic-nephritic syndrome after the resolution of COVID-19 pneumonia. In addition, we conducted a literature review to analyze all described cases of LN, vaccinated and unvaccinated, in COVID-19 showing that the course of COVID-19 is more severe in SLE patients with renal involvement, especially in those who have not been vaccinated. Vaccination is the most important measure for preventing COVID-19 in people with rheumatic diseases such as SLE. The case and data we present suggests that LN relapses can occur even after the infection has resolved and illustrates the benefit of vaccination, the role of modulation of immunosuppression during COVID-19 and the specific risk of disease relapse during SARS-CoV-2 infection., (Copyright by Società Italiana di Nefrologia SIN, Rome,Italy.)

In the context of the increasing number of obese individuals, a major problem is represented by obesity and malnutrition in children. This condition is mainly ascribable to unbalanced diets characterized by high intakes of fat and sugar. Childhood obesity and malnutrition are not only associated with concurrent pathologies but potentially compromise adult life. Considering the strict correlation among systemic metabolism, obesity, and skeletal muscle health, we wanted to study the impact of juvenile malnutrition on the adult skeletal muscle. To this aim, 3-week-old C56BL/6 female and male mice were fed for 20 weeks on a high-fat. high-sugar diet, and their muscles were subjected to a histological evaluation. MyHCs expression, glycogen content, intramyocellular lipids, mitochondrial activity, and capillary density were analyzed on serial sections to obtain the metabolic profile. Our observations indicate that a high-fat, high-sugar diet alters the metabolic profile of skeletal muscles in a sex-dependent way and induces the increase in type II fibers, mitochondrial activity, and lipid content in males, while reducing the capillary density in females. These data highlight the sex-dependent response to nutrition, calling for the development of specific strategies and for a systematic inclusion of female subjects in basic and applied research in this field.

Breast cancer (BC) is currently the most common neoplasm, the second leading cause of cancer death in women worldwide, and is a major health problem. The discovery of new biomarkers is crucial to improve our knowledge of breast cancer and strengthen our clinical approaches to diagnosis, prognosis, and follow-up. In recent decades, there has been increasing interest in circulating RNA (circRNA) as modulators of gene expression involved in tumor development and progression. The study of circulating circRNAs (ccircRNAs) in plasma may provide new non-invasive diagnostic, prognostic, and predictive biomarkers for BC. This review describes the latest findings on BC-associated ccircRNAs in plasma and their clinical utility. Several ccircRNAs in plasma have shown great potential as BC biomarkers, especially from a diagnostic point of view. Mechanistically, most of the reported BC-associated ccircRNAs are involved in the regulation of cell survival, proliferation, and invasion, mainly via MAPK/AKT signaling pathways. However, the study of circRNAs is a relatively new area of research, and a larger number of studies will be crucial to confirm their potential as plasma biomarkers and to understand their involvement in BC.

Glioblastoma is the most frequent and aggressive brain tumor in adults. This study aims to evaluate the expression and prognostic impact of CD99, a membrane glycoprotein involved in cellular migration and invasion. In a cohort of patients with glioblastoma treated with surgery, radiotherapy and temozolomide, we retrospectively analyzed tumor expression of CD99 by immunohistochemistry (IHC) and by quantitative real-time polymerase chain reaction (qRT-PCR) for both the wild type (CD99wt) and the truncated (CD99sh) isoforms. The impact on overall survival (OS) was assessed with the Kaplan-Meier method and log-rank test and by multivariable Cox regression. Forty-six patients with glioblastoma entered this study. Immunohistochemical expression of CD99 was present in 83%. Only the CD99wt isoform was detected by qRT-PCR and was significantly correlated with CD99 expression evaluated by IHC (rho = 0.309, p = 0.037). CD99 expression was not associated with OS, regardless of the assessment methodology used ( p = 0.61 for qRT-PCR and p = 0.73 for IHC). In an exploratory analysis of The Cancer Genome Atlas, casuistry of glioblastomas CD99 expression was not associated with OS nor with progression-free survival. This study confirms a high expression of CD99 in glioblastoma but does not show any significant impact on survival. Further preclinical studies are needed to define its role as a therapeutic target in glioblastoma.

Detecting breast tissue alterations is essential for cancer diagnosis. However, inherent bidimensionality limits histological procedures' effectiveness in identifying these changes. Our study applies a 3D virtual histology method based on X-ray phase-contrast microtomography (PhC μ CT), performed at a synchrotron facility, to investigate breast tissue samples including different types of lesions, namely intraductal papilloma, micropapillary intracystic carcinoma, and invasive lobular carcinoma. One-to-one comparisons of X-ray and histological images explore the clinical potential of 3D X-ray virtual histology. Results show that PhC μ CT technique provides high spatial resolution and soft tissue sensitivity, while being non-destructive, not requiring a dedicated sample processing and being compatible with conventional histology. PhC μ CT can enhance the visualization of morphological characteristics such as stromal tissue, fibrovascular core, terminal duct lobular unit, stromal/epithelium interface, basement membrane, and adipocytes. Despite not reaching the (sub) cellular level, the three-dimensionality of PhC μ CT images allows to depict in-depth alterations of the breast tissues, potentially revealing pathologically relevant details missed by a single histological section. Compared to serial sectioning, PhC μ CT allows the virtual investigation of the sample volume along any orientation, possibly guiding the pathologist in the choice of the most suitable cutting plane. Overall, PhC μ CT virtual histology holds great promise as a tool adding to conventional histology for improving efficiency, accessibility, and diagnostic accuracy of pathological evaluation., (© 2024. The Author(s).)

In the realm of liver transplantation, accurately determining hepatic steatosis levels is crucial. Recognizing the essential need for improved diagnostic precision, particularly for optimizing diagnosis time by swiftly handling easy-to-solve cases and allowing the expert time to focus on more complex cases, this study aims to develop cutting-edge algorithms that enhance the classification of liver biopsy images. Additionally, the challenge of maintaining data privacy arises when creating automated algorithmic solutions, as sharing patient data between hospitals is restricted, further complicating the development and validation process. This research tackles diagnostic accuracy by leveraging novel techniques from the rapidly evolving field of quantum machine learning, known for their superior generalization abilities. Concurrently, it addresses privacy concerns through the implementation of privacy-conscious collaborative machine learning with federated learning. We introduce a hybrid quantum neural network model that leverages real-world clinical data to assess non-alcoholic liver steatosis accurately. This model achieves an image classification accuracy of 97%, surpassing traditional methods by 1.8%. Moreover, by employing a federated learning approach that allows data from different clients to be shared while ensuring privacy, we maintain an accuracy rate exceeding 90%. This initiative marks a significant step towards a scalable, collaborative, efficient, and dependable computational framework that aids clinical pathologists in their daily diagnostic tasks.