Karpinski Score under Digital Investigation: A Fully Automated Segmentation Algorithm to Identify Vascular and Stromal Injury of Donors’ Kidneys

In kidney transplantations, the evaluation of the vascular structures and stromal areas is crucial for determining kidney acceptance, which is currently based on the pathologist’s visual evaluation. In this context, an accurate assessment of the vascular and stromal injury is fundamental to assessing the nephron status. In the present paper, the authors present a fully automated algorithm, called RENFAST (Rapid EvaluatioN of Fibrosis And vesselS Thickness), for the segmentation of kidney blood vessels and fibrosis in histopathological images. The proposed method employs a novel strategy based on deep learning to accurately segment blood vessels, while interstitial fibrosis is assessed using an adaptive stain separation method. The RENFAST algorithm is developed and tested on 350 periodic acid–Schiff (PAS) images for blood vessel segmentation and on 300 Massone’s trichrome (TRIC) stained images for the detection of renal fibrosis. In the TEST set, the algorithm exhibits excellent segmentation performance in both blood vessels (accuracy: 0.8936) and fibrosis (accuracy: 0.9227) and outperforms all the compared methods. To the best of our knowledge, the RENFAST algorithm is the first fully automated method capable of detecting both blood vessels and fibrosis in digital histological images. Being very fast (average computational time 2.91 s), this algorithm paves the way for automated, quantitative, and real-time kidney graft assessments

Karpinski Score under Digital Investigation: A Fully Automated Segmentation Algorithm to Identify Vascular and Stromal Injury of Donors’ Kidneys

In kidney transplantations, the evaluation of the vascular structures and stromal areas is crucial for determining kidney acceptance, which is currently based on the pathologist's visual evaluation. In this context, an accurate assessment of the vascular and stromal injury is fundamental to assessing the nephron status. In the present paper, the authors present a fully automated algorithm, called RENFAST (Rapid EvaluatioN of Fibrosis And vesselS Thickness), for the segmentation of kidney blood vessels and fibrosis in histopathological images. The proposed method employs a novel strategy based on deep learning to accurately segment blood vessels, while interstitial fibrosis is assessed using an adaptive stain separation method. The RENFAST algorithm is developed and tested on 350 periodic acid-Schiff (PAS) images for blood vessel segmentation and on 300 Massone's trichrome (TRIC) stained images for the detection of renal fibrosis. In the TEST set, the algorithm exhibits excellent segmentation performance in both blood vessels (accuracy: 0.8936) and fibrosis (accuracy: 0.9227) and outperforms all the compared methods. To the best of our knowledge, the RENFAST algorithm is the first fully automated method capable of detecting both blood vessels and fibrosis in digital histological images. Being very fast (average computational time 2.91 s), this algorithm paves the way for automated, quantitative, and real-time kidney graft assessments

Manganese(II) Molecular Sources for Plasma-Assisted CVD of Mn Oxides and Fluorides: From Precursors to Growth Process

A viable route to manganese-based materials of high technological interest is plasma-assisted chemical vapor deposition (PA-CVD), offering various degrees of freedom for the growth of high-purity nanostructures from suitable precursors. In this regard, fluorinated \u3b2-diketonate diamine Mn(II) complexes of general formula Mn(dik)2\ub7TMEDA [TMEDA = N,N,N\u2032,N\u2032-tetramethylethylenediamine; Hdik = 1,1,1,5,5,5-hexafluoro-2,4-pentanedione (Hhfa), or 1,1,1-trifluoro-2,4-pentanedione (Htfa)] represent a valuable option in the quest of candidate molecular sources for PA-CVD environments. In this work, we investigate and highlight the chemico-physical properties of these compounds of importance for their use in PA-CVD processes, through the use of a comprehensive experimental\u2013theoretical investigation. Preliminary PA-CVD validation shows the possibility of varying the Mn oxidation state, as well as the system chemical composition from MnF2 to MnO2, by simple modulations of the reaction atmosphere, paving the way to a successful utilization of the target compounds in the growth of manganese-containing nanomaterials for different technological applications

Human Arboviral Infections in Italy: Past, Current, and Future Challenges

: Arboviruses represent a public health concern in many European countries, including Italy, mostly because they can infect humans, causing potentially severe emergent or re-emergent diseases, with epidemic outbreaks and the introduction of endemic circulation of new species previously confined to tropical and sub-tropical regions. In this review, we summarize the Italian epidemiology of arboviral infection over the past 10 years, describing both endemic and imported arboviral infections, vector distribution, and the influence of climate change on vector ecology. Strengthening surveillance systems at a national and international level is highly recommended to be prepared to face potential threats due to arbovirus diffusion

Citrus wastewater as a source of value‐added products: Quali‐quantitative analysis and in vitro screening on breast cancer cell lines

Citrus wastewater from industries is a source of bioactive compounds whose recovery could be a useful approach to convert processing waste into potential resources to be exploited in food, pharmaceutical, and chemical companies. Citrus wastewater, obtained from the industrial processing of Citrus sinensis, was freezedried and qualitative/quantitative evaluated using HPLC/MS Q‐TOF analysis. Antiproliferative activity was investigated on MDA‐MB‐231 (triple‐negative breast cancer cell line), MCF‐7 (breast cancer cell line), and its multidrug‐resistant variant MCF‐7R. Fraction 8 emerged for its cytotoxicity toward MCF‐7R cells. Its main component, the polymethoxylated flavone nobiletin (80%), is likely involved in increasing the number of G1‐phase MCF‐7R cells without inducing cell death. Notably, fraction 8 sensitizes MCF7‐R cells to the antiproliferative effects of doxorubicin, thus contributing to overcoming MCF7‐R multidrug resistance. Our studies highlighted the possibility of applying a sustainable strategy for citrus wastewater recycling to recover functional compounds as useful adjuvants for the prevention and treatment of malignancies

Marine anticancer agents: An overview with a particular focus on their chemical classes

UID/Multi/04378/2019 IF/00700/2014 grant number 216Z167 grant RTA 2015-00010-C03-02 No. PBA/MB/16/01 PDOC/19/02/01The marine environment is a rich source of biologically active molecules for the treatment of human diseases, especially cancer. The adaptation to unique environmental conditions led marine organisms to evolve different pathways than their terrestrial counterparts, thus producing unique chemicals with a broad diversity and complexity. So far, more than 36,000 compounds have been isolated from marine micro- and macro-organisms including but not limited to fungi, bacteria, microalgae, macroalgae, sponges, corals, mollusks and tunicates, with hundreds of new marine natural products (MNPs) being discovered every year. Marine-based pharmaceuticals have started to impact modern pharmacology and different anti-cancer drugs derived from marine compounds have been approved for clinical use, such as: cytarabine, vidarabine, nelarabine (prodrug of ara-G), fludarabine phosphate (pro-drug of ara-A), trabectedin, eribulin mesylate, brentuximab vedotin, polatuzumab vedotin, enfortumab vedotin, belantamab mafodotin, plitidepsin, and lurbinectedin. This review focuses on the bioactive molecules derived from the marine environment with anticancer activity, discussing their families, origin, structural features and therapeutic use.publishersversionpublishe

Validation of the T-Lymphocyte Subset Index (TLSI) as a Score to Predict Mortality in Unvaccinated Hospitalized COVID-19 Patients

Lymphopenia has been consistently reported as associated with severe coronavirus disease 2019 (COVID-19). Several studies have described a profound decline in all T-cell subtypes in hospitalized patients with severe and critical COVID-19. The aim of this study was to assess the role of T-lymphocyte subset absolute counts measured at ward admission in predicting 30-day mortality in COVID-19 hospitalized patients, validating a new prognostic score, the T-Lymphocyte Subset Index (TLSI, range 0–2), based on the number of T-cell subset (CD4+ and CD8+) absolute counts that are below prespecified cutoffs. These cutoff values derive from a previously published work of our research group at Policlinico Tor Vergata, Rome, Italy: CD3+CD4+ < 369 cells/µL, CD3+CD8+ < 194 cells/µL. In the present single-center retrospective study, T-cell subsets were assessed on admission to the infectious diseases ward. Statistical analysis was performed using JASP (Version 0.16.2. JASP Team, 2022, The Amsterdam, The Netherlands) and Prism8 (version 8.2.1. GraphPad Software, San Diego, CA, USA). Clinical and laboratory parameters of 296 adult patients hospitalized because of COVID-19 were analyzed. The overall mortality rate was 22.3% (66/296). Survivors (S) had a statistically significant lower TLSI score compared to non-survivors (NS) (p < 0.001). Patients with increasing TLSI scores had proportionally higher rates of 30-day mortality (p < 0.0001). In the multivariable logistic analysis, the TLSI was an independent predictor of in-hospital 30-day mortality (OR: 1.893, p = 0.003). Survival analysis showed that patients with a TLSI > 0 had an increased risk of death compared to patients with a TLSI = 0 (hazard ratio: 2.83, p < 0.0001). The TLSI was confirmed as an early and independent predictor of COVID-19 in-hospital 30-day mortalit

QUIN 2.0 - new release of the QUaternary fault strain INdicators database from the Southern Apennines of Italy

QUIN database integrates and organizes structural-geological information from published and unpublished sources to constrain deformation in seismotectonic studies. The initial release, QUIN1.0, comprised 3,339 Fault Striation Pairs, mapped on 445 sites exposed along the Quaternary faults of central Italy. The present Data Descriptor introduces the QUIN 2.0 release, which includes 4,297 Fault Striation Pairs on 738 Structural Sites from southern Italy. The newly investigated faults span ~500 km along the Apennines chain, with strikes transitioning from ~SE to ~SW and comprehensively details Fault Striation Pairs’ location, attitude, kinematics, and deformation axes. Additionally, it offers a shapefile of the fault traces hosting the data. The QUIN 2.0 release offers a significant geographic extension to the QUIN 1.0, with comprehensive description of local geometric-kinematic complexities of the regional pattern. The QUIN data may be especially relevant for constraining intra-Apennine potential seismogenic deformation patterns, where earthquake data only offer scattered or incomplete information. QUIN’s data will support studies aimed at enhancing geological understanding, hazard assessment and comprehension of fault rupture propagation and barriers

Covid-19 and the role of smoking: the protocol of the multicentric prospective study COSMO-IT (COvid19 and SMOking in ITaly).

The emergency caused by Covid-19 pandemic raised interest in studying lifestyles and comorbidities as important determinants of poor Covid-19 prognosis. Data on tobacco smoking, alcohol consumption and obesity are still limited, while no data are available on the role of e-cigarettes and heated tobacco products (HTP). To clarify the role of tobacco smoking and other lifestyle habits on COVID-19 severity and progression, we designed a longitudinal observational study titled COvid19 and SMOking in ITaly (COSMO-IT). About 30 Italian hospitals in North, Centre and South of Italy joined the study. Its main aims are: 1) to quantify the role of tobacco smoking and smoking cessation on the severity and progression of COVID-19 in hospitalized patients; 2) to compare smoking prevalence and severity of the disease in relation to smoking in hospitalized COVID-19 patients versus patients treated at home; 3) to quantify the association between other lifestyle factors, such as e-cigarette and HTP use, alcohol and obesity and the risk of unfavourable COVID-19 outcomes. Socio-demographic, lifestyle and medical history information will be gathered for around 3000 hospitalized and 700-1000 home-isolated, laboratory-confirmed, COVID-19 patients. Given the current absence of a vaccine against SARS-COV-2 and the lack of a specific treatment for -COVID-19, prevention strategies are of extreme importance. This project, designed to highly contribute to the international scientific debate on the role of avoidable lifestyle habits on COVID-19 severity, will provide valuable epidemiological data in order to support important recommendations to prevent COVID-19 incidence, progression and mortality