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Abstract Background The potential role of cardiac computed tomography (CT) has increasingly been demonstrated for the assessment of diffuse myocardial fibrosis through the quantification of extracellular volume (ECV). Photon-counting detector (PCD)-CT technology may deliver more accurate ECV quantification compared to energy-integrating detector CT. We evaluated the impact of reconstruction settings on the accuracy of ECV quantification using PCD-CT, with magnetic resonance imaging (MRI)-based ECV as reference. Methods In this post hoc analysis, 27 patients (aged 53.1 ± 17.2 years (mean ± standard deviation); 14 women) underwent same-day cardiac PCD-CT and MRI. Late iodine CT scans were reconstructed with different quantum iterative reconstruction levels (QIR 1−4), slice thicknesses (0.4−8 mm), and virtual monoenergetic imaging levels (VMI, 40−90 keV); ECV was quantified for each reconstruction setting. Repeated measures ANOVA and t-test for pairwise comparisons, Bland–Altman plots, and Lin’s concordance correlation coefficient (CCC) were used. Results ECV values did not differ significantly among QIR levels (p = 1.000). A significant difference was observed throughout different slice thicknesses, with 0.4 mm yielding the highest agreement with MRI-based ECV (CCC = 0.944); 45-keV VMI reconstructions showed the lowest mean bias (0.6, 95% confidence interval 0.1–1.4) compared to MRI. Using the most optimal reconstruction settings (QIR4. slice thickness 0.4 mm, VMI 45 keV), a 63% reduction in mean bias and a 6% increase in concordance with MRI-based ECV were achieved compared to standard settings (QIR3, slice thickness 1.5 mm; VMI 65 keV). Conclusions The selection of appropriate reconstruction parameters improved the agreement between PCD-CT and MRI-based ECV. Relevance statement Tailoring PCD-CT reconstruction parameters optimizes ECV quantification compared to MRI, potentially improving its clinical utility. Key points • CT is increasingly promising for myocardial tissue characterization, assessing focal and diffuse fibrosis via late iodine enhancement and ECV quantification, respectively. • PCD-CT offers superior performance over conventional CT, potentially improving ECV quantification and its agreement with MRI-based ECV. • Tailoring PCD-CT reconstruction parameters optimizes ECV quantification compared to MRI, potentially improving its clinical utility. Graphical Abstract

Abstract Background Type 1 diabetes (T1D) is frequently associated with autoimmune thyroiditis (AT) and coeliac disease (CD). Whether the coexistence of multiple autoimmune diseases increases cardiovascular risk is uncertain. We evaluated the effects of AT and CD on arterial wall thickening and endothelial function in patients with T1D. Methods This observational study analyzed data from T1D patients regularly followed by the Diabetes Care Centre. Clinical and biochemical characteristics and micro and macrovascular complications were collected from the electronic medical records. All subjects performed Echo-Doppler to evaluate Intima-Media Thickness (IMT) of the common carotid artery (CCA) and endothelial function by the flow-mediated dilation (FMD) technique. The statistical analyses were performed by SPSS for Macintosh. Comparison between means was performed using the t-test for unpaired data and the Mann–Whitney U test. The ANalysis Of VAriance and the Tukey posthoc test were applied to compare patients with and without other autoimmune diseases, and control subjects. The p-value for statistical significance was set at p

Abstract Background Pain of musculoskeletal origin is very common in young patients affected by Mucopolysaccharidoses. This scoping review evaluates the evidence for assessment, pharmacological treatment and rehabilitation management for musculoskeletal pain of the latter. Methods A Medline search through PubMed has been performed for studies published in English at least for the past twenty years. Two investigators independently reviewed all search results and extracted those that met the inclusion criteria. Results 29 studies have been selected and analysed in depth, of which 10 related to pain assessment, 11 concerned pharmacological approach, and 8 reported rehabilitation approaches. Conclusion Few data are available in literature concerning the classification and management of pain in children with Mucopolysaccharidoses. Notwithstanding, pain evaluation methods are effectively used to classify pain intensity, according to the age group and communication abilities of young Mucopolysaccharidoses patients. The review emphasizes that drug therapies have a palliative purpose, while rehabilitation reduces musculoskeletal pain and can provide a therapeutic effect on disabilities.

Post-stroke shoulder pain (PSSP) is a debilitating consequence of hemiplegia, often hindering rehabilitation efforts and further limiting motor recovery. With the advent of robotic-assisted therapies in neurorehabilitation, there is potential for innovative interventions for PSSP. This study systematically reviewed the current literature to determine the effectiveness of robotic-assisted rehabilitation in addressing PSSP in stroke patients. A comprehensive search of databases was conducted, targeting articles published up to August 2023. Studies were included if they investigated the impact of robotic-assisted rehabilitation on PSSP. The outcome of interest was pain reduction. The risk of bias was assessed using the Cochrane database. Of the 187 initially identified articles, 3 studies met the inclusion criteria, encompassing 174 patients. The reviewed studies indicated a potential benefit of robotic-assisted rehabilitation in reducing PSSP, with some studies also noting improvements in the range of motion and overall motor function. However, the results varied across studies, with some showing more significant benefits than others, because these use different protocols and robotic equipment.

Optical coherence tomography angiography (OCTA) is an innovative and reliable technique detecting the early preclinical retinal vascular change in patients with diabetes. We have designed our study to evaluate whether an independent relationship exists between continuous glucose monitoring (CGM)-derived glucose metrics and OCTA parameters in young adult patients with type 1 diabetes without diabetic retinopathy (DR). Inclusion criteria were age≥18 years, diagnosis of type 1 diabetes from≥1 year, stable insulin treatment in the last three months, use of real-time CGM, and CGM wear time≥70%. Each patient underwent dilated slit lamp fundus biomicroscopy to exclude the presence of DR. A skilled operator performed OCTA scans in the morning to avoid possible diurnal variation. CGM-derived glucose metrics from the last 2 weeks were collected through the dedicated software during OCTA. Forty-nine patients with type 1 diabetes (age 29 [18; 39] years, HbA1c 7.7±1.0%) and 34 control subjects participated in the study. Vessel density (VD) of the whole image and parafoveal retina in the superficial (SCP) and deep capillary plexus (DCP) was significantly lower in patients with type 1 diabetes compared to controls. The coefficient of variation of average daily glucose, evaluated by CGM, significantly correlated with foveal and parafoveal VD in SCP and with foveal VD in DCP. High glucose variability might be responsible for the early increase of VD in these areas. Prospective studies may help understand if this pattern precedes DR. The difference we detected between patients with and without diabetes confirms that OCTA is a reliable tool for detecting early retinal abnormalities.

Cardiac regeneration is a critical endeavor in the treatment of heart diseases, aimed at repairing and enhancing the structure and function of damaged myocardium. This review offers a comprehensive overview of current advancements and strategies in cardiac regeneration, with a specific focus on regenerative medicine and tissue engineering-based approaches. Stem cell-based therapies, which involve the utilization of adult stem cells and pluripotent stem cells hold immense potential for replenishing lost cardiomyocytes and facilitating cardiac tissue repair and regeneration. Tissue engineering also plays a prominent role employing synthetic or natural biomaterials, engineering cardiac patches and grafts with suitable properties, and fabricating upscale bioreactors to create functional constructs for cardiac recovery. These constructs can be transplanted into the heart to provide mechanical support and facilitate tissue healing. Additionally, the production of organoids and chips that accurately replicate the structure and function of the whole organ is an area of extensive research. Despite significant progress, several challenges persist in the field of cardiac regeneration. These include enhancing cell survival and engraftment, achieving proper vascularization, and ensuring the long-term functionality of engineered constructs. Overcoming these obstacles and offering effective therapies to restore cardiac function could improve the quality of life for individuals with heart diseases.

Hepatic metastases are a poor prognostic factor of colorectal carcinoma (CRC) and new strategies to reduce the risk of liver CRC colonization are highly needed. Herein, we used mouse models of hepatic metastatization to demonstrate that the continuous infusion of therapeutic doses of interferon-alpha (IFNα) controls CRC invasion by acting on hepatic endothelial cells (HECs). Mechanistically, IFNα promoted the development of a vascular antimetastatic niche characterized by liver sinusoidal endothelial cells (LSECs) defenestration extracellular matrix and glycocalyx deposition, thus strengthening the liver vascular barrier impairing CRC trans-sinusoidal migration, without requiring a direct action on tumor cells, hepatic stellate cells, hepatocytes, or liver dendritic cells (DCs), Kupffer cells (KCs) and liver capsular macrophages (LCMs). Moreover, IFNα endowed LSECs with efficient cross-priming potential that, along with the early intravascular tumor burden reduction, supported the generation of antitumor CD8+ T cells and ultimately led to the establishment of a protective long-term memory T cell response. These findings provide a rationale for the use of continuous IFNα therapy in perioperative settings to reduce CRC metastatic spreading to the liver.

BackgroundPersistent symptoms including dyspnea and functional impairment are common in COVID-19 survivors. Poor muscle quality (myosteatosis) associates with poor short-term outcomes in COVID-19 patients. The aim of this observational study was to assess the relationship between myosteatosis diagnosed during acute COVID-19 and patient-reported outcomes at 6 months after discharge.MethodsMyosteatosis was diagnosed based on CT-derived skeletal muscle radiation attenuation (SM-RA) measured during hospitalization in 97 COVID-19 survivors who had available anthropometric and clinical data upon admission and at the 6-month follow-up after discharge. Dyspnea in daily activities was assessed using the modified Medical Research Council (mMRC) scale for dyspnea. Health-related quality of life was measured using the European quality of life questionnaire three-level version (EQ-5D-3L).ResultsCharacteristics of patients with (lowest sex- and age-specific tertile of SM-RA) or without myosteatosis during acute COVID-19 were similar. At 6 months, patients with myosteatosis had greater rates of obesity (48.4 vs. 27.7%, p = 0.046), abdominal obesity (80.0 vs. 47.6%, p = 0.003), dyspnea (32.3 vs. 12.5%, p = 0.021) and mobility problems (32.3 vs. 12.5%, p = 0.004). Myosteatosis diagnosed during acute COVID-19 was the only significant predictor of persistent dyspnea (OR 3.19 [95% C.I. 1.04; 9.87], p = 0.043) and mobility problems (OR 3.70 [95% C.I. 1.25; 10.95], p = 0.018) at 6 months at logistic regression adjusted for sex, age, and BMI.ConclusionMyosteatosis diagnosed during acute COVID-19 significantly predicts persistent dyspnea and mobility problems at 6 months after hospital discharge independent of age, sex, and body mass.Clinical Trial Registration[www.ClinicalTrials.gov], identifier [NCT04318366].

Aims: Individuals with type 1 diabetes (T1D) do not appear to have an elevated risk of severe Coronavirus Disease 19 (COVID‐19). Pre‐existing immune reactivity to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) in unexposed individuals may serve as a protective factor. Hence, our study was designed to evaluate the existence of T cells with reactivity against SARS‐CoV‐2 antigens in unexposed patients with T1D. Materials and methods: Peripheral blood mononuclear cells (PBMCs) were collected from SARS‐CoV‐2 unexposed patients with T1D and healthy control subjects. SARS‐CoV‐2 specific T cells were identified in PBMCs by ex‐vivo interferon (IFN)γ‐ELISpot and flow cytometric assays. The epitope specificity of T cells in T1D was inferred through T Cell Receptor sequencing and GLIPH2 clustering analysis. Results: T1D patients unexposed to SARS‐CoV‐2 exhibited higher rates of virus‐specific T cells than controls. The T cells primarily responded to peptides from the ORF7/8, ORF3a, and nucleocapsid proteins. Nucleocapsid peptides predominantly indicated a CD4+ response, whereas ORF3a and ORF7/8 peptides elicited both CD4+ and CD8+ responses. The GLIPH2 clustering analysis of TCRβ sequences suggested that TCRβ clusters, associated with the autoantigens proinsulin and Zinc transporter 8 (ZnT‐8), might share specificity towards ORF7b and ORF3a viral epitopes. Notably, PBMCs from three T1D patients exhibited T cell reactivity against both ORF7b/ORF3a viral epitopes and proinsulin/ZnT‐8 autoantigens. Conclusions: The increased frequency of SAR‐CoV‐2‐ reactive T cells in T1D patients might protect against severe COVID‐19 and overt infections. These results emphasise the long‐standing association between viral infections and T1D. [ABSTRACT FROM AUTHOR]

Cesare Tripolino,1 Concetta Irace,2 Antonio Cutruzzolà,2 Martina Parise,1 Milena Barone,1 Caterina Scicchitano,1 Claudio Cortese,3 Agostino Gnasso1 1Metabolic Diseases Unit, Department of Clinical and Experimental Medicine, University Magna Graecia, Catanzaro, Italy; 2Department of Health Science, University Magna Graecia, Catanzaro, Italy; 3Department of Experimental Medicine and Surgery, Tor Vergata University, Rome, ItalyCorrespondence: Agostino GnassoMetabolic Diseases Unit, Department of Clinical and Experimental Medicine, Mater Domini Hospital, Magna Græcia University, Catanzaro, ItalyTel +39 9613697039Fax +39 9613697250Email gnasso@unicz.itIntroduction: Non-alcoholic fatty liver disease (NAFLD) is associated with an increased risk of complications in type 1 diabetes (T1DM) patients. To date, several biochemical indexes of NAFLD have been developed. Among these, hepatic steatosis index (HSI) strongly relates with the results of magnetic resonance.Aim: The aim of the present study was to evaluate the possible association between HSI and complications in T1DM.Methods: Medical records of patients with T1DM were evaluated. Macro- and micro-vascular complications were evaluated by a combination of instrumental (ECG, carotid artery echo-Doppler, fundus examination, vibration threshold at biothesiometry) and laboratory examination. HSI was calculated based on gender, body mass index and transaminases level.Results: Of the 124 patients evaluated, 71 were free of complications and 53 had at least one complication. The prevalence of diabetes complications was: 27% for retinopathy, 15% for carotid atherosclerosis, 16% for neuropathy. HSI was directly correlated with age, disease duration, triglycerides, total daily insulin and inversely with HDL and eGFR. In logistic regression analysis, HSI was independently associated with diabetic complications.Conclusion: These findings show that HSI is independently associated with the presence of complications in subjects with T1DM. This can be of clinical utility, allowing a better diagnostic classification of the patient and possibly guiding the therapeutic choice.Keywords: fatty liver, type 1 diabetes, diabetes complications

The growing success of Machine Learning (ML) is making significant improvements to predictive models, facilitating their integration in various application fields. Despite its growing success, there are some limitations and disadvantages: the most significant is the lack of interpretability that does not allow users to understand how particular decisions are made. Our study focus on one of the best performing and most used models in the Machine Learning framework, the Random Forest model. It is known as an efficient model of ensemble learning, as it ensures high predictive precision, flexibility, and immediacy; it is recognized as an intuitive and understandable approach to the construction process, but it is also considered a Black Box model due to the large number of deep decision trees produced within it.The aim of this research is twofold. We present a survey about interpretative proposal for Random Forest and then we perform a machine learning experiment providing a comparison between two methodologies, inTrees, and NodeHarvest, that represent the main approaches in the rule extraction framework. The proposed experiment compares methods performance on six real datasets covering different data characteristics: n. of observations, balanced/unbalanced response, the presence of categorical and numerical predictors. This study contributes to picture a review of the methods and tools proposed for ensemble tree interpretation, and identify, in the class of rule extraction approaches, the best proposal.

Despite multiple pharmacological options, including rapid-acting insulin analogs, postprandial hyperglycemia is still highly prevalent in patients with type 1 and type 2 diabetes. We hypothesize that the new rapid-acting insulin formulation, the so-called faster-acting Aspart, may have a different effect in controlling postprandial hyperglycemic burden according to the quality of the meal compared to the traditional Aspart. Twenty-five patients with type 1 diabetes were consecutively recruited at the diabetes care center of the University Hospital affiliate of the Magna Græcia University of Catanzaro. Each patient performed four meal tests one week apart, two with a predefined high glycemic index (HGI) food and two with a low glycemic index (LGI) food using insulin Aspart once and Faster Aspart the other time. The 0–30 min, 0–60 min, and 0–120 min glucose Area Under the Curve (AUC) of postprandial glycemic excursion, calculated from continuous glucose monitoring data, were significantly lower with Faster Aspart administered before the HGI test meal as compared to Aspart. A significant difference in favor of Faster Aspart was also found when comparing the 0–60 min and 0–120 min AUC after the LGI meal. Faster Aspart may provide better postprandial glucose control than Aspart regardless of the glycemic index of the meal.

BackgroundTelemedicine use in chronic disease management has markedly increased during health emergencies due to COVID-19. Diabetes and technologies supporting diabetes care, including glucose monitoring devices, software analyzing glucose data, and insulin delivering systems, would facilitate remote and structured disease management. Indeed, most of the currently available technologies to store and transfer web-based data to be shared with health care providers. ObjectiveDuring the COVID-19 pandemic, we provided our patients the opportunity to manage their diabetes remotely by implementing technology. Therefore, this study aimed to evaluate the effectiveness of 2 virtual visits on glycemic control parameters among patients with type 1 diabetes (T1D) during the lockdown period. MethodsThis prospective observational study included T1D patients who completed 2 virtual visits during the lockdown period. The glucose outcomes that reflected the benefits of the virtual consultation were time in range (TIR), time above range, time below range, mean daily glucose, glucose management indicator (GMI), and glycemic variability. This metric was generated using specific computer programs that automatically upload data from the devices used to monitor blood or interstitial glucose levels. If needed, we changed the ongoing treatment at the first virtual visit. ResultsAmong 209 eligible patients with T1D, 166 completed 2 virtual visits, 35 failed to download glucose data, and 8 declined the visit. Among the patients not included in the study, we observed a significantly lower proportion of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) users (n=7/43, 16% vs n=155/166, 93.4% and n=9/43, 21% vs n=128/166, 77.1%, respectively; P