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Non invasive immunologic markers of virus-induced liver disease are unmet needs. We tested the clinical significance of quantitative total and IgM-anti-HBc in well characterized chronic-HBsAg-carriers. Sera (212) were obtained from 111 HBsAg-carriers followed-up for 52 months (28-216) during different phases of chronic-HBV-genotype-D-infection: 10 HBeAg-positive, 25 inactive-carriers (HBV-DNA≤2000IU/ml, ALT<30U/L), 66 HBeAg-negative-CHB-patients and 10 with HDV-super-infection. In 35 patients treated with Peg-IFN±nucleos(t)ide-analogues (NUCs) sera were obtained at baseline, end-of-therapy and week-24-off-therapy and in 22 treated with NUCs (for 60 months, 42-134m) at baseline and end-of-follow-up. HBsAg and IgM-anti-HBc were measured by Architect-assays (Abbott, USA); total-anti-HBc by double-antigen-sandwich-immune-assay (Wantai, China); HBV-DNA by COBAS-TaqMan (Roche, Germany). Total-anti-HBc were detectable in all sera with lower levels in HBsAg-carriers without CHB (immune-tolerant, inactive and HDV-superinfected, median 3.26, range 2.26-4.49 Log10 IU/ml) versus untreated-CHB (median 4.68, range 2.76-5.54 Log10 IU/ml), p<0.0001. IgM-anti-HBc positive using the chronic-hepatitis-cut-off\" (0.130-S/CO) were positive in 102 of 212 sera (48.1%). Overall total-anti-HBc and IgM-anti-HBc correlated significantly (p<0.001, r=0.417). Total-anti-HBc declined significantly in CHB patients with response to Peg-IFN (p<0.001) and in NUC-treated patients (p<0.001); the lowest levels (median 2.68, range 2.12-3.08 Log10 IU/ml) were found in long-term responders who cleared HBsAg subsequently. During spontaneous and therapy-induced fluctuations of CHB (remissions and reactivations) total- and IgM-anti-HBc correlated with ALT (p<0.001, r=0.351 and p=0.008, r=0.185 respectively). Total-anti-HBc qualifies as a useful marker of HBV-induced-liver-disease that might help to discriminate major phases of chronic HBV infection and to predict sustained response to antivirals.

Inter-instrument variations of liver stiffness measure (LSM) by transient elastography might be problematic in clinical practice. LSMs provided by 2 different systems were compared in outpatients with chronic liver disease (CLD). In 777 consecutive asymptomatic outpatients admitted at the Hepatology Unit of Pisa University Hospital the agreement of LSMs measured by FibroScan ® (Echosens, France) and FT9000 (Hisky Medical, China) (LSM Fibroscan /LSM FT9000 ) was tested using Pearson correlation and Bland-Altman analyses (BAA). Delta FT9000-FibroScan ® LSM (LSM-D) variations were analysed according to clinic-pathologic characteristics. ALT/AST/GGT and platelets-counts/portal-vein-caliber/spleen-bipolar-diameter were used as proxies of necro-inflammatory and portal hypertension, respectively. LSM FT9000 and LSM Fibroscan were highly correlated ( r  = 0.781, p  < 0.001) overall, but agreement varied according to BMI (normal-weight r  = 0.841, over-weight r  = 0.747, obese r  = 0.647, p  < 0.001). LSM showed a + 0.52 kPa bias ( p  = 0.01) with − 11/12 kPa as 95% Limit of agreement, with higher values measured by LSM FT9000 below 10 kPa and lower values above 20 kPa. In bivariate analysis LSM-D correlated with LSM Fibroscan and AST (β = 0.002, p  = 0.001 with significant interaction, p  = 0.018) and was associated with spleen-bipolar-diameter (β = 0.033, p  = 0.027) and platelets-count (β=-0.008, p  = 0.018) with significant interaction with LSM Fibroscan ( p  < 0.001). LSM Fibroscan and LSM FT9000 are strongly correlated overall with optimal agreement around 10 kPa but limited at ends of the dynamic range: LSM FT9000 provides higher values below 10 kPa whereas LSM Fibroscan higher values over 20 kPa with different measures distribution. LSM discrepancies associate with anthropometric characteristics, necro-inflammatory activity and portal hypertension proxies. These findings suggest the need of systems specific cut-offs in clinical practice.

miRNAs circulating in whole serum and HBsAg-particles are differentially expressed in chronic hepatitis B (CHB) and HBeAg-negative-HBV infection (ENI); their profiles are unknown in chronic hepatitis D (CHD). Serum- and HBsAg-associated miRNAs were analyzed in 75 subjects of 3 well-characterized groups (CHB 25, CHD 25, ENI 25) using next-generation sequencing (NGS). Overall miRNA profiles were consonant in serum and HBsAg-particles but significantly different according to the presence of hepatitis independently of Hepatitis D Virus (HDV)-co-infection. Stringent (Bonferroni Correction < 0.001) differential expression analysis showed 39 miRNAs upregulated in CHB vs. ENI and 31 of them also in CHD vs. ENI. miRNA profiles were coincident in CHB and CHD with only miR-200a-3p upregulated in CHB. Three miRNAs (miR-625-3p, miR-142-5p, and miR-223-3p) involved in immune response were upregulated in ENI. All 3 hepatocellular miRNAs of MiR-B-Index (miR-122-5p, miR-99a-5p, miR-192-5p) were overexpressed in both CHB and CHD patients. In conclusion, CHD and CHB patients showed highly similar serum miRNA profiling that was significantly different from that of individuals with HBeAg-negative infection and without liver disease.

Background: Steatotic liver disease (SLD) is a growing global health concern and may progress to more advanced liver diseases (i.e., fibrosis, cirrhosis, and hepatocellular carcinoma). Early identification of individuals at risk through effective screening strategies is crucial for timely intervention and management. The aim of this population-based study was to evaluate the feasibility of mean/large-scale screening and its importance by analyzing key risk factors, such as metabolic and lifestyle-related determinants. Methods: This cross-sectional study involved 387 subjects aged 18 to 89 years in a remote rural area that stretches among the valleys at the foot of the Apennines and the Apuan Alps. Anthropometric and demographic data were recorded, together with the measurement of blood pressure and cardiac rhythm. Furthermore, US-based liver stiffness (LS) and the ultrasound attenuation parameter (UAP) using the ILivTouch (Hisky Medical, Wuxi, China) device were performed. All data were analyzed with SPSS version 28. Univariate and multivariate analyses were conducted to identify significant predictors of both LS and UAP. Results: Significant associations are observed between elevated LS and UAP values and risk factors, such as BMI and waist circumference (BMI and waist with R = 0.45 and R = 0.34, R = 0.29 and R = 0.28; respectively, for UAP and LS; all with p < 0.001). The presence of hypertension is associated with a high value of LS (p < 0.05), and high UAP with alcohol consumption and sugary coffee intake habit (p < 0.001 and, p < 0.05, respectively). Conclusions: General population screening for SLD is feasible, sustainable, and useful to identify both individuals at risk and patients with progressive liver disease.

In advanced HCC, tyrosine-kinase inhibitors obtain partial responses (PR) in some patients and complete responses (CR) in a few. Better understanding of the mechanism of response could be achieved by the radiomic approach combining digital imaging and serological biomarkers (α-fetoprotein, AFP and protein induced by vitamin K absence-II, PIVKA-II) kinetics. A physic-mathematical model was developed to investigate cancer cells and vasculature dynamics in three prototype patients receiving sorafenib and/or regorafenib and applied in seven others for validation. Overall four patients showed CR, two PR, two stable-disease (SD) and two progressive-disease (PD). The rate constant of cancer cells production was higher in PD than in PR-SD and CR (median: 0.398 vs. 0.325 vs. 0.316 C × day−1). Therapy induced reduction of neo-angiogenesis was greater in CR than in PR-SD and PD (median: 83.2% vs. 29.4% and 2.0%), as the reduction of cell-proliferation (55.2% vs. 7.6% and 0.7%). An additional dose-dependent acceleration of tumor vasculature decay was also observed in CR. AFP and cancer cells followed the same kinetics, whereas PIVKA-II time/dose dependent fluctuations were influenced also by tissue ischemia. In conclusion, pending confirmation in a larger HCC cohort, modeling serological and imaging biomarkers could be a new tool for systemic therapy personalization.

Direct-acting antivirals (DAAs) for hepatitis C virus (HCV) may induce hepatitis B virus (HBV) reactivations in co-infected patients, whose dynamics and outcomes could depend on the phase of HBV infection. We investigated HBsAg and HBV-DNA kinetics in fifteen untreated HBeAg Negative Infection (ENI) (4F-11M, 62.1y) and eight Nucleos(t)ide Analogs (NAs) treated Chronic Hepatitis B (CHB) (3F-6M, 54.8y) with HCV co-infection, receiving DAAs-regimens including Sofosbuvir (13) or not (10). All achieved a sustained virologic response (SVR) and normalized alanine-aminotransferase (ALT). At the direct acting antivirals’ (DAAs) baseline (BL), the HBV-DNA was undetectable (<6 IU/mL) in eight ENI and all CHB, the mean Log-HBsAg was lower in ENI than CHB (0.88 vs. 2.42, p = 0.035). During DAAs, HBV-DNA increased in untreated ENI by >1 Log in five and became detectable in two. Accordingly, mean BL Log-HBV-DNA (0.89) increased at week-4 (1.78; p = 0.100) and at the end of therapy (1.57; p = 0.104). Mean Log-HBsAg decreased at week-4 in ENI (from 0.88 to 0.55; p = 0.020) and CHB (from 2.42 to 2.15; p = 0.015). After DAAs, the HBsAg returned to pre-treatment levels in CHB, but not in ENI (six cleared HBsAg). Female gender and SOF were associated with a greater HBsAg decline. In conclusion, HBV reactivations during DAAs in HCV co-infected ENI caused moderate increases of HBV-DNA without ALT elevations. The concomitant HBsAg decline, although significant, did not modify individual pre-treatment profiles.

Non invasive immunologic markers of virus-induced liver disease are unmet needs. We tested the clinical significance of quantitative total and IgM-anti-HBc in well characterized chronic-HBsAg-carriers. Sera (212) were obtained from 111 HBsAg-carriers followed-up for 52 months (28-216) during different phases of chronic-HBV-genotype-D-infection: 10 HBeAg-positive, 25 inactive-carriers (HBV-DNA less than or equal to 2000IU/ml, ALT<30U/L), 66 HBeAg-negative-CHB-patients and 10 with HDV-super-infection. In 35 patients treated with Peg-IFN plus or minus nucleos(t)ide-analogues (NUCs) sera were obtained at baseline, end-of-therapy and week-24-off-therapy and in 22 treated with NUCs (for 60 months, 42-134m) at baseline and end-of-follow-up. HBsAg and IgM-anti-HBc were measured by Architect-assays (Abbott, USA); total-anti-HBc by double-antigen-sandwich-immune-assay (Wantai, China); HBV-DNA by COBAS-TaqMan (Roche, Germany). Total-anti-HBc were detectable in all sera with lower levels in HBsAg-carriers without CHB (immune-tolerant, inactive and HDV-superinfected, median 3.26, range 2.26-4.49 Log10 IU/ml) versus untreated-CHB (median 4.68, range 2.76-5.54 Log10 IU/ml), p<0.0001. IgM-anti-HBc positive using the chronic-hepatitis-cut-off\" (0.130-S/CO) were positive in 102 of 212 sera (48.1%). Overall total-anti-HBc and IgM-anti-HBc correlated significantly (p<0.001, r=0.417). Total-anti-HBc declined significantly in CHB patients with response to Peg-IFN (p<0.001) and in NUC-treated patients (p<0.001); the lowest levels (median 2.68, range 2.12-3.08 Log10 IU/ml) were found in long-term responders who cleared HBsAg subsequently. During spontaneous and therapy-induced fluctuations of CHB (remissions and reactivations) total- and IgM-anti-HBc correlated with ALT (p<0.001, r=0.351 and p=0.008, r=0.185 respectively). Total-anti-HBc qualifies as a useful marker of HBV-induced-liver-disease that might help to discriminate major phases of chronic HBV infection and to predict sustained response to antivirals.

In this paper a high-voltage sinusoidal power supply controlled by Arduino DUE micro-controller is described. This generator can feed a dielectric barrier discharge (DBD) load with sinusoidal voltages up to 20 kV peak and frequencies in the range 10–60 kHz, with a maximum output power of 200 W. Output voltage can be produced either in a continuous mode, or with on/off modulation cycles, according to treatment/application requirements. This power source is equipped with on-board diagnostics used to measure the output voltage and the charge delivered to the load. With a sample frequency of 500 kHz, Arduino DUE allows to evaluate both the high voltage and the average power feeding the discharge without the use of an expensive external measurement setup. Lissajous techniques are utilized to calculate discharge average power in a quasi-real-time manner. When a load is connected to high-voltage terminals, a self-tuning procedure is carried out to obtain the best working frequency. This parameter allows to minimize power-electronic component stress and to maximize generator efficiency.

Electric vehicles (EVs) penetration growth is essential to reduce transportation-related local pollutants. Most countries are witnessing a rapid development of the necessary charging infrastructure and a consequent increase in EV energy demand. In this context, power demand forecasting is an essential tool for planning and integrating EV charging as much as possible with the electric grid, renewable sources, storage systems, and their management systems. However, this forecasting is still challenging due to several reasons: the still not statistically significant number of circulating EVs, the different users’ behavior based on the car parking scenario, the strong heterogeneity of both charging infrastructure and EV population, and the uncertainty about the initial state of charge (SOC) distribution at the beginning of the charge. This paper aims to provide a forecasting method that considers all the main factors that may affect each charging event. The users’ behavior in different urban scenarios is predicted through their statistical pattern. A similar approach is used to forecast the EV’s initial SOC. A machine learning approach is adopted to develop a battery-charging behavioral model that takes into account the different EV model charging profiles. The final algorithm combines the different approaches providing a forecasting of the power absorbed by each single charging session and the total power absorbed by charging hubs. The algorithm is applied to different parking scenarios and the results highlight the strong difference in power demand among the different analyzed cases.

In the context of electric vehicle (EV) development and positive energy districts with the growing penetration of non-programmable sources, this paper provides a method to predict and manage the aggregate power flows of charging stations to optimize the self-consumption and load profiles. The prediction method analyzes each charging event belonging to the EV population, and it considers the main factors that influence a charging process, namely the EV’s characteristics, charging ratings, and driver behavior. EV’s characteristics and charging ratings are obtained from the EV model’s and charging stations’ specifications, respectively. The statistical analysis of driver behavior is performed to calculate the daily consumptions and the charging energy request. Then, a model to estimate the parking time of each vehicle is extrapolated from the real collected data of the arrival and departure times in parking lots. A case study was carried out to evaluate the proposed method. This consisted of an industrial area with renewable sources and electrical loads. The obtained results show how EV charging can negatively impact system power flows, causing load peaks and high energy demand. Therefore, a charging management system (CMS) able to operate in the smart charging mode was introduced. Finally, it was demonstrated that the proposed method provides better EV integration and improved performance.