Adipokines and Redox Signaling: Impact on Fatty Liver Disease

Adipokines (adipose tissue cytokines) are polypeptide factors secreted by adipose tissue in a highly regulated manner. The 'classical' adipokines (leptin, adiponectin, and resistin) are expressed only by adipocytes, but other adipokines have been shown to be released by resident and infiltrating macrophages, as well as by components of the vascular stroma. Indeed, adipose tissue inflammation is known to be associated with a modification in the pattern of adipokine secretion. Several studies indicate that adipokines can interfere with hepatic injury associated with fatty infiltration, differentially modulating steatosis, inflammation, and fibrosis. Moreover, plasma levels of adipokines have been investigated in patients with nonalcoholic fatty liver disease in order to establish correlations with the underlying state of insulin resistance and with the type and severity of hepatic damage. In this Forum article, we provide a review of recent data that suggest a significant role for oxidative stress, reactive oxygen species, and redox signaling in mediating actions of adipokines that are relevant in the pathogenesis of nonalcoholic fatty liver disease, including hepatic insulin resistance, inflammation, and fibrosis

Un client web EPP per la Regione Toscana

L\u27Istituto di Informatica e Telematica del CNR di Pisa (IIT-CNR) gestisce il Registro del country code Top Level Domain .it (Registro .it). Nel corso del 2009, il Registro .it ha attivato un nuovo sistema di registrazione, denominato "sistema sincrono", basato sul protocollo di comunicazione EPP (Extensible Provisioning Protocol). Al fine di supportare la Regione Toscana nell\u27evoluzione dei propri sistemi di gestione dei domini, conseguentemente al passaggio dal vecchio sistema asincrono al nuovo sistema sincrono, lo IIT-CNR, sulla base di una convenzione tra i due enti, ha fornito il supporto tecnico per la progettazione e realizzazione di un\u27interfaccia client web EPP che disponesse delle funzionalit? necessarie alla registrazione e al mantenimento dei nomi a dominio nel .it in modalit? sincrona. Il client web ? stato implementato con un\u27applicazione J2EE da deployare su un\u27opportuna istanza dell\u27application server JBoss

Graphene-based dental adhesive with anti-biofilm activity

BACKGROUND: Secondary caries are considered the main cause of dental restoration failure. In this context, anti-biofilm and bactericidal properties are desired in dental materials against pathogens such as Streptococcus mutans. To this purpose, graphene based materials can be used as fillers of polymer dental adhesives. In this work, we investigated the possibility to use as filler of dental adhesives, graphene nanoplatelets (GNP), a non toxic hydrophobic nanomaterial with antimicrobial and anti-biofilm properties. RESULTS: Graphene nanoplatelets have been produced starting from graphite intercalated compounds through a process consisting of thermal expansion and liquid exfoliation. Then, a dental adhesive filled with GNPs at different volume fractions has been produced through a solvent evaporation method. The rheological properties of the new experimental adhesives have been assessed experimentally. The adhesive properties have been tested using microtensile bond strength measurements (µ-TBS). Biocidal activity has been studied using the colony forming units count (CFU) method. The anti-biofilm properties have been demonstrated through FE-SEM imaging of the biofilm development after 3 and 24 h of growth. CONCLUSIONS: A significantly lower vitality of S. mutans cells has been demonstrated when in contact with the GNP filled dental adhesives. Biofilm growth on adhesive-covered dentine tissues demonstrated anti-adhesion properties of the produced materials. µ-TBS results demonstrated no significant difference in µ-TBS between the experimental and the control adhesive. The rheology tests highlighted the necessity to avoid low shear rate regimes during adhesive processing and application in clinical protocol, and confirmed that the adhesive containing the 0.2%wt of GNPs possess mechanical properties comparable with the ones of the control adhesive

Are Raw BIA Variables Useful for Predicting Resting Energy Expenditure in Adults with Obesity?

This study aimed to develop and validate new predictive equations for resting energy expenditure (REE) in a large sample of subjects with obesity also considering raw variables from bioimpedance-analysis (BIA). A total of 2225 consecutive obese outpatients were recruited and randomly assigned to calibration (n = 1680) and validation (n = 545) groups. Subjects were also split into three subgroups according to their body mass index (BMI). The new predictive equations were generated using two models: Model 1 with age, weight, height, and BMI as predictors, and Model 2 in which raw BIA variables (bioimpedance-index and phase angle) were added. Our results showed that REE was directly correlated with all anthropometric and raw-BIA variables, while the correlation with age was inverse. All the new predictive equations were effective in estimating REE in both sexes and in the different BMI subgroups. Accuracy at the individual level was high for specific group-equation especially in subjects with BMI > 50 kg/m². Therefore, new equations based on raw-BIA variables were as accurate as those based on anthropometry. Equations developed for BMI categories did not substantially improve REE prediction, except for subjects with a BMI > 50 kg/m². Further studies are required to verify the application of those formulas and the role of raw-BIA variables for predicting REE

Prediction and evaluation of resting energy expenditure in a large group of obese outpatients

The aim of this study was to compare resting energy expenditure (REE) measured (MREE) by indirect calorimetry (IC) and REE predicted (PREE) from established predictive equations in a large sample of obese Caucasian adults

Prediction of body composition in anorexia nervosa: Results from a retrospective study

Summary Background & aims The assessment of body composition is crucial in evaluating nutritional status in female subjects with anorexia nervosa (AN) and improving their clinical management. The aim of this retrospective study was to assess the accuracy of selected BIA (bioimpedance analysis) equations for fat-free mass (FFM) in female AN subjects and to formulate a specific equation for these subjects. Methods Eighty-two restrictive female AN subjects (age 20.5 ± 3.7 yrs, BMI 15.7 ± 1.7 kg/m 2 ) were studied. Body composition was determined with dual-energy X-ray absorptiometry (DXA) and estimated by BIA using five different equations. Linear correlation analysis was carried out to evaluate the association of FFM with selected variables. Multiple regression analysis was used to formulate specific equations to predict FFM in AN. Results All predictive equations underestimated FFM at the population level with a bias from −5.6 to −11.7%, while the percentage of accurate predictions varied from 12.2% to 35.4%. More interestingly, multiple regression analysis clearly indicates that, in addition to weight, ZI 100 or RI also emerged as independent predictors of DXA-derived FFM, increasing the prediction power of the equation well above that observed with anthropometric characteristics only. Conclusions This study shows that the selected predictive BIA equations considered exhibit an insufficient accuracy at the population and the individual level. Predictive formulas based on body weight plus BIA parameters such as RI and ZI 100 offer a rather accurate prediction of FFM (with high R squared)