Link between increased gut hormones signaling satiety and reduced food reward following gastric bypass surgery for obesity

CONTEXT: Roux-en-Y gastric bypass (RYGB) surgery is an effective long-term intervention for weight loss maintenance, reducing appetite, and also food reward, via unclear mechanisms. OBJECTIVE: To investigate the role of elevated satiety gut hormones after RYGB, we examined food hedonic-reward responses after their acute post-prandial suppression. DESIGN: These were randomized, placebo-controlled, double-blind, crossover experimental medicine studies. PATIENTS: Two groups, more than 5 months after RYGB for obesity (n = 7-11), compared with nonobese controls (n = 10), or patients after gastric banding (BAND) surgery (n = 9) participated in the studies. INTERVENTION: Studies were performed after acute administration of the somatostatin analog octreotide or saline. In one study, patients after RYGB, and nonobese controls, performed a behavioral progressive ratio task for chocolate sweets. In another study, patients after RYGB, and controls after BAND surgery, performed a functional magnetic resonance imaging food picture evaluation task. MAIN OUTCOME MEASURES: Octreotide increased both appetitive food reward (breakpoint) in the progressive ratio task (n = 9), and food appeal (n = 9) and reward system blood oxygen level-dependent signal (n = 7) in the functional magnetic resonance imaging task, in the RYGB group, but not in the control groups. RESULTS: Octreotide suppressed postprandial plasma peptide YY, glucagon-like peptide-1, and fibroblast growth factor-19 after RYGB. The reduction in plasma peptide YY with octreotide positively correlated with the increase in brain reward system blood oxygen level-dependent signal in RYGB/BAND subjects, with a similar trend for glucagon-like peptide-1. CONCLUSIONS: Enhanced satiety gut hormone responses after RYGB may be a causative mechanism by which anatomical alterations of the gut in obesity surgery modify behavioral and brain reward responses to food

Mechanisms underlying type 2 diabetes remission after metabolic surgery

Type 2 diabetes prevalence is increasing dramatically worldwide. Metabolic surgery is the most effective treatment for selected patients with diabetes and/or obesity. When compared to intensive medical therapy and lifestyle intervention, metabolic surgery has shown superiority in achieving glycemic improvement, reducing number of medications and cardiovascular risk factors, which translates in long-term benefits on cardiovascular morbidity and mortality. The mechanisms underlying diabetes improvement after metabolic surgery have not yet been clearly understood but englobe a complex interaction among improvements in beta cell function and insulin secretion, insulin sensitivity, intestinal gluconeogenesis, changes in glucose utilization, and absorption by the gut and changes in the secretory pattern and morphology of adipose tissue. These are achieved through different mediators which include an enhancement in gut hormones release, especially, glucagon-like peptide 1, changes in bile acids circulation, gut microbiome, and glucose transporters expression. Therefore, this review aims to provide a comprehensive appraisal of what is known so far to better understand the mechanisms through which metabolic surgery improves glycemic control facilitating future research in the field

Phase behavior of gelatin/maltodextrin aqueous mixtures studied from a combined experimental and theoretical approach

A combined experimental and theoretical study of the phase behavior of mixtures of gelatin and maltodextrin is presented. This system, at neutral pH and 50C, exhibits coexistence of three equilibrium phases: two liquid phases and a third, which is a solid-like precipitate that resembles a coacervate. This phase behavior completely changes at lower pH, where only two phases remain. Flory-Huggins solution theory is used to model the observed phase behavior. The optimal fits of the associated Flory-Huggins mixing parameters are obtained using a novel non-linear regression method based on neural networks. The neural network was trained using as input only the number of phases present, without knowledge of the specific compositions of the coexisting phases. The optimal Flory-Huggins parameters result in phase diagrams which are consistent with our experimental data. A comparison with the experimental results indicates that the method can produce relevant fits of the model parameters in situations where the information is limited. Moreover, the formation of the solid-like precipitate can be explained within the standard Flory-Huggins framework, despite the fact that important local and specific interactions or induced structural changes occur in the system to produce such a precipitate. In conclusion, the model obtained for this system allows a straightforward exploration, prior to the experimental validation, of the appropriate conditions for future practical applications of this system.The authors acknowledge the Spanish Ministry of Science and Innovation, the Agencia Estatal de Investigación and the European Regional Development Fund for CTQ2014-52687-C3-1-P and CTQ2017-84998-P projects, the Generalitat de Catalunya (2017 SGR 1610) and the University Rovira i Virgili (2018PFR-URV-B2-52). F.M. also acknowledges the Universitat Rovira i Virgili for the Martí i Franquès scholarship 2016 MF-PIPF-27. J.E. and Y.B. acknowledge the Marie Sklodowska Curie Initial Training Networks (FP7-PEOPLE-2013-ITN-606713, BIBAFOODS project), and support from Generalitat de Catalunya (2014SGR1655 and 2017 SGR 1778)

Oxovanadium(IV)-sulfite compounds: Synthesis and structural and physical studies

Reaction of VIVOCl2 in strongly acidic aqueous solution with either (NH4)(2)SO3 or Na2SO3 and Bu4NBr at similar to 70 degrees C in the pH range 2.5-4.5 gives the clusters (NH4)(2){V-4(IV)(mu(4)-O)(2)(mu(3)-OH)(2)]((VO)-O-IV)(2)(mu(3)-SO3)( 4)O-4(H2O)(2)} and (n-Bu4N)(2){V-4(IV)(mu(4)-O)(2)(mu(3)-OH)(2)]((VO)-O-IV)(2)(mu(3)-SO 3)(4)O-4(H2O)(2)}, respectively. Reaction of (NH4VO3)-O-V with (NH4)(2)SO3 resulted in the isolation of the first compound. When the latter reaction is carried out in the presence of MgO, compound (NH4)(VO)-O-IV(SO3)(1.5)H2O](infinity)center dot 2.5H(2)O was isolated instead. Compound (n-Bu4N)(2){V-4(IV)(mu(4)-O)(2)(mu(3)-OH)(2)]((VO)-O-IV)(2)(mu(3)-SO 3)(4)O-4(H2O)(2)} and (NH4)(VO)-O-IV(SO3)(1.5)H2O](infinity)center dot 2.5H(2)O were characterized by X-ray structure analysis. The crystal structure of species (n-Bu4N)(2){IV4IV(mu(4)-O)(2)(mu(3)-OH)(2)]((VO)-O-IV)(2)(mu(3)-SO3)(4) O-4(H2O)(2)} revealed a unprecedented hexanuclear cluster consisting of a cubane core M-4(mu(4)-O)(2)(mu(3)- OH)(2)] connected to two other metal atoms through the core oxo-groups and four mu(3)-SO3 bridges. Compound (NH4)VIVO(SO3)(1.5)H2O](infinity)center dot 2.5H(2)O represents a rare example of an open-framework species prepared under mild conditions. Cyclic voltammetric examination of compound (n-Bu4N)(2){IV4IV(mu(4)-O)(2)(mu(3)-OH)(2)]((VO)-O-IV)(2)(mu(3)-SO3) (4)O-4(H2O)(2)] revealed a redox process which was assigned to the oxidation of one core of vanadium(IV) to vanadium(V)

Drug-induced endocrinopathies and diabetes: A combo-endocrinology overview

In the currently overwhelming era of polypharmacy, the balance of the dynamic and delicate endocrine system can easily be disturbed by interfering pharmaceutical agents like medications. Drugs can cause endocrine abnormalities via different mechanisms, including direct alteration of hormone production, changes in the regulation of the feedback axis, on hormonal transport, binding and signaling, as well as similar changes to counter-regulatory hormone systems. Furthermore, drugs can interfere with the hormonal assays, leading to erroneous laboratory results that disorientate clinicians from the right diagnosis. The purpose of this review is to cover a contemporary topic, the drug-induced endocrinopathies, which was presented in the monothematic annual Combo Endo Course 2018. This challenging part of endocrinology is constantly expanding particularly during the last decade, with the new oncological therapeutic agents, targeting novel molecular pathways in the process of malignancies. In this new context of drug-induced endocrine disease, clinicians should be aware that drugs can cause endocrine abnormalities via different mechanisms and mimic a variety of clinical scenarios. Therefore, it is extremely important for clinicians not only to promptly recognize drug-induced hormonal and metabolic abnormalities, but also to address the therapeutic issues for timely intervention. © 2019 European Society of Endocrinology

Drug-induced endocrinopathies and diabetes: A combo-endocrinology overview

In the currently overwhelming era of polypharmacy, the balance of the dynamic and delicate endocrine system can easily be disturbed by interfering pharmaceutical agents like medications. Drugs can cause endocrine abnormalities via different mechanisms, including direct alteration of hormone production, changes in the regulation of the feedback axis, on hormonal transport, binding and signaling, as well as similar changes to counter-regulatory hormone systems. Furthermore, drugs can interfere with the hormonal assays, leading to erroneous laboratory results that disorientate clinicians from the right diagnosis. The purpose of this review is to cover a contemporary topic, the drug-induced endocrinopathies, which was presented in the monothematic annual Combo Endo Course 2018. This challenging part of endocrinology is constantly expanding particularly during the last decade, with the new oncological therapeutic agents, targeting novel molecular pathways in the process of malignancies. In this new context of drug-induced endocrine disease, clinicians should be aware that drugs can cause endocrine abnormalities via different mechanisms and mimic a variety of clinical scenarios. Therefore, it is extremely important for clinicians not only to promptly recognize drug-induced hormonal and metabolic abnormalities, but also to address the therapeutic issues for timely intervention. © 2019 European Society of Endocrinology

Integration of longitudinal deep-radiomics and clinical data improves the prediction of durable benefits to anti-PD-1/PD-L1 immunotherapy in advanced NSCLC patients

Background Identifying predictive non-invasive biomarkers of immunotherapy response is crucial to avoid premature treatment interruptions or ineffective prolongation. Our aim was to develop a non-invasive biomarker for predicting immunotherapy clinical durable benefit, based on the integration of radiomics and clinical data monitored through early anti-PD-1/PD-L1 monoclonal antibodies treatment in patients with advanced non-small cell lung cancer (NSCLC).MethodsIn this study, 264 patients with pathologically confirmed stage IV NSCLC treated with immunotherapy were retrospectively collected from two institutions. The cohort was randomly divided into a training (n = 221) and an independent test set (n = 43), ensuring the balanced availability of baseline and follow-up data for each patient. Clinical data corresponding to the start of treatment was retrieved from electronic patient records, and blood test variables after the first and third cycles of immunotherapy were also collected. Additionally, traditional radiomics and deep-radiomics features were extracted from the primary tumors of the computed tomography (CT) scans before treatment and during patient follow-up. Random Forest was used to implementing baseline and longitudinal models using clinical and radiomics data separately, and then an ensemble model was built integrating both sources of information.ResultsThe integration of longitudinal clinical and deep-radiomics data significantly improved clinical durable benefit prediction at 6 and 9 months after treatment in the independent test set, achieving an area under the receiver operating characteristic curve of 0.824 (95% CI: [0.658,0.953]) and 0.753 (95% CI: [0.549,0.931]). The Kaplan-Meier survival analysis showed that, for both endpoints, the signatures significantly stratified high- and low-risk patients (p-value< 0.05) and were significantly correlated with progression-free survival (PFS6 model: C-index 0.723, p-value = 0.004; PFS9 model: C-index 0.685, p-value = 0.030) and overall survival (PFS6 models: C-index 0.768, p-value = 0.002; PFS9 model: C-index 0.736, p-value = 0.023).ConclusionsIntegrating multidimensional and longitudinal data improved clinical durable benefit prediction to immunotherapy treatment of advanced non-small cell lung cancer patients. The selection of effective treatment and the appropriate evaluation of clinical benefit are important for better managing cancer patients with prolonged survival and preserving quality of life