806 research outputs found

    Unripe carob pods: an innovative source of antioxidant molecules for the preparation of high-added value gummies

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    Purpose: This study aims to investigate unripe carob pod as a source of antioxidant molecules useful in the eco-friendly synthesis of a gelatin conjugate. This one was involved in the preparation of gummies able to produce remarkable human health benefits. Design/methodology/approach: Eco-friendly strategies (ultrasound-assisted extraction, low temperatures and eco-friendly solvents) were employed in the extraction of active molecules. Antioxidant molecules were involved in the grafting reaction with gelatin chains (ascorbic acid/hydrogen peroxide couple as initiator system). Gelatin conjugate represents a useful material able to prepare gummies with remarkable rheological and antioxidant performances over time. Findings: Experimental results confirmed that the green approach allowed the achievement of extracts with remarkable antioxidant properties due to the presence of phenolic moieties. Gelatin conjugate synthesis preserved these functionalities, usefully exploited in the preparation of gummies with significant structural and biological features. Originality/value: Compared to the literature data the preparation of the gummies with outstanding biological properties was performed by employing functional gelatin synthesized by an eco-friendly approach

    Machine-learning based prediction of in-hospital death for patients with takotsubo syndrome: the InterTAK-ML model

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    Aims: Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine-learning (ML) based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles. Methods and results: A Ridge Logistic Regression-based ML model for predicting in-hospital death was developed on 3482 TTS patients from the International Takotsubo Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). 31 clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the receiver-operating characteristic curve (AUC), Sensitivity and Specificity. As secondary endpoint, a K-Medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the ten most relevant features emerging from the main model. The overall incidence of in-hospital death was 5.2%. The InterTAK-ML model showed an AUC of 0.89 (0.85-0.92), Sensitivity 0.85 (0.78-0.95) and Specificity 0.76 (0.74-0.79) in the internal validation cohort and an AUC of 0.82 (0.73-0.91), a sensitivity of 0.74 (0.61-0.87) and a specificity of 0.79 (0.77-0.81) in the external cohort for in-hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in-hospital death (28.8% vs 15.5% vs 5.4% vs 0.8% vs 0.5%) which were consistent also in the external cohort. Conclusion: A ML-based approach for the identification of TTS patients at risk of adverse short-term prognosis is feasible and effective. The InterTAK-ML model showed unprecedented discriminative capability for the prediction of in-hospital death. This article is protected by copyright. All rights reserved

    Which birth weight threshold to start parenteral nutrition? A single center experience

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    Objectives: To analyze the need for parenteral nutrition (PN) in infants with a birth weight (BW) between 1250 and 1499 g. Methods: Retrospective evaluation of clinical, nutritional, growth and neurodevelopmental data of infants with a BW between 1250 and 1499 g consecutively admitted to our institution between 2004 and 2020. Results: Of the 503 infants admitted during the study period, 130 (26%) received PN: in 97 (19%) PN was medically indicated, while in 33 (7%) there was no clear indication. Patients who received medically indicated PN were younger, smaller, and sicker than the 373 infants who were managed with enteral nutrition, and their weight gain was lower (14.6 ¬Ī 4.1 vs 16.9 ¬Ī 4.2 g‚ąôkg‚ąí1‚ąô d‚ąí1, p = 0.000). Body size at 36 weeks and 2-year anthropometry and neurodevelopment of the infants managed with enteral nutrition were not different from our reference values. Conclusions: After lowering the BW threshold for bridging PN from 1500 to 1250 g, we found that PN was started in only 20% of infants with a BW between 1250 and 1500 g. Withholding PN if not medically indicated did not result neither in growth faltering nor in reduced neurodevelopment

    Unsupervised machine learning with cluster analysis in patients discharged after an acute coronary syndrome. Insights from a 23,270-patient study

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    Characterization and management of patients admitted for acute coronary syndromes (ACS) remain challenging, and it is unclear whether currently available clinical and procedural features can suffice to inform adequate decision making. We aimed to explore the presence of specific subsets among patients with ACS. The details on patients discharged after ACS were obtained by querying an extensive multicenter registry and detailing patient features, as well as management details. The clinical outcomes included fatal and nonfatal cardiovascular events at 1-year follow-up. After missing data imputation, 2 unsupervised machine learning approaches (k-means and Clustering Large Applications [CLARA]) were used to generate separate clusters with different features. Bivariate- and multivariable-adjusted analyses were performed to compare the different clusters for clinical outcomes. A total of 23,270 patients were included, with 12,930 cases (56%) of ST-elevation myocardial infarction (STEMI). K-means clustering identified 2 main clusters: a first 1 including 21,998 patients (95%) and a second 1 including 1,282 subjects (5%), with equal distribution for STEMI. CLARA generated 2 main clusters: a first 1 including 11,268 patients (48%) and a second 1 with 12,002 subjects (52%). Notably, the STEMI distribution was significantly different in the CLARA-generated clusters. The clinical outcomes were significantly different across clusters, irrespective of the originating algorithm, including death reinfarction and major bleeding, as well as their composite. In conclusion, unsupervised machine learning can be leveraged to explore the patterns in ACS, potentially highlighting specific patient subsets to improve risk stratification and management

    Glycogen Synthase Kinase 3: Ion Channels, Plasticity, and Diseases

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    Glycogen synthase kinase 3ő≤ (GSK3) is a multifaceted serine/threonine (S/T) kinase expressed in all eukaryotic cells. GSK3ő≤ is highly enriched in neurons in the central nervous system where it acts as a central hub for intracellular signaling downstream of receptors critical for neuronal function. Unlike other kinases, GSK3ő≤ is constitutively active, and its modulation mainly involves inhibition via upstream regulatory pathways rather than increased activation. Through an intricate converging signaling system, a fine-tuned balance of active and inactive GSK3ő≤ acts as a central point for the phosphorylation of numerous primed and unprimed substrates. Although the full range of molecular targets is still unknown, recent results show that voltage-gated ion channels are among the downstream targets of GSK3ő≤. Here, we discuss the direct and indirect mechanisms by which GSK3ő≤ phosphorylates voltage-gated Na+ channels (Nav 1.2 and Nav 1.6) and voltage-gated K+ channels (Kv 4 and Kv 7) and their physiological effects on intrinsic excitability, neuronal plasticity, and behavior. We also present evidence for how unbalanced GSK3ő≤ activity can lead to maladaptive plasticity that ultimately renders neuronal circuitry more vulnerable, increasing the risk for developing neuropsy-chiatric disorders. In conclusion, GSK3ő≤-dependent modulation of voltage-gated ion channels may serve as an important pharmacological target for neurotherapeutic development
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