Antioxidant Bio-Compounds from Chestnut Waste: A Value-Adding and Food Sustainability Strategy.

In an era of escalating environmental challenges, converting organic residues into high-value bioactive compounds provides a sustainable way to reduce waste and enhance resource efficiency. This study explores the potential of the circular bioeconomy through the valorization of agricultural byproducts, with a focus on the antioxidant properties of specific chestnut burr cultivars. Currently, over one-third of food production is wasted, contributing to both humanitarian and environmental crises.

Extract as a Source of Antimicrobial Compounds: A Circular Bioeconomy Approach.

The circular bioeconomy is currently a promising model for repurposing natural sources; these sources include plants due to their abundance of bioactive compounds. This study evaluated the antimicrobial properties of a extract. is an invasive macroalga from the Orbetello Lagoon (Tuscany, Italy), which grows in nutrient-rich environments and has been forming extended mats since 2005.

HGA Triggers SAA Aggregation and Accelerates Fibril Formation in the C20/A4 Alkaptonuria Cell Model.

Alkaptonuria (AKU) is a rare autosomal recessive metabolic disorder caused by mutations in the homogentisate 1,2-dioxygenase (HGD) gene, leading to the accumulation of homogentisic acid (HGA), causing severe inflammatory conditions. Recently, the presence of serum amyloid A (SAA) has been reported in AKU tissues, classifying AKU as novel secondary amyloidosis; AA amyloidosis is characterized by the extracellular tissue deposition of fibrils composed of fragments of SAA. AA amyloidosis may complicate several chronic inflammatory conditions, like rheumatoid arthritis, ankylosing spondylitis, inflammatory bowel disease, chronic infections, neoplasms, etc.

Molecular Origins of the Mendelian Rare Diseases Reviewed by Orpha.net: A Structural Bioinformatics Investigation.

The study of rare diseases is important not only for the individuals affected but also for the advancement of medical knowledge and a deeper understanding of human biology and genetics. The wide repertoire of structural information now available from reliable and accurate prediction methods provides the opportunity to investigate the molecular origins of most of the rare diseases reviewed in the Orpha.net database.

Repurposing Spiny Burr By-Products Extract as a Potentially Effective Anti-Inflammatory Agent for Novel Future Biotechnological Applications.

The concept of a "circular bioeconomy" holds great promise for the health, cosmetic, and nutrition sectors by re-using (Mill.) by-products. This sustainable resource is rich in bioactive secondary metabolites with antioxidant and anti-inflammatory properties.

Molecular and Evolution Studies Unlock the h4-HPPD C-Terminal Tail Gating Mechanism.

The enzyme 4-hydroxyphenylpyruvate dioxygenase (4-HPPD) is involved in the catabolism of the amino acid tyrosine in organisms such as bacteria, plants, and animals. It catalyzes the conversion of 4-hydroxyphenylpyruvate to a homogenisate in the presence of molecular oxygen and Fe(II) as a cofactor. This enzyme represents a key step in the biosynthesis of important compounds, and its activity deficiency leads to severe, rare autosomal recessive disorders, like tyrosinemia type III and hawkinsinuria, for which no cure is currently available.

Using an mHealth approach to collect patient-generated health data for predicting adverse health outcomes among adult survivors of childhood cancer.

Introduction: Cancer therapies predispose childhood cancer survivors to various treatment-related late effects, which contribute to a higher symptom burden, chronic health conditions (CHCs), and premature mortality. Regular monitoring of symptoms between clinic visits is useful for timely medical consultation and interventions that can improve quality of life (QOL). The Health Share Study aims to utilize mHealth to collect patient-generated health data (PGHD; daily symptoms, momentary physical health status) and develop survivor-specific risk prediction scores for mitigating adverse health outcomes including poor QOL and emergency room admissions.

Phytochemical Composition, Anti-Inflammatory Property, and Anti-Atopic Effect of Extract.

Utilizing plant-based resources, particularly their by-products, aligns with sustainability principles and circular bioeconomy, contributing to environmental preservation. The therapeutic potential of plant extracts is garnering increasing interest, and this study aimed to demonstrate promising outcomes from an extract obtained from an underutilized plant waste. , an invasive macroalga found in the Orbetello Lagoon, thrives in eutrophic conditions, forming persistent mats covering approximately 400 hectares since 2005.

[Non-inferiority trials].

Superiority trials are designed to test the hypothesis that a given diagnostic or therapeutic strategy is better than (i.e. "superior to") placebo or an active control.

A Drug Discovery Approach to a Reveal Novel Antioxidant Natural Source: The Case of Chestnut Burr Biomass.

Currently, many environmental and energy-related problems are threatening the future of our planet. In October 2022, the Worldmeter recorded the world population as 7.9 billion people, estimating that there will be an increase of 2 billion by 2057.

Recent Advances in Organic Dyes for Application in Dye-Sensitized Solar Cells under Indoor Lighting Conditions.

Among the emerging photovoltaic (PV) technologies, Dye-Sensitized Solar Cells (DSSCs) appear especially interesting in view of their potential for unconventional PV applications. In particular, DSSCs have been proven to provide excellent performances under indoor illumination, opening the way to their use in the field of low-power devices, such as wearable electronics and wireless sensor networks, including those relevant for application to the rapidly growing Internet of Things technology. Considering the low intensity of indoor light sources, efficient light capture constitutes a pivotal factor in optimizing cell efficiency.

Catheter-based renal artery denervation: facts and expectations.

Catheter-based renal artery denervation (RAD) is entering a new era. After the disappointing results of SYMPLICITY-HTN 3 trial in year 2014, several technical and methodological advancements led to execution of important SHAM-controlled randomized trials with promising results. Now, the 2023 ESH Guidelines give RAD a class of recommendation II with a Level of Evidence B.

Supporting Machine Learning Model in the Treatment of Chronic Pain.

Conventional therapy options for chronic pain are still insufficient and patients most frequently request alternative medical treatments, such as medical cannabis. Although clinical evidence supports the use of cannabis for pain, very little is known about the efficacy, dosage, administration methods, or side effects of widely used and accessible cannabis products. A possible solution could be given by pharmacogenetics, with the identification of several polymorphic genes that may play a role in the pharmacodynamics and pharmacokinetics of cannabis.

Experimental and Numerical Analysis of a Pd-Ag Membrane Unit for Hydrogen Isotope Recovery in a Solid Blanket.

The interest of the fusion community in Pd-Ag membranes has grown in the last decades due to the high value of hydrogen permeability and the possibility of continuous operation, making it a promising technology when a gaseous stream of hydrogen isotopes must be recovered and separated from other impurities. This is the case of the Tritium Conditioning System (TCS) of the European fusion power plant demonstrator, called DEMO. This paper presents an experimental and numerical activity aimed at (i) assessing the Pd-Ag permeator performance under TCS-relevant conditions, (ii) validating a numerical tool for scale-up purposes, and (iii) carrying out a preliminary design of a TCS based on Pd-Ag membranes.

Interpretation of Ambulatory Blood Pressure Monitoring for Risk Stratification in Hypertensive Patients: The 'Ambulatory Does Prediction Valid (ADPV)' Approach.

Several outcome-based prospective investigations have provided solid data which support the prognostic value of 24 h ambulatory blood pressure over and beyond cardiovascular traditional risk factors. Average 24 h, daytime, and nighttime blood pressures are the principal components of the ambulatory blood pressure profile that have improved cardiovascular risk stratification beyond traditional risk factors. Furthermore, several additional ambulatory blood pressure measures have been investigated.

Therapy of Type 2 diabetes: more gliflozines and less metformin?

Metformin is a frequently used anti-diabetic drug. In addition to the well-known modulating properties on glyco-metabolic control, metformin reduces cardiovascular (CV) risk partly independently of its anti-hyperglycaemic effect. The use of 'new' anti-diabetic drugs, inhibitors of the renal Na-glucose co-transporter (SGLTs-I or 'gliflozines') and GLP-1 receptor agonists (GLP1-RAs), has further contributed to challenge the strictly 'gluco-centric' view of diabetic CV disease.

Pharmacological Chaperones and Protein Conformational Diseases: Approaches of Computational Structural Biology.

Whenever a protein fails to fold into its native structure, a profound detrimental effect is likely to occur, and a disease is often developed. Protein conformational disorders arise when proteins adopt abnormal conformations due to a pathological gene variant that turns into gain/loss of function or improper localization/degradation. Pharmacological chaperones are small molecules restoring the correct folding of a protein suitable for treating conformational diseases.

The Impact of Artificial Intelligence in the Odyssey of Rare Diseases.

Emerging machine learning (ML) technologies have the potential to significantly improve the research and treatment of rare diseases, which constitute a vast set of diseases that affect a small proportion of the total population. Artificial Intelligence (AI) algorithms can help to quickly identify patterns and associations that would be difficult or impossible for human analysts to detect. Predictive modeling techniques, such as deep learning, have been used to forecast the progression of rare diseases, enabling the development of more targeted treatments.