Incidence of new-onset hypertension before, during, and after the COVID-19 pandemic: a 7-year longitudinal cohort study in a large population.

BACKGROUND: While the augmented incidence of diabetes after COVID-19 has been widely confirmed, controversial results are available on the risk of developing hypertension during the COVID-19 pandemic. METHODS: We designed a longitudinal cohort study to analyze a closed cohort followed up over a 7-year period, i.e., 3 years before and 3 years during the COVID-19 pandemic, and during 2023, when the pandemic was declared to be over. We analyzed medical records of more than 200,000 adults obtained from a cooperative of primary physicians from January 1, 2017, to December 31, 2023. The main outcome was the new diagnosis of hypertension. RESULTS: We evaluated 202,163 individuals in the pre-pandemic years and 190,743 in the pandemic years, totaling 206,857 when including 2023 data. The incidence rate of new hypertension was 2.11 (95% C.I. 2.08-2.15) per 100 person-years in the years 2017-2019, increasing to 5.20 (95% C.I. 5.14-5.26) in the period 2020-2022 (RR = 2.46), and to 6.76 (95% C.I. 6.64-6.88) in 2023. The marked difference in trends between the first and the two successive observation periods was substantiated by the fitted regression lines of two Poisson models conducted on the monthly log-incidence of hypertension. CONCLUSIONS: We detected a significant increase in new-onset hypertension during the COVID-19 pandemic, which at the end of the observation period affected ~ 20% of the studied cohort, a percentage higher than the diagnosis of COVID-19 infection within the same time frame. This observation suggests that increased attention to hypertension screening should not be limited to individuals who are aware of having contracted the infection but should be extended to the entire population.

Endothelial Extracellular Vesicles Enriched in microRNA-34a Predict New-Onset Diabetes in Coronavirus Disease 2019 (COVID-19) Patients: Novel Insights for Long COVID Metabolic Sequelae.

Emerging evidence indicates that the relationship between coronavirus disease 2019 (COVID-19) and diabetes is 2-fold: 1) it is known that the presence of diabetes and other metabolic alterations poses a considerably high risk to develop a severe COVID-19; 2) patients who survived a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have an increased risk of developing new-onset diabetes. However, the mechanisms underlying this association are mostly unknown, and there are no reliable biomarkers to predict the development of new-onset diabetes. In the present study, we demonstrate that a specific microRNA (miR-34a) contained in circulating extracellular vesicles released by endothelial cells reliably predicts the risk of developing new-onset diabetes in COVID-19. This association was independent of age, sex, body mass index (BMI), hypertension, dyslipidemia, smoking status, and D-dimer. SIGNIFICANCE STATEMENT: We demonstrate for the first time that a specific microRNA (miR-34a) contained in circulating extracellular vesicles released by endothelial cells is able to reliably predict the risk of developing diabetes after having contracted coronavirus disease 2019 (COVID-19). This association was independent of age, sex, body mass index (BMI), hypertension, dyslipidemia, smoking status, and D-dimer. Our findings are also relevant when considering the emerging importance of post-acute sequelae of COVID-19, with systemic manifestations observed even months after viral negativization (long COVID).

MetalHawk: Enhanced Classification of Metal Coordination Geometries by Artificial Neural Networks.

The chemical properties of metal complexes are strongly dependent on the number and geometrical arrangement of ligands coordinated to the metal center. Existing methods for determining either coordination number or geometry rely on a trade-off between accuracy and computational costs, which hinders their application to the study of large structure data sets. Here, we propose MetalHawk (https://github.com/vrettasm/MetalHawk), a machine learning-based approach to perform simultaneous classification of metal site coordination number and geometry through artificial neural networks (ANNs), which were trained using the Cambridge Structural Database (CSD) and Metal Protein Data Bank (MetalPDB). We demonstrate that the CSD-trained model can be used to classify sites belonging to the most common coordination numbers and geometry classes with balanced accuracy equal to 96.51% for CSD-deposited metal sites. The CSD-trained model was also found to be capable of classifying bioinorganic metal sites from the MetalPDB database, with balanced accuracy equal to 84.29% on the whole PDB data set and to 91.66% on manually reviewed sites in the PDB validation set. Moreover, we report evidence that the output vectors of the CSD-trained model can be considered as a proxy indicator of metal-site distortions, showing that these can be interpreted as a low-dimensional representation of subtle geometrical features present in metal site structures.

Peptides and metal ions: A successful marriage for developing artificial metalloproteins.

The mutual relationship between peptides and metal ions enables metalloproteins to have crucial roles in biological systems, including structural, sensing, electron transport, and catalytic functions. The effort to reproduce or/and enhance these roles, or even to create unprecedented functions, is the focus of protein design, the first step toward the comprehension of the complex machinery of nature. Nowadays, protein design allows the building of sophisticated scaffolds, with novel functions and exceptional stability. Recent progress in metalloprotein design has led to the building of peptides/proteins capable of orchestrating the desired functions of different metal cofactors. The structural diversity of peptides allows proper selection of first- and second-shell ligands, as well as long-range electrostatic and hydrophobic interactions, which represent precious tools for tuning metal properties. The scope of this review is to discuss the construction of metal sites in de novo designed and miniaturized scaffolds. Selected examples of mono-, di-, and multi-nuclear binding sites, from the last 20 years will be described in an effort to highlight key artificial models of catalytic or electron-transfer metalloproteins. The authors' goal is to make readers feel like guests at the marriage between peptides and metal ions while offering sources of inspiration for future architects of innovative, artificial metalloproteins.

Engineering Metalloprotein Functions in Designed and Native Scaffolds.

Metalloproteins are crucial for life. The mutual relationship between metal ions and proteins makes metalloproteins able to accomplish key processes in biological systems, often very difficult to reproduce with inorganic coordination compounds under mild conditions. Taking inspiration from nature, many efforts have been devoted to developing artificial molecules as metalloprotein mimics. We have witnessed an explosion of protein design strategies leading to designed metalloproteins, ranging from stable structures to functional molecules. This review illustrates the most recent results for inserting metalloprotein functions in designed and engineered protein scaffolds. The selected examples highlight the potential of different approaches for the construction of artificial molecules capable of simulating and even overcoming the features of natural metalloproteins.

An Artificial Miniaturized Peroxidase for Signal Amplification in Lateral Flow Immunoassays.

Signal amplification strategies are widely used for improving the sensitivity of lateral flow immunoassays (LFiAs). Herein, the artificial miniaturized peroxidase Fe(III)-MimochromeVI*a (FeMC6*a), immobilized on gold nanoparticles (AuNPs), is used as a strategy to obtain catalytic signal amplification in sandwich immunoassays on lateral flow strips. The assay scheme uses AuNPs decorated with the mini-peroxidase FeMC6*a and anti-human-IgG as a detection antibody (dAb), for the detection of human-IgG, as a model analyte. Recognition of the analyte by the capture and detection antibodies is first evidenced by the appearance of a red color in the test line (TL), due to the accumulation of AuNPs. Subsequent addition of 3,3',5,5'-tetramethylbenzidine (TMB) induces an increase of the test line color, due to the TMB being converted into an insoluble colored product, catalyzed by FeMC6*a. This work shows that FeMC6*a acts as an efficient catalyst in paper, increasing the sensitivity of an LFiA up to four times with respect to a conventional LFiA. Furthermore, FeMC6*a achieves lower limits of detection that are found in control experiments where it is replaced with horseradish peroxidase (HRP), its natural counterpart. This study represents a significant proof-of-concept for the development of more sensitive LFiAs, for different analytes, based on properly designed artificial metalloenzymes.

Empagliflozin Improves the MicroRNA Signature of Endothelial Dysfunction in Patients with Heart Failure with Preserved Ejection Fraction and Diabetes.

Endothelial dysfunction represents a key mechanism underlying heart failure with preserved ejection fraction (HFpEF), diabetes mellitus (DM), and frailty. However, reliable biomarkers to monitor endothelial dysfunction in these patients are lacking. In this study, we evaluated the expression of a panel of circulating microRNAs (miRs) involved in the regulation of endothelial function in a population of frail older adults with HFpEF and DM treated for 3 months with empagliflozin, metformin, or insulin. We identified a distinctive pattern of miRs that were significantly regulated in HFpEF patients compared to healthy controls and to HFpEF patients treated with the sodium glucose cotransporter 2 (SGLT2) inhibitor empagliflozin. Three miRs were significantly downregulated (miR-126, miR-342-3p, and miR-638) and two were significantly upregulated (miR-21 and miR-92) in HFpEF patients compared to healthy controls. Strikingly, two of these miRs (miR-21 and miR-92) were significantly reduced in HFpEF patients after the 3-month treatment with empagliflozin, whereas no significant differences in the profile of endothelial miRs were detected in patients treated with metformin or insulin. Taken together, our findings demonstrate for the first time that specific circulating miRs involved in the regulation of endothelial function are significantly regulated in frail HFpEF patients with DM and in response to SGLT2 inhibition. SIGNIFICANCE STATEMENT: We have identified a novel microRNA signature functionally involved in the regulation of endothelial function that is significantly regulated in frail patients with HFpEF and diabetes. Moreover, the treatment with the SGLT2 inhibitor empagliflozin caused a modification of some of these microRNAs in a direction that was opposite to what observed in HFpEF patients, indicating a rescue of endothelial function. Our findings are relevant for clinical practice inasmuch as we were able to establish novel biomarkers of disease and response to therapy.

Beneficial effects of L-Arginine in patients hospitalized for COVID-19: New insights from a randomized clinical trial.

We have recently demonstrated in a double-blind randomized trial the beneficial effects of L-Arginine in patients hospitalized for COVID-19. We hypothesize that one of the mechanisms underlying the favorable effects of L-Arginine is its action on inflammatory cytokines. To verify our hypothesis, we measured longitudinal plasma levels of pro-inflammatory and anti-inflammatory cytokines implied in the pathophysiology of COVID-19 in patients randomized to receive oral L-Arginine or placebo. The study was successfully completed by 169 patients. Patients in the L-Arginine arm had a reduced respiratory support evaluated at 10 and 20 days; moreover, the time to hospital discharge was significantly shorter in the L-Arginine group. The assessment of circulating cytokines revealed that L-Arginine significantly reduced the circulating levels of pro-inflammatory IL-2, IL-6, and IFN-γ and increased the levels of the anti-inflammatory IL-10. Taken together, these findings indicate that adding L-Arginine to standard therapy in COVID-19 patients markedly reduces the need of respiratory support and the duration of in-hospital stay; moreover, L-Arginine significantly regulates circulating levels of pro-inflammatory and anti-inflammatory cytokines.

Allosteric cooperation in a de novo-designed two-domain protein.

We describe the de novo design of an allosterically regulated protein, which comprises two tightly coupled domains. One domain is based on the DF (Due Ferri in Italian or two-iron in English) family of de novo proteins, which have a diiron cofactor that catalyzes a phenol oxidase reaction, while the second domain is based on PS1 (Porphyrin-binding Sequence), which binds a synthetic Zn-porphyrin (ZnP). The binding of ZnP to the original PS1 protein induces changes in structure and dynamics, which we expected to influence the catalytic rate of a fused DF domain when appropriately coupled. Both DF and PS1 are four-helix bundles, but they have distinct bundle architectures. To achieve tight coupling between the domains, they were connected by four helical linkers using a computational method to discover the most designable connections capable of spanning the two architectures. The resulting protein, DFP1 (Due Ferri Porphyrin), bound the two cofactors in the expected manner. The crystal structure of fully reconstituted DFP1 was also in excellent agreement with the design, and it showed the ZnP cofactor bound over 12 Å from the dimetal center. Next, a substrate-binding cleft leading to the diiron center was introduced into DFP1. The resulting protein acts as an allosterically modulated phenol oxidase. Its Michaelis-Menten parameters were strongly affected by the binding of ZnP, resulting in a fourfold tighter Km and a 7-fold decrease in kcat These studies establish the feasibility of designing allosterically regulated catalytic proteins, entirely from scratch.

Natural, Designed and Engineered Metalloenzymes: Structure, Catalytic Mechanisms and Applications.

Bioinorganic chemists have become engaged in the challenge of elucidating the molecular mechanisms that govern how protein scaffolds modulate the properties of metal cofactors [...].

Enzymatic and Bioinspired Systems for Hydrogen Production.

The extraordinary potential of hydrogen as a clean and sustainable fuel has sparked the interest of the scientific community to find environmentally friendly methods for its production. Biological catalysts are the most attractive solution, as they usually operate under mild conditions and do not produce carbon-containing byproducts. Hydrogenases promote reversible proton reduction to hydrogen in a variety of anoxic bacteria and algae, displaying unparallel catalytic performances. Attempts to use these sophisticated enzymes in scalable hydrogen production have been hampered by limitations associated with their production and stability. Inspired by nature, significant efforts have been made in the development of artificial systems able to promote the hydrogen evolution reaction, via either electrochemical or light-driven catalysis. Starting from small-molecule coordination compounds, peptide- and protein-based architectures have been constructed around the catalytic center with the aim of reproducing hydrogenase function into robust, efficient, and cost-effective catalysts. In this review, we first provide an overview of the structural and functional properties of hydrogenases, along with their integration in devices for hydrogen and energy production. Then, we describe the most recent advances in the development of homogeneous hydrogen evolution catalysts envisioned to mimic hydrogenases.

Selective Oxidation of Halophenols Catalyzed by an Artificial Miniaturized Peroxidase.

The development of artificial enzymes for application in sustainable technologies, such as the transformation of environmental pollutants or biomass, is one of the most challenging goals in metalloenzyme design. In this work, we describe the oxidation of mono-, di-, tri- and penta-halogenated phenols catalyzed by the artificial metalloenzyme Fe-MC6*a. It promoted the dehalogenation of 4-fluorophenol into the corresponding 1,4-benzoquinone, while under the same experimental conditions, 4-chloro, 4-bromo and 4-iodophenol were selectively converted into higher molecular weight compounds. Analysis of the 4-chlorophenol oxidation products clarified that oligomers based on C-O bonds were exclusively formed in this case. All results show that Fe-MC6*a holds intriguing enzymatic properties, as it catalyzes halophenol oxidation with substrate-dependent chemoselectivity.

Dye Decolorization by a Miniaturized Peroxidase Fe-MimochromeVI*a.

Oxidases and peroxidases have found application in the field of chlorine-free organic dye degradation in the paper, toothpaste, and detergent industries. Nevertheless, their widespread use is somehow hindered because of their cost, availability, and batch-to-batch reproducibility. Here, we report the catalytic proficiency of a miniaturized synthetic peroxidase, Fe-Mimochrome VI*a, in the decolorization of four organic dyes, as representatives of either the heterocyclic or triarylmethane class of dyes. Fe-Mimochrome VI*a performed over 130 turnovers in less than five minutes in an aqueous buffer at a neutral pH under mild conditions.

A De Novo-Designed Type 3 Copper Protein Tunes Catechol Substrate Recognition and Reactivity.

De novo metalloprotein design is a remarkable approach to shape protein scaffolds toward specific functions. Here, we report the design and characterization of Due Rame 1 (DR1), a de novo designed protein housing a di-copper site and mimicking the Type 3 (T3) copper-containing polyphenol oxidases (PPOs). To achieve this goal, we hierarchically designed the first and the second di-metal coordination spheres to engineer the di-copper site into a simple four-helix bundle scaffold. Spectroscopic, thermodynamic, and functional characterization revealed that DR1 recapitulates the T3 copper site, supporting different copper redox states, and being active in the O2 -dependent oxidation of catechols to o-quinones. Careful design of the residues lining the substrate access site endows DR1 with substrate recognition, as revealed by Hammet analysis and computational studies on substituted catechols. This study represents a premier example in the construction of a functional T3 copper site into a designed four-helix bundle protein.

Mitochondria as playmakers of apoptosis, autophagy and senescence.

Mitochondria are the key energy-producing organelles and cellular source of reactive species. They are responsible for managing cell life and death by a balanced homeostasis passing through a network of structures, regulated principally via fission and fusion. Herein we discuss about the most advanced findings considering mitochondria as dynamic biophysical systems playing compelling roles in the regulation of energy metabolism in both physiologic and pathologic processes controlling cell death and survival. Precisely, we focus on the mitochondrial commitment to the onset, maintenance and counteraction of apoptosis, autophagy and senescence in the bioenergetic reprogramming of cancer cells. In this context, looking for a pharmacological manipulation of cell death processes as a successful route for future targeted therapies, there is major biotechnological challenge in underlining the location, function and molecular mechanism of mitochondrial proteins. Based on the critical role of mitochondrial functions for cellular health, a better knowledge of the main molecular players in mitochondria disfunction could be decisive for the therapeutical control of degenerative diseases, including cancer.

Diabetes and restenosis.

Restenosis, defined as the re-narrowing of an arterial lumen after revascularization, represents an increasingly important issue in clinical practice. Indeed, as the number of stent placements has risen to an estimate that exceeds 3 million annually worldwide, revascularization procedures have become much more common. Several investigators have demonstrated that vessels in patients with diabetes mellitus have an increased risk restenosis. Here we present a systematic overview of the effects of diabetes on in-stent restenosis. Current classification and updated epidemiology of restenosis are discussed, alongside the main mechanisms underlying the pathophysiology of this event. Then, we summarize the clinical presentation of restenosis, emphasizing the importance of glycemic control in diabetic patients. Indeed, in diabetic patients who underwent revascularization procedures a proper glycemic control remains imperative.

Correlation of physical and cognitive impairment in diabetic and hypertensive frail older adults.

BACKGROUND: Diabetes and hypertension are common in older adults and represent established risk factors for frailty. Frailty is a multidimensional condition due to reserve loss and susceptibility to stressors with a high risk of death, hospitalizations, functional and cognitive impairment. Comorbidities such as diabetes and hypertension play a key role in increasing the risk of mortality, hospitalization, and disability. Moreover, frail patients with diabetes and hypertension are known to have an increased risk of cognitive and physical impairment. Nevertheless, no study assessed the correlation between physical and cognitive impairment in frail older adults with diabetes and hypertension. METHODS: We evaluated consecutive frail older patients with diabetes and hypertension who presented at ASL (local health unit of the Italian Ministry of Health) Avellino, Italy, from March 2021 to October 2021. The inclusion criteria were: a previous diagnosis of diabetes and hypertension with no evidence of secondary causes; age > 65 years; a frailty status; Montreal Cognitive Assessment (MoCA) score < 26. RESULTS: 179 patients successfully completed the study. We found a strong and significant correlation between MoCA score and 5-m gait speed test (r: 0.877; p < 0.001). To further verify our results, we performed a linear multivariate analysis adjusting for potential confounding factors, with MoCA score as dependent variable, which confirmed the significant association with glycemia (p < 0.001). CONCLUSIONS: This is the first study showing a significant correlation between 5-m gait speed test and MoCA score in frail diabetic and hypertensive older adults.

Omega-3 fatty acids coordinate glucose and lipid metabolism in diabetic patients.

Omega 3 polyunsaturated fatty acids (n-3 PUFA) are known to have beneficial effects on cardiovascular and metabolic health. However, whether different sources of n-3 PUFA, for instance fatty fish vs vegetable oils, could elicit different effects on glucose and lipid metabolism, remains to be determined. Herein we examine recent findings showing that while a plant-based n-3 PUFA supplementation for six months can reduce fasting blood glucose, marine-based n-3 PUFA can instead reduce serum levels of triglycerides. We also discuss the potential molecular mechanisms that could underlie these different effects on the regulation of glycolipid metabolism.

A Proteomic Approach Reveals That miR-423-5p Modulates Glucidic and Amino Acid Metabolism in Prostate Cancer Cells.

Recently, we have demonstrated that miR-423-5p modulates the growth and metastases of prostate cancer (PCa) cells both in vitro and in vivo. Here, we have studied the effects of miR-423-5p on the proteomic profile in order to identify its intracellular targets and the affected pathways. Applying a quantitative proteomic approach, we analyzed the effects on the protein expression profile of miR-423-5p-transduced PCa cells. Moreover, a computational analysis of predicted targets of miR-423-5p was carried out by using several target prediction tools. Proteomic analysis showed that 63 proteins were differentially expressed in miR-423-5-p-transfected LNCaP cells if compared to controls. Pathway enrichment analysis revealed that stable overexpression of miR-423-5p in LNCaP PCa cells induced inhibition of glycolysis and the metabolism of several amino acids and a parallel downregulation of proteins involved in transcription and hypoxia, the immune response through Th17-derived cytokines, inflammation via amphorin signaling, and ion transport. Moreover, upregulated proteins were related to the S phase of cell cycle, chromatin modifications, apoptosis, blood coagulation, and calcium transport. We identified seven proteins commonly represented in miR-423-5p targets and differentially expressed proteins (DEPs) and analyzed their expression and influence on the survival of PCa patients from publicly accessible datasets. Overall, our findings suggest that miR-423-5p induces alterations in glucose and amino acid metabolism in PCa cells paralleled by modulation of several tumor-associated processes.

Predicting brain age with complex networks: From adolescence to adulthood.

In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brain scans (in the age range 7-64years). We introduce a structural connectivity model of the human brain: MRI scans are divided in rectangular boxes and Pearson's correlation is measured among them in order to obtain a complex network model. Brain connectivity is then characterized through few and easy-to-interpret centrality measures; finally, brain age is predicted by feeding a compact deep neural network. The proposed approach is accurate, robust and computationally efficient, despite the large and heterogeneous dataset used. Age prediction accuracy, in terms of correlation between predicted and actual age r=0.89and Mean Absolute Error MAE =2.19years, compares favorably with results from state-of-the-art approaches. On an independent test set including 262 subjects, whose scans were acquired with different scanners and protocols we found MAE =2.52. The only imaging analysis steps required in the proposed framework are brain extraction and linear registration, hence robust results are obtained with a low computational cost. In addition, the network model provides a novel insight on aging patterns within the brain and specific information about anatomical districts displaying relevant changes with aging.