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.

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).

Identification of Tissue miRNA Signatures for Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC), a neoplasm of the gastrointestinal tract, is the most common pancreatic malignancy (90%) and the fourth highest cause of cancer mortality worldwide. Surgery intervention is currently the only strategy able to offer an advantage in terms of overall survival, but prognosis remains poor even for operated patients. Therefore, the development of robust biomarkers for early diagnosis and prognostic stratification in clinical practice is urgently needed. In this work, we investigated deregulated microRNAs (miRNAs) in tissues from PDAC patients with high (G3) or low (G2) histological grade and with (N+) or without (N-) lymph node metastases. miRNA expression profiling was performed by a comprehensive PCR array and subsequent validation by RT-qPCR. The results showed a significant increase in miR-1-3p, miR-31-5p, and miR-205-5p expression in G3 compared to G2 patients (** p < 0.01; *** p < 0.001; *** p < 0.001). miR-518d-3p upregulation and miR-215-5p downregulation were observed in N+ compared to N- patients. A statistical analysis performed using OncomiR program showed the significant involvement (p < 0.05) of two miRNAs (miR-31 and miR-205) in the histological grade of PDAC patients. Also, an expression analysis in PDAC patients showed that miR-31 and miR-205 had the highest expression at grade 3 compared with normal and other tumor grades. Overall, survival plots confirmed that the overexpression of miR-31 and miR-205 was significantly correlated with decreased survival in TCGA PDAC clinical samples. A KEGG pathway analysis showed that all three miRNAs are involved in the regulation of multiple pathways, including the Hippo signaling, adherens junction and microRNAs in cancer, along with several target genes. Based on in silico analysis and experimental validation, our study suggests the potential role of miR-1-3p, miR-31-5p, and miR-205-5p as useful clinical biomarkers and putative therapeutic targets in PDAC, which should be further investigated to determine the specific molecular processes affected by their aberrant expression.

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.

A human-interpretable machine learning pipeline based on ultrasound to support leiomyosarcoma diagnosis.

The preoperative evaluation of myometrial tumors is essential to avoid delayed treatment and to establish the appropriate surgical approach. Specifically, the differential diagnosis of leiomyosarcoma (LMS) is particularly challenging due to the overlapping of clinical, laboratory and ultrasound features between fibroids and LMS. In this work, we present a human-interpretable machine learning (ML) pipeline to support the preoperative differential diagnosis of LMS from leiomyomas, based on both clinical data and gynecological ultrasound assessment of 68 patients (8 with LMS diagnosis). The pipeline provides the following novel contributions: (i) end-users have been involved both in the definition of the ML tasks and in the evaluation of the overall approach; (ii) clinical specialists get a full understanding of both the decision-making mechanisms of the ML algorithms and the impact of the features on each automatic decision. Moreover, the proposed pipeline addresses some of the problems concerning both the imbalance of the two classes by analyzing and selecting the best combination of the synthetic oversampling strategy of the minority class and the classification algorithm among different choices, and the explainability of the features at global and local levels. The results show very high performance of the best strategy (AUC = 0.99, F1 = 0.87) and the strong and stable impact of two ultrasound-based features (i.e., tumor borders and consistency of the lesions). Furthermore, the SHAP algorithm was exploited to quantify the impact of the features at the local level and a specific module was developed to provide a template-based natural language (NL) translation of the explanations for enhancing their interpretability and fostering the use of ML in the clinical setting.

Incidence of type 2 diabetes before and during the COVID-19 pandemic in Naples, Italy: a longitudinal cohort study.

Background: The association of COVID-19 with the development of new-onset diabetes has been recently investigated by several groups, yielding controversial results. Population studies currently available in the literature are mostly focused on type 1 diabetes (T1D), comparing patients with a SARS-CoV-2 positive test to individuals without COVID-19, especially in paediatric populations. In this study, we sought to determine the incidence of type 2 diabetes (T2D) before and during the COVID-19 pandemic. Methods: In this longitudinal cohort study, we analysed a cohort followed up over a 6-year period using an Interrupted Time Series approach, i.e. 3-years before and 3-years during the COVID-19 pandemic. We analysed data obtained from >200,000 adults in Naples (Italy) from January 1st 2017 to December 31st 2022. In this manner, we had the opportunity to compare the incidence of newly diagnosed T2D before (2017-2019) and during (2020-2022) the COVID-19 pandemic. The key inclusion criteria were age >18-year-old and data availability for the period of observation; patients with a diagnosis of diabetes obtained before 2017 were excluded. The main outcome of the study was the new diagnosis of T2D, as defined by the International Classification of Diseases 10 (ICD-X), including prescription of antidiabetic therapies for more than 30 days. Findings: A total of 234,956 subjects were followed-up for at least 3-years before or 3-years during the COVID-19 pandemic and were included in the study; among these, 216,498 were analysed in the pre-pandemic years and 216,422 in the pandemic years. The incidence rate of T2D was 4.85 (95% CI, 4.68-5.02) per 1000 person-years in the period 2017-2019, vs 12.21 (95% CI, 11.94-12.48) per 1000 person-years in 2020-2022, with an increase of about twice and a half. Moreover, the doubling time of the number of new diagnoses of T2D estimated by unadjusted Poisson model was 97.12 (95% CI, 40.51-153.75) months in the prepandemic period vs 23.13 (95% CI, 16.02-41.59) months during the COVID-19 pandemic. Interestingly, these findings were also confirmed when examining patients with prediabetes. Interpretation: Our data from this 6-year study on more than 200,000 adult participants indicate that the incidence of T2D was significantly higher during the pandemic compared to the pre-COVID-19 phase. As a consequence, the epidemiology of the disease may change in terms of rates of outcomes as well as public health costs. COVID-19 survivors, especially patients with prediabetes, may require specific clinical programs to prevent T2D. Funding: The US National Institutes of Health (NIH: NIDDK, NHLBI, NCATS), Diabetes Action Research and Education Foundation, Weill-Caulier and Hirschl Trusts.

Ketone Bodies Rescue Mitochondrial Dysfunction Via Epigenetic Remodeling.

Ischemic cardiac disease is a major cause of mortality worldwide. However, the exact molecular processes underlying this disorder are not fully known. This study includes a comprehensive and coordinated set of in vivo and in vitro experiments using human cardiac specimens from patients with postischemic heart failure (HF) and healthy control subjects, a murine model of HF, and cellular systems. These approaches identified for the first time a specific pattern of maladaptive chromatin remodeling, namely a double methylation of histone 3 at lysine 27 and a single methylation at lysine 36 (H3_K27me2K36me1) consistently induced by ischemic injury in all these settings: human HF; murine HF; and in vitro models. Mechanistically, this work demonstrates that this histone modification mediates the ischemia-induced transcriptional repression of PPARG coactivator 1α (PGC1α), master regulator of mitochondrial function and biogenesis. Intriguingly, both the augmented H3_K27me2K36me1 and the mitochondrial dysfunction ensued by PGC1α down-regulation were significantly attenuated by the treatment with ß-hydroxybutyrate, the most abundant ketone body in humans, revealing a novel pathway coupling metabolism to gene expression. Taken together, these findings establish maladaptive chromatin remodeling as a key mechanism in postischemic heart injury, functionally modulated by ketone bodies.

Functional Role of Taurine in Aging and Cardiovascular Health: An Updated Overview.

Taurine, a naturally occurring sulfur-containing amino acid, has attracted significant attention in recent years due to its potential health benefits. Found in various foods and often used in energy drinks and supplements, taurine has been studied extensively to understand its impact on human physiology. Determining its exact functional roles represents a complex and multifaceted topic. We provide an overview of the scientific literature and present an analysis of the effects of taurine on various aspects of human health, focusing on aging and cardiovascular pathophysiology, but also including athletic performance, metabolic regulation, and neurological function. Additionally, our report summarizes the current recommendations for taurine intake and addresses potential safety concerns. Evidence from both human and animal studies indicates that taurine may have beneficial cardiovascular effects, including blood pressure regulation, improved cardiac fitness, and enhanced vascular health. Its mechanisms of action and antioxidant properties make it also an intriguing candidate for potential anti-aging strategies.

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 [...].

SGLT2 inhibitors: an evidence-based update on cardiovascular implications.

INTRODUCTION: Sodium Glucose co-Transporter 2 (SGLT2) inhibitors (also known as 'gliflozins') represent a cornerstone to treat diabetes mellitus. Moreover, recent randomized clinical trials have demonstrated important cardioprotective effects of gliflozins, independent of the presence of diabetes. Herein, we summarize the recent therapeutic progress in the cardiovascular field obtained with SGLT2 inhibitors. AREA COVERED: We critically examine the rationale and results of recent clinical studies examining the effects of SGLT2 inhibitors on cardiovascular outcomes, along with a brief overview of the main ongoing trials that have been designed in order to answer the many pending questions in the field of gliflozins and cardiovascular disease. EXPERT OPINION: The favorable results of several clinical trials have broadened the therapeutic scenario for SGLT2 inhibitors, opening, at the same time, new challenges. Additionally, recent preclinical findings have evidenced off-target effects of SGLT2 inhibitors.

Functional and Clinical Importance of SGLT2-inhibitors in Frailty: From the Kidney to the Heart.

SGLT2 (sodium-glucose cotransporter 2) enables glucose and sodium reabsorption in the kidney. SGLT2-inhibitors (also known as gliflozins, which include canagliflozin, dapagliflozin, empagliflozin, and ertugliflozin) act by increasing glycosuria, thereby reducing glycemia. These drugs are critical to reach and keep glycemic control, a crucial feature, especially in patients with comorbidities, like frail individuals. Several studies evaluated the effects of SGLT2-inhibitors in different settings beyond diabetes, revealing that they are actually pleiotropic drugs. We recently evidenced the favorable effects of SGLT2-inhibition on physical and cognitive impairment in frail older adults with diabetes and hypertension. In the present overview, we summarize the latest clinical and preclinical studies exploring the main effects of SGLT2-inhibitors on kidney and heart, emphasizing their potential beneficial actions in frailty.

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.

Fluorescent nanodiamonds as innovative delivery systems for MiR-34a replacement in breast cancer.

Nanodiamonds are innovative nanocrystalline carbon particles able to deliver chemically conjugated miRNAs. In oncology, the use of miRNA-based therapies may represent an advantage, based on their ability to simultaneously target multiple intracellular oncogenic targets. Here, nanodiamonds were tested and optimized to deliver miR-34a, a miRNA playing a key role in inhibiting tumor development and progression in many cancers. The physical-chemical properties of nanodiamonds were investigated suggesting electrical stability and uniformity of structure and size. Moreover, we evaluated nanodiamond cytotoxicity on two breast cancer cell models and confirmed their excellent biocompatibility. Subsequently, nanodiamonds were conjugated with miR-34a, using the chemical crosslinker polyethyleneimine; real-time PCR analysis revealed a higher level of miR-34a in cancer cells treated with the different formulations of nanodiamonds than with commercial transfectant. A significant and early nanodiamond-miR-34a uptake was recorded by FACS and fluorescence microscopy analysis in MCF7 and MDA-MB-231 cells. Moreover, nanodiamond-miR-34a significantly inhibited both cell proliferation and migration. Finally, a remarkable anti-tumor effect of miR-34a-conjugated nanodiamonds was observed in both heterotopic and orthotopic murine xenograft models. In conclusion, this study provides a rationale for the development of new therapeutic strategies based on use of miR-34a delivered by nanodiamonds to improve the clinical treatment of neoplasms.

Peptide-based metalloporphyrin catalysts: unveiling the role of the metal ion in indole oxidation.

Over the last decades, much effort has been devoted to the construction of protein and peptide-based metalloporphyrin catalysts capable of promoting difficult transformations with high selectivity. In this context, mechanistic studies are fundamental to elucidate all the factors that contribute to catalytic performances and product selectivity. In our previous work, we selected the synthetic peptide-porphyrin conjugate MnMC6*a as a proficient catalyst for indole oxidation, promoting the formation of a 3-oxindole derivative with unprecedented selectivity. In this work, we have evaluated the role of the metal ion in affecting reaction outcome, by replacing manganese with iron in the MC6*a scaffold. Even though product selectivity is not altered upon metal substitution, FeMC6*a shows a lower substrate conversion and prolonged reaction times with respect to its manganese analogue. Experimental and theoretical studies have enabled us to delineate the reaction free energy profiles for both catalysts, indicating different thermodynamic limiting steps, depending on the nature of the metal ion.

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.

Designed Rubredoxin miniature in a fully artificial electron chain triggered by visible light.

Designing metal sites into de novo proteins has significantly improved, recently. However, identifying the minimal coordination spheres, able to encompass the necessary information for metal binding and activity, still represents a great challenge, today. Here, we test our understanding with a benchmark, nevertheless difficult, case. We assemble into a miniature 28-residue protein, the quintessential elements required to fold properly around a FeCys4 redox center, and to function efficiently in electron-transfer. This study addresses a challenge in de novo protein design, as it reports the crystal structure of a designed tetra-thiolate metal-binding protein in sub-Å agreement with the intended design. This allows us to well correlate structure to spectroscopic and electrochemical properties. Given its high reduction potential compared to natural and designed FeCys4-containing proteins, we exploit it as terminal electron acceptor of a fully artificial chain triggered by visible light.

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.