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Background: Fibro-calcific aortic valve disease (FCAVD) is a progressive disorder characterized by the thickening and calcification of the aortic valve, eventually leading to aortic stenosis. Adiponectin and leptin, known for their anti-inflammatory and proinflammatory properties, respectively, have been implicated in cardiovascular diseases, but their associations with FCAVD are controversial. This meta-analysis aims to evaluate the relationships between adiponectin and leptin levels and FCAVD, particularly in patients with severe aortic stenosis (AS). Methods: A systematic search was conducted across the PubMed, Scopus, and Web of Science databases to identify studies on adiponectin and leptin levels in FCAVD. The methodological quality of each study was assessed using the Newcastle–Ottawa Scale. Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were calculated, and publication bias was evaluated using Egger’s test and funnel plots. Results: Out of 191 articles identified, 10 studies involving 2360 patients (989 with FCAVD and 1371 controls) were included. The analysis suggested trends in the associations of lower adiponectin levels (SMD = −0.143, 95% CI: −0.344, 0.057, p = 0.161) and higher leptin levels (SMD = 0.175, 95% CI: −0.045, 0.395, p = 0.119) with FCAVD. The association remained a trend for low adiponectin but showed a significant correlation with high leptin in severe AS patients (SMD = 0.29, 95% CI: 0.036, 0.543, p = 0.025). Conclusion: This meta-analysis indicates a potential association between elevated leptin levels and severe aortic stenosis, while the relationship with adiponectin levels remains inconclusive. These findings highlight the need for further and dedicated research to clarify the roles of these adipokines in the pathogenesis of FCAVD and their potential roles as biomarkers for disease progression.

Neurodegenerative disorders are the main cause of cognitive and physical disabilities, affect millions of people worldwide, and their incidence is on the rise. Emerging evidence pinpoints a disturbance of the communication of the gut–brain axis, and in particular to gut microbial dysbiosis, as one of the contributors to the pathogenesis of these diseases. In fact, dysbiosis has been associated with neuro-inflammatory processes, hyperactivation of the neuronal immune system, impaired cognitive functions, aging, depression, sleeping disorders, and anxiety. With the rapid advance in metagenomics, metabolomics, and big data analysis, together with a multidisciplinary approach, a new horizon has just emerged in the fields of translational neurodegenerative disease. In fact, recent studies focusing on taxonomic profiling and leaky gut in the pathogenesis of neurodegenerative disorders are not only shedding light on an overlooked field but are also creating opportunities for biomarker discovery and development of new therapeutic and adjuvant strategies to treat these disorders. Lactiplantibacillus plantarum (LBP) strains are emerging as promising psychobiotics for the treatment of these diseases. In fact, LBP strains are able to promote eubiosis, increase the enrichment of bacteria producing beneficial metabolites such as short-chain fatty acids, boost the production of neurotransmitters, and support the homeostasis of the gut–brain axis. In this review, we summarize the current knowledge on the role of the gut microbiota in the pathogenesis of neurodegenerative disorders with a particular focus on the benefits of LBP strains in Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, autism, anxiety, and depression.

Recent years have ushered in a transformative era in in vitro modeling with the advent of organoids, three-dimensional structures derived from stem cells or patient tumor cells. Still, fully harnessing the potential of organoids requires advanced imaging technologies and analytical tools to quantitatively monitor organoid growth. Optical coherence tomography (OCT) is a promising imaging modality for organoid analysis due to its high-resolution, label-free, non-destructive, and real-time 3D imaging capabilities, but accurately identifying and quantifying organoids in OCT images remain challenging due to various factors. Here, we propose an automatic deep learning-based pipeline with convolutional neural networks that synergistically includes optimized preprocessing steps, the implementation of a state-of-the-art deep learning model, and ad-hoc postprocessing methods, showcasing good generalizability and tracking capabilities over an extended period of 13 days. The proposed tracking algorithm thoroughly documents organoid evolution, utilizing reference volumes, a dual branch analysis, key attribute evaluation, and probability scoring for match identification. The proposed comprehensive approach enables the accurate tracking of organoid growth and morphological changes over time, advancing organoid analysis and serving as a solid foundation for future studies for drug screening and tumor drug sensitivity detection based on organoids.

Despite the availability of vaccines and antivirals and the biological evolution of SARS-CoV-2, the rate of hospitalizations and deaths from COVID-19 remains high in Italy. It is crucial to understand whether and how the clinical characteristics of patients hospitalized for COVID-19 have changed over 2021–2022 and which risk factors are currently associated with adverse outcomes to develop targeted interventions. In this study, we present and compare the characteristics and outcomes of 310 patients with COVID-19 who were hospitalized between 1 August and 9 December 2021, when the Delta SARS-CoV-2 variant was prevalent (Group A), and between 3 January and 30 June 2022, when the Omicron variant was predominant (Group B). Using Survival Analysis, we estimated the cumulative 28-day hazard ratio (H.R.) of Intensive Care Unit (ICU) admission/death of patients in Group B vs. A. We built uni- and multivariate Cox regression models for the overall population and each group to identify risk factors for ICU admission/death among patient features. We found that Group B had a comparable risk of ICU admission/death (HR 1.60, 95% Confidence Interval, C.I. 1.00–2.58, p = 0.05) but a higher prevalence of elderly and co-morbid subjects than Group A. Non-invasive ventilation requirement was associated with adverse outcomes in both Group A (HR 21.03, 95% C.I. 5.34–82.80, p < 0.001) and Group B (HR 4.53, 95% C.I. 2.39–8.59, p < 0.001), as well as in the overall population (HR 3.88, 95% C.I. 2.49–6.06, p < 0.001). During the Omicron wave, elderly and co-morbid subjects had the highest risk of hospitalization and poor outcomes.

Two (consecutive) reductions of the complete Gatenby–Gawlinski model for cancer invasion are proposed in order to investigate the mathematical framework, mainly from a computational perspective. After a brief overview of the full model, we proceed by examining the case of a two-equations-based and one-equation-based reduction, both obtained by means of a quasi-steady-state assumption. We focus on invasion fronts, exploiting a numerical strategy based on a finite volume approximation, and perform corresponding computational simulations to study the sharpness/smoothness of the traveling waves. Then, we employ a space-averaged wave speed estimate—referred to as the LeVeque–Yee formula—to quantitatively approach the propagation phenomenon. Concerning the one-equation-based model, we propose a scalar degenerate reaction-diffusion equation, which proves to be effective in order to qualitatively recover the typical trends arising from the Gatenby–Gawlinski model. Finally, we carry out some numerical tests in a specific case where the analytical solution is available.

The rapid growth of drone use in urban areas has prompted authorities to review airspace regulations, forcing drone manufacturers to anticipate and reduce the noise emissions during the design stage. Additionally, micro air vehicles (MAVs) are designed to be aerodynamically efficient, allowing them to fly farther, longer and safer. In this study, a steady aerodynamic code and an acoustic propagator based on the non-linear vortex lattice method (NVLM) and Farassat’s formulation-1A of the Ffowcs Williams and Hawkings (FW-H) acoustic analogy, respectively, are coupled with pymoo, a python-based optimization framework. This tool is used to perform a multi-objective (noise and aerodynamic efficiency) optimization of a 20 cm diameter two-bladed rotor under hovering conditions. From the set of optimized results, (i.e., the Pareto front), three different rotors are 3D-printed using a stereolithography (SLA) technique and tested in an anechoic room. Here, an array of far-field microphones captures the acoustic radiation and directivity of the rotor, while a balance measures the aerodynamic performance. Both the aerodynamic and aeroacoustic performance of the three different rotors, in line with what has been predicted by the numerical codes, are compared and guidelines for the design of aerodynamically and aeroacoustically efficient MAV rotors are extracted.

Background. Gastrointestinal (GI) cancers are one of the most relevant causes of death globally, frequently associated with poor dietary patterns. The Mediterranean Diet (MedDiet) contributes to cancer prevention. To assess adherence to MedDiet, our research group validated a new score, the Chrono Med Diet Score (CMDS), that captures increased visceral adiposity. Methods. We enrolled 401 subjects who underwent an evaluation for metabolic diseases and specific screening procedures according to current guidelines and were asked to answer CMDS. A total of 71 new cancer cases were recorded, including 40 GI and 31 non-gastrointestinal (NON-GI) cancers. Results. We found that CMDS was reduced in subjects who were diagnosed with cancers. Patients who reported a CMDS score of 12 or less had an over three times increased risk of being diagnosed with GI cancers and presented increased waist circumference and triglycerides and reduced HDL cholesterol compared to adherent subjects. Conclusions. Low CMDS values capture the risk for cancer diagnosis, especially for GI cancers. Thus, CMDS, along with waist circumference, can be considered as a bona fide marker for increased risk of cancer, requiring anticipated screening procedures for the detection of premalignant and early stage GI cancers in patients with low adherence to MedDiet.

Type 2 diabetes mellitus (T2DM) is a prevalent and complex metabolic disorder associated with various complications, including cardiovascular diseases. Sodium-glucose co-transporter 2 inhibitors (SGLT2i) and glucagon-like peptide 1 receptor agonists (GLP1-RA) have emerged as novel therapeutic agents for T2DM, primarily aiming to reduce blood glucose levels. However, recent investigations have unveiled their multifaceted effects, extending beyond their glucose-lowering effect. SGLT2i operate by inhibiting the SGLT2 receptor in the kidneys, facilitating the excretion of glucose through urine, leading to reduced blood glucose levels, while GLP1-RA mimic the action of the GLP1 hormone, stimulating glucose-dependent insulin secretion from pancreatic islets. Both SGLT2i and GLP1-RA have shown remarkable benefits in reducing major cardiovascular events in patients with and without T2DM. This comprehensive review explores the expanding horizons of SGLT2i and GLP1-RA in improving cardiovascular health. It delves into the latest research, highlighting the effects of these drugs on heart physiology and metabolism. By elucidating their diverse mechanisms of action and emerging evidence, this review aims to recapitulate the potential of SGLT2i and GLP1-RA as therapeutic options for cardiovascular health beyond their traditional role in managing T2DM.

Statistical analysis of the properties of single microparticles, such as cells, bacteria or plastic slivers, has attracted increasing interest in recent years. In this regard, field flow cytometry is considered the gold standard technique, but commercially available instruments are bulky, expensive, and not suitable for use in point-of-care (PoC) testing. Microfluidic flow cytometers, on the other hand, are small, cheap and can be used for on-site analyses. However, in order to detect small particles, they require complex geometries and the aid of external optical components. To overcome these limitations, here, we present an opto-fluidic flow cytometer with an integrated 3D in-plane spherical mirror for enhanced optical signal collection. As a result, the signal-to-noise ratio is increased by a factor of six, enabling the detection of particle sizes down to 1.5 µm. The proposed optofluidic detection scheme enables the simultaneous collection of particle fluorescence and scattering using a single optical fiber, which is crucial to easily distinguishing particle populations with different optical properties. The devices have been fully characterized using fluorescent polystyrene beads of different sizes. As a proof of concept for potential real-world applications, signals from fluorescent HEK cells and Escherichia coli bacteria were analyzed.

Background: E-commerce’s convenience, speed, and ability to overcome geographical barriers have made it increasingly popular across industries. This study analyzed the impact of the COVID-19 pandemic on customer experience and satisfaction in supermarket retail e-commerce in the Brazilian market. The objective was to understand how the pandemic influenced satisfaction in this sector. Methods: A survey research method was employed, utilizing the Critical Incident Technique to identify key quality dimensions important to customers. A total of 133 valid responses underwent exploratory factor analysis. Results: Data analysis identified three dimensions significantly affecting overall customer satisfaction. “Presentation of Products in the Application (app)” had the highest correlation, while “Delivery Logistics” had the lowest. However, when considering the COVID-19 factor, “Delivery Logistics” showed the highest correlation. This indicates that the dimension most affected by the pandemic has the least impact on overall satisfaction in supermarket e-commerce. Conclusions: The study emphasizes the significance of understanding customer satisfaction in supermarket e-commerce, not just during the COVID-19 pandemic but also its post-pandemic consequences. Retailers should prioritize improving product presentation in apps, as it greatly influences overall satisfaction. Addressing the pandemic’s impact on delivery logistics is also crucial to ensure competitiveness in the e-commerce market.

Non-genetic photostimulation, which allows for control over cellular activity via the use of cell-targeting phototransducers, is widely used nowadays to study and modulate/restore biological functions. This approach relies on non-covalent interactions between the phototransducer and the cell membrane, thus implying that cell conditions and membrane status can dictate the effectiveness of the method. For instance, although immortalized cell lines are traditionally used in photostimulation experiments, it has been demonstrated that the number of passages they undergo is correlated to the worsening of cell conditions. In principle, this could impact cell responsivity against exogenous stressors, including photostimulation. However, these aspects have usually been neglected in previous experiments. In this work, we investigated whether cell passages could affect membrane properties (such as polarity and fluidity). We applied optical spectroscopy and electrophysiological measurements in two different biological models: (i) an epithelial immortalized cell line (HEK-293T cells) and (ii) liposomes. Different numbers of cell passages were compared to a different morphology in the liposome membrane. We demonstrated that cell membranes show a significant decrease in ordered domains upon increasing the passage number. Furthermore, we observed that cell responsivity against external stressors is markedly different between aged and non-aged cells. Firstly, we noted that the thermal-disordering effect that is usually observed in membranes is more evident in aged cells than in non-aged ones. We then set up a photostimulation experiment by using a membrane-targeted azobenzene as a phototransducer (Ziapin2). As an example of a functional consequence of such a condition, we showed that the rate of isomerization of an intramembrane molecular transducer is significantly impaired in aged cells. The reduction in the photoisomerization rate translates in cells with a sustained reduction of the Ziapin2-related hyperpolarization of the membrane potential and an overall increase in the molecule fluorescence. Overall, our results suggest that membrane stimulation strongly depends on membrane order, highlighting the importance of cell passage during the characterization of the stimulation tools. This study can shine light on the correlation between aging and the development of diseases driven by membrane degradation as well as on the different cell responsivities against external stressors, such as temperature and photostimulation.

Background: Antimicrobial and diagnostic stewardship (AS/DS) principles are crucial for the management of multidrug-resistant organisms (MDROs) infections. We evaluated the impact of a pro-active Infectious Disease (ID) consultation on the mortality risk of patients during an MDROs outbreak in a COVID-19 hospital. Methods: A quasi-experimental study was performed in a dedicated COVID-19 hospital, including patients with suspected/confirmed infection and/or colonization by MDROs, which were managed as follows: (i) according to the standard of care during the pre-phase and (ii) in collaboration with a dedicated ID team performing a pro-active bedside evaluation every 48–72 h in the post-phase. Results: Overall, 112 patients were included (pre-phase = 89 and post-phase = 45). The AS interventions included the following: therapy optimization (33%), de-escalation to narrow the spectrum (24%) or to lessen toxic drugs (20%), and discontinuation of antimicrobials (64%). DS included the request of additional microbiologic tests (82%) and instrumental exams (16%). With the Cox model, after adjusting for age, sex, COVID-19 severity, infection source, etiological agents, and post-phase attendance, only age predicted an increased risk of mortality, while attendance in the post-phase resulted in a decreased risk of mortality. Conclusions: Implementation of AS and DS intervention through a pro-active ID consultation may reduce the risk of 28-day mortality of COVID-19 patients with MDROs infections.

Adherence to the Mediterranean diet (MedDiet) leads to reduction of mortality from all causes, especially in subjects with cardiovascular disease, obesity, and diabetes. Numerous scores have been proposed to evaluate the adherence to MedDiet, mainly focused on eating habits. In this study, we verified whether existing validated MedDiet scores, namely, MEDI-LITE and the Mediterranean Diet Score (MDS), could be associated with visceral adiposity. Failing to find a significant association with adiposity, we proposed the validation of a new, easy-to-use adherence questionnaire, the Chrono Med-Diet score (CMDS). CMDS contains eleven food categories, including chronobiology of dietary habits and physical activity. Compared to the MEDI-LITE score and MDS, low values of CMDS are linked to increased waist circumference (WC) and dysmetabolic conditions. CMDS was also inversely correlated with cardiovascular risk (CVR), as well as Fatty Liver Index (FLI). In conclusion, the CMDS is a novel questionnaire to study the adherence to the MedDiet that, focusing on type and timing of carbohydrates intake, has the peculiar capability of capturing subjects with abdominal obesity, thus being an easy-to-use instrument of personalized medicine.

In heart failure, the biological and clinical connection between abnormal iron homeostasis, myocardial function, and prognosis is known; however, the expression profiles of iron-linked genes both at myocardial tissue and single-cell level are not well defined. Through publicly available bulk and single-nucleus RNA sequencing (RNA-seq) datasets of left ventricle samples from adult non-failed (NF) and dilated cardiomyopathy (DCM) subjects, we aim to evaluate the altered iron metabolism in a diseased condition, at the whole cardiac tissue and single-cell level. From the bulk RNA-seq data, we found 223 iron-linked genes expressed at the myocardial tissue level and 44 differentially expressed between DCM and NF subjects. At the single-cell level, at least 18 iron-linked expressed genes were significantly regulated in DCM when compared to NF subjects. Specifically, the iron metabolism in DCM cardiomyocytes is altered at several levels, including: (1) imbalance of Fe3+ internalization (SCARA5 down-regulation) and reduction of internal conversion from Fe3+ to Fe2+ (STEAP3 down-regulation), (2) increase of iron consumption to produce hemoglobin (HBA1/2 up-regulation), (3) higher heme synthesis and externalization (ALAS2 and ABCG2 up-regulation), (4) lower cleavage of heme to Fe2+, biliverdin and carbon monoxide (HMOX2 down-regulation), and (5) positive regulation of hepcidin (BMP6 up-regulation).

Bile acid (BA) species and the gut microbiota (GM) contribute to intestinal mucosa homeostasis. BAs shape the GM and, conversely, intestinal bacteria with bile salt hydrolase (BSH) activity modulate the BA pool composition. The mutual interaction between BAs and intestinal microorganisms also influences mucosal barrier integrity, which is important for inflammatory bowel disease (IBD) pathogenesis, prevention and therapy. High levels of secondary BAs are detrimental for the intestinal barrier and increase the intestinal inflammatory response and dysbiosis. Additionally, a lack of BSH-active bacteria plays a role in intestinal inflammation and BA dysmetabolism. Thus, BSH-competent bacteria in probiotic formulations are being actively studied in IBD. At the same time, studies exploring the modulation of the master regulator of BA homeostasis, the Farnesoid X Receptor (FXR), in intestinal inflammation and how this impacts the GM are gaining significant momentum. Overall, the choice of probiotic supplementation should be a peculiar issue of personalized medicine, considering not only the disease but also the specific BA and metabolic signatures of a given patient.

Atherosclerosis is a common cause of cardiovascular disease, which, in turn, is often fatal. Today, we know a lot about the pathogenesis of atherosclerosis. However, the main knowledge is that the disease is extremely complicated. The development of atherosclerosis is associated with more than one molecular mechanism, each making a significant contribution. These mechanisms include endothelial dysfunction, inflammation, mitochondrial dysfunction, oxidative stress, and lipid metabolism disorders. This complexity inevitably leads to difficulties in treatment and prevention. One of the possible therapeutic options for atherosclerosis and its consequences may be metformin, which has already proven itself in the treatment of diabetes. Both diabetes and atherosclerosis are complex metabolic diseases, the pathogenesis of which involves many different mechanisms, including those common to both diseases. This makes metformin a suitable candidate for investigating its efficacy in cardiovascular disease. In this review, we highlight aspects such as the mechanisms of action and targets of metformin, in addition to summarizing the available data from clinical trials on the effective reduction of cardiovascular risks.

Computer-aided diagnosis (CAD) systems can help radiologists in numerous medical tasks including classification and staging of the various diseases. The 3D tomosynthesis imaging technique adds value to the CAD systems in diagnosis and classification of the breast lesions. Several convolutional neural network (CNN) architectures have been proposed to classify the lesion shapes to the respective classes using a similar imaging method. However, not only is the black box nature of these CNN models questionable in the healthcare domain, but so is the morphological-based cancer classification, concerning the clinicians. As a result, this study proposes both a mathematically and visually explainable deep-learning-driven multiclass shape-based classification framework for the tomosynthesis breast lesion images. In this study, authors exploit eight pretrained CNN architectures for the classification task on the previously extracted regions of interests images containing the lesions. Additionally, the study also unleashes the black box nature of the deep learning models using two well-known perceptive explainable artificial intelligence (XAI) algorithms including Grad-CAM and LIME. Moreover, two mathematical-structure-based interpretability techniques, i.e., t-SNE and UMAP, are employed to investigate the pretrained models’ behavior towards multiclass feature clustering. The experimental results of the classification task validate the applicability of the proposed framework by yielding the mean area under the curve of 98.2%. The explanability study validates the applicability of all employed methods, mainly emphasizing the pros and cons of both Grad-CAM and LIME methods that can provide useful insights towards explainable CAD systems.

Circulating microRNAs (miRNA) have been proposed as specific biomarkers for several diseases. Quantitative Real-Time PCR (RT-qPCR) is the gold standard technique currently used to evaluate miRNAs expression from different sources. In the last few years, digital PCR (dPCR) emerged as a complementary and accurate detection method. When dealing with gene expression, the first and most delicate step is nucleic-acid isolation. However, all currently available protocols for RNA extraction suffer from the variable loss of RNA species due to the chemicals and number of steps involved, from sample lysis to nucleic acid elution. Here, we evaluated a new process for the detection of circulating miRNAs, consisting of sample lysis followed by direct evaluation by dPCR in plasma from healthy donors and in the cardiovascular setting. Our results showed that dPCR is able to detect, with high accuracy, low-copy-number as well as highly expressed miRNAs in human plasma samples without the need for RNA extraction. Moreover, we assessed a known myocardial infarction-related miR-133a in acute myocardial infarct patients vs. healthy subjects. In conclusion, our results show the suitability of the extraction-free quantification of circulating miRNAs as disease markers by direct dPCR.

The metabolic syndrome (MetS) is a cluster of cardiovascular risk factors characterised by central obesity, atherogenic dyslipidaemia, and changes in the circulating lipidome; the underlying mechanisms that lead to this lipid remodelling have only been partially elucidated. This study used an integrated “omics” approach (untargeted whole serum lipidomics, targeted proteomics, and lipoprotein lipidomics) to study lipoprotein remodelling and HDL composition in subjects with central obesity diagnosed with MetS (vs. controls). Compared with healthy subjects, MetS patients showed higher free fatty acids, diglycerides, phosphatidylcholines, and triglycerides, particularly those enriched in products of de novo lipogenesis. On the other hand, the “lysophosphatidylcholines to phosphatidylcholines” and “cholesteryl ester to free cholesterol” ratios were reduced, pointing to a lower activity of lecithin cholesterol acyltransferase (LCAT) in MetS; LCAT activity (directly measured and predicted by lipidomic ratios) was positively correlated with high-density lipoprotein cholesterol (HDL-C) and negatively correlated with body mass index (BMI) and insulin resistance. Moreover, many phosphatidylcholines and sphingomyelins were significantly lower in the HDL of MetS patients and strongly correlated with BMI and clinical metabolic parameters. These results suggest that MetS is associated with an impairment of phospholipid metabolism in HDL, partially led by LCAT, and associated with obesity and underlying insulin resistance. This study proposes a candidate strategy to use integrated “omics” approaches to gain mechanistic insights into lipoprotein remodelling, thus deepening the knowledge regarding the molecular basis of the association between MetS and atherosclerosis.

The ability to identify ovarian cancer (OC) at its earliest stages remains a challenge. The patients present an advanced stage at diagnosis. This heterogeneous disease has distinguishable etiology and molecular biology. Next-generation sequencing changed clinical diagnostic testing, allowing assessment of multiple genes, simultaneously, in a faster and cheaper manner than sequential single gene analysis. Technologies of proteomics, such as mass spectrometry (MS) and protein array analysis, have advanced the dissection of the underlying molecular signaling events and the proteomic characterization of OC. Proteomics analysis of OC, as well as their adaptive responses to therapy, can uncover new therapeutic choices, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is an urgent need to better understand how the genomic and epigenomic heterogeneity intrinsic to OC is reflected at the protein level, and how this information could potentially lead to prolonged survival.

On 12 March 2020, the World Health Organization (WHO) declared the novel Coronavirus (CoV) disease a global Pandemic and an emerging risk. In order to understand patterns that are typical in COVID-19 pneumonia and track the evolution of the disease, the role of the chest computed tomography (CT) is pivotal. The impact of the illness as well as the efficiency of the therapy are also monitored carefully when performing this imaging exam. Coronaviruses, specifically CoV-2, as RNA viruses, have a tendency to frequently change their genome, giving the virus beneficial characteristics such as greater transmissibility, pathogenicity and the possibility to escape the previously acquired immunity. Therefore, genome evaluation became an extremely important routine practice worldwide. In particular, in Italy, four variants have been recognised and each of them represent a specific temporal wave of the disease. Hence, our goal was to describe imaging findings of COVID-19 pneumonia, specifically its most typical imaging identified during the period of our study, and to assess whether or not SARS-CoV-2 variants determine different CT patterns. Our analyses revealed that the SARS-CoV-2 genotype seems not to interfere with the severity of CT patterns and, in particular, bilateral Ground Glass Opacities (GGOs) are the most frequent findings in all COVID-19 waves.

Rationale—Calcific aortic valve stenosis (CAVS) is a pathological condition of the aortic valve with a prevalence of 3% in the general population. It is characterized by massive rearrangement of the extracellular matrix, mostly due to the accumulation of fibro-calcific deposits driven by valve interstitial cells (VIC), and no pharmacological treatment is currently available. The aim of this study was to evaluate the effects of P2Y2 receptor (P2RY2) activation on fibro-calcific remodeling of CAVS. Methods—We employed human primary VICs isolated from CAVS leaflets treated with 2-thiouridine-5′-triphosphate (2ThioUTP, 10 µM), an agonist of P2RY2. The calcification was induced by inorganic phosphate (2 mM) and ascorbic acid (50 µg/mL) for 7 or 14 days, while the 2ThioUTP was administered starting from the seventh day. 2ThioUTP was chronically administered for 5 days to evaluate myofibroblastic activation. Results—P2RY2 activation, under continuous or interrupted pro-calcific stimuli, led to a significant inhibition of VIC calcification potential (p < 0.01). Moreover, 2ThioUTP treatment was able to significantly reduce pro-fibrotic gene expression (p < 0.05), as well as that of protein α-smooth muscle actin (p = 0.004). Conclusions—Our data suggest that P2RY2 activation should be further investigated as a pharmacological target for the prevention of CAVS progression, acting on both calcification and myofibroblastic activation.

Vitamin D deficiency is often linked with Metabolic Syndrome, both being more frequent with ageing and associated with an increase inflammatory state. Recently, monocytes-to-high density lipoprotein (HDL) ratio (MHR) has emerged as a powerful index to predict systemic inflammation. In this cross-sectional study, we investigated the association between circulating vitamin D level (25-OH vitamin D) and inflammatory status in a population of 1048 adult individuals. Our study reveals an inverse association between 25-OH vitamin D levels and MHR in the overall population. When the population is stratified by gender, waist circumference, and body mass index (BMI), we observed that while in men this relation is strongly significative only in condition of central obesity, in women a lifelong negative correlation exists between circulating 25-OH vitamin D and MHR and it is independent of the metabolic status. These observations underscore the relevance of circulating biomarkers such as MHR in the prediction of systemic inflammatory conditions sustained by vitamin D deficiency also in healthy and young women.

Emerging anticancer agents such as the pan-FGFR Inhibitor have achieved remarkable improvements in the survival of patients with metastatic malignancies. Nevertheless they are still associated with specific ophthalmic toxicities. Understanding their pathophysiology can lead us to better clinical practice of life-threatening and vision-threatening circumstances. To investigate choroidal alterations as a potential pathophysiological mechanism of a serous detachment in bilateral pan-FGFR Inhibitor-Associated Retinopathy (FGFRAR), the morphology of the choroid and choriocapillaris were assessed. The choroidal thickness (ChT) and choriocapillaris flow void were measured by macular optical coherence tomography (OCT) and angiography (OCT-A), respectively. Data were collected at the baseline, then at one-month and two-months follow-ups after starting erdafitinib, in a single case of pulmonary angiosarcoma. Choroidal and choriocapillaris morphology showed stable ChT and choriocapillaris flow void at FGFRAR onset and relapse. To the best of our knowledge, this is the first analyzed case reported with flow-void OCT-angiography. Considering these results, FGFRAR in this patient does not seem to match the pachychoroid spectrum disorder definition; rather, an intracellular mechanism based on intracellular transduction pathways may be at work.

Breast cancer is the most prevalent tumor type among women and female dogs. Tumor malignancy is characterized by the epithelial-to-mesenchymal transition (EMT) which leads to the metastasis formation. The inhibition of angiotensin II type I receptor (AGTR1) by an antagonist such as losartan can suppress angiogenesis, consequently contributing to the metastasis control. The aim of this study was to analyze the capacity of losartan and AGTR-1 gene edition to modulate the EMT process in triple negative/metastatic mammary tumor cells, compared to existing treatment protocols such as carboplatin. The cell lines CF41.Mg and MDA-MB-468, were cultured and treated with carboplatin, losartan, or submitted to AGTR-1 gene edition by CRISPR/Cas9. EMT markers and PARP-1 protein and gene expression were evaluated by immunofluorescence or immunocytochemistry and qRT-PCR, respectively. Cell migration capacity was also evaluated. For CF41.Mg and MDA-MB-468 cell lines, there was an increase in E-cadherin and a decrease in N-cadherin and PARP-1 protein and gene expression after treatment with carboplatin, losartan, both in combination and after AGTR-1 gene edition. There was a decrease in VEGF and PARP-1 protein and gene expression after AGTR-1 gene edition. Moreover, in both lines, reduction in invasion rate was observed after all treatments. Our data suggest that losartan and the gene edition of AGTR-1 by CRISPR/Cas9 were able to block the DNA repair and control the EMT process, such as carboplatin. The results in the canine species are unprecedented, as there are no data in the literature that demonstrate the action of losartan in this tumor type.

Prostate cancer (PC) is the second most common cancer in men worldwide. Due to the large-scale sequencing efforts, there is currently a better understanding of the genomic landscape of PC. The identification of defects in DNA repair genes has led to clinical studies that provide a strong rationale for developing poly (ADP-ribose) polymerase (PARP) inhibitors and DNA-damaging agents in this molecularly defined subset of patients. The identification of molecularly defined subgroups of patients has also other clinical implications; for example, we now know that carriers of breast cancer 2 (BRCA2) pathogenic sequence variants (PSVs) have increased levels of serum prostate specific antigen (PSA) at diagnosis, increased proportion of high Gleason tumors, elevated rates of nodal and distant metastases, and high recurrence rate; BRCA2 PSVs confer lower overall survival (OS). Distinct tumor PSV, methylation, and expression patterns have been identified in BRCA2 compared with non-BRCA2 mutant prostate tumors. Several DNA damage response and repair (DDR)-targeting agents are currently being evaluated either as single agents or in combination in patients with PC. In this review article, we highlight the biology and clinical implications of deleterious inherited or acquired DNA repair pathway aberrations in PC and offer an overview of new agents being developed for the treatment of PC.

Prostate cancer (PC) is the most common cancer in men and the second leading cause of cancer-related death worldwide. Many therapeutic advances over the last two decades have led to an improvement in the survival of patients with metastatic PC, yet the majority of these patients still succumb to their disease. Antiagiogenic therapies have shown substantial benefits for many types of cancer but only a marginal benefit for PC. Ongoing clinical trials investigate antiangiogenic monotherapies or combination therapies. Despite the important role of angiogenesis in PC, clinical trials in refractory castration-resistant PC (CRPC) have demonstrated increased toxicity with no clinical benefit. A better understanding of the mechanism of angiogenesis may help to understand the failure of trials, possibly leading to the development of new targeted anti-angiogenic therapies in PC. These could include the identification of specific subsets of patients who might benefit from these therapeutic strategies. This paper provides a comprehensive review of the pathways involved in the angiogenesis, the chemotherapeutic agents with antiangiogenic activity, the available studies on anti-angiogenic agents and the potential mechanisms of resistance.

Diabetes mellitus (DM) is one of the most common and costly disorders that affect humans around the world. Recently, clinicians and scientists have focused their studies on the effects of glycemic variability (GV), which is especially associated with cardiovascular diseases. In healthy subjects, glycemia is a very stable parameter, while in poorly controlled DM patients, it oscillates greatly throughout the day and between days. Clinically, GV could be measured by different parameters, but there are no guidelines on standardized assessment. Nonetheless, DM patients with high GV experience worse cardiovascular disease outcomes. In vitro and in vivo studies showed that high GV causes several detrimental effects, such as increased oxidative stress, inflammation, and apoptosis linked to endothelial dysfunction. However, the evidence that treating GV is beneficial is still scanty. Clinical trials aiming to improve the diagnostic and prognostic accuracy of GV measurements correlated with cardiovascular outcomes are needed. The present review aims to evaluate the clinical link between high GV and cardiovascular diseases, taking into account the underlined biological mechanisms. A clear view of this challenge may be useful to standardize the clinical evaluation and to better identify treatments and strategies to counteract this DM aspect.

Ovarian cancer (OC) is the second most common gynecological malignancy, accounting for about 14,000 deaths in 2020 in the US. The recognition of tools for proper screening, early diagnosis, and prognosis of OC is still lagging. The application of methods such as radiomics to medical images such as ultrasound scan (US), computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET) in OC may help to realize so-called “precision medicine” by developing new quantification metrics linking qualitative and/or quantitative data imaging to achieve clinical diagnostic endpoints. This narrative review aims to summarize the applications of radiomics as a support in the management of a complex pathology such as ovarian cancer. We give an insight into the current evidence on radiomics applied to different imaging methods.

The use of biomarkers in medicine has become essential in clinical practice in order to help with diagnosis, prognostication and prediction of treatment response. Since Alexander Breslow’s original report on “melanoma and prognostic values of thickness”, providing the first biomarker for melanoma, many promising new biomarkers have followed. These include serum markers, such as lactate dehydrogenase and S100 calcium-binding protein B. However, as our understanding of the DNA mutational profile progresses, new gene targets and proteins have been identified. These include point mutations, such as mutations of the BRAF gene and tumour suppressor gene tP53. At present, only a small number of the available biomarkers are being utilised, but this may soon change as more studies are published. The aim of this article is to provide a comprehensive review of melanoma biomarkers and their utility for current and, potentially, future clinical practice.

Transcript sequencing is a crucial tool for gaining a deep understanding of biological processes in diagnostic and clinical medicine. Given their potential to study novel complex eukaryotic transcriptomes, long-read sequencing technologies are able to overcome some limitations of short-read RNA-Seq approaches. Oxford Nanopore Technologies (ONT) offers the ability to generate long-read sequencing data in real time via portable protein nanopore USB devices. This work aimed to provide the user with the number of reads that should be sequenced, through the ONT MinION platform, to reach the desired accuracy level for a human cell RNA study. We sequenced three cDNA libraries prepared from poly-adenosine RNA of human primary cardiac fibroblasts. Since the runs were comparable, they were combined in a total dataset of 48 million reads. Synthetic datasets with different sizes were generated starting from the total and analyzed in terms of the number of identified genes and their expression levels. As expected, an improved sensitivity was obtained, increasing the sequencing depth, particularly for the non-coding genes. The reliability of expression levels was assayed by (i) comparison with PCR quantifications of selected genes and (ii) by the implementation of a user-friendly multiplexing method in a single run.

The prevalence of being overweight and obese has been expanded dramatically in recent years worldwide. Obesity usually occurs when the energetic introit overtakes energy expenditure from metabolic and physical activity, leading to fat accumulation mainly in the visceral depots. Excessive fat accumulation represents a risk factor for many chronic diseases, including cancer. Adiposity, chronic low-grade inflammation, and hyperinsulinemia are essential factors of obesity that also play a crucial role in tumor onset. In recent years, several strategies have been pointed toward boundary fat accumulation, thus limiting the burden of cancer attributable to obesity. While remodeling fat via adipocytes browning seems a tempting prospect, lifestyle interventions still represent the main pathway to prevent cancer and enhance the efficacy of treatments. Specifically, the Mediterranean Diet stands out as one of the best dietary approaches to curtail visceral adiposity and, therefore, cancer risk. In this Review, the close relationship between obesity and cancer has been investigated, highlighting the biological mechanisms at the basis of this link. Finally, strategies to remodel fat, including browning and lifestyle interventions, have been taken into consideration as a major perspective to limit excess body weight and tumor onset.

Extra virgin olive oil (EVOO) represents one of the most important health-promoting foods whose antioxidant and anti-inflammatory activities are mainly associated to its polyphenols content. To date, studies exploring the effect of EVOO polyphenols on dendritic cells (DCs), acting as a crosstalk between the innate and the adaptive immune response, are scanty. Therefore, we studied the ability of three EVOO extracts (cv. Coratina, Cima di Mola/Coratina, and Casaliva), characterized by different polyphenols amount, to regulate DCs maturation in resting conditions or after an inflammatory stimulus. Cima di Mola/Coratina and Casaliva extracts were demonstrated to be the most effective in modulating DCs toward an anti-inflammatory profile by reduction of TNF and IL-6 secretion and CD86 expression, along with a down-modulation of Il-1β and iNOS expression. From factorial analysis results, 9 polyphenols were tentatively established to play a synergistic role in modulating DCs inflammatory ability, thus reducing the risk of chronic inflammation.

Parkinson’s disease is one of the most common neurodegenerative disorders worldwide, characterized by a progressive loss of dopaminergic neurons mainly localized in the substantia nigra pars compacta. In recent years, the detailed analyses of both genetic and idiopathic forms of the disease have led to a better understanding of the molecular and cellular pathways involved in PD, pointing to the centrality of mitochondrial dysfunctions in the pathogenic process. Failure of mitochondrial quality control is now considered a hallmark of the disease. The peroxisome proliferator-activated receptor gamma coactivator 1 (PGC-1) family acts as a master regulator of mitochondrial biogenesis. Therefore, keeping PGC-1 level in a proper range is fundamental to guarantee functional neurons. Here we review the major findings that tightly bond PD and PGC-1s, raising important points that might lead to future investigations.

Mitral valve prolapse (MVP) associated with severe mitral regurgitation is a debilitating disease with no pharmacological therapies available. MicroRNAs (miRNA) represent an emerging class of circulating biomarkers that have never been evaluated in MVP human plasma. Our aim was to identify a possible miRNA signature that is able to discriminate MVP patients from healthy subjects (CTRL) and to shed light on the putative altered molecular pathways in MVP. We evaluated a plasma miRNA profile using Human MicroRNA Card A followed by real-time PCR validations. In addition, to assess the discriminative power of selected miRNAs, we implemented a machine learning analysis. MiRNA profiling and validations revealed that miR-140-3p, 150-5p, 210-3p, 451a, and 487a-3p were significantly upregulated in MVP, while miR-223-3p, 323a-3p, 340-5p, and 361-5p were significantly downregulated in MVP compared to CTRL (p ≤ 0.01). Functional analysis identified several biological processes possible linked to MVP. In addition, machine learning analysis correctly classified MVP patients from CTRL with high accuracy (0.93) and an area under the receiving operator characteristic curve (AUC) of 0.97. To the best of our knowledge, this is the first study performed on human plasma, showing a strong association between miRNAs and MVP. Thus, a circulating molecular signature could be used as a first-line, fast, and cheap screening tool for MVP identification.

Despite several studies having identified factors associated with successful treatment outcomes in locally advanced cervical cancer, there is the lack of accurate predictive modeling for progression-free survival (PFS) in patients who undergo radical hysterectomy after neoadjuvant chemotherapy (NACT). Here we investigated whether machine learning (ML) may have the potential to provide a tool to predict neoadjuvant treatment response as PFS. In this retrospective observational study, we analyzed patients with locally advanced cervical cancer (FIGO stages IB2, IB3, IIA1, IIA2, IIB, and IIIC1) who were followed in a tertiary center from 2010 to 2018. Demographic and clinical characteristics were collected at either treatment baseline or at 24-month follow-up. Furthermore, we recorded data about magnetic resonance imaging (MRI) examinations and post-surgery histopathology. Proper feature selection was used to determine an attribute core set. Three different machine learning algorithms, namely Logistic Regression (LR), Random Forest (RFF), and K-nearest neighbors (KNN), were then trained and validated with 10-fold cross-validation to predict 24-month PFS. Our analysis included n. 92 patients. The attribute core set used to train machine learning algorithms included the presence/absence of fornix infiltration at pre-treatment MRI as well as of either parametrium invasion and lymph nodes involvement at post-surgery histopathology. RFF showed the best performance (accuracy 82.4%, precision 83.4%, recall 96.2%, area under receiver operating characteristic curve (AUROC) 0.82). We developed an accurate ML model to predict 24-month PFS.

Contrast-Enhanced Spectral Mammography (CESM) is a recently introduced mammographic method with characteristics particularly suitable for breast cancer radiomic analysis. This work aims to evaluate radiomic features for predicting histological outcome and two cancer molecular subtypes, namely Human Epidermal growth factor Receptor 2 (HER2)-positive and triple-negative. From 52 patients, 68 lesions were identified and confirmed on histological examination. Radiomic analysis was performed on regions of interest (ROIs) selected from both low-energy (LE) and ReCombined (RC) CESM images. Fourteen statistical features were extracted from each ROI. Expression of estrogen receptor (ER) was significantly correlated with variation coefficient and variation range calculated on both LE and RC images; progesterone receptor (PR) with skewness index calculated on LE images; and Ki67 with variation coefficient, variation range, entropy and relative smoothness indices calculated on RC images. HER2 was significantly associated with relative smoothness calculated on LE images, and grading tumor with variation coefficient, entropy and relative smoothness calculated on RC images. Encouraging results for differentiation between ER+/ER−, PR+/PR−, HER2+/HER2−, Ki67+/Ki67−, High-Grade/Low-Grade and TN/NTN were obtained. Specifically, the highest performances were obtained for discriminating HER2+/HER2− (90.87%), ER+/ER− (83.79%) and Ki67+/Ki67− (84.80%). Our results suggest an interesting role for radiomics in CESM to predict histological outcomes and particular tumors’ molecular subtype.

Calcific aortic valve disease (CAVD) is the most common valvular heart disease in developed countries predominantly affecting the elderly population therefore posing a large economic burden. It is a gradually progressive condition ranging from mild valve calcification and thickening, without the hemodynamic obstruction, to severe calcification impairing leaflet motion, known as aortic stenosis (AS). The progression of CAVD occurs over many years, and it is extremely variable among individuals. It is also associated with an increased risk of coronary events and mortality. The recent insights into the CAVD pathophysiology included an important role of sex. Accumulating evidence suggests that, in patients with CAVD, sex can determine important differences in the relationship between valvular calcification process, fibrosis, and aortic stenosis hemodynamic severity between men and women. Consequently, it has implications on the development of different valvular phenotypes, left ventricular hypertrophy, and cardiovascular outcomes in men and women. Along these lines, taking into account the sex-related differences in diagnosis, prognosis, and treatment outcomes is of profound importance. In this review, the sex-related differences in patients with CAVD, in terms of pathobiology, clinical phenotypes, and outcomes were discussed.