Carotid artery atherosclerosis: mechanisms of instability and clinical implications.

Cardiovascular disease remains a prominent cause of disability and premature death worldwide. Within this spectrum, carotid artery atherosclerosis is a complex and multifaceted condition, and a prominent precursor of acute ischaemic stroke and other cardiovascular events. The intricate interplay among inflammation, oxidative stress, endothelial dysfunction, lipid metabolism, and immune responses participates in the development of lesions, leading to luminal stenosis and potential plaque instability.

An Artificial Intelligence-Based Non-Invasive Approach for Cardiovascular Disease Risk Stratification in Obstructive Sleep Apnea Patients: A Narrative Review.

Background: Obstructive sleep apnea (OSA) is a severe condition associated with numerous cardiovascular complications, including heart failure. The complex biological and morphological relationship between OSA and atherosclerotic cardiovascular disease (ASCVD) poses challenges in predicting adverse cardiovascular outcomes. While artificial intelligence (AI) has shown potential for predicting cardiovascular disease (CVD) and stroke risks in other conditions, there is a lack of detailed, bias-free, and compressed AI models for ASCVD and stroke risk stratification in OSA patients.

"Artificial histology" in colonic Neoplasia: A critical approach.

Background: The histological assessment of colorectal precancer and cancer lesions is challenging and primarily impacts the clinical strategies of secondary colon cancer prevention. Artificial intelligence (AI) models may potentially assist in the histological diagnosis of this spectrum of phenotypical changes.

Objectives: To provide a current overview of the evidence on AI-based methods for histologically assessing colonic precancer and cancer lesions.

Reproducibility and explainability in digital pathology: The need to make black-box artificial intelligence systems more transparent.

Artificial intelligence (AI), and more specifically Machine Learning (ML) and Deep learning (DL), has permeated the digital pathology field in recent years, with many algorithms successfully applied as new advanced tools to analyze pathological tissues. The introduction of high-resolution scanners in histopathology services has represented a real revolution for pathologists, allowing the analysis of digital whole-slide images (WSI) on a screen without a microscope at hand. However, it means a transition from microscope to algorithms in the absence of specific training for most pathologists involved in clinical practice.

An Unsupervised Learning Tool for Plaque Tissue Characterization in Histopathological Images.

Stroke is the second leading cause of death and a major cause of disability around the world, and the development of atherosclerotic plaques in the carotid arteries is generally considered the leading cause of severe cerebrovascular events. In recent years, new reports have reinforced the role of an accurate histopathological analysis of carotid plaques to perform the stratification of affected patients and proceed to the correct prevention of complications. This work proposes applying an unsupervised learning approach to analyze complex whole-slide images (WSIs) of atherosclerotic carotid plaques to allow a simple and fast examination of their most relevant features.

Combined High-Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and Classifies Metabolic, Immune, Signaling and ECM Intra-Tumor Heterogeneity of Colorectal Cancer.

Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming and epithelial-mesenchymal transition (EMT) were investigated with explorative shotgun proteomics complemented by a Random Forest (RF) machine-learning approach. Deep and superficial tumor regions and distant-site non-tumor samples from the same patients (n = 16) were analyzed.

Artificial Intelligence Models for the Detection of Microsatellite Instability from Whole-Slide Imaging of Colorectal Cancer.

With the advent of whole-slide imaging (WSI), a technology that can digitally scan whole slides in high resolution, pathology is undergoing a digital revolution. Detecting microsatellite instability (MSI) in colorectal cancer is crucial for proper treatment, as it identifies patients responsible for immunotherapy. Even though universal testing for MSI is recommended, particularly in patients affected by colorectal cancer (CRC), many patients remain untested, and they reside mainly in low-income countries.

Thymosin β and β Expression in Human Organs during Development: A Review.

This review summarizes the results of a series of studies performed by our group with the aim to define the expression levels of thymosin β and thymosin β over time, starting from fetal development to different ages after birth, in different human organs and tissues. The first section describes the proteomics investigations performed on whole saliva from preterm newborns and gingival crevicular fluid, which revealed to us the importance of these acidic peptides and their multiple functions. These findings inspired us to start an in-depth investigation mainly based on immunochemistry to establish the distribution of thymosin β and thymosin β in different organs from adults and fetuses at different ages (after autopsy), and therefore to obtain suggestions on the functions of β-thymosins in health and disease.

The Role of Copper Overload in Modulating Neuropsychiatric Symptoms.

Copper is a transition metal essential for growth and development and indispensable for eukaryotic life. This metal is essential to neuronal function: its deficiency, as well as its overload have been associated with multiple neurodegenerative disorders such as Alzheimer's disease and Wilson's disease and psychiatric conditions such as schizophrenia, bipolar disorder, and major depressive disorders. Copper plays a fundamental role in the development and function of the human Central Nervous System (CNS), being a cofactor of multiple enzymes that play a key role in physiology during development.

Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping review.

Background: The field of precision medicine endeavors to transform the healthcare industry by advancing individualised strategies for diagnosis, treatment modalities, and predictive assessments. This is achieved by utilizing extensive multidimensional biological datasets encompassing diverse components, such as an individual's genetic makeup, functional attributes, and environmental influences. Artificial intelligence (AI) systems, namely machine learning (ML) and deep learning (DL), have exhibited remarkable efficacy in predicting the potential occurrence of specific cancers and cardiovascular diseases (CVD).

How to improve epidemiological trustworthiness concerning abdominal aortic aneurysms.

Background: Research on degenerative abdominal aortic aneurysms (AAA) is hampered by complex pathophysiology, sub-optimal pre-clinical models, and lack of effective medical therapies. In addition, trustworthiness of existing epidemiological data is impaired by elements of ambiguity, inaccuracy, and inconsistency. Our aim is to foster debate concerning the trustworthiness of AAA epidemiological data and to discuss potential solutions.

Assisted Reproductive Technologies: A New Player in the Foetal Programming of Childhood and Adult Diseases?

Assisted reproductive technology (ART) is an emerging field in medicine that incorporates complex procedures and has profound ethical, moral, social, religious, and economic implications not just for the individuals who have access to this method but also for society. In this narrative review, we summarise multiple aspects of ART procedures and the possible consequences on the mother and newborn. Moreover, we provide an overview of the possible long-term consequences of ART procedures on the health of newborns, although longitudinal evidence is particularly scant.

Lessons from autopsy: Topographical variability of atherosclerosis plaques.

Atherosclerosis is a complex disease characterized by the accumulation of plaques in arterial walls. Understanding its pathogenesis remains incomplete, with factors like inflammation, oxidative stress, and hypertension playing critical roles. The disease exhibits preferential localization of plaques, with variability observed even within the same individual.

CD44: A New Prognostic Marker in Colorectal Cancer?

Cluster of differentiation 44 (CD44) is a non-kinase cell surface glycoprotein. It is overexpressed in several cell types, including cancer stem cells (CSCs). Cells overexpressing CD44 exhibit several CSC traits, such as self-renewal, epithelial-mesenchymal transition (EMT) capability, and resistance to chemo- and radiotherapy.

Prediction of Response to Anti-Angiogenic Treatment for Advanced Colorectal Cancer Patients: From Biological Factors to Functional Imaging.

Colorectal cancer (CRC) is a leading tumor worldwide. In CRC, the angiogenic pathway plays a crucial role in cancer development and the process of metastasis. Thus, anti-angiogenic drugs represent a milestone for metastatic CRC (mCRC) treatment and lead to significant improvement of clinical outcomes.

Autoimmune liver disease triggered by SARS-CoV-2: a case report and review of the literature.

Background: An increasing number of coronavirus disease 2019 (COVID-19) related autoimmune hepatitis (AIH) and autoimmune liver disease (AILD) has been already described so far in the last three years. This rise has set up some diagnostic and therapeutic concerns, although steroid therapy has mostly been efficient, avoiding main significant side effects.

Case Report: We report the case of a 52-year-old subject displaying liver function impairment at the laboratory tests while positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) swab.

The fascinating theory of fetal programming of adult diseases: A review of the fundamentals of the Barker hypothesis.

The theory of fetal programming of adult diseases was first proposed by David J.P. Barker in the eighties of the previous century, to explain the higher susceptibility of some people toward the development of ischemic heart disease.

Coronary Artery Calcification: Current Concepts and Clinical Implications.

Coronary artery calcification (CAC) accompanies the development of advanced atherosclerosis. Its role in atherosclerosis holds great interest because the presence and burden of coronary calcification provide direct evidence of the presence and extent of coronary artery disease; furthermore, CAC predicts future events independently of concomitant conventional cardiovascular risk factors and to a greater extent than any other noninvasive biomarker of this disease. Nevertheless, the relationship between CAC and the susceptibility of a plaque to provoke a thrombotic event remains incompletely understood.

Carotid Plaque-RADS: A Novel Stroke Risk Classification System.

Background: Carotid artery atherosclerosis is highly prevalent in the general population and is a well-established risk factor for acute ischemic stroke. Although the morphological characteristics of vulnerable plaques are well recognized, there is a lack of consensus in reporting and interpreting carotid plaque features.

Objectives: The aim of this paper is to establish a consistent and comprehensive approach for imaging and reporting carotid plaque by introducing the Plaque-RADS (Reporting and Data System) score.

Human breast milk cells are positive for the pioneer transcription factor ISL1.

Objective: ISL1 is a pioneer transcription factor that plays important roles in cell lineage specification and differentiation, by programming the epigenome and recruiting additional regulatory factors. The aim of this study is to determine whether the human breastmilk contains ISL1-positive stem cells, and, if so, to describe the subcellular localization of ISL1.

Materials And Methods: Breast milk was obtained from fourteen healthy females during the first 2-6 months of lactation.

Mismatch Repair system protein deficiency as a resistance factor for locally advanced rectal adenocarcinoma patients receiving neoadjuvant chemo-radiotherapy.

Background: Available data on Mismatch Repair system (MMR) deficiency are conflicting and derived from small studies. Our study aimed to evaluate the therapeutic implications of MMR status in patients with locally advanced rectal cancer (LARC).

Methods: We retrospectively collected data from 318 patients affected by LARC treated in Italy at the Medical Oncology Units of the University Hospital of Cagliari, Istituto Nazionale dei Tumori Milan, and AOU Ospedali Riuniti Ancona.

Artificial intelligence-based preventive, personalized and precision medicine for cardiovascular disease/stroke risk assessment in rheumatoid arthritis patients: a narrative review.

The challenges associated with diagnosing and treating cardiovascular disease (CVD)/Stroke in Rheumatoid arthritis (RA) arise from the delayed onset of symptoms. Existing clinical risk scores are inadequate in predicting cardiac events, and conventional risk factors alone do not accurately classify many individuals at risk. Several CVD biomarkers consider the multiple pathways involved in the development of atherosclerosis, which is the primary cause of CVD/Stroke in RA.

Combined Salivary Proteome Profiling and Machine Learning Analysis Provides Insight into Molecular Signature for Autoimmune Liver Diseases Classification.

Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The acid-insoluble salivary fraction of AIH and PBC patients, and healthy controls (HCs), was analyzed using a gel-based bottom-up proteomic approach combined with a robust machine learning statistical analysis of the dataset.