Article
Clinical Neurology
Patrick H. Luckett, Charlie Chen, Brian A. Gordon, Julie Wisch, Sarah B. Berman, Jasmeer P. Chhatwal, Carlos Cruchaga, Anne M. Fagan, Martin R. Farlow, Nick C. Fox, Mathias Jucker, Johannes Levin, Colin L. Masters, Hiroshi Mori, James M. Noble, Stephen Salloway, Peter R. Schofield, Adam M. Brickman, William S. Brooks, David M. Cash, Michael J. Fulham, Bernardino Ghetti, Clifford R. Jack, Jonathan Voeglein, William E. Klunk, Robert Koeppe, Yi Su, Michael Weiner, Qing Wang, Daniel Marcus, Deborah Koudelis, Nelly Joseph-Mathurin, Lisa Cash, Russ Hornbeck, Chengjie Xiong, Richard J. Perrin, Celeste M. Karch, Jason Hassenstab, Eric McDade, John C. Morris, Tammie L. S. Benzinger, Randall J. Bateman, Beau M. Ances
Summary: This study analyzed 19 biomarkers of Alzheimer's disease using hierarchical clustering and feature selection, and found that amyloid and tau measures were the primary predictors. Emerging biomarkers of neuronal integrity and inflammation showed weaker predictive ability.
ALZHEIMERS & DEMENTIA
(2023)
Article
Clinical Neurology
Keyi Li, Runqiu Chi, Liangjie Liu, Mofan Feng, Kai Su, Xia Li, Guang He, Yi Shi
Summary: Alzheimer's disease (AD) is a neurodegenerative disease with no effective late-stage treatment, making early prediction crucial. Recent studies have shown that miRNAs, through epigenetic modifications such as DNA methylation, play an important role in neurodegenerative diseases, including AD. Thus, miRNAs may serve as excellent biomarkers in early AD prediction.
FRONTIERS IN NEUROLOGY
(2023)
Article
Geriatrics & Gerontology
Yongyan Pei, Sijia Chen, Fengling Zhou, Tao Xie, Hua Cao
Summary: This study aimed to identify mitophagy-related genes with diagnostic potential for Alzheimer's disease (AD) and establish a diagnostic model for AD. A total of 72 differentially expressed mitophagy-related genes were identified, with four genes identified as biomarkers. A diagnostic prediction model was constructed and its reliability was verified. The findings of this study have implications for the clinical management and mechanistic research of AD.
FRONTIERS IN AGING NEUROSCIENCE
(2023)
Article
Clinical Neurology
Yang Li, Zuolong Chen, Qiong Wang, Xinyi Lv, Zhaozhao Cheng, Yan Wu, Fang Tang, Yong Shen, Feng Gao
Summary: This study used bioinformatics methods to identify potential candidate hub proteins in cerebrospinal fluid for Alzheimer's disease diagnosis. These identified hub proteins, mainly involved in glycometabolism pathways, were upregulated in the cerebrospinal fluid of Alzheimer's disease patients compared to control individuals, and showed excellent discriminatory ability for Alzheimer's disease diagnosis. These hub proteins may serve as potential biomarkers for further research in Alzheimer's disease.
JOURNAL OF NEUROLOGY
(2023)
Article
Neurosciences
Daniella Castro Araujo, Adriano Alonso Veloso, Karina Braga Gomes, Leonardo Cruz de Souza, Nivio Ziviani, Paulo Caramelli
Summary: This study aimed to develop a machine learning-based blood panel to predict the risk of progression from mild cognitive impairment (MCI) to dementia due to Alzheimer's disease (AD). By using ADNI data, researchers created a panel composed of 12 plasma proteins and successfully predicted the risk of MCI patients converting to AD dementia within a four-year time frame.
JOURNAL OF ALZHEIMERS DISEASE
(2022)
Article
Mathematics
Georgiana Ingrid Stoleru, Adrian Iftene
Summary: Alzheimer's Disease is a prevalent condition that is often diagnosed late. Due to limitations in current diagnostic tools, developing an early predictive system based on Artificial Intelligence and identifying biomarkers are important research directions. This survey reviews the use of machine learning techniques for the detection of Alzheimer's Disease and Mild Cognitive Impairment, aiming to identify the most accurate and efficient diagnostic approaches.
Article
Biotechnology & Applied Microbiology
Abhibhav Sharma, Pinki Dey
Summary: A machine learning approach was used to explore genetic risk factors of Alzheimer's disease, revealing novel and highly predictive biomarkers.
Review
Biology
Mei Sze Tan, Phaik-Leng Cheah, Ai-Vyrn Chin, Lai-Meng Looi, Siow-Wee Chang
Summary: Alzheimer's Disease is a common neurodegenerative disease affecting cognition, with increasing incidence as the elderly population grows. Diagnosis is based on clinical criteria including patient history, physical examination, neuropsychological testing and appropriate investigations. Omics techniques may aid in diagnosis and exploration of disease development mechanisms.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Endocrinology & Metabolism
John D. Sluyter, Yoshihiko Raita, Kohei Hasegawa, Ian R. Reid, Robert Scragg, Carlos A. Camargo
Summary: Using machine learning models to predict vitamin D deficiency showed higher accuracy in predicting 25(OH)D <25 nmol/L compared to traditional models, suggesting a potential role for machine learning models in participant selection for vitamin D supplement trials.
JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM
(2022)
Article
Genetics & Heredity
Fan Zhang, Melissa Petersen, Leigh Johnson, James Hall, Sid E. O'Bryant
Summary: In this study, we investigated the improvement of prediction performance for Alzheimer's disease (AD) by combining serum and plasma biomarkers with feature selection. The results showed that the combined feature-selected serum-plasma biomarkers can better predict AD and have important clinical implications.
Review
Biochemistry & Molecular Biology
Serafettin Gunes, Yumi Aizawa, Takuma Sugashi, Masahiro Sugimoto, Pedro Pereira Rodrigues
Summary: Early diagnosis is crucial for delaying the onset of Alzheimer's disease, and current diagnostic methods are invasive and expensive, highlighting the need for more convenient and effective biomarkers. Studies have identified potential biomarkers, but further validation research is necessary.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Neurosciences
Huabin Zhao, Jiawei Wang, Zhongzheng Li, Shenghui Wang, Guoying Yu, Lan Wang
Summary: This study used bioinformatics techniques to explore the correlation between ferroptosis and Alzheimer's disease (AD) and identified 18 ferroptosis-related hub genes. A diagnostic model was established, and genes related to immune cell infiltration were discovered. MicroRNAs and drugs targeting ferroptosis were also identified.
FRONTIERS IN MOLECULAR NEUROSCIENCE
(2023)
Article
Geriatrics & Gerontology
Danmei Chen, Yunpeng Zhang, Rui Qiao, Xiangyu Kong, Hequan Zhong, Xiaokun Wang, Jie Zhu, Bing Li
Summary: This study identified synaptophysin (SYP) and regulator of G protein signaling 4 (RGS4) as potential diagnostic markers for Alzheimer's disease (AD) and demonstrated the involvement of immune cell infiltration in the development and progression of AD.
FRONTIERS IN AGING NEUROSCIENCE
(2022)
Article
Geriatrics & Gerontology
Yeojin Kim, Hyunju Lee
Summary: Researchers propose a pathway information-based neural network (PINNet) to predict Alzheimer's Disease (AD) patients and analyze blood and brain transcriptomic signatures using an interpretable deep learning model. PINNet incorporates pathway prior knowledge from databases and reveals essential pathways and genes for predicting AD. Experimental results demonstrate that PINNet performs well in predicting AD using blood and brain gene expressions, outperforming or being similar to deep learning models without pathway information. Pathway analysis reveals enriched pathways related to cell migration, PI3K-Akt signaling, MAPK signaling, apoptosis, protein ubiquitination, and T-cell activation.
FRONTIERS IN AGING NEUROSCIENCE
(2023)
Article
Engineering, Chemical
Giuseppe Murdaca, Sara Banchero, Marco Casciaro, Alessandro Tonacci, Lucia Billeci, Alessio Nencioni, Giovanni Pioggia, Sara Genovese, Fiammetta Monacelli, Sebastiano Gangemi
Summary: Vascular dementia is a cognitive impairment associated with age and vascular etiology, typically occurring when brain vessels suffer micro-accidents leading to insufficient oxygen and nutrient supply to the brain. Machine learning methods can be utilized to identify predictive biomarkers for cognitive worsening early on, helping save time and money, and reducing the burden on patients.
Letter
Chemistry, Applied
Nicola Cicero, Sebastiano Gangemi, Alessandro Allegra
NATURAL PRODUCT RESEARCH
(2023)
Review
Allergy
Beatriz Cabanillas, Giuseppe Murdaca, Amir Guemari, Maria Jose Torres, Ahmet Kursat Azkur, Emel Aksoy, Joana Vitte, Leticia de las Vecillas, Mattia Giovannini, Ruben Fernandez-Santamaria, Riccardo Castagnoli, Andrea Orsi, Rosa Amato, Irene Giberti, Alba Catala, Dominika Ambrozej, Bianca Schaub, Gerdien A. A. Tramper-Stranders, Natalija Novak, Kari C. C. Nadeau, Ioana Agache, Mubeccel Akdis, Cezmi A. A. Akdis
Summary: The current monkeypox disease outbreak is a new and significant threat to society, with over 55,000 confirmed cases in 103 countries. It is the largest and most serious outbreak since the initial diagnosis in 1970. While monkeypox is usually self-limiting, severe clinical manifestations and complications have been observed, particularly in vulnerable populations. The extensive spread of the current outbreak raises important questions that require investigation to better understand and prevent such threats in the future. A review addressing 50 questions about monkeypox virus and the current outbreak aims to provide up-to-date scientific information and explore the potential causes and consequences of this public health emergency.
Review
Biochemistry & Molecular Biology
Alessandro Allegra, Giuseppe Murdaca, Luca Gammeri, Roberta Ettari, Sebastiano Gangemi
Summary: It is known that airway inflammation plays a crucial role in various respiratory diseases. This review focuses on the changes in respiratory diseases related to alarmins, such as HMGB1 and IL-33, and their relationships with genetic non-coding material like microRNAs. The role of these alarmins in certain pathophysiological processes confirms the existence of an axis composed of HMGB1 and IL-33, which are implicated in ferroptosis, type 2 inflammation, and airway alterations. Additionally, both factors can influence non-coding genetic material that affects respiratory function. Finally, the review outlines alarmins and RNA-based therapeutics proposed for the treatment of respiratory pathologies.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Biochemistry & Molecular Biology
Giuseppe Murdaca, Francesca Paladin, Matteo Borro, Luisa Ricciardi, Sebastiano Gangemi
Summary: Chronic spontaneous urticaria (CSU) is a condition characterized by almost daily occurrence of widespread wheals and angioedema for more than 6 weeks. It affects 1-2% of the general population, with a higher prevalence in female patients and those over 20 years of age. Over 50% of cases are believed to be caused by an autoimmune mechanism involving the production of autoantibodies against the high-affinity immunoglobulin E (IgE) receptor (Fc epsilon RI). This review highlights the close correlation between CSU and various autoimmune and autoinflammatory diseases, emphasizing the need for a comprehensive approach to manage both CSU and its associated comorbidities.
Review
Biochemistry & Molecular Biology
Fabiana Furci, Giuseppe Murdaca, Corrado Pelaia, Egidio Imbalzano, Girolamo Pelaia, Marco Caminati, Alessandro Allegra, Gianenrico Senna, Sebastiano Gangemi
Summary: The airway epithelium is the first line of defense for the lungs against environmental triggers. It releases alarmin cytokines, which mediate inflammation in chronic lung diseases. This review focuses on the role of pulmonary epithelial cells and airway epithelial cell alarmins in driving inflammation and explores the therapeutic potential of targeting these molecules.
Editorial Material
Biochemistry & Molecular Biology
Giuseppe Murdaca, Sebastiano Gangemi
Editorial Material
Biochemistry & Molecular Biology
Giuseppe Murdaca, Sebastiano Gangemi, Monica Greco
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Biochemistry & Molecular Biology
Alessandro Allegra, Giuseppe Mirabile, Alessandro Tonacci, Sara Genovese, Giovanni Pioggia, Sebastiano Gangemi
Summary: Cardiac amyloidosis is a rare restrictive cardiomyopathy caused by abnormal deposition of amyloid protein, leading to impaired organ function. Due to similar clinical symptoms with more common hypertrophic diseases, early diagnosis of cardiac amyloidosis is often delayed. Accurate differentiation of different types of amyloidosis is necessary for appropriate treatment. The underdiagnosis of cardiac amyloidosis delays necessary therapeutic procedures, hinders quality of life, and affects clinical prognosis. Diagnostic work-up includes identification of clinical features, electrocardiographic and imaging findings, and histological demonstration of amyloid deposition. Automated diagnostic algorithms using machine learning techniques can help overcome the difficulty of early diagnosis. This review aims to evaluate various diagnostic approaches and artificial intelligence computational techniques in detecting cardiac amyloidosis.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Biochemistry & Molecular Biology
Raffaele Brancaccio, Giuseppe Murdaca, Rossella Casella, Teresa Loverre, Laura Bonzano, Eustachio Nettis, Sebastiano Gangemi
Summary: Skin inflammation is a common feature of atopic dermatitis, allergic contact dermatitis and chronic spontaneous urticaria, and the pathogenetic mechanisms are not fully understood. This study reviews the role of miRNA in regulating inflammatory mechanisms and innate and adaptive immune responses in these skin conditions. miRNAs are found to be involved in the pathogenesis and regulation of atopic dermatitis, chronic spontaneous urticaria, and allergic contact dermatitis, and they could serve as biomarkers and potential therapeutic targets for these chronic skin conditions.
Review
Biochemistry & Molecular Biology
Alessandro Allegra, Giuseppe Murdaca, Giuseppe Mirabile, Sebastiano Gangemi
Summary: Although immunotherapy is vital in cancer treatment, not all patients benefit from it. Research is focused on improving treatment efficacy and understanding the resistance mechanisms. Immune-based treatments require strong infiltration of T cells into the tumor microenvironment, but immune cells face challenges in the metabolic environment, leading to reduced effectiveness.
Review
Biology
Fabiana Furci, Alessandro Allegra, Alessandro Tonacci, Stefania Isola, Gianenrico Senna, Giovanni Pioggia, Sebastiano Gangemi
Summary: Air pollution exposure can alter gene expression profiles, regulated by microRNAs, leading to the development of various diseases. MicroRNAs are also sensitive to environmental factors like tobacco smoke. Specific microRNA signatures are associated with different diseases, making them potential biomarkers for exposure. This study aims to analyze literature data on the role of environmental stressors in microRNA alterations, specifically identifying changes related to airway diseases, for future preventive, diagnostic, and therapeutic strategies.
Review
Biochemistry & Molecular Biology
Antonino Palumbo, Fabiola Atzeni, Giuseppe Murdaca, Sebastiano Gangemi
Summary: Osteoarthritis (OA) is a prevalent and disabling joint disease influenced by various factors. Recent research has revealed the involvement of damage-associated molecular patterns (DAMPs), particularly alarmins like HMGB1, IL-33, and S100B, in promoting inflammation and degradation in OA chondrocytes. Identifying the molecular signaling of these molecules, their potential use as biomarkers for disease staging, and their suitability as therapeutic targets are important objectives. High levels of HMGB1, in particular, have been observed in OA cartilage, synovium, and synovial fluid, and are associated with disease severity. Strategies targeting HMGB1 have shown promising results in OA cells and animal models and could provide new treatment options for modifying disease progression.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Biochemistry & Molecular Biology
Raffaele Sciaccotta, Giuseppe Murdaca, Santino Caserta, Vincenzo Rizzo, Sebastiano Gangemi, Alessandro Allegra
Summary: This article investigates the role of circular RNAs in the pathogenesis of multiple sclerosis. Circular RNAs influence post-transcriptional control, affecting microRNA and epigenetic factors, and promoting the development of typical MS abnormalities such as neuroinflammation and neuronal cell damage.
Review
Biochemistry & Molecular Biology
Santino Caserta, Sebastiano Gangemi, Giuseppe Murdaca, Alessandro Allegra
Summary: MicroRNAs are small molecules that play important roles in both healthy and pathological cells. They are influenced by genetic factors and epigenetic mechanisms, such as genomic imprinting and X chromosome inactivation in females. MiRNAs have been shown to be correlated with sex and cancer in both solid tumors and hematological malignancies. Understanding the role of miRNAs in cancerogenesis, autophagy, and apoptosis of different types of tumors can have implications for cancer treatment and prognosis.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Gennaro Tartarisco, Giovanni Cicceri, Roberta Bruschetta, Alessandro Tonacci, Simona Campisi, Salvatore Vitabile, Antonio Cerasa, Salvatore Distefano, Alessio Pellegrino, Pietro Amedeo Modesti, Giovanni Pioggia
Summary: This paper presents a Medical Cyber-Physical System (MCPS) for the automatic classification of heart valve diseases onsite. The proposed system combines different neural network models and has been validated on a new dataset, demonstrating high accuracy and feasibility.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
