Article
Endocrinology & Metabolism
Hai Duc Nguyen, Byung Pal Yu, Ngoc Hong Minh Hoang, Won Hee Jo, Hae Young Chung, Min-Sun Kim
Summary: PRL is a promising molecule for the treatment of neurodegenerative disorders like Alzheimer's disease and Parkinson's disease, but the mechanisms responsible for its effects are still not fully understood. Modulating PRL functions and targeting immune mechanisms are key strategies for developing preventive or therapeutic approaches.
NEUROENDOCRINOLOGY
(2022)
Review
Chemistry, Medicinal
Amanda Cano, Elena Fonseca, Miren Ettcheto, Elena Sanchez-Lopez, Itziar de Rojas, Silvia Alonso-Lana, Xavier Morato, Eliana B. Souto, Manuel Toledo, Merce Boada, Marta Marquie, Agustin Ruiz
Summary: Epilepsy is a chronic disease of the central nervous system characterized by an electrical imbalance in neurons. The molecular processes that trigger epileptic seizures and promote neurotoxic effects are currently focused on the glutamate pathway and influx of calcium ions into neurons. Common molecular links between epilepsy and other neurodegenerative diseases have led to investigation of antiseizure drugs for therapeutic potential in these pathologies.
Review
Biochemistry & Molecular Biology
Fatimah K. Khalaf, Jacob Connolly, Bella Khatib-Shahidi, Abdulsahib Albehadili, Iman Tassavvor, Meghana Ranabothu, Noha Eid, Prabhatchandra Dube, Samer J. Khouri, Deepak Malhotra, Steven T. Haller, David J. Kennedy
Summary: Paraoxonase enzymes are an important redox system that protect cells against oxidative stress. The PON enzymes family, consisting of PON-1, PON-2, and PON-3, play a role in preventing cardiovascular disease and are associated with neurological disorders and neurodegenerative diseases. This review summarizes the evidence on the role of PONs in these diseases and their ability to modify risk factors for neurological disorders, focusing on Alzheimer's disease, Parkinson's disease, and other neurodegenerative and neurological diseases.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Neurosciences
Mohammad Rafi Khezri, Keyvan Yousefi, Naime Majidi Zolbanin, Morteza Ghasemnejad-Berenji
Summary: Neurodegenerative diseases, a major cause of mortality and functional dependence among the elderly, have a low success rate in clinical pipelines. MicroRNAs play a crucial role in regulating the occurrence of neurodegenerative diseases, and alterations in certain microRNA levels in clinical samples may have significant clinical implications.
MOLECULAR NEUROBIOLOGY
(2022)
Review
Biochemistry & Molecular Biology
Keelan Jagaran, Moganavelli Singh
Summary: Neurodegenerative disorders result in the gradual degeneration of axons and neurons in the central nervous system, causing major disruptions in patients' lives. Current treatments are only palliative, highlighting the need for a therapeutic strategy targeting the root cause of the diseases. The synergistic use of gene therapy and nanomedicine shows promise in effectively treating these diseases by targeting the causative mutated genes.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Review
Genetics & Heredity
Egle Jakubauskiene, Arvydas Kanopka
Summary: Alternative pre-mRNA splicing is essential for generating protein diversity and is implicated in the pathogenesis of neurological disorders. The splicing machinery also plays a role in cellular adaptation to different microenvironments, such as hypoxia. Understanding the alternative splicing of genes associated with Alzheimer's and Parkinson's diseases can provide insights into the development of these neurodegenerative conditions, including the influence of cellular hypoxic microenvironments.
Review
Pharmacology & Pharmacy
Ekta Yadav, Pankajkumar Yadav, Mohd Masih Uzzaman Khan, HariOm Singh, Amita Verma
Summary: Polyphenols, such as resveratrol, have the ability to cross the blood-brain barrier and are widely used in the treatment of neurodegenerative diseases by targeting mitochondria. These diseases, including Alzheimer's and Parkinson's, are primarily caused by mitochondrial dysfunction and have significant public health implications.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Medicine, Research & Experimental
Yasemin Acar, Duygu Agagunduz, Paola De Cicco, Raffaele Capasso
Summary: This paper provides a literature review on the neurological roles of flavonoids, one of the most abundant phytochemical families, in Parkinson's disease (PD). Flavonoids have been shown to have beneficial effects on PD, such as protecting dopaminergic neurons, improving motor and cognitive abilities, regulating signaling pathways, and modulating oxidative stress and neuroinflammation. In addition, flavonoids can also promote the growth of beneficial strains and reduce pathogenic strains by changing the composition of bacteria in gut microbiota.
BIOMEDICINE & PHARMACOTHERAPY
(2023)
Article
Neurosciences
Hannah Walgrave, Lujia Zhou, Bart De Strooper, Evgenia Salta
Summary: Researchers review the regulation of microRNAs in the pathophysiology of Alzheimer's disease and critically discuss the potential for developing microRNA-based therapeutics using these insights.
MOLECULAR NEURODEGENERATION
(2021)
Review
Pharmacology & Pharmacy
Ankit Tandon, Sangh J. Singh, Rajnish K. Chaturvedi
Summary: Alzheimer's and Parkinson's are two common neurodegenerative disorders, with existing treatments limited in their ability to halt disease progression. Nanotechnology has enabled the development of novel nano-therapeutics for these diseases, allowing for efficient and targeted drug delivery to the brain. Nanoparticles are also being explored for their role in precise diagnosis, with challenges such as route of administration and toxicity needing to be addressed for successful therapeutic outcomes.
CURRENT PHARMACEUTICAL DESIGN
(2021)
Review
Biochemistry & Molecular Biology
Ahsas Goyal, Aanchal Verma, Nandini Dubey, Jyoti Raghav, Anant Agrawal
Summary: Neurodegenerative disorders are severe and disabling diseases with a lack of effective treatments. Natural compounds, particularly flavonoids, extracted from medicinal plants or fruits have shown promise in treating such disorders. Naringenin, a citrus flavonoid, has various biological activities and has emerged as a potential therapeutic agent for neurological disorders.
JOURNAL OF FOOD BIOCHEMISTRY
(2022)
Article
Geriatrics & Gerontology
Nicolas Delcourt, Alix-Marie Pouget, Alicia Grivaud, Leonor Nogueira, Frederic Larvor, Philippe Marchand, Eric Schmidt, Bruno Le Bizec
Summary: This study found that PFAS compounds, widely used in various products, are present in human cerebrospinal fluid and are associated with clinical and biological markers of Alzheimer's disease.
JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES
(2023)
Article
Genetics & Heredity
Veria Vacchiano, Anna Bartoletti-Stella, Giovanni Rizzo, Patrizia Avoni, Piero Parchi, Fabrizio Salvi, Rocco Liguori, Sabina Capellari
Summary: ALS and AD patients have a higher prevalence of Lewy body disease and parkinsonian features. This study found a higher frequency of Parkinson's disease-causative genes in ALS patients, suggesting their potential role in ALS pathogenesis.
Review
Biochemistry & Molecular Biology
Yi-Hsuan Wu, Hsi-Lung Hsieh
Summary: The heme oxygenase system, particularly HO-1 and HO-2, plays an important role in the nervous system. Dysregulation of HO-1 is associated with neurodegenerative diseases.
Review
Neurosciences
Yingying Ji, Kai Zheng, Shiming Li, Caili Ren, Ying Shen, Lin Tian, Haohao Zhu, Zhenhe Zhou, Ying Jiang
Summary: Ferroptosis, as a newly discovered form of cell death, plays a key role in the occurrence and development of neurodegenerative diseases. However, the underlying mechanism of ferroptosis in these diseases remains unclear, and further research is needed to explore its therapeutic potential.
FRONTIERS IN CELLULAR NEUROSCIENCE
(2022)
Article
Biology
Phasit Charoenkwan, Chonlatip Pipattanaboon, Chanin Nantasenamat, Md Mehedi Hasan, Mohammad Ali Moni, Pietro Lio, Watshara Shoombuatong
Summary: Despite existing cancer therapies, the development of new and effective treatments is necessary to address the ongoing cancer recurrence and new cases. This study proposes a new machine learning-based approach, PSRTTCA, for improving the identification and characterization of tumor T cell antigens (TTCAs) based on their primary sequences.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biotechnology & Applied Microbiology
Shudeb Babu Sen Omit, Salma Akhter, Humayan Kabir Rana, A. R. M. Mahamudul Hasan Rana, Nitun Kumar Podder, Mahmudul Islam Rakib, Ashadun Nobi
Summary: Using transcriptomic analysis of RNA-seq datasets from the Gene Expression Omnibus (GEO) database, we identified 27 diseases associated with COVID-19, with hypertension, diabetes, obesity, and lung cancer being observed multiple times in COVID-19 patients. Through cross-comparative analysis and Jaccard's similarity index, we found shared differentially expressed genes (DEGs) linking COVID-19 and the comorbidities, with hypertension being the most associated illness.
BIOMED RESEARCH INTERNATIONAL
(2023)
Article
Clinical Neurology
Anita Sathyanarayanan, Tamara T. Mueller, Mohammad Ali Moni, Katja Schueler, Bernhard T. Baune, Pietro Lio, Divya Mehta
Summary: This review summarizes the methods for discovering biologically meaningful biomarkers for diagnosis, treatment, and prognosis by combining multi-omics data. It discusses conventional and state-of-the-art statistical and machine learning approaches, as well as the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research. Challenges and future applications of multi-omics integration in psychiatric research are also discussed.
EUROPEAN NEUROPSYCHOPHARMACOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Taima Rahman Mim, Maliha Amatullah, Sadia Afreen, Mohammad Abu Yousuf, Shahadat Uddin, Salem A. Alyami, Khondokar Fida Hasan, Mohammad Ali Moni
Summary: Human Activity Recognition (HAR) is a valuable research field for clinical applications, where machine learning algorithms play a significant role. The proposed Gated Recurrent Unit-Inception (GRU-INC) model effectively utilizes both temporal and spatial information of time-series data, achieving high F1-scores on various publicly available datasets. The combination of GRU with Attention Mechanism and Inception module with Convolutional Block Attention Module (CBAM) contributes to the superior recognition rate and lower computational cost of the GRU-INC model. This framework has the potential to be applied in activity-associated clinical and rehabilitation applications.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Biochemical Research Methods
Pietro Bongini, Franco Scarselli, Monica Bianchini, Giovanna Maria Dimitri, Niccolo Pancino, Pietro Lio
Summary: Drug side-effects have a significant impact on public health, care system costs, and drug discovery processes. Predicting the probability of side-effects before their occurrence is crucial to reduce this impact, especially in drug discovery. By integrating heterogeneous data into a graph dataset, this study successfully utilizes Graph Neural Networks (GNNs) to predict drug side-effects, showing promising results. The experimental results highlight the significance of utilizing relationships between data entities and suggest potential future developments in this field.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Md Shofiqul Islam, Khondokar Fida Hasan, Sunjida Sultana, Shahadat Uddin, Pietro Lio', Julian M. W. Quinn, Mohammad Ali Moni
Summary: We propose a hybrid hierarchical attention-based bidirectional recurrent neural network with dilated CNN (HARDC) method for arrhythmia classification. This method fully exploits the dilated CNN and bidirectional recurrent neural network unit (BiGRU-BiLSTM) architecture to generate fusion features, improving the model's performance for prediction. By combining the fusion features with a dilated CNN and a hierarchical attention mechanism, the trained HARDC model showed significantly improved classification results and interpretability of feature extraction on the PhysioNet 2017 challenge dataset.
Review
Polymer Science
Shaik Merkatur Hakim Marjuban, Musfira Rahman, Syeda Sharmin Duza, Mohammad Boshir Ahmed, Dinesh K. Patel, Md Saifur Rahman, Karen Lozano
Summary: In the past decade, researchers have explored the potential of nano and microfiber scaffolds in wound healing, tissue regeneration, and skin protection. The centrifugal spinning technique has gained popularity for its ability to produce large quantities of fiber in a straightforward manner. This literature review discusses the process of fiber generation, the effects of fabrication parameters on fiber morphology, and provides an overview of the advancements in centrifugally spun polymeric fiber-based materials for tissue engineering applications.
Article
Medicine, General & Internal
Md. Tarek Aziz, S. M. Hasan Mahmud, Md. Fazla Elahe, Hosney Jahan, Md Habibur Rahman, Dip Nandi, Lassaad K. Smirani, Kawsar Ahmed, Francis M. Bui, Mohammad Ali Moni
Summary: In this paper, a hybrid framework was proposed to improve the efficiency of osteosarcoma tumor classification by merging different types of CNN-based architectures with a multilayer perceptron algorithm. The proposed model achieved high accuracy for both multiclass and binary classification of osteosarcoma, outperforming existing methods. Experimental findings indicate the potential applicability of this model in supporting osteosarcoma diagnosis in clinics.
Review
Health Care Sciences & Services
Palak Mahajan, Shahadat Uddin, Farshid Hajati, Mohammad Ali Moni
Summary: Machine learning models are utilized to create and improve disease prediction frameworks, and ensemble learning is a technique that combines multiple classifiers to enhance performance. In this study, the performance accuracies of different ensemble techniques (bagging, boosting, stacking, and voting) are assessed against five highly researched diseases. The findings reveal that stacking has the most accurate performance and can assist researchers in understanding current trends in disease prediction models that employ ensemble learning.
Article
Computer Science, Hardware & Architecture
Md. Monirul Islam, Mohammod Abul Kashem, Salem A. Alyami, Mohammad Ali Moni
Summary: This paper presents an IoT framework for aquaculture that allows real-time monitoring and effective control of water-related parameters. The proposed system utilizes sensors and an Arduino microcontroller to collect and store data in an IoT cloud platform. The collected data is then analyzed using various machine learning algorithms, with Random Forest achieving the highest performance scores. The study also includes hardware details of the IoT system and calculates biochemical and chemical oxygen demands.
MICROPROCESSORS AND MICROSYSTEMS
(2023)
Article
Genetics & Heredity
Rabea Khatun, Maksuda Akter, Md. Manowarul Islam, Md. Ashraf Uddin, Md. Alamin Talukder, Joarder Kamruzzaman, Akm Azad, Bikash Kumar Paul, Muhammad Ali Abdulllah Almoyad, Sunil Aryal, Mohammad Ali Moni
Summary: This article proposes an ensemble rank-based feature selection method and classifier to address the challenge of high-dimensional data in cancer diagnosis. The method efficiently discovers the most relevant and useful features by aggregating rankings from different selection methods. The results show high accuracy on multiple datasets and the study identifies a subset of the most important cancer-causing genes and demonstrates their significance.
Article
Computer Science, Information Systems
Nuruzzaman Faruqui, Mohammad Abu Yousuf, Md Whaiduzzaman, A. K. M. Azad, Salem A. Alyami, Pietro Lio, Muhammad Ashad Kabir, Mohammad Ali Moni
Summary: The Internet of Medical Things (IoMT) has become an attractive target for cybercriminals due to its market value and rapid growth. However, IoMT devices have limited computational capabilities, making them vulnerable to cyber-attacks. To address this, a novel Intrusion Detection System (IDS) called SafetyMed is proposed, which combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to defend against intrusion from sequential and grid data. SafetyMed has shown high detection rates and accuracy, making it a potential game-changer in vulnerable sectors like the medical industry.
Review
Computer Science, Information Systems
Showmick Guha Paul, Arpa Saha, Mohammad Shamsul Arefin, Touhid Bhuiyan, Al Amin Biswas, Ahmed Wasif Reza, Naif M. Alotaibi, Salem A. Alyami, Mohammad Ali Moni
Summary: Green computing, or sustainable computing, focuses on developing and optimizing computer technology to be more energy efficient and have less negative impact on the environment. This study reviews and summarizes the advancements, challenges, and future research opportunities in green computing. It provides insights and ideas for organizations, researchers, and institutions conducting research in this field, as well as benefits environmental organizations, companies, and government agencies concerned with reducing carbon emissions and energy consumption.
Article
Health Care Sciences & Services
Md. Martuza Ahamad, Sakifa Aktar, Md. Jamal Uddin, Md. Rashed-Al-Mahfuz, A. K. M. Azad, Shahadat Uddin, Salem A. Alyami, Iqbal H. Sarker, Asaduzzaman Khan, Pietro Lio, Julian M. W. Quinn, Mohammad Ali Moni
Summary: Good vaccine safety and reliability are crucial for countering infectious diseases effectively. This study aims to reduce adverse reactions to COVID-19 vaccines by identifying common factors through patient data analysis and classification. Patient medical histories and postvaccination effects were examined, and statistical and machine learning approaches were used. The analysis revealed that prior illnesses, hospital admissions, and SARS-CoV-2 reinfection were significantly associated with poor patient reactions.
Review
Materials Science, Multidisciplinary
Mozammel Hoque, Masruck Alam, Sungrok Wang, Jahid Uz Zaman, Md. Saifur Rahman, M. A. H. Johir, Limei Tian, Jun-Gyu Choi, Mohammad Boshir Ahmed, Myung-Han Yoon
Summary: This review comprehensively summarizes the chemistry and crosslinking strategies of natural biopolymer-based hydrogels, with a focus on the chemical characteristics of functional group interactions. It also outlines the types, properties, and applications of the resulting hydrogels, and discusses future research prospects in this field.
MATERIALS SCIENCE & ENGINEERING R-REPORTS
(2023)
