Article
Neurosciences
Olivia A. Shipton, Clara S. Tang, Ole Paulsen, Mariana Vargas-Caballero
Summary: The study shows that both A beta and tau protein play a role in the development of Alzheimer's disease. A beta affects synaptic deficits in wild-type mice, but not in mice without tau protein. Additionally, CA3-CA1 synapses in the hippocampus with presynaptic axons from the left CA3 are more vulnerable to A beta.
ACTA NEUROPATHOLOGICA COMMUNICATIONS
(2022)
Article
Biochemistry & Molecular Biology
Pol Picon-Pages, Hugo Fanlo-Ucar, Victor Herrera-Fernandez, Sira Auselle-Bosch, Lorena Galera-Lopez, Daniela A. Gutierrez, Andres Ozaita, Alejandra R. Alvarez, Baldomero Oliva, Francisco J. Munoz
Summary: Alzheimer's disease (AD) is characterized by the presence of extracellular amyloid plaques in the brain, which are composed of aggregated amyloid beta-peptide (Aβ). It has been found that Aβ oligomers (oAβ) induce the production of reactive oxygen species (ROS), resulting in the oxidation of CaMKII alpha. This oxidized form of CaMKII alpha is present in brain samples from AD patients and is activated independently of calcium/calmodulin binding. The oxidation of CaMKII alpha promotes the phosphorylation of CREB and its translocation to the nucleus, leading to the transcription of ARC and BDNF in AD transgenic mice and primary cultures of murine hippocampal neurons.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Katarzyna M. Grochowska, Guilherme M. Gomes, Rajeev Raman, Rahul Kaushik, Liudmila Sosulina, Hiroshi Kaneko, Anja M. Oelschlegel, PingAn Yuanxiang, Irene Reyes-Resina, Gonca Bayraktar, Sebastian Samer, Christina Spilker, Marcel S. Woo, Markus Morawski, Juergen Goldschmidt, Manuel A. Friese, Steffen Rossner, Gemma Navarro, Stefan Remy, Carsten Reissner, Anna Karpova, Michael R. Kreutz
Summary: Soluble beta-amyloid peptide (A beta) causes synaptic dysfunction in early-stage Alzheimer's disease (AD) by suppressing the transcriptional activity of CREB. A beta induces nucleocytoplasmic trafficking of Jacob, which leads to transcriptional inactivation of CREB and loss of synapses. The compound Nitarsone restores CREB activity by hindering the assembly of a Jacob/LMO4/PP1 signalosome, preventing synaptic impairment and cognitive decline in mouse models of AD.
Article
Neurosciences
Risa Takamura, Kotaro Mizuta, Yukiko Sekine, Tanvir Islam, Takashi Saito, Masaaki Sato, Masamichi Ohkura, Junichi Nakai, Toshio Ohshima, Takaomi C. Saido, Yasunori Hayashi
Summary: The study showed that in amyloid precursor protein knock-in mice, temporal representation is preserved while spatial representation is significantly impaired. This is due to a decrease in active place cells overall, but compensatory hyperactivation of remaining place cells near A beta aggregates.
JOURNAL OF NEUROSCIENCE
(2021)
Article
Behavioral Sciences
Samah Labban, Badrah S. Alghamdi, Fahad S. Alshehri, Maher Kurdi
Summary: This study showed that melatonin and resveratrol had positive effects on improving memory deficits in a sporadic mouse model of Alzheimer's disease, with better outcomes when used in combination. Additionally, both substances enhanced the cholinergic system and BDNF, CREB signaling pathways in the prefrontal cortex in the AD mouse model.
BEHAVIOURAL BRAIN RESEARCH
(2021)
Article
Neurosciences
Efrain A. Cepeda-Prado, Babak Khodaie, Gloria D. Quiceno, Swantje Beythien, Elke Edelmann, Volkmar Lessmann
Summary: In this study, low repeat STDP experiments were conducted at Schaffer collateral-CA1 synapses, and it was found that only 3-6 repeats were sufficient to trigger t-LTP. 6x 1:1 t-LTP relied on postsynaptic Ca2+ influx and increased presynaptic glutamate release, while 1:4 t-LTP depended on postsynaptic metabotropic GluRs and ryanodine receptor signaling, as well as postsynaptic insertion of AMPA receptors. Both t-LTP variants were strictly dependent on activation of postsynaptic Ca2+-permeable AMPARs, but were differentially regulated by dopamine receptor signaling. These findings indicate that synaptic changes can occur with just a few mild STDP stimulations within a short period of time.
Article
Endocrinology & Metabolism
Fatemeh Ashourpour, Adele Jafari, Parvin Babaei
Summary: This study demonstrated that chronic administration of Tat-GluR23Y successfully restored spatial memory impaired by amyloid beta neurotoxicity, improving cognitive function in rats; hippocampal level of CREB can reflect the memory performance of rats, providing a new perspective for the treatment of Alzheimer's disease.
METABOLIC BRAIN DISEASE
(2021)
Article
Chemistry, Medicinal
Peyman Taheri, Parichehreh Yaghmaei, Zahra Hajebrahimi, Kazem Parivar
Summary: Nerolidol may offer neuroprotection against Alzheimer's disease by reducing Aβ plaques and increasing BDNF and CREB-1 expression to improve pathological features.
DRUG DEVELOPMENT RESEARCH
(2022)
Article
Biochemistry & Molecular Biology
Fatemeh Ataellahi, Raheleh Masoudi, Mohammad Haddadi
Summary: This study assessed the effects of Tau(WT), A beta(42), and shaggy genes on synaptic genes expression and behavior in Alzheimer's disease, and found that shaggy had a more detrimental effect compared to Tau(WT) or A beta(42). This research is important for drug discovery and suggests that CREB may play a role in compensatory mechanisms independent of the GSK3/CREB pathway.
MOLECULAR BIOLOGY REPORTS
(2023)
Article
Clinical Neurology
Thomas Lancaster, Byron Creese, Valentina Escott-Price, Ian Driver, Georgina Menzies, Zunera Khan, Anne Corbett, Clive Ballard, Julie Williams, Kevin Murphy, Hannah Chandler
Summary: Genome-wide association studies have shown that Alzheimer's disease has a highly polygenic architecture, and the AD polygenic risk score has been linked to cognitive and neuroimaging features observed in asymptomatic individuals. This study observed alterations in autobiographical memory and cingulate structure in individuals with higher AD genetic risk. These findings support the use of genetically informed approaches for the detection and intervention in individuals at increased AD risk.
ALZHEIMERS RESEARCH & THERAPY
(2023)
Article
Endocrinology & Metabolism
Rastin Nikkar, Aghil Esmaeili-Bandboni, Mahshid Badrikoohi, Parvin Babaei
Summary: Communication between astrocytes and neurons plays a critical role in Alzheimer's disease (AD). Inhibition of astrocyte metabolism and BRD4 provided cognitive improvements in early stages of AD, possibly through the CREB signaling pathway and upregulating synaptic proteins. However, inhibition of astrocytes counteracted the memory-boosting effects of BRD4 inhibition.
METABOLIC BRAIN DISEASE
(2022)
Article
Biochemistry & Molecular Biology
Mina Abghari, Jenny Thythy Cecilia Mai Vu, Ninna Eckberg, Blanca I. Aldana, Kristi A. Kohlmeier
Summary: This study found that glutamate-mediated signaling in CA1 neurons and astrocytes was impaired in a mouse model of Alzheimer's disease, and decanoic acid was able to restore this signaling to normal levels.
Article
Neurosciences
Alexandra Pierri Chatzikalymniou, Melisa Gumus, Frances K. Skinner
Summary: The study focuses on models of the CA1 microcircuit in the hippocampus, showing that pyramidal cells are rhythm initiators and their activity is regulated by inhibitory cell populations. There is a strong correlation between input current to pyramidal cells and local field potential theta frequency. This research provides a cellular-based foundation for exploring in vivo rhythm activities.
Article
Agriculture, Multidisciplinary
Li Yan, Yufan Jin, Junping Pan, Xiang He, Shiqian Zhong, Rongcai Zhang, LokLam Choi, Weiwei Su, Jiaxu Chen
Summary: Alzheimer's disease is a neurodegenerative disorder characterized by memory and cognition impairment. A compound called 7,8-DHC derived from coumarin has been found to reduce beta-amyloid accumulation and improve learning and memory impairment by activating specific signaling pathways.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
(2022)
Article
Neurosciences
Lei Qiao, Yue Chen, Xina Dou, Xiaofan Song, Chunlan Xu
Summary: The study demonstrated that biogenic SeNPs can effectively alleviate Aβ(25-35)-induced toxicity in PC12 cells via the Akt/CREB/BDNF signaling pathway.
NEUROTOXICITY RESEARCH
(2022)
Article
Computer Science, Information Systems
Lei Xiao, Gang Mei, Salvatore Cuomo, Nengxiong Xu
Summary: This paper introduces a GPU-based parallel collision detection method that efficiently detects collisions between triangulated models by implementing three parallel triangle-triangle intersection algorithms. Experimental results show that the method performs well in detecting collisions between large triangulated models.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Biophysics
Daniela Bianchi, Rosanna Migliore, Paola Vitale, Machhindra Garad, Paula A. Pousinha, Helene Marie, Volkmar Lessmann, Michele Migliore
Summary: This paper highlights an electrophysiological feature observed in mouse CA1 pyramidal cells that has been ignored by researchers. The increase in membrane potential during sustained inputs cannot be explained by current computational models. A new model is proposed to address this issue.
BIOPHYSICAL JOURNAL
(2022)
Article
Biophysics
Anna Pennacchio, Fabio Giampaolo, Francesco Piccialli, Salvatore Cuomo, Eugenio Notomista, Michele Spinelli, Angela Amoresano, Alessandra Piscitelli, Paola Giardina
Summary: The study proposes a novel solution for detecting mercury pollution in sea water by developing a portable biosensor using a hydrophobin-based chimera. This biosensor can accurately detect mercury (II) concentration in sea water, with the advantage of predicting mercury levels without the use of traditional reader devices. The developed biosensor allows for on-site monitoring of marine pollution by non-skilled personnel.
BIOSENSORS & BIOELECTRONICS
(2022)
Article
Computer Science, Artificial Intelligence
Salvatore Cuomo, Federico Gatta, Fabio Giampaolo, Carmela Iorio, Francesco Piccialli
Summary: This research proposes a portfolio optimization strategy based on assets clustering, aiming to group assets based on their exposure to the same risk factors and construct a market-neutral portfolio. The methodology is applied in various case studies to discuss the results obtained and highlight the strengths and limitations of the proposed strategy.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Zhengjing Ma, Gang Mei, Salvatore Cuomo, Francesco Piccialli
Summary: This paper proposes a deep learning method that combines graph convolutional networks (GCNs) to fuse heterogeneous data for predicting the future state of certain observations. The effectiveness of this approach was verified in an air quality prediction scenario, showing promising results.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Mathematics, Applied
Salvatore Cuomo, Vincenzo Schiano Di Cola, Fabio Giampaolo, Gianluigi Rozza, Maziar Raissi, Francesco Piccialli
Summary: Physics-Informed Neural Networks (PINN) are a type of neural network that incorporates model equations, such as partial differential equations, as a component. PINNs have been used to solve various types of equations, including fractional equations and stochastic partial differential equations. Current research focuses on optimizing PINN through different aspects, such as activation functions, gradient optimization techniques, neural network structures, and loss function structures. Despite the demonstrated feasibility of PINN in certain cases compared to traditional numerical techniques, there are still unresolved theoretical issues.
JOURNAL OF SCIENTIFIC COMPUTING
(2022)
Article
Mathematics, Applied
Giacomo Ascione, Salvatore Cuomo
Summary: This paper introduces a new approach based on the sojourn time process for dealing with discrete-time semi-Markov decision processes. With this approach, the agent can consider different actions based on the sojourn time of the process in the current state. A numerical method based on Q-learning algorithms is investigated, and the algorithm is evaluated through two examples.
JOURNAL OF SCIENTIFIC COMPUTING
(2022)
Article
Multidisciplinary Sciences
Martina Sgritta, Beatrice Vignoli, Domenico Pimpinella, Marilena Griguoli, Spartaco Santi, Andrzej Bialowas, Grzegorz Wiera, Paola Zacchi, Francesca Malerba, Cristina Marchetti, Marco Canossa, Enrico Cherubini
Summary: In Neurodevelopmental Disorders, changes in synaptic plasticity can lead to structural alterations in neuronal circuits involved in cognitive functions. This study tested this hypothesis in mice with the human R451C mutation of the Nlgn3 gene, which is found in some families with autistic children. The results showed that these mice failed to exhibit STD-LTP and this effect persisted into adulthood. Similar results were found in mice lacking the Nlgn3 gene. The loss of STD-LTP was associated with a premature shift of GABA and reduced BDNF availability, suggesting a potential mechanism underlying cognitive deficits in forms of Autism caused by synaptic dysfunctions.
Article
Neurosciences
Emanuela Rizzello, Domenico Pimpinella, Annabella Pignataro, Giulia Titta, Elisabetta Merenda, Michela Saviana, Giovanni Francesco Porcheddu, Chiara Paolantoni, Francesca Malerba, Corinna Giorgi, Giulia Curia, Silvia Middei, Cristina Marchetti
Summary: Epilepsy is a comorbidity associated with Alzheimer's disease, and investigating this association in the early stages of AD can provide insights into the pathology. The study found that repeated seizures caused memory deficits and an increase in A beta levels in pre-symptomatic Alzheimer's mice. It also identified neuronal alterations and suggested the potential use of the antiepileptic drug lamotrigine in countering AD acceleration induced by seizures.
NEUROBIOLOGY OF DISEASE
(2023)
Article
Mathematics, Applied
Salvatore Cuomo, Mariapia De Rosa, Fabio Giampaolo, Stefano Izzo, Vincenzo Schiano Di Cola
Summary: In recent years, Scientific Machine Learning (SciML) methods, particularly Physics-Informed Neural Networks (PINNs), have become popular for solving non-linear partial differential equations (PDEs). This paper numerically tackles the groundwater flow equations using a PINN approach, approximating the Dirac distribution and analyzing its computational ability in higher-dimensional cases. The effectiveness of PINNs is demonstrated through numerical experiments in hydrological applications, comparing the results with the Finite Difference Method (FDM) and highlighting the advantages of PINNs in solving PDEs without discretization.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2023)
Article
Biology
Yuri Elias Rodrigues, Cezar M. Tigaret, Helene Marie, Cian O'Donnell, Romain Veltz
Summary: Discovering the rules of synaptic plasticity is crucial for understanding brain learning. Existing models either lack flexibility to fit experimental data or are too complex to interpret. To overcome these limitations, we propose a new plasticity rule based on a geometrical readout mechanism that accurately predicts plasticity outcomes. Our model successfully reproduces various experimental conditions and suggests that spike timing irregularity strongly affects plasticity outcome. This modelling approach can be applied to other synapses to discover their plasticity rules.
Article
Mathematics, Applied
Francesco Calabro, Salvatore Cuomo, Daniela di Serafino, Giuseppe Izzo, Eleonora Messina
Summary: This paper investigates the resolution of parabolic PDEs using Extreme Learning Machine (ELMs) Neural Networks. The ELMs setting is considered, and a single hidden layer is admitted, making the ANN trainable at a modest computational cost compared to Deep Learning Neural Networks. The results of numerical experiments confirm that ELM-based solution techniques combined with BDF methods can provide high-accuracy solutions of parabolic PDEs.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Mechanics
Fabio Giampaolo, Mariapia De Rosa, Pian Qi, Stefano Izzo, Salvatore Cuomo
Summary: This study proposes a computational approach based on Physics-Informed Neural Networks (PINNs) to deal with nonlinear partial differential equation systems. Using this method, the researchers successfully solve a reaction-diffusion system involving an irreversible chemical reaction and approximate the characteristic Turing patterns for different parameter configurations.
ADVANCED MODELING AND SIMULATION IN ENGINEERING SCIENCES
(2022)
Article
Physics, Multidisciplinary
Brunello Tirozzi, Paolo Buratti
Summary: In this paper, a theory of force-free magnetic field useful for explaining the formation of convex closed sets, bounded by a magnetic separatrix in the plasma, is developed. The theory utilizes an analytic method based on a first-order expansion of the poloidal magnetic flux function, and solves the Grad-Shafranov equation to obtain an analytic expression for the solution. This work is important for understanding the application of force-free magnetic fields in laboratory and astrophysical plasmas.
Article
Computer Science, Theory & Methods
Fan Naijie, Mei Gang, Ding Zengyu, Salvatore Cuomo, Xu Nengxiong
Summary: This study evaluates the impact of the size of uniform grid cells on the efficiency of k Nearest Neighbor (kNN) search and measures the spatial distribution of scattered points using the standard deviation of point coordinates. The results indicate that as the standard deviation of point coordinates increases, the relatively optimal size of grid cells decreases and eventually converges.
INTERNATIONAL JOURNAL OF PARALLEL EMERGENT AND DISTRIBUTED SYSTEMS
(2022)