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Impact of apolipoprotein E isoforms on sporadic Alzheimer's disease:beyond the role of amyloid beta

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Neural Regeneration Research 2024年第1期19卷 80-83页

作者： Madia Lozupone francesco Panza Neurodegenerative Disease Unit Department of Basic MedicineNeuroscienceand Sense OrgansUniversity of Bari Aldo MoroBariItaly Unit of Research Methodology and Data Sciences for Population Health National Institute of Gastroenterology“Saverio de Bellis”Research HospitalCastellana GrotteBariItaly

The impact of apolipoprotein E(ApoE)isoforms on sporadic Alzheimer's disease has long been studied;however,the influences of apolipoprotein E gene(APOE)on healthy and pathological human brains are not fully understood.ApoE exists as three common isoforms(ApoE2,ApoE3,and ApoE4),which differ in two amino acid residues.Traditionally,ApoE binds cholesterol and phospholipids and ApoE isoforms display diffe rent affinities for their receptors,lipids transport and distribution in the brain and periphery.The role of ApoE in the human depends on ApoE isoforms,brain regions,aging,and neural injury.APOE E4 is the strongest genetic risk factor for sporadic Alzheimer's disease,considering its role in influencing amyloid-beta metabolism.The exact mechanisms by which APOE gene variants may increase or decrease Alzheimer's disease risk are not fully understood,but APOE was also known to affect directly and indirectly tau-mediated neurodegeneration,lipids metabolism,neurovascular unit,and microglial function.Consistent with the biological function of ApoE,ApoE4 isoform significantly alte red signaling pathways associated with cholesterol homeostasis,transport,and myelination.Also,the rare protective APOE variants confirm that ApoE plays an important role in Alzheimer's disease pathogenesis.The objectives of the present mini-review were to describe classical and new roles of various ApoE isoforms in Alzheimer's disease pathophysiology beyond the deposition of amyloid-beta and to establish a functional link between APOE,brain function,and memory,from a molecular to a clinical level.APOE genotype also exerted a heterogeneous effect on clinical Alzheimer's disease phenotype and its outcomes.Not only in learning and memory but also in neuro psychiatric symptoms that occur in a premorbid condition.Cla rifying the relationships between Alzheimer's disease-related pathology with neuropsychiatric symptoms,particularly suicidal ideation in Alzheimer's disease patients,may be useful for elucidating also the underlying pathophysiological pro

关键词： Alzheimer's disease amyloid-beta apolipoprotein E dementia glymphatic transport lipids neuropsychiatric symptoms neurovascular unit tau protein

Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 141-156页

作者： Luigi D’Alfonso francesco Giannini Giuseppe Franzè Giuseppe Fedele francesco Pupo Giancarlo Fortino IEEE the Department of Computer Engineering ModelingElectronics and SystemsUniversitàdella CalabriaVia Pietro BucciCubo 42-CRende(CS)87036Italy the Department of Mechanical Engineering Energy Engineering and ManagementUniversitàdella CalabriaVia Pietro BucciCubo 42-CRende(CS)87036Italy

In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the pro

关键词： Distributed model predictive control distributed reinforcement learning routing decisions urban road networks

Impact characterization on thin structures using machine learning approaches

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Chinese Journal of Aeronautics 2024年第2期37卷 30-44页

作者： Flavio DIPIETRANGELO francesco NICASSIO Gennaro SCARSELLI Department of Engineering for Innovation University of SalentoLecce 73100Italy

Machine learning algorithms are trained and compared to identify and to characterise the impact on typical aerospace panels of different geometry.Experimental activities are conducted to build a proper impacts’dataset.Polynomial regression algorithm and artificial neural network are applied and optimised to panels without stringer to test their capability to identify the impacts.Subsequently,the algorithms are applied to panels reinforced with stringers that represent a significant increase of complexity in terms of dynamic features of the system to test:the focus is not only on the impact position’s detection but also on the event’s severity.After the identification of the best algorithm,the corresponding machine learning model is deployed on an ARM processor minicomputer,implementing an impact detection system,able to be installed on board an aerial vehicle,making it a smart aircraft equipped with an artificial intelligence decision-making system.

关键词： Artificial neural network Impact localisation Machine learning Polynomial regression Structural health monitoring

Impact of cattle density on the structure and natural regeneration of a turkey oak stand on an agrosilvopastoral farm in central Italy

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Journal of Forestry Research 2024年第1期35卷 168-182页

作者： Alessandra Pacini francesco Pelleri francesco Marini Alberto Maltoni Barbara Mariotti Gianluigi Mazza Maria Chiara Manetti Department of Agriculture FoodEnvironmentand ForestryUniversity of Florence50144 FlorenceItaly CREA Research Centre for Forestry and Wood 52100 ArezzoItaly PEFC Programme for the Endorsement of Forest Certification 06135 PerugiaItaly

On an agrosilvopastoral farm in central Italy where Maremmana cattle graze in Turkey oak forests,we evaluated the impact of different livestock densities on stand structure,tree diversity and natural regeneration in four types of grazed areas based on the grazing regime adopted:calf-grazed,high-intensity-grazed,low-intensity-grazed,ungrazed control.For each area,we set up three permanent circular plots(radius of 15 m)to survey the structural and dasometric characteristics of the overstorey,understorey,and regeneration layer.The results showed that grazing negatively affected the complexity of the forest structure and its potential to regenerate and maintain a high level of biodiversity.The differences in stand structure observed between the grazing areas were closely related to livestock density.The most sensitive components of the system were the understorey and the regeneration layers.Contrarily,the current grazing management did not affect the dominant tree structure or its composition.Our findings identified medium-term monitoring and regeneration management as the two significant aspects to consider when assessing sustainable livestock.New forests can be established by excluding graz-ing for about 20–25 years.

关键词： Agroforestry Stand structure Regeneration Tree biodiversity Grazing intensity

Polymerization of 1,3-Butadiene with Catalysts Based on Cobalt Dichloride Complexes with Aminophosphines: Switching the Regioselectivity by Varying the MAO/Co Molar Ratio

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Chinese Journal of Polymer Science 2024年第4期42卷 501-510页

作者： Giovanni Ricci Anna Sommazzi francesco Masi Alessandra Forni CNR-Istituto di Scienze e Tecnologie Molecolari“Giulio Natta”(SCITEC) via A.Corti 1220133MilanoItaly Viale Giovanni XXIII 34 I-28100NovaraNOItaly Via Galvani 7 I-26866Sant’Angelo LodigianoLOItaly CNR-Istituto di Scienze e Tecnologie Molecolari“Giulio Natta”(SCITEC) via C.Golgi 1920133MilanoItaly

Several novel cobalt dichloride complexes with amino-phosphine bidentate ligands were synthesized and characterized.For some of them single crystals were obtained and their molecular structure was determined by X-ray diffraction method.All the complexes were then used in combination with MAO for the polymerization of 1,3-butadiene,obtaining polymers with different structures(i.e.,predominantly 1,2 or cis-1,4)mainly depending on the type of ligand and on the MAO/Co molar ratio.The behavior of these novel catalysts was compared with that exhibited,in the polymerization of the same monomer,by the systems CoCl_(2)(PR3)2-MAO and CoCl_(2)(PRPh2)2-MAO(R=alkyl or cycloalkyl group),and by the systems based on cobalt dichloride complexes with various bi-and tridentate ligands(e.g.,diphosphines,bis-imines,pyridyl-imines,bis-iminopyridines).The comparison between the different systems allowed us to make some clarity about the actual and effective role played by the various types of ligands in the polymerization of conjugated dienes with catalytic systems CoCl_(2)(L)-MAO,in which L=mono-,bi-,or tri-dentate ligand.

关键词： 1,3-Butadiene Stereospecific polymerization Cobalt catalysts Regioselectivity Aminophosphine ligands Crystal structures Chelate rings

Developmental toxicity assessment of neonicotinoids and organophosphate esters with a human embryonic stem cell-and metabolism-based fast-screening model

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Journal of Environmental Sciences 2024年第3期137卷 370-381页

作者： Shuxian Zhang Miaomiao Zhao Shichang Li Renjun Yang Nuoya Yin francesco Faiola State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China

In recent years,neonicotinoids(NEOs)and organophosphate esters(OPEs)have been widely used as substitutes for traditional pesticides and brominated fame-retardants,respectively.Previous studies have shown that those compounds can be frequently detected in environmental and human samples,are able to penetrate the placental barrier,and are toxic to animals.Thus,it is reasonable to speculate that NEOs and OPEs may have potential adverse effects in humans,especially during development.We employed a human embryonic stem cell differentiation-and liver S9 fraction metabolism-based fast screening model to assess the potential embryonic toxicity of those two types of chemicals.We show that four NEO and five OPE prototypes targeted mostly ectoderm specification,as neural ectoderm and neural crest genes were down-regulated,and surface ectoderm and placode markers up-regulated.Human liver S9 fraction's treatment could generally reduce the effects of the chemicals,except in a few specific instances,indicating the liver may detoxify NEOs and OPEs.Our findings suggest that NEOs and OPEs interfere with human early embryonic development.

关键词： Neonicotinoids Organophosphate esters Human embryonic stem cells Fast screening model Developmental toxicity

Acute symptomatic seizures in newborns:a narrative review

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Acta Epileptologica 2024年第1期7卷 1-13页

作者： Carlotta Spagnoli francesco Pisani Child Neurology Unit Pediatric DepartmentAzienda USL-IRCCS Di Reggio EmiliaReggio Emilia42123Italy Child Neurology and Psychiatry Unit Department of Human NeurosciencesSapienza University of RomeRome00185Italy Azienda Ospedaliero Universitaria Policlinico Umberto I Rome00185Italy

Acute symptomatic seizures are the main sign of neurological dysfunction in newborns.This is linked to the unique characteristics of the neonatal brain,making it hyperexcitable compared to older ages,and to the common occurrence of some forms of acquired brain injury,namely hypoxic-ischemic encephalopathy.In this narrative review we will provide an overview of neonatal seizures definition,their main underlying etiologies,diagnostic work-up and differential diagnoses,and will discuss about therapeutic options and prognostic outlook.The latest publications from the ILAE Task Force on Neonatal Seizures will be presented and discussed.Of note,they highlight the current lack of robust evidence in this field of clinical neurology.We will also report on specificities pertaining to low-and-middle income countries in terms of incidence,main etiologies and diagnosis.The possibilities offered by telemedicine and automated seizures detection will also be summarized in order to provide a framework for future directions in seizures diagnosis and management with a global perspective.Many challenges and opportunities for improving identification,monitoring and treatment of acute symptomatic seizures in newborns exist.All current caveats potentially represent different lines of research with the aim to provide better care and reach a deeper understanding of this important topic of neonatal neurology.

关键词： Acute symptomatic Neonatal seizures EEG Newborn Outcome Diagnosis Etiologies

A chitosan-based antibacterial hydrogel with injectable and self-healing capabilities

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Marine Life Science & Technology 2024年第1期6卷 115-125页

作者： Rui Chen Yanan Hao Secundo francesco Xiangzhao Mao Wen-Can Huang State Key Laboratory of Marine Food Processing and Safety Control College of Food Science and EngineeringOcean University of ChinaQingdao 266404China Laboratory for Marine Drugs and Bioproducts of Qingdao National Laboratory for Marine Science and Technology Qingdao 266237China Qingdao Key Laboratory of Food Biotechnology Qingdao 266404China Key Laboratory of Biological Processing of Aquatic Products China National Light IndustryQingdao 266404China Istituto di Scienze e Tecnologie Chimiche“Giulio Natta” Consiglio Nazionale delle Ricerche via Mario Bianco 920131 MilanItaly

The presence of bacteria directly affects wound healing.Chitosan-based hydrogel biomaterials are a solution as they offer advantages for wound-healing applications due to their strong antimicrobial properties.Here,a double-cross-linking chitosanbased hydrogel with antibacterial,self-healing,and injectable properties is reported.Thiolated chitosan was successfully prepared,and the thiolated chitosan molecules were cross-linked by Ag-S coordination to form a supramolecular hydrogel.Subsequently,the amine groups in the thiolated chitosan covalently cross-linked with genipin to further promote hydrogel formation.In vitro experimental results indicate that hydrogel can release Ag^(+)over an extended time,achieving an antibacterial rate of over 99% against Escherichia coli and Staphylococcus aureus.Due to the reversible and dynamic feature of Ag-S coordination,an antibacterial hydrogel exhibited injectable and self-healing capabilities.Additionally,the hydrogel showed excellent biocompatibility and biodegradability.

关键词： Hydrogel Chitosan Silver ion Cross-linking Antibacterial

Deep Learning for Financial Time Series Prediction:A State-of-the-Art Review of Standalone and HybridModels

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 187-224页

作者： Weisi Chen Walayat Hussain francesco Cauteruccio Xu Zhang School of Software Engineering Xiamen University of TechnologyXiamen361024China Peter Faber Business School Australian Catholic UniversityNorth Sydney2060Australia Department of Information Engineering Polytechnic University of MarcheAncona60121Italy

Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction performance.Currently,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and implemented.This review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other techniques.For illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related processes.Among the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only model.Some remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency predictions.The principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and to highlight future research directions.

关键词： Financial time series prediction convolutional neural network long short-term memory deep learning attention mechanism finance