Results 121 to 130 of about 1,914 (212)

The Association of Amyloid‐β and Tau With Synaptic Dysfunction in Alzheimer's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the relative contributions of amyloid and tau to synaptic dysfunction in Alzheimer's disease (AD). Methods We included 109 cognitively unimpaired and impaired individuals from the Geneva Memory Center with available CSF synaptic biomarkers (neurogranin, SNAP‐25, GAP‐43). Participants were stratified according to amyloid (A)
Fausto Roveta, Augusto J. Mendes, Valentina Garibotto, Cecilia Boccalini, Aurelien Lathuiliere, Innocenzo Rainero, Elisa Rubino, Henrik Zetterberg, Nicholas J. Ashton, Federica Ribaldi, Giovanni B. Frisoni, for the Alzheimer's Disease Neuroimaging Initiative   +11 more
wiley   +1 more source

Improving the Diagnostic Accuracy of Plasma Alzheimer's Disease Biomarkers With Objective and Subjective Cognitive Screening

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Blood‐based biomarkers are increasingly used to identify Alzheimer's disease (AD) pathology and may play an important role in early disease screening and participant selection for clinical trials. However, their performance across stages of cognitive impairment remains unclear. This study examined whether plasma biomarkers differ in
Maryam Abdolmaleki, Leslie S. Gaynor, Dandan Liu, Timothy J. Hohman, Katherine A. Gifford, Henrik Zetterberg, Angela L. Jefferson, Corey J. Bolton   +7 more
wiley   +1 more source

Four‐Year Cognitive Outcomes in Multiple Sclerosis: Associations With Lesion Myelin Integrity

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Cognitive impairment is prevalent in patients with multiple sclerosis (MS) but whether lesion myelin integrity influences future cognitive outcomes remains unclear. We investigated the relationship between baseline lesion myelin water fraction (MWF) and cognitive performance 4 years later.
Iliana Pliska‐Bloch, Hannah Schwartz, Kimberly H. Markowitz, Abhishek Jaywant, Christopher D. Hildenbrand, Jai Perumal, Ulrike W. Kaunzner, Thanh D. Nguyen, Sandra Hurtado Rúa, Susan A. Gauthier   +9 more
wiley   +1 more source

Unsupervised Machine Learning Identifies Shared Biomechanical and Clinical Variation in Individuals with Knee Osteoarthritis and High Body Mass Index

Arthritis Care &Research, EarlyView.
Objective High body mass index (BMI ≥ 27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck, J. Elyse Borgert, Hyeon Lee, Liubov Arbeeva, Yvonne M. Golightly, Richard F. Loeser, Leigh F. Callahan, Stephen P. Messier, Brian Pietrosimone, Amanda E. Nelson, James S. Marron   +10 more
wiley   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Mechanochemical Synthesis and Characterization of Nanostructured ErB4 and NdB4 Rare‐Earth Tetraborides

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
ErB4 and NdB4 nanostructured powders are produced by mechanochemical synthesis. 5 h mechanical alloying and 4 M HCl acid leaching are used in the production. ErB4 and NdB4 powders exhibit maximum magnetization of 0.4726 emu g−1 accompanied with an antiferromagnetic‐to‐paramagnetic phase transition at about TN = 18 K and 0.132 emu g−1 with a maximum at ...
Burçak Boztemur, Faruk Kaya, Bora Derin, Mustafa Lütfi Öveçoğlu, Ju Li, Duygu Ağaoğulları   +5 more
wiley   +1 more source

Revisiting Stability Criteria in Ball‐Milled High‐Entropy Alloys: Do Hume–Rothery and Thermodynamic Rules Equally Apply?

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
The stability criteria affecting the formation of high‐entropy alloys, particularly focusing in supersaturated solid solutions produced by mechanical alloying, are analyzed. Criteria based on Hume–Rothery rules are distinguished from those derived from thermodynamic relations. The formers are generally applicable to mechanically alloyed samples.
Javier S. Blázquez, Alejandro F. Manchón‐Gordón, Antonio Vidal‐Crespo, Rafael Caballero‐Flores, Jhon J. Ipus, Clara F. Conde   +5 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Microstructural Evolution and Vacancy Defect Formation in Mn–Mo–Ni RPV Steel Under Low Cycle Fatigue: Insights From EBSD and PALS

Advanced Engineering Materials, EarlyView.
Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar, Dhanadeep Dutta, G. Bharat Reddy   +2 more
wiley   +1 more source