Results 91 to 100 of about 80,031 (305)

Targeting Mitochondrial Redox Signaling Promotes Neuroregeneration and Functional Recovery in a Multiple Sclerosis Model

Advanced Science, EarlyView.
Modulation of mitochondrial redox signaling by furapyrrodole activates CYB5R3 and suppresses Notch signaling, unlocking the regenerative potential of endogenous neural progenitor cells. This approach promotes neurogenesis, oligodendrogenesis, and remyelination, thereby improving neuronal function in a mouse model of multiple sclerosis and identifying ...
Yuki Narushima, Joshua Saylor, Shun Saito, Jinyan Zhou, Haruka Kawano, Shehata Anwar, Haruki Oba, Rachel Huezo, Miyu Okano, Haruki Matsuda, Makoto Kawatani, Kaori Honda, Hiroyuki Osada, Yuta Kikuchi, Masahito Ohue, Masami Ishibashi, Takayoshi Arai, Makoto Inoue, Midori A. Arai   +18 more
wiley   +1 more source

Descriptor‐Guided Computational Screening of Non‐Fullerene Acceptor Cores for Organic Solar Cells

Advanced Energy Materials, EarlyView.
We screen over 4000 non‐fullerene acceptors using their ionization energy, electron affinity, quadrupole, and dipole moments to select the top‐ten candidates for a given donor polymer. The workflow recovers known high‐performance motifs and reveals how molecular components influence material properties.
Kun‐Han Lin, J. Terence Blaskovits, Wenlan Liu, Shu‐Yi Hu, Kuei‐Jhong Lin, Sandeep Sharma, Julien Gorenflot, Martin Heeney, Frédéric Laquai, Denis Andrienko   +9 more
wiley   +1 more source

Embedded Morgan Fingerprints for More Efficient Molecular Property Predictions With Machine Learning

Advanced Intelligent Discovery, EarlyView.
High dimensionality of Morgan fingerprints causes overfitting and slow training. Embedded Morgan Fingerprint (eMFP) compresses this encoding while keeping key structural information intact. Tested on five regression models across three databases for HOMO–LUMO gap prediction, eMFP outperforms standard fingerprints, training faster on large, high ...
Emilio Nuñez‐Andrade, Isaac Vidal‐Daza, Rafael Gómez‐Bombarelli, James W. Ryan, Francisco J. Martin‐Martinez   +4 more
wiley   +1 more source

Evaluating smile aesthetic satisfaction and related smile characteristics in dental students

Journal of Oral Biology and Craniofacial Research
Aim: This study aimed to assess the association between self-rated smile satisfaction and the smile dimensions among dental students. Method: An analytical cross-sectional study was conducted on 216 Vietnamese dental students.
Vy Thi Nhat Nguyen, Nhu-Ngoc Thi Tran, Nghia-Huu Nguyen, Thuy-Duong Thi Nguyen   +3 more
doaj   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

Стимулювання інновацій та підприємництва в розумному виробництві. Аналітична записка. [PDF]

Ця аналітична записка була підготовлена в рамках проєкту SMILE (Інновації, навчальні лабораторії та підприємництво у сфері розумного виробництва) Європейського інституту інновацій і технологій в програмі “Horizon Europe” і призначена для освітніх ...
консорціум SMILE EIT HEI Innovate
core   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source

Why do we smile? On the determinants of the implied volatility function. [PDF]

We report simple regressions and Granger causality tests in order to understand the pattern of implied volatilities across exercise prices. We employ all calls and puts transacted between 16:00 and 16:45 on the Spanish IBEX-35 index from January 1994 to ...
Rubio, Gonzalo, Peña Sánchez de Rivera, Juan Ignacio, Serna, Gregorio   +2 more
core  

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source