Results 121 to 130 of about 176 (168)

PERFECTA Loaded Lipid Cubosomes for 19F‐MRI: Physico‐Chemical Characterization

Chemistry – A European Journal, EarlyView.
Phytantriol‐based cubosomes loaded with PERFCTA, a fluorinated MRI probe, were developed as promising systems for imaging and drug delivery. The nanoparticles showed high PERFECTA encapsulation efficiency, strong fluorine MRI signals, and optimal colloidal stability in biological media.
Pietro Milesi, Beatrice Lucia Bona, Cristina Chirizzi, Marco Campanile, Pompea Del Vecchio, Marc Schmutz, Valerie Sartor, Debora Berti, Pierangelo Metrangolo, Francesca Baldelli Bombelli, Barbara Lonetti   +10 more
wiley   +1 more source

Exploring the neuromagnetic signatures of cognitive decline from mild cognitive impairment to Alzheimer's disease dementia. [PDF]

EBioMedicine
Gaubert S, Garces P, Hipp J, Bruña R, Lopéz ME, Maestu F, Vaghari D, Henson R, Paquet C, Engemann DA.   +9 more
europepmc   +1 more source

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

The Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales, Francisco Izaias da Silva Aires, Paulo Gonçalves de Sousa Junior, Calebe Da Rocha Silva, Emanuel Lino Rodrigues, Maria Cristiane Martins de Souza, José C. S. dos Santos   +6 more
wiley   +1 more source

Precision Medicine Gene Network Analyser: part I-cancer driver gene identification through network topology and ensemble machine learning. [PDF]

Genomics Inform
Siddalingappa R, Hussain S, S D, Dheerendra P, Gornale S, B L M, Kothandan G.   +6 more
europepmc   +1 more source

Pitfalls of machine learning models for protein-protein interactions

, 2022
Lannelongue L, Inouye M.
europepmc   +1 more source

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

The Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin, Clémence Fauteux‐Lefebvre, Jules Thibault   +2 more
wiley   +1 more source

Vine copula knockoffs for variable selection in gene expression studies

Canadian Journal of Statistics, EarlyView.
Abstract Identifying clinical and genetic markers is essential for stratifying cancer patients by survival outcomes and guiding personalized treatment strategies. However, gene expression studies often involve high‐dimensional predictors with mixed data types and complex dependence, which complicates reliable variable selection.
José Ulises Márquez Urbina, Alejandro Román Vásquez, Graciela González Farías, Gabriel Escarela   +3 more
wiley   +1 more source

BugPrioritizeAI for multimodal test case prioritisation using bug reports, code changes, and test metadata. [PDF]

Sci Rep
Kalyani P, Rao CP, Goparaju B, Babu KK, Kandimalla PCR.   +4 more
europepmc   +1 more source

The Role of Business R&D in Environmental Sustainability: Evidence From the Nordic Countries

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT As environmental sustainability becomes an increasingly important concern for advanced economies, the role of business innovation in relation to environmental outcomes has attracted increasing attention. This study examines the relationship between business enterprise research and development (BERD) and environmental sustainability in the ...
Abdullah Emre Caglar, Mehmet Ulug, Ismail Demirdag   +2 more
wiley   +1 more source

The AI Sustainability Paradox: How Verification and Regulation Synergize to Curb Greenwashing in Emerging Markets

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Artificial intelligence (AI) reflects a paradox for corporate sustainability: it provides tools for genuine socio‐economic improvement and enables greenwashing at scale. This study examines this duality in emerging Asian markets, where rapid AI adoption coincides with evolving regulatory regimes.
Ashutosh Yadav, Simplice A. Asongu
wiley   +1 more source