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This study establishes a streamlined, scalable, and reproducible workflow for the sustainable and computationally guided development of nanostructured lipid carriers (NLCs) by integrating Quality by Design and molecular simulations with sustainable approaches in formulating plant-based NLCs loaded with curcumin (CUR) as a model natural molecule. Our approach aims to accelerate the screening, optimization, and development processes of nanoformulations while maintaining drug loading and stability and adhering to green chemistry principles. A combined-mixture process and a 3 Factorial/RSM experimental design were used. NLCs were prepared using high-shear hot homogenization at 12,000 RPM for 10 min. Following characterization, NLCs were optimized and evaluated. Molecular dynamics simulations were conducted using GROMACS to study the interaction between CUR and NLCs. The optimized CUR-NLCs had a particle size (80.28 - 87.31 nm), PDI (0.239 - 0.276), and Zeta potential (-11.63 to -14.67 mV), with an encapsulation efficiency (53 - 63 %). The optimized CUR-NLCs demonstrated desirable properties while using plant-based materials and sustainable methods. Employing molecular simulations provided insights into the assembly of NLCs and CUR interactions with their components. The proof-of-concept successfully bridged process optimization with advanced computational pharmaceutics, ensuring that digital transformation and sustainability are at the core of future nanoformulation research and industrial adoption.
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http://dx.doi.org/10.1016/j.ijpharm.2025.125797 | DOI Listing |
Cereb Cortex
August 2025
Aix-Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106, Marseille 13005, France.
Over three decades, statistical parametric mapping has transformed neuroimaging from descriptive mapping to causal inference, placing generative models at the core of causal explanations for brain function. It inspired to a large degree The Virtual Brain, which builds subject-specific digital twins from multimodal data, enabling brain simulations and exploration. Both frameworks converge at parameter estimation, where model and data meet, providing the mathematical manifestation of cause-effect in pathophysiology.
View Article and Find Full Text PDFSmall
September 2025
Guangdong Provincial Key Laboratory for Processing and Forming of Advanced Metallic Materials, South China University of Technology, Guangzhou, 510640, China.
In modern micro/nano fabrication, 3D printing technology drives industry transformation. However, existing technologies face bottlenecks in improving process efficiency and precision, while also struggling to achieve accurate fabrication of composite 3D microstructures. This study proposes a microlens self-focusing printing technique that integrates digital light processing (DLP) 3D printing with an optical microscope platform.
View Article and Find Full Text PDFAppl Radiat Isot
September 2025
Kahramanmaraş İstiklal University, Department of Energy Systems Engineering, Kahramanmaraş, Türkiye.
The rapid advancement of three-dimensional (3D) printing technologies has significantly expanded their potential applications such as sensors and detector technology. In this study, the gamma-ray shielding performance of ulexite-doped composite resins fabricated via Digital Light Processing (DLP) 3D printing was experimentally investigated to evaluate radiation attenuation capacity. Composite resins containing different ulexite loadings (0, 1, 3, and 5 wt%) were exposed to gamma rays at energies of 356, 662, 1173, and 1333 keV to evaluate their attenuation characteristics.
View Article and Find Full Text PDFSci Prog
September 2025
School of Information Science and Technology, Hangzhou Normal University, Hangzhou, China.
At present, significant progress has been made in the research of image encryption, but there are still some issues that need to be explored in key space, password generation and security verification, encryption schemes, and other aspects. Aiming at this, a digital image encryption algorithm was developed in this paper. This algorithm integrates six-dimensional cellular neural network with generalized chaos to generate pseudo-random numbers to generate the plaintext-related ciphers.
View Article and Find Full Text PDFTheor Appl Genet
September 2025
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
The German Federal Ex Situ Genebank for Agricultural and Horticultural Crops (IPK) harbours over 3000 pea plant genetic resources (PGRs), backed up by corresponding information across 16 key agronomic and economical traits. The unbalanced structure and inconsistent format of this historical data has precluded effective leverage of genebank accessions, despite the opportunities contained in its genetic diversity. Therefore, a three-step statistical approach founded in linear mixed models was implemented to enable a rigorous and targeted data curation.
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