Results 151 to 160 of about 455,228 (309)

Microphysiological Glomerular Filtration Barriers: Current Insights, Innovations, and Future Applications

open access: yesAdvanced Biology, EarlyView.
The glomerular filtration barrier (GFB) is the first step of blood filtration by the kidneys. The concerning increase of kidney diseases makes the development of new models essential. In this context, microphysiological glomerular filtration barriers focus on closely reproducing the physiological architecture of the in vivo GFB: podocytes, glomerular ...
Manon Miran   +5 more
wiley   +1 more source

Impact of Amorphous SiO2Nanoparticles on a Living Organism: Morphological, Behavioral, and Molecular Biology Implications [PDF]

open access: gold, 2014
Alfredo Ambrosone   +8 more
openalex   +1 more source

Endocranial Morphology in Metopism. [PDF]

open access: yesBiology (Basel)
Nikolova S, Toneva D, Agre G.
europepmc   +1 more source

Intersection Between Local Anesthetics and Cancer Biology: What Now? Where Are We Going?

open access: yesAdvanced Biology, EarlyView.
Local anesthetics (LAs), widely used in anesthesia, may also play a role in cancer treatment by inhibiting tumor growth, reducing metastasis, and enhancing immune responses. They modulate key pathways like AKT/mTOR and RAS/ERK while affecting angiogenesis and tumor innervation and the immune response.
Eduardo Nunez‐Rodriguez   +3 more
wiley   +1 more source

Adipose Mesenchymal Stem Cell‐Derived Exosomes in Conjunction with Roflumilast Ameliorate Chronic Kidney Disease Through the Modulation of Fibrosis and Inflammation

open access: yesAdvanced Biology, EarlyView.
The novelty of this study showed that the injection of exosomes produced from ADMSCs in combination with Roflumilast poses a more favorable therapeutic outcome for CKD induced by Adriamycin, compared to therapy with exosomes or Roflumilast alone. Roflumilast and exosomes treatment lowered the expression of the apoptotic, fibrotic, and inflammatory ...
Mohamed Ali   +5 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy