Results 221 to 230 of about 1,244,192 (396)

Levey, D.J., Silva, W.R., and Galetti, M. Seed dispersal and frugivory: ecology, evolution and conservation [PDF]

, 2002
Stephen G. Compton
openalex   +1 more source

Fluorescent Nanodiamonds Based Theranostic Platform for pH‐Sensitive Drug Delivery and Quantum Sensing

Advanced Functional Materials, EarlyView.
A multifunctional nanodiamond platform enables pH‐triggered Diazoxide (DZX) delivery and quantum sensing of subcellular radical dynamics in triple‐negative breast cancer cells. Diamond relaxometry revealed reduced lysosomal radicals during DZX‐induced mitochondrial radical elevation, providing insights into redox modulation and organelle‐ resolved ...
Kaiqui Wu, Siyu Fan, Yue Zhang, Willem Woudstra, Thomas Mulder, Laurens Boscher Navarro, Jur van Dijken, Katja Loos, Romana Schirhagl   +8 more
wiley   +1 more source

Estimated epizoochory seed dispersal distances by grazing yak across seasons in an alpine meadow. [PDF]

Front Plant Sci
Wang S, Hou F.
europepmc   +1 more source

Earliest evidence for fruit consumption and potential seed dispersal by birds. [PDF]

Elife, 2022
Hu H, Wang Y, McDonald PG, Wroe S, O'Connor JK, Bjarnason A, Bevitt JJ, Yin X, Zheng X, Zhou Z, Benson RBJ.   +10 more
europepmc   +1 more source

Let the Seeds Fall Where They May: Investigating the Effect of Landscape Features on Fine-Scale Seed Dispersal

, 2000
Monica R. Grasty
openalex   +2 more sources

Modelling the impact of colonisation on genetic diversity and differentiation of forest trees: interaction of life cycle, pollen flow and seed long-distance dispersal [PDF]

, 2003
Frédéric Austerlitz, Pauline Garnier‐géré   +1 more
openalex   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Can Predation Pressure Help Explain the Curious Evolution of Ballistic Seed Dispersal? [PDF]

Ecol Evol
Sharpe CR, Ruxton GD.
europepmc   +1 more source

Long-range seed dispersal enables almost stationary patterns in a model for dryland vegetation. [PDF]

J Math Biol, 2022
Eigentler L, Sherratt JA.
europepmc   +1 more source

Seed dispersal by animals: exact identification of source trees with endocarp DNA microsatellites

, 2001
José A. Godoy, Pedro Jordano
openalex   +2 more sources