Results 221 to 230 of about 301,899 (294)

siRNA Delivery via Cross‐Linked Gelatin Microparticles Enables Targeted Modulation of Osteogenic‐Vascular Cross‐Talk: An Advanced Human 3D in Vitro Test System for Therapeutic siRNA

Advanced Healthcare Materials, EarlyView.
Osteogenic‐angiogenic cross‐talk is a vital prerequisite for vascularized bone regeneration. In this study, we investigated the effects of siRNA‐mediated silencing of two inhibitory proteins, Chordin and WWP‐1, via CaP‐NP‐loaded gelatin microparticles in osteogenically differentiated microtissues.
Franziska Mitrach, Jonas Kubat, Stefan Simm, Alexandra H. Springwald, Burak Demir, Anton Liebezeit, Michael C. Hacker, Michaela Schulz‐Siegmund   +7 more
wiley   +1 more source

Genomic prediction in a small barley population can benefit from training on related populations. [PDF]

G3 (Bethesda)
Skovbjerg CK, Sarup P, Wahlström EM, Jensen JD, Olesen L, Orabi J, Jensen J, Ramstein GP, Jahoor A.   +8 more
europepmc   +1 more source

Optimal Use Of Phenotypic Data For Breeding Using Genomic Predictions

, 2014
Nicolas Heslot
openalex   +1 more source

Evaluation of the Dual Impact of Nanotechnologies on Health and Environment Through Alternative Bridging Models

Advanced Healthcare Materials, EarlyView.
This review explores how alternative invertebrate and small‐vertebrate models advance the evaluation of nanomaterials across medicine and environmental science. By bridging cellular and organismal levels, these models enable integrated assessment of toxicity, biodistribution, and therapeutic performance.
Marie Celine Lefevre, Margherita Bernardeschi, Matteo Battaglini, Gianni Ciofani   +3 more
wiley   +1 more source

Improving Genomic Prediction Using High-Dimensional Secondary Phenotypes: The Genetic Latent Factor Approach. [PDF]

Biom J
Melsen KAC, Kunst JF, Crossa J, Krause MR, van Eeuwijk FA, Kruijer W, Peeters CFW.   +6 more
europepmc   +1 more source

Machine learning for genomic and pedigree prediction in sugarcane [PDF]

Minoru Inamori, Tatsuro Kimura, Masaaki Mori, Yusuke Tarumoto, Taiichiro Hattori, Michiko Hayano, Makoto Umeda, Hiroyoshi Iwata   +7 more
openalex   +1 more source

PiP‐Plex: A Particle‐in‐Particle System for Multiplexed Quantification of Proteins Secreted by Single Cells

Advanced Materials, EarlyView.
Detecting proteins secreted by a single cell while retaining its viability remains challenging. A particles‐in‐particle (PiPs) system made by co‐encapsulating barcoded microparticles (BMPs) with a single cell inside an alginate hydrogel particle is introduced.
Félix Lussier, Byeong‐Ui Moon, Mojra Janta‐Polczynski, Yonatan Morocz, Fabian Svahn, Molly Shen, Ljuboje Lukic, Lidija Malic, Teodor Veres, Andy Ng, David Juncker   +10 more
wiley   +1 more source

QTL detection and genomic prediction for resistance to anthracnose in alfalfa (Medicago sativa). [PDF]

Plant Genome
Pégard M, Gréard C, Grelier M, Gras MC, Saint-Pierre L, Tharel B, Barre P, Julier B.   +7 more
europepmc   +1 more source

Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re‐Usability: A Position Paper From the Nanosafety Community

Advanced Sustainable Systems, EarlyView.
Nanosafety data provide a guiding example for establishing best practices in data management, aligning with FAIR principles and quality criteria. This review explores existing quality assessment approaches for reliability, relevance, and completeness, emphasizing the need for harmonization and adaptation to nanomaterials and advanced materials. The aim
Verónica I. Dumit, Irini Furxhi, Penny Nymark, Antreas Afantitis, Ammar Ammar, Monica J. B. Amorim, Dalila Antunes, Svetlana Avramova, Chiara L. Battistelli, Gianpietro Basei, Cecilia Bossa, Emil Cimpan, Mihaela Roxana Cimpan, Dmitri Ciornii, Anna Costa, Camilla Delpivo, Maria Dusinska, Ana Sofia Fonseca, Steffi Friedrichs, Vasile‐Dan Hodoroaba, Danail Hristozov, Panagiotis Isigonis, Nina Jeliazkova, Nikolay Kochev, Eva Kranjc, Dieter Maier, Georgia Melagraki, Anastasios G. Papadiamantis, Tomasz Puzyn, Hubert Rauscher, Katie Reilly, Araceli Sánchez Jiménez, Janeck J. Scott‐Fordsmand, Neeraj Shandilya, Hyun Kil Shin, Gergana Tancheva, Jeaphianne P. M. van Rijn, Egon L. Willighagen, Ewelina Wyrzykowska, Martine I. Bakker, Damjana Drobne, Thomas E. Exner, Martin Himly, Iseult Lynch   +43 more
wiley   +1 more source

Comparative evaluation of SNP-weighted, Bayesian, and machine learning models for genomic prediction in Holstein cattle. [PDF]

BMC Genomics
Zheng W, Zhang Q, He J, Han B, Zhang Q, Sun D.   +5 more
europepmc   +1 more source