Results 121 to 130 of about 5,053,091 (357)

Letter: Proton beam therapy for acromegaly. [PDF]

, 1975
T. D. R. Hockaday, A. H. Laing, R. B. Welbourn, M. Hartog   +3 more
openalex   +1 more source

Biomaterial Strategies for Targeted Intracellular Delivery to Phagocytes

Advanced Functional Materials, EarlyView.
Phagocytes are essential to a functional immune system, and their behavior defines disease outcomes. Engineered particles offer a strategic opportunity to target phagocytes, harnessing inflammatory modulation in disease. By tuning features like size, shape, and surface, these systems can modulate immune responses and improve targeted treatment for a ...
Kaitlyn E. Woodworth, Neal I. Callaghan, Locke Davenport Huyer   +2 more
wiley   +1 more source

Skull base chordoma treated with proton therapy: A systematic review

Surgical neurology international, 2019
Background: Chordoma located in the skull base is usually a challenging surgical condition. It is often not possible to achieve gross total resection. Residual tumors have been treated with adjuvant focal radiation therapy employing high-energy particles
M. Alahmari, Y. Temel
semanticscholar   +1 more source

Smart Nanogels as Enzyme‐Driven Nanomotors for Navigating Viscous Physiological Barriers

Advanced Functional Materials, EarlyView.
Two families of urease‐powered nanomotors (NMs), with and without a p‐(2‐hydroxyethyl methacrylate) (p‐HEMA) shell, have been successfully prepared. Both types exhibit effective motion in highly viscous synovial fluid media at low urea concentrations (25 mM).
David Esporrín‐Ubieto, Noelia Ruiz‐González, Valerio Di Carlo, Daniel Sánchez‐deAlcázar, Florencia Lezcano, Anna Pushkareva Fazullina, Samuel Sánchez   +6 more
wiley   +1 more source

A comparison of the quality assurance of four dosimetric tools for intensity modulated radiation therapy

Radiology and Oncology, 2015
Background. This study was designed to compare the quality assurance (QA) results of four dosimetric tools used for intensity modulated radiation therapy (IMRT) and to suggest universal criteria for the passing rate in QA, irrespective of the dosimetric ...
Son Jaeman, Baek Taesung, Lee Boram, Shin Dongho, Park Sung Yong, Park Jeonghoon, Lim Young Kyung, Lee Se Byeong, Kim Jooyoung, Yoon Myonggeun   +9 more
doaj   +1 more source

Protons or megavoltage X-rays as boost therapy for patients irradiated for localized prostatic carcinoma an early phase I/II comparison [PDF]

, 1983
J. A. Duttenhaver, William U. Shipley, Theresa Perrone, Lynn Verhey, Michael Goitein, John E. Munzenrider, George R. Prout, Edward C. Parkhurst, Herman D. Suit   +8 more
openalex   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Correction: Feasibility of linac-based fractionated stereotactic radiotherapy and stereotactic radiosurgery for patients with up to ten brain metastases

Radiation Oncology, 2023
Masanori Hirata, Kazuaki Yasui, Naofumi Oota, Hirofumi Ogawa, Tsuyoshi Onoe, Sayo Maki, Yusuke Ito, Kenji Hayashi, Hirofumi Asakura, Shigeyuki Murayama, Koichi Mitsuya, Shoichi Deguchi, Katsumasa Nakamura, Nakamasa Hayashi, Tetsuo Nishimura, Hideyuki Harada   +15 more
doaj   +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

Comparison of Neutron Therapy Beams Produced by 50 MEV Deuterons and 65 MEV Protons on Beryllium [PDF]

, 1982
S. Vynckier, P. Pihet, M. Octave-Prignot, J. P. Meulders, André Wambersie   +4 more
openalex   +1 more source