Antibody-drug conjugates (ADCs) are a family of targeted therapeutic agents for the treatment of cancer. ADC development is a rapidly expanding field of research, with over 80 ADCs currently in clinical development and eleven ADCs (nine containing small-molecule payloads and two with biological toxins) approved for use by the FDA. Compared to traditional small-molecule approaches, ADCs offer enhanced targeting of cancer cells along with reduced toxic side effects, making them an attractive prospect in the field of oncology. To this end, this tutorial review aims to serve as a reference material for ADCs and give readers a comprehensive understanding of ADCs; it explores and explains each ADC component (monoclonal antibody, linker moiety and cytotoxic payload) individually, highlights several EMA- and FDA-approved ADCs by way of case studies and offers a brief future perspective on the field of ADC research.
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http://dx.doi.org/10.3390/molecules26102943 | DOI Listing |
Behav Anal Pract
December 2024
Simmons University, Boston, MA USA.
Unlabelled: One of the most critical intervention strategies when working with individuals with significant language delays associated with autism spectrum disorder and related developmental delays is teaching mands. For mand training to be effective, an establishing operation (EO) must be in effect, yet EOs are often difficult to observe. Before learning to mand, an individual may point to or approach a reinforcer, which likely indicates an EO related to that reinforcer, and may be considered an indicating response (IR).
View Article and Find Full Text PDFBehav Anal Pract
December 2024
Department of Behavior Analysis, Simmons University, Boston, MA USA.
Unlabelled: Mands are consistently described as critical learning targets for members of vulnerable populations in need of language intervention (Ala'i-Rosales et al., 2018; Michael, 1988; Sundberg, 2004). Reviews of the literature demonstrate a prevalence of the mand in the applied literature (e.
View Article and Find Full Text PDFBiomed Eng Lett
January 2025
Department of Computer Engineering, Kwangwoon University, Seoul, 01897 Republic of Korea.
Robotic systems rely on spatio-temporal information to solve control tasks. With advancements in deep neural networks, reinforcement learning has significantly enhanced the performance of control tasks by leveraging deep learning techniques. However, as deep neural networks grow in complexity, they consume more energy and introduce greater latency.
View Article and Find Full Text PDFChemistry
January 2025
Division of Molecular Imaging and Photonics, Department of Chemistry, Katholieke Universiteit Leuven, Celestijnenlaan 200F, 3001, Leuven, Belgium.
Fluorescence spectroscopy and related techniques benefit from exceptional sensitivity and have become engrained in a variety of fields from biosciences to materials sciences. Measuring time-domain fluorescence decays is nowadays a routine task in many laboratories across these different fields. Perhaps surprisingly, a correct data analysis of these fluorescence decay curves presents a formidable challenge and requires extensive insight in the problems associated with fitting this type of data.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, USA.
The implementation of clinical 7T MRI presents both opportunities and challenges for advanced medical imaging. This tutorial provides practical considerations and experiences with 7T MRI in clinical settings. We first explore the history and evolution of MRI technology, highlighting the benefits of increased signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and susceptibility at 7T.
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