The Landmark Series: Neoadjuvant Radiotherapy in Extremity Soft Tissue Sarcoma-The Way to Hypofractionation.

For patients with nonmetastatic soft tissue sarcoma (STS) who are at high risk of local recurrence, the standard of care for limb-conserving local management is combined radiotherapy and surgery. Radiotherapy for STS entails 5 weeks of conventionally fractionated radiotherapy (25 × 2 Gy) preoperatively or 6 or more weeks postoperatively. There is growing interest in the use of preoperative hypofractionated regimes, viz.

Expanding the reaction toolbox for nanoscale direct-to-biology PROTAC synthesis and biological evaluation.

High-throughput chemistry (HTC) and direct-to-biology (D2B) platforms allow for plate-based compound synthesis and biological evaluation of crude mixtures in cellular assays. The rise of these workflows has rapidly accelerated drug-discovery programs in the field of targeted protein degradation (TPD) in recent years by removing a key bottleneck of compound purification. However, the number of chemical transformations amenable to this methodology remain minimal, leading to limitations in the exploration of chemical space using existing library-based approaches.

Brain Metastases in Sarcomas: A Multicenter Retrospective Cohort Study.

Purpose: Brain metastases (BM) in sarcomas occur rarely and are associated with poor prognosis. This study is a large retrospective cohort describing the demographic and clinical characteristics of these patients, treatment strategies, and survival outcomes.

Methods: In total, 81 patients with BM from sarcomas were identified across five sarcoma centers.

Two-Stream Modality-Based Deep Learning Approach for Enhanced Two-Person Human Interaction Recognition in Videos.

Human interaction recognition (HIR) between two people in videos is a critical field in computer vision and pattern recognition, aimed at identifying and understanding human interaction and actions for applications such as healthcare, surveillance, and human-computer interaction. Despite its significance, video-based HIR faces challenges in achieving satisfactory performance due to the complexity of human actions, variations in motion, different viewpoints, and environmental factors. In the study, we proposed a two-stream deep learning-based HIR system to address these challenges and improve the accuracy and reliability of HIR systems.