Targeted protein degradation in hematologic malignancies: latest updates from the 2023 ASH annual meeting.

Protein degraders, emerging as a novel class of therapeutic agents, have gained widespread attention due to their advantages. They have several advantages over traditional small molecule inhibitors, including high target selectivity and ability to target "undruggable" targets and overcome inhibitor drug resistance. Tremendous research and development efforts and massive investment have resulted in rapid advancement of protein degrader drug discovery in recent years.

IMGC-GNN: A multi-granularity coupled graph neural network recommendation method based on implicit relationships.

In the application recommendation field, collaborative filtering (CF) method is often considered to be one of the most effective methods. As the basis of CF-based recommendation methods, representation learning needs to learn two types of factors: attribute factors revealed by independent individuals (e.g.

CFDIL: a context-aware feature deep interaction learning for app recommendation.

The rapid development of mobile Internet has spawned various mobile applications (apps). A large number of apps make it difficult for users to choose apps conveniently, causing the app overload problem. As the most effective tool to solve the problem of app overload, app recommendation has attracted extensive attention of researchers.

A rare case of Primary Central Nervous System Lymphoma initially diagnosed as demyelinating encephalopathy.

We report a case of histopathologically-confirmed primary central nervous system lymphoma who was initially diagnosed as demyelinating encephalopathy. A 58-year-old woman was admitted with confusion and left hemiparesis. Head MR showed abnormal flaky hypointense T1 and hyperintense T2 signals at right thalamus, splenium of corpus callosum, bilateral cerebral peduncle, pons, medulla oblongata, basal ganglia and right corona radiata.