Abstract: The present invention is based, in part, on the identification of a minimal region of the SS18-SSX fusion oncoprotein that mediates a direct, high-affinity interaction between the mSWI/SNF complex and the nucleosome acidic patch, and methods and agents of modulating the interaction between the SS18-SSX fusion protein and H2A K119Ub-marked nucleosomes to treat synovial sarcoma.

Abstract: A System, Method, and Apparatus for Predicting Medical No-Shows and for Scheduling is provided. The system is based on a patient appointment schedule and indicators including office type, practice area, appointment type, engagement with the office leading up to appointment, and a variety of other characteristics of each patient and appointment. The indicators can be selected, weighted proportionately, and input into an algorithm for analysis and processing. The algorithm can then predict the likelihood of a no-show for the respective patient and appointment. The likelihood can then be used for scheduling to minimize the negative impact on the medical professional of the no-show. The algorithm can be used in conjunction with machine learning to improve its accuracy as it informs itself with experience and additional data points. The likelihood of a no-show can be incorporated into scheduling programs and made accessible on mobile devices, computers, and other monitoring devices.

Abstract: A System, Method, and Apparatus for Predicting Medical No-Shows and for Scheduling is provided. The system is based on a patient appointment schedule and indicators including office type, practice area, appointment type, engagement with the office leading up to appointment, and a variety of other characteristics of each patient and appointment. The indicators can be selected, weighted proportionately, and input into an algorithm for analysis and processing. The algorithm can then predict the likelihood of a no-show for the respective patient and appointment. The likelihood can then be used for scheduling to minimize the negative impact on the medical professional of the no-show. The algorithm can be used in conjunction with machine learning to improve its accuracy as it informs itself with experience and additional data points. The likelihood of a no-show can be incorporated into scheduling programs and made accessible on mobile devices, computers, and other monitoring devices.

Abstract: The present invention includes compositions comprising an alkyne-based substrate, an azide-based substrate, optionally a Cu(II) salt and optionally a photoinducible reducing agent. The present invention further includes a method of preparing composite materials that are suitable for use as dental implants using the compositions of the invention.

Abstract: The present invention includes compositions comprising an alkyne-based substrate, an azide-based substrate, optionally a Cu(II) salt and optionally a photoinducible reducing agent. The present invention further includes a method of preparing composite materials that are suitable for use as dental implants using the compositions of the invention.

Abstract: An apparatus, system, and method for displaying content. A portion of content may be displayed to a user. Personal and community data relating to the portion of content may be displayed alongside the portion of content. The personal and community data may include performance-related data. Furthermore, portions of content may be selectively displayed based on customizable performance thresholds.