ABSTRACT
Preparation requires technical research and development, as well as adaptive, proactive governance.
Subject(s)
Artificial Intelligence , Humans , Risk Management , COVID-19/prevention & control , COVID-19/epidemiologyABSTRACT
Extended reality (XR) devices such as the Meta Quest and Apple Vision Pro have seen a recent surge in attention, with motion tracking "telemetry" data lying at the core of nearly all XR and metaverse experiences. Researchers are just beginning to understand the implications of this data for security, privacy, usability, and more, but currently lack large-scale human motion datasets to study. The BOXRR-23 dataset contains 4,717,215 motion capture recordings, voluntarily submitted by 105,852 XR device users from over 50 countries. BOXRR-23 is over 200 times larger than the largest existing motion capture research dataset and uses a new, highly efficient and purpose-built XR Open Recording (XROR) file format.
ABSTRACT
As machine learning systems grow in scale, so do their training data requirements, forcing practitioners to automate and outsource the curation of training data in order to achieve state-of-the-art performance. The absence of trustworthy human supervision over the data collection process exposes organizations to security vulnerabilities; training data can be manipulated to control and degrade the downstream behaviors of learned models. The goal of this work is to systematically categorize and discuss a wide range of dataset vulnerabilities and exploits, approaches for defending against these threats, and an array of open problems in this space.
ABSTRACT
A series of novel 2,4-diaminopyrimidines bearing tetrahydronaphthalenyl moiety were synthesized and evaluated for their anti-anaplastic lymphoma kinase (ALK) activities using enzymatic and cell-based assays. Among the compounds synthesized, compound 17b showed promising pharmacological results in in vitro, ex vivo, and pharmacokinetic studies. An in vivo efficacy study with compound 17b demonstrated highly potent inhibitory activity in H3122 tumor xenograft model mice. A series of kinase assays showed that compound 17b inhibited various kinases including FAK, ACK1, FGFR, RSK1, IGF-1R, among others, thus demonstrating its potential for synergistic anti-tumor activity and development as a multi-targeted non-small cell lung cancer (NSCLC) therapy.
Subject(s)
Antineoplastic Agents/chemistry , Antineoplastic Agents/therapeutic use , Carcinoma, Non-Small-Cell Lung/drug therapy , Lung Neoplasms/drug therapy , Pyrimidines/chemistry , Pyrimidines/therapeutic use , Receptor Protein-Tyrosine Kinases/antagonists & inhibitors , Anaplastic Lymphoma Kinase , Animals , Antineoplastic Agents/pharmacokinetics , Carcinoma, Non-Small-Cell Lung/enzymology , Cell Line, Tumor , Humans , Lung/drug effects , Lung/enzymology , Lung Neoplasms/enzymology , Male , Mice , Mice, SCID , Naphthalenes/chemistry , Naphthalenes/pharmacokinetics , Naphthalenes/therapeutic use , Protein Kinase Inhibitors/chemistry , Protein Kinase Inhibitors/pharmacokinetics , Protein Kinase Inhibitors/therapeutic use , Pyrimidines/pharmacokinetics , Rats , Receptor Protein-Tyrosine Kinases/metabolismABSTRACT
A series of novel 2,4-diaminopyrimidine compounds bearing bicyclic aminobenzazepine were synthesized and evaluated for their anti-ALK activities. The activities of these compounds were confirmed in both enzyme- and cell-based ALK assays. Amongst compounds synthesized, KRCA-0445 showed very promising results in pharmacokinetic study and in vivo efficacy study with H3122 xenograft mouse model.
Subject(s)
Antineoplastic Agents/pharmacology , Benzazepines/pharmacology , Bridged Bicyclo Compounds/pharmacology , Neoplasms, Experimental/drug therapy , Protein Kinase Inhibitors/pharmacology , Pyrimidines/chemistry , Pyrimidines/pharmacology , Receptor Protein-Tyrosine Kinases/antagonists & inhibitors , Anaplastic Lymphoma Kinase , Animals , Antineoplastic Agents/chemistry , Antineoplastic Agents/pharmacokinetics , Benzazepines/chemistry , Benzazepines/pharmacokinetics , Bridged Bicyclo Compounds/chemistry , Bridged Bicyclo Compounds/pharmacokinetics , Cell Line, Tumor , Dose-Response Relationship, Drug , Humans , Mice , Molecular Structure , Neoplasms, Experimental/pathology , Protein Kinase Inhibitors/chemistry , Protein Kinase Inhibitors/pharmacokinetics , Pyrimidines/pharmacokinetics , Receptor Protein-Tyrosine Kinases/metabolism , Structure-Activity RelationshipABSTRACT
The pigmentation patterns of shells in the genus Conus can be generated by a neural-network model of the mantle. We fit model parameters to the shell pigmentation patterns of 19 living Conus species for which a well resolved phylogeny is available. We infer the evolutionary history of these parameters and use these results to infer the pigmentation patterns of ancestral species. The methods we use allow us to characterize the evolutionary history of a neural network, an organ that cannot be preserved in the fossil record. These results are also notable because the inferred patterns of ancestral species sometimes lie outside the range of patterns of their living descendants, and illustrate how development imposes constraints on the evolution of complex phenotypes.
