Establishment and assessment of rodent models of medication-related osteonecrosis of the jaw(MRONJ)

Medication-related osteonecrosis of the jaw(MRONJ)is primarily associated with administering antiresorptive or antiangiogenic drugs.Despite significant research on MRONJ,its pathogenesis and effective treatments are still not fully understood.Animal models can be used to simulate the pathophysiological features of MRONJ,serving as standardized in vivo experimental platforms to explore the pathogenesis and therapies of MRONJ.Rodent models exhibit excellent effectiveness and high reproducibility in mimicking human MRONJ,but classical methods cannot achieve a complete replica of the pathogenesis of MRONJ.Modified rodent models have been reported with improvements for better mimicking of MRONJ onset in clinic.This review summarizes representative classical and modified rodent models of MRONJ created through various combinations of systemic drug induction and local stimulation and discusses their effectiveness and efficiency.Currently,there is a lack of a unified assessment system for MRONJ models,which hinders a standard definition of MRONJ-like lesions in rodents.Therefore,this review comprehensively summarizes assessment systems based on published peer-review articles,including new approaches in gross observation,histological assessments,radiographic assessments,and serological assessments.This review can serve as a reference for model establishment and evaluation in future preclinical studies on MRONJ.

Human-Centric Composite-Quality Modeling and Assessment for Virtual Desktop Clouds

There are several motivations, such as mobility, cost, and secu- rity, that are behind the trend of traditional desktop users transi- tioning to thin-client-based virtual desktop clouds （VDCs）. Such a trend has led to the rising importance of human-centric performance modeling and assessment within user communities that are increasingly making use of desktop virtualization. In this paper, we present a novel reference architecture and its eas- ily deployable implementation for modeling and assessing objec- tive user quality of experience （QoE） in VDCs. This architec- ture eliminates the need for expensive, time-consuming subjec- tive testing and incorporates finite-state machine representa- tions for user workload generation. It also incorporates slow-mo- tion benchmarking with deep-packet inspection of application task performance affected by QoS variations. In this way, a ＂composite-quality＂ metric model of user QoE can be derived. We show how this metric can be customized to a particular user group profile with different application sets and can be used to a） identify dominant performance indicators and troubleshoot bottlenecks and b） obtain both absolute and relative objective user QoE measurements needed for pertinent selection of thin-client encoding configurations in VDCs. We validate our composite-quality modeling and assessment methodology by us- ing subjective and objective user QoE measurements in a re- al-world VDC called VDPilot, which uses RDP and PCoIP thin-client protocols. In our case study, actual users are pres- ent in virtual classrooms within a regional federated university system.