Consensus based framework for digital mobility monitoring

Digital mobility assessment using wearable sensor systems has the potential to capture walking performance in a patient's natural environment. It enables monitoring of health status and disease progression and evaluation of interventions in real-world situations. In contrast to laboratory settings, real-world walking occurs in non-conventional environments and under unconstrained and uncontrolled conditions. Despite the general understanding, there is a lack of agreed definitions about what constitutes real-world walking, impeding the comparison and interpretation of the acquired data across systems and studies. The goal of this study was to obtain expert-based consensus on specific aspects of real-world walking and to provide respective definitions in a common terminological framework. An adapted Delphi method was used to obtain agreed definitions related to real-world walking. In an online survey, 162 participants from a panel of academic, clinical and industrial experts with experience in the field of gait analysis were asked for agreement on previously specified definitions. Descriptive statistics was used to evaluate whether consent (> 75% agreement as defined a priori) was reached. Of 162 experts invited to participate, 51 completed all rounds (31.5% response rate). We obtained consensus on all definitions ("Walking" > 90%, "Purposeful" > 75%, "Real-world" > 90%, "Walking bout" > 80%, "Walking speed" > 75%, "Turning" > 90% agreement) after two rounds. The identification of a consented set of real-world walking definitions has important implications for the development of assessment and analysis protocols, as well as for the reporting and comparison of digital mobility outcomes across studies and systems. The definitions will serve as a common framework for implementing digital and mobile technologies for gait assessment and are an important link for the transition from supervised to unsupervised gait assessment.

Development and interpretation of a QSAR model for in vitro breast cancer (MCF-7) cytotoxicity of 2-phenylacrylonitriles

The Arylhydrocarbon Receptor (AhR), a member of the Per-ARNT-SIM transcription factor family, has been as a potential new target to treat breast cancer sufferers. A series of 2-phenylacrylonitriles targeting AhR has been developed that have shown promising and selective activity against cancerous cell lines while sparing normal non-cancerous cells. A quantitative structure–activity relationship (QSAR) modeling approach was pursued in order to generate a predictive model for cytotoxicity to support ongoing synthetic activities and provide important structure-activity information for new structure design. Recent work conducted by us has identified a number of compounds that exhibited false positive cytotoxicity values in the standard MTT assay. This work describes a good quality model that not only predicts the activity of compounds in the MCF-7 breast cancer cell line, but was also able to identify structures that subsequently gave false positive values in the MTT assay by identifying compounds with aberrant biological behavior. This work not only allows the design of future breast cancer cytotoxic activity in vitro, but allows the avoidance of the synthesis of those compounds anticipated to result in anomalous cytotoxic behavior, greatly enhancing the design of such compounds.