The risk stratification of prostate cancer and breast cancer tumours from patients relies on histopathology, selective genomic testing, or on other methods employing fixed formalin tissue samples. However, static biomarker measurements from bulk fixed-tissue samples provide limited accuracy and actionability. Here, we report the development of a live-primary-cell phenotypic-biomarker assay with single-cell resolution, and its validation with prostate cancer and breast cancer tissue samples for the prediction of post-surgical adverse pathology. The assay includes a collagen-I/fibronectin extracellular-matrix formulation, dynamic live-cell biomarkers, a microfluidic device, machine-vision analysis and machine-learning algorithms, and generates predictive scores of adverse pathology at the time of surgery. Predictive scores for the risk stratification of 59 prostate cancer patients and 47 breast cancer patients, with values for area under the curve in receiver-operating-characteristic curves surpassing 80%, support the validation of the assay and its potential clinical applicability for the risk stratification of cancer patients.

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Among MS patients with walking impairments, the Echo5D AMS acquired walking speeds which were closely correlated with the standard measures of GC and SW. The strong agreement supports the use of Echo5D to assess in-home, real-world walking performance in MS.

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BackgroundGait disturbance is a major contributor to clinical disability in multiple sclerosis (MS). A sensor was developed to assess walking speed at home for people with MS using infrared technology in real-time without the use of wearables.ObjectiveTo develop continuous in-home outcome measures to assess gait in adults with MS.MethodsMovement measurements were collected continuously for 8 months from six people with MS. Average walking speed and peak walking speed were calculated from movement data, then analyzed for variability over time, by room (location), and over the course of the day. In-home continuous gait outcomes and variability were correlated with standard in-clinic gait outcomes.ResultsMeasured in-home average walking speed of participants ranged from 0.33 m/s to 0.96 m/s and peak walking speed ranged from 0.89 m/s to 1.51 m/s. Mean total within-participant coefficient of variation for daily average walking speed and peak walking speed were 10.75% and 10.93%, respectively. Average walking speed demonstrated a moderately strong correlation with baseline Timed 25-Foot Walk (rs = 0.714, P = 0.111).ConclusionNew non-wearable technology provides reliable and continuous in-home assessment of walking speed.