Toward development of clinically translatable diagnostic and prognostic metrics of traumatic brain injury using animal models: A review and a look forward
Hajiaghamemar et al.
The finding, in our words
This review identifies actigraphy, EEG, eye tracking and balance assessments as non-invasive, effort-independent tools that show promise for diagnosing and monitoring traumatic brain injury across animal models and human patients, particularly in children. It concludes that combining multiple biomarkers into a panel offers better prospects than relying on any single measure, though translation from preclinical to clinical use requires addressing age-related differences and interspecies variability.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
In progressive multiple sclerosis, higher serum neurofilament light chain levels were associated with reduced daily step counts from wearables, while higher step counts were linked to lower sNfL. A ten percent increase in steps corresponded to a 0.015 decrease in sNfL z-score, suggesting rising sNfL may predict subsequent mobility decline.
Joseph et al., Annals of clinical and translational neurology (paywalled) · source ↗
The High-Definition Oncology feasibility study in 30 women with metastatic cancer demonstrated high adherence to biospecimen collection (97.4% plasma, 80.7% stool) and wearable monitoring (70–95% of days captured for activity, heart rate, sleep, and oxygen saturation). This establishes a viable framework for decentralised, multimodal data collection in oncology to support individualised treatment models.
Garma et al., JCO precision oncology (paywalled) · source ↗
Wearing-off symptoms during natalizumab treatment in multiple sclerosis correlate with fatigue but not with inflammatory or neurodegenerative biomarkers, suggesting they are not markers of disease activity. Passive wearable monitoring detected subtle end-of-cycle motor declines and dynamic activity features that aligned with fatigue, indicating potential for digital biomarkers to serve as remote endpoints in decentralised neurological care.
Masanneck et al., Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics (paywalled) · source ↗
The study demonstrated that longitudinal remote monitoring using wearable sleep electroencephalography, actigraphy, and self-collected saliva samples is feasible in older adults with mild cognitive impairment or dementia, with high retention and data completeness rates over eight weeks.
This systematic review of ten studies with 49,172 participants found that machine-learning models integrating continuous glucose monitoring data with clinical, genetic and multi-omic biomarkers achieved AUC values up to 0.993 for early type 1 diabetes detection, with plasma CXCL10 and IL-1RA emerging as useful markers. The findings support decentralised diagnostics by validating wearable-derived digital biomarkers alongside plasma biomarkers, though data heterogeneity and limited generalisability remain barriers to clinical implementation.
Mittal et al., International journal of molecular sciences · source ↗