App Characteristics and Accuracy Metrics of Available Digital Biomarkers for Autism: Scoping Review.

BACKGROUND: Diagnostic delays in autism are common, with the time to diagnosis being up to 3 years from the onset of symptoms. Such delays have a proven detrimental effect on individuals and families going through the process. Digital health products, such as mobile apps, can help close this gap due to their scalability and ease of access. Further, mobile apps offer the opportunity to make the diagnostic process faster and more accurate by providing additional and timely information to clinicians undergoing autism assessments. OBJECTIVE: The aim of this scoping review was to synthesize the available evidence about digital biomarker tools to aid clinicians, researchers in the autism field, and end users in making decisions as to their adoption within clinical and research settings. METHODS: We conducted a structured literature search on databases and search engines to identify peer-reviewed studies and regulatory submissions that describe app characteristics, validation study details, and accuracy and validity metrics of commercial and research digital biomarker apps aimed at aiding the diagnosis of autism. RESULTS: We identified 4 studies evaluating 4 products: 1 commercial and 3 research apps. The accuracy of the identified apps varied between 28% and 80.6%. Sensitivity and specificity also varied, ranging from 51.6% to 81.6% and 18.5% to 80.5%, respectively. Positive predictive value ranged from 20.3% to 76.6%, and negative predictive value fluctuated between 48.7% and 97.4%. Further, we found a lack of details around participants' demographics and, where these were reported, important imbalances in sex and ethnicity in the studies evaluating such products. Finally, evaluation methods as well as accuracy and validity metrics of available tools were not clearly reported in some cases and varied greatly across studies. Different comparators were also used, with some studies validating their tools against the Diagnostic and Statistical Manual of Mental Disorders criteria and others through self-reported measures. Further, while in most cases, 2 classes were used for algorithm validation purposes, 1 of the studies reported a third category (indeterminate). These discrepancies substantially impact the comparability and generalizability of the results, thus highlighting the need for standardized validation processes and the reporting of findings. CONCLUSIONS: Despite their popularity, systematic evaluations and syntheses of the current state of the art of digital health products are lacking. Standardized and transparent evaluations of digital health tools in diverse populations are needed to assess their real-world usability and validity, as well as help researchers, clinicians, and end users safely adopt novel tools within clinical and research practices.

Exploring semantic verbal fluency patterns and their relationship to age and Alzheimer's disease in adults with Down syndrome.

INTRODUCTION: Adults with Down syndrome (DS) are at ultra-high risk of developing Alzheimer's disease (AD), characterized by poor episodic memory and semantic fluency in the preclinical phase in the general population. We explored semantic fluency performance in DS and its relationship to age, AD, and blood biomarkers. METHODS: A total of 302 adults with DS at baseline and 87 at follow-up from the London Down Syndrome Consortium cohort completed neuropsychological assessments. Blood biomarkers were measured with the single molecule array technique in a subset of 94 participants. RESULTS: Poorer verbal fluency performance was observed as age increases. Number of correct words declined in those with AD compared to those without over 2 years and was negatively correlated with neurofilament light (r = -0.37, P = .001) and glial fibrillary acidic protein (r = -0.31, P = .012). DISCUSSION: Semantic fluency may be useful as an early indicator of cognitive decline and provide additional information on AD-related change, showing associations with biomarkers in DS.

Action potential alterations induced by single F11 neuronal cell loading.

Several research programmes have demonstrated how Transcranial Ultrasound Stimulation (TUS) can non-invasively and reversibly mechanically perturb neuronal functions. However, the mechanisms through which such reversible and a priori non-damaging behaviour can be observed remain largely unknown. While several TUS protocols have demonstrated motor and behavioural alterations in in vivo models, in vitro studies remain scarce. In particular, an experimental framework able to load mechanically an individual neuron in a controlled manner and simultaneously measure the generation and evolution of action potentials before, during and after such load, while allowing for direct microscopy, has not been successfully proposed. To this end, we herein present a multiphysics setup combining nanoindentation and patch clamp systems, assembled in an inverted microscope for simultaneous bright-field or fluorescence imaging. We evaluate the potential of the platform with a set of experiments in which single dorsal root ganglion-derived neuronal cell bodies are compressed while their spontaneous activity is recorded. We show that these transient quasi-static mechanical loads reversibly affect the amplitude and rate of change of the neuronal action potentials, which are smaller and slower upon indentation, while irreversibly altering other features. The ability to simultaneously image, mechanically and electrically manipulate and record single cells in a perturbed mechanical environment makes this system particularly suitable for studying the multiphysics of the brain at the cell level.

Electrophysiological-mechanical coupling in the neuronal membrane and its role in ultrasound neuromodulation and general anaesthesia.

The current understanding of the role of the cell membrane is in a state of flux. Recent experiments show that conventional models, considering only electrophysiological properties of a passive membrane, are incomplete. The neuronal membrane is an active structure with mechanical properties that modulate electrophysiology. Protein transport, lipid bilayer phase, membrane pressure and stiffness can all influence membrane capacitance and action potential propagation. A mounting body of evidence indicates that neuronal mechanics and electrophysiology are coupled, and together shape the membrane potential in tight coordination with other physical properties. In this review, we summarise recent updates concerning electrophysiological-mechanical coupling in neuronal function. In particular, we aim at making the link with two relevant yet often disconnected fields with strong clinical potential: the use of mechanical vibrations-ultrasound-to alter the electrophysiogical state of neurons, e.g., in neuromodulation, and the theories attempting to explain the action of general anaesthetics. STATEMENT OF SIGNIFICANCE: General anaesthetics revolutionised medical practice; now an apparently unrelated technique, ultrasound neuromodulation-aimed at controlling neuronal activity by means of ultrasound-is poised to achieve a similar level of impact. While both technologies are known to alter the electrophysiology of neurons, the way they achieve it is still largely unknown. In this review, we argue that in order to explain their mechanisms/effects, the neuronal membrane must be considered as a coupled mechano-electrophysiological system that consists of multiple physical processes occurring concurrently and collaboratively, as opposed to sequentially and independently. In this framework the behaviour of the cell membrane is not the result of stereotypical mechanisms in isolation but instead emerges from the integrative behaviour of a complexly coupled multiphysics system.