Use of smartphone-based remote assessments of multiple sclerosis in Floodlight Open, a global, prospective, open-access study.

Floodlight Open was a global, open-access, digital-only study designed to understand the drivers and barriers in deployment and use of a smartphone app in a naturalistic setting and broad study population of people with and without multiple sclerosis (MS). The study utilised the Floodlight Open app: a 'bring-your-own-device' solution that remotely measures a user's mood, cognition, hand motor function, and gait and postural stability via smartphone sensor-based tests requiring active user input ('active tests'). Levels of mobility of study participants ('life-space measurement') were passively measured.

Personalized Longitudinal Assessment of Multiple Sclerosis Using Smartphones.

Personalized longitudinal disease assessment is central to quickly diagnosing, appropriately managing, and optimally adapting the therapeutic strategy of multiple sclerosis (MS). It is also important for identifying idiosyncratic subject-specific disease profiles. Here, we design a novel longitudinal model to map individual disease trajectories in an automated way using smartphone sensor data that may contain missing values.

Preliminary validity of the Draw a Shape Test for upper extremity assessment in multiple sclerosis.

Objective: To validate the smartphone sensor-based Draw a Shape Test - a part of the Floodlight Proof-of-Concept app for remotely assessing multiple sclerosis-related upper extremity impairment by tracing six different shapes.

Methods: People with multiple sclerosis, classified functionally normal/abnormal via their Nine-Hole Peg Test time, and healthy controls participated in a 24-week, nonrandomized study. Spatial (trace accuracy), temporal (mean and variability in linear, angular, and radial drawing velocities, and dwell time ratio), and spatiotemporal features (trace celerity) were cross-sectionally analyzed for correlation with standard clinical and brain magnetic resonance imaging (normalized brain volume and total lesion volume) disease burden measures, and for capacity to differentiate people with multiple sclerosis from healthy controls.

A Remote Digital Monitoring Platform to Assess Cognitive and Motor Symptoms in Huntington Disease: Cross-sectional Validation Study.

Background: Remote monitoring of Huntington disease (HD) signs and symptoms using digital technologies may enhance early clinical diagnosis and tracking of disease progression, guide treatment decisions, and monitor response to disease-modifying agents. Several recent studies in neurodegenerative diseases have demonstrated the feasibility of digital symptom monitoring.

Objective: The aim of this study was to evaluate a novel smartwatch- and smartphone-based digital monitoring platform to remotely monitor signs and symptoms of HD.

Simulating the impact of noise on gait features extracted from smartphone sensor-data for the remote assessment of movement disorders.

Signs and symptoms of movement disorders can be remotely measured at home through sensor-based assessment of gait. However, sensor noise may impact the robustness of such assessments, in particular in a Bring-Your-Own-Device setting where the quality of sensors might vary. Here, we propose a framework to study the impact of inertial measurement unit noise on sensor-based gait features.

A smartphone sensor-based digital outcome assessment of multiple sclerosis.

Background: Sensor-based monitoring tools fill a critical gap in multiple sclerosis (MS) research and clinical care.

Objective: The aim of this study is to assess performance characteristics of the Floodlight Proof-of-Concept (PoC) app.

Methods: In a 24-week study (clinicaltrials.

U-turn speed is a valid and reliable smartphone-based measure of multiple sclerosis-related gait and balance impairment.

Background: People living with multiple sclerosis (MS) experience impairments in gait and mobility, that are not fully captured with manually timed walking tests or rating scales administered during periodic clinical visits. We have developed a smartphone-based assessment of ambulation performance, the 5 U-Turn Test (5UTT), a quantitative self-administered test of U-turn ability while walking, for people with MS (PwMS).

Research Question: What is the test-retest reliability and concurrent validity of U-turn speed, an unsupervised self-assessment of gait and balance impairment, measured using a body-worn smartphone during the 5UTT?

Methods: 76 PwMS and 25 healthy controls (HCs) participated in a cross-sectional non-randomised interventional feasibility study.

Gait Characteristics Harvested During a Smartphone-Based Self-Administered 2-Minute Walk Test in People with Multiple Sclerosis: Test-Retest Reliability and Minimum Detectable Change.

The measurement of gait characteristics during a self-administered 2-minute walk test (2MWT), in persons with multiple sclerosis (PwMS), using a single body-worn device, has the potential to provide high-density longitudinal information on disease progression, beyond what is currently measured in the clinician-administered 2MWT. The purpose of this study is to determine the test-retest reliability, standard error of measurement (SEM) and minimum detectable change (MDC) of features calculated on gait characteristics, harvested during a self-administered 2MWT in a home environment, in 51 PwMS and 11 healthy control (HC) subjects over 24 weeks, using a single waist-worn inertial sensor-based smartphone. Excellent, or good to excellent test-retest reliability were observed in 58 of the 92 temporal, spatial and spatiotemporal gait features in PwMS.

Smartphone- and Smartwatch-Based Remote Characterisation of Ambulation in Multiple Sclerosis During the Two-Minute Walk Test.

Leveraging consumer technology such as smartphone and smartwatch devices to objectively assess people with multiple sclerosis (PwMS) remotely could capture unique aspects of disease progression. This study explores the feasibility of assessing PwMS and Healthy Control's (HC) physical function by characterising gait-related features, which can be modelled using machine learning (ML) techniques to correctly distinguish subgroups of PwMS from healthy controls. A total of 97 subjects (24 HC subjects, 52 mildly disabled (PwMSmild, EDSS [0-3]) and 21 moderately disabled (PwMSmod, EDSS [3.

Building a Machine-Learning Framework to Remotely Assess Parkinson's Disease Using Smartphones.

Objective: Parkinson's disease (PD) is a neurodegenerative disorder that affects multiple neurological systems. Traditional PD assessment is conducted by a physician during infrequent clinic visits. Using smartphones, remote patient monitoring has the potential to obtain objective behavioral data semi-continuously, track disease fluctuations, and avoid rater dependency.

Correction: Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study.

[This corrects the article DOI: 10.2196/14863.].

Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study.

Background: Current clinical assessments of people with multiple sclerosis are episodic and may miss critical features of functional fluctuations between visits.

Objective: The goal of the research was to assess the feasibility of remote active testing and passive monitoring using smartphones and smartwatch technology in people with multiple sclerosis with respect to adherence and satisfaction with the FLOODLIGHT test battery.

Methods: People with multiple sclerosis (aged 20 to 57 years; Expanded Disability Status Scale 0-5.

Look me in the eye: evaluating the accuracy of smartphone-based eye tracking for potential application in autism spectrum disorder research.

Background: Avoidance to look others in the eye is a characteristic symptom of Autism Spectrum Disorders (ASD), and it has been hypothesised that quantitative monitoring of gaze patterns could be useful to objectively evaluate treatments. However, tools to measure gaze behaviour on a regular basis at a manageable cost are missing. In this paper, we investigated whether a smartphone-based tool could address this problem.

Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial.

Background: Ubiquitous digital technologies such as smartphone sensors promise to fundamentally change biomedical research and treatment monitoring in neurological diseases such as PD, creating a new domain of digital biomarkers.

Objectives: The present study assessed the feasibility, reliability, and validity of smartphone-based digital biomarkers of PD in a clinical trial setting.

Methods: During a 6-month, phase 1b clinical trial with 44 Parkinson participants, and an independent, 45-day study in 35 age-matched healthy controls, participants completed six daily motor active tests (sustained phonation, rest tremor, postural tremor, finger-tapping, balance, and gait), then carried the smartphone during the day (passive monitoring), enabling assessment of, for example, time spent walking and sit-to-stand transitions by gyroscopic and accelerometer data.

Patient Recruitment 2.0: Become a Partner in the Patient Journey Using Digital Media.

We describe a digital platform, Pioneering Healthcare, designed to inform and empower people who are impacted by lung cancer. The platform enables Roche to support an online conversation with patients and caregivers about lung cancer, and about the role of lung cancer clinical studies in the development of future treatment options. This conversation is live and ongoing on the platform.

Binding of organometallic ruthenium(II) anticancer compounds to nucleobases: a computational study.

The reaction of the anticancer compound [(eta(6)-benzene)Ru(en)(OH(2))](2+) (1) toward the nucleobases guanine, adenine, and cytosine is studied computationally using DFT/BP86 calculations. The aqua leaving group of such compounds is known to undergo ligand exchange reactions with nucleophilic centers in DNA and preferentially with the N7 atom of guanine, N7(G). Our results show that an H-bonded reactant adduct with nucleobases is formed via either the aqua ligand (cis adduct) or the en (ethylenediamine) ligand (trans adduct) of 1.

DNA structural distortions induced by ruthenium-arene anticancer compounds.

Organometallic ruthenium(II)-arene (RA) compounds combine a rich structural diversity with the potential to overcome existing chemotherapeutic limitations. In particular, the two classes of compounds [Ru(II)(eta(6)-arene)X(en)] and [Ru(II)(eta(6)-arene)(X)2(pta)] (RA-en and RA-pta, respectively; X = leaving group, en = ethylenediamine, pta = 1,3,5-triaza-7-phosphaadamantane) have become the focus of recent anticancer research. In vitro and in vivo studies have shown that they exhibit promising new activity profiles, for which their interactions with DNA are suspected to be a crucial factor.

Structural and Energetic Properties of Organometallic Ruthenium(II) Diamine Anticancer Compounds and Their Interaction with Nucleobases.

We rationalize the chemoselectivity of the monofunctional ruthenium anticancer compound [(η(6)-arene)Ru(II)(en)(OH2)](2+) (en=ethylenediamine; arene=benzene 1, p-cymene 2) toward guanine, using static DFT (BP86) and MP2 calculations together with Car-Parrinello molecular dynamics. The calculated binding energies for the three investigated nucleobases (G, A, C) decreases in the order G(N7) ≫ C(O2) ∼ C(N3) > A(N7) > G(O6) > OH2. The G(N7) complex is the most stable product due to a hydrogen bond of its O6 with one of the H2N-amine groups of en, while the corresponding NH2-H2N(en) interaction in the adenine complex is repulsive.

NMR solvent shifts of adenine in aqueous solution from hybrid QM/MM molecular dynamics simulations.

We present first principles calculations of the NMR solvent shift of adenine in aqueous solution. The calculations are based on snapshots sampled from a molecular dynamics simulation, which were obtained via a hybrid quantum-mechanical/mechanical modeling approach, using an all-atom force field (TIP3P). We find that the solvation via the strongly fluctuating hydrogen bond network of water leads to nontrivial changes in the NMR spectra of the solutes regarding the ordering of the resonance lines.