Smartwatch gait coordination index: New measure for human gait utilizing smartwatch sensor.

Human walking reflects the state of human health. Numerous medical studies have been conducted to analyze walking patterns and to diagnose disease progression. However, this process requires expensive equipment and considerable time and manpower. Smartwatches are equipped with gyro sensors to detect human movements and graph-walking patterns. To measure the abnormality in walking using this graph, we developed a smartwatch gait coordination index (SGCI) and examined its usefulness. The phase coordination index was applied to analyze arm movements. Based on previous studies, the phase coordination index formula was applied to graphs obtained from arm movements, showing that arm and leg movements during walking are correlated with each other. To prove this, a smartwatch was worn on the arms and legs of 8 healthy adults and the difference in arm movements was measured. The SGCI values with abnormal walking patterns were compared with the SGCI values obtained during normal walking. In the first experiment, the measured leg SGCI in normal walking averaged 9.002 ± 3.872 and the arm SGCI averaged 9.847 ± 6.115. The movements of both arms and legs showed stable sinusoidal waves. In fact, as a result of performing a paired t test of both exercise phases measured by the strike point using the maximum and minimum values, it was confirmed that the 2 exercises were not statistically different, as it yielded a P value of 0.469 (significance level α = 0.05). The arm SGCI measured after applying the 3 kg weight impairment on 1 leg was 22.167 ± 4.705. It was confirmed that the leg SGCI and 3 kg weight arm SGCI were statistically significant, as it yielded a P value of 0.001 (significance level α = 0.05). The SCGI can be automatically and continuously measured with the gyro sensor of the smartwatch and can be used as an indirect indicator of human walking conditions.

Effects of clinical, comorbid, and social determinants of health on brain ageing in people with and without HIV: a retrospective case-control study.

BACKGROUND: Neuroimaging reveals structural brain changes linked with HIV infection and related neurocognitive disorders; however, group-level comparisons between people with HIV and people without HIV do not account for within-group heterogeneity. The aim of this study was to quantify the effects of comorbidities such as cardiovascular disease and adverse social determinants of health on brain ageing in people with HIV and people without HIV. METHODS: In this retrospective case-control study, people with HIV from Washington University in St Louis, MO, USA, and people without HIV identified through community organisations or the Research Participant Registry were clinically characterised and underwent 3-Tesla T1-weighted MRI between Dec 3, 2008, and Oct 4, 2022. Exclusion criteria were established by a combination of self-reports and medical records. DeepBrainNet, a publicly available machine learning algorithm, was applied to estimate brain-predicted age from MRI for people with HIV and people without HIV. The brain-age gap, defined as the difference between brain-predicted age and true chronological age, was modelled as a function of clinical, comorbid, and social factors by use of linear regression. Variables were first examined singly for associations with brain-age gap, then combined into multivariate models with best-subsets variable selection. FINDINGS: In people with HIV (mean age 44·8 years [SD 15·5]; 78% [296 of 379] male; 69% [260] Black; 78% [295] undetectable viral load), brain-age gap was associated with Framingham cardiovascular risk score (p=0·0034), detectable viral load (>50 copies per mL; p=0·0023), and hepatitis C co-infection (p=0·0065). After variable selection, the final model for people with HIV retained Framingham score, hepatitis C, and added unemployment (p=0·0015). Educational achievement assayed by reading proficiency was linked with reduced brain-age gap (p=0·016) for people without HIV but not for people with HIV, indicating a potential resilience factor. When people with HIV and people without HIV were modelled jointly, selection resulted in a model containing cardiovascular risk (p=0·0039), hepatitis C (p=0·037), Area Deprivation Index (p=0·033), and unemployment (p=0·00010). Male sex (p=0·078) and alcohol use history (p=0·090) were also included in the model but were not individually significant. INTERPRETATION: Our findings indicate that comorbid and social determinants of health are associated with brain ageing in people with HIV, alongside traditional HIV metrics such as viral load and CD4 cell count, suggesting the need for a broadened clinical perspective on healthy ageing with HIV, with additional focus on comorbidities, lifestyle changes, and social factors. FUNDING: National Institute of Mental Health, National Institute of Nursing Research, and National Institute of Drug Abuse.

The Macromolecular Femtosecond Crystallography Instrument at the Linac Coherent Light Source.

The Macromolecular Femtosecond Crystallography (MFX) instrument at the Linac Coherent Light Source (LCLS) is the seventh and newest instrument at the world's first hard X-ray free-electron laser. It was designed with a primary focus on structural biology, employing the ultrafast pulses of X-rays from LCLS at atmospheric conditions to overcome radiation damage limitations in biological measurements. It is also capable of performing various time-resolved measurements. The MFX design consists of a versatile base system capable of supporting multiple methods, techniques and experimental endstations. The primary techniques supported are forward scattering and crystallography, with capabilities for various spectroscopic methods and time-resolved measurements. The location of the MFX instrument allows for utilization of multiplexing methods, increasing user access to LCLS by running multiple experiments simultaneously.