Risk-prediction model for incident hypertension in patients with obstructive sleep apnea based on SpO2 signals.

This work proposes a method utilizing oxygen saturation (SpO2) for predicting incident hypertension in patients with obstructive sleep apnea (OSA). We extracted time domain features and frequency domain features from the SpO2 signal. For prediction, we employed several machine learning algorithms to establish the 3-year risk prediction model in the Chinese Sleep Health Study, including 250 subjects without baseline hypertension who underwent sleep monitoring. The proposed random forest model achieved an accuracy of 84.4%, a sensitivity of 77.0%, a specificity of 91.5% and an area under the receiver operator characteristic of 84.3% using 10-fold crossvalidation. We show that the model outperformed two sleep medicine specialists using clinical experience to predict hypertension. Furthermore, we applied the prediction results in the public Sleep Heart Health Study database and showed the subjects who were predicted to have hypertension would be at a higher risk in 4-6 years. This work shows the potential of SpO2 signal during sleep for the prediction of hypertension and could be beneficial to the early detection and timely treatment of hypertension in OSA patients.Clinical Relevance-There is no prediction model for incident hypertension in OSA patients in clinical practice. Most patients are unaware of health complexity, symptoms and risk factors before hypertension. Establishing an accurate prediction model can effectively provide early intervention for OSA patients and reduce the prevalence of hypertension.

Relative spectral power quantifying the distribution of intermittent hypoxemia in obstructive sleep apnea is strongly associated with hypertension.

STUDY OBJECTIVES: To investigate the association between the periodicity of distribution of intermittent hypoxemia (IH) and hypertension in adults with obstructive sleep apnea (OSA) and search for an index to quantify the association. METHODS: Samples were derived from two cross-sectional studies: The Sleep Heart Health Study (SHHS) including 3991 adults with age 64.7 ± 10.9 years; and the Chinese Changgung Sleep Health Study (CSHS) including 906 adults with age 59.5 ± 12.4 years. Spectral analysis of peripheral oxygen saturation (SpO2) was performed and the relative spectral power (PFR) in the frequency band of 0.011-0.037 Hz (PFR0.011-0.037Hz) was extracted to quantify the periodic distribution of IH. Multiple logistic regression models were used to calculate the partially and fully adjusted odd ratios for PFR0.011-0.037Hz. RESULTS: PFR0.011-0.037Hz was significantly higher in the hypertension group than non-hypertension group (44.4% ± 0.3% vs. 42.1% ± 0.3%, p < 0.001 in SHHS and 57.4% ± 0.7% vs. 50.5% ± 0.8%, p < 0.001 in CSHS). In the fully adjusted model, individuals in the SHHS with PFR0.011-0.037Hz in the highest quintiles had an odd ratio of 1.33 [95% confidence interval (CI) 1.06-1.67]. Similarly, the group in the CSHS with PFR0.011-0.037Hz in the highest quintile had an odd ratio of 3.08 (95% CI 1.80-5.28). CONCLUSIONS: We developed an IH distribution measure which is strongly associated with hypertension independent of multiple confounding variables. The finding suggests that the periodic distribution of sleep related upper airway obstructions is an essential hypertension characterizing feature.

Dynamic Liquid Metal Catalysts for Boosted Lithium Polysulfides Redox Reaction.

Designing efficient electrocatalysts with high electroconductivity, strong chemisorption, and superior catalytical efficiency to realize rapid kinetics of the lithium polysulfides (LiPSs) conversion process is crucial for practical lithium-sulfur (Li-S) battery applications. Unfortunately, most current electrocatalysts cannot maintain long-term stability due to the possible failure of catalytic sites. Herein, a novel dynamic electrocatalytic strategy with the liquid metal (i.e., gallium-tin, EGaSn) to facilitate LiPSs redox reaction is reported. The combined theoretical simulations and microstructure experiment analysis reveal that Sn atoms dynamically distributed in the liquid Ga matrix act as the main active catalytic center. Meanwhile, Ga provides a uniquely dynamic environment to maintain the long-term integrity of the catalytic system. With the participation of EGaSn, a tailor-made 2 Ah Li-S pouch cell with a specific energy density of 307.7 Wh kg-1 is realized. This work opens up new opportunities for liquid-phase binary alloys as electrocatalysts for high-specific-energy Li-S batteries.

Electroencephalography Theta/Beta Ratio Decreases in Patients with Severe Obstructive Sleep Apnea.

Purpose: Accumulating evidence suggests that theta/beta ratio (TBR), an electroencephalographic (EEG) frequency band parameter, might serve as an objective marker of executive cognitive control in healthy adults. Obstructive sleep apnea (OSA) has a detrimental impact on patients' behavior and cognitive performance while whether TBR is different in OSA population has not been reported. This study aimed to explore the difference in relative EEG spectral power and TBR during sleep between patients with severe OSA and non-OSA groups. Patients and Methods: 142 participants with in-laboratory nocturnal PSG recording were included, among which 100 participants suffered severe OSA (apnea hypopnea index, AHI > 30 events/hour; OSA group) and 42 participants had no OSA (AHI ≤ 5 events/h; control group). The fast Fourier transformation was used to compute the EEG power spectrum for total sleep duration within contiguous 30-second epochs of sleep. The demographic and polysomnographic characteristics, relative EEG spectral power and TBR of the two groups were compared. Results: It was found that the beta band power during NREM sleep and total sleep was significantly higher in the OSA group than controls (p < 0.001, p = 0.012, respectively), and the theta band power during NREM sleep and total sleep was significantly lower in the OSA group than controls (p = 0.019, p = 0.014, respectively). TBR during NREM sleep, REM sleep and total sleep was significantly lower in the OSA group compared to the control group (p < 0.001 for NREM sleep and total sleep, p = 0.015 for REM sleep). TBR was negatively correlated with AHI during NREM sleep (r=-0.324, p < 0.001) and total sleep (r=-0. 312, p < 0.001). Conclusion: TBR was significantly decreased in severe OSA patients compared to the controls, which was attributed to both increased beta power and decreased theta power. TBR may be a stable EEG-biomarker of OSA patients, which may accurately and reliably identify phenotype of patients.

Effect of the supergravity on the formation and cycle life of non-aqueous lithium metal batteries.

Extra-terrestrial explorations require electrochemical energy storage devices able to operate in gravity conditions different from those of planet earth. In this context, lithium (Li)-based batteries have not been fully investigated, especially cell formation and cycling performances under supergravity (i.e., gravity > 9.8 m s-2) conditions. To shed some light on these aspects, here, we investigate the behavior of non-aqueous Li metal cells under supergravity conditions. The physicochemical and electrochemical characterizations reveal that, distinctly from earth gravity conditions, smooth and dense Li metal depositions are obtained under supergravity during Li metal deposition on a Cu substrate. Moreover, supergravity allows the formation of an inorganic-rich solid electrolyte interphase (SEI) due to the strong interactions between Li+ and salt anions, which promote significant decomposition of the anions on the negative electrode surface. Tests in full Li metal pouch cell configuration (using LiNi0.8Co0.1Mn0.1O2-based positive electrode and LiFSI-based electrolyte solution) also demonstrate the favorable effect of the supergravity in terms of deposition morphology and SEI composition and ability to carry out 200 cycles at 2 C (400 mA g-1) rate with a capacity retention of 96%.