A new noninvasive method for measurement of dynamic lung compliance from fluctuations on photoplethysmography in respiration

The 2023 wearable photoplethysmography roadmap

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology.

[Relationship Between Dynamic Compliance and Airway Resistance and Infection Indicators in Elderly Patients With Lung Infection After Radiotherapy for Esophageal Cancer]

Objective

To investigate the performance of using lung dynamic compliance (Cdyn) and airway resistance (RAW) levels to predict lung infection in elderly esophageal cancer patients who have undergone radiotherapy.

Methods

A total of 298 elderly esophageal cancer patients who received radiotherapy at Shanxi Fenyang Hospital between October 2017 and July 2022 were retrospectively enrolled and their clinical data were collected. The patients were divided into an infection group (124 cases) and a non-infection group (174 cases) according to their status of lung infection. Then, in the infection group, CURB-65 score was used to assess the severity of the patients' lung infection and the patients were further divided into subgroups accordingly, with 36 cases in the mild infection subgroup, 58 cases in the moderate infection subgroup, and 30 cases in the severe infection subgroup. The levels of Cdyn, RAW, and infection indicators, including serum procalcitonin (PCT), interleukin-6 (IL-6), and angiotensin Ⅱ (Ang Ⅱ), were measured in both groups of patients and the differences in the findings were compared between the infection and the non-infection groups and among patients with infection of varying degrees of severity. The correlation between Cdyn and RAW and the levels of PCT, IL-6, and Ang Ⅱ was analyzed. Receiver operating characteristic (ROC) curve was used to evaluate the performance of predicting infection with Cdyn and RAW.

Results

The Cdyn level of patients in the infection group was lower than that of patients in the non-infection group, while the RAW level of the infection group was higher than that of the non-infection group (P<0.05). Among the infection subgroup, the level of Cdyn of the mild infection subgroup was higher than those of the moderate and severe infection subgroups, while the levels of RAW, PCT, IL-6, and Ang Ⅱ of the mild infection subgroup were lower than those of the moderate severe subgroups. The level of Cdyn of the moderate infection subgroup was higher than that of the severe infection subgroup, while the RAW, PCT, IL-6, and Ang Ⅱ levels of the moderate infection subgroup were lower than those of the severe infection subgroup, with all difference being statistically significant (P<0.05). The Cdyn level of patients with lung infection was negatively correlated with PCT, IL-6, and Ang Ⅱ levels and the severity of infection (r=-0.501, -0.430, -0.367, and -0.484, respectively, P<0.05), while RAW was positively correlated with PCT, IL-6, and Ang Ⅱ levels and the severity of infection (r=0.483, 0.395, 0.374, and 0.423, respectively, P<0.05). The area under the curve (AUC) of Cdyn and RAW for predicting lung infection in elderly patients with esophageal cancer after radiotherapy were 0.898 (95% confidence interval [CI]: 0.857-0.930) and 0.823 (95% CI: 0.775-0.865), respectively, and the AUC of combined evaluation of Cdyn and RAW was 0.959 (95% CI: 0.930-0.979), which suggested that the predictive performance of combined evaluation was better than evaluation with Cdyn or RAW alone.

Conclusion

When elderly esophageal cancer patients develop lung infection after radiotherapy, their Cdyn level is decreased, while the levels of RAW, PCT, IL-6, and Ang Ⅱ are increased. In addition, the levels of Cdyn and RAW are correlated with the PCT, IL-6, and Ang Ⅱ levels. The combined use of Cdyn and RAW shows good performance for predicting lung infection in patients.

MSC-EXO and tempol ameliorate bronchopulmonary dysplasia in newborn rats by activating HIF-1α

BACKGROUND

Bronchopulmonary dysplasia (BPD) is a major complication of premature infants and an important cause of morbidity and mortality. This study investigates the effect of the combination of mesenchymal stem cells-derived exosomes (MSC-EXO) and tempol on BPD and analyzes its mechanism.

METHODS

MSC-EXO was extracted by centrifugation and identified by transmission electron microscopy (TEM), nanoparticle tracking analysis, and western blot analysis (WB). Tidal volume (TV), minute ventilation (MV), peak inspiratory flow (PIF), and dynamic pulmonary compliance (Cdyn) of rats were measured by BuxCo pulmonary function experimental platform. Hematoxylin-eosin staining was performed to observe the lung morphology and radical alveolar count (RAC) and mean linear intercept (MLI) were assessed. Immunofluorescence (IF) was conducted to detect the expression of CD31 and α-SMA in pulmonary blood vessels. The kits were used to calculate malondialdehyde (MDA), superoxide dismutase (SOD), and total antioxidant capacity (TAOC) concentration in lung tissue. Enzyme linked immunosorbent assay was applied to detect the levels of IL-1β, IL-17, IL-6, and IFN-γ in bronchoalveolar lavage fluid. In addition, the expressions of HIF-1α, vascular endothelial growth factor (VEGF), p-PI3K, and p-AKT were analyzed by WB and IF.

RESULTS

We successfully extracted and identified MSC-EXO. In BPD rats, TV, MV, PIF, and Cdyn decreased, alveoli were simplified, and the number of interalveoli small vessels, blood vessel density decreased. Moreover, RAC, CD31, TAOC, and SOD decreased, and MLI, α-SMA, MDA, IL-1β, IL-17, IL-6, and IFN-γ increased, which was reversed by the combination of MSC-EXO and tempol treatment after combined treatment. In addition, the expression levels of HIF-1α, VEGF, p-PI3K, and p-AKT were increased after combined treatment.

CONCLUSIONS

Combined treatment could improve lung tissue injury, promote pulmonary vascular remodeling, restore lung function, and inhibit oxidative stress in BPD rats. These effects were achieved through activation of HIF-1α.

Wearable In-Ear PPG: Detailed Respiratory Variations Enable Classification of COPD

An ability to extract detailed spirometry-like breath-ing waveforms from wearable sensors promises to greatly improve respiratory health monitoring. Photoplethysmography (PPG) has been researched in depth for estimation of respiration rate, given that it varies with respiration through overall intensity, pulse amplitude and pulse interval. We compare and contrast the extraction of these three respiratory modes from both the ear canal and finger and show a marked improvement in the respiratory power for respiration induced intensity variations and pulse amplitude variations when recording from the ear canal. We next employ a data driven multi-scale method, noise assisted multivariate empirical mode decomposition (NA-MEMD), which allows for simultaneous analysis of all three respiratory modes to extract detailed respiratory waveforms from in-ear PPG. For rigour, we considered in-ear PPG recordings from healthy subjects, both older and young, patients with chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) and healthy subjects with artificially obstructed breathing. Specific in-ear PPG waveform changes are observed for COPD, such as a decreased inspiratory duty cycle and an increased inspiratory magnitude, when compared with expiratory magnitude. These differences are used to classify COPD from healthy and IPF waveforms with a sensitivity of 87% and an overall accuracy of 92%. Our findings indicate the promise of in-ear PPG for COPD screening and unobtrusive respiratory monitoring in ambulatory scenarios and in consumer wearables.