Correcting Underestimation and Overestimation in PolInSAR Forest Canopy Height Estimation Using Microwave Penetration Depth

PolInSAR is an active remote sensing technique that is widely used for forest canopy height estimation, with the random volume over ground (RVoG) model being the most classic and effective forest canopy height inversion approach. However, penetration of microwave energy into the forest often leads to a downward shift of the canopy phase center, which leads to model underestimation of the forest canopy height. In addition, in the case of sparse and low forests, the canopy height is overestimated, owing to the large ground-to-volume amplitude ratio in the RVoG model and severe temporal decorrelation effects. To solve this problem, in this study, we conducted an experiment on forest canopy height estimation with the RVoG model using L-band multi-baseline fully polarized PolInSAR data obtained from the Lope and Pongara test areas of the AfriSAR project. We also propose various RVoG model error correction methods based on penetration depth by analyzing the model’s causes of underestimation and overestimation. The results show that: (1) In tall forest areas, there is a general underestimation of canopy height, and the value of this underestimation correlates strongly with the penetration depth, whereas in low forest areas, there is an overestimation of canopy height owing to severe temporal decorrelation; in this instance, overestimation can also be corrected by the penetration depth. (2) Based on the reference height RH100, we used training sample iterations to determine the correction thresholds to correct low canopy overestimation and tall canopy underestimation; by applying these thresholds, the inversion error of the RVoG model can be improved to some extent. The corrected R2 increased from 0.775 to 0.856, and the RMSE decreased from 7.748 m to 6.240 m in the Lope test area. (3) The results obtained using the infinite-depth volume condition p-value as the correction threshold were significantly better than the correction results for the reference height, with the corrected R2 value increasing from 0.775 to 0.914 and the RMSE decreasing from 7.748 m to 4.796 m. (4) Because p-values require a true height input, we extended the application scale of the method by predicting p-values as correction thresholds via machine learning methods and polarized interference features; accordingly, the corrected R2 increased from 0.775 to 0.845, and the RMSE decreased from 7.748 m to 6.422 m. The same pattern was obtained for the Pongara test area. Overall, the findings of this study strongly suggest that it is effective and feasible to use penetration depth to correct for RVoG model errors

Heparan sulfate-dependent phase separation of CCL5 and its chemotactic activity

Secreted chemokines form concentration gradients in target tissues to control migratory directions and patterns of immune cells in response to inflammatory stimulation; however, how the gradients are formed is much debated. Heparan sulfate (HS) binds to chemokines and modulates their activities. In this study, we investigated the roles of HS in the gradient formation and chemoattractant activity of CCL5 that is known to bind to HS. CCL5 and heparin underwent liquid–liquid phase separation and formed gradient, which was confirmed using CCL5 immobilized on heparin-beads. The biological implication of HS in CCL5 gradient formation was established in CHO-K1 (wild-type) and CHO-677 (lacking HS) cells by Transwell assay. The effect of HS on CCL5 chemoattractant activity was further proved by Transwell assay of human peripheral blood cells. Finally, peritoneal injection of the chemokines into mice showed reduced recruitment of inflammatory cells either by mutant CCL5 (lacking heparin-binding sequence) or by addition of heparin to wild-type CCL5. Our experimental data propose that co-phase separation of CCL5 with HS establishes a specific chemokine concentration gradient to trigger directional cell migration. The results warrant further investigation on other heparin-binding chemokines and allows for a more elaborate insight into disease process and new treatment strategies

Physical activity and sleep pattern in relation to incident Parkinson’s disease: a cohort study

Abstract Background How physical activity (PA) and different sleep traits and overall sleep pattern interact in the development of Parkinson’s disease (PD) remain unknown. Objective To prospectively investigate the joint associations of PA and sleep pattern with risk of PD. Methods Included were 339,666 PD-free participants from the UK Biobank. Baseline PA levels were grouped into low (< 600 MET-mins/week), medium (600 to < 3000 MET-mins/week) and high (≥ 3000 MET-mins/week) according to the instructions of the UK Biobank. Healthy sleep traits (chronotype, sleep duration, insomnia, snoring, and daytime sleepiness) were scored from 0 to 5 and were categorized into “ideal sleep pattern” (≥ 3 sleep scores) and “poor sleep pattern” (0–2 sleep scores). Hazard ratios (HRs) and 95% confidence intervals (CIs) of PD were estimated by Cox proportional hazards models. Results During a median of 11.8 years of follow-up, 1,966 PD events were identified. The PD risk was lower in participants with high PA (HR = 0.73; 95% CI: 0.64, 0.84), compared to those with low PA; and participants with ideal sleep pattern also had a lower risk of PD (HR = 0.78; 95% CI: 0.69, 0.87), compared to those with poor sleep pattern. When jointly investigating the combined effect, participants with both high PA and ideal sleep pattern had the lowest risk of incident PD (HR = 0.55; 95% CI: 0.44, 0.69), compared to those with low PA and poor sleep pattern; notably, participants with high PA but poor sleep pattern also gained benefit on PD risk reduction (HR = 0.74; 95% CI: 0.55, 0.99). Conclusions Both high PA and ideal sleep pattern were independently associated with lower risk of developing PD, and those with both high PA level and ideal sleep pattern had the lowest risk. Our results suggest that improving PA levels and sleep quality may be promising intervention targets for the prevention of PD

Heparan sulfate-dependent phase separation of CCL5 and its chemotactic activity

Secreted chemokines form concentration gradients in target tissues to control migratory directions and patterns of immune cells in response to inflammatory stimulation; however, how the gradients are formed is much debated. Heparan sulfate (HS) binds to chemokines and modulates their activities. In this study, we investigated the roles of HS in the gradient formation and chemoattractant activity of CCL5 that is known to bind to HS. CCL5 and heparin underwent liquid-liquid phase separation and formed gradient, which was confirmed using CCL5 immobilized on heparin-beads. The biological implication of HS in CCL5 gradient formation was established in CHO-K1 (wild-type) and CHO-677 (lacking HS) cells by Transwell assay. The effect of HS on CCL5 chemoattractant activity was further proved by Transwell assay of human peripheral blood cells. Finally, peritoneal injection of the chemokines into mice showed reduced recruitment of inflammatory cells either by mutant CCL5 (lacking heparin-binding sequence) or by addition of heparin to wild-type CCL5. Our experimental data propose that co-phase separation of CCL5 with HS establishes a specific chemokine concentration gradient to trigger directional cell migration. The results warrant further investigation on other heparin-binding chemokines and allows for a more elaborate insight into disease process and new treatment strategies

Additional file 1 of Physical activity and sleep pattern in relation to incident Parkinson’s disease: a cohort study

Supplementary Material