Functional assessment of the gluteus medius, cranial part of the biceps femoris, and vastus lateralis in Beagle dogs based on a novel gait phase classification

In humans, walking analysis based on the gait phase classification has been used for interpretation of functional roles of different movements occurring at individual joints, and it is useful for establishing a rehabilitation plan. However, there have been few reports on canine gait phase classification, and this is one of the reasons for preventing progress in canine rehabilitation. In this study, we determined phases of the canine gait cycle (GC) on the basis of the phase classification for human gait. The canine GC was able to be divided into initial contact (IC) and the following 5 phases: loading response (LR), middle stance (MidSt), pre-swing (PSw), early swing (ESw), and late swing (LSw). Next, the hind limb joint angles of the hip, stifle and tarsal joints and results of surface electromyography of the gluteus medius (GM), cranial part of the biceps femoris (CBF) and vastus lateralis (VL) muscles in relation to the gait phases were analyzed. The activities of three muscles showed similar changes during walking. The muscle activities were high in the LR phase and then declined and reached a minimum in the PSw phase, but they increased and reached a peak in the LSw phase, which was followed by the LR phase. In conclusion, the multiphasic canine GC was developed by modification of the human model, and the GC phase-related changes in the muscle activity and joint angles suggested the functions of GM, CBF and VL muscles in walking

Estimation of Airborne Lidar-Derived Tropical Forest Canopy Height Using Landsat Time Series in Cambodia

In this study, we test and demonstrate the utility of disturbance and recovery information derived from annual Landsat time series to predict current forest vertical structure (as compared to the more common approaches, that consider a sample of airborne Lidar and single-date Landsat derived variables). Mean Canopy Height (MCH) was estimated separately using single date, time series, and the combination of single date and time series variables in multiple regression and random forest (RF) models. The combination of single date and time series variables, which integrate disturbance history over the entire time series, overall provided better MCH prediction than using either of the two sets of variables separately. In general, the RF models resulted in improved performance in all estimates over those using multiple regression. The lowest validation error was obtained using Landsat time series variables in a RF model (R2 = 0.75 and RMSE = 2.81 m). Combining single date and time series data was more effective when the RF model was used (opposed to multiple regression). The RMSE for RF mean canopy height prediction was reduced by 13.5% when combining the two sets of variables as compared to the 3.6% RMSE decline presented by multiple regression. This study demonstrates the value of airborne Lidar and long term Landsat observations to generate estimates of forest canopy height using the random forest algorithm

Aboveground Biomass Estimation Using Structure from Motion Approach with Aerial Photographs in a Seasonal Tropical Forest

We investigated the capabilities of a canopy height model (CHM) derived from aerial photographs using the Structure from Motion (SfM) approach to estimate aboveground biomass (AGB) in a tropical forest. Aerial photographs and airborne Light Detection and Ranging (LiDAR) data were simultaneously acquired under leaf-on canopy conditions. A 3D point cloud was generated from aerial photographs using the SfM approach and converted to a digital surface model (DSMP). We also created a DSM from airborne LiDAR data (DSML). From each of DSMP and DSML, we constructed digital terrain models (DTM), which are DTMP and DTML, respectively. We created four CHMs, which were calculated from (1) DSMP and DTMP (CHMPP); (2) DSMP and DTML (CHMPL); (3) DSML and DTMP (CHMLP); and (4) DSML and DTML (CHMLL). Then, we estimated AGB using these CHMs. The model using CHMLL yielded the highest accuracy in four CHMs (R2 = 0.94) and was comparable to the model using CHMPL (R2 = 0.93). The model using CHMPP yielded the lowest accuracy (R2 = 0.79). In conclusion, AGB can be estimated from CHM derived from aerial photographs using the SfM approach in the tropics. However, to accurately estimate AGB, we need a more accurate DTM than the DTM derived from aerial photographs using the SfM approach

Stimulation of plastidogenesis induced by 5-azacytidine in Euglena gracilis klebs

When etiolated Euglena gracilis was treated with 10 mM 5-azacytidine (5-azaC), an inhibitor of DNA methylation, stimulation of plastidogenesis in both dark and light conditions was observed. The phenomenon occurred in 10-15% of the cells possibly due to the asynchronicity of the cultures. The main features of this sub-population, as evaluated by electron and fluorescence microscopy, were the following: 1. the presence in darkness of differentiating proplastids that were red fluorescent under UV, positive to TCNBT cytochemical reaction (specific for PSII) and negative to DAB (specific for PSI); 2. the acceleration of proplastid differentiation during the first 20-30 h of illumination; 3. the occurrence in both culture conditions of concentric lamellar bodies (LBS). These structures were considered to be proplastids blocked in the first step of evolution, since they emitted a red fluorescence, were contained within compartments limited by a triple-layered envelope, were reactive to TCNBT in darkness and to both TCNBT and DAB in light conditions. Even if the action mechanism of 5-azaC on plastidogenesis in Euglena remains to be defined, the induced stimulatory effect on plastid differentiation pointed to a relationship between DNA methylation and plastid development. Furthermore, the presence of LBS opens the possibility of studying early aspects of plastid development in Euglena