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Background Thomsen-Friedenreich antibody (TF-Ab) is a specific antibody against the Thomsen-Friedenreich antigen (TF-Ag). At present, studies on a number of other tumors have shown that TF-Ab can effectively inhibit metastasis and induce apoptosis in tumor cells. However, the role of TF-Ab in thyroid cancer (TC) remains unclear. Materials and methods Normal subjects and patients with primary papillary TC with or without lymph node metastasis were tested for TF-Ab expression by enzyme-linked immunosorbent assays (ELISAs). Immunofluorescence was used to assess the expression of TF-Ag in thyroid papillary carcinoma with or without lymph node metastasis and undifferentiated cancer tissues. To evaluate the role of TF-Ab in TC, the effects of TF monoclonal antibody (mAb A78-G/A7) on cell biological function were investigated by MTT assays, flow cytometry, adhesion assays and transwell experiments. Results Compared with normal individuals, TF-Ab levels in patients with TC were decreased, but no changes were observed with respect to lymph node metastasis. The expression of TF-Ag in TC tissues was relatively higher than that detected in adjacent tissues, but it was not affected by the presence or absence of lymph node metastasis. Upon treatment mAb A78-G/A7 treating, TC cell cycles were affected, meanwhile the abilities to adhere, invade and migrate were also significantly reduced. Conclusion The results of the present study showed that mAb A78-G/A7 could affect the invasion and migration of all assayed TC cell lines. The effects of mAb A78-G/A7 on the cell cycle, adhesion, invasion and migration of TC cells were more significant than those observed for proliferation and apoptosis.

Filtering of airborne light detection and ranging (LiDAR) data is a challenging task in vegetated mountain areas. Environmental features and LiDAR data characteristics have significant impacts on t...

It has been found that the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is systematically higher than the actual land surface in vegetated areas. This study developed a new...

In recent decades, global biodiversity has gradually diminished due to the increasing pressure from anthropogenic activities and climatic change. Accurate estimations of spatially continuous three-dimensional 3D vegetation structures and terrain information are prerequisites for biodiversity studies, which are usually unavailable in current ecosystem-wide studies. Although the airborne lidar technique has been successfully used for mapping 3D vegetation structures at landscape and regional scales, the relatively high cost of airborne lidar flight mission has significantly limited its applications. The unmanned aerial vehicle UAV provides an alternative platform for lidar data acquisition, which can largely lower the cost and provide denser lidar points compared with airborne lidar. In this study, we implemented a low-cost UAV-borne lidar system, including both a hardware system and a software system, to collect and process lidar data for biodiversity studies. The implemented UAV-borne lidar system was tested in three different ecosystems across China, including a needleleaf–broadleaf mixed forest, an evergreen broadleaf forest, and a mangrove forest. Various 3D vegetation structure parameters e.g. canopy height model, canopy cover, leaf area index, aboveground biomass were derived from the UAV-borne lidar data. The results show that the implemented UAV-borne lidar system can generate very high resolution 3D terrain and vegetation information. The developed UAV-based hardware and software systems provide a turn-key solution for the use of UAV-borne lidar data on biodiversity studies.

Forests of the Sierra Nevada (SN) mountain range are valuable natural heritages for the region and the country, and tree height is an important forest structure parameter for understanding the SN forest ecosystem. There is still a need in the accurate estimation of wall-to-wall SN tree height distribution at fine spatial resolution. In this study, we presented a method to map wall-to-wall forest tree height (defined as Lorey’s height) across the SN at 70-m resolution by fusing multi-source datasets, including over 1600 in situ tree height measurements and over 1600 km2 airborne light detection and ranging (LiDAR) data. Accurate tree height estimates within these airborne LiDAR boundaries were first computed based on in situ measurements, and then these airborne LiDAR-derived tree heights were used as reference data to estimate tree heights at Geoscience Laser Altimeter System (GLAS) footprints. Finally, the random forest algorithm was used to model the SN tree height from these GLAS tree heights, optical imagery, topographic data, and climate data. The results show that our fine-resolution SN tree height product has a good correspondence with field measurements. The coefficient of determination between them is 0.60, and the root-mean-squared error is 5.45 m.

Terrestrial laser scanning (TLS) is a promising tool, used to retrieve leaf area index (LAI). However, the accuracy of LAI estimations based on TLS is still difficult to validate, because...

Treatments to reduce forest fuels are often performed in forests to enhance forest health, regulate stand density, and reduce the risk of wildfires. Although commonly employed, there are concerns that these forest fuel treatments FTs may have negative impacts on certain wildlife species. Often FTs are planned across large landscapes, but the actual treatment extents can differ from the planned extents due to operational constraints and protection of resources e.g. perennial streams, cultural resources, wildlife habitats. Identifying the actual extent of the treated areas is of primary importance to understand the environmental influence of FTs. Light detection and ranging lidar is a powerful remote-sensing tool that can provide accurate measurements of forest structures and has great potential for monitoring forest changes. This study used the canopy height model CHM and canopy cover CC products derived from multi-temporal airborne laser scanning ALS data to monitor forest changes following the implementation of landscape-scale FT projects. Our approach involved the combination of a pixel-wise thresholding method and an object-of-interest OBI segmentation method. We also investigated forest change using normalized difference vegetation index NDVI and standardized principal component analysis from multi-temporal high-resolution aerial imagery. The same FT detection routine was then applied to compare the capability of ALS data and aerial imagery for FT detection. Our results demonstrate that the FT detection using ALS-derived CC products produced both the highest total accuracy 93.5% and kappa coefficient κ 0.70, and was more robust in identifying areas with light FTs. The accuracy using ALS-derived CHM products the total accuracy was 91.6%, and the κ was 0.59 was significantly lower than that using ALS-derived CC, but was still higher than using aerial imagery. Moreover, we also developed and tested a method to recognize the intensity of FTs directly from pre-and post-treatment ALS point clouds.

Lei Zhang,1,* Yanjun Su,1,* Chen Wang,2 Yongsheng Sha,1 Hong Zhu,3 Shumin Xie,4 Sabrina Kwauk,5 Jing Zhang,2 Yunshou Lin,2 Changli Wang1,*1Department of Thoracic Surgery, Key Laboratory of Cancer Prevention and Therapy, Tianjin Lung Cancer Center, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 2Tianjin Medical University, Tianjin, 3Department of Public Health, Tianjin Medical University, Tianjin, 4Xiangya Medical School of Central-South University, Changsha, People's Republic of China; 5School of Public Health, Harvard University, Boston, Cambridge, MA, USA*These authors contributed equally to this workPurpose: This study assessed the nutritional status of elderly Chinese lung cancer inpatients using a revised version of the Mini-Nutritional Assessment (MNA®) tool.Patients and methods: The revised version of the MNA tool was used to assess the nutritional status of 180 elderly Chinese lung cancer inpatients prior to their scheduled surgery between June 2010 and July 2011. Patients' demographic data, anthropometric parameters, and biochemical markers were collected and analyzed.Results: Among the 180 inpatients who underwent the MNA, 9% were malnourished (MNA score < 19), 33% were at risk of malnutrition (MNA score 19–23), and 58% were well nourished (MNA score ≥ 24). There was significant correlation between the MNA scores of patients who were malnourished, at risk of malnutrition, and well nourished (P < 0.001), as well as between total MNA score and most MNA questions. The three patient groups with different nutritional statuses differed significantly in their responses to anthropometrics and global, diet, and subjective assessments.Conclusion: Incidence rates of malnutrition prior to surgery are high among elderly Chinese lung cancer inpatients. The revised MNA is a valid and reliable tool that can be used to assess and prevent malnutrition among these inpatients.Keywords: malnutrition, MNA-SF, nutrition, inpatients, diet