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The impact of various fatty acid types on adaptive immunity remains uncertain, and their roles remain unelucidated. Stearoyl-CoA desaturase (Scd) is a D-9 desaturase, which is a key rate-limiting enzyme for the conversion of saturated fatty acids (SFA) to monounsaturated fatty acids (MUFA) in the fatty acid de novo synthesis. Scd-1 converts stearic acid (SA) and palmitic acid (PA) to oleic acid (OA) and palmitoleic acid (PO), respectively. In this study, through a series of experiments, we showed that Scd-1 and its resulting compound, OA, have a substantial impact on the transformation of CD8+ naïve T cells into effector T cells. Inactivation of Scd-1 triggers the specialization of CD8+ T cells into the Teff subset, enhancing the effector function and mitochondrial metabolism of Teff cells, and OA can partially counteract this. A deeper understanding of lipid metabolism in immune cells and its impact on cell function can lead to new therapeutic approaches for controlling the immune response and improving prognosis. [ABSTRACT FROM AUTHOR]

Many techniques have been proposed to harden programs with protection mechanisms to defend against vulnerability exploits. Unfortunately the vast majority of them cannot be applied to closed source software because they require access to program source code. This paper presents our work on automatically hardening binary code with security workarounds, a protection mechanism that prevents vulnerabilities from being triggered by disabling vulnerable code. By working solely with binary code, our approach is applicable to closed source software. To automatically synthesize security workarounds, we develop binary program analysis techniques to identify existing error handling code in binary code, synthesize security workarounds in the form of binary code, and instrument security workarounds into binary programs. We designed and implemented a prototype or our approach for Windows and Linux binary programs. Our evaluation shows that our approach can apply security workarounds to an average of 69.3% of program code and the security workarounds successfully prevents exploits to trigger real-world vulnerabilities. [ABSTRACT FROM AUTHOR]

Forest is one of the most challenging environments to be recorded in a three-dimensional (3D) digitized geometrical representation, because of the size and the complexity of the environment and the data-acquisition constraints brought by on-site conditions. Previous studies have indicated that the data-acquisition pattern can have more influence on the registration results than other factors. In practice, the ideal short-baseline observations, i.e., the dense collection mode, is rarely feasible, considering the low accessibility in forest environments and the commonly limited labor and time resources. The wide-baseline observations that cover a forest site using a few folds less observations than short-baseline observations, are therefore more preferable and commonly applied. Nevertheless, the wide-baseline approach is more challenging for data registration since it typically lacks the required sufficient overlaps between datasets. Until now, a robust automated registration solution that is independent of special hardware requirements has still been missing. That is, the registration accuracy is still far from the required level, and the information extractable from the merged point cloud using automated registration could not match that from the merged point cloud using manual registration. This paper proposes a discrete overlap search (DOS) method to find correspondences in the point clouds to solve the low-overlap problem in the wide-baseline point clouds. The proposed automatic method uses potential correspondences from both original data and selected feature points to reconstruct rough observation geometries without external knowledge and to retrieve precise registration parameters at data-level. An extensive experiment was carried out with 24 forest datasets of different conditions categorized in three difficulty levels. The performance of the proposed method was evaluated using various accuracy criteria, as well as based on data acquired from different hardware, platforms, viewing perspectives, and at different points of time. The proposed method achieved a 3D registration accuracy at a 0.50-cm level in all difficulty categories using static terrestrial acquisitions. In the terrestrial-aerial registration, data sets were collected from different sensors and at different points of time with scene changes, and a registration accuracy at the raw data geometric accuracy level was achieved. These results represent the highest automated registration accuracy and the strictest evaluation so far. The proposed method is applicable in multiple scenarios, such as 1) the global positioning of individual under-canopy observations, which is one of the main challenges in applying terrestrial observations lacking a global context, 2) the fusion of point clouds acquired from terrestrial and aerial perspectives, which is required in order to achieve a complete forest observation, 3) mobile mapping using a new stop-and-go approach, which solves the problems of lacking mobility and slow data collection in static terrestrial measurements as well as the data-quality issue in the continuous mobile approach. Furthermore, this work proposes a new error estimate that units all parameter-level errors into a single quantity and compensates for the downsides of the widely used parameter- and object-level error estimates; it also proposes a new deterministic point sets registration method as an alternative to the popular sampling methods. [ABSTRACT FROM AUTHOR]

Objective(s): The purpose of this study is to investigate the indication function of the calcium circulation-related factors on the damage to muscle strength and contraction function after nerve injury. The target factors include ryanodine receptor (RyR), inositol-1,4,5-triphosphate receptor (IP3R), phospholamban (PLN), cryptocalcitonin (CASQ), ATPase and troponin C (TNNC). Materials and Methods: Sprague-Dawley (SD) rats were randomly divided into sham-operated group (SO), sciatic nerve injury group (SNI) and sciatic nerve disconnection group (SNT). Sciatic nerve function index and stretching test were used to examine the changes to muscle strength; bilateral gastrocnemius muscles were extracted after execution for gastrocnemius wet weight ratio test. HE staining slides and average cross-sectional area of muscle fibers were acquired to analyze the muscle atrophy. The transcription level of the factors was also measured. Results: Sciatic nerve damage in SNI group was significantly higher than that in SO group in the 6 weeks, but there was no significant difference between SNT and SO groups fallowing sciatic nerve damage. Sciatic nerve function in SNT group was worse than that in SNI group. The average crosssectional area of gastrocnemius muscle fibers in SNI and SNT groups was significantly reduced compared to that in SO group. The transcriptional levels of RyR, PLN, CASQ, ATPase and TNNC in SNI and SNT groups were significantly different from those in SO group. Conclusion: Calcium circulation-related factors could be used as potential indicators for assessment of damages to muscle strength. [ABSTRACT FROM AUTHOR]

Objective(s): Myocarditis is characterized by inflammatory cell infiltration in myocardial stroma. Attenuation of tumor necrosis factor (TNF)-α and interleukin (IL)-1β is a reliable mark for improving the prognosis. Protein kinase B (Akt) plays an important role in the development and progression of myocarditis. The specific role of the natural inhibitor of Akt, Deguelin, on myocarditis has not been reported. In this study, we used deguelin to investigate the effects of natural Akt inhibitor on myocarditis in experimental autoimmune myocarditis (EAM) rats. Materials and Methods: EAM rat models were made by using Lewis rats and Deguelin was injected intraperitoneally on day 3, 6, 9, 12 and 15 after successful modeling. On day 18, rats were sacrificed and the heart weight (HW)/ body weight (BW) ratio were measured. The pathological changes, pathological scores and fibrosis area were evaluated after H.&E. and Masson’s trichrome staining. The mRNA levels of TNF-α and IL-1β were measured by RT-qPCR, while the protein expressions of TNF-α and IL-1β were detected by immunohistochemical staining and Western bolt. The protein expressions of Akt, Akt1, phosphorylated (p-) Akt and nuclear factor (NF)-κB were detected by Western bolt. Results: We found that the TNF-α and IL-1β levels, inflammatory scores and fibrosis areas were markedly increased after 18 days deguelin administration. Conclusion: Akt inhibition with deguelin may aggravate myocarditis of EAM rats. [ABSTRACT FROM AUTHOR]

Objective: To explore the relationships between expression of CD44v6, lymphatic vessel density (LVD) and the clinicopathological parameters of patients. Methods: One hundred early gastric cancer tissues, 55 high-grade gastric intraepithelial neoplasia (HGIN) tissues, 60 low-grade gastric intraepithelial neoplasia (LGIN) tissues and 60 chronic superficial gastritis tissues were collected and set as gastric cancer group, HGIN group, LGIN group and gastritis group respectively. The expression of CD44v6 and LVD of patients in all the groups were detected using twostep immunohistochemical method to analyze the relationships between the expression of CD44v6 and lymphatic vessel density in early gastric cancer tissues and their relationships with the clinicopathological parameters of patients. The values of LVD in predicting lymph node metastasis in early gastric cancer were evaluated using receiver operating characteristic (ROC) curve. Results: The positive expression of CD44v6 and LVD in the gastritis group, LGIN group, HGIN group and gastric cancer group gradually increased. The positive expression of CD44v6 and LVD in early gastric cancer tissues were in no correlation with the gender, age, tumor site, maximum diameter, differentiation degree and invasion depth (P>0.05) and in a correlation with lymphatic metastasis and lymphatic vessel invasion (P<0.06). The positive expression of CD44v6 in the early gastric cancer tissues was in a positive correlation with LVD (P<0.05). The analysis of ROC curves suggested that the area under ROC curve of predicting lymphatic metastasis of early gastric cancer with LVD was 0.837 (95% CI: 0.756~0.910), and the cut-off value was 14; the corresponding sensitivity and specificity were 63.6% and 90.2 respectively. Conclusion: The expression of CD44v6 and LVD in early gastric cancer tissues are in a close correlation with the clinicopathologic features, and joint detection of expression of CD44v6 and LVD can be taken as the indicator of gastric cancer metastasis. [ABSTRACT FROM AUTHOR]

Notch signaling induced interleukin (IL)-22 secretion by CD4+ T cells via retinoid-related orphan nuclear receptor γt (RORγt) or aryl hydrocarbon receptor (AhR). Previous studies have demonstrated that Notch-AhR-IL-22 axis took part in the pathogenesis of chronic viral infection, however, its role in cancer has not been fully elucidated. Thus, the aim of current study was to investigate the involvement of Notch-AhR-IL-22 axis in the pathogenesis of lung adenocarcinoma. A total of 37 late-stage lung adenocarcinoma patients and 17 healthy individuals were enrolled. CD4+ T cells were purified from peripheral bloods and bronchoalveolar lavage fluids (BALF), and were stimulated with γ-secretase inhibitor (GSI). mRNA corresponding to Notch receptors and transcriptional factors were measured by real-time PCR. IL-22 concentration was investigated by ELISA. The bioactivity (including cellular proliferation, cell cycle, apoptosis, and invasion) of lung adenocarcinoma cell line A549 was also assessed in response to recombinant IL-22 stimulation in vitro. Notch1 mRNA expression was significantly elevated in CD4+ T cells purified from peripheral bloods and tumor site BALF in lung adenocarcinoma patients. IL-22 expression and RORγt/AhR mRNA in BALF was also remarkably increased in tumor site. Inhibition of Notch signaling by GSI did not affect cellular proliferation, but reduced IL-22 production in CD4+ T cells from BALF, along with down-regulation of AhR, but not RORγt. Moreover, IL-22 stimulation promoted A549 cells invasion. The current data indicated that elevated Notch1 induced higher IL-22 secretion by CD4+ T cells in lung adenocarcinoma patients, and Notch-AhR-IL-22 axis took part in the pathogenesis of lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Osteomyelitis is commonly caused by Staphylococcus aureus. Both erythromycin and curcumin can suppress S. aureus growth, but their roles in osteomyelitis are barely studied. We aim to explore the activities of erythromycin and curcumin against chronical osteomyelitis induced by methicillin-resistant S. aureus (MRSA). Chronicle implant-induced osteomyelitis was established by MRSA infection in male Wistar rats. Four weeks after bacterial inoculation, rats received no treatment, erythromycin monotherapy, curcumin monotherapy, or erythromycin plus curcumin twice daily for 2 weeks. Bacterial levels, bone infection status, inflammatory signals and side effects were evaluated. Rats tolerated all treatments well, with no death or side effects such as, diarrhea and weight loss. Two days after treatment completion, erythromycin monotherapy did not suppress bacterial growth and had no effect in bone infection, although it reduced serum pro-inflammatory cytokines tumor necrosis factor (TNF)-a and interleukin (IL)-6. Curcumin monotherapy slightly suppressed bacterial growth, alleviated bone infection and reduced TNF-α and IL-6. Erythromycin and curcumin combined treatment markedly suppressed bacterial growth, substantially alleviated bone infection and reduced TNF-a and IL-6. Combination of erythromycin and curcumin lead a much stronger efficiency against MRSA induced osteomyelitis in rats than monotherapy. Our study suggests that erythromycin and curcumin could be a new combination for treating MRSA induced osteomyelitis. [ABSTRACT FROM AUTHOR]

A compact solution for the accurate and automated collection of field data in forests has long been anticipated, and tremendous efforts have been made by applying various remote sensing technologies. The employment of advanced techniques, such as the smartphone-based relascope, terrestrial and mobile photogrammetry, and laser scanning, have led to steady progress, thus steering their applications to a practical stage. However, all recent strategies require human operation for data acquisition, either to place the instrument on site (e.g., terrestrial laser scanning, TLS) or to carry the instrument by an operator (e.g., personal laser scanning, PLS), which remained laborious and expensive. In this paper, a new concept of autonomous forest field investigation is proposed, which includes data collection above and inside the forest canopy by integrating an unmanned aircraft vehicle (UAV) with autonomous driving. As a first step towards realizing this concept, the feasibility of automated tree-level field measurements from a mini-UAV laser scanning system is evaluated. A "low-cost" Velodyne Puck LITE laser scanner is applied for the test. It is revealed that, with the above canopy flight data, the detection rate was 100% for isolated and dominant trees. The accuracy of direct measurements on the diameter at breast height (DBH) from the point cloud is between 5.5 and 6.8 cm due to the system and the methodological error propagation. The estimation of DBH from point cloud metrics, on the other hand, showed an accuracy of 2.6 cm, which is comparable to the accuracies obtained with terrestrial surveys using mobile laser scanning (MLS), TLS or photogrammetric point clouds. The estimation of basal area, stem volume and biomass of individual trees could be obtained with less than 20% RMSE, which is adequate for field reference measurements at tree level. Such results indicate that the concept of UAV laser scanning-based automated tree-level field reference collection can be feasible, even though the whole topic requires further research. [ABSTRACT FROM AUTHOR]

Excessive inflammation including IL-1β -initiated signaling is among the earlies reactions that can cause neuronal damage following spinal cord injury (SCI). It has been suggested that microRNAs may participate in stem cell repair to facilitate functional recovery following SCI. In this study we have shown that in cultured human neural stem cells (hNSC), IL-11β reduced the expression of both KIF3B (kinesin family member 3B) and NOSIP (nitric oxide synthase-interacting protein), two key modulators for restricting inflammation and promoting neuronal regeneration. The induction of microRNA-372 (miR-372) by IL-11β is specifically responsible for the inhibition of KIF3B and NOSIP. The 3' -untranslated regions (UTRs) of both KIF3B and NOSIP contain targeting sequences to miR-372 that directly inhibit their expression. Moreover, we found that the expression of miR-372 was stimulated in hNSC by IL-1β through an NF-κ binding site at its promoter region. Finally, stable overexpression of miR-372 inhibitor in hNSC rescued the IL-1β-induced impairment as shown by significant improvements in tissue water content, myeloperoxidase activity, and behavioral assessments in SCI rats. These findings suggest a critical role of miR-372 in inflammatory signaling and pinpoint a novel target for the treatment of acute SCI. NEW & NOTEWORTHY Our data demonstrate that IL-1β can impair the functional recovery of neural stem cell transplant therapy for spinal cord injury (SCI) treatment in rats. This effect is dependent on microRNA-372 (miR-372)-dependent gene repression of KIF3B and NOSIP. Therefore, specific knockdown of miR-372 may provide benefits for SCI treatments. [ABSTRACT FROM AUTHOR]

Small unmanned aerial vehicle (UAV) based remote sensing is a rapidly evolving technology. Novel sensors and methods are entering the market, offering completely new possibilities to carry out remote sensing tasks. Three-dimensional (3D) hyperspectral remote sensing is a novel and powerful technology that has recently become available to small UAVs. This study investigated the performance of UAV-based photogrammetry and hyperspectral imaging in individual tree detection and tree species classification in boreal forests. Eleven test sites with 4151 reference trees representing various tree species and developmental stages were collected in June 2014 using a UAV remote sensing system equipped with a frame format hyperspectral camera and an RGB camera in highly variable weather conditions. Dense point clouds were measured photogrammetrically by automatic image matching using high resolution RGB images with a 5 cm point interval. Spectral features were obtained from the hyperspectral image blocks, the large radiometric variation of which was compensated for by using a novel approach based on radiometric block adjustment with the support of in-flight irradiance observations. Spectral and 3D point cloud features were used in the classification experiment with various classifiers. The best results were obtained with Random Forest and Multilayer Perceptron (MLP) which both gave 95% overall accuracies and an F-score of 0.93. Accuracy of individual tree identification from the photogrammetric point clouds varied between 40% and 95%, depending on the characteristics of the area. Challenges in reference measurements might also have reduced these numbers. Results were promising, indicating that hyperspectral 3D remote sensing was operational from a UAV platform even in very difficult conditions. These novel methods are expected to provide a powerful tool for automating various environmental close-range remote sensing tasks in the very near future. [ABSTRACT FROM AUTHOR]

This paper investigated the potential of multispectral airborne laser scanning (ALS) data for individual tree detection and tree species classification. The aim was to develop a single-sensor solution for forest mapping that is capable of providing species-specific information, required for forest management and planning purposes. Experiments were conducted using 1903 ground measured trees from 22 sample plots and multispectral ALS data, acquired with an Optech Titan scanner over a boreal forest, mainly consisting of Scots pine (Pinus Sylvestris), Norway spruce (Picea Abies), and birch (Betula sp.), in southern Finland. ALS-features used as predictors for tree species were extracted from segmented tree objects and used in random forest classification. Different combinations of features, including point cloud features, and intensity features of single and multiple channels, were tested. Among the field-measured trees, 61.3% were correctly detected. The best overall accuracy (OA) of tree species classification achieved for correctly-detected trees was 85.9% (Kappa = 0.75), using a point cloud and single-channel intensity features combination, which was not significantly different from the ones that were obtained either using all features (OA = 85.6%, Kappa = 0.75), or single-channel intensity features alone (OA = 85.4%, Kappa = 0.75). Point cloud features alone achieved the lowest accuracy, with an OA of 76.0%. Field-measured trees were also divided into four categories. An examination of the classification accuracy for four categories of trees showed that isolated and dominant trees can be detected with a detection rate of 91.9%, and classified with a high overall accuracy of 90.5%. The corresponding detection rate and accuracy were 81.5% and 89.8% for a group of trees, 26.4% and 79.1% for trees next to a larger tree, and 7.2% and 53.9% for trees situated under a larger tree, respectively. The results suggest that Channel 2 (1064 nm) contains more information for separating pine, spruce, and birch, followed by channel 1 (1550 nm) and channel 3 (532 nm) with an overall accuracy of 81.9%, 78.3%, and 69.1%, respectively. Our results indicate that the use of multispectral ALS data has great potential to lead to a single-sensor solution for forest mapping. [ABSTRACT FROM AUTHOR]

Stretchable electronics represent a new generation of electronics that utilize soft, deformable elastomers as the substrate or matrix instead of the traditional rigid printed circuit boards. As the most essential component of stretchable electronics, the conductors should meet the requirements for both high conductivity and the capability to maintain conductive under large deformations such as bending, twisting, stretching, and compressing. This review summarizes recent progresses in various aspects of this fascinating and challenging area, including materials for supporting elastomers and electrical conductors, unique designs and stretching mechanics, and the subtractive and additive patterning techniques. The applications are discussed along with functional devices based on these conductors. Finally, the review is concluded with the current limitations, challenges, and future directions of stretchable conductors. [ABSTRACT FROM AUTHOR]

Individual tree delineation using remotely sensed data plays a very important role in precision forestry because it can provide detailed forest information on a large scale, which is required by forest managers. This study aimed to evaluate the utility of airborne laser scanning (ALS) data for individual tree detection and species classification in Japanese coniferous forests with a high canopy density. Tree crowns in the study area were first delineated by the individual tree detection approach using a canopy height model (CHM) derived from the ALS data. Then, the detected tree crowns were classified into four classes-Pinus densiflora, Chamaecyparis obtusa, Larix kaempferi, and broadleaved trees-using a tree crown-based classification approach with different combinations of 23 features derived from the ALS data and true-color (red-green-blue-RGB) orthoimages. To determine the best combination of features for species classification, several loops were performed using a forward iteration method. Additionally, several classification algorithms were compared in the present study. The results of this study indicate that the combination of the RGB images with laser intensity, convex hull area, convex hull point volume, shape index, crown area, and crown height features produced the highest classification accuracy of 90.8% with the use of the quadratic support vector machines (QSVM) classifier. Compared to only using the spectral characteristics of the orthophotos, the overall accuracy was improved by 14.1%, 9.4%, and 8.8% with the best combination of features when using the QSVM, neural network (NN), and random forest (RF) approaches, respectively. In terms of different classification algorithms, the findings of our study recommend the QSVM approach rather than NNs and RFs to classify the tree species in the study area. However, these classification approaches should be further tested in other forests using different data. This study demonstrates that the synergy of the ALS data and RGB images could be a promising approach to improve species classifications. [ABSTRACT FROM AUTHOR]

Height models based on high-altitude aerial images provide a low-cost means of generating detailed 3D models of the forest canopy. In this study, the performance of these height models in the detection of individual trees was evaluated in a commercially managed boreal forest. Airborne digital stereo imagery (DSI) was captured from a flight altitude of 5 km with a ground sample distance of 50 cm and corresponds to regular national topographic airborne data capture programs operated in many countries. Tree tops were detected from smoothed canopy height models (CHM) using watershed segmentation. The relative amount of detected trees varied between 26% and 140%, and the RMSE of plot-level arithmetic mean height between 2.2 m and 3.1 m. Both the dominant tree species and the filter used for smoothing affected the results. Even though the spatial resolution of DSI-based CHM was sufficient, detecting individual trees from the data proved to be demanding because of the shading effect of the dominant trees and the limited amount of data from lower canopy levels and near the ground. [ABSTRACT FROM AUTHOR]

It is anticipated that many of the future forest mapping applications will be based on three-dimensional (3D) point clouds. A comparison study was conducted to verify the explanatory power and information contents of several 3D remote sensing data sources on the retrieval of above ground biomass (AGB), stemvolume (VOL), basal area (G), basal-area weighted mean diameter (Dg) and Lorey's mean height (Hg) at the plot level, utilizing the following data: synthetic aperture radar (SAR) Interferometry, SAR radargrammetry, satellite-imagery having stereo viewing capability, airborne laser scanning (ALS) with various densities (0.8-6 pulses/m²) and aerial stereo imagery. Laser scanning is generally known as the primary source providing a 3D point cloud. However, photogrammetric, radargrammetric and interferometric techniques can be used to produce 3D point clouds from space- and air-borne stereo images. Such an image-based point cloud could be utilized in a similar manner as ALS providing that accurate digital terrain model is available. In this study, the performance of these data sources for providing point cloud data was evaluated with 91 sample plots that were established in Evo, southern Finland within a boreal forest zone and surveyed in 2014 for this comparison. The prediction models were built using random forests technique with features derived from each data sources as independent variables and field measurements of forest attributes as response variable. The relative root mean square errors (RMSEs) varied in the ranges of 4.6% (0.97 m)-13.4% (2.83 m) for Hg, 11.7% (3.0 cm)-20.6% (5.3 cm) for Dg, 14.8% (4.0 m²/ha)-25.8% (6.9 m²/ha) for G, 15.9% (43.0 m³/ha)-31.2% (84.2 m³/ha) for VOL and 14.3% (19.2 Mg/ha)-27.5% (37.0 Mg/ha) for AGB, respectively, depending on the data used. Results indicate that ALS data achieved the most accurate estimates for all forest inventory attributes. For image-based 3D data, high-altitude aerial images and WorldView-2 satellite optical image gave similar results for Hg and Dg, which were only slightly worse than those of ALS data. As expected, spaceborne SAR data produced the worst estimates. WorldView-2 satellite data performed well, achieving accuracy comparable to the one with ALS data for G, VOL and AGB estimation. SAR interferometry data seems to contain more information for forest inventory than SAR radargrammetry and reach a better accuracy (relative RMSE decreased from 13.4% to 9.5% for Hg, 20.6% to 19.2% for Dg, 25.8% to 20.9% for G, 31.2% to 22.0% for VOL and 27.5% to 20.7% for AGB, respectively). However, the availability of interferometry data is limited. The results confirmed the high potential of all 3D remote sensing data sources for forest inventory purposes. However, the assumption of using other than ALS data is that there exist a high quality digital terrain model, in our case it was derived from ALS. [ABSTRACT FROM AUTHOR]

A harvester enables detailed roundwood data to be collected during harvesting operations by means of the measurement apparatus integrated into its felling head. These data can be used to improve the efficiency of wood procurement and also replace some of the field measurements, and thus provide both less costly and more detailed ground truth for remote sensing based forest inventories. However, the positional accuracy of harvester-collected tree data is not sufficient currently to match the accuracy per individual trees achieved with remote sensing data. The aim in the present study was to test the accuracy of various instruments utilizing global satellite navigation systems (GNSS) in motion under forest canopies of varying densities to enable us to get an understanding of the current state-of-the-art in GNSS-based positioning under forest canopies. Tests were conducted using several different combinations of GNSS and inertial measurement unit (IMU) mounted on an all-terrain vehicle (ATV) "simulating" a moving harvester. The positions of 224 trees along the driving route were measured using a total-station and real-time kinematic GPS. These trees were used as reference items. The position of the ATV was obtained using GNSS and IMU with an accuracy of 0.7 m (root mean squared error (RMSE) for 2D positions). For the single-frequency GNSS receivers, the RMSE of real-time 2D GNSS positions was 4.2-9.3 m. Based on these results, it seems that the accuracy of novel single-frequency GNSS devices is not so dependent on forest conditions, whereas the performance of the tested geodetic dual-frequency receiver is very sensitive to the visibility of the satellites. When postprocessing can be applied, especially when combined with IMU data, the improvement in the accuracy of the dual-frequency receiver was significant. [ABSTRACT FROM AUTHOR]

Histone methyltransferase enhancer of zeste homolog 2 (EZH2) has been reported to be associated with certain malignant phenotypes in cervical cancer. However, clinicopathological parameters and clinical outcomes of EZH2 in cervical cancer, particularly in cervical squamous cell carcinoma (CSCC) remain largely unknown. The retrospective cohort comprising of 117 consecutive patients with CSCC was incorporated into a tissue microarray which also included 23 paired normal tissues. Immunohistochemical analysis was performed to evaluate the correlation between EZH2 expression and clinicopathological implications. Aberrant overexpression of EZH2 was frequently observed in CSCCs as compared with adjacent normal tissues (P=0.0005). Expression of EZH2 is associated with poor tumor differentiation grade (P=0.020) and lymphovascular invasion (P=0.012). Univariate analysis revealed that the patients with CSCC whose tumors exhibited higher EZH2 levels had inferior overall survival (OS) compared to those whose tumors expressed lower EZH2 (log rank P=0.004). In the multivariate analysis, EZH2 expression was an independent predictor of OS (hazard ratio = 1.836, 95% confidence interval: 1.090-2.993, P=0.022). EZH2 overexpression is common in the development of CSCC and is a promising prognostic predictor for patients with CSCC. [ABSTRACT FROM AUTHOR]

Large animal models of osteoporosis are essential for osteoporosis research. However, the time required to establish an accurate osteoporosis model is unknown. Therefore, the aim of the present study was to establish a large animal model of osteoporosis in goats. In total, 14 Chinese goats were divided into an ovariectomized (OVX, n=7) or sham-operated (SHAM, n=7) group. Vertebral bodies were used to measure the bone mineral density (BMD) prior to the ovariectomy and at 24 months after the ovariectomy. In addition, the BMD of the femoral neck, femoral diaphysis and tibial diaphysis were measured 24 months postoperatively. Bone samples from the vertebral body, femoral head and femoral neck were scanned by micro-computed tomography (CT) to visualize the trabecular and cortical microstructure. Furthermore, the vertebral body, femoral head, femoral neck and tibial diaphysis were analyzed for mechanical strength. The BMD of vertebral body of the OVX group decreased significantly (P<0.01) at 24 months after the ovariectomy when compared with the baseline measurements. Micro-CT scans of the vertebral body revealed that the bone volume fraction, trabecular number, trabecular thickness and the degree of anisotropy decreased by 37.1, 36.7, 10.5 and 16.5%, respectively (P<0.01) in the OVX group when compared with the SHAM group. Additionally, the specific bone surface and trabecular spacing significantly increased by 37.7 and 62%, respectively in the OVX group (P<0.001). Cortical bone porosity in the vertebral body and femoral neck was greater in the OVX group when compared with the SHAM group (P<0.05). In addition, mechanical testing revealed a statistically significant difference between the vertebral bodies of the OVX group and the SHAM group. In conclusion, the present study demonstrated that an ovariectomy was able to induce significant osteoporosis and deterioration of mechanical properties in the bones of goats. [ABSTRACT FROM AUTHOR]

The paper investigated the possible gains in using low density (average 1 pulse/m2) full-waveform (FWF) airborne laser scanning (ALS) data for individual tree detection and tree species classification and compared the results to the ones obtained using discrete return laser scanning. The aim is to approach a low-cost, fully ALS-based operative forest inventory method that is capable of providing species-specific diameter distributions required for wood procurement. The point data derived from waveform data were used for individual tree detection (ITD). Features extracted from segmented tree objects were used in random forest classification by which both feature selection and classification were performed. Experiments were conducted with 5532 ground measured trees from 292 sample plots and using FWF data collected with Leica ALS60 scanner over a boreal forest, mainly consisting of pine, spruce and birch, in southern Finland. For the comparisons, system produced multi-echo discrete laser data (DSC) were also analyzed with the same procedures. The detection rate of individual trees was slightly higher using FWF point data than DSC point data. Overall detection accuracy, however, was similar because commission error was increased when omission error was decreasing. The best overall classification accuracy was 73.4% which contains an 11 percentage points increase when FWF features were included in the classification compared with DSC features alone. The results suggest that FWF ALS data contains more information about the structure and physical properties of the environment that can be used in tree species classification of pine, spruce and birch when comparing with DSC ALS data. [ABSTRACT FROM AUTHOR]

This paper reports on a study of measuring stem curves of standing trees of different species and in different growth stages using terrestrial laser scanning (TLS). Pine and spruce trees are scanned using the multiscan approach in the field, and trees are felled to measure them destructively for the purpose of obtaining reference values. The stem curves are automatically retrieved from laser point clouds, resulting in an accuracy of ~i1 cm. The corresponding manual measurements yield similar accuracy but fewer measurements at the upper parts of tree stems, compared with the automated measurements. The stem volumes based on stem curve data and field measurements and the best Finnish national allometric volume equations (using tree species, height, and diameters at heights of 1.3 and 6 m as predictors) result in similar accuracy. The measurement accuracy of the stem curves and stem volumes is similar for both pine and spruce trees. The results of this paper confirm the feasibility of using TLS to produce stem curve data in an automated, accurate and noninvasive way and indicate that the point cloud provides adequate information to accurately derive stem volumes from standing trees. The stem curves and volumes retrieved from point clouds can be employed in various forest management activities, such as the calibration of national or regional allometric curve functions and the prediction of profits in preharvest inventories. [ABSTRACT FROM PUBLISHER]

A professional-quality, personal laser scanning (PLS) system for collecting tree attributes was demonstrated in this paper. The applied system, which is wearable by human operators, consists of a multi-constellation navigation system and an ultra-high-speed phase-shift laser scanner mounted on a rigid baseplate and consisting of a single sensor block. A multipass-corridor-mapping method was developed to process PLS data and a 2,000 m2 forest plot was utilized in the test. The tree stem detection accuracy was 82.6%; the root mean square error (RMSE) of the estimates of tree diameter at breast height (DBH) was 5.06 cm; the RMSE of the estimates of tree location was 0.38 m. The relative RMSE of the DBH estimates was 14.63%. The results showed, for the first time, the potential of the PLS system in mapping large forest plots. Further research on mapping accuracy in various forest conditions, data correction methods and multi-sensoral positioning techniques is needed. The utilization of this system in different applications, such as harvester operations, should also be explored. In addition to collecting tree-level and plot-level data for forest inventory, other possible applications of PLS for forest ecosystem services include mapping of canopy gaps, measuring leaf area index of large areas, documenting and visualizing forest routes feasible for recreation, hiking and berry and mushroom picking. [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to analyze the effectiveness of the subject librarian literacy training and put forward suggestions for the improvement of the subject librarian literacy training based on the satisfaction degree survey for the CALIS III Subject Librarian Literacy Training. Design/methodology/approach – On the basis of the satisfaction degree survey for the CALIS III Subject Librarian Literacy Training, this paper elaborates on the design of the survey, analyzes effectiveness of the training according to the survey results, and further advances suggestions for the enhancement of the subject librarian literacy training. Findings – As an essential part of the library user service, subject services are highly demanding of subject librarians’ literacy and capabilities. The subject librarians should thus own great abilities to be qualified for the innovative subject service work. Although the CALIS III Librarian Literacy Training and Qualification Certification Program, a vital executive program, has made great achievements, the training still needs to be further improved concerning the schedules, teaching atmosphere, training forms, training content, etc., to enhance the subject librarians’ ability, raise the service standards and promote the fast and sound development of librarianship in China. Originality/value – This paper offers detailed information on how to design a satisfaction degree survey for the subject librarian literacy training, analyzes the effectiveness of the librarian literacy training, and finally makes suggestions for the enhancement of the subject librarian literacy training. Keywords Subject librarians, Librarian literacy training, Subject services, Surveys, Training Paper type Case study [ABSTRACT FROM AUTHOR]

Airborne scanning LiDAR is a promising technique for efficient and accurate biomass mapping due to its capacity for direct measurement of the three-dimensional structure of vegetation. A combination of individual tree detection (ITD) and an area-based approach (ABA) introduced in Vastaranta et al. [1] to map forest aboveground biomass (AGB) and stem volume (VOL) was investigated. The main objective of this study was to test the usability and accuracy of LiDAR in biomass mapping. The nearest neighbour method was used in the ABA imputations and the accuracy of the biomass estimation was evaluated in the Finland, where single tree-level biomass models are available. The relative root-mean-squared errors (RMSEs) in plot-level AGB and VOL imputation were 24.9% and 26.4% when field measurements were used in training the ABA. When ITD measurements were used in training, the respective accuracies ranged between 28.5%-34.9% and 29.2%-34.0%. Overall, the results show that accurate plot-level AGB estimates can be achieved with the ABA. The reduction of bias in ABA estimates in AGB and VOL was encouraging when visually corrected ITD (ITDvisual) was used in training. We conclude that it is not feasible to use ITDvisual in wall-to-wall forest biomass inventory, but it could provide a cost-efficient application for acquiring training data for ABA in forest biomass mapping. [ABSTRACT FROM AUTHOR]

We present two improvements for laser-based forest inventory. The first improvement is based on using last pulse data for tree detection. When trees overlap, the surface model between the trees corresponding to the first pulse stays high, whereas the corresponding model from the last pulse results in a drop in elevation, due to its better penetration between the trees. This drop in elevation can be used for separating trees. In a test carried out in Evo, Southern Finland, we used 292 forests plots consisting of more than 5,500 trees and airborne laser scanning (ALS) data comprised of 12.7 emitted laser pulses per m2. With last pulse data, an improvement of 6% for individual tree detection was obtained when compared to using first pulse data. The improvement increased with an increasing number of stems per plot and with decreasing diameter breast height (DBH). The results confirm that there is also substantial information for tree detection in last pulse data. The second improvement is based on the use of individual tree-based features in addition to the statistical point height metrics in area-based prediction of forest variables. The commonly-used ALS point height metrics and individual tree-based features were fused into the non-parametric estimation of forest variables. By using only four individual tree-based features, stem volume estimation improved when compared to the use of statistical point height metrics. For DBH estimation, the point height metrics and individual tree-based features complemented each other. Predictions were validated at plot level. [ABSTRACT FROM AUTHOR]

The objective was to investigate the error sources of the airborne laser scanning based individual tree detection (ITD), and its effects on forest management planning calculations. The investigated error sources were detection of trees (etd), error in tree height prediction (eh) and error in tree diameter prediction (ed). The effects of errors were analyzed with Monte Carlo simulations. etd was modeled empirically based on a tree's relative size. A total of five different tree detection scenarios were tested. Effect of eh was investigated using 5% and 0% and effect of ed using 20%, 15%, 10%, 5%, 0% error levels, respectively. The research material comprised 15 forest stands located in Southern Finland. Measurements of 5,300 trees and their timber assortments were utilized as a starting point for the Monte Carlo simulated ITD inventories. ITD carried out for the same study area provided a starting point (Scenario 1) for etd. In Scenario 1, 60.2% from stem number and 75.9% from total volume (Vtotal) were detected. When the only error source was etd (tree detection varying from 75.9% to 100% of Vtotal), root mean square errors (RMSEs) in stand characteristics ranged between the scenarios from 32.4% to 0.6%, 29.0% to 0.5%, 7.8% to 0.2% and 5.4% to 0.1% in stand basal area (BA), Vtotal, mean height (Hg) and mean diameter (Dg), respectively. Saw wood volume RMSE varied from 25.1% to 0.2%, as pulp wood volume respective varied from 37.8% to 1.0% when errors stemmed only from etd. The effect of ed was most significant for Vtotal and BA and the decrease in RMSE was from 12.0% to 0.6% (BA) and from 10.9% to 0.5% (Vtotal) in the most accurate tree detection scenario when ed varied from 20% to 0%. The effect of increased accuracy in tree height prediction was minor for all the stand characteristics. The results show that the most important error source in ITD is tree detection. At stand level, unbiased predictions for tree height and diameter are enough, given the present tree detection accuracy. [ABSTRACT FROM AUTHOR]

The transmittance of laser pulses through the forest canopy was studied as a function of forest attributes (inventory parameters) and the scanning angle from the point of view of elevation modeling. Here transmittance is defined as the ratio of the number of pulses within a threshold of the detected elevation model to the total number of transmitted pulses. Airborne laser scanning (ALS) using a Leica ALS50-II scanner took place on 25 July 2009 in the Evo test area in Southern Finland. The total number of circular field test plots with a radius of 10 meters was 246. Several of the test plots were observed from two different flight lines, and this resulted in 454 observations. Multiple regression analysis was applied to calculate statistical parameters for the scanning angle and the forest attributes. The canopy layer is an important factor that influences the number of ground hits. We found that the characteristics of the trees determine the number of transmitted pulses penetrating down to the ground level. When using scanning angles between 0 to 15 degrees in forested areas, the results showed that the scanning angle did not have a statistically significant effect on the vegetation penetration nor on the number of ground hits. It appears to be feasible to increase the scanning angle for boreal forest elevation modeling if some degree of local shadowing can be accepted in the data. By increasing the scanning angle, it is also possible to perform laser scanning and digital aerial photography simultaneously even over forested areas. Nationwide laser scanning in Finland and Sweden is carried out with scanning angles of ±20 degrees, but further studies are needed to assess the results when using even larger scanning angles. [ABSTRACT FROM AUTHOR]

Climate change and rising temperatures have been observed to be related to the increase of forest insect damage in the boreal zone. The common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini can cause severe growth loss and tree mortality in Scots pine (Pinus sylvestris L.) (Pinaceae). In this study, logistic LASSO regression, Random Forest (RF) and Most Similar Neighbor method (MSN) were investigated for predicting the defoliation level of individual Scots pines using the features derived from airborne laser scanning (ALS) data and aerial images. Classification accuracies from 83.7% (kappa 0.67) to 88.1% (kappa 0.76) were obtained depending on the method. The most accurate result was produced using RF with a combination of data from the two sensors, while the accuracies when using ALS and image features separately were 80.7% and 87.4%, respectively. Evidently, the combination of ALS and aerial images in detecting needle losses is capable of providing satisfactory estimates for individual trees. [ABSTRACT FROM AUTHOR]

Approaches to deriving forest information from laser scanner data have generally made use of two methods: the area-based and individual tree-based approaches. In this paper, these two methods were evaluated and compared for their abilities to predict forest attributes at the plot level using the same datasets. Airborne laser scanner data were collected over the Evo forest area, southern Finland, with an averaging point density of 2.6 points/m2. Mean height, mean diameter and volume were predicted from laser-derived features for plots (area-based method) or tree height, diameter at breast height and volume for individual trees (individual tree-based method) using random forests technique. To evaluate and compare the two forest inventory methods, the root-mean-squared error (RMSE) and correlation coefficient (R) between the predicted and observed plot-level values were computed. The results indicated that both area-based method (with an RMSE of 6.42% for mean height, 10.32% for mean diameter and 20.90% for volume) and individual tree-based method (with an RMSE of 5.69% for mean height, 10.77% for mean diameter and 18.55% for volume) produced promising and compatible results. Increase in point density is expected to increase the accuracy of the individual tree-based technique more than that of the area-based technique. [ABSTRACT FROM AUTHOR]

Abstract  The present study was initiated to investigate the role of extracellular signal-regulated kinases (ERK) 1/2 signaling pathway in the early response of spinal cord to systemic inflammation by using Western blotting and immunohistochemical techniques in a rat model intraperitoneally injected with 10 mg/kg of lipopolysaccharide (LPS). The results showed that there was a considerable amount of phosphorylated ERK 1/2 protein in the spinal cord of inflamed animals killed under pentobarbital anesthesia. The result of Western blotting showed that the phosphorylation level of ERK 1/2 in the spinal cord was increased at one hour; then 12 and 24 h after LPS injection the level decreased, while the total ERK 1/2 level seemed unchanged. The phosphorylated ERK 1/2 dominantly existed in the microglia cells of the gray matter of spinal cord, as demonstrated with double immunofluorescent staining 1 h after LPS injection. Collectively, the present results suggest that ERK signal pathway involve the cellular activation in the spinal cord following systemic inflammation, with ERK mainly in microglia. The increase of phosphorylation of ERK 1/2 in microglia of spinal cord after LPS injection implicates that ERK signaling pathway involves intracellular activity of microglia responding to the inflammation. [ABSTRACT FROM AUTHOR]

Abstract  Neuronal nitric oxide synthase (nNOS) has been implicated to influence peripheral nerve lesion and regeneration. Post-synaptic density-95 (PSD-95) is one of nNOS-anchoring proteins and plays an important role in specifying the sites of reaction of NO in nervous system. Here we established a rat sciatic nerve crush (SNC) model to examine the spatiotemporal expression of PSD-95 and nNOS. At gene levels, PSD-95 mRNA diminished shortly after crush, and significantly elevated from 2 days to 2 weeks, whereas nNOS decreased progressively post-operation, reached the valley at 1 day, and markedly up-regulated from 1 to 2 weeks after SNC. The expression of both molecules returned to the control level at 4 weeks post-injury. At protein levels, PSD-95 and nNOS underwent the similar changes as their gene expression except for a time lag during up-regulating. At their peak expression, PSD-95 co-labeled with nNOS in Schwann cells (SCs) of sciatic nerve within 0.5 mm from the lesion site, but had few colocalization in axons. In addition, the interaction between PSD-95 and nNOS enhanced significantly at 2 weeks after SNC. These results suggest a correlation of PSD-95 up-regulation with nNOS in reactive SCs of crushed sciatic nerve, which may lead to understanding the function of PSD-95 during peripheral nerve regeneration. [ABSTRACT FROM AUTHOR]

Dexras1, a brain-enriched member of the Ras subfamily of GTPases, as a novel physiologic nitric oxide (NO) effector, anchor neuronal nitric oxide synthase (nNOS) that increased after spinal cord injury (SCI), to specific targets to enhance NO signaling, and is strongly and rapidly induced during treatment with dexamethasone. It is unknown how the central nervous system (CNS) trauma affects the expression of Dexras1. Here we used spinal cord transection (SCT) model to detect expression of Dexras1 at mRNA and protein level in spinal cord homogenates by real-time PCR and Western blot analysis. The results showed that Dexras1 mRNA upregulated at 3 day, 5 day, and 7 day significantly (P\0.05) that was consistent with the protein level except at 7 day. Immunofluorescence revealed that both neurons and glial cells showed Dexras1 immunoreactivivty (IR) around SCT site, but the proportion is different. Importantly, injury-induced expression of Dexras1 was co-labeled by caspase-3 (apoptotic marker) and Tau-1 (marker for pathological oligodendrocyte). Furthermore, colocalization of Dexras1, carboxy-terminal PSD95/DLG/ZO-1 (PDZ) ligand of nNOS (CAPON) and nNOS was observed in neurons and glial cells, supporting the existence of ternary complexes in this model. Thus, the results that the transient high expression of Dexras1 which localized in apoptotic neurons and pathological oligodendrocytes might provide new insight into the secondary response after SCT. [ABSTRACT FROM AUTHOR]