Comparison of chimeric antigen receptor-T cell-mediated cytotoxicity assays with suspension tumor cells using plate-based image cytometry method.

In the recent decade, chimeric antigen receptor (CAR)-T cell therapy has revolutionized strategies for cancer treatments due to its highly effective clinical efficacy and response for B cell malignancies. The success of CAR-T cell therapy has stimulated the increase in the research and development of various CAR constructs to target different tumor types. Therefore, a robust and efficient in vitro potency assay is needed to quickly identify potential CAR gene design from a library of construct candidates. Image cytometry methodologies have been utilized for various CAR-T cell-mediated cytotoxicity assay using different fluorescent labeling methods, mainly due to their ease-of-use, ability to capture cell images for verification, and higher throughput performance. In this work, we employed the Celigo Image Cytometer to evaluate and compare two CAR-T cell-mediated cytotoxicity assays using GFP-expressing or fluorescent dye-labeled myeloma and plasmacytoma cells. The GFP-based method demonstrated higher sensitivity in detecting CAR-T cell-mediated cytotoxicity when compared to the CMFDA/DAPI viability method. We have established the criteria and considerations for the selection of cytotoxicity assays that are fit-for-purpose to ensure the results produced are meaningful for the specific testing conditions.

Protective effects of aucubin on osteoarthritic chondrocyte model induced by hydrogen peroxide and mechanical stimulus.

BACKGROUND: During the onset of osteoarthritis (OA), certain biochemical events have been shown to accelerate cartilage degradation, including the dysregulation of cartilage ECM anabolism, abnormal generation of reactive oxygen species (ROS) and overproduction of proteolytic enzymes and inflammatory cytokines. The potency of aucubin in protecting cellular components against oxidative stress, inflammation and apoptosis effects are well documented, which makes it a potential candidate for OA treatment. In this study, we aimed to evaluate the protective benefits of aucubin against OA using H2O2 and compression induced OA-like chondrocyte models. METHODS: The effects of aucubin were studied in porcine chondrocytes after 1 mM H2O2 stimulation for 30 min or sustained compression for 24 h. Effects of aucubin on cell proliferation and cytotoxicity of chondrocytes were measured with WST-1 and LDH assays. ROS production was evaluated by the Total ROS/Superoxide Detection Kit. Caspase-3 activity was evaluated by the CaspACE assay system. The levels of apoptosis were evaluated by the Annexin V-FITC apoptosis detection kit. OA-related gene expression was measured by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Total DNA quantification was evaluated by the DNeasy Blood and Tissue kit. Sulfated-glycosaminoglycans (sGAGs) production and content were evaluated by DMMB assay and Alcian blue staining. RESULTS: The results showed that the ROS scavenge effects of aucubin appeared after 1 h of pretreatment. Aucubin could reduce the caspase-3 activity induced by H2O2, and reduced the apoptosis cell population in flowcytometry. In RT-qPCR results, aucubin could maintain ACAN and COL2A1 gene expressions, and prevent IL6 and MMP13 gene up-regulation induced by H2O2 and compression stimulations. In the DMMB assay and Alcian blue staining, aucubin could maintain the sGAG content and protect chondrocytes against compressive stress, but not oxidative stress from H2O2. CONCLUSIONS: These results indicated that aucubin has protective effects in an osteoarthritic chondrocyte model induced by H2O2 and mechanical stimulus.

Extraction of tree crown parameters of high-density pure Cunninghamia lanceolata plantations by combining the U-Net model and watershed algorithm.

As one of the important timber species in China, Cunninghamia lanceolata is widely distributed in southern China. The information of tree individuals and crown plays an important role in accurately monitoring forest resources. Therefore, it is particularly significant to accurately grasp such information of individual C. lanceolata tree. For high-canopy closed forest stands, the key to correctly extract such information is whether the crowns of mutual occlusion and adhesion can be accurately segmented. Taking the Fujian Jiangle State-owned Forest Farm as the research area and using the UAV image as the data source, we developed a method to extract crown information of individual tree based on deep learning method and watershed algorithm. Firstly, the deep learning neural network model U-Net was used to segment the coverage area of the canopy of C. lanceolata, and then the traditional image segmentation algorithm was used to segment the individual tree to obtain the number and crown information of individual tree. Under the condition of maintaining the same training set, validation set and test set, the extraction results of the canopy coverage area by the U-Net model and traditional machine learning methods [random forest (RF) and support vector machine (SVM)] were compared. Then, two individual tree segmentation results were compared, one using the marker-controlled watershed algorithm, and the other using the combination of the U-Net model and marker-controlled watershed algorithm. The results showed that the segmentation accuracy (SA), precision, IoU (intersection over union) and F1-score (harmonic mean of precision and recall) of the U-Net model were higher than those of RF and SVM. Compared with RF, the value of those four indicators increased by 4.6%, 14.9%, 7.6% and 0.05, respectively. Compared with SVM, the four indicators increased by 3.3%, 8.5%, 8.1% and 0.05, respectively. In terms of extracting the number of trees, the overall accuracy (OA) of the U-Net model combined with the marker-controlled watershed algorithm was 3.7% higher than that of the marker-controlled watershed algorithm, with the mean absolute error (MAE) being decreased by 3.1%. In terms of extracting crown area and crown width of individual tree, R2 increased by 0.11 and 0.09, mean squared error decreased by 8.49 m2 and 4.27 m, and MAE decreased by 2.93 m2 and 1.72 m, respectively. The combination of deep learning U-Net model and watershed algorithm could overcome the challenges in accurately extracting the number of trees and the crown information of individual tree of high-density pure C. lanceolata plantations. It was an efficient and low-cost method of extracting tree crown parameters, which could provide a basis for developing intelligent forest resource monitoring.

[Study on the extraction of mycelium polysaccharides from selenium-rich Morchella esculenta with neutral proteinase method].

OBJECTIVE: To study the extraction conditions of mycelium polysaccharides from selenium-rich Morchella esculenta with neutral proteinase for increasing of yield. METHODS: On the basis of single factor tests, orthogonal experiment design was applied to analyze the influence of factors including enzyme dosage, enzymolysis time, enzymolysis temperature and material/liquid ratio on the extraction rate of the polysaccharides. RESULTS: The optimal extraction conditions of mycelium polysaccharides from selenium-rich Morchella esculenta was as follows: enzyme dosage was 1.5%, enzymolysis time was 2 h, enzymolysis temperature was 40 degrees C, and material/liquid ratio was 1:15. The extraction rate of polysaccharide was 11.26% under the extraction conditions. CONCLUSION: The process is simple, stable and practicable, and can be used for the extraction of mycelium polysaccharides from selenium-rich Morchella esculenta.

[Comparison of artificial neural network with compatible biomass model for predicting aboveground biomass of individual tree]. / 人工神经网络与相容性生物量模型预测单木地上生物量的比较.

Forest biomass is an important index in forest development planning and forest resource monitoring. In order to provide a more efficient and low-biased method for estimating individual tree biomass, we introduced artificial neural network here. We used the data of aboveground biomass of 101 Larix olgensis trees harvested from the Dongzhelenghe Forest Farm in Heilongjiang Province to develop four aggregation model systems (AMS), based on different combination of the variables (diameter at breast height, tree height, crown width). The weighted functions were used to eliminate heteroscedasticity. Then, we trained artificial neural network (ANN) biomass model based on the optimal combination. The models were tested by the leave-one-out cross-validation method to compare the accuracy of the two biomass estimation methods. The results showed that biomass model based on only one variable, diameter at breast height, could accurately estimate the biomass of L. olgensis. Adding two indices, tree height and crown width, could improve the fitting performance of models, with AMS4 performing the best among the four addictive model systems. The biomass models developed by the two methods both could estimate biomass at tree level accurately, with the coefficient of determination (R2) of each component was higher than 0.87. Compared with the AMS4, R2 of leaf biomass model was about 0.05 higher, and that of other organs were also about 0.01 higher in artificial neural network model system. In addition, the root mean square error (RMSE) and other indicators were also significantly smaller. For example, the RMSE of tree stem and aboveground biomass were smaller by 2.135 kg and 3.908 kg, respectively. The model's validation statistics mean relative error (MRE) performed better. In general, ANN was a flexible and reliable biomass estimation method, which was worthy consideration when predicting tree component biomass or aboveground biomass.

New design to remove leukocytes from platelet-rich plasma (PRP) based on cell dimension rather than density.

Platelet-rich plasma (PRP) can stimulate the proliferation of stem cells and have a positive effect on tissue repair. Although many commercialized PRP preparation kits are already on the market, first-line clinical workers are still not satisfied with most of the PRP kits. The work of commercial PRP kits is based on the density of blood elements. However, the blood elements are very close in density which makes the separation challenging. Therefore, the mentioned commercialized kits are generally contaminated by leucocytes and erythrocyte. In this study, a home-designed PRP device was developed to use a separation membrane with adequate cut-off pore size of 5 µm, 3 µm and 2 µm for the groups of H5M, H3M, and H2M, respectively, to be placed in the middle of the centrifuge tube. The home-designed H2M showed a very promising results regardless of the final volume (1.82 ± 0.09 ml), platelet yield (8.39 ± 0.44%), Red Blood Cells (0%), White Blood Cells (0%), and Relative Concentration of Platelet Increment value (225.09%). Further, it showed a good result in cell viability and cytotoxicity and confirmed a good multilineage potentials. The concentration in PRP prepared by group H2M was relatively stable and far above average. All the fibrin fibers were linked together as bridging strands or strings and turned into an inter-connected porous structure for nutrients transportation and regenerative cell migration. We believe that the home-designed group H2M should have a great potential to develop into the final product to meet the requirements of first-line clinical workers.

A controlled release system of superoxide dismutase by electrospun fiber and its antioxidant activity in vitro.

In this paper, a new controlled release system of superoxide dismutase was developed by electrospun composite fibers. Highly loading efficacy of sod from 85.6 to 98.0% was achieved. The superoxide dismutase can be released from the system for 234 h, and obvious initial burst release of superoxide dismutase in vitro was not observed. In vitro release rate of superoxide dismutase in the first 66 h basically is faster than the corresponding rate at a later stage. Antioxidant activity of the released superoxide dismutase was still high, and it remained stable during the preparation by electrospinning and release experiment. We hope this composite system be used as an implanted form, in the treatment for several disease involved with the superoxide radical in the future.

The preparation of cell-containing microbubble scaffolds to mimic alveoli structure as a 3D drug-screening system for lung cancer.

Cancer is the leading cause of mortality worldwide, and lung cancer is the most malignant. However, the high failure rate in oncology drug development from in vitro studies to in vivo preclinical models indicates that the modern methods of evaluating drug efficacies in vitro are not reliable. Traditional 2D cell culture has proved inadequate to mimic real physiological conditions. Current 3D cell culture methods do not represent the delicate structure of lung alveoli. To mimic lung alveoli structure, a cell-containing enzyme-crosslinked gelatin microbubble scaffold was produced by mixing surfactant-containing gelatin solution with microbial transglutaminase (mTGase)-mixed A549 cell suspension in a four-channel flow-focusing microfluidic device. With uniform pore size of about 100 µm in diameter, this gelatin microbubble scaffold resembled the lung alveoli in structure and in mechanical properties with good biocompatibility. Effective gemcitabine concentration required to induce cell death in microbubble scaffolds was significantly higher than in 2D culture together with a longer treatment time. Cell death mechanisms were confirmed to be gemcitabine-induced cell apoptosis through Western blotting and real-time polymerase chain reaction. H&E staining and TUNEL assay showed rounded cells with DNA damage in drug-treated scaffolds. Taken together, the cell-containing microbubble scaffolds successfully mimicked lung alveoli in structure and cellular responses after gemcitabine treatment were similar to clinical regimen of treating lung carcinoma. The microbubble scaffold is promising to facilitate anticancer drug discovery by providing more accurate preclinical predictions.

[Responses of radial growth to climate change in Pinus massoniana at different altitudes and slopes.] / ä¸åŒæµ·æ‹”å’Œå¡å‘é©¬å°¾æ¾æ ‘è½®å®½åº¦å¯¹æ°”å€™å˜åŒ–çš„å“åº”.

With dendrochronology method, standard and residual chronologies of Pinus massoniana were established at low altitude (260 m), middle altitude (460 m), high altitude (690 m), sunny slope (270 m), and shady slope (265 m). Relationships between the tree-ring width and the climatic factors were quantified using correlation analysis and redundancy analysis (RDA). The optimal multiple regression models for the radial growth of P. massoniana and the climatic factors were established. We analyzed the change rule of radial growth and its relationship with the climatic factors along with the altitude and slope. The results showed that the radial growth of P. massoniana was significantly affected by precipitation and temperature across the altitude gradient and the slope level, respectively. Among the 120 climatic variables, precipitation in December of last year and the extreme minimum temperature in February of current year had the most significant negative effects on the radial growth at different altitudes and slopes, respectively. This study quantitatively described the impacts of climate change on the radial growth of P. massoniana in the subtropical region, and provided a scientific basis for the planting and management of P. massoniana forest in Jiangle Country under the climate warming background.

[Spatial variation of carbon density in Pinus massoniana forest in Jiangxi Province, China]. / 江西省马尾松林生态系统碳密度空间变异特征.

Carbon density is one of the important indicators for carbon sequestration capacity in forest ecosystems. The analysis of spatial variation in forest carbon density can provide scientific basis for management of forest carbon sink. We investigated the carbon density of Pinus massoniana forest in Jiangxi Province. Based on plot investigation and meaurement of sample carbon content, the spatial autocorrelation and distribution of carbon density were analyzed and explored respectively by using global Moran I, local Moran I and geostatistics. Results from the global Moran I showed that ecosystem carbon density had significant positive spatial autocorrelation and its autocorrelation decreased with the increase of distance. Ecosystem carbon density had no spatial autocorrelation when the distance exceeded 400 km. The spatial distribution of ecosystem carbon density changed from aggregated distribution to random distribution with the increase of distance. Results from the local Moran I showed that the local spatial distribution of ecosystem carbon density was not uniform, and the difference of local spatial distribution gradually increased with the increase of distance. The fitting results of semi-variogram models showed that the spherical model was the best fitting model for the estimation of ecosystem carbon density. The ratio of nugget to sill was 0.36, indicating mode-rate spatial correlation of carbon density. The ecosystem carbon density based on kriging spatial interpolation mainly concentrated in the range of 85.14-153.52 t·hm-2. The spatial distribution regularity was generally low in middle region and high in peripheral region, which was consistent with the terrain characteristics of the study area.

Comparison of object-oriented remote sensing image classification based on different decision trees in forest area.

Geographic Object-Based Image Analysis (GEOBIA) was a product under the background of increasing high-resolution remote sensing data. How to improve the accuracy and efficiency of classification of high-resolution images is one of the important topics in image processing. After objects segmented multiscale by QuickBird image was classified, the efficiency of C5.0, C4.5, and CART decision trees in object-oriented classification of forest areas was analyzed. The accuracy of those three methods were compared with kNN method. The eCognition software was used to multiscale segmentation of remote sensing images, with the result showing that 90 and 40 were the optimal scales. After separating vegetation and non-vegetation at 90 scale, 21 features such as spectrum, texture and shape of different vegetation types were extracted at 40 scale, knowledge mining was carried out by using C5.0, C4.5 and CART decision tree algorithms respectively, and classification rules were automatically established. The vegetation area was classified based on the classification rules and the classification accuracy of different methods was compared. The results showed that the classification accuracy based on decision-tree was higher than that of the traditional kNN method. The accuracy of C5.0 method was the best, with the overall accuracy and Kappa coefficient reaching 90.0% and 0.87, respectively. The decision tree algorithm could effectively improve the accuracy in classification of forest species. The Boosting algorithm of the C5.0 decision tree had the most significant improvement on the classification.

[Purification and analysis of Cimicifuga foetida glycoprotein ( CF- I )].

A kind of glycoprotein ( CF- I ) was extracted from Cimicifuga foetida and purified by DEAE-Cellulose ( DEAE-52) and Sepharose CL-4B. It was identified to be homogeneous glycoprotein complex by electrophoresis and fast protein liquid chromatography (FPLC). alpha-glucosidic bond was detrermined by IR. Typical absorption of polysaccharide was shown in its IR spectrum. It had no typical absorption of nucleic acid or pigment by UV scanning. Glucose, galactose, mannose and arabinose were identified in CF- I with the molar ratio of 11. 94: 2. 18: 1. 38: 1 by GC. Its average MW was estimated to be 5. 8 x 10' by gel filtration. The content of total saccharide, protein and acid polysaccharide was 78% , 14. 4% and 23% respectively. It might be composed of 1-->4 and 1-->6 linked glucopyranose by periodate oxidation and Smith degration.

C-phycocyanin alleviates osteoarthritic injury in chondrocytes stimulated with H2O2 and compressive stress.

During the progression of osteoarthritis (OA), dysregulation of extracellular matrix anabolism, abnormal generation of reactive oxygen species (ROS) and inflammatory cytokines have been shown to accelerate the degradation process of cartilage. The potency of c-phycocyanin (C-PC) to protect cellular components against oxidative stress, along with its anti-inflammation and anti-apoptosis effects, are well documented; however, effects of C-PC on OA are still unclear. In this study, we aimed to investigate the effects of C-PC on OA using H2O2 or compression-stimulated OA-like porcine chondrocyte models. The results showed that C-PC had the ability to inhibit ROS production, reverse caspase-3 activity, and reduce apoptosis cell population. C-PC also reversed aggrecan and type II collagen gene expressions after stimulation with 1mM H2O2 or 60psi of compression. Inhibition of IL-6 and MMP-13 genes was observed in compression-stimulated chondrocytes but not in H2O2-treated cells. In dimethylmethylene blue assay and alcian blue staining, C-PC maintained the sulfated-glycosaminoglycan (sGAG) content after stimulation with compression. We concluded that C-PC can prevent early signs of OA caused by compressive stress and attenuate H2O2-induced oxidative stress. Therefore, we suggest that C-PC can be used as a potential drug candidate for chronic OA treatment.

Development of gelatin nanoparticles conjugated with phytohemagglutinin erythroagglutinating loaded with gemcitabine for inducing apoptosis in non-small cell lung cancer cells.

Gelatin is an efficient drug delivery vehicle for attaching targeting molecules like phytohemagglutinin erythroagglutinating (PHA-E) and carrying the chemotherapeutic agent gemcitabine (GEM). Fluorescent gelatin nanoparticles (GNPs) conjugated with PHA-E and carrying gemcitabine (GNP-(PHA-E)-GEM) were synthesized by nanoprecipitation for guiding gemcitabine-loaded gelatin nanoparticles to NSCLC by PHA-E targeting. GNPs have a uniform narrow size distribution and spherical shape, and their particle size is about 290 nm. The release rate of gemcitabine from nanoparticles reached the plateau of the curve at approximately 30% within 72 hours. PHA-E conjugated nanoparticles could enhance the cellular accumulation of nanoparticles. The results showed that GNP-(PHA-E)-GEM treatment caused an increase of cell growth inhibition and cytotoxicity on NSCLC cells A-549 and H292. In an Annexin V/PI assay, treatment with GNP-(PHA-E)-GEM could induce apoptosis of cancer cells. Treatment of NSCLC cells with GNP-(PHA-E)-GEM firstly resulted in time-dependent inhibition of epidermal growth factor receptor (EGFR) and Akt phosphorylation. And it also could increase p53 phosphorylation. And then it could decrease Bad phosphorylation and increase Bax. Finally, it could result in enhancing the release of cytochrome c, which thus increases caspase-9 and caspase-3. In conclusion, GNP-(PHA-E)-GEM could induce growth inhibition and cytotoxicity, which was mediated through inhibition of EGFR phosphorylation and the switching on of p53 that causes cell apoptosis of NSCLC cells A-549 and H292. It's significant to conjugate PHA-E for targeting cancer and inhibiting EGFR phosphorylation as it could decrease the dosage of gemcitabine, which reduces side effects on normal tissue. GNP-(PHA-E)-GEM has great potential for NSCLC treatment.

Correction: quantitative analysis of ligand-EGFR interactions: a platform for screening targeting molecules.

[This corrects the article DOI: 10.1371/journal.pone.0116610.].

Quantitative analysis of ligand-EGFR interactions: a platform for screening targeting molecules.

Epidermal growth factor receptor (EGFR) is often constitutively stimulated in many cancers owing to the binding of ligands such as epidermal growth factor (EGF). Therefore, it is necessary to investigate the interaction between EGFR and its targeting biomolecules. The main aim of this study was to estimate the binding affinity and adhesion force of two targeting molecules, anti-EGFR monoclonal antibody (mAb LA1) and the peptide GE11 (YHWYGYTPQNVI), with respect to EGFR and to compare these values with those obtained for the ligand, EGF. Surface plasmon resonance (SPR) was used to determine the equilibrium dissociation constant (KD) for evaluating the binding affinity. Atomic force microscopy (AFM) was performed to estimate the adhesion force. In the case of EGFR, the KD of EGF, GE11, and mAb LA1 were 1.77 × 10-7, 4.59 × 10-4 and 2.07 × 10-9, respectively, indicating that the binding affinity of mAb LA1 to EGFR was higher than that of EGF, while the binding affinity of GE11 to EGFR was the lowest among the three molecules. The adhesion force between EGFR and mAb LA1 was 210.99 pN, which is higher than that observed for EGF (209.41 pN), while the adhesion force between GE11 and EGFR was the lowest (59.51 pN). These results suggest that mAb LA1 binds to EGFR with higher binding affinity than EGF and GE11. Moreover, the adhesion force between mAb LA1 and EGFR was greater than that observed for EGF and GE11. The SPR and AFM experiments confirmed the interaction between the receptor and targeting molecules. The results of this study might aid the screening of ligands for receptor targeting and drug delivery.

Fabrication of uniform 4H-SiC mesopores by pulsed electrochemical etching.

In this letter, the uniform 4H silicon carbide (SiC) mesopores was fabricated by pulsed electrochemical etching method. The length of the mesopores is about 19 µm with a diameter of about 19 nm. The introduction of pause time (T off) is crucial to form the uniform 4H-SiC mesopores. The pore diameter will not change if etching goes with T off. The hole concentration decreasing at the pore tips during the T off is the main reason for uniformity.

[Simulation of above ground biomass in Larix olgensis plantation].

By the method of harvesting sampling trees, the information of aboveground biomass in 34 plots of a Larix olgensis plantation were collected, of which, the information from 29 plots was selected and fitted with stand factors and TM image RS factors, respectively to establish biomass models, and the information from the rest 5 plots was used to verify the models accuracy. The aboveground biomass in the Larix olgensis plantation could be linearly fitted with either stand factors or RS factors. For the young-middle aged trees, the estimation accuracy of stand factors model was higher (P(stand) = 94.33%), and the test error was smaller (MRE(stand) = 6%), compared with RS factors model (P(RS) = 92.32% , MRE(RS) = 31%). If only the middle-aged trees were taken into account, the estimation effect of the two models had no significant different (error sum E(stand) = 329.9 t, E(RS) = 313.6 t). Overall, the stand factors model was better for the estimation of Larix olgensis cortex, wood, and stumpage biomass, while the RS factors model was better for the estimation of middle-aged trees leaf, flower, fruit, branch, and crown biomass.