Improved camptothecin encapsulation and efficacy by environmentally sensitive block copolymer/chitosan/fucoidan nanoparticles for targeting lung cancer cells.

In this study, thermo-sensitive poly(N-isopropyl acrylamide) (PNP) was polymerized with pH-sensitive poly(acrylic acid) (PAA) to prepare a PAA-b-PNP block copolymer. Above its cloud point, the block copolymer self-assembled into nanoparticles (NPs), encapsulating the anticancer drug camptothecin (CPT) in situ. Chitosan (CS) and fucoidan (Fu) further modified these NPs, forming Fu-CPT-NPs to enhance biocompatibility, drug encapsulation efficiency (EE), and loading content (LC), crucially facilitating P-selectin targeting of lung cancer cells through a drug delivery system. The EE and LC reached 82 % and 3.5 %, respectively. According to transmission electron microscope observation, these Fu-CPT-NPs had uniform spherical shapes with an average diameter of ca. 250 nm. They could maintain their stability in a pH range of 5.0-6.8. In vitro experimental results revealed that the Fu-CPT-NPs exhibited good biocompatibility and had anticancer activity after encapsulating CPT. It could deliver CPT to cancer cells by targeting P-selectin, effectively increasing cell uptake and inducing cell apoptosis. Animal study results showed that the Fu-CPT-NPs inhibited lung tumor growth by increasing tumor cell apoptosis without causing significant tissue damage related to generating reactive oxygen species in lung cancer cells. This system can effectively improve drug-delivery efficiency and treatment effects and has great potential for treating lung cancer.

Failure Diagnosis for Dental Air Turbine Handpiece with Payload Using Feature Engineering and Temporal Convolution Network.

The internal mechanisms of dental air turbine handpieces (DATHs) have become increasingly intricate over time. To enhance the operational reliability of dental procedures and guarantee patient safety, this study formulated temporal convolution network (TCN) prediction models with the functions of causality in time sequence, transmitting memory, learning, storing, and fast convergence for monitoring the health and diagnosing the rotor and collet failure of DATHs. A handpiece mimicking a dentist's hand load of 100 g was employed to repeatedly mill a glass porcelain block back and forth for cutting. An accelerometer was employed to capture vibration signals during free-running of unrestrained operation of the handpiece, aiming to discern the characteristic features of these vibrations. These data were then utilized to create a diagnostic health classification (DHC) for further developing a TCN, a 1D convolutional neural network (CNN), and long short-term memory (LSTM) prediction models. The three frameworks were used and compared for machine learning to establish DHC prediction models for the DATH. The experimental results indicate that, in terms of DHC predicted for the experimental dataset, the square categorical cross-entropy loss function error of the TCN framework was generally lower than that of the 1D CNN, which did not have a memory framework or the drawback of the vanishing gradient problem. In addition, the TCN framework outperformed the LSTM model, which required a longer history to provide sufficient diagnostic ability. Still, high accuracies were achieved both in the direction of feed-drive milling and in the gravity of the handpiece through vibration signals. In general, the failure classification prediction model could accurately predict the health and failure mode of the dental handpiece before the use of the DATH when an embedded sensor was available. Therefore, this model could prove to be a beneficial tool for predicting the deterioration patterns of real dental handpieces in their remaining useful life.

DEGAP: Dynamic elongation of a genome assembly path.

Genome assembly remains to be a major task in genomic research. Despite the development over the past decades of different assembly software programs and algorithms, it is still a great challenge to assemble a complete genome without any gaps. With the latest DNA circular consensus sequencing (CCS) technology, several assembly programs can now build a genome from raw sequencing data to contigs; however, some complex sequence regions remain as unresolved gaps. Here, we present a novel gap-filling software, DEGAP (Dynamic Elongation of a Genome Assembly Path), that resolves gap regions by utilizing the dual advantages of accuracy and length of high-fidelity (HiFi) reads. DEGAP identifies differences between reads and provides 'GapFiller' or 'CtgLinker' modes to eliminate or shorten gaps in genomes. DEGAP adopts an iterative elongation strategy that automatically and dynamically adjusts parameters according to three complexity factors affecting the genome to determine the optimal extension path. DEGAP has already been successfully applied to decipher complex genomic regions in several projects and may be widely employed to generate more gap-free genomes.

Evaluation of the prognostic performance of different cutoff values of lymph node ratio staging system for stage III colorectal cancer.

This study attempted to compare the prognostic performance of lymph node ratio (LNR) staging system with different cutoff values relative to American Joint Committee on Cancer (AJCC) pN staging system in stage III colorectal cancer (CRC). Overall, 45,069 patients from the SEER dataset and 69 patients from the Second Affiliated Hospital of Nanjing Medical University (the External set) who underwent surgical resection of the primary tumor and were diagnosed with stage III CRC by postoperative pathology were included. Patients were divided into three subgroups based on the LNR cutoff used in previous studies, Kaplan-Meier curves were plotted, and log-rank test was used to compare the differences among groups in terms of cancer-specific survival (CSS). Cox regression model was applied for survival analysis. To evaluate the discriminatory power of different lymph node staging systems, Harrell's C statistic(C-index) and Akaike's Information Criterion (AIC) were applied. A set of optimal cutoff values (0.11; 0.36; 0.66) of LNR staging system with the most considerable discriminatory power to the prognosis in patients with stage III CRC (SEER set: C-index = 0.714; AIC = 58,942.46, External set: C-index = 0.809; AIC = 164.36) were obtained, and both were superior to the AJCC pN staging system (SEER set: C-index = 0.708; AIC = 59,071.20, External set: C-index = 0.788; AIC = 167.06). For evaluating the prognostic efficacy of patients with stage III colorectal cancer, the cutoff value (0.11; 0.36; 0.66) of LNR staging system had the best discrimination and prognostic ability, which was superior to LNR staging system under other cutoff values and AJCC pN staging system.

Whole-genome sequencing of allotetraploid bermudagrass reveals the origin of Cynodon and candidate genes for salt tolerance.

Bermudagrass (Cynodon dactylon) is a globally distributed, extensively used warm-season turf and forage grass with high tolerance to salinity and drought stress in alkaline environments. However, the origin of the species and genetic mechanisms for salinity tolerance in the species are basically unknown. Accordingly, we set out to study evolution divergence events in the Cynodon genome and to identify genes for salinity tolerance. We developed a 604.0 Mb chromosome-level polyploid genome sequence for bermudagrass 'A12359' (n = 18). The C. dactylon genome comprises 2 complete sets of homoeologous chromosomes, each with approximately 30 000 genes, and most genes are conserved as syntenic pairs. Phylogenetic study showed that the initial Cynodon species diverged from Oropetium thomaeum approximately 19.7-25.4 million years ago (Mya), the A and B subgenomes of C. dactylon diverged approximately 6.3-9.1 Mya, and the bermudagrass polyploidization event occurred 1.5 Mya on the African continent. Moreover, we identified 82 candidate genes associated with seven agronomic traits using a genome-wide association study, and three single-nucleotide polymorphisms were strongly associated with three salt resistance genes: RAP2-2, CNG channels, and F14D7.1. These genes may be associated with enhanced bermudagrass salt tolerance. These bermudagrass genomic resources, when integrated, may provide fundamental insights into evolution of diploid and tetraploid genomes and enhance the efficacy of comparative genomics in studying salt tolerance in Cynodon.

π-π Interaction-Induced Organic Long-wavelength Room-Temperature Phosphorescence for In Vivo Atherosclerotic Plaque Imaging.

Room-temperature phosphorescent (RTP) materials have great potential for in vivo imaging because they can circumvent the autofluorescence of biological tissues. In this study, a class of organic-doped long-wavelength (≈600 nm) RTP materials with benzo[c][1,2,5] thiadiazole as a guest was constructed. Both host and guest molecules have simple structures and can be directly purchased commercially at a low cost. Owing to the long phosphorescence wavelength of the doping system, it exhibited good tissue penetration (10 mm). Notably, these RTP nanoparticles were successfully used to image atherosclerotic plaques, with a signal-to-background ratio (SBR) of 44.52. This study provides a new approach for constructing inexpensive red organic phosphorescent materials and a new method for imaging cardiovascular diseases using these materials.

Production of bacterial cellulose (BC)/nisin composite with enhanced antibacterial and mechanical properties through co-cultivation of Komagataeibacter xylinum and Lactococcus lactis subsp. lactis.

By employing co-cultivation technique on Komagataeibacter xylinum and Lactococcus lactis subsp. lactis, bacterial cellulose (BC)/nisin films with improved antibacterial activity and mechanical properties were successfully produced. The findings demonstrated that increased nisin production is associated with an upregulation of gene expression. Furthermore, results from Scanning electronic microscopy (SEM), Fourier transform infrared (FTIR), X-ray diffraction (XRD), and Thermogravimetric analysis (TG) confirmed the integration of nisin within BC. While being biocompatible with human cells, the BC/nisin composites exhibited antimicrobial activity. Moreover, mechanical property analyses showed a noticeable improvement in Young's modulus, tensile strength, and elongation at break by 161, 271, and 195 %, respectively. Additionally, the nisin content in fermentation broth was improved by 170 % after co-culture, accompanied by an 8 % increase in pH as well as 10 % decrease in lactate concentration. Real-time reverse transcription PCR analysis revealed an upregulation of 11 nisin-related genes after co-cultivation, with the highest increase in nisA (5.76-fold). To our knowledge, this is the first study which demonstrates that an increase in secondary metabolites after co-culturing is modulated by gene expression. This research offers a cost-effective approach for BC composite production and presents a technique to enhance metabolite concentration through the regulation of relevant genes.

Enhancing UAV Visual Landing Recognition with YOLO's Object Detection by Onboard Edge Computing.

A visual camera system combined with the unmanned aerial vehicle (UAV) onboard edge computer should deploy an efficient object detection ability, increase the frame per second rate of the object of interest, and the wide searching ability of the gimbal camera for finding the emergent landing platform and for future reconnaissance area missions. This paper proposes an approach to enhance the visual capabilities of this system by using the You Only Look Once (YOLO)-based object detection (OD) with Tensor RTTM acceleration technique, an automated visual tracking gimbal camera control system, and multithread programing for image transmission to the ground station. With lightweight edge computing (EC), the mean average precision (mAP) was satisfied and we achieved a higher frame per second (FPS) rate via YOLO accelerated with TensorRT for an onboard UAV. The OD compares four YOLO models to recognize objects of interest for landing spots at the home university first. Then, the trained dataset with YOLOv4-tiny was successfully applied to another field with a distance of more than 100 km. The system's capability to accurately recognize a different landing point in new and unknown environments is demonstrated successfully. The proposed approach substantially reduces the data transmission and processing time to ground stations with automated visual tracking gimbal control, and results in rapid OD and the feasibility of using NVIDIA JetsonTM Xavier NX by deploying YOLOs with more than 35 FPS for the UAV. The enhanced visual landing and future reconnaissance mission capabilities of real-time UAVs were demonstrated.

Prediction of liver and lung metastases in patients with early-onset colorectal cancer by nomograms based on heterogeneous and homogenous risk factors.

BACKGROUND: Identifying the risk factors for distant metastasis in early-onset colorectal cancer (EOCRC) is crucial for elucidating its etiology and facilitating preventive treatment. This study aims to characterize the variability in EOCRC incidence and discern both heterogeneous and homogeneous risk factors associated with synchronous liver, lung, and hepato-lung metastases. METHODS: This study included patients with EOCRC enrolled in the SEER database between 2010 and 2015 and divided patients into three groups by synchronous liver, lung, and hepato-lung metastases. Each group of patients with different metastasis types was randomly assigned to the development and validation cohort in a ratio of 7:3. Logistic regression was used to analyze the heterogeneous and homogenous risk factors for synchronous liver, lung, and hepato-lung metastases in the development cohort of patients. Nomograms were built to calculate the risk of metastasis, and the receiver operating characteristic (ROC) curve and calibration curve were used to quantitatively evaluate their performance. RESULTS: A total of 16,336 eligible patients with EOCRC were included in this study, of which 17.90% (2924/16,336) had distant metastases. The overall incidences of synchronous liver, lung, and hepato-lung metastases were 11.90% (1921/16,146), 2.42% (390/16,126), and 1.50% (241/16,108), respectively. Positive CEA values before treatment, increased lymphatic metastases, and deeper invasion of intestinal wall were positively correlated with three distant types of metastases. On the contrary, the correlation of age, ethnicity, location of primary tumor, and histologic grade among the three types was inconsistent. The ROC curve and calibration curve proved to have fine performance in predicting distant metastases of EOCRC. CONCLUSIONS: There are significant differences in the incidence of distant metastases in EOCRC, and related risk factors are heterogeneous and homogenous. Although limited risk factors were incorporated in this study, the established nomograms indicated good predictive performance.

Dopamine-dependent functions of hyaluronic acid/dopamine/silk fibroin hydrogels that highly enhance N-acetyl-L-cysteine (NAC) delivered from nasal cavity to brain tissue through a near-infrared photothermal effect on the NAC-loaded hydrogels.

Hyaluronic acid/silk fibroin (HA/SF or HS) hydrogels with remarkable mechanical characteristics have been reported as tissue engineering biomaterials. Herein, the addition of dopamine/polydopamine (DA/PDA) to HS hydrogels to develop multifunctional HA/PDA/SF (or HDS) hydrogels for the delivery of drugs such as N-acetyl-L-cysteine (NAC) from nasal to brain tissue is examined. Herein, DA-dependent functions of HDS hydrogels with highly adhesive forces, photothermal response (PTR) effects generated by near infrared (NIR) irradiation, and anti-oxidative effects were demonstrated. An in-vitro study shows that the HDS/NAC hydrogels could open tight junctions in the RPMI 2650 cell line, a model cell of the nasal mucosa, as demonstrated by the decreased values of transepithelial electrical resistance (TEER) and more discrete ZO-1 staining than those for the control group. This effect was markedly enhanced by NIR irradiation of the HDS/NAC-NIR hydrogels. Compared to the results obtained using NAC solution, an in-vivo imaging study (IVIS) in rats showed an approximately nine-fold increase in the quantity of NAC delivered from the nasal cavity to the brain tissue in the span of 2 h through the PTR effect generated by the NIR irradiation of the nasal tissue and administration of the HDS/NAC hydrogels. Herein, dopamine-dependent multifunctional HDS hydrogels were studied, and the nasal administration of HDS/NAC-NIR hydrogels with PTR effects generated by NIR irradiation was found to have significantly enhanced NAC delivery to brain tissues.

Identification of tumor immunophenotypes associated with immunotherapy response in bladder cancer.

OBJECTIVES: This study aims to reveal immunophenotypes associated with immunotherapy response in bladder cancer, identify the signature genes of immune subtypes, and provide new molecular targets for improving immunotherapy response. METHODS: Bladder cancer immunophenotypes were characterized in the bulk RNA sequencing dataset GSE32894 and Imvigor210, and gene expression signatures were established to identify the immunophenotypes. Expression of gene signatures were validated in single-cell RNA sequencing dataset GSE145140 and human proteins expression data source. Investigation of Immunotherapy Response was performed in IMvigor210 dataset. Prognosis of tumor immunophenotypes was further analyzed. RESULTS: Inflamed and immune-excluded immunophenotypes were characterized based on the tumor immune cell scores. Risk score models that were established rely on RNA sequencing profiles and overall survival of bladder cancer cohorts. The inflamed tumors had lower risk scores, and the low-risk tumors were more likely to respond to atezolizumab, receiving complete response/partial response (CR/PR). Patients who responded to atezolizumab had higher SRRM4 and lower NPHS1 and TMEM72 expression than the non-responders. SRRM4 expression was a protective factor for bladder cancer prognosis, while the NPHS1 and TMEM72 showed the opposite pattern. CONCLUSION: This study provided a novel classification method for tumor immunophenotypes. Bladder cancer immunophenotypes can predict the response to immune checkpoint blockade. The immunophenotypes can be identified by the expression of signature genes.

Using Feature Engineering and Principal Component Analysis for Monitoring Spindle Speed Change Based on Kullback-Leibler Divergence with a Gaussian Mixture Model.

Machining is a crucial constituent of the manufacturing industry, which has begun to transition from precision machinery to smart machinery. Particularly, the introduction of artificial intelligence into computer numerically controlled (CNC) machine tools will enable machine tools to self-diagnose during operation, improving the quality of finished products. In this study, feature engineering and principal component analysis were combined with the online and real-time Gaussian mixture model (GMM) based on the Kullback-Leibler divergence's measure to achieve the real-time monitoring of changes in manufacturing parameters. Based on the attached accelerometer device's vibration signals and current sensing of the spindle, the developed GMM unsupervised learning was successfully used to diagnose the spindle speed changes of a CNC machine tool during milling. The F1-scores with improved experimental results for X, Y, and Z axes were 0.95, 0.88, and 0.93, respectively. The established FE-PCA-GMM/KLD method can be applied to issue warnings when it predicts a change in the manufacturing process parameter. A smart sensing device for diagnosing the machining status can be fabricated for implementation. The effectiveness of the developed method for determining the manufacturing parameter changes was successfully verified by experiments.

In Situ Encapsulation of Camptothecin by Self-Assembly of Poly(acrylic acid)-b-Poly(N-Isopropylacrylamide) and Chitosan for Controlled Drug Delivery.

Camptothecin (CPT) has been shown to exhibit anticancer activity against several cancers. Nevertheless, CPT is very hydrophobic with poor stability, and thus its medical application is limited. Therefore, various drug carriers have been exploited for effectively delivering CPT to the targeted cancer site. In this study, a dual pH/thermo-responsive block copolymer of poly(acrylic acid-b-N-isopropylacrylamide) (PAA-b-PNP) was synthesized and applied to encapsulate CPT. At temperatures above its cloud point, the block copolymer self-assembled to form nanoparticles (NPs) and in situ encapsulate CPT, owing to their hydrophobic interaction as evidenced by fluorescence spectrometry. Chitosan (CS) was further applied on the surface through the formation of a polyelectrolyte complex with PAA for improving biocompatibility. The average particle size and zeta potential of the developed PAA-b-PNP/CPT/CS NPs in a buffer solution were 168 nm and -30.6 mV, respectively. These NPs were still stable at least for 1 month. The PAA-b-PNP/CS NPs exhibited good biocompatibility toward NIH 3T3 cells. Moreover, they could protect the CPT at pH 2.0 with a very slow-release rate. At pH 6.0, these NPs could be internalized by Caco-2 cells, followed by intracellular release of the CPT. They became highly swollen at pH 7.4, and the released CPT was able to diffuse into the cells at higher intensity. Among several cancer cell lines, the highest cytotoxicity was observed for H460 cells. As a result, these environmentally-responsive NPs have the potential to be applied in oral administration.

Manipulating XXY Planar Platform Positioning Accuracy by Computer Vision Based on Reinforcement Learning.

With the rise of Industry 4.0 and artificial intelligence, the demand for industrial automation and precise control has increased. Machine learning can reduce the cost of machine parameter tuning and improve high-precision positioning motion. In this study, a visual image recognition system was used to observe the displacement of an XXY planar platform. Ball-screw clearance, backlash, nonlinear frictional force, and other factors affect the accuracy and reproducibility of positioning. Therefore, the actual positioning error was determined by inputting images captured by a charge-coupled device camera into a reinforcement Q-learning algorithm. Time-differential learning and accumulated rewards were used to perform Q-value iteration to enable optimal platform positioning. A deep Q-network model was constructed and trained through reinforcement learning for effectively estimating the XXY platform's positioning error and predicting the command compensation according to the error history. The constructed model was validated through simulations. The adopted methodology can be extended to other control applications based on the interaction between feedback measurement and artificial intelligence.

A Morphing Point-to-Point Displacement Control Based on Long Short-Term Memory for a Coplanar XXY Stage.

In this study, visual recognition with a charge-coupled device (CCD) image feedback control system was used to record the movement of a coplanar XXY stage. The position of the stage is fedback through the image positioning method, and the positioning compensation of the stage is performed by the image compensation control parameter. The image resolution was constrained and resulted in an average positioning error of the optimized control parameter of 6.712 µm, with the root mean square error being 2.802 µm, and the settling time being approximately 7 s. The merit of a long short-term memory (LSTM) deep learning model is that it can identify long-term dependencies and sequential state data to determine the next control signal. As for improving the positioning performance, LSTM was used to develop a training model for stage motion with an additional dial indicator with an accuracy of 1 µm being used to record the XXY position information. After removing the assisting dial indicator, a new LSTM-based XXY feedback control system was subsequently constructed to reduce the positioning error. In other words, the morphing control signals are dependent not only on time, but also on the iterations of the LSTM learning process. Point-to-point commanded forward, backward and repeated back-and-forth repetitive motions were conducted. Experimental results revealed that the average positioning error achieved after using the LSTM model was 2.085 µm, with the root mean square error being 2.681 µm, and a settling time of 2.02 s. With the assistance of LSTM, the stage exhibited a higher control accuracy and less settling time than did the CCD imaging system according to three positioning indices.

Soil Erosion Characteristics and Scenario Analysis in the Yellow River Basin Based on PLUS and RUSLE Models.

Soil erosion is an important global environmental issue that severely affects regional ecological environment and socio-economic development. The Yellow River (YR) is China's second largest river and the fifth largest one worldwide. Its watershed is key to China's economic growth and environmental security. In this study, six impact factors, including rainfall erosivity (R), soil erosivity (K), slope length (L), slope steepness (S), cover management (C), and protective measures (P), were used. Based on the revised universal soil loss equation (RUSLE) model, and combined with a geographic information system (GIS), the temporal and spatial distribution of soil erosion (SE) in the YR from 2000 to 2020 was estimated. The patch-generating land use simulation (PLUS) model was used to simulate the land-use and land-cover change (LUCC) under two scenarios (natural development and ecological protection) in 2040; the RUSLE factor P was found to be associated with LUCC in 2040, and soil erosion in the Yellow River Basin (YRB) in 2040 under the two scenarios were predicted and evaluated. This method has great advantages in land-use simulation, but soil erosion is greatly affected by rainfall and slope, and it only focuses on the link between land-usage alteration and SE. Therefore, this method has certain limitations in assessing soil erosion by simulating and predicting land-use change. We found that there is generally slight soil erosivity in the YRB, with the most serious soil erosion occurring in 2000. Areas with serious SE are predominantly situated in the upper reaches (URs), followed by the middle reaches (MRs), and soil erosion is less severe in the lower reaches. Soil erosion in the YRB decreased 11.92% from 2000 to 2020; thus, soil erosion has gradually reduced in this area over time. Based on the GIS statistics, land-use change strongly influences SE, while an increase in woodland area has an important positive effect in reducing soil erosion. By predicting land-use changes in 2040, compared to the natural development scenario, woodland and grassland under the ecological protection scenario can be increased by 1978 km2 and 2407 km2, respectively. Soil erosion can be decreased by 6.24%, indicating the implementation of woodland and grassland protection will help reduce soil erosion. Policies such as forest protection and grassland restoration should be further developed and implemented on the MRs and URs of the YR. Our research results possess important trend-setting significance for soil erosion control protocols and ecological environmental protection in other large river basins worldwide.

A compensation mechanism for air pollutants generated by tourism-related land-based transportation: An exergy-based case study from Macao.

This paper discusses the compensation standard for exhaust pollution and devises a compensation mechanism for Macao's tourism-related transport sector based on an integration of chemical exergy and universal exergy, using data on gasoline consumption by automobile sector retrieved from the transportation industry. The results reveal that: (1) the exergy values of air pollutant emissions increased from 1.53 × 1012 kJ in 2010 to 2.03 × 1012 kJ in 2019 (an increase of 1.33 times), and the exergy of CO, NOx, and SO2 emissions accounted for 77.5%, 20.4% and 2.1% of total exhaust emissions in Macao respectively. (2) In 2019, the monetary value of emission exergy, and the environmental costs of air pollution, were 1.7 times greater than in 2010. (3) If Light Rail Transit is compensated for, then the mean interval's values of the upper and lower limits of the compensation standard are 0.55 USD and 0.05 USD, respectively. When gasoline tax is used as a means of compensation it is necessary to raise its rate by about 8% based on the tax rate. A three-stage bargaining game model is used to provide evidence that this compensation standard is practical and acceptable.

Specific and efficient hydrolysis of all outer glucosyls in protopanaxadiol type and protopanaxatriol type ginsenosides by a ß-glucosidase from Thermoclostridium stercorarium.

To develop a new method for enzymatic preparation of minor ginsenosides, T. stercorarium ß-glucosidase (Tsbgl) was characterized and its activities of deglycosylation towards natural ginsenosides were examined. The substrates of 1 mmol l-1 were incubated with the enzyme of 38.3 U ml-1 at 65 â„ƒ and pH 5.0. The Km values of Tsbgl for ginsenosides Rb1, Rg1 and pNPG were 0.37 ± 0.03, 3.26 ± 0.19, and 1.24 ± 0.03 mmol l-1, and the Vmax values were 183.63 ± 7.15, 85.03 ± 4.90, and 117.66 ± 1.96 µmol mg-1 min-1, respectively. The molar conversion of ginsenosides Rb1, Rb2, Rb3, Rc, Re, Rg1, and Rf by Tsbgl within 6 h was 100%, 50.1%, 42.7%, 92.0%, 57.3%, 67.9%, and 76.8%, respectively. The yield of aglycone protopanaxadiol was 35.5 µmol l-1 h-1 for Rb1, while the yields of aglycone protopanaxatriol were 64.2 and 70.4 µmol l-1 h-1 for Rg1 and Rf. Tsbgl with good organic solvent tolerance, mild reaction conditions and broad substrate specificity, could completely remove all outer glucosyls at the C-3 and C-20 hydroxyls of protopanaxadiol-type ginsenosides, and the C-6 and C-20 hydroxyls of protopanaxatriol-type ginsenosides through various pathways, providing a specific and efficient way to produce minor ginsenosides.

Testing the stakeholders' partnership in a tourism waste management network: an ERGM approach.

The exponential random graph model (ERGM) is an effective approach for testing the dynamic and local processes of a network. This paper explores the structure of stakeholders' partnerships in a tourism waste management network using high-order dependency ERGMs based on relational data obtained from a field survey in Motuo County, China. The results reveal that (1) the network has many edges, indicating a tight network; (2) the geometrically weighted edge distribution shows a high transitive effect of the network; (3) the structural effect is more significant than the attribute effect; (4) there is a good agreement between the simulation results and observations, suggesting a tourism waste network with close connections and collaborative division of labor. These findings indicate that different groups of stakeholders have been extensively involved in tourism waste management in Motuo County. The edgewise shared partners formed by stakeholders of different groups increase the information transmission efficiency of the network. The results have implications for tourism waste management, specifically for promoting sustainability transitions via network governance.