Impact of Using Pre- and Post-Bronchodilator Spirometry Reference Values in a Chinese Population.

RATIONALE: Spirometry reference equations that are derived from a large, nationally representative, general population are warranted in China and the impact of using pre- and post-BD spirometry reference values has yet to be assessed in Chinese populations. OBJECTIVES: To present both the pre-BD and post-BD spirometry reference values for Chinese adults using the China Pulmonary Health (CPH) study. METHODS: A reference population of 17969 healthy, non-smoking participants in the CPH study was used to calculate the pre- and post-BD reference values for the forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC. Both pre- and post-BD reference values were applied to the entire CPH population (50991 individuals) to illustrate the divergence between the use of references in determining the disease prevalence and severity grading. MEASUREMENTS AND MAIN RESULTS: The prevalence of airflow limitation was 5.36% using pre-BD reference and 8.02% using the post-BD reference. Individuals who had post-BD FEV1/FVC below post-BD but higher than pre-BD reference values were found to have significantly higher rates of self-reported respiratory symptoms, and significantly lower values in spirometry indicators than those above post-BD reference values. An additional 3.51% of participants were identified as grade II-IV COPD using the post-BD FEV1 predicted values. CONCLUSION: This study generated and applied pre- and post-bronchodilator spirometry reference values in a nationally representative Chinese adult population. Post-BD reference values may serve as an additional criterion in identifying individuals at risk for obstructive pulmonary diseases, its diagnostic and prognostic values should be further investigated.

Targeting MMP9 in CTNNB1 mutant hepatocellular carcinoma restores CD8+ T cell-mediated antitumour immunity and improves anti-PD-1 efficacy.

OBJECTIVE: The gain of function (GOF) CTNNB1 mutations (CTNNB1 GOF ) in hepatocellular carcinoma (HCC) cause significant immune escape and resistance to anti-PD-1. Here, we aimed to investigate the mechanism of CTNNB1 GOF HCC-mediated immune escape and raise a new therapeutic strategy to enhance anti-PD-1 efficacy in HCC. DESIGN: RNA sequencing was performed to identify the key downstream genes of CTNNB1 GOF associated with immune escape. An in vitro coculture system, murine subcutaneous or orthotopic models, spontaneously tumourigenic models in conditional gene-knock-out mice and flow cytometry were used to explore the biological function of matrix metallopeptidase 9 (MMP9) in tumour progression and immune escape. Single-cell RNA sequencing and proteomics were used to gain insight into the underlying mechanisms of MMP9. RESULTS: MMP9 was significantly upregulated in CTNNB1 GOF HCC. MMP9 suppressed infiltration and cytotoxicity of CD8+ T cells, which was critical for CTNNB1 GOF to drive the suppressive tumour immune microenvironment (TIME) and anti-PD-1 resistance. Mechanistically, CTNNB1 GOF downregulated sirtuin 2 (SIRT2), resulting in promotion of ß-catenin/lysine demethylase 4D (KDM4D) complex formation that fostered the transcriptional activation of MMP9. The secretion of MMP9 from HCC mediated slingshot protein phosphatase 1 (SSH1) shedding from CD8+ T cells, leading to the inhibition of C-X-C motif chemokine receptor 3 (CXCR3)-mediated intracellular of G protein-coupled receptors signalling. Additionally, MMP9 blockade remodelled the TIME and potentiated the sensitivity of anti-PD-1 therapy in HCC. CONCLUSIONS: CTNNB1 GOF induces a suppressive TIME by activating secretion of MMP9. Targeting MMP9 reshapes TIME and potentiates anti-PD-1 efficacy in CTNNB1 GOF HCC.

Defining Global Benchmarks for Laparoscopic Right Posterior Sectionectomy/H67: An International Multicenter Study.

OBJECTIVE: We aimed to establish global benchmark outcomes indicators for L-RPS/H67. BACKGROUND: Minimally invasive liver resections has seen an increase in uptake in recent years. Over time, challenging procedures as laparoscopic right posterior sectionectomies (L-RPS)/H67 are also increasingly adopted. METHODS: This is a post hoc analysis of a multicenter database of 854 patients undergoing minimally invasive RPS (MI-RPS) in 57 international centers in 4 continents between 2015 and 2021. There were 651 pure L-RPS and 160 robotic RPS (R-RPS). Sixteen outcome indicators of low-risk L-RPS cases were selected to establish benchmark cutoffs. The 75th percentile of individual center medians for a given outcome indicator was set as the benchmark cutoff. RESULTS: There were 573 L-RPS/H67 performed in 43 expert centers, of which 254 L-RPS/H67 (44.3%) cases qualified as low risk benchmark cases. The benchmark outcomes established for operation time, open conversion rate, blood loss ≥500 mL, blood transfusion rate, postoperative morbidity, major morbidity, 90-day mortality and textbook outcome after L-RPS were 350.8 minutes, 12.5%, 53.8%, 22.9%, 23.8%, 2.8%, 0% and 4% respectively. CONCLUSIONS: The present study established the first global benchmark values for L-RPS/H6/7. The benchmark provided an up-to-date reference of best achievable outcomes for surgical auditing and benchmarking.

Assessment of Global and Regional Lung Compliance in Pulmonary Fibrosis With Hyperpolarized Gas MRI.

BACKGROUND: Lung compliance, a biomarker of pulmonary fibrosis, is generally measured globally. Hyperpolarized 129Xe gas MRI offers the potential to evaluate lung compliance regionally, allowing for visualization of changes in lung compliance associated with fibrosis. PURPOSE: To assess global and regional lung compliance in a rat model of pulmonary fibrosis using hyperpolarized 129Xe gas MRI. STUDY TYPE: Prospective. ANIMAL MODEL: Twenty Sprague-Dawley male rats with bleomycin-induced fibrosis model (N = 10) and saline-treated controls (N = 10). FIELD STRENGTH/SEQUENCE: 7-T, fast low-angle shot (FLASH) sequence. ASSESSMENT: Lung compliance was determined by fitting lung volumes derived from segmented 129Xe MRI with an iterative selection method, to corresponding airway pressures. Similarly, lung compliance was obtained with computed tomography for cross-validation. Direction-dependencies of lung compliance were characterized by regional lung compliance ratios (R) in different directions. Pulmonary function tests (PFTs) and histological analysis were used to validate the pulmonary fibrosis model and assess its correlation with 129Xe lung compliance. STATISTICAL TESTS: Shapiro-Wilk tests, unpaired and paired t-tests, Mann-Whitney U and Wilcoxon signed-rank tests, and Pearson correlation coefficients. P < 0.05 was considered statistically significant. RESULTS: For the entire lung, the global and regional lung compliance measured with 129Xe gas MRI showed significant differences between the groups, and correlated with the global lung compliance measured using PFTs (global: r = 0.891; regional: r = 0.873). Additionally, for the control group, significant difference was found in mean regional compliance between areas, eg, 0.37 (0.32, 0.39) × 10-4 mL/cm H2O and 0.47 (0.41, 0.56) × 10-4 mL/cm H2O for apical and basal lung, respectively. The apical-basal direction R was 1.12 ± 0.09 and 1.35 ± 0.13 for fibrosis and control groups, respectively, indicating a significant difference. DATA CONCLUSION: Our findings demonstrate the feasibility of using hyperpolarized gas MRI to assess regional lung compliance. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Microgel Encapsulated Nanoparticles for Intra-articular Disulfiram Delivery to Treat Osteoarthritis.

Osteoarthritis (OA) affects numerous patients worldwide, and there are no approved disease-modifying drugs. Repurposing FDA-approved small molecular drugs could be a promising alternative strategy to treat OA. Disulfiram (DSF), a clinically approved drug for treatment of alcoholism, inhibits inflammasome activation and exhibits a protective role in interleukin-1ß-induced cardiac injury. However, its efficacy in treating OA remains to be explored due to its poor water solubility and stability, which limit its use in OA treatment. Here, the anti-inflammatory effect of DSF is evaluated in vitro, and a double-layer encapsulation approach is developed for intra-articular delivery of DSF for OA treatment in vivo. DSF is loaded into poly(lactic-co-glycolic acid)-based nanoparticles and encapsulated in gelatin methacrylate microgels through a microfluidic device. Results show that DSF effectively inhibits the expression of key inflammatory cytokines in OA chondrocytes, and the double-layer encapsulation approach reduces the burst release of DSF and prolongs its retention time in the in vitro study. Sustained release of DSF from microgels mitigates cartilage inflammation and subchondral bone erosion in a monoiodoacetate-induced rat OA model. This work demonstrates the potential of repurposing FDA-approved drugs for OA treatment and provides a promising platform for intra-articular delivery of small molecules for superior therapeutic effect.

Porous Mg-Zn-Ca scaffolds for bone repair: a study on microstructure, mechanical properties and in vitro degradation behavior.

Biodegradable porous Mg scaffolds are a promising approach to bone repair. In this work, 3D-spherical porous Mg-1.5Zn-0.2Ca (wt.%) scaffolds were prepared by vacuum infiltration casting technology, and MgF2 and fluorapatite coatings were designed to control the degradation behavior of Mg-based scaffolds. The results showed that the pores in Mg-based scaffolds were composed of the main spherical pores (450-600 µm) and interconnected pores (150-200 µm), and the porosity was up to 74.97%. Mg-based porous scaffolds exhibited sufficient mechanical properties with a compressive yield strength of about 4.04 MPa and elastic modulus of appropriately 0.23 GPa. Besides, both MgF2 coating and fluorapatite coating could effectively improve the corrosion resistance of porous Mg-based scaffolds. In conclusion, this research would provide data support and theoretical guidance for the application of biodegradable porous Mg-based scaffolds in bone tissue engineering.

Multi-model assessment of potential natural vegetation to support ecological restoration.

Ecological restoration is imperative for controlling desertification. Potential natural vegetation (PNV), the theoretical vegetation succession state, can guides near-natural restoration. Although a rising transition from traditional statistical methods to advanced machine learning and deep learning is observed in PNV simulation, a comprehensive comparison of their performance is still unexplored. Therefore, we overview the performance of PNV mapping in terms of 12 commonly used methods with varying spatial scales and sample sizes. Our findings indicate that the methodology should be carefully selected due to the variation in performance of different model types, with Area Under the Curve (AUC) values ranging from 0.65 to 0.95 for models with sample sizes up to 80% of the total sample size. Specifically, semi-supervised learning performs best with small sample sizes (i.e., 10 to 200), while Random Forest, XGBoost, and artificial neural networks perform better with large sample sizes (i.e., over 500). Further, the performance of all models tends to improve significantly as the sample size increases and the grain size of the crystals becomes smaller. Take the downstream Tarim River Basin, a hyper-arid region undergoing ecological restoration, as a case study. We showed that its potential restored areas were overestimated by 2-3 fold as the spatial scale became coarser, revealing the caution needed while planning restoration projects at coarse resolution. These findings enhance the application of PNV in the design of restoration programs to prevent desertification.

Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network.

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide.

Fracture Performance Study of Carbon-Fiber-Reinforced Resin Matrix Composite Winding Layers under UV Aging Effect.

There is limited research on the fracture toughness of carbon-fiber-reinforced polymer (CFRP) materials under accelerated UV aging conditions. In this study, the primary focus was on investigating the influence of varying durations of ultraviolet (UV) irradiation at different temperatures on the Mode I, Mode II, and mixed-mode fracture toughness of CFRP laminates. The results indicate that with increasing UV aging duration, the material's Mode I fracture toughness increases, while Mode II fracture toughness significantly decreases. The mixed-mode fracture toughness exhibits an initial increase followed by a subsequent decrease. Furthermore, as the aging temperature increases, the change in the fracture toughness of the material is more obvious and the rate of change is faster. In addition, the crack expansion of the composite layer of crack-containing Type IV hydrogen storage cylinders was analyzed based on the extended finite element method in conjunction with the performance data after UV aging. The results reveal that cracks in the aged composite material winding layers become more sensitive, with lower initiation loads and longer crack propagation lengths under the same load. UV aging diminishes the overall load-bearing capacity and crack resistance of the hydrogen storage cylinder, posing increased safety risks during its operational service.

Is ALPPS still appropriate for large or locally advanced hepatocellular carcinoma in an era of targeted agents and immunotherapy?

Therapeutic options for large or locally advanced hepatocellular carcinoma (HCC) have limited efficacy. This study investigated the efficacy and safety of drug-eluting beads trans-arterial chemo-embolization (dTACE), portal vein embolization (PVE), tyrosine kinase inhibitor (TKI), and immune checkpoint inhibitors (ICI) compared to Associating Liver Partition and Portal vein ligation for Staged hepatectomy (ALPPS) for large or locally advanced HCC.Data regarding clinicopathological details, safety, and oncological outcomes were reviewed for the quadruple therapy (dTACE-PVE-TKI-ICI) and compared with ALPPS.From 2019 to 2020, 10 patients with large or locally advanced HCC underwent future remnant liver (FRL) modulation (dTACE-PVE-TKI-ICI: 5; ALPPS: 5). All five dTACE-PVE-TKI-ICI cases responded well, with patients #4 and #5 achieving complete tumor necrosis. The overall response rate (ORR) was 5/5. Patients #1-4 underwent hepatectomy, while #5 declined surgery due to complete tumor necrosis. Mean FRL volume increased by 75.3% (range 60.0%-89.4%) in 2-4 months, compared to 104.6% (range 51.3%-160.8%) in 21-37 days for ALPPS (P = 0.032). Major postoperative complications occurred in 1/5 ALPPS patients. Resection rates were 4/4 for quadruple therapy and 5/5 for ALPPS. 2-year progression free survival for dTACE-PVE-TKI-ICI and ALPPS were 5/5 and 3/5, respectively.Quadruple therapy is a feasible, effective strategy for enhancing resectability by downsizing tumors and inducing FRL hypertrophy, with manageable complications and improved long-term prognosis. In addition, it provokes the re-examination of the application of ALPPS in an era of molecular and immune treatments.

Immune checkpoint inhibitor­associated diabetes mellitus in patients with HCC: Report of three cases and literature review.

Treatment with immune checkpoint inhibitors (ICIs) is steadily becoming the standard of care for hepatocellular carcinoma (HCC), with an increasing number of immune-related adverse events (irAEs). However, only a small number of reports on the occurrence of diabetes mellitus (DM) in patients with HCC treated with ICIs have been published. In the present study, the clinical manifestations, laboratory findings, treatment and prognosis of three patients with advanced HCC were reported, who suffered immune-related DM when receiving treatment with ICIs. Furthermore, the relevant literature was reviewed in order to summarize clinical manifestations, possible mechanisms, diagnosis, prognosis of rechallenge and recommended management options, as well as clinical treatment suggestions. ICI-induced diabetes is rare but irAEs are potentially fatal, as diabetic ketoacidosis (DKA) is often the first manifestation. The incidence of immune-related DM is 0.86% and among those cases, the incidence of DKA is 59%. The combination of two ICIs markedly increases the risk. The human leukocyte antigen genotype, islet autoantibodies and autoreactive T cell-mediated ß-cell destruction may be linked to the occurrence of immune-related DM. Patient education and clinicians' awareness of ICI-related DM are good management options. Adequate clinical judgment, close monitoring and early detection are also needed to decide whether to continue immunotherapy or to rechallenge it, so as to achieve the maximum benefit of clinical treatment.

scVSC: Deep variational subspace clustering for single-cell transcriptome data.

Single-cell RNA sequencing (scRNA-seq) is a potent advancement for analyzing gene expression at the individual cell level, allowing for the identification of cellular heterogeneity and subpopulations. However, it suffers from technical limitations that result in sparse and heterogeneous data. Here, we propose scVSC, an unsupervised clustering algorithm built on deep representation neural networks. The method incorporates the variational inference into the subspace model, which imposes regularization constraints on the latent space and further prevents overfitting. In a series of experiments across multiple datasets, scVSC outperforms existing state-of-the-art unsupervised and semi-supervised clustering tools regarding clustering accuracy and running efficiency. Moreover, the study indicates that scVSC could visually reveal the state of trajectory differentiation, accurately identify differentially expressed genes, and further discover biologically critical pathways.

Dissecting Spatiotemporal Structures in Spatial Transcriptomics via Diffusion-Based Adversarial Learning.

Recent advancements in spatial transcriptomics (ST) technologies offer unprecedented opportunities to unveil the spatial heterogeneity of gene expression and cell states within tissues. Despite these capabilities of the ST data, accurately dissecting spatiotemporal structures (e.g., spatial domains, temporal trajectories, and functional interactions) remains challenging. Here, we introduce a computational framework, PearlST (partial differential equation [PDE]-enhanced adversarial graph autoencoder of ST), for accurate inference of spatiotemporal structures from the ST data using PDE-enhanced adversarial graph autoencoder. PearlST employs contrastive learning to extract histological image features, integrates a PDE-based diffusion model to enhance characterization of spatial features at domain boundaries, and learns the latent low-dimensional embeddings via Wasserstein adversarial regularized graph autoencoders. Comparative analyses across multiple ST datasets with varying resolutions demonstrate that PearlST outperforms existing methods in spatial clustering, trajectory inference, and pseudotime analysis. Furthermore, PearlST elucidates functional regulations of the latent features by linking intercellular ligand-receptor interactions to most contributing genes of the low-dimensional embeddings, as illustrated in a human breast cancer dataset. Overall, PearlST proves to be a powerful tool for extracting interpretable latent features and dissecting intricate spatiotemporal structures in ST data across various biological contexts.

Construction of a multi-tissue compound-target interaction network of Qingfei Paidu decoction in COVID-19 treatment based on deep learning and transcriptomic analysis.

The Qingfei Paidu decoction (QFPDD) is a widely acclaimed therapeutic formula employed nationwide for the clinical management of coronavirus disease 2019 (COVID-19). QFPDD exerts a synergistic therapeutic effect, characterized by its multi-component, multi-target, and multi-pathway action. However, the intricate interactions among the ingredients and targets within QFPDD and their systematic effects in multiple tissues remain undetermined. To address this, we qualitatively characterized the chemical components of QFPDD. We integrated multi-tissue transcriptomic analysis with GraphDTA, a deep learning model, to screen for potential compound-target interactions of QFPDD in multiple tissues. We predicted 13 key active compounds, 127 potential targets and 27 pathways associated with QFPDD across six different tissues. Notably, oleanolic acid-AXL exhibited leading affinity in the heart, blood, and liver. Molecular docking and molecular dynamics simulation confirmed their strong binding affinity. The robust interaction between oleanolic acid and the AXL receptor suggests that AXL is a promising target for developing clinical intervention strategies. Through the construction of a multi-tissue compound-target interaction network, our study further elucidated the mechanisms through which QFPDD effectively combats COVID-19 in multiple tissues. Our work also establishes a framework for future investigations into the systemic effects of other Traditional Chinese Medicine (TCM) formulas in disease treatment.

Rapid preparation and proton NMR fingerprinting of polysaccharides from Radix Astragali.

The purity, content, and structure of the polysaccharides prepared from a specific medicinal plant are the fundamental basis to interpret the observed biological activities. An ultrafiltration-based method has been developed for rapid preparation of total and fractional polysaccharides from Radix Astragali in high yield and purity. This method involves extraction of plant material by hot water, treatment with Sevag reagent, and ultrafiltration using molecular weight cutoff concentrators. The prepared polysaccharides were assessed by 1H NMR spectroscopy, providing general purity, fingerprinting, and structural information. This method may be used to efficiently screen polysaccharides in plants.

Diagnostic accuracy of upper tract urothelial carcinoma using biopsy, urinary cytology, and nephroureterectomy specimens: A tertiary cancer center experience.

OBJECTIVES: We studied the diagnostic accuracy and discordance of upper tract urothelial carcinoma (UTUC) by comparing biopsy and urinary cytology with matched nephroureterectomy specimens. METHODS: Sixty-nine patients with UTUC without neoadjuvant treatment were retrospectively identified who had matched biopsy and nephroureterectomy specimens. Twenty patients had concurrent upper tract cytology. H&E and cytology slides were re-reviewed. Statistical analysis was performed. RESULTS: Patients included 48 men and 21 women with a mean age of 69 years. A concordant grade between biopsy and surgical specimen was present in 49 (71%) patients. The mean size of biopsy specimens in the discordant group was significantly smaller than that in the concordant group. Invasion was evaluated in 48 biopsy cases that had adequate subepithelial tissue, and 33 of them were diagnosed with concordant invasion status. Mean tumor size in both tumor grade and invasion discordant groups was significantly larger than that in the concordant group. High-grade urothelial carcinoma was detected in 84% of cases using urinary cytology. CONCLUSIONS: Our study demonstrates the diagnostic challenges of UTUC on small biopsy specimens. Biopsy specimen size and tumor size are significantly associated with the diagnostic discordance. Upper tract cytology showed high diagnostic accuracy and should be complementary to the biopsy.

Comprehensive quality assessment of peppermint oils and commercial products: An integrated approach involving conventional and chiral GC/MS coupled with chemometrics.

Peppermint essential oil (EO) has a multitude of applications, such as a fragrance in cosmetics, personal care and industrial products, or as a flavoring ingredient in food and beverages. Despite its popularity and economic significance, peppermint EO is often adulterated to reduce production costs and to increase profits. Although the ISO standard for peppermint EO exists, detecting sophisticated forms of adulteration remains challenging.The current study used conventional and chiral GC/MS analysis of volatiles compounds, and chemometric techniques to evaluate an extensive set of authentic peppermint EO (n = 22) and commercial products (n = 36) purported to contain peppermint EO. Specifically, thirty-six terpenoids were examined in each sample and compared with the ISO standard. Fifty-three percent of the selected commercial products did not meet the ISO specifications and the ratio between menthone/isomenthone was proven to be a good indicator for authentication and adulteration detection. Chiral GC/MS was further employed to measure eight terpenoids: α-pinene, ß-pinene, limonene, menthol, menthone, isomenthone, pulegone, and menthyl acetate. The enantiomeric compositions of 27 commercial products were above or below the norm measured from authentic peppermint EOs. Of the 27 samples, eight met the ISO standard. A sample class prediction (SCP) model based on partial least squares-discriminant analysis (PLS-DA) of conventional GC/MS data was constructed using authentic peppermint EOs and cornmint EOs. The model can distinguish the most common types of peppermint EOs (US, India, and US/India blend) and cornmint EOs sold in the US market. After construction, the SCP model was then used to analyze commercial samples. One sample, which passed both ISO specification and chiral analysis, was identified as outlier by the SCP model. Overall, the applicability of combining both conventional and chiral GC/MS along with chemometric tools has been successfully demonstrated to address the overall quality of peppermint EOs in commerce and may help combat sophisticated adulteration.

Automatedly identify dryland threatened species at large scale by using deep learning.

Dryland biodiversity is decreasing at an alarming rate. Advanced intelligent tools are urgently needed to rapidly, automatedly, and precisely detect dryland threatened species on a large scale for biological conservation. Here, we explored the performance of three deep convolutional neural networks (Deeplabv3+, Unet, and Pspnet models) on the intelligent recognition of rare species based on high-resolution (0.3 m) satellite images taken by an unmanned aerial vehicle (UAV). We focused on a threatened species, Populus euphratica, in the Tarim River Basin (China), where there has been a severe population decline in the 1970s and restoration has been carried out since 2000. The testing results showed that Unet outperforms Deeplabv3+ and Pspnet when the training samples are lower, while Deeplabv3+ performs best as the dataset increases. Overall, when training samples are 80, Deeplabv3+ had the best overall performance for Populus euphratica identification, with mean pixel accuracy (MPA) between 87.31 % and 90.2 %, which, on average is 3.74 % and 11.29 % higher than Unet and Pspnet, respectively. Deeplabv3+ can accurately detect the boundaries of Populus euphratica even in areas of dense vegetation, with lower identification uncertainty for each pixel than other models. This study developed a UAV imagery-based identification framework using deep learning with high resolution in large-scale regions. This approach can accurately capture the variation in dryland threatened species, especially those in inaccessible areas, thereby fostering rapid and efficient conservation actions.

Crop water productivity assessment and planting structure optimization in typical arid irrigation district using dynamic Bayesian network.

Enhancing crop water productivity is crucial for regional water resource management and agricultural sustainability, particularly in arid regions. However, evaluating the spatial heterogeneity and temporal dynamics of crop water productivity in face of data limitations poses a challenge. In this study, we propose a framework that integrates remote sensing data, time series generative adversarial network (TimeGAN), dynamic Bayesian network (DBN), and optimization model to assess crop water productivity and optimize crop planting structure under limited water resources allocation in the Qira oasis. The results demonstrate that the combination of TimeGAN and DBN better improves the accuracy of the model for the dynamic prediction, particularly for short-term predictions with 4 years as the optimal timescale (R2 > 0.8). Based on the spatial distribution of crop suitability analysis, wheat and corn are most suitable for cultivation in the central and eastern parts of Qira oasis while cotton is unsuitable for planting in the western region. The walnuts and Chinese dates are mainly unsuitable in the southeastern part of the oasis. Maximizing crop water productivity while ensuring food security has led to increased acreage for cotton, Chinese dates and walnuts. Under the combined action of the five optimization objectives, the average increase of crop water productivity is 14.97%, and the average increase of ecological benefit is 3.61%, which is much higher than the growth rate of irrigation water consumption of cultivated land. It will produce a planting structure that relatively reduced irrigation water requirement of cultivated land and improved crop water productivity. This proposed framework can serve as an effective reference tool for decision-makers when determining future cropping plans.

Identification and Functional Characterization of Oxidosqualene Cyclases from Medicinal Plant Hoodia gordonii.

Oxidosqualene cyclases (OSCs) are the key enzymes accountable for the cyclization of 2,3-oxidosqualene to varied triterpenoids and phytosterols. Hoodia gordonii (from the family Apocynaceae), a native of the Kalahari deserts of South Africa, Namibia, and Botswana, is being sold as a prevalent herbal supplement for weight loss. The appetite suppressant properties are attributed to P57AS3, an oxypregnane steroidal glycoside. At the molecular level, the enzymes involved in the biosynthesis of triterpenes and phytosterols from H. gordonii have not been previously reported. In the current study, predicted transcripts potentially encoding oxidosqualene cyclases were recognized first by searching publicly available H. gordonii RNA-seq datasets. Two OSC-like sequences were selected for functional analysis. A monofunctional OSC, designated HgOSC1 which encodes lupeol synthase, and HgOSC2, a multifunctional cycloartenol synthase forming cycloartenol and other products, were observed through recombinant enzyme studies. These studies revealed that distinct OSCs exist for triterpene formation in H. gordonii and provided opportunities for the metabolic engineering of specific precursors in producing phytosterols in this plant species.