An Explainable Graph Neural Framework to Identify Cancer-Associated Intratumoral Microbial Communities.

Microbes are extensively present among various cancer tissues and play critical roles in carcinogenesis and treatment responses. However, the underlying relationships between intratumoral microbes and tumors remain poorly understood. Here, a MIcrobial Cancer-association Analysis using a Heterogeneous graph transformer (MICAH) to identify intratumoral cancer-associated microbial communities is presented. MICAH integrates metabolic and phylogenetic relationships among microbes into a heterogeneous graph representation. It uses a graph transformer to holistically capture relationships between intratumoral microbes and cancer tissues, which improves the explainability of the associations between identified microbial communities and cancers. MICAH is applied to intratumoral bacterial data across 5 cancer types and 5 fungi datasets, and its generalizability and reproducibility are demonstrated. After experimentally testing a representative observation using a mouse model of tumor-microbe-immune interactions, a result consistent with MICAH's identified relationship is observed. Source tracking analysis reveals that the primary known contributor to a cancer-associated microbial community is the organs affected by the type of cancer. Overall, this graph neural network framework refines the number of microbes that can be used for follow-up experimental validation from thousands to tens, thereby helping to accelerate the understanding of the relationship between tumors and intratumoral microbiomes.

A computational mechanistic study on the formation of aryl sulfonyl fluorides via Bi(III) redox-neutral catalysis and further rational design.

Sulfonyl fluorides hold significant importance as highly valued intermediates in chemical biology due to their optimal balance of biocompatibility with both aqueous stability and protein reactivity. The Cornella group introduced a one-pot strategy for synthesizing aryl sulfonyl fluorides via Bi(III) redox-neutral catalysis, which facilitates the transmetallation and direct insertion of SO2 into the BiC(sp2) bond giving the aryl sulfonyl fluorides. We report herein a comprehensive computational investigation of the redox-neutral Bi(III) catalytic mechanism, disclose the critical role of the Bi(III) catalyst and base (i.e., K3PO4), and uncover the origin of SO2 insertion into the Bi(III)C(sp2) bond. The entire catalysis can be characterized via three stages: (i) transmetallation generating the Bi(III)-phenyl intermediate IM3 facilitated by K3PO4. (ii) SO2 insertion into IM3 leading to the formation of Bi(III)-OSOAr intermediate IM5. (iii) IM5 undergoes S(IV)-oxidation yielding the aryl sulfonyl fluoride product 4 and liberating the Bi(III) catalyst for the next catalytic cycle. Each stage is kinetically and thermodynamically feasible. Moreover, we explored other some small molecules (NO2, CO2, H2O, N2O, etc.) insertion reactions mediated by the Bi(III)-complex, and found that NO2 insertions could be easily achieved due to the low insertion barriers (i.e., 17.5 kcal/mol). Based on the detailed mechanistic study, we further rationally designed additional Bi(III) and Sb(III) catalysts, and found that some of which exhibit promising potential for experimental realization due to their low barriers (<16.4 kcal/mol). In this regard, our study contributes significantly to enhancing current Bi(III)-catalytic systems and paving the way for novel Bi(III)-catalyzed aryl sulfonyl fluoride formation reactions.

Applications of artificial intelligence to myeloproliferative neoplasms: a narrative review.

INTRODUCTION: Artificial intelligence (AI) is a rapidly growing field of computational research with the potential to extract nuanced biomarkers for the prediction of outcomes of interest. AI implementations for the prediction for clinical outcomes for myeloproliferative neoplasms (MPNs) are currently under investigation. AREAS COVERED: In this narrative review, we discuss AI investigations for the improvement of MPN clinical care utilizing either clinically available data or experimental laboratory findings. Abstracts and manuscripts were identified upon querying PubMed and the American Society of Hematology conference between 2000 and 2023. Overall, multidisciplinary researchers have developed AI methods in MPNs attempting to improve diagnostic accuracy, risk prediction, therapy selection, or pre-clinical investigations to identify candidate molecules as novel therapeutic agents. EXPERT OPINION: It is our expert opinion that AI methods in MPN care and hematology will continue to grow with increasing clinical utility. We believe that AI models will assist healthcare workers as clinical decision support tools if appropriately developed with AI-specific regulatory guidelines. Though the reported findings in this review are early investigations for AI in MPNs, the collective work developed by the research community provides a promising framework for improving decision-making in the future of MPN clinical care.

Graph Fourier transform for spatial omics representation and analyses of complex organs.

Spatial omics technologies decipher functional components of complex organs at cellular and subcellular resolutions. We introduce Spatial Graph Fourier Transform (SpaGFT) and apply graph signal processing to a wide range of spatial omics profiling platforms to generate their interpretable representations. This representation supports spatially variable gene identification and improves gene expression imputation, outperforming existing tools in analyzing human and mouse spatial transcriptomics data. SpaGFT can identify immunological regions for B cell maturation in human lymph nodes Visium data and characterize variations in secondary follicles using in-house human tonsil CODEX data. Furthermore, it can be integrated seamlessly into other machine learning frameworks, enhancing accuracy in spatial domain identification, cell type annotation, and subcellular feature inference by up to 40%. Notably, SpaGFT detects rare subcellular organelles, such as Cajal bodies and Set1/COMPASS complexes, in high-resolution spatial proteomics data. This approach provides an explainable graph representation method for exploring tissue biology and function.

Management of drug supply chain information based on "artificial intelligence + vendor managed inventory" in China: perspective based on a case study.

Objectives: To employ a drug supply chain information system to optimize drug management practices, reducing costs and improving efficiency in financial and asset management. Methods: A digital artificial intelligence + vendor managed inventory (AI+VMI)-based system for drug supply chain information management in hospitals has been established. The system enables digitalization and intelligentization of purchasing plans, reconciliations, and consumption settlements while generating purchase, sales, inventory reports as well as various query reports. The indicators for evaluating the effectiveness before and after project implementation encompass drug loss reporting, inventory discrepancies, inter-hospital medication retrieval frequency, drug expenditure, and cloud pharmacy service utilization. Results: The successful implementation of this system has reduced the hospital inventory rate to approximately 20% and decreased the average annual inventory error rate from 0.425‰ to 0.025‰, significantly boosting drug supply chain efficiency by 42.4%. It has also minimized errors in drug application, allocation, and distribution while increasing adverse reaction reports. Drug management across multiple hospital districts has been standardized, leading to improved access to medicines and enhanced patient satisfaction. Conclusion: The AI+VMI system improves drug supply chain management by ensuring security, reducing costs, enhancing efficiency and safety of drug management, and elevating the professional competence and service level of pharmaceutical personnel.

The Tumor Microbiome as a Predictor of Outcomes in Patients with Metastatic Melanoma Treated with Immune Checkpoint Inhibitors.

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and its potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICI). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA sequencing (RNA-seq) was conducted on the formalin-fixed, paraffin-embedded and fresh frozen tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival >24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The age of the 71 patients with metastatic melanoma ranged from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy-responsive versus nonresponsive tumors. Responders showed significant enrichment of bacteriophages in the phylum Uroviricota, and nonresponders showed enrichment of several bacteria, including Campylobacter jejuni. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs. SIGNIFICANCE: We analyzed the tumor microbiome and interactions with genes and pathways in metastatic melanoma treated with immunotherapy and identified several microbes associated with immunotherapy response and immune-related gene expression signatures. Machine learning models that combined microbe abundances and gene expression outperformed models using either dataset alone in predicting immunotherapy responses.

Autoencoder to Identify Sex-Specific Sub-phenotypes in Alzheimer's Disease Progression Using Longitudinal Electronic Health Records.

Alzheimer's Disease (AD) is a complex neurodegenerative disorder significantly influenced by sex differences, with approximately two-thirds of AD patients being women. Characterizing the sex-specific AD progression and identifying its progression trajectory is a crucial step to developing effective risk stratification and prevention strategies. In this study, we developed an autoencoder to uncover sex-specific sub-phenotypes in AD progression leveraging longitudinal electronic health record (EHR) data from OneFlorida+ Clinical Research Consortium. Specifically, we first constructed temporal patient representation using longitudinal EHRs from a sex-stratified AD cohort. We used a long short-term memory (LSTM)-based autoencoder to extract and generate latent representation embeddings from sequential clinical records of patients. We then applied hierarchical agglomerative clustering to the learned representations, grouping patients based on their progression sub-phenotypes. The experimental results show we successfully identified five primary sex-based AD sub-phenotypes with corresponding progression pathways with high confidence. These sex-specific sub-phenotypes not only illustrated distinct AD progression patterns but also revealed differences in clinical characteristics and comorbidities between females and males in AD development. These findings could provide valuable insights for advancing personalized AD intervention and treatment strategies.

Silylene-Stabilized Neutral Dibora-Aromatics with a B═B Bond.

The unprecedented silylene-supported dibenzodiboraoxepin 2 and 9,10-diboraphenanthrene complexes 6 and 8 were synthesized. The (NHSi)2B2(xanthene) [NHSi = PhC(NtBu)2(Me2N)Si:] 2 results from debromination of the bis(NHSi)-stabilized bis(dibromoboryl)xanthene 1 with potassium graphite (KC8); 2 is capable of activating white phosphorus and ammonia to form the B2P4 cage compound 3 and H2N-B-B-H diborane species 4, respectively. The thermal rearrangement of 2 affords the 9,10-dihydro-9,10-diboraphenanthrene 5 through a bis(NHSi)-assisted intramolecular reductive C-O-C deoxygenation process. Notably, the 9,10-diboraphenanthrene derivatives 6 and 8 could be generated by deoxygenation of 2 with KC8 and 1,3,4,5-tetramethylimidazol-2-ylidene, respectively. The aromaticity of 6 and 8 was confirmed by computational studies. Strikingly, the NHSi ligand in 8 engenders the monodeoxygenation of carbon dioxide in toluene at room temperature to form the CO-stabilized 9,10-diboraphenanthrene derivative 9 via the silaoxadiborinanone intermediate 10.

Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data.

Deciphering the intricate relationships between transcription factors (TFs), enhancers, and genes through the inference of enhancer-driven gene regulatory networks (eGRNs) is crucial in understanding gene regulatory programs in a complex biological system. This study introduces STREAM, a novel method that leverages a Steiner forest problem model, a hybrid biclustering pipeline, and submodular optimization to infer eGRNs from jointly profiled single-cell transcriptome and chromatin accessibility data. Compared to existing methods, STREAM demonstrates enhanced performance in terms of TF recovery, TF-enhancer linkage prediction, and enhancer-gene relation discovery. Application of STREAM to an Alzheimer's disease dataset and a diffuse small lymphocytic lymphoma dataset reveals its ability to identify TF-enhancer-gene relations associated with pseudotime, as well as key TF-enhancer-gene relations and TF cooperation underlying tumor cells.

Patient-reported physical well-being predicts good long-term survival of hematopoietic stem cell transplantation.

AIM: This study aimed to explore the association between patient-reported items at different time points after hematopoietic stem cell transplantation (HSCT) and long-term survival. METHODS: We conducted a study with 144 allogeneic HSCT patients, following them for 5 years post-transplantation. Data from the Functional Assessment of Cancer Therapy-Bone Marrow Transplant (FACT-BMT) questionnaire were collected before transplantation and at 1, 3, 6, 12, 18, 36, and 60 months after transplantation. Demographic characteristics and survival status were also assessed. RESULTS: Among the 144 cases, the 5-year overall survival (OS), progression-free survival (PFS), non-relapse mortality (NRM), and graft-versus-host disease-free (GRFS) rates were 65%, 48%, 17%, and 36% respectively. Health-related quality of life (HRQOL) showed a fluctuating pattern over 5 years. Using a latent class mixed model, patients were classified into two groups based on their physical well-being (PWB) scores during the 60-month follow-up. Class 1 had initially lower PWB scores, which gradually increased over time. In contrast, Class 2 maintained higher PWB scores with slight increases over time. Kaplan-Meier survival analysis revealed that Class 1 had better OS (70.9% vs. 52.9%, p = 0.021), PFS (60.5% vs. 41.2%, p = 0.039), and GRFS (35.1% vs. 29.3%, p = 0.035) compared to Class 2. CONCLUSIONS: Patients who had higher initial PWB scores after HSCT demonstrated improved long-term survival outcomes. The PWB score could serve as a valuable predictor for the prognosis of HSCT.

Intraoral Acupuncture for Sialorrhea in Stroke Patients: a Study Protocol for a Randomized Controlled Trial.

Importance: Post-stroke sialorrhea (PSS) refers to excessive saliva flowing out the lip border after a stroke. PSS negatively affects patient self-image and social communication and may lead to depression. Limited evidence supports the link between excessive salivation and PSS. No large-scale, strictly controlled randomized controlled trials have shown the effectiveness of acupuncture in treating PSS patients. Objective: We aim to compare the effects of intraoral and sham acupuncture in PSS patients and explore relationships among salivation and drooling severity and frequency and swallowing function in stroke patients. Design: Clinical study protocol, SPIRIT compliant. Setting: Prospective, single-center, randomized, and sham-controlled trial. Population: We will recruit 106 PSS patients to receive 4-week intraoral or sham acupuncture. Additionally, 53 stroke patients without PSS will undergo a conventional 4-week treatment program to compare salivation between PSS and non-PSS patients. Exposures: Intraoral or sham acupuncture. Main Outcomes and Measures: The main evaluation index will be the 3-minute saliva weight (3MSW), comparing changes in 3MSW from baseline to weeks 4 and 8. Secondary assessment indices will include the "Drooling Severity and Frequency Scale" and "Functional Oral Intake Scale." Results: The results from this study will be published in peer-reviewed journals. Conclusion: Comparing effects of intraoral and sham acupuncture in PSS patients, this study may contribute important evidence for future PSS treatment and provide valuable insights into whether salivation issues in stroke patients are attributed to heightened salivary secretion or dysphagia.

The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer.

Tumor hypoxia has been shown to predict poor patient outcomes in several cancer types, partially because it reduces radiation's ability to kill cells. We hypothesized that some of the clinical effects of hypoxia could also be due to its impact on the tumor microbiome. Therefore, we examined the RNA sequencing data from the Oncology Research Information Exchange Network database of patients with colorectal cancer treated with radiotherapy. We identified microbial RNAs for each tumor and related them to the hypoxic gene expression scores calculated from host mRNA. Our analysis showed that the hypoxia expression score predicted poor patient outcomes and identified tumors enriched with certain microbes such as Fusobacterium nucleatum. The presence of other microbes, such as Fusobacterium canifelinum, predicted poor patient outcomes, suggesting a potential interaction between hypoxia, the microbiome, and radiation response. To experimentally investigate this concept, we implanted CT26 colorectal cancer cells into immune-competent BALB/c and immune-deficient athymic nude mice. After growth, in which tumors passively acquired microbes from the gastrointestinal tract, we harvested tumors, extracted nucleic acids, and sequenced host and microbial RNAs. We stratified tumors based on their hypoxia score and performed a metatranscriptomic analysis of microbial gene expression. In addition to hypoxia-tropic and -phobic microbial populations, analysis of microbial gene expression at the strain level showed expression differences based on the hypoxia score. Thus, hypoxia gene expression scores seem to associate with different microbial populations and elicit an adaptive transcriptional response in intratumoral microbes, potentially influencing clinical outcomes. SIGNIFICANCE: Tumor hypoxia reduces radiotherapy efficacy. In this study, we explored whether some of the clinical effects of hypoxia could be due to interaction with the tumor microbiome. Hypoxic gene expression scores associated with certain microbes and elicited an adaptive transcriptional response in others that could contribute to poor clinical outcomes.

Genome-wide analysis of AP2/ERF transcription factors that regulate fruit development of Chinese prickly ash.

BACKGROUND: AP2/ERF is a large family of plant transcription factor proteins that play essential roles in signal transduction, plant growth and development, and responses to various stresses. The AP2/ERF family has been identified and verified by functional analysis in various plants, but so far there has been no comprehensive study of these factors in Chinese prickly ash. Phylogenetic, motif, and functional analyses combined with transcriptome analysis of Chinese prickly ash fruits at different developmental stages (30, 60, and 90 days after anthesis) were conducted in this study. RESULTS: The analysis identified 146 ZbAP2/ERF genes that could be classified into 15 subgroups. The motif analysis revealed the presence of different motifs or elements in each group that may explain the functional differences between the groups. ZbERF13.2, ZbRAP2-12, and ZbERF2.1 showed high levels of expression in the early stages of fruit development. ZbRAP2-4, and ZbERF3.1 were significantly expressed at the fruit coloring stage (R2 and G2). ZbERF16 were significantly expressed at fruit ripening and expression level increased as the fruit continued to develop. Relative gene expression levels of 6 representative ZbAP2/ERFs assessed by RT-qPCR agreed with transcriptome analysis results. CONCLUSIONS: These genes identified by screening can be used as candidate genes that affect fruit development. The results of the analysis can help guide future genetic improvement of Chinese prickly ash and enrich our understanding of AP2/ERF transcription factors and their regulatory functions in plants.

Glycyrrhetinic acid blocks SARS-CoV-2 infection by activating the cGAS-STING signalling pathway.

BACKGROUND AND PURPOSE: Traditional Chinese medicine (TCM) played an important role in controlling the COVID-19 pandemic, but the scientific basis and its active ingredients are still weakly studied. This study aims to decipher the underlying anti-SARS-CoV-2 mechanisms of glycyrrhetinic acid (GA). EXPERIMENTAL APPROACH: GA's anti-SARS-CoV-2 effect was verified both in vitro and in vivo. Homogeneous time-resolved fluorescence assays, biolayer interferometry technology, and molecular docking were employed to examine interactions of GA with human stimulator of interferon genes (hSTING). Immunofluorescence staining, western blot, and RT-qPCR were used to investigate nuclear translocation of interferon regulatory factor 3 (IRF3) and levels of STING target genes. Pharmacokinetics of GA was studied in mice. KEY RESULTS: GA could directly bind to Ser162 and Tyr240 residues of hSTING, thus up-regulating downstream targets and activation of the STING signalling pathway. Such activation is crucial for limiting the replication of SARS-CoV-2 Omicron in Calu-3 cells and protecting against lung injury induced by SARS-CoV-2 Omicron infection in K18-ACE2 transgenic mice. Immunofluorescence staining and western blot indicated that GA increased levels of phosphorylated STING, phosphorylated TANK-binding kinase-1, and cyclic GMP-AMP synthase (cGAS). Importantly, GA increased nuclear translocation of IRF3. Pharmacokinetic analysis of GA in mice indicated it can be absorbed into circulation and detected in the lung at a stable level. CONCLUSION AND IMPLICATIONS: Activation of the cGAS-STING pathway through the GA-STING-IRF3 axis is essential for the antiviral activity of GA in mice, providing new insights into the potential translation of GA for treating SARS-CoV-2 in patients.

Efficacy and safety of drug-coated balloons in chronic total coronary occlusion recanalization: a systematic review and meta-analysis.

BACKGROUND: With advancements in chronic total coronary occlusion (CTO) recanalization techniques and concepts, the success rate of recanalization has been steadily increasing. However, the current data are too limited to draw any reliable conclusions about the efficacy and safety of drug-coated balloons (DCBs) in CTO percutaneous coronary intervention (PCI). Herein, we conducted a meta-analysis to confirm the efficacy of DCB in CTO PCI. METHODS: We systematically searched PubMed, Web of Science and Embase from inception to July 25, 2023. The primary outcome was major advent cardiovascular events (MACE), including cardiac death, nonfatal myocardial infarction (MI), target lesion revascularization (TLR), and target vessel revascularization (TVR). The follow-up angiographic endpoints were late lumen enlargement (LLE), reocclusion and restenosis. RESULTS: Five studies with a total of 511 patients were included in the meta-analysis. Across studies, patients were predominantly male (72.9-85.7%) and over fifty years old. The summary estimate rate of MACE was 13.0% (95% CI 10.1%-15.9%, I2 = 0%, p = 0.428). The summary estimate rates of cardiac death and MI were 2.2% (95% CI 0.7%-3.7%, I2 = 0%, p = 0.873) and 1.2% (95% CI -0.2-2.6%, I2 = 13.7%, p = 0.314), respectively. Finally, the pooled incidences of TLR and TVR were 10.1% (95% CI 5.7%-14.5%, I2 = 51.7%, p = 0.082) and 7.1% (95% CI 3.0%-11.2%, I2 = 57.6%, p = 0.070), respectively. Finally, the summary estimate rates of LLE, reocclusion and restenosis were 59.4% (95% CI 53.5-65.3%, I2 = 0%, p = 0.742), 3.3% (95% CI 1.1-5.4%, I2 = 0%, p = 0.865) and 17.5% (95% CI 12.9-22.0%, I2 = 0%, p = 0.623), respectively. CONCLUSION: Accordingly, DCB has the potential to be used as a treatment for CTO in suitable patients.

Modular access to furo[3,2-c]chromen-4-ones via Yb(OTf)3-catalyzed [3 + 2] annulation of 4-hydroxycoumarins with ß-nitroalkenes.

A facile and efficient strategy for modular access to furo[3,2-c]chromen-4-ones using 4-hydroxycoumarin and ß-nitroalkenes via Lewis acid-catalyzed formal [3 + 2] annulation protocol is described. This reaction proceeds via cascade Michael addition/nucleophilic addition/elimination in the presence of Yb(OTf)3, which involves the formation of two new σ (C-C and C-O) bonds for the construction of a novel furan ring in a single operation. This protocol affords a variety of functional groups, thereby providing a practical and efficient method for the fabrication of a furo[3,2-c]chromen-4-one framework.

A high-performance organic fluorescent probe with aggregation-induced emission properties for long-term tumor monitoring.

Near-infrared organic fluorescent probes have great need in biological sciences and medicine but most of them are still largely unable to meet demand. In this work, a delicate multipurpose organic fluorescent probe (DPPM-TPA) with aggregation-induced emission performances is designed and prepared by facile method to reflect fluorescence labeling, two-photon imaging, and long-term fluorescent tracking. Specifically, DPPM-TPA NPs was constructed from 4-(diphenylamino)phenylboronic acid and DPPM-Br by classical Suzuki coupling reaction and then coated with F127. Such nanoprobe possessed high stability in diverse medium under ambient temperatures, low cytotoxicity, and brilliant fluorescence performance. More importantly, DPPM-TPA NPs showed excellent two-photon imaging and extraordinary long-term fluorescence tracing capacity to malignant tumor, and it can last up to 9 days. These results indicated that DPPM-TPA NPs is expected to serve as a fluorescent probe for photodiagnostic and providing a new idea for the development of long-term fluorescent tracker.

A single-cell and spatial RNA-seq database for Alzheimer's disease (ssREAD).

Alzheimer's Disease (AD) pathology has been increasingly explored through single-cell and single-nucleus RNA-sequencing (scRNA-seq & snRNA-seq) and spatial transcriptomics (ST). However, the surge in data demands a comprehensive, user-friendly repository. Addressing this, we introduce a single-cell and spatial RNA-seq database for Alzheimer's disease (ssREAD). It offers a broader spectrum of AD-related datasets, an optimized analytical pipeline, and improved usability. The database encompasses 1,053 samples (277 integrated datasets) from 67 AD-related scRNA-seq & snRNA-seq studies, totaling 7,332,202 cells. Additionally, it archives 381 ST datasets from 18 human and mouse brain studies. Each dataset is annotated with details such as species, gender, brain region, disease/control status, age, and AD Braak stages. ssREAD also provides an analysis suite for cell clustering, identification of differentially expressed and spatially variable genes, cell-type-specific marker genes and regulons, and spot deconvolution for integrative analysis. ssREAD is freely available at https://bmblx.bmi.osumc.edu/ssread/ .

[Characteristics of leaf stoichiometry and the driving factors of Ammopiptanthus mongolicus, China]. / æ²™å†¬é’å¶ç‰‡åŒ–å­¦è®¡é‡ç‰¹å¾åŠå ¶é©±åŠ¨å› ç´ .

The stoichiometric characteristics of leaves can reflect environmental adaptation of plants, and thus the study of the relationship between them is helpful for exploring plant adaptation strategies. In this study, taking the national second-level key protection species, Ammopiptanthus mongolicus, as the research object, we set up 26 plots to collect samples, and measured the content of carbon (C), nitrogen (N), phosphorus (P) and water use efficiency (WUE) of leaves. We analyzed the relationship between leaf stoichiometric characteristics and WUE, and quantified the contributions of soil, climate, and water use efficiency to the variations of leaf stoichiometry. The results showed that C, N, and P contents in the leaves were (583.99±27.93), (24.31±2.09), and (1.83±0.06) mg·g-1, respectively. The coefficients of variation were 4.8%, 8.6%, and 3.2%, respectively, all belonging to weak variability, indicating that foliar contents of C, N and P tended to a certain stable value. The average value of N:P was 13.3, indicating that the growth of A. mongolicus was mainly limited by N. WUE was not correlated with leaf C content, but was significantly positively correlated with leaf N and P contents and N:P, and significantly negatively correlated with C:N and C:P, indicating that there was a linear synergistic trend between WUE and leaf nutrient content. The main factors influencing leaf C content and C:P were climatic factors, the leaf N content and N:P were mainly affected by soil factors, and the water use efficiency mainly affected leaf P content and C:N, indicating that the driving factors of different stoichiometric characteristics were different. The results could help eva-luate the habitat adaptation of desert plants, which would provide a theoretical basis for the conservation and management of A. mongolicus.