Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Reg...Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Regression models and Neural network models,to perform multi-characteristic coupled displacement prediction because they fail to consider landslide creep characteristics.This paper integrates the creep characteristics of landslides with non-linear intelligent algorithms and proposes a dynamic intelligent landslide displacement prediction method based on a combination of the Biological Growth model(BG),Convolutional Neural Network(CNN),and Long ShortTerm Memory Network(LSTM).This prediction approach improves three different biological growth models,thereby effectively extracting landslide creep characteristic parameters.Simultaneously,it integrates external factors(rainfall and reservoir water level)to construct an internal and external comprehensive dataset for data augmentation,which is input into the improved CNN-LSTM model.Thereafter,harnessing the robust feature extraction capabilities and spatial translation invariance of CNN,the model autonomously captures short-term local fluctuation characteristics of landslide displacement,and combines LSTM's efficient handling of long-term nonlinear temporal data to improve prediction performance.An evaluation of the Liangshuijing landslide in the Three Gorges Reservoir Area indicates that BG-CNN-LSTM exhibits high prediction accuracy,excellent generalization capabilities when dealing with various types of landslides.The research provides an innovative approach to achieving the whole-process,realtime,high-precision displacement predictions for multicharacteristic coupled landslides.展开更多
Microwave radiation has been widely used in various fields,such as communication,industry,medical treatment,and military applications.Microwave radiation may cause injuries to both the structures and functions of vari...Microwave radiation has been widely used in various fields,such as communication,industry,medical treatment,and military applications.Microwave radiation may cause injuries to both the structures and functions of various organs,such as the brain,heart,reproductive organs,and endocrine organs,which endanger human health.Therefore,it is both theoretically and clinically important to conduct studies on the biological effects induced by microwave radiation.The successful establishment of injury models is of great importance to the reliability and reproducibility of these studies.In this article,we review the microwave exposure conditions,subjects used to establish injury models,the methods used for the assessment of the injuries,and the indicators implemented to evaluate the success of injury model establishment in studies on biological effects induced by microwave radiation.展开更多
Inferring gene regulatory networks from large-scale expression data is an important topic in both cellular systems and computational biology. The inference of regulators might be the core factor for understanding actu...Inferring gene regulatory networks from large-scale expression data is an important topic in both cellular systems and computational biology. The inference of regulators might be the core factor for understanding actual regulatory conditions in gene regulatory networks, especially when strong regulators do work significantly. In this paper, we propose a novel approach based on combining neuro-fu^zy network models with biological knowledge to infer strong regulators and interrelated fuzzy rules. The hybrid neuro-fuzzy architecture can not only infer the fuzzy rules, which are suitable for describing the regulatory conditions in regulatory nctworks＋ but also explain the meaning of nodes and weight value in the neural network. It can get useful rules automatically without lhctitious judgments. At the same time, it does not add recursive layers to the model, and the model can also strengthen the relationships among genes and reduce calculation. We use the proposed approach to reconstruct a partial gene regulatory network of yeast, The results show that this approach can work effectively.展开更多
[Objective]The aim was to establish the linear regression prediction models between sowing time and plant productivity, biological yield of forage sorghum in autumn idle land.[Method]The relationships between sowing t...[Objective]The aim was to establish the linear regression prediction models between sowing time and plant productivity, biological yield of forage sorghum in autumn idle land.[Method]The relationships between sowing time and plant productivity, biological yield of forage sorghum were simulated and compared by using field experiment and linear regression analysis.[Result] The sowing time had an important influence on the plant productivity and biological yield of forage sorghum in autumn idle land. The plant productivity and biological yield of forage sorghum both decreased with the delay of sowing time.The regression model between plant fresh weight and sowing time was ？fresh=0.618-0.015x; the regression model between plant dry weight and sowing time was ？dry=0.184-0.005x; and the regression model between biological yield and sowing time was yield=29 126.461-711.448x. During July 23rd to August 30th, when the sowing time was delayed by 1 day, the plant fresh weight of forage sorghum was reduced by 0.015 g, the plant dry weight was reduced by 0.005 g, and the yield was reduced by 711.448 kg/hm2. [Conclusion] The three regression models established in this study will provide theoretical support for the production of forage sorghum.展开更多
This article considers three types of biological systems:the dengue fever disease model,the COVID-19 virus model,and the transmission of Tuberculosis model.The new technique of creating the integration matrix for the ...This article considers three types of biological systems:the dengue fever disease model,the COVID-19 virus model,and the transmission of Tuberculosis model.The new technique of creating the integration matrix for the Bernoulli wavelets is applied.Also,the novel method proposed in this paper is called the Bernoulli wavelet collocation scheme(BWCM).All three models are in the form system of coupled ordinary differential equations without an exact solution.These systems are converted into a system of algebraic equations using the Bernoulli wavelet collocation scheme.The numerical wave distributions of these governing models are obtained by solving the algebraic equations via the Newton-Raphson method.The results obtained from the developed strategy are compared to several schemes such as the Runge Kutta method,and ND solver in mathematical software.The convergence analyses are discussed through theorems.The newly implemented Bernoulli wavelet method improves the accuracy and converges when it is compared with the existing methods in the literature.展开更多
Background: Calotropis procera (C. procera), is an authentic plant naturally grown in the flora of Dead Sea region. Despite its toxicity, C. procera presents healing properties. However, it has not been implemented ye...Background: Calotropis procera (C. procera), is an authentic plant naturally grown in the flora of Dead Sea region. Despite its toxicity, C. procera presents healing properties. However, it has not been implemented yet in cosmetics as an active ingredient. Objective: The biological effects of C. procera callus extract on skin were elucidated solely and in combination with Dead Sea water (DSW). Methods: The capability of C. procera extract to protect against skin inflammation and irritation was tested on ex vivo human skin organ culture by LPS and SDS addition respectively. Viability and cytokine secretion were evaluated. The combination of C. procera extract with Dead Sea water was tested on full thickness skin equivalents. Gene expression and relevant biochemical markers for glycolysis, hypoxia and extracellular matrix balance were tested. Results: C. procera extract exhibits a protective biological activity against skin irritation and inflammation at the biochemical level. Furthermore, a combination of C. procera extract and DSW demonstrates a potential contribution for skin wellbeing via enhance energy production, resistance to hypoxia and extracellular matrix balance. Conclusions: Topical application of C. procera callus extract might support skin balance and wellbeing at the molecular level. Hence, it is recommended for new cosmetic formulae as standalone or in combination with Dead Sea water, in the effort to achieve anti-aging bio-activity that is working beyond skin aging symptoms, especially via skin calming effects and skin energy enhancement.展开更多
The oil spill impact analysis (OSIA) software system has been developed to supply a tool for comprehensive, quantitative environmental impact assessments resulting from oil spills. In the system, a biological componen...The oil spill impact analysis (OSIA) software system has been developed to supply a tool for comprehensive, quantitative environmental impact assessments resulting from oil spills. In the system, a biological component evaluates potential effects on exposed organisms based on results from a physico chemical fates component, including the extent and characteristics of the surface slick, and dissolved and total concentrations of hydrocarbons in the water column. The component includes a particle based exposure model for migratory adult fish populations, a particle based exposure model for spawning planktonic organisms (eggs and larvae), and an exposure model for wildlife species (sea birds or marine mammals). The exposure model for migratory adult fish populations simulates the migration behaviors of fish populations migrating to or staying in their feeding areas, over wintering areas or spawning areas, and determines the acute effects (mortality) and chronic accumulation (body burdens) from the dissolved contaminant. The exposure model for spawning planktonic organisms simulates the release of eggs and larvae, also as particles, from specific spawning areas during the spawning period, and determines their potential exposure to contaminants in the water or sediment. The exposure model for wild species calculates the exposure to surface oil of wildlife (bird and marine mammal) categories inhabiting the contaminated area. Compared with the earlier models in which all kinds of organisms are assumed evenly and randomly distributed, the updated biological exposure models can more realistically estimate potential effects on marine ecological system from oil spill pollution events.展开更多
Background: Positron emission tomography(PET) is a noninvasive method to characterize different metabolic activities of tumors, providing information for staging, prognosis, and therapeutic response of patients with c...Background: Positron emission tomography(PET) is a noninvasive method to characterize different metabolic activities of tumors, providing information for staging, prognosis, and therapeutic response of patients with cancer. The aim of this study was to evaluate the feasibility of18F-fludeoxyglucose(18F-FDG) and 3’-deoxy-3’-18F-fluorothymidine(18F-FLT) PET in predicting tumor biological characteristics of colorectal cancer liver metastasis.Methods: The uptake rate of18F-FDG and18F-FLT in SW480 and SW620 cells was measured via an in vitro cell uptake assay. The region of interest was drawn over the tumor and liver to calculate the maximum standardized uptake value ratio(tumor/liver) from PET images in liver metastasis model. The correlation between tracer uptake in liver metastases and VEGF, Ki67 and CD44 expression was evaluated by linear regression.Results: Compared to SW620 tumor-bearing mice, SW480 tumor-bearing mice presented a higher rate of liver metastases. The uptake rate of18F-FDG in SW480 and SW620 cells was 6.07% ± 1.19% and2.82% ± 0.15%, respectively(t = 4.69, P = 0.04); that of18F-FLT was 24.81% ± 0.45% and 15.57% ± 0.66%, respectively(t = 19.99, P < 0.001). Micro-PET scan showed that all parameters of FLT were significantly higher in SW480 tumors than those in SW620 tumors. A moderate relationship was detected between metastases in the liver and18F-FLT uptake in primary tumors(r = 0.73, P = 0.0019).18F-FLT uptake was also positively correlated with the expression of CD44 in liver metastases(r = 0.81, P = 0.0049).Conclusions: The uptake of18F-FLT in metastatic tumor reflects different biological behaviors of colon cancer cells.18F-FLT can be used to evaluate the metastatic potential of colorectal cancer in nude mice.展开更多
Myasthenia gravis is a chronic autoimmune disorder that affects the neuromuscular junction leading to fluctuating skeletal muscle fatigability. The majority of myasthenia gravis patients have detectable antibodies in ...Myasthenia gravis is a chronic autoimmune disorder that affects the neuromuscular junction leading to fluctuating skeletal muscle fatigability. The majority of myasthenia gravis patients have detectable antibodies in their serum, targeting acetylcholine receptor, muscle-specific kinase, or related proteins. Current treatment for myasthenia gravis involves symptomatic therapy, immunosuppressive drugs such as corticosteroids, azathioprine, and mycophenolate mofetil, and thymectomy, which is primarily indicated in patients with thymoma or thymic hyperplasia. However, this condition continues to pose significant challenges including an unpredictable and variable disease progression, differing response to individual therapies, and substantial longterm side effects associated with standard treatments(including an increased risk of infections, osteoporosis, and diabetes), underscoring the necessity for a more personalized approach to treatment. Furthermore, about fifteen percent of patients, called “refractory myasthenia gravis patients”, do not respond adequately to standard therapies. In this context, the introduction of molecular therapies has marked a significant advance in myasthenia gravis management. Advances in understanding myasthenia gravis pathogenesis, especially the role of pathogenic antibodies, have driven the development of these biological drugs, which offer more selective, rapid, and safer alternatives to traditional immunosuppressants. This review aims to provide a comprehensive overview of emerging therapeutic strategies targeting specific immune pathways in myasthenia gravis, with a particular focus on preclinical evidence, therapeutic rationale, and clinical translation of B-cell depletion therapies, neonatal Fc receptor inhibitors, and complement inhibitors.展开更多
Biological aging is a complex physiological process characterized by a decline in tissue function and the loss of cellular capabilities,which increase an individual's risk of various diseases[1].While genetic fact...Biological aging is a complex physiological process characterized by a decline in tissue function and the loss of cellular capabilities,which increase an individual's risk of various diseases[1].While genetic factors and lifestyle are key influences on biological aging,environmental factors also play a significant role.Given the rapid aging of the global population,elucidating the factors that influence biological aging is crucial for promoting healthy aging.展开更多
Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interact...Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.展开更多
Dengue virus(DENV)is a single-stranded RNA virus transmitted by mosquitoes in tropical and subtropical regions.It causes dengue fever,dengue hemorrhagic fever and dengue shock syndrome in patients.Each year,390 millio...Dengue virus(DENV)is a single-stranded RNA virus transmitted by mosquitoes in tropical and subtropical regions.It causes dengue fever,dengue hemorrhagic fever and dengue shock syndrome in patients.Each year,390 million people are estimated to be infected by four serotypes of dengue virus,creating a great burden on global public health and local economy.So far,no antiviral drug is available for dengue disease,and the newly licensed vaccine is far from satisfactory.One large obstacle for dengue vaccine and drug development is the lack of suitable small animal models.Although some DENV infection models have been developed,only a small number of viral strains can infect immunodeficient mice.In this study,with biologically cloned viruses from a single clinical isolate,we have established two mouse models of DENV infection,one is severe lethal infection in immunocompromised mice,and the other resembles self-limited disease manifestations in Balb/c mice with transient blockage of type I IFN responses.This study not only offers new small animal models of dengue viral infection,but also provides new viral variants for further investigations on dengue viral pathogenesis.展开更多
The collection and annotation of lar ge-scale bird datasets are resource-intensive and time-consuming processes that significantly limit the scalability and accuracy of biodiversity monitoring systems.While self-super...The collection and annotation of lar ge-scale bird datasets are resource-intensive and time-consuming processes that significantly limit the scalability and accuracy of biodiversity monitoring systems.While self-supervised learning(SSL)has emerged as a promising approach for leveraging unannotated data,current SSL methods face two critical challenges in bird species recognition:(1)long-tailed data distributions that result in poor performance on underrepresented species;and(2)domain shift issues caused by data augmentation strategies designed to mitigate class imbalance.Here we present SDNet,a novel SSL-based bird recognition framework that integrates diffusion models with large language models(LLMs)to overcome these limitations.SDNet employs LLMs to generate semantically rich textual descriptions for tail-class species by prompting the models with species taxonomy,morphological attributes,and habitat information,producing detailed natural language priors that capture fine-grained visual characteristics(e.g.,plumage patterns,body proportions,and distinctive markings).These textual descriptions are subsequently used by a conditional diffusion model to synthesize new bird image samples through cross-attention mechanisms that fuse textual embeddings with intermediate visual feature representations during the denoising process,ensuring generated images preserve species-specific morphological details while maintaining photorealistic quality.Additionally,we incorporate a Swin Transformer as the feature extraction backbone whose hierarchical window-based attention mechanism and shifted windowing scheme enable multi-scale local feature extraction that proves particularly effective at capturing finegrained discriminative patterns(such as beak shape and feather texture)while mitigating domain shift between synthetic and original images through consistent feature representations across both data sources.SDNet is validated on both a self-constructed dataset(Bird_BXS)an d a publicly available benchmark(Birds_25),demonstrating substantial improvements over conventional SSL approaches.Our results indicate that the synergistic integration of LLMs,diffusion models,and the Swin Transformer architecture contributes significantly to recognition accuracy,particularly for rare and morphologically similar species.These findings highlight the potential of SDNet for addressing fundamental limitations of existing SSL methods in avian recognition tasks and establishing a new paradigm for efficient self-supervised learning in large-scale ornithological vision applications.展开更多
This study evaluated the accuracy,completeness,and comprehensibility of responses from mainstream large language models(LLMs)to hepatitis C virus(HCV)-related questions,aiming to assess their performance in addressing...This study evaluated the accuracy,completeness,and comprehensibility of responses from mainstream large language models(LLMs)to hepatitis C virus(HCV)-related questions,aiming to assess their performance in addressing patient queries about disease and lifestyle behaviors.The models selected were ChatGPT-4o,Gemini 2.0 Pro,Claude 3.5 Sonnet,and DeepSeek V3,with 12 questions chosen by two HCV experts from the domains of prevention,diagnosis,and treatment.展开更多
Biological nitrogen fixation(BNF)and photosynthetic carbon fixation underpin food production and climate mitigation,yet natural systems are constrained by oxygen sensitivity,high energy demand,and inefficient catalyst...Biological nitrogen fixation(BNF)and photosynthetic carbon fixation underpin food production and climate mitigation,yet natural systems are constrained by oxygen sensitivity,high energy demand,and inefficient catalysts.This review synthesizes advances that recast these processes as engineering targets and proposes a conceptual roadmap that bridges synthetic symbioses with the synthetic biology of enzymes and pathways.For BNF,progress spans cross-kingdom strategies—from refactoring nif gene sets and targeting nitrogenase assembly to eukaryotic organelles,to engineering plant-associated diazotrophs,rhizosphere control circuits,and emerging nodule-like microenvironments.For carbon assimilation,new-to-nature CO_(2)-fixation modules and photorespiratory bypasses illustrate how pathway redesign and alternative carboxylases can circumvent key Calvin–Benson–Bassham limitations,and expanding photosynthetic light capture offers additional leverage.Across these domains,we extract common design principles:(i)nitrogenase output is increasingly governed by carbon/energy supply and electron delivery as much as by oxygen protection;(ii)robust function requires compartment-aware enzyme–chassis coordination,substrate channeling,and dynamic regulation using sensors and control circuits;and(iii)scalable implementation may benefit from distributing metabolic labor across engineered consortia rather than forcing all functions into a single host.We discuss enabling technologies—including AI-guided protein design and directed evolution,cell-free prototyping,chassis toolkits,and materials/bioelectrochemical interfaces—that can accelerate design–build–test–learn cycles and reduce barriers to deployment.Together,these insights define a path toward integrated nitrogen and carbon fixation systems for low-emission agriculture and biomanufacturing.展开更多
Gold nanoclusters(AuNCs)are ultrasmall(<2 nm)aggregates of gold atoms that exhibit discrete electronic states,size-dependent photoluminescence,and exceptional biocompatibility,making them ideal candidates for thera...Gold nanoclusters(AuNCs)are ultrasmall(<2 nm)aggregates of gold atoms that exhibit discrete electronic states,size-dependent photoluminescence,and exceptional biocompatibility,making them ideal candidates for theranostic applications.Their tunable surface chemistry enables targeted delivery,while strong near-infrared emission and environmental responsiveness allow for sensitive detection and deep-tissue imaging.Recent advances have revealed that controlled assembly of AuNCs into higher-order architectures-guided by biological scaffolds such as nucleic acids,peptides,and proteins-can markedly enhance their optical and electronic properties through aggregation-induced emission(AiE)and stabilization of surface ligands.This review summarizes recent progress in the design and biomedical applications of AuNC assemblies generated using biomolecules as structure-directing scaffolds.Covalent and noncovalent interactions with biomolecules enable the formation of well-defined one-,two-,and three-dimensional structures with tunable morphologies and sizes.These assemblies display distinctive photophysical behaviors that have been exploited for biosensing,bioimaging,and therapeutic applications in both cellular and in vivo models.Compared with individual AuNCs,assembled systems offer improved uptake,prolonged circulation,and efficient clearance,while protecting labile cargos such as nucleic acids and proteins.Moreover,their ordered and defined architectures can be engineered for controlled drug release and synergistic photo-or radiotherapeutic effects.Despite these advances,fundamental understanding of how structural organization governs photophysical responses remains limited.Elucidating parameters such as intercluster spacing and loading density will be essential for optimizing performance.Overall,biologically guided AuNC assemblies represent a powerful platform for multifunctional biosensing and therapy,bridging nanoscale design with biological function.展开更多
Panax notoginseng(P.notoginseng),a valuable traditional Chinese medicine,is the dried root of plants in Acanthopanax gracilistylus family,with the effect of dispersing blood stasis,eliminating swelling and relieving p...Panax notoginseng(P.notoginseng),a valuable traditional Chinese medicine,is the dried root of plants in Acanthopanax gracilistylus family,with the effect of dispersing blood stasis,eliminating swelling and relieving pain.With the development of modern medicine,the active ingredients and mechanisms of P.notoginseng have been gradually revealed.The present paper systematically reviews the chemical composition and biological activities of P.nologinseng,to provide a scientific basis and reference for detailed research on P.nologinseng.展开更多
Biological invasion is a pressing environmental and ecological challenge worldwide.Cabomba caroliniana(C.caroliniana),a submerged macrophyte native to South America,is listed as a high-priority invasive species in sev...Biological invasion is a pressing environmental and ecological challenge worldwide.Cabomba caroliniana(C.caroliniana),a submerged macrophyte native to South America,is listed as a high-priority invasive species in several countries.It is critical to understand how water temperature influences its invasiveness for effective management.However,research on the effects of water temperature on C.caroliniana the growth is limited.This study used controlled experiments to examine how water temperature(5-30℃)affects the morphological,physiological,photosynthetic,and stoichiometric traits of C.caroliniana.The results showed that broad water temperature tolerance of C.caroliniana significantly impacts its reproductive capacity and invasive potential.At 5-10℃,cold stress induced carotenoid synthesis and total organic carbon accumulation,enabling adaptation to low temperatures.However,C.caroliniana grew slowly,as its root development was limited,and its invasiveness remained low.At 20-30℃,increased chlorophyll synthesis and enhanced resource-use efficiency supported rapid growth,including more branches,leading to high invasion and dispersal potential.Thus,C.caroliniana exhibited strong colonization and spread quickly in tropical and subtropical waters(>20℃).In temperate zones,populations can be established during summer(20-25℃)and survive winter hrough cold adaptation.We recommended prioritizing control measures during warm seasons(20-30℃)to disrupt propagule dispersal,alongside early monitoring in temperate waters to inhibit ecological invasion.展开更多
The cold chain environment is an important route for the long⁃distance transmission of pathogenic micro⁃organisms.In this study,we explored the mechanisms of secondary propagation through surface contact on cold surfa...The cold chain environment is an important route for the long⁃distance transmission of pathogenic micro⁃organisms.In this study,we explored the mechanisms of secondary propagation through surface contact on cold surfaces.A quantitative statistical experimental method was adopted to study the surface⁃contact transmission of micro⁃organisms,wherein the transfer rate of surface contact was the dependent variable and Escherichia coli was used as the indicator bacterium.The effects of contact pressure(0.44,0.86,1.55,2.25,and 2.94 N/cm^(2)),contact time(0,15,30,45,and 60 s),contact angle(15°and 25°),and surface materials(rubber and cotton gloves)were measured at two storage temperatures:cold storage(5℃)and freezing(-18℃).The results showed that as temperature decreases,the transfer of micro⁃organisms through surface contact becomes less probable.The contact time did not significantly influence the transfer rate of micro⁃organisms when items were handled at cold⁃storage temperatures.Based on these results,we recommend placing items as flat as possible to minimize the tilt angle when handling them at cold⁃storage temperatures.Additionally,if the tilt angle cannot be avoided,rubber gloves should be used when handling items stored at large tilt angles,whereas cotton gloves may be used for items placed at smaller angles.展开更多
Legume-based intercropping enhances asymbiotic biological nitrogen fixation(BNF);however,the underlying mechanisms remain unclear,including the roles of soil keystone diazotroph taxa with varying niche breadths.A fiel...Legume-based intercropping enhances asymbiotic biological nitrogen fixation(BNF);however,the underlying mechanisms remain unclear,including the roles of soil keystone diazotroph taxa with varying niche breadths.A field experiment was conducted to evaluate soil BNF variations between rhizosphere and bulk soils in peanut/cotton intercropping systems and monocultures.BNF activities were measured by nitrogen fixation rates,nitrogenase activity,and nifH gene abundance.Phylogenetic null models,co-occurrence networks,and niche breadth analysis were applied to investigate the roles of diazotrophic keystone taxa and their ecological niches.Rhizosphere soils exhibited 7.8–125.5%higher BNF potentials than bulk soils,whereas intercropping systems showed 11.6–323.0%increases over monocultures for nitrogen fixation rate,nitrogenase activity,and nifH gene abundance(all P<0.05).Diazotrophic community composition and diversity differed significantly,with Proteobacteria(excluding Alphaproteobacteria)enriched in intercropping and rhizosphere soils,while Cyanobacteria and Firmicutes were less abundant.Deterministic processes,particularly heterogeneous selection,dominated community assembly in the rhizosphere(91.9%)and intercropping soils(86.3%).The co-occurrence networks consistently revealed more complex and interconnected communities in intercropping and rhizosphere soils that were dominated by opportunistic diazotrophs(78.8–85.9%),followed by specialists(10.2–18.5%)and generalists(1.38–3.80%).Keystone taxa,including opportunists such as Azoarcus,Azohydromonas,and Steroidobacter,and generalists like Pseudomonas and Azotobacter,correlated positively with microbial biomass carbon and nitrate nitrogen,contributing to enhanced BNF.Peanut/cotton intercropping enhances BNF by selectively enriching the keystone diazotrophic taxa with varying ecological roles,particularly opportunists and generalists.Such targeted intercropping strategies can optimize BNF,improve soil fertility,and promote sustainable agricultural production.展开更多
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd..(Grant No.H20230317)。
文摘Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Regression models and Neural network models,to perform multi-characteristic coupled displacement prediction because they fail to consider landslide creep characteristics.This paper integrates the creep characteristics of landslides with non-linear intelligent algorithms and proposes a dynamic intelligent landslide displacement prediction method based on a combination of the Biological Growth model(BG),Convolutional Neural Network(CNN),and Long ShortTerm Memory Network(LSTM).This prediction approach improves three different biological growth models,thereby effectively extracting landslide creep characteristic parameters.Simultaneously,it integrates external factors(rainfall and reservoir water level)to construct an internal and external comprehensive dataset for data augmentation,which is input into the improved CNN-LSTM model.Thereafter,harnessing the robust feature extraction capabilities and spatial translation invariance of CNN,the model autonomously captures short-term local fluctuation characteristics of landslide displacement,and combines LSTM's efficient handling of long-term nonlinear temporal data to improve prediction performance.An evaluation of the Liangshuijing landslide in the Three Gorges Reservoir Area indicates that BG-CNN-LSTM exhibits high prediction accuracy,excellent generalization capabilities when dealing with various types of landslides.The research provides an innovative approach to achieving the whole-process,realtime,high-precision displacement predictions for multicharacteristic coupled landslides.
基金supported by the National Natural Science Foundation of China(61801506)。
文摘Microwave radiation has been widely used in various fields,such as communication,industry,medical treatment,and military applications.Microwave radiation may cause injuries to both the structures and functions of various organs,such as the brain,heart,reproductive organs,and endocrine organs,which endanger human health.Therefore,it is both theoretically and clinically important to conduct studies on the biological effects induced by microwave radiation.The successful establishment of injury models is of great importance to the reliability and reproducibility of these studies.In this article,we review the microwave exposure conditions,subjects used to establish injury models,the methods used for the assessment of the injuries,and the indicators implemented to evaluate the success of injury model establishment in studies on biological effects induced by microwave radiation.
基金Acknowledgement This paper is supported by National Natural Science Foundation of China （Grant No. 60973092 and No. 60873146）, the National High Technology Research and Development Program of China （Grant No.2009 AA02Z307）, the ＂211 Project＂ of Jilin University, the Key Laboratory for Symbol Computation and Knowledge Engineering （Ministry of Education, China）, and the Key Laboratory for New Technology of Biological Recognition of Jilin Province （No. 20082209）.
文摘Inferring gene regulatory networks from large-scale expression data is an important topic in both cellular systems and computational biology. The inference of regulators might be the core factor for understanding actual regulatory conditions in gene regulatory networks, especially when strong regulators do work significantly. In this paper, we propose a novel approach based on combining neuro-fu^zy network models with biological knowledge to infer strong regulators and interrelated fuzzy rules. The hybrid neuro-fuzzy architecture can not only infer the fuzzy rules, which are suitable for describing the regulatory conditions in regulatory nctworks＋ but also explain the meaning of nodes and weight value in the neural network. It can get useful rules automatically without lhctitious judgments. At the same time, it does not add recursive layers to the model, and the model can also strengthen the relationships among genes and reduce calculation. We use the proposed approach to reconstruct a partial gene regulatory network of yeast, The results show that this approach can work effectively.
文摘[Objective]The aim was to establish the linear regression prediction models between sowing time and plant productivity, biological yield of forage sorghum in autumn idle land.[Method]The relationships between sowing time and plant productivity, biological yield of forage sorghum were simulated and compared by using field experiment and linear regression analysis.[Result] The sowing time had an important influence on the plant productivity and biological yield of forage sorghum in autumn idle land. The plant productivity and biological yield of forage sorghum both decreased with the delay of sowing time.The regression model between plant fresh weight and sowing time was ？fresh=0.618-0.015x; the regression model between plant dry weight and sowing time was ？dry=0.184-0.005x; and the regression model between biological yield and sowing time was yield=29 126.461-711.448x. During July 23rd to August 30th, when the sowing time was delayed by 1 day, the plant fresh weight of forage sorghum was reduced by 0.015 g, the plant dry weight was reduced by 0.005 g, and the yield was reduced by 711.448 kg/hm2. [Conclusion] The three regression models established in this study will provide theoretical support for the production of forage sorghum.
文摘This article considers three types of biological systems:the dengue fever disease model,the COVID-19 virus model,and the transmission of Tuberculosis model.The new technique of creating the integration matrix for the Bernoulli wavelets is applied.Also,the novel method proposed in this paper is called the Bernoulli wavelet collocation scheme(BWCM).All three models are in the form system of coupled ordinary differential equations without an exact solution.These systems are converted into a system of algebraic equations using the Bernoulli wavelet collocation scheme.The numerical wave distributions of these governing models are obtained by solving the algebraic equations via the Newton-Raphson method.The results obtained from the developed strategy are compared to several schemes such as the Runge Kutta method,and ND solver in mathematical software.The convergence analyses are discussed through theorems.The newly implemented Bernoulli wavelet method improves the accuracy and converges when it is compared with the existing methods in the literature.
文摘Background: Calotropis procera (C. procera), is an authentic plant naturally grown in the flora of Dead Sea region. Despite its toxicity, C. procera presents healing properties. However, it has not been implemented yet in cosmetics as an active ingredient. Objective: The biological effects of C. procera callus extract on skin were elucidated solely and in combination with Dead Sea water (DSW). Methods: The capability of C. procera extract to protect against skin inflammation and irritation was tested on ex vivo human skin organ culture by LPS and SDS addition respectively. Viability and cytokine secretion were evaluated. The combination of C. procera extract with Dead Sea water was tested on full thickness skin equivalents. Gene expression and relevant biochemical markers for glycolysis, hypoxia and extracellular matrix balance were tested. Results: C. procera extract exhibits a protective biological activity against skin irritation and inflammation at the biochemical level. Furthermore, a combination of C. procera extract and DSW demonstrates a potential contribution for skin wellbeing via enhance energy production, resistance to hypoxia and extracellular matrix balance. Conclusions: Topical application of C. procera callus extract might support skin balance and wellbeing at the molecular level. Hence, it is recommended for new cosmetic formulae as standalone or in combination with Dead Sea water, in the effort to achieve anti-aging bio-activity that is working beyond skin aging symptoms, especially via skin calming effects and skin energy enhancement.
基金theChinaScholarshipCouncil (CSC)andOceanographicScientificFundsforYouthfromtheStateOceanographicAdministration (No .96 80 1)
文摘The oil spill impact analysis (OSIA) software system has been developed to supply a tool for comprehensive, quantitative environmental impact assessments resulting from oil spills. In the system, a biological component evaluates potential effects on exposed organisms based on results from a physico chemical fates component, including the extent and characteristics of the surface slick, and dissolved and total concentrations of hydrocarbons in the water column. The component includes a particle based exposure model for migratory adult fish populations, a particle based exposure model for spawning planktonic organisms (eggs and larvae), and an exposure model for wildlife species (sea birds or marine mammals). The exposure model for migratory adult fish populations simulates the migration behaviors of fish populations migrating to or staying in their feeding areas, over wintering areas or spawning areas, and determines the acute effects (mortality) and chronic accumulation (body burdens) from the dissolved contaminant. The exposure model for spawning planktonic organisms simulates the release of eggs and larvae, also as particles, from specific spawning areas during the spawning period, and determines their potential exposure to contaminants in the water or sediment. The exposure model for wild species calculates the exposure to surface oil of wildlife (bird and marine mammal) categories inhabiting the contaminated area. Compared with the earlier models in which all kinds of organisms are assumed evenly and randomly distributed, the updated biological exposure models can more realistically estimate potential effects on marine ecological system from oil spill pollution events.
基金supported by grants from the National Natural Science Foundation of China(81471736 and 81671760)the National Science and Technology Pillar Program during the Twelfth Five-Year Plan Period(2015BAI01B09)Project of Research Foundation of the Talent of Scientific and Technical Innovation of Harbin City(2016RAXYJ063)
文摘Background: Positron emission tomography(PET) is a noninvasive method to characterize different metabolic activities of tumors, providing information for staging, prognosis, and therapeutic response of patients with cancer. The aim of this study was to evaluate the feasibility of18F-fludeoxyglucose(18F-FDG) and 3’-deoxy-3’-18F-fluorothymidine(18F-FLT) PET in predicting tumor biological characteristics of colorectal cancer liver metastasis.Methods: The uptake rate of18F-FDG and18F-FLT in SW480 and SW620 cells was measured via an in vitro cell uptake assay. The region of interest was drawn over the tumor and liver to calculate the maximum standardized uptake value ratio(tumor/liver) from PET images in liver metastasis model. The correlation between tracer uptake in liver metastases and VEGF, Ki67 and CD44 expression was evaluated by linear regression.Results: Compared to SW620 tumor-bearing mice, SW480 tumor-bearing mice presented a higher rate of liver metastases. The uptake rate of18F-FDG in SW480 and SW620 cells was 6.07% ± 1.19% and2.82% ± 0.15%, respectively(t = 4.69, P = 0.04); that of18F-FLT was 24.81% ± 0.45% and 15.57% ± 0.66%, respectively(t = 19.99, P < 0.001). Micro-PET scan showed that all parameters of FLT were significantly higher in SW480 tumors than those in SW620 tumors. A moderate relationship was detected between metastases in the liver and18F-FLT uptake in primary tumors(r = 0.73, P = 0.0019).18F-FLT uptake was also positively correlated with the expression of CD44 in liver metastases(r = 0.81, P = 0.0049).Conclusions: The uptake of18F-FLT in metastatic tumor reflects different biological behaviors of colon cancer cells.18F-FLT can be used to evaluate the metastatic potential of colorectal cancer in nude mice.
文摘Myasthenia gravis is a chronic autoimmune disorder that affects the neuromuscular junction leading to fluctuating skeletal muscle fatigability. The majority of myasthenia gravis patients have detectable antibodies in their serum, targeting acetylcholine receptor, muscle-specific kinase, or related proteins. Current treatment for myasthenia gravis involves symptomatic therapy, immunosuppressive drugs such as corticosteroids, azathioprine, and mycophenolate mofetil, and thymectomy, which is primarily indicated in patients with thymoma or thymic hyperplasia. However, this condition continues to pose significant challenges including an unpredictable and variable disease progression, differing response to individual therapies, and substantial longterm side effects associated with standard treatments(including an increased risk of infections, osteoporosis, and diabetes), underscoring the necessity for a more personalized approach to treatment. Furthermore, about fifteen percent of patients, called “refractory myasthenia gravis patients”, do not respond adequately to standard therapies. In this context, the introduction of molecular therapies has marked a significant advance in myasthenia gravis management. Advances in understanding myasthenia gravis pathogenesis, especially the role of pathogenic antibodies, have driven the development of these biological drugs, which offer more selective, rapid, and safer alternatives to traditional immunosuppressants. This review aims to provide a comprehensive overview of emerging therapeutic strategies targeting specific immune pathways in myasthenia gravis, with a particular focus on preclinical evidence, therapeutic rationale, and clinical translation of B-cell depletion therapies, neonatal Fc receptor inhibitors, and complement inhibitors.
基金support from the Shenzhen Science and Technology program(grant number 202208183000115)。
文摘Biological aging is a complex physiological process characterized by a decline in tissue function and the loss of cellular capabilities,which increase an individual's risk of various diseases[1].While genetic factors and lifestyle are key influences on biological aging,environmental factors also play a significant role.Given the rapid aging of the global population,elucidating the factors that influence biological aging is crucial for promoting healthy aging.
基金supported by the National Key R&D Program of China[2022YFF0902703]the State Administration for Market Regulation Science and Technology Plan Project(2024MK033).
文摘Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.
基金supported in part by Science and Technology Commission of Shanghai Municipality(Grant No.19ZR1462900)the National Science Foundation of China(Grant No.31300757)the National Science Foundation of China(Grant No.31870916 and No.31670941)
文摘Dengue virus(DENV)is a single-stranded RNA virus transmitted by mosquitoes in tropical and subtropical regions.It causes dengue fever,dengue hemorrhagic fever and dengue shock syndrome in patients.Each year,390 million people are estimated to be infected by four serotypes of dengue virus,creating a great burden on global public health and local economy.So far,no antiviral drug is available for dengue disease,and the newly licensed vaccine is far from satisfactory.One large obstacle for dengue vaccine and drug development is the lack of suitable small animal models.Although some DENV infection models have been developed,only a small number of viral strains can infect immunodeficient mice.In this study,with biologically cloned viruses from a single clinical isolate,we have established two mouse models of DENV infection,one is severe lethal infection in immunocompromised mice,and the other resembles self-limited disease manifestations in Balb/c mice with transient blockage of type I IFN responses.This study not only offers new small animal models of dengue viral infection,but also provides new viral variants for further investigations on dengue viral pathogenesis.
基金supported by the National Natural Science Foundation of China(32471964)。
文摘The collection and annotation of lar ge-scale bird datasets are resource-intensive and time-consuming processes that significantly limit the scalability and accuracy of biodiversity monitoring systems.While self-supervised learning(SSL)has emerged as a promising approach for leveraging unannotated data,current SSL methods face two critical challenges in bird species recognition:(1)long-tailed data distributions that result in poor performance on underrepresented species;and(2)domain shift issues caused by data augmentation strategies designed to mitigate class imbalance.Here we present SDNet,a novel SSL-based bird recognition framework that integrates diffusion models with large language models(LLMs)to overcome these limitations.SDNet employs LLMs to generate semantically rich textual descriptions for tail-class species by prompting the models with species taxonomy,morphological attributes,and habitat information,producing detailed natural language priors that capture fine-grained visual characteristics(e.g.,plumage patterns,body proportions,and distinctive markings).These textual descriptions are subsequently used by a conditional diffusion model to synthesize new bird image samples through cross-attention mechanisms that fuse textual embeddings with intermediate visual feature representations during the denoising process,ensuring generated images preserve species-specific morphological details while maintaining photorealistic quality.Additionally,we incorporate a Swin Transformer as the feature extraction backbone whose hierarchical window-based attention mechanism and shifted windowing scheme enable multi-scale local feature extraction that proves particularly effective at capturing finegrained discriminative patterns(such as beak shape and feather texture)while mitigating domain shift between synthetic and original images through consistent feature representations across both data sources.SDNet is validated on both a self-constructed dataset(Bird_BXS)an d a publicly available benchmark(Birds_25),demonstrating substantial improvements over conventional SSL approaches.Our results indicate that the synergistic integration of LLMs,diffusion models,and the Swin Transformer architecture contributes significantly to recognition accuracy,particularly for rare and morphologically similar species.These findings highlight the potential of SDNet for addressing fundamental limitations of existing SSL methods in avian recognition tasks and establishing a new paradigm for efficient self-supervised learning in large-scale ornithological vision applications.
基金funded by the National Key Research and Development Program of China(No.2021YFA1100500)the National Natural Science Foundation of China(No.82370662)the Key Research&Development Plan of Zhejiang Province(No.2024C03051).
文摘This study evaluated the accuracy,completeness,and comprehensibility of responses from mainstream large language models(LLMs)to hepatitis C virus(HCV)-related questions,aiming to assess their performance in addressing patient queries about disease and lifestyle behaviors.The models selected were ChatGPT-4o,Gemini 2.0 Pro,Claude 3.5 Sonnet,and DeepSeek V3,with 12 questions chosen by two HCV experts from the domains of prevention,diagnosis,and treatment.
基金supported by the funds of the Ministry of Science and Technology of China(2019YFA0904700)the National Natural Science Foundation of China(32471477)to Cheng Qi.
文摘Biological nitrogen fixation(BNF)and photosynthetic carbon fixation underpin food production and climate mitigation,yet natural systems are constrained by oxygen sensitivity,high energy demand,and inefficient catalysts.This review synthesizes advances that recast these processes as engineering targets and proposes a conceptual roadmap that bridges synthetic symbioses with the synthetic biology of enzymes and pathways.For BNF,progress spans cross-kingdom strategies—from refactoring nif gene sets and targeting nitrogenase assembly to eukaryotic organelles,to engineering plant-associated diazotrophs,rhizosphere control circuits,and emerging nodule-like microenvironments.For carbon assimilation,new-to-nature CO_(2)-fixation modules and photorespiratory bypasses illustrate how pathway redesign and alternative carboxylases can circumvent key Calvin–Benson–Bassham limitations,and expanding photosynthetic light capture offers additional leverage.Across these domains,we extract common design principles:(i)nitrogenase output is increasingly governed by carbon/energy supply and electron delivery as much as by oxygen protection;(ii)robust function requires compartment-aware enzyme–chassis coordination,substrate channeling,and dynamic regulation using sensors and control circuits;and(iii)scalable implementation may benefit from distributing metabolic labor across engineered consortia rather than forcing all functions into a single host.We discuss enabling technologies—including AI-guided protein design and directed evolution,cell-free prototyping,chassis toolkits,and materials/bioelectrochemical interfaces—that can accelerate design–build–test–learn cycles and reduce barriers to deployment.Together,these insights define a path toward integrated nitrogen and carbon fixation systems for low-emission agriculture and biomanufacturing.
基金NR SEQUOIA(ANR-22-CE18-0006)Nan0Gold(ANR-22-CE29-0022)+3 种基金SAMURAI(ANR-24-CE19-2073-01)Wilive(ANR-24-CE09-2351-03)EUR CBH-EUR-GS(ANR-17-EURE 0003)for their financial supportthe French National Research Agency(Labex ARCANE,ANR-11-LABX-003 and CBH-EUR-GS,ANR-17-EURE-0003)that supported part of this study.
文摘Gold nanoclusters(AuNCs)are ultrasmall(<2 nm)aggregates of gold atoms that exhibit discrete electronic states,size-dependent photoluminescence,and exceptional biocompatibility,making them ideal candidates for theranostic applications.Their tunable surface chemistry enables targeted delivery,while strong near-infrared emission and environmental responsiveness allow for sensitive detection and deep-tissue imaging.Recent advances have revealed that controlled assembly of AuNCs into higher-order architectures-guided by biological scaffolds such as nucleic acids,peptides,and proteins-can markedly enhance their optical and electronic properties through aggregation-induced emission(AiE)and stabilization of surface ligands.This review summarizes recent progress in the design and biomedical applications of AuNC assemblies generated using biomolecules as structure-directing scaffolds.Covalent and noncovalent interactions with biomolecules enable the formation of well-defined one-,two-,and three-dimensional structures with tunable morphologies and sizes.These assemblies display distinctive photophysical behaviors that have been exploited for biosensing,bioimaging,and therapeutic applications in both cellular and in vivo models.Compared with individual AuNCs,assembled systems offer improved uptake,prolonged circulation,and efficient clearance,while protecting labile cargos such as nucleic acids and proteins.Moreover,their ordered and defined architectures can be engineered for controlled drug release and synergistic photo-or radiotherapeutic effects.Despite these advances,fundamental understanding of how structural organization governs photophysical responses remains limited.Elucidating parameters such as intercluster spacing and loading density will be essential for optimizing performance.Overall,biologically guided AuNC assemblies represent a powerful platform for multifunctional biosensing and therapy,bridging nanoscale design with biological function.
文摘Panax notoginseng(P.notoginseng),a valuable traditional Chinese medicine,is the dried root of plants in Acanthopanax gracilistylus family,with the effect of dispersing blood stasis,eliminating swelling and relieving pain.With the development of modern medicine,the active ingredients and mechanisms of P.notoginseng have been gradually revealed.The present paper systematically reviews the chemical composition and biological activities of P.nologinseng,to provide a scientific basis and reference for detailed research on P.nologinseng.
基金funded by the Open Project Funding of Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes,Ministry of Education,Hubei University of Technology(HGKFYBP03)the Open Foundation of Resource-exhausted City Transformation and Development Research Center(Hubei Normal University)(KF2024Y07)the College Students'Innovative Entrepreneurial Training Plan Program(S202410513099,202410513009).
文摘Biological invasion is a pressing environmental and ecological challenge worldwide.Cabomba caroliniana(C.caroliniana),a submerged macrophyte native to South America,is listed as a high-priority invasive species in several countries.It is critical to understand how water temperature influences its invasiveness for effective management.However,research on the effects of water temperature on C.caroliniana the growth is limited.This study used controlled experiments to examine how water temperature(5-30℃)affects the morphological,physiological,photosynthetic,and stoichiometric traits of C.caroliniana.The results showed that broad water temperature tolerance of C.caroliniana significantly impacts its reproductive capacity and invasive potential.At 5-10℃,cold stress induced carotenoid synthesis and total organic carbon accumulation,enabling adaptation to low temperatures.However,C.caroliniana grew slowly,as its root development was limited,and its invasiveness remained low.At 20-30℃,increased chlorophyll synthesis and enhanced resource-use efficiency supported rapid growth,including more branches,leading to high invasion and dispersal potential.Thus,C.caroliniana exhibited strong colonization and spread quickly in tropical and subtropical waters(>20℃).In temperate zones,populations can be established during summer(20-25℃)and survive winter hrough cold adaptation.We recommended prioritizing control measures during warm seasons(20-30℃)to disrupt propagule dispersal,alongside early monitoring in temperate waters to inhibit ecological invasion.
基金National Natural Science Foundation of China(Grant No.52278121).
文摘The cold chain environment is an important route for the long⁃distance transmission of pathogenic micro⁃organisms.In this study,we explored the mechanisms of secondary propagation through surface contact on cold surfaces.A quantitative statistical experimental method was adopted to study the surface⁃contact transmission of micro⁃organisms,wherein the transfer rate of surface contact was the dependent variable and Escherichia coli was used as the indicator bacterium.The effects of contact pressure(0.44,0.86,1.55,2.25,and 2.94 N/cm^(2)),contact time(0,15,30,45,and 60 s),contact angle(15°and 25°),and surface materials(rubber and cotton gloves)were measured at two storage temperatures:cold storage(5℃)and freezing(-18℃).The results showed that as temperature decreases,the transfer of micro⁃organisms through surface contact becomes less probable.The contact time did not significantly influence the transfer rate of micro⁃organisms when items were handled at cold⁃storage temperatures.Based on these results,we recommend placing items as flat as possible to minimize the tilt angle when handling them at cold⁃storage temperatures.Additionally,if the tilt angle cannot be avoided,rubber gloves should be used when handling items stored at large tilt angles,whereas cotton gloves may be used for items placed at smaller angles.
基金financially supported by the National Natural Science Foundation of China(32301962 and 31901127)the China Postdoctoral Science Foundation(2024M752947)+2 种基金the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(GZC20232437)the State Key Laboratory of Cotton Bio-breeding and Integrated Utilization Open Fund,China(CB2023C02)the Natural Science Foundation of Henan Province,China(252300420222)。
文摘Legume-based intercropping enhances asymbiotic biological nitrogen fixation(BNF);however,the underlying mechanisms remain unclear,including the roles of soil keystone diazotroph taxa with varying niche breadths.A field experiment was conducted to evaluate soil BNF variations between rhizosphere and bulk soils in peanut/cotton intercropping systems and monocultures.BNF activities were measured by nitrogen fixation rates,nitrogenase activity,and nifH gene abundance.Phylogenetic null models,co-occurrence networks,and niche breadth analysis were applied to investigate the roles of diazotrophic keystone taxa and their ecological niches.Rhizosphere soils exhibited 7.8–125.5%higher BNF potentials than bulk soils,whereas intercropping systems showed 11.6–323.0%increases over monocultures for nitrogen fixation rate,nitrogenase activity,and nifH gene abundance(all P<0.05).Diazotrophic community composition and diversity differed significantly,with Proteobacteria(excluding Alphaproteobacteria)enriched in intercropping and rhizosphere soils,while Cyanobacteria and Firmicutes were less abundant.Deterministic processes,particularly heterogeneous selection,dominated community assembly in the rhizosphere(91.9%)and intercropping soils(86.3%).The co-occurrence networks consistently revealed more complex and interconnected communities in intercropping and rhizosphere soils that were dominated by opportunistic diazotrophs(78.8–85.9%),followed by specialists(10.2–18.5%)and generalists(1.38–3.80%).Keystone taxa,including opportunists such as Azoarcus,Azohydromonas,and Steroidobacter,and generalists like Pseudomonas and Azotobacter,correlated positively with microbial biomass carbon and nitrate nitrogen,contributing to enhanced BNF.Peanut/cotton intercropping enhances BNF by selectively enriching the keystone diazotrophic taxa with varying ecological roles,particularly opportunists and generalists.Such targeted intercropping strategies can optimize BNF,improve soil fertility,and promote sustainable agricultural production.
