A perspective review on the biosynthesis of plant-based secondary metabolites and their application as potent drugs

Many phytochemicals and their derived metabolites produced by plants are extensively employed in commercial goods,pharmaceutical products as well as in the environmental and medicalfields.However,these secondary metabolites obtained from plants are in low amounts,and it is difficult to synthesize them at the industrial level.Despite these challenges,they may be utilized for a variety of medicinal products that are either available in the market or are being researched and tested.Secondary metabolites are complex compounds that exhibit chirality.Further,under controlled conditions with elicitors,desired secondary metabolites may be produced from plant cell cultures.This review emphasizes the various aspects of secondary metabolites including their types,synthesis,and applications as medicinal products.The article aims to promote the use of plant secondary metabolites in the management and treatment of various diseases.

Adulteration detection of plant protein beverages by UPLC-MS/MS based on signature peptide of allergen

Plant protein beverage adulteration occurs frequently,which may cause health problems for consumers due to the hidden allergens.Hence,a novel method was developed for authentication by ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS).Almond,peanut,walnut and soybean were hydrolyzed,followed by separation by NanoLC-Triple TOF MS.The obtained fingerprints were identified by ProteinPilotTM combined with Uniprot,and 16 signature peptides were selected.Afterwards,plant protein beverages treated by trypsin hydrolysis were analyzed with UPLC-MS/MS.This method showed a good linear relationship with R2>0.99403.The limit of quantification(LOQ)were 0.015,0.01,0.5 and 0.05 g/L for almond,peanut,walnut and soybean,respectively.Mean recoveries ranged from 84.77%to 110.44%with RSDs<15%.The developed method was successfully applied to the adulteration detection of 31 plant protein beverages to reveal adulteration and false labeling.Conclusively,this method could provide technical support for authentication of plant protein beverages to protect the rights and health of consumers.

Estimating Key Phenological Dates of Multiple Rice Accessions Using Unmanned Aerial Vehicle-Based Plant Height Dynamics for Breeding

Efficient and high-quality estimation of key phenological dates in rice is of great significance in breeding work. Plant height(PH) dynamics are valuable for estimating phenological dates. However, research on estimating the key phenological dates of multiple rice accessions based on PH dynamics has been limited. In 2022, field traits were collected using unmanned aerial vehicle(UAV)-based images across 435 plots, including 364 rice varieties. PH, dates of initial heading(IH) and full heading(FH), and panicle initiation(PI), and growth period after transplanting(GPAT) were collected during the rice growth stage. PHs were extracted using a digital surface model(DSM) and fitted using Fourier and logistic models. Machine learning algorithms, including multiple linear regression, random forest(RF), support vector regression, least absolute shrinkage and selection operator, and elastic net regression, were employed to estimate phenological dates. Results indicated that the optimal percentile of the DSM for extracting rice PH was the 95th(R^(2) = 0.934, RMSE = 0.056 m). The Fourier model provided a better fit for PH dynamics compared with the logistic models. Additionally, curve features(CF) and GPAT were significantly associated with PI, IH, and FH. The combination of CF and GPAT outperformed the use of CF alone, with RF demonstrating the best performance among the algorithms. Specifically, the combination of CF extracted from the logistic models, GPAT, and RF yielded the best performance for estimating PI(R^(2) = 0.834, RMSE = 4.344 d), IH(R^(2) = 0.877, RMSE = 2.721 d), and FH(R^(2) = 0.883, RMSE = 2.694 d). Overall, UAV-based rice PH dynamics combined with machine learning effectively estimated the key phenological dates of multiple rice accessions, providing a novel approach for investigating key phenological dates in breeding work.

Production and Characterization of a Composite Based on Plaster and Juncus Maritimus Plant Fibers

Nowadays,materials with a limited impact on the environment are required in the construction sector.Considering the interesting properties of natural elements such as natural fibers,it seems advantageous to use them to reinforce materials while protecting the environment and guaranteeing economic gain.Along these lines,this research was devoted to studying the effect of untreated natural fibers extracted from the Juncus maritimus plant(from Southern Morocco)on plaster.First,the effect of the percentage of added fibers on the fluidity of the plaster was evaluated by means of the Marsh’s cone method,that is,by measuring the time taken by a known volume of plaster to flow from a cone through a short tube.Then,the highly porous microstructure of the plaster was observed using a scanning electron microscope(SEM).The diffractogram of Juncus maritimus fibers was built by means of a X-ray diffraction(XRD)method.The values obtained for the wet thermal conductivity of the composites decreased from 0.4853 W/m.K for the reference specimen to 0.4324 W/m K for a fiber volume content of 40%.The densities were calculated to determine the lightness of each composite.The mechanical strengths[flexural and compressive]were evaluated for different percentages of rush fibers.The addition of 20%volume fiber was found to improve the flexural strength to 3.63 MPa compared to the sample without fiber(3.36 MPa),thereby ensuring good toughness of the considered material.Nevertheless,a reduction in compressive strength was observed,due to the poor adhesion between the fibers and the plaster matrix.

The meat of the matter: plant-based meat analogue versus traditional meat product nutritional quality

Plant-based meat analogues(PBMA)are formulated to mimic the sensory characteristics of traditional meat products(TMP)using vegetarian ingredients and are increasingly popular with the trend towards plantbased diets,even among meat-eating consumers.This narrative review compared the nutritional quality of PBMA and TMP to broaden the discussion on the suitability of simulated meat products to substitute TMP,while exploring other attributes for their comparison.The complexity of PBMA and TMP means they are not entirely interchangeable.Importantly,PBMA health effects extend beyond their basic nutrient content and quality.Postprandial metabolism and satiety,for example,can be affected by product formulation,ingredient interactions,and thermomechanical processing involved in producing organoleptically acceptable PBMA.There are specific opportunities for low-sodium PBMA products to contribute to a healthy shift toward plantbased diets.In conclusion,PBMA cannot be assumed to be healthier than TMP.They should be designed with comprehensive consideration of composition and processing to ensure they support consumers who are adopting plant-based diets in realizing the theoretical health benefits.

Dominant woody plant species recognition with a hierarchical model based on multimodal geospatial data for subtropical forests

Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.

Cloud-Model-Based Feature Engineering to Analyze the Energy-Water Nexus of a Full-Scale Wastewater Treatment Plant

Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutrality.However,water-energy nexus analysis and models for WWTPs have rarely been reported to date.In this study,a cloud-model-based energy consumption analysis(CMECA)of a WWTP was conducted to explore the relationship between influent and energy consumption by clustering its influent’s parameters.The principal component analysis(PCA)and K-means clustering were applied to classify the influent condition using water quality and volume data.The energy consumption of the WWTP is divided into five standard evaluation levels,and its cloud digital characteristics(CDCs)were extracted according to bilateral constraints and golden ratio methods.Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity.The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption,represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption.The local WWTP has high energy consumption with 0.3613 kW·h·m^(-3)despite low influent concentration and volumes,across four consumption levels from low(I)to relatively high(IV),showing an unsatisfactory operation and management level.The average oxygenation capacity,internal reflux ratio,and external reflux ratio during high energy efficiency days recognized by further clustering were obtained(0.2924-0.3703 kg O_(2)·m^(-3),1.9576-2.4787,and 0.6603-0.8361,respectively),which could be used as a guide for the days with low energy efficiency.Consequently,this study offers a water-energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.

Comparative Study of Solar PV Power Plant Dimensionnement Connected to Network Based on Monofacial and Bifacial Modules

This article presents the results of comparative study of two PV solar modules technologies,namely monofacial and bifacial.This study main objective is to identify conditions and parameters that make it possible to obtain better energy and economic efficiency from one or other of two technologies.The study reason lies in revival observed on bifacial module in recent years where all the major manufacturers of PV solar panels are developing them where in a few years,this technology risks being at the same price as the monofacial solar panel with better efficiency.Economic indicator used is energy levelized cost(LCOE)which is function technology type,energy productivity,annual investment and operation cost.To achieve this,a 3.685 MWc solar PV power plant was dimensioned and simulated under Matlab for a 3.5 ha site with a 2,320,740,602 FCFA budget for monofacial installation,against 1,925,188,640 FCFA for 2.73 MWc bifacial installation.The LCOE comparative analysis of two technologies calculated over a period of 25 years,showed that plant with bifacial panels is more beneficial if bifacial gain is greater than 9%.It has further been found that it is possible to gain up to 40%of invested cost if bifacial gain reaches 45%.Finally,a loss of about 10%of invested cost could be recorded if bifacial gain is less than 9%.

Plant-based vaccines against viral hepatitis: A panoptic review

The traditional vaccines against hepatitis have been instrumental in reducing the incidence of some types of viral hepatitis;however,the need for cost-effective,easily distributable,and needle-free vaccine alternatives has led to the exploration of plant-based vaccines.Plant-based techniques offer a promising avenue for producing viral hepatitis vaccines due to their low-cost cultivation,scalability,and the potential for oral administration.This review highlights the successful expression of hepatitis B surface antigens in plants and the subsequent formation of virus-like particles,which have shown immunogenicity in preclinical and clinical trials.The challenges such as achieving sufficient antigen expression levels,ensuring consistent dosing,and navigating regulatory frameworks,are addressed.The review considers the potential of plant-based vaccines to meet the demands of rapid vaccine deployment in response to outbreaks and their role in global immunization strategies,particularly in resource-limited settings.This review underscores the significant strides made in plant molecular farming and the potential of plant-based vaccines to complement existing immunization methods against viral hepatitis.

Biomaterials-based anti-inflammatory treatment strategies for Alzheimer's disease

The current therapeutic drugs for Alzheimer's disease only improve symptoms,they do not delay disease progression.Therefo re,there is an urgent need for new effective drugs.The underlying pathogenic factors of Alzheimer's disease are not clear,but neuroinflammation can link various hypotheses of Alzheimer's disease;hence,targeting neuroinflammation may be a new hope for Alzheimer's disease treatment.Inhibiting inflammation can restore neuronal function,promote neuro regeneration,reduce the pathological burden of Alzheimer's disease,and improve or even reverse symptoms of Alzheimer's disease.This review focuses on the relationship between inflammation and various pathological hypotheses of Alzheimer's disease;reports the mechanisms and characteristics of small-molecule drugs(e.g.,nonsteroidal anti-inflammatory drugs,neurosteroids,and plant extracts);macromolecule drugs(e.g.,peptides,proteins,and gene therapeutics);and nanocarriers(e.g.,lipid-based nanoparticles,polymeric nanoparticles,nanoemulsions,and inorganic nanoparticles)in the treatment of Alzheimer's disease.The review also makes recommendations for the prospective development of anti-inflammatory strategies based on nanocarriers for the treatment of Alzheimer's disease.

Influence of external nitrogen-containing donors on polymerization behavior of neodymium-based cis-1,4-polybutadiene rubber

Neodymium(Nd)-based catalyst in butadiene(Bd)polymerization has drawn interests due to its availability in affording higher cis-1,4-unit selectivity than transition metal(Ti,Co,Ni,etc.)-based catalysts[1-2].Such outstanding high cis-1,4-unit selecti-vity is hypothetically originated from the presence of 4 f orbitals,that can participate in monomer coordination and thereby govern subsequent enchainment manners.This unique characteristic also renders the active species highly susceptible to Lewis bases,and may impact the overall selectivity as well as polyme-rization behavior after coordination.Nevertheless,it is still a virgin area in such a field,and the influence of Lewis bases on Nd-based diene polymerizations is still a black box.Based on this consideration,how nitrogen-containing donors(D)impacts the overall behaviors of Nd-mediated Bd polymerizations is disclosed.

Source localization based on field signatures:Laboratory ultrasonic validation

Location awareness in wireless networks is essential for emergency services,navigation,gaming,and many other applications.This article presents a method for source localization based on measuring the amplitude-phase distribution of the field at the base station.The existing scatterers in the target area create unique scattered field interference at each source location.The unique field interference at each source location results in a unique field signature at the base station which is used for source localization.In the proposed method,the target area is divided into a grid with a step of less than half the wavelength.Each grid node is characterized by its field signature at the base station.Field signatures corresponding to all nodes are normalized and stored in the base station as fingerprints for source localization.The normalization of the field signatures avoids the need for time synchronization between the base station and the source.When a source transmits signals,the generated field signature at the base station is normalized and then correlated with the stored fingerprints.The maximum correlation value is given by the node to which the source is the closest.Numerical simulations and results of experiments on ultrasonic waves in the air show that the ultrasonic source is correctly localized using broadband field signatures with one base station and without time synchronization.The proposed method is potentially applicable for indoor localization and navigation of mobile robots.

Flexible,thermal processable,self-healing,and fully bio-based starch plastics by constructing dynamic imine network

The serious environmental threat caused by petroleum-based plastics has spurred more researches in developing substitutes from renewable sources.Starch is desirable for fabricating bioplastic due to its abundance and renewable nature.However,limitations such as brittleness,hydrophilicity,and thermal properties restrict its widespread application.To overcome these issues,covalent adaptable network was constructed to fabricate a fully bio-based starch plastic with multiple advantages via Schiff base reactions.This strategy endowed starch plastic with excellent thermal processability,as evidenced by a low glass transition temperature(T_(g)=20.15℃).Through introducing Priamine with long carbon chains,the starch plastic demonstrated superior flexibility(elongation at break=45.2%)and waterproof capability(water contact angle=109.2°).Besides,it possessed a good thermal stability and self-adaptability,as well as solvent resistance and chemical degradability.This work provides a promising method to fabricate fully bio-based plastics as alternative to petroleum-based plastics.

Role of micro-Ca/In alloying in tailoring the microstructural characteristics and discharge performance of dilute Mg-Bi-Sn-based alloys as anodes for Mg-air batteries

The influence of micro-Ca/In alloying on the microstructural charac teristics,electrochemical behaviors and discharge properties of extruded dilute Mg-0.5Bi-0.5Sn-based(wt.%)alloys as anodes for Mg-air batteries are evaluated.The grain size and texture intensity of the Mg-Bi-Sn-based alloys are significantly decreased after the Ca/In alloying,particularly for the In-containing alloy.Note that,in addition to nanoscale Mg_(3)Bi_(2)phase,a new microscale Mg_(2)Bi_(2)Ca phase forms in the Ca-containing alloy.The electrochemical test results demonstrate that Ca/In micro-alloying can enhance the electrochemical activity.Using In to alloy the Mg-Bi-Sn-based alloy is effective in restricting the cathodic hydrogen evolution(CHE)kinetics,leading to a low self-corrosion rate,while severe CHE occurred after Ca alloying.The micro-alloying of Ca/In to Mg-Bi-Sn-based alloy strongly deteriorates the compactness of discharge products film and mitigates the"chunk effect"(CE),hence the cell voltage,anodic efficiency as well as discharge capacity are greatly improved.The In-containing alloy exhibits outstanding discharge performance under the combined effect of the modified microstructure and discharge products,thus making it a potential anode material for primary Mg-air battery.

Construction of coal pitch-based HA-K grafted poly condensates and their excellent anti-temperature and viscosity-reducing properties

Humic acids(HAs)are widely used as filtrate and viscosity reducers in drilling fluids.However,their practical utility is limited due to poor stability in salt resistance and high-temperature resistance.Hightemperature coal pitch(CP)is a by-product from coal pyrolysis above 650℃.The substance's molecular structure is characterized by a dense arrangement of aromatic hydrocarbon and alkyl substituents.This unique structure gives it unique chemical properties and excellent drilling performance,surpassing traditional humic acids in drilling operations.Potassium humate is prepared from CP(CP-HA-K)by thermal catalysis.A new type of high-quality humic acid temperature-resistant viscosity-reducer(Graft CP-HA-K polymer)is synthesized with CP-HA-K,hydrolyzed polyacrylonitrile sodium salt(Na-HPAN),urea,formaldehyde,phenol and acrylamide(AAM)as raw materials.The experimental results demonstrate that the most favorable conditions for the catalytic preparation of CP-HA-K are 1 wt%catalyst dosage,30 wt%KOH dosage,a reaction temperature of 250℃,and a reaction time of 2 h,resulting in a maximum yield of CP-HA-K of 39.58%.The temperature resistance of the Graft CP-HA-K polymer is measured to be 177.39℃,which is 55.39℃ higher than that of commercial HA-K.This is due to the abundant presence of amide,hydroxyl,and amine functional groups in the Graft CP-HA-K polymer,which increase the length of the carbon chains,enhance the electrostatic repulsion on the surface of solid particles.After being aged to 120℃ for a specified duration,the Graft CP-HA-K polymer demonstrates significantly higher viscosity reduction(42.12%)compared to commercial HA-K(C-HA-K).Furthermore,the Graft CP-HA-K polymer can tolerate a high salt concentration of 8000 mg.L-1,measured after the addition of optimum amount of 3 wt%Graft CP-HA-K polymer.The action mechanism of Graft CP-HA-K polymer on high-temperature drilling fluid is that the Graft CP-HA-K polymer can increase the repulsive force between solid particles and disrupt bentonite's reticulation structure.Overall,this research provides novelty insights into the synthesis of artificial humic acid materials and the development of temperature-resistant viscosity reducers,offering a new avenue for the utilization of CP resources.

Prediction of Lubricant Physicochemical Properties Based on Gaussian Copula Data Expansion

The composition of base oils affects the performance of lubricants made from them.This paper proposes a hybrid model based on gradient-boosted decision tree(GBDT)to analyze the effect of different ratios of KN4010,PAO40,and PriEco3000 component in a composite base oil system on the performance of lubricants.The study was conducted under small laboratory sample conditions,and a data expansion method using the Gaussian Copula function was proposed to improve the prediction ability of the hybrid model.The study also compared four optimization algorithms,sticky mushroom algorithm(SMA),genetic algorithm(GA),whale optimization algorithm(WOA),and seagull optimization algorithm(SOA),to predict the kinematic viscosity at 40℃,kinematic viscosity at 100℃,viscosity index,and oxidation induction time performance of the lubricant.The results showed that the Gaussian Copula function data expansion method improved the prediction ability of the hybrid model in the case of small samples.The SOA-GBDT hybrid model had the fastest convergence speed for the samples and the best prediction effect,with determination coefficients(R^(2))for the four indicators of lubricants reaching 0.98,0.99,0.96 and 0.96,respectively.Thus,this model can significantly reduce the model’s prediction error and has good prediction ability.

Improving Satellite-Retrieved Cloud Base Height with Ground-Based Cloud Radar Measurements

Cloud base height(CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a lookup table(LUT) of effective cloud water content(ECWC), representing the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness(CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparative analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar(MMCR) measurements, and results show that the mean bias(correlation coefficient) is0.18±1.79 km(0.73), which is lower(higher) than 0.23±2.11 km(0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar(i.e., Cloud Sat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing networks, and the improved CBH retrievals will contribute to better cloud radiative effect estimates.

Elastic wave insulation and propagation control based on the programmable curved-beam periodic structure

Curved-beams can be used to design modular multistable metamaterials(MMMs)with reprogrammable material properties,i.e.,programmable curved-beam periodic structure(PCBPS),which is promising for controlling the elastic wave propagation.The PCBPS is theoretically equivalent to a spring-oscillator system to investigate the mechanism of bandgap,analyze the wave propagation mechanisms,and further form its geometrical and physical criteria for tuning the elastic wave propagation.With the equivalent model,we calculate the analytical solutions of the dispersion relations to demonstrate its adjustability,and investigate the wave propagation characteristics through the PCBPS.To validate the equivalent system,the finite element method(FEM)is employed.It is revealed that the bandgaps of the PCBPS can be turned on-and-off and shifted by varying its physical and geometrical characteristics.The findings are highly promising for advancing the practical application of periodic structures in wave insulation and propagation control.

The effect of salt anion in ether‐based electrolyte for electrochemical performance of sodium‐ion batteries:A case study of hard carbon

Compared with the extensively used ester‐based electrolyte,the hard carbon(HC)electrode is more compatible with the ether‐based counterpart in sodium‐ion batteries,which can lead to improved cycling stability and robust rate capability.However,the impact of salt anion on the electrochemical performance of HC electrodes has yet to be fully understood.In this study,the anionic chemistry in regulating the stability of electrolytes and the performance of sodium‐ion batteries have been systematically investigated.This work shows discrepancies in the reductive stability of the anionic group,redox kinetics,and component/structure of solid electrolyte interface(SEI)with different salts(NaBF_(4),NaPF_(6),and NaSO_(3)CF_(3))in the typical ether solvent(diglyme).Particularly,the density functional theory calculation manifests the preferred decomposition of PF_(6)−due to the reduced reductive stability of anions in the solvation structure,thus leading to the formation of NaF‐rich SEI.Further investigation on redox kinetics reveals that the NaPF_(6)/diglyme can induce the fast ionic diffusion dynamic and low charge transfer barrier for HC electrode,thus resulting in superior sodium storage performance in terms of rate capability and cycling life,which outperforms those of NaBF_(4)/diglyme and NaSO_(3)CF_(3)/diglyme.Importantly,this work offers valuable insights for optimizing the electrochemical behaviors of electrode materials by regulating the anionic group in the electrolyte.

RoBGP:A Chinese Nested Biomedical Named Entity Recognition Model Based on RoBERTa and Global Pointer

Named Entity Recognition(NER)stands as a fundamental task within the field of biomedical text mining,aiming to extract specific types of entities such as genes,proteins,and diseases from complex biomedical texts and categorize them into predefined entity types.This process can provide basic support for the automatic construction of knowledge bases.In contrast to general texts,biomedical texts frequently contain numerous nested entities and local dependencies among these entities,presenting significant challenges to prevailing NER models.To address these issues,we propose a novel Chinese nested biomedical NER model based on RoBERTa and Global Pointer(RoBGP).Our model initially utilizes the RoBERTa-wwm-ext-large pretrained language model to dynamically generate word-level initial vectors.It then incorporates a Bidirectional Long Short-Term Memory network for capturing bidirectional semantic information,effectively addressing the issue of long-distance dependencies.Furthermore,the Global Pointer model is employed to comprehensively recognize all nested entities in the text.We conduct extensive experiments on the Chinese medical dataset CMeEE and the results demonstrate the superior performance of RoBGP over several baseline models.This research confirms the effectiveness of RoBGP in Chinese biomedical NER,providing reliable technical support for biomedical information extraction and knowledge base construction.