Silver nanoparticles(Ag NPs)have attracted attention in the field of biomaterials due to their excellent antibacterial property.However,the reducing and stabilizing agents used for the chemical reduction of Ag NPs are...Silver nanoparticles(Ag NPs)have attracted attention in the field of biomaterials due to their excellent antibacterial property.However,the reducing and stabilizing agents used for the chemical reduction of Ag NPs are usually toxic and may cause water pollution.In this work,Ag NPs(31.2 nm in diameter)were prepared using the extract of straw,an agricultural waste,as the reducing and stabilizing agent.Experimental analysis revealed that the straw extract contained lignin,the structure of which possesses phenolic hydroxyl and methoxy groups that facilitate the reduction of silver salts into Ag NPs.The surfaces of Ag NPs were negatively charged due to the encapsulation of a thin layer of lignin molecules that prevented their aggregation.After the prepared Ag NPs were added to the precursor solution of acrylamide,free radical polymerization was triggered without the need for extra heating or light irradiation,resulting in the rapid formation of an Ag NP-polyacrylamide composite hydrogel.The inhibition zone test proved that the composite hydrogel possessed excellent antibacterial ability due to the presence of Ag NPs.The prepared hydrogel may have potential applications in the fabrication of biomedical materials,such as antibacterial dressings.展开更多
Objective Emerging evidence suggests that exposure to ultrafine particulate matter(UPM,aerodynamic diameter<0.1μm)is associated with adverse cardiovascular events.Previous studies have found that Shenlian(SL)extra...Objective Emerging evidence suggests that exposure to ultrafine particulate matter(UPM,aerodynamic diameter<0.1μm)is associated with adverse cardiovascular events.Previous studies have found that Shenlian(SL)extract possesses anti-inflammatory and antiapoptotic properties and has a promising protective effect at all stages of the atherosclerotic disease process.In this study,we aimed to investigated whether SL improves UPM-aggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis.Methods We established a mouse model of MI+UPM.Echocardiographic measurement,measurement of myocardialinfarct size,biochemical analysis,enzyme-linked immunosorbent assay(ELISA),histopathological analysis,Transferase dUTP Nick End Labeling(TUNEL),Western blotting(WB),Polymerase Chain Reaction(PCR)and so on were used to explore the anti-inflammatory and antiapoptotic effects of SL in vivo and in vitro.Results SL treatment can attenuate UPM-induced cardiac dysfunction by improving left ventricular ejection fraction,fractional shortening,and decreasing cardiac infarction area.SL significantly reduced the levels of myocardial enzymes and attenuated UPM-induced morphological alterations.Moreover,SL significantly reduced expression levels of the inflammatory cytokines IL-6,TNF-α,and MCP-1.UPM further increased the infiltration of macrophages in myocardial tissue,whereas SL intervention reversed this phenomenon.UPM also triggered myocardial apoptosis,which was markedly attenuated by SL treatment.The results of in vitro experiments revealed that SL prevented cell damage caused by exposure to UPM combined with hypoxia by reducing the expression of the inflammatory factor NF-κB and inhibiting apoptosis in H9c2 cells.Conclusion Overall,both in vivo and in vitro experiments demonstrated that SL attenuated UPMaggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis.The mechanisms were related to the downregulation of macrophages infiltrating heart tissues.展开更多
This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared ...This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared spectroscopy,X-ray diffraction,high-performance anion-exchange chromatography,and differential scanning calorimetry.Significant differences were observed in their morphological,physicochemical,and functional properties.PMS had a smaller particle size(13.68 μm),irregular polygonal shape,A-type,lower water absorption(62.67 %),and higher oil absorption(51.17 %).In contrast,SGS exhibited larger particles(31.75 μm),a nearly spherical shape,B-type,higher crystallinity(50.66 %),and greater amylose content(21.54 %),with superior thermal stability,shear resistance,and gelatinization enthalpy.SGS also contained higher resistant starch(83.28 %) and longer average chain length(20.58 %),but showed lower solubility,swelling power,light transmittance,and freeze-thaw stability.The physicochemical properties differences in crystal pattern and particle morphology between PMS and SGS lead to distinct behaviors during in vitro digestion and fermentation.These findings highlight the potential of medicinal plant starches in functional ingredients and industrial processes.展开更多
Imaging hyperspectral technology has distinctive advantages of non-destructive and non-contact measurement,and the integration of spectral and spatial data.These characteristics present new methodologies for intellige...Imaging hyperspectral technology has distinctive advantages of non-destructive and non-contact measurement,and the integration of spectral and spatial data.These characteristics present new methodologies for intelligent geological sensing in tunnels and other underground engineering projects.However,the in situ acquisition and rapid classification of hyperspectral images in underground still faces great challenges,including the difficulty in obtaining uniform hyperspectral images and the complexity of deploying sophisticated models on mobile platforms.This study proposes an intelligent lithology identification method based on partition feature extraction of hyperspectral images.Firstly,pixel-level hyperspectral information from representative lithological regions is extracted and fused to obtain rock hyperspectral image partition features.Subsequently,an SG-SNV-PCA-DNN(SSPD)model specifically designed for optimizing rock hyperspectral data,performing spectral dimensionality reduction,and identifying lithology is integrated.In an experimental study involving 3420 hyperspectral images,the SSPD identification model achieved the highest accuracy in the testing set,reaching 98.77%.Moreover,the speed of the SSPD model was found to be 18.5%faster than that of the unprocessed model,with an accuracy improvement of 5.22%.In contrast,the ResNet-101 model,used for point-by-point identification based on non-partitioned features,achieved a maximum accuracy of 97.86%in the testing set.In addition,the partition feature extraction methods significantly reduce computational complexity.An objective evaluation of various models demonstrated that the SSPD model exhibited superior performance,achieving a precision(P)of 99.46%,a recall(R)of 99.44%,and F1 score(F1)of 99.45%.Additionally,a pioneering in situ detection work was carried out in a tunnel using underground hyperspectral imaging technology.展开更多
Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and...Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.展开更多
Moringa oleifera(MO)is traditionally used to mitigate inflammatory-mediated disorders;however,the influence of ecotypic variation on its anti-inflammatory activity remains poorly understood.In this study,we compared t...Moringa oleifera(MO)is traditionally used to mitigate inflammatory-mediated disorders;however,the influence of ecotypic variation on its anti-inflammatory activity remains poorly understood.In this study,we compared the phytochemical composition and anti-inflammatory activity of ethanolic extracts obtained from fresh and dried leaves of four MO ecotypes(India,Paraguay,Mozambique,and Pakistan),all grown under the same outdoor conditions,as well as two commercial powders(Just Moringa and WISSA),using LPS-stimulated RAW 264.7 macrophages.Extracts from fresh leaves were 19-43%more cytotoxic than those from dried leaves,depending on the ecotype,likely due to higher cyanogenic glycoside content.Extracts from the India and Paraguay ecotypes,characterized by high levels of quercetin derivatives and caffeic acids,as well as Just Moringa,enriched in kaempferol derivatives,significantly inhibited LPS-induced nitric oxide(NO)production(p<0.05).Just Moringa and Paraguay extracts also reduced iNOS gene expression(p<0.05 and p<0.01,respectively),whereas only the Paraguay extract decreased iNOS protein levels(p<0.05).In contrast,quercetin-3-O-glucoside and rutin showed significant effects only at concentrations approximately 100-fold higher than those present in the extracts,indicating that the phytocomplex displays greater bioactivity than individual compounds.Overall,these results demonstrate that ecotypic variation strongly affects the polyphenolic composition and anti-inflammatory properties of MO leaves,highlighting the importance of reporting both origin and phytochemical composition in MO-based products.展开更多
The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precis...The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.展开更多
Seaweed extract contains plant growth regulators and bio-stimulants that enhance plant growth and development.In Bangladesh,winter rice(Boro rice)in the nursery bed often shows poor seed emergence and weak seedling gr...Seaweed extract contains plant growth regulators and bio-stimulants that enhance plant growth and development.In Bangladesh,winter rice(Boro rice)in the nursery bed often shows poor seed emergence and weak seedling growth due to low temperature.This problem can be addressed by using seaweed extract as a seed priming agent and bio-stimulant.The objective of this study was to evaluate the effectiveness of seaweed extract(Crop Plus)on seed emergence,seedling growth,and vigor of winter rice in the nursery.Two experiments were conducted at Bangladesh Agricultural University using BRRI dhan89.The laboratory experiment consisted of 17 treatments combining three concentrations of Crop Plus(5000,10,000 and 15,000 ppm)and four priming durations(6,12,18,and 24 h),along with hydro-priming and a no priming as control.Seed priming with 15,000 ppm for 24 h produced the highest germination percentage and superior seedling growth traits.The nursery bed experiment comprised 11 treatments combining two doses(1 mL m^(−2)and 2 mL m^(−2))of Crop Plus and five different foliar application schedules,along with a control.All treatments outperformed the control,with the best results from Crop Plus@2 mL m^(−2)applied at 20 and 30 days after sowing(DAS).Overall,the treatment involving seed priming with 15,000 ppm seaweed extract for 24 h,followed by nursery application at 2 mL m^(−2)at 20 and 30 DAS,resulted in higher germination and improved early growth of winter rice.However,further validation across multiple locations,seasons,and rice cultivars is recommended.展开更多
As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive stu...As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive study.In this work,we first report a convenient synthetic method for the construction of DAPhen using Friedländer reaction by two facile steps(vs.previous 12 steps).A variety of DAPhen ligands are readily available,especially unsymmetrical ones,which give us a platform to systematically study the substituent effect on f-block elements extraction performance.The performance of unsymmetrical extractants is experimentally confirmed to falls between that of their corresponding symmetrical extractants by extracting UO_(2)^(2+) as the representative f-block element.This work provides a direct and versatile method to synthesize symmetrical and unsymmetrical DAPhen,which paves way for the investigations on their coordination properties with metal ions and other applications.展开更多
Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future...Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.展开更多
This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3...This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3+) extraction efficiency of 93.5%and a back-extraction efficiency of 82.7%,with selectivity coefficients of β_(Sc/Fe)=459 and β_(Sc/Al)=4241,which are considerably higher as compared to the current extraction systems.The extraction mechanism was studied and interpreted.The enhanced extraction efficiency is attributed to the increased hydrophobicity of the ternary complex,whereas the back-extraction efficiency can be ascribed to the attenuated stability of the complex.C272 and C272–iso-octanol systems also possess considerable surface activity,which is beneficial for the phase separation in solvent extraction.Based on the solvent extraction results,a preliminary study was conducted on polymer inclusion membranes(PIMs)using the binary system for Sc^(3+) separation to avoid the formation of the third phase,achieving an optimal initial flux of PIM of 6.71×10^(−4)mol·m^(−2)·h^(−1).Our results provide valuable information on highly efficient Sc^(3+) separation,and the study on PIM extraction has shown a green alternative to solvent extraction.展开更多
Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targ...Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targets,complex backgrounds,and small objects in remote sensing.Maintaining model lightweight to address resource constraints in remote sensing scenarios while improving task completion for remote sensing tasks remains a research hotspot.Therefore,we propose an enhanced multi-scale feature extraction lightweight network EM-YOLO based on the YOLOv8s architecture,specifically optimized for the characteristics of large target scale variations,diverse orientations,and numerous small objects in remote sensing images.Our innovations lie in two main aspects:First,a dynamic snake convolution(DSC)is introduced into the backbone network to enhance the model’s feature extraction capability for oriented targets.Second,an innovative focusing-diffusion module is designed in the feature fusion neck to effectively integrate multi-scale feature information.Finally,we introduce Layer-Adaptive Sparsity for magnitude-based Pruning(LASP)method to perform lightweight network pruning to better complete tasks in resource-constrained scenarios.Experimental results on the lightweight platform Orin demonstrate that the proposed method significantly outperforms the original YOLOv8s model in oriented remote sensing object detection tasks,and achieves comparable or superior performance to state-of-the-art methods on three authoritative remote sensing datasets(DOTA v1.0,DOTA v1.5,and HRSC2016).展开更多
Accurate state of health(SOH)estimation is essential for the safe and reliable operation of lithium-ion batteries.However,existing methods face significant challenges,primarily because they rely on complete charge–di...Accurate state of health(SOH)estimation is essential for the safe and reliable operation of lithium-ion batteries.However,existing methods face significant challenges,primarily because they rely on complete charge–discharge cycles and fixed-form physical constraints,which limit adaptability to different chemistries and real-world conditions.To address these issues,this study proposes an approach that extracts features from segmented state of charge(SOC)intervals and integrates them into an enhanced physics-informed neural network(PINN).Specifically,voltage data within the 25%–75%SOC range during charging are used to derive statistical,time–frequency,and mechanism-based features that capture degradation trends.A hybrid PINN-Lasso-Transformer-BiLSTM architecture is developed,where Lasso regression enables sparse feature selection,and a nonlinear empirical degradation model is embedded as a learnable physical term within a dynamically scaled composite loss.This design adaptively balances data-driven accuracy with physical consistency,thereby enhancing estimation precision,robustness,and generalization.The results show that the proposed method outperforms conventional neural networks across four battery chemistries,achieving root mean square error and mean absolute error below 1%.Notably,features from partial charging segments exhibit higher robustness than those from full cycles.Furthermore,the model maintains strong performance under high temperatures and demonstrates excellent generalization capacity in transfer learning across chemistries,temperatures,and C-rates.This work establishes a scalable and interpretable solution for accurate SOH estimation under diverse practical operating conditions.展开更多
To ease the scarcity of lithium(Li)resource and cut down on environmental pollution,an efficient,selective,inexpensive and sustainable Li recycling process from waste batteries is needed,which is yet to be achieved.He...To ease the scarcity of lithium(Li)resource and cut down on environmental pollution,an efficient,selective,inexpensive and sustainable Li recycling process from waste batteries is needed,which is yet to be achieved.Here,we report a low-potential photoelectrochemical(PEC)system that selectively and efficiently extracts Li metals from multi-cation electrolytes under 1 sun illumination.Based on the difference of redox potential,we can get rid of the disturbance of other cations(i.e.,Fe,Co and Ni ions)by a bias-free PEC device to realize the extraction of high-purity Li metals on a coplanar Si-based photocathode-TiO_(2) photoanode tandem device at 2 V of applied bias(far less than the redox potentials of Li^(+)/Li).In such system,the extraction rate of Li metals(purity>99.5%)exceeds 1.35 g h^(-1)m^(-2)with 90%of Faradaic efficiency.Long-term experiments,different electrode/electrolyte tests,and various price assessments further demonstrate the stability,compatibility and economy of PEC extraction system,enabling a solar-driven pathway for the recycling of critical metal resources.展开更多
As a key low-carbon energy source,nuclear power plays a vital role in the global transition toward sustainable energy.Photocatalytic uranium extraction from seawater(UES)offers a promising solution to ensure long-term...As a key low-carbon energy source,nuclear power plays a vital role in the global transition toward sustainable energy.Photocatalytic uranium extraction from seawater(UES)offers a promising solution to ensure long-term uranium supply but is challenged by ultra-low uranium concentrations and ion interference.To overcome these issues,we design three diketopyrrolopyrrole-based covalent organic frameworks(COFs)via a synergisticπ-extended lock and carboxyl-functionalized anchor molecular engineering strategy.Among them,TPy-DPP-COF features a covalently lockedπ-conjugated structure that enhances planarity,optimizes energy alignment,and minimizes exciton binding energy,thereby promoting charge transfer and suppressing recombination.Concurrently,carboxyl groups enable uranyl-specific coordination and create local electric fields to facilitate charge separation.These features contribute to the outstanding performance of TPy-DPP-COF,which achieves a high uranium adsorption capacity of 16.33 mg g−1 in natural seawater under irradiation,with only 29.3%capacity loss after 10 cycles,surpassing industrial benchmarks.Density functional theory(DFT)calculations and experimental studies reveal a synergistic photocatalysis-adsorption pathway,with DPP units acting as active sites for uranium reduction.This work highlights a molecular design strategy for developing efficient COF-based photocatalysts for practical marine uranium recovery.展开更多
Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representati...Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.展开更多
Background:Neurological disorders(NDs),including ischemic stroke(IS),Parkinson’s disease(PD),and Alzheimer’s disease(AD),are major contributors to global morbidity and mortality.Boswellia extract has demonstrated ne...Background:Neurological disorders(NDs),including ischemic stroke(IS),Parkinson’s disease(PD),and Alzheimer’s disease(AD),are major contributors to global morbidity and mortality.Boswellia extract has demonstrated neuroprotective properties,yet a comprehensive systematic review assessing its efficacy remains absent.This study aims to evaluate the efficacy of Boswellia extract in treating NDs,with a particular focus on its effects in AD and its potential for long-term neurorestoration,thereby supporting further investigation into Boswellia’s therapeutic role in ND management.Methods:A systematic literature search was performed in PubMed,Web of Science,ScienceDirect,and Google Scholar for English-language studies published up to March 2024.Eighteen studies met the inclusion criteria and were included in the meta-analysis.The study protocol was registered on PROSPERO(CRD42024524386).Eligible studies involved rodent models of IS,PD,or AD with post-operative interventions using Boswellia extract.Data extraction focused on mechanisms of action,dosages,treatment durations,and therapeutic outcomes.Studies were excluded if they involved non-ND models,combined treatments,or had incomplete data.Two researchers independently conducted literature screening and data extraction.Statistical analyses were conducted using Stata(version 17)and RevMan(version 5.4),employing fixed or random-effects models based on heterogeneity assessments.Result s:Boswellia extract significantly improved the mean effect size for NDs(ES=1.28,95%CI(1.05,1.51),P<0.001).Specifically,it reduced cerebral infarct volume in IS(SMD=−2.87,95%CI(−3.42,−2.32))and enhanced behavioral outcomes in AD(SMD=3.26,95%CI(2.07,5.14))and PD(SMD=5.37,95%CI(3.93,6.80)).Subgroup analyses revealed that Boswellia extract exhibited superior efficacy in AD when administered orally and via intra-cerebroventricular injection.Long-term treatment with Boswellia extract suggested potential neurorestorative effects.Additionally,Boswellia extract was more effective than its monomeric constituents,highlighting its promising role in ND treatment.Conclusion:Boswellia extract demonstrates significant neuroprotective effects across various NDs,particularly in AD and in promoting long-term neurorestoration.These findings support the need for further research into Boswellia’s potential as a therapeutic agent in the management of neurological disorders.展开更多
AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longit...AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longitudinal observational study,detailed medical histories of APAC patients and comprehensive ophthalmic examinations at final followup were collected.Logistic regression analysis was performed to identify predictors of blindness.Univariate and multivariate linear regression analyses were conducted to determine risk factors associated with visual outcomes.RESULTS:This study included 39 affected eyes of 31 subjects(26 females)with an average age of 74.1±8.0y.At 6.7±4.2y after APAC attack,2(5.7%)eyes had bestcorrected visual acuity(VA)worse than 3/60.Advanced glaucomatous visual field loss was observed in 15(39.5%)affected eyes and 5(25.0%)fellow eyes.Nine affected eyes(23.7%)had GON,and 11(28.9%)were blind.Six(15.4%)affected eyes and 2(9.1%)fellow eyes had suspicious progression.A significantly higher blindness rate in factory workers compared to office workers.Logistic regression identified that worse VA at attack(OR 10.568,95%CI 1.288-86.695;P=0.028)and worse early postoperative VA(OR 13.214,95%CI 1.157-150.881;P=0.038)were risk factors for blindness.Multivariate regression showed that longer duration of elevated intraocular pressure(P=0.004)and worse early postoperative VA(P=0.009)were associated with worse visual outcomes.CONCLUSION:Despite LE surgery,some APAC patients experience continued visual function deterioration.Lifelong monitoring is necessary.Target pressure and progression rates should be re-evaluated during follow-up.展开更多
Objective:To investigate the efficacy and underlying mechanisms of standardized Salvia miltiorrhiza extract(SMEX)in alleviating menopausal symptoms using MCF-7 cells and an ovary-intact menopause mouse model resulting...Objective:To investigate the efficacy and underlying mechanisms of standardized Salvia miltiorrhiza extract(SMEX)in alleviating menopausal symptoms using MCF-7 cells and an ovary-intact menopause mouse model resulting from hypothalamic-pituitary-ovarian axis aging.Methods:Estrogen receptor(ER)-related molecular responses were first assessed in MCF-7 cells treated with SMEX.In vivo efficacy was then evaluated in 52-week-old female mice orally administered SMEX(50 or 100 mg/kg/day)or 17β-estradiol(E2)for 12 weeks.ER expression and downstream AKT/ERK signaling pathways in uterine tissues were determined.In addition,histological analysis of reproductive organs,assessment of serum lipid and hormone levels,neurotransmitter measurements,and behavioral tests were performed.Results:SMEX upregulated ERαand ERβexpression and suppressed pS2 mRNA in MCF-7 cells,indicating selective ER modulation.In SMEX-treated mice,uterine ER expression and activation of the AKT and ERK pathways were significantly increased,leading to partial restoration of epithelial thickness and stratification in the oviduct and vagina.SMEX also significantly reduced serum low-density lipoprotein cholesterol levels and reversed menopausal alterations in the follicle-stimulating hormone/luteinizing hormone ratio.Additionally,it elevated serotonin and norepinephrine levels in the pituitary,thereby alleviating depression-like behavior.Conclusions:SMEX modulates ER signaling and improves neurohormonal balance,effectively alleviating menopausal symptoms in both in vitro and in vivo models.This highlights its potential as a safe,natural alternative to hormone replacement therapy and as a promising functional ingredient in therapeutic natural products.展开更多
[ Objective] The aim was to provide evidence and countermeasures for study on allelopathy of eggplant and supply a scientific basis for ecological management of allelopathy and establishment of a reasonable, effective...[ Objective] The aim was to provide evidence and countermeasures for study on allelopathy of eggplant and supply a scientific basis for ecological management of allelopathy and establishment of a reasonable, effective intercropping and continuous cropping system. [ Method] Allelopathy of aerial part extracts from grafted eggplants was studied by bioassay. [ Result] The results showed that aerial part extracts of eggplants have autotoxiclty which inhibited seed germination and seedling growth of eggplants. Aerial part extracts of grafted eggplants inhibited seed germination and seedling growth of tomato, pepper and cu cumber at different level. Inhibition intensity of extracts was in order of tomato 〉 pepper 〉 cucumber. The inhibition effect was higher at 0.2 g/ml concentration than 0.1 g/ml concentration. There wasn＇t significance between ownrooted treatments and grafted treatments. [ Conclusion] Eggplant is not suitable for round of inter-cropping with tomato, pepper and cucumber.展开更多
基金financially supported by the National Natural Science Foundation of China(No.52203209)the State Key Laboratory of Solid Waste Reuse for Building Materials,China(No.SWR-2022-009)the Fundamental Research Funds for the Central Universities,China(No.FRF-IDRY22-012)。
文摘Silver nanoparticles(Ag NPs)have attracted attention in the field of biomaterials due to their excellent antibacterial property.However,the reducing and stabilizing agents used for the chemical reduction of Ag NPs are usually toxic and may cause water pollution.In this work,Ag NPs(31.2 nm in diameter)were prepared using the extract of straw,an agricultural waste,as the reducing and stabilizing agent.Experimental analysis revealed that the straw extract contained lignin,the structure of which possesses phenolic hydroxyl and methoxy groups that facilitate the reduction of silver salts into Ag NPs.The surfaces of Ag NPs were negatively charged due to the encapsulation of a thin layer of lignin molecules that prevented their aggregation.After the prepared Ag NPs were added to the precursor solution of acrylamide,free radical polymerization was triggered without the need for extra heating or light irradiation,resulting in the rapid formation of an Ag NP-polyacrylamide composite hydrogel.The inhibition zone test proved that the composite hydrogel possessed excellent antibacterial ability due to the presence of Ag NPs.The prepared hydrogel may have potential applications in the fabrication of biomedical materials,such as antibacterial dressings.
基金supported by CACMS Innovation Fund(No CI2021A04611,CI2021A05106)Scientific and technological innovation project of China Academy of Chinese Medical Sciences(CI2021B015)+1 种基金Scientific and technological innovation project of China Academy of Chinese Medical Sciences(CI2023E001TS01)Fundamental research funds for the central public welfare research institutes(L2022035).
文摘Objective Emerging evidence suggests that exposure to ultrafine particulate matter(UPM,aerodynamic diameter<0.1μm)is associated with adverse cardiovascular events.Previous studies have found that Shenlian(SL)extract possesses anti-inflammatory and antiapoptotic properties and has a promising protective effect at all stages of the atherosclerotic disease process.In this study,we aimed to investigated whether SL improves UPM-aggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis.Methods We established a mouse model of MI+UPM.Echocardiographic measurement,measurement of myocardialinfarct size,biochemical analysis,enzyme-linked immunosorbent assay(ELISA),histopathological analysis,Transferase dUTP Nick End Labeling(TUNEL),Western blotting(WB),Polymerase Chain Reaction(PCR)and so on were used to explore the anti-inflammatory and antiapoptotic effects of SL in vivo and in vitro.Results SL treatment can attenuate UPM-induced cardiac dysfunction by improving left ventricular ejection fraction,fractional shortening,and decreasing cardiac infarction area.SL significantly reduced the levels of myocardial enzymes and attenuated UPM-induced morphological alterations.Moreover,SL significantly reduced expression levels of the inflammatory cytokines IL-6,TNF-α,and MCP-1.UPM further increased the infiltration of macrophages in myocardial tissue,whereas SL intervention reversed this phenomenon.UPM also triggered myocardial apoptosis,which was markedly attenuated by SL treatment.The results of in vitro experiments revealed that SL prevented cell damage caused by exposure to UPM combined with hypoxia by reducing the expression of the inflammatory factor NF-κB and inhibiting apoptosis in H9c2 cells.Conclusion Overall,both in vivo and in vitro experiments demonstrated that SL attenuated UPMaggravated myocardial ischemic injury by inhibiting inflammation and cell apoptosis.The mechanisms were related to the downregulation of macrophages infiltrating heart tissues.
基金supported by the National Natural Science Foundation of China (No.82174074)。
文摘This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared spectroscopy,X-ray diffraction,high-performance anion-exchange chromatography,and differential scanning calorimetry.Significant differences were observed in their morphological,physicochemical,and functional properties.PMS had a smaller particle size(13.68 μm),irregular polygonal shape,A-type,lower water absorption(62.67 %),and higher oil absorption(51.17 %).In contrast,SGS exhibited larger particles(31.75 μm),a nearly spherical shape,B-type,higher crystallinity(50.66 %),and greater amylose content(21.54 %),with superior thermal stability,shear resistance,and gelatinization enthalpy.SGS also contained higher resistant starch(83.28 %) and longer average chain length(20.58 %),but showed lower solubility,swelling power,light transmittance,and freeze-thaw stability.The physicochemical properties differences in crystal pattern and particle morphology between PMS and SGS lead to distinct behaviors during in vitro digestion and fermentation.These findings highlight the potential of medicinal plant starches in functional ingredients and industrial processes.
基金support from the National Natural Science Foundation of China(Grant Nos.52379103,52279103)the Natural Science Foundation of Shandong Province(Grant No.ZR2023YQ049).
文摘Imaging hyperspectral technology has distinctive advantages of non-destructive and non-contact measurement,and the integration of spectral and spatial data.These characteristics present new methodologies for intelligent geological sensing in tunnels and other underground engineering projects.However,the in situ acquisition and rapid classification of hyperspectral images in underground still faces great challenges,including the difficulty in obtaining uniform hyperspectral images and the complexity of deploying sophisticated models on mobile platforms.This study proposes an intelligent lithology identification method based on partition feature extraction of hyperspectral images.Firstly,pixel-level hyperspectral information from representative lithological regions is extracted and fused to obtain rock hyperspectral image partition features.Subsequently,an SG-SNV-PCA-DNN(SSPD)model specifically designed for optimizing rock hyperspectral data,performing spectral dimensionality reduction,and identifying lithology is integrated.In an experimental study involving 3420 hyperspectral images,the SSPD identification model achieved the highest accuracy in the testing set,reaching 98.77%.Moreover,the speed of the SSPD model was found to be 18.5%faster than that of the unprocessed model,with an accuracy improvement of 5.22%.In contrast,the ResNet-101 model,used for point-by-point identification based on non-partitioned features,achieved a maximum accuracy of 97.86%in the testing set.In addition,the partition feature extraction methods significantly reduce computational complexity.An objective evaluation of various models demonstrated that the SSPD model exhibited superior performance,achieving a precision(P)of 99.46%,a recall(R)of 99.44%,and F1 score(F1)of 99.45%.Additionally,a pioneering in situ detection work was carried out in a tunnel using underground hyperspectral imaging technology.
文摘Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.
文摘Moringa oleifera(MO)is traditionally used to mitigate inflammatory-mediated disorders;however,the influence of ecotypic variation on its anti-inflammatory activity remains poorly understood.In this study,we compared the phytochemical composition and anti-inflammatory activity of ethanolic extracts obtained from fresh and dried leaves of four MO ecotypes(India,Paraguay,Mozambique,and Pakistan),all grown under the same outdoor conditions,as well as two commercial powders(Just Moringa and WISSA),using LPS-stimulated RAW 264.7 macrophages.Extracts from fresh leaves were 19-43%more cytotoxic than those from dried leaves,depending on the ecotype,likely due to higher cyanogenic glycoside content.Extracts from the India and Paraguay ecotypes,characterized by high levels of quercetin derivatives and caffeic acids,as well as Just Moringa,enriched in kaempferol derivatives,significantly inhibited LPS-induced nitric oxide(NO)production(p<0.05).Just Moringa and Paraguay extracts also reduced iNOS gene expression(p<0.05 and p<0.01,respectively),whereas only the Paraguay extract decreased iNOS protein levels(p<0.05).In contrast,quercetin-3-O-glucoside and rutin showed significant effects only at concentrations approximately 100-fold higher than those present in the extracts,indicating that the phytocomplex displays greater bioactivity than individual compounds.Overall,these results demonstrate that ecotypic variation strongly affects the polyphenolic composition and anti-inflammatory properties of MO leaves,highlighting the importance of reporting both origin and phytochemical composition in MO-based products.
基金supported by the National Natural Science Foundation of China(No.52403035)the Shanghai Sailing Program(23YF1400300)+1 种基金the Fundamental Research Funds for the Central Universities(2232023D-05)the Weiqiao Teaching and Research Innovation Program.
文摘The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.
基金funded by Bangladesh Agricultural University Research System(BAURES)through the Project No.2024/48/BAU.
文摘Seaweed extract contains plant growth regulators and bio-stimulants that enhance plant growth and development.In Bangladesh,winter rice(Boro rice)in the nursery bed often shows poor seed emergence and weak seedling growth due to low temperature.This problem can be addressed by using seaweed extract as a seed priming agent and bio-stimulant.The objective of this study was to evaluate the effectiveness of seaweed extract(Crop Plus)on seed emergence,seedling growth,and vigor of winter rice in the nursery.Two experiments were conducted at Bangladesh Agricultural University using BRRI dhan89.The laboratory experiment consisted of 17 treatments combining three concentrations of Crop Plus(5000,10,000 and 15,000 ppm)and four priming durations(6,12,18,and 24 h),along with hydro-priming and a no priming as control.Seed priming with 15,000 ppm for 24 h produced the highest germination percentage and superior seedling growth traits.The nursery bed experiment comprised 11 treatments combining two doses(1 mL m^(−2)and 2 mL m^(−2))of Crop Plus and five different foliar application schedules,along with a control.All treatments outperformed the control,with the best results from Crop Plus@2 mL m^(−2)applied at 20 and 30 days after sowing(DAS).Overall,the treatment involving seed priming with 15,000 ppm seaweed extract for 24 h,followed by nursery application at 2 mL m^(−2)at 20 and 30 DAS,resulted in higher germination and improved early growth of winter rice.However,further validation across multiple locations,seasons,and rice cultivars is recommended.
基金financial support from the National Natural Science Foundation of China (Nos.22476178,U2067213)Natural Science Foundation of Zhejiang Province (No.LRG25B060002)。
文摘As an important class of phenanthroline derivatives containing soft N and hard O donor atoms,the laborious syntheses of unsymmetrical 1,10-phenanthroline-derived diamide ligands(DAPhen) have hindered its extensive study.In this work,we first report a convenient synthetic method for the construction of DAPhen using Friedländer reaction by two facile steps(vs.previous 12 steps).A variety of DAPhen ligands are readily available,especially unsymmetrical ones,which give us a platform to systematically study the substituent effect on f-block elements extraction performance.The performance of unsymmetrical extractants is experimentally confirmed to falls between that of their corresponding symmetrical extractants by extracting UO_(2)^(2+) as the representative f-block element.This work provides a direct and versatile method to synthesize symmetrical and unsymmetrical DAPhen,which paves way for the investigations on their coordination properties with metal ions and other applications.
基金National Natural Science Foundation of China under Grants 62122069,62071431,62072490,62301490Science and Technology Development Fund of Macao,Macao,China under Grant 0158/2022/A+2 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515011287)MYRG2020-00107-IOTSCFDCT SKL-IOTSC(UM)-2021-2023。
文摘Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.
基金support from the National Natural Science Foundation of China Regional Innovation and Development Joint Fund(U24A20557)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDC0230403)+3 种基金the National Natural Science Foundation of China(22378393,22208356)“Hundred Talents Program”of the Chinese Academy of Sciencesthe Chinese Academy of Sciences stably supports the youth team plan in the field of basic research(YSBR 038)Key Research&Development projects in Qinghai Province(2023-HZ-805).
文摘This article presents a new synergistic extraction system composed of Cyanex 272(C272,bis(2,4,4-trimethylpentyl)phosphinic acid)and iso-octanol for Sc_(3+) separation.The proposed synergistic system possessed an Sc^(3+) extraction efficiency of 93.5%and a back-extraction efficiency of 82.7%,with selectivity coefficients of β_(Sc/Fe)=459 and β_(Sc/Al)=4241,which are considerably higher as compared to the current extraction systems.The extraction mechanism was studied and interpreted.The enhanced extraction efficiency is attributed to the increased hydrophobicity of the ternary complex,whereas the back-extraction efficiency can be ascribed to the attenuated stability of the complex.C272 and C272–iso-octanol systems also possess considerable surface activity,which is beneficial for the phase separation in solvent extraction.Based on the solvent extraction results,a preliminary study was conducted on polymer inclusion membranes(PIMs)using the binary system for Sc^(3+) separation to avoid the formation of the third phase,achieving an optimal initial flux of PIM of 6.71×10^(−4)mol·m^(−2)·h^(−1).Our results provide valuable information on highly efficient Sc^(3+) separation,and the study on PIM extraction has shown a green alternative to solvent extraction.
基金funded by the Hainan Province Science and Technology Special Fund under Grant ZDYF2024GXJS292.
文摘Deep learning has made significant progress in the field of oriented object detection for remote sensing images.However,existing methods still face challenges when dealing with difficult tasks such as multi-scale targets,complex backgrounds,and small objects in remote sensing.Maintaining model lightweight to address resource constraints in remote sensing scenarios while improving task completion for remote sensing tasks remains a research hotspot.Therefore,we propose an enhanced multi-scale feature extraction lightweight network EM-YOLO based on the YOLOv8s architecture,specifically optimized for the characteristics of large target scale variations,diverse orientations,and numerous small objects in remote sensing images.Our innovations lie in two main aspects:First,a dynamic snake convolution(DSC)is introduced into the backbone network to enhance the model’s feature extraction capability for oriented targets.Second,an innovative focusing-diffusion module is designed in the feature fusion neck to effectively integrate multi-scale feature information.Finally,we introduce Layer-Adaptive Sparsity for magnitude-based Pruning(LASP)method to perform lightweight network pruning to better complete tasks in resource-constrained scenarios.Experimental results on the lightweight platform Orin demonstrate that the proposed method significantly outperforms the original YOLOv8s model in oriented remote sensing object detection tasks,and achieves comparable or superior performance to state-of-the-art methods on three authoritative remote sensing datasets(DOTA v1.0,DOTA v1.5,and HRSC2016).
基金supported by the Shanghai Pilot Program for Basic Research(22T01400100-18)the National Natural Science Foundation of China(22278127 and 12447149)+1 种基金the Fundamental Research Funds for the Central Universities(2022ZFJH004)the Postdoctoral Fellowship Program of CPSF(GZB20250159).
文摘Accurate state of health(SOH)estimation is essential for the safe and reliable operation of lithium-ion batteries.However,existing methods face significant challenges,primarily because they rely on complete charge–discharge cycles and fixed-form physical constraints,which limit adaptability to different chemistries and real-world conditions.To address these issues,this study proposes an approach that extracts features from segmented state of charge(SOC)intervals and integrates them into an enhanced physics-informed neural network(PINN).Specifically,voltage data within the 25%–75%SOC range during charging are used to derive statistical,time–frequency,and mechanism-based features that capture degradation trends.A hybrid PINN-Lasso-Transformer-BiLSTM architecture is developed,where Lasso regression enables sparse feature selection,and a nonlinear empirical degradation model is embedded as a learnable physical term within a dynamically scaled composite loss.This design adaptively balances data-driven accuracy with physical consistency,thereby enhancing estimation precision,robustness,and generalization.The results show that the proposed method outperforms conventional neural networks across four battery chemistries,achieving root mean square error and mean absolute error below 1%.Notably,features from partial charging segments exhibit higher robustness than those from full cycles.Furthermore,the model maintains strong performance under high temperatures and demonstrates excellent generalization capacity in transfer learning across chemistries,temperatures,and C-rates.This work establishes a scalable and interpretable solution for accurate SOH estimation under diverse practical operating conditions.
基金the National Natural Science Foundation of China(22479047,22409058)the Outstanding Youth Scientist Foundation of Hunan Province(2022JJ10023)the Provincial Natural Science Foundation of Guangdong(2023A1515011745)for financial support of this research。
文摘To ease the scarcity of lithium(Li)resource and cut down on environmental pollution,an efficient,selective,inexpensive and sustainable Li recycling process from waste batteries is needed,which is yet to be achieved.Here,we report a low-potential photoelectrochemical(PEC)system that selectively and efficiently extracts Li metals from multi-cation electrolytes under 1 sun illumination.Based on the difference of redox potential,we can get rid of the disturbance of other cations(i.e.,Fe,Co and Ni ions)by a bias-free PEC device to realize the extraction of high-purity Li metals on a coplanar Si-based photocathode-TiO_(2) photoanode tandem device at 2 V of applied bias(far less than the redox potentials of Li^(+)/Li).In such system,the extraction rate of Li metals(purity>99.5%)exceeds 1.35 g h^(-1)m^(-2)with 90%of Faradaic efficiency.Long-term experiments,different electrode/electrolyte tests,and various price assessments further demonstrate the stability,compatibility and economy of PEC extraction system,enabling a solar-driven pathway for the recycling of critical metal resources.
基金the Young Elite Scientists Sponsorship Program by JXAST(2024QT11)the National Natural Science Foundation of China(22465001,22309003)the Jiangxi Provincial Natural Science Foundation(20232BAB203042,20242BAB22002).
文摘As a key low-carbon energy source,nuclear power plays a vital role in the global transition toward sustainable energy.Photocatalytic uranium extraction from seawater(UES)offers a promising solution to ensure long-term uranium supply but is challenged by ultra-low uranium concentrations and ion interference.To overcome these issues,we design three diketopyrrolopyrrole-based covalent organic frameworks(COFs)via a synergisticπ-extended lock and carboxyl-functionalized anchor molecular engineering strategy.Among them,TPy-DPP-COF features a covalently lockedπ-conjugated structure that enhances planarity,optimizes energy alignment,and minimizes exciton binding energy,thereby promoting charge transfer and suppressing recombination.Concurrently,carboxyl groups enable uranyl-specific coordination and create local electric fields to facilitate charge separation.These features contribute to the outstanding performance of TPy-DPP-COF,which achieves a high uranium adsorption capacity of 16.33 mg g−1 in natural seawater under irradiation,with only 29.3%capacity loss after 10 cycles,surpassing industrial benchmarks.Density functional theory(DFT)calculations and experimental studies reveal a synergistic photocatalysis-adsorption pathway,with DPP units acting as active sites for uranium reduction.This work highlights a molecular design strategy for developing efficient COF-based photocatalysts for practical marine uranium recovery.
文摘Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.
基金supported by the National Natural Science Foundation of China,specifically through grants(No.8227431382304947)Key Research and Development Project of Shaanxi Province(2023GHZD43).Peer re v iew information。
文摘Background:Neurological disorders(NDs),including ischemic stroke(IS),Parkinson’s disease(PD),and Alzheimer’s disease(AD),are major contributors to global morbidity and mortality.Boswellia extract has demonstrated neuroprotective properties,yet a comprehensive systematic review assessing its efficacy remains absent.This study aims to evaluate the efficacy of Boswellia extract in treating NDs,with a particular focus on its effects in AD and its potential for long-term neurorestoration,thereby supporting further investigation into Boswellia’s therapeutic role in ND management.Methods:A systematic literature search was performed in PubMed,Web of Science,ScienceDirect,and Google Scholar for English-language studies published up to March 2024.Eighteen studies met the inclusion criteria and were included in the meta-analysis.The study protocol was registered on PROSPERO(CRD42024524386).Eligible studies involved rodent models of IS,PD,or AD with post-operative interventions using Boswellia extract.Data extraction focused on mechanisms of action,dosages,treatment durations,and therapeutic outcomes.Studies were excluded if they involved non-ND models,combined treatments,or had incomplete data.Two researchers independently conducted literature screening and data extraction.Statistical analyses were conducted using Stata(version 17)and RevMan(version 5.4),employing fixed or random-effects models based on heterogeneity assessments.Result s:Boswellia extract significantly improved the mean effect size for NDs(ES=1.28,95%CI(1.05,1.51),P<0.001).Specifically,it reduced cerebral infarct volume in IS(SMD=−2.87,95%CI(−3.42,−2.32))and enhanced behavioral outcomes in AD(SMD=3.26,95%CI(2.07,5.14))and PD(SMD=5.37,95%CI(3.93,6.80)).Subgroup analyses revealed that Boswellia extract exhibited superior efficacy in AD when administered orally and via intra-cerebroventricular injection.Long-term treatment with Boswellia extract suggested potential neurorestorative effects.Additionally,Boswellia extract was more effective than its monomeric constituents,highlighting its promising role in ND treatment.Conclusion:Boswellia extract demonstrates significant neuroprotective effects across various NDs,particularly in AD and in promoting long-term neurorestoration.These findings support the need for further research into Boswellia’s potential as a therapeutic agent in the management of neurological disorders.
文摘AIM:To investigate the long-term outcomes in acute primary angle closure(APAC)patients treated with lens extraction(LE)surgery and to identify risk factors for glaucomatous optic neuropathy(GON).METHODS:In this longitudinal observational study,detailed medical histories of APAC patients and comprehensive ophthalmic examinations at final followup were collected.Logistic regression analysis was performed to identify predictors of blindness.Univariate and multivariate linear regression analyses were conducted to determine risk factors associated with visual outcomes.RESULTS:This study included 39 affected eyes of 31 subjects(26 females)with an average age of 74.1±8.0y.At 6.7±4.2y after APAC attack,2(5.7%)eyes had bestcorrected visual acuity(VA)worse than 3/60.Advanced glaucomatous visual field loss was observed in 15(39.5%)affected eyes and 5(25.0%)fellow eyes.Nine affected eyes(23.7%)had GON,and 11(28.9%)were blind.Six(15.4%)affected eyes and 2(9.1%)fellow eyes had suspicious progression.A significantly higher blindness rate in factory workers compared to office workers.Logistic regression identified that worse VA at attack(OR 10.568,95%CI 1.288-86.695;P=0.028)and worse early postoperative VA(OR 13.214,95%CI 1.157-150.881;P=0.038)were risk factors for blindness.Multivariate regression showed that longer duration of elevated intraocular pressure(P=0.004)and worse early postoperative VA(P=0.009)were associated with worse visual outcomes.CONCLUSION:Despite LE surgery,some APAC patients experience continued visual function deterioration.Lifelong monitoring is necessary.Target pressure and progression rates should be re-evaluated during follow-up.
基金funded by UNDBIO Co.,Ltd.No specific grant number was assigned.
文摘Objective:To investigate the efficacy and underlying mechanisms of standardized Salvia miltiorrhiza extract(SMEX)in alleviating menopausal symptoms using MCF-7 cells and an ovary-intact menopause mouse model resulting from hypothalamic-pituitary-ovarian axis aging.Methods:Estrogen receptor(ER)-related molecular responses were first assessed in MCF-7 cells treated with SMEX.In vivo efficacy was then evaluated in 52-week-old female mice orally administered SMEX(50 or 100 mg/kg/day)or 17β-estradiol(E2)for 12 weeks.ER expression and downstream AKT/ERK signaling pathways in uterine tissues were determined.In addition,histological analysis of reproductive organs,assessment of serum lipid and hormone levels,neurotransmitter measurements,and behavioral tests were performed.Results:SMEX upregulated ERαand ERβexpression and suppressed pS2 mRNA in MCF-7 cells,indicating selective ER modulation.In SMEX-treated mice,uterine ER expression and activation of the AKT and ERK pathways were significantly increased,leading to partial restoration of epithelial thickness and stratification in the oviduct and vagina.SMEX also significantly reduced serum low-density lipoprotein cholesterol levels and reversed menopausal alterations in the follicle-stimulating hormone/luteinizing hormone ratio.Additionally,it elevated serotonin and norepinephrine levels in the pituitary,thereby alleviating depression-like behavior.Conclusions:SMEX modulates ER signaling and improves neurohormonal balance,effectively alleviating menopausal symptoms in both in vitro and in vivo models.This highlights its potential as a safe,natural alternative to hormone replacement therapy and as a promising functional ingredient in therapeutic natural products.
基金Supported by National Natural Science Foundation of China(30370971)863 Program of China(2004AA247010)And theResearch Project of Liaoning Education Department(2004D206)~~
文摘[ Objective] The aim was to provide evidence and countermeasures for study on allelopathy of eggplant and supply a scientific basis for ecological management of allelopathy and establishment of a reasonable, effective intercropping and continuous cropping system. [ Method] Allelopathy of aerial part extracts from grafted eggplants was studied by bioassay. [ Result] The results showed that aerial part extracts of eggplants have autotoxiclty which inhibited seed germination and seedling growth of eggplants. Aerial part extracts of grafted eggplants inhibited seed germination and seedling growth of tomato, pepper and cu cumber at different level. Inhibition intensity of extracts was in order of tomato 〉 pepper 〉 cucumber. The inhibition effect was higher at 0.2 g/ml concentration than 0.1 g/ml concentration. There wasn＇t significance between ownrooted treatments and grafted treatments. [ Conclusion] Eggplant is not suitable for round of inter-cropping with tomato, pepper and cucumber.
