In this paper, the determinacy of regular lexical selectional restrictions is examined from both the internal structures of the single selectional restrictions (i.e.semantic selectional restrictions) and relationship ...In this paper, the determinacy of regular lexical selectional restrictions is examined from both the internal structures of the single selectional restrictions (i.e.semantic selectional restrictions) and relationship between the structures of several selectional restrictions. Hence, our analysis and description are shifted from casual and indeterminate strings and markers on case basis to determined rules and circumspect dynamic systems, from lexical precepts to knowledge precepts, from the state of memory to rational deduction and rhetorical devices. Further studies indicate that selectional restrictions are intertwined structures, a feature that makes it possible to be one of the bases for lexical selectional restrictions to come into existence. Its related theories are the grarantee for scientific observations of selectional restriction structures.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
BACKGROUND Post-stroke depression(PSD)is associated with hypothalamic-pituitary-adrenal(HPA)axis dysfunction and neurotransmitter deficits.Selective serotonin reuptake inhibitors(SSRIs)are commonly used,but their effi...BACKGROUND Post-stroke depression(PSD)is associated with hypothalamic-pituitary-adrenal(HPA)axis dysfunction and neurotransmitter deficits.Selective serotonin reuptake inhibitors(SSRIs)are commonly used,but their efficacy is limited.This study investigated whether combining SSRIs with traditional Chinese medicine(TCM)Free San could enhance their therapeutic effects.AIM To evaluate the clinical efficacy and safety of combining SSRIs with Free San in treating PSD,and to assess its impact on HPA axis function.METHODS Ninety-two patients with PSD were enrolled and randomly divided into control groups(n=46)and study groups(n=46).The control group received the SSRI paroxetine alone,whereas the study group received paroxetine combined with Free San for 4 weeks.Hamilton Depression Scale and TCM syndrome scores were assessed before and after treatment.Serum serotonin,norepinephrine,cortisol,cor-ticotropin-releasing hormone,and adrenocorticotropic hormone were measured.The treatment responses and adverse reactions were recorded.RESULTS After treatment,the Hamilton Depression Scale and TCM syndrome scores were significantly lower in the study group than in the control group(P<0.05).Serum serotonin and norepinephrine levels were significantly higher in the study group than in the control group,whereas cortisol,corticotropin-releasing hormone,and adrenocorticotropic hormone levels were significantly lower(P<0.05).The total efficacy rates were 84.78%and 65.22%in the study and control groups,respectively(P<0.05).No significant differences in adverse reactions were observed between the two groups(P>0.05).CONCLUSION Combining SSRIs with Free San can enhance therapeutic efficacy,improve depressive symptoms,and regulate HPA axis function in patients with PSD with good safety and clinical application value.展开更多
GEMIN5 is a predominantly cytoplasmic multifunctional protein, known to be involved in recognizing snRNAs through its WD40 repeats domain placed at the N-terminus. A dimerization domain in the middle region acts as a ...GEMIN5 is a predominantly cytoplasmic multifunctional protein, known to be involved in recognizing snRNAs through its WD40 repeats domain placed at the N-terminus. A dimerization domain in the middle region acts as a hub for protein–protein interaction, while a non-canonical RNA-binding site is placed towards the C-terminus. The singular organization of structural domains present in GEMIN5 enables this protein to perform multiple functions through its ability to interact with distinct partners, both RNAs and proteins. This protein exerts a different role in translation regulation depending on its physiological state, such that while GEMIN5 down-regulates global RNA translation, the C-terminal half of the protein promotes translation of its mRNA. Additionally, GEMIN5 is responsible for the preferential partitioning of mRNAs into polysomes. Besides selective translation, GEMIN5 forms part of distinct ribonucleoprotein complexes, reflecting the dynamic organization of macromolecular complexes in response to internal and external signals. In accordance with its contribution to fundamental cellular processes, recent reports described clinical loss of function mutants suggesting that GEMIN5 deficiency is detrimental to cell growth and survival. Remarkably, patients carrying GEMIN5 biallelic variants suffer from neurodevelopmental delay, hypotonia, and cerebellar ataxia. Molecular analyses of individual variants, which are defective in protein dimerization, display decreased levels of ribosome association, reinforcing the involvement of the protein in translation regulation. Importantly, the number of clinical variants and the phenotypic spectrum associated with GEMIN5 disorders is increasing as the knowledge of the protein functions and the pathways linked to its activity augments. Here we discuss relevant advances concerning the functional and structural features of GEMIN5 and its separate domains in RNA-binding, protein interactome, and translation regulation, and how these data can help to understand the involvement of protein malfunction in clinical variants found in patients developing neurodevelopmental disorders.展开更多
Electrocatalytic nitrate reduction reaction(NO3RR)represents a sustainable and environmentally benign route for ammonia(NH3)synthesis.However,NO3RR is still limited by the competition from hydrogen evolution reaction(...Electrocatalytic nitrate reduction reaction(NO3RR)represents a sustainable and environmentally benign route for ammonia(NH3)synthesis.However,NO3RR is still limited by the competition from hydrogen evolution reaction(HER)and the high energy barrier in the hydrogenation step of nitrogen-containing intermediates.Here,we report a selective etching strategy to construct Ru M nanoalloys(M=Fe,Co,Ni,Cu)uniformly dispersed on porous nitrogen-doped carbon substrates for efficient neutral NH3electrosynthesis.Density functional theory calculations confirm that the synergic effect between Ru and transition metal M modulates the electronic structure of the alloy,significantly lowering the energy barrier for the conversion of*NO_(2)to*HNO_(2).Experimentally,the optimized Ru Fe-NC catalyst achieves 100%Faraday efficiency with a high yield rate of 0.83 mg h^(-1)mg^(-1)catat a low potential of-0.1 V vs.RHE,outperforming most reported catalysts.In situ spectroscopic analyses further demonstrate that the Ru M-NC effectively promotes the hydrogenation of nitrogen intermediates while inhibiting the formation of hydrogen radicals,thereby reducing HER competition.The Ru FeNC assembled Zn-NO_(3)^(-)battery achieved a high open-circuit voltage and an outstanding power density and capacity,which drive selective NO_(3)^(-)conversion to NH3.This work provides a powerful synergistic design strategy for efficient NH3electrosynthesis and a general framework for the development of advanced multi-component catalysts for sustainable nitrogen conversion.展开更多
Developing biomass platform compounds into high value-added chemicals is a key step in renewable resource utilization.Herein,we report porous carbon-supported Ni-ZnO nanoparticles catalyst(Ni-ZnO/AC)synthesized via lo...Developing biomass platform compounds into high value-added chemicals is a key step in renewable resource utilization.Herein,we report porous carbon-supported Ni-ZnO nanoparticles catalyst(Ni-ZnO/AC)synthesized via low-temperature coprecipitation,exhibiting excellent performance for the selective hydrogenation of 5-hydroxymethylfurfural(HMF).A linear correlation is first observed between solvent polarity(E_(T)(30))and product selectivity within both polar aprotic and protic solvent classes,suggesting that solvent properties play a vital role in directing reaction pathways.Among these,1,4-dioxane(aprotic)favors the formation of 2,5-bis(hydroxymethyl)furan(BHMF)with 97.5%selectivity,while isopropanol(iPrOH,protic)promotes 2,5-dimethylfuran production with up to 99.5%selectivity.Mechanistic investigations further reveal that beyond polarity,proton-donating ability is critical in facilitating hydrodeoxygenation.iPrOH enables a hydrogen shuttle mechanism where protons assist in hydroxyl group removal,lowering the activation barrier.In contrast,1,4-dioxane,lacking hydrogen bond donors,stabilizes BHMF and hinders further conversion.Density functional theory calculations confirm a lower activation energy in iPrOH(0.60 eV)compared to 1,4-dioxane(1.07 eV).This work offers mechanistic insights and a practical strategy for solvent-mediated control of product selectivity in biomass hydrogenation,highlighting the decisive role of solvent-catalyst-substrate interactions.展开更多
BACKGROUND Breast cancer is one of the most prevalent malignancies affecting women worldwide,with approximately 2.3 million new cases diagnosed annually.Breast cancer stem cells(BCSCs)play pivotal roles in tumor initi...BACKGROUND Breast cancer is one of the most prevalent malignancies affecting women worldwide,with approximately 2.3 million new cases diagnosed annually.Breast cancer stem cells(BCSCs)play pivotal roles in tumor initiation,progression,metastasis,therapeutic resistance,and disease recurrence.Cancer stem cells possess selfrenewal capacity,multipotent differentiation potential,and enhanced tumorigenic activity,but their molecular characteristics and regulatory mechanisms require further investigation.AIM To comprehensively characterize the molecular features of BCSCs through multiomics approaches,construct a prognostic prediction model based on stem cellrelated genes,reveal cell-cell communication networks within the tumor microenvironment,and provide theoretical foundation for personalized treatment strategies.METHODS Flow cytometry was employed to detect the expression of BCSC surface markers(CD34,CD45,CD29,CD90,CD105).Transcriptomic analysis was performed to identify differentially expressed genes.Least absolute shrinkage and selection operator regression analysis was utilized to screen key prognostic genes and construct a risk scoring model.Single-cell RNA sequencing and spatial transcriptomics were applied to analyze tumor heterogeneity and spatial gene expression patterns.Cell-cell communication network analysis was conducted to reveal interactions between stem cells and the microenvironment.RESULTS Flow cytometric analysis revealed the highest expression of CD105(96.30%),followed by CD90(68.43%)and CD34(62.64%),while CD29 showed lower expression(7.16%)and CD45 exhibited the lowest expression(1.19%).Transcriptomic analysis identified 3837 significantly differentially expressed genes(1478 upregulated and 2359 downregulated).Least absolute shrinkage and selection operator regression analysis selected 10 key prognostic genes,and the constructed risk scoring model effectively distinguished between high-risk and low-risk patient groups(P<0.001).Single-cell analysis revealed tumor cellular heterogeneity,and spatial transcriptomics demonstrated distinct spatial expression gradients of stem cell-related genes.MED18 gene showed significantly higher expression in malignant tissues(P<0.001)and occupied a central position in cell-cell communication networks,exhibiting significant correlations with tumor cells,macrophages,fibroblasts,and endothelial cells.CONCLUSION This study comprehensively characterized the molecular features of BCSCs through multi-omics approaches,identified reliable surface markers and key regulatory genes,and constructed a prognostic prediction model with clinical application value.展开更多
Lithium-oxygen(Li-O2)batteries are perceived as a promising breakthrough in sustainable electrochemical energy storage,utilizing ambient air as an energy source,eliminating the need for costly cathode materials,and of...Lithium-oxygen(Li-O2)batteries are perceived as a promising breakthrough in sustainable electrochemical energy storage,utilizing ambient air as an energy source,eliminating the need for costly cathode materials,and offering the highest theoretical energy density(~3.5 k Wh kg^(-1))among discussed candidates.Contributing to the poor cycle life of currently reported Li-O_(2)cells is singlet oxygen(1O_(2))formation,inducing parasitic reactions,degrading key components,and severely deteriorating cell performance.Here,we harness the chirality-induced spin selectivity effect of chiral cobalt oxide nanosheets(Co_(3)O_(4)NSs)as cathode materials to suppress 1O_(2)in Li-O_(2)batteries for the first time.Operando photoluminescence spectroscopy reveals a 3.7-fold and 3.23-fold reduction in 1O_(2)during discharge and charge,respectively,compared to conventional carbon paperbased cells,consistent with differential electrochemical mass spectrometry results,which indicate a near-theoretical charge-to-O_(2)ratio(2.04 e-/O_(2)).Density functional theory calculations demonstrate that chirality induces a peak shift near the Fermi level,enhancing Co 3d-O 2p hybridization,stabilizing reaction intermediates,and lowering activation barriers for Li_(2)O_(2)formation and decomposition.These findings establish a new strategy for improving the stability and energy efficiency of sustainable Li-O_(2)batteries,abridging the current gap to commercialization.展开更多
The endoplasmic reticulum,a key cellular organelle,regulates a wide variety of cellular activities.Endoplasmic reticulum autophagy,one of the quality control systems of the endoplasmic reticulum,plays a pivotal role i...The endoplasmic reticulum,a key cellular organelle,regulates a wide variety of cellular activities.Endoplasmic reticulum autophagy,one of the quality control systems of the endoplasmic reticulum,plays a pivotal role in maintaining endoplasmic reticulum homeostasis by controlling endoplasmic reticulum turnover,remodeling,and proteostasis.In this review,we briefly describe the endoplasmic reticulum quality control system,and subsequently focus on the role of endoplasmic reticulum autophagy,emphasizing the spatial and temporal mechanisms underlying the regulation of endoplasmic reticulum autophagy according to cellular requirements.We also summarize the evidence relating to how defective or abnormal endoplasmic reticulum autophagy contributes to the pathogenesis of neurodegenerative diseases.In summary,this review highlights the mechanisms associated with the regulation of endoplasmic reticulum autophagy and how they influence the pathophysiology of degenerative nerve disorders.This review would help researchers to understand the roles and regulatory mechanisms of endoplasmic reticulum-phagy in neurodegenerative disorders.展开更多
Heat shock protein family B(small)member 8(HSPB8)is a 22 kDa ubiquitously expressed protein belonging to the family of small heat shock proteins.HSPB8 is involved in various cellular mechanisms mainly related to prote...Heat shock protein family B(small)member 8(HSPB8)is a 22 kDa ubiquitously expressed protein belonging to the family of small heat shock proteins.HSPB8 is involved in various cellular mechanisms mainly related to proteotoxic stress response and in other processes such as inflammation,cell division,and migration.HSPB8 binds misfolded clients to prevent their aggregation by assisting protein refolding or degradation through chaperone-assisted selective autophagy.In line with this function,the pro-degradative activity of HSPB8 has been found protective in several neurodegenerative and neuromuscular diseases characterized by protein misfolding and aggregation.In cancer,HSPB8 has a dual role being capable of exerting either a pro-or an anti-tumoral activity depending on the pathways and factors expressed by the model of cancer under investigation.Moreover,HSPB8 exerts a protective function in different diseases by modulating the inflammatory response,which characterizes not only neurodegenerative diseases,but also other chronic or acute conditions affecting the nervous system,such as multiple sclerosis and intracerebellar hemorrhage.Of note,HSPB8 modulation may represent a therapeutic approach in other neurological conditions that develop as a secondary consequence of other diseases.This is the case of cognitive impairment related to diabetes mellitus,in which HSPB8 exerts a protective activity by assuring mitochondrial homeostasis.This review aims to summarize the diverse and multiple functions of HSPB8 in different pathological conditions,focusing on the beneficial effects of its modulation.Drug-based and alternative therapeutic approaches targeting HSPB8 and its regulated pathways will be discussed,emphasizing how new strategies for cell and tissue-specific delivery represent an avenue to advance in disease treatments.展开更多
Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these i...Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these internal magnetic fields accurately,data selection based on specific criteria is often employed to minimize the influence of rapidly changing current systems in the ionosphere and magnetosphere.However,the quantitative impact of various data selection criteria on internal geomagnetic field modeling is not well understood.This study aims to address this issue and provide a reference for constructing and applying geomagnetic field models.First,we collect the latest MSS-1 and Swarm satellite magnetic data and summarize widely used data selection criteria in geomagnetic field modeling.Second,we briefly describe the method to co-estimate the core,crustal,and large-scale magnetospheric fields using satellite magnetic data.Finally,we conduct a series of field modeling experiments with different data selection criteria to quantitatively estimate their influence.Our numerical experiments confirm that without selecting data from dark regions and geomagnetically quiet times,the resulting internal field differences at the Earth’s surface can range from tens to hundreds of nanotesla(nT).Additionally,we find that the uncertainties introduced into field models by different data selection criteria are significantly larger than the measurement accuracy of modern geomagnetic satellites.These uncertainties should be considered when utilizing constructed magnetic field models for scientific research and applications.展开更多
The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more e...The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more efficient and reliable intrusion detection systems(IDSs).However,the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs.Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues.While most of these researchers reported the success of these preprocessing techniques on a shallow level,very few studies have been performed on their effects on a wider scale.Furthermore,the performance of an IDS model is subject to not only the utilized preprocessing techniques but also the dataset and the ML/DL algorithm used,which most of the existing studies give little emphasis on.Thus,this study provides an in-depth analysis of feature selection and normalization effects on IDS models built using three IDS datasets:NSL-KDD,UNSW-NB15,and CSE–CIC–IDS2018,and various AI algorithms.A wrapper-based approach,which tends to give superior performance,and min-max normalization methods were used for feature selection and normalization,respectively.Numerous IDS models were implemented using the full and feature-selected copies of the datasets with and without normalization.The models were evaluated using popular evaluation metrics in IDS modeling,intra-and inter-model comparisons were performed between models and with state-of-the-art works.Random forest(RF)models performed better on NSL-KDD and UNSW-NB15 datasets with accuracies of 99.86%and 96.01%,respectively,whereas artificial neural network(ANN)achieved the best accuracy of 95.43%on the CSE–CIC–IDS2018 dataset.The RF models also achieved an excellent performance compared to recent works.The results show that normalization and feature selection positively affect IDS modeling.Furthermore,while feature selection benefits simpler algorithms(such as RF),normalization is more useful for complex algorithms like ANNs and deep neural networks(DNNs),and algorithms such as Naive Bayes are unsuitable for IDS modeling.The study also found that the UNSW-NB15 and CSE–CIC–IDS2018 datasets are more complex and more suitable for building and evaluating modern-day IDS than the NSL-KDD dataset.Our findings suggest that prioritizing robust algorithms like RF,alongside complex models such as ANN and DNN,can significantly enhance IDS performance.These insights provide valuable guidance for managers to develop more effective security measures by focusing on high detection rates and low false alert rates.展开更多
This research aims to study the bio-adsorption process of two dyes,Cibacron Green H3G(CG-H3G)and Terasil Red(TR),in a single system and to bring them closer to the industrial textile discharge by a binary mixture of t...This research aims to study the bio-adsorption process of two dyes,Cibacron Green H3G(CG-H3G)and Terasil Red(TR),in a single system and to bring them closer to the industrial textile discharge by a binary mixture of two dyes(TR+CG-H3G).The Cockle Shell(CS)was used as a natural bio-adsorbent.The characterizations of CS were investigated by Fourier transform infrared(FTIR),X-ray diffraction(XRD),scanning electron microscopy(SEM),energy-dispersive X-ray spectroscopy(EDX)and Brunauer–Emmett–Teller(BET).The adsorption potential of Cockle Shells was tested in two cases(single and binary system)and determined by:contact time(0–60 min),bio-adsorption dose(3–15 g/L),initial concentration(10–300 mg/L),temperature(22–61°C)and pH solution(2–12).The study of bio-adsorption(equilibrium and kinetics)was conducted at 22°C.The kinetic studies demon-strated that a pseudo-second-order adsorption mechanism had a good correlation coefficient(R2≥0.999).The Langmuir isotherm modeling provided a well-defined description of TR and CG-H3G bio-adsorption on cockle shells,exhibiting maximum capacities of 29.41 and 3.69 mg/g respectively at 22°C.The thermodynamic study shows that the reaction between the TR,CG-H3G dyes molecules and the bio-adsorbent is exothermic,spontaneous in the range of 22–31°C with the aleatory character decrease at the solid-liquid interface.The study of selectivity in single and binary systems has been performed under optimal operating conditions using the industrial textile rejection pH(pH=6.04).CG-H3G dye is found to have a higher selectivity than TR in single(0–60 min)and binary systems with a range of 6–45 min,as shown by the selectivity measurement.It was discovered that CS has the capability to remove both CG-H3G and TR dyes in both simple and binary systems,making it a superior bio-adsorbent.展开更多
Clear aligner treatment is a novel technique in current orthodontic practice.Distinct from traditional fixed orthodontic appliances,clear aligners have different material features and biomechanical characteristics and...Clear aligner treatment is a novel technique in current orthodontic practice.Distinct from traditional fixed orthodontic appliances,clear aligners have different material features and biomechanical characteristics and treatment efficiencies,presenting new clinical challenges.Therefore,a comprehensive and systematic description of the key clinical aspects of clear aligner treatment is essential to enhance treatment efficacy and facilitate the advancement and wide adoption of this new technique.This expert consensus discusses case selection and grading of treatment difficulty,principle of clear aligner therapy,clinical procedures and potential complications,which are crucial to the clinical success of clear aligner treatment.展开更多
The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly re...The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all ‘polygenic effects' associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359Duroc×Landrace×Yorkshire pigs from Guangxi Zhuang Autonomous Region, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed 4breeding strategies applied to different scenarios: Ⅰ, only spectral and genotypic data exist for the target population;Ⅱ, only spectral data exist for the target population;Ⅲ, only spectral and genotypic data but with different prediction processes exist for the target population;and Ⅳ, only spectral and phenotypic data exist for the target population.The 4 scenarios were used to evaluate the genomic estimated breeding value(GEBV) accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies Ⅱ, Ⅲ, and Ⅳ was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2, 40.8 and 15.5%, respectively on average. Among them, the prediction accuracy of Strategy Ⅱ for fat(%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy Ⅰ was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the 4 strategies was lower than that of traditional GS methods, with Strategy Ⅳ being the lowest as it did not require genotyping.Our findings demonstrate that GS methods based on VIS/NIRS data have significant predictive potential and are worthy of further research to provide a valuable reference for the development of effective and affordable breeding strategies.展开更多
Transcutaneous electrical acupoint stimulation(TEAS)is a kind of physical therapy that use electric cur-rent through the electrodes placed on the surface of acupoints to produce clinical effects in the human body,whic...Transcutaneous electrical acupoint stimulation(TEAS)is a kind of physical therapy that use electric cur-rent through the electrodes placed on the surface of acupoints to produce clinical effects in the human body,which is characterized by less adverse reaction and convenient operation.It has been widely used in the treatment of various diseases.This review introduces six major clinical applications of TEAS,named analgesia,regulation of gastrointestinal function,improvement of reproductive function,enhancement of cognitive function,promotion of limb function recovery and relief of fatigue.Besides,TEAS has been ap-plied to the treatment of other chronic diseases such as hypertension and diabetes,achieving satisfactory clinical effects.However,two crucial challenges are encountered in the development of TEAS.One is the lack of standardization in the selection of parameters such as waveform,frequency,intensity and stimula-tion duration.The other is the limitation on the flexibility in the acupoint selection.This review analyzes key issues that need to be addressed in the current clinical application of TEAS,such as the selection of parameters and acupoints,and this review provides a certain reference value for optimizing regimens of TEAS and promoting its development and application.展开更多
Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain c...Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.展开更多
Nitrogen(N)enrichment has resulted in widespread alteration of grassland ecosystem processes and functions mainly through disturbance in soil enzyme activities.However,we lack a comprehensive understanding of how N de...Nitrogen(N)enrichment has resulted in widespread alteration of grassland ecosystem processes and functions mainly through disturbance in soil enzyme activities.However,we lack a comprehensive understanding of how N deposition affects specific key soil enzymes that mediate plant-soil feedback of grassland.Here,with a meta-analysis on 1446 cases from field observations in China,we show that N deposition differently affects soil enzymes associated with soil biochemical processes.Specifically,N-promoted C,N,and P-acquiring hydrolase activities significantly increased by 8.73%,7.67%,and 8.69%,respectively,related to an increase in microbial-specific enzyme secretion.The increased relative N availability and soil acidification were two potential mechanisms accounting for the changes in soil enzyme activities with N enrichment.The mixed N addition in combination of NH_(4)NO_(3) and urea showed greater stimulation effect on soil enzyme activities.However,the high rate and long-term N addition tended to weaken the positive responses of soil C-,Nand P-acquiring hydrolase activities to N enrichment.Spatially increased mean annual precipitation and temperature primarily promoted the positive effects of N enrichment on N-and P-acquiring hydrolase activities,and the stimulation of C-and N-acquiring hydrolase activities by N enrichment was intensified with the increase in soil depth.Finally,multimodal inference showed that grassland type was the most important regulator of responses of microbial C,N,and P-acquiring hydrolase activities to N enrichment.This meta-analysis provides a comprehensive insight into understanding the key role of N enrichment in shaping soil enzyme activities of grassland ecosystems.展开更多
Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination...Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.展开更多
文摘In this paper, the determinacy of regular lexical selectional restrictions is examined from both the internal structures of the single selectional restrictions (i.e.semantic selectional restrictions) and relationship between the structures of several selectional restrictions. Hence, our analysis and description are shifted from casual and indeterminate strings and markers on case basis to determined rules and circumspect dynamic systems, from lexical precepts to knowledge precepts, from the state of memory to rational deduction and rhetorical devices. Further studies indicate that selectional restrictions are intertwined structures, a feature that makes it possible to be one of the bases for lexical selectional restrictions to come into existence. Its related theories are the grarantee for scientific observations of selectional restriction structures.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金Supported by Open Project of Jiangsu Province Key Laboratory of Integrated Traditional Chinese and Western Medicine for the Prevention and Treatment of Geriatric Diseases,No.202232.
文摘BACKGROUND Post-stroke depression(PSD)is associated with hypothalamic-pituitary-adrenal(HPA)axis dysfunction and neurotransmitter deficits.Selective serotonin reuptake inhibitors(SSRIs)are commonly used,but their efficacy is limited.This study investigated whether combining SSRIs with traditional Chinese medicine(TCM)Free San could enhance their therapeutic effects.AIM To evaluate the clinical efficacy and safety of combining SSRIs with Free San in treating PSD,and to assess its impact on HPA axis function.METHODS Ninety-two patients with PSD were enrolled and randomly divided into control groups(n=46)and study groups(n=46).The control group received the SSRI paroxetine alone,whereas the study group received paroxetine combined with Free San for 4 weeks.Hamilton Depression Scale and TCM syndrome scores were assessed before and after treatment.Serum serotonin,norepinephrine,cortisol,cor-ticotropin-releasing hormone,and adrenocorticotropic hormone were measured.The treatment responses and adverse reactions were recorded.RESULTS After treatment,the Hamilton Depression Scale and TCM syndrome scores were significantly lower in the study group than in the control group(P<0.05).Serum serotonin and norepinephrine levels were significantly higher in the study group than in the control group,whereas cortisol,corticotropin-releasing hormone,and adrenocorticotropic hormone levels were significantly lower(P<0.05).The total efficacy rates were 84.78%and 65.22%in the study and control groups,respectively(P<0.05).No significant differences in adverse reactions were observed between the two groups(P>0.05).CONCLUSION Combining SSRIs with Free San can enhance therapeutic efficacy,improve depressive symptoms,and regulate HPA axis function in patients with PSD with good safety and clinical application value.
基金partially supported by grants PID2020-115096RB-I00 and PID2023-148273NB-I00 from Ministerio de Ciencia y Universidad (MICIU/AEI)(to EMS)。
文摘GEMIN5 is a predominantly cytoplasmic multifunctional protein, known to be involved in recognizing snRNAs through its WD40 repeats domain placed at the N-terminus. A dimerization domain in the middle region acts as a hub for protein–protein interaction, while a non-canonical RNA-binding site is placed towards the C-terminus. The singular organization of structural domains present in GEMIN5 enables this protein to perform multiple functions through its ability to interact with distinct partners, both RNAs and proteins. This protein exerts a different role in translation regulation depending on its physiological state, such that while GEMIN5 down-regulates global RNA translation, the C-terminal half of the protein promotes translation of its mRNA. Additionally, GEMIN5 is responsible for the preferential partitioning of mRNAs into polysomes. Besides selective translation, GEMIN5 forms part of distinct ribonucleoprotein complexes, reflecting the dynamic organization of macromolecular complexes in response to internal and external signals. In accordance with its contribution to fundamental cellular processes, recent reports described clinical loss of function mutants suggesting that GEMIN5 deficiency is detrimental to cell growth and survival. Remarkably, patients carrying GEMIN5 biallelic variants suffer from neurodevelopmental delay, hypotonia, and cerebellar ataxia. Molecular analyses of individual variants, which are defective in protein dimerization, display decreased levels of ribosome association, reinforcing the involvement of the protein in translation regulation. Importantly, the number of clinical variants and the phenotypic spectrum associated with GEMIN5 disorders is increasing as the knowledge of the protein functions and the pathways linked to its activity augments. Here we discuss relevant advances concerning the functional and structural features of GEMIN5 and its separate domains in RNA-binding, protein interactome, and translation regulation, and how these data can help to understand the involvement of protein malfunction in clinical variants found in patients developing neurodevelopmental disorders.
基金financially supported by National Natural Science Foundation of China(22466010)Guizhou Provincial Basic Research Program(Natural Science)ZK[2023]47 and key program ZD[2025]075+6 种基金Innovation and Entrepreneurship Project for overseas Talents in Guizhou Province[2022]02Specific Natural Science Foundation of Guizhou University(X202207)the national undergraduate innovation and entrepreneurship training program(gzugc2023006gzusc2024012)SRT project of Guizhou university(2023SRT0292023SRT024)supported by Shanghai Technical Service Center of Science and Engineering Computing,Shanghai University。
文摘Electrocatalytic nitrate reduction reaction(NO3RR)represents a sustainable and environmentally benign route for ammonia(NH3)synthesis.However,NO3RR is still limited by the competition from hydrogen evolution reaction(HER)and the high energy barrier in the hydrogenation step of nitrogen-containing intermediates.Here,we report a selective etching strategy to construct Ru M nanoalloys(M=Fe,Co,Ni,Cu)uniformly dispersed on porous nitrogen-doped carbon substrates for efficient neutral NH3electrosynthesis.Density functional theory calculations confirm that the synergic effect between Ru and transition metal M modulates the electronic structure of the alloy,significantly lowering the energy barrier for the conversion of*NO_(2)to*HNO_(2).Experimentally,the optimized Ru Fe-NC catalyst achieves 100%Faraday efficiency with a high yield rate of 0.83 mg h^(-1)mg^(-1)catat a low potential of-0.1 V vs.RHE,outperforming most reported catalysts.In situ spectroscopic analyses further demonstrate that the Ru M-NC effectively promotes the hydrogenation of nitrogen intermediates while inhibiting the formation of hydrogen radicals,thereby reducing HER competition.The Ru FeNC assembled Zn-NO_(3)^(-)battery achieved a high open-circuit voltage and an outstanding power density and capacity,which drive selective NO_(3)^(-)conversion to NH3.This work provides a powerful synergistic design strategy for efficient NH3electrosynthesis and a general framework for the development of advanced multi-component catalysts for sustainable nitrogen conversion.
基金the National Nature Science Foundation of China for Excellent Young Scientists Fund(32222058)Fundamental Research Foundation of CAF(CAFYBB2022QB001).
文摘Developing biomass platform compounds into high value-added chemicals is a key step in renewable resource utilization.Herein,we report porous carbon-supported Ni-ZnO nanoparticles catalyst(Ni-ZnO/AC)synthesized via low-temperature coprecipitation,exhibiting excellent performance for the selective hydrogenation of 5-hydroxymethylfurfural(HMF).A linear correlation is first observed between solvent polarity(E_(T)(30))and product selectivity within both polar aprotic and protic solvent classes,suggesting that solvent properties play a vital role in directing reaction pathways.Among these,1,4-dioxane(aprotic)favors the formation of 2,5-bis(hydroxymethyl)furan(BHMF)with 97.5%selectivity,while isopropanol(iPrOH,protic)promotes 2,5-dimethylfuran production with up to 99.5%selectivity.Mechanistic investigations further reveal that beyond polarity,proton-donating ability is critical in facilitating hydrodeoxygenation.iPrOH enables a hydrogen shuttle mechanism where protons assist in hydroxyl group removal,lowering the activation barrier.In contrast,1,4-dioxane,lacking hydrogen bond donors,stabilizes BHMF and hinders further conversion.Density functional theory calculations confirm a lower activation energy in iPrOH(0.60 eV)compared to 1,4-dioxane(1.07 eV).This work offers mechanistic insights and a practical strategy for solvent-mediated control of product selectivity in biomass hydrogenation,highlighting the decisive role of solvent-catalyst-substrate interactions.
基金the Natural Science Foundation of Yongchuan District,No.2023yc-jckx20021.
文摘BACKGROUND Breast cancer is one of the most prevalent malignancies affecting women worldwide,with approximately 2.3 million new cases diagnosed annually.Breast cancer stem cells(BCSCs)play pivotal roles in tumor initiation,progression,metastasis,therapeutic resistance,and disease recurrence.Cancer stem cells possess selfrenewal capacity,multipotent differentiation potential,and enhanced tumorigenic activity,but their molecular characteristics and regulatory mechanisms require further investigation.AIM To comprehensively characterize the molecular features of BCSCs through multiomics approaches,construct a prognostic prediction model based on stem cellrelated genes,reveal cell-cell communication networks within the tumor microenvironment,and provide theoretical foundation for personalized treatment strategies.METHODS Flow cytometry was employed to detect the expression of BCSC surface markers(CD34,CD45,CD29,CD90,CD105).Transcriptomic analysis was performed to identify differentially expressed genes.Least absolute shrinkage and selection operator regression analysis was utilized to screen key prognostic genes and construct a risk scoring model.Single-cell RNA sequencing and spatial transcriptomics were applied to analyze tumor heterogeneity and spatial gene expression patterns.Cell-cell communication network analysis was conducted to reveal interactions between stem cells and the microenvironment.RESULTS Flow cytometric analysis revealed the highest expression of CD105(96.30%),followed by CD90(68.43%)and CD34(62.64%),while CD29 showed lower expression(7.16%)and CD45 exhibited the lowest expression(1.19%).Transcriptomic analysis identified 3837 significantly differentially expressed genes(1478 upregulated and 2359 downregulated).Least absolute shrinkage and selection operator regression analysis selected 10 key prognostic genes,and the constructed risk scoring model effectively distinguished between high-risk and low-risk patient groups(P<0.001).Single-cell analysis revealed tumor cellular heterogeneity,and spatial transcriptomics demonstrated distinct spatial expression gradients of stem cell-related genes.MED18 gene showed significantly higher expression in malignant tissues(P<0.001)and occupied a central position in cell-cell communication networks,exhibiting significant correlations with tumor cells,macrophages,fibroblasts,and endothelial cells.CONCLUSION This study comprehensively characterized the molecular features of BCSCs through multi-omics approaches,identified reliable surface markers and key regulatory genes,and constructed a prognostic prediction model with clinical application value.
基金supported by Basic Science Research Program(Priority Research Institute)through the NRF of Korea funded by the Ministry of Education(2021R1A6A1A10039823)by the Korea Basic Science Institute(National Research Facilities and Equipment Center)grant funded by the Ministry of Education(2020R1A6C101B194)。
文摘Lithium-oxygen(Li-O2)batteries are perceived as a promising breakthrough in sustainable electrochemical energy storage,utilizing ambient air as an energy source,eliminating the need for costly cathode materials,and offering the highest theoretical energy density(~3.5 k Wh kg^(-1))among discussed candidates.Contributing to the poor cycle life of currently reported Li-O_(2)cells is singlet oxygen(1O_(2))formation,inducing parasitic reactions,degrading key components,and severely deteriorating cell performance.Here,we harness the chirality-induced spin selectivity effect of chiral cobalt oxide nanosheets(Co_(3)O_(4)NSs)as cathode materials to suppress 1O_(2)in Li-O_(2)batteries for the first time.Operando photoluminescence spectroscopy reveals a 3.7-fold and 3.23-fold reduction in 1O_(2)during discharge and charge,respectively,compared to conventional carbon paperbased cells,consistent with differential electrochemical mass spectrometry results,which indicate a near-theoretical charge-to-O_(2)ratio(2.04 e-/O_(2)).Density functional theory calculations demonstrate that chirality induces a peak shift near the Fermi level,enhancing Co 3d-O 2p hybridization,stabilizing reaction intermediates,and lowering activation barriers for Li_(2)O_(2)formation and decomposition.These findings establish a new strategy for improving the stability and energy efficiency of sustainable Li-O_(2)batteries,abridging the current gap to commercialization.
基金supported by the National Natural Science Foundation of China,Nos.92049120 and 81870897STI2030-Major Projects,No.2021ZD0204001+6 种基金Guangdong Key Project for Development of New Tools for the Diagnosis and Treatment of Autism,No.2018B030335001the Natural Science Foundation of Jiangsu Province,No.BK20181436the National Major Scientific and Technological Special Project for Significant New Drug Development,No.2019ZX09301102the Discipline Construction Program of the Second Affiliated Hospital of Soochow University,No.XKTJ-TD202003Sino-German Cooperation Mobility Programme,No.M-0679the Science and Technology Project of Suzhou,No.SKY2022161Research Project of Neurological Diseases of the Second Affiliated Hospital of Soochow University Medical Center,No.ND2023A01(all to QHM)。
文摘The endoplasmic reticulum,a key cellular organelle,regulates a wide variety of cellular activities.Endoplasmic reticulum autophagy,one of the quality control systems of the endoplasmic reticulum,plays a pivotal role in maintaining endoplasmic reticulum homeostasis by controlling endoplasmic reticulum turnover,remodeling,and proteostasis.In this review,we briefly describe the endoplasmic reticulum quality control system,and subsequently focus on the role of endoplasmic reticulum autophagy,emphasizing the spatial and temporal mechanisms underlying the regulation of endoplasmic reticulum autophagy according to cellular requirements.We also summarize the evidence relating to how defective or abnormal endoplasmic reticulum autophagy contributes to the pathogenesis of neurodegenerative diseases.In summary,this review highlights the mechanisms associated with the regulation of endoplasmic reticulum autophagy and how they influence the pathophysiology of degenerative nerve disorders.This review would help researchers to understand the roles and regulatory mechanisms of endoplasmic reticulum-phagy in neurodegenerative disorders.
基金supported by:Fondazione Telethon-Italy(No.GGP19128 to AP)Fondazione Cariplo-Italy(No.2021-1544 to RC)+14 种基金Fondazione Italiana di Ricerca per la Sclerosi Laterale Amiotrofica(AriSLA)-Italy(No.MLOpathy to APTarget-RAN to AP)Association Française contre les Myopathies-France(AFM Telethon No.23236 to AP)Kennedy’s Disease Association-USA(2018 grant to RC2020 grant to MG)Ministero dell’Universitàe della Ricerca(MIUR)-Italy(PRIN-Progetti di ricerca di interesse nazionale(No.2017F2A2C5 to APNo.2022EFLFL8 to APNo.2020PBS5MJ to VCNo.2022KSJZF5 to VC)PRIN-Progetti di ricerca di interesse nazionale-bando 2022,PNRR finanziato dall’Unione europea-Next Generation EU,componente M4C2,investimento 1.1(No.P2022B5J32 to RC and No.P20225R4Y5 to VC)CN3:RNA-Codice Proposta:CN_00000041Tematica Sviluppo di terapia genica e farmaci con tecnologia a RNA(Centro Nazionale di Ricerca-CN3 National Center for Gene Therapy and Drugs based on RNA Technology to AP)Progetto Dipartimenti di Eccellenza(to DiSFeB)Ministero della Salute,Agenzia Italiana del Farmaco(AIFA)-Italy(Co_ALS to AP)Universitàdegli Studi di Milano(piano di sviluppo della ricerca(PSR)UNIMI-linea B(to RC and BT).
文摘Heat shock protein family B(small)member 8(HSPB8)is a 22 kDa ubiquitously expressed protein belonging to the family of small heat shock proteins.HSPB8 is involved in various cellular mechanisms mainly related to proteotoxic stress response and in other processes such as inflammation,cell division,and migration.HSPB8 binds misfolded clients to prevent their aggregation by assisting protein refolding or degradation through chaperone-assisted selective autophagy.In line with this function,the pro-degradative activity of HSPB8 has been found protective in several neurodegenerative and neuromuscular diseases characterized by protein misfolding and aggregation.In cancer,HSPB8 has a dual role being capable of exerting either a pro-or an anti-tumoral activity depending on the pathways and factors expressed by the model of cancer under investigation.Moreover,HSPB8 exerts a protective function in different diseases by modulating the inflammatory response,which characterizes not only neurodegenerative diseases,but also other chronic or acute conditions affecting the nervous system,such as multiple sclerosis and intracerebellar hemorrhage.Of note,HSPB8 modulation may represent a therapeutic approach in other neurological conditions that develop as a secondary consequence of other diseases.This is the case of cognitive impairment related to diabetes mellitus,in which HSPB8 exerts a protective activity by assuring mitochondrial homeostasis.This review aims to summarize the diverse and multiple functions of HSPB8 in different pathological conditions,focusing on the beneficial effects of its modulation.Drug-based and alternative therapeutic approaches targeting HSPB8 and its regulated pathways will be discussed,emphasizing how new strategies for cell and tissue-specific delivery represent an avenue to advance in disease treatments.
基金supported by the National Natural Science Foundation of China(42250101)the Macao Foundation。
文摘Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these internal magnetic fields accurately,data selection based on specific criteria is often employed to minimize the influence of rapidly changing current systems in the ionosphere and magnetosphere.However,the quantitative impact of various data selection criteria on internal geomagnetic field modeling is not well understood.This study aims to address this issue and provide a reference for constructing and applying geomagnetic field models.First,we collect the latest MSS-1 and Swarm satellite magnetic data and summarize widely used data selection criteria in geomagnetic field modeling.Second,we briefly describe the method to co-estimate the core,crustal,and large-scale magnetospheric fields using satellite magnetic data.Finally,we conduct a series of field modeling experiments with different data selection criteria to quantitatively estimate their influence.Our numerical experiments confirm that without selecting data from dark regions and geomagnetically quiet times,the resulting internal field differences at the Earth’s surface can range from tens to hundreds of nanotesla(nT).Additionally,we find that the uncertainties introduced into field models by different data selection criteria are significantly larger than the measurement accuracy of modern geomagnetic satellites.These uncertainties should be considered when utilizing constructed magnetic field models for scientific research and applications.
文摘The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more efficient and reliable intrusion detection systems(IDSs).However,the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs.Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues.While most of these researchers reported the success of these preprocessing techniques on a shallow level,very few studies have been performed on their effects on a wider scale.Furthermore,the performance of an IDS model is subject to not only the utilized preprocessing techniques but also the dataset and the ML/DL algorithm used,which most of the existing studies give little emphasis on.Thus,this study provides an in-depth analysis of feature selection and normalization effects on IDS models built using three IDS datasets:NSL-KDD,UNSW-NB15,and CSE–CIC–IDS2018,and various AI algorithms.A wrapper-based approach,which tends to give superior performance,and min-max normalization methods were used for feature selection and normalization,respectively.Numerous IDS models were implemented using the full and feature-selected copies of the datasets with and without normalization.The models were evaluated using popular evaluation metrics in IDS modeling,intra-and inter-model comparisons were performed between models and with state-of-the-art works.Random forest(RF)models performed better on NSL-KDD and UNSW-NB15 datasets with accuracies of 99.86%and 96.01%,respectively,whereas artificial neural network(ANN)achieved the best accuracy of 95.43%on the CSE–CIC–IDS2018 dataset.The RF models also achieved an excellent performance compared to recent works.The results show that normalization and feature selection positively affect IDS modeling.Furthermore,while feature selection benefits simpler algorithms(such as RF),normalization is more useful for complex algorithms like ANNs and deep neural networks(DNNs),and algorithms such as Naive Bayes are unsuitable for IDS modeling.The study also found that the UNSW-NB15 and CSE–CIC–IDS2018 datasets are more complex and more suitable for building and evaluating modern-day IDS than the NSL-KDD dataset.Our findings suggest that prioritizing robust algorithms like RF,alongside complex models such as ANN and DNN,can significantly enhance IDS performance.These insights provide valuable guidance for managers to develop more effective security measures by focusing on high detection rates and low false alert rates.
基金supported by the University Salah Boubnider-Constantine 3 (Algeria).
文摘This research aims to study the bio-adsorption process of two dyes,Cibacron Green H3G(CG-H3G)and Terasil Red(TR),in a single system and to bring them closer to the industrial textile discharge by a binary mixture of two dyes(TR+CG-H3G).The Cockle Shell(CS)was used as a natural bio-adsorbent.The characterizations of CS were investigated by Fourier transform infrared(FTIR),X-ray diffraction(XRD),scanning electron microscopy(SEM),energy-dispersive X-ray spectroscopy(EDX)and Brunauer–Emmett–Teller(BET).The adsorption potential of Cockle Shells was tested in two cases(single and binary system)and determined by:contact time(0–60 min),bio-adsorption dose(3–15 g/L),initial concentration(10–300 mg/L),temperature(22–61°C)and pH solution(2–12).The study of bio-adsorption(equilibrium and kinetics)was conducted at 22°C.The kinetic studies demon-strated that a pseudo-second-order adsorption mechanism had a good correlation coefficient(R2≥0.999).The Langmuir isotherm modeling provided a well-defined description of TR and CG-H3G bio-adsorption on cockle shells,exhibiting maximum capacities of 29.41 and 3.69 mg/g respectively at 22°C.The thermodynamic study shows that the reaction between the TR,CG-H3G dyes molecules and the bio-adsorbent is exothermic,spontaneous in the range of 22–31°C with the aleatory character decrease at the solid-liquid interface.The study of selectivity in single and binary systems has been performed under optimal operating conditions using the industrial textile rejection pH(pH=6.04).CG-H3G dye is found to have a higher selectivity than TR in single(0–60 min)and binary systems with a range of 6–45 min,as shown by the selectivity measurement.It was discovered that CS has the capability to remove both CG-H3G and TR dyes in both simple and binary systems,making it a superior bio-adsorbent.
文摘Clear aligner treatment is a novel technique in current orthodontic practice.Distinct from traditional fixed orthodontic appliances,clear aligners have different material features and biomechanical characteristics and treatment efficiencies,presenting new clinical challenges.Therefore,a comprehensive and systematic description of the key clinical aspects of clear aligner treatment is essential to enhance treatment efficacy and facilitate the advancement and wide adoption of this new technique.This expert consensus discusses case selection and grading of treatment difficulty,principle of clear aligner therapy,clinical procedures and potential complications,which are crucial to the clinical success of clear aligner treatment.
基金supported by the National Natural Science Foundation of China(32160782 and 32060737).
文摘The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all ‘polygenic effects' associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359Duroc×Landrace×Yorkshire pigs from Guangxi Zhuang Autonomous Region, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed 4breeding strategies applied to different scenarios: Ⅰ, only spectral and genotypic data exist for the target population;Ⅱ, only spectral data exist for the target population;Ⅲ, only spectral and genotypic data but with different prediction processes exist for the target population;and Ⅳ, only spectral and phenotypic data exist for the target population.The 4 scenarios were used to evaluate the genomic estimated breeding value(GEBV) accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies Ⅱ, Ⅲ, and Ⅳ was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2, 40.8 and 15.5%, respectively on average. Among them, the prediction accuracy of Strategy Ⅱ for fat(%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy Ⅰ was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the 4 strategies was lower than that of traditional GS methods, with Strategy Ⅳ being the lowest as it did not require genotyping.Our findings demonstrate that GS methods based on VIS/NIRS data have significant predictive potential and are worthy of further research to provide a valuable reference for the development of effective and affordable breeding strategies.
基金Supported by Shanghai 2020“Science and Technology Innovation Action Plan”Medical Innovation Research Special Program:20Y21902800Shanghai Municipal Health Commission Shanghai Three-Year Action Plan to Further Accelerate the Development of Traditional Chinese Medicine Inheritance and Innovation:ZY(2021-2023)−0302)+1 种基金Shanghai Key Specialty(Acupuncture)Construction Project:shslczdzk04701Shanghai 2024"Science and Technology Innovation Action Plan"star cultivation(Sail special):24YF2740600.
文摘Transcutaneous electrical acupoint stimulation(TEAS)is a kind of physical therapy that use electric cur-rent through the electrodes placed on the surface of acupoints to produce clinical effects in the human body,which is characterized by less adverse reaction and convenient operation.It has been widely used in the treatment of various diseases.This review introduces six major clinical applications of TEAS,named analgesia,regulation of gastrointestinal function,improvement of reproductive function,enhancement of cognitive function,promotion of limb function recovery and relief of fatigue.Besides,TEAS has been ap-plied to the treatment of other chronic diseases such as hypertension and diabetes,achieving satisfactory clinical effects.However,two crucial challenges are encountered in the development of TEAS.One is the lack of standardization in the selection of parameters such as waveform,frequency,intensity and stimula-tion duration.The other is the limitation on the flexibility in the acupoint selection.This review analyzes key issues that need to be addressed in the current clinical application of TEAS,such as the selection of parameters and acupoints,and this review provides a certain reference value for optimizing regimens of TEAS and promoting its development and application.
基金funded by the Natural Science Foundation of China(Grant Nos.42377164 and 41972280)the Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202305).
文摘Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA28110300)National Natural Science Foundation of China(No.U23A2004)+3 种基金Natural Science Foundation of Jilin Province,China(No.YDZJ202201ZYTS522)Science and Technology Cooperation Program between Jilin Province and Chinese Academy of Sciences(No.2023SYHZ0053)Innovation Team Program of Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences(No.2023CXTD02)the European Commission under Marie Sk?odowska-Curie(No.101034371)。
文摘Nitrogen(N)enrichment has resulted in widespread alteration of grassland ecosystem processes and functions mainly through disturbance in soil enzyme activities.However,we lack a comprehensive understanding of how N deposition affects specific key soil enzymes that mediate plant-soil feedback of grassland.Here,with a meta-analysis on 1446 cases from field observations in China,we show that N deposition differently affects soil enzymes associated with soil biochemical processes.Specifically,N-promoted C,N,and P-acquiring hydrolase activities significantly increased by 8.73%,7.67%,and 8.69%,respectively,related to an increase in microbial-specific enzyme secretion.The increased relative N availability and soil acidification were two potential mechanisms accounting for the changes in soil enzyme activities with N enrichment.The mixed N addition in combination of NH_(4)NO_(3) and urea showed greater stimulation effect on soil enzyme activities.However,the high rate and long-term N addition tended to weaken the positive responses of soil C-,Nand P-acquiring hydrolase activities to N enrichment.Spatially increased mean annual precipitation and temperature primarily promoted the positive effects of N enrichment on N-and P-acquiring hydrolase activities,and the stimulation of C-and N-acquiring hydrolase activities by N enrichment was intensified with the increase in soil depth.Finally,multimodal inference showed that grassland type was the most important regulator of responses of microbial C,N,and P-acquiring hydrolase activities to N enrichment.This meta-analysis provides a comprehensive insight into understanding the key role of N enrichment in shaping soil enzyme activities of grassland ecosystems.
基金supports by the National Natural Science Foundation of China(Nos.82201135)"2015"Cultivation Program for Reserve Talents for Academic Leaders of Nanjing Stomatological School,Medical School of Nanjing University(No.0223A204).
文摘Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.