Asian rice comprises two major subspecies:Xian(X)and Geng(G),and the diverged resistance genes(R)have provided a foundation for breeding improved cultivars to control rice blast disease.After conducting two-phase alle...Asian rice comprises two major subspecies:Xian(X)and Geng(G),and the diverged resistance genes(R)have provided a foundation for breeding improved cultivars to control rice blast disease.After conducting two-phase allele mining using six updated FNP marker systems,the functional haplotypes at Pit,Pib,and Pi63 strictly diverged into the X-populations and were defined as X-R loci,while those at Pi54,Pi37,and Pi36 into the G-populations as G-R loci.The genic diversity at the three X-R loci(16 alleles)was twofold higher than that at the three G-R loci(8 alleles),and the allelic diversity in the Southern region(21 alleles)was nearly double that in the Northeastern region(11 alleles).Both observations reflect a significant difference in genetic diversity between X-and G-populations,and indicate that the effective R-genes mainly originated from X-subspecies.Based on the allelic structures characterized by a set of 10 parameters,8 and 16 alleles were respectively recognized as favorable and promising ones for the regional breeding programs.The genotypic structures of the two regional populations were almost different,indicating that the diverged alleles have been further assembled into two series of regional genotypes through long-term breeding programs,despite the presence of one-third of region-common alleles.The genotypic diversity in the Southern region(55 genotypes)was nearly twice as high as that in the Northeastern region(28),which perfectly reflects the aforementioned differences in both genic and allelic diversities.After analyzing the genotypic structures using a set of 13 parameters,4 and 23 genotypes,respectively,can be recommended as the favorable and promising ones for the regional breeding programs.The case study serves as a concrete sample of how to identify the favorable and promising alleles and genotypes,and beneficial parents based their comprehensive population structures for gene-designed breeding.展开更多
In this study,we developed a single-beam optical trap-based surface-enhanced Raman scattering(SERS)optofluidic molecular fingerprint spectroscopy detection system.This system utilizes a single-beam optical trap to con...In this study,we developed a single-beam optical trap-based surface-enhanced Raman scattering(SERS)optofluidic molecular fingerprint spectroscopy detection system.This system utilizes a single-beam optical trap to concentrate free silver nanoparticles(AgNPs)within an optofluidic chip,significantly enhancing SERS performance.We investigated the optical field distribution characteristics within the tapered fiber using COMSOL simulation software and established a MATLAB simulation model to validate the single-beam optical trap's effectiveness in capturing AgNPs,demonstrating the theoretical feasibility of our approach.To verify the particle capture efficacy of the system,we experimentally controlled the optical trap's on-off state to manage the capture and release of particles precisely.The experimental results indicated that the Raman signal intensity in the capture state was significantly higher than in the non-capture state,confirming that the single-beam optical trap effectively enhances the SERS detection capability of the optofluidic detection system.Furthermore,we employed Raman mapping techniques to investigate the impact of the capture area on the SERS effect,revealing that the spectral intensity of molecular fingerprints in the laser-trapping region is significantly improved.We successfully detected the Raman spectrum of crystal violet at a concentration of 10^(−9)mol/L and pesticide thiram at a concentration of 10^(−5)mol/L,further demonstrating the ability of the single-beam optical trap in enhancing the molecular fingerprint spectrum identification capability of the SERS optofluidic chips.The optical trapping SERS optofluidic detection system developed in this study,as a key component of an integrated optoelectronic sensing system,holds the potential for integration with portable high-power lasers and high-performance Raman spectrometers.This integration is expected to advance highly integrated technologies and significantly enhance the overall performance and portability of optoelectronic sensing systems.展开更多
Anion-exchange membrane water electrolyzers(AEMWEs)for green hydrogen production have received intensive attention due to their feasibility of using earth-abundant NiFe-based catalysts.By introducing a third metal int...Anion-exchange membrane water electrolyzers(AEMWEs)for green hydrogen production have received intensive attention due to their feasibility of using earth-abundant NiFe-based catalysts.By introducing a third metal into NiFe-based catalysts to construct asymmetrical M-NiFe units,the d-orbital and electronic structures can be adjusted,which is an important strategy to achieve sufficient oxygen evolution reaction(OER)performance in AEMWEs.Herein,the ternary NiFeM(M:La,Mo)catalysts featured with distinct M-NiFe units and varying d-orbitals are reported in this work.Experimental and theoretical calculation results reveal that the doping of La leads to optimized hybridization between d orbital in NiFeM and 2p in oxygen,resulting in enhanced adsorption strength of oxygen intermediates,and reduced rate-determining step energy barrier,which is responsible for the enhanced OER performance.More critically,the obtained NiFeLa catalyst only requires 1.58 V to reach 1 A cm^(−2) in an anion exchange membrane electrolyzer and demonstrates excellent long-term stability of up to 600 h.展开更多
With the deepening of epigenetic research,studies have shown that N6-methyladenosine(m^(6)A)is closely related to the development of rheumatoid arthritis(RA),but the mechanism is still unclear.In the study,we collecte...With the deepening of epigenetic research,studies have shown that N6-methyladenosine(m^(6)A)is closely related to the development of rheumatoid arthritis(RA),but the mechanism is still unclear.In the study,we collected synovial tissues from normal controls and patients with osteoarthritis(OA)or RA.The levels of m^(6)A and inflammation were analyzed by immunofluorescence staining and western blotting.The roles of IGF2BP3 in cell proliferation and inflammatory activation were explored using transfection and RNA immunoprecipitation assays.IGF2BP3^(−/−)mice were generated and used to establish an arthritis mouse model by transferring serum from adult arthritis K/BxN mice.We found m^(6)A levels were markedly increased in RA patients and mouse models,and the expression of IGF2BP3 was upregulated in individuals with RA and related to the levels of inflammatory markers.IGF2BP3 played an important part in RA-fibroblast-like synoviocytes(FLS)by promoting cell proliferation,migration,invasion,inflammatory cytokine release and inhibiting autophagy.In addition,IGF2BP3 inhibited autophagy to reduce ROS production,thereby decreasing the inflammatory activation of macrophages.More importantly,RASGRF1-mediated mTORC1 activation played a crucial role in the ability of IGF2BP3 to promote cell proliferation and inflammatory activation.In an arthritis model of IGF2BP3^(−/−)mice,IGF2BP3 knockout inhibited RA-FLS proliferation and inflammatory infiltration,and further ameliorated RA joint injury.Our study revealed an important role for IGF2BP3 in RA progression.The targeted inhibition of IGF2BP3 reduced cell proliferation and inflammatory activation and limited RA development,providing a potential strategy for RA therapy.展开更多
Rheumatoid arthritis(RA)is a progressive autoimmune disease characterized by bone destruction that is primarily caused by the overactivation of osteoclasts(OCs),which are critical therapeutic targets.Triptolide(TP)has...Rheumatoid arthritis(RA)is a progressive autoimmune disease characterized by bone destruction that is primarily caused by the overactivation of osteoclasts(OCs),which are critical therapeutic targets.Triptolide(TP)has strong anti-RA effects but is limited by its narrow therapeutic window and associated toxicity,necessitating combination therapy to increase its efficacy and reduce side effects.Medicarpin(Med),a flavonoid with anti-inflammatory and anti-bone destruction properties,has shown potential in reducing osteoclastogenesis.However,the mechanisms underlying the synergistic effects of TP and Med on RA treatment remain unclear.We addressed this issue by evaluating the effects of TP,Med,and their combination on a collagen-induced arthritis(CIA)rat model,with a focus on bone erosion as the primary research endpoint.We subsequently performed experimental validation in an in vitro OC dif-ferentiation model to assess the impacts of these treatments on OC formation and function.Based on polymerase chain reaction(PCR)microarray data from RA patients,further investigations focused on N^(6)-methyladenosine(m^(6)A)methylation and its regulatory factors,methyltransferase-like 3(METTL3)and YT521-B homology domain family protein 1(YTHDF1),which have been identified as potential tar-gets of TP and Med.Key findings revealed that the TP and Med combination significantly alleviated bone destruction and inhibited OC differentiation,exerting stronger effects at lower doses than either drug alone.Mechanistically,TP and Med synergistically modulated METTL3 and YTHDF1 to suppress osteo-clastogenesis through distinct m6 A methylation pathways,contributing to the mitigation of RA-associated bone destruction.Overall,our data highlight the potential of the m^(6)A modification as a ther-apeutic mechanism for the combined use of TP and Med for RA treatment,providing a theoretical basis for the clinical application of herbal active ingredient combinations.展开更多
BACKGROUND Acute variceal bleeding(AVB)in patients with cirrhosis remains life-threatening;moreover,the current risk stratification methods have certain limitations.Rebleeding and mortality after AVB remain major chal...BACKGROUND Acute variceal bleeding(AVB)in patients with cirrhosis remains life-threatening;moreover,the current risk stratification methods have certain limitations.Rebleeding and mortality after AVB remain major challenges.Although preemptive transjugular intrahepatic portosystemic shunt(p-TIPS)can improve outcomes,not all patients benefit equally.Accurate risk stratification is needed to guide treatment decisions and identify those most likely to benefit from p-TIPS.AIM To develop an artificial intelligence(AI)-driven model to guide AVB treatment decisions,and identify candidates eligible for p-TIPS.METHODS Patients with cirrhosis and AVB,from two multicenter retrospective cohorts in China,who received endoscopic variceal ligation plus pharmacotherapy(n=1227)or p-TIPS(n=1863)were included.Baseline data within 24 hours of hospital admission were obtained.The AI-AVB model,based on the six-week failure and one-year mortality rates,was developed to predict treatment efficacy and compared with standard risk scores.Outcomes and adverse events of the treatments were compared across the high-and low-risk subgroups stratified using the AI-AVB model.RESULTS The AI-AVB model demonstrated superior predictive performance compared to traditional risk stratification methods.In the internal validation cohort,the model achieved an area under the curve(AUC)of 0.842 for predicting six-week treatment failure and 0.954 for one-year mortality.In the external validation cohort,the AUCs were 0.814 and 0.889,respectively.The model effectively identified patients at high risk of first-line treatment failure who may benefit from aggressive interventions such as p-TIPS.In contrast,advancing the treatment strategy for low-risk patients did not notably improve the short-term prognosis.CONCLUSION The AI-AVB model can predict treatment outcomes,stratify the failure risk in cirrhotic patients with AVB,aid in clinical decisions,identify p-TIPS beneficiaries,and optimize personalized treatment strategies.展开更多
Two novel skeleton sesquiterpenoids(1 and 6),along with four new iphionane-type sesquiterpenes(2−5)and six new cyperane-type sesquiterpenes(7−11),were isolated from the whole plant of Artemisia hedinii(A.hedinii).The ...Two novel skeleton sesquiterpenoids(1 and 6),along with four new iphionane-type sesquiterpenes(2−5)and six new cyperane-type sesquiterpenes(7−11),were isolated from the whole plant of Artemisia hedinii(A.hedinii).The two novel skeleton compounds(1 and 6)were derived from the decarbonization of iphionane and cyperane-type sesquiterpenes,respectively.Their structures were elucidated through a comprehensive analysis of spectroscopic data,including high-resolution electrospray ionization mass spectrometry(HR-ESI-MS)and 1D and 2D nuclear magnetic resonance(NMR)spectra.The absolute configurations were determined using electronic circular dichroism(ECD)spectra,single-crystal X-ray crystallographic analyses,time-dependent density functional theory(TDDFT)ECD calculation,density functional theory(DFT)NMR calculations,and biomimetic syntheses.The biomimetic syntheses of the two novel skeletons(1 and 6)were inspired by potential biogenetic pathways,utilizing a predominant eudesmane-type sesquiterpene(A)in A.hedinii as the substrate.All compounds were evaluated in LX-2 cells for their anti-hepatic fibrosis activity.Compounds 2,8,and 10 exhibited significant activity in downregulating the expression ofα-smooth muscle actin(α-SMA),a protein involved in hepatic fibrosis.展开更多
Multiple sclerosis (MS) is characterized by chronic,slowly expanding lesions with the accumulation of myeloid cells,which lead to brain atrophy and progressive disability.The role of mitochondria,especially mitochondr...Multiple sclerosis (MS) is characterized by chronic,slowly expanding lesions with the accumulation of myeloid cells,which lead to brain atrophy and progressive disability.The role of mitochondria,especially mitochondrial respiratory complexes and metabolites,in controlling myeloid immune responses,is well-documented but not fully understood in diseases of the central nervous system (CNS).The groundbreaking study by Prof.Peruzzotti-Jametti et al.[1],entitled"Mitochondrial complexⅠactivity in microglia sustains neuroinflammation"published in Nature,delves into the intricate dynamics between mitochondrial function within microglia and the perpetuation of chronic neuroinflammation,specifically in MS.The core point of their investigation is the hypothesis that mitochondrial complexⅠ(CI) activity,through a mechanism known as reverse electron transport (RET),generates reactive oxygen species (ROS) in microglia,thereby sustaining inflammatory response in the CNS.This increases ROS production from the mitochondria,which is thought to be a crucial factor in the maintenance of a pro-inflammatory state in the microglia,contributing to the pathology of MS and similar neuroinflammatory diseases.展开更多
Feature selection(FS)is essential in machine learning(ML)and data mapping by its ability to preprocess high-dimensional data.By selecting a subset of relevant features,feature selection cuts down on the dimension of t...Feature selection(FS)is essential in machine learning(ML)and data mapping by its ability to preprocess high-dimensional data.By selecting a subset of relevant features,feature selection cuts down on the dimension of the data.It excludes irrelevant or surplus features,thus boosting the performance and efficiency of the model.Particle Swarm Optimization(PSO)boasts a streamlined algorithmic framework and exhibits rapid convergence traits.Compared with other algorithms,it incurs reduced computational expenses when tackling high-dimensional datasets.However,PSO faces challenges like inadequate convergence precision.Therefore,regarding FS problems,this paper presents a binary version enhanced PSO based on the Support Vector Machines(SVM)classifier.First,the Sand Cat Swarm Optimization(SCSO)is added to enhance the global search capability of PSO and improve the accuracy of the solution.Secondly,the Latin hypercube sampling strategy initializes populations more uniformly and helps to increase population diversity.The last is the roundup search strategy introducing the grey wolf hierarchy idea to help improve convergence speed.To verify the capability of Self-adaptive Cooperative Particle Swarm Optimization(SCPSO),the CEC2020 test suite and CEC2022 test suite are selected for experiments and applied to three engineering problems.Compared with the standard PSO algorithm,SCPSO converges faster,and the convergence accuracy is significantly improved.Moreover,SCPSO’s comprehensive performance far exceeds that of other algorithms.Six datasets from the University of California,Irvine(UCI)database were selected to evaluate SCPSO’s effectiveness in solving feature selection problems.The results indicate that SCPSO has significant potential for addressing these problems.展开更多
Contact detection is the most time-consuming stage in 3D discontinuous deformation analysis(3D-DDA)computation.Improving the efficiency of 3D-DDA is beneficial for its application in large-scale computing.In this stud...Contact detection is the most time-consuming stage in 3D discontinuous deformation analysis(3D-DDA)computation.Improving the efficiency of 3D-DDA is beneficial for its application in large-scale computing.In this study,aiming at the continuous-discontinuous simulation of 3D-DDA,a highly efficient contact detection strategy is proposed.Firstly,the global direct search(GDS)method is integrated into the 3D-DDA framework to address intricate contact scenarios.Subsequently,all geometric elements,including blocks,faces,edges,and vertices are divided into searchable and unsearchable parts.Contacts between unsearchable geometric elements would be directly inherited,while only searchable geometric elements are involved in contact detection.This strategy significantly reduces the number of geometric elements involved in contact detection,thereby markedly enhancing the computation efficiency.Several examples are adopted to demonstrate the accuracy and efficiency of the improved 3D-DDA method.The rock pillars with different mesh sizes are simulated under self-weight.The deformation and stress are consistent with the analytical results,and the smaller the mesh size,the higher the accuracy.The maximum speedup ratio is 38.46 for this case.Furthermore,the Brazilian splitting test on the discs with different flaws is conducted.The results show that the failure pattern of the samples is consistent with the results obtained by other methods and experiments,and the maximum speedup ratio is 266.73.Finally,a large-scale impact test is performed,and approximately 3.2 times enhanced efficiency is obtained.The proposed contact detection strategy significantly improves efficiency when the rock has not completely failed,which is more suitable for continuous-discontinuous simulation.展开更多
基金funded by grants from the National Key R&D Project(2023YFD1400201-02,2023YFD1400203-02)the National Natural Science Foundation of China(31870137)+1 种基金the National Transgenic Research Project(2015ZX08001-002)the Key R&D Project of Guangdong Province(2022B0202060005).
文摘Asian rice comprises two major subspecies:Xian(X)and Geng(G),and the diverged resistance genes(R)have provided a foundation for breeding improved cultivars to control rice blast disease.After conducting two-phase allele mining using six updated FNP marker systems,the functional haplotypes at Pit,Pib,and Pi63 strictly diverged into the X-populations and were defined as X-R loci,while those at Pi54,Pi37,and Pi36 into the G-populations as G-R loci.The genic diversity at the three X-R loci(16 alleles)was twofold higher than that at the three G-R loci(8 alleles),and the allelic diversity in the Southern region(21 alleles)was nearly double that in the Northeastern region(11 alleles).Both observations reflect a significant difference in genetic diversity between X-and G-populations,and indicate that the effective R-genes mainly originated from X-subspecies.Based on the allelic structures characterized by a set of 10 parameters,8 and 16 alleles were respectively recognized as favorable and promising ones for the regional breeding programs.The genotypic structures of the two regional populations were almost different,indicating that the diverged alleles have been further assembled into two series of regional genotypes through long-term breeding programs,despite the presence of one-third of region-common alleles.The genotypic diversity in the Southern region(55 genotypes)was nearly twice as high as that in the Northeastern region(28),which perfectly reflects the aforementioned differences in both genic and allelic diversities.After analyzing the genotypic structures using a set of 13 parameters,4 and 23 genotypes,respectively,can be recommended as the favorable and promising ones for the regional breeding programs.The case study serves as a concrete sample of how to identify the favorable and promising alleles and genotypes,and beneficial parents based their comprehensive population structures for gene-designed breeding.
基金financial supports from National Natural Science Foundation of China(62175023).
文摘In this study,we developed a single-beam optical trap-based surface-enhanced Raman scattering(SERS)optofluidic molecular fingerprint spectroscopy detection system.This system utilizes a single-beam optical trap to concentrate free silver nanoparticles(AgNPs)within an optofluidic chip,significantly enhancing SERS performance.We investigated the optical field distribution characteristics within the tapered fiber using COMSOL simulation software and established a MATLAB simulation model to validate the single-beam optical trap's effectiveness in capturing AgNPs,demonstrating the theoretical feasibility of our approach.To verify the particle capture efficacy of the system,we experimentally controlled the optical trap's on-off state to manage the capture and release of particles precisely.The experimental results indicated that the Raman signal intensity in the capture state was significantly higher than in the non-capture state,confirming that the single-beam optical trap effectively enhances the SERS detection capability of the optofluidic detection system.Furthermore,we employed Raman mapping techniques to investigate the impact of the capture area on the SERS effect,revealing that the spectral intensity of molecular fingerprints in the laser-trapping region is significantly improved.We successfully detected the Raman spectrum of crystal violet at a concentration of 10^(−9)mol/L and pesticide thiram at a concentration of 10^(−5)mol/L,further demonstrating the ability of the single-beam optical trap in enhancing the molecular fingerprint spectrum identification capability of the SERS optofluidic chips.The optical trapping SERS optofluidic detection system developed in this study,as a key component of an integrated optoelectronic sensing system,holds the potential for integration with portable high-power lasers and high-performance Raman spectrometers.This integration is expected to advance highly integrated technologies and significantly enhance the overall performance and portability of optoelectronic sensing systems.
基金financially supported by the National Natural Science Foundation of China(22309137,22279095)Open subject project State Key Laboratory of New Textile Materials and Advanced Processing Technologies(FZ2023001).
文摘Anion-exchange membrane water electrolyzers(AEMWEs)for green hydrogen production have received intensive attention due to their feasibility of using earth-abundant NiFe-based catalysts.By introducing a third metal into NiFe-based catalysts to construct asymmetrical M-NiFe units,the d-orbital and electronic structures can be adjusted,which is an important strategy to achieve sufficient oxygen evolution reaction(OER)performance in AEMWEs.Herein,the ternary NiFeM(M:La,Mo)catalysts featured with distinct M-NiFe units and varying d-orbitals are reported in this work.Experimental and theoretical calculation results reveal that the doping of La leads to optimized hybridization between d orbital in NiFeM and 2p in oxygen,resulting in enhanced adsorption strength of oxygen intermediates,and reduced rate-determining step energy barrier,which is responsible for the enhanced OER performance.More critically,the obtained NiFeLa catalyst only requires 1.58 V to reach 1 A cm^(−2) in an anion exchange membrane electrolyzer and demonstrates excellent long-term stability of up to 600 h.
基金supported by the National Natural Science Foundation of China(U22A20374,52373273)National High Level Hospital Clinical Research Funding of China-Japan Friendship Hospital(Grant number:2024-NHLHCRF-JBGSWZ-02).
文摘With the deepening of epigenetic research,studies have shown that N6-methyladenosine(m^(6)A)is closely related to the development of rheumatoid arthritis(RA),but the mechanism is still unclear.In the study,we collected synovial tissues from normal controls and patients with osteoarthritis(OA)or RA.The levels of m^(6)A and inflammation were analyzed by immunofluorescence staining and western blotting.The roles of IGF2BP3 in cell proliferation and inflammatory activation were explored using transfection and RNA immunoprecipitation assays.IGF2BP3^(−/−)mice were generated and used to establish an arthritis mouse model by transferring serum from adult arthritis K/BxN mice.We found m^(6)A levels were markedly increased in RA patients and mouse models,and the expression of IGF2BP3 was upregulated in individuals with RA and related to the levels of inflammatory markers.IGF2BP3 played an important part in RA-fibroblast-like synoviocytes(FLS)by promoting cell proliferation,migration,invasion,inflammatory cytokine release and inhibiting autophagy.In addition,IGF2BP3 inhibited autophagy to reduce ROS production,thereby decreasing the inflammatory activation of macrophages.More importantly,RASGRF1-mediated mTORC1 activation played a crucial role in the ability of IGF2BP3 to promote cell proliferation and inflammatory activation.In an arthritis model of IGF2BP3^(−/−)mice,IGF2BP3 knockout inhibited RA-FLS proliferation and inflammatory infiltration,and further ameliorated RA joint injury.Our study revealed an important role for IGF2BP3 in RA progression.The targeted inhibition of IGF2BP3 reduced cell proliferation and inflammatory activation and limited RA development,providing a potential strategy for RA therapy.
基金supported by the National Natural Science Foundation of China(U22A20374).
文摘Rheumatoid arthritis(RA)is a progressive autoimmune disease characterized by bone destruction that is primarily caused by the overactivation of osteoclasts(OCs),which are critical therapeutic targets.Triptolide(TP)has strong anti-RA effects but is limited by its narrow therapeutic window and associated toxicity,necessitating combination therapy to increase its efficacy and reduce side effects.Medicarpin(Med),a flavonoid with anti-inflammatory and anti-bone destruction properties,has shown potential in reducing osteoclastogenesis.However,the mechanisms underlying the synergistic effects of TP and Med on RA treatment remain unclear.We addressed this issue by evaluating the effects of TP,Med,and their combination on a collagen-induced arthritis(CIA)rat model,with a focus on bone erosion as the primary research endpoint.We subsequently performed experimental validation in an in vitro OC dif-ferentiation model to assess the impacts of these treatments on OC formation and function.Based on polymerase chain reaction(PCR)microarray data from RA patients,further investigations focused on N^(6)-methyladenosine(m^(6)A)methylation and its regulatory factors,methyltransferase-like 3(METTL3)and YT521-B homology domain family protein 1(YTHDF1),which have been identified as potential tar-gets of TP and Med.Key findings revealed that the TP and Med combination significantly alleviated bone destruction and inhibited OC differentiation,exerting stronger effects at lower doses than either drug alone.Mechanistically,TP and Med synergistically modulated METTL3 and YTHDF1 to suppress osteo-clastogenesis through distinct m6 A methylation pathways,contributing to the mitigation of RA-associated bone destruction.Overall,our data highlight the potential of the m^(6)A modification as a ther-apeutic mechanism for the combined use of TP and Med for RA treatment,providing a theoretical basis for the clinical application of herbal active ingredient combinations.
基金Supported by Key Research and Development Program of Jiangsu Province,No.BE2023767Xuzhou Key Research and Development Program under Grant,No.KC23273+1 种基金Affiliated Hospital of Xuzhou Medical University,No.2022ZL26Construction Project of High-Level Hospital of Jiangsu Province,No.GSPSJ20240802.
文摘BACKGROUND Acute variceal bleeding(AVB)in patients with cirrhosis remains life-threatening;moreover,the current risk stratification methods have certain limitations.Rebleeding and mortality after AVB remain major challenges.Although preemptive transjugular intrahepatic portosystemic shunt(p-TIPS)can improve outcomes,not all patients benefit equally.Accurate risk stratification is needed to guide treatment decisions and identify those most likely to benefit from p-TIPS.AIM To develop an artificial intelligence(AI)-driven model to guide AVB treatment decisions,and identify candidates eligible for p-TIPS.METHODS Patients with cirrhosis and AVB,from two multicenter retrospective cohorts in China,who received endoscopic variceal ligation plus pharmacotherapy(n=1227)or p-TIPS(n=1863)were included.Baseline data within 24 hours of hospital admission were obtained.The AI-AVB model,based on the six-week failure and one-year mortality rates,was developed to predict treatment efficacy and compared with standard risk scores.Outcomes and adverse events of the treatments were compared across the high-and low-risk subgroups stratified using the AI-AVB model.RESULTS The AI-AVB model demonstrated superior predictive performance compared to traditional risk stratification methods.In the internal validation cohort,the model achieved an area under the curve(AUC)of 0.842 for predicting six-week treatment failure and 0.954 for one-year mortality.In the external validation cohort,the AUCs were 0.814 and 0.889,respectively.The model effectively identified patients at high risk of first-line treatment failure who may benefit from aggressive interventions such as p-TIPS.In contrast,advancing the treatment strategy for low-risk patients did not notably improve the short-term prognosis.CONCLUSION The AI-AVB model can predict treatment outcomes,stratify the failure risk in cirrhotic patients with AVB,aid in clinical decisions,identify p-TIPS beneficiaries,and optimize personalized treatment strategies.
基金supported from the National Natural Science Foundation of China(No.21920102003)the Key-Area Research and Development Program of Guangdong Province(No.2020B0303070002)the National Key R&D Program“Strategic Scientific and Technological Innovation Cooperation”Key Project(No.2022YFE0203600).
文摘Two novel skeleton sesquiterpenoids(1 and 6),along with four new iphionane-type sesquiterpenes(2−5)and six new cyperane-type sesquiterpenes(7−11),were isolated from the whole plant of Artemisia hedinii(A.hedinii).The two novel skeleton compounds(1 and 6)were derived from the decarbonization of iphionane and cyperane-type sesquiterpenes,respectively.Their structures were elucidated through a comprehensive analysis of spectroscopic data,including high-resolution electrospray ionization mass spectrometry(HR-ESI-MS)and 1D and 2D nuclear magnetic resonance(NMR)spectra.The absolute configurations were determined using electronic circular dichroism(ECD)spectra,single-crystal X-ray crystallographic analyses,time-dependent density functional theory(TDDFT)ECD calculation,density functional theory(DFT)NMR calculations,and biomimetic syntheses.The biomimetic syntheses of the two novel skeletons(1 and 6)were inspired by potential biogenetic pathways,utilizing a predominant eudesmane-type sesquiterpene(A)in A.hedinii as the substrate.All compounds were evaluated in LX-2 cells for their anti-hepatic fibrosis activity.Compounds 2,8,and 10 exhibited significant activity in downregulating the expression ofα-smooth muscle actin(α-SMA),a protein involved in hepatic fibrosis.
基金supported by the Taishan Scholars Program of Shandong Province(tsqn202312344).
文摘Multiple sclerosis (MS) is characterized by chronic,slowly expanding lesions with the accumulation of myeloid cells,which lead to brain atrophy and progressive disability.The role of mitochondria,especially mitochondrial respiratory complexes and metabolites,in controlling myeloid immune responses,is well-documented but not fully understood in diseases of the central nervous system (CNS).The groundbreaking study by Prof.Peruzzotti-Jametti et al.[1],entitled"Mitochondrial complexⅠactivity in microglia sustains neuroinflammation"published in Nature,delves into the intricate dynamics between mitochondrial function within microglia and the perpetuation of chronic neuroinflammation,specifically in MS.The core point of their investigation is the hypothesis that mitochondrial complexⅠ(CI) activity,through a mechanism known as reverse electron transport (RET),generates reactive oxygen species (ROS) in microglia,thereby sustaining inflammatory response in the CNS.This increases ROS production from the mitochondria,which is thought to be a crucial factor in the maintenance of a pro-inflammatory state in the microglia,contributing to the pathology of MS and similar neuroinflammatory diseases.
基金supported by the Fundamental Research Funds for the Central Universities of China(No.300102122105)the Natural Science Basic Research Plan in Shaanxi Province of China(2023-JC-YB-023).
文摘Feature selection(FS)is essential in machine learning(ML)and data mapping by its ability to preprocess high-dimensional data.By selecting a subset of relevant features,feature selection cuts down on the dimension of the data.It excludes irrelevant or surplus features,thus boosting the performance and efficiency of the model.Particle Swarm Optimization(PSO)boasts a streamlined algorithmic framework and exhibits rapid convergence traits.Compared with other algorithms,it incurs reduced computational expenses when tackling high-dimensional datasets.However,PSO faces challenges like inadequate convergence precision.Therefore,regarding FS problems,this paper presents a binary version enhanced PSO based on the Support Vector Machines(SVM)classifier.First,the Sand Cat Swarm Optimization(SCSO)is added to enhance the global search capability of PSO and improve the accuracy of the solution.Secondly,the Latin hypercube sampling strategy initializes populations more uniformly and helps to increase population diversity.The last is the roundup search strategy introducing the grey wolf hierarchy idea to help improve convergence speed.To verify the capability of Self-adaptive Cooperative Particle Swarm Optimization(SCPSO),the CEC2020 test suite and CEC2022 test suite are selected for experiments and applied to three engineering problems.Compared with the standard PSO algorithm,SCPSO converges faster,and the convergence accuracy is significantly improved.Moreover,SCPSO’s comprehensive performance far exceeds that of other algorithms.Six datasets from the University of California,Irvine(UCI)database were selected to evaluate SCPSO’s effectiveness in solving feature selection problems.The results indicate that SCPSO has significant potential for addressing these problems.
基金financially supported by the National Key R&D Program of China(Grant No.2023YFC3081200)the National Natural Science Foundation of China(Grant Nos.U21A20159 and 52179117).
文摘Contact detection is the most time-consuming stage in 3D discontinuous deformation analysis(3D-DDA)computation.Improving the efficiency of 3D-DDA is beneficial for its application in large-scale computing.In this study,aiming at the continuous-discontinuous simulation of 3D-DDA,a highly efficient contact detection strategy is proposed.Firstly,the global direct search(GDS)method is integrated into the 3D-DDA framework to address intricate contact scenarios.Subsequently,all geometric elements,including blocks,faces,edges,and vertices are divided into searchable and unsearchable parts.Contacts between unsearchable geometric elements would be directly inherited,while only searchable geometric elements are involved in contact detection.This strategy significantly reduces the number of geometric elements involved in contact detection,thereby markedly enhancing the computation efficiency.Several examples are adopted to demonstrate the accuracy and efficiency of the improved 3D-DDA method.The rock pillars with different mesh sizes are simulated under self-weight.The deformation and stress are consistent with the analytical results,and the smaller the mesh size,the higher the accuracy.The maximum speedup ratio is 38.46 for this case.Furthermore,the Brazilian splitting test on the discs with different flaws is conducted.The results show that the failure pattern of the samples is consistent with the results obtained by other methods and experiments,and the maximum speedup ratio is 266.73.Finally,a large-scale impact test is performed,and approximately 3.2 times enhanced efficiency is obtained.The proposed contact detection strategy significantly improves efficiency when the rock has not completely failed,which is more suitable for continuous-discontinuous simulation.
