Artificial intelligence(AI)is significantly advancing precision medicine,particularly in the fields of immunogenomics,radiomics,and pathomics.In immunogenomics,AI can process vast amounts of genomic and multi-omic dat...Artificial intelligence(AI)is significantly advancing precision medicine,particularly in the fields of immunogenomics,radiomics,and pathomics.In immunogenomics,AI can process vast amounts of genomic and multi-omic data to identify biomarkers associated with immunotherapy responses and disease prognosis,thus providing strong support for personalized treatments.In radiomics,AI can analyze high-dimensional features from computed tomography(CT),magnetic resonance imaging(MRI),and positron emission tomography/computed tomography(PET/CT)images to discover imaging biomarkers associated with tumor heterogeneity,treatment response,and disease progression,thereby enabling non-invasive,real-time assessments for personalized therapy.Pathomics leverages AI for deep analysis of digital pathology images,and can uncover subtle changes in tissue microenvironments,cellular characteristics,and morphological features,and offer unique insights into immunotherapy response prediction and biomarker discovery.These AI-driven technologies not only enhance the speed,accuracy,and robustness of biomarker discovery but also significantly improve the precision,personalization,and effectiveness of clinical treatments,and are driving a shift from empirical to precision medicine.Despite challenges such as data quality,model interpretability,integration of multi-modal data,and privacy protection,the ongoing advancements in AI,coupled with interdisciplinary collaboration,are poised to further enhance AI’s roles in biomarker discovery and immunotherapy response prediction.These improvements are expected to lead to more accurate,personalized treatment strategies and ultimately better patient outcomes,marking a significant step forward in the evolution of precision medicine.展开更多
In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture,multi-level deployment in a complex network environment will lead to high inves...In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture,multi-level deployment in a complex network environment will lead to high investment in software and hardware and cannot achieve intensive multi-level deployment.This paper realizes the goal of system scalability by introducing micro service architecture and technology stack and realizes the goal of resource intensification by introducing the idea of a data forwarding agent.The designed architecture scheme has been practically applied in the“Jiangxi emergency early warning information release system software platform(phase I)project”(hereinafter referred to as“provincial emergency”),which meets the needs of flexible deployment of multi-level applications across meteorological wide area network(WAN),business private network of other commissions,offices,and bureaus,government extranet,Internet and other complex networks,and fully verifies the scientificity and rationality of the scheme.It has achieved the goal of intensive and scalable construction of provincial emergencies under the complex network environment,greatly improved the early warning capacity and communication capacity of emergencies and comprehensive disasters,provided a reliable guarantee for disaster prevention and reduction,and provided a reference for the construction of current and future early warning release system and capacity improvement project.展开更多
This study investigated the regulatory potential of salidroside(SAL),a primary active compound in Rhodiola rosea L.,on osteoclast differentiation by modulating the hypoxia-inducible factor 1-alpha(HIF-1α)pathway in o...This study investigated the regulatory potential of salidroside(SAL),a primary active compound in Rhodiola rosea L.,on osteoclast differentiation by modulating the hypoxia-inducible factor 1-alpha(HIF-1α)pathway in osteoblasts.Luciferase reporter assay and chromatin immunoprecipitation(Ch IP)assay were employed to validate whether the receptor activator of nuclear factor-κB ligand(RANKL)is the downstream target gene of HIF-1αin osteoblasts.The study also utilized lipopolysaccharide(LPS)-induced mouse osteolysis to examine the impact of SAL on osteolysis in vivo.Furthermore,conditioned medium(CM)from SAL-pretreated osteoblasts was used to investigate the paracrine effects on osteoclastogenesis through the HIF-1αpathway.Hypoxic condition-induced overexpression of HIF-1αupregulated RANKL levels by binding to the RANKL promoter and enhancing transcription in osteoblastic cells.In vivo,SAL significantly alleviated bone tissue hypoxia and decreased the expression of HIF-1αby downregulating the expression of RANKL,vascular endothelial growth factor(VEGF),interleukin 6(IL-6),and angiopoietin-like 4(ANGPTL4).In the paracrine experiment,conditioned media from SAL-pretreated osteoblasts inhibited differentiation through the HIF-1α/RANKL,VEGF,IL-6,and ANGPTL4 pathways.RANKL emerges as the downstream target gene regulated by HIF-1αin osteoblasts.SAL significantly alleviates bone tissue hypoxia and bone loss in LPS-induced osteolysis through the HIF-1α/RANKL,VEGF,IL-6,and ANGPTL4 pathways.SAL inhibits osteoclast differentiation by regulating osteoblast paracrine secretion.展开更多
Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization proces...Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization processes lead to different order of crystallization dynamics within the perovskite thin film,resulting in the differences of additive distribution.We then tailor-designed an additive molecule named 1,3-bis(4-methoxyphenyl)thiourea to obtain films with fewer defects and holes at the buried interface,and prepared perovskite solar cells with a certified efficiency of 23.75%.Furthermore,this work also demonstrates an efficiency of 20.18%for the large-area perovskite solar module(PSM)with an aperture area of 60.84 cm^(2).The PSM possesses remarkable continuous operation stability for maximum power point tracking of T_(90)>1000 h in ambient air.展开更多
基金supported by grants from the National Natural Science Foundation of China(Grant No.82272008)The Science&Technology Development Fund of Tianjin Education Commission for Higher Education(Grant No.2021KJ194)Tianjin Key Medical Discipline(Specialty)Construction Project(Grant No.TJYXZDXK-009A).
文摘Artificial intelligence(AI)is significantly advancing precision medicine,particularly in the fields of immunogenomics,radiomics,and pathomics.In immunogenomics,AI can process vast amounts of genomic and multi-omic data to identify biomarkers associated with immunotherapy responses and disease prognosis,thus providing strong support for personalized treatments.In radiomics,AI can analyze high-dimensional features from computed tomography(CT),magnetic resonance imaging(MRI),and positron emission tomography/computed tomography(PET/CT)images to discover imaging biomarkers associated with tumor heterogeneity,treatment response,and disease progression,thereby enabling non-invasive,real-time assessments for personalized therapy.Pathomics leverages AI for deep analysis of digital pathology images,and can uncover subtle changes in tissue microenvironments,cellular characteristics,and morphological features,and offer unique insights into immunotherapy response prediction and biomarker discovery.These AI-driven technologies not only enhance the speed,accuracy,and robustness of biomarker discovery but also significantly improve the precision,personalization,and effectiveness of clinical treatments,and are driving a shift from empirical to precision medicine.Despite challenges such as data quality,model interpretability,integration of multi-modal data,and privacy protection,the ongoing advancements in AI,coupled with interdisciplinary collaboration,are poised to further enhance AI’s roles in biomarker discovery and immunotherapy response prediction.These improvements are expected to lead to more accurate,personalized treatment strategies and ultimately better patient outcomes,marking a significant step forward in the evolution of precision medicine.
文摘In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture,multi-level deployment in a complex network environment will lead to high investment in software and hardware and cannot achieve intensive multi-level deployment.This paper realizes the goal of system scalability by introducing micro service architecture and technology stack and realizes the goal of resource intensification by introducing the idea of a data forwarding agent.The designed architecture scheme has been practically applied in the“Jiangxi emergency early warning information release system software platform(phase I)project”(hereinafter referred to as“provincial emergency”),which meets the needs of flexible deployment of multi-level applications across meteorological wide area network(WAN),business private network of other commissions,offices,and bureaus,government extranet,Internet and other complex networks,and fully verifies the scientificity and rationality of the scheme.It has achieved the goal of intensive and scalable construction of provincial emergencies under the complex network environment,greatly improved the early warning capacity and communication capacity of emergencies and comprehensive disasters,provided a reliable guarantee for disaster prevention and reduction,and provided a reference for the construction of current and future early warning release system and capacity improvement project.
基金supported by grants from the National Natural Science Foundation of China(Nos.81572852 and 82104671)the Great Program of the Science Foundation of Tianjin(No.18JCZDJC33200)+1 种基金Heilongjiang Province Fund(No.LH2020H102)Tianjin Key Medical Discipline(Specialty)Construction Project(No.TJYXZDXK-032A)。
文摘This study investigated the regulatory potential of salidroside(SAL),a primary active compound in Rhodiola rosea L.,on osteoclast differentiation by modulating the hypoxia-inducible factor 1-alpha(HIF-1α)pathway in osteoblasts.Luciferase reporter assay and chromatin immunoprecipitation(Ch IP)assay were employed to validate whether the receptor activator of nuclear factor-κB ligand(RANKL)is the downstream target gene of HIF-1αin osteoblasts.The study also utilized lipopolysaccharide(LPS)-induced mouse osteolysis to examine the impact of SAL on osteolysis in vivo.Furthermore,conditioned medium(CM)from SAL-pretreated osteoblasts was used to investigate the paracrine effects on osteoclastogenesis through the HIF-1αpathway.Hypoxic condition-induced overexpression of HIF-1αupregulated RANKL levels by binding to the RANKL promoter and enhancing transcription in osteoblastic cells.In vivo,SAL significantly alleviated bone tissue hypoxia and decreased the expression of HIF-1αby downregulating the expression of RANKL,vascular endothelial growth factor(VEGF),interleukin 6(IL-6),and angiopoietin-like 4(ANGPTL4).In the paracrine experiment,conditioned media from SAL-pretreated osteoblasts inhibited differentiation through the HIF-1α/RANKL,VEGF,IL-6,and ANGPTL4 pathways.RANKL emerges as the downstream target gene regulated by HIF-1αin osteoblasts.SAL significantly alleviates bone tissue hypoxia and bone loss in LPS-induced osteolysis through the HIF-1α/RANKL,VEGF,IL-6,and ANGPTL4 pathways.SAL inhibits osteoclast differentiation by regulating osteoblast paracrine secretion.
基金supported by National Natural Science Foundation of China(62104082)Guangdong Basic and Applied Basic Research Foundation(2022A1515010746,2022A1515011228,and 2022B1515120006)the Science and Technology Program of Guangzhou(202201010458).
文摘Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization processes lead to different order of crystallization dynamics within the perovskite thin film,resulting in the differences of additive distribution.We then tailor-designed an additive molecule named 1,3-bis(4-methoxyphenyl)thiourea to obtain films with fewer defects and holes at the buried interface,and prepared perovskite solar cells with a certified efficiency of 23.75%.Furthermore,this work also demonstrates an efficiency of 20.18%for the large-area perovskite solar module(PSM)with an aperture area of 60.84 cm^(2).The PSM possesses remarkable continuous operation stability for maximum power point tracking of T_(90)>1000 h in ambient air.
