Nanozymes have received great attention owing to the advantages of easy preparation and low cost. Unlike natural enzymes that readily adapt to physiological environments, artificial nanozymes are apt to passivate in c...Nanozymes have received great attention owing to the advantages of easy preparation and low cost. Unlike natural enzymes that readily adapt to physiological environments, artificial nanozymes are apt to passivate in complex clinical samples （e.g., serum）, which may damage the catalytic capability and consequently limit the application in biomedical analysis. To conquer this problem, in this study, we fabricated novel nanozyme@DNA hydrogel architecture by incorporat^ng nanozymes into a pure DNA hydrogel. Gold nanoparticles （AuNPs） were adopted as a model nanozyme. Results indicate that AuNPs incorporated in the DNA hydrogel retain their catalytic capability in serum as they are protected by the hydrogel, whereas AuNPs alone totally lose the catalytic capability in serum. The detection of hydrogen peroxide and glucose in serum based on the catalysis of the AuNPs@DNA hydrogel was achieved. The detection limit of each reaches 1.7 and 38 ~M, respectively, which is equal to the value obtained using natural enzymes. Besides the mechanisms, some other advantages, such as recyclability and availability, have also been explored. This nanozyme@DNA hydrogel architecture may have a great potential for the utilization of nanozymes as well as the application of nanozymes for biomedical analysis in complex physiological samples.展开更多
Human schistosomiasis,caused mainly by three principal species including Schistosoma japonicum,S.mansoni,and S.hematobium,remains a major public health concern worldwide.S.japonicum is prevalent in southern China,bein...Human schistosomiasis,caused mainly by three principal species including Schistosoma japonicum,S.mansoni,and S.hematobium,remains a major public health concern worldwide.S.japonicum is prevalent in southern China,being a major disease risk for 66 million people.The bloodfluke has a complex life cycle for survival:as a free-living form in fresh water and as a parasite in the snail intermediate and vertebrate definitive hosts.Systems-based biomedical analyses,including genomic,transcriptomic,proteomic and metabonomic approaches,have been performed on the schistosome.These comprehensive investigations have not only char-acterized the genomic features but also chartered gene and protein expression profiles across genders and develop-mental stages.The integration of the huge information will lay a global and solid foundation for the molecular architecture of the biology,pathogenesis,and host-parasite interactions of the human bloodfluke,which will facilitate the development of a new antischistosomal vaccine and drugs as well as diagnostic markers for the treatment and control of schistosomiasis.展开更多
The 193 nm deep-ultraviolet(DUV)laser plays a critical role in advanced semiconductor chip manufacturing[1,2],micro-nano material characterization[3,4]and biomedical analysis[5,6],due to its high spatial resolution an...The 193 nm deep-ultraviolet(DUV)laser plays a critical role in advanced semiconductor chip manufacturing[1,2],micro-nano material characterization[3,4]and biomedical analysis[5,6],due to its high spatial resolution and short wavelength.Efficient and compact 193 nm DUV laser source thus becomes a hot research area.Currently,193 nm Ar F excimer gas laser is widely employed in DUV lithography systems and serves as the enabling technology for 7 and 5 nm semiconductor fabrication.展开更多
The rapid development of biological and medical examination methods has vastly expanded personal biomedical information,including molecular,cel-lular,image,and electronic health record datasets.Integrating this wealth...The rapid development of biological and medical examination methods has vastly expanded personal biomedical information,including molecular,cel-lular,image,and electronic health record datasets.Integrating this wealth of information enables precise disease diagnosis,biomarker identification,and treatment design in clinical settings.Artificial intelligence(Al)techniques,particularly deep learning models,have been extensively employed in biomedical applications,demonstrating increased precision,efficiency,and generalization.The success of the large language and vision models fur-ther significantly extends their biomedical applications.However,challenges remain in learning these multimodal biomedical datasets,such as data privacy,fusion,and model interpretation.In this review,we provide a comprehensive overview of various biomedical data modalities,multimodal rep-resentation learning methods,and the applications of Al in biomedical data integrative analysis.Additionally,we discuss the challenges in applying these deep learning methods and how to better integrate them into biomedical scenarios.We then propose future directions for adapting deep learn-ing methods with model pretraining and knowledge integration to advance biomedical research and benefit their clinical applications.展开更多
Earlier recognition of breast cancer is crucial to decrease the severity and optimize the survival rate.One of the commonly utilized imaging modalities for breast cancer is histopathological images.Since manual inspec...Earlier recognition of breast cancer is crucial to decrease the severity and optimize the survival rate.One of the commonly utilized imaging modalities for breast cancer is histopathological images.Since manual inspection of histopathological images is a challenging task,automated tools using deep learning(DL)and artificial intelligence(AI)approaches need to be designed.The latest advances of DL models help in accomplishing maximum image classification performance in several application areas.In this view,this study develops a Deep Transfer Learning with Rider Optimization Algorithm for Histopathological Classification of Breast Cancer(DTLRO-HCBC)technique.The proposed DTLRO-HCBC technique aims to categorize the existence of breast cancer using histopathological images.To accomplish this,the DTLRO-HCBC technique undergoes pre-processing and data augmentation to increase quantitative analysis.Then,optimal SqueezeNet model is employed for feature extractor and the hyperparameter tuning process is carried out using the Adadelta optimizer.Finally,rider optimization with deep feed forward neural network(RO-DFFNN)technique was utilized employed for breast cancer classification.The RO algorithm is applied for optimally adjusting the weight and bias values of the DFFNN technique.For demonstrating the greater performance of the DTLRO-HCBC approach,a sequence of simulations were carried out and the outcomes reported its promising performance over the current state of art approaches.展开更多
The results of 31 cases of sutureless esophagogastrostomy by intraluminal elastic circular ligation (IECL) with the biodegradable supporting tube were reported. The fate of the supporting tube could be tracked satisfa...The results of 31 cases of sutureless esophagogastrostomy by intraluminal elastic circular ligation (IECL) with the biodegradable supporting tube were reported. The fate of the supporting tube could be tracked satisfactorily by X-ray, The tube-dislodge time was 15.03 +/- 2.23 days and unaffected by the size of supporting tube or the site of anastomosis, The supporting tube could be safely absorbed or partially discharged through the alimentary tract. IECL, with the merits of saving time, anastomosing tightly and leaving no suture materials in the anastomotic site, can be expected to further reduce the incidence of anastomotic leakage and provide references for other gastrointestinal anastomosis.展开更多
基金This work was supported by the National Natural Science Foundation of China （Nos. 21575088, 21235003, and 31200742）, and the Natural Science Foundation of Shanghai （No. 14ZR1416500）.
文摘Nanozymes have received great attention owing to the advantages of easy preparation and low cost. Unlike natural enzymes that readily adapt to physiological environments, artificial nanozymes are apt to passivate in complex clinical samples （e.g., serum）, which may damage the catalytic capability and consequently limit the application in biomedical analysis. To conquer this problem, in this study, we fabricated novel nanozyme@DNA hydrogel architecture by incorporat^ng nanozymes into a pure DNA hydrogel. Gold nanoparticles （AuNPs） were adopted as a model nanozyme. Results indicate that AuNPs incorporated in the DNA hydrogel retain their catalytic capability in serum as they are protected by the hydrogel, whereas AuNPs alone totally lose the catalytic capability in serum. The detection of hydrogen peroxide and glucose in serum based on the catalysis of the AuNPs@DNA hydrogel was achieved. The detection limit of each reaches 1.7 and 38 ~M, respectively, which is equal to the value obtained using natural enzymes. Besides the mechanisms, some other advantages, such as recyclability and availability, have also been explored. This nanozyme@DNA hydrogel architecture may have a great potential for the utilization of nanozymes as well as the application of nanozymes for biomedical analysis in complex physiological samples.
基金supported by the Special Funds for State Key Development Program for Basic Research of China(973 Program)(No.2010CB529200).
文摘Human schistosomiasis,caused mainly by three principal species including Schistosoma japonicum,S.mansoni,and S.hematobium,remains a major public health concern worldwide.S.japonicum is prevalent in southern China,being a major disease risk for 66 million people.The bloodfluke has a complex life cycle for survival:as a free-living form in fresh water and as a parasite in the snail intermediate and vertebrate definitive hosts.Systems-based biomedical analyses,including genomic,transcriptomic,proteomic and metabonomic approaches,have been performed on the schistosome.These comprehensive investigations have not only char-acterized the genomic features but also chartered gene and protein expression profiles across genders and develop-mental stages.The integration of the huge information will lay a global and solid foundation for the molecular architecture of the biology,pathogenesis,and host-parasite interactions of the human bloodfluke,which will facilitate the development of a new antischistosomal vaccine and drugs as well as diagnostic markers for the treatment and control of schistosomiasis.
基金supported by the National Natural Science Foundation of China(Grant Nos.62450006,62304217,62274157,62127807,62234011,62034008,62074142,62074140)Tianshan Innovation Team Program(Grant No.2022TSYCTD0005)+1 种基金Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0880000)Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant Nos.2023124,Y2023032)。
文摘The 193 nm deep-ultraviolet(DUV)laser plays a critical role in advanced semiconductor chip manufacturing[1,2],micro-nano material characterization[3,4]and biomedical analysis[5,6],due to its high spatial resolution and short wavelength.Efficient and compact 193 nm DUV laser source thus becomes a hot research area.Currently,193 nm Ar F excimer gas laser is widely employed in DUV lithography systems and serves as the enabling technology for 7 and 5 nm semiconductor fabrication.
基金supported by the National Key R&D Program(Grant Nos.2023YFF1204701 and 2022YFF1202101)the Self-supporting Program of Guangzhou Laboratory(Grant No.SRPG22007)+1 种基金the CAS Research Fund(Grant No.XDB38050200)Guangdong Basic and Applied Basic Research Foundation(Grant No.2023B1515130008),China.
文摘The rapid development of biological and medical examination methods has vastly expanded personal biomedical information,including molecular,cel-lular,image,and electronic health record datasets.Integrating this wealth of information enables precise disease diagnosis,biomarker identification,and treatment design in clinical settings.Artificial intelligence(Al)techniques,particularly deep learning models,have been extensively employed in biomedical applications,demonstrating increased precision,efficiency,and generalization.The success of the large language and vision models fur-ther significantly extends their biomedical applications.However,challenges remain in learning these multimodal biomedical datasets,such as data privacy,fusion,and model interpretation.In this review,we provide a comprehensive overview of various biomedical data modalities,multimodal rep-resentation learning methods,and the applications of Al in biomedical data integrative analysis.Additionally,we discuss the challenges in applying these deep learning methods and how to better integrate them into biomedical scenarios.We then propose future directions for adapting deep learn-ing methods with model pretraining and knowledge integration to advance biomedical research and benefit their clinical applications.
基金This project was funded by the Deanship of Scientific Research(DSR),King Abdulaziz University,Jeddah,under grant no.(D-773-130-1443).
文摘Earlier recognition of breast cancer is crucial to decrease the severity and optimize the survival rate.One of the commonly utilized imaging modalities for breast cancer is histopathological images.Since manual inspection of histopathological images is a challenging task,automated tools using deep learning(DL)and artificial intelligence(AI)approaches need to be designed.The latest advances of DL models help in accomplishing maximum image classification performance in several application areas.In this view,this study develops a Deep Transfer Learning with Rider Optimization Algorithm for Histopathological Classification of Breast Cancer(DTLRO-HCBC)technique.The proposed DTLRO-HCBC technique aims to categorize the existence of breast cancer using histopathological images.To accomplish this,the DTLRO-HCBC technique undergoes pre-processing and data augmentation to increase quantitative analysis.Then,optimal SqueezeNet model is employed for feature extractor and the hyperparameter tuning process is carried out using the Adadelta optimizer.Finally,rider optimization with deep feed forward neural network(RO-DFFNN)technique was utilized employed for breast cancer classification.The RO algorithm is applied for optimally adjusting the weight and bias values of the DFFNN technique.For demonstrating the greater performance of the DTLRO-HCBC approach,a sequence of simulations were carried out and the outcomes reported its promising performance over the current state of art approaches.
文摘The results of 31 cases of sutureless esophagogastrostomy by intraluminal elastic circular ligation (IECL) with the biodegradable supporting tube were reported. The fate of the supporting tube could be tracked satisfactorily by X-ray, The tube-dislodge time was 15.03 +/- 2.23 days and unaffected by the size of supporting tube or the site of anastomosis, The supporting tube could be safely absorbed or partially discharged through the alimentary tract. IECL, with the merits of saving time, anastomosing tightly and leaving no suture materials in the anastomotic site, can be expected to further reduce the incidence of anastomotic leakage and provide references for other gastrointestinal anastomosis.
