Accurate prediction of cloud resource utilization is critical.It helps improve service quality while avoiding resource waste and shortages.However,the time series of resource usage in cloud computing systems often exh...Accurate prediction of cloud resource utilization is critical.It helps improve service quality while avoiding resource waste and shortages.However,the time series of resource usage in cloud computing systems often exhibit multidimensionality,nonlinearity,and high volatility,making the high-precision prediction of resource utilization a complex and challenging task.At present,cloud computing resource prediction methods include traditional statistical models,hybrid approaches combining machine learning and classical models,and deep learning techniques.Traditional statistical methods struggle with nonlinear predictions,hybrid methods face challenges in feature extraction and long-term dependencies,and deep learning methods incur high computational costs.The above methods are insufficient to achieve high-precision resource prediction in cloud computing systems.Therefore,we propose a new time series prediction model,called SDVformer,which is based on the Informer model by integrating the Savitzky-Golay(SG)filters,a novel Discrete-Variation Self-Attention(DVSA)mechanism,and a type-aware mixture of experts(T-MOE)framework.The SG filter is designed to reduce noise and enhance the feature representation of input data.The DVSA mechanism is proposed to optimize the selection of critical features to reduce computational complexity.The T-MOE framework is designed to adjust the model structure based on different resource characteristics,thereby improving prediction accuracy and adaptability.Experimental results show that our proposed SDVformer significantly outperforms baseline models,including Recurrent Neural Network(RNN),Long Short-Term Memory(LSTM),and Informer in terms of prediction precision,on both the Alibaba public dataset and the dataset collected by Beijing Jiaotong University(BJTU).Particularly compared with the Informer model,the average Mean Squared Error(MSE)of SDVformer decreases by about 80%,fully demonstrating its advantages in complex time series prediction tasks in cloud computing systems.展开更多
Background: Chimeric antigen receptor-engineered T-cell(CAR-T) therapy is a newly developed immunotherapy used in the treatment of cancers. Because CAR-T therapy has shown great success in treating CD19-positive hemat...Background: Chimeric antigen receptor-engineered T-cell(CAR-T) therapy is a newly developed immunotherapy used in the treatment of cancers. Because CAR-T therapy has shown great success in treating CD19-positive hematological malignancies, its application has been explored in the treatment of solid tumors, such as liver cancer. In this review, we discuss the immune characteristics of liver cancer, the obstacles encountered during the application of CAR-T therapy, and preclinical and clinical progress in the use of CAR-T therapy in patients with liver cancer.Data sources: The data on CAR-T therapy related to liver cancers were collected by searching Pub Med and the Web of Science databases prior to December 2017 with the keywords "chimeric antigen receptor","CAR-T", "liver cancer", "hepatocellular carcinoma", and "solid tumor". Additional articles were identified by manual search of references found in the primary articles. The data for clinical trials were collected by searching Clinical Trials.gov.Results: The liver has a tolerogenic nature in the intrahepatic milieu and its tumor microenvironment significantly affects tumor progression. The obstacles that reduce the efficacy of CAR-T therapy in solid tumors include a lack of specific tumor antigens, limited trafficking and penetration of CAR-T cells to tumor sites, and an immunosuppressive tumor microenvironment. To overcome these obstacles, several strategies have emerged. In addition, several strategies have been developed to manage the side effects of CAR-T, including enhancing the selectivity of CARs and controlling CAR-T activity. To date, no clinical trials of CAR-T therapy against HCC have been completed. However, preclinical studies in vitro and in vivo have shown potent antitumor efficacy. Glypican-3, mucin-1, epithelial cell adhesion molecule, carcinoembryonic antigen, and other targets are currently being studied.Conclusions: The application of CAR-T therapy for liver cancer is just beginning to be explored and more research is needed. However, we are optimistic that CAR-T therapy will offer a new approach for the treatment of liver cancers in the future.展开更多
Background： A major shortcoming in tissue engineered blood vessels （TEBVs） is the lack of healthy and easily attainable smooth muscle cells （SMCs）. Smooth muscle progenitor cells （SPCs）, especially from periphe...Background： A major shortcoming in tissue engineered blood vessels （TEBVs） is the lack of healthy and easily attainable smooth muscle cells （SMCs）. Smooth muscle progenitor cells （SPCs）, especially from peripheral blood, may offer an alternative cell source for tissue engineering involving a less invasive harvesting technique. Methods： SPCs were isolated from 5-ml fresh rat peripheral blood by density-gradient centrifugation and cultured for 3 weeks in endothelial growth medium-2-MV （EGM-2-MV） medium containing platelet-derived growth factoroBB （PDGF BB）. Before seeded on the synthesized scaffold, SPC-derived smooth muscle outgrowth cell （SOC） phenotypes were assessed by immuno-fluorescent staining, Western blot analysis, and reverse transcription polymerase chain reaction （RT-PCR）. The cells were seeded onto the silk fibroin-modified poly（3-hydroxybutyrate-co-3-hydroxyhexanoate） （SF-PHBHHx） scaflblds by 6× 10^4 cells/cm^2 and cultured under the static condition for 3 weeks. The growth and proliferation of the seeded cells on the scaffold were analyzed by 3-（4,5-dimethylthiazol-2-yl）-diphenyltetrazolium bromide （MTT） assay, scanning electron microscope （SEM）, and 4,6-diamidino-2-phenylindole （DAPI） staining. Results： SOCs displayed specific ＂hill and valley＂ morphology, expressed the specific markers of the SMC lineage： smooth muscle （SM） a-actin, calponin and smooth muscle myosin heavy chain （SM MHC） at protein and messenger ribonucleic acid （mRNA） levels. RT-PCR results demonstrate that SOCs also expressed smooth muscle protein 22a （SM22a, a contractile protein, and extracellular matrix components elastin and matrix Gla protein （MGP）, as well as vascular endothelial growth factor （VEGF）. After seeded on the SF-PHBHHx scaffold, the cells showed excellent metabolic activity and proliferation. Conclusion： SPCs isolated from peripheral blood can be differentiated the SMCs in vitro and have an impressive growth potential in the biodegradable synthesized scaffold. Thus, SPCs may be a promising cell sointo urce for constructing TEBVs.展开更多
This paper introduces a rigid-flexible coupling wearable exoskeleton robot for lower limb,which is designed in light of gait biomechanics and beneficial for low limb movement disorders by implementing gait training.Th...This paper introduces a rigid-flexible coupling wearable exoskeleton robot for lower limb,which is designed in light of gait biomechanics and beneficial for low limb movement disorders by implementing gait training.The rationality of the proposed mechanism is shown with the implementation of the dynamic simulation through MSC ADAMS.For the purposes of lightweight,the exoskeleton mechanism is optimized through finite element analysis.It can be concluded from performance evaluation experiment,the mechanism has certain advantages over existing exoskeleton robots,namely,comfortable,lightweight,low cost,which can be utilized for rehabilitation training in medical institutions or as a daily-walking ancillary equipment for patients.展开更多
Hepatocellular carcinoma(HCC)is the most common type of primary hepatocellular carcinoma(PHC).Early diagnosis of HCC remains the key to improve the prognosis.In recent years,with the promotion of the concept of precis...Hepatocellular carcinoma(HCC)is the most common type of primary hepatocellular carcinoma(PHC).Early diagnosis of HCC remains the key to improve the prognosis.In recent years,with the promotion of the concept of precision medicine and more in-depth analysis of the biological mechanism underlying HCC,new diagnostic methods,including emerging serum markers,liquid biopsies,molecular diagnosis,and advances in imaging(novel contrast agents and radiomics),have emerged one after another.Herein,we reviewed and analyzed scientific advances in the early diagnosis of HCC and discussed their application and shortcomings.This review aimed to provide a reference for scientific research and clinical practice of HCC.展开更多
文摘Accurate prediction of cloud resource utilization is critical.It helps improve service quality while avoiding resource waste and shortages.However,the time series of resource usage in cloud computing systems often exhibit multidimensionality,nonlinearity,and high volatility,making the high-precision prediction of resource utilization a complex and challenging task.At present,cloud computing resource prediction methods include traditional statistical models,hybrid approaches combining machine learning and classical models,and deep learning techniques.Traditional statistical methods struggle with nonlinear predictions,hybrid methods face challenges in feature extraction and long-term dependencies,and deep learning methods incur high computational costs.The above methods are insufficient to achieve high-precision resource prediction in cloud computing systems.Therefore,we propose a new time series prediction model,called SDVformer,which is based on the Informer model by integrating the Savitzky-Golay(SG)filters,a novel Discrete-Variation Self-Attention(DVSA)mechanism,and a type-aware mixture of experts(T-MOE)framework.The SG filter is designed to reduce noise and enhance the feature representation of input data.The DVSA mechanism is proposed to optimize the selection of critical features to reduce computational complexity.The T-MOE framework is designed to adjust the model structure based on different resource characteristics,thereby improving prediction accuracy and adaptability.Experimental results show that our proposed SDVformer significantly outperforms baseline models,including Recurrent Neural Network(RNN),Long Short-Term Memory(LSTM),and Informer in terms of prediction precision,on both the Alibaba public dataset and the dataset collected by Beijing Jiaotong University(BJTU).Particularly compared with the Informer model,the average Mean Squared Error(MSE)of SDVformer decreases by about 80%,fully demonstrating its advantages in complex time series prediction tasks in cloud computing systems.
文摘Background: Chimeric antigen receptor-engineered T-cell(CAR-T) therapy is a newly developed immunotherapy used in the treatment of cancers. Because CAR-T therapy has shown great success in treating CD19-positive hematological malignancies, its application has been explored in the treatment of solid tumors, such as liver cancer. In this review, we discuss the immune characteristics of liver cancer, the obstacles encountered during the application of CAR-T therapy, and preclinical and clinical progress in the use of CAR-T therapy in patients with liver cancer.Data sources: The data on CAR-T therapy related to liver cancers were collected by searching Pub Med and the Web of Science databases prior to December 2017 with the keywords "chimeric antigen receptor","CAR-T", "liver cancer", "hepatocellular carcinoma", and "solid tumor". Additional articles were identified by manual search of references found in the primary articles. The data for clinical trials were collected by searching Clinical Trials.gov.Results: The liver has a tolerogenic nature in the intrahepatic milieu and its tumor microenvironment significantly affects tumor progression. The obstacles that reduce the efficacy of CAR-T therapy in solid tumors include a lack of specific tumor antigens, limited trafficking and penetration of CAR-T cells to tumor sites, and an immunosuppressive tumor microenvironment. To overcome these obstacles, several strategies have emerged. In addition, several strategies have been developed to manage the side effects of CAR-T, including enhancing the selectivity of CARs and controlling CAR-T activity. To date, no clinical trials of CAR-T therapy against HCC have been completed. However, preclinical studies in vitro and in vivo have shown potent antitumor efficacy. Glypican-3, mucin-1, epithelial cell adhesion molecule, carcinoembryonic antigen, and other targets are currently being studied.Conclusions: The application of CAR-T therapy for liver cancer is just beginning to be explored and more research is needed. However, we are optimistic that CAR-T therapy will offer a new approach for the treatment of liver cancers in the future.
基金supported by Shanghai Science Committee Fund for Key Research Project (No. 04JC14012)Fudan University Med-X Fund, China
文摘Background： A major shortcoming in tissue engineered blood vessels （TEBVs） is the lack of healthy and easily attainable smooth muscle cells （SMCs）. Smooth muscle progenitor cells （SPCs）, especially from peripheral blood, may offer an alternative cell source for tissue engineering involving a less invasive harvesting technique. Methods： SPCs were isolated from 5-ml fresh rat peripheral blood by density-gradient centrifugation and cultured for 3 weeks in endothelial growth medium-2-MV （EGM-2-MV） medium containing platelet-derived growth factoroBB （PDGF BB）. Before seeded on the synthesized scaffold, SPC-derived smooth muscle outgrowth cell （SOC） phenotypes were assessed by immuno-fluorescent staining, Western blot analysis, and reverse transcription polymerase chain reaction （RT-PCR）. The cells were seeded onto the silk fibroin-modified poly（3-hydroxybutyrate-co-3-hydroxyhexanoate） （SF-PHBHHx） scaflblds by 6× 10^4 cells/cm^2 and cultured under the static condition for 3 weeks. The growth and proliferation of the seeded cells on the scaffold were analyzed by 3-（4,5-dimethylthiazol-2-yl）-diphenyltetrazolium bromide （MTT） assay, scanning electron microscope （SEM）, and 4,6-diamidino-2-phenylindole （DAPI） staining. Results： SOCs displayed specific ＂hill and valley＂ morphology, expressed the specific markers of the SMC lineage： smooth muscle （SM） a-actin, calponin and smooth muscle myosin heavy chain （SM MHC） at protein and messenger ribonucleic acid （mRNA） levels. RT-PCR results demonstrate that SOCs also expressed smooth muscle protein 22a （SM22a, a contractile protein, and extracellular matrix components elastin and matrix Gla protein （MGP）, as well as vascular endothelial growth factor （VEGF）. After seeded on the SF-PHBHHx scaffold, the cells showed excellent metabolic activity and proliferation. Conclusion： SPCs isolated from peripheral blood can be differentiated the SMCs in vitro and have an impressive growth potential in the biodegradable synthesized scaffold. Thus, SPCs may be a promising cell sointo urce for constructing TEBVs.
基金The work is supported in part by the National Natural Science Foundation of China under Grants(61873304)in part by the China Postdoctoral Science Foundation Funded Project under Grant(2018M641784)also in part by the Funding of Jilin Province Science and Technology(JJKH20210745KJ).
文摘This paper introduces a rigid-flexible coupling wearable exoskeleton robot for lower limb,which is designed in light of gait biomechanics and beneficial for low limb movement disorders by implementing gait training.The rationality of the proposed mechanism is shown with the implementation of the dynamic simulation through MSC ADAMS.For the purposes of lightweight,the exoskeleton mechanism is optimized through finite element analysis.It can be concluded from performance evaluation experiment,the mechanism has certain advantages over existing exoskeleton robots,namely,comfortable,lightweight,low cost,which can be utilized for rehabilitation training in medical institutions or as a daily-walking ancillary equipment for patients.
基金Natural Science Foundation of China(No.81902484)China Postdoctoral Science Foundation(No.2020M670864)+2 种基金Medical and Health Talents Project of Jilin Province(Nos.2019SCZT003,2020SCZT096)Youth Support Project of Jilin Association for Science and Technology(No.202028)Project of Hepatobiliary and Pancreatic Disease Translational Medicine Platform Construction(No.2017F009)
文摘Hepatocellular carcinoma(HCC)is the most common type of primary hepatocellular carcinoma(PHC).Early diagnosis of HCC remains the key to improve the prognosis.In recent years,with the promotion of the concept of precision medicine and more in-depth analysis of the biological mechanism underlying HCC,new diagnostic methods,including emerging serum markers,liquid biopsies,molecular diagnosis,and advances in imaging(novel contrast agents and radiomics),have emerged one after another.Herein,we reviewed and analyzed scientific advances in the early diagnosis of HCC and discussed their application and shortcomings.This review aimed to provide a reference for scientific research and clinical practice of HCC.
