Neutron time-of-flight(ToF)measurement is a highly accurate method for obtaining the kinetic energy of a neutron by measuring its velocity,but requires precise acquisition of the neutron signal arrival time.However,th...Neutron time-of-flight(ToF)measurement is a highly accurate method for obtaining the kinetic energy of a neutron by measuring its velocity,but requires precise acquisition of the neutron signal arrival time.However,the high hardware costs and data burden associated with the acquisition of neutron ToF signals pose significant challenges.Higher sampling rates increase the data volume,data processing,and storage hardware costs.Compressed sampling can address these challenges,but it faces issues regarding optimal sampling efficiency and high-quality reconstructed signals.This paper proposes a revolutionary deep learning-based compressed sampling(DL-CS)algorithm for reconstructing neutron ToF signals that outperform traditional compressed sampling methods.This approach comprises four modules:random projection,rising dimensions,initial reconstruction,and final reconstruction.Initially,the technique adaptively compresses neutron ToF signals sequentially using three convolutional layers,replacing random measurement matrices in traditional compressed sampling theory.Subsequently,the signals are reconstructed using a modified inception module,long short-term memory,and self-attention.The performance of this deep compressed sampling method was quantified using the percentage root-mean-square difference,correlation coefficient,and reconstruction time.Experimental results showed that our proposed DL-CS approach can significantly enhance signal quality compared with other compressed sampling methods.This is evidenced by a percentage root-mean-square difference,correlation coefficient,and reconstruction time results of 5%,0.9988,and 0.0108 s,respectively,obtained for sampling rates below 10%for the neutron ToF signal generated using an electron-beam-driven photoneutron source.The results showed that the proposed DL-CS approach significantly improves the signal quality compared with other compressed sampling methods,exhibiting excellent reconstruction accuracy and speed.展开更多
This paper analyzes the current status,technological developments,academic exchange platforms,and future challenges and solutions in the field of intelligent ophthalmology(IO)in China.In terms of technology,significan...This paper analyzes the current status,technological developments,academic exchange platforms,and future challenges and solutions in the field of intelligent ophthalmology(IO)in China.In terms of technology,significant progress has been made in various areas,including diabetic retinopathy,fundus image analysis,quality assessment of medical artificial intelligence products,clinical research methods,technical evaluation,and industry standards.Researchers continually enhance the safety and standardization of IO technology by formulating a series of clinical application guidelines and standards.The establishment of domestic and international academic exchange platforms provides extensive collaboration opportunities for professionals in various fields,and various academic journals serve as publication platforms for IO research.However,challenges such as technological innovation,data privacy and security,lagging regulations,and talent shortages still pose obstacles to future development.To address these issues,future efforts should focus on strengthening technological research and development,regulatory framework construction,talent cultivation,and increasing patient awareness and acceptance of new technologies.By comprehensively addressing these challenges,IO in China is poised to further lead the industry’s development on a global scale,bringing more innovation and convenience to the field of ophthalmic healthcare.展开更多
Tuberculosis(TB)belongs to infectious diseases leading to the high mortality and morbidity worldwide.Since long-term bacilli burden leads to metabolic disorders in TB patients,metabolic biomarkers with diagnosis and p...Tuberculosis(TB)belongs to infectious diseases leading to the high mortality and morbidity worldwide.Since long-term bacilli burden leads to metabolic disorders in TB patients,metabolic biomarkers with diagnosis and prognosis potential are worthy of elucidation.In this study,^(1)H nuclear magnetic resonance spectroscopy(^(1)H NMR)-based plasma metabolomics were investigated dynamically in onset TB patients undergoing conventional anti-TB chemotherapy before and along with the treatment.We found that metabolomic profiles altered before and after the treatment of 2 and 4 months,among which four amino acids,including 4-aminobenzoate,phenylalanine,serine,and threonine,were screened out with significant decrease at 6 months after anti-TB therapy in the training longitudinal samples and validated in another longitudinal samples.Moreover,we have also confirmed the increase of 4 amino acid contents in the periphery of active TB patients when compared to those in healthy controls(HCs).Receiver operating characteristic(ROC)analysis revealed that the combination of 4 amino acids was able to distinguish TB patients from HC with an area under the curve(AUC)value of 0.9120.031(P<0.0001).Therefore,our study has identified an amino acid panel with increased levels in active TB patients and declined along with conventional anti-TB treatment,which might be potential in distinguishing TB patients from HCs as well as prognosis candidates in clinics.展开更多
Objective Although immune dysregulation is implicated in the pathogenesis of endometriosis(EMs),the specific role of prostate transmembrane protein androgen induced 1(PMEPA1)in modulating the function of regulatory T ...Objective Although immune dysregulation is implicated in the pathogenesis of endometriosis(EMs),the specific role of prostate transmembrane protein androgen induced 1(PMEPA1)in modulating the function of regulatory T cells(Tregs)remains inadequately understood.This study aimed to elucidate the regulatory mechanisms by which PMEPA1 influences the activity of Tregs,thereby facilitating the invasion of endometrial stromal cells(ESCs).Methods Single-cell RNA sequencing(scRNA-seq)was performed on matched ectopic ovarian lesions and eutopic endometria from 3 patients.Clinical specimens from patients with EMs and control subjects were examined for PMEPA1 expression.Primary human Tregs isolated from peripheral blood mononuclear cells were subjected to PMEPA1 overexpression(via plasmid)or knockdown(via siRNA).Modulation of the PI3K pathway was conducted via the activator 740Y-P or the inhibitor LY294002.The secretion of IL-10 and TGF-βby Tregs was quantified using an enzyme-linked immunosorbent assay.Ectopic ESCs cocultured with modified Tregs were assessed for their proliferation,migration,and invasion capabilities.Results scRNA-seq data revealed significant upregulation of PMEPA1 in Tregs from ectopic ovarian lesions compared with paired eutopic endometria.PMEPA1 expression was increased in the ectopic lesions and peritoneal fluid mononuclear cells of patients with EMs.Tregs overexpressing PMEPA1 demonstrated reduced secretion of IL-10 and TGF-βbut exhibited hyperactivation of the PI3K/AKT signaling pathway.Treatment with LY294002 ameliorated the impairment in cytokine secretion.Coculture experiments with Tregs expressing high levels of PMEPA1 resulted in increased invasion,migration,and proliferation of ESCs.Conclusion PMEPA1 impairs Treg-mediated immunosuppression by hyperactivating the PI3K/AKT pathway,thereby facilitating the invasiveness of ESCs in EMs.展开更多
基金supported by the National Defense Technology Foundation Program of China(No.JSJT2022209A001-3)Sichuan Science and Technology Program(No.2021JDRC0011)+1 种基金Nuclear Energy Development Research Program of China(Research on High Energy X-ray Imaging of Nuclear Fuel)Scientific Research and Innovation Team Program of Sichuan University of Science and Engineering(No.SUSE652A001).
文摘Neutron time-of-flight(ToF)measurement is a highly accurate method for obtaining the kinetic energy of a neutron by measuring its velocity,but requires precise acquisition of the neutron signal arrival time.However,the high hardware costs and data burden associated with the acquisition of neutron ToF signals pose significant challenges.Higher sampling rates increase the data volume,data processing,and storage hardware costs.Compressed sampling can address these challenges,but it faces issues regarding optimal sampling efficiency and high-quality reconstructed signals.This paper proposes a revolutionary deep learning-based compressed sampling(DL-CS)algorithm for reconstructing neutron ToF signals that outperform traditional compressed sampling methods.This approach comprises four modules:random projection,rising dimensions,initial reconstruction,and final reconstruction.Initially,the technique adaptively compresses neutron ToF signals sequentially using three convolutional layers,replacing random measurement matrices in traditional compressed sampling theory.Subsequently,the signals are reconstructed using a modified inception module,long short-term memory,and self-attention.The performance of this deep compressed sampling method was quantified using the percentage root-mean-square difference,correlation coefficient,and reconstruction time.Experimental results showed that our proposed DL-CS approach can significantly enhance signal quality compared with other compressed sampling methods.This is evidenced by a percentage root-mean-square difference,correlation coefficient,and reconstruction time results of 5%,0.9988,and 0.0108 s,respectively,obtained for sampling rates below 10%for the neutron ToF signal generated using an electron-beam-driven photoneutron source.The results showed that the proposed DL-CS approach significantly improves the signal quality compared with other compressed sampling methods,exhibiting excellent reconstruction accuracy and speed.
基金Supported by Grants from the National Natural Science Foundation of China,No.81172271the Specialized Re-search Fund for the Doctoral Program of Higher Education,No.20110001110064
文摘AIM: To investigate esophageal Helicobacter pylori (H. pylori) colonization on esophageal injury caused by reflux and the related mechanisms.
基金Supported by National Nature Science Foundation of China(No.62306254)SanMing Project of Medicine in Shenzhen(No.SZSM202311012)+1 种基金Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties(No.SZGSP014)Shenzhen Science and Technology Program(No.KCXFZ20211020163813019).
文摘This paper analyzes the current status,technological developments,academic exchange platforms,and future challenges and solutions in the field of intelligent ophthalmology(IO)in China.In terms of technology,significant progress has been made in various areas,including diabetic retinopathy,fundus image analysis,quality assessment of medical artificial intelligence products,clinical research methods,technical evaluation,and industry standards.Researchers continually enhance the safety and standardization of IO technology by formulating a series of clinical application guidelines and standards.The establishment of domestic and international academic exchange platforms provides extensive collaboration opportunities for professionals in various fields,and various academic journals serve as publication platforms for IO research.However,challenges such as technological innovation,data privacy and security,lagging regulations,and talent shortages still pose obstacles to future development.To address these issues,future efforts should focus on strengthening technological research and development,regulatory framework construction,talent cultivation,and increasing patient awareness and acceptance of new technologies.By comprehensively addressing these challenges,IO in China is poised to further lead the industry’s development on a global scale,bringing more innovation and convenience to the field of ophthalmic healthcare.
基金supported by grants from the National Key Research and Development Program of China(No.2021YFC2301500)Chinese National Mega Science and Technology Program on Infectious Diseases(Nos.2018ZX10731301-001-004 and 2018ZX10302301-002-002)+4 种基金Shanghai 2020“Science and Technology Innovation Action Plan”Technological Innovation Fund of China(No.20Z11900500)Science Foundation of Shanghai Municipal Commission of Science and Technology,China(No.24ZR1442000)Postdoctoral Fellowship Program of CPSF of China(No.GZC20241041),National Natural Science Foundation of China(No.81501361)Innovative Research Team of High-level Local Universities in Shanghai,China(No.SSMU-ZLCX20180202)Shanghai Frontiers Science Center of Cellular Homeostasis and Human Diseases,China。
文摘Tuberculosis(TB)belongs to infectious diseases leading to the high mortality and morbidity worldwide.Since long-term bacilli burden leads to metabolic disorders in TB patients,metabolic biomarkers with diagnosis and prognosis potential are worthy of elucidation.In this study,^(1)H nuclear magnetic resonance spectroscopy(^(1)H NMR)-based plasma metabolomics were investigated dynamically in onset TB patients undergoing conventional anti-TB chemotherapy before and along with the treatment.We found that metabolomic profiles altered before and after the treatment of 2 and 4 months,among which four amino acids,including 4-aminobenzoate,phenylalanine,serine,and threonine,were screened out with significant decrease at 6 months after anti-TB therapy in the training longitudinal samples and validated in another longitudinal samples.Moreover,we have also confirmed the increase of 4 amino acid contents in the periphery of active TB patients when compared to those in healthy controls(HCs).Receiver operating characteristic(ROC)analysis revealed that the combination of 4 amino acids was able to distinguish TB patients from HC with an area under the curve(AUC)value of 0.9120.031(P<0.0001).Therefore,our study has identified an amino acid panel with increased levels in active TB patients and declined along with conventional anti-TB treatment,which might be potential in distinguishing TB patients from HCs as well as prognosis candidates in clinics.
文摘Objective Although immune dysregulation is implicated in the pathogenesis of endometriosis(EMs),the specific role of prostate transmembrane protein androgen induced 1(PMEPA1)in modulating the function of regulatory T cells(Tregs)remains inadequately understood.This study aimed to elucidate the regulatory mechanisms by which PMEPA1 influences the activity of Tregs,thereby facilitating the invasion of endometrial stromal cells(ESCs).Methods Single-cell RNA sequencing(scRNA-seq)was performed on matched ectopic ovarian lesions and eutopic endometria from 3 patients.Clinical specimens from patients with EMs and control subjects were examined for PMEPA1 expression.Primary human Tregs isolated from peripheral blood mononuclear cells were subjected to PMEPA1 overexpression(via plasmid)or knockdown(via siRNA).Modulation of the PI3K pathway was conducted via the activator 740Y-P or the inhibitor LY294002.The secretion of IL-10 and TGF-βby Tregs was quantified using an enzyme-linked immunosorbent assay.Ectopic ESCs cocultured with modified Tregs were assessed for their proliferation,migration,and invasion capabilities.Results scRNA-seq data revealed significant upregulation of PMEPA1 in Tregs from ectopic ovarian lesions compared with paired eutopic endometria.PMEPA1 expression was increased in the ectopic lesions and peritoneal fluid mononuclear cells of patients with EMs.Tregs overexpressing PMEPA1 demonstrated reduced secretion of IL-10 and TGF-βbut exhibited hyperactivation of the PI3K/AKT signaling pathway.Treatment with LY294002 ameliorated the impairment in cytokine secretion.Coculture experiments with Tregs expressing high levels of PMEPA1 resulted in increased invasion,migration,and proliferation of ESCs.Conclusion PMEPA1 impairs Treg-mediated immunosuppression by hyperactivating the PI3K/AKT pathway,thereby facilitating the invasiveness of ESCs in EMs.
