Biliary tract cancer(BTC)is a group of heterogeneous sporadic diseases,including intrahepatic,hilar,and distal cholangiocarcinoma,as well as gallbladder cancer.BTC is characterized by high invasiveness and extremely p...Biliary tract cancer(BTC)is a group of heterogeneous sporadic diseases,including intrahepatic,hilar,and distal cholangiocarcinoma,as well as gallbladder cancer.BTC is characterized by high invasiveness and extremely poor prognosis,with a global increased incidence due to intrahepatic cholangiocarcinoma(ICC).The 18Ffludeoxyglucose positron emission tomography(PET)computed tomography(18F-FDG PET/CT)combines glucose metabolic information(reflecting the glycolytic activity of tumor cells)with anatomical structure to assess tumor metabolic heterogeneity,systemic metastasis,and molecular characteristics noninvasively,overcoming the limitations of traditional imaging in the detection of micrometastases and recurrent lesions.18F-FDG PET/CT offers critical insights in clinical staging,therapeutic evaluation,and prognostic prediction of BTC.This article reviews research progress in this field over the past decade,with a particular focus on the advances made in the last 3 years,which have not been adequately summarized and recognized.The research paradigm in this field is shifting from qualitative to quantitative studies,and there have been significant breakthroughs in using 18F-FDG PET/CT metabolic information to predict gene expression in ICC.Radiomics and deep learning techniques have been applied to ICC for prognostic prediction and differential diagnosis.Additionally,PET/magnetic resonance imaging is increasingly demonstrating its value in this field.展开更多
Recognized as a pivotal facet in Beyond Fifth-Generation(B5G)and the upcoming Sixth-Generation(6G)wireless networks,Unmanned Aerial Vehicle(UAV)communications pose challenges due to limited capabilities when serving a...Recognized as a pivotal facet in Beyond Fifth-Generation(B5G)and the upcoming Sixth-Generation(6G)wireless networks,Unmanned Aerial Vehicle(UAV)communications pose challenges due to limited capabilities when serving as mobile base stations,leading to suboptimal service for edge users.To address this,the collaborative formation of Coordinated Multi-Point(CoMP)networks proves instrumental in alleviating the issue of the poor Quality of Service(QoS)at edge users in the network periphery.This paper introduces a groundbreaking solution,the Hybrid Uplink-Downlink Non-Orthogonal Multiple Access(HUD-NOMA)scheme for UAV-aided CoMP networks.Leveraging network coding and NOMA technology,our proposed HUD-NOMA effectively enhances transmission rates for edge users,notwithstanding a minor reduction in signal reception reliability for strong signals.Importantly,the system’s overall sum rate is elevated.The proposed HUD-NOMA demonstrates resilience against eavesdroppers by effectively managing intended interferences without the need for additional artificial noise injection.The study employs a stochastic geometry approach to derive the Secrecy Outage Probability(SOP)for the transmissions in the CoMP network,revealing superior performance in transmission rates and lower SOP compared to existing methods through numerical verification.Furthermore,guided by the theoretical SOP derivation,this paper proposes a power allocation strategy to further reduce the system’s SOP.展开更多
At present,carbon capture and storage(CCS)is the only mature and commercialized technology capable of effectively and economically reducing greenhouse gas emissions to achieve a significant and immedi-ate impact on th...At present,carbon capture and storage(CCS)is the only mature and commercialized technology capable of effectively and economically reducing greenhouse gas emissions to achieve a significant and immedi-ate impact on the CO_(2) level on Earth.Notably,long-term geological storage of captured CO_(2) has emerged as a primary storage method,given its minimal impact on surface ecological environments and high level of safety.The integrity of CO_(2) storage wellbores can be compromised by the corrosion of steel casings and degradation of cement in supercritical CO_(2) storage environments,potentially leading to the leakage of stored CO_(2) from the sites.This critical review endeavors to establish a knowledge foundation for the cor-rosion and materials degradation associated with geological CO_(2) storage through an in-depth examina-tion and analysis of the environments,operation,and the state-of-the-art progress in research pertaining to the topic.This article discusses the physical and chemical properties of CO_(2) in its supercrit-ical phase during injection and storage.It then introduces the principle of geological CO_(2) storage,consid-erations in the construction of storage systems,and the unique geo-bio-chemical environment involving aqueous media and microbial communities in CO_(2) storage.After a comprehensive analysis of existing knowledge on corrosion in CO_(2) storage,including corrosion mechanisms,parametric effects,and corro-sion rate measurements,this review identifies technical gaps and puts forward potential avenues for fur-ther research in steel corrosion within geological CO_(2) storage systems.展开更多
This study primarily aimed to investigate the prevalence of human papillomavirus(HPV)and other common pathogens of sexually transmitted infections(STIs)in spermatozoa of infertile men and their effects on semen parame...This study primarily aimed to investigate the prevalence of human papillomavirus(HPV)and other common pathogens of sexually transmitted infections(STIs)in spermatozoa of infertile men and their effects on semen parameters.These pathogens included Ureaplasma urealyticum,Ureaplasma parvum,Chlamydia trachomatis,Mycoplasma genitalium,herpes simplex virus 2,Neisseria gonorrhoeae,Enterococcus faecalis,Streptococcus agalactiae,Pseudomonas aeruginosa,and Staphylococcus aureus.A total of 1951 men of infertile couples were recruited between 23 March 2023,and 17 May 2023,at the Department of Reproductive Medicine of The First People’s Hospital of Yunnan Province(Kunming,China).Multiplex polymerase chain reaction and capillary electrophoresis were used for HPV genotyping.Polymerase chain reaction and electrophoresis were also used to detect the presence of other STIs.The overall prevalence of HPV infection was 12.4%.The top five prevalent HPV subtypes were types 56,52,43,16,and 53 among those tested positive for HPV.Other common infections with high prevalence rates were Ureaplasma urealyticum(28.3%),Ureaplasma parvum(20.4%),and Enterococcus faecalis(9.5%).The prevalence rates of HPV coinfection with Ureaplasma urealyticum,Ureaplasma parvum,Chlamydia trachomatis,Mycoplasma genitalium,herpes simplex virus 2,Neisseria gonorrhoeae,Enterococcus faecalis,Streptococcus agalactiae,and Staphylococcus aureus were 24.8%,25.4%,10.6%,6.4%,2.4%,7.9%,5.9%,0.9%,and 1.3%,respectively.The semen volume and total sperm count were greatly decreased by HPV infection alone.Coinfection with HPV and Ureaplasma urealyticum significantly reduced sperm motility and viability.Our study shows that coinfection with STIs is highly prevalent in the semen of infertile men and that coinfection with pathogens can seriously affect semen parameters,emphasizing the necessity of semen screening for STIs.展开更多
Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accu...Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.展开更多
Imaging evaluation of lymph node metastasis and infiltration faces problems such as low artificial outline efficiency and insufficient consistency.Deep learning technology based on convolutional neural networks has gr...Imaging evaluation of lymph node metastasis and infiltration faces problems such as low artificial outline efficiency and insufficient consistency.Deep learning technology based on convolutional neural networks has greatly improved the technical effect of radiomics in lymph node pathological characteristics analysis and efficacy monitoring through automatic lymph node detection,precise segmentation and three-dimensional reconstruction algorithms.This review focuses on the automatic lymph node segmentation model,treatment response prediction algorithm and benign and malignant differential diagnosis system for multimodal imaging,in order to provide a basis for further research on artificial intelligence to assist lymph node disease management and clinical decision-making,and provide a reference for promoting the construction of a system for accurate diagnosis,personalized treatment and prognostic evaluation of lymph node-related diseases.展开更多
Polymer materials commonly employed in low Earth orbit(LEO)environments are highly susceptible to atomic oxygen(AO)attack,leading to severe degradation and deterioration of their properties.To address this challenge,3...Polymer materials commonly employed in low Earth orbit(LEO)environments are highly susceptible to atomic oxygen(AO)attack,leading to severe degradation and deterioration of their properties.To address this challenge,3-glycidyloxypropyltrimethoxysilane-modified hexagonal boron nitride(h-BN@KH560)nanohybrids were synthesized and incorporated into epoxy(EP)composites to enhance their AO erosion resistance.The resulting hexagonal boron nitride-based epoxy nanocomposites(FBN/EP)were systematically evaluated for their tribological performance and AO erosion resistance using a series of characterization techniques.The results demonstrated that the incorporation of h-BN@KH560 nanohybrids significantly improved the wear resistance and AO erosion resistance of the EP matrix.Specific ally,the FBN_(1.0)/EP nanocomposite exhibited an 86.1%reduction in wear rate compared to pure EP,while FBN_(5.0)/EP nanocomposite achieved optimal AO erosion resistance,with a minimal erosion rate of 3.58×10^(-24)cm^(3)atoms^(-1)at an AO dose of 1.2×10^(21)atoms cm^(-2).These findings indicate that the incorporating content-induced distribution of h-BN@KH560 within the EP matrix strongly influences the wear resistance of FBN/EP nanocomposites,but there is a relatively minor effect on their AO erosion resistance.The enhanced AO erosion resistance is attributed to the synergistic barrier protection provided by h-BN@KH560 and the formed B_(2)O_(3)and SiO_(2)layers under AO irradiation.This study offers a promising strategy for extending the service life of epoxy nanocomposites in harsh LEO environments.展开更多
Esophageal cancer(EC),a common malignant tumor of the digestive tract,requires early diagnosis and timely treatment to improve patient prognosis.Automated detection of EC using medical imaging has the potential to inc...Esophageal cancer(EC),a common malignant tumor of the digestive tract,requires early diagnosis and timely treatment to improve patient prognosis.Automated detection of EC using medical imaging has the potential to increase screening efficiency and diagnostic accuracy,thereby significantly improving long-term survival rates and the quality of life of patients.Recent advances in deep learning(DL),particularly convolutional neural networks,have demons-trated remarkable performance in medical imaging analysis.These techniques have shown significant progress in the automated identification of malignant tumors,quantitative analysis of lesions,and improvement in diagnostic accuracy and efficiency.This article comprehensively examines the research progress of DL in medical imaging for EC,covering various imaging modalities such as digital pathology,endoscopy,computed tomography,etc.It explores the clinical value and application prospects of DL in EC screening and diagnosis.Additionally,the article addresses several critical challenges that must be overcome for the clinical translation of DL techniques,including constructing high-quality datasets,promoting multimodal feature fusion,and optimizing artificial intelligence-clinical workflow integration.By providing a detailed overview of the current state of DL in EC imaging and highlighting the key challenges and future directions,this article aims to guide future research and facilitate the clinical implementation of DL technologies in EC management,ultimately contributing to better patient outcomes.展开更多
Hepatocellular carcinoma(HCC)expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming.Aldolase A(ALDOA)plays a prominent role in glycolysis;however,little is known about its ro...Hepatocellular carcinoma(HCC)expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming.Aldolase A(ALDOA)plays a prominent role in glycolysis;however,little is known about its role in HCC development.In the present study,we aim to explore how ALDOA is involved in HCC proliferation.HCC proliferation was markedly suppressed both in vitro and in vivo following ALDOA knockout,which is consistent with ALDOA overexpression encouraging HCC proliferation.Mechanistically,ALDOA knockout partially limits the glycolytic flux in HCC cells.Meanwhile,ALDOA translocated to nuclei and directly interacted with c-Jun to facilitate its Thr93 phosphorylation by P21-activated protein kinase;ALDOA knockout markedly diminished c-Jun Thr93 phosphorylation and then dampened c-Jun transcription function.A crucial site Y364 mutation in ALDOA disrupted its interaction with c-Jun,and Y364S ALDOA expression failed to rescue cell proliferation in ALDOA deletion cells.In HCC patients,the expression level of ALDOA was correlated with the phosphorylation level of c-Jun(Thr93)and poor prognosis.Remarkably,hepatic ALDOA was significantly upregulated in the promotion and progression stages of diethylnitrosamine-induced HCC models,and the knockdown of Aldoa strikingly decreased HCC development in vivo.Our study demonstrated that ALDOA is a vital driver for HCC development by activating c-Jun-mediated oncogene transcription,opening additional avenues for anti-cancer therapies.展开更多
Objective: To evaluate the cost-utility of nivolumab plus chemotherapy compared with chemotherapy alone as the first-line treatment for advanced gastric, gastro-oesophageal junction, and esophageal adenocarcinoma in C...Objective: To evaluate the cost-utility of nivolumab plus chemotherapy compared with chemotherapy alone as the first-line treatment for advanced gastric, gastro-oesophageal junction, and esophageal adenocarcinoma in China. Methods: Based on CheckMate649, a partitioned survival model was carried out with a circulation cycle of 6 weeks to simulate the patient’s lifetime. Sensitivity analysis were adopted to verify the robustness of the results. Results: The results of the base-case analysis showed that both the total cost and utility of the nivolumab group were higher, and the ICUR value was CNY 267498.67/QALY, more than 3 times the GDP per capita of China in 2020. The results of deterministic sensitivity analysis indicated that the three most influential factors were the utility value of PFS state, the cost of nivolumab and the discount rate. The results of probabilistic sensitivity analysis were consistent with those of base-case analysis, proving that the results were robust. The scenario analysis illustrated that economical price of nivolumab was CNY 3652.71. Conclusions: Under the willing-to-pay threshold of three times the GDP per capita of China in 2020, compared with chemotherapy alone, nivolumab plus chemotherapy is not a cost-effective option in China.展开更多
文摘Biliary tract cancer(BTC)is a group of heterogeneous sporadic diseases,including intrahepatic,hilar,and distal cholangiocarcinoma,as well as gallbladder cancer.BTC is characterized by high invasiveness and extremely poor prognosis,with a global increased incidence due to intrahepatic cholangiocarcinoma(ICC).The 18Ffludeoxyglucose positron emission tomography(PET)computed tomography(18F-FDG PET/CT)combines glucose metabolic information(reflecting the glycolytic activity of tumor cells)with anatomical structure to assess tumor metabolic heterogeneity,systemic metastasis,and molecular characteristics noninvasively,overcoming the limitations of traditional imaging in the detection of micrometastases and recurrent lesions.18F-FDG PET/CT offers critical insights in clinical staging,therapeutic evaluation,and prognostic prediction of BTC.This article reviews research progress in this field over the past decade,with a particular focus on the advances made in the last 3 years,which have not been adequately summarized and recognized.The research paradigm in this field is shifting from qualitative to quantitative studies,and there have been significant breakthroughs in using 18F-FDG PET/CT metabolic information to predict gene expression in ICC.Radiomics and deep learning techniques have been applied to ICC for prognostic prediction and differential diagnosis.Additionally,PET/magnetic resonance imaging is increasingly demonstrating its value in this field.
基金supported in part by the National Key R&D Program of China under Grant 2022YFB3104503in part by the National Natural Science Foundation of China under Grant 62202054,and Grant 61931001+2 种基金in part by the National Natural Science Foundation of China No.62202054the Young Elite Scientists Sponsorship Program of the China Association for Science and Technology under Grant 2023QNRC001in part by the U.S.National Science Foundation under Grant 2136202.
文摘Recognized as a pivotal facet in Beyond Fifth-Generation(B5G)and the upcoming Sixth-Generation(6G)wireless networks,Unmanned Aerial Vehicle(UAV)communications pose challenges due to limited capabilities when serving as mobile base stations,leading to suboptimal service for edge users.To address this,the collaborative formation of Coordinated Multi-Point(CoMP)networks proves instrumental in alleviating the issue of the poor Quality of Service(QoS)at edge users in the network periphery.This paper introduces a groundbreaking solution,the Hybrid Uplink-Downlink Non-Orthogonal Multiple Access(HUD-NOMA)scheme for UAV-aided CoMP networks.Leveraging network coding and NOMA technology,our proposed HUD-NOMA effectively enhances transmission rates for edge users,notwithstanding a minor reduction in signal reception reliability for strong signals.Importantly,the system’s overall sum rate is elevated.The proposed HUD-NOMA demonstrates resilience against eavesdroppers by effectively managing intended interferences without the need for additional artificial noise injection.The study employs a stochastic geometry approach to derive the Secrecy Outage Probability(SOP)for the transmissions in the CoMP network,revealing superior performance in transmission rates and lower SOP compared to existing methods through numerical verification.Furthermore,guided by the theoretical SOP derivation,this paper proposes a power allocation strategy to further reduce the system’s SOP.
文摘At present,carbon capture and storage(CCS)is the only mature and commercialized technology capable of effectively and economically reducing greenhouse gas emissions to achieve a significant and immedi-ate impact on the CO_(2) level on Earth.Notably,long-term geological storage of captured CO_(2) has emerged as a primary storage method,given its minimal impact on surface ecological environments and high level of safety.The integrity of CO_(2) storage wellbores can be compromised by the corrosion of steel casings and degradation of cement in supercritical CO_(2) storage environments,potentially leading to the leakage of stored CO_(2) from the sites.This critical review endeavors to establish a knowledge foundation for the cor-rosion and materials degradation associated with geological CO_(2) storage through an in-depth examina-tion and analysis of the environments,operation,and the state-of-the-art progress in research pertaining to the topic.This article discusses the physical and chemical properties of CO_(2) in its supercrit-ical phase during injection and storage.It then introduces the principle of geological CO_(2) storage,consid-erations in the construction of storage systems,and the unique geo-bio-chemical environment involving aqueous media and microbial communities in CO_(2) storage.After a comprehensive analysis of existing knowledge on corrosion in CO_(2) storage,including corrosion mechanisms,parametric effects,and corro-sion rate measurements,this review identifies technical gaps and puts forward potential avenues for fur-ther research in steel corrosion within geological CO_(2) storage systems.
基金supported by the Yunnan Provincial Key Laboratory of Clinical Virology(No.202002AG070062)the Key Projects of Yunnan Province Science and Technology Department(No.202302AA310044)the National Natural Science Foundation of China(No.82060664).
文摘This study primarily aimed to investigate the prevalence of human papillomavirus(HPV)and other common pathogens of sexually transmitted infections(STIs)in spermatozoa of infertile men and their effects on semen parameters.These pathogens included Ureaplasma urealyticum,Ureaplasma parvum,Chlamydia trachomatis,Mycoplasma genitalium,herpes simplex virus 2,Neisseria gonorrhoeae,Enterococcus faecalis,Streptococcus agalactiae,Pseudomonas aeruginosa,and Staphylococcus aureus.A total of 1951 men of infertile couples were recruited between 23 March 2023,and 17 May 2023,at the Department of Reproductive Medicine of The First People’s Hospital of Yunnan Province(Kunming,China).Multiplex polymerase chain reaction and capillary electrophoresis were used for HPV genotyping.Polymerase chain reaction and electrophoresis were also used to detect the presence of other STIs.The overall prevalence of HPV infection was 12.4%.The top five prevalent HPV subtypes were types 56,52,43,16,and 53 among those tested positive for HPV.Other common infections with high prevalence rates were Ureaplasma urealyticum(28.3%),Ureaplasma parvum(20.4%),and Enterococcus faecalis(9.5%).The prevalence rates of HPV coinfection with Ureaplasma urealyticum,Ureaplasma parvum,Chlamydia trachomatis,Mycoplasma genitalium,herpes simplex virus 2,Neisseria gonorrhoeae,Enterococcus faecalis,Streptococcus agalactiae,and Staphylococcus aureus were 24.8%,25.4%,10.6%,6.4%,2.4%,7.9%,5.9%,0.9%,and 1.3%,respectively.The semen volume and total sperm count were greatly decreased by HPV infection alone.Coinfection with HPV and Ureaplasma urealyticum significantly reduced sperm motility and viability.Our study shows that coinfection with STIs is highly prevalent in the semen of infertile men and that coinfection with pathogens can seriously affect semen parameters,emphasizing the necessity of semen screening for STIs.
基金funded by the Youth Fund of the National Natural Science Foundation of China(Grant No.42261070).
文摘Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.
基金Supported by Clinical Trials from the Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University,No.2021-LCYJ-MS-11Nanjing Drum Tower Hospital National Natural Science Foundation Youth Cultivation Project,No.2024-JCYJQP-15.
文摘Imaging evaluation of lymph node metastasis and infiltration faces problems such as low artificial outline efficiency and insufficient consistency.Deep learning technology based on convolutional neural networks has greatly improved the technical effect of radiomics in lymph node pathological characteristics analysis and efficacy monitoring through automatic lymph node detection,precise segmentation and three-dimensional reconstruction algorithms.This review focuses on the automatic lymph node segmentation model,treatment response prediction algorithm and benign and malignant differential diagnosis system for multimodal imaging,in order to provide a basis for further research on artificial intelligence to assist lymph node disease management and clinical decision-making,and provide a reference for promoting the construction of a system for accurate diagnosis,personalized treatment and prognostic evaluation of lymph node-related diseases.
基金financially supported by Natural Science Foundation of Zhejiang Province(No.LY23E050004)Ningbo City’s Key Technology Breakthrough Plan for“Science and Technology Innovation Yongjiang 2035(No.2024Z133)+1 种基金the National Natural Science Foundation of China(No.52375220)the Natural Science Foundation of Ningbo Municipality(No.2024QL021)
文摘Polymer materials commonly employed in low Earth orbit(LEO)environments are highly susceptible to atomic oxygen(AO)attack,leading to severe degradation and deterioration of their properties.To address this challenge,3-glycidyloxypropyltrimethoxysilane-modified hexagonal boron nitride(h-BN@KH560)nanohybrids were synthesized and incorporated into epoxy(EP)composites to enhance their AO erosion resistance.The resulting hexagonal boron nitride-based epoxy nanocomposites(FBN/EP)were systematically evaluated for their tribological performance and AO erosion resistance using a series of characterization techniques.The results demonstrated that the incorporation of h-BN@KH560 nanohybrids significantly improved the wear resistance and AO erosion resistance of the EP matrix.Specific ally,the FBN_(1.0)/EP nanocomposite exhibited an 86.1%reduction in wear rate compared to pure EP,while FBN_(5.0)/EP nanocomposite achieved optimal AO erosion resistance,with a minimal erosion rate of 3.58×10^(-24)cm^(3)atoms^(-1)at an AO dose of 1.2×10^(21)atoms cm^(-2).These findings indicate that the incorporating content-induced distribution of h-BN@KH560 within the EP matrix strongly influences the wear resistance of FBN/EP nanocomposites,but there is a relatively minor effect on their AO erosion resistance.The enhanced AO erosion resistance is attributed to the synergistic barrier protection provided by h-BN@KH560 and the formed B_(2)O_(3)and SiO_(2)layers under AO irradiation.This study offers a promising strategy for extending the service life of epoxy nanocomposites in harsh LEO environments.
基金Supported by Funding for Clinical Trials from the Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University,No.2021-LCYJ-MS-11.
文摘Esophageal cancer(EC),a common malignant tumor of the digestive tract,requires early diagnosis and timely treatment to improve patient prognosis.Automated detection of EC using medical imaging has the potential to increase screening efficiency and diagnostic accuracy,thereby significantly improving long-term survival rates and the quality of life of patients.Recent advances in deep learning(DL),particularly convolutional neural networks,have demons-trated remarkable performance in medical imaging analysis.These techniques have shown significant progress in the automated identification of malignant tumors,quantitative analysis of lesions,and improvement in diagnostic accuracy and efficiency.This article comprehensively examines the research progress of DL in medical imaging for EC,covering various imaging modalities such as digital pathology,endoscopy,computed tomography,etc.It explores the clinical value and application prospects of DL in EC screening and diagnosis.Additionally,the article addresses several critical challenges that must be overcome for the clinical translation of DL techniques,including constructing high-quality datasets,promoting multimodal feature fusion,and optimizing artificial intelligence-clinical workflow integration.By providing a detailed overview of the current state of DL in EC imaging and highlighting the key challenges and future directions,this article aims to guide future research and facilitate the clinical implementation of DL technologies in EC management,ultimately contributing to better patient outcomes.
基金supported by the National Natural Science Foundation of China(Grant No.:81473329)the Natural Science Basic Research Program of Shaanxi Province,China(Grant No.:2023-JC-JQ-61)+1 种基金the Science and Technology Project of Shaanxi Province in China(Grant No.:2022YWZX-PG-01)the Scientific Research Project of Shaanxi Administration of Traditional Chinese Medicine,China(Grant Nos.:2019-GJ-JC012,2021-04-ZZ-001,2021-QYPT-003,and 2022-SLRH-YQ-004).
文摘Hepatocellular carcinoma(HCC)expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming.Aldolase A(ALDOA)plays a prominent role in glycolysis;however,little is known about its role in HCC development.In the present study,we aim to explore how ALDOA is involved in HCC proliferation.HCC proliferation was markedly suppressed both in vitro and in vivo following ALDOA knockout,which is consistent with ALDOA overexpression encouraging HCC proliferation.Mechanistically,ALDOA knockout partially limits the glycolytic flux in HCC cells.Meanwhile,ALDOA translocated to nuclei and directly interacted with c-Jun to facilitate its Thr93 phosphorylation by P21-activated protein kinase;ALDOA knockout markedly diminished c-Jun Thr93 phosphorylation and then dampened c-Jun transcription function.A crucial site Y364 mutation in ALDOA disrupted its interaction with c-Jun,and Y364S ALDOA expression failed to rescue cell proliferation in ALDOA deletion cells.In HCC patients,the expression level of ALDOA was correlated with the phosphorylation level of c-Jun(Thr93)and poor prognosis.Remarkably,hepatic ALDOA was significantly upregulated in the promotion and progression stages of diethylnitrosamine-induced HCC models,and the knockdown of Aldoa strikingly decreased HCC development in vivo.Our study demonstrated that ALDOA is a vital driver for HCC development by activating c-Jun-mediated oncogene transcription,opening additional avenues for anti-cancer therapies.
文摘Objective: To evaluate the cost-utility of nivolumab plus chemotherapy compared with chemotherapy alone as the first-line treatment for advanced gastric, gastro-oesophageal junction, and esophageal adenocarcinoma in China. Methods: Based on CheckMate649, a partitioned survival model was carried out with a circulation cycle of 6 weeks to simulate the patient’s lifetime. Sensitivity analysis were adopted to verify the robustness of the results. Results: The results of the base-case analysis showed that both the total cost and utility of the nivolumab group were higher, and the ICUR value was CNY 267498.67/QALY, more than 3 times the GDP per capita of China in 2020. The results of deterministic sensitivity analysis indicated that the three most influential factors were the utility value of PFS state, the cost of nivolumab and the discount rate. The results of probabilistic sensitivity analysis were consistent with those of base-case analysis, proving that the results were robust. The scenario analysis illustrated that economical price of nivolumab was CNY 3652.71. Conclusions: Under the willing-to-pay threshold of three times the GDP per capita of China in 2020, compared with chemotherapy alone, nivolumab plus chemotherapy is not a cost-effective option in China.
