Laser additively manufactured microscale metallic lattices show great potential for high-performance applications,yet trade-offs among geometric precision,structural integrity,and computational efficiency still persis...Laser additively manufactured microscale metallic lattices show great potential for high-performance applications,yet trade-offs among geometric precision,structural integrity,and computational efficiency still persist.Here,we introduce a stereolithography file format-free(STL-free)hybrid toolpath generation method for laser-based powder bed fusion(PBF-LB)that synergizes implicit geometric modeling with optimized laser scanning strategy,overcoming these limitations.By circumventing traditional mesh-based workflows,our method directly translates implicit lattice geometries into laser toolpaths while precisely regulating energy deposition trajectories.This mesh-free process enables the fabrication of complex shell lattices with ultra-thin walls and enhanced surface quality.In addition to reducing memory usage and processing time by up to 90%,the method yields a synergistic enhancement in mechanical performance,notably improving both strength and toughness.By bridging computational design and fabrication,this framework enables the scalable production of high-performance microscale lattices and unlocks their potential for industrial applications.展开更多
Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-...Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.展开更多
The Ordos Basin is a large superimposed hydrocarbon-bearing basin in China,and further research on the sedimentary characteristics and sedimentary evolution of the sequence framework of target layers is of great theor...The Ordos Basin is a large superimposed hydrocarbon-bearing basin in China,and further research on the sedimentary characteristics and sedimentary evolution of the sequence framework of target layers is of great theoretical and practical significance for guiding oil and gas exploration.The sedimentary facies and sedimentary evolution of the high-resolution sequence framework of the Carboniferous Taiyuan Formation in the Hangjinqi area have been systematically analyzed for the first time by drilling,logging and seismic data.The results show that four types of sequence interfaces can be identified in the Taiyuan Formation:regional unconformity surfaces,scour surfaces,lithologic-lithofacies transformation surfaces and flooding surfaces.According to the sedimentary response caused by the upward and downward movements of the base level at different levels,the Taiyuan Formation can be divided into 2 long-term cycles(LSC_(1)-LSC_(2)),4 mid-term cycles(MSC_(1)-MSC4)and 7 short-term cycles(SSC_(1)-SSC7).The long-and mid-term cycles correspond to members T_(1)and T_(2)and layers T_(1)-1,T_(1-2),T_(2-1),and T_(2)-2,respectively.Long-term cycles are dominated by C_(1);mid-term cycles are dominated by C_(1)and C_(2),followed by A2;and short-term cycles are dominated by C_(1),C_(2),A1 and A2.Under the high-resolution sequence stratigraphic framework,the Hangjinqi area underwent a transformation of fan delta and tidal flat depositional systems during the Taiyuan Formation sedimentary period.In the MSC_(1)-MSC_(2)stage,owing to a large-scale paleocontinent,the fan delta sedimentary body,which was limited in scale and scope,developed only in the southeastern corner and gradually transitioned basinward to tidal flat facies.In the MSC3-MSC4 stage,as the paleocontinent continuously decreased and the sedimentary range expanded,fan-delta plain sedimentation began in the study area.Several braided distributary channels with poor connectivity developed on the fan-delta plain,and between them were floodplains and peat swamps.展开更多
Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,w...Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.展开更多
High-resolution transmission electron microscopy(HRTEM)promises rapid atomic-scale dynamic structure imaging.Yet,the precision limitations of aberration parameters and the challenge of eliminating aberrations in Cs-co...High-resolution transmission electron microscopy(HRTEM)promises rapid atomic-scale dynamic structure imaging.Yet,the precision limitations of aberration parameters and the challenge of eliminating aberrations in Cs-corrected transmission electron microscopy constrain resolution.A machine learning algorithm is developed to determine the aberration parameters with higher precision from small,lattice-periodic crystal images.The proposed algorithm is then validated with simulated HRTEM images of graphene and applied to the experimental images of a molybdenum disulfide(MoS_(2))monolayer with 25 variables(14 aberrations)resolved in wide ranges.Using these measured parameters,the phases of the exit-wave functions are reconstructed for each image in a focal series of MoS_(2)monolayers.The images were acquired due to the unexpected movement of the specimen holder.Four-dimensional data extraction reveals time-varying atomic structures and ripple.In particular,the atomic evolution of the sulfur-vacancy point and line defects,as well as the edge structure near the amorphous,is visualized as the resolution has been improved from about 1.75?to 0.9 A.This method can help salvage important transmission electron microscope images and is beneficial for the images obtained from electron microscopes with average stability.展开更多
[Objective]The paper aimed to effectively reduce the occurrence of bacterial resistance associated with breeding practices and to mitigate food safety risks by controlling the illegal use of veterinary drugs in self-f...[Objective]The paper aimed to effectively reduce the occurrence of bacterial resistance associated with breeding practices and to mitigate food safety risks by controlling the illegal use of veterinary drugs in self-formulated feed at the source.[Method]A screening database comprising 274 illegally added chemical drugs in self-formulated feed was established utilizing ultra-performance liquid chromatography coupled with quadrupole/electrostatic field orbitrap high-resolution mass spectrometry(HPLC-Q-Exactive Focus/MS).Subsequently,253 batches of self-formulated feed samples from various farms in Hebei Province were screened and quantitatively analyzed.[Result]The screening results indicated the presence of 8 pharmaceutical components across 10 batches of self-formulated feed samples,with a detection rate of 3.2%and concentrations ranging from 0.06 to 28851.8μg/g.[Conclusion]The application of high-resolution mass spectrometry is feasible and highly significant for the risk monitoring of illegally added drugs in self-formulated feed.展开更多
While algorithms have been created for land usage in urban settings,there have been few investigations into the extraction of urban footprint(UF).To address this research gap,the study employs several widely used imag...While algorithms have been created for land usage in urban settings,there have been few investigations into the extraction of urban footprint(UF).To address this research gap,the study employs several widely used image classification method classified into three categories to evaluate their segmentation capabilities for extracting UF across eight cities.The results indicate that pixel-based methods only excel in clear urban environments,and their overall accuracy is not consistently high.RF and SVM perform well but lack stability in object-based UF extraction,influenced by feature selection and classifier performance.Deep learning enhances feature extraction but requires powerful computing and faces challenges with complex urban layouts.SAM excels in medium-sized urban areas but falters in intricate layouts.Integrating traditional and deep learning methods optimizes UF extraction,balancing accuracy and processing efficiency.Future research should focus on adapting algorithms for diverse urban landscapes to enhance UF extraction accuracy and applicability.展开更多
BACKGROUND Rectal cancer is a common malignant tumor of the digestive system,with older patients representing the predominantly affected population.Magnetic resonance imaging(MRI)has been widely applied in preoperativ...BACKGROUND Rectal cancer is a common malignant tumor of the digestive system,with older patients representing the predominantly affected population.Magnetic resonance imaging(MRI)has been widely applied in preoperative tumor assessment;however,the value of high-resolution MRI(HR-MRI)combined with dynamic contrast-enhanced(DCE)scanning in the preoperative diagnosis of rectal cancer in older patients remains unclear.AIM To evaluate the value of HR-MRI combined with DCE scanning in the preoperative diagnosis of rectal cancer in older patients.METHODS This retrospective study included 148 consecutive older female patients with rectal cancer who were treated at our hospital between December 2020 and December 2024.Clinical data and HR-MRI and DCE scan findings were collected.Histopathological examination after surgical resection served as the gold standard.The diagnostic accuracy of MRI for preoperative T and N staging was calculated.Consistency,sensitivity,and specificity between HR-MRI combined with DCE scanning and pathological staging were analyzed using the k test.Among the 148 patients,the overall accuracy of T staging was 84.5%.Sensitivity for T1,T2,T3,and T4 staging was 75.00%,62.50%,89.47%,and 90.48%,respectively,whereas specificity was 100.00%,94.35%,79.25%,and 96.06%,respectively.T staging based on HR-MRI combined with DCE scanning showed good agreement with pathological staging(k=0.8176,P<0.001).For N staging,sensitivity and specificity were 54.88%and 84.85%for N0,36.96%and 72.55%for N1,and 70.00%and 73.44%for N2,respectively;agreement with pathological N staging was poor(k=0.259,P<0.001).CONCLUSION HR-MRI combined with DCE scanning demonstrates high diagnostic accuracy for T staging of rectal cancer in older patients and can provide a theoretical basis for treatment planning.However,its diagnostic accuracy for N staging requires improvement.展开更多
Severe acute respiratory syndrome (SARS) is an acute respiratory infectious disease caused by a novel coronavirus, firstly broke out in November 2002 in Guangdong and prevailed quickly in Beijing, Hong Kong, Taiwan an...Severe acute respiratory syndrome (SARS) is an acute respiratory infectious disease caused by a novel coronavirus, firstly broke out in November 2002 in Guangdong and prevailed quickly in Beijing, Hong Kong, Taiwan and other regions of China. It was one of the most potential pandemic diseases and had affected more than 20 other countries.^(1,2) There have been a lot of resear-ches^(2-7) in terms of its etiology, epidemiology, pathogenesis, clinical characteristics, diagnostics, treatment and prevention, vaccines and so on.Along with control of the epidemic situation, a great number of SARS patients were in the recovery phase, therefore, we undertook a half-year follow-up investigation on their clinical, laboratory and image situations.展开更多
基金financial support of the Hong Kong Special Administrative Region University Grants Committee—General Research Fund CUHK14209523Collaborative Research Fund C4074-22G,C4002-22Y and C7074-23Gsupport by the University of Massachusetts Amherst。
文摘Laser additively manufactured microscale metallic lattices show great potential for high-performance applications,yet trade-offs among geometric precision,structural integrity,and computational efficiency still persist.Here,we introduce a stereolithography file format-free(STL-free)hybrid toolpath generation method for laser-based powder bed fusion(PBF-LB)that synergizes implicit geometric modeling with optimized laser scanning strategy,overcoming these limitations.By circumventing traditional mesh-based workflows,our method directly translates implicit lattice geometries into laser toolpaths while precisely regulating energy deposition trajectories.This mesh-free process enables the fabrication of complex shell lattices with ultra-thin walls and enhanced surface quality.In addition to reducing memory usage and processing time by up to 90%,the method yields a synergistic enhancement in mechanical performance,notably improving both strength and toughness.By bridging computational design and fabrication,this framework enables the scalable production of high-performance microscale lattices and unlocks their potential for industrial applications.
基金supported by the Natural Science Foundation of Hubei Provincial Department of Education(D20232101)Shandong Second Medical University 2024 Affiliated Hospital(Teaching Hospital)Scientific Research Development Fund Project(2024FYQ026)+3 种基金the innovative Research Programme of Xiangyang No.1 People’s Hospital(XYY2023ZY01)Faculty Development Grants of Xiangyang No.1 People’s Hospital Affiliated to Hubei University of Medicine(XYY2023D05)Joint supported by Hubei Provincial Natural Science Foundation and Xiangyang of China(2025AFD091)Traditional Chinese Medicine Scientific Research Project of Hubei Provincial Administration of Traditional Chinese Medicine(ZY2025D019).
文摘Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.
基金supported by the Fundamental Research Funds for the Liaoning Universities(Grant No.LJ202410166012).
文摘The Ordos Basin is a large superimposed hydrocarbon-bearing basin in China,and further research on the sedimentary characteristics and sedimentary evolution of the sequence framework of target layers is of great theoretical and practical significance for guiding oil and gas exploration.The sedimentary facies and sedimentary evolution of the high-resolution sequence framework of the Carboniferous Taiyuan Formation in the Hangjinqi area have been systematically analyzed for the first time by drilling,logging and seismic data.The results show that four types of sequence interfaces can be identified in the Taiyuan Formation:regional unconformity surfaces,scour surfaces,lithologic-lithofacies transformation surfaces and flooding surfaces.According to the sedimentary response caused by the upward and downward movements of the base level at different levels,the Taiyuan Formation can be divided into 2 long-term cycles(LSC_(1)-LSC_(2)),4 mid-term cycles(MSC_(1)-MSC4)and 7 short-term cycles(SSC_(1)-SSC7).The long-and mid-term cycles correspond to members T_(1)and T_(2)and layers T_(1)-1,T_(1-2),T_(2-1),and T_(2)-2,respectively.Long-term cycles are dominated by C_(1);mid-term cycles are dominated by C_(1)and C_(2),followed by A2;and short-term cycles are dominated by C_(1),C_(2),A1 and A2.Under the high-resolution sequence stratigraphic framework,the Hangjinqi area underwent a transformation of fan delta and tidal flat depositional systems during the Taiyuan Formation sedimentary period.In the MSC_(1)-MSC_(2)stage,owing to a large-scale paleocontinent,the fan delta sedimentary body,which was limited in scale and scope,developed only in the southeastern corner and gradually transitioned basinward to tidal flat facies.In the MSC3-MSC4 stage,as the paleocontinent continuously decreased and the sedimentary range expanded,fan-delta plain sedimentation began in the study area.Several braided distributary channels with poor connectivity developed on the fan-delta plain,and between them were floodplains and peat swamps.
基金funded by the National Natural Science Foundation of China(62273213,62472262,62572287)Natural Science Foundation of Shandong Province(ZR2024MF144)+1 种基金Natural Science Foundation of Shandong Province for Innovation and Development Joint Funds(ZR2022LZH001)Taishan Scholarship Construction Engineering.
文摘Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.
基金financial support from the National Natural Science Foundation of China(Grant No.61971201)。
文摘High-resolution transmission electron microscopy(HRTEM)promises rapid atomic-scale dynamic structure imaging.Yet,the precision limitations of aberration parameters and the challenge of eliminating aberrations in Cs-corrected transmission electron microscopy constrain resolution.A machine learning algorithm is developed to determine the aberration parameters with higher precision from small,lattice-periodic crystal images.The proposed algorithm is then validated with simulated HRTEM images of graphene and applied to the experimental images of a molybdenum disulfide(MoS_(2))monolayer with 25 variables(14 aberrations)resolved in wide ranges.Using these measured parameters,the phases of the exit-wave functions are reconstructed for each image in a focal series of MoS_(2)monolayers.The images were acquired due to the unexpected movement of the specimen holder.Four-dimensional data extraction reveals time-varying atomic structures and ripple.In particular,the atomic evolution of the sulfur-vacancy point and line defects,as well as the edge structure near the amorphous,is visualized as the resolution has been improved from about 1.75?to 0.9 A.This method can help salvage important transmission electron microscope images and is beneficial for the images obtained from electron microscopes with average stability.
基金Supported by the Earmarked Fund for Hebei Agriculture Research System(HBCT2024260407)。
文摘[Objective]The paper aimed to effectively reduce the occurrence of bacterial resistance associated with breeding practices and to mitigate food safety risks by controlling the illegal use of veterinary drugs in self-formulated feed at the source.[Method]A screening database comprising 274 illegally added chemical drugs in self-formulated feed was established utilizing ultra-performance liquid chromatography coupled with quadrupole/electrostatic field orbitrap high-resolution mass spectrometry(HPLC-Q-Exactive Focus/MS).Subsequently,253 batches of self-formulated feed samples from various farms in Hebei Province were screened and quantitatively analyzed.[Result]The screening results indicated the presence of 8 pharmaceutical components across 10 batches of self-formulated feed samples,with a detection rate of 3.2%and concentrations ranging from 0.06 to 28851.8μg/g.[Conclusion]The application of high-resolution mass spectrometry is feasible and highly significant for the risk monitoring of illegally added drugs in self-formulated feed.
文摘While algorithms have been created for land usage in urban settings,there have been few investigations into the extraction of urban footprint(UF).To address this research gap,the study employs several widely used image classification method classified into three categories to evaluate their segmentation capabilities for extracting UF across eight cities.The results indicate that pixel-based methods only excel in clear urban environments,and their overall accuracy is not consistently high.RF and SVM perform well but lack stability in object-based UF extraction,influenced by feature selection and classifier performance.Deep learning enhances feature extraction but requires powerful computing and faces challenges with complex urban layouts.SAM excels in medium-sized urban areas but falters in intricate layouts.Integrating traditional and deep learning methods optimizes UF extraction,balancing accuracy and processing efficiency.Future research should focus on adapting algorithms for diverse urban landscapes to enhance UF extraction accuracy and applicability.
基金Supported by Tianjin Key Medical Discipline(Specialty)Construction Project,No.TJYXZDXK-3-012B.
文摘BACKGROUND Rectal cancer is a common malignant tumor of the digestive system,with older patients representing the predominantly affected population.Magnetic resonance imaging(MRI)has been widely applied in preoperative tumor assessment;however,the value of high-resolution MRI(HR-MRI)combined with dynamic contrast-enhanced(DCE)scanning in the preoperative diagnosis of rectal cancer in older patients remains unclear.AIM To evaluate the value of HR-MRI combined with DCE scanning in the preoperative diagnosis of rectal cancer in older patients.METHODS This retrospective study included 148 consecutive older female patients with rectal cancer who were treated at our hospital between December 2020 and December 2024.Clinical data and HR-MRI and DCE scan findings were collected.Histopathological examination after surgical resection served as the gold standard.The diagnostic accuracy of MRI for preoperative T and N staging was calculated.Consistency,sensitivity,and specificity between HR-MRI combined with DCE scanning and pathological staging were analyzed using the k test.Among the 148 patients,the overall accuracy of T staging was 84.5%.Sensitivity for T1,T2,T3,and T4 staging was 75.00%,62.50%,89.47%,and 90.48%,respectively,whereas specificity was 100.00%,94.35%,79.25%,and 96.06%,respectively.T staging based on HR-MRI combined with DCE scanning showed good agreement with pathological staging(k=0.8176,P<0.001).For N staging,sensitivity and specificity were 54.88%and 84.85%for N0,36.96%and 72.55%for N1,and 70.00%and 73.44%for N2,respectively;agreement with pathological N staging was poor(k=0.259,P<0.001).CONCLUSION HR-MRI combined with DCE scanning demonstrates high diagnostic accuracy for T staging of rectal cancer in older patients and can provide a theoretical basis for treatment planning.However,its diagnostic accuracy for N staging requires improvement.
文摘Severe acute respiratory syndrome (SARS) is an acute respiratory infectious disease caused by a novel coronavirus, firstly broke out in November 2002 in Guangdong and prevailed quickly in Beijing, Hong Kong, Taiwan and other regions of China. It was one of the most potential pandemic diseases and had affected more than 20 other countries.^(1,2) There have been a lot of resear-ches^(2-7) in terms of its etiology, epidemiology, pathogenesis, clinical characteristics, diagnostics, treatment and prevention, vaccines and so on.Along with control of the epidemic situation, a great number of SARS patients were in the recovery phase, therefore, we undertook a half-year follow-up investigation on their clinical, laboratory and image situations.
