目的系统评价“补虚化浊法”中药联合抗血管内皮生长因子(VEGF)治疗湿性年龄相关性黄斑变性(wAMD)的临床疗效。方法检索PubMed、Web of Science、Embase、中国知网、万方、维普、中国生物医学文献数据库中应用“补虚化浊法”中药治疗wAM...目的系统评价“补虚化浊法”中药联合抗血管内皮生长因子(VEGF)治疗湿性年龄相关性黄斑变性(wAMD)的临床疗效。方法检索PubMed、Web of Science、Embase、中国知网、万方、维普、中国生物医学文献数据库中应用“补虚化浊法”中药治疗wAMD的随机对照试验文献,检索时间为建库至2023年5月31日,对文献按照纳入标准与排除标准进行筛选和数据录取,采用Cochrane软件评价文献质量,采用RevMan 5.4软件进行统计分析。结果共纳入13项研究,包括患者1,002例(1,041只眼),其中采用“补虚化浊法”联合抗VEGF治疗的治疗组501例(523只眼),单纯抗VEGF治疗的对照组501例(518只眼)。治疗组在提高国际标准视力[MD=0.100,95%CI(0.050,0.140),Z=4.310,P=0.000]、LogMAR视力[MD=-0.080,95%CI(-0.110,-0.050),Z=5.560,P=0.000]、视力总有效率[OR=2.070,95%CI(1.280,3.340),Z=2.970,P=0.000]、降低黄斑中心凹厚度[MD=-19.130,95%CI(-24.940,-13.310),Z=6.450,P=0.000]、提高荧光渗漏吸收率[OR=4.910,95%CI(2.870,8.400),Z=5.800,P=0.000]、提高临床总有效率[OR=3.810,95%CI(1.990,7.310),Z=4.030,P=0.000]方面优于对照组,差异均有统计学意义。结论“补虚化浊法”中药联合抗VEGF治疗wAMD疗效优于单纯抗VEGF治疗。展开更多
工作福利是减少福利依赖、激活救助对象的主要公共政策。以2001—2021年在Web of Science数据库核心合集收录的487篇工作福利主题的文献为研究对象,采用文献计量分析法,梳理工作福利主题的文献研究动态和热点演进过程,并结合关键节点文...工作福利是减少福利依赖、激活救助对象的主要公共政策。以2001—2021年在Web of Science数据库核心合集收录的487篇工作福利主题的文献为研究对象,采用文献计量分析法,梳理工作福利主题的文献研究动态和热点演进过程,并结合关键节点文献分析该领域的前沿和重点。研究发现,工作福利前沿聚焦在劳动力市场视角、社会政策视角、分群分类视角三方面。未来,国内工作福利研究的主题将集中在对于城乡领域工作福利实践模式、工作福利的激活和减贫机制进行实证研究,构建中国特色的“激活”分析框架,以及丰富中国情境下的工作福利理论体系。展开更多
In medical image segmentation task,convolutional neural networks(CNNs)are difficult to capture long-range dependencies,but transformers can model the long-range dependencies effectively.However,transformers have a fle...In medical image segmentation task,convolutional neural networks(CNNs)are difficult to capture long-range dependencies,but transformers can model the long-range dependencies effectively.However,transformers have a flexible structure and seldom assume the structural bias of input data,so it is difficult for transformers to learn positional encoding of the medical images when using fewer images for training.To solve these problems,a dual branch structure is proposed.In one branch,Mix-Feed-Forward Network(Mix-FFN)and axial attention are adopted to capture long-range dependencies and keep the translation invariance of the model.Mix-FFN whose depth-wise convolutions can provide position information is better than ordinary positional encoding.In the other branch,traditional convolutional neural networks(CNNs)are used to extract different features of fewer medical images.In addition,the attention fusion module BiFusion is used to effectively integrate the information from the CNN branch and Transformer branch,and the fused features can effectively capture the global and local context of the current spatial resolution.On the public standard datasets Gland Segmentation(GlaS),Colorectal adenocarcinoma gland(CRAG)and COVID-19 CT Images Segmentation,the F1-score,Intersection over Union(IoU)and parameters of the proposed TC-Fuse are superior to those by Axial Attention U-Net,U-Net,Medical Transformer and other methods.And F1-score increased respectively by 2.99%,3.42%and 3.95%compared with Medical Transformer.展开更多
Accurate and reliable crack segmentation is a challenge and meaningful task.In this article,aiming at the characteristics of cracks on the concrete images,the intensity frequency information of source images which is ...Accurate and reliable crack segmentation is a challenge and meaningful task.In this article,aiming at the characteristics of cracks on the concrete images,the intensity frequency information of source images which is obtained by Discrete Wavelet Transform(DWT)is fed into deep learning-based networks to enhance the ability of network on crack segmentation.To well integrate frequency information into network an effective and novel DWTA module based on the DWT and scSE attention mechanism is proposed.The semantic information of cracks is enhanced and the irrelevant information is suppressed by DWTA module.And the gap between frequency information and convolution information from network is balanced by DWTA module which can well fuse wavelet information into image segmentation network.The Unet-DWTA is proposed to preserved the information of crack boundary and thin crack in intermediate feature maps by adding DWTA module in the encoderdecoder structures.In decoder,diverse level feature maps are fused to capture the information of crack boundary and the abstract semantic information which is beneficial to crack pixel classification.The proposed method is verified on three classic datasets including CrackDataset,CrackForest,and DeepCrack datasets.Compared with the other crack methods,the proposed Unet-DWTA shows better performance based on the evaluation of the subjective analysis and objective metrics about image semantic segmentation.展开更多
BACKGROUND Renal pelvis sarcomatoid carcinoma(RPSC)is a rare and aggressive malignancy whose diagnosis is difficult because radiological imaging results can lead to misclassification as a more common type of renal tum...BACKGROUND Renal pelvis sarcomatoid carcinoma(RPSC)is a rare and aggressive malignancy whose diagnosis is difficult because radiological imaging results can lead to misclassification as a more common type of renal tumor.In addition,clinical management of patients with RPSC is difficult because of the limited efficacy of available treatments.In this study,we present a comprehensive description of a patient who presented with RPSC and a simultaneous renal vein tumor thrombus.CASE SUMMARY During April,2020,a 64-year-old female presented with an isolated episode of hematuria accompanied by abdominal pain.Computed tomography(CT)and magnetic resonance imaging(MRI)showed a lesion in the right renal pelvis.We therefore performed a radical nephrectomy of the right kidney.The subsequent histopathological and immunological results verified the diagnosis of RPSC.Despite administration of 6 cycles of a gemcitabine-cisplatin regimen,the patient's condition progressively deteriorated,and she died about 15 mo after the nephrectomy.CONCLUSION We performed a comprehensive analysis of a patient with RPSC that included CT,MRI,immunohistochemistry,and genetic testing.The insights from our detailed analysis of this patient and our concomitant review of the literature may assist clinicians in their diagnosis and treatment of RPSC.展开更多
文摘目的系统评价“补虚化浊法”中药联合抗血管内皮生长因子(VEGF)治疗湿性年龄相关性黄斑变性(wAMD)的临床疗效。方法检索PubMed、Web of Science、Embase、中国知网、万方、维普、中国生物医学文献数据库中应用“补虚化浊法”中药治疗wAMD的随机对照试验文献,检索时间为建库至2023年5月31日,对文献按照纳入标准与排除标准进行筛选和数据录取,采用Cochrane软件评价文献质量,采用RevMan 5.4软件进行统计分析。结果共纳入13项研究,包括患者1,002例(1,041只眼),其中采用“补虚化浊法”联合抗VEGF治疗的治疗组501例(523只眼),单纯抗VEGF治疗的对照组501例(518只眼)。治疗组在提高国际标准视力[MD=0.100,95%CI(0.050,0.140),Z=4.310,P=0.000]、LogMAR视力[MD=-0.080,95%CI(-0.110,-0.050),Z=5.560,P=0.000]、视力总有效率[OR=2.070,95%CI(1.280,3.340),Z=2.970,P=0.000]、降低黄斑中心凹厚度[MD=-19.130,95%CI(-24.940,-13.310),Z=6.450,P=0.000]、提高荧光渗漏吸收率[OR=4.910,95%CI(2.870,8.400),Z=5.800,P=0.000]、提高临床总有效率[OR=3.810,95%CI(1.990,7.310),Z=4.030,P=0.000]方面优于对照组,差异均有统计学意义。结论“补虚化浊法”中药联合抗VEGF治疗wAMD疗效优于单纯抗VEGF治疗。
文摘工作福利是减少福利依赖、激活救助对象的主要公共政策。以2001—2021年在Web of Science数据库核心合集收录的487篇工作福利主题的文献为研究对象,采用文献计量分析法,梳理工作福利主题的文献研究动态和热点演进过程,并结合关键节点文献分析该领域的前沿和重点。研究发现,工作福利前沿聚焦在劳动力市场视角、社会政策视角、分群分类视角三方面。未来,国内工作福利研究的主题将集中在对于城乡领域工作福利实践模式、工作福利的激活和减贫机制进行实证研究,构建中国特色的“激活”分析框架,以及丰富中国情境下的工作福利理论体系。
基金supported in part by the National Natural Science Foundation of China under Grant 61972267the National Natural Science Foundation of Hebei Province under Grant F2018210148+1 种基金the University Science Research Project of Hebei Province under Grant ZD2021334the Science and Technology Project of Hebei Education Department(ZD2022098).
文摘In medical image segmentation task,convolutional neural networks(CNNs)are difficult to capture long-range dependencies,but transformers can model the long-range dependencies effectively.However,transformers have a flexible structure and seldom assume the structural bias of input data,so it is difficult for transformers to learn positional encoding of the medical images when using fewer images for training.To solve these problems,a dual branch structure is proposed.In one branch,Mix-Feed-Forward Network(Mix-FFN)and axial attention are adopted to capture long-range dependencies and keep the translation invariance of the model.Mix-FFN whose depth-wise convolutions can provide position information is better than ordinary positional encoding.In the other branch,traditional convolutional neural networks(CNNs)are used to extract different features of fewer medical images.In addition,the attention fusion module BiFusion is used to effectively integrate the information from the CNN branch and Transformer branch,and the fused features can effectively capture the global and local context of the current spatial resolution.On the public standard datasets Gland Segmentation(GlaS),Colorectal adenocarcinoma gland(CRAG)and COVID-19 CT Images Segmentation,the F1-score,Intersection over Union(IoU)and parameters of the proposed TC-Fuse are superior to those by Axial Attention U-Net,U-Net,Medical Transformer and other methods.And F1-score increased respectively by 2.99%,3.42%and 3.95%compared with Medical Transformer.
基金National Natural Science Foundation of China under Grant 61972267National Natural Science Foundation of Hebei Province under Grant F2018210148University Science Research Project of Hebei Province under Grant ZD2021334。
文摘Accurate and reliable crack segmentation is a challenge and meaningful task.In this article,aiming at the characteristics of cracks on the concrete images,the intensity frequency information of source images which is obtained by Discrete Wavelet Transform(DWT)is fed into deep learning-based networks to enhance the ability of network on crack segmentation.To well integrate frequency information into network an effective and novel DWTA module based on the DWT and scSE attention mechanism is proposed.The semantic information of cracks is enhanced and the irrelevant information is suppressed by DWTA module.And the gap between frequency information and convolution information from network is balanced by DWTA module which can well fuse wavelet information into image segmentation network.The Unet-DWTA is proposed to preserved the information of crack boundary and thin crack in intermediate feature maps by adding DWTA module in the encoderdecoder structures.In decoder,diverse level feature maps are fused to capture the information of crack boundary and the abstract semantic information which is beneficial to crack pixel classification.The proposed method is verified on three classic datasets including CrackDataset,CrackForest,and DeepCrack datasets.Compared with the other crack methods,the proposed Unet-DWTA shows better performance based on the evaluation of the subjective analysis and objective metrics about image semantic segmentation.
基金Science and Technology Development Program of Jilin Province,No.2020122256JC and No.20200201602JC.
文摘BACKGROUND Renal pelvis sarcomatoid carcinoma(RPSC)is a rare and aggressive malignancy whose diagnosis is difficult because radiological imaging results can lead to misclassification as a more common type of renal tumor.In addition,clinical management of patients with RPSC is difficult because of the limited efficacy of available treatments.In this study,we present a comprehensive description of a patient who presented with RPSC and a simultaneous renal vein tumor thrombus.CASE SUMMARY During April,2020,a 64-year-old female presented with an isolated episode of hematuria accompanied by abdominal pain.Computed tomography(CT)and magnetic resonance imaging(MRI)showed a lesion in the right renal pelvis.We therefore performed a radical nephrectomy of the right kidney.The subsequent histopathological and immunological results verified the diagnosis of RPSC.Despite administration of 6 cycles of a gemcitabine-cisplatin regimen,the patient's condition progressively deteriorated,and she died about 15 mo after the nephrectomy.CONCLUSION We performed a comprehensive analysis of a patient with RPSC that included CT,MRI,immunohistochemistry,and genetic testing.The insights from our detailed analysis of this patient and our concomitant review of the literature may assist clinicians in their diagnosis and treatment of RPSC.
