BACKGROUND Chemotherapy for malignant tumors can cause brain changes and cognitive impairment,leading to chemotherapy-induced cognitive impairment(CICI).Current research on CICI has focused on breast cancer and Hodgki...BACKGROUND Chemotherapy for malignant tumors can cause brain changes and cognitive impairment,leading to chemotherapy-induced cognitive impairment(CICI).Current research on CICI has focused on breast cancer and Hodgkin’s lymphoma.Whether patients with non-Hodgkin’s lymphoma(NHL)undergoing chemo-therapy have cognitive impairment has not been fully investigated.therapy have cognitive impairment has not been fully investigated.AIM To investigate whether NHL patients undergoing chemotherapy had cognitive impairments.METHODS The study included 100 NHL patients who were required to complete a compre-hensive psychological scale including the Brief Psychiatric Examination Scale(MMSE)at two time points:before chemotherapy and within 2 wk of two chemo-therapy courses.A language proficiency test(VFT),Symbol Number Pattern Test(SDMT),Clock Drawing Test(CDT),Abbreviated Daily Cognition Scale(ECog-12),Prospective and Retrospective Memory Questionnaire,and Karnofsky Perfor-mance Status were used to assess cognitive changes before and after chemo-therapy.RESULTS The VFT scores for before treatment(BT)and after treatment(AT)groups were 45.20±15.62,and 42.30±17.53,respectively(t-2.16,P<0.05).The CDT scores were 8(3.5-9.25)for BT and 7(2.5-9)for AT groups(Z-2.1,P<0.05).Retrospective memory scores were 13.5(9-17)for BT and 15(13-18)for AT(Z-3.7,P<0.01).The prospective memory scores were 12.63±3.61 for BT and 14.43±4.32 for AT groups(t-4.97,P<0.01).The ECog-12 scores were 1.71(1.25-2.08)for BT and 1.79(1.42-2.08)for AT groups(Z-2.84,P<0.01).The SDMT and MMSE values did not show a significant difference between BT and AT groups.CONCLUSION Compared to the AT group,the BT group showed impaired language,memory,and subjective cognition,but objec-tive cognition and execution were not significantly affected.展开更多
Malignant non-Hodgkins lymphoma (MHNL) of the uterus is uncommon. We report a case diagnosed on the basis of histologic and immunohistochemical studies of a hysterectomy specimen induced by a very painful pelvic mass ...Malignant non-Hodgkins lymphoma (MHNL) of the uterus is uncommon. We report a case diagnosed on the basis of histologic and immunohistochemical studies of a hysterectomy specimen induced by a very painful pelvic mass in a 50-year-old patient with no previous history of the disease. It was classified as Ann Arbor IV Bb after imaging, given the medullary infiltration and signs of clinical and biological evolutivity: the patient had received two courses of chemotherapy, CHOP protocol. She died 23 days after the second treatment due to a hypertensive crisis.展开更多
Background:The primary cause of treatment failure in patients with refractory or relapsed B-cell non-Hodgkin lymphoma(r/r B-NHL)is resistance to current therapies,and therapy-induced senescence(TIS)stands out as a cru...Background:The primary cause of treatment failure in patients with refractory or relapsed B-cell non-Hodgkin lymphoma(r/r B-NHL)is resistance to current therapies,and therapy-induced senescence(TIS)stands out as a crucial mechanism contributing to tumor drug resistance.Here,we analyzed SENEX/Rho GTPase Activating Protein 18(ARHGAP18)expression and prognostic significance in doxorubicin-induced B-NHL-TIS model and r/r B-NHL patients,investigating its target in B-NHL cell senescence and the effect of combining specific inhibitors on apoptosis resistance in B-NHL-TIS cells.Methods:Raji cells were transfected with the human SENEX shRNA recombinant lentiviral vector(Sh-SENEX)and the empty vector negative(NC)to construct a stable transfection cell line with knockdown of SENEX.Effect of SENEX-silencing on B-NHL-TIS formation,cell function and cell cycle-related pathways was analyzed.Using doxorubicin(DOX)-inducible senescent B-NHL cells combined with the specific cyclin dependent kinase 4/6(CDK4/6)inhibitor Palbociclib to observe that blocking CDK4/6 effects on TIS formation.SENEX expression of 21 B-NHL patients and 8 healthy controls were analyzed by qRT-PCR,and the correlation between its expression and clinical indicators were evaluated.Results:The downregulation of SENEX expression promotes G1-S phase transition and apoptosis while inhibiting cell proliferation,collectively suppressing the formation of TIS in B-NHL.Blockade of CDK4/6 promotes the DOX-induced G1 phase arrest to enhance TIS formation in B-NHL cells which can reverse the regulatory effect of silencing SENEX on B-NHL cell cycle regulation and senescence.The expression levels of SENEX were notably elevated in B-NHL patients compared to healthy controls,and Elevated expression levels of SENEX were associated with poor prognosis of B-NHL patients.Conclusions:SENEX enhances apoptosis resistance in B-NHL by inhibiting CDK4/6,thereby preventing G1-S phase transition and promoting TIS formation.展开更多
[目的]本文旨在解决在自然环境下不同成熟度苹果目标检测精度较低的问题。[方法]提出了一种改进的YOLOv5s模型SODSTR-YOLOv5s(YOLOv5s with small detection layer and omni-dimensional dynamic convolution and swin transformer bloc...[目的]本文旨在解决在自然环境下不同成熟度苹果目标检测精度较低的问题。[方法]提出了一种改进的YOLOv5s模型SODSTR-YOLOv5s(YOLOv5s with small detection layer and omni-dimensional dynamic convolution and swin transformer block),用于不同成熟度苹果检测。首先改进YOLOv5s的多尺度目标检测层,在Prediction中构建检测160×160特征图的检测头,提高小尺寸的不同成熟度苹果的检测精度;其次在Backbone结构中融合Swin Transformer Block,加强同级成熟度的苹果纹理特征融合,弱化纹理特征分布差异带来的消极影响,提高模型泛化能力;最后将Neck结构的Conv模块替换为动态卷积模块ODConv,细化局部特征映射,实现局部苹果细粒度特征的充分提取。基于不同成熟度苹果数据集进行试验,验证改进模型的性能。[结果]改进模型SODSTR-YOLOv5s检测的精确率、召回率、平均精度均值分别为89.1%、95.5%、93.6%,高、中、低成熟度苹果平均精度均值分别为94.1%、93.1%、93.7%,平均检测时间为16 ms,参数量为7.34 M。相比于YOLOv5s模型,改进模型SODSTR-YOLOv5s精确率、召回率、平均精度均值分别提高了3.8%、5.0%、2.9%,参数量和平均检测时间分别增加了0.32 M和5 ms。[结论]改进模型SODSTR-YOLOv5s提升了在自然环境下对不同成熟度苹果的检测能力,能较好地满足实际采摘苹果的检测要求。展开更多
针对煤矿高噪声、低照度、运动模糊与大批量煤矸混杂等复杂工况环境因素导致煤矸识别存在误检、漏检以及检测精度低的问题,提出一种基于CFS-YOLO算法的煤矸智能识别模型。采用ConvNeXt V2(Convolutional Neural Network with NeXt Units...针对煤矿高噪声、低照度、运动模糊与大批量煤矸混杂等复杂工况环境因素导致煤矸识别存在误检、漏检以及检测精度低的问题,提出一种基于CFS-YOLO算法的煤矸智能识别模型。采用ConvNeXt V2(Convolutional Neural Network with NeXt Units Version 2)特征提取模块替换主干网络末端的2个C3(Cross Stage Partial Bottle Neck Mudule)模块,通过将掩码自动编码器(Masked Autoencoders,MAE)和全局响应归一化(Global Response Normalization,GRN)层添加到ConvNeXt架构中,有效缓解特征崩溃问题以及保持特征在网络传递过程中的多样性;采用Focal-EIOU(Focal and Efficient Intersection Over Union)损失函数替换原CIOU(Computer Intersection Over Union)损失函数,通过其Focal-Loss机制和调整样本权重的方式优化边界框回归任务中的样本不平衡问题,提高模型的收敛速度和定位精度;添加无参注意力机制(Simple Attention Mechanism,SimAM)于主干网络每个C3模块的后端,凭借其注意力权重自适应调整策略,提升模型对尺度变化较大或低分辨率煤矸目标关键特征的提取能力。通过消融试验和对比试验验证所提CFS-YOLO模型的有效性与优越性。试验结果表明:CFS-YOLO模型对于煤矸在煤矿高噪声、低照度、运动模糊与大批量煤矸混杂等复杂环境下的检测效果均得到有效提高,模型的平均精度均值达到90.2%,相较于原YOLOv5s模型的平均精度均值提高了3.7%,平均检测速度达到90.09 FPS,可充分满足煤矸实时检测的需求。同时与YOLOv5s、YOLOv7-tiny与YOLOv8n等6种YOLO系列算法相比,CFS-YOLO模型对煤矿复杂环境的适应性最强且综合检测性能最佳,可为煤矸的智能高效分选提供技术支持。展开更多
文摘BACKGROUND Chemotherapy for malignant tumors can cause brain changes and cognitive impairment,leading to chemotherapy-induced cognitive impairment(CICI).Current research on CICI has focused on breast cancer and Hodgkin’s lymphoma.Whether patients with non-Hodgkin’s lymphoma(NHL)undergoing chemo-therapy have cognitive impairment has not been fully investigated.therapy have cognitive impairment has not been fully investigated.AIM To investigate whether NHL patients undergoing chemotherapy had cognitive impairments.METHODS The study included 100 NHL patients who were required to complete a compre-hensive psychological scale including the Brief Psychiatric Examination Scale(MMSE)at two time points:before chemotherapy and within 2 wk of two chemo-therapy courses.A language proficiency test(VFT),Symbol Number Pattern Test(SDMT),Clock Drawing Test(CDT),Abbreviated Daily Cognition Scale(ECog-12),Prospective and Retrospective Memory Questionnaire,and Karnofsky Perfor-mance Status were used to assess cognitive changes before and after chemo-therapy.RESULTS The VFT scores for before treatment(BT)and after treatment(AT)groups were 45.20±15.62,and 42.30±17.53,respectively(t-2.16,P<0.05).The CDT scores were 8(3.5-9.25)for BT and 7(2.5-9)for AT groups(Z-2.1,P<0.05).Retrospective memory scores were 13.5(9-17)for BT and 15(13-18)for AT(Z-3.7,P<0.01).The prospective memory scores were 12.63±3.61 for BT and 14.43±4.32 for AT groups(t-4.97,P<0.01).The ECog-12 scores were 1.71(1.25-2.08)for BT and 1.79(1.42-2.08)for AT groups(Z-2.84,P<0.01).The SDMT and MMSE values did not show a significant difference between BT and AT groups.CONCLUSION Compared to the AT group,the BT group showed impaired language,memory,and subjective cognition,but objec-tive cognition and execution were not significantly affected.
文摘Malignant non-Hodgkins lymphoma (MHNL) of the uterus is uncommon. We report a case diagnosed on the basis of histologic and immunohistochemical studies of a hysterectomy specimen induced by a very painful pelvic mass in a 50-year-old patient with no previous history of the disease. It was classified as Ann Arbor IV Bb after imaging, given the medullary infiltration and signs of clinical and biological evolutivity: the patient had received two courses of chemotherapy, CHOP protocol. She died 23 days after the second treatment due to a hypertensive crisis.
基金This work was supported by the Major Subject of Science and Technology of Anhui Province(Grant Number:201903a07020030).
文摘Background:The primary cause of treatment failure in patients with refractory or relapsed B-cell non-Hodgkin lymphoma(r/r B-NHL)is resistance to current therapies,and therapy-induced senescence(TIS)stands out as a crucial mechanism contributing to tumor drug resistance.Here,we analyzed SENEX/Rho GTPase Activating Protein 18(ARHGAP18)expression and prognostic significance in doxorubicin-induced B-NHL-TIS model and r/r B-NHL patients,investigating its target in B-NHL cell senescence and the effect of combining specific inhibitors on apoptosis resistance in B-NHL-TIS cells.Methods:Raji cells were transfected with the human SENEX shRNA recombinant lentiviral vector(Sh-SENEX)and the empty vector negative(NC)to construct a stable transfection cell line with knockdown of SENEX.Effect of SENEX-silencing on B-NHL-TIS formation,cell function and cell cycle-related pathways was analyzed.Using doxorubicin(DOX)-inducible senescent B-NHL cells combined with the specific cyclin dependent kinase 4/6(CDK4/6)inhibitor Palbociclib to observe that blocking CDK4/6 effects on TIS formation.SENEX expression of 21 B-NHL patients and 8 healthy controls were analyzed by qRT-PCR,and the correlation between its expression and clinical indicators were evaluated.Results:The downregulation of SENEX expression promotes G1-S phase transition and apoptosis while inhibiting cell proliferation,collectively suppressing the formation of TIS in B-NHL.Blockade of CDK4/6 promotes the DOX-induced G1 phase arrest to enhance TIS formation in B-NHL cells which can reverse the regulatory effect of silencing SENEX on B-NHL cell cycle regulation and senescence.The expression levels of SENEX were notably elevated in B-NHL patients compared to healthy controls,and Elevated expression levels of SENEX were associated with poor prognosis of B-NHL patients.Conclusions:SENEX enhances apoptosis resistance in B-NHL by inhibiting CDK4/6,thereby preventing G1-S phase transition and promoting TIS formation.
文摘[目的]本文旨在解决在自然环境下不同成熟度苹果目标检测精度较低的问题。[方法]提出了一种改进的YOLOv5s模型SODSTR-YOLOv5s(YOLOv5s with small detection layer and omni-dimensional dynamic convolution and swin transformer block),用于不同成熟度苹果检测。首先改进YOLOv5s的多尺度目标检测层,在Prediction中构建检测160×160特征图的检测头,提高小尺寸的不同成熟度苹果的检测精度;其次在Backbone结构中融合Swin Transformer Block,加强同级成熟度的苹果纹理特征融合,弱化纹理特征分布差异带来的消极影响,提高模型泛化能力;最后将Neck结构的Conv模块替换为动态卷积模块ODConv,细化局部特征映射,实现局部苹果细粒度特征的充分提取。基于不同成熟度苹果数据集进行试验,验证改进模型的性能。[结果]改进模型SODSTR-YOLOv5s检测的精确率、召回率、平均精度均值分别为89.1%、95.5%、93.6%,高、中、低成熟度苹果平均精度均值分别为94.1%、93.1%、93.7%,平均检测时间为16 ms,参数量为7.34 M。相比于YOLOv5s模型,改进模型SODSTR-YOLOv5s精确率、召回率、平均精度均值分别提高了3.8%、5.0%、2.9%,参数量和平均检测时间分别增加了0.32 M和5 ms。[结论]改进模型SODSTR-YOLOv5s提升了在自然环境下对不同成熟度苹果的检测能力,能较好地满足实际采摘苹果的检测要求。
文摘针对煤矿高噪声、低照度、运动模糊与大批量煤矸混杂等复杂工况环境因素导致煤矸识别存在误检、漏检以及检测精度低的问题,提出一种基于CFS-YOLO算法的煤矸智能识别模型。采用ConvNeXt V2(Convolutional Neural Network with NeXt Units Version 2)特征提取模块替换主干网络末端的2个C3(Cross Stage Partial Bottle Neck Mudule)模块,通过将掩码自动编码器(Masked Autoencoders,MAE)和全局响应归一化(Global Response Normalization,GRN)层添加到ConvNeXt架构中,有效缓解特征崩溃问题以及保持特征在网络传递过程中的多样性;采用Focal-EIOU(Focal and Efficient Intersection Over Union)损失函数替换原CIOU(Computer Intersection Over Union)损失函数,通过其Focal-Loss机制和调整样本权重的方式优化边界框回归任务中的样本不平衡问题,提高模型的收敛速度和定位精度;添加无参注意力机制(Simple Attention Mechanism,SimAM)于主干网络每个C3模块的后端,凭借其注意力权重自适应调整策略,提升模型对尺度变化较大或低分辨率煤矸目标关键特征的提取能力。通过消融试验和对比试验验证所提CFS-YOLO模型的有效性与优越性。试验结果表明:CFS-YOLO模型对于煤矸在煤矿高噪声、低照度、运动模糊与大批量煤矸混杂等复杂环境下的检测效果均得到有效提高,模型的平均精度均值达到90.2%,相较于原YOLOv5s模型的平均精度均值提高了3.7%,平均检测速度达到90.09 FPS,可充分满足煤矸实时检测的需求。同时与YOLOv5s、YOLOv7-tiny与YOLOv8n等6种YOLO系列算法相比,CFS-YOLO模型对煤矿复杂环境的适应性最强且综合检测性能最佳,可为煤矸的智能高效分选提供技术支持。
