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复方利多卡因TTPB-PECS-全身麻醉对乳腺癌根治术患者术后疼痛及早期康复的影响

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海南医学 2024年第7期35卷 944-950页

作者：刘洋张威李姣杨祖悌南阳南石医院麻醉科河南南阳473000

目的探讨复方利多卡因胸横肌平面阻滞(TTPB)-胸神经阻滞(PECS)-全身麻醉对乳腺癌根治术患者术后镇痛及早期康复的影响。方法选取2021年3月至2023年5月于南阳南石医院行乳腺癌根治术的98例患者纳入研究,按随机数表法分为对照组和观察组... 详细信息

目的探讨复方利多卡因胸横肌平面阻滞(TTPB)-胸神经阻滞(PECS)-全身麻醉对乳腺癌根治术患者术后镇痛及早期康复的影响。方法选取2021年3月至2023年5月于南阳南石医院行乳腺癌根治术的98例患者纳入研究,按随机数表法分为对照组和观察组各49例,对照组患者给予罗哌卡因TTPB-PECS-全身麻醉,观察组患者给予复方利多卡因TTPB-PECS-全身麻醉。比较两组患者术中丙泊酚、瑞芬太尼用量、镇痛泵有效按压次数/实际按压次数(D1/D2)、术后48 h内舒芬太尼用量、补救镇痛率、康复相关指标、不良反应及入室时(T0)、切皮时(T1)、手术30 min时(T2)、术毕即刻(T3)、术后2 h(T4)、6 h(T5)、12 h(T6)、24 h(T7)不同时间点疼痛评分[视觉模拟量表(VAS)]、镇静评分[Ramsay评分法]、疼痛介质水平[神经肽Y(NPY)、前列腺素E2(PGE2)、β-内啡肽]、炎性因子水平[白介素-6(IL-6)、单核细胞趋化蛋白-1(MCP-1)、肿瘤坏死因素-α(TNF-α)]。结果两组患者的丙泊酚用量、术中瑞芬太尼用量比较差异均无统计学意义(P>0.05);观察组患者术后48 h内的舒芬太尼用量、补救镇痛率分别为(25.49±6.41)μg、4.08%,明显低于对照组的(49.32±7.25)μg、18.37%,D1/D2为0.83±0.31,明显高于对照组的0.64±0.20,差异均具有统计学意义(P0.05)。结论相比罗哌卡因TTPB-PECS-全身麻醉,复方利多卡因TTPB-PECS-全身麻醉可减少患者术后镇痛药物用量,减轻应激反应,加速术后康复,其远期镇痛效果更好,且安全性更高。

关键词：复方利多卡因胸横肌平面阻滞-胸神经阻滞-全身麻醉乳腺癌根治术镇痛早期康复

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基于美国FAERS数据库的克唑替尼不良事件信号挖掘与分析

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中国医院用药评价与分析 2024年第6期24卷 748-751,755页

作者：刘红霞张越郑凯乐杨提上海市儿童医院/上海交通大学医学院附属儿童医院药学部上海200062 青岛市即墨区人民医院临床药学科山东青岛266200 上海市浦东新区公利医院药学部上海200135

目的:挖掘克唑替尼的药品不良事件(ADE)信号,为临床安全用药提供参考。方法:收集2011年8月26日至2023年3月31日美国食品药品监督管理局不良事件报告系统(FAERS)数据库中的克唑替尼相关ADE报告,利用比例失衡法中的报告比值比(ROR)法和综... 详细信息

目的:挖掘克唑替尼的药品不良事件(ADE)信号,为临床安全用药提供参考。方法:收集2011年8月26日至2023年3月31日美国食品药品监督管理局不良事件报告系统(FAERS)数据库中的克唑替尼相关ADE报告,利用比例失衡法中的报告比值比(ROR)法和综合标准法(MHRA)进行数据挖掘,采用《ICH国际医学用语词典》(MedDRA)中的首选系统器官分类(SOC)和首选术语(PT)对ADE进行描述、分类和统计。结果:共检索到目标药物克唑替尼相关ADE报告22 493例;以男性患者为主(11 862例,占52.74%),且集中于≥65岁(109例,占0.48%);主要上报国家为美国(12 837例,占57.07%);共涉及严重不良事件18 370例次,以住院为主(4 595例次,占严重不良事件总例次数的25.01%)。共挖掘到61 453个ADE信号,涉及15种SOC,主要为全身性疾病及给药部位各种反应、胃肠道功能疾病。报告例次数排序靠前的ADE信号涉及死亡、腹泻、恶心、疲劳等PT;信号强度排序靠前的ADE信号涉及软组织肉瘤、恶性结缔组织瘤、转移性滑膜肉瘤等PT。结论:克唑替尼所致ADE主要包括全身性异常、胃肠道反应、各项检查指标异常等;使用克唑替尼前,临床应做好用药评估,并在治疗期间重点关注患者的血液指标和全身性反应,以保障治疗的安全性。

关键词：克唑替尼美国食品药品监督管理局不良事件报告系统药品不良事件数据挖掘

基于网络药理学的刺芒柄花素抗颈动脉粥样硬化斑块的作用靶点及机制

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同济大学学报（医学版） 2024年第1期45卷 24-30页

作者：李珊赵康杨提王莹邓生琼湖北医药学院公共卫生与健康学院湖北十堰442099 上海市浦东新区公利医院检验科上海200135

目的利用网络药理学方法联合GEO基因芯片数据及分子对接技术探索刺芒柄花素治疗颈动脉粥样硬化斑块的潜在分子作用机制。方法在PubChem等数据库获取刺芒柄花素的作用靶点,在GeneCards、DisGeNET等数据库获取颈动脉粥样硬化斑块相关靶... 详细信息

目的利用网络药理学方法联合GEO基因芯片数据及分子对接技术探索刺芒柄花素治疗颈动脉粥样硬化斑块的潜在分子作用机制。方法在PubChem等数据库获取刺芒柄花素的作用靶点,在GeneCards、DisGeNET等数据库获取颈动脉粥样硬化斑块相关靶点基因,与GEO芯片筛选的差异基因合并去重后得到颈动脉粥样硬化斑块靶点基因;通过构建韦恩图,得到药物与疾病共有靶点;利用R软件包对共有靶点进行富集分析;利用String在线平台构建共有靶点蛋白互作网络,运用Cytoscape软件对网络进行拓扑学参数筛选得到核心靶点;再运用分子对接技术将筛选出来的核心靶点分别与刺芒柄花素的结合活性进行验证。结果筛选出413个刺芒柄花素作用靶点及1 244个颈动脉粥样硬化斑块表达差异基因,两者取交集后得到55个刺芒柄花素干预颈动脉粥样硬化斑块的潜在靶点,KEGG富集分析显著富集于PPAR信号通路、MAPK信号等通路,并显示基因功能与炎症及细胞凋亡相关;运用Cytoscape筛选得到核心靶点CAP1、CXCL8、EGFR、FOS、CTSS、IGF1、MMP9、PPARG;分子对接模拟验证显示,CAP1、CXCL8、EGFR、FOS、IGF1、MMP9、PPARG等核心靶点与刺芒柄花素结合强,有较好的结合活性。结论刺芒柄花素作用于CAP1等多个核心靶点调节炎症相关信号通路,进而发挥抗动脉斑块形成的作用,可为后续临床用药提供数据支持。

关键词：网络药理学 GEO数据库刺芒柄花素动脉粥样硬化斑块

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Network Configuration Entity Extraction Method Based on Transformer with Multi-Head Attention Mechanism

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Computers, Materials & Continua 2024年第1期78卷 735-757页

作者： yang yang Zhenying Qu Zefan Yan Zhipeng Gao ti Wang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China Product Development Department China Unicom Smart City Research InstituteBeijing100044China

Nowadays,ensuring thequality of networkserviceshas become increasingly *** are turning toknowledge graph technology,with a significant emphasis on entity extraction in the identification of device *** research paper presents a novel entity extraction method that leverages a combination of active learning and attention ***,an improved active learning approach is employed to select the most valuable unlabeled samples,which are subsequently submitted for expert *** approach successfully addresses the problems of isolated points and sample redundancy within the network configuration sample *** the labeled samples are utilized to train the model for network configuration entity ***,the multi-head self-attention of the transformer model is enhanced by introducing the Adaptive Weighting method based on the Laplace mixture *** enhancement enables the transformer model to dynamically adapt its focus to words in various positions,displaying exceptional adaptability to abnormal data and further elevating the accuracy of the proposed *** comparisons with Random Sampling(RANDOM),Maximum Normalized Log-Probability(MNLP),Least Confidence(LC),Token Entrop(TE),and Entropy Query by Bagging(EQB),the proposed method,Entropy Query by Bagging and Maximum Influence Active Learning(EQBMIAL),achieves comparable performance with only 40% of the samples on both datasets,while other algorithms require 50% of the ***,the entity extraction algorithm with the Adaptive Weighted Multi-head Attention mechanism(AW-MHA)is compared with BILSTM-CRF,Mutil_Attention-Bilstm-Crf,Deep_Neural_Model_NER and BERT_Transformer,achieving precision rates of 75.98% and 98.32% on the two datasets,*** tests demonstrate the statistical significance and effectiveness of the proposed algorithms in this paper.

关键词： Entity extraction network configuration knowledge graph active learning transformer

Effect of Wave Nonlinearity on the Instantaneous Seabed Liquefaction

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China Ocean Engineering 2024年第1期38卷 93-103页

作者： WANG Zhao-jun SUI ti-ti ZHANG Chi PAN Jun-ning Key Laboratory of Port Waterway and Sedimentation Engineering of the Ministry of TransportNanjing Hydraulic Research InstituteNanjing 210024China Key Laboratory of Coastal Disaster and Protection(Hohai University) Ministry of EducationNanjing 210098China The National Key Laboratory of Water Disaster Prevention Nanjing 210098China

The nonlinear variation of wave is commonly seen in nearshore area,and the resulting seabed response and liquefaction are of high concern to coastal *** this study,an analytical formula considering the nonlinear wave skewness and asymmetry is adopted to provide wave pressure on the seabed *** liquefaction depth attenuation coefficient and width growth coefficient are defined to quantitatively characterize the nonlinear effect of wave on seabed *** on the 2D full dynamic model of wave-induced seabed response,a detailed parametric study is carried out in order to evaluate the influence of the nonlinear variation of wave loadings on seabed ***,new empirical prediction formulas are proposed to fast predict the maximum liquefaction under nonlinear *** indicate that(1)Due to the influence of wave nonlinearity,the vertical transmission of negative pore water pressure in the seabed is hindered,and therefore,the amplitude decreases significantly.(2)In general,with the increase of wave nonlinearity,the liquefaction depth of seabed decreases *** under asymmetric and skewed wave loading,the attenuation of maximum seabed liquefaction depth is the most significant among all the nonlinear wave ***,highly skewed wave can cause the liquefaction depth of seabed greater than that under linear wave.(3)The asymmetry of wave pressure leads to the increase of liquefaction width,whereas the influence of skewedness is not significant.(4)Compared with the nonlinear waveform,seabed liquefaction is more sensitive to the variation of nonlinear degree of wave loading.

关键词： nonlinear wave seabed response seabed liquefaction numerical simulation liquefaction prediction

Tumor microenvironment reprogramming by nanomedicine to enhance the effect of tumor immunotherapy

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Asian Journal of Pharmaceutical Sciences 2024年第2期19卷 1-37页

作者： Yu Huang Hui Fan Huihui ti School of Chinese Materia Medica Guangdong Pharmaceutical UniversityGuangzhou 510006China Guangdong Province Precise Medicine Big Date of Traditional Chinese Medicine Engineering Technology Research Center Guangdong Pharmaceutical UniversityGuangzhou 510006China School of Pharmacy Guangdong Pharmaceutical UniversityGuangzhou 510006China

With the rapid development of the fields of tumor biology and immunology, tumor immunotherapy has been used in clinical practice and has demonstrated significant therapeutic potential, particularly for treating tumors that do not respond to standard treatment options. Despite its advances, immunotherapy still has limitations, such as poor clinical response rates and differences in individual patient responses, largely because tumor tissues have strong immunosuppressive microenvironments. Many tumors have a tumor microenvironment (TME) that is characterized by hypoxia, low pH, and substantial numbers of immunosuppressive cells, and these are the main factors limiting the efficacy of antitumor immunotherapy. The TME is crucial to the occurrence, growth, and metastasis of tumors. Therefore, numerous studies have been devoted to improving the effects of immunotherapy by remodeling the TME. Effective regulation of the TME and reversal of immunosuppressive conditions are effective strategies for improving tumor immunotherapy. The use of multidrug combinations to improve the TME is an efficient way to enhance antitumor immune efficacy. However, the inability to effectively target drugs decreases therapeutic effects and causes toxic side effects. Nanodrug delivery carriers have the advantageous ability to enhance drug bioavailability and improve drug targeting. Importantly, they can also regulate the TME and deliver large or small therapeutic molecules to decrease the inhibitory effect of the TME on immune cells. Therefore, nanomedicine has great potential for reprogramming immunosuppressive microenvironments and represents a new immunotherapeutic strategy. Therefore, this article reviews strategies for improving the TME and summarizes research on synergistic nanomedicine approaches that enhance the efficacy of tumor immunotherapy.

关键词： Tumor immunotherapy Tumor micr oenvir onment Nanomedicine Tumor repr ogramming

Cyber-physical Collaborative Restoration Strategy for Power Transmission System Considering Maintenance Scheduling

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1331-1341页

作者： Baozhong ti Chuanyun Zhang Jingfei Liu Zhaoyuan Wu Ziyang Huang North China Branch of State Grid Corporation of China Beijing 100053China State Grid Beijing Electric Power Company Beijing 100031China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electrical and Electronic EngineeringNorth China Electric Power UniversityBeijing 102206China IEEE CSEE

In order to improve the ability of power transmission system to cope with compound faults on the communication side and power side,a cyber-physical collaborative restoration strategy is ***,according to the information system’s role in fault diagnosis,remote control of equipment maintenance and automatic output adjustment of generator restoration,a cyber-physical coupling model is *** this basis,a collaborative restoration model of power transmission system is established by studying interactions among maintenance schedule paths,information system operation,and power system *** on power flow linearization and the large M-ε method,the above model is transformed into a mixed integer linear programming model,whose computational burden is reduced further by the clustering *** to the parameters of IEEE39 New England system,the geographic wiring diagram of the cyber-physical system is *** results show the proposed restoration strategy can consider the support function of the information system and space-time coordination of equipment maintenance at both sides comprehensively to speed up load recovery progress.

关键词： Clustering method collaborative restoration cyber-physical power system maintenance scheduling power transmission system restoration

Analytical libration control law for electrodynamic tether system with current constraint

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Astrodynamics 2024年第2期8卷 237-246页

作者： Shidong Xu ti Chen Hao Wen Dongping Jin State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing210016China

This study focuses on stabilizing the libration dynamics of an electrodynamic tether system(EDTS)using generalized torques induced by the Lorentz *** contrast to existing numerical optimization methods,a novel analytical feedback control law is developed to stabilize the in-plane and out-of-plane motions of a tether by modulating the electric current *** saturation constraint on the current is accounted for by adding an auxiliary dynamic system to the *** enhance the robustness of the proposed controller,multiple perturbations of the orbital dynamics,modeling uncertainties,and external disturbances are approximated using a neural network in which the weighting matrix and approximation error are estimated simultaneously,such that these perturbations are well compensated for during the control design of the ***,a dynamically scaled generalized inverse is utilized to address the singular matrix in the control *** closed-loop system is proven to be ultimately bounded based on Lyapunov stability ***,numerical simulations are performed to demonstrate the effectiveness of the proposed analytical control law.

关键词： electrodynamic tether system(EDTS) libration dynamics analytical control current constraint

Better use of experience from other reservoirs for accurate production forecasting by learn-to-learn method

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Petroleum Science 2024年第1期21卷 716-728页

作者： Hao-Chen Wang Kai Zhang Nancy Chen Wen-Sheng Zhou Chen Liu Ji-Fu Wang Li-Ming Zhang Zhi-Gang Yu Shi-ti Cui Mei-Chun yang China University of Petroleum(East China) 66 Changjiang West RoadQingdao West Coast New AreaQingdao266580ShandongChina University of Calgary 2500 University Dr NWCalgaryT2N 1N4AlbertaCanada Qingdao University of Technology Qingdao266071ShandongChina State Key Laboratory of Offshore Oil Exploitation Beijing100028China CNOOC Research Institute Ltd. Beijing100028China CNPC Tarim Oilfield Branch Company Korla841000XinjiangChina National Engineering Laboratory for Exploration and Development of Low-Permeability Oil and Gas Fields Xi'an710000ShaanxiChina Sinopec Matrix Co. LTDQingdao266000ShandongChina

To assess whether a development strategy will be profitable enough,production forecasting is a crucial and difficult step in the *** development history of other reservoirs in the same class tends to be studied to make predictions ***,the permeability field,well patterns,and development regime must all be similar for two reservoirs to be considered in the same *** results in very few available experiences from other reservoirs even though there is a lot of historical information on numerous reservoirs because it is difficult to find such similar *** paper proposes a learn-to-learn method,which can better utilize a vast amount of historical data from various ***,the proposed method first learns how to learn samples before directly learning rules in ***,by utilizing gradients from networks with independent parameters and copied structure in each class of reservoirs,the proposed network obtains the optimal shared initial parameters which are regarded as transferable information across different *** on that,the network is able to predict future production indices for the target reservoir by only training with very limited samples collected from reservoirs in the same *** cases further demonstrate its superiority in accuracy to other widely-used network methods.

关键词： Production forecasting Multiple patterns Few-shot learning Transfer learning