The influence of resistance exercise training prescription variables on skeletal muscle mass,strength,and physical function in healthy adults:An umbrella review

Purpose:The aim of this umbrella review was to determine the impact of resistance training(RT)and individual RT prescription variables on muscle mass,strength,and physical function in healthy adults.Methods:Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines,we systematically searched and screened eligible systematic reviews reporting the effects of differing RT prescription variables on muscle mass(or its proxies),strength,and/or physical function in healthy adults aged>18 years.Results:We identified 44 systematic reviews that met our inclusion criteria.The methodological quality of these reviews was assessed using A Measurement Tool to Assess Systematic Reviews;standardized effectiveness statements were generated.We found that RT was consistently a potent stimulus for increasing skeletal muscle mass(4/4 reviews provide some or sufficient evidence),strength(4/6 reviews provided some or sufficient evidence),and physical function(1/1 review provided some evidence).RT load(6/8 reviews provided some or sufficient evidence),weekly frequency(2/4 reviews provided some or sufficient evidence),volume(3/7 reviews provided some or sufficient evidence),and exercise order(1/1 review provided some evidence)impacted RT-induced increases in muscular strength.We discovered that 2/3 reviews provided some or sufficient evidence that RT volume and contraction velocity influenced skeletal muscle mass,while 4/7 reviews provided insufficient evidence in favor of RT load impacting skeletal muscle mass.There was insufficient evidence to conclude that time of day,periodization,inter-set rest,set configuration,set end point,contraction velocity/time under tension,or exercise order(only pertaining to hypertrophy)influenced skeletal muscle adaptations.A paucity of data limited insights into the impact of RT prescription variables on physical function.Conclusion:Overall,RT increased muscle mass,strength,and physical function compared to no exercise.RT intensity(load)and weekly frequency impacted RT-induced increases in muscular strength but not muscle hypertrophy.RT volume(number of sets)influenced muscular strength and hypertrophy.

Responses of Annual Variability of Vegetation NPP to Climate Variables Using Satellite Techniques in Gadarif State, Sudan

Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.

Discovering Latent Variables for the Tasks With Confounders in Multi-Agent Reinforcement Learning

Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that agents cannot directly observe. However, most of the existing latent variable discovery methods lack a clear representation of latent variables and an effective evaluation of the influence of latent variables on the agent. In this paper, we propose a new MARL algorithm based on the soft actor-critic method for complex continuous control tasks with confounders. It is called the multi-agent soft actor-critic with latent variable(MASAC-LV) algorithm, which uses variational inference theory to infer the compact latent variables representation space from a large amount of offline experience.Besides, we derive the counterfactual policy whose input has no latent variables and quantify the difference between the actual policy and the counterfactual policy via a distance function. This quantified difference is considered an intrinsic motivation that gives additional rewards based on how much the latent variable affects each agent. The proposed algorithm is evaluated on two collaboration tasks with confounders, and the experimental results demonstrate the effectiveness of MASAC-LV compared to other baseline algorithms.

Evaluating the Efficacy of Latent Variables in Mitigating Data Poisoning Attacks in the Context of Bayesian Networks:An Empirical Study

Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables.However,the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data streams.One of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks,wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their performance.In this research paper,we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning algorithms.Our framework utilizes latent variables to quantify the amount of belief between every two nodes in each causal model over time.We use our innovative methodology to tackle an important issue with data poisoning assaults in the context of Bayesian networks.With regard to four different forms of data poisoning attacks,we specifically aim to strengthen the security and dependability of Bayesian network structure learning techniques,such as the PC algorithm.By doing this,we explore the complexity of this area and offer workablemethods for identifying and reducing these sneaky dangers.Additionally,our research investigates one particular use case,the“Visit to Asia Network.”The practical consequences of using uncertainty as a way to spot cases of data poisoning are explored in this inquiry,which is of utmost relevance.Our results demonstrate the promising efficacy of latent variables in detecting and mitigating the threat of data poisoning attacks.Additionally,our proposed latent-based framework proves to be sensitive in detecting malicious data poisoning attacks in the context of stream data.

Multi-Objective Optimization Algorithm for Grouping Decision Variables Based on Extreme Point Pareto Frontier

The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly focus on objectives,treating decision variables as a total variable to solve the problem without consideringthe critical role of decision variables in objective optimization.As seen,a variety of decision variable groupingalgorithms have been proposed.However,these algorithms are relatively broad for the changes of most decisionvariables in the evolution process and are time-consuming in the process of finding the Pareto frontier.To solvethese problems,a multi-objective optimization algorithm for grouping decision variables based on extreme pointPareto frontier(MOEA-DV/EPF)is proposed.This algorithm adopts a preprocessing rule to solve the Paretooptimal solution set of extreme points generated by simultaneous evolution in various target directions,obtainsthe basic Pareto front surface to determine the convergence effect,and analyzes the convergence and distributioneffects of decision variables.In the later stages of algorithm optimization,different mutation strategies are adoptedaccording to the nature of the decision variables to speed up the rate of evolution to obtain excellent individuals,thusenhancing the performance of the algorithm.Evaluation validation of the test functions shows that this algorithmcan solve the multi-objective optimization problem more efficiently.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

Wave propagation of a functionally graded plate via integral variables with a hyperbolic arcsine function

Several studies on functionally graded materials(FGMs)have been done by researchers,but few studies have dealt with the impact of the modification of the properties of materials with regard to the functional propagation of the waves in plates.This work aims to explore the effects of changing compositional characteristics and the volume fraction of the constituent of plate materials regarding the wave propagation response of thick plates of FGM.This model is based on a higher-order theory and a new displacement field with four unknowns that introduce indeterminate integral variables with a hyperbolic arcsine function.The FGM plate is assumed to consist of a mixture of metal and ceramic,and its properties change depending on the power functions of the thickness of the plate,such as linear,quadratic,cubic,and inverse quadratic.By utilizing Hamilton’s principle,general formulae of the wave propagation were obtained to establish wave modes and phase velocity curves of the wave propagation in a functionally graded plate,including the effects of changing compositional characteristics of materials.

Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

The Determination Method of Product Engineering Features Based on Linguistic Variables

To overcome the problem of imprecise and unclear information in the development of quality functions,a method for determining the priority of engineering features based on mixed linguistic variables is proposed.First,the evaluation member uses the determined linguistic variable to give the correlation strength evaluation matrix of customer requirements and engineering features.Secondly,the relative importance of the evaluation member and customer requirements are aggregated.Finally,the priority of engineering features is obtained by calculating the deviation.The feasibility and practicability of this method are proven by taking the design of a new product of a long bag low-pressure pulse dust collector as an example.

NLRP3炎症小体抑制剂MCC950通过抑制Th1/Th17和促进Tregs改善脓毒症小鼠器官损伤

目的:探讨核苷酸结合寡聚化结构域样受体蛋白3(NLRP3)炎症小体抑制剂MCC950对脓毒症小鼠T细胞分化及器官损伤的影响。方法:将18只C57BL/6雄性小鼠随机分为假手术组(sham组)、脓毒症模型组(CLP组)和MCC950治疗组(MCC950组),每组6只。其中CLP组和MCC950组通过盲肠结扎穿孔(CLP)的方法制备脓毒症模型。MCC950组腹腔注射溶于0.5 mL 0.9%氯化钠溶液的MCC950(50 mg/kg),sham组和CLP组腹腔注射等体积的0.9%氯化钠溶液。CLP术后24 h收集小鼠血清及器官标本。HE染色法观察脓毒症小鼠肺脏、肾脏组织病理损伤程度,并计算生存率;Western blot法检测脾脏NLRP3蛋白含量;ELISA法检测小鼠血清和肺组织的细胞因子水平(IL-1β、IL-18、IL-1α、IL-6、TNF-α);分离脾脏获得脾脏淋巴细胞,采用流式细胞术检测辅助性T细胞(Th)1、Th17、调节性T细胞(Tregs)比例。结果:与sham组相比,CLP组小鼠肺组织炎性细胞浸润、水肿和肺泡壁增厚,肾小管刷状缘和上皮细胞减少,肾小球萎缩,肾小管成弥漫性扩张,大量炎性细胞浸润,脾脏NLRP3的蛋白表达上调(P<0.05),血清IL-1β、IL-18、IL-1α、IL-6、TNF-α水平均升高(P<0.05),肺组织中IL-1α、IL-6、TNF-α水平均升高(P<0.05),脾脏CD4^(+)IFN-γ^(+)Th1、CD4^(+)IL-17^(+)Th17、CD4^(+)CD25^(+)Foxp3^(+)Tregs比例均升高(P<0.05),小鼠7 d生存率为30%(P<0.05)。与CLP组相比,MCC950组小鼠肺组织炎性细胞浸润减轻,水肿减退,肾小管扩张不明显,炎性细胞浸润亦有所减轻,脾脏NLRP3的蛋白表达下调(P<0.05),血清IL-1β、IL-18、IL-1α、IL-6、TNF-α水平均降低(P<0.05),肺组织中IL-1α、IL-6、TNF-α水平均降低(P<0.05),脾脏CD4^(+)IFN-γ^(+)Th1、CD4^(+)IL-17^(+)Th17比例减少,CD4^(+)CD25^(+)Foxp3^(+)Tregs比例明显增加(P<0.05),小鼠7 d生存率显著提升(P<0.05)。结论:MCC950阻断NLRP3可改善脓毒症小鼠的器官损伤,其作用可能依赖于抑制Th1/Th17反应和促进Tregs反应。

经颅磁声电刺激对健康与帕金森病大鼠神经回路中beta振荡的影响

背景:经颅磁声电刺激是一种基于磁声耦合电效应的无创、高精度脑神经聚焦刺激方法,可调节神经节律振荡活动,从而影响大脑的运动、认知等功能。目的:探究经颅磁声电刺激对健康与帕金森病大鼠神经回路中beta振荡的影响。方法:①动物实验:采用随机数字表法将24只Wistar大鼠随机分为4组,每组6只:正常对照组不进行任何干预;正常刺激组大脑前额叶皮质接受经颅磁声电刺激(空间峰值脉冲平均强度为13.33 W/cm^(2),基波频率为0.4 MHz,基波周期数为1000,脉冲重复频率为200 Hz);模型对照组、模型刺激组通过腹腔注射1-甲基-4-苯基-1,2,3,6-四氢吡啶建立帕金森病模型,造模成功后,模型对照组大脑前额叶皮质接受经颅磁声电假刺激,模型刺激组大脑前额叶皮质接受经颅磁声电刺激,每天刺激时长2.0 min,刺激结束停留8-10 min后,采集大鼠执行T迷宫过程中局部场电位信号并同时记录行为学正确率,对比分析各组局部场电位信号能量的时频分布情况和行为差异,当大鼠正确率连续3 d高于80%后停止刺激实验和T迷宫实验。②建模仿真实验:构建经颅磁声电刺激下皮质-基底神经节回路模型,分别改变超声发射周期(5,10,20 ms)、超声发射占空比(30%,50%,90%)和感应电流密度(20,50,100μA/cm^(2)),比较不同刺激参数下健康与帕金森病大鼠beta振荡的功率谱密度值。结果与结论:①动物实验:正常对照组大鼠的空间学习能力强于模型对照组(P<0.001),正常刺激组大鼠的空间学习能力强于正常对照组(P<0.05),模型刺激组大鼠的空间学习能力强于模型对照组(P<0.01);正常对照组beta振荡能量分布较为集中,正常刺激组较正常对照组beta振荡信号能量有所降低,模型对照组与模型刺激组beta振荡能量广泛分布且能量值显著高于正常对照组、正常刺激组,并且模型刺激组beta振荡信号能量明显低于模型对照组;②建模仿真实验:不加刺激时,健康大鼠beta频段功率谱密度峰值(30 dB)显著低于帕金森病大鼠(55 dB);施加经颅磁声电刺激后,两组大鼠beta频段功率谱密度值普遍降低;beta频段功率谱密度峰值与超声发射周期呈正相关、与感应电流密度呈负相关,当超声发射占空比为50%时功率谱密度峰值最低;③结果表明:经颅磁声电刺激可抑制健康与帕金森病大鼠的beta振荡,进而改善大鼠的运动功能与决策认知功能。

含T接逆变型分布式电源配电网的自适应距离保护

大量逆变型分布式电源(Inverter Interfaced Distributed Generation,IIDG)接入配电网,传统继电保护技术的可靠性无法满足。为了提高配电网供电可靠性,适应可再生能源大量渗透的新型电力系统,针对含T形接入IIDG的配电网,文章提出了一种自适应性的距离保护方案。分析了故障发生在不同位置对保护的影响,根据IIDG在系统发生故障时的输出特性,通过BP神经网络利用保护本地电气信息计算IIDG的输出电流,实时整定动作值。该方法由于无需与远方通信,动作速度快,并且减少了通信系统的投资。最后在MATLAB中建立了含T形接入IIDG的10 kV配电网模型,并与传统距离保护进行了对比,验证了该保护方法的优越性。

Th17和调节性T细胞在人类免疫缺陷病毒疾病进展中的作用及其调控机制

目的本研究通过观察人类免疫缺陷病毒(HIV)感染者外周血Th17、Treg细胞及其相关转录因子、细胞因子的表达,进一步揭示Th17、Treg细胞的调控机制及其在HIV感染者疾病进展中的作用。方法选取2019年1月—2019年10月河南省上蔡县HIV感染者80例作为研究组,选取同地区健康人群20例作为对照组。采用流式细胞术检测外周血CD4^(+)T、CD8^(+)T及外周血单个核细胞Th17、Treg,酶联免疫吸附试验检测血浆中细胞因子白细胞介素-17(IL-17)、IL-23水平,实时聚合酶链反应检测转录因子ROR-γt及Foxp3 mRNA表达,Pearson法分析Th17、Treg与CD4^(+)T的相关性。结果研究组CD4^(+)T、CD4^(+)T/CD3+T、CD4^(+)T/CD8^(+)T低于对照组(P<0.05),CD8^(+)T和CD8^(+)T/CD3+T高于对照组(P<0.05)。研究组Th17/CD4^(+)T、Th17/Treg低于对照组(P<0.05),Treg/CD4^(+)T高于对照组(P<0.05)。研究组ROR-γtmRNA高于对照组(P<0.05),Foxp3mRNA低于对照组(P<0.05)。研究组IL-17、IL-23水平低于对照组(P<0.05)。Pearson相关性分析结果表示,Th17细胞百分比与CD4^(+)T细胞计数呈正相关(r=0.293,P<0.05),Treg细胞百分比与CD4^(+)T细胞计数呈负相关(r=-0.198,P<0.05)。结论HIV感染能降低Th17细胞、升高Treg细胞,破坏机体免疫平衡,其机制与调控转录因子ROR-γt、Foxp3及细胞因子IL-17、IL-23表达有关,Th17细胞、Treg细胞与HIV感染者疾病进展密切相关。

黄芪对甲状腺功能正常的桥本甲状腺炎患者外周血T淋巴细胞亚群表达的影响

目的·探讨黄芪对甲状腺功能正常的桥本甲状腺炎患者T淋巴细胞亚群及细胞因子表达的影响。方法·选择2020年1月—12月在上海市第六人民医院金山分院接受治疗且资料完整的甲状腺功能正常的桥本甲状腺炎患者120例,采用随机数字表将患者为干预组及对照组,每组各60例。对照组治疗方案为碘适宜状态饮食,干预组在对照组治疗方案基础上联合黄芪药液口服(150 mL/次,2次/d)治疗。连续治疗6个月,比较2组治疗前后外周血清T淋巴细胞亚群(CD3^(+)、CD4^(+)、CD8^(+)、CD4^(+)/CD8^(+)),细胞因子[包括白细胞介素2(interleukin-2,IL-2)、肿瘤坏死因子α(tumor necrosis factor-α,TNF-α)、IL-6、IL-10],超敏C反应蛋白(hypersensitive C-reactive protein,hs-CRP),红细胞沉降率(erythrocyte sedimentation rate,ESR),以及甲状腺功能及自身抗体、肝肾功能等指标的变化。观察黄芪治疗期间不良反应。应用多因素线性回归分析甲状腺过氧化物酶抗体(thyroid peroxidase antibody,TPOAb)变化幅度的影响因素。结果·最终纳入118例患者,每组各59例。治疗6个月后,干预组CD4^(+)T细胞比例,CD4^(+)/CD8^(+)比值,IL-2、TNF-α、IL-6、IL-10、hs-CRP、ESR、TPOAb和甲状腺球蛋白抗体(thyroglobulin antibody,TGAb)水平均较治疗前及其同期对照组显著改善,差异均有统计学意义(均P<0.05)。对照组治疗后上述指标与治疗前比较,差异均无统计学意义(P>0.05)。治疗后干预组未见严重不良反应。多因素线性回归分析结果显示,应用黄芪、CD4^(+)T细胞、CD4^(+)/CD8^(+)比值升高幅度及hs-CRP下降幅度均是TPOAb下降幅度的独立影响因素(β=−0.393,P=0.029;β=−0.513,P=0.010;β=−0.351,P=0.035;β=0.434,P=0.023)。结论·黄芪可改善甲状腺功能正常的桥本甲状腺炎患者CD4^(+)T细胞、IL-2、TNF-α、IL-6、IL-10水平及CD4^(+)/CD8^(+)比值,且安全性佳。

流行性感冒患儿外周血MAIT细胞的免疫生物学特性

目的探讨流行性感冒患儿外周血黏膜相关恒定T(MAIT)细胞的变化及其临床意义。方法选取2023年1—5月就诊于某儿童医院感染科门诊和住院治疗的流行性感冒患儿,分为普通型组和重症型组,同时选择该院体检的健康儿童作为健康对照组。患儿入院24 h内抽血送检,采用流式细胞技术检测MAIT细胞(CD3^(+)CD161^(+)TCRVα7.2^(+)细胞)比例,表达PD-1、CD69、穿孔素、CD107α的MAIT细胞比例,比较各组差异。结果与对照组相比,普通型、重症型患儿外周血MAIT细胞比例逐步下降,表达CD69和穿孔素阳性的MAIT细胞比例逐步升高,三者间比较,差异均有统计学意义(均P<0.05);表达CD107α的MAIT细胞比例比较,差异无统计学意义(P>0.05);PD-1阳性的MAIT细胞比例升高(P<0.05),但普通型、重症型组间比较,差异无统计学意义(P>0.05)。结论外周血MAIT细胞减少伴免疫活化在流行性感冒发病中起一定作用。

BCMA CAR-T治疗复发/难治性多发性骨髓瘤患者的长期疗效和影响因素分析

目的:评价靶向B细胞成熟抗原(B cell maturation antigen,BCMA)嵌合抗原受体T细胞(chimeric antigen receptor-T cell,CAR-T)治疗复发/难治性多发性骨髓瘤(relapsed/refractory multiple myeloma,R/R MM)的长期疗效和安全性。方法:回顾性分析2018年7月至2023年7月在南昌大学第一附属医院接受BCMA CAR-T细胞治疗20例R/R MM患者的临床资料,随访日期截至2023年12月31日。应用Kaplan-Meier生存分析评估患者总生存(overall survival,OS)率和无进展生存(progression-free survival,PFS)率,并统计相关不良反应。结果:20例R/R MM患者,既往中位治疗线数为3(2~6)线,客观缓解率(objective response rate,ORR)为75%,完全缓解(complete response,CR)率为50%;中位随访时间29个月,中位PFS为26个月。10例CR的患者中,5例在末次随访时仍处于缓解状态,缓解持续时间最短为6个月,最长48个月。亚组分析中,髓外浸润、17p缺失遗传学异常和肿瘤高负荷患者PFS显著更差(P<0.05)。细胞因子释放综合征(cytokine release syndrome,CRS)是CAR-T细胞治疗最常见的不良反应,发生率为90%,3~4级CRS的发生率为35%;远期不良反应少,未发生CAR-T细胞治疗相关死亡。结论:BCMA CAR-T细胞是当前R/R MM治疗的有效方案,不良反应可控。髓外浸润和肿瘤高负荷的患者治疗有效,但持久反应欠佳,如何进一步巩固和维持患者的疗效,值得进一步设计前瞻性的临床研究并探究其差异性。

肿瘤微环境中与CD8^(+)T细胞耗竭相关的分化及代谢重编程的研究进展

CD8^(+)T细胞耗竭是导致机体免疫应答减弱及恶性肿瘤复发转移的核心原因。T细胞不仅在迁移进入肿瘤微环境(tumor microenvironment,TME)时需要突破重重屏障,而且在浸润至肿瘤微环境的T细胞的分化及代谢过程依然受到多因素的调控,往往造成CD8+T细胞抗肿瘤活性受到抑制,进一步形成耗竭性T细胞,导致免疫逃逸。因此,研究导致T细胞耗竭的相关因素及发生机制是逆转机体低免疫应答的关键,为抗肿瘤免疫治疗提供坚实的基础及依据。该文综述了近年来关于CD8^(+)T细胞在肿瘤微环境中的浸润分化、代谢重编程及耗竭性T细胞形成的相关过程,以期为改善T细胞抗肿瘤疗效提供潜在策略。

结直肠癌组织高表达IL-35对Th1和Th17可塑性的作用

目的 探讨结直肠癌组织中高表达的抑制性细胞因子白细胞介素(IL)-35对辅助性T细胞1(Th1)和辅助性T细胞17(Th17)可塑性的作用。方法 选取2019年3月—2020年2月上海交通大学医学院附属新华医院结直肠癌患者90例(结直肠癌组)和健康体检者28名(正常对照组)。采用流式细胞术检测结直肠癌组和正常对照组外周血Th1百分比(Th1%)和Th17百分比(Th17%)。基于Kaplan-Meier Plotter数据库分析γ-干扰素(IFN-γ)和IL-17A高表达对结直肠癌患者总生存期和预后不良的影响。采用免疫组化法检测结直肠癌患者癌组织和癌旁组织(距肿瘤边缘≥2 cm)中IL-35的表达。采用酶联免疫吸附试验检测结直肠癌患者和正常对照者血清IL-35水平。采用体外诱导Th1分化实验观察IL-35对Th1分泌IL-17A和IFN-γ的影响。结果与正常对照组比较,结直肠癌组Th1%显著降低(P=0.019),Th17%显著升高(P<0.001)。结直肠癌组Th1%与Th17%的r2值(0.393 4)与正常对照组(0.041 0)比较差异有统计学意义(P=0.007)。基于KaplanMeierPlotter数据库的分析结果显示,IFN-γmRNA低表达是结直肠癌患者总生存期缩短的危险因素[风险比(HR)=0.74,95%可信区间(CI)为0.58~0.94,P=0.013],IL-17A mRNA高表达是结直肠癌患者总生存期缩短的危险因素(HR=1.26,95%CI为1.02~1.59,P=0.020)。结直肠癌患者癌组织IL-35表达显著高于癌旁组织(P<0.001)。Ⅰ~Ⅱ期(早期)和Ⅲ~Ⅳ期(晚期)结直肠癌患者血清IL-35水平均显著高于正常对照者(P<0.05)。体外诱导Th1分化实验结果显示,IL-35可降低Th1中IFN-γ表达,提高IL-17A表达。结论 结直肠癌患者外周血Th1和Th17呈异常变化,且IL-35表达增加。高表达的IL-35可降低Th1中IFN-γ表达,提高IL-17A表达。

优化T-SPOT.TB在区分脊柱结核与其他脊柱感染中的诊断效能

目的 探讨结核感染T细胞斑点试验(T-SPOT.TB)在脊柱结核(STB)鉴别诊断中的效能,并通过受试者工作特征(ROC)曲线最佳截断值优化诊断效能。方法 收集2010年1月—2019年5月某院脊柱感染患者的临床资料,包括术前T-SPOT.TB检测结果、白细胞计数、C-反应蛋白、血沉、降钙素原和结核抗体等相关数据,根据诊断标准进行临床诊断,分析T-SPOT.TB在术前诊断STB与其他脊柱感染中的灵敏度和特异度,评价优化后的T-SPOT.TB指标的诊断效能。结果 共纳入132例患者,其中78例(59.09%)为STB,54例(40.91%)为非结核脊柱感染。T-SPOT.TB在鉴别诊断STB方面的灵敏度为67.68%,特异度为66.67%。单因素logistic回归分析显示,与非结核脊柱感染比较,T-SPOT.TB检测诊断STB的OR值为4.188(95%CI:1.847~9.974,P<0.001)。优化T-SPOT.TB评价指标,通过绘制ROC曲线,确定ESAT-6、CFP-10、CFP-10+ESAT-6在STB和非结核脊柱感染鉴别诊断中的最佳截断值,分别为12.5、19.5、36,曲线下面积(AUC)分别是0.765 6、0.741 5、0.778 6,均具有较好的诊断性能,其中以CFP-10+ESAT-6的AUC最高。CFP-10+ESAT-6特异性斑点数在脊柱结核诊断中性能更佳,其诊断准确度为75.56%,较优化前T-SPOT.TB的67.42%高。结论 T-SPOT.TB检测在区分STB与非结核脊柱感染方面显示出较高的诊断效能,T-SPOT.TB检测呈阳性,尤其是当CFP-10+ESAT-6的斑点数超过36时,提示脊柱结核的可能性较大。

磁共振T1rho序列、T2 mapping技术在膝关节早期软骨退变早期诊断中的评估价值

目的探讨磁共振T1rho序列、T2 mapping技术在膝关节早期软骨退变早期诊断中的评估价值。方法选取2020年1月至2022年11月在我院治疗的110例膝关节早期软骨退变患者(观察组),按照疾病严重程度分为轻度退变组及重度退变组,另选取同期在我院进行体检的64例健康者为对照组,受试者均行磁共振T1rho序列、T2 mapping技术扫描,测量受试者T2值及T1ρ值,探讨磁共振T1rho序列、T2 mapping技术在膝关节早期软骨退变早期诊断中的评估价值。结果观察组股骨外侧面、股骨内侧面、胫骨外侧面、胫骨内侧面、髋骨面T2值均明显高于对照组(P<0.05),重度退变亚组患者股骨外侧面、股骨内侧面、胫骨外侧面、胫骨内侧面、髋骨面T2值显著高于轻度退变者(P<0.05);观察组股骨内踝负重区、股骨内踝非负重区、股骨外踝负重区、股骨外踝非负重区、胫骨外侧平台区、胫骨内侧平台区、髌后软骨区磁共振T1ρ值明显高于对照组(P<0.05),重度退变亚组患者股骨内踝负重区、股骨内踝非负重区、股骨外踝负重区、股骨外踝非负重区、胫骨外侧平台区、胫骨内侧平台区、髌后软骨区磁共振T1ρ值明显高于轻度退变亚组患者(P<0.05);磁共振T1rho序列在膝关节早期软骨退变中早期诊断及严重程度评估中的的诊断ROC值及特异度明显高于T2 mapping技术(P<0.05),但后者具有更高的敏感度(P<0.05)。结论磁共振T1rho序列、T2 mapping技术均能有效反映膝关节早期软骨退变中软骨组织学成分变化情况,还可为膝关节软骨退变严重程度评估提供客观依据,二者具有一定互补价值。