Additive Maps Preserving{1,2,T}-inverses

Let F be a field of characteristic not 2 and 3.Let f:Mmn(F)→Mmn(F)be an additive map preserving{1,2,T}-inverse,i.e.f(A)=f(A)f(B)Tf(A),f(B)=f(B)f(A)Tf(B)for any A,B C Mmn(F)with A=ABTA,B=BATB.In this paper,we give the sufficient and necessary condition for f to be such a map.

SDGNN: Symmetry-Preserving Dual-Stream Graph Neural Networks

Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.

Privacy-Preserving Consensus-Based Distributed Economic Dispatch of Smart Grids via State Decomposition

This paper studies the privacy-preserving distributed economic dispatch(DED)problem of smart grids.An autonomous consensus-based algorithm is developed via local data exchange with neighboring nodes,which covers both the islanded mode and the grid-connected mode of smart grids.To prevent power-sensitive information from being disclosed,a privacy-preserving mechanism is integrated into the proposed DED algorithm by randomly decomposing the state into two parts,where only partial data is transmitted.Our objective is to develop a privacy-preserving DED algorithm to achieve optimal power dispatch with the lowest generation cost under physical constraints while preventing sensitive information from being eavesdropped.To this end,a comprehensive analysis framework is established to ensure that the proposed algorithm can converge to the optimal solution of the concerned optimization problem by means of the consensus theory and the eigenvalue perturbation approach.In particular,the proposed autonomous algorithm can achieve a smooth transition between the islanded mode and the grid-connected mode.Furthermore,rigorous analysis is given to show privacy-preserving performance against internal and external eavesdroppers.Finally,case studies illustrate the feasibility and validity of the developed algorithm.

2P3FL:A Novel Approach for Privacy Preserving in Financial Sectors Using Flower Federated Learning

The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages.As a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model.However,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy.To address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global convergence.Resultantly improves the privacy of the local models.This analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)datasets.Precision,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and FedProx.The experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.

A Cloud-Fog Enabled and Privacy-Preserving IoT Data Market Platform Based on Blockchain

The dynamic landscape of the Internet of Things(IoT)is set to revolutionize the pace of interaction among entities,ushering in a proliferation of applications characterized by heightened quality and diversity.Among the pivotal applications within the realm of IoT,as a significant example,the Smart Grid(SG)evolves into intricate networks of energy deployment marked by data integration.This evolution concurrently entails data interchange with other IoT entities.However,there are also several challenges including data-sharing overheads and the intricate establishment of trusted centers in the IoT ecosystem.In this paper,we introduce a hierarchical secure data-sharing platform empowered by cloud-fog integration.Furthermore,we propose a novel non-interactive zero-knowledge proof-based group authentication and key agreement protocol that supports one-to-many sharing sets of IoT data,especially SG data.The security formal verification tool shows that the proposed scheme can achieve mutual authentication and secure data sharing while protecting the privacy of data providers.Compared with previous IoT data sharing schemes,the proposed scheme has advantages in both computational and transmission efficiency,and has more superiority with the increasing volume of shared data or increasing number of participants.

Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

As the volume of healthcare and medical data increases from diverse sources,real-world scenarios involving data sharing and collaboration have certain challenges,including the risk of privacy leakage,difficulty in data fusion,low reliability of data storage,low effectiveness of data sharing,etc.To guarantee the service quality of data collaboration,this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning,termed FL-HMChain.This system is composed of three layers:Data extraction and storage,data management,and data application.Focusing on healthcare and medical data,a healthcare and medical blockchain is constructed to realize data storage,transfer,processing,and access with security,real-time,reliability,and integrity.An improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior,ensuring the overall reliability and trustworthiness of the collaborative model training process.Furthermore,healthcare and medical data collaboration services in real-world scenarios have been discussed and developed.To further validate the performance of FL-HMChain,a Convolutional Neural Network-based Federated Learning(FL-CNN-HMChain)model is investigated for medical image identification.This model achieves better performance compared to the baseline Convolutional Neural Network(CNN),having an average improvement of 4.7%on Area Under Curve(AUC)and 7%on Accuracy(ACC),respectively.Furthermore,the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.

Insights into upper blepharoplasty: Conservative volume-preserving techniques

This editorial commentary critically examines the systematic review by Miotti et al,which discusses the evolving trends in upper lid blepharoplasty towards a conservative,volume-preserving approach.The review emphasizes the shift from traditional tissue resection to techniques that maintain anatomical integrity,paralleling broader trends in panfacial rejuvenation.Miotti et al delve into the nuances of fat pad management,advocating for conservation over reduction to sustain natural contours and improve long-term aesthetic outcomes.This perspective is supported by comparative studies and empirical data,such as those from Massry and Alghoul et al,highlighting the benefits of conservative approaches in terms of patient satisfaction and aesthetic longevity.The review also stresses the importance of surgeon discretion in adapting procedures to diverse patient demographics,particularly in addressing distinct features such as the Asian upper eyelid.However,it identifies a significant gap in long-term comparative research,underscoring the need for future studies to substantiate the safety and efficacy of these minimalist techniques.Overall,Miotti et al.'s work contributes profoundly to the discourse on personalized,conservative cosmetic surgery,urging ongoing research to refine and validate surgical best practices in upper eyelid blepharoplasty.

Bipolar hip arthroplasty using conjoined tendon preserving posterior lateral approach in treatment of displaced femoral neck fractures

BACKGROUND Hip fractures account for 23.8%of all fractures in patients over the age of 75 years.More than half of these patients are older than 80 years.Bipolar hemiarthroplasty(BHA)was established as an effective management option for these patients.Various approaches can be used for the BHA procedure.However,there is a high risk of postoperative dislocation.The conjoined tendon-preserving posterior(CPP)lateral approach was introduced to reduce postoperative dislocation rates.AIM To evaluate the effectiveness and safety of the CPP lateral approach for BHA in elderly patients.METHODS We retrospectively analyzed medical data from 80 patients with displaced femoral neck fractures who underwent BHA.The patients were followed up for at least 1 year.Among the 80 patients,57(71.3%)were female.The time to operation averaged 2.3 d(range:1-5 d).The mean age was 80.5 years(range:67-90 years),and the mean body mass index was 24.9 kg/m^(2)(range:17-36 kg/m^(2)).According to the Garden classification,42.5%of patients were typeⅢand 57.5%of patients were typeⅣ.Uncemented bipolar hip prostheses were used for all patients.Torn conjoined tendons,dislocations,and adverse complications during and after surgery were recorded.RESULTS The mean postoperative follow-up time was 15.3 months(range:12-18 months).The average surgery time was 52 min(range:40-70 min)with an average blood loss of 120 mL(range:80-320 mL).The transfusion rate was 10%(8 of 80 patients).The gemellus inferior was torn in 4 patients(5%),while it was difficult to identify in 2 patients(2.5%)during surgery.The posterior capsule was punctured by the fractured femoral neck in 3 patients,but the conjoined tendon and the piriformis tendon remained intact.No patients had stem varus greater than 3 degrees or femoral fracture.There were no patients with stem subsidence more than 5 mm at the last follow-up.No postoperative dislocations were observed throughout the follow-up period.No significance was found between preoperative and postoperative mean Health Service System scores(87.30±2.98 vs 86.10±6.10,t=1.89,P=0.063).CONCLUSION The CPP lateral approach can effectively reduce the incidence of postoperative dislocation without increasing perioperative complications.For surgeons familiar with the posterior lateral approach,there is no need for additional surgical instruments,and it does not increase surgical difficulty.

An Arbitrarily High Order and Asymptotic Preserving Kinetic Scheme in Compressible Fluid Dynamic

We present a class of arbitrarily high order fully explicit kinetic numerical methods in compressible fluid dynamics,both in time and space,which include the relaxation schemes by Jin and Xin.These methods can use the CFL number larger or equal to unity on regular Cartesian meshes for the multi-dimensional case.These kinetic models depend on a small parameter that can be seen as a"Knudsen"number.The method is asymptotic preserving in this Knudsen number.Also,the computational costs of the method are of the same order of a fully explicit scheme.This work is the extension of Abgrall et al.(2022)[3]to multidimensional systems.We have assessed our method on several problems for two-dimensional scalar problems and Euler equations and the scheme has proven to be robust and to achieve the theoretically predicted high order of accuracy on smooth solutions.

Clinical Observation on the Treatment of Diabetic Kidney Disease with Damp-heat Stasis Syndrome in Clinical Proteinuria Stage by Kunkui Kidney Preserving Paste

[Objectives]To evaluate the clinical efficacy and safety of Kunkui Kidney Preserving Paste in the treatment of diabetic kidney disease(DKD)patients with damp-heat stasis syndrome in the clinical proteinuria stage.[Methods]Retrospective analysis was made on 30 patients with DKD who were diagnosed with damp-heat stasis syndrome in the clinical proteinuria stage from March 2021 to March 2023 in Jiangsu Province Hospital of Chinese Medicine,and who took Kunkui Kidney Preserving Paste continuously for six months.The urinary albumin/creatinine ratio(UACR),urinary complement C3,and urea nitrogen(BUN)of DKD patients before and after treatment were compared,and estimated glomerular filtration rate(eGFR),blood creatinine(Scr),and cystatin C(CysC)were estimated,and the therapeutic effects on renal function and urinary protein were evaluated.[Results]After treatment,UACR significantly decreased(P<0.01),and urinary complement C3 and Scr decreased(P<0.05),while other indicators showed no significant statistical difference(P>0.05).In terms of evaluating the efficacy of urinary protein therapy,8 cases showed recent relief;8 cases showed significant effect;9 cases were effective,and 5 cases were invalid after treatment,with a total effective rate of 83.33%.In terms of renal function efficacy evaluation,8 cases showed significant effect;4 cases were effective;11 cases were stable,and 7 cases were invalid,with a total effective rate of 76.67%.In the safety evaluation,there were no obvious adverse reactions.[Conclusions]The Kunkui Kidney Preserving Past has significant clinical efficacy and safety in treating DKD patients with damp-heat stasis syndrome in the clinical proteinuria period.It has significant advantages in reducing urinary protein and protecting renal function,which is worthy of clinical promotion.

Ship recognition based on HRRP via multi-scale sparse preserving method

In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) based on the maximum margin criterion(MMC) is proposed for recognizing the class of ship targets utilizing the high-resolution range profile(HRRP). Multi-scale fusion is introduced to capture the local and detailed information in small-scale features, and the global and contour information in large-scale features, offering help to extract the edge information from sea clutter and further improving the target recognition accuracy. The proposed method can maximally preserve the multi-scale fusion sparse of data and maximize the class separability in the reduced dimensionality by reproducing kernel Hilbert space. Experimental results on the measured radar data show that the proposed method can effectively extract the features of ship target from sea clutter, further reduce the feature dimensionality, and improve target recognition performance.

Analysis of quality of life in patients after transgastric natural orifice transluminal endoscopic gallbladder-preserving surgery

BACKGROUND At present,laparoscopic cholecystectomy(LC)is the main surgical treatment for gallstones.But,after gallbladder removal,there are many complications.Therefore,it is hoped to remove stones while preserving the function of the gallbladder,and with the development of endoscopic technology,natural orifice transluminal endoscopic surgery came into being.AIM To compare the quality of life,perioperative indicators,adverse events after LC and transgastric natural orifice transluminal endoscopic gallbladder-preserving surgery(EGPS)in patients with gallstones.METHODS Patients who were admitted to The First Affiliated Hospital of Xinjiang Medical University from 2020 to 2022 were retrospectively collected.We adopted propen-sity score matching(1:1)to compare EGPS and LC patients.RESULTS A total of 662 cases were collected,of which 589 cases underwent LC,and 73 cases underwent EGPS.Propensity score matching was performed,and 40 patients were included in each of the groups.In the EGPS group,except the gastr-ointestinal defecation(P=0.603),the total score,physical well-being,mental well-being,and gastrointestinal digestion were statistically significant compared with the preoperative score after surgery(P<0.05).In the LC group,except the mental well-being,the total score,physical well-being,gastrointestinal digestion,the gastrointestinal defecation was statistically significant compared with the preoperative score after surgery(P<0.05).When comparing between groups,gastrointestinal defecation had significantly difference(P=0.002)between the two groups,there was no statistically significant difference in the total postoperative score and the other three subscales.In the surgery duration,hospital stay and cost,LC group were lower than EGPS group.The recurrence factors of gallstones after EGPS were analyzed:and recurrence was not correlated with gender,age,body mass index,number of stones,and preoperative score.CONCLUSION Whether EGPS or LC,it can improve the patient’s symptoms,and the EGPS has less impact on the patient’s defecation.It needed to,prospective,multicenter,long-term follow-up,large-sample related studies to prove.

Temporally Preserving Latent Variable Models:Offline and Online Training for Reconstruction and Interpretation of Fault Data for Gearbox Condition Monitoring

Latent variable models can effectively determine the condition of essential rotating machinery without needing labeled data.These models analyze vibration data via an unsupervised learning strategy.Temporal preservation is necessary to obtain an informative latent manifold for the fault diagnosis task.In a temporalpreserving context,two approaches exist to develop a condition-monitoring methodology:offline and online.For latent variable models,the available training modes are not different.While many traditional methods use offline training,online training can dynamically adjust the latent manifold,possibly leading to better fault signature extraction from the vibration data.This study explores online training using temporal-preserving latent variable models.Within online training,there are two main methods:one focuses on reconstructing data and the other on interpreting the data components.Both are considered to evaluate how they diagnose faults over time.Using two experimental datasets,the study confirms that models from both training modes can detect changes in machinery health and identify faults even under varying conditions.Importantly,the complementarity of offline and online models is emphasized,reassuring their versatility in fault diagnostics.Understanding the implications of the training approach and the available model formulations is crucial for further research in latent variable modelbased fault diagnostics.

Mesenchymal stromal cells modulate unfolded protein response and preserve β-cell mass in type 1 diabetes

Introduction:Transplantation of mesenchymal stromal cells(MSCs)is a promising therapy for type 1 diabetes(T1D).However,whether the infused MSCs affect the endoplasmic reticulum stress or subsequent unfolded protein response inβcells remains unclear.Methods:To investigate this,we induced early-onset T1D in non-obese diabetic mice using streptozotocin.Subsequently,T1D mice were randomly assigned to receive either MSCs or phosphate-buffered saline.We observed the in vivo homing of MSCs and assessed their effectiveness by analyzing blood glucose levels,body weight,histopathology,pancreatic protein expression,and serum levels of cytokines,proinsulin,and C-peptide.Results:Infused MSCs were found in the lungs,liver,spleen,and pancreas of T1D mice.They exhibited various effects,including reducing blood glucose levels,regulating immunity,inhibiting inflammation,increasingβ-cell areas,and reducing the expression of key proteins in the unfolded protein response pathway.Fasting serum proinsulin and C-peptide levels were significantly higher in the MSCs treatment group than in the T1D model group.However,there was no significant difference in the biomarker ofβ-cell endoplasmic reticulum stress,the ratio of fasting serum proinsulin to C-peptide,between the two groups.Conclusion:Ourfindings reveal that MSCs infusion does not alleviate endoplasmic reticulum stress inβcells directly but modulates the unfolded protein response pathway to preserveβ-cell mass and function in T1D mice.

GLP-1受体激动剂对心血管作用的研究进展

胰高血糖素样肽-1(glucagon-like peptide-1,GLP-1)由肠道内分泌细胞产生。GLP-1受体激动剂(GLP-1 receptor agonists,GLP-1RAs)促进葡萄糖相关的胰岛素分泌和抑制胰高血糖素分泌。GLP-1RAs还能抑制胃排空、食物摄入和限制体质量增加。在过去的十年中,GLP-1RAs对心血管系统影响的研究已经取得重大进展。口服小分子GLP-1RAs具有潜在优势,可以提高该类药物的应用。该文综述了GLP-1RAs在心血管疾病治疗中的多种作用,为GLP-1RAs的心血管获益提供新见解。

1-甲基环丙烯结合水杨酸处理维持百香果甲基环丙烯结合水杨酸处理维持百香果果实贮藏品质

为延长百香果的贮藏期并保持贮藏过程中的品质,对比研究2 mmol/L水杨酸(salicylic acid,SA)、1 mmol/L 1-甲基环丙烯(1-methylcyclopropene,1-MCP)、1-MCP结合SA处理对紫色百香果果实采后贮藏期间品质、活性氧、抗氧化酶指标的影响。百香果果实经SA、1-MCP和1-MCP结合SA处理后,一定程度抑制乙烯的释放和脂氧合酶(li-poxygenase,LOX)活性,促进几丁质酶(chitinase,CHI)和β-1,3-葡聚糖酶(β-1,3-glucanase,GLU)的活性,增强抗氧化和抗病性作用,降低腐烂率。但因SA可以增强呼吸,故导致凹陷和失重,加快总酸流失;1-MCP抑制呼吸作用,增强超氧化物歧化酶(superoxide dismutase,SOD)活性,有利于控制失重和凹陷,但其对过氧化物酶(peroxidase,POD)活性的影响不利于控制衰老。1-MCP结合SA对POD活性,CHI活性以及GLU活性的正向影响强于单独使用1-MCP或SA处理。因此,1-MCP结合SA通过提高百香果果实的抗氧化能力和抗病能力,降低百香果果实的凹陷、失重和腐烂率,且可有效避免单独使用1-MCP或SA处理的不良作用,协同维持百香果果实采后贮藏品质。

糖尿病视网膜病变患者SDF-1、HO-1及MDA水平变化及与IL-6、TNF-α、CRP的相关性

目的 分析糖尿病视网膜病变(DR)患者基质细胞衍生因子(SDF-1)、血红素加氧酶-1(HO-1)及丙二醛(MDA)水平变化及与白介素-6(IL-6)、肿瘤坏死因子(TNF-α)、C反应蛋白(CRP)的相关性。方法 选取2020年5月至2023年1月解放军总医院收治的131例DR患者为DR组,另选取同期在本院住院的2型糖尿病患者100例为非DR组。比较两组SDF-1、HO-1、MDA水平;比较两组IL-6、TNF-α、CRP水平;比较不同分期DR患者SDF-1、HO-1、MDA水平;采用Logistic回归分析影响DR发生的相关因素,分析DR组患者SDF-1、HO-1、MDA水平与IL-6、TNF-α、CRP的相关性。结果 DR组SDF-1、HO-1水平比非DR组低,MDA水平比非DR组高,差异有统计学意义(P<0.05);DR组IL-6、TNF-α、CRP水平均比非DR组高,差异有统计学意义(P<0.05);SDF-1、HO-1水平:Ⅰ~Ⅱ期>Ⅲ~Ⅳ期>Ⅴ~Ⅵ期,MDA水平:Ⅰ~Ⅱ期<Ⅲ~Ⅳ期<Ⅴ~Ⅵ期,差异有统计学意义(P<0.05);经Logistic多因素分析显示,性别为女、BMI≥24 km/m2、合并患有高血压、高血脂、IL-6>1.17 mg/mL、TNF-α>30 ng/L、CRP>10 ng/mL、SDF-1>2 ng/mL、HO-1<125 ng/mL、MDA>4.06μmol/mL均是影响DR发生的独立危险因素(P<0.05);血清炎性因子IL-6、TNF-α、CRP与SDF-1、HO-1呈负相关,与MDA呈正相关,且均为中度相关(P<0.05)。结论 SDF-1、HO-1、MDA、IL-6、CRP、TNF-α水平与DR的发生、发展有一定关系,通过检测上述指标水平可为进一步探讨DR的发病机制和治疗方法提供新的思路。

铁抑素-1对糖尿病中晚期小鼠肝肾组织的保护作用

糖尿病是一种发病率高且并发症多的代谢性疾病,其中2型糖尿病(type 2 diabetes mellitus,T2DM)占比较大。目前研究表明,T2DM伴随着肝、肾等脏器损伤引起并发症,严重危害人体健康。铁死亡通过芬顿反应产生大量活性氧(reactive oxygen species,ROS),ROS累积会激活缺氧诱导因子-1α(hypoxia inducible factor-1,HIF-1α),从而引发血管内皮生长因子(vascular endothelial growth factor,VEGF)水平升高,铁死亡抑制剂——铁抑素-1(ferrostatin-1,Fer-1)具有强抗氧化能力,所以基于缺氧诱导因子-1α/血管内皮生长因子(HIF-1α/VEGF)信号通路,探讨Fer-1对糖尿病中晚期小鼠肝、肾组织的保护作用。实验以21~22周龄db/db小鼠作为糖尿病中晚期模型,铁死亡抑制剂Fer-1为干预药物。db/m小鼠为空白对照组,连续4周测量体重、血糖,实验中还对各组小鼠进食量、饮水量进行记录;测定血清中丙氨酸氨基转移酶(alanine aminotransferase,ALT)、天冬氨酸氨基转移酶(aspartate aminotransferase,AST)水平,测定肝肾组织中ROS、谷胱甘肽(glutathione,GSH)活性以及尿蛋白含量,并用苏木素-伊红(hematoxylin-eosin,HE)染色处理肝、肾组织切片,光镜观察病理学形态,再通过Western印迹法分别检测肝、肾组织中HIF-1α、VEGF和谷胱甘肽过氧化物酶4(glutathione peroxidase 4,GPX4)蛋白质水平。在db/db组小鼠中发现,Fer-1(1 mg·kg^(-1),ig)可明显减少进食量和饮水量,降低小鼠血清中的ALT、AST水平、肝肾组织中ROS生成量以及尿蛋白水平,显著升高GSH活性,显著改善了肝、肾的病理组织状况,并且明显抑制肝肾组织中HIF-1α和VEGF蛋白质指标、提高GPX4蛋白水平。Fer-1虽不能改变糖尿病小鼠的体重和降低血糖,但能对糖尿病中晚期小鼠的肝、肾组织发挥保护作用,其作用机制可能与HIF-1α/VEGF和GPX4有关。

口服葡萄糖耐量试验1h血糖对糖尿病前期的诊断和鉴别价值

目的:探讨口服葡萄糖耐量试验(OGTT)1 h血糖对糖尿病前期的诊断和鉴别价值。方法:收集2019年6月至2022年6月于北京中医药大学东直门医院门诊及住院行OGTT的受试者1 206例,其中血糖正常412例,糖尿病前期358例,糖尿病436例。比较3组OGTT不同时点血糖与空腹血糖(FPG)、空腹胰岛素(FINS)、稳态模型胰岛素抵抗指数(HOMA-IR)、胰岛β细胞分泌功能指数(HOMA-β)水平;采用ROC曲线分析OGTT 1 h血糖对糖尿病前期的诊断和鉴别价值。结果:3组OGTT各时点血糖均为糖尿病组>糖尿病前期组>血糖正常组(P<0.05)。FPG、HOMA-IR糖尿病组>糖尿病前期组>血糖正常组,FINS、HOMA-β糖尿病组<糖尿病前期组<血糖正常组(P<0.05)。ROC曲线分析结果显示,OGTT 1 h血糖诊断糖尿病前期的AUC(95%CI)为0.758(0.724~0.792),以敏感度最大选取最佳切点值,该值为9.35 mmol/L,此时敏感度为0.701,特异度为0.709;OGTT 1 h血糖对糖尿病和糖尿病前期鉴别的AUC(95%CI)为0.956(0.942~0.969),以敏感度最大选取最佳切点值,该值为12.55 mmol/L,此时敏感度为0.901,特异度为0.908。结论:OGTT 1 h血糖对糖尿病前期具有一定的诊断和鉴别价值。

肺腺癌患者胸水肿瘤细胞PD-L1/TTF-1表达及应用分析

目的探讨肺腺癌患者胸水肿瘤细胞程序性细胞死亡配体1(PD-L1)/甲状腺转录因子1(TTF-1)、PD-L1免疫组化染色的表达及与组织标本PD-L1表达一致性及其应用研究。方法选取2021年1月至2023年4月间首都医科大学附属北京朝阳医院收治的符合入组条件的50例肺腺癌患者为研究对象,比较同一病例组织标本中肿瘤细胞的PD-L1表达和胸水细胞蜡块中肿瘤细胞的PD-L1、PD-L1/TTF-1表达情况,评估它们之间表达的一致性。结果50例肺腺癌组织标本PD-L1的表达与患者性别、年龄、标本类型、病灶性质、标本来源和EGFR突变对比差异无统计学意义(P>0.05);胸水细胞蜡块中肿瘤细胞PD-L1/TTF-1免疫组化双染的表达与组织标本PD-L1表达的一致性较好(κ=0.846,P<0.05),明显高于PD-L1免疫组化单染(κ=0.754,P<0.05),与手术或活检切除标本一致性较好(κ=0.90,P<0.05),高于胸腔镜或穿刺小标本(κ=0.82,P<0.05),与原发病灶标本的一致性适中(κ=0.689,P<0.05),与转移病灶标本的一致性较好(κ=0.779,P<0.05)。结论胸水细胞学标本采用PD-L1/TTF-1免疫组化双染与组织标本PD-L1表达一致性较高,细胞蜡块PD-L1/TTF-1双染可在组织不易获取时作为一种有益补充,供临床制定免疫治疗方案参考。