面向深度学习视觉应用ISP过程的图像缩放攻击实验平台

大多数基于深度学习技术的视觉设备都配备了图像信号处理(Image Signal Processing, ISP)过程以实现RAW数据到RGB图像的转换,同时集成数据预处理过程以完成高效的图像处理。该文在同时考虑ISP和数据预处理过程影响基础上,搭建了深度学习视觉应用实验平台,提出针对ISP过程的图像缩放攻击,即精心制作对抗RAW经过ISP过程得到攻击图像,一旦缩放到特定尺寸就会呈现出完全不同的样貌。由于所提出的攻击是由基于ISP过程的梯度驱动的,因此构建了一个等效模型来学习目标ISP的转换过程,利用等效模型的近似梯度来发动攻击。该攻击平台的构建涵盖了深度学习算法、图像处理及对抗攻击优化等内容,有助于学生深入学习和理解基于深度学习视觉应用的任务处理原理以及深度学习模型的弱点,培养学生针对复杂算法问题的创新与实践能力。

关于ISP锌冶炼工艺转型升级和绿色发展的几点思考

本文分享了近年来我国ISP锌冶炼工艺取得的进展以及转型升级和绿色发展的几点思考。目前,我国铅锌冶炼技术比较成熟,铅冶炼以侧吹或底吹熔池熔炼为主的三连炉工艺,锌冶炼以湿法浸出为主的工艺,在环保和能耗方面都处于国际领先水平。密闭鼓风炉炼铅锌工艺(以下简称“ISP工艺”)则是一种比较成熟的铅锌联合冶炼方法,也是当今世界最主要的火法炼锌工艺,具有原料适应性强、综合回收利用水平高、经济效益好、锌锭品质高等优势,但同时也因能耗较高、环保风险大等问题受到广泛关注。

Developmental exposure to thyroid disruptors:misprogramming of the brain's stem cells in later life?

Introduction:Ever since the discovery of neural stem cells(NSCs)in the adult mammalian brain,scientists have been trying to decipher which signals govern their turnover and lineage commitment to generate neurons and glia.Understanding their role in nervous tissue homeostasis can provide new insights into the etiology of several neurological disorders,and might one day be turned to our advantage to promote endogenous brain injury repair.Others and we have identified thyroid hormone(TH)as a key factor transcriptionally regulating NSC behavior in the largest niche of the adult mammalian brain:the subventricular zone(SVZ).

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

In vivo astrocyte reprogramming following spinal cord injury

Harmful and helpful roles of astrocytes in spinal cord injury(SCI):SCI induce gradable sensory,motor and autonomic impairments that correlate with the lesion severity and the rostro-caudal location of the injury site.The absence of spontaneous axonal regeneration after injury results from neuron-intrinsic and neuron-extrinsic parameters.Indeed,not only adult neurons display limited capability to regrow axons but also the injury environment contains inhibitors to axonal regeneration and a lack of growth-promoting factors.Amongst other cell populations that respond to the lesion,reactive astrocytes were first considered as only detrimental to spontaneous axonal regeneration.Indeed,astrocytes.

Transcriptional reprogramming during human osteoclast differentiation identifies regulators of osteoclast activity

Enhanced osteoclastogenesis and osteoclast activity contribute to the development of osteoporosis,which is characterized by increased bone resorption and inadequate bone formation.As novel antiosteoporotic therapeutics are needed,understanding the genetic regulation of human osteoclastogenesis could help identify potential treatment targets.This study aimed to provide an overview of transcriptional reprogramming during human osteoclast differentiation.Osteoclasts were differentiated from CD14+monocytes from eight female donors.RNA sequencing during differentiation revealed 8980 differentially expressed genes grouped into eight temporal patterns conserved across donors.These patterns revealed distinct molecular functions associated with postmenopausal osteoporosis susceptibility genes based on RNA from iliac crest biopsies and bone mineral density SNPs.Network analyses revealed mutual dependencies between temporal expression patterns and provided insight into subtype-specific transcriptional networks.The donor-specific expression patterns revealed genes at the monocyte stage,such as filamin B(FLNB)and oxidized low-density lipoprotein receptor 1(OLR1,encoding LOX-1),that are predictive of the resorptive activity of mature osteoclasts.The expression of differentially expressed G-protein coupled receptors was strong during osteoclast differentiation,and these receptors are associated with bone mineral density SNPs,suggesting that they play a pivotal role in osteoclast differentiation and activity.The regulatory effects of three differentially expressed G-protein coupled receptors were exemplified by in vitro pharmacological modulation of complement 5 A receptor 1(C5AR1),somatostatin receptor 2(SSTR2),and free fatty acid receptor 4(FFAR4/GPR120).Activating C5AR1 enhanced osteoclast formation,while activating SSTR2 decreased the resorptive activity of mature osteoclasts,and activating FFAR4 decreased both the number and resorptive activity of mature osteoclasts.In conclusion,we report the occurrence of transcriptional reprogramming during human osteoclast differentiation and identified SSTR2 and FFAR4 as antiresorptive G-protein coupled receptors and FLNB and LOX-1 as potential molecular markers of osteoclast activity.These data can help future investigations identify molecular regulators of osteoclast differentiation and activity and provide the basis for novel antiosteoporotic targets.

Glia-to-neuron reprogramming to the rescue?

Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative medicine.The brea kth rough discovery that induced pluripotent stem cells could be generated from adult mouse fibroblasts is powerful proof that cell fate can be changed.An exciting extension of the discovery of cell fate impermanence is the direct cellular reprogram ming hypothesis-that terminally differentiated cells can be reprogrammed into other adult cell fates without first passing through a stem cell state.

Neurocircuit regeneration by extracellular matrix reprogramming

The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.

Improved Unit Commitment with Accurate Dynamic Scenarios Clustering Based on Multi-Parametric Programming and Benders Decomposition

Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.

Key Factors to Consider When Introducing a New Vaccine in Low-Income Settings: Lessons from Malawi Expanded Program on Immunization

Introduction: As new vaccines become available, countries must assess the relevance to introduce them into their vaccination schedules. Malawi has recently introduced several new vaccines and plans to introduce more. This study was conducted to identify key factors that need to be considered when deciding to introduce a new vaccine and current challenges faced by low and middle income countries using Malawi as an example. Methodology: The study employed a desk review approach, examining published literature from various sources such as PubMed, Medline, and Google Scholar. Policy documents from organizations like the World Health Organization, GAVI the Alliance, and the Ministry of Health for Malawi were also included. A total of 99 articles and documents on new vaccine introduction, challenges of immunization, policy documents in immunization and health systems strengthening were included. The review focused on addressing five key areas critical to new vaccine introduction namely: the need for a vaccine, availability of the vaccine, safety and effectiveness of the vaccine, demand for the vaccine, and the prudent use of public or private funds. Results: Malawi considered the burden of cervical cancer and the significance of malaria in the country when introducing the HPV and malaria vaccines. The country opted for vaccines that can be handled by the cold chain capacity and available human resources. Despite that malaria vaccine and Typhoid Conjugate Vaccine trials were done in country, there are limited vaccine safety and efficacy trials conducted in Malawi, leading to a reliance on WHO-prequalified vaccines. Demand for newly introduced vaccines varied, with high demand for Oral Cholera Vaccine during a cholera outbreak, while demand for COVID-19 vaccines decreased over time. Although cost-effectiveness studies were limited in the country, 2 studies indicated that Typhoid Conjugate Vaccine and malaria vaccine would be cost effective. All these have been implemented despite having challenges like lack of accurate surveillance data, inadequate cold chain capacity, limited safety and efficacy vaccine clinical trials, political influence, and limited funding. Conclusion: Despite several challenges Malawi set a good example of the careful considerations required before introducing a new vaccine. The process involves data review, priority setting, precise planning, and consultation with stakeholders. Low-income countries should invest in vaccine safety, efficacy, and cost-effectiveness trials.

Research and Practice of Cardiopulmonary Rehabilitation Training Programs

In today’s society, the incidence of cardiopulmonary diseases is increasing annually, seriously affecting patients’ quality of life. Therefore, developing a scientific and effective rehabilitation training program is of great significance. This study first analyzes the theoretical basis of cardiopulmonary rehabilitation training, including the effects of aerobic exercise, interval training, and strength training on cardiopulmonary function. Based on this, a comprehensive rehabilitation training program is designed, which includes personalized training plans, comprehensive interventions, multidisciplinary collaboration, patient education, and regular follow-up visits. The cardiopulmonary rehabilitation training plan developed in this study has certain scientific practicability, which provides a theoretical basis for cardiopulmonary rehabilitation training, and also provides a reference for medical institutions, rehabilitation centers and communities, which is helpful for promotion and application to a wider range of patients with cardiopulmonary diseases.

Quercetin Alleviates Lipopolysaccharide-Induced Cardiac Inflammation via Inhibiting Autophagy and Programmed Cell Death

Objective The aim of this study is to explore the potential modulatory role of quercetin against Endotoxin or lipopolysaccharide(LPS)induced septic cardiac dysfunction.Methods Specific pathogen-free chicken embryos(n=120)were allocated untreated control,phosphate buffer solution(PBS)vehicle,PBS with ethanol vehicle,LPS(500 ng/egg),LPS with quercetin treatment(10,20,or 40 nmol/egg,respectively),Quercetin groups(10,20,or 40 nmol/egg).Fifteenday-old embryonated eggs were inoculated with abovementioned solutions via the allantoic cavity.At embryonic day 19,the hearts of the embryos were collected for histopathological examination,RNA extraction,real-time polymerase chain reaction,immunohistochemical investigations,and Western blotting.Results They demonstrated that the heart presented inflammatory responses after LPS induction.The LPS-induced higher mRNA expressions of inflammation-related factors(TLR4,TNFα,MYD88,NF-κB1,IFNγ,IL-1β,IL-8,IL-6,IL-10,p38,MMP3,and MMP9)were blocked by quercetin with three dosages.Quercetin significantly decreased immunopositivity to TLR4 and MMP9 in the treatment group when compared with the LPS group.Quercetin significantly decreased protein expressions of TLR4,IFNγ,MMP3,and MMP9 when compared with the LPS group.Quercetin treatment prevented LPS-induced increase in the mRNA expression of Claudin 1 and ZO-1,and significantly decreased protein expression of claudin 1 when compared with the LPS group.Quercetin significantly downregulated autophagyrelated gene expressions(PPARα,SGLT1,APOA4,AMPKα1,AMPKα2,ATG5,ATG7,Beclin-1,and LC3B)and programmed cell death(Fas,Bcl-2,CASP1,CASP12,CASP3,and RIPK1)after LPS induction.Quercetin significantly decreased immunopositivity to APOA4,AMPKα2,and LC3-II/LC3-I in the treatment group when compared with the LPS group.Quercetin significantly decreased protein expressions of AMPKα1,LC3-I,and LC3-II.Quercetin significantly decreased the protein expression to CASP1 and CASP3 by immunohistochemical investigation or Western blotting in treatment group when compared with LPS group.Conclusion Quercetin alleviates cardiac inflammation induced by LPS through modulating autophagy,programmed cell death,and myocardiocytes permeability.

An Empirical Application of User-Guided Program Analysis

Although static program analysis methods are frequently employed to enhance software quality,their efficiency in commercial settings is limited by their high false positive rate.The EUGENE tool can effectively lower the false positive rate.However,in continuous integration(CI)environments,the code is always changing,and user feedback from one version of the software cannot be applied to a subsequent version.Additionally,people find it difficult to distinguish between true positives and false positives in the analytical output.In this study,we developed the EUGENE-CI technique to address the CI problem and the EUGENE-rank lightweight heuristic algorithm to rate the reports of the analysis output in accordance with the likelihood that they are true positives.On the three projects ethereum,go-cloud,and kubernetes,we assessed our methodologies.According to the trial findings,EUGENE-CI may drastically reduce false positives while EUGENE-rank can make it much easier for users to identify the real positives among a vast number of reports.We paired our techniques with GoInsight~1 and discovered a vulnerability.We also offered a patch to the community.

Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks

Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.

Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming

Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.

Effectiveness of Co-Testing in Cervical Cancer Screening Program in Macao SAR

Background: Cervical cancer remains a significant public health concern in Macao SAR despite the implementation of a cervical cancer screening program and HPV vaccination. To improve early detection, Macao SAR introduced HPV DNA testing alongside cytology (co-testing) as the primary screening method in 2019. This study evaluates the effectiveness of co-testing in identifying cervical precancerous lesions (CIN2+) compared to cytology alone. Methods: We conducted a retrospective analysis of women aged 30 - 65 years who participated in the routine cervical cancer screening program in Macao SAR Primary Healthcare Centers from 2019 to 2022. Data from over 70,000 women were analyzed, comparing the detection rates of CIN2+ through co-testing and cytology alone. Women with abnormal cytology or positive HPV results were referred for colposcopy. Results: The introduction of co-testing led to a significant increase in the detection of CIN2+, particularly in women with atypical squamous cells of undetermined significance (ASCUS) or negative for intraepithelial lesion or malignancy (NILM) cytology results. Between 2019 and 2022, the percentage of women with ASCUS/NILM and any high-risk HPV (hrHPV) positive who were diagnosed with CIN2+ after colposcopy were 24%, 13%, 10% and 7.5% respectively. This highlights the ability of co-testing to identify high-risk individuals who would have been missed by cytology alone. Discussion: Our findings demonstrate the effectiveness of co-testing in improving the sensitivity of cervical cancer screening in Macao SAR. The inclusion of HPV DNA testing allows for better risk stratification of women with ASCUS/NILM cytology, leading to more targeted referrals for colposcopy and timely detection of precancerous lesions. The initial high positive rate in 2019 (24%) might be attributed to the small sample size and potentially reflects a backlog of undiagnosed cases prior to co-testing implementation. Conclusion: The implementation of co-testing in Macao SAR’s cervical cancer screening program significantly improves the early detection of precancerous lesions, particularly in women with ambiguous cytology results. This proactive approach contributes to reducing cervical cancer morbidity and mortality and improving women’s health outcomes in Macao SAR.

Efficacy comparison of fruquintinib,regorafenib monotherapy or plus programmed death-1 inhibitors for microsatellite stable metastatic colorectal cancer

BACKGROUND Regorafenib(R)and fruquintinib(F)are the standard third-line regimens for colorectal cancer(CRC)according to the National Comprehensive Cancer Network guidelines,but both have limited efficacy.Several phase 2 trials have indicated that R or F combined with immune checkpoint inhibitors can reverse immunosuppression and achieve promising efficacy for microsatellite stable or proficient mismatch repair(MSS/pMMR)CRC.Due to the lack of studies comparing the efficacy between F,R,F plus programmed death-1(PD-1)inhibitor,and R plus PD-1 inhibitors(RP),it is still unclear whether the combination therapy is more effective than monotherapy.AIM To provide critical evidence for selecting the appropriate drugs for MSS/pMMR metastatic CRC(mCRC)patients in clinical practice.METHODS A total of 2639 CRC patients were enrolled from January 2018 to September 2022 in our hospital,and 313 MSS/pMMR mCRC patients were finally included.RESULTS A total of 313 eligible patients were divided into F(n=70),R(n=67),F plus PD-1 inhibitor(FP)(n=95)and RP(n=81)groups.The key clinical characteristics were well balanced among the groups.The median progression-free survival(PFS)of the F,R,FP,and RP groups was 3.5 months,3.6 months,4.9 months,and 3.0 months,respectively.The median overall survival(OS)was 14.6 months,15.7 months,16.7 months,and 14.1 months.The FP regimen had an improved disease control rate(DCR)(P=0.044)and 6-month PFS(P=0.014)and exhibited a better trend in PFS(P=0.057)compared with F,and it was also significantly better in PFS than RP(P=0.030).RP did not confer a significant survival benefit;instead,the R group had a trend toward greater benefit with OS(P=0.080)compared with RP.No significant differences were observed between the R and F groups in PFS or OS(P>0.05).CONCLUSION FP is superior to F in achieving 6-month PFS and DCR,while RP is not better than R.FP has an improved PFS and 6-month PFS compared with RP,but F and R had similar clinical efficacy.Therefore,FP may be a highly promising strategy in the treatment of MSS/pMMR mCRC.

Enhancing Data Analysis and Automation: Integrating Python with Microsoft Excel for Non-Programmers

Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.

Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.

Assessment of programmed death-ligand 1 expression in primary tumors and paired lymph node metastases of gastric adenocarcinoma

BACKGROUND Anti-programmed death-1/programmed death-ligand 1(PD-1/PD-L1)immuno-therapy has demonstrated promising results on gastric cancer(GC).However,PD-L1 can express differently between metastatic sites and primary tumors(PT).AIM To compare PD-L1 status in PT and matched lymph node metastases(LNM)of GC patients and to determine the correlation between the PD-L1 status and clinicopathological characteristics.METHODS We retrospectively reviewed 284 GC patients who underwent D2-gastrectomy.PD-L1 was evaluated by immunohistochemistry(clone SP142)using the com-bined positive score.All PD-L1+PT staged as pN+were also tested for PD-L1 expression in their LNM.PD-L1(-)GC with pN+served as the comparison group.RESULTS Among 284 GC patients included,45 had PD-L1+PT and 24 of them had pN+.For comparison,44 PD-L1(-)cases with pN+were included(sample loss of 4 cases).Of the PD-L1+PT,54.2%(13/24 cases)were also PD-L1+in the LNM.Regarding PD-L1(-)PT,9.1%(4/44)had PD-L1+in the LNM.The agreement between PT and LNM had a kappa value of 0.483.Larger tumor size and moderate/severe peritumoral inflammatory response were associated with PD-L1 positivity in both sites.There was no statistical difference in overall survival for PT and LNM according to the PD-L1 status(P=0.166 and P=0.837,respectively).CONCLUSION Intra-patient heterogeneity in PD-L1 expression was observed between the PT and matched LNM.This disagreement in PD-L1 status may emphasize the importance of considering different tumor sites for analyses to select patients for immunotherapy.