Staging laparoscopy improves treatment decision-makingfor advanced gastric cancer

AIM To evaluate the clinical value of staging laparoscopyin treatment decision-making for advancedgastric cancer （GC）.METHODS： Clinical data of 582 patients with advancedGC were retrospectively analyzed. All patientsunderwent staging laparoscopy. The strength ofagreement between computed tomography （CT） stage,endoscopic ultrasound （EUS） stage, laparoscopic stage,and final stage were determined by weighted Kappastatistic （Kw）. The number of patients with treatmentdecision-changes was counted. A χ 2 test was used toanalyze the correlation between peritoneal metastasisor positive cytology and clinical characteristics.RESULTS： Among the 582 patients, the distributions ofpathological T classifications were T2/3 （153, 26.3%）,T4a （262, 45.0%）, and T4b （167, 28.7%）. Treatmentplans for 211 （36.3%） patients were changed after staging laparoscopy was performed. Two （10.5%） of19 patients in M1 regained the opportunity for potentialradical resection by staging laparoscopy. Unnecessarylaparotomy was avoided in 71 （12.2%） patients. Thestrength of agreement between preoperative T stageand final T stage was in almost perfect agreement （Kw= 0.838; 95% confidence interval （CI）： 0.803-0.872;P 〈 0.05） for staging laparoscopy; compared with CTand EUS, which was in fair agreement. The strengthof agreement between preoperative M stage andfinal M stage was in almost perfect agreement （Kw= 0.990; 95% CI： 0.977-1.000; P 〈 0.05） for staginglaparoscopy; compared with CT, which was in slightagreement. Multivariate analysis revealed that tumorsize （≥ 40 mm）, depth of tumor invasion （T4b）, andBorrmann type （Ⅲ or Ⅳ） were significantly correlatedwith either peritoneal metastasis or positive cytology.The best performance in diagnosing P-positive wasobtained when two or three risk factors existed.CONCLUSION： Staging laparoscopy can improvetreatment decision-making for advanced GC anddecrease unnecessary exploratory laparotomy.

Process of Decision-Making of Anti-Cancer Treatment in Elderly Patients with Advanced Lung Cancer

The aim of this study was to identify the decision-making process of anti-cancer treatment in elderly patients with advanced lung cancer. Semi-structured interviews were conducted with 17 patients aged 70 and above to collect data on their feelings and thoughts from the time of diagnosis till they made treatment decisions. The data was analyzed using the Modified Grounded Theory Approach that was modified by Prof. Yasuhito Kinoshita. We found the process to be composed of six categories. The results showed that elderly patients with advanced lung cancer were panicked over unavoidable death when informed of stage IV lung cancer and offered suggestions about anti-cancer treatment. However, trying to accept the situation where death is imminent, patients reconsidered having cancer in older age and recognized a desire to survive even in older age. This process diverged into two paths: one group of patients changed their ideas from radical to life-prolonging treatment by recognizing a desire to survive even in older age and then made anti-cancer treatment decisions by carefully choosing treatment that would allow to carry on their usual way of life;the other group of patients made treatment decisions by carefully choosing physicians to whom they could entrust their life in older age. These findings suggest that it is important for nurses to: 1) encourage patients to talk in order to have them think about what they have valued and want to value in the rest of their life;2) assess if patients prefer to decide on their own by carefully choosing treatment or entrust treatment decisions to physicians;and 3) offer support according to patients’ preferences.

Decision-Making Process for the Place of Death of Elderly Patients with Advanced Cancer and Their Families

Purpose: This study aims to understand how elderly patients with advanced cancer and their families make a decision for a place of death for the patient. Methods: Semi-structured interviews were conducted with 17 pairs of elderly patients and members of their family. The patients had finished anticancer treatment and made some decision about the preferred place of death. A modified grounded-theory approach was used for the data analysis. Results: Making a “tentative” decision for the place of death of the elderly patients is a process with the core category [carefully choosing the final place for self-fulfillment]. The patients were “conducting a comprehensive review of the place of death” and “embracing the wishes for a way of life without difficulty”. Involving the family in making a “tentative” decision about the place of death of the elderly patients is the process with the core category [realizing the wish of patients in the terminal condition for the way for death]. The families were “examining the place of death from different aspects” and “respecting the patient’s intention as far as possible”. Conclusions: When the patients [carefully choosing the final place for self-fulfillment], it was important to reconcile their wishes with the burden on the families. When the families were trying to [realize the wish of patients in the terminal condition for the way for dying], it was important to balance the respect for the patient intentions and homecare they can provide for the patient. For the patients and their families, it is essential to mutually understand the intentions and wishes of the other party in decision making about the place of death.

基于PLCSIM Advanced和Simulink的自动化生产线仿真实训平台设计

为解决自动化生产线实训线下课程实验硬件套数不足、实验时长和场地受限等问题,提升教学质量,设计了一种基于PLCSIM Advanced和Simulink的自动化生产线仿真实训平台。该仿真平台以实训设备为依托,使用Simulink搭建被控对象仿真模型,在PLCSIM Advanced仿真控制器中编写控制算法,通过应用程序接口(application programming interface,API)通信实现对象模型与控制器间数据的实时交换和仿真。以纸张张力控制设备为例,介绍了仿真实训平台搭建和实施过程。实践教学表明,该仿真平台提高了自动化生产线实训课程的教学成效,激发了学生实践学习的兴趣,提升了学生发现、解决复杂工程问题的能力,让学生深刻体会到团队合作和有效沟通的重要性。

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

Present situation and prospect of immunotherapy for unresectable locally advanced esophageal cancer during peri-radiotherapy

Four major studies(Checkmate577,Keynote-590,Checkmate649 and Attraction-4)of locally advanced esophageal cancer published in 2020 have established the importance of immunotherapy,represented by anti-programmed death protein(PD)-1 in postoperative adjuvant treatment and advanced first-line treatment of locally advanced or advanced esophageal cancer and esophagogastric junction cancer,from the aspects of proof of concept,long-term survival,overall survival rate and progression-free survival.For unresectable or inoperable nonmetastatic esophageal cancer,concurrent radiotherapy and chemotherapy is the standard treatment recommended by various guidelines.Because its curative effect is still not ideal,it is necessary to explore radical radiotherapy and chemotherapy in the future,and it is considered to be promising to combine them with immunotherapeutic drugs such as anti-PD-1.This paper mainly discusses how to combine radical concurrent radiotherapy and chemotherapy with immunotherapy for unresectable local advanced esophageal cancer.

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.

Design and analysis of an advanced thermal management system for the solar close observations and proximity experiments spacecraft

In this paper,the mission and the thermal environment of the Solar Close Observations and Proximity Experiments(SCOPE)spacecraft are analyzed,and an advanced thermal management system(ATMS)is designed for it.The relationship and functions of the integrated database,the intelligent thermal control system and the efficient liquid cooling system in the ATMS are elaborated upon.For the complex thermal field regulation system and extreme space thermal environment,a modular simulation and thermal field planning method are proposed,and the feasibility of the planning algorithm is verified by numerical simulation.A solar array liquid cooling system is developed,and the system simulation results indicate that the temperatures of the solar arrays meet the requirements as the spacecraft flies by perihelion and aphelion.The advanced thermal management study supports the development of the SCOPE program and provides a reference for the thermal management in other deep-space exploration programs.

Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees

While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost

Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk.

Clinical outcomes of second-line chemotherapy in patients with advanced pancreatic adenocarcinoma:a real-world study

Objective:Little progress has been made in recent years using first-line chemotherapy,including gemcitabine combined with nab-paclitaxel,FOLFIRINOX,and NALIRIFOX,for advanced pancreatic adenocarcinoma(APC).In addition,the optimal second-line chemotherapy regimen has not been determined.This study aimed to compare the effectiveness of different types of second-line chemotherapy for APC.Methods:Patients with APC who received first-line treatment from January 2008 to January 2021 were considered eligible for this retrospective analysis.The primary and secondary endpoints were overall survival(OS)and progression-free survival(PFS),respectively.Results:Four hundred and thirty-seven and 617 patients were treated with 5-fluorouracil-and gemcitabine-based chemotherapy as first-line treatment,respectively.Demographic and clinical features,except age and liver metastasis,were comparable between the two groups(P<0.05).The median OS was 8.8 and 7.8 months in patients who received a 5-fluorouracil-and gemcitabine-based combined regimen for first-line therapy,respectively(HR=1.244,95%CI=1.090–1.419;P<0.001).The median OS was 5.6 and 1.9 months in patients who received second-line chemotherapy and supportive care,respectively(HR=0.766,95%CI=0.677–0.867;P<0.001).The median PFS was not significantly differently between gemcitabine or 5-fluorouracil monotherapy and combination therapy.Conclusions:A 5-fluorouracil-or gemcitabine-based combined regimen was shown to be as effective as a single 5-fluorouracil or gemcitabine regimen as second-line therapy for patients with APC.

Determination of the best materials for development and designing product using a multi-criteria decision-making

Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are effective.An approach of MCDM is needed to cater to criteria of material assortment simultaneously.More firms are now concerned about increasing their productivity using mathematical tools.To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material.In addition,by using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),the inherent ambiguities of decision-makers in paired evaluations are considered in this research.It goes on to construct a mathematical bi-objective model for determining the best item to purchase.Design/methodology/approach–The entropy perspective is implemented in this paper to evaluate the weight parameters,while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system.The intermediate pipes are used to join the components of the exhaust systems.The materials usually used to manufacture intermediate pipe are SUS 436LM,SUS 430,SUS 304,SUS 436L,SUH 409 L,SUS 441 L and SUS 439L.These seven materials are evaluated based on tensile strength(TS),hardness(H),elongation(E),yield strength(YS)and cost(C).A hybrid methodology combining entropy-based criteria weighting,with the TOPSIS for alternative ranking,is pursued to identify the optimal design material for an engineered application in this paper.This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes.After that,the authors searched for and considered eight materials and evaluated them on the following five criteria:(1)TS,(2)YS,(3)H,(4)E and(5)C.The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes,on their performance and on the cost.In this structure,the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment.This essentially measures the quantity of information each criterion contribution,indicating the relative importance of these criteria better.Subsequently,the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative.The results show that SUS 309,SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.Findings–The material matrix of the decision presented in Table 3 was normalized through Equation 5,as shown in Table 5,and the matrix was multiplied with weighting criteriaß_j.The obtained weighted normalized matrix V_ij is presented in Table 6.However,the ideal,worst and best value was ascertained by employing Equation 7.This study is based on the selection of material for the development of intermediate pipe using MCDM,and it involves four basic stages,i.e.method of translation criteria,screening process,method of ranking and search for methods.The selection was done through the TOPSIS method,and the criteria weight was obtained by the entropy method.The result showed that the top three materials are SUS 309,SUS 432L and SUS 436 LM,respectively.For the future work,it is suggested to select more alternatives and criteria.The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality(ELECTRE),Decision-Making Trial and Evaluation Laboratory(DEMATEL)and Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE).Originality/value–The results provide important conclusions for material selection in this targeted application,verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.

The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric data.By Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is essential.Existing measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive results.For instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different implication.In the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria equally.Due to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both sets.According to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one another.The suggested DFM’s fundamental characteristics are provided.Based on the newly developed DFM,a unique approach tomultiple criterion group decision-making is offered.Our suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in PFSs.Our proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter zero.The method’s applicability and validity shown by the findings are contrasted with those obtained using various other existing approaches.To assess its stability and usefulness,a sensitivity analysis is done.

A Comprehensive Survey on Advanced Persistent Threat (APT) Detection Techniques

The increase in number of people using the Internet leads to increased cyberattack opportunities.Advanced Persistent Threats,or APTs,are among the most dangerous targeted cyberattacks.APT attacks utilize various advanced tools and techniques for attacking targets with specific goals.Even countries with advanced technologies,like the US,Russia,the UK,and India,are susceptible to this targeted attack.APT is a sophisticated attack that involves multiple stages and specific strategies.Besides,TTP(Tools,Techniques,and Procedures)involved in the APT attack are commonly new and developed by an attacker to evade the security system.However,APTs are generally implemented in multiple stages.If one of the stages is detected,we may apply a defense mechanism for subsequent stages,leading to the entire APT attack failure.The detection at the early stage of APT and the prediction of the next step in the APT kill chain are ongoing challenges.This survey paper will provide knowledge about APT attacks and their essential steps.This follows the case study of known APT attacks,which will give clear information about the APT attack process—in later sections,highlighting the various detection methods defined by different researchers along with the limitations of the work.Data used in this article comes from the various annual reports published by security experts and blogs and information released by the enterprise networks targeted by the attack.

A phase Ⅰ study of Hemay022, an irreversible dual EGFR/HER2 tyrosine kinase inhibitor in Chinese patients with HER2-positive advanced breast cancer

Objective: Hemay022 is a novel small-molecule and an irreversible tyrosine kinase inhibitor with the target of epidermal growth factor receptor(EGFR)/human epidermal growth factor receptor 2(HER2), which demonstrated anti-tumor activity in preclinical studies. This first-in-human study evaluated the safety, pharmacokinetics,tolerability and preliminary anti-tumor activity of Hemay022 in HER2-positive advanced breast cancer patients.Methods: Heavily pretreated patients with HER2-positive advanced breast cancer were assigned to eight dose cohorts in a 3+3 dose-escalation pattern at doses of 50-600 mg QD and 300 mg BID. Eligible patients were given a single dose of Hemay022 on d 1 in week 0, followed by once daily continuous doses for four weeks in 28-day cycles.Pharmacokinetic samples were obtained on d 1 and d 28. Clinical responses were assessed every eight weeks.Results: Twenty-eight patients with advanced breast cancer were treated with Hemay022. The most frequently reported drug-related adverse events were diarrhoea(85.7%), vomiting(28.6%), nausea(25.0%) and decreased appetite(17.9%). No grade 4 drug-related adverse events were reported. At 50-600 mg doses, steady state areas under the concentration-time curve and peak concentrations increased with doses. One patient achieved complete response(CR), and three achieved partial response(PR). The objective response rate(ORR) and disease control rate(DCR) were 14.3% and 46.4% in 28 patients, respectively. The median progression-free survival(PFS) was3.98 months.Conclusions: Hemay022 at the dose of 500 mg once daily was well tolerated. The pharmacokinetic properties and encouraging anti-tumor activities of Hemay022 in advanced breast cancer patients warranted further evaluation of Hemay022 for treating breast cancer patients in the current phase Ⅲ trial(No. NCT05122494).

A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying capacity.This approach can capture the imprecision and ambiguity often present in human perception.With the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making algorithms.By implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology.

Comprehensive analysis of advanced glycation end-products in commonly consumed foods:presenting a database for dietary AGEs and associated exposure assessment

Advanced glycation end-products(AGEs)are a group of heterogeneous compounds formed in heatprocessed foods and are proven to be detrimental to human health.Currently,there is no comprehensive database for AGEs in foods that covers the entire range of food categories,which limits the accurate risk assessment of dietary AGEs in human diseases.In this study,we first established an isotope dilution UHPLCQq Q-MS/MS-based method for simultaneous quantification of 10 major AGEs in foods.The contents of these AGEs were detected in 334 foods covering all main groups consumed in Western and Chinese populations.Nε-Carboxymethyllysine,methylglyoxal-derived hydroimidazolone isomers,and glyoxal-derived hydroimidazolone-1 are predominant AGEs found in most foodstuffs.Total amounts of AGEs were high in processed nuts,bakery products,and certain types of cereals and meats(>150 mg/kg),while low in dairy products,vegetables,fruits,and beverages(<40 mg/kg).Assessment of estimated daily intake implied that the contribution of food groups to daily AGE intake varied a lot under different eating patterns,and selection of high-AGE foods leads to up to a 2.7-fold higher intake of AGEs through daily meals.The presented AGE database allows accurate assessment of dietary exposure to these glycotoxins to explore their physiological impacts on human health.

Prognostic analysis of related factors of adverse reactions to immunotherapy in advanced gastric cancer and establishment of a nomogram model

BACKGROUND Immunotherapy for advanced gastric cancer has attracted widespread attention in recent years.However,the adverse reactions of immunotherapy and its relationship with patient prognosis still need further study.In order to determine the association between adverse reaction factors and prognosis,the aim of this study was to conduct a systematic prognostic analysis.By comprehensively evaluating the clinical data of patients with advanced gastric cancer treated by immunotherapy,a nomogram model will be established to predict the survival status of patients more accurately.AIM To explore the characteristics and predictors of immune-related adverse reactions(irAEs)in advanced gastric cancer patients receiving immunotherapy with programmed death protein-1(PD-1)inhibitors and to analyze the correlation between irAEs and patient prognosis.METHODS A total of 140 patients with advanced gastric cancer who were treated with PD-1 inhibitors in our hospital from June 2021 to October 2023 were selected.Patients were divided into the irAEs group and the non-irAEs group according to whether or not irAEs occurred.Clinical features,manifestations,and prognosis of irAEs in the two groups were collected and analyzed.A multivariate logistic regression model was used to analyze the related factors affecting the occurrence of irAEs,and the prediction model of irAEs was established.The receiver operating characteristic(ROC)curve was used to evaluate the ability of different indicators to predict irAEs.A Kaplan-Meier survival curve was used to analyze the correlation between irAEs and prognosis.The Cox proportional risk model was used to analyze the related factors affecting the prognosis of patients.RESULTS A total of 132 patients were followed up,of whom 63(47.7%)developed irAEs.We looked at the two groups’clinical features and found that the two groups were statistically different in age≥65 years,Ki-67 index,white blood cell count,neutrophil count,and regulatory T cell(Treg)count(all P<0.05).Multivariate logistic regression analysis showed that Treg count was a protective factor affecting irAEs occurrence(P=0.030).The ROC curve indicated that Treg+Ki-67+age(≥65 years)combined could predict irAEs well(area under the curve=0.753,95%confidence interval:0.623-0.848,P=0.001).Results of the Kaplan-Meier survival curve showed that progressionfree survival(PFS)was longer in the irAEs group than in the non-irAEs group(P=0.001).Cox proportional hazard regression analysis suggested that the occurrence of irAEs was an independent factor for PFS(P=0.006).CONCLUSION The number of Treg cells is a separate factor that affects irAEs in advanced gastric cancer patients receiving PD-1 inhibitor immunotherapy.irAEs can affect the patients’PFS and result in longer PFS.Treg+Ki-67+age(≥65 years old)combined can better predict the occurrence of adverse reactions.