An Active Deception Defense Model Based on Address Mutation and Fingerprint Camouflage

The static and predictable characteristics of cyber systems give attackers an asymmetric advantage in gathering useful information and launching attacks.To reverse this asymmetric advantage,a new defense idea,called Moving Target Defense(MTD),has been proposed to provide additional selectable measures to complement traditional defense.However,MTD is unable to defeat the sophisticated attacker with fingerprint tracking ability.To overcome this limitation,we go one step beyond and show that the combination of MTD and Deception-based Cyber Defense(DCD)can achieve higher performance than either of them.In particular,we first introduce and formalize a novel attacker model named Scan and Foothold Attack(SFA)based on cyber kill chain.Afterwards,we develop probabilistic models for SFA defenses to provide a deeper analysis of the theoretical effect under different defense strategies.These models quantify attack success probability and the probability that the attacker will be deceived under various conditions,such as the size of address space,and the number of hosts,attack analysis time.Finally,the experimental results show that the actual defense effect of each strategy almost perfectly follows its probabilistic model.Also,the defense strategy of combining address mutation and fingerprint camouflage can achieve a better defense effect than the single address mutation.

Plant Chemical Defenses against Insect Herbivores—Using theWild Tobacco as a Model

The Nicotiana genus, commonly known as tobacco, holds significant importance as a crucial economic crop. Confrontedwith an abundance of herbivorous insects that pose a substantial threat to yield, tobacco has developed adiverse and sophisticated array of mechanisms, establishing itself as a model of plant ecological defense. Thisreview provides a concise overview of the current understanding of tobacco’s defense strategies against herbivores.Direct defenses, exemplified by its well-known tactic of secreting the alkaloid nicotine, serve as a potent toxinagainst a broad spectrum of herbivorous pests. Moreover, in response to herbivore attacks, tobacco enhancesthe discharge of volatile compounds, harnessing an indirect strategy that attracts the predators of the herbivores.The delicate balance between defense and growth leads to the initiation of most defense strategies only after aherbivore attack. Among plant hormones, notably jasmonic acid (JA), play central roles in coordinating thesedefense processes. JA signaling interacts with other plant hormone signaling pathways to facilitate the extensivetranscriptional and metabolic adjustments in plants following herbivore assault. By shedding light on these ecologicaldefense strategies, this review emphasizes not only tobacco’s remarkable adaptability in its natural habitatbut also offers insights beneficial for enhancing the resilience of current crops.

A shield of defense:Developing ballistic composite panels with effective electromagnetic interference shielding absorption

The primary goal of this study is to develop cost-effective shield materials that offer effective protection against high-velocity ballistic impact and electromagnetic interference(EMI)shielding capabilities through absorption.Six fiber-reinforced epoxy composite panels,each with a different fabric material and stacking sequence,have been fabricated using a hand-layup vacuum bagging process.Two panels made of Kevlar and glass fibers,referred to as(K-NIJ)and(G-NIJ),have been tested according to the National Institute of Justice ballistic resistance protective materials test NIJ 0108.01 Standard-Level IIIA(9 mm×19 mm FMJ 124 g)test.Three panels,namely,a hybrid of Kevlar and glass(H-S),glass with ceramic particles(C-S),and glass with recycled rubber(R-S)have been impacted by the bullet at the center,while the fourth panel made of glass fiber(G-S)has been impacted at the side.EMI shielding properties have been measured in the X-band frequency range via the reflection-transmission method.Results indicate that four panels(K-NIJ,G-NIJ,H-S,and G-S)are capable of withstanding high-velocity impact by stopping the bullet from penetrating through the panels while maintaining their structural integrity.However,under such conditions,these panels may experience localized delamination with variable severity.The EMI measurements reveal that the highest absorptivity observed is 88% for the KNIJ panel at 10.8 GHz,while all panels maintain an average absorptivity above 65%.All panels act as a lossy medium with a peak absorptivity at different frequencies,with K-NIJ and H-S panels demonstrating the highest absorptivity.In summary,the study results in the development of a novel,costeffective,multifunctional glass fiber epoxy composite that combines ballistic and electromagnetic interference shielding properties.The material has been developed using a simple manufacturing method and exhibits remarkable ballistic protection that outperforms Kevlar in terms of shielding efficiency;no bullet penetration or back face signature is observed,and it also demonstrates high EMI shielding absorption.Overall,the materials developed show great promise for various applications,including the military and defense.

Seasonal increase in nest defense,but not egg rejection,in a cuckoo host

The interactions between avian brood parasites and their hosts provide an informative and easy-to-handle system for studying coevolution.Avian brood parasitism reduces the reproductive success of hosts,and thus,hosts have evolved anti-parasitic strategies,such as rejecting parasitic eggs and adopting aggressive nest defense strategies,to avoid the cost brought on by brood parasitism.To test whether host anti-parasitic strategies are adjusted with the risk of being parasitized when the breeding seasons of brood parasites and hosts are not synchronous,we conducted a field experiment assessing nest defense and egg recognition behaviors of the Isabelline Shrike(Lanius isabellinus),a host of the Common Cuckoo(Cuculus canorus).In the local area,the host Isabelline Shrike begins to breed in April,whereas the summer migratory Common Cuckoo migrates to the local area in May and begins to lay parasitic eggs.Results showed that nest defense behaviors of the Isabelline Shrike increases significantly after cuckoo arrival,showing higher aggressiveness to cuckoo dummies,with no significant difference in attack rates among cuckoo,sparrowhawk and dove dummies,but their egg rejection did not change significantly.These results imply that Isabelline Shrikes may adjust their nest defense behavior,but not egg rejection behavior,with seasonality.

Two intestinal microbiota-derived metabolites, deoxycholic acid and butyrate, synergize to enhance host defense peptide synthesis and alleviate necrotic enteritis

Background Necrotic enteritis(NE)is a major enteric disease in poultry,yet effective mitigation strategies remain elusive.Deoxycholic acid(DCA)and butyrate,two major metabolites derived from the intestinal microbiota,have independently been shown to induce host defense peptide(HDP)synthesis.However,the potential synergy between these two compounds remains unexplored.Methods To investigate the possible synergistic effect between DCA and butyrate in regulating HDP synthesis and barrier function,we treated chicken HD11 macrophage cells and jejunal explants with DCA and sodium butyrate(NaB),either individually or in combination,for 24 h.Subsequently,we performed RNA isolation and reverse transcrip-tion-quantitative PCR to analyze HDP genes as well as the major genes associated with barrier function.To further determine the synergy between DCA and NaB in enhancing NE resistance,we conducted two independent trials with Cobb broiler chicks.In each trial,the diet was supplemented with DCA or NaB on the day-of-hatch,followed by NE induction through sequential challenges with Eimeria maxima and Clostridium perfringens on d 10 and 14,respectively.We recorded animal mortality after infection and assessed intestinal lesions on d 17.The impact of DCA and NaB on the microbiota in the ileum and cecum was evaluated through bacterial 16S rRNA gene sequencing.Results We found that the combination of DCA and NaB synergistically induced multiple HDP genes in both chicken HD11 cells and jejunal explants.Additionally,the gene for claudin-1,a major tight junction protein,also exhibited synergistic induction in response to DCA and NaB.Furthermore,dietary supplementation with a combination of 0.75 g/kg DCA and 1 g/kg NaB led to a significant improvement in animal survival and a reduction in intestinal lesions compared to either compound alone in a chicken model of NE.Notably,the cecal microbiota of NE-infected chickens showed a marked decrease in SCFA-producing bacteria such as Bacteroides,Faecalibacterium,and Cuneatibacter,with lactobacilli becoming the most dominant species.However,supplementation with DCA and NaB largely restored the intestinal microbiota to healthy levels.Conclusions DCA synergizes with NaB to induce HDP and claudin-1 expression and enhance NE resistance,with potential for further development as cost-effective antibiotic alternatives.

Machine Learning Security Defense Algorithms Based on Metadata Correlation Features

With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time requirements.Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats.This paper proposes a machine-learning security defense algorithm based on metadata association features.Emphasize control over unauthorized users through privacy,integrity,and availability.The user model is established and the mapping between the user model and the metadata of the data source is generated.By analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be realized.Define and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense system.The experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is good.This method can effectively resist data intrusion and has high air traffic control security.It can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.

Two-Stage Optimal Scheduling of Community Integrated Energy System

From the perspective of a community energy operator,a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads.The day-ahead scheduling analyzes whether various controllable loads participate in the optimization and investigates the impact of their responses on the operating economy of the community integrated energy system(IES)before and after;the intra-day scheduling proposes a two-stage rolling optimization model based on the day-ahead scheduling scheme,taking into account the fluctuation of wind turbine output and load within a short period of time and according to the different response rates of heat and cooling power,and solves the adjusted output of each controllable device.The simulation results show that the optimal scheduling of controllable loads effectively reduces the comprehensive operating costs of community IES;the two-stage optimal scheduling model can meet the energy demand of customers while effectively and timely suppressing the random fluctuations on both sides of the source and load during the intra-day stage,realizing the economic and smooth operation of IES.

Two-Stage Planning of Distributed Power Supply and Energy Storage Capacity Considering Hierarchical Partition Control of Distribution Network with Source-Load-Storage

Aiming at the consumption problems caused by the high proportion of renewable energy being connected to the distribution network,it also aims to improve the power supply reliability of the power system and reduce the operating costs of the power system.This paper proposes a two-stage planning method for distributed generation and energy storage systems that considers the hierarchical partitioning of source-storage-load.Firstly,an electrical distance structural index that comprehensively considers active power output and reactive power output is proposed to divide the distributed generation voltage regulation domain and determine the access location and number of distributed power sources.Secondly,a two-stage planning is carried out based on the zoning results.In the phase 1 distribution network-zoning optimization layer,the network loss is minimized so that the node voltage in the area does not exceed the limit,and the distributed generation configuration results are initially determined;in phase 2,the partition-node optimization layer is planned with the goal of economic optimization,and the distance-based improved ant lion algorithm is used to solve the problem to obtain the optimal distributed generation and energy storage systemconfiguration.Finally,the IEEE33 node systemwas used for simulation.The results showed that the voltage quality was significantly improved after optimization,and the overall revenue increased by about 20.6%,verifying the effectiveness of the two-stage planning.

Effective Utilization of Government-Provided CTI by Small Businesses within the Defense Industrial Base

There are two broad objectives of the research reported in this paper. First, we assess whether government-provided cyber threat intelligence (CTI) is helpful in preventing, or responding to, cyber-attacks among small businesses within the U.S. Defense Industrial Base (DIB). Second, we identify ways of improving the effectiveness of government-provided CTI to small businesses within the DIB. Based on a questionnaire-based survey, our findings suggest that government-provided CTI helps businesses within the DIB in preventing, or responding to, cyber-attacks providing a firm is familiar with the CTI. Unfortunately, a large percentage of small firms are not familiar with the government-provided CTI feeds and consequently are not utilizing the CTI. This latter situation is largely due to financial constraints confronting small businesses that prevent firms from having the wherewithal necessary to effectively utilize the government-provided CTI. However, we found a significant positive association between a firm’s familiarity with the government-provided CTI and whether a firm is being periodically reviewed by the Defense Counterintelligence and Security Agency (DCSA) or is compliant with the Cybersecurity Maturity Model Certification (CMMC) program. The findings from our study also show that the participating firms believe that external cyber threats are more likely to be the cause of a future cybersecurity breach than internal cybersecurity threats. Finally, our study found that the portion of the IT budget that small businesses within the DIB spend on cybersecurity-related activities is dependent on the perception that a firm would be the target of an external cyber-attack.

Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises

As cyber threats keep changing and business environments adapt, a comprehensive approach to disaster recovery involves more than just defensive measures. This research delves deep into the strategies required to respond to threats and anticipate and mitigate them proactively. Beginning with understanding the critical need for a layered defense and the intricacies of the attacker’s journey, the research offers insights into specialized defense techniques, emphasizing the importance of timely and strategic responses during incidents. Risk management is brought to the forefront, underscoring businesses’ need to adopt mature risk assessment practices and understand the potential risk impact areas. Additionally, the value of threat intelligence is explored, shedding light on the importance of active engagement within sharing communities and the vigilant observation of adversary motivations. “Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises” is a comprehensive guide for organizations aiming to fortify their cybersecurity posture, marrying best practices in proactive and reactive measures in the ever-challenging digital realm.

GUARDIAN: A Multi-Tiered Defense Architecture for Thwarting Prompt Injection Attacks on LLMs

This paper introduces a novel multi-tiered defense architecture to protect language models from adversarial prompt attacks. We construct adversarial prompts using strategies like role emulation and manipulative assistance to simulate real threats. We introduce a comprehensive, multi-tiered defense framework named GUARDIAN (Guardrails for Upholding Ethics in Language Models) comprising a system prompt filter, pre-processing filter leveraging a toxic classifier and ethical prompt generator, and pre-display filter using the model itself for output screening. Extensive testing on Meta’s Llama-2 model demonstrates the capability to block 100% of attack prompts. The approach also auto-suggests safer prompt alternatives, thereby bolstering language model security. Quantitatively evaluated defense layers and an ethical substitution mechanism represent key innovations to counter sophisticated attacks. The integrated methodology not only fortifies smaller LLMs against emerging cyber threats but also guides the broader application of LLMs in a secure and ethical manner.

Influence of two-stage harvesting on the properties of cold-pressed rapeseed(Brassica napus L.)oils

Rapeseed(Brassica napus L.)harvesting method is critical since it significantly determines the seed yield,oil quality,and industrial efficiency.This study investigated the influences of harvesting methods on the quality of cold-pressed rapeseed oil of two varieties.Oil color,peroxide value(POV),tocopherol content,fatty acid composition,and polarity of total polyphenols(PTP)contents of two rapeseed varieties in Huanggang and Xiangyang were compared through artificially simulated combined harvesting and two-stage harvesting.Results showed significant differences in the quality of rapeseed oil between the two harvesting methods.The red value(R-value),POV,total tocopherol contents,linoleic and linolenic acid content,and PTP content of the pressed rapeseed oil prepared by the combined harvesting method were about 27.6,5.7,15.8,2.0,0.5,and 28.6%lower than those of the oil produced from the two-stage harvesting method,respectively.Xiangyang and Huayouza62 performed better in the two regions and two varieties,respectively.To sum up,the rapeseed oil obtained 41–44 days after final flowering of combined harvesting,35 days after final flowering,and six days of post-ripening of the two-stage harvesting had the best quality.

Chained Dual-Generative Adversarial Network:A Generalized Defense Against Adversarial Attacks

Neural networks play a significant role in the field of image classification.When an input image is modified by adversarial attacks,the changes are imperceptible to the human eye,but it still leads to misclassification of the images.Researchers have demonstrated these attacks to make production self-driving cars misclassify StopRoad signs as 45 Miles Per Hour(MPH)road signs and a turtle being misclassified as AK47.Three primary types of defense approaches exist which can safeguard against such attacks i.e.,Gradient Masking,Robust Optimization,and Adversarial Example Detection.Very few approaches use Generative Adversarial Networks(GAN)for Defense against Adversarial Attacks.In this paper,we create a new approach to defend against adversarial attacks,dubbed Chained Dual-Generative Adversarial Network(CD-GAN)that tackles the defense against adversarial attacks by minimizing the perturbations of the adversarial image using iterative oversampling and undersampling using GANs.CD-GAN is created using two GANs,i.e.,CDGAN’s Sub-ResolutionGANandCDGAN’s Super-ResolutionGAN.The first is CDGAN’s Sub-Resolution GAN which takes the original resolution input image and oversamples it to generate a lower resolution neutralized image.The second is CDGAN’s Super-Resolution GAN which takes the output of the CDGAN’s Sub-Resolution and undersamples,it to generate the higher resolution image which removes any remaining perturbations.Chained Dual GAN is formed by chaining these two GANs together.Both of these GANs are trained independently.CDGAN’s Sub-Resolution GAN is trained using higher resolution adversarial images as inputs and lower resolution neutralized images as output image examples.Hence,this GAN downscales the image while removing adversarial attack noise.CDGAN’s Super-Resolution GAN is trained using lower resolution adversarial images as inputs and higher resolution neutralized images as output images.Because of this,it acts as an Upscaling GAN while removing the adversarial attak noise.Furthermore,CD-GAN has a modular design such that it can be prefixed to any existing classifier without any retraining or extra effort,and 2542 CMC,2023,vol.74,no.2 can defend any classifier model against adversarial attack.In this way,it is a Generalized Defense against adversarial attacks,capable of defending any classifier model against any attacks.This enables the user to directly integrate CD-GANwith an existing production deployed classifier smoothly.CD-GAN iteratively removes the adversarial noise using a multi-step approach in a modular approach.It performs comparably to the state of the arts with mean accuracy of 33.67 while using minimal compute resources in training.

Novel 18β-glycyrrhetinic acid amide derivatives show dual-acting capabilities for controlling plant bacterial diseases through ROS-mediated antibacterial efficiency and activating plant defense responses

Natural products have long been a crucial source of,or provided inspiration for new agrochemical discovery.Naturally occurring 18β-glycyrrhetinic acid shows broad-spectrum bioactivities and is a potential skeleton for novel drug discovery.To extend the utility of 18β-glycyrrhetinic acid for agricultural uses,a series of novel 18β-glycyrrhetinic acid amide derivatives were prepared and evaluated for their antibacterial potency.Notably,compound 5k showed good antibacterial activity in vitro against Xanthomonas oryzae pv.oryzae(Xoo,EC50=3.64 mg L–1),and excellent protective activity(54.68%)against Xoo in vivo.Compound 5k induced excessive production and accumulation of reactive oxygen species in the tested pathogens,resulting in damaging the bacterial cell envelope.More interestingly,compound 5k could increase the activities of plant defense enzymes including catalase,superoxide dismutase,peroxidase,and phenylalanine ammonia lyase.Taken together,these enjoyable results suggested that designed compounds derived from 18β-glycyrrhetinic acid showed potential for controlling intractable plant bacterial diseases by disturbing the balance of the phytopathogen’s redox system and activating the plant defense system.

The dual antimicrobial and immunomodulatory roles of host defense peptides and their applications in animal production

Host defense peptides(HDPs)are small molecules with broad-spectrum antimicrobial activities against infectious bacteria,viruses,and fungi.Increasing evidence suggests that HDPs can also indirectly protect hosts by modulating their immune responses.Due to these dual roles,HDPs have been considered one of the most promising antibiotic substitutes to improve growth performance,intestinal health,and immunity in farm animals.This review describes the antimicrobial and immunomodulatory roles of host defense peptides and their recent applications in animal production.

Tourism Route Recommendation Based on A Multi-Objective Evolutionary Algorithm Using Two-Stage Decomposition and Pareto Layering

Tourism route planning is widely applied in the smart tourism field.The Pareto-optimal front obtained by the traditional multi-objective evolutionary algorithm exhibits long tails,sharp peaks and disconnected regions problems,which leads to uneven distribution and weak diversity of optimization solutions of tourism routes.Inspired by these limitations,we propose a multi-objective evolutionary algorithm for tourism route recommendation(MOTRR)with two-stage and Pareto layering based on decomposition.The method decomposes the multiobjective problem into several subproblems,and improves the distribution of solutions through a two-stage method.The crowding degree mechanism between extreme and intermediate populations is used in the two-stage method.The neighborhood is determined according to the weight of the subproblem for crossover mutation.Finally,Pareto layering is used to improve the updating efficiency and population diversity of the solution.The two-stage method is combined with the Pareto layering structure,which not only maintains the distribution and diversity of the algorithm,but also avoids the same solutions.Compared with several classical benchmark algorithms,the experimental results demonstrate competitive advantages on five test functions,hypervolume(HV)and inverted generational distance(IGD)metrics.Using the experimental results of real scenic spot datasets from two famous tourism social networking sites with vast amounts of users and large-scale online comments in Beijing,our proposed algorithm shows better distribution.It proves that the tourism routes recommended by our proposed algorithm have better distribution and diversity,so that the recommended routes can better meet the personalized needs of tourists.

Blockchain Security Threats and Collaborative Defense:A Literature Review

As a distributed database,the system security of the blockchain is of great significance to prevent tampering,protect privacy,prevent double spending,and improve credibility.Due to the decentralized and trustless nature of blockchain,the security defense of the blockchain system has become one of the most important measures.This paper comprehensively reviews the research progress of blockchain security threats and collaborative defense,and we first introduce the overview,classification,and threat assessment process of blockchain security threats.Then,we investigate the research status of single-node defense technology and multi-node collaborative defense technology and summarize the blockchain security evaluation indicators and evaluation methods.Finally,we discuss the challenges of blockchain security and future research directions,such as parallel detection and federated learning.This paper aims to stimulate further research and discussion on blockchain security,providing more reliable security guarantees for the use and development of blockchain technology to face changing threats and challenges through continuous updating and improvement of defense technologies.

Multi-source coordinated stochastic restoration for SOP in distribution networks with a two-stage algorithm

After suffering from a grid blackout, distributed energy resources(DERs), such as local renewable energy and controllable distributed generators and energy storage can be used to restore loads enhancing the system’s resilience. In this study, a multi-source coordinated load restoration strategy was investigated for a distribution network with soft open points(SOPs). Here, the flexible regulation ability of the SOPs is fully utilized to improve the load restoration level while mitigating voltage deviations. Owing to the uncertainty, a scenario-based stochastic optimization approach was employed,and the load restoration problem was formulated as a mixed-integer nonlinear programming model. A computationally efficient solution algorithm was developed for the model using convex relaxation and linearization methods. The algorithm is organized into a two-stage structure, in which the energy storage system is dispatched in the first stage by solving a relaxed convex problem. In the second stage, an integer programming problem is calculated to acquire the outputs of both SOPs and power resources. A numerical test was conducted on both IEEE 33-bus and IEEE 123-bus systems to validate the effectiveness of the proposed strategy.

Attacks Against Cross-Chain Systems and Defense Approaches:A Contemporary Survey

The blockchain cross-chain is a significant technology for inter-chain interconnection and value transfer among different blockchain networks.Cross-chain overcomes the“information island”problem of the closed blockchain network and is increasingly applied to multiple critical areas such as finance and the internet of things(IoT).Blockchain can be divided into three main categories of blockchain networks:public blockchains,private blockchains,and consortium blockchains.However,there are differences in block structures,consensus mechanisms,and complex working mechanisms among heterogeneous blockchains.The fragility of the cross-chain system itself makes the cross-chain system face some potential security and privacy threats.This paper discusses security defects on the cross-chain implementation mechanism,and discusses the impact of the structural features of blockchain networks on cross-chain security.In terms of cross-chain intercommunication,a cross-chain attack can be divided into a multi-chain combination attack,native chain attack,and inter-chain attack diffusion.Then various security threats and attack paths faced by the cross-chain system are analyzed.At last,the corresponding security defense methods of cross-chain security threats and future research directions for cross-chain applications are put forward.

Alu antisense RNA ameliorates methylglyoxal-induced human lens epithelial cell apoptosis by enhancing antioxidant defense

AIM:To determine whether an antisense RNA corresponding to the human Alu transposable element(Aluas RNA)can protect human lens epithelial cells(HLECs)from methylglyoxal-induced apoptosis.METHODS:Cell counting kit-8(CCK-8)and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide(MTT)assays were used to assess HLEC viability.HLEC viability/death was detected using a Calcein-AM/PI double staining kit;the annexin V-FITC method was used to detect HLEC apoptosis.The cytosolic reactive oxygen species(ROS)levels in HLECs were determined using a reactive species assay kit.The levels of malondialdehyde(MDA)and the antioxidant activities of total-superoxide dismutase(T-SOD)and glutathione peroxidase(GSH-Px)were assessed in HLECs using their respective kits.RT-q PCR and Western blotting were used to measure m RNA and protein expression levels of the genes.RESULTS:Aluas RNA rescued methylglyoxal-induced apoptosis in HLECs and ameliorated both the methylglyoxalinduced decrease in Bcl-2 m RNA and the methylglyoxalinduced increase in Bax m RNA.In addition,Aluas RNA inhibited the methylglyoxal-induced increase in Alu sense RNA expression.Aluas RNA inhibited the production of ROS induced by methylglyoxal,restored T-SOD and GSHPx activity,and moderated the increase in MDA content after treatment with methylglyoxal.Aluas RNA significantly restored the methylglyoxal-induced down-regulation of Nrf2 gene and antioxidant defense genes,including glutathione peroxidase,heme oxygenase 1,γ-glutamylcysteine synthetase and quinone oxidoreductase 1.Aluas RNA ameliorated methylglyoxal-induced increases of the m RNA and protein expression of Keap1 that is the negative regulator of Nrf2.CONCLUSION:Aluas RNA reduces apoptosis induced by methylglyoxal by enhancing antioxidant defense.