Defense Strategies Research Articles

CoCoNuTs are a diverse subclass of Type IV restriction systems predicted to target RNA.

A comprehensive census of McrBC systems, among the most common forms of prokaryotic Type IV restriction systems, followed by phylogenetic analysis, reveals their enormous abundance in diverse prokaryotes and a plethora of genomic associations. We focus on a previously uncharacterized branch, which we denote coiled-coil nuclease tandems (CoCoNuTs) for their salient features: the presence of extensive coiled-coil structures and tandem nucleases. The CoCoNuTs alone show extraordinary variety, with three distinct types and multiple subtypes. All CoCoNuTs contain domains predicted to interact with translation system components, such as OB-folds resembling the SmpB protein that binds bacterial transfer-messenger RNA (tmRNA), YTH-like domains that might recognize methylated tmRNA, tRNA, or rRNA, and RNA-binding Hsp70 chaperone homologs, along with RNases, such as HEPN domains, all suggesting that the CoCoNuTs target RNA. Many CoCoNuTs might additionally target DNA, via McrC nuclease homologs. Additional restriction systems, such as Type I RM, BREX, and Druantia Type III, are frequently encoded in the same predicted superoperons. In many of these superoperons, CoCoNuTs are likely regulated by cyclic nucleotides, possibly, RNA fragments with cyclic termini, that bind associated CARF (CRISPR-Associated Rossmann Fold) domains. We hypothesize that the CoCoNuTs, together with the ancillary restriction factors, employ an echeloned defense strategy analogous to that of Type III CRISPR-Cas systems, in which an immune response eliminating virus DNA and/or RNA is launched first, but then, if it fails, an abortive infection response leading to PCD/dormancy via host RNA cleavage takes over.

DETECTION OF WIRELESS NETWORK ATTACKS USING SUPERVISED MACHINE LEARNING TECHNIQUE

The security and integrity of computer networks are seriously threatened by network assaults. Keeping a safe network environment requires the capacity to anticipate and stop these threats. Supervised machine learning methods have become powerful instruments for attacking network traffic and spotting patterns that point to malicious behaviour. We provide an in-depth examination of supervised machine learning methods for network attack prediction. We gather the data, preprocess it, extract pertinent features, and structure it so that machine learning algorithms may use it.We assess these algorithms' performance. To understand the fundamental patterns and traits of network assaults, we look at how interpretability the trained models are. This enables network managers to comprehend the types of threats and create suitable. Keywords - Network Attacks, Supervised Machine Learning, Network security,Network traffic analysis, Malicious behavior detection, Feature extraction,Machine learning algorithm,Model interpretability,Network attack patterns,Network defense strategies,Naive Bayes Algorithm, Ridge Classfier ,Random Forest Classfier

Sinomenine attenuates pulmonary fibrosis by downregulating TGF-β1/Smad3, PI3K/Akt and NF-κB signaling pathways

BackgroundSince COVID-19 became a global epidemic disease in 2019, pulmonary fibrosis (PF) has become more prevalent among persons with severe infections, with IPF being the most prevalent form. In traditional Chinese medicine, various disorders are treated using Sinomenine (SIN). The SIN’s strategy for PF defense is unclear.MethodsBleomycin (BLM) was used to induce PF, after which inflammatory factors, lung histological alterations, and the TGF-/Smad signaling pathway were assessed. By administering various dosages of SIN and the TGF- receptor inhibitor SB-431,542 to human embryonic lung fibroblasts (HFL-1) and A549 cells, we were able to examine proliferation and migration as well as the signaling molecules implicated in Epithelial-Mesenchymal Transition (EMT) and Extra-Cellular Matrix (ECM).ResultsIn vivo, SIN reduced the pathological changes in the lung tissue induced by BLM, reduced the abnormal expression of inflammatory cytokines, and improved the weight and survival rate of mice. In vitro, SIN inhibited the migration and proliferation by inhibiting TGF-β1/Smad3, PI3K/Akt, and NF-κB pathways, prevented the myofibroblasts (FMT) of HFL-1, reversed the EMT of A549 cells, restored the balance of matrix metalloenzymes, and reduced the expression of ECM proteins.ConclusionSIN attenuated PF by down-regulating TGF-β/Smad3, PI3K/Akt, and NF-κB signaling pathways, being a potential effective drug in the treatment of PF.

360 DEGREE DESTROYER FOR MILITARY

The "360 Degree Destroyer for Military" model operates by automatically detecting various threats such as missiles, tankers, guns, humans, and drones using a laptop camera. Detection is accomplished through the implementation of CNN algorithms. Instead of firing upon detection, the system utilizes a laser to pinpoint detected object and LED is used to indicate the threat level of the detected object, and this system also detects the land mine using metal sensor. Messages indicating the presence of detected objects are promptly sent to Telegram for immediate action. Additionally, the movement of the robot can be controlled manually via Bluetooth by establishing a communication link between a Bluetooth-enabled device (such as a smartphone or a computer) and the robot's control system. This link allows commands to be sent wirelessly from the device to the robot, enabling control over its movement. This manual control via Bluetooth can include commands to move forward, backward, turn left or right, stop, or perform other predefined actions. This innovative approach to threat detection and communication provides a flexible and efficient solution for defense strategies, enhancing situational awareness and response capabilities. Keywords--- Threat Detection, Land Mine, Missiles, Tankers, Guns, Humans, Drones, Laptop Camera, CNN, Laser, Led, Telegram, Bluetooth.

Challenges and efforts in managing AI trustworthiness risks: a state of knowledge

This paper addresses the critical gaps in existing AI risk management frameworks, emphasizing the neglect of human factors and the absence of metrics for socially related or human threats. Drawing from insights provided by NIST AI RFM and ENISA, the research underscores the need for understanding the limitations of human-AI interaction and the development of ethical and social measurements. The paper explores various dimensions of trustworthiness, covering legislation, AI cyber threat intelligence, and characteristics of AI adversaries. It delves into technical threats and vulnerabilities, including data access, poisoning, and backdoors, highlighting the importance of collaboration between cybersecurity engineers, AI experts, and social-psychology-behavior-ethics professionals. Furthermore, the socio-psychological threats associated with AI integration into society are examined, addressing issues such as bias, misinformation, and privacy erosion. The manuscript proposes a comprehensive approach to AI trustworthiness, combining technical and social mitigation measures, standards, and ongoing research initiatives. Additionally, it introduces innovative defense strategies, such as cyber-social exercises, digital clones, and conversational agents, to enhance understanding of adversary profiles and fortify AI security. The paper concludes with a call for interdisciplinary collaboration, awareness campaigns, and continuous research efforts to create a robust and resilient AI ecosystem aligned with ethical standards and societal expectations.

Calcium signaling: Unveiling its role in disease control in plants

<p>Calcium signaling is a fundamental regulatory mechanism in plants, governing a myriad of physiological processes crucial for growth, development, and responses to environmental stimuli, including biotic stresses such as pathogen attack. Over the past decades, research into the intricate network of calcium signaling pathways has revealed its pivotal role in orchestrating plant defense mechanisms against a diverse array of pathogens. This review comprehensively examines the multifaceted roles of calcium ions in modulating plant immune responses, elucidating the molecular mechanisms underlying calcium-mediated signal transduction and its integration with other defense signaling pathways. We delve into the intricate crosstalk between calcium signaling and various hormonal pathways, reactive oxygen species (ROS) signaling, and secondary metabolite biosynthesis, highlighting the interconnectedness of these regulatory networks in shaping plant defense strategies. Furthermore, we explore the potential applications of calcium-based strategies for sustainable disease management in agriculture, including the use of calcium channel blockers, calcium chelators, and calcium-rich compounds as novel antimicrobial agents and priming agents for enhancing plant immunity. Challenges and future directions in the field are also discussed, aiming to advance our understanding of calcium signaling in plant-pathogen interactions and harness its potential for developing innovative approaches to combat plant diseases and ensure global food security. This review provides a comprehensive overview of the current state of knowledge regarding calcium signaling in plant disease control, offering valuable insights and perspectives for future research endeavors in this rapidly evolving field.<strong></strong></p>

Smart Defense: How Self-Learning AI Can Shield Bangladeshi Medical Records

The digitalization of healthcare records in Bangladesh presents both opportunities and challenges, particularly concerning the security and protection of sensitive patient information. As electronic health records (EHRs) become increasingly prevalent, the threat of cyberattacks targeting medical data escalates, necessitating innovative solutions to fortify the country's healthcare cybersecurity infrastructure. This paper investigates the efficacy of self-learning artificial intelligence (AI) systems in safeguarding Bangladeshi medical records against cyber threats. The traditional methods of securing medical records, such as firewalls and antivirus software, are proving inadequate against the evolving tactics of cybercriminals. Bangladesh faces unique challenges in this regard, including limited resources, lack of cybersecurity awareness among healthcare professionals, technological fragmentation, and an increasingly sophisticated threat landscape. To address these challenges, there is a growing imperative to explore novel approaches that can adapt and evolve in real-time to counter emerging cyber threats. Self-learning AI systems represent a promising frontier in healthcare cybersecurity. By leveraging advanced machine learning algorithms, these systems can analyze vast amounts of data to detect patterns indicative of cyber threats. Unlike static security measures, self-learning AI continuously learns from new information and adjust their defense strategies, accordingly, enabling them to stay ahead of evolving threats. Key functionalities of self-learning AI include anomaly detection, threat prediction, and adaptive defense mechanisms, all of which are essential for safeguarding medical records in Bangladesh's healthcare landscape. The implications of integrating self-learning AI into Bangladesh's healthcare cybersecurity framework are significant. Not only can these technologies enhance the detection and prevention of cyber threats, but they can also alleviate resource constraints and technical challenges faced by healthcare organizations. However, successful implementation requires comprehensive training, adherence to data privacy regulations, and ongoing monitoring to ensure the effectiveness and reliability of AI-driven security measures. The protection of medical records is paramount as Bangladesh continues its digital transformation in healthcare. Self-learning AI offers a dynamic and proactive approach to cybersecurity, empowering healthcare organizations to mitigate risks and preserve patient privacy in an increasingly digitized landscape. Embracing these innovative technologies is crucial for building a resilient healthcare ecosystem that prioritizes data security and patient trust.

Research on proactive defense and dynamic repair of complex networks considering cascading effects

Cascading effects can result in the nonlinear propagation of failures in complex networks, ultimately leading to network collapse. Research on the fault propagation principles, defense strategies, and repair strategies can help mitigate the effects of cascading failures. Especially, proactive defense and dynamic repair are flexible and effective methods to ensure network security. Most studies on the cascade of complex networks are based on the unprocessed initial information of the network. However, marginal nodes are a type of node that cloaks the initial information of the network. In this study, we rank the importance of nodes according to the intensity of network energy confusion after the removal of this node, clarify the meaning of marginal nodes and proposed two methods to screen marginal nodes. The results indicated that the proactive removal of marginal nodes can effectively reduce the effect of cascading failures without causing any negative disturbance to the energy flow of the network. In addition, network repair according to the proposed strategy can minimize the cascade effect in the repair process and improve repair efficiency.

Alterations in the Anatomy and Ultrastructure of Leaf Blade in Norway Maple (Acer platanoides L.) Growing on Mining Sludge: Prospects of Using This Tree Species for Phytoremediation

Alterations in leaf architecture can be used as an indicator of the substrate toxicity level as well as the potential of a given plant species in the phytoremediation of polluted areas, e.g., mining sludge. In this work, we demonstrated, for the first time, the nature and scale of alterations in leaf architecture at the tissue and cellular levels occurring in Norway maple growing on mining sludge originating from a copper mine in Lubin (Poland). The substrate differs from other mine wastes, e.g., calamine or serpentine soils, due to an extremely high level of arsenic (As). Alterations in leaf anatomy predominantly included the following: (1) a significant increase in upper epidermis thickness; (2) a significant decrease in palisade parenchyma width; (3) more compact leaf tissue organization; (4) the occurrence of two to three cell layers in palisade parenchyma in contrast to one in the control; (5) a significantly smaller size of cells building palisade parenchyma. At the cellular level, the alterations included mainly the occurrence of local cell wall thickenings—predominantly in the upper and lower epidermis—and the symptoms of accelerated leaf senescence. Nevertheless, many chloroplasts showed almost intact chloroplast ultrastructure. Modifications in leaf anatomy could be a symptom of alterations in morphogenesis but may also be related to plant adaptation to water deficit stress. The occurrence of local cell wall thickenings can be considered as a symptom of a defence strategy involved in the enlargement of apoplast volume for toxic elements (TE) sequestration and the alleviation of oxidative stress. Importantly, the ultrastructure of leaf cells was not markedly disturbed. The results suggested that Norway maple may have good phytoremediation potential. However, the general shape of the plant, the significantly smaller size of leaves, and accelerated senescence indicated the high toxicity of the mining sludge used in this experiment. Hence, the phytoremediation of such a substrate, specifically including use of Norway maple, should be preceded by some amendments—which are highly recommended.

Melatonin Mitigates Lead-Induced Oxidative Stress and Modifies Phospholipid Profile in Tobacco BY-2 Suspension Cells

Many studies have shown that melatonin (an indoleamine) is an important molecule in plant physiology. It is known that this indoleamine is crucial during plant stress responses, especially by counteracting secondary oxidative stress (efficient direct and indirect antioxidant) and switching on different defense plant strategies. In this report, we present exogenous melatonin’s potential to protect lipid profile modification and membrane integrity in Nicotiana tabacum L. line Bright Yellow 2 (BY-2) cell culture exposed to lead. There are some reports of the positive effect of melatonin on animal cell membranes; ours is the first to report changes in the lipid profile in plant cells. The experiments were performed in the following variants: LS: cells cultured on unmodified LS medium—control; (ii) MEL: BY-2 cells cultured on LS medium with melatonin added from the beginning of culture; (iii) Pb: BY-2 cells cultured on LS medium with Pb2+ added on the 4th day of culture; (iv) MEL+Pb: BY-2 cells cultured on LS medium with melatonin added from the start of culture and stressed with Pb2+ added on the 4th day of culture. Lipidomic analysis of BY-2 cells revealed the presence of 40 different phospholipids. Exposing cells to lead led to the overproduction of ROS, altered fatty acid composition and increased PLD activity and subsequently elevated the level of phosphatidic acid at the cost of dropping the phosphatidylcholine. In the presence of lead, double-bond index elevation, mainly by higher quantities of linoleic (C18:2) and linolenic (C18:3) acids in the log phase of growth, was observed. In contrast, cells exposed to heavy metal but primed with melatonin showed more similarities with the control. Surprisingly, the overproduction of ROS caused of lipid peroxidation only in the stationary phase of growth, although considerable changes in lipid profiles were observed in the log phase of growth—just 4 h after lead administration. Our results indicate that the pretreatment of BY-2 with exogenous melatonin protected tobacco cells against membrane dysfunctions caused by oxidative stress (lipid oxidation), but also findings on a molecular level suggest the possible role of this indoleamine in the safeguarding of the membrane lipid composition that limited lead-provoked cell death. The presented research indicates a new mechanism of the defense strategy of plant cells generated by melatonin.

Effects of polyethylene and biodegradable microplastics on the physiology and metabolic profiles of dandelion

Biodegradable plastics, such as poly(butylene adipate terephthalate) (PBAT) and polylactic acid (PLA), are potential alternatives to conventional polyethylene (PE), both of which are associated with the production of microplastics (MPs). However, the toxicity of these compounds on medicinal plants and their differential effects on plant morphophysiology remain unclear. This study supplemented soils with MPs sized at 200 μm at a rate of 1% w/w and incubated them for 50 days to investigate the impact of MPs on the growth and metabolites of dandelion (Taraxacum mongolicum Hand.-Mazz.). The results demonstrated that the investigated MPs decreased the growth of dandelion seedlings, induced oxidative stress, and altered the activity of antioxidant enzymes (superoxide dismutase, peroxidase, and catalase). Based on the comprehensive toxicity assessment results, the ecological toxicity was in the following order: PE MPs > PBAT MPs > PLA MPs. Metabolomics analyses revealed metabolic reprogramming in dandelion plants, leading to the enrichment of numerous differentially accumulated metabolites (DAMs) in the leaves. These pathways include carbohydrate metabolism, energy metabolism, and biosynthesis of secondary metabolites, suggesting that dandelions respond to MP stress by enhancing the activity of sugar, organic acid, and amino acid metabolic pathways. In addition, phenolic acids and flavonoids are critical for maintaining the balance in the antioxidant defense system. Our results provide substantial insights into the toxicity of biodegradable MPs to plants and shed light on plant defense and adaptation strategies. Further assessment of the safety of biodegradable MPs in terrestrial ecosystems is essential to provide guidance for environmentally friendly management.

Functional traits of predators and decomposer prey determine context dependency in trophic control over ecosystems.

Research Highlight: Piccoli, G. C. d. O., Antiqueira, P. A. P., Srivastava, D. S., & Romero, G. Q. (2024). Trophic cascades within and across ecosystems: The role of anti-predatory defences, predator type and detritus quality. Journal of Animal Ecology, 00, 1-14. https://doi.org/10.1111/1365-2656.14063. Ecosystem functioning is controlled by the interplay between bottom-up supply of limiting nutrients and top-down animal feedback effects. However, the degree of animal versus nutrient control is context-dependent. A key challenge lies in characterizing this context dependency which is hypothesized to depend on differences in animal functional traits. Reporting on an important experiment, Piccoli etal. (2014) evaluate how interactions among functionally different predators and decomposer prey create context dependency in top-down control of a model system-tropical bromeliad tank ecosystems. Bromeliad plants hold water in their tanks supporting microcosm ecosystems containing terrestrial and aquatic insect larvae and arachnids. The ecosystems are supported by nutrients in plant litter that rains down from forest canopies into the tanks. Nutrients are released after litter is decomposed by a functionally diverse community of larval insect decomposers that differ in feeding mode and antipredator defence strategy. This decomposer community is preyed upon by an exclusively narrowly ranging aquatic insect larval predator and widely ranging spider predator that crosses between the aquatic and surrounding terrestrial ecosystems. Experimental manipulation of the animal community to test for the degree of control by predators mediated by the functionally diverse prey community included four treatments: (i) a control with the detritivores composing different function groups but without predators, (ii) the cross-ecosystem spider predator added, (iii) the purely aquatic damselfly larvae predator added and (iv) both predator types added to capture their interacting effect on ecosystem function (decomposition, nutrient release, and plant growth). Notably, the study resolved the causal pathways and strengths of direct and indirect control using structural equation modelling. These findings reveal how context dependency arises due to different capacities of the predators alone and together to overcome prey defences and control their abundances, with attendant cascading effects that diminished as well as enhanced decomposition and nutrient release to support bromeliad plant production. The study reveals that predators have a decided, albeit qualitatively and quantitatively different, hand in shaping the degree of bottom-up control through feedback effect on the release of limiting nutrients. This ground-breaking study provides a way forward in understanding the mechanisms determining context dependency in the control over ecosystem functioning.

Sequential fusion‐based defense strategy against sophisticated Byzantine attacks in cognitive IoT networks

Sequential fusion‐based defense strategy against sophisticated Byzantine attacks in cognitive <scp>IoT</scp> networks

Understanding desiccation tolerance and sex-specific responses in Bryum argenteum: insights from phenological phases and physiological analyses.

Desiccation tolerance (DT) is crucial for survival in arid environments, where organisms develop strategies in reproduction, maintenance, and defense to cope with water scarcity. Therefore, investigating the relationship between reproduction and DT is essential to understand the ecology and adaptive strategies of species. This study explores the connection between the development of male and female gametangia in the moss Bryum argenteum and the decrease in DT during the progression of phenological phases in gametangia and protonema. Samples collected from a dry tropical forest in Brazil were cultivated, cloned, and subjected to desiccation. Subsequently, the physiological parameters of shoots and protonemata were analysed. Shoot and protonema regeneration were monitored for 28 days after the physiological analyses. Both phases were subjected to control and desiccation treatments. Significant effects of desiccation and sex on the physiological parameters and regeneration capacity of shoots and protonemata were found. Male shoots generally exhibited lower values in Fv/Fm, and ϕPSII, while females demonstrated higher values and better recovery after desiccation. Protonemata also showed variation in Fv/Fm over time and sex, with no significant differences in ϕPSII between them. Desiccated male shoots had higher mortality rates and produced fewer new shoots. Regarding the females, the regeneration patterns varied between the desiccation-exposed groups and the control, with decreased shoot production, and some protonemata growing into filaments without forming shoots. These findings improve our understanding of bryophytes ecological responses to desiccation stress and provide insights into their adaptive strategies in challenging environments, such as the possible rarity of males in dioicous mosses populations.

Machine Learning in Cybersecurity : Applications, Challenges and Future Directions

Machine learning (ML) is transforming cybersecurity by enabling advanced detection, prevention and response mechanisms. This paper provides a comprehensive review of ML's role in cybersecurity, examining both theoretical frameworks and practical implementations. It outlines the emerging threats targeting ML models, such as adversarial attacks, data poisoning and model inversion attacks and discusses state-of-the-art defense strategies, including adversarial training, robust architectures and differential privacy. Additionally, the paper explores various ML applications in cybersecurity from intrusion detection to malware classification, highlighting their impact on enhancing security measures. An anomaly inference algorithm is proposed for the early detection of cyber-intrusions at the substations. Cybersecurity has become a vital research area. The paper concludes with a discussion on the key research directions and best practices for creating secure and resilient ML systems in a data-driven world. This paper delves into how Machine Learning (ML) revolutionizes cybersecurity, empowering advanced detection, prevention, and response mechanisms. It offers a thorough exploration of ML's pivotal role in cybersecurity, encompassing theoretical frameworks and practical applications. It addresses emerging threats like adversarial attacks and data poisoning, alongside cutting-edge defense strategies such as adversarial training and robust architectures.

Nucleic Acid Sensing by STING Induces an IFN-like Antiviral Response in a Marine Invertebrate.

The cytosolic detection of pathogen-derived nucleic acids has evolved as an essential strategy for host innate immune defense in mammals. One crucial component in this process is the stimulator of IFN genes (STING), which acts as a vital signaling adaptor, connecting the cytosolic detection of DNA by cyclic GMP-AMP (cGAMP) synthase (cGAS) to the downstream type I IFN signaling pathway. However, this process remains elusive in invertebrates. In this study, we present evidence demonstrating that STING, an ortholog found in a marine invertebrate (shrimp) called Litopenaeus vannamei, can directly detect DNA and initiate an IFN-like antiviral response. Unlike its homologs in other eukaryotic organisms, which exclusively function as sensors for cyclic dinucleotides, shrimp STING has the ability to bind to both double-stranded DNA and cyclic dinucleotides, including 2'3'-cGAMP. In vivo, shrimp STING can directly sense DNA nucleic acids from an infected virus, accelerate IFN regulatory factor dimerization and nuclear translocation, induce the expression of an IFN functional analog protein (Vago4), and finally establish an antiviral state. Taken together, our findings unveil a novel double-stranded DNA-STING-IKKε-IRF-Vago antiviral axis in an arthropod, providing valuable insights into the functional origins of DNA-sensing pathways in evolution.

Ethical Implications of Environmental Policies and Practices

Purpose: The aim of this study was to investigate the ethical implications of environmental policies and practices. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to the ethical implications of environmental policies and practices. Preliminary empirical review revealed that environmental decision-making is complex, involving trade-offs between competing values. It emphasized the importance of incorporating principles of justice and equity into governance processes, recognizing the disproportionate impact of environmental degradation on marginalized communities. The study identified gaps and shortcomings in current policies, highlighting the need for enhanced accountability and inclusivity. It advocated for a holistic and interdisciplinary approach to environmental governance, involving collaboration across diverse stakeholders to develop more effective and morally defensible strategies for addressing environmental challenges. Unique Contribution to Theory, Practice and Policy: The Environmental Justice theory, Ethical Decision- Making theory and Sustainability theory may be used to anchor future studies on the ethical implications of environmental policies and practices. The study made several recommendations, contributing to theory, practice, and policy. It recommended integrating ethical frameworks into policy development, strengthening community engagement, promoting environmental justice and equity, enhancing transparency and accountability, implementing ethical education and training, and fostering international cooperation. These recommendations aimed to ensure that environmental policies reflected ethical considerations, empowered communities, addressed systemic inequalities, promoted democratic governance, enhanced ethical awareness, and facilitated collaborative solutions to global environmental challenges. Keywords: Ethical Implications, Environmental Policies, Sustainability, Environmental Justice, Equity, Community Engagement, Transparency, Accountability, Policy Development, Participatory Governance, Democratic Deliberation, Environmental Inequalities, Ethical Frameworks, Education And Training, International Cooperation, Solidarity, Stakeholders, Decision-Making Processes, Global Environmental Challenges

Terpenes as Potential Anti-Alzheimer’s Disease Agents

Alzheimer’s disease (AD), a slowly progressive neurodegenerative disorder, is the main cause of dementia worldwide. However, currently, the approved drugs to combat AD are effective only in treating its symptoms. In fact, an efficacious treatment for this complex and multifactorial disorder remains to be discovered, demanding the urgent development of new therapeutic approaches for the disease, such as the use of bioactive secondary metabolites (SMs) from natural sources. Sessile organisms, like plants, are unable to escape from adverse environmental conditions and must therefore create their own defense. Their main defense strategy is chemical defense that includes the production of an enormously diverse array of bioactive SMs, such as terpenes and their derivatives. This largest and most diverse group of plant SMs also provide the treatment of several diseases due to their broad-spectrum bioactivities, for example, anticancer, antioxidant, and anti-inflammatory properties. Thus, the evaluation of the neuroprotective potential of terpenes is imperative. It is known that the major AD clinical indications (CIs) are extracellular senile plaques of amyloid-β (Aβ) protein, intracellular hyperphosphorylated tau (τ) neurofibrillary tangles (NFTs), uncommon neuroinflammatory response, oxidative stress, and synaptic and neuronal dysfunction. Therefore, terpenes that may decrease these CIs might be used for AD treatment. Surely, terpenes targeting more than one AD pathogenic mechanism, multi-target drug ligands (MTDLs), have the potential to become a leading AD treatment. Thus, this review analyzes, for each CI, the scaffolds of the selected terpenes leading to the highest activity.

Light-speed, contemporary war, and Australia’s national defence strategic review

AbstractIn our hyperconnected contemporary world, military and civilian digital and cyber technologies rely upon uncontested and uncongested access to frequencies in the electromagnetic spectrum (EMS). This reliance enables light-speed signalic connectivity, interconnectivity, operability, and interoperability of the systems and devices that perpetuate twenty-first century modes of information, remote, hybrid, and digital warfare. Informed by cultural theorist Paul Virilio’s commentaries on speed, light-speed, and war, this article examines speed as an inflection that insidiously underpins the Australian Government’s 2023 National Defence: Defence Strategy Review (DSR) (public version). This is not an exhaustive study of light-speed or the DSR. Rather, this article aims to show how speed and light-speed, used as investigatory lenses, can provide critical insights into relationships between contemporary technology, and war. To this end, the article refers to US and UK defence and government electromagnetic spectrum policy statements, interpolating them into motivations for AUKUS, and the DSR’s positioning.

Distributionally Robust Coordinated Defense Strategy for Time-Sensitive Networking Enabled Cyber–Physical Power System

Distributionally Robust Coordinated Defense Strategy for Time-Sensitive Networking Enabled Cyber–Physical Power System