The increasing use of Internet of Things (IoT) devices has led to a rise in Distributed Denial of Service (DDoS) and Denial of Service (DoS) attacks on these networks. These attacks can have severe consequences, resulting in the unavailability of critical services and financial losses. In this paper, we propose an Intrusion Detection System (IDS) based on a Conditional Tabular Generative Adversarial Network (CTGAN) for detecting DDoS and DoS attacks on IoT networks. Our CGAN-based IDS utilizes a generator network to produce synthetic traffic that mimics legitimate traffic patterns, while the discriminator network learns to differentiate between legitimate and malicious traffic. The syntactic tabular data generated by CTGAN is employed to train multiple shallow machine-learning and deep-learning classifiers, enhancing their detection model performance. The proposed approach is evaluated using the Bot-IoT dataset, measuring detection accuracy, precision, recall, and F1 measure. Our experimental results demonstrate the accurate detection of DDoS and DoS attacks on IoT networks using the proposed approach. Furthermore, the results highlight the significant contribution of CTGAN in improving the performance of detection models in machine learning and deep learning classifiers. The Internet of Things (IoT) has become more widespread in recent years, with applications ranging from smart homes and wearable technology to factory automation. However, due to their increased use, IoT devices are increasingly vulnerable to Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks and other novel cyber threats. DDoS/DoS attacks on IoT networks aim to make the services and resources of the targeted network or devices inaccessible to legitimate users. This is accomplished by inundating the network or devices with an enormous volume of malicious traffic, depleting their available resources such as bandwidth, processing power, or memory. Traditional intrusion detection systems (IDS) have difficulty retaining and identifying these threats because of the amount and diversity of IoT data .With more and more devices connecting to networks and inadequate protections in place, DDoS attacks on IoT infrastructure have become more common and destructive. The purpose of these kinds of attacks is to employ many infected machines to flood a network or server with traffic, rendering it unavailable to its legitimate users. IoT networks are vulnerable to DDoS attacks because of their limited processing capacity, lack of security measures, and the possibility of broad infiltration, which might jeopardize critical data and cause disruptions in services like healthcare and transportation. Developing IDS systems that can identify DDoS attacks is vital for ensuring the availability and security of IoT networks .According to a report by Kaspersky , the numAnother report by NETSCOUT  revealedThese statistics indicate that IoT devices are becoming an increasingly popular target for DDoS and DoS attacks, and organizations must take proactive measures to protect their networks and devices from these attacks.To detect DDoS/DoS attacks in IoT networks, traditional IDS utilize approaches such as statistical anomaly detection, signature-based detection, and machine learning-based detection. However, the detection of DDoS/DoS attacks in IoT networks poses a significant challenge for traditional intrusion detection systems (IDS). These systems typically employ techniques such as statistical anomaly detection, signature-based detection, and machine learning-based detection. However, the unique characteristics of IoT networks, including a vast number of interconnected devices, varied communication protocols, and heterogeneous traffic patterns, contribute to the complexity of detecting malicious activities. Traditional IDS methods, which were primarily designed for conventional networks, struggle to cope with the dynamic and unpredictable nature of IoT environments .This study highlights the critical need to investigate new ways to improve IDS detection capabilities for IoT networks. Researchers can make strides in developing more reliable and accurate techniques for identifying and mitigating DDoS/DoS assaults by addressing the challenges posed by the enormous quantity and variety of IoT traffic. Safeguarding IoT networks and devices through enhanced detection methods is essential for maintaining the trustworthiness and security of many IoT applications and services.To aid in the development of efficient DDoS/DoS detection approaches for IoT networks, researchers can push the limits of existing research, explore new detection algorithms, utilize advanced machine learning algorithms such as CTGAN, or adapt existing methods to suit the distinctive features of IoT traffic. Ultimately, these advancements will strengthen the security and resilience of IoT systems, making them more resistant to and better equipped to handle the increasing dangers of DDoS/DoS attacks.An approach that leverages CTGAN for accurate identification of DDoS and DoS attacks in IoT networks. The proposed approach utilizes the power of generative adversarial networks to synthesize realistic network traffic data, enabling more effective detection and classification of malicious activities.Conducting an extensive evaluation of the classification performance of various shallow machine learning (ML) and deep learning (DL) models. By leveraging the synthetic dataset generated by CTGAN, this research pioneers a comprehensive assessment of different ML and DL algorithms, providing insights into their strengths and weaknesses in detecting DDoS/DoS attacks in IoT networks. This evaluation contributes to the understanding of the most effective models for accurate attack classification.Furthermore, this evaluation serves as a valuable resource for future researchers in the same field, aiding them in identifying the optimal combination of machine ML or DL techniques in conjunction with CTGAN.Addressing the issue of extreme class imbalance in the Bot-IoT dataset through the utilization of synthetic data generation. The research proposes the use of CTGAN to generate synthetic data that represents the minority class of DDoS and DoS attacks. By augmenting the dataset with synthetic samples, this approach helps alleviate the challenges associated with imbalanced training data, enhancing the performance and robustness of detection models.The key contributions of this research work can be summarized as follows:By presenting these contributions, the research contributes to the development of more effective and reliable intrusion detection systems tailored to the unique characteristics of IoT environments.The remaining sections of the paper are organized as follows: This section provides an overview of DDoS and DoS attacks on IoT networks and briefly explains the Conditional Tabular Generative Adversarial Network (CTGAN).IoT networks are highly susceptible to cyber-attacks, with DDoS and DoS attacks being two of the most prevalent types. These attacks can cause significant disruptions to critical services, resulting in financial loss and damage to the reputation of affected organizations. The vulnerability of IoT devices is a significant contributing factor to these attacks, as they often lack security measures and computing resources. DDoS attacks involve a coordinated effort by multiple devices to flood a network or server with traffic, rendering it inaccessible to legitimate users. This is often accomplished by utilizing compromised devices, such as those infected with malware or bots. In contrast, DoS attacks involve a single device or a small group of devices overwhelming the network with traffic, causing it to become unavailable. The key differentiator between DDoS and DoS attacks is the number of devices employed to carry out the attack .There are several ways in which DDoS and DoS attacks against IoT devices are distinct from DDoS and DoS attacks on conventional networks. One key distinction between conventional computing devices and IoT devices is the latter’s generally lower processing power and memory. This makes them more susceptible to resource depletion attacks, in which the target is subjected to such a high volume of requests or traffic that it becomes incapacitated. In addition, it might be more difficult to identify and counteract attacks in real-time when dealing with IoT devices since they may be dispersed across a large geographical region and linked through a variety of network protocols and communication channels. The necessity for strong security measures to defend against DDoS and DoS attacks will only increase as IoT devices continue to spread and become more ingrained in essential infrastructure and day-to-day life ,8.Furthermore, the low-cost and easy-to-use nature of IoT devices, coupled with a lack of emphasis on security during their design, makes them an attractive target for cybercriminals to exploit their vulnerabilities. Many IoT devices have default login credentials that are either easily guessable or readily accessible, enabling attackers to gain unauthorized entry to these devices and exploit them for malicious activities, including the initiation of DDoS and DoS attacks.Generally, DDoS/DoS attacks in IoT networks pose unique challenges, with certain types of attacks being more prevalent. One example is IoT Botnet-based DDoS attacks . These aCTGAN  is a speCTGAN trains both the generator and discriminator networks simultaneously to produce their respective outcomes. The generator network takes white noise as input and generates synthetic data samples. On the other hand, the discriminator network receives both real and synthetic data as input to differentiate between the two. As the training progresses, the generator network aims to produce synthetic data that increasingly resembles the actual data, while the discriminator network strives to improve its ability to distinguish between real and synthetic instances.A key feature of CTGAN is its capability to generate conditioned synthetic data, enabling the generation of data under specific circumstances, such as predefined column values or the absence of certain patterns. This conditional data generation feature proves particularly valuable when adhering to regulatory or corporate guidelines during data synthesis.CTGAN effectively generates synthetic tabular data while preserving the statistical characteristics of the original data and accommodating conditional data production. Consequently, it finds applications in various domains, including data privacy and security, data augmentation, and data sharing .In this study, CTGAN was chosen over traditional GAN models  due to iVarious studies have proposed different techniques for detecting DoS and DDoS attacks in IoT networks using machine learning algorithms. For instance, Cviti et al. developed a method using a boosting technique of logistic model trees to detect DDoS traffic for various classes of IoT devices. Their results achieved accuracy rates ranging from 99.92% to 99.9% for the four device classes considered . Roopak Hodo et al. proposed a multilayer perceptron (MLP)-based intrusion detection system (IDS) to detect DoS attacks in IoT networks, which accurately distinguished between various DDoS and DoS attacks . MohammeUsing the CIDDS-001, UNSWNB15, and NSL-KDD datasets, Verma et al. demonstrated a number of shallow ML algorithms, such as random forest (RF), Adaboost (AB), gradient boosting machine (GBM), extremely randomized trees (ERT), classification and regression tree (CART), and multilayer perceptron (MLP) neural network, with RF achieving the best results with an accuracy rate of 94% .Chopra et al. compared several rudimentary ML algorithms, including Naive Bayes, J48, RF, and ZeroR classifiers, for detecting and classifying DDoS attacks in IoT using the Bot-IoT dataset. However, the authors suggest that these models may not perform well when applied to large-scale IoT datasets due to the poor accuracy performance of naive ML algorithms in such contexts .In Churcher et al.’s work , the BotAlimi et al.  introducAlmaraz-Rivera et al.  conducteSusilo and Sari (2020)  proposedIn their study, Kumar et al. introduced a fog computing-based distributed Intrusion Detection System (IDS) for detecting Distributed Denial of Service (DDoS) attacks on mining pools in IoT networks enabled by blockchain technology. The proposed model is evaluated using Random Forests and an optimized gradient tree boosting system on distributed fog nodes, and the evaluation is conducted using the BoT-IoT dataset. The results demonstrate that XGBoost performs better in binary attack detection, while the Random Forest outperforms in multi-attack detection. Furthermore, the Random Forest exhibits faster training and testing times on distributed fog nodes compared to XGBoost .For example, Verma et al. achieved the highest accuracy of 94% using random forest on the CIDDS-001, UNSW-NB15, and NSL-KDD datasets, while Mohammed et al. observed varying results when comparing naive Bayes, Bayes Net, and ZeroR on the UNSW-NB15 dataset. It’s essential to use datasets that reflect the characteristics of IoT networks, such as Bot-IoT and UNSW-NB15, to evaluate the effectiveness of existing and future approaches instead of using non-IoT datasets like CICIDS-2019, CISIDS-2017, and NSL-KDD.Moreover, This section describes an approach to detect TCP and UDP DDoS and DoS attacks on IoT networks using CTGAN to produce adversarial samples that are highly representative of actual IoT network traffic. To further improve the accuracy of DDoS and DoS detection in IoT networks, these samples are used to train several shallow ML and DL classifiers. CTGAN can replicate data with near-perfect statistical accuracy since it is trained using real-world samples. Data cleansing: This procedure involves identifying data that is lacking, incorrect, erroneous, or irrelevant so it can be updated or removed. For example, if a feature has no available value in the dataset, it is assigned a value of 0.Categorical data transformation: This step entails converting data from one format to another. For example, the characteristics of the String/Object datatype are substituted by a unique number. The Categorical data in the dataset used are: proto, saddr, sport, daddr, dport, category, subcategory. Feature scaling: This procedure maps the information onto the unit sphere or converts it to the interval  . erval 0,   , TGAN 3, and CTGThis stage is the core stage of the proposed approach which aims to generate synthetic data and perturb it to create adversarial samples is a promising approach for improving the robustness of ML and DL learning models for detecting DoS and DDoS detection in IoT networks.X is the real data, and Z is a noise vector. The generator network inputs X and Z and produces a batch of synthetic data samples as outputs. The generator network is trained to minimize the distance between the distribution of the synthetic data and the real data distribution.CTGAN generator network can be represented as a function P is a function that adds a small amount of noise or changes to Y. If the model misclassifies To create an adversarial example using CTGAN, a synthetic data sample The workflow of the proposed approach can be summarized as follows:Synthetic Traffic Generation: The CTGAN-based IDS employs a generator network to produce synthetic traffic that closely mimics legitimate traffic patterns. This synthetic traffic generation step enables the IDS to effectively distinguish between legitimate and malicious traffic, facilitating accurate detection and mitigation of DoS and DDoS attacks.Discriminator Network: The discriminator network, a crucial component within the CTGAN framework, learns to differentiate between legitimate and malicious traffic. By analyzing the characteristics and patterns of the traffic, the discriminator enhances the IDS’s ability to detect and classify attacks. This helps in effectively identifying and mitigating both DoS and DDoS attacks on IoT networks.Enhanced Detection Models: The syntactic tabular data generated by CTGAN is utilized to train multiple shallow machine-learning and deep-learning classifiers. The training process involves using the synthetic data to enhance the performance of the detection models. This results in improved accuracy and effectiveness in detecting and mitigating DoS and DDoS attacks.The proposed approach leverages the capabilities of CTGAN to generate synthetic traffic, train detection models, and enhance the overall performance of the IDS. By combining synthetic traffic generation, discrimination analysis, and improved detection models, the approach aims to enhance the security of IoT networks against DoS and DDoS attacks.During this phase, the focus is on training multiple shallow ML and DL models to create detection models capable of accurately detecting DDoS and DoS attacks. The adversarial examples generated in the previous stage, denoted as It is worth noting that this approach is not limited to TCP and UDP DDoS and DoS attacks. It can be applied to various datasets, enabling the identification of different types of attacks across different domains or fields. The flexibility of this approach makes it adaptable and applicable to diverse scenarios where attack detection is required.The CTGAN-based IDS employs a generator network to produce synthetic traffic that closely mimics legitimate traffic patterns. This synthetic traffic generation step enables the IDS to effectively distinguish between legitimate and malicious traffic, facilitating accurate detection and mitigation of DoS and DDoS attacks.The discriminator network, a crucial component within the CTGAN framework, learns to differentiate between legitimate and malicious traffic. By analyzing the characteristics and patterns of the traffic, the discriminator enhances the IDS’s ability to detect and classify attacks. This helps in effectively identifying and mitigating both DoS and DDoS attacks on IoT networks.The syntactic tabular data generated by CTGAN is utilized to train multiple shallow machine-learning and deep-learning classifiers. The training process involves using the synthetic data to enhance the performance of the detection models. This results in improved accuracy and effectiveness in detecting and mitigating DoS and DDoS attacks.By training multiple models using the adversarial examples, the aim is to enhance the detection capabilities and robustness of the models against various attack scenarios. Once deployed, these trained models can effectively analyze network traffic data and accurately identify instances of DDoS and DoS attacks, contributing to the security and stability of IoT networks. The workflow of the proposed approach in detecting DDoS/DOS attacks in IoT network can be summarized as follows:This section describes the experimental setup, the data, the evaluation metrics, and the results of the proposed approach.The BoT-IoT dataset  is emploThe number of records in the training and testing sets for each attack category in the BoT-IoT traffic is presented in The analysis of The pre-processed filtered dataset presented in It is worth mentioning that during the transformation steps, the categorical data is converted to numerical values, as shown in Described below are metrics for measuring the efficacy of the proposed approach. Numerous research studies, including ,36, use The objective of this section is to evaluate the efficiency of the syntactic tabular dataset, denoted as ion (LR) , Naive Bion (LR) , Random ion (LR) , Decisioion (LR) , and Supion (LR) . Additioion (LR) , Recurreion (LR) , and Gation (LR) . These cbased on .Based on In summary, the results indicate that the CTGAN approach has a positive impact on the performance of both shallow ML and DL classifiers in most cases. Specifically, the NB, RNN, and GRU models demonstrate notable improvements in detection accuracy, precision, recall, and F1 measure when using the syntactic tabular dataset generated by CTGAN.Overall, the findings of this study reveal the significant impact of leveraging CTGAN  on the performance of intrusion detection models in IoT networks. By using CTGAN to generate synthetic attack instances and augment the training dataset, the LSTM, RNN, and GRU models have exhibited remarkable improvements in accurately detecting DoS and DDoS attacks. This highlights the importance of utilizing advanced data generation techniques to enhance the effectiveness of intrusion detection systems.In contrast, the random forest classifier and decision tree classifier models have demonstrated comparatively weaker performance metrics in this study. These models, when trained on the original dataset without the benefits of CTGAN-generated synthetic data, may lack the ability to effectively capture the intricacies and complexities of modern IoT-based attacks. Therefore, caution is advised when considering the use of these models for intrusion detection in IoT networks.To ensure robust and reliable intrusion detection, it is recommended to prioritize the utilization of LSTM, RNN, and GRU models, which have shown superior performance in accurately identifying DoS and DDoS attacks. These models, when combined with advanced data generation techniques like CTGAN, have the potential to significantly enhance the security of IoT networks against evolving attack vectors. Furthermore, a comparative analysis was conducted between our proposed approach and the work proposed in . In ordeThe results tabulated in These findings highlight the effectiveness of the proposed approach in enhancing the performance of intrusion detection models. By leveraging CTGAN to generate synthetic data, the CNN and MLP models achieve higher mean accuracy, indicating their improved capability to accurately detect intrusion attempts in IoT networks. This improvement can be attributed to the ability of CTGAN to generate realistic synthetic data that captures the complexities of modern attack patterns, enabling the models to learn more effectively and make better predictions.Overall, these results provide strong evidence supporting the efficacy of the proposed approach in improving the performance of intrusion detection systems. The use of CTGAN-generated synthetic data offers a promising avenue for enhancing the accuracy and reliability of detection models, ultimately contributing to the security and resilience of IoT networks against evolving cyber threats.Our study proposes a CGAN-based IDS for detecting DDoS attacks on IoT networks. The proposed IDS overcomes the limitations of existing IDS systems by employing a generator network to create synthetic traffic that imitates legitimate traffic patterns, and a discriminator network to detect anomalies. We evaluated the proposed approach using the BoT-IoT dataset in two scenarios.In the first scenario, we evaluated multiple machines and deep learning classifiers using the original BoT-IoT dataset. This allowed us to establish a baseline performance for the detection models. In the second scenario, we evaluated the same machines and classifiers using the syntactic tabular dataset generated by CTGAN. This enabled us to assess the impact of using synthetic data on the performance of the detection models.Our experimental results indicate that the syntactic tabular dataset significantly enhanced the detection model performance of multiple machines and deep learning classifiers. The use of synthetic data generated by CTGAN improved the models’ ability to accurately detect DDoS attacks on IoT networks. These findings demonstrate the effectiveness of our proposed CGAN-based IDS in improving the performance of intrusion detection systems.In future work, we plan to investigate the effectiveness of our proposed CGAN-based IDS for detecting other types of attacks on IoT networks. By expanding the scope of our research, we aim to develop a comprehensive IDS solution that can effectively detect various types of intrusions in IoT environments. Additionally, we also aim to explore the potential of utilizing reinforcement learning techniques to further enhance the performance of the proposed Intrusion Detection System (IDS). By leveraging the capabilities of reinforcement learning, we anticipate achieving even higher accuracy and adaptability in detecting and mitigating attacks targeting IoT devices. Furthermore, we plan to evaluate the performance of the proposed approach using various benchmarking datasets to ensure its effectiveness and robustness across different scenarios.


Plant invasions can have long-lasting impacts on soil nitrification, which plays a critical role in nutrient cycling and plant growth. This review examines the legacy effects of plant invasion on soil nitrification, focusing on the underlying mechanisms, context dependence, and implications for management. We synthesize literature on the positive, negative and neutral legacy effects of plant invasion on soil nitrification, highlighting the complexity of these effects and the need for further research to fully understand them. Positive legacy effects include increased soil microbial biomass or activity, potentially enhancing nutrient availability for plants. However, negative legacy effects, like reduced nitrifier abundance, can result in decreased soil nitrification rates and nutrient availability. In some cases, changes to nitrification during active invasion appear transitory after the removal of invasive plants, indicating neutral short-term legacies. We discuss the context dependence of legacy effects considering factors, including location, specific invasive plant species, and other environmental conditions. Furthermore, we discuss the implications of these legacy effects for management and restoration strategies, such as the removal or control of invasive plants, and potential approaches for restoring ecosystems with legacy effects on soil nitrification. Finally, we highlight future research directions, including further investigation into the mechanisms and context dependence of legacy effects, and the role of plant–microbe interactions. Overall, this review provides insights into the legacy effects of plant invasion on soil nitrification and their implications for ecosystems. Alien species invading ecosystems are a major driver of global environmental change and the second greatest threat to biodiversity, following habitat loss . These iLegacy effects refer to the long-lasting impacts of a disturbance or event on the abiotic and biotic properties of an ecosystem . In the Invasive plant species may affect soil nitrogen cycling by altering the nitrogen inputs and outputs, soil pH, and microbial community structure. For example, invasive species can increase soil nitrogen availability and alter soil nitrogen forms by increasing nitrate leaching and decreasing ammonium adsorption ,17,18. IOverall, the concept of legacy effects is important in understanding the long-term impacts of disturbances on soil properties and ecosystem function. More research is needed to elucidate the specific mechanisms underlying legacy effects and their potential influence on soil nitrification following plant invasion.4+) into nitrate (NO3−), which is an essential plant nutrient [Pinus strobus was found to accumulate higher nitrogen and carbon with a longer nitrogen residence time, retaining nitrogen in its tissues for longer periods compared to native grasses and oak trees. This allowed P. strobus to accumulate more nitrogen from the soil over time without an equal return through decomposition [The legacy effects of plant invasion on soil nitrification allude to the long-lasting influence of invasive plants on the nitrification process in the soil. Nitrification is a microbial-mediated process that drives the conversion of ammonium  that suppress the activity of nitrifying bacteria like Nitrosomonas spp. in the soil [+-ATPase activity [+-ATPase [The belowground inputs, for example root litter and exudates, can significantly impact the soil microbiota by acting as a source of carbon for their growth and influencing their activity involved in the process of nitrification . Severalectively ,57. Soilectively ,59,60. Hthe soil ,62,63. Tthe soil ,62. By sthe soil . It has activity ,66,67. O+-ATPase  and may +-ATPase . This lo+-ATPase . It has +-ATPase .The changes in the soil microbial communities and nutrient processes induced by the invasive plants can produce lasting effects on nitrification, even after their removal from the soil, and can affect the growth and functions of the succeeding plant species inhabiting the invaded area for an extended period . The soiIt is noteworthy that the legacies of plant invasion on soil nitrification are contingent upon the particular invasive plant species, the attributes of the invaded ecosystem, and the interplay between the invasive flora and the indigenous soil microbial communities ,73. FurtInvasive species can have positive effects on soil nitrification that leads to higher microbial biomass and activity in the soil. These effects have a significant contribution towards soil nutrient availability and ultimately the plant growth. For example, nitrogen-fixing invasive species can enhance the availability of nutrients and have a beneficial impact on the growth of recolonizing plant species, particularly those that grow rapidly and can take advantage of the increased nutrient availability .Bromus tectorum L. (cheatgrass), compared to Artemisia tridentata Nutt. (sagebrush), perennial grass stands of the same age, enhances the availability of nitrogen in the soil. Cheatgrass dominance leads to higher rates of both net and gross nitrogen mineralization, as well as net nitrification. The study demonstrates that cheatgrass soils, whether disturbed or intact, exhibited increased net rates of nitrogen cycling during field and laboratory incubations. Furthermore, cheatgrass soils contained higher concentrations of soil organic carbon and nitrogen compared to sagebrush-grass soils, suggesting that cheatgrass has beneficial long-term effects on soil nitrification. A study also demonstrates that invasive species like Microstegium vimineum enhance nitrification rates in the invaded soil, and it proposes that monocultures of invasions are sustained by the presence of high soil nitrate concentrations. These positive plant–soil interactions, facilitated by microbial nutrient transformations and nutrient availability, may be an underrecognized mechanism that supports the persistence of plant invasions [Geddes et al.  found thnvasions .In summary, positive legacy effects of plant invasion on soil nitrification can arise from changes in soil microbial communities, nutrient availability, and nutrient cycling dynamics caused by invasive plants. These effects include the establishment of novel plant–soil feedbacks, increased nutrient release from decomposers, and persistent microbial soil legacies.Aegilops triuncialis (goatgrass) and Elymus caput-medusae (Medusahead), decreased soil NO3− and potential nitrification as compared to native plant communities in California. This indicates a negative impact on soil nitrification caused by invasive plants, and these changes in soil conditions may contribute to the persistence of invasive plant populations, potentially hindering restoration efforts. A study by Suding et al. [Bromus tectorum) when introduced into sagebrush ecosystems exhibited lower soil nitrogen availability and rates of net nitrification compared to uninvaded plots, and these impacts persisted for at least three years following the removal of the invasive grasses.Invasive plants can have negative legacies on the process of soil nitrification by altering the soil nitrifying community and impacting the soil nutrients . These lg et al.  revealedg et al.  reportedInvasive plants have been reported to have negative legacy effects on soil microbial communities and nitrogen cycling, which may survive even after the treatment of herbicide . The stuIt is important to note that the specific negative effects of invasive plants on soil nitrification can vary depending on the particular invasive species, ecosystem characteristics, and management practices. These effects can have significant implications for ecosystem functioning, nutrient cycling, and plant community dynamics.Invasive plants can have neural effects on soil nitrification rates, nitrifier abundance, and community composition over the long-term following invasion and removal, indicating a lack of persistent positive or negative legacy impacts on the nitrification process in the soils of the corresponding ecosystems. Studies on the neutral legacy effects of plant invasions on soil nitrification have reported mixed results, with some demonstrating transient effects but others reporting persistent alterations even after invader removal. Overall, research on the processes and context-dependence of neutral nitrification legacies is limited in comparison to negative or positive impacts .Morella faya 5–7 years after its removal from the invaded site [M. faya. The study concluded that the positive legacy effects of this invasive N-fixer on nitrification were reversible once it was removed from the ecosystem, indicating that the removal of M. faya allowed recovery of the nitrifier community and nitrification function to a non-invaded state. Several recent studies have documented a lack of legacy effects on nitrifier abundance or nitrification rates in historically invaded soils compared to uninvaded soils [A study in Hawaii investigated the legacy effects of the nitrogen-fixing invasive tree ded site . It was ed soils . Howevered soils . They pred soils . This sued soils . ElucidaIn these cases, changes to the nitrifier community and nitrification processes induced during active invasion appeared transitory once the invasive species was removed from the ecosystem. Within a few years, aspects of the nitrification function like nitrate production rates and nitrifier community structure appeared resilient and recovered to conditions similar to never-invaded soils. The timescale of these studies may not have been long enough to fully evaluate legacy effects, which could take decades to disappear in some ecosystems. However, the evidence does suggest neutral or negligible legacy impacts on nitrification for some invasive plant species over this shorter time span. Further investigation across diverse ecosystems is needed to discern when neutral legacies will emerge and their implications for restoration.The legacy effects of invading plants on soil nitrification might vary greatly depending on the location of the invasion, the particular species of invasive plant that was involved, and any other relevant environmental conditions . The preIt is possible for the legacy effects on soil nitrification to be affected by the location where the invasive plant species first establish themselves. The qualities of the soil, the meteorological circumstances, as well as the existing plant and microbial communities, might differ from one area to another, which can lead to changes in the processes of soil nitrification. For instance, variations in soil pH, the amount of organic matter present, and the availability of nutrients can all have an effect on the activity and composition of nitrifying microorganisms, which in turn can have an effect on the rates of nitrification in the soil ,88. In aHow the legacies of plant invasion impact on soil nitrification are also determined by the specific invasive plants species involved. Various invasive plant species exhibit a wide variety of characteristics and interactions with the microbial communities in the soil, all of which have the potential to affect nitrification in the soil. Invasive plants have the potential to either release allelochemicals or affect the environment of the rhizosphere, both of which have the potential of changing the composition and activity of the soil microbiota that are engaged in the nitrification process. Depending on the particular plant–microbe interactions, these shifts can either boost or lower the soil’s nitrification rates ,88,89. FThe residual impacts of invasive plants on soil nitrification can also be influenced by other environmental factors, such as the availability of nutrients and the disturbances in the ecosystem. The growth and competitive advantage of invasive plants can be affected by the availability of nutrients, particularly nitrogen deposition, which has the potential to change the effect that these plants have on nitrification in the soil ,91. The Having provided the above information, there is still a need to explore the combined influence of location, invasive plant species, and other environmental factors on soil nitrification. However, considering the general understanding of the topic and the factors involved, it is reasonable to assume that these factors interact and collectively shape the legacy effects of invasive plants on soil nitrification. Understanding these effects can provide insights into the long-term implications of plant invasions on soil ecosystems and help improve predictions and management strategies for invasive species.Invasive plant species have the potential to have a substantial impact on soil nitrification, impacting nitrogen cycling, ecosystem processes, and native plant communities. Managing invasive plant species based on their effects on soil nitrification necessitates a complete approach that takes into account the invasive species’ particular traits, the local ecology, and available resources.Phragmites australis while encouraging the growth of native species such as Melaleuca ericifolia [The elimination and management of invasive plant species is one method for dealing with the problem. This may require repeated burning, grazing, pruning, mowing, or uprooting the plants, either by hand or with a machine, and could be incorporated when reviewing soil nitrogen management options . When inicifolia . Furthericifolia ,103. ThiTopsoil removal rapidly and dramatically lowers nitrogen availability by extracting the surface soil layers where nitrogen accumulates . HoweverEcosystems that have been subjected to legacy effects on soil nitrification may necessitate the implementation of specific restoration strategies to address the altered nitrogen dynamics. Introducing beneficial microorganisms to the soil can aid in the restoration of nitrification processes. Certain microbial communities play a crucial role in nitrification, and their absence or alteration due to disturbances can disrupt nitrogen cycling. By inoculating the soil with nitrifying microorganisms, the restoration of nitrification can be promoted, helping to reestablish the natural nutrient cycling processes . ApplyinIt is important to note that the specific management and restoration strategies may vary depending on the characteristics of the invasive species, the ecosystem, and local conditions. Monitoring and adaptive management approaches are essential to assess the effectiveness of these strategies and make adjustments as necessary.The legacy effects of plant invasion on soil nitrification are a complex phenomenon that requires further research to fully understand the underlying mechanisms and context dependence. Non-native plants have the potential to significantly modify soil microbial communities . These aThere is still a lack of consensus regarding the relative effects of aboveground and belowground plant inputs on nutrient cycling and microbial communities ,108,109.In conclusion, the impact of plant invasions on soil nitrification is a complex and multifaceted phenomenon. The invasion of alien plant species can have both short-term and long-term effects on soil microbial community composition, nutrient cycling processes, and soil carbon and nitrogen content. Understanding the legacy of plant invasions on soil nitrification is crucial for effective management and restoration strategies, as it provides insights into the mechanisms driving ecosystem changes and the potential implications for ecosystem functioning and services. Further research is needed to explore the long-term consequences of plant invasions on soil nitrification and develop comprehensive management approaches that consider the complex interactions between invasive plants, soil microbial communities, and nutrient dynamics.


One of Ukraine's leading scientists and innovators, our dear friend Professor Tatiana V. Serebrovskaya, passed away on April 5, 2021, from consequences of COVID-19. .Ironically, the aim of Tatiana's last article, which she coauthored with her daughter Zoya, was to contribute to a better mechanistic understanding of hypoxia and the cytokine storm in COVID-19 . Tatiana was awarded the medal for Honesty in Science by the International Association of Scientists, and was founding member and copresident of the Polish-Ukrainian Respiratory Working Group.Among many other trailblazing discoveries, Tatiana and her colleagues demonstrated the beneficial effects of targeted ambient hypoxic exposures on the cardiorespiratory system and exercise performance in older people (Shatilo et al, Tatiana's pioneering research made her immortal. She will be a beacon for generations of future researchers working on the application of hypoxia-related interventions and her legacy will certainly bear abundant fruit for human health. We sincerely hope that the global scientific community's commitment enables Ukrainian scientists to continue their work in safety until the barbaric war comes to a hopefully very rapid end and allows Ukrainian science to thrive.


Cardiovascular disease and osteoporotic fractures (OF) are the main diseases affecting the health of middle-aged and elderly people. With the gradual increase of population aging in China and even the world, the incidence of the two and the prevalence of high-risk groups are also showing a continuous upward trend. The relationship between the two, especially the impact of cardiovascular disease on the risk and prognosis of OF, has attracted more and more attention. Therefore, it is of great significance to fully understand the pathogenesis of cardiovascular and cerebrovascular diseases and the resulting osteoporosis and to provide targeted interventions to prevent the occurrence of diseases and fractures. This article reviews the relationship between one of the Cardiovascular disease—stroke and related therapeutic drugs and the risk of OF, and the role of oxidative stress in its pathophysiological mechanism by reviewing relevant domestic and foreign literature in recent years, in order to gain a more comprehensive understanding of the association between stroke and OF, and then provide a basis and reference for screening high-risk groups of fractures and reducing the burden on the health system caused by the disease. In addiNumerous scholars have conducted research on this disease before, covering the etiology, pathogenesis and treatment of post-stroke osteoporosis, and all of them have achieved good results. This paper systematically summarizes the etiology, pathogenesis and treatment methods of post-stroke osteoporosis by summarizing previous studies, and innovatively introduces the role of oxidative stress in the whole process of the disease, which provides new ideas for the related research and treatment of the disease in the future.Osteoporosis is a known consequence of stroke. The pattern of bone loss observed in patients with stroke is different from that usually encountered with postmenopausal osteoporosis, which is limited to the paralyzed side and more obvious in the upper limbs. There are many reasons for osteoporosis in stroke patients, including limited exercise and reduced load due to paralysis, insufficient nutrition intake due to eating disorders, intake of various drugs and reduction of vitamin D due to insufficient sunshine , As showPeople at high risk of stroke are already at risk for osteoporosis and fracture . HoweverThere are many potential mechanisms that lead to bone loss after stroke, and restricted movement is one of the important factors involved in this process. BMD studies of the upper and lower extremities consistently show more bone loss on the restricted side than on the unrestricted side. The exact mechanism of the reduction in BMD on the hemiplegic side after stroke is not fully understood, but the link between reduced mobility and bone loss has long been known. In a pivotal study published by Schneider and McDonald in 1984, serum and urinary calcium rose rapidly in 90 healthy young men on bed rest for 5–36 weeks, plateaued for several weeks at week 6, and then declined to a plateau above the dynamic baseline. This happened even when volunteers were given vitamin D supplements throughout the study . This exVitamin D is one of the fat-soluble vitamins thought to have anti-rickets activity. Vitamin D is not only abundant in nature, but is also synthesized in the skin with the help of the sun’s UV-B rays . VitaminOsteoporosis is closely linked to hyperlipidemia and its incidence increases with age. This may be due to an imbalance between bone cells and fat cells in the bone marrow. Research shows that among stroke patients admitted to rehabilitation, the proportion of patients with abnormal bone density is higher than that of those with normal bone density. The levels of total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), apolipoprotein A and B in the abnormal group were higher than those in the normal group, while the bone mineral density of L1 ∼ L4, femoral neck and proximal femur were lower than those in the normal group, suggesting that the level of lipid metabolism in stroke patients may be the influencing factor of their bone , Other sProton pump inhibitors (PPIs) are powerful acid-suppressing drugs that are currently widely used to treat drug-related upper gastrointestinal disorders. Current research suggests a link between the use of PPIs and the risk of osteoporosis and bone fractures –33. HowePost-stroke depression is very common, with a reported prevalence of approximately 31% . Which iin vivo  is an independent risk factor for acute cerebral infarction, and that changes in serum Hcy levels are closely related to changes in cerebral vascular endothelial function and the occurrence of cerebral infarction . Hcy is In addition to the oxidative stress mechanism, Hcy may also play a neurotoxic role through microglia-mediated neuroinflammatory injury: treatment with Hcy can activate microglia, significantly increase the volume of cerebral infarction and induce cell injury. One possible mechanism by which Hcy enhances the inflammatory response of microglia is that JAK 2/STAT 3, a key immune signaling pathway, is normally expressed in the brain. It also plays an important role in regulating microglial activation and inflammatory response. The study by Chen S et al. tested whether the JAK 2 inhibitor AG 490 could affect the expression of pSTAT3, the microglia-specific markers Iba-1 and OX-42, and the pro-inflammatory mediators TNF-α and IL-6 induced by Hcy. The results showed that activation of STAT 3 and secretion of IL-6 in microglia were significantly upregulated in Hcy-treated ischemic brain tissue and this effect was reversed by AG 490. The experimental results indicate that the increased expression of STAT 3 after homocysteine treatment may be involved in microglial activation and neuroinflammatory injury in rats with middle cerebral artery ischemia-reperfusion.For bone, there is limited evidence that homocysteine has a direct effect on bone, including bone density. The potential mechanism of the association between high homocysteine levels and fracture risk may involve the interference of homocysteine with collagen cross-linking and the specific interference of homocysteine with collagen cross-linking and fibril formation in solution. As collagen cross-linking is very important for the stability and strength of the collagen network, interference with its formation may alter the bone matrix, which may increase bone fragility .2+ and Fe3+ mediate lipid peroxidation through hydroperoxide to form lipid free radicals, leading to DNA denaturation and further aggravating cell damage. (3) The accumulation of ROS can cause a large increase in macrophages, damage to the blood-brain barrier, hemorrhagic transformation and cerebral edema after stroke.When blood flow is restored after cerebral ischemia, brain tissue can be damaged and deteriorate. Many mechanisms are involved in this process, such as inflammatory activation, oxidative stress, ferroptosis, etc. Among these, dysregulation of iron metabolism is closely linked to the occurrence of ischemia-reperfusion injury : after rOxidative and nitrosative stress are characterized by an imbalance between oxidative and antioxidant systems, leading to an increase in reactive oxygen species (ROS) and reactive nitrogen species (RNS). The vascular wall is also equipped with oxidative systems such as xanthine oxidase. , mitocho2–  is expressed in central and peripheral nerve cells and blood vessel walls, which contributes to vasodilation and is considered anti-atherosclerotic. In contrast, inducible NOS (iNOS), which is induced by inflammation, oxidative stress and sepsis, is atherosclerotic, possibly due to the formation of peroxynitrite (ONOO–), thereby increasing nitrite stress  is considered to be an important source of RONS in the vascular wall, and there are many types of NOx, of which NOx 4 is the most abundant at the vascular level, but it is controversial whether it has the functions of promoting atherosclerosis and preventing atherosclerosis at the same time: NOx 4 releases more hydrogen peroxide than O2– , so amou2– . The Ince stress .After a stroke, dyskinesia reduces the activity of the limbs and bone tissue loses the stimulus of mechanical stress. When the mechanical stress received by the bone is reduced, the activity of osteoclasts is increased, which leads to the easy absorption of bone tissue and the obvious reduction of bone mineral density in the body, which eventually leads to different degrees of osteoporosis. Increasing daily activity can reduce the incidence of osteoporosis, while immobilization after bed rest can cause hypercalcemia and hypercalciuria in patients with moderate and severe stroke, especially in the elderly, and accelerate bone absorption to cause osteoporosis.Mitochondria, the powerhouses of cells, maximize the use of intracellular oxygen while generating energy and ROS. Low levels of ROS can maintain bone homeostasis and balance between osteoclasts and osteoblasts . AbnormaThe maintenance of bone mass depends not only on the resorptive function of osteoclasts and the function of osteoblasts, but also on the difference in the production and apoptosis rates of osteoblasts and osteoclasts. Among them, osteoblasts play an important role in maintaining bone homeostasis, regulating cytoplasmic matrix mineralization, controlling bone remodeling and osteoclast differentiation . OsteoblThe management of osteoporosis post-stroke warrants meticulous attention. Osteoporosis significantly heightens fracture risk, and post-stroke patients typically require prolonged bed rest or wheelchair use, which may expedite bone loss. Hence, timely and effective treatment measures for stroke patients with osteoporosis become crucial. At present, the management of osteoporosis post-stroke encompasses drug therapy, calcium and vitamin D supplementation, exercise, and rehabilitation. The medication regimen typically involves estrogen drugs, bisphosphonates, and biodegradable, osteocalcin-related peptides which have shown efficacy in reducing bone loss rate and fracture incidence. Calcium and vitamin D supplementation can improve bone mineral density, while exercise and rehabilitation can lower the risk of fracture by enhancing muscle strength and balance. Additionally, the writing must adhere to grammatical correctness, avoid biased language, and maintain clear, concise, and objective language throughout the text. However, it must be noted that subjective evaluations need to be excluded unless clearly marked as such. The treatment plan needs to be tailored to the individual conditions of each patient, and therefore, an individualized treatment plan should be created accordingly. Abbreviations of technical terms must always be explained when they are first used. In brief, the comprehensive consideration of several factors is crucial in addressing osteoporosis treatment after stroke. An individualized treatment plan is useful in mitigating fracture risk and enhancing patients’ quality of life. However, a study of stroke patients revealed inadequate assessment and treatment of osteoporosis and fracture risk factors. However, a study of stroke patients revealed inadequate assessment and treatment of osteoporosis and fracture risk factors. However, a study of stroke patients revealed inadequate assessment and treatment of osteoporosis and fracture risk factors. The percentage of stroke patients receiving osteoporosis medication or supplements is relatively low. It is essential to enhance comprehension, prevention, and management of bone loss in this vulnerable population .Non-pharmacological treatment remains the cornerstone for maintaining bone health prior to the onset of osteoporosis or fragility fractures. Physical exercise is particularly advantageous in averting falls and fractures among the wider population –72. GaitAnother non-pharmacological approach involves increasing the duration of exposure to sunlight. Stroke patients frequently face social isolation, which may restrict their exposure to sunlight. That is one of the reasons behind the vitamin D deficiency in stroke patients. The scientific comprehension of the significance of vitamin D extends beyond its role in the absorption of calcium and phosphorus and the maintenance of healthy teeth and bones. Especially amongst the elderly, vitamin D assumes a crucial physiological function in numerous non-skeletal processes, such as regulating the normal thyroid function, blood clotting, providing muscle strength and flexibility, enhancing the production of endogenous antibiotics, preventing the onset of autoimmune and allergic diseases, combating infectious diseases, and discouraging the growth of tumors –81. AccoRegarding the effect of statins on osteoporosis after stroke, Lin, SM and colleagues  conducteBisphosphonates are frequently used as therapeutic drugs for osteoporosis following stroke, and previous studies have reported their beneficial effects on stroke patients , BisphosFracture is now recognized as a risk factor in stroke, and preventing the development of hemiplegic osteoporosis should be a priority in managing stroke patients. Post-stroke osteoporosis has not been fully recognized and treated compared to postmenopausal osteoporosis. Oxidative stress theory is a crucial theory in the process of stroke and osteoporosis. It is important to investigate the mechanism of oxidative stress in the cardiovascular, cerebrovascular, and bone metabolism systems to elucidate the causes of stroke and osteoporosis. As its research deepens, our comprehension of the physiological and pathological mechanisms and treatment measures increases. Controlling the serum homocysteine level, avoiding or relieving ischemia-reperfusion of cerebrovascular or limb blood vessels, and managing atherosclerosis caused by nitration stress (rather than oxidative stress) through medication are all important for the treatment of stroke and the subsequent osteoporosis. In the future, treatment can focus on two areas: (1) Blocking signal pathways associated with oxidative stress during cerebral atherosclerosis or mitigating ischemia-reperfusion injury; and (2) Addressing the impact of lipid metabolism disorder or oxidative stress on osteoclast activity post-stroke. It is expected that advancements in molecular biology, basic medicine, and clinical medicine technology will enhance the comprehension of the pathogenesis of stroke-induced osteoporosis, and facilitate the development of more effective drugs and technologies to treat and prevent it. Osteoporosis after stroke is a prevalent and incapacitating aftermath that impairs the quality of life of stroke victims. The precise mechanism underlying the occurrence of stroke and osteoporosis is yet to be fully understood, hampering progress in developing effective intervention strategies. Nonetheless, recent research suggests that the incidence of fracture can be effectively reduced by mitigating the risk of falls through activities such as drug therapy, physical exercise and targeted fall-prevention measures. Further research is required to establish the most efficient intervention methods for osteoporosis in stroke survivors and to determine the means of resolving complications simultaneously.This study provides an overview of the pathogenesis and treatment options for stroke and post-stroke osteoporosis. It also explores the role of oxidative stress theory in the disease, presenting information on its etiology, symptoms, treatment methods, and suggestions for preventive measures. The study examines treatment outcomes and side effects, and offers guidance to doctors in formulating more appropriate treatment plans. Furthermore, it presents novel ideas for developing new drugs or treatment methods in the future, with potentially significant impacts on the prevention and treatment of post-stroke osteoporosis patients.JL: Visualization, Writing – original draft, Writing – review and editing. JS: Conceptualization, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – review and editing. LS: Data curation, Investigation, Software, Writing – review and editing.


The need to overcome the limitations of LP Ho:YAG laser lithotripsy has prompted major technological advancements in the field of laser technology for endoscopic lithotripsy. The introduction of high-power (HP) Ho:YAG laser generators up to 150 W, the implementation of pulse modulation for the Ho:YAG laser beam, and the marketing of both thulium fiber laser (TFL) and pulsated Tm:YAG laser generators have dramatically increased the number of available options. However, these novelties have not always been supported by an adequate level of scientific evidence, especially in real-life clinical scenarios. Several pre-clinical studies have shown the potential advantages of these new laser technologies for endoscopic lithotripsy, but there is an absence of consistent in vivo evidence.Flexible ureteroscopy (fURS) with laser lithotripsy is currently the gold standard surgical treatment for ureteral and kidney stones with a maximum diameter of 2 cm . For nea3) [As opposed to LP Ho:YAG laser generators, HP variants may achieve high frequencies, reaching up to 120 Hz, thus leading to potentially faster stone ablation. This has important implications in terms of the choice of parameters, lithotripsy technique, and perioperative outcomes . A recen3) .TM  made its entrance into the endourological armamentarium in 2017. Several other similar options, such as Virtual BasketTM , Advanced ModeTM , and Stabilization ModeTM , were later developed. The underlying idea is to split a single laser pulse into two sub-pulses with different peak power. The first sub-pulse generates a vapor bubble in the fluid medium, enabling a second sub-pulse to reach the target without dissipating its energy in the medium, thereby maximizing the effect on the target and reducing stone retropulsion [In addition to the implementation of HP lithotripsy, does pulse modulation play a significant role as well? Despite the possibility of configuring the laser for both short and long pulse modalities for stone fragmentation and dusting lithotripsy technique , the Mosopulsion . Moreoveopulsion . Similaropulsion . There iopulsion .The latest innovation in the field of endoscopic laser lithotripsy is represented by TFL, which is rapidly spreading worldwide as an excellent alternative to the Ho:YAG laser. This laser technology largely differs from Ho:YAG laser in several physical and technical aspects . BrieflyOverall, despite the improvement in available technologies for endoscopic laser lithotripsy and the broader field of endourology , there iFurthermore, when treating stone disease, it is important to remember that there is much more that we can do beyond properly using the available technology. For instance, adequate knowledge of the biology of lithogenesis and the possible measures aimed at improving the management of patients with stone disease significantly improves the clinical outcomes of patients .In conclusion, a surge of technological innovations and improvements has recently occurred in the field of endoscopic laser lithotripsy. However, clinical evidence regarding the benefits in terms of surgical outcomes in real-life scenarios is still lacking, as most of the available results originate from pre-clinical studies. Beyond the importance of technology, we emphasize the importance of patient metabolic assessment in the pursuit of obtaining and maintaining a stone-free status.


The inconsistency of existing findings on the relationship between institutional investors’ shareholdings and the level of corporate Environmental, Social and Governance (ESG) disclosure may lie in the insufficient consideration of the heterogeneity of institutional investors and investee firms. In this paper, from the perspective of institutional investor heterogeneity, we use a two-way fixed effects model to examine the impact of institutional investors on corporate ESG disclosure and the possible mechanism of this impact using a sample of Chinese A-share-listed firms from 2012 to 2020. We show that institutional investor shareholding can improve the level of corporate ESG information disclosure by enhancing auditor supervision and analyst attention to these external supervision. In terms of institutional investor heterogeneity, it is found that independent institutional investors and stable institutional investors play a stronger role in promoting the level of ESG information disclosure. Moreover, the positive net effect of the institutional investors on improving the level of ESG information disclosure is more pronounced in non-heavily polluting industries and state-owned enterprises. This paper enriches the impact of institutional investors’ shareholding on corporate ESG disclosure from a heterogeneity perspective. The influence of institutional investors on corporate Environmental, Social and Governance (ESG) information disclosure is a hot topic for scholars. However, existing studies have not reached a consistent conclusion on whether institutional investor shareholding can improve the ESG information disclosure level of invested enterprises. One view is that the shareholding of institutional investors can improve the level of ESG information disclosure of invested enterprises –3. In thThe possible reason for this result lies in insufficient consideration of the heterogeneity of institutional investors and investee enterprises . DiffereThis paper adopts Chinese A-share listed companies from 2012 to 2020 as a sample and examines the impact of institutional investors on corporate ESG information disclosure and its possible mechanisms. The main contributions of this paper are as follows: First, from the perspective of institutional investor heterogeneity and corporate heterogeneity, the impact of institutional investor shareholding on corporate ESG information disclosure is enriched. This, to a certain extent, explains the inconsistence of existing research conclusions on the relationship between institutional investors and corporate ESG information disclosure [The rest of this paper is organized, as follows. Section 2 outlines the theoretical analysis and research hypotheses. Section 3 describes the research method, while the empirical results and analysis are presented in Section 4. Section 5 presents further research and Section 6 offers the conclusions of this paper.The existing literature infers that institutional investors have capital, professional and informational advantages and can influence the invested enterprises. On the one hand, institutional investors have more professional knowledge, stronger research teams and stronger information collection and analysis capabilities , which cThere are two different views of institutional investors on the influence of invested enterprises, one is value investment view and the other is speculation view .The value investment theory holds that institutional investors pay attention to the long-term development of the invested enterprise, which represents a responsible investment behaviour . InstituAnother view, however, is that institutional investors are short-term investors who are short-sighted and speculative and hope to exit quickly and gain value-added income. They focus on their reputation and interests and do not consider the long-term development of the invested enterprise, which is contrary to the original intention of the value investment concept. ESG is an indicator that integrates environmental responsibility, social responsibility and corporate governance. It emphasizes that enterprises should pay attention to non-financial behaviours such as environmental protection, green production, corporate social responsibility, employee rights and interests protection, as well as corporate governance when pursuing maximum benefits. However, none of these goals can be achieved overnight. Enterprise ESG behavior is a long-term process. From a long-term perspective, the pursuit of ESG is conducive to the sustainable development of enterprises and increases enterprise value, which is consistent with the long-term development philosophy of institutional investors. In the short term, ESG behaviour will consume the capital, workforce and material resources of the enterprise and may even have little effect, which may not be consistent with the profit-seeking nature of institutional investors. Institutional investors with short-sighted and speculative ideas will reduce the level of ESG information disclosure. Institutional investors are not active stakeholders , and theBased on the above theoretical analysis, this paper proposes the following competitive assumptions:H1a: The ESG information disclosure quality of enterprises held by institutional investors is better.H1b: The ESG information disclosure quality of enterprises held by institutional investors is worse.Due to differences in investment preference and investment philosophy, different types of institutional investors will have different degrees of supervision and incentive on the management, so their influence on the ESG information disclosure of the invested enterprises is also different. Therefore, it is necessary to distinguish the types of institutional investors and study their impact on ESG information disclosure of investee enterprises from the perspective of institutional investor heterogeneity . IndepenH2a: Compared with non-independent institutional investors, the ESG information disclosure quality of enterprises held by independent institutional investors is better.H2b: Compared with transactional institutional investors, the ESG information disclosure quality of enterprises held by stable institutional investors is better.Considering that in the capital market with Chinese characteristics, listed enterprises have two property rights, state-owned and non-state-owned, and the difference in property rights makes enterprises differ greatly in corporate governance, information disclosure and other aspects . The busIn terms of corporate pollution attributes, due to the implementation of China’s "two-carbon" policy, enterprises in heavily polluting industries have received more social attention, especially facing greater regulatory pressure from the government, which requires more disclosure of ESG information . TherefoBased on the above analysis, hypothesis H3a and H3b are proposed in this paper:H3a: Compared with non-state-owned enterprises, state-owned enterprises held by institutional investors have better ESG information disclosure quality.H2b: Compared with enterprises in heavy polluting industries, the ESG information disclosure quality of enterprises in non-heavy polluting industries held by institutional investors is better.This paper took Chinese A-share listed enterprises from 2012 to 2020 as the initial research samples and selected them according to the following criteria: (1) ST and *ST enterprises were excluded; (2) Listed enterprises in the financial industry were excluded; (3) Samples with missing or incomplete data were removed. This resulted in 10,749 observations. ESG data derived from the overall ESG scores and rates of listed enterprises on Hexun website. The data relating to enterprise finance was derived from China Stock Market and Accounting Research database (CSMAR). To avoid the influence of outliers, continuous variables were curtailed at 1% and 99% levels.The dependent variable is the quality of enterprise ESG information disclosure, specifically divided into enterprise ESG score (ESG-S) and enterprise ESG rating (ESG-R). The quality of enterprise ESG information disclosure is measured by Hexun’s ESG evaluation system for listed enterprises. Hexun’s evaluation of the ESG of listed enterprises is based on 97 aspects of environmental responsibility, social responsibility and corporate governance, according to which an overall score and rating is derived. The total score of the ESG is 100, and the higher the score, the better the enterprise’s ESG performance. The ESG rating is divided into five grades as follows: A is the highest grade with a value of 5, and E is the lowest grade with a value of 1.The independent variable is the shareholding ratio of institutional investors (INS).The control variables include enterprise size (Size), enterprise age (Age), asset-liability ratio (Lev), growth opportunity (Growth), enterprise performance (ROA), price-earnings ratio (PE), the shareholding ratio of the largest shareholder (Ratio) and the independence of board of directors (Indepe). The specific definitions of all variables are shown in To verify the hypotheses, we set the following regression model. We use the two-way fixed effect model for regression and perform a robust treatment on the standard error of the regression results to correct the heteroscedasticity problem.iμ refers to the fixed effect of individual enterprises and tη refers to the annual fixed effect.In the formula, i represents the enterprise, t represents the year, ESG represents the enterprise’s quality of ESG information disclosure, and ESG-S and ESG-R of the enterprise in the ith year are used, respectively. Further, INS represents institutional investors’ shareholding, and Controls represent control variables, First, replace the dependent variables. The measurement method for the quality of ESG information disclosure of dependent variable enterprises is replaced by the Chinese Securities Index ESG rating for inspection. The highest value of AAA is 9, and the lowest value of C is 1. The results in Second, replace the independent variables. According to the median of institutional investors’ shareholding ratio, the dummy variable is constructed by grouping, and the regression is conducted again. The results in First, consider the lag effects. Considering that institutional investors’ shareholding influence on the level of enterprise ESG information disclosure may have a lag effect, the dependent variable is regressed again after a lag period. The results in Second, consider the impact of environmental protection policies. The Environmental Protection Tax Law of the People’s Republic of China was introduced on December 25, 2016, changing environmental protection fees into taxes. This policy has significantly improved the level of enterprise ESG related information disclosure . TherefoFirst, we consider the tool variable method. Referring to the paper of Liang , we use Second, we adopt Heckman’s two-stage method. Some unobservable characteristics of enterprises may affect the selection of enterprises by institutional investors and the level of ESG information disclosure of enterprises simultaneously, leading to selective bias in the sample. This paper uses Heckman’s two-stage method to modify the possible endogeneity. In the first stage, a probit model that affects institutional investors’ shareholding is established to calculate the inverse Mills ratio (IMR). In the selection model, INS is the explained variable. If it exceeds the median, the value is 1; otherwise, it is 0. There are five independent variables. The first one is whether the company belongs to the HS300. The second one is the difference between the voting rights proportion and the cash flow rights proportion (Vcright), which is the proportion of control rights of listed enterprises owned by the actual controller minus the proportion of ownership held by them. The third one is information transparency (Trans), measured by the sum of the absolute values of the enterprise’s manipulative accruals in the previous three years. The internal control level (Inter score) is measured by the natural logarithm of the enterprise’s internal control index plus 1. The last one is the geographic location (East). If the enterprise is located in the eastern province, the geographic location value takes 1; otherwise, it takes 0. In the second stage, the inverse Mills ratio is added to the original regression model as a control variable for regression. The results in Institutional investors have professional and informational advantages. Their stock selections can transmit a value signal, attract the attention of securities analysts and other external supervisors, improve the level of external supervision of enterprises , and thuAccording to the paper of Chen et al. , we diviMoreover, institutional investors are divided into stable and transactional institutional investors according to Yang et al. . First, Considering that in the capital market with Chinese characteristics, listed enterprises have two kinds of property rights, state-owned and non-state-owned, the difference in property rights makes enterprises differ greatly in corporate governance, information disclosure, etc. Institutional investors who enter state-owned enterprises (SOEs) as non-public shareholders may play a supervisory and governance role in the information disclosure of SOEs. This leads to a more obvious impact of institutional investors’ shareholding on the quality of ESG information disclosure of SOEs. This paper regresses the property right nature of the whole sample. The results are shown in Moreover, this paper divides Chinese listed enterprises into two groups according to whether they belong to heavy pollution industries and tests the difference in the impact of institutional investors’ shareholding on the quality of ESG information disclosure of these two types of enterprises. If the enterprise belongs to the mining, textile, clothing, fur, metallic and non-metallic, biological medicine, petrochemical plastic, paper and printing industry, water, electricity and gas, food and beverage industry, etc., it is defined as a heavily polluted enterprise; otherwise, it is defined as the non-heavily polluted enterprise. The regression results are shown in This paper uses the Chinese A-share listed enterprises from 2012 to 2020 as the sample to study the relationship between institutional investors and enterprises’ ESG information disclosure. It starts with the external factors that affect the ESG information disclosure of enterprises and studies the impact and mechanism of institutional investors’ shareholding on the quality of enterprise ESG information disclosure. The empirical results show that institutional investor shareholding can significantly improve the level of ESG information disclosure of Chinese listed companies. The analysis of the impact mechanism shows that institutional investor shareholding improves the level of ESG information disclosure by upgrading auditor supervision and analysts’ attention to this external supervision. Heterogeneity analysis shows that independent institutional investors are more pronounced in improving the quality of ESG information disclosure. The higher the stability of institutional investor shareholding, the better the quality of ESG information disclosure. Institutional investor shareholding plays a strong role in improving the quality of ESG information disclosure of SOEs and enterprises in non-heavily polluting industries. The original conclusions are still robust after replacing variable measurements, considering the lag effect and environmental policy impact, and using tool variables and Heckman’s two-stage method to eliminate endogenous problems.This paper enriches the impact of institutional investors’ shareholding on corporate ESG disclosure from a heterogeneity perspective. This explains, to some extent, the inconsistency of the findings of existing studies on the relationship between institutional investors and corporate ESG disclosure . In addiThis finding has important policy and academic implications. For investee companies, it is necessary to understand that different types of institutional investors may have different levels of incentives to supervise management due to differences in investment preferences and investment philosophies, etc., and therefore there are some differences in their impact on ESG disclosure of investee companies. Investee companies need to cooperate more with independent and stable institutional investors to improve the quality of ESG disclosure. For regulators, on the one hand, regulators should create conditions to encourage institutional investors to actively participate in corporate governance and supervision, and on the other hand, they also need to cultivate stable institutional investors, and give full play to their motivation and ability in enhancing the level of ESG disclosure of enterprises; in addition to this, in the mixed ownership reform of state-owned enterprises (SOEs), they can guide institutional investors to enter SOEs as non-public shareholders, and give full play to their role in SOEs’ ESG information disclosure. For researchers, the differences in heterogeneity of institutional investors need to be considered when studying the relationship between institutional investors and corporate ESG disclosure. This paper examines the impact of institutional investors on corporate ESG disclosure performance and draws relatively robust conclusions, but there are still some limitations, and future research can continue to expand in the following aspects. On the one hand, in addition to the external monitoring mechanisms of auditor supervision and analyst attention mentioned in this paper, subsequent research can continue to delve deeper into other relevant mechanisms of institutional investors affecting corporate ESG disclosure performance, such as the signing of betting agreements, if detailed information on investment covenants can be obtained. On the other hand, although the possible endogeneity problem is solved by applying the replacement variable measurement, considering the lagged effect and the impact of environmental policies as well as the use of instrumental variables and Heckman’s two-stage method after controlling for the financial characteristics of the firms, corporate governance and other characteristics. However, because of the lack of exogenous shock events, the interference of endogeneity problems cannot be completely ruled out, and the endogeneity problems can be better solved subsequently by finding more appropriate methods.S1 Dataset(XLSX)Click here for additional data file.


Our understanding of the process leading to hypertension is allowing us to adopt principles of therapy that may be more beneficial for patients.To review the physiology, vascular biology, and mechanisms of hypertension.Hypertension, particularly in high-risk patients, is a result of loss of balance and the absence of the ability to vasodilate normally. The interaction between the endothelial cell and the smooth muscle cell is very important in this process. The endothelium is a group of cells that produce compounds that are important in regulating vascular homeostasis by elaborating factors such as angiotensin II, nitric oxide (NO), endothelin, and prostaglandins. Specifically, NO is found in endothelial cells responsible for smooth muscle relaxation. Gaseous NO diffuses across the endothelial cell and into the underlying smooth muscle cell, where it stimulates the pathway of guanylate cyclase to produce vasorelaxation. Normal endothelium maintains vascular tone and blood viscosity, prevents abnormal blood clotting and bleeding, limits inflammation of the vasculature, and suppresses smooth muscle cell proliferation. Abnormal endothelium causes increased inflammation and hypertrophy of the smooth muscle cells, promotes thrombosis and vasoconstriction, and creates a situation ripe for establishment and rapid growth of atherosclerotic plaques. Endothelial dysfunction also predicts poor outcome in patients with non insulin-dependent diabetes mellitus and may worsen insulin resistance, increase vascular reactivity, and encourage macrovascular disease.Understanding endothelial vasculature will be imperative as researchers develop newer compounds that may enhance NO formation within the vasculature.


Exercise in the prevention, management of and rehabilitation from cardiovascular diseases” presents information on the cardiovascular effects of various forms of exercise through original and review articles. All these studies provide different insights into the therapeutic effects of exercise in individuals with CVD.Management of and Rehabilitation from cardiovascular diseases (CVD) in the recent decades is one of the greatest tasks for health professionals. The Research Topic “Marzuca-Nassr et al., showed that a 12-week hybrid exercise-based cardiac rehabilitation program  was capable of improving both functional capacity  and muscle strength (handgrip) in adults and older patients with coronary disease. New delivery strategies, like hybrid cardiac rehabilitation and tele-rehabilitation as well, could help to improve access and increase adherence to rehabilitation programs in patients with coronary artery disease, especially in the elderly.Although regular physical activity has been proven to reduce CVD associated morbidity and mortality, optimal exercise modality, in terms of type of exercise, duration, frequency, and intensity of it remains unclear. New training protocols were developed and tested in recent years. Alternatives to standard rehabilitation have been proposed. In this Research Topic, the original article developed by Ramis et al. investigated the effects of a single aerobic and resistance exercise sessions on ambuatory blood pressure monitoring (ABPM) in middle-aged subjects with hypertension, and found that PEH did occur in both exercise groups, although it was more pronounced after aerobic exercise. ABPM did not differ between both types of exercising and a control groups sessions for 24 h. This study gives support to the hypothesis that the accumulation of exercise sessions could amplify the beneficial effects of pharmacological treatment  and other studies would indicate that exercise can lower blood pressure, an effect more evident with the aerobic intervention.Physical exercise is a non-pharmacological strategy not only in patients with cardiac diseases but also in the management of arterial hypertension. To understand better the mechanisms of the blood pressure lowering effect of exercise, an expedient model has been that of studying blood pressure behaviour for a time after a single bout of different exercise modalities, the so-called post exercise hypothension (PEH). By using this approach, reatment . OverallHowever, the exact mechanisms of exercise benefits are not yet fully known. It would be of great interest to know how physical activity can affect CVD, as preventive and treatment tool.Tao et al. summarized the currently available information on the effects of different durations and intensities of aerobic exercise on vascular endothelial function in different populations, starting from the assumpion that the duration and the intensity of exercise are the key factors that affect the endothelial function, as assessed by flow-mediated dilation technique (FMD). The review included 20 RCT studies and the results indicated that moderate- and vigorous-intensity, but not low-intensity, aerobic exercise, improved FMD, an effect associated with the duration of the training program . In addition, the improvement was greater in patients with a worse basal FMD and of older age.It is assumed that benefits of exercise include effects on endothelial function, in addition to the effects on autonomic nervous system  and metaFurther studies are clearly warranted to understand the optimal exercise protocols and the underlying mechanisms.Han and Ju investigated the effects of an ancient martial art, the taekwondo, on measures of metabolic syndrome (MS), that included Body Mass Index (BMI), Systolic (BP) and Diastolic (DBP) Blood Pressure, Fasting Blood Glucose (FBG), Trygliceride (TG) and High Density Lipoproteins-Cholesterol (HDL-C)  reported that all MS indicators significantly improved with the taekwondo intervention, similarly to the more classic aerobic  . Han and aerobic , enduran aerobic  and resi aerobic .The authors ascribed these effects to the taekwondo training characteristics, which involve complicated movements that require the synchronization of numerous body parts, such as twisting blocks, flying kicks, and fast motions, not restricted to just one portion of the body, resembling most of all other exercise training modalities. The beneficial effects of taekwondo on the MS indicators were more accentuated in older woman population, exercising three times a week for at least 12 weeks at moderate to high intensity, similarly to the recommendations of the American Diabetes Associaton .However, given the specificity of taekwondo training and its mainly regional diffusion, these benefits, at present, cannot be generalized to the general population around the world.Overall, the research discussed in this Research Topic underscores the importance of exercise as a major component in preventing and managing CVD. It highlights the effectiveness of various exercise training strategies in improving many cardiovascular parameters and risk factors with the potential of preventing the development of CVD.


An 84-year-old woman with anemia and a 4-week history of discomfort on the right-side of the abdomen received treatment for hypertension, dyslipidemia, and osteoporosis. She had been treated with the traditional Chinese drug Kami-shoyo-san  for several years for neuropsychiatric symptoms secondary to menopause. Physical examination revealed a soft abdomen with no tenderness.A colonoscopy revealed bluish edematous mucosa, decreased blood vessel permeability, and multiple small ulcers with white slough extending from the cecum to the hepatic flexure  but wereBased on the typical combination of endoscopic and radiological findings, the patient was diagnosed with idiopathic mesenteric phlebosclerosis (IMP); herbal drug treatment was immediately discontinued, conservative treatment was initiated, and regular endoscopic and radiological observations were scheduled.Idiopathic mesenteric phlebosclerosis is a rare disease reported mostly in East Asian countries (including Japan). Herbal medicines containing geniposide  are one of the major causes of IMP.When considering IMP as a differential diagnosis, clinicians should recall typical findings on endoscopic and CT images. It is useful to assess the severity and extent of IMP, such as the involved bowel segment, to indicate conservative treatment outcomes and surgical needs.Most of the IMPs in the literature review were reported in Japan, China, and Korea, but two were reported in Canada and one each in Germany, the United States, and the United Kingdom; in addition, clinicians should be cautious about oral medications in travelers from Asia.


The number of publications on nanomedicine in oncology has been exponential over the last ten years, going from 640 publications in 2012 to 2487 publications in 2022, reflecting the growing interest and potential of these new technologies.Since observations made in the 1970s and 1980s regarding the preferential extravasation of nano-encapsulated drugs in tumors, the enhanced permeability and retention (EPR) effect  has beenTechnological progress of nanoparticles enabled the successful development of molecules such as mRNA/siRNA, whose therapeutic concept has emerged since the 1990s . Thus, tThis Special Issue exposes a wide range of applications of nanoparticles in cancer area, particularly for therapeutic applications where they exceed conventional therapies by their better pharmacological profile . InnovatThanks to improved molecular and histological screening techniques, nanoparticles are emerging as ideal candidates for personalized medicine, opening broad prospects for pharmaceutical research and drug development. This is evidenced by the current boom in the development of nano-production platforms.Despite the rise in these new technologies, several challenges remain.Concerning the pharmacological knowledge of nanoparticles in the circulating phase, a meta-analysis on preclinical models revealed that after systemic injection, only 0.7% of nanoparticles accumulated at the cancer site . Indeed,Concerning strategies for circumventing the tumor barrier, despite abundant data on intratumor accumulation by the EPR effect, there is a great heterogeneity in the distribution of nanoparticles in the tumor and tumor microenvironment . The tumThe complex molecular assembly of nanoparticles makes them highly specific; thus, this technology is part of a personalized medicine strategy. We will, therefore, need to develop more biomarkers predictive of efficiency, integrating big data and artificial intelligence to optimize design of nanoparticles by building predictive models of their biodistribution, uptake and other biological outcomes.


The unquestionable role of the intestinal microbiota in health and the development ofseveral diseases has resulted, in recent decades, in numerous publications on thesubject. In parallel, interest in the use of probiotics to modulate the intestinalmicrobiota has intensified, resulting in an exponential increase in studies andpublications that open frontiers for new treatments in several areas of medicine.. The so-called gut-brain-kidney axis links CKD to immune system dysregulation,metabolic disturbance, and sympathetic activation, and all these factors are linked tointestinal dysbiosis. Crosstalk is achieved by the effects of dysbiotic metabolites on intestinal andkidney immunity, inflammation-induced intestinal barrier disruption, and the resultinginflux of dysbiotic metabolites into the kidney through circulation. Studies point out that intestinal modulation aimed at increasing short-chainfatty acid production and decreasing endotoxemia by lipopolysaccharides can delay kidneyfunction deterioration, preventing or contributing to the treatment of CKD and its complications.Evidence of a bidirectional relationship between dysbiosis and Chronic Kidney Disease(CKD) has also been reported. The intestinal microbiota interacts with kidney functionthrough different complex mechanisms, including its influence on the immune system andon the formation of uremic toxins “Use of probiotics in patients with chronic kidney disease on hemodialysis: arandomized clinical trial” demonstrates the importance of better evaluating theeffectiveness of probiotic therapy in patients on dialysis and sheds light on thisknowledge.In hemodialysis patients, results are divergent, and this therapy must be chosen withcaution. The recent study published in BJNLactobacillus plantarum A87, Lactobacillusrhamnosus, Bifidobacterium bifidum A218, andBifidobacterium longum A101) for 3 months reduced the levels ofsyndecan-1 and glycemia, indicating possible improvements in metabolism and reduction insystemic inflammation. Syndecan-1 is one of the main components of the endothelialglycocalyx. Its expression in the immune system and its release in serum increasesinflammatory stimuli, and this occur when there is damage to the endothelial glycocalyx,a condition present in CKD on hemodialytic therapy.We congratulate the authors for the excellent double-blind randomized clinical trial with70 patients on hemodialysis, which showed that the use of probiotics(, as in the aforementioned study, which reinforces the potential of this treatmentin this group of patients. Furthermore, studies show the importance of intestinal uremictoxins on inflammation as a significant cardiovascular risk factor, which is the maincause of death in dialysis patients. The study by Taki showed that the administration of Bifidocteruim longum reducedhomocysteine levels in hemodialysis patients. However, the direct effect of probioticsin reducing cardiovascular mortality in this population has not yet been confirmed inrandomized clinical trials.The finding of glycemic reduction was also extremely important, considering the closerelationship between diabetes mellitus and CKD. Studies indicate that the use ofprobiotics improves glycemic control, especially when 3 or more strains of bacteria are associated. Thus, it is essential that the prescription of probiotics is always based onscientific evidence and individualized to the clinical condition of each patient.The risks of using probiotics in hemodialysis patients remain poorly explored. In thegeneral population, probiotics could theoretically result in the following side effects:systemic infections, deleterious metabolic activities, excessive immune stimulation insusceptible individuals, and gene transfer. WHO/FAO recommend that new strains beevaluated for safety in human studies to assess side effectsL. acidophilu. B longum andS. Thermophilus for a period of at least 12 weeks improved thequality of life of hemodialysis patients. The choice of treatment based on scientific evidence must be aligned with theexpected outcomes.Defining expected outcomes when using probiotics in patients on dialysis should also bean important factor to consider. The recently published study by Shamanadze et al showedthat correction of intestinal flora with .Finally, the definition of doses, the choice of strains, and the duration of use vary inthe literature and remain uncertain, which makes it difficult to analyze theeffectiveness of probiotics in patients on hemodialysis. Undoubtedly, the definition ofthese variables could contribute to the use of this tool in the challenging treatment ofCKD. Furthermore, associating the use of probiotics with effective dietary interventionsis essential, and future studies should consider this association