Vasovagal syncope (VVS) refers to a heterogeneous group of conditions whereby the cardiovascular reflexes normally controlling the circulation are interrupted irregularly in response to a trigger, resulting in vasodilation, bradycardia, or both. VVS affects one-third of the population at least once in their lifetime or by the age of 60, reduces the quality of life, and may cause disability affecting certain routines. It poses a considerable economic burden on society, and, despite its prevalence, there is currently no proven pharmacological treatment for preventing VVS. The novel procedure of ganglionated plexus (GP) ablation has emerged rapidly in the past two decades, and has been proven successful in treating syncope. Several parameters influence the success rate of GP ablation, including specific ablation sites, localization and surgical techniques, method of access, and the integration of other interventions. This review aims to provide an overview of the existing literature on the physiological aspects and clinical effectiveness of GP ablation in the treatment of VVS. Specifically, we explore the association between GPs and VVS and examine the impact of GP ablation procedures as reported in human clinical trials. Our objective is to shed light on the therapeutic significance of GP ablation in eliminating VVS and restoring normal sinus rhythm, particularly among young adults affected by this condition. Vasovagal syncope (VVS) is the most common form of neurally mediated reflex syncope (NMS), and usually refers to a heterogeneous group of conditions whereby the cardiovascular reflexes normally controlling the circulation are interrupted irregularly in response to a trigger. This results in vasodilation, bradycardia, or both, thereby promoting syncope . Also knThe heart is innervated by nerves from the brain and spinal cord, which either stimulate or inhibit physiological cardiac functions such as heart rate and contraction force. These nerves make up the cardiac autonomic nervous system (CANS) and include sympathetic and parasympathetic avenues. Under pathological conditions, the density of these nerve fibers in the heart may be altered, leading to either too much activation (hyper-innervation) or too little (hypo-innervation). This difference in innervation may cause a spatial imbalance in the activation of the heart, leading to cardiac autonomic dysfunction  related Cardiac contraction and heart rate are achieved by the innervation of heart tissue via CANS. All neuronal elements, including cell bodies, axons, and dendrites, are arranged and bundled to form nerves; the sympathetic and parasympathetic nerves that comprise CANS originate in the central nervous system (CNS) as preganglionic nerves, while sensory afferent nerves originate in the heart tissue and blood vessels and project into the CNS. The difference between the sensory and autonomic nervous systems is the location of their ganglia, where synapses of the postganglionic neurons derive. Innervation of the heart is established via postganglionic synapses, where acetylcholine neurotransmitters bind to postsynaptic receptors located on the postganglionic neuron inside the heart.Sensory nerves have a different anatomy and function than the sympathetic and parasympathetic nerves. Their main cardiac function is to provide feedback from baroreceptors on the aortic arch to the brain to maintain homeostasis. Sensory nerves provide information to the CNS and convey information on blood pressure, oxygen, carbon dioxide, and sugar levels in the blood. The sensory cell body gives rise to axons which sprout to both the heart and brain. The signal starts in the heart and is directed towards the brain via the neuronal cell body, whereas in sympathetic and parasympathetic nerves, the cell body also indicates the starting site of the signal. The sensory cell body lies within the dorsal root ganglia in the peripheral nervous system (PNS). Sensory nerves lay in close proximity to the autonomic nerves, and while responding to the cardiac stimulus, they relay back to the brain. Subsequently, the brain modulates output towards the heart, which is regulated by the parasympathetic and sympathetic nerves.The cardiac autonomic nervous system can be simply divided into extrinsic and intrinsic elements according to the alignment and localization of nerve fibers, their cell bodies, and joint ganglia. The extrinsic, or central, CANS comprises central nerves originating in the brain and the spinal cord and forming the external ganglia, which then synapse with secondary neurons en route to the heart. The intrinsic CANS is confined within the heart and specifies small parasympathetic neurons that synapse with vagal sprouting nerves to activate their responses within the heart. The intrinsic system designates an extensive epicardial neural network comprising clustered nerve fibers of all types and parasympathetic cell bodies, which together constitute the GP, on both the atria and ventricles, as well as around pulmonary veins and great vessels . These GThe GPs are composed of a heterogeneous population of neurons, including efferent (into the heart), afferent (away from the heart), and many small interconnecting neurons comprising the bulk of the GP . AdditioAnatomically, the four major atrial GPs are located in close proximity to the pulmonary veins (PVs), and each innervates one of the four PVs, as well as the surrounding atrial myocardium ,16 Figu. In addiAs previously described, the CANS consists of parasympathetic, sympathetic, and sensory neural elements residing in different anatomical sites of the heart. It is recognized that parasympathetic and sympathetic systems reach their target organs via pre- and postganglionic nerve fibers. The cell bodies of postganglionic sympathetic and sensory neurons lie in the CNS and away from the heart, whereas cell bodies of postsynaptic parasympathetic neurons are very close to or within the heart . This diUnder normal physiological conditions, the involuntary function of the heart is maintained by the balance of inhibitory  and excitatory (sympathetic) tones. This balance is facilitated by the brainstem and regulates the instantaneous heart rate. In certain instances, this balance is impaired due to an over-stimulated vagal response triggered by the vagal reflex. Physiologically, the vagal reflex, which can activate through multiple triggers, produces (1) severe cardioinhibition  and/or (2) vasodilation . In the case of cardioinhibition, which instigates prolonged asystole, the patient typically recovers spontaneously within minutes.The mechanism of vagal stimulation is initiated by the local release of acetylcholine. There is an influx of acetylcholine stimulating the PV ganglia, inducing PV firing and reducing the action potential duration in the atrial myocytes in the PV sleeves, causing them to fire until suppressed , and thuSeveral animal studies have shown that vagal efferent postganglionic neurons innervating the heart are primarily located in discrete epicardial ganglionic structures known as fat pads ,32,33. SPachon et al.  were theSeveral strategies have emerged to treat VVS by CNA and are currently used to target GP inputs within the heart. This evolving comprehensive approach includes anatomic and electrocardiographic mapping techniques, as well as physiologic and pharmacologic methods. The physiologically-guided approaches incorporate spectral mapping or HFS, whereas anatomically-guided methodologies purely target the GPs by location. Currently, there is no consensus on the best tactic for identifying atrial GP sites for CNA. Several additional parameters have not yet been confirmed; these include (1) the extent to which GP ablation is necessary to attenuate the vagal activity in patients, and (2) corroboration of the vagal denervation endpoints .Three subtypes of VVS can be divided into the following broad categories: (1) pure cardioinhibition (with or without asystole); (2) pure vasodepression, in which hypotension occurs without a significant decrease in heart rate; and (3) a mixed type of cardioinhibition and vasodepression. Cardioinhibition is caused by abrupt and intense vagal reflex with or without defined triggers. Despite pharmacological and pacemaker implantation efforts, the latter are highly rejected by young patients. The Second Vasovagal Pacemaker Study confirmed the weak evidence of the efficacy of pacemaker therapy .Several different approaches have been used for identification of parasympathetic autonomic ganglia in atria, including HFS, spectral analysis (SA), and an anatomical approach (AA). We comprehensively examine them herein and discuss the pros and cons of each. Prior to the use of ablation as the principal method to denervate the CANS, the achievement of pulmonary vein isolation (PVI) served as a suitable procedure. PVI is associated with denervation of the CANS and a significant reduction in AF recurrence . EndocarAs opposed to the PVI technique ,49, GP aIn 2004, Pachon et al.  used theBy applying online, real-time spectral mapping, it is possible to reveal the fibrillary myocardium (AF nests) to lead the ablation of the first neuron . Using tIn 2011, Pachon et al. performed extensive right and left atrial ablation to treat patients with VVS, guided by spectral analysis for “AF nests” to complete vagal denervation. In their study, 40 of 43 patients remained free of syncope after a mean follow-up of 45 months . AlthougAs a stand-alone tactic, the AA was initially performed in two VVS cases by Rebecchi et al. . In thisIn the same year, Sun et al.  comparedIn the following year, in 2017, AA was used by Rivarola et al.  in a hetPo et al. developed a technique to localize and ablate the GP, which serves as the “integration centers” of the intrinsic cardiac autonomic nervous system (ICANS) . ApplyinThe first group to practice selective HFS-guided GP ablation for the treatment of VVS was introduced by Yao et al., who reported successful outcomes in 10 patients with highly symptomatic VVS . SelectiCardNM is a novel approach which was instigated in recent years by Debruyne et al.  in orderQin et al. further confirmed that targeting the ARGP and the aorta-superior vena cava (Ao-SVC) fat pad (using the AA approach) is sufficient to terminate the vasovagal response, as the sinus rate (SR) increased considerably at these particular sites promptly post-ablation . HoweverThe new methodology of high-density mapping in combination with an auto-algorithm fraction mapping system, developed by Aksu et al. to treat AF and VVS , may allAs mentioned above, there are several anatomical sites at which to approach the ablation, but the main ones are through the left or right atrium, or both, and sometimes also through the superior vena cava (SVC). Very seldom, other tactics are used. Authors have discussed the pros and cons to each approachable anatomical site, and we summarize their justifications here.The right atrium GP controls the function of the SA node; electrical stimulation of the RAGP reduces the SR . The SLGSeveral useful methods have been applied in order to evaluate the completion and success of the ablation. Extracardiac vagal stimulation remains the best tool with which to identify and achieve the procedural endpoint , and mayp-values pre- and post-ablation  predicts morbidity and mortality in high-risk and comorbid patients, where SDNN values < 50 ms are classified as at risk, 50–100 ms as compromised health, and >100 ms as healthy . For CNAablation  during tGP ablation appears to be an efficacious technique for improving outcomes, primarily in patients with neurocardiogenic syncopes. Nonetheless, some very important questions remain unanswered. The long-term outcomes of GP ablation, the precise location and depth of GPs, and the ultimate mechanism of GP ablation to improve VVS are still not fully understood. A recent study by Xu et al. validated that HFS and AA are both efficient and safe approaches to successful VVS relief .Collateral damage is a major disadvantage of current thermal ablation techniques, and introduces a risk of damaging the myocardium and the surrounding tissue. Alternative, less damaging methods are currently available to treat paroxysmal and persistent AF, but do not fix the physiological effects produced by GPs during VVS. The pulsed-field ablation technique is tissue-selective, only damaging myocardial cells  and leavAnother problem is the difficulty of delivering precise, appropriate energy to GPs. While GPs, in association with PVs, are accessed with relative ease, others are found in concealed locations. Overall, there is significant complexity involved in catheter positioning both within the pericardial space and the heart itself. A more efficient and effective visualization of GPs using imaging techniques may provide useful information for improved localization. These advances have significantly propelled research over the last decade. While the understanding of GP locations is sometimes obscure, this may be due to the degree of anatomical variability between individuals .However, the specifics in terms of report accuracy of the GPs that have been targeted in some research papers remain ambiguous, with some studies not including nor clearly describing which GPs were targeted or where they were ablated ,51,62,63HRV has been found to be a predictor of ablation success, and is a useful, non-invasive tool for investigating cardiac autonomic tone ,92; it mRecurrent syncope episodes post-CNA are not well described in the literature. Long-term follow-up studies are needed to determine whether nerve regeneration leads to the recurrence of syncope symptoms. A recent report suggested that reinnervation of GPs, in some cases, may be the cause of recurrent syncopes 7 months post-ablation ; furtherCurrently, sample size is a major limitation in many studies, with numbers ranging from individual case studies to research including up to 123 patients . EvidentThe use of GP ablation as an adjunctive technique to enhance the outcomes of PVI isolation in patients with paroxysmal AF appears to be both safe and effective. Potential complications associated with GP ablation may rarely occur, especially after LA procedures, such as cardiac perforation, sinus node dysfunction, AV block, phrenic nerve paralysis, and stroke. Two patients (out of sixty-six) developed postoperative bradycardia following HFS-directed CAN, but quickly recovered with drug treatment . In anotEncouraging results have been observed regarding GP ablation in patients with VVS. However, several important questions remain unanswered. Firstly, the long-term outcomes of GP ablation, particularly over a period of 5 years, have not been thoroughly studied. Secondly, the precise mechanism through which GP ablation leads to improved outcomes is not fully understood. To address these uncertainties, it is recommended that a randomized, preferably blinded, placebo-controlled trial be conducted to elucidate the true role of GP ablation in VVS patients. Furthermore, the correlation between the clinical outcomes and the extent or technique of ablation remains unknown. Lastly, CNA is an innovative and promising therapeutic option for certain patients with VVS. Existing observational evidence highlights significant success in eliminating syncope in this population, and the occurrence of recurrent syncope following CNA has not been extensively described.Several strategies for atrial autonomic denervation have been reported. However, the optimal technique for identifying atrial GP sites, either physiologically guided  or anatomically guided, has not been established yet ,50,52,82


Brain barriers (BB) are the gatekeepers of the central nervous system, essential to protect the brain from xenobiotics, microorganisms, and other harmful agents. Conversely, disruption of BB is a key event responsible for several changes during the onset and progression of brain diseases . Thus, the results of this article will contribute to optimize the medical procedure, taking into account the time of the day when TBI occurs.It is well-established that disturbances in the circadian rhythms are observed in patients recovering from traumatic brain injury (TBI), which are critical for the recuperation process. The first article of this Research Topic, shows that circadian rhythms are crucial determinants of TBI outcome. The authors showed that health parameters and scores vary depending on the light-dark cycle at which induced TBI occurred, in male Wistar rats .The urgent need for new therapies for primary insomnia with minimal side effects, turned out to be the main objective of one of the other articles published. Although the transcutaneous auricular vagus nerve stimulation, has been reported as an effective treatment for insomnia, the inter-individual variations in the efficacy of this treatment are not well-understood. The authors observed that during continuous transcutaneous auricular vagus nerve stimulation, patients with primary insomnia showed variable sensitivity, that might be explained by the distinct control of the sensorimotor network by the autonomic nervous system . Thus, this article established an important relationship between the circadian molecular system, namely the SCN, and the psychiatric-related behaviors.The link between circadian rhythms and mood and anxiety disorders, was another subject addressed in this Research Topic. The authors analyzed the involvement of the master clock, located in the suprachiasmatic nucleus (SCN) of the hypothalamus, in regulating psychiatric-related behaviors in mice using optogenetic stimulation paradigms. They concluded that SCN-mediated dampening of rhythms is directly correlated with depressive- and anxiety-like behaviors .Finally, the last published article also tried to relate alterations in biological rhythms with depressive disorders and consequently possible changes in tumor markers, due to the development of chronic inflammatory diseases. They concluded that the incidence of non-suicidal self-injury, a risk factor for suicide in depressive patients, was relatively high in adolescents. Furthermore, the construction of an index including a combination of depression score, tumor marker levels, and age can identify non-suicidal self-injury behaviors among adolescent patients with diagnosed depressive disorders (In summary, this Research Topic is a step forward to understanding the influence of circadian rhythms in health and disease and we hope that the reader will find it a useful reference in the emerging field of adequate “rhythmic” therapeutic strategies taking into consideration the influence of the circadian biology.TQ wrote the first draft. CS, JC-N, MK, and IG provided critical comments and editorial suggestions for revisions. All authors agreed on the submitted version.


The COVID-19 pandemic had a significant impact on neurology training programs, leading to disruptions and changes that may have long-term implications for neurological education. The objective of this study was to investigate the impact of COVID-19 on neurological training programs, collecting available data relating to residents’ experience worldwide. We performed a systematic search of the literature published on PubMed from January 2020 to March 2023, including studies referring to quantitative analysis of residents’/trainees’ perspectives. Specifically, we included studies that examined how the pandemic has affected clinical and research activities, the use of telemedicine, the delivery of education and the psychological status of residents. Of the 95460 studies identified through database searching, 12 studies met the full criteria and underwent data extraction. In conclusion, the COVID-19 pandemic has had significant impacts on neurology training programs, highlighting the need for resilience and flexibility in medical education. Future research should focus on the long-term outcomes of these adaptations in the quality of neurology education and patient care.  The COVID-19 pandemic has presented an unprecedented challenge to healthcare systems worldwide . Indeed,Within this context, the pandemic also had a significant impact on neurology training programs, leading to disruptions and changes that may have long-term implications for neurological education . Indeed,During the first part of the outbreak, hospitals rapidly shifted their mission to the management of COVID-19 patients, and many residents participated directly in this process, working in COVID-19 units . Use of The aim of this systematic review is to investigate the impact of COVID-19 on neurological training programs, collecting available data on residents’ experience worldwide. To our knowledge, this is the first review that systematically addresses the consequences of COVID-19 on neurology residency programs. We performed a systematic search of the literature published on PubMed from January 2020 to March 2023 using the following searching string: (((COVID-19) AND (neurology)) AND (training)) OR (residency). We conducted a systematic review (not registered) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines . Only stOf the 95,460 studies identified through database searching, 95,418 records were excluded because the abstract or the title did not fulfil the inclusion criteria for this review . Forty-two full papers were assessed for eligibility, and, eventually, only 12 studies met the aforementioned full criteria and underwent data extraction  14,15,1,23,24,25Full-text articles were then independently reviewed by two authors for eligibility and included if they comprised quantitative analysis of residents’/trainees’ perspectives with specific reference to clinical and research activities, the use of telemedicine, the delivery of education and the psychological status of the residents engaged in neurology. Disagreements in study inclusion were resolved through iterative discussions with the other authors until consensus was achieved. Data were framed into a narrative review.The Italian study by Di Lorenzo and colleagues found that the 97% of the Italian residents who completed the survey changed their clinical routine because of the outbreak . The majAccording to the study by the young section of the Italian Society of Neurology , most ofData from Italian residents showed that, during the COVID-19 pandemic, there was a wide use of telemedicine in Italy, especially in comparison with in the past, when this method was occasionally used only by 14% of neurology residents . Due to In the vast majority (92%) of the Italian centers examined by Di Lorenzo and others, both lessons and seminars were delivered on online platforms . The surThe Italian investigation by Di Lorenzo and others showed that psychological support for residents working during the outbreak was offered to a quarter of neurology trainees . AlthougAccording to this systematic review, the COVID-19 pandemic has caused significant changes to neurology training programs worldwide. These modifications have affected various aspects of residency, including clinical and research activities, the implementation and use of telemedicine, the delivery of education and the psychological well-being of the residents.The impact on clinical activities was reported to be substantial in almost all the studies included in this review. There has been a widespread decrease in time spent with neurological patients ,16,18,23Research activities were generally reported as having decreased during the outbreak ,16,22,23The use of telemedicine has been dramatically amplified during the pandemic. This sudden increase has demonstrated the potential utility of this resource but has also highlighted potential issues regarding the confidence and proficiency of residents in delivering virtual care ,22,23,25Online learning was widely use in several hospitals/universities for the delivery of neurology education ,22,23,24Moreover, the pandemic also forced a shift from in-person conferences/meetings to virtual conferences. After initial hesitation about moving all material and presentations online, due mainly to technical reasons and also to the feeling of impersonality due to the nature of the virtual meeting, virtual conferences fulfilled the main mission of organizing high-quality congresses despite the restrictions of the impersonal format, as evidenced by the high registration numbers of attendees . The geoAs far as psychological implications are concerned, the pandemic increased stress levels ,22,23,24Our findings are in line with a worldwide WHO survey of international neurological patient and scientific organizations that examined the disruption and mitigation of neurological services during the outbreak . The autThis review had some limitations, including potential selection bias due to the inclusion criteria and the fact that some regions may be overrepresented in the data. Additionally, the studies included in this review were conducted at different points during the pandemic, which could have influenced the results due to changing circumstances and adaptations over time. Moreover, none of the studies evaluated the academic performance of neurological trainees.In conclusion, the COVID-19 pandemic has had significant impacts on neurology training programs, highlighting the need for resilience and flexibility in medical education. The lessons learned during this crisis could inform future adaptations to residency programs, ensuring that trainees receive comprehensive and effective training even in the case of unprecedented challenges. Future research should focus on the long-term outcomes of these adaptations in the quality of neurology education and patient care.


Low-Earth orbit (LEO) satellites have limited on-board resources, user terminals are unevenly distributed in the constantly changing coverage area, and the service requirements vary significantly. It is urgent to optimize resource allocation under the constraint of limited satellite spectrum resources and ensure the fairness of service admission control. Therefore, we propose an intelligent hierarchical admission control (IHAC) strategy based on deep reinforcement learning (DRL). This strategy combines the deep deterministic policy gradient (DDPG) and the deep Q network (DQN) intelligent algorithm to construct upper and lower hierarchical resource allocation and admission control frameworks. The upper controller considers the state features of each ground zone and satellite resources from a global perspective, and determines the beam resource allocation ratio of each ground zone. The lower controller formulates the admission control policy based on the decision of the upper controller and the detailed information of the users’ services. At the same time, a designed reward and punishment mechanism is used to optimize the decisions of the upper and lower controllers. The fairness of users’ services admissions in each ground zone is achieved as far as possible while ensuring the reasonable allocation of beam resources among zones. Finally, online decision-making and offline learning were combined, so that the controller could make full use of a large number of historical data to learn and generate intelligent strategies with stronger adaptive ability while interacting with the network environment in real time. A large number of simulation results show that IHAC has better performance in terms of a successful service admission rate, service drop rate, and fair resource allocation. Among them, the number of accepted services increased by 20.36% on average, the packet loss rate decreased by 17.56% on average, and the resource fairness increased by 17.16% on average. With the continuous advancement of communication technologies and the rapid growth of global communication demands, the existing terrestrial network can provide high-speed and diversified services for densely populated areas, but it still has obvious shortcomings in dealing with long distances, a wide coverage, large capacity, and harsh terrain communication environment. At the same time, as an important supplement to the ground network, a satellite network has significant advantages in expanding the communication coverage, improving the communication capacity and reliability in hot spots, and realizing the space–air–ground–sea integrated network ,2. AmongMulti-beam satellite communication technology is an effective approach to solve the above challenges. This technology achieves multiple frequency reuses and polarization reuse through spatial isolation, which can increase satellite communication capacity exponentially. At the same time, the dynamically adjusted beam direction can help the satellite system allocate resources more effectively and further meet the needs of the variability in coverage area and the diversity of communication requirements . HoweverLin et al. ,7 proposThe emergence of the above research results brings new ideas and methods for the resource allocation of multi-beam LEO satellite communication. However, when dealing with the diverse and time-varying communication requirements in the network, these methods are difficult for meeting the needs of rapid and dynamic resource allocation due to high algorithm complexity and long calculation times. Machine learning (ML)  has supeLiao et al.  designedBy introducing DRL, the above research provided a forward-looking solution for solving resource allocation in multi-beam LEO satellite networks. However, current research still has some shortcomings, with the main deficiency being the lack of consideration for fair user service admission in the optimal allocation of resources. In the multi-beam LEO satellite communication system, the coverage area of the satellite is constantly changing, and the needs of users in the area are diverse.If fairness is not considered in resource allocation, this will result in some users being overlooked or frequently denied access, while others consistently occupy more resources. Over time, this leads to a significant decline in user experience, causing dissatisfaction with the services provided by the satellite. However, in the existing research, traditional algorithms exhibit limited flexibility and adaptability when confronted with the complexities of the satellite communication environment. Moreover, accurately extracting the key information required for fair admission control strategies from a vast array of service demand characteristics often proves challenging. Additionally, a comprehensive and effective hierarchical admission control strategy capable of achieving the cooperative optimization of resource allocation rationality and admission control fairness has yet to be established. Hence, we propose an intelligent hierarchical admission control (IHAC) strategy based on DRL. This approach incorporates the user service model, the dynamic priority model, and carefully designed controller feature inputs, along with a reward and punishment mechanism. Through the utilization of DRL, IHAC aims to efficiently allocate multi-beam resources and exercise control over user service access within the coverage area, simultaneously addressing both objectives.In this paper, the DLR method is employed to effectively manage the multi-beam satellite communication system. By combining deep deterministic policy gradient (DDPG) and deep Q-network (DQN) algorithms, a hierarchical admission control strategy is constructed, encompassing both upper- and lower-level controllers. The upper-level controller employs DDPG to comprehensively consider the service demands of various ground zones and formulate resource scheduling strategies from a global perspective. This ensures optimized resource utilization while ensuring the coordinated allocation of beam resources among different ground zones. The lower-level controller employs DQN to receive decisions from the upper-level controller and refines the global strategy into localized admission control strategies for each ground zone’s services.This paper develops user service models and dynamic priority models for services. The user service model enables controllers to have a deeper understanding of different types of service characteristics, leading to more precise decision-making. By introducing the adaptive dynamic priority model, controllers can achieve efficient resource utilization while considering the fairness of competitive services, leading to a more balanced resource allocation. Furthermore, careful design is applied to the feature inputs, reward functions, and penalty terms of both upper- and lower-level controllers, facilitating a more comprehensive and detailed understanding of service demands. This guides controller decisions towards optimizing both efficient resource utilization and overall fairness of the communication system.In simulation experiments, the proposed strategy is compared with DAQC  and WOA The contributions of this paper are as follows:The remainder of this paper is organized as follows. In LEO satellite communication systems, as the satellite moves in the orbit, its coverage will change, and the corresponding traffic load and service priorities will also change. In order to meet the changing requirements of ground tasks, it is necessary to allocate satellite resources reasonably. The resource allocation problem is mainly affected by time window constraints, satellite power consumption constraints, ground user priorities, etc.M fixed ground zones, and the communication tasks are assigned to different ground zones according to the location of their initiating users. In the context of multibeam satellite communication, LEO satellites allocate their transmission capacity into multiple beams, each directed towards a specific ground zone. LEO satellites can dynamically adjust the beam resources of ground zones in real-time based on the distribution of services on the ground, and further decide whether to admit user services within these zones. This communication architecture between user terminals and satellites forms a complex system.The system model for multibeam LEO satellite communication is illustrated in The core focus of this paper is to address the complex issue of user service requests within multibeam satellite communication systems. The initial step involves constructing a user service model to depict various types of user services. This user service model comprehensively accounts for various parameters and features of the requested services to ensure a comprehensive and accurate representation of user service requirements. In addition to the user model, we also establish a dynamic user service priority model. Given the constantly changing communication environment, service priorities are adjusted based on dynamically changing conditions, such as the remaining service value and service urgency. By introducing an adaptive dynamic priority mechanism, the user service admission process is further optimized to ensure efficient resource utilization, while achieving fair resource allocation among competitive services. Among them, the relevant variable descriptions of user services are presented in With the movement of satellites and the progression of time, the status of user services is constantly changing. We design a sextuple to represent the data model of user services within a beam. Let there be Building upon the initial priority of user services, this paper also takes into account the aspects of the remaining service value and the urgency of service provisioning. The dynamic priority Let DRL, as a powerful artificial intelligence technique, offers the core advantage of autonomous learning and optimization in complex and uncertain environments. It achieves this by interacting with the environment, accumulating experiences, and progressively improving decision quality ,28,29,30The integration of the DDPG algorithm and DQN algorithm, which are prominent components of DRL, provides a novel solution for hierarchical admission control in satellite communication systems. DDPG extends the concepts of DQN and the Actor-Critic framework, effectively handling the complexity of state spaces, making it particularly suitable for the continuous action control problem of allocating beam resources to ground zones. On the other hand, DQN can accurately perceive and analyze the state features and communication demands of user services, addressing the discrete admission control problem. Combining these DRL algorithms with LEO satellite communication hierarchical admission control leads to intelligent decisions regarding user admission into the communication network and optimal resource allocation under limited resource conditions.The combination of the above DRL algorithms, LEO satellite communication resource allocation, and admission control forms a two-level intelligent admission control framework, as illustrated in Within the context of this hierarchical admission control strategy, it is necessary to holistically consider the relationships among all ground zones, while also giving due consideration to the priority and fairness management among user services. The implementation of this strategy introduces a new level of intelligence to the entire communication system, allowing the system to better adapt to diverse communication needs and provide users with a higher-quality communication experience.As illustrated in In the upper-level admission control strategy, each ground zone initially conducts unified scheduling and management of its internal services. After analyzing and processing user service information, the ground zone’s state features are formed and submitted to the upper-level DDPG. The input features encompass both user service and ground zone information, such as the number of service requests in the ground zone, total dynamic priority, and aggregate requested bandwidth. This empowers the DDPG to gain comprehensive insights into interactions and communication needs among users within the ground zone, thus providing more precise guidance for higher-level decisions. Meanwhile, the input features for the lower-level DQN include the upper-level DDPG’s resource allocation strategy for the ground zone and more detailed user service information, such as service types. This design enables the lower-level DQN to more accurately assess each user’s communication performance, enabling more targeted admission control decisions.mth ground zone, and To be specific, the upper-level DDPG’s input features are denoted as The specific features are given by the following formulas.mth beam:mth ground zone; The ratios of the requested bandwidth, power, and capacity of the In the proposed hierarchical admission control architecture, the upper- and lower-level controllers are responsible for the scheduling of satellite-to-ground beam resources and the admission control of user services within ground zones, respectively. The upper-level controller plays a crucial role in global decision-making. It aggregates network state features from various ground zones and feeds this information into the DDPG neural network. Subsequently, based on these network state features, DDPG formulates a set of resource scheduling policies Specifically, when Once the satellite completes the resource scheduling for various ground zones, it enters the domain of the lower-level controller. The primary responsibility of the lower-level controller is the admission control of user services within each ground zone. At this stage, the lower-level DQN leverages the state feature In the proposed intelligent hierarchical admission control framework based on DRL, the reward function plays a crucial role. The design of this key element not only establishes a close correlation between the network state feature input and the admission control policy output but also guides the neural network towards rapidly approaching and converging to the predefined optimization objectives. During the resource scheduling process for various ground zones by the satellite, the design of the reward function for the upper-level DDPG needs to take into account the overall system performance, ensuring both communication system efficiency and fairness. This prevents excessive bias of communication resources towards specific ground zones, which could impact the overall communication effectiveness. Therefore, the reward function The lower-level DQN is built upon the foundation of the upper-level admission control strategy and aims to make decisions for services within each ground zone. In this architecture, a reasonable lower-level admission control strategy’s primary concern is to ensure compliance with the resource allocation proportions set by the upper level. If the total resource consumption of admitted services exceeds these limits, the lower-level DQN reward function needs to impose a certain penalty to maintain system balance and stability. Similarly, the fairness of the intra-zone service admission control strategy must also be ensured. Therefore, we employ the total dynamic priority To ensure data consistency, we have normalized these values. Through these two components, the lower-level DQN is guided to balance the dynamic priority and waiting time of intra-zone user services. Additionally, We delve into the exploration of DDPG and DQN, evolved from the traditional Q-learning algorithm, and their collaborative implementation in the hierarchical admission control framework. However, these methods also inherit issues such as instability, overestimation, and convergence challenges that have been associated with traditional Q-learning, especially when utilizing neural networks to estimate Q-values.In conventional Q-learning, a common practice involves using a single online network to estimate Q-values for each state-action pair, and decisions are made based on the action with the highest Q-value. Nevertheless, this approach can lead to unstable Q-value estimations, particularly during the initial stages of training. This instability arises from the chain reaction triggered by the parameter updates in the neural network, resulting in fluctuations in Q-values. Furthermore, as traditional Q-learning employs a greedy strategy to select actions with the highest Q-values, it can lead to the overestimation of Q-values, subsequently affecting the accuracy of the policy.To overcome these challenges, we introduce the concepts of a target network and experience replay mechanism in DRL. Specifically, the target network shares the same structure as the online network but employs a different parameter update strategy. The target network’s parameters are copied from the online network at regular intervals or through a soft update approach. This separation of neural networks ensures that the calculation of the target network Q-values is unaffected by the direct influence of the online network, reducing the immediate impact of the online network’s instability and mitigating the chain reaction caused by parameter updates.Furthermore, in interactive environments, the acquired data are often highly correlated, with potential correlations between consecutive data points. This correlation can lead to the neural network being influenced by related data during the training process, thereby causing instability. The experience replay mechanism, by randomly sampling from an experience buffer, breaks down data correlation, enhancing data utilization efficiency. The deployment of neural networks is as follows.Online Actor Network: Online Critic Network: Target Actor Network and Target Critic Network: Online DQN: While interacting with the environment, the upper- and lower-level controllers accumulate a variety of state-action pairs’ experience samples During the training phase of DDPG, the online actor network utilizes the experience samples The online actor network relies on the backpropagation of the policy gradient The target Q-value is obtained by taking a weighted sum of the current reward Finally, we adopted a soft update approach for updating the parameters of both target networks, where in each update iteration, the parameters are updated by weighting them with the learning rate Given that we have adopted a distributed ground zone approach with multiple intelligent agents and treated each ground zone as an individual agent, in this architecture, each ground zone needs to balance resource allocation and services admission decisions while collaborating and interacting with others. This involves finding a balance between cooperation and competition among multiple intelligent agents. Moreover, we recognize that the upper-level controller comprehensively considers the dynamic situations of each ground zone based on global information, thereby partially balancing the resource competition process among them and indirectly providing a global perspective for the lower-level controller. Therefore, we opt for a decentralized training approach for the deployment of lower-level controller agents. In this scheme, each ground zone’s agent is relatively independent in its training, making decisions based on local information. Here, we provide an overview of the training process for a single intelligent agent.The lower-level controller primarily focuses on training the online DQN, and its principle is similar to training the online critic network in the upper-level controller. Similarly, based on the sample The parameter update of the target DQN still adopts the soft update method:Considering the characteristics of satellite high-speed movement and the real-time variability of users’ needs and demands, we have adopted a strategy of online decision-making and offline learning for the training and decision-making of intelligent agents. This strategy aims to ensure that the agents can make adaptive decisions in real-time environments and continuously enhance their decision-making capabilities through offline learning.During the online decision-making phase, the intelligent agents interact with the environment through the upper and lower-level controllers, accumulating experiences. This real-time interaction process enables the agents to promptly perceive changes in the satellite movement, the distribution of user services, and the actual utilization of resources. In the offline learning phase, we utilize these accumulated experiences to optimize the agents’ decision-making capabilities. By deeply learning and analyzing the experiential data, the agents can acquire insights into more intricate patterns and trends. The detailed strategy process is illustrated in Overall, the dual approach of online decision-making and offline learning allows the agents to balance the real-time responsiveness and learning capability. This strategy not only enables the agents to make timely decisions in dynamic environments but also continuously enhances their decision-making abilities through offline learning, thereby achieving a more intelligent and adaptive hierarchical admission control system.According to the relevant parameters of the Iridium constellation, a simulation environment is built by STK to obtain the satellite coverage time of each ground zone. Then, we establish a simulation system, and implement an intelligent hierarchical admission control strategy through MATLAB. Its simulation parameters are shown in In the field of DRL, the convergence of algorithms is regarded as a key indicator for evaluating the performance and effectiveness of the algorithm. Especially when applied to LEO satellite communication systems, the convergence speed and stability of the reward function directly reflect the optimization level of the algorithm and its adaptability under different circumstances. Therefore, we observed the changes in the reward function during model training to obtain the optimal settings for model parameters. Furthermore, in simulation experiments, the proposed IHAC strategy is compared with DAQC and WOA in terms of channel user quantity, successful access probability, and drop call rate, demonstrating the applicability and superiority of the proposed strategy.x-axis represents the number of training episodes and the y-axis represents the reward value. In DRL algorithms, the objective is to learn to select the optimal policy to maximize the cumulative reward. The reward discount factor can be used to balance the immediate reward at the current time step and the future rewards, with a larger discount factor focusing more on future rewards, allowing the controller to consider the long-term impact of actions and promoting algorithm convergence. Therefore, in our experiments, we set the reward discount factors as In this paper, simulation verification is conducted using a time division approach, where a single resource allocation time window is divided into 10 units of simulated time. The proposed strategy in this paper shows a significant improvement in channel utilization after sufficient training. It not only avoids resource wastage but also effectively meets the access demands of user services. Compared to DAQC and WOA, the proposed strategy achieves the highest received service count of 280 and 320, respectively, while the accepted service count is increased by 22.95% and 21.19%, respectively. The results highlight that the proposed intelligent strategy, after training, significantly enhances the utilization of channels, not only preventing resource wastage but also efficiently satisfying the access requirements of user services.The rate of successful service access is a critical parameter that reflects user service satisfaction and is one of the core goals of satellite networks. A high rate of successful service access implies that services are more likely to be effectively provided. Especially in scenarios with numerous service demands, terminal users need to compete for limited beam resources. Therefore, the level of this indicator significantly impacts user experience. As shown in Compared to services that have not been accessed yet, services that are interrupted after accessing are more challenging to accept. This not only means that the resources allocated to the service are released but that this also requires reapplication and resource competition to continue the service. As shown in The fairness of resource allocation is defined by the ratio of allocated resources to requested resources, which reflects the satisfaction of ground zone services. Achieving fair resource allocation can reduce unnecessary resource competition. An analysis of Finally, we show the performance comparison between IHAC and baseline algorithms with average metric data, as shown in D and the time complexity f of the fitness function. That is, it can be roughly expressed as In the controller, the computation related to DRL consumes most of the resources, and we focus on analyzing its time and space complexity. During the inference and operation of DDPG and DQN, their computational overhead mainly depends on the number of nodes in the input layer. Specifically, if M represents the number of ground zones, K represents the characteristic dimension of each ground zone, N represents all user services within the satellite coverage, and L represents the characteristic dimension of user services, then the input layer of DDPG consists of MK units, and the input layer of DQN consists of NL units. Then the time complexity can be expressed as We can find that DL techniques require more computation and storage costs compared to traditional strategies. However, the IHAC we consider can not only achieve the adaptive ability to the dynamic environment through the feature extraction of massive data, but also achieve the dual goals of efficient utilization of beam resources and service fairness.This paper proposes an intelligent hierarchical admission control (IHAC) strategy based on DRL for LEO satellites. The strategy addresses the resource allocation and admission control challenges in the field of multi-beam satellite communications, specifically focusing on intelligent admission control for ground zone services within a multi-beam coverage area. The strategy employs DDPG and DQN algorithms to create a hierarchical control strategy that coordinates global resource scheduling with local service admission. The integration of user service models and adaptive dynamic priority models ensures a balance between resource utilization and fairness.By introducing well-designed state feature inputs and reward mechanisms, the strategy guides decision-making to achieve efficient resource utilization and fairness. In summary, the IHAC strategy proposed in this paper fills the gap in the field of satellite multi-beam communications by providing a comprehensive and effective hierarchical admission control strategy. Leveraging the power of DRL, this strategy can cater to diverse service demands, ensuring both efficient resource utilization and service fairness. It presents a solution for the optimization and advancement of multi-beam satellite communication systems.


This study examined the impacts of climate change on okra and tomato yields. Fertilizer consumption and credit to the crop sector were considered as covariates in the analysis. Time-series data, spanning a period of 40 years, were obtained from various sources. An autoregressive distributed lag model was applied to analyze short- and long-term impacts of climate change and agricultural inputs on okra and tomato yields. Not all variables were stationary at levels (order zero), but they were all significant at first difference, indicating the presence of cointegration. The Bound’s test F-ratio was statistically significant and implied the presence of long- and short-term relationships among the variables studied. The mean temperatures had negative impacts on okra and tomato yields in both the short and long terms. Credit guaranteed to the crop sector had positive short- and long-term impacts on tomato yield; fertilizer consumption had a negative long-term impact on okra yield. Our study concludes that climate change, particularly rising temperature, impacts herbaceous fruit crop production in Nigeria. Therefore, we recommend that breeding and disseminating climate-smart tomato and okra varieties will help fruit crop farmers respond to rising temperatures. One of the greatest issues of the 21st century is global climate change. According to a growing body of evidence, climate change is undeniable and occurring at an incredible rate ,4. VariaRising temperatures, unpredictable rainfall patterns, rising sea levels, flooding, drought and desertification, land degradation, increased frequency of extreme weather events, depleted fresh water supplies, and declining biodiversity are all manifestations of climate change in Nigeria ,14. Rain2, also has an impact on the development and growth of crops, as well as on the prevalence of insect pests and diseases [Magnesium is another important nutrient found in okra that is necessary for healthy bodily growth and function . Climatediseases .The cultivation of fruit crops, therefore, is becoming unprofitable due to crop failures, low yields, declining quality, and rising pest and disease issues in climates that are changing . ConsequSome theoretical and empirical studies have focused on investigating climate impacts on cereal crops, such as rice, maize, wheat, and sorghum ,36,37,38However, with regards to changing climate, the importance of fruits to food and nutrition security, the vulnerability of herbaceous fruit crops to climate vagaries, and the importance of other agricultural production inputs (credit and fertilizer) in herbaceous fruit crop production in Africa’s most populous nation—Nigeria—research studies are needed to understand the extent to which herbaceous fruit crops would be affected by changes in temperature and precipitation. This will contribute to the design and development of climate-resilient strategies for the herbaceous fruit crop sub-sector, the attainment of the Sustainable Development Goals, the actualization of the country’s agricultural policy, and the achievement of the ambitions of the Nationally Determined Contribution, as well as other climate commitments.Several studies have been undertaken to understand the impacts of climate change on crop production in Nigeria ,64,65,66This paper used time-series data (1981–2020) obtained from four databases—the Central Bank of Nigeria Statistical Bulletin, FAOSTAT, World Development Indicators, and the World Bank Climate Change Knowledge Portal. We used data obtained from the Central Bank of Nigeria 2020 Statistical Bulletin, FAOSTAT, and World Bank Climate Change Knowledge Portal. Specifically, tomato and okra yield statistics were obtained from the FAOSTAT database, fertilizer consumption data were obtained from the World Development Indicators database, temperature and rainfall statistics were obtained from World Bank Climate Change Knowledge Portal, while credit guaranteed to the crop sector data were obtained from the Central Bank of Nigeria Statistical Bulletin. The details of the data and sources are presented in We used the autoregressive distributed lag (ARDL) model to analyze the impacts of climate change and production inputs on okra and tomato yield in Nigeria. The ARDL has the ability to model both the short- and long-term impacts between dependent variable(s) and independent variables ,46,58. TWe applied the popular autoregressive distributed lag (ARDL) approach by Pesaran et al.  to modelThe implicit model of the autoregressive distributed lag framework used in this study is stated as follows:The average tomato yield was 76,881.20 hg/ha, the minimum yield under for the studied period was 37,208 hg/ha, while the maximum yield was 103,455 hg/ha. The coefficient of skewness (−0.35) of tomato yield showed that most of the yields recorded across the years studied were close to the maximum value, with few close to the minimum value. Average temperature was 27.17 °C, while the average total rainfall was 1137.11 mm. Average fertilizer consumption was 10.04 kg per hectare of arable land, while average total credit guaranteed to the crop sector was USD 17,196.85.We used the cumulative sum (CUSUM) and cumulative sum of squares (CUSUMSQ) tests recommended by Pesaran and Shin  and PesaWe used the Ramsey RESET test to examine whether the model has an omitted variable problem or not. The Ramsey RESET test result is presented in We used the Bounds test to determine whether there is a long-run relationship between the dependent variables (okra and tomato yield) and independent variables . The result is also presented in Fertilizer consumption negatively and significantly affected okra yield in the long run. The coefficient was −0.48, implying that a 1% increase in fertilizer consumption would decrease okra yield by approximately 0.48% in the long run.Total credit guaranteed to the crop sector positively but insignificantly affected okra yield. For the tomato yield model, the estimate of total credit guaranteed to the crop sector was positive (0.15) and statistically significant at 5%. Thus, in the long run, a 1% increase in the total credit guaranteed to the crop sector would increase tomato yield by 0.15%, ceteris paribus.We now focus on interpreting the results of the short-run estimates. Mean temperature estimate was statistically significant under both models (okra and tomato yield). From The short-run and the long-run effects of the total credit guaranteed to the crop sector on crop yields (okra and tomato) are the same. The estimate of total credit guaranteed to the crop sector under the okra yield model was positive but not statistically significant, both in the long run and short run. However, the total credit guaranteed to the crop sector was positively and significantly related tomato yield both in the, short and long runs. Therefore, total credit guaranteed to the crop sector had a positive significant impact on average tomato yield in the short run. Thus, a 1% increase in credit guaranteed to the crop sector would increase tomato by 0.07% in the short run. This study analyzed the effects of climate change (proxied by average temperature and precipitation) and agricultural production inputs (such as credit and fertilizer) on herbaceous fruit crop production (okra and tomato). With regards to the effect of temperature and the fruit crop yields, we found that mean temperature had significant and negative relationships with both crops (okra and tomato) in both the short and the long terms. This suggests that rising temperature significantly decreased herbaceous fruit crop yield in the country. Camejo et al. , in theiOn the effect of fertilizer use and herbaceous fruit crop yields in Nigeria, we found that fertilizer application had a negative and significant impact on okra yield in the long run. However, in the short run, the result showed a positive but statistically insignificant relationship with okra yield in Nigeria. Masuku et al.  also fouWe also examined the impact of credit on herbaceous fruit crop yields. Our result shows that credit increased tomato production. Our finding shows that credit had a positive impact on okra and tomato production, both in the short run and long run. While the effect was statistically significant for tomato production, it was not for okra production, both in the short and long terms. Our result indicates that credit can boost tomato production in the long run. Credit increases agricultural production in the short run ,90. For This study analyzed the impacts of climate change on herbaceous fruit crop (tomato and okra) yield in Nigeria using credit and fertilizer as covariates. Using time-series data spanning a period of 40 years and the ARDL model, we can conclude that climate change and agricultural production inputs have both short- and long-term impacts on okra and tomato yields. The impacts of climate and agricultural inputs on herbaceous fruit crops have revealed the significant roles temperature, fertilizer, and credit play in fruit crop growth and development.Relying on long-term okra and tomato yield, climate, fertilizer consumption, and credit statistics obtained from the FAOSTAT, World Bank Climate Change Knowledge Portal, World Bank World Development Indicators, and Central Bank of Nigeria Statistical Bulletin, we observed that temperature has both short-term and long-term negative impacts on tomato and okra yields. This has implications on climate adaptation and planning. For policy purposes, we suggest that, to achieve SDG goal 1, for example, continued efforts are needed to review existing climate change policies, plans, and commitments that will promote investments in climate smart agriculture and dissemination of associated technologies to fruit crop farmers. This would reduce the risk of fruit crop failure whilst ameliorating the effect of climate change on the agricultural livelihoods of many people in Nigeria and Africa.Moreover, we observed fertilizer consumption per hectare of arable land significantly decreased okra yield in the long run but insignificantly increased the yield in the short run. With this finding, policy actions should focus on precision agriculture and efficient use of fertilizer in fruit crop production. Therefore, mapping the soil fertility levels of different agroecological zones and localities in Nigeria and Africa would go a long way determining the exact quantity, quality, and type of fertilizer needed in each area and reduce overflow or underflow of nutrients in the soil. Therefore, we recommend the implementation or upscale of soil fertility testing projects in various localities on the continent.Overall, this study strengthens the view that credit plays a significant role in crop production because of the positive long-term impact of credit on tomato yield. Therefore, making credit available to farmers will help to achieve the food and nutrition security and poverty reduction goals of the United Nations, Africa, and Nigeria. Thus, the study recommends that policies should be geared towards intensifying every effort to increase access to affordable credit facilities to farmers. Governments, financial institutions, and donors can formulate and implement sustainable and affordable credit access programs for fruit crop farmers.One important limitation of this study needs to be mentioned. In general, maximum and minimum temperatures also have impacts on crop yield; this study only analyzed the effect of average temperature. Future studies should expand on this aspect by adding minimum and maximum temperatures in exploring the short- and long-run dynamics of climate change and crop production. The current study  nonetheless suffices for the illumination of the effects of climate change on herbaceous fruit crop production in Nigeria.


Transcranial magnetic stimulation (TMS) is an innovative and non-invasive technique used in the diagnosis and treatment of psychiatric and neurological disorders. Repetitive TMS (rTMS) can modulate neuronal activity, neuroplasticity and arousal of the waking and sleeping brain, and, more generally, overall mental health. Numerous studies have examined the predictors of the efficacy of rTMS on clinical outcome variables in various psychiatric disorders. These predictors often encompass the stimulated brain region’s location, electroencephalogram (EEG) activity patterns, potential morphological and neurophysiological anomalies, and individual patient’s response to treatment. Most commonly, rTMS is used in awake patients with depression, catatonia, and tinnitus. Interestingly, rTMS has also shown promise in inducing slow-wave oscillations in insomnia patients, opening avenues for future research into the potential beneficial effects of these oscillations on reports of non-restorative sleep. Furthermore, neurophysiological measures emerge as potential, disease-specific biomarkers, aiding in predicting treatment response and monitoring post-treatment changes. The study posits the convergence of neurophysiological biomarkers and individually tailored rTMS treatments as a gateway to a new era in psychiatric care. The potential of rTMS to induce slow-wave activity also surfaces as a significant contribution to personalized treatment approaches. Further investigations are called for to validate the imaging and electrophysiological biomarkers associated with rTMS. In conclusion, the potential for rTMS to significantly redefine treatment strategies through personalized approaches could enhance the outcomes in neuropsychiatric disorders. Transcranial magnetic stimulation (TMS) is a non-invasive method that modulates neural processing in the brain by stimulating a magnetic coil that generates a magnetic field which then induces depolarizing neuronal cell membrane potentials in the cortical tissue beneath the coil and influences the associated activity of neural loops. The context-dependent overall number of pulses, the location of the coil in relation to the brain, the frequency and intensity of the magnetic stimulation, the time duration between each string, and the target regions on the cortex are linked to the effects of TMS . The mecMoreover, there are a growing number of studies supporting the efficacy of rTMS for other conditions such as insomnia, catatonia, post-traumatic stress disorder, anxiety, Parkinson’s disease, tinnitus, MCI, and other diagnoses . NeverthMost of the studies were conducted during the waking state. At the same time, positive effects on the consolidation of neuronal activity were found in the polysomnographic recordings, suggesting a positive influence on sleep quality.Despite the proven effects of rTMS at the neuronal level and having a positive impact on clinical outcome variables, the question about the cause of non-response in some patients remains unanswered. An answer can be sought in the analysis of the following conditions: 1) the stimulation protocols vary between research groups, 2) the frequency used has a different effect on different individuals, 3) the timing of the rTMS could show a different effect depending on day or night when the stimulation was applied, 4) the electroencephalogram (EEG) activity of the stimulated areas shows chronobiological oscillations that could play a role in potentiating or inhibiting the EEG activity of the stimulated brain region, 5) the pathology of the disease could be located elsewhere than in the stimulated region, and 6) the neuronal connectivity of the stimulated region could be primed by the previous treatment that suppresses the reactivity of the neurons underlying the coil, such as polypharmacotherapy, and for other unknown reasons.Traditional TMS studies report on the impact of TMS on neural activity in specific brain regions and its impact on underlying connectivity and its alterations. Therefore, it is important to perform targeted measurements of functional connectivity and/or neural network and investigate how connectivity and network changes occur .Changes in the amplitude of motor evoked potentials (MEPs) elicited by transcranial magnetic stimulation are a suitable model to study the neurophysiology of rTMS and its effects on the brain, i.e., different ways in which rTMS stimulation protocols can be used therapeutically. The interindividual variability of the mean MEP response to rTMS has been investigated in many studies, leading to questions about the utility of this model. rTMS is able to modulate individual moment-to-moment variability in neuronal activity, and this may have implications for the therapeutic application of rTMS .The aim of this review is to use a non-standardized approach to measuring rTMS-induced neuroplasticity, including stimulation in the evening and the effects of rTMS on the sleep–wake rhythm of treated subjects.A literature search was conducted in March 2022 using the scientific databases PubMed and Google Scholar, covering publications from January 2003 to March 2022. Studies were identified by combinations of the following keywords in the title or abstract: rTMS, neuroplasticity, individual differences, variability, clinical predictors, sleep–wake rhythm, sleep, and EEG.The literature review was limited to published research articles written in English. In addition, to be included in this review, the identified articles had to be original studies or reviews on the effects of rTMS on various disorders and on possible clinical predictors or correlates of treatment outcomes when using rTMS. First, studies whose titles clearly indicated that they were unrelated to the topic were excluded. The abstracts of the remaining studies were then analyzed for relevance to the topic, which led to a second wave of exclusions. After exclusion at the title and abstract level, the remaining articles were thoroughly analyzed in full text, as well as their reference list screened, to identify relevant publications that were not covered by the search strategy. Ultimately, 17 studies that met the previously defined inclusion criteria were included in the literature review.For the treatment of depressive disorders, the left or right dorsolateral prefrontal cortex (DLPFC) is often the focus of repeated stimulation employed daily for 3–6 weeks by a strong, time-varying magnetic field (pulse duration 100–400 μs and intensity 1.5–2.5 Tesla) . This apAs stated in a recent study by Han and colleagues (2003), despite FDA approval of DLPFC-targeted rTMS for depression treatment 15 years ago, the precise mechanisms underlying its antidepressant effects remain elusive. To tackle this issue, the research team analyzed TMS-electroencephalogram (EEG) data from 64 healthy control (HC) subjects and 53 patients with major depressive disorder (MDD) pre- and post-rTMS treatment. The findings revealed that, prior to the treatment, patients with MDD exhibited lower activity in the DLPFC, hippocampus (HPC), and orbitofrontal cortex (OFC), as well as reduced DLPFC–OFC connectivity compared to HCs, as measured by the TMS-evoked potential (TEP) amplitude ratio of P60/N100, and local mean field amplitude area under the curve. Remarkably, post-active rTMS treatment, MDD patients showed significant increases in activity within the DLPFC, HPC, and OFC at the sensor level. Particularly, the enhancement in HPC activity through delta changes was closely associated with the alleviation of depressive outcome variables. The findings highlight the important role of the orbitofrontal–hippocampal pathway in the reduction of depressive symptoms following rTMS treatment, suggesting additional potential targets for brain stimulation in depression .Another large multicenter, placebo-controlled study also showed that deep TMS, a modified coil form with lower focality and thus higher penetration depth, as monotherapy was attempted in patients with 1–2 unsuccessful pharmacological treatments whose antidepressant effects were compared to placebo stimulation . InteresFurthermore, the interplay between rTMS and antidepressant medication has been the subject of multiple studies, with a focus on understanding their combined efficacy in treating MDD. Building on these studies, Wilke and colleagues (2022) conducted a retrospective analysis of patients with non-psychotic MDD undergoing rTMS treatment while on medication. The study focused on those using psychostimulants such as lisdexamfetamine/dextroamphetamine, methylphenidate/dexmethylphenidate, and modafinil/armodafinil. The findings indicated that patients taking psychostimulants experienced a significantly greater clinical improvement than those not on these medications during their rTMS treatment. The psychostimulant group showed significant enhancements in sleep and mood/cognition domains. Interestingly, smaller doses of lisdexamfetamine/dextroamphetamine correlated with better rTMS outcomes. Despite promising results, the authors cautioned that the study’s small sample size, limited data on psychostimulant use duration, and the lack of causal evidence necessitate further trials for solidifying the safety and efficacy of combining psychostimulants with rTMS .These studies underscore the promising potential of rTMS in both standalone and combined treatments for depression and the need for further research to fully understand the complexities and optimal applications of this therapy.In recent years, rTMS has received increasing attention as a therapeutic tool in treating psychiatric disorders and is even discussed as a treatment alternative to electroconvulsive therapy . Till daAlthough disturbances in neural maturation during the onset of schizophrenia suggest the presence of hypokinetic motor irregularities and potential malfunctions within the cerebral motor network associated with catatonia, a more comprehensive understanding is needed. Additional discussions have posited a decreased activity in the DLPFC and other areas of the brain. Nevertheless, contemporary consensus seems to gravitate toward hyperactivity within the pre-supplementary motor area (pre-SMA) and the supplementary motor area (SMA) as the principal causative factors underlying catatonia . MoreovePresently, the empirical support for utilizing rTMS as a therapeutic intervention for catatonia remains somewhat restricted to a series of case studies. Even though the pre-ponderance of these studies consists of relatively few cases, there is an emerging body of evidence suggesting that rTMS could be particularly potent in cases of refractory schizophrenic catatonia.To further consolidate these preliminary findings, there is an imperative need to conduct more extensive research. Future inquiries should focus on specific combinations of rTMS with pharmacotherapy or psychotherapy. Furthermore, understanding the neurobiological predictors of response, differential indications, and maintenance treatment could be invaluable in advancing this treatment modality, ultimately enhancing patient care and clinical outcomes.Although rTMS has been initially developed as a therapeutic tool for neurological and psychiatric disorders, it is now gaining progressive momentum in the area of sleep research . Sleep, Ultimately, research on the impact of rTMS on sleep, particularly in healthy individuals, is still in its early stages. Determining the optimal rTMS parameters, understanding individual differences in response, and elucidating the underlying neural mechanisms remain the ongoing areas of investigation with potential implications for populations with disordered sleep.The physiology of the sleep–wake cycle is characterized by cyclic oscillations of EEG activity, which are divided into non-rapid eye movement (NREM) and rapid eye movement (REM) sleep stages. Starting in the 1970s, numerous research studies began investigating the relationship between the K-complex and the delta waves of NREM sleep and the relationship between the K-complex and sleep cyclicity as a complex multifunctional phenomenon of the sleeping brain involved in information processing .Building on this understanding of NREM sleep and the intricate dynamics of brain activity it involves, more recent research has focused on the role of slow cortical oscillations  and thalamocortical spindle activity (12–15 Hz) during NREM sleep. This coupling is considered crucial for memory formation. Indeed, various neuromodulation techniques using slow oscillatory transcranial stimulation have been demonstrated to enhance functional cross-frequency coupling between memory-relevant brain oscillations. Notably, they have been shown to improve visual memory consolidation in patients with mild cognitive impairment (MCI), a precursor to Alzheimer’s disease . This beIn a separate but related development, techniques such as transcranial magnetic, electrical, and auditory stimulation are being applied in the treatment of sleep disorders. These methods have demonstrated utility in modulating arousal and sleep patterns, particularly in patients suffering from insomnia and hypersomnia, with implications for the broader improvement of mental health.Individuals suffering from insomnia typically exhibit persistent hyperarousal over a 24-h cycle, as well as a decrease in SWS and an increase in power of fast frequencies (within the EEG β-range) during NREM sleep . RemarkaA recent pilot study by Extrapolating from these findings, it becomes evident that the capacity to modulate sleep dynamics could have profound implications in psychiatric research and clinical practice. As our understanding of the complexities of sleep and its impact on cognitive and behavioral processes deepens, the prospective therapeutic benefits of sleep modulation across various mental disorders increasingly stand out as a pivotal area of research exploration.In the treatment of depression, partial and non-responses to rTMS are common, creating an ongoing quest to understand why responses to this neuromodulation treatment differ among patients . This chIn this regard, various studies have identified potential predictors of antidepressant response in structural alterations of both gray and white matter, particularly the reduced gray matter volumes in the insula, anterior cingulate, and the HPC . InteresIn addition, a recent cross-diagnostic meta-analysis conducted by In addition to the growing body of research that highlights the role of specific brain regions and their structural alterations in predicting the treatment response, there is also emerging evidence on the potential of neurophysiological measures serving as biomarkers. For instance, As we pivot toward a more personalized approach in psychiatric treatment, these findings gain significance. The burgeoning field of personalized medicine in psychiatry necessitates the identification of robust biomarkers that can reflect the function of the central nervous system at the neuronal activity level . These bIn this context, rTMS stands out due to its proven efficacy and its potential for individualized treatment approaches. Research has demonstrated the predictability of treatment response to rTMS based on brain activity patterns and the association of post-treatment changes in these patterns with the overall treatment response, particularly in depression . This suThe use of rTMS to trigger slow waves in humans holds promise for personalized treatment approaches. The elicitation of slow waves via TMS, dependent on the dosage and administration site, can significantly increase SWA across the scalp, possibly inducing a shift to a deep sleep stage . This fiIn summary, the application of rTMS to mental health disorders provides exciting opportunities for personalized treatment approaches, particularly through the identification and use of neurophysiological and neuroimaging biomarkers. As we continue to understand the role of brain activity in neuropsychiatric disorders, rTMS stands as a potential game-changer, enabling clinicians to tailor treatment strategies for individual patients and ultimately enhance treatment outcomes.


Natural and anthropogenic sources of metals in the ecosystem are perpetually increasing; consequently, heavy metal (HM) accumulation has become a major environmental concern. Human exposure to HMs has increased dramatically due to the industrial activities of the 20th century. Mercury, arsenic lead, chrome, and cadmium have been the most prevalent HMs that have caused human toxicity. Poisonings can be acute or chronic following exposure via water, air, or food. The bioaccumulation of these HMs results in a variety of toxic effects on various tissues and organs. Comparing the mechanisms of action reveals that these metals induce toxicity via similar pathways, including the production of reactive oxygen species, the inactivation of enzymes, and oxidative stress. The conventional techniques employed for the elimination of HMs are deemed inadequate when the HM concentration is less than 100 mg/L. In addition, these methods exhibit certain limitations, including the production of secondary pollutants, a high demand for energy and chemicals, and reduced cost-effectiveness. As a result, the employment of microbial bioremediation for the purpose of HM detoxification has emerged as a viable solution, given that microorganisms, including fungi and bacteria, exhibit superior biosorption and bio-accumulation capabilities. This review deals with HM uptake and toxicity mechanisms associated with HMs, and will increase our knowledge on their toxic effects on the body organs, leading to better management of metal poisoning. This review aims to enhance comprehension and offer sources for the judicious selection of microbial remediation technology for the detoxification of HMs. Microbial-based solutions that are sustainable could potentially offer crucial and cost-effective methods for reducing the toxicity of HMs. Heavy metals (HMs) are defined as metallic elements with a greater density than water . HMs areThe presence of HMs in composting materials poses a considerable obstacle to their utilization. Consequently, there has been a significant focus on mitigating the toxicity of HMs during the composting process. The composting of HMs primarily impacts microorganisms, and the toxicity levels of different HMs exhibit variability . VariousThe exposure of humans to HMs is a result of industrial activities and can manifest through various means, such as ingestion, inhalation, and dermal absorption . HMs areThe presence of HMs in the ecosystem is attributed to anthropogenic activities, which are the primary sources of human exposure to these substances . HMs areHMs have the potential to be conveyed to various locations on soil and water bodies via erosion, run-off, or acid rain. The diagram presented in Arsenic (As) is a hazardous metallic element that can be found in various geological formations, as well as in water and air. As exhibits carcinogenic properties in humans and is associated with various detrimental health outcomes in both the short and prolonged periods . The proMercury (Hg) is a hazardous HM that is ubiquitous in the environment. It has the potential to undergo methylation, leading to the formation of methylmercury (MeHg), which can accumulate in the food web. The consumption of seafood has been linked to human exposure to Hg . LipoperLead (Pb) is a toxic HM that has the tendency to accumulate in various tissues including blood, bones, and most body organs . ExposurThe accumulation of chromium (Cr) in body organs has been found to have potential implications for human health . Cr has Copper (Cu) is a vital micronutrient for humans. However, excessive levels of Cu can lead to toxic and harmful effects . The accNickel (Ni) is ubiquitously distributed in various environmental compartments such as air, water, and soil . The adv22+) has been observed to accumulate in kidney and bone tissues. This accumulation has been found to cause acute and chronic damage to the kidneys, while also increasing the likelihood of osteosarcoma and ontogenesis [Recent ecological research has examined the potential correlation between prolonged consumption of uranium (U) through drinking water and an elevated risk of leukemia as well as kidney, lung, and colorectal cancer in both genders . It has ogenesis . Exposurogenesis .Cadmium (Cd) is a toxic HM that has detrimental effects on human health . The impIron (Fe) is an essential element for various biological processes, including but not limited to DNA replication, mitochondrial respiration, and oxygen transport, that are crucial for the survival of almost all living organisms. Fe is a redox-active element that plays a role in the generation of ROS, which can cause damage to cellular membranes, DNA, and proteins . Fe is aVanadium (V) is present in various environmental compartments such as soil, water, and air. Various tissues and organs, such as the kidney, central nervous system, lung, lymphoid organs, and immune system, undergo histological and physiological changes as a result of this HM . ExposurCobalt (Co) is a mineral that occurs naturally and can be detected in over a hundred organic and inorganic compounds . The expThallium (TI) exhibits greater toxicity than Hg, Cd, and Pb . Chronic2+, As3+, Cd2+, As2+, and Pb2+). These states can effectively interact with biological molecules, including proteins and enzymes, to form robust and enduring bonds [Upon ingestion via food or water, HMs undergo acidification within the stomach’s acidic environment. Under acidic conditions, the aforementioned elements undergo oxidation and attain their respective oxidative states  can effectively create an optimal environment for the removal of heavy metals (HMs) from sludge . Sulfur-Extensive endeavors have been undertaken over a prolonged period to tackle the protracted persistence of HMs in the environment. Notwithstanding, the issue persists as a result of the increasing utilization of HM and the absence of feasible eradication remedies . In orde+) and electrons (e−), which subsequently culminates in the production of energy. The diagram presented in Microbial fuel cells (MFCs) are bio-electrochemical devices that facilitate the decomposition of organic waste into smaller molecules, thereby liberating protons  have demonstrated exceptional adsorption capabilities toward various HMs such as Cu, Pb, and Cr, owing to their potential adsorption active sites. The utilization of CNTs for the purpose of removing HMs from wastewater is impeded by the considerable expenses associated with their production, as well as the difficulty of isolating CNTs from the wastewater stream . The utiThe application of contemporary biotechnological techniques such as genetic engineering and recombinant DNA technology has expedited the process of biodegradation and remediation of HMs . MetagenThe issue of toxicity caused by HMs has emerged as a significant environmental challenge, with detrimental impacts on agricultural productivity and food security. The toxic effects of HMs result in their accumulation in the environment, which has adverse effects on human health, plant growth, and marine ecosystems. HMs can gain entry into the human body through various routes, such as ingestion via drinking water or food, inhalation through air, or through dermal exposure. After being absorbed, HMs are retained and accumulate within the human body. The accumulation of noxious metals in biological systems results in a range of deleterious consequences on diverse body tissues and organs. Various physical and chemical approaches have been suggested as potential remedies for the pollution caused by HMs. Nonetheless, the effectiveness of these techniques has been limited, and progress in this area has been slow. Therefore, alternative methodologies utilizing bioremediation have been explored. The employment of microbial bioremediation has emerged as an effective, reliable, and eco-friendly alternative for HM detoxification. However, HMs can interfere with the cellular activities of microorganisms depending on the existing concentration. The metal-tolerant microbes can enhance HM bioremediation. Microbes exhibit varying cellular structures, and their mechanisms for dealing with HM toxicity are typically dependent on the affinity of cellular biomolecules for metal ions and the stability of the specific metal in question. Microorganisms employ enzymatic systems or develop resistance through various mechanisms as a means of self-protection against HMs. However, the development of large-scale applications of combined remediation technology is recommended. In the context of practical application, one can acquire knowledge from both domestic and international experiences and enhance the judicious utilization of cutting-edge technologies. The mitigation of harmful effects caused by HMs necessitates the implementation of both scientific and community-based remediation technologies. Furthermore, forthcoming studies will derive advantages from assessing novel targets as protective procedures against organ toxicity triggered by HMs.


The growing pressure to identify and nurture talented athletes for adult competitions has led sports organizations to invest significant efforts in identifying markers of talent at increasingly younger ages , 2. InitA significant challenge in the pursuit of a reliable predictive model for adult performance is the emergence of the “biologic genotype,” which suggests that genetics plays a partial role in the physical, physiological, or anthropometric traits necessary for athletic success . This phThe first process is the phenotypic process of pubertal changes, namely growth and maturation. The significant influence of growth and maturation on body size, physical function and performance, psychological, social, and behavioral characteristics has been widely recognized , 12, 13.Longitudinal data monitoring of young athletes’ growth and development is scarce, and mostly limited to stature and body mass . InterprHowever, interpretations of the variation in size, performance, and behavior of young athletes associated with growth and maturity are mostly based on cross-sectional data. Prediction-based equations, such as the maturity offset equations , 25 or p“Quick fixes” to interpret maturity status and timing based on non-invasive estimates are limited , despiteRecently, the application of bio-banding in the talent development context of youth sports has been advocated and applied in professional clubs or academies in the search for young “elite” athletes . The appThe second bias is the phenomenon of Relative Age Effect (RAE). Albeit being the object of an extensive body of literature –40, RAE Unlike maturity status, RAE is easy to assess and offers a field for quantitative studies about the persistence of the phenomenon in adult sport. The observation of the RAE bias in the top levels of competition is highly dependent of the type of sport e.g., –39]. How. How39)]Our own research  revealedThe outcomes are more a consequence of the athletes’ responses to the training loads and to the ecologies of practice than determined by a particular characteristic like the birth quarter, maturity status or the year of engagement in talent development programs. Hence, the challenge remains to limit the potential bias associated to RAE on young athletes selection/exclusion, particularly at early ages.The third bias is represented by the interaction between maturation and the training load. We focus on two issues: influence of training exposure on developmental changes in performance, and monitoring training loads and maturity status.Coaches and researchers know that metabolic capacities are altered and enhanced by continued training through biological adaptations. When measuring of developmental changes during the specialization years, the maturation process acts as a confounding factor when interpreting eventual improvements in performance associated to training exposure . FurtherOn the other hand, researchers are well aware of the obstacles raised by the multidimensional nature of performance and by the demands of each specific sport , 4, 46. There is a large body of data describing training loads monitoring in talent development environments, particularly in youth football . Recentl(i)Adopting open-science and data sharing practices, allowing to overcome the expected small samples sizes reported, and combination of different sources of information;(ii)Go beyond statements about the limits of non-invasive predictive methods of somatic maturity status, and explore advanced modeling approaches to include information and critically assess the models and inferences;(iii)Consider theoretical lenses to frame questions, models and interpretations of potential mismatches between young athletes, and within-athlete development.To allow meaningful interpretations of young talented athletes data, we focus our suggestion to researches on three key issues:The potential biases associated to growth, maturation, RAE and training loads are especially challenging for coaches, who must evaluate their athletes’ performances on a daily basis. Furthermore, the decisions made by coaches, as perceived by young athletes, are not limited to selection or exclusion but also involve micro-management of training sessions and competitions . On the other hand, the structures of talent development settings vary in terms of their human resources, sport types, and overall organization. In professional sports, talent development facilities have the capacity to recruit, support, and prepare the best prospects, and professional coaches are likely to benefit from the counseling of a performance analysis team. Even in such situations, the traps of maturity status and RAE are still present and can lead to decisions made without scientific or logical basis.