Response Of System Research Articles

Soluble immune checkpoint molecules in cancer risk, outcomes prediction, and therapeutic applications.

Immunotherapy has emerged as a pivotal modality in cancer treatment, with immune checkpoint inhibitors effectively combating malignancies by impeding crucial pathways within the immune system and stimulating patients' immune responses. Soluble forms of immune checkpoints exhibit a remarkable diversity and can be readily tracked in circulation, holding immense potential as biomarkers for cancer treatment. An increasing number of studies focused on soluble immune checkpoints in cancer have emerged thanks to technological advancements. In this systematic review, we comprehensively summarized the recent studies on soluble immune checkpoints in human cancer risk prediction, outcome prediction, therapeutic applications, and potential molecular mechanisms, which demonstrated the promising future of soluble immune checkpoints in clinical applications. The clinical relevance of soluble immune checkpoints has been recognized in multiple cancers, yet the therapeutic applications and mechanisms remain obscure. Interpreting the impacts and mechanisms of soluble immune checkpoints could shed a light on the novel strategies of cancer screening, treatments, and outcome prediction.

Processor in the loop implementation of Artificial neural network controller for BLDC motor speed control

This paper's goal is to use a proportional integral derivative controller and an artificial neural network controller (ANNC) to control the speed of a BLDC motor. The outcomes of the MATLAB/SIMULINK simulation are used as the basis for comparing the two controllers. On the other hand, the ANNC makes the BLDC motor's reaction more consistent and dependable. In other words, it reduces peak time, overshoot, and settle time while speeding up system responses. ANNC is implemented in Processor in the Loop (PIL) experimenting with Arduino Mega. It is based on the generated C-code and executed it in the embedded card. The experiment's outcomes match those of the MATLAB/SIMULINK simulation.

Cardiological and Psychophysiological Reaction of Schoolchildren with Different Types of Central Gemodynamics to Prolonged Physical Activity

The present paper considers the issues of optimizing the construction of a lesson of recreational physical education by differentiating the load on the basis of data on the physical fitness of students. It also touches upon the question of the response of stress-realizing systems of schoolchildren to the physical work performed. The aim of the study is to investigate the cardiologic and psychophysiologic response of schoolchildren with different types of central hemodynamics to prolonged physical workload. Methodology. Cardiologic and psychophysiologic parameters of 74 male students aged 12–13 years were studied. The sample included only practically healthy individuals without severe chronic and acute diseases. All students were divided into three groups by physical fitness (based on the results of the PWC170 test) and three subgroups by the type of central hemodynamics (according to N.N. Savitsky: hypokinetic, eukinetic, hyperkinetic). Heart rate and attention response to running exercise of different durations with excellent rest intervals and response were evaluated. Conclusion. The results obtained indicate different reactions of schoolchildren with different types of central hemodynamics to prolonged physical load: the hypokinetic type had stable heart rate values during the load, better recovery after the load and the least decrease in attention according to the B. Bourdon test. The hyperkinetic type, on the contrary, had unstable dynamics of heart rate during exercise, the lowest rate of heart rate recovery and a pronounced decrease in attention. The eukinetic type had average performance on all tests. The results of the study can be used as a tool to optimize the methodology of the educational process through the most effective dosing of the load.

MicroRNA bmo-miR-31-5p inhibits apoptosis and promotes BmNPV proliferation by targeting the CYP9e2 gene of Bombyx mori.

Bombyx mori nuclear polyhedrosis virus (BmNPV), as a typical baculovirus, is the primary pathogen that infects the silkworm B. mori, a lepidopteran species. Owing to the high biological safety of BmNPV in infecting insects, it is commonly utilized as a biological insecticide for pest control. Apoptosis is important in the interaction between the host and pathogenic microorganisms. MicroRNAs (miRNAs) influence immune responses and promote stability of the immune system via apoptosis. Therefore, the study of apoptosis-related miRNA in silkworms during virus infection can not only provide support for standardizing the prevention and control of diseases and insect pests, but also reduce the economic losses to sericulture caused by the misuse of biological pesticides. Through transcriptome sequencing, we identified a miRNA, miR-31-5p, and demonstrated that it can inhibit apoptosis in silkworm cells and promote the proliferation of BmNPV in BmE-SWU1 cells. We identified a target gene of miR-31-5p, B. mori cytochrome P450 9e2 (BmCYP9e2), and demonstrated that it can promote apoptosis in silkworm cells and inhibit the proliferation of BmNPV. Moreover, we constructed transgenic silkworm strains with miR-31-5p knockout and confirmed that they can inhibit the proliferation of BmNPV. These data indicate that miR-31-5p may exert functions of inhibiting apoptosis and promoting virus proliferation by regulating BmCYP9e2. The findings demonstrate how miRNAs influence host cell apoptosis and how they are involved in the host immune system response to viruses, providing important insights into the applications of biological insecticides for pest control. © 2024 Society of Chemical Industry.

Review on Monoclonal Antibodies (mAbs) as a Therapeutic Approach for Type 1 Diabetes.

Monoclonal antibodies have been successfully utilized in a variety of animal models to treat auto-immune illnesses for a long time. Immune system responses will either be less active or more active depending on how the immune system is operating abnormally. Immune system hypoactivity reduces the body's capacity to fight off various invading pathogens, whereas immune system hyperactivity causes the body to attack and kill its own tissues and cells. For maximal patient compliance, we will concentrate on a variety of antibody therapies in this study to treat Type 1 diabetes (an autoimmune condition). T-cells are responsible for the auto-immune condition known as T1D, which causes irregularities in the function of β-cells in the pancreas. As a result, for the treatment and prevention of T1D, immunotherapies that selectively restore continuous beta cellspecific self-tolerance are needed. Utilizing monoclonal antibodies is one way to specifically target immune cell populations responsible for the auto-immune-driven disease (mAb). Numerous mAbs have demonstrated clinical safety and varied degrees of success in modulating autoimmunity, including T1D. A targeted cell population is exhausted by mAb treatments, regardless of antigenic specificity. One drawback of this treatment is the loss of obtained protective immunity. Immune effector cell function is regulated by nondepleting monoclonal antibodies (mAb). The antigenfocused new drug delivery system is made possible by the adaptability of mAbs. For the treatment of T1D and T-cell-mediated autoimmunity, different existing and potential mAb therapy methods are described in this article.

Safety and efficacy of intra-erythrocyte dexamethasone sodium phosphate in children with ataxia telangiectasia (ATTeST): a multicentre, randomised, double-blind, placebo-controlled phase 3 trial

Ataxia telangiectasia is a multisystem disorder with progressive neurodegeneration. Corticosteroids can improve neurological functioning in patients with the disorder but adrenal suppression and symptom recurrence on treatment discontinuation has limited their use, prompting the development of novel steroid delivery systems. The aim of the ATTeST study was to evaluate the efficacy and safety of intra-erythrocyte delivery of dexamethasone sodium phosphate compared with placebo in children with ataxia telangiectasia. This multicentre, randomised, double-blind, placebo-controlled, phase 3 trial was done at 22 centres in 12 countries (Australia, Belgium, Germany, India, Israel, Italy, Norway, Poland, Spain, Tunisia, the UK, and the USA). Eligible participants were children aged 6 years or older weighing more than 15 kg who met clinical criteria for ataxia telangiectasia but who had preserved autonomous gait. Participants were randomly assigned (1:1:1) to low-dose (approximately 5-10 mg), or high-dose (approximately 14-22 mg) intra-erythrocyte dexamethasone sodium phosphate, or placebo, using an independent interactive web response system, with minimisation for sex and age (6-9 years vs ≥10 years). Intravenous intra-erythrocyte dexamethasone sodium phosphate was administered once a month for 6 months. Participants, employees of the sponsor, investigators, all raters of efficacy endpoints, and central reviewers were masked to treatment assignment and dose allocations. The primary efficacy endpoint was change in the modified International Cooperative Ataxia Rating Scale (mICARS) from baseline to month 6, assessed in the modified intention-to-treat (mITT) population, which included all randomly assigned participants who received at least one dose of study drug and had at least one post-baseline efficacy assessment. This trial is registered with Clinicaltrials.gov (NCT02770807) and is complete. Between March 2, 2017, and May 13, 2021, 239 children were assessed for eligibility, of whom 176 were randomly assigned. One patient assigned to high-dose intra-erythrocyte dexamethasone sodium phosphate did not initiate treatment. 175 patients received at least one dose of treatment (59 patients received the low dose and 57 received the high dose of intra-erythrocyte dexamethasone sodium phosphate, and 59 received placebo). The mITT population comprised 164 participants (56 children in the low-dose group, 54 children in the high-dose group, and 54 in the placebo group). Compared with the placebo group, no differences were identified with regard to change in mICARS score from baseline to 6 months in the low-dose group (least squares mean difference -1·37 [95% CI -2·932 to 0·190]) or the high-dose group (-1·40 [-2·957 to 0·152]; p=0·0765). Adverse events were reported in 43 (73%) of 59 participants in the low-dose group, 47 (82%) of 57 participants in the high-dose group, and 43 (73%) of 59 participants in the placebo group. Serious adverse events were observed in six (10%) of 59 participants in the low-dose group, seven (12%) of 57 participants in the high-dose group, and seven (12%) of 59 participants in the placebo group. There were no reports of hyperglycaemia, hypertension, hirsutism, or Cushingoid appearance in any of the treatment groups, nor any treatment-related deaths. Although there were no safety concerns, the primary efficacy endpoint was not met, possibly related to delays in treatment reducing the number of participants who received treatment as outlined in the protocol, and potentially different treatment effects according to age. Studies of intra-erythrocyte delivery of dexamethasone sodium phosphate will continue in participants aged 6-9 years, on the basis of findings from subgroup analyses from this trial. EryDel and Quince Therapeutics.

Virtual vibration test rig for fatigue analysis of dozer push arms

AbstractTo obtain accurate fatigue life results for construction machinery components, acquiring load spectra is crucial, as their authenticity and validity directly determine the precision of the analysis. In working conditions, component attitudes change continuously, but they remain static on the vibration test rig (VTR), so the acquired target signals should match with the actual component attitudes in the driving signal generation. This paper proposes an efficient and economical simulation‐based virtual VTR for fatigue analysis of dozers. First, the relationship between the push arm rotation angle and the cylinder stroke is established, since the cylinder strokes can be measured easily in data acquisition experiments. Second, load decomposition is used to determine the attitude relationship between virtual VTR conditions and actual conditions, and target signals are calculated based on this attitude relationship and measured data. According to the system's frequency response function, the driving signals are iterated until the system's response signals converge with the target signals. Finally, the iteratively obtained load spectra are utilized for fatigue life analysis. The results show that the virtual VTR can effectively and accurately obtain the results of fatigue analysis and has engineering application significance.

A Brief History of Polyclonal Antibody Therapies Against Bacterial and Viral Diseases Before COVID-19.

The use of the serum or plasma of patients or animals who have recovered from an infectious disease, or had been immunized with a relevant antigen, to treat or prevent the same infection in others began in the late 1880s when French and German scientists uncovered, one step at a time, several of the elements of the immune system's response to infection. A key finding was that the damage caused by some bacteria depends upon their secreted toxins which can be neutralized by biologic agents. Antitoxins to diphtheria and tetanus began to be manufactured in large animals in France, Germany, and the US in the 1890s and were soon being used worldwide. The impact of diphtheria antitoxin on childhood mortality was profound. Shortly after the development of antitoxins, convalescent serum began to be used for its anti-bactericidal properties thus addressing serious infections caused by non-toxin-producing organisms. The effectiveness of antitoxins and antisera was demonstrated by examining mortality rates in hospitals before and after the introduction of antitoxins, by comparisons of treated and untreated patients, by comparing early and late treatment and dosage, by examining vital data mortality trends, and by several randomized and alternate assignment trials. Antitoxins continue to have a role in the rare cases of diphtheria and other conditions largely eradicated by immunization, but serum therapy nearly disappeared from the medical armamentarium with the development of antibiotics in the 1940s. Inasmuch as new human pathogens are now emerging with unprecedented regularity as seen in the recent COVID-19 pandemic, and because specific therapies are unlikely to be available for them, plasma-based antibody therapies are likely to again carve out a niche in infectious disease control.

Global stability analysis, stabilization and synchronization of an SEIR epidemic model

In this paper, we investigate an SEIR epidemic model in which recruitment is assumed to be regulated by a constant function. The SEIR model is a widely-used epidemiological framework that categorises the population into four distinct groups: Susceptible, Exposed, Infectious, and Removed. It employs a system of differential equations to describe the transitions of individuals among these groups, making it a valuable tool for understanding and modelling the dynamics of infectious diseases. Mathematical analysis is used to study the dynamic behaviour of this model. We first determine the basic reproduction number, denoted as R 0 , which governs the dynamics of the SEIR model. Our findings reveal that when R 0 is less than 1, the unique disease-free equilibrium is asymptotically stable, and there is no endemic equilibrium. However, when R 0 exceeds 1, the disease-free equilibrium becomes unstable, and a unique, asymptotically stable endemic equilibrium emerges. Furthermore, by constructing appropriate Lyapunov functions, we have studied the global asymptotic stability of the two equilibrium points. On the other hand, we have used the backstepping method to design a control law that stabilises the SEIR model towards the disease-free equilibrium, which means the eradication of the disease from the target population. Next, we have used the same method to synchronise the SEIR drive system and the SEIR response system. This method is used to stabilise the synchronisation error dynamics arising from the mismatch between the drive and response systems. Finally, we presented numerical simulations to illustrate the theoretical results.

PSO based linear parameter varying-model predictive control for trajectory tracking of autonomous vehicles

In this paper, Linear Parameter Varying-Model Predictive Control (LPV-MPC) for trajectory tracking for Autonomous Vehicles (AVs) is proposed. This method is based on the time-varying LPV is the form of the state space representation from the mathematical model of the vehicle. The LPV representation form which uses the dynamic model of the vehicle allows the incorporation of time-varying dynamics, providing a more accurate representation of the vehicle's behavior. The designed LPV-MPC controller for AVs is specifically designed to handle constraints in trajectory tracking. To enhance its performance, Particle Swarm Optimization (PSO) is employed as an optimization technique. PSO is used to tune the weighting matrices of the control parameters, optimizing the system response and improving trajectory tracking performance. To evaluate the effectiveness of the LPV-MPC system, extensive simulations are conducted and results are compared with Linear and Non-Linear MPCs. The main benefit of using the LPV-MPC method is its ability to calculate solutions almost as good as the non-linear MPC version yet significantly reducing the computational cost. The capability of the LPV-MPC controller as compared to the linear version is in its effective tracking, particularly for the non-linear reference trajectories.

Pupillometry and autonomic nervous system responses to cognitive load and false feedback: an unsupervised machine learning approach

Pupillometry and autonomic nervous system responses to cognitive load and false feedback: an unsupervised machine learning approach

The ventilator of the future: key principles and unmet needs.

Persistent shortcomings of invasive positive pressure ventilation make it less than an ideal intervention. Over the course of more than seven decades, clinical experience and scientific investigation have helped define its range of hazards and limitations. Apart from compromised airway clearance and lower airway contamination imposed by endotracheal intubation, the primary hazards inherent to positive pressure ventilation may be considered in three broad categories: hemodynamic impairment, potential for ventilation-induced lung injury, and impairment of the respiratory muscle pump. To optimize care delivery, it is crucial for monitoring and machine outputs to integrate information with the potential to impact the underlying requirements of the patient and/or responses of the cardiopulmonary system to ventilatory interventions. Trending analysis, timely interventions, and closer communication with the caregiver would limit adverse clinical trajectories. Judging from the rapid progress of recent years, we are encouraged to think that insights from physiologic research and emerging technological capability may eventually address important aspects of current deficiencies.

Metrics for quantifying the efficiency of atmospheric CO2 reduction by marine carbon dioxide removal (mCDR)

Abstract Marine carbon dioxide removal (mCDR) is gaining interest as a tool to meet global climate goals. Because the response of the ocean-atmosphere system to mCDR takes years to centuries, modeling is required to assess the impact of mCDR on atmospheric CO2¬ reduction. Here, we use a coupled ocean-atmosphere model to quantify the atmospheric CO2 reduction in response to a CDR perturbation. We define two metrics to characterize the atmospheric CO2 response to both instantaneous ocean alkalinity enhancement (OAE) and direct air capture (DAC): the cumulative additionality (α) measures the reduction in atmospheric CO2 relative to the magnitude of the CDR perturbation, while the relative efficiency () quantifies the cumulative additionality of mCDR relative to that of DAC. For DAC, α is 100% immediately following CDR deployment, but declines to roughly 50% by 100 years post-deployment as the ocean degasses CO2 in response to the removal of carbon from the atmosphere. For instantaneous OAE, α is zero initially and reaches a maximum of 40-90% several years to decades later, depending on regional CO2 equilibration rates and ocean circulation processes. The global mean  approaches 100% after 40 years, showing that instantaneous OAE is nearly as effective as DAC after several decades. However, there are significant geographic variations, with  approaching 100% most rapidly in the low latitudes while  stays well under 100% for decades to centuries near deep and intermediate water formation sites. These metrics provide a quantitative framework for evaluating sequestration timescales and carbon market valuation that can be applied to any mCDR strategy.

On the Assessment of Reinforced Concrete (RC) Walls under Contact/Near-Contact Explosive Charges: A Deep Neural Network Approach

In recent years, the use of machine learning has been expanded to several fields, with promising advances in structural engineering applications. Deep neural network models have been implemented to predict the structural response of systems under conventional loading. Some of those neural network models are based on datasets containing images, test data, and/or data produced by using finite element models developed for a specific environment. While the accuracy of these models relies on the size and quality of the dataset, their use for blast analysis is rather limited, as publicly available data are scarce or restricted. Reinforced concrete (RC) walls or slabs under blast loading are commonly evaluated for flexural and shear behaviour, for which performance guidelines are widely available. While such response mechanisms are typically associated with the far-field range, the target response is controlled by local failure modes when blast loads are generated by contact or near-contact detonations. This paper introduces the implementation of a neural network model for the response prediction of RC walls subjected to contact and near-contact explosions. The model predicts the damage category (i.e., no damage, spall, and breach) associated with a given explosion scenario. The model is trained using experimental data from multiple test programmes available in open-source literature. It considers several parameters associated with the explosive charge (e.g., type, geometry, charge weight, and standoff) and RC target (e.g., material properties, geometry, and reinforcement). The model is able to accurately predict 81% of the total breached specimens, 66% of the total spalled specimens, and 71% of the full set of non-damaged specimens, with an overall accuracy of 72%, with precision and recall ranging from 60 to 76% and 66 to 81%, respectively. The current model is shown to be a significantly better predictor of the damage category than the semi-empirical approach outlined in UFC 3-340-02, making it a promising tool that can be improved with the inclusion of more experimental data.

Dimensional Self‐Assembled Magnetic Coupling via Embedding Ferromagnetic Nanoparticles in Multi‐Channel Fibers for Microwave Absorption

Abstract1D magnetic fibers with significant morphological diversity and magnetic anisotropy are highly desirable for optimizing magnetic properties and electromagnetic responsiveness. However, it remains challenging for the precise control over internal magnetic interactions within each fiber. Herein, a strategy for self‐assembled magnetic coupling is taken to achieve the controllable reconstruction of continuous multiple coupling networks within a single fiber. High‐density ultrafine cobalt nanoparticles are uniformly embedded inside a carbon framework with a 1D multi‐channel structure (Co@MCF). This structure establishes a complex magnetic response system characterized by inherent inter‐fiber interactions and refined intra‐fiber self‐assembling coupling. The distinctive distribution of magnetic flux lines demonstrates enhanced magnetic sensitivity. This results in a minimum reflection loss of −57.65 dB and a broadband absorption frequency range of 7.28 GHz at 1.9 mm, effectively covers the entire Ku band and a substantial portion of the X band. The multi‐channel structure enhances the understanding of the relationship between microstructure and performance in magnetic fibers. Additionally, it positions Co@MCF as a highly competitive candidate for microwave absorption applications.

Multi-method piecewise low-frequency identification

Inter-area frequency modes of electromechanical oscillations are decisive factors that influence the performance of electrical power systems. However, the accurate estimation of these frequencies remains a challenge due to the non-linear behavior of the response system following a disturbance and the strong coupling among the frequencies. This work describes a curve fitting and electromechanical frequency estimation algorithm, called Multi-method Piecewise Identification (MPI), based on a combination of the Matrix Pencil Method (MPM), the Prony method, and Subspace Identification (SSI), choosing the best approximation of an interval basis according to the model accuracy index (MAI) and the mean square error (MSE). The advantages and limitations of MPI were analyzed by computational analyses that were carried out with Python-based code that estimates the low frequencies for several ringdown signals, including oscillating signals from Australian and Brazilian systems that arise after large disturbances. To ensure robustness to random and noisy conditions, the method was tested with a synthetic signal with Gaussian white noise and time-variant frequencies, and compared to the methods mentioned above, the Hilbert–Huang Transform (HHT), and Eigensystem Realization Algorithm (ERA). The MPI has shown robust results and is capable of obtaining a better fitting for the signal than the other methods.

Association of Unc-51-like Kinase 4 (ULK4) with the reactivity of the extended reward system in response to conditioned stimuli

Objectives ULK4 is an established candidate gene for mental disorders and antipsychotic treatment response. We investigated the association of functional genetic variation at the ULK4 locus with the human extended dopaminergic reward system using fMRI during the performance of a well-established reward paradigm. Methods Two hundred and thirty-four patients were included in this study. Association of genetic variation in the ULK4 gene with reward system functioning were determined using the Desire-Reason-Dilemma (DRD) paradigm which allows to assess brain activation in response to conditioned reward stimuli. Results Variant prioritisation revealed the strongest functional signatures for the ULK4 variant rs17215589, coding for amino acid exchange Ala715Thr. For rs17215589 minor allele carriers, we detected increased activation responses to conditioned reward stimuli in the ventral tegmental area, nucleus accumbens and several cortical brain regions of the extended reward system. Conclusions Our findings provide further evidence in humans that genetic variation in ULK4 may increase the vulnerability to mental disorders, by modulating the extended reward system function. Future studies are needed to confirm the modulation of the extended reward system by ULK4 and to specify the role of this mechanism in the pathogenesis of psychiatric disorders.

The Possibility of Detrimental Effects on Soil–Structure Interaction in Seismic Design Due to a Shift in System Frequency

Soil–structure interaction (SSI) leads to a modification in the dynamic properties of structure, but due to the complexity of analysis, it is traditionally assumed in seismic designs that the structure is fixed-supported on the ground, which brings about potential risks to the seismic performances of structure. The study works on the possibility of SSI having detrimental effects by comparing the dynamic responses of the SSI system to a fixed-base structure, and presents charts for an evaluation of the system frequency of SSI for the purpose of engineering practice. In order to reveal the physical nature, the SSI model is reduced to its simplest form, consisting of a SDOF oscillator, a three-dimensional rectangular foundation, and a multi-layered half-space. The energy dissipation in the soil is achieved by foundation impedances and the substructure method. Previously, the foundation impedances are usually acquired by two-dimensional or axisymmetric three-dimensional models in uniform half-space to avoid the high cost of the more realistic, fully 3D models, while a high-precision indirect boundary element method is employed, combined with the non-singular Green’s functions of distributed loads to calculate the foundation impedances. Although SSI dampens the peak amplitude of structure response in the frequency domain, case studies on four buildings’ responses to 42 earthquakes in the time history show a possibility of 15–20% that SSI amplifies the dynamic responses of structures, such as the maximum and the mean values in the time history, depending on the properties of the structures and the site, as well as the frequency component of incident waves.

Supporting children and young people affected by domestic abuse in Wales: a multiagency perspective on existing responses in the school system

ABSTRACT Children and young people (CYP) who experience domestic abuse are at greater risk of negative outcomes in adult life. In Wales, an emphasis is placed on a multiagency response to domestic abuse, and there is growing interest in the role of schools in prevention and intervention. A mixed-methods design was adopted to explore the views of professionals on the current response to domestic abuse. Questionnaires were completed by 36 schools in Wales, and a series of focus groups was held with CYP workers from specialist domestic abuse settings and from school and social work staff. Data were analysed using descriptive statistics and reflexive thematic analysis. Four overarching themes were developed. Findings illustrate that, whilst there are a variety of interventions and support available for CYP who have experienced domestic abuse, an effective response is impacted by the systems in place to respond to it. It is argued that current practice needs to be more radical if meaningful change is to take place for CYP and their families. Implications for practice are discussed, including the role of the educational psychologist (EP).

A new hybrid fixed and adaptive gains control algorithm to reduce power losses on LLCL filter-based renewable energy conversion systems with systematic parametrization using Grey Wolf optimizer

Currently, there is a transition in the energy matrix around the world, where traditional sources of energy generation are continually being replaced by energy generation systems based on renewable sources to mitigate the climate crisis. In this bias, this work presents the mathematical modeling of an LLCL filter, used to connect power generation systems based on renewable energy sources to the electrical grid, and presents a novel hybrid fixed-and adaptive gains control strategy for current injection into the grid using this system. The developed hybrid controller is composed of a proportional–integral controller and a direct robust adaptive controller. The first term of the controller guarantees the reference current, while the second term of the controller is used for disturbance rejection. Furthermore, a systematic procedure for the controller’s parametrization based on Grey Wolf Optimizer is also provided. The control of the current injected into the grid is carried out considering the LLCL filter without passive damping resistors in the filter structure to avoid power losses due to the passive filter elements. Additionally, the LLCL filter model considers minimal parasitic resistances to evaluate the controller’s performance and optimize it for the application of interest, aiming to maximize the system performance by ensuring a short transient regime due to the fast closed-loop system response. Simulation results indicate high performance of this optimized control strategy with small tracking error even considering grid impedance variations.