Response Of System Research Articles

Review of Development and Characteristics Research on Electro-hydraulic Servo System

Background: The nonlinear problem of the electro-hydraulic servo system directly affects the system accuracy, response speed and other indicators, and the resulting problems of control inaccuracy and response delay urgently need to be solved. Method: This article provides an overview of the working principle of electro-hydraulic servo systems, reviews the development history of electro-hydraulic servo systems, and summarizes the current research difficulties and latest patents of electro-hydraulic servo systems from the characteristics of active and passive loading systems,electro-hydraulic servo system multi flexibility characteristics, gap nonlinearity,parameter time-varying characteristics,mathematical modeling,force tracking accuracy control strategy, etc. Result: A large number of scholars have proposed the latest optimization strategies to address the nonlinear problems in various aspects of the electro-hydraulic servo system, effectively improving the control accuracy and static and dynamic characteristics of the electro-hydraulic servo system. Conclusion: By summarizing the latest progress in the study of nonlinear problems in various links of electro-hydraulic servo systems, it has played a guiding role in their future improvement and optimization strategies.

Exosomal MicroRNAs modulate the cognitive function in fasudil treated APPswe/PSEN1dE9 transgenic (APP/PS1) mice model of Alzheimer's disease.

Alzheimer's disease (AD) is characterized by cognitive decline stemming from the accumulation of beta-amyloid (Aβ) plaques and the propagation of tau pathology through synapses. Exosomes, crucial mediators in neuronal development, maintenance, and intercellular communication, have gained attention in AD research. Yet, the molecular mechanisms involving exosomal miRNAs in AD remain elusive. In this study, we treated APPswe/PSEN1dE9 transgenic (APP/PS1) mice, a model for AD, with either vehicle (ADNS) or fasudil (ADF), while C57BL/6 (control) mice received vehicle (WT). Cognitive function was evaluated using the Y-maze test, and AD pathology was confirmed through immunostaining and western blot analysis of Aβ plaques and phosphorylated tau. Exosomal RNAs were extracted, sequenced, and analyzed from each mouse group. Our findings revealed that fasudil treatment improved cognitive function in AD mice, as evidenced by increased spontaneous alternation in the Y-maze test and reduced Aβ plaque load and phosphorylated tau protein expression in the hippocampus. Analysis of exosomal miRNAs identified three miRNAs (mmu-let-7i-5p, mmu-miR-19a-3p, mmu-miR-451a) common to both ADNS vs ADF and WT vs ADNS groups. Utilizing miRTarBase software, we predicted and analyzed target genes associated with these miRNAs. Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of miRNA target genes indicated that mmu-miR-19a-3p and mmu-miR-451a are implicated in signal transduction, immune response, cellular communication, and nervous system pathways. Specifically, mmu-miR-19a-3p targeted genes involved in the sphingolipid signaling pathway, such as Pten and Tnf, while mmu-miR-451a targeted Nsmaf, Gnai3, and Akt3. Moreover, mmu-miR-451a targeted Myc in signaling pathways regulating the pluripotency of stem cells. In conclusion, fasudil treatment enhanced cognitive function by modulating exosomal MicroRNAs, particularly mmu-miR-451a and mmu-miR-19a-3p. These miRNAs hold promise as potential biomarkers and therapeutic targets for novel AD treatments.

Computational modeling of the synergistic role of GCN2 and the HPA axis in regulating the integrated stress response in the central circadian timing system.

The circadian timing system and integrated stress response (ISR) systems are fundamental regulatory mechanisms that maintain body homeostasis. The central circadian pacemaker in the suprachiasmatic nucleus (SCN) governs daily rhythms through interactions with peripheral oscillators via the hypothalamus-pituitary-adrenal (HPA) axis. On the other hand, ISR signaling is pivotal for preserving cellular homeostasis in response to physiological changes. Notably, disrupted circadian rhythms are observed in cases of impaired ISR signaling. In this work, we examine the potential interplay between the central circadian system and the ISR, mainly through the SCN and HPA axis. We introduce a semimechanistic mathematical model to delineate SCN's capacity for indirectly perceiving physiological stress through glucocorticoid-mediated feedback from the HPA axis and orchestrating a cellular response via the ISR mechanism. Key components of our investigation include evaluating general control nonderepressible 2 (GCN2) expression in the SCN, the effect of physiological stress stimuli on the HPA axis, and the interconnected feedback between the HPA and SCN. Simulation revealed a critical role for GCN2 in linking ISR with circadian rhythms. Experimental findings have demonstrated that a Gcn2 deletion in mice leads to rapid re-entrainment of the circadian clock following jetlag as well as to an elongation of the circadian period. These phenomena are well replicated by our model, which suggests that both the swift re-entrainment and prolonged period can be ascribed to a reduced robustness in neuronal oscillators. Our model also offers insights into phase shifts induced by acute physiological stress and the alignment/misalignment of physiological stress with external light-dark cues. Such understanding aids in strategizing responses to stressful events, such as nutritional status changes and jetlag.NEW & NOTEWORTHY This study is the first theoretical work to investigate the complex interaction between integrated stress response (ISR) sensing and central circadian rhythm regulation, encompassing the suprachiasmatic nucleus (SCN) and hypothalamus-pituitary-adrenal (HPA) axis. The findings carry implications for the development of dietary or pharmacological interventions aimed at facilitating recovery from stressful events, such as jetlag. Moreover, they provide promising prospects for potential therapeutic interventions that target circadian rhythm disruption and various stress-related disorders.

Supply Chain System Optimization Model for Logistics Enterprises in the Internet of Things Era Based on Improved ECC Algorithm

In this article, a new method to optimize the supply chain system (SCS) of logistics companies in the era of Internet of Things (IoT) using an improved elliptic curve cryptography (ECC) algorithm was put forward.The focus of this research was to address the challenges faced by logistics organizations in adapting to the complexity of modern supply chains and meeting the growing demands of customers. The research aimed to improve the efficiency, security and reliability of supply chain management systems by utilizing advances in ECC algorithms.By conducting comprehensive performance tests of the proposed system, including interface testing, joggle testing, and system response time analysis, the study demonstrated the superiority of the system over traditional systems. The research findings indicated that the system based on the improved ECC algorithm outperformed traditional systems in terms of interface effectiveness, usability, and system response time. The improved ECC algorithm enhanced the security of the encryption process, making it more resistant to unauthorized access, and improved the system’s overall data processing load capacity. Additionally, the system demonstrated superior performance in managing logistics data and information, facilitating better decision-making and efficiency in logistics operations. Overall, this research contributes to the advancement of supply chain management in the IoT era by providing a practical and efficient solution for logistics enterprises to optimize their supply chain systems. The innovative application of the improved ECC algorithm offers a secure, reliable, and efficient approach to managing logistics operations, addressing the challenges posed by the complexities of modern supply chains.

Building a Responsive Legal System Through Reforming the Indonesian Constitution

Legal politics or what is known as policy direction is important in order to provide direction on the form and material of law. However, in a study that examines the problems of law enforcement, in Indonesia, which was studied from a legal sociology perspective, it was stated that developments in the world today often give rise to various problems, whether in the form of violations of norms that exist in social life or rules that have a tendency to create a phenomenon that is contrary to moral and ethical rules as well as legal rules. This paper aims to find out the facts and legal political realities that occur on post-reform legislation in forming responsive laws. Using a normative writing method. The direction of legal politics in post-reform Indonesia is the desire to form a responsive legal system, this can be implicitly seen in several changes to the constitution. Change towards responsive law is not something instant and easy, there must be a commitment from the state and the people together to realize the ideal of this system. Although the current implementation of law still experiences many errors here and there, at least the existing legal products have led to laws that responsive, what is needed now are leadership figures who are able to bring Indonesia to the implementation of responsive laws that are in accordance with what was previously expected in order to achieve prosperity for the people.

Fluid-structure coupling analysis in liquid-filled containers using scaled boundary finite element method

In this study, a semi-analytical model is developed to investigate the fluid-structure coupling characteristics of liquid sloshing in an elastic rectangular container subjected to horizontal external excitation based on the scaled boundary finite element method (SBFEM) for the first time. The fluid inside the container is assumed to be incompressible, inviscid and irrotational, with the hydrodynamic pressure chosen as independent nodal variable in the governing equations. The container walls are considered as cantilever beams. The coupled fluid-structure system is initially divided into the structural domain and fluid domain, after which the SBFEM is employed to obtain the governing equations for each sub-domain. In the framework of the SBFEM, only the boundary of each sub-domain, rather than the entire computational domain, needs to be meshed and discretized. This method reduces the spatial dimension of the problem by one and offers an efficient approach to model the computational domain, while allowing for analytical formulations to be derived for the internal of the domain, resulting in an accurate description of the field variables. The fundamental equation of the entire coupled fluid-structure system is then assembled by performing the equilibrium condition and compatibility condition to ensure the balance of interaction forces at the interface between container walls and the liquid. The free vibrations analysis of the fluid-structure coupling system is solved by utilizing the generalized eigenvalue problem, and the transient dynamic response is determined using the synchronous solution algorithm in conjunction with the implicit-implicit scheme of the Newmark method. To validate the excellent accuracy and stability of the proposed formulation, several numerical examples are presented to investigate the free vibration and transient dynamic characteristics for the fluid-structure coupling problem. The obtained results show good agreement with reference solutions available in the literature. Additionally, the effects of geometrical and material parameters on the system responses are examined and discussed.

Probabilistic neural transfer function estimation with Bayesian system identification.

Neural population responses in sensory systems are driven by external physical stimuli. This stimulus-response relationship is typically characterized by receptive fields, which have been estimated by neural system identification approaches. Such models usually require a large amount of training data, yet, the recording time for animal experiments is limited, giving rise to epistemic uncertainty for the learned neural transfer functions. While deep neural network models have demonstrated excellent power on neural prediction, they usually do not provide the uncertainty of the resulting neural representations and derived statistics, such as most exciting inputs (MEIs), from in silico experiments. Here, we present a Bayesian system identification approach to predict neural responses to visual stimuli, and explore whether explicitly modeling network weight variability can be beneficial for identifying neural response properties. To this end, we use variational inference to estimate the posterior distribution of each model weight given the training data. Tests with different neural datasets demonstrate that this method can achieve higher or comparable performance on neural prediction, with a much higher data efficiency compared to Monte Carlo dropout methods and traditional models using point estimates of the model parameters. At the same time, our variational method provides us with an effectively infinite ensemble, avoiding the idiosyncrasy of any single model, to generate MEIs. It allows to estimate the uncertainty of stimulus-response function, which we have found to be negatively correlated with the predictive performance at model level and may serve to evaluate models. Furthermore, our approach enables us to identify response properties with credible intervals and to determine whether the inferred features are meaningful by performing statistical tests on MEIs. Finally, in silico experiments show that our model generates stimuli driving neuronal activity significantly better than traditional models in the limited-data regime.

Breach diameter prediction of reinforced concrete wall under contact/near-contact explosives using deep neural network

In recent years, the use of Machine Learning (ML) has been expanded to several engineering fields with applications in structural engineering. Deep Neural Network (DNN) models have been widely implemented to predict the response of structural systems under conventional loading. The accuracy of these DNN models relies on the size of the dataset used, which can vary from hundreds to thousands of data points, typically formed by images, test data, and/or finite element models built for a specific environment. Such dependency becomes a limitation when DNN models are intended to be used in blast analysis and/or design, as data are typically scarce or restricted. This paper introduces the implementation of an ML/DNN model for the prediction of breach diameter of a reinforced concrete target subjected to contact and near-contact explosions. The DNN model predicts the breach diameter using experimentally collected concrete breach data. The DNN model considers several parameters related to the charge (e.g., type, geometry, orientation, casement properties) and wall target (e.g., material properties, geometry, reinforcement, fiber content), as well as proximity between the target and explosive. It was found that charge geometry, charge placement type, target thickness, scaled distance, and fiber content in the mix were important features affecting the breach diameter prediction.

Analytical solution for forced vibration of multilayer structures composed of plates with different geometric dimensions

Multilayer system composed of parallel plate components with different geometric dimensions is frequently used to describe engineering objects, such as electronic assembly. In this work, an analytical method was proposed for forced vibration of this type of multilayer system. The proposed method overcomes the limitation that the traditional wave method is only applicable to all plate components must have the same in-plane dimensions. The proposed analytical method has an efficiency advantages in parameter analysis than element-based methods such as finite element method (FEM). The connection joints between two adjacent plate components, such as ball grid array (BGA) solder interconnect, are represented by elastic springs. The vibration of each component are described in terms of general and physical analytical waves, respectively, and the dynamic coupling between them are established by an equivalent dynamic flexibility matrix. The forced responses of the multilayer system are analytically calculated by solving the system equation in wave space. In the numerical examples, the effectiveness of the proposed method is validated by comparing the present results with the FEM results. The influence of number of the defective solder joints on vibration response is also investigated.

Research on DSP-based data model identification and triple-loop PID control of electro-hydraulic actuators

This paper focuses on the electro-hydraulic actuator of a certain type of aircraft, detailing the DSP-based hardware structure and principles. The study utilizes data acquisition and data model identification to establish a second-order model for the electro-hydraulic actuator. Verification sets and mean squared error (MSE) calculations, with an MSE value of 0.0110, indicate a reasonable identification model. Subsequently, a controller design structure is proposed based on the identified model. Finally, simulations validate the identified model and the triple-loop PID control. Experimental results show that the system's sine response output amplification factor is 0.9242.

Fumonisin B1 induces endoplasmic reticulum damage and inflammation by activating the NXR response and disrupting the normal CYP450 system, leading to liver damage in juvenile quail.

Fumonisin B1 (FB1) is a mycotoxin affecting animal health through the food chain and has been closely associated with several diseases such as pulmonary edema in pigs and diarrhea in poultry. FB1 is mainly metabolized in the liver. Although a few studies have shown that FB1 causes liver damage, the molecular mechanism of liver damage is unclear. This study aimed to evaluate the role of liver damage, nuclear xenobiotic receptor (NXR) response and cytochrome P450 (CYP450)-mediated defense response during FB1 exposure. A total of 120 young quails were equally divided into two groups (control and FB1 groups). The quails in the control group were fed on a normal diet, while those in the FB1 group were fed on a quail diet containing 30mg/kg for 42 days. Histopathological and ultrastructural changes in the liver, biochemical parameters, inflammatory factors, endoplasmic reticulum (ER) factors, NXR response and CYP450 cluster system and other related genes were examined at 14 days, 28 days and 42 days. The results showed that FB1 exposure impaired the metabolic function and caused liver injury. FB1 caused ER stress and decreased adenosine triphosphatease activity, induced the expression of inflammation-related genes such as interleukin 6 and nuclear factor kappa-B, and promoted inflammation. In addition, FB1 disrupted the expression of multiple CYP450 isoforms by activating nuclear xenobiotic receptors (NXRs). The present study confirms that FB1 exposure disturbs the homeostasis of cytochrome P450 systems (CYP450s) in quail liver by activating NXR responses and thereby causing liver damage. This study's findings provide insight into the molecular mechanisms of FB1-induced hepatotoxicity.

Development of an Alokon Stock Management Information System Using a Lean Development Approach

This study explores the development of an Alokon Stock Management Information System using the Lean Development approach to enhance the efficiency and effectiveness of stock management for contraceptive devices and drugs (alokon) distributed by the Women's Empowerment, Child Protection, and Family Planning Service in Indonesia. Alokon plays a critical role in family planning and reproductive health services. The research aims to address challenges such as inaccurate stock data, distribution delays, and the inability to meet demand promptly, which can disrupt health services. The Lean Development approach, emphasizing principles such as eliminating waste, strengthening learning, and delivering results quickly, was employed to create a responsive and adaptive system tailored to user needs. The resulting system incorporates features for managing alokon data, monitoring stock levels, and generating reports to ensure adequate stock availability and timely distribution. Evaluation of the system's usability was conducted using the System Usability Scale (SUS), involving ten respondents from the primary user groups. The average SUS score was 75, indicating a good level of usability. Users reported the system as comfortable and easy to use, although feedback highlighted areas for further improvement.

Septin 9 expression regulates 'don't eat me' signals and identifies an immune-epithelial class of intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) is a highly heterogeneous and aggressive liver cancer with limited therapeutic options. Precise classification and immunotherapy are perspectives to improve the treatments. We reported the role of septin 9 in apico-basal polarity and epithelial-to-mesenchymal transition (EMT). Here, we aim to elucidate its role in iCCA. We analyzed single-cell transcriptomes from human iCCA tumor cells based on phenotype and cell state. Knockdown of the septin 9 gene (SEPT9) was done using small interfering RNA (siRNA); interferon-γ (IFN-γ) stimulation was performed using different CCA cells; gene expressions were analyzed by reverse transcription and real-time PCR analysis (RT-qPCR); and immunofluorescence, immunoblotting, and flow cytometry were performed to assess the expression of proteins. The differential distributions of SEPT9 and vimentin (VIM) gene expressions allowed us to define specific cellular trajectories of malignant cells and thus identified distinct clusters of iCCA cells. One cluster was enriched in VIM and extracellular-matrix (ECM) remodeling molecules, and another had high expression of SEPT9 and genes from the 'don't eat me' signal involved in immune escape. This antagonism between SEPT9 and VIM was confirmed by in vitro experiments. Notably, SEPT9 and 'don't eat me' gene expressions were inversely correlated to those of vimentin and the EMT markers. SEPT9 expression was upregulated by IFN-γ and SEPT9 knockdown decreased expression of 'don't eat me' signal genes and increased expression of mesenchymal markers. Cancer Cell Line Encyclopedia (CCLE) transcriptome database analyses confirmed that iCCA cells enriched in septin 9 exhibit epithelial-like features. This study revealed septin 9 as a cytoskeleton element of iCCA epithelial-like cells and a regulator of the immune system response. It also brings new insights into the enigmatic relationship between EMT and immune response. Notably, we decoded a potential mechanism that could sensitize patients to immunotherapies.

Use of wireless technologies in IoT projects

When it comes to creating projects based on the use of the Internet of Things (IoT), wireless sensor networks are often used. Edge computing in IoT technology reduces system response delays to sensor output signals and increases the network throughput. At the same time, a short-range sensor network can work locally without access to the Internet, while long-range networks, as a rule, require access to the Internet and use both edge and cloud computing. The paper shows the features of the application of both peripheral and cloud computing in the practical implementation of IoT projects with various methods of wireless data transmission. Specific examples show the possibility of data transmission over a short distance using ESP-NOW technology, nRF24L01 radio modules and creating a local Wi-Fi access point. The range of sensor data transmission between microcontrollers is practically determined for each proposed option. The calculation of the range of the LoRa radio line is carried out for the actual sensitivity values of the receiver. The Okamura-Hata radio wave propagation model is proposed to estimate the LoRa radio line’s total loss. The operational range of LoRa modules with different types of signal modulation is practically determined. The essence of edge computing combined with digital and analogue sensors is shown. Peculiarities of peripheral computing during the implementation of IoT projects for remote control of blood saturation of patients using wireless technologies are considered. An example of data transmission of the air quality control system through a gateway based on an ESP8266 microcontroller with a graphical display of measurements in the IoT cloud service ThingSpeak and Blynk was provided.

Coupled vibration of low-medium-speed maglev vehicle-guideway system on isolated bridge with lead rubber bearings

This paper investigates the dynamic response of low-medium-speed (LMS) maglev vehicle moving on the isolated bridge with lead rubber bearings (LRBs). In the vehicle-guideway bridge model, the vehicle is simulated as a 50-degree-of-freedom model consisting of a car-body and ten bogie modules. The guideway bridge with LRB is established by the finite element method, and the guideway is interacted with the vehicle by the actively controlled electromagnetic forces. The LRB is simulated by the nonlinear spring element for reflecting the hysteretic performance, and a fast nonlinear analysis (FNA) method is proposed to achieve the potential nonlinear behavior of LRB under vehicle load. Then, the dynamic response of maglev vehicle running on the isolated bridge with LRB is investigated and compared to that on the non-isolated bridge. The effect of vehicle speed and LRB isolation degree on the coupled system responses is studied. Furthermore, the driving quality of vehicle on LRB bridge is discussed, and the applicability of LRB to maglev line bridge is thoroughly evaluated. The results show that the installation of LRB exhibits relatively insignificant influence on the vertical response of vehicle-guideway system, while could enlarge the lateral response. The lateral response of coupled system is much more vulnerable to the isolation degree, and it is recommended that the isolation degree of LRB should not exceed 2.50 to guarantee the driving comfort and running safety.

Silenced Survivors: A Systematic Review of the Barriers to Reporting, Investigating, Prosecuting, and Sentencing of Adult Female Rape and Sexual Assault.

Sexual victimization of adult women remains an underreported crime. This systematic review identified and synthesized the barriers to reporting, investigating, prosecuting, and sentencing cases of sexual assault and rape against adult women in Western countries. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a comprehensive search was conducted on August 3, 2023, across databases including PsycINFO, MEDLINE, Cochrane Library, Scopus, ProQuest Central, Web of Science, MedNar, and ProQuest Dissertations & Theses. Studies meeting the inclusion criteria provided relevant information on the decision not to formally disclose, investigate, prosecute, or convict incidents of sexual assault and rape of adult women. We included 28 studies and identified 70 barriers in total. Identified barriers were most prevalent to reporting, followed by investigating, prosecuting, and, lastly, sentencing. Key themes in the barriers included lack of trust in the criminal justice system, internal reactions, rape myths and societal norms, and perpetrator characteristics. The identified barriers emphasize an urgent need for reform of the criminal justice system's response to sexual assault and rape. Prioritizing victim-survivors' needs, enhancing transparency of the criminal justice system, and addressing attrition rates are crucial. Future studies need to engage with diverse population to address all victim-survivors' needs and provide further insights into the challenges across all stages of the criminal justice system to enhance the outcome of rape and sexual assault cases.

Effect of temperature gradient-induced periodic deformation of CRTS Ⅲ slab track on dynamic responses of the train-track system

Effect of temperature gradient-induced periodic deformation of CRTS Ⅲ slab track on dynamic responses of the train-track system

Managing Cardiovascular Risk in Patients with Autoimmune Diseases: Insights from a Nutritional Perspective.

Autoimmune diseases manifest as an immune system response directed against endogenous antigens, exerting a significant influence on a substantial portion of the population. Notably, a leading contributor to morbidity and mortality in this context is cardiovascular disease (CVD). Intriguingly, individuals with autoimmune disorders exhibit a heightened prevalence of CVD compared to the general population. The meticulous management of CV risk factors assumes paramount importance, given the current absence of a standardized solution to this perplexity. This review endeavors to address this challenge from a nutritional perspective. Emerging evidence suggests that inflammation, a common thread in autoimmune diseases, also plays a pivotal role in the pathogenesis of CVD. Nutritional interventions aimed at reducing inflammation have shown promise in mitigating cardiovascular risk. The integration of nutritional strategies into the management plans for patients with autoimmune diseases offers a holistic approach to reducing cardiovascular risk. While conventional pharmacological treatments remain foundational, the addition of targeted dietary interventions can provide a complementary pathway to improve cardiovascular outcomes.

SLC4A4 as a novel biomarker involved in immune system response and lung adenocarcinoma progression

BackgroundAltered expression and activity of solute carrier family 4 member 4 (SLC4A4) could affect the growth, survival and metastasis of tumor cells. Currently, the role of SLC4A4 in lung adenocarcinoma (LUAD) immunotherapy and prognosis was not entirely clear. MethodsWe analyzed SLC4A4 expression in LUAD tissues and cell lines using quantitative reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemistry. The effects of SLC4A4 overexpression on angiogenesis, cell migration, invasion, and epithelial-mesenchymal transition were examined. Public databases helped construct a risk model evaluating SLC4A4′s expression on LUAD prognosis and immunotherapy response. Additionally, a xenograft model, flow cytometry, and enzyme-linked immunosorbent assay further explored SLC4A4′s role in tumor immune microenvironment infiltration. ResultsUpregulation of SLC4A4 promoted apoptosis in the LUAD cell line and significantly inhibited the migration and invasive ability of cancer cells (P<0.01). A total of 10 key genes (including SIGLEC6, RHOV, PIR, MOB3B, MIR3135B, LPAR6, KRT8, ITGA2, CPS1, and C6) were screened according to SLC4A4 expression, immune score and stromal score, and a prognostic model with good outcome was constructed (AUC values of which in the training cohort at 1,3, and 5 years reached 0.73, 0.73, and 0.72, respectively). Importantly, we demonstrated that high expression of SLC4A4 was able to increase the proliferation level and cytokine secretion of CD8+ T cells for the purpose of promoting the immune system response to LUAD. ConclusionOur study revealed that SLC4A4 can serve as a prognostic indicator for LUAD, providing new insights into the treatment and diagnosis of LUAD.

Analysis of the dynamics of gene expression in patients with acute COVID-19 and in recovery period

Massive infections of people with the previously unidentified SARS-CoV-2 virus have been a shock to the global healthcare system. While many studies have focused on the clinical manifestations of the disease and its treatment methods, understanding the molecular and genetic aspects of infection has proved critical to understanding the pathogenetic mechanisms of host-pathogen interaction. The scientists focused on issues of gene expression and their regulation in response to SARS-CoV-2 infection. In particular, we conducted a study of gene expression within the framework of the project «COVID-19: Scientific and technological justification of the response system to the spread of new respiratory infections, including coronavirus infection», the results of which are presented in the article [1].Hence, variations in the gene expression profiles of TLR 3 (Toll-Like receptor), TLR 7, TLR 4, ACE 2 (Angiotensing converting enzyme), TMPRSS 13 (Transmembrane serine protease), INF-Ɣ (Interferon gamma), and IL 4 (Interleukin) were discerned across all investigated cohorts, including those assessed six months post-recovery. There is a complex of pathways of immune system to defense with the infection including the involvement of toll-like receptor signaling pathways which contact of viral particles. Moreover, the surge in ACE2 expression demonstrates the multifunctional role as gates for Sars-Cov-2 to enter cells and activation of innate immunity responses. Although, the upregulation of INF-Ɣ and IL-4 as proinflammatory cytokines were contributed to the initiation and the progression of the cytokine storm.