T cells follow a triphasic distinct pathway of activation, proliferation and differentiation before becoming functionally and phenotypically ‘exhausted’ in settings of chronic infection, autoimmunity and in cancer. Exhausted T cells progressively lose canonical effector functions, exhibit altered transcriptional networks and epigenetic signatures and gain constitutive expression of a broad coinhibitory receptor suite. This review outlines recent advances in our understanding of exhausted T cell biology and examines cellular and molecular mechanisms by which a state of dysfunction or exhaustion is established, and mechanisms by which exhausted T cells may still contribute to pathogen or tumour control. Further, this review describes our understanding of exhausted T cell heterogeneity and outlines the mechanisms by which checkpoint blockade differentially engages exhausted T cell subsets to overcome exhaustion and recover T cell function.

Cancer immunotherapy targeting immune checkpoints has exhibited promising clinical outcomes in many cancers, but it offers only limited benefits for pancreatic cancer (PC). Cancer stem cells (CSCs), a minor subpopulation of cancer cells, play important roles in tumor initiation, progression, and drug resistance. Accumulating evidence suggests that CSCs employ immunosuppressive effect to evade the immune recognition. However, clinical implications of the associations among CD8+ T cells infiltration, programmed death receptor ligand-1 (PD-L1) expression, and CSCs existence are poorly understood in PC. Immunostaining and quantitative analysis were performed to assess CD8+ T cells infiltration, PD-L1 expression, and their relationship with CD44+/CD133+ CSCs and disease progression in PC. CD8+ T cells infiltration was associated with better survival while PD-L1 expression was correlated with PC recurrence. Both the low CD8+ T cells infiltration/high PD-L1 expression group and the high CD8+ T cells infiltration/high PD-L1 expression group show high levels of CD44+/CD133+ CSCs, but patients with low CD8+ T cells infiltration/high PD-L1 expression had worse survival and higher recurrence risk than those with high CD8+ T cells infiltration/high PD-L1 expression. Moreover, CD8+ T cells infiltration could reduce unfavorable prognostic effect of high co-expression of PD-L1 and CD44/CD133. Our study highlights an interaction among CD8+ T cells infiltration, PD-L1 expression, and CD44+/CD133+ CSCs existence, which contributes to PC progression and immune evasion.

In this work α-synuclein amyloid fibrils, formation of which is a biomarker of the Parkinson’s disease, were investigated with the use of fluorescent probe thioflavin T (ThT). Experimental conditions of the protein fibrillogenesis were chosen so that a sufficient number of continuous measurements can be performed to characterize and analyze all stages of this process. The reproducibility of fibrillogenesis and the structure of the obtained aggregates (that is a critical point for their further investigation) were proved using a wide range of physical-chemical methods. For determination of ThT—α-synuclein amyloid fibrils binding parameters sample and reference solutions were prepared with the use of equilibrium microdialysis. By absorption spectroscopy of these solutions ThT—fibrils binding mode with the binding constant about 10⁴ M⁻¹ and stoichiometry of ThT per protein molecule about 1:8 was observed. Fluorescence spectroscopy of the same solutions with the subsequent correction of the recorded fluorescence intensity on the primary inner filter effect allowed to determine another mode of ThT binding to fibrils with the binding constant about 10⁶ M⁻¹ and stoichiometry about 1:2500. Analysis of photophysical characteristics of the dye molecules bound to the sites of different binding modes allowed to assume the possible localization of these sites. Obtained differences in the ThT binding parameters to amyloid fibrils formed from α-synuclein and other amyloidogenic proteins, as well as in the photophysical characteristics of the bound dye, confirmed the hypothesis of amyloid fibrils polymorphism.

Immunomodulation as means of immunotherapy has been studied in major research and clinical laboratories for many years. T-Regulatory (Treg) cell therapy is one of the modulator used in immunotherapy approaches. Similarly, nuclear receptor peroxisome proliferator activated receptor gamma (PPARγ) has extensively been shown to play a role as an immuno-modulator during inflammation. Given their mutual roles in downregulating the immune response, current study examined the influence of PPARγ ligands i.e thiazolidinedione (TZD) class of drugs on Foxp3 expression and possible crosstalk between PPARγ and nTreg cells of NOD and NOR mice. Results showed that TZD drug, ciglitazone and natural ligand of PPARγ 15d-prostaglandin downregulated Foxp3 expression in activated nTreg cells from both NOD and NOR mice. Interestingly, addition of the PPARγ inhibitor, GW9662 further downregulated Foxp3 expression in these cells from both mice. We also found that PPARγ ligands negatively regulate Foxp3 expression in activated nTreg cells via PPARγ-independant mechanism(s). These results demonstrate that both natural and synthetic PPARγ ligands capable of suppressing Foxp3 expression in activated nTreg cells of NOD and NOR mice. This may suggest that the effect of PPARγ ligands in modulating Foxp3 expression in activated nTreg cells is different from their reported effects on effector T cells. Given the capability to suppress foxp3 gene, it is possible to be tested as immunomodulators in cancer-related studies.

Stunting is a major public health issue in Aceh, Indonesia, requiring advanced analytical techniques for effective interventions. This study presents a novel hybrid machine learning framework designed to enhance the analysis of stunting through improved classification, predic-tive modeling, and clustering optimization. The framework utilizes Support Vector Machines (SVM) with Radial Basis Function (RBF) and Sigmoid kernels for classification. The RBF kernel achieved an accuracy of 91.3%, significantly outperforming the Sigmoid kernel's 85.6%. Linear Regression was employed for predictive modeling, yielding a Mean Squared Error (MSE) of 0.137, which indicates strong predictive accuracy. In clustering, the optimized K-Medoids method, in-corporating a weight product approach, demonstrated superior efficiency by requiring only 3 iterations for convergence, compared to 7 iterations for the conventional K-Medoids method. Additionally, it achieved a higher Calinski Harabasz Index of 93.7, compared to 85.2 for the conventional method. This comprehensive approach enhances accuracy and efficiency across classification, prediction, and clustering tasks, providing valuable insights for targeted interventions and policy development to address stunting in Aceh.

For the purpose of improve the sustainability of products sold in the EU, Digital Product Passports is a mandatory solution. These passports would systematically gather information about products, such as detailing the materials involved to aid recycling and remanufacturing efforts, or recording the emissions produced throughout the manufacturing process. The overall goal is the establishment of a circular economy in the EU. Current research on Digital Product Passports is focused on collating content for sector-specific applications. However, achieving sustainability goals through Digital Product Passports will require new methods and technical solutions for digital collaboration between supply chain participants, especially in the manufacturing sector. Collaborative work on Digital Product Passports requires trust and traceability in data and access management to ensure privacy over the data contained. One way to enable this securely and confidentially is through the use of blockchain technology, in which stored data cannot be concealed, which is key to the traceability of digital product data documentation. This paper therefore presents a concept for the implementation of generically applicable cross-industry blockchain-based digital product passports. To this end, generic supply chain processes have been abstracted and condensed into the architecture of smart contracts. Great attention is paid to the establishment of traceability as well as privacy through the selection of the blockchain technology Secret Network in combination with Gaia-X functionalities. An illustrative use case for digital product passports in manufacturing is used to demonstrate the applicability of the presented concept. In this use case information about the digital nameplate and carbon footprint is exchanged securely and confidentially in a multi-tenant supply chain network based on the Industry 4.0 infomation model of the Asset Administration Shell.

The regions with the best economy have a greater capacity to develop low-income or social impact housing, thus contributing to the reduction of poverty, and therefore, to the fulfillment of the Sustainable Development Goals. This is observed in fewer people living in extreme poverty and with fewer unmet basic needs. The present article analyzes the correlation between development by the main economic sectors in the different regions (departments) of Colombia, and the offer of low-income housing. The valid relationship found is between the economic condition of the regions (GDP) and non-social housing (more expensive commercial value) (Spearman´s Rho: 0.9). That means that there is an imbalance between regional economic capacity and the low-income housing offer because their economic potential allows them to have less of a demanding population, that is, living in poverty. This correlation is higher with activities that are mostly developed in an urban environment, such as manufacturing, construction, real estate, and finance and insurance. On the contrary, the correlation is lower with industries such as mining and agriculture, which mostly operate in rural areas. The analysis for low-income housing and economic sectors GDP yields low correlations, but are especially dismissible for more rural industries, such as mining and agriculture. The analysis shows the change of trend in the correlations for the year 2021, the beginning of the post-pandemic economic recovery.

The paper proposes a game theory model of price oligopoly with a heterogeneous product, where total demand depends linearly on the minimum market price. This model develops the Bertrand oligopoly for the case of imperfect price elasticity of demand. The most interesting result is an asymmetric Nash equilibrium with different prices and sales in the situation of symmetric oligopolists. The asymmetry is explained by the fact that a decrease in the minimum market price leads not only to a reallocation of consumers among firms, but also to an increase in total demand. Modifications of a two-stage game with a leader and followers and the price discrimination model are also considered. Microeconomic substantiation of the model is given on the basis of the spatial differentiation approach.

Actinobacteria are known for their production of bioactive specialized metabolites, but still under-exploited due to silent biosynthetic gene clusters (BGCs) not expressed in conventional laboratory cultures conditions. In this study, three marine-derived actinobacteria were cultured using the one strain many compounds method (OSMAC) to explore the real potential of these microorganisms. Salinispora arenicola (SH-78) and two Micromonospora sp. (SH-82 and SH-57) were grown under varying parameters such as time, medium composition, and culture support. The microbial extracts produced were chemically screened by high-resolution analysis (HRMS/MS). The data were used to build ion identity molecular networks (IIMN) and annotate the specialized metabolites detected. A selection of extracts was biologically screened for their cytotoxic and antiplasmodial activities. The IIMNs and the annotations produced were used to assess the impact of culture parameters on the metabolomic diversity of the selected actinobacteria and highlight the presence of unique molecules to specific culture conditions. Micromonospora sp. SH-57 produced a greater quantity of metabolites in liquid culture, with higher associated biological activity. The method employed allowed to explore deeper the specialized metabolites production and to identify the best culture conditions to produce bioactive natural products.

In light of the recent pandemic, several COVID-19 vaccines were developed, tested and approved in a very short time, a process that otherwise takes many years. Above all, these efforts have also unmistakably revealed the capacity limits and potential for improvement in vaccine production. This review aims to emphasize recent approaches for targeted rapid adaptation and production of vaccines from an interdisciplinary multifaceted perspective. Using literature research, stakeholder analysis and a value proposition canvas, we reviewed technological innovations on the pharmacological level, formulation, validation and resilient vaccine production to supply bottlenecks and logistic networks. We identified four main drivers to accelerate the vaccine product life cycle: computerized candidate screening, modular production, digitized quality management and a resilient business model with corresponding transparent supply chains. In summary, the results presented here can serve as a guide and implementation tool for flexible, scalable vaccine production to respond swiftly to pandemic situations in the future.

This paper bases on panel data from 30 provinces and municipalities in China spanning the period of 2010 to 2021 to examine the evolving mechanisms and influencing factors of agricultural product circulation efficiency in the provinces along the Belt and Road Initiative (BRI) within the context of green total factor productivity (TFP). The study research employs various methodologies including the SBM-DDF model, GML index, system GMM, and global Moran's I index. The findings are as follows: Initially, the provinces along the BRI exhibit an overall negative growth trend in the green TFP of agricultural product circulation, with a noticeable decline observed particularly after the initiation of the BRI in 2014. Secondly, foreign investment levels significantly contribute to the positive enhancement of green TFP in agricultural product circulation among the provinces along the BRI. Eventually, environmental regulations, government support, and the level of international trade in agricultural products exert significant negative impacts. Thirdly, the results of spatial effect tests reveal substantial spatial spillover effects in the green TFP of agricultural product circulation among the provinces along the BRI, as demonstrated through examinations utilizing three distinct spatial matrices.

Energy imports and the transition to renewable energy sources are of critical importance in the current geopolitical context, which necessitates concrete actions to tackle the energy crisis at the European Union level. The study aims to explore the impact of imported non-renewable energy resources on the EU-27 economy. It examines the correlations and causal relationships between GDP, GVA, R&D investments, and energy imports from 2000 to 2021. Data normality was assessed using the Shapiro-Wilk test, while Pearson's test identified correlations between variables. Linear and multiple regression analyses were conducted to determine the effects of changes in independent variables on dependent variables. The study found a strong association between natural gas imports and GDP, with increases in GDP leading to a more than fourfold rise in imports. Furthermore, multiple regression analysis indicated that a 1% increase in R&D investments results in a 2.21% decrease in fossil fuel imports in 91.7% of cases. This suggests that R&D investments contribute to improved efficiency and the use of renewable energy sources.

From the perspective of manufacturing companies, the political, media and economic discourse on decarbonisation of the recent years manifests itself as an increasing social expectation of action. In Germany in particular, this discourse is also being driven forward by powerful companies, respectively sectors, most notably the automotive industry. Against this background, it was examined how German manufacturing companies react to rising societal pressure and emerging policies. It is examined which measures the companies have taken or plan to take to reduce their footprint, which aspirations are associated with this and by which structural characteristics (company size, energy intensity, sector) these are influenced. A mix methods approach was applied, utilising data gathered from approx. 900 companies in context of the Energy Efficiency Index of German Industry (EEI), along with media research focusing on decarbonisation plans and initiatives announced. We demonstrate that one-size-serves-all approaches are not suitable to decarbonise industry as the situation and ambitions differ considerably depending on size, energy intensity and sector. Even though the level of ambition and urgency is high, particularly micro and energy intensive companies are challenged. The research uncovers a series of questions that call for attention to materialise the ambitions and address the challenges outlined.

Information molecules of DNA and RNA should obey principles of quantum mechanics where unitary operators in form of unitary matrices have key meanings. Unitary matrices are the basis of calculations in quantum computers. This article presents some author's results, which show that matrix forms of the representation of structured systems of molecular-genetic alphabets can be considered as sets of sparse unitary matrices related with phenomenologic features of the degeneracy of the genetic code. These sparse unitary matrices have orthogonal systems of functions in their rows and columns. A complementarity exists among some unitary genetic matrices in relation each other. Decompositions of numeric genetic matrices into sets of sparse unitary matrices are connected with the logical operation of modulo-2 addition used in quantum computers as well. Tensor (or Kronecker) families of unitary genetic matrices with their fractal-like properties are also considered. The described results are discussed in the frame of development of quantum-information approaches for modeling genetic systems.

The emergence of the Internet of Things (loT) has led to remarkable advancements in various sectors such as urbanization, manufacturing, and healthcare, intending to enhance the quality of life and contribute to the world economy. However, by the conclusion of 2024, ti is projected that the global network of the Internet of Things (IoT) will encompass over 207billion interconnected devices. The immense data collected and exchanged are often stored in centralized servers, leading to vulnerabilities such as data breaches. Blockchain technology, originally developed for cryptocurrency transactions, provides a possible solution for these challenges with its decentralized, immutable, and encrypted features. This survey provides a comprehensive discussion regarding the fusion of Blockchain technology and the loT, covering architectural alignment, application, security, and limitations. The contributions of this survey include an overview of Blockchain technology and its secure applications, the integration of Blockchain into IoT , an examination of suitable methods for Blockchain integration,and a taxonomy or security and limitations of loT and blockchain integration.

Oxidative stress and chronic inflammation create a perpetual cycle in the elderly, where impaired immune function amplifies susceptibility to oxidative damage, and oxidative stress further weakens the immune response. This cycle is particularly detrimental to the respiratory system of the elderly, which is an easy target for constant exogenous harmful attacks during cold/flu season or under heavy air pollution. Herbal medicines that protect respiratory function are seen as safer alternatives to conventional therapies; however, there is limited availability of scientifically validated, safe, and effective natural supplements for these conditions. In this study, we evaluated a standardized bioflavonoid composition, UP446, which contains bioactives from the roots of Scutellaria baicalensis and the heartwoods of Acacia catechu, as a natural and nutritional supplement for its antioxidative and immunoregulatory effects in oxidative stress-accelerated aging and chemically induced immune suppression mouse models. Immunosenescence was induced by continual subcutaneous injection of D-galactose (D-Gal) at a dose of 500 mg/kg/day in CD-1 mice. UP446 was administered orally at doses of 100 mg/kg and 200 mg/kg starting in the fifth week of immunosenescence induction. The study lasted a total of ten weeks. All mice received a quadrivalent influenza vaccine 14 days before the end of the study. Whole blood, serum, spleen homogenate, and thymus tissues were used for analysis.Cyclophosphamide (Cy)-induced immunosuppression was triggered by three consecutive injections of cyclophosphamide at 80 mg/kg/day, followed by oral administration of UP446 for 18 days at doses of 100 mg/kg and 200 mg/kg. Blood was collected from each animal at necropsy, and serum was isolated for IgA and IgG ELISA analysis. UP446 was found to improve immune response, as evidenced by stimulation of innate (NK cells) and adaptive immune responses (T cells and cytotoxic T cells), an increase in antioxidant capacity (glutathione peroxidase), preservation of vital immune organs (the thymus), and a reduction in NFκB. UP446 also increased serum levels of IgA and IgG. The findings presented in this report demonstrate the antioxidative, anti-inflammatory, and immune-regulatory activities of UP446, suggesting its potential use in respiratory conditions involving immune stress due to aging, oxidative stress, and/or pathogenic challenges.

A novel Gram-stain-negative, facultatively anaerobic and mixotrophic bacterium, designated as strain LZ166T, was isolated from the bathyplagic seawater in the western Pacific Ocean. Cells were short rod-shaped, oxidase- and catalase- positive, and motile by means of lateral flagella. Growth of strain LZ166T was observed at 10-45 ℃ (optimum, 34-37 ℃), at pH 5-10 (optimum, 6-8) and in the presence of 0-5% NaCl (optimum, 1-3%). Phylogenetic analysis based on the 16S rRNA gene showed that strain LZ166T shared the highest similarity (98.58%) with Aquibium oceanicum B7T, and formed a distinct branch within the Aquibium genus. Genomic characterization, including average nucleotide identity (ANI, 90.73-76.79%), average amino identity (AAI, 88.50-79.03%) and digital DNA-DNA hybridization (dDDH, 36.1-22.2%) values between LZ166T and other species within the Aquibium genus, further substantiated its novelty. The genome of strain LZ166T was 6,119,659 bp in size with a 64.7 mol% DNA G+C content. The predominant fatty acid was summed feature 8 (C18:1ω7c and/or C18:1ω6c). The major polar lipids identified were Diphosphatidylglycerol (DPG), phosphatidylethanolamine (PE), glycolipid (GL) and phosphatidylglycerol (PG), with ubiquinone-10 (Q-10) as the predominant respiratory quinone. Genomic annotation indicated the presence of genes for a diverse metabolic profile, including pathways for carbon fixation via the Calvin–Benson–Bassham cycle and inorganic sulfur oxidation. Based on polyphasic taxonomic results, strain LZ166T represented a novel species of the genus Aquibium, for which the name Aquibium pacificus sp. nov., is proposed, with the type strain LZ166T (= MCCC M28807T = KACC 23148T = KCTC 82889T).

Cancer cells are believed to be recognized and controlled by the immune system of the host, especially the adaptive immune system. Cancers may be initiated by a single gene defect in stem cells or regenerating cells during the replacement of old or injured tissue cells, and additional gene defect(s) then occur. To compensate for missing proteins intracellular homeostasis systems, such as proteostasis, may work with activation of new genes. The risk or predisposing factors in cancers may be related to the number of tissue cell renewals (the turnover time) and the probability of gene defect(s). Oncological symptoms may be associated with substances that are derived from antigens expressed on cancer cells and those derived from damaged cancer cells with corresponding immune reactions. In patients with cancers or other conditions, inadequate immune components to control these substances may result in chronic inflammatory or autoimmune diseases. Cancer cells communicate with host cells, including the immune cells such as T cells, for survival and proliferation and may need assistance from immune cells against intracellular infections or physicochemical insults. T cell-based immune therapeutics have been developed and clinically used in some cancers, especially in advanced cancers. We further discuss the oncogenesis, pathophysiology of cancers, and unresolved issues in tumor immunology and reinterpret the effectiveness of T cell-based therapies under the protein-homeostasis-system hypothesis.

Sparkling wines elaborated by means Ancestral method, also called Pét-Nats, are nowadays gaining an increasing share of the market. However, the scientific information about these wines is very scarce. For that reason, the aim of this research was to compare the physicochemical composition and sensory attributes of a representative sampling of commercial sparkling wines elaborated by Ancestral and Traditional methods. Ancestral sparkling wines were more heterogenous than Traditional sparkling wines because some of them showed lower internal pressure, higher turbidity, higher colour intensity and less foamability. These differences would be probably because the ancestral elaboration protocol is not so well defined as in the case of Traditional sparkling wines. However, Ancestral method has the advantage of being able to work with riper grapes and with lower doses of sulphur dioxide.

T-cell independent (TI) pathway activated by microbiota results in the generation of low-affinity homeostatic IgA with a critical role in intestinal homeostasis. Moderate aerobic exercise (MAE) provides a beneficial impact on intestinal immunity but the action of MAE on TI-IgA generation under senescence conditions is unknown. This study aimed to determine the effects of long-term MAE on TI-IgA production in young (3 months old) BALB/c mice exercised until adulthood (6 months) or aging (24 months). Lamina propria (LP) from the small intestine was obtained to determine B cells and plasma cells sub-populations by flow cytometry and molecular factors related to class switch recombination (TSLP/APRIL/BAFF/iNOS/RDH) and synthesis of IgA (α-chain/IL-6/IL-21/TGF-β); and epithelial cells to evaluate IgA-transitosis (pIgR/TNFα/IFN-/IL-4), by RT-qPCR technique. Results were compared with data obtained from sedentary age-matched mice. Statistical analysis was computed with ANDOVA and P<0.05 was considered as statistically significant difference. Under senescence conditions MAE promoted the B cell and IgA+B cells and APRIL that may im-prove the intestinal response and ameliorated the inflammatory environment associated pre-sumably with the downmodulation of pIgR. Data suggested that MAE improved the IgA and downmodulate the cytokine pro-inflammatory expression favoring homeostatic conditions in aging.

Graft injury affects over 50% of liver transplant (LT) recipients, but non-invasive biomarkers to diagnose and guide treatment are currently limited. We aimed to develop a biomarker of graft injury by integrating serum metabolomic profiles with clinical variables. Serum from 55 LT recipients with biopsy confirmed metabolic-dysfunction associated steatohepatitis (MASH), T-cell mediated rejection (TCMR) and biliary complications was collected and processed using a combination of LC-MS/MS assay. The metabolomic profiles were integrated with clinical information using a multi-class Machine Learning (ML) classifier. The efficacy of the model was assessed through the evaluation of the Out-of-Bag (OOB) error estimate. Our ML model yielded an overall accuracy of 79.66% with an OOB estimate of the error rate at 19.75%. The model exhibited a maximum ability to distinguish MASH, with an OOB error estimate of 7.4% compared to 22.2% for biliary and 29.6% for TCMR. The metabolites serine and serotonin emerged as the topmost predictors. When predicting binary outcomes using 3 models: Biliary (biliary vs. rest), MASH (MASH vs. rest) and TCMR (TCMR vs. rest), the AUCs were 0.882, 0.972 and 0.96 respectively. Our ML tool integrating serum metabolites with clinical variables shows promise as a non-invasive, multi-class serum biomarker of graft pathology.

Ulcerative colitis is a chronic immune-mediated disease of unclear etiology, affecting people of different ages and significantly reducing the quality of life. Modern methods of therapy are mainly represented by anti-inflammatory drugs and are not aimed at a specific pathogenetic factor. In this study, we investigated the effect of transplantation of sterile stool filtrate from healthy donors on the induction of anti-inflammatory immune mechanisms. It was shown that performing such a procedure in patients with ulcerative colitis caused the appearance of T helper cells in the blood, which reacted to the content of sterile stool filtrates in an antigen-specific manner and produced IL10. At the same time, cells of the same patients before therapy in response to the addition of sterile stool filtrates were less reactive and predominantly produced IL4, indicating its pro-inflammatory skewing. The obtained data demonstrated the effect of an anti-inflammatory shift in the T-helper response after transplantation of sterile stool filtrate, which increased and persisted for at least three months after the procedure.

Severe COVID-19 is a major cause of morbidity and mortality worldwide, especially to those with co-morbidities, the elderly and the immunocompromised. However, the molecular determinants critical for severe COVID-19 progression remain to be fully elucidated. Meta-analysis of transcriptomic RNAseq and single-cell sequencing datasets comparing between severe and mild COVID-19 patients have demonstrated that the early expansion of myeloid-derived suppressor cells (MDSCs) could a key feature of severe COVID-19 progression. Besides serving as potential early prognostic biomarkers for severe COVID-19 progression, several studies have also indicated the functional roles of MDSCs in severe COVID-19 pathogenesis and possibly even long COVID. Given the potential links between MDSCs and severe COVID-19, we examined the existing literature summarizing the characteristics of MDSCs, the evidence of MDSCs in facilitating severe COVID-19 pathogenesis and discuss the potential therapeutic avenues that can be explored to reduce the risk and burden of severe COVID-19. We also provide a web app where users can visualise the temporal changes of specific genes or MDSC-related gene sets during severe COVID-19 progression and disease resolution at https://temporal-severe-covid.streamlit.app/, based on our previous study described by Ong et al., 2021.

A locally-rotationally-symmetric Bianchi-I model filled with strange quark matter (SQM) is explored in f(R, T) gravity. We take f(R, T) = R + 2 f(T) = R + 2λT, where R is the Ricci scalar, T is the trace of energy-momentum tensor and λ is an arbitrary constant. Exact solutions are obtained by assuming that the expansion scalar is proportional to the shear scalar. This yields a constant value for the deceleration parameter, q = 2, which corresponds to the decelerated phase of the universe. The model is found to be physically viable for λ < −1. SQM during early evolution mimics ultra-relativistic radiation whereas at late times, it behaves as dust, quintessence or even the cosmological constant depending on the value of λ. The effective matter acts as a stiff fluid irrespective of the matter content and of the f(R, T) terms. The model is shear free at late times but remains anisotropic throughout the evolution. In the absence of the f(R, T) terms, SQM accelerates the universe. In the specific case when SQM vanishes at late times, the effect of f(R, T) is to accelerate the universe. The model admits the possibility that SQM could be an alternative to dark energy.

This paper discusses a passive control issue for Nonlinear Time-Varying (NTV) systems subject to stability and attenuation performance. Based on the modeling approaches of Takagi-Sugeno (T-S) fuzzy model and the Linear Parameter-Varying (LPV) model, a Parameter-Dependent Polynomial Fuzzy (PDPF) model is constructed to represent the NTV systems. According to Parallel Distributed Compensation (PDC) concept, a parameter-dependent polynomial fuzzy controller is built to achieve robust stability and passivity of PDPF model. Furthermore, the passive theory is applied to achieve the performance constraining the disturbance effect on the PDPF systems. To develop the stability criteria, by introducing a parameter-dependent polynomial Lyapunov function, one can derive some stability conditions which belong to the term of Sum-Of-Squares (SOS) form. Based on the Lyapunov function, two stability criteria are proposed to design the corresponding PDPF controller such that the NTV system is robustly stable and passive. Finally, a numerical example is applied to demonstrate the effectiveness of the proposed stability criterion.

To address the problem that it is easy to form coverage blind areas when wireless sensor networks are randomly deployed, an improved coverage optimization algorithm based on improved Salpa swarm Intelligent algorithm (ATSSA) is proposed for wireless sensor networks. Firstly, the pop-ulation is initialized using tent chaotic sequence to enhance the optimization ability of the algo-rithm. Secondly, the T-distribution mutation is added to the update formula of the leaders for improving the ability to jump out of the local optimal value. Finally, an adaptive formula for updating the position of the follower is proposed, which not only guarantees the local searching ability of the algorithm in the late iteration period, but also improves the global searching ability of the algorithm in the early iteration period. The experimental results show that ATSSA algorithm can improve the coverage of the wireless sensor networks and reduce deployment costs com-pared with other algorithms, when it is used in the wireless sensor networks.

Chronic hepatitis B infection remains a significant worldwide health burden, placing persons at risk for hepatocellular cancer and hepatic fibrosis. Chronic hepatitis B virus (CHB) infection is characterized by elevated levels of immunosuppressive regulatory T cells (Tregs), which can inhibit the function of effector T cells and lead to an insufficient immune clearance response against HBV in the host. Theoretically, suppression of Treg functionality and percentage could increase anti-HBV reactivity in CHB-infected patients, although this has not yet been explored. We attempted to enhance our previously established anti-CHB protocol utilizing the GM-CSF+IFN-α+rHBVvac regimen (GMI-HBVac) by incorporating Mafosfamide (MAF), which has been utilized in anticancer therapy in the past. Intravenous administration of MAF to rAAV8-1.3HBV-infected mice resulted in a dose-dependent reduction of Tregs in the blood, rebounding to pretreatment levels 10 days later. To determine the efficacy of anti-CHB, 2ug/ml MAF was combined with the GMI-HBVac in an HBV-infected animal model as an anti-Treg treatment. When rAAV8-1.3HBV-infected mice were immunized with MAF+GMI-HBVac, peripheral blood Tregs decreased significantly, leading to dendritic cell activation, HBV-specific T cell proliferation, and upregulation of IFN-gamma producing CD8+T cells. In addition, MAF+GMI-HBVac vaccination stimulates T cell infiltration in HBV-infected liver. These conditions may contribute to an enhanced immune response and the clearance of HBV-associated antigens, including serum HBsAg, serum HBcAg, and HBcAg+ hepatocytes. Overall, this is the first indication that MAF was utilized as an adjuvant to deplete Tregs and paired with GMI-HBVac as a unique therapeutic vaccine regimen against established CHB mice to produce a functional cure, as seen by the remarkable clearance of HBsAg.

Background: CD169 has been found overexpressed in the blood of COVID-19 patients and identified as a biomarker in the early disease. We have analysed CD169 in blood cells of COVID-19 patients to assess its role as predictive marker of the disease. Methods : The ratio of the CD169 Median median Fluorescence fluorescence Intensity intensity of CD169 between monocytes and lymphocytes (CD169 RMFI ) was analysed by flow cytometry in blood samples of COVID-19 patients (COV) and healthy donors (HD ) and correlated with immunophenotyping, inflammatory markers, cytokines mRNA expression, pulmonary involvement and disease progression. Results: CD169 RMFI increased in COV but not in HD. CD169 RMFI correlated with T-cell differentiation and exhaustion markers as well as with B cells maturation and differentiation. In vitro stimulation of PBMCs of HD with SARS-CoV-2 Spike spike protein induced CD169 RMFI together with IL-6 and IL-10 gene expression. Likewise, CD169 RMFI correlated with blood cytokine mRNA levels, inflammatory markers, and pneumonia severity in patients which that had not received any treatment at sampling. Notably, in untreated patients, CD169 RMFI reflected the respiratory outcome during hospitalization. Conclusion : Considering the immunological role of CD169 and its involvement during the infection and the progression of COVID-19, it could be considered as an early biomarker to evaluate disease progression and clinical outcome.

Chimeric antigen receptor (CAR)-T cell-based therapies have achieved substantial successes against B-cell malignancies, what has led to a growing scientific and clinical interest on extending their use to solid cancers. However, results for solid tumours have been limited up to now, in part due to the immuno-suppressive tumour microenvironment, that is able to inactivate CAR-T cell clones. In this paper we put forward a mathematical model describing the competition of CAR-T and tumour cells, accounting for their immunosuppressive capabilities. Using the mathematical model, we show that the use of large numbers of CAR-T cells targeting the solid tumour antigens could overcome the cancer immunosuppressive potential. To achieve such high levels of CAR-T cells we propose and study computationaly, the manufacture and injection of CAR-T cells targeting two antigens: CD19 and a tumour-associated antigen. We study in-silico the resulting dynamics of the disease after the injection of this product and find that the expansion of the CAR-T cell population in the blood and lymphopoietic organs could lead to the massive generation of an army of CAR-T cells targetting the solid tumour, and potentially overcoming its inmune suppression capabilities. That strategy could benefit from the combination with PD-1 inhibitors and of low tumour loads. Our computational results provide a theoretical support for the treatment of different types of solid tumours using T-cells engineered with combination treatments of dual CARs with on- and off-tumour activity and anti-PD1 drugs after completion of classical cytoreductive treatments.

Abstract The COVID-19 pandemic is thought to began in Wuhan, China in December 2019. Mobility analysis identified East-Asia and Oceania countries to be highly-exposed to COVID-19 spread, consistent with the earliest spread occurring in these regions. However, here we show that while a strong positive correlation between case-numbers and exposure level could be seen early-on as expected, at later times the infection-level is found to be negatively correlated with exposure-level. Moreover, the infection level is positively correlated with the population size, which is puzzling since it has not reached the level necessary for population-size to affect infection-level through herd immunity. These issues are resolved if a low-virulence Corona-strain (LVS) began spreading earlier in China outside of Wuhan, and later globally, providing immunity from the later appearing high-virulence strain (HVS). Following its spread into Wuhan, cumulative mutations gave rise to the emergence of an HVS, known as SARS-CoV-2, starting the COVID-19 pandemic. We model the co-infection by an LVS and an HVS, and show that it can explain the evolution of the COVID-19 pandemic and the non-trivial dependence on the exposure level to China and the population-size in each country. We find that the LVS began its spread a few months before the onset of the HVS, and that its spread doubling-time is $\sim 1.59\pm 0.17$ times slower than the HVS. Although more slowly spreading, its earlier onset allowed the LVS to spread globally before the emergence of the HVS. In particular, in countries exposed earlier to the LVS and/or having smaller population-size, the LVS could achieve herd-immunity earlier, and quench the later-spread HVS at earlier stages. We find our two-parameter (the spread-rate and the initial onset time of the LVS) can accurately explain the current infection levels (R^2$\mathrm{=0.74}$; correlation p-value (p) of 5x10^-13$$). Furthermore, countries exposed early should have already achieved herd-immunity. We predict that in those countries cumulative infection levels could rise by no more than 2-3 times the current level through local-outbreaks, even in the absence of any containment measures. We suggest several tests and predictions to further verify the double-strain co-infection model and discuss the implications of identifying the LVS.

Multiple lines of evidence indicate that CD8$^+$ T cells are important in the control of HIV-1 (HIV) replication. However, CD8$^+$ T cells induced by natural infection cannot eliminate the virus or reduce viral loads to acceptably low levels in most infected individuals. Understanding the basic quantitative features of CD8$^+$ T-cell responses induced during the course of HIV infection may therefore inform us about the limits that HIV vaccines, which aim to induce protective CD8$^+$ T-cell responses, must exceed. Using previously published experimental data from a cohort of HIV-infected individuals with sampling times from acute to chronic infection we defined the quantitative properties of CD8$^+$ T-cell responses to the whole HIV proteome. In contrast with a commonly held view, we found that the relative number of HIV-specific CD8$^+$ T-cell responses (response breadth) changed little over the course of infection (first 400 days post-infection), with moderate but statistically significant changes occurring only during the first 35 symptomatic days. This challenges the idea that a change in the T-cell response breadth over time is responsible for the slow speed of viral escape from CD8$^+$ T cells in the chronic infection. The breadth of HIV-specific CD8$^+$ T-cell responses was not correlated with the average viral load for our small cohort of patients. Metrics of relative immunodominance of HIV-specific CD8$^+$ T-cell responses such as Shannon entropy or the Evenness index were also not significantly correlated with the average viral load. Our mathematical-model-driven analysis suggested extremely slow expansion kinetics for the majority of HIV-specific CD8$^+$ T-cell responses and the presence of intra- and interclonal competition between multiple CD8$^+$ T-cell responses; such competition may limit the magnitude of CD8$^+$ T-cell responses, specific to different epitopes, and the overall number of T-cell responses induced by vaccination. Further understanding of mechanisms underlying interactions between the virus and virus-specific CD8$^+$ T-cell response will be instrumental in determining which T-cell-based vaccines will induce T-cell responses providing durable protection against HIV infection.

We evaluated epidemiological evolution and economic impact of COVID-19 pandemic in the European Union (EU) and worldwide, and the effects of control strategies on them. We collected incidence, mortality, and gross domestic product (GDP) data between the first quarter of 2020 and of 2023. Then, we reviewed the effectiveness of the mitigation and zero-COVID control strategies. The statistical analysis was done calculating the incidence rate ratio (IRR) of two rates and its 95% confidence interval (CI). In the EU, COVID-19 presented six epidemic waves. The sixth one at the beginning of 2022 was the biggest. Globally, the biggest wave occurred at the beginning of 2023. Highest mortality rates were observed in the EU during 2020-2021 and globally at the beginning of 2021. In mitigation countries, mortality was much higher than in zero-COVID countries (IRR= 6.82; CI:6.14-7.60; p<0.001). A GDP reduction was observed worldwide, except in Asia. None of the eight zero-COVID countries presented a GDP growth percentage lower than the EU percentage in 2020, and 3/8 in 2022 (p=0.054). COVID-19 pandemic caused epidemic waves with high mortality rates and a negative impact on GDP. The zero-COVID strategy was more effective in avoiding mortality and potentially had less impact on GDP.

In autonomous driving systems, high-speed and real-time image processing, along with object recognition, are crucial technologies. This paper builds upon the research achievements in in-dustrial item sorting systems and proposes an object recognition and sorting system for auton-omous driving. In industrial sorting lines, goods sorting robots often need to work at high speeds to efficiently sort large volumes of items. This poses a challenge to the robot's real-time vision and sorting capabilities, making it both practical and economically viable to implement a real-time and low-cost sorting system in a real-world industrial sorting line. Existing sorting systems have limitations such as high cost, high computing resource consumption, and high power consump-tion. These issues lead to the fact that existing sorting systems are typically used only in large industrial plants. In this paper, we design a high-speed, low-cost, low-resource-consumption FPGA (Field-Programmable Gate Array) based item sorting system that achieves similar perfor-mance to current mainstream sorting systems at a lower cost and consumption than existing sorting systems. The recognition part employs a morphological recognition method, which segments the image using a frame difference algorithm and then extracts the color and shape features of the items. To handle sorting, a six-degree-of-freedom robotic arm is introduced in the sorting segment. The improved cubic B-spline interpolation algorithm is employed to plan the motion trajectory and consequently control the robotic arm to execute the corresponding actions. Through a series of experiments, this system achieves an average recognition delay of 25.26ms, ensures smooth operation of the gripping motion trajectory, minimizes resource consumption, and reduces implementation costs.

An approach to the implementation of neural network for real-time cryptographic data protection with symmetric keys oriented on embedded systems is presented. This approach is valuable especially for onboard communication systems in unmanned aerial vehicles (UAV) because of suitability to hardware implementation. In this study we evaluate the possibility to build such a system in hardware implementation at FPGA. The proposed integrated neural network approach for real-time cryptographic data protection was based on theoretical foundations of neural network cryptographic data protection, new algorithms and structures of neural network data encryption and decryption, modern hardware components with programmable structure. The development and implementation of the on-board neural network system for cryptographic data protection in real-time are based on the following principles: variable composition of equipment; modularity; conveyorization and spatial parallelism; hardware and software modification and making them suitable for data encryption and decryption. The tabular-algorithmic method for calculation of the scalar product has been improved that makes it possible to perform fast calculation of the scalar product of fixed-point and floating-point input data by bringing them to the largest common order of weights and forming tables of macro-partial products. Components of neural network cryptographic data encryption and decryption have been developed on the processor core supplemented by specialized scalar product calculation modules. The specialized hardware for neural network cryptographic data encryption was developed using VHDL for equipment programming in the Quartus II development environment ver. 13.1 and the appropriate libraries, and implemented on the basis of the FPGA EP3C16F484C6 Cyclone III family.

In this work, we offer a novel and accurate method in order to find the solution of the linear differential equations over the intervals [0, 1) based on the generalization of Legendre wavelets. The mechanism is still upon workable implementation of the operational matrix of integration and its derivatives. This method reduces the problems into algebraic equations via the properties of generalized Legendre wavelet (GLW) together with the operational matrix of integration. The function approximation has been picked out in such a way so as to enumerate the connection coefficients in an facile manner. The proposed numerical technique, based on the GLW, has been examined on three linear problems as a consequence of this investigation. The outcomes have shown that this method, as opposed to some other existing numerical and analytical methods, is a very useful and advantageous for tackling such problems.

Globally, non-timber forest products (NTFPs) continue to contribute vastly to addressing the food, poverty reduction, income, and livelihood requirements of people in rural areas. However, as at now, there is no specific existing data highlighting periodic contributions of NTFPs to the economy of the Eastern region and the country. The study analyses the contribution of NTFPs towards economic development in the Eastern region and the achievement of SDGs in Ghana. Through Focus Group Discussions and qualitative analysis, it was concluded that NTFPs contribute immensely towards the economic development of the Eastern region and the country through employment and direct taxes. Ultimately, it is evident from the study that the destruction of the Atiwa forest reserve for the purpose of bauxite mining will widely hinder the country’s achievement of the SDGs. Also, the study found out that residents will continue to exploit forest resources if the core concerns of institutional deficiencies and rural poverty are not addressed. To curb this situation, there should be sustainable, regulated, and authorized harvesting of NTFPs/NWFPs, community/user empowerment, sectoral education and training programmes, etc. Even though these are common solutions, the study found them extremely rare in the study area.

Wheat (Triticum aestivum L.) breeding programs can take over a decade to release a new variety. However, new methods of selection such as genomic selection (GS) must be integrated to decrease the time it takes to release new varieties to meet the demand of a growing population. The implementation of GS into breeding programs is still being explored, with many studies showing its potential to change wheat breeding through achieving higher genetic gain. In this review, we explore the integration of GS for a wheat breeding program by redesigning the traditional breeding pipeline to implement GS. We propose implementing a two-part breeding strategy by differentiating between population improvement and product development. The implementation of GS in the product development pipeline can be integrated into most stages and can predict within and across breeding cycles. Additionally, we explore optimizing the population improvement strategy through GS recurrent selection schemes to reduce crossing cycle time and significantly increase genetic gain. The recurrent selection schemes can be optimized for parental selection, maintenance of genetic variation, and optimal cross-prediction. Overall, we outline the ability to increase the genetic gain of a breeding program by implementing GS and a two-part breeding strategy.

Using the PLCC advantages generates revenue and lowers costs more than might be anticipated. It ensures better decisions by using a more perfect and practical assessment of revenues and costs. Although the supplier selection (SC) product life cycle cost (SCPLCC) is an important consideration among corporations, SCPLCC problem has become associated with deciding how one supplier should be selected from possible alternatives. In this study, we applied two types of goal programming, multiobjective linear programming and revised multichoice goal programming to develop a PLCC-based concept to solve the SCPLCC problem and construct a decision-making tool for application to a case of supply chain management in a Taiwanese light-emitting diode company in the high-tech industry. Our study main contribution Company managers can easily use the two approaches of the SCPLCC model with different parameters to solve SCPLCC model problems. Finally, we comparing five models found RMCGP with weighted linear goal programming had an adequate effect for application to the PLCC concept for high-technology company; this cloud make company decision–makers focus on low PLCC and select better supplier.

Product Design is getting nowadays new challenges on developing new products, since the industry is in a rush to introduce products into the marketplace, where customers demand products faster, cheaper, and free of failures. In the meantime, global companies are always trying to improve their Product Design process to get advantages over their competitors using proven tools like FEMA and mixing methodologies like Fuzzy theories with FMEA. Even today using all this tools and combination of methodologies there is a gap to address and it is required a robust risk analysis solving current issues in the electronic industry. This document aims to reveal a novel integrated method, where Failure Mode and Effect Analysis, Pythagorean Fuzzy Sets and Dimensional Analysis are cohesive into a model that minimize the uncertainty of the ranking and prioritization over the Failure Mode and Effect Analysis execution, helping to identify risks within an accurate grade over possible failures in the Product Design process. A real practical example is used to show the proposed method, where it is identified a robust methodology integration and solid and results using a sensitivity analysis.

Life cycle assessment (LCA) is used frequently as a decision support tool for evaluating different design choices of products based on their environmental impacts. A life cycle usually comprises several phases of varying timespan. The amount of emissions generated from different life cycle phases of a product could be significantly different from one another. In conventional LCA, the emissions generated from the life cycle phases of a product are aggregated at the inventory analysis stage, which is then used as an input for life cycle impact assessment. However, when the emissions are aggregated, the temporal variability of inventory data is ignored, which may result in inaccurate environmental impact assessment. Besides, the conventional LCA does not consider the environmental impact of circular products with multiple use cycles. It poses difficulties in identifying the hotspots of emission-intensive activities with the potential to mislead conclusions and implications for both practice and policy. To address this issue and to analyse the embedded temporal variations in inventory data in a CE context, the paper proposes to calculate the emission intensity for each life cycle phase. It is argued that calculating and comparing emission intensity, based on the timespan and amount of emissions for individual life cycle phases, at the inventory analysis stage of LCA offers a complementary approach to the traditional aggregate emission-based LCA approach. In a circular scenario, it helps to identify significant issues during different life cycle phases and the relevant environmental performance improvement opportunities through product, business model and supply chain design.

In this article we study the presence of chaos in supersymmetric(SUSY) quantum mechanics. For that purpose we present a form of 4-point out of time order correlator(OTOC) for SUSY quantum mechanical systems using tensor product formalism. We calculate the 4-point OTOC for SUSY 1D harmonic oscillator and find that the OTOC is exactly equal to that of 1D bosonic harmonic oscillator system. In similar manner using the eigenstate representation of supersymmetric systems we calculate the generalized higher order out of time order correlator. The higher order OTOC is a more sensitive measure of chaos than the usual 4-point correlator used in literature. Finally, we calculate the generalized 2N-point OTOC for SUSY 1D harmonic oscillator.

In this article, we prove an orthogonal decomposition theorem for real inner product gyrogroups, which unify some well-known gyrogroups in the literature: Einstein, M\"{o}bius, Proper Velocity, and Chen's gyrogroups. This leads to the study of left (right) coset partition of a real inner product gyrogroup induced from a subgyrogroup that is a finite-dimensional subspace. As a result, we obtain gyroprojectors onto the subgyrogroup and its orthogonal complement. We construct also quotient spaces and prove an associated isomorphism theorem. The left (right) cosets are characterized using gyrolines (cogyrolines) together with automorphisms of the subgyrogroup. With the algebraic structure of the decompositions, we study fiber bundles and sections inherited by the gyroprojectors. Finally, the general theory is exemplified for the aforementioned gyrogroups.

Protoflavones, a rare group of natural flavonoids with a non-aromatic B-ring, are best known of their antitumor properties. The protoflavone B-ring is a versatile moiety that may be explored for other pharmacological purposes, but common cytotoxicity of these compounds is a limitation to such efforts. Protoapigenone was previously found to be active against the lytic cycle of Epstein-Barr virus (EBV). Further, the 5-hydroxyflavone moiety is a known pharmacophore against HIV-integrase. The aim of this work was to prepare a series of less cytotoxic protoflavone analogs, and to study their antiviral activity against HIV and EBV. Twenty-seven compounds including 18 new derivatives were prepared from apigenin through oxidative de-aromatization and subsequent continuous-flow hydrogenation, deuteration, and/or 4′-oxime formation. One compound was active against HIV at the micromolar range, and 3 compounds showed significant activity against the EBV lytic cycle at the medium-low nanomolar range. Among these, protoapigenone 1′-O-isopropyl ether (6) was identified as a promising lead due to its 73-times selectivity of its antiviral over its cytotoxic effect, which exceeds that of protoapigenone by 2.4-times. Our results open new opportunities to design new, potent and safe anti-EBV agents based on the natural protoflavone moiety.

In this paper, we introduce a new generalization of the r-Stirling numbers of the second kind based on the q-numbers via an exponential generating function. We investigate their some properties and derive several relations among q-Bernoulli numbers and polynomials, and newly de…ned (q, r, w)-Stirling numbers of the second kind. We also obtain q-Bernstein polynomials as a linear combination of (q, r, w)-Stirling numbers of the second kind and q-Bernoulli polynomials in w.

In the present paper, we introduce (p, q)-extension of Apostol type Frobenius-Euler polynomials and numbers and investigate some basic identities and properties for these polynomials and numbers, including addition theorems, difference equations, derivative properties, recurrence relations and so on. Then, we provide integral representations, explicit formulas and relations for these polynomials and numbers. Moreover, we discover (p, q)-extensions of Carlitz's result [L. Carlitz, Mat. Mag., 32 (1959), 247–260] and Srivastava and Pintér addition theorems in [H. M. Srivastava, A. Pinter, Appl. Math. Lett., 17 (2004), 375–380].

Background: IL-15 is a homeostatic cytokine for human T and NK cells. However, whether other cytokines influence the effect of IL-15 is not known. We have studied the impact that IL-10, TGF-, IL-17A and IFN- have on the IL-15-induced proliferation of human T cells and the expression of HLA class I (HLA-I) molecules. Methods: Peripheral blood lymphocytes (PBL) were labeled with CFSE, and stimulated for 12 days with IL-15 in the absence or presence of the other cytokines. The proportion of proliferating T cells and the expression of cell surface HLA-I molecules were analyzed by flow cytometry. Results: The IL-15-induced proliferation and expansion of T cells was paralleled by an increase in the expression of HC-10-reactive HLA-I molecules, namely on T cells that underwent ≥5-6 cycles of cell division. Noteworthy, the IL-15-induced proliferation of T cells was potentiated by IL-10 and TGF-β, but not by IL-17 or IFN-, and was associated with a decrease in the expression of HC-10-reactive molecules. Conclusions: The cytokines IL-10 and TGF-β potentiate the proliferative capacity that IL-15 has on human T cells in vitro, an effect that is associated with a reduction in the amount of HC-10 reactive HLA class I molecules induced by IL-15.

Uterine leiomyosarcoma (LMS) is a rare and aggressive form of uterine cancer, with a poor prognosis and high number of uterine cancer-related deaths. Chimeric Antigen Receptor (CAR) T-cell therapy is an immunotherapy approach to antigen specific of cancer cell, thereby enhancing the immune system's ability to target and destroy cancer cells. This study aims to investigate the potential of targeting differentially expressed genes (DEGs) as a novel therapeutic strategy using CAR T-cell technology in LMS. Genome datasets were obtained from NCBI-GEO database, Of the five datasets, genes that experienced significant overexpression in at least three datasets were categorized as DEGs, and DEGs were evaluated for protein localization, Gene Ontology, bioactivity, interaction, and overexpression. The results identified 25 DEGs, with ten of them expressed on the plasma membrane; four of them—HMMR, KIF20A, PRC1, and ZWINT—were part of the main protein network derived from the 25 DEGs. The dominant bioactivity of these PMGs involves influencing the cell cycle, particularly processes related to chromosome segregation. In conclusion, HMMR, KIF20A, PRC1, and ZWINT are high-potential DEGs as candidates for tumor-associated antigen CAR T-cell therapy. Further research, both in vitro and in vivo, is needed to enhance the validity of these findings.

Candidate vaccines against African swine fever virus (ASFV) based on naturally attenuated or genetically modified viruses have the potential to generate protective immune responses, although there is no consensus on what defines a protective immune response against ASFV. Studies, espe-cially in sensible host species, focused on unravelling protective mechanisms will contribute to the development of safer and more effective vaccines. The present study provides a detailed analysis of phenotypic and functional data on cellular responses induced by intradermal immunization and subsequent boosting of domestic pigs with the naturally attenuated field strain Lv17/WB/Rie1, as well as the mechanisms underlying protection against intramuscular challenge with the virulent genotype II Armenia/07 strain. The transient mild to moderate increase of IL-8 and IL-10 in serum observed after immunization might be directly correlated with survival. Protection was also associated with a robust ASFV-specific polyfunctional memory T cell response, where CD4CD8 and CD8 T cells were identified as the main cellular sources of virus-specific IFNγ and TNFα. In parallel to cytokine response, these T-cell subsets also showed specific cytotoxic activity as evidenced by the increased expression of the CD107a degranulation marker. Along with virus-specific multifunctional CD4CD8 and CD8 T responses, the increased levels of antigen experienced cytotoxic CD4 T cells observed after challenge in immunized pigs might also contribute to control virulent infection by killing mechanisms targeting infected antigen-presenting cells. Future studies should elucidate whether the memory T-cell responses evidenced in the present study persist and provide long-term protection against further ASFV infections.

Sarcomas are a group of malignancies of mesenchymal origin with plethora of subtypes. Given the sheer heterogeneity of various subtypes and rarity of the disease, management of sarcomas has been challenging with poor patient outcomes. Surgery, radiation therapy and chemotherapy have remained the backbone of treatment in patients with sarcoma. The introduction of immunotherapy has rev-olutionized the treatment of various solid and hematological malignancies. In this review, we discuss basics of immunotherapy and immune microenvironment in sarcomas, various modalities of im-munotherapy such as immune checkpoint blockade, oncolytic viruses, cancer targeted antibodies, vaccine therapy and adoptive cell therapies like CAR T-cell therapy, T cell therapy, TCR therapy.

Persistent human papillomavirus (HPV) infection is responsible for practically all cervical and a high proportion of anogenital and oropharyngeal cancers. Therapeutic HPV vaccines in clinical development show great promise in improving outcomes for patients who mount an anti-HPV T cell response, but far from all patients elicit a sufficient immunological response. This witnesses a translational gap between animal models and human patients. Here, we investigated the potential of a new assay consisting of co-culturing vaccine-transduced dendritic cells (DCs) with syngeneic healthy human peripheral blood mononuclear cells (PBMCs) to mimic a human in vivo immunization. This new promising human ex vivo PBMC assay was evaluated using an innovative therapeutic adenovirus (Adv)-based HPV vaccine encoding the E1, E2, E6, and E7 HPV16 genes. This new method allowed us to show that vaccine-transduced DCs yielded functional effector T cells and unveiled information on immunohierarchy showing E1-specific T cell immunodominance over time. We suggest that this assay can be a valuable translational tool to complement the known animal models, not only for HPV therapeutic vaccines, and supports the use of E1 as an immunotherapeutic target. Nevertheless, the findings reported here need to be validated in a larger number of donors, and preferably in patient samples.

(1) Background: SARS-CoV-2 infection is mostly accompanied by mild COVID-19 symptoms in children. However, the multisystem inflammatory syndrome (MIS-C) and long-term sequelae are often severe complications. Therefore, the protection of the pediatric population against SARS-CoV-2 with effective vaccines is particularly important. Here we compare the humoral and cellular immune responses elicited in children (n=15) aged 5-11 years vaccinated with RBD-based vaccines combined in a heterologous scheme of SOBERANA® 02 and SOBERANA® Plus with those from children (n=10) aged 4-11 years who recovered from mild symptomatic COVID-19. (2) Methods: Blood samples were taken 14 days after last dose for vaccinated and 45-60 days after the infection diagnosis for COVID-19 recovered children. Anti-RBD IgG and ACE2-RBD inhibition were assessed by ELISA; IgA, cytokine and cytotoxic related proteins profile were determined by multiplex assays. Total B and T cell subpopulations and IFN-γ release were measured by multiparametric flow cytometry using a large panel of antibodies after in vitro stimulation with S1 peptides. (3) Results: Significant higher levels of specific anti-RBD IgG and IgA and ACE2-RBD inhibition capacity were found in vaccinated children in comparison to COVID-19 recovered children. Th1-like and Th2-like CD4+ T cells were also significantly higher in vaccinated subjects. IFN-γ secretion were higher in central memory CD4+ T cells of COVID-19 recovered children, but no differences between both groups were found in CD4+ and CD8+ T cells effector, terminal and naïve T cell subpopulations. High levels of IL-2, IL-6, IFN-γ and IL-10 in contrast to low levels of IL-4 suggesting a predominant Th1 cell polarization. Cytotoxic-related proteins granzyme A and B, perforin and granulin were also found in the supernatant after S1 stimulation in both vaccinated and recovered children. (4) Conclusions: Vaccination with the heterologous scheme of SOBERANA® 02/ SOBERANA® Plus induces strong antibody and cellular immune response compared to natural infections of young children.

The focus of the current research indicates a new Bianchi type-V anisotropic, homogeneous astrophysical model with modified theory of f(R, T) gravity and Λ(t), time-dependent cosmological constant. The significant effect of the model is that the field equations solutions find using a time-dependent quadratic deceleration parameter. We observed anisotropy parameter remains constant both in the belated universe and early universe. The deportment of the equation of state (EOS) parameter, pressure, and energy density, cosmological constant and other parameters are also discussed. This cosmological model indicated the possibility of an accelerating universe with negative pressure, such as a universe dominated by dark energy. Om(z) diagnostic test suggested that the universe starts with quintessence nature and ends as a phantom model. Also, energy conditions of this model are represented here to ensure the model is physically reasonable and based on observations.

ABSTRACT: Recurrent glioblastoma (rGBM) is a highly aggressive form of brain cancer that poses a significant challenge for treatment in neurooncology, and the survival status of patients after relapse usually means rapid deterioration, and also the leading cause of death among patients. In recent years, immunotherapy has emerged as a promising strategy for the treatment of recurrent glioblastoma by stimulate the body's immune system to recognize and attack cancer cells , which could be used as a in combination with other treatments such as surgery, radiation, and chemotherapy to improve outcomes for patients with recurrent glioblastoma, This therapy combines several key methods such as the use of monoclonal antibodies, chimeric antigen receptor T cell (CAR-T) therapy, checkpoint inhibitors, oncolytic viral therapy cancer vaccines, and combination strategies. In this review, we mainly document the latest immunotherapies for the treatment of glioblastoma and focus on the rGBM especially.

Intestinal commensal microbes, called the gut microbiota, play a critical role in host immune homeostasis through active microbial metabolites and innate and adaptive immune responses. Dysbiosis or imbalance of the gut microbiota composition is associated with inflammatory bowel disease (IBD) which includes Crohn’s disease and ulcerative colitis. The incidence and prevalence rates of IBD have been increasing worldwide. It is well recognized that butyrate, a microbial metabolite of diet fibers, is a major energy source for colonocytes and plays a crucial role in regulating immune function and maintaining epithelial barrier function and intestinal homeostasis. Emerging evidence suggests that butyrate might be a potential therapeutic agent to treat IBD. In this review, we discuss about gut microbial metabolites, particularly butyrate, the synthesis and metabolism of butyrate, mechanisms of butyrate in immune and epithelial barrier function. Furthermore, we review the current research on various therapeutic implications of butyrate in IBD.

Diffuse intrinsic pontine glioma (DIPG) is recognized as a pediatric brainstem cancer with a 0% survival rate. On a molecular basis, DIPG commonly results from mutations in histone H3, specifically a mutation in the H3K27M gene, that promotes tumorigenesis and results in presentation of this fatal brainstem tumor. DIPG is challenging to treat, as surgical intervention is inefficacious due to the location where the glioma resides. To date, traditional treatments such as radiation, chemotherapy, and immunotherapy have not increased survival rates and have only been successful at relieving symptoms. Future therapeutic approaches such as proton beam radiation, Chimeric Antigen Receptor T Cell (CAR-T) immunotherapy, and alternative epigenetic pharmaceuticals are under investigation for potential benefits. Various clinical trials have also explored these treatment procedures to discover potential increases in survival rates in both animal and human studies. In this review, we will evaluate the pathology and molecular characteristics of DIPG, the current and future approaches to DIPG treatment; and, lastly, we will discuss clinical trials that have been completed to develop successful treatment options.

Hepatitis B virus (HBV) is known to cause severe liver diseases such as acute or chronic hepatitis, liver cirrhosis and hepatocellular carcinoma. Chronic hepatitis B (CHB) infection is a major health problem with nearly 300 million individuals infected worldwide. Currently, nucleos(t)ide analogs (NAs) and interferon alpha are clinically approved treatments for HBV infection. NAs are potent antiviral agents that bind to HBV polymerase and block viral reverse transcription and replication. Besifovir dipivoxil maleate (BSV) is a newly developed NA against HBV in the form of acyclic nucleotide phosphonate that is available for oral administration similar to adefovir and tenofovir. Until now, resistance to BSV treatment has not been reported. In this study, we found a CHB patient who showed viral breakthrough after long-term treatment with BSV. The isolated HBV DNA from patient’s serum were cloned into the replication-competent HBV 1.2mer and the sequence of reverse transcriptase (RT) domain of HBV polymerase were analyzed. We also examined the drug susceptibility of generated clones in vitro. Several mutations were identified in HBV RT domain. A particular mutant harboring ten RT mutations showed resistance to BSV treatment in vitro. The ten mutations include rtV23I (I), rtH55R (R), rtY124H (H), rtD134E (E), rtN139K (K), rtL180M (M), rtM204V (V), rtQ267L (L), rtL269I (I) and rtL336M (M). To further identify the responsible mutations for BSV resistance, we performed in vitro drug susceptibility assay on several artificial clones. As a result, our study revealed that rtL180M (M) and rtM204V (V) mutations, already known as lamivudine-resistant mutations, confer resistance to BSV in the CHB patient.

Targeted radionuclide therapy (TRT) has recently seen a surge in popularity, with the use of radionuclides conjugated to small molecules and antibodies. Similarly, immunotherapy also has shown promising results – an example being chimeric antigen receptor (CAR) T-cells therapy in hematologic malignancies. Moreover, TRT and CAR T therapies possess unique features that require special consideration when determining how to dose, time, and sequence combination treatments, including the distribution of TRT dose in the body, the decay rate of the radionuclide, and the proliferation and persistence of the CAR-T cells. These characteristics complicate additive or synergistic effects of combination therapies and warrant a mathematical treatment which includes these dynamics in relation to the proliferation and clearance rates of the target tumor cells. Here we combine two previously published mathematical models in a multiple myeloma setting to explore the effects of dose, timing, and sequencing of TRT and CAR-T cell based therapies. We find that for a fixed TRT and CAR-T cell dose, the tumor proliferation rate is the most important parameter in determining the best timing of TRT and CAR T therapies.

In this tutorial review, we compare and contrast the chemical mechanisms of electrophile/oxidant sensing, and the molecular mechanisms of signal propagation. We critically analyze biological systems in which these different pathways are believed to be manifest and what the data really mean. Finally, we discuss applications of this knowledge to disease treatment and drug development.

Healthy human subjects develop spontaneous CD8+ T cell responses to melanocyte antigens (MA) expressed by normal melanocytes, such as Tyrosinase, MAGE-A3, Melan/Mart-1, gp100, and NY-ESO-1. This natural autoimmunity directed against melanocytes might confer protection against the development of malignant melanoma (MM), where MA are present as overexpressed tumor-associated antigens. Consistent with this notion we report here that functional T cell reactivity to MA was found to be diminished in untreated MM patients: while 57.5% of healthy controls (n=40) exhibited high-frequency MA-specific T cell reactivity ex vivo, such was detected in only 12% of the untreated MM patients (n=24). Three lines of evidence suggest that the MA-reactive T cells present in healthy subjects undergo exhaustion once MM establishes itself. First, only the MA-specific T cell reactivity was affected in the MM patients; that to third party recall antigens was not. Second, in these patients, the residual MA-specific T cells, unlike third party antigen reactive T cells, were functionally impaired, showing a diminished per cell IFN-γ productivity. Third, successful immunotherapy with AGI-101H melanoma vaccine restored natural CD8+ T cell autoimmunity to MA in 85% of the vaccinated patients (n= 27). The role of natural T cell autoimmunity to tumor-associated MA is discussed based on discrete levels of T cell activation thresholds.

Cellular therapy has emerged as an attractive option for the treatment of cancer, and adoptive transfer of chimeric antigen receptor (CAR) expressing T cells has gained FDA approval in hematologic malignancy. However, limited efficacy has been observed utilizing CAR-T therapy in solid tumors. Natural killer (NK) cells are crucial for tumor surveillance and exhibit potent killing capacity of aberrant cells in an antigen-independent manner. Adoptive transfer of unmodified allogeneic or autologous NK cells has shown limited clinical benefit due to factors including low cell number, low cytotoxicity and failure to migrate to tumor sites. To address these problems, immortalized and autologous NK cells have been genetically engineered to express high affinity receptors (CD16), CARs directed against surface proteins (PD-L1, CD19, Her2, etc.) and endogenous cytokines (IL-2 and IL-15) that are crucial for NK cell survival and cytotoxicity, with positive outcomes reported by several groups both preclinically and clinically. With a multitude of NK cell-based therapies currently in clinic trials, it is likely they will play a crucial role in next-generation cell therapy-based treatment. In this review we will highlight the recent advances and limitations of allogeneic, autologous and genetically enhanced NK cells used in adoptive cell therapy.

MIMO (multiple-input multiple-output) radar provides much more flexibility than the traditional radar for its ability to realize far more observation channels than the actual number of T/R (transmit and receive) elements. Designing the array of MIMO imaging radar, the commonly used virtual array theory generally assumes that all elements are placed on the same line. However, due to the physical size of the antennas and coupling effect between T/R elements, a certain height difference between T/R arrays is essential, resulting in the defocusing of edge points of the scene. On the other hand, the virtual array theory implies far-field approximation, leading to inevitable high grating lobes in the imaging result of near-field edge points of the scene observed by common MIMO array. To tackle these problems, this paper derives the relationship between target’s PSF (point spread function) and pattern of T/R arrays, by which the design criterion of near-field imaging MIMO array is presented. Firstly, the proper height between T/R arrays is designed to focus the near-field edge points well. Secondly, the far-field array is modified to suppress the grating lobes in the near-field area. Finally, the validity of the proposed methods is verified by simulations and an experiment.

Advancements in technology have revolutionized communication on social media platforms, where reviews and comments greatly influence product selection. Current opinion mining methods predominantly focus on textual content, overlooking the rich information within customer-posted images, termed here as Multus-Medium. This research introduces an innovative deep learning approach, Multus Medium Opinion Mining (MMOM), capitalizing on both text and image data for comprehensive product review analysis. MMOM employs an integrated model of Bidirectional Long Short-Term Memory (BiLSTM) and embedded Convolutional Neural Network (CNN), incorporating architectures of GoogleNet and VGGNet, thus enabling efficient extraction and fusion of textual and visual features. This synergistic approach enables data collection, preprocessing, feature extraction, fusion strategy-based feature vector generation, and subsequent product recommendation. Performance evaluation on two diverse real-world datasets name as “flicker8k” and “t4sa”. These datasets show substantial improvement over existing methods. MMOM outperforms standard benchmark models, achieving an accuracy, F1 score and ROC over fliker8k are 90.38%, 88.75% and 93.08%, whereas for twitter dataset are 88.54%, 86.34%, and 92.26% respectively, the accuracy of purposed model is 7.34% and 9.54% higher than the other two mentioned techniques. These statistics highlight the robustness and applicability of MMOM across various domains. The compelling results underscore the potential of MMOM, providing a more holistic and precise approach to opinion mining in the era of social media product reviews. This research, product recommendation helps the customer to make purchasing decision. Last but not the least, the purposed scheme can further be expanded in any other sentiment task like hospital recommendation system, crop farming recommendation and medical diagnostic system etc.

In order to harmonize supply and demand of green energy, new future-proof technologies are needed. Here, hydrogen plays a key role. Within the current framework conditions, the production of green hydrogen is not yet economically viable. The use of the oxygen produced and the possible increase in efficiency associated with it mostly remains unconsidered. The aim is to demonstrate that the economic efficiency of a power-to-gas (PtG) project can be increased by using the by-product oxygen. In this research project, a water electrolyser connected to grid is powered to supply hydrogen to a hydrogen refuelling station. By utilising the by-product oxygen from water electrolysis for a wastewater treatment plant (WWTP), it is shown that the net present value (NPV) of the project can be improved by up to 13 % compared to the initial scenario. If a photovoltaic (PV) system is used in addition to grid electricity for higher green hydrogen production, the NPV can be further improved by up to 58 %. The levelized cost of hydrogen (LCOH) is calculated for different scenarios with and without oxygen configuration. A sensitivity analysis is then performed to find important parameters.

Supplier selection (SC) product life cycle cost (SCPLCC) is an important consideration among corporations, SCPLCC problem has become associated with deciding how one supplier should be selected from possible alternatives. In this study, we applied two types of goal programming, multiobjective linear programming and revised multichoice goal programming to develop a PLCC-based concept to solve the SCPLCC problem and construct a decision-making tool for application to a case of supply chain management in a Taiwanese light-emitting diode company in the high-tech industry. Our study main contribution Company managers can easily use the two approaches of the SCPLCC model with different parameters to solve SCPLCC model problems. Finally, we comparing five models found RMCGP with weighted linear goal programming had an adequate effect for application to the PLCC concept for high-technology company; this cloud makes company decision–makers focus on low PLCC and select a better supplier in sustainable supply chains goal.

The article is devoted to biological models using recurrence sequences, which are connected with the harmonic progression 1, 1/2, …, 1/n, and some cooperative properties of genomes. The harmonic progression is itself one of the recurrence sequences based on the harmonic mean. This progression appears in the hyperbolic rules of oligomer cooperative organization in eukaryotic and prokaryotic genomes. This allows thinking that the harmonic progression is also related to inherited physiological systems, which must be structurally consistent with the genetic coding system for their transmission to descendants and survival in evolution. The harmonic progression is one of historically known mathematical series, whose features were studied by Pythagoras, Leibniz, Newton, Euler, Fourier, Dirichlet, Riemann. It is widely used in many known algorithms and is closely related to some other important mathematical objects, for example, the function of the natural logarithm and harmonic numbers. Accordingly, the article describes the possibilities of using these interrelated mathematical objects to model biological structures, including logarithmic spirals and some other. Modeling inherited spiral configurations seems to be a particularly urgent task, since they are extremely common at all levels of organization of living bodies and, according to Goethe, are lines of life. The principle of a recurrence similarity, that is a special similarity of parts and transformations presented in recurrence sequences of numbers and matrix operators (the scale similarity and scale transformations are only particular cases of such similarity), is considered as one of the key principles of structural organization of living bodies.

The author's method of oligomer sums for analysis of oligomer compositions of eukaryotic and prokaryotic genomes is described. The use of this method revealed the existence of general rules for cooperative oligomeric organization of a wide list of genomes. These rules are called hyperbolic because they are associated with hyperbolic sequences including the harmonic progression 1, 1/2, 1/3, .., 1/n. These rules are demonstrated by examples of quantitative analysis of many genomes from the human genome to the genomes of archaea and bacteria. The hyperbolic (harmonic) rules, speaking about the existence of algebraic invariants in full genomic sequences, are considered as candidates for the role of universal rules for the cooperative organization of genomes. The described phenomenological results were obtained as consequences of the previously published author's quantum-information model of long DNA sequences. The oligomer sums method was also applied to the analysis of long genes and viruses including the COVID-19 virus; this revealed, in characteristics of many of them, the phenomenon of such rhythmically repeating deviations from model hyperbolic sequences, which are associated with DNA triplets. In addition, an application of the oligomer sums method are shown to the analysis of the following long sequences: 1) amino acid sequences in long proteins like the protein Titin; 2) phonetic sequences of long Russan literary texts (for checking of thoughts of many authors that phonetic organization of human languages is deeply connected with the genetic language). The topics of the algebraic harmony in living bodies and of the quantum-information approach in biology are discussed.

In this paper, we provide some enlightening examples of the application of Clifford algebra in geometry, which show the concise representation, simple calculation and profound insight of this algebra. The definition of Clifford algebra implies geometric concepts such as vector, length, angle, area and volume, and unifies the calculus of scalar, spinor, vector and tensor, so that it is able to naturally describe all variables and calculus in geometry and physics. Clifford algebra unifies and generalizes real number, complex, quaternion and vector algebra, converts complicated relations and operations into intuitive matrix algebra independent of coordinate systems. By localizing the basis or frame of space-time and introducing differential and connection operators, Clifford algebra also contains Riemann geometry. Clifford algebra provides a unified, standard, elegant and open language and tools for numerous complicated mathematical and physical theories. Clifford algebra calculus is an arithmetic-like operation that can be well understood by everyone. This feature is very useful for teaching purposes, and popularizing Clifford algebra in high schools and universities will greatly improve the efficiency of students to learn fundamental knowledge of mathematics and physics. So Clifford algebra can be expected to complete a new big synthesis of scientific knowledge.

Solar energy is a renewable resources of energy which is broadly utilized and have the least pollution impact between the available alternatives of fossil fuels. In this investigation, machine leaening approaches of neural networks (NN), neuro-fuzzy and least squares support vector machine (LSSVM) are used to build the models for prediction of the thermal performance of a photovoltaic-thermal solar collector (PV/T) by estimating its efficiency as an output of the model while inlet temperature, flow rate, heat, solar radiation, and heat of sun are input of the designed model. Experimental measurements was prepared by designing a solar collector system and 100 data extracted. Different analyses are also performed to examine the credibility of the introduced approaches revealing great performance. The suggested LSSVM model represented the best performance regarding the mean squared error (MSE) of 0.003 and correlation coefficient (R²) value of 0.99, respectively.

Formalism proofing general derivation, applying matrix properties operations, showing fundamental relationships with inner product to outer product has been advanced here. This general proof formalism has direct application with physics to quantify quantum density at micro scale level to time commutator at macro scale level. System of operator algebraic equations have been rigorously derived to obtain analytic solutions which are physically acceptable. Extended physics application will include metricizing towards unitarization to achieve gaging Hamiltonian mechanics to electromagnetic gravitational strong theory, towards grand unifying physics atomistic to astrophysics or vice versa via quantum relativistic general physics thereby patching to classical physics fields energy.

We recently identified that cerebral mRNA expression for inducible costimulator (ICOS) and its ligans, ICOSL, both significantly increases during elimination of Toxoplasma gondii cysts from the brains of infected mice by perforin-mediated cytotoxic activity of CD8⁺ T cells. In the present study, we examined the role of ICOS in activating the effector activity of CD8⁺ T cells in response to the cysts in infected mice. Following adoptive transfer of splenic CD8⁺ T cells from chronically infected ICOS-deficient (ICOS^-/-) and wild-type (WT) mice to infected SCID mice, fewer CD8⁺ T cells were detected in the brains of the recipients of ICOS^-/- than WT CD8⁺ T cells. However, such lower numbers of ICOS^-/- CD8⁺ T cells, which migrated into the brains of the recipients, eliminated T. gondii cysts more efficiently than WT CD8⁺ T cells did. Consistently, the ICOS^-/- CD8⁺ T cells secreted greater amounts of granzyme B in response to T. gondii antigens in vitro than did WT CD8⁺T cells. We identified that ICOS^-/- CD8⁺ T cells express significantly greater levels of CD28 on their surface than WT CD8⁺ T cells, and relative expression levels of CD28 mRNA in ratios to CD8b mRNA levels in the brains of the recipients of those CD8⁺ T cells strongly correlated with their relative expression levels of mRNA for T-bet transcription factor and perforin. Furthermore, blocking of CD28 signaling by a combination of anti-CD80 and anti-CD86 antibodies abolished the increased cytotoxic activity of the ICOS^-/- CD8⁺ T cells in vitro. The present study uncovered notable compensatory interactions between ICOS and CD28 to secure the cytotoxic effector activity of CD8⁺ T cells against a microbial infection in a murine model of chronic infection with T. gondii.

Chimeric antigen receptor T cells (CAR-Ts) have shown a remarkable efficacy in hematological malignancies, but limited responses in solid tumors. Among solid tumors, CAR-T cell therapy was particularly explored in brain tumors. CAR-T cells have shown a limited clinical efficacy in various types of brain tumors due to several factors that have hampered their activity, including tumor antigen heterogeneity (not all tumor cells express the target antigen), the limited access of CAR-T cells to brain tumor cells, limited CAR-T cell trafficking and in vivo persistence and the presence of a highly immunosuppressive tumor microenvironment. Despite these considerations, some recent studies have shown promising anti-tumor activity of GD2-CAR-T cells on diffuse midline gliomas and neuroblastomas and of CARv3-TEAM-E cells in glioblastomas. However, strategies are required to improve the effect of CAR-T cells in brain tumors, including advanced CAR-T cell design with multiple antigenic targeting and incorporation of combination therapies.

Dengue virus is a global health problem most prevalent in tropical and subtropical regions. However, after the approval of two vaccines, Dengvaxia, TV003/TV005 of Takeda, for its prevention, problems were reported, like enhanced risks of infection or less efficiency of protection. Since then, more struggles have been in demand for the development of better vaccines. Here, we conducted a new design through an in-silico strategy. Initially, epitopes were chosen based on their antigenicity, immunogenicity, and binding affinity with MHC molecule, while excluded with allergenicity, toxicity and potential risk of antibody dependent enhancement. Subsequently, a core antigen was constructed with selected epitopes and linked with distinct adjuvant proteins to achieve three candidate vaccines, PSDV-1~3. PSDV-2 was chosen for further validation based on their advantage in physicochemical and structural properties. With a panel of simulations, this artificial protein showed tight binding with pattern recognition receptors, good stability, robust immune induction, and ultimately was confirmed as a high quality vaccine candidate. The plasmid for its recombinant expression was then designed accordingly. With our new design, one more choice was obtained for the effective protection from Dengue virus. Further experimental validations are still require to confirm it protection capacity and safety.

Simple Summary: Breast cancer is the most common invasive cancer among women. Triple-negative breast cancer (TNBC) accounts for 15–20% of newly diagnosed breast cancers and has the worst prognosis. However, TNBC patients are not a homogeneous group, and there are differences in the course of the disease as well as in response to treatment. For this reason, differentiation of subtypes of this tumor is important for optimal therapeutic decision and risk prediction. The presented study focuses on the expression of the androgen receptor (AR) and the infiltration of T-lymphocytes in the tumor stroma (TILs) of TNBC patients. Correlation of these tested biomarkers with standard prognostic factors. Defining new prognostic factors for 3-year overall survival (OS). Abstract: Background: Analysis of the practical benefit of testing the expression of AR and the TILs in patients with TNBC and their correlation with standard prognostic factors. Methods: The study group consisted of 86 female patients treated for TNBC. T-lymphocyte infiltration was examined in H+E staining. AR expression, CD8 and CD4 T-lymphocytes were evaluated in immunohistochemistry. Results: Significantly negative correlation was found between AR expression and the CD8 T-lymphocyte infiltration levels. A significant negative correlation was found between the AR expression and G and Ki 67, and a positive correlation between the TILs levels and G and Ki 67. Patients with AR expression and low TILs levels had the highest percentage of diagnosed distant metastases and 3-years OS. Patients with high TILs no distant metastases or deaths were diagnosed. The level of TILs turned out to be a significant independent prognostic factor. Conclusions: Based on the assessment of AR expression and TILs infiltration, the group of highest and lowest risk was determined. The prognostic factor of known parameters such as TNM and a new factor - TILs was confirmed. On the other hand, parameters such as G and Ki 67 and the tested factor - AR had no effect on the prognosis.

Immune responses to influenza (flu) antigens reflect memory to prior infections or vaccinations, which might influence immunity to new flu antigens. Memory of past antigens has been termed “original antigenic sin” or more recently “immune imprinting” and “seniority”. We have researched a comparison between the immune response to live flu infections and inactivated flu vaccina-tions. A brief history of antibody generation theories is presented culminating in new findings about the immune-network theory suggesting that a network of clones exists between an-ti-idiotypic antibodies and T cell receptors. Findings regarding the 2009 pandemic flu strain and immune responses to it are presented, including memory B cells and conserved regions within the hemagglutinin protein. The importance of CD4+ memory T cells and cytotoxic CD8+ T cells responding to both infections and vaccinations are discussed and compared. Innate immune cells like natural killer (NK) cells and macrophages are discussed regarding their roles in adaptive immune responses. Antigen presentation via macroautophagy processes are described. New vaccines in development are mentioned along with the results of some clinical trials. The manu-script concludes with how repeated vaccinations are impacting the immune system and a sketch of what might be behind the imprinting phenomenon, including future research directions.

A set of polymer composite bolted T-joints with novel configuration consisting of internal skeleton and external skin was fabricated using a prepreg-RTM co-curing molding process. Experiments were conducted to study their mechanical properties under bending load. A finite element model with a polymer resin area between the skin and skeleton was established and verified by the experimental results. Then, the damage propagation process and failure mechanism of the joint and the influence of three factors related to the layer characteristics of the skin and skeleton were investigated by the validated models. The results show that the bending stiffness and the yield limit load of the novel composite T-joint are 0.81 times and 1.65 times that of the 2A12 aluminum T-joint respectively, while at only 55.4% of its weight. The damage of the joint initiates within the resin area and leads to a degradation of the joint bending performances. The preferred stacking sequence of the skeleton is [0/+45/90/-45]ns when primarily subjected to bending loads. The decrease in bending performances is within 5% with the inclining angle of the skeleton less than 12 degrees. The more layers of 90° in the skin, the better bending performances of the joints, while the more layer of 0°, the poorer bending performances.

Calpain is delineated as a superfamily of cysteine proteases containing a CysPC motif within their genes. Among the fifteen species of mammalian homologs, calpain-1 and -2, which are categorized as conventional isozymes, execute limited proteolysis in a calcium-dependent fashion. Accordingly, the calpain system participates in physiological and pathological phenomena, encompassing cell migration, apoptosis, skeletal muscle integrity, and synaptic plasticity. The dysregulation of the calpain system has been inextricably linked to a multitude of diseases, such as ischemic and degenerative diseases, rendering it a subject of profound interest in the fields of basic research and pharmaceutical development aimed at therapeutic interventions. Recent investigations have unveiled the contributions of both conventional and unconventional calpains to the pathogenesis of cardiometabolic disorders, such as atherosclerosis, diabetes, and hepatic diseases. Consequently, the present review accentuates the pivotal role of calpains in the complications of cardiometabolic diseases and embarks upon a discourse regarding calpains as molecular targets.

Background. Waning of neutralizing and cell-mediated immune response after the primary vac-cine cycle (PVC) and the first booster dose (BD) is of concern, especially for PLWH with a CD4 count ≤200 cells/ mm3.Methods.Neutralizing antibodies (nAbs) titers by microneutralization assay against WD614G /Omicron BA.1 and IFNγ production by ELISA assay were measured in samples of PLWH at 4 time points [2 and 4 months post-PVC (T1 and T2), 2 weeks and 5 months after the BD (T3 and T4)]. Participants were stratified by CD4 count after PVC (LCD4, <200/mm3; ICD4, 201-500/mm3 and HCD4, >500/mm3). Mixed models were used to compare mean responses over T1-T4 across CD4 groups. Results. 314 PLWH on ART (LCD4=56; ICD4=120; HCD4=138) were enrolled. At T2, levels of nAbs were significantly lower in LCD4 vs ICD4/HCD4 (p=0.04). BD was crucial for increasing nAbs titres above 1:40 at T3 and up to T4 for WD614G. A positive T cell response after PVC was observed in all groups, regardless of CD4 (p=0.31). Conclusions. Waning of nAbs after PVC was more important in LCD4 group. BD managed to re-establish higher levels of nAbs against WD614G which were retained for 5 months. The level of T-cellular response was significantly higher in HCD4 and ICD4 compared to the LCD4 group although it remained above detectable levels over the entire study period regardless of CD4 count. Keywords: HIV-1 infection; SARS-CoV-2 infection;

Myelodysplastic syndromes or neoplasms (MDS) are a heterogeneous group of myeloid clonal disorders characterized by peripheral blood cytopenias, blood and marrow cell dysplasia and an increased risk for evolution to acute myeloid leukemia (AML). Non-coding RNAs, especially microRNAs and long non-coding RNAs serve as regulators of normal and malignant hematopoiesis and have been implicated in carcinogenesis. This review will present a comprehensive summary of the biology and role of non-coding RNAs, including the less studied circRNA, siRNA, piRNA, and snoRNA as potential prognostic and/or predictive biomarkers or therapeutic targets in MDS.

Ubiquitin-Specific-peptidase 22 (Usp22) cleaves ubiquitin moieties from numerous proteins, in particular transcription factors. Recently, it was reported that Usp22 acts as negative regulator of interferon-dependent responses. In the current study, we investigated the role of Usp22 deficiency upon acute viral infection with lymphocytic choriomeningitis (LCMV) virus. We found that lack of Usp22 on bone marrow derived cells (Usp22 fl/fl Vav1-Cre mice) reduced induction of type I and II interferons. Limited type I interferon response did not influence virus replication. However, restricted expression of PD-L1 led to increased frequencies of functional virus-specific CD8+ T cells and rapid death of Usp22 deficient mice. CD8+ T cell depletion experiments revealed that accelerated CD8+ T cells were responsible for enhanced lethality in Usp22 deficient mice. In conclusion, we found that the lack of Usp22 generated a pathological CD8+ T cell response, which gave rise to severe disease in mice.

B and T lymphocytes demonstrate important alterations in patients with Systemic Lupus Erythematous (SLE), with significant up-regulation of Double Negative (DN) B cells. Aim of this study was to evaluate correlation of T cell immunity changes with the distinct B cell-pattern SLE. In the present study, Flow cytometry was performed in 30 patients with SLE, on remission, and 31 healthy controls, to detect DN B cells (CD19+IgD-CD27-) and a wide range of T lymphocyte subpopulations, based on the presence of CD45RA, CCR7, CD31, CD28, CD57, defined as naive, memory and advanced differentiated/senescent T cells. Both B and T lymphocytes were significantly reduced in SLE patients. However, the percentage of DN B cells were increased, compared to HC, 12.9(2.3-74.2) vs. 8(1.7-35), p=0.04. Distribution of CD4 and CD8 lymphocytes demonstrated a shift to advanced differentiated subsets. The population of DN B cells had significant positive correlation with most of early differentiated T lymphocytes, CD4CD31+, CD4CD45RA+CD28+, CD4CD45RA+CD57-, CD4CD45RA-CD57-, CD4CD28+CD57-, CD4CD28+CD57+, CD4 CM, CD8 CD31+, CD8 NAÏVE, CD8CD45RA-CD57-, CD8CD28+CD57-, CD8CD28+CD57+. Multiple Regression analysis revealed CD4CD31+, CD8CD45RA-CD57- and CD8CD28+CD57- cells as independent parameters contributing to DN B cells, adjusted R2=0.534, p<0.0001. The predominance of DN B cells in patients with SLE is closely associated with early differentiated T lymphocyte subsets, indicating a potential causality role of DN B cells in T lymphocyte activation.

RNA interference is a highly conserved process in which non-coding small RNAs (sRNA) modulate gene expression at the post-transcriptional level influencing plant growth and development. Dicer-like (DCL), Argonaute (AGO) and RNA-dependent RNA polymerase (RDR) are the core elements involved in gene silencing and their gene families have been explored in many plants. However, these genes and their response to abiotic stresses have not yet been well in wheat. In this study, 82 AGO, 31 DCL, and 31 RDR genes were identified and phylogenetic analysis of these proteins showed that clustered into ten, four and four clades respectively. RNA-seq analysis revealed constitutive expression of AGO1, AGO9, and DCL2 family expression analysis in tissues under normal and stress conditions, whereas RDR1 which is known to engage in siRNA biogenesis showed higher expression levels in wheat leaf tissues. Our findings build the foundation for comparative genomics analyses of RNA silencing elements in cereal crops, as well as new insights into the functional complexity of RNA silencing in wheat stress responses, which is critical for understanding the processes underlying wheat stress responses.

The most widely spread and neglected zoonotic disease – Leptospirosis, with an estimated 1.03 million cases and 58,900 deaths occurring annually, is a concern and can be prevented only by effective immunization. Due to the urgent need for a novel vaccine, various research organizations have been evaluating the protective immune response elicited by recombinant vaccines. In this study amino-acid sequences of Outermembrane protein (OMPL) 1, LipL 32, 41 and 46 from ten pathogenic serovars of Leptospira were selected to obtain epitopes that induce CD4+ and CD8+ T cell responses by binding to the MHC molecules. These B cell and T cell epitopes were used to design multi-epitope vaccine to which an adjuvant sequence was added at the N-terminal end and appropriate linkers were used to join the different epitopes to increase the efficiency of the vaccine constructs. Using an immuno-informatics approach, constructs were analyzed for the physiochemical properties, secondary and tertiary structure and its validation, docking with different receptors and prediction of binding affinity for each docked complex, followed by molecular dynamics simulation. Taking in consideration all the results, multi-epitope constructs designed may prove to be promising vaccine candidates against Leptospirosis and warrants experimental validation.

γδT have functions of innate and adaptive immunity, with the potential to induce durable responses while being well-tolerated, with limited adverse effects, making it attractive as a tool for immunotherapy. γδT faces challenges as a frontline tool in clinical oncology, with limited response rates due to difficulties in reaching tumor sites with consistent cytotoxic activity and strength. Modulated Electro-hyperthermia (mEHT) is a loco-regional treatment, whereby energy-transmission from an electromagnetic field selectively targets the plasma membrane of tumor cells, inducing apoptosis and activating immune cells. We hypothesized that mEHT could enhance therapeutic effects by drawing γδT to tumor cells, while also rendering tumor cells to be more susceptible to cytotoxic effects. In this study, NOD/SCID mice harboring subcutaneous human HepG2 tumors were treated with intravenous injections of γδT after mEHT treatment. This method increased infiltration of γδT into the tumor site, significantly inhibiting tumor growth as compared to monotherapy with either modality. These data suggest that γδT could mediate a potent anti-tumor effect when combined with mEHT, and provide a strong rationale for combining these modalities in clinical application for cancer treatment.

Immunotherapy has been considered for years as a viable and attractive treatment option for patients with cancer. Among immunotherapy arsenal, the targeting of intratumoral immune cells by immune-checkpoint inhibitory agents has recently revolutionized the treatment of several subtypes of tumours. These approaches aimed at restoring an effective anti-tumour immunity, rapidly reached the market thanks to the simultaneous identification of inhibitory signals that dampen an effective antitumor response in a large variety of neoplastic cells, and the clinical development of monoclonal antibodies targeting checkpoint receptors. Leading therapies in solid tumours are mainly focused on the cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4) and programmed-death 1 (PD-1) pathways. These approaches have found a promising testing ground in both Hodgkin lymphoma and non-Hodgkin lymphoma, mainly because in these diseases the malignant cells interact with the immune system and commonly provide signals that regulate immune function. Although several trials have already demonstrated evidence of therapeutic activity with some checkpoint inhibitors in lymphoma, many of the immunologic lessons learned from solid tumours may not directly translate to lymphoid malignancies. In this sense, the mechanisms of effective antitumor responses are different between the different lymphoma subtypes, while the reasons for this substantial difference remain partially unknown. This review will discuss the current advances of immune-checkpoint blockade therapies in B-cell lymphoma and will build a projection of how the field may evolve in the near future. In particular, we will analyze the current strategies being evaluated both preclinically and clinically with the aim to foster the use of immune-checkpoint inhibitors in non-Hodgkin lymphoma, including combination approaches with chemotherapeutics, biological agents and/or different immunologic therapies.

Coronavirus disease (COVID-19) is a new discovered strain where WHO officially declares the disease as COVID-19 while the virus responsible for it called Severe Acute Respiratory Syndrome Coronavirus 2 or SARS-CoV-2. The incubation period of this disease is between 14 days. Ordinary clinical symptoms that reported around the world include fever, cough, fatigue, diarrhoea and vomiting as well as asymptomatic for certain people. Infection is spread mainly through broad droplets. In early March 2020, WHO again has announced that COVID-19 is a pandemic with currently no specific treatment. The potential use of SARS-COV-2 proteome as a vaccine candidate by analysing through B-cell and T-cell antigenicity by using a immunoinformatics approach as a vaccine development early stage. In this study, we used consensus sequence for SARS-COV-2 proteome that was retrieved from NCBI database. VaxiJen 2.0 was mainly used to identify the antigenic property of SARS-COV-2 proteins. IEDB then used to analyse the B-cell epitope, the presence of T cell immunogenic epitope in SARS-COV-2 proteins was obtained by using compromise method of MHC class I and II tools that accessible respectively using ProPred-1 server and MHC II Binding Prediction in IEDB database. The best epitopes of B and T-cell epitopes were predicted with high antigencity and the information is disseminated through web-based database resource (https://covid-19.omicstutorials.com/epitopes/). This study will be useful to find a new epitope-based candidate for SARS-COV-2. However, further study needs to be done for the next stages of vaccine development.

Neisseria gonorrhoeae is a strict human pathogen responsible for more than 100 million new sexually transmitted infections worldwide each year. Due to the global emergence of antibiotic resistance, the CDC recently listed N. gonorrhoeae as an urgent threat to public health. No vaccine is available in spite of the huge disease burden and the possibility of untreatable gonorrhea. The aim of this study is to investigate the immunogenicity of a novel whole-cell based inactivated gonococcal microparticle vaccine formulation loaded in dissolvable microneedles for transdermal administration. The nanotechnology-based vaccine formulation consists of inactivated whole-cell gonococci strain CDC-F62, spray dried and encapsulated into biodegradable cross-linked albumin matrix with sustained slow antigen release. The dry vaccine nanoparticles were then loaded in a dissolvable microneedle skin patch for transdermal delivery. The efficacy of the whole-cell microparticles vaccine formulation loaded in microneedles was assessed in vitro using dendritic ,cells and macrophages as well as in vivo mouse model. Antibody titers were measured using an ELISA and antigen-specific T lymphocytes were assessed in spleens and lymph nodes. Here we report that whole-cell based gonococcal microparticle vaccine loaded in dissolvable microneedles for transdermal administration induced significant increase in antigen-specific IgG antibody titers and antigen-specific CD4 and CD8 T lymphocytes in mice compared to gonococcal antigens in solution or empty microneedles. Significant increase in antigen-specific IgG antibody levels was observed at end of week 2 in groups that received the vaccine compared to the group receiving empty nanoparticles. The advantages of using formalin-fixed whole-cell gonococci that all immunogenic epitopes are covered and preserved from degradation. The spherical shaped micro and nanoparticles are biological mimics of gonococci, therefore present to the immune system as invaders but without the ability to suppress adaptive immunity. In conclusion, the transdermal delivery of microparticles vaccine via a microneedle patch was shown to be an effective system for vaccine delivery. The novel gonorrhea nanovaccine is cheap to produce in a stable dry powder and can be delivered in microneedle skin patch obviating the need for needle use or the cold chain.

Balanced and coordinated economic development across regions is a critical goal of regional economic development and new-type urbanization in China. However, few studies have examined economic growth convergence clubs at the county level. To extend the research on convergence clubs, this research applies a log t convergence test and a dynamic spatial ordered Probit model (DSOP) to endogenously identify economic growth convergence clubs in counties and to examine the influence of initial states and structures on club convergence probability. The study sample covers 2286 counties of China from 1992 to 2010. The results show significant convergence club patterns at the county levels, resulting in the gradual formation of six convergence clubs. The DSOP estimation results show that per capita fixed assets, population density and industrialization have promoted convergence club formation to varying degrees.

Business-to-business (B2B) manufacturing companies are increasingly confronted with transformative trends such as sustainability, digitalization, and servitization. These trends are changing how product portfolios are developed, and value contributions are assessed, and therefore have disruptive potential. Dealing with these disruptive factors in Product Portfolio Management (PPM) is a largely unexplored topic. This study presents an empirical-qualitative exploration that contributes significantly to the field. The aim is to clarify the extent to which disruptive factors influence the evaluation and shaping of the product portfolio in B2B manufacturing companies. The Gioia method was used to evaluate 21 semi-structured interviews with experts from leading B2B manufacturing companies. Eight overarching challenges in PPM resulting from the disruptive factors were identified. Based on the eight overarching challenges and their associated causal relationships, two aggregated dimensions of action were derived: (1) increasing speed and flexibility by using generative artificial intelligence (AI) in a defined PPM process and (2) adjusting the product portfolio evaluation to consider various strategic drivers. These two dimensions of action call for future research to overcome the disruptive factors in PPM.

As matrix representations of magic labelings of related hypergraphs, magic squares and their various variants have been applied to many domains. Among various subclasses, trimagic squares have been investigated for over a hundred years. The existence problem for trimagic squares with singly even orders and orders 16n has been solved completely. However, very little is known for the existence of trimagic squares with other even orders except for the only three examples and three families. We construct normal trimagic squares by using product constructions, row-square magic rectangles, and trimagic pairs of orthogonal diagonal Latin squares. We give a new product construction: For positive integers p, q, and r having the same parity other than 1, 2, 3, 6, if normal p × q and r × q row-square magic rectangles exist, then a normal trimagic square with order pqr exists. As its application, we construct normal trimagic squares of orders 8q^3 and 8pqr for all odd integers q not less than 7 and p,r ∈ {7, 11, 13, 17, 19, 23, 29, 31, 37}. Our construction can easily be extended to construct multimagic squares.

Land surface temperature (LST) is a crucial parameter in climate and ecology, exerting significant influence on meteorological conditions, ecosystems, and human life. LST data sources are diverse, with remote sensing being the prevailing means of acquisition. FY-4A/AGRI offers high-quality LST products for East Asia. In this study, we evaluated the performance of the product in Hunan Province and conducted refined analysis of surface heat resources based on the 4km/1h resolution product over a two-year period. The results demonstrate that the FY-4A LST product effectively captures surface temperature (R=0.893), albeit with a relatively high error level (Bias=-6.295℃; RMSE=8.58℃), particularly in capturing high LST values. The performance of this product is superior in the eastern flat terrain area of Hunan Province compared to its performance in the western mountainous region due to environmental conditions causing systematic errors that contribute to instability in detection deviation for this product. Surface heat resources are more abundant in eastern Hunan Province than in mountainous areas located west and southwardly, and the detailed distribution of them at finer scales is mainly influenced by the terrain and climate conditions. There is no obvious seasonal difference in the distribution of heat resources except in winter, and rapid urbanization within Chang-Zhu-Tan urban agglomeration during two years has significantly altered the spatial distribution pattern of surface heat resources across Hunan Province. These findings provide a quantitative baseline for assessing FY-4A satellite's detection capability while serving as a reference for further application of its LST products and establishing foundations for divisional classification and utilization strategies pertaining to surface heat resources within Hunan Province.

Current trends in industrial development strive for maximum digitalization. The digital industrial revolution has been going on for more than a dozen years, Industry 4.0 and the idea of digital twins (DT) is becoming the focus of virtually all industrial sectors. Some sectors are more predisposed to digitalization, for others the process is much more difficult. This depends mainly on the specific characteristics and susceptibility of a given industry, including the current degree of digitalization of enterprises, as well as the knowledge and mental readiness of employees. The individual characteristics of an industry are important. Shipyards belong to the industry with a traditional approach, where the degree of digitalization remains low. As a result, the efficiency of shipbuilding processes and the quality of ships built are not sufficiently controlled. The article addresses this problem, reviews work in the field of digitalization of shipbuilding processes and points out the needs and challenges in this area. The article proposes the concept of a DT system for the entire ship design and production process. Key areas of digitalization of actual processes were defined, and a division was made into planning, monitoring and process analysis activities. Special attention was paid to the area of dimensional quality control and the Dimensional Quality Management Metasystem (DQMM) was featured in the comprehensive DT system. The requirements were defined and the limitations of the proposed solution were identified, taking into account a number of external factors including the degree of readiness of the manufacturer – the shipyard. The developed DT system concept was tested on the example of the construction process of a simplified ship. Practical aspects of the implementation of the proposed solution, in particular DQMM, were indicated.

The neural network technology for real-time cryptographic data protection with symmetric keys (masking codes, neural network architecture and weights matrix) for unmanned aerial vehicles (UAV) onboard communication systems has been developed. It provides hardware and software implementation with high technical and operational characteristics. The development of neural network technology for real-time cryptographic data protection was performed using an integrated approach based on theoretical foundations of neural network cryptographic data protection, new algorithms and structures of neural network data encryption and decryption, modern element base with the possibility of programming for the structure, and computer-aided design of hardware and software tools. The development and implementation of the on-board system of neural network cryptographic data protection in real-time are based on the following principles: variable composition of equipment; modularity; conveyorization and spatial parallelism; specialization and adaptation of hardware and software to data encryption and decryption. The tabular-algorithmic method of calculating the scalar product has been improved, it provides fast calculation of the scalar product of input data for both fixed and floating-point by bringing to the largest common order of weights and forming tables of macro-partial products for them. Components of neural network cryptographic data encryption and decryption have been developed on the processor core supplemented by specialized scalar product calculation modules. The specialized hardware for neural network cryptographic data encryption was developed using VHDL for equipment programming in the Quartus II development environment ver. 13.1 and the appropriate libraries, and implemented on the basis of the FPGA EP3C16F484C6 Cyclone III family.

Supplier selection (SC) continues to be a crucial component in manufacturing procurement. Using the PLCC advantages generates revenue and lowers costs more than might be anticipated. Supplier selection (SC) product life cycle cost (SCPLCC) is an important consideration among corporations, SCPLCC problem has become associated with deciding how one supplier should be selected from possible alternatives. Past literature on this topic is limited. We try to close this gap in knowledge. In this study, we attempt to apply two types of goal programming, multiobjective linear programming and revised multichoice goal programming to develop a PLCC-based concept to solve the SCPLCC problem and construct a decision-making tool for application to a case of supply chain management in a Taiwanese light-emitting diode company in the high-tech industry. Our study main contribution Company managers can easily use the two approaches of the SCPLCC model with different parameters to solve SCPLCC model problems. Finally, we are comparing five models found RMCGP with weighted linear goal programming had an adequate effect for application to the PLCC concept for high-technology Company; this cloud makes company decision–makers focus on low PLCC and select a better supplier in sustainable supply chains development.

Today’s purchasing companies demand an advanced buyer equal of enactment from their supplier while the two parties maintain a respectful connection. Although the supplier selection (SC) product life cycle cost (SCPLCC) is an important consideration among corporations, SCPLCC problem has become associated with deciding how one supplier should be selected from possible alternatives. In this study, we applied two types of goal programming, multiobjective linear programming and revised multichoice goal programming to develop a PLCC-based concept to solve the SCPLCC problem and construct a decision-making tool for application to a case of supply chain management in a Taiwanese light-emitting diode company in the high-tech industry. Our study main contribution Company managers can easily use the two approaches of the SCPLCC model with different parameters to solve SCPLCC model problems. Finally, we comparing five models found RMCGP with weighted linear goal programming had an adequate effect for application to the PLCC concept for high-technology comapny; this cloud make company decision–makers focus on low PLCC and select better supplier.

Man-made shallow fishponds in the Czech Republic have been facing a high eutrophication since 1950s. Anthropogenic eutrophication and feeding of fish have strongly affected the physico-chemical properties of water and its aquatic community composition leading to harmful algal bloom formation. In our current study, we have characterised the phytoplankton community across three hypertrophic ponds to assess the phytoplankton dynamics during the vegetation season. We microscopically identified and quantified 29 cyanobacterial taxa comprised of non-toxigenic and toxigenic species. Further, a detailed cyanopeptides (CNPs) profiling was performed using molecular networking analysis of liquid chromatography tandem mass spectrometry (LC–MS/MS) data coupled with dereplication strategy. This MS networking approach coupled with dereplication on online global natural product social networking (GNPS) web platform led us to putatively identify forty CNPs: fourteen anabaenopeptins, ten microcystins, five cyanopeptolins, six microginins, two cyanobactins, a dipeptide radiosumin, a cyclooctapeptide planktocyclin and epidolastatin12. We have applied the binary logistic regression to estimate the CNPs producer by correlating the GNPS data with the species abundance. Usage of The combination of molecular networking and dereplication on online global natural product social networking (GNPS) web platform has proved as a valuable approach for rapid and simultaneous detection of high number of peptides, and rapidly assessing the risk for harmful bloom.

The article shows materials to the question about algebraic features of the genetic code and about the dictatorial influence of the DNA and RNA molecules on the whole organism. Presented results testify in favor that the genetic code is an algebraic code related with a wide class of algebraic codes, which are a basis of noise-immune coding of information in communication technologies. Structural features of the genetic systems are associated with hypercomplex double (or hyperbolic) numbers and with bisymmetric doubly stochastic matrices. The received results confirm that represented matrix approaches are effective for modeling genetic phenomena and revealing the interconnections of structures of biological bodies at various levels of their organization. This allows one to think that living organisms are algebraically encoded entities where structures of genetic molecules have the dictatorial influence on inherited structures of the whole organism. New described algebraic approaches and results are discussed.

The present reality about the Nigerian economy calls for investment and development in the non-oil sector. This becomes necessary as a result of fall in the oil price in the global market. This paper examined the Bayesian Vector Autoregression (BVAR) modeling and forecasting of the dynamic interrelationship between Economic growth and revenue from the oil and non-oil sectors in Nigeria. To achieve this, annual data on Gross Domestic Product (GDP), revenue from oil and non-oil sectors were collected from Central Bank of Nigeria (CBN) bulletin, the sample from 1981 to 2008 was used for analysis, while sample from 2009 to 2014 was used for model validation. Six (6) versions of Sims-Zha BVAR models were compared for out-of-sample forecast, the result revealed the superiority of the BVAR6 model over the other BVAR models. Lastly, evidence from the decomposition forecast errors revealed that revenue of oil sector contributed 7.69% to GDP while revenue from non-oil sector contributed 0.12% to GDP in Nigeria. This paper therefore recommended that the present government should encourage investment that is geared toward development in the non-oil sector, of which it has the capacity to improve the Economic growth of the Nigerian economy.

Histone deacetylase inhibitors (HDACis) are being recognized as a potentially effective treatment approach for peripheral T-cell lymphoma (PTCL), which is a diverse group of aggressive lymphomas with a bleak prognosis. Recent evidence has shown that HDACi are effective in treating PTCL, especially in cases where the disease has relapsed or is resistant to other treatments, and there are few available options. Several clinical trials have demonstrated that HDACi, such as romidepsin and belinostat, can elicit long-lasting positive outcomes in individuals with PTCL, either when used alone or in conjunction with conventional chemotherapy. They exert their anti-tumor actions by regulating gene expression through inhibiting histone deacetylases, which results in the halting of cell division, programmed cell death, and the transformation of cancerous T-cell, as indicated by gene expression profile studies. Importantly, besides clinical trials, real-world evidence indicated that the utilization of HDACi presents a significant and beneficial treatment choice for PTCL. However, although HDACi showed potential effectiveness, they couldn’t cure most patients. Therefore, new combination with conventional drugs as well as new targeted agents are under investigation.

Background/Objectives Immune effector cell-associated hematotoxicity (ICAHT) is a frequent adverse event after chimeric antigen receptor (CAR)-T cell therapy. Grade ≥3 thrombocytopenia occurs in around one third of patients, many of whom become platelet transfusion-dependent. Without pharmacological support, platelet recovery may last for months. Eltrombopag is a thrombopoietin receptor agonist (TPO-RA) able to accelerate megakaryopoiesis, which has been used successfully in patients with bone marrow failure and immune thrombocytopenia (ITP.) Its role to manage thrombocytopenia, and other cytopenias, in CAR-T cell-treated patients has been scarcely addressed in the real-world setting. Our aim was to report the Feasibility of this approach and the outcome of patients included in the GETH-TC registry. Methods This is a retrospective, multicenter, observational study. Patients who developed platelet transfusion-dependence subsequently to CAR-T cell treatment were recruited in 10 Spanish hospitals and followed-up for at least 30 days after the first dose of eltrombopag was administered. Results Thirty-eight patients were enroled and followed-up for a median (interquartile range [IQR]) of 175 (99, 489) days since CAR-T cell infusion. At eltrombopag start, 18 patients had thrombocytopenia and another severe cytopenia, while 8 patients had severe pancytopenia. After 32 (14, 38) days on eltrombopag, 29 (76.3%) patients recovered platelet transfusion independence. The number of platelet units used correlated with the time needed to restore platelet counts to levels ³20x10⁹/L (Rho = 0.639, p <0.001). Non-responders to eltrombopag required more platelet units (58 [29, 69] vs. 12 [6, 26] in responders, p = 0.002). Nineteen out of 23 (82.6%) patients recovered from severe neutropenia after 22 (11, 31) days on eltrombopag. Twenty-nine out of 35 (82.9%) patients recovered red blood cell (RBC) transfusion independence after 29 (17, 44) days. Seven patients recovered all cell lineages while on treatment. No thromboembolic events were reported. Only 2 transient toxicities (cholestasis, hyperbilirubinemia) were reported during eltrombopag treatment, none of which compelled permanent drug withdrawal. Conclusions Eltrombopag can be safely used to manage thrombocytopenia and accelerate transfusion independence in CAR-T cell-treated patients.

For monitoring of chimeric antigen receptor (CAR) T-cell therapies antigen-based CAR detection methods are usually applied. However, for each target-antigen a separate detection system is required. Furthermore, when monitoring CAR T-cells in the blood of patients treated with bispecific antibodies or T-cell engagers (bsAbs/BiTEs) recognize the same antigen, these methods producing false-positive results in clinical diagnostics. Anti-CAR-linker monoclonal antibodies (mAbs) targeting the linker sequence between the variable domains of the antigen binding CAR fragment, promise an universal and unbiased CAR detection. To test this, we analyzed clinical specimens of all BCMA- and CD19 targeting CAR T-cell products currently approved for clinical use. We found a highly specific and sensitive CAR detection by using anti-CAR-linker mAb in blood cells from patients treated with Ide-cel, Tisa-cel, Axi-cel, Brexu-cel, and Liso-cel. For Ide-cel and Tisa-cel the sensitivity was significant lower compared to antigen-based CAR detection assays. Strikingly, the specificity of anti-CAR linker mAb was not affected by the simultaneous presence of bispecific blinatumomab or teclistamab for Axi-cel, Brexu-cel, Liso-cel or Ide-cel, respectively. Cilta-cel (containing an monomeric G4S-CAR linker) could not be detected by anti-CAR linker mAb. In conclusion, anti-CAR-linker mAbs are highly specific and useful for CAR T-cell monitoring but not universal applicable.