Strong Stability Research Articles

Introducing and analyzing a new combined version of the unstable Schrödinger equations with strong and weak stability effects

In the literature, two types of unstable nonlinear Schrodinger equations have been independently developed and studied. Each was derived by incorporating either a self-effect term or a time-space dispersion term into the standard nonlinear Schrodinger equation. Both models describe the time evolution of disturbances in unstable media. The primary contribution of this work is the combination of these two types into a single, new unstable version of the nonlinear Schrodinger equation. This new model is analyzed using two effective methods: the rational sine-cosine and the rational sinh-cosh functions. Additionally, a comparison test of the embedded unstable terms is conducted to assess their respective impacts on the stability of the Schrodinger model. Finally, graphical analyses, including 2D and 3D plots, are performed to validate the study’s findings.

Vertically Aligned Ultrathin CoNi-LDH@NiS@MXCF Core-Shell Heterostructure for Flexible Supercapacitor Electrodes and Oxygen Evolution Reaction.

A multilayer core-shell heterostructure with CoNi-LDH as the core and NiS nanosheets as the shell is deposited on MXene-coated carbon nanofibers by electrospinning and electrochemical deposition. This unique structure not only combines highly conductive and hydrophilic one-dimensional carbon nanofibers but also exposes abundant two-dimensional reactive sites and multiple ion diffusion channels to maximize material utilization, enhance electron transfer kinetics, accelerate Faraday reaction, high capacitance and strong stability. The CNNS@MXCF electrode exhibits outstanding electrochemical characteristics, including a capacity of 1441.8 F g-1 at a current density of 1 A g-1 and excellent cycling stability. The CNNS@MXCF//VN@MXCF device shows a high energy density of 84.4 Wh kg-1 at 0.8 kW kg-1 power density, with nearly 92% capacitance retention after 10,000 cycles (30 A g-1). In addition, the oxygen evolution reaction (OER) shows a small overpotential of 128 mV, confirming the versatility and large potential of the materials and strategy.

On the asymptotic normality of persistent Betti numbers

Abstract Persistent Betti numbers are a major tool in persistent homology, a subfield of topological data analysis. Many tools in persistent homology rely on the properties of persistent Betti numbers considered as a two-dimensional stochastic process $ (r,s) \mapsto n^{-1/2} (\beta^{r,s}_q ( \mathcal{K}(n^{1/d} \mathcal{X}_n))-\mathbb{E}[\beta^{r,s}_q ( \mathcal{K}( n^{1/d} \mathcal{X}_n))])$ . So far, pointwise limit theorems have been established in various settings. In particular, the pointwise asymptotic normality of (persistent) Betti numbers has been established for stationary Poisson processes and binomial processes with constant intensity function in the so-called critical (or thermodynamic) regime; see Yogeshwaran et al. (Prob. Theory Relat. Fields167, 2017) and Hiraoka et al. (Ann. Appl. Prob.28, 2018). In this contribution, we derive a strong stabilization property (in the spirit of Penrose and Yukich, Ann. Appl. Prob.11, 2001) of persistent Betti numbers, and we generalize the existing results on their asymptotic normality to the multivariate case and to a broader class of underlying Poisson and binomial processes. Most importantly, we show that multivariate asymptotic normality holds for all pairs (r, s), $0\le r\le s<\infty$ , and that it is not affected by percolation effects in the underlying random geometric graph.

Deciphering the pharmacological mechanism of Radix astragali for allergic rhinitis through network pharmacology and experimental validation

Radix Astragali (RA) has been recognized for its therapeutic potential in allergic rhinitis (AR), yet its potential pharmacological mechanisms remain elusive. This study systematically investigated the physicochemical properties and biological activities of RA’s phytochemicals, aiming to elucidate their targets and mechanisms in AR treatment. We identified 775 potential targets of RA’s key phytochemicals and intersected these with 29,544 AR-related disease targets, pinpointing 747 shared therapeutic targets. A protein-protein interaction network analysis categorized these targets into five subclusters, with TNF, NFKB1, IKBKB, NFKBIA, and CHUK emerging as central nodes. Enrichment analysis revealed their roles in inflammatory and immune responses, particularly through the NF-κB, TNF, IL-17, Toll-like receptor, and NOD-like receptor signaling pathways. Molecular docking and dynamics simulations confirmed the strong binding affinity and stability of RA’s phytochemicals to these targets. In vivo, RA intervention effectively reversed the expression of key inflammatory markers in an IL-13-induced nasal mucosa inflammation model. Our findings suggest that RA’s multitargeted approach involves the modulation of critical inflammatory pathways, highlighting its therapeutic potential.

Measuring Spatial Ability: Analysis of Spatial Ability Test for Gulf State Students Using Item Response Theory

This study evaluates the psychometric properties of the spatial ability test using the three-parameter logistic model within item response theory. The final version of the scale comprised 29 dichotomous items, administered to a sample of 2,694 male and female students from grades 5 and 6 across schools in the Arab Gulf region. The test adhered to the three-parameter model, satisfying the assumptions of unidimensionality and local independence. The item difficulty parameters ranged from -1.541 to 1.735, discrimination parameters spanned from 0.419 to 5.252, and guessing parameters varied between 0.00 and 0.346. With a marginal reliability coefficient of 0.86, the scale demonstrated strong stability. These findings indicate that the test items align with established measurement principles, supporting the spatial ability test as a valid and reliable assessment tool for measuring spatial abilities in the Gulf region. The results have important implications for educational assessment in the Arab Gulf and could guide the development of similar assessments in other educational contexts. Further research is recommended to improve the test’s precision and explore its application in diverse educational settings.

Effects of Laurus extract against cadmium-induced neurotoxicity in rats

Cadmium (Cd) is a hazardous heavy metal with widespread environmental presence, posing significant threats to human and animal health. This study investigates the neurotoxic effects of Cd exposure and explores the therapeutic efficacy of Laurus nobilis L. in counteracting these adverse effects. Cd exposure induces oxidative stress and neurotoxicity, leading to neuronal damage and histopathological alterations. Laurus, known for its antioxidant properties, is assessed for its potential in mitigating Cd-induced neurotoxicity through in vitro antioxidant assays, GC–MS analysis, HPLC profiling, and experimental animal models. Results demonstrate that Laurus ethanolic extract exhibits significant antioxidant activity, attributed to its phenolic and flavonoid constituents. GC–MS analysis reveals various bioactive compounds in the extract, including Hexadecanoic acid methyl ester and (Z)-13-Docosenamide, which posses neuroprotective properties. HPLC analysis identifies phenolic compounds such as ellagic acid and flavonoids like rutin and kaempferol in the extract. In vivo studies in rats exposed to Cd demonstrate that Laurus extract administration mitigates Cd-induced alterations in body and brain weight, hematological parameters, liver and kidney function, oxidative stress markers, and acetylcholinesterase (AchE) activity. Histopathological examination confirms the protective effects of Laurus against Cd-induced neuronal damage. The SOD model, validated with high resolution (2.05 Å) and strong R values (work: 0.192, free: 0.236, observed: 0.194), shows strong structural stability (C-score: 0.30). Docking studies reveal high binding affinities of kaempferol (−8.1 kcal/mol) and rutin (−8.7 kcal/mol) with SOD with kaempferol demonstrating superior solubility, lipophilicity, and drug-likenessSimulation analysis confirms the protein’s flexibility and adaptability, highlighting its therapeutic potential, especially with kaempferol. These findings suggest the therapeutic potential of Laurus. as a natural remedy for Cd-induced neurotoxicity, highlighting its antioxidant and neuroprotective properties.

High-Performance Photocatalytic Degradation of Aromatic Compounds Using Co-MOF-74/ZnIn2S4/CNF Aerogels with Enhanced Charge Separation and Photothermal Synergy

Although photocatalytic degradation using semiconductor materials has been widely studied, there are still challenges such as slow reaction kinetics and complex synthesis process. To overcome these problems, Co-MOF-74@ZnIn2S4@CNF composite aerogel was developed in this study, which significantly improved the photocatalytic efficiency. This novel structure integrates three key functions: 1) the one-dimensional Co-MOF-74-NTs nanotube enhances carrier mobility based on its high aspect ratio; 2) the Co-MOF-74@ZnIn2S4 heterojunction facilitates charge separation for efficient generation of reactive oxygen species; 3) the porous cellulose aerogel promotes the adsorption of substrates and improves the photothermal effect due to its intrinsic thermal conductivity and insulation, and will facilitate effective charge separation. This combined functionality resulted in highly efficient degradation of paraxylene, with 91.6% of degradation efficiency and 68.79% of mineralization rate within 3h under simulated sunlight. Several experiments demonstrated that the Co-MOF-74@ZnIn2S4@CNF aerogel possessed strong stability and effective catalytic properties for a variety of aromatic compounds. This study introduces a new photocatalytic system combining heterogeneous structure and photothermal effect to enhance charge transfer, providing an efficient solution for photothermal-assisted Aromatic Compounds degradation.

Sn-Pb Perovskite with Strong Light and Oxygen Stability for All-Perovskite Tandem Solar Cells.

Research on mixed Sn-Pb perovskite solar cells (PSCs) is gaining significant attention due to their potential for high efficiency in all-perovskite tandem solar cells. However, Sn2+ in Sn-Pb perovskite is susceptible to oxidation, leading to a high defect density. The oxidation primarily occurs through two pathways: one involving a reaction with oxygen, and the other related to iodine defects, which generate I2 and further accelerate the oxidation of Sn2⁺, greatly reducing stability. First, to tackle the photo-stability issues caused by iodine defects, amber acid (AA) is screened as the additive. The Carboxyl group on AA can strongly coordinate with Sn2+, reinforcing the Sn─I bond and electrostatically interacting with negatively charged defects. This interaction inhibits the photoinduced formation of I2 and the subsequent oxidation of Sn2+, thereby enhancing the stability of Sn─Pb PSCs under continuous illumination. Building on the foundation of AA, a reductive sulfhydryl group is introduced to synthesize thiomalic acid (TA). It inhibits the formation of Sn4+ in both the perovskite precursor and the perovskite film, thereby improving air stability while maintaining strong photostability. Consequently, single PSCs achieved a champion efficiency of 22.7%. The best-performing two-terminal all-perovskite tandem solar cell achieved a power conversion efficiency of 28.6% with improved operational stability.

Comparative Analysis of Fuzzy Logic, PID, and FOPID Controllers in DC Microgrid Voltage Regulation for Power Plants: Integrating Renewable Energy Sources

The worldwide direction moving towards sustainable energy solutions requires more advanced control mechanisms within power systems, especially in DC microgrids that combine renewable energy sources like solar panels and wind turbines with conventional power setups. This paper addresses the necessary challenge of maintaining steady and efficient DC voltage control—important for the dependability and performance of power plants. Specifically, it looks at the efficiency of four different control strategies: classic PID (Proportional-Integral-Derivative) controllers, Fuzzy Logic Controllers (FLC), Fractional Order PID (FOPID) controllers, and a new mixed system that merges Fuzzy Logic with PID controllers in a Fuzzy-PI layout. Our approach utilizes a strict comparative analysis using MATLAB Simulink simulations, assessing each controller’s capacity to manage dynamic load shifts, adjust to the unpredictability of renewable energy inputs, and preserve strong voltage stability under various operational cases. The simulations are crafted to single out the most effective control strategy to boost efficiency and toughness in microgrid operations. This study adds substantially to the progress of control strategies in hybrid energy systems, offering important insights into the creation of more complex and reliable power management solutions. By evaluating the performance of these varied controllers, we aim to underline potential upgrades in control systems that could support better energy management in intricate grid setups, thereby encouraging the wider inclusion of renewable energy technologies into power grids.

Weak and strong stabilisation of a class of bilinear systems with time varying delay

This paper deals with the feedback stabilisation of a class of bilinear systems with varying time delay. Firstly, we use the step-by-step method to prove the existence and uniqueness of the mild solution of the closed-loop system. Secondly, we study the weak and strong stabilisation when the usual observability estimates are not necessary verified. The main idea consists of decomposing the whole system according the observable and unobservable states. The obtained results are also exploited to prove the feedback stabilisation of linear systems. Finally, applications to partial differential equations are further provided.

Planetary boundary layer scheme in the INMCM Earth system model

Abstract The paper reviews the planetary boundary layer parameterizations in the current generation of the INMCM Earth system model. We discuss some of the challenges and improvements necessary to correctly reproduce the essential non-linear interactions of physical processes common to the boundary-layer physics. Overview of some of the improvements implemented in the PBL single-column version of the INMCM model is presented. These include the hierarchy of turbulence closures of different computational complexity suited for modelling a thin stable boundary layer. The closures are based on a consistent definition of the first-order, single- and two-equation approaches and inclusion of stability functions in the surface layer parameterizations tailored for strong static stability of the atmosphere.

A novel pan-epitope based nanovaccine self-assembled with CpG enhances immune responses against flavivirus

BackgroundFlavivirus is a highly prevalent and outbreak-prone disease, affecting billions of individuals annually and posing substantial public health challenges. Vaccination is critical to reducing the global impact of flavivirus infections, making the development of a safe and effective vaccine a top priority. The self-assembled pan-epitope vaccine presents key advantages for improving immunogenicity and safety without relying on external vectors or adding immunomodulatory elements, both of which are essential for successful vaccine development.ResultsIn this study, the pan-epitope peptide TBT was combined with adjuvant CpG to form the TBT-CpG nanovaccine (TBT-CpG NaVs), which was found to be spherical, uniform in shape, and demonstrated strong serum stability. In vitro studies showed that the TBT-CpG NaVs were efficiently taken up and internalized by bone marrow-derived dendritic cells (BMDCs). Flow cytometry and transcriptomic analysis indicated that the antigens were effectively presented to antigen-presenting cells (APCs) via the MHC II pathway, which facilitated BMDCs maturation and promoted the release of pro-inflammatory cytokines IL-1β, TNF-α, and IL-6. In vivo studies confirmed that TBT-CpG NaVs enhanced antigen-specific IgG levels, significantly increased IFN-γ and IL-4 expression in spleen cells, and offered protective effects against Dengue virus (DENV) and Zika virus (ZIKV) infections. Safety evaluations revealed no hepatotoxicity and no significant organ damage in immunized mice.ConclusionThe self-assembled candidate nanovaccine TBT-CpG NaVs effectively activates BMDCs and triggers a targeted immune response, providing antiviral effects against DENV and ZIKV. This vaccine demonstrates good immunogenicity and safety, establishing a promising foundation and a new strategy for the development of safe and effective vaccines.Graphical

Defects and oxygen functional groups on sludge biochar synergistic activation of PMS for degradation of sulfamethoxazole and practical application

As one of the by-product, residual sludge needs to be utilized urgently. For this purpose, sludge biochar (ASBC-1) abundant oxygen functional groups (OFGs) with edge defects was designed to reuse the residual sludge. The ASBC-1/ Peroxymonosulfate (PMS) system removed 94.63 % of sulfamethoxazole (SMX) within 30 min and had strong pH versatility, interference resistance, and stability. Raman and X-ray photoelectron spectroscopy (XPS) analysis revealed that the degree of defects and the content of OFGs were influenced by different acidification conditions. Furthermore, the relationship between degradation performance and the degree of defects or OFGs was confirmed by Pearson correlation analysis. DFT calculations revealed that the degree of defects and OFGs synergistically promoted the activation of PMS. A continuous flow fixed-bed reactor with gel pellets as packing material was constructed, and the removal rate of SMX was suitable under different water matrix backgrounds. This method provided a treatment and disposal solution for reusing sludge resources in accordance with the principles of sustainable development.

An in vitro biomechanical evaluation of integrated lateral plate combined with oblique lateral interbody fusion in different bone conditions

Oblique lateral interbody fusion (OLIF) is a minimally invasive surgery for the treatment of lumbar degenerative diseases (LDD). Under normal bone mass(NB), supplemental with lateral plate (LP) fixation has been proven to provide stability and reduce complications. However, it is unclear whether OLIF combined with LP fixation can achieve satisfactory fixation effects in cases of osteoporosis(OP) or osteopenia (OS)? In this study, Eighteen L3-5 spinal specimens from 3 to 6 months old fresh calves were equally divided into 3 groups: group A (NB), group B (OS) and group C (OP). A load control scheme was adopted and evaluated using multidirectional nondestructive moments (± 7.5 N·m). An electronic universal tester and a tensile/torsion tester were simulated to generate 6 degrees of freedom of motion, and a VIC-3D three-dimensional optical full-field strain measurement system dynamically tracked the surgical segmental displacement. Each spine was evaluated under the following conditions at the L4-5 level: intact (INT); OLIF stand-alone (SA); cage supplemented with LP, cage supplemented with unilateral pedicle screws (UPS), and cage supplemented with bilateral pedicle screws (BPS). The current data show that With NB and OS models, LP fixation significantly reduced ROM in the LB and AR directions, with slightly less stability than BPS fixation and comparable to UPS. In the case of OP, LP fixation may increase the risk of internal fixation failure, and it is more preferable to choose BPS fixation with stronger stability.

A Haloalkane Dehalogenase DhaA Nanoparticle Based on Pullulan Conjugation and Polyethyleneimine Adsorption.

Haloalkane dehalogenase DhaA is a member of the α/β-hydrolase superfamily and can degrade the halogenated compounds. However, the enzyme could not tolerate harsh and extreme environmental conditions, such as high temperature, extreme pH, and hypersaline, which limits its practical applications. Pullulan is a hydrophilic polysaccharide and acts as an additive to improve the enzyme stability. Polyethyleneimine (PEI) is a protein stabilizer and a polymer with a high density of ionizable amino groups. In the present study, DhaA was covalently conjugated with acetylated pullulan and adsorbed with PEI by electrostatic interactions to form nanoparticles (PEI-pullulan-DhaA). As compared with DhaA, PEI-pullulan-DhaA essentially maintained the enzymatic activity of DhaA, along with slight change in the kinetic parameters and enzyme conformation. The conjugated pullulan tends to form a large hydrated layer around DhaA. PEI, a cationic polymer, generated an amphiphilic microenvironment around DhaA. Pullulan conjugation and PEI adsorption could significantly improve the stability of DhaA against high temperature and low pH by structural stabilization of DhaA. PEI-pullulan-DhaA could also tolerate the hypersaline, organic solvents, and long-term storage. Thus, PEI-pullulan-DhaA has a strong environmental stability and is promising for industrial and environmental applications.

In Silico Design of Peptide Inhibitors Targeting HER2 for Lung Cancer Therapy

Background/Objectives: Human epidermal growth factor receptor 2 (HER2) is overexpressed in several malignancies, such as breast, gastric, ovarian, and lung cancers, where it promotes aggressive tumor proliferation and unfavorable prognosis. Targeting HER2 has thus emerged as a crucial therapeutic strategy, particularly for HER2-positive malignancies. The present study focusses on the design and optimization of peptide inhibitors targeting HER2, utilizing machine learning to identify and enhance peptide candidates with elevated binding affinities. The aim is to provide novel therapeutic options for malignancies linked to HER2 overexpression. Methods: This study started with the extraction and structural examination of the HER2 protein, succeeded by designing the peptide sequences derived from essential interaction residues. A machine learning technique (XGBRegressor model) was employed to predict binding affinities, identifying the top 20 peptide possibilities. The candidates underwent further screening via the FreeSASA methodology and binding free energy calculations, resulting in the selection of four primary candidates (pep-17, pep-7, pep-2, and pep-15). Density functional theory (DFT) calculations were utilized to evaluate molecular and reactivity characteristics, while molecular dynamics simulations were performed to investigate inhibitory mechanisms and selectivity effects. Advanced computational methods, such as QM/MM simulations, offered more understanding of peptide–protein interactions. Results: Among the four principal peptides, pep-7 exhibited the most elevated DFT values (−3386.93 kcal/mol) and the maximum dipole moment (10,761.58 Debye), whereas pep-17 had the lowest DFT value (−5788.49 kcal/mol) and the minimal dipole moment (2654.25 Debye). Molecular dynamics simulations indicated that pep-7 had a steady binding free energy of −12.88 kcal/mol and consistently bound inside the HER2 pocket during a 300 ns simulation. The QM/MM simulations showed that the overall total energy of the system, which combines both QM and MM contributions, remained around −79,000 ± 400 kcal/mol, suggesting that the entire protein–peptide complex was in a stable state, with pep-7 maintaining a strong, well-integrated binding. Conclusions: Pep-7 emerged as the most promising therapeutic peptide, displaying strong binding stability, favorable binding free energy, and molecular stability in HER2-overexpressing cancer models. These findings suggest pep-7 as a viable therapeutic candidate for HER2-positive cancers, offering a potential novel treatment strategy against HER2-driven malignancies.

A hybrid linear Diophantine fuzzy group decision approach for enterprise digital transformation maturity evaluation

PurposeThe main goal of this paper is to present a synthetic multiple criteria group decision-making (MCGDM) methodology for assessing the enterprise digital maturity with linear Diophantine fuzzy (LDF) setting.Design/methodology/approachThis paper utilizes the presented LDF generalized Dombi operator to aggregate assessment information of experts. The developed combined weight model through merging the rank sum (RS) model and symmetry point of criterion (SPC) method is used to ascertain the comprehensive importance of criterion. The evaluation based on distance from average solution (EDAS) approach based upon regret theory (RT) is presented to achieve the sorting of candidate enterprises.FindingsFirstly, the proposed method has strong stability. Secondly, the proposed method takes into consideration the psychological behavior of experts during the decision-making process which further enhances the rationality of the decision results. Finally, the proposed method integrates expert and criterion weight determination models which provides a practical evaluation framework for assessing the digital maturity of enterprises. The research outcomes confirm that the proposed approach fails to resolve the decision problems with unknown weight information flexibly, but also reflect the psychological behavior of expert in decision process. The presented weight approach also provides a rational algorithm to ascertain the weight more accurate.Originality/valueA composite LDF group decision-making approach is presented by aggregating the proposed generalized Dombi operator, combined weight model and the EDAS model, which make the outcome more reasonable. Sensitivity analysis and comparison study are conducted to reflect the superiority of the proposed approach.

Novel cobalt-doped CuFe2O4 spinel catalyst for enhanced peroxymonosulfate activation to achieve rapid degradation of tetracycline hydrochloride: Dominant roles of O2[rad]- and 1O2 in the oxidation process

Heterogeneous peroxymonosulfate (PMS) catalysis is a promising method for water pollution treatment. CuFe2O4 spinel can activate PMS, but its application is limited by its tendency to agglomerate and its low-mass transfer efficiency. In this study, a cobalt-doped CuFe2O4 (CuFeCoO4, CFCo-1) was successfully synthesized, achieving a degradation efficiency of 98.36 % for tetracycline hydrochloride (TCH) within 21 min, with a high degradation rate corresponding to a kinetic constant of 0.2041 min−1. CFCo-1 demonstrated strong resistance to interference from inorganic ions and organic compounds. It maintained over 90 % TCH removal efficiency with negligible leaching of metal ions after five cycles, indicating that the catalyst had strong cyclic stability. Mechanistic analysis revealed that cobalt doping improved the electron transfer efficiency of the catalyst, enabling CFCo-1 to activate PMS and degrade the pollutant through both radical (OH, SO4- and O2-) and non-radical (1O2) pathways, with O2- and 1O2 being the dominant species. The potential degradation pathways of TCH were proposed based on theoretical calculation and the identification of degradation products. In conclusion, cobalt doping is an effective strategy for enhancing the catalytic performance of spinel for efficient degradation of pollutants in water.

An immune scoring system predicts prognosis and immune characteristics in lung adenocarcinoma brain metastases by RNA sequencing.

Previous studies have reported that the tumor immune microenvironment (TIME) was associated with the prognosis of lung cancer patients and the efficacy of immunotherapy. However, given the significant challenges in obtaining specimens of brain metastases (BrMs), few studies explored the correlation between the TIME and the prognosis in patients with BrMs from lung adenocarcinoma (LUAD). Transcript profiling of archival formalin-fixed and paraffin-embedded specimens of BrMs from 70 LUAD patients with surgically resected BrMs was carried out using RNA sequencing. An immune scoring system, the green-yellow module score (GYMS), was developed to predict prognosis and immune characteristics in both BrMs and primary LUAD using Weighted Correlation Network analysis (WGCNA) and GSVA analysis. We comprehensively evaluated the immunological role of GYMS based on gene expression profile of LUAD BrMs by systematically correlating GYMS with immunological characteristics and immunotherapy responsiveness in the BrMs. Immunohistochemistry was applied for validation. We found that the high-GYMS group had better clinical prognosis and inflamed immune landscape including high infiltrations of various immune cells, increased immunomodulatory expression, and enriched immune-related pathways by using RNA-seq and immunohistochemical analysis. Low-GYMS group presented a lacked immune infiltration characteristic. Besides, the high-GYMS group had lower TIDE score and higher T-cell inflamed score than low-GYMS group. The GYMS has been validated in independent BrMs cohorts and primary NSCLC cohort treated with anti-PD-1/PD-L1, showing strong reproducibility and stability in both primary LUAD and BrMs. In addition, we construct a GYMS-related risk signature for patients with LUAD BrMs to predict prognosis. We identified two immune-related subtypes which used to estimate prognosis and immune characteristics and developed a reliable GYMS-related risk signature in LUAD BrMs. These results will enhance the understanding of the immune microenvironment in LUAD BrMs and lay the theoretical foundation for the development of personalized therapies for LUAD patients with BrMs.

Comparative Analysis of Business Environment Dynamics in Central and Eastern Europe: A Multi-Criteria Approach

The COVID-19 pandemic has negatively impacted the world economy and global society. However, small- and medium-sized enterprises are among the most vulnerable and affected groups of businesses, and in some cases, life-saving interventions have resulted in serious existential implications. The difficulties of insufficient demand, non-negligible fixed costs, and inadequate financing are unsustainable for many firms. Thus, the main aim of this study is to evaluate the variables influencing business activities, apply macroeconomic variables to compare the business environments in fifteen European countries, and utilize appropriate statistical techniques to confirm the results. Significant differences exist in the business climate across selected European countries, as identified by the TOPSIS method, CPI, and GCI. Low levels of corruption, strong economic stability, and high competitiveness make countries like Germany and Austria attractive for business environments. Estonia is also a leader in technological innovation and low corruption. Conversely, Bulgaria and Romania are struggling with higher levels of corruption and reduced competitiveness, potentially impeding business endeavours. The Visegrad Group countries are in the middle of the spectrum, scoring average to good but with opportunities for improvement in corruption and innovation. Overall, the business climate in these countries is diverse, reflecting their unique economic, political, and social circumstances.