Search Results (26,737)

The application of cellular spheroids in bone tissue engineering research has gained significant interest in the last decade. Compared to monolayer cell cultures, the 3D architecture allows for more physiological cell–cell and cell–extracellular matrix (ECM) interactions that make cellular spheroids a suitable model system to investigate the bone ECM in vitro. The use of 3D model systems requires fine-tuning of the experimental methods used to study cell morphology, ECM deposition and mineralization, and cell–ECM interactions. In this study, we use a construct made of MC3T3-E1 cellular spheroids encapsulated in an alginate hydrogel to study and characterize the deposited ECM. Spheroid shape and structure were evaluated using confocal microscopy. The deposited collagenous ECM was characterized using Second Harmonic Imaging Microscopy (SHIM), quantitative hydroxyproline (HYP) assay, and Transmission Electron Microscopy (TEM). The use of hydrogel constructs enabled easy handling and imaging of the samples, while also helping to preserve the spheroid’s stability by preventing cells from adhering to the culture dish surface. We used a non-modified alginate hydrogel that did not facilitate cell attachment and therefore functioned as an inert encapsulating scaffold. Constructs were cultured for up to 4 weeks. SHIM, HYP assay, and TEM confirmed the deposition of a collagenous matrix. We demonstrated that alginate-encapsulated bone spheroids are a convenient and promising model for studying the bone ECM in vitro. Full article

This study presents a detailed analysis of the combustion dynamics of stoichiometric H₂–air and CH₄–air mixtures in a 20 L closed vessel over an initial temperature range of 298–423 K. We integrate experimental pressure–time P(t) measurements with numerical analysis to extract laminar burning velocity (LBV) and deflagration index (K_G) values, and we assess three independent kinetic mechanisms (KiBo_MU, University of San Diego, Lund University) via simulations. For H₂–air, LBV increases from 0.50 m/s at 298 K to 0.94 m/s at 423 K (temperature exponent α ≈ 1.79), while for CH₄–air, LBV rises from 0.36 m/s to 0.96 m/s (α ≈ 2.82). In contrast, the deflagration index K_G decreases by ca. 20% for H₂–air and ca. 30% for CH₄–air over the same temperature span. The maximum explosion pressure (P_max) and peak pressure rise rate ((dP/dt)_max) also exhibit systematic increases with temperature. A comparison with model predictions shows agreement within experiments, providing data for safety modeling and kinetic mechanism validation in H₂- and CH₄-based energy systems. Full article

The Industrial Internet of Things (IIoT), a key enabler of Industry 4.0, integrates advanced communication technologies with the industrial economy to enable intelligent manufacturing and interconnected systems. Secure and reliable identity authentication in the IIoT becomes essential as connectivity expands across devices, systems, and domains. Blockchain technology presents a promising solution due to its decentralized, tamper-resistant, and traceable characteristics, facilitating secure and transparent identity verification. However, current blockchain-based cross-domain authentication schemes often lack a lightweight design, rendering them unsuitable for latency-sensitive and resource-constrained industrial environments. This paper proposes a lightweight cross-domain authentication scheme that combines blockchain with Chebyshev chaotic mapping. Unlike existing schemes relying heavily on Elliptic Curve Cryptography or bilinear pairing, our design circumvents such computationally intensive primitives entirely through the algebraic structure of Chebyshev polynomials. A formal security analysis using the Real-Or-Random (ROR) model demonstrates the scheme’s robustness. Furthermore, performance evaluations conducted with Hyperledger Fabric and the MIRACL cryptographic library validate the method’s effectiveness and superiority over existing approaches in terms of both security and operational efficiency. Full article

Background: Understanding the duration and quality of immune memory following SARS-CoV-2 infection and vaccination is critical for informing public health strategies and vaccine development. While waning antibody levels have raised concerns about long-term protection, the persistence of memory B cells (MBCs) and T cells plays a vital role in sustaining immunity. Materials and Methods: We conducted a longitudinal prospective study over 12 months, enrolling 285 participants in total, either after natural infection or vaccination with BNT162b2 or mRNA-1273. Peripheral blood samples were collected at four defined time points (baseline, 1–2 months, 6–7 months, and 12–13 months after vaccination or disease onset). Immune responses were assessed through serological assays quantifying anti-RBD IgG and neutralizing antibodies, B-ELISPOT, and multiparameter flow cytometry for S1-specific memory B cells. Results: Both mRNA vaccines induced robust B cell and antibody responses, exceeding those observed after natural infection. Memory B cell frequencies peaked at 6 months and declined by 12 months, but remained above the baseline. The mRNA-1273 vaccine elicited stronger and more durable humoral and memory B-cell-mediated immunity compared to BNT162b2, likely influenced by its higher mRNA dose and longer prime-boost interval. Class-switched memory B cells and S1-specific B cells were significantly expanded in vaccine recipients. Natural infection induced more heterogeneous immune memory. Conclusions: Both mRNA vaccination and natural SARS-CoV-2 infection induce a comparable expansion of memory B cell subsets, reflecting a consistent pattern of humoral immune responses across all studied groups. These findings highlight the importance of vaccination in generating sustained immunological memory and suggest that the vaccine platform and dosage influence the magnitude and durability of immune responses against SARS-CoV-2. Full article

The article presents the first method based on high-performance liquid chromatography and ultraviolet detection (HPLC-UV) for the determination of timonacic (thioproline, 1,3-thiazolidine-4-carboxylic acid, tPro) in pharmaceutical tablets and face care products (creams, sera, foundations, suncreams). Sample preparation primarily involves solid-liquid extraction (SLE) of tPro with 0.2 mol/L phosphate buffer pH 6, derivatization with 0.25 mol/L 2-chloro-1-methylquinolinium tetrafluoroborate (CMQT), followed by polytetrafluoroethylene (PTFE) membrane filtration. The chromatographic separation of the stable UV-absorbing 2-S-quinolinium derivative is achieved within 14 min at 25 °C on a Zorbax SB-C18 (150 × 4.6 mm, 5 µm) column using gradient elution. The eluent consists of 0.1 mol/L trichloroacetic acid (TCA), pH 1.7, in a mixture with acetonitrile (ACN) delivered at a flow rate of 1 mL/min. The analyte is quantified by monitoring at 348 nm. The assay linearity was observed within 0.5–125 μmol/L. The limit of quantification (LOQ) was found to be 0.5 μmol/L. The accuracy ranged from 93.22% to 104.31% and 97.38% to 103.48%, while precision varied from 0.30% to 11.23% and 1.13% to 9.64% for intra- and inter-assay measurements, respectively. The method was successfully applied to commercially available on the Polish market pharmaceutical and cosmetic products. Full article

The maritime sector faces escalating demands to minimize emissions and optimize operational efficiency under tightening environmental regulations. Although technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twins (DT) offer substantial potential, their deployment in real-time ship performance analytics is at an emerging state. This paper proposes a machine learning-driven framework for real-time ship performance management. The framework starts with data collected from onboard sensors and culminates in a decision support system that is easily interpretable, even by non-experts. It also provides a method to forecast vessel performance by extrapolating Key Performance Indicator (KPI) values. Furthermore, it offers a flexible methodology for defining KPIs for every crucial component or aspect of vessel performance, illustrated through a use case focusing on fuel oil consumption. Leveraging Artificial Neural Networks (ANNs), hybrid multivariate data fusion, and high-frequency sensor streams, the system facilitates continuous diagnostics, early fault detection, and data-driven decision-making. Unlike conventional static performance models, the framework employs dynamic KPIs that evolve with the vessel’s operational state, enabling advanced trend analysis, predictive maintenance scheduling, and compliance assurance. Experimental comparison against classical KPI models highlights superior predictive fidelity, robustness, and temporal consistency. Furthermore, the paper delineates AI and ML applications across core maritime operations and introduces a scalable, modular system architecture applicable to both commercial and naval platforms. This approach bridges advanced simulation ecosystems with in situ operational data, laying a robust foundation for digital transformation and sustainability in maritime domains. Full article

Malignant mediastinal tumors are a group representing some of the most demanding oncological challenges for early, multi-level, and successful management. The timely identification of any suspicious clinical symptomatology is urgent in achieving an accurate, staged histological diagnosis, in order to follow up with an equally detailed medical therapeutic plan (interventional or not) and determine the principal goals regarding efficient overall treatment in these patients. We report a case of a 24-year-old male patient with an incident-free prior medical history. An initial chest X-ray was performed after the patient reported short-term, consistent moderate chest pain symptomatology, early work fatigue, and shortness of breath. The following imaging procedures (chest CT, PET-CT) indicated the presence of an anterior mediastinal mass (meas. ~11 cm × 10 cm × 13 cm, SUV: 8.7), applying additional pressure upon both right heart chambers. The Alpha-Fetoprotein (aFP) blood levels had exceeded at least 50 times their normal range. Two consecutive diagnostic attempts with non-specific histological results, a negative-for-malignancy fine-needle aspiration biopsy (FNA-biopsy), and an additional tumor biopsy, performed via mini anterior (R) thoracotomy with “suspicious” cellular gatherings, were performed elsewhere. After admission to our department, an (R) Video-Assisted Thoracic Surgery (VATS) was performed, along with multiple tumor biopsies and moderate pleural effusion drainage. The tumor’s measurements had increased to DMax: 16 cm × 9 cm × 13 cm, with a severe degree of atelectasis of the Right Lower Lobe parenchyma (RLL) and a pressure-displacement effect upon the Superior Vena Cava (SVC) and the (R) heart sinus, based on data from the preoperative chest MRA. The histological report indicated elements of a combined, non-seminomatous germ-cell mediastinal tumor, posthuberal-type teratoma, and embryonal carcinoma. The imminent chemotherapeutic plan included a “BEP” (Bleomycin^®/Cisplatin^®/Etoposide^®) scheme, which needed to be modified to a “VIP” (Cisplatin^®/Etoposide^®/Ifosfamide^®) scheme, due to an acute pulmonary embolism incident. While the aFP blood levels declined, even reaching normal measurements, the tumor’s size continued to increase significantly (DMax: 28 cm × 25 cm × 13 cm), with severe localized pressure effects, rapid weight loss, and a progressively worsening clinical status. Thus, an emergency surgical intervention took place via median sternotomy, extended with a complementary “T-Shaped” mini anterior (R) thoracotomy. A large, approx. 4 Kg mediastinal tumor was extracted, with additional RML and RUL “en-bloc” segmentectomy and partial mediastinal pleura decortication. The following histological results, apart from verifying the already-known posthuberal-type teratoma, indicated additional scattered small lesions of combined high-grade rabdomyosarcoma, chondrosarcoma, and osteosarcoma, as well as numerous high-grade glioblastoma cellular gatherings. No visible findings of the previously discovered non-seminomatous germ-cell and embryonal carcinoma elements were found. The patient’s postoperative status progressively improved, allowing therapeutic management to continue with six “TIP” (Cisplatin^®/Paclitaxel^®/Ifosfamide^®) sessions, currently under his regular “follow-up” from the oncological team. This report underlines the importance of early, accurate histological identification, combined with any necessary surgical intervention, diagnostic or therapeutic, as well as the appliance of any subsequent multimodality management plan. The diversity of mediastinal tumors, especially for young patients, leaves no place for complacency. Such rare examples may manifest, with equivalent, unpredictable evolution, obliging clinical physicians to stay constantly alert and not take anything for granted. Full article

Soil fugitive dust (SFD) emissions pose a significant threat to both human health and the environment, highlighting the need for accurate and reliable estimation and assessment in the desert regions of northwest China. This study used climate, soil, and vegetation data from Bayingolin Prefecture (2001–2022) and applied the WEQ model to analyze temporal and spatial variations in total suspended particulate (TSP), PM₁₀, and PM_2.5 emissions and their driving factors. The region exhibited high emission factors for TSP, PM₁₀, and PM_2.5, averaging 55.46 t km⁻² a⁻¹, 27.73 t km⁻² a⁻¹, and 4.14 t km⁻² a⁻¹, respectively, with pronounced spatial heterogeneity and the highest values observed in Yuli, Qiemo, and Ruoqiang. The annual average emissions of TSP, PM₁₀, and PM_2.5 were 3.23 × 10⁷ t, 1.61 × 10⁷ t, and 2.41 × 10⁶ t, respectively. Bare land was the dominant source, contributing 72.55% of TSP emissions. Both total emissions and emission factors showed an overall upward trend, reaching their lowest point around 2012, followed by significant increases in most counties during 2012–2022. Annual precipitation, wind speed, and temperature were identified as the primary climatic drivers of soil dust emissions across all counties, and their influences exhibited pronounced spatial heterogeneity in Bazhou. In Ruoqiang, Bohu, Korla, and Qiemo, dust emissions are mainly limited by precipitation, although dry conditions and sparse vegetation can amplify the role of wind. In Heshuo, Hejing, and Yanqi, stable vegetation helps to lessen wind’s impact. In Yuli, wind speed and temperature are the main drivers, whereas in Luntai, precipitation and temperature are both important constraints. These findings highlight the need to consider emission intensity, land use, or surface condition changes, and the potential benefits of increasing vegetation cover in severely desertified areas when formulating regional dust mitigation strategies. Full article

Rapid urbanization and escalating disaster risks necessitate resilient urban governance systems. Smart city initiatives that leverage digital technologies—such as the internet of things (IoT), big data analytics, and artificial intelligence (AI)—demonstrate transformative potential in enhancing emergency management capabilities. However, empirical evidence regarding their causal impact and underlying mechanisms remains limited, particularly in developing economies. Drawing on panel data from 275 Chinese prefecture-level cities over the period 2006–2021 and using China’s smart city pilot policy as a quasi-natural experiment, this study applies a multi-period difference-in-differences (DID) approach to rigorously assess the effects of smart city construction on emergency management capabilities. Results reveal that smart city construction produced a statistically significant improvement in emergency management capabilities, which remained robust after conducting multiple sensitivity checks and controlling for potential confounding policies. The benefits exhibit notable heterogeneity: emergency management capability improvements are most pronounced in central China and in cities at the extremes of population size—megacities (>10 million residents) and small cities (<1 million residents)—while effects remain marginal in medium-sized and eastern cities. Crucially, mechanism analysis reveals that digital technology application fully mediates 86.7% of the total effect, whereas factor allocation efficiency exerts only a direct, non-mediating influence. These findings suggest that smart cities primarily enhance emergency management capabilities through digital enablers, with effectiveness contingent upon regional infrastructure development and urban scale. Policy priorities should therefore emphasize investments in digital infrastructure, interagency data integration, and targeted capacity-building strategies tailored to central and western regions as well as smaller cities. Full article

The swift advancement of fifth-generation (5G) wireless technology brings forth a range of enhancements to address the increasing demand for data, the proliferation of smart devices, and the growth of the Internet of Things (IoT). This highly interconnected communication environment necessitates using multiple-input multiple-output (MIMO) systems to achieve adequate channel capacity. In this article, a 2-port MIMO system using two flipped parallel 1 × 2 arrays and a 2-port MIMO system using two opposite 1 × 4 arrays designed and fabricated antennas for 5G wireless communication in the sub-6 GHz band, are presented, overcoming the limitations of previous designs in gain, radiation efficiency and MIMO performance. The designed and fabricated single-element antenna features a circular microstrip patch design based on ROGER 5880 (RT5880) substrate, which has a thickness of 1.57 mm, a permittivity of 2.2, and a tangential loss of 0.0009. The 2-port MIMO of two 1 × 2 arrays and the 2-port MIMO of two 1 × 4 arrays have overall dimensions of 132 × 66 × 1.57 mm³ and 140 × 132 × 1.57 mm³, respectively. The MIMO of two 1 × 2 arrays and MIMO of two 1 × 4 arrays encompass maximum gains of 8.3 dBi and 10.9 dBi, respectively, with maximum radiation efficiency reaching 95% and 97.46%. High MIMO performance outcomes are observed for both the MIMO of two 1 × 2 arrays and the MIMO of two 1 × 4 arrays, with the channel capacity loss (CCL) ˂ 0.4 bit/s/Hz and ˂0.3 bit/s/Hz, respectively, an envelope correlation coefficient (ECC) ˂ 0.006 and ˂0.003, respectively, directivity gain (DG) about 10 dB, and a total active reflection coefficient (TARC) under −10 dB, ensuring impedance matching and effective mutual coupling among neighboring parameters, which confirms their effectiveness for 5G applications. The three fabricated antennas were experimentally tested and implemented using the MIMO Application Framework version 19.5 for 5G systems, demonstrating operational effectiveness in 5G applications. Full article

The Tree–Seed Algorithm (TSA) is a symmetry-driven metaheuristic algorithm that shows potential for complex optimization problems, but it suffers from local optimum entrapment and slow convergence. To address these limitations, we propose the ADTSA algorithm. First, ADTSA adopts a symmetry-driven dual-layer framework for seed generation, which promotes effective information exchange between subpopulations and accelerates convergence speed. In later iterations, ADTSA enhances the population’s exploitation ability through a population fusion mechanism, further improving the convergence speed. Moreover, we propose a historical optimal solution archiving and replacement mechanism, along with a t-distribution perturbation mechanism, to enhance the algorithm’s ability to escape local optima. ADTSA also strengthens population diversity and avoids local optima through convex lens symmetric reverse generation based on the optimal solution. With these mechanisms, ADTSA converges more effectively to the global optimum during the evolutionary process. Tests on the IEEE CEC 2014 benchmark functions showed that ADTSA outperformed several top-performing algorithms, such as LSHADE, JADE, LSHADE-RSP, and the latest TSA variants, and it also excelled in comparison with other optimization algorithms, including GWO, PSO, BOA, GA, and RSA, underscoring its robust performance across diverse testing scenarios. The proposed ADTSA’s applicability in solving complex constrained problems was also validated, with the results showing that ADTSA achieved the best solutions for these complex problems. Full article

Background/Objectives: This study aims to uncover the variables related to the success of the intervention. Methods: A retrospective study was conducted on patients who underwent joint replacement surgery utilizing a customized alloplastic system between 2018 and 2023, comprising subjects with complete records for both the planning and follow-up phases. The Student’s t-test was applied with a significance threshold of p < 0.05. Results: Forty-eight subjects were admitted for initial analysis, and 31 subjects were evaluated with a minimum follow-up of 1 year and a maximum of 7 years, with a mean age of 36.37 ± 15.53. The TMJ diagnosis was mainly with degenerative TMJ disease, followed by ankylosis and craniofacial syndromes, and an average of 2.1 ± 1.2 previous surgeries were noted. Degenerative joint disease correlated with increased pain (p < 0.0001) and a higher prevalence of prior joint surgery (p < 0.0001). Thirty-one subjects were followed up with 47 prostheses installed; 74.4% underwent complementary surgery with other facial osteotomies. Significant improvements (p < 0.0001) were observed when comparing pain levels pre- and postoperatively, with a decrease from 5.5 (±2.3) to 2.2 (±0.4). Concerning the interincisal opening, there was a significant increase (p < 0001) from 25.85 (±10.2) mm to 35.93 (±4.2) mm in mouth opening. TMJ replacement treatment is efficient and effective, demonstrating stability in follow-up assessments for up to 7 years. Conclusions: The indications for replacement are diverse and may benefit patients who have not yet progressed to end-stage TMJ disease. Full article

Background: Vascular risk factors (VRFs) are known to influence cerebral small vessel disease (cSVD) burden and progression. However, their specific impact on the presence and distribution of each cSVD imaging marker (white matter hyperintensity [WMH], perivascular spaces [PVSs], lacunes, and cerebral microbleeds [CMBs]) and their spatial distribution remains unclear. Methods: We conducted a retrospective analysis of 93 patients with lacunar stroke with a standardized investigational magnetic resonance imaging protocol using a 3T scanner. WMH and PVSs were segmented semi-automatically, and lacunes and CMBs were manually segmented. We assessed the univariable associations of four common VRFs (hypertension, hyperlipidemia, diabetes, and smoking) with the load of each cSVD marker. Then, we assessed the independent associations of these VRFs in multivariable regression models adjusted for age and sex. Spatial lesion patterns were explored with regional volumetric comparisons using Pearson’s coefficient analysis, which was adjusted for multiple comparisons, and by visually examining heatmap lesion distributions. Results: Hypertension was the VRF that exhibited stronger associations with the cSVD markers in the univariable analysis. In the multivariable analysis, only lacunes (p = 0.009) and PVSs in the basal ganglia (p = 0.014) and white matter (p = 0.016) were still associated with hypertension. In the regional analysis, hypertension showed a higher WMH load in deep structures and white matter, particularly in the posterior periventricular regions. In patients with hyperlipidemia, WMH was preferentially found in hippocampal regions. Conclusions: Hypertension was confirmed to be the VRF with the most impact on cSVD load, especially for lacunes and PVSs, while the lesion topography was variable for each VRF. These findings shed light on the complexity of cSVD expression in relation to factors detrimental to vascular health. Full article

Neisseria gonorrhoeae, the causative agent of gonorrhea, represents a major public health concern due to its increasing antimicrobial resistance. While often asymptomatic—particularly in extragenital infections—untreated cases can lead to severe complications and further transmission. Despite global efforts to monitor antimicrobial resistance, data on the molecular determinants underlying decreased susceptibility in N. gonorrhoeae remain scarce in Peru. This study aimed to detect mutations in the penA and 23S rRNA genes, which confer decreased susceptibility to cephalosporins and azithromycin resistance. We extracted DNA from 124 N. gonorrhoeae-positive clinical rectal specimens collected in Aptima Combo 2 transport tubes from MSM patients. These DNA samples were then screened using the Mismatch Amplification Mutation Assay-based real-time PCR (MAMA-qPCR) to identify mutations in the 23S rRNA and penA genes. Each sample underwent separate reactions to detect A2059G and C2611T mutations in the 23S rRNA gene, and 86 of these samples were further tested in individual qPCR assays for the penA D345 deletion (D345del) or G545S mutations. Sanger sequencing was performed on all DNA samples positive for 23S rRNA mutations by MAMA-qPCR assay, and on 27 DNA samples that yielded sufficient penA amplicons for additional sequencing. Using the MAMA-qPCR assay for the 23S rRNA gene, 64 of 124 samples amplified in the A2059G reaction: 2 (3.1%) carried the mutation, and 62 were classified as wild type. In the C2611T reaction, 42 of 124 samples amplified, and none of them carried the mutation. Using the MAMA-qPCR assay for the penA gene, we only analyzed 86 samples, as the remaining 38 samples had insufficient DNA yield. A total of 44 of the 86 samples amplified in the D345del reaction: 5 (11.4%) carried the D345del, and 39 were classified as wild type. In the G545S reaction, 4 (6.4%) carried the mutation, and 58 were classified as wild type. Finally, sequencing of the penA gene in the 27 samples revealed mutations related to decreased susceptibility to cephalosporins. This study identified genetic mutations conferring resistance to azithromycin and decreased susceptibility to cephalosporins, providing an overview of the circulating mutations conferring resistance in N. gonorrhoeae strains in Peru. Full article

This study investigates the effects of copper nanoparticles (CuNPs) on KRT19 gene expression in four breast cancer cell lines (MDA-MB-231, MDA-MB-468, MCF7, and T47D), representing triple-negative and luminal subtypes. Using cytotoxicity assays, quantitative RT-PCR, and bioinformatics tools (STRING, g:Profiler), we demonstrate subtype-specific, dose-dependent KRT19 suppression, with epithelial-like cell lines showing greater sensitivity. CuNPs, characterized by dynamic light scattering (DLS) and transmission electron microscopy (TEM) with a mean size of 179 ± 15 nm, exhibited dose-dependent cytotoxicity. Bioinformatics analyses suggest KRT19′s potential as a biomarker for CuNP-based therapies, pending in vivo and clinical validation. These findings highlight CuNPs’ therapeutic potential and the need for further studies to optimize their application in personalized breast cancer treatment. Full article