Search Results (142)

This study evaluated the impact of the encapsulation of sea buckthorn and grape pomace extracts in liposomal formulations on the retention and release of bioactive compounds and their antioxidant activity. The profile and composition of lipophilic extracts of sea buckthorn and hydrophilic extracts of grape pomace were analyzed. Encapsulation efficiency, retention rate, and the content of bioactive compounds encapsulated in liposomal formulations prepared in two media—water and ethanol—were evaluated. The encapsulation efficiency varied between 84 and 90%, indicating the superior encapsulation of the bioactive compounds. The retention rate varied between 79 and 86%, which indicated the stability of the liposome-encapsulated compounds over time. The antioxidant activity of the encapsulated samples was determined in vitro, under the conditions of gastric (pH 1.8) and intestinal (pH 8.2) digestion, in relation to the non-encapsulated extracts. The antioxidant activity of both liposomal formulations was higher than that of the nonencapsulated extracts during gastric digestion. Moreover, an increase over time in the antioxidant activity, expressed as % DPPH inhibition, was observed for all samples, with around 90% DPPH inhibition for non-encapsulated extracts and 92% for the encapsulated extracts, demonstrating the stability of bioactive compounds in acidic pH. Oppositely, when exposed to intestinal simulated digestion (alkaline pH), the antioxidant activity decreased over time to around 24% DPPH inhibition for both encapsulated and nonencapsulated extracts. These results provide a foundation for the further development and application of liposomal delivery systems in functional foods. Full article

Protein tyrosine kinases (PTKs) function as key molecules in the signaling pathways in addition to their impact as a therapeutic target for the treatment of many human diseases, including cancer. PTKs are characterized by their ability to phosphorylate serine, threonine, or tyrosine residues and can thereby rapidly and reversibly alter the function of their protein substrates in the form of significant changes in protein confirmation and affinity for their interaction with protein partners to drive cellular functions under normal and pathological conditions. PTKs are classified into two groups: one of which represents tyrosine kinases, while the other one includes the members of the serine/threonine kinases. The group of tyrosine kinases is subdivided into subgroups: one of them includes the member of receptor tyrosine kinases (RTKs), while the other subgroup includes the member of non-receptor tyrosine kinases (NRTKs). Both these kinase groups function as an “on” or "off" switch in many cellular functions. NRTKs are enzymes which are overexpressed and activated in many cancer types and regulate variable cellular functions in response to extracellular signaling-dependent mechanisms. NRTK-mediated different cellular functions are regulated by kinase-dependent and kinase-independent mechanisms either in the cytoplasm or in the nucleus. Thus, targeting NRTKs is of great interest to improve the treatment strategy of different tumor types. This review deals with the structure and mechanistic role of NRTKs in tumor progression and resistance and their importance as therapeutic targets in tumor therapy. Full article

Complex systems (CSs) have garnered increasing attention in science education due to their prevalence in the natural world and their importance in addressing pressing issues such as climate change, pandemics, and biodiversity loss. However, the instruments for assessing one’s CS knowledge are limited, and the knowledge of CSs among in-service teachers remains underreported. Guided by the complexity framework, we launched a study to develop and validate a survey instrument for measuring the knowledge of CSs among high school teachers and undergraduate students, as well as delineating the contours of their knowledge. In this article, we present the development and validation of a Complex Systems Knowledge Survey (CSKS), and we use the survey to compare the CS knowledge among 252 high school teachers and 418 undergraduate students in the United States. Our key findings include that (1) both high school teachers and undergraduates exhibit relatively low knowledge of decentralization and stochasticity, (2) undergraduates, especially those in non-STEM majors, demonstrate moderate to low knowledge of emergence, (3) few teachers and undergraduates differentiate between complicated and complex systems, and (4) teachers and undergraduates recognize CS examples across natural and social systems. The implications of our findings are discussed. Full article

Let ${\mathcal{K}}_{+}\left({\mu }_i\right)=\{Q_{s_i}^{{\mu }_i},s_i\in (m_0^{{\mu }_i},m_{+}^{{\mu }_i})\}$, $i=1,2$, be two CSK families generated by the nondegenerate probability measures ${\mu }_1$ and ${\mu }_2$ with support bounded from above. Define the set of measures $\mathcal{L}={\mathcal{K}}_{+}\left({\mu }_1\right)•{\mathcal{K}}_{+}\left({\mu }_2\right)=\{Q_{s_1}^{{\mu }_1}•Q_{s_2}^{{\mu }_2},s_1\in (m_0^{{\mu }_1},m_{+}^{{\mu }_1})\mathrm{and}{s}_2\in (m_0^{{\mu }_2},m_{+}^{{\mu }_2})\},$ where $Q_{s_1}^{{\mu }_1}•Q_{s_2}^{{\mu }_2}$ denotes the Fermi convolution of $Q_{s_1}^{{\mu }_1}$ and $Q_{s_2}^{{\mu }_2}$. We prove that if $\mathcal{L}$ is still a CSK family (that is, $\mathcal{L}={\mathcal{K}}_{+}\left(\sigma \right)$ for some nondegenerate probability measure ()$\sigma$), then the probability measures $\sigma$, ${\mu }_1$ and ${\mu }_2$ are of the free Poisson type and follow the free Poisson law up to affinity. The same result, regarding the free Poisson measure, is obtained if we consider the t-deformed free convolution $\begin{array}{|c|}\hline t\\ \hline\end{array}$ replacing the Fermi convolution • in the family of measures $\mathcal{L}$. Full article

The article addresses anthropogenic and geological conditions related to the development of soil subsidence in the western zone of Recife (Brazil). Over the past 50 years, human activity has intensified in areas previously affected by soft soils (clay, silt, and sandstone) resulting in subsidence due to additional loads (landfills and constructions). The duration of the settlement process can be significantly influenced by the specific characteristics of the soil composition and geological conditions of the location. This work presents, for the first time, accurate InSAR time series maps that describe the spatial pattern and temporal evolution of the settlement, as well as the correlation with the geological profile, and validation with Global Navigation Satellite System (GNSS) data. Persistent Scatterer Interferometry (PS-InSAR) was employed in the analysis of Single Look Complex (SLC) images generated by 100 ascending COSMO-SkyMed (CSK) and 65 PAZ (32 ascending, and 33 descending) from the X-band, along with 135 descending Sentinel-1 (S1) acquisitions from the C-band. These data were acquired over the period from 2011 to 2023. The occurrence of subsidence was identified in several locations within the western region, with the most significant displacement rates observed in the northern, central, and southern areas. In the northern region, the displacement rates were estimated to be approximately −20 mm/year, with the Várzea and Caxangá neighborhoods exhibiting the highest rates. In the central region, the displacement rates were estimated to be approximately −15 mm/year, with the Engenho do Meio, Cordeiro, Torrões, and San Martin neighborhoods exhibiting the highest rates. Finally, in the southern region, the displacement rates were estimated to be up to −25 mm/year, with the Caçote, Ibura, and Ipsep neighborhoods exhibiting the highest rates. Additionally, east–west movements were observed, with velocities reaching up to −7 mm/year toward the west. These movements are related to the lowering of the land. The study highlights that anthropogenic effects in the western zone of Recife contribute to the region’s vulnerability to soil subsidence. Full article

The traditional k-means algorithm is widely used in large-scale data clustering because of its easy implementation and efficient process, but it also suffers from the disadvantages of local optimality and poor robustness. In this study, a Csk-means algorithm based on contour similarity is proposed to overcome the drawbacks of the traditional k-means algorithm. For the traditional k-means algorithm, which results in local optimality due to the influence of outliers or noisy data and random selection of the initial clustering centers, the Csk-means algorithm overcomes both drawbacks by combining data lattice transformation and dissimilar interpolation. In particular, the Csk-means algorithm employs Fisher optimal partitioning of the similarity vectors between samples for the process of determining the number of clusters. To improve the robustness of the k-means algorithm to the shape of the clusters, the Csk-means algorithm utilizes contour similarity to compute the similarity between samples during the clustering process. Experimental results show that the Csk-means algorithm provides better clustering results than the traditional k-means algorithm and other comparative algorithms. Full article

In free probability, the theory of Cauchy–Stieltjes Kernel (CSK) families has recently been introduced. This theory is about a set of probability measures defined using the Cauchy kernel similarly to natural exponential families in classical probability that are defined by means of the exponential kernel. Within the context of CSK families, this article presents certain features of the Marchenko–Pastur law based on the Fermi convolution and the t-deformed free convolution. The Marchenko–Pastur law holds significant theoretical and practical implications in various fields, particularly in the analysis of random matrices and their applications in statistics, signal processing, and machine learning. In the specific context of CSK families, our study of the Marchenko–Pastur law is summarized as follows: Let ${\mathcal{K}}_{+}(\mu )=\{Q_m^{\mu }(dx);m\in (m_0^{\mu },m_{+}^{\mu })\}$ be the CSK family generated by a non-degenerate probability measure $\mu$ with support bounded from above. Denote by ${\left(Q_m^{\mu }\right)}^{•s}$ the Fermi convolution power of order $s>0$ of the measure $Q_m^{\mu }$. We prove that if ${\left(Q_m^{\mu }\right)}^{•s}\in {\mathcal{K}}_{+}(\mu )$, then $\mu$ is of the Marchenko–Pastur type law. The same result is obtained if we replace the Fermi convolution • with the t-deformed free convolution $\begin{array}{|c|}\hline t\\ \hline\end{array}$. Full article

Visible Light Communication (VLC) is emerging as a promising technology to meet the demands of fifth-generation (5G) networks and the Internet of Things (IoT). This study introduces a novel RGB-LED-based VLC system design that leverages autoencoders, addressing the often overlooked impact of optical-to-electrical (O/E) conversion efficiency. Unlike traditional methods, our autoencoder-based system not only improves communication performance but also mitigates the negative effects of O/E conversion. Through comprehensive simulations, we show that the proposed autoencoder structure enhances system robustness, achieving superior performance compared to traditional VLC systems. By quantitatively assessing the impact of O/E conversion—a critical aspect previously overlooked in the literature—our work bridges a crucial gap in VLC research. This contribution not only advances the understanding of VLC systems but also provides a strong foundation for future enhancements in 5G and IoT connectivity. Full article

Periodontal diseases, chronic inflammatory conditions affecting oral health, are primarily driven by microbial plaque biofilm and the body’s inflammatory response, leading to tissue damage and potential tooth loss. These diseases have significant physical, psychological, social, and economic impacts, necessitating effective management strategies that include early diagnosis, comprehensive treatment, and innovative therapeutic approaches. Recent advancements in biomanufacturing have facilitated the development of natural bioactive compounds, such as polyphenols, terpenoids, alkaloids, saponins, and peptides, which exhibit antimicrobial, anti-inflammatory, and tissue regenerative properties. This review explores the biomanufacturing processes—microbial fermentation, plant cell cultures, and enzymatic synthesis—and their roles in producing these bioactive compounds for managing periodontal diseases. The integration of these natural compounds into periodontal therapy offers promising alternatives to traditional treatments, potentially overcoming issues like antibiotic resistance and the disruption of the natural microbiota, thereby improving patient outcomes. Full article

Margaritasite is a mineral compound discovered in the early 1980s in Chihuahua, Mexico. It is a natural cesium uranyl vanadate found only, so far, in the Margaritas mine of the Peña Blanca highlands. In this work, a thorough characterization of the aforementioned mineral is presented. The portfolio of the techniques employed includes high-resolution X-ray diffraction, scanning electron microscopy with energy dispersive X-ray spectroscopy, transmission electron microscopy in selected area electron diffraction (SAED) mode, and X-ray absorption spectroscopy (XAS). After extensive data analysis and modeling, new information on the mineral has been retrieved. Its phase composition is margaritasite–carnotite: a solid solution of cesium and potassium uranyl vanadate [(Cs,K)₂(UO₂)₂(VO₄)₂·nH₂O], and margaritasite, which is practically pure cesium uranyl vanadate [Cs₂(UO₂)₂(VO₄)₂·nH₂O]. The crystal structure of both components presents the space group P 1 2₁/c 1. Yet, each phase has similar, but appreciably different, lattice parameters. The mineral has a lamellar tabular and prismatic morphology. SAED patterns confirm the crystal structure of margaritasite. XAS spectra of Cs, V, and U confirm the elemental composition, oxidation states, and interatomic distances of this structure. These findings are consistent with the presence of cesium in this unique mineral from the paragenesis point of view. Full article

C-terminal Src kinase (CSK) is the major inhibitory kinase for Src family kinases (SFKs) through the phosphorylation of their C-tail tyrosine sites, and it regulates various types of cellular activity in association with SFK function. As a cytoplasmic protein, CSK needs be recruited to the plasma membrane to regulate SFKs’ activity. The regulatory mechanism behind CSK activity and its subcellular localization remains largely unclear. In this work, we developed a genetically encoded biosensor based on fluorescence resonance energy transfer (FRET) to visualize the CSK activity in live cells. The biosensor, with an optimized substrate peptide, confirmed the crucial Arg¹⁰⁷ site in the CSK SH2 domain and displayed sensitivity and specificity to CSK activity, while showing minor responses to co-transfected Src and Fyn. FRET measurements showed that CSK had a relatively mild level of kinase activity in comparison to Src and Fyn in rat airway smooth muscle cells. The biosensor tagged with different submembrane-targeting signals detected CSK activity at both non-lipid raft and lipid raft microregions, while it showed a higher FRET level at non-lipid ones. Co-transfected receptor-type protein tyrosine phosphatase alpha (PTPα) had an inhibitory effect on the CSK FRET response. The biosensor did not detect obvious changes in CSK activity between metastatic cancer cells and normal ones. In conclusion, a novel FRET biosensor was generated to monitor CSK activity and demonstrated CSK activity existing in both non-lipid and lipid raft membrane microregions, being more present at non-lipid ones. Full article

The code-shift keying (CSK) modulation method can achieve higher information transmission rates without changing the spread spectrum signal bandwidth. In order to optimise the spread spectrum modulation and demodulation of GNSS signals, in addition to the signal structure, binary phase-shift keying (BPSK) and CSK signals using time-division multiplexing are proposed. A tracking method based on the BPSK-CSK signals is also proposed, which generates the P-branch local codes by fast Fourier transform to obtain the code-slice spacings for the E-branch and the L-branch local codes. Then, the tracked BPSK signals and tracked CSK signals are compared and analysed. Finally, the bit error rate (BER) and tracking error of each method are compared and analysed by comparing with the tracking of conventional BPSK signals and tracking of CSK signals, in order to verify the convergence process of the I-branch integral value. The BPSK-CSK signal tracking method proposed in this paper combines the high information transmission rate of CSK-modulated signals and the low BER of BPSK signals, and the results provide a solid foundation for high-precision GNSS services. Full article

A notion of generalized (two-parameterized) t-transformation of free convolution, also called $(\mathbf{t}=(a,b\left)\right)$-deformed free convolution, is introduced for $a\in \mathbb{R}$ and $b>0$. In this article, some results of $\mathbf{t}$-deformed free convolution are given within the theory of Cauchy-Stieltjes Kernel (CSK) families. The variance function is a fundamental concept in CSK families. An expression is provided for the variance function under $\mathbf{t}$-deformed free convolution power. In addition, through the use of the variance function, an approximation is provided for members of the $\mathbf{t}$-deformed free Gaussian CSK family and members of the $\mathbf{t}$-deformed free Poisson CSK family respectively. Furthermore, by involving the free multiplicative convolution, a new limit theorem is provided with respect to $\mathbf{t}$-deformed free convolution. Full article

Many previous studies have primarily focused on the use of deep learning for interferometric processing or separate recognition purposes rather than targeted measurements of detected wellpads. The present study centered around the integration of deep learning recognition and interferometric measurements for Tengiz oilfield wellpads. This study proposes the optimization, automation, and acceleration of targeted ground deformation wellpad monitoring. Mask Region-based Convolutional Neural Network (R-CNN)-based deep learning wellpad recognition and consequent Small Baseline Subset Synthetic Aperture Radar Interferometry (SBAS-InSAR) analyses were used for the assessment of ground deformation in the wellpads. The Mask R-CNN technique allowed us to detect 159 wells with a confidence level of more than 95%. The Mask R-CNN model achieved a precision value of 0.71 and a recall value of 0.91. SBAS-InSAR interferometric measurements identified 13 wells for Sentinel-1 (SNT1), 8 wells for COSMO-SkyMed (CSK), and 20 wells for TerraSAR-X (TSX) located within the −54–−40 mm/y class of vertical displacement (VD) velocity. Regression analyses for the annual deformation velocities and cumulative displacements (CD) of wells derived from SNT1, CSK, and TSX satellite missions showed a good agreement with R² > 95. The predictions for cumulative displacements showed that the vertical subsidence processes will continue and reach −339 mm on 31 December 2023, with increasing spatial coverage and the potential to impact a higher number of wells. The hydrological analyses in the Tengiz oilfield clearly demonstrated that water flow has been moving towards the detected hotspot of subsidence and that its accumulation will increase with increasing subsidence. This detected subsidence hotspot was observed at a crossing with a seismic fault that might always be subject to reactivation. The role of this seismic fault should also be investigated as one of the ground deformation-controlling factors, even though this area is not considered seismically active. The primary practical and scientific values of these studies were identified for the operational risk assessment and maintenance needs of oilfield and gas field operators. Full article

Excessive reactive oxygen species production can detrimentally impact skin cell physiology, resulting in cell growth arrest, melanogenesis, and aging. Recent clinical studies have found that lactic acid bacteria have a special effect directly or indirectly on skin organs, but the exact mechanism has not been elucidated. In this study, we investigated the mechanisms underlying the antioxidant protective effect and the inhibitory effect on melanin synthesis of Lactobacillus kunkeei culture supernatant (CSK), isolated from Apis mellifera Linnaeus (the Western honeybee). CSK exhibited notable efficacy in promoting cell migration and wound healing under oxidative stress, surpassing the performance of other strains. CSK pretreatment significantly upregulated the expression of Nrf2/HO-1 (nuclear factor erythroid 2-related factor 2/heme oxygenase-1), a key player in cellular defenses against oxidative stress, relative to the control H₂O₂-treated cells. The DCF-DA (dichloro-dihydro-fluorescein diacetate) assay results confirmed that CSK’s ability to enhance Nrf2 and HO-1 expression aligns with its robust ability to remove H₂O₂-induced reactive oxygen species. Furthermore, CSK upregulated MAPK (mitogen-activated protein kinase) phosphorylation, an upstream signal for HO-1 expression, and MAPK inhibitors compromised the wound-healing effect of CSK. Additionally, CSK exhibited inhibitory effects on melanin synthesis, downregulating melanogenesis-related genes in B16F10 cells. Thus, the present study demonstrated that CSK exhibited antioxidant effects by activating the Nrf2/HO-1 pathway through MAPK phosphorylation, thereby restoring cell migration and demonstrating inhibitory effects on melanin production. These findings emphasize the antioxidant and antimelanogenic potential of CSK, suggesting its potential use as a therapeutic agent, promoting wound healing, and as an active ingredient in skin-lightening cosmetics. Full article