Search Results (126)

The emergence of H5N1 highly pathogenic avian influenza virus (HPAIV) clade 2.3.4.4b in dairy cattle across multiple U.S. states in early 2024 marks a major shift in the virus’s host range and epidemiological profile. Traditionally limited to bird species, the ongoing detection of H5N1 in cattle, a mammalian host not previously considered vulnerable, raises urgent animal and human health concerns about zoonoses and mammalian adaptation. We assessed the feasibility of using commercially available pasteurized milk as a sentinel matrix for the molecular detection and genetic characterization of H5N1 HPAIV. Our aim was to determine whether retail milk could serve as a practical tool for virological monitoring and to evaluate the use of full-length genome segment amplification for extracting genomic sequence information from this highly processed matrix. Our results link HPAIV sequences in store-bought milk to the cattle outbreak and highlight both the potential and the limitations of retail milk as a surveillance window. Together, these findings provide evidence that influenza A virus RNA can be repeatedly detected in retail milk in patterns linked to specific supply chains, with genomic data confirming close relationships with the viruses circulating in cattle. Full article

The dried root extract of Astragalus membranaceus, also known as Astragali radix, is widely used in traditional Chinese medicine for its multiple health benefits and well-established safety profile. Astragalus root extract exhibits several bioactive properties, including anti-inflammatory, antioxidant, antiviral and hepatoprotective effects. Due to its unique features, it is being investigated in a novel application as a complementary remedy in the management of joint disorders. In this study, we evaluated the effect of Astragalus membranaceus hydroalcoholic root extract (0.01 and 0.1 mg/mL) in vitro on the HTB-94 cell line, a well-known model for studying inflammatory pathways in human chondrocytes. The mRNA modulation levels were measured by quantitative real-time polymerase chain reaction (qRT-PCR), while the protein secretion levels were assessed using an Enzyme-Linked Immunosorbent Assay (ELISA). Results obtained demonstrated that this extract is able to decrease the tumor necrosis factor-α (TNF-α)-induced inflammatory response by downregulating both the mRNA expression and release of the pro-inflammatory mediators Interleukin-6 (IL-6), Interleukin-1β (IL-1β) and Interelukin-8 (IL-8), as well as matrix metalloproteases, including Matrix Metalloprotease-3 (MMP-3), Matrix Metalloprotease-13 (MMP-13) and A disintegrin, and metalloproteinase with thrombospondin motifs 5 (ADAMTS-5). Moreover, the interleukin and matrix metalloprotease production was also assessed in non-TNF-α-stimulated cells, revealing that the extract did not alter the basal levels of these mediators. Finally, our findings highlight the potential benefits of Astragalus membranaceus extract, both in terms of its favorable safety profile and its efficacy mitigating joint inflammatory responses. These results support the potential of this extract as a nutraceutical agent for joint health support. Full article

A novel unified progressive hybrid censoring is introduced to combine both progressive and hybrid censoring plans to allow flexible test termination either after a prespecified number of failures or at a fixed time. This work develops both frequentist and Bayesian inferential procedures for estimating the parameters, reliability, and hazard rates of the inverted Nadarajah–Haghighi lifespan model when a sample is produced from such a censoring plan. Maximum likelihood estimators are obtained through the Newton–Raphson iterative technique. The delta method, based on the Fisher information matrix, is utilized to build the asymptotic confidence intervals for each unknown quantity. In the Bayesian methodology, Markov chain Monte Carlo techniques with independent gamma priors are implemented to generate posterior summaries and credible intervals, addressing computational intractability through the Metropolis—Hastings algorithm. Extensive Monte Carlo simulations compare the efficiency and utility of frequentist and Bayesian estimates across multiple censoring designs, highlighting the superiority of Bayesian inference using informative prior information. Two real-world applications utilizing rare minerals from gold and diamond durability studies are examined to demonstrate the adaptability of the proposed estimators to the analysis of rare events in precious materials science. By applying four different optimality criteria to multiple competing plans, an analysis of various progressive censoring strategies that yield the best performance is conducted. The proposed censoring framework is effectively applied to real-world datasets involving diamonds and gold, demonstrating its practical utility in modeling the reliability and failure behavior of rare and high-value minerals. Full article

Terahertz (THz) communication is regarded as a promising technology for future 6G networks because of its advances in providing a bandwidth that is orders of magnitude wider than current wireless networks. However, the large bandwidth and the large number of antennas in THz massive multiple-input multiple-output (MIMO) systems induce a pronounced beam split effect, leading to a serious array gain loss. To mitigate the beam split effect, this paper considers a delay-phase precoding (DPP) architecture in which a true-time-delay (TTD) network is introduced between radio-frequency (RF) chains and phase shifters (PSs) in the standard hybrid precoding architecture. Then, we propose a fast Riemannian conjugate gradient optimization-based alternating minimization (FRCG-AltMin) algorithm to jointly optimize the digital precoding, analog precoding, and delay matrix, aiming to maximize the spectral efficiency. Different from the existing method, which solves an approximated version of the analog precoding design problem, we adopt an FRCG method to deal with the original problem directly. Simulation results demonstrate that our proposed algorithm can improve the spectral efficiency, and achieve superior performance over the existing algorithm for wideband THz massive MIMO systems with angular spread. Full article

In tolerance design for complex mechanical systems, 3D dimension chain analyses are crucial for assembly accuracy. The current methods (e.g., worst-case analysis, statistical tolerance analysis) face limitations from oversimplified assumptions—treating datum features as ideal geometries while ignoring manufacturing-induced spatial distribution of form errors and failing to characterize 3D coupled error constraints. This study proposes a six-dimensional spatial dimension chain (SDC) model based on transfer matrix theory. The key innovations include (1) a six-dimensional model integrating position and orientation vectors, incorporating geometric error propagation constraints for high-fidelity error prediction and tolerance optimization, (2) the characterization of spatially distributed form errors and 3D coupled errors of spatial dimension chain-based multiple mating-surface constraint (SDC-MMSC) using six-degree-of-freedom (6-DoF) geometric error components, reducing the assembly topology complexity while improving the efficiency, and (3) a 6-DoF error characterization method for non-mating-constrained data, providing the theoretical basis for SDC modeling. The experimental validation on an aero-engine casing assembly shows that the SDC model captures multidimensional closed-loop spatial errors, with absolute errors of max–min closed-loop distances below 9.3 μm and coaxiality prediction errors under 8.3%. The SDC-MMSC method demonstrates superiority, yielding normal vector angular errors <0.008° and envelope surface RMSE values <0.006 mm. This method overcomes traditional simplified assumptions, establishing a high-precision, multidimensional distributed-form-error-driven SDC model for complex mechanical systems. Full article

Cannabidiol (CBD), a phytocannabinoid commonly isolated from chemotype III Cannabis sativa plants, is known for its therapeutic potential. However, comprehensive information on its bioavailability is still lacking. The key objective of this study was to investigate the impact of specific formulations on CBD delivery to the site of action and, in particular, the brain of experimental animals. As brain tissue is an extremely complex matrix, a highly sensitive method employing liquid chromatography–tandem mass spectrometry (LC-MS/MS) had to be implemented. To make it applicable for multiple analytes, the method was validated for 17 other phytocannabinoids and selected metabolites. Using this method, a pharmacokinetic study was conducted on 200 brain samples collected from rats that had been administered various CBD formulations (carriers) via oral gavage. The peak concentration in brain occurred within 1–2 h; notably, the highest was reached with carriers containing triacylglycerols with the shortest fatty acid chains (caprylic/capric). In addition to the parent compound, 7-hydroxy-cannabidiol and 7-carboxy-cannabidiol were detected, confirming rapid post-administration metabolism. Overall, this research enhances understanding of CBD distribution in the brain and underscores the impact of specific formulations on its bioavailability, offering insights into optimizing CBD-based therapies to be both effective and ‘patient-friendly’. Full article

To overcome the shortcomings of traditional polyurethane, such as poor weather resistance and susceptibility to hydrolysis, this study systematically explores the preparation techniques of organic silicon-modified polyurethane and its application in intelligent sports fields. By introducing siloxane into the polyurethane matrix through copolymerization, physical blending, and grafting techniques, the microphase separation structure and interfacial properties of the material are effectively optimized. In terms of synthesis processes, the one-step method achieves efficient preparation by controlling the isocyanate/hydroxyl molar ratio (1.05–1.15), while the prepolymer chain extension method optimizes the crosslinked network through dual reactions. The modified material exhibits significant performance improvements: tensile strength reaches 60 MPa, tear resistance reaches 80 kN/m, and the elastic recovery rate ranges from 85% to 92%, demonstrating outstanding weather resistance. In sports field applications, the 48% impact absorption rate meets the requirements for athletic tracks, wear resistance of <15 mg suits gym floors, and the impact resistance for skate parks reaches 55%–65%. Its environmental benefits are notable, with volatile organic compounds (VOC) <50 g/L and a recycling rate >85%, complying with green building material standards. However, its development is still constrained by multiple factors: insufficient material interface compatibility, a comprehensive cost of 435 RMB/m², and the lack of a quality evaluation system. Future research priorities include constructing dynamic covalent crosslinked networks (e.g., self-healing systems), adopting bio-based raw materials to reduce carbon footprint by 30%–50%, and integrating flexible sensing technologies for intelligent responsiveness. Through multidimensional innovation, this material is expected to evolve toward multifunctionality and environmental friendliness, providing core material support for the intelligent upgrading of sports fields. Full article

Methionine restriction (MetR) is a common adjuvant treatment for cancer. However, studies of MetR have paid little attention to its potential implications for fibrosis. Hypertrophic scarring (HTS) is an abnormal fibrotic response after burn trauma that results from the excessive activation of fibroblasts. Because of the absence of a fully effective pharmacological treatment, HTS frequently causes great annoyance in patients as a common sequela of burns. To date, the effects of MetR on hypertrophic scar fibroblasts (HTSFs) remain unclear. This study aimed to investigate the anti-fibrotic effects of MetR and explore the associated alterations in signaling pathways in HTSFs. We isolated HTSFs from post-burn HTS tissues and cultured them in a specially prepared MetR medium. Cell and immunocytochemical staining images were captured using light and fluorescence microscopes, respectively. Cell proliferation was evaluated using a CellTiter-Glo Luminescent Cell Viability Assay Kit. mRNA and protein expression levels were determined using quantitative reverse transcription polymerase chain reaction and Western blotting, respectively. In HTSFs, MetR reduced cellular inflammation; downregulated multiple signaling pathways, including the TGF-β-SMAD, STAT, and AKT/mTOR pathways; and upregulated MAPKs. Furthermore, MetR arrested the cell cycle, promoted apoptosis, suppressed cell proliferation and migration, and reduced extracellular matrix protein secretion, thereby exerting multifaceted inhibitory effects on HTS. Our results demonstrated that MetR can inhibit scars’ formation and suggest that regulating methionine metabolism in the scar environment may help treat scars. Full article

Background/Objectives: The main objective of this research work was to identify and determine the antibiotic resistance of the false-positive isolates on chromogenic agar when analyzing Salmonella in chicken meat. Methods: A total of 234 samples of chicken meat (carcasses, cuts and preparations) were studied using buffered peptone water for primary enrichment, Rappaport–Vassiliadis soy broth for secondary enrichment and Salmonella Chromogen Agar Set as a selective solid medium. Colonies with a morphology characteristic of Salmonella (one isolate per sample) were identified by matrix-assisted laser desorption ionization and time-of-flight mass spectrometry (MALDI-TOF). Results: Colonies with a characteristic morphology of Salmonella were detected in 71 samples. Only five isolates (7.0% of the total) corresponded to the genus Salmonella. Other genera detected were Hafnia (three isolates; 4.2% of the total), Escherichia (22; 31.0%), Klebsiella (19; 26.8%), Proteus (6; 8.5%) and Pseudomonas (16; 22.5%). The 66 isolates of these last five genera were tested for susceptibility to a panel of 42 antibiotics of clinical importance by disc diffusion. All isolates presented multiple resistances, to between 4 and 29 antibiotics, all of them having a multi drug-resistant (MDR) phenotype except for one Pseudomonas strain, with an extensively drug-resistant (XDR) phenotype. Conclusions: These results highlight the low selectivity of this method, with the specific culture media under test, for the detection of Salmonella in poultry meat. The considerable prevalence of antibiotic resistance observed suggests a need to improve control measures throughout the poultry meat production chain to prevent this food from becoming a reservoir of bacteria with resistance to multiple antibiotics. Full article

Automatic differentiation (AD) is a general method for computing exact derivatives in complex sensitivity analyses and optimisation tasks, particularly when closed-form solutions are unavailable and traditional analytical or numerical methods fall short. This paper introduces a vectorised formulation of AD grounded in matrix calculus. It aligns naturally with the matrix-oriented style prevalent in statistics, supports convenient implementations, and takes advantage of sparse matrix representation and other high-level optimisation techniques that are not available in the scalar counterpart. Our formulation is well-suited to high-dimensional statistical applications, where finite differences (FD) scale poorly due to the need to repeat computations for each input dimension, resulting in significant overhead, and is advantageous in simulation-intensive settings—such as Markov Chain Monte Carlo (MCMC)-based inference—where FD requires repeated sampling and multiple function evaluations, while AD can compute exact derivatives in a single pass, substantially reducing computational cost. Numerical studies are presented to demonstrate the efficacy and speed of the proposed AD method compared with FD schemes. Full article

This paper is dedicated to dealing with the design issue of a non-fragile state estimator for a type of nonlinear complex network subject to random couplings and random multiple time delays under binary encoding schemes (BESs). The BESs are put into use in the transmission of data from the sensor to the remote estimator. The phenomenon of bit errors is considered in the process of signal transmission, whose description utilizes a Bernoulli-distributed random sequence. The random couplings are represented by using the Kronecker delta function as well as a Markov chain. This paper aims to conduct a non-fragile state estimation such that, in the presence of some variations/perturbations in the gain parameter of the estimator, the estimation error dynamics will reach exponential ultimate boundedness in mean square and the ultimate bound will be minimized. Utilizing both stochastic analysis and matrix inequality processing, a sufficient condition is provided to guarantee that the constructed estimator satisfies the expected estimation performance, and the estimator gains are acquired by tackling an optimization issue constrained by some linear matrix inequalities. Eventually, two simulation examples are conducted, whose results verify that the approach to the design of a non-fragile estimator in this paper is effective. Full article

Clear cell renal cell carcinoma (ccRCC) is characterized by significant clinical and molecular heterogeneity, with immune and metabolic processes playing crucial roles in tumor progression and influencing patient outcomes. This study aims to elucidate the molecular subtypes of ccRCC by employing non-negative matrix factorization (NMF) clustering on differentially expressed genes (DEGs), thereby identifying distinct transcriptional profiles, immune cell infiltration patterns, and subsequent survival outcomes. Utilizing NMF clustering, we identified two molecular subtypes of ccRCC. We developed a prognostic model using LASSO–Cox regression, validated with multiple datasets and quantitative reverse transcription polymerase chain reaction (qRT-PCR), incorporating ten immunity- and metabolism-related genes (IMRGs) for overall survival (OS) prediction. Immune cell infiltration and tumor mutational burden (TMB) analyses were performed to explore differences between high- and low-risk groups, while Gene Set Enrichment Analysis (GSEA) provided insights into relevant biological pathways. The findings revealed that subtype C1, characterized by a “cold” tumor microenvironment, correlates with better prognostic outcomes compared to subtype C2, which exhibits an immunologically active environment and worse survival prospects. High-risk patients demonstrated poorer OS associated with alterations in immune and metabolic pathways. Immune checkpoint analysis indicated the upregulation of CTLA4, LAG3, and LGALS9 in high-risk patients, suggesting potential therapeutic targets. A nomogram integrating IMRG risk scores with clinical factors displayed high predictive accuracy for 1-, 3-, and 5-year OS. These findings provide novel insights into the molecular heterogeneity of ccRCC and emphasize the interconnected roles of immune dysregulation and metabolic alterations in tumor progression. By identifying key prognostic biomarkers and potential therapeutic targets, this study paves the way for innovative strategies aimed at harnessing immune and metabolic pathways for better clinical outcomes in ccRCC patients. Full article

With the development of the smart logistics industry, the demand for intelligent loading and unloading (ILU) within urban supply chains (USCs) is increasing. However, few studies have examined the critical success factors (CSFs) for enhancing ILU in USCs. This study establishes a CSF model to support ILU improvement. Specifically, it integrates stakeholder theory, resource-based view theory, and innovation diffusion theory. Through research conducted in collaboration with 16 logistics industry specialists in Korea, 19 critical factors were identified. Fuzzy DEMATEL and the Adversarial Interpretive Structure Model (AISM) were then applied to analyze the identified factors. The results indicate that stakeholder collaboration, government support, and regulatory compliance are the most important factors affecting ILU improvement within USCs. Finally, cross-impact matrix multiplication applied to classification (MICMAC) analysis further verifies that these factors have a high driving power and low dependence, making them independent driving factors of the entire system. Furthermore, this study emphasizes the role of market research and automated system design. This work contributes to the knowledge on the intelligent logistics management of supply chains. Full article

Tendons are connective tissues that join muscles and bones and are rich in glycosaminoglycans (GAGs). Decorin is a proteoglycan with one dermatan sulfate (DS) or chondroitin sulfate (CS) chain (a type of GAG) attached to its core protein and is involved in regulating the assembly of collagen fibrils in the tendon extracellular matrix (ECM). Calcium-activated nucleotidase 1 (CANT1), a nucleotidase that hydrolyzes uridine diphosphate into uridine monophosphate and phosphate, plays an important role in GAG synthesis in cartilage. In the present study, we performed detailed histological and biochemical analyses of the tendons from Cant1 knockout (Cant1^−/−) mice. No abnormalities were observed in the tendons on postnatal day 1 (P1); however, remarkable hypoplasia was observed on P30 and P180. The collagen fibrils were more angular and larger in the Cant1^−/− tendons than in the control (Ctrl) tendons. In the Cant1^−/− tendons, the DS/CS content was significantly reduced, and the DC/CS chains attached to the decorin core protein became shorter than those in the Ctrl tendons. No abnormalities were observed in the proliferation and differentiation of tendon fibroblasts (tenocytes) in the Cant1^−/− mice. These results strongly suggest that CANT1 dysfunction causes defective DS/CS synthesis, followed by impairment of decorin function, which regulates collagen fibrogenesis in the tendon ECM. Multiple joint dislocations are a clinical feature of Desbuquois dysplasia type 1 caused by human CANT1 mutations. The multiple joint dislocations associated with this genetic disorder may be attributed to tendon fragility resulting from CANT1 dysfunction. Full article

There are limited parallel robots applicable to three-axis grinding machines due to the restricted reachable workspace originating from multiple kinematic chains with spatial kinematic joints. The parallel robot will gain significant potential in the industry if a larger workspace can be achieved. This research introduces a special relationship between upper triangular matrix and parallel robot structures for the purpose of designing a group of novel parallel robots without spatial kinematic joints. The detailed inverse kinematic solution of the selected parallel manipulator is derived in accordance with its straightforward architecture. Several singularity configurations are found on the basis of the first-order kinematic relation. The translational reachable workspace is close to a triangular prism. The dexterity and stiffness performances based on the Jacobian matrix are explored for the chosen parallel manipulator. Both indices display a downward trend as the mobile platform rises higher. Full article