Search Results (5,921)

Background/Objectives: Hypertension is a global health challenge. Zhengan Xifeng Decoction (ZXD), a classical traditional Chinese medicine, has shown clinical efficacy against hypertension. This study aimed to identify the bioactive constituents of ZXD and elucidate its antihypertensive mechanisms by integrating plasma UPLC–MS (ultra-performance liquid chromatography–mass spectrometry) analysis, network pharmacology, and molecular dynamics (MD) simulations. Methods: ZXD constituents and plasma-absorbed compounds were characterized by UPLC–MS. Putative targets (TCMSP, SwissTargetPrediction) were cross-referenced with hypertension targets (GeneCards, OMIM) and analyzed in a STRING protein–protein interaction network (Cytoscape) to define hub targets, followed by GO/KEGG enrichment. Selected protein–ligand complexes underwent docking, Prime MM-GBSA calculation, and MD validation. Results: A total of 72 absorbed components were identified, including 14 prototype compounds and 58 metabolites. Network pharmacology identified ten key bioactive compounds (e.g., liquiritigenin, isoliquiritigenin, and caffeic acid), 149 hypertension-related targets, and ten core targets such as SRC, PIK3CA, PIK3CB, EGFR, and IGF1R. Functional enrichment implicated cardiovascular, metabolic, and stress-response pathways in the antihypertensive effects of ZXD. Molecular docking demonstrated strong interactions between key compounds, including liquiritigenin, caffeic acid, and isoliquiritigenin, and core targets, supported by the MM-GBSA binding free energy estimation. Subsequent MD simulations confirmed the docking poses and validated the stability of the protein–ligand complexes over time. Conclusions: These findings provide mechanistic insights into the multi-component, multi-target, and multi-pathway therapeutic effects of ZXD, offering a scientific basis for its clinical use and potential guidance for future drug development in hypertension management. Full article

YKL-40, an obesity-related inflammatory biomarker, has inconsistently been associated with insulin resistance, and its relationship with metabolic syndrome is not well established. This study investigated the associations of YKL-40 levels with insulin resistance and metabolic syndrome independently of obesity. We analyzed data from 4303 participants without diabetes in the Taiwan Biobank. Insulin resistance was defined by the highest quartile of triglyceride-glucose body mass index (TyG-BMI). Metabolic syndrome was defined per AHA/NLHBI criteria. Both univariate and multivariate analyses demonstrated significant correlations between YKL-40 levels and TyG-BMI. Participants with higher YKL-40 quartiles exhibited increased odds of TyG-BMI-estimated insulin resistance even after adjusting for established predictors of TyG-BMI, including waist circumference. Similarly, higher YKL-40 quartiles significantly correlated with increased metabolic syndrome prevalence, and this relationship persisted after stratifying participants by weight status (normal weight vs. overweight/obese). Interaction analysis indicated that overweight/obesity individuals consistently had higher metabolic syndrome prevalence than normal-weight counterparts within identical YKL-40 quartiles, though the impact of overweight/obese diminished across rising YKL-40 quartiles (p for interaction = 0.008). Increased YKL-40 levels are significantly associated with TyG-BMI-estimated insulin resistance and metabolic syndrome, independent of obesity. There is a significant interaction between overweight/obese and YKL-40 levels in determining metabolic syndrome prevalence. Full article

Non-communicable diseases (NCDs) are the leading global cause of death, causing over 43 million deaths in 2021, including 18 million premature deaths, disproportionately affecting low- and middle-income countries. NCDs also incur significant economic losses, estimated at USD 7 trillion from 2011 to 2025, despite low prevention costs. This study evaluated body mapping indicators: body mass index (BMI), waist circumference, and waist-to-hip ratio—for predicting NCD risk, including hypertension, diabetes, and cardiovascular diseases, using data from a nationally representative survey in Ghana. The study sampled 5775 participants via multistage stratified sampling, ensuring proportional representation by region, urban/rural residency, age, and gender. Ethical approval and informed consent were obtained. Anthropometric and biochemical data, including height, weight, waist and hip circumferences, blood pressure, fasting glucose, and lipid profiles, were collected using standardized protocols. Data analysis was conducted with STATA 17.0, accounting for complex survey design. Significant sex-based differences were observed: men were taller and lighter, while women had higher BMI and waist/hip circumferences. NCD prevalence increased with age, peaking at 60–69 years, and was higher in females. Lower education and marital status (widowed, divorced, separated) correlated with higher NCD prevalence. Obesity and high waist circumference strongly predicted NCD risk, but individual anthropometric measures lacked screening accuracy. Integrated screening and tailored interventions are recommended for improved NCD detection and management in resource-limited settings. Full article

Background: Insulin resistance (IR) is common in overweight or obese individuals. Dysregulation of trace elements such as cobalt (Co) and manganese (Mn) has been associated with obesity and IR markers in individuals with diabetes. However, their role in non-diabetic states is less understood. Objective: This study aimed to analyze the association between serum Co and Mn levels and IR in overweight and obese women without diabetes. Methods: A total of 112 overweight or obese women were evaluated for their anthropometric, metabolic, and biochemical characteristics. To estimate IR, the homeostatic model assessment of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), triglyceride–glucose index (TyG), and triglyceride–glucose–body mass index (TyG-BMI) were calculated. Serum Co and Mn concentrations were quantified by inductively coupled plasma mass spectrometry (ICP-MS). Results: Our results show that 77% of participants exhibited central fat accumulation and a high prevalence of IR. Fasting insulin (FINS), HOMA-IR, and TyG-BMI were significantly higher in obese women, while adiponectin (Adpn) was lower. Moreover, Co was inversely associated with FINS (p = 0.003) and HOMA-IR (p = 0.011), and positively associated with QUICKI (p = 0.011) in obese women. In contrast, serum Mn levels showed negative correlations with fasting glucose (FG) (p = 0.021) and the TyG index (p = 0.048) in overweight women. Conclusions: Co serum levels were positively associated with FG and QUICKI and negatively associated with FINS and HOMA-IR in the obese group. Mn showed negative associations with FG and the TyG index, suggesting that these trace elements may play a role in the IR in people with obesity. Full article

The probability density function (PDF) of the product of two normal random variables remains an open discussion. Researchers have proposed many forms of PDFs. Among these, two notable PDFs are an analytical solution with infinite summation and an integral form with transformation. For practical computation, they must be estimated. The form with infinite summation must be truncated to a finite summation, and the form still in integration must be computed numerically. As a result of this estimation, an error occurs in the value of the estimation. This paper derives upper bounds for the estimation error resulting from truncation and numerical approximation in integral calculations. The upper bound error between the exact PDF and the truncated PDF is expressed as a geometric series using Bessel function inequality and Stirling’s approximation. The geometric formula allows the quantification of the total truncation error to be determined. For the PDF, which is still in integration form, the trapezoidal rule is used for numeric calculation. Hence, the error can be determined using the error-bound formula. The two estimated PDFs have their own advantages and disadvantages. The truncated PDF gives a relatively small upper bound value compared to the numerical calculation integral form PDF for a small value domain. However, the truncated PDF fails to perform for a large value domain, and only the integral form PDF can be used. The error for the estimation is applied to the conventional mass measurement. The results demonstrate that the error can be controlled through an analytical approach. Full article

Lattice structures are lightweight architected materials particularly suitable for aerospace and automotive applications due to their ability to combine mechanical strength with reduced mass. Among various topologies, Body-Centered Cubic (BCC) lattices are widely employed for their geometric regularity and favorable strength-to-weight ratio. Advances in Additive Manufacturing (AM) have enabled the precise and customizable fabrication of such complex architectures, reducing material waste and increasing design flexibility. This study investigates the low-velocity impact behavior of two polylactic acid (PLA)-based BCC lattice panels differing in strut diameter: BCC1.5 (1.5 mm) and BCC2 (2 mm). Experimental impact tests and finite element simulations were performed to evaluate their energy absorption () capabilities. In addition to conventional global performance indices, a dimensionless parameter, is introduced to quantify the ratio between local plastic indentation and global displacement, allowing for a refined characterization of deformation modes and structural efficiency. Results show that BCC1.5 absorbs more energy than BCC2, despite the latter’s higher stiffness. This suggests that thinner struts enhance energy dissipation under dynamic loading. Despite minor discrepancies, numerical simulations provide accurate estimations of and support the robustness of the index within the examined configuration, highlighting its potential to deformation heterogeneity. Full article

Background: Air pollution is a well-established risk factor for cardiovascular and metabolic diseases. Although Southern Switzerland is considered a relatively low-pollution area, levels of nitrogen dioxide (NO₂) and particulate matter (PM₁₀) still exceed the latest WHO air quality guidelines. This study aimed to assess the association between long-term exposure to air pollutants, vascular aging, and body composition in a Swiss population sample. Methods: A cross-sectional analysis was conducted on 1202 participants from the Ticino Epidemiological Stiffness Study (2017–2018). Vascular health was assessed via pulse wave velocity (PWV), used to estimate vascular age. Body composition was evaluated through bioimpedance analysis, yielding fat mass index (FMI), body cellular mass (BCM), and body cellular mass index (BCMI). Individual exposure to NO₂ and PM₁₀ was estimated, using geocoded residential data and environmental monitoring records from 2002 to 2017. Statistical models were adjusted for major cardiovascular risk factors. Results: Higher exposure to NO₂ was significantly associated with increased vascular age (mean delta age: +0.53 years in the high exposure group) and adverse body composition markers, including higher FMI and lower BCM/BCMI. These associations remained significant after adjusting for confounders. PM₁₀ showed weaker associations, significant only in unadjusted models. Conclusions: Even in a relatively clean environment, exposure to NO₂ is linked to early vascular aging and unfavorable body composition. These findings reinforce the need for stricter air quality standards and underline the importance of continuous environmental health surveillance, even in regions considered low risk. Full article

In this study, we propose a simple and effective method for gas analysis by establishing a correlation between residual gas analyzer (RGA) intensity and gas concentration. To achieve this, we focused on CF₄ and NF₃, two high-global warming potential (GWP) gases commonly used in industrial applications. The experiment was conducted in four key steps: identifying gas species using optical emission spectroscopy (OES), calibrating RGA with a quadrupole mass spectrometer (QMS), constructing a five-point calibration graph to correlate RGA and Fourier-transform infrared spectroscopy (FT-IR) data, and estimating the concentration of unknown samples using the calibration graph. The results under plasma-on conditions demonstrated correlation and accuracy, confirming the reliability of our approach. In other words, the method effectively captured the relationship between RGA intensity and gas concentration, providing valuable insights into concentration trends. Thus, our approach serves as a useful tool for estimating gas concentrations and understanding the correlation between RGA intensity and gas composition. Full article

Blow flies (Diptera: Calliphoridae) play a crucial role in the decomposition process and serve as important forensic indicators due to their predictable colonization patterns. This review focuses on the dynamics of maggot masses, highlighting their ecological roles, thermoregulation, and implications for forensics. We summarize data on the self-organizing behavior of maggot masses, which is influenced by chemical cues and environmental factors. These masses can generate internal temperatures that exceed ambient levels by 10–20 °C, accelerating larval growth and impacting competition among individuals. This localized heating complicates the estimation of the postmortem interval (PMI), as traditional models may not take these thermal influences into account. Furthermore, maggot masses contribute significantly to nutrient cycling and soil enrichment, while the behavior of the larvae includes both cooperation and competition, which is influenced by the species composition present. This review highlights challenges in PMI estimation due to heat production but also discusses advancements in molecular tools and thermal modeling that enhance accuracy. Ultimately, we identify knowledge gaps regarding species diversity, microbial interactions, and environmental variability that impact mass dynamics, suggesting future research avenues that could enhance ecological understanding and forensic applications. Full article

It is just as important to produce high-quality drinking water as it is to distribute it throughout the water supply system without compromising chemical or microbiological quality. Therefore, it is essential to study the migration of substances in contact with water to assess potential chemical contamination under the conditions usually found in distribution systems, which is critical for potential toxicity studies. This initial characterization of the material allows for the assessment of its suitability for contact with drinking water. The rubber material used in the water supply system was selected and subjected to migration tests for 29 days using demineralized water. The potential organic contaminants from migration waters were extracted using liquid–liquid extraction (LLE) and quantified using gas chromatography–mass spectrometry (GC-MS). More than 50 organic compounds were quantified in migration waters. Most of the organic compounds were considered unexpected substances. Benzothiazole, 2-benzothiazole, and 2-mercaptobenzothiazole were dominant compounds. The unknowns showed a lower estimated concentration at the consumer tap (C_Tap) than the maximum tolerable concentration at the tap (MTC_Tap), and their sum was less than 5.0 µg/L. The studied rubber material is suitable for use in the water distribution system, as it satisfies the criteria of the migration tests. Full article

Finite element (FE) models are widely used in structural health monitoring to represent real structures and assess their condition, but discrepancies often arise between numerical and actual structural behavior due to simplifying assumptions, uncertain parameters, and environmental influences. Temperature variation, in particular, significantly affects structural stiffness and modal properties, yet it is often treated as noise in traditional model updating methods. This study treats temperature changes as valuable information for model updating and structural damage quantification. The Bayesian model updating approach (BMUA) is a probabilistic approach that updates uncertain model parameters by combining prior knowledge with measured data to estimate their posterior probability distributions. However, traditional BMUA methods assume mass is known and only update stiffness. A novel BMUA framework is proposed that incorporates thermal buckling and temperature-dependent stiffness estimation and introduces an algorithm to eliminate the coupling effect between mass and stiffness by using temperature-induced stiffness changes. This enables the simultaneous updating of both parameters. The framework is validated through numerical simulations on a three-story aluminum shear frame under uniform and non-uniform temperature distributions. Under healthy and uniform temperature conditions, stiffness parameters were estimated with high accuracy, with errors below 0.5% and within uncertainty bounds, while mass parameters exhibited errors up to 13.8% that exceeded their extremely low standard deviations, indicating potential model bias. Under non-uniform temperature distributions, accuracy declined, particularly for localized damage cases, with significant deviations in both parameters. Full article

The first comprehensive mass balance estimation for the world’s largest tropical icefield is presented. Geodetical mass balance was calculated using photogrammetry from aerial and satellite images spanning from 1955 to 2024. The results meet expected quality standards using some new satellite sources, such as the Peruvian PeruSAT-1, although the quality of airborne imagery is consistently lower than that of satellite sources. The Nevado Coropuna icefield remained almost stable between 1955 and 1986 with −0.04 m dh yr⁻¹. Since then, it has undergone a sustained and accelerated negative mass balance, reaching a maximum annual dh yr⁻¹ of −0.73 ± 0.19 in the 2020–2023 timeframe. The glacier loss is not equal across the entire ice mass, but more acute in the northern and northeastern outlet tongues. Debris-covered ice and rock glaciers show a much weaker negative mass balance signal. The impact of ENSO events is not evident in the overall ice evolution, although their long-term relevance is acknowledged. Overall, the negative response of Nevado Coropuna to global warming (−0.36 ± 0.12 m.w.e. yr⁻¹ for the 2013 to 2024 period) is less pronounced than that of other Peruvian glaciers, but more severe than that reported for the nearby Dry Andes of Chile and Argentina. Full article

The size and mass of fish are crucial parameters in aquaculture management. However, existing research primarily focuses on conducting fish size and mass estimation under ideal conditions, which limits its application in actual aquaculture scenarios with complex water quality and fluctuating lighting. A non-contact size and mass measurement framework is proposed for complex underwater environments, which integrates the improved FishKP-YOLOv11 module based on YOLOv11, stereo vision technology, and a Random Forest model. This framework fuses the detected 2D key points with binocular stereo technology to reconstruct the 3D key point coordinates. Fish size is computed based on these 3D key points, and a Random Forest model establishes a mapping relationship between size and mass. For validating the performance of the framework, a self-constructed grass carp dataset for key point detection is established. The experimental results indicate that the mean average precision (mAP) of FishKP-YOLOv11 surpasses that of diverse versions of YOLOv5–YOLOv12. The mean absolute errors (MAEs) for length and width estimations are 0.35 cm and 0.10 cm, respectively. The MAE for mass estimations is 2.7 g. Therefore, the proposed framework is well suited for application in actual breeding environments. Full article

Background/Objectives: Sarcopenia, characterized by progressive loss of skeletal muscle mass and strength, significantly impacts physical function and quality of life in older adults. Traditional measurement methods like Dual-energy X-ray absorptiometry (DEXA) are often inaccessible in primary care. This study aimed to develop and validate an AI-driven auto-segmentation model for muscle mass assessment using long X-rays as a more accessible alternative to DEXA. Methods: This was a retrospective validation study using data from the Real Hip Cohort at Inha University Hospital in South Korea. 351 lower extremity X-ray images from 157 patients were collected and analyzed. AI-based semantic segmentation models, including U-Net, V-Net, and U-Net++, were trained and validated on this dataset to automatically segment muscle regions. Model performance was assessed using Intersection over Union (IoU) and Dice Similarity Coefficient (DC) metrics. The correlation between AI-derived muscle measurements and the DEXA-derived skeletal muscle index was evaluated using Pearson correlation analysis and Bland–Altman analysis. Results: The study analyzed data from 157 patients (mean age 77.1 years). The U-Net++ architecture achieved the best segmentation performance with an IoU of 0.93 and DC of 0.95. Pearson correlation demonstrated a moderate to strong positive correlation between the AI model’s muscle estimates and DEXA results (r = 0.72, *** p < 0.0001). Regression analysis showed a coefficient of 0.74, indicating good agreement with reference measurements. Conclusions: This study successfully developed and validated an AI-driven auto-segmentation model for estimating muscle mass from long X-rays. The model provides an accessible alternative to DEXA, with potential to improve sarcopenia diagnosis and management in community and primary care settings. Future work will refine the model and explore its application to additional muscle groups. Full article

Gellan gum (Gellan), a versatile polysaccharide applied in gel formation and prebiotic formulations, is often processed to tailor its molecular properties. Previous studies employed gamma irradiation and chemical hydrolysis, though without addressing systematic scaling behavior. This study investigates the structural and conformational modifications of Gellan in dilute aqueous salt solutions using a safer and eco-friendly approach: atmospheric low-dose electron beam (e-beam) degradation coupled with viscosity analysis. Native and E-beam-treated Gellan samples (0.05 g/cm³ in 0.1 M KCl) were examined by relative viscosity at varying temperatures, with intrinsic viscosity and molar mass determined via Solomon–Ciuta and Mark–Houwink relations. Molar mass degradation followed first-order kinetics, yielding rate constants and degradation lifetimes. Structural parameters, including radius of gyration and second virial coefficient, produced scaling coefficients of 0.62 and 0.15, consistent with perturbed coil conformations in a good solvent. The shape factor confirmed preservation of an ideal random coil structure despite irradiation. Conformational flexibility was further analyzed using theoretical models. Transition state theory (TST) revealed that e-beam radiation lowered molar mass and activation energy but raised activation entropy, implying reduced flexibility alongside enhanced solvent interactions. The freely rotating chain (FRC) model estimated end-to-end distance (R_θ) and characteristic ratio (C_∞), while the worm-like chain (WLC) model quantified persistence length (l_p). Results indicated decreased R_θ, increased l_p, and largely unchanged C_∞, suggesting diminished chain flexibility without significant deviation from ideal coil behavior. Overall, this work provides new insights into Gellan’s scaling laws and flexibility under aerobic low-dose E-beam irradiation, with relevance for bioactive polysaccharide applications. Full article