Search Results (2,091)

Background/Objectives: Differential diagnosis between Crohn’s disease (CD) and ulcerative colitis (UC) can be sometimes difficult resulting in the diagnosis of unspecified inflammatory bowel diseases (IBD-U). Data suggest that IgG antibodies against integrin αvβ6 (V6 Ab) help to identify UC patients. Recent studies suggest that measuring V6 Ab serum levels may be valuable for differential diagnostic purposes. The primary objective of the study was to assess the sensitivity and specificity of V6 Ab serum-level measurement in our IBD population to differentiate between colonic/ileocolonic CD and UC with an established diagnosis. Furthermore, we assessed the correlation between disease characteristics, activity and V6 Ab serum levels in UC patients. Methods: Consecutive IBD patients with an established diagnosis undergoing control colonoscopy in a tertiary IBD center were included. Baseline demographic data, current treatment, disease extent, clinical, biomarker, endoscopic and histologic disease activity were collected. V6 Ab serum levels were measured with the Anti-Integrin αvβ6 ELISA Kit (RUO). Patients’ written informed consent was obtained. Results: A total of 40 IBD patients, including 10 CD and 30 UC patients (15 with clinical activity and 15 in clinical remission) were enrolled. V6 Ab serum levels were significantly higher in UC patients compared to CD (p = 0.039). ROC analysis found 1.33 U/mL to be the best cut-off level (p = 0.04; AUC: 0.71) with 100% sensitivity and 50% specificity and a positive predictive value of 85.7% and a negative predictive value of 100% to differentiate between UC and CD. No significant correlation was found between V6 Ab serum levels and CRP (p = 0.057), fecal calprotectin (p = 0.77), endoscopic activity (p = 0.624) or disease extent (p = 0.624) in UC patients. Conclusions: Our study supports the value of V6 Ab serum level measurement as a differential diagnostic tool in IBD patients; however, the optimal cut-off value is yet to be determined. Our data do not support its role in disease activity monitoring. Full article

With the progress of global aging, osteoporosis, as a systemic bone disease, has become an increasingly serious public health problem. Osteoporosis has an insidious onset, and the fractures it causes have a high rate of disability and mortality. Early diagnosis and intervention of the disease are particularly important. Currently, diagnostic methods for osteoporosis, such as dual-energy X-ray absorptiometry (DXA), quantitative computed tomography (QCT), and bone turnover markers (BTM), all have their limitations. miRNA is a type of non-coding RNA that plays a role in the epigenetic regulation of gene expression. A large number of studies have shown that miRNA is involved in the formation and functional execution of osteoblasts. The differential expression of miRNA levels can effectively distinguish osteoporosis patients from normal individuals, and miRNA detection has the advantages of simple sample collection, non-invasive measurement, specificity for bone metabolism, correct correlation with standard techniques for bone remodeling analysis, and the ability to respond to the treatment of diseases affecting bone metabolism. This makes miRNAs potentially effective diagnostic markers for osteoporosis. This article aims to summarize our current understanding of miRNA regulation of osteoblast generation and function, and we will also discuss the potential value of these miRNAs as biomarkers for the diagnosis of osteoporosis. Full article

As a vital ecological security barrier and climate regulator in northwestern China, the spatial patterns and evolving formation mechanisms of ecosystem services within the Qinghai Lake basin hold significant strategic value for ecological conservation and national park development in the region. This study selected land use data during 2000–2020, integrating the equivalent factor method, spatial correlation analysis, and the geodetector approach to systematically investigate the spatial heterogeneity characteristics of ESV in the Qinghai Lake basin and its corresponding driving mechanisms. The results indicate the following: (1) During the period 2000–2020, grassland consistently constituted the primary land cover category within the Qinghai Lake Basin, accounting for over 60% of the total area; water bodies (16.67%) and unused land (16.56%) represented the secondary land use categories. Over this twenty-year period, the total ESV exhibited a slight increasing trend, rising from USD 30.30 × 10⁸ to USD 30.75 × 10⁸, representing a growth of 0.31%. Regulating services constituted the primary component of ESV. The highest contribution to ESV originated from water bodies, with grassland ranking second. (2) ESV displayed a spatial arrangement marked by “high values in the lake center and low values in the surrounding areas” and “higher values in the southeast and lower values in the northwest.” Its spatial correlation exhibits a pronounced positive relationship. The number of units classified as high-high clusters (primarily water bodies at low elevations) and low-low clusters (mainly grasslands and unused land at high elevations) both increased over the study period, indicating a continuous intensification of ESV spatial agglomeration. (3) Results from the geographical detector reveal that both natural and anthropogenic factors collectively drive the spatial variation in ESV, with natural factors exhibiting stronger explanatory capacity. Among these, elevation and temperature are identified as the dominant drivers of ESV spatiotemporal differentiation. The combined effect of two interacting factors surpasses the influence exerted by any single factor in isolation. This research clarifies that the spatial distribution of ESV in the Qinghai Lake Basin, which features “high values in the lake center and low values in the surrounding areas” as well as “higher values in the southeast and lower values in the northwest,” is jointly shaped by the combined control of vertical zonality governed by topographic and climatic factors and the spatial differentiation of human activities. In low-altitude lakeshore zones, ESV rose as a consequence of water body expansion and the enforcement of ecological conservation measures, leading to the emergence of high-value clusters. In contrast, ESV improvement in high-elevation regions remained limited, constrained by fragile natural conditions and minimal human intervention. The insights derived from this research offer a scientific foundation for refining the “one core, four zones, one ring, multiple points” functional zoning framework of the Qinghai Lake National Park, as well as for developing tailored management approaches suited to distinct elevation-based regions. Full article

Shape-stabilized phase change materials (SSPCMs) have been a promising thermal energy storage (TES) solution to combine the high energy density of solid-to-liquid (SL) PCMs and the structural stability of solid–solid PCMs. Although polymeric matrices have been used for their reduced cost and ease of processability, few have evaluated the use of crosslinked natural rubber (NR). In this study, we evaluate by differential scanning calorimetry (DSC) the preparation of room-temperature tailorable SSCPMs by the design of NR matrices with different crosslink density vulcanized by dicumyl peroxide (DCP) or sulphur, with special focus on the quantification of the content of PCM. The results indicate that the amount of PCM stable in the NR matrix is low, with PCM contents between 16 and 24% and enthalpies between 16 and 20 J·g⁻¹. Likewise, it is well-known that thermophysical properties of the PCMs vary upon confinement in a small-scale porous matrix. The confinement of the PCM in the rubber network results in a measured enthalpy below the expected value, and a melting point depression of up to 23.6 °C, dependent on crosslink density. These results highlight the structural complexity of NR-PCM composites and the need for further investigation. Full article

Accurate characterization of ore grindability is essential for optimizing mill throughput, reducing energy consumption, and predicting mill performance under varying ore conditions. However, the standard Bond work index (BWI) test remains time-consuming, costly, and requires a large amount of sample. This study evaluates the effectiveness of several rapid, low-cost alternatives, Leeb rebound hardness (LRH), Cerchar abrasivity Index (CAI), portable X-ray fluorescence (pXRF), and hyperspectral imaging (HSI), as proxies for grindability in gold-bearing ores. Sixty-two hand-size rock samples collected from two adjacent Canadian open-pit mines were analyzed using these techniques and subsequently grouped into ten ore groups for BWI testing. LRH and CAI effectively differentiated moderate (<15 kWh/t) from hard (>15 kWh/t) grindability classes, while geochemical features and HSI-based mineralogical attributes also showed strong predictive capability. HSI, in particular, provided non-destructive, spatially continuous data that are advantageous for complex geology and large-scale operational deployment. A conceptual workflow integrating HSI with complementary field measurements is proposed to support comminution planning and optimization, enabling more responsive and timely decision-making. While BWI testing remains necessary for circuit design, the results highlight the value of combining rapid proxy measurements with advanced analytics to enhance geometallurgical modelling, reduce operational risk, and improve overall mine-to-mill performance. Full article

Accurate quantification of forest aboveground biomass (AGB) is essential for monitoring terrestrial carbon stocks. While total AGB estimation is widely practiced, resolving component biomass such as canopy, branches, leaves, and trunks enhances the precision of carbon sink assessments and provides critical structural parameters for ecosystem modeling. Most studies rely on a single SAR sensor or a limited range of SAR features, which restricts their ability to represent vegetation structural complexity and reduces biomass estimation accuracy. Here, we propose a phased fusion strategy that integrates backscatter intensity, interferometric coherence, texture measures, and polarimetric decomposition parameters derived from dual-frequency ALOS-2, GF-3, and Sentinel-1A SAR data. These complementary multi-dimensional SAR features are incorporated into a Random Forest model optimized using an Adaptive Genetic Algorithm (RF-AGA) to estimate forest total and component estimation. The results show that the progressive incorporation of coherence and texture features markedly improved model performance, increasing the accuracy of total AGB to R² = 0.88 and canopy biomass to R² = 0.78 under leave-one-out cross-validation. Feature contribution analysis indicates strong complementarity among SAR parameters. Polarimetric decomposition yielded the largest overall contribution, while L-band volume scattering was the primary driver of trunk and canopy estimation. Coherence-enhanced trunk prediction increased R² by 13 percent, and texture improved canopy representation by capturing structural heterogeneity and reducing saturation effects. This study confirms that integrating coherence and texture information within the RF-AGA framework enhances AGB estimation, and that the differential contributions of multi-dimensional SAR parameters across total and component biomass estimation originate from their distinct structural characteristics. The proposed framework provides a robust foundation for regional carbon monitoring and highlights the value of integrating complementary SAR features with ensemble learning to achieve high-precision forest carbon assessment. Full article

To address the thermal management challenges in electronic devices, this study systematically investigates the effects of injection molding and compression molding on the microstructure and thermal conductivity of poly(vinylidene fluoride)/boron nitride nanosheet (PVDF/BNNs) composites. Using 10 μm diameter BNNs as thermal conductive fillers and PVDF as the matrix, the composites were characterized via scanning electron microscopy (SEM), thermal conductivity measurements, rheological analysis, X-ray diffraction (XRD), and mechanical tests. The results demonstrate that the strong shear stress in injection molding induces significant alignment of BNNs along the flow direction, leading to remarkable thermal conductivity anisotropy. At a PVDF/BNNs mass ratio of 90/10, the in-plane thermal conductivity of the injection-molded composite reaches 1.26 W/(m·K), while the through-plane conductivity is only 0.40 W/(m·K). In contrast, compression molding, which involves minimal shear, results in randomly dispersed BNNs and isotropic thermal conductivity, with both in-plane and through-plane values around 0.41 W/(m·K) at the same filler loading. Both processing methods preserve the coexistence of α- and β-crystalline phases in PVDF. However, injection molding enhances matrix crystallinity through stress-induced crystallization, yielding composites with higher density and superior tensile properties. Compression molding, due to slower cooling, leads to incomplete PVDF crystallization, as evidenced by a shoulder peak near 164 °C in differential scanning calorimetry (DSC) curves. This study elucidates the mechanism by which processing methods regulate the structure and properties of PVDF/BNNs composites, offering theoretical and practical guidance for designing high-performance thermally conductive materials. Full article

Background: Diagnosis is the fundamental basis for understanding biomechanics in orthodontic treatment and for accurately designing the treatment plan. Traditionally, the sagittal plane has been the primary focus of assessment; however, it is essential to consider the patient in all three spatial planes. Therefore, it is necessary to explore the transverse plane, which is equally as crucial as the sagittal and vertical planes. With current technological advances, it is now possible to obtain three-dimensional images of the patient using cone-beam computed tomography (CBCT), allowing evaluation of all planes in a single diagnostic test. This study aimed to assess the diagnostic methods used for transverse analysis and the usefulness of CBCT for this purpose. Material and Methods: To select the studies for this review, we searched the PubMed, Scopus, and Cochrane databases for publications between 1965 and 2021. Our inclusion criteria targeted studies that evaluated the transverse plane using CBCT or CT. We assessed the level of evidence according to the OCEBM classification and evaluated the risk of bias using the QUADAS-2 scale. Results: After reviewing 535 articles, we selected 16 that met the established criteria. These studies compared various diagnostic methods for transverse analysis and their reproducibility indices. We identified the absence of a gold standard for measuring transverse discrepancies and high variability among diagnostic methods as the main limitations. Conclusions: Based on the available evidence, it can be concluded that dental and skeletal transverse discrepancies can be reliably differentiated using the diagnostic techniques evaluated in this study, particularly through CBCT-based assessment. Therefore, the diagnosis of transverse discrepancies should not be considered unclear, as it can be established using objective and measurable criteria. These findings reinforce the clinical value of current diagnostic tools and highlight the importance of accurate three-dimensional interpretation for informed and effective treatment decision-making. Full article

Background/Objectives: The triglyceride-to-High-density lipoprotein cholesterol (TG/HDL) ratio is an established marker of atherogenic dyslipidaemia and insulin resistance. Although its association with subclinical atherosclerosis has been reported, the relative contributions of long-term TG/HDL burden and visit-to-visit variability to carotid intima media thickness (CIMT) remain unclear. This study aimed to evaluate the differential associations of the longitudinal mean and temporal variability of the TG/HDL ratio with CIMT. Methods: This retrospective single-center observational cohort study included 260 adult patients with at least three years of longitudinal lipid measurements and a standardized carotid ultrasonography assessment. The longitudinal mean TG/HDL ratio and variability indices, including standard deviation, coefficient of variation, average real variability and variability independent of the mean, were calculated. CIMT was measured using B-mode ultrasonography. Associations were assessed using correlation analyses, multivariable linear regression, joint category analyses and stratified analyses according to statin therapy. Results: The longitudinal mean TG/HDL ratio was independently associated with increased CIMT after adjustment for traditional cardiovascular risk factors. In contrast, TG/HDL variability indices showed no independent association with CIMT and did not improve model performance beyond the mean TG/HDL ratio. Restricted cubic spline analysis demonstrated a significant non-linear association between TG/HDL mean and CIMT, suggesting a threshold-dependent relationship. Joint category analyses demonstrated higher CIMT values in groups with elevated TG/HDL mean regardless of variability status. A significant interaction was observed between TG/HDL variability and statin therapy (p for interaction = 0.011). Conclusions: These findings indicate that cumulative exposure to atherogenic dyslipidaemia, reflected by the long-term mean TG/HDL ratio, is more strongly associated with subclinical carotid atherosclerosis than short-term lipid fluctuations. Full article

The present study analyses the changes in antioxidative behavior of biodegradable Poly(lactic acid) (PLA)-based composite films with bioactive additives derived from pomegranate peel, an abundant agricultural by-product rich in antioxidants and antimicrobials. PLA-based composites were prepared by incorporating industrial-grade pomegranate peel powder (PoP) via melt extrusion at concentrations of 1–5 percent by weight (wt.%). For mechanical characterization, the resulting films were subjected to tensile testing. Their thermal properties were further characterized using thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), dynamic oxidation induction temperature measurements (OIT), complemented by Fourier-transform infrared spectroscopy (FT-IR), color analysis, rheology, scanning electron microscopy (SEM), and UV-Vis spectroscopy. Results show that the incorporation of PoP had no significant impact on the characteristic transition temperatures (Tg, Tm, and Tc) of PLA, indicating that the thermal behavior of the polymer matrix was largely preserved. However, while the thermo-oxidative stability of PLA was improved in the presence of PoP, with a maximum at 3 wt.% of PoP, increasing the OIT by 30 °C, the mechanical performance of the composite films was adversely affected, as evidenced by decreased tensile strength and elongation at break indication embrittlement, especially for ≥3 wt.% of PoP. Significant changes were observed in the films’ surface properties, as well as in their color parameters and UV transmittance values. Consequently, while PoP offers potential bioactive functionality for use as a sustainable additive, its content must be carefully optimized to maintain an acceptable balance between functionality and mechanical integrity. Full article

Background: Even though there have been improvements in antimicrobial and supportive therapies, sepsis and septic shock are still major causes of death in intensive care units. Early prognostic stratification is very important for helping doctors make decisions. Platelet-derived indices may provide useful, low-cost indicators that signify both inflammatory activation and coagulation irregularities. This study looked at how well different platelet-based ratios could predict death in the hospital from sepsis. Materials and Methods: We performed a prospective observational study spanning one year in a tertiary ICU, enrolling 114 adult patients diagnosed with sepsis or septic shock. Upon admission, four platelet-related biomarkers were measured: the C-reactive protein-to-platelet ratio (CPR), the platelet-to-lymphocyte ratio (PLR), the platelet-to-white blood cell ratio (PWR), and the platelet-to-creatinine ratio (PCR). Logistic regression models and receiver operating characteristic (ROC) analyses were employed to assess predictive accuracy. Results: Compared to survivors, non-survivors (n = 39) had much higher CRP levels and CPR values, alongside lower platelet and lymphocyte counts. The CPR index showed the best ability in differentiating between non-survivors and survivors (AUC 0.757), with a best cutoff of 0.886. In simplified multivariate models, CPR was still an independent predictor of death in the hospital (OR 1.98; 95% CI 1.22–3.21), whereas PLR and PWR were not. PCR showed a non-significant trend toward lower values in not survivors. Conclusions: CPR is a strong and clinically viable predictor of early mortality in sepsis, outperforming other platelet-based indices. Derived from routine laboratory parameters, CPR serves as a valuable adjunct for initial risk stratification in the ICU. To further confirm its prognostic role and incorporation into current scoring systems, large-scale multicenter studies with longitudinal measurements are warranted to validate its prognostic utility and integration into existing scoring systems. Full article

This study investigates the different mechanisms through which environmental disclosure and green accounting practices influence investment attractiveness in an emerging market context. Drawing on legitimacy theory and the resource-based view, we examine whether these environmental accountability mechanisms create value directly or through enhanced sustainability performance. Using survey data from 290 non-financial firms listed on the Saudi Stock Exchange, we employ partial least squares structural equation modeling to test a mediated-moderation model within the Saudi Vision 2030 framework. The results reveal differentiated value-creation pathways: environmental disclosure affects investment attractiveness indirectly through sustainable economic outcomes (full mediation; indirect effect β = 0.121, p < 0.001), while green accounting demonstrates both direct (β = 0.237, p < 0.001) and indirect effects (β = 0.091, p < 0.01), indicating partial mediation. Both practices are positively associated with sustainable economic outcomes (β_ED = 0.290, β_GA = 0.219, p < 0.001), which in turn are positively related to investment attractiveness (β = 0.416, p < 0.001). Unexpectedly, Vision 2030 alignment shows no significant moderating effect (β = 0.042, p = 0.498), suggesting that the sustainability–investment relationship is not significantly conditioned by perceived alignment with the national strategic framework in this sample. The model explains 25.7% of the variance in investment attractiveness and 20.0% of that in sustainable economic outcomes, indicating moderate explanatory power. These findings contribute to the environmental accounting literature by suggesting that internal management-oriented practices may be more closely associated with investment attractiveness than disclosure transparency alone. Overall, the results indicate that green accounting systems are associated with investment attractiveness, while environmental disclosure appears to require observable sustainability performance to be reflected in investment perceptions, offering measured implications for corporate strategy and regulatory policy in sustainability transitions. Full article

Piglets weaning is a critical developmental stage marked by significant metabolic and inflammatory challenges. The hepatic responses during this period may differ among pig breeds with distinct genetic backgrounds. To explore the phenotypic and molecular differences in the livers between the Zaozhuang Heigai (HG) pig and Duroc×Landrace×Yorkshire (DLY) piglets and elucidate the regulatory mechanisms of genetic background on liver function, five 35-day-old piglets from each breed were selected. Body weight and liver coefficients were measured; histological features of liver sections were observed, and the transcriptome and metabolome of the liver were determined using mRNA sequencing and non-targeted metabolomics analysis. The results showed that HG piglets had significantly lower body weight (p < 0.01) and slightly higher liver coefficients than DLY piglets. Histological examination revealed that the hepatic lobule structure was intact in both breeds, while mild hepatic congestion was observed in some DLY piglets. Transcriptome analysis identified 429 differentially expressed genes (DEGs) with criteria of FDR adjusted p-values < 0.01 and |log₂(Fold Change)| > 1, and they were significantly enriched in oxidoreductase activity, peroxisome proliferator-activated receptor (PPAR) signaling, and arachidonic acid metabolism pathways. Metabolome analysis identified 169 differentially expressed metabolites (DEMs) with criteria of p < 0.05, VIP > 1, and |log₂(Fold Change)| > 1, and they were significantly enriched in nucleotide metabolism, arginine biosynthesis, and arachidonic acid metabolism pathways. Integrative analysis of DEGs and DEMs showed that arachidonic acid metabolism was the common pathway. Within this pathway, key genes (GPX3, ALOX5, and CBR3) were significantly associated with specific metabolites (15-deoxy-PGJ₂ and phosphatidylcholines) (FDR adjusted p < 0.05), suggesting a gene–metabolite interaction network that coordinates inflammatory regulation and oxidative stress. These findings provide molecular evidence for breed-specific hepatic metabolic regulation during the weaning period and are therefore conducive to the management of weaned piglets and the investigation of local pig characteristics. Full article

Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique that utilizes magnetic fields to induce cortical electric currents, enabling both the measurement and modulation of neuronal activity. Initially developed as a diagnostic tool, TMS now serves dual roles in clinical neurology, offering insight into neurophysiological dysfunctions and the therapeutic modulation of abnormal cortical excitability. This review examines key TMS outcome measures, including motor thresholds (MT), input–output (I/O) curves, cortical silent periods (CSP), and paired-pulse paradigms such as short-interval intracortical inhibition (SICI), short-interval intracortical facilitation (SICF), intracortical facilitation (ICF), long interval cortical inhibition (LICI), interhemispheric inhibition (IHI), and short-latency afferent inhibition (SAI). These biomarkers reflect underlying neurotransmitter systems and can aid in differentiating neurological conditions. Diagnostic applications of TMS are explored in Parkinson’s disease (PD), dystonia, essential tremor (ET), Alzheimer’s disease (AD), and mild cognitive impairment (MCI). Each condition displays characteristic neurophysiological profiles, highlighting the potential for TMS-derived biomarkers in early or differential diagnosis. Therapeutically, repetitive TMS (rTMS) has shown promise in modulating cortical circuits and improving motor and cognitive symptoms. High- and low-frequency stimulation protocols have demonstrated efficacy in PD, dystonia, ET, AD, and MCI, targeting the specific cortical regions implicated in each disorder. Moreover, the successful application of TMS in differentiating and treating AD and MCI underscores its clinical utility and translational potential across all neurodegenerative conditions. As research advances, increased attention and investment in TMS could facilitate similar diagnostic and therapeutic breakthroughs for other neurological disorders that currently lack robust tools for early detection and effective intervention. Moreover, this review also aims to underscore the importance of maintaining standardized TMS protocols. By highlighting inconsistencies and variability in outcomes across studies, we emphasize that careful methodological design is critical for ensuring the reproducibility, comparability, and reliable interpretation of TMS findings. In summary, this review emphasizes the value of TMS as a distinctive, non-invasive approach to probing brain function and highlights its considerable promise as both a diagnostic and therapeutic modality in neurology—roles that are often considered separately. Full article

This study addresses the ongoing challenge of accurately classifying beers by fermentation type and product category, an issue of growing importance for quality control, authenticity assessment, and product differentiation in the brewing sector. We applied a multiblock chemometric framework that integrates phenolic profiling obtained via GC–MS, antioxidant and antiradical activity derived from in vitro assays, and complementary colorimetric and physicochemical measurements. Principal Component Analysis (PCA) revealed clear compositional structuring within the dataset, with p-coumaric, gallic, syringic, and malic acids emerging as major contributors to variance. Supervised machine-learning classification demonstrated robust performance, achieving approximately 93% accuracy in discriminating top- from bottom-fermented beers, supported by a well-balanced confusion matrix (25 classified and 2 misclassified samples per group). When applied to ale–lager categorization, the model retained strong predictive ability, reaching 90% accuracy, largely driven by the C* chroma value and the concentrations of tyrosol, acetic acid, homovanillic acid, and syringic acid. The integration of multiple analytical blocks significantly enhanced class separation and minimized ambiguity between beer categories. Overall, these findings underscore the value of multi-block chemometrics as a powerful strategy for beer characterization, supporting brewers, researchers, and regulatory bodies in developing more reliable quality-assurance frameworks. Full article