Search Results (105)

Background/Objectives: Gastrointestinal bleeding (GIB) in hemodialysis (HD) patients carries substantial mortality risk. The A4C and CHAMPS scores are novel risk stratification tools, while CAGIB was developed for cirrhosis-associated GIB. We compared the discriminative performance of these scores in HD patients with acute GIB, stratified by variceal and non-variceal etiology. Methods: We conducted a retrospective cohort study of 57 HD patients with acute GIB (January 2020–December 2024) following STROBE and TRIPOD guidelines. Patients were stratified as non-variceal (n = 42) or variceal (n = 15). The primary outcome was 30-day mortality; secondary outcomes included ICU admission, rebleeding, and transfusion requirements. A4C, CHAMPS, CAGIB, ABC, AIMS65, and Glasgow–Blatchford scores were compared using AUROC analysis. Results: Mean age was 45.8 ± 13.2 years. Non-variceal GIB (73.7%) was predominantly caused by angiodysplasia (28.6%) and peptic ulcer disease (23.8%); variceal GIB (26.3%) was mainly from esophageal varices (80.0%). Overall 30-day mortality was 17.5%, significantly higher in variceal (26.7%) versus non-variceal GIB (14.3%, p = 0.048). For non-variceal GIB, CHAMPS demonstrated excellent mortality discrimination (AUROC 0.91), significantly outperforming CAGIB (AUROC 0.68, p = 0.02). Conversely, for variceal GIB, CAGIB showed superior performance (AUROC 0.89) compared to CHAMPS (AUROC 0.72, p = 0.04). A4C performed consistently for transfusion prediction across both groups (AUROC 0.75–0.78). Conclusions: Optimal risk stratification in HD patients with GIB requires etiology-specific scoring: CHAMPS for non-variceal and CAGIB for variceal bleeding. This complementary performance reflects distinct pathophysiological mechanisms underlying mortality. Prospective validation in larger multicenter cohorts is warranted. Full article

Recognizable and distinctive streets are essential not only for navigation but also for fostering place identity and therefore socio-environmental sustainability in cities. The recognition depends on both high-level visual features (e.g., buildings, trees, etc.) and low-level ones (e.g., colors, spatial frequencies, etc.). While the former has been examined extensively, the latter remains less understood. This study addresses this gap via a multi-disciplinary perspective, by exploring how low-level visual features influence attention and cognitive processing during street recognition using an eye-tracking device. In the experiment, participants were expected to recognize Huaihai Road in China from other historic, tree-shaded, commercial streets with similar appearance (e.g., the Champs-Élysées in France, Omotesando in Japan, and Shaanxi South Road and Fuxing Middle Road in China). Results showed that removing mid-to-high spatial frequencies significantly improved recognition accuracy, while the absence of color led to a notable decline in accuracy. Markedly, the presence or absence of trees did not significantly affect recognition accuracy, suggesting that trees may be not vital for street recognition. These findings underscore the importance of global visual cues and color in the recognition process and provide practical computational design insights for urban distinctiveness and cultural sustainability. Full article

As an underutilized industrial byproduct generated during bioactive compound extraction from Millettia speciosa Champ. seeds, the residual protein fraction represents a promising sustainable resource for valorization. Millettia speciosa Champ. seed protein (MP) was extracted, and its fundamental physicochemical and functional properties were evaluated for potential applications in the food industry. Structural characterization revealed that MP had a molecular weight distribution with major components at 14.0 kDa and 116.0 kDa, with respective denaturation temperatures of 79.75 °C and 91.77 °C. The main structure of MP included different proportions of intramolecular α-helices and random coils in different pH microenvironments, based on circular dichroism spectroscopy. The MP displayed similar solubility profiles to the soy protein isolate (SP), but with lower solubility at slightly acidic pH, low solubility at pH 5.0, and comparable solubility above pH 8.0. Functional assessments showed that MP possessed emulsifying, foaming, water-binding, and fat-absorption capacities comparable to those of SPI, although the in vitro digestibility was relatively lower. These findings indicate that MP may serve as a safe and nutritious functional ingredient for health-oriented food products. Full article

Cardiometabolic phenotypes such as obesity and impaired insulin action are key determinants of type 2 diabetes (T2D). Growing evidence highlights the postprandial state as a critical window in metabolic regulation, where epigenetic mechanisms, particularly DNA methylation in insulin-sensitive tissues, may play pivotal roles. However, their dynamics across prandial states in subcutaneous adipose tissue (SAT) remain unclear. We analyzed genome-wide DNA methylation in paired fasting and postprandial SAT biopsies from 29 asymptomatic, drug-naïve individuals classified as controls (n = 8), prediabetes n = 9), or T2D (n = 12). Postprandial samples followed a standardized mixed-meal test. DNA methylation was quantified using the Illumina MethylationEPIC array and analyzed through the Chip Analysis Methylation Pipeline (ChAMP) pipeline. Differential methylation was more pronounced postprandially, especially in the T2D group. After adjusting for age and sex, 4599 differentially methylated CpG sites (DMCs) were identified, with increased hypermethylation in T2D. A total of 130 DMCs across 99 genes, including LCLAT1, HLA-C, ZNF714, and HOOK2, were shared by prediabetes and T2D groups. Over-representation analysis revealed 202 enriched pathways related to insulin resistance, AMPK signaling, and immune responses. Additionally, 110 Differentially Methylated Regions (DMRs), including ZNF577 and AGPAT1, were detected. These findings reveal early, prandial-dependent epigenetic alterations in SAT that precede overt dysglycemia, offering insights into personalized prevention in T2D. Full article

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. In Mexico, its higher incidence and lower survival suggest a role for epigenetic factors like DNA methylation (DNAme). We conducted an epigenome-wide association study (EWAS) to define the methylation landscape and identify the profiles associated with ALL and relapse. Bone marrow or peripheral blood samples from pediatric ALL patients at diagnosis and controls without ALL were analyzed using an Infinium MethylationEPIC v2.0 array. Differential methylation was assessed using the ChAMP package. We identified a significant hypermethylated profile in ALL patients compared to controls. Probes in MAD1L1 and RPTOR contained the most differentially methylated CpG sites. Key affected pathways included proliferation, neurotransmission, and neuronal signaling. Survival analysis revealed that hypomethylation of four specific CpGs—cg01052776 (RNH1), cg20747787, cg05001671, and cg01767116 (FBXL22)—was significantly associated with an increased risk of relapse, highlighting their potential as prognostic biomarkers. This study underscores the importance of epigenetic mechanisms in pediatric ALL. Full article

This research examines Champing, a new niche tourism phenomenon, enjoyed by over 10,000 people, that until now has not been examined in academic literature. The study analyses how Champing markets itself and is perceived by users to evaluate its proposition and its possible categorization as a form of camping and staycation. The research also explores Champing’s potential to contribute to more authentic and experiential forms of tourism and a possible solution to the challenges of overtourism. A netnographic approach was adopted, combining content analysis from the Champing website with thematic analysis of over 142 ‘Champers’ reviews of their Champing experience. The website content and thematic analysis highlights how Champing is promoted through heritage narratives, minimalist facilities, and links to local cultural and natural attractions through three core themes: Peaceful, Explore, and Novel and New. Findings position Champing as a niche tourism product that extends the camping and staycation portfolio. Analysis highlights how Champing aligns with policy objectives of local economies and heritage and as an option to mitigate against overtourism and foster experiential travel. This paper provides the first empirical analysis of Champing and extends research on camping and staycations; and it demonstrates the value of Netnography to tourism practices research. Full article

Conventional thermospheric density models are limited in their ability to capture solar-geomagnetic coupling dynamics and lack probabilistic uncertainty estimates. We present MSIS-UN (NRLMSISE-00 with Uncertainty Quantification), an innovative framework integrating sparse principal component analysis (sPCA) with heteroscedastic neural networks. Our methodology leverages multi-satellite density measurements from the CHAMP, GRACE, and SWARM missions, coupled with MSIS-00-derived exospheric temperature (tinf) data. The technical approach features three key innovations: (1) spherical harmonic decomposition of T∞ using spatiotemporally orthogonal basis functions, (2) sPCA-based extraction of dominant modes from sparse orbital sampling data, and (3) neural network prediction of temporal coefficients with built-in uncertainty quantification. This integrated framework significantly enhances the temperature calculation module in MSIS-00 while providing probabilistic density estimates. Validation against SWARM-C measurements demonstrates superior performance, reducing mean absolute error (MAE) during quiet periods from MSIS-00’s 44.1% to 23.7%, with uncertainty bounds (1σ) achieving an MAE of 8.4%. The model’s dynamic confidence intervals enable rigorous probabilistic risk assessment for LEO satellite collision avoidance systems, representing a paradigm shift from deterministic to probabilistic modeling of thermospheric density. Full article

The Mass Ratio Hypothesis states that the growth dynamics of dominant species influence forest species diversity by regulating the niches of subordinate and transient species. However, this prediction has not yet been empirical confirmed in subtropical forests over long term. Using data from 1995 to 2017, we examined how dominant tree species regulate species evenness and richness by analyzing their height and diameter growth in three clear-cut forests (Castanopsis carlesii (Hemsl.) Hayata, Castanopsis fissa (Champ. ex Benth.) Rehder & E. H. Wilson, and Cunninghamia lanceolata (Lamb.) Hook. stands), combined with the mean value of species niche breadth (measures the diversity of resources a species utilizes) across the community, including separate analyzes for subordinate (persistently coexisting with dominants species) and transient species (temporarily occurring species). Our results showed that an increase in height and diameter growth of dominant species had a negative effect on niche breadth of subordinate species, which in turn reduced species evenness (p < 0.01) but showed no significant relationship with species richness (p ≥ 0.05). Growth dynamics of dominants had no significant influence on the niche breadth of transient species. The early-fast growing dominant C. lanceolata significantly restricted the niche breadth of subordinate species (1.16 ± 0.23), resulting in relatively low evenness (0.49 ± 0.11). Conversely, the late-fast growing dominant C. carlesii promoted niche expansion (6.62 ± 1.20), resulting in higher evenness (0.81 ± 0.02). C. fissa -dominated strands with intermediate growth increments, exhibited moderate species evenness. These findings provide long-term empirical support for the Mass Ratio Hypothesis by demonstrating that growths of dominant species modulate niche partitioning in subordinates and thereby shape species diversity in subtropical forest communities. Full article

The composition and structure of understory plants are crucial for forest ecosystem succession and stability. This study examined the impact of various Cunninghamia lanceolata mixed plantation patterns on understory biodiversity, aiming to provide a theoretical foundation for sustainable management. Six patterns were evaluated using sample plots at Guanshan Forest Farm in Jiangxi Province, China. Understory vegetation diversity, biomass, and soil properties—including total nitrogen, available nitrogen, total phosphorus, available phosphorus, total potassium, available potassium, soil organic matter, and pH—were quantitatively analyzed. Significant differences in diversity among the patterns were revealed. The ‘Cunninghamia lanceolata + Phoebe bournei (Hemsl.) Yen C. Yang + Schima superba Gardner & Champ’ mixed plantation exhibited the most pronounced enhancement of understory plant diversity, whereas the ‘C. lanceolata + Liquidambar formosana Hance’ pattern demonstrated the least significant effects among all treatments. Significant correlations were detected between soil nutrients and diversity indices. Mixed patterns enhance diversity through expanded ecological niches and optimized microenvironments, thereby strengthening ecological functions and management efficiency. Full article

Lower gastrointestinal bleeding (LGIB) is a frequent and potentially life-threatening clinical condition. Over the past two decades, several prognostic scoring systems have been developed to stratify risk and guide the management of patients with LGIB. This comprehensive review aims to summarize and compare the current evidence on the utility, accuracy, and limitations of key LGIB scoring systems, including the Glasgow-Blatchford Score (GBS), AIMS65, ABC score, Oakland score, SALGIB, CHAMPS, and Rockall score. We conducted a structured literature review of studies evaluating these scores in adult patients with LGIB. For each scoring system, we analyzed its origin, components, intended use, and predictive performance regarding clinical outcomes such as severe bleeding, transfusion requirement, in-hospital mortality, rebleeding, and safe discharge. Comparative analyses of diagnostic accuracy were extracted where available. Our findings indicate that while no single score offers comprehensive predictive accuracy across all outcomes, certain tools are particularly effective for specific endpoints. The Oakland and GBS scores are useful for identifying patients at low risk who may be managed safely as outpatients. The ABC and CHAMPS scores demonstrate superior performance in predicting mortality, especially in elderly or comorbid populations. SALGIB, a newer score developed in Vietnam, shows promising performance for early triage but requires further validation. The Rockall score, although historically valuable in upper GI bleeding, offers limited applicability in LGIB due to its reliance on post-endoscopic findings. In conclusion, multiple prognostic tools are now available to support early decision-making in LGIB. Their optimal use requires understanding their strengths, limitations, and appropriate clinical contexts. Integrating these scores into routine practice, along with clinical judgment, can enhance patient outcomes and resource allocation. Full article

The polysaccharide of Millettia speciosa Champ. ex Benth (MSCP) has antioxidant properties, but its impact on chicken growth and development is not yet known. This study used chlortetracycline as a control to assess MCSP as a feed antibiotic substitute and its effects on Wenchang chicken production, slaughter performance, and meat quality. A total of 576 healthy 80-day-old Wenchang chickens were randomly allocated to six experimental groups. The control group (Control) received a basal diet, while the antibiotic group (CTC) was supplemented with 2 g/kg chlortetracycline (CTC). Four additional experimental groups were administered varying doses of MSCP: 400 mg/kg (MSCP₄₀₀), 800 mg/kg (MSCP₈₀₀), 1600 mg/kg (MSCP₁₆₀₀), and 3200 mg/kg (MSCP₃₂₀₀), respectively. The study discovered that incorporating MSCP and CTC into chicken diets significantly boosted the final body weight and average daily feed intake compared to the control group (p < 0.01), with MSCP notably enhancing average daily weight gain. With the addition of 800 mg/kg MSCP, chicken growth performance is comparable to that achieved with antibiotics in feed. However, it did not impact slaughtering performance (p > 0.05). In addition, MSCP significantly raised the pH after 24 h (p < 0.05) and decreased the yellowness (p < 0.01) of breast muscle. MSCP increased the essential amino acids (EAA) proportion in breast muscle (p < 0.05), EAA to nonessential amino acids (NEAA) ratio (p < 0.05), and diversity of fatty acids while decreasing C20:0 and increasing C18:2N6 and C22:1N9 content. Moreover, MSCP significantly reduced muscle fiber size (p < 0.01), increased fiber density (p < 0.01), boosted MYOD1 expression (p < 0.05), and decreased MSTN expression in breast muscle (p < 0.01). Overall, our study showed that supplementing the diet with MSCP, particularly at a dose of 800 mg/kg, enhanced growth, meat quality, muscle morphology, amino acid content, fatty acid composition, and gene expression related to muscle development in breast muscle. The results indicate that MSCP is a feed additive with the potential to replace antibiotics and improve meat quality, showing promising application potential. Full article

Accurate thermospheric mass density (TMD) prediction is critical for applications in solar-terrestrial physics, spacecraft safety, and remote sensing systems. While existing deep learning (DL)-based TMD models are predominantly data-driven, their performance remains constrained by observational data limitations. This study proposes ResNet-MSIS, a novel hybrid framework that integrates prior knowledge from the empirical NRLMSIS-2.1 model into a residual network (ResNet) architecture. The incorporation of NRLMSIS-2.1 enhanced the performance of ResNet-MSIS, yielding a lower root mean squared error (RMSE) of 0.2657 × ${10}^{-12}$ kg/m³ in TMD prediction compared with 0.2750 × ${10}^{-12}$ kg/m³ from ResNet, along with faster convergence during training and better generalization on Gravity Recovery and Climate Experiment (GRACE-A) data, which was trained and validated on the CHAllenging Minisatellite Payload (CHAMP) TMD data (2000–2009, altitude of 305–505 km, avg. 376 km) under quiet geomagnetic conditions (Kp ≤ 3). The DL model was subsequently tested on the remaining CHAMP-derived TMD observations, and the results demonstrated that ResNet-MSIS outperformed both ResNet and NRLMSIS-2.1 on the test dataset. The model’s robustness was further demonstrated on GRACE-A data (2002–2009, altitude of 450–540 km, avg. 482 km) under magnetically quiet conditions, with the RMSE decreasing from 0.3352 × ${10}^{-12}$ kg/m³ to 0.2959 × ${10}^{-12}$ kg/m³, indicating improved high-altitude prediction accuracy. Additionally, ResNet-MSIS effectively captured the horizontal TMD variations, including equatorial mass density anomaly (EMA) and midnight density maximum (MDM) structures, confirming its ability to learn complex spatiotemporal patterns. This work underscores the value of merging data-driven methods with domain-specific prior knowledge, offering a promising pathway for advancing TMD modeling in space weather and atmospheric research. Full article

Recent advancements in wearable devices have significantly enhanced remote patient monitoring, enabling healthcare professionals to evaluate conditions within home settings. While electronic health records (EHRs) offer extensive clinical data, they often lack crucial contextual information about patients’ daily lives and symptoms. By integrating continuous self-reported outcomes related to vulnerability, anxiety, and depression from older adult cancer survivors with objective data from wearables, we can develop personalised risk models that address time-varying risk factors in cancer care. Our study combines real-world data from wearable devices with self-reported information, employing process mining techniques to analyse dynamic risk models for vulnerability and anxiety. Unlike traditional static assessments, this approach recognises that risk factors evolve. Collaborating with healthcare professionals, we analysed data from the LifeChamps study to create two dynamic risk models. This collaborative effort revealed how activity and sleep patterns influence self-reported vulnerability and anxiety among participants. It underscored the potential of wearable sensors and artificial intelligence techniques for deeper analysis and understanding, making us all part of a larger effort in cancer care. Overall, patients with prolonged sedentary activity had a higher risk of vulnerability, while those with highly dynamic sleep patterns were more likely to report anxiety and depression. Prostate-metastatic patients showed an increased risk of vulnerability compared to other cancer types. Full article

We incorporated a comprehensive dataset encompassing recent measurements from satellites such as the Macau Science Satgellite-1 (MSS-1), Swarm, and CHAMP, as well as aero and ocean magnetic measurements, alongside ground-based data from 1936 to 2000. This amalgamation is the basis for constructing a lithospheric magnetic field model of the Chinese mainland, employing the three-dimensional Surface Spline (3DSS) model. Additionally, we used the World Digital Magnetic Anomaly Map (WDMAM)-2.1 and CHAOS-7.13 models to address data gaps horizontally and vertically. To evaluate the efficacy of the new model, we compared it not only with established models such as SHA1050, NGDC720, and LCS-1 but also with the new model excluding the MSS-1 data. The results show a high agreement between the 3DSS model and other global models at a spatial resolution of 0.05°. Furthermore, we inspected the rapid variations in the magnetic field with increasing altitude, demonstrating a smooth transition across the altitudes covered by the three satellites. Error analyses reflected the importance of MSS-1 data, which contributed notably to modelling by capturing finer-scale magnetic structures. The increased data availability correlated positively with the model’s accuracy, as evidenced by the Root Mean Square Error (RMSE), registering an optimal value of 0.02 nT. The new model reveals additional geological details in southern Tibet, northeastern Inner Mongolia, and the adjacent areas of Liaoning and Jilin provinces, which are not discernible in other global models. The relationship between these anomalies and heat flow in northeastern China appears less evident, suggesting a complex interplay of orogenic processes and surface mineralogy in shaping these magnetic signatures. Full article

Mixing and matching N₂-fixing leguminous species is a crucial strategy to enhance quality and efficiency in sustainable forestry. Tree leaves and rhizosphere are primary sites for matter and energy exchange, functioning as key assimilation organs that forests provide for ecological services. The introduction of functional species alters soil properties, which, in turn, directly or indirectly shape leaf functional traits, soil microbial dynamics, and their association. However, the correlation between aboveground functional traits and belowground rhizosphere soil microorganisms of dominant tree species in mixed leguminous and non-leguminous forests remains unclear. In this study, the responses and correlations of leaf functional traits and rhizosphere soil microbial communities of Castanopsis hystrix Hook. f. & Thomson ex A. DC. across three forest types were investigated. A pure forest (PF) of C. hystrix was designated as control forest, while a leguminous mixed forest (LMF) consisting of C. hystrix and the leguminous species Acacia mangium Willd. as well as a non-leguminous mixed forest (NMF) comprising C. hystrix and the non-leguminous species Schima superba Gardner & Champ. served as experimental forests. Seven leaf functional trait indices were measured, and the high-throughput sequencing of soil microbial communities was included in the analysis. The results were as follows: Firstly, compared to the pure forest, the specific leaf area (SLA) of C. hystrix significantly decreased in both mixed forest types (p < 0.05). Additionally, in comparison to the pure forest, the leaf area (LA) and leaf organic carbon content (LOC) of C. hystrix significantly reduced (p < 0.05), whereas the leaf total phosphorus content (LTP) significantly increased in the non-leguminous tree species mixed forest (p < 0.01). The leaf dry matter content (LDMC), relative chlorophyll content (RCC), and leaf total nitrogen content (LTN) of C. hystrix exhibited no significant differences among the three forest types (p > 0.05). Secondly, neither the dominant phyla of rhizosphere soil microorganisms nor the bacterial richness and diversity had differences in the mixed forests. However, the richness and diversity of rhizosphere soil fungi significantly increased in the mixed forests, and those in the leguminous mixed forest exhibited more positive effects compared to those in the non-leguminous mixed forest. Finally, redundancy analysis (RDA) showed significant correlations between plant leaf functional traits and rhizosphere soil microorganisms. Specifically, LDMC, SLA, LTN, and LTP of C. hystrix showed significant correlations with differences in the structure of bacterial community (p < 0.05), and LTN was significantly correlated with differences in the structure of the fungal community (p < 0.05). In summary, we found that plant leaf functional traits and the community of rhizosphere soil microorganisms displayed significant differences in the mixed forests, and those mixed with leguminous trees may further enhance the assimilation processes by modifying the utilization of nutrients such as carbon, nitrogen, and phosphorus by plants and microorganisms. Meanwhile, our results support the interaction of physiological and ecological processes between the aboveground and belowground parts of C. hystrix. These findings emphasize the important roles of N₂-fixing leguminous trees and synergy of aboveground–belowground processes in establishing sustainable artificial forests. Full article