Search Results (11,933)

This study developed a new magnetic adsorbent from waste coconut shells using high-temperature carbonization, EDTA-2Na chelation, and Fe₃O₄ magnetic loading. Response surface methodology optimized the preparation conditions to a mass ratio of activated carbon: EDTA-2Na:Fe₃O₄ = 2:0.6:0.2. Characterization (SEM, XRD, FT-IR, and EDS) showed that EDTA-2Na increased the surface carboxyl and amino group density, while Fe₃O₄ loading (Fe concentration 6.83%) provided superior magnetic separation performance. The optimal adsorption conditions of Cu²⁺ by EDTA-2Na-Fe₃O₄-activated carbon composite material are as follows: when pH = 5.0 and the initial concentration is 180 mg/L, the equilibrium adsorption capacity reaches 174.96 mg/g, and the removal rate reaches 97.2%. The optimal adsorption conditions for Pb²⁺ are as follows: when pH = 6.0 and the initial concentration is 160 mg/L, the equilibrium adsorption capacity reaches 157.60 mg/g, and the removal rate reaches 98.5%. The optimal adsorption conditions for Cd²⁺ are pH = 8.0 and an initial concentration of 20 mg/L. The equilibrium adsorption capacity reaches 18.76 mg/g, and the removal rate reaches 93.8%. The adsorption followed the pseudo-second-order kinetics (R² > 0.95) and Langmuir/Freundlich isotherm models, indicating chemisorption dominance. Desorption experiments using 0.1 mol/L HCl and EDTA-2Na achieved efficient desorption (>85%), and the material retained over 80% of its adsorption capacity after five cycles. This cost-effective and sustainable adsorbent offers a promising solution for heavy metal wastewater treatment. Full article

Extreme precipitation events severely impact agriculture, reducing yields and land use efficiency. The spatiotemporal distribution of Total Column Water Vapor (TCWV), the primary gaseous form of water, directly influences sustainable agricultural management. This study, through multi-source data fusion, employs methods including the Mann–Kendall test, sliding change-point detection, wavelet transform, pixel-scale trend estimation, and linear regression to analyze the spatiotemporal dynamics of global TCWV from 1959 to 2023 and its impacts on agricultural systems, surpassing the limitations of single-method approaches. Results reveal a global TCWV increase of 0.0168 kg/m²/year from 1959–2023, with a pivotal shift in 2002 amplifying changes, notably in tropical regions (e.g., Amazon, Congo Basins, Southeast Asia) where cumulative increases exceeded 2 kg/m² since 2000, while mid-to-high latitudes remained stable and polar regions showed minimal content. These dynamics escalate weather risks, impacting sustainable agricultural management with irrigation and crop adaptation. To enhance prediction accuracy, we propose a novel hybrid model combining wavelet transform with LSTM, TCN, and GRU deep learning models, substantially improving multidimensional feature extraction and nonstationary trend capture. Comparative analysis shows that WT-TCN performs the best (MAE = 0.170, R² = 0.953), demonstrating its potential for addressing climate change uncertainties. These findings provide valuable applications for precision agriculture, sustainable water resource management, and disaster early warning. Full article

Constipation is a prevalent gastrointestinal disorder that significantly impairs quality of life. While pharmacological agents such as loperamide are widely used to induce constipation in experimental models, there is increasing interest in natural alternatives for alleviating intestinal dysfunction. In this study, we investigated the laxative effects of soybean powder fermented by Bacillus subtilis DKU_09 in a loperamide-induced rat model of constipation. The probiotic strain was isolated from cheonggukjang, a traditional Korean fermented soybean paste, and its identity was confirmed through 16S rRNA sequencing. Fermented soybean powder was characterized morphologically via scanning electron microscopy and chemically via HPLC to assess its isoflavone content. Rats were administered loperamide (5 mg/kg) for four days to induce constipation and were then treated with fermented soybean powder at doses of 100, 200, or 300 mg/kg. No pharmacological laxatives (e.g., PEG) were used as a positive control; instead, values from the treatment groups were compared with those from the loperamide-only constipation group. Key outcomes of fecal output, water content, colonic fecal retention, and gastrointestinal transit ratio were measured. The fermented product significantly improved stool frequency and moisture content, reduced colonic fecal retention, and restored gastrointestinal transit in a dose-dependent manner. Notably, the 300 mg/kg group demonstrated nearly complete recovery of fecal parameters without affecting body weight. Statistical analysis was performed using one-way ANOVA followed by Tukey’s post hoc test. These findings suggest that Bacillus subtilis-fermented soybean powder exerts synergistic laxative effects through the combined action of probiotic viability and fermentation-enhanced bioactive compounds such as aglycone isoflavones. This study supports the potential use of fermented soybean-based nutraceuticals as a natural and safe intervention for constipation and gastrointestinal dysregulation. Full article

The aim was to investigate the genetic effects of a SNP located in the precursor region of gga-miR-3528. (1) Single-nucleotide polymorphisms within precursor regions of microRNAs play crucial biological roles. (2) Utilizing a Gushi–Anka F₂ resource population (n = 860), we screened and validated miRNA SNPs. A SNP mutation in the miR-3528 precursor region was identified. Specific primers were designed to amplify the polymorphic fragment. Genotyping was performed for this individual SNP across the population, using the MassArray system. Association analyses were conducted between this SNP and chicken growth and body measurement traits, carcass traits, meat quality traits, and serum enzyme activities. (3) The rs14098602 (+12 bp A > G) was identified within the precursor region of gga-miR-3528. Significant associations (p < 0.05) were observed between this SNP and chicken growth traits (body weight at the age of 0 day, body weight at the age of 2 weeks, and body weight at the age of 4 weeks), carcass traits (evisceration weight), meat quality traits (subcutaneous fat rate and pectoral muscle density), and serum enzyme activities (total protein, albumin, globulin, cholinesterase, and lactate dehydrogenase). (4) These findings suggest that the polymorphism at rs14098602 may influence chicken growth, meat quality, and serum biochemical indices, through specific mechanisms. The gga-miR-3528 gene likely plays an important role in chicken development. Therefore, this SNP can serve as a molecular marker for genetic breeding and auxiliary selection of growth-related traits, facilitating the rapid establishment of elite chicken populations with superior genetic resources. Full article

The accurate and effective prediction of PM2.5 concentrations is crucial for mitigating air pollution, improving environmental quality, and safeguarding public health. To address the challenge of strong temporal correlations in PM2.5 concentration forecasting, this paper proposes a novel hybrid model that integrates the Particle Optimization Algorithm (POA) and Variational Mode Decomposition (VMD) with the Long Short-Term Memory (LSTM) network. First, POA is employed to optimize VMD by adaptively determining the optimal parameter combination [k, α], enabling the decomposition of the original PM2.5 time series into subcomponents while reducing data noise. Subsequently, an LSTM model is constructed to predict each subcomponent individually, and the predictions are aggregated to derive hourly PM2.5 concentration forecasts. Empirical analysis using datasets from Beijing, Tianjin, and Tangshan demonstrates the following key findings: (1) LSTM outperforms traditional machine learning models in time series forecasting. (2) The proposed model exhibits superior effectiveness and robustness, achieving optimal performance metrics (e.g., MAE: 0.7183, RMSE: 0.8807, MAPE: 4.01%, R²: 99.78%) in comparative experiments, as exemplified by the Beijing dataset. (3) The integration of POA with serial decomposition techniques effectively handles highly volatile and nonlinear data. This model provides a novel and reliable tool for PM2.5 concentration prediction, offering significant benefits for governmental decision-making and public awareness. Full article

TRPV1 regulates neuronal and vascular function mediated by NO and CGRP. Systemic arterial hypertension (SAH) induces an imbalance in vascular mediators NO and CGRP by altering the transport of Ca²⁺ ions through TRPV1, generating cellular damage. We studied the effect of topical capsaicin (CS) treatment on cardiac mechanical work, oxidative stress (CAT, NO, BH4, and BH2), cellular damage (MDA, MTO, and 8HO2dG), and inflammation (IL-6 and TNFα), generated by SAH, which was induced by L-NAME, in male Wistar rats. CS was added to a moisturizing cream and applied to the abdomen of animals for two weeks. Experimental groups were as follows: (1) Control, (2) Control + Cream, (3) Hypertensive, and (4) Hypertensive + Cream. Hearts were exposed to ischemia-reperfusion (I-R) using the Langendorff technique to study the potential cardioprotection of CS. Expression of SOD1, SOD2, catalase, eNOS, pNOS, TRPV1, and CGRP in cardiac tissue was evaluated. In the Hypertensive group, TRPV1 activation by CS (Hypertensive + Cream) reduced oxidative stress (OS), decreasing cellular damage and inflammation and increasing CAT, modulating biochemical and tissue alterations induced by OS generated by SAH. In parallel, an increase in tissue levels and the expression of CGRP, TRPV1, and eNOS, induced by CS, was observed. These findings indicate that pretreatment with CS attenuates cardiac I-R and SAH injury in rats. The cardioprotective mechanism may be based on TRPV1-mediated CGRP overexpression. Full article

This study investigates the use of a Random Forest (RF), an artificial intelligence (AI) model, to estimate the planetary boundary layer height (PBLH) over Central Amazonia from climatic elements data collected during the GoAmazon experiment, held in 2014 and 2015, as it is a key metric for air quality, weather forecasting, and climate modeling. The novelty of this study lies in estimating PBLH using only surface-based meteorological observations. This approach is validated against remote sensing measurements (e.g., LIDAR, ceilometer, and wind profilers), which are seldom available in the Amazon region. The dataset includes various meteorological features, though substantial missing data for the latent heat flux (LE) and net radiation (Rn) measurements posed challenges. We addressed these gaps through different data-cleaning strategies, such as feature exclusion, row removal, and imputation techniques, assessing their impact on model performance using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and $r^2$ metrics. The best-performing strategy achieved an RMSE of 375.9 m. In addition to the RF model, we benchmarked its performance against Linear Regression, Support Vector Regression, LightGBM, XGBoost, and a Deep Neural Network. While all models showed moderate correlation with observed PBLH, the RF model outperformed all others with statistically significant differences confirmed by paired t-tests. SHAP (SHapley Additive exPlanations) values were used to enhance model interpretability, revealing hour of the day, air temperature, and relative humidity as the most influential predictors for PBLH, underscoring their critical role in atmospheric dynamics in Central Amazonia. Despite these optimizations, the model underestimates the PBLH values—by an average of 197 m, particularly in the spring and early summer austral seasons when atmospheric conditions are more variable. These findings emphasize the importance of robust data preprocessing and higtextight the potential of ML models for improving PBLH estimation in data-scarce tropical environments. Full article

Pistachio nuts are among the 50 best foods with the highest antioxidant potential. They have a balanced content of mono- (~70%) and polyunsaturated (~20%) fatty acids, minerals, and bioactive compounds such as tocopherols, phytosterols, and phenolic compounds, which have shown rapid accessibility in the stomach. Pistachio consumption provides several health benefits, primarily due to its antioxidant properties and high content of essential nutrients. In this study, we analyzed the mineral composition, total phenolic content (TP), antioxidant activity (AA), and UHPLC/MS-MS polyphenolic profile of three Argentinian pistachio crops. Additionally, the physicochemical parameters and the elemental profiles of the growing soils were determined, as they influence mineral uptake and the synthesis of bioactive compounds in pistachio kernels. The TP was not significantly modified by the growing soils, with Crop3 presenting the highest TP content (276 ± 14 mg GA/100 g DW). Crop3 exhibited 18% higher TP content compared to Crop2. Similarly, FRAP values ranged from 28.0 to 36.5 mmol TE/100 g DW, with Crop1 showing a 30% increase compared to Crop2. DPPH values varied from 19.0 to 24.3 mmol TE/100 g DW, with Crop1 displaying 28% higher activity than Crop2. However, the polyphenolic profile was similar for all crops analyzed. Thirty compounds were identified; only Crop 1 contained the flavanone eriodyctiol and the isoflavone genistein, while the flavanone naringenin and the flavone luteolin were identified in Crop1 and Crop3. Regarding mineral content, the pistachio kernels mainly contained K, Ca, and Mg. Multivariate analyses revealed distinct elemental and antioxidant profiles among crops. LDA achieved classification accuracies of 77.7% for soils and 74.4% for kernels, with Pb, Zn, Cu, Rb, Sr, and Mn as key discriminants. CCA confirmed strong soil–kernel mineral correlations (r = 1), while GPA showed higher congruence between antioxidant traits and kernel composition than with soil geochemistry. These findings underscore the importance of soil composition in determining the nutritional quality of pistachio kernels, thereby supporting the beneficial health effects associated with pistachio consumption. Full article

IgG Fc binding protein (FcGBP) is a mucin-like protein that binds strongly to IgG and IgG–antigen complexes in intestinal mucus. FcGBP presence and its altered expression levels in meconium accumulating in the fetal intestine and amniotic fluid flowing in the intestine may provide new knowledge of the mechanisms responsible for the immune adaptation of the fetus to extrauterine life. FcGBP concentrations were measured by ELISA in the first-pass meconium and amniotic fluid samples collected from 120 healthy neonates delivered by either vaginal birth (n = 35) or cesarean section (n = 85) at 36 to 41 weeks gestation. The meconium FcGBP concentrations (405.78 ± 145.22 ng/g) decreased (r = −0.241, p = 0.007) over the course of 36 to 41 weeks gestation, but there were no significant changes (p > 0.05) in the amniotic fluid FcGBP (135.70 ± 35.83 ng/mL) in the same period. Both meconium and amniotic fluid FcGBP concentrations were higher (p < 0.05) in neonates delivered by cesarean section. Decreases in the meconium FcGBP concentrations correlated (r = −0.37, p = 0.027) with the gestational age in neonates delivered by vaginal birth but not in those delivered by cesarean section (p > 0.05). No association was found between the FcGBP concentrations in meconium and amniotic fluid and the birth weight (p > 0.05). With the development of the mucosal immune system in the fetal intestine over the course of the third trimester of gestation, the meconium FcGBP concentrations decrease. Increased FcGBP concentrations measured in the meconium and amniotic fluid of neonates delivered by cesarean section may possibly indicate altered intestinal mucosal function. Intrauterine growth is not associated with the intestinal mucosal barrier maturation involving FcGBP. Full article

Disease resistance is one of the most important target traits for sugarcane genetic improvement. Sugarcane brown stripe (SBS) caused by Helminthosporium stenospilum is one of the most destructive foliar diseases, which not only reduces harvest cane yield but also sugar content. This study aimed to identify quantitative trait loci (QTL) and candidate genes associated with SBS resistance. Here, the phenotypic investigation in six field habitats showed a continuous normal distribution, revealing that the SBS resistance trait is a quantitative trait. Two high-density linkage maps based on the single-dose markers calling from the Axiom Sugarcane100K SNP chip were constructed for the dominant sugarcane cultivars YT93-159 (SBS-resistant) and ROC22 (SBS-susceptible) with a density of 2.53 cM and 2.54 cM per SNP marker, and mapped on 87 linkage groups (LGs) and 80 LGs covering 3069.45 cM and 1490.34 cM of genetic distance, respectively. A total of 32 QTL associated with SBS resistance were detected by QTL mapping, which explained 3.73–11.64% of the phenotypic variation, and the total phenotypic variance explained (PVE) in YT93-159 and ROC22 was 107.44% and 79.09%, respectively. Among these QTL, four repeatedly detected QTL (qSBS-Y38-1, qSBS-Y38-2, qSBS-R8, and qSBS-R46) were considered stable QTL. Meanwhile, two major QTL, qSBS-Y38 and qSBS-R46, could account for 11.47% and 11.64% of the PVE, respectively. Twenty-five disease resistance candidate genes were screened by searching these four stable QTL regions in their corresponding intervals, of which Soffic.01G0010840-3C (PR3) and Soffic.09G0017520-1P (DND2) were significantly up-regulated in YT93-159 by qRT-PCR, while Soffic.01G0040620-1P (EDR2) was significantly up-regulated in ROC22. These results will provide valuable insights for future studies on sugarcane breeding in combating this disease. Full article

Despite the widespread accessibility of vaccines and antivirals, seasonal influenza virus epidemics continue to pose a threat to public health. In this study, we constructed a recombinant replication-deficient simian adenovirus type 25 vector carrying the full-length hemagglutinin (HA) of the H1N1 influenza virus, named rSAd25-H1. Both systemic and mucosal humoral immune responses, as well as the protective efficacy, were assessed in mice immunized via the intramuscular (IM) or intranasal (IN) route. A single-dose IM or IN administration of rSAd25-H1 elicited a robust systemic IgG antibody response, including hemagglutination inhibition antibodies. As expected, only IN immunization was able to induce IgA production in serum and respiratory mucosa. Notably, a single dose of rSAd25-H1 at the highest dose (10¹⁰ viral particles) conferred complete protection against lethal homologous H1N1 challenge in mice despite the route of administration. These findings demonstrate the potential of simian adenovirus type 25-based vectors as a promising candidate for intranasal vaccine development targeting respiratory pathogens. Full article

This review outlines a comprehensive methodology for the research and development of heterogeneous catalytic technologies (R&D_HeCaTe). Emphasis is placed on the fundamental interactions between reactants, solvents, and heterogeneous catalysts—specifically the roles of catalytic centers and support materials (e.g., functional groups) in modulating activation energies and stabilizing catalytic functionality. Particular attention is given to catalyst deactivation mechanisms and potential regeneration strategies. The application of molecular modeling and chemical engineering analyses, including reaction kinetics, thermal effects, and mass and heat transport phenomena, is identified as essential for R&D_HeCaTe. Reactor configuration is discussed in relation to key physicochemical parameters such as molecular diffusivity, reaction exothermicity, operating temperature and pressure, and the phase and “aggressiveness” of the reaction system. Suitable reactor types—such as suspension reactors, fixed-bed reactors, and flow microreactors—are evaluated accordingly. Economic and environmental considerations are also addressed, with a focus on the complexity of reactions, selectivity versus conversion trade-offs, catalyst disposal, and separation challenges. To illustrate the breadth and applicability of the proposed framework, representative industrial processes are discussed, including ammonia synthesis, fluid catalytic cracking, methanol production, alkyl tert-butyl ethers, and aniline. Full article

Earthquakes, as one of the most destructive natural disasters, often cause significant casualties and severe economic losses. Accurate prediction of earthquake fatalities is of great importance for pre-disaster prevention and mitigation planning, as well as post-disaster emergency response deployment. To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). The method first employs PCA to reduce the dimensionality of the influencing factor data, eliminating redundant information and improving modeling efficiency. Subsequently, the IWOA is used to intelligently optimize key hyperparameters of the XGBoost model, enhancing the prediction accuracy and stability. Using 42 major earthquake events in China from 1970 to 2025 as a case study, covering regions including the west (e.g., Tonghai in Yunnan, Wenchuan, Jiuzhaigou), central (e.g., Lushan in Sichuan, Ya’an), east (e.g., Tangshan, Yingkou), north (e.g., Baotou in Inner Mongolia, Helinger), northwest (e.g., Jiashi in Xinjiang, Wushi, Yongdeng in Gansu), and southwest (e.g., Lancang in Yunnan, Lijiang, Ludian), the empirical results showed that the PCA-IWOA-XGBoost model achieved an average test set accuracy of 97.0%, a coefficient of determination (R²) of 0.996, a root mean square error (RMSE) and mean absolute error (MAE) reduced to 4.410 and 3.430, respectively, and a residual prediction deviation (RPD) of 21.090. These results significantly outperformed the baseline XGBoost, PCA-XGBoost, and IWOA-XGBoost models, providing improved technical support for earthquake disaster risk assessment and emergency response. Full article

Premature ovarian insufficiency (POI) is an important factor in female infertility and is often associated with oxidative stress. Alginate oligosaccharides (AOSs), derived from the degradation of alginate, have been demonstrated to have protective effects against various oxidative stress-related diseases. However, the impact of AOSs on POI has not been previously explored. The current study explored the effects of AOSs on ovarian dysfunction in a mouse model of POI induced by D-galactose (D-gal). Female C57BL/6 mice were randomly divided into five groups: the control (CON), POI model (D-gal), and low-, medium-, and high-dose AOS groups (AOS-L, 100 mg/kg/day; AOS-M, 150 mg/kg/day; AOS-H, 200 mg/kg/day). For 42 consecutive days, mice in the D-gal, AOS-L, AOS-M, and AOS-H groups received daily intraperitoneal injections of D-gal (200 mg/kg/day), whereas those in the CON group received equivalent volumes of sterile saline. Following D-gal injection, AOSs were administered via gavage at the specified doses; mice in the CON and D-gal groups received sterile saline instead. AOS treatment markedly improved estrous cycle irregularities, normalized serum hormone levels, reduced granulosa cell apoptosis, and increased follicle counts in POI mice. Moreover, AOSs significantly reduced ovarian oxidative stress and senescence in POI mice, as indicated by lower levels of malondialdehyde (MDA), higher activities of catalase (CAT) and superoxide dismutase (SOD), and decreased protein expression of 4-hydroxynonenal (4-HNE), nitrotyrosine (NTY), 8-hydroxydeoxyguanosine (8-OHdG), and p16 in ovarian tissue. Analysis of the gut microbiota through 16S rRNA gene sequencing and short-chain fatty acid (SCFA) analysis revealed significant differences in gut microbiota composition and SCFA levels (acetic acid and total SCFAs) between control and D-gal-induced POI mice. These differences were largely alleviated by AOS treatment. AOSs changed the gut microbiota by increasing the abundance of Ligilactobacillus and decreasing the abundance of Clostridiales, Clostridiaceae, Marinifilaceae, and Clostridium_T. Additionally, AOSs mitigated the decline in acetic acid and total SCFA levels observed in POI mice. Notably, the total SCFA level was significantly correlated with the abundance of Ligilactobacillus, Marinifilaceae, and Clostridium_T. In conclusion, AOS intervention effectively mitigates ovarian oxidative stress, restores gut microbiota homeostasis, and regulates the microbiota–SCFA axis, collectively improving D-gal-induced POI. Therefore, AOSs represent a promising therapeutic strategy for POI management. Full article

Background: Mesenchymal stem cells (MSCs) are a promising tool in regenerative medicine due to their ability to secrete paracrine factors that modulate tissue repair. Extracellular vesicles (EVs) released by MSCs contain bioactive molecules (e.g., mRNAs, miRNAs, proteins) and play a key role in intercellular communication. Methods: This study compared the transcriptomic profiles (mRNA and miRNA) of equine MSCs derived from adipose tissue (AT-MSCs), bone marrow (BM-MSCs), and ovarian fibroblasts (as a differentiated control). Additionally, miRNAs present in EVs secreted by these cells were characterized using next-generation sequencing. Results: All cell types met ISCT criteria for MSCs, including CD90 expression, lack of MHC II, trilineage differentiation, and adherence. EVs were isolated using ultracentrifugation and validated with nanoparticle tracking analysis and flow cytometry (CD63, CD81). Differential expression analysis revealed distinct mRNA and miRNA profiles across cell types and their secreted EVs, correlating with tissue origin. BM-MSCs showed unique regulation of genes linked to early development and osteogenesis. EVs contained diverse RNA species, including miRNA, mRNA, lncRNA, rRNA, and others. In total, 227 and 256 mature miRNAs were detected in BM-MSCs and AT-MSCs, respectively, including two novel miRNAs per MSC type. Fibroblasts expressed 209 mature miRNAs, including one novel miRNA also found in MSCs. Compared to fibroblasts, 60 and 92 differentially expressed miRNAs were identified in AT-MSCs and BM-MSCs, respectively. Conclusions: The results indicate that MSC tissue origin influences both transcriptomic profiles and EV miRNA content, which may help to interpret their therapeutic potential. Identifying key mRNAs and miRNAs could aid in future optimizing of MSC-based therapies in horses. Full article