Search Results (71,865)

Retrotransposons exhibit increased activity in cancer cells. One possible approach to anticancer therapy is to use this activity to influence the energy balance in cells. Abnormal distribution of retrotransposons in the genome requires additional energy consumption, which can lead to a significant decrease in the total amount of free ATP molecules in the cell. A decrease in ATP levels below a certain threshold can in turn trigger a cell death program. To investigate the possibility of such a scenario, we developed a mathematical model of the cellular energy balance that describes the dynamics of energy consumption by the main cellular processes, including costs of retrotransposon activity. The model considers changes in the concentrations of ATP, active retrotransposons (LINE-1 and SINE) in the human genome, as well as mRNAs and proteins that are expression products of retrotransposon and constitutive genes. We estimated the parameter values in the model based on literature data and numerical optimization. We found a single stable stationary solution, characterized by low retrotransposon activity, and used it as the reference steady state for further analysis. Parametric sensitivity analysis revealed the parameters whose changes had the greatest impact on cellular ATP levels. The LINE-1 deactivation rate constant and the maximum LINE-1 transcription rate were the most sensitive among the transposon-related parameters. Perturbation of these parameters led to a decrease in the number of free ATP to 30% of the reference value and below. Transcription of retrotransposons under perturbed parameters became comparable to the translation of constitutive genes in terms of energy costs. The presented results indicate that cancer cell death can be initiated by increasing the load on the energy balance due to the activation of transposons. Full article

Despite increasing evidence that cigarette smoke is a significant source of indoor fine particulate matter (PM_2.5), quantitative emission factors (EFs) for PM_2.5 and its toxic chemical composition in mainstream (MS) and sidestream (SS) smoke are still not well defined. In this study, we employed a custom-designed chamber to separately collect MS (intermittent puff) and SS (continuous sampling) smoke from eleven cigarette models, representing six brands and two product types, under controlled conditions. PM_2.5 was collected on quartz-fiber filters and analyzed for carbon fractions (using the thermal–optical IMPROVE-A protocol), nine water-soluble inorganic ions (by ion chromatography), and twelve trace elements (via ICP-MS). SS smoke exhibited significantly higher mass fractions of total analyzed species (84.7% vs. 65.9%), carbon components (50.6% vs. 44.2%), water-soluble ions (17.1% vs. 13.7%), and elements (17.0% vs. 7.0%) compared to MS smoke. MS smoke is characterized by a high proportion of pyrolytic organic carbon fractions (OC₁–OC₃) and specific elements such as vanadium (V) and arsenic (As), while SS smoke shows elevated levels of elemental carbon (EC1), water-soluble ions (NH₄⁺, NO₃⁻), and certain elements like zinc (Zn) and cadmium (Cd). The toxicity-weighted distribution indicates that MS smoke primarily induces membrane disruption and pulmonary inflammation through semi-volatile organics and elements, whereas SS smoke enhances oxidative stress and cardiopulmonary impairment via EC-mediated reactions and secondary aerosol formation. The mean OC/EC ratio of 132.4 in SS smoke is an order of magnitude higher than values reported for biomass or fossil-fuel combustion, indicative of extensive incomplete combustion unique to cigarettes and suggesting a high potential for oxidative stress generation. Emission factors (µg/g cigarette) revealed marked differences: MS delivered higher absolute EFs for PM_2.5 (422.1), OC (8.8), EC (5.0), Na⁺ (32.6), and V (29.2), while SS emitted greater proportions of NH₄⁺, NO₃⁻, Cl⁻, and carcinogenic metals (As, Cd, Zn). These findings provide quantitative source profiles suitable for receptor-oriented indoor source-apportionment models and offer toxicological evidence to support the prioritization of comprehensive smoke-free regulations. Full article

Background and Objectives: Type 2 diabetes (T2DM) substantially increases cardiovascular risk; beyond the well-recognized left-ventricular involvement in diabetic cardiomyopathy, emerging data indicate subclinical right-ventricular (RV) dysfunction may also be present. This study aimed to evaluate whether speckle-tracking echocardiography identifies subclinical right-ventricular systolic dysfunction in type 2 diabetes, despite normal conventional indices and preserved global systolic function. Materials and Methods: We conducted a cross-sectional, single-center study in accordance with STROBE recommendations, enrolling 77 participants, 36 adults with T2DM, and 41 non-diabetic controls, between December 2024 and July 2025. All participants underwent comprehensive transthoracic echocardiography, including conventional parameters (tricuspid annular plane systolic excursion (TAPSE), tricuspid annular systolic velocity (TV S’), right ventricular fractional area change (RVFAC)) and deformation imaging (right ventricular global longitudinal strain (RV GLS), right ventricular free wall longitudinal strain (RVFWS)) using speckle-tracking echocardiography. Biochemical and clinical data, including glycosylated hemoglobin (HbA1c), were recorded. Correlation and ROC curve analyses were performed to explore associations and predictive value. Results: The mean age was comparable between the two groups (62.08 ± 9.54 years vs. 60.22 ± 13.39 years; p = 0.480). While conventional RV parameters did not differ significantly between groups, diabetic patients had significantly lower RV GLS (−13.86 ± 6.07% vs. −18.59 ± 2.27%, p < 0.001) and RVFWS (−15.64 ± 4.30% vs. −19.03 ± 3.53%, p < 0.001). HbA1c levels correlated positively with RV strain impairment (RVFWS r = 0.41, p < 0.001). Both RV GLS and RVFWS were independent predictors of RV dysfunction in logistic regression analysis. ROC analysis showed good diagnostic performance for RV GLS, AUC = 0.84 with an optimal cut-off −17.2% (sensitivity 86.1% and specificity 80.5%) and RVFWS, AUC = 0.76 with cut-off −17.6% (sensitivity 77.8; specificity 80.5%) in identifying early myocardial involvement. Conclusions: RV systolic dysfunction may occur early in T2DM, even when traditional echocardiographic indices remain within normal limits. Speckle-tracking echocardiography, particularly RV GLS and RVFWS, offers sensitive detection of subclinical myocardial impairment, reinforcing its value in early cardiovascular risk stratification among diabetic patients. Full article

Capsicum is one of the most economically significant vegetable crops worldwide, owing to its high content of bioactive compounds with nutritional, pharmacological, and industrial relevance. However, research has focused on C. annuum, often disregarding local diversity and secondary gene pools, which may contain hidden variation for quality traits. Therefore, this study evaluated the genetic and phenotypic diversity of 283 accessions from the Colombian germplasm collection in the agrobiodiversity hotspot of northwest South America, representing all five domesticated species of the genus. A total of 18 morphological, physicochemical, and biochemical fruit traits were assessed, including texture, color, capsaicinoid, and carotenoid content. The phenotypic data were integrated with genomic information obtained through genotyping-by-sequencing (GBS) using the C. annuum reference genome and a multispecies pangenome. Fixed-and-Random-Model-Circulating-Probability-Unification (FarmCPU) and Bayesian-information-and-Linkage-disequilibrium-Iteratively-Nested-Keyway (BLINK) genome-wide association studies (GWAS) were performed on both alignments, respectively, leading to the identification of complex polygenic architectures with 144 and 150 single nucleotide polymorphisms (SNPs) significantly associated with key fruit quality traits. Candidate genes involved in capsaicinoid biosynthesis were identified within associated genomic regions, terpenoid and sterol pathways, and cell wall modifiers. These findings highlight the potential of integrating pangenomic resources with multi-omics approaches to accelerate Capsicum improvement programs and facilitate the development of cultivars with enhanced quality traits and increased agro-industrial value. Full article

Background/Objectives: The success of artificial reproductive technologies (ARTs) depends on different factors, such as patient-specific reproductive features, ovarian response to stimulation, oocyte and embryo quality, and endometrial receptivity. This study aimed to evaluate their association with oocyte yield, fertilization, endometrial thickness, and pregnancy outcomes. Methods: A prospective clinical study included 128 women undergoing IVF/ICSI. Baseline hormone levels (E2, P4, FSH, LH, AMH) were assessed prior to stimulation. E2 levels were monitored during stimulation, and P4 was measured on the day of oocyte retrieval. Patients were grouped based on P4 levels (<2 ng/mL vs. ≥2 ng/mL). IVF outcomes and endometrial characteristics were statistically analyzed. Results: Lower P4 levels (<2 ng/mL) on the day of oocyte retrieval were significantly associated with higher fertilization rates (p < 0.003), more fertilized oocytes (p < 0.001), and increased pregnancy rates (p < 0.001). Elevated P4 (≥2 ng/mL) correlated with a higher frequency of thin endometrium (<7 mm, p < 0.007). E2 levels on the hCG trigger day correlated positively with the number of retrieved and mature oocytes and fertilization outcomes (p < 0.05). Patients who achieved pregnancy had lower P4 and BMI, and higher E2, AMH, and endometrial thickness. ROC identified a P4 threshold of 1.99 ng/mL with moderate predictive value. Conclusions: Elevated progesterone levels on the day of oocyte retrieval negatively impact fertilization and pregnancy outcomes, likely due to impaired endometrial receptivity. Combined assessment of P4, E2, AMH, and endometrial thickness may enhance embryo transfer planning and improve IVF success rates. Full article

This study aimed to investigate the effect of storage time on the fermentation quality, bacterial community structure, and metabolic profiles of Jinmu grain grass silage. It was ensiled in vacuum bags for 60 days. Samples were collected after 0, 3, 7, 15, 30, and 60 days of ensiling. Nutritional analysis revealed no significant differences in dry matter (DM), ether extract (EE), crude protein (CP), neutral detergent fiber (NDF), or acid detergent fiber (ADF) across storage periods (p > 0.05), but relative feeding value (RFV) significantly increased at 30 and 60 days (p < 0.05). Fermentation quality improved with prolonged storage, pH values declined to 4.01 at 60 days, while lactic acid (LA) and acetic acid (AA) increased significantly (p < 0.05). Butyric acid(BA) was undetected. 16S rDNA sequencing showed bacterial diversity (Chao1, Simpson, and Shannon indices) increased significantly at 30 and 60 days (p < 0.01); The relative abundance of Lacticaseibacillus, and Amylolactobacillus at 30 days were significantly higher than 0 and 60 days (p < 0.05); The relative abundance of Stenotrophomonas, Serratia, Comamonas, GKS98_freshwater_group, and Sphingobium at 60 days were significantly higher than 0 and 30 days (p < 0.05). Comprehensive targeted metabolomics identified 2958 metabolites. There were 256 differential metabolites shared by the comparison groups at 0, 30, and 60 days. The pathways for enrichment of differential metabolites mainly include plant hormone signal transduction, Histidine metabolism, arginine biosynthesis, etc. In conclusion, the storage time of Jinmu grain grass silage can enhance its fermentation quality by influencing microbial communities and metabolic pathways. Full article

Natural lignocellulosic fibers (NLFs) replacing synthetic fibers have been used as reinforcement in polymer matrix composites. In this work, a lesser-known NLF endemic to the Amazon region, the envira fiber (Bocageopsis multiflora), was analyzed for its basic physical, thermochemical, morphological, and mechanical characteristics. In addition, epoxy matrix composites with 10, 20, 30, and 40 vol% of continuous and aligned envira fibers were evaluated by Fourier transform infrared spectroscopy (FTIR) and tensile tests. The results were statistically compared by ANOVA and Tukey’s test. The density found for the envira fiber was 0.23 g/cm³. The crystallinity index and microfibrilar angle obtained were 69.5% and 7.07°, respectively. Fiber thermal stability was found up to around 210 °C. FTIR confirmed the presence of functional groups characteristic of NLFs. Morphological analysis by SEM revealed that the envira fiber displayed fine bundles of fibrils and a rough surface along its length. The average strength value of the envira fiber was found to be 62 MPa. FTIR analysis of the composites confirmed the presence of the main constituents of the epoxy resin and NLFs. The tensile strength results indicated that the envira fiber addition increased the strength of the composites up to 40 vol%. The analysis of the fracture region revealed brittle aspects. These results indicate that envira fibers present potential reinforcement for polymer matrix composites and can be used in engineering applications, favored by their lightness and cost-effectiveness. Full article

This paper addresses the synergy between environmental and economic benefits in the green power trading market by constructing a collaborative game model for environmental rights value and electricity energy value. Based on this, a model for maximizing the benefits of flexible resource operation is proposed. Through the combination of non-cooperative and cooperative games, the conflict and synergy mechanisms of multiple stakeholders are quantified, and the Shapley value allocation rule is designed to achieve Pareto optimality. Simultaneously, considering the spatiotemporal regulation capability of flexible resources, dynamic weight adjustment, cross-period environmental rights reserve, and risk diversification strategies are proposed. Simulation results show that under the scenario of a carbon price of 50 CNY/ton (≈7.25 USD/ton) and a peak–valley electricity price difference of 0.9 CNY/kWh (≈0.13 USD/kWh), when the environmental weight coefficient α = 0.5, the total revenue reaches 6.857 × 10⁷ CNY (≈9.94 × 10⁶ USD), with environmental benefits accounting for 90%, a 15.3% reduction in carbon emission intensity, and a 1.74-fold increase in energy storage cycle utilization rate. This research provides theoretical support for green power market mechanism design and resource optimization scheduling under “dual-carbon” goals. Full article

Background: A short cervix in the second trimester significantly increases preterm birth risk, yet no reliable first-trimester prediction method exists. Current guidelines lack consensus on which women should undergo transvaginal ultrasound (TVUS) screening for cost-effective prevention. Therefore, it is vital to establish a highly accurate and economical method for use in the early stages of pregnancy to predict short cervix in mid-pregnancy. Methods: A total of 1480 pregnant women with singleton pregnancies and at least one risk factor for spontaneous preterm birth (<37 weeks) were recruited from January 2020 to December 2020 at the Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine. Cervical length was assessed at 20–24 weeks of gestation, with a short cervix defined as <25 mm. Feature selection employed tree models, regularization, and recursive feature elimination (RFE). Seven machine learning models (logistic regression, linear discriminant analysis, k-nearest neighbors, support vector machine, decision tree, random forest, XGBoost) were trained to predict mid-trimester short cervix. The XGBoost model—an ensemble method leveraging sequential decision trees—was analyzed using Shapley Additive Explanation (SHAP) values to assess feature importance, revealing consistent associations between clinical predictors and outcomes that align with known clinical patterns. Results: Among 1480 participants, 376 (25.4%) developed mid-trimester short cervix. The XGBoost-based prediction model demonstrated high predictive performance in the training set (Recall = 0.838, F1 score = 0.848), test set (Recall = 0.850, F1 score = 0.910), and an independent dataset collected in January 2025 (Recall = 0.708, F1 score = 0.791), with SHAP analysis revealing pre-pregnancy BMI as the strongest predictor, followed by second-trimester pregnancy loss history, peripheral blood leukocyte count (WBC), and positive vaginal microbiological culture results (≥10⁵ CFU/mL, measured between 11⁺⁰ and 13⁺⁶ weeks). Conclusions: The XGBoost model accurately predicts mid-trimester short cervix using first-trimester clinical data, providing a 6-week window for targeted interventions before the 20–24-week gestational assessment. This early prediction could help guide timely preventive measures, potentially reducing the risk of spontaneous preterm birth (sPTB). Full article

Due to the shortage of construction aggregates, carbonate rock aggregates—including mainly limestone aggregates—have long been used in structural concrete in many countries worldwide. On the other hand, earlier tests on the shear fracture toughness of concretes with limestone aggregates were very limited and were even abandoned for many years. For the above reasons, in this paper, completely new fracture toughness tests were performed according to the mode II fracture for limestone concretes with different grain size distributions. Two types of aggregate grain were used, i.e., two with maximum grain sizes of 8 mm (M1 series concrete) and 16 mm (M2 series concrete). During the experiments, the critical stress-intensity factor (K_IIc) and critical unit work of failure (J_IIc) were determined. Based on the conducted studies, it was found that higher values of fracture mechanics parameters were noted as the grain sizes of the aggregate used increased. The increases in the analyzed fracture mechanics parameters were noticeably greater in the M2 series concrete compared to the results for the M1 series concrete, specifically by 27% for K_IIc and 35% for J_IIc. In addition to macroscopic tests, detailed microstructural analyses of the ITZ area between the coarse aggregate grains and the cement matrix were conducted. Based on the captured images, it was determined that, in the M1 series concrete, the contacts between the aggregate grains and the cement paste exhibit a loose structure with visible microcracks. In contrast, the M2 series concrete showed no visible damages within the ITZ area itself nor at their displacement at a distance of approximately a few μm away from this area. This microstructure of both materials resulted in the M1 series concrete being more prone to rapid and sudden fracture propagation, leading to its brittle behavior during the fracture process. In contrast, the large, well-developed limestone aggregate grains in the M2 series concrete facilitated improved stress transfer beyond the ITZ area into the cement matrix, preserving the continuity of the material structure and consequently leading to quasi-plastic behavior of the concrete during the fracture process. The novelty and utilitarianism of the research undertaken result from the fact that exploring the properties of concretes with limestone aggregates using mode II fracture is an important aspect of evaluating the durability and safety of concrete structures subjected mainly to shear forces. Full article

This paper introduces a novel four-party evolutionary game model to analyze cooperation dynamics in High-Value Mixed Cropping (HMC) systems integrating non-pesticide cacao, cashew nut, and free-range chicken farming within circular and sharing economy frameworks. The model uniquely examines strategic interactions among local government and three farming family types (cacao, cashew, and chicken), incorporating both regulatory mechanisms and cooperative behaviors. Through rigorous stability analysis and MATLAB simulations based on empirical data from Southeast Vietnam, we identify precise conditions for Evolutionarily Stable Strategies (ESSs) that sustain long-term cooperation. Our results demonstrate that government incentives (subsidies, technical support) and reputational sanctions critically shape farmers’ and consumers’ payoffs, thereby steering the system toward collective action equilibria. In particular, increasing the strength of positive incentives or reputational benefits enlarges the basin of attraction for full-cooperation ESSs, regardless of initial strategy distributions. Conversely, overly punitive sanctions can destabilize collaborative outcomes. These findings underscore the pivotal role of well-balanced policy instruments in fostering resilience, innovation, and resource circulation within rural agroecosystems. Finally, we propose targeted policy recommendations, such as graduated subsidy schemes, participatory monitoring platforms, and cooperative branding initiatives, to reinforce circular economy practices and accelerate progress toward the United Nations Sustainable Development Goals. Full article

The complexity of fake information and the inefficiency of parameter optimization in detection models present dual challenges for current detection technologies. Therefore, this paper proposes a hybrid detection model named MIBKA-CNN-BiLSTM, which significantly improves detection accuracy and efficiency through a triple-strategy enhancement of the Black Kite Optimization Algorithm (MIBKA) and an optimized dual-channel deep learning architecture. First, three improvements are introduced in the MIBKA. The population initialization process is restructured using circle chaotic mapping to enhance parameter space coverage. The conventional random perturbation is replaced by a random-to-elite differential mutation strategy (DE/rand-to-best/1) to balance global exploration and local exploitation. Moreover, a logarithmic spiral opposition-based learning (LSOBL) mechanism is integrated to dynamically explore the opposition solution space. Second, a CNN-BiLSTM dual-channel feature extraction network is constructed, with hyperparameters such as the number of convolutional kernels and LSTM units optimized by MIBKA to enable adaptive model structure alignment with task requirements. Finally, a high-quality fake information dataset is created based on social media platforms, including CCTV. The experimental results show that our model achieves the highest accuracy on the self-built dataset, which is 3.11% higher than the optimal hybrid model. Additionally, on the Weibo21 dataset, our model’s accuracy and F1-score increased by 1.52% and 1.71%, respectively, compared to the average values of all baseline models. These findings offer a practical and effective approach for detecting lightweight and robust false information. Full article

The aim of the study was to determine the fluctuations of selected physiological parameters in young Lipizzan stallions (n = 10) during the initial phase of their training as indicators of adaptation to a graded exercise load and stress exposure. For this purpose, four exercise tests (ExT) with lunging were carried out over a period of one year. Physiological parameters (gait speed, heart and respiratory rate (HR and RR), rectal and body surface temperature (RT and BST), and cortisol and lactate concentration (CORT and LAC)) were measured before and after training. In all ExT, gait speeds increased (p < 0.001) during the transitions from walk to trot and canter, followed by a significant (p < 0.001) increase in HR, RT, BST, and CORT, but not LAC values. However, the gate speed has no influence on the measured parameters. The highest BST values and corresponding warming were measured in the cranial region, followed by the caudal and distal body regions. The values of the measured variables remained within the ranges for warm-blooded horses, indicating adequate adaptation of the stallions to the applied stress level, but their variations could depend on air temperature or humidity. The results presented contribute to the knowledge of the complex physiological processes that occur in horses during exercise and point to the importance of environmental factors for adaptation to exercise. Full article

The high acidity, alcohol, and mycotoxin levels in distiller’s grains (DGs) limit its application in practical production. To address these issues, a new DG fermentation technique was developed in this research. Firstly, four strains were selected and the fermentation conditions were optimized to ferment the fresh DGs. When the inoculum was set at 8%, the fermentation temperature was maintained at 35 °C, the fermentation time lasted for 48 h, the bacterial mixture ratio (Bacillus subtilis ASAG 216: Lactobacillus acidophilus G1: Saccharomyces cerevisiae ANP 101: Streptococcus thermophilus EFR 046) was 1:1:2:1, and the contents of crude protein in fermented DGs (FDGs) were the highest, so we chose these fermentation conditions to ferment the DGs. In addition, under these fermentation conditions, the amino acids were significantly (p < 0.05) increased while the concentrations of crude fiber and mycotoxins contents were significantly (p < 0.05) decreased in FDGs than in DGs. Subsequently, the nutritional value of DGs and FDGs were evaluated using a two-step in vitro digestion method. The digestibility of dry matter, protein, and crude fiber increased by 16.23%, 13.54%, and 64.09%, respectively, in FDGs compared to that in DGs. Finally, laying hens were treated by adding 0%, 1%, 2%, and 4% FDG to the basal diet for 4 weeks. The results demonstrated that addition of 2% FDG in the diet could significantly (p < 0.05) increase the laying rate of hens compared to that fed the control diet, while addition of 4% FDG in the diet could remarkably (p < 0.05) reduce the rate of broken eggs compared to the other groups. There were no significant (p > 0.05) differences in other indices. These indicates that FDG has potential as a functional feed additive to enhance animal productivity. Full article

As global food demand continues to rise, conventional agricultural practices face increasing difficulty in sustainably meeting production requirements. In response, deep learning-driven automated systems have emerged as promising solutions for enhancing precision farming. Nevertheless, accurate fruit segmentation remains a significant challenge in orchard environments due to factors such as occlusion, background clutter, and varying lighting conditions. This study proposes the Depthwise Asymmetric Bottleneck with Attention Mechanism Network (DABAMNet), an advanced convolutional neural network (CNN) architecture composed of multiple Depthwise Asymmetric Bottleneck Units (DABou), specifically designed to improve apple segmentation in RGB imagery. The model incorporates the Convolutional Block Attention Module (CBAM), a dual attention mechanism that enhances channel and spatial feature discrimination by adaptively emphasizing salient information while suppressing irrelevant content. Furthermore, the CBAM attention module employs multiple global pooling strategies to enrich feature representation across varying spatial resolutions. Through comprehensive ablation studies, the optimal configuration was identified as early CBAM placement after DABou unit 5, using a reduction ratio of 2 and combined global max-min pooling, which significantly improved segmentation accuracy. DABAMNet achieved an accuracy of 0.9813 and an Intersection over Union (IoU) of 0.7291, outperforming four state-of-the-art CNN benchmarks. These results demonstrate the model’s robustness in complex agricultural scenes and its potential for real-time deployment in fruit detection and harvesting systems. Overall, these findings underscore the value of attention-based architectures for agricultural image segmentation and pave the way for broader applications in sustainable crop monitoring systems. Full article