Search Results (9,857)

The extensive use of antibiotics in intensive farming weakens immunity and threatens food safety. Stevia isochlorogenic acid (SICA), a kind of dicaffeoylquinic acid derived from stevia residue, exhibits strong antioxidant activity. This study evaluated the ability of SICA to improve immune function in an immunosuppressed broiler model. SICA significantly increased the spleen, thymus, and bursa of Fabricius indices (p < 0.05), alleviated spleen damage, and elevated serum interleukin-2 (IL-2), IL-4, interferon-γ, IL-1β, tumor necrosis factor-α, immunoglobulins (IgA, IgM, IgG), and complement components C3 and C4 (p < 0.05). Isobaric tags for relative and absolute quantification-based proteomics indicated that SICA enhanced splenic immune function by activating cell adhesion molecules, phagosomes, and the intestinal immune network for IgA production pathways. Quantitative PCR analysis showed upregulation of mRNA and protein levels of B-cell receptor, major histocompatibility complex class II, protein tyrosine phosphatase receptor type C, and neutrophil cytosolic factor 2 (p67phox) and downregulation of C-C motif chemokine receptor 9. Molecular docking demonstrated the strongest binding affinity between SICA and p67phox. Overall, SICA effectively alleviated immunosuppression in broiler chickens and represents a promising natural alternative to antibiotic feed additives. Full article

This work provides the first systematic survey of the two–photon properties of 97 natural 9,10–anthraquinones from plants and fungi. A comprehensive computational dataset of two–photon absorption properties calculated using RI–CC2/aug–cc–pVDZ is presented. Single degenerate photon energies are required for two–photon excitation span 575.8–1007.9 nm across the five lowest singlet states, with all S₀→S₁ transitions falling within the biological therapeutic window. Remarkably, S₃ state exhibits systematically enhanced TPA efficiency, with 60% of compounds surpassing 1 GM and achieving a mean cross–section of 29.9 GM–substantially higher than S₁ (mean: 7.5 GM) or S₅ (mean: 12.2 GM). Three compounds demonstrate exceptional performance: cynodontin (73.6 GM, S₂), dermocybin (68.7 GM, S₄), and morindone (50.7 GM, S₃). Natural transition orbital analysis reveals that these excitations possess high configurational purity (82.5–94.2% single–excitation character) and diagnostics validating the single–reference treatment. The observed spatial separation between hole and particle NTOs, combined with extreme transition dipole anisotropy along the molecular long axis, indicates dipolar charge–transfer enhancement. Comprehensive structure–property analysis establishes that strategic peri–hydroxylation (1,5 or 1,8), alkoxylation, and multi–site donor substitution maximise TPA cross–sections through enhanced charge–transfer character and longitudinal polarisability. Comparison with aqueous–phase calculations for three compounds reveals non–systematic solvent–induced redistributions of TPA activity across excited states, indicating that gas–phase outcomes serve primarily as internal benchmarks and intrinsic descriptors of structure–property relationships rather than quantitative predictors of photoactivity. Full article

Background: Cervical cancer (CC) is the fourth most common malignancy in women around the world, with more than 600,000 new cases registered in 2022 and around 350,000 deaths. It is a growing social problem, especially in developing countries. Almost all cases of cervical cancer are caused by persistent infection with oncogenic high-risk human papillomavirus (HPV). This malignancy usually exhibits a gradual development through well-defined precursor stages, known as cervical intraepithelial neoplasia (CIN) grades 1, 2, and 3, before evolving into invasive carcinoma. In diagnostic practice, several biomarkers have been implemented to improve the detection of high-risk cervical lesions. p16 and Ki-67 greatly aid in identifying HPV-driven dysplasia, but they cannot always reliably distinguish progressive lesions from regressive or transient HPV infections. These limitations highlight the need for novel biomarkers with better predictive accuracy to complement current screening and diagnostic algorithms. ROMO1 has become a possible marker of a high-ROS, high-risk tumor phenotype in a number of cancers. Although oxidative stress, HPV, and cervical carcinogenesis have been linked, nothing is known about ROMO1’s involvement in cervical neoplasia. There is currently a lack of thorough information regarding the expression of ROMO1 in normal vs. precancerous lesions and in cervical cancer, as well as on whether or not its expression is correlated with the severity of the disease. In order to define ROMO1 expression throughout the course of cervical squamous neoplastic development, the current study was created. Methods: We performed immunohistochemical analysis of ROMO1 expression on cervical tissue samples from three groups: healthy cervix (n = 30), cervical intraepithelial neoplasia (CIN) (n = 41), and invasive cervical carcinoma (n = 205). ROMO1 expression in invasive carcinoma was evaluated using an H-score scale. Results: ROMO1 expression was basal in all normal cervix samples (0/30 cases). In contrast, CIN lesions showed 100% ROMO1 expression in the suprabasal layers of abnormal cells in all CIN cases. In invasive cervical carcinomas, ROMO1 expression was heterogeneous. In our cancer cohort (n = 205), ROMO1 H-score showed no significant association with the following: FIGO stage I vs. II vs. III (p = 0.25); histologic grade G1 vs. G2 vs. G3 (p = 0.46); lymphovascular invasion (no vs. yes; p = 0.80); nodal status N0 vs. N1 (p = 0.67); patient age (≤50 y vs. >50 y; p = 0.38). However, ROMO1 expression did vary by histologic subtype (AC vs. ASC vs. SCC; p = 0.02), with SCC enriched for strong staining compared to AC/ASC. With regard to tumor stage (pT stage), pT2a tumors exhibited significantly lower ROMO1 (pT1b1–pT2b; p = 0.035) than pT1b1 (p = 0.04). No other clinicopathologic variable remained significant. Notably, ROMO1 expression was highest in stage I tumors and declined in more advanced stages of cervical carcinoma. Conclusions: These results show a clear pattern of ROMO1 expression across the cervical neoplasia spectrum: it is attenuated in invasive tumors (with a peak in early-stage illness), significantly raised in pre-cancerous CIN lesions, and negligible in normal epithelium. The idea that oxidative stress may be the primary cause of early malignant transformation in the cervix is supported by the noticeable overexpression of ROMO1 in early lesions. For the detection of early-stage cervical carcinoma and high-grade precancerous lesions, ROMO1 may be a useful auxiliary biomarker. Full article

The non-destructive estimation of grain yield could increase the efficiency of soybean breeding through early genotype testing, allowing for more precise selection of superior varieties. High-throughput phenotyping (HTPP) data can be combined with machine learning (ML) to develop accurate prediction models. In this study, an unmanned aerial vehicle (UAV) equipped with a multispectral camera was utilized to collect data on plant density (PD), plant height (PH), canopy cover (CC), biomass (BM), and various vegetation indices (VIs) from different stages of soybean development. These traits were used within random forest (RF) and partial least squares regression (PLSR) algorithms to develop models for soybean yield estimation. The initial RF model produced more accurate results, as it had a smaller error between actual and predicted yield compared with the PLSR model. To increase the efficiency of the RF model and optimize the data collection process, the number of predictors was gradually decreased by eliminating highly correlated VIs and selecting the most important variables. The final prediction was based only on several VIs calculated from a few mid-soybean stages. Although the reduction in the number of predictors increased the yield estimation error to some extent, the R² in the final model remained high (R² = 0.79). Therefore, the proposed ML model based on specific HTPP variables represents an optimal balance between efficiency and prediction accuracy for in-season soybean yield estimation. Full article

Background and Aims: Colon capsule endoscopy (CCE) provides a non-invasive alternative to traditional colonoscopy. This study evaluated the feasibility, safety, diagnostic yield (DY), and patient satisfaction of the OMOM CC100 CCE system, with special focus on fully remote (n = 30) and partially remote (n = 89) administration across four centres to advance decentralised models. Methods: This prospective, investigator-initiated, international multicentre feasibility study enrolled 119 patients aged 18–75 years at centres in Denmark, Sweden, Portugal, and Poland from July 2024 to May 2025. Indications included rectal bleeding, iron-deficiency anaemia, a positive faecal immunochemical test, changes in bowel habit, suspected inflammatory bowel disease (IBD), post-polypectomy or colorectal cancer (CRC) surgery surveillance, and a family history of CRC. The OMOM CC100 capsule was employed with a standardised bowel preparation regimen. Administration was fully remote in Denmark using the IntelliGI™ platform and partially remote (clinic ingestion, home completion) at the other sites. Primary outcomes encompassed procedure feasibility, completion rate (capsule excretion or anal verge visualisation), bowel cleanliness (Leighton-Rex scale ≥ 3), diagnostic yield, and patient satisfaction. Secondary measures included transit times, adverse events, and technical failures. Results: Median age was 55.7 years (65 males, 54 females). Overall completion rate was 79%, varying by centre: Sweden (90%), Portugal (81%), Denmark (80%), and Poland (63%). Adequate bowel cleanliness was achieved in 71% of cases. Diagnostic findings included polyps (25 patients), angioectasia (20), diverticulosis (17), and mucosal inflammation (17); 42% were normal. Fully remote administration yielded 80% completion and 89.7% satisfaction. No serious adverse events occurred; overall satisfaction was 81%, with 87% preferring home-based procedures. Conclusions: The OMOM CC100 CCE system is feasible, safe, with DY comparable to established systems. IntelliGI™-enabled remote administration promotes decentralised care, enhancing accessibility. Full article

We investigate how generative AI tools function in smart learning by estimating a structural path model that combines the Stimulus–Organism–Response (SOR) framework with Self-Determination Theory (SDT). Using survey data from N = 540 university students and covariance-based SEM, we examine whether perceptions of these tools—usefulness (PU), ease of use (PEU), creative benefit (PCB), and personalization (PP)—align with SDT’s motivational states of perceived autonomy (PA) and perceived competence (PC) and, in turn, relate to creative confidence (CC) and creative engagement (CE). All four perceptions show positive links to PA and PC, with PP exhibiting the largest association with PA. PA precedes PC, indicating a sequential motivational route. At the behavioral level, PC relates more strongly to CC, whereas PA shows a comparatively larger association with CE. In aggregate, the results support integrating SOR with SDT to explain students’ psychological responses to generative AI tools and inform course designs that cultivate autonomy and competence to sustain creative confidence and engagement in smart-learning contexts. Full article

Remote sensing image change captioning (RSICC) fuses computer vision and natural language processing to translate visual differences between bi-temporal remote sensing images into interpretable text, with applications in environmental monitoring, urban planning, and disaster assessment. Multimodal Large Language Models (MLLMs) boost RSICC performance but suffer from inefficient inference due to massive parameters, whereas lightweight models enable fast inference yet lack generalization across diverse scenes, which creates a critical timeliness-generalization trade-off. To address this, we propose the Dual-Constrained Transformer (DCT), an end-to-end lightweight RSICC model with three core modules and a decoder. Full-Level Feature Distillation (FLFD) transfers hierarchical knowledge from a pre-trained Dinov3 teacher to a Generalizable Lightweight Visual Encoder (GLVE), enhancing generalization while retaining compactness. Key Change Region Adaptive Weighting (KCR-AW) generates Region Difference Weights (RDW) to emphasize critical changes and suppress backgrounds. Hierarchical encoding and Difference weight Constrained Attention (HDC-Attention) refine multi-scale features via hierarchical encoding and RDW-guided noise suppression; these features are fused by multi-head self-attention and fed into a Transformer decoder for accurate descriptions. The DCT resolves three core issues: lightweight encoder generalization, key change recognition, and multi-scale feature-text association noise, achieving a dynamic balance between inference efficiency and description quality. Experiments on the public LEVIR-CC dataset show our method attains SOTA among lightweight approaches and matches advanced MLLM-based methods with only 0.98% of their parameters. Full article

While tremendous progress has been made towards achieving highly efficient and practical Private Set Intersection (PSI) protocols during the last decade, the development of post-quantum PSI is still far from satisfactory. Existing post-quantum PSI protocols encounter a dilemma: while those based on fully homomorphic encryption (FHE) achieve low online communication, they suffer from significant online computation; conversely, protocols based on post-quantum Oblivious Pseudorandom Functions (OPRFs) exhibit excellent online computational performance but incur substantially high online communication. To overcome this dilemma, we present a lattice-based PSI protocol that achieves optimal online performance in both communication and computation. Our solution introduces two core innovations: a robust signal comparison algorithm based on RLWE key exchange, which determines the intersection through signal consistency rather than direct shared key comparison, and an optimized Oblivious Key–Value Stores (OKVS) implementation featuring a composite key–value mapping for efficient handling of high-dimensional RLWE polynomials. We implement the protocol and conduct extensive benchmarks in both symmetric and asymmetric set-size settings. The results show that our construction achieves the lowest online overhead in both computation and communication among all tests. For example, with asymmetric set sizes $(2^{12},11041)$, the online phase requires only $0.132$ s, yielding $19\times$ and $282\times$ improvements over FHE-based (CCS’21) and OPRF-based (EUROCRYPT’25) protocols, respectively. Even at $(2^{24},11041)$, our online communication time is only 0.201 s, which is $226\times$ and $184\times$ that of FHE-based and OPRF-based PSI, respectively. Additionally, our online communication overhead is the lowest in all tests; however, this comes at the cost of heavy offline communication overhead for very large set sizes, revealing a clear trade-off between pre-computation and online efficiency. This work addresses a critical gap in post-quantum PSI by delivering a protocol that achieves balanced online communication and computational overhead, thereby enabling broader practical deployment. Full article

Effective stakeholder management is essential in construction projects, but numerous context-specific challenges often hinder its implementation. This study investigates the factors that limit stakeholder management in Türkiye’s construction industry through a structured, multi-stage analytical approach. A systematic literature review first identified 69 stakeholder management challenges (SMCs). A questionnaire administered to 164 construction professionals was then analyzed using the normalized mean value (NMV) approach, which identified 53 critical challenges (CCs). To reduce the dimensionality of the 53 CCs, exploratory factor analysis (EFA) was conducted, resulting in four overarching factors: (1) weak planning, coordination, and implementation deficiencies; (2) institutional and operational weaknesses; (3) communication problems; and (4) legal regulations, bureaucratic barriers, and ethical issues. Finally, structural equation modeling (SEM) was applied to highlight the effect sizes of these factors in stakeholder management, rather than to perform predictive modeling. The results show that institutional and operational weaknesses and communication problems exert the strongest negative influences. By clearly linking the 53 CCs with four higher-level factors, this study provides a coherent analytical structure and a robust methodological basis for understanding the barriers to effective stakeholder management. The findings offer actionable insights for construction practitioners and policymakers seeking to enhance coordination, communication, and governance mechanisms in complex project environments. Full article

Background and Objectives: Chemical androgen deprivation and estrogenization are essential components of clinical treatment for advanced prostate cancer and male-to-female sex transition. The aim of this study was to determine the effects of these therapies on anthropometric parameters, liver histology, and biochemical parameters, with the goal of establishing experimental models that accurately represent current clinical practice. Materials and Methods: Young adult Wistar rats were divided into nine groups: intact control (IC), control vehicle (CV), cyproterone acetate-treated (CA), flutamide-treated (F), control sesame oil (CO), estradiol valerate-treated (E), combined control (CC), flutamide + estradiol valerate (F + E), and cyproterone acetate + estradiol valerate (CA + E)-treated groups. Treatments were administered by subcutaneous injection for four weeks. Results: The administration of estradiol valerate, alone or combined with antiandrogens, reduced final body mass and white adipose tissue mass. Notable changes were observed in absolute and relative pituitary, liver, prostate, and testis mass in the E, F + E and CA + E groups. There were no significant changes in liver histology or glycogen deposition; however, the combined treatment groups showed an increased volume density of binucleated hepatocytes and fibrotic tissue. Regarding biochemical parameters, androgen deprivation and/or estrogenization caused marked changes in serum triglyceride, LDL (low-density lipoproteins), ALP (alkaline phosphatase), AST (aspartate aminotransferase), ALT (alanine aminotransferase), Bil-T (bilirubin), creatinine, and urea levels. Conclusions: Given the importance of these therapies in clinical practice, providing a model based on the evaluated parameters offers a solid platform for future research. Full article

The valorization of grapevine pruning residues through pyrolysis provides a sustainable approach to agricultural waste management, producing biochar with agricultural use potential and carbon sink functionality. This study investigated pruning residues from 12 grapevine cultivars to evaluate the cultivar effects on biochar properties. Samples were collected along the Croatian coast from Istria to Dalmatia and included six indigenous cultivars (Malvazija istarska, Pošip, Maraština, Teran, Plavina, and Plavac mali) and six introduced cultivars (Chardonnay, Pinot blanc, Sauvignon blanc, Merlot, Cabernet Sauvignon, and Syrah). For each cultivar, residues were collected from three distinct vineyards with three replicates per vineyard. Pyrolysis was conducted in a muffle furnace at 400 °C. The pruning residues showed acidic pH (4.79–5.45), moderate electrical conductivity (1694–2390 µS cm⁻¹), and ash contents of 2.65–3.49% among all cultivars. Significant differences were observed among cultivars in residue carbon content and ash fraction, which were reflected in the resulting biochar. Biochar yield ranged from 32% to 35%, while pH values were alkaline, ranging from 10.20 to 11.13. Total carbon increased from 43.77 to 45.36% in grapevine-pruning residues to 65.88–71.57% in biochar. FT-IR spectra revealed cultivar-dependent variation in aromatic C=C intensification, while SEM analysis indicated differences in pore abundance and surface area (1.63–4.13 m² g⁻¹) between cultivars. These results demonstrate that carbon-dense cultivars produced biochars with greater structural stability, indicating enhanced resistance to decomposition. Spectroscopic and microscopic analyses consistently showed increased aromatic condensation, reduced aliphatic functionality, and greater porosity following pyrolysis. These cultivar-dependent differences highlight pruning residues as a chemically heterogeneous but predictable feedstock, with biochar properties primarily governed by the intrinsic characteristics of the source material. Full article

Riverbank erosion is a significant natural disaster that is prevalent in the deltaic regions in Bangladesh, resulting in loss of land, crops, and settlements. This research work is concentrated on the Satkhira Koyra area and is oriented towards a comparative assessment of the functionality of geo-bag and cement concrete (CC) blocks for erosion control purposes. The results showed that a geogrid could be used on the riverbank slope for more soil stability. The proposed approach is that the geogrid is used as a base layer for the slope. The sand-filled geo-bags are more cost-effective with this combination. Field monitoring and hydraulic model testing were used to identify their performance under natural flow conditions. Lined with geotextile fabric and filled with sand, the geo-bags were located in the most susceptible riverbank areas. The empirical results showed that the geo-bags provide the same levels of hydraulic resistance as those provided by CC blocks, but with substantial economic benefits and installation accomplished by local labor. When used in combination with a geogrid base layer, the geo-bag construction ensured excellent slope stability and allowed the establishment of natural vegetation, thus contributing to an environmentally friendly restoration. While CC blocks remain the optimal solution for high-value structures, the combined geogrid and geo-bag system offers a more flexible, cost-effective, and environmentally friendly alternative for stable erosion protection. Full article

Background and Objective: Changes in female sex hormone levels are closely linked to the development and progression of uterine fibroids (UFs). Clinical approaches to fibroid management vary according to guidelines and depend on patient symptoms, fibroid size, and clinician judgment. Despite available diagnostic tools, surgical decisions remain largely subjective. With the advancement of artificial intelligence (AI) and clinical decision support technologies, clinical experience can now be transferred into data-driven computational models trained with hormone-based parameters. To develop a clinical decision support algorithm that predicts surgical necessity for uterine fibroids by integrating fibroid characteristics and female sex hormone levels. Methods: This multicenter study included 618 women with UFs who presented to three hospitals; 238 underwent surgery. Statistical analyses and artificial intelligence-based modeling were performed to compare surgical and non-surgical groups. Training was conducted with each hormone—follicle-stimulating hormone (FSH), luteinizing hormone (LH), estrogen (E2), prolactin (PRL), and anti-Müllerian hormone (AMH)—and with 126 input combinations including hormonal and morphological variables. Five supervised learning algorithms—support vector machine, decision tree, random forest, and k-nearest neighbors—were applied, resulting in 630 trained models. In addition to this retrospective development phase, a prospective validation was conducted in which 20 independent clinical cases were evaluated in real time by a gynecologist blinded to both the model predictions and the surgical outcomes. Agreement between the clinician’s assessments and the model outputs was measured. Results: FSH, LH, and PRL levels were significantly lower in the surgery group (p < 0.001, 0.009, and <0.001, respectively), while E2 and AMH were higher (p = 0.012 and 0.001). Fibroid volume was also greater among surgical cases (90.8 cc vs. 73.1 cc, p < 0.001). The random forest model using LH, FSH, E2, and AMH achieved the highest accuracy of 91 percent. In the external validation phase, the model’s predictions matched the blinded gynecologist’s decisions in 18 of 20 cases, corresponding to a 90% concordance rate. The two discordant cases were later identified as borderline scenarios with clinically ambiguous surgical indications. Conclusions: The decision support algorithm integrating hormonal and fibroid parameters offers an objective and data-driven approach to predicting surgical necessity in women with UFs. Beyond its strong internal performance metrics, the model demonstrated a high level of clinical concordance during external validation, achieving a 90% agreement rate with an independent, blinded gynecologist. This alignment underscores the model’s practical reliability and its potential to reduce subjective variability in surgical decision-making. By providing a reproducible and clinically consistent framework, the proposed AI-based system represents a meaningful advancement toward the validated integration of computational decision tools into routine gynecological practice. Full article

Polyethylene (PE) films are widely used as waterproofing materials on the surfaces of metal pipelines. Poor adhesion of PE films to a metal substrate reduces durability, leading to shorter service life and higher economic costs. The current research aims to study the modification of PE films in atmospheric pressure gliding arc plasma (GAP). The adhesion properties of the modified films were investigated using the contact angle method and adhesion work calculations. During the modification process, the GAP treatment duration and deflector nozzle angle of attack were optimized to 10 s and 135°, respectively. It was established that the adhesion work increased from 62.1 to 141.3 mJ/m² after 10 s GAP modification compared to untreated PE. GAP modifying of PE films for 30 s or more is impractical, as the increase in the adhesion work ceases after that. It was found that surface roughness R_max increased by up to 4.1 times after 10 s GAP modification compared with nontreated PE. The PE films acquired hydrophilic properties after plasma modification, due to changes in the polymer surface’s chemical structure. The results of IR spectroscopy studies indicated oxidation of the film surface, an increase in the concentration of surface polar groups (-COOH, OH, C=O), and the formation of double bonds (C=C), which led to improved adhesive properties. A study of the electret properties showed that the observed decline and subsequent stabilization of values occurred within the first 24 h. Mechanical tests indicated improved performance of the GAP-modified PE films compared to the non-treated ones in the PE–mastic–PE and PE–mastic–steel systems. Due to their enhanced contact properties, the modified PE films are of interest as a base material for creating waterproofing materials. Full article

Protein phosphatase 2Cs (PP2Cs) constitute a widespread family of signaling regulators in plants and play central roles in abscisic acid (ABA)-mediated stress signaling; however, the PP2C gene family has not yet been systematically identified and characterized in pea (Pisum sativum), a salt-sensitive legume crop. In this study, we identified 89 PsPP2C genes based on domain features and sequence homology. These genes are unevenly distributed across seven chromosomes and classified into ten subfamilies, providing a comparative framework for evaluating structural and regulatory diversification within the PsPP2C family. The encoded proteins vary substantially in length, physicochemical properties, and predicted subcellular localization, while most members contain the conserved PP2Cc catalytic domain. Intra- and interspecies homology analyses identified 19 duplicated gene pairs in pea and numerous orthologous relationships with several model plants; all reliable gene pairs exhibited Ka/Ks < 1, indicating pervasive purifying selection. PsPP2C genes also showed broad variation in exon number and intron phase, and their promoter regions contained diverse light-, hormone-, and stress-related cis-elements with heterogeneous positional patterns. Expression profiling across 11 tissues revealed pronounced tissue-specific differences, with generally higher transcript abundance in roots and seeds than in other tissues. Under salt treatment, approximately 20% of PsPP2C genes displayed concentration- or time-dependent transcriptional changes. Among them, PsPP2C67 and PsPP2C82—both belonging to the clade A PP2C subfamily—exhibited the most pronounced induction under high salinity and at early stress stages. Functional annotation indicated that these two genes are involved in ABA-related processes, including regulation of abscisic acid-activated signaling pathway, plant hormone signal transduction, and MAPK signaling pathway-plant. Collectively, this study provides a systematic characterization of the PsPP2C gene family, including its structural features, evolutionary patterns, and transcriptional responses to salt stress, thereby establishing a foundation for future functional investigations. Full article