Search Results (293)

Background: Unplanned hospitalizations in patients with cancer are associated with adverse outcomes, including intensive care unit (ICU) transfer and in-hospital mortality. This study aimed to evaluate the predictive role of the prognostic nutritional index (PNI) and albumin-to-globulin ratio (AGR) for these outcomes in patients with unplanned hospitalization in a medical oncology ward. Methods: This retrospective, single-center study included patients aged ≥18 years with malignancy who had unplanned hospitalization between 1 January and 30 April 2025. PNI and AGR were calculated at admission. The primary outcome was ICU transfer or in-hospital mortality. Univariable and multivariable logistic regression analyses were performed, with AGR and PNI evaluated in separate models to avoid collinearity. Predictive performance was assessed using ROC analysis. Results: A total of 418 patients were included, with adverse clinical outcomes in 26.8%. Metastatic disease was present in 73.7%, and gastrointestinal (41.6%) and lung cancers (21.5%) were most common. In univariable analysis, metastatic disease (p < 0.001), Eastern Cooperative Oncology Group (ECOG) performance status (p < 0.001), cancer type (p = 0.030), reason for hospitalization (p = 0.001), AGR (p < 0.001), and PNI (p < 0.001) were significantly associated with adverse clinical outcomes. In multivariable analyses performed in separate models, ECOG ≥ 2 emerged as the strongest independent predictor of adverse clinical outcomes (AGR model: OR: 9.93; PNI model: OR: 11.14; both p < 0.001). Metastatic disease remained an independent risk factor, while higher AGR and PNI values were independently associated with a reduced risk (all p < 0.05). Among hospitalization reasons, only electrolyte imbalance/transfusion was associated with a lower risk, whereas most cancer type subgroups were not independently significant. Both indices showed moderate predictive performance, with PNI performing slightly better than AGR (AUC: 0.729 vs. 0.707). Conclusions: ECOG performance status, together with PNI and AGR, were identified as practical and accessible predictors of adverse clinical outcomes in patients with unplanned hospitalization in a medical oncology ward. Full article

Antimicrobial resistance (AMR) represents a critical global health challenge, with methicillin-resistant Staphylococcus aureus (MRSA) posing a significant threat in both hospital-acquired and community-associated infections. Research has demonstrated that biofilm formation is a key factor contributing to drug resistance in MRSA. In this study, we investigated an fungus, Fusarium oxysporum BPF55, isolated from Blaps rynchopetera, which inhibits MRSA biofilm formation. The aim of this research was to identify the fungal strain and comprehensively characterize its genomic features, as well as to evaluate its anti-MRSA biofilm potential. Whole-genome sequencing revealed a genome size of 50,097,681 base pairs, a GC content of 47.36%, and 16,507 predicted coding genes. AntiSMASH analysis identified 56 secondary metabolite biosynthetic gene clusters, including those involved in the synthesis of various natural products such as terpenes, non-ribosomal peptides, and polyketides. Using UPLC-MS/MS, 15 compounds were annotated from the ethyl acetate extract. Molecular docking studies demonstrated that four compounds exhibit varying affinities for SarA and AgrA, two key proteins involved in MRSA biofilm formation. Overall, these findings suggest that the fungus F. oxysporum BPA55 produces a variety of secondary metabolites and contains bioactive compounds with potential anti-MRSA biofilm activity. Full article

Staphylococcus aureus is a major cause of skin and soft tissue infections, necessitating the development of new topical agents with rapid bactericidal activity and low resistance potential. Here, we evaluated the antibacterial activity of a pyrazolone copper complex (P-FAH-Cu-phen) against S. aureus, investigated its in vitro mode of action, and its assessed therapeutic efficacy in a murine model of S. aureus-infected skin trauma. P-FAH-Cu-phen exhibited potent bactericidal activity (minimum inhibitory concentration [MIC] 1.4 μg/mL; minimum bactericidal concentration [MBC] 2.8 μg/mL) and rapid killing (>91% eradication within 2.5 min), with no detectable MIC increase under the tested serial passaging conditions. Cell-envelope dysfunction was evidenced by increased supernatant alkaline phosphatase activity, elevated leakage of nucleic acids and proteins, and reduced membrane-associated Na⁺/K⁺- and Ca²⁺/Mg²⁺-ATPase activities. At sub-inhibitory concentrations, P-FAH-Cu-phen reduced haemolytic and coagulase activities, modulated virulence gene expression (sea, hla, agrA), and inhibited biofilm formation and biofilm-associated metabolic activity. In vivo, topical treatment accelerated wound closure and histopathological repair, increased hydroxyproline content, reduced bacterial burden, and lowered TNF-α and IL-10 levels in wound tissues. Collectively, P-FAH-Cu-phen shows multi-faceted anti-infective activity and exhibits further development as a topical candidate for S. aureus-infected skin wounds. Full article

Background: Hematologic malignancies pose a critical threat to global health, with their pathological progression intrinsically linked to metabolic dysregulation and nutrient imbalance. Malnutrition accelerates the trajectory of adverse outcomes while substantially diminishing the quality of survival. Although several nutritional assessment tools are currently used in clinical practice, a significant evidence gap persists regarding their validation in populations with hematologic neoplasms. This study systematically evaluates the prognostic performance of existing nutritional assessment instruments in this cohort. Based on these findings, we further explored the feasibility of a preliminary framework that reflects metabolic characteristics specific to this population. Methods: This prospective cohort study analyzed nutritional assessment data from 1067 patients with hematologic malignancies enrolled in the INSCOC registry. Eight assessment systems were examined: Patient-Generated Subjective Global Assessment (PG-SGA), Modified PGSGA (mPG-SGA), PGSGA Short Form (PG-SGA SF), Abbreviated PGSGA (abPG-SGA), Nutritional Risk Screening-2002 (NRS-2002), Global Leadership Initiative on Malnutrition criteria (GLIM), Scored-GLIM, and Karnofsky Performance Status Scale (KPS). Kaplan–Meier survival curves and multivariate Cox regression analyses were conducted to investigate the association between nutritional status and overall survival (OS) and to determine the prognostic weight of individual components within the nutritional assessment tools. Linear regression models were applied to examine the relationships between nutritional assessment tools, length of hospital stay (LOS), and EORTC QLQ-C30 scores. The predictive performance of the tools was evaluated using the area under the receiver operating characteristic curve (AUC) and the concordance index (C-index). Least absolute shrinkage and selection operator (LASSO) regression was applied to optimize the selection of inflammation-related biomarkers. Results: A total of 1067 participants were analyzed (mean [SD] age, 55.54 [17.4] years; 625 were male [58.6%]). Cox proportional hazards regression demonstrated statistically significant associations for all eight nutritional assessment tools (p ≤ 0.05). However, their prognostic discrimination was limited, as indicated by the AUC analysis. Specifically, the area under the curve (AUC) values for each tool were as follows: mPG-SGA, 0.561; NRS-2002, 0.557; PG-SGA, 0.550; KPS, 0.544; PG-SGA SF, 0.542; abPG-SGA, 0.528; Scored-GLIM, 0.489; and GLIM, 0.473. The concordance index validation further corroborated these findings. Prognostically significant components and inflammation-related biomarkers identified by Cox and LASSO regression were combined to explore a composite assessment approach, termed the Hematologic Marker–Patient Generated Subjective Global Assessment (HMPG-SGA), incorporating the albumin–globulin ratio (AGR). The HMPG-SGA was significantly associated with overall survival (p < 0.001), with an AUC of 0.616 and a C-index of 0.605. Conclusions: Multidimensional validation demonstrated limited prognostic discrimination of eight conventional nutritional assessment tools for overall survival in patients with hematologic malignancies. Based on existing assessment tools and integrated hematologic indicators, the HMPG-SGA was preliminarily explored as a prognostic assessment tool in hematologic malignancies. Full article

Concrete remains one of the most widely utilized construction materials, valued particularly for its exceptional compressive strength. However, exposure to fire can compromise both its internal microstructure and external integrity. This research investigates the behavior of concrete manufactured with recycled concrete coarse aggregate (RCA) derived from construction waste, aiming to establish experimental evidence of fire’s impact on compressive strength. We employed the Optimal Density Method to design mix proportions targeting 24 MPa compressive strength. The experimental program comprised 45 cylindrical samples distributed across three replacement levels: 0%, 15%, and 30% natural aggregate substitution with RCA. Following 28 days of curing, samples underwent direct fire exposure in a melting furnace. Temperature progression was monitored using a pyrometer, ranging from ambient (0 °C) through 250 °C, 400 °C, 600 °C, to 800 °C, with controlled exposure duration at each level. Three samples were tested at each temperature. After fire exposure, samples were cooled for 24 h at ambient temperature before compression testing. The densities of the fresh specimens were determined to be 2254.06 kg/m³ for HS-0AR%, 2210.09 kg/m³ for HS-15AR%, and 2180.85 kg/m³ for HS-30AR%, with a percentage density variation with respect to HS-0AR% of 1.95% and 3.25%, respectively. Finally, in relation to the compressive strength of concrete, a reduction of 4.34% was observed for 15% AGR and 5.72% for 30%, suggesting that the variations may be due to factors such as the water/cement ratio, the quality of the aggregate, and the curing conditions of concrete. In addition, several pathologies were observed, such as cracking, fissures, color changes, and spalling. Full article

NOTCH1 is associated with various tumors, including oral squamous cell carcinoma (OSCC), with a complex role depending on cellular contexts. Our aim was to analyze the expression of NOTCH1, several stem cell markers, and selected microRNAs in preneoplastic lesion of the oral cavity, oral epithelial dysplasia (OAD). Our study included formalin-fixed paraffin-embedded biopsy samples of 36 cases of OAD and 15 cases of normal oral mucosa. Expression of NOTCH1, stem cell markers (AGR2, KLF4, NANOG, OCT4, SOX2), and miR-27a, miR-34a, miR-128, miR-145, miR-150, and miR-335 was analyzed by quantitative PCR (qPCR). Expression of NOTCH1 protein was analyzed by immunohistochemistry. In OAD compared to normal mucosa, we found a significant increase in mRNA levels of NOTCH1, stem cell markers AGR2, NANOG, OCT4, and SOX2, and miR-150 and miR-128. NOTCH1 mRNA positively correlated with all five stem cell markers’ mRNA levels and miR-150. Immunohistochemistry showed variable expression patterns of NOTCH1 in OAD and normal mucosa. Our results support the role of NOTCH1 in early phases of OSCC development, with a potential contributory role in stemness, in association with AGR2, NANOG, OCT4, and SOX2, miR-150 and miR-128. These results support a complex role of NOTCH1 in carcinoma development, i.e., from oncogenic to tumor suppressor roles and stemness maintenance, not only in invasive OSCC but also in its precursor—OED. Full article

Background/Objectives: Staphylococcus aureus virulence is tightly regulated by the agr (accessory gene regulator) quorum-sensing system. Targeting AgrC, the histidine kinase receptor that serves as a core regulator of agr signaling, represents a promising antivirulence strategy that circumvents conventional bactericidal pressure. Methods: In this study, structure-based virtual screening using AutoDock Vina was performed, followed by molecular dynamics simulations, to identify potent analogs of known AgrC inhibitors. Results: A cyclo[Ala-Phe-OLeu-Phe-D-Leu] exhibiting high binding affinity and stable receptor interaction was selected for further evaluation. Antimicrobial susceptibility testing confirmed that the compound did not inhibit bacterial growth. However, at a concentration of 16 µg/mL, it significantly inhibited hemolytic activity with high reproducibility, and the inhibition rate reached 77.60%. Quantitative reverse transcription PCR (RT-qPCR) demonstrated that the compound decreased some key AgrC-mediated genes, including agrC, agrA, saeS, hla, spa, fnbA, and lukS. Conclusions: These findings identify a promising cyclic pentapeptide inhibitor of AgrC that effectively attenuates S. aureus virulence without exerting bactericidal pressure. This work provides a valuable lead compound and offers novel insights for the development of advanced, safe, and effective antivirulence therapeutics. Full article

Accurate preoperative diagnosis of periprosthetic joint infection (PJI) is difficult, complicating distinction between septic and aseptic failures. This study assessed the value of common serum biomarkers and three calculated ratios—albumin–globulin ratio (AGR), C-reactive protein–albumin ratio (CAR), and C-reactive protein–AGR ratio (CAGR)—in diagnosing PJI after primary total hip arthroplasty (THA). We retrospectively reviewed patients undergoing revision THA for PJI or aseptic failure from 2011 to 2021 at a single institution. Inclusion required reported serum white blood cell count (WBC), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), albumin (Alb), and total protein (TP). Diagnostic performance was evaluated using areas under the curve (AUCs), with higher values indicating better accuracy. Ratios were defined as: AGR = Alb/[TP − Alb], CAR = CRP/Alb, and CAGR = CRP/AGR. Among 128 cases, 67 were PJI and 61 aseptic. AUCs were: WBC (0.53), CRP (0.69), ESR (0.75), Alb (0.69), Glb (0.63), TP (0.53), AGR (0.72), CAR (0.70), and CAGR (0.71). Optimal cutoff, sensitivity, and specificity were: CRP (10.5, 0.76, 0.59), ESR (41.0, 0.70, 0.72), AGR (1.10, 0.64, 0.75), CAR (3.37, 0.73, 0.64), and CAGR (10.9, 0.75, 0.66). ESR, AGR, CAR, and CAGR demonstrated acceptable accuracy. These readily available markers and ratios may aid PJI diagnosis, supporting improved clinical decision-making. Full article

This study aimed to assess the phenotypic changes in tetraploids of two gooseberry genotypes (‘White Triumph’ and AGR9, 2n = 4x = 32) in relation to their diploid counterparts (2n = 2x = 16). Tetraploid plants of the ‘White Triumph’ cultivar were characterized by lower growth dynamics than the diploid (control) plants, with the exception of clone A7/2-4x, whose height was increased. Tetraploid plants from three AGR9 gooseberry clones exhibited enhanced growth dynamics compared to control plants. The stomatal length of tetraploid gooseberry genotypes was greater than that of the control, but the stomatal density was lower in tetraploids. The leaf blades and petiole lengths of the tetraploid, ‘White Triumph’, and AGR9 plants were significantly larger than those of their diploid counterparts. Almost all nine evaluated anatomical traits (upper and lower epidermis thickness, palisade and sponge tissue thickness, amount of intercellular spaces, midrib diameter, phloem and xylem thickness, and surface of midrib cells) of the leaves in tetraploids were significantly greater than those of their diploid counterparts. Principal component analysis (PCA) distinguished genotypes according to the ploidy level. The first two principal components explained 74.8% of the total variance, with PC1 (49.99%) representing the primary axis separating diploid (2x) and tetraploid (4x) genotypes. To the best of our knowledge, there have been no published reports on the phenotypic assessment of gooseberry tetraploids. The vigorous gooseberry tetraploids characterized in this study are likely the first of their kind to be reported. Full article

The environmental and social crises affecting global agri-food systems highlight the need for a profound transformation of production models and their territorial relations. In this context, agroecology, understood as science, practice, and movement, has emerged as a paradigm capable of integrating ecological sustainability, social equity, and community participation. Within this framework, the work carried out by CREA in the AgrEcoMed project (new agroecological approach for soil fertility and biodiversity restoration to improve economic and social resilience of Mediterranean farming systems), funded by the PRIMA programme, investigates agroecology as a social and political process of territorial regeneration. This process is grounded in co-design with local stakeholders, collective learning, and the construction of multi-actor networks for agroecology in the Mediterranean. The Manifesto functions as a tool for participatory governance and value convergence, aiming to consolidate a shared vision for the Mediterranean agroecological transition. The article examines, through an analysis of the existing literature, the role of agroecological networks and empirically examines the function of the collective co-creation of the Manifesto as a tool for social innovation. The methodology is based on a participatory action-research approach that used local focus groups, World Café, and thematic analysis to identify the needs of the companies involved. The results highlight the formation of a multi-actor network currently comprising around 90 members and confirm the effectiveness of the Manifesto as a boundary object for horizontal governance. This demonstrates how sustainability can emerge from dialogue, cooperation, and the co-production of knowledge among local actors. Full article

Methicillin-resistant coagulase-negative staphylococci (MRCoNS) are a major cause of infectious diseases, owing to their ability to form biofilms and colonize community and hospital environments. MRCoNS strains were identified using biochemical tests, an MALDI-TOF MS analyzer, and PCR-based 16S rRNA gene confirmation. This study was designed to assess antibiotic resistance and biofilm-forming capacity and to determine the presence of the mecA, mecC, agrA, srtA, icaABCD, bap, fnbAB, and clfAB genes in MRCoNS isolates. From patients undergoing random screening during hospitalization in the Orthopedics Clinic in Slovakia, 28 strains of MRCoNS were identified: S. epidermidis (n = 10), S. hominis (n = 8), S. haemolyticus (n = 4), S. lugdunensis (n = 3), while S. simulans, S. pasteuri, and S. warneri were detected only once. The highest rates of resistance were observed for ampicillin, oxacillin, rifampicin, trimethoprim (100%), and erythromycin (62%). The mecA gene was detected in 12 analyzed isolates. In 12 isolates, MDR, strong efflux pump activity, and strong or moderate biofilm formation were simultaneously detected. Our findings highlight the problems posed by biofilm-forming, resistant CoNS in hospitalized patients and the importance of diagnostics, separation, rapid treatment, and proper hospital hygiene. Full article

When forest fires occur, timely detection and initial attack are critical for fire prevention. This study focuses on optimizing the cruise path of Unmanned Aerial Vehicles (UAVs) from the perspective of initial attack. It aims to maximize coverage of regions where initial attack success rates are low, shorten the time taken to detect fires, and, in turn, boost detection effectiveness and the initial attack success. In this paper, a path planning strategy, Improved Multi-Objective Crested Porcupine Optimizer (IMOCPO), is proposed. This strategy employs a weighted sum approach to formulate a composite objective function that balances global search and local optimization capabilities, considering practical requirements such as UAV endurance and uneven distribution of risk areas, thus enhancing adaptability in complex forest environments. The weight selection is justified through systematic grid search and validated by sensitivity analysis. The proposed strategy was compared and evaluated with a related strategy using four metrics: high-risk coverage rate, grid coverage rate, Average Distance Risk (ADR), and Average Grid Risk (AGR). Results show that the proposed path planning strategy performs better in these metrics. This study provides an effective solution for optimizing UAV cruise strategies in forest fire monitoring and has practical significance for improving the intelligence of forest fire prevention. Full article

Rhododendron tomentosum is an aromatic plant belonging to the Ericaceae family, widely used for different applications, but still lacking in its molecular signature. This work provides a complete chemical and biological characterization of the hydroalcoholic extract of R. tomentosum tips of twigs. Combining untargeted metabolomic analysis with bioassays, a correlation between chemical composition and biological activity was defined. To this regard, liquid chromatography high-resolution tandem mass spectrometry (LC-MS/MS) revealed a heterogeneous chemical composition, including flavonoids, such as quercetin, catechin, and their derivatives, as well as a first tentative identification of novel aesculin derivatives. Cell-based model experiments on stressed immortalized human keratinocytes demonstrated the antioxidant activity of the extract. Moreover, it exhibited significant antifungal and antibacterial effects against Trichoderma atroviride AGR2, Botrytis cinerea, and Clavibacter michiganensis, while promoting the growth of the beneficial bacterium Bacillus amyloliquefaciens. These findings highlight the rich diversity of bioactive molecules present in R. tomentosum hydroalcoholic extract, bridging its chemical composition to its functional properties. Overall, these results suggest its promising potential for applications in improving plant health, as well as in pharmaceutical, cosmetic, and agricultural industries. Full article

Background: Infections caused by Staphylococcus aureus are a health problem worsened by antibiotic resistance. New drugs, including those inhibiting virulence and resistance mechanisms, are needed. This study aimed to evaluate the anti-growth, anti-virulence, and anti-biofilm activities of Trametes villosa. (2) Methods: Fractions were obtained from the basidiomata of T. villosa. Anti-growth, anti-hemolysis, and anti-biofilm activities were tested against S. aureus strains using resazurin microtiter, blood cell lysis, and crystal violet assays, respectively. Cytotoxicity was evaluated in Vero and HaCaT cells using sulforhodamine B. The active fractions were subjected to GC-MS analysis and molecular docking with S. aureus quorum-sensing receptors. Results: The n-hexane and ethyl acetate (EtOAc) fractions exhibited anti-growth activity against all strains (MIC: 31.2–2000 µg/mL). These fractions also displayed anti-hemolysis (IC₅₀ = 33.8 ± 1.1–53.8 ± 5.1 µg/mL) and anti-biofilm formation activity (IC₅₀ = 106.6 ± 4.8–383.4 ± 31.4 µg/mL), while exhibiting low cytotoxicity in Vero and HaCat. GC-MS analysis revealed that both active fractions mainly contained alkanes, aldehydes, and fatty acids. Molecular docking revealed that isovanillic acid, identified in the EtOAc fraction, exhibited optimal interactions with S. aureus quorum-sensing receptors AgrA and SarA. (4) Conclusions: Our research highlights the potential of T. villosa as a source of bioactive compounds effective against S. aureus. Full article

Background: Ovarian cancer is characterized by high mortality rates, primarily due to diagnosis at late stages. Current biomarkers, such as CA125, have demonstrated limited efficacy for early detection. While high-dimensional proteomics offers a more comprehensive view of systemic biology, the analysis of such data, where the number of features far exceeds the number of samples, presents a significant computational challenge. Methods: This study utilized a nested case–control cohort of longitudinal pre-diagnostic serum samples from the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) profiled for eight candidate ovarian cancer biomarkers (CA125, HE4, PEBP4, CHI3L1, FSTL1, AGR2, SLPI, DNAH17) and 92 additional cancer-associated proteins from the Olink Oncology II panel. We employed a Synolitic Graph Neural Network framework that transforms high-dimensional multi-protein data into sample-specific, interconnected graphs using a synolitic network approach. These graphs, which encode the relational patterns between proteins, were then used to train Graph Neural Network (GNN) models for classification. Performance of the network approach was evaluated together with conventional machine learning approaches via 5-fold cross-validation on samples collected within one year of diagnosis and a separate holdout set of samples collected one to two years prior to diagnosis. Results: In samples collected within one year of ovarian cancer diagnosis, conventional machine learning models—including XGBoost, random forests, and logistic regression—achieved the highest discriminative performance, with XGBoost reaching an ROC-AUC of 92%. Graph Convolutional Networks (GCNs) achieved moderate performance in this interval (ROC-AUC ~71%), with balanced sensitivity and specificity comparable to mid-performing conventional models. In the 1–2 year early-detection window, conventional model performance declined sharply (XGBoost ROC-AUC 46%), whereas the GCN maintained robust discriminative ability (ROC-AUC ~74%) with relatively balanced sensitivity and specificity. These findings indicate that while conventional approaches excel at detecting late pre-diagnostic signals, GNNs are more stable and effective at capturing subtle early molecular changes. Conclusions: The synolitic GNN framework demonstrates robust performance in early pre-diagnostic detection of ovarian cancer, maintaining accuracy where conventional methods decline. These results highlight the potential of network-informed machine learning to identify subtle proteomic patterns and pathway-level dysregulation prior to clinical diagnosis. This proof-of-concept study supports further development of GNN approaches for early ovarian cancer detection and warrants validation in larger, independent cohorts. Full article