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Klebsiella pneumoniae is an opportunistic pathogen associated with both community-acquired and nosocomial infections. Multidrug-resistant (MDR) strains are increasingly implicated in urinary tract infections (UTIs), traveller’s diarrhoea, bacteraemia, and sepsis. β-lactam antibiotics are commonly used for treatment; however, antimicrobial resistance has emerged largely due to the production of extended-spectrum β-lactamases (ESBLs), which confer resistance mainly to penicillins, oxyimino-cephalosporins, and monobactams, while cephamycins and carbapenems usually remain stable to ESBL-mediated hydrolysis and compromise therapeutic efficacy. ESBL-producing strains represent a major cause of severe Gram-negative infections. This study aimed to determine the prevalence of ESBL-producing K. pneumoniae among UTI patients in Jordanian hospitals (Al Mafraq, Ma’an, and Islamic Hospitals), evaluate their antimicrobial susceptibility patterns, and detect antimicrobial resistance genes at the molecular level. A total of 450 urine isolates of K. pneumoniae were collected from UTI patients between November 2023 and May 2024. Isolates were identified in hospital laboratories using standard microbiological methods. Antimicrobial susceptibility testing was performed, and molecular characterisation of ESBL-associated genes was conducted using polymerase chain reaction (PCR). Out of 450 K. pneumoniae isolates collected from UTI patients across three Jordanian regions, 72 (16%) were confirmed as ESBL producers. Among the 72 ESBL-positive K. pneumoniae isolates, 34 (47.2%) were recovered from the Central region, 20 (27.8%) from the North, and 18 (25.0%) from the South. Molecular analysis revealed that 41.7% of ESBL-producing isolates carried the blaCTX-M gene, while 33.3% harboured the blaOXA gene. All ESBL-producing isolates demonstrated antimicrobial resistance to third-generation cephalosporins. A significantly higher proportion of ESBL-producing isolates was identified in female patients (84.7%) compared with males (15.3%). A significant association was observed between blaOXA gene distribution and geographic region (p = 0.016), whereas blaCTX-M gene distribution showed no significant regional association. ESBL-producing K. pneumoniae accounted for a substantial proportion of UTI isolates in Jordan, with blaCTX-M identified as the predominant resistance gene. The higher burden observed in the Central region and among female patients highlights notable distribution patterns in this cohort. These findings emphasise the necessity for sustained molecular surveillance and strengthened antimicrobial stewardship strategies to limit the dissemination of ESBL-producing strains in Jordanian healthcare settings. Full article

As artificial intelligence reshapes professional workflows, understanding what drives effective AI use among employees has become a critical concern for organizations. Moving beyond traditional technology acceptance frameworks, this study develops an integrative multi-level model to examine the behavioral determinants of AI use performance (AUP) among journalists. Drawing on the Technology Acceptance Model (TAM) and the Expectation Confirmation Model (ECM) and incorporating individual and organizational factors, a survey was conducted among 543 journalists in China. Hypotheses are tested via a hybrid PLS-SEM and artificial neural network (ANN) approach to capture both linear and non-linear relationships. The findings reveal that expectation confirmation significantly enhances AUP by driving perceived usefulness and satisfaction. Digital literacy, personal trust in AI, and organizational support positively influence AUP, whereas communication barriers exert the strongest negative effect. Demographic variables (gender, age, education) show no significant impact. Notably, the ANN sensitivity analysis identifies communication barriers as the most influential predictor overall, a finding not apparent from linear analysis alone. This study advances theoretical understanding of employee behavioral responses in AI-integrated professional contexts and offers practical insights into how organizations can foster effective employee–AI collaboration through targeted communication strategies and supportive infrastructure. Full article

The scientific evidence regarding the use of plant-derived extracts to alleviate exercise-induced muscle damage in horses remains limited. Mulberry leaf flavonoids (MLFs) are the primary bioactive constituents of a traditional medicinal plant and are potent antioxidants. The aim of this study was to investigate the protective effects of MLFs against exercise-induced muscle damage. In this study, twelve Mongolian horses were used in a 3 × 3 Latin square design to investigate the protective effects of MLFs. Our results showed that high-intensity exercise negatively impacted the immune status, metabolic state, myofibrillar structure, and antioxidant capacity of the horses. Conversely, MLFs significantly reduced blood levels of white blood cells (WBC), monocytes (MON), aspartate aminotransferase (AST), creatine kinase (CK), and malondialdehyde (MDA) across various exercise distances and during recovery. Simultaneously, MLFs increased serum glutathione peroxidase (GPx), superoxide dismutase (SOD), and total antioxidant capacity (T-AOC). Mechanistically, transcriptomic analysis revealed that dietary MLFs upregulated genes associated with myofibrillar structural proteins (MYOZ2, MYOM3), the antioxidant defense system (GPX3, SOD3), and skeletal muscle satellite cell proliferation and differentiation (MYOD1, MRF6). Furthermore, quantitative proteomics indicated the enrichment of the PI3K-Akt and TGF-β signaling pathways, as well as ECM–receptor interactions, suggesting their potential involvement in regulating protein metabolism and facilitating myofibrillar restoration. Overall, MLFs effectively alleviated inflammation, metabolic disorder, and exercise-induced muscle damage. Under the tested conditions, a daily dosage of 10 g MLFs provided superior protective effects. Full article

In the assessment of bearing capacity for in-service bridge pile foundations, static load tests are costly, destructive, and difficult to scale. The traditional dynamic formula approach relies heavily on an empirical dynamic–static conversion coefficient that introduces considerable uncertainty. To address these limitations, this study proposes a non-destructive evaluation method for pile foundation bearing capacity based on measured dynamic stiffness and machine learning algorithms. Using data from a highway bridge inspection project, a dataset comprising 680 piles was compiled, including measured dynamic stiffness, geometric parameters, and design load information. An end-to-end binary classification model was constructed to map multidimensional physical features to an engineering decision target, namely, whether the bearing capacity meets the design requirement. The performance of several algorithms was compared, including logistic regression, random forest, and gradient boosting decision tree (GBDT). Among the evaluated models, the GBDT model demonstrated the best capability for capturing the complex nonlinear pile–soil interactions. On an independent test set, it achieved an accuracy of 96.3% and an F1 score of 0.96, with a very low false-negative rate, satisfying the high precision required for engineering safety screening. Feature importance analysis indicates that measured dynamic stiffness contributed approximately 42% to the classification outcome, establishing it as the dominant indicator for detecting capacity deficiencies and reinforcing its physical relevance as a key health indicator for pile foundations. This study demonstrates that data-driven methods can effectively circumvent the uncertainty associated with traditional empirical coefficients, providing a promising approach to the health monitoring and rapid evaluation of in-service bridge pile foundations. Full article

Background/Objectives: Sentinel lymph node biopsy is central to axillary staging in breast cancer, but conventional mapping often relies on radioisotopes and/or blue dye. Indocyanine green fluorescence has emerged as an alternative, although evidence for its use as a sole tracer in routine practice remains limited. This study evaluated the technical feasibility, lymph node yield, nodal metastasis detection, and short-term clinical outcomes of indocyanine green used as the only tracer for axillary staging in a consecutive single-centre cohort. Methods: This retrospective observational cohort study included 260 patients with histologically confirmed breast cancer who underwent axillary surgery at University Hospital Kaspela between 2024 and 2025 under an institutional protocol using indocyanine green as the sole tracer. Indocyanine green-guided mapping was attempted in all patients. For node-focused statistical analyses, a predefined complete-case–cohort of 230 patients was used. Descriptive analyses assessed axillary procedure distribution, lymph node yield, nodal metastasis, and postoperative outcomes. Exploratory multivariable logistic regression was performed to evaluate predictors of nodal metastasis. Results: Mapping was successful in 259/260 patients (99.6%). In the complete-case–cohort, sentinel lymph node biopsy was performed in 166/230 patients (72.2%), targeted axillary dissection in 4/230 (1.7%), and axillary lymph node dissection in 60/230 (26.1%). Median overall lymph node yield was 4 (IQR 3–7), but this pooled value reflected heterogeneous axillary procedures and should not be interpreted as sentinel node yield alone. In the clinically node-negative upfront SLNB subgroup, median lymph node yield was 4 (IQR 2.75–5), and nodal metastasis was identified in 22/112 patients (19.6%). Overall, nodal metastasis was identified in 58/230 patients (25.2%), with a median of 2 metastatic nodes (IQR 1–3) among nodal-positive cases. Reoperation for axillary lymph node dissection occurred in 14/230 patients (6.1%). In exploratory multivariable analysis, suspicious biopsied-positive nodes (OR 12.85, 95% CI 3.98–41.52), suspicious non-biopsied nodes (OR 15.58, 95% CI 3.44–70.59), and neoadjuvant therapy (OR 0.31, 95% CI 0.11–0.87) were associated with nodal metastasis; these findings should be interpreted cautiously given the expected clinical relationship between preoperative nodal suspicion and nodal positivity, and the limited number of nodal-positive events. Conclusions: Indocyanine green used as a sole tracer demonstrated high technical feasibility within a heterogeneous real-world axillary staging workflow in this single-centre cohort. These findings should be interpreted as implementation-focused feasibility data rather than formal diagnostic validation, given the retrospective design, heterogeneous case mix, and absence of an internal comparator. Full article

This study investigates whether aerodynamic interaction effects in an interlocked (negative-gap) counter-rotating dual Savonius rotor configuration can improve the efficiency of drag-based vertical-axis wind turbines in urban wind conditions. Two-dimensional Computational Fluid Dynamics (CFD) simulations were performed in ANSYS Fluent 2025 R2 using both steady and unsteady RANS approaches, including dynamic meshing to enable collision-free rotation in the interlocked overlap region. The numerical setup was first validated for a single two-bucket reference rotor against published experimental data of torque and power coefficients and subsequently applied to dual-rotor configurations with negative gap distances. The results show that the dual-rotor arrangement redistributes torque production over the azimuth angle and yields a smoother and consistently positive mean static torque coefficient, indicating improved self-starting behavior compared to the single rotor. Under transient operation, the dual-rotor configuration yields higher power coefficient values across the entire investigated tip-speed ratio range. The highest performance gain is observed at a tip-speed ratio of $\lambda \approx 1.0$, where the peak power coefficient increases from $c_p\approx 0.25$ (single-rotor) to $c_p\approx 0.32$ (dual-rotor), corresponding to an improvement of the power coefficient of about $\Delta c_p/c_{p0}\approx 28\%$. Full article

To enrich the breeding resources of Xanthoceras sorbifolium and provide support for its industrialization, we conducted multi-trait comparisons and comprehensive evaluations of 48 elite X. sorbifolium clones with high oil contents and high comprehensive utilization values, based on germplasms preserved at Qiuxian Forest Farm, Handan, Hebei Province, China. The coefficients of variation for quantitative traits were 7.04–74.16%, with variability being greatest in shell and fruit weights. Cluster analysis categorized the 48 germplasms into four distinct groups, with marked inter-group trait differences. Soluble protein, soluble sugar, and starch contents varied significantly among accessions. The average kernel oil content was 60.30%, differences in oil content were validated at the cellular level through microscopic oil body observations. Correlation analysis demonstrated that comprehensive oil content was strongly significantly positively correlated with fruit- and seed-related traits, whereas oil content was strongly significantly negatively correlated with fruit shell thickness and seed coat thickness. Principal component analysis extracted five principal components with a cumulative contribution rate of 72.747%, encapsulating four core information dimensions: fruit and seed size, oil content, protein quality, and energy substances. Membership function analysis, selected germplasms G10, G2, G4, G7, G20, G24, G17, G, G34, and G5 as optimal accessions. These clones are suitable core breeding materials due to their outstanding performance in terms of nutrient content, geometric characteristics, and fruit and seed weights. Notably, G24, G5, and G17 demonstrated significant advantages in oil quality with high linoleic acid (C18:2), oleic acid (C18:1), and nervonic acid (C24:1) contents, respectively, indicating the excellent potential of X. sorbifolium development for oil production. Full article

Genetic resources of small ruminants are essential for food security in arid regions; however, basic data for each breed in Saudi Arabia remain incomplete. This study establishes a comprehensive national database through a systematic survey of 104 farms, covering 21,214 heads of livestock (sheep and goats) across the kingdom’s primary agro-ecological zones between January and October 2025. Although national census data indicate that major breeds of sheep such as Naeemi, Najdi, Arabi, and Harri or goats such as Ardi exceed the FAO’s numerical thresholds for “not at risk,” our analysis reveals a fundamental paradox of “genetic vulnerability,” defined as a high risk of inbreeding depression and genetic stagnation despite high census numbers. The results show significant regional variations in prolificacy (p < 0.05), with the southern region displaying a substantial productivity gap compared to the central and eastern regions, mainly due to reliance on traditional grazing (46.7%) and limited infrastructure. This vulnerability is driven by a high risk of systematic inbreeding, with 65.7% of breeders acquiring sires from their own herds, a situation worsened by a severe 80% shortage of high-quality breeding males in the central region. Furthermore, selection criteria heavily emphasize esthetic phenotypic traits (over 80%) rather than production indicators (less than 8%), hindering genetic progress. Correlation analysis showed that higher farmer education levels were negatively associated with reproductive challenges (r = −0.216), while high feed prices remained a near-universal obstacle (97.1%). To mitigate these risks, we recommend implementing region-specific sire exchange programs to break closed breeding loops and establishing a national performance recording system to shift selection focus from phenotypic traits to measurable productivity. This study provides a vital, evidence-based framework for transitioning toward data-driven, resilient conservation and breeding strategies. Full article

The emerging threat of antibiotic-resistant pathogens and the limitations that conventional cancer chemotherapies display have created an urgent need for the development of innovative therapeutic strategies. Combining the pleiotropic biological roles of antimicrobial peptides (AMPs) and nanomaterials through their conjugation presents a promising possibility of targeting both microbial membranes and malignant cells. In the present study, we engineered a novel bioactive material by immobilizing the insect-derived AMP Papiliocin onto multi-walled—decorated with polyethylene–glycol—carbon nanotubes (PEG-MWCNTs) to prevent proteolytic degradation of the peptide and enhance its cellular delivery. Recombinant Papiliocin was cloned, heterologously expressed, purified and conjugated onto the PEG-MWCNT carrier. Successful expression and conjugation were validated via immunoblotting and Fourier transform infrared (FT-IR) spectroscopy, respectively. Further physicochemical characterization of the bionanocomposites was conducted using Dynamic Light Scattering (DLS) and Zeta potential measurements. Biologically, the biofunctionalized material exhibited potent, broad-spectrum antimicrobial activity both on Staphylococcus aureus and Escherichia coli, inhibiting almost 90% of the latter’s growth, highlighting the bioconjugate’s specific interactions with the Gram-negative pathogens’ membranes. Furthermore, it significantly reduced biofilm formation in Candida albicans, as indicated by the TCP assay. In parallel with its antimicrobial effects, CNTs-PEG–Papiliocin significantly reduced cancer cell viability and induced apoptosis via the extrinsic apoptosis pathway in HeLa cells, a response assisted by efficient intracellular delivery. Notably, cytotoxicity assays demonstrated lesser cytotoxic effect against non-tumorigenic HaCaT cells relative to the cancerous cell line. Collectively, these findings indicate the Papiliocin–biofunctionalized CNTs as a versatile, dual-action therapeutic agent with potential for antimicrobial activity and anticancer mode of action. Full article

This study investigated the effects of dietary nano-antimicrobial peptides (NAP) on the microbial communities and metabolic profiles in Tibetan sheep. Using 16S rRNA gene high-throughput sequencing and non-targeted metabolomics, the contents of the small intestine, rumen, and rectum were systematically analyzed in a control group (Group A) and a NAP-supplemented group (Group B). Multi-omics integration methods, including O2PLS and Pearson correlation analysis, were employed to explore the association between microbial communities and metabolites. Alpha and beta diversity analyses revealed significant differences (p < 0.05) in the microbial community structure of the small intestine between the two groups. In contrast, the rumen and rectal microbiota remained relatively stable, indicating that the regulatory effects of NAP on the intestinal microecology are site-specific. In the small intestine, NAP altered the composition of dominant functional microbiota and the abundance of taxa related to energy metabolism. Metabolomic analysis identified significant shifts in metabolic profiles, specifically within the bile acid, fatty acid, and phospholipid pathways (p < 0.05). Group A exhibited baseline steady-state characteristics (e.g., cholic acids and phospholipids), whereas Group B showed activation of unsaturated fatty acids and related metabolites. Multi-omics integration revealed a stable systematic association between intestinal microbial genera and metabolites. Specifically, bile acid and prostaglandin metabolites were negatively correlated with Firmicutes-related taxa. These findings suggest that NAP supplementation may contribute to maintaining host energy metabolism and intestinal homeostasis by regulating intestinal microecology. Full article

Bordetella petrii is an environmentally versatile Gram-negative bacterium with hydrocarbon-degrading capabilities, yet its genetic and metabolic characteristics remain poorly characterized. This study investigated the genomic features of a PAH-degrading Bordetella petrii strain P003 isolated from contaminated oil in Kuwait using bioinformatic approaches. The genome of B. petrii P003 was sequenced and analyzed for genomic islands, comparative genomics, and PAH degradation pathways. The draft genome assembly of B. petrii P003 was 5,011,660 bp with 49 contigs and 68.67% GC content. It contained 4687 coding sequences, 5 rRNAs, and 56 tRNAs. Prediction of genomic islands (GIs) revealed that strain P003 possessed 99 GIs, whereas the reference B. pertii DSM 12,804 had 58 unique GIs. Comparative genomics showed 279 locally collinear blocks with the reference strain. The P003 genome encoded multiple genes involved in PAH, naphthalene, and benzoate degradation pathways, including an 8-gene PAH operon (pht4, ph2, pht5, pht3, pcaG, pcaH, nahAb/nagAb/ndoA/nbzA). We found that pcaG and pcaH encode the enzymes responsible for the breakdown of PAH, protocatechuate 3,4-dioxygenase, alpha and beta subunits (EC: 1.13.11.3). The genomic analysis of B. petrii P003 provides insights into its PAH degradation capabilities and potential for bioremediation applications. The strain possesses an expanded repertoire of aromatic compound degradation genes compared to reference strains, suggesting enhanced metabolic versatility for degrading environmental pollutants. Full article

Environmental, Social, and Governance (ESG) performance has become critical for businesses seeking transparency, sustainability, and stakeholder confidence. However, the extant evidence is equivocal regarding its influence on company performance. Corporate governance may play an important role in determining the efficacy of ESG efforts. Hence, this research investigates the relationship between corporate governance and firm performance, focusing on the moderating role of ESG performance, using unbalanced panel data from 370 Malaysian firms for the period from 2012 to 2023. For analysis of the data, fixed effects estimation, Driscoll–Kraay robust standard errors, and a subsample analysis were used. The results reveal that board expertise and independence enhance firm performance, whereas board gender diversity negatively affects market valuation (Tobin’s Q). Similarly, audit committee expertise shows a negative effect. Further, the results reveal that ESG strengthens the role of board expertise but weakens the influence of audit committee independence. This study offers practical and theoretical insights for policymakers, scholars, and stakeholders seeking to balance sustainability with financial performance, bridging a notable gap in the literature by thoroughly examining the relationship between board gender diversity and ESG performance, and how it affects company performance. This reveals new insights into the strategic significance of diverse leadership in promoting both financial and non-financial results by bridging the gap between corporate governance and sustainability. Full article

Periodic time-series forecasting is central to 6G-enabled urban digital twins, where both cellular traffic management and environmental sensing demand accurate predictions over recurring diurnal and weekly regimes. Contrastive self-supervised learning has emerged as a promising approach for learning temporal representations, yet when applied to such periodic data, it suffers from class collision: temporally distant but semantically similar recurrent patterns are pushed apart as false negatives. We propose Clustering-Enhanced Contrastive Learning (CECL), which couples temporal contrastive learning with a clustering regularizer that maintains a Gaussian mixture structure over the latent space, preserving global periodic structure while retaining local discriminability. We evaluate CECL on five datasets across three tracks spanning two domains: cellular traffic forecasting (Milan CDR, 20 cells), multi-site hourly air-quality forecasting (Beijing Multi-Site, 12 stations; QUANT, 3 cities), and daily air-quality forecasting (Haikou and Taizhou). Across all tracks, CECL consistently outperforms supervised and contrastive baselines, reducing RMSE by 3–$10\%$ relative to the strongest contrastive competitor (CoST). These results demonstrate that clustering-guided contrastive regularization yields robust gains for periodic forecasting in both 6G network management and environmental sensing scenarios. Full article

Background/Objectives: Non-celiac gluten sensitivity (NCGS) is a syndrome characterized by intestinal and extraintestinal symptoms triggered by gluten ingestion. Although anti-gliadin IgG antibody (AGA IgG) has been proposed as a potential biomarker for NCGS, its sensitivity and specificity in real-world clinical settings remain unclear. This study aimed to evaluate the clinical utility of AGA IgG in NCGS and to characterize its clinical features, including psychological distress and physical quality of life (QOL), in patients with clinically suspected NCGS attending a specialized outpatient unit in Japan, where patients reported symptoms related to the ingestion of gluten-containing grains (primarily wheat). Methods: We evaluated plasma AGA IgG levels in 45 patients with suspected NCGS based on clinical presentation and in 83 age- and sex-matched healthy controls. Plasma AGA IgG was measured using ELISA. Clinical symptoms and QOL were assessed using validated scales, including the 36-Item Short Form Health Survey (SF-36), Patient Health Questionnaire (PHQ-9 and PHQ-15), Generalized Anxiety Disorder-7 (GAD-7), and the Japanese version of the Irritable Bowel Syndrome Quality of Life measure (IBS-QOL-J). Results: The AGA IgG positivity rate was significantly higher in the suspected NCGS group (33.3%) than in the control group (13.3%; p < 0.01). Using clinical suspicion as the reference, the sensitivity and specificity of AGA IgG were 33.3% and 86.7%, respectively. Patients with suspected NCGS exhibited significantly lower physical and mental QOL and higher scores for depressive, anxiety, and somatic symptoms compared to controls. No significant clinical differences were found between AGA IgG-positive and IgG-negative individuals within the suspected NCGS group. Conclusions: AGA IgG demonstrated a specificity of 86.7% and a sensitivity of 33.3% for suspected NCGS, indicating its limited utility as a standalone biomarker. These findings suggest that suspected NCGS involves significant somatic and psychological burdens regardless of serological status. Future studies should explore whether a multi-marker panel could improve the identification of “True NCGS” in diverse clinical populations. Full article

Written feedback on high-stakes assessment has the potential to provide students with valuable advice for future assessment episodes, but when feedback has a negative impact on students’ emotions, it can negate any benefits. This exploratory study reports on the perceptions of 14 lecturers and 19 students regarding their emotions toward written assessment feedback within a university preparatory program for students at a regional university in Australia. Focus groups were used to collect data from the participants. The data were analysed with NVivo Version 11 software. The data were further analysed by the authors, who identified and categorised phrases pertaining to students’ and lecturers’ emotions about feedback. The study found that lecturers and students had mixed feelings about written feedback, especially when personal connections between lecturers, other staff, and students were tenuous. It concluded that further research focusing on the impact of emotions on how students perceive written feedback and apply it in future assessments could provide insights into how to enhance contemporary tertiary teaching and assessment practices. Full article