Search Results (263,793)

Background/Objectives: Enteroviruses (EV) cause neonatal infections with variable incidence and severity, occasionally progressing to invasive disease. This study reports the experience of two Italian neonatal centers with invasive neonatal EV infection (NEVI), describing management and outcomes in relation to the existing literature. Methods: This retrospective study included neonates diagnosed with NEVI. Data related to clinical symptoms, treatment and outcomes were reported and compared to those available in the current literature. Results: All nine neonates presented with systemic infection symptoms; onset ranged from the second to the thirty-fourth day of life, with eight of nine infants presenting after 72 h, most following readmission after initial discharge rather than continuous hospitalization from birth. The transmission route (vertical versus horizontal) could not be determined with certainty. All nine neonates had central nervous system infection confirmed by RT-PCR detection of EV in cerebrospinal fluid; two presented seizures or epileptiform abnormalities, and one developed myocarditis. IVIG was administered upon diagnosis. All infants survived to discharge in stable condition; neuroimaging abnormalities were documented in two infants, and long-term neurodevelopmental outcome could not be assessed in most patients due to incomplete follow-up. Conclusions: Invasive NEVI cannot be clinically differentiated from severe bacterial infection, warranting a high index of suspicion, particularly when caregivers report symptoms of viral infection. Further studies are needed to clarify aspects of management, including the potential benefit of IVIG administration. Full article

Addressing childhood obesity and premature pubarche together is critical for understanding the systemic and neurodevelopmental consequences of early endocrine stimulation in childhood. In this study, resting-state functional magnetic resonance imaging data from 11 children with premature pubarche (PP) and 7 children with both obesity and premature pubarche (OB + PP) were analyzed. Independent component analysis (ICA) was applied to identify spatially independent networks among participants. Significant components obtained from the ICA were used as seeds in the resting-state functional connectivity analysis (p < 0.001). When we examined our ICA results, we observed significant differences between our groups in 5 ICs. The regions showing differences between the groups largely overlapped with the Visual Network (VN), Dorsal Attention Network (DAN), Default Mode Network (DMN), and Salience Network (SN). In children with premature pubarche accompanied by obesity, increased functional connectivity was observed in the Posterior Cingulate Cortex (PCC) seed in the DMN and in the Anterior Cingulate Cortex (ACC) seed in the SN. Our findings suggest that PP is associated with altered functional connectivity in the DAN and SN. The observed differences in resting-state functional connectivity suggest that obesity may be associated with altered brain network organization within the premature pubarche population. However, these findings should be interpreted with caution, and longitudinal studies are needed to determine their developmental significance. Full article

In this study, a chitosan-based colloidal delivery system (CD) was developed as a natural delivery system for phenolic compounds from propolis extracts obtained via accelerated solvent extraction (ASE) and evaluated for improving the functional properties of walnut sausages. Propolis extract was incorporated into a chitosan (C)-based colloidal delivery system formulated with varying concentrations of diacetyl tartaric acid ester of mono- and diglycerides (DATEM) and lecithin (L). The formulation containing 2.5% chitosan, 12% DATEM and propolis, with a particle size of 265.9 nm and a ζ-potential of +40.8 mV, was selected for further characterization and food applications. The phenolic encapsulation of CD depended on the structural characteristics of individual phenolic compounds, with chrysin (70.51%), vanillin (65.12%), and benzoic acid (51.26%) exhibiting the highest encapsulation; CD-treated walnut sausage decreased the lipid oxidation and improved the storage stability of the walnut sausage during storage. These findings indicate that the chitosan-based colloidal delivery system is a promising carrier for improving the encapsulation of propolis phenolics in walnut sausage. Full article

Background: Autoantibodies are central to the diagnosis and risk stratification of systemic sclerosis (SSc), but their prevalence and clinical associations may vary across populations. This study aimed to evaluate the prevalence and immuno-clinical associations of different autoantibodies in the Rheumatic Diseases Portuguese Register systemic sclerosis cohort. Methods: This was a multicentre observational registry-based study that used data from the Reuma.pt SSc module. Patients were divided according to autoantibody status, and associations between autoantibody expression and clinical data were assessed using appropriate statistical tests, with Bonferroni correction applied for multiple comparisons. Multivariable binary logistic regression was performed for clinically relevant outcomes, with adjustment for sex, age at diagnosis and disease duration. Results: A total of 1080 patients were included, 87.5% female, with a mean age at last evaluation of 60.2 ± 14.6 years and a mean disease duration of 12.4 ± 10.0 years. Limited cutaneous SSc was the most frequent clinical category (57.4%), followed by diffuse cutaneous SSc (17.7%), very early diagnosis of systemic sclerosis (VEDOSS; 12.3%), overlap syndromes (9.8%) and SSc sine scleroderma (2.8%). Antinuclear antibodies were present in 93.4% of patients. Anti-centromere antibodies (ACAs) were the most frequent SSc-specific autoantibodies (54.6%), followed by topoisomerase I antibodies (ATAs; 21.8%). ACA positivity was associated with limited cutaneous disease; older age at diagnosis; and lower frequency of interstitial lung disease (ILD), myositis and flexion contractures. ATA positivity was associated with diffuse cutaneous disease, male sex, higher modified Rodnan skin score (mRSS), digital ulcers, flexion contractures, oesophageal involvement and ILD. Among less frequent autoantibodies, anti-Pm/Scl antibodies were associated with myositis, joint involvement, calcinosis and ILD; anti-U1RNP antibodies with younger age, MCTD overlap, myositis and joint involvement; anti-RNA polymerase III antibodies (ARAs) with scleroderma renal crisis and higher mRSS; anti-U3RNP antibodies with diffuse cutaneous disease and renal involvement; and anti-Ku antibodies with overlap syndromes. Conclusions: In this large real-world SSc cohort, autoantibody status was strongly associated with distinct clinical phenotypes, confirming its value for disease stratification. While most established immuno-clinical associations were reproduced, some differences from international cohorts were observed, supporting the need for population-specific validation of autoantibody associations in SSc. Full article

Decisions made during the pre-construction phase play a decisive role in the success of healthcare building projects. Although pre-construction critical success factors (CSFs) have received considerable research attention, few studies have transformed CSF-based expert ratings into a quantitative and interpretable performance index. This paper develops and applies a two-stage Mamdani Fuzzy Inference System (FIS) to assess pre-construction performance in healthcare building projects. Data were collected using an online survey completed by construction professionals experienced in healthcare projects. After excluding incomplete responses, careless responses, and multivariate outliers, 201 valid responses were retained. A total of 54 CSFs grouped into eight pre-construction domains were assessed on a five-point Likert scale. The Relative Importance Index (RII) values were calculated and utilized as fuzzy rule weights. In Stage A, CSF-level ratings were converted into eight group-level performance scores, and in Stage B, these scores were integrated to form a single Pre-Construction Healthcare Project Performance Index (PCHPPI). The model was developed in MATLAB R2025b and used five triangular membership functions. The results showed that the scores at group level varied from 63.9% for Technology and Digital Integration to 66.7% for Procurement Planning. The overall PCHPPI was 62.7%, classified as High. Sensitivity analysis was performed using alternate weightings, membership function settings, defuzzification techniques and ±5% input variations. The PCHPPI was classified as High in all examined situations, indicating that it is relatively robust to modest variations in model assumptions and input conditions. This indicates that healthcare pre-construction performance is generally satisfactory but remains closer to the lower boundary of the High classification, suggesting room for improvement. The PCHPPI and Performance Octagon provide a structured basis for performance assessment, diagnosis, and potential benchmarking across pre-construction domains, providing a practical assessment instrument for healthcare construction organizations and project teams. The proposed framework provides a structured decision-support approach for project readiness evaluation during the early planning of healthcare building projects. Full article

Important gaps remain in our understanding of the vaginal virome. Its composition, interactions with the bacterial microbiome and host immune system, and implications for vaginal homeostasis, human papillomavirus (HPV) persistence, and obstetric outcomes remain incompletely defined. The vaginal virome is a dynamic component of the female genital ecosystem. It includes viruses that infect human cells, bacteriophages, and endogenous viral elements. Observational studies have associated altered viral composition or diversity with vaginal dysbiosis, persistent HPV detection, and adverse pregnancy outcomes, including preterm birth. These relationships remain correlative, and causality has not been established. Bacteriophage-based therapies and recombinant endolysins may selectively target bacterial biofilms associated with bacterial vaginosis. However, most applications remain preclinical or in early clinical development. Better characterization of the interactions among viruses, bacteria, epithelial cells, and mucosal immunity may support future diagnostic biomarkers and precision therapeutic strategies in women’s health. Full article

Gummies have evolved from traditional confectionery products into hydrogel-based systems capable of incorporating and releasing bioactive compounds. This review examines the main formulation and technological factors governing their structure and functionality, with an emphasis on the use of hydrocolloids, alternative sweetening systems, and molecular interactions, the incorporation of bioactives, and the recent use of emerging technologies in their production. The literature was retrieved from Scopus, Web of Science, ScienceDirect, and Google Scholar, encompassing studies published between 2005 and August 2026. The literature shows that the type of hydrocolloid and the sweetener composition strongly influence gel formation, water mobility, hydrogen bonding, crystallization, texture, and storage stability. Plant byproducts, extracts, and marine-derived ingredients provide additional sources of bioactive compounds, while microencapsulation, nanoencapsulation, high-pressure processing, cryoconcentration, ultrasound, and 3D printing offer opportunities to enhance their protection and release. However, interactions between bioactive compounds and the gel matrix can affect texture, sensory acceptance, stability, and bioaccessibility. Therefore, developing functional gummies requires a comprehensive understanding of formulation, hydrogel structure, processing conditions, and bioactive stability to obtain products with suitable technological, sensory, and functional properties. Full article

Background: Receptor conversion following neoadjuvant therapy may alter eligibility for adjuvant systemic therapy in breast cancer. However, current guidelines provide limited recommendations for biomarker-guided treatment adaptation after receptor change. We aimed to characterize clinical decision-making after receptor conversion and identify a framework describing treatment adaptation across clinically relevant receptor conversion scenarios. Methods: A nationwide cross-sectional survey was conducted between August and September 2025 among Polish medical oncologists involved in breast cancer care. The questionnaire assessed receptor reassessment practices and treatment recommendations across five receptor conversion scenarios. Treatment decisions were classified into three predefined strategies—baseline-driven, residual disease-driven, and combined—according to whether they relied on pretreatment biomarkers, residual disease biomarkers, or both. Results: A total of 104 medical oncologists completed the survey. Routine receptor reassessment in residual disease was reported by 52.9% of respondents, while 73.1% incorporated residual disease biomarkers into treatment planning either routinely or selectively. Overall, baseline-driven strategies accounted for only 26.3% of treatment decisions, compared with 40.2% for combined strategies and 33.5% for residual disease-driven strategies. Combined strategies predominated following hormone receptor conversion (52.9% for luminal HER2-negative to TNBC and 55.8% for TNBC to luminal HER2-negative). Baseline-driven approaches were most frequently selected following HER2 loss (42.3%), whereas HER2 gain favored residual disease-driven strategies in TNBC-to-HER2-positive conversion (46.2%) and combined strategies in luminal HER2-negative-to-HER2-positive conversion (48.1%). Conclusions: A three-strategy framework of clinical decision-making emerged after receptor conversion, with most treatment decisions incorporating residual disease biology despite limited guideline direction. This framework highlights an important evidence gap and provides a practical foundation for future studies evaluating treatment adaptation after receptor conversion. Full article

Accurate state-of-health (SOH) prediction is essential for the safe and cost-effective operation of lithium-ion battery systems. However, current data-driven methods still struggle to jointly extract multiscale degradation information, capture long-range dependencies, fuse heterogeneous health indicators, and provide transparent model decisions. This study proposes an interpretable multi-feature SOH prediction framework that integrates improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), Autoformer, and a bidirectional temporal convolutional network (BiTCN). ICEEMDAN adaptively decomposes capacity-related sequences into intrinsic mode functions and residual components, thereby suppressing noise and representing degradation dynamics at multiple temporal scales. Autoformer captures long-term trends and periodic patterns through series decomposition and auto-correlation, whereas BiTCN models local dynamic fluctuations through bidirectional temporal convolutions. The decomposed components and health indicators are then fused for battery health-state prediction. Shapley additive explanations (SHAP) are used to quantify feature contributions, and interval prediction is introduced to evaluate predictive uncertainty. Experiments on CALCE lithium-ion battery datasets show that the proposed ICEEMDAN-Autoformer-BiTCN model outperforms the tested baseline combinations, achieving an MAE of 6.6646 and an R² of 0.9896 under ICEEMDAN decomposition. SHAP analysis further indicates that residual components, SOH-related information, cycle number, and internal resistance make consistent contributions across battery samples. These results suggest that the proposed framework improves prediction accuracy while providing a more interpretable and uncertainty-aware approach to battery health assessment. Full article

Triple Friction Pendulum (TFP) bearings are widely employed as seismic isolation systems to reduce seismic force and deformation demands in structures. However, the combined influence of vertical mass-distribution irregularity, soil–structure interaction (SSI), structural eccentricity, and nonstationary earthquake excitation on the nonlinear torsional response of TFP-isolated buildings remains insufficiently understood. This study investigates the seismic response of a five-storey reinforced concrete (RCC) building equipped with TFP bearings subjected to nonstationary spectrum-compatible horizontal earthquake ground motions. The investigated structure represents a low-to-medium-rise isolated building with a superstructure period Ts ≤ 0.5 s, and the conclusions are applicable within the examined structural configuration, adopted TFP properties, and equivalent SSI modelling assumptions. A nonlinear time-history analysis framework combined with Monte Carlo-based spectrum-compatible ground-motion simulations is employed to evaluate the effects of SSI, structural eccentricity, and vertical mass-distribution irregularity. Validation against OpenSees benchmark simulations demonstrates strong agreement in the predicted structural responses. Parametric analyses show that increasing the soil stiffness ratio from 0.5 to 2.0 reduces the normalized isolation displacement by approximately 46.5% and the corner rotational response by approximately 36.7%. Conversely, increasing the vertical mass-irregularity ratio from 1.0 to 1.5 increases the inter-storey drift ratio by approximately 60% and corner-displacement magnification by approximately 48.6% within the investigated cases. The results demonstrate that seismic response is governed not only by the magnitude of vertical mass irregularity but also by its location due to changes in inertia-force distribution, modal participation, and lateral–torsional coupling. These findings highlight the importance of considering SSI and vertical mass distribution simultaneously when assessing the seismic performance of torsionally asymmetric TFP-isolated RCC buildings. Further studies incorporating taller structures, multidirectional excitation, detailed soil–foundation interaction models, and experimentally calibrated TFP properties are required to extend the applicability of the findings. Full article

Despite extensive research on the abrasive properties of lunar regolith, the use of in-process tribological signals for wear assessment remains insufficiently studied. The aim of this work is to evaluate the relationship between torque response and abrasive wear severity in rotating shaft–seal systems exposed to lunar regolith simulants. Rotating EN 1.4404 stainless-steel shafts and spring-loaded natural polytetrafluoroethylene (PTFE) lip seals were tested under three-body abrasive wear conditions. Five particle-size fractions of LX-M100 Lunar Mare and LX-TH100 simulants were investigated at test durations of 15 min, 30 min and 1440 min. Frictional torque was continuously recorded, while post-test shaft surface roughness was used to characterize wear severity and Scanning Electron Microscope (SEM) analysis of the PTFE counterface was used to identify wear mechanisms. The results showed that torque response systematically depended on particle-size fraction and simulant type. Furthermore, the torque-response descriptors provide in-process information related to abrasive interaction severity, with peak torque events ($T_{max}$) showing the strongest relationship with abrasive surface modification. The statistical analysis was based on 27 complete observations, and considering the prematurely terminated test runs and the resulting limitations of the dataset, the obtained relationships are interpreted as exploratory. These findings provide a physical basis for torque-based wear monitoring in sealed rotating mechanisms for future lunar applications. Full article

Urban heat islands pose increasing risks to human settlements, yet the differential mechanisms by which grey–green spaces regulate diurnal and nocturnal land surface temperature across local climate zones remain insufficiently understood. This study addresses this gap through a Hangzhou case study, integrating a ten-indicator grey–green space system with two local spatial identification approaches—K-means clustering and an LCZ-inspired simplified scheme—and a Random Forest-SHAP framework. The LCZ-inspired scheme outperformed K-means clustering, with a mean diurnal–nocturnal Test R² of 0.4344 across twelve models, compared to 0.2977 for K-means. Diurnal and nocturnal LST were driven by systematically different factors: building density dominated daytime LST in most LCZ types (22.0% to 27.8%), while canopy height dominated nighttime LST (22.7% to 30.2%), revealing a systematic shift from building-dominated daytime to vegetation-dominated nighttime. This shift did not occur in compact built-up areas, suggesting that built-up density may be a threshold condition for the shift. Key variables exhibited nonlinear threshold effects with saturation points varying by LCZ type: canopy height cooling saturated at approximately 4 m in LCZ2 but required 17–21 m in LCZ3 and LCZA. These SHAP-based patterns and turning points should be regarded as exploratory, sample-dependent associations evaluated within the training data; their spatial stability across held-out regions was not assessed. Factor interactions were interval-dependent rather than globally fixed. Spatial cross-validation confirmed that random splitting substantially overestimated model performance, highlighting the necessity of spatially explicit validation. The methodological framework provides a replicable approach for urban thermal environment research and offers LCZ-specific threshold hypotheses for thermal regulation planning in subtropical megacities, subject to further spatial and cross-city validation. Full article