The full scaffold construction method is widely used in cast-in-place box beam construction and is especially sensitive to foundation settlement in soft soil areas, which can significantly impact project quality. Based on the Zhejiang Shiyitang Expressway project, this study proposed a combination of superficial ground treatment and preloading method to reduce costs and improve construction efficiency. An artificial solidified crust layer (ASCL) with a depth of 1.5 m was constructed using in-situ solidification technology, achieving a bearing capacity of 180 kPa. Settlement, pore water pressure, and lateral displacement at various depths were monitored during the foundation preloading, scaffold preloading, and cast-in-place box beam loading stages through in-situ testing and numerical modeling. The ground settlement 30 days after concrete casting was 15.4 mm, with most of the settlement occurring during the foundation and scaffold preloading stages. The ASCL was included in the additional stress calculation, resulting in a 27% reduction in total settlement compared to conditions without the ASCL. The influence of permeability coefficient, soil compression modulus, loading mode, and load application area was analyzed using the validated numerical model. The final settlements were found to be similar for soils with varying permeability coefficients, indicating that the superficial ground treatment method is suitable for different soil types. The "effective range" of foundation preloading refers to the width between the bridge web and the bridge pile foundation.
Additive manufacturing allows for the creation of custom acetabular components with unique shapes, geometries, and sizes for patients who have massive bone loss. The aim of the present study was to evaluate the implant survivorship, imaging results, and clinical outcomes of custom, three-dimensional (3D) printed hemipelvis reconstructions in both the oncologic and non-oncologic setting. We retrospectively identified seven total hip arthroplasties (THAs) from 2018 to 2023 that utilized a novel ultra-porous, custom, 3D-printed component. Indications for surgery were chondrosarcoma in three patients, aseptic loosening of the acetabular component in two patients, osteosarcoma in one patient, and reimplantation as part of two-stage revision for infection in one patient. All revision THAs had massive acetabular bone loss (Paprosky IIIB), and all primary neoplasm resections were Enneking-Dunham type III. The mean age was 56 years, 86% were men, and the mean body mass index was 33. The mean follow-up was four years (range, one to six). At final follow-up, all ultra-porous, 3D-printed constructs remained in situ. There was one patient revised to a constrained liner for dislocation, and one other reoperation occurred for infection. There was an additional dislocation treated with a closed reduction. On radiographic and computed tomography images, the proximal portion of all components were osseointegrated to the ilium with no radiolucent lines. The inferior ischial flange had ingrowth failure in four cases. At the final follow-up, all patients were ambulatory (three without any gait aids, three patients who had a cane, and one who had a walker). There was no patient who died of disease, and there were no local recurrences. Ultra-porous, custom, 3D-printed components used for hemipelvis reconstructions in salvage cases of arthroplasty and oncologic reconstruction demonstrated promising excellent early results with all osseointegrated to the ilium, all in situ to date, and all patients independently ambulatory. Dislocation continues to be the most common complication.
This study aimed to evaluate whether chemical exchange saturation transfer (CEST) imaging, in combination with the nonionic X-ray iodinated contrast agent Iobitridol, can detect extracellular pH (pHe) in rats with gliomas and enable the construction of quantitative pHe maps. CEST pH imaging was performed both on Iobitridol phantoms and on rat models bearing brain gliomas, using a 7.0 Tesla small animal MRI scanner (Agilent Technologies) and employing varying radiofrequency (RF) powers (1.5, 3.0, and 6.0 µT) based on the ratio of apparent exchange-dependent relaxation (AREXratio) technique (specifically, 1.5/6.0 µT and 3.0/6.0 µT). The results indicated that AREXratio can more effectively eliminate the influence of magnetization transfer (MT) effects from the CEST signal, thereby enabling more accurate quantification of pH. In vivo CEST pHe imaging distinctly delineated the glioma regions, and quantitative analysis demonstrated that the mean extracellular pH values within gliomas were closely aligned and exhibited an acidic profile. These results further verify the reliability and accuracy of CEST imaging for quantitative assessment of the tumor microenvironment's acidity in gliomas. In conclusion, this study is the first to demonstrate that non-invasive CEST imaging can accurately detect the acidic extracellular microenvironment of brain gliomas and produce quantitative pHe maps with good spatial resolution, highlighting its significant potential for clinical translation.
When disposed of in landfills, printed circuit boards (PCBs) release hazardous substances. Furthermore, the global sand crisis has gained considerable attention among environmentalists over the last few years, and the United Nations has proposed some initiatives to reduce the use of river sand. Despite the existence of several promising sustainable alternatives to alluvial sand, there has been little effort to implement those initiatives in the construction industry. This study explores the use of recycled non-metallic PCB (NM-PCB) as a partial replacement for fine aggregate in mortar, combined with silica fume and marble powder. No data on their combined effects on mortar properties has been discovered yet which restricted large-scale application of NM-PCB in the construction industry. Therefore, this study investigates the potential of machine learning (ML) to predict the compressive strength (CS) of mortar containing NM-PCB, silica fume, and marble powder, as CS is the most critical property of concrete. A comprehensive experimental dataset of 270 samples was developed with eight (8) input variables, with compressive strength as the output. Due to the significant pozzolanic activity of silica fume and the micro filler effect of marble powder, their optimal dosage in mortar was determined using machine learning. The highest Compressive Strength (CS) achieved was 17.6 MPa in a mix containing 5% SF, 5% MP and 3% NM-PCB. Linear Regression, Random Forest, and Extreme Gradient Boosting models were applied to predict compressive strength, with RF and XGB optimized via grid search and validated using k-fold cross-validation. Model performance was evaluated using R², RMSE, MAE, and MAPE. The Random Forest model was the most accurate, achieving an R² of 0.96, while XGBoost also performed well with R² = 0.90. SHAP analysis showed that silica fume (7-12 kg/m³) and NM-PCB (13-22 kg/m³) enhance compressive strength when combined with over 360 kg/m³ of cement. ICE and PDP analyses highlighted curing age as the most influential factor, with silica fume, water-cement ratio, and superplasticizer dosage also significantly affecting strength. A graphical user interface was developed as a decision-support tool for researchers and preliminary mix design optimization for practitioners and externally validated with experimental results demonstrating that recycling NM-PCB in concrete promotes sustainable construction.
In sharp force injury cases, assessments of applied force and injury severity primarily rely on empirical judgment, lacking quantitative and objective data support. This study aims to construct a high-fidelity finite element (FE) head model, validate it using 3D-printed biomimetic skull experiments, and investigate the relationship between momentum and injury severity in sharp instrument stabs to the head, thereby providing scientific evidence for case analysis. A high-fidelity FE head model was reconstructed based on the Total Human Model for Safety (THUMS) model. Biomimetic skulls were 3D-printed using PEEK material. Experimental data obtained from slashing with a Chinese kitchen knife were collected via sensors and motion capture systems, using the erosion failure model to simulate wound formation. Following model validation, the approach was applied to a real stabbing fatality case to systematically simulate stabbing processes under varying momenta (0.75-11.25 kg·m/s). FE model validation demonstrated close alignment between simulation and experimental results, with errors in wound dimensions and slashing force within 15.0%. Case reconstruction revealed that the minimum momentum required to reproduce penetrating injury in the homicide case was 9.75 kg·m/s. In the present simulation framework, momentum values of 0.75 kg·m/s, 2.25 kg·m/s, and 5.25 kg·m/s were associated with minor, moderate, and serious skull injuries, respectively. This study provides a biomechanical framework for quantitative simulation and illustrative case reconstruction of sharp force injuries. The real-case application serves primarily as an example of the proposed biomechanical reconstruction approach, which may enhance the objectivity of injury severity assessment when integrated with other forensic evidence and provide reproducible biomechanical support for case investigation.
Osimertinib is a key treatment for EGFR-mutated non-small cell lung cancer, but interstitial lung disease (ILD) remains a rare yet potentially life-threatening pulmonary adverse event. Early recognition of osimertinib-associated ILD and clarification of its underlying mechanisms are important for improving clinical management. In this study, real-world pharmacovigilance data from the FDA Adverse Event Reporting System (FAERS; 2015Q4-2025Q2) were extracted, deduplicated, and evaluated using four disproportionality algorithms. Potential molecular links between osimertinib and ILD were further explored by integrating drug- and disease-related targets from SwissTargetPrediction, CTD, GeneCards, and DisGeNET, followed by intersection analysis, protein-protein interaction (PPI) network construction, and functional enrichment analysis. A total of 24,676 osimertinib-related adverse event reports were identified, and ILD emerged as one of the strongest pulmonary safety signals. Among 484 ILD reports, cases were more commonly observed in older patients, women, and Asian patients, and were associated with high rates of hospitalization and serious clinical outcomes. Twenty-one overlapping targets between osimertinib and ILD were identified, and PPI network analysis highlighted CTNNB1, KRAS, STAT3, and TP53 as central nodes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated significant involvement of cancer-related pathways, EGFR tyrosine kinase inhibitor resistance, and multiple signaling and regulatory pathways, including PI3K-Akt, MAPK, and Wnt/β-catenin-related signaling, suggesting potential roles in inflammation, epithelial injury, and fibrotic remodeling. Together, these findings integrate pharmacovigilance evidence with network-based mechanistic prediction and provide a basis for risk-stratified monitoring and further experimental validation of osimertinib-associated ILD. 1 Article types. Original Research.
Critically ill patients with ischemic stroke face substantial in-hospital mortality. Early and accurate prediction of mortality risk may facilitate timely risk stratification and improve intensive care management. This study aimed to develop and externally validate a machine learning-based predictive model using multicenter datasets. We extracted data from MIMIC-IV (n = 3,568), eICU-CRD (n = 2,535), and Tongji University Hospital (TJUH, n = 144). Eight predictors identified through multivariable logistic regression were used for model construction. Five algorithms-Random Forest, XGBoost, LightGBM, Logistic Regression, and an ensemble SuperLearner-were trained and evaluated. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, F1 score, and calibration. DeLong's test compared the AUROC of the SuperLearner with those of the four base models. Decision curve analysis (DCA) was used to evaluate clinical utility. The SuperLearner demonstrated the strongest discrimination, with AUROCs of 0.80 (95% CI: 0.75-0.85) in MIMIC-IV, 0.82 (95% CI: 0.80-0.84) in eICU-CRD, and 0.76 (95% CI: 0.64-0.87) in TJUH. Sensitivity and specificity ranged from 0.70 to 0.83 and 0.68-0.82 across datasets, outperforming the four baseline models (all p < 0.05). Calibration curves showed reasonable agreement between predicted and observed outcomes, although deviations were noted at probability extremes. DCA indicated net clinical benefit across a wide range of thresholds, while slight fluctuations suggest potential overestimation at higher thresholds. The SuperLearner model achieved robust and consistent predictive performance across three independent cohorts. While showing potential utility for early mortality risk estimation in critically ill ischemic stroke patients, its clinical application requires further prospective validation and real-world implementation studies.
Gastroesophageal junction adenocarcinoma (GEJAC) is a highly lethal malignancy, and its molecular mechanisms are still not well understood. Reliable biomarkers for early diagnosis and immunotherapy are urgently needed. This study sought to identify hub genes linked to GEJAC by analyzing datasets from the Gene Expression Omnibus (GEO) and examining their correlation with immune cell infiltration. Transcriptome data of GEJAC samples and matched normal controls were obtained from GEO. Differentially expressed genes were identified, followed by WGCNA to determine hub genes. Functional annotation was carried out through GO, KEGG, and PPI network analysis to elucidate their biological significance. A diagnostic prediction model was established using logistic regression, and its accuracy was validated through ROC curve analysis. Immune cell composition was assessed with the CIBERSORT algorithm, and the associations between hub genes and immune cell subsets were further investigated. A total of 392 genes with differential expression were identified, among which 47 overlapping candidates were screened by intersecting WGCNA modules with DEGs. Functional enrichment analysis revealed that these genes were involved in meiotic nuclear division, mitotic cell cycle checkpoint, and the p53 signaling pathway. Five hub genes (TPX2, CCNB2, BUB1, TOP2A, ASPM) were selected for the construction of a diagnostic model, which achieved strong predictive performance (AUC = 0.9). Immune infiltration analysis revealed an inverse relationship between all five hub genes and resting memory CD4 + T cells, as well as a positive relationship with activated memory CD4 + T cells. This study identified TPX2, CCNB2, BUB1, TOP2A, and ASPM as potential candidate diagnostic biomarkers for GEJAC at the transcriptomic level. These genes are closely associated with immune cell infiltration, providing new insights into GEJAC pathogenesis and potential targets for immunotherapy.
Continuous cropping obstacles (CCO) severely limit the sustainable development of sweetpotato (Ipomoea batatas (L.) Lam.) industry. However, the transcriptional regulatory network of sweetpotato in response to continuous cropping stress (CCS) is unreported. Accordingly, transcriptome sequencing was employed to elucidate this network in two cultivars (Shangshu19 and Yizi138). CCS markedly inhibited the growth of Yizi138, while its inhibition on Shangshu19 was relatively minor. Additionally, significantly more differentially expressed genes (DEGs) were detected in Shangshu19 compared with Yizi138. Metabolic pathways, plant hormone signal transduction, and the MAPK signaling pathway exert crucial functions in defending Shangshu19 against CCS. Weighted gene co-expression network analysis (WGCNA) demonstrated that multiple genes in the MEdarkred module, such as IbPR1, IbWRKY70, and IbCRK10, exhibited a positive correlation with continuous cropping tolerance, suggesting that these genes may be critically involved in boosting sweetpotato tolerance to continuous cropping. In contrast, continuous cropping impaired the photosynthetic system and energy metabolism in Yizi138, inhibiting its growth. Shangshu19 enhances its tolerance to CCS via three strategies: regulation of key pathways, maintenance of physiological functions, and construction of a coordinated regulatory network mediated by IbPR1, IbWRKY70, and IbCRK10. These findings provide a theoretical foundation and genetic resources for breeding continuous cropping tolerance sweetpotato cultivars.
Layered backfilling is a critical construction method for ensuring the overall stability of backfill in deep mines. Its cyclic "fill-cure-refill" operation mode induces complex thermo-hydro-mechanical-chemical (THMC) coupling effects and significant spatiotemporal heterogeneity within the backfill body. Addressing the limitation that existing research predominantly focuses on single continuous filling and lacks in-depth investigation into the physical field transfer mechanisms at layered interfaces, this paper establishes a fully coupled THMC numerical simulation model for Cemented Paste Backfill (CPB) considering a time-varying computational domain. On this basis, the influence laws of the cement-sand ratio (c/s ratio), inter-layer interval time, and layering strategy (continuous, two-layer, and three-layer) on the spatiotemporal evolution of temperature, seepage, and stress fields were systematically analyzed. Results indicate that the c/s ratio is the primary driver of multi-field evolution; higher ratios increase peak temperatures and matrix suction rates, enhancing early strength. Interval time governs pore water pressure (PWP) dissipation; longer interval utilizes a "peak-shifting effect" to reduce heat accumulation and improve vertical stress. Furthermore, a three-layer strategy creates "sawtooth-like" PWP dissipation, effectively preventing the high-pressure accumulation and stress lag associated with continuous filling. This work clarifies THMC mechanisms at layered interfaces, providing a theoretical basis for optimizing backfill consolidation.
Recurrent miscarriage (RM), a complex pregnancy disorder with largely undefined molecular mechanisms, has been associated with epigenetic abnormalities in chorionic tissue. This study aimed to elucidate methylation-dependent cilia-related genes (CRGs) implicated in RM. An integrative analysis combining RNA sequencing, public transcriptome data, and DNA methylation profiles was conducted to identify RM-related CRGs. Machine learning algorithms were applied to determine the most relevant candidates. Immune infiltration profiling, gene set enrichment analysis (GSEA), and competitive endogenous RNA (ceRNA) network construction were employed to clarify molecular pathways. RT-qPCR validation was performed using clinical samples. Fourteen methylation-regulated CRGs were identified, among which SLC1A2 and ZDHHC20 were confirmed as key candidates. GSEA indicated their association with spliceosome, cell cycle, and proteasome pathways. Immune analysis demonstrated decreased infiltration of activated CD4+ T cells, effector memory CD4+ T cells, and Th2 cells in RM, with SLC1A2 and ZDHHC20 expression positively correlated with these immune subsets. The ceRNA networks indicated that SLC1A2 and ZDHHC20 were modulated by 7 miRNAs and 19 lncRNAs, respectively. RT-qPCR results showed significant overexpression of SLC1A2, but not ZDHHC20, in RM chorionic tissue. Collectively, SLC1A2 represents a methylation-regulated CRG that links ciliary impairment, immune imbalance, and epigenetic modulation in RM, revealing a novel molecular axis and suggesting its diagnostic and therapeutic potential.
Osteoarthritis (OA) is a chronic, disabling condition whose pathogenesis remains unclear. TRPM4 is closely associated with OA, but its specific roles and regulatory networks within different cell subsets remain to be elucidated. This study integrates single-cell and transcriptomic sequencing data to systematically analyse the cell-specific expression patterns, key downstream molecules, and regulatory networks of TRPM4, with the aim of identifying new therapeutic targets for OA. OA-related datasets were obtained from public databases. Key cells were identified at the single-cell level, and analyses including enriched pathways and cell communication were conducted. Candidate genes were screened by cross-referencing differentially expressed genes (DEGs), key module genes from high-dimensional weighted gene co-expression network analysis (hdWGCNA) analysis related to key cells, and TRPM4-related DEGs. We then employed machine learning algorithms and expression levels to screen key genes. Subsequently, analyses such as functional enrichment, immune infiltration analysis, construction of molecular regulatory networks, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were executed. Human Leukocyte Antigen-DR Alpha Chain (HLA-DRA) cells were the key cells, and the enriched pathways they participated in mainly included "FMO oxidizes nucleophiles", and frequent cell-cell interactions were observed between HLA-DRA cells and synovial subintimal fibroblasts (SSF) in OA. Later, 2 key genes (FOSL2 and S100A11) were obtained. S100A11 was up-regulated, while FOSL2 was down-regulated in the OA group, and RT-qPCR showed consistent results (p < 0.05). In addition, FOSL2 and S100A11 shared 14 enriched pathways, such as the p53 pathway and oxidative phosphorylation, and there were infiltration differences of 8 types of immune cells between OA and control samples (p < 0.05). The miRNA-mRNA network (e.g., has-miR-6134-S100A11) was constructed. This study suggested that TRPM4-associated HLA-DRA+ antigen-presenting cells may be associated with osteoarthritis, and, based on transcriptomic correlation analysis and limited qPCR validation, identified S100A11 and FOSL2 as candidate biomarkers associated with TRPM4. These findings provided preliminary, hypothesis-generating clues regarding the cellular heterogeneity and immunometabolic pathways in which TRPM4 may be involved in osteoarthritis; however, its specific role remained to be validated by subsequent functional experiments.
This study aimed to investigate the impact of the treatment duration, initiation timing, and inflammatory factors on immunotherapy maintenance in patients with stage III unresectable lung squamous cell carcinoma. A retrospective analysis was conducted on 100 patients with stage III unresectable lung squamous cell carcinoma who received comprehensive treatment consisting of induction chemotherapy followed by concurrent chemoradiotherapy and consolidation immunotherapy (i.e., the "induction + concurrent chemoradiotherapy + consolidation immunotherapy" regimen) between January 2019 and December 2022. The analysis focused on treatment efficacy and prognostic factors. All statistical analyses were performed using SPSS software (version 25.0). Survival analysis was conducted using the Kaplan-Meier method, with between-group comparisons assessed by the Log-rank test (for univariate analysis, significance level α = 0.10). Multivariate analysis was performed using the Cox proportional hazards regression model (significance level α = 0.05). Optimal cutoff values for the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) were determined using SPSS, and their sensitivity and specificity were calculated. Subsequently, based on these optimal cutoff values, patients were stratified into high- and low-value groups, thereby converting these continuous variables into categorical variables for further analysis. Among the 100 patients who received induction chemotherapy followed by concurrent chemoradiotherapy and consolidation immunotherapy, the 1-, 3-, and 5-year overall survival (OS) rates were 88.8%, 61.6%, and 43.6%, respectively. The corresponding 1-, 3-, and 5-year progression-free survival (PFS) rates were 74.6%, 45.3%, and 39.7%. Until the last follow-up, disease recurrence or metastasis occurred in 46 cases, including 15 cases of local recurrence, 16 cases of distant metastasis (8 with intracranial metastasis, 5 with liver metastasis, and 3 with bone metastasis), and 15 cases of regional lymph node metastasis (involving station 2, 4, 7 and supraclavicular lymph nodes).Univariate analysis identified TNM stage (p = 0.002), maintenance immunotherapy duration (p < 0.001), and interval between immunotherapy initiation and the last chemotherapy (p = 0.054) as factors associated with overall survival (OS).Multivariate Cox analysis confirmed that TNM stage (p = 0.03) and maintenance immunotherapy duration (p = 0.005) remained independently associated with OS. For progression-free survival (PFS), univariate analysis showed that the maintenance immunotherapy duration (p = 0.012) and TNM stage (p < 0.001) were significantly associated with PFS. Multivariate Cox analysis further demonstrated that both TNM stage (p = 0.01) and the maintenance immunotherapy duration (p = 0.034) retained independent associations with PFS. For patients with locally advanced lung squamous cell carcinoma, the comprehensive regimen of induction chemotherapy followed by concurrent chemoradiotherapy and consolidation immunotherapy-initiating consolidation immunotherapy two weeks after completing concurrent chemoradiotherapy and continuing for two years-yielded favorable outcomes, with efficacy comparable to that reported in previous studies. In this cohort, more advanced clinical stage, higher neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), and lower lymphocyte-to-monocyte ratio (LMR) were associated with poorer prognosis. The prognostic prediction model constructed based on TNM stage, NLR, PLR, and LMR demonstrated good predictive performance and clinical utility, representing a simple, economical, and effective tool worthy of further exploration for guiding clinical decision-making.
Engagement questionnaires have been widely recognized as an indicator of clinician performance, workplace satisfaction, and organizational outcomes. There are several tools that measure engagement among physicians and nurses. However, no validated engagement tools exist for pharmacists, whose work environment and responsibilities differ. This gap highlights the need for a pharmacist-specific engagement tool. This study aimed to assess reliability and factor structure of the POWER Engagement Framework questionnaire. The POWER Engagement Framework was developed to assess the professional and organizational factors that play a role in pharmacist engagement in a pharmacist-led primary care practice environment. It encompasses five core constructs derived and adapted from the literature - Potential, Opportunity, Well-being, Environment, and Resources (POWER). Pharmacists who had worked two or more shifts in the pharmacy primary care clinic in Alberta, Canada completed an online questionnaire administered via the Qualtrics Survey platform between June - September 2024. A comprehensive validation analysis was conducted which included Spearman correlation, internal consistency using Cronbach's alpha and Confirmatory Factor Analysis (CFA). Demographic information was available for 93/113 participants, of whom almost two thirds 61.3% (57/93) were Canadian-trained pharmacists. The overall standardized Cronbach's alpha was 0.82, indicating good internal reliability. Spearman's correlations suggest that pharmacists perceive Well-being, Environment, and Resources as important factors that will enhance their ability to excel and grow in the profession. Validity was assessed using CFA, which tested whether the data fit the hypothesized factor structure of the five constructs. The CFA largely supported the hypothesized factor structure, particularly for Potential and Environment, while Well-being and Resources exhibited weaker model fit. This study presents the validation of the first pharmacist-specific tool to measure engagement. The POWER Engagement Framework demonstrated good reliability and conceptual coherence to assess pharmacist engagement. Refinement for Well-being and Resources constructs could improve the model.
The accumulation of polyester plastics poses a major challenge for efficient recycling strategies. Enzymatic depolymerization is a promising biotechnological approach, but it is often limited by enzyme instability and the need for costly purification procedures. Here, we report a thermostable self-assembling protein nanocage scaffold derived from the C-terminal domain of the Escherichia coli BetT protein (BetTC) for polyester depolymerization. A poly(ethylene terephthalate) (PET) hydrolase variant (ICCG, an engineered cutinase) was genetically fused to the nanocage through rationally designed linkers to construct a biohybrid nanocatalyst. Systematic evaluation of different linker architectures revealed that enzyme presentation on the nanocage critically influences catalytic activity. In particular, the rigid proline-glycine (PG) linker construct exhibited approximately a twofold higher PET degradation rate compared to free ICCG, while also showing enhanced activity toward poly(butylene adipate-co-terephthalate) (PBAT). The nanocage also conferred exceptional thermal robustness, maintaining structural integrity after prolonged incubation at 50 °C. Notably, the nanocatalyst remained active in unpurified E. coli lysates, enabling a simplified, purification-free biocatalytic process. Overall, this work establishes the BetTC nanocage as an effective and engineerable protein scaffold for developing robust biocatalysts in polyester depolymerization, a key step towards recycling.
This paper explores the structural design and material application of seating systems in science museums, focusing on safety and ergonomic comfort. To address the requirements of modern exhibition environments, the study employs finite element analysis (FEA) and body pressure distribution experiments to evaluate the mechanical performance and user comfort of four distinct seat structures and materials: polyurethane, polyester fiber, polypropylene foam, and memory foam. The investigation analyzes their effects on stress distribution, strain, and pressure relief. Results indicate that while structural design is critical for ensuring uniform stress distribution, material properties primarily dictate comfort and pressure alleviation. Specifically, memory foam and polyurethane demonstrate the optimal balance between comfort and load-bearing capacity, whereas polypropylene presents risks of localized stress concentration. Consequently, the study proposes a "structural optimization coupled with material matching" strategy, utilizing rigid materials for load-bearing and flexible materials for comfort interface. These findings provide practical guidance for the engineering design and material selection of public seating in science museums.
The eggs of Samia cynthia ricini are a promising host for mass-rearing Trichogramma chilonis, but the effects of egg collection methods, fertilization status, and cold storage on rearing efficiency remain unclear. We evaluated the combined impacts of egg collection methods (spontaneous oviposition vs. manual dissection) and fertilization status on host egg yield and T. chilonis' rearing performance, and examined the cold storage effectiveness for unparasitized and parasitized S. c. ricini eggs. Fertilization status and collection method interacted significantly to affect the host egg yield and parasitoid progeny. Spontaneously laid unfertilized egg treatment had the highest total eggs per female, T. chilonis emergence rate, total progeny, and reproductive coefficient. Spontaneous oviposition outperformed manual dissection, increasing female ratio and emerged adults per egg. At 2 ± 1 °C, underwater storage of unparasitized eggs yielded significantly more parasitized eggs than conventional storage. Compared to fresh eggs, 10-day storage significantly increased total emerged T. chilonis adults and emerged adults per host egg. However, storage beyond 20 days significantly reduced reproductive performance. For parasitized eggs stored at 10 ± 1 °C for 7-21 days, T. chilonis emergence rate and progeny per host egg did not differ significantly from the non-stored control. However, storage for 21 days significantly inhibited progeny emergence. Spontaneously laid unfertilized eggs are the optimal host for rearing T. chilonis. Unparasitized eggs should not undergo underwater cold storage beyond 20 days. Parasitized eggs should not be cold-stored over 21 days. These findings offer valuable insights for optimizing T. chilonis mass production. © 2026 Society of Chemical Industry.
Nurse turnover intention is a multifactorial construct shaped by individual, occupational, organizational, and policy-level factors. Although widely studied in some regions, evidence from Southern Europe, particularly Spain, remains scarce. Understanding these factors in diverse healthcare contexts is essential for designing effective retention strategies that are both locally relevant and internationally informative. This study aims to explore turnover intention prevalence and associated factors among nurses across different care settings in Spain. A cross-sectional study. Primary care, hospitals, emergency services, or social healthcare settings. A total of 20,316 actively employed nurses. An online survey was disseminated by the Spanish Ministry of Health and other institutional channels. Turnover intention was the primary outcome and was measured with a single item asking whether nurses intended to leave the profession within the next 10 years (yes/no). Work-related variables and perceptions of care quality and patient safety were also collected. Multivariable logistic regression was used to identify key predictors across care settings. Of the 20,316 participants, most were women (84.8%) and 50.3% were under 35 years. Overall, 39.58% reported an intention to leave the nursing profession within 10 years. Turnover intention was significantly associated with perceptions of care quality (OR = 1.706, p < 0.001) and patient safety (OR = 1.809, p < 0.001), regional disparities, and temporary employment contracts (OR = 1.333, p < 0.001). In primary care, working as a generalist and on afternoon shifts increased turnover risk, while in hospitals, long shifts (> 7.5 h) were influential. This study provides novel insights into nurse turnover intention in Spain, highlighting the interplay of modifiable institutional factors and regional disparities in a decentralized health system. Turnover intention was strongly associated with organizational conditions, reinforcing the urgent need for tailored, context-sensitive retention strategies. Standardizing definitions, measurements, and temporal frameworks remains critical for advancing comparative research and developing effective, evidence-based interventions to strengthen the nursing workforce.
Infectious bone defects remain a clinical challenge due to the lack of spatiotemporal control over bacterial infection, immune microenvironment modulation, vascular regeneration, and osteogenic differentiation. Herein, we engineered a modularly assembled 808 nm near-infrared (NIR)-responsive therapeutic system with three functional modules, including a 3D-printed honeycomb-mimetic poly(lactic acid) (HP) framework as a mechanically supportive module, collagen-graphene oxide-black phosphorus (CGB) nanocomposite hydrogel as an ECM-mimetic filling module, and NIR-responsive black phosphorus (BP)-release module. Under NIR-induced mild photothermal effects, CGB@HP hydrogel exhibited NIR-responsive BP-release, BP's degradation into PO43-, and upregulation of heat shock protein 47, thus promoting antibacterial activity, osteogenesis and angiogenesis capacities, and induction of macrophage polarization toward the pro-reparative M2 phenotype. In vivo validation in a rat model of infectious critical-sized bone defects further demonstrated that the CGB@HP system accelerated bone healing by attenuating local inflammation, upregulating pro-healing factor secretion, recruiting endogenous stem cells, and stimulating vascular regeneration. Collectively, this work introduces a modular NIR-responsive platform that leverages synergistic physical (mild photothermal therapy) and chemical (BP release/degradation) cues to remodel the damaged tissue microenvironment. By integrating structural support, bioactive molecule delivery, and NIR-responsive immunomodulation, this modular assembly offers a promising strategy and broad implications for infectious bone regeneration through the combination of multifunctional modules into a construct.
Vδ1 T cells are promising for solid tumor immunotherapy but limited by peripheral rarity and inefficient expansion. This study aimed to establish a scalable expansion protocol and evaluate the therapeutic potential of unmodified and CAR-engineered Vδ1 T cells. Vδ1 T cells were expanded with a patented humanized Vδ1 TCR antibody plus cytokine cocktail (vs. commercial protocols). Transcriptomic profiling, in vitro cytotoxicity assays, in vivo xenograft experiments (vs. Vδ2 T cells), and PARP1-mediated lactate resistance analyses were performed. MSLN/NCL-targeted CAR-Vδ1 T cells were constructed and validated in OVCAR8-baring mice models. Average 1 × 10¹⁰ high-purity Vδ1 T cells were obtained from 10 mL peripheral blood, outperforming commercial protocols. Expanded cells retained a stem-like phenotype, exerted superior antitumor activity vs. Vδ2 T cells, and resisted lactate-induced apoptosis via high PARP1 expression. CAR and IL-15 modified Vδ1 T cells showed potent anti-tumor efficacy. This efficient Vδ1 T cell expansion protocol overcomes key clinical translation barriers. Vδ1 and CAR-Vδ1 T cells represent a novel off-the-shelf immunotherapeutic strategy for solid tumors.