Search Results (183)

Chiral molecules are crucial in the field of optical devices, molecular recognition, and other novel functional materials due to their unique spatially asymmetric configuration and optical activity. In this study, a chiral molecule, Cholest-3-yl (E)-3-(4-carbamoylphenyl)acrylate (CCA), was combined with dyes containing large conjugated structures, tetramethylporphyrin tetrasulfonic acid (TPPS), and Nickel(II) phthalocyanine-tetrasulfonic acid tetrasodium salt (TsNiPc), and composite LB films of CCA/TPPS and CCA/TsNiPc were successfully prepared by using Langmuir-Blodgett (LB) technology. The circular dichroism (CD) test proved that the CCA/TPPS composite film had a strong CD signal at 300–400 nm, and the composite film showed chirality. This significant optical activity provides a new idea and option for the application of LB films in chiral sensors. In the Surface Enhanced Raman Spectroscopy (SERS) test, the CCA/TPPS composite film was sensitive to signal sensing, in which the enhancement factor EF = 2.28 × 10⁵, indicating that a large number of effective signal response regions were formed on the surface of the film, and the relative standard deviation (RSD) = 12.08%, which demonstrated that the film had excellent uniformity and reproducibility. The high sensitivity and low signal fluctuation make the CCA/TPPS composite LB film a promising SERS substrate material. Full article

Background: CCAAT/enhancer-binding protein alpha–basic leucine zipper in-frame (CEBPA^bZIP-inf) mutations are associated with favorable outcomes in acute myeloid leukemia (AML). So far, there are limited data on integrating clinical and genomic features impacting the outcomes. Methods: Clinical and genomic data from consecutive patients with CEBPA^bZIP-inf were reviewed. A Cox proportional hazards regression was used to identify the variables associated with event-free survival (EFS), relapse-free survival (RFS) and survival. Results: 224 CEBPA^bZIP-inf patients were included in this study. In the 201 patients, except for the 19 receiving the transplant in the first complete remission with no events (the transplant cohort), multivariate analyses showed that IKZF1 mutations/deletions were significantly associated with poor EFS (p = 0.001) and RFS (p < 0.001); FLT3-ITD mutations, poor RFS (p = 0.048). In addition, increasing WBC count, lower hemoglobin concentration, non-intensive induction, and MRD positivity after first consolidation predicted poor outcomes. On the basis of the number of adverse prognostic covariates for RFS, the 201 patients were classified into low-, intermediate- or high-risk subgroups, and there were significant differences in the 3-year EFS, RFS and survival rates (all p < 0.001); however, except for survival in the low-risk group, these metrics were lower than those in the transplant cohort. Conclusions: We identified a potential high-risk population with adverse prognostic factors in CEBPA^bZIP-inf AML patients for which transplantation should be considered. Full article

Gaucher disease (GD) is an autosomal recessive disorder caused by the deficient activity of the lysosomal enzyme glucocerebrosidase (GCase). Although enzyme replacement therapy (ERT) remains the standard of care for non-neuropathic GD patients, its high cost significantly limits accessibility. To enhance production efficiency, we developed a lentiviral system encoding a codon-optimized GCase gene driven by the human elongation factor 1a (hEF1α) promoter for stable production in human cell lines. A functional lentiviral vector, LV_EF1α_GBA_Opt, was generated at a titer of 7.88 × 10⁸ LV particles/mL as determined by qPCR. Six transduction cycles were performed at a multiplicity of infection of 30–50. The transduced heterogeneous human cell population showed GCase-specific activity of 307.5 ± 53.49 nmol/mg protein/h, which represents a 3.21-fold increase compared to wild-type 293FT cells (95.58 ± 16.5 nmol/mg protein/h). Following single-cell cloning, two clones showed specific activity of 763.8 ± 135.1 and 752.0 ± 152.1 nmol/mg/h (clones 15 and 16, respectively). These results show that codon optimization, a lentiviral delivery system, and clonal selection together enable the establishment of stable human cell lines capable of producing high levels of biologically active, synthetic recombinant GCase in vitro. Further studies are warranted for the functional validation in GD patient-derived fibroblasts and animal models. Full article

Nature-Based Solutions (NBSs) offer promising pathways to enhance ecological resilience and address urban water challenges, particularly in heritage cities where conventional gray infrastructure often fails to balance environmental needs with cultural preservation. This study proposes a strategic framework for the integration of NBSs into historic urban landscapes by employing Internal–External (IE) matrix modeling and an impact–uncertainty assessment, grounded in a structured evaluation of key internal strengths and weaknesses, as well as external opportunities and threats. The Internal Factor Evaluation (IFE) score of 2.900 indicates a favorable internal environment, characterized by the multifunctionality of NBS and their ability to reconnect urban populations with nature. Meanwhile, the External Factor Evaluation (EFE) score of 2.797 highlights moderate support from policy and public awareness but identifies barriers such as funding shortages and interdisciplinary coordination. Based on these findings, two strategies are developed: an SO (Strength–Opportunity) strategy, promoting community-centered and policy-driven NBS design, and a WO (Weakness–Opportunity) strategy, targeting resource optimization through legal support and cross-sectoral collaboration. This study breaks new ground by transforming theoretical NBS concepts into actionable, culturally sensitive planning tools that enable decision-makers to navigate the unique challenges of implementing adaptive stormwater and environmental management in historically constrained urban environments. Full article

In recent years, non-invasive methods for the analysis of biological fluids have attracted growing interest. In this study, we propose a straightforward approach to fabricating silver nanoparticle (AgNP)-coated non-woven polyacrylonitrile substrates for surface-enhanced Raman scattering (SERS). AgNPs were synthesized directly on the substrate using borohydride reduction, ensuring uniform distribution. The optimized SERS substrates exhibited a high enhancement factor (EF) of up to 10⁵ for the detection of 4-mercaptobenzoic acid (4-MBA). To enable glucose sensing, the substrates were further functionalized with glucose oxidase (GOx), allowing detection in the 1–10 mM range. Machine learning classification and regression models based on gradient boosting were employed to analyze SERS spectra, enhancing the accuracy of quantitative predictions (R² = 0.971, accuracy = 0.938, limit of detection = 0.66 mM). These results highlight the potential of AgNP-modified substrates for reliable and reusable biochemical sensing applications. Full article

Cu-based nanomaterials have received considerable attention as promising and cost-effective substrates for surface-enhanced Raman spectroscopy (SERS) applications despite their relatively low enhancement factor (EF) compared to noble metals like gold and silver. In this study, a fast and affordable synthesis route is proposed to obtain a three-dimensional porous copper film (NPC) via an electrodeposition technique based on the dynamic hydrogen bubbling template (DHBT). Two sets of NPC film were synthesized, one without additives and the other with cetyltrimethylammonium bromide (CTAB). The impacts of deposition time on the NPCs’ porous morphology, thickness, and SERS performance were systematically investigated. With the optimal deposition time, the nanopore sizes could be tailored from 26.8 to 73 μm without additives and from 12.8 to 24 µm in the presence of CTAB. The optimal additive-free NPC film demonstrated excellent SERS performance at 180 s of deposition, while the CTAB-modified film showed strong enhancement at 120 s towards methylene blue (MB), a highly toxic dye, achieving a detection limit of 10⁻⁶ M. Additionally, the samples with CTAB showed better efficiency than those without CTAB. The calculated EF of NPC was found to be 5.9 × 10³ without CTAB and 2.5 × 10³ with the CTAB, indicating the potential of NPC as a cost-effective candidate for high-performance SERS substrates. This comprehensive study provides insights into optimizing the structural morphology of the NPCs to maximize their SERS enhancement factor and improve their detection sensitivity toward MB, thus overcoming the limitations associated with conventional copper-based SERS substrates. Full article

(1) Background: Asomate, as a dithiocarbamate compound, is moderately toxic to the human body; thus, it is necessary to develop a rapid and efficient method for detection. To meet this need, this study introduced a rapid, non-destructive, and efficient method for detecting asomate residues on the surface of apples based on surface-enhanced Raman spectroscopy (SERS) combined with flexible substrates. (2) Methods: Concave Au nanorods (AuCNAs) were synthesized in advance. Then, the AuCNAs were loaded on an electrostatically spun film to generate a flexible TiO₂/ZrO₂/AuCNAs substrate for detection. (3) Results: The flexible substrate exhibited strong SERS activity, with an enhancement factor (EF) up to 9.40 × 10⁷ for 4-MBA. Meanwhile, the finite-difference time-domain (FDTD) simulation showed that the localized surface plasmon resonance (LSPR) effects related to the enhancement of the SERS signal are mainly generated from the ‘hot spots’ in AuCNAs. The density functional theory (DFT) simulation detailedly revealed that the SERS peaks could be generated by the interaction among asomate molecules, disassociated Au atoms, and Au facets. Moreover, the asomate in apple peel was analyzed with the limit of detection (LOD) as low as below 10 nM, allowing for the rapid detection of asomate directly on apple peels. (4) Conclusions: The flexible TiO₂/ZrO₂/AuCNAs film can be used for the in situ detection of asomate in apple peel at low concentrations. Moreover, the simulation methods, including FDTD and DFT, explained the mechanism of SERS from the flexible substrates. Full article

Fish oil’s neuroprotective effects in ethanol-induced liver injury was investigated through the factor 2 (NRF2)/Kelch-like ECH-associated protein 1 (KEAP1) pathway. Male Wistar rats received a control liquid diet (C) or an ethanol diet (E), with 25% or 57% of fat replaced by fish oil (CF25, CF57, EF25, EF57) for 8 weeks. Compared to the C group, the E group exhibited brain damage, including impaired performance of Y maze and novel object recognition test, increased glial fibrillary acidic protein (GFAP)-positive astrocytes, and ionized calcium-binding adapter molecule 1 (Iba-1)-positive microglia. In the prefrontal cortex, glutathione (GSH) and phosphorylated (p)-NRF2 decreased, catalase activity increased, and nqo1 mRNA declined; hippocampal NRF2 and nqo1 were also downregulated. However, compared to the E group, the EF25 and EF57 groups exhibited restored spatial and memory functions, reduced GFAP and Iba-1 expressions, potentiated β-amyloid (Aβ) clearance, and escalated catalase activity. Furthermore, increases in p-NRF2 and elevated hippocampal nqo1 mRNA expressions in the prefrontal cortex were observed in the EF25 and EF57 groups. In conclusion, fish oil ameliorated deficits in spatial and memory functions, and enhanced Aβ1-42 clearance in the prefrontal cortex and hippocampus of rats with chronic ethanol-induced liver damage by activating the NRF2/KEAP1 pathway. Full article

Enhancing the precision of carbon accounting not only improves climate policy design, but also contributes directly to sustainability goals by enabling more targeted and accountable emission reduction strategies. Therefore, accurate carbon inventories are foundational to evidence-based climate action and sustainable development planning. This study estimates the carbon emissions of Hunan Province from 2016 to 2020 using the sectoral approach and energy activity data across four major sectors—industrial production, thermal power generation, transportation, and residential life. Emission factors (EFs) were drawn from three different sources: direct measurements, IPCC (Intergovernmental Panel on Climate Change) default values, and published literature. An improved Monte Carlo simulation method was employed to assess the uncertainty of carbon emission accounting associated with different EF sources. The experimental results indicated that carbon emissions calculated based on the literature and default EFs were systematically higher than those derived from empirical measurements, primarily due to discrepancies in the industrial and power generation sectors. In a representative year (2017), the carbon emission estimated based on measured EFs produced the narrowest confidence intervals, reflecting lower uncertainty (−5.31–8.17%), while the uncertainties of carbon emissions calculated using the literature and default EFs were −6.88–9.03% and −5.77–9.94%, respectively. The industrial carbon emissions were the dominant source of overall uncertainty, while the transportation carbon emission had a comparatively minor impact. Importantly, across all departments, the use of measured EFs significantly reduced the uncertainty of carbon inventories, reinforcing the value of locally calibrated data. These findings underscore the urgent need for improved EF measurement systems and standardized accounting practices to support the reliability of subnational carbon inventories. Full article

The eukaryotic translation elongation factor 1 (eEF1) family exhibits critical roles in RNA viral infection beyond its canonical function in protein synthesis. This review analyzes the structural characteristics of eEF1A and the eEF1B complex, and their regulatory mechanisms during viral infection. eEF1A impacts viral replication by stabilizing viral RNA-dependent RNA polymerase (RdRp) complexes, modulating genomic RNA synthesis, and facilitating viral assembly through cytoskeletal regulation. eEF1B subunits contribute through enhancing viral mRNA translation, regulating nuclear transport of viral components, and mediating post-translational modifications. The high conservation of eEF1 proteins across species and their involvement in multiple stages of viral replication establish them as promising broad-spectrum antiviral targets. Current eEF1-targeting compounds like plitidepsin demonstrate efficacy against diverse viral families, though therapeutic development faces challenges in balancing antiviral activity with host toxicity. This review provides a theoretical foundation for developing novel antiviral strategies targeting host–virus interaction interfaces and offers insights into addressing emerging infectious diseases. Full article

Background: Urinary tract infection (UTI) is predominantly caused by uropathogenic Escherichia coli (UPEC). Previous studies have reported that the fimbriae of UPEC are involved in virulence and antimicrobial resistance. We aimed to analyze the fimbrial gene profiles of UPEC and investigate the specificity of these expressions in symptomatic UTI, urinary device use, and levofloxacin (LVFX) resistance/extended-spectrum beta-lactamase (ESBL) production. Methods: A total of 120 UPEC strains were isolated by urine culture between 2019 and 2023 at our institution. They were subjected to an antimicrobial susceptibility test and polymerase chain reaction (PCR) to identify 14 fimbrial genes and their association with clinical outcomes or antimicrobial resistance. Results: The prevalence of the papG2 gene was significantly higher in the symptomatic UTI group by multivariate analyses (OR 5.850, 95% CI 1.390–24.70, p = 0.016). The prevalence of the c2395 gene tended to be lower in the symptomatic UTI group with urinary devices (all p < 0.05). In LVFX-resistant UPEC strains from both the asymptomatic bacteriuria (ABU) and the symptomatic UTI group, the expression of the papEF, papG3, c2395, and yadN genes tended to be lower (all p < 0.05). Conclusion: The fimbrial genes of UPEC are associated with virulence and LVFX resistance, suggesting that even UPEC with fewer motility factors may be more likely to ascend the urinary tract in the presence of the urinary devices. These findings may enhance not only the understanding of the virulence of UPEC but also the management of UTI. Full article

Robust credit risk prediction in emerging economies increasingly demands the integration of external factors (EFs) beyond borrowers’ control. This study introduces a scenario-based methodology to incorporate EF—namely COVID-19 severity (mortality and confirmed cases), climate anomalies (temperature deviations, weather-induced road blockages), and social unrest—into machine learning (ML) models for credit delinquency prediction. The approach is grounded in a CRISP-DM framework, combining stationarity testing (Dickey–Fuller), causality analysis (Granger), and post hoc explainability (SHAP, LIME), along with performance evaluation via AUC, ACC, KS, and F1 metrics. The empirical analysis uses nearly 8.2 million records compiled from multiple sources, including 367,000 credit operations granted to individuals and microbusiness owners by a regulated Peruvian financial institution (FMOD) between January 2020 and September 2023. These data also include time series of delinquency by economic activity, external factor indicators (e.g., mortality, climate disruptions, and protest events), and their dynamic interactions assessed through Granger causality to evaluate both the intensity and propagation of external shocks. The results confirm that EF inclusion significantly enhances model performance and robustness. Time-lagged mortality (COVID MOV) emerges as the most powerful single predictor of delinquency, while compound crises (climate and unrest) further intensify default risk—particularly in portfolios without public support. Among the evaluated models, CNN and XGB consistently demonstrate superior adaptability, defined as their ability to maintain strong predictive performance across diverse stress scenarios—including pandemic, climate, and unrest contexts—and to dynamically adjust to varying input distributions and portfolio conditions. Post hoc analyses reveal that EF effects dynamically interact with borrower income, indebtedness, and behavioral traits. This study provides a scalable, explainable framework for integrating systemic shocks into credit risk modeling. The findings contribute to more informed, adaptive, and transparent lending decisions in volatile economic contexts, relevant to financial institutions, regulators, and risk practitioners in emerging markets. Full article

UAV remote sensing is widely used in the agricultural sector due to its non-destructive, rapid, and cost-effective advantages. This study utilized two years of field data with multisource fused imagery of soybeans to evaluate lodging conditions and investigate the impact of lodging grade information on yield prediction. Unlike traditional approaches that build empirical lodging models using band reflectance, vegetation indices, and texture features, this research introduces a transfer learning framework. This framework employs a ResNet18 encoder to directly extract features from raw images, bypassing the complexity of manual feature extraction processes. To address the imbalance in the lodging dataset, the Synthetic Minority Over-sampling Technique (SMOTE) strategy was employed in the feature space to balance the training set. The findings reveal that deep learning effectively extracts meaningful features from UAV imagery, outperforming traditional methods in lodging grade classification across all growth stages. On the 65 days after emergence (DAE), lodging grade classification using ResNet18 features achieved the highest accuracy (Accuracy = 0.76, recall = 0.76, F1 score = 0.73), significantly exceeding the performance of traditional methods. However, classification accuracy was relatively low in plots with higher lodging grades (lodging grades = 3, 5, 7), with an accuracy of 0.42 and an F1 score of 0.56. After applying the SMOTE module to balance the samples, the classification accuracy in plots with higher lodging grades improved to 0.65, marking an increase of 54.76%. To improve accuracy in yield prediction, this study integrates lodging information with other features, such as canopy spectral reflectance, vegetation indices, and texture features, using two multimodal data fusion strategies: input-level fusion (ResNet-EF) and intermediate-level fusion (ResNet-MF). The findings reveal that the intermediate-level fusion strategy consistently outperforms input-level fusion in yield prediction accuracy across all growth stages. Specifically, the intermediate-level fusion model incorporating measured lodging grade information achieved the highest prediction accuracy on the 85 DAE (R² = 0.65, RMSE = 529.56 kg/ha). Furthermore, when predicted lodging information was used, the model’s performance remained comparable to that of the measured lodging grades, underscoring the critical role of lodging factors in enhancing yield estimation accuracy. Full article

Hybrid nanostructures can be engineered to exhibit superior functionality beyond the level attainable from each of the constituent nanomaterials by synergistically integrating their unique properties. In this work, we designed individual hybrid nanorods (NRs) of ZnO–Ag in different heterojunction configurations where each hybrid NR consists of a single ZnO NR forming a junction with a single Ag NR. We subsequently employed the ZnO–Ag hybrid NRs in the fluorescence detection of the model chemical and biological analytes, rhodamine 6G (R6G), and tumor necrosis factor-α (TNF-α), that undergo simple as well as more complex immunoreaction steps on the hybrid NRs. We determine how parameters such as the analyte concentration, ZnO–Ag heterojunction configuration, and NR length can influence the fluorescence signals, enhancement factors (EFs), as well as changes in EFs (%EFs) at different positions on the hybrid NRs. We provide much needed insights into the fluorescence enhancement capability of single hybrid NR systems using a signal source located external to the NRs. Moreover, we identify key consideration factors that are critical to the design and optimization of a hybrid NR platform for achieving high signal enhancements. We show that higher EFs are consistently observed from the junction relative to other positions in a given hybrid NR, from the end–end relative to other heterojunction configurations, and from longer than shorter ZnO NRs. Our research efforts demonstrate that the synergistic interplay of the two component NRs of ZnO and Ag escalates the fluorescence detection capability of the ZnO–Ag hybrid NR. A superior enhancement level surpassing those attainable by each component NR alone can be obtained from the hybrid NR. Hence, our work further substantiates the potential utility of individual semiconductor-metal hybrid NRs for highly miniaturized and ultra-trace level detection, especially by leveraging the critical consideration factors to achieve a higher detection capability. Full article

Surface-enhanced Raman scattering (SERS) is extensively employed for detecting organics, where its sensitivity and selectivity are strongly influenced by the properties of the SERS substrates. In this work, a simple hydrothermal synthesis followed by a subsequent reduction was used to prepare Au-CeO₂ composite nanocubes as a new SERS substrate, in which the side length of the CeO₂ cubes was 20~30 nm and the diameter of the Au nanoparticles was 5~25 nm. Using methylene blue (MB) and crystal violet (CV) as probe molecules, the lowest detection limit (LDL) of methylene blue (MB) on the Au-CeO₂ composite nanocubes substrate was 10⁻⁷ M, and the maximum SERS enhancement factor (EF) was 2.6 × 10⁵. As a result, the lowest detection limit (LDL) of crystal violet (CV) was 10⁻⁷ M, and the maximum enhancement factor (EF) was 3.7 × 10⁴. The above results proved that the Au-CeO₂ composite nanocubes had a quite good Raman enhancement effect, which could be used as a SERS substrate. Finally, a Raman enhancement mechanism is proposed for the Au-CeO₂ nanucubes. Full article