Search Results (1,104)

Background: Gemcitabine (GEM) remains a cornerstone in the treatment of pancreatic cancer. Upon exposure to GEM, pancreatic cancer cells (PCCs) tend to adapt quickly to outcompete drug-induced cytotoxicity, thereby contributing to treatment failure. Thus, understanding GEM-induced molecular changes in PCCs is important. Methods: Three primary PCC lines (PCC-1, PCC-2, PCC-7) and Mia PaCa-2 cultured for 40 passages (p) in the absence (control) or presence of GEM (GemR) were assessed for phenotypic changes. Proteome profiles for all PCCs at p10, p20, p25, p30, p35, and p40 were obtained using mass spectrometry (MS). Protein expression was determined using immunoblotting. Differentially abundant proteins (DAPs) were evaluated for enrichment of functional and biological attributes and protein–protein interactions. Results: GEM sensitivity and growth were both reduced in GemR versus paired controls for all four PCC lines. MS mapped > 7000 proteins in each PCC line, and the abundance of 70–83% of these was found to be significantly altered when comparing all sample groups. Proteomic changes in GemR versus paired controls differed remarkably among the PCCs and were affected by passaging and treatment duration. DAPs at p40 were mostly related to metabolic pathways, including nucleotide metabolism and diverse cell growth processes. Several closely related DAPs and multiple hub proteins in each PCC line were identified. Conclusions: Overall, this study revealed cell-line-specific, heterogeneous changes in proteome profiles of PCCs following their long-term exposure to GEM, and these were likely affected by treatment duration, dosage, and passaging. Full article

This study experimentally investigates the mechanical and dynamic hygrothermal behavior of compressed earth block (CEB) walls subjected to simulated climatic cycles representative of a tropical humid environment. Four formulations were tested: raw soil (D0), soil with kenaf fibers (DF), soil with fibers and cement (DFC), and soil with fibers, cement, and slag (DFCL). Performance was assessed in an instrumented bi-climatic cell, enabling the determination of thermal and hygroscopic attenuation factors and time lags, complemented by standardized uniaxial compression and three-point bending tests. DFCL achieved a compressive strength of about 10 MPa, nearly twice that of DF (~6 MPa), exceeding the threshold required for buildings up to R + 1. Regarding hygrothermal behavior, DFCL exhibited the highest thermal attenuation factor (2.24) and a hygroscopic attenuation factor of 2.05, with corresponding time lags of ~0.9 h (thermal) and ~1.1 h (hygroscopic). These results highlight superior thermal inertia and moisture regulation, well suited to the constraints of tropical humid climates. Overall, the findings confirm the potential of kenaf fiber-reinforced cement–slag stabilized CEBs as a sustainable construction solution, particularly for load-bearing walls in hot and humid regions. In addition to technical performance, DFCL also offers environmental and economic advantages, as the use of local fibers and slag reduces Portland cement consumption and costs, reinforcing its sustainability potential in tropical contexts. Full article

This study investigates the dynamics and sources of atmospheric mercury in Qinhuangdao (QHD), a coastal urban area significantly impacted by both marine and terrestrial sources. Sampling of gaseous elemental mercury (GEM), fine particle-bound mercury (PBM_2.5), and coarse particle-bound mercury (PBM_2.5–10) was conducted from September 2022 to August 2023. The annual mean concentrations of GEM, PBM_2.5, and PBM_2.5–10 were 2.66, 1.01, and 0.73 ng m⁻³, respectively, with PBM levels among the highest reported for coastal cities in eastern China. GEM displayed a pronounced midday peak (12:00–14:00) with correlations to temperature (R² = 0.25–0.65) and a significant winter association with SO₂ (R² = 0.52), suggesting the combined influence of surface re-emission and coal combustion. Seasonal variations in the GEM/CO ratio (spring: 7.12; winter: 2.62) further reflected the shift between natural and combustion-related sources. PBM_2.5 exhibited elevated concentrations (1.0–1.4 ng m⁻³) under westerly winds (~3 m s⁻¹), indicating inputs from traffic, shipping, and light industries, while PBM_2.5–10 (0.5–1.1 μg m⁻³) was strongly linked to coal-handling activities at QHD port and soil resuspension. Backward trajectory analysis showed continental air masses dominated in winter (53–100%) and maritime air masses in summer (30–50%), whereas high Hg/Na ratios in PM_2.5 (3.22 × 10⁻⁴) and PM_2.5–10 (2.17 × 10⁻⁴), far exceeding typical marine aerosol values (10⁻⁷–10⁻⁵), indicated negligible marine contributions to PBM. These findings provide new insights into the processes driving mercury pollution in coastal urban environments and highlight the critical role of port-related activities in regional mercury management. Full article

Kimberlite has attracted considerable interest among geologists as the primary source of natural gem-quality diamonds. The term “transitional kimberlite” was previously introduced to categorize rocks that exhibit bulk geochemical and Sr–Nd isotopic characteristics intermediate between those of archetypal kimberlite (formerly Group-I) and orangeite (formerly Group-II). Nevertheless, the petrogenesis of transitional diamond-bearing kimberlites remains poorly understood due to limited research. The diamondiferous transitional Wafangdian kimberlite in the North China Craton (NCC) thus provides a valuable opportunity for a detailed case study. We investigated fresh hypabyssal transitional Wafangdian kimberlites using bulk-rock major and trace element geochemistry to constrain near-primary parental magma compositions and decipher their petrogenesis. Geochemical compositions identify samples affected by crustal contamination based on elevated SiO₂, Pb, heavy rare earth element (HREE) concentrations, and Sr isotopic ratios. Compositional variations among macrocrystic samples (MgO: 29.7–31.5 wt.%; SiO₂: 30.6–34.7 wt.%; CaO: 3.9–7.5 wt.%; Mg^# [atomic Mg/(Mg + Fe²⁺) × 100]: 85–88) result from substantial entrainment and partial assimilation of peridotite xenoliths (up to 35%). In contrast, variations within aphanitic samples (MgO: 24.0–29.7 wt.%; SiO₂: 27.7–30.9 wt.%; CaO: 6.0–11.8 wt.%; Mg^#: 81–85) are attributed to fractional crystallization of olivine and phlogopite (~1–32%). Based on these constraints, the near-primary parental magma composition for the Wafangdian kimberlite is estimated as ~29.7 wt.% SiO₂, ~29.7 wt.% MgO, and Mg^# 85. Trace element concentrations in the transitional Wafangdian kimberlites resemble those of archetypal kimberlites globally (e.g., Nb/U > 26, La/Nb < 1.4, Ba/Nb < 16, Th/Nb < 0.25), indicating a shared convective mantle source. However, the Wafangdian kimberlites exhibit distinct characteristics: ε_Nd(t) values ranging from −3.44 to −1.77, higher Al₂O₃ and K₂O contents, and lower Ce/Pb ratios (10–20) compared to archetypal kimberlites. These features suggest the mantle source region was profoundly influenced by deeply subducted oceanic material. Full article

At present, although there are a variety of assessment systems to rate the financing ability of enterprises, these systems suffer from the problems of outdated indicators and subjective weighting methods. In this paper, the impact of ESG performance on financing ability is taken as an evaluation index and combined with 13 other indexes to construct a new TOPSIS assessment system. Cooperative game theory in the form of the entropy weight method and a BP neural network is used to avoid the subjectivity of weighting. After establishing the evaluation model, we selected cross-sectional data from 4590 listed companies on the Shanghai and Shenzhen stock exchanges in 2023 to train the evaluation model and explore the impact of various indicators on financing capabilities. The results show the following: (1) Total revenue and total assets of main board companies are the main factors affecting financing ability. (2) Total revenue growth rate, total revenue, and R&D costs of Science and Technology Innovation Board Market (STAR Market) companies are the main factors affecting the financing ability. (3) Growth Enterprise Market (GEM) companies’ total revenue and R&D costs are the main factors affecting financing ability. This study uses data from 2023. In practical applications, it is recommended to use the latest data for evaluation and analysis, and to update the weights every six months. Full article

Isolated permafrost is widely distributed in freeze–thaw transition zones, characterized by blurred boundaries and strong spatial variability. Traditional methods such as drilling and electrical resistivity surveys are often limited in achieving efficient and continuous boundary identification. This study focuses on a typical isolated permafrost region in Northeast China and proposes a boundary detection strategy based on multi-frequency electromagnetic (EM) measurements using the GEM-2 sensor. By designing multiple frequency combinations and applying joint inversion, a boundary identification framework was developed and validated against borehole data. Results show that the multi-frequency joint inversion method improves the spatial identification accuracy of permafrost boundaries compared to traditional point-based techniques. In areas lacking boreholes, the method still demonstrates coherent boundary imaging and strong adaptability to geomorphological conditions. The multi-frequency joint inversion strategy significantly enhances imaging continuity and effectively captures electrical variations in complex freeze–thaw transition zones. Overall, this study establishes a complete non-invasive technical workflow—“acquisition–inversion–validation–imaging”—providing an efficient and scalable tool for engineering site selection, foundation design, and permafrost degradation monitoring. It also offers a methodological paradigm for electromagnetic frequency optimization and subsurface electrical boundary modeling. Full article

This study presents a comprehensive validation of total ozone columns from ozone profile (O₃P) and total ozone column (O₃T) products measured by the Geostationary Environment Monitoring Spectrometer (GEMS), through comparisons with Pandora, Ozone Mapping and Profiler Suite (OMPS) and TROPOspheric Monitoring Instrument (TROPOMI). O₃P version 3.0 demonstrates reduced dependence on viewing geometry compared to version 2.0, whereas the O₃T product shows a consistent offset between versions (v2.0 vs. v2.1). In comparison with Pandora, O₃P exhibits seasonal bias patterns similar to those seen in TROPOMI and OMPS, ranging from −2% in summer to +5% in winter. However, O₃T maintains abnormally persistent negative biases across seasons and times of day, along with a long-term degradation of 2–3% from 2021 to 2024. These findings suggest that O₃T biases likely result from uncorrected radiometric biases rather than algorithmic limitations. Validation metrics further highlight inconsistencies in O₃T, including a lower regression slope (~0.95) in the mid-latitude and higher root mean square errors in the low-latitude (~5%), compared to the other products (near 1.0 and 1–3%, respectively). Overall, O₃P outperforms TROPOMI and OMPS across most validation metrics in mid-latitudes and performs similarly at low latitudes. Full article

Conventional wastewater treatment plants (WWTPs) have limited efficiency in removing emerging pollutants (EPs), meaning these pollutants persist and lead to widespread ecological contamination. In this study, real effluents from a WWTP were characterized using TOC and Py-GC/MS, which indicated the presence of various organic compounds that could be indicative of micro-nanoplastics (MNPs) or plastics additives. To address this challenge, we propose the use of a photocatalytic membrane reactor (PMR) as an advanced treatment system capable of achieving high degradation efficiency under mild operating conditions. Preliminary experimental tests were conducted using various commercial photocatalysts (TiO₂, WO₃, Nb₂O₅), four UV lamps, and oxidants (air, O₂) using added Gemfibrozil (GEM) as a drug model compound. Real effluent samples collected from WWTP were tested with and without pretreatment to remove coarse particles prior to photocatalysis. Mineralization was achieved in both cases, but it occurred at a higher rate for the pretreated effluent. The mineralization of GEM and EPs in real effluent was achieved within five hours under UV irradiation using titanium dioxide (TiO₂) as a low-cost photocatalyst in a PMR. The results highlight the potential of photocatalytic systems, and particularly PMRs, as a promising technology for removing recalcitrant pollutants in real effluents offering a viable solution for improved environmental protection. Full article

Sparse Matrix–Vector Multiplication (SpMV) is a critical computational kernel in high-performance computing (HPC) and artificial intelligence (AI). However, its irregular memory access patterns lead to frequent cache misses on multi-level cache hierarchies, significantly degrading performance. Scratchpad memory (SPM), a software-managed, low-latency on-chip memory, offers improved data locality and control, making it a promising alternative for irregular workloads. To enhance SpMV performance, we propose a vectorized execution framework targeting SPM-augmented processors. Recognizing the limitations of traditional formats for vectorization, we introduce Sorted-Row-Block ELL (SRB-ELL), a new matrix storage format derived from ELLPACK (ELL). SRB-ELL stores only non-zero elements, partitions the matrix into row blocks, and sorts them by block size to improve load balance and SIMD efficiency. We implement and evaluate SRB-ELL on a custom processor architecture with integrated SPM using the gem5 simulator. Experimental results show that, compared to vectorized CSR-based SpMV, the SRB-ELL design achieves up to 1.48× speedup and an average of 1.19×. Full article

The impact of encapsulating gemcitabine (GEM) into nanoparticles on its delivery remains underexplored, with the potential benefits of targeted drug delivery and stimuli-responsive release yet to be fully clarified. Herein, we designed a near-infrared (NIR) light-responsive polymeric nanoparticle, ZnPc@P(PEG-CMA-TKGEM), which integrates reactive oxygen species (ROS) generation and cell imaging capabilities. The self-assembled polymeric micelles exhibit a hydrodynamic size of ~134 nm. Under NIR irradiation, the cumulative drug release rate reaches 51% within 48 h, which is three times higher than that of the non-irradiated control group. In cytotoxicity assays, the cell viability of the NIR-irradiated drug-loaded group is approximately 17%, while that of the NIR-irradiated blank group (without drug loading) remains above 80%. These results confirm that the nanocarriers successfully deliver GEM to target cells and achieve controlled drug release via NIR stimulation. Full article

Background and Objectives: Endometrial adenocarcinoma is among the most prevalent malignancies of the female reproductive system, and therapeutic options remain limited, particularly in advanced stages. In recent years, natural agents, especially flavonoids, have gained considerable interest for their capacity to enhance the effectiveness of chemotherapeutic drugs and modulate tumor-related molecular mechanisms. Hesperidin, a citrus-derived flavonoid, is recognized for its antioxidant and anti-inflammatory effects, while Gemcitabine, a nucleoside analog, is widely used in cancer treatment. Investigating their combined effects on endometrial carcinoma cells could yield novel insights into multimodal therapeutic development. This current study aimed to assess the impact of Hesperidin (Hes) and Gemcitabine (Gem) on ISHIKAWA cells, a human endometrial adenocarcinoma model, with particular attention to pathways associated with hypoxia, angiogenesis, apoptosis, and oxidative stress. Materials and Methods: ISHIKAWA cells were treated with varying concentrations of Hes (50–200 µM) and Gem (10–50 nM), either individually or together, for 24 and 48 h. Cell viability was determined using the MTT assay, while apoptosis was measured by Caspase-3/7 activity and NucBlue nuclear staining. Intracellular reactive oxygen species (ROS) generation was quantified via DCFH-DA fluorescence. Expression levels of HIF-1α, VEGF, Bax, Bcl-2, and Caspase-3 were examined by RT-qPCR. Synergistic interactions were analyzed with the Chou–Talalay combination index. Biological enrichment was further explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Results: Both Hes and Gem significantly decreased ISHIKAWA cell viability in a concentration- and time-dependent manner (p < 0.001). The combined treatment induced stronger apoptotic effects, as reflected by increased Caspase-3/7 activity and nuclear morphological changes. RT-qPCR demonstrated upregulation of Bax and Caspase-3, together with downregulation of Bcl-2, HIF-1α, and VEGF. While Hes reduced intracellular ROS, Gem elevated it; their combination produced a balanced oxidative response. All dose combinations displayed strong synergism (CI < 1). GO and KEGG enrichment confirmed the involvement of apoptosis-, angiogenesis-, and hypoxia-related pathways. Conclusions: Co-treatment with Hes and Gem exhibits synergistic anticancer activity in endometrial cancer cells by promoting apoptosis, suppressing angiogenesis- and hypoxia-related gene expression, and modulating oxidative stress. This combined therapeutic approach highlights its potential as a promising adjuvant option, warranting further evaluation in in vivo and translational studies. Full article

Recent developments in large language models allow for real time, context-aware tutoring. AI Gem, presented in this article, is a layered architecture that integrates personalization, adaptive feedback, and curricular alignment into transformer based tutoring agents. The architecture combines retrieval augmented generation, Bayesian learner model, and policy-based dialog in a verifiable and deployable software stack. The opportunities are scalable tutoring, multimodal interaction, and augmentation of teachers through content tools and analytics. Risks are factual errors, bias, over reliance, latency, cost, and privacy. The paper positions AI Gem as a design framework with testable hypotheses. A scenario-based walkthrough and new diagrams assign each learner step to the ten layers. Governance guidance covers data privacy across jurisdictions and operation in resource constrained environments. Full article

We present new spectroscopic orbits for the bright binaries Mizar B, 3 Pup, $\nu$ Gem, 2 Lac, and $\varphi$ Aql. Our analysis is based on medium-resolution ($R\approx$ 12,000) échelle spectra obtained with the 0.81-m telescope and fiber-fed eShel spectrograph of the Three College Observatory (Greensboro, NC, USA) between 2015 and 2024. Orbital elements were inferred with an affine-invariant Markov-chain Monte-Carlo sampler; convergence was verified through the integrated autocorrelation time and the Gelman–Rubin statistic. Errors quote the 16th–84th-percentile credible intervals. Compared with previously published orbital solutions for the studied stars, our method improves the root-mean-square residuals by 25–50% and bring the 1$\sigma$ uncertainties on the radial velocity (RV) semi-amplitudes down to 0.02–0.15 km $s^{-1}$. These gains translate into markedly tighter mass functions and systemic RVs, providing a robust dynamical baseline for future interferometric and photometric studies. A complete Python analysis pipeline is openly available in a GitHub repository, ensuring full reproducibility. The results demonstrate that a Bayesian RV analysis with well-motivated priors and rigorous convergence checks yields orbital parameters that are both more precise and more reproducible than previous determinations, while offering fully transparent uncertainty budgets. Full article

This study explored the use of Borassus fruit fiber as reinforcement for earthen matrices (BFRC). The experimental results of the testing carried out on the structural properties were used to generate a primary dataset for training and testing machine learning (ML) models. Linear regression (LR), Decision tree regressor (DTR), and gradient boosting regression (GBR) were used to build an ensemble learning (EL) model during the prediction of the hygroscopic properties, Young’s modulus, and compressive strength of the BFRC. Fiber content, activation concentration, curing days, dry weight, saturated weight, mass, flexural vibration, longitudinal vibration, correction factor, maximum load, and cross-sectional area were the various inputs considered in the structural properties prediction. The performance of both EL and single models (SMs) was appraised via three performance metrics—mean square error (MSE), root mean square (RMSE), and the coefficient of determination (R²)—to comparatively ascertain the model’s efficiency. Results showed that all models exhibited high accuracy in predicting Young’s modulus and compressive strength. Ensemble learning outperformed single models in predicting these properties, with MSE, RMSE, and R² of 0.01 MPa, 0.1 MPa, and 99% and 3,923,262.5 MPa, 1980.7 Pa, and 99% for compressive strength and Young’s modulus, respectively. However, for hygroscopic behavior, linear regression (LR) demonstrated superior performance compared to other models, with MSE, RMSE, and R² values of 0.13%, 0.36%, and 99%. Full article

Heparin-based delivery platforms have gained increasing attention in regenerative medicine due to their exceptional affinity for growth factors and versatility in structural and functional design. This review first introduces the molecular biosynthesis and physicochemical diversity of heparin, which underpin its binding selectivity and degradability. It then categorizes the delivery platforms into microspheres, nanofibers, and hydrogels, with detailed discussions on their fabrication techniques, biofunctional integration of heparin, and release kinetics. Special focus is given to stimuli-responsive systems—including pH-, enzyme-, redox-, thermal-, and ultrasound-sensitive designs—which allow spatiotemporal control over growth factor release. The platform applications are organized by tissue types, encompassing soft tissue regeneration, bone and cartilage repair, neuroregeneration, cardiovascular regeneration, wound healing, anti-fibrotic therapies, and cancer microenvironment modulation. Each section provides recent case studies demonstrating how heparin enhances the bioactivity, localization, and therapeutic efficacy of pro-regenerative or anti-pathologic growth factors. Collectively, these insights highlight heparin’s dual role as both a carrier and modulator, positioning it as a pivotal component in next-generation, precision-targeted delivery systems. Full article