Search Results (7,661)

This study synthesizes and comparatively investigates two squaric acid-based phthalocyanine-like dyes, SNF and its long-chain alkylated derivative LNF, to systematically elucidate the influence of peripheral hydrophobic groups on their third-order nonlinear optical (NLO) properties. The NLO characteristics were comprehensively characterized using femtosecond Z-scan and I-scan techniques at both 800 nm and 900 nm. Both dyes exhibited strong saturable absorption (SA), confirming their potential as saturable absorbers. Critically, the comparative analysis revealed that SNF exhibits a significantly greater nonlinear absorption coefficient (β) compared to LNF under identical conditions. For instance, at 800 nm, the β of SNF was approximately 3–5 times larger than that of LNF. This result conclusively demonstrates that the introduction of long hydrophobic alkyl chains attenuates the NLO response. Furthermore, I-scan measurements revealed excellent SA performance, with high modulation depths (e.g., LNF: 43.0% at 900 nm) and low saturation intensities. This work not only clarifies the structure–property relationship in these D-A-D dyes but also presents a clear strategy for modulating the NLO properties of organic chromophores for applications in near-infrared pulsed lasers. Full article

Background/Objectives: Cancer suffers from unresolved therapeutic challenges owing to the lack of targeted therapies and heightened recurrence risk. This study aimed to investigate the new series of hydroxamate by structurally modifying the pharmacophore of vorinostat. Methods: The present work involves the synthesis of 15 differently substituted 2H-1,2,3-triazole-based hydroxamide analogs by employing triazole ring as a cap with varied linker fragments. The compounds were evaluated for their anticancer effect, especially their anti-breast cancer response. Molecular docking and molecular dynamics simulations were conducted to examine binding interactions. Results: Results indicated that among all synthesized hybrids, the molecule VI(i) inhibits the growth of MCF-7 and A-549 cells (GI₅₀ < 10 μg/mL) in an antiproliferative assay. Compound VI(i) was also tested for cytotoxic activity by employing an MTT assay against A549, MCF-7, and MDA-MB-231 cell lines, and the findings indicate its potent anticancer response, especially against MCF-7 cells with IC₅₀ of 60 µg/mL. However, it experiences minimal toxicity towards the normal cell line (HEK-293). Mechanistic studies revealed a dual-pathway activation: first, apoptosis (17.18% of early and 10.22% of late apoptotic cells by annexin V/PI analysis); second, cell cycle arrest at the S and G2/M phases. It also promotes ROS generation in a concentration-dependent manner. The HDAC–inhibitory assay, extended in silico molecular docking, and MD simulation experiments further validated its significant binding affinity towards HDAC 1 and 6 isoforms. DFT and ADMET screening further support the biological proclivity of the title compounds. The notable biological contribution of VI(i) highlights it as a potential candidate, especially against breast cancer cells. Full article

This study presents the development of Cu-doped NiMo/TiO₂ photoelectrocatalysts for simultaneous green hydrogen production and pharmaceutical pollutant removal under simulated solar irradiation. The catalysts were synthesized via wet impregnation (15 wt.% total metal loading with 0.6 wt.% Cu) and thermally treated at 400 °C and 900 °C to investigate structural transformations and catalytic performance. Comprehensive characterization (XRD, BET, SEM, XPS) revealed phase transitions, enhanced crystallinity, and redistribution of redox states upon Cu incorporation, particularly the formation of NiTiO₃ and an increase in oxygen vacancies. Crystallite sizes for anatase, rutile, and brookite ranged from 21 to 47 nm at NiMoCu400, while NiMoCu900 exhibited only the rutile phase with 55 nm crystallites. BET analysis showed a surface area of 44.4 m²·g⁻¹ for NiMoCu400, and electrochemical measurements confirmed its higher electrochemically active surface area (ECSA, 2.4 cm²), indicating enhanced surface accessibility. In contrast, NiMoCu900 exhibited a much lower BET surface area (1.4 m²·g⁻¹) and ECSA (1.4 cm²), consistent with its inferior photoelectrocatalytic performance. Compared to previously reported binary NiMo/TiO₂ systems, the ternary NiMoCu/TiO₂ catalysts demonstrated significantly improved hydrogen production activity and more efficient photoelectrochemical degradation of paracetamol. Specifically, NiMoCu400 showed an anodic peak current of 0.24 mA·cm⁻² for paracetamol oxidation, representing a 60% increase over NiMo400 and a cathodic current of –0.46 mA·cm⁻² at –0.1 V vs. RHE under illumination, nearly six times higher than the undoped counterpart (–0.08 mA·cm⁻²). Mott–Schottky analysis further revealed that NiMoCu400 retained n-type behavior, while NiMoCu900 exhibited an unusual inversion to p-type, likely due to Cu migration and rutile-phase-induced realignment of donor states. Despite its higher photosensitivity, NiMoCu900 showed negligible photocurrent, confirming that structural preservation and surface redox activity are critical for photoelectrochemical performance. This work provides mechanistic insight into Cu-mediated photoelectrocatalysis and identifies NiMoCu/TiO₂ as a promising bifunctional platform for integrated solar-driven water treatment and sustainable hydrogen production. Full article

Environmental sustainability and responsible resource utilization are critical global challenges. In this work, we present a sustainable and circular-economy-based approach for synthesizing CuFe₂O₄ nanoparticles by directly utilizing copper oxide minerals sourced from Chilean mining operations. Copper sulfate (CuSO₄) was extracted from these minerals through acid leaching and used as a precursor for nanoparticle synthesis via both chemical co-precipitation and microwave-assisted methods. The influence of different precipitating agents—NaOH, Na₂CO₃, and NaF—was systematically evaluated. XRD and FESEM analyses revealed that NaOH produced the most phase-pure and well-dispersed nanoparticles, while NaF resulted in secondary phase formation. The microwave-assisted method further improved particle uniformity and reduced agglomeration due to rapid and homogeneous heating. Electrochemical characterization was conducted to assess the suitability of the synthesized CuFe₂O₄ for supercapacitor applications. Cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) measurements confirmed pseudocapacitive behavior, with a specific capacitance of up to 1000 F/g at 2 A/g. These findings highlight the potential of CuFe₂O₄ as a low-cost, high-performance electrode material for energy storage. This study underscores the feasibility of converting primary mined minerals into functional nanomaterials while promoting sustainable mineral valorization. The approach can be extended to other critical metals and mineral residues, including tailings, supporting the broader goals of a circular economy and environmental remediation. Full article

Accelerated industrialization and surging energy demands have led to continuously rising atmospheric CO₂ concentrations. Developing sustainable methods to reduce atmospheric CO₂ levels is crucial for achieving carbon neutrality. Concurrently, the rapid development of new energy vehicles has driven a significant increase in demand for lithium-ion batteries (LIBs), which are now approaching an end-of-life peak. Efficient recycling of valuable metals from spent LIBs represents a critical challenge. This study employs conventional hydrometallurgical processing to recover valuable metals from spent LIBs. Subsequently, Ni-doped Co₃O₄ (Ni:Co₃O₄) supported on the natural mineral attapulgite (ATP) was synthesized via a sol–gel method. The incorporation of a small amount of Ni into the Co₃O₄ lattice generates oxygen vacancies, inducing a localized surface plasmon resonance (LSPR) effect, which significantly enhances charge carrier transport and separation efficiency. During the photocatalytic reduction of CO₂, the primary product CO generated by the Ni:Co₃O₄/ATP composite achieved a high production rate of 30.1 μmol·g⁻¹·h⁻¹. Furthermore, the composite maintains robust catalytic activity even after five consecutive reaction cycles. Full article

Cancer metabolic reprogramming plays a critical role in tumor progression and therapeutic resistance, underscoring the need for advanced analytical strategies. Metabolomics, leveraging mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, offers a comprehensive and functional readout of tumor biochemistry. By enabling both targeted metabolite quantification and untargeted profiling, metabolomics captures the dynamic metabolic alterations associated with cancer. The integration of metabolomics with machine learning (ML) approaches further enhances the interpretation of these complex, high-dimensional datasets, providing powerful insights into cancer biology from biomarker discovery to therapeutic targeting. This review systematically examines the transformative role of ML in cancer metabolomics. We discuss how various ML methodologies—including supervised algorithms (e.g., Support Vector Machine, Random Forest), unsupervised techniques (e.g., Principal Component Analysis, t-SNE), and deep learning frameworks—are advancing cancer research. Specifically, we highlight three major applications of ML–metabolomics integration: (1) cancer subtyping, exemplified by the use of Similarity Network Fusion (SNF) and LASSO regression to classify triple-negative breast cancer into subtypes with distinct survival outcomes; (2) biomarker discovery, where Random Forest and Partial Least Squares Discriminant Analysis (PLS-DA) models have achieved >90% accuracy in detecting breast and colorectal cancers through biofluid metabolomics; and (3) prognostic modeling, demonstrated by the identification of race-specific metabolic signatures in breast cancer and the prediction of clinical outcomes in lung and ovarian cancers. Beyond these areas, we explore applications across prostate, thyroid, and pancreatic cancers, where ML-driven metabolomics is contributing to earlier detection, improved risk stratification, and personalized treatment planning. We also address critical challenges, including issues of data quality (e.g., batch effects, missing values), model interpretability, and barriers to clinical translation. Emerging solutions, such as explainable artificial intelligence (XAI) approaches and standardized multi-omics integration pipelines, are discussed as pathways to overcome these hurdles. By synthesizing recent advances, this review illustrates how ML-enhanced metabolomics bridges the gap between fundamental cancer metabolism research and clinical application, offering new avenues for precision oncology through improved diagnosis, prognosis, and tailored therapeutic strategies. Full article

A new series of 6-arylaminoflavones was synthesized via the Buchwald–Hartwig cross-coupling reaction, aiming to functionalize the flavone core efficiently. Reaction optimization revealed that Pd₂(dba)₃/XantPhos with Cs₂CO₃ in toluene provided the best yields, with isolated yields ranging from 8% to 95%, depending on the arylamine structure. Steric hindrance and electron-withdrawing groups at the arylamine ring impacted the reaction outcomes. Cytotoxicity assays in different human cancer cell lines indicated that substitution patterns at both the arylamine and B-rings strongly impacted biological activity. In particular, compounds bearing a 3,4-dimethoxy substitution at the B-ring and a trifluoromethyl (13c) or chlorine (13g) group at the aniline moiety exhibited enhanced cytotoxicity. These findings provide insights into the structure–activity relationship of 6-arylaminoflavones while contributing to the development of synthetic methodologies for functionalized flavones. Full article

Background: Colorectal liver metastasis (CRLM) represents a major clinical challenge in oncology, affecting 25–50% of colorectal cancer patients and significantly impacting survival. While multimodal therapies—including surgical resection, systemic chemotherapy, and local ablative techniques—have improved outcomes, prognosis remains heterogeneous due to variations in tumor biology, patient factors, and institutional practices. Methods: This review synthesizes current evidence on prognostic factors influencing CRLM management, encompassing clinical (e.g., tumor burden, anatomic distribution, timing of metastases), biological (e.g., CEA levels, inflammatory markers), and molecular (e.g., RAS/BRAF mutations, MSI status, HER2 alterations) determinants. Results: Key findings highlight the critical role of molecular profiling in guiding therapeutic decisions, with RAS/BRAF mutations predicting resistance to anti-EGFR therapies and MSI-H status indicating potential responsiveness to immunotherapy. Emerging tools like circulating tumor DNA (ctDNA) and radiomics offer promise for dynamic risk stratification and early recurrence detection, while the gut microbiome is increasingly recognized as a modulator of treatment response. Conclusions: Despite advancements, challenges persist in standardizing resectability criteria and integrating multidisciplinary approaches. Current guidelines (NCCN, ESMO, ASCO) emphasize personalized strategies but lack granularity in terms of incorporating novel biomarkers. This exhaustive review underscores the imperative for the development of a unified, biomarker-integrated framework to refine CRLM management and improve long-term outcomes. Full article

In this study, we successfully synthesized olivine-type FePO₄ via an in situ oxidation method and further developed two composite cathode materials (o-FePO₄-1/GR-1 and o-FePO₄-1/GR-2) by incorporating graphene. The composites were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray Photoelectron Spectroscopy (XPS), revealing a three-dimensional porous layered structure with an enhanced surface area and strong interaction between FePO₄ nanoparticles and graphene layers. Electrochemical tests demonstrated that the composite electrodes exhibited significantly improved performance compared to pristine FePO₄, with discharge capacities of 147 mAh g⁻¹ at 1C and 163 mAh g⁻¹ at 0.1C for o-FePO₄-1/GR-2, approaching the level of LiFePO₄. The incorporation of graphene effectively enhanced the electrochemical reaction kinetics, highlighting the innovation of our method in developing high-performance cathode materials for lithium-ion batteries. Full article

This study investigated the effect of KOH activation on biochar, with a focus on how porosity and potassium content influence microwave-assisted catalytic biodiesel production, using experimental design approaches. Activated biochar was synthesized from oat hull waste through KOH activation, followed by pyrolysis under controlled conditions. The biochar was characterized through chemical, morphological, and physical analyses, and its catalytic performance in converting used waste cooking oil (WCO) into biodiesel was evaluated using methanol as the acyl acceptor and microwave irradiation to optimize the reaction via experimental design. Results revealed that increasing the KOH/biomass ratio significantly enhanced the specific surface area (SSA) of the catalyst, achieving a maximum SSA of 637.28 m²/g under optimal pyrolysis conditions: 600 °C for 3 h with a KOH/biomass ratio of 2. A maximum fatty acid methyl ester (FAME) yield of 100% was achieved within 1 min of microwave-assisted reaction using an optimized catalyst dosage of 2.5%, a WCO/MeOH molar ratio of 1/12, and a reaction temperature of 150 °C, with the catalyst being successfully recycled across three cycles. An economic and energy evaluation estimated a catalyst production cost of USD 176.97/kg and a biodiesel production cost of USD 8.9/kg of FAMEs. This research provides a straightforward and cost-effective approach for biofuel production. Full article

Bone metastasis remains a significant cause of morbidity and diminished quality of life in patients with advanced breast, prostate, and lung cancers. Emerging research highlights the pivotal role of reversible epigenetic alterations, including DNA methylation, histone modifications, chromatin remodeling complex dysregulation, and non-coding RNA networks, in orchestrating each phase of skeletal colonization. Site-specific promoter hypermethylation of tumor suppressor genes such as HIN-1 and RASSF1A, alongside global DNA hypomethylation that activates metastasis-associated genes, contributes to cancer cell plasticity and facilitates epithelial-to-mesenchymal transition (EMT). Key histone modifiers, including KLF5, EZH2, and the demethylases KDM4/6, regulate osteoclastogenic signaling pathways and the transition between metastatic dormancy and reactivation. Simultaneously, SWI/SNF chromatin remodelers such as BRG1 and BRM reconfigure enhancer–promoter interactions that promote bone tropism. Non-coding RNAs, including miRNAs, lncRNAs, and circRNAs (e.g., miR-34a, NORAD, circIKBKB), circulate via exosomes to modulate the RANKL/OPG axis, thereby conditioning the bone microenvironment and fostering the formation of a pre-metastatic niche. These mechanistic insights have accelerated the development of epigenetic therapies. DNA methyltransferase inhibitors (e.g., decitabine, guadecitabine) have shown promise in attenuating osteoclast differentiation, while histone deacetylase inhibitors display context-dependent effects on tumor progression and bone remodeling. Inhibitors targeting EZH2, BET proteins, and KDM1A are now advancing through early-phase clinical trials, often in combination with bisphosphonates or immune checkpoint inhibitors. Moreover, novel approaches such as CRISPR/dCas9-based epigenome editing and RNA-targeted therapies offer locus-specific reprogramming potential. Together, these advances position epigenetic modulation as a promising axis in precision oncology aimed at interrupting the pathological crosstalk between tumor cells and the bone microenvironment. This review synthesizes current mechanistic understanding, evaluates the therapeutic landscape, and outlines the translational challenges ahead in leveraging epigenetic science to prevent and treat bone metastases. Full article

In recent years, data augmentation techniques have become the predominant approach for addressing highly imbalanced classification problems in machine learning. Algorithms such as the Synthetic Minority Over-sampling Technique (SMOTE) and Conditional Tabular Generative Adversarial Network (CTGAN) have proven effective in synthesizing minority class samples. However, these methods often introduce distributional bias and noise, potentially leading to model overfitting, reduced predictive performance, increased computational costs, and elevated cybersecurity risks. To overcome these limitations, we propose a novel architecture, FADEL, which integrates feature-type awareness with a supervised discretization strategy. FADEL introduces a unique feature augmentation ensemble framework that preserves the original data distribution by concurrently processing continuous and discretized features. It dynamically routes these feature sets to their most compatible base models, thereby improving minority class recognition without the need for data-level balancing or augmentation techniques. Experimental results demonstrate that FADEL, solely leveraging feature augmentation without any data augmentation, achieves a recall of 90.8% and a G-mean of 94.5% on the internal test set from Kaohsiung Chang Gung Memorial Hospital in Taiwan. On the external validation set from Kaohsiung Medical University Chung-Ho Memorial Hospital, it maintains a recall of 91.9% and a G-mean of 86.7%. These results outperform conventional ensemble methods trained on CTGAN-balanced datasets, confirming the superior stability, computational efficiency, and cross-institutional generalizability of the FADEL architecture. Altogether, FADEL uses feature augmentation to offer a robust and practical solution to extreme class imbalance, outperforming mainstream data augmentation-based approaches. Full article

Healthy food service guidelines (HFSG) comprise food, nutrition, behavioral design, and other standards to guide the purchasing, preparation, and offering of foods and beverages in worksites and institutional food service. To date, there have been few attempts to synthesize evidence for HFSG effectiveness in non-K-12 or early childhood education sectors, particularly at worksites and institutional food services. We conducted a scoping review to achieve the following: (1) characterize the existing literature on the effectiveness of HFSG for improving the institution’s food environment, financial outcomes, and consumers’ diet quality and health, and (2) identify gaps in the literature. The initial search in PubMed and Web of Science retrieved 10,358 articles; after screening and snowball searching, 68 articles were included for analysis. Studies varied in terms of HFSG implementation settings, venues, and outcomes in both U.S. (n = 34) and non-U.S. (n = 34) contexts. The majority of HFSG interventions occurred in venues where food is sold (e.g., worksite cafeterias, vending machines). A diversity of HFSG terminology and measurement tools demonstrates the literature’s breadth. Literature gaps include quasi-experimental study designs, as well as interventions in settings that serve dependent populations (e.g., universities, elderly feeding programs, and prisons). Full article

Background: Pharmacy technicians are increasingly involved in immunization services, enhancing vaccine accessibility and reducing pharmacies’ workload. This scoping review aims to (1) provide a comprehensive overview of pharmacy technicians’ involvement in immunization services across various healthcare settings and countries, and (2) conduct a comparative analysis of training curricula for pharmacy technicians on immunization. Methods: A scoping review was conducted following the Arksey and O’Malley framework. A comprehensive search of the PubMed and Scopus databases was performed using keywords and MeSH terms such as “pharmacy technician(s)”, “immunization”, “vaccination”, “role”, and “involvement”. Studies included assessed pharmacy technicians’ roles in vaccine administration, training, and public health outcomes. Descriptive and thematic analyses were used to synthesize the findings. In addition, a supplementary analysis of immunization training curricula was conducted, reviewing programs from different countries to identify similarities, differences, and gaps in course structure, content, and delivery formats. Lastly, a comprehensive toolkit was developed, offering guidelines intended to facilitate the implementation of immunization training programs. Results: A total of 35 articles met the inclusion criteria, primarily from the United States of America (n = 30), Canada (n = 2), Ethiopia (n = 1), Denmark (n = 1) and United Kingdom (n = 1). The findings indicate that pharmacy technicians contribute significantly to vaccine administration, patient education, and workflow optimization, particularly in community pharmacies. The COVID-19 pandemic accelerated their involvement in immunization programs. Key challenges include regulatory barriers, a lack of standardized training, and resistance from other healthcare professionals. Facilitators include legislative support (e.g., the PREP Act), structured training programs, and collaborative pharmacist–technician models. Conclusions: Pharmacy technicians can play a vital role in expanding immunization services, improving vaccine uptake, and reducing pharmacist workload. Addressing regulatory inconsistencies, enhancing training, and fostering interprofessional collaboration are crucial for their effective integration of immunization programs. Since immunization by pharmacy technicians is not yet allowed in many EU countries, this review will provide a foundational basis to address their potential to support the healthcare workforce and improve access to immunization services. Full article

Background: The quality of decision-making processes is increasingly recognized as critical to public trust and policy sustainability. Objectives: This narrative review aims to identify and describe process-focused decision support models (DSMs) applied in pharmaceutical policy, and to examine their potential contributions to improving procedural quality in decisions related to pricing, reimbursement, and access to medicines. Methods: Relevant peer-reviewed and gray literature published between 2000 and 2025 was considered, drawing from key databases (e.g., PubMed and Scopus) and international policy reports (e.g., WHO, ISPOR, and HTA agencies). Studies were included if they provided insights into DSMs addressing at least one dimension of decision process quality. Results: Findings are synthesized narratively and organized by tool type, application context, and key quality dimensions. Frequently referenced tools included the Quality of Decision-Making Orientation Scheme (QoDoS), WHO-INTEGRATE, and AGREE II. QoDoS emerged as the only tool applied across regulatory, HTA, and industry settings, evaluating both individual- and organizational-level practices. WHO-INTEGRATE highlighted equity and legitimacy considerations but lacked a structured format. Overall, most tools demonstrated benefits in promoting internal consistency, transparency, and stakeholder engagement; however, their adoption remains limited, especially in low- and middle-income countries. Conclusions: Process-focused DSMs offer promising avenues for enhancing transparency, consistency, and legitimacy in pharmaceutical policy. Further exploration is needed to standardize evaluation approaches and expand the use of DSMs in diverse health systems. Full article