Search Results (12,082)

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by amyloid-β (Aβ) plaques, neurofibrillary tangles, blood–brain barrier dysfunction, oxidative stress (OS), and neuroinflammation. Current treatments provide symptomatic relief, but do not halt the disease’s progression. OS plays a crucial role in AD pathogenesis by promoting Aβ accumulation. Nuclear factor erythroid 2-related factor 2 (NRF2) is a key regulator of the antioxidant response, influencing genes involved in OS mitigation, mitochondrial function, and inflammation. Dysregulation of NRF2 is implicated in AD, making it a promising therapeutic target. Emerging evidence suggests that adherence to a Mediterranean diet (MD), which is particularly rich in polyphenols from extra virgin olive oil (EVOO), is associated with improved cognitive function and a reduced risk of mild cognitive impairment. Polyphenols can activate NRF2, enhancing endogenous antioxidant defenses. This study employs a computational approach to explore the potential of bioactive compounds in EVOO to modulate NRF2-related pathways in AD. We analyzed transcriptomic data from AD and EVOO-treated samples to identify NRF2-associated genes, and used chemical structure-based analysis to compare EVOO’s bioactive compounds with known NRF2 activators. Enrichment analysis was performed to identify common biological functions between NRF2-, EVOO-, and AD-related pathways. Our findings highlight important factors and biological functions that provide new insight into the molecular mechanisms through which EVOO consumption might influence cellular pathways associated with AD via modulation of the NRF2 pathway. The presented approach provides a different perspective in the discovery of compounds that may contribute to neuroprotective mechanisms in the context of AD. Full article

Annona amazonica R.E. Fries (synonyms Annona amazonica var. lancifolia R.E. Fries), popularly known in Brazil as “envireira”, is a tropical tree belonging to the Annonaceae family and is traditionally used as a food source. In this work, the in vitro and in vivo anti-liver cancer effects of essential oil (EO) from A. amazonica leaves were investigated for the first time. The chemical composition of the EO was evaluated via GC–MS and GC–FID. The alamar blue assay was used to evaluate the cytotoxicity of EOs against different cancerous and noncancerous cell lines. Cell cycle analyses, YO-PRO-1/PI staining, and rhodamine 123 staining were performed via flow cytometry in HepG2 cells treated with EO. The in vivo antitumor activity of EO was evaluated in NSG mice that were xenografted with HepG2 cells and treated with EO at a dose of 60 mg/kg. The major constituents (>5%) of the EO were (E)-caryophyllene (32.01%), 1,8-cineole (13.93%), α-copaene (7.77%), α-humulene (7.15%), and α-pinene (5.13%). EO increased apoptosis and proportionally decreased the number of viable HepG2 cells. The induction of DNA fragmentation and cell shrinkage together with a significant reduction in the ΔΨm in EO-treated HepG2 cells confirmed that EO can induce apoptosis. A significant 39.2% inhibition of tumor growth in vivo was detected in EO-treated animals. These data indicate the anti-liver cancer potential of EO from A. amazonica leaves. Full article

Allergic contact dermatitis (ACD) is an immunologic reaction to a dermal chemical exposure that, once triggered in an individual, will result in an allergic response following subsequent encounters with the allergen. Air Force epidemiological consultations have indicated that aircraft structural maintenance workers may experience ACD at elevated rates compared to other occupations. We aimed to better understand the utility of non-animal testing methods in characterizing the sensitization potential of chemicals used during Air Force operations by evaluating the skin sensitization hazard of Air Force-relevant chemicals using new approach methodologies (NAMs) in a case study. We also evaluated the use of NAM data to develop preliminary candidate surface guidelines (PCSGs, maximum concentrations of chemicals on workplace surfaces to prevent induction of dermal sensitization) for chemicals identified as sensitizers. NAMs for assessing skin sensitization, including in silico models and experimental assays, were leveraged into an integrated approach to predict sensitization hazard for 19 chemicals. Local lymph node assay effective concentration values were predicted from NAM assay data via previously published quantitative models. The derived values were used to calculate PCSGs, which can be used to compare the presence of these chemicals on work surfaces to better understand the risk of Airmen developing ACD from occupational exposures. Full article

Background/Objectives: Hyperlipidemia is a major risk factor for cardiovascular disease and atherosclerosis. Polyphenols found in polyphenol-rich extra virgin olive oil (EVOO) have been shown to possess strong antioxidant, anti-inflammatory, and cardioprotective properties. The present study aimed to assess the effects of two types of EVOO with different polyphenol content and dosages on the lipid profile of hyperlipidemic patients. Methods: In this single-blind, randomized clinical trial, 50 hyperlipidemic patients were randomized to receive either a higher-dose, lower-phenolic EVOO (414 mg/kg phenols, 20 g/day) or a lower-dose, higher-phenolic EVOO (1021 mg/kg phenols, 8 g/day), for a period of 4 weeks. These doses were selected to ensure equivalent daily polyphenol intake in both groups (~8.3 mg of total phenols/day), based on chemical analysis performed using NMR spectroscopy. The volumes used (8–20 g/day) reflect typical daily EVOO intake and were well tolerated by participants. A group of 20 healthy individuals, separated into two groups, also received the two types of EVOO, respectively, for the same duration. Primary endpoints included blood levels of total blood cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, lipoprotein-a (Lpa), and apolipoproteins A1 and B. Measurements were performed at baseline and at the end of the 4-week intervention. Linear mixed models were performed for the data analysis. Results: The higher-phenolic, lower-dose EVOO group showed a more favorable change in total blood cholesterol (p = 0.045) compared to the lower-phenolic, higher-dose group. EVOO intake was associated with a significant increase in HDL (p < 0.001) and reduction in Lp(a) (p = 0.040) among hyperlipidemic patients in comparison to healthy individuals. Conclusions: EVOO consumption significantly improved the lipid profile of hyperlipidemic patients. Higher-phenolic EVOO at lower dosages appears to be more effective in improving the lipid profile than lower-phenolic EVOO in higher dosages. Full article

The unique properties of graphene have allowed for the development of graphene-based field-effect transistors (GFETs) for applications in biosensors and chemical devices. However, the modeling and optimization of GFET performance exhibit great challenges. Herein, we propose a quantum transport simulation model for graphene-based field-effect transistors (GFETs) implemented in the open-source Octave programming language. The proposed simulation model (named SimQ) combines the Landauer–Büttiker formalism with self-consistent Schrödinger–Poisson solutions, enabling reliable simulations of transport phenomena. Our approach agrees well with established models, achieving Landauer–Büttiker transmission and tunneling transmission of 0.28 and 0.92, respectively, which are validated against experimental data. The model can predict key GFET characteristics, including carrier mobilities (500–4000 cm²/V·s), quantum capacitance effects, and high-frequency operation (80–100 GHz). SimQ offers detailed insights into charge distribution and wave function evolution, achieving an enhanced computational efficiency through optimized algorithms. Our work contributes to the modeling of graphene-based field-effect transistors, providing a flexible and accessible simulation platform for designing and optimizing GFETs with potential applications in the next generation of electronic devices. Full article

In the preceding and early stages of cancer progression, local drug delivery to pre-cancerous and cancerous skin lesions may be applied as an alternative or supplementary therapy. At present, 5-Fluorouracil, imiquimod, and tirbanibulin creams and ointments have established their place in practice, while several other active pharmaceutical ingredients (APIs) (e.g., calcipotriol, tretinoin, diclofenac) have been repurposed, used off-label, or are currently being investigated in mono- or combined chemotherapies of skin cancers. Apart from them, dozens to hundreds of therapeutics of natural and synthetic origin are proven to possess anti-tumor activity against melanoma, squamous cell carcinoma (SCC), and other skin cancer types in in vitro studies. Their clinical introduction is most often limited by low skin permeability, challenged targeted drug delivery, insufficient chemical stability, non-selective cytotoxicity, or insufficient safety data. A variety of prodrug and nanotechnological approaches, including vesicular systems, micro- and nanoemulsions, solid lipid nanoparticles, nanostructured lipid carriers, polymeric nanoparticles, and others, offer versatile solutions for overcoming the biophysical barrier function of the skin and the undesirable physicochemical nature of some drug molecules. This review aims to present the most significant aspects and latest achievements on the subject. Full article

Promoting sustainable development requires a clear understanding of how short-term fluctuations in anthropogenic emissions affect urban environmental quality. This is especially relevant for cities experiencing rapid industrial changes or emergency policy interventions. Among key environmental concerns, variations in ambient pollutants like ozone (O₃) are closely tied to both public health and long-term sustainability goals. However, traditional chemical transport models often face challenges in accurately estimating emission changes and providing timely assessments. In contrast, statistical approaches such as the difference-in-differences (DID) model utilize observational data to improve evaluation accuracy and efficiency. This study leverages the synthetic difference-in-differences (SDID) approach, which integrates the strengths of both DID and the synthetic control method (SCM), to provide a more reliable and accurate analysis of the impacts of interventions on city-level air quality. Using Shanghai’s 2022 lockdown as a case study, we compare the deweathered ozone (O₃) concentration in Shanghai to a counterfactual constructed from a weighted average of cities in the Yangtze River Delta (YRD) that did not undergo lockdown. The quasi-natural experiment reveals an average increase of 4.4 μg/m³ (95% CI: 0.24–8.56) in Shanghai’s maximum daily 8 h O₃ concentration attributable to the lockdown. The SDID method reduces reliance on the parallel trends assumption and improves the estimate stability through unit- and time-specific weights. Multiple robustness checks confirm the reliability of these findings, underscoring the efficacy of the SDID approach in quantitatively evaluating the causal impact of emission perturbations on air quality. This study provides credible causal evidence of the environmental impact of short-term policy interventions, highlighting the utility of SDID in informing adaptive air quality management. The findings support the development of timely, evidence-based strategies for sustainable urban governance and environmental policy design. Full article

Flocculants are indispensable in water and wastewater treatment, enabling the aggregation and removal of suspended particles, colloids, and emulsions. However, the conventional development and application of flocculants rely heavily on empirical methods, which are time-consuming, resource-intensive, and environmentally problematic due to issues such as sludge production and chemical residues. Recent advances in machine learning (ML) have opened transformative avenues for the design, optimization, and intelligent application of flocculants. This review systematically examines the integration of ML into flocculant research, covering algorithmic approaches, data-driven structure–property modeling, high-throughput formulation screening, and smart process control. ML models—including random forests, neural networks, and Gaussian processes—have successfully predicted flocculation performance, guided synthesis optimization, and enabled real-time dosing control. Applications extend to both synthetic and bioflocculants, with ML facilitating strain engineering, fermentation yield prediction, and polymer degradability assessments. Furthermore, the convergence of ML with IoT, digital twins, and life cycle assessment tools has accelerated the transition toward sustainable, adaptive, and low-impact treatment technologies. Despite its potential, challenges remain in data standardization, model interpretability, and real-world implementation. This review concludes by outlining strategic pathways for future research, including the development of open datasets, hybrid physics–ML frameworks, and interdisciplinary collaborations. By leveraging ML, the next generation of flocculant systems can be more effective, environmentally benign, and intelligently controlled, contributing to global water sustainability goals. Full article

Catalysis research is complex and interdisciplinary, involving diverse physical effects and challenging data practices. Research data often captures only selected aspects, such as specific reactants and products, limiting its utility for machine learning and the implementation of FAIR (Findable, Accessible, Interoperable, Reusable) workflows. To improve this, semantic structuring through ontologies is essential. This work extends the established ontologies by refining logical relations and integrating semantic tools such as the Web Ontology Language or the Shape Constraint Language. It incorporates application programming interfaces from chemical databases, such as the Kyoto Encyclopedia of Genes and Genomes and the National Institute of Health’s PubChem database, and builds upon established ontologies. A key innovation lies in automatically decomposing chemical substances through database entries and chemical identifier representations to identify functional groups, enabling more generalized reaction classification. Using new semantic functionality, functional groups are flexibly addressed, improving the classification of reactions such as saponification and ester cleavage with simultaneous oxidation. A graphical interface (GUI) supports user interaction with the knowledge graph, enabling ontological reasoning and querying. This approach demonstrates improved specificity of the newly established ontology over its predecessors and offers a more user-friendly interface for engaging with structured chemical knowledge. Future work will focus on expanding ontology coverage to support a wider range of reactions in catalysis research. Full article

In this study, a highly cadmium (II)-resistant bacterium strain, C10-4, identified as Bacillus altitudinis, was isolated from a sediment sample collected from Baiyangdian Lake, China. The minimum inhibitory concentration (MIC) of Cd(II) for strain C10-4 was 1600 mg/L. Factors such as the contact time, pH, Cd(II) concentration, and biomass dosage affected the adsorption of Cd(II) by strain C10-4. The adsorption process fit well to the Langmuir adsorption isotherm model and the pseudo-second-order kinetics model, based on the Cd(II) adsorption data obtained from the cells of strain C10-4. This suggests that Cd(II) is adsorbed by strain C10-4 cells via a single-layer homogeneous chemical adsorption process. According to the Langmuir model, the maximum biosorption capacity was 3.31 mg/g for fresh-strain C10-4 biomass. Cd(II) was shown to adhere to the bacterial cell wall through SEM-EDS analysis. FTIR spectroscopy further indicated that the main functional sites for the binding of Cd(II) ions on the cell surface of strain C10-4 were functional groups such as N-H, -OH, -CH-, C=O, C-O, P=O, sulfate, and phosphate. After the inoculation of strain C10-4 into Cd(II)-contaminated soils, there was a significant reduction (p < 0.01) in the exchangeable fraction of Cd and an increase (p < 0.01) in the sum of the reducible, oxidizable, and residual fractions of Cd. The results show that Bacillus altitudinis C10-4 has good potential for use in the remediation of Cd(II)-contaminated soils. Full article

Postharvest losses amongst small-scale farmers in developing countries are high due to inadequate resources and infrastructure. Among the various affected crops, tomatoes are particularly vulnerable; however, studies on postharvest losses of most fruits and vegetables are limited. Therefore, this study aimed to assess postharvest tomato losses under different production systems within the small-scale supply chain using the indirect assessment (questionnaires and interviews) and direct quantification of losses. Farmers reported tomato losses due to insects (82.35%), cracks, bruises, and deformities (70.58%), and diseases (64.71%). Chemical sprays were the main form of pest and disease control reported by all farmers. The direct quantification sampling data revealed that 73.07% of the tomatoes were substandard at the farm level, with 47.92% and 25.15% categorized as medium-quality and poor-quality, respectively. The primary contributors to the losses were decay (39.92%), mechanical damage (31.32%), and blotchiness (27.99%). Postharvest losses were significantly higher under open-field production systems compared to closed tunnels. The fungi associated with decay were mainly Geotrichum, Fusarium spp., and Alternaria spp. These findings demonstrate the main drivers behind postharvest losses, which in turn highlight the critical need for intervention through training and support, including the use of postharvest loss reduction technologies to enhance food security. Full article

The accurate dosing of polyaluminum chloride (PAC) is essential for achieving effective coagulation in drinking water treatment, yet conventional methods such as jar tests are limited in their responsiveness and operational efficiency. This study proposes a hybrid modeling framework that integrates artificial neural networks (ANN) with genetic algorithms (GA) to optimize PAC dosage under variable raw water conditions. Operational data from 400 jar test experiments, collected between 2022 and 2024 at the Yanahurco water treatment plant (Ecuador), were used to train an ANN model capable of predicting six post-treatment water quality indicators, including turbidity, color, and pH. The ANN achieved excellent predictive accuracy (R² > 0.95 for turbidity and color), supporting its use as a surrogate model within a GA-based optimization scheme. The genetic algorithm evaluated dosage strategies by minimizing treatment costs while enforcing compliance with national water quality standards. The results revealed a bimodal dosing pattern, favoring low PAC dosages (~4 ppm) during routine conditions and higher dosages (~12 ppm) when influent quality declined. Optimization yielded a 49% reduction in median chemical costs and improved color compliance from 52% to 63%, while maintaining pH compliance above 97%. Turbidity remained a challenge under some conditions, indicating the potential benefit of complementary coagulants. The proposed ANN–GA approach offers a scalable and adaptive solution for enhancing chemical dosing efficiency in water treatment operations. Full article

The utilisation of edible insects for human nutrition is a long-standing practice in many parts of the globe, and is being gradually introduced into countries without an entomophagic tradition as well. These unconventional sources of protein of animal origin have arisen as a sustainable alternative to other animal protein sources, such as meat. This review intends to present the compilation of data in the scientific literature on the chemical composition and nutritional value of the bee brood of A. mellifera species and subspecies as edible foods. For this, a comprehensive search of the scientific literature was carried out using the databases ScienceDirect, Scopus, Pub-Med, BOn, and SciELO. Appropriate keywords were used for the search to reach the research works that addressed the topics of the review. The results showed that bee brood has considerable quantities of protein, fat and carbohydrates. The most abundant amino acids are leucine and lysine (these two being essential amino acids) and aspartic acid, glutamic acid, and proline (these three being non-essential amino acids). As for the fatty acids, bee broods contain approximately equal fractions of saturated and monounsaturated fatty acids, while the polyunsaturated fatty acids are negligible. The dietary minerals present in higher quantities are potassium, phosphorus, and magnesium, and the most abundant vitamins are vitamin C and niacin; choline is also present, although it is not a true vitamin. Although bee brood from A. mellifera has potential for human consumption as a nutrient-rich food, there are still many aspects that need to be further studied in the future, such as safety and hazards linked to possible regular consumption. Full article

Per- and polyfluoroalkyl substances (PFASs) have gained significant attention due to their widespread distribution in the environment and potential adverse health effects. While ingestion, especially through contaminated drinking water, is considered the primary route of human exposure, recent research suggests that other pathways, such as inhalation and dermal absorption, also play a significant role. This review provides a concise overview of the toxicological impacts of both legacy and emerging PFASs, such as GenX and perfluorobutane sulfonic acid (PFBS), with a particular focus on their effects on the liver, kidneys, and immune and nervous systems, based on findings from recent in vivo, in vitro, and epidemiological studies. Despite the transition to PFAS alternatives, much of the existing toxicity data focus on a few legacy compounds, such as perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), which have been linked to adverse immune outcomes, particularly in children. However, evidence for carcinogenic risk remains limited to populations with extremely high exposure levels, and data on neurodevelopmental effects remain underexplored. While epidemiological and experimental animal studies supported these findings, significant knowledge gaps persist, especially regarding emerging PFASs. Therefore, this review examines the visceral, neural, and immunotoxicity data for emerging PFASs and mixtures from recent studies. Given the known risks from well-studied PFASs, a precautionary principle should be adopted to mitigate human health risks posed by this large and diverse group of chemicals. Full article

Molecular sensor systems, e.g., implantables and wearables, provide extensive health-related monitoring. Glucose sensor systems have historically prevailed in wearable bioanalysis applications due to their continuous and reliable glucose monitoring, a feat not yet accomplished for other biomarkers. However, the advancement of reagentless detection methodologies may facilitate the creation of molecular sensor systems for multiple analytes. Improving the sensitivity and selectivity of molecular sensor systems is also crucial for biomarker detection under intricate physiological circumstances. The term multidomain molecular sensor systems is utilized to refer, in general, to both biological and chemical sensor systems. This review examines methodologies for enhancing signal amplification, improving selectivity, and facilitating reagentless detection in multidomain molecular sensor devices. The review also analyzes the fundamental components of multidomain molecular sensor systems, including substrate materials, bodily fluids, power, and decision-making units. The review article further investigates how extensive data gathered from multidomain molecular sensor systems, in conjunction with current data processing algorithms, facilitate biomarker detection for precision medicine. Full article