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PubMed2025

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5​ concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution↗
PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗
PubMed2026

Unconfined compressive strength prediction for the ordinary Portland cement-steel slag-silica fume ternary system based on response surface methodology.

This research was undertaken to address environmental concerns associated with industrial solid waste and to reduce cement consumption in geotechnical engineering. It specifically investigates the feasibility of using steel slag (SS) and silica fume (SF) as partial substitutes for ordinary Portland cement (OPC) in soil stabilization. The effects of SS, SF, OPC, and initial moisture content on the unconfined compressive strength (UCS) of stabilized soil were investigated through single-factor experiments and response surface methodology (RSM). The results show that SS and SF can synergistically enhance the strength of stabilized soil, although their interaction effect was not statistically significant within the investigated ranges. Compared with soil stabilized solely with OPC, the addition of 18 % SS and 10 % SF reduced OPC consumption by 3 % without compromising strength. Microstructural and compositional analyses further revealed that SS mainly supplied calcium- and silica-bearing components, while SF provided highly reactive silica and micro-filling effects, jointly promoting hydration reactions and improving the compactness of the stabilized soil matrix. As a result, more hydration products were formed in the OPC/SS/SF-stabilized soil than in the OPC-stabilized soil, which contributed to pore filling and strength enhancement. This study provides useful guidance for the sustainable utilization of industrial solid waste and the low-carbon development of soil stabilization materials.

Construction Materials↗
PubMed2026

Does high fructose consumption trigger microglia activation and neuroinflammation? A systematic review.

This systematic review evaluated the effects of fructose intake on neuroinflammatory markers in rodent models. The search terms Fructose AND neuroinflammation OR Neurodegeneration OR chemokines OR interleukins OR microglia OR behaviour OR memory OR cognition were used in Google Scholar, Scopus and Web of Science. Thirteen animal studies investigating fructose-induced neuroinflammation that matched the eligibility criteria were included in the study. Across the studies, 16 inflammatory markers were identified and significantly altered following exposure to fructose. The findings consistently demonstrated elevated expression of pro-inflammatory cytokines, TNF-α, IL-6, and IL-1β, following fructose administration. Fructose consumption also dysregulated MCP-1, fractalkine, and CX3CR1 levels, thereby promoting inflammatory signalling and microglial activation. Furthermore, fructose exposure significantly increased IBA-1 and CD11b, indicating sustained neuroimmune activation. Alterations in important inflammatory pathways involving TLR4, NLRP3, NF-κB, MyD88, iNOS, and cyclooxygenases (COX-1 and COX-2) were also observed. In contrast, expression of the anti-inflammatory regulator peroxisome proliferator-activated receptor gamma (PPARγ) was reduced after fructose treatment. Overall, the findings suggest that chronic fructose consumption induces neuroinflammation through multiple inflammatory and immune-related mechanisms in the brain. These effects appear to be dose- and duration-dependent and may contribute significantly to neurodegeneration and cognitive impairment.

Microglia↗
PubMed2026

Comprehensive source-risk assessment of organophosphate esters in surface water of the Dianchi Lake Basin, Yunnan, China.

Organophosphate esters (OPEs), widely used as flame retardants and plasticizers, have been increasingly detected in aquatic environments. However, investigations of their distribution in high-altitude plateau lakes remain scarce. Identifying and quantifying the sources and associated risks of OPEs are crucial for subsequent water environment management. In this study, an integrated source-risk analysis approach was employed by combining the Positive Matrix Factorization (PMF) model, the Geodetector (GD) model, and risk quotient (RQ). Analysis of 14 OPEs in surface waters of the Dianchi Lake Basin (DLB) revealed 12 detectable compounds, with total OPEs concentrations (ΣOPEs) ranging from not detected (ND)-64.6 ng/L during the wet season and ND-35.8 ng/L during the dry season. Elevated ΣOPEs were primarily observed at inflow sites in the northern part of the lake and in urban rivers. Source apportionment indicated four major contributing sources: agricultural films containing flame-retardant and plasticizer additives, traffic-related particulate emissions, releases from household and personal care products, and industrial production and applications of flame retardants in plastics, electronics, and related products (the predominant source). The ecological impact caused by OPEs ranges from no risk to low risk, with tris(2-chloroethyl) phosphate emitted from industrial source being the primary driver of potential environmental risk. These findings highlight the necessity of prioritizing industrial sources in future management strategies. Overall, this study provides a methodological framework for source apportionment and risk assessment of OPEs and offers scientific evidence to support environmental management of OPEs in the DLB.

Environmental Monitoring↗
PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗
PubMed2026

Meta-analysis of source identification and apportionment in soil: A systematic review of analytical procedures, receptor modeling, and environmental applications.

Soil pollution poses significant risks to ecosystems and human health, necessitating accurate source identification and apportionment to guide mitigation strategies. This systematic review evaluates the application of Positive Matrix Factorization (PMF) and other receptor models in soil pollution studies, focusing on analytical procedures, tracer indicators, and environmental applications. This review aims to provide a comprehensive framework for conducting soil source apportionment studies, aiding policymakers in designing effective, region-specific environmental management strategies by compiling global trends and methodological insights. The study addresses sampling protocols, emphasizing representativeness and quality control. Data from 500 peer-reviewed publications highlight the dominance of research in China, Eastern Europe, and South Asia, with agricultural soils being the most frequently studied. Key findings reveal that traffic emissions (20.8 %) and industrial activities (19.4 %) are the primary global contributors to soil contamination, with regional variations such as coal combustion in cold climates and agricultural inputs in developing regions. Policy recommendations include stricter industrial regulations, sustainable agricultural practices, and targeted remediation efforts based on source-specific risks.

Soil Pollutants↗
PubMed2026

Strategy for enhanced production of A40926B0 in Nonomuraea gerenzanensis using an efficient CRISPR/AsCas12f1 system.

The global emergence of vancomycin-resistant Gram-positive pathogens underscores the urgent need for efficient production of novel lipoglycopeptide antibiotics. Dalbavancin, a last-resort therapeutic agent, relies on its key biosynthetic precursor A40926B0, whose industrial manufacture is severely limited by the low yield of wild-type Nonomuraea gerenzanensis and inefficient genetic tools for this rare actinomycete. Here, we developed a high-efficiency CRISPR/AsCas12f1 genome editing system and applied systematic metabolic engineering to boost A40926B0 biosynthesis. First, conjugation conditions were optimized to elevate the transfer efficiency in N. gerenzanensis D11. The hypercompact AsCas12f1 nuclease showed markedly lower cytotoxicity than SpCas9 and enabled 100% gene deletion efficiency with preferred PAMs (TTTG, CTTG, GTTG). Second, we strengthened the shikimate pathway via multiple genetic strategies: overexpressing feedback-resistant DAHP synthase (aroG fbr ) and chorismate mutase/prephenate dehydrogenase (tyrA fbr ), as well as knocking out pheA. This manipulation blocks the phenylalanine synthetic branch and redirects metabolic flux toward the l-tyrosine branch. Third, we engineered the branched-chain fatty acid (BCFA) pathway via promoter replacement of bkdA2B2C2, LipAB, fabF and deletion of acdH to enhance isododecanoyl side-chain supply. The combinatorial engineering yielded strain B-13, which produced 1740 mg/L A40926B0 in shake flasks. Finally, 50-L fed-batch fermentation with continuous maltodextrin feeding further increased the titer to 1817 mg/L, the highest reported titer to date. This work establishes a robust CRISPR editing tool for N. gerenzanensis and provides valuable engineering references for precursor-oriented strain improvement targeting lipoglycopeptide antibiotics, offering insights for the industrial scale production of A40926B0.

A40926B0↗
PubMed2026

Comprehensive quality profiling and comparative metabolic characterization of seven dominant fresh-eating Chinese olive (Canarium album Lour.) cultivars in Southern China.

Fresh-eating Chinese olive (Canarium album Lour.) is a subtropical fruit endemic to southern China with considerable commercial value, yet systematic quality characterization of dominant cultivars remains scarce. This study established a multi-dimensional quality dataset for seven dominant cultivars from Fujian and Guangdong provinces, integrating nutritional components, soluble sugars, organic acids, mineral elements, volatile profiles, and non-targeted metabolomics. Significant cultivar-specific differences were observed across all evaluated dimensions: "Lingfeng" exhibited a sugar-dominant low-acid profile, whereas "Sanleng" showed elevated phenolic constituents accumulation. Volatile profiling identified terpenoid-based candidate discriminatory biomarkers, and metabolomic analysis revealed phenylpropanoid biosynthesis, tryptophan metabolism, and starch and sucrose metabolism as the most variable pathways. Correlations between untargeted profiling and targeted absolute quantification validated untargeted result reliability and revealed their complementarity in nutritional evaluation. These findings provide baseline data for FECO germplasm evaluation and targeted industrial utilization.

China↗
PubMed2026

Transcriptomic insights into the molecular mechanism of antifouling agent-induced settlement inhibition in the Pacific oyster Crassostrea gigas.

Marine biofouling remains a persistent challenge to maritime industries and marine ecosystems worldwide. In this study, we systematically evaluated the acute toxicity, settlement inhibitory efficacy, and underlying molecular mechanisms of an N-oleyl-1,3-propanediamine-based antifouling agent using pediveliger larvae of the Pacific oyster Crassostrea gigas. The 96 h-LC50 of the agent was determined to be 0.81 mg/L, and exposure to 1.68 mg/L achieved complete larval settlement inhibition without inducing significant acute toxicity. Transcriptomic analysis identified 791 differentially expressed genes, dominated by downregulated genes associated with ribosomal function, translation, cell adhesion, and cytoskeletal organization. The agent exerts its inhibitory effect primarily through the global suppression of protein synthesis, disruption of cell-substrate adhesion and cytoskeletal integrity, and induction of proteotoxic stress responses. These findings reveal a multi-pathway molecular mechanism underlying antifouling agent-induced settlement inhibition in oyster larvae and provide key molecular biomarkers to support the development of eco-friendly antifouling technologies.

Animals↗
PubMed2026

Food-derived extracellular vesicles as delivery platforms for medicine-food homology components in metabolic syndrome.

Diet-induced obesity and associated metabolic syndromes have become major global public health challenge, highlighting the urgent need for safe and effective strategies. Recently, food-derived extracellular vesicles (FDEVs) have garnered increasing attention as natural nanocarriers due to their excellent biocompatibility and specific targeted delivery capabilities. FDEVs can efficiently deliver medicine-food homology components (MFHCs) to precisely regulate lipid metabolism, inflammatory responses, and insulin sensitivity, thereby improving obesity and its metabolic abnormalities. This systematic review summarizes recent advances in the use of FDEVs as delivery vehicles for MFHCs to suppress diet-induced obesity and metabolic syndrome, with a particular focus on the underlying molecular mechanisms, including signaling pathway regulation and cellular metabolic remodeling. In addition, the clinical translational potential and industrial application prospects of FDEVs are evaluated, and key challenges related to preparation techniques, safety assessment, and large-scale production are discussed. By integrating current evidence, this review aims to provide theoretical framework and future perspectives for the development of FDEVs as a novel targeted delivery platform and treatment of metabolic diseases.

Extracellular Vesicles↗
PubMed2026

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide↗
PubMed2026

Watershed-scale risk assessment of cadmium contamination in Chinese cropland soils: Dual pathways of irrigation input and flood-driven transport.

Irrigation and flood events serve as critical pathways for the transport of cadmium (Cd) from industrial sources into cropland soils at the watershed scale, constituting a major driver of widespread Cd contamination in China's cropland soil. This study evaluated the risk of Cd contamination in cropland soils across China's nine major river basins at the watershed scale, focusing on the contributions of irrigation and flood events, and conducted a sensitivity analysis of key risk factors. The assessment was conducted within a framework that considered factors including hazard, exposure, and vulnerability. The results revealed that numerous watersheds in southeastern China are exposed to dual pressures of Cd contamination risks in cropland soils, driven by both irrigation practices and flood events. Watersheds categorized as High-High, High-Moderate, or Moderate-High risk, reflecting combined Cd contamination risks from irrigation and flood, are vital to China's grain production, contributing 67.1 % of the national cropland area and 66.4 % of the grain yield. The study suggests localized strategies for managing cropland soils Cd contamination risks from irrigation and flood at the watershed scale in China, alongside strengthened cross-regional collaboration in southeastern China.

Cadmium↗
PubMed2026

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30 weeks) and late laying (50 weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Animals↗
PubMed2026

Mechanistic insights into flavor deterioration in bitter sturgeon caviar: Evidence from lipidomics and metagenomics.

This study systematically compared the flavor and multi-omics differences between normal caviar and bitter caviar based on quantitative descriptive analysis (QDA), volatile compounds (VOCs) analysis, untargeted lipidomics, and metagenomics. The results showed that bitter caviar was characterized not only by increased bitterness, but also by decreased positive sensory attributes, including buttery, nutty, and marine fresh. VOCs analysis indicated that the volatile profile of bitter caviar was reorganized. Compounds such as 3-hydroxy-2-butanone, 1-octen-3-ol, and (E, Z)-2,6-nonadienal showed higher relative odor activity values (rOAVs); however, these changes did not improve its overall sensory experience. Untargeted lipidomics identified 492 differential lipids. These changes were mainly characterized by decreased PC and increased DG and LPC in bitter caviar. KEGG pathways analysis showed that these differential lipids were mainly associated with glycerophospholipid metabolism, choline metabolism in cancer, and retrograde endocannabinoid signaling. Metagenomic analysis showed that bacteria dominated the microbial community of caviar. Among them, Bacillus and Micromonospora showed relatively high abundance in the caviar microbiota. They were also closely associated with lipid metabolic changes involving PC, DG, and LPC, suggesting their potential as candidate targets for future microbiota-directed regulation of caviar quality. These findings provide new insights into the mechanisms underlying sensory deterioration and flavor formation in bitter caviar, and offer a theoretical basis for improving caviar quality in industrial production.

Animals↗
PubMed2026

Elucidating the evolution of meat quality, water distribution, microstructure, and protein structure during sous-vide and micro-pressure cooking.

This study investigated the evolution of eating quality (colour, texture and volatile flavour compounds), water status, microstructure and protein structure of pork meat under different cooking methods. The methods analysed included traditional cooking (TC: 10, 20, 30 and 40 min, 100 °C), sous-vide cooking (SV: 1, 2, 3 and 4 h, 60 °C) and micro-pressure cooking (MC: 10, 20, 30 and 40 min, 120 °C). Across the three cooking processes, as cooking time increased, cooking loss, lightness, yellowness, P23, β-sheet, random coil and surface hydrophobicity of the meat samples increased. By contrast, redness, P22, hydrogen proton density, esters content, α-helix, β-turn and sulfhydryl group content decreased. Moreover, the Warner-Bratzler shear force (WBSF), adhesiveness, hardness, springiness, gumminess, chewiness, alcohols, aldehydes, ketones and fluorescence intensity of the meat samples, initially increased and then decreased as cooking progressed. SV resulted in higher water-holding capacity (WHC), improved redness and increased alcohol and ester levels, whereas MC produced softer meat and greater water mobility. Furthermore, MC enhanced the degree of microstructural damage and protein structural unfolding in the meat. MC requires less time to achieve textures and flavours similar to those obtained using the TC and SV methods. Thus, MC is an efficient cooking method for the catering industry to obtain desired meat quality rapidly.

Cooking↗
PubMed2026

Microbial diversity, functional activities, and safety risks in fermented tea: a comprehensive review.

Microbial fermented teas are gaining global popularity due to their unique sensory profiles and health benefits. The quality and safety of these products are governed by complex microbial ecosystems that orchestrate the biotransformation of tea leaf components. This review addresses a critical paradox in the field: the same microbial activities that generate desirable bioactive metabolites, such as theabrownins and organic acids, also create ecological niches for mycotoxigenic fungi, posing significant health risks from contaminants like ochratoxin A, citrinin, and aflatoxins. While extensive research has cataloged the microbial diversity in these systems, a comprehensive framework linking processing environments to microbial community assembly, functional outcomes, and quantifiable safety risks remains elusive. This review systematically bridges this gap by synthesizing current knowledge on the microbial consortia-dominated by Aspergillus, Penicillium, Bacillus, and Lactiplantibacillus species-that drive tea fermentation. We critically analyze their functional roles in enhancing flavor, bioactivity, and potential probiotic activity while simultaneously evaluating the mechanisms of mycotoxin production and accumulation. By integrating microbial ecology, biochemistry, and food safety, we propose a forward-looking perspective focused on transitioning the industry from traditional, spontaneous fermentation to modern, controlled biotechnological processes. This approach, centered on the use of defined starter cultures, predictive modeling, and active biocontrol strategies, provides a roadmap for ensuring the consistent quality and safety of fermented tea products, ultimately unlocking their full potential as high-quality functional foods.

Tea↗
PubMed2026

Mitophagy-mediated ferroptosis involved in 2,5-hexanedione-induced neurotoxicity in rats.

n-Hexane, a widespread environmental and industrial pollutant, poses serious health risks, particularly neurotoxicity. Chronic exposure primarily induces sensorimotor neuropathy via its metabolite 2,5-hexanedione (HD), yet the mechanisms underlying HD-induced neuronal injury remain unclear. Recent evidence implicates ferroptosis, an iron-dependent form of regulated cell death, in neurodegenerative processes. In this study, Sprague-Dawley (SD) rats were exposed to HD to establish a neuropathy model. Ferroptosis involvement was assessed using the iron chelator deferoxamine (DFO) and the ferroptosis inhibitor Ferrostatin-1. The potential role of mitophagy in HD-induced ferroptosis was evaluated by monitoring mitophagy markers and by autophagy inhibition with chloroquine (CQ). In vitro, SH-SY5Y cells were transfected with PINK-1 siRNA to explore mitophagy-mediated regulation of ferroptosis. HD exposure led to iron accumulation, lipid peroxidation, mitochondrial abnormalities, and decreased GPX4 in rat spinal neurons. DFO or ferrostatin-1 treatment ameliorated these changes and preserved mitochondrial integrity. Mechanistic analyses revealed HD-induced activation of mitophagy, as shown by upregulation of Beclin-1, LC3II, Drp-1, and PINK-1, with concomitant downregulation of P62 in spinal mitochondria. CQ suppressed mitophagy, reduced iron deposition and lipid peroxidation, and improved motor function. Similarly, PINK-1 knockdown in SH-SY5Y cells mitigated HD-induced mitophagy and ferroptosis. These findings demonstrate that HD induces neuronal ferroptosis via mitophagy activation. Inhibition of ferroptosis or mitophagy effectively attenuates HD-induced neurotoxicity, suggesting potential therapeutic strategies to reduce neural damage from environmental n-hexane exposure.

Animals↗