Role of ZNF334 in cervical cancer: implications for EMT reversal and tumor suppression.

Zinc-finger proteins are involved in many biological processes. However, the role of Zinc-finger protein 334 (ZNF334) in cervical cancer remains unidentified. This study showed that promoter methylation of ZNF334 was responsible for its reduced expression. ZNF334 suppressed malignant biological behaviors in cervical cancer. Notably, ZNF334 reversed the EMT process both in vitro and in vivo. RNA-seq coupled with bioinformatics analysis caught P3H3 which is upregulated by ZNF334. Dual-luciferase reporter and Chromatin immunoprecipitation assays illustrated that ZNF334 directly regulate P3H3. Knockdown of P3H3 attenuated the reversal of EMT induced by ZNF334. Additionally, ZNF334 overexpression sensitized cervical cancer cells to the cytotoxic effects of paclitaxel, cyclosporine and sunitinib. In conclusions, this study illustrated that DNA methylation-based silencing ZNF334 played a vital role in cervical cancer, by regulating P3H3 in turn affects EMT. ZNF334 has the potential to become a novel diagnostic biomarker and a potential treatment target for cervical cancer.

Deciphering m6A methylation in monocyte-mediated cardiac fibrosis and monocyte-hitchhiked erythrocyte microvesicle biohybrid therapy.

Rationale: Device implantation frequently triggers cardiac remodeling and fibrosis, with monocyte-driven inflammatory responses precipitating arrhythmias. This study investigates the role of m6A modification enzymes METTL3 and METTL14 in these responses and explores a novel therapeutic strategy targeting these modifications to mitigate cardiac remodeling and fibrosis. Methods: Peripheral blood mononuclear cells (PBMCs) were collected from patients with ventricular septal defects (VSD) who developed conduction blocks post-occluder implantation. The expression of METTL3 and METTL14 in PBMCs was measured. METTL3 and METTL14 deficiencies were induced to evaluate their effect on angiotensin II (Ang II)-induced myocardial inflammation and fibrosis. m6A modifications were analyzed using methylated RNA immunoprecipitation followed by quantitative PCR. NF-κB pathway activity and levels of monocyte migration and fibrogenesis markers (CXCR2 and TGF-ß1) were assessed. An erythrocyte microvesicle-based nanomedicine delivery system was developed to target activated monocytes, utilizing the METTL3 inhibitor STM2457. Cardiac function was evaluated via echocardiography. Results: Significant upregulation of METTL3 and METTL14 was observed in PBMCs from patients with VSD occluder implantation-associated persistent conduction block. Deficiencies in METTL3 and METTL14 significantly reduced Ang II-induced myocardial inflammation and fibrosis by decreasing m6A modification on MyD88 and TGF-ß1 mRNAs. This disruption reduced NF-κB pathway activation, lowered CXCR2 and TGF-ß1 levels, attenuated monocyte migration and fibrogenesis, and alleviated cardiac remodeling. The erythrocyte microvesicle-based nanomedicine delivery system effectively targeted inflamed cardiac tissue, reducing inflammation and fibrosis and improving cardiac function. Conclusion: Inhibiting METTL3 and METTL14 in monocytes disrupts the NF-κB feedback loop, decreases monocyte migration and fibrogenesis, and improves cardiac function. Targeting m6A modifications of monocytes with STM2457, delivered via erythrocyte microvesicles, reduces inflammation and fibrosis, offering a promising therapeutic strategy for cardiac remodeling associated with device implantation.

Development and validation of a predictive model for vertebral fracture risk in osteoporosis patients.

OBJECTIVE: This study aimed to develop and validate a predictive model for osteoporotic vertebral fractures (OVFs) risk by integrating demographic, bone mineral density (BMD), CT imaging, and deep learning radiomics features from CT images. METHODS: A total of 169 osteoporosis-diagnosed patients from three hospitals were randomly split into OVFs (n = 77) and Non-OVFs (n = 92) groups for training (n = 135) and test (n = 34). Demographic data, BMD, and CT imaging details were collected. Deep transfer learning (DTL) using ResNet-50 and radiomics features were fused, with the best model chosen via logistic regression. Cox proportional hazards models identified clinical factors. Three models were constructed: clinical, radiomics-DTL, and fusion (clinical-radiomics-DTL). Performance was assessed using AUC, C-index, Kaplan-Meier, and calibration curves. The best model was depicted as a nomogram, and clinical utility was evaluated using decision curve analysis (DCA). RESULTS: BMD, CT values of paravertebral muscles (PVM), and paravertebral muscles' cross-sectional area (CSA) significantly differed between OVFs and Non-OVFs groups (P < 0.05). No significant differences were found between training and test cohort. Multivariate Cox models identified BMD, CT values of PVM, and CSAPS reduction as independent OVFs risk factors (P < 0.05). The fusion model exhibited the highest predictive performance (C-index: 0.839 in training, 0.795 in test). DCA confirmed the nomogram's utility in OVFs risk prediction. CONCLUSION: This study presents a robust predictive model for OVFs risk, integrating BMD, CT data, and radiomics-DTL features, offering high sensitivity and specificity. The model's visualizations can inform OVFs prevention and treatment strategies.

HIF-1 Transcriptionally Regulates Basal Expression of STING to Maintain Cellular Innate Immunity.

Stimulator of IFN genes (STING) is a critical component of the innate immune system, playing an essential role in defending against DNA virus infections. However, the mechanisms governing basal STING regulation remain poorly understood. In this study, we demonstrate that the basal level of STING is critically maintained by hypoxia-inducible factor 1 (HIF-1)α through transcription. Under normal conditions, HIF-1α binds constitutively to the promoter region of STING, actively promoting its transcription. Knocking down HIF-1α results in a decrease in STING expression in multiple cell lines and zebrafish, which in turn reduces cellular responses to synthetic dsDNAs, including cell signaling and IFN production. Moreover, this decrease in STING levels leads to an increase in cellular susceptibility to DNA viruses HSV-1 and pseudorabies virus. These findings unveil a (to our knowledge) novel role of HIF-1α in maintaining basal STING levels and provide valuable insights into STING-mediated antiviral activities and associated diseases.

Highly Sensitive Force Sensor Based on High-Q Asymmetric V-Shaped CaF2 Resonator.

Whispering gallery mode (WGM) resonators have high-quality factors and can be used in high-sensitivity sensors due to the narrow line width that allows for the detection of small external changes. In this paper, a force-sensing system based on a high-Q asymmetric V-shaped CaF2 resonator is proposed. Based on the dispersion coupling mechanism, the deformation of the resonator is achieved by loading force, and the resonant frequency is changed to determine the measurement. By adjusting the structural parameters of the asymmetric V-shaped resonator, the deformation of the resonator under force loading is improved. The experimental results show that the sensitivity of the V-shaped tip is 18.84 V/N, which determines the force-sensing resolution of 8.49 µN. This work provides a solution for force-sensing measurements based on a WGM resonator.

7D High-Dynamic Spin-Multiplexing.

Multiplexing technology creates several orthogonal data channels and dimensions for high-density information encoding and is irreplaceable in large-capacity information storage, and communication, etc. The multiplexing dimensions are constructed by light attributes and spatial dimensions. However, limited by the degree of freedom of interaction between light and material structure parameters, the multiplexing dimension exploitation method is still confused. Herein, a 7D Spin-multiplexing technique is proposed. Spin structures with four independent attributes (color center type, spin axis, spatial distribution, and dipole direction) are constructed as coding basic units. Based on the four independent spin physical effects, the corresponding photoluminescence wavelength, magnetic field, microwave, and polarization are created into four orthogonal multiplexing dimensions. Combined with the 3D of space, a 7D multiplexing method is established, which possesses the highest dimension number compared with 6 dimensions in the previous study. The basic spin unit is prepared by a self-developed laser-induced manufacturing process. The free state information of spin is read out by four physical quantities. Based on the multiple dimensions, the information is highly dynamically multiplexed to enhance information storage efficiency. Moreover, the high-dynamic in situ image encryption/marking is demonstrated. It implies a new paradigm for ultra-high-capacity storage and real-time encryption.

Metabolic reprogramming in tumor immune microenvironment: Impact on immune cell function and therapeutic implications.

Understanding of the metabolic reprogramming has revolutionized our insights into tumor progression and potential treatment. This review concentrates on the aberrant metabolic pathways in cancer cells within the tumor microenvironment (TME). Cancer cells differ from normal cells in their metabolic processing of glucose, amino acids, and lipids in order to adapt to heightened biosynthetic and energy needs. These metabolic shifts, which crucially alter lactic acid, amino acid and lipid metabolism, affect not only tumor cell proliferation but also TME dynamics. This review also explores the reprogramming of various immune cells in the TME. From a therapeutic standpoint, targeting these metabolic alterations represents a novel cancer treatment strategy. This review also discusses approaches targeting the regulation of metabolism of different nutrients in tumor cells and influencing the tumor microenvironment to enhance the immune response. In summary, this review summarizes metabolic reprogramming in cancer and its potential as a target for innovative therapeutic strategies, offering fresh perspectives on cancer treatment.

The health benefits of dietary polyphenols on pediatric intestinal diseases: Mechanism of action, clinical evidence and future research progress.

Pediatric intestinal development is immature, vulnerable to external influences and produce a variety of intestinal diseases. At present, breakthroughs have been made in the treatment of pediatric intestinal diseases, but there are still many challenges, such as toxic side effects, drug resistance, and the lack of more effective treatments and specific drugs. In recent years, dietary polyphenols derived from plants have become a research hotspot in the treatment of pediatric intestinal diseases due to their outstanding pharmacological activities such, as anti-inflammatory, antibacterial, antioxidant and regulation of intestinal flora. This article reviewed the mechanism of action and clinical evidence of dietary polyphenols in the treatment of pediatric intestinal diseases, and discussed the influence of physiological characteristics of children on the efficacy of polyphenols, and finally prospected the new dosage forms of polyphenols in pediatrics.

Immunological characteristics of CD103+CD161+ T lymphocytes on chronic rhinosinusitis with nasal polyps.

Chronic rhinosinusitis with nasal polyps (CRSwNPs) is a heterogeneous disease characterized by local inflammation of the upper airway and sinus mucosa. T cell-mediated immune responses play irreplaceable roles in the pathogenesis of nasal polyps. CD161+ T cells have been implicated in the pathology of several diseases through cytokine production and cytotoxic activity. However, the immunological characteristics of CD161+ T cells in nasal mucosa are still not well understood, particularly in CRSwNPs. Our research revealed a notable enrichment of CD161+ T cells in nasal tissues compared to peripheral blood, with a significantly more infiltration of CD161+ T cells in CRSwNPs compared to control nasal samples. Phenotypical analysis found that CD161+ T cells predominantly co-expressed tissue-resident memory surface markers CD103, CD69, and CD45RO. CD161+CD103+ T cells demonstrated complicated effector functions, marked by elevated levels of PD-1, CTLA-4, IL-17, and IFN-γ and diminished expression of FoxP3 and CD25. Interestingly, despite CD161+ T cells was more abundant in polyp tissues compared to normal control tissues, and then further categorizing polyp samples into distinct groups based on clinical characteristics, only the recurrent CRSwNP group showed a significant reduction in CD161+CD8+ T cells compared to the primary CRSwNP group. This finding suggested the necessity for further research to comprehensively understand the underlying mechanisms and the broader significance of CD161+ T cells in the advancement and relapse of CRSwNPs.

Tunable mid-infrared photodetector based on graphene plasmons controlled by ferroelectric polarization for micro-spectrometer.

Surface plasmonic detectors have the potential to be key components of miniaturized chip-scale spectrometers. Graphene plasmons, which are highly confined and gate-tunable, are suitable forin situlight detection. However, the tuning of graphene plasmonic photodetectors typically relies on the complex and high operating voltage based on traditional dielectric gating technique, which hinders the goal of miniaturized and low-power consumption spectrometers. In this work, we report a tunable mid-infrared (MIR) photodetector by integrating of patterned graphene with non-volatile ferroelectric polarization. The polarized ferroelectric thin film provides an ultra-high surface electric field, allowing the Fermi energy of the graphene to be manipulated to the desired level, thereby exciting the surface plasmon polaritons effect, which is highly dependent on the free carrier density of the material. By exciting intrinsic graphene plasmons, the light transmittance of graphene is greatly enhanced, which improves the photoelectric conversion efficiency of the device. Additionally, the electric field on the surface of graphene enhanced by the graphene plasmons accelerates the carrier transfer efficiency. Therefore, the responsivity of the device is greatly improved. Our simulations show that the detectors have a tunable resonant spectral response of 9-14µm by reconstructing the ferroelectric domain and exhibit a high responsivity to 5.67 × 105A W-1at room temperature. Furthermore, we also demonstrate the conceptual design of photodetector could be used for MIR micro-spectrometer application.

Numerical Simulation Study on the Influence of Fracture on Borehole Wave Modes: Insights from Fracture Width, Filling Condition, and Acoustic Frequency.

Unconventional reservoirs, such as shale and tight formations, have become increasingly vital contributors to oil and gas production. In these reservoirs, fractures serve as crucial spaces for fluid migration and storage, making their precise assessment essential. Array acoustic logging stands out as a pivotal method for evaluating fractures. To investigate the impact of fracture width, fracture-filling conditions, and acoustic frequency on compressional and shear waves, a three-dimensional variable mesh finite difference program was employed for acoustic logging numerical simulation. Firstly, numerical models representing fractured formations with varying fracture widths and distinct fluid-filling conditions were established, and array acoustic logging numerical simulations were conducted at different frequencies. Subsequently, the waveform data were processed to extract acoustic characteristic parameters, such as velocities and amplitude attenuations of compressional and shear waves. Finally, a quantitative analysis was conducted to examine the variation patterns of characteristic parameters of refracted compressional and shear waves in relation to fracture properties. The research results indicate that amplitude attenuation information derived from borehole wave modes is particularly sensitive to the changes in fracture properties. As fracture width increased, we observed a significant amplitude attenuation in both compressional and shear waves, proportional to the logarithm of the attenuation coefficients. Furthermore, when the fracture width was constant, gas-filled fractures exhibited more prominent amplitude attenuation than water-filled fractures, with shear wave attenuation being more sensitive to the filling material. Moreover, from a quantitative perspective, the analysis revealed that the attenuation coefficients of refracted compressional and shear waves exhibited an exponential variation with gas saturation. Notably, once fracture width and filling conditions were established, the amplitudes of compressional and shear waves at the dominant frequency of 40 kHz were significantly reduced compared to those at 8 kHz, accompanied by increased attenuation. Subsequent quantitative analysis revealed that, when the product of fracture width and dominant frequency remains constant, the corresponding attenuation coefficient ratios approach 1. This indicates that the attenuation process of acoustic propagation in fractured media follows the principle of acoustic similarity. The findings of this study provide reference for further research on fracture property evaluation methods based on array acoustic logging data.

Comprehensive pan-cancer analysis of mitochondrial outer membrane permeabilisation activity reveals positive immunomodulation and assists in identifying potential therapeutic targets for immunotherapy resistance.

BACKGROUND: Mitochondrial outer membrane permeabilisation (MOMP) plays a pivotal role in cellular death and immune activation. A deeper understanding of the impact of tumour MOMP on immunity will aid in guiding more effective immunotherapeutic strategies. METHODS: A comprehensive pan-cancer dataset comprising 30 cancer-type transcriptomic cohorts, 20 immunotherapy transcriptomic cohorts and three immunotherapy scRNA-seq datasets was collected and analysed to determine the influence of tumour MOMP activity on clinical prognosis, immune infiltration and immunotherapy effectiveness. Leveraging 65 scRNA-Seq datasets, the MOMP signature (MOMP.Sig) was developed to accurately reflect tumour MOMP activity. The clinical predictive value of MOMP.Sig was explored through machine learning models. Integration of the MOMP.Sig model and a pan-cancer immunotherapy CRISPR screen further investigated potential targets to overcome immunotherapy resistance, which subsequently underwent clinical validation. RESULTS: Our research revealed that elevated MOMP activity reduces mortality risk in cancer patients, drives the formation of an anti-tumour immune environment and enhances the response to immunotherapy. This finding emphasises the potential clinical application value of MOMP activity in immunotherapy. MOMP.Sig, offering a more precise indicator of tumour cell MOMP activity, demonstrated outstanding predictive efficacy in machine-learning models. Moreover, with the assistance of the MOMP.Sig model, FOXO1 was identified as a core modulator that promotes immune resistance. Finally, these findings were successfully validated in clinical immunotherapy cohorts of skin cutaneous melanoma and triple-negative breast cancer patients. CONCLUSIONS: This study enhances our understanding of MOMP activity in immune modulation, providing valuable insights for more effective immunotherapeutic strategies across diverse tumours.

Population interaction network in representative gravitational search algorithms: Logistic distribution leads to worse performance.

In this paper, a novel study on the way inter-individual information interacts in meta-heuristic algorithms (MHAs) is carried out using a scheme known as population interaction networks (PIN). Specifically, three representative MHAs, including the differential evolutionary algorithm (DE), the particle swarm optimization algorithm (PSO), the gravitational search algorithm (GSA), and four classical variations of the gravitational search algorithm, are analyzed in terms of inter-individual information interactions and the differences in the performance of each of the algorithms on IEEE Congress on Evolutionary Computation 2017 benchmark functions. The cumulative distribution function (CDF) of the node degree obtained by the algorithm on the benchmark function is fitted to the seven distribution models by using PIN. The results show that among the seven compared algorithms, the more powerful DE is more skewed towards the Poisson distribution, and the weaker PSO, GSA, and GSA variants are more skewed towards the Logistic distribution. The more deviation from Logistic distribution GSA variants conform, the stronger their performance. From the point of view of the CDF, deviating from the Logistic distribution facilitates the improvement of the GSA. Our findings suggest that the population interaction network is a powerful tool for characterizing and comparing the performance of different MHAs in a more comprehensive and meaningful way.

Investigation of zero-phonon line characteristics in ensemble nitrogen-vacancy centers at 1.6†K-300†K.

The ensemble of nitrogen-vacancy (NV) centers is widely used in quantum information transmission, high-precision magnetic field, and temperature sensing due to their advantages of long-lived state and the ability to be pumped by optical cycling. In this study, we investigate the zero-phonon line behavior of the two charge states of NV centers by measuring the photoluminescence of the NV center at 1.6 K-300 K. The results demonstrate a positional redshift, an increase in line width, and a decrease in fluorescence intensity for the ZPL of NV0 and NV- as the temperature increased. In the range of 10 K to 140 K, the peak shift with high concentrations of NV- revealed an anomaly of bandgap reforming. The peak position undergoes a blueshift and then a redshift as temperature increases. Furthermore, the transformation between NV0 and NV- with temperature changes has been obtained in diamonds with different nitrogen concentrations. This study explored the ZPL characteristics of NV centers in various temperatures, and the findings are significant for the development of high-resolution temperature sensing and high-precision magnetic field sensing in ensemble NV centers.

Landscape of the gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health.

OBJECTIVE: The remodelling of gut mycobiome (ie, fungi) during pregnancy and its potential influence on host metabolism and pregnancy health remains largely unexplored. Here, we aim to examine the characteristics of gut fungi in pregnant women, and reveal the associations between gut mycobiome, host metabolome and pregnancy health. DESIGN: Based on a prospective birth cohort in central China (2017 to 2020): Tongji-Huaxi-Shuangliu Birth Cohort, we included 4800 participants who had available ITS2 sequencing data, dietary information and clinical records during their pregnancy. Additionally, we established a subcohort of 1059 participants, which included 514 women who gave birth to preterm, low birthweight or macrosomia infants, as well as 545 randomly selected controls. In this subcohort, a total of 750, 748 and 709 participants had ITS2 sequencing data, 16S sequencing data and serum metabolome data available, respectively, across all trimesters. RESULTS: The composition of gut fungi changes dramatically from early to late pregnancy, exhibiting a greater degree of variability and individuality compared with changes observed in gut bacteria. The multiomics data provide a landscape of the networks among gut mycobiome, biological functionality, serum metabolites and pregnancy health, pinpointing the link between Mucor and adverse pregnancy outcomes. The prepregnancy overweight status is a key factor influencing both gut mycobiome compositional alteration and the pattern of metabolic remodelling during pregnancy. CONCLUSION: This study provides a landscape of gut mycobiome dynamics during pregnancy and its relationship with host metabolism and pregnancy health, which lays the foundation of the future gut mycobiome investigation for healthy pregnancy.

A generative benchmark for evaluating the performance of fluorescent cell image segmentation.

Fluorescent cell imaging technology is fundamental in life science research, offering a rich source of image data crucial for understanding cell spatial positioning, differentiation, and decision-making mechanisms. As the volume of this data expands, precise image analysis becomes increasingly critical. Cell segmentation, a key analysis step, significantly influences quantitative analysis outcomes. However, selecting the most effective segmentation method is challenging, hindered by existing evaluation methods' inaccuracies, lack of graded evaluation, and narrow assessment scope. Addressing this, we developed a novel framework with two modules: StyleGAN2-based contour generation and Pix2PixHD-based image rendering, producing diverse, graded-density cell images. Using this dataset, we evaluated three leading cell segmentation methods: DeepCell, CellProfiler, and CellPose. Our comprehensive comparison revealed CellProfiler's superior accuracy in segmenting cytoplasm and nuclei. Our framework diversifies cell image data generation and systematically addresses evaluation challenges in cell segmentation technologies, establishing a solid foundation for advancing research and applications in cell image analysis.

Ab initio determination of melting and sound velocity of neon up to the deep interior of the Earth.

The thermophysical properties and elemental abundances of the noble gases in terrestrial materials can provide unique insights into the Earth's evolution and mantle dynamics. Here, we perform extensive ab initio molecular dynamics simulations to determine the melting temperature and sound velocity of neon up to 370 GPa and 7500 K to constrain its physical state and storage capacity, together with to reveal its implications for the deep interior of the Earth. It is found that solid neon can exist stably under the lower mantle and inner core conditions, and the abnormal melting of neon is not observed under the entire temperature (T) and pressure (P) region inside the Earth owing to its peculiar electronic structure, which is substantially distinct from other heavier noble gases. An inspection of the reduction for sound velocity along the Earth's geotherm evidences that neon can be used as a light element to account for the low-velocity anomaly and density deficit in the deep Earth. A comparison of the pair distribution functions and mean square displacements of MgSiO3-Ne and Fe-Ne alloys further reveals that MgSiO3 has a larger neon storage capacity than the liquid iron under the deep Earth condition, indicating that the lower mantle may be a natural deep noble gas storage reservoir. Our results provide valuable information for studying the fundamental behavior and phase transition of neon in a higher T-P regime, and further enhance our understanding for the interior structure and evolution processes inside the Earth.

Promoting tissue repair using deferoxamine nanoparticles loaded biomimetic gelatin/HA composite hydrogel.

To effectively address underlying issues and enhance the healing process of hard-to-treat soft tissue defects, innovative therapeutic approaches are required. One promising strategy involves the incorporation of bioactive substances into biodegradable scaffolds to facilitate synergistic tissue regeneration, particularly in vascular regeneration. In this study, we introduce a composite hydrogel design that mimics the extracellular matrix by covalently combining gelatin and hyaluronic acid (HA), with the encapsulation of deferoxamine nanoparticles (DFO NPs) for potential tissue regeneration applications. Crosslinked hydrogels were fabricated by controlling the ratio of HA in the gelatin-based hydrogels, resulting in improved mechanical properties, enhanced degradation ability, and optimised porosity, compared with hydrogel formed by gelatin alone. The DFO NPs, synthesized using a double emulsion method with poly (D,L-lactide-co-glycolide acid), exhibited a sustained release of DFO over 12 d. Encapsulating the DFO NPs in the hydrogel enabled controlled release over 15 d. The DFO NPs, composite hydrogel, and the DFO NPs loaded hydrogel exhibited excellent cytocompatibility and promoted cell proliferationin vitro. Subcutaneous implantation of the composite hydrogel and the DFO NPs loaded hydrogel demonstrated biodegradability, tissue integration, and no obvious adverse effects, evidenced by histological analysis. Furthermore, the DFO NPs loaded composite hydrogel exhibited accelerated wound closure and promoted neovascularisation and granular formation when tested in an excisional skin wound model in mice. These findings highlight the potential of our composite hydrogel system for promoting the faster healing of diabetes-induced skin wounds and oral lesions through its ability to modulate tissue regeneration processes.

Transformation of dissolved organic matter during groundwater arsenite removal using air cathode iron electrocoagulation.

Dissolve organic matters (DOM) usually showed negative effect on the removal of inorganic arsenic (As) in groundwater by electrochemical approaches, yet which parts of sub-component within DOM played the role was lack of evidence. Herein, we investigated the effects of land-source humic-like acid (HA) on groundwater As(III) removal using air cathode iron electrocoagulation, based on the parallel factor analysis of three-dimensional excitation-emission matrix and statistical methods. Our results showed that the land-source HA contained five kinds of components and all components presented significantly negative correlations with the removal of both As(III) and As(V). However, the high aromatic fulvic-like acid and low aromatic humic-like acid components of land-source HA presented the opposite correlations with the concentration of As(III) during the reaction. The high aromaticity fulvic-like components of land-source HA (Sigma-Aldrich HA, SAHA) produced during the reaction facilitated the oxidation of As(III) due to its high electron transfer capacities and good solubility in wide pH range, but the low aromaticity humic-like ones worked against the oxidation of As(III). Our findings offered the novel insights for the flexible activities of DOM in electron Fenton system.

[Cannabinoid receptor 1 agonist arachidonyl-2'-chloroethylamide (ACEA) improves sepsis-associated encephalopathy by inhibiting inflammatory factors].

Objective To investigate the impact of the cannabinoid receptor agonist arachidonyl-2'-chloroethylamide (ACEA) on cognitive function in mice with sepsis-associated encephalopathy (SAE). Methods C57BL/6 mice were randomly divided into artificial cerebrospinal fluid (ACSF) and lipopolysaccharide (LPS) groups. The SAE model was established by intraventricular injection of LPS. The severity of sepsis in mice was assessed by sepsis severity score (MSS) and body mass changes. Behavioral paradigms were used to evaluate motor ability (open field test) and cognitive function (contextual fear conditioning test, Y-maze test). To evaluate the effects of ACEA intervention on SAE, mice were randomly assigned to ACSF group, ACEA intervention combined with ACSF group, LPS group, and ACEA intervention combined with LPS group. The dosage of ACEA intervention was 1.5 mg/kg. Real-time quantitative PCR was used to measure the mRNA expression levels of interleukin 1ß (IL-1ß), IL-6, and tumor necrosis factor α (TNF-α) in mouse hippocampal tissues. Western blot analysis was used to assess the protein levels of IL-6 and TNF-α in the hippocampus. Nissl staining was performed to examine neuronal damage in the CA1 region of the mouse hippocampus. Behavioral paradigms were again employed to evaluate motor ability and cognitive function. Results Three days after intraventricular LPS injection, mice exhibited significant cognitive dysfunction, confirming SAE modeling. Compared to the control group, the LPS group showed significant increases in mRNA of inflammatory factors such as IL-6, TNF-α, and IL-1ß, together with significant increases in IL-6 and TNF-α protein levels in the hippocampus, a decrease in Nissl bodies in the CA1 region, and significant cognitive dysfunction. Compared to the LPS group, the ACEA intervention group showed a significant decrease in the mRNA of IL-6, TNF-α, and IL-1ß, a significant reduction in IL-6 and TNF-α protein levels, an increase in Nissl bodies, and improved cognitive function. Conclusion ACEA improves cognitive function in SAE mice by inhibiting the expression levels of inflammatory factors IL-6 and TNF-α.