Zn promoted GaZrOx ternary solid solution oxide combined with SAPO-34 effectively converts CO2 to light olefins with low CO selectivity.

We proposed a new strategy for CO2 hydrogenation to prepare light olefins by introducing Zn into GaZrOx to construct ZnGaZrOx ternary oxides, which was combined with SAPO-34 to prepare a high-performance ZnGaZrOx/SAPO-34 tandem catalyst for CO2 hydrogenation to light olefins. By optimizing the Zn doping content, the ratio and mode of the two-phase composite, and the process conditions, the 3.5%ZnGaZrOx/SAPO-34 tandem catalyst showed excellent catalytic performance and good high-temperature inhibition of the reverse water-gas shift (RWGS) reaction. The catalyst achieved 26.6% CO2 conversion, 82.1% C2=-C4= selectivity and 11.8% light olefins yield. The ZnGaZrOx formed by introducing an appropriate amount of Zn into GaZrOx significantly enhanced the spillover H2 effect and also induced the generation of abundant oxygen vacancies to effectively promote the activation of CO2. Importantly, the RWGS reaction was also significantly suppressed at high temperatures, with the CO selectivity being only 46.1% at 390°C.

Uncovering the molecular mechanism of Mume Fructus in treatment of Sjögren's syndrome.

BACKGROUND: Modern medicine has no cure for the xerostomia caused by the early onset of Sjögren's syndrome. Mume Fructus is a common Chinese herbal medicine used to relieve xerostomia. However, the molecular mechanisms of the effects of Mume Fructus are unknown. In this study, network pharmacology and molecular docking were used to investigate the mechanisms of action of Mume Fructus on Sjögren's syndrome. MATERIALS AND METHOD: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database was used to identify the active components and targets of Mume Fructus, and the UniProt database was used to identify the genes encoding these targets. SS-related targets were also identified from the GeneCards and OMIM databases. By finding the intersection of the targets of the compounds and the targets of Sjögren's syndrome, the predicted targets of Mume Fructus in the treatment of Sjögren's syndrome were obtained. Further investigation of the active compounds and their targets was carried out by constructing a network of "medicine-candidate compound-target-disease" using Cytoscape 3.7.2, the Protein-Protein Interaction network using the STRING database and Cytoscape 3.7.2, and key targets were identified by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on R software. Finally, molecular docking was used to verify the affinity of the candidate compounds to the key targets. RESULTS: Quercetin, beta-sitosterol, and kaempferol in Mume Fructus interact with AKT1, IL-6, IL-1B, JUN, CASP3, and MAPK8. These results suggest that Mume Fructus exerts its therapeutic effects on the peripheral gland injury of Sjögren's syndrome and its secondary cardiovascular disease and tumorigenesis through anti-inflammatory, anti-oxidant, and anti-tumor pathways. CONCLUSION: With network pharmacology, this study systematically identified the main active components, targets, and specific mechanisms of the therapeutic effects of Mume Fructus on Sjögren's syndrome, providing both a theoretical basis and research direction for further investigations on Mume Fructus.

Neural mechanism of non-adaptive cognitive emotion regulation in patients with non-suicidal self-injury.

BACKGROUND: The incidence of non-suicidal self-injury (NSSI) has been on the rise in recent years. Studies have shown that people with NSSI have difficulties in emotion regulation and cognitive control. In addition, some studies have investigated the cognitive emotion regulation of people with NSSI which found that they have difficulties in cognitive emotion regulation, but there was a lack of research on cognitive emotion regulation strategies and related neural mechanisms. METHODS: This study included 117 people with NSSI (age = 19.47 ± 5.13, male = 17) and 84 non-NSSI participants (age = 19.86 ± 4.14, male = 16). People with NSSI met the DSM-5 diagnostic criteria, and non-NSSI participants had no mental or physical disorders. The study collected all participants' data of Cognitive Emotion Regulation Questionnaire (CERQ) and functional magnetic resonance imaging (fMRI) to explore the differences in psychological performance and brain between two groups. Afterwards, Machine learning was used to select the found differential brain regions to obtain the highest correlation regions with NSSI. Then, Allen's Human Brain Atlas database was used to compare with the information on the abnormal brain regions of people with NSSI to find the genetic information related to NSSI. In addition, gene enrichment analysis was carried out to find the related pathways and specific cells that may have differences. RESULTS: The differences between NSSI participants and non-NSSI participants were as follows: positive refocusing (t = -4.74, p < 0.01); refocusing on plans (t = -4.11, p < 0.01); positive reappraisal (t = -9.22, p < 0.01); self-blame (t = 6.30, p < 0.01); rumination (t = 3.64, p < 0.01); catastrophizing (t = 9.10, p < 0.01), and blaming others (t = 2.52, p < 0.01), the precentral gyrus (t = 6.04, pFDR < 0.05) and the rolandic operculum (t = -4.57, pFDR < 0.05). Rolandic operculum activity was negatively correlated with blaming others (r = -0.20, p < 0.05). Epigenetic results showed that excitatory neurons (p < 0.01) and inhibitory neurons (p < 0.01) were significant differences in two pathways, "trans-synaptic signaling" (p < -log108) and "modulation of chemical synaptic transmission" (p < -log108) in both cells. CONCLUSIONS: People with NSSI are more inclined to adopt non-adaptive cognitive emotion regulation strategies. Rolandic operculum is also abnormally active. Abnormal changes in the rolandic operculum of them are associated with non-adaptive cognitive emotion regulation strategies. Changes in the excitatory and inhibitory neurons provide hints to explore the abnormalities of the neurological mechanisms at the cellular level of them. Trial registration number NCT04094623.

Cultivating High-Performance Flexible All-in-One Supercapacitors with 3D Network Through Continuous Biosynthesis.

Flexible supercapacitors are potential to power next-generation flexible electronics. However, the mechanical and electrochemical stability of flexible supercapacitors under different flexible conditions is limited by the weak bonding between adjacent layers, posing a significant hindrance to their practical applicability. Herein, based on the uninterrupted 3D network during the growth of bacterial cellulose (BC), w e have cultivated a flexible all-in-one supercapacitor through a continuous biosynthesis process. This strategy ensures the continuity of the 3D network of BC throughout the material, thereby forming a continuous electrode-separator-electrode structure. Benefitting from this bioinspired structure, the all-in-one supercapacitor not only achieves a high areal capacitance (3.79 F cm-2) of electrodes but also demonstrates the integration of high tensile strength (2.15 MPa), high shear strength (more than 54.6 kPa), and high bending resistance, indicating a novel pathway towards high-performance flexible power sources. This article is protected by copyright. All rights reserved.

DSFE: Decoding EEG-based finger motor imagery using feature-dependent frequency, feature fusion and ensemble learning.

Accurate decoding finger motor imagery is essential for fine motor control using EEG signals. However, decoding finger motor imagery is particularly challenging compared with ordinary motor imagery. This paper proposed a novel EEG decoding method of featuredependent frequency band selection, feature fusion, and ensemble learning (DSFE) for finger motor imagery. First, a feature-dependent frequency band selection method based on correlation coefficient (FDCC) was proposed to select feature-specific effective bands. Second, a feature fusion method was proposed to fuse different types of candidate features to produce multiple refined sets of decoding features. Finally, an ensemble model using the weighted voting strategy was proposed to make full use of these diverse sets of final features. The results on a public EEG dataset of five fingers motor imagery showed that the DSFE method is effective and achieves the highest decoding accuracy of 50.64%, which is 7.64% higher than existing studies using exactly the same data. The experiments further revealed that both the effective frequency bands of different subjects and the effective frequency bands of different types of features are different in finger motor imagery. Furthermore, compared with two-hand motor imagery, the effective decoding information of finger motor imagery is transferred to the lower frequency. The idea and findings in this paper provide a valuable perspective for understanding fine motor imagery in-depth.

Cold-Sintered All-Inorganic Perovskite Bulk Composite Scintillators for Efficient X-ray Imaging.

Cost-effective bulk scintillators with high density, large-area, and long-term stability are desirable for high-energy radiation detections. Conventional bulk polycrystalline or single-crystal scintillators are generally synthesized by high-temperature approaches, and it is challenging to realize simultaneously high detectivity/responsivity, spatial resolution, and rapid time response. Here, we report the cold sintering of bulk scintillators (at 90 °C) based on an "emitter-in-matrix" principle, in which emissive CsPbBr3 nanocrystals are embedded in a durable and transparent Cs4PbBr6 matrix. These bulk scintillators exhibit high light yield (33,800 photons MeV-1), low detection limit (79 nGyair s-1), fast decay time (9.8 ns), and outstanding spatial resolution of 8.9 lp mm-1 to X-ray radiation and an energy resolution of 19.3% for γ-ray (59.6 keV) detection. The composite scintillator also shows exceptional stability against environmental degradation and cyclic X-ray radiation. Our results demonstrate a cost-effective strategy for developing perovskite-based bulk transparent scintillators with exceptional performance and high radioluminescence stability for high-energy radiation detection and imaging.

Machine Learning Assisted Self-Powered Identity Recognition Based on Thermogalvanic Hydrogel for Intelligent Security.

Identity recognition as the first barrier of intelligent security plays a vital role, which is facing new challenges that are unable to meet the need of intelligent era due to low accuracy, complex configuration and dependence on power supply. Here, a finger temperature-driven intelligent identity recognition strategy is presented based on a thermogalvanic hydrogel (TGH) by actively discerning biometric characteristics of fingers. The TGH is a dual network PVA/Agar hydrogel in an H2O/glycerol binary solvent with [Fe(CN)6]3-/4- as a redox couple. Using a concave-arranged TGH array, the characteristics of users can be distinguished adequately even under an open environment by extracting self-existent intrinsic temperature features from five typical sites of fingers. Combined with machine learning, the TGH array can recognize different users with a high average accuracy of 97.6%. This self-powered identity recognition strategy is further applied to a smart lock, attaining a more reliable security protection from biometric characteristics than bare passwords. This work provides a promising solution for achieving better identity recognition, which has great advantages in intelligent security and human-machine interaction toward future Internet of everything.

Weight status changes from childhood to adulthood were associated with cardiometabolic outcomes in adulthood.

AIM: Few studies have assessed the association between weight changes from childhood to adulthood and cardiometabolic factors in adulthood. The aim of this study was to explore the relationships between weight changes from childhood to adulthood and cardiometabolic factors in adulthood using national Chinese data. METHODS: We included 649 participants from the China Health and Nutrition Survey from 1989 to 2009 and divided them into four groups by their body mass index from 6 to 37 years of age. They were selected using multistage random cluster sampling from 15 areas with large variations in economic and social development. Poisson regression models assessed associations between weight status changes and cardiometabolic outcomes in adulthood. RESULTS: The risk of multiple abnormal cardiometabolic outcomes in adulthood was increased in the 126 subjects with normal weight in childhood but overweight or obesity in adulthood and the 28 with obesity at both ages, compared to the 462 with normal weight at both ages. There was insufficient evidence to demonstrate that the 33 who had weight issues as children, but not as adults, had an increased risk. CONCLUSION: Being overweight or obese in both childhood and adulthood or during adulthood only increased the risk of abnormal cardiometabolic outcomes in adulthood. Larger studies need to investigate whether weight problems in childhood, but not adulthood, increase the risk.

Visualizing Motion Trail via Phosphorescence Carbon Nanodots-Based Delay Display Array.

A scene that contains both old and instant events with a clear motion trail is visually intriguing and dynamic, which can convey a sense of change, transition, or evolution. Developing an eco-friendly delay display system offers a powerful tool for fusing old and instant events, which can be used for visualizing motion trails. Herein, we brighten triplet excitons of carbon nanodots (CNDs) and increase their emission yield by a multidimensional confinement strategy, and the CND-based delay display array is demonstrated. The intense confinement effects via multidimensional confinement strategy suppress nonradiative transitions, and 240% enhancement in the phosphorescence efficiency and 260% enhancement in the lifetime of the CNDs are thus realized. Considering their distinctive phosphorescence performances, a delay display array containing a 4 × 4 CND-based delay lighting device is demonstrated, which can provide ultralong phosphorescence over 7 s, and the motion that occurred in different timelines is recorded clearly. This finding will motivate the investigation of phosphorescent CNDs in motion trail recognition.

A novel strategy for enhancing the stability of aptamer conformations in heavy metal ion detection.

BACKGROUND: Detection methods based on aptamer probes have great potential and progress in the field of rapid detection of heavy metal ions. However, the unstable conformation of aptamers often results in poor sensitivity due to the dissociation of aptamer-target complex in real environments. RESULTS: In this study, we developed a locking aptamer probe and combined it with AgInZnS quantum dots for the first time to detect cadmium ions. When cadmium ions are combined with the probe, the cadmium ions are fixed in the core-locking position, forming a stable cavity structure. The limit of detection (LOD) was achieved at a concentration of 6.9 nmol L-1, with a broad detection range from 10 nmol L-1 to 1000 µmol L-1, and good recovery rates (92.93%-102.8 %) were achieved in aquatic product testing. The locking aptamer probe with stable conformation effectively enhances the stability of the aptamer-target complex and remains good stability in four buffer environments as well as a 600 mmol L-1 salt solution; it also exhibits good stability at pH 6.5-7.5 and temperatures ranging from 25 °C to 35 °C. SIGNIFICANCE: Overall, our study presented a general, simple, and cost-effective strategy for stabilizing aptamer conformations, and used for highly sensitive detection of cadmium ions.

Causal Association Between Diabetes, Body Mass Index and Lichen Sclerosus: A Bidirectional Two-Sample Mendelian Randomization Analysis.

Background: Previous observational studies have found that lichen sclerosus (LS) is associated with metabolic statuses, such as diabetes mellitus (DM) and body mass index (BMI). However, there are also some studies showing that LS is not related to DM and BMI. The mechanism behind observational results is still unclear. Therefore, the causality of this relationship remains unknown. In this study, a bidirectional two-sample Mendelian randomization (MR) was conducted to investigate the correlation between DM, BMI, and LS. Methods: The instrumental variables related to DM (including type 1 and type 2 diabetes), and BMI were identified from genome-wide association studies (GWAS) and a GWAS meta-analysis. The GWAS data for LS was from obtained the eighth edition of the FinnGen biological database released in 2022. Inverse variance weighted (IVW), weighted median, and MR-Egger methods were used to conduct a bidirectional two-sample MR analysis. Thereafter, the heterogeneity and horizontal pleiotropy were examined to determine whether the results were affected by a single-nucleotide polymorphism (SNP). Results: We found a lack of evidence for the causal association of DM, and BMI on LS in inverse variance weighted (type 1 diabetes, OR=0.97, 95% CI=0.91-1.04, p=0.429; type 2 diabetes, OR=0.91, 95% CI=0.82-1.00, p=0.0511; BMI, OR=0.92, 95% CI=0.73-1.15, p=0.4554). In the other direction, the results also showed that LS had no significant causal effect on DM and BMI. Conclusion: This MR analysis demonstrated no significant causal relationship between DM and BMI with LS in both directions, which contradicts previous observational studies reporting a positive association. Potential confounding factors may contribute to previously observed associations, and further research is necessary.

Prolonged HPA axis dysregulation in postpartum depression associated with adverse early life experiences: A cross-species translational study.

Childhood and adolescent stress increase the risk of postpartum depression (PPD), often providing an increased probability of treatment refractoriness. Nevertheless, the mechanisms linking childhood/adolescent stress to PPD remain unclear. Our study investigated the longitudinal effects of adolescent stress on the hypothalamic-pituitary-adrenal (HPA) axis and postpartum behaviors in mice and humans. Adolescent social isolation prolonged glucocorticoid elevation, leading to long-lasting postpartum behavioral changes in female mice. These changes were unresponsive to current PPD treatments but improved with post-delivery glucocorticoid receptor antagonist treatment. Childhood/adolescent stress significantly impacted HPA axis dysregulation and PPD in human females. Repurposing glucocorticoid receptor antagonists for some cases of treatment-resistant PPD may be considered.

Identification of PavHB16 gene in Prunus avium and validation of its function in Arabidopsis thaliana.

Sweet cherry (Prunus avium L.) is one of the most economically important fruits in the world. However, severe fruit abscission has brought significant challenges to the cherry industry. To better understand the molecular regulation mechanisms underlying excessive fruit abscission in sweet cherry, the fruit abscission characteristics, the anatomical characteristics of the abscission zone (AZ), as well as a homeodomain-Leucine Zipper gene family member PavHB16 function were analyzed. The results showed that the sweet cherry exhibited two fruit abscission peak stages, with the "Brooks" cultivar demonstrating the highest fruit-dropping rate (97.14%). During these two fruit abscission peak stages, both the retention pedicel and the abscising pedicel formed AZs. but the AZ in the abscising pedicel was more pronounced. In addition, a transcription factor, PavHB16, was identified from sweet cherry. The evolutionary analysis showed that there was high homology between PavHB16 and AtHB12 in Arabidopsis. Moreover, the PavHB16 protein was localized in the nucleus. Overexpression of PavHB16 in Arabidopsis accelerated petal shedding. In the PavHB16-overexpressed lines, the AZ cells in the pedicel became smaller and denser, and the expression of genes involved in cell wall remodeling, such as cellulase 3 gene (AtCEL3), polygalacturonase 1 (AtPG1), and expandin 24(AtEXPA24) were upregulated. The results suggest that PavHB16 may promote the expression of genes related to cell wall remodeling, ultimately facilitating fruit abscission. In summary, this study cloned the sweet cherry PavHB16 gene and confirmed its function in regulating sweet cherry fruit abscission, which provided new data for further study on the fruit abscission mechanism. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01443-8.

Self-Supervised Joint Learning for pCLE Image Denoising.

Probe-based confocal laser endoscopy (pCLE) has emerged as a powerful tool for disease diagnosis, yet it faces challenges such as the formation of hexagonal patterns in images due to the inherent characteristics of fiber bundles. Recent advancements in deep learning offer promise in image denoising, but the acquisition of clean-noisy image pairs for training networks across all potential scenarios can be prohibitively costly. Few studies have explored training denoising networks on such pairs. Here, we propose an innovative self-supervised denoising method. Our approach integrates noise prediction networks, image quality assessment networks, and denoising networks in a collaborative, jointly trained manner. Compared to prior self-supervised denoising methods, our approach yields superior results on pCLE images and fluorescence microscopy images. In summary, our novel self-supervised denoising technique enhances image quality in pCLE diagnosis by leveraging the synergy of noise prediction, image quality assessment, and denoising networks, surpassing previous methods on both pCLE and fluorescence microscopy images.

Association of Ultraprocessed Food Consumption with Risk of Cardiovascular Disease Among Individuals with Type 2 Diabetes: Findings from the UK Biobank.

SCOPE: Among patients with diabetes, who have modified nutritional behavior and a higher risk of cardiovascular disease (CVD), the influence of ultraprocessed foods (UPFs) on CVD remains unknown. The study aims to evaluate the association between UPF intake and the risk of CVD among individuals with type 2 diabetes (T2D) and further examine the potential biological pathways linking the association. METHODS AND RESULTS: This study includes 5405 participants with T2D who provided at least one 24-h dietary recall from the UK Biobank study. In the fully adjusted models, a 10% increase in the proportion of UPFs is associated with higher hazards of overall CVD (hazard ratio [HR]: 1.10; 95% confidence interval [CI]: 1.04, 1.15), coronary heart disease (HR: 1.10; 95% CI: 1.04, 1.16), heart failure (HR: 1.14; 95% CI: 1.05, 1.25), but not stroke (HR: 1.01; 95% CI: 0.90, 1.12). Cystatin C, high-density lipoprotein cholesterol (HDL-C), apolipoprotein A, C-reactive protein, and body mass index collectively explain 26.9% (12.8%, 48.5%) of the association between UPF intake and the risk of overall CVD. CONCLUSION: Higher UPF intakes are associated with increased hazards of CVD among individuals with T2D, and the association is partly mediated through worsening biomarkers of renal function, lipid metabolism, inflammation, and body weight.

Alterations in CX3CL1 Levels and Its Role in Viral Pathogenesis.

CX3CL1, also named fractalkine or neurotactin, is the only known member of the CX3C chemokine family that can chemoattract several immune cells. CX3CL1 exists in both membrane-anchored and soluble forms, with each mediating distinct biological activities. CX3CL1 signals are transmitted through its unique receptor, CX3CR1, primarily expressed in the microglia of the central nervous system (CNS). In the CNS, CX3CL1 acts as a regulator of microglia activation in response to brain disorders or inflammation. Recently, there has been a growing interest in the role of CX3CL1 in regulating cell adhesion, chemotaxis, and host immune response in viral infection. Here, we provide a comprehensive review of the changes and function of CX3CL1 in various viral infections, such as human immunodeficiency virus (HIV), SARS-CoV-2, influenza virus, and cytomegalovirus (CMV) infection, to highlight the emerging roles of CX3CL1 in viral infection and associated diseases.

Double-walled Al-based MOF with large microporous specific surface area for trace benzene adsorption.

Double-walled metal-organic frameworks (MOFs), synthesized using Zn and Co, are potential porous materials for trace benzene adsorption. Aluminum is with low-toxicity and abundance in nature, in comparison with Zn and Co. Therefore, a double-walled Al-based MOF, named as ZJU-520(Al), with large microporous specific surface area of 2235 m2 g-1, pore size distribution in the range of 9.26-12.99 Å and excellent chemical stability, was synthesized. ZJU-520(Al) is consisted by helical chain of AlO6 clusters and 4,6-Di(4-carboxyphenyl)pyrimidine ligands. Trace benzene adsorption of ZJU-520(Al) is up to 5.98 mmol g-1 at 298 K and P/P0 = 0.01. Adsorbed benzene molecules are trapped on two types of sites. One (site I) is near the AlO6 clusters, another (site II) is near the N atom of ligands, using Grand Canonical Monte Carlo simulations. ZJU-520(Al) can effectively separate trace benzene from mixed vapor flow of benzene and cyclohexane, due to the adsorption affinity of benzene higher than that of cyclohexane. Therefore, ZJU-520(Al) is a potential adsorbent for trace benzene adsorption and benzene/cyclohexane separation.

County land use carbon emission and scenario prediction in Mianyang Science and Technology City New District, Sichuan Province, China.

The role of carbon emissions resulting from land use change in the compilation of national greenhouse gas emission inventories is of paramount significance. This study is centered on the Mianyang Science and Technology City New Area located in Sichuan Province, China. We used the CLUE-S model and Sentinel-2A remote sensing data from 2017 to simulate and validate land use changes in 2022. Based on this validation, we established three simulation scenarios: a baseline scenario, an agricultural development scenario, and a construction development scenario. Using remote sensing data from 2022, we projected the land use for 2030. We also used CO2 concentration data collected in 2022 and 2023, processed the data using ArcGIS and Python, and conducted a quantitative analysis of carbon emissions under each scenario. Ultimately, the accuracy of both measured and predicted CO2 values for 2023 was juxtaposed and authenticated, thus concluding the investigative cycle of this study. Key findings include: (1) The accuracy of the CLUE-S model in the study area was assessed using overall accuracy, quantity disagreement and allocation disagreement indexes. In 2022, the overall accuracy is 98.19%, the quantity disagreement is 1.7%, and the allocation disagreement is 2.2%. (2) Distinct land resource utilization characteristics in scenarios, highlighting potential impacts on economic development and pollution. (3) Increased carbon emissions across scenarios, with construction development showing the highest rise (4.170%) and agricultural development the lowest (0.766%). (4) The predictive accuracy of the validation group's CO2 concentration values can reach 99.5%. This study proposes precise CO2 prediction at the county level, thus laying the groundwork for future research endeavors. Such findings are indispensable for informing carbon policy formulation and promoting low-carbon development strategies.

Dysregulated Glucuronidation of Bilirubin Exacerbates Liver Inflammation and Fibrosis in Schistosomiasis Japonica through the NF-κB Signaling Pathway.

Hepatic fibrosis is an important pathological manifestation of chronic schistosome infection. Patients with advanced schistosomiasis show varying degrees of abnormalities in liver fibrosis indicators and bilirubin metabolism. However, the relationship between hepatic fibrosis in schistosomiasis and dysregulated bilirubin metabolism remains unclear. In this study, we observed a positive correlation between total bilirubin levels and the levels of ALT, AST, LN, and CIV in patients with advanced schistosomiasis. Additionally, we established mouse models at different time points following S. japonicum infection. As the infection time increased, liver fibrosis escalated, while liver UGT1A1 consistently exhibited a low expression, indicating impaired glucuronidation of bilirubin metabolism in mice. In vitro experiments suggested that SEA may be a key inhibitor of hepatic UGT1A1 expression after schistosome infection. Furthermore, a high concentration of bilirubin activated the NF-κB signaling pathway in L-O2 cells in vitro. These findings suggested that the dysregulated glucuronidation of bilirubin caused by S. japonicum infection may play a significant role in schistosomiasis liver fibrosis through the NF-κB signaling pathway.