Berbamine ameliorates DSS-induced colitis by inhibiting peptidyl-arginine deiminase 4-dependent neutrophil extracellular traps formation.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease with immune dysregulation affecting colon inflammatory response. Recent studies have highlighted that neutrophil extracellular traps (NETs) play an important role in the pathogenesis of UC. Berbamine (BBM), one of the bioactive ingredients extracted from Chinese herbal medicine Berberis vulgaris L, has attracted intensive attentions due to its significant anti-inflammatory activity and a marketing drug for treating leukemia in China. However, the exact role and potential molecular mechanism of BBM against UC remains elusive. In the present study, our results showed that BBM could markedly improve the pathological phenotype and the colon inflammation in mice with dextran sulfate sodium (DSS)-induced colitis. Then, comprehensive approaches combining network pharmacology and molecular docking analyses were employed to predict the therapeutic potential of BBM in treating UC by peptidyl-arginine deiminase 4 (PAD4), a crucial molecule involved in NETs formation. The molecular docking results showed BBM had a high affinity for PAD4 with a binding energy of -9.3 kcal/mol Moreover, PAD4 expression and NETs productions, including citrullination of histone H3 (Cit-H3), neutrophil elastase (NE), myeloperoxidase (MPO) in both neutrophils and colonic tissue were reduced after BBM administration. However, in the mice with DSS-induced colitis pretreated with GSK484, a PAD4-specific inhibitor, BBM could not further reduce disease related indexes, expression of PAD4 and NETs productions. Above all, the identification of PAD4 as a potential target for BBM to inhibit NETs formation in colitis provides novel insights into the development of BBM-derived drugs for the clinical management of UC.

Effects of Cadmium and Lead Co-exposure on Sleep Status in Rural Areas Northwestern China.

In this study, we explored how cadmium and lead co-exposure affects sleep status among residents of a polluted area and nature reserve in rural northwestern China. Cadmium and lead levels were measured using blood samples, and sleep status was evaluated using sleep questionnaires, with the main sleep indicators including sleep duration, sleep quality, bedtime, and staying up. Furthermore, cadmium-lead co-exposure levels were divided into three groups: high exposure, medium exposure, and low exposure. Subjects in the contaminated area had significantly higher exposure levels (p < 0.001) and more negative sleep indicators (p < 0.01). Significant differences were found for all four sleep indicators in the high exposure group compared to the low exposure group (p < 0.01). Moreover, the overall evaluation of sleep status with high cadmium-lead co-exposure had a negative impact. Our data suggest that cadmium-lead co-exposure has a negative effect on sleep status and may have a synergistic effect on sleep.

Bayesian analysis of physiologically based toxicokinetic (PBTK) modeling for pentachlorophenol exposure in pregnant women.

Pentachlorophenol (PCP) is a persistent organic compound that is widely present in the environment. The estimation of internal exposure levels for a given external exposure using toxicokinetic models is key to the human health risk assessment of PCP. The present study developed a physiologically based multicompartmental pharmacokinetic (PBTK) model to describe and predict the behavior of pentachlorophenol (PCP) in an organism. The model consists of stomach, intestines, adipose tissue, kidneys and fast- and poorly perfused tissues that are interconnected via blood circulation. We constructed a PBTK model of PCP in rats and extrapolated it to human dietary PCP exposure. The toxicokinetic data of PCP in human tissues and excreta were obtained from the published literature. Based on the collected PCP dietary survey and internal exposure data of pregnant women in Shanghai, Bayesian statistical analysis was performed for the model using Markov chain Monte Carlo (MCMC) simulation. The posterior distributions of the sensitive parameters were estimated, and the model was parameter optimized and validated using the pregnant women's test dataset. The results showed that the root mean square error (RMSE) improved 37.3% compared to the original model, and a systematic literature search revealed that the optimized model achieved acceptable prediction results for other datasets in China. A PCP metabolism model based on the exposure characteristics of pregnant women in China was constructed in the present study. The model provides a theoretical basis for the study of PCP toxicity and risk assessment.

Microstructure and Texture Evolution in Cold-Rolled and Annealed Oxygen-Free Copper Sheets.

Commercial oxygen-free copper sheets were cold-rolled with reduction rates ranging from 20% to 87% and annealed at 400, 500 and 600 °C. The microstructure and texture evolution during the cold-rolling and annealing processes were studied using optical microscopy (OM), scanning electron microscopy (SEM) and electron back-scattered diffraction (EBSD). The results show that the deformation textures of {123}<634> (S), {112}<111> (Copper) and {110}<112> (Brass) were continuously enhanced with the increase in cold-rolling reduction. The orientations along the α-oriented fiber converged towards Brass, and the orientation density of ß fiber obviously increased when the rolling reduction exceeded 60%. The recrystallization texture was significantly affected by the cold-rolling reduction. After 60% cold-rolling reduction, Copper and S texture components gradually decreased, and the {011}<511> recrystallization texture component formed with the increase in annealing temperature. After 87% cold-rolling reduction, a strong Cube texture formed, and other textures were inhibited with the increase in annealing temperature. The strong Brass and S deformation texture was conducive to the formation of a strong Cube annealing texture. The density of the annealing twin boundary decreased with the increase in annealing temperature, and more annealing twin boundaries formed in the oxygen-free copper sheets with the increase in cold-rolling reduction.

A latent profile analysis of psychological resilience in gastric cancer survivors: A cross-sectional study.

PURPOSE: To characterize patterns of psychological resilience in gastric cancer survivors using latent profile analyses and to explore the factors influencing these latent profiles based on Kumpfer's resilience framework. METHODS: Five hundred eighty-six gastric cancer survivors were recruited between July 30, 2021, and May 1, 2023. A demographic and clinical characteristics questionnaire, Connor and Davidson's Resilience Scale (CD-RISC), Fear of Progression Questionnaire Short Form (FoP-Q-SF), General Self-efficacy Scale (GSES), Medical Coping Modes Questionnaire (MCMQ), and Social Support Rating Scale (SSRS) were used for the investigation. Latent profile analysis of the resilience of gastric cancer survivors was conducted, and the factors influencing the latent profiles were explored by multivariate logistic regression analysis. RESULTS: A total of 586 questionnaires were collected, and 572 were valid, with an effective recovery rate of 97.61%. The results of latent profile analysis showed that the resilience of gastric cancer survivors was divided into four subgroups, namely, the low-resilience group (18.4%), moderate-resilience group (43.2%), medium-high-resilience group (30.2%), and high-resilience group (8.2%). Multivariate logistic regression analysis showed that fear of disease progression, self-efficacy, medical coping mode and social support were influencing factors of subgroups. CONCLUSIONS: Psychological resilience in gastric cancer survivors is individualized. Nurses should assess risk and protective factors for survivor resilience based on Kumpfer's resilience framework, identify unique needs, and develop new approaches and interventions.

The possibly role of GnIH in stress and gut dysfunction in chicken.

Stress is known to disrupt the intestinal barrier and induce intestinal dysfunction. A critical role for gonadotropin inhibitory hormone (GnIH) in stress has emerged. However, whether GnIH mediates stress-induced intestinal dysfunction remains unknown. The present study explored this question through in vivo and in vitro experiments in hens. Our in vivo experiments showed that continuous intraperitoneal injection of GnIH not only significantly increased the concentration of stress hormones in serum, but also significantly elevated the mRNA expression of glucocorticoid receptor (GR) in the duodenum and jejunum. Moreover, morphological and molecular analyses revealed that GnIH disrupted the physical and chemical barriers of the intestine and dramatically increased inflammatory factor levels in the intestine and serum of hens. Interestingly, the microbiomics results showed that GnIH altered the structure and composition of the gut flora in the cecum, revealing an increased abundance of harmful intestinal bacteria such as Desulfovibrionaceae. Similar results were found in in vitro studies in which the GnIH-induced intestinal mucosal barrier was disrupted, and inflammation increased in jejunal explants, although no significant difference was found in the expression of GR between the control and GnIH groups. Our results demonstrated that GnIH not only directly damaged intestinal barriers and elevated intestinal inflammation but also mediated stress and microflora imbalance-induced intestinal function disorder, suggesting that GnIH is a potential therapeutic target for gut dysfunction, stress-induced intestinal function disorder, and inflammatory bowel disease in animals and humans.

Assessment of the role of false-positive alerts in computer-aided polyp detection for assistance capabilities.

BACKGROUND AND AIM: False positives (FPs) pose a significant challenge in the application of artificial intelligence (AI) for polyp detection during colonoscopy. The study aimed to quantitatively evaluate the impact of computer-aided polyp detection (CADe) systems' FPs on endoscopists. METHODS: The model's FPs were categorized into four gradients: 0-5, 5-10, 10-15, and 15-20 FPs per minute (FPPM). Fifty-six colonoscopy videos were collected for a crossover study involving 10 endoscopists. Polyp missed rate (PMR) was set as primary outcome. Subsequently, to further verify the impact of FPPM on the assistance capability of AI in clinical environments, a secondary analysis was conducted on a prospective randomized controlled trial (RCT) from Renmin Hospital of Wuhan University in China from July 1 to October 15, 2020, with the adenoma detection rate (ADR) as primary outcome. RESULTS: Compared with routine group, CADe reduced PMR when FPPM was less than 5. However, with the continuous increase of FPPM, the beneficial effect of CADe gradually weakens. For secondary analysis of RCT, a total of 956 patients were enrolled. In AI-assisted group, ADR is higher when FPPM ≤ 5 compared with FPPM > 5 (CADe group: 27.78% vs 11.90%; P = 0.014; odds ratio [OR], 0.351; 95% confidence interval [CI], 0.152-0.812; COMBO group: 38.40% vs 23.46%, P = 0.029; OR, 0.427; 95% CI, 0.199-0.916). After AI intervention, ADR increased when FPPM ≤ 5 (27.78% vs 14.76%; P = 0.001; OR, 0.399; 95% CI, 0.231-0.690), but no statistically significant difference was found when FPPM > 5 (11.90% vs 14.76%, P = 0.788; OR, 1.111; 95% CI, 0.514-2.403). CONCLUSION: The level of FPs of CADe does affect its effectiveness as an aid to endoscopists, with its best effect when FPPM is less than 5.

CBX7 silencing promoted liver regeneration by interacting with BMI1 and activating the Nrf2/ARE signaling pathway.

Multiple studies have shown knockdown of chromobox 7 (CBX7) promotes the regenerative capacity of various cells or tissues. We examined the effect of CBX7 on hepatocyte proliferation and liver regeneration after 2/3 hepatectomy in a mouse model. For in vitro experiments, NCTC 1469 and BNL CL.2 hepatocytes were co-transfected with siRNA-CBX7-1 (si-CBX7-1), siRNA-CBX7-2 (si-CBX7-2), pcDNA-CBX7, si-BMI1-1, si-BMI1-2, pcDNA-BMI1, or their negative control. For in vivo experiments, mice were injected intraperitoneally with lentivirus-packaged shRNA and shRNA CBX7 before hepatectomy. Our results showed that CBX7 was rapidly induced in the early stage of liver regeneration. CBX7 regulated hepatocyte proliferation, cell cycle, and apoptosis of NCTC 1469 and BNL CL.2 hepatocytes. CBX7 interacted with BMI1 and inhibited BMI1 expression in hepatocytes. Silencing BMI1 aggregated the inhibitory effect of CBX7 overexpression on hepatocyte viability and the promotion of apoptosis. Furthermore, silencing BMI1 enhanced the regulatory effect of CBX7 on Nrf2/ARE signaling in HGF-induced hepatocytes. In vivo, CBX7 silencing enhanced liver/body weight ratio in PH mice. CBX7 silencing promoted the Ki67-positive cell count and decreased the Tunel-positive cell count after hepatectomy, and also increased the expression of nuclear Nrf2, HO-1, and NQO-1. Our results suggest that CBX7 silencing may increase survival following hepatectomy by promoting liver regeneration.

Peripheral 5-HT mediates GnIH-induced feeding behavior and energy metabolism disorder in chickens via the 5-HT2C receptor.

Gonadotropin-inhibitory hormone (GnIH) plays a critical role of reproduction in vertebrate since its discovery. Recently, a regulatory role of GnIH in appetite and the energy metabolism has emerged, despite its precise physiological mechanisms remain unknown. Thus, the present study evaluated the effects of a single or long-term GnIH treatments (administered via intraperitoneal injection) on the food intake, weight and glucolipid metabolism of chickens, while investigated the possible neuroendocrinology factors and its mechanism that involved in GnIH-induced obesity and glucolipid metabolism disorder. Our results showed that the intraperitoneal administration of GnIH to chickens resulted in marked body mass increased, hyperlipidemia, hyperglycemia and glucose intolerance. Subsequently, the results of metabolomics and pharmacological inhibition of 5-HT2C receptor studies revealed that blocked 5-HT2C receptor reinforced the effects of GnIH on food intake, body weight and the levels of blood glucose and lipid, resulted in GnIH-induced hyperglycaemia, hyperlipidemia and hepatic lipid deposition even worse, suggesting that peripheral 5-HT via 5-HT2C receptor may act as a negative feedback regulator to interplay with GnIH and jointly homeostatic control of energy balance in chickens. Our present study provide evidence of the cross-talk between GnIH and 5-HT in food intake and energy metabolism at the in vivo pharmacological level and to propose a molecular basis for these interactions, suggesting that functional interaction between GnIH and 5-HT may open new avenues to understand the mechanism of neuroendocrine network involved in appetite and energy metabolism as well as provide a new therapeutic strategy to prevent obesity, diabetes and metabolic disorders.

Development and validation of an early mortality risk model for pediatric hemophagocytic lymphohistiocytosis: a comparison with HScore, PELOD-2, P-MODS, and pSOFA.

There has been no severity evaluation model for pediatric patients with hemophagocytic lymphohistiocytosis (HLH) that uses readily available parameters. This study aimed to develop a novel model for predicting the early mortality risk in pediatric patients with HLH using easily obtained parameters whatever etiologic subtype. Patients from one center were divided into training and validation sets for model derivation. The developed model was validated using an independent validation cohort from the second center. The prediction model with nomogram was developed based on logistic regression. The model performance underwent internal and external evaluation and validation using the area under the receiver operating characteristic curve (AUC), calibration curve with 1000 bootstrap resampling, and decision curve analysis (DCA). Model performance was compared with the most prevalent severity evaluation scores, including the PELOD-2, P-MODS, and pSOFA scores. The prediction model included nine variables: glutamic-pyruvic transaminase, albumin, globulin, myohemoglobin, creatine kinase, serum potassium, procalcitonin, serum ferritin, and interval between onset and diagnosis. The AUC of the model for predicting the 28-day mortality was 0.933 and 0.932 in the training and validation sets, respectively. The AUC values of the HScore, PELOD-2, P-MODS and pSOFA were 0.815, 0.745, 0.659 and 0.788, respectively. The DCA of the 28-day mortality prediction exhibited a greater net benefit than the HScore, PELOD-2, P-MODS and pSOFA. Subgroup analyses demonstrated good model performance across HLH subtypes. The novel mortality prediction model in this study can contribute to the rapid assessment of early mortality risk after diagnosis with readily available parameters.

An exploration on the machine-learning-based stroke prediction model.

Introduction: With the rapid development of artificial intelligence technology, machine learning algorithms have been widely applied at various stages of stroke diagnosis, treatment, and prognosis, demonstrating significant potential. A correlation between stroke and cytokine levels in the human body has recently been reported. Our study aimed to establish machine-learning models based on cytokine features to enhance the decision-making capabilities of clinical physicians. Methods: This study recruited 2346 stroke patients and 2128 healthy control subjects from Chongqing University Central Hospital. A predictive model was established through clinical experiments and collection of clinical laboratory tests and demographic variables at admission. Three classification algorithms, namely Random Forest, Gradient Boosting, and Support Vector Machine, were employed. The models were evaluated using methods such as ROC curves, AUC values, and calibration curves. Results: Through univariate feature selection, we selected 14 features and constructed three machine-learning models: Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Machine (GBM). Our results indicated that in the training set, the RF model outperformed the GBM and SVM models in terms of both the AUC value and sensitivity. We ranked the features using the RF algorithm, and the results showed that IL-6, IL-5, IL-10, and IL-2 had high importance scores and ranked at the top. In the test set, the stroke model demonstrated a good generalization ability, as evidenced by the ROC curve, confusion matrix, and calibration curve, confirming its reliability as a predictive model for stroke. Discussion: We focused on utilizing cytokines as features to establish stroke prediction models. Analyses of the ROC curve, confusion matrix, and calibration curve of the test set demonstrated that our models exhibited a strong generalization ability, which could be applied in stroke prediction.

Enhancing Methane Gas Sensing through Defect Engineering in Ag-Ru Co-doped ZnO Nanorods.

Detection of leaks of flammable methane (CH4) gas in a timely manner can mitigate health, safety, and environmental risks. Zinc oxide (ZnO), a polar semiconductor with controllable surface defects, is a promising material for gas sensing. In this study, Ag-Ru co-doped into self-assembled ZnO nanorod arrays (ZnO NRs) was prepared by a one-step hydrothermal method. The Ag-Ru co-doped sample shows a good hydrophobic property as a result of its particular microstructure, which results in high humidity resistance. In addition, oxygen vacancy density significantly increased after Ag-Ru co-doping. Density functional theory (DFT) calculations revealed an exceptionally high charge density accumulated at the Ru sites and the formation of a localized strong electric field, which provides additional energy for the CH4 reaction with •O2- at the surface at room temperature. Optimized AgRu0.025-ZnO demonstrated an outstanding CH4 sensing performance, with a limit of detection (LOD) as low as 2.24 ppm under free-heat and free-light conditions. These findings suggest that introducing defects into the ZnO lattice, such as oxygen vacancies and localized ions, offers a promising approach to improving the gas sensing performance.

Narrowband Organic/Inorganic Hybrid Afterglow Materials.

Narrowband afterglow materials display interesting functions in high-quality anti-counterfeiting and multiplexed bioimaging. However, there is still a limited exploration of these afterglow materials, especially for those with a full width at half maxima (FWHM) around 30 nm. Here, we report the fabrication of narrowband organic/inorganic hybrid afterglow materials via energy transfer technology. Coronene (Cor) with a long phosphorescence feature and broad phosphorescence band is selected as the donor for energy transfer, and inorganic quantum dots (QDs) of CdSe/ZnS with a narrowband emission are used as acceptors. Upon doping into the organic matrix, the resultant three-component materials exhibit a narrowband afterglow with an afterglow lifetime of approximately 3.4 s and an FWHM of 31 nm. The afterglow wavelength of the afterglow materials can be controlled by the QDs. This work based on organic/inorganic hybrids provides a facile approach for developing multicolor and narrowband afterglow materials, as well as opens a new way for expanding the features of organic afterglow for multifunctional applications. It is expected to rely on narrowband afterglow emitters to solve the "spectrum congestion" problem of high-density information storage in optical anti-counterfeiting and information encryption.

Transfer RNA-derived fragment tRF-23-Q99P9P9NDD promotes progression of gastric cancer by targeting ACADSB. / 转移RNA衍生片段tRF-23-Q99P9P9NDD通过靶向ACADSB促进胃癌进展.

Gastric cancer (GC) is one of the most common gastrointestinal tumors. As a newly discovered type of non-coding RNAs, transfer RNA (tRNA)|-derived small RNAs (tsRNAs) play a dual biological role in cancer. Our previous studies have demonstrated the potential of tRF-23-Q99P9P9NDD as a diagnostic and prognostic biomarker for GC. In this work, we confirmed for the first time that tRF-23-Q99P9P9NDD can promote the proliferation, migration, and invasion of GC cells in vitro. The dual luciferase reporter gene assay confirmed that tRF-23-Q99P9P9NDD could bind to the 3' untranslated region (UTR) site of acyl-coenzyme A dehydrogenase short/branched chain (ACADSB). In addition, ACADSB could rescue the effect of tRF-23-Q99P9P9NDD on GC cells. Next, we used Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) to find that downregulated ACADSB in GC may promote lipid accumulation by inhibiting fatty acid catabolism and ferroptosis. Finally, we verified the correlation between ACADSB and 12 ferroptosis genes at the transcriptional level, as well as the changes in reactive oxygen species (ROS) levels by flow cytometry. In summary, this study proposes that tRF-23-Q99P9P9NDD may affect GC lipid metabolism and ferroptosis by targeting ACADSB, thereby promoting GC progression. It provides a theoretical basis for the diagnostic and prognostic monitoring value of GC and opens up new possibilities for treatment.

Association and mediation analyses among multiple metal exposure, mineralocorticoid levels, and serum ion balance in residents of northwest China.

Toxic metals are vital risk factors affecting serum ion balance; however, the effect of their co-exposure on serum ions and the underlying mechanism remain unclear. We assessed the correlations of single metal and mixed metals with serum ion levels, and the mediating effects of mineralocorticoids by investigating toxic metal concentrations in the blood, as well as the levels of representative mineralocorticoids, such as deoxycorticosterone (DOC), and serum ions in 471 participants from the Dongdagou-Xinglong cohort. In the single-exposure model, sodium and chloride levels were positively correlated with arsenic, selenium, cadmium, and lead levels and negatively correlated with zinc levels, whereas potassium and iron levels and the anion gap were positively correlated with zinc levels and negatively correlated with selenium, cadmium and lead levels (all P < 0.05). Similar results were obtained in the mixed exposure models considering all metals, and the major contributions of cadmium, lead, arsenic, and selenium were highlighted. Significant dose-response relationships were detected between levels of serum DOC and toxic metals and serum ions. Mediation analysis showed that serum DOC partially mediated the relationship of metals (especially mixed metals) with serum iron and anion gap by 8.3% and 8.6%, respectively. These findings suggest that single and mixed metal exposure interferes with the homeostasis of serum mineralocorticoids, which is also related to altered serum ion levels. Furthermore, serum DOC may remarkably affect toxic metal-related serum ion disturbances, providing clues for further study of health risks associated with these toxic metals.

Corrigendum: Recent status and trends of nanotechnology in cervical cancer: a systematic review and bibliometric analysis.

[This corrects the article DOI: 10.3389/fonc.2024.1327851.].

Treatment Options for Hepatocellular Carcinoma Using Immunotherapy: Present and Future.

Hepatocellular carcinoma (HCC) is a common cancer, and the body's immune responses greatly affect its progression and the prognosis of patients. Immunological suppression and the maintenance of self-tolerance in the tumor microenvironment are essential responses, and these form part of the theoretical foundations of immunotherapy. In this review, we first discuss the tumor microenvironment of HCC, describe immunosuppression in HCC, and review the major biomarkers used to track HCC progression and response to treatment. We then examine antibody-based therapies, with a focus on immune checkpoint inhibitors (ICIs), monoclonal antibodies that target key proteins in the immune response (programmed cell death protein 1, anti-cytotoxic T-lymphocyte associated protein 4, and programmed death-ligand 1) which have transformed the treatment of HCC and other cancers. ICIs may be used alone or in conjunction with various targeted therapies for patients with advanced HCC who are receiving first-line treatments or subsequent treatments. We also discuss the use of different cellular immunotherapies, including T cell receptor (TCR) T cell therapy and chimeric antigen receptor (CAR) T cell therapy. We then review the use of HCC vaccines, adjuvant immunotherapy, and oncolytic virotherapy, and describe the goals of future research in the development of treatments for HCC.

Domino Michael/Oxa-Michael Reactions of the Unsymmetric Double Michael Acceptor for Access to Bicyclic Furo[2,3-b]pyrrole.

By creating an unsymmetric double Michael acceptor 1, we were able to synthesize the nonaromatic-fused bicyclic furo[2,3-b]pyrrole nucleus using a domino Michael/oxa-Michael reaction. Adopting benzoyl acetonitrile 2d (CN as the electron-withdrawing group) as a substrate, we discovered a (DHQ)2AQN-catalyzed method for high diastereo- and enantioselectivity of those products. The reaction path has been determined by isolating the reaction intermediates, and density functional theory calculations support these findings. Beyond providing a synthetic approach, this work illustrated the compounds' possible use in antitumor activity.

Identifying the predictive role and the related drugs of oxidative stress genes in the hepatocellular carcinoma.

BACKGROUND AND AIMS: Oncogenesis and tumor development have been related to oxidative stress (OS). The potential diagnostic utility of OS genes in hepatocellular carcinoma (HCC), however, remains uncertain. As a result, this work aimed to create a novel OS related-genes signature that could be used to predict the survival of HCC patients and to screen OS related-genes drugs that might be used for HCC treatment. METHODS: We used The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database to acquire mRNA expression profiles and clinical data for this research and the GeneCards database to obtain OS related-genes. Following that, biological functions from Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on differentially expressed OS-related genes (DEOSGs). Subsequently, the prognostic risk signature was constructed based on DEOSGs from the TCGA data that were screened by using univariate cox analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO) regression, and multivariate cox analysis. At the same time, we developed a prognostic nomogram of HCC patients based on risk signature and clinical-pathological characteristics. The GEO data was used for validation. We used the receiver operating characteristic (ROC) curve, calibration curves, and Kaplan-Meier (KM) survival curves to examine the prediction value of the risk signature and nomogram. Finally, we screened the differentially expressed OS genes related drugs. RESULTS: We were able to recognize 9 OS genes linked to HCC prognosis. In addition, the KM curve revealed a statistically significant difference in overall survival (OS) between the high-risk and low-risk groups. The area under the curve (AUC) shows the independent prognostic value of the risk signature model. Meanwhile, the ROC curves and calibration curves show the strong prognostic power of the nomogram. The top three drugs with negative ratings were ZM-336372, lestaurtinib, and flunisolide, all of which inversely regulate different OS gene expressions. CONCLUSION: Our findings indicate that OS related-genes have a favorable prognostic value for HCC, which sheds new light on the relationship between oxidative stress and HCC, and suggests potential therapeutic strategies for HCC patients.

Dual-mode detection of 2,6-pyridinedicarboxylic acid based on the enhanced peroxidase-like activity and fluorescence property of novel Eu-MOFs.

2,6-Pyridinedicarboxylic acid (DPA) is a significant biomarker of anthrax, which is a deadly infectious disease for human beings. However, the development of a convenient anthrax detection method is still a challenge. Herein, we report a novel europium metal-organic framework (Eu-MOF) with an enhanced peroxidase-like activity and fluorescence property for DPA detection. The Eu-MOF was one-step synthesized using Eu3+ ions and 2-methylimidazole. In the presence of DPA, the intrinsic fluorescence of Eu3+ ions is sensitized, the fluorescence intensity linearly increases with an increase in DPA concentration, and the fluorescence color changes from blue to purple. Simultaneously, the peroxide-like activity of the Eu-MOF is enhanced by DPA, which can promote the oxidation of TMB to oxTMB. The absorbance values increase linearly with DPA concentrations, and the colorimetric images change from colorless to blue. The dual-mode detection of DPA has good sensitivity with a colorimetric detection limit of 0.67 µM and a fluorescent detection limit of 16.67 nM. Moreover, a simple detection method for DPA was developed using a smartphone with the RGB analysis system. A portable kit with standard color cards was developed using paper test strips. The proposed methods have good practicability for DPA detection in real samples. In conclusion, the developed Eu-MOF biosensor offers a valuable and general platform for anthrax diagnosis.