Summary
Cepharanthine (CEP) is an active alkaloid isolated from Stephania Cepharantha Hayata. It is reported that the anti‐inflammatory properties of CEP could be employed to treat a variety of ...diseases. In this study, we first found that CEP ameliorates ulcerative colitis (UC) induced by DSS. The effect of CEP on gut microbiota was further evaluated by 16S rRNA gene sequencing, antibiotic pretreatment and faecal microbiota transplantation (FMT). Results showed that the abundances of gut microbiota, such as Romboutsia, Turicibacter and Escherichia‐Shigella (especially Romboutsia), were significantly reduced after CEP treatment. Additionally, we explored the mechanisms of CEP by a strategy integrating transcriptomics with network pharmacology. The transcriptome data confirmed that CEP functioned through cytokine and cytokine receptor pathways. The expression levels of 10 pro‐inflammatory hub genes (such as CXCL1, CXCL9, CCL7) were positively correlated with the abundance of Romboutsia. Our data identified Romboutsia as a potential pathobiont in UC. Collectively, we confirmed that CEP relieved colon inflammation by modulating gut microbiota and pro‐inflammatory cytokine expression. CEP can be adopted to design novel effective therapeutic strategies for UC.
We confirmed that Cepharanthine relieved colon inflammation by modulating gut microbiota and pro‐inflammatory cytokine expression. Cepharanthine can be adopted to design novel effective therapeutic strategies for UC.
This article aims to explore the underlying molecular mechanisms and prognosis‐related genes in pancreatic cancer metastasis. Pancreatic cancer metastasis‐related gene chip data were downloaded from ...GENE EXPRESSION OMNIBUS(GEO)database. Differentially expressed genes were screened after R‐package pre‐treatment. Functional annotations and related signalling pathways were analysed using DAVID software. GEPIA (Gene Expression Profiling Interactive Analysis) was used to perform prognostic analysis, and differential genes associated with prognosis were screened and validated using data from GEO. We screened 40 healthy patients, 40 primary pancreatic cancer and 40 metastatic pancreatic cancer patients, collected serum, designed primers and used qPCR to test the expression of prognosis‐related genes in each group. 109 differentially expressed genes related with pancreatic cancer metastasis were screened, of which 49 were up‐regulated and 60 were down‐regulated. Functional annotation and pathway analysis revealed differentially expressed genes were mainly concentrated in protein activation cascade, extracellular matrix construction, decomposition, etc In the biological process, it is mainly involved in signalling pathways such as PPAR, PI3K‐Akt and ECM receptor interaction. Prognostic analysis showed the expression levels of four genes were significantly correlated with the overall survival time of patients with pancreatic cancer, namely SCG5, CRYBA2, CPE and CHGB. qPCR experiments showed the expression of these four genes was decreased in both the primary pancreatic cancer group and the metastatic pancreatic cancer group, and the latter was more significantly reduced. Pancreatic cancer metastasis is closely related to the activation of PPAR pathway, PI3K‐Akt pathway and ECM receptor interaction. SCG5, CRYBA2, CPE and CHGB genes are associated with the prognosis of pancreatic cancer, and their low expression suggests a poor prognosis.
Objectives. To investigate the protective effect of ginsenoside Rg1 on relieving sepsis-induced lung inflammation and injury in vivo and in vitro. Methods. Cultured human pulmonary epithelial cell ...line A549 was challenged with LPS to induce cell injury, and CLP mouse model was generated to mimic clinical condition of systemic sepsis. Rg1 was applied to cells or animals at indicated dosage. Apoptosis of cultured cells was quantified by flow cytometry, along with ELISA for inflammatory cytokines in supernatant. For septic mice, lung tissue pathology was examined, plus ELISA assay for serum cytokines. Western blotting was used to examine the activation of inflammatory pathways and ER stress marker proteins in both cells and mouse lung tissues. Reactive oxygen species (ROS) level was quantified by DCFDA kit. Results. Ginsenoside Rg1 treatment remarkably suppressed apoptosis rate of LPS-induced A549 cells, relieved mouse lung tissue damage, and elevated survival rate. Rg1 treatment also rescued cells from LPS-induced intracellular ROS. In both A549 cells and mouse lung tissues, further study showed that Rg1 perfusion significantly suppressed the secretion of inflammatory cytokines including tumor necrosis factor- (TNF-) alpha and interleukin- (IL-) 6 and relieved cells from ER stress as supported by decreased expression of marker proteins via upregulating sirtuin 1 (SIRT1). Conclusion. Our results showed that ginsenoside Rg1 treatment effectively relieved sepsis-induced lung injury in vitro and in vivo, mainly via upregulating SIRT1 to relieve ER stress and inflammation. These findings provide new insights for unrevealing potential candidate for severe sepsis accompanied with lung injury.
In recent decades, with the continuous development of high‐throughput sequencing technology, data volume in medical research has increased, at the same time, almost all clinical researchers have ...their own independent omics data, which provided a better condition for data mining and a deeper understanding of gene functions. However, for these large amounts of data, many common and cutting‐edge effective bioinformatics research methods still cannot be widely used. This has encouraged the establishment of many analytical platforms, a portion of databases or platforms were designed to solve the special analysis needs of users, for instance, MG RAST, IMG/M, Qiita, BIGSdb, and TRAPR were developed for specific omics research, and some databases or servers provide solutions for special problems solutions. Metascape was designed to only provide functional annotations of genes as well as function enrichment analysis; BioNumerics and RidomSeqSphere+ perform multilocus sequence typing; CARD provides only antimicrobial resistance annotations. Additionally, some web services are outdated, and inefficient interaction often fails to meet the needs of researchers, such as our previous versions of the platform. Therefore, the demand to complete massive data processing tasks urgently requires a comprehensive bioinformatics analysis platform. Hence, we have developed a website platform, Sangerbox 3.0 (http://vip.sangerbox.com/), a web‐based tool platform. On a user‐friendly interface that also supports differential analysis, the platform provides interactive customizable analysis tools, including various kinds of correlation analyses, pathway enrichment analysis, weighted correlation network analysis, and other common tools and functions, users only need to upload their own corresponding data into Sangerbox 3.0, select required parameters, submit, and wait for the results after the task has been completed. We have also established a new interactive plotting system that allows users to adjust the parameters in the image; moreover, optimized plotting performance enables users to adjust large‐capacity vector maps on the web site. At the same time, we have integrated GEO, TCGA, ICGC, and other databases and processed data in batches, greatly reducing the difficulty to obtain data and improving the efficiency of bioimformatics study for users. Finally, we also provide users with rich sources of bioinformatics analysis courses, offering a platform for researchers to share and exchange knowledge.
Sangerbox with a user‐friendly interface supports differential analysis, correlation analyses, pathway enrichment analysis, weighted correlation network analysis, and so on. A new interactive plotting system that allows users to adjust the parameters in the image. It has organized GEO, TCGA, ICGC, and other databases; a rapid batch processing reduces the difficulty in data acquirement, greatly improving the efficiency.
Heavy concrete shielding properties for carbon therapy Wang, Jin-Long; Lu, Jiade J; Ding, Da-Jun ...
Nuclear engineering and technology,
June 2023, 2023-06-00, 2023-06-01, 2023-06, Letnik:
55, Številka:
6
Journal Article
Recenzirano
Odprti dostop
As medical facilities are usually built at urban areas, special concrete aggregates and evaluation methods are needed to optimize the design of concrete walls by balancing density, thickness, ...material composition, cost, and other factors. Carbon treatment rooms require a high radiation shielding requirement, as the neutron yield from carbon therapy is much higher than the neutron yield of protons. In this case study, the maximum carbon energy is 430 MeV/u and the maximum current is 0.27 nA from a hybrid particle therapy system. Hospital or facility construction should consider this requirement to design a special heavy concrete. In this work, magnetite is adopted as the major aggregate. Density is determined mainly by the major aggregate content of magnetite, and a heavy concrete test block was constructed for structural tests. The compressive strength is 35.7 MPa. The density ranges from 3.65 g/cm3 to 4.14 g/cm3, and the iron mass content ranges from 53.78% to 60.38% from the 12 cored sample measurements. It was found that there is a linear relationship between density and iron content, and mixing impurities should be the major reason leading to the nonuniform element and density distribution. The effect of this nonuniformity on radiation shielding properties for a carbon treatment room is investigated by three groups of Monte Carlo simulations. Higher density dominates to reduce shielding thickness. However, a higher content of high-Z elements will weaken the shielding strength, especially at a lower dose rate threshold and vice versa. The weakened side effect of a high iron content on the shielding property is obvious at 2.5 μSv/h. Therefore, we should not blindly pursue high Z content in engineering. If the thickness is constrained to 2 m, then the density can be reduced to 3.3 g/cm3, which will save cost by reducing the magnetite composition with 50.44% iron content. If a higher density of 3.9 g/cm3 with 57.65% iron content is selected for construction, then the thickness of the wall can be reduced to 174.2 cm, which will save space for equipment installation.
Lactobacillus plantarum (LP) has been shown to exhibit protective effects on intestinal barrier function in septic rats, although the regulatory mechanism has not been established. We determined ...whether LP imparts such protective effects in a lipopolysaccharide (LPS)-induced Caco2 cell monolayer model and whether cAMP-PKA signaling is the underlying mechanism of action. The cyclic adenosine monophosphate (cAMP) agonist, forskolin (FSK), and the protein kinase A (PKA) inhibitor, HT89, were used to study the protective effect of LP on the destruction of the tight junction (TJ) structure of cells treated with LPS and the corresponding changes in cAMP-PKA signaling. Our experimental results demonstrated that LP promoted the expression of TJ proteins between Caco2 cells after LPS treatment, and increased the electrical barrier detection (TEER) between Caco2 cells. Moreover, transmission electron microscopy (TEM) revealed that the TJ structural integrity of cells treated with LPS + LP was improved compared to cells treated with LPS alone. In addition, our findings were consistent between the FSK and LP intervention group, while HT89 inhibited LP influence. Taken together, our results indicate that LP has an improved protective effect on LPS-induced damage to the monolayer membrane barrier function of Caco2 cells and is regulated by the cAMP-PKA pathway.
Our previous studies found that disturbances in gut microbiota might have a causative role in the onset of major depressive disorder (MDD). The aim of this study was to investigate whether there were ...sex differences in gut microbiota in patients with MDD.
First-episode drug-naïve MDD patients and healthy controls were included. 16S rRNA gene sequences extracted from the fecal samples of the included subjects were analyzed. Principal-coordinate analysis and partial least squares-discriminant analysis were used to assess whether there were sex-specific gut microbiota. A random forest algorithm was used to identify the differential operational taxonomic units. Linear discriminant-analysis effect size was further used to identify the dominant sex-specific phylotypes responsible for the differences between MDD patients and healthy controls.
In total, 57 and 74 differential operational taxonomic units responsible for separating female and male MDD patients from their healthy counterparts were identified. Compared with their healthy counterparts, increased Actinobacteria and decreased Bacteroidetes levels were found in female and male MDD patients, respectively. The most differentially abundant bacterial taxa in female and male MDD patients belonged to phyla Actinobacteria and Bacteroidia, respectively. Meanwhile, female and male MDD patients had different dominant phylotypes.
These results demonstrated that there were sex differences in gut microbiota in patients with MDD. The suitability of Actinobacteria and Bacteroidia as the sex-specific biomarkers for diagnosing MDD should be further explored.
Cepharanthine (CEP), a bisbenzylisoquinoline alkaloid from tubers of Stephania, protects against some inflammatory diseases. Aconitate decarboxylase 1 (ACOD1) is also known as immune-responsive gene ...1 (IRG1), which plays an important immunometabolism role in inflammatory diseases by mediating the production of itaconic acid. ACOD1 exhibits abnormal expression in ulcerative colitis (UC). However, whether CEP can combat UC by affecting ACOD1 expression remains unanswered. This study was designed to explore the protective effects and mechanisms of CEP in treating colitis through in vitro and in vivo experiments. In vitro assays indicated that CEP inhibited LPS-induced secretion of pro-inflammatory cytokines and ACOD1 expression in RAW264.7 macrophages. Additionally, in the mouse model of DSS-induced colitis, CEP decreased macrophage infiltration and ACOD1 expression in colon tissue. After treatment with antibiotics (Abx), the expression of ACOD1 changed with the composition of gut microbiota. Correlation analysis also revealed that Family-XIII-AD3011-group and Rumini-clostridium-6 were positively correlated with ACOD1 expression level. Additionally, data of the integrative Human Microbiome Project (iHMP) showed that ACOD1 was highly expressed in the colon tissue of UC patients and this expression was positively correlated with the severity of intestinal inflammation. Collectively, CEP can counter UC by modulating gut microbiota and inhibiting the expression of ACOD1. CEP may serve as a potential pharmaceutical candidate in the treatment of UC.
Background
Ovarian clear cell carcinoma (OCCC) represents a subtype of ovarian epithelial carcinoma (OEC) known for its limited responsiveness to chemotherapy, and the onset of distant metastasis ...significantly impacts patient prognoses. This study aimed to identify potential risk factors contributing to the occurrence of distant metastasis in OCCC.
Methods
Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, we identified patients diagnosed with OCCC between 2004 and 2015. The most influential factors were selected through the application of Gaussian Naive Bayes (GNB) and Adaboost machine learning algorithms, employing a Venn test for further refinement. Subsequently, six machine learning (ML) techniques, namely XGBoost, LightGBM, Random Forest (RF), Adaptive Boosting (Adaboost), Support Vector Machine (SVM), and Multilayer Perceptron (MLP), were employed to construct predictive models for distant metastasis. Shapley Additive Interpretation (SHAP) analysis facilitated a visual interpretation for individual patient. Model validity was assessed using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and the area under the receiver operating characteristic curve (AUC).
Results
In the realm of predicting distant metastasis, the Random Forest (RF) model outperformed the other five machine learning algorithms. The RF model demonstrated accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and AUC (95% CI) values of 0.792 (0.762–0.823), 0.904 (0.835–0.973), 0.759 (0.731–0.787), 0.221 (0.186–0.256), 0.974 (0.967–0.982), 0.353 (0.306–0.399), and 0.834 (0.696–0.967), respectively, surpassing the performance of other models. Additionally, the calibration curve's Brier Score (95%) for the RF model reached the minimum value of 0.06256 (0.05753–0.06759). SHAP analysis provided independent explanations, reaffirming the critical clinical factors associated with the risk of metastasis in OCCC patients.
Conclusions
This study successfully established a precise predictive model for OCCC patient metastasis using machine learning techniques, offering valuable support to clinicians in making informed clinical decisions.
Wheat Qu contains various microorganisms and is the fermentation starter for rice wine. The impact of geographic location on the volatile compounds and microbial communities in wheat Qu remains ...unknown. This study demonstrated significant differences in the volatile compound profiles of wheat Qu from different regions of China. Phenylethyl alcohol, hexadecanoic acid methyl ester, 9-octadecenoic acid methyl ester, and 2-octanone were the main volatile compounds detected. The bacterial and fungal communities in wheat Qu also differed significantly according to geographic location with both communities explaining the variation in volatile compounds (bacteria making the greater contribution). The bacterial community was dominated by Pediococcus, Weissella, and Lactobacillus while the fungal community was dominated by Saccharomycopsis and Rhizopus. Bacteria exhibited more significant associations with volatile compounds than fungi did. Prediction of metabolic function demonstrated significantly different profiles for the bacterial communities from different regions. These data showed that geographic location considerably affects the composition of volatile compounds and microbial communities in wheat Qu, with the bacterial community being the main contributor to variation of volatile compounds.
•Impact of geographic locations on microbiota and volatiles in wheat Qu was studied.•Bacterial community mainly contributed to the variance of volatiles compounds.•LAB, Saccharomycopsis and Rhizopus were the dominant microorganisms in wheat Qu.•Bacterial functions within wheat Qu varied according to geographic locations.
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