ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

The chemical constituents from the n-butanol fraction of ethanol extract of safflower (Carthamus tinctorius L.) were isolated and purified using chromatographic process including MCI Gel CHP-20, ODS, Sephadex LH-20 column chromatography, and semi-preparative HPLC method, and one alkyne and two phenylpropanoid derivants were obtained. Their structures were identified as (5R,E)-tetradecane-12-ene-8,10-diyne-1,5,14-triol (1), (E)-8-O-β-D-glucopyranosyl n-butyl cinnamate (2), and (7S,8S)-7-(4-hydroxy-3-methoxybenzene)-7-butyl-8,9-diol (3) by modern spectroscopy methods (1D NMR, 2D NMR, UV, IR and MS). 1-3 are all new compounds. Compounds 1-3 were screened for their anti-renal fibrosis activities in vitro, and none of them showed obvious effect.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

This study aimed to investigate the effect of Dahuang Zhechong Pills(DHZCP) in delaying heart aging(HA) and explore the potential mechanism. Network pharmacology and molecular docking were employed to explore the targets and potential mechanisms of DHZCP in delaying HA. Furthermore, in vitro experiments were conducted with the DHZCP-containing serum to verify key targets and pathways in D-galactose(D-gal)-induced aging of cardiomyocytes. Active components of DHZCP were searched against the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCSMP), and relevant targets were predicted. HA-related targets were screened from the GeneCards, Online Mendelian Inheritance in Man(OMIM), and DisGeNET. The common targets shared by the active components of DHZCP and HA were used to construct a protein-protein interaction network in STRING 12.0, and core targets were screened based on degree in Cytoscape 3.9.1. Metaspace was used for Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analyses of the core targets to predict the mechanisms. Molecular docking was performed in AutoDock Vina. The results indicated that a total of 774 targets of the active components of DHZCP and 4 520 targets related to HA were screened out, including 510 common targets. Core targets included B-cell lymphoma 2(BCL-2), serine/threonine kinase 1(AKT1), and hypoxia-inducible factor 1 subunit A(HIF1A). The GO and KEGG enrichment analyses suggested that DHZCP mainly exerted its effects via the phosphatidylinositol 3-kinase(PI3K)/AKT signaling pathway, HIF-1α signaling pathway, longevity signaling pathway, and apoptosis signaling pathway. Among the pathways predicted by GO and KEGG enrichment analyses, the PI3K/AKT/HIF-1α signaling pathway was selected for verification. The cell-counting kit 8(CCK-8) assay showed that D-gal significantly inhibited the proliferation of H9c2 cells, while DHZCP-containing serum increased the viability of H9c2 cells. SA-β-gal staining revealed a significant increase in the number of blue-green positive cells in the D-gal group, which was reduced by DHZCP-containing serum. TUNEL staining showed that DHZCP-containing serum decreased the number of apoptotic cells. After treatment with DHZCP-containing serum, the protein levels of Klotho, BCL-2, p-PI3K/PI3K, p-AKT1/AKT1, and HIF-1α were up-regulated, while those of P21, P16, BCL-2 associated X protein(Bax), and cleaved caspase-3 were down-regulated. The results indicated that DHZCP delayed HA via multiple components, targets, and pathways. Specifically, DHZCP may delay HA by reducing apoptosis via activating the PI3K/AKT/HIF-1α signaling pathway.
Proto-Oncogene Proteins c-akt/genetics* ; Drugs, Chinese Herbal/pharmacology* ; Signal Transduction/drug effects* ; Apoptosis/drug effects* ; Myocytes, Cardiac/cytology* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Phosphatidylinositol 3-Kinases/genetics* ; Animals ; Rats ; Humans ; Molecular Docking Simulation ; Aging/metabolism* ; Protein Interaction Maps/drug effects* ; Heart/drug effects* ; Network Pharmacology

In order to compare the differences in growth and secondary metabolite accumulation of Panax quinquefolius between understory and field planting, growth indexes, photosynthetic characteristics, soil enzyme activities, secondary metabolite contents, and antioxidant activities of P. quinquefolius under different planting modes were examined and compared, and One-way analysis of variance(ANOVA) and correlation analyses were carried out by using the software SPSS 25.0 and GraphPad Prism 9.5. The Origin 2021 software was used for plotting. The results showed that compared with those under field planting, the plant height, leaf length, leaf width, photosynthetic rate, and chlorophyll content of P. quinquefolius under understory planting were significantly reduced, and arbuscular mycorrhizal fungi(AMF) infestation rate and infestation intensity, ginsenoside content, and antioxidant activity were significantly increased. The activities of inter-root soil urease, sucrase, and catalase increased, while the activities of non-inter-root soil urease and alkaline phosphatase increased. Correlation analyses showed that the plant height and leaf length of P. quinquefolius plant were significantly positively correlated with net photosynthetic rate, transpiration rate, chlorophyll content, and electron transfer rate(P<0.05), while ginsenoside content was significantly negatively correlated with net photosynthetic rate, chlorophyll content, and electron transfer rate(P<0.05) and significantly positively correlated with AMF infestation rate and infestation intensity(P<0.05). In addition, ginsenoside content was significantly positively correlated with the activities of inter-root soil sucrase, urease, and catalase(P<0.05). This study provides basic data for revealing the mechanism of secondary metabolite accumulation in P. quinquefolius under understory planting and for exploring and practicing the ecological mode of P. quinquefolius under understory planting.
Panax/microbiology* ; China ; Secondary Metabolism ; Soil/chemistry* ; Photosynthesis ; Plant Leaves/metabolism* ; Chlorophyll/metabolism* ; Mycorrhizae