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Objective To investigate the association between clinical features and survival in distant metastatic endometrial carcinoma (EC) patients, and to construct a prognostic risk model to guide the clinical practice. Methods The clinical data of EC patients with distant metastases were retrospectively collected from the SEER database between 2010 and 2017. Univariate and multivariate Cox regression analyses were applied to determine the independent prognostic factors of metastatic EC patients, and then a nomogram model was constructed based on these predictive factors. The predictive performance of the model was evaluated and internally validated using C-index, receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA). In addition, the model was externally validated using the data collected from the EC patients with distant metastases admitted to the First Affiliated Hospital of Chongqing Medical University between October 2013 and December 2019. Results A total of 1 807 EC patients with distant metastases who met the inclusion and exclusion criteria in the SEER database were enrolled in this study. Multivariate Cox analysis revealed that tumor size, grade, and histological type were independent risk factors for distant metastatic EC; and race, surgery, and chemotherapy were independent protective factors for metastatic distant EC. In the training cohort, the C-index of the constructed nomogram model was 0.711 (95%CI: 0.695~0.727); in the internal validation cohort, the C-index of the model was 0.744 (95%CI: 0.721~0.768); ROC curve analysis indicated that the model had good prediction and discrimination; calibration curve showed that there was a high consistency between the predicted survival probability and the actual survival probability; meanwhile, the results of DCA curves revealed that the model had great potential for clinical utility. Furthermore, based on the 21 EC patients with distant metastases included as an external validation dataset, the results showed that the model had good predictive ability. Conclusion A survival prediction model for distant metastatic EC is established, and it can assist clinicians in evaluating the prognosis of patients and performing personalized clinical decisions for this specific population.

The non-volatile compounds in a compound Lujiu (38%vol) was detected by high-performance liquid chromatography quadrupole time-of- flight tandem mass spectrometry (HPLC-Q-TOF-MS/MS). The compound Lujiu was intragastric administered to mice for 22 d to investigate its effect on weight-bearing swimming and evaluate its anti-fatigue health benefits. The results showed that a total of 52 non-volatile substances were identified from the compound Lujiu (0.225 7 g crude drug/ml), including 24 saponins, 6 flavonoids, 4 nucleosides, 4 amino acids, 3 alkaloids, and 11 others. Compared with the model group, the body weight reduction of mice in the low, medium and high dose groups was significantly reduced (P

Background: Surgery is the best approach to treat endometrial cancer (EC); however, there is currently a deficiency in effective scoring systems for predicting EC recurrence post-surgical resection. This study aims to develop a clinicopathological-inflammatory parameters-based nomogram to accurately predict the postoperative recurrence-free survival (RFS) rate of EC patients. Methods: A training set containing 1068 patients and an independent validation set consisting of 537 patients were employed in this retrospective study. The prognostic factors for RFS were identified by univariable and multivariable Cox proportional hazards regression analyses, and integrated into nomogram. The C-index, area under the curves (AUC), and calibration curves were employed to determine the predictive discriminability and accuracy of nomogram. Utilizing the nomogram, patients were stratified into low- and high-risk groups, and the Kaplan-Meier survival curve was further employed to assess the clinical efficacy of the model. Results: Cox regression analyses revealed that age (HR = 1.769, P = 0.002), FIGO staging (HR = 1.790, P = 0.018), LVSI (HR = 1.654, P = 0.017), Ca125 (HR = 1.532, P = 0.023), myometrial invasion (HR = 1.865, P = 0.001), cervical stromal invasion (HR = 1.655, P = 0.033), histology (HR = 2.637, P < 0.001), p53 expression (HR = 1.706, P = 0.002), PLR (HR = 1.971, P = 0.003), SIRI (HR = 2.187, P = 0.003), and adjuvant treatment (HR = 0.521, P = 0.003) were independent prognostic factors for RFS in patients with EC. A combined clinicopathologic-inflammatory parameters model was constructed, which outperformed the single-indicator model and other established models in predicting the 1-, 3-, and 5-year RFS rates in patients with EC. Conclusion: The nomogram demonstrated sufficient accuracy in predicting the RFS probabilities of EC, enabling personalized clinical decision-making for future clinical endeavors. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the prognosis value of the clinical parameters and immunohistochemical markers of patients with early-onset endometrial cancer (EC) and establish a nomogram to accurately predict recurrence-free survival (RFS) of early-onset EC after resection. Methods: A training dataset containing 458 patients and an independent testing dataset consisting of 170 patients were employed in this retrospective study. The independent risk factors related to RFS were confirmed using Cox regression models. A nomogram model was established to predict RFS at 3 and 5 years post-hysterectomy. The C-index, area under the curve (AUC) of the receiver operating characteristic (ROC) curve, and calibration curve were calculated to assess the predictive accuracy of the nomogram. Results: In all early-onset EC patients, more than half (368/628, 58.6%) were diagnosed in the age range of 45-49 years. Meanwhile, the recurrence rate of early-onset EC is approximately 10.8%. Multivariate Cox regression analyses showed that histological subtype, FIGO stage, myometrial invasion, lymphovascular space invasion (LVSI), P53 expression, and MMR status were independent prognostic factors related to RFS (all P < 0.05) and established the nomogram predicting 3- and 5-year RFS. The C-index and calibration curves of the nomogram demonstrated a close correlation between predicted and actual RFS. Patients were divided into high- and low-risk groups according to the model of RFS. Conclusions: Combining clinical parameters and immunohistochemical markers, we developed a robust nomogram to predict RFS after surgery for early-onset EC patients. This nomogram can predict prognosis well and guide treatment decisions. [ABSTRACT FROM AUTHOR]

Eupatorium lindleyanum DC. (EL) is a traditional Chinese herb known for its phlegm-reducing, cough-relieving and asthma-calming properties. It is widely used for treating cough and bronchitis. However, preliminary experiments have revealed wide variations in the composition of its different medicinal parts (flowers, leaves and stems), and the composition and efficacy of its different medicinal parts remain largely underexplored at present. In this study, non-targeted rapid resolution liquid chromatography coupled with a quadruple time-of-flight mass spectrometry (RRLC-Q-TOF-MS)-based metabolomics approach was developed to investigate the differences in the chemical composition of different medicinal parts of EL. We identified or tentatively identified 9 alkaloids, 11 flavonoids, 14 sesquiterpene lactones, 3 diterpenoids and 24 phenolic acids. In addition, heatmap visualization, quantitative analysis by high-performance liquid chromatography (HPLC-PDA) and ultra-high-performance liquid chromatography–triple quadrupole tandem mass spectrometry (UPLC-MS/MS) showed particularly high levels of sesquiterpene lactones, flavonoids and phenolic acids in the flowers, such as eupalinolide A and B and chlorogenic acid, among others. The leaves also contained some flavonoid sesquiterpene lactones and phenolic acids, while the stems were almost absent. The findings of in vitro activity studies indicated that the flowers exhibited a notable inhibitory effect on the release of the inflammatory factors TNF-α and IL-6, surpassing the anti-inflammatory efficacy observed in the leaves. Conversely, the stems demonstrated negligible anti-inflammatory activity. The variations in anti-inflammatory activity among the flowers, leaves and stems of EL can primarily be attributed to the presence of flavonoids, phenolic acids and sesquiterpene lactones in both the flowers and leaves. Additionally, the flowers contain a higher concentration of these active components compared to the leaves. These compounds mediate their anti-inflammatory effects through distinct biochemical pathways. The results of this study are anticipated to provide a scientific basis for the rational and effective utilization of EL resources. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the metastatic pattern, identify the risk factors, and establish a nomogram for predicting prognosis of endometrial cancer (EC) with distant metastasis. Methods: A retrospective cohort study of women diagnosed with EC was conducted according to the Surveillance, Epidemiology, and End Results (SEER) database during 2010–2017. Multivariate logistic analysis and Cox analysis were performed to identify the risk factors in promoting distant metastasis and predictors associated with overall survival (OS) in this particular subpopulation. A nomogram was then constructed and validated by the concordance index (C‐index), the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis. Results: A total of 2799 cases of distant metastasis in EC patients were identified, with an overall incidence rate of 3.74% from 2010 to 2017. Black race, unmarried status, non‐endometrioid histologic types, and grade IV were significant risk factors for distant metastasis in EC patients. Meanwhile, race, histology, grade, metastasis status, surgery, lymphadenectomy, and chemotherapy were identified as independent prognostic factors for OS. A nomogram to predict 1‐, 3‐, and 5‐year OS was established, and presented favorable accuracy and clinical applicability. Patients were further divided into high‐ and low‐risk groups according to the model. Conclusion: The nomogram was developed as a highly accurate, individualized tool to better predict the prognosis of EC patients with distant metastasis, which would help clinicians to identify high‐risk patients, and adjust and tailor their treatment strategies. Synopsis: Surveillance, Epidemiology, and End Results (SEER) analysis of metastatic endometrial cancer. [ABSTRACT FROM AUTHOR]

In this study, an immunocompromised rat model was established by long-term diet control and excessive swimming and treated with extracts of raw licorice (RL) and honey-roasted licorice (HL) to explore the immunomodulatory efficacy and gut microbiota composition with their metabolites. Pharmacological experiment confirmed that honey-roasting enhanced the ability of RL to regulate inflammatory cytokines and gut mucosal-layer homeostasis. The analysis of 16S rRNA sequences showed that both RL and HL regulated the balance of gut microbiota, but HL exhibited better effects than RL in regulating microbiota closely related to inflammatory cytokines (Coriobacteriaceae_UCG-002) as well as short-chain fatty acids-producing bacteria (Dubosiella and Ruminococcus). Moreover, HL improved the contents of butyrate and isobutyrate in feces more significantly than RL. In conclusion, the balance of gut microbiota and short-chain fatty acids might be one of the pathways that honey-roasting improve the immunomodulatory efficacy of licorice. Abbreviations: ANOVA: analysis of variance; BCA: bicinchoninic acid; ELISA: enzyme-linked immunosorbent assay; HRP: horseradish peroxidase; LDA: the linear discriminant analysis; LEfSe: the linear discriminant analysis effect size; MS: mass spectrometry; OTU: operational taxonomic units; PBS: phosphate buffered saline; PCoA: principal coordinate analysis; PVDF: polyvinylidene fluoride; RIPA: radio immunoprecipitation assay; SCFAs: short-chain fatty acids; [ABSTRACT FROM AUTHOR]