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Sishen pill (SSP) is an old Chinese medicine used to treat colitis with spleen-kidney-yang deficiency (SKYD) syndromes. However, its exact mechanism of action has not yet been fully elucidated. The aim of this study was to evaluate the effects and potential mechanisms of SSP on colitis with SKYD syndromes in mice. Colitis with SKYD syndromes was induced by rhubarb, hydrocortisone, and dextran sulfate sodium (DSS), and treatment was provided with SSP. Flow cytometry was performed to examine the inflammatory dendritic cell (infDC) regulations of SSP. The changes in the gut microbiota (GM) and fecal metabolites post-SSP treatment were investigated using the combination of 16S rRNA sequencing and untargeted metabolomics. Additionally, we also examined whether SSPs could regulate the infDCs by modifying TLR4/NF-κB signaling pathways. Compared with the DSS group, the disease activity index, colonic weight, index of colonic weight, and colonic injury scores, as well as the levels of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, and IL-12p70 decreased significantly in the DSS + SSP group, while free triiodothyronine (FT3), free tetraiodothyronine (FT4), testosterone (TESTO), body weight change, colonic length, and the levels of IL-10 increased. Also, SSP decreased the amounts of CD103+CD11c+iNOS+, CD103+CD11c+TNF-α+, CD11c+CD103+CD324+, CD103+CD11c+MHC-II+, and CD103+CD11c+CD115+. Interestingly, 16S rRNA sequencing and untargeted metabolomics showed that SSP treatment restored the dysbiosis of GM and improved the dysfunction in fecal metabolism in colitis mice with SKYD syndromes. Correlation analysis indicated that the modulatory effects of SSP on FT3, FT4, IL-10, colonic weight index, CD103+CD11c+TNF-α+, CD103+CD11c+MHC-II+, and 13 common differential metabolites were related to alterations in the abundance of Parvibacter, Aerococcus, norank_f_Lachnospiraceae, Lachnospiraceae_UCG-006, Akkermansia, and Rhodococcus in the GM. In addition, SSP markedly inhibited the activation of the TLR4, MyD88, TRAF6, TAB2, and NF-κBp65 proteins and activated IκB. These results indicate that SSP can effectively alleviate colitis mice with SKYD syndrome by regulating infDCs, GM, fecal metabolites, and TLR4/NF-κB signaling pathways. [ABSTRACT FROM AUTHOR]

Simple Summary: The objective response rate of lenvatinib combined with transarterial chemoembolization for unresectable hepatocellular carcinoma is unsatisfactory. We aimed to develop predictive models using demographic characteristics, pre-treatment serum biomarkers and tumor characteristics of unresectable hepatocellular carcinoma patients by five machine learning algorithms to predict the response under combined treatments. We identified the 10 most important predictors, including K, low-density lipoprotein, D-dimer, red blood cell, alanine aminotransferase, albumin, monocyte, tumor size, triglyceride, and age. In addition, we applied the Shapley Additive exPlanation to explain the best-performing random forest predictive model to provide a reasonable explanation of the efficacy prediction at an individualized level. The combination of machine learning and Shapley Additive exPlanation can provide valuable suggestions for clinical decision making. Background: Lenvatinib and transarterial chemoembolization (TACE) are first-line treatments for unresectable hepatocellular carcinoma (HCC), but the objective response rate (ORR) is not satisfactory. We aimed to predict the response to lenvatinib combined with TACE before treatment for unresectable HCC using machine learning (ML) algorithms based on clinical data. Methods: Patients with unresectable HCC receiving the combination therapy of lenvatinib combined with TACE from two medical centers were retrospectively collected from January 2020 to December 2021. The response to the combination therapy was evaluated over the following 4–12 weeks. Five types of ML algorithms were applied to develop the predictive models, including classification and regression tree (CART), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM). The performance of the models was assessed by the receiver operating characteristic (ROC) curve and area under the receiver operating characteristic curve (AUC). The Shapley Additive exPlanation (SHAP) method was applied to explain the model. Results: A total of 125 unresectable HCC patients were included in the analysis after the inclusion and exclusion criteria, among which 42 (33.6%) patients showed progression disease (PD), 49 (39.2%) showed stable disease (SD), and 34 (27.2%) achieved partial response (PR). The nonresponse group (PD + SD) included 91 patients, while the response group (PR) included 34 patients. The top 40 most important features from all 64 clinical features were selected using the recursive feature elimination (RFE) algorithm to develop the predictive models. The predictive power was satisfactory, with AUCs of 0.74 to 0.91. The SVM model and RF model showed the highest accuracy (86.5%), and the RF model showed the largest AUC (0.91, 95% confidence interval (CI): 0.61–0.95). The SHAP summary plot and decision plot illustrated the impact of the top 40 features on the efficacy of the combination therapy, and the SHAP force plot successfully predicted the efficacy at the individualized level. Conclusions: A new predictive model based on clinical data was developed using ML algorithms, which showed favorable performance in predicting the response to lenvatinib combined with TACE for unresectable HCC. Combining ML with SHAP could provide an explicit explanation of the efficacy prediction. [ABSTRACT FROM AUTHOR]

Background: Recent study showed that individuals with type 2 diabetes have a high risk of developing colorectal cancer (CRC), in which Receptor for Advanced Glycation End Products (RAGE) plays a pivotal role. We conducted a cross-sectional study to examine the relationships of circulating sRAGE, CRC and other clinical factors in type2 diabetes patients. Methods: A total of 150 type 2 diabetes patients aged 50 years and older were enrolled, including 50 patients with CRC and 100 patients without CRC. We measured Serum levels of sRAGE and interleukin-6(IL-6) using an enzyme-linked immunosorbent assay (ELISA). In addition, other clinical parameters were also measured during hospitalization. Results: Type 2 diabetes patients with CRC had higher triglyceride, total cholesterol, IL-6, and circulating sRAGE levels and lower use of medicines than type 2 diabetes patients without CRC. Circulating sRAGE was associated with an increased risk for CRC (OR = 2.289 for each SD increase in sRAGE, 95% CI = 1.037–5.051; P = 0.04) among Type 2 diabetes patients after adjustment for confounders. Furthermore, circulating sRAGE levels among type 2 diabetes patients were positively correlated with triglyceride (r = 0.377, P < 0.001), total cholesterol (r = 0.491, P < 0.001), and low-density lipoprotein cholesterol (LDL-c)(r = 0.330, P < 0.001) levels; the homeostatic model assessment for insulin resistance(HOMA-IR)score (r = 0.194, P = 0.017); and fasting serum insulin (r = 0.167, P = 0.041) and IL-6 (r = 0.311, P < 0.001) concentrations. Conclusions: Our results suggested that circulating sRAGE is independently risk factor for CRC, and also closely related to inflammation, dyslipidemia in type 2 diabetes patients. [ABSTRACT FROM AUTHOR]

Background Greek migrants to Australia have low all-cause and cardiovascular disease (CVD) mortality. This may be partly due to maintenance of a traditional Mediterranean diet and its interaction with CVD risk factors. The enzyme paraoxonase-1 (PON1) is thought to contribute to the anti- atherogenic properties of high density lipoproteins (HDL) by metabolizing lipid peroxides. PON1 activity is subject to modulation by dietary and genetic factors. Aims To determine PON1 activity in Greek migrants and Anglo-Celtic subjects recruited from the Melbourne Collaborative Cohort Study, and its relationship to coronary risk factors and dietary markers. Methods Greek (n = 127) and Anglo-Celtic (n = 128) participants in the MCCS were recruited. By design, there were approximately equal numbers of men and women and of diabetic and non-diabetic subjects. Subjects were screened for glucose tolerance, dyslipidaemia, hypertension and coronary heart disease. Plasma markers of diet (carotenoids, retinol, tocopherol, homocysteine) and inflammation (C-reactive protein) were assessed. Serum PON1 activity was determined spectrophotometrically using two substrates: paraoxon (paraoxonase) and phenylacetate (arylesterase). Results PON1 activity was significantly higher in the presence of hyperlipidaemia but otherwise did not vary by ethnicity, presence of coronary heart disease, diabetes, hypertension or smoking. Among subjects with the high activity phenotype (defined by the ratio of paraoxonase:arylesterase activity), paraoxonase activity correlated directly with circulating diet-derived carotenoid concentrations for Greeks, and inversely with homocysteine and C-reactive protein for Anglo-Celtics. No such associations were seen among subjects with the low activity phenotype. Conclusions The data suggest that dietary modulation of athero-sclerotic risk may vary according to PON1 phenotype. [ABSTRACT FROM AUTHOR]

Non‐small cell lung cancer (NSCLC) is the main type of lung cancer, with a low 5‐year survival rate because of the absence of effective clinical biomarkers for early diagnosis. Based on the immunosurveillance theory, we proposed that changes in the immune system are more pronounced than tumour‐associated antigens during the early stage of cancer. Therefore, a new strategy was designed to screen early diagnostic biomarkers from peripheral leukocytes in early‐stage NSCLCs with transcriptome sequencing. A total of 358 immune‐related differentially expressed genes were identified between early‐NSCLC patients and healthy individuals. Orosomucoid‐1 (ORM1, a acute phase protein), the total ORM and chitotriosidase‐1 (involved in degradation of chitobiose) were selected for further verification in 210 serum samples by western blotting, ELISA and nephelometry immunoassay (based on immuno‐scatter turbidmetry). Receiver operating characteristic curve analysis show that ORM1 and total ORM have excellent diagnostic efficacies, with area under the curve of 0.862 and 0.920, respectively, which significantly distinguished very early‐NSCLC (IA) from healthy samples. Flow cytometry results showed that CD15+ neutrophils made up 73% of ORM1+ peripheral leukocytes. In mouse lung cancer model, serum ORM1, but not liver ORM1, changed significantly in the early stage of NSCLC. ORM1 expression in peripheral leukocytes was regulated by TGF‐β and mediated by the TGF‐β/Smad signalling pathway. Our results indicated that combined ORM and TGF‐β could be a promising clinical biomarker in the diagnosis of early NSCLC. [ABSTRACT FROM AUTHOR]