Regulation of Fatty Acid Metabolism and Inhibition of Colorectal Cancer Progression by Erchen Decoction.

Erchen decoction (ECD) is a traditional Chinese prescription widely used in the treatment of various diseases such as obesity, fatty liver, diabetes, and hypertension. In this study, we investigated the effect of ECD on fatty acid metabolism in a colorectal cancer (CRC) mouse model fed a high-fat (HF) diet. The HF-CRC mouse model was established by azoxymethane (AOM)/dextran sulphate sodium (DSS) combined with a high-fat diet. Mice were then gavaged with ECD. Change in the body weight was recorded every two weeks for 26 weeks. Changes in blood glucose (GLU), total cholesterol (TC), total triglycerides (TG), and C-reactive protein (CRP) were measured. Colorectal tissues were collected to observe changes in colorectal length and tumorigenesis. Hematoxylin-eosin (HE) staining and immunohistochemical staining were performed to observe changes in intestinal structure and inflammatory markers. Fatty acids and the expression of related genes in colorectal tissues were also studied. ECD gavage inhibited HF-induced weight gain. CRC induction and HF diet intake resulted in increased GLU, TC, TG, and CRP, where ECD gavage reduced these elevated indicators. ECD gavage also increased colorectal length and inhibited tumorigenesis. HE staining revealed that ECD gavage suppressed inflammatory infiltration of colorectal tissues. ECD gavage suppressed the fatty acid metabolism abnormalities caused by HF-CRC in colorectal tissues. Consistently, ECD gavage lowered ACSL4, ACSL1, CPT1A, and FASN levels in colorectal tissues. Conclusions. ECD inhibited HF-CRC progression through the regulation of fatty acid metabolism.

A Nomogram model for the early warning of essential hypertension risks based on the principles of traditional Chinese medicine syndrome elements / 数字中医药（英文）

@#[Objective] To construct a Nomogram model for the prediction of essential hypertension (EH) risks with the use of traditional Chinese medicine (TCM) syndrome elements principles in conjunction with cutting-edge biochemical detection technologies. [Methods] A case-control study was conducted, involving 301 patients with essential hypertension in the hypertensive group and 314 without in the control group. Comprehensive data, including the information on the four TCM diagnoses, general data, and blood biochemical indicators of participants in both groups, were collected separately for analysis. The differentiation principles of syndrome elements were used to discern the location and nature of hypertension. One-way analysis was carried out to screen for potential risk factors of the disease. Least absolute shrinkage and selection operator (LASSO) regression was used to identify factors that contribute significantly to the model, and eliminate possible collinearity problems. At last, multivariate logistic regression analysis was used to both screen and quantify independent risk factors essential for the prediction model. The “rms” package in the R Studio was used to construct the Nomogram model, creating line segments of varying lengths based on the contribution of each risk factor to aid in the prediction of risks of hypertension. For internal model validation, the Bootstrap program package was utilized to perform 1000 repetitions of sampling and generate calibration curves. [Results] The results of the multivariate logistic regression analysis revealed that the risk factors of EH included age, heart rate (HR), waist-to-hip ratio (WHR), uric acid (UA) levels, family medical history, sleep patterns (early awakening and light sleep), water intake, and psychological traits (depression and anger). Additionally, TCM syndrome elements such as phlegm, Yin deficiency, and Yang hyperactivity contributed to the risk of EH onset as well. TCM syndrome elements liver, spleen, and kidney were also considered the risk factors of EH. Next, the Nomogram model was constructed using the aforementioned 14 risk predictors, with an area under the curve (AUC) of 0.868 and a 95% confidence interval (CI) ranging from 0.840 to 0.895. The diagnostic sensitivity and specificity were found to be 80.7% and 85.0%, respectively. Internal validation confirmed the model’s robust predictive performance, with aconsistency index (C-index) of 0.879, underscoring the model’s strong predictive ability. [Conclusion] By integrating TCM syndrome elements, the Nomogram model has realized the objective, qualitative, and quantitative selection of early warning factors for developing EH, resulting in the creation of a more comprehensive and precise prediction model for EH risks.

Investigating the effects and mechanisms of Erchen Decoction in the treatment of colorectal cancer by network pharmacology and experimental validation.

Objective: Erchen Decoction (ECD), a well-known traditional Chinese medicine, exerts metabolism-regulatory, immunoregulation, and anti-tumor effects. However, the action and pharmacological mechanism of ECD remain largely unclear. In the present study, we explored the effects and mechanisms of ECD in the treatment of CRC using network pharmacology, molecular docking, and systematic experimental validation. Methods: The active components of ECD were obtained from the TCMSP database and the potential targets of them were annotated by the STRING database. The CRC-related targets were identified from different databases (OMIM, DisGeNet, GeneCards, and DrugBank). The interactive targets of ECD and CRC were screened and the protein-protein interaction (PPI) networks were constructed. Then, the hub interactive targets were calculated and visualized from the PPI network using the Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. In addition, the molecular docking was performed. Finally, systematic in vitro, in vivo and molecular biology experiments were performed to further explore the anti-tumor effects and underlying mechanisms of ECD in CRC. Results: A total of 116 active components and 246 targets of ECD were predicted based on the component-target network analysis. 2406 CRC-related targets were obtained from different databases and 140 intersective targets were identified between ECD and CRC. 12 hub molecules (STAT3, JUN, MAPK3, TP53, MAPK1, RELA, FOS, ESR1, IL6, MAPK14, MYC, and CDKN1A) were finally screened from PPI network. GO and KEGG pathway enrichment analyses demonstrated that the biological discrepancy was mainly focused on the tumorigenesis-, immune-, and mechanism-related pathways. Based on the experimental validation, ECD could suppress the proliferation of CRC cells by inhibiting cell cycle and promoting cell apoptosis. In addition, ECD could inhibit tumor growth in mice. Finally, the results of molecular biology experiments suggested ECD could regulate the transcriptional levels of several hub molecules during the development of CRC, including MAPKs, PPARs, TP53, and STATs. Conclusion: This study revealed the potential pharmacodynamic material basis and underlying molecular mechanisms of ECD in the treatment of CRC, providing a novel insight for us to find more effective anti-CRC drugs.

An Effective Treatment of Perimenopausal Syndrome by Combining Two Traditional Prescriptions of Chinese Botanical Drugs.

Ethnopharmacological relevance: Two types of traditional Chinese formulas of botanical drugs are prescribed for treating perimenopausal syndrome (PMS), a disorder in middle-aged women during their transition to menopause. One is for treating PMS as kidney deficiency (KD) due to senescence and declining reproductive functions, and the other is for treating it as liver qi stagnation (LQS) in association with stress and anxiety. Despite the time-tested prescriptions, an objective attestation to the effectiveness of the traditional Chinese treatment of PMS is still to be established and the associated molecular mechanism is still to be investigated. Materials and methods: A model for PMS was generated from perimenopausal rats with chronic restraint stress (CRS). The effectiveness of traditional Chinese formulas of botanical drugs and a combination of two of the formulas was evaluated based on 1H NMR plasma metabolomic, as well as behavioral and physiological, indicators. To investigate whether the formulas contained ligands that could compensate for the declining level of estrogen, the primary cause of PMS, the ligand-based NMR technique of saturation transfer difference (STD) was employed to detect possible interacting molecules to estrogen receptors in the decoction. Results: Each prescription of the classical Chinese formula moderately attenuated the metabolomic state of the disease model. The best treatment strategy however was to combine two traditional Chinese formulas, each for a different etiology, to adjust the metabolomic state of the disease model to that of rats at a much younger age. In addition, this attenuation of the metabolomics of the disease model was by neither upregulating the estrogen level nor supplementing an estrogenic compound. Conclusion: Treatment of PMS with a traditional Chinese formula of botanical drugs targeting one of the two causes separately could ameliorate the disorder moderately. However, the best outcome was to treat the two causes simultaneously with a decoction that combined ingredients from two traditional prescriptions. The data also implicated a new paradigm for phytotherapy of PMS as the prescribed decoctions contained no interacting compound to modulate the activity of estrogen receptors, in contrast to the treatment strategy of hormone replacement therapy.

The important herbal pair for the treatment of COVID-19 and its possible mechanisms.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) is an unprecedented disaster for people around the world. Many studies have shown that traditional Chinese medicine (TCM) are effective in treating COVID-19. However, it is difficult to find the most effective combination herbal pair among numerous herbs, as well as identifying its potential mechanisms. Herbal pair is the main form of a combination of TCM herbs, which is widely used for the treatment of diseases. It can also help us to better understand the compatibility of TCM prescriptions, thus improving the curative effects. The purpose of this article is to explore the compatibility of TCM prescriptions and identify the most important herbal pair for the treatment of COVID-19, and then analyze the active components and potential mechanisms of this herbal pair. METHODS: We first systematically sorted the TCM prescriptions recommended by the leading experts for treating COVID-19, and the specific herbs contained in these prescriptions across different stages of the disease. Next, the association rule approach was employed to examine the distribution and compatibility among these TCM prescriptions, and then identify the most important herbal pair. On this basis, we further investigated the active ingredients and potential targets in the selected herbal pair by a network pharmacology approach, and analyzed the potential mechanisms against COVID-19. Finally, the main active compounds in the herbal pair were selected for molecular docking with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) 3CLpro and angiotensin converting enzyme II (ACE2) for further verification. RESULT: We obtained 32 association rules for the herbal combinations in the selection of TCM treatment for COVID-19. The results showed that the combination of Amygdalus Communis Vas (ACV) and Ephedra sinica Stapf (ESS) had the highest confidence degree and lift value, as well as high support degree, which can be used in almost all the stages of COVID-19, so ACV and ESS (AE) were selected as the most important herbal pair. There were 26 active ingredients and 44 potential targets, which might be related to the herbal pair of AE against COVID-19. The main active ingredients of AE against COVID-19 were quercetin, kaempferol, luteolin, while the potential targets were Interleukin 6 (IL-6), Mitogen-activated Protein Kinase 1 (MAPK)1, MAPK8, Interleukin-1ß (IL-1ß), and Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB) p65 subunit (RELA). The protein-protein interaction (PPI) cluster demonstrated that IL-6 was the seed in the cluster, which plays an important role in connecting other nodes in the PPI network. The potential pathways mainly involved tumor necrosis factor (TNF), Toll-like receptor (TLR), hypoxia-inducible factor-1 (HIF-1), and nucleotide-binding oligomerization domain (NOD)-like receptor (NLRs). The molecular docking results showed that the main active ingredients of AE have good affinity with SARS-COV-2 3CLpro and ACE2, which are consistent with the above analysis. CONCLUSIONS: There were 32 association rules in the TCM prescriptions recommended by experts for COVID-19. The combination of ACV and EAS was the most important herbal pair for the treatment of COVID-19. AE might have therapeutic effects against COVID-19 by affecting the inflammatory and immune responses, cell apoptosis, hypoxia damage and other pathological processes through multiple components, targets and pathways.

Modeling of diagnosis for metabolic syndrome by integrating symptoms into physiochemical indexes.

BACKGROUND: Metabolic syndrome (MS) is a major global health concern comprising a cluster of co-occurring conditions that increase the risk of heart disease, stroke and type 2 diabetes. MS is usually diagnosed using a combination of physiochemical indexes (such as BMI, abdominal circumference and blood pressure) but largely ignores clinical symptoms when investigating prevention and treatment of the disease. Exploring predictors of MS using multiple diagnostic indicators may improve early diagnosis and treatment of MS. Traditional Chinese medicine (TCM) attaches importance to the etiology of disease symptoms and indications using four diagnostic methods, which have long been used to treat metabolic disease. Therefore, in this study, we aimed to develop predictive indicators for MS using both physiochemical indexes and TCM methods. METHODS: Clinical information (including both physiochemical and TCM indexes) was obtained from a cohort of 586 individuals across 4 hospitals in China, comprising 136 healthy controls and 450 MS cases. Using this cohort, we compared three classic machine learning methods: decision tree (DT), support vector machine (SVM) and random forest (RF) towards MS diagnosis using physiochemical and TCM indexes, with the best model selected by comparing the accuracy, specificity and sensitivity of the three models. In parallel, the best proportional partition of the training data to the test data was confirmed by observing the changes in evaluation indexes using each model. Next, three subsets containing different categories of variables (including both TCM and physicochemical indexes combined - termed the "fused indexes", only physicochemical indexes, and TCM indexes only) were compared and analyzed using the best performing model and optimum training to test data proportion. Next, the best subset was selected through comprehensive comparative analysis, and then the important prediction variables were selected according to their weight. RESULTS: When comparing the three models, we found that the RF model had the highest average accuracy (average 0.942, 95%CI [0.925, 0.958]) and sensitivity (average 0.993, 95%CI [0.990, 0.996]). Besides, when the training set accounted for 80% of the cohort data, the specificity got the best value and the accuracy and sensitivity were also very high in RF model. In view of the performance of the three different subsets, the prediction accuracy and sensitivity of models analyzing the fused indexes and only physicochemical indexes remained at a high level. Further, the mean value of specificity of the model using fused indexes was 0.916, which was significantly higher than the model with only physicochemical indexes (average 0.822) and the model with only TCM indexes (average 0.403). Based on the RF model and data allocation ratio (8:2), we further extracted the top 20 most significant variables from the fused indexes, which included 14 physicochemical indexes and 6 TCM indexes including wiry pulse, chest tightness, spontaneous perspiration, greasy tongue coating etc. CONCLUSION: Compared with SVM and DT models, the RF model showed the best performance, especially when the ratio of the training set to test set is 8:2. Compared with single predictive indexes, the model constructed by combining physiochemical indexes with TCM indexes (i.e. the fused indexes) exhibited better predictive ability. In addition to common physicochemical indexes, some TCM indexes, such as wiry pulse, chest tightness, spontaneous perspiration, greasy tongue coating, can also improve diagnosis of MS.

The Metabolomic Rationale for Treating Perimenopausal Syndrome as Kidney Deficiency.

BACKGROUND: Traditional Chinese medicine (TCM) typically attributes the etiopathogenesis of perimenopausal syndrome (PMS) to kidney deficiency in the TCM stratification system for diagnosis. However, the molecular basis of this classical attribution remains to be investigated. Aim of the Study. By unraveling the responses to TCM treatment for kidney deficiency, the metabolomic link between PMS and kidney deficiency can be evaluated for in-depth understanding of the mechanism of TCM treatment and development of better treatment protocols. MATERIALS AND METHODS: With naturally aged rats as a model for PMS, the metabolomic response to TCM treatment for kidney deficiency was investigated by 1H NMR. RESULTS: 1H NMR metabolomic evidence of plasma samples demonstrates that treatments with two classical TCM prescriptions for kidney deficiency, decoctions of Yougui and Zuogui, result in modulating the metabolic state of the disease model towards that of rats of younger age. CONCLUSION: The data support the notion that kidney deficiency is responsible, in part at least, for PMS, and the relevant prescriptions are helpful in dampening the changes in the body's metabolic states to alleviate symptoms of the disorder.

A Microcosmic Syndrome Differentiation Model for Metabolic Syndrome with Multilabel Learning.

BACKGROUND: Metabolic syndrome (MS) is a complex multisystem disease. Traditional Chinese medicine (TCM) is effective in preventing and treating MS. Syndrome differentiation is the basis of TCM treatment, which is composed of location and/or nature syndrome elements. At present, there are still some problems for objective and comprehensive syndrome differentiation in MS. This study mainly proposes a solution to two problems. Firstly, TCM syndromes are concurrent, that is, multiple TCM syndromes may develop in the same patient. Secondly, there is a lack of holistic exploration of the relationship between microscopic indexes, and TCM syndromes. In regard to these two problems, multilabel learning (MLL) method in machine learning can be used to solve them, and a microcosmic syndrome differentiation model can also be built innovatively, which can provide a foundation for the establishment of the next model of multidimensional syndrome differentiation in MS. METHODS: The standardization scale of TCM four diagnostic information for MS was designed, which was used to obtain the results of TCM diagnosis. The model of microcosmic syndrome differentiation was constructed based on 39 physicochemical indexes by MLL techniques, called ML-kNN. Firstly, the multilabel learning method was compared with three commonly used single learning algorithms. Then, the results from ML-kNN were compared between physicochemical indexes and TCM information. Finally, the influence of the parameter k on the diagnostic model was investigated and the best k value was chosen for TCM diagnosis. RESULTS: A total of 698 cases were collected for the modeling of the microcosmic diagnosis of MS. The comprehensive performance of the ML-kNN model worked obviously better than the others, where the average precision of diagnosis was 71.4%. The results from ML-kNN based on physicochemical indexes were similar to the results based on TCM information. On the other hand, the k value had less influence on the prediction results from ML-kNN. CONCLUSIONS: In the present study, the microcosmic syndrome differentiation model of MS with MLL techniques was good at predicting syndrome elements and could be used to solve the diagnosis problems of multiple labels. Besides, it was suggested that there was a complex correlation between TCM syndrome elements and physicochemical indexes, which worth future investigation to promote the development of objective differentiation of MS.

Verification of the Efficacy and Safety of Qi-Replenishing Chinese Medicine in Treating Prediabetes: A Meta-Analysis and Literature Review.

BACKGROUND: Qi-replenishing Chinese medicines (QCMs) are used for treating prediabetes in the traditional Chinese medicine (TCM) clinical practice. The aims of this meta-analysis were to (i) verify the efficacy and safety of QCMs in treating prediabetes and (ii) investigate the clinical outcomes between the trials complying with and not complying with the principle of "syndrome differentiation." METHODS: We included only randomized controlled clinical trials (RCTs) whose Jadad scores were not less than 4. The overall clinical outcomes, including the incidence rate of diabetes, normalization of blood glucose, changes in fasting blood glucose (FBG), 2 h postprandial blood glucose, HbA1c, and occurrence of adverse events, were evaluated. Subgroup analyses were performed. RESULTS: A total of 11 RCTs that enrolled 2210 patients with prediabetes were included. We observed that overall treatment with QCMs significantly ameliorated the clinical outcomes of prediabetes without increasing incidence of adverse events. The results of subgroup analyses revealed that prescribing QCMs complying with syndrome differentiation ameliorated all the clinical indices, whereas prescribing not complying with syndrome differentiation could not achieve significant amelioration in FBG and HbA1c levels. Furthermore, the subgroup with syndrome differentiation reported more adverse events. CONCLUSIONS: The overall results suggested that QCMs are effective and safe in treating prediabetes. Results of subgroup analyses indicated that the groups with syndrome differentiation presented better efficacy but had a higher occurrence of adverse events. This study indicated the important role of the principle of syndrome differentiation in TCM and that the adverse events of QCMs cannot be ignored in TCM clinical practice.

Factor and Cluster Analysis for TCM Syndromes of Real-World Metabolic Syndrome at Different Age Stage.

BACKGROUND: Traditional Chinese medicine (TCM) has the characteristics of multitarget and overall regulation, which has certain advantages in preventing and treating of metabolic syndrome (MS). The aim of the present study was to evaluate the similarities and differences of TCM syndrome distribution in different age groups to promote the optimization of treatment strategies. METHODS: This study was based on a real-world survey conducted in 3 hospitals in China. There are 1262 collected cases of MS meeting the inclusion criteria, which were divided into the young group, middle-aged group, and elderly group. Factor analysis (FA) was conducted for syndrome element extraction, and K-means cluster analysis was processed for syndrome type classification. Frequency analysis and Chi-square test were used to compare the syndrome characteristics of each group. RESULTS: Common factors extracted were assigned to 18 syndrome elements including 11 nature syndrome elements and 7 location syndrome elements. Phlegm and dampness are the most frequent syndrome elements in general. Compared with the middle-aged group and elderly group, the young group has more obvious nature syndrome elements in heat and Qi deficiency, and location syndrome elements in the stomach. As for the middle-aged group, the frequency of location syndrome in kidney syndrome was higher than that in other groups. When it comes to the elderly group, it is shown that the symptoms of Yin deficiency and blood deficiency increase with age and the old patients may have more location syndrome elements in the lung and gallbladder. CONCLUSION: The TCM syndrome of MS is complex in that there may be the characteristics of deficiency and excess syndrome simultaneously. The main pathological factors of MS were phlegm and dampness. Besides, MS patients at different age periods may have their own syndrome distribution features. So, it is reasonable to adhere to the method of resolving phlegm and removing dampness and, at the same time, adopt the ways of clearing heat, promoting Qi, nourishing Yin, supplementing blood as well as regulating the liver, promoting the lung, transporting the spleen, nourishing the heart, and nourishing the kidney based on the syndrome feature of MS in different age stages.

Erchen Decoction Mitigates Lipid Metabolism Disorder by the Regulation of PPARγ and LPL Gene in a High-Fat Diet C57BL/6 Mice Model.

Erchen decoction (ECD) is a common treatment prescribed in traditional Chinese medicine (TCM) clinics, which has remarkable efficacy in the treatment of obesity, fatty liver, hyperlipidemia, diabetes, and other diseases caused by phlegm. In this study, we investigated the effect that ECD had on the lipid metabolism induced by high-fat diet in C57BL/6 mice. Body weight, body length, and abdominal circumference were detected. Blood lipid content was measured via biochemical assay kit. The gene and protein expression of PPARγ and LPL in visceral fat and skeletal muscle of mice was measured by real-time PCR and western blot. The research discovered that the phlegm-resolving effect that ECD had on high-fat diet mice was mainly manifested as reduced body weight, Lee's index, abdominal circumference, and level of TG and TC. Meanwhile, we observed significantly increased PPARγ mRNA and protein level in visceral fat and PPARγ and LPL protein level in skeletal muscle in the ECD group. Contrarily, a decrease in PPARγ mRNA level in skeletal muscle in the ECD group was observed. Therefore, we speculate that ECD regulates the lipid metabolic disorder by decreasing the blood lipid level. Moreover, the potential molecular mechanism of ECD is to promote the expression of PPARγ in visceral fat and skeletal muscle and the expression of LPL in skeletal muscle.

Erchen Decoction Ameliorates Lipid Metabolism by the Regulation of the Protein CAV-1 and the Receptors VLDLR, LDLR, ABCA1, and SRB1 in a High-Fat Diet Rat Model.

Lipid metabolism disorder is a common metabolic disorder characterized by abnormal lipid levels in blood. Erchen decoction (ECD) is a traditional Chinese medicine prescription, which is used for the treatment of diseases caused by retention of phlegm dampness. It has been reported to ameliorate the disorder of lipid metabolism. The aim of the present study was to investigate the effects and underlying mechanisms of ECD in lipid metabolism disorder induced by a high-fat diet (HFD) in rats. ECD (4.35g/kg/d) and atorvastatin (10mg/kg/d, positive control) were orally administered to HFD-fed rats for four weeks. The parameters, food, water consumption, body weight, body length, liver, and visceral fat weight and the content of serum lipids and lipid transporters were assessed. The effects of ECD on the mRNA and protein expression levels of lipid transport factors were measured by real-time PCR and western blotting. The present study demonstrated that ECD improved the disorders of serum lipid and lipid transporters in HFD-fed rats, TG (0.70±0.08 mmol/L, p<0.01), LDL-C (1.50±0.19 mmol/L, p<0.01), LDL (1.38±0.21 mmol/L, p<0.05), and oxLDL (1.77±0.39 ng/mL, p<0.05) were downregulated, while HDL-C (0.87±0.13 mmol/L, p<0.01), FFA (0.62±0.13 mmol/L, p<0.05), HDL (38.8±4.0 mg/dL, p<0.05), and CETP (903.6±120.0 ng/mL, p<0.05) were upregulated. But ECD obviously had no effects on the indices food/water/energy intake, body/tissue (liver and fat) weight, and BMI (p>0.05). Concomitantly, ECD reversed the abnormal expressions of those lipid transport factors in the liver and visceral fat.

Effect of serum from postmenopausal women with osteoporosis exhibiting the Kidney-Yang deficiency pattern on bone formation in an hFOB 1.19 human osteoblastic cell line.

The aim of the present study was to investigate the underlying mechanism of the Kidney-Yang deficiency (KYD) pattern of osteoporosis in postmenopausal women of a certain age range by comparing the effect of serum from postmenopausal women with osteoporosis exhibiting the KYD pattern with that of serum from postmenopausal women without osteoporosis on bone formation in an hFOB 1.19 human osteoblastic cell line. A random selection of 30 female, postmenopausal volunteers aged 60-70 years, including 15 cases without osteoporosis and 15 cases with the KYD pattern of osteoporosis, were enrolled at the Physical Examination Center of the Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine. Venous blood was extracted and the serum was separated. The hFOB 1.19 cells were treated with 10% KYD pattern-serum or control serum from postmenopausal women of the same age range without osteoporosis. It was found that the KYD pattern-serum significantly decreased the cell viability, activity of alkaline phosphatase and number of calcified nodules, as well as downregulated the expression of osteocalcin and osteoprotegerin (OPG) and upregulated that of receptor activator of nuclear factor κB ligand (RANKL) in the hFOB 1.19 cells. In addition, the present results showed that the concentrations of estradiol (E2), OPG and insulin-like factor-1 (IGF-1) in the KYD pattern-serum were lower than those in the control serum. In combination, these findings suggest that the downregulation of E2, OPG and IGF-1 in the KYD pattern-serum inhibits the OPG/RANKL system, leading to a decrease in bone formation in the hFOB 1.19 cells. This indicates that the alterations in E2, OPG and IGF-1 may account for the susceptibility of certain postmenopausal women to the KYD pattern of osteoporosis.

Erchen Decoction Prevents High-Fat Diet Induced Metabolic Disorders in C57BL/6 Mice.

Erchen decoction (ECD) is a traditional Chinese medicine prescription, which is used in the treatment of obesity, hyperlipidemia, fatty liver, diabetes, hypertension, and other diseases caused by retention of phlegm dampness. In this study we investigated the potential mechanism of ECD, using metabolism-disabled mice induced by high-fat diet. Body weight and abdominal circumference were detected. OGTT was measured by means of collecting blood samples from the tail vein. Blood lipid levels and insulin were measured using biochemical assay kit. Real-time PCR was used to measure the CDKAL1 gene expression and western blot was used to measure the protein expression. Through the research, it was found that ECD showed markedly lower body weight and abdominal circumference than those in the HFD group. Consistently, we observed that ECD significantly improved glucose tolerance, promoted the secretion of insulin and decreased the level of TG, TC level. Meanwhile, we observed significantly increased CDKAL1 mRNA and protein level in the ECD group. Therefore, we speculate that the potential molecular mechanism of ECD is to promote the CDKAL1 expression, ameliorate islet cell function, and raise insulin levels to regulate the metabolic disorder.