Dataset Information

Metabolomic analysis of anti-hypoxia and anti-anxiety effects of Fu Fang Jin Jing Oral Liquid.

ABSTRACT:

Background

Herba Rhodiolae is a traditional Chinese medicine used by the Tibetan people for treating hypoxia related diseases such as anxiety. Based on the previous work, we developed and patented an anti-anxiety herbal formula Fu Fang Jin Jing Oral Liquid (FJJOL) with Herba Rhodiolae as a chief ingredient. In this study, the anti-hypoxia and anti-anxiety effects of FJJOL in a high altitude forced-swimming mouse model with anxiety symptoms will be elucidated by NMR-based metabolomics.

Methods

In our experiments, the mice were divided randomly into four groups as flatland group, high altitude saline-treated group, high altitude FJJOL-treated group, and high altitude diazepam-treated group. To cause anxiety effects and hypoxic defects, a combination use of oxygen level decreasing (hypobaric cabin) and oxygen consumption increasing (exhaustive swimming) were applied to mice. After a three-day experimental handling, aqueous metabolites of mouse brain tissues were extracted and then subjected to NMR analysis. The therapeutic effects of FJJOL on the hypobaric hypoxia mice with anxiety symptoms were verified.

Results

Upon hypoxic exposure, both energy metabolism defects and disorders of functional metabolites in brain tissues of mice were observed. PCA, PLS-DA and OPLS-DA scatter plots revealed a clear group clustering for metabolic profiles in the hypoxia versus normoxia samples. After a three-day treatment with FJJOL, significant rescue effects on energy metabolism were detected, and levels of ATP, fumarate, malate and lactate in brain tissues of hypoxic mice recovered. Meanwhile, FJJOL also up-regulated the neurotransmitter GABA, and the improvement of anxiety symptoms was highly related to this effect.

Conclusions

FJJOL ameliorated hypobaric hypoxia effects by regulating energy metabolism, choline metabolism, and improving the symptoms of anxiety. The anti-anxiety therapeutic effects of FJJOL were comparable to the conventional anti-anxiety drug diazepam on the hypobaric hypoxia mice. FJJOL might serve as an alternative therapy for the hypoxia and anxiety disorders.

SUBMITTER: Liu X

PROVIDER: S-EPMC3799728 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Metabolomic analysis of anti-hypoxia and anti-anxiety effects of Fu Fang Jin Jing Oral Liquid.

Liu Xia X Zhu Wei W Guan Shuhong S Feng Ruihong R Zhang Hui H Liu Qiuhong Q Sun Peng P Lin Donghai D Zhang Naixia N Shen Jun J

PloS one 20131018 10

<h4>Background</h4>Herba Rhodiolae is a traditional Chinese medicine used by the Tibetan people for treating hypoxia related diseases such as anxiety. Based on the previous work, we developed and patented an anti-anxiety herbal formula Fu Fang Jin Jing Oral Liquid (FJJOL) with Herba Rhodiolae as a chief ingredient. In this study, the anti-hypoxia and anti-anxiety effects of FJJOL in a high altitude forced-swimming mouse model with anxiety symptoms will be elucidated by NMR-based metabolomics.<h4 ...[more]

PMID: 24205180

Similar Datasets

Project description:BackgroundSimulating vegetation distribution is an effective method for identifying vegetation distribution patterns and trends. The primary goal of this study was to determine the best simulation method for a vegetation in an area that is heavily affected by human disturbance.MethodsWe used climate, topographic, and spectral data as the input variables for four machine learning models (random forest (RF), decision tree (DT), support vector machine (SVM), and maximum likelihood classification (MLC)) on three vegetation classification units (vegetation group (I), vegetation type (II), and formation and subformation (III)) in Jing-Jin-Ji, one of China's most developed regions. We used a total of 2,789 vegetation points for model training and 974 vegetation points for model assessment.ResultsOur results showed that the RF method was the best of the four models, as it could effectively simulate vegetation distribution in all three classification units. The DT method could only simulate vegetation distribution in units I and II, while the other two models could not simulate vegetation distribution in any of the units. Kappa coefficients indicated that the DT and RF methods had more accurate predictions for units I and II than for unit III. The three vegetation classification units were most affected by six variables: three climate variables (annual mean temperature, mean diurnal range, and annual precipitation), one geospatial variable (slope), and two spectral variables (Mid-infrared ratio of winter vegetation index and brightness index of summer vegetation index). Variables Combination 7, including annual mean temperature, annual precipitation, mean diurnal range and precipitation of driest month, produced the highest simulation accuracy.ConclusionsWe determined that the RF model was the most effective for simulating vegetation distribution in all classification units present in the Jing-Jin-Ji region. The RF model produced high accuracy vegetation distributions in classification units I and II, but relatively low accuracy in classification unit III. Four climate variables were sufficient for vegetation distribution simulation in such region.

Project description:BackgroundCondyloma acuminatum (CA) is a sexually transmitted disease characterized by the anomalous proliferation of keratinocytes caused by human papillomavirus (HPV) infection. Fu Fang Gang Liu liquid (FFGL) is an effective externally administered prescription used to treat CA; however, its molecular mechanism remains unclear. This study aimed to identify and experimentally validate the major active ingredients and prospective targets of FFGL.MethodsNetwork pharmacology, transcriptomics, and enrichment analysis were used to identify the active ingredients and prospective targets of FFGL, which were confirmed through subsequent experimental validation using mass spectrometry, molecular docking, western blotting, and in vitro assays.ResultsThe network pharmacology analysis revealed that FFGL contains a total of 78 active compounds, which led to the screening of 610 compound-related targets. Among them, 59 overlapped with CA targets and were considered to be targets with potential therapeutic effects. The protein-protein interaction network analysis revealed that protein kinase B (Akt) serine/threonine kinase 1 was a potential therapeutic target. To further confirm this result, we performed ribonucleic acid sequencing (RNA-seq) assays on HPV 18+ cells after FFGL exposure and conducted enrichment analyses on the differentially expressed genes that were screened. The enrichment analysis results indicated that the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway may be a key pathway through which FFGL exerts its effects. Further in vitro experiments revealed that FFGL significantly inhibited the activity of HPV 18+ cells and reduced PI3K and Akt protein levels. A rescue experiment indicated that the reduction in cell viability induced by FFGL was partially restored after the administration of activators of the PI3K/Akt pathway. We further screened two active components of FFCL that may be efficacious in the treatment of CA: periplogenin and periplocymarin. The molecular docking experiments showed that these two compounds exhibited good binding activity to Akt1.ConclusionFFGL reduced HPV 18+ cell viability by inhibiting key proteins in the PI3K/Akt pathway; this pathway may represent an essential mechanism through which FFGL treats CA. Periplogenin and periplocymarin may play a significant role in this process.

Project description:BackgroundPolycystic ovary syndrome (PCOS) is the most common heterogeneous endocrine disease among women of childbearing age, characterized by androgen excess and ovarian dysfunction. Aerobic exercise is an important solution used to manage PCOS, due to its multiple benefits. Yi Jin Jing is an important component of traditional Chinese exercise (TCE), based on the root of traditional Chinese medicine theory (TCM), which focuses on keeping the body as a whole in a harmonious state. However, to date there is no literature on the benign effects of Yi Jin Jing on PCOS. The primary purpose of this protocol is to assess the effectiveness of aerobic exercise versus Yi Jin Jing, on the management of ovarian function in young overweight/obese women with PCOS.MethodsThe study will conduct a controlled randomized, superiority trial with three-arm parallel groups, recruiting 90 women diagnosed with PCOS, ages between 18 and 35 years, with a body mass index (BMI) ≥ 23 kg/m2. Women will be randomly assigned to either control group (combined oral contraceptives) or one of the intervention groups (Yi Jin Jing group or aerobic exercise group) with an allocation rate of 1:1:1. After randomization, the intervention will be conducted within a 12-week period. The primary outcome would be anti-Mullerian hormone (AMH) level; the secondary outcomes would be biochemical profiles, ovarian volume, antral follicle count, BMI, menstrual frequency, and homeostasis model assessment of insulin resistance (HOMA-IR). Outcome measures would be collected during baseline and end of treatment. Reporting of the study will follow the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) statement.DiscussionThis proposed study will be the first randomized clinical trial to evaluate the comparative effectiveness of aerobic exercise versus Yi Jin Jing on the management of ovarian function in young overweight/obese women with PCOS. The results may provide a new evidence-based management strategy for young women with PCOS.Trial registrationChinese Clinical Trial Registry ChiCTR1900022385 . Registered on 9 April 2019.

Dataset Information

Metabolomic analysis of anti-hypoxia and anti-anxiety effects of Fu Fang Jin Jing Oral Liquid.

Background

Methods

Results

Conclusions

Publications

Metabolomic analysis of anti-hypoxia and anti-anxiety effects of Fu Fang Jin Jing Oral Liquid.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets