Metabonomic analysis of follicular fluid in patients with diminished ovarian reserve

BackgroundOvarian reserve is an important factor determining female reproductive potential. The number and quality of oocytes in patients with diminished ovarian reserve (DOR) are reduced, and even if in vitro fertilization-embryo transfer (IVF-ET) is used to assist their pregnancy, the clinical pregnancy rate and live birth rate are still low. Infertility caused by reduced ovarian reserve is still one of the most difficult clinical problems in the field of reproduction. Follicular fluid is the microenvironment for oocyte survival, and the metabolic characteristics of follicular fluid can be obtained by metabolomics technology. By analyzing the metabolic status of follicular fluid, we hope to find the metabolic factors that affect the quality of oocytes and find new diagnostic markers to provide clues for early detection and intervention of patients with DOR.MethodsIn this research, 26 infertile women with DOR and 28 volunteers with normal ovarian reserve receiving IVF/ET were recruited, and their follicular fluid samples were collected for a nontargeted metabonomic study. The orthogonal partial least squares discriminant analysis model was used to understand the separation trend of the two groups, KEGG was used to analyze the possible metabolic pathways involved in differential metabolites, and the random forest algorithm was used to establish the diagnostic model.Results12 upregulated and 32 downregulated differential metabolites were detected by metabolic analysis, mainly including amino acids, indoles, nucleosides, organic acids, steroids, phospholipids, fatty acyls, and organic oxygen compounds. Through KEGG analysis, these metabolites were mainly involved in aminoacyl-tRNA biosynthesis, tryptophan metabolism, pantothenate and CoA biosynthesis, and purine metabolism. The AUC value of the diagnostic model based on the top 10 metabolites was 0.9936.ConclusionThe follicular fluid of patients with DOR shows unique metabolic characteristics. These data can provide us with rich biochemical information and a research basis for exploring the pathogenesis of DOR and predicting ovarian reserve function

Conversion of alpine pastureland to artificial grassland altered CO2 and N2O emissions by decreasing C and N in different soil aggregates

Background The impacts of land use on greenhouse gases (GHGs) emissions have been extensively studied. However, the underlying mechanisms on how soil aggregate structure, soil organic carbon (SOC) and total N (TN) distributions in different soil aggregate sizes influencing carbon dioxide (CO2), and nitrous oxide (N2O) emissions from alpine grassland ecosystems remain largely unexplored. Methods A microcosm experiment was conducted to investigate the effect of land use change on CO2and N2O emissions from different soil aggregate fractions. Soil samples were collected from three land use types, i.e., non-grazing natural grassland (CK), grazing grassland (GG), and artificial grassland (GC) in the Bayinbuluk alpine pastureland. Soil aggregate fractionation was performed using a wet-sieving method. The variations of soil aggregate structure, SOC, and TN in different soil aggregates were measured. The fluxes of CO2 and N2O were measured by a gas chromatograph. Results Compared to CK and GG, GC treatment significantly decreased SOC (by 24.9–45.2%) and TN (by 20.6–41.6%) across all soil aggregate sizes, and altered their distributions among soil aggregate fractions. The cumulative emissions of CO2 and N2O in soil aggregate fractions in the treatments of CK and GG were 39.5–76.1% and 92.7–96.7% higher than in the GC treatment, respectively. Moreover, cumulative CO2emissions from different soil aggregate sizes in the treatments of CK and GG followed the order of small macroaggregates (2–0.25 mm) > large macroaggregates (> 2 mm) > micro aggregates (0.25–0.053 mm) > clay +silt (< 0.053 mm), whereas it decreased with aggregate sizes decreasing in the GC treatment. Additionally, soil CO2 emissions were positively correlated with SOC and TN contents. The highest cumulative N2O emission occurred in micro aggregates under the treatments of CK and GG, and N2O emissions among different aggregate sizes almost no significant difference under the GC treatment. Conclusions Conversion of natural grassland to artificial grassland changed the pattern of CO2 emissions from different soil aggregate fractions by deteriorating soil aggregate structure and altering soil SOC and TN distributions. Our findings will be helpful to develop a pragmatic management strategy for mitigating GHGs emissions from alpine grassland