ABSTRACT
OBJECTIVE: Interleukin 22 (IL-22) plays a role in inflammatory diseases. However, whether IL-22 affects the function of ovarian granulosa cells (GCs) and its relationship with Polycystic Ovary Syndrome (PCOS)remains unclear. METHODS: We investigated the level of IL-22 in human follicular fluid using ELISA. The expression and localization of the IL-22 receptor 1 (IL-22R1) in GCs were investigated by RT-PCR and immunofluorescence staining, respectively. The proliferation of KGN cells (human GCs line) was assessed by CCK-8 assay and EdU assay after treatment with recombinant human IL-22 (rhIL-22) and lipopolysaccharide (LPS). Apoptosis was assessed using flow cytometry. Apoptotic proteins and steroidogenic genes were detected by western blotting. RESULTS: ELISA's results showed that compared with the control group, PCOS patients showed lower expression of IL-22 in follicular fluid. Immunofluorescence showed that IL-22R1 is expressed and localized in human granulosa cell membranes. IL-22 promoted cell proliferation and reversed LPS-induced inhibition of cell proliferation. IL-22 alone did not affect apoptotic or steroidogenic protein expression, however, it reversed LPS-induced apoptosis via downregulation of Bcl-2, upregulation of Bax and cleaved caspase-3, and restoration of LPS-downregulated StAR, CYP11A1, and CYP19A1 expression. Western blotting confirmed that IL-22 activated the JAK2/STAT3 signaling. CONCLUSION: IL-22 promotes cell proliferation, inhibits apoptosis, and regulates KGN cell steroidogenesis confronted with LPS, and decreased IL-22 may be involved in the development of PCOS.
Subject(s)
Lipopolysaccharides , Polycystic Ovary Syndrome , Female , Humans , Lipopolysaccharides/pharmacology , Apoptosis , Interleukins , Cell Proliferation , Interleukin-22ABSTRACT
Herein, the negative photoconductivity (NPC) effect has been observed in nanodiamonds (NDs) for the first time, and with illumination under a 660 nm laser lamp, the conductivity of the NDs decreases significantly. The NPC effect has been attributed to the trapping of carriers by the absorbed water molecules on the ND surfaces. A humidity sensor has been constructed based on the NPC effect of the NDs, and the sensitivity of the sensor can reach 106%, which is the highest value ever reported for carbon-based humidity sensors.
ABSTRACT
Central nervous system injury leads to irreversible neuronal loss and glial scar formation, which ultimately results in persistent neurological dysfunction. Regenerative medicine suggests that replenishing missing neurons may be an ideal approach to repair the damage. Recent researches showed that many mature cells could be transdifferentiated into functional neurons by reprogramming. Therefore, reprogramming endogenous glia in situ to produce functional neurons shows great potential and unique advantage for repairing neuronal damage and treating neurodegenerative diseases. The present review summarized the current research progress on in situ transdifferentiation in the central nervous system, focusing on the cell types, characteristics and research progress of glial cells that could be transdifferentiated in situ, in order to provide theoretical basis for the development of new therapeutic strategies of neuronal injury and further clinical application.
Subject(s)
Cell Transdifferentiation , Cellular Reprogramming , Central Nervous System/cytology , Neuroglia/cytology , Neurons/cytology , Humans , Neurodegenerative DiseasesABSTRACT
The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation with the spatial heterogeneity under the three vegetation types. According to the temporal and spatial heterogeneity of the optimal values, the parameters of the BIOME-BGC model could be classified in order to adopt different parameter strategies in practical application. The conclusion could help to deeply understand the parameters and the optimal values of the ecological process models, and provide a way or reference for obtaining the reasonable values of parameters in models application.
