[Pilot study of genetic counseling and prenatal diagnosis in androgen insensitivity syndrome: with 3 families reports]

Objective: To explore genetic counseling and prenatal diagnosis strategies for women who have androgen insensitivity syndrome (AIS) family history or pregnancy history of AIS proband. Methods: Three families of complete AIS (CAIS) were retrospectively reported and summarized. The subsequent pregnancies and processes of prenatal diagnosis were followed up. Results: Among three CAIS families, one family had androgen receptors (AR) gene mutation diagnosis; the other two families were diagnosed clinically without gene diagnosis. All three mothers of CAIS probands were in pregnant again when they sought counseling, with gestational weeks between 7－13 weeks. They underwent chorionic villi sampling or amniocentesis in their second trimester (at 12, 16, 17 weeks respectively). Chromosome gender of all three fetuses were 46,XY, which was inconsistent with the ultrasonographic phenotype of external genitalia. All patients chose selective abortion in their second trimester. The external genitalia of all aborted fetuses were female phenotype, which supported the diagnosis of CAIS. Conclusion: Genetic counseling and prenatal diagnosis should be provided to high-risk patients with family history of AIS or proband pregnancy history, so as to achieve the goal of good childbearing and sound childrearing.

Effect of lncRNA AK023948 on rats with postmenopausal osteoporosis via PI3K/AKT signaling pathway

OBJECTIVE

To investigate the effect of long non-coding ribonucleic acid (lncRNA) AK023948 (AK0) on rats with postmenopausal osteoporosis via the phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) signaling pathway.

MATERIALS AND METHODS

Firstly, postmenopausal osteoporosis rat models were established to obtain osteoblasts. The phosphorylation level of AKT was analyzed by controlling the expression of AK0 gene in osteoblasts. Finally, XTT was used to analyze the proliferation of osteoblasts and the messenger ribonucleic acid (mRNA) expression level of caspase in AK0 gene knockout (KO) rat model.

RESULTS

In the bone tissue of postmenopausal osteoporosis rats, the levels of phospho-PI3K (p-PI3K), p-Akt, and p-phosphoinositide-dependent kinase-1(PDK1) were significantly decreased (p<0.05). In rat model osteoblasts, the overexpression of AK0 gene upregulated the phosphorylation level of AKT, while the interference with small interfering RNA (siRNA) in AK0 gene decreased that of AKT. Knocking out AK0 gene led to the down-regulation of phosphorylation level of AKT in cells. Moreover, if the AK0 gene was re-expressed in the KO rat model cells, the phosphorylation level of AKT was restored to a certain extent, but still lower than that after the overexpression of AK0 gene. Although the proliferation rate of osteoblasts in estrogen deficiency-related osteoporosis rats was low, the growth rate of osteoblasts with AK0 KO was remarkably lower than that in blank control group (p<0.05). It was also found that there was a certain correlation between AK0 gene and osteoblast apoptosis.

CONCLUSIONS

LncRNA AK0 can regulate the phosphorylation level of AKT in osteoblasts of rats with estrogen deficiency-related osteoporosis through the PI3K/AKT signaling pathway, thus regulating the proliferation of osteoblasts. It is speculated that lncRNA AK0 may be an important factor in regulating the PI3K/AKT signaling pathway.

Combining remote sensing imagery and forest age inventory for biomass mapping

Aboveground biomass (AGB) of forests is an important component of the global carbon cycle. In this study, Landsat ETM(+) images and field forest inventory data were used to estimate AGB of forests in Liping County, Guizhou Province, China. Three different vegetation indices, including simple ratio (SR), reduced simple ratio (RSR), and normalized difference vegetation index (NDVI), were calculated from atmospherically corrected ETM(+) reflectance images. A leaf area index (LAI) map was produced from the RSR map using a regression model based on measured LAI and RSR. The LAI map was then used to develop an initial AGB map, from which forest stand age was deduced. Vegetation indices, LAI, and forest stand age were together used to develop AGB estimation models for different forest types through a stepwise regression analysis. Significant predictors of AGB changed with forest types. LAI and NDVI were significant predictors of AGB for Chinese fir (R(2)=0.93). The model using LAI and stand age as predictors explained 94% of the AGB variance for coniferous forests. Stand age captured 79% of the AGB variance for broadleaved forests (R(2)=0.792). AGB of mixed forests was predicted well by LAI and SR (R(2)=0.931). Without differentiating among forest types, the model with SR and LAI as predictors was able to explain 90% of AGB variances of all forests. In Liping County, AGB shows a strong gradient that increases from northeast to southwest. About 64% of the forests have AGB in the range from 90 to 180 t ha(-1).