Transport system x c À is a member of plasma membrane heterodimeric amino-acid transporters and consists of two protein components, xCT and 4F2hc. This system mediates cystine entry coupled with the exodus of intracellular glutamate and regulates the intracellular glutathione (GSH) levels in most mammalian cultured cells. We studied the activity of system x c À and GSH content in human ovarian cancer cell line (A2780) and its cisplatin (CDDP)-resistant variant (A2780DDP). The rate of cystine uptake was approximately 4.5-fold higher in A2780DDP cells than in A2780 cells and the cystine uptake in A2780DDP cells was mediated by system x c À . Intracellular GSH content was much higher in A2780DDP cells but it fell drastically in the presence of excess glutamate, which inhibited the cystine uptake competitively. xCT and 4F2hc mRNAs were definitely expressed in A2780DDP cells, but far less in A2780 cells. Expression of system x c À activity by transfection with cDNAs for xCT and 4F2hc made A2780 cells more resistant to CDDP. Similar results on the cystine uptake were obtained in human colonic cancer cell lines. These findings suggest that the system x c À plays an important role in maintaining the higher levels of GSH and consequently in CDDP resistance in cancer cell lines.

This is the first report determining the association between pre-eclampsia and mutated MTHFR. Our results suggest that the T677 allele may represent a genetic risk factor for pre-eclampsia. Although extensive studies on the negative association between the incidence of pre-eclampsia and a diet containing abundant fruit and vegetables and B6, B 12, and folate supplementation, which is effective

Preeclampsia is a pregnancy-specific syndrome and a major cause of maternal mortality. The pathophysiology of preeclampsia is unknown, and no proteome analysis of preeclampsia has been reported. We sought to identify proteins associated with preeclampsia using a proteomic technique and performed two-dimensional electrophoresis (2-DE) on sera from six patients with preeclampsia and six normal pregnant women, followed by comparison of the SYPRO Ruby-stained 2-DE profiles. A group of overexpressed spots was identified in the limited study set. Overexpressed spots were identified as clusterin by matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS) followed by peptide mass fingerprinting, a protein database search, and Western blot analysis. Additionally, sera of 80 preeclamptic women and 80 normal pregnant women were processed by immunoassay methods to confirm changes in clusterin concentrations quantitatively. Immunoassays showed that clusterin levels in the 80 preeclamptic women were significantly higher than those in the 80 controls (mean +/- SD; 1.62 +/- 0.46 times reference level in preeclamptic women vs. 1.30 +/- 0.46 times reference level in controls, P < 0.001). Proteomic analysis of serum proteins is a promising tool for studying preeclampsia pathophysiology and identifying proteins associated with preeclampsia.

Preeclampsia is associated with thrombosis of the intervillous or spiral artery. A deletion/insertion polymorphism (4G or 5G) in the promoter of the plasminogen activator inhibitor type 1 (PAI-1) gene is suggested to be involved in regulating the synthesis of the inhibitor, 4G allele, being associated with the enhanced gene expression and plasma PAI-1 levels. We assessed the association between preeclampsia and the 4G/5G polymorphism of the PAI-1 gene in 115 preeclamptic patients, 210 pregnant controls, and 298 healthy volunteer controls. The frequency of the homozygotes for the 4G allele was significantly higher in the patients than in the control pregnant women (P ϭ 0.04) or in the healthy volunteers (P ϭ 0.02). The 4G allele frequency was also significantly higher in the patients than in the control group of pregnant women (P ϭ 0.03) and in the healthy volunteers (P ϭ 0.02). These results suggest that the presence of the 4G/4G genotype of the PAI-1 gene is one of the risk factors for preeclampsia.

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The purpose of this study was to determine the proportion of fetal nucleated red blood cells (NRBCs) among enriched NRBCs and to evaluate the effectiveness of enriching NRBCs in maternal blood using fluorescence-activated cell sorting (FACS) to separate NRBCs. The origin of enriched NRBCs was determined using fluorescence in situ hybridization (FISH) methods. Y-specific signals were observed in 4.6 +/- 1.5 per cent of the enriched cells from 14 of 16 (87.5 per cent) pregnant women who gave birth to boys. In this series, the specificity of the fetal sex diagnosis was 100 per cent, the sensitivity 88 per cent, and the negative predictive value 86 per cent. Fetal NRBCs are present in maternal blood and FACS has the potential to enrich fetal NRBCs. Fetal cells were estimated to be enriched more than 10,000-fold in the first trimester and more than 100-fold in the third trimester. Average frequencies of fetal cells in maternal blood were 8.1 x 10(-5) and 1.6 x 10(-5) in the first trimester and the second/third trimesters. However, most of the NRBCs in maternal blood are maternal in origin.

BackgroundThere are many mobile phone apps aimed at helping women map their ovulation and menstrual cycles and facilitating successful conception (or avoiding pregnancy). These apps usually ask users to input various biological features and have accumulated the menstrual cycle data of a vast number of women.ObjectiveThe purpose of our study was to clarify how the data obtained from a self-tracking health app for female mobile phone users can be used to improve the accuracy of prediction of the date of next ovulation.MethodsUsing the data of 7043 women who had reliable menstrual and ovulation records out of 8,000,000 users of a mobile phone app of a health care service, we analyzed the relationship between the menstrual cycle length, follicular phase length, and luteal phase length. Then we fitted a linear function to the relationship between the length of the menstrual cycle and timing of ovulation and compared it with the existing calendar-based methods.ResultsThe correlation between the length of the menstrual cycle and the length of the follicular phase was stronger than the correlation between the length of the menstrual cycle and the length of the luteal phase, and there was a positive correlation between the lengths of past and future menstrual cycles. A strong positive correlation was also found between the mean length of past cycles and the length of the follicular phase. The correlation between the mean cycle length and the luteal phase length was also statistically significant. In most of the subjects, our method (ie, the calendar-based method based on the optimized function) outperformed the Ogino method of predicting the next ovulation date. Our method also outperformed the ovulation date prediction method that assumes the middle day of a mean menstrual cycle as the date of the next ovulation.ConclusionsThe large number of subjects allowed us to capture the relationships between the lengths of the menstrual cycle, follicular phase, and luteal phase in more detail than previous studies. We then demonstrated how the present calendar methods could be improved by the better grouping of women. This study suggested that even without integrating various biological metrics, the dataset collected by a self-tracking app can be used to develop formulas that predict the ovulation day when the data are aggregated. Because the method that we developed requires data only on the first day of menstruation, it would be the best option for couples during the early stages of their attempt to have a baby or for those who want to avoid the cost associated with other methods. Moreover, the result will be the baseline for more advanced methods that integrate other biological metrics.