Non-invasive prediction of preeclampsia using the maternal plasma cell-free DNA profile and clinical risk factors

BackgroundPreeclampsia (PE) is a pregnancy complication defined by new onset hypertension and proteinuria or other maternal organ damage after 20 weeks of gestation. Although non-invasive prenatal testing (NIPT) has been widely used to detect fetal chromosomal abnormalities during pregnancy, its performance in combination with maternal risk factors to screen for PE has not been extensively validated. Our aim was to develop and validate classifiers that predict early- or late-onset PE using the maternal plasma cell-free DNA (cfDNA) profile and clinical risk factors.MethodsWe retrospectively collected and analyzed NIPT data of 2,727 pregnant women aged 24–45 years from four hospitals in China, which had previously been used to screen for fetal aneuploidy at 12 + 0 ~ 22 + 6 weeks of gestation. According to the diagnostic criteria for PE and the time of diagnosis (34 weeks of gestation), a total of 143 early-, 580 late-onset PE samples and 2,004 healthy controls were included. The wilcoxon rank sum test was used to identify the cfDNA profile for PE prediction. The Fisher’s exact test and Mann–Whitney U-test were used to compare categorical and continuous variables of clinical risk factors between PE samples and healthy controls, respectively. Machine learning methods were performed to develop and validate PE classifiers based on the cfDNA profile and clinical risk factors.ResultsBy using NIPT data to analyze cfDNA coverages in promoter regions, we found the cfDNA profile, which was differential cfDNA coverages in gene promoter regions between PE and healthy controls, could be used to predict early- and late-onset PE. Maternal age, body mass index, parity, past medical histories and method of conception were significantly differential between PE and healthy pregnant women. With a false positive rate of 10%, the classifiers based on the combination of the cfDNA profile and clinical risk factors predicted early- and late-onset PE in four datasets with an average accuracy of 89 and 80% and an average sensitivity of 63 and 48%, respectively.ConclusionIncorporating cfDNA profiles in classifiers might reduce performance variations in PE models based only on clinical risk factors, potentially expanding the application of NIPT in PE screening in the future

Application of various genetic analysis techniques for detecting two rare cases of 9p duplication mosaicism during prenatal diagnosis

Abstract Background The identification of genetic mosaicism and the genetic counseling needed following its discovery have been challenging problems in the field of prenatal diagnosis. Herein, we describe the clinical phenotypes and various prenatal diagnostic processes used for two rare cases of 9p duplication mosaicism and review the prior literature in the field to evaluate the merits of different methods for diagnosing mosaic 9p duplication. Methods We recorded ultrasound examinations, reported the screening and diagnosis pathways, and analyzed the mosaic levels of the two cases of 9p duplication using karyotype analysis, chromosomal microarray analysis (CMA), and fluorescence in situ hybridization analysis (FISH). Results Case 1 had a normal clinical phenotype for tetrasomy 9p mosaicism, and Case 2 showed multiple malformations caused by both trisomy 9 and trisomy 9p mosaicism. Both cases were initially suspected after non‐invasive prenatal screening (NIPT) based on cell‐free DNA. The mosaic ratio of 9p duplication found via karyotyping was lower than what was discovered by CMA and FISH, in both cases. Contrary to previous findings, the mosaic level of trisomy 9 found by karyotype analysis was greater than what was found by CMA, in terms of complex mosaicism involving trisomy 9 and trisomy 9p, in Case 2. Conclusion NIPT can indicate 9p duplication mosaicism during prenatal screening. Different strengths and limitations existed in terms of diagnosing mosaic 9p duplication by karyotype analysis, CMA, and FISH. The combined use of various methods may be capable of more accurately determining break‐points and mosaic levels of 9p duplication during prenatal diagnosis

Overexpression of OLC1 in Lung Squamous Cell Carcinoma Tissues is Associated with Poor Prognosis of Patients

Background and objective OLC1 (overexpressed in lung cancer 1), screened out and cloned in our previous research, is a new gene associated with lung cancer. It is highly expressed in lung cancer and many other malignant tumors, and is associated with poor prognosis of esophageal squamous cell carcinoma, ovarian cancer, breast cancer and colorectal cancer. The aim of this research was to detect the expression level of OLC1 in the tumor tissues of lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) and explore its relationship with the prognosis of lung cancer patients. Methods Lung cancer tissues of 108 SCC and 90 ADC was dealed with immunohistochemical staining to detect the expression level of OLC1. The relationship between the expression level of OLC1 and clinical parameters and prognosis was analyzed. Results The rate of high expression of OLC1 staining in ADC was significantly higher than that in SCC (87.5% vs 55.3%, P<0.001). The overexpression of OLC1 in tumor tissues did not have a significant relationship with the prognosis of patients with ADC, but it was related with a poor prognosis of SCC patients as the univariate analysis showed. However the multivariate regression analysis showed that correlation between the overexpression of OLC1 and poor prognosis of SCC patients did not have a statistical significance (P=0.05). Conclusion The expression of OLC1 in ADC might be higher than that in SCC. A higher score of OLC1 staining in tumor tissue was associated with a poorer prognosis of patients with SCC, but could not be an independent predictor for a shorter overall survival in patients with SCC

Confidential-DPproof: Confidential Proof of Differentially Private Training

International audiencePost hoc privacy auditing techniques can be used to test the privacy guarantees of a model, but come with several limitations: (i) they can only establish lower bounds on the privacy loss, (ii) the intermediate model updates and some data must beshared with the auditor to get a better approximation of the privacy loss, and (iii) the auditor typically faces a steep computational cost to run a large number of attacks. In this paper, we propose to proactively generate a cryptographic certificate of privacy during training to forego such auditing limitations. We introduce Confidential-DPproof , a framework for Confidential Proof of Differentially Private Training, which enhances training with a certificate of the (ε, δ)-DP guarantee achieved. To obtain this certificate without revealing information about the training data or model, we design a customized zero-knowledge proof protocol tailored to the requirements introduced by differentially private training, including random noise addition and privacy amplification by subsampling. In experiments on CIFAR-10, Confidential-DPproof trains a model achieving state-of-the-art 91% test accuracy with a certified privacy guarantee of (ε = 0.55, δ = 10−5)-DP in approximately 100 hours

PI3K/Akt Signaling Pathway Modulates Influenza Virus Induced Mouse Alveolar Macrophage Polarization to M1/M2b

<div><p>Macrophages polarized to M1 (pro-inflammation) or M2 (anti-inflammation) phenotypes in response to environmental signals. In this study, we examined the polarization of alveolar macrophage (AM), following induction by different influenza virus strains (ST169 (H1N1), ST602 (H3N2) and HKG9 (H9N2)). Macrophages from other tissues or cell line exert alternative responding pattern, and AM is necessary for investigating the respiratory system. AM polarized toward the M1 phenotype after 4 hours of infection by all three virus strains, and AM to presented M2b phenotype after 8 hours induction, and immunosuppressive phenotype after 24 hours of induction. Protein expression assay showed similar results as the gene expression analysis for phenotype verification. The ELISA assay showed that TNF-α secretion was up-regulated after 4 and 8 hours of infection by influenza viruses, and it returned to basal levels after 24 hours of infection. IL-10 expression was elevated after 8 and 24 hours of infection. Immunofluorescence showed that iNOS expression was up-regulated but not Arg1 expression. Influenza virus notably increased phospho-Akt but not phospho-Erk1/2 or phospho-p38, and the AM polarization pattern have been changed by LY294002 (PI3K inhibitor). In conclusion, our results demonstrate the dynamic polarization of AM induced by influenza viruses, and suggested that PI3K/Akt signaling pathway modulates AM polarization to M1/M2b.</p></div

AM was treated with a given PI3K/Akt inhibitor, LY294002, for 1 h before stimulation by ST169 (H1N1), ST602 (H3N2) and HKG9 (H9N2).

<p>The LY294002 remarkable down regulate the macrophage polarization markers, such as, TNF-α, iNOS, MCP1 and IL-10. *p<0.05, **p<0.01.</p

AM was infected by influenza viruses at 2 MOI, and immunostained for iNOS and Arg1 at the indicated times.

<p>The nucleus was stained with Hoechst (blue). Exposure to negative control (virus culture medium) resulted in an iNOS^lowArg1^low phenotype at the three time pointes. Viruses infected AM induced iNOS (green) but not Arg1 (red) expression after 4 hours and 8 hours induction, after 24 hours induction, virus induced AM an iNOS^lowArg1^low phenotype similar to negative control.</p

The Quantity and Purity of AM.

<p>(A) showed that AM was detected by flow cytometry, result (a) showed that AM (R1, framed region) is 51.1% of BAL cells. (b) and (c) showed AM is framed as Alexa Fluor 488 labeled F4/80 positive cells (d) showed AM was purified by adhere to the plate and the purity was detected as 95.2% by flow cytometry. (B) showed AM was purified by adhere to the coverslip, Alexa Fluor 488 labeled rabbit anti mouse F4/80 was used as the macrophage membrane marker, and the nuclear was stained by Hoechst, negative cells were red arrow headed; negative (MDCK cells) and positive (Raw264.7 cells) control was processed follow the same condition. (C) showed the purity from five independent microscope captures (of picture B) was detected as 96.8%.</p

Gene expression of AM infected by influenza viruses at 2 MOI in vitro after 4 hours.

<p>Results are expressed as a ratio to mock-inoculated cells after 4 hours induction. ST169 (H1N1), ST602 (H3N2) and HKG9 (H9N2) promote M1 polarization of AM. mRNA levels of M1, M2 and Toll like receptors genes of AM was analyzed by qRT-PCR. All genes were normalized to GAPDH expression. Set as 1 and indicated by the horizontal X-axis, four duplication per gene was detected. ↑ =  mild upregulated (P<0.05), ↓ = mild downregulated (P<0.05); ↑↑ =  dramatically upregulated (p<0.01), ↓↓ = dramatically downregulated (P<0.01), the significant fold change were numbered. Three independent experiments have been processed.</p

Gene expression of AM infected by influenza viruses in vitro at 2 MOI after 24 hours.

<p>Results are expressed as a ratio to mock-inoculated cells after 24 hours induction. ST169 (H1N1) and ST602 (H3N2) promoted immunosuppression of AM whereas HKG9 (H9N2) induced potential M2 pattern. mRNA levels of M1, M2 and Toll like receptors genes of AM was analyzed by qRT-PCR. Set as 1 and indicated by the horizontal X axis, four duplication per gene was detected. ↑ =  mild upregulated (P<0.05), ↓ = mild downregulated (P<0.05); ↑↑ = dramatically upregulated (p<0.01), ↓↓ = dramatically downregulated (P<0.01), the significant fold change were numbered. Three independent experiments have been processed.</p