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Objective To explore the clinical significance of non-invasive prenatal genetic testing to screen prenatal fetal chromosomal abnormalities. Methods Peripheral blood was collected from 6 283 pregnant women who underwent non-invasive prenatal genetic testing at our hospital, and fetal DNA was extracted and purified for analysis. The complementary base principle of semiconductor chip technology was used to analyze all sequenced signals with BioelectronSeq 4000. Invasive prenatal diagnosis was performed in high-risk pregnant women according to the results of the sex chromosome sequencing signal analysis. Results Of the 6 283 pregnant women screened, 14 were found to have chromosomal abnormalities, and the positive rate was 0. 22％. Karyotype analysis was performed on 11 of the women; the remaining 3 refused to be diagnosed. Of these 11 women, 2 of the 5 patients with a high risk of XO were diagnosed with fetal chromosomal abnormalities (diagnosed as XO/XXX chimera and XO, respectively), and 3 were diagnosed with a normal karyotype; 5 patients with a high risk of XXY were diagnosed as XXY; and 1 patient with a high risk of XXX was confirmed as XXX. NIPT accuracy was measured to be 73％ (8/11). The detection rate of fetal chromosomal abnormalities by non-invasive prenatal genetic testing was significantly higher in the years 2015-2016 than in 2011-2014 (P ＜ 0. 05). Conclusion Non-invasive prenatal genetic testing for screening chromosomal abnormalities has a high accuracy rate and could improve the detection rate of fetal chromosomal abnormalities.
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7 T high field magnetic resonance imaging (MRI) provides a useful tool for microscopic spatial resolution visualizing anatomy. In addition, it enables the observation and analysis of tissue metabolism and function. 7 T MRI is now developing fast both in its technology and in its potential prospective medical applications. This review introduces current applications and possible future developments of the 7 T MRI in the field of human brain imaging for clinical studies and practices.
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Humans , Brain , Pathology , Brain Diseases , Pathology , Image Enhancement , Methods , Magnetic Resonance Imaging , Methods , NeuroimagingABSTRACT
To correctly classify EEG with different mental tasks, a new learning algorithm for Evolving Cascade Neural Networks (ECNNs) is described to avoid over-fitting of a neural network due to noise and redundant features. The learning algorithm calculates the value of a fitness function on validate set and accordingly updates the connection weights on training set. The learning algorithm uses the regularity criterion for selecting the neurons with relevant connection. If the value Cr calculated for the rth neuron is less than the value Cr-1 calculated for the previous (r-1) neuron, the features that feed the rth neuron are relevant, else they are irrelevant. An ECNN starts to learn with one input node and then, adding new inputs as well as new hidden neurons, evolves it. The trained ECNN has a nearly minimal number of input and hidden neurons as well as connections. The algorithm is applied to classify EEG with two mental tasks. The trained ECNN has correctly classified 83.1% of the testing segments. It shows a better result, compared with a standard BP network.
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Humans , Algorithms , Electroencephalography , Methods , Neural Networks, Computer , Signal Processing, Computer-AssistedABSTRACT
AIM:To investigate the effects of aminophylline used early in resuscitation on achievement ratio of resuscitation,the concentrations of plasma norepinephrine(NE),adenosine and nitric oxide(NO),and the levels of cardiac tissue endothelin-1(ET-1)and adenosine in rats with sudden cardiac arrest.METHODS:Sixty SD rats were randomly divided into three groups:operated control(group A),epinephrine treatment(group B),and epinephrine plus aminophylline treatment(group C).Each group had 20 rats.The concentrations of plasma NE,adenosine and NO,and the levels of cardiac tissue ET-1 and adenosine were examined in group A and 30 min after survived in group B and group C.RESULTS:The duration of circulation recovered in group C was less than that in group B,significantly(P0.05).The concentrations of plasma adenosine and NE,and the levels of cardiac tissue ET-1 and adenosine in group B and group C were higher than those in group A significantly(P
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The duration of QRS wave,P wave and T wave of ECG can be computerized auto-detected with digital signal process and waveform recognition technology. It can diagnose 15 kinds of abnormal ECG such as ventricular presystole automatically and print out corresponding diagnosis reports. In order to verify the systems stability and creditability, we used American MIT-BIH database to test our algorithms and got a good result.