Characterization of GDP-mannose Pyrophosphorylase from Escherichia Coli O157:H7 EDL933 and Its Broad Substrate Specificity

GDP-mannose pyrophosphorylase gene (ManC) of Escherichia coli (E. coli) O157 was cloned and expressed as a highly soluble protein in E. coli BL21 (DE3). The enzyme was subsequently purified using hydrophobic and ion exchange chromatographies. ManC showed very broad substrate specificities for four nucleotides and various hexose-1-phosphates, yielding ADP-mannose, CDP-mannose, UDP-mannose, GDP-mannose, GDP-glucose and GDP-2-deoxy-glucose

Increased pulsatility index of the basilar artery is a risk factor for neurological deterioration after stroke: a case control study

Background : Higher pulsatility of the middle cerebral artery (MCA) is known to be associated with stroke progression. We investigated whether pulsatility index (PI) of the basilar artery (BA) can predict neurological deterioration (ND) after acute cerebral infarction. Methods : A total of 708 consecutive patients with acute ischemic stroke who had undergone transcranial Doppler (TCD) ultrasonography were included. ND was defined as an increase in the National Institutes of Health Stroke Scale scores by two or more points after admission. The patients were categorized into quartiles according to BA PI. Multivariable logistic regression analysis was performed to examine whether BA PI is independently associated with ND. Results : BA PI was well correlated with the right (n = 474, r2 = 0.573, P < 0.001) by Pearson correlation analysis although MCA PI could not be measured from right MCA (n = 234, 33.05%) and left MCA (n = 252, 35.59%) by TCD owing to insufficient temporal bone window. Multivariable logistic regression analysis including age, sex, cerebral atherosclerosis burden, National Institutes of Health Stroke Scale at admission, and the proportion of patients with current smoking status, hypertension, diabetes mellitus, atrial fibrillation revealed that the higher BA PI (odds ratio, 3.28; confidence interval, 1.07–10.17; P = 0.038) was independently associated with ND. Conclusions : BA PI, which would be identified regardless of temporal window, could predict ND among acute stroke patients.The work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03029909, NRF-2019R1F1A1059455) and by the Korean Society of Hypertension (2019). The funding has no role in design, collection, analysis, or interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication

Use of the Clock Drawing Test and the Rey–Osterrieth Complex Figure Test-copy with convolutional neural networks to predict cognitive impairment

Background The Clock Drawing Test (CDT) and Rey–Osterrieth Complex Figure Test (RCFT) are widely used as a part of neuropsychological test batteries to assess cognitive function. Our objective was to confirm the prediction accuracies of the RCFT-copy and CDT for cognitive impairment (CI) using convolutional neural network algorithms as a screening tool. Methods The CDT and RCFT-copy data were obtained from patients aged 60–80 years who had more than 6 years of education. In total, 747 CDT and 980 RCFT-copy figures were utilized. Convolutional neural network algorithms using TensorFlow (ver. 2.3.0) on the Colab cloud platform ( www.colab.research.google.com ) were used for preprocessing and modeling. We measured the prediction accuracy of each drawing test 10 times using this dataset with the following classes: normal cognition (NC) vs. mildly impaired cognition (MI), NC vs. severely impaired cognition (SI), and NC vs. CI (MI + SI). Results The accuracy of the CDT was better for differentiating MI (CDT, 78.04 ± 2.75; RCFT-copy, not being trained) and SI from NC (CDT, 91.45 ± 0.83; RCFT-copy, 90.27 ± 1.52); however, the RCFT-copy was better at predicting CI (CDT, 77.37 ± 1.77; RCFT, 83.52 ± 1.41). The accuracy for a 3-way classification (NC vs. MI vs. SI) was approximately 71% for both tests; no significant difference was found between them. Conclusions The two drawing tests showed good performance for predicting severe impairment of cognition; however, a drawing test alone is not enough to predict overall CI. There are some limitations to our study: the sample size was small, all the participants did not perform both the CDT and RCFT-copy, and only the copy condition of the RCFT was used. Algorithms involving memory performance and longitudinal changes are worth future exploration. These results may contribute to improved home-based healthcare delivery.The costs for manuscript publication, design of the study, data management, and writing of the manuscript were supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A6A3A01078538)