Objective To explore the activity and its possible neural mechanism of brain default mode network by using resting state functional magnetic resonance imaging (fMRI) in patients with mild cognitive impairment (MCI). Methods The 20 amnestic MCI patients and 25 healthy controls were included in this study, and all subjects underwent mini-mental state examination (MMSE), auditory verbal learning test (AVLT) and fMRI. The data were analyzed by amplitude of low frequency fluctuation (ALFF), and the enhanced and weakened regions of ALFF were observed and compared in both MCI patients and healthy controls. Results MMSE and AVLT tests showed that the memory function was seriously impaired in MCI patients compared with healthy controls, which is based on the short and long delayed episodic memory impairment (2.4±1.7 vs. 6.6±1.4, t=3.70, P＜0.01; 2.1±1.6 vs. 6.7±1.5, t=4.16, P＜0.01). The resting state fMRI showed that MCI patients had significant decreases of ALFF in hippocampal formation, parahippocampal cortex and lateral temporal cortex as compared with health controls (t=2.58, 2.43 and 1.75, all P＜0.01), which were closely relevant to the episodic memory. And they had significant increases in temporal-parietal joint and inferior parietal lobule (t=3.14 and 2.77, both P＜0.01). Conclusions MCI patients show significant decreased active intensity of some DMN nodes that is related to episodic memory in resting state. Increased active intensity in MCI patients would be some type of compensation.

OBJECTIVE: The prior functional MRI studies have demonstrated significantly abnormal activity in the bilateral superior temporal gyrus (STG) of anxiety patients. The purpose of the current investigation was to determine whether the abnormal activity in these regions was related to a loss of functional connectivity between these regions. MATERIALS AND METHODS: Ten healthy controls and 10 anxiety patients underwent noninvasive fMRI while actively listening to emotionally neutral words alternated by silence (Task 1) or threat-related words (Task 2). The participants were instructed to silently make a judgment of each word's valence (i.e., unpleasant, pleasant, or neutral). A coherence analysis was applied to the functional MRI data to examine the functional connectivity between the left and the right STG, which was selected as the primary region of interest on the basis of our prior results. RESULTS: The data demonstrated that the anxiety patients exhibited significantly increased activation in the bilateral STG than the normal controls. The functional connectivity analysis indicated that the patient group showed significantly decreased degree of connectivity between the bilateral STG during processing Task 2 compared to Task 1 (t = 2.588, p = 0.029). In addition, a significantly decreased connectivity was also observed in the patient group compared to the control group during processing Task 2 (t = 2.810, p = 0.012). CONCLUSION: Anxiety patients may exhibit increased activity of the STG but decreased functional connectivity between the left and right STG, which may reflect the underlying neural abnormality of anxiety disorder, and this will provide new insights into this disease.
Adult ; Anxiety Disorders/pathology/*physiopathology ; Case-Control Studies ; Emotions/physiology ; Female ; Humans ; Magnetic Resonance Imaging/*methods ; Male ; Middle Aged ; Temporal Lobe/pathology/*physiopathology

Objective:To compare the curative effects of different venous cannulas and drainage to improve patient's whole body oxygenation during the auxiliary process of venous-arterial extracorporeal membrane oxygenation (VA-ECMO) in lung transplantation.Methods:From December 2016 to December 2019, 12 patients who were assisted by VA-ECMO in one lung transplantation in People's Hospital of Henan Province were selected as the research objects. According to the number of side holes of venous cannulas, they were divided into two groups: one group with few side holes and other group with multiple side holes. The differences in blood gas indexes among the right radial artery, left radial artery, and right internal jugular vein before and after assistance were compared, and the assistance effect was evaluated.Results:The arterial partial pressure of oxygen (PaO 2) of blood gas indexes of the right and left radial arteries in both groups were significantly higher than that before assistance [mmHg (1 mmHg = 0.133 kPa): right and left radial artery in few side holes group: 79.5±4.2 vs. 48.3±3.8 and 88.1±3.5 vs. 48.3±3.8; right and left radial artery in multiple side holes group: 67.7±5.9 vs. 48.7±3.2 and 84.0±3.8 vs. 48.7±3.2, all P < 0.05]. The arterial partial pressure of carbon dioxide (PaCO 2) of blood gas index was significantly lower than that before assistance (mmHg: 44.2±2.6 vs. 71.7±4.4 for the right radial artery and 44.7±1.4 vs. 71.7±4.4 for the left radial artery in the group with few side holes; 46.2±2.1 vs. 71.2±3.5 for the right radial artery and 44.1±1.9 vs. 71.2±3.5 for the left radial artery in the group with multiple side holes, all P < 0.05). The partial pressure of oxygen in venous blood (PvO 2) of blood gas index of ECMO system in the group with few side holes was significantly lower than that of the multiport side holes group (mmHg: 56.4±3.2 vs. 88.7±1.5, P < 0.01), and the partial pressure of carbon dioxide in venous blood (PvCO 2) was significantly higher than that of multiport side holes group (mmHg: 63.6±3.7 vs. 44.2±1.7, P < 0.01). Conclusions:When VA-ECMO is used in lung transplantation, the superior vena cava blood flow can be fully drained by using intravenous cannula with few side holes. It can effectively improve the oxygenation of the upper body of lung transplant patients, avoid the dilemma of hypoxemia in the upper body and hyperxemia in the lower body, provide more effective assistance to patients undergoing single lung transplantation, and is more meaningful for improving the oxygenation status of the whole body in patients undergoing single lung transplantation.

【Objective】 To construct the eukaryotic expression vector carrying the human wild-type p27 and lacking nuclear localization signal p27△NLS coding sequences， and the express them in HEK293T cells， which may contribute to investigating the different locations and roles of p27 in the cytoplasm and nucleus. 【Methods】 Total RNA was prepared from human breast cancer MCF7 cells， and cDNA was obtained by reverse transcription-polymerase chain reaction （RT-PCR）. After amplification of the p27 CDs and non-NLS fragments by PCR， full length p27WT （CDKN1B， NM_004064.5） and p27△NLS coding regions were obtained. PCR products were then subcloned into the eukaryotic expression vector pCMV-Blank. After identification with bacterial PCR， double restriction enzyme digestion and sequencing， they were defined officially as pCMV-p27WT and pCMV-p27△NLS， respectively. The recombinant plasmids were transfected into HEK293T cells by electroporation. After 48 h， the levels of p27 protein in the cytoplasm and nucleus were detected by Western blotting. 【Results】 The sequencing results showed that the sequences of p27WT and p27△NLS inserted into the plasmids were both correctly consistent with that of NM_004064.5. After transfection with pCMV-p27WT， total p27 protein expression was increased and distributed in both the cytoplasm and nucleus of HEK293T cells. After transfection with pCMV-p27△NLS， p27 protein was significantly increased and almost entirely localized in the cytoplasm of HEK293T cells. 【Conclusion】 The eukaryotic expression plasmids of human p27WT and p27△NLS coding sequences were successfully constructed and overexpressed in HEK293T cells. This research may lay a foundation for investigating the biological function of p27 in the cell cycle progression of tumor cells.

Objective To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. Methods Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People’s Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients’radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients’radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. Results The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = −5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. Conclusions The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.