OBJECTIVE To investigate the distribution and drug resistance of multidrug-resistant bacteria in the neonatal intensive care unit of a three-A children's hospital in Henan Province,and to provide reference for ational drug use in clinical practice.METHODS Clinical specimens from hospitalized newborns in neonatal intensive care unit from a three-A children's hospital from Jan.1,2019 to Dec.31,2023 were subjected to etiological exam-ination and drug sensitivity test,and to analyze the distribution and drug resistance of multidrug-resistant bacteri-a in hospitalized newborns.RESULTS During the 5-year period,1139 strains of multidrug-resistant bacteria were i-solated,including 229 gram-positive bacteria(20.11％)and 910 gram-negative bacteria(79.89％).There were 92 strains of methicillin-resistant Staphylococcus aureus(MRSA)(accounting for 8.08％),57 strains(accounting for 5.00％)of methicillin-resistant coagulase-negative Staphylococcus epidermidis and 28 strains(accounting for 2.46％)of methicillin-resistant coagulase-negative human Staphylococcus.370 strains(accounting for 32.48)of carbapenem-resistant Klebsiella pneumoniae(CRKP),268 strains(accounting for 23.53％)of extenspectrum β-lactamase-producing Escherichia coli and 85 strains(accounting for 7.46％)of K.pneumoniae,there were 767 sputum specimens(67.34％),160 blood specimens from peripheral intravenous puncture and central venous cath-eterization(PICC)(14.05％),63 bronchoalveolar lavage fluid specimens(5.53％),29 secretion specimens(eye and wound secretions)(2.54％),and 120 other specimens(10.54％).K.pneumoniae and E.coli producing su-per-broad spectrum β-lactamase,CRKP and MRSA were the main drug-resistant bacteria.CONCLUSION The sit-uation of drug resistance in neonatal intensive care unit is serious,therefore monitoring bacterial resistance should be strengthened according to the clinical laboratory results,and antibiotics should be applied rationally.

Objective:To investigate the characteristics of resting-state mirror homotopic connectivity and the gray matter volume of brain in patients with neuropsychiatric systemic lupus erythematosus (NPSLE).Methods:From June 2020 to March 2023, a total of 35 NPSLE patients (NPSLE group) and 30 non-NPSLE patients (non-NPSLE group) were selected from Taizhou People's Hospital Affiliated to Nanjing Medical University, another 31 healthy volunteers were recruited as the healthy controls(HC group). All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) and mini-mental state examination (MMSE) assessments. The patients in NPSLE and non-NPSLE groups were additionally assessed using the fatigue scale for motor and cognitive functions (FSMC) and the hospital anxiety and depression scale (HADS).The DPABI V7.0 toolkit based on the MATLAB platform was used to preprocess the rs-fMRI data and calculate the voxel-mirrored homotopic connectivity(VMHC) indexes, and the differences in VMHC between groups were evaluated by covariance analysis in SPM12.0 software, and the VMHC values of brain regions with significant differences were extracted for further comparison between the two groups.Partial correlation analysis was performed to investigate the association between VMHC values and clinical parameters in NPSLE patients.The brain regions with significant differences between NPSLE patients and non-NPSLE patients were used as region of interest (ROI), and gray matter volumes within these ROIs were then calculated by VBM8 toolbox.Results:(1)There were statistically significant differences in the VMHC values of bilateral precentral gyrus, bilateral dorsolateral superior frontal gyrus, bilateral medial and paracingulate gyrus, bilateral parahippocampal gyrus, bilateral middle occipital gyrus, bilateral postcentral gyrus, and bilateral superior temporal gyrus among the 3 groups( F=11.246-14.102, all P<0.05). The NPSLE group exhibited significantly lower VMHC values in these regions compared to both the non-NPSLE group and HC group (all P<0.05), but there were no significant differences in these regions between the non-NPSLE group and HC group (all P>0.05).(2) The gray matter volumes of bilateral dorsolateral superior frontal gyrus(right: (0.57±0.11)mm 3, (0.65±0.08)mm 3, t=-3.409, P=0.001; left: (0.53±0.10)mm 3, (0.60±0.07)mm 3, t=-3.082, P=0.003), bilateral precentral gyrus(right: (0.32±0.06)mm 3, (0.35±0.04)mm 3, t=-2.044, P=0.045; left: (0.39±0.06)mm 3, (0.42±0.04)mm 3, t=-2.505, P=0.015), right medial and paracingulate gyrus((0.66±0.08)mm 3, (0.70±0.07)mm 3, t=-2.491, P=0.015) and left superior temporal gyrus((0.57±0.09)mm 3, (0.61±0.06)mm 3, t=- 2.344, P=0.022) in the NPSLE group were smaller than those of non-NPSLE group.(3)Correlation analysis showed that the VMHC value of dorsolateral superior frontal gyrus was positively correlated with IgA level in NPSLE patients ( r=0.353, P=0.047). Conclusion:Patients with NPSLE generally have decreased mirror homotopy functional connectivity in the cerebral hemispheres, accompanied by a decrease in gray matter volume in some brain regions, which can provide a certain neuroimaging basis for the pathogenesis of brain injury.

Objective:To investigate the predictive value of computed tomography(CT) based radiomics model for the prognosis of patients with pancreatic ductal adenocarcinoma(PDAC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 206 PDAC patients who were admitted to Zhongshan Hospital of Fudan University from August 2018 to December 2020 were collected. There were 115 males and 91 females, aged (64±9)years. All 206 pati-ents underwent enhanced CT examination. Based on radom number table, the 206 patients were randomly divided into a training set of 165 cases and a validation set of 41 cases with a ratio of 4∶1. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) follow-up; (2) analysis of prognostic factors of PDAC patients in the training set; (3) construction and evaluation of prediction model for prognosis of PDAC patients. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Wilcoxon W test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. The Kaplan-Meier method was used to calculate the survival rate and Log-rank test was used for survival analysis. Univariate and multivariate analyses were conducted using the COX regression model. The PyCharm software was used for the least absolute shrinkage and selection operator method (LASSO)-COX regression analysis. The receiver operating characteristic curve was plotted to evaluate the performance of radiomics model. Results:(1)Follow-up. Of the 206 patients,205 cases were followed up for 17.1(range, 12.0?40.1)months. The postoperative 1-, 2-, 3-year survival rates were 80.10%, 29.61% and 4.85%. (2) Analysis of prognostic factors for PDAC patients in the training dataset. Results of multivariate analysis showed that pathological N stage was an independent influencing factor for prognosis of PDAC patients in the training set ( hazard ratio=1.476, 95% confidence interval as 1.054?2.067, P<0.05). (3) Construction and evaluation of prediction model for prognosis of PDAC patients. A total of 1 595 radiomics features were finally extracted from the 206 patients. By intra-group feature selection and dimensionality reduction using LASSO-COX regression model, 10 radiomics features were obtained. Combined with 10 radiomics features and 11 clinical features, using the LASSO-COX regression analysis, 15 features were finally extracted to construct the CT based radiomics model for predicting prognosis of PDAC. The areas under receiver operating characteristic curve of the prediction model in predicting 2-year and 3-year overall survival rates of PDAC patients in the training set were 0.834 (95% confidence interval as 0.777?0.891) and 0.883 (95% confidence interval as 0.834?0.932), respectively. The area under curve of the prediction model for patients in the validation set was 0.606 (95% confidence interval as 0.456?0.756) and 0.625 (95% confidence interval as 0.477?0.773). Conclusion:The prediction model constructed on CT based radiomics features and clinical features for predicting the prognosis of PDAC patients shows a promising prediction efficiency.

Objective:To investigate the characteristics of resting-state mirror homotopic connectivity and the gray matter volume of brain in patients with neuropsychiatric systemic lupus erythematosus (NPSLE).Methods:From June 2020 to March 2023, a total of 35 NPSLE patients (NPSLE group) and 30 non-NPSLE patients (non-NPSLE group) were selected from Taizhou People's Hospital Affiliated to Nanjing Medical University, another 31 healthy volunteers were recruited as the healthy controls(HC group). All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) and mini-mental state examination (MMSE) assessments. The patients in NPSLE and non-NPSLE groups were additionally assessed using the fatigue scale for motor and cognitive functions (FSMC) and the hospital anxiety and depression scale (HADS).The DPABI V7.0 toolkit based on the MATLAB platform was used to preprocess the rs-fMRI data and calculate the voxel-mirrored homotopic connectivity(VMHC) indexes, and the differences in VMHC between groups were evaluated by covariance analysis in SPM12.0 software, and the VMHC values of brain regions with significant differences were extracted for further comparison between the two groups.Partial correlation analysis was performed to investigate the association between VMHC values and clinical parameters in NPSLE patients.The brain regions with significant differences between NPSLE patients and non-NPSLE patients were used as region of interest (ROI), and gray matter volumes within these ROIs were then calculated by VBM8 toolbox.Results:(1)There were statistically significant differences in the VMHC values of bilateral precentral gyrus, bilateral dorsolateral superior frontal gyrus, bilateral medial and paracingulate gyrus, bilateral parahippocampal gyrus, bilateral middle occipital gyrus, bilateral postcentral gyrus, and bilateral superior temporal gyrus among the 3 groups( F=11.246-14.102, all P<0.05). The NPSLE group exhibited significantly lower VMHC values in these regions compared to both the non-NPSLE group and HC group (all P<0.05), but there were no significant differences in these regions between the non-NPSLE group and HC group (all P>0.05).(2) The gray matter volumes of bilateral dorsolateral superior frontal gyrus(right: (0.57±0.11)mm 3, (0.65±0.08)mm 3, t=-3.409, P=0.001; left: (0.53±0.10)mm 3, (0.60±0.07)mm 3, t=-3.082, P=0.003), bilateral precentral gyrus(right: (0.32±0.06)mm 3, (0.35±0.04)mm 3, t=-2.044, P=0.045; left: (0.39±0.06)mm 3, (0.42±0.04)mm 3, t=-2.505, P=0.015), right medial and paracingulate gyrus((0.66±0.08)mm 3, (0.70±0.07)mm 3, t=-2.491, P=0.015) and left superior temporal gyrus((0.57±0.09)mm 3, (0.61±0.06)mm 3, t=- 2.344, P=0.022) in the NPSLE group were smaller than those of non-NPSLE group.(3)Correlation analysis showed that the VMHC value of dorsolateral superior frontal gyrus was positively correlated with IgA level in NPSLE patients ( r=0.353, P=0.047). Conclusion:Patients with NPSLE generally have decreased mirror homotopy functional connectivity in the cerebral hemispheres, accompanied by a decrease in gray matter volume in some brain regions, which can provide a certain neuroimaging basis for the pathogenesis of brain injury.

Objective:To investigate the predictive value of computed tomography(CT) based radiomics model for the prognosis of patients with pancreatic ductal adenocarcinoma(PDAC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 206 PDAC patients who were admitted to Zhongshan Hospital of Fudan University from August 2018 to December 2020 were collected. There were 115 males and 91 females, aged (64±9)years. All 206 pati-ents underwent enhanced CT examination. Based on radom number table, the 206 patients were randomly divided into a training set of 165 cases and a validation set of 41 cases with a ratio of 4∶1. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) follow-up; (2) analysis of prognostic factors of PDAC patients in the training set; (3) construction and evaluation of prediction model for prognosis of PDAC patients. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Wilcoxon W test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. The Kaplan-Meier method was used to calculate the survival rate and Log-rank test was used for survival analysis. Univariate and multivariate analyses were conducted using the COX regression model. The PyCharm software was used for the least absolute shrinkage and selection operator method (LASSO)-COX regression analysis. The receiver operating characteristic curve was plotted to evaluate the performance of radiomics model. Results:(1)Follow-up. Of the 206 patients,205 cases were followed up for 17.1(range, 12.0?40.1)months. The postoperative 1-, 2-, 3-year survival rates were 80.10%, 29.61% and 4.85%. (2) Analysis of prognostic factors for PDAC patients in the training dataset. Results of multivariate analysis showed that pathological N stage was an independent influencing factor for prognosis of PDAC patients in the training set ( hazard ratio=1.476, 95% confidence interval as 1.054?2.067, P<0.05). (3) Construction and evaluation of prediction model for prognosis of PDAC patients. A total of 1 595 radiomics features were finally extracted from the 206 patients. By intra-group feature selection and dimensionality reduction using LASSO-COX regression model, 10 radiomics features were obtained. Combined with 10 radiomics features and 11 clinical features, using the LASSO-COX regression analysis, 15 features were finally extracted to construct the CT based radiomics model for predicting prognosis of PDAC. The areas under receiver operating characteristic curve of the prediction model in predicting 2-year and 3-year overall survival rates of PDAC patients in the training set were 0.834 (95% confidence interval as 0.777?0.891) and 0.883 (95% confidence interval as 0.834?0.932), respectively. The area under curve of the prediction model for patients in the validation set was 0.606 (95% confidence interval as 0.456?0.756) and 0.625 (95% confidence interval as 0.477?0.773). Conclusion:The prediction model constructed on CT based radiomics features and clinical features for predicting the prognosis of PDAC patients shows a promising prediction efficiency.

OBJECTIVE To investigate the distribution and drug resistance of multidrug-resistant bacteria in the neonatal intensive care unit of a three-A children's hospital in Henan Province,and to provide reference for ational drug use in clinical practice.METHODS Clinical specimens from hospitalized newborns in neonatal intensive care unit from a three-A children's hospital from Jan.1,2019 to Dec.31,2023 were subjected to etiological exam-ination and drug sensitivity test,and to analyze the distribution and drug resistance of multidrug-resistant bacteri-a in hospitalized newborns.RESULTS During the 5-year period,1139 strains of multidrug-resistant bacteria were i-solated,including 229 gram-positive bacteria(20.11％)and 910 gram-negative bacteria(79.89％).There were 92 strains of methicillin-resistant Staphylococcus aureus(MRSA)(accounting for 8.08％),57 strains(accounting for 5.00％)of methicillin-resistant coagulase-negative Staphylococcus epidermidis and 28 strains(accounting for 2.46％)of methicillin-resistant coagulase-negative human Staphylococcus.370 strains(accounting for 32.48)of carbapenem-resistant Klebsiella pneumoniae(CRKP),268 strains(accounting for 23.53％)of extenspectrum β-lactamase-producing Escherichia coli and 85 strains(accounting for 7.46％)of K.pneumoniae,there were 767 sputum specimens(67.34％),160 blood specimens from peripheral intravenous puncture and central venous cath-eterization(PICC)(14.05％),63 bronchoalveolar lavage fluid specimens(5.53％),29 secretion specimens(eye and wound secretions)(2.54％),and 120 other specimens(10.54％).K.pneumoniae and E.coli producing su-per-broad spectrum β-lactamase,CRKP and MRSA were the main drug-resistant bacteria.CONCLUSION The sit-uation of drug resistance in neonatal intensive care unit is serious,therefore monitoring bacterial resistance should be strengthened according to the clinical laboratory results,and antibiotics should be applied rationally.

Objective:To develop a risk prediction model for identifying bronchopulmonary dysplasia (BPD) associated pulmonary hypertension (PH) in very premature infants.Methods:This was a retrospective cohort study. The clinical data of 626 very premature infants whose gestational age <32 weeks and who suffered from BPD were collected from October 1 st, 2015 to December 31 st, 2021 of the Seventh Medical Center of the People′s Liberation Army General Hospital as a modeling set. The clinical data of 229 very premature infants with BPD of Hunan Children′s Hospital from January 1 st, 2020 to December 31 st, 2021 were collected as a validation set for external verification. The very premature infants with BPD were divided into PH group and non PH group based on the echocardiogram after 36 weeks′ corrected age in the modeling set and validation set, respectively. Univariate analysis was used to compare the basic clinical characteristics between groups, and collinearity exclusion was carried out between variables. The risk factors of BPD associated PH were further screened out by multivariate Logistic regression, and the risk assessment model was established based on these variables. The receiver operating characteristic (ROC) area under curve (AUC) and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the model′s discrimination and calibration power, respectively. And the calibration curve was used to evaluate the accuracy of the model and draw the nomogram. The bootstrap repeated sampling method was used for internal verification. Finally, decision curve analysis (DCA) to evaluate the clinical practicability of the model was used. Results:A total of 626 very premature infants with BPD were included for modeling set, including 85 very premature infants in the PH group and 541 very premature infants in the non PH group. A total of 229 very premature infants with BPD were included for validation set, including 24 very premature infants in the PH group and 205 very premature infants in the non PH group. Univariate analysis of the modeling set found that 22 variables, such as artificial conception, fetal distress, gestational age, birth weight, small for gestational age, 1 minute Apgar score ≤7, antenatal corticosteroids, placental abruption, oligohydramnios, multiple pulmonary surfactant, neonatal respiratory distress syndrome (NRDS)>stage Ⅱ, early pulmonary hypertension, moderate-severe BPD, and hemodynamically significant patent ductus arteriosus (hsPDA) all had statistically significant influence between the PH group and the non PH group (all P<0.05). Antenatal corticosteroids, fetal distress, NRDS >stage Ⅱ, hsPDA, pneumonia and days of invasive mechanical ventilation were identified as predictive variables and finally included to establish the Logistic regression model. The AUC of this model was 0.86 (95% CI 0.82-0.90), the cut-off value was 0.17, the sensitivity was 0.77, and the specificity was 0.84. Hosmer-Lemeshow goodness-of-fit test showed that P>0.05. The AUC for external validation was 0.88, and the Hosmer-Lemeshow goodness-of-fit test suggested P>0.05. Conclusions:A high sensitivity and specificity risk prediction model of PBD associated PH in very premature infants was established. This predictive model is useful for early clinical identification of infants at high risk of BPD associated PH.

Objective:To investigate the predictive effect of perioperative depression and anxiety symptoms in breast cancer patients on the fear of cancer recurrence.Methods:A total of 194 patients with breast cancer during perioperative period from May 2019 to May 2020 in Qilu Hospital of Shandong University were selected. The depression, anxiety and fear of cancer recurrence were investigated by the general information questionnaire, the Generalized Anxiety Disorder-7 (GAD-7), the Patient Health Questionnaire-9 (PHQ-9) and the Fear of Progression Questionnaire-Short Form (FOR-Q-SF) at admission and two weeks after surgery, respectively.Results:Perioperative depression and anxiety symptoms of breast cancer patients were significant predictors of fear of cancer recurrence ( B value was 2.325, OR value was 10.22, P<0.05; B value was 2.570, OR value was 13.07, P<0.05), and patients with depression and anxiety symptoms after surgery were at higher risk of fear of cancer recurrence ( OR values were 7.653-25.403, P<0.01). Conclusions:For breast cancer patients with negative emotions and fear of disease progression, it is necessary to help them improve their psychological coping ability, encouraging patients to actively cooperate with follow-up treatment, improving the prognosis, and improving their overall quality of life.

Objective:To evaluate the relationship between decreased atrial myoelectric conduction and gap junction protein 40 (Cx40) and Cx43 in rats with reperfusion atrial arrhythmia.Methods:Sixteen Langendorff-isolated heart perfusion models were randomly divided into control group (group C) and ischemia-reperfusion group (group IR), with 8 rats in each group.According to whether the atrial arrhythmia occurred after reperfusion, group IR was further divided into reperfusion non-atrial arrhythmia subgroup (group R-NAA) and reperfusion atrial arrhythmia subgroup (group R-AA). Group C was balanced perfusion with K-H solution (37 ℃) for 120 min.In group IR, hearts were perfused with K-H solution (37 ℃) for 30 min, perfusion was then stopped, Thomas solution (4 ℃, 20 ml/kg) was injected to induce cardiac arrest for 60 min, the surrounding of the heart was protected with 4 ℃Thomas solution, and hearts were perfused with Thomas solution (4 ℃, 10 ml/kg) again after 30 min of cardiac arrest and then with K-H solution 37 ℃ for 30 min.At 120 min of equilibration or 30 min of reperfusion, the effective refractory period (ERP) and conduction velocity (CV) of the right atrium were measured, the expression of Cx40 and Cx43 in the right atrial myocardium was detected by Western blot, and ratio of Cx40 to Cx40+ Cx43 and the ratio of Cx43 to Cx40+ Cx43 were calculated.Results:The incidence of reperfusion atrial arrhythmia was 38% in group IR.Compared with group C, ERP was significantly prolonged, CV was decreased, the expression of Cx40 and Cx43 was down-regulated, the ratio of Cx40 to Cx40+ Cx43 was increased, and the ratio of Cx43 to Cx40+ Cx43 was decreased in R-NAA and R-AA groups ( P<0.05). Compared with group R-NAA, ERP was significantly prolonged, CV was decreased, the expression of Cx40 and Cx43 was down-regulated, the ratio of Cx40 to Cx40+ Cx43 was increased, and the ratio of Cx43 to Cx40+ Cx43 was decreased in group R-AA ( P<0.05). Conclusion:The decreased atrial myoelectric conduction may be related to the down-regulation of Cx40 and Cx43 expression in rats with reperfusion atrial arrhythmia.

Objective: To construct and identify a mouse model with conditional knockout (cKO) of p75 neurotrophin receptor (p75NTR-cKO) gene in epidermis cells by Cre-loxP system. Methods: Five p75NTR^flox/flox transgenic C57BL/6J mice (aged 6-8 weeks, male and female unlimited, the age and sex of mice used for reproduction were the same below) and five keratin 14 promotor-driven (KRT14-) Cre^{+ /-} transgenic C57BL/6J mice were bred and hybridized via Cre-loxP system. Five p75NTR^flox/+ ·KRT14-Cre^{+ /-} mice selected from the first generation of mice were mated with five p75NTR^flox/flox mice to obtain the second generation hybrids. After the second generation mice were born 20-25 days, the parts of the mice tail were cut off to identify the genotype by polymerase chain reaction method. Four p75NTR gene complete cKO mice (6 weeks old) and 4 wild-type mice (6 weeks old) were selected and sacrificed respectively. The abdominal skin tissue and brain tissue were excised to observe the expression of p75NTR in the two tissue of two types of mice by immunohistochemical staining. The abdominal skin tissue of two types of mice was obtained to observe the histomorphological changes by hematoxylin and eosin staining. Results: (1) Twenty second generation mice were bred. The genotype of 4 mice was p75NTR^flox/flox·KRT14-Cre^{+ /-}(p75NTR^-/-), i. e. p75NTR gene complete cKO mice; the genotype of 5 mice was p75NTR^flox/+ ·KRT14-Cre^{+ /-}, i. e. p75NTR gene partial cKO mice; the genotype of 5 mice was p75NTR^flox/flox·KRT14-Cre^-/-, and that of 6 mice was p75NTR^flox/+ ·KRT14-Cre^-/-, all of which were wild-type mice. (2) The expression of p75NTR was negative in skin epidermis tissue of p75NTR gene complete cKO mice, while numerous p75NTR positive expression was observed in skin epidermis tissue of wild-type mice. Abundant p75NTR positive expression was observed in brain tissue of both wild-type mice and p75NTR gene complete cKO mice. (3) There was no abnormal growth of skin epidermis tissue in both wild-type mice and p75NTR gene complete cKO mice, with intact hair follicle structure. Conclusions Applying Cre-loxP system can successfully construct a p75NTR-cKO mice model in epidermis cells without obvious changes in skin histomorphology.