Objective To investigate the clinical and epidemiologieal feat ures of epidemic cerebrospinal meningitis in recent 3 years,aiming to develop the strategies for controlling this disease.Methods A retrospective analysis was conducted in 65 hospitalized patients with epidemic cerehrospinal meningitis from 2003 to 2006.Chi-square test was used for statistical analysis.Results The majority of these 65 patients were juvenile and adult,accounting for 44.6%(29 cases)and 35.4%(23 cases),respectively,while the infant patients account for the smallest percentage,only 6.2%(4 cases).Most cases occurred in spring(from February to April).The clinical features of most patients belonged to common type(72.3%),followed by fulminant type(27.7%).Five cases(7.7%)died,all of whom were fulminant cases.Totally 33 strains of Neisseria meningitidis were isolated,with positive culture rate of 50.8%(33/65 cases).The positive rate of blood culture was 44.6%(29/65 cases)and that of cerebrospinal fluid cuhure was 31.4%(16/51 cases).Isolates of Neisseria meningitidis were still highly sensitive to penicillin,ceftriaxone and cefotaxime.However,the resistance rates of strains to compound sulfamethoxazole,gentamycin and ciprofloxacin were all above 80%.Resuhs of serological typing revealed thai 82.8%(53/64 cases)cases belonged to group C.There were more severe cases and higher death rate in patients infected by group C meningococcus.Conclusions Serogroup C of the meningococcus have become the preponderant strains in Anhui Province.Most of the patients infected hy group C are J uveniles and adults.Penicillin and the third generation cephalosporins are still highly aclive againsl Neisseria meningitidis.

Objective:To assess the value of the ROX index in evaluating the efficacy of high-flow nasal cannula oxygen therapy (HFNC) in patients with coronavirus infected disease (COVID-19).Methods:This is a retrospective study. The included patients were diagnosed as COVID-19 in the intensive care unit (ICU) of the Cancer Center of Union Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology from February 15, 2020 to March 15, 2020. All the patients were treated by HFNC. According to whether the patient subsequently received non-invasive positive pressure ventilation or invasive positive pressure ventilation, patients were divided into the HFNC success group and the HFNC failure group. Parameters in the two groups such as basic characteristics, lactic acid, number of chest radiographs, APACHE II, lymphocyte count, baseline respiratory rate, baseline percutaneous oxygen saturation, baseline PaO 2/FiO 2, baseline ROX index, and ROX index after 2, 6 and 12 h HFNC treatment were analyzed with t test, Chi-square test or rank sum test. Results:A total of 57 cases were included in this study. There were no significant differences in sex, age, comorbidities, lactic acid, quadrants of chest radiograph lung infection, APACHE II, lymphocyte count, and baseline respiratory frequency, transcutaneous oxygen saturation, oxygenation index, and ROX index between the HFNC success group and the HFNC faliure group ( P>0.05). Logistic regression analysis showed that ROX index after 2 h HFNC treatment ( OR=0.069), ROX index after 6 h HFNC treatment ( OR=0.194) and ROX index after 12 h HFNC treatment ( OR=0.036) were all protective factors for the therapeutic effect of HFNC treatment in COVID-19 patients. ROC curve showed that there were significant differences in ROX index after 2 h HFNC treatment, ROX index after 6 h HFNC treatment, and ROX index after 12 h HFNC treatment ( P<0.05). In the evaluation index, the area under the ROC curve of the ROX index after 2 h HFNC treatment was 0.838, the sensitivity was 64.5%, and the specificity was 100%. After 6 h HFNC treatment, the area under the ROX index ROC curve was 0.762, the sensitivity was 64.5%, and the specificity was 92.3%. After 12 h HFNC treatment, the ROX index ROC curve area was 0.866, the sensitivity was 67.7%, and the specificity was 100%. Conclusions:The ROX index can be used to evaluate the efficacy of HFNC in COVID-19 patients in a timely, simple and real-time manner.

Objective To investigate the profile and antibiotic resistance of bacteria in patients with ascites infection in intensive care unit (ICU) patients in order to provide a reference for rational clinical use of antibiotics. Methods A retrospective analysis was conducted. The bacteria isolated from ascetic fluid patients admitted from January 1st, 2004 to October 31st, 2015 to ICU of the First Affiliated Hospital of Anhui Medical University were identified, and their susceptibility to antibiotics was analyzed. Patients, who were admitted from January 1st, 2004 to December 31st, 2009 were assigned to group A, and patients admitted afterwards were assigned to group B. Results A total of 637 specimens of ascetic fluid were examined, with 185 positive culture (29.0%) during the 12 years, and 203 strains of bacteria were found. Among them 126 strains (62.1%) of gram-negative bacteria (G-), 54 (26.6%) of gram-positive bacteria (G+) and 23 (11.3%) strains of fungi were found. Compared the result of group B with that of group A, the proportion of G- bacteria was increased [71.2% (99/139) vs. 44.2% (27/64)], and that of G+ decreased [17.3% (24/139) vs. 46.9% (30/64)] in group B. The difference was statistically significant (χ2 = 20.34, P = 0.001). The main pathogenic bacteria were G-, and Enterobacteriaceae was the most common pathogenic bacteria in intra-abdominal infection of ICU patients. The isolation rate of Escherichia coli and Klebsiella pneumoniae(35.7%, 10.3%) ranked in the first and third in G- bacteria, respectively. The resistant rate of Escherichia coli against penicillin and third generation cephalosporin were > 95.0% and > 73.3%, and it showed a sensitive rate of 70% to β-lactam/inhibitor, amikacin and minocycline, and a higher sensitivity to carbapenems and tigecycline (11.1%, 0). Forty-eight strains of non-fermentation bacteria were found with a rate of 23.7%. The positive rates of Acinetobacter baumannii in groups A and B were 7.8% (5/64) and 23.7% (33/139), respectively, and they ranked first among non-fermentation bacteria. Twenty strains (62.5%) multidrug-resistant Acinetobacter baumannii were found. Acinetobacter baumannii showed a resistance rate of 84.6% to cefoperazone/sulbactam, 35.3% to minocycline, and 53.3% to tigecycline. Candida albicans was the most commonly isolated fungus in intra-abdominal infections (87.5%). No strains resistant to common antifungal drugs were isolated. Conclusions G- bacteria was the main pathogen in intra-abdominal infection in patients with ascites. Non-fermenters showed an increasing trend of producing infection, and the proportion of multidrug-resistant Acinetobacter baumannii infection increased year by year, and more attention should be taken by attending doctors.

BACKGROUND:Tougu Xiaotong Capsule has pretty good clinical therapeutic effect on osteoarthritis of early and middle periods. However, the mechanism of Tougu Xiaotong Capsule is not ful y clarified. The RhoA GTPases can regulate chondrocyte apoptosis and hypertrophy.
OBJECTIVE:To observe the Tougu Xiaotong Capsule on the expression of Rac1and Cdc42 in tumor necrosis factor-α-induced in vitro cultured rat articular chondrocytes, and to explore its mechanism of action for combating osteoarthritis.
METHODS:Knee cartilage of the 4-week-old Sprague-Dawley rats was used to stably establish in vitro culture system of chondrocytes. Passage 3 chondrocytes were identified by toluidine blue staining. Chondrocyte apoptosis was successful y induced by 20μg/L tumor necrosis factor-αand then Tougu Xiaotong Capsule at different dosage (500, 100, 20 mg/L) was given after 24-hour incubation. MTT assay was used to detect cellsurvival, flow cytrometry to measure mitochondrial membrane potential, and western blot assay to determine the protein expression of Rac1, Cdc42, Bax and Bcl-2.
RESULTS AND CONCLUSION:Tougu Xiaotong Capsule could reduce tumor necrosis factor-α-induced apoptosis of chondrocytes to improve the survival rate of the cells, and at the same time, could down-regulate the protein expression of Rac1, Cdc42 and Bax and increase the protein expression of Bcl-2 significantly (P<0.05). Tougu Xiaotong Capsule possibly plays a therapeutic efficacy on osteoarthritis by reducing promote apoptosis Rac1, Cdc42 and Bax expression and increasing apoptosis inhibiting gene Bcl-2 expression, thereby to inhibit apoptosis of chondrocytes.

BACKGROUND:Previous studies have found that electroacupuncture can delay articular cartilage degeneration mediated by JAK-STAT signaling pathway through upregulating the expression level of transforming growth factor β1 as well as mRNA expression levels of STAT3, Smad3 and LepR. In the meanwhile, electroacupuncture can inhibit the mRNA expression of p38 and Fas mRNA mediated by MAPK signaling pathways, further inhibiting the apoptosis of chondrocytes. OBJECTIVE: To explore the effect of electroacupuncture on the degeneration of articular cartilage in rats with knee osteoarthritis based on Ras-Raf-MEK1/2-ERK1/2 signaling pathway. METHODS:120 male healthy Sprague-Dawley rats aged 2 months olds were selected and randomly divided into normal, model, 15-minite electroacupuncture and 30-minute electroacupuncture groups (n=30 per group). The rats in the latter three groups received the intra-articular injection of 4% papain bilaterally, and the remaining rats received no intervention. At 2 weeks after modeling, the latter two groups were respectively given 15- and 30-minute electroacupuncture, five times weekly for consecutive 12 weeks. The morphology of the cartilage was observed by hematoxylin-eosin staining, the expression level of interleukin-1β in the synovium was detected by ELISA assay, and the protein expression levels of Ras, Raf, MEK1/2, ERK1/2, C-MYC, C-FOS, and C-JUN were detected by western blot analysis. RESULTS AND CONCLUSION: Hematoxylin-eosin staining showed that: in the model group, the cartilage surface was rough, the cartilage layer became thinner, and the cartilage structure was damaged with incomplete tidal line; in the 15- and 30-minute electroacupuncture groups, the cartilage structure was complete with clear layers and complete tidal line. ELISA showed that the expression level of interleukin-1β in the model group was significantly higher than that in the normal group (P< 0.01), and the level in the 15- and 30-minute electroacupuncture groups was significantly lower than that in the model group (P < 0.05). Western blot assay found that compared with the normal group, the protein expression levels of Ras, Raf, MEK1/2, ERK1/2, C-MYC, C-FOS, and C-JUN were increased in the model group. However, all above protein levels except ERK1/2 in the 15- and 30-minute electroacupuncture groups were significantly lower than those in the model group (P < 0.01,P < 0.05). To conclude, electroacupuncture inhibits the degeneration of articular cartilage in osteoarthritisvia Ras-Raf-MEK1/2-ERK1/2 signaling pathway and downregulating the expression level of interleukin-1β.

Objective To study the relationship of carotid atherosclerosis score (CAS) with carotid atherosclerotic disease and its clinical indexes in ischemic stroke patients.Methods Ninety-six patients with ischemic stroke (＜2 weeks) or transient ischemic attack underwent high-resolution MRI of bilateral carotid arteries to measure their carotid atherosclerotic luminal stenosis,maximal wall thickness (MaxWT) and plaque involvement size.The carotid plaque images with unstable components of lipid-rich core (LRC) were analyzed with CASCAD software.The CAS value was calculated and divided into low risk group and high risk group.The relationship between CAS and its clinical indexes was analyzed.Results LRC was detected in plaques of 148 carotid arteries of the 96 patients with a CAS value of 21.6％±17.5％.The CAS value was related with the carotid luminal stenosis,MaxWT and plaque involvement size (r =0.610,r=0.569,r =0.527,P＜ 0.001).A significant difference was found in carotid luminal stenosis,MaxWT and plaque involvement size with a different CAS value (P＜0.01).The CAS value was related with LDL and HDL/TC ratio (r=0.469,P＜0.01;r=-0.269,P=0.035).The SBP,DBP and LDL level were higher in high risk group than in low risk group (P＜0.05).Conclusion CAS is closely related with carotid atherosclerotic disease and lipid metabolism.The higher the CAS value is,the higher the risk of carotid plaque hemorrhage and fibrous cap rupture is.

Objective To investigate the value of automatic segmentation of carotid vessel wall in multicontrast MR images using U?Net neural network. Methods Patients were retrospectively collected from 2012 to 2015 in Carotid Atherosclerosis Risk Assessment (CARE II) study. All patients who recently suffered ischemic stroke and/or transient ischemic attack underwent identical, state?of?the?art multicontrast MRI technique. A total of 17 568 carotid vessel wall MR images from 658 subjects were included in this study after inclusion criteria and exclusion criteria. All MR images were analyzed using customized analysis platform (CASCADE). Randomly, 10 592 images were assigned into training dataset, 3 488 images were assigned into validating dataset and 3 488 images were assigned into test dataset according to a ratio of 6∶2∶2. Data augmentation was performed to avoid over fitting and improve the ability of model generalization. The fine?tuned U?Net model was utilized in the segmentation of carotid vessel wall in multicontrast MR images. The U?Net model was trained in the training dataset and validated in the validating dataset. To evaluate the accuracy of carotid vessel wall segmentation, the sensitivity, specificity and Dice coefficient were used in the testing dataset. In addition, the interclass correlation and the Bland?Altman analysis of max wall thickness and wall area were obtained to demonstrate the agreement of the U?Net segmentation and the manual segmentation. Results The sensitivity, specificity and Dice coefficient of the fine?tuned U?Net model achieved 0.878,0.986 and 0.858 in the test dataset, respectively. The interclass correlation (95% confidence interval) was 0.921 (0.915-0.925) for max wall thickness and 0.929 (0.924-0.933) for wall area. In the Bland?Altman analysis, the difference of max wall thickness was (0.037±0.316) mm and the difference of wall area was (1.182±4.953) mm2. The substantial agreement was observed between U?Net segmentation method and manual segmentation method. Conclusion Automatic segmentation of carotid vessel wall in multicontrast MR images can be achieved using fine?tuned U?Net neural network, which is trained and tested in the large scale dataset labeled by professional radiologists.

Objective: To investigate the value of automatic segmentation of carotid vessel wall in multicontrast MR images using U-Net neural network. Methods: Patients were retrospectively collected from 2012 to 2015 in Carotid Atherosclerosis Risk Assessment (CARE II) study. All patients who recently suffered ischemic stroke and/or transient ischemic attack underwent identical, state-of-the-art multicontrast MRI technique. A total of 17 568 carotid vessel wall MR images from 658 subjects were included in this study after inclusion criteria and exclusion criteria. All MR images were analyzed using customized analysis platform (CASCADE). Randomly, 10 592 images were assigned into training dataset, 3 488 images were assigned into validating dataset and 3 488 images were assigned into test dataset according to a ratio of 6∶2∶2. Data augmentation was performed to avoid over fitting and improve the ability of model generalization. The fine-tuned U-Net model was utilized in the segmentation of carotid vessel wall in multicontrast MR images. The U-Net model was trained in the training dataset and validated in the validating dataset. To evaluate the accuracy of carotid vessel wall segmentation, the sensitivity, specificity and Dice coefficient were used in the testing dataset. In addition, the interclass correlation and the Bland-Altman analysis of max wall thickness and wall area were obtained to demonstrate the agreement of the U-Net segmentation and the manual segmentation. Results: The sensitivity, specificity and Dice coefficient of the fine-tuned U-Net model achieved 0.878,0.986 and 0.858 in the test dataset, respectively. The interclass correlation (95% confidence interval) was 0.921 (0.915-0.925) for max wall thickness and 0.929 (0.924-0.933) for wall area. In the Bland-Altman analysis, the difference of max wall thickness was (0.037±0.316) mm and the difference of wall area was (1.182±4.953) mm². The substantial agreement was observed between U-Net segmentation method and manual segmentation method. Conclusion Automatic segmentation of carotid vessel wall in multicontrast MR images can be achieved using fine-tuned U-Net neural network, which is trained and tested in the large scale dataset labeled by professional radiologists.