Objective To explore the impact of prolonged sitting on lumbar disc degeneration using MRI T1ρ and T2 mapping.Methods A total of 25 taxi drivers(prolonged sitting group)and 24 age-matched non-prolonged sitting volunteers(control group)underwent routine lumbar MRI,T1ρ,and T2 mapping.The differences of T1ρ and T2 values for different Pfirrmann grades of anterior annulus fibrosus(AAF),nucleus pulposus(NP),and posterior annulus fibrosus(PAF)were analyzed using Variance analysis,Spearman correlation test,and receiver operating characteristic(ROC)curve was drawn,with independent t-tests was used for between-group com-parisons.Results Statistically significant differences were observed in T1ρ and T2 values for all Pfirrmann Ⅰ-Ⅱ grades NP and Pfirrmann Ⅱ-Ⅳgrades AAF,NP,and PAF in both groups(P＜0.05).Both T1ρ and T2 values were negatively correlated with Pfirrmann grades.The area under the curve(AUC)of T1ρ values for NP at each Pfirrmann grade were 0.928,0.987,and 0.968,respectively,while the AUC of T2 values for NP were 0.777,0.966,and 0.975,respectively.The T1ρ and T2 values of L4/L5 NP and L5/S1 AAF,NP,and PAF were lower in the prolonged sitting group compared to the control group(P＜0.05).Conclusion T1ρ is superior to T2 mapping in detecting lumbar disc degeneration.Prolonged sitting is more likely to cause degeneration of L4/L5 and L5/S1 inter-vertebral discs.

AIM:To study the effect of NEDD8-conjugating enzyme UBE2F on lung adenocarcino-ma metastasis.METHODS:The expression of UBE2F in lung adenocarcinoma was analyzed using TIMER2.0,UALCAN and HPA databases.Kaplan-Mei-er Plotter database was used to analyze the rela-tionship between UBE2F expression and survival rate of lung adenocarcinoma.A UBE2F-knockout lung adenocarcinoma cell line was constructed us-ing CRISPR/Cas9 technology,and a UBE2F-knockout lung adenocarcinoma metastasis model was con-structed in nude mice to verify the effect of UBE2F knockout on lung adenocarcinoma metastasis.The effects of UBE2F knockout on invasion and migra-tion of lung adenocarcinoma cells were examined by cell scratch assay and Transwell invasion and mi-gration assays.The effect of down-regulated UBE2F expression on snail expression,a key marker of epi-thelial-mesenchymal transition(EMT),was detect-ed by Western blot and Real time PCR.RESULTS:Multiple database analysis showed that UBE2F was highly expressed in lung cancer,and Kaplan-Meier Plotter analysis showed that high expression of UBE2F in lung adenocarcinoma had better progno-sis than low expression.In vivo experiments showed that compared with control group,the number of nodules metastasized on the lung sur-face of nude mice after UBE2F knockout was signifi-cantly increased(P<0.05).Cell scratch assay and Transwell assay showed that UBE2F enhanced the migration and invasion ability of lung cancer cells after knockout,and the difference were statistically significant(P<0.05).Western blot and Real time PCR results indicated that the level of EMT tran-scription factor snail protein and mRNA increased after UBE2F knockout.CONCLUSION:In lung ade-nocarcinoma cells,UBE2F down-regulation leads to Snail accumulation and promotes invasion and me-tastasis of lung adenocarcinoma cells.

Objective:To explore the characteristics of echocardiographic parameters among the many parameters of two-dimensional transthoracic echocardiography(2D-TTE) and three-dimensional speckle tracking imaging (3D-STI) that can be used for early identification of familial hypertrophic cardiomyopathy(FHCM) mutation gene carriers, and construct a Nomogram prediction model, in order to provide a diagnostic method for early identification of G+ P- patients for clinical practice.Methods:A total of 15 FHCM families admitted to the General Hospital of Ningxia Medical University from November 2017 to August 2022 were enrolled.Whole exome sequencing and Sanger sequencing technology were used for gene detection, among which 54 were G+ P- and 75 were G-P-. Stratified random sampling was used to divide the subjects into training set ( n=90) and test set ( n=39) according to the ratio of 7∶3. Philips iE33 ultrasonic diagnostic instrument and TomTec offline software were used to obtain relevant ultrasonic parameters. Lasso regression and Logistic regression were used to screen echocardiographic parameters and obtain independent risk factors for early prediction of G+ P-, based on which a Nomogram prediction model was established. Results:①Lasso-Logistic regression showed that global longitudinal strain(GLS) ( OR=1.739, 95% CI=1.305-2.316) and left ventricular outflow trac velocity time integral(LVOT-VTI) ( OR=1.358, 95% CI=1.072-1.722) could be used as independent risk factors for early prediction of G+ P-. ②The Nomogram prediction model was established based on the above indicators. After 1000 internal verifications of Bootstrap self-sampling, the C-indices of the training set and the test set were 0.885 (95% CI=0.816-0.954), 0.878 (95% CI=0.764-0.992), which had good internal consistency. ③The results of the calibration curve showed that the risk of G+ P- predicted by the Nomogram model was basically consistent with the actual risk (training set P=0.990, test set P=0.961); the clinical decision curve shows that under different threshold probabilities, using this prediction model to provide patients with clinical decision-making could bring benefits to patients. Conclusions:Echocardiographic parameters GLS and LVOT-VTI can be used as independent risk factors to predict FHCM mutation gene carriers. The Nomogram prediction model has good discrimination, goodness of fit and clinical benefit in identifying whether the family members of FHCM patients carry the mutation gene, and it can provide a new idea and evaluation method for the early identification of FHCM mutation gene carriers by echocardiography.

Animals ; Mice ; Corticotropin-Releasing Hormone/metabolism* ; Neurons/metabolism* ; Brain/metabolism*

Objective:To investigate the value of a preoperatively MRI-based deep learning (DL) radiomics machine learning model to distinguish low-grade and high-grade soft tissue sarcomas (STS).Methods:From November 2007 to May 2019, 151 patients with STS confirmed by pathology in the Affiliated Hospital of Qingdao University were enrolled as training sets, and 131 patients in the Affiliated Hospital of Shandong First Medical University and the Third Hospital of Hebei Medical University were enrolled as external validation sets. According to the French Federation Nationale des Centres de Lutte Contre le Cancer classification (FNCLCC) system, 161 patients with FNCLCC grades Ⅰ and Ⅱ were defined as low-grade and 121 patients with grade Ⅲ were defined as high-grade. The hand-crafted radiomic (HCR) and DL radiomic features of the lesions were extracted respectively. Based on HCR features, DL features, and HCR-DL combined features, respectively, three machine-learning models were established by decision tree, logistic regression, and support vector machine (SVM) classifiers. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each machine learning model and choose the best one. The univariate and multivariate logistic regression were used to establish a clinical-imaging factors model based on demographics and MRI findings. The nomogram was established by combining the optimal radiomics model and the clinical-imaging model. The AUC was used to evaluate the performance of each model and the DeLong test was used for comparison of AUC between every two models. The Kaplan-Meier survival curve and log-rank test were used to evaluate the performance of the optimal machine learning model in the risk stratification of progression free survival (PFS) in STS patients.Results:The SVM radiomics model based on HCR-DL combined features had the optimal predicting power with AUC values of 0.931(95%CI 0.889-0.973) in the training set and 0.951 (95%CI 0.904-0.997) in the validation set. The AUC values of the clinical-imaging model were 0.795 (95%CI 0.724-0.867) and 0.615 (95%CI 0.510-0.720), and of the nomogram was 0.875 (95%CI 0.818-0.932) and 0.786 (95%CI 0.701-0.872) in the training and validation sets, respectively. In validation set, the performance of SVM radiomics model was better than those of the nomogram and clinical-imaging models ( Z=3.16, 6.07; P=0.002,<0.001). Using the optimal radiomics model, there was statistically significant in PFS between the high and low risk groups of STS patients (training sets: χ2=43.50, P<0.001; validation sets: χ2=70.50, P<0.001). Conclusion:Preoperative MRI-based DL radiomics machine learning model has accurate prediction performance in differentiating the histopathological grading of STS. The SVM radiomics model based on HCR-DL combined features has the optimal predicting power and was expected to undergo risk stratification of prognosis in STS patients.

Objective:To investigate the distribution and antimicrobial resistance profile of clinical bacteria isolated from blood culture in China.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2018 to December 2019. Antibiotic susceptibility tests were conducted with agar dilution or broth dilution methods recommended by US Clinical and Laboratory Standards Institute (CLSI). WHONET 5.6 was used to analyze data.Results:During the study period, 14 778 bacterial strains were collected from 50 hospitals, of which 4 117 (27.9%) were Gram-positive bacteria and 10 661(72.1%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (37.2%), Klebsiella pneumoniae (17.0%), Staphylococcus aureus (9.7%), coagulase-negative Staphylococci (8.7%), Pseudomonas aeruginosa (3.7%), Enterococcus faecium (3.4%), Acinetobacter baumannii(3.4%), Enterobacter cloacae (2.9%), Streptococci(2.8%) and Enterococcus faecalis (2.3%). The the prevalence of methicillin-resistant S. aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus were 27.4% (394/1 438) and 70.4% (905/1 285), respectively. No glycopeptide-resistant Staphylococcus was detected. More than 95% of S. aureus were sensitive to amikacin, rifampicin and SMZco. The resistance rate of E. faecium to vancomycin was 0.4% (2/504), and no vancomycin-resistant E. faecalis was detected. The ESBLs-producing rates in no carbapenem-resistance E. coli, carbapenem sensitive K. pneumoniae and Proteus were 50.4% (2 731/5 415), 24.6% (493/2001) and 35.2% (31/88), respectively. The prevalence of carbapenem-resistance in E. coli and K. pneumoniae were 1.5% (85/5 500), 20.6% (518/2 519), respectively. 8.3% (27/325) of carbapenem-resistance K. pneumoniae was resistant to ceftazidime/avibactam combination. The resistance rates of A. baumannii to polymyxin and tigecycline were 2.8% (14/501) and 3.4% (17/501) respectively, and that of P. aeruginosa to carbapenem were 18.9% (103/546). Conclusions:The surveillance results from 2018 to 2019 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while E. coli was the most common pathogen, and ESBLs-producing strains were in majority; the MRSA incidence is getting lower in China; carbapenem-resistant E. coli keeps at a low level, while carbapenem-resistant K. pneumoniae is on the rise obviously.

Objective:To investigate the distribution and antimicrobial resistance profile of clinical bacteria isolated from blood culture in China.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2016 to December 2017. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by US Clinical and Laboratory Standards Institute (CLSI) 2019. WHONET 5.6 was used to analyze data.Results:During the study period, 8 154 bacterial strains were collected from 33 hospitals, of which 2 325 (28.5%) were Gram-positive bacteria and 5 829 (71.5%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (34.7%), Klebsiella pneumoniae (15.8%), Staphylococcus aureus (11.3%), coagulase-negative Staphylococci (7.4%), Acinetobacter baumannii (4.6%), Pseudomonas aeruginosa (3.9%), Enterococcus faecium (3.8%), Streptococci (2.9%), Enterobacter cloacae (2.7%) and Enterococcus faecalis (2.5%). Methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus (MRCNS) accounted for 34.2%(315/922) and 77.7%(470/605), respectively. No vancomycin-resistant Staphylococcus was detected. The resistance rate of Enterococcus faecium to vancomycin was 0.6%(2/312), and no vancomycin-resistant Enterococcus faecium was detected. The ESBLs-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus were 55.7%(1 576/2 831), 29.9%(386/1 289) and 38.5%(15/39), respectively. The incidences of carbapenem-resistance in Escherichia coli, Klebsiella pneumoniae were 1.2%(33/2 831), 17.5%(226/1 289), respectively. The resistance rates of Acinetobacter baumannii to polymyxin and tigecycline were 14.8%(55/372) and 5.9%(22/372) respectively, and those of Pseudomonas aeruginosa to polymyxin and carbapenem were 1.3%(4/315) and 18.7%(59/315), respectively. Conclusion:The surveillance results from 2016 to 2017 showed that the main pathogens of blood stream infection in China were gram-negative bacteria, while Escherichia coli was the most common pathogen; the MRSA incidence was lower than other surveillance data in the same period in China; carbapenem-resistant Escherichia coli was at a low level during this surveillance, while carbapenem-resistant Klebsiella pneumoniae is on the rise.

Objective: To explore the effect of blended health literacy education combining WeChat and participatory class among college students, and to provide references for enriching the technology of health education in college. Methods: Using cluster random sampling method, 378 freshmen from 10 classes of a non-medical college in Guangzhou were selected as the research objects. The intervention group (193) was given blended health literacy education including WeChat and participatory class education, while the control group (185) recieved no intervention. The other types of health educaiton were not limited in both groups. A survey was conducted among those college students before and after the health education by applying Questionnaire on College Students’ Health Literacy. Results: According to the baseline survey, there were no significant differences between the intervention group and the control group in the level of health literacy and basic situations(P>0.05). But after the intervention, the scores of health literacy and basic health concept and knowledge, health skills of three aspects were (54.34±6.03) (23.91±2.44) (12.39±2.32) respectively, and infectious diseases prevention, chronic diseases prevention, safety and first aid，health information of six health issues were(5.59±1.34) (10.17±1.57) (12.88±1.55) (6.33±1.58), higher than those in the control group, and the differences were statistically significant(t=3.50, 2.50, 3.94, 2.50, 2.79, 2.48, 2.12, P<0.05). The overall health literacy level of the intervention group was 71.5%(138/193) and the control group was 51.9%(96/185), there was significant difference between two groups(χ2=15.40, P<0.01). Conclusion Blended health literacy education improves college students’ health literacy level sbustantially, which may provide references to the technology of health literacy intervention in college.

Objective To improve the diagnostic accuracy of primary renal rare benign tumors by exploring and analyzing the CT/MRI and clinical pathologic features.Methods 9 patients with primary renal rare benign tumors pathologically proven lesions after operation who had CT or MRI exams with contrast were enrolled in our hospital.The radiological and clinical pathological features of all tumors were analyzed respectively.Results The cases were the mixed epithelial and stromal tumor of kidney (MESTK),cystic nephroma(CN),renal leiomyoma(RL)and renal oncocytoma(RO)respectively.Location:6 cases were in left kidney and 3 in right kidney.Size:long diameter 2.5-8.9 cm,mean 5.7 cm;short diameter 2.5-8.4 cm,mean 4.9 cm.The tumor shape included oval(n=7) and irregular(n=2).9 cases protruded from the renal surface.MESTK showed polycystic lesions on preconstrast,various degrees of cystic wall and septum enhancement were detected on enhancement scans.CN showed cystic lesions and calcification on preconstrast, slight septum enhancement were detected on enhancement scans.RL showed heterogeneous density or signal with patchy necrosis and clear border on precontrast,the obvious enhancement was found on cortex and medullary phase and slight washout enhancement was detected on excretory phase.RO showed heterogeneous hypointense on T1 WI,hyperintense on T2 WI and mixed isodensity and hypodensity on CT precontrast.Slight delayed enhancement was found in central scar and washout enhancement was detected in parenchyma on three phases.Conclusion There are some special CT/MRI characteristics for primary renal rare benign tumors,which could improve their diagnosis and differential diagnosis combined with the clinical pathological features.

AIM To prepare D-α-tocopherol polyethylene glycol 1000 succinate (TPGS)-modified artesunate liposomes and to investigate the in vitro anti-tumor activity.METHODS The liposomes prepared by thin-film dispersion method were characterized by transmission electron microscopy and particle size analyzer,and the encapsulation efficiency was determined by ultrafiltration centrifugation.The liposomes' cytotoxicity to human hepatoma HepG2 cells was evaluated by MTT method.RESULTS The average particle size,PDI,Zeta potential,encapsulation efficiency,drug loading of the liposomes were 126.7 nm,0.182,-10.1 mV,78.8％ and 18.38％,respectively.The liposomes displayed a significant inhibition on HepG2 cells with the IC50 value of 0.034 μmol/mL.CONCLUSION Compared with non-TPGS-modified artesunate liposomes,the TPGS-modified artesunate liposomes prepared by this method afford smaller vesicle size,better stability and higher encapsulation efficiency with stronger in vitro anti-tumor activity.