Objective To investigate the effects of protocadherin 20 (PCDH20) in the spinal cord in the development of bone cancer pain (BCP) in rats.Methods Thirty-six SPF female Sprague-Dawley rats,weighing 180-200 g,were randomly divided into 4 groups (n =9 each):sham operation group (group S),BCP group,lentivirus control group (group LC) and PCDH20 siRNA lentivirus group (group P).Control lentivirus and lentivirus containing PCDH20 siRNA 4 μl were injected into the ipsilateral spinal cord in groups LC and P,respectively.One week later,BCP was induced by injection of Walker 256 breast cancer cells into the upper segment of bone marrow of right tibia.The mechanical paw withdrawal threshold (MWT) was measured at 1 day before injection of lentivirus (T1),1 day before BCP (T2),and 7,14 and 21 days after BCP (T3-5).Three rats in each group were sacrificed after measurement of the MWT at 21 day after BCP and the tibia on the operated side was obtained for examination of invasion of the cancer cells with light microscope.The spinal cord was removed for determination of the expression of PCDH20 and postsynaptic density 95 (PSD95) protein (by Western blot) and mRNA (by RTPCR).Results In groups BCP,LC and P,the cancer cells grew out of the bone and destroyed the cortical bone seriously.Compared with group S,the MWT was significantly decreased at T3-5 in groups BCP,LC and P,the expression of PCDH20 and PSD95 protein and mRNA was up-regulated in groups BCP and LC,and the expression of PCDH20 was up-regulated in group P (P ＜ 0.05).Compared with BCP group,no significant change was found in the MWT and expression of PCDH20 and PSD95 protein and mRNA in group LC (P ＞ 0.05),and the MWT was significantly increased at T4,5 and the expression of PCDH20 and PSD95 protein and mRNA was down-regulated in group P (P ＜ 0.05).Conclusion PCDH20 is involved in the development of BCP through regulating the expression of PSD95 in the spinal cord and adjusting the function of excitatory synapse in rats.

Objective To study the cell death in macrophages (THP-1) stimulated with different agonists (H37Rv-PPD or BCG-PPD) and to investigate the relationship between Toll like receptor (TLR)-2 and THP-1 apoptosis. Methods H37Rv-PPD and BCG-PPD were used to stimulate THP-1 cells for 3 h, 8 h, 15 h and 24 h, respectively with or without TLR-2 blockade. Cells were analyzed by flow cytometry to detect the TLR-2 expression. Annexin V staining and Hochest staining were performed to evaluate apoptosis. Results The apoptosis cells were increased when stimulated with BCG-PPD and the percentage was 30.2% at 24 h, which were confirmed by Hochest staining.However, the expression of TLR-2 did not increase simultaneously with percentage of 8.8% at 24 h.Nevertheless, most cells presented with necrosis form when stimulated with H37Rv-PPD and the expression of TLR-2 remained at high level with the percentage of 17.2% at 24 h, while the percent of apoptosis rate was only 7.7%. Under treatment of TLR-2 antibodies, the percentage of apoptosis decreased to 10.5% at 24 h of BCG-PPD stimulation and TLR-2 expressions were down-regulated to less than 3% at all time points; but after H37Rv-PPD stimulation, the percentage of apoptosis and TLR-2 expression did not changed obviously. Conclusions The attenuated BCG-PPD induces THP-1 apoptosis predominately, which is partially correlated with TLR-2 expression. While virulent H37Rv-PPD induces THP-1 necrosis predominately.

Objective To study the different response in macrophages treated with different agoβ and IL-10 in Mycobacterium tuberculosisnists(H37Rv-PPD and BCG-PPD)related with Mycobacterium tuberculosis and the relationship with TNF-αt,IL-1β and IL-10.Methods Using H37Rv-PPD and BCG-PPD to stimulate THP-1 cell for 3h,8h,15h,24h respectively.Cells were ananlyzed by Hochest staining under fluorescence microscopy to assay cell death(apoptosis and necrosis).At each stimulating time,TNF-α,IL-1β and IL-10 were examined by ELISA.Results Under fluorescence microscopy,it could easily see oval apoptotic bodies of THP-1 stimulated by BCG-PPD.However ,the nucleus were often isolated and necrosis-like when cells were stimulated by H37Rv-PPD.In a word ,BCG-PPD tend to induce THP-1 cells to apoptosis,but H37Rv-PPD inclined to induce cells to undergo necrosis.In supernatant of cells stimulated by BCG-PPD,the expression of TNF-αand IL-10 were lower than the cells stimulated by H37Rv-PPD,but the expression of IL-1β was higher than the latter.Conclusion It indicated that the necrosis of cells stimulated by H37Rv-PPD was asossiated with the excessive expression of TNF-α and IL-10,and the apoptosis of cells induced by BCG-PPD was IL-1β related.Perhaps the mechanism of differences in virulence exist in protein of strain,and associated with cytokines IL-1β,TNF-α and IL-10.

Objective To observe value of high frequency ultrasound for inspection of T7-8 paravertebral space and adjacent structures.Methods Color Doppler ultrasonic diagnostic apparatus with linear array transducer (frequency 3-12 MHz) were used.Taking shoulder blade,ribs,thoracic spine and transverse process as anatomical marks,T7-8 paravertebral spaces of 30 normal adult (a total of 60 side) were examined.Ultrasonographic features of T7-8 paravertebral space and the adjacent structures were observed.Results T7-8 thoracic paravertebral showed as similar triangular shape with ultrasonography,interior solid homogeneously hypoechoic was noticed.Adjacent muscles of T7-8 paravertebral space included the trapezius,latissimus dorsi,spinalis,semispinalis,multifidus,rotatores and intercostal muscles.Color Doppler or power Doppler flow imaging could demonstrate posterior intercostal artery in the paravertebral space.Conclusion High frequency ultrasound can clearly show T7-8 paravertebral space and adjacent structures,thus providing ultrasonic references for clinical diagnosis and treatment of lesions of thoracic space and adjacent structures.

Objective To establish and validate a prediction model for gastric cancer lymph node metastasis based on four machine learning(ML)algorithms.Methods A retrospective analysis was conducted on clinical data of 531 patients who underwent radical gastrectomy.The patients were ran-domly divided into training set(399 patients)and test set(132 patients)in a ratio of 3 to 1.Univari-ate analysis was used to screen for variables associated with gastric cancer lymph node metastasis,and Logistic regression,random forest,K-nearest neighbor algorithm,and support vector machine algo-rithm models were established to rank the importance of variables.All ML algorithm models were vali-dated in the test set,and receiver operating characteristic(ROC)curves were plotted.The optimal ML algorithm model was determined based on the area under the curve(AUC),sensitivity,specifici-ty,and accuracy.A nomogram model was constructed based on the variable importance ranking of the optimal ML algorithm model.The discrimination,calibration,and clinical applicability of the nomo-gram model were evaluated using ROC curves,calibration curves,and decision curves.Results The results of the comparison of the four ML algorithm models showed that the random forest model was the optimal algorithm model.The accuracy,sensitivity,and specificity of the random forest model in the training set were 72.7％,69.9％,and 75.0％,respectively,with an AUC of 0.803.The accuracy,sensitivity,and specificity of the random forest model in the test set were 64.4％,66.7％,and 62.5％,respectively,with an AUC of 0.751.A nomogram model was constructed based on the variables of the random forest algorithm model.The ROC curve showed that the AUCs of the nomogram model in the training set and test set were 0.721 and 0.776,respectively.Calibration curves and decision curves showed that the nomogram model had good calibration and clinical applicability in both the training set and test set.Conclusion The random forest model is the optimal algorithm model a-mong the four ML algorithm models.The nomogram model based on the random forest model can ac-curately predict the risk of gastric cancer lymph node metastasis,thereby better guiding clinical di-agnosis and treatment decisions.

Objective To establish and validate a prediction model for gastric cancer lymph node metastasis based on four machine learning(ML)algorithms.Methods A retrospective analysis was conducted on clinical data of 531 patients who underwent radical gastrectomy.The patients were ran-domly divided into training set(399 patients)and test set(132 patients)in a ratio of 3 to 1.Univari-ate analysis was used to screen for variables associated with gastric cancer lymph node metastasis,and Logistic regression,random forest,K-nearest neighbor algorithm,and support vector machine algo-rithm models were established to rank the importance of variables.All ML algorithm models were vali-dated in the test set,and receiver operating characteristic(ROC)curves were plotted.The optimal ML algorithm model was determined based on the area under the curve(AUC),sensitivity,specifici-ty,and accuracy.A nomogram model was constructed based on the variable importance ranking of the optimal ML algorithm model.The discrimination,calibration,and clinical applicability of the nomo-gram model were evaluated using ROC curves,calibration curves,and decision curves.Results The results of the comparison of the four ML algorithm models showed that the random forest model was the optimal algorithm model.The accuracy,sensitivity,and specificity of the random forest model in the training set were 72.7％,69.9％,and 75.0％,respectively,with an AUC of 0.803.The accuracy,sensitivity,and specificity of the random forest model in the test set were 64.4％,66.7％,and 62.5％,respectively,with an AUC of 0.751.A nomogram model was constructed based on the variables of the random forest algorithm model.The ROC curve showed that the AUCs of the nomogram model in the training set and test set were 0.721 and 0.776,respectively.Calibration curves and decision curves showed that the nomogram model had good calibration and clinical applicability in both the training set and test set.Conclusion The random forest model is the optimal algorithm model a-mong the four ML algorithm models.The nomogram model based on the random forest model can ac-curately predict the risk of gastric cancer lymph node metastasis,thereby better guiding clinical di-agnosis and treatment decisions.

Objective:To extract the differentially expressed key genes of primary biliary cholangitis (PBC) using bioinformatics methods, so as to provide information for further study into the mechanism.Methods:The GSE119600 dataset was downloaded from the GEO database to obtain differentially expressed genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for differentially expressed genes. Protein-protein interaction (PPI) network reconstruction, Cytoscape software visualization, and core gene screening were performed. The area under the receiver operating characteristic curve (ROC AUC) was used to assess the diagnostic effectiveness of genes and plot the pROC software package. The x-Cell software was used to calculate the enrichment score of 34 immune cells in each sample. Finally, four key genes (PSMA4, PSMA1, PSMB1, and PSMA3) were selected. Blood samples were analyzed using the qPCR method.Results::A total of 373 immune-related differentially expressed genes were identified. Eight genes (PSMC6, PSMB2, PSMB1, PSMA3, PSMA4, PSMA1, PSMD7, and PSMB5) were screened from the 178 nodes and 596 edges as hub genes of the PPI network, which were significantly related to amino acid metabolism, hematopoietic stem cell differentiation, cell cycle, and immune processes. PSMA4, PSMA1, PSMB1, and PSMA3 were defined as immunological biomarkers for PBC with an AUC value of the ROC curve > 0.7. Immunoinfiltrating cell analysis showed that the proportion of eosinophils was significantly higher in PBC patients compared to the control group, whereas the proportion of CD4+ memory T cells, plasma cells, Th2 cells, and cDC cells was significantly lower in PBC patients than the control group. Plasma cells were associated with all four immunological biomarkers. Seven PBC patients and seven healthy subjects were selected for peripheral blood qPCR validation, which demonstrates that PSMB1, PSMA3, PSMA1, and PSMA4 levels were significantly lower in PBC patients than healthy subjects, with a statistically significant difference.Conclusion::Bioinformatics screened eight key genes, of which four were key immunological markers and may serve as a basis for clinical diagnosis and mechanism exploration.

Objective: To investigate the serotype distribution and antimicrobial susceptibility pattern of Streptococcus pneumoniae (S. pneumoniae), Haemophilus influenzae (H. influenzae) and Moraxella catarrhalis (M. catarrhalis) isolates collected from nasopharyngeal swabs from Uygur children in Kashi. Methods: Nasopharyngeal swabs were collected from inpatient Uygur children aged from 1 month to 5 years with respiratory infections from the pediatric department, the First People's Hospital of Kashi, Xinjiang Uygur Autonomous Region. Antimicrobial susceptibilities of the isolates were determined with E-test and KB disk diffusion methods. The production of β-lactamase was detected for H. influenzae and M. catarrhalisisolates using nitrocefin disc method. Quellung test and latex agglutination test were adopted to identify serotypes of S. pneumoniae and H. influenzae isolates. Results: Forty-seven S. pneumoniae, 13 H. influenzae and 16 M. catarrhalis isolates were detected. All of the 47 S. pneumoniae isolates were sensitive to parenteral penicillin, amoxicillin-clavulanic acid, vancomycin and levofloxacin; the susceptibility rates to cefotaxime, imipenem and chloramphenicol were 94% (44/47), 89% (42/47), and 98% (46/47). The resistance rate to erythromycin was 74% (35/47). The most common serotype of S. pneumoniae was serotype 19A (10 strains, 21%). The coverage rate of 13-valent conjugate vaccine (PCV13) was 70% (33/47). None of the 13 H. influenzae isolates could be typed. They were highly susceptible to tested β-lactams antibiotics, except ampicillin. Only one H. influenzae isolate could produce β-lactamase, and two isolates were identified as β-lactamase-negative-ampicillin-resistant ones. The sixteen M. catarrhalis isolates were all positive in β-lactamase detection, but sensitive to amoxicillin-clavulanic acid, cephalosporins and meropenem. Conclusions In Kashi, Xinjiang Uygur Autonmous Region, S. pneumoniae isolates from Uygur children were highly sensitive to parenteral penicillin and other β-lactams antibiotics. H. influenzae isolates from Uygur children were highly susceptible to amoxicillin-clavulanic acid, cephalosporins and ciprofloxacin. All M. catarrhalis isolates from Uygur children could produce β-lactamase, but were sensitive to the enzyme inhibitors and cephalosporins.

Objective:To understand the current situation of nurses in 52 hospitals in China on mastery of knowledge about skin injury in the elderly based on the background of mixed-mode homogenization training.Methods:Using the convenient sampling method, a total of 1 067 nurses from 52 hospitals in China were selected as the research objects in January 2021. A self-designed questionnaire on knowledge of skin injury in the elderly was used to investigate the nurses through the questionnaire star and univariate analysis was used to analyze the influencing factors. A total of 1 067 questionnaires were distributed and 1 067 valid questionnaires were recovered, and the effective recovery rate was 100%.Results:The knowledge scores of pressure injury, incontinence-associated dermatitis, skin tear and xerosis cutis among 1067 nurses were (95.66±7.37) , (95.65±9.15) , (91.37±15.45) and (87.67±15.91) , respectively. The results of univariate analysis showed that hospital grade was the influencing factor of nurses' knowledge score of pressure injury, skin tear and incontinence-associated dermatitis ( P<0.05) , educational background was the influencing factor of nurses' knowledge score of skin tear ( P<0.05) , professional title was the influencing factor of nurses' knowledge scores of pressure injury, incontinence-associated dermatitis and xerosis cutis ( P<0.05) . Conclusions:Hospitals at all levels need to strengthen the theoretical and practical knowledge training for nurses on skin xerosis and skin tear in the elderly, especially for nurses with primary titles and lower education in grassroots hospitals.

Hepatic stellate cells (HSCs) represent a significant component of hepatocellular carcinoma (HCC) microenvironments which play a critical role in tumor progression and drug resistance. Tumor-on-a-chip technology has provided a powerful in vitro platform to investigate the crosstalk between activated HSCs and HCC cells by mimicking physiological architecture with precise spatiotemporal control. Here we developed a tri-cell culture microfluidic chip to evaluate the impact of HSCs on HCC progression. On-chip analysis revealed activated HSCs contributed to endothelial invasion, HCC drug resistance and natural killer (NK) cell exhaustion. Cytokine array and RNA sequencing analysis were combined to indicate the iron-binding protein LIPOCALIN-2 (LCN-2) as a key factor in remodeling tumor microenvironments in the HCC-on-a-chip. LCN-2 targeted therapy demonstrated robust anti-tumor effects both in vitro 3D biomimetic chip and in vivo mouse model, including angiogenesis inhibition, sorafenib sensitivity promotion and NK-cell cytotoxicity enhancement. Taken together, the microfluidic platform exhibited obvious advantages in mimicking functional characteristics of tumor microenvironments and developing targeted therapies.