The purpose of this study was to ascertain the usefullness of four mental health measures in their application to Chinese elderly subjects. These measures which included CES—D, GHQ—30, LSI, and MST were adapted to assess general symptoms of depression and minor psychiatic disorder, life satisfaction, and mental state of the elderly people. Results of these findings indicated that split—half and test—retest reliabilities of these measures were highly satisfactory. With respect to validity, test performace of a group of psychiatric patients (N=31) and normal elderly subjects (N=30) were found to be significantly differencetiated. Furthermore, the pattern of scores obtained by the psychiatric patients also matched well with the clinical diagnosis made by a consultant. Normative data in an old—old sample (N=554) revealed mild to moderate correlations between measures, reflecting favourably on their convergent validity. Significant sex differences were found, which necessitated the establishment of separate norms for males and females subjects.

BACKGROUND:Locking compression plate and dynamic hip screw are the two major extramedul ary fixations for the femoral intertrochanteric fractures, however, the comparison of the clinical efficacy between two methods is stil controversial. OBJECTIVE:To systematical y evaluate the clinical efficacy of locking compression plate versus dynamic hip screw in the treatment of femoral intertrochanteric fractures, and provide a theoretical basis for clinical application. METHODS:Authors searched for control ed studies on locking compression plate and dynamic hip screw in the treatment of femoral intertrochanteric fractures in PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, VIP periodical database, Wanfang resource database, Chinese Biomedical Literature service systems published from January 1999 to April 2014. The inclusion and exclusion criteria were made, and the literature meeting the criteria was screened, and the methodological quality of the included studies was evaluated. Meta-analysis was carried out using the RevMan 5.2 software. RESULTS AND CONCLUSION:Ultimately 682 patients from 8 studies met the inclusion criteria, including 336 patients in the locking compression plate group and 346 patients in the dynamic hip screw group. Meta-analysis results showed that:there were no statistical y significant differences in operating time [MD=-12.07, 95%CI (-29.85, 5.71), P=0.18], peri-operative bleeding loss [MD=-15.01, 95%CI (-87.85, 57.83), P=0.69], post-operation drainage [MD=-13.62, 95%CI (-28.49, 1.26), P=0.07], ambulation time [MD=-0.14, 95%CI (-0.68, 0.41), P=0.63], length of hospitalization [MD=-0.74, 95%CI (-2.29, 0.82), P=0.35], bone union time [MD=-1.18, 95%CI (-2.78, 0.42), P=0.15] between locking compression plate and dynamic hip screw groups. The excellent and good rate of postoperative hip function reduction [OR=2.03, 95%CI (1.23, 3.36), P=0.006] was significantly higher in locking compression plate group than in the dynamic hip screw group. The incidence of coxa vara was lower in the locking compression plate group than in the dynamic hip screw group [OR=0.34, 95%CI (0.12, 0.96), P=0.04]. There were no significant differences in looseness, breakage, withdrawal of internal fixation [OR=1.20, 95%CI (0.59, 2.45), P=0.61] and the incidence of total complications [OR=0.55, 95%CI (0.24, 1.28), P=0.16] between locking compression plate and dynamic hip screw groups. However, the included studies have high possibility of selection bias and measurement bias, and wil affect proof strength of results. Therefore, more clinical randomized control ed studies with compact design are needed for verification.

Objective:To investigate the prediction value of observed to expected lung area to head circumference ratio (o/e LHR), measured at different gestational age with various methods, on indication for extracorporeal membrane oxygenation (ECMO) in fetuses with isolated left-sided congenital diaphragmatic hernia (CDH).Methods:Clinical data of 40 neonates who were diagnosed with left-sided CDH and treated in Guangzhou Women and Children's Medical Center were retrospectively collected from January 2017 to May 2021. The o/e LHRs were prenatally calculated using maximum diameter and tracing method at 22-24 and 31-33 weeks of gestation. According to whether the neonates had indications for ECMO after birth or not, they were divided into ECMO ( n=12) or non-ECMO group ( n=28). Differences in the o/e LHR and general situations between the two groups were analyzed using C hi-square test, independent sample t-test, and non-parametric Mann-Whitney U test. Binary logistic regression was used to analyze the influencing factors for ECMO requirement and receiver operating characteristic (ROC) curve was used to evaluate the value of o/e LHR in predicting the indication for ECMO. Results:Both maximum diameter and tracing method suggested that the o/e LHR at 31-33 gestational weeks was lower than that at 22-24 gestational weeks [maximun diameter method: 40.4 (32.9-51.5) vs 45.1 (36.3-53.4), Z=－2.48, P=0.013; tracing method: 38.6 (33.2-47.6) vs 44.1 (35.9-51.7), Z=－3.29, P=0.001]. There was no statistical difference in o/e LHR detected at the same gestational weeks between the two methods (both P>0.05). Binary logistic regression showed that o/e LHR measured at 31-33 gestational weeks using maximum diameter method was an independent protective factor for ECMO requirement ( OR=0.873, 95% CI: 0.790-0.965, P=0.008). ROC curve analysis showed that the area under the curve for evaluating the predictive value of o/e LHR for ECMO requirement was 0.830 with the sensitivity of 83.3% and the specificity of 71.4% when the cut-off value of o/e LHR at 31-33 gestational weeks was 38.195 measured by maximum diameter method. Conclusions:The o/e LHR measured at 31-33 weeks is lower than that at 22-24 weeks of gestation by both methods. The o/e LHR measured by maximum diameter method at 31-33 weeks of gestation may be useful for predicting the ECMO indication after birth but requiring comprehensive evaluation of clinical conditions due to its insufficient predicting power.

OBJECTIVE: The aim of this study was to use a guinea pig model of prolonged allergic-induced rhinitis to characterize the feature of nasal mucosa remodeling. METHOD: Forty-eight male Hartley guinea pigs were randomly divided into six groups: allergen challenged groups (Group OVA(2w) , Group OVA(6w) and Group OVA(12w)) and control groups respectively (Group Sal(2w), Group Sal(6w) and Group Sal(12w)). Each group had 8 guinea pigs. To develop a guinea pig model of nasal mucosa remodeling, ovalbumin-sensitized guinea pigs were repeatedly challenged with allergen twice a week from two weeks to 12 weeks. Matched control groups were challenged with physiological saline. Nasal lavage was performed 24 hours after the last intranasal challenge. Then nasal mucosa were obtained. HE, AB-PAS, MT, and immunohistochemical staining against transforming growth factor-beta1 (TGF-beta1) were performed. Eosinophil cationic protein (ECP) and OVA-special IgE (OVA-sIgE) were detected by ELISA in nasal lavage fluid. RESULT: (1) The levels of OVA-sIgE in nasal lavage fluid in Group OVA(6w) and Group OVA(12w) were significantly different from Group OVA(2w), while the levels of ECP had no significant difference among the experiment groups. The levels of OVA-sIgE and ECP in experiment groups were significantly different from control groups respectively (P < 0.01). (2) Grade 0 and Grade 1 of epithelial damage were significantly different in Group OVA(6w) and Group OVA(12w) when compared with from Group OVA(2w) (P < 0.01). At the same time, Grade 0 and Grade 1 of epithelial damage were statistically different in the experiment groups when compared with the respectively control groups (P < 0.05). (3) Goblet gland hyperplasia and collagen deposit within the extracellular matrix (ECM) were easily found in Group OVA(6w) and Group OVA(12w) compared with Group OVA(2w) (P < 0.01). The number of goblet gland and the ratio of collagen deposit were statistically more in Group OVA(6w) and Group OVA(12w) than in Group Sal(6w) and Group Sal(12w) (P < 0.05). That feature of the ratio of collagen deposit did not show in Group OVA(2w) versus Group Sal(2w). (4) Increased TGF-beta1 expressions were observed in Group OVA(6w) and Group OVA(12w) compared with Group OVA(2w) (P < 0.01). Those increasing expressions were also observed in experiment groups rather than in the respectively control groups (P < 0.01). CONCLUSION Epithelial damage, goblet cells hyperplasia and collagen deposition in ECM were observed as the features of remodeling in this guinea pig model of allergic rhinitis under prolonged allergen challenge. Epithelial damage, excessive expression of related cytokines and enhancement activity of enzymes were observed in early time after challenge of allergen. The features of goblet cells hyperplasia and collagen deposition in ECM were observed at a later stage.
Airway Remodeling ; Allergens ; immunology ; Animals ; Disease Models, Animal ; Guinea Pigs ; Male ; Nasal Mucosa ; immunology ; pathology ; Rhinitis, Allergic, Perennial ; immunology ; pathology

OBJECTIVE: The aim of this study was to explore the changes of the extracellular matrix in nasal mucosa by a guinea pig model of prolonged allergic-induced rhinitis. METHOD: Thirty-two male Hartley guinea pigs were randomly divided into four groups: allergen challenged groups (Group 2 w, Group 6 w and Group 12 w) and a control group. Ovalbumin-sensitized guinea pigs were repeatedly challenged with allergen twice a week from 2 weeks to 12 weeks. Matched control groups were challenged with physiological saline. Nasal mucosa were obtained from the animals killed. Hematoxylin-Eosin, Masson's trichrome, and immunohistochemical staining against transforming growth factor-beta1 (TGF-beta1), Collagen III and Collagen I were performed to nasal mucosa. RESULT: (1) Pathological examination showed obvious infiltration of eosinophils and the enlarged thickness of epithelial layer of nasal mucosa in the experiment groups. (2) The area ratios of blue stained in the extracellular matrix of nasal mucosa were increased. The area ratios of blue stained were statistically different in Group 6 w and Group 12 w compared with the control group. (3) The increasing absorbance of TGF-beta1 were statistically different in the experiment groups with the control group. The absorbance of Collagen III and Collagen I showed a rising trend along prolonged allergen challenged in the experiment groups. CONCLUSION Prolonged allergen challenge and the inflammation of nasal mucosa, can lead to the increasing of the inflammation relevant factors and the deposit of collagen in the extracellular matrix of nasal mucosa.
Allergens ; immunology ; Animals ; Collagen Type I ; metabolism ; Collagen Type III ; metabolism ; Eosinophils ; immunology ; Extracellular Matrix ; immunology ; metabolism ; pathology ; Guinea Pigs ; Inflammation ; Male ; Nasal Mucosa ; immunology ; metabolism ; pathology ; Rhinitis, Allergic, Perennial ; immunology ; metabolism ; pathology ; Transforming Growth Factor beta1 ; metabolism

BACKGROUND:Hypoxia is strongly associated with the development and progression of osteoarthritic chondrocyte injury,but the specific targets and regulatory mechanisms are unclear. OBJECTIVE:A machine learning approach was used to identify KDEL(Lys-Asp-Glu-Leu)receptor 3(KDELR3)as a characteristic gene for osteoarthritis hypoxia and immune infiltration analysis,to provide new ideas and methods for the treatment of osteoarthritis. METHODS:The osteoarthritis-related datasets were downloaded from the GEO database and the GSEA website to obtain hypoxia-related genes.The osteoarthritis datasets were batch-corrected and immune infiltration analyzed using R language,and osteoarthritis hypoxia genes were extracted for differential analysis.Differentially expressed genes were analyzed for GO function and KEGG signaling pathway.Weighted correlation network analysis(WGCNA)and machine learning were also used to screen osteoarthritis hypoxia signature genes,and in vitro cellular experiments were performed to validate expression and correlate immune infiltration analysis using the datasets and qPCR. RESULTS AND CONCLUSION:(1)8492 osteoarthritis genes were obtained by batch correction and principal component analysis,mainly strongly associated with immune cells such as Macrophages M2 and Mast cells resting;200 hypoxia genes were also obtained,resulting in 41 osteoarthritis hypoxia differentially expressed genes.(2)GO analysis involved mainly biological processes such as response to nutrient levels and glucocorticoids;cellular components such as lysosomal lumen and Golgi lumen;and molecular functions such as 14-3-3 protein binding and DNA-binding transcriptional activator activity.(3)KEGG analysis of osteoarthritis hypoxia differentially expressed genes was associated with signaling pathways such as PI3K-Akt,FoxO,and microRNAs in cancer.(4)The characteristic gene KDELR3 was obtained after using WGCNA analysis and machine learning screening.(5)The gene expression of KDELR3 was found to be higher in the test group than in the control group in the synovium(P=0.014)but lower in the meniscus(P=0.024)after validation by gene microarray.(6)In vitro chondrocyte assay showed that the expression of KDELR3 was higher in cartilage than in the control group(P=0.005),while KDELR3 was closely associated with Macrophages M0(P=0.014)and T cells follicular helper(P=0.014).Using a machine learning approach,we confirmed that KDELR3 can be used as a hypoxic signature gene for osteoarthritis and may intervene in osteoarthritis pathogenesis by improving hypoxia,expecting to provide a new direction for better treatment of osteoarthritis.

BACKGROUND:Ferroptosis is strongly associated with the occurrence and progression of osteoarthritis,but the specific characteristic genes and regulatory mechanisms are not known. OBJECTIVE:To identify osteoarthritis ferroptosis signature genes and immune infiltration analysis using the WGCNA and various machine learning methods. METHODS:The osteoarthritis dataset was downloaded from the GEO database and ferroptosis-related genes were obtained from the FerrDb website.R language was used to batch correct the osteoarthritis dataset,extract osteoarthritis ferroptosis genes and perform differential analysis,analyze differentially expressed genes for GO function and KEGG signaling pathway.WGCNA analysis and machine learning(random forest,LASSO regression,and SVM-RFE analysis)were also used to screen osteoarthritis ferroptosis signature genes.The in vitro cell experiments were performed to divide chondrocytes into normal and osteoarthritis model groups.The dataset and qPCR were used to verify expression and correlate immune infiltration analysis. RESULTS AND CONCLUSION:(1)12 548 osteoarthritis genes were obtained by batch correction and PCA analysis,while 484 ferroptosis genes were obtained,resulting in 24 differentially expressed genes of osteoarthritis ferroptosis.(2)GO analysis mainly involved biological processes such as response to oxidative stress and response to organophosphorus,cellular components such as apical and apical plasma membranes,and molecular functions such as heme binding and tetrapyrrole binding.(3)KEGG analysis exhibited that differentially expressed genes of osteoarthritis ferroptosis were related to signaling pathways such as the interleukin 17 signaling pathway and tumor necrosis factor signaling pathway.(4)After using WGCNA analysis and machine learning screening,we obtained the characteristic gene KLF2.After validation by gene microarray,we found that the gene expression of KLF2 was higher in the test group than in the control group in the meniscus(P=0.000 14).(5)In vitro chondrocyte assay showed that type Ⅱ collagen and KLF2 expression was lower in the osteoarthritis group than in the control group in chondrocytes(P<0.05),while in osteoarthritis ferroptosis,mast cells activated was closely correlated with dendritic cells(r=0.99);KLF2 was closely correlated with natural killer cells(r=-1,P=0.017)and T cells follicular helper(r=-1,P=0.017).(6)The findings indicate that using WGCNA analysis and machine learning methods confirmed that KLF2 can be a characteristic gene for osteoarthritis ferroptosis and may improve osteoarthritis ferroptosis by interfering with KLF2.