0.05). Both the cost-effectiveness ratio and the ?C/?E in Group C were lower than in Group D. CONCLUSION: Group C is the best one in terms of cost-effectiveness.

Objective To determine the content of indirubin in Kangbingan Oral Liquid by UV spectrophotometer methods.Methods The content of indirubin was determined by Heltos Gamma ultravioletvisible spectrophotometer with chloroformic solution of 2～8 ?g/mL confected by standard sample of indigotin and indirubin.The sample of negative blank solution was confected by the prescription without Radix Isatidis.The standard sample and the blank sample were determined separately with the wavelength at 500～700 nm.Results Indirubin had the maximum absorption at wavelength of 540.0 nm and indigotin had the maximum absorption at wavelength of 634.5 nm.The linear correlation was available at the range of 0.20～1.40 ?g/mL,and the correct coefficient was 0.999 4.The average recovery rate was 99.05% and RSD was 0.87%(n=6).Conclusion This method is simple and accurate,and can be used to control the quality of Kangbingan Oral Liquid.

the terminal leaves,light saturation point was 1 302 ?mol/(m2?s),light compensation point was 101.5 ?mol/(m2?s);The diurnal change trend of Pn showed a double peak curve,presenting a typical phenomenon of "photosynthesis midday depression".There was a close correlation between Pn and stomatal conductance (Gs)(r=0.88,P

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Objective:To analyze the biomechanical stress distribution on the sagittal fractured of the mandibular condyle(SFMC) fixed by double plates in 3 different ways.Methods:The fixation finite element models with double straight plates(SS),one straight and one L-form plates(SL),and double L-form plates(LL)were established.The biomechanical stresses on condyle were calculated with finite element analysis.Results:In the model of SS fixation the maximum equivalent stress (MES),maximum total displacement (MTD)and maximum total corner(MTC)of condylar stump were 525.475 MPa,0.902 2 mm and 0.260 1°;MES,MTD,and MTC on fractured free-end were 4.425 MPa,0.882 7 mm and 0.019 9°,respectively.In the model of SL fixation MES,MTD and MTC on condylar stump were 1 135 MPa,0.9367 mm and 0.126 1°;MES,MTD and MTC on fractured free-end were 2.656 MPa,0.887 1 mm and 0.016 9°,respectively.In the model of LL fixation MES,MTD and MTC on condylar stump were 2 208 MPa,0.923 8 mm and 0.172 2°;MES,MTD and MTC on fractured free-end were 14.66 8 MPa,0.876 6 mm and 0.018 1°,respectively.Conclusion:Double L plates fixation is a proper way for SFMC.

AIM:To analyze circulating miR-141 in the serum as a non-invasive biomarker in the patients with prostate cancer ( PCa) and benign prostate hyperplasia ( BPH) , and healthy individuals.METHODS: A total of 75 pa-tients with PCa, 52 with BPH and 40 healthy individuals were enrolled into this study.Total RNA was isolated from the se-rum samples and the circulating levels of miR-141 were determined using quantitative real-time polymerase chain reaction. RESULTS:The serum levels of miR-141 were significantly higher in the patients with PCa compared to the patients with BPH and the healthy controls (P<0.01).The level of miR-141 in PCa group obviously differed from that in BPH group and healthy control group with high diagnosis performance, with areas under the curve of 0.785 and 0.801, respectively. No statistically significant difference of the serum miR-141 levels between the patients with BPH and healthy individuals was observed (P>0.05).The serum miR-141 level was also found to be related to Gleason score, clinical stage and bone me-tastasis status of the patients with PCa (P<0.05), and the patients with higher Gleason scores had higher serum miR-141 levels.No relationship was detected between miRNA-141 level and the patient’ s age, biochemistry recurrence and serum prostate-specific antigen level (P>0.05 for all comparisons).CONCLUSION: Circulating miR-141 could serve as a non-invasive biomarker for prostate cancer diagnosis, staging and prognosis prediction.