Objective To compare five time series models and predict the monthly incidence of bacillary dysentery in Qinghai Province in 2024,and provide reference for the prevention and control.Methods The epidemic charac-teristics of bacterial dysentery in Qinghai Province from 2014 to 2023 were analyzed.R4.3.1 software was used for establishing seasonal autoregressive integrated moving average(SARIMA)model,Holt-Winters triple exponential smoothing(Holt Winters)model,exponential smoothing(ETS)model,neural network autoregression(NNAR)model,and trigonometric seasonality,Box-Cox transformation,ARMA errors,trend and seasonal components(TBATS)model.Fitting effect of the models was analyzed and accuracy was compared.Results From 2014 to 2023,a total of 5 833 cases of bacterial dysentery were reported in Qinghai Province,without deaths,male to fe-male ratio being 1.23∶1.The highest incidence was reported in 2016(15.45 per 100 000 people),and the lowest in-cidence was reported in 2023(3.68 per 100 000 people).Incidence increased from 2014 to 2016,then decreased,showing an obvious overall downward trend.Case number in＜5 years age group was the highest,accounting for 29.76％of the total cases(n=1 736).Regarding population distribution,the top three were children in childcare institutions and scattered children(35.56％),farmers(24.65％),and students(12.62％).Except the additive Holt-Winters model,the predicted trends of the other four models were consistent with actuality.The ETS model had the best fitting effect,with a relatively balanced overall performance(training set:MAE=0.13,RMSE=0.21,MAPE=19.55％;testing set:MAE=0.11,RMSE=0.16,MAPE=28.66％).It is recommended to pre-dict the incidence of bacillary dysentery in Qinghai Province based on ETS model.Conclusion From 2014 to 2023,bacterial dysentery in Qinghai Province showed a downward trend,with the peak of the epidemic from June to Au-gust.Preschool and scattered children were high-risk groups.Among the five prediction models,ETS model has the best fitting effect,and can be used to predict the incidence of bacillary dysentery.

Objective To compare five time series models and predict the monthly incidence of bacillary dysentery in Qinghai Province in 2024,and provide reference for the prevention and control.Methods The epidemic charac-teristics of bacterial dysentery in Qinghai Province from 2014 to 2023 were analyzed.R4.3.1 software was used for establishing seasonal autoregressive integrated moving average(SARIMA)model,Holt-Winters triple exponential smoothing(Holt Winters)model,exponential smoothing(ETS)model,neural network autoregression(NNAR)model,and trigonometric seasonality,Box-Cox transformation,ARMA errors,trend and seasonal components(TBATS)model.Fitting effect of the models was analyzed and accuracy was compared.Results From 2014 to 2023,a total of 5 833 cases of bacterial dysentery were reported in Qinghai Province,without deaths,male to fe-male ratio being 1.23∶1.The highest incidence was reported in 2016(15.45 per 100 000 people),and the lowest in-cidence was reported in 2023(3.68 per 100 000 people).Incidence increased from 2014 to 2016,then decreased,showing an obvious overall downward trend.Case number in＜5 years age group was the highest,accounting for 29.76％of the total cases(n=1 736).Regarding population distribution,the top three were children in childcare institutions and scattered children(35.56％),farmers(24.65％),and students(12.62％).Except the additive Holt-Winters model,the predicted trends of the other four models were consistent with actuality.The ETS model had the best fitting effect,with a relatively balanced overall performance(training set:MAE=0.13,RMSE=0.21,MAPE=19.55％;testing set:MAE=0.11,RMSE=0.16,MAPE=28.66％).It is recommended to pre-dict the incidence of bacillary dysentery in Qinghai Province based on ETS model.Conclusion From 2014 to 2023,bacterial dysentery in Qinghai Province showed a downward trend,with the peak of the epidemic from June to Au-gust.Preschool and scattered children were high-risk groups.Among the five prediction models,ETS model has the best fitting effect,and can be used to predict the incidence of bacillary dysentery.

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 compare clinical effects of external fixation and minimally invasive percutaneous plate osteosynthesis (MIPPO) after external fixation in treating open fractures of tibial shaft. METHODS: From January 2020 to June 2022, 151 patients with open fracture of tibial shaft treated with external fixation stenting were divided into external fixation group and combined group according to different surgical methods. There were 81 patients in external fixation group, including 48 males and 33 females, aged from 21 to 68 years old with an average of (42.58±7.44) years old;according to Gustilo classification, 49 patients with typeⅡ, 32 patients with type ⅢA;the time from injury to treatment ranged from 2.5 to 10 h with an average of (4.25±0.74) h;external fixed stenting was performed. There were 70 patients in combined group, including 42 males and 28 females, aged from 20 to 69 years old with an average of (41.39±7.02) years old;35 patients with type Ⅱ and 35 patients with type ⅢA according to Gustilo classification;the time from injury to treatment ranged from 3 to 9 h with an average of (4.31±0.85) h;MIPPO treatment was performed after external fixed stenting. The time of callus formation, fracture healing and complications were compared between two groups. Rasmussen score and Hospital for Special Surgery (HSS) score were used to evaluate functional recovery of knee joint at 6 months after operation. RESULTS: Both groups were followed up for 6 to 13 months with an average of (10.17±2.33) months. The time of callus formation and fracture healing were (13.98±4.02) d and (70.26±12.15) d in combined group, and (18.56±4.37) d and (79.87±15.41) d in external fixation group, respectively. Combined group was better than external fixation group in the time of callus formation and fracture healing (P<0.05). At six months after operation, Rasmussen and HSS scores in combined group were (26.79±3.11) and (83.36±9.44), which were higher than those in external fixation group (24.51±4.63) and (79.63±8.46) (P<0.05). In external fixation group, there were 2 patients with incision infection, 2 patients with nail tract infection, 1 patient with stent loosening, fracture displacement, delayed union and malunion, and 1 patient with biocompatibility reaction in combined group, with statistical significance between two groups (P<0.05). CONCLUSION MIPPO could accelerate callus formation and fracture healing, improve knee function, improve clinical effects and reduce complications in patients with open tibial shaft fractures after external and external fixation.
Humans ; Male ; Female ; Middle Aged ; Adult ; Aged ; Tibial Fractures/physiopathology* ; Fracture Fixation, Internal/methods* ; Retrospective Studies ; Bone Plates ; External Fixators ; Fractures, Open/physiopathology* ; Stents ; Young Adult

OBJECTIVE: To analyze the clinical efficacy of manual reduction combined with 3D printing small splint external fixation and synchronous manual reduction combined with traditional small splint external fixation in the treatment of humeral shaft. METHODS: Between January 2021 and December 2022, 40 patients with humeral shaft fractures were treated with 3D printing small splints and traditional small splints. They were divided into 3D group and traditional group according to different fixation methods. Among them, there were 15 males and 5 females in the 3D group, aged from 20 to 52 years old with an average of (36.3±15.6) years old. In the traditional group there were 17 males and 3 females, aged from16 to 51 years old with an average of (32.9±17.2) years old. The occurrence of complications, duration of fracture healing, rate of fracture healing, subjective evaluation scores for brace comfort at 1 week and 4 weeks, as well as the Constant-Murley shoulder function score and Mayo elbow function score at 8 weeks and 16 weeks were compared between the two groups. RESULTS: All patients were followed up for 16 weeks. The 3D group did not experience any complications, while there were two cases of complications in the traditional group. However, this difference was not found to be statistically significant (χ²=2.105, P=0.146). The fracture healing time of the 3D group (90.1±4.5) days was significantly shorter compared to that of the traditional group (93.3±3.8) days (P<0.05). The subjective evaluation scores for brace comfort in the 3D group (53.7±2.3) points and (62.8±1.1) points were significantly higher than those in the traditional group (45.6±2.4) points and (52.3±1.4) points at 1 and 4 weeks after reduction (P<0.05). After 8 weeks of reduction, the Constant-Murley shoulder function score in the 3D group was(68.1±5.3) points, which demonstrated a statistically significant improvement compared to the traditional group(54.3±4.9) points (P<0.05). However, at 16 weeks post-reduction, there were no significant differences observed between the two groups (P>0.05). The Mayo elbow function score of the 3D group (84.1±7.5) points was significantly superior to that of the traditional group (79.5±6.8) points at 8 weeks post-reduction (P<0.05). However, there was no statistically significant difference between the two groups at 16 weeks post-reduction (P>0.05). CONCLUSION For humeral shaft fractures with conservative treatment indications, manual reduction combined with 3D printed small splints is a good choice for treatment. The patient's comfort level is higher, which can not only reduce the occurrence of complications, but also improve the fracture healing rate and joint function to a certain extent, and improve the patient's quality of life.
Humans ; Female ; Male ; Adult ; Middle Aged ; Humeral Fractures/physiopathology* ; Printing, Three-Dimensional ; Splints ; Adolescent ; Young Adult ; Fracture Healing

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 investigate the clinical manifestations,molecular genetics and gonadal pathol-ogy characteristics of patients with disorders of sex development(DSD),and to summarize the clinical experi-ence of identifying rare diseases from common symptoms.Methods The clinical data of 416 patients with DSD diagnosed and treated in the multidisciplinary center of DSD of Guangzhou Women and Children's Medical Cen-ter from May 2018 to August 2023 were retrospectively analyzed,summarized and discussed.Results Accord-ing to chromosome karyotype,416 cases of DSD were classified into three types:92 cases(22.1％)of abnormal sex chromosome karyotype,285 cases(68.5％)of 46,XY karyotype and 39 cases(9.4％)of 46,XX karyotype.Among the 92 patients with abnormal sex chromosome karyotype,59 cases were raised as males,18 cases(30.5％)complained of short penis with hypospadias and cryptorchidism.The most common karyotype was 45,X/46,XY(58 cases,63.0％).Among the 285 patients with 46,XY karyotype,238 cases were raised as males,and 63 cases(26.5％)complained of short penis and hypospadias;47 cases were raised as females,and 13 ca-ses(27.7％)complained of inguinal mass.A total of 216 patients with 46,XY karyotype were subjected to whole exome gene detection,and 155 cases(71.8％)were found to have molecular pathogenesis with the clinical phe-notype.Among the 39 patients with 46,XX karyotype,19 cases were raised as males,and 8 cases(42.1％)com-plained of short penis and hypospadias.In the 18 cases of gonad biopsy,17 cases showed testicular tissue in go-nads.Whole exome sequencing was performed in 14 cases.NR5A1 gene heterozygous mutation,SRY gene muta-tion and SOX3 gene mutation were found in 2 cases,respectively(14.3％).Twenty cases were raised as females,and 14 cases(70.0％)complained of clitoral hypertrophy.Gonad biopsy was performed in 8 cases,with 7 cases of ovotestis(87.5％)and 1 case of NR5A1 gene heterozygous mutation(14.3％).Conclusions The etiologies of DSD are complex and diverse,and the clinical manifestations are various,which can be manifested as hypospa-dias,micropenis,cryptorchidism and other common symptoms of the urinary system.Different etiologies have dif-ferent treatment options.Therefore,chromosome karyotype,molecular genetic testing and gonadal pathology can be used to clarify the cause of disease,especially for rare diseases,improve the detection rate,reduce the rate of missed diagnosis,and ensure reasonable treatment,especially sex selection.