OBJECTIVE To improve the efficiency and quality of dispensed oral drug management in the inpatient pharmacy， and ensure the safety of drug use in patients. METHODS SWOT （strength， weakness， opportunity， threat） analysis method was used to analyze the internal strengths and weaknesses， as well as the external opportunities and threats in the construction of a closed-loop management system for dispensed oral drugs in the inpatient pharmacy of our hospital， and propose improvement strategies. RESULTS & CONCLUSIONS A refined， full-process， closed-loop traceability management system for dispensed oral drugs in the inpatient pharmacies was successfully established， which is traceable in origin， trackable in destination， and accountable in responsibility. After the application of this system， the registration rate of dispensed drug information and the correctness rate of registration content both reached 100%. The proportion of overdue drug varieties in the same period of 2024 decreased by 77.78% compared to March 2020， the inventory volume decreased by 29.50% compared to the first quarter of 2020， the per-bed medication volume decreased by 32.14% compared to the first quarter of 2020； the average workload per post in the same period of 2023 increased by 49.09% compared to 2019， the dispensing accuracy rate reached 100%， and the improvement rate of quality control problem increased by 25.25% compared to 2021. This system effectively improves the safety and accuracy of dispensed oral drug management in the inpatient pharmacy.

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 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

PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

OBJECTIVES: To investigate the clinical features and prognosis of children with non-Down-syndrome-related acute megakaryoblastic leukemia (non-DS-AMKL). METHODS: A retrospective analysis was conducted on the medical data of 17 children with non-DS-AMKL who were admitted to Children's Hospital of The First Affiliated Hospital of Zhengzhou University from January 2013 to December 2023, and their clinical features, treatment, and prognosis were summarized. RESULTS: Among the 17 children with non-DS-AMKL, there were 8 boys and 9 girls. Fourteen patients had an onset age of less than 36 months, with a median age of 21 months (range:13-145 months). Immunophenotyping results showed that 16 children were positive for CD61 and 13 were positive for CD41. The karyotype analysis was performed on 16 children, with normal karyotype in 6 children and abnormal karyotype in 9 children, among whom 5 had complex karyotype and 1 had no mitotic figure. Detected fusion genes included EVI1, NUP98-KDM5A, KDM5A-MIS18BP1, C22orf34-BRD1, WT1, and MLL-AF9. Genetic alterations included TET2, D7S486 deletion (suggesting 7q-), CSF1R deletion, and PIM1. All 17 children received chemotherapy, among whom 16 (94%) achieved complete remission after one course of induction therapy, and 1 child underwent hematopoietic stem cell transplantation (HSCT) and remained alive and disease-free. Of all children, 7 experienced recurrence, among whom 1 child received HSCT and died of graft-versus-host disease. At the last follow-up, six patients remained alive and disease-free. CONCLUSIONS Non-DS-AMKL primarily occurs in children between 1 and 3 years of age. The patients with this disorder have a high incidence rate of chromosomal abnormalities, with complex karyotypes in most patients. Some patients harbor fusion genes or gene mutations. Although the initial remission rate is high, the long-term survival rate remains low.
Humans ; Male ; Female ; Leukemia, Megakaryoblastic, Acute/etiology* ; Child, Preschool ; Infant ; Child ; Retrospective Studies ; Prognosis ; Down Syndrome/complications*

BACKGROUND: Mild cognitive impairment (MCI) is common in atrial fibrillation (AF) patients and may develop earlier in those with multiple cardiovascular comorbidities, potentially impairing self-management and treatment adherence. This study aimed to characterize the prevalence and profile of MCI in AF patients, examine its associations with cardiovascular comorbidities, and assess how these comorbidities influence specific cognitive domains. METHODS: This cross-sectional study analyzed data from AF patients who underwent cognitive assessment between 2017 and 2021. Cognitive status was categorized as MCI or non-MCI based on the Montreal Cognitive Assessment. Associations between comorbidities and MCI were assessed by logistic regression, and cognitive domains were compared using the Mann-Whitney U test. RESULTS: Of 4136 AF patients (mean age: 64.7 ± 9.4 years, 64.7% male), 33.5% of patients had MCI. Among the AF patients, 31.2% of patients had coronary artery disease, 20.1% of patients had heart failure, and 18.1% of patients had hypertension. 88.7% of patients had left atrial enlargement, and 11.0% of patients had reduced left ventricular ejection fraction. Independent factors associated with higher MCI prevalence included older age (OR = 1.04, 95% CI: 1.03-1.05, P < 0.001), lower education level (OR = 1.51, 95% CI: 1.31-1.73, P < 0.001), hypertension (OR = 1.28, 95% CI: 1.07-1.52, P = 0.001), heart failure (OR = 1.24, 95% CI: 1.04-1.48, P = 0.020), and lower left ventricular ejection fraction (OR = 1.43, 95% CI: 1.04-1.98, P = 0.028). A higher CHA₂DS₂-VASc score (OR = 1.27, 95% CI: 1.22-1.33, P < 0.001; ≥ 2 points vs. < 2 points), and greater atherosclerotic cardiovascular disease burden (OR = 1.45, 95% CI: 1.02-2.08, P = 0.040; 2 types vs. 0 type) were linked to increased MCI risk. These above factors influenced various cognitive domains. CONCLUSIONS MCI is common in AF and closely associated with cardiovascular multimorbidity. Patients with multiple comorbidities are at higher risk, highlighting the importance of routine cognitive assessment to support self-management and integrated care.