To evaluate long-term survival and clinical outcomes of patients with knee osteo-arthritis undergoing total knee arthroplasty (TKA) through long-term follow-up.

BACKGROUND:Cervical disc herniation can cause pain in the neck and shoulder area,as well as radiating pain in the upper limbs.The incidence rate is increasing year by year and tends to affect younger individuals.Fully understanding the biomechanical characteristics of the cervical spine in adolescents is of great significance for preventing and delaying the onset of cervical disc herniation in this age group. OBJECTIVE:To reconstruct cervical spine models for both healthy adolescents and adolescent patients with cervical disc herniation utilizing finite element analysis techniques,to analyze the motion range of the C1-T1 cervical vertebrae as well as the biomechanical characteristics of the annulus fibrosus,nucleus pulposus,endplates,and the cartilage of the small joints. METHODS:A normal adolescent's cervical spine and an adolescent patient with cervical disc herniation were selected in this study.The continuous scan cervical spine CT raw image data were imported into Mimics 21.0 in DICOM format.The C1-T1 vertebrae were reconstructed separately.Subsequently,the established models were imported into the 3-Matic software for disc reconstruction.The perfected models were then imported into Hypermesh software for meshing of the vertebrae,nucleus pulposus,annulus fibrosus,and ligaments,creating valid geometric models.After assigning material properties,the final models were imported into ABAQUS software to observe the joint motion range of the C1-C7 cervical vertebrae segments under different conditions,and to analyze the biomechanical characteristics of the annulus fibrosus,nucleus pulposus,endplates,and small joint cartilage of each cervical spine segment. RESULTS AND CONCLUSION:(1)In six different conditions,the joint motion range of the C1 vertebra in the cervical spine models of both normal adolescent and adolescent patient with cervical disc herniation was higher than that of the other vertebrae.Additionally,the joint motion range of each cervical spine segment in normal adolescent was greater than that in adolescent patient with cervical disc herniation.(2)In the cervical spine model of normal adolescent,the maximum stress values in the annulus fibrosus and nucleus pulposus were found on the left side during C2-3 flexion conditions(0.43 MPa and 0.17 MPa,respectively).In the cervical spine model of adolescent patient with cervical disc herniation,the maximum stress values were found on the left side during C7-T1 flexion conditions(0.54 MPa and 0.18 MPa,respectively).(3)In the cervical spine model of normal adolescent,the maximum stress value on the endplate was found on the left side of the upper endplate of C3 during flexion conditions(1.46 MPa).In the model of adolescent patient with cervical disc herniation,the maximum stress value on the endplate was found on the left side of the lower endplate of C7 during flexion conditions(1.32 MPa).(4)In the cervical spine model of normal adolescent,the maximum stress value in the small joint cartilage was found in the C2-3 left rotation conditions(0.98 MPa).In adolescent patient with cervical disc herniation,the stress in the small joint cartilage significantly increased under different conditions,especially in C1-2,with the maximum stress found during left flexion(3.50 MPa).(5)It is concluded that compared to normal adolescent,adolescent patient with cervical disc herniation exhibits altered cervical curvature and a decrease in overall joint motion range in the cervical spine.In adolescent with cervical disc herniation,there is a significant increase in stress on the annulus fibrosus,nucleus pulposus,and endplates in the C7-T1 segment.The stress on the left articular cartilage of the C1-2 is notable.Abnormal cervical curvature may be the primary factor causing these stress changes.

Background: The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies. Methods: MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function. Results: Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores. Conclusion Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.

Background: The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies. Methods: MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function. Results: Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores. Conclusion Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.

Background: The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies. Methods: MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function. Results: Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores. Conclusion Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.

Background: The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies. Methods: MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function. Results: Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores. Conclusion Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.

Objective: To reveal the molecular biological mechanism of a rare Dc-variant individual using PacBio third-generation sequencing technology. Methods: ABO and Rh blood type identification, DAT, unexpected antibody screening and D antigen enhancement test were conducted by serological testing. The absorption-elution test was used to detect the e antigen. RHCE gene typing was performed by PCR-SSP, and the 1-10 exons of RHCE were sequenced by Sanger sequencing. The full-length sequences of RHCE, RHD and RHAG were detected by PacBio third-generation sequencing technology. Results: Serological findings: Blood type O, Dc-phenotype, DAT negative, unexpected antibody screening negative; enhanced D antigen expression; no detection of e antigen in the absorption-elution test. PCR-SSP genotyping indicated the presence of only the RHCE c allele. Sanger sequencing results: Exons 5-9 of RHCE were deleted, exon 1 had a heterozygous mutation at c. 48G/C, and exon 2 had five heterozygous mutations at c. 150C/T, c. 178C/A, c. 201A/G, c. 203A/G and c. 307C/T. Third-generation sequencing results: RHCE genotype was RHCE 02N. 08/RHCE-D(5-9)-CE; RHD genotype was RHD 01/RHD 01; RHAG genotype was RHAG 01/RHAG 01 (c. 808G>A and c. 861G>A). Conclusion: This Dc-individual carries the allele RHCE 02N. 08 and the novel allele RHCE-D(5-9)-CE. The findings of this study provide data support and a theoretical basis for elucidating the molecular mechanisms underlying RhCE deficiency phenotypes.

Objective To evaluate the effect of a multidisciplinary collaborative quality control management (hereinafter referred to as "QC management") on improving the performance of biological safety cabinets in hospital. Methods A total of 63 ClassⅡbiological safety cabinets in active use at Peking University Third Hospital were selected as the study subjects using the before-after study mode. Conventional management was implemented on the biological safety cabinets from 2018 to 2021. QC management was used in 2022. The compliance of biological safety cabinets management norm and performance differences under the two models were compared. Results The median and the 25th and 75th percentiles [M(P₂₅, P₇₅)] of the service life among these 63 biological safety cabinets were 3 (1,6) years. The overall performance pass rate and inflow velocity pass rate of biological safety cabinets were higher in the QC management than that in the conventional management (90.5% vs 65.1%, 96.8% vs 84.1%, both P<0.05). However, there was no significant difference in downflow velocity, high-efficiency particulate air filter integrity, cleanliness, airflow smoke pattern, noise, and illumination pass rates of biosafety cabinets before and after the implementation of QC management (79.4% vs 88.9%, 90.5% vs 100.0%, 96.8% vs 100.0%, 85.7% vs 100.0%, 100.0% vs 100.0%, and 85.7% vs 96.8%, respectively; all P>0.05). Conclusion sQC management improves the standardization of biological safety cabinet management and key performance indicators in hospital.

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control