This study investigated the effects of Rehmanniae Radix Praeparata on striatal neuronal apoptosis in rats with attention deficit hyperactivity disorder(ADHD) based on the B-cell lymphoma-2(Bcl-2)/Bcl-2-associated X protein(Bax)/caspase-3 signaling pathway. Twenty-four 3-week-old male spontaneously hypertensive rats(SHR) were randomly divided into a model group, a methylphenidate group(2 mg·kg~(-1)·d~(-1)), and a Rehmanniae Radix Praeparata group(2.4 mg·kg~(-1)·d~(-1)). Age-matched male Wistar Kyoto(WKY) rats were used as the normal control group, with 8 rats in each group. The rats were administered by gavage for 28 days. Body weight and food intake were recorded for each group. The open field test and elevated plus maze test were used to assess hyperactivity and impulsive behaviors. Nissl staining was used to detect changes in striatal neurons and Nissl bodies. Terminal deoxynucleotidyl transferase dUTP nick end labeling(TUNEL) fluorescence staining was used to detect striatal cell apoptosis. Western blot was employed to detect the expression levels of Bcl-2, Bax, and caspase-3 proteins in the striatum. The results showed that compared with the model group, Rehmanniae Radix Praeparata significantly reduced the total movement distance, average movement speed, and central area residence time in the open field test, and significantly reduced the ratio of open arm entries, open arm stay time, and head dipping in the elevated plus maze test. Furthermore, it increased the number of Nissl bodies in striatal neurons, significantly downregulated the apoptosis index, significantly increased Bcl-2 protein expression and the Bcl-2/Bax ratio, and reduced Bax and caspase-3 protein expression. In conclusion, Rehmanniae Radix Praeparata can reduce hyperactivity and impulsive behaviors in ADHD rats. Its mechanism may be related to the regulation of the Bcl-2/Bax/caspase-3 signaling pathway in the striatum, enhancing the anti-apoptotic capacity of striatal neurons.
Animals ; Male ; Apoptosis/drug effects* ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Caspase 3/genetics* ; Proto-Oncogene Proteins c-bcl-2/genetics* ; bcl-2-Associated X Protein/genetics* ; Rehmannia/chemistry* ; Attention Deficit Disorder with Hyperactivity/physiopathology* ; Signal Transduction/drug effects* ; Neurons/cytology* ; Rats, Inbred SHR ; Rats, Inbred WKY ; Humans ; Corpus Striatum/cytology* ; Plant Extracts

Objective To explore the risk factors for noncontiguous spinal fractures(NSFs)in the elderly.Methods The clinical data of 614 elderly patients with spinal fracture from January 2013 to December 2019 were analyzed retrospectively.Patients were divided into the NSFs group and the Non-NSFs group according to whether NSFs occurred or not.Univariate analysis and multivariate Logistic regression analysis were used to screen the risk factors of NSFs.Results Univariate analysis showed that female(P=0.003),high-energy violent injury(P=0.032),osteoporosis(P=0.004),fracture in spring(P=0.020),and previous spinal fracture history(P<0.001)were associated with the occurrence of NSFs.Multivariate Logistic regression analysis showed that fracture in spring(P=0.024),previous spinal fracture history(P<0.001)and high-energy violent injury(P=0.038)were the independent risk factors for the occurrence of NSFs in the elderly.Conclusion High-energy violent injury,fracture in spring and previous spinal fracture history are the independent risk factors for the occurrence of NSFs in the elderly.Therefore,elderly patients with the above risk factors should be examined more carefully and comprehensively to avoid missed diagnosis and delayed diagnosis.In order to reduce the incidence of this disease,corresponding measures should be taken according to the preventable risk factors.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Objective To compare the effects of different detector combinations of 320-row CT on the image quality and radiation dose of head CT to explore the feasibility of using a wide detector for head CT scanning.Methods Totally 100 patients underwent head CT scanning due to trauma or cerebrovascular disease at some hospital from June to August 2023 were collected prospectively and divided into group A and group B by using block randomization grouping method,with the length of the block group being 2 and 50 patients in each group.In group A,all the detectors had the widths at z-axis direction being 40×0.5 mm and head scanning was completed after multiple exposures;in group B,detector combinations with widths of 280×0.5 mm or 320×0.5 mm were chosen based on the patient's head size in the head-foot direction(z-axis direction),and head scanning was performed with a single-turn exposure.The remaining scanning and image reconstruction parameters in the two groups were kept completely consistent.The head image quality of the 2 groups was evaluated objectively and scored subjectively by 2 radiologists.The volume CT dose index(CTDIvol),dose length product(DLP)and exposure time of the 2 groups were recorded,and the effective dose(ED)was calculated.SPSS 22.0 software was used for statistical analysis.Results In terms of objective evaluation of image quality,at the level of the parietal skull group B had the CT value of gray matter,image noise and contrast to noise ratio(CNR)of the images higher than those of group A,and the differences were statistically significant(all P<0.05);at the level of the posterior skull group B had the CT values of gray and white matter,image noise and air noise lower while CNR higher than those of group A,and the differences were statistically significant(all P<0.05).In terms of subjective scoring of image quality,at the levels of parietal and posterior skull group A behaved better than group B,and the differences were statistically significant(all P<0.05).In group A 5 patients had obvious motion artifacts affecting the diagnosis and the image quality scores not higher than 2,and secondary scanning had to be carried out;In group B all the patients had no obvious motion artifacts and met the diagnosis requirements.When compared with group A Group B had the CTDIvol,DLP,ED and exposure time decreased by 17.44%,17.24%,17.48%and 85.53%,respectively,and the differences were statistically significant(all P<0.05).Conclusion A wide detector gains advantages over a 20 mm detector in image quality when 320-row CT is used for head CT scanning,with the diagnosis requirements satisfied.[Chinese Medical Equipment Journal,2025,46(4):57-62]

Objective To compare the effects of different detector combinations of 320-row CT on the image quality and radiation dose of head CT to explore the feasibility of using a wide detector for head CT scanning.Methods Totally 100 patients underwent head CT scanning due to trauma or cerebrovascular disease at some hospital from June to August 2023 were collected prospectively and divided into group A and group B by using block randomization grouping method,with the length of the block group being 2 and 50 patients in each group.In group A,all the detectors had the widths at z-axis direction being 40×0.5 mm and head scanning was completed after multiple exposures;in group B,detector combinations with widths of 280×0.5 mm or 320×0.5 mm were chosen based on the patient's head size in the head-foot direction(z-axis direction),and head scanning was performed with a single-turn exposure.The remaining scanning and image reconstruction parameters in the two groups were kept completely consistent.The head image quality of the 2 groups was evaluated objectively and scored subjectively by 2 radiologists.The volume CT dose index(CTDIvol),dose length product(DLP)and exposure time of the 2 groups were recorded,and the effective dose(ED)was calculated.SPSS 22.0 software was used for statistical analysis.Results In terms of objective evaluation of image quality,at the level of the parietal skull group B had the CT value of gray matter,image noise and contrast to noise ratio(CNR)of the images higher than those of group A,and the differences were statistically significant(all P<0.05);at the level of the posterior skull group B had the CT values of gray and white matter,image noise and air noise lower while CNR higher than those of group A,and the differences were statistically significant(all P<0.05).In terms of subjective scoring of image quality,at the levels of parietal and posterior skull group A behaved better than group B,and the differences were statistically significant(all P<0.05).In group A 5 patients had obvious motion artifacts affecting the diagnosis and the image quality scores not higher than 2,and secondary scanning had to be carried out;In group B all the patients had no obvious motion artifacts and met the diagnosis requirements.When compared with group A Group B had the CTDIvol,DLP,ED and exposure time decreased by 17.44%,17.24%,17.48%and 85.53%,respectively,and the differences were statistically significant(all P<0.05).Conclusion A wide detector gains advantages over a 20 mm detector in image quality when 320-row CT is used for head CT scanning,with the diagnosis requirements satisfied.[Chinese Medical Equipment Journal,2025,46(4):57-62]

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Objective To explore the risk factors for noncontiguous spinal fractures(NSFs)in the elderly.Methods The clinical data of 614 elderly patients with spinal fracture from January 2013 to December 2019 were analyzed retrospectively.Patients were divided into the NSFs group and the Non-NSFs group according to whether NSFs occurred or not.Univariate analysis and multivariate Logistic regression analysis were used to screen the risk factors of NSFs.Results Univariate analysis showed that female(P=0.003),high-energy violent injury(P=0.032),osteoporosis(P=0.004),fracture in spring(P=0.020),and previous spinal fracture history(P<0.001)were associated with the occurrence of NSFs.Multivariate Logistic regression analysis showed that fracture in spring(P=0.024),previous spinal fracture history(P<0.001)and high-energy violent injury(P=0.038)were the independent risk factors for the occurrence of NSFs in the elderly.Conclusion High-energy violent injury,fracture in spring and previous spinal fracture history are the independent risk factors for the occurrence of NSFs in the elderly.Therefore,elderly patients with the above risk factors should be examined more carefully and comprehensively to avoid missed diagnosis and delayed diagnosis.In order to reduce the incidence of this disease,corresponding measures should be taken according to the preventable risk factors.

Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.

Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.

Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3％.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.