Objective:To explore the role and possible mechanism of ACOT11 in renal fibrosis model mice.Methods:A mouse model of renal fibrosis was established by unilateral ureteral obstruction(UUO)(Sham group and UUO7 group),and the expression of ACOT11 in the kidneys of UUO induced fibrosis mouse models was detected by protein immunoblotting and real-time fluorescence quantitative PCR(qRT-PCR).Subsequently,immunohistochemistry,Masson staining,H&E staining,PAS staining,and other experimental methods were used to detect the expression levels of fibrosis biomarkers fibronectin,α-SMA,and COL-1 in the kidneys of control and experimental group mice.In addition,by constructing ACOT11 gene knockout model mice and using the gene knockout model mice to construct a renal fibrosis model,the expression levels of fibrosis biomarkers such as fibronectin,α-SMA,COL-1,as well as fibrosis mechanism pathway related indicators TGF-β and Smad2 in the kidneys of each group of mice were further detected.Results:The results of WB and qRT-PCR experiments showed that the expression of ACOT11 in the kidney tissue of UUO model mice was significantly reduced compared to the Sham group.After knocking out the ACOT11 gene,H&E staining,PAS staining,and Masson staining showed that pathological inflammatory reactions such as abnormal glomerular and tubular structures,inflammatory cell infiltration and interstitial fibrous tissue proliferation in mice were significantly aggravated compared to the control group,and the expression of fibrosis markers Fibronectin,α-SMA,and COL-1 was significantly higher than that of the control group.Conclusion:ACOT11 plays a protective role in mice with unilateral ureteral obstruction model.After ACOT11 gene knockout,the fibrosis biomarkers of the mouse kidney increases and the degree of fibrosis worsens.

Objective:To construct a predictive model for mortality in patients with multiple trauma combined with thoracic injuries and evaluate its predictive value.Methods:A retrospective cohort study was conducted to analyze the clinical data of 184 patients with multiple trauma combined with thoracic injuries admitted to the International Zhuang Medicine Hospital Affiliated to Guangxi University of Chinese Medicine from April 2019 to December 2023, including 129 males and 55 females, aged 19-85 years [(46.1±13.7)years]. According to the prognostic outcomes at 3-month follow-up after discharge, the patients were divided into survival group ( n=145) and death group ( n=39). Data were recorded in both groups at admission, including gender, age, and cause of injury, laboratory tests such as systolic blood pressure, oxygen saturation (SaO 2), hemoglobin (Hb), neutrophil-to-lymphocyte ratio (NLR), and lactate, combined injuries such as the number of combined injuries, number of rib fracture, bilateral rib fracture, first-rib fracture, sternum fracture, thoracic vertebral fracture, bilateral pulmonary contusion, bilateral pneumothorax, subarachnoid hemorrhage, subdural hematoma, epidural hematoma, skull fracture, skull base fracture, cervical vertebral fracture, brain herniation, cerebral contusion, lumbar vertebral fracture, pelvic and abdominal cavity hematoma, liver injury, kidney injury, spleen injury, clavicle fracture, scapular fracture, femoral fracture, and pelvic fracture, and injury scores such as shock index (SI), modified shock index (MSI), injury severity score (ISS), revised trauma score (RTS), Glasgow coma score (GCS), and thoracic trauma severity (TTS) score. Univariate binary logistic regression analysis was used to screen for risk factors of death in patients with multiple trauma combined with thoracic injuries. LASSO regression and multivariate logistic regression analysis were employed to identify predictive variables and independent risk factors for mortality in those patients and to construct a regression equation. A nomogram prediction model based on the regression equation was developed using R language. Receiver operating characteristic (ROC) curves were plotted to evaluate the discrimination of the model. The ROC curves were internally validated using the Bootstrap method with 1 000 resamples. The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test. The clinical application value of the model was evaluated using decision curve analysis (DCA) and clinical impact curve (CIC) analysis. Results:There were statistically significant differences between the survival group and the death group in systolic blood pressure, SaO 2, NLR, lactate, number of combined injuries, subarachnoid hemorrhage, subdural hematoma, skull fracture, skull base fracture, brain herniation, liver injury, SI, MSI, ISS, RTS, GCS, and TTS ( P<0.05 or 0.01). The results of the univariate binary logistic regression analysis showed that the above-mentioned related variables except for systolic blood pressure were all significantly associated with death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Five predictive variables, TTS, GCS, brain herniation, ISS, and lactate were obtained in LASSO regression analysis. The results of the multivariate logistic regression analysis showed that GCS ( OR=0.70, 95% CI 0.58, 0.83), brain herniation ( OR=46.18, 95% CI 4.27, 499.26), TTS ( OR=1.71, 95% CI 1.30, 2.24), and lactate ( OR=1.35, 95% CI 1.01, 1.80) were independent risk factors for death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Based on the aforementioned independent risk factors, a regression formula was constructed as follows: P=e x/(1+e x), with the x=-0.36×"GCS"+3.83×"brain herniation"+0.53×"TTS"+0.30×"lactate levels"-11.03. The area under the ROC curve (AUC) of the predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on the equation was 0.97 (95% CI 0.93, 1.00). The AUC was internally validated using the Bootstrap method with 1 000 samples, resulting in an AUC of 0.97 (95% CI 0.91, 1.00). The results of the H-L goodness-of-fit test showed that the bias-corrected calibration curve of the model was in good consistence with the actual curve and both of them were close to the ideal curve. In the evaluation of the clinical application value of the predictive model, the DCA results showed that the predictive model could achieve good clinical net benefit. The CIC results showed that when the threshold probability was greater than 0.7, the model-identified high-risk patients for death highly matched the patients who actually died. Conclusion:The predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on GCS, brain herniation, TTS, and lactate has good predictive performance and clinical application value.

Objective To design a performance testing platform to evaluate the working status and performance characteristics of the ventilator proportional solenoid valve.Methods The performance testing platform had its hardware including a high-pressure gas source,a pressure regulating valve,sensors and etc,and its software designed based on PyQt5 and composed of several modules for data acquisition,parameter setting,image display,indicator computation,result output and etc.Two kinds of proportional solenoid valves(Valve 1、Valve2)were selected for static and dynamic tests to verify the performance of the platform.Results The platform developed facilitated the proportional solenoid valve to carry out accurate computation of static and dynamic indicators at real time and time domain and waveform feature extraction of sensor data by precision control and data acquisition for the proportional solenoid valve.Static tests showed that Valve 1 gained advantages over Valve 2 in static flow characteristics involving in lowered repeatability,return error and offset while enhanced stability;dynamic tests indicated Valve 2 had rapid flow variations and significant flow fluctuation impacts,Valve 1 showed smooth dynamic response changes,and Valve 2 behaved better than Valve 1 in dynamic performance.Conclusion The testing platform developed comprehensively demonstrates the performance characteristics and working performance of the ventilator proportional solenoid valve,which is of great significance to enhance the reliability and safety of the ventilator.[Chinese Medical Equipment Journal,2025,46(1):13-19]

AIM To investigate the effects of volatile oil from Acorus tatarinowii Schott(A.tatarinowii)on neuroinflammation in a rat model of tic disorders.METHODS The SD rats were randomly divided into the blank group(8 rats)and the model group(40 rats).The rat models of tic disorders established successfully by intraperitoneal injection of iminodiapropionitrile(IDPN)were further divided into the model group,the tiapride group and the high-dose,moderate-dose and low-dose A.tatarinowii volatile oil groups,with 8 rats in each group.The 4-week intragastric treatment of respective drug was initiated the next day after the completion of modeling,and normal saline was dosed upon the blank group and the model group,during which the rats' behavioral changes were assessed by stereotyped behavior and motor behavior score every week.After the administration,the rats had their morphological changes of striatal neurons observed by Nissl staining;their levels of TGF-β,IL-10,TNF-αand IL-1β in serum and striatum detected by ELISA;their striatal protein expressions of CX3CL1 and CX3CR1 detected by Western blot and immunohistochemistry;and their striatal expressions of M1,M2 microglia marker proteins CD86,CD206,SYN and PSD-95 detected by immunofluorescence co-staining.RESULTS Compared with the model group,the A.tatarinowii volatile oil groups demonstrated improved twitch-like behavior;decreased scores of motor behavior and rigid behavior(P＜0.01);alleviated damage of Nissl bodies in neurons;increased serum and striatum levels of TGF-β and IL-10(P＜0.05,P＜0.01);decreased levels of TNF-α and IL-1β(P＜0.01);decreased striatal protein expressions of CX3CL1 and CX3CR1(P＜0.01);increased protein expressions of PSD95 and SYN(P＜0.05,P＜0.01);and decreased CD86/Iba1(P＜0.01)and increased CD206/Iba1(P＜0.01)in terms of the fluorescence intensity.CONCLUSION A.tatarinowii volatile oil contributes an anti-tic effect and improves the neuroinflammation in the brain of the rat model of tic disorders by promoting the transformation of microglia into M2 type via CX3CL1/CX3CR1 signal axis.

Objective:To explore the role and possible mechanism of ACOT11 in renal fibrosis model mice.Methods:A mouse model of renal fibrosis was established by unilateral ureteral obstruction(UUO)(Sham group and UUO7 group),and the expression of ACOT11 in the kidneys of UUO induced fibrosis mouse models was detected by protein immunoblotting and real-time fluorescence quantitative PCR(qRT-PCR).Subsequently,immunohistochemistry,Masson staining,H&E staining,PAS staining,and other experimental methods were used to detect the expression levels of fibrosis biomarkers fibronectin,α-SMA,and COL-1 in the kidneys of control and experimental group mice.In addition,by constructing ACOT11 gene knockout model mice and using the gene knockout model mice to construct a renal fibrosis model,the expression levels of fibrosis biomarkers such as fibronectin,α-SMA,COL-1,as well as fibrosis mechanism pathway related indicators TGF-β and Smad2 in the kidneys of each group of mice were further detected.Results:The results of WB and qRT-PCR experiments showed that the expression of ACOT11 in the kidney tissue of UUO model mice was significantly reduced compared to the Sham group.After knocking out the ACOT11 gene,H&E staining,PAS staining,and Masson staining showed that pathological inflammatory reactions such as abnormal glomerular and tubular structures,inflammatory cell infiltration and interstitial fibrous tissue proliferation in mice were significantly aggravated compared to the control group,and the expression of fibrosis markers Fibronectin,α-SMA,and COL-1 was significantly higher than that of the control group.Conclusion:ACOT11 plays a protective role in mice with unilateral ureteral obstruction model.After ACOT11 gene knockout,the fibrosis biomarkers of the mouse kidney increases and the degree of fibrosis worsens.

Objective To design a performance testing platform to evaluate the working status and performance characteristics of the ventilator proportional solenoid valve.Methods The performance testing platform had its hardware including a high-pressure gas source,a pressure regulating valve,sensors and etc,and its software designed based on PyQt5 and composed of several modules for data acquisition,parameter setting,image display,indicator computation,result output and etc.Two kinds of proportional solenoid valves(Valve 1、Valve2)were selected for static and dynamic tests to verify the performance of the platform.Results The platform developed facilitated the proportional solenoid valve to carry out accurate computation of static and dynamic indicators at real time and time domain and waveform feature extraction of sensor data by precision control and data acquisition for the proportional solenoid valve.Static tests showed that Valve 1 gained advantages over Valve 2 in static flow characteristics involving in lowered repeatability,return error and offset while enhanced stability;dynamic tests indicated Valve 2 had rapid flow variations and significant flow fluctuation impacts,Valve 1 showed smooth dynamic response changes,and Valve 2 behaved better than Valve 1 in dynamic performance.Conclusion The testing platform developed comprehensively demonstrates the performance characteristics and working performance of the ventilator proportional solenoid valve,which is of great significance to enhance the reliability and safety of the ventilator.[Chinese Medical Equipment Journal,2025,46(1):13-19]

AIM To investigate the effects of volatile oil from Acorus tatarinowii Schott(A.tatarinowii)on neuroinflammation in a rat model of tic disorders.METHODS The SD rats were randomly divided into the blank group(8 rats)and the model group(40 rats).The rat models of tic disorders established successfully by intraperitoneal injection of iminodiapropionitrile(IDPN)were further divided into the model group,the tiapride group and the high-dose,moderate-dose and low-dose A.tatarinowii volatile oil groups,with 8 rats in each group.The 4-week intragastric treatment of respective drug was initiated the next day after the completion of modeling,and normal saline was dosed upon the blank group and the model group,during which the rats' behavioral changes were assessed by stereotyped behavior and motor behavior score every week.After the administration,the rats had their morphological changes of striatal neurons observed by Nissl staining;their levels of TGF-β,IL-10,TNF-αand IL-1β in serum and striatum detected by ELISA;their striatal protein expressions of CX3CL1 and CX3CR1 detected by Western blot and immunohistochemistry;and their striatal expressions of M1,M2 microglia marker proteins CD86,CD206,SYN and PSD-95 detected by immunofluorescence co-staining.RESULTS Compared with the model group,the A.tatarinowii volatile oil groups demonstrated improved twitch-like behavior;decreased scores of motor behavior and rigid behavior(P＜0.01);alleviated damage of Nissl bodies in neurons;increased serum and striatum levels of TGF-β and IL-10(P＜0.05,P＜0.01);decreased levels of TNF-α and IL-1β(P＜0.01);decreased striatal protein expressions of CX3CL1 and CX3CR1(P＜0.01);increased protein expressions of PSD95 and SYN(P＜0.05,P＜0.01);and decreased CD86/Iba1(P＜0.01)and increased CD206/Iba1(P＜0.01)in terms of the fluorescence intensity.CONCLUSION A.tatarinowii volatile oil contributes an anti-tic effect and improves the neuroinflammation in the brain of the rat model of tic disorders by promoting the transformation of microglia into M2 type via CX3CL1/CX3CR1 signal axis.

Objective:To construct a predictive model for mortality in patients with multiple trauma combined with thoracic injuries and evaluate its predictive value.Methods:A retrospective cohort study was conducted to analyze the clinical data of 184 patients with multiple trauma combined with thoracic injuries admitted to the International Zhuang Medicine Hospital Affiliated to Guangxi University of Chinese Medicine from April 2019 to December 2023, including 129 males and 55 females, aged 19-85 years [(46.1±13.7)years]. According to the prognostic outcomes at 3-month follow-up after discharge, the patients were divided into survival group ( n=145) and death group ( n=39). Data were recorded in both groups at admission, including gender, age, and cause of injury, laboratory tests such as systolic blood pressure, oxygen saturation (SaO 2), hemoglobin (Hb), neutrophil-to-lymphocyte ratio (NLR), and lactate, combined injuries such as the number of combined injuries, number of rib fracture, bilateral rib fracture, first-rib fracture, sternum fracture, thoracic vertebral fracture, bilateral pulmonary contusion, bilateral pneumothorax, subarachnoid hemorrhage, subdural hematoma, epidural hematoma, skull fracture, skull base fracture, cervical vertebral fracture, brain herniation, cerebral contusion, lumbar vertebral fracture, pelvic and abdominal cavity hematoma, liver injury, kidney injury, spleen injury, clavicle fracture, scapular fracture, femoral fracture, and pelvic fracture, and injury scores such as shock index (SI), modified shock index (MSI), injury severity score (ISS), revised trauma score (RTS), Glasgow coma score (GCS), and thoracic trauma severity (TTS) score. Univariate binary logistic regression analysis was used to screen for risk factors of death in patients with multiple trauma combined with thoracic injuries. LASSO regression and multivariate logistic regression analysis were employed to identify predictive variables and independent risk factors for mortality in those patients and to construct a regression equation. A nomogram prediction model based on the regression equation was developed using R language. Receiver operating characteristic (ROC) curves were plotted to evaluate the discrimination of the model. The ROC curves were internally validated using the Bootstrap method with 1 000 resamples. The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test. The clinical application value of the model was evaluated using decision curve analysis (DCA) and clinical impact curve (CIC) analysis. Results:There were statistically significant differences between the survival group and the death group in systolic blood pressure, SaO 2, NLR, lactate, number of combined injuries, subarachnoid hemorrhage, subdural hematoma, skull fracture, skull base fracture, brain herniation, liver injury, SI, MSI, ISS, RTS, GCS, and TTS ( P<0.05 or 0.01). The results of the univariate binary logistic regression analysis showed that the above-mentioned related variables except for systolic blood pressure were all significantly associated with death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Five predictive variables, TTS, GCS, brain herniation, ISS, and lactate were obtained in LASSO regression analysis. The results of the multivariate logistic regression analysis showed that GCS ( OR=0.70, 95% CI 0.58, 0.83), brain herniation ( OR=46.18, 95% CI 4.27, 499.26), TTS ( OR=1.71, 95% CI 1.30, 2.24), and lactate ( OR=1.35, 95% CI 1.01, 1.80) were independent risk factors for death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Based on the aforementioned independent risk factors, a regression formula was constructed as follows: P=e x/(1+e x), with the x=-0.36×"GCS"+3.83×"brain herniation"+0.53×"TTS"+0.30×"lactate levels"-11.03. The area under the ROC curve (AUC) of the predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on the equation was 0.97 (95% CI 0.93, 1.00). The AUC was internally validated using the Bootstrap method with 1 000 samples, resulting in an AUC of 0.97 (95% CI 0.91, 1.00). The results of the H-L goodness-of-fit test showed that the bias-corrected calibration curve of the model was in good consistence with the actual curve and both of them were close to the ideal curve. In the evaluation of the clinical application value of the predictive model, the DCA results showed that the predictive model could achieve good clinical net benefit. The CIC results showed that when the threshold probability was greater than 0.7, the model-identified high-risk patients for death highly matched the patients who actually died. Conclusion:The predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on GCS, brain herniation, TTS, and lactate has good predictive performance and clinical application value.

Background: Porcine circovirus type 2 (PCV2) infection is ubiquitous around the world.Diagnosis of the porcine circovirus-associated disease requires clinic-pathological elements together with the quantification of viral loads. Furthermore, given pig farms in regions lacking access to sufficient laboratory equipment, developing diagnostic devices with high accuracy, accessibility, and affordability is a necessity. Objectives: This study aims to investigate two newly developed diagnostic tools that may satisfy these criteria. Methods: We collected 250 specimens, including 170 PCV2-positive and 80 PCV2-negative samples. The standard diagnosis and cycle threshold (Ct) values were determined by quantitative polymerase chain reaction (qPCR). Then, two point-of-care (POC) diagnostic platforms, convective polymerase chain reaction (cPCR, qualitative assay: positive or negative results are shown) and EZtargex (quantitative assay: Ct values are shown), were examined and analyzed. Results: The sensitivity and specificity of cPCR were 88.23% and 100%, respectively; the sensitivity and specificity of EZtargex were 87.65% and 100%, respectively. These assays also showed excellent concordance compared with the qPCR assay (κ = 0.828 for cPCR and κ = 0.820 for EZtargex). The statistical analysis showed a great diagnostic power of the EZtargex assay to discriminate between samples with different levels of positivity. Conclusions The two point-of-care diagnostic platforms are accurate, rapid, convenient and require little training for PCV2 diagnosis. These POC platforms can discriminate viral loads to predict the clinical status of the animals. The current study provided evidence that these diagnostics were applicable with high sensitivity and specificity in the diagnosis of PCV2 infection in the field.

Objective To explore the correlation between the diameter of patients'autologous tendon and the prognosis of anterior cruciate ligament(ACL)reconstruction surgery.Methods From October 2018 to October 2023,82 patients who underwent anterior cruciate ligament reconstruction surgery at Wuxi No.904 Hospital were selected.Based on whether complications occurred after the anterior cruciate ligament reconstruction surgery,they were divided into a group with good prognosis(n=64)and a group with poor prognosis(n=18).Performing univariate analysis on the prognosis of anterior cruciate ligament reconstruction surgery.Pearson correlation analysis was used to analyze the relationship between tendon diameter and prognosis.A multifactorial Logistic regression model was applied to analyze the factors influencing the prognosis of ACL reconstruction and construct a nomogram.The diagnostic efficacy of tendon diameter on the prognosis of ACL reconstruction was analyzed using the receiver operating characteristic(ROC)curve.Results The results of the univariate analysis showed that there were statistically significant differences in gender and age between the two groups(P＜0.05).The tendon diameter and cross-sectional area in the group with a good prognosis were higher than those in the group with a poor prognosis(P＜0.05).Post-treatment,the Lysholm,Tegner,and IKDC scores in the group with a good prognosis were higher than those in the group with a poor prognosis(P＜0.05).Pearson correlation analysis showed a significant positive correlation between the patient's tendon diameter and Lysholm,Tegner,and IKDC scores(r=0.417,0.411、0.446,P＜0.05).Logistic analysis indicated that gender,age,tendon diameter,and tendon cross-sectional area are factors affecting the prognosis of ACL reconstruction(P＜0.05).The ROC curve results showed that the combined diagnostic effect of gender,age,tendon diameter,and cross-sectional area is significantly better than any single factor alone.Conclusion There is a significant correlation between the patient's autologous tendon diameter and the prognosis of ACL reconstruction surgery.An increase in autologous tendon diameter enhances knee joint function and improves patient prognosis.