OBJECTIVE To investigate the inhibitory effect mechanism of Anzheng Kangliu Decoction against colorectal cancer by suppressing glycolysis through regulation of the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target of rapamycin(mTOR)signaling pathway.METHODS Human colorectal cancer SW620 cells were treated with Anzheng Kangliu De-coction,and cell proliferation and migration abilities were assessed.Forty-two BALB/c nude mice were randomly divided into a blank control group,model group,5-fluorouracil(5-FU)group(0.025 g·kg-1),Anzheng Kangliu Decoction low-dose group(7.67 g·kg-1),medium-dose group(15.34 g·kg-1),and high-dose group(30.68 g·kg-1).The inhibitory effect of Anzheng Kan-gliu Decoction on subcutaneous xenograft tumors was evaluated by observing body weight,tumor volume,tumor mass,HE staining,im-munohistochemical staining of Ki67 and other indicators.High-throughput transcriptome sequencing was performed to identify differen-tially expressed genes and pathways in tumor tissues between the model group and the Anzheng Kangliu Decoction medium-dose group,elucidating the potential mechanism of Anzheng Kangliu Decoction against colorectal cancer.Glucose and lactate assay kits were used to measure glucose consumption and lactate production in SW620 cells and tumor tissues after Anzheng Kangliu Decoction intervention.Western blot was employed to detect the expression levels of p-PI3K/PI3K,p-Akt/Akt,p-mTOR/mTOR,hexokinase 2(HK2),and lactate dehydrogenase A(LDHA)in SW620 cells and tumor tissues following Anzheng Kangliu Decoction treatment.RE-SULTS In vitro cell experiments demonstrated that,compared with the blank control group,Anzheng Kangliu Decoction intervention significantly inhibited the proliferation and migration of SW620 cells(P<0.01),reduced glucose consumption and lactate production(P<0.05,P<0.01),and downregulated the protein expression levels of p-PI3K/PI3K,p-Akt/Akt,p-mTOR/mTOR,HK2,and LDHA(P<0.05,P<0.01).In vivo animal experiments revealed that,compared with the model group,Anzheng Kangliu Decoction suppressed the growth of subcutaneous xenograft tumors in nude mice(P<0.01),increased tumor tissue necrosis,decreased glucose consumption and lactate production in tumor tissues(P<0.05,P<0.01),and reduced the protein expression levels of p-PI3K/PI3K,p-Akt/Akt,p-mTOR/mTOR,HK2,and LDHA(P<0.05,P<0.01).CONCLUSION Anzheng Kangliu Decoction exerts an in-hibitory effect on colorectal cancer,and its mechanism may be associated with the suppression of glycolysis through regulation of the PI3K/Akt/mTOR signaling pathway.

Objective:To development a deep learning（DL） model based on conventional MRI for automatic segmentation and differential diagnosis of nasopharyngeal carcinoma（NPC） and nasopharyngeal lymphoma（NPL）. Methods:The retrospective study included 142 patients with NPL and 292 patients with NPC who underwent conventional MRI at Renmin Hospital of Wuhan University from June 2012 to February 2023. MRI from 80 patients were manually segmented to train the segmentation model. The automatically segmented regions of interest（ROIs） formed four datasets: T1 weighted images（T1WI）, T2 weighted images（T2WI）, T1 weighted contrast-enhanced images（T1CE）, and a combination of T1WI and T2WI. The ImageNet-pretrained ResNet101 model was fine-tuned for the classification task. Statistical analysis was conducted using SPSS 22.0. The Dice coefficient loss was used to evaluate performance of segmentation task. Diagnostic performance was assessed using receiver operating characteristic（ROC） curves. Gradient-weighted class activation mapping（Grad-CAM） was imported to visualize the model's function. Results:The DICE score of the segmentation model reached 0.876 in the testing set. The AUC values of classification models in testing set were as follows: T1WI: 0.78（95%CI 0.67-0.81）, T2WI: 0.75（95%CI 0.72-0.86）, T1CE: 0.84（95%CI 0.76-0.87）, and T1WI+T2WI: 0.93（95%CI 0.85-0.94）. The AUC values for the two clinicians were 0.77（95%CI 0.72-0.82） for the junior, and 0.84（95%CI 0.80-0.89） for the senior. Grad-CAM analysis revealed that the central region of the tumor was highly correlated with the model's classification decisions, while the correlation was lower in the peripheral regions. Conclusion:The deep learning model performed well in differentiating NPC from NPL based on conventional MRI. The T1WI+T2WI combination model exhibited the best performance. The model can assist in the early diagnosis of NPC and NPL, facilitating timely and standardized treatment, which may improve patient prognosis.
Humans ; Nasopharyngeal Carcinoma/diagnostic imaging* ; Deep Learning ; Magnetic Resonance Imaging ; Retrospective Studies ; Nasopharyngeal Neoplasms/diagnostic imaging* ; Lymphoma/diagnostic imaging* ; Diagnosis, Differential ; ROC Curve ; Male ; Female ; Middle Aged ; Adult

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.

For middle-aged and elderly patients with conditions such as spinal fractures and degenerative spinal diseases, spinal internal fixation is a core surgical procedure for reconstructing spinal stability, heavily relying on the biomechanical stability provided by pedicle screw systems. Whereas, these patients are often complicated by osteoporosis that can significantly compromise the stability of the bone-pedicle screw interface, leading to a marked increase in pedicle screw loosening and surgical failure rates. The bone cement-augmented pedicle screw technique, which involves injecting bone cement into the vertebral body or screw trajectory to optimize the mechanical properties of the bone-pedicle screw composite, has been proven to significantly enhance fixation strength and effectively prevent screw-related failures, thereby reducing the incidence of internal fixation failure in high-risk populations undergoing spinal fusion. However, the widespread clinical application of this technique has faced challenges such as inaccurate clinical decision-making (indication and contraindication selection), non-standardized operative practices, and insufficient awareness of complication prevention, resulting in considerable variability in clinical outcomes and even severe complications. To address this, Prof. Luo Fei from First Affiliated Hospital of Army Medical University initiated the project and the Chinese Association Orthopaedic Surgeons organized relevant experts to develop the Evidence-based clinical practice guideline for bone cement-augmented pedicle screw technique ( version 2025), based on current evidence. The guidelines put forward 8 recommendations regarding the clinical value, scope of application, and operational standards of the technique, aiming to provide evidence-based medical support and technical standardization for clinical decision-making.

OBJECTIVE To investigate the inhibitory effect mechanism of Anzheng Kangliu Decoction against colorectal cancer by suppressing glycolysis through regulation of the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target of rapamycin(mTOR)signaling pathway.METHODS Human colorectal cancer SW620 cells were treated with Anzheng Kangliu De-coction,and cell proliferation and migration abilities were assessed.Forty-two BALB/c nude mice were randomly divided into a blank control group,model group,5-fluorouracil(5-FU)group(0.025 g·kg-1),Anzheng Kangliu Decoction low-dose group(7.67 g·kg-1),medium-dose group(15.34 g·kg-1),and high-dose group(30.68 g·kg-1).The inhibitory effect of Anzheng Kan-gliu Decoction on subcutaneous xenograft tumors was evaluated by observing body weight,tumor volume,tumor mass,HE staining,im-munohistochemical staining of Ki67 and other indicators.High-throughput transcriptome sequencing was performed to identify differen-tially expressed genes and pathways in tumor tissues between the model group and the Anzheng Kangliu Decoction medium-dose group,elucidating the potential mechanism of Anzheng Kangliu Decoction against colorectal cancer.Glucose and lactate assay kits were used to measure glucose consumption and lactate production in SW620 cells and tumor tissues after Anzheng Kangliu Decoction intervention.Western blot was employed to detect the expression levels of p-PI3K/PI3K,p-Akt/Akt,p-mTOR/mTOR,hexokinase 2(HK2),and lactate dehydrogenase A(LDHA)in SW620 cells and tumor tissues following Anzheng Kangliu Decoction treatment.RE-SULTS In vitro cell experiments demonstrated that,compared with the blank control group,Anzheng Kangliu Decoction intervention significantly inhibited the proliferation and migration of SW620 cells(P<0.01),reduced glucose consumption and lactate production(P<0.05,P<0.01),and downregulated the protein expression levels of p-PI3K/PI3K,p-Akt/Akt,p-mTOR/mTOR,HK2,and LDHA(P<0.05,P<0.01).In vivo animal experiments revealed that,compared with the model group,Anzheng Kangliu Decoction suppressed the growth of subcutaneous xenograft tumors in nude mice(P<0.01),increased tumor tissue necrosis,decreased glucose consumption and lactate production in tumor tissues(P<0.05,P<0.01),and reduced the protein expression levels of p-PI3K/PI3K,p-Akt/Akt,p-mTOR/mTOR,HK2,and LDHA(P<0.05,P<0.01).CONCLUSION Anzheng Kangliu Decoction exerts an in-hibitory effect on colorectal cancer,and its mechanism may be associated with the suppression of glycolysis through regulation of the PI3K/Akt/mTOR signaling pathway.

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.

For middle-aged and elderly patients with conditions such as spinal fractures and degenerative spinal diseases, spinal internal fixation is a core surgical procedure for reconstructing spinal stability, heavily relying on the biomechanical stability provided by pedicle screw systems. Whereas, these patients are often complicated by osteoporosis that can significantly compromise the stability of the bone-pedicle screw interface, leading to a marked increase in pedicle screw loosening and surgical failure rates. The bone cement-augmented pedicle screw technique, which involves injecting bone cement into the vertebral body or screw trajectory to optimize the mechanical properties of the bone-pedicle screw composite, has been proven to significantly enhance fixation strength and effectively prevent screw-related failures, thereby reducing the incidence of internal fixation failure in high-risk populations undergoing spinal fusion. However, the widespread clinical application of this technique has faced challenges such as inaccurate clinical decision-making (indication and contraindication selection), non-standardized operative practices, and insufficient awareness of complication prevention, resulting in considerable variability in clinical outcomes and even severe complications. To address this, Prof. Luo Fei from First Affiliated Hospital of Army Medical University initiated the project and the Chinese Association Orthopaedic Surgeons organized relevant experts to develop the Evidence-based clinical practice guideline for bone cement-augmented pedicle screw technique ( version 2025), based on current evidence. The guidelines put forward 8 recommendations regarding the clinical value, scope of application, and operational standards of the technique, aiming to provide evidence-based medical support and technical standardization for clinical decision-making.

To investigate the effects of ORF9 gene of porcine circovirus type 2(PCV2)on PK-15,eu-karyotic expression plasmid was constructed and transfected into PK-15 cells,and the effects of overexpression of ORF9 on proliferation,apoptosis and immunization of PK-15 cells were exam-ined by flow cytometry and qRT-PCR.The results showed that ORF9 gene overexpression signifi-cantly up-regulated the expression levels of the ER stress marker gene GRP78,increased the num-ber of S phase cells,accelerated cell cycle progression,increased the apoptosis rate of PK-15 cells,up-regulated the expression levels of apoptosis-related genes caspase-3,caspase-8,caspase-9,p53 and Bax(P＜0.01),down-regulated the expression levels of apoptosis-related genes Bcl-2,up-reg-ulated the expression levels of immune-related genes 1L-8,IL-10,NF-κB and TNF-α(P＜0.01),and down-regulated the expression levels of immune-related genes IL-2,IFN-β and IL-12(P＜0.01).The above results indicate that ORF9 gene may promote the proliferation and apoptosis of PK-15 cells and play a role in the escape process of PK-15 cells.

In order to understand the genomic characteristics and genetic variation and strain type of infectious bursal disease virus(IBDV)isolate GZGY2022,which caused the death of chickens in Guizhou farm,primers were designed to amplify the whole genome of the isolate,and genetic evo-lution and strain type analysis were performed after cloning and sequencing.The results showed that the A and B segments of IBDV genome were 3 260,2 827 bp,respectively,encoding VP2-VP5 and VP1 genes.The nucleotide sequence homology between the A and B segments of this strain and the VvIBDV were 96.2％-98.7％and 87.7％-98.9％,respectively,which is the highest with NN1172 strain,83.1％-94.7％and 90.1％-91.0％with other strains.The results of genetic evolution and strain type study showed that IBDV strains can be divided into 6 branches according to antigen and virulence,and the A and B segments of the strain were clustered in the evolutionary branch of VvIBDV,and the strain was A3B3 genotype according to the new genotype classification method.The results of amino acid sequence analysis showed that there were 3 and 7 unique amino acid site variations in the A and B segments of the strain,respectively,and 13 unique characteristic amino acid sites in the coding region of the full-length genome were consistent with VvIBDV.The VP2 sequence of segment A has 19 characteristic amino acid identical with VvIBDV,among which hyper variable regions 222A,242I,253Q,256I,279D,284A,294I and 299S were characteristic ami-no acid sites of the VvIBDV,and the heptapeptide region sequence SWSASGS was consistent with the virulent strain.The VP1 sequence of segment B has 10 characteristic amino acid identical with VvIBDV,among which 61I,145T and 287A were the characteristic amino acid sites of the VvIB-DV.In addition,the nucleotide sequence GGTGCC of 777-782 did not form the restriction endo-nuclease site of Kpn Ⅰ,and combined with the triplet site 145/146/147(TEG),the segment B was consistent with the NN1172 strain,showed that its virulence was slightly weaker than that of the B2 strain of VvIBDV.The results of recombination analysis showed that there were no breaks and recombination sites in the sequence of the strain,and no recombination event occurred.In summa-ry,this study found that GZGY2022 strain belonged to the A3B3 genotype non-recombinant VvIB-DV strain,and its special amino acid sites were consistent with the molecular characteristics of VvIBDV.This study lays the foundation for further exploring the genomic characteristics and path-ogenicity of VvIBDV.

{L-End}Objective To explore the impact of workplace violence (WPV) on occupational burnout among healthcare workers. {L-End}Methods A total of 675 healthcare workers from an infectious disease hospital were selected as the study subjects using typical sampling method. The Workplace Violence in the Healthsector Country Case Studies Research Instruments: Survey Questionnaire and the Maslach Burnout Inventory 2-item were used to investigate the incidence of WPV and occupational burnout. {L-End}Results The incidence of WPV among the study subjects was 35.1%, with incidences of physical and psychological violence at 2.2% and 34.1%, respectively. The detection rates of emotional exhaustion, depersonalization, and occupational burnout were 25.9%, 12.6%, and 52.4%, respectively. The result of multifactorial logistic regression analysis showed that experiencing psychological violence, having a bachelor or master degree or higher, and having more concerns about WPV were influencing factors for emotional exhaustion (all P<0.05). Knowing the reporting process for violent incidents and having more concerns about WPV were influencing factors for depersonalization (all P<0.05). Being in a minority ethnic group, having a bachelor, a master degree or higher, experiencing psychological violence, and having more concerns about WPV were influencing factors for occupational burnout (all P<0.05). {L-End}Conclusion WPV increases the risk of occupational burnout among healthcare workers. Effective measures should be implemented to reduce the incidence of WPV, decrease the level of occupational burnout, and promote the overall well-being of healthcare workers.