Objective:To evaluate the clinical utility of machine learning model based radiomics in predicting high-risk molecular subtypes of lower-grade gliomas(LrGGs).Methods:This was a cross-sectional study. A total of 287 patients diagnosed with LrGGs in the First Hospital of Shanxi Medical University, Shanxi Provincial People′s Hospital, and the Third Hospital of Shanxi Medical University from January 2011 to September 2023 were retrospectively collected, including 166 males and 121 females; 114 cases of high-risk molecular subtypes and 173 cases of non-high-risk molecular subtypes. All patients were divided into 201 cases in the training set and 86 cases in the test set according to 7∶3 in simple randomized grouping method. All patients underwent contrast-enhanced T 1WI (CE-T 1WI) and T 2-weighted fluid-attenuated inversion recovery sequence imaging (T 2-FLAIR), and the imaging features of high-risk and non-high-risk molecular subtypes were analyzed. Analysis of variance, recursive feature elimination, and Kruskal-Wallis were used for radiomics feature screening, and a support vector machine (SVM) classifier was used to construct a radiomics-based classifier model. Univariate and multivariate logistic regression were used to analyze clinical variables independently influencing high-risk molecular subtypes of LrGGs to construct a clinical model; a combined model was developed by integrating radiomics labels and clinical variables. Receiver operating characteristic curve and area under the curve (AUC), calibration curve, and decision curve were used to compare the predictive performance of different models. Results:The patient′s age ( OR=1.042, 95% CI 1.018-1.068, P=0.001), pathological grade ( OR=2.270, 95% CI 1.212-4.311, P=0.011), MGMT methylation status ( OR=0.456, 95% CI 0.238-0.866, P=0.017), and ependymal involvement ( OR=7.335, 95% CI 2.929-18.370, P<0.001) were independent influencing factors for the high-risk molecular subtype of LrGGs, and a clinical model was developed based on these factors. An SVM model was constructed based on 12 radiomics features (3 radiomics features based on CE-T 1WI and 9 radiomics features based on T 2-FLAIR). The radiomics score of the probability output by the SVM model was combined with age, pathological grade, MGMT methylation status, and ependymal involvement to develop a combined model. The AUC values of the SVM model for predicting the high-risk molecular subtype of LrGGs were 0.824 and 0.859 in the training set and test set, respectively; the AUC values of the clinical model in the training set and test set were 0.759 and 0.721, respectively; and the AUC values of the combined model in the training set and test set were 0.823 and 0.815, respectively. The combined model had a high clinical net benefit. Conclusion:The machine learning MRI radiomics model can preoperatively predict high risk molecular subtypes of LGGrs, assist in individualized treatment decisions.

Objective:To evaluate the clinical utility of machine learning model based radiomics in predicting high-risk molecular subtypes of lower-grade gliomas(LrGGs).Methods:This was a cross-sectional study. A total of 287 patients diagnosed with LrGGs in the First Hospital of Shanxi Medical University, Shanxi Provincial People′s Hospital, and the Third Hospital of Shanxi Medical University from January 2011 to September 2023 were retrospectively collected, including 166 males and 121 females; 114 cases of high-risk molecular subtypes and 173 cases of non-high-risk molecular subtypes. All patients were divided into 201 cases in the training set and 86 cases in the test set according to 7∶3 in simple randomized grouping method. All patients underwent contrast-enhanced T 1WI (CE-T 1WI) and T 2-weighted fluid-attenuated inversion recovery sequence imaging (T 2-FLAIR), and the imaging features of high-risk and non-high-risk molecular subtypes were analyzed. Analysis of variance, recursive feature elimination, and Kruskal-Wallis were used for radiomics feature screening, and a support vector machine (SVM) classifier was used to construct a radiomics-based classifier model. Univariate and multivariate logistic regression were used to analyze clinical variables independently influencing high-risk molecular subtypes of LrGGs to construct a clinical model; a combined model was developed by integrating radiomics labels and clinical variables. Receiver operating characteristic curve and area under the curve (AUC), calibration curve, and decision curve were used to compare the predictive performance of different models. Results:The patient′s age ( OR=1.042, 95% CI 1.018-1.068, P=0.001), pathological grade ( OR=2.270, 95% CI 1.212-4.311, P=0.011), MGMT methylation status ( OR=0.456, 95% CI 0.238-0.866, P=0.017), and ependymal involvement ( OR=7.335, 95% CI 2.929-18.370, P<0.001) were independent influencing factors for the high-risk molecular subtype of LrGGs, and a clinical model was developed based on these factors. An SVM model was constructed based on 12 radiomics features (3 radiomics features based on CE-T 1WI and 9 radiomics features based on T 2-FLAIR). The radiomics score of the probability output by the SVM model was combined with age, pathological grade, MGMT methylation status, and ependymal involvement to develop a combined model. The AUC values of the SVM model for predicting the high-risk molecular subtype of LrGGs were 0.824 and 0.859 in the training set and test set, respectively; the AUC values of the clinical model in the training set and test set were 0.759 and 0.721, respectively; and the AUC values of the combined model in the training set and test set were 0.823 and 0.815, respectively. The combined model had a high clinical net benefit. Conclusion:The machine learning MRI radiomics model can preoperatively predict high risk molecular subtypes of LGGrs, assist in individualized treatment decisions.

ObjectiveBased on tumor necrosis factor alpha （TNF-α）/tumor necrosis factor receptor 1 （TNFR1）/receptor-interacting protein kinases （RIPKs） signaling pathway， this paper aims to study the effect of modified Erchentang on inflammation in rats with chronic obstructive pulmonary disease （COPD） and explore its mechanism of action. MethodA total of 60 SD rats were randomly divided into normal group， model group， high， medium， and low-dose groups （20， 10， 5 g·kg^-1·d^-1） of modified Erchentang， and Xiaokechuan group （3.5 mL·kg^-1·d^-1）， with 10 rats in each group. The COPD rat model was established by cigarette smoke combined with lipopolysaccharide （LPS）. The normal group and model group were given the same amount of normal saline for 21 days by gavage administration. The contents of TNF-α and TNFR1 in bronchoalveolar lavage fluid （BALF） of rats were detected by enzyme-linked immunosorbent assay （ELISA）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect mRNA expressions of RIPK1， RIPK3， and mixed lineage kinase domain-like （MLKL） in the lung tissue. The protein expressions of RIPK1， RIPK3， and MLKL in the lung tissue were detected by Western blot. The pathological changes in lung tissue were observed by hematoxylin-eosin （HE） staining. ResultCompared with the normal group， the contents of TNF-α and TNFR1 in BALF of the model group were significantly increased （P<0.01）， and the mRNA and protein expression levels of RIPK1， RIPK3， and MLKL in the lung tissue were significantly increased （P<0.01）. Compared with the model group， the contents of TNF-α and TNFR1 in BALF of high， medium， and low-dose groups of modified Erchentang and Xiaokechuan group were decreased （P<0.01）. The mRNA and protein expression levels of RIPK1， RIPK3， and MLKL in the lung tissue were decreased to different degrees （P<0.05， P<0.01）. ConclusionModified Erchentang can effectively improve the inflammatory response of lung tissue in COPD rats， and the mechanism may be by inhibiting the activation of the TNF-α/TNFR1/RIPKs signaling pathway.

ObjectiveTo study the effect of modified Erchentang on the expression of key molecules in the high mobility group Box 1 protein （HMGB1）/receptor for advanced glycation endproduct （RAGE）/nuclear factor-κB （NF-κB） signaling pathway in bronchioles of rats with chronic obstructive pulmonary disease （COPD）， to explore the mechanism of modified Erchentang against bronchiolar inflammation of COPD rats via HMGB1/RAGE/NF-κB signaling pathway. MethodSixty SD rats were randomly divided into normal group， model group， modified Erchentang low-， medium- and high-dose groups （5， 10， 20 g·kg^-1·d^-1） and ethyl pyruvate （HMGB1 inhibitor） group， with 10 in each group. The COPD rat model was prepared by cigarette smoke combined with tracheal injection of lipopolysaccharide （LPS）. After modeling， the modified Erchentang groups were given corresponding drugs （ig） and Ringer's solution （4 mL， ip）， while the EP group was treated with equal volume of normal saline （ig） and EP （0.04 g·kg^-1·d^-1， ip）. The normal group and the model group received equal volume of normal saline （ig） and Ringer's solution （ip） for 21 consecutive days. The contents of HMGB1， chemokine （C-X-C motif） ligand 1 （CXCL1）， CXCL2 and monocyte chemotactic protein-1 （MCP-1） in bronchoalveolar lavage fluid （BALF） were detected by enzyme-linked immunosorbent assay （ELISA）. The mRNA expressions of HMGB1， RAGE and NF-κB p65 were determined by Real-time polymerase chain reaction （Real-time PCR）， and the protein expressions of HMGB1， RAGE， p-NF-κB p65， and alpha-smooth muscle actin （α-SMA） in bronchioles tissue of rats were determined by immunohistochemistry （IHC）. ResultCompared with the conditions in the normal group， the forced vital capacity （FVC）， forced expiratory volume in the first second （FEV1） and FEV1/FVC in the model group were decreased （P<0.01） while the contents of HMGB1， CXCL1， CXCL2 and MCP-1 in BALF were increased （P<0.01）. And the model group presented higher mRNA expressions of HMGB1， RAGE and NF-κB p65 （P<0.01） and protein expressions of HMGB1， RAGE， p-NF-κB p65 and α-SMA （P<0.05， P<0.01） than the normal group. Compared with the model group， the modified Erchentang medium- and high-dose groups had increased FEV1/FVC （P<0.05， P<0.01）， lowered contents of HMGB1， CXCL1， CXCL2 and MCP-1 in BALF （P<0.05， P<0.05）， and reduced mRNA expressions of HMGB1， RAGE and NF-κB p65 （P<0.05， P<0.01） and protein expressions of HMGB1， RAGE， p-NF-κB p65 and α-SMA （P<0.05， P<0.01）. ConclusionModified Erchentang can resist bronchiolar inflammation of COPD rats. The mechanism may be related to down-regulating the mRNA expressiona of HMGB1 and RAGE， inhibiting the activity of NF-κB， and reducing the release of HMGB1， CXCL1， CXCL2 and MCP-1， thus suppressing the inflammatory injury and abnormal repair of bronchioles.

ObjectiveTo observe the effect of modified Erchentang on the expression of key molecules in the Jagged1/Notch1/Hes1 signaling pathway in lung tissues of rats with chronic obstructive pulmonary disease （COPD） and explore its anti-inflammatory effect and molecular mechanism on COPD through the Jagged1/Notch1/Hes1 signaling pathway. MethodSixty SD rats were randomly divided into normal group， model group， low-， medium-， and high-dose modified Erchentang groups （5， 10， 20 g·kg^-1）， and γ-secretase inhibitor DAPT group （0.02 g·kg^-1）， with 10 rats in each group. The COPD model was induced in rats by cigarette smoking combined with intratracheal instillation of lipopolysaccharide （LPS）. Rats were treated with corresponding drugs by gavage， while those in the normal group and the model group were treated with the same amount of normal saline by gavage. The serum levels of Notch1， soluble intercellular adhesion molecule-1 （sICAM-1）， activated leukocyte cell adhesion molecule （ALCAM）， and soluble vascular adhesion molecule-1 （sVCAM-1） were detected by enzyme-linked immunosorbent assay （ELISA）. The mRNA expression of Jagged1， Notch1， and Hes1 was detected by Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. The protein expression of Jagged1， Notch1， Notch1 intracellular domain （NICD1）， and Hes1 in lung tissues of rats was detected by immunohistochemistry （IHC）. ResultCompared with the normal group， the model group showed increased serum content of Notch1， sICAM-1， ALCAM， and sVCAM-1 （P<0.01）， increased mRNA expression of Jagged1， Notch1， and Hes1 in lung tissues （P<0.01）， and increased protein expression of Jagged1， Notch1， NICD1， and Hes1 （P<0.01）. Compared with the model group， the medium- and high-dose modified Erchentang groups and the DAPT group showed decreased serum content of Notch1， sICAM-1， ALCAM， and sVCAM-1 （P<0.05， P<0.05）， down-regulated mRNA expression of Jagged1， Notch1， and Hes1 （P<0.05， P<0.01）， and reduced protein expression of Jagged1， Notch1， NICD1， and Hes1（P<0.05， P<0.01）. ConclusionModified Erchentang may inhibit the inflammatory response in the lung of COPD rats， and its mechanism may be related to the resistance of inflammatory injury in the lung by decreasing the mRNA expression of Jagged1， Notch1， and Hes1 and inhibiting the release of Notch1， sICAM-1， ALCAM， and sVCAM-1.

Objective:To evaluate the shoulder arthroscopic treatment of avulsion fracture of humeral greater tuberosity with double-row suture bridge.Methods:Retrospectively analyzed were the 13 avulsion fractures of humeral greater tuberosity which had been treated by shoulder arthroscopic double-row suture bridge at Bone and Joint Department, Guangzhou Liwan District Orthopedic Hospital from March, 2018 to March, 2020. There were 6 males and 7 females, with an average ages of 52.3 years (from 35 to 69 years). According to the Mutch classification, all the fractures of humeral greater tuberosity were attributed to the avulsion type. Of them, 3 were simple avulsion fractures of humeral greater tuberosity and 10 were complicated with shoulder anterior dislocation which was reduced manually before operation. There were 3 obsolete avulsion fractures of humeral greater tuberosity. Regular clinic and X-ray follow-ups were carried out. At the final follow-up, the pain, range of motion (ROM) and stability of the shoulder joint were assessed using visual analogue scale (VAS), American shoulder elbow scores (ASES), and Korean shoulder scores (KSS).Results:All the patients were followed up for an average of 12.3 months (from 10 to 16 months) postoperatively. No infection or shoulder instability was observed. At the final follow-up, the abduction and elevation averaged 164.6° (from 135° to 180°), the lateral external rotation 62.7° (from 40° to 80°), the internal rotation touch back test T10 level (from L2 to T6), the VAS 0.65 (from 0 to 2.5), the ASES 90.5 (from 78 to 100), and the KSS 91.5 (from 84 to 100).Conclusion:Shoulder arthroscopic treatment of avulsion fracture of humeral greater tuberosity with double-row suture bridge is minimally invasive and allows for repair of combined injury, leading to quick postoperative recovery.

ObjectiveTo investigate the molecular mechanism of the anti-inflammatory effect of Erchentang in the lung tissue of the rat model of chronic obstructive pulmonary disease （COPD） via the heparin-binding factor （Midkine）/transmembrane receptor protein （Notch2）/Hey1 signaling pathway. MethodSixty SD rats were randomized into normal group， model group， modified Erchentang （5， 10， 20 g·kg^-1·d^-1） groups， and Notch1 pathway inhibitor （γ-secretase inhibitor， DAPT， 0.02 g·kg^-1） group， with 10 rats in each group. The rat model of COPD was established by cigarette smoke combined with lipopolysaccharide （LPS）. After the modeling， the rats were administrated with corresponding drugs by gavage， and those in the normal and model groups were administrated with normal saline by gavage for 21 days. The levels of Midkine， cytokine-induced neutrophil chemoattractant-1 （CINC-1）， macrophage-derived chemokine （MDC）， chemokine ligand 5 （CXCL5）， neutrophil elastase （NE）， and nuclear factor-kappa B （NF-κB） p65 in bronchoalveolar lavage fluid （BALF） were determined by enzyme-linked immunosorbent assay （ELISA）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and immunohistochemistry were respectively employed to determine the mRNA and protein levels of Midkine， Notch2， and Hey1 in the lung tissue. ResultCompared with the normal group， the modeling increased the levels of Midkine， CINC-1， MDC， CXCL5， NE， and NF-κB p65 in BALF （P<0.01） and up-regulated the mRNA and protein levels of Midkine， Notch2， and Hey1 in the lung tissue （P<0.01）. Compared with the model group， medium- and high-dose modified Erchentang and DAPT lowered the levels of Midkine， CINC-1， MDC， CXCL5， and NF-κB p65 in BALF （P<0.01） and down-regulated the mRNA levels of Midkine， Notch2， and Hey1 （P<0.01）. ConclusionModified Erchentang may inhibit the inflammation in COPD rats by down-regulating the expression of Midkine， Notch2， and Hey1 and reducing the content of Midkine， CINC-1， MDC， and CXCL5.

Objective:To explore the diagnostic value of synthetic magnetic resonance imaging (syMRI) quantitative parameters for benign and malignant breast lesions.Methods:From September 2018 to March 2019, a total of 43 cases of breast lesions which were confirmed by surgery and pathology in Cancer Hospital, Chinese Academy of Medical Sciences were enrolled in this study. All patients underwent syMRI sequence scans before and after enhancement except for conventional T2WI, DWI, and enhancement scans. GE AW4.7 workstation was used to generate syMRI parameter maps (T1, T2, proton density mappings), and ITK-SNAP software was used to delineate the volume of interest. The T1, T2, PD values before and after dynamic contrast enhanced (DCE) were obtained, and the change values of each parameter were calculated. Meanwhile, the apparent diffusion coefficient (ADC) and time intensity curve (TIC) of the lesions were measured. The differences of each parameter value were compared between benign and malignant breast lesions, and the receiver operating characteristic (ROC) curve was used to analyze the diagnostic performance of each parameter.Results:Among the 43 enrolled cases, 13 were benign and 30 were malignant. Among the syMRI parameters, the pre-enhancement parameters including T1pre (median 1 663.07 ms), T2pre (median 103.33 ms), post-enhancement parameters ΔT1 (median 1 022.68 ms) and ΔT2 (median 27.67 ms) of benign group, significantly higher than those of the malignant group (the medians were 1 141.74, 92.53, 664.95, and 16.19 ms, respectively, P<0.05). The ADC value of the benign group (median 1.66×10 -3mm 2/s) was significantly higher than that of the malignant group (median 1.00×10 -3mm 2/s, P<0.05). The benign group included 6 cases of TIC curve type Ⅰ, 5 cases of type Ⅱ, and 2 cases of type Ⅲ. The malignant group included 2 cases of TIC curve type Ⅰ, 17 cases of type Ⅱ, and 11 cases of type Ⅲ. The difference between the two groups was statistically significant ( P<0.05). The area under the ROC curve (AUC) of T1pre before DCE was 0.869, higher than 0.806 of ADC and 0.697 of TIC. When the best cut-off value of 1 282.94 ms was chosen, the sensitivity and specificity of diagnosis were 76.9% and 93.3%, respectively. The combination of T1pre and T2pre can further improve the diagnostic performance (AUC=0.908). Conclusions:Among the syMRI quantitative parameters, T1pre, T2pre, ΔT1 and ΔT2 have good value for the differential diagnosis of benign and malignant breast lesions. T1pre has the best diagnostic performance, and the combination of T1pre and T2pre can further improve the diagnostic performance.

Objective:To explore the diagnostic value of synthetic magnetic resonance imaging (syMRI) quantitative parameters for benign and malignant breast lesions.Methods:From September 2018 to March 2019, a total of 43 cases of breast lesions which were confirmed by surgery and pathology in Cancer Hospital, Chinese Academy of Medical Sciences were enrolled in this study. All patients underwent syMRI sequence scans before and after enhancement except for conventional T2WI, DWI, and enhancement scans. GE AW4.7 workstation was used to generate syMRI parameter maps (T1, T2, proton density mappings), and ITK-SNAP software was used to delineate the volume of interest. The T1, T2, PD values before and after dynamic contrast enhanced (DCE) were obtained, and the change values of each parameter were calculated. Meanwhile, the apparent diffusion coefficient (ADC) and time intensity curve (TIC) of the lesions were measured. The differences of each parameter value were compared between benign and malignant breast lesions, and the receiver operating characteristic (ROC) curve was used to analyze the diagnostic performance of each parameter.Results:Among the 43 enrolled cases, 13 were benign and 30 were malignant. Among the syMRI parameters, the pre-enhancement parameters including T1pre (median 1 663.07 ms), T2pre (median 103.33 ms), post-enhancement parameters ΔT1 (median 1 022.68 ms) and ΔT2 (median 27.67 ms) of benign group, significantly higher than those of the malignant group (the medians were 1 141.74, 92.53, 664.95, and 16.19 ms, respectively, P<0.05). The ADC value of the benign group (median 1.66×10 -3mm 2/s) was significantly higher than that of the malignant group (median 1.00×10 -3mm 2/s, P<0.05). The benign group included 6 cases of TIC curve type Ⅰ, 5 cases of type Ⅱ, and 2 cases of type Ⅲ. The malignant group included 2 cases of TIC curve type Ⅰ, 17 cases of type Ⅱ, and 11 cases of type Ⅲ. The difference between the two groups was statistically significant ( P<0.05). The area under the ROC curve (AUC) of T1pre before DCE was 0.869, higher than 0.806 of ADC and 0.697 of TIC. When the best cut-off value of 1 282.94 ms was chosen, the sensitivity and specificity of diagnosis were 76.9% and 93.3%, respectively. The combination of T1pre and T2pre can further improve the diagnostic performance (AUC=0.908). Conclusions:Among the syMRI quantitative parameters, T1pre, T2pre, ΔT1 and ΔT2 have good value for the differential diagnosis of benign and malignant breast lesions. T1pre has the best diagnostic performance, and the combination of T1pre and T2pre can further improve the diagnostic performance.

Objective ToinvestigatethefeasibilityofassessingliverfunctiongradingbyIDEAL-IQsequenceon1.5T MR.Methods The patientswhowereclinicallydiagnosedaslivecirrhosisandunderwent1.5T MRIDEAL-IQsequenceinourhospitalfrom February 2016toDecember2017wereanalyzedretrospectively.TheyweredividedintoA,BandCgradesaccordingtotheChild-Pughgrading standardofliverfunction.Finally,therewere30patientsinChild-PughA,25patientsinChild-PughBand16patientsinChild-Pugh C.ThefatratiomapsandR2?relaxationratemapswereusedtomeasuretheliverfatcontentandironcontentbythetwoobservers onAW4.6workstation,respectively.ThemeanvaluesofthefatfractionsandtheR2?valuesweremeasuredandcomparedbyusing K ruskal-W allis H testamongthethreegroups.Then,thegroupAandBwerecombinedtoestablishthepredictivemodelindiagnosingthegroup Cbyusingthe L o g istic regressionanalysis,whichcombinedthefatfractionandR2?value.TheROCcurvewasdrawntoobtainedtheAUC,and calculatedthesensitivityandthespecificitywiththeoptimalthreshold.Results Thereweregoodconsistencyofmeasurementdata betweenthetwoobserves(ICC>0.8).ThefatfractionandR2?valueincreasedwiththedecreaseoftheliverfunction.Thefatfractionsofthe Child-PughA,BandCgroupwere(3.58±0.91)%,(3.64±1.20)%,(6.87±3.91)%,respectively.TheR2?valuesoftheChild-Pugh A,BandCgroupswere(33.31±11.80)Hz,(38.00±13.31)Hz,(58.98±44.54)Hz,respectively.TheAUCofwhichcombinedfat fractionandR2?valuediagnosingChild-PughCwas0.843.Thesensitivityandthespecificitywere81.8% and81.3%,respectively. Conclusion The1.5T MRIDEAL-IQsequencecanbeusedtoevaluatetheliverreserveunctionoflivercirrhosispatientsaccording ffatfractionandR2?value,especiallyfortheChild-PughCcirrhosis patientswithhighsensitivityandspecificity.