Objective To investigate the application value of clinical-radiomics nomogram in predicting the expression of liver kinase B1(LKB1)in non-small cell lung cancer(NSCLC)before surgery.Methods A total of 140 NSCLC patients were randomized into training group(n=106)and validation group(n=34)according to the ratio of 7∶3.The training group was used as the study cohort to screen the clinically independent predictors and radiomics characteristics related to LKB1 expression,and the clinical model,radiomics model and clinical-radiomics nomogram model were constructed,respectively.The predictive performance of the three models was analyzed using the receiver operating characteristic(ROC)curve in the training group,and validated in the validation group.The calibration curve was used to assess the consistency between the predicted results of nomogram model and the actual observations,and the decision curve was used to evaluate the clinical benefit of the nomogram model.Results The clinical model consisted of pathological type and hilal/mediastinal lymphadenopathy,the radiomics model consisted of Radiomics score(Radscore),and the nomogram model consisted of Radscore,pathological type and hilal/mediastinal lymphadenopathy.In the training group,the area under the curve(AUC)of the nomogram model,radiomics model and clinical model was 0.884,0.843 and 0.788,respectively.In the validation group,the AUC of the three models were 0.976,0.851,and 0.912,respectively.The calibration curve analysis showed good consis-tency between the predicted results of nomogram model and the actual observations,and the decision curve showed that the model had good clinical benefit.Conclusion Radiomics combined with clinical risk factors can effectively predict the expression of LKB1 in NSCLC patients before surgery,so as to contribute to the formulation of therapeutic strategies in clinical practice.

Objective To investigate the application value of clinical-radiomics nomogram in predicting the expression of liver kinase B1(LKB1)in non-small cell lung cancer(NSCLC)before surgery.Methods A total of 140 NSCLC patients were randomized into training group(n=106)and validation group(n=34)according to the ratio of 7∶3.The training group was used as the study cohort to screen the clinically independent predictors and radiomics characteristics related to LKB1 expression,and the clinical model,radiomics model and clinical-radiomics nomogram model were constructed,respectively.The predictive performance of the three models was analyzed using the receiver operating characteristic(ROC)curve in the training group,and validated in the validation group.The calibration curve was used to assess the consistency between the predicted results of nomogram model and the actual observations,and the decision curve was used to evaluate the clinical benefit of the nomogram model.Results The clinical model consisted of pathological type and hilal/mediastinal lymphadenopathy,the radiomics model consisted of Radiomics score(Radscore),and the nomogram model consisted of Radscore,pathological type and hilal/mediastinal lymphadenopathy.In the training group,the area under the curve(AUC)of the nomogram model,radiomics model and clinical model was 0.884,0.843 and 0.788,respectively.In the validation group,the AUC of the three models were 0.976,0.851,and 0.912,respectively.The calibration curve analysis showed good consis-tency between the predicted results of nomogram model and the actual observations,and the decision curve showed that the model had good clinical benefit.Conclusion Radiomics combined with clinical risk factors can effectively predict the expression of LKB1 in NSCLC patients before surgery,so as to contribute to the formulation of therapeutic strategies in clinical practice.

Goiter is a kind of non-inflammatory and non-neoplastic hyperplasia and enlargement. Many studies have shown that substances such as thiocyanates and isothiocyanates can prevent the development of a variety of tumors. However, some studies have also found that such substances can lead to goiter. In this article, relevant information on common goitrogen in food are collected to explore their mechanism of action, laying a foundation for guiding residents to maintain a healthy and balanced diet.

Objective To investigate the preoperative predictive value of clinical-radiomics nomogram on N1-N2 lymph node metastasis in patients with stage Ⅰ to Ⅲ A primary lung adenocarcinoma(PL A).Methods A total of 164 PLA patients were divided into a training set(n=114)and an validation set(n=50).Three logistic regression models were created separately and the predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and area under the curve(AUC)respectively.The AUC difference between models was tested by the DeLong test.The calibration degree was evaluated by the calibration curve.Decision curve analysis was performed to evaluate the benefits of clinical application.Results The radiomics model consisted of 8 imaging features[Radiomics score(Radscore)].The clinical model was composed of tumor type(central or peripheral)and tumor size.The tumor type,tumor size and Radscore formed the nomogram model.In the training set,the prediction of the nomogram model was more effective(AUC=0.909)than the clinical model(AUC=0.748)and the radiomics model(AUC=0.814),while the differences in AUC were statistically significant(P＜0.05).In the validation set,the prediction of the nomogram model was more effective(AUC=0.875)than the clinical model(AUC=0.682),and the difference in AUC was statistically significant(P＜0.05).The prediction of the nomogram model was also more effective than the radiomics model(AUC=0.799),but the difference in AUC was not statistically significant(P＞0.05).The calibration curve showed that the clinical-radiomics nomogram had a high level of calibration and the decision curve analysis showed good benefits from clinical application.Conclusion The clinical-radiomics nomogram is proven to be more effective than radiomics or clinical factors alone in the preoperative prediction of stage Ⅰ to Ⅲ A PLA N1-N2 lymph node metastasis.

Objective:To study the diagnostic value of artificial intelligence B-ultrasound image computer-aided diagnosis system (hereinafter referred to as intelligent ultrasound system) in adult goiter.Methods:In June 2022 and March 2023, two phases of thyroid disease survey were carried out in 4 cities in Anhui Province. One village was selected in each city, and 250 adults were selected as survey subjects in each village. Adult bilateral thyroid area was scanned by both intelligent ultrasound system and conventional ultrasound scanning equipment, and the effectiveness of intelligent ultrasound system in the diagnosis of goiter was analyzed based on the results of conventional ultrasound examination. Receiver operating characteristic (ROC) curve was drawn, and Kappa test was used to analyze the consistency between intelligent ultrasound system and conventional ultrasound examination in the diagnosis of goiter. At the same time, Spearman correlation analysis and Bland-Altman method were used to evaluate the consistency of the two methods in measuring thyroid volume.Results:After screening and removing outliers and missing values, a total of 910 adults were included, including 253 males (27.80%) and 657 females (72.20%). The age was (45.92 ± 10.20) years old, ranging from 18 to 60 years old. The sensitivity, specificity, and accuracy of the intelligent ultrasound system for diagnosing adult goiter were 80.00%, 99.67%, and 99.56%, respectively. The area under the ROC curve (AUC) was 0.996, which was consistent with the results of conventional ultrasound examination for diagnosing goiter ( κ = 0.67, P < 0.001). After controlling for variables such as gender, thyroid function, and thyroid nodules, the intelligent ultrasound system showed good consistency with conventional ultrasound examination in the diagnosis of goiter in females, adults with thyroid dysfunction, and adults without thyroid nodules ( κ = 0.66, 0.80, 0.80, P < 0.001). The consistency in the diagnosis of goiter in adults with thyroid nodules was moderate ( κ = 0.56, P < 0.001). Spearman correlation analysis showed a highly positive correlation between the measurement results of adult thyroid volume by intelligent ultrasound system and conventional ultrasound examination ( r = 0.88, P < 0.001). The Bland-Altman method results showed that only 4.62% (42/910) of points in adults were outside the 95% consistency limit, indicating good consistency between intelligent ultrasound system and conventional ultrasound examination in measuring thyroid volume (< 5%). The proportion of points outside the 95% consistency limit in males, adults with thyroid dysfunction, and adults with thyroid nodules was 6.72% (17/253), 5.83% (12/206), and 6.45% (12/186), respectively. Conclusions:The intelligent ultrasound system has certain diagnostic value for adult goiter and has good consistency with conventional ultrasound examination for thyroid volume measurement. However, the accuracy of diagnosis for males and adults with thyroid nodules still needs to be improved.

Objective : To investigate the effect of high concentration of Caerulomycin A (Cae A) on HK2 in renal tubular epithelial cells and to explore the role of cytoplasmic nucleotide⁃binding oligomerization domain⁃like receptor protein 3 (NLRP3) in this process. Methods : The effect of different concentrations of Cae A on the viability of HK2 cells was determined by MTT; the expression of kidney injury molecule (KIM⁃1) and NLRP3 was detected by real⁃time quantitative PCR , Western blot and immunofluorescence , while the effect of Cae A on the mRNA expression of IL⁃1β , IL⁃18 , IL⁃33 , MCP⁃1 , TNF⁃α was also measured by real⁃time quantitative PCR. HK2 cells were divided into control group , high concentration of Cae A group and high concentration of Cae A plus NLRP3 inhibitor CY⁃09 group , and the expression of KIM⁃1 and NLRP3 protein was detected by Western blot. Results : The results of MTT showed that high concentration of Cae A could inhibit HK2 cell viability. Real⁃time quantitative PCR , Western blot and immunofluorescence assays showed that high concentration of Cae A upregulated the expression of KIM⁃1 and NLRP3 , as well as the mRNA levels of IL⁃1β , IL⁃18 , IL⁃33 , MCP⁃1 , TNF⁃α , while CY⁃09 could down⁃regulate the expression of NLRP3 and KIM⁃1. Conclusion High concentration of Cae A significantly inhibited the viability of HK2 cells and induced damage and inflammatory response to HK2 with some nephrotoxicity that might be achieved via NLRP3 pathway.

ObjectiveTo reveal the targets and molecular mechanisms of the action of Qiangxin Decoction （强心汤） for the treatment of chronic heart failure based on the combination of network pharmacology and molecular docking. MethodsThe active ingredients of Qiangxin Decoction were retrieved from TCMSP database， and the targets of chronic heart failure were screened by searching GeneCards， OMIM， TTD， PharmGkb， and DrugBank databases， and the intersections were taken to obtain the intersecting targets of Qiangxin Decoction for the treatment of chronic heart failure. STRING platform was used to construct the protein-protein interaction network （PPI）， Cytoscape 3.8.0 software was used to calculate the network topology to screen the core targets， and R 4.2.3 was used to construct the “active ingredient-target” network by analyzing the GO enrichment analysis and KEGG pathway enrichment analysis. AutoDock 1.5.7 was used for molecular docking to predict the binding performance of active ingredients and core targets. ResultsSeventy-five intersecting targets were identified for the treatment of chronic heart failure with Qiangxin Decoction， among which the core targets were estrogen receptor 1 （ESR1， degree value=7）， nuclear receptor coactivator 1 （NCOA1， degree value=8）， glucocorticoid receptor （NR3C1， degree value=7）， and nuclear receptor coactivator 2 （NCOA2， degree value=7）. GO enrichment analysis showed that the top 3 items with the smallest P value in molecular function were G protein-coupled amine receptor activity， postsynaptic neurotransmitter receptor activity， and neurotransmitter receptor activity （P＜0.01）； the top 3 items with the smallest P value in biological process were adenylyl cyclase-activated adrenergic receptor signaling pathway， adrenergic receptor signaling pathway， and adenylyl cyclase-regulated G protein-coupled receptor signaling pathway （P＜0.01）； the top 3 items with the smallest P values in cellular composition were components of the postsynaptic membrane， synaptic membrane， and presynaptic membrane （P＜0.01）. KEGG enrichment analysis showed that the top 5 key signaling pathways were neuroactive ligand-receptor interactions， calcium signaling pathway， dopaminergic synapses， cocaine addiction， and cyclic guanosine monophosphate-protein kinase G （cGMP-PKG） signaling pathway. The molecular docking results showed that lignans and isoflavones had lower binding energies and more structural stability with the four core targets （ESR1， NCOA1， NR3C1， NCOA2）. ConclusionThe treatment of chronic heart failure by Qiangxin Decoction was associated with neuroactive ligand-receptor interactions， calcium signaling pathway， dopaminergic synapses， chemoattractant-receptor activation， cGMP-PKG signaling pathway， lipids and atherosclerosis， and cAMP signaling pathway， and lignans and isoflavones may be the core active compounds in its treatment of chronic heart failure.

Objective:To explore the value of radiomics model based on intratumoral and peritumoral early dynamic contrast-enhanced (DCE) MRI for identifying benign and malignant in breast imaging reporting and data system (BI-RADS) 4 tumors.Methods:A total of 191 patients diagnosed with BI-RADS 4 breast tumors by breast MRI examination with clear pathological diagnosis from January 2016 to December 2020 in the First Affiliated Hospital of Bengbu Medical College were analyzed retrospectively, including 77 benign and 114 malignant cases, aged 23-68 (46±10) years. The one-slice image with the largest area of the lesion of the second stage DCE-MRI images was selected to outline the region of interest, and automatically conformal extrapolated by 5 mm to extract the intra-tumoral and peritumoral radiomics features. The included cases were randomly divided into training and testing cohorts in the ratio of 8∶2. The statistical and machine learning methods were used for feature dimensionality reduction and selection of optimal radiomics features, and logistic regression was used as the classifier to establish the intratumoral, peritumoral, and intratumoral combined with peritumoral radiomics models. The independent risk factors that could predict the benignity and malignancy of breast tumors were retained as clinical-radiological characteristics by univariate and multivariate logistic regression to establish a clinical-radiological model. Finally, the intratumoral and peritumoral radiomics features were combined with clinical-radiological features to develop a combined model of the three. The receiver operating curve was used to analyze the predictive performance of each model and calculate the area under the curve (AUC),the AUC was compared by DeLong test. The stability of the three-component combined diagnostic model was tested by 10-fold cross-validation, and the model was visualized by plotting nomogram and calibration curves.Results:In the training cohort, the AUC of the three-component combined model for identifying benign and malignant BI-RADS 4 breast tumors was significantly higher than that of the intratumoral radiomics model ( Z=3.38, P<0.001), the peritumoral radiomics model ( Z=4.01, P<0.001), the intratumoral combined with peritumoral radiomics model ( Z=3.11, P=0.002), and the clinical-radiological model ( Z=3.24, P=0.001). And the AUC, sensitivity, specificity, accuracy, and F1-score of the three-component combined model were 0.932, 91.2%, 86.9%, 87.0% and 0.89, respectively. In the testing cohort, the three-component combined model also had the highest AUC value (0.875), and diagnostic sensitivity, specificity, accuracy and malignancy F1-score were 95.7%, 62.5%, 76.9%, and 0.89, respectively. The AUC calculated by 10-fold cross-validation was 0.90 (0.85-0.92), and the predicted curve of the three-component combined model in the calibration curve was in good agreement with the ideal curve. Conclusion:The three-component combined diagnostic model based on the intratumoral and peritumoral radiomics features and clinical-radiological features of early DCE-MRI has good performance and stability for identifying the benign and malignant in BI-RADS 4 breast tumors, and it can provide guidance for clinical decision non-invasively.

Objective:To explore the application value of digital three-dimensional(3D) reconstruction technology in the repair of oral and maxillofacial defects with superficial inferior epigastric artery (SIEA) flap.Methods:Twelve cases of oral cancer patients, including 8 males and 4 females; aged (57.4±12.6) years, were selected from the Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Bengbu Medical College from January 2018 to October 2019 and were proposed to repair with SIEA flap. There were 10 cases of squamous cell carcinoma, one case of adenoid cystic carcinoma and 1 case of mucinous epidermal carcinoma. The data were imported into AW4.7 software for post-processing. The left or right dominant donor area was selected to clarify the origin, diameter, alignment, and location of penetration point of the flap blood supply, and digital 3D reconstruction technology was used to guide the flap preoperative design.Results:Eleven cases were repaired by SIEA flap in 12 patients, one case was repaired by superficial iliac artery flap because the source artery was undiscovered, one case had venous vascular crisis after surgery, and the rest of the flap survived. In 11 patients repaired with SIEA flap, there was no significant difference between the preoperative SIEA diameter measured by CTA [(1.0±0.3) mm] and the actual measured value [(1.1±0.3) mm] ( P>0.05). The follow-up was 6 to 12 months, with an average of 10 months, and the donor-receiver areas were all healed in phase Ⅰ. No obvious complications occurred, and the abdominal scar was hidden. Conclusions:In the SIEA flap repair oral and maxillofacial defect reconstruction surgery, the use of digital 3D reconstruction technology can objectively reflect the diameter and the location of the superficial artery of the abdominal wall before surgery, effectively reduce the difficulty and risk of flap surgery.

Objective: To explore the imaging changes of lung lesions in patients with imported COVID-19 patients when reaching the discharge standard. Method: The clinical and CT imaging data of 60 patients with imported COVID-19 cured and discharged from January to February 2020 in Anhui Province were retrospectively collected. The clinical characteristics of the patients and the characteristics of chest CT images at discharge were analyzed. Results: Fever (57 cases) and cough (55 cases) were the main symptoms in 60 patients. At the initial diagnosis, 5 cases were mild, 53 were ordinary, and 2 were severe. In 5 light patients, 3 cases were negative in the whole course of CT examination, 2 cases were negative in the first time and abnormal in the second time. . The first CT imaging features of 55 patients (53 common type and 2 severe type)were mainly bilateral lung involvement (51 cases), multiple lesions (33 cases), more common under the pleura (40 cases), and ground glass opacities were the most common. (55 cases). The clinical features of chest CT in clinical outcomes are that the ground glass shadow in the lung gradually fades and was completely absorbed (19 cases); the scope of ground glass shadow in the lung expanded and progressed to crazy-paving, consolidation shadow, and the lesion gradually absorbs again followed by Fibrous cord shadows (27 cases); ground-glass opacities in the lungs quickly progressed to a consolidation and then slowly absorbed . Most of the lesions were accompanied by more residual fibrous cord shadows (4 cases). In 2 severe patients, the lesions in the lungs were larger ground glass, and a big amount of fibrous foci remained after slowly absorption. Conclusion Chest CT plays an important role in the diagnosis and treatment of imported COVID-19, and the degree of lung involvement seen on CT images is in good agreement with clinical outcome.