Objective:A nomogram model for predicting double positivity of microvascular invasion (MVI) and vascular endothelial-to-mesenchymal transition (VETC) in patients with hepatocellular carcinoma (HCC) was constructed and its predictive performance was evaluated.Methods:A retrospective analysis was conducted on 326 HCC patients who were treated at the Third People's Hospital of Nantong and the First Affiliated Hospital of Soochow University from January 2013 to June 2023, including 240 males and 86 females, with an average age of (58.7±9.0) years. The 326 patients were randomly divided into a training set ( n=228) and a test set ( n=98) at a ratio of 7: 3 using the random number table method. The training set was divided into a double-positive group ( n=54) and a control group ( n=174) based on whether the HCC patients were double positive for MVI and VETC. Univariate and multivariate logistic regression analyses were performed to identify the influencing factors of double positivity of microvascular invasion in HCC patients, and a nomogram for predicting double positivity of microvascular invasion patterns was constructed based on the multivariate. The predictive performance and clinical net benefit of the nomogram were evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Results:There were statistically significant differences in alpha-fetoprotein, gamma-glutamyl transferase, and phosphatidylinositol proteoglycan between the two groups (all P<0.05). Multivariate logistic regression analysis showed that LI-RADS category ( OR=8.58, 95% CI: 1.87-39.38), intratumoral hemorrhage ( OR=2.16, 95% CI: 1.14-4.07), and intratumoral arteries ( OR=2.59, 95% CI: 1.19-5.64) were all influencing factors of double positivity of microvascular invasion patterns in HCC patients (all P<0.05). Based on the multivariate results, a nomogram was constructed. In the training set, the area under the ROC curve for predicting double positivity of microvascular invasion patterns in HCC patients was 0.769 (95% CI: 0.720-0.814). In the test set, the area under the ROC curve for predicting double positivity of microvascular invasion patterns in HCC patients was 0.756 (95% CI: 0.622-0.850). The calibration curve showed a good fit between the predicted model and the ideal curve. Decision curve analysis showed that the clinical applicability was good when the threshold was 0.01-0.80 in the training set and 0.01-0.65 in the test set. Conclusion:The nomogram model based on LI-RADS category, intratumoral hemorrhage, and intratumoral arteries can effectively predict double positivity of microvascular invasion patterns in HCC patients and has good clinical applicability.

Actinomycetes are important producers of high-value natural products, and the engineering of actinomycetes to enhance the biosynthesis of target natural products has long been a hot research topic in the scientific community. However, non-rational engineering methods suffer from low beneficial mutation rates, which limit the efficiency of mutant screening. The integration of high-throughput screening (HTS) technologies can effectively enhance the screening efficiency of elite mutants and significantly shorten the cycle of actinomycete strain engineering. This review comprehensively discusses various HTS technologies suitable for the engineering of actinomycete strains and compares them in terms of application scenarios, advantages, and disadvantages. HTS technologies include microplate-based screening, antimicrobial activity screening, antibiotic resistance screening, fluorescence-activated cell sorting (FACS), and fluorescence-activated droplet sorting (FADS). Additionally, this review summarizes the applications of these technologies in assisting actinomycete strain engineering and enhancing the yields of target compounds. The development and application of HTS technologies have not only facilitated the exploration of natural product resources in actinomycetes but also provided strong support for the rapid and efficient construction of high-performance engineered actinomycete strains.
Actinobacteria/metabolism* ; High-Throughput Screening Assays/methods* ; Genetic Engineering/methods* ; Biological Products/metabolism* ; Flow Cytometry ; Metabolic Engineering/methods*

Objective To quantify the mean fat fraction(FF)values of hip abductor muscles using the MR least squares estimation method of iterative water-fat separation(IDEAL-IQ)technique and to analyze the correlation between muscle fat infiltration and cartilage damage in hip osteoarthritis(HOA),age and gender.Methods Ninety-five patients with clinical symptoms of hip joint(HOA group)and volunteers(control group)underwent MRI conventional sequence and IDEAL-IQ sequence scans of the hip joint were selected.Hip cartilage damage was graded based on conventional MRI sequences(mild HOA group and severe HOA group),and the FF values of hip abductor muscles were measured for each group.ANOVA analysis and Pearson correlation tests were used to compare the differences between the groups and correlation analyses were performed.Results The FF values of hip abductor muscles in the mild HOA group and severe HOA group were significantly higher than those in the control group,with statistically significant differences(P＜0.05).There were correlations between the FF values of hip abductor muscles and the degree of HOA cartilage damage,age and gender(r=0.677,0.566,0.311).Conclusion The IDEAL-IQ technique can be used for quantitative research on muscle fat infiltration,and fat infiltration in hip abductor muscles is an important risk factor for HOA cartilage damage.

Objective:A nomogram model for predicting double positivity of microvascular invasion (MVI) and vascular endothelial-to-mesenchymal transition (VETC) in patients with hepatocellular carcinoma (HCC) was constructed and its predictive performance was evaluated.Methods:A retrospective analysis was conducted on 326 HCC patients who were treated at the Third People's Hospital of Nantong and the First Affiliated Hospital of Soochow University from January 2013 to June 2023, including 240 males and 86 females, with an average age of (58.7±9.0) years. The 326 patients were randomly divided into a training set ( n=228) and a test set ( n=98) at a ratio of 7: 3 using the random number table method. The training set was divided into a double-positive group ( n=54) and a control group ( n=174) based on whether the HCC patients were double positive for MVI and VETC. Univariate and multivariate logistic regression analyses were performed to identify the influencing factors of double positivity of microvascular invasion in HCC patients, and a nomogram for predicting double positivity of microvascular invasion patterns was constructed based on the multivariate. The predictive performance and clinical net benefit of the nomogram were evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Results:There were statistically significant differences in alpha-fetoprotein, gamma-glutamyl transferase, and phosphatidylinositol proteoglycan between the two groups (all P<0.05). Multivariate logistic regression analysis showed that LI-RADS category ( OR=8.58, 95% CI: 1.87-39.38), intratumoral hemorrhage ( OR=2.16, 95% CI: 1.14-4.07), and intratumoral arteries ( OR=2.59, 95% CI: 1.19-5.64) were all influencing factors of double positivity of microvascular invasion patterns in HCC patients (all P<0.05). Based on the multivariate results, a nomogram was constructed. In the training set, the area under the ROC curve for predicting double positivity of microvascular invasion patterns in HCC patients was 0.769 (95% CI: 0.720-0.814). In the test set, the area under the ROC curve for predicting double positivity of microvascular invasion patterns in HCC patients was 0.756 (95% CI: 0.622-0.850). The calibration curve showed a good fit between the predicted model and the ideal curve. Decision curve analysis showed that the clinical applicability was good when the threshold was 0.01-0.80 in the training set and 0.01-0.65 in the test set. Conclusion:The nomogram model based on LI-RADS category, intratumoral hemorrhage, and intratumoral arteries can effectively predict double positivity of microvascular invasion patterns in HCC patients and has good clinical applicability.

Objective To quantify the mean fat fraction(FF)values of hip abductor muscles using the MR least squares estimation method of iterative water-fat separation(IDEAL-IQ)technique and to analyze the correlation between muscle fat infiltration and cartilage damage in hip osteoarthritis(HOA),age and gender.Methods Ninety-five patients with clinical symptoms of hip joint(HOA group)and volunteers(control group)underwent MRI conventional sequence and IDEAL-IQ sequence scans of the hip joint were selected.Hip cartilage damage was graded based on conventional MRI sequences(mild HOA group and severe HOA group),and the FF values of hip abductor muscles were measured for each group.ANOVA analysis and Pearson correlation tests were used to compare the differences between the groups and correlation analyses were performed.Results The FF values of hip abductor muscles in the mild HOA group and severe HOA group were significantly higher than those in the control group,with statistically significant differences(P＜0.05).There were correlations between the FF values of hip abductor muscles and the degree of HOA cartilage damage,age and gender(r=0.677,0.566,0.311).Conclusion The IDEAL-IQ technique can be used for quantitative research on muscle fat infiltration,and fat infiltration in hip abductor muscles is an important risk factor for HOA cartilage damage.

The biggest challenge of breast cancer treatment is metastasis and drug resistance.Breast cancer metastasis increa-ses mortality and decreases the life quality of patients.At present,the mechanism of breast cancer metastasis is not completely under-stood,and the multi-step process of metastasis,namely metastasis cascade,is determined by the internal characteristics of tumor cells and tumor microenvironment.Among the factors driving breast cancer metastasis,the role of inflammatory reaction has gradually attrac-ted attention.The inflammatory environment composed of immune cells,cytokines,chemokines,and growth factors has an important im-pact on the invasion and metastasis of cancer cells.By studying the interaction between inflammatory reaction,tumor cells and tumor microenvironment,it is expected to discover drug targets for the prevention and treatment of breast cancer metastasis.This article re-views the role of inflammation in the tumor microenvironment of breast cancer metastasis.

Objective:To develop a nomogram to predict vessels that encapsulate tumor cluster and/or microvascular invasion-positive hepatocellular carcinoma (VM-HCC) based on multiregional radiomics score derived from multisequence MRI.Methods:Clinical data of 209 patients with HCC undergoing radical liver resection at Affiliated Nantong Hospital 3 of Nantong University from January 2016 to December 2021 were retrospectively analyzed, including 149 males and 60 females, aged (58.5±9.2) years. Patients were divided into a training set ( n=146) and a testing set ( n=63). The patients in training set were further classified into two groups based on pathological results: the VM-HCC group ( n=76) and the non-VM-HCC group ( n=70). Radiomics features were extracted from the arterial phase and hepatobiliary phase images within the tumor, peritumor, and combined regions of interest. The arterial phase and hepatobiliary phase features from the same regions were integrated to obtain dual-sequence features. After feature selection, linear support vector machines (SVM) and linear regression machine learning classifiers were employed to construct radiomics models for different sequences and regions. The optimal radiomics model was selected based on the area under the receiver operating characteristic (ROC) curve from the testing set. Logistic regression analysis was performed to identify independent predictors of VM-HCC, and a visual nomogram was constructed using the results of the multivariate logistic regression analysis and the radiomics score of the optimal radiomics model. ROC curves were plotted, and area under curve (AUC) were calculated to evaluate the models’ discriminatory ability. Calibration curves and decision curve analysis (DCA) were utilized to assess the model’s calibration and clinical utility. Results:Among the radiomics models, the dual-sequence-combined region model based on the SVM classifier exhibited the best AUC in the testing set (AUC=0.764, 95% CI: 0.646-0.882). Multivariate logistic regression analysis indicated that HCC patients with protein induced by vitamin K absence or antagonist-II (PIVKA-II) levels >40 mAU/ml ( OR=4.266, 95% CI: 1.921-9.473, P<0.001) had a higher risk of VM-HCC. The nomogram combining PIVKA-II>40 mAU/ml and radiomics score achieved AUC of 0.806 (95% CI: 0.733-0.867) in the training set and 0.817 (95% CI: 0.699-0.903) in the testing set for predicting VM-HCC. The calibration curves of the nomogram showed good fit in both the training and testing sets. DCA indicated that the model possesses good clinical utility. Conclusion:The nomogram based on multiregional radiomics score derived from multisequence MRI demonstrates a good predictive performance for VM-HCC, which could facilitate the risk stratification of recurrence in HCC patients.

Objective To observe the value of the scoring model of MRI features for predicting proliferative hepatocellular carcinoma(HCC).Methods Data of 241 patients with pathologically confirmed HCC,including 90 cases of proliferative HCC and 151 cases of non-proliferative HCC were analyzed retrospectively.Univariate and multivariate logistic regression were used to compare the clinical and MRI findings evaluated according to liver imaging reporting and data system version 2018 between groups.The independent predictive factors of proliferative HCC were screened,and scores were assigned according to the weight,then a scoring model was constructed.Receiver operating characteristic(ROC)curve was drawn,and the area under the curves(AUC)were calculated to assess the predictive efficacy of this model.The patients were divided into high and low proliferation risk subgroups based on the optimal score thresholds.The recurrence free survival(RFS)rates and early RFS rates were compared between groups and subgroups.Results MRI showed tumor corona enhancement,arterial phase annular hyper-enhancement,intratumoral vessels,much focus parenchymal low enhancement and irregular tumor margins were all independent predictive factors for proliferative HCC(OR=3.287,2.362,4.542,2.997,2.379,all P＜0.05),which were then were scored with 7,5,9,7 and 5,respectively,with a total score of 0-33.AUC of the obtained scoring model for predicting proliferative HCC was 0.818.Taken 9 points as the optimal score thresholds,97 cases were assigned into high proliferation subgroup and 144 into low proliferation risk subgroups).Significant differences of RFS rates and early RFS rates were found between groups and subgroups(all P＜0.05).Conclusion MRI features scoring model could effectively predict proliferative HCC.

Purpose To investigate the pathological characteristics of hepatocellular carcinoma(HCC)with irregular rim-like arterial phase enhancement(IRE)using gadoxetic acid-enhanced,and its early recurrence prognostic significance after surgery.Materials and Methods This retrospective study included 131 patients with surgically confirmed HCCs who underwent gadoxetic acid-enhanced MRI from February 2015 to September 2021 in the Third People's Hospital of Nantong.According to the enhancement pattern of gadoxetic acid-enhanced MRI in arterial phase,HCC were divided into IRE-HCC and non-IRE-HCC.Clinical,pathological and imaging characteristics were compared between IRE-HCC and non-IRE-HCC.Logistic regression analyses were performed to identify clinical,pathological and imaging features associated with IRE-HCC.Early recurrence(within 2 years)was evaluated by using Kaplan-Meier analysis.Cox regression analysis was performed to determine independent predictors of early recurrence.Results Cytokeratin 19(CK19)(OR=9.027,95%CI 2.533-32.170,P=0.001),microvascular invasion(OR=3.606,95%CI 1.024-12.701,P=0.046)and diffusion weighted imaging target signs(OR=10.370,95%CI 3.046-35.303,P=0.000)were independent predictors for IRE-HCC.The 2-year cumulative recurrence-free survival rate postoperative of IRE-HCC was 24.1%,which was significantly shorter than that of non-IRE-HCC(55.9%,χ2=19.971,P=0.000).Microvascular invasion(HR=2.206,95%CI 1.152-4.226,P=0.017)and IRE(HR=2.454,95%CI 1.408-4.275,P=0.002)were independent predictors of early postoperative recurrence of HCC.Conclusion IRE-HCC are associated with CK19,microvascular invasion and diffusion weighted imaging target signs,and have a high recurrence rate and poor prognosis in the early postoperative period.