Liver fibrosis is a key histologic marker of long-term outcome in chronic liver disease. Non-invasive tests (NITs) have been shown to have predictive value, but the superiority of "dynamic" versus "static" assessment remains controversial. This article systematically reviews the latest evidence to elucidate the association between longitudinal changes in NITs and hepatic adverse events and assess the incremental contribution of dynamic monitoring to the model. Additionally, it reveals that the dynamic monitoring of NITs is truly superior to single evaluation, but the evidence is limited and the heterogeneity is significant. Dynamic modeling approaches for NITs require a shift from traditional parameter estimation to time-series machine learning. Future studies should make breakthroughs in disease stratification, modeling method innovation, data quality improvement, and prediction ability assessment so as to promote the transition of NITs from "static risk label" to "dynamic individualized engine," which can truly serve clinical decision-making.

This study investigated the prevalence and potential mechanisms of gentamicin heterore-sistance in Streptococcus isolates from dairy cows.In this study,A total of 39 Streptococcus isola-ted from raw milk were collected,and the minimum inhibitory concentration(MIC)of gentamicin and other drugs on the isolates was determined by micro broth dilution method,and the K-B paper diffusion method,colony analysis profile(PAP),and resistance stability test were used to investigate the heteroresistance characteristics of Streptococcus,and the mechanism of heteroresis-tance was analyzed based on whole genome sequencing and resequencing.Seven suspected heterore-sistance strains were identified by K-B paper diffusion method,accounting for 17.95％(7/39)of the total number of suspected strains.PAP confirmed that the MIC to MNIC ratio of L147,L108 and L174 was greater than 8,and the frequency of resistant subgroups ranged from 1.38×10-5 to 8.18 × 10-5,which was greater than 1 × 10-7,confirming that they were heteroresistance strains.Resistance stability tests revealed that the resistant subpopulations of all three strains were not stably inherited.Whole-genome sequencing revealed mutations in the ribosomal target genes of aminoglycoside antibiotics,rsmA,rsmB and rsmE,compared with the reference genome,which may lead to heteroresistance to gentamicin in Streptococcus.The occurrence of heteroresistance of Streptococcus to gentamicin is high in dairy sources,so more attention should be paid to the occur-rence of heteroresistance when using gentamicin for clinical treatment.

This study investigated the prevalence and potential mechanisms of gentamicin heterore-sistance in Streptococcus isolates from dairy cows.In this study,A total of 39 Streptococcus isola-ted from raw milk were collected,and the minimum inhibitory concentration(MIC)of gentamicin and other drugs on the isolates was determined by micro broth dilution method,and the K-B paper diffusion method,colony analysis profile(PAP),and resistance stability test were used to investigate the heteroresistance characteristics of Streptococcus,and the mechanism of heteroresis-tance was analyzed based on whole genome sequencing and resequencing.Seven suspected heterore-sistance strains were identified by K-B paper diffusion method,accounting for 17.95％(7/39)of the total number of suspected strains.PAP confirmed that the MIC to MNIC ratio of L147,L108 and L174 was greater than 8,and the frequency of resistant subgroups ranged from 1.38×10-5 to 8.18 × 10-5,which was greater than 1 × 10-7,confirming that they were heteroresistance strains.Resistance stability tests revealed that the resistant subpopulations of all three strains were not stably inherited.Whole-genome sequencing revealed mutations in the ribosomal target genes of aminoglycoside antibiotics,rsmA,rsmB and rsmE,compared with the reference genome,which may lead to heteroresistance to gentamicin in Streptococcus.The occurrence of heteroresistance of Streptococcus to gentamicin is high in dairy sources,so more attention should be paid to the occur-rence of heteroresistance when using gentamicin for clinical treatment.

Liver fibrosis is a key histologic marker of long-term outcome in chronic liver disease. Non-invasive tests (NITs) have been shown to have predictive value, but the superiority of "dynamic" versus "static" assessment remains controversial. This article systematically reviews the latest evidence to elucidate the association between longitudinal changes in NITs and hepatic adverse events and assess the incremental contribution of dynamic monitoring to the model. Additionally, it reveals that the dynamic monitoring of NITs is truly superior to single evaluation, but the evidence is limited and the heterogeneity is significant. Dynamic modeling approaches for NITs require a shift from traditional parameter estimation to time-series machine learning. Future studies should make breakthroughs in disease stratification, modeling method innovation, data quality improvement, and prediction ability assessment so as to promote the transition of NITs from "static risk label" to "dynamic individualized engine," which can truly serve clinical decision-making.

Objective To discuss the value of clinical radiomic nomogram(CRN)and deep convolutional neural network(DCNN)in distinguishing atypical pulmonary hamartoma(APH)from atypical lung adenocarcinoma(ALA).Methods A total of 307 patients were retrospectively recruited from two institutions.Patients in institu-tion 1 were randomly divided into the training(n=184:APH=97,ALA=87)and internal validation sets(n=79:APH=41,ALA=38)in a ratio of 7∶3,and patients in institution 2 were assigned as the external validation set(n=44:APH=23,ALA=21).A CRN model and a DCNN model were established,respectively,and the performances of two models were compared by delong test and receiver operating characteristic(ROC)curves.A human-machine competition was conducted to evaluate the value of AI in the Lung-RADS classification.Results The areas under the curve(AUCs)of DCNN model were higher than those of CRN model in the training,internal and external validation sets(0.983 vs 0.968,0.973 vs 0.953,and 0.942 vs 0.932,respectively),however,the differences were not statistically significant(p=0.23,0.31 and 0.34,respectively).With a radiologist-AI com-petition experiment,AI tended to downgrade more Lung-RADS categories in APH and affirm more Lung-RADS cat-egories in ALA than radiologists.Conclusion Both DCNN and CRN have higher value in distinguishing APH from ALA,with the former performing better.AI is superior to radiologists in evaluating the Lung-RADS classification of pulmonary nodules.

Objective To construct a radiomics nomogram combining clinical and a radiomics signature for distinguishing type Ⅱpapillary renal cell carcinoma(pRCC)from atypical clear cell renal cell carcinoma(ccRCC).Methods Clinical and CT data of patients with pathologically confirmed type Ⅱ pRCC(62 cases)and atypical ccRCC(56 cases)were analyzed.A random sample was divided into a training set(82 cases)and a test set(36 cases)in a ratio of 7∶3.Clinical factors were screened to construct clinical factor models.A total of 1 595 radiomics features of tumors were extracted from the corticomedullary phase CT images and based on the most effective features to construct a radiomics signature and calculate the radiomics score(Rad-score).A radiomics nomogram was constructed by combining the Rad-score and independent clinical factors.Receiver operating characteristic(ROC)curve was used to assess the clini-cal usefulness of the models.Decision curve analysis(DCA)was used to assess the difference between the models.Results The radiomics signature showed good discrimination in training set area under the curve(AUC)0.894[95％confidence interval(CI)0.834-0.947]and test set AUC 0.879(95％CI 0.774-0.963).The AUC of the clinical factors model in training set and test set were 0.725(95％CI 0.646-0.804)and 0.698(95％CI 0.567-0.819).The AUC of the radiomics nomogram in training set and test set were 0.901(95％CI 0.840-0.953)and 0.901(95％CI 0.809-0.975).DCA demonstrated the radiomics nomogram outmatched the clinical factors model and radiomics signature in the aspects of clinical usefulness.Conclusion Radiomics nomogram based on enhanced CT can provide good prediction of type Ⅱ pRCC and atypical ccRCC preoperatively,improve the diagnostic accuracy and provide guidance for future clinical treatment.

Objective:To investigate the value of nomogram based on radiomics features of CT enterography (CTE) combined with clinical characteristics to predict secondary loss of response (SLOR) after infliximab (IFX) treatment in patients with Crohn′s disease (CD).Methods:This study was a case-control study. Clinical and imaging data of 155 patients with CD diagnosed at the First Affiliated Hospital of Anhui Medical University from March 2015 to July 2022 were retrospectively collected. The patients were divided into a training set ( n=108) and a testing set ( n=47) in the ratio of 7∶3 by stratified sampling method. All patients were treated according to the standardized protocol and were classified as SLOR (43 in the training set and 18 in the testing set) and non-SLOR (65 in the training set and 29 in the testing set) according to treatment outcome. Based on the data from the training group, independent clinical predictors of SLOR after IFX treatment were screened in the clinical data using univariate and multivariate logistic regression analysis to establish a clinical model. Intestinal phase images were selected to be outlined layer by layer along the margin of the lesion to obtain the volume of the region of interest to extract the radiomics features. The radiomics features were screened using univariate analysis and the minimum absolute shrinkage and selection operator to establish the radiomics model. Multivariate logistic regression analysis was used to build a combined clinical-radiomics model based on the screened clinical independent predictors and radiomics characters, then a nomogram was drawn. The predictive efficacy of the 3 models for SLOR after IFX treatment was assessed by receiver operating characteristic curves, and the area under the curve (AUC) was calculated. The decision curve analysis was applied to evaluate the clinical utility of the models. Results:Disease duration ( OR=1.983, 95% CI 1.966-2.000, P=0.046) and intestinal stenosis ( OR=1.246, 95% CI 1.079-1.764, P=0.015) were identified as the independent predictors of SLOR in the clinical data, and a clinical model was established. Totally 9 radiomics features were included in the radiomics model. The AUCs of clinical, radiomics, and combined models for predicting SLOR after IFX treatment in CD patients were 0.691 (95% CI 0.591-0.792), 0.896 (95% CI 0.836-0.955), and 0.910 (95% CI 0.855-0.965) in the training set, and 0.722 (95% CI 0.574-0.871), 0.866 (95% CI 0.764-0.968), and 0.889 (95% CI 0.796-0.982) in the testing set. Decision curve analysis in the testing set showed higher net clinical benefits for both the radiomics model and combined model than the clinical model, and combined model had higher net clinical benefits than the radiomics model over most threshold probability intervals. Conclusions:CTE-based radiomics model can effectively predict SLOR after IFX treatment in patients with CD, and a combined model by incorporating clinical characteristics of disease duration and intestinal stenosis can further improve the predictive efficacy.

Objective:To investigate the stability and feasibility of improved silent MRA technique based on hybrid-arterial spin labeling(ASL) for imaging intracranial arterial stenosis.Methods:From September 2019 to May 2020, totally 35 patients with suspected intracranial vascular stenosis in Department of Neurology of Northern Jiangsu People′s Hospital were enrolled in this study. Silent MRA and improved silent MRA based on hybrid-ASL technique were performed respectively. The acquisition noise (noise measurement and subjective score) of two kinds of MRA examination were evaluated respectively. Two neuroradiologists performed image quality scoring and signal-to-noise ratio (SNR) measurement of intracranial arteries (including internal carotid artery, vertebrobasilar artery, anterior cerebral artery, middle cerebral artery, and posterior cerebral artery) in the two kinds of MRA images using a double-blind, completely randomized method. Independent sample t-test was used to compare the image quality and SNR of two kinds of MRA images in each segment. Two experts assessed the degree of stenosis at the site of confirmed intracranial artery stenosis. Kappa test was used to assess interobserver and intermodel agreement. Results:There was no significant difference in acquisition noise between improved silent MRA and silent MRA ( P>0.05). In all five segments measured, the image quality scores of internal carotid artery [(4.40±0.49)scores], anterior cerebral artery[(4.30±0.33)scores] and middle cerebral artery [(4.46±0.34)scores] in improved silent MRA were higher than those in silent MRA images [(4.02±0.43)scores, (4.02±0.31)scores, (4.02±0.31)scores; t=2.825, 2.877, 1.683, all P<0.05)]. The SNR of internal carotid artery (9.11±1.23) and middle cerebral artery (8.77±1.87) in improved silent MRA images was higher than that in silent MRA images (7.83±1.33, 8.06±2.67, respectively; t=11.154, 3.268, both P<0.05). A total of 24 patients (38 lesions) with intracranial vascular stenosis were diagnosed by CTA. Improved silent MRA (Kappa=0.89, 95%CI 0.82-0.95) and silent MRA (Kappa=0.85, 95%CI 0.77-0.92) were highly consistent among observers in evaluating the degree of cerebrovascular stenosis.The results of improved silent MRA were highly consistent with those of CTA (Kappa=0.92, 95%CI 0.87-0.98), and those of silent MRA were highly consistent with those of CTA (Kappa=0.85, 95%CI 0.77-0.92). Conclusions:The improved silent MRA is feasible to improve the imaging quality and signal uniformity through efficient marking based on keeping the low noise features. In the diagnosis of intracranial stenosis and occlusive disease, the stability of improved silent MRA imaging improves the diagnostic efficiency of stenosis to a certain extent.

Objective: To evaluate the effect of different irradiation methods on the long-term prognosis of patients with clinical T_2-3N₀M₀ esophageal squamous cell carcinoma, aiming to select the optimal treatment for these patients. Methods: A total of 268 eligible patients admitted to our hospital from January 2007 to December 2012 were enrolled in this study. All patients were divided into the involved-field irradiation (IFI) and elective node irradiation (ENI) groups. The composition ratio, prognostic factors and adverse events were analyzed between two groups. Results: The median overall survival (OS) time was 35.5 months (95%CI : 30.12-40.88) and the median disease-free survival (DFS) time was 23.5 months (95%CI: 19.00-28.00). According to the multivariate analysis results, all patients were assigned into two groups at a ratio of 1 vs.1(n=86 in each group). Multivariate analysis after propensity score matching (PSM) demonstrated that irradiation method was the independent factor of OS (P=0.038), and T stage and radiotherapy were the independent factors affecting DFS (P=0.002, 0.032). The incidence of ≥grade Ⅱ adverse events did not significantly differ between two groups (P=0.819, 0.756). However, patients with combined chemotherapy experienced more adverse events. Conclusion ENI can prolong the OS and DFS of patients with clinical T_2-3N₀M₀ esophageal squamous cell carcinoma, and does not increase the incidence of severe adverse events.

Objective: To evaluate the effect of locoregional risk factors of esophageal cancer on the recurrence of gross tumor volume (GTV) in patients with N₀ esophageal squamous cell carcinoma after radical intensity-modulated radiotherapy (IMRT) and to evaluate its effect on the 10-year survival of patients. Methods: Clinical data of 374 patients with clinical N₀ esophageal squamous cell carcinoma who underwent radical IMRT in the Fourth Hospital of Hebei Medical University from 2005 to 2010 were retrospectively analyzed. Involved-field irradiation was performed in 284 patients and selective lymph node irradiation was given in 90 patients. Concurrent radiochemotherapy was conducted in 69l patients and sequential radiochemotherapy was performed in 38 patients. The survival analysis was carried out by Kaplan-Meier method. The prognosis analysis was performed by multivariate Cox’s regression model. Results: A total of 143 patients (38.2%) had recurrence in GTV. The maximum transverse diameter (GTV-D), GTV volume (GTV-V) and GTV volume/length (GTV-V/L) of GTV patients were significantly longer than those without recurrence in GTV (P=0.008, 0.043, 0.001). ROC curve analysis showed that the optimal diagnostic thresholds for GTV-D, GTV-L, GTV-V and GTV-V/L for GTV recurrence were 3.5 cm, 5.5 cm, 24.0 cm³ and 4.6 cm², respectively (P=0.000, 0.003, 0.000 and 0.000), and the ratio of recurrence within GTV in the patient group was significantly greater than that in the smaller group (P=0.000, 0.002, 0.001 and 0.000). GTV-L and GTV-V/L were the independent risk factors of recurrence in GTV (P=0.021 and 0.009). The 3-, 5-and 10-year survival rates of all patients in the whole group were 42.9%, 23.2% and 7.9%, respectively. Multivariate analysis demonstrated that age, T stage, concurrent radiochemotherapy, GTV-D and GTV-V/L were the independent risk factors of survival (P=0.027, 0.000, 0.018, 0.009 and 0.034). The main cause of death in patients with a survival time of more than 5 years was still associated with cancer. Conclusions The locoregional risk factors of esophageal cancer exert significant effect on the recurrence of GTV in patients with N₀ esophageal squamous cell carcinoma undergoing radical radiochemotherapy, which can be utilized as the predicting markers. Both GTV-D and GTV-V/L are significantly correlated the 10-year survival of patients.