Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

Objective:To investigate the impact of different etiologies on the spatial distribution pattern of infarcts and the mapping pattern of focal symptoms in acute ischemic stroke (AIS) using a population-based standardized spatial analysis of MRI.Methods:This was a cross-sectional study. Clinical [age, sex distribution, admission National Institutes of Health Stroke Scale (NIHSS) score and 90-day modified Rankin Scale (mRS) score at discharge, etc.] and imaging data of 2 610 patients with AIS attending 9 Medical Centers from January 2015 to December 2021 were retrospectively analyzed. All patients were categorized into 1 718 cases of large artery atherosclerosis (LAA) type, 335 cases of cardioembolism (CE) type, and 557 cases of small artery occlusion (SAO) type according to TOAST typing. All patients underwent diffusion-weighted imaging, and the detected infarct lesions were segmented and aligned to the standardized space using artificial intelligence-assisted methods, and the spatial distribution frequency heatmaps of lesion locations in patients with different TOAST subtypes were plotted and compared with each other by χ2 test. Lesion-symptom image brain maps with different clinical symptoms were further plotted, and differences of lesion-symptom image relationships among different TOAST subtypes were observed and compared with each other by interaction effect. Results:In all patients, the favored sites of infarct lesions were the bilateral middle cerebral artery region in the anterior circulation and the occipital and brainstem regions in the posterior circulation. Compared with the LAA type, the CE type lesions were more likely to occur in the anterior cerebral artery region, the occipital lobe, and the cerebellum posterior, while the SAO type lesions were more likely to occur in the perforator artery supply area. The lesion-symptom mapping results showed that AIS patients with infarct lesions in the frontoparieto-temporal region in the presence of a left middle cerebral artery supply had higher admission NIHSS scores and higher discharge 90-day mRS scores for the LAA type than for the CE type( P<0.05); AIS patients with infarcted lesions in the brainstem region and some cerebellar regions in the presence of vertebrobasilar artery supply had higher admission NIHSS scores and higher discharge 90-day mRS scores for the CE type than for the LAA type( P<0.05). Conclusion:At the population level, brain mapping reveals specific infarct distribution patterns and differences in lesion-symptom mapping patterns of different etiologies AIS patients, providing imaging evidence for the understanding of AIS pathogenetic mechanisms and clinical management.

Objective:To investigate the impact of different etiologies on the spatial distribution pattern of infarcts and the mapping pattern of focal symptoms in acute ischemic stroke (AIS) using a population-based standardized spatial analysis of MRI.Methods:This was a cross-sectional study. Clinical [age, sex distribution, admission National Institutes of Health Stroke Scale (NIHSS) score and 90-day modified Rankin Scale (mRS) score at discharge, etc.] and imaging data of 2 610 patients with AIS attending 9 Medical Centers from January 2015 to December 2021 were retrospectively analyzed. All patients were categorized into 1 718 cases of large artery atherosclerosis (LAA) type, 335 cases of cardioembolism (CE) type, and 557 cases of small artery occlusion (SAO) type according to TOAST typing. All patients underwent diffusion-weighted imaging, and the detected infarct lesions were segmented and aligned to the standardized space using artificial intelligence-assisted methods, and the spatial distribution frequency heatmaps of lesion locations in patients with different TOAST subtypes were plotted and compared with each other by χ2 test. Lesion-symptom image brain maps with different clinical symptoms were further plotted, and differences of lesion-symptom image relationships among different TOAST subtypes were observed and compared with each other by interaction effect. Results:In all patients, the favored sites of infarct lesions were the bilateral middle cerebral artery region in the anterior circulation and the occipital and brainstem regions in the posterior circulation. Compared with the LAA type, the CE type lesions were more likely to occur in the anterior cerebral artery region, the occipital lobe, and the cerebellum posterior, while the SAO type lesions were more likely to occur in the perforator artery supply area. The lesion-symptom mapping results showed that AIS patients with infarct lesions in the frontoparieto-temporal region in the presence of a left middle cerebral artery supply had higher admission NIHSS scores and higher discharge 90-day mRS scores for the LAA type than for the CE type( P<0.05); AIS patients with infarcted lesions in the brainstem region and some cerebellar regions in the presence of vertebrobasilar artery supply had higher admission NIHSS scores and higher discharge 90-day mRS scores for the CE type than for the LAA type( P<0.05). Conclusion:At the population level, brain mapping reveals specific infarct distribution patterns and differences in lesion-symptom mapping patterns of different etiologies AIS patients, providing imaging evidence for the understanding of AIS pathogenetic mechanisms and clinical management.

Objective:To investigate the predictive value of fluid-attenuated inversion recovery (FLAIR) signal strength ratio (SIR) in onset time≤4.5 h in patients with acute ischemic stroke.Methods:A retrospective analysis was performed; 180 acute ischemic stroke patients admitted to Department of Neurology, Nanjing Hospital Affiliated to Nanjing Medical University from January 2020 to June 2023 were chosen. Hypoperfusion intensity ratio (HIR) was used to evaluate the collateral circulation (poor collateral circulation: HIR≤0.4; good collateral circulation: HIR>0.4); clinical data and imaging indexes between poor collateral circulation and good collateral circulation groups were compared. Univariate and multivariate Logistic regressions were used to analyze the influencing factors for onset time≤4.5 h in patients with acute ischemic stroke. Correlation between SIR and onset time was analyzed in patients with acute ischemic stroke. Role of HIR as agency between SIR and onset time was explored. Receiver operating characteristic (ROC) curve was used to analyze the predictive efficacy of SIR and diffusion weighted imaging (DWI)-FLAIR mismatch in onset time≤4.5 h in acute ischemic stroke patients.Results:Of the 180 patients, 100 were into the good collateral circulation group and 80 were into the poor collateral circulation group; compared with the good collateral circulation group, the poor collateral circulation group had significantly higher percentage of patients with hyperlipidemia, larger DWI infarction volume before treatment, larger perfusion weighted imaging (PWI)-DWI mismatch volume and higher SIR ( P<0.05). In these 180 patients, 76 had onset time≤4.5 h and 104 had onset time>4.5 h. Univariate Logistic regression analysis showed that hyperlipidemia, DWI infarct volume before treatment, DWI-FLAIR mismatch, HIR and SIR were influencing factors for onset time≤4.5 h in acute ischemic stroke patients ( P<0.05). Multivariate Logistic regression analysis showed that hyperlipidemia ( OR=6.654, 95% CI: 5.751-8.824, P<0.001), HIR ( OR=0.724, 95% CI: 0.521-1.321, P=0.041) and SIR ( OR=739.881, 95% CI: 383.296-14 258.065, P<0.001) were independent influencing factors for onset time≤4.5 h in acute ischemic stroke patients. Pearson correlation analysis showed that SIR was positively correlated to onset time in patients with acute ischemic stroke ( r=0.420, P<0.05), and SIR was positively correlated to onset time in patients from poor collateral circulation group ( r=0.781, P<0.05). ROC curve showed that AUC of SIR in predicting onset time≤4.5 h was 0.917 (95% CI: 0.814-1.000, P<0.001) and that of DWI-FLAIR mismatch in predicting onset time≤4.5 h was 0.530 (95% CI: 0.509-0.757, P=0.075) in poor collateral circulation group, enjoying significant difference in predictive efficacy. Conclusion:Acute ischemic stroke patients with low HIR and SIR have higher odds of onset time≤4.5 h; SIR can more accurately predict the onset time in these patients with poor collateral circulation.

Objective:To evaluate the effect of deep learning based on DWI and fluid attenuated inversion recovery (FLAIR) to construct a prediction model of the onset time in acute stroke.Methods:A total of 324 cases of acute stroke with clear onset time, from January 2017 to May 2020 in Nanjing First Hospital, were retrospectively enrolled and analyzed. The patients were divided into a training set of 226 patients and a test set of 98 patients according to the complete randomization method using a 7∶3 ratio, and the patients were divided into ≤ 4.5 h and >4.5 h according to symptom onset time in each group. The acute infarction areas on DWI and the corresponding high signal area on FLAIR were manually outlined by physician. Using the InceptionV3 model as the basic model for image features extraction, the deep learning prediction model based on single sequence (DWI, FLAIR) and multi sequences (DWI+FLAIR) were established and verified. Then the area under curve (AUC), accuracy of human readings, single sequence model and multi sequence model in predicting the acute stroke onset time from imaging were compared.Results:DWI-FLAIR mismatch was found in 94 cases (94/207) of patients with symptom onset time from imaging ≤ 4.5 h, while in 28 cases (28/117) of patients with symptom onset time from imaging >4.5 h. ROC analysis showed that the AUC of DWI-FLAIR mismatch in predicting acute stroke onset time from imaging was 0.607, and the accuracy was 60.2%. The prediction model of deep learning based on single sequence showed that the AUC of FLAIR was 0.761 and the accuracy was 71.4%; the AUC of DWI was 0.836 and the accuracy was 81.6%. The AUC of predicting stroke onset time based on the multi-sequence (DWI+FLAIR) deep learning model was 0.852, which was significantly better than that of manual identification ( Z = 0.617, P = 0.002), FLAIR sequence deep learning model ( Z = 2.133, P = 0.006) and DWI sequence deep learning model ( Z = 1.846, P = 0.012). Conclusion:The deep learning model based on DWI and FLAIR is superior to human readings in predicting acute stroke onset time from imaging, which could provide guidance for intravenous thrombolytic therapy for acute stroke patients with unknown onset time.

Objective To investigate the feasibility and application value of the benign and malignant classificational methods of renal occupying CT images based on convolutional neural networks (CNN). Methods An image omics method that can automatically learn the image features and classify CT images was used. Firstly, the CNN model obtained by large-scale natural image training was used to migrate the characteristics of the renal occupancy lesions CT images, and then the fine-tuning of the full connection layer was used to realize the benign and malignant classification of the images. Results The evaluation indexes of the VGG19 model were lower than ResNet50 and Inception V3, and the training result showed obvious overfitting. The accuracy, sensitivity and negative prediction values of the Inception V3 model was 93.8％, 99.5％ and 99.1％, respectively, which were higher than that of the ResNet50 model. Conclusions The benign and malignant classification of renal occupancy lesions CT images using CNN is a reasonable and feasible method, and the fine-tuned Inception V3 model has a better classification performance.

Objective: To compare the application of iASSIST assisted total knee arthroplasty (TKA) and three-dimentional(3D) printing personal specific instrument (PSI) assist TKA in the treatment of osteoarthritis (OA). Methods: Clinical data of 47 patients with OA admitted at Department of Orthopaedic Surgery in Nanjing Medical University Nanjing Hospital between April and September 2016 were retrospectively reviewed, including 20 males and 27 females, aging from 57 to 77 years with mean age of (63.8±8.2) years. They were randomly divided into iASSIST-TKA group (23 patients) and PSI-TKA group (24 patients). The data such as hip knee ankle (HKA) angle, frontal femoral component (FFC) angle, frontal tibial component (FTC) angle, lateral femoral component (LFC) angle, lateral tibial component (LTC) angle, time of operation, post-operative wound drainage, period of hospitalization, visual analog scale (VAS) and Knee Society Score (KSS) at 1 day, 7 days, 14 days, 1 month and 3 months were recorded and compared between the two groups. T test was used to compare measurement data, Fisher exact test and χ² test were applied to enumeration data in comparison among groups, and Kruskal-Wallis test was applied to ranked data. Results: The deviation values of HKA, FFC, LFC, FTC and LTC angles were all below 3°(-2° to 2°), and there were no significant difference between iASSIST-TKA group and PSI-TKA group (Z=-0.610 to 0.000, P=0.542 to 1.000). Compared to PSI-TKA group, the time of operation was long((80.7±8.8) minutes vs.(60.2±7.8) minutes), the amount of post-operative wound drainage was increased((210.7±32.1) ml vs.(185.5±30.2)ml) and the period of hospitalization decreased((5.4±2.4) d vs.(6.7±1.6) d) in iASSIST-TKA group, there were significant difference(t=-2.190 to 8.460, P=0.000 to 0.033). There were no significant difference in intra-operative blood drainage((18.4±5.4) ml vs.(17.3±6.2) ml) between the two groups(t=0.650, P=0.521). PSI-TKA group had a superior VAS score(4.8±0.6 vs. 5.5±0.9, 3.6±0.8 vs. 4.3±0.9), KSS clinical score(49.3±5.5 vs. 44.2±6.4, 54.9±4.0 vs. 50.8±4.2) and KSS function score(44.1±2.9 vs. 41.2±3.5, 49.6±3.8 vs. 46.6±3.2) in 1 day and 7 days post-operation(t=-3.420 to 3.150, P=0.001 to 0.007). There were no significant difference in VAS and KSS score in 14 days, 1 month and 3 months post-operation(t=-1.390 to 0.530, P=0.170 to 1.000) between the two groups. Conclusions The iASSIST-TKA and PSI-TKA can help to make TKA procedure more accurately. iASSIST-TKA may take longer time of operation and have slower recovery, PSI-TKA may need more X-ray input and longer period of hospitalization. The long-term research of both techniques may be valuable for the further clinical usage.

Purpose To explore the value of 128-slice dual source CT (DSCT) three-dimensional post-processing techniques in the diagnosis of acute aortic dissection (AAD). Materials and Methods All image data of 116 patients with AAD who underwent conventional and enhanced DSCT scan by dual-energy scanning technology were retrospectively analyzed, and the multi-planar reconstruction (MPR), volume rendering (VR) and maximum intensity projection (MIP) were conducted in the workstation. Taking digital subtraction angiography (DSA) as the diagnostic gold standard, we analyzed the imaging manifestation of the original and 3D-reconstruction images and evaluated the specificity and the sensitivity of diagnostic accuracy and the image quality. Results The diagnostic accuracy of conventional scan was 37.1%(43/116). The display rates of MPR for initial break, intimal flap and true and false lumen were 93.1%, 100.0%and 100.0%, respectively. The display rates of VR and MIP for the initial break were 33.62%and 6.90%, respectively, which was both lower than that of MPR. The display rate of MIP for the true and false lumen was 23.28%. The overall display capability of MPR was significantly better than that of VR and MIP (P<0.01), and the display capability of VR was better than that of MIP (P<0.01). The sensitivity and specificity of enhanced DSCT in the diagnosis of AAD were both 100.0%. Conclusion DSCT has a fast and reliable diagnostic value on AAD. Conventional CT signs should be highly valued in the evaluation of chest or abdominal pain; and a thin layer of MPR and VR should be chosen in the three-dimensional reconstruction;whilst MIP reconstruction may be unnecessary for AAD.

Purpose To study the application of MR diffusion tensor imaging (DTI) quantitative parameters in grading of cerebral glioma on a 3.0T scanner. Materials and Methods DTI mapping of 51 cases of cerebral glioma confirmed by pathology were retrospective analyzed. All the cases were divided into two groups: low-grade gliomas (grade I-II, 18 cases) and high-grade gliomas (grade III-IV, 33 cases). Value of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD),λ1, λ2, and λ3 of the tumor, peritumoral edema and contralateral tissue area were recorded and compared. Results rMDt, rADt, rRDt, λ1t, λ2t and λ3t of tumor in the low-grade glioma group were higher than those in the high-grade glioma group, and the difference was statistically significant (t=-3.235- -2.458, P<0.05). rFAt was lower in the low-grade glioma group, and the difference was not statistically significant (t=1.554, P>0.05). rFAe of peritumoral edema in the low-grade glioma group was higher than those in the high-grade group, while rMDe, rADe, rRDe, λ1e, λ2e and λ3e were lower in the low-grade group. All differences were not statistically significant except λ1e (t=2.052, P<0.05). ROC analysis showed the area under the curve (Az) of rMDt, rADt, rRDt, λ1t, λ2t, λ3t and λ1e were 0.746, 0.710, 0.762, 0.735, 0.722, 0.705 and 0.374, respectively. Az value of rMDt, rADt, rRDt,λ1t, λ2t, λ3t were statistically different between the low- and high-grade gliomas (Z=3.287-4.605, P<0.001). Conclusion Among DTI quantitative parameters on glioma grading, rMD, rAD, rRD, λ1, λ2, and λ3 of tumor area are helpful in grading gliomas.

OBJECTIVE: To evaluate dual-source CT in the Standford B aortic dissection in the postoperative follow-up and to compare radiation dose of dual-energy mode with single-energy scanning. METHODS: A total of 40 patients with aortic dissection after endovascular exclusion underwent dualsource CT. Tweny patients took the dual-energy scanning mode (100 kV and 140 kV, pitch 1.0); the other 20 patients had single-energy mode (120 kV, pitch 2.0). In both groups CareDose4D technology was used to track the current method. All images were analyzed to observe the stent shape, with or without endoleaks and the rate of thrombosis absorption. Radiation dose, scan length, and scan time were recorded for all patients, and then compared between dual-energy mode and single-energy scanning. RESULTS: The difference in scan length and image quality was not significant between the dualenergy group and the single-energy group. The acquisition time of the dual-energy group was longer than that of the single-energy group, with significant difference. Radiation dose of the single-energy group was lower than that of the dual-energy group, with significant difference. CONCLUSION Dual-source CT can objectively evaluate the conditions after the endovascular exclusion of aortic dissection. The operative effect and complications may be analyzed comprehensively. The radiation dose of the single-energy scan mode with medium pitch is lower than that of the dual-energy mode.
Aneurysm, Dissecting ; diagnostic imaging ; Aortic Aneurysm ; diagnostic imaging ; Humans ; Radiation Dosage ; Sensitivity and Specificity ; Tomography, X-Ray Computed