Background Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive treatment for ischemic stroke. Astrocytes regulation has been suggested as one mechanism for rTMS effectiveness. But how rTMS regulates astrocytes remains largely undetermined. There were neurotoxic and neuroprotective phenotypes of astrocytes (also denoted as classically and alternatively activated astrocytes or A1 and A2 astrocytes) pertaining to pro- or anti-inflammatory gene expression. Pro-inflammatory or neurotoxic polarized astrocytes were induced during cerebral ischemic stroke. The present study aimed to investigate the effects of rTMS on astrocytic polarization during cerebral ischemic/reperfusion injury. Methods Three rTMS protocols were applied to primary astrocytes under normal and oxygen-glucose deprivation/reoxygenation (OGD/R) conditions. Cell survival, proliferation, and phenotypic changes were assessed after 2-day treatment. Astrocytes culture medium (ACM) from control, OGD/R, and OGD/R + rTMS groups were mixed with neuronal medium to culture neurons for 48 h and 7 days, in order to explore the influence on neuronal survival and synaptic plasticity. In vivo, rats were subjected to middle cerebral artery occlusion (MCAO), and received posterior orbital intravenous injection of ACM collected from different groups at reperfusion, and at 3 days post reperfusion. The apoptosis in the ischemic penumbra, infarct volumes, and the modified Neurological Severity Score (mNSS) were evaluated at 1 week after reperfusion, and cognitive functions were evaluated using the Morris Water Maze (MWM) tests. Finally, the 10 Hz rTMS was directly applied to MCAO rats to verify the rTMS effects on astrocytic polarization. Results Among these three frequencies, the 10 Hz protocol exerted the greatest potential to modulate astrocytic polarization after OGD/R injury. Classically activated and A1 markers were significantly inhibited by rTMS treatment. In OGD/R model, the concentration of pro-inflammatory mediator TNF-α decreased from 57.7 to 23.0 рg/mL, while anti-inflammatory mediator IL-10 increased from 99.0 to 555.1 рg/mL in the ACM after rTMS treatment. The ACM collected from rTMS-treated astrocytes significantly alleviated neuronal apoptosis induced by OGD/R injury, and promoted neuronal plasticity. In MCAO rat model, the ACM collected from rTMS treatment decreased neuronal apoptosis and infarct volumes, and improved cognitive functions. The neurotoxic astrocytes were simultaneously inhibited after rTMS treatment. Conclusion Inhibition of neurotoxic astrocytic polarization is a potential mechanism for the effectiveness of high-frequency rTMS in cerebral ischemic stroke.

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In hemodialysis patients with LV hypertrophy, myocardial function was impaired not only in longitudinal direction but also in circumferential direction despite preserved LVEF. Low longitudinal strain is related to LV hypertrophy, concentric geometry and pre-dialysis blood pressure.

Both CEUS and CECT imaging modalities are effective for the differential diagnosis of benign and malignant SRMs. Furthermore, CEUS may be more effective than CECT for the qualitative diagnosis of small papillary RCC.

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These authors contributed equally to this workPurpose: We aimed to assess the classification performance of a computed tomography (CT)-based radiomic signature for discriminating invasive and non-invasive lung adenocarcinoma. Patients and Methods: A total of 192 patients (training cohort, n=116; validation cohort, n=76) with pathologically confirmed lung adenocarcinoma were retrospectively enrolled in the present study. Radiomic features were extracted from preoperative unenhanced chest CT images to build a radiomic signature. Predictive performance of the radiomic signature were evaluated using an intra-cross validation cohort. Diagnostic performance of the radiomic signature was assessed via receiver operating characteristic (ROC) analysis. Results: The radiomic signature consisted of 14 selected features and demonstrated good discrimination performance between invasive and non-invasive adenocarcinoma. The area under the ROC curve (AUC) for the training cohort was 0.83 (sensitivity, 0.84 ; specificity, 0.78; accuracy, 0.82), while that for the validation cohort was 0.77 (sensitivity, 0.94; specificity, 0.52 ; accuracy, 0.82). Conclusion: The CT-based radiomic signature exhibited good classification performance for discriminating invasive and non-invasive lung adenocarcinoma, and may represent a valuable biomarker for determining therapeutic strategies in this patient population.

Background In this study, we tested whether a combination of radiomic features extracted from baseline pre-immunotherapy computed tomography (CT) images and clinicopathological characteristics could be used as novel noninvasive biomarkers for predicting the clinical benefits of non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). Methods The data from 92 consecutive patients with lung cancer who had been treated with ICIs were retrospectively analyzed. In total, 88 radiomic features were selected from the pretreatment CT images for the construction of a random forest model. Radiomics model 1 was constructed based on the Rad-score. Using multivariate logistic regression analysis, the Rad-score and significant predictors were integrated into a single predictive model (radiomics nomogram model 1) to predict the durable clinical benefit (DCB) of ICIs. Radiomics model 2 was developed based on the same Rad-score as radiomics model 1.Using multivariate Cox proportional hazards regression analysis, the Rad-score, and independent risk factors, radiomics nomogram model 2 was constructed to predict the progression-free survival (PFS). Results The models successfully predicted the patients who would benefit from ICIs. For radiomics model 1, the area under the receiver operating characteristic curve values for the training and validation cohorts were 0.848 and 0.795, respectively, whereas for radiomics nomogram model 1, the values were 0.902 and 0.877, respectively. For the PFS prediction, the Harrell’s concordance indexes for the training and validation cohorts were 0.717 and 0.760, respectively, using radiomics model 2, whereas they were 0.749 and 0.791, respectively, using radiomics nomogram model 2. Conclusions CT-based radiomic features and clinicopathological factors can be used prior to the initiation of immunotherapy for identifying NSCLC patients who are the most likely to benefit from the therapy. This could guide the individualized treatment strategy for advanced NSCLC.

BackgroundTo investigate the contrast-enhanced ultrasound (CEUS) findings of renal cell carcinoma (RCC) associated with Xp11.2 translocation/TFE3 gene fusion (Xp11.2/TFE3) in adult patients by comparison with those of clear cell RCC (ccRCC) and papillary RCC (pRCC).MethodsIn total, 110 patients (110 renal masses) who underwent CEUS examinations were enrolled in this study. The cases included 18 Xp11.2/TFE3 RCCs, 60 ccRCCs and 32 pRCCs. All masses were confirmed by operative pathology. The CEUS imaging data of these patients were retrospectively analysed by two readers. The conventional US and CEUS features of Xp11.2/TFE3 RCC were compared with those of ccRCC and pRCC.ResultsThe age of the patients with Xp11.2/TFE3 RCC ranged from 20 to 68 years, with a mean age of 38.3 ± 16.3 years and a slight female predominance. The weighted kappa value that interprets the concordance between the interobserver agreement of the US and CEUS features ranged from 0.61 to 0.89. On conventional US and CEUS imaging of Xp11.2/TFE3 RCCs, the tumours were hypoechoic (6/18, 33.3%), isoechoic (8/18, 44.4%), and hyperechoic (4/18, 22.2%). The cystic component was present in 5 cases (27.8%), calcification was present in 9 cases (50.0%), and colour flow signal was present in 7 cases (38.9%). Most cases showed simultaneous wash-in (11/18, 61.1%); the peak enhancement showed hypoenhancement (6/18, 33.3%), isoenhancement (10/18, 55.6%), and hyperenhancement (2/18, 11.1%); most cases exhibited heterogeneous enhancement (12/18, 66.7%) and fast- or simultaneous-out (16/18, 88.9%); and a pseudocapsule was present in 6 cases (33.3%). In the multivariate logistic regression analysis, calcification and lower peak enhancement were more likely to be present in Xp11.2/TFE3 RCC than in ccRCC (P < 0.05), and younger age and relatively high peak enhancement were more likely to be present in Xp11.2/TFE3 RCC than in pRCC (P < 0.05). The calcification combined peak enhancement model differentiated Xp11.2/TFE3 RCC from ccRCC, and the age combined peak enhancement model differentiated Xp11.2/TFE3 RCC from pRCC with an AUC, a sensitivity and a specificity of 0.896, 94.4% and 73.3% and 0.786, 50.0% and 100.0%, respectively.ConclusionsThe specific CEUS features combined with demographic information and clinical symptoms may be helpful for differentiating Xp11.2/TFE3 RCC from ccRCC and pRCC.