Our findings indicate a crucial role of ABCB6 in ALA metabolism and accumulation of PpIX in glioma. ABCB6 overexpression is a potential approach to enhance accumulation of PpIX for optimizing the subjective discrimination of vague fluorescence and improving the efficacy of ALA-based photodynamic therapy.

Prior randomized trials have generally shown harm or no benefit of stenting added to medical therapy for patients with symptomatic severe intracranial atherosclerotic stenosis, but it remains uncertain as to whether refined patient selection and more experienced surgeons might result in improved outcomes.OBJECTIVE To compare stenting plus medical therapy vs medical therapy alone in patients with symptomatic severe intracranial atherosclerotic stenosis. DESIGN, SETTING, AND PARTICIPANTSMulticenter, open-label, randomized, outcome assessor-blinded trial conducted at 8 centers in China. A total of 380 patients with transient ischemic attack or nondisabling, nonperforator (defined as nonbrainstem or non-basal ganglia end artery) territory ischemic stroke attributed to severe intracranial stenosis (70%-99%) and beyond a duration of 3 weeks from the latest ischemic symptom onset were recruited between March 5, 2014, and November 10, 2016, and followed up for 3 years (final follow-up: November 10, 2019).INTERVENTIONS Medical therapy plus stenting (n = 176) or medical therapy alone (n = 182). Medical therapy included dual-antiplatelet therapy for 90 days (single antiplatelet therapy thereafter) and stroke risk factor control. MAIN OUTCOMES AND MEASURESThe primary outcome was a composite of stroke or death within 30 days or stroke in the qualifying artery territory beyond 30 days through 1 year. There were 5 secondary outcomes, including stroke in the qualifying artery territory at 2 years and 3 years as well as mortality at 3 years. RESULTS Among 380 patients who were randomized, 358 were confirmed eligible (mean age, 56.3 years; 263 male [73.5%]) and 343 (95.8%) completed the trial. For the stenting plus medical therapy group vs medical therapy alone, no significant difference was found for the primary outcome of risk of stroke or death (8.0% [14/176] vs 7.2% [13/181]; difference, 0.4% [95% CI, −5.0% to 5.9%]; hazard ratio, 1.10 [95% CI, 0.52-2.35]; P = .82). Of the 5 prespecified secondary end points, none showed a significant difference including stroke in the qualifying artery territory at 2 years (9.9% [17/171] vs 9.0% [16/178]; difference, 0.7% [95% CI, −5.4% to 6.7%]; hazard ratio, 1.10 [95% CI, 0.56-2.16]; P = .80) and 3 years (11.3% [19/168] vs 11.2% [19/170]; difference, −0.2% [95% CI, −7.0% to 6.5%]; hazard ratio, 1.00 [95% CI, 0.53-1.90]; P > .99). Mortality at 3 years was 4.4% (7/160) in the stenting plus medical therapy group vs 1.3% (2/159) in the medical therapy alone group (difference, 3.2% [95% CI, −0.5% to 6.9%]; hazard ratio, 3.75 [95% CI, 0.77-18.13]; P = .08).CONCLUSIONS AND RELEVANCE Among patients with transient ischemic attack or ischemic stroke due to symptomatic severe intracranial atherosclerotic stenosis, the addition of percutaneous transluminal angioplasty and stenting to medical therapy, compared with medical therapy alone, resulted in no significant difference in the risk of stroke or death within 30 days or stroke in the qualifying artery territory beyond 30 days through 1 year. The find...

Glioblastoma multiforme (GBM) is the most malignant brain tumor in humans. Previous studies have demonstrated that microRNA plays important roles in the development and proliferation of GBM cells. Here we defined the mechanism by which miR-212-3p regulated the proliferation of GBM. In this study, we showed that miR-212-3p expression was significantly down-regulated and negatively correlated with serum and glucocorticoid-inducible kinase 3 (SGK3) in GBM. Either over-expression of miR-212-3p or silence of SGK3 decreased viability of GBM cells. Moreover, miR-212-3p directly bound to 3'UTR of SGK3 and inhibited its mRNA and protein expression. And over-expression of SGK3 rescued the decreased proliferation of GBM cells induced by miR-212-3p. Importantly, miR-212-3p also suppressed tumor growth in vivo. Collectively, our results demonstrated that miR-212-3p inhibited proliferation of GBM cells by directly targeting SGK3, and could potentially serve as a new therapeutic target for GBM.

Mdivi-1 is a selective inhibitor of mitochondrial fission protein, Drp1, and can penetrate the blood-brain barrier. Previous studies have shown that Mdivi-1 improves neurological outcomes after ischemia, seizures and trauma but it remains unclear whether Mdivi-1 can attenuate early brain injury after subarachnoid hemorrhage (SAH). We thus investigated the therapeutic effect of Mdivi-1 on early brain injury following SAH. Rats were randomly divided into four groups: sham; SAH; SAH + vehicle; and SAH + Mdivi-1. The SAH model was induced by standard intravascular perforation and all of the rats were subsequently sacrificed 24 h after SAH. Mdivi-1 (1.2 mg/kg) was administered to rats 30 min after SAH. We found that Mdivi-1 markedly improved neurologic deficits, alleviated brain edema and BBB permeability, and attenuated apoptotic cell death. Mdivi-1 also significantly reduced the expression of cleaved caspase-3, Drp1 and p-Drp1, attenuated the release of Cytochrome C from mitochondria, inhibited excessive mitochondrial fission, and restored the ultra-structure of mitochondria. Furthermore, Mdivi-1 reduced levels of MDA, 3-NT, and 8-OHdG, and improved SOD activity. Taken together, our data suggest that Mdivi-1 exerts neuroprotective effects against cell death induced by SAH and the underlying mechanism may be inhibition of Drp1-activated mitochondrial fission and oxidative stress.

Background Diffusion‐weighted imaging (DWI) in MRI plays an increasingly important role in diagnostic applications and developing imaging biomarkers. Automated whole‐breast segmentation is an important yet challenging step for quantitative breast imaging analysis. While methods have been developed on dynamic contrast‐enhanced (DCE) MRI, automatic whole‐breast segmentation in breast DWI MRI is still underdeveloped. Purpose To develop a deep/transfer learning‐based segmentation approach for DWI MRI scans and conduct an extensive study assessment on four imaging datasets from both internal and external sources. Study Type Retrospective. Subjects In all, 98 patients (144 MRI scans; 11,035 slices) of four different breast MRI datasets from two different institutions. Field Strength/Sequences 1.5T scanners with DCE sequence (Dataset 1 and Dataset 2) and DWI sequence. A 3.0T scanner with one external DWI sequence. Assessment Deep learning models (UNet and SegNet) and transfer learning were used as segmentation approaches. The main DCE Dataset (4,251 2D slices from 39 patients) was used for pre‐training and internal validation, and an unseen DCE Dataset (431 2D slices from 20 patients) was used as an independent test dataset for evaluating the pre‐trained DCE models. The main DWI Dataset (6,343 2D slices from 75 MRI scans of 29 patients) was used for transfer learning and internal validation, and an unseen DWI Dataset (10 2D slices from 10 patients) was used for independent evaluation to the fine‐tuned models for DWI segmentation. Manual segmentations by three radiologists (>10‐year experience) were used to establish the ground truth for assessment. The segmentation performance was measured using the Dice Coefficient (DC) for the agreement between manual expert radiologist's segmentation and algorithm‐generated segmentation. Statistical Tests The mean value and standard deviation of the DCs were calculated to compare segmentation results from different deep learning models. Results For the segmentation on the DCE MRI, the average DC of the UNet was 0.92 (cross‐validation on the main DCE dataset) and 0.87 (external evaluation on the unseen DCE dataset), both higher than the performance of the SegNet. When segmenting the DWI images by the fine‐tuned models, the average DC of the UNet was 0.85 (cross‐validation on the main DWI dataset) and 0.72 (external evaluation on the unseen DWI dataset), both outperforming the SegNet on the same datasets. Data Conclusion The internal and independent tests show that the deep/transfer learning models can achieve promising segmentation effects validated on DWI data from different institutions and scanner types. Our proposed approach may provide an automated toolkit to help computer‐aided quantitative analyses of breast DWI images. Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:635–643.

This qualitative study assessed the feasibility and comparability of findings from face-to-face versus on-line chat focus groups including 12 individuals affected by colon cancer. Discussion questions focused on issues of lifestyle (nutrition and exercise), cancer screening, and treatment. Despite demographic differences, the themes that emerged from the two types of groups were similar. On-line participants generally talked more about cancer treatment and advocacy issues and used support groups more frequently. The anonymity of on-line chat groups appeared to provide a more comfortable forum for some people to discuss sensitive personal health issues. As both methods provided similar results, researchers may wish to consider circumstances in which using chat-based focus groups may provide a feasible alternative to traditional face-to-face groups.

Hyponatremia does not predict poor outcome in all-grade aSAH patients. However, late-onset hyponatremia in high-grade aSAH patients is associated with cerebral infarction. Therefore, the appropriate management of hyponatremia could be beneficial in those patients.

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