Medical image segmentation methods are generally designed as fully-supervised to guarantee model performance, which requires a significant amount of expert annotated samples that are high-cost and laborious. Semi-supervised image segmentation can alleviate the problem by utilizing a large number of unlabeled images along with limited labeled images. However, learning a robust representation from numerous unlabeled images remains challenging due to potential noise in pseudo labels and insufficient class separability in feature space, which undermines the performance of current semi-supervised segmentation approaches. To address the issues above, we propose a novel semi-supervised segmentation method named as Rectified Contrastive Pseudo Supervision (RCPS), which combines a rectified pseudo supervision and voxel-level contrastive learning to improve the effectiveness of semi-supervised segmentation. Particularly, we design a novel rectification strategy for the pseudo supervision method based on uncertainty estimation and consistency regularization to reduce the noise influence in pseudo labels. Furthermore, we introduce a bidirectional voxel contrastive loss in the network to ensure intra-class consistency and inter-class contrast in feature space, which increases class separability in the segmentation. The proposed RCPS segmentation method has been validated on two public datasets and an in-house clinical dataset. Experimental results reveal that the proposed method yields better segmentation performance compared with the state-of-the-art methods in semi-supervised medical image segmentation. The source code is available at https://github.com/hsiangyuzhao/RCPS .

Background: Autophagy is considered to be another restorative focus for the treatment of brain tumors. Although several research have demonstrated that melatonin induces autophagy in colon cancer and hepatoma cells, there has not been any direct evidence of whether melatonin is capable of inducing autophagy in human glioma cells. Results: In the present research, we report that melatonin or its agonist, agomelatine, induced autophagy in A172 and U87-MG glioblastoma cells for a concentration-and time-dependent way, which was significantly attenuated by treatment with luzindole, a melatonin receptor antagonist. Furthermore, by suppressing autophagy at the late-stage with bafilomycin A1 and early stage with 3-MA, we found that the melatonin-induced autophagy was activated early, and the autophagic flux was complete. Melatonin treatment alone did not induce any apoptotic changes in the glioblastoma cells, as measured by flow cytometry. Western blot studies confirmed that melatonin alone prominently upregulated the levels of Beclin 1 and LC3 II, which was accompanied by an increase in the expression of Bcl-2, whereas it had no effect on the expression of Bax in the glioblastoma cells. Remarkably, co-treatment with 3-MA and melatonin significantly enhanced the apoptotic cell population in the glioblastoma cells, along with a prominent decrease in the expression of bcl-2 and increase in the Bax expression levels, which collectively indicated that the disruption of autophagy triggers the melatonin-induced apoptosis in glioblastoma cells. Conclusions: These results provide information indicating that melatonin may act as a common upstream signal between autophagy and apoptosis, which may lead to the development of new therapeutic strategies for glioma.

Summary: Aims: Recent evidence indicates that the increased expression of calpain small subunit 1 (Capn4) is associated with tumorigenesis. This study was designed to explore the role which Capn4 plays in human glioma.Methods: We detected the expression of Capn4 by immunohistochemistry in tissue microarrays and tissue samples. Following the down‐regulation of Capn4 in glioma cell lines by a specific short hairpin RNA, the function of Capn4 in invasion, migration, and proliferation was assessed. We then evaluated the prognostic role of Capn4 using univariate and multivariate analysis in 94 glioblastoma (GBM) patients.Results: Glioma tissues exhibited notably higher expression of Capn4 compared with control brain tissues and was positively correlated with histological malignancy. The down‐regulation of Capn4 in glioma cells led to a decrease in invasion and migration in vitro. Through univariate analysis, the prognosis of GBM patients with Capn4 overexpression was significantly poorer with respect to progression‐free survival (PFS) and overall survival (OS). Based on the results of the multivariate analysis, Capn4^high was demonstrated to be a negative independent prognostic indicator for PFS and OS in GBM patients.Conclusion: The overexpression of Capn4 is a novel negative prognostic marker, and Capn4 may be used as a new target in therapeutic strategies for human glioma.

As a widely known plant hormone, Abscisic acid plays an important role in the progress of planting cell and their stress response. Recently, we reported that ABA might play an anti-cancer role in glioma tissues. In the present study, the molecular mechanism of ABA anti-cancer was further explored in glioblastoma cells. By measuring LC3 puncta formation and conversion in glioblastoma cells, inhibiting the autophagic pathway, targeting the essential autophagic modulator beclin 1 with RNA interference, and analysing cellular morphology via transmission electron microscopy, we found that ABA-treated glioblastoma cells exhibited the features of autophagy. Specifically, ABA-induced autophagy in glioblastoma cells was mediated by the MAPK/JNK signalling pathway rather than the PI3K/AKT/mTOR axis. Moreover, the inhibition or knockdown of JNK specifically blocked ABA-induced autophagic cell death. ABA-induced autophagy was further confirmed in tumour-bearing mice and was accompanied by the inhibition of glioma growth in vivo. This report is the first to describe autophagy induced by ABA and mediated by the MAPK/JNK pathway in human cancer cells and tumour-bearing mice. These results may shed some light in new therapeutic strategies of glioma.

Mutations in leucine-rich repeat kinase 2 (LRRK2) are recognized as the most frequent cause of Parkinson’s disease (PD). As a multidomain ROCO protein, LRRK2 is characterized by the presence of both a Ras-of-complex (ROC) GTPase domain and a kinase domain connected through the C-terminal of an ROC domain (COR). The bienzymatic ROC–COR–kinase catalytic triad indicated the potential role of GTPase domain in regulating kinase activity. However, as a functional GTPase, the detailed intrinsic regulation of the ROC activation cycle remains poorly understood. Here, combining extensive molecular dynamics simulations and Markov state models, we disclosed the dynamic structural rearrangement of ROC’s homodimer during nucleotide turnover. Our study revealed the coupling between dimerization extent and nucleotide-binding state, indicating a nucleotide-dependent dimerization-based activation scheme adopted by ROC GTPase. Furthermore, inspired by the well-known R1441C/G/H PD-relevant mutations within the ROC domain, we illuminated the potential allosteric molecular mechanism for its pathogenetic effects through enabling faster interconversion between inactive and active states, thus trapping ROC in a prolonged activated state, while the implicated allostery could provide further guidance for identification of regulatory allosteric pockets on the ROC complex. Our investigations illuminated the thermodynamics and kinetics of ROC homodimer during nucleotide-dependent activation for the first time and provided guidance for further exploiting ROC as therapeutic targets for controlling LRRK2 functionality in PD treatment.