N6-methyladenosine demethylase ALKBH5 homologous protein protects against cerebral I/R injury though suppressing SNHG3-mediated neural PANoptosis: Involvement of m6A-related macromolecules in the diseases of nervous system.

In order to address this gap in knowledge, the present study utilized both in vivo and in vitro models to investigate the role of the m6A demethylase ALKBH5 in protecting against cerebral I/R injury by inhibiting PANoptosis (Pytoptosis, Ppoptosis, and Necroptosis) in an m6A-dependent manner. They observed that ALKBH5, the predominant m6A demethylase, was downregulated in these models, while SNHG3 and PANoptosis-related proteins (ZBP1, AIM2, Cappase-3, Caspase-8, cleaved Caspase-1, GSDMD-N, and p-MLKL) were elevated. Additionally, both ALKBH5 overexpression and SNHG3-deficiency were found to ameliorate PANoptosis and injury induced by OGD/reperfusion and OGD/RX in both mice tissues and astrocyte cells. Further experiments demonstrated that ALKBH5 induced m6A-demethylation in SNHG3, leading to its degradation. Low expression of SNHG3, on the other hand, prevented the formation of the SNHG3-ELAVL1-ZBP1/AIM2 complex, which in turn destabilized ZBP1 and AIM2 mRNA, resulting in the downregulation of these PANoptosis-related genes. Ultimately, the rescue experiments provided evidence that ALKBH5 protected against PANoptosis in cerebral I/R injury models through the inhibition of SNHG3.This study sheds light on the intricate molecular mechanisms involved in the pathogenesis of cerebral I/R injury and highlights the potential of m6A-related genes as therapeutic targets in this condition.

METTL3-deficiency Suppresses Neural Apoptosis to Induce Protective Effects in Cerebral I/R Injury via Inhibiting RNA m6A Modifications: A Pre-clinical and Pilot Study.

N6-Methyladenosine (m6A) RNA methylation involves in regulating the initiation, progression and aggravation of cerebral ischemia-reperfusion (I/R) injury, however, the detailed functions and mechanisms by which m6A drives cerebral I/R injury are not fully understood. This study found that methyltransferase-like 3 (METTL3) m6A-dependently regulated cerebral I/R injury trough regulating a novel LncRNA ABHD11-AS1/miR-1301-3p/HIF1AN/HIF-1α axis. Specifically, the middle cerebral artery occlusion (MCAO)/reperfusion mice models and glucose deprivation (OGD)/reoxygenation (RX) astrocyte cell models were respectively established, and we verified that METTL3, ABHD11-AS1 and HIF1AN were upregulated, whereas miR-1301-3p and HIF-1α were downregulated in both MCAO/reperfusion mice tissues and OGD/RX astrocytes. Mechanical experiments confirmed that METTL3 m6A dependently increased stability and expression levels of ABHD11-AS1, and elevated ABHD11-AS1 sponged miR-1301-3p to upregulate HIF1AN, resulting in the downregulation of HIF-1α. Moreover, silencing of METTL3 rescued MCAO/reperfusion and OGD/RX-induced oxidative stress-associated cell apoptosis and cell cycle arrest in both mice brain tissues in vivo and the mouse primary astrocytes in vitro, which were abrogated by overexpressing ABHD11-AS1 and downregulating miR-1301-3p. Taken together, our study firstly reported a novel METTL3/m6A/ ABHD11-AS1/miR-1301-3p/HIF1AN/HIF-1α signaling cascade in regulating the progression of cerebral I/R injury, and future work will focus on investigating whether the above genes can be used as biomarkers for the treatment of cerebral I/R injury by performing clinical studies.

CaricatureShop: Personalized and Photorealistic Caricature Sketching.

In this paper, we propose the first sketching system for interactively personalized and photorealistic face caricaturing. Input an image of a human face, the users can create caricature photos by manipulating its facial feature curves. Our system first performs exaggeration on the recovered 3D face model, which is conducted by assigning the laplacian of each vertex a scaling factor according to the edited sketches. The mapping between 2D sketches and the vertex-wise scaling field is constructed by a novel deep learning architecture. Our approach allows outputting different exaggerations when applying the same sketching on different input figures in term of their different geometric characteristics, which makes the generated results "personalized". With the obtained 3D caricature model, two images are generated, one obtained by applying 2D warping guided by the underlying 3D mesh deformation and the other obtained by re-rendering the deformed 3D textured model. These two images are then seamlessly integrated to produce our final output. Due to the severe stretching of meshes, the rendered texture is of blurry appearances. A deep learning approach is exploited to infer the missing details for enhancing these blurry regions. Moreover, a relighting operation is invented to further improve the photorealism of the result. These further make our results "photorealistic". The qualitative experiment results validated the efficiency of our sketching system.