Generated Image Editing Method Based on Global-Local Jacobi Disentanglement for Machine Learning.

Accurate semantic editing of the generated images is extremely important for machine learning and sample enhancement of big data. Aiming at the problem of semantic entanglement in generated image latent space of the StyleGAN2 network, we proposed a generated image editing method based on global-local Jacobi disentanglement. In terms of global disentanglement, we extract the weight matrix of the style layer in the pre-trained StyleGAN2 network; obtain the semantic attribute direction vector by using the weight matrix eigen decomposition method; finally, utilize this direction vector as the initialization vector for the Jacobi orthogonal regularization search algorithm. Our method improves the speed of the Jacobi orthogonal regularization search algorithm with the proportion of effective semantic attribute editing directions. In terms of local disentanglement, we design a local contrast regularized loss function to relax the semantic association local area and non-local area and utilize the Jacobi orthogonal regularization search algorithm to obtain a more accurate semantic attribute editing direction based on the local area prior MASK. The experimental results show that the proposed method achieves SOTA in semantic attribute disentangled metrics and can discover more accurate editing directions compared with the mainstream unsupervised generated image editing methods.

Rab3a attenuates spinal cord injury by mediating vesicle release.

BACKGROUND: Rab3a regulates vesicle secretion and transport. Emerging evidences have shown that extracellular vesicles (EVs) can reach target lesions of injured spinal cords and exert a positive effect on these lesions. However, the molecular mechanism by which Rab3a regulates vesicle secretion to ameliorate spinal cord injury (SCI) is not fully understood. METHODS: An SCI rat model was established which was used to examine the pathological changes and Rab3a expression in spinal cord tissue. Rab3a was overexpressed in the model rats to demonstrate its effect on SCI repair. Rab3a was also knocked down in neuronal cells to verify its role in vesicle secretion and neuronal cells. The binding protein of Rab3a was identified by Co-IP and mass spectrometry. RESULTS: Rab3a was significantly downregulated in SCI rats and Rab3a overexpression promoted SCI repair. Rab3a knockdown inhibited the secretion of neuronal cell-derived EVs. Compared to the EVs from the equal number of control neuronal cells, EVs from Rab3a-knockdown neuronal cells promoted M1 macrophage polarization, which in turn, promoted neuronal cell apoptosis. Mechanistically, STXBP1 was identified as a binding protein of Rab3a, and their interaction promoted the secretion of neuronal cell-derived EVs. Furthermore, METTL2b was significantly downregulated in SCI rats, and METTL2b knockdown significantly reduced Rab3a protein expression. CONCLUSION: These results suggest that Rab3a promotes the secretion of neuronal cell-derived EVs by interacting with its binding protein STXBP1. Neuronal cells-derived EVs inhibited the polarization of M1 macrophages in the spinal cord microenvironment, thereby promoting SCI repair. Our findings provide a theoretical basis for the clinical treatment of SCI.

Analysis and Experimental Validation of Rheumatoid Arthritis Innate Immunity Gene CYFIP2 and Pan-Cancer.

Rheumatoid arthritis (RA) is a chronic, heterogeneous autoimmune disease. Its high disability rate has a serious impact on society and individuals, but there is still a lack of effective and reliable diagnostic markers and therapeutic targets for RA. In this study, we integrated RA patient information from three GEO databases for differential gene expression analysis. Additionally, we also obtained pan-cancer-related genes from the TCGA and GTEx databases. For RA-related differential genes, we performed functional enrichment analysis and constructed a weighted gene co-expression network (WGCNA). Then, we obtained 490 key genes by intersecting the significant module genes selected by WGCNA and the differential genes. After using the RanddomForest, SVM-REF, and LASSO three algorithms to analyze these key genes and take the intersection, based on the four core genes (BTN3A2, CYFIP2, ST8SIA1, and TYMS) that we found, we constructed an RA diagnosis. The nomogram model showed good reliability and validity after evaluation, and the ROC curves of the four genes showed that these four genes played an important role in the pathogenesis of RA. After further gene correlation analysis, immune infiltration analysis, and mouse gene expression validation, we finally selected CYFIP2 as the cut-in gene for pan-cancer analysis. The results of the pan-cancer analysis showed that CYFIP2 was closely related to the prognosis of patients with various tumors, the degree of immune cell infiltration, as well as TMB, MSI, and other indicators, suggesting that this gene may be a potential intervention target for human diseases including RA and tumors.

CLP1 is a Prognosis-Related Biomarker and Correlates With Immune Infiltrates in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic, heterogeneous autoimmune disease with a high disability rate that seriously affects society and individuals. However, there is a lack of effective and reliable diagnostic markers and therapeutic targets. In this study, we identified diagnostic markers of RA based on RNA modification and explored its role as well as degree of immune cell infiltration. We used the gene expression profile data of three synovial tissues (GSE55235, GSE55457, GSE77298) from the Gene Expression Omnibus (GEO) database and the gene of 5 RNA modification genes (including m6A, m1A, m5C, APA, A-1), combined with cluster analysis, identified four RNA modifiers closely related to RA (YTHDC1, LRPPRC, NOP2, and CLP1) and five immune cells namely T cell CD8, CD4 memory resting, T cells regulatory (Tregs) Macrophages M0, and Neutrophils. Based on the LASSO regression algorithm, hub genes and immune cell prediction models were established respectively in RA and a nomogram based on the immune cell model was built. Around 4 key RNA modification regulator genes, miRNA-mRNA, mRNA-TF networks have been established, and GSEA-GO, KEGG-GSEA enrichment analysis has been carried out. Finally, CLP1 was established as an effective RA diagnostic marker, and was highly positively correlated with T cells follicular helper (Tfh) infiltration. On the other hand, highly negatively correlated with the expression of mast cells. In short, CLP1 may play a non-negligible role in the onset and development of RA by altering immune cell infiltration, and it is predicted to represent a novel target for RA clinical diagnosis and therapy.

Adventitious shoot organogenesis from leaf explants of Portulaca pilosa L.

This study established, for the first time, shoot proliferation and plant regeneration protocols via shoot organogenesis from leaf explants of a medical and ornamental plant, Portulaca pilosa L. The optimal proliferation of axillary shoots was 6.2-fold within 30 days on Murashige and Skoog (MS) medium supplemented with 3.0 µM 6-benzyladenine (BA). Shoots could be induced directly from leaf explants, forming an average of 3.8 adventitious shoots per explant, on optimal MS medium supplemented with 1.0 µM thidiazuron (TDZ) and 0.1 µM α-naphthaleneacetic acid (NAA). A higher concentration of TDZ (3.0 µM), alone or in combination with 0.1 µM NAA, induced somatic embryo-like shoot buds and then developed into real shoots. Rooting was easier since roots were induced on all rooting media within one month. Half-strength MS medium free of plant growth regulators was best for rooting. Rooted plantlets were transferred to a sand: perlite (1:1, v/v) substrate, resulting in highest survival (90%). Plantlets showed more robust growth, however, on substrates of yellow mud: perlite (1:1, v/v) or peat soil: vermiculite: perlite (1:1:1, v/v).