A Real-Time Effectiveness Evaluation Method for Remote Sensing Satellite Clusters on Moving Targets.

Recently, remote sensing satellites have become increasingly important in the Earth observation field as their temporal, spatial, and spectral resolutions have improved. Subsequently, the quantitative evaluation of remote sensing satellites has received considerable attention. The quantitative evaluation method is conventionally based on simulation, but it has a speed-accuracy trade-off. In this paper, a real-time evaluation model architecture for remote sensing satellite clusters is proposed. Firstly, a multi-physical field coupling simulation model of the satellite cluster to observe moving targets is established. Aside from considering the repercussions of on-board resource constraints, it also considers the consequences of the imaging's uncertainty effects on observation results. Secondly, a moving target observation indicator system is developed, which reflects the satellite cluster's actual effectiveness in orbit. Meanwhile, an indicator screening method using correlation analysis is proposed to improve the independence of the indicator system. Thirdly, a neural network is designed and trained for stakeholders to realize a rapid evaluation. Different network structures and parameters are comprehensively studied to determine the optimized neural network model. Finally, based on the experiments carried out, the proposed neural network evaluation model can generate real-time, high-quality evaluation results. Hence, the validity of our proposed approach is substantiated.

Tissue characterization at an enhanced resolution across spatial omics platforms with deep generative model.

Recent advances in spatial omics have expanded the spectrum of profiled molecular categories beyond transcriptomics. However, many of these technologies are constrained by limited spatial resolution, hindering our ability to deeply characterize intricate tissue architectures. Existing computational methods primarily focus on the resolution enhancement of transcriptomics data, lacking the adaptability to address the emerging spatial omics technologies that profile various omics types. Here, we introduce soScope, a unified generative framework designed to enhance data quality and spatial resolution for molecular profiles obtained from diverse spatial technologies. soScope aggregates multimodal tissue information from omics, spatial relations and images, and jointly infers omics profiles at enhanced resolutions with omics-specific modeling through distribution priors. With comprehensive evaluations on diverse spatial omics platforms, including Visium, Xenium, spatial-CUT&Tag, and slide-DNA/RNA-seq, soScope improves performances in identifying biologically meaningful intestine and kidney architectures, revealing embryonic heart structure that cannot be resolved at the original resolution and correcting sample and technical biases arising from sequencing and sample processing. Furthermore, soScope extends to spatial multiomics technology spatial-CITE-seq and spatial ATAC-RNA-seq, leveraging cross-omics reference for simultaneous multiomics enhancement. soScope provides a versatile tool to improve the utilization of continually expanding spatial omics technologies and resources.

Mutation of miR-21 targets endogenous lipoprotein receptor-related protein 6 and nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is a chronic disorder characterized by hepatic fat accumulation and abnormal lipid metabolism. Although miR-21 has been implicated in nonalcoholic fatty liver disease, it is unknown whether miR-21 could function as a therapeutic target. Here, we perform transfection analysis of miR-21 mimic or control mimic to evaluate the effects of miR-21 expression levels on human HepG2 nonalcoholic fatty liver cells. We used siRNA techniques to knock down miR-21 in HepG2 and control 293T cell lines, and then monitored lipid production and the expression levels of genes involved in lipid metabolism. The effects of miR-21 expression levels on LDL receptor-related protein 6 (LRP6) expression were evaluated using qRT-PCR and western blot analyses. Luciferase reporter assays were conducted to confirm the effects of miR-21 expression levels on LRP6. The results indicated that transfection of miR-21 mimic induced changes in the expression levels of lipogenic enzymes, including acetyl-CoA carboxylase 1 (ACC1), stearoyl CoA desaturase (1SCD1), sterol regulatory element-binding protein 1 (SREBP1), and liver X receptor alpha (LXRα). Transfection of miR-21 mimic suppressed the transcription and translation of LRP6 at the mRNA and protein levels, whereas miR-21 knockdown increased the expression levels of LRP6. Transfection of miR-21 mimic in HepG2 cells also induced lipid production and triggered the expression of critical lipid metabolic enzymes. These data suggest that mutation of miR-21 may be a new therapeutic strategy to treat nonalcoholic fatty liver diseases by targeting endogenous LRP6.

Association of Adiponectin gene polymorphisms and nonalcoholic fatty liver disease.

OBJECTIVE: To investigate the correlation between Adiponectin gene polymorphisms and the genetic susceptibility of nonalcoholic fatty liver disease (NAFLD). METHODS: 357 NAFLD patients from January 2005 to December 2013 and 357 cases of healthy controls among the Han population were collected; polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was used to detect three tagSNPs (Rs2241767, rsl501299 and rs3774261) of Adiponectin. Risk factors were analyzed by multivariate logistic regression and haplotype analysis was performed using SHEsis software. RESULTS: Rs2241767, rsl501299 and rs3774261 polymorphisms were associated with the risk of NAFLD. Haplotype analysis showed that, A-T-A haplotype was a protective factor of NAFLD (OR: 0.154, 95% CI: 0.011-0.576, P = 0.004) and G-G-A (OR: 4.012, 95% CI: 2.118-10.324, P < 0.001) and G-T-G (OR: 5.219, 95% CI: 2.751-12.651, P < 0.001) haplotype was risk factors of NAFLD. CONCLUSION: There was an association between Adiponectin gene polymorphisms and the genetic susceptibility of NAFLD.