Permafrost Stability Mapping on the Tibetan Plateau by Integrating Time-Series InSAR and the Random Forest Method

The ground deformation rate is an important index for evaluating the stability and degradation of permafrost. Due to limited accessibility, in-situ measurement of the ground deformation of permafrost areas on the Tibetan Plateau is a challenge. Thus, the technique of time-series interferometric synthetic aperture radar (InSAR) is often adopted for measuring the ground deformation rate of the permafrost area, the effectiveness of which is, however, degraded in areas with geometric distortions in synthetic aperture radar (SAR) images. In this study, a method that integrates InSAR and the random forest method is proposed for an improved permafrost stability mapping on the Tibetan Plateau; to demonstrate the application of the proposed method, the permafrost stability mapping in a small area located in the central region of the Tibetan Plateau is studied. First, the ground deformation rate in the concerned area is studied with InSAR, in which 67 Sentinel-1 scenes taken in the period from 2014 to 2020 are collected and analyzed. Second, the relationship between the environmental factors (i.e., topography, land cover, land surface temperature, and distance to road) and the permafrost stability is mapped with the random forest method based on the high-quality data extracted from the initial InSAR analysis. Third, the permafrost stability in the whole study area is mapped with the trained random forest model, and the issue of data scarcity in areas where the terrain visibility of SAR images is poor or InSAR results are not available in permafrost stability mapping can be overcome. Comparative analyses demonstrate that the integration of the InSAR and the random forest method yields a more effective permafrost stability mapping compared with the sole application of InSAR analysis

An Improved R-Index Model for Terrain Visibility Analysis for Landslide Monitoring with InSAR

The interferometric synthetic aperture radar (InSAR) technique is widely adopted for detecting and monitoring landslides, but its effectiveness is often degraded in mountainous terrains, due to geometric distortions in the synthetic aperture radar (SAR) image input. To evaluate the terrain effect on the applicability of InSAR in landslide monitoring, a variety of visibility evaluation models have been developed, among which the R-index models are quite popular. In consideration of the poor performance of the existing R-index models in the passive layover region, this study presents an improved R-index model, in which a coefficient for improving the visibility evaluation in the far passive layover regions is incorporated. To demonstrate the applicability of the improved R-index model, the terrain visibility of SAR images in Fengjie, a county in the Three Gorges Reservoirs region, China, is studied. The effectiveness of the improved R-index model is demonstrated through comparing the visibility evaluation results with those obtained from the existing R-index models and P-NG method. Further, the effects of the line-of-sight (LOS) parameters of SAR images and the resolution of the digital elevation model (DEM) on the terrain visibility are discussed

Combined Transcriptome and Metabolome Analysis Reveals Adaptive Defense Responses to DON Induction in Potato

Phytophthora infestans poses a serious threat to potato production, storage, and processing. Understanding plant immunity triggered by fungal elicitors is important for the effective control of plant diseases. However, the role of the potato stress response to Fusarium toxin deoxynivalenol (DON)-induced stress is still not fully understood. In this study, the metabolites of DON-treated potato tubers were studied for four time intervals using UPLC-MS/MS. We identified 676 metabolites, and differential accumulation metabolite analysis showed that alkaloids, phenolic acids, and flavonoids were the major differential metabolites that directly determined defense response. Transcriptome data showed that differentially expressed genes (DEGs) were significantly enriched in phenylpropane and flavonoid metabolic pathways. Weighted gene co-expression network analysis (WGCNA) identified many hub genes, some of which modulate plant immune responses. This study is important for understanding the metabolic changes, transcriptional regulation, and physiological responses of active and signaling substances during DON induction, and it will help to design defense strategies against Phytophthora infestans in potato

Prototheca spp. induce an inflammatory response via mtROS-mediated activation of NF-κB and NLRP3 inflammasome pathways in bovine mammary epithelial cell cultures

Abstract Emergence of bovine mastitis caused by Prototheca algae is the impetus to better understand these infections. Both P. bovis and P. ciferrii belong to Prototheca algae, but they differ in their pathogenicity to induce inflammatory responses. The objective was to characterize and compare pathogenesis of inflammatory responses in bMECs induced by P. bovis versus P. ciferrii. Mitochondrial ultrastructure, activity and mtROS in bMECs were assessed with transmission electron microscopy and laser scanning confocal microscopy. Cytokines, including TNF-α, IL-1β and IL-18, were measured by ELISA and real-time PCR, whereas expressions of various proteins in the NF-κB and NLRP3 inflammasome pathways were detected with immunofluorescence or Western blot. Infection with P. bovis or P. ciferrii damaged mitochondria, including dissolution and vacuolation of cristae, and decreased mitochondrial activity, with P. bovis being more pathogenic and causing greater destruction. There were increases in NADPH production and mtROS accumulation in infected bMECs, with P. bovis causing greater increases and also inducing higher cytokine concentrations. Expressions of NF-κB-p65, p-NF-κB-p65, IκBα and p-IκBα proteins in the NF-κB pathway, as well as NLRP3, Pro Caspase1, Caspase1 p20, ASC, Pro IL-1β, and IL-1β proteins in the NLRP3 inflammasome pathway, were significantly higher in P. bovis-infected bMECs. However, mito-TEMPO significantly inhibited production of cytokines and decreased expression of proteins in NF-κB and NLRP3 inflammasome pathways in bMECs infected with either P. bovis or P. ciferrii. In conclusion, P. bovis or P. ciferrii infections induced inflammatory responses in bMECs, with increased mtROS in damaged mitochondria and activated NF-κB and NLRP3 inflammasome pathways, with P. bovis causing a more severe reaction

Buried interface molecular hybrid for inverted perovskite solar cells

Perovskite solar cells (PSCs) with an "inverted" architecture are a key pathway for commercializing this emerging photovoltaic technology due to the better power conversion efficiency (PCE) and operational stability as compared to the "normal" device structure. Specifically, PCEs of the inverted PSCs have exceeded 25% owing to the development of improved self-assembled molecules (SAMs)1-5 and passivation strategies6-8. Nevertheless, poor wettability and agglomerations of SAMs9-12 will cause interfacial losses, impeding further improvement in PCE and stability. Herein, we report on molecular hybrid at the buried interface in inverted PSCs by co-assembling a multiple carboxylic acid functionalized aromatic compound of 4,4',4''-nitrilotribenzoicacid (NA) with a popular SAM of [4-(3,6-dime-thyl-9H-carbazol-9-yl)butyl]phosphonic acid (Me-4PACz) to improve the heterojunction interface. The molecular hybrid of Me-4PACz with NA could substantially improve the interfacial characteristics. The resulting inverted PSCs demonstrated a record-certified steady-state efficiency of 26.54%. Crucially, this strategy aligns seamlessly with large-scale manufacturing, achieving the highest certified PCE for inverted mini-modules at 22.74% (aperture area: 11.1 cm2). Our device also maintained 96.1% of its initial PCE after more than 2,400 hours of 1-sun operation in ambient air