Naive and primed pluripotency is characterized by distinct signaling requirements, transcriptomes, and developmental properties, but both cellular states share key transcriptional regulators: Oct4, ...Sox2, and Nanog. Here, we demonstrate that transition between these two pluripotent states is associated with widespread Oct4 relocalization, mirrored by global rearrangement of enhancer chromatin landscapes. Our genomic and biochemical analyses identified candidate mediators of primed state-specific Oct4 binding, including Otx2 and Zic2/3. Even when differentiation cues are blocked, premature Otx2 overexpression is sufficient to exit the naive state, induce transcription of a substantial subset of primed pluripotency-associated genes, and redirect Oct4 to previously inaccessible enhancer sites. However, the ability of Otx2 to engage new enhancer regions is determined by its levels, cis-encoded properties of the sites, and the signaling environment. Our results illuminate regulatory mechanisms underlying pluripotency and suggest that the capacity of transcription factors such as Otx2 and Oct4 to pioneer new enhancer sites is highly context dependent.
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•Oct4 binding and enhancer patterns change in naive to primed pluripotency transition•Oct4 cooperates with distinct set of transcription factors in naive and primed state•Ectopic Otx2 can reorganize Oct4 binding even in the absence of differentiation cues•Otx2 and Oct4 ability to engage new enhancers is dependent on cis-regulatory features
During transition from naive to primed pluripotency, Buecker et al. show that Oct4 binding as well as enhancer patterns are globally reorganized. Collaborating transcription factors such as Otx2 and Zic2/3 mediate changes of Oct4 binding.
Due to rapid losses of mangrove forests caused by anthropogenic disturbances and climate change, accurate and contemporary maps of mangrove forests are needed to understand how mangrove ecosystems ...are changing and establish plans for sustainable management. In this study, a new classification algorithm was developed using the biophysical characteristics of mangrove forests in China. More specifically, these forests were mapped by identifying: (1) greenness, canopy coverage, and tidal inundation from time series Landsat data, and (2) elevation, slope, and intersection-with-sea criterion. The annual mean Normalized Difference Vegetation Index (NDVI) was found to be a key variable in determining the classification thresholds of greenness, canopy coverage, and tidal inundation of mangrove forests, which are greatly affected by tide dynamics. In addition, the integration of Sentinel-1A VH band and modified Normalized Difference Water Index (mNDWI) shows great potential in identifying yearlong tidal and fresh water bodies, which is related to mangrove forests. This algorithm was developed using 6 typical Regions of Interest (ROIs) as algorithm training and was run on the Google Earth Engine (GEE) cloud computing platform to process 1941 Landsat images (25 Path/Row) and 586 Sentinel-1A images circa 2015. The resultant mangrove forest map of China at 30m spatial resolution has an overall/users/producer’s accuracy greater than 95% when validated with ground reference data. In 2015, China’s mangrove forests had a total area of 20,303ha, about 92% of which was in the Guangxi Zhuang Autonomous Region, Guangdong, and Hainan Provinces. This study has demonstrated the potential of using the GEE platform, time series Landsat and Sentine-1A SAR images to identify and map mangrove forests along the coastal zones. The resultant mangrove forest maps are likely to be useful for the sustainable management and ecological assessments of mangrove forests in China.
Constructal optimization of a plate condenser with fixed heat transfer rate and effective volume in ocean thermal energy conversion (OTEC) system is performed based on constructal theory. ...Optimizations of entropy generation rate ( S ˙ g ) in heat transfer process and total pumping power ( P sum ) due to friction loss are two conflicting objectives for a plate condenser. With the conventional optimization method, the plate condenser is designed by taking a composite function (CF) considering both S ˙ g and P sum as optimization objectives, and employing effective length, width, and effective number of heat transfer plates as design variables. Effects of structural parameters of the plate condenser and weighting coefficient of CF on design results are investigated. With a multi-objective genetic algorithm, the plate condenser is designed by simultaneously optimizing S ˙ g and P sum , and the Pareto optimal set is obtained. The results demonstrate that CFs after primary and twice-constructal optimizations are respectively reduced by 7.8% and 9.9% compared with the initial CF, and the effective volume of the plate condenser has a positive impact on the twice minimum CF. Furthermore, the Pareto optimal set can provide better selections for performance optimizations of plate condensers.
Image classification is a fundamental task in remote sensing image processing. In recent years, deep convolutional neural networks (DCNNs) have experienced significant breakthroughs in natural image ...recognition. The remote sensing field, however, is still lacking a large-scale benchmark similar to ImageNet. In this paper, we propose a remote sensing image classification benchmark (RSI-CB) based on massive, scalable, and diverse crowdsourced data. Using crowdsourced data, such as Open Street Map (OSM) data, ground objects in remote sensing images can be annotated effectively using points of interest, vector data from OSM, or other crowdsourced data. These annotated images can, then, be used in remote sensing image classification tasks. Based on this method, we construct a worldwide large-scale benchmark for remote sensing image classification. This benchmark has large-scale geographical distribution and large total image number. It contains six categories with 35 sub-classes of more than 24,000 images of size 256 × 256 pixels. This classification system of ground objects is defined according to the national standard of land-use classification in China and is inspired by the hierarchy mechanism of ImageNet. Finally, we conduct numerous experiments to compare RSI-CB with the SAT-4, SAT-6, and UC-Merced data sets. The experiments show that RSI-CB is more suitable as a benchmark for remote sensing image classification tasks than other benchmarks in the big data era and has many potential applications.
The decrease in strength of potential slip surface after an earthquake and heavy rainfall, is one of the main causes of rock failures. However, fundamental natural frequency can demonstrate the ...changes in physical and mechanical parameters and support a real-time quantitative assessment of the safety of rocks. This study applied Laser Doppler Vibrometry in an experiment called Frozen-Thawing Test (FTT) in which the entire collapse process caused by strength degradation is simulated. The results show that the safety factor calculated by fundamental natural frequency can give us a new method for stability assessment of unstable rocks. Therefore, the method can satisfy real-time safety evaluation of unstable rocks and will offer a foundation for better responses to rock collapse.
Genomic studies of lung adenocarcinoma (LUAD) have advanced our understanding of the disease’s biology and accelerated targeted therapy. However, the proteomic characteristics of LUAD remain poorly ...understood. We carried out a comprehensive proteomics analysis of 103 cases of LUAD in Chinese patients. Integrative analysis of proteome, phosphoproteome, transcriptome, and whole-exome sequencing data revealed cancer-associated characteristics, such as tumor-associated protein variants, distinct proteomics features, and clinical outcomes in patients at an early stage or with EGFR and TP53 mutations. Proteome-based stratification of LUAD revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Further, we nominated potential drug targets and validated the plasma protein level of HSP 90β as a potential prognostic biomarker for LUAD in an independent cohort. Our integrative proteomics analysis enables a more comprehensive understanding of the molecular landscape of LUAD and offers an opportunity for more precise diagnosis and treatment.
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•Discovery of prognosis-associated proteins and pathways at early stage of LUAD•Proteomics revealed three subtypes related to clinical and molecular features•Identification of subtype-specific kinases and cancer-associated phosphoproteins•Identification of potential prognostic biomarkers and drug targets in LUAD
Integrative proteomic characterization of lung adenocarcinoma in 103 Chinese patients identifies three subtypes related to clinical and molecular features and nominates potential prognostic biomarkers and drug targets.
Cardiovascular disease is a major cause of death worldwide. Inflammasome infiltration has been identified to play a central role in the pathological progression of certain cardiovascular diseases, ...such as vascular damage spanning atherosclerosis, aneurysm, or arteritis; ischemic heart disease; and other nonischemic heart diseases including diabetic cardiomyopathy, chronic heart failure, and hypertension- or virus-induced cardiac dysfunction. The NLRP3 inflammasome, a key participant in the innate immune response, requires both priming and activation signals for the initiation of inflammation. Piling evidence has revealed that the NLRP3 inflammasome could exert an inflammatory effect by inducing the secretion of proinflammatory cytokines (i.e., IL-1β, IL-18) or could cause pyroptosis, a novel programmed cell death process, in a caspase-1-dependent manner. The importance of the NLRP3 inflammasome in cardiac disease has been broadly investigated. In this review, we present the current knowledge regarding the function of NLRP in vascular disease, ischemic heart disease, and nonischemic heart disease and discuss the potential therapeutic options targeting the NLRP3 inflammasome.
A marine condenser with exhausted steam as the working fluid is researched in this paper. Constructal designs of the condenser are numerically conducted based on single and multi-objective ...optimizations, respectively. In the single objective optimization, there is an optimal dimensionless tube diameter leading to the minimum total pumping power required by the condenser. After constructal optimization, the total pumping power is decreased by 42.3%. In addition, with the increase in mass flow rate of the steam and heat transfer area and the decrease in total heat transfer rate, the minimum total pumping power required by the condenser decreases. In the multi-objective optimization, the Pareto optimal set of the entropy generation rate and total pumping power is gained. The optimal results gained by three decision methods in the Pareto optimal set and single objective optimizations are compared by the deviation index. The optimal construct gained by the TOPSIS decision method corresponding to the smallest deviation index is recommended in the optimal design of the condenser. These research ideas can also be used to design other heat transfer devices.
Kalina cycle and organic Rankine cycle have different optimal heat source temperatures. To realize cascade utilization of low-temperature waste heat, a model of novel Kalina-organic Rankine combined ...cycle is established by using a dual-pressure Kalina cycle as top cycle and a dual-pressure organic Rankine cycle as bottom cycle, and constructal thermodynamic optimization is carried out by uniting constructal theory and finite-time thermodynamics. With the total turbine volume and total heat exchanger area being fixed, the optimal tube external diameters of the evaporators in the dual-pressure Kalina cycle and dual-pressure organic Rankine cycle are obtained by maximizing the net power output of the Kalina-organic Rankine combined cycle system. The results prove that the net power outputs of the Kalina-organic Rankine combined cycle system after four progressive optimizations are increased by 2.62%, 5.41%, 15.05% and 16.17%, respectively, compared to the initial one. In the quartic constructal thermodynamic optimization, the optimal tube external diameters of the high- and low-temperature evaporators in the DPKC are 0.024m and 0.023m, respectively, and the those in the DPORC are 0.020m and 0.024m, respectively. The results obtained will improve the performance of the KORCC and promote the efficient utilization of waste heat.
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•A model of novel Kalina-organic Rankine combined cycle is established.•Dual-pressure Kalina cycle is top cycle and dual-pressure ORC is bottom cycle.•Combination of constructal theory with finite time thermodynamics is applied.•Power is optimization objective and is improved by 16.17% after optimization.•Power is improved significantly comparing combined cycle with two separate cycles.
The NCI-60 cell line collection is a very widely used panel for the study of cellular mechanisms of cancer in general and in vitro drug action in particular. It is a model system for the tissue types ...and genetic diversity of human cancers and has been extensively molecularly characterized. Here, we present a quantitative proteome and kinome profile of the NCI-60 panel covering, in total, 10,350 proteins (including 375 protein kinases) and including a core cancer proteome of 5,578 proteins that were consistently quantified across all tissue types. Bioinformatic analysis revealed strong cell line clusters according to tissue type and disclosed hundreds of differentially regulated proteins representing potential biomarkers for numerous tumor properties. Integration with public transcriptome data showed considerable similarity between mRNA and protein expression. Modeling of proteome and drug-response profiles for 108 FDA-approved drugs identified known and potential protein markers for drug sensitivity and resistance. To enable community access to this unique resource, we incorporated it into a public database for comparative and integrative analysis (http://wzw.tum.de/proteomics/nci60).
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•Broad survey of protein and kinase expression in the NCI-60 cell line panel•Proteomic analysis clusters cell lines according to tumor type•The correlation between proteomic and transcriptomic data is examined•Proteomics is particularly powerful for identifying drug-resistance mechanisms
Kuster, Gholami, and colleagues present a global survey of protein and kinase expression in the NCI-60 panel. Their bioinformatics analysis reveals strong cell line clustering according to tumor type. Integrative analysis discloses a high degree of correlation between the transcriptome and proteome and shows that each technique provides complementary information. In particular, proteomics appears to be powerful for identifying drug-resistance mechanisms. These data are available to the community for broad utilization in biological research.
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