Tibet’s ancient topography and its role in climatic and biotic evolution remain speculative due to a paucity of quantitative surface-height measurements through time and space, and sparse fossil ...records. However, newly discovered fossils from a present elevation of ∼4,850 m in central Tibet improve substantially our knowledge of the ancient Tibetan environment. The 70 plant fossil taxa so far recovered include the first occurrences of several modern Asian lineages and represent a Middle Eocene (∼47 Mya) humid subtropical ecosystem. The fossils not only record the diverse composition of the ancient Tibetan biota, but also allow us to constrain the Middle Eocene land surface height in central Tibet to ∼1,500 ± 900 m, and quantify the prevailing thermal and hydrological regime. This “Shangri-La”–like ecosystem experienced monsoon seasonality with a mean annual temperature of ∼19 °C, and frosts were rare. It contained few Gondwanan taxa, yet was compositionally similar to contemporaneous floras in both North America and Europe. Our discovery quantifies a key part of Tibetan Paleogene topography and climate, and highlights the importance of Tibet in regard to the origin of modern Asian plant species and the evolution of global biodiversity.
The stacking between nanosheets is an intriguing and inevitable phenomenon in the chemistry of nano-interfaces. Two-dimensional metal-organic framework nanosheets are an emerging type of nanosheets ...with ultrathin and porous features, which have high potential in separation applications. Here, the stacking between single-layer metal-organic framework nanosheets is revealed to show three representative conformations with tilted angles of 8°, 14°, and 30° for Zr-1, 3, 5-(4-carboxylphenyl)-benzene framework as an example. Efficient untwisted stacking strategy by simple heating is proposed. A detailed structural analysis of stacking modes reveals the creation of highly ordered sub-nanometer micropores in the interspacing of untwisted nano-layers, yielding a high-resolution separator for the pair of para-/meta-isomers over the twisted counterparts and commercial HP-5MS and VF-WAXMS columns. This general method is proven by additional nanosheet examples and supported by Grand Canonical Monte Carlo simulation. This finding will provide a synthetic route in the rational design of functionalities in two-dimensional metal-organic framework nanosheet.
In this review, we summarized recent progresses in transition metal oxide based electrode materials for hybrid capacitors. Different synthesis routes and electrochemical performances of electrode ...materials and storage mechanisms of capacitor devices have been presented in details.
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In the past few years, the increasing energy consumption of traditional fossil fuels has posed a huge threat to human health. It is very imperious to develop the sustainable and renewable energy storage and conversion devices with low cost and environment friendly features. Hybrid supercapacitors are emerging as one of the promising energy devices with high power density, fast charge-discharge process and excellent cycle stability. However, morphology and structure of the electrode materials exert serious effect on their electrochemical performances. In this review, we summarized recent progresses in transition metal oxide based electrode materials for supercapacitors. Different synthesis routes and electrochemical performances of electrode materials and storage mechanisms of supercapacitor devices have been presented in details. The future developing trends of supercapacitor based on metal oxide electrode materials are also proposed.
Baicalein, a widely used Chinese herbal medicine, has multiple pharmacological activities. However, the precise mechanisms of the anti-proliferation and anti-metastatic effects of baicalein on ...gallbladder cancer (GBC) remain poorly understood. Therefore, the aim of this study was to assess the anti-proliferation and anti-metastatic effects of baicalein and the related mechanism(s) on GBC. In the present study, we found that treatment with baicalein induced a significant inhibitory effect on proliferation and promoted apoptosis in GBC-SD and SGC996 cells, two widely used gallbladder cancer cell lines. Additionally, treatment with baicalein inhibited the metastasis of GBC cells. Moreover, we demonstrated for the first time that baicalein inhibited GBC cell growth and metastasis via down-regulation of the expression level of Zinc finger protein X-linked (ZFX). In conclusion, our studies suggest that baicalein may be a potential phytochemical flavonoid for therapeutics of GBC and ZFX may serve as a molecular marker or predictive target for GBC.
•The deep features of water-cement ratio, recycled coarse aggregate replacement ratio, recycled fine aggregate replacement ratio, fly ash replacement ratio as well as their combinations are learned ...through neural networks.•The proposed prediction model is developed using the softmax regression.•The simulated results show that the prediction model based on deep learning exhibits the advantages including higher precision, higher efficiency and higher generalization ability compared with the traditional neural network model.
Considering on the current difficulties of predicting the compressive strength of recycled aggregate concrete, this paper proposes a prediction model based on deep learning theory. First, the deep features of water-cement ratio, recycled coarse aggregate replacement ratio, recycled fine aggregate replacement ratio, fly ash replacement ratio as well as their combinations are learned through a convolutional neural networks. Then, the prediction model is developed using the softmax regression. 74 sets of concrete block masonry with different mix ratios are used in the experiments and the results show that the prediction model based on deep learning exhibits the advantages including higher precision, higher efficiency and higher generalization ability compared with the traditional neural network model, and could be considered as a new method for calculating the strength of recycled concrete.
Testicular tumors are the most common tumors in adolescent and young men and germ cell tumors (TGCTs) account for most of all testicular cancers. Increasing incidence of TGCTs among males provides ...strong motivation to understand its biological and genetic basis. Gains of chromosome arm 12p and aneuploidy are nearly universal in TGCTs, but TGCTs have low point mutation rate. It is thought that TGCTs develop from premalignant intratubular germ cell neoplasia that is believed to arise from the failure of normal maturation of gonocytes during fetal or postnatal development. Progression toward invasive TGCTs (seminoma and nonseminoma) then occurs after puberty. Both inherited genetic factors and environmental risk factors emerge as important contributors to TGCT susceptibility. Genome-wide association studies have so far identified more than 30 risk loci for TGCTs, suggesting that a polygenic model fits better with the genetic landscape of the disease. Despite high cure rates because of its particular sensitivity to platinum-based chemotherapy, exploration of mechanisms underlying the occurrence, progression, metastasis, recurrence, chemotherapeutic resistance, early diagnosis and optional clinical therapeutics without long-term side effects are urgently needed to reduce the cancer burden in this underserved age group. Herein, we present an up-to-date review on clinical challenges, origin and progression, risk factors, TGCT mouse models, serum diagnostic markers, resistance mechanisms, miRNA regulation, and database resources of TGCTs. We appeal that more attention should be paid to the basic research and clinical diagnosis and treatment of TGCTs.
Computational drug repositioning aims to identify potential applications of existing drugs for the treatment of diseases for which they were not designed. This approach can considerably accelerate ...the traditional drug discovery process by decreasing the required time and costs of drug development. Tensor decomposition enables us to integrate multiple drug- and disease-related data to boost the performance of prediction. In this study, a nonnegative tensor decomposition for drug repositioning, NTD-DR, is proposed. In order to capture the hidden information in drug-target, drug-disease, and target-disease networks, NTD-DR uses these pairwise associations to construct a three-dimensional tensor representing drug-target-disease triplet associations and integrates them with similarity information of drugs, targets, and disease to make a prediction. We compare NTD-DR with recent state-of-the-art methods in terms of the area under the receiver operating characteristic (ROC) curve (AUC) and the area under the precision and recall curve (AUPR) and find that our method outperforms competing methods. Moreover, case studies with five diseases also confirm the reliability of predictions made by NTD-DR. Our proposed method identifies more known associations among the top 50 predictions than other methods. In addition, novel associations identified by NTD-DR are validated by literature analyses.
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