The t(8;21) fusion product, AML1/ETO, and hypoxia-inducible factor 1α (HIF1α) form a feed-forward transcription loop that cooperatively transactivates the DNA methyltransferase 3a gene promoter that ...leads to DNA hypermethylation and drives leukemia cell growth. Suppression of the RNA N
-methyladenosine (m
A)-reader enzyme YTH N
-methyladenosine RNA binding protein 2 (YTHDF2) specifically compromises cancer stem cells in acute myeloid leukemia (AML) but promotes hematopoietic stem cell expansion without derailing normal hematopoiesis. However, the relevance of expression between AML1/ETO-HIF1α loop and YTHDF2, and its functional relationship with t(8;21) AML have not been documented. Here, we show that YTHDF2 is highly expressed in t(8;21) AML patients and associated with a higher risk of relapse and inferior relapse-free survival. Knockdown of YTHDF2 in leukemia cells causes an impaired cell proliferation rate in vitro and in mice. Mechanistically, HIF1α is able to bind to the hypoxia-response elements of the 5'-untranslated region of the YTHDF2 gene and promotes the transactivity of the YTHDF2 promoter. Knockdown and overexpression of either AML1/ETO or HIF1α resulted in decreased and increased YTHDF2 protein and mRNA expression in t(8;21) AML cells. In particular, knockdown of YTHDF2 resulted in increased global mRNA m
A levels in t(8;21) AML cells, accompanied by increased TNF receptor superfamily member 1b (TNFRSF1b) mRNA and protein expression levels. Last, we demonstrated that the m
A methylation and expression levels of the TNFRSF1b gene were both negatively correlated with HIF1α expression levels. In conclusion, YTHDF2 is a downstream target of the AML1/ETO-HIF1α loop and promotes cell proliferation probably by modulating the global m
A methylation in t(8;21) AML.
Multi-label image recognition is a practical and challenging task compared to single-label image classification. However, previous works may be suboptimal because of a great number of object ...proposals or complex attentional region generation modules. In this paper, we propose a simple but efficient two-stream framework to recognize multi-category objects from global image to local regions, similar to how human beings perceive objects. To bridge the gap between global and local streams, we propose a multi-class attentional region module which aims to make the number of attentional regions as small as possible and keep the diversity of these regions as high as possible. Our method can efficiently and effectively recognize multi-class objects with an affordable computation cost and a parameter-free region localization module. Over three benchmarks on multi-label image classification, our method achieves new state-of-the-art results with a single model only using image semantics without label dependency. In addition, the effectiveness of the proposed method is extensively demonstrated under different factors such as global pooling strategy, input size and network architecture. Code has been made available at https://github.com/gaobb/MCAR .
Abstract
Artificially performing chemical reactions in living biosystems to attain various physiological aims remains an intriguing but very challenging task. In this study, the Schiff base reaction ...was conducted in cells using Sc(OTf)
3
as a catalyst, enabling the in situ synthesis of a hollow covalent organic polymer (HCOP) without external stimuli. The reversible Schiff base reaction mediated intracellular Oswald ripening endows the HCOP with a spherical, hollow porous structure and a large specific surface area. The intracellularly generated HCOP reduced cellular motility by restraining actin polymerization, which consequently induced mitochondrial deactivation, apoptosis, and necroptosis. The presented intracellular synthesis system inspired by the Schiff base reaction has strong potential to regulate cell fate and biological functions, opening up a new strategic possibility for intervening in cellular behavior.
Deep Label Distribution Learning With Label Ambiguity Gao, Bin-Bin; Xing, Chao; Xie, Chen-Wei ...
IEEE transactions on image processing,
2017-June, 2017-Jun, 2017-6-00, 20170601, Volume:
26, Issue:
6
Journal Article
Peer reviewed
Open access
Convolutional neural networks (ConvNets) have achieved excellent recognition performance in various visual recognition tasks. A large labeled training set is one of the most important factors for its ...success. However, it is difficult to collect sufficient training images with precise labels in some domains, such as apparent age estimation, head pose estimation, multilabel classification, and semantic segmentation. Fortunately, there is ambiguous information among labels, which makes these tasks different from traditional classification. Based on this observation, we convert the label of each image into a discrete label distribution, and learn the label distribution by minimizing a Kullback-Leibler divergence between the predicted and ground-truth label distributions using deep ConvNets. The proposed deep label distribution learning (DLDL) method effectively utilizes the label ambiguity in both feature learning and classifier learning, which help prevent the network from overfitting even when the training set is small. Experimental results show that the proposed approach produces significantly better results than the state-of-the-art methods for age estimation and head pose estimation. At the same time, it also improves recognition performance for multi-label classification and semantic segmentation tasks.
Abstract
While inheriting the exceptional merits of single atom catalysts, diatomic site catalysts (DASCs) utilize two adjacent atomic metal species for their complementary functionalities and ...synergistic actions. Herein, a DASC consisting of nickel-iron hetero-diatomic pairs anchored on nitrogen-doped graphene is synthesized. It exhibits extraordinary electrocatalytic activities and stability for both CO
2
reduction reaction (CO
2
RR) and oxygen evolution reaction (OER). Furthermore, the rechargeable Zn-CO
2
battery equipped with such bifunctional catalyst shows high Faradaic efficiency and outstanding rechargeability. The in-depth experimental and theoretical analyses reveal the orbital coupling between the catalytic iron center and the adjacent nickel atom, which leads to alteration in orbital energy level, unique electronic states, higher oxidation state of iron, and weakened binding strength to the reaction intermediates, thus boosted CO
2
RR and OER performance. This work provides critical insights to rational design, working mechanism, and application of hetero-DASCs.
SUMMARY
Developing seed depends on sugar supply for its growth and yield formation. Maize (Zea mays L.) produces the largest grains among cereals. However, there is a lack of holistic understanding ...of the transcriptional landscape of genes controlling sucrose transport to, and utilization within, maize grains. By performing in‐depth data mining of spatio‐temporal transcriptomes coupled with histological and heterologous functional analyses, we identified transporter genes specifically expressed in the maternal–filial interface, including (i) ZmSWEET11/13b in the placento‐chalazal zone, where sucrose is exported into the apoplasmic space, and (ii) ZmSTP3, ZmSWEET3a/4c (monosaccharide transporters), ZmSUT1, and ZmSWEET11/13a (sucrose transporters) in the basal endosperm transfer cells for retrieval of apoplasmic sucrose or hexoses after hydrolysis by extracellular invertase. In the embryo and its surrounding regions, an embryo‐localized ZmSUT4 and a cohort of ZmSWEETs were specifically expressed. Interestingly, drought repressed those ZmSWEETs likely exporting sucrose but enhanced the expression of most transporter genes for uptake of apoplasmic sugars. Importantly, this drought‐induced fluctuation in gene expression was largely attenuated by an increased C supply via controlled pollination, indicating that the altered gene expression is conditioned by C availability. Based on the analyses above, we proposed a holistic model on the spatio‐temporal expression of genes that likely govern sugar transport and utilization across maize maternal and endosperm and embryo tissues during the critical stage of grain set. Collectively, the findings represent an advancement towards a holistic understanding of the transcriptional landscape underlying post‐phloem sugar transport in maize grain and indicate that the drought‐induced changes in gene expression are attributable to low C status.
Significance Statement
Although maize (Zea mays L.) produces the largest grain among cereals through a small ‘gateway’ for assimilates, indicating a strong sink capacity, there is a lack of holistic understanding of the molecular basis underlying sugar import into the grains. Here, we uncovered a cohort of key genes controlling sugar delivery to the endosperm and embryo and further found that drought repressed those genes exporting sucrose into the apoplasmic space but enhanced those genes involved in uptake of sugars by the filial tissues.
Water electrolysis offers a promising energy conversion and storage technology for mitigating the global energy and environmental crisis, but there still lack highly efficient and pH-universal ...electrocatalysts to boost the sluggish kinetics for both cathodic hydrogen evolution reaction (HER) and anodic oxygen evolution reaction (OER). Herein, we report uniformly dispersed iridium nanoclusters embedded on nitrogen and sulfur co-doped graphene as an efficient and robust electrocatalyst for both HER and OER at all pH conditions, reaching a current density of 10 mA cm
with only 300, 190 and 220 mV overpotential for overall water splitting in neutral, acidic and alkaline electrolyte, respectively. Based on probing experiments, operando X-ray absorption spectroscopy and theoretical calculations, we attribute the high catalytic activities to the optimum bindings to hydrogen (for HER) and oxygenated intermediate species (for OER) derived from the tunable and favorable electronic state of the iridium sites coordinated with both nitrogen and sulfur.
We show herein that 1,10‐dicyano substitution restricts the paragon fluxionality of bullvalene to just 14 isomers which isomerize along a single cycle. The restricted fluxionality of ...1,10‐dicyanobullvalene (DCB) is investigated by means of: (i) Bonding analyses of the isomer structures using the adaptive natural density partitioning (AdNDP). (ii) Quantum dynamical simulations of the isomerizations along the cyclic intrinsic reaction coordinate of the potential energy surface (PES). The PES possesses 14 equivalent potential wells supporting 14 isomers which are separated by 14 equivalent potential barriers supporting 14 transition states. Accordingly, at low temperatures, DCB appears as a hindered molecular rotor, without any delocalization of the wavefunction in the 14 potential wells, without any nuclear spin isomers, and with completely negligible tunneling. These results are compared and found to differ from those for molecular boron rotors. (iii) Born‐Oppenheimer molecular dynamics (BOMD) simulations of thermally activated isomerizations. (iv) Calculations of the rate constants in the frame of transition state theory (TST) with reasonable agreement achieved with the BOMD results. (v) Simulations of the equilibration dynamics using rate equations for the isomerizations with TST rate coefficients. Accordingly, in the long‐time limit, isomerizations of the 14 isomers, each with Cs symmetry, approach the “14 Cs → C7v” thermally averaged structure. This is a superposition of the 14 equally populated isomer structures with an overall C7v symmetry. By extrapolation, the results for DCB yield working hypotheses for so far un‐explored properties e.g. for the equilibration dynamics of C10H10.
Extensive first‐principles theory investigations indicate that a 1,10‐dicyano substitution restricts the fluxionality of bullvalene C3v C10H10 to 14 isomers of Cs 1,10‐C10H8(CN)2 (a) which isomerize along one isomerization cycle, resulting in a thermally averaged structure with the symmetry of C7v (b).
Long-term stability is an essential requirement for perovskite solar cells (PSCs) to be commercially viable. Heterojunctions built by low-dimensional and three-dimensional perovskites (1D/3D or ...2D/3D) help to improve the stability of PSCs. However, the insulated organic cations of low-dimensional perovskite impede the transport of carriers, decreasing the power conversion efficiency (PCE) of PSCs. Herein, we introduce an in situ cross-linking polymerizable propargylammonium (PA + ) to the 3D perovskite film at surfaces and grain boundaries to form a 1D/3D perovskite heterostructure. This passivation strategy not only significantly improves the interfacial carrier transport but also releases residual tensile strain in perovskite films. As a result, the corresponding devices achieve a champion PCE of 21.19%, while maintaining 93% of their initial efficiency after 3055 h of continuous illumination under maximum power point (MPP) operating conditions.
Peptide‐based materials are one of the most important biomaterials, with diverse structures and functionalities. Over the past few decades, a self‐assembly strategy is introduced to construct ...peptide‐based nanomaterials, which can form well‐controlled superstructures with high stability and multivalent effect. More recently, peptide‐based functional biomaterials are widely utilized in clinical applications. However, there is no comprehensive review article that summarizes this growing area, from fundamental research to clinic translation. In this review, the recent progress of peptide‐based materials, from molecular building block peptides and self‐assembly driving forces, to biomedical and clinical applications is systematically summarized. Ex situ and in situ constructed nanomaterials based on functional peptides are presented. The advantages of intelligent in situ construction of peptide‐based nanomaterials in vivo are emphasized, including construction strategy, nanostructure modulation, and biomedical effects. This review highlights the importance of self‐assembled peptide nanostructures for nanomedicine and can facilitate further knowledge and understanding of these nanosystems toward clinical translation.
The recent progress in peptide‐based nanomaterials from building block peptides and self‐assembly driving forces to application‐directed ex situ and in situ construction of nanomaterials is systematically summarized. The advantages of intelligent in situ construction of peptide‐based nanomaterials in vivo are emphasized. The importance of self‐assembled peptide nanostructures for nanomedicine is highlighted.