Rational engineering active sites and vantage defects of catalysts are promising but grand challenging task to enhance photoreduction CO2 to high value‐added C2 products. In this study, we designed ...an N,S‐codoped Fe‐based MIL‐88B catalyst with well‐defined bipyramidal hexagonal prism morphology via a facile and effective process, which was synthesized by addition of appropriate 1,2‐benzisothiazolin‐3‐one (BIT) and acetic acid to the reaction solution. Under simulated solar irradiation, the designed catalyst exhibits high C2H4 evolution yield of 17.7 μmol g−1⋅h, which has been rarely achieved in photocatalytic CO2 reduction process. The synergistic effect of Fe‐N coordinated sites and reasonable defects in the N,S‐codoped photocatalyst can accelerate the migration of photogenerated carriers, resulting in high electron density, and this in turn helps to facilitate the formation and dimerization of C−C coupling intermediates for C2H4 effectively.
The integration of new active sites with beneficial defects in Fe‐MOF MIL‐88B catalysts gives enhanced photoreduction of CO2 to C2H4 under visible light. The modified structure promotes the migration and separation of the photoelectrons to produce the pivotal C−C coupling intermediate for the generation of C2H4, a result supported by in situ FT‐IR analysis.
The coordination microenvironment of metal active sites in metal–organic frameworks (MOFs) plays a crucial role in its performance for electrochemical CO2 reduction reaction (CO2RR). However, it ...remains a challenge to clarify the structure–performance relationship for CO2RR catalyzed by MOFs. Herein, a series of MOFs with different coordination microenvironments of Cu(I) sites (CuCl, CuBr, and CuI) to evaluate their performances for CO2RR is synthesized. With the increasing radius of halogen atom, the CO2 adsorption capacity increases and d‐band center of Cu positively shifts to the Fermi level, leading to enhance the selectivity of CO2 to CH4 conversion. CuI gives the highest total Faradaic efficiency (FE) of 83.2%, with a FE of CH4 up to 57.2% and CH4 partial current density of 60.7 mA cm−2 at −1.08 V versus reversible hydrogen electrode. Theoretical calculations reveal that the shifted d‐band center of Cu site contributes to reduced formation energies of *CH2O and *CH3O intermediates, which is the potential‐determining step of CO2RR and thus facilitates the electrocatalytic CO2 reduction to CH4. This study opens a new avenue for studying the relationship between the coordination microenvironment of active site and electroreduction reaction performance of MOFs.
Exploring the structure−performance relationship of electrocatalytic CO2 reduction on metal–organic frameworks (MOFs) remains a challenge. Herein, a series of stable MOFs (CuCl, CuBr, CuI) are synthesized and comprehensive analysis is undertaken to reveal the relationship between the coordination microenvironment of Cu active site and performance of converting CO2 to CH4.
•Circ_0000442 functions as tumor-suppressor in breast cancer by sponging miR-148b-3p.•MiR-148b-3p acts as a tumor promoter by directly targeting PTEN in breast ...cancer.•Circ_0000442/miR-148b-3p/PTEN/PI3K/Akt axis regulates breast cancer progression.
Breast cancer remains the most common malignancy in women worldwide. Circular RNAs (circRNAs) are a newly validated type of endogenous non-coding RNAs and accumulating evidence suggests that aberrant circRNAs are involved in disease pathogenesis. However, the function of circRNAs in breast cancer remains largely unknown. This study is aimed to characterize the potential role and mechanism of hsa_circ_0000442 (circ_0000442) in breast cancer. The human breast epithelial cell line (MCF-10A), breast cancer cell lines (MCF-7, T47D, BT474, SK-BR-3, MDA-MB-231, SUM-1315) and the Balb/C Nude mice were used for exploration, and the qRT-PCR, western blot, dual-luciferase reporter assay, glo assay, colony formation assay, and tumor xenograft were carried out for investigation. In this study, the results showed a lower expression of circ_0000442 in breast cancer tumor tissues compared with the adjacent normal tissues. Subsequently, circ_0000442 was found to acted as the sponge of miR-148b-3p in breast cancer cells, thus exerting the tumor-suppressive effects. In the subsequent mechanism study, results showed that miR-148b-3p directly targeted PTEN, a well-known tumor suppressor which negatively regulats PI3K/Akt pathway, thus promoting tumor growth in breast cancer. Overall, this study for the first time identified the tumor-suppressive role of circ_0000442 in breast cancer and found PTEN as a novel direct target of miR-148b-3p. The regulatory role of circ_0000442/miR-148b-3p/PTEN/PI3K/Akt axis was preliminarily confirmed in breast cancer cells and mouse models. These findings suggest an important progress in our standing of breast cancer and lay the foundation for the further function, diagnosis, therapy and prognosis research of circular RNAs in breast cancer.
The point process is a solid framework to model sequential data, such as videos, by exploring the underlying relevance. As a challenging problem for high-level video understanding, weakly supervised ...action recognition and localization in untrimmed videos have attracted intensive research attention. Knowledge transfer by leveraging the publicly available trimmed videos as external guidance is a promising attempt to make up for the coarse-grained video-level annotation and improve the generalization performance. However, unconstrained knowledge transfer may bring about irrelevant noise and jeopardize the learning model. This article proposes a novel adaptability decomposing encoder-decoder network to transfer reliable knowledge between the trimmed and untrimmed videos for action recognition and localization by bidirectional point process modeling, given only video-level annotations. By decomposing the original features into the domain-adaptable and domain-specific ones based on their adaptability, trimmed-untrimmed knowledge transfer can be safely confined within a more coherent subspace. An encoder-decoder-based structure is carefully designed and jointly optimized to facilitate effective action classification and temporal localization. Extensive experiments are conducted on two benchmark data sets (i.e., THUMOS14 and ActivityNet1.3), and the experimental results clearly corroborate the efficacy of our method.
Catalytic depolymerization represents a promising approach for the closed-loop recycling of plastic wastes. Here, we report a knowledge-driven catalyst development for poly(ethylene terephthalate) ...(PET) recycling, which not only achieves more than 23-fold enhancement in specific activity but also reduces the alkali concentration by an order of magnitude compared with the conventional hydrolysis. Substituted binuclear zinc catalysts are developed to regulate biomimetic intramolecular PET hydrolysis. Hammett studies and density functional theory (DFT) calculations indicate that the substituents modify the charge densities of the active centers, and an optimal substituent should slightly increase the electron richness of the zinc sites to facilitate the formation of a six-membered ring intermediate. The understanding of the structure-activity relationship leads to an advanced catalyst with a specific activity of 778 ± 40 g
h
g
in 0.1 M NaOH, far outcompeting the conventional hydrolysis using caustic bases (<33.3 g
h
g
in 1-5 M NaOH). This work opens new avenues for environmentally benign PET recycling.
In practical machine learning applications, human instruction is indispensable for model construction. To utilize the precious labeling effort effectively, active learning queries the user with ...selective sampling in an interactive way. Traditional active learning techniques merely focus on the unlabeled data set under a unidirectional exploration framework and suffer from model deterioration in the presence of noise. To address this problem, this paper proposes a novel bidirectional active learning algorithm that explores into both unlabeled and labeled data sets simultaneously in a two-way process. For the acquisition of new knowledge, forward learning queries the most informative instances from unlabeled data set. For the introspection of learned knowledge, backward learning detects the most suspiciously unreliable instances within the labeled data set. Under the two-way exploration framework, the generalization ability of the learning model can be greatly improved, which is demonstrated by the encouraging experimental results.
A novel niobium oxyiodate sulfate, Nb2O3(IO3)2 (SO4), was fabricated by a rational multi‐component design under moderate hydrothermal conditions. This multi‐component design is inspired by an ...interesting niobium oxysulfate reaction, which opens a new door for synthetic method to effectively introduce refractory metals such as Nb into crystal structures by hydrothermal synthesis. Nb2O3(IO3)2(SO4) features a cube‐like topological structure with a large phase‐matching second harmonic generation (SHG) response (6×KDP), a wide transparency window (0.38–8 μm), and a high laser damage threshold (LDT) (20×AgGaS2). It has the highest thermostability (stable up to 580 °C under air) among reported non‐centrosymmetric (NCS) iodates and sulfates and is stable in water and even concentrated H2SO4. Furthermore, Nb2O3(IO3)2(SO4) is a unique nonlinear optical (NLO) material among iodates and sulfates, because its SHG effect is mainly caused by the MO6 units rather than the IO3 or SO4 units, which is demonstrated by density functional theory (DFT) calculations.
Oh my‐obium! The synthesis of crystalline Nb2O3(IO3)2(SO4) under moderate hydrothermal conditions is reported. The highly thermostable crystal features a strong second‐harmonic‐generation response, a wide transparency window, and a high laser damage threshold.
Phlorizin (PHZ) is one of phytonutrients in apples that contributes to the health-promoting effect implicated by the saying, 'an apple a day keeps the doctor away'. PHZ was firstly identified as a ...competitive inhibitor of sodium-glucose co-transporters-2 (SGLT2); however, its low bioavailability makes it hard to fully explain its pharmacological mechanisms. This study aimed to investigate the ameliorating effect of PHZ on high-fat diet (HFD)-induced obesity via modulating the "gut microbiota-barrier axis". Firstly, C57BL/6 J mice were fed a normal chow diet (NCD) or HFD coadministered with or without PHZ for 12 weeks. Our results showed that PHZ supplementation significantly reduced HFD-induced body weight gain (P < .001), alleviated metabolic disorders (MDs) like insulin resistance (P < .001) and elevation of serum lipopolysaccharides (LPS) (P < .001), attenuated HFD-induced gut microbiota alterations, enhanced short-chain fatty acids (SCFAs) production (P < .001), and inhibited fecal LPS production (P < .001). To investigate the role of the fecal microbiota in the observed beneficial effects, a fecal microbiota transplantation (FMT) experiment was performed by transplanting the feces of the four groups of mice (as donor mice) daily collected from the fourth week to a new batch of acclimatized HFD-fed mice. Our results confirmed that feeding the gut contents of the PHZ-modulated mice could attenuate HFD-induced MDs, accompanied by enhanced glucagon-like peptide 2 (GLP-2) secretion (P < .001) and restoration of HFD-induced damage in the gut epithelial barrier. This study has provided evidence that the "gut microbiota-barrier axis" was an alternative target for the anti-obesity effect of PHZ. This work has also provided an explanation for the high efficacy of PHZ despite the low bioavailability, and PHZ holds great potential to be developed as a functional food ingredient.
Weakly supervised temporal action localization (WS-TAL) aims to identify the time intervals corresponding to actions of interest in untrimmed videos with video-level weak supervision. For most ...existing WS-TAL methods, two commonly encountered challenges are under-localization and over-localization, which inevitably bring about severe performance deterioration. To address the issues, this paper proposes a transformer-structured stochastic process modeling framework, namely StochasticFormer, to fully investigate finer-grained interactions among the intermediate predictions to achieve further refined localization. StochasticFormer is built on a standard attention-based pipeline to derive preliminary frame/snippet-level predictions. Then, the pseudo localization module generates variable-length pseudo action instances with the corresponding pseudo labels. Using the pseudo "action instance - action category" pairs as fine-grained pseudo supervision, the stochastic modeler aims to learn the underlying interaction among the intermediate predictions with an encoder-decoder network. The encoder consists of the deterministic and latent path to capture the local and global information, which are subsequently integrated by the decoder to obtain reliable predictions. The framework is optimized with three carefully designed losses, i.e. the video-level classification loss, the frame-level semantic coherence loss, and the ELBO loss. Extensive experiments on two benchmarks, i.e., THUMOS14 and ActivityNet1.2, have shown the efficacy of StochasticFormer compared with the state-of-the-art methods.
Weakly supervised action localization is a challenging task with extensive applications, which aims to identify actions and the corresponding temporal intervals with only video-level annotations ...available. This paper analyzes the order-sensitive and location-insensitive properties of actions, and embodies them into a self-augmented learning framework to improve the weakly supervised action localization performance. To be specific, we propose a novel two-branch network architecture with intra/inter-action shuffling, referred to as ActShufNet. The intra-action shuffling branch lays out a self-supervised order prediction task to augment the video representation with inner-video relevance, whereas the inter-action shuffling branch imposes a reorganizing strategy on the existing action contents to augment the training set without resorting to any external resources. Furthermore, the global-local adversarial training is presented to enhance the model's robustness to irrelevant noises. Extensive experiments are conducted on three benchmark datasets, and the results clearly demonstrate the efficacy of the proposed method.
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