Knockdown of SETD5 inhibited glycolysis and tumor growth in gastric cancer cells by down-regulating Akt signaling pathway.

Gastric cancer (GC) is the 5th most common cancer and the 3rd leading cause of cancer-related death worldwide. It is of great significance to study the underlying molecular mechanism of GC, and targeting glycolysis is a good strategy to treat GC. SET domain containing 5 (SETD5) contains a catalytic methyltransferase SET domain, which is known as a lysine methyltransferase that affects the progression of multiple cancers. However, its possible role in GC was still unclear. Here, we revealed that SETD5 was highly expressed in GC and was associated with a poor prognosis. Further through the in vitro experiments, we revealed that the downregulation of SETD5 inhibited the proliferation and migration of GC cells. Knockdown of SETD5 inhibited glucose consumption and glycolysis. Further studies have shown that SETD5 knockdown restrained the Akt signaling pathway. Therefore, we thought that SETD5 could act as a GC target.

Tuning thermal and electrical properties of MXenes via dehydration.

Recently, MXenes (a class of two-dimensional transition metal carbides) have attracted great attention in various applications such as humidity sensors, owing to their unique electrical and thermal properties. However, previous studies of MXenes mostly focus on their humidity-sensing characteristics such as the mechanical response, and only few reports on their electrical and thermal response are available. Herein, we present novel transient electrothermal experiments to demonstrate that a transition from a negative to a positive resistance-temperature relationship can take place when the MXene sample becomes fully dehydrated. This surprising and unusual phenomenon was elucidated through non-equilibrium molecular dynamics simulations and attributed to water absorption/desorption onto the chemically active MXene surface. A linear relationship was also found between electrical/thermal properties and environmental humidity, which could be related to water adsorption on the surface of the MXene sensor. We further decomposed the total measured thermal conductivity and found that phonons were the dominant thermal carriers in the MXene sample. The main breakthrough of this work is the discovery of the unusual resistance-temperature relationship, which should be applicable to the design of MXene-based sensors for various applications.

Electrical and Magnetic Transport Properties of Co2VGa Half-Metallic Heusler Alloy.

This study performed a systematic experimental investigation into the structural, magnetic, and transport properties of the Co2VGa Heusler alloy, which was theoretically predicted to exhibit half-metallic ferromagnetism. It has been experimentally found that the studied alloy has a relatively high-ordered L21 cubic structure at room temperature and orders ferromagnetically below ~350 K. Interestingly, by fitting the electric transport data with the properly governing equations in two different temperature regions, the two-magnon scattering process (the T9/2 dependence) appears in the temperature range from 30 to 75 K. Moreover, the magnetoresistance effect changes from a negative value to a positive value when the temperature is below 100 K. Such experimental findings provide indirect evidence that the half-metallic nature of this alloy is retained only when the temperature is below 100 K. On the other hand, the magnetic transport measurements indicate that the anomalous Hall coefficient of this alloy increases when the temperature increases and reaches a relatively high value (~8.3 µΩ·cm/T) at 300 K due to its lower saturated magnetization. By analyzing the anomalous Hall resistivity scale with the longitudinal resistivity, it was also found that the anomalous Hall effect can be ascribed to the combined effect of extrinsic skew scattering and intrinsic Berry curvature, but the latter contribution plays a dominant role.

Parameter-Efficient Deep Neural Networks With Bilinear Projections.

Recent research on deep neural networks (DNNs) has primarily focused on improving the model accuracy. Given a proper deep learning framework, it is generally possible to increase the depth or layer width to achieve a higher level of accuracy. However, the huge number of model parameters imposes more computational and memory usage overhead and leads to the parameter redundancy. In this article, we address the parameter redundancy problem in DNNs by replacing conventional full projections with bilinear projections (BPs). For a fully connected layer with D input nodes and D output nodes, applying BP can reduce the model space complexity from O(D2) to O(2D) , achieving a deep model with a sublinear layer size. However, the structured projection has a lower freedom of degree compared with the full projection, causing the underfitting problem. Therefore, we simply scale up the mapping size by increasing the number of output channels, which can keep and even boosts the model accuracy. This makes it very parameter-efficient and handy to deploy such deep models on mobile systems with memory limitations. Experiments on four benchmark data sets show that applying the proposed BP to DNNs can achieve even higher accuracies than conventional full DNNs while significantly reducing the model size.

Architecturally Robust Graphene-Encapsulated MXene Ti2CT x@Polyaniline Composite for High-Performance Pouch-Type Asymmetric Supercapacitor.

A harmonized three-component composite system which preserves the characteristics of individual components is of interest in the field of energy storage. Here, we present a graphene-encapsulated MXene Ti2CT x@polyaniline composite (GMP) material realized in a systematically stable configuration with different ternary nanomaterials for supercapacitor electrodes. Due to the different ζ-potentials in a high-pH solution, chemically converted graphene (negatively charged) is thoroughly unfolded to allow full encapsulation, but the MXene Ti2CT x@polyaniline composite with a low positive ζ-potential is easily attracted toward a counter-charged substance. The obtained GMP electrode exhibits improved cycling stability and better electrochemical performance owing to the use of mechanically robust and chemically inert graphene and the densely intercalated conductive polyaniline between the multilayer MXenes. The GMP electrode has a high gravimetric capacitance of 635 F g-1 (volumetric capacitance of 1143 F cm-3) at a current density of 1 A g-1 with excellent cycling stability of 97.54% after 10 000 cycles. Furthermore, the asymmetric pouch-type supercapacitor assembled using the GMP as a positive electrode and graphene as a negative electrode yields a high energy density of 42.3 Wh kg-1 at a power density of 950 W kg-1 and remarkable cycling stability (94.25% after 10 000 cycles at 10 A g-1).

Ilmenite Nanotubes for High Stability and High Rate Sodium-Ion Battery Anodes.

To solve the problem of large volume change and low electronic conductivity of earth-abundant ilmenite used in rechargeable Na-ion batteries (SIBs), an anode of tiny ilmenite FeTiO3 nanoparticle embedded carbon nanotubes (FTO⊂CNTs) has been successfully proposed. By introducing a TiO2 shell on metal-organic framework (Fe-MOF) nanorods by sol-gel deposition and subsequent solid-state annealing treatment of these core-shell Fe-MOF@TiO2, such well-defined FTO⊂CNTs are obtained. The achieved FTO⊂CNT electrode has several distinct advantages including a hollow interior in the hybrid nanostructure, fully encapsulated ultrasmall electroactive units, flexible conductive carbon matrix, and stable solid electrolyte interface (SEI) of FTO in cycles. FTO⊂CNT electrodes present an excellent cycle stability (358.8 mA h g-1 after 200 cycles at 100 mA g-1) and remarkable rate capability (201.8 mA h g-1 at 5000 mA g-1) with a high Coulombic efficiency of approximately 99%. In addition, combined with the typical Na3V2(PO4)3 cathode to constitute full SIBs, the assembled FTO⊂CNT//Na3V2(PO4)3 batteries are also demonstrated with superior rate capability and a long cycle life.

New Nanoconfined Galvanic Replacement Synthesis of Hollow Sb@C Yolk-Shell Spheres Constituting a Stable Anode for High-Rate Li/Na-Ion Batteries.

In the current research project, we have prepared a novel Sb@C nanosphere anode with biomimetic yolk-shell structure for Li/Na-ion batteries via a nanoconfined galvanic replacement route. The yolk-shell microstructure consists of Sb hollow yolk completely protected by a well-conductive carbon thin shell. The substantial void space in the these hollow Sb@C yolk-shell particles allows for the full volume expansion of inner Sb while maintaining the framework of the Sb@C anode and developing a stable SEI film on the outside carbon shell. As for Li-ion battery anode, they displayed a large specific capacity (634 mAh g-1), high rate capability (specific capabilities of 622, 557, 496, 439, and 384 mAh g-1 at 100, 200, 500, 1000, and 2000 mA g-1, respectively) and stable cycling performance (a specific capacity of 405 mAh g-1 after long 300 cycles at 1000 mA g-1). As for Na-ion storage, these yolk-shell Sb@C particles also maintained a reversible capacity of approximate 280 mAh g-1 at 1000 mA g-1 after 200 cycles.

Metal-Organic Framework-Derived NiSb Alloy Embedded in Carbon Hollow Spheres as Superior Lithium-Ion Battery Anodes.

The MOFs (metal-organic frameworks) have been extensively used for electrode materials due to their high surface area, permanent porosity, and hollow structure, but the role of antimony on the MOFs is unclear. In this work, we design the hollow spheres Ni-MOFs with SbCl3 to synthesize NiSb⊂CHSs (NiSb-embedded carbon hollow spheres) via simple annealing and galvanic replacement reactions. The NiSb⊂CHSs inherited the advantages of Ni-MOFs with hollow structure, high surface area, and permanent porosity, and the NiSb nanoparticles are coated by the formed carbon particles which could effectively solve the problem of vigorous volume changes during the Li+ insertion/extraction process. The porous and network structure could well provide an extremely reduced pathway for fast Li+ diffusion and electron transport and provide extra free space for alleviating the structural strain. The NiSb⊂CHSs with these features were used as Li-ion batteries for the first time and exhibited excellent cycling performance, high specific capacity, and great rate capability. When coupled with a nanostructure LiMn2O4 cathode, the NiSb⊂CHSs//LiMn2O4 full cell also characterized a high voltage operation of ≈3.5 V, high rate capability (210 mA h g-1 at a current density of 2000 mA g-1), and high Coulombic efficiency of approximate 99%, meeting the requirement for the increasing demand for improved energy devices.

Web Video Event Recognition by Semantic Analysis From Ubiquitous Documents.

In recent years, the task of event recognition from videos has attracted increasing interest in multimedia area. While most of the existing research was mainly focused on exploring visual cues to handle relatively small-granular events, it is difficult to directly analyze video content without any prior knowledge. Therefore, synthesizing both the visual and semantic analysis is a natural way for video event understanding. In this paper, we study the problem of Web video event recognition, where Web videos often describe large-granular events and carry limited textual information. Key challenges include how to accurately represent event semantics from incomplete textual information and how to effectively explore the correlation between visual and textual cues for video event understanding. We propose a novel framework to perform complex event recognition from Web videos. In order to compensate the insufficient expressive power of visual cues, we construct an event knowledge base by deeply mining semantic information from ubiquitous Web documents. This event knowledge base is capable of describing each event with comprehensive semantics. By utilizing this base, the textual cues for a video can be significantly enriched. Furthermore, we introduce a two-view adaptive regression model, which explores the intrinsic correlation between the visual and textual cues of the videos to learn reliable classifiers. Extensive experiments on two real-world video data sets show the effectiveness of our proposed framework and prove that the event knowledge base indeed helps improve the performance of Web video event recognition.

Increased α-tubulin1b expression indicates poor prognosis and resistance to chemotherapy in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer deaths worldwide. It is important to understand molecular mechanisms of HCC progression and to develop clinically useful biomarkers for the disease. AIM: We aimed to investigate the possible involvement of α-tubulin1b (TUBA1B) in HCC pathology. METHODS: Tissue specimens were obtained from 114 HCC patients during hepatectomy. Immunohistochemistry and western blot analysis were used to detect TUBA1B expression in HCC tissues and cell lines. TUBA1B was knocked down in HCC cells by siRNA transfection. CCK-8 assay and flow cytometry were applied to determine cell proliferation and cell cycle progression, respectively. The efficacy of paclitaxel chemotherapy was evaluated by plate colony formation assay. RESULTS: TUBA1B was higher expressed in HCC tumor tissues than in adjacent nontumor tissues. TUBA1B and Ki-67 expressions were positively related to each other, and both their expressions were significantly associated with histological grade of HCC patients. Univariate and multivariate survival analyses revealed that TUBA1B was a significant predictor for overall survival of HCC patients. TUBA1B expression was increased in HCC cells during the G1- to S-phase transition. TUBA1B knockout in HCC cells inhibited cell proliferation, and attenuated resistance to paclitaxel. CONCLUSIONS: Our results indicated that TUBA1B expression was upregulated in HCC tumor tissues and proliferating HCC cells, and an increased TUBA1B expression was associated with poor overall survival and resistance to paclitaxel of HCC patients.

The relationship between Cyclin G1 and survival in patients treated surgically for HCC.

BACKGROUND/AIM: Cyclin G1 is a cell-cycle-regulatory protein that is frequently seen in elevated amounts in malignant tissue, including astrocytomas; melanoma; carcinoma of the esophagus, lung, and breast; as well as cancer of the cervix, uterus, and ovary. By contrast, it has demonstrated inhibitory activity in human hepatocellular carcinoma (HCC). METHODOLOGY: We investigated the role of cyclin G1 in HCC tissue obtained from 76 donors using immunohistochemistry and Western blot analysis to explore its relationship with HCC pathology and univariate and multivariate analyses to explore its relationship with surgical prognosis and patient survival. RESULTS: We found that cyclin G1 levels were increased in normal tissue compared with HCC tissue and vary over the course of the cell cycle, with equal distribution between the nucleus and cytoplasm observed during normal serum support and accelerated release from the nucleus into the cytoplasm observed during serum starvation. CONCLUSION: Our findings suggest a role for cyclin G1 in anti-HCC gene therapy.