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As one of the most aggressive malignancies, non-small cell lung carcinoma (NSCLC) has high risks of death. It has been demonstrated that circRNAs accelerate NSCLC progression, but the underlying molecular mechanisms of circRNAs in NSCLC were still obscure. In the first place, the circRNA microarray of NSCLC was investigated in this study, and hsa_circ_0008003 (circ-0008003) was chosen as the research object. Then, it was unveiled that the expression of circ-0008003 examined via qRT-PCR was elevated in tumour tissues relative to the non-tumour tissues, which was associated with TNM stage and lymphatic metastasis in NSCLC. Additionally, the prognosis of NSCLC patients with high circ-0008003 level was poor. Besides, circ-0008003 silencing dampened the invasion and proliferation of NSCLC cells. Next, according to the mechanistic studies, circ-0008003 functioned as a ceRNA of ZNF281 in NSCLC by acting as the endogenous sponge for miR-488, which was proved to be a tumour suppressor in NSCLC. Additionally, ZNF281 overexpression and miR-488 suppression recovered the influences of repressed circ-0008003 on NSCLC cellular processes. It was validated in this research that circ-0008003 triggered tumour formation in NSCLC, which was adjusted via miR-488/ZNF281 axis, casting a novel light on the resultful target for treating NSCLC and predicting the prognosis. [ABSTRACT FROM AUTHOR]

Stretchable micropower sources with high energy density and stability under repeated tensile deformation are key components of flexible/wearable microelectronics. Herein, through the combination of strain engineering and modulation of the interlayer spacing, freestanding and lightweight MXene/bacterial cellulose (BC) composite papers with excellent mechanical stability and a high electrochemical performance are first designed and prepared via a facile all-solution-based paper-making process. Following a simple laser-cutting kirigami patterning process, bendable, twistable, and stretchable all-solid-state micro-supercapacitor arrays (MSCAs) are further fabricated. As expected, benefiting from the high-performance MXene/BC composite electrodes and rational sectional structural design, the resulting kirigami MSCAs exhibit a high areal capacitance of 111.5 mF cm−2, and are stable upon stretching of up to 100% elongation, and in bent or twisted states. The demonstrated combination of an all-solution-based MXene/BC composite paper-making method and an easily manipulated laser-cutting kirigami patterning technique enables the fabrication of MXene-based deformableall-solid-state planar MSCAs in a simple and efficient manner while achieving excellent areal performance metrics and high stretchability, making them promising micropower sources that are compatible with flexible/wearable microelectronics. [ABSTRACT FROM AUTHOR]

Sesame-husk-like porous SnO2 nanocylinders were synthesised by a refluxed technique followed calcination in air. Served as anode materials for lithium-ion batteries, porous SnO2 nanocylinders showed a higher initial discharge capacity of 2411.3 mAh/g at 100 mA/g compared with non-porous SnO2 nanocylinders (2043.6 mAh/g). Moreover, porous SnO2 nanocylinders demonstrated better cyclability and rate capability in comparison with non-porous SnO2 nanocylinders. For porous SnO2 nanocylinders, a higher discharge capacity of 414.5 mAh/g after 50 cycles at a current density of 100 mA/g can be successfully delivered, and a higher reversible capacity of 248.3 mAh/g at 1000 mA/g current density after 100 cycles could be retained. The improved electrochemical performance is mainly ascribed to the unique porous nanostructures. [ABSTRACT FROM AUTHOR]

Camera-based observation of forest canopies allows for low-cost, continuous, high temporal-spatial resolutions of plant phenology and seasonality of functional traits. In this study, we extracted canopy color index (green chromatic coordinate, Gcc) from the time-series canopy images provided by a digital camera in a deciduous forest in Massachusetts, USA. We also measured leaf-level photosynthetic activities and leaf area index (LAI) development in the field during the growing season, and corresponding leaf chlorophyll concentrations in the laboratory. We used the Bayesian change point (BCP) approach to analyze Gcc. Our results showed that (1) the date of starting decline of LAI (DOY 263), defined as the start of senescence, could be mathematically identified from the autumn Gcc pattern by analyzing change points of the Gcc curve, and Gcc is highly correlated with LAI after the first change point when LAI was decreasing (R2 = 0.88, LAI < 2.5 m2/m2); (2) the second change point of Gcc (DOY 289) started a more rapid decline of Gcc when chlorophyll concentration and photosynthesis rates were relatively low (13.4 ± 10.0% and 23.7 ± 13.4% of their maximum values, respectively) and continuously reducing; and (3) the third change point of Gcc (DOY 295) marked the end of growing season, defined by the termination of photosynthetic activities, two weeks earlier than the end of Gcc curve decline. Our results suggested that with the change point analysis, camera-based phenology observation can effectively quantify the dynamic pattern of the start of senescence (with declining LAI) and the end of senescence (when photosynthetic activities terminated) in the deciduous forest. [ABSTRACT FROM AUTHOR]

Since sparse representation (SR) was first introduced into robust face recognition, the argument has lasted for several years about whether sparsity can improve robust face recognition or not. Some work argued that the robust sparse representation (RSR) model has a similar recognition rate as non-sparse solution, while it needs a much higher computational cost due to the larger feature dimensionality in the pixel space. In this study, the authors reveal that the standard RSR model, which expands the dictionary with the identity matrix to reconstruct corruption or occlusion in face images, is essentially a non-sparse solution with a relatively large residual. The reason why the RSR model underperforms may be its inappropriately expanded bases rather than the sparsity itself. Thereby, this study proposes to design a dictionary with an expanded noise bases set which can precisely reconstructs any corruption or occlusion in face images in a subspace. Experimental results show that the algorithm can greatly improve recognition rates for robust face recognition. In addition, the algorithm can be simply performed in a subspace with a small feature dimensionality, thus efficient enough for real systems. This study makes us come to the conclusion that solving the approximation problem in raw pixel space is not necessary for robust face recognition, while solving in a subspace with a much smaller feature dimensionality is enough when the dictionary is well expanded. Finally, this study also confirms that the sparsity plays an important role in SR based classification. [ABSTRACT FROM AUTHOR]