No abstract

With the recent explosion in high-throughput genotyping technology, the amount and quality of single-nucleotide polymorphism (SNP) data has increased exponentially. Therefore, the identification of SNP interactions that are associated with common diseases is playing an increasing and important role in interpreting the genetic basis of disease susceptibility and in devising new diagnostic tests and treatments. However, because these data sets are large, although they typically have small sample sizes and low signal-to-noise ratios, there has been no major breakthrough despite many efforts, making this a major focus in the field of bioinformatics. In this article, we review the two main aspects of SNP interaction studies in recent years-the simulation and identification of SNP interactions-and then discuss the principles, efficiency and differences between these methods.

This work reports the use of the chip-based GaN-based micro-LED (μLED) arrays for multifunctional applications as microdisplay, data transmitters, photodetectors, and solar cells. The functions of display and transmitter have been reported, and particularly, we experimentally demonstrated that μLED arrays could be used as self-powered, high-performance, and wavelength-selective photodetectors (PDs), enabling high-speed multiple-input multiple-output (MIMO) visible light communications (VLC) under on−off keying (OOK) modulation scheme using 405 nm violet laser diodes (LDs) as transmitters. The optoelectronic and communication characteristics of the μLED-based PDs with diameters of 40, 60 and 100 μm were systematically studied. The optoelectronic analysis shows superior performances of μLEDbased PDs at a 405 nm wavelength compared with other previously reported GaN-based PDs. Under a bias voltage of −5 V, the comparable peak responsivities of 0.27, 0.31, and 0.24 A/W, specific detectivities of 1.1 × 10 11 , 2.3 × 10 12 , and 2.1 × 10 12 cm H 1/2 W −1 , and linear dynamic ranges (LDRs) of 152, 162, and 164 dB were achieved for 40, 60, and 100 μm μLEDs, respectively. Even at zero-bias, that is, self-powered mode, we have achieved high peak responsivities of 0.24, 0.29, and 0.21 A/ W, high specific detectivities of 7.5 × 10 12 , 1.5 × 10 13 , and 1.3 × 10 13 cm H 1/2 W −1 , and high LDR up to 186, 196, and 197 dB for 40, 60, and 100 μm μLEDs, respectively. The μLEDs could also be used to harvest the optical energy of the system, working as solar cells. The μLED-based PD arrays were tested as receivers in the VLC system to implement high-speed parallel communication, which yields maximum data rates of 180, 175, and 185 Mbps for single 40, 60, and 100 μm μLED-based PDs at a distance of 1 m with BERs of 3.5 × 10 −3 , 3.7 × 10 −3 , and 3.5 × 10 −3 , respectively. Furthermore, the 2 × 2 MIMO parallel VLC system was achieved to increase the VLC data rate, which suggests the potential of using large μLED-based PD arrays for multiple Gbps and even Tbps VLC applications.

No abstract

MicroRNAs (miRNAs) regulate genes that are associated with various diseases. To better understand miRNAs, the miRNA regulatory mechanism needs to be investigated and the real targets identified. Here, we present miRTDL, a new miRNA target prediction algorithm based on convolutional neural network (CNN). The CNN automatically extracts essential information from the input data rather than completely relying on the input dataset generated artificially when the precise miRNA target mechanisms are poorly known. In this work, the constraint relaxing method is first used to construct a balanced training dataset to avoid inaccurate predictions caused by the existing unbalanced dataset. The miRTDL is then applied to 1,606 experimentally validated miRNA target pairs. Finally, the results show that our miRTDL outperforms the existing target prediction algorithms and achieves significantly higher sensitivity, specificity and accuracy of 88.43, 96.44, and 89.98 percent, respectively. We also investigate the miRNA target mechanism, and the results show that the complementation features are more important than the others.

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Mesoporous solid strong bases are highly promising for applications as environmentally benign catalysts in various reactions. Their preparation attracts increasing attention for the demand of sustainable chemistry. In the present study, a new strategy was designed to fabricate strong basicity on mesoporous silica by using multifunction of a carbon interlayer. A typical mesoporous silica, SBA-15, was precoated with a layer of carbon prior to the introduction of base precursor LiNO3. The carbon interlayer performs two functions by promoting the conversion of LiNO3 at low temperatures and by improving the alkali-resistant ability of siliceous host. Only a tiny amount of LiNO3 was decomposed on pristine SBA-15 at 400 °C; for the samples containing >8 wt % of carbon, however, LiNO3 can be entirely converted to strongly basic sites Li2O under the same conditions. The guest-host redox reaction was proven to be the answer for the conversion of LiNO3, which breaks the tradition of thermally induced decomposition. More importantly, the residual carbon layer can prevent the siliceous frameworks from corroding by the newly formed strongly basic species, which is different from the complete destruction of mesostructure in the absence of carbon. Therefore, materials possessing both ordered mesostructure and strong basicity were successfully fabricated, which is extremely desirable for catalysis and impossible to realize by conventional methods. We also demonstrated that the resultant mesoporous basic materials are active in heterogeneous synthesis of dimethyl carbonate (DMC) and the yield of DMC can reach 32.4%, which is apparently higher than that over the catalysts without a carbon interlayer (<12.9%) despite the same lithium content. The strong basicity, in combination with the uniform mesopores, is believed to be responsible for such a high activity.

It is desirable for a sustainable society that the production and utilization of renewable materials are net‐zero in terms of carbon emissions. Carbon materials with emerging applications in CO2 utilization, renewable energy storage and conversion, and biomedicine have attracted much attention both academically and industrially. However, the preparation process of some new carbon materials suffers from energy consumption and environmental pollution issues. Therefore, the development of low‐cost, scalable, industrially and economically attractive, sustainable carbon material preparation methods are required. In this regard, the use of biomass and its derivatives as a precursor of carbon materials is a major feature of sustainability. Recent advances in the synthetic strategy of sustainable carbon materials and their emerging applications are summarized in this short review. Emphasis is made on the discussion of the original intentions and various sustainable strategies for producing sustainable carbon materials. This review provides basic insights and significant guidelines for the further design of sustainable carbon materials and their emerging applications in catalysis and the biomedical field.