Improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies

BACKGROUND: Ion Torrent and Ion Proton are semiconductor-based sequencing technologies that feature rapid sequencing speed and low upfront and operating costs, thanks to the avoidance of modified nucleotides and optical measurements. Despite of these advantages, however, Ion semiconductor sequencing technologies suffer much reduced sequencing accuracy at the genomic loci with homopolymer repeats of the same nucleotide. Such limitation significantly reduces its efficiency for the biological applications aiming at accurately identifying various genetic variants. RESULTS: In this study, we propose a Bayesian inference-based method that takes the advantage of the signal distributions of the electrical voltages that are measured for all the homopolymers of a fixed length. By cross-referencing the length of homopolymers in the reference genome and the voltage signal distribution derived from the experiment, the proposed integrated model significantly improves the alignment accuracy around the homopolymer regions. CONCLUSIONS: Besides improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies with the proposed model, similar strategies can also be used on other high-throughput sequencing technologies that share similar limitations

Taxonomic Distribution of FosB in Human-Microbiota and Activity Comparison of Fosfomycin Resistance

FosB, a Mg2+ dependent thioltransferase, confers antibiotic resistance to fosfomycin through enzymatic drug inactivation. Among all antibiotic resistant proteins in the Antibiotic Resistance Genes Database and the Comprehensive Antibiotic Resistance Database, FosB is within 5% of the most number of ARPs identified in Human Microbiome Project reference database but mainly distributed in limited genera, i.e., 122 of total 133 FosB homologues are found from Bacillus and Staphylococcus. Furthermore, these FosB sequences could be divided into three clusters based on their phylogenetic relationship, i.e., two groups of FosB were mainly from Bacillus, and another was mainly from Staphylococcus. Finally, we confirmed that FosB from the group of Staphylococcus presented the highest resistance ability to fosfomycin by in silico and in vitro comparisons. In summary, this study elaborates the specific taxonomic characteristics and resistant abilities of FosB in human microbiota, which might help in developing more promising fosfomycin-like antibiotics

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A Residual Attention and Local Context-Aware Network for Road Extraction from High-Resolution Remote Sensing Imagery

Extracting road information from high-resolution remote sensing images (HRI) can provide crucial geographic information for many applications. With the improvement of remote sensing image resolution, the image data contain more abundant feature information. However, this phenomenon also enhances the spatial heterogeneity between different types of roads, making it difficult to accurately discern the road and non-road regions using only spectral characteristics. To remedy the above issues, a novel residual attention and local context-aware network (RALC-Net) is proposed for extracting a complete and continuous road network from HRI. RALC-Net utilizes a dual-encoder structure to improve the feature extraction capability of the network, whose two different branches take different feature information as input data. Specifically, we construct the residual attention module using the residual connection that can integrate spatial context information and the attention mechanism, highlighting local semantics to extract local feature information of roads. The residual attention module combines the characteristics of both the residual connection and the attention mechanism to retain complete road edge information, highlight essential semantics, and enhance the generalization capability of the network model. In addition, the multi-scale dilated convolution module is used to extract multi-scale spatial receptive fields to improve the model’s performance further. We perform experiments to verify the performance of each component of RALC-Net through the ablation study. By combining low-level features with high-level semantics, we extract road information and make comparisons with other state-of-the-art models. The experimental results show that the proposed RALC-Net has excellent feature representation ability and robust generalizability, and can extract complete road information from a complex environment

Flexible Design of Low-Delay MEC-VLC Integrating Network Based on Attocell Overlap for IIoT

Recently, multi-access edge computing (MEC) cooperating with fifth-generation (5G) mobile communication technology or WiFi has been widely discussed for low-delay systems. However, for the Industrial Internet of Things, which raises higher requirements on system delay, security, capacity, etc., visible light communication (VLC) has better adaptability due to its controllable attocells. Therefore, we establish a computation and transmission integrated system with MEC-VLC as the main body. To solve the imbalance of resource utilization caused by users’ movement in intensive attocells, we propose a series of flexible design schemes based on access points’ cooperation in attocell overlapping areas. We formulate the overlap-based low-delay flexible system design as an optimization problem and then design the system based on it. Specifically, we first give an attocell-associated congestion judgment criterion and correspondingly propose a user discard algorithm. After that, we offer an iterative optimization method for task assignment, which adjusts computing-transmitting units’ cooperation mode to enhance the overall time delay. Then, the computing and transmitting resources are jointly allocated for delay reduction. Finally, our simulation demonstrates that the overlap-based design has a lower user discard ratio than the traditional distance-based system. The maximum delay and standard deviation are also reduced. Consequently, the flexible design based on attocell overlap can improve the reliability, capacity, and fairness of the low-delay integrating system

Constructing Ru/TiO 2 Heteronanostructures Toward Enhanced Photocatalytic Water Splitting via a RuO 2 /TiO 2 Heterojunction and Ru/TiO 2 Schottky Junction

Photocatalysts based on metallic Ru and RuO2 dual co-catalysts modified TiO2 nanobelts (NBs) are constructed through a wet-impregnation reduction method with post thermal oxidation. The samples are characterized carefully and their photocatalytic activities for the half reactions of water splitting as well as full water splitting are evaluated systematically under solar light irradiation. The detailed characterizations and analyses clearly reveal the formation of a Schottky junction at the Ru-TiO2 interface and of RuO2/TiO2 heterojunctions. The results of the photocatalytic tests show that both Ru and RuO2 can improve the photocatalytic activity for H2/O2 evolution and water splitting. Moreover, the photocatalytic activity of the TiO2 NBs can be further enhanced by co-modification with dual Ru and RuO2 co-catalysts. The RuO2/TiO2 heterojunction improves the transfer of the photogenerated holes from the TiO2 to the RuO2, where water can be oxidized by the holes to evolve O2, and the Ru/TiO2 Schottky junction promotes the transfer of photogenerated electrons from the TiO2 NBs to the metallic Ru for proton reduction into H2. These two processes are involved in the overall water splitting. This work provides an important reference for designing highly efficient photocatalysts for water splitting through loading of dual co-catalysts containing the same element but with different valence structures.MOE (Min. of Education, S’pore)Accepted versio

MoS2-coated microspheres of self-sensitized carbon nitride for efficient photocatalytic hydrogen generation under visible light irradiation

We have successfully coated the self-sensitized carbon nitride (SSCN) microspheres with a layer of MoS2 through a facile one-pot hydrothermal method by using (NH4)2MoS4 as the precursor. The resulted MoS2-coated SSCN photocatalyst appears as a core-shell structure and exhibits enhanced visible-light activities for photocatalytic H2 generation as compared to the un-coated SSCN and the standard g-C3N4 reference with MoS2 coating. The photocatalytic test results suggest that the oligomeric s-triazine dyes on the SSCN surface can provide additional light-harvesting capability and photogenerated charge carriers, and the coated MoS2 layer can serve as active sites for proton reduction towards H2 evolution. This synergistic effect of surface triazine dyes and MoS2 coating greatly promotes the activity of carbon nitride microspheres for vishible-light-driven H2 generation. This work provides a new way of future development of low-cost noble-metal-free photocatalysts for efficient solar-driven hydrogen production.MOE (Min. of Education, S’pore)Accepted versio

Electrocatalysis for Oxygen Reduction Reaction on EDTAFeNa and Melamine co-Derived Self-Supported Fe-N-C Materials

To explore high-performing alternatives to platinum-based catalysts is highly desirable for lowering costs and thus promoting fuel cell commercialization. Herein, self-supported Fe-N-C materials were prepared by the pyrolysis of dual precursors including EDTA ferric sodium (EDTAFeNa) and melamine (MA), followed by acid-leaching and final annealing. Towards an oxygen reduction reaction (ORR) in 0.1 M KOH, the as-prepared MA/EDTAFeNa-HT2 delivered onset (Eonset) and half-wave (E1/2) potentials of 0.97 and 0.84 V vs. RHE, respectively, identical with that of a state-of-the-art Pt/C catalyst, accompanied with predominantly a four-electron pathway. The introduction of MA and extension of acid-leaching promoted a positive shift of 50 mV for E1/2 relative to that of only the EDTAFeNa-derived counterpart. It was revealed that the enhancement of ORR activity is attributed to a decrease in magnetic Fe species and increase in pyridinic/quanternary nitrogen content whilst nearly excluding effects of the graphitization degree, variety of crystalline iron species, and mesoscopic structure. The usage of dual precursors exhibited great potential for the large-scale production of inexpensive and efficient Fe-N-C materials