Combination of genetic engineering and random mutagenesis for improving production of raw-starch-degrading enzymes in Penicillium oxalicum.

BACKGROUND: Raw starch-degrading enzyme (RSDE) is applied in biorefining of starch to produce biofuels efficiently and economically. At present, RSDE is obtained via secretion by filamentous fungi such as Penicillium oxalicum. However, high production cost is a barrier to large-scale industrial application. Genetic engineering is a potentially efficient approach for improving production of RSDE. In this study, we combined genetic engineering and random mutagenesis of P. oxalicum to enhance RSDE production. RESULTS: A total of 3619 mutated P. oxalicum colonies were isolated after six rounds of ethyl methanesulfonate and Co60-γ-ray mutagenesis with the strain A2-13 as the parent strain. Mutant TE4-10 achieved the highest RSDE production of 218.6 ± 3.8 U/mL with raw cassava flour as substrate, a 23.2% compared with A2-13. Simultaneous deletion of transcription repressor gene PoxCxrC and overexpression of activator gene PoxAmyR in TE4-10 resulted in engineered strain GXUR001 with an RSDE yield of 252.6 U/mL, an increase of 15.6% relative to TE4-10. Comparative transcriptomics and real-time quantitative reverse transcription PCR revealed that transcriptional levels of major amylase genes, including raw starch-degrading glucoamylase gene PoxGA15A, were markedly increased in GXUR001. The hydrolysis efficiency of raw flour from cassava and corn by crude RSDE of GXUR001 reached 93.0% and 100%, respectively, after 120 h and 84 h with loading of 150 g/L of corresponding substrate. CONCLUSIONS: Combining genetic engineering and random mutagenesis efficiently enhanced production of RSDE by P. oxalicum. The RSDE-hyperproducing mutant GXUR001 was generated, and its crude RSDE could efficiently degrade raw starch. This strain has great potential for enzyme preparation and further genetic engineering.

Single-Mode-Tuned Tricolor Emissions of Upconversion/Afterglow Hybrids for Anticounterfeiting Applications.

This work presents a highly secure anticounterfeiting strategy based on upconversion/afterglow hybrids with tricolor emissions tuned by a single 975 nm laser. The hybrids are composed of NaYF4:Yb/Tm and NaYF4:Yb/Er microrods and CaS:Eu2+ afterglow phosphors. Under 975 nm excitation, the hybrids exhibit multicolor emissions from green to white by adjusting laser power and then emit red afterglow light when the 975 nm laser is off. Under synergistic excitation of the blue-green light emitted by Tm/Er microrods, the red afterglow emission not only has a strong initial intensity but also lasts for 3 s. Obvious trichromatic changes from green to white to red can be observed by the naked eye. A pattern printed by the hybrid ink exhibits tricolor emissions by laser adjustment and switch. This proves that upconversion/afterglow hybrids are an excellent candidate for anticounterfeiting applications with high-level security but a simple recognition method.

A Novel Method for Asynchronous Time-of-Arrival-Based Source Localization: Algorithms, Performance and Complexity.

In time-of-arrival (TOA)-based source localization, accurate positioning can be achieved only when the correct signal propagation time between the source and the sensors is obtained. In practice, a clock error usually exists between the nodes causing the source and sensors to often be in an asynchronous state. This leads to the asynchronous source localization problem which is then formulated to a least square problem with nonconvex and nonsmooth objective function. The state-of-the-art algorithms need to relax the original problem to convex programming, such as semidefinite programming (SDP), which results in performance loss. In this paper, unlike the existing approaches, we propose a proximal alternating minimization positioning (PAMP) method, which minimizes the original function without relaxation. Utilizing the biconvex property of original asynchronous problem, the method divides it into two subproblems: the clock offset subproblem and the synchronous source localization subproblem. For the former we derive a global solution, whereas the later is solved by a proposed efficient subgradient algorithm extended from the simulated annealing-based Barzilai-Borwein algorithm. The proposed method obtains preferable localization performance with lower computational complexity. The convergence of our method in Lyapunov framework is also established. Simulation results demonstrate that the performance of PAMP method can be close to the optimality benchmark of Cramér-Rao Lower Bound.

Hyperspectral inversion of heavy metal content in reclaimed soil from a mining wasteland based on different spectral transformation and modeling methods.

Conventional methods for investigating heavy metal contamination in soil are time consuming and expensive. We explored reflectance spectroscopy as an alternative method for assessing heavy metals. Four spectral transformation methods, first-order differential (FDR), second-order differential (SDR), continuum removal (CR) and continuous wavelet transform (CWT), are used for the original spectral data. Spectral preprocessing effectively eliminated the noise and baseline drifting and also highlighted the locations of the spectral feature bands. Partial least squares regression (PLSR) and radial basis function neural network (RBF) were used to study the hyperspectral inversion of four heavy metals (Cr, As, Ni, Cd). The inversion models of four heavy metals were established in the bands with the highest correlation coefficient. The inversion effects were evaluated by the coefficient of determination (R2), root mean square error (RMSE) and residual predictive deviation (RPD) indexes. The R values of the correlation coefficient were significantly improved after smoothing and spectral transformation compared to the original waveband. The method combining continuous wavelet transform (CWT) with radial basis function neural network (RBF) had the best inversion effect on the four heavy metals. When compared to partial least squares regression (PLSR), the RMSE values were reduced by approximately 2. The CWT-RBF method can be used as a means of inversion of heavy metals in mining wasteland reclaimed land.

Self-powered SBD solar-blind photodetector fabricated on the single crystal of ß-Ga2O3.

A Schottky barrier diode (SBD) solar-blind photodetector was fabricated based on the single crystal ß-Ga2O3. Cu and Ti/Au were deposited on the top and bottom surface of Ga2O3 as Schottky and ohmic contacts, respectively. The SBD exhibits a higher rectification ratio of up to 5 × 107 at ±2 V. The photoresponse spectra show a maximum responsivity at 241 nm and a cutoff wavelength of 256 nm. The solar-blind/ultraviolet and solar-blind/visible rejection ratio can reach a high level of up to 200 and 1000, respectively. It is interesting that the device has a clear response to the solar-blind wavelength at zero bias, which confirms it can be used as a self-powered solar-blind photodetector.