Rapid screening of the novel bioactive peptides with notable α-glucosidase inhibitory activity by UF-LC-MS/MS combined with three-AI-tool from black beans.

This work aimed to propose a rapid method to screen the bioactive peptides with anti-α-glucosidase activity instead of traditional multiple laborious purification and identification procedures. 242 peptides binding to α-glycosidase were quickly screened and identified by bio-affinity ultrafiltration combined with LC-MS/MS from the double enzymatic hydrolysate of black beans. Top three peptides with notable anti-α-glucosidase activity, NNNPFKF, RADLPGVK and FLKEAFGV were further rapidly screened and ranked by the three artificial intelligence tools (three-AI-tool) BIOPEP database, PeptideRanker and molecular docking from the 242 peptides. Their IC50 values were in order as 4.20 ± 0.11 mg/mL, 2.83 ± 0.03 mg/mL, 1.32 ± 0.09 mg/mL, which was opposite to AI ranking, for the hydrophobicity index of the peptides was not included in the screening criteria. According to the kinetics, FT-IR, CD and ITC analyses, the binding of the three peptides to α-glucosidase is a spontaneous and irreversible endothermic reaction that results from hydrogen bonds and hydrophobic interactions, which mainly changes the α-helix structure of α-glucosidase. The peptide-activity can be evaluated vividly by AFM in vitro. In vivo, the screened FLKEAFGV and RADLPGVK can lower blood sugar levels as effectively as acarbose, they are expected to be an alternative to synthetic drugs for the treatment of Type 2 diabetes.

Compressive sensing beamforming based on covariance for acoustic imaging with noisy measurements.

Compressive sensing, a newly emerging method from information technology, is applied to array beamforming and associated acoustic applications. A compressive sensing beamforming method (CSB-II) is developed based on sampling covariance matrix, assuming spatially sparse and incoherent signals, and then examined using both simulations and aeroacoustic measurements. The simulation results clearly show that the proposed CSB-II method is robust to sensing noise. In addition, aeroacoustic tests of a landing gear model demonstrate the good performance in terms of resolution and sidelobe rejection.

Experimental evaluation of flow-induced noise in level flight of the pigeon (Columba livia).

The experimental method employed in an anechoic wind tunnel to characterize flow-induced noise of the pigeon (Columba livia) during level flight is described in this letter. A live pigeon was managed to maintain a steady level flight at the wind tunnel test flow of 15 m/s. A microphone array was fabricated, and the conventional beamforming method was then adopted to yield the corresponding narrowband acoustic images and broadband sound pressure spectral results. The results justified the experimental method developed in this work. It can be seen that the flight noise of the pigeon is mostly from the wing tips. In addition, the spectral waveform of the pigeon flight suggests a slope of -20 dB/dec between 500 Hz and 5 kHz.

Acoustic imaging of a duct spinning mode by the use of an in-duct circular microphone array.

An imaging method of acoustic spinning modes propagating within a circular duct simply with surface pressure information is introduced in this paper. The proposed method is developed in a theoretical way and is demonstrated by a numerical simulation case. Nowadays, the measurements within a duct have to be conducted using in-duct microphone array, which is unable to provide information of complete acoustic solutions across the test section. The proposed method can estimate immeasurable information by forming a so-called observer. The fundamental idea behind the testing method was originally developed in control theory for ordinary differential equations. Spinning mode propagation, however, is formulated in partial differential equations. A finite difference technique is used to reduce the associated partial differential equations to a classical form in control. The observer method can thereafter be applied straightforwardly. The algorithm is recursive and, thus, could be operated in real-time. A numerical simulation for a straight circular duct is conducted. The acoustic solutions on the test section can be reconstructed with good agreement to analytical solutions. The results suggest the potential and applications of the proposed method.

Influence of mRNA features on siRNA interference efficacy.

Design of small interference RNA (siRNA) is one of the most important steps in effectively applying the RNA interference (RNAi) technology. The current siRNA design often produces inconsistent design results, which often fail to reliably select siRNA with clear silencing effects. We propose that when designing siRNA, one should consider mRNA global features and near siRNA-binding site local features. By a linear regression study, we discovered strong correlations between inhibitory efficacy and both mRNA global features and neighboring local features. This paper shows that, on average, less GC content, fewer stem secondary structures, and more loop secondary structures of mRNA at both global and local flanking regions of the siRNA binding sites lead to stronger inhibitory efficacy. Thus, the use of mRNA global features and near siRNA-binding site local features are essential to successful gene silencing and hence, a better siRNA design. We use a random forest model to predict siRNA efficacy using siRNA features, mRNA features, and near siRNA binding site features. Our prediction method achieved a correlation coefficient of 0.7 in 10-fold cross validation in contrast to 0.63 when using siRNA features only. Our study demonstrates that considering mRNA and near siRNA binding site features helps improve siRNA design accuracy. The findings may also be helpful in understanding binding efficacy between microRNA and mRNA.