Efficient Screening of nNOS-PSD95 Uncoupling Agents Based on Radiometric Fluorescent Molecularly Imprinted Sensors

Novel and efficient ratiometric fluorescent molecularly imprinted sensors (RFMIS) based on epitopes were developed, which can be used for the sensitive detection of neuronal nitric oxide synthase in the screening of neuronal nitric oxide synthase-postsynaptic density95 (nNOS-PSD95) coupling inhibitors. Under appropriate conditions, the fluorescence of the carbon dots quenched with the increasing concentration of nNOS1-133, while the fluorescence of the quantum dots remained unchanged. The fluorescence ratio had a good linearity in the concentration range of 0-500 ng mL-1 for nNOS1-133 and the determination limit was 0.14 ng mL-1. Using the classical nNOS-PSD95 coupling inhibitor (ZL006) as a control, the RFMIS were used as the detector to detect the free nNOS released by Gnetol and 2,3,5,4ʹ-tetrahydroxystilbene-2-O-β-Dglucoside from natural medicine after inhibition of nNOS-PSD95. The results have shown that the uncoupling efficiencies was consistent with co-immunoprecipitation experiments. The study provides a new idea and a new way for efficient screening of nature nNOS-PSD95 coupling inhibitors from natural medicine with the advantages of high efficiency, sensitivity and traceability

Preparation and Characterization of Epitope-Based Ratiometric Fluorescent Molecularly Imprinted Polymers

In order to solve the problem of difficult detection of neuronal nitric oxide synthase in the screening of neuronal nitric oxide synthase-postsynaptic density95 (nNOS-PSD95) uncoupling agent, this study used 133 amino acids (nNOS1-133) at the nitrogen terminal of nNOS as template molecules, carbon dots and quantum dots as ratio fluorescence recognition elements, SiO2 as matrix for the first time, combined with surface molecular imprinting technology and antigen-determining principle, to prepare ratiometric flurescent molecularly imprinted polymers (RFMIPs). The resulting RFMIPs were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy and thermogravimetric analysis，exhibiting uniform spherical morphology, which unambiguously confirmed the successful formation of the nanosensor. The result indicates that the synthesized sensors have promising potential for the assay of trace peptides in complex matrices

READS-V: Real-time Automated Detection of Epileptic Seizures from Surveillance Videos via Skeleton-based Spatiotemporal ViG

An accurate and efficient epileptic seizure onset detection system can significantly benefit patients. Traditional diagnostic methods, primarily relying on electroencephalograms (EEGs), often result in cumbersome and non-portable solutions, making continuous patient monitoring challenging. The video-based seizure detection system is expected to free patients from the constraints of scalp or implanted EEG devices and enable remote monitoring in residential settings. Previous video-based methods neither enable all-day monitoring nor provide short detection latency due to insufficient resources and ineffective patient action recognition techniques. Additionally, skeleton-based action recognition approaches remain limitations in identifying subtle seizure-related actions. To address these challenges, we propose a novel skeleton-based spatiotemporal vision graph neural network (STViG) for efficient, accurate, and timely REal-time Automated Detection of epileptic Seizures from surveillance Videos (READS-V). Our experimental results indicate STViG outperforms previous state-of-the-art action recognition models on our collected patients' video data with higher accuracy (5.9% error) and lower FLOPs (0.4G). Furthermore, by integrating a decision-making rule that combines output probabilities and an accumulative function, our READS-V system achieves a 5.1 s EEG onset detection latency, a 13.1 s advance in clinical onset detection, and zero false detection rate.Comment: 12 pages, 8 figures, 8 table

Model-Driven Based Deep Unfolding Equalizer for Underwater Acoustic OFDM Communications

It is challenging to design an equalizer for the complex time-frequency doubly-selective channel. In this paper, we employ the deep unfolding approach to establish an equalizer for the underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) system, namely UDNet. Each layer of UDNet is designed according to the classical minimum mean square error (MMSE) equalizer. Moreover, we consider the QPSK equalization as a four-classification task and adopt minimum Kullback-Leibler (KL) to achieve a smaller symbol error rate (SER) with the one-hot coding instead of the MMSE criterion. In addition, we introduce a sliding structure based on the banded approximation of the channel matrix to reduce the network size and aid UDNet to perform well for different-length signals without changing the network structure. Furthermore, we apply the measured at-sea doubly-selective UWA channel and offshore background noise to evaluate the proposed equalizer. Experimental results show that the proposed UDNet performs better with low computational complexity. Concretely, the SER of UDNet is nearly an order of magnitude lower than that of MMSE

Strategies and challenges with the microbial conversion of methanol to high-value chemicals

As alternatives to traditional fermentation substrates, methanol (CH3OH), carbon dioxide (CO2) and methane (CH4) represent promising one-carbon (C1) sources that are readily available at low-cost and share similar metabolic pathway. Of these C1 compounds, methanol is used as a carbon and energy source by native methylotrophs, and can be obtained from CO2 and CH4 by chemical catalysis. Therefore, constructing and rewiring methanol utilization pathways may enable the use of one-carbon sources for microbial fermentations. Recent bioengineering efforts have shown that both native and nonnative methylotrophic organisms can be engineered to convert methanol, together with other carbon sources, into biofuels and other commodity chemicals. However, many challenges remain and must be overcome before industrial-scale bioprocessing can be established using these engineered cell refineries. Here, we provide a comprehensive summary and comparison of methanol metabolic pathways from different methylotrophs, followed by a review of recent progress in engineering methanol metabolic pathways in vitro and in vivo to produce chemicals. We discuss the major challenges associated with establishing efficient methanol metabolic pathways in microbial cells, and propose improved designs for future engineering

Application of Sliding Mode Trajectory Tracking Control Design for Two-Wheeled Mobile Robots

A trajectory tracking controller is proposed to drive the wheeled mobile robot (WMR) to follow a predefined trajectory robustly within a finite time under the presence of uncertainties. The two-wheeled mobile robot and tracking error system are modelled by kinematic equations, the stability and reachability of the sliding mode controller are analysed based on the system models. A two-wheeled mobile robot is built by using the STM32F407 (ARM Cortex-M4 microcontroller) board and a MATLAB GUI, and a cooperative real-time operating system are implemented by using C programming language in order to provide convenient system configuration and improve the overall tracking performance. It is demonstrated that the line and circular trajectories are well tracked in simulation and experiment

The Pichia pastoris transmembrane protein GT1 is a glycerol transporter and relieves the repression of glycerol on AOX1 expression

Promoter of alcohol oxidase I (PAOX1) is the most efficient promoter involved in the regulation of recombinant protein expression in Pichia pastoris (P. pastoris). PAOX1 is tightly repressed by the presence of glycerol in the culture medium; thus, glycerol must be exhausted before methanol can be taken up by P. pastoris and the expression of the heterologous protein can be induced. In this study, a candidate glycerol transporter (GT1, GeneID: 8197545) was identified, and its role was confirmed by further studies (e.g. bioinformatics analysis, heterologous complementation in Schizosaccharomyces pombe (S. pombe)). When GT1 is co-expressed with enhanced green fluorescent protein (EGFP), it localizes to the membrane and S. pombe carrying gt1 but not the wild-type strain can grow on medium containing glycerol as the sole carbon source. The present study is the first to report that AOX1 in the X-33gt1 mutant can achieve constitutive expression in medium containing glycerol; thus, knocking down gt1 can eliminate the glycerol repression of PAOX1 in P. pastoris. These results suggest that the glycerol transporter may participate in the process of PAOX1 inhibition in glycerol medium

p21-activated kinase is involved in the sporulation, pathogenicity, and stress response of Arthrobotrys oligospora under the indirect regulation of Rho GTPase-activating protein

The p21-GTPase-activated protein kinases (PAKs) participate in signal transduction downstream of Rho GTPases, which are regulated by Rho GTPase-activating proteins (Rho-GAP). Herein, we characterized two orthologous Rho-GAPs (AoRga1 and AoRga2) and two PAKs (AoPak1 and AoPak2) through bioinformatics analysis and reverse genetics in Arthrobotrys oligospora, a typical nematode-trapping (NT) fungus. The transcription analyses performed at different development stages suggested that Aopaks and Aorga1 play a crucial role during sporulation and trap formation, respectively. In addition, we successfully deleted Aopak1 and Aorga1 via the homologous recombination method. The disruption of Aopak1 and Aorga1 caused a remarkable reduction in spore yield and the number of nuclei per cell, but did not affect mycelial growth. In ∆Aopak1 mutants, the trap number was decreased at 48 h after the introduction of nematodes, but nematode predatory efficiency was not affected because the extracellular proteolytic activity was increased. On the contrary, the number of traps in ∆Aorga1 mutants was significantly increased at 36 h and 48 h. In addition, Aopak1 and Aorga1 had different effects on the sensitivity to cell-wall-disturbing reagent and oxidant. A yeast two-hybrid assay revealed that AoPak1 and AoRga1 both interacted with AoRac, and AoPak1 also interacted with AoCdc42. Furthermore, the Aopaks were up-regulated in ∆Aorga1 mutants, and Aorga1 was down-regulated in ∆Aopak1 mutants. These results reveal that AoRga1 indirectly regulated AoPAKs by regulating small GTPases