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The liquid-liquid extraction method using reverse micelles can simultaneously extract lipid and protein of oilseeds, which have become increasingly popular in recent years. However, there are few studies on mass transfer processes and models, which are helpful to better control the extraction process of oils and proteins. In this paper, mass transfer process of peanut protein extracted by bis(2-ethylhexyl) sodium sulfosuccinate (AOT)/isooctane reverse micelles was investigated. The effects of stirring speed (0, 70, 140, and 210 r/min), temperature of extraction (30, 35, 40, 45, and 50 °C), peanut flour particle size (0.355, 0.450, 0.600, and 0.900 mm) and solid-liquid ratio (0.010, 0.0125, 0.015, 0.0175, and 0.020 g/mL) on extraction rate were examined. The results showed that extraction rate increased with temperature rising, particle size reduction as well as solid-liquid ratio increase respectively, while little effect of stirring speed (P > 0.05) was observed. The apparent activation energy of extraction process was calculated as 10.02 kJ/mol and Arrhenius constant (A) was 1.91 by Arrhenius equation. There was a linear relationship between reaction rate constant and the square of the inverse of initial particle radius (1/r02) (P

Abstract Large-scale brain activity mapping is important for understanding the neural basis of behaviour. Electrocorticograms (ECoGs) have high spatiotemporal resolution, bandwidth, and signal quality. However, the invasiveness and surgical risks of electrode array implantation limit its application scope. We developed an ultrathin, flexible shape-changing electrode array (SCEA) for large-scale ECoG mapping with minimal invasiveness. SCEAs were inserted into cortical surfaces in compressed states through small openings in the skull or dura and fully expanded to cover large cortical areas. MRI and histological studies on rats proved the minimal invasiveness of the implantation process and the high chronic biocompatibility of the SCEAs. High-quality micro-ECoG activities mapped with SCEAs from male rodent brains during seizures and canine brains during the emergence period revealed the spatiotemporal organization of different brain states with resolution and bandwidth that cannot be achieved using existing noninvasive techniques. The biocompatibility and ability to map large-scale physiological and pathological cortical activities with high spatiotemporal resolution, bandwidth, and signal quality in a minimally invasive manner offer SCEAs as a superior tool for applications ranging from fundamental brain research to brain-machine interfaces.

Abstract Controlled assembly of nanoparticles (NPs) has garnered much interest over the past two decades. Beyond established techniques, new methods utilizing local short‐range or large‐scale long‐range interactions remain to be explored to achieve diverse micro‐ and nanoscale structures. Here, we report the controlled emergence of vortex‐pair arrays within monodispersed gold nanorods by applying a direct current electric field across a pair of sawtooth electrodes. By employing in situ darkfield microscopy and particle collective analysis, we elucidate the mechanism behind the formation and stabilization of the NP vortices, attributing it to the combined effects of the electrode shape, high NP density, and high solution viscosity. We further explore the controllability of the vortex‐pair arrays and obtain multiple complex vortice patterns. Our findings will facilitate the investigation of efficient and controlled dynamic assembly of NPs under external fields and help manufacture next‐generation optoelectronic functional materials.

In order to enhance the flavor of hydrolysate from the mixture of chicken skeleton and chicken breast, the hydrolysis of chicken skeleton and chicken breast composite substrate was carried out by biological enzymatic hydrolysis technology. The enzymatic hydrolysis process was optimized by single factor experiment and orthogonal experiment. Furthermore, the free amino acid content and molecular weight distribution of peptide in hydrolysates were analyzed. The results pointed out that the flavor of hydrolysate was better using simultaneous hydrolysis with protamex and flavourzyme by the ratio of 3:1. The optimal enzymolysis conditions were as follows: Ratio of chicken skeleton to chicken breast 9:1, solid-liquid ratio 1:2 g/mL, temperature 50 ℃, pH7.5, enzyme dosage 0.6%, and hydrolysis time 3 h. Under these conditions, the hydrolysate had a prominent umami taste, obvious meat flavor and good taste, with hydrolysis degree and sensory score of 13.60% and 4.7, respectively. With the prolongation of enzymatic hydrolysis time, the content of total free amino acids and peptides with low molecular weight increased continuously. Under the optimal process conditions, the content of bitter amino acids in the hydrolysate was 2.74 mg/mL, accounting for 71.73% of the total free amino acids, which were the main amino acids, and the content of peptides with molecular weight less than 3 kDa was 93.26%. The results provide a reference for the comprehensive development and application of low-value chicken skeleton.

Durian contains rich flavor components that undergo complex changes during drying. In this study, durian was subjected to integrated freeze-drying (IFD), conventional freeze-drying (CFD), and hot air drying (AD). Compared with the fresh samples, those dried by IFD, CFD, and AD lost 11, 9, and 7 original volatile compounds, respectively, and generated 7, 6, and 8 new volatile compounds, respectively, and showed a rapid and then slow decreasing trend in the total content during drying. However, the types of amino acids and soluble sugars remained unchanged during each of the drying methods. Furthermore, volatile compounds showed a significant negative correlation with the majority of amino acids and a significant positive correlation with soluble sugars. The IFD samples had the highest content of volatile compounds, amino acids, and soluble sugars. Therefore, IFD is recommended as a preferable drying method for durian.

Mechanisms of sleep remain elusive. Here, authors developed mouse sleep fMRI based on simultaneous electrophysiology and mapped global and sequential state transition patterns, together with global patterns triggered by SWRs in NREM and awake states.

The available treatments for depression have substantial limitations, including low response rates and substantial lag time before a response is achieved. We applied deep brain stimulation (DBS) to the lateral habenula (LHb) of two rat models of depression (Wistar Kyoto rats and lipopolysaccharide-treated rats) and observed an immediate (within seconds to minutes) alleviation of depressive-like symptoms with a high-response rate. Simultaneous functional MRI (fMRI) conducted on the same sets of depressive rats used in behavioral tests revealed DBS-induced activation of multiple regions in afferent and efferent circuitry of the LHb. The activation levels of brain regions connected to the medial LHb (M-LHb) were correlated with the extent of behavioral improvements. Rats with more medial stimulation sites in the LHb exhibited greater antidepressant effects than those with more lateral stimulation sites. These results indicated that the antidromic activation of the limbic system and orthodromic activation of the monoaminergic systems connected to the M-LHb played a critical role in the rapid antidepressant effects of LHb-DBS. This study indicates that M-LHb-DBS might act as a valuable, rapid-acting antidepressant therapeutic strategy for treatment-resistant depression and demonstrates the potential of using fMRI activation of specific brain regions as biomarkers to predict and evaluate antidepressant efficacy.

Peanut oil body emulsion occurs during the process of aqueous enzymatic extraction (AEE). The free oil is difficult to release and extract because its structure is stable and not easily destroyed. Demulsification can release free oil in an oil body emulsion, so various fatty acids were selected for the demulsification. Changes in the amount of heptanoic acid added, solid–liquid ratio, reaction temperature, and reaction time were adopted to investigate demulsification, and the technological conditions of demulsification were optimized. While the optimal conditions were the addition of 1.26% of heptanoic acid, solid–liquid ratio of 1:3.25, reaction temperature of 72.7 °C, and reaction time of 55 min, the maximum free oil yield was (95.84 ± 0.19)%. The analysis of the fatty acid composition and physicochemical characterization of peanut oils extracted using four methods were studied during the AEE process. Compared with the amount of oil extracted via other methods, the unsaturated fatty acids of oils extracted from demulsification with heptanoic acid contained 78.81%, which was significantly higher than the other three methods. The results of physicochemical characterization indicated that the oil obtained by demulsification with heptanoic acid had a higher quality. According to the analysis of the amino acid composition, the protein obtained using AEE was similar to that of commercial peanut protein powder (CPPP). However, the essential amino acid content of proteins extracted via AEE was significantly higher than that of CPPP. The capacity of water (oil) holding, emulsifying activity, and foaming properties of protein obtained via AEE were better than those for CPPP. Overall, heptanoic acid demulsification is a potential demulsification method, thus, this work provides a new idea for the industrial application of simultaneous separation of oil and proteins via AEE.

The task of referring expression comprehension (REC) is to localise an image region of a specific object described by a natural language expression, and all existing REC methods assume that the object described by the referring expression must be located in the given image. However, this assumption is not correct in some real applications. For example, a visually impaired user might tell his robot ‘please take the laptop on the table to me’. In fact, the laptop is not on the table anymore. To address this problem, the authors propose a novel REC model to deal with the situation where expression‐image mismatching occurs and explain the mismatching by linguistic feedback. The authors' REC model consists of four modules: the expression parsing module, the entity detection module, the relationship detection module, and the matching detection module. They built a data set called NP‐RefCOCO+ from RefCOCO+ including both positive samples and negative samples. The positive samples are original expression‐image pairs in RefCOCO+. The negative samples are the expression‐image pairs in RefCOCO+, whose expressions are replaced. They evaluate the model on NP‐RefCOCO+ and the experimental results show the advantages of their method for dealing with the problem of expression‐image mismatching.

Combination of fMRI and deep brain stimulation (DBS) allows for large-scale mapping of brain responses to DBS. Here the authors develop highly MRI compatible graphene fiber electrodes for full brain activation pattern mapping under DBS in Parkinsonian rats.

Implantable brain electrophysiology electrodes are valuable tools in both fundamental and applied neuroscience due to their ability to record neural activity with high spatiotemporal resolution from shallow and deep brain regions. Their use has been hindered, however, by the challenges in achieving chronically stable operations. Furthermore, implantable depth neural electrodes can only carry out limited data sampling within predefined anatomical regions, making it challenging to perform large-area brain mapping. Minimizing inflammatory responses and associated gliosis formation, and improving the durability and stability of the electrode insulation layers are critical to achieve long-term stable neural recording and stimulation. Combining electrophysiological measurements with simultaneous whole-brain imaging techniques, such as magnetic resonance imaging (MRI), provides a useful solution to alleviate the challenge in scalability of implantable depth electrodes. In recent years, various carbon-based materials have been used to fabricate flexible neural depth electrodes with reduced inflammatory responses and MRI-compatible electrodes, which allows structural and functional MRI mapping of the whole brain without obstructing any brain regions around the electrodes. Here, we conducted a systematic comparative evaluation on the electrochemical properties, mechanical properties, and MRI compatibility of different kinds of carbon-based fiber materials, including carbon nanotube fibers, graphene fibers, and carbon fibers. We also developed a strategy to improve the stability of the electrode insulation without sacrificing the flexibility of the implantable depth electrodes by sandwiching an inorganic barrier layer inside the polymer insulation film. These studies provide us with important insights into choosing the most suitable materials for next-generation implantable depth electrodes with unique capabilities for applications in both fundamental and translational neuroscience research.

Electrical impedance tomography (EIT) calculates the internal conductivity distribution of a body using electrical contact measurement and has become increasingly attractive in the biomedical field. However, the design of optimal tomography image reconstruction algorithms has not achieved an adequate level of progress and maturity. The spatial-temporal properties are crucial for the improvement of reconstruction quality and efficiency in dynamic EIT reconstruction. However, these properties have not been fully utilized in previous research. In this paper, a mathematical model for EIT reconstruction is built upon a combination of the low-rank and the sparsity theories. In addition to the low-rank method based on the nuclear norm constraint, the patch-based sparse method is also used to obtain the spatial features of a reconstructed image, according to the characteristic of an irregular boundary for the EIT image. The mathematical model of the new method is solved using the variable split (VS) algorithm. The imaging results are compared with the reconstruction results of the traditional algorithms. The experimental results demonstrate better performance of the new method compared with the traditional methods. The effectiveness of the proposed scheme is verified.

Lemon juice vesicles have abundant flavor components that can undergo complex changes during drying. Three drying methods, including integrated freeze-drying (IFD), conventional freeze-drying (CFD), and hot-air drying (AD), were studied to determine their effects on the dynamic changes in the flavor compounds in lemon juice vesicles. Compared with the fresh samples, the final dried samples that underwent IFD, CFD, and AD lost seven, seven, and six volatile flavor compounds and three, four, and five amino acids, respectively; the order of the loss ratios with respect to the volatile compound content was: 82.73% in CFD > 71.22% in IFD > 28.78% in AD. AD resulted in the highest total amino acid content (10.83 ± 0.20 mg/g), which was 1.39 and 5.54 mg/g higher than that of IFD and CFD, respectively; CFD resulted in the highest total organic acid content (45.94 ± 0.34 mg/g), which was 8.01 and 7.87 mg/g higher than that of IFD and AD, respectively; and AD contributed to the highest total soluble sugars (17.12 ± 0.20 mg/g), which was 1.24 and 1.49 mg/g higher than that of IFD and CFD, respectively. A correlation analysis demonstrated that most of the amino acids and the soluble sugars were closely related to the profiles of the volatile compounds in the lemon juice vesicles during drying.

Electrical impedance tomography (EIT) has been applied in the field of human-computer interaction due to its advantages including the fact that it is non-invasive and has both low power consumption and a low cost. Previous work has focused on static gesture recognition based on EIT. Compared with static gestures, dynamic gestures are more informative and can achieve more functions in human-machine collaboration. In order to verify the feasibility of dynamic gesture recognition based on EIT, a traditional excitation drive pattern is optimized in this paper. The drive pattern of the fixed excitation electrode is tested for the first time to simplify the measurement process of the dynamic gesture. To improve the recognition accuracy of the dynamic gestures, a dual-channel feature extraction network combining a convolutional neural network (CNN) and gated recurrent unit (GRU), namely CG-SVM, is proposed. The new center distance loss is designed in order to simultaneously supervise the intra-class distance and inter-class distance. As a result, the discriminability of the confusing data is improved. With the new excitation drive pattern and classification network, the recognition accuracy of different interference data has increased by 2.7~14.2%. The new method has stronger robustness, and realizes the dynamic gesture recognition based on EIT for the first time.

Membrane module integrity monitoring is essential in the water treatment process. An intelligent detection method for membrane integrity based on array impedance measurement is proposed in the paper. The boundary voltage is collected in real time through the designed electrical sensor array. The Deep Neural Networks (DNN) is used for analyzing the degree of membrane damage based on collected voltage data. In our experiment, six kinds of membrane status are designed to verify the sensors and detection accuracy. Compared with traditional probe electrodes, electrical sensor arrays can obtain the overall condition of membrane inside the pipe without invasion. The membrane state recognition method based on DNN discards the empirical judgment in the traditional measurement method, and realizes intelligent detection by means of deep learning. For the samples obtained from the experiment, the recognition accuracy of this method reaches 94.1%. To illustrate the universality of this method, we performed a real-time detection experiment. As a result, the accuracy of network identification reaches 93.8%.

The electrical response of the eye to optical stimulus is important in disease diagnosis but current electrodes used have limitations. Here, the authors report on the development of soft transparent graphene-based contact lens electrodes for electroretinogram recording and test the device in vivo.

Abstract Background Butyl butyrate has been considered as a promising fuel source because it is a kind of natural ester which can be converted from renewable and sustainable lignocellulosic biomass. Compared with the conventional chemical methods for butyl butyrate production, the enzymatic approach has been demonstrated to be more attractive, mainly owing to the mild reaction conditions, high specificity, low energy consumption, and environmental friendliness. Cutinases play an important role in the butyl butyrate production process. However, the production level of cutinases is still relatively low. Thus, to identify novel cutinases suitable for butyl butyrate synthesis and enhance their yields is of great value in biofuel industry. Results A novel cutinase gene (McCut) was cloned from a thermophilic fungus Malbranchea cinnamomea and expressed in Pichia pastoris. The highest cutinase activity of 12, 536 U/mL was achieved in 5-L fermentor, which is by far the highest production for a cutinase. McCut was optimally active at pH 8.0 and 45 °C. It exhibited excellent stability within the pH range of 3.0–10.5 and up to 75 °C. The cutinase displayed broad substrate specificity with the highest activity towards p-nitrophenyl butyrate and tributyrin. It was capable of hydrolyzing cutin, polycaprolactone, and poly(butylene succinate). Moreover, McCut efficiently synthesized butyl butyrate with a maximum esterification efficiency of 96.9% at 4 h. The overall structure of McCut was resolved as a typical α/β-hydrolase fold. The structural differences between McCut and Aspergillus oryzae cutinase in groove and loop provide valuable information for redesign of McCut. These excellent features make it useful in biosynthesis and biodegradation fields. Conclusions A novel cutinase from M. cinnamomea was identified and characterized for the first time. High-level expression by P. pastoris is by far the highest for a cutinase. The enzyme exhibited excellent stability and high esterification efficiency for butyl butyrate production, which may make it a good candidate in biofuel and chemical industries.

Librarians need feedback from users to improve library services. On the other hand, users need assistance from librarians in order to gain a better understanding of library services. This paper focuses on how Chinese students use U.S. academic libraries’ virtual reference services (VRS), and how academic librarians use VRS. By collecting data from Chinese students and librarians, this paper hopes to create a better understanding of these two factors in order to improve VRS.

Electrical impedance tomography (EIT) is a technique that calculates the distribution of electrical impedance of a living body by measuring the surface voltage of the living body, which is available for continuous monitoring of the lung function to reduce the risk of intensive lung injury. The global inhomogeneity index (GI) is employed to assess the degree of ventilation homogeneity at different levels of lung injury. The GI values calculated in the current research are all based on two-dimensional EIT reconstruction images; however, this method does not correctly detect low levels of lung injury. In this paper, we establish a true 3D thorax model and propose a method for calculating the GI based on 3D EIT reconstruction images to evaluate lung injury. Simulations reveal that this method can accurately reflect the disease state of lung injury compared with the 2D GI calculation method, and even mild damage of lung injury can be adequately detected.

Two hormone-sensitive lipase (HSL) family esterases (RmEstA and RmEstB) from the thermophilic fungus Rhizomucor miehei, exhibiting distinct substrate specificity, have been recently reported to show great potential in industrial applications. In this study, the crystal structures of RmEstA and RmEstB were determined at 2.15 Å and 2.43 Å resolutions, respectively. The structures of RmEstA and RmEstB showed two distinctive domains, a catalytic domain and a cap domain, with the classical α/β-hydrolase fold. Catalytic triads consisting of residues Ser161, Asp262, and His292 in RmEstA, and Ser164, Asp261, and His291 in RmEstB were found in the respective canonical positions. Structural comparison of RmEstA and RmEstB revealed that their distinct substrate specificity might be attributed to their different substrate-binding pockets. The aromatic amino acids Phe222 and Trp92, located in the center of the substrate-binding pocket of RmEstB, blocked this pocket, thus narrowing its catalytic range for substrates (C2–C8). Two mutants (F222A and W92F in RmEstB) showing higher catalytic activity toward long-chain substrates further confirmed the hypothesized interference. This is the first report of HSL family esterase structures from filamentous fungi.jlr The information on structure-function relationships could open important avenues of exploration for further industrial applications of esterases.

With the rapid development of CT technology, especially the higher resolution of CT machine and a sharp increase in the amount of slices, to extract and three-dimensionally display aortic dissection from the huge medical image data became a challenging task. In this paper, active shape model combined with spatial continuity was adopted to realize automatic reconstruction of aortic dissection. First, we marked aortic feature points from big data sample library and registered training samples to build a statistical model. Meanwhile, gray vectors were sampled by utilizing square matrix, which set the landmarks as the center. Posture parameters of the initial shape were automatically adjusted by the method of spatial continuity between CT sequences. The contrast experiment proved that the proposed algorithm could realize accurate aorta segmentation without selecting the interested region, and it had higher accuracy than GVF snake algorithm (93.29% versus 87.54% on aortic arch, 94.30% versus 89.25% on descending aorta). Aortic dissection membrane was extracted via Hessian matrix and Bayesian theory. Finally, the three-dimensional visualization of the aortic dissection was completed by volume rendering based on the ray casting method to assist the doctors in clinical diagnosis, which contributed to improving the success rate of the operations.

BackgroundEsterases with excellent merits suitable for commercial use in ester production field are still insufficient. The aim of this research is to advance our understanding by seeking for more unusual esterases and revealing their characterizations for ester synthesis.Methodology/principal findingsA novel esterase-encoding gene from Rhizomucor miehei (RmEstA) was cloned and expressed in Escherichia coli. Sequence analysis revealed a 975-bp ORF encoding a 324-amino-acid polypeptide belonging to the hormone-sensitive lipase (HSL) family IV and showing highest similarity (44%) to the Paenibacillus mucilaginosus esterase/lipase. Recombinant RmEstA was purified to homogeneity: it was 34 kDa by SDS-PAGE and showed optimal pH and temperature of 6.5 and 45°C, respectively. The enzyme was stable to 50°C, under a broad pH range (5.0-10.6). RmEstA exhibited broad substrate specificity toward p-nitrophenol esters and short-acyl-chain triglycerols, with highest activities (1,480 U mg(-1) and 228 U mg(-1)) for p-nitrophenyl hexanoate and tributyrin, respectively. RmEstA efficiently synthesized butyl butyrate (92% conversion yield) when immobilized on AOT-based organogel.ConclusionRmEstA has great potential for industrial applications. RmEstA is the first reported esterase from Rhizomucor miehei.

Pulmonary edema assessment is a key factor in monitoring and guiding the treatment of critically ill patients. To date, the methods available at the bedside to estimate the physiological correlation of pulmonary edema and extravascular pulmonary fluid are often unreliable or require invasive measurements. The aim of this article is to develop an imaging method of reliably assessing pulmonary edema by utilizing functional electrical impedance tomography. In this article, the Split-Bregman algorithm is used to solve the Total Variation (TV) minimization problem in EIT image reconstruction. A thorax model is constructed according to CT images of rats. Through simulation and experiment, the proposed method improves the quality of reconstructed image significantly compared with existing methods. A pulmonary edema experiment in rats is also carried out. The development of pulmonary edema is analyzed numerically through EIT images. [ABSTRACT FROM AUTHOR]