A high-density 1,024-channel probe for brain-wide recordings in non-human primates.

Large-scale neural population recordings with single-cell resolution across the primate brain remain challenging. Here we introduce the Neuroscroll probe that isolates single neuronal activities simultaneously from 1,024 densely spaced channels that are flexibly distributed across the shank of the probe. The Neuroscroll probe length is easily tunable for individual probes from 10 mm to 90 mm, covering the brain size of non-human primates and humans, and the probes remain intact and functional after repeated bending deformations. The Neuroscroll probes provided reliable recordings from large neural populations with high chronic stability up to 105 weeks in rats. Recording with each Neuroscroll probe yielded hundreds of well-isolated single units simultaneously from multiple brain regions distributed across the entire depth of the rhesus macaque brain. With the thousand simultaneously recorded channels, unprecedented probe length, excellent mechanical stability and flexible recording site distribution, the Neuroscroll probes enable a wide range of new experimental paradigms in system neuroscience studies with great versatility.

Cellulose Nanofiber Films with Gold Nanoparticles Electrostatically Adsorbed for Facile Surface-Enhanced Raman Scattering Detection.

Cellulose nanofiber (CNF) holds great promise in applications such as surface-enhanced Raman scattering (SERS), catalysis, esthesia, and detection. This study aimed to build novel CNF-based SERS substrates through a facile synthetic method. Citrate-reduced gold nanoparticles (AuNPs) were adsorbed on the cationized CNF surface due to electrostatic interactions, and uniform AuNPs@(2,3-epoxypropyl trimethylammonium chloride)EPTMAC@CNF flexible SERS substrates were prepared by a simple vacuum-assisted filtration method. The probe molecule methylene blue was chosen to assess the performance of the CNF-based SERS substrate with a sensitivity up to 10-9 M, superior signal reproducibility (relative standard deviation (RSD) = 4.67%), and storage stability (more than 30 days). Tensile strength tests indicated that the CNF-based films had good mechanical properties. In addition, CNF-based substrates can easily capture and visually identify microplastics in water. These results demonstrate the potential application of the flexible, self-assembled AuNPs@EPTMAC@CNF flexible SERS substrate for prompt and sensitive detection of trace substances.

Changes in the characteristic volatile aromatic compounds in tuna cooking liquid during fermentation and deodorization by Lactobacillus plantarum RP26 and Cyberlindnera fabianii JGM9-1.

Tuna cooking liquid has unpleasant aroma. In our previous studies, Cyberlindnera fabianii JGM9-1 and Lactobacillus plantarum RP26 demonstrated the ability to degrade this unpleasant aroma. However, the mechanism of microbial deodorization remains unclear. In this study, tuna cooking liquid was fermented using JGM9-1 alone, RP26 alone, and a combination of both strains. Changes in volatile aromatic compounds during fermentation were analyzed using HS-SPME-GC/MS. The unpleasant aroma of tuna cooking liquid were nine characteristic aromatic compounds associated with fishy, stinky, and greasy aromas. Furthermore, we found that the fermentation of microbes removed these unpleasant aromatic compounds and replaced them with pleasant aromatic compounds that contributed to fruity, grassy, and floral aromas. Finally, we screened 21 strong pairwise correlations between the production and consumption of characteristic volatile aromatic compounds by RP26 and JGM9-1, through HCA, VIP, OAV and Spearman's pairwise correlation analysis. These results help to clarify the metabolic mechanisms of microbial deodorization in tuna cooking liquid.

Component identification for the SERS spectra of microplastics mixture with convolutional neural network.

With the increasing interest in microplastics (MPs) pollutants, relevant detection technologies are also developing. In MPs analysis, vibrational spectroscopy represented by surface-enhanced Raman spectroscopy (SERS) is widely used because they can provide unique fingerprint characteristics of chemical components. However, it is still a challenge to separate various chemical components from the SERS spectra of MPs mixture. In this study, it is innovatively proposed to combine the convolutional neural networks (CNN) model to simultaneously identify and analyze each component in the SERS spectra of six common MPs mixture. Different from the traditional method, which requires a series of spectral preprocessing such as baseline correction, smoothing and filtering, the average identification accuracy of MP components is as high as 99.54 % after the unpreprocessed spectral data is trained by CNN, which is better than other classical algorithms such as support vector machine (SVM), principal component analysis linear discriminant analysis (PCA-LDA), partial least squares discriminant analysis (PLS-DA), Random Forest (RF), and K Near Neighbor (KNN), with or without spectral preprocessing. The high accuracy shows that CNN can be used to quickly identify MPs mixture with unpreprocessed SERS spectra data.

Changes in characteristic volatile aroma substances during fermentation and deodorization of Gracilaria lemaneiformis by lactic acid bacteria and yeast.

Gracilaria lemaneiformis is a source of several bioactive natural products in China. Previously, we obtained Saccharomyces cerevisiae JJ4 and Lactobacillus paracasei paracasei RP38, that reduced the fishy odor of G. lemaneiformis. However, the associated deodorization mechanisms remain unclear. Here, G. lemaneiformis was fermented using single strain JJ4, single strain RP38, and both strains together. Dynamic changes in volatile aroma substances during fermentation were measured using HS-SPME-GC/MS. We found that the unpleasant aromas of raw G. lemaneiformis were primarily due to 3-octanone, cyclooctanol, and 1-methylcycloheptanol. Fermentation with lactic acid bacteria and yeast could reduce the substances associated with unpleasant aromas. The potentially characteristic aromatic substances consumed and produced by the different strains were determined using Opls-da and Spearman's correlations with VIP value >1 and |r| > 0.6. These results help to clarify the metabolic mechanisms by which different microbes reduce the fishy smell of G. lemaneiformis.

[The role of the ubiquitin proteasome system and PP2A in spermatogenesis].

The ubiquitin proteasome system (UPS) plays an important role in cell degradation, and is involved in many biological processes such as cell cycle regulation, immune response, DNA damage repair, and signal transduction. It also acts a crucial part in spermatogenesis by selectively degrading proteins and regulating such processes as DNA repair and protamine histone replacement. PP2A, as an essential serine/threonine phosphatase, participates in a variety of life activities. Studies have shown the involvement of UPS in the ubiquitination regulation of PP2A and that of PP2A in several stages of meiosis. This review updates the roles of UPS and PP2A in spermatogenesis.

A gold nanoparticle doped flexible substrate for microplastics SERS detection.

Due to overuse of plastic products, decomposed microplastics (MPs) are widely spread in aquatic ecosystems, and will cause irreparable harm to the human body through the food chain. Traditional MP detection methods require cumbersome sample pre-processing procedures and complex instruments, so there is an urgent demand to develop methods to achieve simple on-site detection. Herein, a simple, sensitive, accurate, and stable MP detection method based on surface-enhanced Raman scattering (SERS) is investigated. Considering the hydrophobic problems of MPs, gold nanoparticle (AuNP) doped filter paper as a flexible SERS substrate is applied to capture MPs in the fiber pores. Benefitting from the electromagnetic (EM) hot spots generated by AuNPs, the Raman signal of MPs can be effectively enhanced. Meanwhile, the flexible SERS substrate has good sensitivity to a minimum detectable concentration of 0.1 g L-1 for polyethylene terephthalate (PET) in water, and the maximum enhancement factor (EF) can reach 360.5. Furthermore, the practicability of the developed method has been proved by the successful detection of MPs in tap water and pond water. This research provides an easy process, high sensitivity, and good reproducibility method for MP detection.

Gold nanospheres assembly via corona discharge technique for flexible SERS substrate.

Noble metal nanoparticles (NMNPs) assembly substrates with strongly enhanced local electromagnetic fields provide new possibilities for surface-enhanced Raman spectroscopy (SERS) sensing. Although the external-electric-field-based self-assembly (EEFSA) strategy for decreasing NMNP gap in liquid phase is relatively developed, it is rarely described in solid phase. Here, by combining corona discharge technique (CDT) as a simple EEFSA approach on flexible substrate surface modification, a flexible SERS substrate medicated with gold nanospheres (AuNSs) is produced. Because of the CDT's peculiar discharge event, makes AuNSs aggregation simply achieved. The modified flexible SERS substrate is sensitive to the detection limit of ∼10-5 mM for Rhodamine 6G (R6G), with a maximum enhancement factor of 2.79×106. Furthermore, finite-difference time-domain (FDTD) simulation confirms the SERS enhancement impact of AuNSs-based substrate. This study not only provides a low-cost, simple-to-process, high-yield, high sensitivity, and activity flexible SERS substrate, but also suggests a more practical and adaptable NMNPs self-assembly approach.

Investigation on enhanced mathematical morphological operators for bearing fault feature extraction.

Morphological filtering has been extensively applied to rotating machinery diagnostics, whereas traditional morphological operators cannot effectively extract fault-triggered transient impulse components from noisy mechanical vibration signal. In this paper, a framework of generalized compound morphological operator (GCMO) is presented to enhance the extraction ability of impulsive fault features. Further, several new compound morphological operators are developed for transient impulse extraction by introducing the product, convolution, and cross-correlation operations into the GCMO framework. In addition, a novel strategy for selecting the structural element length is proposed to optimize the repetitive impulse feature extraction of the compound morphological operators. The fault feature extraction performance of the developed compound morphological operators is investigated and validated on the simulation signals and measured railway bearing vibration signals, and compared with the combined morphological operators and five existing feature extraction methods. The results demonstrate that the morphological cross-correlation operators are more efficient in repetitive fault impulse feature extraction and bearing fault diagnosis than the combined morphological operators and the comparison methods.

Optimal frequency band selection using blind and targeted features for spectral coherence-based bearing diagnostics: A comparative study.

Identifying a spectral frequency band with abundant fault information from spectral coherence is essential for improved envelope spectrum-based bearing diagnosis. Both blind features and targeted features have been employed to distinguish informative spectral frequency band of spectral coherence. However, how to select appropriate feature to correctly discriminate the optimal frequency band of spectral coherence in different scenarios is problematic. In this study, a new targeted feature is presented to quantify the signal-to-noise ratio in narrow frequency bands of spectral coherence, and further a method based on the proposed feature is developed to distinguish an optimal spectral frequency band of spectral coherence for bearing diagnostics. The efficiency of the developed method, typical blind feature-based methods and typical targeted feature-based methods in identifying the defect-sensitive frequency band of spectral coherence and bearing fault diagnosis is validated and compared using simulated signals with different interference noises and bearing experimental signals. The advantages and limitations of typical blind and targeted feature-based methods in different scenarios are summarized to guide the application. The results demonstrate that the developed targeted feature can efficiently evaluate bearing failure information in the cyclic frequency domain, and the presented approach can accurately discriminate the failure-related spectral frequency band of spectral coherence and detect different bearing faults compared with the methods based on the state-of-the-art features.

Weigh-in-Motion System Based on an Improved Kalman and LSTM-Attention Algorithm.

A weigh-in-motion (WIM) system continuously and automatically detects an object's weight during transmission. The WIM system is used widely in logistics and industry due to increasing labor and time costs. However, the accuracy and stability of WIM system measurements could be affected by shock and vibration under high speed and heavy load. A novel six degrees-of-freedom (DOF), mass-spring damping-based Kalman filter with time scale (KFTS) algorithm was proposed to filter noise due to the multiple-input noise and its frequency that is highly coupled with the basic sensor signal. Additionally, an attention-based long short-term memory (LSTM) model was built to predict the object's mass by using multiple time-series sensor signals. The results showed that the model has superior performance compared to support vector machine (SVM), fully connected network (FCN) and extreme gradient boosting (XGBoost) models. Experiments showed this improved deep learning model can provide remarkable accuracy under different loads, speed and working situations, which can be applied to the high-precision logistics industry.

Self-Organized Fractal Structures on Plasma-Exposed Silver Surface.

Planar fractal microstructure is observed on the silver film treated by positive corona discharge for the first time. Due to the abundant positive ions driven by the electrical field of positive polarity, surface modification is mainly induced by the plasma oxidation effect, resulting in a large scale of dendritic pattern with self-similarity and hierarchy. In contrast, negative ions dominate the plasma-film interaction under negative corona discharge condition, leading to a different surface morphology without fractal characteristics. A growth model based on the modified diffusion-limited aggregation (DLA) theory is proposed to describe the formation of the dendritic fractal structure, whilst the physics behind is attributed to the electric field directed diffusion of the positive ions around the surface roughness. Numerical simulation verifies the high density of the hot spot in the dendritic pattern, which may enable potential applications in fractal photonic metamaterials.

Short communication: Chemical structure, concentration, and pH are key factors influencing antimicrobial activity of conjugated bile acids against lactobacilli.

Effects of chemical structure, concentration, and pH on antimicrobial activity of conjugated bile acids were investigated in 4 strains of lactobacilli. Considerable differences were observed in the antimicrobial activity between the 6 human conjugated bile acids, including glycocholic acid, taurocholic acid, glycodeoxycholic acid, taurodeoxycholic acid, glycochenodeoxycholic acid, and taurochenodeoxycholic acid. Glycodeoxycholic acid and glycochenodeoxycholic acid generally showed significantly higher antimicrobial activity against the lactobacilli, but glycocholic acid and taurocholic acid exhibited the significantly lower antimicrobial activity. Glycochenodeoxycholic acid was selected for further analysis, and the results showed its antimicrobial activity was concentration-dependent, and there was a significantly negative linear correlation (R2 > 0.98) between bile-antimicrobial index and logarithmic concentration of the bile acid for each strain of lactobacilli. Additionally, the antimicrobial activity of glycochenodeoxycholic acid was also observed to be pH-dependent, and it was significantly enhanced with the decreasing pH, with the result that all the strains of lactobacilli were unable to grow at pH 5.0. In conclusion, chemical structure, concentration, and pH are key factors influencing antimicrobial activity of conjugated bile acids against lactobacilli. This study provides theoretical guidance and technology support for developing a scientific method for evaluating the bile tolerance ability of potentially probiotic strains of lactobacilli.

Pectin-microfibrillated cellulose microgel: Effects on survival of lactic acid bacteria in a simulated gastrointestinal tract.

Using high pressure microfluidization, we prepared micro-fibrillated soybean cellulose (MFSC) and analyzed its morphology and structure. MFSC was then incorporated into low-methoxyl pectin (PC) to coat lactic acid bacteria (LAB) by ionotropic gelation, and the effects of PC-MFSC microgel on LAB survival in a simulated gastrointestinal tract were investigated. Particle size analysis showed that the MFSC particle size decreased significantly with increasing jet pressure. Transmission electron microscopy analysis indicated that many cellulosic microfibers appeared at 150 MPa. Infrared spectroscopy and X-ray diffraction analysis revealed that the crystal structure changed from ß-cellulose I type to II type with increasing jet pressure, but excessive pressure (200 MPa) damaged the crystalline structure of MFSC. Scanning microscopy indicated that cellulosic microfibers not only promoted a compact pectin gel morphology but also adhered to and coated the LAB in the pectin gel. MFSC-150 stabilized the pectin gel network, preventing the weakening of the gel under low pH conditions. Compared with other PC-MFSCs, PC-MFSC-150 microgel significantly decreased LAB susceptibility to gastrointestinal juice and increased the viability of LAB.

Insight into the formation, structure and digestibility of lotus seed amylose-fatty acid complexes prepared by high hydrostatic pressure.

Lotus seed amylose-fatty acid complexes were prepared using high hydrostatic pressure and the relationship between their structural properties and digestibility was investigated. The formation of lotus seed amylose-fatty acid complexes increased the values of weight molar mass (Mw), number molar mass (Mn), polydispersity index and resistant starch content compared to those of amylose controls. Mw and Mn values of lotus seed amylose and complexes decreased with an increase in high hydrostatic pressure from 500 MPa to 600 MPa, suggesting that the lotus seed amylose was decomposed into short glucan chains. The presence of single helical lotus seed amylose-fatty acid complexes and double helical retrograded amylose was investigated using Raman spectroscopy and imaging. The results from Raman spectra and in vitro digestion showed that the content of both single helical LSA-fatty acid complexes and double helical retrograded LSA were responsible for digestibility of the complex matrix.

An improved complementary ensemble empirical mode decomposition with adaptive noise and its application to rolling element bearing fault diagnosis.

A novel time-frequency analysis method called complementary complete ensemble empirical mode decomposition (EEMD) with adaptive noise (CCEEMDAN) is proposed to analyze nonstationary vibration signals. CCEEMDAN combines the advantages of improved EEMD with adaptive noise and complementary EEMD, and it improves decomposition performance by reducing reconstruction error and mitigating the effect of mode mixing. However, because white noise mixed in with the raw vibration signal covers the whole frequency bandwidth, each mode inevitably contains some mode noise, which can easily inundate the fault-related information. This paper proposes a time-frequency analysis method based on CCEEMDAN and minimum entropy deconvolution (MED) for fault detection of rolling element bearings. First, a raw signal is decomposed into a series of intrinsic mode functions (IMFs) by using the CCEEMDAN method. Then a sensitive parameter (SP) based on adjusted kurtosis and Pearson's correlation coefficient is applied to select a sensitive mode that contains the most fault-related information. Finally, the MED is applied to enhance the fault-related impulses in the selected IMF. The fault signals of high-speed train axle-box bearing are applied to verify the effectiveness of the proposed method. Results show that the proposed method can effectively reveal axle-bearing defects' fault information. The comparisons illustrate the superiority of SP over kurtosis for selecting the sensitive mode from the resulted signal of CCEEMEDAN. Further, we conducted comparisons that highlight the superiority of our proposed method over individual CCEEMDAN and MED methods and over two other popular signal-processing methods, variational mode decomposition and fast kurtogram.

Reaction kinetics of phenols and p-nitrophenols in flowing aerated aqueous solutions generated by a discharge plasma jet.

In this paper, we propose a method for removing phenols and p-nitrophenols (PNPs) from flowing aqueous solutions generated by atmospheric pressure plasma jets (APPJs). For analyzing the removal characteristics, multiple techniques were used, including flow speed analysis of the aerated solution, optical emission spectroscopy (OES), and liquid chromatography. In addition, the reaction kinetics of diffusion and activation control processes were evaluated using aerated fluid speed variation and the corresponding activation energy. From these results, the relative intensities of hydroxyl radicals produced by an APPJ in water were found to be stronger than those in air and to decrease with increasing flow speed. Furthermore, the reaction kinetics were found to be diffusion-controlled when the solution flow speed was low and activation-controlled under high solution flow speed. It was also found that the degradation efficiency was enhanced with increasing flow speed, which increased the discharge voltage and temperature of the solution and changed the initial pH value when TiO2/UV catalysis was used. From the complex relationship between the reactive species, fluid diffusion, and discharge parameters in wastewater described herein, it is anticipated that these findings will facilitate new approaches to both the design and optimization of discharge reactors intended for wastewater treatment.

Understanding the crystal structure of lotus seed amylose-long-chain fatty acid complexes prepared by high hydrostatic pressure.

This paper presents an innovative approach using high hydrostatic pressure to prepare lotus seed amylose-long-chain fatty acid (stearic acid, oleic acid, and linoleic acid) complexes. The aim of this work was to investigate the spherocrystal structure and distribution of fatty acid within complexes. Wide-angle X-ray diffraction diffractograms indicated the presence of typical V6-type polymorphs and B-type non-complexed amylose. The V6-type complexes were further confirmed as V6III polymorph from nuclear magnetic resonance. The degree of crystallinity and the complex index value decreased as the preparation pressure of the complexes increased, and the amylose-oleic acid complexes exhibited the highest relative crystallinity and complex index value in all of the conditions. Small-angle X-ray scattering indicated a larger proportion of crystalline and more compact structure within complexes than that of lotus seed amylose. The morphology of complexes with the spherulite form was determined from scanning electron microscopy images, and the distribution of fatty acid molecules within the spherulites of complexes was estimated using nuclear magnetic resonance, confocal laser scanning microscopy, and small-angle X-ray scattering. The results demonstrated that the fatty acids were within and between the amylose helix, and they were also trapped inside the amorphous lamellae of the complexes. This work provides an in-depth study of the spherocrystal structure within lotus seed amylose-long-chain fatty acid complexes and proposes a new model for spherulites.

Structural and thermal properties of amylose-fatty acid complexes prepared via high hydrostatic pressure.

An innovative approach of high hydrostatic pressure was used to prepare lotus seed amylose-fatty acid complexes. The objective of this study was to investigate their structure and thermal properties. WAXD pattern of amylose changed from B-type to B- and V6-type hybrid polymorphs, and its relative crystallinity increased upon the addition of fatty acids. Carboxyl group observed by FTIR indicates the formation of complexes. SAXS was performed to measure the lamellar structure of complexes. The complexes were more compact and had lower amounts of amorphous regions compared with amylose controls. Entrapped fatty acids, higher melting temperature, and enthalpy change of complexes but not of the controls were detected by DSC. The distribution of fatty acid molecules in the complex matrix was estimated through NMR. Under different pressures, the complexes exhibited dissimilar characteristics with the increase in aliphatic chain length, as observed by WAXD, FTIR, DSC and NMR.

Slowly digestible properties of lotus seed starch-glycerine monostearin complexes formed by high pressure homogenization.

Starch-lipid complexes were prepared using lotus seed starch (LS) and glycerin monostearate (GMS) via a high-pressure homogenization process, and the effect of high pressure homogenization (HPH) on the slow digestion properties of LS-GMS was investigated. The digestion profiles showed HPH treatment reduced the digestive rate of LS-GMS, and the extent of this change was dependent on homogenized pressure. Scanning electron microscopy displayed HPH treatment change the morphology of LS-GMS, with high pressure producing more compact block-shape structure to resist enzyme digestion. The results of Gel-permeation chromatography and Small-angle X-ray scattering revealed high homogenization pressure impacted molecular weight distribution and semi-crystalline region of complexes, resulting in the formation of new semi-crystalline with repeat unit distance of 16-18 nm and molecular weight distribution of 2.50-2.80 × 105 Da, which displayed strong enzymatic resistance. Differential scanning calorimeter results revealed new semi-crystalline lamellar may originate from type-II complexes that exhibited a high transition temperature.