Glutamine attenuates bisphenol A-induced intestinal inflammation by regulating gut microbiota and TLR4-p38/MAPK-NF-κB pathway in piglets.

Bisphenol A (BPA), as a kind of widely exerted environmental hazardous material, brings toxicity to both humans and animals. This study aimed to investigate the role of glutamine (Gln) in intestinal inflammation and microbiota in BPA-challenged piglets. Thirty-two piglets were randomly divided into four groups according to 2 factors including BPA (0 vs. 0.1%) and Gln (0 vs. 1%) supplemented in basal diet for a 42-day feeding experiment. The results showed BPA exposure impaired piglet growth, induced intestinal inflammation and disturbed microbiota balance. However, dietary Gln supplementation improved the growth performance, while decreasing serum pro-inflammatory cytokine levels in BPA-challenged piglets. In addition, Gln attenuated intestinal mucosal damage and inflammation by normalizing the activation of toll-like receptor 4 (TLR4)-p38/MAPK-nuclear factor-kappa B (NF-κB) pathway caused by BPA. Moreover, dietary Gln supplementation decreased the abundance of Actinobacteriota and Proteobacteria, and attenuated the decreased abundance of Roseburia, Prevotella, Romboutsia and Phascolarctobacterium and the content of short-chain fatty acids in cecum contents caused by BPA exposure. Moreover, there exerted potential relevance between the gut microbiota and pro-inflammatory cytokines and cecal short-chain fatty acids. In conclusion, Gln is critical nutrition for attenuating BPA-induced intestinal inflammation, which is partially mediated by regulating microbial balance and suppressing the TLR4/p38 MAPK/NF-κB signaling.

Histamine Causes Pyroptosis of Liver by Regulating Gut-Liver Axis in Mice.

Huangjiu usually caused rapid-drunkenness and components such as ß-benzyl ethanol (ß-be), isopentanol (Iso), histamine (His), and phenethylamine (PEA) have been reported linked with intoxication. However, the destructive effect of these components on gut microbiota and liver is unclear. In this study, we found oral treatment of these components, especially His, stimulated the level of oxidative stress and inflammatory cytokines in liver and serum of mice. The gut microbiota community was changed and the level of lipopolysaccharide (LPS) increased significantly. Additionally, cellular pyroptosis pathway has been assessed and correlation analysis revealed a possible relationship between gut microbiota and liver pyroptosis. We speculated oral His treatment caused the reprogramming of gut microbiota metabolism, and increased LPS modulated the gut-liver interaction, resulting in liver pyroptosis, which might cause health risks. This study provided a theoretical basis for the effect of Huangjiu, facilitating the development of therapeutic and preventive strategies for related inflammatory disorders.

Light-Driven Molecular Motors Boost the Selective Transport of Alkali Metal Ions through Phospholipid Bilayers.

A hydrophobic light-driven rotary motor is functionalized with two 18-crown-6 macrocycles and incorporated into phospholipid bilayers. In the presence of this molecular construct, fluorescence assays and patch clamp experiments show the formation of selective alkali ion channels through the membrane. Further, they reveal a strongly accelerated ion transport mechanism under light irradiation. This increase of the fractional ion transport activity (up to 400%) is attributed to the out-of-equilibrium actuation dynamics of the light-driven rotary motors, which help to overcome the activation energy necessary to achieve translocation of alkali ions between macrocycles along the artificial channels.

Bilayer versus Polymeric Artificial Water Channel Membranes: Structural Determinants for Enhanced Filtration Performances.

Artificial water channels (AWCs) and their natural aquaporin counterparts selectively transport water. They represent a tremendous source of inspiration to devise biomimetic membranes for several applications, including desalination. They contain variable water-channel constructs with adaptative architectures and morphologies. Herein, we critically discuss the structural details that can impact the performances of biomimetic I quartets, obtained via adaptive self-assembly of alkylureido-ethylimidazoles HC4-HC18 in bilayer or polyamide (PA) membranes. We first explore the performances in bilayer membranes, identifying that hydrophobicity is an essential key parameter to increase water permeability. We compare various I quartets with different hydrophobic tails (from HC4 to HC18), and we reveal that a huge increase in single-channel water permeability, from 104 to 107 water molecules/s/channel, is obtained by increasing the size of the alkyl tail. Quantitative assessment of AWC-PA membranes shows that water permeability increases roughly from 2.09 to 3.85 L m-2 h-1 bar-1, for HC4 and HC6 reverse osmosis membranes, respectively, while maintaining excellent NaCl rejection (99.25-99.51%). Meanwhile, comparable HC8 loading induces a drop of performance reminiscent of a defective membrane formation. We show that the production of nanoscale sponge-like water channels can be obtained with insoluble, low soluble, and low dispersed AWCs, explaining the observed subpar performance. We conclude that optimal solubility enabling breakthrough performance must be considered to not only maximize the inclusion and the stability in the bilayer membranes but also achieve an effective homogeneous distribution of percolated particles that minimizes the defects in hybrid polyamide membranes.

Hydroxy Channels-Adaptive Pathways for Selective Water Cluster Permeation.

Artificial water channels (AWCs) are known to selectively transport water, with ion exclusion. Similarly to natural porins, AWCs encapsulate water wires or clusters, offering continuous and iterative H-bonding that plays a vital role in their stabilization. Herein, we report octyl-ureido-polyol AWCs capable of self-assembly into hydrophilic hydroxy channels. Variants of ethanol, propanediol, and trimethanol are used as head groups to modulate the water transport permeabilities, with rejection of ions. The hydroxy channels achieve a single-channel permeability of 2.33 × 108 water molecules per second, which is within the same order of magnitude as the transport rates for aquaporins. Depending on their concentration in the membrane, adaptive channels are observed in the membrane. Over increased concentrations, a significant shift occurs, initiating unexpected higher water permeation. Molecular simulations probe that spongelike or cylindrical aggregates can form to generate transient cluster water pathways through the bilayer. Altogether, the adaptive self-assembly is a key feature influencing channel efficiency. The adaptive channels described here may be considered an important milestone contributing to the systematic discovery of artificial water channels for water desalination.

Artificial Water Channels: Towards Biomimetic Membranes for Desalination.

Natural Aquaporin (AQP) channels are efficient water translocating proteins, rejecting ions. Inspired by this masterpiece of nature, Artificial Water Channels (AWCs) with controlled functional structures, can be potentially used to mimic the AQPs to a certain extent, offering flexible avenues toward biomimetic membranes for water purification. The objective of this paper is to trace the historical development and significant advancements of current reported AWCs. Meanwhile, we attempt to reveal important structural insights and supramolecular self-assembly principles governing the selective water transport mechanisms, toward innovative AWC-based biomimetic membranes for desalination.

Effects of progesterone on the lipolysis of lipid droplets and prostaglandin E2 synthesis in murine cervical epithelial cells.

Previous studies demonstrated that progesterone (P4) can promote prostaglandin (PG) E2 production; however, how P4 mediates the synthesis of PGE2 remains unclear. In this study, cervical epithelial cells from mice during the follicular phase were cultured invitro and treated with different concentrations of P4 (5, 10, and 20nM). The results of the present study suggest that treatment of murine cervical epithelial cells with 10nM P4 for 24h contributed to: (1) significantly increased expression of protein kinase A (PKA), cytosolic phospholipase A2 (cPLA2) and PGE synthase (PGES)-1; (2) higher phosphorylated (p-) to total extracellular signal-regulated kinase (ERK) 1/2 and hormone-sensitive lipase (HSL) ratios; (3) a significant decrease in the number of lipid droplets (LDs) and fatty acid content within LDs in epithelial cells; and (4) enhanced arachidonic acid and PGE2 levels in cells compared with the control (0nM P4) group (P<0.01 for all findings). In contrast, the PKA inhibitor H89 contributed to significantly decreased cPLA2, PGES-1 and HSL expression, ERK1/2 phosphorylation and arachidonic acid and PGE2 levels, even in the presence of P4. These data show that P4 can act via the PKA/ERK1/2 pathway to stimulate lipolysis of triacylglycerol in the LD core and degradation of phospholipid in the LD membrane to promote PGE2 synthesis in murine cervical epithelial cells.

Molecular dynamics simulations reveal statistics and microscopic mechanisms of water permeation in membrane-embedded artificial water channel nanoconstructs.

Understanding water transport mechanisms at the nanoscale level remains a challenge for theoretical chemical physics. Major advances in chemical synthesis have allowed us to discover new artificial water channels, rivaling with or even surpassing water conductance and selectivity of natural protein channels. In order to interpret experimental features and understand microscopic determinants for performance improvements, numerical approaches based on all-atom molecular dynamics simulations and enhanced sampling methods have been proposed. In this study, we quantify the influence of microscopic observables, such as channel radius and hydrogen bond connectivity, and of meso-scale features, such as the size of self-assembly blocks, on the permeation rate of a self-assembled nanocrystal-like artificial water channel. Although the absolute permeation rate extrapolated from these simulations is overestimated by one order of magnitude compared to the experimental measurement, the detailed analysis of several observed conductive patterns in large assemblies opens new pathways to scalable membranes with enhanced water conductance for the future design.

Fast and Accurate Lane Detection via Graph Structure and Disentangled Representation Learning.

It is desirable to maintain high accuracy and runtime efficiency at the same time in lane detection. However, due to the long and thin properties of lanes, extracting features with both strong discrimination and perception abilities needs a huge amount of calculation, which seriously slows down the running speed. Therefore, we design a more efficient way to extract the features of lanes, including two phases: (1) Local feature extraction, which sets a series of predefined anchor lines, and extracts the local features through their locations. (2) Global feature aggregation, which treats local features as the nodes of the graph, and builds a fully connected graph by adaptively learning the distance between nodes, the global feature can be aggregated through weighted summing finally. Another problem that limits the performance is the information loss in feature compression, mainly due to the huge dimensional gap, e.g., from 512 to 8. To handle this issue, we propose a feature compression module based on decoupling representation learning. This module can effectively learn the statistical information and spatial relationships between features. After that, redundancy is greatly reduced and more critical information is retained. Extensional experimental results show that our proposed method is both fast and accurate. On the Tusimple and CULane benchmarks, with a running speed of 248 FPS, F1 values of 96.81% and 75.49% were achieved, respectively.

Radar Transformer: An Object Classification Network Based on 4D MMW Imaging Radar.

Automotive millimeter-wave (MMW) radar is essential in autonomous vehicles due to its robustness in all weather conditions. Traditional commercial automotive radars are limited by their resolution, which makes the object classification task difficult. Thus, the concept of a new generation of four-dimensional (4D) imaging radar was proposed. It has high azimuth and elevation resolution and contains Doppler information to produce a high-quality point cloud. In this paper, we propose an object classification network named Radar Transformer. The algorithm takes the attention mechanism as the core and adopts the combination of vector attention and scalar attention to make full use of the spatial information, Doppler information, and reflection intensity information of the radar point cloud to realize the deep fusion of local attention features and global attention features. We generated an imaging radar classification dataset and completed manual annotation. The experimental results show that our proposed method achieved an overall classification accuracy of 94.9%, which is more suitable for processing radar point clouds than the popular deep learning frameworks and shows promising performance.

Robust Target Detection and Tracking Algorithm Based on Roadside Radar and Camera.

Intelligent transportation systems (ITSs) play an increasingly important role in traffic management and traffic safety. Smart cameras are the most widely used sensors in ITSs. However, cameras suffer from a reduction in detection and positioning accuracy due to target occlusion and external environmental interference, which has become a bottleneck restricting ITS development. This work designs a stable perception system based on a millimeter-wave radar and camera to address these problems. Radar has better ranging accuracy and weather robustness, which is a better complement to camera perception. Based on an improved Gaussian mixture probability hypothesis density (GM-PHD) filter, we also propose an optimal attribute fusion algorithm for target detection and tracking. The algorithm selects the sensors' optimal measurement attributes to improve the localization accuracy while introducing an adaptive attenuation function and loss tags to ensure the continuity of the target trajectory. The verification experiments of the algorithm and the perception system demonstrate that our scheme can steadily output the classification and high-precision localization information of the target. The proposed framework could guide the design of safer and more efficient ITSs with low costs.

Dynamic Hand Gesture Recognition in In-Vehicle Environment Based on FMCW Radar and Transformer.

Hand gesture recognition technology plays an important role in human-computer interaction and in-vehicle entertainment. Under in-vehicle conditions, it is a great challenge to design gesture recognition systems due to variable driving conditions, complex backgrounds, and diversified gestures. In this paper, we propose a gesture recognition system based on frequency-modulated continuous-wave (FMCW) radar and transformer for an in-vehicle environment. Firstly, the original range-Doppler maps (RDMs), range-azimuth maps (RAMs), and range-elevation maps (REMs) of the time sequence of each gesture are obtained by radar signal processing. Then we preprocess the obtained data frames by region of interest (ROI) extraction, vibration removal algorithm, background removal algorithm, and standardization. We propose a transformer-based radar gesture recognition network named RGTNet. It fully extracts and fuses the spatial-temporal information of radar feature maps to complete the classification of various gestures. The experimental results show that our method can better complete the eight gesture classification tasks in the in-vehicle environment. The recognition accuracy is 97.56%.

A Joint 2D-3D Complementary Network for Stereo Matching.

Stereo matching is an important research field of computer vision. Due to the dimension of cost aggregation, current neural network-based stereo methods are difficult to trade-off speed and accuracy. To this end, we integrate fast 2D stereo methods with accurate 3D networks to improve performance and reduce running time. We leverage a 2D encoder-decoder network to generate a rough disparity map and construct a disparity range to guide the 3D aggregation network, which can significantly improve the accuracy and reduce the computational cost. We use a stacked hourglass structure to refine the disparity from coarse to fine. We evaluated our method on three public datasets. According to the KITTI official website results, Our network can generate an accurate result in 80 ms on a modern GPU. Compared to other 2D stereo networks (AANet, DeepPruner, FADNet, etc.), our network has a big improvement in accuracy. Meanwhile, it is significantly faster than other 3D stereo networks (5× than PSMNet, 7.5× than CSN and 22.5× than GANet, etc.), demonstrating the effectiveness of our method.

Illicium verum and Eucommia ulmoides leaf extracts promote nutrient availability and antioxidant capacity in piglets by upregulating duodenal and jejunal Nrf2/TNF-α.

The effect of Illicium verum extracts (IVE) or Eucommia ulmoides leaf extracts (ELE) on nutrient availability, duodenal and jejunal antioxidant ability of Duroc ×Landrace × Yorkshire (DLY) and Chinese native Licha-black (LCB) piglets was investigated. Ninety-six piglets (48 DLY and 48 LCB respectively) without significant difference in body weight (11.22 ± 0.32 kg) were used in a 2 × 4 factorial design. Animals were randomly allocated to four treatments, and each had four replicates with three DLY and three LCB piglets. Treatments were basal diet (CON) and basal diet with 500 mg/kg IVE, 250 mg/kg ELE and 50 mg/kg chlortetracycline (CHL) respectively. Animals were placed individually for 7-days adaptation following 42-days test. Results showed the significant interaction (p < 0.05) between dietary treatments and pig species in activity of total superoxide dismutase (T-SOD) and glutathione peroxidase (GSH-Px), content of malondialdehyde (MDA), and α-tumour necrosis factor (TNF-α), nuclear factor erythroid 2-related factor 2 (Nrf2) and Nrf2/TNF-α at mRNA and protein level in duodenum and jejunum of DLY and LCB piglets. The IVE and ELE increased (p < 0.05) activity of GSH-Px and T-SOD, and the Nrf2/TNF-α at mRNA and protein level, however, the decreased (p < 0.05) MDA content, and TNF-α at mRNA and protein level in duodenum and jejunum were observed. The CHL decreased (p < 0.05) activity of GSH-Px and T-SOD, TNF-α and Nrf2 at mRNA and protein level in duodenum, but increased (p < 0.05) MDA content and Nrf2/TNF-α in jejunum. DLY piglets had higher (p < 0.05) nutrient digestibility (organic matter, crude protein and gross energy), availability (biological value and net protein utilization), MDA content, and TNF-α at mRNA and protein level in jejunum, and had lower (p < 0.05) activity of GSH-Px and T-SOD, and Nrf2 and Nrf2/TNF-α at mRNA and protein level in duodenum and jejunum than LCB. In conclusion, the 500 mg/kg IVE and 250 mg/kg ELE improved the nutrient availability, and the improvement of antioxidant capacity is realized by activating the Nrf2/TNF-α of duodenum and jejunum. The CHL had adverse effects on antioxidant ability of DLY and LCB piglets. The results showed that the nutrient digestion and absorption capacity of DLY were stronger than that of LCB piglets, but the antioxidant capacity was lower than that of LCB piglets. Therefore, the IVE and ELE are recommended as a new potential alternative to antibiotics in piglets' diets.

Self-Assembled Artificial Ion-Channels toward Natural Selection of Functions.

Owing to their significant physiological functions, especially as selective relays for translocation of physiological relevant species through cellular membranes, natural ion channels play important role in the living organisms. During the last decades, the field of self-assembled ion channels has been continuously developed. Convergent multidimensional self-assembly strategies have been used for the synthesis of unimolecular channels or non-covalent self-organized channels, designed to mimic natural ion channel proteins and for which a rich array of interconverting or adaptive channel conductance states can be observed. In this review, we give an overview on the development of various self-assembled artificial channels in a bottom-up approach, especially their design, self-assembly behaviour, transport activity in lipid bilayer membranes, mechanism of transport and comparison with natural ion channels. Finally, we discuss their applications, the potential challenges facing in this field as well as future development and perspectives.

Characteristics of lipid droplets and the expression of proteins involved in lipolysis in the murine cervix during mid-pregnancy.

Lipid droplets (LDs) are reservoirs of arachidonoyl lipids for prostaglandin (PG) E2 synthesis, and progesterone can stimulate PGE2 synthesis; however, the relationship between progesterone and LD metabolism in the murine cervix remains unclear. In the present study we examined LD distribution and changes in the expression of proteins involved in lipolysis and autophagy in the murine cervix during pregnancy, and compared the findings with those in dioestrous mice. During mid-pregnancy, LDs were predominantly distributed in the cervical epithelium. Electron microscopy revealed the transfer of numerous LDs from the basal to apical region in the luminal epithelium, marked catabolism of LDs, an elevated number of LDs and autophagosomes and a higher LD:mitochondrion size ratio in murine cervical epithelial cells (P<0.05). In addition, immunohistochemical and western blotting analyses showed significantly higher cAMP-dependent protein kinase, adipose triglyceride lipase and hormone-sensitive lipase expression, and a higher light chain 3 (LC3) II:LC3I ratio in the stroma and smooth muscles and, particularly, in murine cervical epithelial cells, during mid-pregnancy than late dioestrus. In conclusion, these results suggest that the enhanced lipolysis of LDs and autophagy in murine cervical tissues were closely related to pregnancy and were possibly controlled by progesterone because LD catabolism may be necessary for energy provision and PGE2 synthesis to maintain a closed pregnant cervix.

Effect of Illicium verum or Eucommia ulmoides leaf extracts on the anti-stress ability, and mRNA and protein expression of Nrf2 and TNF-α in Duroc × Landrace × Yorkshire and Chinese native Licha-black nursery piglets.

Plant extracts are considered to be an effective alternative to antibiotics in response to weaning stress in piglets. This study evaluated the effect of Illicium verum extracts (IVE) or Eucommia ulmoides leaf extracts (ELE) on growth performance, serum and liver antioxidant ability of nursery piglets, as well as the difference of IVE and ELE on Duroc × Landrace × Yorkshire (DLY) and Chinese native Licha-black (LCB) piglets. A total of 96 nursery piglets (48 DLY and 48 LCB piglets) with an average body weight of 11.22 ± 0.32 kg were randomly divided into four treatments in a 2 × 4 factorial design. Each treatment had four replicates with 3 DLY and 3 LCB piglets per replicate respectively. Treatments included: basal diet, basal diet + 500 mg/kg IVE, basal diet + 250 mg/kg ELE and basal diet + 50 mg/kg chlortetracycline (CHL). All piglets were housed individually for the 42 days trial period after 7 days adaptation. Results showed that there were significant interactions (p < .05) between piglets species and dietary treatments in average daily gain (ADG) and feed efficiency, serum and hepatic glutathione peroxidase (GSH-Px) and malondialdehyde (MDA), hepatic integral optical density (IOD) of α-tumour necrosis factor (TNF-α), hepatic relative mRNA expressions of nuclear factor erythroid 2-related factor 2 (Nrf2)/TNF-α and protein expression of TNF-α. Regardless of piglets species, supplementation with IVE and ELE increased (p < .05) ADG and feed efficiency, T-SOD and GSH-Px in serum and liver, hepatic IOD of Nrf2, hepatic mRNA and protein expression of Nrf2/TNF-α. However, CHL treatment resulted in lower (p < .05) serum GSH-Px and hepatic mRNA and protein expression of Nrf2/TNF-α, and higher hepatic MDA and IOD of TNF-α. Compared to LCB, DLY piglets had higher (p < .05) ADG and feed efficiency, serum and hepatic MDA, and protein expression of TNF-α, but lower (p < .05) ADFI, liver index, serum and hepatic GSH-Px, hepatic IOD of TNF-α, mRNA expressions of Nrf2/TNF-α were observed. In conclusion, Illicium verum (500 mg/kg) and Eucommia ulmoides leaf (250 mg/kg) extracts can increase the growth performance and antioxidant ability of DLY and LCB piglets, while chlortetracycline produces undesirable side-effects on the antioxidant ability of DLY and LCB piglets. Illicium verum and Eucommia ulmoides leaf extracts produced different antioxidant effects in DLY and LCB piglets with the Chinese native Licha-black pig responding better than Duroc × Landrace × Yorkshire.

Reticuloendotheliosis virus and avian leukosis virus subgroup J synergistically increase the accumulation of exosomal miRNAs.

BACKGROUND: Co-infection with avian leukosis virus subgroup J and reticuloendotheliosis virus induces synergistic pathogenic effects and increases mortality. However, the role of exosomal miRNAs in the molecular mechanism of the synergistic infection of the two viruses remains unknown. RESULTS: In this study, exosomal RNAs from CEF cells infected with ALV-J, REV or both at the optimal synergistic infection time were analysed by Illumina RNA deep sequencing. A total of 54 (23 upregulated and 31 downregulated) and 16 (7 upregulated and 9 downregulated) miRNAs were identified by comparing co-infection with two viruses, single-infected ALV-J and REV, respectively. Moreover, five key miRNAs, including miR-184-3p, miR-146a-3p, miR-146a-5p, miR-3538 and miR-155, were validated in both exosomes and CEF cells by qRT-PCR. GO annotation and KEGG pathway analysis of the miRNA target genes showed that the five differentially expressed miRNAs participated in virus-vector interaction, oxidative phosphorylation, energy metabolism and cell growth. CONCLUSIONS: We demonstrated that REV and ALV-J synergistically increased the accumulation of exosomal miRNAs, which sheds light on the synergistic molecular mechanism of ALV-J and REV.

Metal Coordination Stoichiometry Controlled Formation of Linear and Hyperbranched Supramolecular Polymers.

Controlling the topologies of polymers is a hot topic in polymer chemistry because the physical and/or chemical properties of polymers are determined (at least partially) by their topologies. This study exploits the host-guest interactions between dibenzo-24-crown-8 and secondary ammonium salts and metal coordination interactions between 2,6-bis(benzimidazolyl)-pyridine units with metal ions (Zn(II) and/or Eu(III) ) as orthogonal non-covalent interactions to prepare supramolecular polymers. By changing the ratios of the metal ion additives (Zn(NO3 )2 and Eu(NO3 )3 ) linkers to join the host-guest dimeric complex, the linear supramolecular polymers (100 mol% Zn(NO3 )2 per ligand) and hyperbranched supramolecular polymers (97 mol% Zn(NO3 )2 and 3 mol% Eu(NO3 )3 per ligand) are separately and successfully constructed. This approach not only expands topological control over polymeric systems, but also paves the way for the functionalization of smart and adaptive materials.

Automatical Spike Sorting With Low-Rank and Sparse Representation.

Spikesorting is crucial in studying neural individually and synergistically encoding and decoding behaviors. However, existent spike sorting algorithms perform unsatisfactorily in real scenarios where heavy noises and overlapping samples are commonly in the spikes, and the spikes from different neurons are similar. To address such challenging scenarios, we propose an automatic spike sporting method in this paper, which integrally combines low-rank and sparse representation (LRSR) into a unified model. In particular, LRSR models spikes through low-rank optimization, uncovering global data structure for handling similar and overlapped samples. To eliminate the influence of the embedded noises, LRSR uses a sparse constraint, effectively separating spikes from noise. The optimization is solved using alternate augmented Lagrange multipliers methods. Moreover, we conclude with an automatic spike-sorting framework that employs the spectral clustering theorem to estimate the number of neurons. Extensive experiments over various simulated and real-world datasets demonstrate that our proposed method, LRSR, can handle spike sorting effectively and efficiently.