Comprehensive Analysis of CircRNA Expression Profiles in Multiple Tissues of Pigs.

Circular RNAs (circRNAs) are a class of non-coding RNAs with diverse functions, and previous studies have reported that circRNAs are involved in the growth and development of pigs. However, studies about porcine circRNAs over the past few years have focused on a limited number of tissues. Based on 215 publicly available RNA sequencing (RNA-seq) samples, we conducted a comprehensive analysis of circRNAs in nine pig tissues, namely, the gallbladder, heart, liver, longissimus dorsi, lung, ovary, pituitary, skeletal muscle, and spleen. Here, we identified a total of 82,528 circRNAs and discovered 3818 novel circRNAs that were not reported in the CircAtlas database. Moreover, we obtained 492 housekeeping circRNAs and 3489 tissue-specific circRNAs. The housekeeping circRNAs were enriched in signaling pathways regulating basic biological tissue activities, such as chromatin remodeling, nuclear-transcribed mRNA catabolic process, and protein methylation. The tissue-specific circRNAs were enriched in signaling pathways related to tissue-specific functions, such as muscle system process in skeletal muscle, cilium organization in pituitary, and cortical cytoskeleton in ovary. Through weighted gene co-expression network analysis, we identified 14 modules comprising 1377 hub circRNAs. Additionally, we explored circRNA-miRNA-mRNA networks to elucidate the interaction relationships between tissue-specific circRNAs and tissue-specific genes. Furthermore, our conservation analysis revealed that 19.29% of circRNAs in pigs shared homologous positions with their counterparts in humans. In summary, this extensive profiling of housekeeping, tissue-specific, and co-expressed circRNAs provides valuable insights into understanding the molecular mechanisms of pig transcriptional expression, ultimately deepening our understanding of genetic and biological processes.

Recognition-Enabled Automated Analyte Identification via 19F NMR.

Nuclear magnetic resonance (NMR) is an indispensable tool for structural elucidation and noninvasive analysis. Automated identification of analytes with NMR is highly pursued in metabolism research and disease diagnosis; however, this process is often complicated by the signal overlap and the sample matrix. We herein report a detection scheme based on 19F NMR spectroscopy and dynamic recognition, which effectively simplifies the detection signal and mitigates the influence of the matrix on the detection. It is demonstrated that this approach can not only detect and differentiate capsaicin and dihydrocapsaicin in complex real-world samples but also quantify the ibuprofen content in sustained-release capsules. Based on the 19F signals obtained in the detection using a set of three 19F probes, automated analyte identification is achieved, effectively reducing the odds of misrecognition caused by structural similarity.

Unsupervised learning of cross-modal mappings in multi-omics data for survival stratification of gastric cancer.

Aims: This study presents a survival stratification model based on multi-omics integration using bidirectional deep neural networks (BiDNNs) in gastric cancer. Methods: Based on the survival-related representation features yielded by BiDNNs through integrating transcriptomics and epigenomics data, K-means clustering analysis was performed to cluster tumor samples into different survival subgroups. The BiDNNs-based model was validated using tenfold cross-validation and in two independent confirmation cohorts. Results: Using the BiDNNs-based survival stratification model, patients were grouped into two survival subgroups with log-rank p-value = 9.05E-05. The subgroups classification was robustly validated in tenfold cross-validation (C-index = 0.65 ± 0.02) and in two confirmation cohorts (E-GEOD-26253, C-index = 0.609; E-GEOD-62254, C-index = 0.706). Conclusion: We propose and validate a robust and stable BiDNN-based survival stratification model in gastric cancer.

Combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions for quantitative source apportionment of heavy metals in suburban agricultural soils.

Quantitative identification of heavy metals (HM) sources in soils is key to prevention and control of heavy metal pollution. In this study, UNMIX, PMF (Positive matrix factorization) model and Pb-Zn-Cu isotopic compositions were combined to quantitatively identify heavy metal sources in a suburban agricultural area of Kaifeng, China. Using multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) and ICP-MS, we measured Pb, Zn and Cu stable isotopic compositions, HM concentrations and HM chemical fractions in studied soils, as well as potential sources around the highly polluted site, including total suspended particle, compound fertilizer, irrigated river water and sediments. The results showed that total contents and chemical fractions of heavy metals, as well as Pb-Zn-Cu isotopic compositions presented great variation in different sites, which implied that heavy metal accumulation was obviously affected by local anthropogenic pollution source. UNMIX and PMF presented good agreement on source apportionment that industrial and agricultural activities (61.74% and 60.75% for UNMIX and PMF, respectively) were the major contributors to heavy metal accumulation in the study area. Especially, sewage irrigation and atmosphere deposition accounted for a large proportion (28.14% and 41.03% for UNMIX and PMF, respectively). Moreover, isotopic compositions of Pb, Zn and Cu in highly polluted soils and environment media gave further confirmation that sewage irrigation and atmosphere deposition were primary anthropogenic source. Therefore, combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions showed good coordination in quantitative and specific source identification of heavy metals in agricultural soils.

First Report of Leaf Sheath Disease, Caused by Microdochium seminicola, on Zizania latifolia in China.

Zizania latifolia, which belongs to the tribe Oryzea, has been widely grown over thousands of years as an aquatic vegetable in China. In the autumn of 2019, the disease harmful to the leaf sheaths of Z. latifolia was found in Jinhua City and Lishui City, Zhejiang Province. The disease caused brown oval-shaped spots (3~5 cm long, 0.5~1 cm wide) on leaf sheaths (Figure 1A). The infected plants produced non-commercial Jiaobai. The surface of the Jiaobai was pale yellow instead of white, and the length of the Jiaobai was 25% shorter than the uninfected plants. To 2022, the disease has been found in most planting areas of Z. latifolia in Zhejiang, Jiangsu, Fujian, Jiangxi and Anhui provinces in China. About 20%~50% incidence of the disease in these main production areas has seriously threatened the yield and quality of Jiaobai. To identify the causal agent, diseased leaf sheaths were collected. Symptomatic leaf sheath tissue was sterilized with 75% alcohol for 30 sec, and then washed three times with sterile distilled water for 1 min. A total of 37 strains were isolated on potato dextrose agar (PDA). We selected 10 strains for further morphological identification. An abundant mass of aerial mycelia was formed in 8 days (Figure 1B). The mycelium is transparent, septate and smooth. Conidia is fusiform, straight or curved, 0~3 septa, hyaline, tapering and rounding at the apex (Figure 1C and 1D). Strain XYQ3 was obtained through multi-generation culture. To further identify the pathogen of this fungus, genomic DNA was extracted and internal transcribed spacer (ITS), large subunit rDNA (LSU), ß-tubulin (BTUB) and DNA-directed RNA polymerase II subunit (RPB2) of strain XYQ3 were amplified. These sequences were obtained and submitted to GenBank (accession numbers MT605000, OP585914, MZ619085, MZ619084, respectively). After alignment analysis of sequencing data, we found that the ITS sequence indicated 100% identity with M. seminicola (GenBank acc no. KP859007). The LSU sequence showed 100% identity with M. seminicola (GenBank acc no. KP858943). The BTUB sequence showed 99.47% identity with M. seminicola (GenBank acc no. KP859070). The RPB2 sequence has higher identity with M. seminicola, reaching 99.76% with 4 sequences (GenBank acc nos. KP859140, KP859116, KP859134 and KP859130). Strain XYQ3 and a total of 16 other Microdochium isolates were selected for phylogenetic analysis using the ITS, LSU, BTUB and RPB2 sequences (Figure 2). Phylogenetic tree analysis revealed that strain XYQ3 was clustered with the M. seminicola clade, including M. seminicola strains MFG 60131, MFG 60132, CBS 122706 and KAS 1527. Therefore, this fungus was identified as M. seminicola based on morphological observation, multiple sequences alignment analysis and phylogenetic analysis. Strain XYQ3 was used in pathogenicity tests. According to Koch's postulates, 10 fresh leaf sheaths and leaves of host plants were inoculated by spraying conidial suspension at the concentration of 1×106 conidia/mL. Sterile water was sprayed as negative control. Inoculated plants were cultured under 25℃ light for 10 h, darkness for 14 h, covered with plastic film to maintain high humidity above 65%, and observed daily for disease development. After 6 d, symptoms similar to those observed in the field (Figure 1E and 1F). The pathogen of this fungus was re-isolated from the symptomatic inoculated leaf sheath and re-identified as strain XYQ3. Many Microdochium species are important pathogens of Poaceae (Liang et al., 2019). M. seminicola is classified as a new species in the Xylariales family by the report of Hernández-Restrepo (Hernandez-Restrepo et al., 2016) and was only found in wheat, oats and barley so far (Gagkaeva et al., 2020; Gavrilova et al., 2020). To the best of our knowledge, this fungus is the first report in the disease of Z. latifolia. As this disease is prevalent in main planting areas of Z. latifolia and has seriously threatened the production of Jiaobai, it is very important to isolate and identify the pathogen for the subsequent drug screening and control.

Exploring the landscape of Buckingham potentials for silica by machine learning: Soft vs hard interatomic forcefields.

Interatomic forcefields for silicate glasses often rely on partial (rather than formal) charges to describe the Coulombic interactions between ions. Such forcefields can be classified as "soft" or "hard" based on the value of the partial charge attributed to Si atoms, wherein softer forcefields rely on smaller partial charges. Here, we use machine learning to efficiently explore the "landscape" of Buckingham forcefields for silica, that is, the evolution of the overall forcefield accuracy as a function of the forcefield parameters. Interestingly, we find that soft and hard forcefields correspond to two distinct, yet competitive local minima in this landscape. By analyzing the structure of the silica configurations predicted by soft and hard forcefields, we show that although soft and hard potentials offer competitive accuracy in describing the short-range order structure, soft potentials feature a higher ability to describe the medium-range order.

Medial prefrontal cortex in neurological diseases.

The medial prefrontal cortex (mPFC) is a crucial cortical region that integrates information from numerous cortical and subcortical areas and converges updated information to output structures. It plays essential roles in the cognitive process, regulation of emotion, motivation, and sociability. Dysfunction of the mPFC has been found in various neurological and psychiatric disorders, such as depression, anxiety disorders, schizophrenia, autism spectrum disorders, Alzheimer's disease, Parkinson's disease, and addiction. In the present review, we summarize the preclinical and clinical studies to illustrate the role of the mPFC in these neurological diseases.

3D Pose Detection of Closely Interactive Humans Using Multi-View Cameras.

We propose a method to automatically detect 3D poses of closely interactive humans from sparse multi-view images at one time instance. It is a challenging problem due to the strong partial occlusion and truncation between humans and no tracking process to provide priori poses information. To solve this problem, we first obtain 2D joints in every image using OpenPose and human semantic segmentation results from Mask R-CNN. With the 3D joints triangulated from multi-view 2D joints, a two-stage assembling method is proposed to select the correct 3D pose from thousands of pose seeds combined by joint semantic meanings. We further present a novel approach to minimize the interpenetration between human shapes with close interactions. Finally, we test our method on multi-view human-human interaction (MHHI) datasets. Experimental results demonstrate that our method achieves high visualized correct rate and outperforms the existing method in accuracy and real-time capability.

Lack of hepatic stimulator substance expression promotes hepatocellular carcinoma metastasis partly through ERK-activated epithelial-mesenchymal transition.

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies due to its high frequency of metastasis via the epithelial-mesenchymal transition (EMT) pathway. Hepatic stimulator substance (HSS) can protect hepatocytes from injury and promote liver growth. Recent studies indicated that HSS expression is increased in HCC tissues; however, whether HSS expression is potentially associated with HCC metastasis, particularly through the EMT pathway, remains largely unknown. In this study, the relationship between HSS expression and HCC metastasis was investigated in clinical samples of HCC. Meanwhile, the regulation of HCC metastasis and EMT progression by HSS were also analyzed in both in vitro and in vivo models. The results showed that the expression of 23 kDa HSS was significantly decreased among HCC tissues with angioinvasion. A decrease in HSS predicted poor prognosis with a lower survival rate. Furthermore, the growth of xenograft tumors after inoculating MHCC97H-HSS-shRNA (HCC) cells into nude mice was notably accelerated compared to those inoculated with HSS-expressing cells. Further analysis revealed that knockdown of HSS expression in both MHCC97H and HepG2 cells could enhance the migration of these HCC cells. Concurrently, interference of HSS expression by shRNA promoted conversion of morphologically epithelial-like HCC cells into mesenchymal-like cells, together with downregulations of epithelial markers (such as E-cadherin and zonula occludens-1) and upregulation of mesenchymal-like makers (such as α-SMA, ß-catenin, and fibronectin). Furthermore, it was demonstrated that, as well as promoting EMT, HSS-shRNA induced the phosphorylation of extracellular signal-regulated kinase (ERK) and elevated the expression of the EMT-related transcription factor Snail. Specific inhibition of HSS-shRNA-induced ERK phosphorylation by PD98059 attenuated HCC cell migration in a dose-dependent manner. In conclusion, we demonstrated that downregulation of HSS expression contributes to HCC metastasis partially through the ERK-activated EMT pathway.

Two new 13,14:14,15-disecopregnane-type compounds from the roots of Cynanchum paniculatum.

Two new 13,14:14,15-disecopregnane-type compounds glaucogenin F (1), glaucogenin F 3-O-ß-D-oleandropyranoside (2), together with three known compounds cynapanoside A (3), cynatratoside A (4), and neocynapanogenin F 3-O-ß-D-oleandropyranoside (5) were isolated from the 95% ethanol extract of the roots of Cynanchum paniculatum. The structures of new compounds were elucidated on the basis of extensive spectroscopic analyses, including 1D and 2D NMR, HRESIMS and NOESY.

Raman Spectra of Bredigite at High Temperature and High Pressure.

Bredigite was synthesized by using the Piston-Cylinder in 1.2 GPa and 1 473 K. With external heating device and diamond anvil cell, high temperature and high pressure Raman spectra of bredigite were collected at temperatures 298, 353, 463, 543, 663, 773 and 873 K and with pressure from 1 atm up to 14.36 GPa (room temperature). The SEM image showed that the sample consisted of one crystalline phase with grain size ranging from 10～20 µm. The EPMA data suggest a chemical formula of Ca7.03(2)Mg0.98(2)Si3.94(2)O16 which was identical to the theoretical component of bredigite. The Raman spectroscopic results indicate there were 29 vibration bands of bredigite at high temperature. Some bands were merging, weakening and disappearing increasingly with the temperature, which was obvious in the range of 800~1 200 cm-1. The vibration bands of 909, 927 and 950 cm-1 disappeared at 873, 773 and 873 K, respectively. The results primarily indicated that the structure of bredigite was stable under experimental condition. In addition, isobaric mode-Grüneisen parameters and isothermal mode-Grüneisen parameters were calculated, yielding 1.47(2) and 0.45(3) as their mean values, respectively. Anharmonic coefficients were estimated based on the high temperature and high pressure Raman experiments, showing that the contributions to anharmonic-effect induced with the Si­O vibration modes were smaller than other modes.

[In vivo evaluation of magnetic and hydrodynamic suspension centrifugal ventricular assist device].

OBJECTIVE: To verify the function of magnetic and hydrodynamic suspension centrifugal ventricular assist device in a sheep model. METHODS: The device was implanted into left ventricular apex on beating hearts. The outflow graft of each device was anastomosed to descending aorta in 11 animals. Hematologic, biochemical and blood clotting tests before and after surgery were performed. The data of pump functions were collected continuously. RESULTS: Among them, there were death from ventricular fibrillation (n = 3), acute pulmonary edema (n = 1) and left ventricular thrombus and molar cardiac muscle (n = 5). One animal survived for 75 days and died from bacterial infection after pumping for 59 hours. During assistance for 120 days, the flow rate was 3.0-3.4 L/min. All hematologic and biochemical parameters were within normal ranges in one sheep. The walking sheep wore the controller and lithium battery with a blood pump. Neither mechanical wearing nor thrombus formation was observed for inflow and outflow conduits or pump interior. CONCLUSIONS: The magnetic and hydrodynamic suspension centrifugal ventricular assist device demonstrates excellent hemocompatibility and reliability. And there is a great prospect of clinical success.

[Elastic registration method to compute deformation functions for mitral valve].

Mitral valve disease is one of the most popular heart valve diseases. Precise positioning and displaying of the valve characteristics is necessary for the minimally invasive mitral valve repairing procedures. This paper presents a multi-resolution elastic registration method to compute the deformation functions constructed from cubic B-splines in three dimensional ultrasound images, in which the objective functional to be optimized was generated by maximum likelihood method based on the probabilistic distribution of the ultrasound speckle noise. The algorithm was then applied to register the mitral valve voxels. Numerical results proved the effectiveness of the algorithm.

Hypergraph-Based Multi-View Action Recognition Using Event Cameras.

Action recognition from video data forms a cornerstone with wide-ranging applications. Single-view action recognition faces limitations due to its reliance on a single viewpoint. In contrast, multi-view approaches capture complementary information from various viewpoints for improved accuracy. Recently, event cameras have emerged as innovative bio-inspired sensors, leading to advancements in event-based action recognition. However, existing works predominantly focus on single-view scenarios, leaving a gap in multi-view event data exploitation, particularly in challenges like information deficit and semantic misalignment. To bridge this gap, we introduce HyperMV, multi-view event-based action recognition framework. HyperMV converts discrete event data into frame-like representations and extracts view-related features using a shared convolutional network. By treating segments as vertices and constructing hyperedges using rule-based and KNN-based strategies, a multi-view hypergraph neural network that captures relationships across viewpoint and temporal features is established. The vertex attention hypergraph propagation is also introduced for enhanced feature fusion. To prompt research in this area, we present the largest multi-view event-based action dataset THUMV-EACT-50, comprising 50 actions from 6 viewpoints, which surpasses existing datasets by over tenfold. Experimental results show that HyperMV significantly outperforms baselines in both cross-subject and cross-view scenarios, and also exceeds the state-of-the-arts in frame-based multi-view action recognition.

Research on the parameter design and calibration and control of EV in-vehicle active sound generation system.

In order to improve the interior sound quality of electric vehicles (EVs) under acceleration and uniform speed conditions, to balance the comfort and dynamics of the interior sound, and to improve the accuracy and performance of the active sound generation system (ASGS), this article carries out the research related to the parameter design, sound calibration, evaluation methodology, and control system of the EV ASGS. Propose an in-vehicle sound design method focusing on three dimensions, including engine order composition, spectral energy distribution, and sound amplitude enhancement in the typical speed range, and determine the in-vehicle sound design scheme and the total sound value target. Focus on the sound parameter design, calibration and evaluation methods of EV ASGS considering the frequency response characteristics of the loudspeaker, sound amplitude control accuracy, sound quality, and psychoacoustic parameters, clarify the active sound parameter settings of EVs, complete the analysis of sound extraction methods, complete the engine order sound fitting, and design the ASGS of the EV interior by combining the subjective and objective evaluations. Develop the control software and hardware of the ASGS, complete the construction and accuracy verification of the ASGS based on the in-vehicle sound system, and realize the sound calibration of the ASGS under the static conditions of the real vehicle and the verification of the target achievement. The real-vehicle test shows that the ASGS reduces the sharpness of 1.0 acum and 0.52 acum under acceleration and constant speed conditions, respectively, and improves the comfort and dynamics of in-vehicle sound. The objective and subjective evaluation results show that the parameter design, selection and accuracy of the sound calibration and evaluation methods of the ASGS in the EV determines the accuracy and effect of the ASGS.

Research on the characteristics of EV interior sound quality and its dynamic active control system design and development un-der accelerated driving conditions.

In order to improve the interior sound quality of Electric Vehicles (EV), solve the problem of low sense of power and comfort of the interior sound as well as the large electromagnetic excitation order noise of motor and the sharp interior sound, this article designs a dynamic active sound control system for EV under accelerated driving conditions. Firstly, by comparing and analyzing the sound spectrum characteristics of fuel vehicle (FV) and EV during acceleration, a short-time Fourier transform (STFT) is adopted to extract and synthesize the engine sound. Secondly, the influence of the engine order composition and the energy distribution in the frequency domain on the sound quality of the vehicle is analyzed, and an active control system for sound quality is proposed. And the software and hardware development of the active control sound system is completed. Finally, through real-vehicle testing and verification, the sense of comfort and power of the EV interior sound has been greatly improved during acceleration, and the total value of interior sound can meet the requirement. The sound pressure level and loudness of interior sound have been increased, and the sharpness of the sound inside the vehicle has been improved, with a maximum reduction of 1.0acum.

ARTC1-mediated VAPB ADP-ribosylation regulates calcium homeostasis.

Mono-ADP-ribosylation (MARylation) is a post-translational modification that regulates a variety of biological processes, including DNA damage repair, cell proliferation, metabolism, and stress and immune responses. In mammals, MARylation is mainly catalyzed by ADP-ribosyltransferases (ARTs), which consist of two groups: ART cholera toxin-like (ARTCs) and ART diphtheria toxin-like (ARTDs, also known as PARPs). The human ARTC (hARTC) family is composed of four members: two active mono-ADP-ARTs (hARTC1 and hARTC5) and two enzymatically inactive enzymes (hARTC3 and hARTC4). In this study, we systematically examined the homology, expression, and localization pattern of the hARTC family, with a particular focus on hARTC1. Our results showed that hARTC3 interacted with hARTC1 and promoted the enzymatic activity of hARTC1 by stabilizing hARTC1. We also identified vesicle-associated membrane protein-associated protein B (VAPB) as a new target of hARTC1 and pinpointed Arg50 of VAPB as the ADP-ribosylation site. Furthermore, we demonstrated that knockdown of hARTC1 impaired intracellular calcium homeostasis, highlighting the functional importance of hARTC1-mediated VAPB Arg50 ADP-ribosylation in regulating calcium homeostasis. In summary, our study identified a new target of hARTC1 in the endoplasmic reticulum and suggested that ARTC1 plays a role in regulating calcium signaling.

Pig-eRNAdb: a comprehensive enhancer and eRNA dataset of pigs.

Enhancers and the enhancer RNAs (eRNAs) have been strongly implicated in regulations of transcriptions. Based the multi-omics data (ATAC-seq, ChIP-seq and RNA-seq) from public databases, Pig-eRNAdb is a dataset that comprehensively integrates enhancers and eRNAs for pigs using the machine learning strategy, which incorporates 82,399 enhancers and 37,803 eRNAs from 607 samples across 15 tissues of pigs. This user-friendly dataset covers a comprehensive depth of enhancers and eRNAs annotation for pigs. The coordinates of enhancers and the expression patterns of eRNAs are downloadable. Besides, thousands of regulators on eRNAs, the target genes of eRNAs, the tissue-specific eRNAs, and the housekeeping eRNAs are also accessible as well as the sequence similarity of eRNAs with humans. Moreover, the tissue-specific eRNA-trait associations encompass 652 traits are also provided. It will crucially facilitate investigations on enhancers and eRNAs with Pig-eRNAdb as a reference dataset in pigs.

A past Haff disease outbreak associated with eating freshwater pomfret in South China.

BACKGROUND: Haff disease is unexplained rhabdomyolysis caused by consumption of fishery products in the previous 24 h. It was first identified in Europe in 1924 but the condition is extremely rare in China. Here we describe a past outbreak of acute food borne muscle poisoning that occurred in Guangdong Province (South China) in 2009. METHODS: The first full outbreak of Haff disease reported in Jiangsu Province (East China) in 2010, indicated that the incidence of the disease may be increasing in China. We, therefore first retrospectively reviewed epidemiologic, trace-back, environmental studies, and laboratory analyses, including oral toxicity testing to ascertain risk and chemical analysis to identify toxin(s), from the 2009 Guangdong outbreak. Then we compared data from the 2009 outbreak with data from all other Haff disease outbreaks that were available. RESULTS: Clinical symptoms and laboratory findings indicated that the 2009 Guangdong outbreak disease was consistent with rhabdomyolysis. Epidemiologic, trace-back, environmental studies and laboratory analyses implied that the disease was caused by freshwater Pomfrets consumed prior to the onset of symptoms. We also identified common factors between the 2009 Guangdong outbreak and previous Haff disease outbreaks reported around the world, while as with other similar outbreaks, the exact etiological factor(s) of the disease remains unknown. CONCLUSIONS: The 2009 Guangdong outbreak of 'muscle poisoning' was retrospectively identified as an outbreak of Haff disease. This comprised the highest number of cases reported in China thus far. Food borne diseases emerging in this unusual form and the irregular pattern of outbreaks present an ongoing public health risk, highlighting the need for improved surveillance and diagnostic methodology.

SuperFast: 200× Video Frame Interpolation via Event Camera.

Traditional frame-based video frame interpolation (VFI) methods rely on the linear motion assumption and brightness invariance assumption, which may lead to fatal errors confronting the scenarios with high-speed motions. To tackle the above challenge, inspired by the advantages of event cameras on asynchronously recording brightness changes at each pixel, we propose a Fast-Slow joint synthesis framework for event-enhanced high-speed video frame interpolation, named SuperFast, in this paper, which can generate high frame rate (5000 FPS, 200× faster) video from the input low frame rate (25 FPS) video and the corresponding event stream. In our framework, the task is divided into two sub-tasks, i.e., video frame interpolation for the contents with and without high-speed motions, which are tackled by two corresponding branches, i.e., the fast synthesis pathway and the slow synthesis pathway. The fast synthesis pathway leverages a spiking neural network to encode the input event stream, and combines boundary frames to generate intermediate results through synthesis and refinement, targeting on contents with high-speed motions. The slow synthesis pathway stacks the two input boundary frames and the event stream to synthesize intermediate results, focusing on relatively slow-motion contents. Finally, a fusion module with a comparison loss is utilized to generate the final video frame interpolation results. We also build a hybrid visual acquisition system containing an event camera and a high frame rate camera, and collect the first 5000 FPS High-Speed Event-enhanced Video frame Interpolation (THU[Formula: see text]) dataset. To evaluate the performance of our proposed framework, we have conducted experiments on our THU[Formula: see text] dataset and the existing HS-ERGB dataset. Experimental results demonstrate that our proposed framework can achieve state-of-the-art 200× video frame interpolation performance under high-speed motion scenarios.