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Abstract The ORF9b protein, derived from the nucleocapsid’s open-reading frame in both SARS-CoV and SARS-CoV-2, serves as an accessory protein crucial for viral immune evasion by inhibiting the innate immune response. Despite its significance, the precise regulatory mechanisms underlying its function remain elusive. In the present study, we unveil that the ORF9b protein of SARS-CoV-2, including emerging mutant strains like Delta and Omicron, can undergo ubiquitination at the K67 site and subsequent degradation via the proteasome pathway, despite certain mutations present among these strains. Moreover, our investigation further uncovers the pivotal role of the translocase of the outer mitochondrial membrane 70 (TOM70) as a substrate receptor, bridging ORF9b with heat shock protein 90 alpha (HSP90α) and Cullin 5 (CUL5) to form a complex. Within this complex, CUL5 triggers the ubiquitination and degradation of ORF9b, acting as a host antiviral factor, while HSP90α functions to stabilize it. Notably, treatment with HSP90 inhibitors such as GA or 17-AAG accelerates the degradation of ORF9b, leading to a pronounced inhibition of SARS-CoV-2 replication. Single-cell sequencing data revealed an up-regulation of HSP90α in lung epithelial cells from COVID-19 patients, suggesting a potential mechanism by which SARS-CoV-2 may exploit HSP90α to evade the host immunity. Our study identifies the CUL5-TOM70-HSP90α complex as a critical regulator of ORF9b protein stability, shedding light on the intricate host–virus immune response dynamics and offering promising avenues for drug development against SARS-CoV-2 in clinical settings.

Background To train highly qualified medical talent in 5-year programs and improve students’ analytical and problem-solving abilities, it is necessary to change the traditional teaching method. This study introduces the combined teaching method of case-based learning (CBL) and clinical pathway and evaluates its role in practical gynecological teaching. Methods Medical students in a 5-year program who were enrolled in the fourth year were selected as the research subjects; these students were randomized into two groups that separately received either the traditional teaching method or the combined teaching method of CBL and clinical pathway. Before the internship, a questionnaire was administered to explore students’ views of internship in gynecology, and after the internship, the questionnaire was administered to assess the two teaching methods. Furthermore, theoretical and skill tests were performed both before and after the internship. Results A total of 206 medical students in a 5-year program who were in their fourth year were enrolled in the study. Students in the experimental group performed significantly better than those in the control group. They performed significantly better in the postinternship test than in the preinternship test (P < 0.001). The questionnaire showed that more students in the experimental group thought that their learning interests, clinical skills, case analysis ability, clinical communication ability, understanding of theoretical knowledge and clinical thinking ability had improved and significantly differed between the two groups (P < 0.05). Discussion Compared to traditional teaching methods, combined teaching method of CBL and clinical pathway can elevate students’ academic performance, improve their learning enthusiasm and help promote clinical teachers’ teaching quality. Additionally, this novel method is effective in facilitating the achievement of teaching objectives and improving the quality of talent training. Therefore, the combined teaching method of CBL and clinical pathway should be popularized and applied in gynecological practice.

Abstract Tea plant [Camellia sinensis (L.) O. Kuntze] is one of the important foliar cash crops in China, and its root system absorbs heavy metal (HM) elements enriched in the soil and transports them to the over ground part. In order to ensure the safety of the soil ecological environment and tea raw materials in the tea production area, the HM contents of soil and tea plant leaves in Suzhou tea plantations were detected, the relationship between HMs and soil physicochemical properties was analyzed, and the ecological risk of HMs in tea plantation soils was evaluated by using relevant detection techniques and evaluation models. The results showed that the average pH of tea plantation soils around Tai Lake in Suzhou was within the range suitable for the growth of tea plants. The pH, soil organic matter, total nitrogen, available phosphorus and available potassium of tea plantation soil satisfying the requirements of high quality, high efficiency and high yield (‘3H’) tea plantation accounted for 47.06%, 26.47%, 8.82%, 79.41% and 67.65%, respectively. Site 2 fully met the requirements of ‘3H’ tea plantation. In addition, the contents of cadmium (Cd) and mercury (Hg) were extremely variable, and the average contents exceeded the background value of soil in Jiangsu Province, but the HM contents of tea leaves all met the pollution-free standard, and the HM contents of tea leaves around Tai Lake in Suzhou were generally at a safe level. The composite ecological risk index ranged from 0.05 to 0.60, and 32 of the 34 sample sites (except site 21 and site 23) are the most suitable agricultural land for tea plantations.

Today, pathogenic microorganisms are increasingly developing resistance to conventional drugs, necessitating the exploration of alternative strategies. In addressing this challenge, nano-based antibacterial agents offer a promising avenue of research. In the present study, we used an extract of Moringa oleifera, a widely recognized edible and medicinal plant, to synthesize biogenetic tellurium nanoparticles (Bio-TeNPs). Transmission electron microscopy, scanning electron microscopy, and dynamic light scattering analyses revealed that the obtained Bio-TeNPs had diameters between 20 and 50 nm, and zeta potential values of 23.7 ± 3.3 mV. Fourier-transform infrared spectroscopy and X-ray photoelectron spectroscopy revealed that the Bio-TeNPs consisted primarily of Te(0), along with some organic constituents. Remarkably, these Bio-TeNPs exhibited potent antibacterial activity against a spectrum of pathogens, including Escherichia coli, Klebsiella pneumoniae, Shigella dysenteriae, Salmonella typhimurium, Streptococcus pneumoniae, and Streptococcus agalactiae. In addition, findings from growth curve experiments, live/dead cell staining, and scanning electron microscopy observations of cell morphology demonstrated that Bio-TeNPs at a concentration of 0.07 mg/mL effectively disrupted E. coli and K. pneumoniae cells, leading to cell rupture or shrinkage. The biofilm inhibition rates of 0.7 mg/mL Bio-TeNPs against E. coli and K. pneumoniae reached 92% and 90%, respectively. In addition, 7 mg/mL Bio-TeNPs effectively eradicated E. coli from the surfaces of glass slides, with a 100% clearance rate. These outcomes underscore the exceptional antibacterial efficacy of Bio-TeNPs and highlight their potential as promising nanomaterials for combating bacterial infections.

This study investigated the effects of dietary resveratrol (RES) and β-Hydroxy-β-methyl butyric acid (HMB) on immune, oxidative, and morphological changes in the livers of Tibetan sheep using transcriptomics and metabolomics. One hundred and twenty male Tibetan lambs of a similar initial weight (15.5 ± 0.14 kg) were randomly divided into four groups with thirty lambs per treatment: (1) H group (basal diet without RES or HMB); (2) H-RES group (1.5 g/day of RES); (3) H-HMB group (1250 mg/day of HMB); (4) H-RES-HMB group (1.5 g/day of RES and 1250 mg/day of HMB). The experiment was conducted for 100 days, including a pre-test period of 10 days and a formal period of 90 days. The results showed significantly increased concentrations of glutathione peroxidase, superoxide dismutase, and IgM in the H-RES-HMB group (p < 0.05), while the malondialdehyde levels were significantly decreased (p < 0.05). The glycolytic indices including creatinine kinase (CK), malate dehydrogenase (MDH), and succinate dehydrogenase (SDH) were significantly increased in the H-RES-HMB group compared with the others (p < 0.05). A histological analysis showed that the hepatic plate tissue in the H-RES-HMB group appeared normal with multiple cells. The transcriptomic analysis showed that the expression of genes associated with the calcium signaling pathway (MYLK2, CYSLTR2, ADCY1, HRH1, ATP2B2, NOS2, HRC, ITPR1, and CAMK2B) and the NF-κB signaling pathway (BCL2 and CARD14) in the H-RES-HMB group were upregulated. The key differential metabolites (d-pyroglutamic acid, DL-serine, DL-threonine, fumarate, and glyceric acid) were enriched in the pathways associated with D-amino acid metabolism, the citrate cycle (TCA cycle), and carbon metabolism. The combined transcriptomic and non-targeted metabolomic analyses showed the co-enrichment of differential genes (NOS2 and GLUD1) and metabolites (fumarate) in arginine biosynthesis-regulated glycolytic activity, whereas the differential genes (ME1, SCD5, FABP2, RXRG, and CPT1B) and metabolites (Leukotriene b4) co-enriched in the PPAR signaling pathway affected the immune response by regulating the PI3K/AKT and cGMP/PKG signaling. In conclusion, the dietary RES and HMB affected the hepatic antioxidant capacity, immune response, and glycolytic activity through modulating the transcriptome (BCL2, CAMK2B, ITPR1, and IL1R1) and metabolome (DL-serine, DL-threonine, fumaric acid, and glycolic acid).

Epigenetics refers to the mechanisms such as DNA methylation and histone modification that influence gene expression without altering the DNA sequence. These epigenetic modifications can regulate gene transcription, splicing, and stability, thereby impacting cell differentiation, development, and disease occurrence. The formation of dentin is intrinsically linked to the odontogenic differentiation of dental pulp stem cells (DPSCs), which are recognized as the optimal cell source for dentin-pulp regeneration due to their varied odontogenic potential, strong proliferative and angiogenic characteristics, and ready accessibility Numerous studies have demonstrated the critical role of epigenetic regulation in DPSCs differentiation into specific cell types. This review thus provides a comprehensive review of the mechanisms by which epigenetic regulation controls the odontogenesis fate of DPSCs.

Abstract Arsenic (As) is a cancerogenic metalloid ubiquitously distributed in the environment, which can be easily accumulated in food crops like rice. Jasmonic acid (JA) and its derivatives play critical roles in plant growth and stress response. However, the role of endogenous JA in As accumulation and detoxification is still poorly understood. In this study, we found that JA biosynthesis enzymes Allene Oxide Synthases, OsAOS1 and OsAOS2, regulate As accumulation and As tolerance in rice. Evolutionary bioinformatic analysis indicated that AOS1 and AOS2 have evolved from streptophyte algae (e.g. the basal lineage Klebsormidium flaccidum) – sister clade of land plants. Compared to other two AOSs, OsAOS1 and OsAOS2 were highly expressed in all examined rice tissues and their transcripts were highly induced by As in root and shoot. Loss-of-function of OsAOS1 (osaos1–1) showed elevated As concentration in grains, which was likely attributed to the increased As translocation from root to shoot when the plants were subjected to arsenate [As(V)] but not arsenite [As (III)]. However, the mutation of OsAOS2 (osaos2–1) showed no such effect. Moreover, osaos1–1 and osaos2–1 increased the sensitivity of rice plants to both As(V) and As(III). Disrupted expression of genes involved in As accumulation and detoxification, such as OsPT4, OsNIP3;2, and OsOASTL-A1, was observed in both osaos1–1 and osaos2–1 mutant lines. In addition, a As(V)-induced significant decrease in Reactive Oxygen Species (ROS) production was observed in the root of osaos1–1 but not in osaos2–1. Taken together, our results indicate OsAOS1 modulates both As allocation and detoxification, which could be partially attributed to the altered gene expression profiling and ROS homeostasis in rice while OsAOS2 is important for As tolerance.

The dry beach length determines the hydraulic boundary of tailings impoundments and significantly impacts the infiltration line, which is crucial for the tailings dam. A deep learning method utilizing satellite images is presented to recognize the dry beach area and accurately measure the length of dry beaches in tailing ponds. Firstly, satellite images of various tailing ponds were gathered and the collection was enlarged to create a dataset of satellite images of tailing ponds. Then, a deep learning method was created using YOLOv5-seg to identify the dry beach area of tailing ponds from satellite images. The mask of the dry beach region was segmented and contour extraction was then carried out. Finally, the beach crest line was fitted based on the extracted contour. The pixel distance between the beach crest line and the dry beach boundary was measured and then translated into real distance by ground resolution. This paper’s case study compared the calculated length of dry beach with the real length obtained by field monitoring. The results of the case study showed that the minimum error of the method was 2.10%, the maximum error was 3.46%, and the average error was 2.70%, indicating high precision for calculating dry beach length in tailing ponds.

Tea plants are a perennial crop with significant economic value. Chlorophyll, a key factor in tea leaf color and photosynthetic efficiency, is affected by the photoperiod and usually exhibits diurnal and seasonal variations. In this study, high-throughput transcriptomic analysis was used to study the chlorophyll metabolism, under different photoperiods, of tea plants. We conducted a time-series sampling under a skeleton photoperiod (6L6D) and continuous light conditions (24 L), measuring the chlorophyll and carotenoid content at a photoperiod interval of 3 h (24 h). Transcriptome sequencing was performed at six time points across two light cycles, followed by bioinformatics analysis to identify and annotate the differentially expressed genes (DEGs) involved in chlorophyll metabolism. The results revealed distinct expression patterns of key genes in the chlorophyll biosynthetic pathway. The expression levels of CHLE (magnesium-protoporphyrin IX monomethyl ester cyclase gene), CHLP (geranylgeranyl reductase gene), CLH (chlorophyllase gene), and POR (cytochrome P450 oxidoreductase gene), encoding enzymes in chlorophyll synthesis, were increased under continuous light conditions (24 L). At 6L6D, the expression levels of CHLP1.1, POR1.1, and POR1.2 showed an oscillating trend. The expression levels of CHLP1.2 and CLH1.1 showed the same trend, they both decreased under light treatment and increased under dark treatment. Our findings provide potential insights into the molecular basis of how photoperiods regulate chlorophyll metabolism in tea plants.

This study demonstrated that wearable devices can distinguish between different levels of horse activity, categorized into three types based on the horse’s gaits: low activity (standing), medium activity (walking), and high activity (trotting, cantering, and galloping). Current research in activity level classification predominantly relies on deep learning techniques, known for their effectiveness but also their demand for substantial data and computational resources. This study introduces a combined acceleration threshold behavior recognition method tailored for wearable hardware devices, enabling these devices to classify the activity levels of horses directly. The approach comprises three sequential phases: first, a combined acceleration interval counting method utilizing a non-linear segmentation strategy for preliminary classification; second, a statistical analysis of the variance among these segments, coupled with multi-level threshold processing; third, a method using variance-based proximity classification for recognition. The experimental results show that the initial stage achieved an accuracy of 87.55% using interval counting, the second stage reached 90.87% with variance analysis, and the third stage achieved 91.27% through variance-based proximity classification. When all three stages are combined, the classification accuracy improves to 92.74%. Extensive testing with the Xinjiang Wild Horse Group validated the feasibility of the proposed solution and demonstrated its practical applicability in real-world scenarios.

Pomacea canaliculata, as an invasive exotic species in Asia, can adversely affect crop yields, eco-environment, and human health. Application of molluscicides containing metaldehyde is one effective method for controlling P. canaliculata. In order to investigate the effects of metaldehyde on adult snails, we conducted acute toxicological experiments to investigate the changes in enzyme activities and histopathology after 24 h and 48 h of metaldehyde action. The results showed that the median lethal concentrations (LC) of metaldehyde on P. canaliculata were 3.792, 2.195, 1.833, and 1.706 mg/L at exposure times of 24, 48, 72, and 96 h, respectively. Treatment and time significantly affected acetylcholinesterase (AChE), glutathione S-transferase (GST), and total antioxidant capacity (TAC) activity, with sex significantly affecting AChE, GST, and TAC activity and time significantly affecting carboxylesterase (CarE). In addition, the interaction of treatment and time significantly affected the activity of GST, CarE and TAC. In addition, histopathological changes occurred in the digestive glands, gills and gastropods of apple snail exposed to metaldehyde. Histological examination of the digestive glands included atrophy of the digestive cells, widening of the hemolymph gap, and an increase in basophils. In treated snails, the hemolymph gap in the gills was widely dilated, the columnar cells were disorganized or even necrotic, and the columnar muscle cells in the ventral foot were loosely arranged and the muscle fibers reduced. The findings of this study can provide some references for controlling the toxicity mechanism of invasive species.

The fungal Gβ-like protein has been reported to be involved in a variety of biological processes, such as mycelial growth, differentiation, conidiation, stress responses and infection. However, molecular mechanisms of the Gβ-like protein in regulating fungal development and pathogenicity are largely unknown. Here, we show that the Gβ-like protein gene Bcgbl1 in the gray mold fungus Botrytis cinerea plays a pivotal role in development and pathogenicity by regulating the mitogen-activated protein (MAP) kinases signaling pathways. The Bcgbl1 deletion mutants were defective in mycelial growth, sclerotial formation, conidiation, macroconidial morphogenesis, plant adhesion, and formation of infection cushions and appressorium-like structures, resulting in a complete loss of pathogenicity. Bcgbl1 interacted with BcSte50, the adapter protein of the cascade of MAP kinase (MAPK). Bcgbl1 mutants had reduced phosphorylation levels of two MAPKs, namely Bmp1 and Bmp3, thereby reducing infection. However, deletion of Bcgbl1 did not affect the intracellular cAMP level, and exogenous cAMP could not restore the defects. Moreover, Bcgbl1 mutants exhibited defects in cell wall integrity and oxidative stress tolerance. Transcriptional profiling revealed that Bcgbl1 plays a global role in regulation of gene expression upon hydrophobic surface induction. We further uncovered that three target genes encoding the hydrophobic surface binding proteins (HsbAs) contributed to the adhesion and virulence of B. cinerea. Overall, these findings suggest that Bcgbl1 had multiple functions and provided new insights for deciphering the Bcgbl1-mediated network for regulating development and pathogenicity of B. cinerea.

Background: To evaluate the corneal biomechanics of stable keratoconus suspects (Stable-KCS) at 1-year follow-up and compare them with those of subclinical keratoconus (SKC). Methods: This prospective case-control study included the eyes of 144 patients. Biomechanical and tomographic parameters were recorded (Corvis ST and Pentacam). Patients without clinical signs of keratoconus in both eyes but suspicious tomography findings were included in the Stable-KCS group (n = 72). Longitudinal follow-up was used to evaluate Stable-KCS changes. Unilateral keratoconus contralateral eyes with suspicious tomography were included in the SKC group (n = 72). T-tests and non-parametric tests were used for comparison. Multivariate general linear models were used to adjust for confounding factors for further analysis. Receiver operating characteristic (ROC) curves were used to analyze the distinguishability. Results: The biomechanical and tomographic parameters of Stable-KCS showed no progression during the follow-up time (13.19 ± 2.41 months, p > 0.05). Fifteen biomechanical parameters and the Stress–Strain Index (SSI) differed between the two groups (p < 0.016). The A1 dArc length showed the strongest distinguishing ability (area under the ROC = 0.888) between Stable-KCS and SKC, with 90.28% sensitivity and 77.78% specificity at the cut-off value of −0.0175. Conclusions: The A1 dArc length could distinguish between Stable-KCS and SKC, indicating the need to focus on changes in the A1 dArc length for keratoconus suspects during the follow-up period. Although both have abnormalities on tomography, the corneal biomechanics and SSI of Stable-KCS were stronger than those of SKC, which may explain the lack of progression of Stable-KCS.

Background: The overactivation of NF-κB signaling is a key hallmark for the pathogenesis of extranodal natural killer/T cell lymphoma (ENKTL), a very aggressive subtype of non-Hodgkin’s lymphoma yet with rather limited control strategies. Previously, we found that the dysregulated exportin-1 (also known as CRM1) is mainly responsible for tumor cells to evade apoptosis and promote tumor-associated pathways such as NF-κB signaling. Methods: Herein we reported the discovery and biological evaluation of a potent small molecule CRM1 inhibitor, LFS-1107. We validated that CRM1 is a major cellular target of LFS-1107 by biolayer interferometry assay (BLI) and the knockdown of CRM1 conferred tumor cells with resistance to LFS-1107. Results: We found that LFS-1107 can strongly suppresses the growth of ENKTL cells at low-range nanomolar concentration yet with minimal effects on human platelets and healthy peripheral blood mononuclear cells. Treatment of ENKTL cells with LFS-1107 resulted in the nuclear retention of IkBα and consequent strong suppression of NF-κB transcriptional activities, NF-κB target genes downregulation and attenuated tumor cell growth and proliferation. Furthermore, LFS-1107 exhibited potent activities when administered to immunodeficient mice engrafted with human ENKTL cells. Conclusions: Therefore, LFS-1107 holds great promise for the treatment of ENKTL and may warrant translation for use in clinical trials. Funding: Yang's laboratory was supported by the National Natural Science Foundation of China (Grant: 81874301), the Fundamental Research Funds for Central University (Grant: DUT22YG122) and the Key Research project of 'be Recruited and be in Command' in Liaoning Province (Personal Target Discovery for Metabolic Diseases).

Serotonin (5-HT) has been reported to play an important role in mammary gland involution that is defined as the process through which the gland returns to a nonlactating state. However, the overall picture of the regulatory mechanisms of 5-HT and the effects of serotonylation on mammary gland involution still need to be further investigated. The current study aimed to investigate the effects of 5-HT on global gene expression profiles of bovine mammary epithelial cells (MAC-T) and to preliminarily examine whether the serotonylation involved in the mammary gland involution by using Monodansylcadaverine (MDC), a competitive inhibitor of transglutaminase 2. Results showed that a high concentration of 5-HT decreased viability and transepithelial electrical resistance (TEER) in MAC-T cells. Transcriptome analysis indicated that 2477 genes were differentially expressed in MAC-T cells treated with 200 μg/mL of 5-HT compared with the control group, and the Notch, p53, and PI3K-Akt signaling pathways were enriched. MDC influenced 5-HT-induced MAC-T cell death, fatty acid synthesis, and the formation and disruption of tight junctions. Overall, a high concentration of 5-HT is able to accelerate mammary gland involution, which may be regulated through the Notch, p53, and PI3K-Akt signaling pathways. Serotonylation is involved in bovine mammary gland involution.

The hydrodynamic conditions of rivers affect fish habitats by influencing parameters such as river bottom topography. Ecological restoration projects change the water morphological characteristics of rivers. Here, water flow characteristics of the upper Yangtze River before and after the construction of a restoration project were analyzed using the computational fluid dynamics simulation method. The longitudinal diversion dam could divide the river into two flow velocity zones, and the outer flow is similar to the original river with a flow velocity of 0.75 m/s. However, flow velocity on the inner side of the river was about 0.25 m/s, forming a larger buffer area. The eddy became more diversified and stable, with a high eddy viscosity coefficient and less fluctuations, at 9 Pa·s; this was conducive to fish aggregation and spawning. At different depths, large gradient differences were observed between the inner and outer sides of the longitudinal diversion dam, and the turbulent current and upward flow of the inner side were obvious; this was more favorable to the aggregation of different fish species. The longitudinal dam body was under a pressure of about 200.2 Pa at the same flow rate; this was significantly lower than the pressure on the transverse dam body. The field flow test and fish survey data showed that the error rate of the simulation using the RNG turbulent model was less than 10% compared with actual mapping. After the restoration of fish habitats by the longitudinal diversion dam, the number of fish species in the area increased from 40 to 49; The density of fish in the water increased from 71.40 fish per 1,000 m2 before the project to 315.70 fish per 1,000 m2 after the project. These results can provide a reference for the rapid assessment of water morphology and fish habitat restoration in the future.

Successful pathogen infection in plant depends on a proper interaction between the invading pathogen and its host. Post-translational modification (PTM) plays critical role(s) in plant-pathogen interaction. However, how PTM of viral protein regulates plant immunity remains poorly understood. Here, we found that S162 and S165 of Chinese wheat mosaic virus (CWMV) cysteine-rich protein (CRP) are phosphorylated by SAPK7 and play key roles in CWMV infection. Furthermore, the phosphorylation-mimic mutant of CRP (CRPS162/165D) but not the non-phosphorylatable mutant of CRP (CRPS162/165A) interacts with RNA-binding protein UBP1-associated protein 2C (TaUBA2C). Silencing of TaUBA2C expression in wheat plants enhanced CWMV infection. In contrast, overexpression of TaUBA2C in wheat plants inhibited CWMV infection. TaUBA2C inhibits CWMV infection through recruiting the pre-mRNA of TaNPR1, TaPR1 and TaRBOHD to induce cell death and H2O2 production. This effect can be supressed by CRPS162/165D through changing TaUBA2C chromatin-bound status and attenuating it's the RNA- or DNA-binding activities. Taken together, our findings provide new knowledge on how CRP phosphorylation affects CWMV infection as well as the arms race between virus and wheat plants.

Current yeast metabolic engineering in isoprenoids production mainly focuses on rewiring of cytosolic metabolic pathway. However, the precursors, cofactors and the enzymes are distributed in various sub-cellular compartments, which may hamper isoprenoid biosynthesis. On the other side, pathway compartmentalization provides several advantages for improving metabolic flux toward target products. We here summarize the recent advances on harnessing sub-organelle for isoprenoids biosynthesis in yeast, and analyze the knowledge about the localization of enzymes, cofactors and metabolites for guiding the rewiring of the sub-organelle metabolism. This review may provide some insights for constructing efficient yeast cell factories for production of isoprenoids and even other natural products.

Extracting gait biometrics from videos has been receiving rocketing attention given its applications, such as person re-identification. Although deep learning arises as a promising solution to improve the accuracy of most gait recognition algorithms, the lack of enough training data becomes a bottleneck. One of the solutions to address data deficiency is to generate synthetic data. However, gait data synthesis is particularly challenging as the inter-subject and intra-subject variations of walking style need to be carefully balanced. In this paper, we propose a complete 3D framework to synthesize unlimited, realistic, and diverse motion data. In addition to walking speed and lighting conditions, we emphasize two key factors: 3D gait motion style and character appearance. Benefiting from its 3D nature, our system can provide various gait-related data, such as accelerometer data and depth map, not limited to silhouettes. We conducted various experiments using the off-the-shelf gait recognition algorithm and draw the following conclusions: (1) the real-to-virtual gap can be closed when adding a small portion of real-world data to a synthetically trained recognizer; (2) the amount of real training data needed to train competitive gait recognition systems can be reduced significantly; (3) the rich variations in gait data are helpful for investigating algorithm performance under different conditions. The synthetic data generator, as well as all experiments, will be made publicly available.

Japanese encephalitis virus (JEV) is the major cause of viral encephalitis in humans throughout Asia. In the past twenty years, the emergence of the genotype I (GI) JEV as the dominant genotype in Asian countries has raised a significant threat to public health security. However, no clinically approved drug is available for the specific treatment of JEV infection, and the commercial vaccines derived from the genotype III JEV strains merely provided partial protection against the GI JEV. Thus, an easy-to-perform platform in high-throughput is urgently needed for the antiviral drug screening and assessment of neutralizing antibodies specific against the GI JEV. In this study, we established a reverse genetics system for the GI JEV strain (YZ-1) using a homologous recombination strategy. Using this reverse genetic system, a gaussia luciferase (Gluc) expression cassette was inserted into the JEV genome to generate a reporter virus (rGI-Gluc). The reporter virus exhibited similar growth kinetics to the parental virus and remained genetically stable for at least ten passages in vitro. Of note, the bioluminescence signal strength of Gluc in the culture supernatants was well correlated with the viral progenies determined by viral titration. Taking advantage of this reporter virus, we established Gluc readout-based assays for antiviral drug screening and neutralizing antibody detection against the GI JEV. These Gluc readout-based assays exhibited comparable performance to the assays using an actual virus and are less time consuming and are applicable for a high-throughput format. Taken together, we generated a GI JEV reporter virus expressing a Gluc gene that could be a valuable tool for an antiviral drug screening assay and neutralization assay.

In this study, a group of large-scale biofloc shrimp culturing facilities were designed. The bioflocs were domesticated by continuously reducing the ratio of carbon to feed. The bacterial community diversity on the 20th, 40th, 60th, and 80th days was analyzed by high-throughput sequencing technology. The results showed that the biofloc content (0~16.8 ± 4.3) mL/L, TSS concentration (0~247.46 ± 27.3) mL/L, total ammonia nitrogen concentration (0~0.28 ± 0.052) mg/L, nitrite nitrogen concentration (0~4.13 ± 1.42) mg/L, nitrate nitrogen concentration (108.57 ± 19.6) mg/L were all within the safe concentration range of Litopenaeus vannamei. With the progress of reducing carbon input, the Chao1 index, the number of operational taxonomic units, and the Shannon index increased significantly. The number of OTUs of B80 (572.36 ± 13.26) was significantly higher than that of B60 (489.69 ± 12.97), B40 (423.35 ± 18.46) and B20 (407.67 ± 15.65) (p < 0.05). The Chao1 index of B80 (768.58 ± 36.96) was significantly higher than that of B60 (646.8 ± 52.53), B40 (569.7 ± 46.53) and B20 (516.3 ± 21.35) (p < 0.05). The Shannon index of B80 (5.63 ± 0.16) was higher than that of B60 (4.85 ± 0.13), B40 (4.68 ± 0.21) and B20 (3.65 ± 0.22), with significant difference (p < 0.05). At the end of the experiment, the domestication formed a micro-ecosystem with Proteobacteria as the carrier (46.98 ± 15.82%), Chloroflexi as the skeleton (2.2 ± 0.36%), Nitrospirae (1.35 ± 0.26%) as the main water treatment functional bacteria, and other bacteria as auxiliary nitrogen and phosphorus removal; At the genus level, unclassified_f_Rhodobacteracea (22.97 ± 3.82%), Ruegeria (10.35 ± 1.26%), Muricauda (5.73 ± 0.61%), Algoriphagus (3.75% ± 0.85%) and Nitrospira (1.56 ± 0.56%) are the dominant bacteria. Under the synergistic effect of the above bacteria, the biofloc system remains relatively stable. The survival rate and unit yield of shrimp were (65.32 ± 6.85)% and (4.15 ± 1.58) kg/m3, respectively.

In a convolutional neural network (CNN), dropout cannot work well because dropped information is not entirely obscured in convolutional layers where features are correlated spatially. Except for randomly discarding regions or channels, many approaches try to overcome this defect by dropping influential units. In this paper, we propose a non-random dropout method named FocusedDropout, aiming to make the network focus more on the target. In FocusedDropout, we use a simple but effective method to search for the target-related features, retain these features and discard others, which is contrary to the existing methods. We find that this novel method can improve network performance by making the network more target focused. Additionally, increasing the weight decay while using FocusedDropout can avoid overfitting and increase accuracy. Experimental results show that with a slight cost, 10% of batches employing FocusedDropout, can produce a nice performance boost over the baselines on multiple datasets of classification, including CIFAR10, CIFAR100 and Tiny ImageNet, and has a good versatility for different CNN models.

AimsTo characterize the genetic landscape and mutation spectrum of patients with corneal dystrophies (CDs) in a large Han ethnic Chinese Cohort with inherited eye diseases (IEDs).MethodsRetrospective study. A large IED cohort was recruited in this study, including 69 clinically diagnosed CD patients, as well as other types of eye diseases patients and healthy family members as controls. The 792 genes on the Target_Eye_792_V2 chip were used to screen all common IEDs in our studies, including 22 CD-related genes.ResultsWe identified 2334 distinct high-quality variants on 22 CD-related genes in a large IEDs cohort. A total of 21 distinct pathogenic or likely pathogenic mutations were identified, and the remaining 2313 variants in our IED cohort had no evidence of CD-related pathogenicity. Overall, 81.16% (n = 56/69) of CD patients received definite molecular diagnoses, and transforming growth factor-beta-induced protein (TGFBI), CHTS6, and SLC4A11 genes covered 91.07, 7.14, and 1.79% of the diagnosed cases, respectively. Twelve distinct disease-associated mutations in the TGFBI gene were identified, 11 of which were previously reported and one is novel. Four of these TGFBI mutations (p.D123H, p.M502V, p.P501T, and p.P501A) were redefined as likely benign in our Han ethnic Chinese IED cohort after performing clinical variant interpretation. These four TGFBI mutations were detected in asymptomatic individuals but not in CD patients, especially the previously reported disease-causing mutation p.P501T. Among 56 CD patients with positive detected mutations, the recurrent TGFBI mutations were p.R124H, p.R555W, p.R124C, p.R555Q, and p.R124L, and the proportions were 32.14, 19.64, 14.29, 10.71, and 3.57%, respectively. Twelve distinct pathogenic or likely pathogenic mutations of CHTS6 were detected in 28 individuals. The recurrent mutations were p.Y358H, p.R140X, and p.R205W, and the proportions were 25.00, 21.43, and 14.29%, respectively. All individuals associated with TGFBI were missense mutations; 74.19% associated with CHTS6 mutations were missense mutations, and 25.81% were non-sense mutations. Hot regions were located in exons 4 and 12 of TGFBI individuals and located in exon 3 of CHTS6 individuals. No de novo mutations were identified.ConclusionFor the first time, our large cohort study systematically described the variation spectrum of 22 CD-related genes and evaluated the frequency and pathogenicity of all 2334 distinct high-quality variants in our IED cohort. Our research will provide East Asia and other populations with baseline data from a Han ethnic population-specific level.

Generative Adversarial Networks (GANs) are powerful generative models for numerous tasks and datasets. However, most of the existing models suffer from mode collapse. The most recent research indicates that the reason for it is that the optimal transportation map from random noise to the data distribution is discontinuous, but deep neural networks (DNNs) can only approximate continuous ones. Instead, the latent representation is a better raw material used to construct a transportation map point to the data distribution than random noise. Because it is a low-dimensional mapping related to the data distribution, the construction procedure seems more like expansion rather than starting all over. Besides, we can also search for more transportation maps in this way with smoother transformation. Thus, we have proposed a new training methodology for GANs in this paper to search for more transportation maps and speed the training up, named Express Construction. The key idea is to train GANs with two independent phases for successively yielding latent representation and data distribution. To this end, an Auto-Encoder is trained to map the real data into the latent space, and two couples of generators and discriminators are used to produce them. To the best of our knowledge, we are the first to decompose the training procedure of GAN models into two more uncomplicated phases, thus tackling the mode collapse problem without much more computational cost. We also provide theoretical steps toward understanding the training dynamics of this procedure and prove assumptions. No extra hyper-parameters have been used in the proposed method, which indicates that Express Construction can be used to train any GAN models. Extensive experiments are conducted to verify the performance of realistic image generation and the resistance to mode collapse. The results show that the proposed method is lightweight, effective, and less prone to mode collapse.

In this paper, we propose a novel training strategy named Feature Mining for convolutional neural networks (CNNs) that aims to strengthen the network’s learning of the local features. Through experiments, we found that different parts of the feature contain different semantics, while the network will inevitably lose a large amount of local information during feedforward propagation. In order to enhance the learning of the local features, Feature Mining divides the complete feature into two complementary parts and reuses this divided feature to make the network capture different local information; we call the two steps Feature Segmentation and Feature Reusing. Feature Mining is a parameter-free method with a plug-and-play nature and can be applied to any CNN model. Extensive experiments demonstrated the wide applicability, versatility, and compatibility of our method.

Background The swamp eel (Monopterus albus) is a commercially important farmed species in China. The dysbiosis and homeostasis of gut microbiota has been suggested to be associated with the swamp eel’s disease pathogenesis and food digestion. Although the contributions of gut microbiome in fish growth and health has been increasingly recognized, little is known about the microbial community in the intestine of the swamp eel (Monopterus albus). Methods The intestinal microbiomes of the five distinct gut sections (midgut content and mucosa, hindgut content and mucosa, and stools) of swamp eel were compared using Illumina MiSeq sequencing of the bacterial 16S rRNA gene sequence and statistical analysis. Results The results showed that the number of observed OTUs in the intestine decreased proximally to distally. Principal coordinate analysis revealed significant separations among samples from different gut sections. There were 54 core OTUs shared by all gut sections and 36 of these core OTUs varied significantly in their abundances. Additionally, we discovered 66 section-specific enriched KEGG pathways. These section-specific enriched microbial taxa (e.g., Bacillus, Lactobacillus) and potential function capacities (e.g., amino acid metabolism, carbohydrate metabolism) might play vital roles in nutrient metabolism, immune modulation and host-microbe interactions of the swamp eel. Conclusions Our results showed that microbial diversity, composition and function capacity varied substantially across different gut sections. The gut section-specific enriched core microbial taxa and function capacities may perform important roles in swamp eel’s nutrient metabolism, immune modulation, and host-microbe interactions. This study should provide insights into the gut microbiome of the swamp eel.

It has been shown that the learning rate is one of the most critical hyper-parameters for the overall performance of deep neural networks. In this paper, we propose a new method for setting the global learning rate, named random amplify learning rates (RALR), to improve the performance of any optimizer in training deep neural networks. Instead of monotonically decreasing the learning rate, we expect to escape saddle points or local minima by amplifying the learning rate between reasonable boundary values based on a given probability. Training with RALR rather than conventionally decreasing the learning rate achieves further improvement on networks’ performance without extra consumption. Remarkably, the RALR is complementary with state-of-the-art data augmentation and regularization methods. Besides, we empirically study its performance on image classification tasks, fine-grained classification tasks, object detection tasks, and machine translation tasks. Experiments demonstrate that RALR can bring a notable improvement while preventing overfitting when training deep neural networks. For example, the classification accuracy of ResNet-110 trained on the CIFAR-100 dataset using RALR achieves a 1.34% gain compared with ResNet-110 trained traditionally.

Anthropogenic nitrogen (N) and sulfur (S) deposition can change above- and belowground biodiversity, including soil microbial diversity. The diversity of denitrifying microorganisms is of great significance to the calculation of the global nitrogen cycle and nitrogen flux. For a long time, nirK and nirS have been used as the functional genes to study denitrifying microorganisms, and have gradually become molecular markers for studying the composition and diversity of denitrifying bacteria. Here, three-time exposures to N and S applications (7, 30, and 60 days), were independently established. Additionally, the abundance, diversity, and structure of nirK- and nirS-type denitrifying communities were examined by sequencing analyses in response to three treatments, namely, N and S (TN/S), sodium chloride (TNaCl) and deionized water (pH = 7.0) (CK). Our results suggest that TN/S led to higher electrical conductivity (EC), total nitrogen (TN), total organic carbon (TOC), nitrate nitrogen (NO3−-N), ammonium nitrogen (NH4+-N), and lower pH compared with TNaCl and CK, which affected the diversity of nirK- and nirS-type denitrifying bacterial communities. We also observed that the nirK-type denitrifying community demonstrated a higher sensitivity to N and S additions. Overall, our results are important for the understanding of nitrogen in soil and N2O emissions.

Cystatins, as reversible inhibitors of papain-like and legumain proteases, have been identified in several plant species. Although the cystatin family plays crucial roles in plant development and defense responses to various stresses, this family in wheat (Triticum aestivum L.) is still poorly understood. In this study, 55 wheat cystatins (TaCystatins) were identified. All TaCystatins were divided into three groups and both the conserved gene structures and peptide motifs were relatively conserved within each group. Homoeolog analysis suggested that both homoeolog retention percentage and gene duplications contributed to the abundance of the TaCystatin family. Analysis of duplication events confirmed that segmental duplications played an important role in the duplication patterns. The results of codon usage pattern analysis showed that TaCystatins had evident codon usage bias, which was mainly affected by mutation pressure. TaCystatins may be regulated by cis-acting elements, especially abscisic acid and methyl jasmonate responsive elements. In addition, the expression of all selected TaCystatins was significantly changed following viral infection and cold stress, suggesting potential roles in response to biotic and abiotic challenges. Overall, our work provides new insights into TaCystatins during wheat evolution and will help further research to decipher the roles of TaCystatins under diverse stress conditions.

The formation of gaps in the endothelium is a crucial process underlying both cancer and immune cell extravasation, contributing to the functioning of the immune system during infection, the unfavorable development of chronic inflammation and tumor metastasis. Here, we present a stochastic-mechanical multiscale model of an endothelial cell monolayer and show that the dynamic nature of the endothelium leads to spontaneous gap formation, even without intervention from the transmigrating cells. These gaps preferentially appear at the vertices between three endothelial cells, as opposed to the border between two cells. We quantify the frequency and lifetime of these gaps, and validate our predictions experimentally. Interestingly, we find experimentally that cancer cells also preferentially extravasate at vertices, even when they first arrest on borders. This suggests that extravasating cells, rather than initially signaling to the endothelium, might exploit the autonomously forming gaps in the endothelium to initiate transmigration.

The food-burying behavior has been reported in many mammals and birds, but was rarely observed in invertebrates. The red imported fire ants, Solenopsis invicta Buren, is an invasive pest in many areas of the world that usually performing food-burying during the foraging processes. However, the impacted factors and measureable patterns of this behavior is largely unknown. In the present study, food-burying vs food-transport behaviors of Solenopsis invicta were observed under laboratory and field conditions. When starved (no food was provided for 37 days) in the laboratory, food (sausage) was consumed by large numbers of ants, and few burying behaviors were observed. However, when food was provided until satiation of the colonies, food-transport was suppressed and significantly more soil particles were relocated on the food and graph paper square (where the food was placed) when compared with these colonies exposed to starved conditions. Videotapes showed that soil particles (1.47 ± 0.09 mm2) were preferentially placed adjacent to (in contact with) the food items at the beginning; and after the edges were covered, ants transported significantly smaller soil particles (1.13 ± 0.06 mm2) to cover the food. Meanwhile, larger particles (1.96 ± 0.08 mm2) were pulled/dragged around (but not in contact with) the food. Interestingly, only a small number of ants, mainly the small workers, were involved in food-burying, and the ants tended to repeatedly transport soil particles. A total of 12 patterns of particle transport were identified, and soil particles were most frequently picked from the foraging arena and subsequently placed adjacent to the food. In the field, almost all released food was actively transported by Solenopsis invicta workers, and no burying behavior was observed. Our results show that the food-burying behavior of Solenopsis invicta may be associated with the suppressed foraging activity, and the burying task may be carried out by certain groups of workers.

The swamp eel (Monopterus albus) is an important commercial farmed fish species in China. However, it is susceptible to Aeromonas hydrophila infections, resulting in high mortality and considerable economic loss. Povidone-iodine (PVP-I) is a widely used chemical disinfectant in aquaculture, which can decrease the occurrence of diseases and improve the survival. However, environmental organic matter could affect the bactericidal effectiveness of PVP-I, and the efficacy of PVP-I in aquaculture water is still unknown. In this paper, disinfection assays were conducted to evaluate the effectiveness of PVP-I against the A. hydrophila in different types of water. We found that the effective germicidal concentration of PVP-I in outdoor aquaculture water was 25 ppm for 12 h. In indoor aquaculture water with 105 CFU/mL bacteria, 10 ppm and 20 ppm of PVP-I could kill 99% and 100% of the bacteria, respectively. The minimal germicidal concentration of PVP-I in Luria-Bertani broth was 4,000 ppm. Available iodine content assay in LB solutions confirmed that the organic substance had negative impact on the effectiveness of PVP-I, which was consistent with the different efficacy of PVP-I in different water samples. Acute toxicity tests showed that the 24 h-LC50 of PVP-I to swamp eel was 173.82 ppm, which was much higher than the germicidal concentrations in outdoor and indoor aquaculture water, indicating its safety and effectivity to control the A. hydrophila. The results indicated PVP-I can be helpful for preventing the transmission of A. hydrophila in swamp eel aquaculture.

The escaping behavior of termites has been documented under laboratory conditions; however, no study has been conducted in a field setting due to the difficulty of observing natural behaviors inside wood or structures (e.g., nests, tunnels, etc.). The black-winged termite, Odontotermes formosanus (Shiraki), is a subterranean macrotermitine species which builds extensive mud tubes on tree trunks. In the present study, 41 videos (totaling ∼2,700 min) were taken on 22 colonies/subcolonies of O. formosanus after their mud tubes were partially damaged by hand. In general, termites consistently demonstrated three phases of escape, including initiation (wandering near the mud-tube breach), individual escaping (single termites moving downward), and massive, unidirectional escaping flows (groups of termites moving downward). Downward moving and repairing were the dominant behavioral activities of individuals and were significantly more frequent than upward moving, turning/backward moving, or wandering. Interestingly, termites in escaping flows moved significantly faster than escaping individuals. Repairing behavior was observed shortly after the disturbance, and new mud tubes were preferentially constructed from the bottom up. When predators (i.e., ants) were present, however, termites stopped moving and quickly sealed the mud-tube openings by capping the broken ends. Our study provides an interesting example that documents an animal (besides humans) simultaneously carrying out pathway repairs and emergency evacuation without congestion.

This study explored the inhibiting effect and mechanism of myricanol on lung adenocarcinoma A549 xenografts in nude mice. Forty nude mice with subcutaneous A549 xenografts were randomly divided into five groups: high-dose myricanol (40 mg/kg body weight) group; middle-dose myricanol (20 mg/kg body weight) group; low-dose myricanol (10 mg/kg body weight) group; polyethylene glycol 400 vehicle group (1 mL/kg); and tumor model group. Nude mice were sacrificed after 14 days of treatment and the tumor inhibition rate (TIR, %) was then calculated. The relative mRNA expression levels of Bax, Bcl-2, VEGF, HIF-1α, and survivin in the tumor tissues were determined by real-time PCR. TUNEL assay was applied to determine cellular apoptosis, while IHC test was performed to detect the protein expression levels of Bax, Bcl-2, VEGF, HIF-1α, and survivin. The TIR of the three myricanol-treated groups ranged from 14.9% to 38.5%. The IHC results showed that the protein expression of Bcl-2, VEGF, HIF-1α, and survivin were consistently downregulated, whereas that of Bax was upregulated after myricanol treatment. Myricanol also significantly upregulated the mRNA expression of Bax and downregulated that of Bcl-2, VEGF, HIF-1α, and survivin in a dose-dependent manner (p < 0.05 to 0.001). These results are consistent with those of IHC. The TUNEL assay results indicated that apoptotic-positive cells significantly increased in the myricanol-treated tumor tissues compared with the cells of the vehicle control group (p < 0.01 to 0.001). These data suggest that myricanol could significantly decelerate tumor growth in vivo by inducing apoptosis.

The general utilization of processing equipment in industry has increased the risk of foreign material contamination. For example, peanut and walnut contaminants in whole wheat flour, which typically a healthy food, are a threat to people who are allergic to nuts. The feasibility of utilizing near-infrared hyperspectral imaging to inspect peanut and walnut powder in whole wheat flour was evaluated herein. Hyperspectral images at wavelengths 950–1700 nm were acquired. A standard normal variate combined with the Savitzky–Golay first derivative spectral transformation was adopted for the development of a partial least squares regression (PLSR) model to predict contamination concentrations. A successive projection algorithm (SPA) and uninformative variable elimination (UVE) for feature wavelength selection were compared. Two individual prediction models for peanut or walnut-contaminated flour, and a general multispectral model for both peanut-contaminated flour and walnut-contaminated flour, were developed. The optimal general multispectral model had promising results, with a determination coefficient of prediction (Rp2) of 0.987, and a root mean square error of prediction (RMSEP) of 0.373%. Visualization maps based on multispectral PLSR models reflected the contamination concentration variations in a spatial manner. The results demonstrated that near-infrared hyperspectral imaging has the potential to inspect peanut and walnut powders in flour for rapid quality control.

Visible/near-infrared (Vis/NIR) hyperspectral imaging (400–1000 nm) was applied to identify the growth process of Aspergillus flavus and Aspergillus parasiticus. The hyperspectral images of the two fungi that were growing on rose bengal medium were recorded daily for 6 days. A band ratio using two bands at 446 nm and 460 nm separated A. flavus and A. parasiticus on day 1 from other days. Image at band of 520 nm classified A. parasiticus on day 6. Principle component analysis (PCA) was performed on the cleaned hyperspectral images. The score plot of the second to sixth principal components (PC2 to PC6) gave a rough clustering of fungi in the same incubation time. However, in the plot, A. flavus on day 3 and day 4 and A. parasiticus on day 2 and day 3 overlapped. The average spectra of each fungus in each growth day were extracted, then PCA and support vector machine (SVM) classifier were applied to the full spectral range. SVM models built by PC2 to PC6 could identify fungal growth days with accuracies of 92.59% and 100% for A. flavus and A. parasiticus individually. In order to simplify the prediction models, competitive adaptive reweighted sampling (CARS) was employed to choose optimal wavelengths. As a result, nine (402, 442, 487, 502, 524, 553, 646, 671, 760 nm) and seven (461, 538, 542, 742, 753, 756, 919 nm) wavelengths were selected for A. flavus and A. parasiticus, respectively. New optimal wavelengths SVM models were built, and the identification accuracies were 83.33% and 98.15% for A. flavus and A. parasiticus, respectively. Finally, the visualized prediction images for A. flavus and A. parasiticus in different growth days were made by applying the optimal wavelength’s SVM models on every pixel of the hyperspectral image.

Fungi infection in maize kernels is a major concern worldwide due to its toxic metabolites such as mycotoxins, thus it is necessary to develop appropriate techniques for early detection of fungi infection in maize kernels. Thirty-six sterilised maize kernels were inoculated each day with Aspergillus parasiticus from one to seven days, and then seven groups (D1, D2, D3, D4, D5, D6, D7) were determined based on the incubated time. Another 36 sterilised kernels without inoculation with fungi were taken as control (DC). Hyperspectral images of all kernels were acquired within spectral range of 921–2529 nm. Background, labels and bad pixels were removed using principal component analysis (PCA) and masking. Separability computation for discrimination of fungal contamination levels indicated that the model based on the data of the germ region of individual kernels performed more effectively than on that of the whole kernels. Moreover, samples with a two-day interval were separable. Thus, four groups, DC, D1–2 (the group consisted of D1 and D2), D3–4 (D3 and D4), and D5–7 (D5, D6, and D7), were defined for subsequent classification. Two separate sample sets were prepared to verify the influence on a classification model caused by germ orientation, that is, germ up and the mixture of germ up and down with 1:1. Two smooth preprocessing methods (Savitzky-Golay smoothing, moving average smoothing) and three scatter-correction methods (normalization, standard normal variate, and multiple scatter correction) were compared, according to the performance of the classification model built by support vector machines (SVM). The best model for kernels with germ up showed the promising results with accuracies of 97.92% and 91.67% for calibration and validation data set, respectively, while accuracies of the best model for samples of the mixed kernels were 95.83% and 84.38%. Moreover, five wavelengths (1145, 1408, 1935, 2103, and 2383 nm) were selected as the key wavelengths in the discrimination of fungal contamination levels. In general, near-infrared hyperspectral imaging can be used for early detection of fungal contamination in maize kernels.