Antiviral activity of luteolin against porcine epidemic diarrhea virus in silico and in vitro.

BACKGROUND: Porcine epidemic diarrhea virus (PEDV) mainly causes acute and severe porcine epidemic diarrhea (PED), and is highly fatal in neonatal piglets. No reliable therapeutics against the infection exist, which poses a major global health issue for piglets. Luteolin is a flavonoid with anti-viral activity toward several viruses. RESULTS: We evaluated anti-viral effects of luteolin in PEDV-infected Vero and IPEC-J2 cells, and identified IC50 values of 23.87 µM and 68.5 µM, respectively. And found PEDV internalization, replication and release were significantly reduced upon luteolin treatment. As luteolin could bind to human ACE2 and SARS-CoV-2 main protease (Mpro) to contribute viral entry, we first identified that luteolin shares the same core binding site on pACE2 with PEDV-S by molecular docking and exhibited positive pACE2 binding with an affinity constant of 71.6 µM at dose-dependent increases by surface plasmon resonance (SPR) assay. However, pACE2 was incapable of binding to PEDV-S1. Therefore, luteolin inhibited PEDV internalization independent of PEDV-S binding to pACE2. Moreover, luteolin was firmly embedded in the groove of active pocket of Mpro in a three-dimensional docking model, and fluorescence resonance energy transfer (FRET) assays confirmed that luteolin inhibited PEDV Mpro activity. In addition, we also observed PEDV-induced pro-inflammatory cytokine inhibition and Nrf2-induced HO-1 expression. Finally, a drug resistant mutant was isolated after 10 cell culture passages concomitant with increasing luteolin concentrations, with reduced PEDV susceptibility to luteolin identified at passage 10. CONCLUSIONS: Our results push forward that anti-PEDV mechanisms and resistant-PEDV properties for luteolin, which may be used to combat PED.

Untargeted metabonomics and TLR4/ NF-κB signaling pathway analysis reveals potential mechanism of action of Dendrobium huoshanense polysaccharide in nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is marked by hepatic steatosis accompanied by an inflammatory response. At present, there are no approved therapeutic agents for NAFLD. Dendrobium Huoshanense polysaccharide (DHP), an active ingredient extracted from the stems of Dendrobium Huoshanense, and exerts a protective effect against liver injury. However, the therapeutic effects and mechanisms of action DHP against NAFLD remain unclear. DHP was extracted, characterized, and administered to mice in which NAFLD had been induced with a high-fat and high-fructose drinking (HFHF) diet. Our results showed that DHP used in this research exhibits the characteristic polysaccharide peak with a molecular weight of 179.935 kDa and is composed primarily of Man and Glc in a molar ratio of 68.97:31.03. DHP treatment greatly ameliorated NAFLD by significantly reducing lipid accumulation and the levels of liver function markers in HFHF-induced NAFLD mice, as evidenced by decreased serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), total cholesterol (TC) and total triglyceride (TG). Furthermore, DHP administration reduced hepatic steatosis, as shown by H&E and Oil red O staining. DHP also inhibited the Toll-like receptor 4 (TLR4)/nuclear factor-kappa B (NF-κB) signaling pathway expression, thereby reducing levels of hepatic proinflammatory cytokines. Besides, untargeted metabolomics further indicated that 49 metabolites were affected by DHP. These metabolites are strongly associated the metabolism of glycine, serine, threonine, nicotinate and nicotinamide, and arachidonic acid. In conclusion, DHP has a therapeutic effect against NAFLD, whose underlying mechanism may involve the modulation of TLR4/NF-κB, reduction of inflammation, and regulation of the metabolism of glycine, serine, threonine, nicotinate and nicotinamide metabolism, and arachidonic acid metabolism.

Oxygen-functionalized Fe3O4@o-polypyrrole acting as high-efficiency oxidase mimics and their application in glutathione colorimetric sensing.

The enzyme-like properties of nanozymes may be considerably affected by the structure and surface groups, which thus need to be optimized. Here, through a simple NaOH chemical corrosion method, the chemical structure similar to N-Methylpyrrolidone (NMP), which possessed intrinsic oxidase-like activity, was introduced into polypyrrole (PPy), and then this nanomaterial became oxygen-functionalized PPy (o-PPy) with excellent oxidase-like activity from PPy without this property. Furthermore, after compounding magnetic Fe3O4, the obtained nanocomposites Fe3O4@o-PPy nanoparticles (Fe3O4@o-PPy NPs) showed superiorities in separation during synthesis and real-time control of enzyme catalysis. Studies have found that the enzymatic activity of Fe3O4@o-PPy NPs depended on the amount of functionalized oxygen and the conjugation extent of o-PPy. Fe3O4@o-PPy NPs had efficient oxidase-like activity under a wide range of pH and temperature. Based on the oxidase-like activity of Fe3O4@o-PPy NPs, a colorimetric sensor for glutathione (GSH), which presented rich color changes and satisfactory colorimetric resolution by adding the amaranth, was realized. We believe that the functional modification and structural regulation of PPy can not only realize its wider application but also promote the discovery of novel and efficient nanozymes.

Parotid Gland Segmentation Using Purely Transformer-Based U-Shaped Network and Multimodal MRI.

Parotid gland tumors account for approximately 2% to 10% of head and neck tumors. Segmentation of parotid glands and tumors on magnetic resonance images is essential in accurately diagnosing and selecting appropriate surgical plans. However, segmentation of parotid glands is particularly challenging due to their variable shape and low contrast with surrounding structures. Recently, deep learning has developed rapidly, and Transformer-based networks have performed well on many computer vision tasks. However, Transformer-based networks have yet to be well used in parotid gland segmentation tasks. We collected a multi-center multimodal parotid gland MRI dataset and implemented parotid gland segmentation using a purely Transformer-based U-shaped segmentation network. We used both absolute and relative positional encoding to improve parotid gland segmentation and achieved multimodal information fusion without increasing the network computation. In addition, our novel training approach reduces the clinician's labeling workload by nearly half. Our method achieved good segmentation of both parotid glands and tumors. On the test set, our model achieved a Dice-Similarity Coefficient of 86.99%, Pixel Accuracy of 99.19%, Mean Intersection over Union of 81.79%, and Hausdorff Distance of 3.87. The purely Transformer-based U-shaped segmentation network we used outperforms other convolutional neural networks. In addition, our method can effectively fuse the information from multi-center multimodal MRI dataset, thus improving the parotid gland segmentation.

Swin MoCo: Improving parotid gland MRI segmentation using contrastive learning.

BACKGROUND: Segmentation of the parotid glands and tumors by MR images is essential for treating parotid gland tumors. However, segmentation of the parotid glands is particularly challenging due to their variable shape and low contrast with surrounding structures. PURPOSE: The lack of large and well-annotated datasets limits the development of deep learning in medical images. As an unsupervised learning method, contrastive learning has seen rapid development in recent years. It can better use unlabeled images and is hopeful to improve parotid gland segmentation. METHODS: We propose Swin MoCo, a momentum contrastive learning network with Swin Transformer as its backbone. The ImageNet supervised model is used as the initial weights of Swin MoCo, thus improving the training effects on small medical image datasets. RESULTS: Swin MoCo trained with transfer learning improves parotid gland segmentation to 89.78% DSC, 85.18% mIoU, 3.60 HD, and 90.08% mAcc. On the Synapse multi-organ computed tomography (CT) dataset, using Swin MoCo as the pre-trained model of Swin-Unet yields 79.66% DSC and 12.73 HD, which outperforms the best result of Swin-Unet on the Synapse dataset. CONCLUSIONS: The above improvements require only 4 h of training on a single NVIDIA Tesla V100, which is computationally cheap. Swin MoCo provides new approaches to improve the performance of tasks on small datasets. The code is publicly available at https://github.com/Zian-Xu/Swin-MoCo.

DesTrans: A medical image fusion method based on Transformer and improved DenseNet.

Medical image fusion can provide doctors with more detailed data and thus improve the accuracy of disease diagnosis. In recent years, deep learning has been widely used in the field of medical image fusion. The traditional method of medical image fusion is to operate by superimposing and other methods of pixels. The introduction of deep learning methods has improved the effectiveness of medical image fusion. However, these methods still have problems such as edge blurring and information redundancy. In this paper, we propose a deep learning network model based on Transformer and an improved DenseNet network module integration that can be applied to medical images and solve the above problems. At the same time, the method can be moved to natural images. The use of Transformer and dense concatenation enhances the feature extraction capability of the method by limiting the feature loss which reduces the risk of edge blurring. We compared several representative traditional methods and more advanced deep learning methods with this method. The experimental results show that the Transformer and the improved DenseNet network module have a strong capability of feature extraction. The method yields good results both in terms of visual quality and objective image evaluation metrics.

Smartphone-assisted hydrogel platform based on BSA-CeO2 nanoclusters for dual-mode determination of acetylcholinesterase and organophosphorus pesticides.

A dual-mode sensor was developed for detecting acetylcholinesterase (AChE) and organophosphorus pesticides (OPs) via bifunctional BSA-CeO2 nanoclusters (NCs) with oxidase-mimetic activity and fluorescence property. The dual-mode sensor has the characteristics of self-calibration and self-verification, meeting the needs of different detection conditions and provide more accurate results. The colorimetric sensor and fluorescence sensor have been successfully used for detecting AChE with limit of detection (LOD) of 0.081 mU/mL and 0.056 mU/mL, respectively, while the LOD for OPs were 0.9 ng/mL and 0.78 ng/mL, respectively. The recovery of AChE was 93.9-107.2% and of OPs was 95.8-105.0% in actual samples. A novel strategy was developed to monitor pesticide residues and detect AChE level, which will motivate future work to explore the potential applications of multifunctional nanozymes.

Bulk anda single-cell transcriptome profiling reveals the molecular characteristics of T cell-mediated tumor killing in pancreatic cancer.

Background: Despite the potential of immune checkpoint blockade (ICB) as a promising treatment for Pancreatic adenocarcinoma (PAAD), there is still a need to identify specific subgroups of PAAD patients who may benefit more from ICB. T cell-mediated tumor killing (TTK) is the primary concept behind ICB. We explored subtypes according to genes correlated with the sensitivity to TKK and unraveled their underlying associations for PAAD immunotherapies. Methods: Genes that control the responsiveness of T cell-induced tumor destruction (GSTTK) were examined in PAAD, focusing on their varying expression levels and association with survival results. Moreover, samples with PAAD were separated into two subsets using unsupervised clustering based on GSTTK. Variability was evident in the tumor immune microenvironment, genetic mutation, and response to immunotherapy among different groups. In the end, we developed TRGscore, an innovative scoring system, and investigated its clinical and predictive significance in determining sensitivity to immunotherapy. Results: Patients with PAAD were categorized into 2 clusters based on the expression of 52 GSTTKs, which showed varying levels and prognostic relevance, revealing unique TTK patterns. Survival outcome, immune cell infiltration, immunotherapy responses, and functional enrichment are also distinguished among the two clusters. Moreover, we found the CATSPER1 gene promotes the progression of PAAD through experiments. In addition, the TRGscore effectively predicted the responses to chemotherapeutics or immunotherapy in patients with PAAD and overall survival. Conclusions: TTK exerted a vital influence on the tumor immune environment in PAAD. A greater understanding of TIME characteristics was gained through the evaluation of the variations in TTK modes across different tumor types. It highlights variations in the performance of T cells in PAAD and provides direction for improved treatment approaches.

[Chemical Characteristics and Genetic Analysis of Karst Groundwater in the Beijing Xishan Area].

As an important water supply source in Beijing， karst groundwater has played an irreplaceable role in the security of urban water supply and ecological environment protection in the past 70 years. The Xishan karst groundwater system， located in the upper reaches of western Beijing， belongs to ecological conservation areas. There are several centralized water supply fields in this area. In this study， the Xishan karst groundwater system was taken as the research object. A total of 120 karst groundwater samples in this area were investigated by using statistical analysis， ion ratio， and principal component analysis （PCA） methods to explore the spatial distribution characteristics and formation mechanism of groundwater hydrochemistry. The research results showed that： ① the groundwater quality of the Xishan system was generally good， with the characteristics of neutral pH and low salinity. A total of 84.17% of the water samples were classified as hard water. The chemical type of groundwater was mainly HCO3-Ca·Mg. ② The chemical composition of groundwater was mainly affected by the water-rock interaction， and the weathering source of rock was mainly the dissolution of carbonate. ③ The results of principal component analysis showed that 34.41% of the chemistry formation of groundwater could be explained by carbonate dissolution， 27.33% by rock salt and evaporate dissolution， 11.76% by aquifer sediment dissolution， and 10.30% by domestic sewage discharge. From the recharge area to the runoff area and then to the discharge area， the TH and TDS gradually increased. Coal mining drainage and human activities were the main factors that caused groundwater degradation and variable hydrochemical types in the piedmont. In the future， it is necessary to further strengthen environmental governance， control point and non-point source pollution， and continuously monitor key areas to provide scientific support for ecological and environmental protection.

How plants sense and respond to osmotic stress.

Drought is one of the most serious abiotic stresses to land plants. Plants sense and respond to drought stress to survive under water deficiency. Scientists have studied how plants sense drought stress, or osmotic stress caused by drought, ever since Charles Darwin, and gradually obtained clues about osmotic stress sensing and signaling in plants. Osmotic stress is a physical stimulus that triggers many physiological changes at the cellular level, including changes in turgor, cell wall stiffness and integrity, membrane tension, and cell fluid volume, and plants may sense some of these stimuli and trigger downstream responses. In this review, we emphasized water potential and movements in organisms, compared putative signal inputs in cell wall-containing and cell wall-free organisms, prospected how plants sense changes in turgor, membrane tension, and cell fluid volume under osmotic stress according to advances in plants, animals, yeasts, and bacteria, summarized multilevel biochemical and physiological signal outputs, such as plasma membrane nanodomain formation, membrane water permeability, root hydrotropism, root halotropism, Casparian strip and suberin lamellae, and finally proposed a hypothesis that osmotic stress responses are likely to be a cocktail of signaling mediated by multiple osmosensors. We also discussed the core scientific questions, provided perspective about the future directions in this field, and highlighted the importance of robust and smart root systems and efficient source-sink allocations for generating future high-yield stress-resistant crops and plants.

Isolation, characterization, evaluation of pathogenicity, and immunomodulation through interferon production of duck adenovirus type-3 (DAdV-3).

Duck adenovirus type-3 (DAdV-3) is a poorly characterized duck virus. A comprehensive analysis of the DAdV-3 pathogenicity and host immune response could be a valuable addition. Herein, DAdV-3 was isolated from Muscovy duck and virus-specific genes were confirmed by polymerase chain reaction (PCR). The obtained gene fragments were sequenced and compared with the reference sequence. Results confirmed that the clinically isolated virus was DAdV-3, named as HF-AN-2020. To evaluate DAdV-3 host immune response, the expression levels of MDA5, STING, IRF7, MAVS, and NF-κB, and inflammatory cytokines (IFN-ß, IFN-γ, and IL-1ß) were determined by quantitative reverse transcriptase PCR (qRT-PCR). The expression levels of IFN-ß and IFN-γ were 32.6- and 28.6-fold, respectively, higher (P < 0.01) than the control group. It was found that the upregulation of STING and NF-κB pathways was directly involved in the regulation of inflammatory cytokines (IFN-ß, IFN-γ, and IL-1ß). Furthermore, the gene regulation pathways consecutively upregulated the expression levels of MDA5, STING, IRF7, MAVS, and NF-κB up to 31.6, 10.5, 31.4, 2.2, and 2.6-fold, respectively, higher (P < 0.01) than the control group. The TCID50 of DAdV-3 for Muscovy duck and chicken was 10-3.24/0.1 mL with 0% mortality, indicating low pathogenicity in both Muscovy ducks and chickens, but DAdV-3 can induce higher expression of interferons. Genome analysis showed mutations in 4 amino acids located in ORF19B (Ser to Thr), ORF66 (Leu to Phe, Ile to Leu), and ORF67 (Gly to stop codon). This study provides essential and basic information for further research on the mechanism of the cellular immune responses against adenoviruses.

Time-resolved chemical monitoring of whole plant roots with printed electrochemical sensors and machine learning.

Traditional single-point measurements fail to capture dynamic chemical responses of plants, which are complex, nonequilibrium biological systems. We report TETRIS (time-resolved electrochemical technology for plant root environment in situ chemical sensing), a real-time chemical phenotyping system for continuously monitoring chemical signals in the often-neglected plant root environment. TETRIS consisted of low-cost, highly scalable screen-printed electrochemical sensors for monitoring concentrations of salt, pH, and H2O2 in the root environment of whole plants, where multiplexing allowed for parallel sensing operation. TETRIS was used to measure ion uptake in tomato, kale, and rice and detected differences between nutrient and heavy metal ion uptake. Modulation of ion uptake with ion channel blocker LaCl3 was monitored by TETRIS and machine learning used to predict ion uptake. TETRIS has the potential to overcome the urgent "bottleneck" in high-throughput screening in producing high-yielding plant varieties with improved resistance against stress.

Natural variants of molybdate transporters contribute to yield traits of soybean by affecting auxin synthesis.

Soybean (Glycine max) is a crop with high demand for molybdenum (Mo) and typically requires Mo fertilization to achieve maximum yield potential. However, the genetic basis underlying the natural variation of Mo concentration in soybean and its impact on soybean agronomic performance is still poorly understood. Here, we performed a genome-wide association study (GWAS) to identify GmMOT1.1 and GmMOT1.2 that drive the natural variation of soybean Mo concentration and confer agronomic traits by affecting auxin synthesis. The soybean population exhibits five haplotypes of the two genes, with the haplotype 5 demonstrating the highest expression of GmMOT1.1 and GmMOT1.2, as well as the highest transport activities of their proteins. Further studies showed that GmMOT1.1 and GmMOT1.2 improve soybean yield, especially when cultivated in acidic or slightly acidic soil. Surprisingly, these two genes contribute to soybean growth by enhancing the activity of indole-3-acetaldehyde (IAAld) aldehyde oxidase (AO), leading to increased indole-3-acetic acid (IAA) synthesis, rather than being involved in symbiotic nitrogen fixation or nitrogen assimilation. Furthermore, the geographical distribution of five haplotypes in China and their correlation with soil pH suggest the potential significance of GmMOT1.1 and GmMOT1.2 in soybean breeding strategies.

The evolutionary innovation of root suberin lamellae contributed to the rise of seed plants.

Seed plants overtook ferns to become the dominant plant group during the late Carboniferous, a period in which the climate became colder and dryer1,2. However, the specific innovations driving the success of seed plants are not clear. Here we report that the appearance of suberin lamellae (SL) contributed to the rise of seed plants. We show that the Casparian strip and SL vascular barriers evolved at different times, with the former originating in the most recent common ancestor (MRCA) of vascular plants and the latter in the MRCA of seed plants. Our results further suggest that most of the genes required for suberin formation arose through gene duplication in the MRCA of seed plants. We show that the appearance of the SL in the MRCA of seed plants enhanced drought tolerance through preventing water loss from the stele. We hypothesize that SL provide a decisive selective advantage over ferns in arid environments, resulting in the decline of ferns and the rise of gymnosperms. This study provides insights into the evolutionary success of seed plants and has implications for engineering drought-tolerant crops or fern varieties.

A dirigent protein complex directs lignin polymerization and assembly of the root diffusion barrier.

Functionally similar to the tight junctions present in animal guts, plant roots have evolved a lignified Casparian strip as an extracellular diffusion barrier in the endodermis to seal the root apoplast and maintain nutrient homeostasis. How this diffusion barrier is structured has been partially defined, but its lignin polymerization and assembly steps remain elusive. Here, we characterize a family of dirigent proteins (DPs) essential for both the localized polymerization of lignin required for Casparian strip biogenesis in the cell wall and for attachment of the strip to the plasma membrane to seal the apoplast. We reveal a Casparian strip lignification mechanism that requires cooperation between DPs and the Schengen pathway. Furthermore, we demonstrate that DPs directly mediate lignin polymerization as part of this mechanism.

Endocytosis-mediated entry of a caterpillar effector into plants is countered by Jasmonate.

Insects and pathogens release effectors into plant cells to weaken the host defense or immune response. While the imports of some bacterial and fungal effectors into plants have been previously characterized, the mechanisms of how caterpillar effectors enter plant cells remain a mystery. Using live cell imaging and real-time protein tracking, we show that HARP1, an effector from the oral secretions of cotton bollworm (Helicoverpa armigera), enters plant cells via protein-mediated endocytosis. The entry of HARP1 into a plant cell depends on its interaction with vesicle trafficking components including CTL1, PATL2, and TET8. The plant defense hormone jasmonate (JA) restricts HARP1 import by inhibiting endocytosis and HARP1 loading into endosomes. Combined with the previous report that HARP1 inhibits JA signaling output in host plants, it unveils that the effector and JA establish a defense and counter-defense loop reflecting the robust arms race between plants and insects.

[Active components and potential mechanism of Taohong Siwu Decoction in regulating ischemic stroke based on target cell trapping combined with network pharmacology, molecular docking, and experimental validation].

The potential anti-stroke active components in Taohong Siwu Decoction(THSWD) were identified by target cell trapping coupled with ultra-high performance liquid chromatography-quadrupole-time of flight mass spectrometry(UPLC-Q-TOF-MS). The underlying mechanism of active components in THSWD in the treatment of ischemic stroke(IS) was explored by network pharmacology, molecular docking, and experimental validation. The UPLC-Q-TOF-MS technology combined with the UNIFI data analysis platform was used to analyze the composition of the cellular fragmentation fluid after co-incubation of THSWD with target cells. The targets of potential active components and IS were collected by network pharmacology, and the common targets underwent protein-protein interaction(PPI), Gene Ontology(GO), and Kyoto Encyclopedia of Genes and Genomes(KEGG) signaling pathway enrichment analyses. The target cell trapping component-core target-signaling pathway network was constructed, and the active components were molecularly docked to the top targets in the PPI network, followed by pharmacodynamic validation in vitro. Fifteen active components were identified in the target cellular fragmentation fluid, including bicyclic monoterpenes, cyanoglycosides, flavonols, quinoid chalcones, phenylpropanoids, and tannins. As revealed by the analysis of network pharmacology, THSWD presumably regulated PI3K-AKT, FoxO, MAPK, Jak-STAT, VEGF, HIF-1, and other signaling pathways to affect inflammatory cascade reaction, angiogenesis, oxidative stress, pyroptosis, apoptosis, and other pathological processes via paeoniflorin, butylphthalide, dehydrated safflower yellow B, 3,4-dicaffeoylquinic acid, amygdalin, paeoniflorin, and ligusticolactone. Molecular docking and in vitro pharmacodynamic validation revealed that the target cell trapping active components could promote neovascularization in rat brain microvascular endothelial cells(rBMECs) in the oxygen-glucose deprivation/reoxygenation(OGD/R) model. The application of target cell trapping coupled with UPLC-Q-TOF-MS technology can rapidly screen out the potential active components in THSWD. The active components of THSWD can be predicted to intervene in the pathogenesis of IS through network pharmacology, and molecular docking combined with experimental validation can further clarify the efficacy, thus providing a theoretical basis for research ideas on the pharmacodynamic substance basis of traditional Chinese medicine compounds.

[Origin identification of Poria cocos based on hyperspectral imaging technology].

To realize the non-destructive and rapid origin discrimination of Poria cocos in batches, this study established the P. cocos origin recognition model based on hyperspectral imaging combined with machine learning. P. cocos samples from Anhui, Fujian, Guangxi, Hubei, Hunan, Henan and Yunnan were used as the research objects. Hyperspectral data were collected in the visible and near infrared band(V-band, 410-990 nm) and shortwave infrared band(S-band, 950-2 500 nm). The original spectral data were divided into S-band, V-band and full-band. With the original data(RD) of different bands, multiplicative scatter correction(MSC), standard normal variation(SNV), S-G smoothing(SGS), first derivative(FD), second derivative(SD) and other pretreatments were carried out. Then the data were classified according to three different types of producing areas: province, county and batch. The origin identification model was established by partial least squares discriminant analysis(PLS-DA) and linear support vector machine(LinearSVC). Finally, confusion matrix was employed to evaluate the optimal model, with F1 score as the evaluation standard. The results revealed that the origin identification model established by FD combined with LinearSVC had the highest prediction accuracy in full-band range classified by province, V-band range by county and full-band range by batch, which were 99.28%, 98.55% and 97.45%, respectively, and the overall F1 scores of these three models were 99.16%, 98.59% and 97.58%, respectively, indicating excellent performance of these models. Therefore, hyperspectral imaging combined with LinearSVC can realize the non-destructive, accurate and rapid identification of P. cocos from different producing areas in batches, which is conducive to the directional research and production of P. cocos.

[Origin identification of Polygonatum cyrtonema based on hyperspectral data].

In this study, visual-near infrared(VNIR), short-wave infrared(SWIR), and VNIR + SWIR fusion hyperspectral data of Polygonatum cyrtonema from different geographical origins were collected and preprocessed by first derivative(FD), second derivative(SD), Savitzky-Golay smoothing(S-G), standard normalized variate(SNV), multiplicative scatter correction(MSC), FD+S-G, and SD+S-G. Three algorithms, namely random forest(RF), linear support vector classification(LinearSVC), and partial least squares discriminant analysis(PLS-DA), were used to establish the identification models of P. cyrtonema origin from three spatial scales, i.e., province, county, and township, respectively. Successive projection algorithm(SPA) and competitive adaptive reweighted sampling(CARS) were used to screen the characteristic bands, and the P. cyrtonema origin identification models were established according to the selected characteristic bands. The results showed that(1)after FD preprocessing of VNIR+SWIR fusion hyperspectral data, the accuracy of recognition models established using LinearSVC was the highest, reaching 99.97% and 99.82% in the province origin identification model, 100.00% and 99.46% in the county origin identification model, and 99.62% and 98.39% in the township origin identification model. The accuracy of province, county, and township origin identification models reached more than 98.00%.(2)Among the 26 characteristic bands selected by CARS, after FD pretreatment, the accuracy of origin identification models of different spatial scales was the highest using LinearSVC, reaching 98.59% and 97.05% in the province origin identification model, 97.79% and 94.75% in the county origin identification model, and 90.13% and 87.95% in the township origin identification model. The accuracy of identification models of different spatial scales established by 26 characteristic bands reached more than 87.00%. The results show that hyperspectral imaging technology can realize accurate identification of P. cyrtonema origin from different spatial scales.

Development of a CD8+ T cell-based molecular classification for predicting prognosis and heterogeneity in triple-negative breast cancer by integrated analysis of single-cell and bulk RNA-sequencing.

Background: Triple-negative breast cancer (TNBC), although the most intractable subtype, is characterized by abundant immunogenicity, which enhances responsiveness to immunotherapeutic measures. Methods: First, we identified CD8+ T cell core genes (TRCG) based on single-cell sequence and traditional transcriptome sequencing and then used this data to develop a first-of-its-kind classification system based on CD8+ T cells in patients with TNBC. Next, TRCG-related patterns were systematically analyzed, and their correlation with genomic features, immune activity (microenvironment associated with immune infiltration), and clinicopathological characteristics were assessed in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), the Cancer Genome Atlas (TCGA), GSE103091, GSE96058 databases. Additionally, a CD8+ T cell-related prognostic signature (TRPS) was developed to quantify a patient-specific TRCG pattern. What's more, the genes-related TRPS was validated by polymerase chain reaction (PCR) experiment. Results: This study, for the first time, distinguished two subsets in patients with TNBC based on the TRCG. The immune microenvironment and prognostic stratification between these have distinct heterogeneity. Furthermore, this study constructed a novel scoring system named TRPS, which we show to be a robust prognostic marker for TNBC that is related to the intensity of immune infiltration and immunotherapy. Moreover, the levels of genes related the TRPS were validated by quantitative Real-Time PCR. Conclusions: Consequently, this study unraveled an association between the TRCG and the tumor microenvironment in TNBC. TRPS model represents an effective tool for survival prediction and treatment guidance in TNBC that can also help identify individual variations in TME and stratify patients who are sensitive to anticancer immunotherapy.