Transcriptomics analyses reveal the key genes involved in stamen petaloid formation in Alcea rosea L.

Alcea rosea L. is a traditional flower with a long cultivation history. It is extensively cultivated in China and is widely planted in green belt parks or used as cut flowers and potted ornamental because of its rich colors and flower shapes. Double-petal A. rosea flowers have a higher aesthetic value compared to single-petal flowers, a phenomenon determined by stamen petaloid. However, the underlying molecular mechanism of this phenomenon is still very unclear. In this study, an RNA-based comparative transcriptomic analysis was performed between the normal petal and stamen petaloid petal of A. rosea. A total of 3,212 differential expressed genes (DEGs), including 2,620 up-regulated DEGs and 592 down-regulated DEGs, were identified from 206,188 unigenes. Numerous DEGs associated with stamen petaloid were identified through GO and KEGG enrichment analysis. Notably, there were 63 DEGs involved in the plant hormone synthesis and signal transduction, including auxin, cytokinin, gibberellin, abscisic acid, ethylene, brassinosteroid, jasmonic acid, and salicylic acid signaling pathway and 56 key transcription factors (TFs), such as MADS-box, bHLH, GRAS, and HSF. The identification of these DEGs provides an important clue for studying the regulation pathway and mechanism of stamen petaloid formation in A. rosea and provides valuable information for molecular plant breeding.

Lysine malonylation of DgnsLIPID TRANSFER PROTEIN1 at the K81 site improves cold resistance in chrysanthemum.

Lysine malonylation (Kmal) is a recently discovered posttranslational modification, and its role in the response to abiotic stress has not been reported in plants. In this study, we isolated a nonspecific lipid transfer protein, DgnsLTP1, from chrysanthemum (Dendranthema grandiflorum var. Jinba). Overexpression and CRISPR-Cas9-mediated gene editing of DgnsLTP1 demonstrated that the protein endows chrysanthemum with cold tolerance. Yeast 2-hybrid, bimolecular fluorescence complementation, luciferase complementation imaging, and coimmunoprecipitation experimental results showed that DgnsLTP1 interacts with a plasma membrane intrinsic protein (PIP) DgPIP. Overexpressing DgPIP boosted the expression of DgGPX (glutathione peroxidase), increased the activity of GPX, and decreased the accumulation of reactive oxygen species (ROS), thereby enhancing the low-temperature stress tolerance of chrysanthemum, while the CRISPR-Cas9-mediated mutant dgpip inhibited this process. Transgenic analyses in chrysanthemum showed that DgnsLTP1 improves the cold resistance of chrysanthemum in a DgPIP-dependent manner. Moreover, Kmal of DgnsLTP1 at the K81 site prevented the degradation of DgPIP in Nicotiana benthamiana and chrysanthemum, further promoted DgGPX expression, enhanced GPX activity, and scavenged excess ROS produced by cold stress, thereby further enhancing the cold resistance of chrysanthemum.

Unraveling Key Factors for Hypoxia Tolerance in Contrasting Varieties of Cotton Rose by Comparative Morpho-physiological and Transcriptome Analysis.

The cotton rose (Hibiscus mutabilis) is a plant species commonly found in tropical and subtropical regions. It is remarkably resilient to waterlogging stress; however, the underlying mechanism behind this trait is yet unknown. This study used hypoxia-tolerant "Danbanhong" (DBH) and more hypoxia-sensitive "Yurui" (YR) genotypes and compared their morpho-physiological and transcriptional responses to hypoxic conditions. Notably, DBH had a higher number of adventitious roots (20.3) compared to YR (10.0), with longer adventitious roots in DBH (18.3 cm) than in YR (11.2 cm). Furthermore, the formation of aerenchyma was 3-fold greater in DBH compared to YR. Transcriptomic analysis revealed that DBH had more rapid transcriptional responses to hypoxia than YR. Identification of a greater number of differentially expressed genes (DEGs) for aerenchyma, adventitious root formation and development, and energy metabolism in DBH supported that DBH had better morphological and transcriptional adaptation than YR. DEG functional enrichment analysis indicated the involvement of variety-specific biological processes in adaption to hypoxia. Plant hormone signaling transduction, MAPK signaling pathway and carbon metabolism played more pronounced roles in DBH, whereas the ribosome genes were specifically induced in YR. These results show that effective multilevel coordination of adventitious root development and aerenchyma, in conjunction with plant hormone signaling and carbon metabolism, is required for increased hypoxia tolerance. This study provides new insights into the characterization of morpho-physiological and transcriptional responses to hypoxia in H. mutabilis, shedding light on the molecular mechanisms of its adaptation to hypoxic environments.

Novel EDGE encoding method enhances ability to identify genetic interactions.

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)-rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.

Effects of cadmium and zinc interactions on the physiological biochemistry and enrichment characteristics of Iris pseudacorus.

Compound pollution with cadmium (Cd) and zinc (Zn) is common in nature. The effects of compounded Cd and Zn on the growth and development of Iris pseudacorus in the environment and the plant's potential to remediate heavy metals in the environment remain unclear. In this study, the effects of single and combined Cd and Zn stress on I. pseudacorus growth and the enrichment of heavy metals in I. pseudacorus seedlings were investigated. The results showed that under Cd (160 µM) and Zn (800 µM) stress, plant growth was significantly inhibited and photosynthetic performance was affected. Cd+Zn200 (160 µM + 200 µM) reduced the levels of malondialdehyde, hydrogen peroxide, and non-protein thiols by 31.29%, 53.20%, and 13.29%, respectively, in the aboveground tissues compared with levels in the single Cd treatment. However, Cd+Zn800 (160 µM + 800 µM) had no effect. Cd and Zn800 inhibited the absorption of mineral elements, while Zn200 had little effect on plants. Compared with that for Cd treatment alone, Cd + Zn200 and Cd+Zn800 reduced the Cd content in aboveground tissues by 54.15% and 49.92%, respectively, but had no significant effect on Cd in the root system. Zn significantly reduced the Cd content in subcellular components and limited the content and proportion of Cd extracted using water and ethanol. These results suggest that a low supply of Zn reduces Cd accumulation in aboveground tissues by promoting antioxidant substances and heavy metal chelating agents, thus protecting the photosynthetic systems. The addition of Zn also reduced the mobility and bioavailability of Cd to alleviate its toxicity in I. pseudacorus.

Clinicopathological features of differentiated thyroid carcinoma as predictors of the effects of radioactive iodine therapy.

BACKGROUND: Patients with differentiated thyroid cancer (DTC) usually have an excellent prognosis; however, 5 %-15 % develop radioactive iodine-refractory (RAIR) DTC (RAIR-DTC), which has a poor prognosis and limited treatment options. The aim of the present study was to investigate the clinicopathological characteristics of RAIR-DTC in order to provide clinical evidence for timely prediction of the effects of iodine therapy. METHODS: Clinicopathological data for 44 patients with RAIR-DTC and 50 patients with radioiodine-avid DTC (RAIA-DTC) were retrospectively analyzed. The risk factors for RAIR-DTC were evaluated and a RAIR-DTC prediction model was established. RESULTS: RAIR-DTC showed unique clinicopathological features that differed from those of RAIA-DTC; these included age >55 years, a high-risk histological subtype, a large tumor size, a late TNM stage, calcification, distant metastasis, and more than six metastatic lymph nodes. Patients with RAIR-DTC also developed earlier tumor progression. Binary logistic regression analysis showed that distant metastasis, a high-risk histological subtype, and a maximum tumor diameter of ≥12.5 mm were independent risk factors for RAIR-DTC, and the specificity and sensitivity of a combination of these three parameters for the prediction of RAIR-DTC were 98.0 % and 56.8 %, respectively. Decision curve analysis and the calibration curve revealed that the combined prediction of these three parameters had good repeatability and accuracy. CONCLUSION: The clinicopathological features of DTC can effectively predict the effects of iodine therapy. A combination of distant metastasis, a high-risk histological subtype, and a maximum tumor diameter of ≥12.5 mm showed significantly higher prediction accuracy.

Motion artifact removal in coronary CT angiography based on generative adversarial networks.

OBJECTIVES: Coronary motion artifacts affect the diagnostic accuracy of coronary CT angiography (CCTA), especially in the mid right coronary artery (mRCA). The purpose is to correct CCTA motion artifacts of the mRCA using a GAN (generative adversarial network). METHODS: We included 313 patients with CCTA scans, who had paired motion-affected and motion-free reference images at different R-R interval phases in the same cardiac cycle and included another 53 CCTA cases with invasive coronary angiography (ICA) comparison. Pix2pix, an image-to-image conversion GAN, was trained by the motion-affected and motion-free reference pairs to generate motion-free images from the motion-affected images. Peak signal-to-noise ratio (PSNR), structural similarity (SSIM), Dice similarity coefficient (DSC), and Hausdorff distance (HD) were calculated to evaluate the image quality of GAN-generated images. RESULTS: At the image level, the median of PSNR, SSIM, DSC, and HD of GAN-generated images were 26.1 (interquartile: 24.4-27.5), 0.860 (0.830-0.882), 0.783 (0.714-0.825), and 4.47 (3.00-4.47), respectively, significantly better than the motion-affected images (p < 0.001). At the patient level, the image quality results were similar. GAN-generated images improved the motion artifact alleviation score (4 vs. 1, p < 0.001) and overall image quality score (4 vs. 1, p < 0.001) than those of the motion-affected images. In patients with ICA comparison, GAN-generated images achieved accuracy of 81%, 85%, and 70% in identifying no, < 50%, and ≥ 50% stenosis, respectively, higher than 66%, 72%, and 68% for the motion-affected images. CONCLUSION: Generative adversarial network-generated CCTA images greatly improved the image quality and diagnostic accuracy compared to motion-affected images. KEY POINTS: • A generative adversarial network greatly reduced motion artifacts in coronary CT angiography and improved image quality. • GAN-generated images improved diagnosis accuracy of identifying no, < 50%, and ≥ 50% stenosis.

Unveiling orientation dependence of anisotropic plasticity in polycrystalline copper by nanoindentation.

The mechanical properties of crystalline materials are influenced by their deformation behavior, which is associated with their microstructural characteristics. Specifically, crystallographic orientation greatly affects the microscale plastic deformation of individual grains. In this study, experiments and finite element simulations of Berkovich nanoindentations are conducted to investigate the impact of crystallographic orientation in polycrystalline copper. A crystal plasticity constitutive model is developed for copper materials, which accurately captures their indentation mechanical response. The results showed that the indentation behavior of polycrystalline copper exhibits a high degree of anisotropy due to significant variation in slip systems for different crystallographic orientations. This results in different mechanical responses of individual grains and distinct material pileup morphologies on the indented surface. Additionally, the study revealed that crystallographic orientation plays a critical role in determining the indentation size effect. These findings have important implications for the design of materials where plasticity is a crucial factor.

Effects of 24-Epibrassinolide, melatonin and their combined effect on cadmium tolerance in Primula forbesii Franch.

This study aimed to investigate the interaction between 24-Epibrassinolide (EBR) and melatonin (MT) and their effects on cadmium (Cd)-stressed Primula forbesii Franch. P. forbesii seedlings were hydroponically acclimatized at 6-7 weeks, then treated with Cd (200 µmol L-1), 24-EBR (0.1 µmol L-1), and MT (100 µmol L-1) after two weeks. Cd stress significantly reduced crown width, shoot, root length, shoot fresh weight, and fresh and dry root weights. Herein, 24-EBR, MT, and 24-EBR+MT treatments attenuated the growth inhibition caused by Cd stress and improved the morphology, growth indexes, and ornamental characteristics of P. forbesii under Cd stress. 24-EBR had the best effect by effectively alleviating Cd stress and promoting plant growth and development. 24-EBR significantly increased all growth parameters compared to Cd treatment. In addition, 24-EBR significantly improved the gas exchange parameters, activities of antioxidant enzymes, and the cycle efficiency of AsA-GSH. Furthermore, 24-EBR increased the activities of ascorbate peroxidase (APX), glutathione reductase (GR), dehydroascorbate reductase (DHAR), and monodehydroascorbate reductase (MDHAR) by 127.29%, 61.31%, 61.22%, and 51.04%, respectively, compared with the Cd treatment. Therefore, 24-EBR removed the reactive oxygen species produced by stress, thus protecting plants against stress damage. These results indicate that 24-EBR can effectively enhance the tolerance of P. forbesii to Cd stress.

Abscisic acid (ABA) alleviates cadmium toxicity by enhancing the adsorption of cadmium to root cell walls and inducing antioxidant defense system of Cosmos bipinnatus.

Cadmium (Cd) pollution is a global problem affecting soil ecology and plant growth. Abscisic acid (ABA) acts as a growth and stress hormone, regulates cell wall synthesis, and plays an important role in plant responses to stress. There are few studies on the mechanisms behind abscisic acid alleviation of cadmium stress in Cosmos bipinnatus, especially in regards to regulation of the root cell wall. This study examined the effects of different concentrations of abscisic acid at different concentrations of cadmium stress. Through adding 5 µmol/L and 30 µmol/L cadmium, followed by spraying 10 µmol/L and 40 µmol/L ABA in a hydroponic experiment, it was found that under two concentrations of cadmium stress, low concentration of ABA improved root cell wall polysaccharide, Cd, and uronic acid content. Especially in pectin, after the application of low concentration ABA, the cadmium concentration was significantly increased by 1.5 times and 1.2 times compared with the Cd concentration under Cd5 and Cd30 treatment alone, respectively. Fourier-Transform Infrared spectroscopy (FTIR) demonstrated that cell wall functional groups such as -OH and -COOH were increased with exposure to ABA. Additionally, the exogenous ABA also increased expression of three kinds of antioxidant enzymes and plant antioxidants. The results of this study suggest that ABA could reduce Cd stress by increasing Cd accumulation, promoting Cd adsorption on the root cell wall, and activating protective mechanisms. This result could help promote application of C. bipinnatus for phytostabilization of cadmium-contaminated soil.

Transcriptome Analyses Reveal the Aroma Terpeniods Biosynthesis Pathways of Primula forbesii Franch. and the Functional Characterization of the PfDXS2 Gene.

Primula forbesii Franch. is a unique biennial herb with a strong floral fragrance, making it an excellent material for studying the aroma characteristics of the genus Primula. The floral scent is an important ornamental trait that facilitates fertilization. However, the molecular mechanism regulating the floral scent in Primula is unknown. In order to better understand the biological mechanisms of floral scents in this species, this study used RNA sequencing analysis to discuss the first transcriptome sequence of four flowering stages of P. forbesii, which generated 12 P. forbesii cDNA libraries with 79.64 Gb of clean data that formed 51,849 unigenes. Moreover, 53.26% of the unigenes were annotated using public databases. P. forbesii contained 44 candidate genes covering all known enzymatic steps for the biosynthesis of volatile terpenes, the major contributor to the flower's scent. Finally, 1-deoxy-d-xylulose 5-phosphate synthase gene of P. forbesii (PfDXS2, MK370094), the first key enzyme gene in the 2-c-methyl-d-erythritol 4-phosphate (MEP) pathway of terpenoids, was cloned and functionally verified using virus-induced gene silencing (VIGs). The results showed that PfDXS2-silencing significantly reduced the relative concentrations of main volatile terpenes. This report is the first to present molecular data related to aroma metabolites biosynthesis pathways and the functional characterization of any P. forbesii gene. The data on RNA sequencing provide comprehensive information for further analysis of other plants of the genus Primula.

Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra-Low-Dose Chest CT.

Background Ultra-low-dose (ULD) CT could facilitate the clinical implementation of large-scale lung cancer screening while minimizing the radiation dose. However, traditional image reconstruction methods are associated with image noise in low-dose acquisitions. Purpose To compare the image quality and lung nodule detectability of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-V (ASIR-V) in ULD CT. Materials and Methods Patients who underwent noncontrast ULD CT (performed at 0.07 or 0.14 mSv, similar to a single chest radiograph) and contrast-enhanced chest CT (CECT) from April to June 2020 were included in this prospective study. ULD CT images were reconstructed with filtered back projection (FBP), ASIR-V, and DLIR. Three-dimensional segmentation of lung tissue was performed to evaluate image noise. Radiologists detected and measured nodules with use of a deep learning-based nodule assessment system and recognized malignancy-related imaging features. Bland-Altman analysis and repeated-measures analysis of variance were used to evaluate the differences between ULD CT images and CECT images. Results A total of 203 participants (mean age ± standard deviation, 61 years ± 12; 129 men) with 1066 nodules were included, with 100 scans at 0.07 mSv and 103 scans at 0.14 mSv. The mean lung tissue noise ± standard deviation was 46 HU ± 4 for CECT and 59 HU ± 4, 56 HU ± 4, 53 HU ± 4, 54 HU ± 4, and 51 HU ± 4 in FBP, ASIR-V level 40%, ASIR-V level 80% (ASIR-V-80%), medium-strength DLIR, and high-strength DLIR (DLIR-H), respectively, of ULD CT scans (P < .001). The nodule detection rates of FBP reconstruction, ASIR-V-80%, and DLIR-H were 62.5% (666 of 1066 nodules), 73.3% (781 of 1066 nodules), and 75.8% (808 of 1066 nodules), respectively (P < .001). Bland-Altman analysis showed the percentage difference in long diameter from that of CECT was 9.3% (95% CI of the mean: 8.0, 10.6), 9.2% (95% CI of the mean: 8.0, 10.4), and 6.2% (95% CI of the mean: 5.0, 7.4) in FBP reconstruction, ASIR-V-80%, and DLIR-H, respectively (P < .001). Conclusion Compared with adaptive statistical iterative reconstruction-V, deep learning image reconstruction reduced image noise, increased nodule detection rate, and improved measurement accuracy on ultra-low-dose chest CT images. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Lee in this issue.

A WRKY transcription factor, PyWRKY75, enhanced cadmium accumulation and tolerance in poplar.

Cadmium (Cd) pollution has detrimental effects on the ecological environment and human health. Currently, phytoremediation is considered an environmentally friendly way to remediate Cd pollution. The application of transgenic plants to remediate soil pollution is a new technology that has emerged in recent years. In this study, PyWRKY75 was isolated and cloned from Populus yunnanensis, and the functionality of PyWRKY75 in woody plants (poplar) under Cd stress was verified. The increase in plant height of the OE-41 line (overexpression poplar) was 33.2% higher than that of the wild type (WT). Moreover, PyWRKY75 significantly promoted the absorption and accumulation of Cd in poplar, which increased by 51.32% in the OE-41 line when compared with the WT. The chlorophyll content of transgenic poplar leaves was higher than that of the WT, which reflected a protective mechanism of PyWRKY75. Other antioxidants, such as POD, SOD, CAT, APX, AsA, GSH and PCs, also made the transgenic poplars more tolerant to Cd, and they behaved differently in roots, stems and leaves. In general, PyWRKY75 played a potential role in regulating plant tolerance to Cd stress. This study provides a scientific basis and a new type of modified poplar for Cd pollution remediation.

Lysine decrotonylation of glutathione peroxidase at lysine 220 site increases glutathione peroxidase activity to resist cold stress in chrysanthemum.

Lysine crotonylation is a protein post-translational modification that has been newly discovered in recent years. There are few studies on the lysine crotonylation of proteins in plants, and their functions in response to cold stress are still unclear. In this study, the chrysanthemum (Chrysanthemum morifolium Ramat.) glutathione peroxidase (GPX) gene was selected and named DgGPX1, and was found to be responsive to low temperature. Overexpression of DgGPX1 improved the cold resistance of transgenic chrysanthemum by increasing GPX activity to reduce the accumulation of reactive oxygen species (ROS) under low-temperature conditions. Furthermore, the level of DgGPX1 lysine crotonylation at lysine (K) 220 decreased under low temperature in chrysanthemum. Lysine decrotonylation of DgGPX1 at K220 further increased GPX activity to reduce ROS accumulation under cold stress, and thereby enhanced the cold resistance of chrysanthemum. The above results show that lysine decrotonylation of DgGPX1 at K220 increases GPX activity to resist cold stress in chrysanthemum.

Proteome-wide and lysine crotonylation profiling reveals the importance of crotonylation in chrysanthemum (Dendranthema grandiforum) under low-temperature.

BACKGROUND: Low-temperature severely affects the growth and development of chrysanthemum which is one kind of ornamental plant well-known and widely used in the world. Lysine crotonylation is a recently identified post-translational modification (PTM) with multiple cellular functions. However, lysine crotonylation under low-temperature stress has not been studied. RESULTS: Proteome-wide and lysine crotonylation of chrysanthemum at low-temperature was analyzed using TMT (Tandem Mass Tag) labeling, sensitive immuno-precipitation, and high-resolution LC-MS/MS. The results showed that 2017 crotonylation sites were identified in 1199 proteins. Treatment at 4 °C for 24 h and - 4 °C for 4 h resulted in 393 upregulated proteins and 500 downregulated proteins (1.2-fold threshold and P < 0.05). Analysis of biological information showed that lysine crotonylation was involved in photosynthesis, ribosomes, and antioxidant systems. The crotonylated proteins and motifs in chrysanthemum were compared with other plants to obtain orthologous proteins and conserved motifs. To further understand how lysine crotonylation at K136 affected APX (ascorbate peroxidase), we performed a site-directed mutation at K136 in APX. Site-directed crotonylation showed that lysine decrotonylation at K136 reduced APX activity, and lysine complete crotonylation at K136 increased APX activity. CONCLUSION: In summary, our study comparatively analyzed proteome-wide and crotonylation in chrysanthemum under low-temperature stress and provided insights into the mechanisms of crotonylation in positively regulated APX activity to reduce the oxidative damage caused by low-temperature stress. These data provided an important basis for studying crotonylation to regulate antioxidant enzyme activity in response to low-temperature stress and a new research ideas for chilling-tolerance and freezing-tolerance chrysanthemum molecular breeding.

Lysine crotonylation of DgTIL1 at K72 modulates cold tolerance by enhancing DgnsLTP stability in chrysanthemum.

Lysine crotonylation of proteins is a recently identified post-translational modification (PTM) in plants. However, the function of lysine-crotonylated proteins in response to abiotic stress in plants has not been reported. In this study, we identified a temperature-induced lipocalin-1-like gene (DgTIL1) from chrysanthemum and showed that it was notably induced in response to cold stress. Overexpression of DgTIL1 enhanced cold tolerance in transgenic chrysanthemum. Ubiquitin membrane yeast two-hybrid (MYTH) system and bimolecular fluorescence complementation (BIFC) assays showed that DgTIL1 interacts with a nonspecific lipid transfer protein (DgnsLTP), which can promote peroxidase (POD) gene expression and POD activity to reduce the accumulation of reactive oxygen species (ROS) and improve resistance to cold stress in DgnsLTP transgenic chrysanthemum. In addition, we found that DgTIL1 was lysine crotonylated at K72 in response to low temperature in chrysanthemum. Moreover, lysine crotonylation of DgTIL1 prevented DgnsLTP protein degradation in tobacco and chrysanthemum. Inhibition of DgnsLTP degradation by lysine crotonylation of DgTIL1 further enhanced POD expression and POD activity, reduced the accumulation of ROS under cold stress in DgTIL1 transgenic chrysanthemum, thus promoting the cold resistance of chrysanthemum.

Human-recognizable CT image features of subsolid lung nodules associated with diagnosis and classification by convolutional neural networks.

OBJECTIVES: The interpretability of convolutional neural networks (CNNs) for classifying subsolid nodules (SSNs) is insufficient for clinicians. Our purpose was to develop CNN models to classify SSNs on CT images and to investigate image features associated with the CNN classification. METHODS: CT images containing SSNs with a diameter of ≤ 3 cm were retrospectively collected. We trained and validated CNNs by a 5-fold cross-validation method for classifying SSNs into three categories (benign and preinvasive lesions [PL], minimally invasive adenocarcinoma [MIA], and invasive adenocarcinoma [IA]) that were histologically confirmed or followed up for 6.4 years. The mechanism of CNNs on human-recognizable CT image features was investigated and visualized by gradient-weighted class activation map (Grad-CAM), separated activation channels and areas, and DeepDream algorithm. RESULTS: The accuracy was 93% for classifying 586 SSNs from 569 patients into three categories (346 benign and PL, 144 MIA, and 96 IA in 5-fold cross-validation). The Grad-CAM successfully located the entire region of image features that determined the final classification. Activated areas in the benign and PL group were primarily smooth margins (p < 0.001) and ground-glass components (p = 0.033), whereas in the IA group, the activated areas were mainly part-solid (p < 0.001) and solid components (p < 0.001), lobulated shapes (p < 0.001), and air bronchograms (p < 0.001). However, the activated areas for MIA were variable. The DeepDream algorithm showed the image features in a human-recognizable pattern that the CNN learned from a training dataset. CONCLUSION: This study provides medical evidence to interpret the mechanism of CNNs that helps support the clinical application of artificial intelligence. KEY POINTS: • CNN achieved high accuracy (93%) in classifying subsolid nodules on CT images into three categories: benign and preinvasive lesions, MIA, and IA. • The gradient-weighted class activation map (Grad-CAM) located the entire region of image features that determined the final classification, and the visualization of the separated activated areas was consistent with radiologists' expertise for diagnosing subsolid nodules. • DeepDream showed the image features that CNN learned from a training dataset in a human-recognizable pattern.

Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors.

BACKGROUND: Motion artifacts affect the images of coronary calcified plaques. This study utilized convolutional neural networks (CNNs) to classify the motion-contaminated images of moving coronary calcified plaques and to determine the influential factors for the classification performance. METHODS: Two artificial coronary arteries containing four artificial plaques of different densities were placed on a robotic arm in an anthropomorphic thorax phantom. Each artery moved linearly at velocities ranging from 0 to 60 mm/s. CT examinations were performed with four state-of-the-art CT systems. All images were reconstructed with filtered back projection and at least three levels of iterative reconstruction. Each examination was performed at 100%, 80% and 40% radiation dose. Three deep CNN architectures were used for training the classification models. A five-fold cross-validation procedure was applied to validate the models. RESULTS: The accuracy of the CNN classification was 90.2 ± 3.1%, 90.6 ± 3.5%, and 90.1 ± 3.2% for the artificial plaques using Inception v3, ResNet101 and DenseNet201 CNN architectures, respectively. In the multivariate analysis, higher density and increasing velocity were significantly associated with higher classification accuracy (all P < 0.001). The classification accuracy in all three CNN architectures was not affected by CT system, radiation dose or image reconstruction method (all P > 0.05). CONCLUSIONS: The CNN achieved a high accuracy of 90% when classifying the motion-contaminated images into the actual category, regardless of different vendors, velocities, radiation doses, and reconstruction algorithms, which indicates the potential value of using a CNN to correct calcium scores.

Motion-corrected coronary calcium scores by a convolutional neural network: a robotic simulating study.

OBJECTIVE: To classify motion-induced blurred images of calcified coronary plaques so as to correct coronary calcium scores on nontriggered chest CT, using a deep convolutional neural network (CNN) trained by images of motion artifacts. METHODS: Three artificial coronary arteries containing nine calcified plaques of different densities (high, medium, and low) and sizes (large, medium, and small) were attached to a moving robotic arm. The artificial arteries moving at 0-90 mm/s were scanned to generate nine categories (each from one calcified plaque) of images with motion artifacts. An inception v3 CNN was fine-tuned and validated. Agatston scores of the predicted classification by CNN were considered as corrected scores. Variation of Agatston scores on moving plaque and by CNN correction was calculated using the scores at rest as reference. RESULTS: The overall accuracy of CNN classification was 79.2 ± 6.1% for nine categories. The accuracy was 88.3 ± 4.9%, 75.9 ± 6.4%, and 73.5 ± 5.0% for the high-, medium-, and low-density plaques, respectively. Compared with the Agatston score at rest, the overall median score variation was 37.8% (1st and 3rd quartile, 10.5% and 68.8%) in moving plaques. CNN correction largely decreased the variation to 3.7% (1.9%, 9.1%) (p < 0.001, Mann-Whitney U test) and improved the sensitivity (percentage of non-zero scores among all the scores) from 65 to 85% for detection of coronary calcifications. CONCLUSIONS: In this experimental study, CNN showed the ability to classify motion-induced blurred images and correct calcium scores derived from nontriggered chest CT. CNN correction largely reduces the overall Agatston score variation and increases the sensitivity to detect calcifications. KEY POINTS: • A deep CNN architecture trained by CT images of motion artifacts showed the ability to correct coronary calcium scores from blurred images. • A correction algorithm based on deep CNN can be used for a tenfold reduction in Agatston score variations from 38 to 3.7% of moving coronary calcified plaques and to improve the sensitivity from 65 to 85% for the detection of calcifications. • This experimental study provides a method to improve its accuracy for coronary calcium scores that is a fundamental step towards a real clinical scenario.

Ruminal epithelial cell proliferation and short-chain fatty acid transporters in vitro are associated with abundance of period circadian regulator 2 (PER2).

The major circadian clock gene PER2 is closely related to cell proliferation and lipid metabolism in various nonruminant cell types. Objectives of the study were to evaluate circadian clock-related mRNA abundance in cultured goat ruminal epithelial cells (REC), and to determine effects of PER2 on cell proliferation and mRNA abundance of short-chain fatty acid (SCFA) transporters, genes associated with lipid metabolism, cell proliferation, and apoptosis. Ruminal epithelial cells were isolated from weaned Boer goats (n = 3; 2 mo old; ∼10 kg of body weight) by serial trypsin digestion and cultured at 37°C for 24 h. Abundance of CLOCK and PER2 proteins in cells was determined by immunofluorescence. The role of PER2 was assessed through the use of a knockout model with short interfering RNA, and sodium butyrate (15 mM) was used to assess the effect of upregulating PER2. Both CLOCK and PER2 were expressed in REC in vitro. Sodium butyrate stimulation increased mRNA and protein abundance of PER2 and PER3. Furthermore, PER2 gene silencing enhanced cell proliferation and reduced cellular apoptosis in isolated REC. In contrast, PER2 overexpression in response to sodium butyrate led to lower cellular proliferation and ratio of cells in the S phase along with greater ratio of cells in the G2/M phase. Those responses were accompanied by downregulated mRNA abundance of CCND1, CCNB1, CDK1, and CDK2. Among the SCFA transporters, PER2 silencing upregulated mRNA abundance of MCT1 and MCT4. However, it downregulated mRNA abundance of PPARA and PPARG. Overexpression of PER2 resulted in lower mRNA abundance of MCT1 and MCT4, and greater PPARA abundance. Overall, data suggest that CLOCK and PER2 might play a role in the control of cell proliferation, SCFA, and lipid metabolism. Further studies should be conducted to evaluate potential mechanistic relationships between circadian clock and SCFA absorption in vivo.