Identification of differentially expressed sequences in bud differentiation of oriental hybrid lily cultivar ‘Sorbonne’ via suppression subtractive hybridization

The developmental process of lily flower bud differentiation has been studied in morphology thoroughly, but the mechanism in molecular biology is still ambiguous and few studies on genetic expression have been carried out. Little is known about the physiological responses of flower bud differentiation in Oriental hybrid lily ‘Sorbonne’ (Lilium spp.) during the stages of flower bud differentiation and the genes involved in these responses. In this study, the differences in gene expression between two stages of lily bud differentiation: the stage before bud differentiation (SB) and the stage of bud differentiation (SD) were studied. The suppression subtractive hybridization (SSH) method conducted to generate large-scale expressed sequence tags (EST) was designed to identify gene candidates related to the morphological and physiological differences between the stage before bud differentiation and the stage of bud differentiation of lily. The results showed that the SD could induce differential expression of the genes related to lily flower bud differentiation. EST were isolated, cloned, sequenced and identified using BlastN and BlastX, and indicated that at the stage of the flower bud differentiation, there is an activation of a floral development response at a molecular level, mainly related to low temperature and post-transcriptional regulation of nucleic acids. 24.1% of the isolated sequences are not yet described which showed the lack of genomic information currently available for lily. Sequence analysis revealed that most of the differentially expressed genes are related to metabolism and regulation such as protein synthesis and catabolism of carbohydrate related to flower formation. Some genes also encoded transcription factors. These genes showed high mRNA transcript levels in the stage of flower bud differentiation. This study revealed that unknown genes are putatively involved in the stage of lily flower bud differentiation, which serve as a starting point for understanding the differentiation of lily flower bud.Keywords: Lily flower bud differentiation, gene expression, suppression subtractive hybridization (SSH

Automatic Extraction and Sign Determination of Respiratory Signal in Real-time Cardiac Magnetic Resonance imaging

In real-time (RT) cardiac cine imaging, a stack of 2D slices is collected sequentially under free-breathing conditions. A complete heartbeat from each slice is then used for cardiac function quantification. The inter-slice respiratory mismatch can compromise accurate quantification of cardiac function. Methods based on principal components analysis (PCA) have been proposed to extract the respiratory signal from RT cardiac cine, but these methods cannot resolve the inter-slice sign ambiguity of the respiratory signal. In this work, we propose a fully automatic sign correction procedure based on the similarity of neighboring slices and correlation to the center-of-mass curve. The proposed method is evaluated in eleven volunteers, with ten slices per volunteer. The motion in a manually selected region-of-interest (ROI) is used as a reference. The results show that the extracted respiratory signal has a high, positive correlation with the reference in all cases. The qualitative assessment of images also shows that the proposed approach can accurately identify heartbeats, one from each slice, belonging to the same respiratory phase. This approach can improve cardiac function quantification for RT cine without manual intervention.Comment: IEEE ISBI 2020, International Symposium on Biomedical Imagin

FAN: Fatigue-Aware Network for Click-Through Rate Prediction in E-commerce Recommendation

Since clicks usually contain heavy noise, increasing research efforts have been devoted to modeling implicit negative user behaviors (i.e., non-clicks). However, they either rely on explicit negative user behaviors (e.g., dislikes) or simply treat non-clicks as negative feedback, failing to learn negative user interests comprehensively. In such situations, users may experience fatigue because of seeing too many similar recommendations. In this paper, we propose Fatigue-Aware Network (FAN), a novel CTR model that directly perceives user fatigue from non-clicks. Specifically, we first apply Fourier Transformation to the time series generated from non-clicks, obtaining its frequency spectrum which contains comprehensive information about user fatigue. Then the frequency spectrum is modulated by category information of the target item to model the bias that both the upper bound of fatigue and users' patience is different for different categories. Moreover, a gating network is adopted to model the confidence of user fatigue and an auxiliary task is designed to guide the learning of user fatigue, so we can obtain a well-learned fatigue representation and combine it with user interests for the final CTR prediction. Experimental results on real-world datasets validate the superiority of FAN and online A/B tests also show FAN outperforms representative CTR models significantly

Online identification of lithium-ion battery model parameters with initial value uncertainty and measurement noise

Online parameter identification is essential for the accuracy of the battery equivalent circuit model (ECM). The traditional recursive least squares (RLS) method is easily biased with the noise disturbances from sensors, which degrades the modeling accuracy in practice. Meanwhile, the recursive total least squares (RTLS) method can deal with the noise interferences, but the parameter slowly converges to the reference with initial value uncertainty. To alleviate the above issues, this paper proposes a co-estimation framework utilizing the advantages of RLS and RTLS for a higher parameter identification performance of the battery ECM. RLS converges quickly by updating the parameters along the gradient of the cost function. RTLS is applied to attenuate the noise effect once the parameters have converged. Both simulation and experimental results prove that the proposed method has good accuracy, a fast convergence rate, and also robustness against noise corruption

Antimicrobial Mechanism of Antimicrobial Peptide from Paenibacillus ehimensis against Penicillium expansum Spores

Penicillium expansum, a common spoilage organism in postharvest fruits, can cause fruit decay and deterioration and endanger human health. It is of great significance to investigate the antimicrobial mechanism of the antimicrobial peptide from Paenibacillus ehimensis on P. expansum spores. The antimicrobial activity of the antimicrobial peptide against P. expansum spores was determined by using the two-fold dilution method as well as measuring the time-killing curve. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to evaluate the effect of the antimicrobial peptide on the ultrastructure of P. expansum spores. The effects of the antimicrobial peptide on the cell membrane and reactive oxygen species (ROS) accumulation of P. expansum were analyzed by fluorescence probes. The results showed that the minimum inhibitory concentration (MIC) of the antimicrobial peptide against P. expansum spores was 3.5 AU/mL. The spore germination rate was significantly decreased by 28.30%, 84.57% and 100% by the antimicrobial peptide at concentrations of 0.5 MIC, 1 MIC and 2 MIC compared with the blank control (P < 0.05). After treatment with the antimicrobial peptide, the spores appeared seriously sunken, the intracellular contents were leaked out, and the morphology and structure were changed. The antimicrobial peptide damaged the cell wall of P. expansum, resulting in the leakage of alkaline phosphatase. The antimicrobial peptide depolarized the cell membrane potential in a dose-dependent manner, and increased the cell membrane permeability, leading to K+ leakage. The fluidity of the cell membrane was increased, which in turn resulted in a significant decrease in DPH fluorescence intensity (P < 0.05). The integrity of the cell membrane was damaged by the antimicrobial peptide, so the fluorescence intensity of SYTOX-Green and the contamination rate of PI were increased. Moreover, the antimicrobial peptide at 1 MIC and 2 MIC increased the fluorescence intensity of DCFH-DA significantly (P < 0.05) and resulted in ROS accumulation, which affected the physiology and metabolism of P. expansum spores. This study indicated that the target sites of the antimicrobial peptide against P. expansum spores were mainly the cell membrane and ROS metabolism

Increased KIF15 Expression Predicts a Poor Prognosis in Patients with Lung Adenocarcinoma

Background/Aims: Lung cancer is the leading cause of cancer-related deaths worldwide. The outcome of patients with non-small cell lung cancer remains poor; the 5-year survival rate for stage IV non-small cell lung cancer is only 1.0%. KIF15 is a tetrameric kinesin spindle motor that has been investigated for its regulation of mitosis. While the roles of kinesin motor proteins in the regulation of mitosis and their potentials as therapeutic targets in pancreatic cancer have been described previously, the role of KIF15 in lung cancer development remains unknown. Methods: Paired lung carcinoma specimens and matched adjacent normal tissues were used for protein analysis. Clinical data were obtained from medical records. We first examined KIF15 messenger RNA expression in The Cancer Genome Atlas database, and then determined KIF15 protein levels using immunohistochemistry and western blotting. Differences between the groups were analyzed using repeated measures analysis of variance. Overall survival was analyzed using the Kaplan–Meier method. Cell-cycle and proliferation assays were conducted using A549, NCI-H1299, and NCI-H226 cells. Results: KIF15 was significantly upregulated at both the messenger RNA and protein levels in human lung tumor tissues. In patients with lung adenocarcinoma, KIF15 expression was positively associated with disease stages; high KIF15 expression predicted a poor prognosis. KIF15 knockdown using short hairpin RNA in two human lung adenocarcinoma cell lines induced G1/S phase cell cycle arrest and inhibited cell growth, but there was no effect in human lung squamous cell carcinoma. Conclusion: Our findings show that KIF15 is involved in lung cancer carcinogenesis. KIF15 could therefore serve as a specific prognostic marker for patients with lung adenocarcinoma