Identification of Topping Responsive Proteins in Tobacco Roots

Tobacco plant has many responses to topping, such as the increase in ability of nicotine synthesis and secondary growth of roots. Some topping responsive miRNAs and genes had been identified in our previous work, but it is not enough to elaborate mechanism of tobacco response to topping. Here, topping responsive proteins were screened from tobacco roots with two-dimensional electrophoresis. Of these proteins, calretulin (CRT) and Auxin-responsive protein IAA9 were related to the secondary growth of roots, LRR disease resistance, heat shock protein 70 and farnesyl pyrophosphate synthase 1（FPPS）were involved in wounding stress response, and F-box protein played an important role in promoting the ability of nicotine synthesis after topping. In addition, there were five tobacco bHLH proteins (NtbHLH, NtMYC1a, NtMYC1b, NtMYC2a and NtMYC2b) related to nicotine synthesis. It was suggested that NtMYC2 might be the main positive transcription factor and NtbHLH protein is a negative regulator in the JA-mediating activation of nicotine synthesis after topping. Tobacco topping activates some comprehensive biology processes involving IAA and JA signaling pathway, and the identification of these proteins will be helpful to understand the process of topping response

The Lyman-α\alpha Emission in a C1.4 Solar Flare Observed by the Extreme Ultraviolet Imager aboard Solar Orbiter

The hydrogen Lyman-$\alpha$ (H {\sc i} Ly$\alpha$) emission during solar flares has rarely been studied in spatially resolved images and its physical origin has not been fully understood. In this paper, we present novel Ly$\alpha$ images for a C1.4 solar flare (SOL2021-08-20T22:00) from the Extreme Ultraviolet Imager aboard Solar Orbiter, together with multi-waveband and multi-perspective observations from the Solar Terrestrial Relations Observatory Ahead and the Solar Dynamics Observatory spacecraft. It is found that the Ly$\alpha$ emission has a good temporal correlation with the thermal emissions at 1--8 \AA\ and 5--7 keV, indicating that the flaring Ly$\alpha$ is mainly produced by a thermal process in this small event. However, nonthermal electrons play a minor role in generating Ly$\alpha$ at flare ribbons during the rise phase of the flare, as revealed by the hard X-ray imaging and spectral fitting. Besides originating from flare ribbons, the Ly$\alpha$ emission can come from flare loops, likely caused by plasma heating and also cooling that happen in different flare phases. It is also found that the Ly$\alpha$ emission shows fairly similar features with the He {\sc ii} 304 \AA\ emission in light curve and spatio-temporal variation along with small differences. These observational results improve our understanding of the Ly$\alpha$ emission in solar flares and also provide some insights for investigating the Ly$\alpha$ emission in stellar flares.Comment: 19 pages, 7 figures, and 2 tables. ApJ accepted. Comments are welcom

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Deep learning–based radiomic nomograms for predicting Ki67 expression in prostate cancer

Abstract Background To explore the value of a multiparametric magnetic resonance imaging (MRI)-based deep learning model for the preoperative prediction of Ki67 expression in prostate cancer (PCa). Materials The data of 229 patients with PCa from two centers were retrospectively analyzed and divided into training, internal validation, and external validation sets. Deep learning features were extracted and selected from each patient’s prostate multiparametric MRI (diffusion-weighted imaging, T2-weighted imaging, and contrast-enhanced T1-weighted imaging sequences) data to establish a deep radiomic signature and construct models for the preoperative prediction of Ki67 expression. Independent predictive risk factors were identified and incorporated into a clinical model, and the clinical and deep learning models were combined to obtain a joint model. The predictive performance of multiple deep-learning models was then evaluated. Results Seven prediction models were constructed: one clinical model, three deep learning models (the DLRS-Resnet, DLRS-Inception, and DLRS-Densenet models), and three joint models (the Nomogram-Resnet, Nomogram-Inception, and Nomogram-Densenet models). The areas under the curve (AUCs) of the clinical model in the testing, internal validation, and external validation sets were 0.794, 0.711, and 0.75, respectively. The AUCs of the deep models and joint models ranged from 0.939 to 0.993. The DeLong test revealed that the predictive performance of the deep learning models and the joint models was superior to that of the clinical model (p < 0.01). The predictive performance of the DLRS-Resnet model was inferior to that of the Nomogram-Resnet model (p < 0.01), whereas the predictive performance of the remaining deep learning models and joint models did not differ significantly. Conclusion The multiple easy-to-use deep learning–based models for predicting Ki67 expression in PCa developed in this study can help physicians obtain more detailed prognostic data before a patient undergoes surgery

The White-light Emissions in Two X-class Flares Observed by ASO-S and CHASE

The white-light continuum emissions in solar flares (i.e., white-light flares) are usually observed on the solar disk but, in a few cases, off the limb. Here we present on-disk as well as off-limb continuum emissions at 3600 A (in the Balmer continuum) in an X2.1 flare (SOL2023-03-03T17:52) and an X1.5 flare (SOL2023-08-07T20:46), respectively, observed by the White-light Solar Telescope on the Advanced Space-based Solar Observatory. These continuum emissions are seen at the ribbons for the X2.1 flare and on loops during the X1.5 event, in which the latter also appears in the decay phase. These emissions also show up in the pseudocontinuum images at Fe I λ6173 from the Helioseismic and Magnetic Imager on the Solar Dynamics Observatory. In addition, the ribbon sources in the X2.1 flare exhibit significant enhancements in the Fe I line at 6569.2 A and the nearby continuum observed by the Chinese Hα Solar Explorer. It is found that the on-disk continuum emissions in the X2.1 flare are related to a nonthermal electron-beam heating either directly or indirectly, while the off-limb emissions in the X1.5 flare are associated with thermal plasma cooling or due to Thomson scattering. These comprehensive continuum observations provide good constraints on flare energy deposition models, which helps us to better understand the physical mechanism of white-light flares.ISSN:1967-2014ISSN:2041-821

DNA polymerase iota promotes EMT and metastasis of esophageal squamous cell carcinoma by interacting with USP7 to stabilize HIF-1α

Abstract Esophageal squamous cell carcinoma (ESCC) is one of the most lethal cancer types, with a low 5-year survival rate of ~20%. Our prior research has suggested that DNA Polymerase iota (Pol ι), a member of Y-family DNA polymerase, plays a crucial role in the invasion and metastasis of ESCC. However, the underlying mechanism is not well understood. In this study, we utilized ChIP-PCR and luciferase reporter assays to investigate the binding of HIF-1α to the promoter of the Pol ι gene. Transwell, wound healing, and mouse models were employed to assess the impact of Pol ι and HIF-1α on the motility of ESCC cells. Co-immunoprecipitation and Western blot were carried out to explore the interaction between Pol ι and HIF-1α, while qRT-PCR and Western blot were conducted to confirm the regulation of Pol ι and HIF-1α on their downstream targets. Our results demonstrate that HIF-1α activates the transcription of the Pol ι gene in ESCC cells under hypoxic conditions. Furthermore, the knockdown of Pol ι impeded HIF-1α-induced invasion and metastasis. Additionally, we found that Pol ι regulates the expression of genes involved in epithelial-mesenchymal transition (EMT) and initiates EMT through the stabilization of HIF-1α. Mechanistically, Pol ι maintains the protein stability of HIF-1α by recruiting USP7 to mediate the deubiquitination of HIF-1α, with the residues 446–578 of Pol being crucial for the interaction between Pol ι and USP7. Collectively, our findings unveil a novel feedforward molecular axis of HIF-1α- Pol ι -USP7 in ESCC that contributes to ESCC metastasis. Hence, our results present an attractive target for intervention in ESCC