Function and clinical application of exosome—how to improve tumor immunotherapy?

In recent years, immunotherapy has been increasingly used in clinical practice to treat tumors. However, immunotherapy’s efficacy varies between tumor types and patient populations, and long-term drug resistance often occurs during treatment. Therefore, it is essential to explore the molecular mechanisms of immunotherapy to improve its efficacy. In this review, we focus on the significance of tumor-derived exosomes in the clinical treatment of tumors and how modifying these exosomes may enhance immune effectiveness. Specifically, we discuss exosome components, such as RNA, lipids, and proteins, and the role of membrane molecules on exosome surfaces. Additionally, we highlight the importance of engineered exosomes for tumor immunotherapy. Our goal is to propose new strategies to improve the efficacy of tumor immunotherapy

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

Data from a flexible framework to assess patterns and drivers of beta diversity across spatial scales

&lt;p&gt;&lt;span&gt;The patterns and underlying ecological (e.g., environmental filtering) and &lt;/span&gt;&lt;span&gt;historical&lt;/span&gt;&lt;span&gt; (e.g., priority effects) drivers of beta diversity are scale-dependent but generally difficult to distinguish&lt;/span&gt; &lt;span&gt;and rarely explored with a sufficiently broad range of spatial scales. We propose a general scale-explicit framework to assess and contrast the patterns and drivers of beta diversity across hierarchical spatial scales ranging from within fine-scale ecoregion-scale to among broad-scale ecoregion-scale. By applying this framework to aquatic macroinvertebrate datasets, we show that beta diversity generally increases with spatial extent.&lt;/span&gt; &lt;span&gt;With an increasing spatial extent, beta diversity shifts from being more influenced by environmental filtering to being more influenced by recent historical factors (i.e., past beta diversity). Such recent historical effects may result from past environmental variation rather than priority effects.&lt;/span&gt;&lt;span&gt; We also found that the small-scale and large-scale environmental drivers act differently on beta diversity across spatial extents. Our research reveals a complex spatial-scale dependence in beta diversity patterns and their drivers and provides a more holistic understanding of beta diversity dynamics. Our framework represents a flexible way to unravel the internal structure of beta diversity across scales by partitioning of entire beta diversity variation into scale-specific differences and may have broad application in community ecology, landscape planning and biodiversity conservation.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;Data are compiled in different files containing the following information: 1) Presence-absence macroinvertebrate taxon dataset in the previous survey, 2) Presence-absence macroinvertebrate taxon dataset in the following survey, 3) dataset of explanatory variables.&lt;/p&gt;&lt;p&gt;Funding provided by: National Natural Science Foundation of China&lt;br&gt;Crossref Funder Registry ID: https://ror.org/01h0zpd94&lt;br&gt;Award Number: 32101270&lt;/p&gt

A flexible framework to assess patterns and drivers of beta diversity across spatial scales

Peer reviewe

Experimental study on the imaging of the squeezed state light with-4. 93dB quantum-noise reduction at 1064 nm

A stable amplitude squeezed state light was generated by utilizing the optical parametric down-conversion (OPDC) technique based on periodically poled KTiOPO4(PPKTP) in an optical parametric oscillator (OPO) resonator. We observed a-4. 93dB of squeezing in homodyne measurement. The imaging experiments of resolution target were conducted. It shown that the imaging resolution with squeezed state light as light source was 1. 26 times that of the resolution with coherent light as light source. The squeezed state light was applied for imaging of real objects and we found that the imaging with squeezed light as light source is more distinct and has less distortion

Regional Short-term Micro-climate Air Temperature Prediction with CBPNN

This paper proposes a novel short-term air temperature prediction with three-layer Back Propagation Neural Network (BPNN) for the regional application of next 1-12 hours. With the continuous collection of eight real-time micro-climate parameters in the experimentation and demonstration stations in our university, the Multiple Stepwise Regression (MSR) is employed to screen the original historical data to find the parameter factors with greater contribution rate. On the basis of the Root Mean Square Error (RMSE) value evaluating the optimal fitting degree of the stepwise regression, the Levenberg-Marquardt (LM) and the Resilient Propagation (R-Prop) training algorithm are employed to construct a Combined BPNN (CBPNN) with two MSR inputs. Compared with the known micro-climate data sets, the Mean Absolute Error (MAE) is to evaluate the applicability of CBPNN prediction model. The experimentation shows that the MAE is within 4°C in the next 12 hours. This proposal will be deployed in stations in our university for extreme weather warnings, and could be applied to some regional short-term parameter prediction for the future agricultural production service

Regional Short-term Micro-climate Air Temperature Prediction with CBPNN

This paper proposes a novel short-term air temperature prediction with three-layer Back Propagation Neural Network (BPNN) for the regional application of next 1-12 hours. With the continuous collection of eight real-time micro-climate parameters in the experimentation and demonstration stations in our university, the Multiple Stepwise Regression (MSR) is employed to screen the original historical data to find the parameter factors with greater contribution rate. On the basis of the Root Mean Square Error (RMSE) value evaluating the optimal fitting degree of the stepwise regression, the Levenberg-Marquardt (LM) and the Resilient Propagation (R-Prop) training algorithm are employed to construct a Combined BPNN (CBPNN) with two MSR inputs. Compared with the known micro-climate data sets, the Mean Absolute Error (MAE) is to evaluate the applicability of CBPNN prediction model. The experimentation shows that the MAE is within 4°C in the next 12 hours. This proposal will be deployed in stations in our university for extreme weather warnings, and could be applied to some regional short-term parameter prediction for the future agricultural production service

Synergistic effect of PB2 283M and 526R contributes to enhanced virulence of H5N8 influenza viruses in mice

International audienceAbstractHighly pathogenic avian influenza (HPAI) H5N8 virus has caused considerable economic losses to poultry industry and poses a great threat to public health. Our previous study revealed two genetically similar HPAI H5N8 viruses displaying completely different virulence in mice. However, the molecular basis for viral pathogenicity to mammals remains unknown. Herein, we generated a series of reassortants between the two viruses and evaluated their virulence in mice. We demonstrated that 283M in PB2 is a new mammalian virulence marker for H5 viruses and that synergistic effect of amino acid residues 283M and 526R in PB2 is responsible for high virulence of the HPAI H5N8 virus. Analysis of available PB2 sequences showed that PB2 283M is highly conserved among influenza A viruses, while PB2 526R presents in most of human H3N2 and H5N1 isolates. Further study confirmed that the residues 283M and 526R had similar impacts on an HPAI H5N1 virus, suggesting that influenza viruses with both residues may replicate well in mammalian hosts. Together, these results present new insights for synergistic effect of 283M and 526R in PB2 of H5 HPAI virus on virulence to mammalian host, furthering our understanding of the pathogenesis of influenza A virus

Ultrasound-guided intraoperative inferior vena cava stent implantation for treatment of acute hypotension during orthotopic liver transplantation

Severe obstruction of inferior vena cava (IVC) outflow after orthotopic liver transplantation can result in persistent hypotension, leading to transplantation failure and intraoperative circulatory instability and can even threaten the patient's life. IVC stent implantation is a therapeutic approach to relieve the obstruction of IVC outflow. In the present report, we describe two cases of IVC stent implantation assisted by color Doppler ultrasound during orthotopic liver transplantation to manage the persistent hypotension caused by acute obstruction of IVC outflow. At 1 and 3 months of follow-up, the stent position was optimal, and the stent and IVC patency were satisfactory without thrombosis