Quantity and clinical relevance of circulating endothelial progenitor cells in human ovarian cancer

<p>Abstract</p> <p>Background</p> <p>Circulating bone marrow-derived endothelial progenitor cells (EPCs) have been reported to participate in tumor angiogenesis and growth; however, the role of circulating EPCs in tumor progression is controversial. The role of circulating EPCs in ovarian cancer progression and angiogenesis has not yet been investigated.</p> <p>Methods</p> <p>The number of circulating EPCs in the peripheral blood in 25 healthy volunteers and 42 patients with ovarian cancer was determined by flow cytometry. EPCs were defined by co-expression of CD34 and vascular endothelial growth factor receptor 2 (VEGFR2). In addition, we determined CD34 and VEGFR2 mRNA levels by real-time reverse transcription-polymerase chain reaction. Plasma levels of vascular endothelial growth factor (VEGF) and matrix metalloproteinase-9 (MMP-9) were determined by enzyme-linked immunosorbent assay.</p> <p>Results</p> <p>Circulating levels of EPCs were significantly increased in ovarian cancer patients, correlating with tumor stage and residual tumor size. Higher levels of EPCs were detected in patients with stage III and IV ovarian cancer than in patients with stage I and II disease. After excision of the tumor, EPCs levels rapidly declined. Residual tumor size greater than 2 cm was associated with significantly higher levels of EPCs. In addition, high circulating EPCs correlated with poor overall survival. Pretreatment CD34 mRNA levels were not significantly increased in ovarian cancer patients compared with healthy controls; however, VEGFR2 expression was increased, and plasma levels of VEGF and MMP-9 were also elevated.</p> <p>Conclusions</p> <p>Our results demonstrate the clinical relevance of circulating EPCs in ovarian cancer. EPCs may be a potential biomarker to monitor ovarian cancer progression and angiogenesis and treatment response.</p

Recovery and treatment of fracturing flowback fluids in the Sulige Gasfield, Ordos Basin

AbstractCentralized and group well deployment and factory-like fracturing techniques are adopted for low-permeability tight sandstone reservoirs in the Sulige Gasfield, Ordos Basin, so as to realize its efficient and economic development. However, environmental protection is faced with grim situations because fluid delivery rises abruptly on site in a short time due to centralized fracturing of the well group. Based on the characteristics of gas testing after fracturing in this gas field, a fracturing flowback fluid recovery and treatment method suitable for the Sulige Gasfield has been developed with the landform features of this area taken into account. Firstly, a high-efficiency well-to-well fracturing flowback fluid recovery and reutilization technique was developed with multi-effect surfactant polymer recoverable fracturing fluid system as the core, and in virtue of this technique, the treatment efficiency of conventional guar gum fracturing fluid system is increased. Secondly, for recovering and treating the end fluids on the well sites, a fine fracturing flowback fluid recovery and treatment technique has been worked out with “coagulation and precipitation, filtration and disinfection, and sludge dewatering” as the main part. Owing to the application of this method, the on-site water resource utilization ratio has been increased and environmental protection pressure concerned with fracturing operation has been relieved. In 2014, field tests were performed in 62 wells of 10 well groups, with 32980 m3 cumulative treated flowback fluid, 17160 m3 reutilization volume and reutilization ratio over 70%. Obviously, remarkable social and economical benefits are thus realized

The emission positions of kHz QPOs and Kerr spacetime influence

Based the Alfven wave oscillation model (AWOM) and relativistic precession model (RPM) for twin kHz QPOs, we estimate the emission positions of most detected kHz QPOs to be at r=18+-3 km (R/15km) except Cir X-1 at r = 30\+-5 km (R/15km). For the proposed Keplerian frequency as an upper limit to kHz QPO, the spin effects in Kerr Spacetime are discussed, which have about a 5% (2%) modification for that of the Schwarzchild case for the spin frequency of 1000 (400) Hz.The application to the four typical QPO sources, Cir X-1, Sco X-1, SAX J1808.4-3658 and XTE 1807-294, is mentioned.Comment: Science China, Physics, Mechanics & Astronomy, 2010, 53, NO.

A novel mRNA vaccine, SYS6006, against SARS-CoV-2

The development of vaccines that can efficiently prevent the infection of SARS-CoV-2 is necessary to fight the COVID-19 epidemic. mRNA vaccine has been proven to induce strong humoral and cellular immunity against SARS-CoV-2. Here, we studied the immunogenicity and protection efficacy of a novel mRNA vaccine SYS6006. High expression of mRNA molecules in 293T cells was detected. The initial and boost immunization with a 21-day interval was determined as an optimal strategy for SYS6006. Two rounds of immunization with SYS6006 were able to induce the neutralizing antibodies against the SARS-CoV-2 wild-type (WT) strain, and Delta and Omicron BA.2 variants in mice or non-human primates (NHPs). A3rd round of vaccination could further enhance the titers of neutralization against Delta and Omicron variants. In vitro ELISpot assay showed that SYS6006 could induce memory B cell and T cell immunities specifically against SARS-CoV-2 in mice. FACS analysis indicated that SYS6006 successfully induced SARS-CoV-2-specific activation of T follicular helper cell (Tfh) and Th1 cell, and did not induce CD4+Th2 response in NHPs. SYS6006 vaccine could significantly reduce the viral RNA loads and prevent lung lesions in Delta variant infected hACE2 transgenic mice. Therefore, SYS6006 could provide significant immune protection against SARS-CoV-2

The PI3K/Akt pathway upregulates Id1 and integrin α4 to enhance recruitment of human ovarian cancer endothelial progenitor cells

<p>Abstract</p> <p>Background</p> <p>Endothelial progenitor cells (EPCs) contribute to tumor angiogenesis and growth. We aimed to determine whether inhibitors of differentiation 1 (Id1) were expressed in circulating EPCs of patients with ovarian cancer, whether Id1 could mediate EPCs mobilization and recruitment, and, if so, what underlying signaling pathway it used.</p> <p>Methods</p> <p>Circulating EPCs cultures were from 25 patients with ovarian cancer and 20 healthy control subjects. Id1 and integrin α4 expression were analyzed by real-time reverse transcription-polymerase chain reaction and western blot. EPCs proliferation, migration, and adhesion were detected by MTT, transwell chamber, and EPCs-matrigel adhesion assays. Double-stranded DNA containing the interference sequences were synthesized according to the structure of a pGCSIL-GFP viral vector and then inserted into a linearized vector. Positive clones were identified as lentiviral vectors that expressed human Id1 short hairpin RNA (shRNA).</p> <p>Results</p> <p>Id1 and integrin α4 expression were increased in EPCs freshly isolated from ovarian cancer patients compared to those obtained from healthy subjects. siRNA-mediated Id1 downregulation substantially reduced EPCs function and integrin α4 expression. Importantly, Inhibition of PI3K/Akt inhibited Id1 and integrin α4 expression, resulting in the decreasing biological function of EPCs.</p> <p>Conclusions</p> <p>Id1 induced EPCs mobilization and recruitment is mediated chiefly by the PI3K/Akt signaling pathway and is associated with activation of integrin α4.</p

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90ĝ€¯d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and "hotspots"of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question

Prediction Model of Vibration Feature for Equipment Maintenance Based on Full Vector Spectrum

Establishing a prediction model is a key step for the implementation of prognostic and health management. The prediction model can be used to forecast the change trend of the characteristics of the vibration signal and analyze the potential failure in the future. Taking the vibration of power plant steam turbine as an example, the full vector fusion and fault prediction were studied. Due to the fact that the evaluation of the machine fault with only one transducer may result in a fault judgement with partiality, an information fusion method based on the theory of full vector spectrum was adopted to extract the vibration feature. An autoregressive prediction model was established. The collected vibration signals with pairing channels were fused. The time sequence of the fused vectors and spectrums were used to build the prediction model. The amplitude of main vector of rotating frequency and spectrum order structure were analyzed and predicted. The uncertainty of the spectrum structure can be eliminated by the information fusion. The reliability of the fault prediction was improved. The study on vibration prediction model system laid a technical foundation for the fault prognostic research