351 research outputs found
Microneedle interventional therapy combined with cervical spine manipulation for cervicogenic dizziness
Feasibility analysis of storing solar energy in heterogeneous deep aquifer by hot water circulation: Insights from coupled hydro-thermo modeling
Storing solar energy in the subsurface as heat is a promising way for energy storage and conversion, which has a great potential to address the temporal and spatial mismatch between energy demand and supply. Thermal energy storage in deep aquifers can convert intermittent solar energy into stable high temperature geothermal energy. In this study, a new solar energy storage and conversion system is proposed where solar energy is firstly converted into heat using parabolic troughs and then stored in deep aquifers by high temperature hot water circulation. The geostatistical modelling and hydro-thermo coupling simulations are adopted to investigate the feasibility and efficiency of solar energy storage in deep aquifers. Specifically, how rock permeability heterogeneity (in terms of autocorrelation length and global permeability heterogeneity) impacts the temporal and spatial evolution of temperature distribution and storage efficiency is examined. The simulation results indicate that increased horizontal autocorrelation length and global heterogeneity may accelerate thermal breakthrough, deteriorating storage efficiency. High permeability heterogeneity may also lead to high injection pressure. Deep aquifers with small horizontal autocorrelation lengths and low global heterogeneity tend to have higher storage efficiency. These findings may improve our understanding of solar energy storage mechanism in deep aquifers and guide field applications.Document Type: Original articleCited as: Wang, Y., Zhong, K., Gao, Y., Sun, Z., Dong, R., Wang, X. Feasibility analysis of storing solar energy in heterogeneous deep aquifer by hot water circulation: Insights from coupled hydro-thermo modeling. Advances in Geo-Energy Research, 2023, 10(3): 159-173. https://doi.org/10.46690/ager.2023.12.0
A prediction model for N2 disease in T1 non–small cell lung cancer
ObjectiveControversy remains over the routine use of mediastinoscopy or positron emission tomography in T1 non–small cell lung cancer without lymph node enlargement on computed tomography because the risk of N2 involvement is comparatively low. We aimed to develop a prediction model for N2 disease in cT1N0 non–small cell lung cancer to aid in the decision-making process.MethodsWe reviewed the records of 530 patients with computed tomography–defined T1N0 non–small cell lung cancer who underwent surgical resection with systematic lymph node dissection. Correlations between N2 involvement and clinicopathologic parameters were assessed using univariate analysis and binary logistic regression analysis. A prediction model was built on the basis of logistic regression analysis and was internally validated using bootstrapping.ResultsThe incidence of N2 disease was 16.8%. Four independent predictors were identified in multivariate logistic regression analysis and included in the prediction model: younger age at diagnosis (odds ratio, 0.974; 95% confidence interval, 0.952-0.997), larger tumor size (odds ratio, 2.769; 95% confidence interval, 1.818-4.217), central tumor location (odds ratio, 3.204; 95% confidence interval, 1.512-6.790), and invasive adenocarcinoma histology (odds ratio, 3.537; 95% confidence interval, 1.740-7.191). This model shows good calibration (Hosmer–Lemeshow test: P = .784), reasonable discrimination (area under the receiver operating characteristic curve, 0.726; 95% confidence interval, 0.669-0.784), and minimal overfitting demonstrated by bootstrapping.ConclusionsWe developed a 4-predictor model that can estimate the probability of N2 disease in computed tomography–defined T1N0 non–small cell lung cancer. This prediction model can help to determine the cost-effective use of mediastinal staging procedures
Up-regulation of MiR-205 under hypoxia promotes epithelial-mesenchymal transition by targeting ASPP2
The epithelial–mesenchymal transition (EMT) is one of the crucial procedures for cancer invasion and distal metastasis. Despite undergoing intensive studies, the mechanisms underlying EMT remain to be completely elucidated. Here, we identified that apoptosis-stimulating protein of p53-2 (ASPP2) is a novel target of MiR-205 in various cancers. Interestingly, the binding site of MiR-205 at the 3′-untranslated region of ASPP2 was highly conserved among different species. An inverse correlation between MiR-205 and ASPP2 was further observed in vivo in cervical cancers, suggesting MiR-205 may be an important physiological inhibitor of ASPP2. Hypoxia is a hallmark of solid tumor microenvironment and one of such conditions to induce EMT. Notably, MiR-205 was remarkably induced by hypoxia in cervical and lung cancer cells. A marked suppression of ASPP2 was observed simultaneously. Further studies confirmed that hypoxia-induced ASPP2 suppression was mainly attributed to the elevated MiR-205. Interestingly, the alteration of MiR-205/ASPP2 under hypoxia was accompanied with the decreased epithelial marker E-cadherin and increased mesenchymal marker Vimentin, as well as a morphological transition from the typical cobblestone-like appearance to the mesenchymal-like structure. More importantly, MiR-205 mimics or ASPP2 silencing similarly promoted EMT process. By contrast, ASPP2 recovery or MiR-205 inhibitor reversed MiR-205-dependent EMT. Further studies demonstrated that the newly revealed MiR-205/ASPP2 axis promoted cell migration and also increased cell proliferation both in vivo and in vitro. These data together implicated a critical impact of MiR-205/ASPP2 on promoting EMT. MiR-205/ASPP2 may be potential diagnostic and therapeutic biomarkers in cervical and lung cancers
Cost-Effective Current Measurement Technique for Four-Phase SRM Control by Split Dual Bus Line Without Pulse Injection and Voltage Penalty
Modulation of the major histocompatibility complex by neural stem cell-derived neurotrophic factors used for regenerative therapy in a rat model of stroke
Exploring the supersymmetric U(1) U(1) model with dark matter, muon and mass limits
We study the low scale predictions of supersymmetric standard model extended
by symmetry, obtained from breaking via a
left-right supersymmetric model, imposing universal boundary conditions. Two
singlet Higgs fields are responsible for the radiative symmetry breaking, and a singlet fermion is introduced to
generate neutrino masses through inverse seesaw mechanism. The lightest
neutralino or sneutrino emerge as dark matter candidates, with different low
scale implications. We find that the composition of the neutralino LSP changes
considerably depending on the neutralino LSP mass, from roughly half
bino, half MSSM bino, to singlet higgsino, or completely dominated by MSSM
higgsino. The sneutrino LSP is statistically much less likely, and when it
occurs it is a 50-50 mixture of right-handed sneutrino and the scalar . Most of the solutions consistent with the relic density constraint survive
the XENON 1T exclusion curve for both LSP cases. We compare the two scenarios
and investigate parameter space points and find consistency with the muon
anomalous magnetic moment only at the edge of deviation from the
measured value. However, we find that the sneutrino LSP solutions could be
ruled out completely by strict reinforcement of the recent mass
bounds. We finally discuss collider prospects for testing the model
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