lncRNA VIM-AS1 acts as a prognostic biomarker and promotes apoptosis in lung adenocarcinoma.

Background: Long non-coding RNA VIM-antisense 1 (VIM-AS1) has been reported that it is involved in the progression of several cancers. However, the aberrant expression profile, clinical significance, and biological function of VIM-AS1in lung adenocarcinoma (LUAD) have not been fully described. We tend to perform a comprehensive analysis to identify the clinical prognostic value of VIM-AS1 for LUAD patients and explore its potential molecular mechanisms in LUAD development. Methods: The expression features of VIM-AS1 in LUAD were identified based on Cancer Genome Atlas database (TCGA) and genotypic tissue expression (GTEx). The LUAD patients' lung tissues were collected to testify above expression features. Survival analysis and COX regression analysis were performed to evaluate the prognostic value of VIM-AS1 in LUAD patients. Then Correlation analysis was performed to filter VIM-AS1 co-expression genes, and their molecular functions were constructed. Furtherly, we constructed the lung carcinoma A549 cell line with VIM-AS1 overexpression to test its effect on cell function. Results: VIM-AS1 expression levels were significantly downregulated in LUAD tissues. VIM-AS1 with low expression is significantly associated with short overall survival (OS), disease-specific survival (DSS), progress free interval (PFI), late T pathological stage, and lymph node metastasis for LUAD patients. The low expression level of VIM-AS1 was an independent risk factor for poor prognosis for LUAD patients. The biological functions of co-expressed genes indicated that VIM-AS1 regulating the apoptosis process may be the potential mechanism for LUAD. Specifically, we testified VIM-AS1 can promote apoptosis in A549 cells. Conclusion: VIM-AS1 was significantly downregulated in LUAD tissues, and it can be a promising prognostic index for LUAD development. VIM-AS1 regulating apoptotic effects may play important roles in LUAD progression.

Machine learning predictive model for severe COVID-19.

To develop a modified predictive model for severe COVID-19 in people infected with Sars-Cov-2. We developed the predictive model for severe patients of COVID-19 based on the clinical date from the Tumor Center of Union Hospital affiliated with Tongji Medical College, China. A total of 151 cases from Jan. 26 to Mar. 20, 2020, were included. Then we followed 5 steps to predict and evaluate the model: data preprocessing, data splitting, feature selection, model building, prevention of overfitting, and Evaluation, and combined with artificial neural network algorithms. We processed the results in the 5 steps. In feature selection, ALB showed a strong negative correlation (r = 0.771, P < 0.001) whereas GLB (r = 0.661, P < 0.001) and BUN (r = 0.714, P < 0.001) showed a strong positive correlation with severity of COVID-19. TensorFlow was subsequently applied to develop a neural network model. The model achieved good prediction performance, with an area under the curve value of 0.953(0.889-0.982). Our results showed its outstanding performance in prediction. GLB and BUN may be two risk factors for severe COVID-19. Our findings could be of great benefit in the future treatment of patients with COVID-19 and will help to improve the quality of care in the long term. This model has great significance to rationalize early clinical interventions and improve the cure rate.

New Adsorption Models for Entirely Describing the Adsorption Isotherm and Heat of Methane in Heterogeneous Nanopore Structures of Coal.

To understand the adsorption mechanism of methane in heterogeneous nanopore structures of coal, integral adsorption models based on linear, exponential, hyperbolic and quadratic energy distribution functions are established. The adsorption energy domain of the new models is assumed to be a finite interval. These new adsorption models can describe both the adsorption isotherm and the adsorption heat. A volumetric method of adsorption with a microcalorimetry system is used to measure the adsorption isotherms and integral heat, and then the parameters of the new models are obtained by fitting the experimental data. Since the adsorption heat can be different for different adsorption models, it is necessary to fit the adsorption isotherms and heat simultaneously. The fitting results of the adsorption isotherms and heat show that the new models are able to describe the experimental data better than the Langmuir model. By comparing the fitting results and the effective range of adsorption energy of the different adsorption models, it is shown that the exponential energy distribution function is the most reasonable model for methane adsorption in coals, which can be used to evaluate the energetic heterogeneity of nanopores in coal samples. The decreasing exponential energy distributions of three coal samples indicate that a larger adsorption energy corresponds to fewer adsorption sites in the coal samples. The proportion of high adsorption energy is related to the micro-nanopore volume in the coal samples.

[Characteristics of Soil Nutrients and Fungal Community Composition in Crop Rhizosphere Under Different Rotation Patterns].

To study the characteristics of soil nutrients and fungal community composition under different rotation patterns in the arid zone of central Ningxia, we used millet rotation soybean (MRG), rotation grain amaranth (MRA), rotation quinoa (MRQ), and continuous millet rotation (CK) as the objects. The soil nutrient content was determined, and the sequence of the ITS variation region of soil fungi was determined using the Illumina MiSeq high-throughput sequencing platform. The results showed that the effects of different rotation patterns on the soil nutrients were different. The soil pH and electrical conductivity decreased under three rotation patterns, and the soil total nitrogen, total potassium, total phosphorus, and organic matter contents increased. The number of OTUs and α diversity index was higher than those of continuous millet rotation. The results of the fungal community composition study showed that Ascomycota was the dominant flora in 4 patterns. The cluster analysis showed that the fungal genus composition of MRA and MRG was the most similar, followed by MRQ, and that of CK was significantly different with the other three rotation patterns. A correlation analysis showed that the soil nutrients were significantly correlated with several dominant fungal genera (P<0.05 or P<0.01). Further, the soil total nitrogen, total potassium, nitrate nitrogen, and organic matter contents were the most important factors influencing the soil fungal communities. Principal component analysis (PCA) showed that the MRG rotation patterns were better than those of the MRA and MRQ patterns. In summary, crop rotation improved the polytrophic index of the fungal community, changed the soil fungal community structure, and improved soil fertility. Among, the millet and soybean rotation were the best, and we have suggested to promote cereal rotation as one of the main rotation patterns in the cereal industry in the central dry zone.

Parameter identification for fractional fractal diffusion model based on experimental data.

This paper studies the techniques of parameter estimation and their application in determining parameters of the fractional fractal diffusion model. On account of the basic structural characteristics of the porous coal matrix, the fractional fractal diffusion model is established to express the gas transport mechanism in the heterogeneous coal matrix. A L1 finite difference method in the temporal direction while spectral collocation method in the spatial direction is proposed to solve the model numerically. Then, by means of the gas adsorption and desorption experiments in coal samples, attempts have been made by the BFGS method, nonlinear conjugate gradient method, and Bayesian method to compare and contrast to obtain the physical parameters of the model. Furthermore, advantages and limitations of different estimation methods are discussed.

Charge-Transfer Modeling and Polarization DRT Analysis of Proton Ceramics Fuel Cells Based on Mixed Conductive Electrolyte with the Modified Anode-Electrolyte Interface.

A charge-transfer model considering the mixed conductivities of proton, oxygen ion, and free electron in interface-modified La2Ce2O7 (LCO) electrolyte is designed to analyze the characteristics of proton ceramics fuel cell in the field of the open-circuit voltage, internal short-circuit current, proton-transfer number, discharging curves, oxygen/hydrogen partial pressure, and cell efficiencies. The properties of anode-supported single cells with the modified anode-electrolyte interface containing an in situ formed doped BaCeO3 reaction layer are compared to those of unmodified cells at various temperatures T and H2O partial pressures. Besides, the electrochemical impedance spectroscopies of both cells were investigated by the relaxation time distribution to distinguish different polarization processes. The results indicated that the reaction interface layer can effectively reduce the internal short-circuit current density and increase the proton-transfer number of electrolytes. Importantly, the NiO-BaZr0.1Ce0.7Y0.2O3-δ anode can also make more protons transfer from anode to cathode and participate in the cathodic reaction for LCO-based proton ceramics fuel cell. The polarization of the cell decreases with the increase of water partial pressure, which leads to the increase of open-circuit voltage and cell efficiency.

Calcium waves initiating from the anomalous subdiffusive calcium sparks.

The objective of the study is to investigate the propagation of Ca(2+) waves in full-width cardiac myocytes and carry out sensitivity analysis to study the effects of various physiological parameters on global Ca(2+) waves. Based on the anomalous subdiffusion of Ca(2+) sparks, a mathematical model was proposed to characterize the Ca(2+) waves. The computed results were in agreement with the experimental measurements using confocal microscopy. This model includes variables of current through the Ca(2+) release unit (CRU; ICRU), duration of current flow through CRU (Topen), Ca(2+) sensitivity parameter (K), the longitudinal and transverse spatial separation of CRUs (lx and ly, where x denotes longitudinal direction (x-axis) and y denotes transverse direction (y-axis)) and Ca(2+) diffusion coefficients (Dx, Dy). The spatio-temporal mechanism of the anomalous Ca(2+) sparks led to results that were different from those based on Fick's law. The major findings were reported as: ICRU affected the dynamic properties of Ca(2+) waves more significantly than Topen; the effect of K on the properties of Ca(2+) waves was negligible; ly affected the amplitude significantly, but lx affected the longitudinal velocity significantly; in turn, the limitation and significance of the study are discussed.

Modeling calcium wave based on anomalous subdiffusion of calcium sparks in cardiac myocytes.

Ca(2+) sparks and Ca(2+) waves play important roles in calcium release and calcium propagation during the excitation-contraction (EC) coupling process in cardiac myocytes. Although the classical Fick's law is widely used to model Ca(2+) sparks and Ca(2+) waves in cardiac myocytes, it fails to reasonably explain the full-width at half maximum(FWHM) paradox. However, the anomalous subdiffusion model successfully reproduces Ca(2+) sparks of experimental results. In this paper, in the light of anomalous subdiffusion of Ca(2+) sparks, we develop a mathematical model of calcium wave in cardiac myocytes by using stochastic Ca(2+) release of Ca(2+) release units (CRUs). Our model successfully reproduces calcium waves with physiological parameters. The results reveal how Ca(2+) concentration waves propagate from an initial firing of one CRU at a corner or in the middle of considered region, answer how large in magnitude of an anomalous Ca(2+) spark can induce a Ca(2+) wave. With physiological Ca(2+) currents (2pA) through CRUs, it is shown that an initial firing of four adjacent CRUs can form a Ca(2+) wave. Furthermore, the phenomenon of calcium waves collision is also investigated.