449 research outputs found

    Discharge Forecasting By Applying Artificial Neural Networks At The Jinsha River Basin, China

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    Flood prediction methods play an important role in providing early warnings to government offices. The ability to predict future river flows helps people anticipate and plan for upcoming flooding, preventing deaths and decreasing property destruction. Different hydrological models supporting these predictions have different characteristics, driven by available data and the research area. This study applied three different types of Artificial Neural Networks (ANN) and an autoregressive model to study the Jinsha river basin (JRB), in the upper part of the Yangtze River in China. The three ANN techniques include feedforward back propagation neural networks (FFBPNN), generalized regression neural networks (GRNN), and the radial basis function neural networks (RBFNN). Artificial Neural Networks (ANN) has shown Great deal of accuracy as compared to statistical autoregressive (AR) model because statistical model cannot able to simulate the non-linear pattern. The results varied across the cases used in the study; based on available data and the study area, FFBPNN showed the best applicability, compared to other techniques

    High expression of ubiquitin-conjugating enzyme 2C (UBE2C) correlates with nasopharyngeal carcinoma progression

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    BACKGROUND: Overexpression of ubiquitin-conjugating enzyme 2C (UBE2C) has been detected in many types of human cancers, and is correlated with tumor malignancy. However, the role of UBE2C in human nasopharyngeal carcinoma (NPC) is unclear. In this study, we investigated the role of aberrant UBE2C expression in the progression of human NPC. METHODS: Immunohistochemical analysis was performed to detect UBE2C protein in clinical samples of NPC and benign nasopharyngeal tissues, and the association of UBE2C expression with patient clinicopathological characteristics was analyzed. UBEC2 expression profiles were evaluated in cell lines representing varying differentiated stages of NPC and immortalized nasopharyngeal epithelia NP-69 cells using quantitative RT-PCR, western blotting and fluorescent staining. Furthermore, UBE2C was knocked down using RNA interference in these cell lines and proliferation and cell cycle distribution was investigated. RESULTS: Immunohistochemical analysis revealed that UBE2C protein expression levels were higher in NPC tissues than in benign nasopharyngeal tissues (P<0.001). Moreover, high UBE2C protein expression was positively correlated with tumor size (P=0.017), lymph node metastasis (P=0.016) and distant metastasis (P=0.015) in NPC patients. In vitro experiments demonstrated that UBE2C expression levels were inversely correlated with the degree of differentiation of NPC cell lines, whereas UBE2C displayed low level of expression in NP-69 cells. Knockdown of UBE2C led to significant arrest at the S and G2/M phases of the cell cycle, and decreased cell proliferation was observed in poorly-differentiated CNE2Z NPC cells and undifferentiated C666-1 cells, but not in well-differentiated CNE1 and immortalized NP-69 cells. CONCLUSIONS: Our findings suggest that high expression of UBE2C in human NPC is closely related to tumor malignancy, and may be a potential marker for NPC progression

    A Contribution by Ice Nuclei to Global Warming

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    Ice nuclei (IN) significantly affect clouds via supercooled droplets, that in turn modulate atmospheric radiation and thus climate change. Since the IN effect is relatively strong in stratiform clouds but weak in convective ones, the overall effect depends on the ratio of stratiform to convective cloud amount. In this paper, 10 years of TRMM (Tropical Rainfall Measuring Mission) satellite data are analyzed to confirm that stratiform precipitation fraction increases with increasing latitude, which implies that the IN effect is stronger at higher latitudes. To quantitatively evaluate the IN effect versus latitude, large-scale forcing data from ten field campaigns are used to drive a CRM (cloud-resolving model) to generate longterm cloud simulations. As revealed in the simulations, the increase in the net downward radiative flux at the TOA (top of the atmosphere) from doubling the current IN concentrations is larger at higher latitude, which is attributed to the meridional tendency in the stratiform precipitation fraction. Surface warming from doubling the IN concentrations, based on the radiative balance of the globe, is compared with that from anthropogenic COZ . It is found that the former effect is stronger than the latter in middle and high latitudes but not in the Tropics. With regard to the impact of IN on global warming, there are two factors to consider: the radiative effect from increasing the IN concentration and the increase in IN concentration itself. The former relies on cloud ensembles and thus varies mainly with latitude. In contrast, the latter relies on IN sources (e.g., the land surface distribution) and thus varies not only with latitude but also longitude. Global desertification and industrialization provide clues on the geographic variation of the increase in IN concentration since pre-industrial times. Thus, their effect on global warming can be inferred and then be compared with observations. A general match in geographic and seasonal variations between the inferred and observed warming suggests that IN may have contributed positively to global warming over the past decades, especially in middle and high latitudes

    Identification of diagnostic hub genes related to neutrophils and infiltrating immune cell alterations in idiopathic pulmonary fibrosis

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    BackgroundThere is still a lack of specific indicators to diagnose idiopathic pulmonary fibrosis (IPF). And the role of immune responses in IPF is elusive. In this study, we aimed to identify hub genes for diagnosing IPF and to explore the immune microenvironment in IPF.MethodsWe identified differentially expressed genes (DEGs) between IPF and control lung samples using the GEO database. Combining LASSO regression and SVM-RFE machine learning algorithms, we identified hub genes. Their differential expression were further validated in bleomycin-induced pulmonary fibrosis model mice and a meta-GEO cohort consisting of five merged GEO datasets. Then, we used the hub genes to construct a diagnostic model. All GEO datasets met the inclusion criteria, and verification methods, including ROC curve analysis, calibration curve (CC) analysis, decision curve analysis (DCA) and clinical impact curve (CIC) analysis, were performed to validate the reliability of the model. Through the Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm (CIBERSORT), we analyzed the correlations between infiltrating immune cells and hub genes and the changes in diverse infiltrating immune cells in IPF.ResultsA total of 412 DEGs were identified between IPF and healthy control samples, of which 283 were upregulated and 129 were downregulated. Through machine learning, three hub genes (ASPN, SFRP2, SLCO4A1) were screened. We confirmed their differential expression using pulmonary fibrosis model mice evaluated by qPCR, western blotting and immunofluorescence staining and analysis of the meta-GEO cohort. There was a strong correlation between the expression of the three hub genes and neutrophils. Then, we constructed a diagnostic model for diagnosing IPF. The areas under the curve were 1.000 and 0.962 for the training and validation cohorts, respectively. The analysis of other external validation cohorts, as well as the CC analysis, DCA, and CIC analysis, also demonstrated strong agreement. There was also a significant correlation between IPF and infiltrating immune cells. The frequencies of most infiltrating immune cells involved in activating adaptive immune responses were increased in IPF, and a majority of innate immune cells showed reduced frequencies.ConclusionOur study demonstrated that three hub genes (ASPN, SFRP2, SLCO4A1) were associated with neutrophils, and the model constructed with these genes showed good diagnostic value in IPF. There was a significant correlation between IPF and infiltrating immune cells, indicating the potential role of immune regulation in the pathological process of IPF

    Efficacy of two different dosages of prednisone for treatment of subacute thyroiditis: a single-centre, prospective, randomized, open-label, non-inferiority trial

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    Introduction: The study aimed to explore the efficacy and safety of low-dose (LD) and regular-dose (RD) prednisone (PDN) for the treatment of subacute thyroiditis (SAT). Material and methods: Patients were randomly allocated using the block randomization method to the 2 groups. The primary outcome was the time required for PDN treatment. Secondary outcomes included percentages of relapse, mean score for the Morisky Medication Adherence Scale-8© (MMAS-8), time required for symptoms to resolve, cumulative PDN dose (mg), and mean erythrocyte sedimentation rate (ESR) at 2 weeks and at baseline. Results: The study cohort included 77 patients, randomized 74 participants, and 68 completed the study. There was no significant difference in the treatment duration between the LD and RD groups (55.31 ± 14.05 vs. 61.25 ± 19.95 days, p = 0.053). The mean difference in the time required for PDN treatment between the LD and RD groups was –1.86 [95% confidence interval (CI) = –10.64 to 6.92] days, which was within the non-inferiority margin of 7 days. There was a significant difference in the mean score for MMAS-8 between the LD and RD groups (5.84 ± 0.88 vs. 5.33 ± 1.12, p = 0.031). Also, there was a significant difference in the cumulative PDN dose between the LD and RD groups (504.22 ± 236.86 vs. 1002.28 ± 309.86, p = 0.046). The ESR at 2 weeks was statistically significant compared to baseline values in both groups, with pre-treatment and post-treatment ESRs of 49.91 ± 24.95 and 17.91 ± 12.60/mm/h, (p &lt; 0.0001) in the LD group and 65.08 ± 21.77 and 17.23 ± 13.61/mm/h (p &lt; 0.0001) in the RD group. Conclusion: Low-dose PDN therapy may be sufficient to achieve complete recovery and better outcomes for SAT. This study is registered with the Chinese Clinical Trial Registry (02/10/2021 ChiCTR2100051762)

    SCRaMbLE generates designed combinatorial stochastic diversity in synthetic chromosomes

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    Synthetic chromosome rearrangement and modification by loxP-mediated evolution (SCRaMbLE) generates combinatorial genomic diversity through rearrangements at designed recombinase sites. We applied SCRaMbLE to yeast synthetic chromosome arm synIXR (43 recombinase sites) and then used a computational pipeline to infer or unscramble the sequence of recombinations that created the observed genomes. Deep sequencing of 64 synIXR SCRaMbLE strains revealed 156 deletions, 89 inversions, 94 duplications, and 55 additional complex rearrangements; several duplications are consistent with a double rolling circle mechanism. Every SCRaMbLE strain was unique, validating the capability of SCRaMbLE to explore a diverse space of genomes. Rearrangements occurred exclusively at designed loxPsym sites, with no significant evidence for ectopic rearrangements or mutations involving synthetic regions, the 99% nonsynthetic nuclear genome, or the mitochondrial genome. Deletion frequencies identified genes required for viability or fast growth. Replacement of 3′ UTR by non-UTR sequence had surprisingly little effect on fitness. SCRaMbLE generates genome diversity in designated regions, reveals fitness constraints, and should scale to simultaneous evolution of multiple synthetic chromosomes.</jats:p
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