128 research outputs found

    Analysis on the Environmental Conditions for Economic Development in Central China

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    AbstractUsing the data of year 2005 to 2009, quantitatively analyze central regional environmental conditions from the aspects of environmental support level, environmental governance capacity, environment al support capacity and coordination between economic development and environment. Main conclusions are as follows: environmental pollution and environmental improvement co-exist, but increasing pressure on environmental pollution is particularly evident; environmental governance efforts are enhanced greatly; environmental support capacity index shows an increasing trend in general; coordination between economic development and environment fluctuates acutely. some remarks and advices are given finally

    Research on Environmental Regeneration Evaluation System and Design of Industrial Heritage from the Perspective of City-Industry Integration

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    As China gradually enters the post-industrial era, the problem of industrial heritage has become an important issue in recent years. Taking industrial heritage as the research object, city-industry integration as the means, regeneration design as the goal, and Xi\u27an Liucunbu Petrochemical Plant as the carrier, an evaluation system for the industrial heritage of Xi\u27an Liucunbu Petrochemical Plant was established by Delphi method and analytic hierarchy process, and the regeneration design of industrial heritage was carried out according to the evaluation system. The results were as follows: (1) the positioning strategy of regeneration evaluation system of Xi\u27an Liucunbu Petrochemical Plant should be "transformation and utilization" through calculation; (2) the transformation value of tank farm, process plant area and build-up area was determined by weight value, and the corresponding design activities that had certain rationality were carried out, which reduced design positioning errors caused by subjectivity; (3) the construction of a new small-town design strategy system integrating "innovative and entrepreneurial manufacturing factory, modern logistics factory, public facility supporting area and petrochemical plant ruins park" could reasonably solve the problem of industrial heritage in the Xixian New Area of Shaanxi Province, China. Therefore, an evaluation system should be first established for the research of industrial heritage, which will guide the design practice, and the industrial heritage of this plot is further designed based on the national upper-level planning

    Codon optimization, expression, purification, and functional characterization of recombinant human IL-25 in Pichia pastoris

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    Interleukin (IL)-25 (also known as IL-17E) is a distinct member of the IL-17 cytokine family which induces IL-4, IL-5, and IL-13 expression and promotes pathogenic T helper (Th)-2 cell responses in various organs. IL-25 has been shown to have crucial role between innate and adaptive immunity and also a key component of the protection of gastrointestinal helminthes. In this study, to produce bioactive recombinant human IL-25 (rhIL-25), the cDNA of mature IL-25 was performed codon optimization based on methylotropic yeast Pichia pastoris codon bias and cloned into the expression vector pPICZαA. The recombinant vector was transformed into P. pichia strain X-33 and selected by zeocin resistance. Benchtop fermentation and simple purification strategy were established to purify the rhIL-25 with about 17 kDa molecular mass. Functional analysis showed that purified rhIL-25 specifically bond to receptor IL-17BR and induce G-CSF production in vitro. Further annexin V-FITC/PI staining assay indicated that rhIL-25 induced apoptosis in two breast cancer cells, MDA-MB-231 and HBL-100. This study provides a new strategy for the large-scale production of bioactive IL-25 for biological and therapeutic applications

    Lipid alternations in the plasma of COVID-19 patients with various clinical presentations.

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    BACKGROUND: COVID-19 is a highly infectious respiratory disease that can manifest in various clinical presentations. Although many studies have reported the lipidomic signature of COVID-19, the molecular changes in asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals remain elusive. METHODS: This study combined a comprehensive lipidomic analysis of 220 plasma samples from 166 subjects: 62 healthy controls, 16 asymptomatic infections, and 88 COVID-19 patients. We quantified 732 lipids separately in this cohort. We performed a difference analysis, validated with machine learning models, and also performed GO and KEGG pathway enrichment analysis using differential lipids from different control groups. RESULTS: We found 175 differentially expressed lipids associated with SASR-CoV-2 infection, disease severity, and viral persistence in patients with COVID-19. PC (O-20:1/20:1), PC (O-20:1/20:0), and PC (O-18:0/18:1) better distinguished asymptomatic infected individuals from normal individuals. Furthermore, some patients tested positive for SARS-CoV-2 nucleic acid by RT-PCR but did not become negative for a longer period of time (≥60 days, designated here as long-term nucleic acid test positive, LTNP), whereas other patients became negative for viral nucleic acid in a shorter period of time (≤45 days, designated as short-term nucleic acid test positive, STNP). We have found that TG (14:1/14:1/18:2) and FFA (4:0) were differentially expressed in LTNP and STNP. CONCLUSION: In summary, the integration of lipid information can help us discover novel biomarkers to identify asymptomatic individuals and further deepen our understanding of the molecular pathogenesis of COVID-19

    Correlation between preconception maternal non-occupational exposure to interior decoration or oil paint odour and average birth weight of neonates: findings from a nationwide cohort study in China\u27s rural areas

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    BACKGROUND: Birth weight is a critical indicator of neonatal health and foretells people\u27s health in adolescence and even adulthood. Some researchers have warned against the adverse effects on babies\u27 birth weight of exposure to pollutants in interior decoration or oil paint by odour intake. This study evaluated the effects of maternal exposure to such factors before conception on the birth weights of neonates. METHODS: Data on 213 461 cases in this study were from the database of the free National Pre-pregnancy Checkups Project. Defined as \u27exposed\u27 were those women exposed to oil paint odour or interior decoration at home or in the workplace within 6 months before their pregnancy. The study focused on revealing the correlation between such exposure and the birth weight of the neonates of these women, especially the incidence of macrosomia and low birth weight (LBW). Statistical analysis was conducted using the Kruskal-Wallis H test, the Mann-Whitney U test and logistic regression. RESULTS: The birth weight of babies from mothers non-occupationally exposed to such settings averaged 3465 g (range 3150-3650 g), whereas the birth weight of those from mothers free of such exposure averaged 3300 g (range 3000-3600g). Maternal exposure preconception to interior decoration or oil paint odour reduced the incidence of LBW in their babies (p=0.003, OR 0.749, 95% CI 0.617 to 0.909). Such exposure may also augment the probability of macrosomia (p \u3c 0.001, OR 1.297, 95% CI 1.133 to 1.484). CONCLUSION: Maternal exposure to interior decoration or oil paint odour preconception may increase the average birth weight of neonates, as well as the incidence of macrosomia

    AD-BERT: Using Pre-trained contextualized embeddings to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease

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    Objective: We develop a deep learning framework based on the pre-trained Bidirectional Encoder Representations from Transformers (BERT) model using unstructured clinical notes from electronic health records (EHRs) to predict the risk of disease progression from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD). Materials and Methods: We identified 3657 patients diagnosed with MCI together with their progress notes from Northwestern Medicine Enterprise Data Warehouse (NMEDW) between 2000-2020. The progress notes no later than the first MCI diagnosis were used for the prediction. We first preprocessed the notes by deidentification, cleaning and splitting, and then pretrained a BERT model for AD (AD-BERT) based on the publicly available Bio+Clinical BERT on the preprocessed notes. The embeddings of all the sections of a patient's notes processed by AD-BERT were combined by MaxPooling to compute the probability of MCI-to-AD progression. For replication, we conducted a similar set of experiments on 2563 MCI patients identified at Weill Cornell Medicine (WCM) during the same timeframe. Results: Compared with the 7 baseline models, the AD-BERT model achieved the best performance on both datasets, with Area Under receiver operating characteristic Curve (AUC) of 0.8170 and F1 score of 0.4178 on NMEDW dataset and AUC of 0.8830 and F1 score of 0.6836 on WCM dataset. Conclusion: We developed a deep learning framework using BERT models which provide an effective solution for prediction of MCI-to-AD progression using clinical note analysis
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