[Study on clinical symptoms and influencing factors of influenza-associated severe acute respiratory illness in children younger than 5 years old in Suzhou of China, 2011-2017]

Objective: To study the influencing factors of influenza-associated severe acute respiratory illness (SARI) in children younger than 5 years of old in Suzhou, and to provide evidence to support the improvement of prevention and control strategies for influenza in children. Methods: We conducted a prospective influenza surveillance for hospitalized SARI and outpatient influenza-like illness (ILI) at Children's Hospital of Soochow University from April 2011 to March 2017. We compared the clinical and other characteristics of influenza-positive patients with SARI to those with ILI to find the differences and to identify influencing factors of influenza-associated SARI, using χ² test and unconditional logistic regression. Results: We found 786 cases of influenza-associated ILI and 413 cases of influenza-associated SARI during the study period. Cough, runny nose, shortness of breath, asthma or wheezing were more common in influenza-associated SARI than in influenza-associated ILI (P<0.01). Univariate and multivariate logistic regression showed that the influencing factors which significantly associated with increased risk of influenza-associated SARI were as follows: younger age (<6 months OR=3.6, 6-23 months aOR=2.5), respiratory infection history within 3 months (aOR=4.5), chronic lung disease history (OR=3.4), fever above 39.0 ℃ (39.0-39.9 ℃ aOR=2.4, ≥40.0 ℃ aOR=6.0), and the presence of A/H1N1 (aOR=2.3), A/H3N2 (aOR=1.9). Conclusion: Children younger than 2 years old, with a history of chronic lung disease, a history of respiratory infection within 3 months, or with a fever peak above 39.0 ℃ should seek medical advice as soon as possible or receive annual influenza vaccination to reduce the incidence of influenza-associated serious outcomes.

POS0851 IDENTIFICATION OF HUB GENES AND PATHWAYS IN DERMATOMYOSITIS BY BIOINFORMATICS ANALYSIS

Background:

Dermatomyositis (DM) is a chronic systemic autoimmune disease characterized by inflammatory infiltrates in the skin and muscle1. The genes and pathways in the inflamed myopathies in patients with DM are poorly understood2.

Objectives:

To identify the key genes and pathways associated with DM and further discover its pathogenesis.

Methods:

Muscle tissue gene expression profile (GSE143323) were acquired from the GEO database, which included 39 DM samples and 20 normal samples. The differentially expressed genes (DEGs) in DM muscle tissue were screened by adopting the R software. Gene ontology (GO) and Kyoto Encyclopedia of Genome (KEGG) pathway enrichment analysis was performed by Metascape online analysis tool. A protein-protein interaction (PPI) network was then constructed by STRING software using the genes in significantly different pathways. Network of DEGs was analyzed by Cytoscape software. And degree of nodes was used to screen key genes.

Results:

Totally, 126 DEGs were obtained, which contained 122 up-regulated and 4 down-regulated. GO analysis revealed that most of the DEGs were significantly enriched in type I interferon signaling pathway, response to interferon-gamma, collagen-containing extracellular matrix, response to interferon-alpha and bacterium, positive regulation of cell death, leukocyte chemotaxis. KEGG pathway analysis showed that upregulated DEGs enhanced pathways associated with the hepatitis C, complement and coagulation cascades, p53 signaling pathway, RIG-I-like receptor signaling, Osteoclast differentiation, and AGE-RAGE signaling pathway. Ten hub genes were identified in DM, they were ISG15, IRF7, STAT1, MX1, OASL, OAS2, OAS1, OAS3, GBP1, and IRF9 according to the Cytoscape software and cytoHubba plugin.

Conclusion:

The findings from this bioinformatics network analysis study identified the key hub genes that might provide new molecular markers for its diagnosis and treatment.

References:

[1]Olazagasti JM, Niewold TB, Reed AM. Immunological biomarkers in dermatomyositis. Curr Rheumatol Rep 2015;17(11):68. doi: 10.1007/s11926-015-0543-y [published Online First: 2015/09/26].

[2]Chen LY, Cui ZL, Hua FC, et al. Bioinformatics analysis of gene expression profiles of dermatomyositis. Mol Med Rep 2016;14(4):3785-90. doi: 10.3892/mmr.2016.5703 [published Online First: 2016/09/08].

[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0458 IDENTIFICATION OF HUB GENES AND MOLECULAR PATHWAYS IN PATIENTS WITH RHEUMATOID ARTHRITIS BY BIOINFORMATICS ANALYSIS

Background:

Rheumatoid arthritis (RA) is a chronic, inflammatory synovitis based systemic disease of unknown etiology1. The genes and pathways in the inflamed synovium of RA patients are poorly understood.

Objectives:

This study aims to identify differentially expressed genes (DEGs) associated with the progression of synovitis in RA using bioinformatics analysis and explore its pathogenesis2.

Methods:

RA expression profile microarray data GSE89408 were acquired from the public gene chip database (GEO), including 152 synovial tissue samples from RA and 28 healthy synovial tissue samples. The DEGs of RA synovial tissues were screened by adopting the R software. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. Protein-protein interaction (PPI) networks were assembled with Cytoscape software.

Results:

A total of 654 DEGs (268 up-regulated genes and 386 down-regulated genes) were obtained by the differential analysis. The GO enrichment results showed that the up-regulated genes were significantly enriched in the biological processes of myeloid leukocyte activation, cellular response to interferon-gamma and immune response-regulating signaling pathway, and the down-regulated genes were significantly enriched in the biological processes of extracellular matrix, retinoid metabolic process and regulation of lipid metabolic process. The KEGG annotation showed the up-regulated genes mainly participated in the staphylococcus aureus infection, chemokine signaling pathway, lysosome signaling pathway and the down-regulated genes mainly participated in the PPAR signaling pathway, AMPK signaling pathway, ECM-receptor interaction and so on. The 9 hub genes (PTPRC, TLR2, tyrobp, CTSS, CCL2, CCR5, B2M, fcgr1a and PPBP) were obtained based on the String database model by using the Cytoscape software and cytoHubba plugin3.

Conclusion:

The findings identified the molecular mechanisms and the key hub genes of pathogenesis and progression of RA.

References:

[1]Xiong Y, Mi BB, Liu MF, et al. Bioinformatics Analysis and Identification of Genes and Molecular Pathways Involved in Synovial Inflammation in Rheumatoid Arthritis. Med Sci Monit 2019;25:2246-56. doi: 10.12659/MSM.915451 [published Online First: 2019/03/28]

[2]Mun S, Lee J, Park A, et al. Proteomics Approach for the Discovery of Rheumatoid Arthritis Biomarkers Using Mass Spectrometry. Int J Mol Sci 2019;20(18) doi: 10.3390/ijms20184368 [published Online First: 2019/09/08]

[3]Zhu N, Hou J, Wu Y, et al. Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis. Medicine (Baltimore) 2018;97(22):e10997. doi: 10.1097/MD.0000000000010997 [published Online First: 2018/06/01]

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

Background:

Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.

Objectives:

To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.

Methods:

Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.

Results:

A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.

Conclusion:

DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.

References:

[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].

[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].

[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0742 SCREENING AND BIOINFORMATICS ANALYSIS OF HUB GENES AND PATHWAYS FOR PRIMARY SJÖGREN’S SYNDROME BASED ON GEO DATABASE

Background:

Primary Sjögren’s syndrome (pSS) is an autoimmune disease that featured as lymphoplasmacytic infiltration of the exocrine glands leading to sicca symptoms1. However, its underlying molecular mechanisms remain elusive.

Objectives:

This study aims to identify differentially expressed genes (DEGs) and pathways associated with the progression of pSS using bioinformatics analysis and explore its pathogenesis.

Methods:

The pSS-associated gene chip data set GSE66795 was obtained from the Gene Expression Omnibus (GEO) database, which included 131 cases of fully-phenotyped pSS patients’ whole blood samples and 29 cases of control samples. DEGs were screened Using R software. Online tool Metascape2 was used to make Gene Ontology (GO) and KEGG pathway enrichment. The PPI network was performed using String database. Hub genes were identified by Cytoscape.

Results:

A total of 108 DEGs were captured, including 101 up-regulated genes and 7 down-regulated genes. GO enrichment showed that these DEGs were primarily enriched in defense response to virus, response to interferon-gamma, regulation of innate immune response, response to interferon-beta, double-stranded RNA binding, response to interferon-alpha. KEGG pathway enrichment analysis showed these DEGs were principally enriched in Influenza A, RIG-I-like receptor signaling pathway, necroptosis, Staphylococcus aureus infection. Finally, 9 hub genes (STAT1, IRF7, OAS2, GBP1, OAS1, IFIT3, IFIH1, OAS3, DDX60) had highest degree value.

Conclusion:

The findings identified molecular mechanisms and the key hub genes that may involve in the occurrence and development of pSS.

References:

[1]Francois H, Mariette X. Renal involvement in primary Sjogren syndrome. Nat Rev Nephrol 2016;12(2):82-93. doi: 10.1038/nrneph.2015.174 [published Online First: 2015/11/17].

[2]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0848 IDENTIFICATION OF POTENTIAL CRUCIAL GENES AND KEY PATHWAYS IN PULMONARY ARTERIAL HYPERTENSION WITH SYSTEMIC SCLEROSIS BY BIOINFORMATIC ANALYSIS

Background:

Pulmonary arterial hypertension with systemic sclerosis (SSc-PAH) is the main cause of death in patients with SSc. Early diagnosis and timely treatment are very important to reduce the mortality of patients with SSc-PAH1. At present, there are not many sensitive markers for the diagnosis of SSc-PAH. Therefore, it is necessary to mine more sensitive markers as more accurate and practical predictors, which is of great significance for the diagnosis and treatment of SSc-PAH.

Objectives:

To discover the differentially expressed genes (DEGs) and activated signaling pathways in SSc-PAH.

Methods:

Fifty-five samples (27 SSc-PAH v.s 28 normal controls) in GSE33463 chip data obtained from Gene Expression Omnibus (GEO) were included in this study. DEGs in SSc-PAH patients were screened by R, key pathways and hub genes were discoved by Metascape2, STRING3 and Cytoscape.

Results:

Total 431 genes with large differences were identified, including 238 up-regulated genes and 193 down-regulated genes, after standardizing the data (|logFC| > 1; P < 0.05). GO analysis showed that the upregulated genes were mainly involved in defense response to virus, hemoglobin complex, platelet alpha granule membrane and cytokine binding. The downregulated genes were mainly characterized by positive regulation of cell death, regulation of MAPK cascade, regulation of DNA-binding transcription factor activity and transcription factor AP-1 complex. Several significant enriched pathways obtained in the KEGG pathway analysis were Influenza A, Hepatitis C, IL-17 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway. Finally, after the selected differential genes were introduced into STRING online software, the data information of protein interaction network was derived, and 12 core genes in the network were identified, they were CXCL8, PPBP, LPAR1, FPR2, GNG11, CXCL10, LPAR5, JUN, C3AR1, CCR2, CCR3, IRF2.

Conclusion:

The genes and signal pathways related to SSc-PAH discovered by bioinformatics methods could not only provided new molecular markers for its diagnosis and treatment, but also provided new ideas for its related biological research.

References:

[1]Zheng JN, Li Y, Yan YM, et al. Identification and Validation of Key Genes Associated With Systemic Sclerosis-Related Pulmonary Hypertension. Front Genet 2020;11:816. doi: 10.3389/fgene.2020.00816 [published Online First: 2020/08/15].

[2]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].

[3]Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 2019;47(D1):D607-D13. doi: 10.1093/nar/gky1131 [published Online First: 2018/11/27].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

Prediction of spinal anesthesia-induced hypotension during elective cesarean section: a systematic review of prospective observational studies

BACKGROUND

Spinal anesthesia is the standard for elective cesarean section but spinal anesthesia-induced hypotension remains an important problem. Accurate prediction of hypotension could enhance clinical decision-making, alter management, and facilitate early intervention. We performed a systematic review of predictors of spinal anesthesia-induced hypotension and their predictive value during cesarean section.

METHODS

PubMed, Embase, Cochrane Library, Google Scholar and Web of Science databases were searched for prospective observational studies assessing the diagnostic accuracy of predictors of spinal anesthesia-induced hypotension in elective cesarean section. The quality of studies was assessed and predictors were grouped in domains based on the type of predictor.

RESULTS

Thirty-eight studies (n=3086 patients) were included. In most studies, patients received 500-1000 mL crystalloid preload or 500-2000 mL crystalloid coload. Vasopressors for post-spinal hypotension were boluses of ephedrine 5-15 mg and/or phenylephrine 25-100 µg in most studies. The hypotension rate varied from 29% to 80% based on the definition. For analysis, >30 predictors were classified into seven domains: demographic characteristics, baseline hemodynamic variables, baseline sympathovagal balance, postural stress testing, peripheral perfusion indices, blood volume and fluid responsiveness indices, and genetic polymorphism.

CONCLUSIONS

Environmental and individual factors increased outcome variability, which restricted the value of the autonomic nervous system and peripheral perfusion indices for prediction of spinal anesthesia-induced hypotension. Supine stress tests may reflect parturients' cardiovascular tolerance during hemodynamic fluctuations and may optimize the predictive value of static state predictors. Future research for predicting spinal anesthesia-induced hypotension should focus on composite and dynamic parameters during the supine stress tests.

Construction of an MnO2 nanosheet array 3D integrated electrode for sensitive enzyme-free glucose sensing

MnO₂ based electrochemical enzyme-free glucose sensors remain significantly limited by their low electronic conductivity and associated complex preparation. In this paper, an MnO₂ nanosheet array supported on nickel foam (MnO₂ NS/NF) was prepared using a simple hydrothermal synthesis and employed as a 3D integrated electrode for enzyme-free glucose detection. It was found that MnO₂ NS/NF shows high performance with a wide linear range from 1 μM to 1.13 mM, a high sensitivity of 6.45 mA mM^-1 cm^-2, and a low detection limit of 0.5 μM (S/N = 3). Besides, MnO₂ NS/NF shows high selectivity against common interferences and good reliability for glucose detection in human serum. This work demonstrates the promising role of MnO₂ NS/NF as an efficient integrated electrode in enzyme-free glucose detection with high performance.

Development of a new dynamic foveated imager on wide-angle infra-red thermography system to improve local spatial resolution in EAST

A new dynamic foveated imager has been developed and commissioned on the wide-angle infra-red thermography system in the Experimental Advanced Superconducting Tokamak. This technique improves the local spatial resolution by a factor of 2 while maintaining the wide-angle view to ensure safety operation. Taking advantage of the new foveated imager, heat flux splitting under the application of resonant magnetic perturbation (RMP) coils has been clearly observed. The results indicate that the toroidal asymmetric power load pattern is closely related to the perturbation field induced by the RMP coils.

MiR-92 overexpression suppresses immune cell function in ovarian cancer via LATS2/YAP1/PD-L1 pathway

PURPOSE

Increasing evidence suggested that microRNA plays an important role in ovarian cancer. In this study, the role of miR-92 in ovarian cancer was investigated.

METHODS

In this study, miR-92 expression in clinical sample was evaluated, role of miR-92 was investigated in vitro, and underlying mechanism was investigated using Chip, co-IP, and western blot.

RESULTS

In this study, we show that miR-92 is overexpressed in ovarian cancer tissue compared with normal cancer tissue. Transfection of miR-92 increased proliferation of ovarian cancer cell, and increased migration capacity and colony formation were observed after miR-92 transfection; we found that expression of LATS2 was decreased by miR-92, and this was further confirmed by luciferase assay, which proved that miR-92 is targeting 3' of the endogenous LATS2 gene. Downregulation of LATS2 resulted in increased translocation of YAP1 and upregulation of PD-L1, which subsequently suppressed NK cell function and promoted T cell apoptosis. Moreover, co-transfection of YAP1-targeted shRNA could relieve miR-92-induced immune suppression effect. Mechanically, immunoprecipitation (IP) was used to show that LATS2 interacted with YAP1 and subsequently limited nuclear translocation of YAP1; chromatin immunoprecipitation (ChIP) was used to confirm that YAP1 could bind to enhancer region of PD-L1 to enhance transcription activity of PD-L1.

CONCLUSIONS

Our data revealed a novel mechanism which finally resulted in immune suppression in ovarian cancer.

Non-invasive and real-time proliferative activity estimation based on a quantitative radiomics approach for patients with acromegaly: a multicenter study

BACKGROUND

Proliferative activity prediction is important for determining individual treatment strategies for patients with acromegaly, and tumor proliferative activity is usually measured by the expression of Ki-67.

OBJECTIVE

This study aimed to assess the value of a magnetic resonance imaging (MRI)-based radiomics approach in predicting the Ki-67 index of acromegaly patients.

METHODS

A total of 138 patients with acromegaly were retrospectively reviewed and randomly assigned to primary and validation cohorts. Radiomics features were extracted from MR images, and then the elastic net and recursive feature elimination algorithms were applied to determine critical radiomics features for constructing a radiomics signature. Subsequently, multivariable logistic regression analysis was used to select the most informative clinical features, and a radiomics nomogram incorporating a radiomics signature and selected clinical features was constructed for individual predictions. Twenty-five acromegaly patients were enrolled for multicenter model validation.

RESULTS

Seventeen radiomics features were selected to construct a radiomics signature that achieved an area under the curve (AUC) value of 0.96 and 0.89 in the primary cohort and the validation cohort, respectively. A radiomics nomogram that incorporated the radiomics signature and eight selected clinical features was constructed and showed good discrimination and calibration, with an AUC of 0.94 in the primary cohort and 0.91 in the validation cohort. The radiomics signature in the multicenter validation achieved an accuracy of 88.2%. The analysis of the decision curve showed that the radiomics signature and radiomics nomogram were clinically useful for patients with acromegaly.

CONCLUSIONS

The radiomics signature developed in this study could aid neurosurgeons in predicting the Ki-67 index of patients with acromegaly and could contribute to non-invasive measurement of proliferative activity, affecting individual treatment strategies.

Linezolid for the treatment of extensively drug-resistant tuberculosis: a systematic review and meta-analysis

SETTING: Studies have shown that linezolid (LZD) can be used to treat extensively drug-resistant tuberculosis (XDR-TB).OBJECTIVE: To conduct a systematic review and meta-analysis to assess existing evidence concerning efficacy and safety of LZD for XDR-TB treatment.DESIGN: The MEDLINE@OVID, PubMed, EMBASE, the Cochrane Library, Clinical Trials, Sinomed, CMCI, CNKI, VIP and Wanfang databases were systematically searched for randomised controlled trials, cohort studies, case series or case reports on XDR-TB patients treated with LZD from January 2000 to December 2016. Summary estimates of the rate of sputum culture conversion, treatment success and adverse effects were calculated; data that could not be combined were summarised and described qualitatively. The combined results were examined for heterogeneity, sensitivity and publishing bias.RESULTS: Twenty-two original studies covering a total of 302 patients with XDR-TB fulfilled the inclusion criteria. Pooled estimates for sputum culture conversion and treatment success rates were respectively 93.2% and 67.4% in XDR-TB patients on LZD treatment. The pooled estimates for the rate of myelosuppression, peripheral neuropathy, optic neuritis and adverse reactions of the gastrointestinal tract were respectively 42.5%, 26.0%, 19.0% and 35.0%. Heterogeneity was mostly due to the initial dose of LZD (≤600 mg/d or >600 mg/d), as patients with a high initial dose of LZD were more likely to have myelosuppression (48.4% vs. 24.8%, P = 0.010) and adverse events of the gastrointestinal tract (41.3% vs.15.4%, P = 0.100).CONCLUSION: LZD appears to be effective for XDR-TB, but adverse events are common. An LZD dose of ≤600 mg/d as the initial dose for treating XDR-TB patients is recommended.

Effects of thermal boundary condition on methane oxidation in landfill cover soil at different ambient temperatures

Microbial aerobic methane oxidation (MAMO) has been considered as an environmental-friendly method for mitigating methane emission from municipal landfill sites. Soil column has in a landfill cover under one-dimensional (1-D) condition. However, most of the published soil column tests failed to simulate 1-D heat transfer due to the use of thermal conductive boundary at the sidewall. In the present study, a heavily instrumented soil column was developed to quantify the effects of thermal boundary condition on the methane oxidation efficiency under different ambient temperatures in landfill cover soil. The sidewall of the soil column was thermally insulated to ensure 1-D heat transport as would have been typically expected in the field condition. Two soil column tests with and without thermal insulation were conducted at a range of controlled ambient temperatures from 15 to 30°C, for studying how soil moisture, matric suction, gas pressure, soil temperature and gas concentration evolve with MAMO. The test results reveal that ignoring thermal insulation in a soil column test would result in a greater loss of soil heat generation by MAMO and hence oxidation efficiency by up to 100% for the range of temperature considered. When the ambient temperature increased to 30°C (but less than the optimum temperature for MAMO), the MAMO efficiency increased abruptly at first but then decreased substantially with time, and this is likely due to the accumulation of biomass generated by MAMO.

Revision of a CHF correlation for PWR under low pressure conditions with only dimensionless parameters as independent variables

Accurate prediction of the critical heat flux (CHF) is one of the key tasks of PWR core design and safety assessment, for the maximal allowable heat flux in the reactor core is limited by CHF. Since CHF in rod bundle cannot be predicted analytically, up-to-date predictive approach is based on empirical correlations related to the local thermal-hydraulic conditions, geometry and power distribution. However, development of CHF correlation for PWR fuel assemblies under low pressure conditions (2–10 MPa) is constrained by limited amount of experimental data points, which builds up in statistics a typical problem of small sample amounts, but requiring simultaneously high prediction accuracy. In our previous study, stepwise regression method was applied to develop a dimensional, empirical CHF correlation for PWR under low pressure conditions, termed as the advanced low pressure CHF correlation (ALPC), which successfully solves the challenge of small sample problem. However, the ALPC correlation still uses dimensional independent variables with less physical meanings, which limits its physical interpretability. In the current study, stepwise regression method was used to develop a revised, dimensionless version of the ALPC CHF correlation. First, various dimensionless, two-phase thermal-hydraulic parameters that might influence CHF were selected as candidate independent variables. With stepwise regression, the form and coefficients of the revised CHF correlation were optimized in a dynamic manner. Compared to the current ALPC correlation, the revised version developed in this study possesses a similar simple form but a much higher prediction accuracy. Revision of the ALPC correlation demonstrates clearly the advantages of utilizing dimensionless parameters as independent variables in CHF correlation, which points out a new direction of developing rod-bundle CHF correlations for engineering purpose.