Publications by authors named "Nan Duan"

14 Publications

  • Page 1 of 1

Combination of Urine Exosomal mRNAs and lncRNAs as Novel Diagnostic Biomarkers for Bladder Cancer.

Front Oncol 2021 27;11:667212. Epub 2021 Apr 27.

Department of Clinical Laboratory, Peking University First Hospital, Beijing, China.

Background: The recent discovery of miRNAs and lncRNAs in urine exosomes has emerged as promising diagnostic biomarkers for bladder cancer (BCa). However, mRNAs as the direct products of transcription has not been well evaluated in exosomes as biomarkers for BCa diagnosis. The purpose of this study was to identify tumor progression-related mRNAs and lncRNAs in urine exosomes that could be used for detection of BCa.

Methods: RNA-sequencing was performed to identify tumor progression-related biomarkers in three matched superficial tumor and deep infiltrating tumor regions of muscle-invasive bladder cancer (MIBC) specimens, differently expressed mRNAs and lncRNAs were validated in TCGA dataset (n = 391) in the discovery stage. Then candidate RNAs were chosen for evaluation in urine exosomes of a training cohort (10 BCa and 10 healthy controls) and a validation cohort (80 BCa and 80 healthy controls) using RT-qPCR. The diagnostic potential of the candidates were evaluated by receiver operating characteristic (ROC) curves.

Results: RNA sequencing revealed 8 mRNAs and 32 lncRNAs that were significantly upregulated in deep infiltrating tumor region. After validation in TCGA database, 10 markedly dysregulated RNAs were selected for further investigation in urine exosomes, of which five (mRNAs: KLHDC7B, CASP14, and PRSS1; lncRNAs: MIR205HG and GAS5) were verified to be significantly dysregulated. The combination of the five RNAs had the highest AUC to disguising the BCa (0.924, 95% CI, 0.875-0.974) or early stage BCa patients (0.910, 95% CI, 0.850 to 0.971) from HCs. The expression levels of these five RNAs were correlated with tumor stage, grade, and hematuria degrees.

Conclusions: These findings highlight the potential of urine exosomal mRNAs and lncRNAs profiling in the early diagnosis and provide new insights into the molecular mechanisms involved in BCa.
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http://dx.doi.org/10.3389/fonc.2021.667212DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8111292PMC
April 2021

Insights into the mechanism regulating the differential expression of the P28-OMP outer membrane proteins in obligatory intracellular pathogen .

Emerg Microbes Infect 2021 Dec;10(1):461-471

Key Laboratory of Molecular Microbiology and Technology of the Ministry of Education, Department of Microbiology, College of Life Sciences, Nankai University, Tianjin, People's Republic of China.

causes human monocytic ehrlichiosis (HME), which is one of the most prevalent, life-threatening emerging infectious zoonoses. The life cycle of includes ticks and mammals, in which proteins are expressed differentially contributing to bacterial survival and infection. Among the P28-OMP outer membrane proteins, OMP-1B and P28 are predominantly expressed in tick cells and mammalian macrophages, respectively. The mechanisms regulating this differential expression have not been comprehensively studied. Here, we demonstrate that the transcriptional regulators EcxR and Tr1 regulate the differential expression of and in Recombinant Tr1 bound to the promoters of and and transactivated and promoter-EGFP fusion constructs in . The consensus sequence of Tr1 binding motifs was A/TATA as determined with DNase I footprint assay. Tr1 showed a higher affinity towards the promoter than the promoter as determined with surface plasmon resonance. EcxR activated the expression in response to a temperature decrease. At 37°C low level of Tr1 activated the expression. At 25°C high level of Tr1 activated the expression, while repressing the expression by binding to an additional site upstream of the gene. Our data provide insights into a novel mechanism mediated by Tr1 regulating differential gene expression, which may aid in the development of new therapeutics for HME.
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http://dx.doi.org/10.1080/22221751.2021.1899054DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7971322PMC
December 2021

Enhancing detection of steady-state visual evoked potentials using channel ensemble method.

J Neural Eng 2021 Feb 18. Epub 2021 Feb 18.

Xi'an Jiaotong University School of Mechanical Engineering, XIANNING WEST ROAD, XI'AN, Shaanxi, 710049, CHINA.

Objective: This study proposed and evaluated a channel ensemble approach to enhance detection of steady-state visual evoked potentials (SSVEPs).

Approach: Collected multi-channel electroencephalogram (EEG) signals were classified into multiple groups of new analysis signals based on correlation analysis, and each group of analysis signals contained signals from a different number of electrode channels. These groups of analysis signals were used as the input of a training-free feature extraction model, and the obtained feature coefficients were converted into feature probability values using the softmax function. The ensemble value of multiple sets of feature probability values was determined and used as the final discrimination coefficient.

Main Results: Compared with canonical correlation analysis (CCA), likelihood ratio test (LRT), and multivariate synchronization index (MSI) analysis methods using a standard approach, the recognition accuracies of the methods using a channel ensemble approach were improved by 5.05%, 3.87%, and 3.42%, and the information transfer rates (ITRs) were improved by 6.00%, 4.61%, and 3.71%, respectively. The channel ensemble method also obtained better recognition results than the standard algorithm on the public dataset. This study validated the efficiency of the proposed method to enhance the detection of SSVEPs, demonstrating its potential use in practical brain-computer interface (BCI) systems.

Significance: A SSVEP-based BCI system using a channel ensemble method could achieve high ITR, indicating great potential of this design for various applications with improved control and interaction.
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http://dx.doi.org/10.1088/1741-2552/abe7cfDOI Listing
February 2021

Clinical manifestation and genetic findings in three boys with low molecular Weight Proteinuria - three case reports for exploring Dent Disease and Fanconi syndrome.

BMC Nephrol 2021 01 11;22(1):24. Epub 2021 Jan 11.

Department of Clinical Laboratory, Peking University First Hospital, No.8 Xishiku St., Xicheng District, 100034, Beijing, China.

Background: Dent disease is an X-linked form of progressive renal disease. This rare disorder was characterized by hypercalciuria, low molecular weight (LMW) proteinuria and proximal tubular dysfunction, caused by pathogenic variants in CLCN5 (Dent disease 1) or OCRL (Dent disease 2) genes. Fanconi syndrome is a consequence of decreased water and solute resorption in the proximal tubule of the kidney. Fanconi syndrome caused by proximal tubular dysfunction such as Dent disease might occur in early stage of the disease.

Case Presentation: Three cases reported in this study were 3-, 10- and 14-year-old boys, and proteinuria was the first impression in all the cases. All the boys presented with LMW proteinuria and elevated urine albumin-to-creatinine ratio (ACR). Case 1 revealed a pathogenic variant in exon 11 of CLCN5 gene [NM_001127899; c.1444delG] and a nonsense mutation at nucleotide 1509 [p.L503*], and he was diagnosed as Dent disease 1. Case 2 carried a deletion of exon 3 and 4 of OCRL1 gene [NM_000276.4; c.120-238delGA] and a nonsense mutation at nucleotide 171 in exon 5 [p.E57*], and this boy was diagnosed as Dent disease 2. Genetic analysis of Case 3 showed a missense mutation located in exon 2 of HNF4A gene [EF591040.1; c.253C > T; p.R85W] which is responsible for Fanconi syndrome. All of three pathogenic variants were not registered in GenBank.

Conclusions: Urine protein electrophoresis should be performed for patients with proteinuria. When patients have LMW proteinuria and/or hypercalciuria, definite diagnosis and identification of Dent disease and Fanconi syndrome requires further genetic analyses.
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http://dx.doi.org/10.1186/s12882-020-02225-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7802264PMC
January 2021

Instance Transfer Subject-Dependent Strategy for Motor Imagery Signal Classification Using Deep Convolutional Neural Networks.

Comput Math Methods Med 2020 28;2020:1683013. Epub 2020 Aug 28.

School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

In the process of brain-computer interface (BCI), variations across sessions/subjects result in differences in the properties of potential of the brain. This issue may lead to variations in feature distribution of electroencephalogram (EEG) across subjects, which greatly reduces the generalization ability of a classifier. Although subject-dependent (SD) strategy provides a promising way to solve the problem of personalized classification, it cannot achieve expected performance due to the limitation of the amount of data especially for a deep neural network (DNN) classification model. Herein, we propose an instance transfer subject-independent (ITSD) framework combined with a convolutional neural network (CNN) to improve the classification accuracy of the model during motor imagery (MI) task. The proposed framework consists of the following steps. Firstly, an instance transfer learning based on the perceptive Hash algorithm is proposed to measure similarity of spectrogram EEG signals between different subjects. Then, we develop a CNN to decode these signals after instance transfer learning. Next, the performance of classifications by different training strategies (subject-independent- (SI-) CNN, SD-CNN, and ITSD-CNN) are compared. To verify the effectiveness of the algorithm, we evaluate it on the dataset of BCI competition IV-2b. Experiments show that the instance transfer learning can achieve positive instance transfer using a CNN classification model. Among the three different training strategies, the average classification accuracy of ITSD-CNN can achieve 94.7 ± 2.6 and obtain obvious improvement compared with a contrast model ( < 0.01). Compared with other methods proposed in previous research, the framework of ITSD-CNN outperforms the state-of-the-art classification methods with a mean kappa value of 0.664.
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http://dx.doi.org/10.1155/2020/1683013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7474754PMC
August 2020

Data Augmentation for Motor Imagery Signal Classification Based on a Hybrid Neural Network.

Sensors (Basel) 2020 Aug 11;20(16). Epub 2020 Aug 11.

School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

As an important paradigm of spontaneous brain-computer interfaces (BCIs), motor imagery (MI) has been widely used in the fields of neurological rehabilitation and robot control. Recently, researchers have proposed various methods for feature extraction and classification based on MI signals. The decoding model based on deep neural networks (DNNs) has attracted significant attention in the field of MI signal processing. Due to the strict requirements for subjects and experimental environments, it is difficult to collect large-scale and high-quality electroencephalogram (EEG) data. However, the performance of a deep learning model depends directly on the size of the datasets. Therefore, the decoding of MI-EEG signals based on a DNN has proven highly challenging in practice. Based on this, we investigated the performance of different data augmentation (DA) methods for the classification of MI data using a DNN. First, we transformed the time series signals into spectrogram images using a short-time Fourier transform (STFT). Then, we evaluated and compared the performance of different DA methods for this spectrogram data. Next, we developed a convolutional neural network (CNN) to classify the MI signals and compared the classification performance of after DA. The Fréchet inception distance (FID) was used to evaluate the quality of the generated data (GD) and the classification accuracy, and mean kappa values were used to explore the best CNN-DA method. In addition, analysis of variance (ANOVA) and paired -tests were used to assess the significance of the results. The results showed that the deep convolutional generative adversarial network (DCGAN) provided better augmentation performance than traditional DA methods: geometric transformation (GT), autoencoder (AE), and variational autoencoder (VAE) ( < 0.01). Public datasets of the BCI competition IV (datasets 1 and 2b) were used to verify the classification performance. Improvements in the classification accuracies of 17% and 21% ( < 0.01) were observed after DA for the two datasets. In addition, the hybrid network CNN-DCGAN outperformed the other classification methods, with average kappa values of 0.564 and 0.677 for the two datasets.
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http://dx.doi.org/10.3390/s20164485DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7474427PMC
August 2020

Microbial Distribution and Antibiotic Susceptibility of Lower Respiratory Tract Infections Patients From Pediatric Ward, Adult Respiratory Ward, and Respiratory Intensive Care Unit.

Front Microbiol 2020 30;11:1480. Epub 2020 Jun 30.

Department of Clinical Laboratory, Peking University First Hospital, Beijing, China.

Introduction: Lower respiratory tract infections (LRTIs) account for significant morbidity and mortality in patients admitted to hospitals worldwide, especially in children and elderly. The prevalent microorganisms and antibiotic susceptibility were investigated among LRTI patients from the pediatric ward, adult respiratory ward, and respiratory intensive care unit (RICU) in order to achieve more efficient treatment protocols and better recovery.

Methods: In this retrospective cross-sectional study (January 2016 to December 2019), 4,161 positive culture samples out of 18,798 different specimens (9,645 respiratory tract samples and 9,153 blood samples) from LRTI patients were analyzed for pathogen incidence and antibiotic sensitivity.

Results: Among the respiratory tract cultures, the frequency of Gram-negative bacterial strains was higher than Gram-positive bacterial strains. was the dominant pathogen in both the adult respiratory ward ( = 156, 21.49%) and RICU ( = 975, 35.67%), whereas ( = 66, 19.19%) was the most common bacterium in the pediatric ward. Among the blood cultures, Gram-positive bacteria remained the major microorganisms involved in LRTIs, and the most frequent pathogen was ( = 59, 47.20%) in the pediatric ward and ( = 10, 21.8%) in adult respiratory ward. However, Gram-negative bacteria were the main pathogens in the RICU, of which ( = 51, 27.57%) is the most prevalent. of LRTI patients remained highly susceptible (>70%) to routine antibiotics in pediatric ward. However, it only had high susceptibility to amikacin, tobramycin, gentamicin in both the adult respiratory ward and RICU and its antibiotic sensitivity to meropenem and imipenem was moderate in the adult respiratory ward and mild (<30%) in the RICU. isolated from LRTI patients was highly susceptible to linezolid, daptomycin, teicoplanin, vancomycin, tigecycline, rifampicin, and trimethoprim/sulfamethoxazole in all three wards, moderately susceptible to gentamicin in both the adult respiratory ward and RICU and to clindamycin, oxacillin, moxifloxacin only in the adult respiratory ward.

Conclusions: Microbial distribution and their patterns of antibiotic susceptibility revealed a high divergence among LRTI patients admitted to different wards in this hospital. Thus, different antibiotic therapies should be considered for distinct age groups.
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http://dx.doi.org/10.3389/fmicb.2020.01480DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338583PMC
June 2020

Baseline Glycated Albumin Predicts the Renal Dysfunction in a Five-Year Prospective Population-Based Study.

Clin Lab 2020 Jul;66(7)

Background: Glycated albumin (GA) was reported to be associated with renal dysfunction in non-diabetic CKD population. This study assessed the correlation of GA and renal dysfunction and explored risk factors affecting renal progression in a general population-based study through a five-year follow-up.

Methods: Individuals who underwent a physical examination between September 2010 and September 2015 were enrolled. Multivariate linear regression was performed to assess the relationship between GA and eGFR change rate. The relationship between GA and renal progression was analyzed by multivariate logistic regression among 1,501 participants. Other risk factors were also explored and their predictive value was evaluated by ROC analysis, external validation was carried out in another 603 participants from the general population.

Results: The frequencies of subjects with renal progression increased obviously with the increment of baseline and mean GA according to quartile stratification (p for trend < 0.001). Baseline GA, age, and uric acid (p < 0.05) were identified as risk factors for renal dysfunction with a 30% or more decrease of eGFR. For every 1% increase of GA, the risk of deterioration of renal function increased to 1.585 in the population (95% CI, 1.299 - 1.935, p < 0.001). The predictive value of the model-building equation was confirmed by ROC analysis (AUC = 0.82, 95% CI: 0.773 - 0.832, p < 0.001) and in the validation group, predictive sensitivity and specificity were 85.7% and 73.5%.

Conclusions: Baseline GA is independently associated with renal dysfunction. Uric acid and age are also considered risk factors. GA combining with age, serum creatinine and uric acid can serve as predictive indicators for the progression of renal dysfunction.
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http://dx.doi.org/10.7754/Clin.Lab.2019.190634DOI Listing
July 2020

Crk1/2 and CrkL play critical roles in maintaining podocyte morphology and function.

Exp Cell Res 2020 09 11;394(1):112135. Epub 2020 Jun 11.

Department of Clinical Laboratory, Peking University First Hospital, Beijing, China. Electronic address:

Podocytes are actin-rich epithelial cells whose effacement and detachment are the main cause of glomerular disease. Crk family proteins: Crk1/2 and CrkL are reported to be important intracellular signaling proteins that are involved in many biological processes. However, the roles of them in maintaining podocyte morphology and function remain poorly understood. In this study, specific knocking down of Crk1/2 and CrkL in podocytes caused abnormal cell morphology, actin cytoskeleton rearrangement and dysfunction in cell adhesion, spreading, migration, and viability. The p130Cas, focal adhesion kinase, phosphatidylinositol 3-kinase/Akt, p38 and JNK signaling pathways involved in these alterations. Furthermore, knocking down CrkL alone conferred a more modest phenotype than did the Crk1/2 knockdown and the double knockdown. Kidney biopsy specimens from patients with focal segmental glomerulosclerosis and minimal change nephropathy showed downregulation of Crk1/2 and CrkL in glomeruli. In zebrafish embryos, Crk1/2 and CrkL knockdown compromised the morphology and caused abnormal glomerular development. Thus, our results suggest that Crk1/2 and CrkL expression are important in podocytes; loss of either will cause podocyte dysfunction, leading to foot process effacement and podocyte detachment.
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http://dx.doi.org/10.1016/j.yexcr.2020.112135DOI Listing
September 2020

Urine afamin and afamin-creatinine ratio as biomarkers for kidney injury.

Biomark Med 2018 11 15;12(11):1241-1249. Epub 2018 Nov 15.

Department of Clinical Laboratory, Peking University First Hospital, 100034, Beijing, PR China.

Aim: The aim of this study was to evaluate the urine afamin (uAFM) and afamin-creatinine ratio (AfCR) levels in patients with glomerulonephritis.

Patients & Methods: We determined uAFM and AfCR of 247 healthy volunteers and 129 biopsy-proven glomerulonephritis patients.

Results: Analytical evaluation study revealed the assay is a reliable and robust test for measuring uAFM. For reference intervals, uAFM and AfCR values were different significantly between males and females. uAFM and AfCR levels were significantly increased in patients with primary membranous nephropathy, IgA nephropathy and minimal change disease compared with healthy volunteers. uAFM and AfCR were positively correlated with urine albumin and albumin-creatinine ratio, respectively.

Conclusion: Our study suggested that uAFM and AfCR may be attractive biomarkers for kidney injury.
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http://dx.doi.org/10.2217/bmm-2018-0126DOI Listing
November 2018

Urine proteomics of primary membranous nephropathy using nanoscale liquid chromatography tandem mass spectrometry analysis.

Clin Proteomics 2018 7;15. Epub 2018 Feb 7.

1Department of Clinical Laboratory, Peking University First Hospital, Beijing, China.

Background: Primary membranous nephropathy (PMN) is an important cause of nephrotic syndrome in adults. Urine proteome may provide important clues of pathophysiological mechanisms in PMN. In the current study, we analyzed and compared the proteome of urine from patients with PMN and normal controls.

Methods: We performed two technical replicates (TMT1 and TMT2) to analyze and compare the urine proteome from patients with PMN and normal controls by tandem mass tag (TMT) technology coupled with nanoscale liquid chromatography tandem mass spectrometry analysis (LC-MS/MS). Gene ontology (GO) enrichment analysis was performed to analyse general characterization of the proteins. The proteins were also matched against the database of Kyoto Encyclopedia of Genes and Genomes (KEGG). For validation, Western blot was used to analyze the selected proteins.

Results: A total of 509 proteins and 411 proteins were identified in TMT1 and TMT2, respectively. 249 proteins were both identified in two technical replicates. GO analysis and KEGG analysis revealed immunization and coagulation were predominantly involved. Among the differential protein, the overexcretion of alpha-1-antitrypsin (A1AT) and afamin (AFM) were validated by Western blot analysis.

Conclusions: Our data showed the important role of immunologic mechanism in the development of PMN, and the value of urinary A1AT and AFM in biomarker discovery of patients with PMN. The discovery of the overexcretion of A1AT and AFM in the urine can help to further elucidate pathogenetic mechanisms involved in PMN.
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http://dx.doi.org/10.1186/s12014-018-9183-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801694PMC
February 2018

Assessment of Glycated Albumin as a Useful Indicator for Renal Dysfunction in Diabetic and Nondiabetic Population.

Clin Lab 2017 Jul;63(7):1129-1137

Background: Glycated albumin (GA) reflects serum glucose of the preceding 2 - 3 weeks and plays an important role in diabetes mellitus (DM). This study aimed at investigating whether GA can assess renal dysfunction in population.

Methods: 3818 individuals attending physical examination were enrolled in this cross-sectional study and divided into five groups: healthy controls, impaired fasting glucose, DM without renal complications, DM with albuminuria, and nondiabetic chronic kidney disease patients. All analyses were conducted using the subjects with both fasting venous blood and morning urine samples.

Results: Among all groups, mean GA, hemoglobin A1c, fasting plasma glucose, and serum creatinine were the highest and estimated glomerular filtration rate (eGFR) was the lowest in DM with albuminuria group. When eGFR was 90 - 105 mL/minute/1.73 m2 or mildly decreased to 60 - 90 mL/minute/1.73 m2, GA increased significantly with elevating albumin-to-creatinine ratio (ACR) from 0 - 10 mg/g to 10 - 30 mg/g to > 30 mg/g (p < 0.001 and p < 0.001). GA increased further when eGFR decreased moderately to severely as a result of renal function continuing to deteriorate (eGFR ≤ 60 mL/minute/1.73 m2).When ACR ≤ 30 mg/g and eGFR ≤ 60 mL/minute/ 1.73 m2, more than 50% subjects were DM patients and had significantly higher GA levels than other subjects with eGFR > 105 mL/minute/1.73 m2. After adjusting demographics, every 5% rise of GA levels showed a 1.778fold increased risk in all subjects (adjusted odds ratio [OR], 1.778; 95% confidence interval [CI], 1.373 - 2.302; p < 0.001) and 1.737-fold risk in DM subjects (adjusted OR, 1.737; 95% CI, 1.221 - 2.471; p = 0.002) for occurrence of ACR > 30mg/g in contrast to ACR ≤ 30 mg/g. Compared to eGFR > 90 mL/minute/1.73 m2, 5% rise of GA levels showed a 1.482-fold risk for eGFR 60 - 90 mL/minute/1.73 m2 (adjusted OR, 1.482; 95% CI, 1.112 - 1.975; p = 0.007) and a 1.996-fold risk for eGFR ≤ 60 mL/minute/1.73 m2 (adjusted OR, 1.996; 95% CI, 1.366 - 2.916; p < 0.001).

Conclusions: Increased GA serves as a risk marker for renal dysfunction. GA combined with eGFR and ACR can reflect renal function changes in population.
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http://dx.doi.org/10.7754/Clin.Lab.2017.161224DOI Listing
July 2017

New thermodynamic entropy calculation based approach towards quantifying the impact of eutrophication on water environment.

Sci Total Environ 2017 Dec 14;603-604:86-93. Epub 2017 Jun 14.

School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology, Sydney, Broadway, NSW 2007, Australia. Electronic address:

Although the eutrophication phenomenon has been studied for a long time, there are still no quantifiable parameters available for a comprehensive assessment of its impacts on the water environment. As contamination alters the thermodynamic equilibrium of a water system to a state of imbalance, a novel method was proposed, in this study, for its quantitative evaluation. Based on thermodynamic analyses of the algal growth process, the proposed method targeted, both theoretically and experimentally, the typical algae species encountered in the water environment. By calculating the molar enthalpy of algae biomass production, the heat energy dissipated in the photosynthetic process was firstly evaluated. The associated entropy production (ΔS) in the aquatic system could be then obtained. For six algae strains of distinct molecular formulae, the heat energy consumed for the production of a unit algal biomass was found to proportionate to the mass of nitrogen (N) or phosphorus (P) uptake through photosynthesis. A proportionality relationship between ΔS and the algal biomass with a coefficient circa 44kJ/g was obtained. By the principle of energy conservation, the heat energy consumed in the process of algae biomass production is stored in the algal biomass. Furthermore, by measuring the heat of combustion of mature algae of Microcystis flos-aquae, Anabaena flos-aquae, and Chlorella vulgaris, the proportionality relationships between the heat energy and the N and P contents were validated experimentally at 90% and 85% confidence levels, respectively. As the discharge of excess N and P from domestic wastewater treatment plants is usually the main cause of eutrophication, the proposed impact assessment approach estimates that for a receiving water body, the ΔS due to a unit mass of N and P discharge is 268.9kJ/K and 1870.1kJ/K, respectively. Consequently, P discharge control would be more important for environmental water protection.
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http://dx.doi.org/10.1016/j.scitotenv.2017.06.069DOI Listing
December 2017

Serum anti-PLA2R antibody and glomerular PLA2R deposition in Chinese patients with membranous nephropathy: A cross-sectional study.

Medicine (Baltimore) 2017 Jun;96(24):e7218

Department of Clinical Laboratory, Peking University First Hospital, Beijing Department of Clinical Laboratory, Tianjin Nankai Hospital, Tianjin, The People's Republic of China.

M-type phospholipase A2 receptor (PLA2R) is the major target antigen in primary membranous nephropathy (PMN). Previous studies have evaluated the diagnostic value of serum anti-PLA2R antibody. However, the correlation of serum anti-PLA2R antibody and glomerular PLA2R deposition, and their association with clinical characteristics need to be further evaluated.A total of 136 patients were involved as inception group because serum anti-PLA2R antibody and glomerular PLA2R antigen were simultaneously measured. We examined serum anti-PLA2R antibody by ELISA and glomerular PLA2R deposition by immunofluorescence assay.Positive serum anti-PLA2R antibody and glomerular PLA2R deposition were seen in 58.8% (80/136) and 95.6% (130/136) patients, respectively (P < .001). Proteinuria, serum total protein, serum albumin, serum creatinine, and estimated glomerular filtration rate (eGFR) had significant differences between patients with serum anti-PLA2R antibody and those without. Serum anti-PLA2R antibody levels were correlated with serum albumin, serum creatinine, eGFR, and proteinuria. Glomerular PLA2R deposition intensities were weakly correlated with proteinuria. Unexpectedly, there was a positive correlation rather than a negative correlation between glomerular PLA2R deposition intensity and eGFR.In conclusion, serum anti-PLA2R antibody is more closely correlated with disease activity and renal function than glomerular PLA2R deposition.
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http://dx.doi.org/10.1097/MD.0000000000007218DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5478356PMC
June 2017