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Dai H, Shan Z, Shi L, Duan Y, An Y, He C, Lyu Y, Zhao Y, Wang M, Du Y, Xie J, Yang Y, Zhao B. Mulberry leaf polysaccharides ameliorate glucose and lipid metabolism disorders via the gut microbiota-bile acids metabolic pathway. Int J Biol Macromol 2024; 282:136876. [PMID: 39490871 DOI: 10.1016/j.ijbiomac.2024.136876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2024] [Revised: 10/17/2024] [Accepted: 10/22/2024] [Indexed: 11/05/2024]
Abstract
Mulberry leaf polysaccharides (MLP) are integral components of Mulberry leaves that confer hypoglycemic and hypolipidemic properties. This study investigated the efficacy of MLP in treating Type 2 Diabetes Mellitus (T2DM) and the underlying mechanisms related to gut microbiota-bile acids metabolism in T2DM rats. The findings revealed that MLP apparently reduced fasting blood glucose and lipid levels, ameliorated disorders in glucose and lipid metabolism, and mitigated insulin resistance. MLP enhanced the abundance of Prevotella, Ruminococcus, and Lactobacillus, thereby rectifying the gut microbiota dysbiosis in rats, which effectively restored gut microbiota homeostasis and composition. Furthermore, the data demonstrated that MLP modulated bile acid metabolism, as evidenced by reduced serum cholesterol levels, enhanced mRNA expression of hepatic cholesterol 7α- hydroxylase (Cyp7a1) and cholesterol 12α- hydroxylase (Cyp8b1), and ileal G protein-coupled bile acid receptor (Tgr5), while suppressing hepatic and ileal farnesoid X receptor (Fxr) mRNA expression in T2DM rats. Additionally, MLP upregulated the protein expression of hepatic CYP7A1 and CYP8B1, and ileal TGR5, while inhibiting FXR protein levels in the liver and ileum of T2DM rats. These results suggest that MLP can rectify disorders in glucose and lipid metabolism via the gut microbiota-bile acids metabolic pathway.
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Affiliation(s)
- Hongyu Dai
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China; Operations and Management Department, Ya'an People's Hospital, Ya'an 625099, China
| | - Ziyi Shan
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Lu Shi
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China; Central Laboratories, Qingdao Municipal Hospital, Qingdao 266011, China
| | - Yuhui Duan
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Yongcheng An
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Changhao He
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Yinglan Lyu
- College of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Yige Zhao
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Menglu Wang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Yuhang Du
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Jiamei Xie
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Yang Yang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Baosheng Zhao
- Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China.
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Dicu-Andreescu I, Garneata L, Ciurea OA, Dicu-Andreescu IG, Ungureanu EA, Vlad DV, Visan AC, Ungureanu VG, Vlad VV, Vasioiu PC, Ciutacu EM, Neicu M, Penescu M, Verzan C, Capusa C. Are the Hematological Parameters Useful in Differentiating Acute Pyelonephritis from Cystitis in Patients with Chronic Kidney Disease? MAEDICA 2024; 19:511-518. [PMID: 39553351 PMCID: PMC11565154 DOI: 10.26574/maedica.2024.19.3.511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2024]
Abstract
BACKGROUND AND OBJECTIVES The importance of hematological parameters has started to be explored with increased interest in many fields lately, with different studies finding an association between those parameters and inflammatory status, atherosclerosis, comorbidities, malnutrition, neoplasia and even a faster progression of chronic kidney disease (CKD). On the other hand, CKD itself presents as an inflammatory condition, in which a lot of pathways are modified and the response to an infectious agent could be less than expected. Regarding the latter aspect, in this study we aim to explore the differences between the hematologic response during a lower versus upper urinary tract infection in patients with CKD. MATERIALS AND METHODS We analyzed 70 patients with chronic kidney disease and either cystitis or pyelonephritis considering the hematologic parameters, the classical inflammatory ones as well as the etiology of CKD. RESULTS Neutrophils, neutrophils/lymphocytes ratio (NLR), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) and fibrinogen were higher in patients with pyelonephritis (PNA), while albumin was significantly lower. In a binary logistic regression model that explained 80.2% of the variability of PNA diagnosis and correctly predicted it in 92.9% of cases, NLR, CRP and fibrinogen were the independent predictors. CONCLUSIONS Hematologic parameters can serve not only as an indicator of the inflammatory status, but also as a laboratory biomarker for PNA in patients with CKD.
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Affiliation(s)
- Ioana Dicu-Andreescu
- Faculty of Medicine, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Liliana Garneata
- Faculty of Medicine, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
- Nephrology Department, "Dr. Carol Davila" Teaching Hospital of Nephrology, Bucharest, Romania
| | - Otilia-Andreea Ciurea
- Faculty of Medicine, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
- Nephrology Department, "Dr. Carol Davila" Teaching Hospital of Nephrology, Bucharest, Romania
| | | | | | - Denis-Valentin Vlad
- Faculty of Medicine, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | | | | | - Violeta-Valentina Vlad
- Faculty of Medicine, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | | | - Elis-Mihaela Ciutacu
- Nephrology Department, "Dr. Carol Davila" Teaching Hospital of Nephrology, Bucharest, Romania
| | - Mihaela Neicu
- Nephrology Department, "Dr. Carol Davila" Teaching Hospital of Nephrology, Bucharest, Romania
| | - Mircea Penescu
- Faculty of Medicine, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
- Nephrology Department, "Dr. Carol Davila" Teaching Hospital of Nephrology, Bucharest, Romania
| | - Constantin Verzan
- Faculty of Medicine, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
- Nephrology Department, "Dr. Carol Davila" Teaching Hospital of Nephrology, Bucharest, Romania
| | - Cristina Capusa
- Faculty of Medicine, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
- Nephrology Department, "Dr. Carol Davila" Teaching Hospital of Nephrology, Bucharest, Romania
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Haley E, Luke N, Mathur M, Festa RA, Wang J, Jiang Y, Anderson LA, Baunoch D. The Prevalence and Association of Different Uropathogens Detected by M-PCR with Infection-Associated Urine Biomarkers in Urinary Tract Infections. Res Rep Urol 2024; 16:19-29. [PMID: 38221993 PMCID: PMC10787514 DOI: 10.2147/rru.s443361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 12/16/2023] [Indexed: 01/16/2024] Open
Abstract
Background Many emerging uropathogens are currently identified by multiplex polymerase chain reaction (M-PCR) in suspected UTI cases. Standard urine culture (SUC) has significantly lower detection rates, raising questions about whether these organisms are associated with UTIs and truly cause inflammation. Objective To determine if microbes detected by M-PCR were likely causative of UTI by measuring inflammatory biomarkers in the urine of symptomatic patients. Design Setting and Participants Midstream voided urine was collected from subjects ≥60 years presenting to urology clinics with symptoms of UTI (n = 1132) between 01/2023 and 05/2023. Microbe detection was by M-PCR and inflammation-associated biomarker (neutrophil gelatinase-associated lipocalin, interleukin 8, and interleukin 1β) was by enzyme-linked immunosorbent assay. Biomarker positivity was measured against individual and groups of organisms, E. coli and non-E. coli cases, emerging uropathogens, monomicrobial and polymicrobial cases. Outcome Measurements and Statistical Analysis Distributions were compared using 2-sample Wilcoxon Rank Sum test with 2-tailed p-values < 0.05 considered statistically significant. Results and Limitations M-PCR was positive in 823 (72.7%) specimens with 28 of 30 (93%) microorganisms/groups detected. Twenty-six of twenty-eight detected microorganisms/groups (93%) had ≥2 biomarkers positive in >66% of cases. Both non-E. coli cases and E. coli cases had significant biomarker positivity (p < 0.05). Limitations were that a few organisms had low prevalence making inferences about their individual significance difficult. Conclusion The majority of microorganisms identified by M-PCR were associated with active inflammation measured by biomarker positivity, indicating they are likely causative of UTIs in symptomatic patients. This includes emerging uropathogens frequently not detected by standard urine culture.
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Affiliation(s)
- Emery Haley
- Department of Clinical Research, Pathnostics, Irvine, CA, USA
| | - Natalie Luke
- Department of Clinical Research, Pathnostics, Irvine, CA, USA
| | - Mohit Mathur
- Department of Medical Affairs, Pathnostics, Irvine, CA, USA
| | - Richard A Festa
- Department of Research and Development, Pathnostics, Irvine, CA, USA
| | - Jimin Wang
- Department of Statistical Analysis, Stat4Ward, Pittsburgh, PA, USA
| | - Yan Jiang
- Department of Statistical Analysis, Stat4Ward, Pittsburgh, PA, USA
| | - Lori A Anderson
- L.Anderson Diagnostic Market Access Consulting, San Diego, CA, USA
| | - David Baunoch
- Department of Research and Development, Pathnostics, Irvine, CA, USA
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Xiong Y, Liu YM, Hu JQ, Zhu BQ, Wei YK, Yang Y, Wu XW, Long EW. A personalized prediction model for urinary tract infections in type 2 diabetes mellitus using machine learning. Front Pharmacol 2024; 14:1259596. [PMID: 38269284 PMCID: PMC10806526 DOI: 10.3389/fphar.2023.1259596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 12/12/2023] [Indexed: 01/26/2024] Open
Abstract
Patients with type 2 diabetes mellitus (T2DM) are at higher risk for urinary tract infections (UTIs), which greatly impacts their quality of life. Developing a risk prediction model to identify high-risk patients for UTIs in those with T2DM and assisting clinical decision-making can help reduce the incidence of UTIs in T2DM patients. To construct the predictive model, potential relevant variables were first selected from the reference literature, and then data was extracted from the Hospital Information System (HIS) of the Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital for analysis. The data set was split into a training set and a test set in an 8:2 ratio. To handle the data and establish risk warning models, four imputation methods, four balancing methods, three feature screening methods, and eighteen machine learning algorithms were employed. A 10-fold cross-validation technique was applied to internally validate the training set, while the bootstrap method was used for external validation in the test set. The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to evaluate the performance of the models. The contributions of features were interpreted using the SHapley Additive ExPlanation (SHAP) approach. And a web-based prediction platform for UTIs in T2DM was constructed by Flask framework. Finally, 106 variables were identified for analysis from a total of 119 literature sources, and 1340 patients were included in the study. After comprehensive data preprocessing, a total of 48 datasets were generated, and 864 risk warning models were constructed based on various balancing methods, feature selection techniques, and a range of machine learning algorithms. The receiver operating characteristic (ROC) curves were used to assess the performances of these models, and the best model achieved an impressive AUC of 0.9789 upon external validation. Notably, the most critical factors contributing to UTIs in T2DM patients were found to be UTIs-related inflammatory markers, medication use, mainly SGLT2 inhibitors, severity of comorbidities, blood routine indicators, as well as other factors such as length of hospital stay and estimated glomerular filtration rate (eGFR). Furthermore, the SHAP method was utilized to interpret the contribution of each feature to the model. And based on the optimal predictive model a user-friendly prediction platform for UTIs in T2DM was built to assist clinicians in making clinical decisions. The machine learning model-based prediction system developed in this study exhibited favorable predictive ability and promising clinical utility. The web-based prediction platform, combined with the professional judgment of clinicians, can assist to make better clinical decisions.
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Affiliation(s)
- Yu Xiong
- Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yu-Meng Liu
- Department of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China
| | - Jia-Qiang Hu
- Personalized Drug Therapy Key Laboratory of Sichuan Province, Department of Pharmacy, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Bao-Qiang Zhu
- Personalized Drug Therapy Key Laboratory of Sichuan Province, Department of Pharmacy, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
- School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China
| | - Yuan-Kui Wei
- Personalized Drug Therapy Key Laboratory of Sichuan Province, Department of Pharmacy, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Yan Yang
- Department of Endocrinology and Metabolism, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
- Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, Sichuan, China
| | - Xing-Wei Wu
- Personalized Drug Therapy Key Laboratory of Sichuan Province, Department of Pharmacy, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - En-Wu Long
- Personalized Drug Therapy Key Laboratory of Sichuan Province, Department of Pharmacy, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
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Chedid P, Sokhn ES. Prevalence of type 2 diabetes (T2D) in Lebanon: association with inflammatory and infectious clinical markers. BMC Public Health 2023; 23:2523. [PMID: 38104079 PMCID: PMC10725583 DOI: 10.1186/s12889-023-17328-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 11/24/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND Diabetes is a growing health concern in the Middle East, particularly in countries with high rates of obesity and unhealthy lifestyles. Therefore, this study aimed to determine the prevalence of type 2 diabetes (T2D) in Lebanon and its association with clinical markers of inflammation and infection. METHODS This cross-sectional study examined retrospectively the medical laboratory record of 4093 patients from all Lebanese regions. Prevalence of T2D and its association with age, gender, calcium, vitamin D (VitD), neutrophils-to-lymphocytes ratio (NLR), and C-reactive protein (CRP) were determined. The prevalence of infection in a subpopulation of 712 patients tested from blood, body fluid, sputum, swab, tissue, and urine samples and its etiology was also assessed. RESULTS Overall, 17% (n = 690) of our participants had T2D, and the mean HbA1c was 5.9% ± 1.2. Age, gender, triglycerides, NLR, and calcemia were significantly associated with T2D. The prevalence of infections in a subgroup of 712 patients was 11.1% (n = 79). Urinary tract infections (UTIs) caused by Escherichia coli (E. coli) were the most common cause of infection, with the highest prevalence in the pre-diabetic group. Serum CRP level was significantly higher in the diabetic group than the pre-diabetic and control groups. Diabetic patients also presented a significantly higher percentage of NLR > 3 compared to the pre-diabetic and control groups. CONCLUSION The prevalence of T2D is increasing in the Lebanese population compared to prior reports. These results should be considered to guide effective public health preventive strategies.
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Affiliation(s)
- Pia Chedid
- Molecular Testing Laboratory, Medical Laboratory Department, Faculty of Health Sciences, Beirut Arab University, Beirut, Lebanon
| | - Elie Salem Sokhn
- Molecular Testing Laboratory, Medical Laboratory Department, Faculty of Health Sciences, Beirut Arab University, Beirut, Lebanon.
- Laboratory Department, Lebanese Hospital-Geitaoui University Medical Center, Beirut, Lebanon.
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Guo M, Gao B, Su J, Zeng Y, Cui Z, Liu H, Guo X, Zhu Y, Wei B, Zhao Y, Qin J, Lu X, Li Q. Phenotypic and genetic characterization of hypervirulent Klebsiella pneumoniae in patients with liver abscess and ventilator-associated pneumonia. BMC Microbiol 2023; 23:338. [PMID: 37957579 PMCID: PMC10644596 DOI: 10.1186/s12866-023-03022-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 09/14/2023] [Indexed: 11/15/2023] Open
Abstract
Ventilator-associated pneumonia (VAP) and pyogenic liver abscess (PLA) due to Klebsiella pneumoniae infection can trigger life-threatening malignant consequences, however, there are few studies on the strain-associated clinical pathogenic mechanisms between VAP and PLA. A total of 266 patients consist of 129 VAP and 137 PLA were included for analysis in this study. We conducted a comprehensive survey for the two groups of K. pneumoniae isolates, including phenotypic experiments, clinical epidemiology, genomic analysis, and instrumental analysis, i.e., to obtain the genomic differential profile of K. pneumoniae strains responsible for two distinct infection outcomes. We found that PLA group had a propensity for specific underlying diseases, especially diabetes and cholelithiasis. The resistance level of VAP was significantly higher than that of PLA (78.57% vs. 36%, P < 0.001), while the virulence results were opposite. There were also some differences in key signaling pathways of biochemical processes between the two groups. The combination of iucA, rmpA, hypermucoviscous phenotype, and ST23 presented in K. pneumoniae infection is more important and highly prudent for timely treatment. The present study may contribute a benchmark for the K. pneumoniae clinical screening, epidemiological surveillance, and effective therapeutic strategies.
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Affiliation(s)
- Mingquan Guo
- Department of Laboratory Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
- Shanghai Institute of Phage, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Bo Gao
- Department of Critical Care Medicine, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
| | - Jun Su
- Department of Laboratory Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Yigang Zeng
- Department of Laboratory Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Zelin Cui
- Department of Laboratory Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haodong Liu
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - XiaoKui Guo
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yongzhang Zhu
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Beiwen Wei
- Department of Laboratory Medicine, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanan Zhao
- Department of Laboratory Medicine, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Juanxiu Qin
- Department of Laboratory Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Xiaoye Lu
- Department of Emergency Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Qingtian Li
- Department of Laboratory Medicine, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Parnell LKS, Luke N, Mathur M, Festa RA, Haley E, Wang J, Jiang Y, Anderson L, Baunoch D. Elevated UTI Biomarkers in Symptomatic Patients with Urine Microbial Densities of 10,000 CFU/mL Indicate a Lower Threshold for Diagnosing UTIs. Diagnostics (Basel) 2023; 13:2688. [PMID: 37627948 PMCID: PMC10453813 DOI: 10.3390/diagnostics13162688] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/20/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023] Open
Abstract
The literature lacks consensus on the minimum microbial density required for diagnosing urinary tract infections (UTIs). This study categorized the microbial densities of urine specimens from symptomatic UTI patients aged ≥ 60 years and correlated them with detected levels of the immune response biomarkers neutrophil gelatinase-associated lipocalin (NGAL), interleukin-8 (IL-8), and interleukin-1-beta (IL-1β). The objective was to identify the microbial densities associated with significant elevation of these biomarkers in order to determine an optimal threshold for diagnosing symptomatic UTIs. Biobanked midstream voided urine samples were analyzed for microbial identification and quantification using standard urine culture (SUC) and multiplex-polymerase chain reaction (M-PCR) testing, while NGAL, IL-8, and IL-1β levels were measured via enzyme-linked immunosorbent assay (ELISA). NGAL, IL-8, and IL-1β levels were all significantly elevated at microbial densities ≥ 10,000 cells/mL when measured via M-PCR (p < 0.0069) or equivalent colony-forming units (CFUs)/mL via SUC (p < 0.0104) compared to samples with no detectable microbes. With both PCR and SUC, a consensus of two or more elevated biomarkers correlated well with microbial densities > 10,000 cells/mL or CFU/mL, respectively. The association between ≥10,000 cells and CFU per mL with elevated biomarkers in symptomatic patients suggests that this lower threshold may be more suitable than 100,000 CFU/mL for diagnosing UTIs.
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Affiliation(s)
- Laura K. S. Parnell
- Department of Scientific Writing, Precision Consulting, 6522 Harbor Mist, Missouri City, TX 77459, USA;
| | - Natalie Luke
- Department of Clinical Research, Pathnostics, 15545 Sand Canyon Suite 100, Irvine, CA 92618, USA; (N.L.); (E.H.)
| | - Mohit Mathur
- Department of Medical Affairs, Pathnostics, 15545 Sand Canyon Suite 100, Irvine, CA 92618, USA;
| | - Richard A. Festa
- Department of Research and Development, Pathnostics, 15545 Sand Canyon Suite 100, Irvine, CA 92618, USA;
| | - Emery Haley
- Department of Clinical Research, Pathnostics, 15545 Sand Canyon Suite 100, Irvine, CA 92618, USA; (N.L.); (E.H.)
| | - Jimin Wang
- Department of Statistical Analysis, Stat4Ward, 2 Edgemoor Lane, Pittsburgh, PA 15238, USA; (J.W.); (Y.J.)
| | - Yan Jiang
- Department of Statistical Analysis, Stat4Ward, 2 Edgemoor Lane, Pittsburgh, PA 15238, USA; (J.W.); (Y.J.)
| | - Lori Anderson
- Department of Diagnostic Market Access, Pathnostics, 15545 Sand Canyon Suite 100, Irvine, CA 92618, USA;
| | - David Baunoch
- Department of Research and Development, Pathnostics, 15545 Sand Canyon Suite 100, Irvine, CA 92618, USA;
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Chancellor M, Lamb L, Ward E, Bartolone S, Carabulea A, Sharma P, Janicki J, Smith C, Laudano M, Abraham N, M. Zwaans B. Comparing concentration of urinary inflammatory cytokines in interstitial cystitis, overactive bladder, urinary tract infection, and bladder cancer. UROLOGICAL SCIENCE 2022. [DOI: 10.4103/uros.uros_26_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
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Horváth J, Wullt B, Naber KG, Köves B. Biomarkers in urinary tract infections - which ones are suitable for diagnostics and follow-up? GMS INFECTIOUS DISEASES 2020; 8:Doc24. [PMID: 33299741 PMCID: PMC7705555 DOI: 10.3205/id000068] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction: Urinary tract infections (UTIs) are one of the most common infections worldwide. Under special circumstances, clinicians must rely on laboratory findings, which might have a weak predicting value, misguiding the practitioners and leading to incorrect diagnosis and overuse of antibiotics. Therefore, there is an urgent need for reliable biomarkers in UTIs. Methods: We performed a literature search for biomarkers used in UTIs from January 1999 until May 2020. We used "urinary tract infection" and "biomarker" as the main key words in the PubMed, Medline and Cochrane databases. After peer review, we excluded the duplicates and identified the suitable articles, from which we collected the data and divided the available biomarkers into 5 groups: i) conventional markers; ii) promising, thoroughly studied biomarkers; iii) promising biomarkers that need further studies; iv) biomarkers of unknown significance; v) controversial, not useful markers. Results: We found 131 articles, mostly from the paediatric population. Neutrophil gelatinase-associated lipocalin (NGAL) and interleukins (IL) have a leading role in diagnosing and differentiating UTIs based on a lot of observational, comparative trials. Heparin Binding Protein (HBP), Lactoferrin (LF), Heat-Shock Protein-70 (HSP-70), Human Defensin-5 (HD-5), Lipopolysaccharide Binding Protein (LBP) and mass spectrometry studies are promising, but confirming data are lacking. The measurable components of the innate immune system and local host cell response could be appropriate biomarkers, but their significance is currently unknown. Conclusions: Conventional biomarkers for UTIs have low specificity. The use of urinary NGAL and interleukins could improve the sensitivity and specificity of laboratory diagnosis of UTIs.
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Affiliation(s)
- József Horváth
- BKMK SZTE ÁOK Okt. Kh. Urológiai Osztálya, Kecskemét, Hungary
| | - Björn Wullt
- Division of Microbiology, Immunology and Glycobiology, Lund University, Lund, Sweden
| | - Kurt G. Naber
- Department of Urology, Technical University of Munich, Munich, Germany
| | - Béla Köves
- Jahn Ferenc Dél-pesti Kórház és Rendelőintézet, Budapest, Hungary
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