Research progress of microbes of urinary tract and urinary tract infection
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摘要: 人体尿路中存在着常驻微生物群落,但临床对于泌尿道微生物组与宿主的关系和基本生物学原理尚未阐明。详细了解尿路感染(UTI)的发病机制,是临床开发有效治疗UTI的新型抗菌药物的关键。通过对代谢组学和基因表达的研究,人们开始了解细菌毒力在整个感染周期中的动态调控情况,从而能准确地确定细菌毒力的决定因素。目前,关于人体微生物群落的研究已取得一定进展,本综述有望为UTI新型疗法的开发提供参考,从而改善患者的生活质量。Abstract: Resident microbial communities exist in urinary tract of humanity. However, the relationship between the urological microbiome and the host as well as the basic biological principles have not been elucidated in clinical practice. A detailed understanding of the pathogenesis of urinary tract infection(UTI)is the key to the clinical development of novel antimicrobial agents for the effective treatment of UTI. Through the study of metabolomics and gene expression, people began to understand the dynamic regulation of bacterial virulence throughout the infectious cycle, so as to accurately confirm the determinant factors of bacterial virulence. At present, some progress has been made in the study of human microbiome, and the review expected to provide references for the development of new UTI therapies, thus improving the quality of life of patients.
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Keywords:
- urinary tract /
- microbes /
- urinary tract infection /
- antibiotics /
- treatment strategies
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卒中相关性肺炎(SAP)是急性脑梗死(ACI)患者最常见的并发症之一，发病率为7%~22%(老年患者发病率更高)，与ACI患者住院时间延长、病死率增高密切相关[1-2]。有研究[3-4]对ACI患者进行预防性抗感染治疗，以期降低SAP发病率，但结果并不如意。研究[5]证实，年龄大、卒中程度严重、合并糖尿病、合并房颤等是SAP的高危因素，但这些因素大多基于临床表现，而ACI患者的临床特征往往并不典型。此外，床旁胸片和痰培养的诊断敏感性较低[6], 因此亟需寻找更客观易得的预测指标。血清胆碱酯酶(SChE)分为乙酰胆碱酯酶(AChE)和丁酰胆碱酯酶(BuChE), 其中AChE主要分布于脑部和外周的神经组织，可水解乙酰胆碱，是主要的生理活性物质，而BuChE主要分布于肝脏、血清中，对乙酰胆碱的活性较低，主要参与有机磷中毒过程。AChE已被证实在脓毒症患者血清中显著下降，且与脓毒症严重程度相关[7]。中性粒细胞与淋巴细胞比值(NLR)作为一种感染预测指标，相较传统炎症标志物如白细胞计数、中性粒细胞计数、C反应蛋白(CRP)等有更高的预测价值[8]。相关研究[9]显示, NLR对肺炎具有良好的预测能力，且与抗生素使用剂量反映指标呈正相关。目前，AChE和NLR对SAP的预测价值尚不明确。本研究探讨外周血中AChE、NLR对ACI患者发生SAP的预测价值，现报告如下。
1. 资料与方法
1.1 一般资料
回顾性选取2018年1月—2021年1月上海市第五人民医院收治的202例ACI患者作为研究对象，男105例、女97例，年龄(80.00±8.24)岁。纳入标准: ①发病24 h内入院者; ②符合ACI诊断标准者[10]。排除标准: ①筛查前3个月内有严重创伤或急性心肌梗死史、手术史等患者; ②合并未治愈的恶性肿瘤或血液系统疾病者; ③活动性感染性疾病、肝硬化失代偿、慢性肾脏/心脏功能不全、慢性呼吸衰竭等患者; ④使用免疫调节剂治疗者(因AChE和NLR均受系统性炎症影响); ⑤临床资料不全及中途放弃治疗者; ⑥入院24 h内死亡者。将入院48 h后发生SAP的105例患者纳入SAP组，未发生SAP的97例患者纳入对照组。本研究为回顾性研究，未对患者进行样本采集及药物临床试验，且经上海市第五人民医院伦理委员会审核批准。
1.2 研究方法
记录所有患者的一般资料(含性别、年龄和既往糖尿病、高血压、心房颤动病史等); 入院24 h内采集所有患者静脉血检测血常规指标和AChE、CRP等指标水平，并记录美国国立卫生研究院卒中量表(NIHSS)评分; 患者住院期间均接受规范治疗，记录患者住院时间和转归结果。采用单因素分析比较2组间性别、年龄、既往病史、NLR、AChE、CRP、NIHSS评分、住院时间和病死率差异，然后对差异有统计学意义的自变量进行多因素Logistic回归分析，探讨ACI患者发生SAP的危险因素。应用受试者工作特征(ROC)曲线分析多因素Logistic回归分析中的阳性自变量对SAP的预测价值，并分析阳性自变量与ACI严重程度和转归的关系。
1.3 统计学分析
采用SPSS 24.0统计学软件分析数据，正态分布的计量资料以(x±s)表示，偏态分布的计量资料以[M(P25, P75)]表示, 2组数据比较采用t检验(正态分布)或Mann-Whitney U检验(偏态分布)。计数资料以[n(%)]表示, 2组比较采用χ2检验。P＜0.05为差异有统计学意义。
2. 结果
2.1 影响ACI患者发生SAP的单因素分析
SAP组年龄、合并心房颤动者占比、白细胞计数、中性粒细胞计数、NLR、CRP水平、NIHSS评分和病死率均高于对照组，住院时间长于对照组，淋巴细胞计数、AChE水平低于对照组，差异有统计学意义(P＜0.05或P＜0.01); 2组性别、血小板计数和合并糖尿病、高血压病情况比较，差异无统计学意义(P>0.05)。见表 1。
表 1 2组患者一般资料和实验室指标等比较(x±s)[n(%)][M(P25, P75)]指标 SAP组(n=105) 对照组(n=97) t/χ2/Z P 年龄/岁 82.87±7.15 76.89±8.24 5.49 ＜0.01 性别 男 53(50.48) 52(53.61) 0.20 0.66 女 52(49.52) 45(46.39) 既往史 糖尿病 40(38.10) 44(45.36) 1.10 0.30 高血压病 73(69.52) 74(76.29) 1.17 0.29 心房颤动 50(47.62) 10(10.31) 33.61 ＜0.01 实验室指标 白细胞/(×109/L) 9.45±3.03 6.39±1.50 9.21 ＜0.01 中性粒细胞/(×109/L) 7.62±2.90 4.08±1.25 11.44 ＜0.01 淋巴细胞/(×109/L) 1.12±0.62 1.67±0.57 -6.54 ＜0.01 NLR 8.45±5.94 2.69±1.16 9.89 ＜0.01 血小板/(×109/L) 195.68±80.36 201.27±56.93 -0.57 0.57 AChE/(U/L) 4 779.03±1 229.73 7 116.76±1 260.60 -13.34 ＜0.01 CRP/(mg/L) 23.00(14.50, 43.00) 2.00(1.00, 3.00) -12.02 ＜0.01 NIHSS评分/分 12.01±5.46 3.67±2.54 14.08 ＜0.01 住院时间/d 16.63±5.92 10.22±2.58 10.11 ＜0.01 死亡 13(12.38) 1(1.03) 10.07 ＜0.01 SAP: 卒中相关性肺炎; NLR: 中性粒细胞与淋巴细胞比值; AChE: 乙酰胆碱酯酶; CRP: C反应蛋白; NIHSS: 美国国立卫生研究院卒中量表。 2.2 影响ACI患者发生SAP的多因素分析
白细胞、中性粒细胞、淋巴细胞与NLR存在联系，本研究选择其他单因素分析中差异有统计学意义的指标(年龄、心房颤动、NLR、CRP、AChE、NIHSS评分)作为自变量(各变量赋值情况见表 2)进行多因素Logistic回归分析，其中CRP存在明显离群点，故予以剔除。多因素Logistic回归分析结果显示, AChE、NLR均是SAP的独立影响因素(P＜0.01), 见表 3。
表 2 变量赋值说明变量 赋值 年龄 >80岁=1, ≤80岁=0 心房颤动 有=1, 无=0 NLR 实际值 C反应蛋白 >10 mg/L=1, ≤10 mg/L=0 AChE 实际值 NIHSS评分 >5分=1, ≤5分=0 NLR: 中性粒细胞与淋巴细胞比值; AChE: 乙酰胆碱酯酶; NIHSS: 美国国立卫生研究院卒中量表。 表 3 ACI患者发生SAP危险因素的多因素Logistic回归分析变量 β SE Wald HR 95%CI P 年龄 0.30 0.69 0.20 1.36 0.36~5.14 0.66 心房颤动 1.45 0.78 3.46 4.24 0.93~19.45 0.06 NLR 1.13 0.25 19.93 3.10 1.89~5.10 ＜0.01 AchE -0.01 0.01 18.84 0.99 0.98~1.00 ＜0.01 NIHSS评分 0.94 0.68 1.91 2.55 0.68~9.57 0.17 ACI: 急性脑梗死; SAP: 卒中相关性肺炎; NLR: 中性粒细胞与淋巴细胞比值; AChE: 乙酰胆碱酯酶, NIHSS: 美国国立卫生研究院卒中量表; SE: 标准误; HR: 风险比; 95%CI: 95%置信区间。 2.3 AChE和NLR对ACI患者发生SAP的预测价值
AChE[曲线下面积(AUC)为0.92, 截断值为5 994.00 U/L]、NLR(AUC为0.93, 截断值为4.43)对ACI患者发生SAP均有较高的预测价值，且AChE联合NLR的预测价值更高(AUC为0.98), 见表 4、图 1。
表 4 AChE和NLR对ACI患者发生SAP的预测价值指标 截断值 AUC 95%CI 敏感度/% 特异度/% AChE 5 994.00 0.92 0.89~0.96 88.60 87.60 NLR 4.43 0.93 0.90~0.97 82.90 91.80 AChE联合NLR - 0.98 0.97~0.99 - - AChE: 乙酰胆碱酯酶; NLR: 中性粒细胞与淋巴细胞比值; ACI: 急性脑梗死; SAP: 卒中相关性肺炎; AUC: 曲线下面积; 95%CI: 95%置信区间。 2.4 不同AChE、NLR水平患者病情严重程度和转归结局比较
根据AChE预测SAP发生的截断值5 994.00 U/L, 将患者分为低AChE组(AChE≤5 994.00 U/L)和高AChE组(AChE>5 994.00 U/L), 低AChE组NIHSS评分、病死率高于高AChE组，住院时间长于高AChE组，差异有统计学意义(P＜0.05)，见表 5; 根据NLR预测SAP发生的截断值4.43, 将患者分为低NLR组(NLR < 4.43)和高NLR组(NLR≥4.43), 高NLR组NIHSS评分高于低NLR组，住院时间长于低NLR组，差异有统计学意义(P＜0.05), 2组病死率差异无统计学意义(P>0.05), 见表 6。
表 5 不同AChE水平ACI患者病情严重程度和转归情况比较(x±s)[n(%)]指标 低AChE组(n=87) 高AChE组(n=115) NIHSS评分/分 13.17±5.05 4.10±2.90* 住院时间/d 15.89±6.18 11.78±4.44* 死亡 14(16.09) 0* AChE: 乙酰胆碱酯酶; ACI: 急性脑梗死; NIHSS: 美国国立卫生研究院卒中量表。与低AChE组比较, * P＜0.05。 表 6 不同NLR水平ACI患者病情严重程度和转归情况比较(x±s)[n(%)]指标 低NLR组(n=95) 高NLR组(n=107) NIHSS评分/分 4.82±4.05 11.59±5.82* 住院时间/d 11.07±3.41 16.34±6.30* 死亡 4(4.21) 10(9.35) NLR: 中性粒细胞与淋巴细胞比值; ACI: 急性脑梗死; NIHSS: 美国国立卫生研究院卒中量表。与低NLR组比较, * P＜0.05。 3. 讨论
SAP是ACI住院患者最常见的并发症和致死原因之一，但目前临床尚缺乏可有效评价SAP发病风险的指标[1-2]。近年来，临床对AChE、NLR指标的研究逐渐增多, AChE已被证实是评估ACI严重程度和预后的重要指标[11], 另有研究[12]发现NLR在SAP的预测和诊断中具有较高的敏感性，但关于AChE与SAP发病风险的研究尚较少见。本研究探讨了AChE、NLR对SAP发病风险的预测价值，结果显示, AChE降低、NLR升高与ACI患者SAP发病密切相关; ROC曲线显示, AChE、NLR对ACI患者发生SAP的预测价值较高，且二者联合的预测价值进一步提高。本研究还发现，与高AChE组ACI患者相比，低AChE组患者神经缺损功能严重，住院时间延长，病死率升高; 与低NLR组ACI患者相比，高NLR组患者神经缺损功能严重，住院时间延长。
陈华[11]报道，脑卒中患者AChE活性越低，预后越差。相关研究[13]发现, AChE与脑梗死患者整体炎症状态有关, AChE可能在其中起着保护作用。黄帆等[14]发现，大面积脑梗死患者AChE与神经缺损严重程度及预后呈负相关，与本研究结论基本一致。目前，关于AChE在SAP中作用的研究较少，但其已被证实是脓毒症等感染性疾病的保护性因素, FENG W M等[15]选取359例脓毒症病例作为研究对象，发现死亡组AChE水平显著下降，且AChE下降幅度与病情危重程度和死亡密切相关。本研究发现, AChE是SAP发生的保护性因素, ROC曲线显示AChE对SAP发生有较高的预测价值，且低水平AChE患者的神经功能缺损程度更重，住院时间更长，病死率更高。
ACI可诱发全身炎症反应，一方面是通过分泌生长因子刺激中性粒细胞增多，另一方面是通过下丘脑-垂体-肾上腺轴抑制免疫反应，诱导淋巴细胞凋亡[15-16]。ACI患者发生SAP会进一步使中性粒细胞增多，因此NLR可能是评价SAP的潜在敏感指标。郭志良等[17]发现, NLR是SAP发生风险的预测因素，且高NLR与肺炎严重程度、NIHSS评分相关。本研究结果显示，与未发生SAP的对照组比较, SAP组患者年龄更大，合并心房颤动者更多，白细胞、中性粒细胞增多，淋巴细胞减少, CRP水平、NIHSS评分更高; 多因素Logistic回归分析显示, NLR升高是SAP发生的独立危险因素; ROC曲线显示, NLR对SAP发生有较高的预测价值，且NLR联合AChE对SAP发生的预测价值更高; 依据NLR截断值分组后发现，与低NLR组比较，高NLR组患者神经功能缺损程度更重，住院时间更长，病死率则无显著差异。本研究为单中心回顾性研究，样本量偏少，导致CRP存在明显的离群点，未能纳入多因素分析，且可能存在选择偏倚，故未来还需进一步开展大样本量前瞻性研究加以验证。
综上所述，血清AChE、NLR均与ACI患者SAP发病密切相关，其中AChE是SAP的保护性因素, NLR是SAP的危险性因素。AChE联合NLR对SAP发生风险具有重要的预测价值，且AChE、NLR水平可影响ACI患者病情严重程度和转归。
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ÖZTÜRK R, MURT A. Epidemiology of urological infections: a global burden[J]. World J Urol, 2020, 38(11): 2669-2679.
FLORES-MIRELES A L, WALKER J N, CAPARON M, et al. Urinary tract infections: epidemiology, mechanisms of infection and treatment options[J]. Nat Rev Microbiol, 2015, 13(5): 269-284.
FOXMAN B. Urinary tract infection syndromes: occurrence, recurrence, bacteriology, risk factors, and disease burden [J]. Infect Dis Clin North Am, 2014, 28(1): 1-14.
Consortium The Human Microbiome Project. Structure, function and diversity of the healthy human microbiome[J]. Nature, 2012, 486(7402): 207-214.
LLOYD-PRICE J, MAHURKAR A, RAHNAVARD G, et al. Erratum: Strains, functions and dynamics in the expanded Human Microbiome Project[J]. Nature, 2017, 551(7679): 256.
Consortium The Human Microbiome Project. A framework for human microbiome research[J]. Nature, 2012, 486(7402): 215-221.
HILT E E, MCKINLEY K, PEARCE M M, et al. Urine is not sterile: use of enhanced urine culture techniques to detect resident bacterial flora in the adult female bladder[J]. J Clin Microbiol, 2014, 52(3): 871-876.
SIDDIQUI H, NEDERBRAGT A J, LAGESEN K, et al. Assessing diversity of the female urine microbiota by high throughput sequencing of 16S rDNA amplicons[J]. BMC Microbiol, 2011, 11: 244.
BRUBAKER L, WOLFE A J. The female urinary microbiota, urinary health and common urinary disorders[J]. Ann Transl Med, 2017, 5: 34.
ARAGÓN I M, HERRERA-IMBRODA B, QUEIPO-ORTUÑO M I, et al. The urinary tract microbiome in health and disease[J]. Eur Urol Focus, 2018, 4(1): 128-138.
MAGISTRO G, STIEF C G. The urinary tract microbiome: the answer to all our open questions?[J]. Eur Urol Focus, 2019, 5(1): 36-38.
WOLFE A J, TOH E, SHIBATA N, et al. Evidence of uncultivated bacteria in the adult female bladder[J]. J Clin Microbiol, 2012, 50(4): 1376-1383.
FOUTS D E, PIEPER R, SZPAKOWSKI S, et al. Integrated next-generation sequencing of 16S rDNA and metaproteomics differentiate the healthy urine microbiome from asymptomatic bacteriuria in neuropathic bladder associated with spinal cord injury[J]. J Transl Med, 2012, 10: 174.
KHASRIYA R, SATHIANANTHAMOORTHY S, ISMAIL S, et al. Spectrum of bacterial colonization associated with urothelial cells from patients with chronic lower urinary tract symptoms[J]. J Clin Microbiol, 2013, 51(7): 2054-2062.
PEARCE M M, ZILLIOX M J, ROSENFELD A B, et al. The female urinary microbiome in urgency urinary incontinence[J]. Am J Obstet Gynecol, 2015, 213(3): 347. e1-347. e11.
RAVEL J, GAJER P, ABDO Z, et al. Vaginal microbiome of reproductive-age women[J]. PNAS, 2011, 108(Supplement_1): 4680-4687.
KINROSS J M, DARZI A W, NICHOLSON J K. Gut microbiome-host interactions in health and disease[J]. Genome Med, 2011, 3(3): 14.
MIMEE M, CITORIK R J, LU T K. Microbiome therapeutics: Advances and challenges[J]. Adv Drug Deliv Rev, 2016, 105: 44-54.
BRUBAKER L, WOLFE A J. The new world of the urinary microbiota in women[J]. Am J Obstet Gynecol, 2015, 213(5): 644-649.
BAO Y, AL K F, CHANYI R M, et al. Questions and challenges associated with studying the microbiome of the urinary tract[J]. Ann Transl Med, 2017, 5(2): 33.
NG K M, FERREYRA J A, HIGGINBOTTOM S K, et al. Microbiota-liberated host sugars facilitate post-antibiotic expansion of enteric pathogens[J]. Nature, 2013, 502(7469): 96-99.
ISAAC S, SCHER J U, DJUKOVIC A, et al. Short- and long-term effects of oral vancomycin on the human intestinal microbiota[J]. J Antimicrob Chemother, 2017, 72(1): 128-136.
ZHANG L, HUANG Y, ZHOU Y, et al. Antibiotic administration routes significantly influence the levels of antibiotic resistance in gut microbiota[J]. Antimicrob Agents Chemother, 2013, 57(8): 3659-3666.
CAI T, MAZZOLI S, MONDAINI N, et al. The role of asymptomatic bacteriuria in young women with recurrent urinary tract infections: to treat or not to treat?[J]. Clin Infect Dis, 2012, 55(6): 771-777.
BECATTINI S, TAUR Y, PAMER E G. Antibiotic-induced changes in the intestinal microbiota and disease[J]. Trends Mol Med, 2016, 22(6): 458-478.
SENDER R, FUCHS S, MILO R. Revised estimates for the number of human and bacteria cells in the body[J]. PLoS Biol, 2016, 14(8): e1002533.
GILBERT J A, BLASER M J, CAPORASO J G, et al. Current understanding of the human microbiome [J]. Nat Med, 2018, 24(4): 392-400.
GRITZ E C, BHANDARI V. The human neonatal gut microbiome: a brief review[J]. Front Pediatr, 2015, 3: 17.
SHANNON M B, LIMEIRA R, JOHANSEN D, et al. Bladder urinary oxygen tension is correlated with urinary microbiota composition[J]. Int Urogynecol J, 2019, 30(8): 1261-1267.
REITZER L, ZIMMERN P. Rapid growth and metabolism of UropathogenicEscherichia coliin relation to urine composition[J]. Clin Microbiol Reviews, 2019, 33(1): e00101-e00119.
BOUATRA S, AZIAT F, MANDAL R, et al. The human urine metabolome[J]. PLoS One, 2013, 8(9): e73076.
FORSYTH V S, ARMBRUSTER C E, SMITH S N, et al. Rapid Growth of Uropathogenic Escherichia coli during Human Urinary Tract Infection[J]. mBio, 2018, 9(2): e00186.
HYNES W L, WALTON S L. Hyaluronidases of Gram-positive bacteria[J]. FEMS Microbiol Lett, 2000, 183(2): 201-207.
KAWAI K, KAMOCHI R, OIKI S, et al. Probiotics in human gut microbiota can degrade host glycosaminoglycans[J]. Sci Rep, 2018, 8: 10674.
ZúÑIGA M, MONEDERO V, YEBRA M J. Utilization of host-derived glycans by intestinal Lactobacillus and Bifidobacterium species[J]. Frontiers in Microbiology, 2018, 9: 1917.
GILBERT N M, O'BRIEN V P, LEWIS A L. Transient microbiota exposures activate dormant Escherichia coli infection in the bladder and drive severe outcomes of recurrent disease[J]. PLoS Pathog, 2017, 13(3): e1006238.
PRICE T K, DUNE T, HILT E E, et al. The clinical urine culture: enhanced techniques improve detection of clinically relevant microorganisms[J]. J Clin Microbiol, 2016, 54(5): 1216-1222.
MOUSTAFA A, LI W Z, SINGH H, et al. Microbial metagenome of urinary tract infection[J]. Sci Rep, 2018, 8: 4333.
MULDER M, RADJABZADEH D, HASSING R J, et al. The effect of antimicrobial drug use on the composition of the genitourinary microbiota in an elderly population[J]. BMC Microbiol, 2019, 19: 9.
THOMAS-WHITE K, FORSTER S C, KUMAR N, et al. Culturing of female bladder bacteria reveals an interconnected urogenital microbiota[J]. Nat Commun, 2018, 9: 1557.
STAPLETON A E, AU-YEUNG M, HOOTON T M, et al. Randomized, placebo-controlled phase 2 trial of a Lactobacillus crispatus probiotic given intravaginally for prevention of recurrent urinary tract infection[J]. Clin Infect Dis, 2011, 52(10): 1212-1217.
SPAULDING C N, KLEIN R D, RUER S, et al. Selective depletion of uropathogenic E. coli from the gut by a FimH antagonist[J]. Nature, 2017, 546(7659): 528-532.
KLEIN T, ABGOTTSPON D, WITTWER M, et al. FimH antagonists for the oral treatment of urinary tract infections: from design and synthesis to in vitro and in vivo evaluation[J]. J Med Chem, 2010, 53(24): 8627-8641.
CUSUMANO C K, PINKNER J S, HAN Z F, et al. Treatment and prevention of urinary tract infection with orally active FimH inhibitors[J]. Sci Transl Med, 2011, 3(109): 109ra115.
SCHÖNEMANN W, CRAMER J, MÜHLETHALER T, et al. Improvement of aglycone π-stacking yields nanomolar to sub-nanomolar FimH antagonists[J]. ChemMedChem, 2019, 14(7): 749-757.
JARVIS C, HAN Z F, KALAS V, et al. Antivirulence isoquinolone mannosides: optimization of the biaryl aglycone for FimH lectin binding affinity and efficacy in the treatment of chronic UTI[J]. ChemMedChem, 2016, 11(4): 367-373.
MYDOCK-MCGRANE L, CUSUMANO Z, HAN Z F, et al. AntivirulenceC-mannosides as antibiotic-sparing, oral therapeutics for urinary tract infections[J]. J Med Chem, 2016, 59(20): 9390-9408.
CONOVER M S, RUER S, TAGANNA J, et al. Inflammation-induced adhesin-receptor interaction provides a fitness advantage to uropathogenic E. coli during chronic infection[J]. Cell Host Microbe, 2016, 20(4): 482-492.
KALAS V, HIBBING M E, MADDIRALA A R, et al. Structure-based discovery of glycomimetic FmlH ligands as inhibitors of bacterial adhesion during urinary tract infection[J]. PNAS, 2018, 115(12): E2819-E2828.
DURAJ-THATTE A M, PRAVESCHOTINUNT P, NASH T R, et al. Modulating bacterial and gut mucosal interactions with engineered biofilm matrix proteins[J]. Sci Rep, 2018, 8: 3475.
SMITH A L, BROWN J, WYMAN J F, et al. Treatment and prevention of recurrent lower urinary tract infections in women: a rapid review with practice recommendations[J]. J Urol, 2018, 200(6): 1174-1191.
SCHLAGER T A, LEGALLO R, INNES D, et al. B cell infiltration and lymphonodular hyperplasia in bladder submucosa of patients with persistent bacteriuria and recurrent urinary tract infections[J]. J Urol, 2011, 186(6): 2359-2364.
HAWKEY C J. COX-1 and COX-2 inhibitors[J]. Best Pract Res Clin Gastroenterol, 2001, 15(5): 801-820.
HANNAN T J, ROBERTS P L, RIEHL T E, et al. Inhibition of cyclooxygenase-2 prevents chronic and recurrent cystitis[J]. EBioMedicine, 2014, 1(1): 46-57.
BLEIDORN J, GÁGYOR I, KOCHEN M M, et al. Symptomatic treatment(ibuprofen)or antibiotics(ciprofloxacin)for uncomplicated urinary tract infection- Results of a randomized controlled pilot trial[J]. BMC Med, 2010, 8: 30.
GÁGYOR I, BLEIDORN J, KOCHEN M M, et al. Ibuprofen versus fosfomycin for uncomplicated urinary tract infection in women: randomised controlled trial[J]. BMJ, 2015: h6544.
KRONENBERG A, BüTIKOFER L, ODUTAYO A, et al. Symptomatic treatment of uncomplicated lower urinary tract infections in the ambulatory setting: randomised, double blind trial[J]. BMJ, 2017, 359: j4784.
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