Spectral characteristics of urine from patients with end-stage kidney disease analyzed using Raman Chemometric Urinalysis (Rametrix)

Senger, Ryan S.; Sullivan, Meaghan; Gouldin, Austin; Lundgren, Stephanie; Merrifield, Kristen; Steen, Caitlin; Baker, Emily; Vu, Tommy; Agnor, Ben; Martinez, Gabrielle; Coogan, Hana; Carswell, William; Kavuru, Varun; Karageorge, Lampros; Dev, Devasmita; Du, Pang; Sklar, Allan H.; Pirkle, James L.; Guelich, Susan; Orlando, Giuseppe; Robertson, John L.

doi:10.1371/journal.pone.0227281

Cited by 20 publications

(32 citation statements)

References 30 publications

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“…For the IR and Raman spectroscopy methods the LOD might not be so relevant factor. The IR and Raman methods is better characterized by how accurate a particular method can distinguish whether a spectra belongs to a healthy subject or not, as evidenced from works [ 158 , 164 ].…”

Section: Discussionmentioning

confidence: 99%

“…PCA showed high discrimination between dialysis and normality (95 % accuracy). Senger et al analyzed by the Raman spectroscopy three types of patients: patients receiving peritoneal dialysis (PD) therapy for end-stage kidney disease; patients receiving peritoneal dialysis (PD) therapy for end-stage kidney disease; urine from healthy human volunteers, as shown in Figure 5 [ 164 ]. The authors used the set of mathematical procedures on spectra which included spectral processing (e.g., truncation, baselining, and vector normalization); principal component analysis (PCA); statistical analyses (ANOVA and pairwise comparisons); discriminant analysis of principal components (DAPC); and testing DAPC models using a leave-one-out build/test validation procedure.…”

Section: Detection Techniquesmentioning

confidence: 99%

“…(B) Averaged, baselined, and vector normalized Raman spectra from 395 spent PD dialysate specimens. Reprinted from [ 164 ]. …”

Section: Detection Techniquesmentioning

confidence: 99%

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Review: Detection and quantification of proteins in human urine

Aitekenov

Gaipov

Bukasov

2021

Talanta

125

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Extensive medical research showed that patients, with high protein concentration in urine, have various kinds of kidney diseases, referred to as proteinuria. Urinary protein biomarkers are useful for diagnosis of many health conditions – kidney and cardio vascular diseases, cancers, diabetes, infections. This review focuses on the instrumental quantification (electrophoresis, chromatography, immunoassays, mass spectrometry, fluorescence spectroscopy, the infrared spectroscopy, and Raman spectroscopy) of proteins (the most of all albumin) in human urine matrix. Different techniques provide unique information on what constituents of the urine are. Due to complex nature of urine, a separation step by electrophoresis or chromatography are often used for proteomics study of urine. Mass spectrometry is a powerful tool for the discovery and the analysis of biomarkers in urine, however, costs of the analysis are high, especially for quantitative analysis. Immunoassays, which often come with fluorescence detection, are major qualitative and quantitative tools in clinical analysis. While Infrared and Raman spectroscopies do not give extensive information about urine, they could become important tools for the routine clinical diagnostics of kidney problems, due to rapidness and low-cost. Thus, it is important to review all the applicable techniques and methods related to urine analysis. In this review, a brief overview of each technique’s principle is introduced. Where applicable, research papers about protein determination in urine are summarized with the main figures of merits, such as the limit of detection, the detectable range, recovery and accuracy, when available.

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Section: Discussionmentioning

confidence: 99%

Section: Detection Techniquesmentioning

confidence: 99%

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Review: Detection and quantification of proteins in human urine

Aitekenov

Gaipov

Bukasov

2021

Talanta

125

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“…Then, it has been applied to complex biological samples, such as fluids [9,10], cells [11,12], minerals as physiological [13][14][15] and pathological calcifications [16][17][18] and tissues [19]. Such versatility explains the numerous applications of Raman spectroscopy in different specialties of medicine [20][21][22], among which are nephrology [23][24][25][26][27][28][29][30], rheumatology [31][32][33], hematology [34][35][36], gastroenterology [37,38] or endocrinology [39,40]. Note that in vivo Raman experiments are also envisaged and proofs of concepts have already been demonstrated in a few domains of applications [41][42][43][44].…”

Section: Introductionmentioning

confidence: 99%

Raman opportunities in the field of pathological calcifications

Lucas¹,

Bazin²,

Daudon³

2022

Comptes Rendus. Chimie

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The aim of this contribution is to present to the community the very unique diagnostic capabilities of Raman spectroscopy in the context of pathological calcifications. By offering the clinician the opportunity to determine within seconds the chemical composition of micron-sized crystallites, possibly in vivo, Raman analyses find no equivalent among the large set of analytical tools available. After a brief recap of some peculiar aspects of this spectrometry and a presentation of the latest instrumental developments, this review gathers the most recent literature on the use of Raman to diagnose various lithiases or microcrystalline pathologies.

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“…2,3 It has also found applications in a variety of medical studies, such as disease diagnosis and monitoring efficacy and progress of therapy. 4–8…”

Section: Introductionmentioning

confidence: 99%

ISREA: An Efficient Peak-Preserving Baseline Correction Algorithm for Raman Spectra

Senger

et al. 2020

Appl Spectrosc

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A critical step in Raman spectroscopy is baseline correction. This procedure eliminates the background signals generated by residual Rayleigh scattering or fluorescence. Baseline correction procedures relying on asymmetric loss functions have been employed recently. They operate with a reduced penalty on positive spectral deviations that essentially push down the baseline estimates from invading Raman peak areas. However, their coupling with polynomial fitting may not be suitable over the whole spectral domain and can yield inconsistent baselines. Their requirement of the specification of a threshold and the non-convexity of the corresponding objective function further complicates the computation. Learning from their pros and cons, we have developed a novel baseline correction procedure called the iterative smoothing-splines with root error adjustment (ISREA) that has three distinct advantages. First, ISREA uses smoothing splines to estimate the baseline that are more flexible than polynomials and capable of capturing complicated trends over the whole spectral domain. Second, ISREA mimics the asymmetric square root loss and removes the need of a threshold. Finally, ISREA avoids the direct optimization of a non-convex loss function by iteratively updating prediction errors and refitting baselines. Through our extensive numerical experiments on a wide variety of spectra including simulated spectra, mineral spectra, and dialysate spectra, we show that ISREA is simple, fast, and can yield consistent and accurate baselines that preserve all the meaningful Raman peaks.

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Spectral characteristics of urine from patients with end-stage kidney disease analyzed using Raman Chemometric Urinalysis (Rametrix)

Cited by 20 publications

References 30 publications

Review: Detection and quantification of proteins in human urine

Review: Detection and quantification of proteins in human urine

Raman opportunities in the field of pathological calcifications

ISREA: An Efficient Peak-Preserving Baseline Correction Algorithm for Raman Spectra

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