Analysis Of Body Fluids Research Articles

Network analysis of hepatocellular carcinoma liquid biopsies augmented by single-cell sequencing data.

Liquid biopsy, the analysis of body fluids, represents a promising approach for disease diagnosis and prognosis with minimal intervention. Sequencing cell-free RNA derived from liquid biopsies has been very promising for the diagnosis of several diseases. Cancer research, in particular, has emerged as a prominent candidate since early diagnosis has been shown to be a critical determinant of disease prognosis. Although high-throughput analysis of liquid biopsies has uncovered many differentially expressed genes in the context of cancer, the functional connection between these genes is not investigated in depth. An important approach to remedy this issue is the construction of gene networks which describes the correlation patterns between different genes, thereby allowing to infer their functional organization. In this study, we aimed at characterizing extracellular transcriptome gene networks of hepatocellular carcinoma patients compared to healthy controls. Our analysis revealed a number of genes previously associated with hepatocellular carcinoma and uncovered their association network in the blood. Our study thus demonstrates the feasibility of performing gene co-expression network analysis from cell-free RNA data and its utility in studying hepatocellular carcinoma. Furthermore, we augmented cell-free RNA network analysis with single-cell RNA sequencing data which enables the contextualization of the identified network modules with cell-type specific transcriptomes from the liver.

Transfer, persistence and recovery of DNA and mRNA vaginal mucosa markers after intimate and social contact with Bayesian network analysis for activity level reporting

In sexual assault cases, it can be challenging to identify the type of body fluids/ cell types present in a crime scene sample, especially the origin of epithelial cells. Therefore, more labs are applying mRNA body fluid analysis for saliva, skin and vaginal mucosa markers. To address activity level propositions, it is necessary to assign probabilities of transfer, persistence, prevalence and recovery of DNA and mRNA markers. In this study we analysed 158 samples (fingernail swabs, penile swabs and boxershorts) from 12 couples collected at different time points post intimate contact and after non-intimate contact in order to detect DNA from the person of interest (POI) and mRNA vaginal mucosa markers. Samples were DNA and RNA co-extracted and analysed with PowerPlex®Fusion 6C System and 19-plex mRNA primer mix respectively, using Endpoint PCR and the CE platform. Vaginal mucosa was detected up to 36 h post intimate contact, but also detected in one non-intimate contact sample. In 94% of intimate contact and 50 % of non-intimate contact samples the DNA results support the proposition that POI is the donor (LR ≥ 10,000). There was a strong association between the detection of vaginal mucosa and the average RFU value of the POI. The data were used to instantiate a comprehensive Bayesian network to evaluate the evidence at activity level, given alternate propositions conditioned upon indirect or direct transfer events. It is shown that the value of the evidence is mainly affected by the high DNA quantity (measured as mean RFU) that is recovered from the POI. The detection of vaginal mucosa had low impact upon the resultant likelihood ratio.

Cascaded enzymatic reaction-mediated multicolor pixelated quantitative system integrated microfluidic wearable analytical device (McPiQ-μWAD) for non-invasive and sensitive glucose diagnostics

Non-invasive body fluid analysis has been increasingly developed for health monitoring and disease diagnostics. However, some portable devices, as one representative non-invasive application, must require complicated multi-step reactions, expensive photoelectric components, and be difficult for large-scale fabrication. Herein, we have integrated a cascaded enzymatic reaction-mediated multicolor pixelated quantitative system on the wearable microfluidic device (McPiQ-μWAD) for non-invasive and sensitive detection of sweat glucose. This is the first application of non-invasive portable detection using multicolor pixelated quantification, and it’s also the first smartphone-assistant multicolor pixelated analysis for Localized Surface Plasmon Resonance (LSPR) of gold nanorods (Au NRs). The wearable device incorporated laser-ablated microfluidic technology and enzyme-mediated Au NRs etching system for the achievement of rapid and sensitive pixelated quantification. The McPiQ-μWAD successfully transferred sweat glucose into a visual colorful signal in the concentration range of 0.02–2.4 mM (0.36–43.2 mg/dL) by pixelated quantification with the limit of detection (LOD) of 0.02 mM (0.36 mg/dL). Compared with commercial glucose kit-based spectrometry, the detection results of real sweat samples from healthy volunteers showed desirable reliability and accuracy based on the McPiQ-μWAD. The presented McPiQ-μWAD provides the high potential to be broadly utilized for non-invasive analyses for applications in family health surveillance and point-of-care tests of emergency.

Capillary Electrophoresis Applied to Human Urine Analysis for Clinical Diagnosis: New Trends and Perspectives

Capillary electrophoresis (CE) is an electromigration-based separation technique that emerged in the early 90s and has been evolving since then. Over recent decades, the association of CE with new technologies and detections strategies is enhancing its intrinsic mightiness. Today, CE is a part of the main high-throughput analytical platform used for medical-related applications, together with traditional gas chromatography, high-performance liquid chromatography, and fingerprinting spectroscopic methods. New strategies for assessing human disorders involve a thorough analysis of bodily fluids through said instrumentation. In this context, human urine is considered an excellent alternative, for being rich in information and easily collected with minimal inconvenience for the doners. Overall, since it is an ultrafiltrate of the human bloodstream, urine composition should be changed if any condition jeopardizes human homeostasis. Thus, monitoring the levels of biomarkers in urine by an advantageous technique such as CE can be an interesting choice for diagnostic and other clinical purposes. In this review, we will be commenting on the new tendencies and technologies applied to human urine analysis by CE over the last five years. We will be starting by commenting the applications onto target groups of molecules followed by addressing the CE feasibility for the determination of general chemical profiles through untargeted omics approaches, and finishing with the perspectives on the subject.

Effect of Pre-Analytical Errors on Turnaround Time of Central Clinical Laboratory: A Study Protocol

Clinical laboratories are crucial for medical care and recovery because they have evidence from body fluid analysis. Laboratory observations are used to make the majority of medical decisions. As a result, clinical lab results must be precise and timely. Laboratory quality management systems must include the influence of pre-analytical procedures in regions, including non conformance detection and control, continuous upgrade, internal audit, and quality indicators in order to be accredited as per ISO 15189:2012. Quality assurance (QA) has risen to the top of the priority list as a major source of worry. In terms of QA, "errors" in lab services are the most significant category that laboratories constantly monitor and assess. It is the responsibility of the clinical laboratory to provide precise and punctual results. The pre-analytical phase, on the other hand, is directly connected to the specimen collecting method and is mostly out of the laboratory's direct control; additionally, the majority of pre analytical mistakes are caused by human errors. As a result, the most essential and required methods to prevent these mistakes are phlebotomy team education and training programs. In this article, we have observed the effect of pre-analytical errors on turnaround time of central clinical laboratory of the hospital and also discovered the way to decrease the pre-analytical errors of inpatient samples.

Application of Proteogenomics to Urine Analysis towards the Identification of Novel Biomarkers of Prostate Cancer: An Exploratory Study

Simple SummaryProstate cancer (PCa) is one of the most common cancers. Due to the limited and invasive approaches for PCa diagnosis, it is crucial to identify more accurate and non-invasive biomarkers for its detection. The aim of our study was to non-invasively uncover new protein targets for detecting PCa using a proteomics and proteogenomics approach. This work identified several dysregulated mutant protein isoforms in urine from PCa patients, some of them predicted to have a protective or an adverse role in these patients. These results are promising given urine’s non-invasive nature and offers an auspicious opportunity for research and development of PCa biomarkers.To identify new protein targets for PCa detection, first, a shotgun discovery experiment was performed to characterize the urinary proteome of PCa patients. This revealed 18 differentially abundant urinary proteins in PCa patients. Second, selected targets were clinically tested by immunoblot, and the soluble E-cadherin fragment was detected for the first time in the urine of PCa patients. Third, the proteogenome landscape of these PCa patients was characterized, revealing 1665 mutant protein isoforms. Statistical analysis revealed 6 differentially abundant mutant protein isoforms in PCa patients. Analysis of the likely effects of mutations on protein function and PPIs involving the dysregulated mutant protein isoforms suggests a protective role of mutations HSPG2*Q1062H and VASN*R161Q and an adverse role of AMBP*A286G and CD55*S162L in PCa patients. This work originally characterized the urinary proteome, focusing on the proteogenome profile of PCa patients, which is usually overlooked in the analysis of PCa and body fluids. Combined analysis of mass spectrometry data using two different software packages was performed for the first time in the context of PCa, which increased the robustness of the data analysis. The application of proteogenomics to urine proteomic analysis can be very enriching in mutation-related diseases such as cancer.

Performance evaluation of UF-4000 body fluid mode for automated body fluid cell counting

BackgroundCytological analysis of body fluids (BF) provides important information for diagnosis in various medical conditions. We evaluated the analytical performance of the UF-4000 BF mode for ascitic, cerebrospinal, pleural, synovial and continuous ambulatory peritoneal dialysis fluids compared to light microscopy counting (LM). Materials and methods223 consecutive BF were analyzed by UF-4000 and results were compared using Pearson’s correlation, Bland-Altman analysis, and contingence tests at relevant cut-off values. This study also included the evaluation of precision, linearity, and carryover. ResultsFor white and red blood cells (WBC, RBC) counts in all BF, correlation was excellent with Pearson’s coefficients R2 > 0,98. Bland-Altman analysis didn’t reveal significant differences with limited bias for WBC ranging from −10 to −1 WBC/µL and bias ranging from −43 to −6/µL for RBC. At specific cut-off values for WBC, Se and Spe were 100% except for ascites (Spe = 98%) due to two false positive.Precision evaluated at three concentration levels was good for each parameter (WBC < 10%). Linearity was excellent for WBC (R2 > 0,99) and carryover negligible (<0,004%). ConclusionUF-4000 BF mode is a good alternative to manual LM for BF cell counting. This automated method gives rapid and accurate results which is important for therapeutic decisions.

Fast and Sensitive Quantification of AccQ-Tag Derivatized Amino Acids and Biogenic Amines by UHPLC-UV Analysis from Complex Biological Samples.

Metabolomic analysis of different body fluids bears high importance in medical sciences. Our aim was to develop and validate a fast UHPLC-UV method for the analysis of 33 amino acids and biogenic amines from complex biological samples. AccQ-Tag derivatization was conducted on target molecules and the derivatized targets were analyzed by UHPLC-UV. The detection of the analytes was carried out with UV analysis and by Selected Reaction Monitoring (SRM)-based targeted mass spectrometry. The method was validated according to the FDA guidelines. Serum and non-stimulated tear samples were collected from five healthy individuals and the samples were analyzed by the method. The method was successfully validated with appropriate accuracy and precision for all 33 biomolecules. A total of 29 analytes were detected in serum samples and 26 of them were quantified. In the tears, 30 amino acids and biogenic amines were identified and 20 of them were quantified. The developed and validated UHPLC-UV method enables the fast and precise analysis of amino acids and biogenic amines from complex biological samples.

Evaluation of robustness in untargeted metabolomics: Application of multivariate analysis, linear regression and hierarchical modeling

Gas chromatography coupled with mass spectrometry (GC-MS) is considered as a reliable and effective technique for metabolomics analysis of human tissues and body fluids. However, sample preparation procedure for GC-MS is multi-stage, long-lasting and error-prone. That is why Design of Experiments approach is often used to assess the performance of commonly applied sample preparation procedures. In this work, Plackett-Burman design with 5 center points was used to evaluate the impact of 10 variables on the extraction and derivatization of metabolites from human urine samples. The obtained data was subjected to statistical analysis. In the first approach, the principal component analysis was performed to simplify the data matrix. The first two components (explaining the highest percent of the variability) were selected as response variables. They were regressed with parameters to assess the effects of the applied changes. The obtained PCA-based models suggest that alterations applied in input parameters settings may contribute to significant changes in the obtained responses, e.g. altered overnight incubation time influences the obtained metabolic profiles. In the second approach, the whole dataset was simplified by calculating the average signal intensity across metabolites. Those values, subjected to linear regression also pointed the overnight incubation time as the factor affecting sample preparation process the most. Finally, hierarchical linear modeling was applied in order to provide detailed evaluation of the applied changes. Such an approach enables the selection of variables influencing sample's metabolic profiles and each metabolite individually, providing also robustness to outliers. Ultimately, 12 experiments enabled to identify critical stages of the applied sample preparation procedure in terms of metabolic profile (abundances of specific metabolites). Furthermore, the obtained results might also suggest the direction for optimization of GC-MS method for targeted analysis of urine metabolites of different physico-chemical properties and allow to propose some minor modifications that might be beneficial for quality and repeatability of non-targeted experiments.

Synthesis and characterization of sol-gel bioactive glass nanoparticles doped with boron and copper

In this work the sol-gel synthesis of bioactive glass nanoparticles containing both boron and copper oxides is reported for the first time in the literature. Two acid/base co-catalysed methods were compared. The obtained glasses have been characterized in terms of morphology, composition, particle surface area, phase analysis and bioactivity in acellular simulated body fluids. The almost spherical nanoparticles (<100 nm diameter) obtained are characterized by a certain degree of aggregation and have compositions, which are coherent with the theoretical ones. Each glass revealed the ability to promote the growth of hydroxyapatite on its surface during soaking in simulated body fluid, thus we can assume that the addition of boron and copper did not negatively affect the bioactivity of the sol-gel derived glasses. Future investigations will be devoted to biological characterizations for cytotoxicity, antibacterial properties and pro-angiogenetic abilities.

Sex discrimination from urine traces for forensic purposes using attenuated total reflectance Fourier transform infrared spectroscopy and multivariate data analysis.

The characteristics of ATR FT-IR spectroscopy are extremely attractive and escalating popularity in the field of body fluid analysis owing to its non-destructive, rapid, and reliable nature. Herein, the present study establishes that how ATR FT-IR spectroscopy could be utilized as a non-destructive, non-invasive, and confirmatory technique for sex discrimination from dry urine traces. Traces of body fluids are of paramount importance to criminal investigations as a major source of individualization by DNA profiling. However, the significance of DNA profiling from urine traces is highly diminished due to the small amount of DNA in urine traces. For that reason, the sex discrimination between the male and female donors is sorely desirable. In this study, ATR FT-IR spectroscopy in combination with partial least squares-discriminant analysis (PLS-DA) model unequivocally demonstrated the successful sex discrimination of an individual from dry traces of urine with 95.3% accuracy. PCA-Linear Discriminant Analysis (LDA) approach provided 85.2% of accuracy; however, PCA could not provide the sufficient findings for the discrimination of male and female urine spectra. The validation study was conducted and obtained 0% rates of false-positive and negative assignments. Additionally, this study also attended to assess the influence of substrates on the analysis of urine traces and results have been discussed.

A Wearable Microneedle-Based Extended Gate Transistor for Real-Time Detection of Sodium in Interstitial Fluids.

Sodium is a prominent prognostic biomarker for assessing health status, such as dysnatremia. As of now, detection and monitoring of sodium levels in the human body is carried out by means of laborious and bulky laboratory equipmentand/or by offline analysis of various body fluids. Herein, an innovative stretchable, skin-conformal and fast-response microneedle extended-gate FET biosensor is reported for real-time detection of sodium in interstitial fluids for minimally invasive health monitoring along with high sensitivity, low limit of detection, excellent biocompatibility, and on-body mechanical stability. The integration of the reported device with a wireless-data transmitter and the Internet-of-Things cloud for real-time monitoring and long-term analysis is reported and discussed. This platform would eventually help bringing unlimited possibilities for effecient medical care and accurate clinical decision-making.

A pilot exploration of multi-omics research of gut microbiome in major depressive disorders

The pathophysiology of major depressive disorder (MDD) remains obscure. Recently, the microbiota-gut-brain (MGB) axis’s role in MDD has an increasing attention. However, the specific mechanism of the multi-level effects of gut microbiota on host metabolism, immunity, and brain structure is unclear. Multi-omics approaches based on the analysis of different body fluids and tissues using a variety of analytical platforms have the potential to provide a deeper understanding of MGB axis disorders. Therefore, the data of metagenomics, metabolomic, inflammatory factors, and MRI scanning are collected from the two groups including 24 drug-naïve MDD patients and 26 healthy controls (HCs). Then, the correlation analysis is performed in all omics. The results confirmed that there are many markedly altered differences, such as elevated Actinobacteria abundance, plasma IL-1β concentration, lipid, vitamin, and carbohydrate metabolism disorder, and diminished grey matter volume (GMV) of inferior frontal gyrus (IFG) in the MDD patients. Notably, three kinds of discriminative bacteria, Ruminococcus bromii, Lactococcus chungangensis, and Streptococcus gallolyticus have an extensive correlation with metabolome, immunology, GMV, and clinical symptoms. All three microbiota are closely related to IL-1β and lipids (as an example, phosphoethanolamine (PEA)). Besides, Lactococcus chungangensis is negatively related to the GMV of left IFG. Overall, this study demonstrate that the effects of gut microbiome exert in MDD is multifactorial.

Surface-Enhanced Raman Spectroscopic (SERS) Characterization of Low Molecular Weight Fraction of the Serum of Breast Cancer Patients with Principal Component Analysis (PCA) and Partial Least Square-Discriminant Analysis (PLS-DA)

Vibrational spectroscopic techniques including Raman spectroscopy have been increasingly used for the analysis of body fluids particularly blood serum. Low molecular weight protein fractions (LMWFs) present in blood serum are usually associated with pathological condition related to disease. However, human serum analysis is challenging because these LMWFs are dominated by high molecular weight proteins, making analysis by Raman spectroscopy difficult. In the current study, in order to overcome this limitation, the separation of the high molecular weight fraction (HMWF) was done by centrifugal filtration of the sera from breast cancer patients using 50 kDa filters. The filtrate was analyzed by surface-enhanced Raman spectroscopy (SERS). Comparison of the SERS spectral features of the whole serum and their filtrate fraction obtained by ultra-centrifugation indicate that this approach is capable of potentially targeting small circulating biomarkers dominated by the HMWF in unmodified serum. SERS spectra of the filtrate fractions of modified disease samples contain prominent peaks at 477, 684, 743, 859, 1263, 1275 and 1512 cm−1 in comparison to unmodified serum. The SERS peaks at 573, 594, 730, 743, 859, 963, 1103 and 1453 cm−1 in spectra collected from cancerous serum filtrate fractions distinguished them from healthy samples. The spectra were further analyzed by principal component analysis (PCA) and partial least squares – discriminant analysis (PLS-DA). The validated PLS-DA model yielded classification of the cancerous and healthy samples with the sensitivity and specificity of 99% each.

ExoRBase 2.0: an atlas of mRNA, lncRNA and circRNA in extracellular vesicles from human biofluids.

Extracellular vesicles (EVs) are small membranous vesicles that contain an abundant cargo of different RNA species with specialized functions and clinical implications. Here, we introduce an updated online database (http://www.exoRBase.org), exoRBase 2.0, which is a repository of EV long RNAs (termed exLRs) derived from RNA-seq data analyses of diverse human body fluids. In exoRBase 2.0, the number of exLRs has increased to 19 643 messenger RNAs (mRNAs), 15 645 long non-coding RNAs (lncRNAs) and 79 084 circular RNAs (circRNAs) obtained from ∼1000 human blood, urine, cerebrospinal fluid (CSF) and bile samples. Importantly, exoRBase 2.0 not only integrates and compares exLR expression profiles but also visualizes the pathway-level functional changes and the heterogeneity of origins of circulating EVs in the context of different physiological and pathological conditions. Our database provides an attractive platform for the identification of novel exLR signatures from human biofluids that will aid in the discovery of new circulating biomarkers to improve disease diagnosis and therapy.

Pyrosequencing Primer Design for Forensic Biology Applications.

The polymerase chain reaction (PCR) is used to copy DNA in vitro for a variety of applications including amplifying a target DNA, mutating a base, adding tags, and sequencing by synthesis applications. Next-generation sequencing (NGS) is a DNA sequencing technology that has been applied to screening cancer and tissue variants, deep sequencing, and gene expression analysis, and more recently, it has been applied to DNA typing for human identification, estimating age, and detecting and differentiating body fluids. Body fluids are normally identified using color tests, microscopy, and immunochromatographic assays. Pyrosequencing is an NGS approach that has been applied to body fluid analysis. The pyrosequencing assays can detect one or several mixedbody fluids by analysis of their tissue-specific differentially methylated regions (tDMRs). Here, the process of designing pyrosequencing primers for forensic biology applications is described.

Reduced Graphene Oxide-Coated Silica Nanospheres as Flexible Enzymatic Biosensors for Detection of Glucose in Sweat

Noninvasive flexible electrochemical sensors for body fluid analysis are subject to strict requirements for sensitivity and detection limit. In this work, a three-dimensional (3D) flexible biosenso...

Metabolite Identification Using Infrared Ion Spectroscopy─Novel Biomarkers for Pyridoxine-Dependent Epilepsy.

Untargeted liquid chromatography–mass spectrometry (LC–MS)-based metabolomics strategies are being increasingly applied in metabolite screening for a wide variety of medical conditions. The long-standing “grand challenge” in the utilization of this approach is metabolite identification—confidently determining the chemical structures of m/z-detected unknowns. Here, we use a novel workflow based on the detection of molecular features of interest by high-throughput untargeted LC–MS analysis of patient body fluids combined with targeted molecular identification of those features using infrared ion spectroscopy (IRIS), effectively providing diagnostic IR fingerprints for mass-isolated targets. A significant advantage of this approach is that in silico-predicted IR spectra of candidate chemical structures can be used to suggest the molecular structure of unknown features, thus mitigating the need for the synthesis of a broad range of physical reference standards. Pyridoxine-dependent epilepsy (PDE-ALDH7A1) is an inborn error of lysine metabolism, resulting from a mutation in the ALDH7A1 gene that leads to an accumulation of toxic levels of α-aminoadipic semialdehyde (α-AASA), piperideine-6-carboxylate (P6C), and pipecolic acid in body fluids. While α-AASA and P6C are known biomarkers for PDE in urine, their instability makes them poor candidates for diagnostic analysis from blood, which would be required for application in newborn screening protocols. Here, we use combined untargeted metabolomics–IRIS to identify several new biomarkers for PDE-ALDH7A1 that can be used for diagnostic analysis in urine, plasma, and cerebrospinal fluids and that are compatible with analysis in dried blood spots for newborn screening. The identification of these novel metabolites has directly provided novel insights into the pathophysiology of PDE-ALDH7A1.

Performance evaluation of automated cell counts compared with reference methods for body fluid analysis.

Cellular analysis of body fluids (BFs) can assist clinicians for the diagnosis of many medical conditions. The aim of this work is the evaluation of the analytical performance of the UF-5000 body fluid mode (UF-BF) analyzer compared to the gold standard method (optical microscopy, OM) and to XN-1000 (XN-BF), another analyzer produced by the same manufacturer (Sysmex) and with a similar technology for BF analysis. One hundred BF samples collected in K3EDTA tubes were analyzed by UF-BF, XN-BF and OM. The agreement was evaluated using Passing and Bablok regression and Bland-Altman plot analysis. The receiver operating characteristic (ROC) curves were selected for evaluating the diagnostic agreement between OM classification and UF-BF parameters. Comparison between UF-BF and OM, in all BF types, showed Passing and Bablok's slope comprised between 0.99 (polymorphonuclear cells count, PMN-BF) and 1.39 (mononuclear cells count, MN-BF), the intercepts ranged between 26.47 (PMN-BF parameter) and 226.80 (white blood cell count). Bland-Altman bias was comprised between 7.3% (total cell count, TC-BF) and 52.9% (MN-BF). Comparison between UF-BF and XN-BF in all BF showed slopes ranged between 1.07 (TC-BF and PMN-BF) and 1.16 (MN-BF), intercepts ranged between 8.30 (PMN) and 64.78 (WBC-BF). Bland-Altman bias ranged between 5.8 (TC-BF) and 21.1% (MN-BF). The ROC curve analysis showed an area under the curve ranged between 0.9664 and 1.000. UF-BF shows very good performance for the differential counts of cells in ascitic, pleural and synovial fluids and therefore it is useful to screen and count cells in this type of BF.

Schirmer paper tear sampling of human eye diseases for paper spray mass spectrometry analysis

Paper spray mass spectrometry (PSMS) is a powerful analytical technique for direct analysis of human body fluids. Schirmer paper is commonly used to collect human tears in clinical examination. In this work, Schirmer paper was used for noninvasive sampling and storing of healthy and disease-infected human tears, and was then performed PSMS for direct tear analysis under both positive and negative detection modes. 24 healthy tear samples, 34 tear samples of meibomain gland dysfunction, 44 tear samples of senile cataract, and 32 tear samples of allergic conjunctivitis were investigated in this work. Screening potential biomarkers of different eye diseases were carried out by combining multivariate analysis methods. 41 positive ions and 53 negative ions were proposed to be potential biomarkers in this work. The capacity of Schirmer paper for storing tear sample at different temperatures was investigated. The present study shows that direct coupling Schirmer PSMS with multivariate analysis could be a simple, rapid, and in vivo method for screening the biomarkers from human tears that involved different eye diseases.