Multiple sclerosis （MuS） is a chronic， inflammatory， demyelinating disease of the central nervous system， with a globally increasing prevalence. Its pathogenesis involves complex interactions among immune dysregulation， genetic predisposition， and environmental factors. These contribute to a wide spectrum of clinical manifestations， posing significant challenges for both diagnosis and treatment. Metabolomics， the comprehensive analysis of small-molecule metabolites， has emerged as a powerful approach to elucidate MuS pathophysiology and identify potential biomarkers. In particular， alterations in amino acid and lipid metabolism are closely associated with inflammation， myelin damage， neurotransmitter imbalance， and immune activation. This review summarizes recent advancements in the application of chromatography-mass spectrometry techniques to MuS biomarker research. Key technologies include liquid chromatography-tandem mass spectrometry （LC-MS/MS） for analyzing metabolites in biological fluids， high resolution mass spectrometry （HRMS） for precise metabolite identification， gas chromatography-mass spectrometry （GC-MS） for profiling volatile compounds， and matrix-assisted laser desorption ionization-time of flight mass spectrometry （MALDI-TOF MS） for mapping spatial metabolite distributions in tissues. Metabolomic analyses of MuS patient samples have revealed significant disruptions in amino acid metabolism. For instance， reduced arginine levels and elevated asymmetric dimethylarginine levels in cerebrospinal fluid suggest vascular dysfunction. Altered tryptophan metabolism， including altered levels of kynurenic acid and 5-hydroxytryptophan， reflects neurotransmitter imbalances. Increased pyroglutamic acid levels indicate oxidative stress. Lipid metabolism is also markedly perturbed in MuS. Changes in palmitic acid levels affect cell membrane integrity， while alterations in sphingolipids， key components of myelin， are linked to demyelination. Elevated oxysterols correlate with neuroinflammation and immune dysregulation. Additionally， systemic lipid changes， such as reduced low-density lipoprotein and altered high-density lipoprotein cholesterol levels， have been associated with disease activity and progression. Due to their high sensitivity， resolution， and throughput， chromatography-mass spectrometry techniques are well-suited for detecting these metabolic alterations. Representative studies demonstrate the utility of LC-MS/MS in detecting amino acid perturbations in plasma and cerebrospinal fluid （CSF）， GC-MS in identifying lipid abnormalities in serum， HRMS in generating detailed brain tissue metabolite profiles， and MALDI-TOF MS in visualizing lesion-specific metabolic distributions. These findings have led to the identification of promising biomarker candidates. For instance， decreased arginine may indicate endothelial dysfunction， while elevated oxysterols may serve as markers of neuroinflammatory activity. Such biomarkers hold potential for facilitating early diagnosis， disease monitoring， and personalized treatment strategies. Metabolomics via chromatography-mass spectrometry technologies has significantly advanced our understanding of MuS pathophysiology. Amino acid dysregulation affects neurotransmitter synthesis and immune modulation， while lipid imbalances impair myelin integrity and cellular signaling. These insights provide a foundation for the development of metabolite-based diagnostic tools and therapeutic interventions. Nonetheless， several challenges remain. MuS exhibits high heterogeneity， and metabolomic data are complex and variable. Improved biomarker specificity and standardization are needed for clinical application. Technological advances in chromatography-mass spectrometry resolution， along with standardized protocols， will be essential. Large-scale clinical validation across MuS subtypes is also critical. Integrating metabolomics with genomics and environmental factors may enhance biomarker reliability and elucidate individual disease trajectories. In conclusion， this review highlights the crucial role of chromatography-mass spectrometry-based metabolomics in MuS research. By unraveling the metabolic underpinnings of inflammation and demyelination， it provides valuable insights into disease mechanisms and introduces novel avenues for early diagnosis and targeted therapy. Collaborative research efforts and methodological rigor will be key to translating these discoveries into clinical impact.

Phosphatidylcholine （PC） and lysophosphatidylcholine （LPC） homologues are closely associated with coronary atherosclerosis. Accurate determination of their contents can provide an important basis for the clinical diagnosis and prognosis of coronary artery disease （CAD）. In this study， an analytical method based on liquid chromatography-tandem mass spectrometry was established， which enabled the simultaneous and accurate determination of 30 PC and LPC homologues using only 10 μL of human serum. Methanol-acetonitrile-methyl tert-butyl methyl ether-water was used as the extraction system， and an XBridge C18 column was selected as the stationary phase. The mobile phase consisted of an acetonitrile-water mixture （1∶1， volume ratio） and isopropanol， both containing 7.5 mmol/L ammonium formate and 0.15% （volume ratio） formic acid， and gradient elution was adopted for separation. Detection was performed using an electrospray ionization source in the positive ion mode with multiple reaction monitoring. Method validation results showed that the method exhibited a good linear relationship， with an average linear correlation coefficient of ≥0.999 7 over a linear range of 0.125-100 μg/mL. The limits of detection and limits of quantification were 0.01-1.94 μg/mL and 0.03-6.48 μg/mL， respectively. The recoveries ranged from 85.4% to 114.3%， while the intra-day precision and inter-day precision were no more than 4.6% and 12.6%， respectively. Serum samples from 110 clinical volunteers who underwent coronary angiography were determined using this method. The average population concentration of PC homologues was 526.80 μg/mL， and that of LPC homologues was 73.67 μg/mL. Spearman correlation analysis revealed that PC and LPC homologues were closely correlated with the severity of CAD， as well as with related clinical biochemical and lipid metabolism indicators， suggesting that they could serve as potential CAD-related metabolites in clinical practice. Designed to meet clinical analysis needs， this method features small serum sample volume， simple operation， and excellent response. It can efficiently determine 30 PC and LPC homologues in human serum， providing an important reference for exploring the association between these two lipid classes and CAD， as well as the translational application of related biomarkers.

To promote the standardization and harmonization of glycated hemoglobin A1c （HbA1c） testing results in medical laboratories across Beijing， we established a reference method for HbA1c. This method participated in the International Comparison Program for HbA1c Reference Laboratories organized by the European Reference Laboratory Network for HbA1c to validate its accuracy. The experimental samples consisted of HbA1c network reference laboratory proficiency testing samples imported annually from the Netherlands， including six calibrators （A-F）， ten intercomparison samples， several quality control materials， and additional auxiliary samples with International Federation of Clinical Chemistry and Laboratory Medicine （IFCC）-assigned values. The pre-treatment process involved digesting samples with protein endopeptidase Glu-C. The experimental samples were removed from the -80 ℃ freezer and allowed to reach room temperature. Subsequently， 50 μL of Glu-C （mass concentration： 200 μg/mL） was added to each sample vial at a ratio of total hemoglobin to enzyme of 1 mg∶0.01 mg. The volume was then adjusted to a final volume of 500 μL with ammonium acetate solution （50 mmol/L， pH 4.3）. After thorough mixing， the samples were incubated at 37 ℃ for 18-20 h. Using mobile phases of methanol and 0.1% formic acid aqueous solution under gradient elution conditions， the detection of HbA1c in international samples was performed via high performance liquid chromatography-tandem mass spectrometry （HPLC-MS/MS）. A gradient elution mode was employed for liquid chromatography separation using a Shimadzu C18 column （50 mm×3 mm， 2.2 μm）. The injector temperature was maintained at 4-8 ℃， with a column temperature of 30 ℃. The flow rate was kept constant at 0.6 mL/min， with an injection volume of 5 μL and a total run time of 8 min. The MS detection was performed using electrospray ionization （ESI） in positive ion mode with multiple reaction monitoring （MRM）. The monitored ion pairs for the precursor and product ions of non-glycated and glycated N-terminal hexapeptides are m/z 348.2/237.2 and m/z 429.2/245.2， respectively. The linearity was evaluated by performing regression analysis. The HbA1c （mmol/mol） quantification in unknown samples was achieved by performing linear regression using Analyst 1.6.2 software. Peak areas were integrated， with the abscissa （X-axis） representing the known concentration ratio of HbA1c to hemoglobin A0 （HbA0）， and the ordinate （Y-axis） representing the average peak area ratio of glycated to non-glycated hexapeptides. Both glycated and non-glycated hexapeptides eluted within 3 min， with linear correlation coefficients ranging from 0.999 6 to 0.999 8. The quality control （QC） materials （≥3 types） annually provided by the IFCC were analyzed. Since each QC material in every shipment typically consists of two replicated vials， enzymatic digestion was performed in two separate batches. For each batch， five parallel samples were processed， followed by triplicate injections of each sample. Intra-assay and total coefficients of variation （CV） were calculated. The intra-assay coefficients of variation （CVs） were 0.35%-2.20%， and the total CVs were 0.83%-2.39%. From 2018 to 2024， IFCC compared individual laboratory results with the overall median， calculating proportional bias （slope） and systematic bias （intercept） based on linear regression. Our laboratory’s combined statistical test value （computed from slope and intercept） ranged from 0.1 to 3.0. The systematic bias ranged from -0.69 to 1.27， and the proportional bias ranged from -0.009 to 0.021. The residual values from all testing points in the 2024 proficiency testing （PT） program were evenly distributed around zero. Furthermore， the magnitude of residual deviations from zero was relatively small compared to those observed across the 15 participating laboratories， demonstrating satisfactory consistency in our laboratory’s analytical results. The established HbA1c reference method demonstrated robust performance， achieving satisfactory results in IFCC international comparisons from 2018 to 2024.

Steroid hormones play a critical role in maintaining pregnancy and supporting fetal development. Accurate quantification of these hormones is essential for evaluating the endocrine status during pregnancy. While chemiluminescence immunoassay （CLIA） is widely used in clinical practice in China， it has inherent methodological limitations. In contrast， liquid chromatography-tandem mass spectrometry （LC-MS/MS） has been internationally recognized for its superior analytical performance but remains underutilized in Chinese obstetric practice. Moreover， systematic evaluations comparing these two methods in pregnant women are still lacking. This study aimed to develop and validate an isotope-dilution LC-MS/MS method for the simultaneous quantification of four key steroid hormones， including cortisol， dehydroepiandrosterone sulfate （DHEAS）， testosterone， and 17-hydroxyprogesterone （17-OHP）. In addition， a consistency analysis was conducted between LC-MS/MS and CLIA among pregnant women. Method validation followed international bioanalytical guidelines， evaluating linearity， limits of quantification （LOQs）， recovery， and precision. Serum samples from 94 pregnant women were collected at Guangdong Women and Children Hospital between January 2022 and December 2023， and were analyzed using both LC-MS/MS and CLIA. Method comparison was performed using paired t-tests， Pearson correlation， Bland-Altman plots， and Passing-Bablok regression to assess concentration differences， correlation， and systematic biases between the two methods. In this study， the established LC-MS/MS method exhibited excellent performance， with linear coefficients of determination >0.999， LOQs of 0.008-0.137 ng/mL， spiked recoveries of 92.1%-110.9%， and intra-assay relative standard deviations （RSDs） of 3.2%-9.0%， meeting the requirements for clinical detection. In a cohort of 94 pregnant women， paired t-tests revealed significant differences in hormone concentrations measured by LC-MS/MS and CLIA （all P<0.001）. Specifically， LC-MS/MS yielded significantly lower values for cortisol （64.31 vs. 120.60 ng/mL） and DHEAS （532.44 vs. 1 612.1 ng/mL）， but higher values for testosterone （1.10 vs. 0.88 ng/mL） and 17-OHP （2.00 vs. 1.07 ng/mL）. Bland-Altman analysis further revealed obvious negative proportional biases for cortisol and DHEAS， with bias values of -56.29 ng/mL and -1 079.68 ng/mL， respectively. Additionally， the biases increased with the increase of concentration. In contrast， testosterone and 17-OHP showed positive biases， with bias values of 0.22 ng/mL and 0.89 ng/mL， respectively. The two methods showed extremely strong positive correlations in the detection of the four hormones （P<0.001， r=0.819-0.974）， among which the correlation of testosterone detection results was the highest （r=0.974）. In the Passing-Bablok regression analysis， the consistency regression equation for cortisol was C_LC-MS/MS=-3.58+0.57C_CLIA. The confidence interval （CI） of the slope did not include 1， indicating obvious proportional bias. The consistency regression equation for DHEAS was C_LC-MS/MS=-59.77+0.38C_CLIA. The CIs of the intercept and slope did not include 0 and 1， respectively， suggesting the existence of fixed and proportional biases. The consistency regression equation for testosterone was C_LC-MS/MS=-0.05+1.30C_CLIA. The CIs of the intercept and slope did not include 0 and 1， respectively， indicating the existence of fixed and proportional biases. In addition， the differences increased with the increase of concentration. For 17-OHP， the regression equation was C_LC-MS/MS=0.10+1.75C_CLIA. Though the intercept was not statistically significant， the slope deviated significantly from 1， indicating a proportional bias. Additionally， LC-MS/MS values were significantly higher， and the difference increased with rising concentration. In conclusion， the established LC-MS/MS method offers high sensitivity， precision， and accuracy for the simultaneous quantification of multiple steroid hormones. The method reliably measured cortisol， DHEAS， testosterone， and 17-OHP levels in maternal serum. Additionally， our results revealed statistically significant differences between the two methods across all four hormones in pregnant women， with biases varying by concentration. These findings highlight the importance for clinicians to consider methodological differences when interpreting hormone test results during pregnancy， in order to improve the accuracy of endocrine assessment and reduce the risk of misdiagnosis due to analytical discrepancies. Future studies should incorporate large-scale maternal cohorts covering all stages of pregnancy and high-risk populations to further assess the clinical applicability of different methods and promote the standardization of LC-MS/MS for obstetric endocrine monitoring. In parallel， trimester-specific reference intervals should be established to support clinical interpretation and risk evaluation.

Accurate quantification of fat-soluble vitamin A （VA）， vitamin D （25（OH）D）， vitamin E （VE）， vitamin K （VK） is essential for health assessment and disease diagnosis. Liquid chromatography-tandem mass spectrometry （LC-MS/MS） plays a crucial role in the measurement of these vitamins due to its high specificity and sensitivity. However， the comparability and concordance of the detection results among different LC-MS/MS methods are still suboptimal. In this study， the analytical performance including linearity， limit of detection， limit of quantitation， precision， accuracy and carryover was evaluated according to CLSI C62 and the Suggestions on Clinical Application of Liquid Chromatography-Mass Spectrometry. Aliquots of 40 patient samples were collected from August to October 2022 from the Second Xiangya Hospital， Central South University. These fat-soluble vitamins were measured using three LC-MS/MS methods. Passing-Bablok regression， Bland-Altman plots and concordance correlation coefficient （CCC） were performed to compare the differences among three methods. The consistency of the results before and after recalibration with a unified calibrator was evaluated. The results showed that the total CVs for the three mass spectrometry kits were 2.7%-10.1%， and the recoveries for all kits ranged from 88.8% to 109.2%， indicating that their detection performance met the requirements for clinical application. Concordance correlation analysis showed that two of the three methods had substantial agreement in vitamin D testing （CCC： 0.938）， while the CCCs for other methods ranged from 0.322 to 0.853. After recalibration with a unified calibrator， except for vitamin K， the CCCs for the results of the three methods ranged from 0.918 to 0.983. In conclusion， the performance validation results of three LC-MS/MS methods for fat-soluble vitamins meet clinical requirements. The consistency among the three methods was poor， but using a unified calibrator significantly improved the consistency of these methods. The study provides recommendations for the standardization of clinical fat-soluble vitamin testing， thereby contributing to improved accuracy and consistency of results. This study will provide more reliable evidence for clinical diagnosis and treatment.

Accurate and reliable analytical methods are fundamental to ensuring the validity and reproducibility of scientific results， particularly in research involving trace-level contaminants in biological samples. While standardized methods regulated by official guidelines are commonly used in certified laboratories， research laboratories often rely on in-house or self-developed non-standard methods tailored for specific studies. These methods， however， frequently lack harmonized validation criteria， especially regarding accuracy evaluation. Traditionally， method accuracy is assessed through single performance indicators such as recovery， relative standard deviation （RSD）， or bias. These indicators， although useful， may vary widely in their interpretation and offer limited insight into overall method performance， particularly when comparing between laboratories or over different concentration ranges. To address these limitations， the Société Française des Sciences et Techniques Pharmaceutiques （SFSTP） introduced the accuracy profile approach. This method integrates both trueness and precision using a statistical model to generate β-expectation tolerance intervals， allowing a visual and comprehensive representation of whether an analytical method meets predefined acceptance criteria across multiple concentration levels. Unlike traditional evaluations， which may obscure marginal performance failures， the accuracy profile provides a single， unified framework that simplifies interpretation and decision-making. In this study， we applied the SFSTP accuracy profile approach to validate a high performance liquid chromatography-tandem mass spectrometry （HPLC-MS/MS） method for quantifying 20 urinary phenols. Method performance was assessed at three concentration levels （low， medium， and high） and the results were compared with conventional validation methods. The intra-batch RSD values ranged from 2.8% to 10.7%， and inter-batch RSD values ranged from 3.3% to 14.4%. The pooled intermediate precision RSD ranged from 4.9% to 16.6%， indicating acceptable reproducibility. Relative errors were between -25.3% and 13.0%， According to traditional evaluation using single parameters， the accuracy of all 20 phenol measurements met standard criteria. However， accuracy profile analysis revealed that only 13 phenols， such as bisphenol AF and bisphenol B， had β-expectation tolerance intervals entirely within the ±30% acceptance limits across all tested concentration levels. The remaining seven phenols， including benzylparaben and benzophenone-8， exceeded acceptable limits at low or medium concentrations， suggesting areas for method optimization. In conclusion， this study demonstrates that the HPLC-MS/MS method provides reliable quantitative results for the majority of tested urinary phenols. More importantly， the SFSTP accuracy profile offers a superior alternative to conventional validation methods by combining accuracy parameters and risk analysis into a coherent， statistically sound framework. This approach enables researchers to clearly identify the strengths and weaknesses of analytical methods without increasing experimental complexity or cost. Its advantages in standardization， interpretability， and decision-making support its broader adoption for validating non-standard methods in research and applied laboratories.

Neonatal sepsis remains a leading cause of morbidity and mortality among newborns worldwide. Despite advances in neonatal care， early diagnosis of sepsis remains challenging due to the lack of sensitive and specific biomarkers. While serum-based indicators have been widely studied， lipid metabolism in cerebrospinal fluid （CSF） remains relatively underexplored， limiting our understanding of central nervous system involvement （CNS） in the early stages of neonatal sepsis. This study aimed to systematically investigate lipid metabolic alterations in both serum and CSF samples from neonates with confirmed sepsis and to identify potential lipid biomarkers for early diagnosis. Seventeen neonates with blood culture-positive sepsis and seventeen controls with negative blood culture results were enrolled from the Neonatal Intensive Care Unit of Guangdong Women and Children Hospital （Women and Children’s Hospital， Southern University of Science and Technology） between February 2020 and August 2023. Paired serum and CSF samples were collected and analyzed using targeted lipidomics based on liquid chromatography-tandem mass spectrometry （LC-MS/MS）. Univariate analyses， including Student’s t-tests and Mann-Whitney U tests， were applied to identify statistically significant differences in lipid levels between groups. Multivariate analyses， including principal component analysis （PCA） and orthogonal partial least squares discriminant analysis （OPLS-DA）， were employed to further evaluate group separation and identify discriminatory lipid species. Pathway enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes （KEGG） database， and candidate biomarkers were selected using the Boruta feature selection algorithm and evaluated for diagnostic performance using receiver operating characteristic （ROC） curve analysis. A total of 322 lipid metabolites were identified in serum， with cholesteryl esters （CE）， triacylglycerols （TAG）， and phosphatidylcholines （PC） being the most abundant lipid classes. In the sepsis group， levels of nearly all lipid subclasses were significantly decreased compared to controls （P<0.05）， except for TAG and diacylglycerols （DAG）， which were not significantly altered. In CSF， 300 lipid species were detected， dominated by CE， PC， and phosphatidylethanolamines （PE）. Significantly reduced levels of PE， ceramides （Cer）， and lyso phosphatidylethanolamines （LPE） were observed in septic neonates （P<0.05）. PCA plots demonstrated tight clustering of quality control （QC） samples， indicating high analytical reproducibility and stable instrument performance. In serum， PCA accounted for 66.1% of total variance， showing preliminary group separation that was further confirmed by OPLS-DA （R²Y=0.601， Q²Y=0.271）， which identified 107 significantly downregulated lipid metabolites. Similarly， CSF PCA explained 75.7% of the variance， and OPLS-DA （R²Y=0.579， Q²Y=0.368） revealed 34 significantly downregulated lipid metabolites. Pathway enrichment analysis （FDR-P<0.05， pathway impact>0.10） showed that glycerophospholipid metabolism was the most significantly enriched pathway in both serum and CSF， followed by ether lipid and sphingolipid metabolism in serum. Key shared metabolites included PE（42：9）， PC（38：0）， LPC（22：6）， and LPE（22：6）， while PS（40：6） and PI（40：4） were specific to serum. Notably， thirteen differential lipid species were consistently identified in both serum and CSF， among which LPE（18：2）， ePE（36：4）， and Cer（d18：1/25：0） exhibited significant positive correlations between the two fluids （Pearson r=0.369-0.382， P<0.05）， suggesting potential trans-barrier lipid communication or shared regulatory mechanisms. Boruta-based machine learning analysis identified LPC（28：1）， LPE（18：2） and ePE（36：4） in serum as candidate biomarkers. These exhibited excellent diagnostic performance， with area under the curve （AUC） values of 0.96， 0.94， and 0.94， respectively， sensitivities ranging from 82.4% to 88.2%， and specificities from 94.1% to 100%. In CSF， Cer（d18：1/26：0）， Cer（d18：1/25：0）， and Cer（d18：1/24：1） were identified as high-importance variables. These demonstrated diagnostic AUCs of 0.89， 0.91， and 0.80， with sensitivities between 88.2% and 100% and specificities ranging from 64.7% to 70.6%. In summary， this study provides the first integrated lipidomic profiling of serum and CSF in neonatal sepsis， highlighting a consistent disruption in lipid metabolism， particularly within the glycerophospholipid pathway. Serum lipid biomarkers show promise as non-invasive early screening tools， while CSF lipid alterations offer valuable insights into CNS involvement and potential early neuroinflammatory responses. These findings support the potential of lipid-based biomarkers in improving the precision and timeliness of neonatal sepsis diagnosis. Nevertheless， the relatively small sample size and single-center design may limit the generalizability of the results. Future multicenter studies with larger cohorts are warranted to validate these findings and support clinical translation into neonatal care.

Dry eye is characterized as a multifactorial disorder affecting the tear film and ocular surface， leading to symptoms of discomfort and visual disturbances， with the potential for ocular surface damage. It is among the most prevalent ocular surface disorders， with an estimated prevalence ranging from 5.0% to 50.0%， and an overall prevalence between 21.0% and 50.4% in China. Despite its high global prevalence， the fundamental mechanisms underlying the pathology of dry eye remain largely unexplored. Vitamins are crucial for maintaining ocular surface homeostasis， with vitamins A and E being physiologically present and essential for cell differentiation， development， and proper function. Deficiencies in these vitamins are frequently associated with dry eye， and systemic supplementation has been shown to benefit patients with low vitamin intake. Vitamins A and E may have potential clinical predictive value for the diagnosis and treatment of dry eye. In this study， a liquid chromatography-tandem mass spectrometry （LC-MS/MS） method was developed to simultaneously measure the concentrations of vitamins A and E in human tears. A Phenomenex Kinetex C18 column was employed for gradient elution at a flow rate of 0.4 mL/min. The mobile phase A consisted of a 0.1% formic acid aqueous solution， while mobile phase B comprised a 2 mmol/L ammonium acetate and 0.1% formic acid methanol solution. Positive atmospheric pressure chemical ionization in multiple reaction monitoring mode was utilized for MS/MS detection. The analytical method for vitamin A demonstrated a validated linear range of 5.00-300.00 ng/mL， with a limit of detection at 2.00 ng/mL. The spiked recoveries were between 98.3% and 104.7%， and intra- and inter-day precision ranged from 1.2% to 7.0%. Similarly， the method for vitamin E exhibited a validated linear range of 25.00-1 000.00 ng/mL， with a limit of detection at 6.00 ng/mL. The spiked recoveries ranged from 97.9% to 105.5%， and intra- and inter-day precision varied between 3.0% and 5.7%. Tear samples from five patients with dry eye and nine healthy volunteers were analyzed using this method. In the dry eye group， the average concentrations of vitamin A and vitamin E were 9.60 （5.13-12.54） ng/mL and 42.00 （31.75-128.00） ng/mL， respectively. In the healthy group， the average concentrations of vitamin A and vitamin E were 18.10 （12.46-21.69） ng/mL and 211.00 （181.00-459.75） ng/mL， respectively. Statistical differences in vitamin A and vitamin E levels between the dry eye group and the healthy group were identified using the Wilcoxon Mann-Whitney test （P<0.05）. This study introduces a straightforward and reliable LC-MS/MS method for the detection of tear VA and VE levels， while also investigating their association with dry eye. This offers a novel reference for understanding the potential risk factors associated with dry eye.

Copeptin， as a stable surrogate biomarker for arginine vasopressin （AVP）， plays an important role in the differential diagnosis of polyuria-polydipsia syndromes. Current guidelines recommend dynamic monitoring of copeptin levels during stimulation tests to assist in differentiating AVP deficiency （AVP-D） from primary polydipsia. Although these methods are well-established， they have certain limitations. Therefore， safer and more feasible stimulants with reliable effects are of clinical interest. Additionally， the currently available copeptin assay， which is based on time-resolved immunofluorescence assay， can be subject to interference from autoantibodies or hemolysis. This study aims to evaluate the effects of four common stimulants used in growth hormone function tests， namely levodopa， insulin， glucagon， and octreotide， on copeptin levels using a reliable liquid chromatography-tandem mass spectrometry （LC-MS/MS） method developed in our laboratory. A total of 62 subjects undergoing growth hormone function tests were retrospectively enrolled and stratified by stimulation type： levodopa （n=28）， insulin-induced hypoglycemia （n=7）， glucagon （n=20）， and octreotide （n=7）. Blood samples were collected at baseline， 30， 60， 90， and 120 min （for the glucagon stimulation test， samples were collected at 120 and 180 min） for growth hormone determination. Copeptin levels at each time point were measured using LC-MS/MS. The effects of stimulation and correlations were analyzed using the Wilcoxon paired signed-rank test， Mann-Whitney test， and Spearman correlation analysis. The results demonstrated that copeptin levels increased under levodopa stimulation by a maximum of 8.47-fold of baseline （p<0.000 1）， under insulin stimulation by a maximum of 5.85-fold of baseline （p=0.031 2）， under glucagon stimulation by a maximum of 1.43-fold of baseline （p<0.000 1）， and decreased under octreotide to 43% of baseline （p<0.05）. No significant correlation was observed between copeptin level changes and those in growth hormone levels. In the levodopa-stimulation group， the maximum value of copeptin in patients with AVP deficiency was significantly lower than that in non-AVP deficiency patients （p=0.000 2）， and the area under the receiver operating characteristic curve was 0.98 （95% confidence interval 0.94–1.00， p=0.002 1）. Our results demonstrate that levodopa and insulin can effectively stimulate copeptin secretion， whereas octreotide exhibits a suppressive effect. These findings offer important physiological insights into AVP regulation and indicate that certain GH stimulation agents may have extended utility in copeptin-based diagnostic strategies. The LC-MS/MS method for detecting copeptin has potential clinical value in the diagnosis of patients with AVP deficiency and can provide a new detection method for clinical practice. However， the relatively small sample sizes restrict the statistical power， and larger prospective studies are warranted.

Diabetic retinopathy （DR） is a common blinding eye disease caused by diabetes mellitus and is the leading cause of acquired vision loss in adults worldwide. DR is asymptomatic in its early stages， and patients often miss the optimal treatment window by the time they seek medical attention due to vision impairment. Traditional methods used for DR diagnosis have inherent limitations and are not conducive to large-scale rapid screening. Biomarkers can reflect the stage of the disease owing to their specificity and sensitivity， which is crucial for the early diagnosis of DR. In the present study， 142 potential literature-based biomarkers associated with DR were included in a knowledge-directed strategy. And metabolites with different physicochemical properties were chromatographically separated using a 100-mm Discovery HS F5 column. A pseudo-targeted metabolomics method based on ultra-high performance liquid chromatography-tandem mass spectrometry （UHPLC-MS/MS） that simultaneously scans positive and negative ions was established to improve analysis coverage and throughput. The method was validated using eight representative isotope-labeled internal standards as analytical targets. All isotope-labeled internal standards exhibited satisfactory linearities in both positive- and negative-ionization modes， with linear dynamic ranges spanning over three orders of magnitude and correlation coefficients （r²） above 0.995. Extraction recoveries ranged between 75% and 108% at three distinct concentration levels with relative standard deviations （RSDs） below 13%. Notably， 91% of the isotope-labeled internal standards exhibited intra-day precision with RSDs of less than 5% across both ionization modes. Similarly， 91% of the analytes demonstrated inter-day precision with RSDs of less than 10%， with all below 16.3%， indicating good method precision. The developed method was used to analyze 137 serum samples， including 40 DR-free patients with diabetes mellitus （NDR） and 97 patients with DR to investigate the practicality of the method. Quality control （QC） samples were used to evaluate the data， which revealed that the instrument was stable during the analytical sequence. Partial least squares discriminant analysis （PLS-DA） models were constructed to identify and differentiate between the metabolic profiles of the DR and NDR groups with the aim of providing a statistical basis for the classification and diagnosis of DR based on metabolic differences observed in the serum samples. The NDR group and DR groups of varying clinical grades were well separated. A total of 85 differential metabolites were identified between NDR and DR groups using nonparametric tests. Further analysis led to the selection of choline and 12-hydroxyeicosatetraenoic acid （12-HETE） as two markers that effectively distinguished the DR and NDR groups. In addition， the markers exhibited a good ability to distinguish between DR and NDR patients when used in combination. The pseudo-targeted metabolomics-based knowledge-directed method developed in this study provides a reference for screening and diagnosing DR.

Urothelial carcinoma （UC） is a globally prevalent malignancy lacking robust non-invasive biomarkers. Metabolic reprogramming is a recognized cancer hallmark. Untargeted metabolomics enables high-throughput and unbiased analysis of bodily fluids， offering a promising approach for discovering novel biomarkers in UC. This investigation employs untargeted metabolomic profiling to detect novel urinary biomarkers in UC cohorts. The analytical strategy prioritizes tumor-associated metabolic perturbations through pathway-centric characterization of dysregulated biochemical networks. This study systematically characterizes differential metabolites and associated pathway dysregulations in UC cohorts. The approach seeks to establish a reliable metabolic signature with diagnostic and prognostic value. The findings are expected to advance the development of novel clinical tools. UC biomarkers should optimally integrate preclinical identification， treatment response tracking， and precision-tailored interventions. This investigation provides a methodological framework for exploring cancer metabolism in UC. And it offers evidence-based insights to support translational research and precision medicine initiatives in oncology. This study was conducted at Beijing Chao-Yang Hospital， Capital Medical University， between January and December 2020. A total of 60 urine specimens were consecutively collected. They comprised 30 histologically confirmed UC patients and 30 healthy controls with normal urinalysis findings. Clinical data was prospectively collected via structured case report forms. It encompassed baseline demographics， comorbidities， anthropometric and behavioral factors， and UC pathological parameters. All urine samples were collected prior to invasive procedures. And they were labeled， snap-frozen in liquid nitrogen， and stored at -80 ℃ until analysis. Metabolic profiling was performed using a quadrupole-orbitrap high resolution mass spectrometer equipped with a heated electrospray ionization source. Mass spectrometric data processing was performed using Progenesis QI software. Data processing followed the following workflow： raw data import， spectral peak alignment， feature extraction， and deconvolution. The Progenesis QI software generated datasets containing retention time， peak intensity， and mass-to-charge ratios. Multivariate signal decomposition enabled independent resolution of adduct species， including protonated and sodium-adducted ions. Quality control measures included elimination of ion features demonstrating intra-batch coefficient of variation >15% across technical replicates. This rigorous preprocessing protocol ensured removal of unstable signals. And it preserved biologically relevant metabolic features for subsequent multivariate analysis. No statistically significant differences were observed in baseline clinical characteristics between UC and healthy control cohorts （P>0.05）. Untargeted metabolomic profiling was performed using liquid chromatography-tandem mass spectrometry （LC-MS/MS）. Principal component analysis （PCA） revealed no distinct cluster separation between groups. This result was potentially attributed to limited intergroup metabolic variations or restricted sample size. To enhance discriminatory capacity， supervised orthogonal partial least squares-discriminant analysis （OPLS-DA） was implemented for feature selection. This approach effectively addressed variable collinearity while minimizing non-biological noise interference. Differentially expressed metabolites were identified through variable importance in projection scores， fold change and adjusted P-values. Metabolic pathway analysis was conducted， incorporating pathway enrichment analysis. This multi-tiered analytical approach systematically prioritized UC-associated metabolic perturbations while controlling for confounding factors in specimen analysis. Supervised OPLS-DA was employed to identify differential metabolites and associated metabolic pathways. Significant urinary metabolic disparities were detected between UC patients and healthy controls. Alterations were observed in L-Histidine， N-Acetyltryptophan， 5′-methylthioadenosine， N-methylnicotinamide， L-octanoylcarnitine， 3-indolehydracrylic acid， N¹，N¹²-diacetylspermine， pantothenic acid and so on （P<0.05）. Pathway enrichment analysis revealed perturbations spanning amino acid metabolism， nucleotide biosynthesis， vitamin cofactor utilization， and carbohydrate processing. The histidine metabolism pathway demonstrated the highest topological impact. It was followed by the arginine biosynthesis pathway， arginine and proline metabolism pathway， and the tryptophan catabolism pathway. Future validation in larger cohorts and mechanistic studies is warranted to confirm their clinical utility. The aberrant pathways may offer novel biomarkers and therapeutic targets， particularly for patients resistant to conventional therapies.

As a clinical sample， serum is widely used in disease research due to the minimally invasive nature of its collection and easy accessibility. Exosomes in serum not only carry various bioactive substances such as proteins and nucleic acids but also participate in intercellular communication， which is closely associated with the development of multiple diseases. As one of the most critical post-translational modifications， protein phosphorylation dynamically regulates cellular signaling networks and participates in disease pathogenesis. However， due to the low abundance of exosomes in serum and the fact that phosphoproteins constitute only 1%–2% of the total proteome， direct analysis of exosomal phosphoproteins from serum faces significant challenges. The specific expression of phosphoproteins in exosomes provides novel perspectives for disease diagnosis. In this study， magnetic bifunctional nanoparticles （MagphTi⁴⁺） based on 2-trifluoromethyl-4-aminobenzoic acid and Ti⁴⁺ were synthesized， which anchor the exosome bilayer membrane through the hydrophobic interactions of 2-trifluoromethyl-4-aminobenzoic acid and the electrostatic interactions of Ti⁴⁺， and the magnetic responsiveness ensures the isolation of exosomes. Simultaneously， the enrichment of phosphopeptides was achieved by the chelation between Ti⁴⁺ and phosphate groups. MagphTi⁴⁺ was characterized by cold field scanning electron microscopy， thermogravimetric analysis， Fourier transform infrared spectroscopy， X-ray photoelectron spectroscopy and zeta potential measurement， demonstrating the successful synthesis and functional characteristics of MagphTi⁴⁺. The precise recognition and rapid separation of exosomes were validated by cold field scanning electron microscopy， transmission electron microscopy and sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Using β-casein as a standard phosphoprotein model， a magnetic solid-phase extraction （MSPE）-matrix-assisted laser desorption ionization-time of flight mass spectrometry platform was established， which demonstrated high selectivity （mass ratio of β-casein to bovine serum albumin was 1∶5 000） and sensitivity （detection limit was 0.4 fmol/μL） for phosphopeptide detection. Subsequently， the method was applied to saliva and nonfat milk samples； 11 phosphopeptides were identified in saliva and 20 were identified in nonfat milk， which demonstrates excellent enrichment capability for phosphopeptide detection in real samples. When applied to clinical serum samples， the method successfully achieved the extraction of exosomes in serum and enrichment of phosphopeptides with low abundance. This integrated approach provides a powerful tool for exosome capture and phosphopeptide enrichment from complex biological samples， showing significant potential for high-throughput phosphoproteomic analysis of exosomes from clinical serum and the screening of disease biomarkers. Further application of the method developed in this study holds promise for elucidating the mechanisms of exosome-mediated intercellular transmission of phosphorylation signaling， thereby identifying novel targets related to tumor metastasis and immune escape.

Drugs used to treat hematologic malignancies often exhibit narrow therapeutic windows， significant inter-individual variability， and high risks of drug-drug interactions， necessitating therapeutic drug monitoring （TDM） for individualized dosing. For patients requiring concomitant antifungal therapy due to infections arising from severe chemotherapy-induced myelosuppression， TDM can optimize plasma concentrations of both antineoplastic and antifungal agents. This concurrent optimization ensures anti-tumor efficacy while effectively mitigating the risk of invasive fungal infections， positioning TDM as a critical component of personalized management in hematologic malignancies. This study established and validated a rapid ultra-high performance liquid chromatography-tandem mass spectrometry （UHPLC-MS/MS） method for the simultaneous quantification of the antineoplastic agents selinexor （SEL） and venetoclax （VEN）， along with the antifungal agents voriconazole （VOR） and posaconazole （POSA） in human plasma. Chromatographic separation was achieved using a Kinetex^® XB-C18 column （50 mm × 3.0 mm， 2.6 µm） with a mobile phase consisting of methanol and 10 mmol/L ammonium acetate containing 0.1% formic acid， delivered at a flow rate of 0.5 mL/min under gradient elution conditions. The injection volume was 2 μL， and the total run time was 4.0 min. Detection employed an electrospray ionization source operating in positive ion mode with multiple reaction monitoring （MRM）. Following optimization of mass spectrometric parameters， the method underwent comprehensive validation. Calibration curves demonstrated excellent linearity （r>0.994） over the ranges of 0.04-1.48 μg/mL for SEL， 0.15-5.50 μg/mL for VEN， 0.29-11.77 μg/mL for VOR， and 0.15-6.05 μg/mL for POSA. Intra-day and inter-day precisions （RSDs） were ≤7.1% at all concentration levels. Extraction recoveries were ≥85.3%， demonstrating efficient and consistent sample processing. Method accuracy， determined by the percentage deviation of measured concentrations from nominal values， fell within the acceptable range of 87.4% to 109.0% across all QC levels， confirming the method’s trueness. The practical utility of the validated UHPLC-MS/MS method was demonstrated through its application to clinical specimens. We collected and analyzed 81 clinical samples from 30 patients with acute myeloid leukemia treated with the combination of SEL and VEN. Measured plasma concentrations of SEL in these patients ranged from 0.049 μg/mL to 0.646 μg/mL. Notably， significant inter-individual variability in the peak plasma concentration （C_max） of SEL was observed within the same treatment cycle for approximately 30% of the patient cohort. This study offers evidence-based support for personalized precision therapy in this patient population， which exhibits substantial inter-individual variability and complex drug-drug interactions in clinical practice.

Leukemia is a malignant tumor of the hematological system characterized by the uncontrolled proliferation of abnormal hematopoietic cells in the bone marrow. It often presents with anemia， bleeding tendency， infection risk and organ invasion. These clinical symptoms bring severe survival risks to patients. Although traditional chemotherapy regimens are effective in the treatment of some hematological malignancies， their efficacy is limited for elderly patients， those with high-risk genetic characteristics or comorbidities. In recent years， targeted drugs have revolutionized the treatment of leukemia. By selectively inducing tumor cell apoptosis， they have significantly improved the remission rate and survival prognosis of patients with multiple leukemia subtypes. Venetoclax is a B-cell lymphoma 2 （BCL-2） inhibitor and plays an important role in the clinical treatment of hematological malignancies， such as acute myeloid leukemia and chronic lymphocytic leukemia. In addition， it also shows potential efficacy in other hematological malignancies such as multiple myeloma and mantle cell lymphoma. Although the efficacy of venetoclax is remarkable， the individual differences in blood drug concentration are significant due to factors such as drug interactions， polymorphisms of metabolic enzymes， and liver and kidney function. Venetoclax exhibits significant inter-individual pharmacokinetic differences， the trough concentration is significantly correlated with the treatment response， and if the peak concentration exceeds the warning concentration， adverse reactions will be triggered. Clinical trials have reported a variety of adverse events associated with venetoclax， including neutropenia， tumor lysis syndrome， thrombocytopenia， infection， anemia， diarrhea， nausea， upper respiratory tract infection， cough and musculoskeletal pain. Therefore， to minimize the risk of adverse events in the clinical use of venetoclax as much as possible， it is necessary to reasonably guide its clinical dosage. Therapeutic drug monitoring can optimize individual dosing regimens by measuring the steady-state concentration in patients’ blood. This research aims to establish a rapid， sensitive and reliable ultra performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） method. This method is used for the quantitative determination of venetoclax in plasma， and its performance was validated. This method employs an electrospray ionization and multiple reaction monitoring （MRM） in the positive ion mode to detect venetoclax and its isotope internal standard venetoclax-d₈. Methanol was used for protein precipitation， C18 reversed-phase chromatographic column was used for liquid phase separation. Gradient elution was performed using acetonitrile and 0.1% formic acid aqueous solution as the mobile phases. The flow rate was 0.4 mL/min， the run time was 3.5 min， and the retention time of venetoclax was 1.95 min. The analysis time is short， facilitationg the rapid determination of clinical samples. Dosage escalation is commonly adopted in the treatment of venetoclax. In this study， a pretreatment approach involving extraction followed by dilution was used. This methodincreased the upper limit of quantification and expanded the linear range. The linear range of venetoclax was 50–10 000 ng/mL， r²>0.999. The method had good specificity. The intra-run precision and inter-run precision were 1.8%–4.5% and 2.7%–6.1%， respectively， the recoveries were 100.3%–102.9%， the matrix effects ranged from 88.0% to 111.0%， and the carryover was less than 20% of the minimum concentration of linear range. This method was applied to the therapeutic drug monitoring of venetoclax in acute myeloid leukemia （AML） patients， and the peak and trough concentrations of venetoclax were obtained for different patients to monitor their blood drug concentration. The above research results indicate that this method can accurately and robustly quantify venetoclax in human plasma， which helps address the drug monitoring needs of leukemia patients receiving venetoclax treatment and guide clinical personalizd therapy.

This study aimed to explore the application and pedagogical innovation of liquid chromatography-tandem mass spectrometry （LC-MS/MS） in undergraduate thesis training for medical laboratory science students. Using the development of 25-hydroxyvitamin D₂ （25（OH）D₂） and 25-hydroxyvitamin D₃ （25（OH）D₃） external quality assessment （EQA） samples as a teaching platform， an experimental teaching model driven by research tasks and clinical practice was established. The teaching design encompassed the entire workflow， including sample preparation， instrument operation， data processing， and result evaluation， enabling students to acquire hands-on experience with core LC-MS/MS techniques and quality control procedures. Through the implementation of the experimental project， students participated in EQA sample preparation， reference method-based quantification， homogeneity and stability assessments， and EQA result analysis， thereby gaining comprehensive exposure to the process from experimental design to result interpretation. The results demonstrated that the prepared EQA samples exhibited satisfactory homogeneity and stability， meeting the quality standards established by the China National Accreditation Service for Conformity Assessment （CNAS）. In the “2024 Beijing Serum Vitamin D EQA” activity， a total of 16 medical laboratory institutions in Beijing participated. Teaching practice revealed that this project significantly enhanced students’ comprehensive abilities in experimental design， instrument operation， data analysis， and quality assessment， while also fostering scientific thinking and teamwork. By introducing advanced analytical techniques into the undergraduate curriculum under the educational concept of “research-driven teaching and integration of industry and education”， this approach not only optimized course content and experimental procedures but also broadened students’ practical perspectives in clinical laboratory and research applications. This study provides a replicable teaching model for undergraduate laboratory education and offers valuable insights for promoting the integration of advanced analytical technologies into medical laboratory science training.