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.

Molecular imprinting technology is an emerging technique that achieves specific recognition of imprinted molecules by simulating the interactions between antibody and antigen or between enzyme and substrate. The core of this technology lies in the preparation of molecularly imprinted polymers （MIPs）. However， traditional preparation methods of MIPs face severe challenges due to drawbacks such as uneven morphology， limited conformational choices for molecular recognition， random and uncontrollable polymerization， and environmental safety hazards， making the innovation of synthesis methods urgent. In recent years， with the proposal of green chemistry concepts and the development of green synthesis methods， the preparation technology of MIPs has gradually transitioned towards resource-saving and environment-friendly directions. The preparation of green molecularly imprinted polymers （GMIPs） aims to replace traditional methods by reducing the use of solvents and the generation of waste liquids during the synthesis process， employing safe and non-toxic reagents and solvents， and developing efficient synthesis methods to improve energy efficiency. Green solvents such as water， supercritical carbon dioxide， deep eutectic solvents， and ionic liquids are used to replace organic solvents in the synthesis of traditional MIPs. Functional monomers with biocompatibility and environmental friendliness， including chitosan， cellulose， itaconic acid， dopamine， and cyclodextrin， have found increasing applications in the preparation of MIPs. In addition， the preparation technology of MIPs is gradually transitioning towards resource conservation and environmental friendliness. The development of novel synthesis methods such as green precipitation polymerization， microwave-assisted synthesis， supercritical fluid technology， ultrasound-assisted polymerization， and computer simulation-assisted design and characterization has promoted the popularity of GMIPs preparation methods. These novel preparation methods significantly improve the functionality and environmental compatibility of MIPs by precisely regulating reaction conditions， reducing energy consumption， and minimizing harmful by-products. They not only optimize the synthesis efficiency of MIPs， but also provide new ideas for solving the bottlenecks of traditional methods in morphology control and large-scale production. GMIPs， with their high selectivity， stability， and tunability， have shown breakthrough applications in multiple frontier fields. For example， in environmental monitoring， GMIPs are applied to detect heavy metal ions （such as lead and arsenic）， organic pollutants （such as pesticides and antibiotics）， and explosives in aqueous environments. In the field of food safety analysis， GMIPs enable efficient enrichment and detection of trace pollutants （such as pesticide residues， veterinary drugs， and mycotoxins） in food matrices， significantly outperforming traditional methods. In biomedical applications， GMIPs are developed as drug controlled-release systems， biomarker detection platforms， and targeted therapeutic carriers. In addition， the efficient performance of GMIPs in sample pretreatment （such as solid-phase extraction） further reduces analysis costs and reduces reliance on organic solvents. This paper reviews the novel preparation methods of GMIPs and their applications in environmental monitoring， food safety， and biomedicine in recent years， and provides an outlook on the development of GMIPs.

Molecularly imprinted technology （MIT） represents an advanced synthetic strategy that emulates biological recognition mechanisms， such as antigen-antibody or enzyme-substrate interactions， by creating three-dimensional cavity-like structures through the directional assembly of functional monomers around a template molecule. This process generates spatial and functional complementarity， enabling highly selective recognition of target species. Molecularly imprinted polymers （MIPs）， often described as “synthetic antibodies”， overcome the intrinsic limitations of natural biomolecules by offering superior selectivity， robustness， cost-effectiveness， and structural tunability. These features position MIPs as promising alternatives to natural antibodies in targeted sensing and drug delivery， with broad applications across biomedical， environmental， and pharmaceutical domains， including pollutant detection， and food safety monitoring. Despite substantial progress， key challenges remain， such as uneven imprinting layers， template residue， and limited aqueous compatibility in macromolecular imprinting. Furthermore， issues of industrial scalability， unclear recognition mechanisms， and insufficient integration with emerging fields such as microfluidics and artificial intelligence have hindered large-scale translation. In recent years， our research team has systematically advanced MIT through a tri-dimensional strategy encompassing high-throughput monomer screening， mechanistic elucidation of molecular recognition， and directional assembly of functional units. By establishing a standardized monomer library and integrating molecular dynamics simulations， we achieved precise material design under complex conditions. Through process optimization and material innovation， we developed a highly efficient solid-phase surface imprinting method that enables the fabrication of smart MIPs with stimuli-responsive properties （e.g.， temperature and pH）. These MIPs exhibit markedly enhanced binding affinity， with equilibrium dissociation constant （K_D） reaching 10^-12 mol/L， over four orders of magnitude higher than those of non-imprinted polymers （NIPs）. Building on these advances， we established cross-disciplinary application platforms， including affinity-based protein separation and purification systems capable of efficient dual-enzyme cascade immobilization and inactivated enzyme renaturation. In the biomedical domain， we developed ultrasensitive biosensing methods achieving picogram-level detection of heart failure biomarkers and single-digit （≈5 cells/mL） detection of cancer cells in whole blood， extending these methods toward integrated tumor theranostics and microbial community regulation. This paper comprehensively summarizes our team’s recent innovations in the rational design， functionalized fabrication， and cross-disciplinary applications of MIPs， spanning biosensing， biocatalysis， and biomedical diagnostics/therapeutics， while contextualizing these within the latest global advances in biomedicine and catalysis. Looking forward， we identify three strategic research frontiers for next-generation MIT. （i） Smart responsive material systems： design MIPs capable of multi-stimuli responsiveness （e.g.， magnetic， photothermal， and pH cues） to enable programmable drug release， real-time signal monitoring， and dynamic feedback regulation. （ii） Quantitative modeling of dynamic recognition： establish multi-scale theoretical frameworks to elucidate coupling between cavity flexibility and target conformational dynamics， guiding structure optimization and function-oriented design of adaptive MIPs. （iii） Integrated intelligent theranostic platforms： integrate microfluidics and biomimetic recognition modules into closed-loop systems capable of biomarker detection， targeted delivery， and real-time therapeutic feedback， bridging the gap between in vitro sensing and in vivo precision intervention. Synergistic advancement along these trajectories will empower MIT to transcend its role as a “static recognition material” and evolve into an intelligent， adaptive， and systematic biomedical platform. Such evolution will accelerate the translation of MIT innovations from laboratory to clinic and industry， propelling progress in personalized medicine， point-of-care diagnostics， and synthetic biology， and yielding profound scientific and societal impact.

Drugs play an indispensable role in the fields of medicine， agriculture， and animal husbandry. However， their long-term and improper use may lead to drug residues in food， the environment and organisms， posing a potentially serious threat to human health and the ecological environment. For instance， antibiotic residues may induce bacterial resistance， pesticide residues may cause neurotoxicity， and hormone drugs may interfere with the endocrine system. Therefore， developing sensitive and accurate detection methods for drug residues has become an important prerequisite and current hot topic in drug research. Meanwhile， the complicated matrices and low contents of the residues make it necessary for the widely used chromatography/mass spectrometry （MS） determination technologies to be coupled with efficient sample pretreatment procedures. Molecularly imprinted solid-phase microextraction （MI-SPME） technology combines the rapidity， high efficiency and solvent-free characteristics of SPME， and the specific recognition and selective adsorption capabilities of molecularly imprinted polymers （MIPs）， and shows significant advantages in the highly selective separation and enrichment of drug residues in complex samples. In recent years， the MI-SPME technology has become a research hotspot in the field of drug residue detection.This work systematically reviews the research progress since 2019 on the application of MI-SPME coupled with chromatography/MS in drug residue detection across food safety， environmental monitoring and biomedical fields. First， this work introduces in detail on the working principle and operation process of SPME technology. SPME achieves efficient enrichment of target analytes through the selective adsorption of the stationary phase-coated fibers， offering simplicity， speed， minimal solvent use， and compatibility with analytical instruments such as chromatography/MS.Next， the review focuses on elaborating the preparation methods and new technologies and strategies of MIPs. The traditional methods for preparing MIPs mainly include free radical polymerization， in-situ polymerization and sol-gel methods. However， traditional MIPs have defects such as template leakage risk， limited binding ability， and irregular material morphology， which restrict the application range. To this end， researchers have developed a series of novel preparation technologies and strategies， such as surface imprinting， nanoimprinting， dummy template imprinting， multi-template imprinting， multifunctional monomer imprinting and stimulus-response imprinting. These technologies and strategies have significantly enhanced the recognition and enrichment ability of MIPs for trace drug residues in complex samples by optimizing their structures and performances.To meet the requirements of different sample types and analytical instruments， MI-SPME media need to be designed into specific technical configurations through chemical or physical methods. This review summarizes six different MI-SPME device modes： MIPs-coated fiber SPME， MIPs in-tube SPME （IT-SPME）， MIPs stir bar sorptive extraction （SBSE）， MIPs dispersive SPME （DSPME）， MIPs thin-film SPME （TFME）， and MIPs in-tip SPME. Each mode offers unique advantages for the separation， enrichment and determination of drug residues in real samples. For example， the coated fiber SPME is simple to operate and suitable for direct immersion or headspace extraction of liquid samples； IT-SPME features miniaturization and automation， with excellent compatibility with chromatographic and mass spectrometric systems； DSPME achieves efficient separation and enrichment by dispersing adsorbents directly into sample solutions.Then， the applications of MI-SPME in the fields of food safety， environmental monitoring and biological medicine are summarized， highlighting typical research examples. In the field of food safety， MI-SPME can be used to detect pesticide residues， veterinary drug residues， and drugs for human use in fruits， vegetables， animal meats and dairy products. In environmental monitoring， it can be used for the detection of drug residues in aqueous environments and soil. In the field of biological medicine， it can be used for the analysis of drug residues in biological samples such as plasma， urine， and serum.Although the MI-SPME technology has shown great potential in drug residue detection， it still faces some challenges. For example， the preparation process of MIPs needs to be further optimized to improve their selectivity and stability； the development and application of new materials （such as graphene， metal-organic frameworks） for composite MIPs still need to solve problems such as high cost and complex processes； the integration of MI-SPME technology and automated equipment is also a bottleneck and important direction for future development. Looking ahead， with the advancement of green chemistry principles and point-of-care testing technologies， MI-SPME is expected to play an even greater role in drug residue detection. It will provide more efficient and precise technical support for food safety， environmental monitoring， and biomedical research.