Probe Electrospray Ionization Mass Spectrometry Research Articles

Automated sample preparation for electrospray ionization mass spectrometry based on CLOCK-controlled autonomous centrifugal microfluidics.

We report a centrifugal microfluidic device that automatically performs sample preparation under steady-state rotation for clinical applications using mass spectrometry. The autonomous microfluidic device was designed for the control of liquid operation on centrifugal hydrokinetics (CLOCK) paradigm. The reported device was highly stable, with less than 7% variation with respect to the time of each unit operation (sample extraction, mixing, and supernatant extraction) in the preparation process. An agitation mechanism with bubbling was used to mix the sample and organic solvent in this device. We confirmed that the device effectively removed the protein aggregates from the sample, and the performance was comparable to those of conventional manual sample preparation procedures that use high-speed centrifugation. In addition, probe electrospray ionization mass spectrometry (PESI-MS) was performed to compare the device-treated and manually treated samples. The obtained PESI-MS spectra were analyzed by partial least squares discriminant analysis, and the preparation capability of the device was found to be equivalent to that of the conventional method.

Probe Electrospray Ionization Tandem Mass Spectrometry for the Detection and Quantification of Benzodiazepines.

Legally prescribed benzodiazepines (BZDs) and designer BZDs are widely misused and must be determined in multiple contexts (eg, overdose, drug-facilitated sexual assaults, or driving under the influence of drugs). This study aimed to develop a method for measuring serum BZD levels using probe electrospray ionization (PESI) mass spectrometry and an isotope dilution approach. A tandem mass spectrometer equipped with a probe electrospray ionization source in multiple reaction monitoring mode was used. Isotope dilution was applied for quantification using a deuterated internal standard at a fixed concentration for alprazolam, bromazepam, diazepam, nordiazepam, oxazepam, temazepam, zolpidem, and zopiclone. This method included designer BZDs: clonazolam, deschloroetizolam, diclazepam, etizolam, flualprazolam, flubromazepam, flubromazolam, meclonazepam, nifoxipam, and pyrazolam. Sample preparation was done by mixing 10 µL of serum with 500 µL of an ethanol/ammonium formate 0.01 mol/L buffer. Complete validation was performed, and the method was compared with liquid chromatography coupled with mass spectrometry (LC-MS/MS) and immunoassays (IC) by analyzing 40 real samples. The analysis time for identification and quantification of the 18 molecules was 2.5 minutes. This method was fully validated, and the limits of quantification varied from 5 to 50 mcg/L depending on the molecule. In the 40 real samples, 100% of molecules (n = 89) were detected by both LC-MS/MS and PESI-MS/MS, and regression analysis showed excellent agreement between the 2 methods (r2 = 0.98). On IC, bromazepam and zolpidem were not detected in 2 and 1 cases, respectively. PESI-MS/MS allows serum BZD detection and measurement. Given the isotope dilution approach, a calibration curve was not required, and its performance was similar to that of LC-MS/MS, and its specificity was higher than that of IC.

Plastic probe electrospray ionization mass spectrometry developed for rapid fingerprint profile of biological samples without pretreatment.

A triangular-shaped flat plastic substrate probe was prepared for direct electrospray ionization mass spectrometry (ESI-MS) for analysis of untreated chemical and biological samples including liquids (Met-Arg-Phe-Ala peptide, reserpine, and dodecyl aldehyde), solids (biological samples, traditional Chinese medicine), and powders (roasted coffee, rhizoma coptidis, lotus plumule, and Schisandra sphenanthera). Quantitative analysis of reserpine in water yielded a detection limit of 1ngmL-1, dynamic response range within 1-500ngmL-1, and linearity of signal response ˃0.9925. Compared to the conventional capillary ESI, this plastic probe ESI offers lower cost of analysis (US $0.0056 per probe), higher sensitivity, lower sample consumption, longer signal duration (>6min), better reproducibility, signal stability, and higher speed of analysis (<10s per sample, including sample loading). Overall, the results indicate the potential of ESI-MS based on flat plastic probes as a versatile method for simple, sensitive, and stable analysis of untreated biological sample analysis.

μ-PESI-based MS profiling combined with untargeted metabolomics analysis for rapid identification of red wine geographical origin.

The commercial value of red wine is strongly linked to its geographical origin. Given the large global market, there is great demand for high-throughput screening methods to authenticate the geographical source of red wine. However, only limited techniques have been established up to now. Herein, a sensitive and robust method, namely probe electrospray ionization mass spectrometry (μ-PESI-MS), was established to achieve rapid analysis at approximately 1.2 min per sample without any pretreatment. A scotch near the needle tip provides a fixed micro-volume for each analysis to achieve satisfactory ion signal reproducibility (RSD < 26.7%). In combination with a machine learning algorithm, 16 characteristic ions were discovered from thousands of detected ions and were utilized for differentiating red wine origin. Among them, the relative abundances of two characteristic metabolites (trigonelline and proline) correlated with geographical conditions (sun exposure and water stress) were identified, providing the rationale for differentiation of the geographical origin. The proposed μ-PESI-MS-based method demonstrates a promising high-throughput determination capability in red wine traceability.

New Diagnostic Modality Combining Mass Spectrometry and Machine Learning for the Discrimination of Malignant Intraductal Papillary Mucinous Neoplasms

BackgroundAn intraductal papillary mucinous neoplasm (IPMN) is a pancreatic tumor with malignant potential. Although we anticipate a sensitive method to diagnose the malignant conversion of IPMN, an effective strategy has not yet been established. The combination of probe electrospray ionization-mass spectrometry (PESI-MS) and machine learning provides a promising solution for this purpose.MethodsWe prospectively analyzed 42 serum samples obtained from IPMN patients who underwent pancreatic resection between 2020 and 2021. Based on the postoperative pathological diagnosis, patients were classified into two groups: IPMN-low grade dysplasia (n = 17) and advanced-IPMN (n = 25). Serum samples were analyzed by PESI-MS, and the obtained mass spectral data were converted into continuous variables. These variables were used to discriminate advanced-IPMN from IPMN-low grade dysplasia by partial least square regression or support vector machine analysis. The areas under receiver operating characteristics curves were obtained to visualize the difference between the two groups.ResultsPartial least square regression successfully discriminated the two disease classes. From another standpoint, we selected 130 parameters from the entire dataset by PESI-MS, which were fed into the support vector machine. The diagnostic accuracy was 88.1%, and the area under the receiver operating characteristics curve was 0.924 by this method. Approximately 10 min were required to perform each method.ConclusionPESI-MS combined with machine learning is an easy-to-use tool with the advantage of rapid on-site analysis. Here, we show the great potential of our system to diagnose the malignant conversion of IPMN, which would be a promising diagnostic tool in clinical settings.

Probe electrospray ionization mass spectrometry-based rapid diagnosis of liver tumors.

Prompt differential diagnosis of liver tumors is clinically important and sometimes difficult. A new diagnostic device that combines probe electrospray ionization-mass spectrometry (PESI-MS) and machine learning may help provide the differential diagnosis of liver tumors. We evaluated the diagnostic accuracy of this new PESI-MS device using tissues obtained and stored from previous surgically resected specimens. The following cancer tissues (with collection dates): hepatocellular carcinoma (HCC, 2016-2019), intrahepatic cholangiocellular carcinoma (ICC, 2014-2019), and colorectal liver metastasis (CRLM, 2014-2019) from patients who underwent hepatic resection were considered for use in this study. Non-cancerous liver tissues (NL) taken from CRLM cases were also incorporated into the analysis. Each mass spectrum provided by PESI-MS was tested using support vector machine, a type of machine learning, to evaluate the discriminatory ability of the device. In this study, we used samples from 91 of 139 patients with HCC, all 24 ICC samples, and 103 of 202 CRLM samples; 80 NL from CRLM cases were also used. Each mass spectrum was obtained by PESI-MS in a few minutes and was evaluated by machine learning. The sensitivity, specificity, and diagnostic accuracy of the PESI-MS device for discriminating HCC, ICC, and CRLM from among a mix of all three tumors and from NL were 98.9%, 98.1%, and 98.3%; 87.5%, 93.1%, and 92.6%; and 99.0%, 97.9%, and 98.3%, respectively. This study demonstrated that PESI-MS and machine learning could discriminate liver tumors accurately and rapidly.

Ultrafast Measurement of Metformin in the Clinical Setting Using Probe Electrospray Ionization Mass Spectrometry.

Metformin (MtF) is a treatment used for type 2 diabetes. Lactic acidosis (LA) is a frequent complication that can be either induced by or associated with elevated MtF plasma concentrations. When coupled with a mass spectrometry (MS) system, the probe electrospray ionization (PESI) method allows direct and rapid analysis of different types of matrices without pretreatment. In this study, we developed a PESI-MS method for the determination of MtF in plasma. We used a tandem mass spectrometer equipped with a PESI source in the reaction monitoring mode for the quantitation of MtF. MtF-d6 was chosen as the internal standard (IS), following an isotope dilution (ID) approach. The method was fully validated with six concentration levels (0.5-50 mg/L). The matrix effect was evaluated for each level, and the specificity was tested with a mix of potential co-medications. Using patient samples, the performance was compared with two classical LC-MS-MS and LC-diode array detector (DAD) methods used in external labs. Sample preparation consisted in mixing 10 µL plasma in 1,000 µL ethanol/ammonium formate buffer including MtF-d6 at a fixed concentration of 5 mg/L. The total run time was 0.31 min. ID gave satisfactory results of accuracy and precision (min-max: -12.1 to 15.8% and 1.0-17.1%, respectively). The matrix effect was fully corrected by the internal standard (bias < 1%). The specificity study also reported satisfactory results. Finally, in a representative group of 29 patients (55% with a concentration <5 mg/L, 38% with a concentration >5 mg/L and 7% not detected), we observed almost identical results when comparing LC-DAD and LC-MS-MS to PESI-MS (r2 > 0.99). We propose a specific, sensitive, accurate and ultrafast solution for the measurement of MtF in patient plasma, with no sample preparation or calibration curve building. This could be helpful in a core lab when rapid diagnosis of LA is needed.

Fast Classification of Thyroid Nodules with Ultrasound Guided-Fine Needle Biopsy Samples and Machine Learning

A rapid classification method was developed for the malignant and benign thyroid nodules with ultrasound guided-fine needle aspiration biopsy (FNAB) samples. With probe electrospray ionization mass spectrometry, the mass-scan data of FNAB samples were used as datasets for machine learning. The patients were marked as malignant (98 patients), benign (110 patients) or undetermined (42 patients) by experienced doctors in terms of ultrasound, the B-Raf (BRAF) gene, and cytopathology inspections. Pairwise coupling was performed on 163 ions to generate 3630 ion ratios as new features for classifier training. With the new features, the performance of the multilayer perception (MLP) classifier is much better than that with the 163 ions as features directly. After training, the accuracy of the MLP classifier is as high as 92.0%. The accuracy of the single-blind test is 82.4%, which proved the good generalization ability of the MLP classifier. The overall concordance is 73.0% between prediction and six-month follow-up for patients in the undetermined group. Especially, the classifier showed high accuracy for the undetermined patients with suspicious for papillary carcinoma diagnosis (90.9%). In summary, the machine learning method based on FNAB samples has potential for real clinical applications.

Rapid diagnosis of papillary thyroid carcinoma with machine learning and probe electrospray ionization mass spectrometry.

Frozen section examination could provide pathological diagnosis for surgery of thyroid nodules, which is time-consuming, skill- and experience-dependent. This study developed a rapid classification method for thyroid nodules and machine learning. Total 69 tissues were collected including 43 nodules and 26 nodule-adjacent tissues. Intraoperative frozen section was first performed to give accurate diagnosis, and the rest frozen specimen were pretreated for probe electrospray ionization mass measurement. By multivariate analysis of mass scan data, a series compounds were found downregulated in the extraction solution of papillary thyroid carcinoma (PTC), but some were found upregulated by mass spectrometry imaging. m/z 758.5713 ([PC[34:2] + H]+ ), m/z 772.5845 ([PC[32:0] + K]+ ), and m/z 786.6037 ([PC[36:2] + H]+ ) were firstly identified as potential biomarkers for nodular goiter (NG). Machine learning was employed by means of support vector machine (SVM) and random forest (RF) algorithms. For classification of PTC from NG, SVM and RF algorithms exhibited the same performance and the concordance was 94.2% and 94.4% between prediction and pathological diagnosis with positive and negative mass dataset, respectively. For the classification of PTC from PTC adjacent tissues, SVM was better than RF and the concordance was 93.8% and 83.3% with positive and negative mass dataset, respectively. With the identified compounds as training features, the sensitivity and specificity are 87.5% and 88.9% for the test set. The developed method could also correctly predict the malignancy of one medullary thyroid carcinoma and one adenomatous goiter (benign). The diagnosis time is about 10min for one specimen, and it is very promising for the intraoperative diagnosis of papillary thyroid carcinoma.

Versatile Mass Spectrometry-Based Intraoperative Diagnosis of Liver Tumor in a Multiethnic Cohort

Currently used techniques for intraoperative assessment of tumor resection margins are time-consuming and laborious and, more importantly, lack specificity. Moreover, pathological diagnosis during surgery does not often give a clear outcome. Recent advances in mass spectrometry (MS) and instrumentation have made it possible to obtain detailed molecular information from tissue specimens in real-time, with minimal sample pre-treatment. Probe Electro Spray Ionization MS (PESI-MS), combined with artificial intelligence (AI), has demonstrated its effectiveness in distinguishing liver cancer tissues from healthy tissues in a large Italian population group. As the MS profile can reflect the patient’s ethnicity, dietary habits, or particular operating room procedures, the AI algorithm must be well trained to distinguish different groups. We used a large dataset composed of liver tumor and healthy specimens, from the Italian and Japanese populations, to develop a versatile algorithm free from ethnic bias. The system can classify tissues with discrepancies &lt;5% from the pathologist’s diagnosis. These results demonstrate the potential of the PESI-MS system to distinguish tumor from surrounding non-tumor tissues in patients, with minimal bias from race/ethnicity or etiological characteristics or operating room procedures.

New strategy for evaluating pancreatic tissue specimens from endoscopic ultrasound-guided fine needle aspiration and surgery.

Background and AimPreoperative histological evaluation of pancreatic neoplasms is important for guiding the resection strategy and preventing postoperative adverse events. However, conventional endoscopic methods have technical limitations that reduce the accuracy of the histopathological examination. Probe electrospray ionization mass spectrometry (PESI‐MS) may be a useful technique for rapidly evaluating small specimens.MethodsThis single‐center prospective study included patients with pancreatic neoplasms between October 2018 and December 2019. Pancreatic ductal adenocarcinoma (PDAC) specimens were obtained via endoscopic ultrasound‐guided fine needle aspiration (EUS‐FNA) and non‐neoplastic tissue was obtained via surgery. Specimens were subjected to PESI‐MS and the mass spectra were analyzed using partial least squares regression‐discriminant analysis.ResultsThe study included 40 patients with 20 nonneoplastic specimens and 19 PDAC specimens (1 case of neuroendocrine carcinoma was omitted). All nonneoplastic specimens were sufficient for PESI‐MS analysis, although only 7 of 19 PDAC specimens were sufficient for PESI‐MS analysis because of poor sample quality or insufficient quantity (<1 mg). Among the 27 analyzed cases, the mass spectra clearly differentiated between the PDAC and nonneoplastic specimens.ConclusionsThis study revealed that PESI‐MS could differentiate between PDAC and nonneoplastic specimens, even in cases where EUS‐FNA produced very small specimens.

Applying Probe Electrospray Ionization Mass Spectrometry to Cytological Diagnosis: A Preliminary Study by Using Cultured Lung Cancer Cells

Objectives: Cytology and histology are 2 indispensable diagnostic tools for cancer diagnosis, which are rapidly increasing in importance with aging populations. We applied mass spectrometry (MS) as a rapid approach for swiftly acquiring nonmorphological information of interested cells. Conventional MS, which primarily rely on promoting ionization by pre-applying a matrix to cells, has the drawback of time-consuming both on data acquisition and analysis. As an emerging method, probe electrospray ionization-MS (PESI-MS) with a dedicated probe is capable to pierce sample and measure specimen in small amounts, either liquid or solid, without the requirement for sample pretreatment. Furthermore, PESI-MS is timesaving compared to the conventional MS. Herein, we investigated the capability of PESI-MS to characterize the cell types derived from the respiratory tract of human tissues. Study Design: PESI-MS analyses with DPiMS-2020 were performed on various type of cultured cells including 5 lung squamous cell carcinomas, 5 lung adenocarcinomas, 5 small-cell carcinomas, 4 malignant mesotheliomas, and 2 normal controls. Results: Several characteristic peaks were detected at around m/z 200 and 800 that were common in all samples. As expected, partial least squares-discriminant analysis of PESI-MS data distinguished the cancer cell types from normal control cells. Moreover, distinct clusters divided squamous cell carcinoma from adenocarcinoma. Conclusion: PESI-MS presented a promising potential as a novel diagnostic modality for swiftly acquiring specific cytological information.

Application of probe electrospray ionization mass spectrometry to the analysis of poisons and drugs in adulterated foods and beverages

Application of probe electrospray ionization mass spectrometry to the analysis of poisons and drugs in adulterated foods and beverages

Probe Electrospray Ionization (PESI) and Its Modified Versions: Dipping PESI (dPESI), Sheath-Flow PESI (sfPESI) and Adjustable sfPESI (ad-sfPESI).

In 2007, probe electrospray ionization/mass spectrometry (PESI/MS) was developed. In this technique, the needle is moved down along a vertical axis and the tip of the needle touched to the sample. After capturing the sample at the needle tip, the needle is then moved up and a high voltage is applied to the needle at the highest position to generate electrospray. Due to the discontinuous sampling followed by the generation of spontaneous electrospray, sequential and exhaustive electrospray takes place depending on the surface activity of the analytes. As modified versions of PESI, dipping PESI (dPESI), sheath-flow PESI (sfPESI) and adjustable sfPESI (ad-sfPESI) have been developed. These methods are complementary to each other and they can be applicable to surface and bulk analysis of various biological samples. In this article, the characteristics of these methods and their applications to real samples will be reviewed.

Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry.

Probe electrospray ionization mass spectrometry (PESI-MS) is an ambient ionization-based mass spectrometry method that surpasses the original electrospray ionization technique in features such as the rapidity of analysis, simplicity of the equipment and procedure, and lower cost. This study found that the PESI-MS system with machine learning has the potential to establish a lipid-based diagnosis of breast cancer with higher accuracy, using a simpler approach. Rapid mass spectrometry for breast cancer.

Sample Preparation for Probe Electrospray Ionization Mass Spectrometry.

Mass spectrometry (MS) is a powerful tool in analytical chemistry because it provides very accurate information about molecules, such as mass-to-charge ratios (m/z), which are useful to deduce molecular weights and structures. While it is essentially a destructive analytical method, recent advancements in the ambient ionization technique have enabled us to acquire data while leaving tissue in a relatively intact state in terms of integrity. Probe electrospray ionization (PESI) is a so-called direct method because it does not require complex and time-consuming pretreatment of samples. A fine needle serves as a sample picker, as well as an ionization emitter. Based on the very sharp and fine property of the probe tip, destruction of the samples is minimal, allowing us to acquire the real-time molecular information from living things in situ. Herein, we introduce three applications of PESI-MS technique that will be useful for biomedical research and development. One involves the application to solid tissue, which is the basic application of this technique for the medical diagnosis. As this technique requires only 10 mg of the sample, it may be very useful in the routine clinical settings. The second application is for in vitro medical diagnostics where human blood serum is measured. The ability to measure fluid samples is also valuable in various biological experiments where a sufficient volume of sample for conventional analytical techniques cannot be provided. The third application leans toward the direct application of probe needles in living animals, where we can obtain real-time dynamics of metabolites or drugs in specific organs. In each application, we can infer the molecules that have been detected by MS or use artificial intelligence to obtain a medical diagnosis.

In situ analysis of single cell and biological samples with rGO-Cu functional probe ESI-MS spectrometry

At present, probe electrospray ionization mass spectrometry is widely used in the single cell analysis. As the continuous expansion of requirements for detecting more metabolite species from single cells, the sensitivity and accuracy of the instrument and the enrichment capacity of the probes are in high demand. Therefore, a high efficiency functional probe electrospray ionization mass spectrometry (FPESI–MS) analysis platform is established. In this platform, nitrogen aggregation/gas heating system and reduced graphene oxide functional copper probe (rGO-Cu probe) are firstly reported. The nitrogen aggregation/gas heating system can promote desorption of the analytes from probe and aggregate the product ions into the ion cluster to increase the ion transport capacity and the detection efficiency. rGO-Cu probe formed huge specific surface area to enrich the analytes without sacrificing the electrical conductivity. The probe substrates were prepared by electrochemical etching, after rGO-functionalization, the tip diameter of all kinds of the probes were measured to be less than 100 nm, which is much smaller than the PC12 single cells. Graphene oxide cannot be completely reduced by electrochemical methods, thus the rGO-Cu probe can enrich the analytes through the huge surface area of the graphene thin layer, as well as the hydrogen bond and the electrostatic absorption of the surface oxygen-containing groups. Seven AD related neurotransmitters and sixteen biomarkers in PC12 single cells and twelve metabolites in serum of AD rats were successfully analyzed by using FPESI–MS, and this method is expected to be used in the rapid detection of metabolites in biological samples and living organism.

Time-resolved in situ monitoring of photocatalytic reactions by probe electrospray ionization mass spectrometry.

Probe electrospray ionization mass spectrometry (PESI-MS) has been demonstrated to be a useful in situ and online analytical technique for monitoring of various reactions. In this work, PESI-MS with a surface-modified probe was adopted and applied to in situ monitoring of photocatalytic reactions. Typical reactions of semiconductor photocatalysts, namely TiO2, SnO2, WO3, SiC and ZnS catalyzed methylene blue (MB) and brilliant green (BG) degradation, were selected to demonstrate the potential of PESI-MS to monitor heterogeneous photocatalytic reactions occurring in suspensions. Surface modification of the probe ensures increased wettability during the whole monitoring process. PESI-MS could provide continuous sampling and real-time MS results without time-consuming and cumbersome sample pretreatments. This method has other merits including good reproducibility and stability (time scale > 60 min), convenience of operation, low sample consumption, high time resolution and high tolerance to suspended photocatalyst particles. Time-resolved mass spectra and ion chromatograms of every chemical species e.g. the substrate and reactive intermediates could be obtained, which is helpful for a better understanding of the photocatalytic reaction process. Thus, PESI-MS could be a versatile analytical technique for in situ photocatalytic reaction analysis and could be an alternative means for the evaluation of photocatalyst performance.

Molecularly Imprinted Polymer-Coated Probe Electrospray Ionization Mass Spectrometry Determines Phorbol Esters and Deoxyphorbol Metabolites in Jatropha curcas Leaves.

In this study, a molecularly imprinted polymer-coated probe electrospray ionization mass spectrometry (MIPCPESI-MS) method was developed for detection of phorbol esters (PEs) and deoxyphorbol metabolites in Jatropha curcas leaves. Such an approach was established by sticking on a metallic needle a molecularly imprinted polymer to particularly design a MIP-coated probe for selective sampling and ionization of PEs and deoxyphorbol metabolites. By a subsequent application of a high voltage and methanol, as spray solvent, ESI was generated for direct and rapid analysis under ambient and open-air conditions. MIP-coated probe exhibited a high sampling capacity of the PEs and its metabolites in methanolic extracts of J. curcas leaves compared with the non-imprinted polymer (NIP)-coated probe. MIPCPESI-MS allowed the detection of phorbol 12,13-diacetate (PDA) from J. curcas leaves with minimal sample preparation, and with detection limit and quantification reaching 0.28μg/mL and 0.92μg/mL, respectively. Also, good linearity was obtained with R2 > 0.99 and precision and accuracy values between 4.06-13.49% and - 1.60 to - 15.26%, respectively. The current method was successfully applied to screening methanolic extracts of six different J. curcas leaf genotypes (three toxic and three non-toxic). PDA and three PE deoxyphorbol metabolites were identified only from toxic genotypes, in which PDA was determined with concentration ranging from 222.19 ± 23.55 to 528.23 ± 19.72μg/g. All these findings support that the MIPCPESI-MS method developed here has a high potential for the analysis of PEs in plant extracts enabling differentiation of toxic and non-toxic genotypes earlier in the leaves.

Lab-made solid phase microextraction phases for off line extraction and direct mass spectrometry analysis: Evaluating the extraction parameters

The analyses of drugs and metabolites in complex matrices have been widely studied in recent years. However, due to high levels endogenous compounds and matrix complexity, these analyses require a sample pre-treatment step. To this aim, two lab-made extractive phases were integrated to probe electrospray ionization mass spectrometry (PESI-MS) technique for direct analysis of illicit drugs in biological fluids and phorbol esters in Jatropha curcas extract. The polypyrrole (PPy) phase was electropolymerized onto a platinum wire surface by cyclic voltammetry. The molecularly imprinted polymer (MIP) was synthesized and adhered onto a stainless-steel needle with epoxy resin. The PPy-PESI-MS method showed to be linear in a concentration range from 1 to 500 μg L−1, with accuracy values between -2.1 and 14%, and precision values between 0.8 and 10.8%. The MIP-PESI-MS method showed to be linear in a concentration range from 0.9 to 30 mg L−1, with accuracy values between -1.6 and -15.3%, and precision values between 4.1 and 13.5%.