Novel analytical approaches for biomarker detection in neonatology

La principal motivación de esta tesis doctoral es el análisis de biomarcadores basados en moléculas pequeñas de relevancia en el periodo neonatal, específicamente, en situaciones de asfixia perinatal y estrés oxidativo. Se han desarrollado métodos analíticos novedosos y se han adaptado para lidiar con los retos que suponen las muestras en neonatología, empleando enfoques mínimamente invasivos y pequeñas cantidades de muestra. Se han implementado diferentes procesados de muestra para el análisis de orina, sangre y leche humana como la extracción en fase sólida y diferentes tipos de desprotenización. Los métodos analíticos desarrollados están basados en: cromatografía líquida acoplada a espectrometría de masas tándem (LC-MS/MS) para el análisis de biomarcadores relacionados con la síntesis de fosfolípidos, biomarcadores de daño oxidativo a ADN, proteínas y lípidos; cromatografía de gases acoplada a espectrometría de masas (GC-MS) para el análisis de biomarcadores del metabolismo energético; espectroscopía Raman amplificada por superficies (SERS) para el análisis de glutatión. Los diferentes métodos desarrollados se han aplicado con éxito en la evaluación temprana de la asfixia perinatal, el análisis de los compuestos relacionados con el metabolismo energético bajo tratamiento de hipotermia terapéutica, el análisis de nuevos biomarcadores de peroxidación lipídica después de la asfixia perinatal, el análisis del estrés oxidativo en leche materna, y el análisis directo de glutatión en micromuestras de sangre. Por tanto, se ha demostrado la aplicabilidad potencial de las tecnologías analíticas avanzadas en la toma de decisiones clínicas.The main motivation of this PhD thesis is the assessment of small molecule biomarkers with relevance in the neonatal period, and more specifically, in situations of perinatal asphyxia and oxidative stress of the newborn. Novel analytical methods have been developed and tailored to deal with the limitations of sampling in the neonatal population, employing minimally invasive approaches and small sample amounts. Different sample pre-processing steps are implemented within the workflows for the analysis of urine, blood, and human milk including Solid Phase Extraction and different deproteinizations. The employed analytical methods are based on Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) for the analysis of phospholipid synthesis-related biomarkers, DNA & protein oxidative damage compounds, and lipid peroxidation products; Gas chromatography-Mass spectrometry (GC-MS) for the analysis of biomarkers of the energy metabolism; and Surface Enhanced Raman Spectroscopy (SERS) for the analysis of glutathione. The different developed methods have been successfully applied in the early assessment of severity of perinatal asphyxia, the analysis of the energy metabolism-related compounds under therapeutic hypothermia treatment, the analysis of novel lipid peroxidation biomarkers after perinatal asphyxia, the analysis of oxidative stress in human milk, and the direct analysis of glutathione in blood microsamples. Therefore, it has been demonstrated the potential applicability of the advanced analytical technologies into the clinical decision-making

High Concentration of Protein Oxidation Biomarker O-Tyr/Phe Predicts Better Outcome in Childhood Bacterial Meningitis

Neuronal damage in bacterial meningitis (BM) partly stems from the host´s inflammatory response and induced oxidative stress (OS). We studied the association of cerebrospinal fluid (CSF) biomarkers indicating oxidative damage to proteins with course of illness and outcome in childhood BM in Angola. Ortho-tyrosine/phenylalanine (o-Tyr/Phe), 3-chlorotyrosine/para-tyrosine (3Cl-Tyr/p-Tyr), and 3-nitrotyrosine/para-tyrosine (3NO2-Tyr/p-Tyr) concentration ratios were measured in 79 BM admission CSF samples, employing liquid chromatography coupled to tandem mass spectrometry. Besides death, disease outcomes were registered on Day 7 of treatment and one month after discharge (control visit). The outcome was graded according to the modified Glasgow Outcome Scale (GOS), which considers neurological and audiological sequelae. Children with a o-Tyr/Phe ratio below the median were more likely to present focal convulsions and secondary fever during recovery and suboptimal outcome (GOS < 5) on Day 7 and at control visit (odds ratio (OR) 2.85; 95% CI 1.14–7.14 and OR 5.23; 95% CI 1.66–16.52, respectively). Their most common sequela was ataxia on Day 7 and at control visit (OR 8.55; 95% CI 2.27–32.22 and OR 5.83; 95% CI 1.12–30.4, respectively). The association of a higher admission CSF o-Tyr/Phe ratio with a better course and outcome for pediatric BM points to a beneficial effect of OS

Protein Oxidation Biomarkers and Myeloperoxidase Activation in Cerebrospinal Fluid in Childhood Bacterial Meningitis

The immunological response in bacterial meningitis (BM) causes the formation of reactive oxygen and nitrogen species (ROS, RNS) and activates myeloperoxidase (MPO), an inflammatory enzyme. Thus, structural oxidative and nitrosative damage to proteins and DNA occurs. We aimed to asses these events in the cerebrospinal fluid (CSF) of pediatric BM patients. Phenylalanine (Phe), para-tyrosine (p-Tyr), nucleoside 2′-deoxiguanosine (2dG), and biomarkers of ROS/RNS-induced protein and DNA oxidation: ortho-tyrosine (o-Tyr), 3-chlorotyrosine (3Cl-Tyr), 3-nitrotyrosine (3NO₂-Tyr) and 8-oxo-2′-deoxyguanosine (8OHdG), concentrations were measured by liquid chromatography coupled to tandem mass spectrometry in the initial CSF of 79 children with BM and 10 without BM. All biomarkers, normalized with their corresponding precursors, showed higher median concentrations (p < 0.0001) in BM compared with controls, except 8OHdG/2dG. The ratios o-Tyr/Phe, 3Cl-Tyr/p-Tyr and 3NO₂-Tyr/p-Tyr were 570, 20 and 4.5 times as high, respectively. A significantly higher 3Cl-Tyr/p-Tyr ratio was found in BM caused by Streptococcus pneumoniae, than by Haemophilus influenzae type b, or Neisseria meningitidis (p = 0.002 for both). In conclusion, biomarkers indicating oxidative damage to proteins distinguished BM patients from non-BM, most clearly the o-Tyr/Phe ratio. The high 3Cl-Tyr/p-Tyr ratio in pneumococcal meningitis suggests robust inflammation because 3Cl-Tyr is a marker of MPO activation and, indirectly, of inflammation

Protein Oxidation Biomarkers and Myeloperoxidase Activation in Cerebrospinal Fluid in Childhood Bacterial Meningitis

The immunological response in bacterial meningitis (BM) causes the formation of reactive oxygen and nitrogen species (ROS, RNS) and activates myeloperoxidase (MPO), an inflammatory enzyme. Thus, structural oxidative and nitrosative damage to proteins and DNA occurs. We aimed to asses these events in the cerebrospinal fluid (CSF) of pediatric BM patients. Phenylalanine (Phe), para-tyrosine (p-Tyr), nucleoside 2′-deoxiguanosine (2dG), and biomarkers of ROS/RNS-induced protein and DNA oxidation: ortho-tyrosine (o-Tyr), 3-chlorotyrosine (3Cl-Tyr), 3-nitrotyrosine (3NO₂-Tyr) and 8-oxo-2′-deoxyguanosine (8OHdG), concentrations were measured by liquid chromatography coupled to tandem mass spectrometry in the initial CSF of 79 children with BM and 10 without BM. All biomarkers, normalized with their corresponding precursors, showed higher median concentrations (p < 0.0001) in BM compared with controls, except 8OHdG/2dG. The ratios o-Tyr/Phe, 3Cl-Tyr/p-Tyr and 3NO₂-Tyr/p-Tyr were 570, 20 and 4.5 times as high, respectively. A significantly higher 3Cl-Tyr/p-Tyr ratio was found in BM caused by Streptococcus pneumoniae, than by Haemophilus influenzae type b, or Neisseria meningitidis (p = 0.002 for both). In conclusion, biomarkers indicating oxidative damage to proteins distinguished BM patients from non-BM, most clearly the o-Tyr/Phe ratio. The high 3Cl-Tyr/p-Tyr ratio in pneumococcal meningitis suggests robust inflammation because 3Cl-Tyr is a marker of MPO activation and, indirectly, of inflammation

High Oxygen Does Not Increase Reperfusion Injury Assessed with Lipid Peroxidation Biomarkers after Cardiac Arrest: A Post Hoc Analysis of the COMACARE Trial

The products of polyunsaturated fatty acid peroxidation are considered reliable biomarkers of oxidative injury in vivo. We investigated ischemia-reperfusion-related oxidative injury by determining the levels of lipid peroxidation biomarkers (isoprostane, isofuran, neuroprostane, and neurofuran) after cardiac arrest and tested the associations between the biomarkers and different arterial oxygen tensions (PaO2). We utilized blood samples collected during the COMACARE trial (NCT02698917). In the trial, 123 patients resuscitated from out-of-hospital cardiac arrest were treated with a 10–15 kPa or 20–25 kPa PaO2 target during the initial 36 h in the intensive care unit. We measured the biomarker levels at admission, and 24, 48, and 72 h thereafter. We compared biomarker levels in the intervention groups and in groups that differed in oxygen exposure prior to randomization. Blood samples for biomarker determination were available for 112 patients. All four biomarker levels peaked at 24 h; the increase appeared greater in younger patients and in patients without bystander-initiated life support. No association between the lipid peroxidation biomarkers and oxygen exposure either before or after randomization was found. Increases in the biomarker levels during the first 24 h in intensive care suggest continuing oxidative stress, but the clinical relevance of this remains unresolved

High Oxygen Does Not Increase Reperfusion Injury Assessed with Lipid Peroxidation Biomarkers after Cardiac Arrest: A Post Hoc Analysis of the COMACARE Trial

The products of polyunsaturated fatty acid peroxidation are considered reliable biomarkers of oxidative injury in vivo. We investigated ischemia-reperfusion-related oxidative injury by determining the levels of lipid peroxidation biomarkers (isoprostane, isofuran, neuroprostane, and neurofuran) after cardiac arrest and tested the associations between the biomarkers and different arterial oxygen tensions (PaO2). We utilized blood samples collected during the COMACARE trial (NCT02698917). In the trial, 123 patients resuscitated from out-of-hospital cardiac arrest were treated with a 10–15 kPa or 20–25 kPa PaO2 target during the initial 36 h in the intensive care unit. We measured the biomarker levels at admission, and 24, 48, and 72 h thereafter. We compared biomarker levels in the intervention groups and in groups that differed in oxygen exposure prior to randomization. Blood samples for biomarker determination were available for 112 patients. All four biomarker levels peaked at 24 h; the increase appeared greater in younger patients and in patients without bystander-initiated life support. No association between the lipid peroxidation biomarkers and oxygen exposure either before or after randomization was found. Increases in the biomarker levels during the first 24 h in intensive care suggest continuing oxidative stress, but the clinical relevance of this remains unresolved

Riesgo quirúrgico tras resección pulmonar anatómica en cirugía torácica. Modelo predictivo a partir de una base de datos nacional multicéntrica

Introduction: the aim of this study was to develop a surgical risk prediction model in patients undergoing anatomic lung resections from the registry of the Spanish Video-Assisted Thoracic Surgery Group (GEVATS). Methods: data were collected from 3,533 patients undergoing anatomic lung resection for any diagnosis between December 20, 2016 and March 20, 2018. We defined a combined outcome variable: death or Clavien Dindo grade IV complication at 90 days after surgery. Univariate and multivariate analyses were performed by logistic regression. Internal validation of the model was performed using resampling techniques. Results: the incidence of the outcome variable was 4.29% (95% CI 3.6-4.9). The variables remaining in the final logistic model were: age, sex, previous lung cancer resection, dyspnea (mMRC), right pneumonectomy, and ppo DLCO. The performance parameters of the model adjusted by resampling were: C-statistic 0.712 (95% CI 0.648-0.750), Brier score 0.042 and bootstrap shrinkage 0.854. Conclusions: the risk prediction model obtained from the GEVATS database is a simple, valid, and reliable model that is a useful tool for establishing the risk of a patient undergoing anatomic lung resection

First -decay spectroscopy of and new -decay branches of

19 pags., 14 figs., 3 tabs.The  decay of the neutron-rich and was investigated experimentally in order to provide new insights into the nuclear structure of the tin isotopes with magic proton number above the shell. The -delayed -ray spectroscopy measurement was performed at the ISOLDE facility at CERN, where indium isotopes were selectively laser-ionized and on-line mass separated. Three -decay branches of were established, two of which were observed for the first time. Population of neutron-unbound states decaying via rays was identified in the two daughter nuclei of and , at excitation energies exceeding the neutron separation energy by 1 MeV. The -delayed one- and two-neutron emission branching ratios of were determined and compared with theoretical calculations. The -delayed one-neutron decay was observed to be dominant -decay branch of even though the Gamow-Teller resonance is located substantially above the two-neutron separation energy of . Transitions following the  decay of are reported for the first time, including rays tentatively attributed to . In total, six new levels were identified in on the basis of the coincidences observed in the and decays. A transition that might be a candidate for deexciting the missing neutron single-particle state in was observed in both  decays and its assignment is discussed. Experimental level schemes of and are compared with shell-model predictions. Using the fast timing technique, half-lives of the , and levels in were determined. From the lifetime of the state measured for the first time, an unexpectedly large transition strength was deduced, which is not reproduced by the shell-model calculations.M.P.-S. acknowledges the funding support from the Polish National Science Center under Grants No. 2019/33/N/ST2/03023 and No. 2020/36/T/ST2/00547 (Doctoral scholarship ETIUDA). J.B. acknowledges support from the Universidad Complutense de Madrid under the Predoctoral Grant No. CT27/16- CT28/16. This work was partially funded by the Polish National Science Center under Grants No. 2020/39/B/ST2/02346, No. 2015/18/E/ST2/00217, and No. 2015/18/M/ST2/00523, by the Spanish government via Projects No. FPA2017-87568-P, No. RTI2018-098868-B-I00, No. PID2019-104390GB-I00, and No. PID2019-104714GB-C21, by the U.K. Science and Technology Facilities Council (STFC), the German BMBF under Contract No. 05P18PKCIA, by the Portuguese FCT under the Projects No. CERN/FIS-PAR/0005/2017, and No. CERN/FIS-TEC/0003/2019, and by the Romanian IFA Grant CERN/ISOLDE. The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 654002. M.Str. acknowledges the funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 771036 (ERC CoG MAIDEN). J.P. acknowledges support from the Academy of Finland (Finland) with Grant No. 307685. Work at the University of York was supported under STFC Grants No. ST/L005727/1 and No. ST/P003885/1

Teaching of Machine Learning and Chemometrics in Analytical Chemistry Based on Interactive Hands-on Activities

[EN] Despite the growing popularity of machine learning (ML), the teaching of this disruptive field in analytical chemistry is challenging due to the lack of enough programming background in both, professors, and students. Because of that, this subject is sometimes underrated or even ignored in chemistry curriculums. In this work, we firstly surveyed the previous knowledge in multivariate analysis and programming by students enrolled in the master’s degree in chemistry. Upon recognizing a deficiency in fundamental programming and statistical principles, we carried out actions to close the gap between ML and analytical chemistry in under- and post-graduate level. Accordingly, we proposed the use of the interactive software Orange and the programming of apps with MATLAB for teaching ML in the laboratory lessons of analytical chemistry. With this approach, two laboratory lessons were designed and conducted which are focused on analysis of foodstuffs by infrared spectroscopy and using ML in daily contexts. The evaluation of the methodologies proposed indicated that the use of interactive software made ML more appealing to the students and contributed to a better understanding of ML concepts.[ES] A pesar de la creciente popularidad de las técnicas de aprendizaje automático (“machine learning”, en inglés) su enseñanza en química analítica es un reto debido a la falta de conocimientos en programación por parte del alumnado y el profesorado. Debido a ello, estas técnicas suelen obviarse o incluirse sucintamente en los currículos. En este trabajo, estudiamos los conocimientos previos de programación y análisis multivariante del alumnado matriculado en el Máster en Química e identificamos diferentes deficiencias en conceptos básicos de programación y estadística. En consecuencia, para cerrar la brecha entre el aprendizaje automático y la química analítica, planteamos el uso del programa interactivo Orange y la programación de aplicaciones con MATLAB. Utilizando este enfoque, diseñamos y llevamos a cabo dos sesiones prácticas consistentes en el análisis de alimentos mediante espectroscopía infrarroja y en la implementación de modelos de aprendizaje automático aplicados a contextos cotidianos. Tras evaluar las metodologías propuestas, comprobamos que estas hacen el aprendizaje automático más atractivo para el estudiantado contribuyendo a su mejor aprendizaje.Ayuda Margarita Salas (ref. UP2021-044-MS21-084) del Ministerio de Universidades-Next Generation EU; Ayuda RyC (ref. RYC2019-026556-I) Ministerio de Investigación y Ciencia (MCIN/AEI/10.13039/501100011033).Sánchez Illana, Á.; Wood, B.; Pérez Guaita, D. (2023). Enseñanza del machine learning y la quimiometría en química analítica mediante propuestas prácticas e interactivas. Editorial Universitat Politècnica de València. 246-260. https://doi.org/10.4995/INRED2023.2023.1667924626