Abstract Forest ecosystems are likely to shift faster in response to climate change than their maximum natural rate at which they can migrate and establish. This thesis introduces an interdisciplinary approach to develop a proactive management strategy towards climate change through assisted populations’ migration for two pine species; Aleppo pine (Pinus halepensis Mill.) and Black pine (Pinus nigra ssp. salzmannii). The main objectives of this study were to (1) evaluate plantation performance and phenotypic plasticity in the broad context of genotype by environment interaction (GEI) of these pine seed sources out-planted in contrasting trial sites to test a hypothetical northwards migration for further selection under specific conditions, (2) compare the efficiency of joint regression and Additive Main effect and Multiplicative Interaction (AMMI) models in elucidating seed sources adaptation patterns in each site then, (3) explain the basis of the differential response of seed sources to induced drought and cold stresses through the physiological, metabolomic and proteomic analyses. This study reproduced real conditions of reforestation in potential future climatic conditions either in field or under phytotron controlled conditions. The selective use of the intraspecific variability was demonstrated to have a potential contribution to alleviate adverse climate change impacts on forest ecosystems. For both species, certain seed sources were able to cope better with specific climate perturbations than others in response to the northwards shifts; seedlings not belonging to the target site could be selected for facing current climate irregularities in different environments. Abstract Here, provenances moved from slightly different transfer distance metrics were the best performers. The main problem is the high expected seedlings mortality due to freezing events and drought stress mainly for seedlings belonging to warmer provenances. Seed sources phenotypic plasticity was low to moderate for height and diameter growth and the environmental effect had a great influence on their performance variation. The AMMI models demonstrated higher adequacy to analyse complex GEI than the joint regression analysis. An important finding is that specific adaptation to adverse environmental conditions was coupled with low phenotypic plasticity responses. Differences among Aleppo pine seed sources subjected to induced drought conditions were significant for chlorophyll fluorescence, pigments and soluble sugars contents. However, induced cold stress changes transpiration rate, stomatal conductance, pigments and glucose contents. The decrease in photosynthesis under drought, unlike to cold stress, was due to stomatal closure. At the considered metabolomic level, drought tolerance was related to the decrease of glucose and fructose and the increase of sucrose contents in needles. However, the cold tolerance was associated to the decrease of glucose and the increase of sucrose and fructose contents. At the proteomic level, most of the identified proteins were related to the transcriptional machinery and sugar metabolism. The presence of enzyme related to the sulphur amino-acids metabolism could be the limiting factor for drought stress in Aleppo pine. Keywords Assisted population migration, Reforestation, Pinus halepensis, Pinus nigra ssp. salzmannii, Seed Sources, Out-planting performance, Survival, Growth, Phenotypic Plasticity, Genotype by Environment Interaction, Adaptation, Physiology, Metabolomic, Proteomic. / Taïbi, K. (2014). Integrated approach for addressing assisted population migration programs in forest management to climate change: out-planting performance, genotype by environment interactions, physiological and molecular response [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48467 / TESIS

La résilience des agricultures subsahariennes face aux perturbations environnementales et socio-économiques repose en partie sur le maintien des diversités spécifique, variétale et génétique présentes au sein des agrosystèmes, mais aussi sur la préservation du droit pour les cultivateurs de reproduire et d'échanger librement les semences et les savoirs relatifs aux variétés. Pourtant, peu de données sont réellement disponibles sur la circulation effective des semences et les mécanismes modulant les flux de gènes et les introgressions génétiques entre variétés cultivées dans les agrosystèmes sahéliens. Chez le mil en particulier, il n’existe que des données très parcellaires sur les relations entre la diversité de la plante d’une part et la diversité socio-culturelle des agriculteurs d'autre part. Dans la première partie je me suis intéressé aux interactions entre l’organisation en groupes socio-culturels des agriculteurs et la structure génétique des populations de mil dans le bassin du lac Tchad. Les analyses de la diversité génétique suggèrent l’existence d’une barrière sociale à la diffusion des gènes sur l’ensemble de cette région. Néanmoins ces barrières ne sont pas suffisantes pour empêcher les introgressions génétiques entre populations cultivées par des agriculteurs appartenant à des groupes ethnolinguistiques différents. Dans le deuxième chapitre, je me suis intéressé au rôle des processus d’adaptation locale sur la circulation des gènes. Les résultats m’ont conduit à proposer l’hypothèse selon laquelle les flux de gènes entre types nommés précoces et tardifs sont plus importants dans les régions du nord où la pluviométrie est faible. Enfin dans le troisième chapitre j’ai quantifié la diversité biochimique des grains de mil de plusieurs variétés de mil, dont les usages culinaires varient selon les groupes ethnolinguistiques ou dont les qualités gustatives sont appréciées différemment. J’ai utilisé pour cela une approche combinée de protéomique et de métabolique. Parmi les 1072 spots protéiques quantifiés seulement 7 permettent de distinguer les types nommés photopériodiques des types nommés non ou peu photopériodiques. Les données de métabolomique suggèrent la présence de champignons, qui pourraient être des endophytes, dans certains des échantillons analysés. / The resilience of sub-Saharan farming systems to environmental and socioeconomic disturbances is partly based on the maintenance of agro-biodiversity, but also on preserving the right for farmers to reproduce and freely exchange seeds and related knowledge. However, few data are actually available on effective seed flow and on mechanisms modulating gene flow and genetic introgression between landraces grown in Sahelian farming systems. For pearl millet especially, there are only very few data on the relationship between diversity of this crop on the one hand and the socio-cultural diversity of farmers on the other hand. In the first part of my thesis, I was interested in assessing a potential relationship between ethnolinguistic diversity and population genetic structure of pearl millet in the Lake Chad Basin. Analysis of molecular polymorphisms suggests the existence of social barrier to seed flow among ethnolinguistic groups. However, these barriers are not sufficient to prevent genetic introgression between pearl millet populations cultivated by farmers belonging to different ethno-linguistic groups. In the second chapter, I focused on the role of local adaptation on gene flow. The results led me to propose the hypothesis that gene flow between early and late landraces are higher in the northern regions where rainfall is weak. Finally in the third part, I have quantified the biochemical compound of pearl millet seeds belonging to different varieties that show different uses or culinary preferences among farmers belonging to different ethnolingiuistic groups. I used a combined approach of proteomics and metabolics. Among the 1072 protein spots quantified only 7 distinguish the very photoperiodic non photoperiodic landrace. Metabolomics data suggest the presence of fungi, possibly endophytes, in some of the samples analyzed.

Background Prostate cancer (PCa) is the most frequently diagnosed malignant disease among adult males in the USA and the second leading cause of cancer deaths in men. Due to the lack of diagnostic tools that are able to differentiate highly malignant and aggressive cases from indolent tumors, overtreatment has become very common in the era of prostate specific antigen (PSA) screening. New diagnostic methods to determine biological status, malignancy, aggressiveness and extent of PCa are urgently needed. 1H High Resolution Magic Angle Spinning Nuclear Magnetic Resonance Spectroscopy (1H HRMAS MRS) can be used to establish PCa metabolomic profiles while preserving tissue architecture for subsequent histopathological analysis. Immunohistochemistry (IHC), as opposed to conventional histopathology methods, has the potential to provide objective, more accurate and quantitative knowledge of tissue pathology. This diagnostic- accuracy study sought to evaluate a novel approach to quantitatively identify metabolomic markers of PCa by exploring the potential of PCa immunomarkers to quantify metabolomic profiles established by 1H HRMAS MRS. Material and Methods 1H HRMAS MRS was performed on tissue samples of 51 prostate cancer patients using a 14.1 Tesla NMR spectrometer (BRUKER Biospin, Billerica, MA) with a rotor synchronized CPMG pulse sequence. Spectral intensities of 36 regions of interest were measured as integrals of curve fittings with Lorentzian-Gaussian line shapes. Immunohistochemistry (IHC) was carried out following the spectroscopy scan, using three prostate immunomarkers to identify cancerous and benign glands: P504S (Alpha-methylacyl-CoA-racemace), CK903 (high-molecular weight cytokeratin) and p63. The immunostaining quality following 1H HRMAS MRS was evaluated and compared to unscanned sections of the same sample, to verify the stability and accessibility of the proposed immunomarkers. IHC images were automatically and quantitatively evaluated, using a quantitative image analysis program (QIAP), to determine the percentage of cancerous and benign epithelia in the tissue cross- sections. The results of the program were validated by a correlation with the results of a quantitative IHC review and quantitative conventional histopathology analysis performed by an experienced pathologist. Ultimately, spectral intensities and the cancer epithelium percentage, obtained from quantitative immunohistochemistry, were correlated in order to validate PCa metabolomic markers identified by 1H HRMAS MRS. Patient outcomes and incidence of recurrence were determined by retrospective review of medical records five years after initial surgery. Categories of recurrence were correlated to spectral intensities to explore potential metabolomic markers of recurrence in the cohort. Results Immunostainings with P504S and CK903 showed excellent staining quality and accessibility following 1H HRMAS MRS, suggesting these markers to be suitable for the presented quantitative approach to determine metabolomics profiles of PCa. In contrast, the quality of p63 IHC was impaired after previously performed spectroscopy. IHC using the immunomarkers P504S and CK903 on adjacent slides was found to present a feasible quantitative diagnostic method to distinguish between benign and cancerous conditions in prostate tissue. The cancer epithelium percentage as determined by QIAP showed a significant correlation to the results of quantitative IHC analysis performed by a pathologist (p < 0.001), as well as to a quantitative conventional histopathology review (p = 0.001). The same was true for the benign epithelium percentage (p < 0.001 and p = 0.0183), validating the presented approach. Two metabolomic regions showed a significant correlation between relative spectral intensities and the cancer epithelium percentage as determined by QIAP: 3.22 ppm (p = 0.015) and 2.68 ppm (p = 0.0144). The metabolites corresponding to these regions, phosphocholine and citrate, could be identified as metabolomic markers of PCa in the present cohort. 45 patients were followed for more than 12 months. Of these, 97.8% were still alive five years after initial surgery. 11 patients (24.4%) experienced a recurrence during the follow- up time. The categories of recurrence showed a correlation to the spectral intensities of two regions, 2.33 – 2.3 ppm (p = 0.0403) and 1.28 ppm (p = 0.0144), corresponding to the metabolites phosphocreatine and lipids. Conclusion This study introduces a method that allows an observer-independent, quantitative analysis of IHC to help establish metabolomic profiles and identify metabolomic markers of PCa from spectral intensities obtained with 1H HRMAS NMR Spectroscopy. The immunomarkers P504S and CK903 have been found suitable IHC analysis following 1H HRMAS MRS. A prospective in vivo application of PCa metabolite profiles and metabolomic markers determined by the presented method could serve as highly sensitive, non- invasive diagnostic tool. This observer- independent, computer- automated, quantitative analysis could help to distinguish highly aggressive tumors from low-malignant conditions, avoid overtreatment and reduce risks and complications for cancer patients in the future. Further studies are needed to verify the identified PCa metabolomic markers and to establish clinical applicability.:Table of Contents Glossary 1 Introduction 1. 1 Prostate Cancer 1. 2 Detection of Prostate Cancer – State of the Art 1. 2. 1 Prostate- Specific Antigen Test and Digital Rectal Examination 1.2.2 Radiographic Methods in PCa Detection 1.2.3 Transrectal Core Biopsies and Histopathological Analysis 1.2.4 Histopathological Grading of Prostate Cancer: GLEASON Score 1.3 Challenges and Need for New Approaches in PCa Diagnostic Management 2 Scientific Background I: Nuclear Magnetic Resonance,1H HRMAS NMR Spectroscopy and Metabolomic Profiles 2.1 Nuclear Magnetic Resonance 2.1.1 Spin Precession 2.1.2 Magnetic Resonance 2.1.3 Chemical Shift and J- coupling 2.2 Nuclear Magnetic Resonance 2.2.1 Magic Angle Spinning and 1H HRMAS NMR Spectroscopy 2.2.2 MAS Spinning Rates and Spinning Side Bands 2. 3 Metabolomics, Metabolite Profiles and Clinical Utility 3 Scientific Background II: Immunohistochemistry of Prostate Cancer 4 Aims of the Study 5 Material and Methods 5.1 Prostate Tissue Samples and Patient Demographics 5.2 1H HRMAS NMR Spectroscopy 5.2.1 Sample Preparation 5.2.2 Spectroscopy Scan 5.2.3 Data Processing 5.3 Immunohistochemistry 5.3.1 Immunohistochemistry Material and Equipment 5.3.2. Immunohistochemistry Protocol 5. 3. 3 Prostate Immunomarker Stability after 1H HRMAS NMR Spectroscopy 5.3.4 Qualitative IHC Analysis 5. 3.5 Quantitative IHC Analysis 5.3.5.1 Quantitative IHC Slide Review 5.3.5.2 Computer-Automated Quantitative IHC Analysis 5.3 Quantitative Histopathology 5. 4 Identification of Prostate Cancer Metabolomic Markers 5. 5 Patient Outcomes and Recurrence Categories 5.6 Statistical Analysis 6 Results 6. 1 Patient demographics 6. 2 Spectroscopy Results 6. 3 Immunohistochemistry 6. 3. 1 Evaluation of Prostate Immunomarker Stability after 1H HRMAS MRS 6. 3. 2 Qualitative Immunohistochemistry 6. 4 Quantitative Immunohistochemistry 6. 4. 1 Quantitative IHC Slide Review 6. 4. 2 Computer-Automated Quantitative IHC Evaluation using QIAP 6. 5 Quantitative Histopathology 6. 6 Identification of Prostate Cancer Metabolomic Markers using QIAP 6. 7 Patient Outcomes and Recurrence 7 Discussion 8 Summary / Abstract 9 Zusammenfassung 10 References 11 Erklärung über die eigenständige Abfassung der Arbeit 12 Danksagung 13 Lebenslauf und Publikationsverzeichnis Appendix A.1 Immunostaining protocols A.2 Spectral Intensities Measured by 1H HRMAS MRS in 51 Samples A.3 Graphs for Correlations of Spectral Intensities and CaE% determined by QIAP in 34 Additional Regions of Interest / Einführung Prostatakrebs ist eine häufigsten Krebserkrankungen in den USA und die zweithäufigste malignom- assoziierte Todesursache männlicher Patienten weltweit. Seit der Einführung des Prostata- spezifischen Antigen (PSA)- Screeningtests wird diese Krebsart in früheren Stadien diagnostiziert und therapiert, wodurch die Mortalitätsrate in den letzten Jahren deutlich reduziert werden konnte. Da moderne diagnostische Methoden bislang jedoch nicht ausreichend in der Lage sind, suffizient zwischen hochmalignen und weniger aggressiven Varianten dieses bösartigen Krebsleidens zu unterscheiden, werden häufig auch Patienten aggressiv therapiert, deren niedriggradiges Prostatakarzinom keine klinische Relevanz gehabt hätte. Es besteht daher ein großes wissenschaftliches Interesse an der Entwicklung neuer diagnostischer Methoden zur akkuraten Bestimmung von biologischem Status, Malignität, Aggressivität und Ausmaß einer Prostatakrebserkrankung. \\\\\\\"1H High Resolution Magic Angle Spinning Nuclear Magnetic Resonance Spectroscopy\\\\\\\" (1H HRMAS MRS) ist eine vielversprechende diagnostische Methode, welche es ermöglicht, metabolomische Profile von Prostatakrebs zu erstellen, ohne die Gewebsstruktur der analysierten Proben zu zerstören. Durch anschließende histopathologische Begutachtung lassen sich die erstellten Metabolitprofile validieren und evaluieren. Im Gegensatz zu konventionellen histopathologischen Methoden können durch immunhistochemische Verfahren dabei objektivere, akkuratere und quantifizierbare histopathologische Erkenntnisse gewonnen werden. Die vorliegende Studie präsentiert einen neuentwickelten diagnostischen Ansatz zur quantitativen Bestimmung von metabolomischen Markern von Prostatakrebs, basierend auf der Durchführung von 1H HRMAS NMR Spektroskopie und quantitativer Immunhistochemie. Material und Methoden Einundfünfzig Gewebsproben von Prostatakrebspatienten wurden mittels 1H HRMAS MRS an einem 14.1 T BRUKER NMR Spektrometer unter Einsatz einer CPMG-Pulssequenz untersucht. Spektrale Intensitäten in 36 Metabolitregionen wurden gemessen. Anschließend wurden die analysierten Gewebeproben mit drei Immunfärbemarkern für sowohl malignes (P504S, Alpha-methylacyl-CoA-racemase) als auch benignes (CK903, High-molecular weight cytokeratin, und p63) Prostatagewebe angefärbt und quantitativ mit Hilfe eines Bildanalyseprogramms (QIAP) ausgewertet. Die Anwendbarkeit und Auswertbarkeit der genannten Immunomarker nach Spektroskopie wurde evaluiert und mit der Färbungsqualität von nicht- gescannten Schnitten verglichen. Die Resultate der automatischen Auswertung durch QIAP konnten durch einen erfahrenen Pathologen in einer quantitativen Analyse der Immunfärbungen sowie konventioneller histologischer Färbungen derselben Gewebsproben validiert werden. Die spektralen Intensitäten aus den Messungen mit 1H HRMAS MRS wurden mit den korrespondierenden Ergebnissen der quantitativen Auswertung der Immunfärbungen korreliert, um metabolomische Marker von Prostatakrebs zu identifizieren. Der klinische Verlauf und die Rezidivrate der Patienten wurden 5 Jahre nach der initialen Prostatektomie retrospektiv bestimmt. Rezidivkategorien wurden erstellt und mit den bestimmten spektralen Intensitäten korreliert, um metabolomische Marker für das Auftreten von Prostatakrebsrezidiven zu identifizieren. Ergebnisse Die Immunfärbungen mit P504S und CK903 zeigten exzellente Qualität und Auswertbarkeit nach vorheriger 1H HRMAS MRS. Beide Marker eigneten sich zur Durchführung von quantitativer Immunhistochemie an spektroskopierten Gewebeproben. Im Gegensatz dazu war die Qualität der Immunfärbungen mit p63 nach Spektroskopie vermindert. Quantitative Immunfärbungen unter Einsatz der Immunmarker P504S und CK903 stellten eine praktikable diagnostische Methode dar, um zwischen malignen und benignem Prostatagewebe zu unterscheiden. Der Anteil von bösartig verändertem Prostatagewebe, bestimmt durch QIAP, korrelierte signifikant mit den Ergebnissen der quantitativen Analyse der Immunfärbungen durch den Pathologen (p < 0.001), sowie mit der quantitativen Auswertung der konventionellen histopathologischen Färbung (p = 0.001). Ebenso ließ sich die Bestimmung des Anteils von benignem Gewebe mit QIAP zu den Ergebnissen der pathologischen Analyse korrelieren (p < 0.001 und p = 0.0183). Für zwei metabolomische Regionen konnte ein signifikante Korrelation zwischen relativen spektralen Intensitäten, bestimmt mit 1H HRMAS NMR Spektroskopie, und dem Anteil von malignem Epithelium in derselben Gewebeprobe, ermittelt durch QIAP, festgestellt werden: 3.22 ppm (p = 0.015) und 2.68 ppm (p = 0.0144). Die zu diesen Regionen korrespondierenden Metaboliten, Phosphocholin und Zitrat, konnten als potentielle metabolomische Marker für Prostatakrebs identifiziert werden. Die retrospektiven Analyse der klinischen Daten der Patienten fünf Jahre nach Prostatektomie ergab eine Überlebensrate von 97.8%. Elf dieser Patienten (24.4%) erlitten ein Rezidiv ihrer Erkrankung. Die bestimmten Rezidivkategorien korrelierten signifikant mit zwei metabolomischen Regionen (2.33 – 2.3 ppm, p = 0.0403 und 1.28 ppm, p = 0.0144), welche zu den Metaboliten Phosphokreatin und Lipiden korrespondierten. Schlussfolgerung Die vorliegende Studie präsentiert einen diagnostischen Ansatz zur objektiven und quantitativen Bestimmung metabolomischer Marker von Prostatakrebs unter Verwendung von 1H HRMAS MRS und Immunhistochemie. P504S und CK903 eignen sich als Immunmarker für quantitative Immunfärbungen nach vorheriger Durchführung von 1H HRMAS MRS. Die Metaboliten Phosphocholin und Zitrat konnten in der vorliegenden Patientenkohorte als potentielle metabolomische Marker für Prostatakrebs identifiziert werden. Eine mögliche in vivo Anwendung der gefundenen metabolomischen Marker könnte als hochsensitives, objektives und nicht- invasives diagnostisches Werkzeug der Prostatakrebsdiagnostik dienen. Der vorliegende untersucherunabhängige, automatisierte und quantitative diagnostischer Ansatz hat das Potential, zwischen hochmalignen und weniger aggressiven Krebsfällen zu unterscheiden und somit unnötige Risiken und Komplikationen für Prostatakrebspatienten zu reduzieren. Weitere Untersuchungen sind notwendig, um die identifizierten metabolomischen Marker zu verifizieren und eine klinische Anwendung zu etablieren.:Table of Contents Glossary 1 Introduction 1. 1 Prostate Cancer 1. 2 Detection of Prostate Cancer – State of the Art 1. 2. 1 Prostate- Specific Antigen Test and Digital Rectal Examination 1.2.2 Radiographic Methods in PCa Detection 1.2.3 Transrectal Core Biopsies and Histopathological Analysis 1.2.4 Histopathological Grading of Prostate Cancer: GLEASON Score 1.3 Challenges and Need for New Approaches in PCa Diagnostic Management 2 Scientific Background I: Nuclear Magnetic Resonance,1H HRMAS NMR Spectroscopy and Metabolomic Profiles 2.1 Nuclear Magnetic Resonance 2.1.1 Spin Precession 2.1.2 Magnetic Resonance 2.1.3 Chemical Shift and J- coupling 2.2 Nuclear Magnetic Resonance 2.2.1 Magic Angle Spinning and 1H HRMAS NMR Spectroscopy 2.2.2 MAS Spinning Rates and Spinning Side Bands 2. 3 Metabolomics, Metabolite Profiles and Clinical Utility 3 Scientific Background II: Immunohistochemistry of Prostate Cancer 4 Aims of the Study 5 Material and Methods 5.1 Prostate Tissue Samples and Patient Demographics 5.2 1H HRMAS NMR Spectroscopy 5.2.1 Sample Preparation 5.2.2 Spectroscopy Scan 5.2.3 Data Processing 5.3 Immunohistochemistry 5.3.1 Immunohistochemistry Material and Equipment 5.3.2. Immunohistochemistry Protocol 5. 3. 3 Prostate Immunomarker Stability after 1H HRMAS NMR Spectroscopy 5.3.4 Qualitative IHC Analysis 5. 3.5 Quantitative IHC Analysis 5.3.5.1 Quantitative IHC Slide Review 5.3.5.2 Computer-Automated Quantitative IHC Analysis 5.3 Quantitative Histopathology 5. 4 Identification of Prostate Cancer Metabolomic Markers 5. 5 Patient Outcomes and Recurrence Categories 5.6 Statistical Analysis 6 Results 6. 1 Patient demographics 6. 2 Spectroscopy Results 6. 3 Immunohistochemistry 6. 3. 1 Evaluation of Prostate Immunomarker Stability after 1H HRMAS MRS 6. 3. 2 Qualitative Immunohistochemistry 6. 4 Quantitative Immunohistochemistry 6. 4. 1 Quantitative IHC Slide Review 6. 4. 2 Computer-Automated Quantitative IHC Evaluation using QIAP 6. 5 Quantitative Histopathology 6. 6 Identification of Prostate Cancer Metabolomic Markers using QIAP 6. 7 Patient Outcomes and Recurrence 7 Discussion 8 Summary / Abstract 9 Zusammenfassung 10 References 11 Erklärung über die eigenständige Abfassung der Arbeit 12 Danksagung 13 Lebenslauf und Publikationsverzeichnis Appendix A.1 Immunostaining protocols A.2 Spectral Intensities Measured by 1H HRMAS MRS in 51 Samples A.3 Graphs for Correlations of Spectral Intensities and CaE% determined by QIAP in 34 Additional Regions of Interest

<p>Canines can detect different diseases simply by smelling different biological sample types, including  urine,  breath  and  sweat.  This  has  led  researchers  to  try  and  discovery  unique  volatile  organic compound (VOC) biomarkers. The power of VOC biomarkers lies in the fact that one day they may be able to be utilized for noninvasive, rapid and accurate diagnostics at a point of care using  miniaturized  biosensors.  However,  the  identity  of  the  specific  VOC  biomarkers  must  be  demonstrated before designing and fabricating sensing systems. Through  an  extensive  series  of  experiments,  VOCs  in  urine  are  profiled  by  solid  phase  microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS) to identify biomarkers for breast cancer using murine models. The results from these experiments indicated that  unique  classes  of  urinary  VOCs,  primarily  terpene/terpenoids  and  carbonyls,  are  potential  biomarkers  of  breast  cancer.  Through  implementing  chemometric  approaches,  unique  panels  of  VOCs  were  identified  for  breast  cancer  detection,  identifying  tumor  location,  determining  the  efficacy of dopaminergic antitumor treatments, and tracking cancer progression. Other diseases, including COVID-19 and hypoglycemia (low blood sugar) were also probed to identify volatile biomarkers present in breath samples.  VOC biomarker identification is an important step toward developing portable gas sensors, but  another  hurdle  that  exists  is  that  current  sensors  lack  selectivity  toward  specific  VOCs  of  interest.  Furthermore,  testing  sensors  for  sensitivity  and  selectivity  is  an  extensive  process  as  VOCs  must  be  tested  individually  because  the  sensors  do  not  have  modes  of  chromatographic  separation or compound identification. Another set of experiments is presented to demonstrate that SPME  fibers  can  be  coated  with  materials,  used  to  extract  standard  solutions  of  VOCs,  and  analyzed  by  GC-MS  to  determine  the  performance  of  various  gas  sensing  layers.  In  the  first  of  these  experiments,  polyetherimide  (PEI)  was  coated  onto  a  SPME  fiber  and  compared  to  commercial polyacrylate (PAA) fibers. The second experiment tuned the extraction efficiency of polyvinylidene fluoride (PVDF) - carbon black (CB) composites and showed that they had higher sensitivity  for  urinary  VOC  extraction  relative  to  a  polydimethylsiloxane  (PDMS)  SPME  fiber.  These results demonstrate SPME GC-MS can rapidly characterize and tune the VOC adsorption capabilities of gas sensing layers. </p>

No description available.

<p dir="ltr">Mass spectrometry imaging (MSI) is a powerful technique for visualizing the distribution of molecules within biological samples. Advancements in MSI instrumentation and computational tools have enabled the impactful applications of this technique across various fields including clinical research, drug discovery, forensics, microbiology, and natural products. Nanospray desorption electrospray ionization (nano-DESI), an ambient localized liquid extraction ionization technique, has proven valuable to the MSI community. Nano-DESI has been used for imaging of various molecules in biological samples including drugs, metabolites, lipids, N-linked glycans, and proteins.</p><p dir="ltr">My research has been focused on expanding the sensitivity and specificity of nano-DESI for biomolecular imaging. One of the newly developed methods employs ammonium fluoride NH₄F as a solvent additive to enhance the sensitivity of nano-DESI for the analysis of lipids in negative ionization mode. Secondly, methods were developed for the spatial mapping of isobaric and isomeric species in biological tissues by implementing nano-DESI MSI on a triple quadrupole (QqQ) mass spectrometer. This work used multiple reaction monitoring (MRM) mode of a QqQ with unit mass resolution to separate isobaric lipid species that require high mass resolving power and imaging of isomeric low-abundance species in tissue sections. Next, I demonstrate nano-DESI as a liquid extraction technique for imaging of N-linked glycans within biological tissue sections. Lastly, the spatial distribution of eicosanoids and specialized pro-resolving mediators (SPMs) in a mouse model for acetaminophen-induced liver injury (AILI) provides insights into the inflammation and resolution phases of AILI. Collectively, these developments have advanced the sensitivity, chemical specificity, and molecular coverage of nano-DESI for imaging of different classes of molecules in biological tissues.</p>

A study was undertaken of plants used for treatment of diabetic symptoms by traditional healers of the Eeyou Istchee Cree (Canada), Lukomir Highlanders (Bosnia & Herzegovina), and Q’eqchi’ Maya (Belize). All antidiabetic plants were ranked by syndromic importance value (SIV) based on 15 symptoms, all of which were recognized by the Cree and Maya and 8 by the Highlanders. The Cree used only 18 species, the Highlanders 41, and the Maya 150, numbers which reflect the diversity of flora in their region. Vaccinium (Ericaceae) was one of the few genera in all three regions and the only consensus genus between the Cree and Highlander study sites. The Q’eqchi’ Maya ethnobotany did not present any cross-cultural consensus genera with Cree or Highlander medicinal plants, perhaps due to major biogeographic differences. In ethnopharmacological studies, Vaccinium species and Q’eqchi’ antidiabetic plants were tested in an assay relevant to diabetes, the advanced glycation endproduct (AGE) inhibition assay. Boreal and tropical Vaccinium species were potent inhibitors of AGEs and demonstrated concentration dependent inhibition, with a half maximal inhibitory concentration (IC50) range of 5.93–100 µg/mL. Phenolic content ranged from 80.3 to 201 µg/mL in boreal samples and from 1470 to 2170 µg/mL in tropical samples. Tropical species have a greater phenolic content and AGE inhibition. Seven Q’eqchi’ antidiabetic plant species were tested and all plant extracts showed AGE-inhibition. The IC50s ranged from 40.8 to 733 µg/mL, and the most active was Tynanthus guatemalensis Donn.. Tynanthus guatemalensis IC50 was about fives times greater (less active) than the mean ± SE IC50 reported for six tropical Vaccinium species of Vaccinium (8.77 ± 0.79 μg/mL). The highest consensus and most active Maya antidiabetic plant, Tynanthus guatemalensis Donn. Sm. was discovered to be an important plant recorded in archeological artifacts from the Late Classic Maya period (~750 CE). Ancient Maya used a cross shaped sign (k’an glyph) as a decorative element on Late Classic polychrome vessels and murals. The sign was believed to be the xylem template for a plant used as a flavouring in cacao drinks. However, the plant was incorrectly identified in the literature as Pimenta dioica (L.) Merr. (common name: Allspice) based on a common name and aromatic plant quality – not from a botanical voucher specimen. Pimenta dioica wood does not have a cross shape visible in the xylem but a unique character visible after a cross section of T. guatemalensis, is the xylem's cross shape organization. Wood of T. guatemalensis' also has an "allspice" aroma. Tynanthus guatemalensis is most likely the true botanical template behind the ancient Maya k’an glyph and this finding would show the continuity of use of this medicinal plant from ancient to modern times. Vaccinium was selected for an in depth phytochemical analysis using modern metabolomic methods. Nuclear magnetic resonance (1H NMR) was used to evaluate leaf extract spectra to provide information on (1) the taxonomic identity and (2) quantities of bioactive metabolites across multiple sites. Spectra clearly differentiated leaf samples of V. angustifolium, V. boreale, V. corymbosum, V. macrocarpon, V. myrtilloides, V. myrtillus, V. ovalifolium, and V. uliginosum according to generic, subgeneric, specific, phenotypic circumscriptions. Quantification of chlorogenic acid and hyperoside were replicated with a method that is highly reproducible across multiple sites with different NMR equipment. This methodology provides an important new approach to taxonomy and quality control for plants and natural health products.

A study was undertaken of plants used for treatment of diabetic symptoms by traditional healers of the Eeyou Istchee Cree (Canada), Lukomir Highlanders (Bosnia & Herzegovina), and Q’eqchi’ Maya (Belize). All antidiabetic plants were ranked by syndromic importance value (SIV) based on 15 symptoms, all of which were recognized by the Cree and Maya and 8 by the Highlanders. The Cree used only 18 species, the Highlanders 41, and the Maya 150, numbers which reflect the diversity of flora in their region. Vaccinium (Ericaceae) was one of the few genera in all three regions and the only consensus genus between the Cree and Highlander study sites. The Q’eqchi’ Maya ethnobotany did not present any cross-cultural consensus genera with Cree or Highlander medicinal plants, perhaps due to major biogeographic differences. In ethnopharmacological studies, Vaccinium species and Q’eqchi’ antidiabetic plants were tested in an assay relevant to diabetes, the advanced glycation endproduct (AGE) inhibition assay. Boreal and tropical Vaccinium species were potent inhibitors of AGEs and demonstrated concentration dependent inhibition, with a half maximal inhibitory concentration (IC50) range of 5.93–100 µg/mL. Phenolic content ranged from 80.3 to 201 µg/mL in boreal samples and from 1470 to 2170 µg/mL in tropical samples. Tropical species have a greater phenolic content and AGE inhibition. Seven Q’eqchi’ antidiabetic plant species were tested and all plant extracts showed AGE-inhibition. The IC50s ranged from 40.8 to 733 µg/mL, and the most active was Tynanthus guatemalensis Donn.. Tynanthus guatemalensis IC50 was about fives times greater (less active) than the mean ± SE IC50 reported for six tropical Vaccinium species of Vaccinium (8.77 ± 0.79 μg/mL). The highest consensus and most active Maya antidiabetic plant, Tynanthus guatemalensis Donn. Sm. was discovered to be an important plant recorded in archeological artifacts from the Late Classic Maya period (~750 CE). Ancient Maya used a cross shaped sign (k’an glyph) as a decorative element on Late Classic polychrome vessels and murals. The sign was believed to be the xylem template for a plant used as a flavouring in cacao drinks. However, the plant was incorrectly identified in the literature as Pimenta dioica (L.) Merr. (common name: Allspice) based on a common name and aromatic plant quality – not from a botanical voucher specimen. Pimenta dioica wood does not have a cross shape visible in the xylem but a unique character visible after a cross section of T. guatemalensis, is the xylem's cross shape organization. Wood of T. guatemalensis' also has an "allspice" aroma. Tynanthus guatemalensis is most likely the true botanical template behind the ancient Maya k’an glyph and this finding would show the continuity of use of this medicinal plant from ancient to modern times. Vaccinium was selected for an in depth phytochemical analysis using modern metabolomic methods. Nuclear magnetic resonance (1H NMR) was used to evaluate leaf extract spectra to provide information on (1) the taxonomic identity and (2) quantities of bioactive metabolites across multiple sites. Spectra clearly differentiated leaf samples of V. angustifolium, V. boreale, V. corymbosum, V. macrocarpon, V. myrtilloides, V. myrtillus, V. ovalifolium, and V. uliginosum according to generic, subgeneric, specific, phenotypic circumscriptions. Quantification of chlorogenic acid and hyperoside were replicated with a method that is highly reproducible across multiple sites with different NMR equipment. This methodology provides an important new approach to taxonomy and quality control for plants and natural health products.

In forensic autopsies, accurately estimating the postmortem interval (PMI) is crucial. Traditional methods, relying on physical parameters and police data, often lack precision, particularly after approximately two days have passed since the person's death. New methods are increasingly focusing on analyzing postmortem metabolomics in biological systems, acting as a 'fingerprint' of ongoing processes influenced by internal and external molecules. By carefully analyzing these metabolomic profiles, which span a diverse range of information from events preceding death to postmortem changes, there is potential to provide more accurate estimates of the PMI. The limitation of available real human data has hindered comprehensive investigation until recently. Large-scale metabolomic data collected by the National Board of Forensic Medicine (RMV, Rättsmedicinalverket) presents a unique opportunity for predictive analysis in forensic science, enabling innovative approaches for improving  PMI estimation. However, the metabolomic data appears to be large, complex, and potentially nonlinear, making it difficult to interpret. This underscores the importance of effectively employing machine learning algorithms to manage metabolomic data for the purpose of PMI predictions, the primary focus of this project.  In this study, a dataset consisting of 4,866 human samples and 2,304 metabolites from the RMV was utilized to train a model capable of predicting the PMI. Random Forest (RF) and Artificial Neural Network (ANN) models were then employed for PMI prediction. Furthermore, feature selection and incorporating sex and age into the model were explored to improve the neural network's performance.  This master's thesis shows that ANN consistently outperforms RF in PMI estimation, achieving an R2 of 0.68 and an MAE of 1.51 days compared to RF's R2 of 0.43 and MAE of 2.0 days across the entire PMI-interval. Additionally, feature selection indicates that only 35% of total metabolites are necessary for comparable results with maintained predictive accuracy. Furthermore, Principal Component Analysis (PCA) reveals that these informative metabolites are primarily located within a specific cluster on the first and second principal components (PC), suggesting a need for further research into the biological context of these metabolites.  In conclusion, the dataset has proven valuable for predicting PMI. This indicates significant potential for employing machine learning models in PMI estimation, thereby assisting forensic pathologists in determining the time of death. Notably, the model shows promise in surpassing current methods and filling crucial gaps in the field, representing an important step towards achieving accurate PMI estimations in forensic practice. This project suggests that machine learning will play a central role in assisting with determining time since death in the future.

Les pollutions par les xénobiotiques, en particulier les pesticides, et les métaux lourds issus des activités agricoles présentent une grande complexité de composition chimique et de dynamique spatio-temporelle. La présence de bandes enherbées entre les parcelles cultivées et les cours d’eau permet une limitation de la diffusion de ces pollutions résiduelles vers les milieux naturels. Le compartiment végétal de ces bandes enherbées peut jouer de multiples rôles dans ce contexte de protection environnementale. L’étude comparative réalisée in situ et en conditions contrôlées de laboratoire a permis de mettre en évidence le rôle biologique du compartiment végétal avec son implication directe dans les processus in planta d’absorption, de stockage et/ou de dégradation au moins partielle. Un tel rôle phytoremédiateur est dépendant de la capacité des plantes à se maintenir sur ces milieux pollués, qui diffère selon l’espèce considérée et structure ainsi les communautés végétales des bandes enherbées. L’étude intégrative en conditions contrôlées des réponses des plantes aux interactions avec les xénobiotiques à faibles doses, à différentes échelles de complexité du fonctionnement végétal, a permis de montrer les effets de ces stress chimiques chez l’espèce modèle Arabidopsis thaliana et chez l’espèce prairiale Lolium perenne. Les xénobiotiques et les métaux lourds à des doses subtoxiques ont induit d’importants bouleversements métabolomiques et moléculaires chez ces espèces, avec des effets cryptiques de ces polluants et de leurs produits de dégradation. L’analyse en conditions de multi-pollution, qui reflètent de manière réaliste les pollutions péri-agricoles, a montré la complexité et la difficulté de prédiction des interactions entre les effets des contaminants en mélange. Ces mécanismes de réponses diffèrent selon l’espèce et le polluant et laissent supposer des divergences en termes de perception et/ou de transport des polluants, ou de coordination des réponses moléculaires et métaboliques. Arabidopsis a ainsi présenté une coordination de ses réponses orientée vers une augmentation des métabolites de stress, et une diminution des métabolites carbonés (sucres solubles), en parallèle de modifications de l’expression de gènes impliqués dans les défenses antioxydantes, les défenses contre les stress xénobiotiques, ou dans la dynamique des phytohormones. Le stress chimique a entraîné chez Lolium des modifications majeures du métabolisme azoté, ainsi qu’un remaniement des processus de photorespiration. L’analyse transcriptomique de cette espèce a de plus montré que la majorité des gènes identifiés sont impliqués dans des voies de transduction de signal, montrant ainsi la complexité des mécanismes de réponse et les couplages qui existent entre les signaux métaboliques, en particulier liés aux sucres, les voies de signalisation associées aux phytohormones, les signaux de stress et la photosynthèse. / Environmental pollutions by xenobiotics, especially by pesticides and heavy metals derived from agricultural activities, show an important complexity of chemical composition and of spatiotemporal dynamic. Vegetative filter strips between cultivated fields and streams limit the diffusion of these residual pollutions to natural environments. However, the exact biological role of plant in these buffer strips is poorly understood in this context of environmental and ecological protection. A comparative study carried out in situ and in controlled conditions highlighted the role of plant compartment in the processes of absorption, storage and/or partial degradation of pollutants in planta. Such capability of phytoremediation depends on the maintenance of a vegetal cover in area subjected to recurring flow of pesticides, it varies according to species and leads to the structuration of vegetative filter strip communities. An integrative study in controlled conditions of plant responses to low doses of pollutants allowed to analyze at different levels of complexity the impacts of chemical stresses on the model species Arabidopsis thaliana and the grassland species Lolium perenne. Low and sublethal doses of xenobiotics, associated degradation products and heavy metals induced cryptic perturbations at metabolic and molecular levels. Multi-pollution analyses, which reflect realistic conditions of environmental exposure, highlighted complex interactive effects between pollutants in mixture and the difficulty to predict them. The mechanisms of response to these chemical stresses differ according to the species and the pollutant, and suggest differences in term of perception and/or transport of pollutants, or of coordination of molecular and metabolic responses. Arabidopsis presented a coordination of its responses toward an increase of stress metabolites, a decrease of carbon metabolites (soluble carbohydrates), in parallel with modifications of gene expressions implicated on antioxidant defences, defence against xenobiotic stresses, or phytohormone dynamic. Chemical stress leads to major modifications of nitrogen metabolism in Lolium, and perturbations of processes of photorespiration. De novo transcriptomic analysis of Lolium therefore showed that a majority of identified genes are related to signal transduction pathways, highlighting the complexity of response mechanisms and the links between metabolic signals, especially linked to carbohydrate, hormonal signaling pathways, stress signals and photosynthesis. Subtoxic chemical stress induced cryptic re-engineering of plant processes that may explain the development of tolerance for some species and their persistence in area affected by residual pollution.