4,532 research outputs found
Parámetros genéticos de los caracteres morfológicos lineales de la raza caprina murciano-granadina y sus relaciones con otros caracteres funcionales
Linear appraisal systems (LAS) are effective strategies for systematically collecting zoometric information from animal populations. Traditionally applied LAS in goats was developed considering the variability and scales found in highly selected breeds. Implementing LAS may reduce time, personnel, and resource needs when performing zoometric large-scale collection. Moreover, selection for zoometrics defines individuals’ productive longevity, endurance, enhanced productive abilities, and consequently, long-term profitability. As a result, traditional LAS may no longer cover the different contexts of goat breeds widespread throughout the world, and departures from normality may be indicative of the different stages of selection at which a certain population can be found. In the first study, an evaluation of the distribution and symmetry properties of twenty-eight zoometric traits was developed. After symmetry analysis was performed, the scale readjustment proposal suggested specific strategies should be implemented such as scale reduction of lower or upper levels, determination of a setup moment to evaluate and collect information from young (up to 2 years) and adult bucks (over 2 years), the addition of upper categories in males due to upper values in the scale being incorrectly clustered together. Thus, the particular analysis of each variable permits determining specific strategies for each trait and serve as a model for other breeds, either selected or in terms of selection. The aim of the second study was to propose a method to optimize and validate LAS in opposition to traditional measuring protocols routinely implemented in Murciano-Granadina goats. The data sample consisted of 41323 LAS and traditional measuring records, belonging to 22727 herdbook registered primipara does, 17111 multipara does, and 1485 bucks. Each record comprised information on 17 linear traits for primipara and multipara does, and 10 traits for bucks. All zoometric parameters were scored on a 9-points scale. Cronbach’s alpha values suggested a high internal consistency of the optimized variable panel. Model fit, variability explanation power, and predictive power (MSE, AIC/AICc, and BIC, respectively) suggested a model comprising zoometric LAS scores performed better than traditional zoometry. Optimization procedures result in reduced models able to capture variability for dairy-related zoometric traits without noticeable detrimental effects on model validity properties. The third study aimed to perform a particular analysis of each variable that permits determining specific strategies for each trait and serves as a model for other breeds. Among the strategies proposed are the reduction/readjustment of the levels in the scale as it happens for limb-related traits, the extension of the scale as it occurs in the stature of males, or the subdivision of the scale used in males into two categories, bucks younger than two years and bucks of two years old and older. Murciano- Granadina goat breed has drifted towards better dairy-linked conformation traits but without losing the grounds of the zoometric basis which confers it with enhanced adaptability to the environment. Hence, such strategies can help to achieve a better understanding of the momentum of selection for dairy-linked zoometric traits in Murciano-Granadina population and their future evolution to enhance the profitability and efficiency of breeding plans. The objective of the fourth study was to evaluate the progress of heritabilities of the traits comprising the linear appraisal system in the Murciano-Granadina breed during the complete decade from December 2011 to December 2021. The estimated values for heritability were obtained from multivariate analyzes using the BLUP methodology and MTDFREML software. For 2021 heritabilities, a simple animal model was applied to records collected from 22727 primiparous goats and 17111 multiparous goats belonging to 85 herds. The model included the linear and quadratic and linear components of the covariates age and days in milk, respectively. The fixed effects considered in the model were herd, reproductive status, calving month, and herd/year interaction. The animal was considered as a random effect. The variables studied included five characteristics related to structure and capacity, two traits related to dairy structure, six related to the mammary system, and three related to legs and feet. The heritabilities for structure and capacity characters progressed from 0.22 to 0.28 including non-convergent variables in June 2012 to values between 0.10 and 0.41 with all variables converging in June 2021. Heritabilities for dairy structure progressed from 0.18 with nonconvergent variables in 2011 to 0.17 to 0.25 in 2021. Heritabilities for mammary system traits progressed from 0.12 to 0, 27 with non-convergent variables in 2012 to between 0.10 and 0.41 in 2021. For legs and feet, heritabilities progressed from 0.16 to 0.17 with non-convergent variables to 0.09 a 0.22. Genetic progress is not only evident in heritability values, but there has been a notable reduction in the standard error of heritabilities from 0.1000 (0.080-0.120) to 0.000 (0.000-0.001) from 2011 to 2021. These results provide evidence of the enhancement in the effectiveness and precision of the linear qualification system applied during the past decade and its successful integration into the breeding program of the Murciano- Granadina breed. The fifth study estimates genetic and phenotypic parameters for zoometric/LAS traits in Murciano-Granadina goats, estimate genetic and phenotypic correlations among all traits, and to determine whether major area selection would be appropriate or if adaptability strategies may need to be followed. Heritability estimates for the zoometric/LAS traits were low to high, ranging from 0.09 to 0.43 and the accuracy of estimation has improved after decades rendering standard errors negligible. Scale inversion of specific traits may need to be performed before major areas selection strategies are implemented. Genetic and phenotypic correlations suggest that negative selection against thicker bones and higher rear insertion heights, indirectly results in the optimization of selection practices in the rest of the traits, especially of those in the structure and capacity and mammary system major areas. The integration and implementation of the strategies proposed within Murciano-Granadina breeding program maximize selection opportunities and the sustainable international competitiveness of the Murciano- Granadina goat in the dairy goat breed panorama. The objective of the sixth study was to develop a discriminant canonical analysis (DCA) tool that permits outlining the role of the individual haplotypes of each component of the casein complex (αS1, β, αS2, and κ-casein) on zoometrics/linear appraisal breeding values. The relationship of the predicted breeding value for 17 zoometric/Linear appraisal traits and αS1, β, αS2, and κ-casein genes haplotypic sequences was assessed. Results suggest that, although a lack of significant differences (P>0.05) was reported across the predictive breeding values of zoometric/linear appraisal traits for αS1, αS2 and κ casein, significant differences were found for β Casein (P0,05) en los valores de cría predichos de los rasgos de zoometría/calificación lineal para la αS1, αS2 y κ-caseína, se encontraron diferencias significativas para la β-caseína (P<0,05), respectivamente. La presencia de secuencias haplotípicas de β-caseína GAGACCCC, GGAACCCC, GGAACCTC, GGAATCTC, GGGACCCC, GGGATCTC y GGGGCCCC, vinculadas a combinaciones diferenciales de mayores cantidades de leche de mayor calidad en términos de su composición, también puede estar relacionada con una mayor valoración zoométrica/lineal de la predicción de los valores de cría. La selección debe realizarse con cuidado, dado que la consideración de animales aparentemente deseables que presentan la secuencia haplotípica GGGATCCC en el gen de la β- caseína, debido a sus valores genéticos predichos positivos para ciertos rasgos de zoometría/calificación lineal, como la altura de la inserción trasera, la calidad ósea , la inserción anterior, la profundidad de ubre, la vista lateral de patas traseras y la vista trasera de patas traseras pueden conducir a una selección indirecta frente al resto de rasgos de zoometría/calificación lineal y a su vez conducir a una selección ineficiente hacia un tipo morfotipo lechero óptimo en cabras Murciano-Granadina. Por el contrario, la consideración de animales que presentan la secuencia haplotípica GGAACCCC implica también considerar animales que aumentan el potencial genético para todos los rasgos de zoometría/calificación lineal, haciéndolos así recomendables como reproductores. La información derivada de los presentes análisis mejorará la selección de individuos reproductores que busquen un tipo lechero bastante deseable, a través de la determinación de las secuencias haplotípicas que presentan en el locus β-caseína. Todos estos estudios persiguen la obtención de un conocimiento más profundo de los caracteres morfológicos lineales de la raza caprina Murciano-Granadina y sus relaciones con otras características funcionales. Esto sienta las bases para estrategias de normalización y mejora de la capacidad productiva y el morfotipo lechero de la cabra Murciano-Granadina y ayudará a alcanzar su consolidación competitiva en el panorama caprino lechero internacional
Natural and Technological Hazards in Urban Areas
Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events
Investigation of the metabolism of rare nucleotides in plants
Nucleotides are metabolites involved in primary metabolism, and specialized
metabolism and have a regulatory role in various biochemical reactions in all forms of life. While in other organisms, the nucleotide metabolome was characterized
extensively, comparatively little is known about the cellular concentrations of
nucleotides in plants. The aim of this dissertation was to investigate the nucleotide metabolome and enzymes influencing the composition and quantities of nucleotides in plants. For this purpose, a method for the analysis of nucleotides and nucleosides in plants and algae was developed (Chapter 2.1), which comprises efficient quenching of enzymatic
activity, liquid-liquid extraction and solid phase extraction employing a weak-anionexchange resin. This method allowed the analysis of the nucleotide metabolome of plants in great depth including the quantification of low abundant deoxyribonucleotides and deoxyribonucleosides. The details of the method were summarized in an article, serving as a laboratory protocol (Chapter 2.2).
Furthermore, we contributed a review article (Chapter 2.3) that summarizes the
literature about nucleotide analysis and recent technological advances with a focus on plants and factors influencing and hindering the analysis of nucleotides in plants, i.e., a complex metabolic matrix, highly stable phosphatases and physicochemical
properties of nucleotides. To analyze the sub-cellular concentrations of metabolites, a protocol for the rapid isolation of highly pure mitochondria utilizing affinity chromatography was developed (Chapter 2.4).
The method for the purification of nucleotides furthermore contributed to the
comprehensive analysis of the nucleotide metabolome in germinating seeds and in
establishing seedlings of A. thaliana, with a focus on genes involved in the synthesis of thymidilates (Chapter 2.5) and the characterization of a novel enzyme of purine nucleotide degradation, the XANTHOSINE MONOPHOSPHATE PHOSPHATASE (Chapter 2.6). Protein homology analysis comparing A. thaliana, S. cerevisiae, and H. sapiens led to the identification and characterization of an enzyme involved in the metabolite damage repair system of plants, the INOSINE TRIPHOSPHATE PYROPHOSPHATASE (Chapter 2.7). It was shown that this enzyme dephosphorylates deaminated purine nucleotide triphosphates and thus prevents their incorporation into nucleic acids. Lossof-function mutants senesce early and have a constitutively increased content of salicylic acid. Also, the source of deaminated purine nucleotides in plants was investigated and it was shown that abiotic factors contribute to nucleotide damage.Nukleotide sind Metaboliten, die am Primärstoffwechsel und an spezialisierten
Stoffwechselvorgängen beteiligt sind und eine regulierende Rolle bei verschiedenen
biochemischen Reaktionen in allen Lebensformen spielen. Während bei anderen
Organismen das Nukleotidmetabolom umfassend charakterisiert wurde, ist in Pflanzen
vergleichsweise wenig über die zellulären Konzentrationen von Nukleotiden bekannt.
Ziel dieser Dissertation war es, das Nukleotidmetabolom und die Enzyme zu
untersuchen, die die Zusammensetzung und Menge der Nukleotide in Pflanzen
beeinflussen. Zu diesem Zweck wurde eine Methode zur Analyse von Nukleotiden und
Nukleosiden in Pflanzen und Algen entwickelt (Kapitel 2.1), die ein effizientes Stoppen
enzymatischer Aktivität, eine Flüssig-Flüssig-Extraktion und eine
Festphasenextraktion unter Verwendung eines schwachen Ionenaustauschers
umfasst. Mit dieser Methode konnte das Nukleotidmetabolom von Pflanzen eingehend
analysiert werden, einschließlich der Quantifizierung von Desoxyribonukleotiden und
Desoxyribonukleosiden mit geringer Abundanz. Die Einzelheiten der Methode wurden
in einem Artikel zusammengefasst, der als Laborprotokoll dient (Kapitel 2.2).
Darüber hinaus wurde ein Übersichtsartikel (Kapitel 2.3) verfasst, der die Literatur
über die Analyse von Nukleotiden und die jüngsten technologischen Fortschritte
zusammenfasst. Der Schwerpunkt lag hierbei auf Pflanzen und Faktoren, die die
Analyse von Nukleotiden in Pflanzen beeinflussen oder behindern, d. h. eine komplexe
Matrix, hochstabile Phosphatasen und physikalisch-chemische Eigenschaften von
Nukleotiden.
Um die subzellulären Konzentrationen von Metaboliten zu analysieren, wurde ein
Protokoll für die schnelle Isolierung hochreiner Mitochondrien unter Verwendung einer
Affinitätschromatographie entwickelt (Kapitel 2.4).
Die Methode zur Analyse von Nukleotiden trug außerdem zu einer umfassenden
Analyse des Nukleotidmetaboloms in keimenden Samen und in sich etablierenden
Keimlingen von A. thaliana bei, wobei der Schwerpunkt auf Genen lag, die an der
Synthese von Thymidilaten beteiligt sind (Kapitel 2.5), sowie zu der Charakterisierung
eines neuen Enzyms des Purinnukleotidabbaus, der XANTHOSINE
MONOPHOSPHATE PHOSPHATASE (Kapitel 2.6). Eine Proteinhomologieanalyse, die A. thaliana, S. cerevisiae und H. sapiens
miteinander verglich führte zur Identifizierung und Charakterisierung eines Enzyms,
das an der Reparatur von geschädigten Metaboliten in Pflanzen beteiligt ist, der
INOSINE TRIPHOSPHATE PYROPHOSPHATASE (Kapitel 2.7). Es konnte gezeigt
werden, dass dieses Enzym desaminierte Purinnukleotidtriphosphate
dephosphoryliert und so deren Einbau in Nukleinsäuren verhindert.
Funktionsverlustmutanten altern früh und weisen einen konstitutiv erhöhten Gehalt an Salicylsäure auf. Außerdem wurde die Quelle der desaminierten Purinnukleotide in Pflanzen untersucht, und es wurde gezeigt, dass abiotische Faktoren zur
Nukleotidschädigung beitragen
The Application of Data Analytics Technologies for the Predictive Maintenance of Industrial Facilities in Internet of Things (IoT) Environments
In industrial production environments, the maintenance of equipment has a decisive influence on costs and on the plannability of production capacities. In particular, unplanned failures during production times cause high costs, unplanned downtimes and possibly additional collateral damage. Predictive Maintenance starts here and tries to predict a possible failure and its cause so early that its prevention can be prepared and carried out in time. In order to be able to predict malfunctions and failures, the industrial plant with its characteristics, as well as wear and ageing processes, must be modelled. Such modelling can be done by replicating its physical properties. However, this is very complex and requires enormous expert knowledge about the plant and about wear and ageing processes of each individual component. Neural networks and machine learning make it possible to train such models using data and offer an alternative, especially when very complex and non-linear behaviour is evident.
In order for models to make predictions, as much data as possible about the condition of a plant and its environment and production planning data is needed. In Industrial Internet of Things (IIoT) environments, the amount of available data is constantly increasing. Intelligent sensors and highly interconnected production facilities produce a steady stream of data. The sheer volume of data, but also the steady stream in which data is transmitted, place high demands on the data processing systems. If a participating system wants to perform live analyses on the incoming data streams, it must be able to process the incoming data at least as fast as the continuous data stream delivers it. If this is not the case, the system falls further and further behind in processing and thus in its analyses. This also applies to Predictive Maintenance systems, especially if they use complex and computationally intensive machine learning models. If sufficiently scalable hardware resources are available, this may not be a problem at first. However, if this is not the case or if the processing takes place on decentralised units with limited hardware resources (e.g. edge devices), the runtime behaviour and resource requirements of the type of neural network used can become an important criterion.
This thesis addresses Predictive Maintenance systems in IIoT environments using neural networks and Deep Learning, where the runtime behaviour and the resource requirements are relevant. The question is whether it is possible to achieve better runtimes with similarly result quality using a new type of neural network. The focus is on reducing the complexity of the network and improving its parallelisability. Inspired by projects in which complexity was distributed to less complex neural subnetworks by upstream measures, two hypotheses presented in this thesis emerged: a) the distribution of complexity into simpler subnetworks leads to faster processing overall, despite the overhead this creates, and b) if a neural cell has a deeper internal structure, this leads to a less complex network. Within the framework of a qualitative study, an overall impression of Predictive Maintenance applications in IIoT environments using neural networks was developed. Based on the findings, a novel model layout was developed named Sliced Long Short-Term Memory Neural Network (SlicedLSTM). The SlicedLSTM implements the assumptions made in the aforementioned hypotheses in its inner model architecture.
Within the framework of a quantitative study, the runtime behaviour of the SlicedLSTM was compared with that of a reference model in the form of laboratory tests. The study uses synthetically generated data from a NASA project to predict failures of modules of aircraft gas turbines. The dataset contains 1,414 multivariate time series with 104,897 samples of test data and 160,360 samples of training data.
As a result, it could be proven for the specific application and the data used that the SlicedLSTM delivers faster processing times with similar result accuracy and thus clearly outperforms the reference model in this respect. The hypotheses about the influence of complexity in the internal structure of the neuronal cells were confirmed by the study carried out in the context of this thesis
Solidification behavior of high nitrogen stainless steels and establishment of a one-dimensional heat transfer framework
Duplex stainless steel (DSS) has excellent corrosion resistance and mechanical properties due to its dual-phase structure. The solidification process is the key to determining the structure of materials, and an in-depth investigation of solidification can help us better understand the properties of materials. The melting and solidification processes of S32101 DSS were investigated using high temperature confocal microscopy (HTCM)
Rational development of stabilized cyclic disulfide redox probes and bioreductive prodrugs to target dithiol oxidoreductases
Countless biological processes allow cells to develop, survive, and proliferate. Among these, tightly balanced regulatory enzymatic pathways that can respond rapidly to external impacts maintain dynamic physiological homeostasis. More specifically, redox homeostasis broadly affects cellular metabolism and proliferation, with major contributions by thiol/disulfide oxidoreductase systems, in particular, the Thioredoxin Reductase Thioredoxin (TrxR/Trx) and the Glutathione Reductase-Glutathione-Glutaredoxin (GR/GSH/Grx) systems.
These cascades drive vital cellular functions in many ways through signaling, regulating other proteins' activity by redox switches, and by stoichiometric reductant transfers in metabolism and antioxidant systems. Increasing evidence argues that there is a persistent alteration of the redox environment in certain pathological states, such as cancer, that heavily involve the Trx system: upregulation and/or overactivity of the Trx system may support or drive cancer progression, making both TrxR and Trx promising targets for anti-cancer drug development.
Understanding the biochemical mechanisms and connections between certain redox cascades requires research tools that interact with them. The state-of-the-art genetic tools are mostly ratiometric reporters that measure reduced:oxidized ratios of selected redox pairs or the general thiol pool. However, the precise cellular roles of the central oxidoreductase systems, including TrxR and Trx, remain inaccessible due to the lack of probes to selectively measure turnover by either of these proteins. However, such probes would allow measuring their effective reductive activity apart from expression levels in native systems, including in cells, animals, or patient samples. They are also of high interest to identify chemical inhibitors for TrxR/Trx in cells and to validate their potential use as anti-cancer agents (to date, there is no selective cellular Trx inhibitor, and most known TrxR inhibitors were not comprehensively evaluated considering selectivity and potential off-targets). However, small molecule redox imaging tools are underdeveloped: their protein specificity, spectral properties, and applicability remain poorly precedented.
This work aimed to address this opportunity gap and develop novel, small molecule diagnostic and therapeutic tools to selectively target the Trx system based on a modular trigger cargo design: artificial cyclic disulfide substrates (trigger) for oxidoreductases are tethered to molecular agents (cargo) such that the cargo’s activity is masked and is re-established only through reduction by a target protein.
The rational design of these novel reduction sensors to target the cell's strongest disulfide-reducing enzymes was driven by the following principles: (i) cyclic disulfide triggers with stabilized ring systems were used to gain low reduction potentials that should resist reduction except by the strongest cellular reductases, such as Trx; and (ii) the cyclic topology also offers the potential for kinetic reversibility that should select for dithiol-type redox proteins over the cellular monothiol background. Creating imaging agents based on such two-component designs to selectively measure redox protein activity in native cells required to combine the correct trigger reducibility, probe activation kinetics, and imaging modalities and to consider the overall molecular architecture.
The major prior art in this field has applied cyclic 5-membered disulfides (1,2 dithiolanes) as substrates for TrxR in a similar way to create such tools. However, this motif was described elsewhere as thermodynamically instable and was due to widely used for dynamic covalent cascade reactions. By comparing a novel 1,2 dithiolane-based probe to the state-of-the-art probes, including commercial TrxR sensors, by screening a conclusive assay panel of cellular TrxR modulations, I clarified that 1,2 dithiolanes are not selective substrates for TrxR in biological settings (Nat Commun 2022).
Instead, aiming for more stable ring systems and thus more robust redox probes, during this work, I developed bicyclic 6 membered disulfides (piperidine fused 1,2 dithianes) with remarkably low reduction potentials. I showed that molecular probes using them as reduction sensors can be mostly processed by thioredoxins while being stable against reduction by GSH. The thermodynamically stabilized decalin like topology of the cis-annelated 1,2 dithianes requires particularly strong reductants to be cleaved. They also select for dithiol type redox proteins, like Trx, based on kinetic reversibility and offer fast cyclization due to the preorganization by annelation (JACS 2021).
This work further expanded the system’s modularity with structural cores based on piperazine-fused 1,2 dithianes with the two amines allowing independent derivatization. Diagnostic tools using them as reduction sensors proved equally robust but with highly improved activation kinetics and were thus cellularly activated. Cellular studies evolved that they are substrates for both Trxs and their protein cousins Grxs, so measuring the cellular dithiol protein pool rather than solely Trx activity (preprint 2023).
Finally, a trigger based on a slightly adapted reduction sensor, a desymmetrized 1,2 thiaselenane, was designed for selective reduction by TrxR’s selenol/thiol active site, then combined with a precipitating large Stokes’ shift fluorophore and a solubilizing group, to evolve the first selective probe RX1 to measure cellular TrxR activity, which even allowed high throughput inhibitor screening (Chem 2022).
The central principle of this work was further advanced to therapeutic prodrugs based on the duocarmycin cargo (CBI) with tunable potency (JACS Au 2022) that can be used to create off-to-on therapeutic prodrugs. Such CBI prodrugs employing stabilized 1,2 dichalcogenide triggers proved to be cytotoxins that depend on Trx system activity in cells. They could further be exploited for cell-line dependent reductase activity profiling by screening their redox activation indices, the reduction-dependent part of total prodrug activation, in 177 cell lines. Beyond that, these prodrugs were well-tolerated in animals and showed anti-cancer efficacy in vivo in two distinct mouse tumor models (preprint 2022).
Taken together, I introduced unique monothiol-resistant reducible motifs to target the cellular Trx system with chemocompatible units for each for TrxR and Trx/Grx, where the cyclic nature of the dichalcogenides avoids activation by GSH. By using them with distinct molecular cargos, I developed novel selective fluorescent reporter probes; and introduced a new class of bioreductive therapeutic constructs based on a common modular design. These were either applied to selectively measure cellular reductase activity or to deliver cytotoxic anti cancer agents in vivo. Ongoing work aims to differentiate between the two major redox effector proteins Trx and Grx, requiring additional layers of selectivity that may be addressed by tuned molecular recognition. The flexible use of various molecular cargos allows harnessing the same cellular redox machinery by either probes or prodrugs. This allows predictive conclusions from diagnostics to be directly translated into therapy and offers great potential for future adaptation to other enzyme classes and therapeutic venues.Die zelluläre Redox-Homöostase hängt von Thiol/Disulfid-Oxidoreduktasen ab, die den Stoffwechsel, die Proliferation und die antioxidative Antwort von Zellen beeinflussen. Die wichtigsten Netzwerke sind die Thioredoxin Reduktase-Thioredoxin (TrxR/Trx) und Glutathion Reduktase-Glutathion-Glutaredoxin (GR/GSH/Grx) Systeme, die über Redox-Schalter in Substratproteinen lebenswichtige zelluläre Funktionen steuern und so an der Redox-Regulation und -Signalübertragung beteiligt sind. Persistente Veränderungen des Redoxmilieus in pathologischen Zuständen, wie z. B. bei Krebs, sind in hohem Maße mit dem Trx-System verbunden. Eine Hochregulierung und/oder Überaktivität des Trx-Systems, die bei vielen Krebsarten auftreten, unterstützt zudem das Fortschreiten des Krebswachstums, was TrxR/Trx zu vielversprechenden Zielproteinen für die Entwicklung neuer Krebsmedikamente macht.
Um die biochemischen Prozesse dahinter zu erforschen, sind spezielle Techniken zur Visualisierung und Messung enzymatischer Aktivität nötig. Die hierzu geeigneten, meist genetischen Sensoren messen ratiometrisch das Verhältnis reduzierter/oxidierter Spezies in zellulärem Umfeld oder spezifisch ausgewählte Redoxpaare. Die weitere Erforschung der exakten Funktion von TrxR/Trx und deren Substrate ist jedoch durch mangelnde Nachweismethoden limitiert. Diese sind außerdem zur Validierung chemischer Hemmstoffe für TrxR/Trx in Zellen und deren potenziellen Verwendung als Krebsmittel von großem Interesse. Bislang gibt es keinen selektiven zellulären Trx-Inhibitor und potenzielle Off-Target-Effekte der bekannten TrxR-Inhibitoren wurden nicht abschließend bewertet.
Ziel dieser Arbeit ist die Entwicklung niedermolekularer, diagnostischer und therapeutischer Werkzeuge, die selektiv auf das Trx-System abzielen und auf einem modularen Trigger-Cargo Design basieren. Hierzu werden zyklische Disulfid-Substrate (Trigger) für Oxidoreduktasen so mit molekularen Wirkstoffen (Cargo) verknüpft, dass dabei die Wirkstoffaktivität maskiert, und erst nach Reduktion durch ein Zielprotein wiederhergestellt wird. Diese neuartigen, synthetischen Reduktionssensoren basieren auf den folgenden Grundprinzipien: (i) Zyklische Disulfide sind thermodynamisch stabilisiert und können nur durch die stärksten Reduktasen gespalten werden; und (ii) die zyklische Topologie ermöglicht die kinetische Reversibilität der zwei Thiol-Disulfid-Austauschreaktionen, die eine erste Reaktion mit Monothiolen, wie z. B. GSH, sofort umkehrt und so eine vollständige Reduktion verhindert.
Die meisten früheren Arbeiten auf diesem Gebiet verwendeten ein zyklisches, fünfgliedriges Disulfid (1,2 Dithiolan) als Substrat für TrxR. Das gleiche Strukturmotiv wurde jedoch an anderer Stelle als thermodynamisch instabil beschrieben und aufgrund dieser Eigenschaft explizit für dynamische Kaskadenreaktionen verwendet. Deshalb vergleicht diese Arbeit zu Beginn einen neuen 1,2 Dithiolan basierten fluorogenen Indikator mit bestehenden, z. T. kommerziellen, Redox Sonden für TrxR in einer Reihe von Zellkultur-Experimenten unter Modulation der zellulären TrxR Aktivität und stellt so einen Widerspruch in der Literatur klar: 1,2 Dithiolane eignen sich nicht als selektive Substrate für TrxR, da sie labil sowohl gegen die Reduktion durch andere Redoxproteine, als auch gegen den Monothiol Hintergrund in Zellen sind (Nat. Commun. 2022).
Als alternatives Strukturmotiv wird in dieser Arbeit ein bizyklisches sechsgliedriges Disulfid (anneliertes 1,2 Dithian) etabliert. Durch sein niedriges Reduktionspotenzial, also seine hohe Resistenz gegen Reduktion, werden molekulare Sonden basierend auf diesem 1,2 Dithian als Reduktionssensor fast ausschließlich von Trx aktiviert, nicht aber von TrxR oder GSH (JACS 2021). Dieses Kernmotiv bestimmt dabei die Reduzierbarkeit, und damit die Enzymspezifität, durch seine zyklische Natur und die Annelierung, auch unter Verwendung unterschiedlicher Farb-/Wirkstoffe. Auf dieser Grundlage konnte die molekulare Struktur durch einen weiteren Modifikationspunkt für die flexible Verwendung weiterer funktioneller Einheiten ergänzt werden. Obwohl zelluläre Studien ergaben, dass diese neuartigen 1,2 Dithian Einheiten in Zellen sowohl Trx als auch das strukturell verwandte Grx adressieren, sind die daraus resultierenden diagnostischen Moleküle wertvoll, um den katalytischen Umsatz zellulärer Dithiol-Reduktasen, der sogenannten Trx Superfamilie, selektiv anzuzeigen (Preprint 2023).
Begünstigt durch das modulare Moleküldesign stellt diese Arbeit zudem das erste Reportersystem RX1 zum selektiven Nachweis der TrxR-Aktivität in Zellen vor. Es basiert auf der Verwendung eines zyklischen, unsymmetrischen Selenenylsulfid-Sensors (1,2 Thiaselenan), der selektiv von dem einzigartigen Selenolat der TrxR angegriffen wird, und dadurch letztlich nur von TrxR reduziert werden kann. RX1 eignete sich zudem für eine Hochdurchsatz-Validierung bestehender TrxR Inhibitoren und unterstreicht dadurch den kommerziellen Nutzen derartiger Diagnostika (Chem 2022).
Das zentrale Trigger-Cargo Konzept dieser Arbeit wurde für therapeutische Zwecke weiterentwickelt und nutzt dabei den einzigartigen Wirkmechanismus der Duocarmycin-Naturstoffklasse (CBI) (JACS Au 2022) zur Entwicklung reduktiv aktivierbarer Therapeutika. CBI Prodrugs basierend auf stabilisierten Redox-Schaltern (1,2 Dithiane für Trx; 1,2 Thiaselenan für TrxR) reagierten signifikant auf TrxR-Modulation in Zellen. Sie wurden darüber hinaus durch das Referenzieren ihrer Aktivität gegenüber nicht-reduzierbaren Kontrollmoleküle für die Erstellung zelllinienabhängiger Profile der Reduktaseaktivität in 177 Zelllinien genutzt. Schließlich waren diese neuen Krebsmittel im Tiermodell gut verträglich und zeigten in zwei verschiedenen Mausmodellen eine krebshemmende Wirkung (Preprint 2022b).
Zusammenfassend präsentiert diese Dissertation monothiol-resistente reduzierbare Trigger-Einheiten für das zelluläre Trx-System zur Entwicklung neuartiger, selektiver Reporter-Sonden, sowie eine neue Klasse reduktiv aktivierbarer Krebsmittel auf Basis eines adaptierbaren Trigger-Cargo Designs. Diese fanden entweder zur selektiven Messung zellulärer Proteinaktivität oder zum Einsatz als Antikrebsmittel Verwendung. Es wurden chemokompatible Motive sowohl für TrxR als auch für Trx/Grx identifiziert, wobei deren zyklische Natur eine Aktivierung durch GSH verhindert. Eine weitere Differenzierung zwischen den beiden Redox-Proteinen Trx und Grx und anderen Proteinen der Trx-Superfamilie erfordert eine zusätzliche Ebene der Selektierung, z. B. durch molekulare Erkennung, und ist Gegenstand laufender Arbeiten.
Die flexible Verwendung verschiedener molekularer Wirkstoffe ermöglicht dabei die „Pipeline-Entwicklung“ von Diagnostika und Therapeutika, die von der zellulären Redox-Maschinerie analog umgesetzt werden, und dadurch Schlussfolgerungen aus der Diagnostik direkt auf eine Therapie übertragbar machen. Dies birgt großes Potenzial für künftige Entwicklungen bei einer potenziellen Übertragung des modularen Konzepts auf andere Enzymklassen und therapeutische Einsatzgebiete
Systemic Circular Economy Solutions for Fiber Reinforced Composites
This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials
A framework for the economic-environmental feasibility assessment of short-sea shipping autonomous vessels
Despite the pursued autonomous ships initiatives, the lack of information on emerging technologies and their costs along with the limited investigations of the autonomy effects on logistics render these vessels feasibility assessment challenging. This study aims at developing an overarching framework to support decisions for the transition to autonomous shipping. The ship lifetime capital, operational and voyage expenditures are estimated to quantify the economic-environmental impact and required investments. Several scenarios are defined to address the input data uncertainty. The case of a short-sea shipping cargo vessel operating in the Norwegian waters is studied, considering its conversion to operate autonomously, as well as the next generation crewless ship design. The derived results demonstrate that the converted autonomous ships can reduce the lifetime present value by 1–12% and the carbon emissions by 4%, whereas the new autonomous design leads to their further reductions by 3–4% and 4–7%, respectively. These savings can further increase by 6–7% by reducing the autonomous ships sailing speed, as crew replacement periods are not required. The estimated economic margin indicates that the next-generation autonomous ships can adopt greener technologies, such as hydrogen or green ammonia, to achieve the targeted carbon emissions reduction
Continuous Glucose Monitoring for the diagnosis of Gestational Diabetes Mellitus.
Gestational Diabetes Mellitus (GDM) incidence and negative outcomes are increasing worldwide. The validity of the oral glucose tolerance test (OGTT) for GDM diagnosis remains contested. Continuous Glucose Monitoring (CGM) could represent a more acceptable and replicable test. Aim of this project was to assess CGM for GDM diagnosis.
This PhD thesis is based on five projects: a systematic review of the diagnostic indicators of GDM, an online questionnaire to recruit women at high and low risk of GDM, a retrospective cohort study on the use of the Medtronic iPro2 CGM device for GDM diagnosis, a prospective cohort study on the use of the Abbott Freestyle Libre PRO 2 CGM and a survey study on women and healthcare providers perception of both methods. CGM data were analysed as distribution parameters (mean, CV, SD, maximum value), variability parameters (MAGE and MODD) and time spent in the recommended range, then combined in a CGM score of Variability (CGMSV).
In the systematic review were included 174 full-text articles on blood, ultrasound, post-natal and amniotic fluid biomarkers. The ultrasound gestational diabetic score (UGDS) was the most promising biomarker for triangulation. In the GDM risk questionnaire (n=45), triangulation of a composite risk factors score (RFS) with CGMSV and OGTT results highlighted six possible OGTT misdiagnoses (discordant with RFS and CGMSV). In the Medtronic pilot Study (n=73), GDM women (n=33) had significantly higher RFS and CGMSV. The triangulation analysis (n=60) suggested 12 probable misdiagnoses. In the Abbott pilot study (n=87), no significant demographic nor CGM data difference was found between NGT and GDM, possibly due to the small GDM sample size (n=13). With triangulation, 11 OGTT results were potentially false. UGDS (n=22) was positive in only one woman, considered a true negative otherwise. In the survey study, women reported significantly higher acceptability of CGM versus OGTT (n=70 and n=60, respectively), and 94% would recommend CGM for GDM diagnosis. HCP (n=30) scored CGM acceptability significantly lower than women and expressed doubts about the correlation between CGM data and perinatal outcomes.
CGM represents a more acceptable alternative to OGTT for GDM diagnosis. HCP expressed doubt about CGM accuracy, and issues of establishing superiority to OGTT remain. Further research on larger cohorts of patients with additional triangulation elements is needed to confirm CGM acceptability and accuracy and refine its use
Building Energy Modeling and Studies of Electric Power Distribution Systems with Distributed Energy Resources
There is significant opportunity for savings in energy and investment from improved performance of electric Power Distribution Systems (PDSs) through optimal planning and operation of conventional voltage-controlling devices. Novel multi-step model conversion and optimal capacitor planning (OCP) procedures are proposed for large-scale utility PDSs and are exemplified with an existing utility circuit of approximately 4,000 buses. Simulated optimal control and operation is achieved with a cluster-based approach that utilizes load-forecasting to minimize equipment degradation by intelligently dispersing device setting adjustments over time such that they remain most applicable. Improved performance may also be achieved through smart building technologies and Virtual Power Plant (VPP) control of increasingly more prevalent Distributed Energy Resources (DERs). The established simulation test bed for PDSs incorporates DERs to evaluate VPP implementations and an optimization process for control timing is proposed that minimizes targeted peak power and possible resulting increase in total daily energy. The advanced VPP controls incorporate the Consumer Technology Association (CTA) 2045 standard and EnergyStar performance characterizations to leverage HVAC systems as Generalized Energy Storage (GES) for load manipulation and to support the integration of demand-side generating DERs, such as local solar Photo-Voltaic (PV) systems
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