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Verteilung und Determinanten der psychosozialen Gesundheit bei Grundschulkindern in Tansania: Eine Querschittsdatenanalyse der KaziAfya-Studie
No full textHintergrund: Die psychosoziale Gesundheit wird als Mass zur Beschreibung des mentalen, sozialen und psychischen Wohlbefindens eines Menschen herangezogen. Trotz hoher Suizidraten und psychosozialer Herausforderung, ist die psychosoziale Gesundheit von Menschen in Subsahara-Afrika bisher kaum untersucht. Speziell Grundschulkinder sind aufgrund ihres jungen Alters eine gefährdete Gruppe. Diese Arbeit versucht diese Forschungslücke zu schliessen, indem sie die psychosoziale Gesundheit von Grundschulkindern in Tansania auf geschlechts- und klassenstufenspezifische Unterschiede untersucht. Ausserdem werden die Determinanten “Schulstress”, “Schlafgesundheit” und “körperliche Aktivität” auf ihren Einfluss auf die psychosoziale Gesundheit geprüft.
Methoden: An vier Grundschulen in Tansania wurden unter 646 Kindern der Schulklassen 1 bis 4 die psychosoziale Gesundheit (HRQoL), die körperliche Aktivität (Akzelerometermessung), die Schlafgesundheit (Composite Sleep Health Score) und der Schulstress (Health-Behavior in School-Aged Children [HBSC]) erhoben und durch statistische Methoden ausgewertet. Körperliche Aktivität, Schlafgesundheit und Schulstress wurden im Rahmen einer multiplen linearen Regressionsanalyse als mögliche Determinanten der psychosozialen Gesundheit untersucht.
Ergebnisse: Es konnte kein statistisch geschlechtsspezifischer Unterschied in der psychosozialen Gesundheit festgestellt werden. Im Klassenstufenvergleich zeigt sich, dass Kinder der vierten Klassenstufe eine signifikant höhere psychosoziale Gesundheit aufweisen als Kinder der ersten Klassenstufe. Von den drei untersuchten Prädiktoren sagt lediglich der Prädiktor "Schulstress” die psychosoziale Gesundheit von Grundschulkindern in Tansania signifikant positiv vorher. Explorative Analysen zeigten, dass Kinder der vierten Klasse bedeutsam mehr Schulstress und geringere Schlafgesundheit und körperliche Aktivität aufwiesen als die niedrigeren Klassenstufen.
Diskussion: Die verbesserte psychosoziale Gesundheit in der vierten Klassenstufe wird darauf zurückgeführt, dass Kinder im Grundschulalter primär nach Kompetenzerwerb streben, und Kinder der vierten Klasse dieses Bedürfnis möglicherweise stärker erfüllen als Kinder der ersten Klasse. Der positive Zusammenhang des Schulstresses mit der psychosozialen Gesundheit wird auf den Effekt zwischen den Klassenstufen zurückgeführt. Kinder der höheren Klassenstufen zeigen zwar mehr Stress und gleichzeitig eine höhere psychosoziale Gesundheit, haben aber möglicherweise zwischenzeitlich mehr Resilienz erworben, um ihr psychosoziales Wohlbefinden zu steigern und aufrechtzuerhalten. Diese Variable sollte daher in künftigen Studien einbezogen werden. Zuletzt sollten künftige Studien die Entwicklungen und Lebensereignisse innerhalb der vierten Klassenstufe näher beleuchten, um die Verschlechterung in der Schlafgesundheit, dem Schulstress und der körperlichen Aktivität nachzuvollziehen und entsprechende Präventionsprogramme entwickeln und einsetzen zu können
Bayesian approaches to discovery and inference with non-linear causal models
Get PDFCausal discovery and inference from observational data is an essential problem in statistics posing both modeling and computational challenges. Bayesian network models provide a rigorous approach to the problem by compactly describing the joint distribution and the causal relationships through a graph. When the underlying graph is unknown, structure learning methods are used to estimate it from the available data. Such a task poses considerable challenges, but is key to describing data-generating mechanisms in many complex applications. This thesis presents new developments in structure learning and causal inference, with a focus on computational efficiency and non-parametric, Bayesian approaches for observational data.
Firstly, we introduce a new constraint-based structure learning algorithm based on the popular PC algorithm. The new method, called the dual PC algorithm, leverages the inverse relationship between covariance and precision matrices. By exploiting block matrix inversions it can also perform tests on partial correlations of complementary (or dual) conditioning sets. The dual PC algorithm proceeds by first considering marginal and full-order conditional independence relationships and progressively moving to central-order ones. Simulation studies show that the dual PC algorithm outperforms the classic PC algorithm both in terms of run time and in recovering the underlying network structure. We also study the effects of deviations from Gaussianity on the performance of the classical and dual PC algorithms, and propose alternative approaches when consistency no longer holds.
Next, we address the problem of learning the structure of Gaussian Process Networks (GPNs), a class of Bayesian networks which employ Gaussian processes as priors for the conditional expectation of each variable given its parents. We adopt a Bayesian approach, accounting for uncertainty in the graphical estimate via a posterior distribution over structures. We show how Monte Carlo and Markov chain Monte Carlo methods can be used to sample from the graph posterior distribution, allowing accurate posterior inference in high-dimensional cases. Our method outperforms state-of-the-art algorithms in recovering the graphical structure of the network in various non-linear simulation settings. The proposed method is also shown to provide an accurate approximation of the network's posterior distribution.
Finally, we consider the problem of the Bayesian estimation of the effects of hypothetical interventions in the GPN model. We detail how to perform causal inference on GPNs by simulating the effect of an intervention across the whole network and propagating the effect of the intervention on downstream variables. A simpler computational approximation can be derived by estimating the intervention distribution as a function of local variables only, modeling the conditional distributions via additive Gaussian processes. We extend both frameworks beyond the case of a known causal graph, incorporating uncertainty about the causal structure using the previously developed Bayesian structure learning methods. Simulation studies show that our approach is able to identify the effects of hypothetical interventions with non-Gaussian, non-linear observational data and accurately reflect the posterior uncertainty of the causal estimates. Finally we compare the results of our GPN-based causal inference approach to existing methods on a dataset of A. thaliana gene expressions
The association between healthy habits and healthy minds in today’s youth
Get PDFThe thesis is rooted in Antonovsky’s salutogenesis theory, emphasizing how human experiences are shaped by opportunities, particularly social capital (SC) and self-efficacy (SE), contributing to individuals' sense of coherence. Analyzing health through the World Health Organization’s definition as holistic well-being, this theoretical framework has been applied in Switzerland, a high-income, multicultural nation, and Palestine, a low-income country with a youthful, collective society.
In Switzerland, the thesis assessed the relationship between quality of life (QoL) and accelerometer-derived physical activity (PA) using data from the SOPHYA cohort (2013-2019) of Swiss youth aged 6 to 16. Two main studies examined cross-sectional and prospective associations between PA and QoL.
In Palestine, the thesis planned a study exploring SC, SE, and social contagion's role in students' lifestyle and mental health, with the study protocol published in BMJ Open (Darkhawaja R et al. BMJ Open 2022 Jan 19; 12(1):e049033).
The thesis confirmed a positive association between device-measured moderate-to-vigorous physical activity (MVPA) and QoL in Swiss youth, especially cross-sectionally. However, it also revealed a simultaneous decline in both PA and QoL with aging, highlighting the importance of age-specific health interventions promoting both PA and QoL.
Recommendations included shorter follow-up times and more longitudinal measurements in future studies to better understand the sustainable benefits of PA promotion on QoL in youth
Inferring chemistry from data with atomistic machine learning: applications to potential energy surfaces and chemical space
Get PDFThe influence of machine learning (ML) in chemistry is undeniable, and it is a powerful tool to obtain chemical insights from large amounts of data. In particular, ML is a perfect tool for exploring chemical space because it allows to obtain good results in a relatively short time. The quality of the results obtained with an ML model highly depends on the data used to train it. After introducing fundamental concepts in Chapters 1 and 2, Chapter 3 deals with the effect of training data on predicting a chemical property. Results show that adequate predictions require a large chemical diversity in the training set. This can be obtained by either using many chemical motives or employing an adequate number of conformers. Once the effect of the data is clear, the next aspect evaluated is the confidence in the predictions obtained with ML models. To this end, two uncertainty quantification strategies based on Bayesian statistics were implemented. The insights into the interplay between error, uncertainty and chemistry provide us with an essential understanding of how a chemical database can be constructed. The previous chapters deal with the use of data obtained from ab-initio calculations. Nevertheless, it is expected that a model can reproduce experimental results. Chapter 5 deals with improving a potential energy surface (PES) based on experimental results by employing a procedure called morphing. Continuing with the study of PES, Chapter 6 uses one of the models introduced in Chapter 3 to study a reactive process. In this case, the performance of detecting outliers through uncertainty quantification was evaluated and compared with the other two strategies. Finally, Chapter 7 plays with adding samples from the conformational space represented by a PES to chemical databases biased towards a chemical insight. The last chapter summarizes the different aspects of the relationships between data and chemistry for exploring chemical space or working with PES. Also, it provides insights into future extensions of the projects presented here
Development of an artificial peroxidase based on a human carbonic anhydrase protein
Get PDFArtificial metalloenzymes are constructed through the incorporation of a metal catalyst into a protein scaffold. The protein scaffold provides second coordination sphere around the catalytic moiety, endowing it with various attributes to the reaction that the free catalyst does not possess. In this PhD thesis, we will present the development of an artificial peroxidase (ArPase) by combining an Fe-TAML (TAML = Tetra Amide Macrocyclic Ligand) catalyst with a human carbonic anhydrase scaffold. We will show that the protein scaffold enhances the peroxidase activity of the catalyst. Through directed evolution facilitated by screening on cell lysates, the activity of ArPase was improved both in terms of total turnover number and enantiomeric excess. Additionally, a library of chimeric hCAII scaffolds was explored for further improving the performance of the ArPase.
Overall, this thesis highlights the advantage of “genetic” optimization of a Fe-TAML catalyst through the assembly of an ArPase
Polymer fixed-targets for time-resolved serial protein crystallography at XFELs and synchrotrons
Get PDFSerial crystallography at X-ray free electron lasers (XFELs) and synchrotron light sources, termed serial femto-second crystallography (SFX) and serial synchrotron crystallography (SSX) respectively, has become an effective method for determining macromolecular structures at room or near-physiological temperatures with minimal radiation damage. To support these experiments, various delivery methods have been developed, with fixed-targets based on micro-pattern solid-supports or chips proving to be particularly reliable. Fixed-targets reduce sample consumption, facilitate rapid optimization of sample loading, and are compatible with high-throughput technologies. The primary focus for this research was to create a novel polymer based fixed-target, the MIcro-Structured Polymer based fixed-target (MISP-chip), optimized for minimal background noise, cost-effective production, user-friendly handling, durability, high reusability, and applicability to both serial crystallography and pump-probe experiments. This fixed-target was aimed to be developed and established as a novel fixed-target delivery method for serial crystallography at synchrotrons and XFELs, specifically tailored for SwissFEL’s CristallinaMX experimental station. Using silicon microfabrication and polymer replication technologies, we have designed inverted pyramidal shaped wells in membranes ranging from 25-50 µm in thickness. This design enables crystals to funnel into predefined positions, optimizing the hit-rate of the probing X-ray beam. The polymer-based film provides low x-ray absorption and scattering background, high design flexibility and the potential for mass-fabrication at low cost. A clear COP and opaque COC chip were made for conducting standard serial and pump-probe experiments. Simultaneously, efforts were dedicated to investigating ligand binding interactions aiming to optimize a photocaged biotin-streptavidin system for pump-probe TR-SX experiments in attempt to reveal the structural dynamics of the binding events by using coumarins as the photocage
Biochemical and physiological characterisation of a mouse model knocked-in for the RyR1 p.F4976L mutation identified in a severely affected child
No full textThe muscular system is one of the most important systems of our body. Muscles are not only essential for movements, but also for many other purposes, such as maintenance of posture, generation of heat and more. Moreover, the muscular system is in continuous communication with other systems, playing an important role for essential mechanisms such as breathing, blood circulation, digestion, immune response, etc. In general, we can distinguish different type of muscles: skeletal muscles, cardiac muscles or smooth muscles. While cardiac muscles and smooth muscles are under involuntary control, skeletal muscles carry out mainly voluntary movements (dynamic work), keep posture (isokinetic work) and are also involved in other processes, such as shivering for heat production, glucose storage, and metabolism.
On a molecular level, skeletal muscle contraction sees the Ryanodine receptor 1 (RyR1) as the main molecular player, responsible for the release of calcium from the sarcoplasmic reticulum into the cytosol and for enabling the contraction process. The process that converts an electrical stimulation to the generation of the contraction, is named Excitation-Contraction Coupling (ECC). The RyR1 plays a pivotal role in the ECC process, being the physical calcium release effector, starter and modulator of the contraction. Mutations in the RYR1 gene lead often to deleterious phenotypes, and are the most frequent cause of Congenital Myopathies (CMs). CMs are a group of early onset, neuromuscular disorders of variable severity, normally present at birth, and characterized by a stable or pejorative progressive phenotype with typical muscle biopsy findings. Patients affected by CMs present typical symptoms, including weakness of axial and proximal muscles, and in some cases cardiorespiratory and extraocular muscles (EOMs) involvement. Clinicians have re-classified CMs due to mutations in the RyR1, as “Ryanodine receptor type 1-related myopathies” (RYR1-RMs).
RYR1-RMs can be divided in four classes, depending on: i) histological features, ii) position of the mutation inside the protein sequence, iii) inheritance pattern of the mutation, which can be either dominant or recessive. Depending on the combinations of these characteristics, mutations can affect the RyR1 differently, changing its biophysical behaviour, stability and expression levels. Consequently, RYR1-RMs can be divided in three main classes: 1) Gain of function mutations, which are present as dominant mutations and are mostly related to Malignant hyperthermia susceptibility (MH – MIM #145600); 2) Loss of function CMs, such as Central core disease (CCD – MIM #117000) which is also caused by dominant mutations; 3) Centronuclear myopathy (CNM) and Multiminicore disease (MmD – MIM #255320), which are mainly due to recessive mutations and characterized by a pathogenic decrease of the RyR1 protein amount with consequent muscle weakness. While MH and CCD causative mutations are pathogenic at the heterozygous level, CNM or MmD patients comes either as homozygous or compound heterozygous. RYR1 dominant mutations are usually present within specific hotspots, while recessive mutations are evenly distributed throughout the whole protein sequence, with no specific pathogenic hotspots. While RYR1-RMs due to dominant mutations have been extensively studied and their pathological molecular implications are better defined, the way of action of recessive RYR1-RMs remains under investigation and more elusive. A specific isogenic mouse model is an important tool to elucidate the pathomechanisms and clinical relevance of a mutation.
Many mouse models have been created to better understand the molecular and pathological modifications brought by RYR1-RM mutations. Our lab extensively concentrates on the study of recessive RYR1 mutations, and in order to increase the knowledge around them, we created several mouse models isogenic to mutations found in severely affected patients.
In this study we characterized a novel transgenic mouse model, homozygous for the Ryr1p.F4976L (referable throughout the work as Ho). This mouse is knocked-in for an isogenic mutation found in a severely affected patient. In fact, the Ho mouse was created to understand if the molecular modifications brought by this homozygous RyR1 mutation could impact the correct muscle performance of the mouse, and ultimately to draw a correlation between the animal model and the clinical cases.
From a clinical point of view, the male proband, first son of Caucasian nonconsanguineous parents, was born preterm at around 29 weeks and was exhibiting sever hypotonia, together with respiratory distress. Moreover, the child was presenting a “floppy baby” phenotype, with general weakness. Initially he was proposed to present a myotonic dystrophy, but then he was found to carry the RYR1 gene variant c.14928C>G (p.Phe4976Leu) in exon 104 (via Next- Generation and Sanger sequencing). Parents were found to be heterozygous for the same mutation, but with a normal and healthy phenotype. At the moment, while still presenting a myopathic phenotype, the patient’s conditions have improved, being able to maintain a sitting position and walk with assistance.
Here, we describe the characterization of the Ho Ryr1p.F4976L mouse model and show that the mice have an impaired in vivo and ex vivo muscle performance, more prominently affecting fast twitch muscles, and impairing the calcium release after electrical stimulation. Interestingly, muscle fibres from Ho mice show higher levels of resting calcium, which were decreased to basal WT levels after administration of the SOCE inhibitor BTP2, leading to the hypothesis of a RyR1 leakage and SOCE involvement. Ultrastructural changes, such as decrease of calcium release units (CRU), increased number of dyads or presence of myofibrillar degeneration, portray a picture of general modifications that are probably not causative but consecutive to the presence of the mutation. Interestingly, with this model we can once more see the involvement of extraocular muscles (EOMs) in recessive RYR1-RMs. Significant changes in the biochemical composition of these type of muscles were majorly exemplified by the reduction of the specific EOM Myosin heavy chain (MyHC): MyHC13/EO. We already reported a similar situation in our double knock-in mouse model (RyR1p.Q1970fsX16+A4329D), in which almost the complete absence of this myosin isoform was shown. This is particularly important, since in the case of the Ho mouse the reduction is only of around 50%. Comparing the two animal models, since the RyR1Q1970fsX16+A4329D exhibited a more severe muscle impairment, we can hypothesize a MYHC13 dosage effect in the clinical outcome.
In general, we can conclude that the new p.F4976L mouse model recapitulates in part but on a milder level the phenotype of the affected child.
Despite many steps forward in a better understanding of RYR1 recessive diseases, studies like this must still be performed to expand our knowledge on recessive RYR1-RMs, which will help in the development of therapeutic approaches aimed to treat congenital myopathies linked to recessive RYR1 mutations
Nanostructured pervaporation membranes for bioethanol dehydration
Get PDFCurrent commercial membranes are applied for drying first generation of bioethanol, but the purification and drying of second and third generation of bioethanol are big challenges due to the impurities (fusel alcohols, organic acids, aldehydes, etc.) that are present in the industrial streams. Those impurities harm the membrane materials, either polymeric or ceramic. Even molecular sieves suffer damages due to these harmful components. Therefore, the development of next generation pervaporation membranes is crucial to make pervaporation more attractive and more competitive.
In the first part of the thesis, we investigate the ability of commercial membranes to trigger a specific behavior under different media. Dehydration of binary methyl acetate–water mixtures under neutral, acidic, and basic conditions was carried out by using PERVAP™ composite membranes based on poly(vinyl alcohol) (PVA) and poly(N-vinylpyrrolidone-co-(2-(dimethylamino)ethyl methacrylate)) P(NVP-co-DMAEMA). The effects of an acid (HCl) and a base (NaOH) on the separation performance of the membrane during the pervaporation process were investigated. The pH-responsive nature of membranes has been confirmed by swelling tests and analysis of the chemical structure of polymeric membranes. In addition, a mechanism of ring-opening of NVP units is proposed and correlated to the changes of membrane separation performance. Such membranes are known to be stable in the presence of impurities such as acetaldehyde. However, the membranes typically exhibit poor performance in ethanol/water separation due to low selectivity which is linked to the use of a commercial copolymer designed for other applications, thus discouraging their use for bioethanol dehydration processes. This motivated the need for customizing the copolymer properties to enhance membrane formulations for specific applications like ethanol dehydration.
In the second part of the thesis, we deepen the investigation of the copolymer. Rather than commercial copolymers, tailor-made poly(N-vinylpyrrolidone-co-(2-(dimethylamino)ethyl methacrylate)) P(NVP-co-DMAEMA) and poly(N-vinylpyrrolidone-co-N-vinylimidazole) P(NVP-co-PNVIm) with defined monomer molar ratio are synthesized via free radical polymerization. The random copolymers are fully characterized and then blended with PVA to investigate their chemical and thermal properties as membrane materials. Composite membranes are further prepared from the PVA/copolymer blends on a porous support, which are evaluated in terms of separation performance for the dehydration of ethanol by pervaporation. The membranes prepared from the blends exhibit up to four times higher water permeances than pristine PVA membrane, albeit the selectivity is slightly lower. Nevertheless, the membranes from blends with a ratio of 95:5 (PVA/copolymer) show improved selectivity and higher permeance values compared to the commercial PERVAP™ 4155–80, especially the blends composed by the copolymers of coPDMAEMA60 and coPDMAEMA20. The membrane prepared from the blend containing the homopolymer coPDMAEMA100 exhibits the highest water/ethanol selectivity and shows stable separation performance throughout the whole long-term stability test, while exposed to acetaldehyde. Thus, this study demonstrates that by synthesizing tailored copolymers (rather using the commercial ones) and blending with PVA, the separation performance of membranes can be significantly improved and tuned for specific dehydration processes. These prototypes have proven their efficiency and stability for second and third generation bioethanol dehydration processes. Thus, a considerable step towards the deployment of these membranes has been made.
In the last part, tailor-made poly(vinyl alcohol)-b-poly(styrene) copolymers (PVA-b-PS) for separation membranes are synthesized by the combination of reversible-deactivation radical polymerization techniques. The special features of these di-block copolymers are the high molecular weight (> 70 kDa), the high PVA content (> 80 wt.%), and the good film-forming property. They are soluble only in hot dimethyl sulfoxide, but through the “solvent-switch” technique, they self-assemble in aqueous media to form micelles. When the self-assembled micelles are cast on a porous substrate, thin-film membranes with higher water permeance than that of PVA homopolymer are obtained. Thus, by using these tailor-made PVA-b-PS copolymers, it is demonstrated that chemical cross-linkers and acid catalysts can no longer be needed to produce PVA membranes, since the PS nanodomains within the PVA matrix act as cross-linking points. Lastly, subsequent thermal annealing of the thin film enhances the membrane selectivity due to the improved microphase separation
Harnessing multi-photon excitation: from spectroscopy to catalysis
No full textPhotoredox catalysis has emerged as a versatile method in organic synthesis for the mild activation of small molecules, thus enabling novel chemical transformations. However, initiating challenging chemical transformations with a single visible photon faces intrinsic energetic limitations, corresponding to the energy of blue photons, as well as additional cumulative energy losses of the photocatalyst itself. As a result, considerable attention has been directed towards multi-photonic mechanisms, aiming to extend the thermodynamic boundaries of photoredox catalysis by the cumulative energy of two visible photons per catalytic turnover. Although these multi-photon approaches have opened up numerous new chemical transformations, the underlying mechanisms present a significant challenge. Yet, enhanced understanding is needed for the rational design of novel and more efficient catalytic systems or for the development of novel excitation strategies. This thesis aims to address the increasing complexity of multi-photon excitation strategies through an in-depth study of their photocatalytic applications and mechanistic processes. By combining these approaches, the goal is to uncover the underlying mechanisms, that could facilitate better control over photocatalytic reactivity and open up new methodologies for photoredox catalysis.
The first part (Chapter 2) presents an overview of the photocatalytic scope of excited organic radicals as extremely potent photocatalysts, surpassing the current limits of classical photoredox catalysis. Further, this chapter aims to elucidate the proposed mechanism by comparing the theoretical and observed reactivity and summarizes methods for uncovering the main reaction pathway, fostering a deeper understanding, which can lead to improved catalytic systems. A kinetic analysis of the ultra-fast decay rate of the proposed excited organic radical photocatalysts indicates the possibility of anti-Kasha reactivity if pre-association with the substrate occurs.
This will be followed by the introduction of a novel excitation strategy mimicking photosystems I and II by introducing two different light absorbers for the discovery of novel highly reactive organic radical anions (Chapter 3). Using a consecutive excitation strategy with two visible photons leads to an exceptionally strong reductant, able to activate C(sp2)―F bonds, which were previously beyond the reach of excited organic radicals. Using time-resolved optical spectroscopy, we followed each light-dependent elementary step of the overall mechanism, including the reaction of the radical anion with the substrate. Further, the first direct evidence for the anticipated pre-association between radical ions and substrates was provided, revealing substantial free energy similar to that involved in template effects in supramolecular chemistry.
In the second research project (Chapter 4), novel organic triplet photosensitizers, the isoacridones, with simultaneously formed photoactive singlet- and triplet-excited states were developed. The uncommon photophysical behavior of these new isoacridones offers new perspectives for multiphotonic mechanisms, where parallel triplet-triplet energy transfer and electron transfer are required. To illustrate the potential applications of these new isoacridone dyes, proof-of-concept photoreactions such as Birch-type arene reductions and challenging C(sp2)―C(sp2) couplings, were achieved, and the tandem reactivity was spectroscopically analyzed.
In the last part of this thesis, rare water-soluble cyclometalated iridium(III) complexes with redox-active excited states, high triplet energies, and long excited state lifetimes were applied in multi-photonic mechanisms in the challenging solvent water. In Chapter 4, the high triplet excited state energies were employed for sensitized triplet-triplet annihilation upconversion, reaching unprecedented singlet excited state energies of almost 4 eV in water. The applied annihilators exhibit potent excited state reduction potentials capable of decomposing persistent tertiary ammonium compounds as typical water pollutants. In Chapter 5, the same iridium(III) based photosensitizers combined with a well-known rhodium co-catalyst were employed for the regioselective reduction of a NAD+ (NAD = nicotinamide adenine dinucleotide) mimic under physiological conditions. NADH is involved in many biologically relevant redox reactions and its regeneration is of interest in photobiocatalysis. Here, we used two sequential photoinduced electron transfers from the iridium(III) photosensitizer, followed by a proton transfer, ultimately generating the active rhodium co-catalyst. The electron transfer processes were analyzed based on the correlation between the electron transfer efficiency of the iridium(III) photosensitizer to the rhodium co-catalyst and the overall reaction's efficiency, providing insights into the overall mechanism.
These findings have the potential to introduce novel mechanistic concepts within the field of multi-photon catalysis, including tandem triplet-triplet energy transfer and electron transfer reactivity. Additionally, our findings on photocatalyst-substrate aggregations clarify one of the most controversial aspects of modern photocatalysis. Our work introduces new perspectives for photochemistry that go beyond current kinetic and thermodynamic constraints
Inflammatory dynamics in the gut: exploring diet-immune interplay in obesity
No full text"The dose makes the poison: A high-fat diet based on extra virgin olive oil
leads to glucose intolerance and increased total liver lipids in mice"
1.Obesity is associated with the development of glucose intolerance and systemic low-grade
inflammation. Extra virgin olive oil (EVOO) has been identified as a promising candidate
in dietary interventions due to its anti-oxidative and anti-inflammatory effects. However,
the effect on metabolic health remains inconclusive. In parallel, this study aimed to
investigate the metabolic and immunological outcomes of an EVOO high-fat diet (E-HFD)
compared to another plant-based high-fat diet (coconut oil HFD, C-HFD).
Male mice aged 5-8 weeks were fed an E-HFD, C-HFD, or control diet for up to 6 months
and metabolically characterized by glucose, insulin, pyruvate tolerance tests, and glucosestimulated
insulin secretion. Immune cell phenotyping was performed using flow
cytometry in the gut, adipose, and liver tissues. Both HFDs induced hyperinsulinemia, but
the E-HFD led to more pronounced glucose intolerance and insulin resistance. Mice fed an
E-HFD had significantly elevated total liver lipids and increased expression of lipogenesis
genes, particularly Srebp1c, after only one week of HFD, consistent with increased
lipogenesis
Additionally, mice fed E-HFD exhibited increased glycogenic capacity as a measure of
glycogenesis. There were no differences in gut microbiota, systemic inflammation, and
cholesterol between both HFDs, but plasma triglycerides were elevated in C-HFD.
Supporting anti-inflammatory effects, mice on E-HFD showed partial protection from
inflammation in the adipose tissue and colon. In conclusion, our study highlights tissuespecific
metabolic and immune responses induced by different dietary fat sources.
Importantly, although E-HFD has less pro-inflammatory properties than C-HFD, it results
in more pronounced glucose intolerance/insulin resistance, potentially driven by
increased hepatic lipogenesis.
"scRNA-seq analysis of intestinal immune cells reveals dynamic changes upon
high-fat diet feeding in mice"
2.Obesity represents a significant global health concern and is linked to chronic low-grade
inflammation, glucose intolerance, and diabetes. The gastrointestinal tract and its
immune system play a pivotal role in developing and progressing metabolic diseases.
High-fat diets (HFDs), commonly employed to model obesity in mice, have been
demonstrated to significantly alter the composition and function of intestinal immune
cells. These immune cells are sensors of the environment and likely play a crucial role in
the pathogenesis of obesity-induced inflammation and glucose intolerance. Our study,
therefore, investigates how intestinal immune cells, in particular monocytes and
macrophages, evolve over the course of HFD exposure, to elucidate their role in metabolic
disease.
Here, we show that short-term HFD exposure significantly increased pro-inflammatory
macrophage subpopulations (P1 and P2) and upregulated interferon (IFN)γ and IFNα
pathways in monocytes and macrophages. This early innate immune response occured
before significant weight gain and was lost upon prolonged HFD exposure. At this stage,
adaptive immune responses became active, pro-inflammatory macrophages decreased,
and oxidative phosphorylation pathways were downregulated, resembling endotoxin
tolerance. Several genes of the cGAS-STING pathway were upregulated in monocytes and
macrophages after short-term HFD exposure, which might represent the onset of the
chronic gut inflammation. Local and short-term inhibition of the cGAS-STING pathway
resulted in a slight improvement in glucose tolerance. Our study emphasizes the timedependent
changes in intestinal immunity, highlighting an upregulated cGAS-STING
pathway and interferon response that initiates the disease process. At the chronic stage
of the disease, there is an exhaustion of innate immunity, while the adaptive immune
response takes over.
This dynamic nature of intestinal immune cell responses upon HFD provides new
insights into the role of the gut-immune axis in obesity-induced inflammation and metabolic dysfunction. Understanding these mechanisms offers potential avenues for
therapeutic strategies targeting early immune responses to prevent or mitigate obesity-related
metabolic diseases.
"scRNA-seq analysis of human intestinal myeloid cells suggests immunedampened
phenotype in obesity"
3.Obesity is associated with chronic low-grade inflammation and metabolic dysfunction.
Previous studies have shown that obesity is linked to significant changes in the immune
landscape of the gastrointestinal tract, impacting both metabolic and immune
responses. However, the differential transcriptional changes, in particular in myeloid
cells comprising most cells of the innate immune system within the gut of obese
individuals, remain unclear. This study aimed to elucidate the impact of obesity on
intestinal myeloid cells, specifically monocytes, macrophages, and dendritic cells using
single-cell RNA sequencing (scRNA-seq). Obese and non-obese participants were
recruited for colonoscopies, during which colon biopsies were collected from four
individuals in each group. Flow cytometry and scRNA-seq were employed to analyze the
immune cell populations and their gene expression profiles. The study identified
eight distinct clusters of myeloid cells, including monocytes, inflammatory macrophages,
resident macrophages, conventional dendritic cells (cDC1 and cDC2 subtypes), and a
transitional dendritic cell cluster. Our findings revealed that obesity causes only minor
transcriptional changes within identified cell clusters. Utilizing gene set enrichment
analysis, we found a general downregulation of genes involved in innate immune
activation and metabolic processes. Specifically, oxidative phosphorylation and other
mitochondrial-related pathways were downregulated in several myeloid cell clusters,
suggesting altered energy metabolism. These changes imply a shift towards a state
resembling endotoxin tolerance, characterized by reduced immune responsiveness. Our
results demonstrate that intestinal myeloid cells adapt during the chronic state of obesity
towards an immune-dampened phenotype.
This study highlights the complex nature of intestinal immunity in the context of obesity,
emphasizing the importance of understanding the dynamic immune cell changes. The
downregulation of critical metabolic and immune pathways in myeloid cells suggests
potential targets for interventions aimed at restoring immune function and metabolic
balance in obese individuals