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Regulation of VEGF-induced intussusceptive angiogenesis by Notch4 signaling
Get PDFIntroduction. Vascular endothelial growth factor-A (VEGF) is the master regulator of vascular growth and a key target for therapeutic angiogenesis. However, VEGF causes either normal or aberrant angiogenesis depending on its dose in the microenvironment around each producing cell in vivo. We previously found that therapeutic doses of VEGF in skeletal muscle do not induce angiogenesis by the well-studied mechanism of sprouting, but rather through intussusception, whose regulation is essentially unknown. Notch signaling is critical in sprouting angiogenesis and endothelium expresses both Notch1 and Notch4. We previously found that Notch1 activation and Dll4 expression are lost during the transition between normal or aberrant angiogenesis by VEGF. Here we investigated whether and how Notch4 and Jag1 regulate the process of splitting angiogenesis by increasing VEGF doses, in the therapeutic target tissue of skeletal muscle.
Methods. VEGF doses inducing either normal or aberrant angiogenesis were delivered in hindlimb skeletal muscles of (a) SCID mice, by implanting well-characterized monoclonal populations of transduced myoblasts, or (b) Notch4-WT (N4+/+) and Notch4-KO (N4-/-) mice, by injecting either (i) fibrin matrices decorated with an engineered, cross-linkable version of VEGF protein or (ii) a therapeutically relevant adenoviral vector. In SCID mice, Notch signaling was globally inhibited by co-expressing a secreted form of the ligand Dll4 (sDll4). In N4+/+, Jag1 interaction with Notch receptors was specifically prevented by systemically delivering a Jag1-neutralizing antibody.
Results. In SCID mice, global Notch inhibition by sDll4 did not impair normal angiogenesis, but completely prevented aberrant vascular growth, converting it into morphologically normal and functionally perfused microvascular networks. Similar results were observed when only Notch4 signaling was genetically abrogated in N4-/- mice, without interfering with Notch1 signaling. Angiogenic normalization was not dependent on the mode of VEGF delivery, as it could be observed with both controlled VEGF protein delivery within fibrin matrices and uncontrolled expression by a clinically relevant adenoviral gene therapy vector. Jag1 blockade failed to prevent aberrant structures, but also increased Dll4 expression, thus suggesting the involvement of a compensatory mechanism which could result in Notch4 activation despite the absence of Jag1-mediated stimulus. The lack of Notch4 signaling did not affect the total amount of proliferating endothelial cells, but it significantly reduced their speed of proliferation, leading to a more moderate degree of circumferential enlargement and therefore enabling successful splitting into normal vascular structures. Gene set enrichment analysis revealed a downregulation of sets connected with cell proliferation and metabolism in N4-/- mice, including Myc target gene sets, which points to a potential crosstalk between Notch4 and Myc signaling pathways.
Conclusion. Notch4 signaling determines the switch between normal and aberrant angiogenesis by modulating the speed of endothelial proliferation by VEGF and therefore emerging as a relevant target to ensure therapeutic angiogenesis. The role of Jag1 and Dll4 in the process is currently being investigated
Spatiotemporal modeling of historical airborne pollen concentrations in Switzerland
No full textPollen is one of the most common causes of seasonal allergies. Pollen exposure is related to
allergic and respiratory diseases. Allergic disease is an important public health problem that
has risen dramatically in recent years. Climate change, which has led to rising temperature, can
affect the different allergenic pollen types, timing, and length of the pollen season. Therefore,
predicting pollen concentration is valuable to assess the risk level, and also to determine the
effects of pollen exposure on cardiovascular, respiratory, and cognitive health. However, the
prediction of airborne pollen concentrations is challenging due to the complex relationships
between biotic and environmental variables.
This dissertation investigated the spatiotemporal distributions predicted for five allergenic
pollen types, including hazel, alder, ash, birch, and grass pollen, across Switzerland. A set of
spatial and temporal predictors, including wind speed, wind direction, temperature,
precipitation, relative humidity, Normalized Difference Vegetation Index (NDVI), elevation,
land use, and tree type were used to develop spatiotemporal models to predict pollen
concentration. In addition, statistical and machine learning algorithms including LASSO,
Ridge, Elastic net, Random forest, XGBoost, and ANNs along with ensemble model evaluated
to national-wide prediction of airborne allergenic pollen concentration. Finally, a comparison
between the developed spatiotemporal machine learning model and the dispersion model
COSMO-ART was made to model pollen concentration of grass, alder, and birch pollen in
Switzerland.
The results showed the importance of the meteorological parameters in all the developed
models. Furthermore, results indicated that the land use information such as broadleaf forest,
mixed forest, agricultural land, and urban areas had an impact on pollen concentration,
typically in large buffer sizes. Despite the limited number of monitoring stations, the models
were able to explain and predict variations in the concentration of pollen at high spatial
resolution. Results indicated that the concentrations of grass and birch pollen types are notably
higher in northern Switzerland, with higher concentrations observed mainly within southern
valleys, while alder pollen concentrations reach high levels within southern valleys.
Evaluation of the performance of the various statistical, machine learning, and ensemble
methods revealed that the Random forest model is a better choice compared to alternative
machine learning methods for modelling pollen concentration. However, an ensemble model
with a combination of machine learning algorithms is a better technique for estimating
accurately pollen concentration. The impact of the different spatial and temporal variables
varies based on selected algorithms and pollen types.
The statistical assessment of the spatiotemporal machine learning model and the dispersion
model indicated a weak correlation of alder pollen and a strong correlation of grass pollen.
Furthermore, findings suggested a higher agreement of statistical models with the measured
concentrations at stations, compared to the dispersion model for all pollen types.
This was the first spatiotemporal statistical model for pollen, predicting daily exposure maps
with a fine spatial resolution of 1x1 km across Switzerland. The results of this project will be
used to estimate the pollen concentration for the panel participants in the main project named
Effects of Pollen on Cardiorespiratory Health and ALlergic symptoms (EPOCHAL) as well as
the SNC (Swiss National Cohort) and various other health studies
Externe Effekte des Verkehrs 2021 : Umwelt-, Unfall- und Gesundheitseffekte des Strassen-, Schienen-, Luft- und Schiffsverkehrs
Get PDFAusganglage und Zweck
Die externen Effekte des Verkehrs sind Bestandteil der vom Bundesamt für Statistik (BFS) publizierten Statistik «Kosten und Finanzierung des Verkehrs» (KFV). Diese umfassende Zusammenstellung stellt eine wichtige Grundlage für die Verkehrspolitik dar. Zudem sind die externen Kosten des Schwerverkehrs – neben weiteren Aspekten – bei der Festlegung des Tarifes der leistungsabhängigen Schwerverkehrsabgabe (LSVA) relevant.
Die externen Effekte des Verkehrs werden vom Bundesamt für Raumentwicklung (ARE) jähr-lich ausgewiesen und müssen transparent und gemäss dem aktuellen Stand des Wissens berechnet werden (vgl. Art. 7, al. 3 Schwerverkehrsabgabegesetz). Um die Aktualität der Be-rechnungsmethode zu gewährleisten, beauftragt das ARE regelmässig eine Methodenüber-prüfung. Der vorliegende Bericht dokumentiert die Überprüfung, präsentiert die Resultate für das Referenzjahr 2021 und nimmt entsprechende Rückrechnungen bis 2010 vor. Diese Ar-beiten folgen auf die Methodenberichte für die Referenzjahre 2010 (Ecoplan; INFRAS (2014)) und 2015 (INFRAS; Ecoplan (2019)).
Im Rahmen der vorliegenden Methodenüberprüfung wurden die externen Effekte des Verkehrs auf den aktuellen Stand der wissenschaftlichen Erkenntnisse gebracht. Es wurden insbeson-dere Datengrundlagen (Mengengerüste), Belastungs-Wirkungs-Beziehungen und Kos-tensätze aktualisiert. So wurden z.B. neue Krankheitsbilder (Lungenkrebs, Diabetes und De-menz), die durch Luftverschmutzung verursacht werden, in die Berechnungen integriert oder der Klimakostensatz aktualisiert. Weiter wurde / wurden:
•die Sicht Verkehrsteilnehmende ins Zentrum gestellt (die Sicht Verkehrsträger wird nicht mehr berechnet);
•die relevanten Kostenbestandteile überprüft und angepasst: der Bereich «zusätzliche Kos-ten in städtischen Räumen» wird nicht mehr berechnet, die Überlastungskosten der Ver-kehrsinfrastruktur werden ab sofort in die Publikation der externen Effekte integriert;
•zusätzliche Differenzierungen eingeführt: separate Resultate für Elektromobilität, nach Gemeindetyp (städtisch, intermediär, ländlich) sowie nach Kanton.
Das ARE konnte auf finanzielle Unterstützung durch das Bundesamt für Umwelt (BAFU) und aller 26 Kantone zählen. Das Projekt wurde inhaltlich vom BFS, von den Bundesämtern für Strassen (ASTRA), Verkehr (BAV), Zivilluftfahrt (BAZL), Umwelt (BAFU) und Energie (BFE) begleitet. Internationale Expertinnen und Experten (siehe Impressum) haben das Vorgehens-konzept validiert
Influence of training time in a 12-week training intervention on cardiorespiratory fitness
No full textCardiorespiratory fitness is a key factor in healthspan, especially for older adults. Evidence shows that endurance and strength performance vary within individuals throughout the day, yet it remains unclear if training at peak offers advantages for enhancing performance or health outcomes. This master thesis aimed to investigate the effects of training time (nadir vs. peak) on ̇VO2peak improvements in adults aged 60-80 years over a 12-week intervention.
Thirty-two participants were randomized to train at either their individual nadir or peak, deter-mined by pre-intervention strength testing across four times of day (08:00, 12:00, 16:00, 20:00). Participants completed supervised strength training twice weekly and endurance train-ing once weekly on an ergometer with target heart rate at 60% of individual ̇VO2peak. Changes in ̇VO2peak (L/min) from pre- to post-intervention were analyzed, with ANCOVA adjusting for baseline fitness.
The mean difference in ̇VO2peak was 0.14 (0.24) L/min (95% CI: 0.01, 0.27) in the nadir group (p = 0.041) and 0.21 (0.37) L/min (95% CI: -0.07, 0.49) in the peak group (p = 0.119). Post-intervention, direct comparison between groups showed a mean difference of 0.01 (0.27) L/min (95% CI: -0.56, 0.54), slightly favoring the nadir group (p = 0.514).
The results show that both the nadir and peak training groups improved ̇VO2peak, with no significant differences between them. This suggests that regular physical activity has a positive effect on ̇VO2peak in older adults, regardless of the time of day of training, emphasizing the importance of consistency of training rather than specific timing
An overview on the local limit of non-local conservation laws, and a new proof of a compactness estimate
Get PDFConsider a non-local (i.e., involving a convolution term) conservation law: when the convolution term converges to a Dirac delta, in the limit we formally recover a classical (or "local") conservation law. In this note we overview recent progress on this so-called non-local to local limit and in particular we discuss the case of anistropic kernels, which is extremely relevant in view of applications to traffic models. We also provide a new proof of a related compactness estimate
Characterization of autoantibodies and their triggers in myelin oligodendrocyte glycoprotein antibody-associated disease
No full textMounting evidence points to a pivotal role of autoantibodies in the pathophysiology of demyelinating disorders of the central nervous system (CNS). In the clinical management of patients, autoantibodies are used as diagnostic biomarkers. The triggers and mechanisms behind the complex autoimmune responses, however, are not yet fully understood. Myelin oligodendrocyte glycoprotein (MOG) antibody associated disease (MOGAD) is a recently classified demyelinating CNS disease characterized by the presence of autoantibodies against MOG, a protein expressed solely in the CNS. The diagnosis of MOGAD is associated with several challenges, and the pathophysiology of the disease remains elusive.
This PhD thesis comprises three specific aims: (1) to address challenges in the diagnosis of MOGAD in light of the recently published MOGAD diagnostic criteria, (2) to explore MOG reactive autoantibodies of the immunoglobulin A (IgA) isotype as a potential biomarker in CNS demyelinating disease, and (3) to investigate post infectious and vaccine related triggers in MOGAD through the cloning and in depth characterization of antibodies from patients.
To enable the characterization of MOG reactive antibody responses in patients, we used a flow cytometry assay with live cells expressing human MOG (hMOG). To identify and clone autoantibodies, we enriched and isolated MOG-reactive B cells from patients using a customized assay with cells expressing fluorescence labeled hMOG. In vitro techniques were used to characterize antibody reactivities to a panel of self- and foreign antigens, and single cell sequencing experiments were performed to decipher the immune cell origin and phenotype of the autoreactive antibodies.
Addressing the first aim of this thesis, we found that the performance of the MOGAD diagnostic criteria resulted in discordant diagnoses of MOGAD in some cases, and the performance of MOG antibody testing with different methods gave diverse results in a subset of the samples. Investigating a different patient cohort, MOG antibodies were only detected in rare cases of patients with psychiatric disease. In the second aim of this thesis, we identified MOG antibodies of the IgA isotype in a subgroup of patients with demyelinating diseases. Notably, these patients presented with distinct clinical features compared to patients who were seropositive for MOG antibodies of the immunoglobulin G isotype. As part of the third aim, we cloned MOG reactive antibodies from different donors. Although the majority of the monoclonal antibodies did not react against other antigens, one antibody derived from a patient with post-vaccination development of MOGAD showed cross reactivity to hMOG and tetanus toxoid. We were able to delineate the B cell phenotype of the B cells that produced this antibody clone.
The results of this thesis underscore the need to identify additional biomarkers to facilitate the differential diagnosis of MOGAD and propose MOG-IgA as a potential novel biomarker in patients with demyelinating disorders. The cloning and characterization of patient derived MOG-reactive antibodies provides important insight into their specificity and function and lays the groundwork for future investigations regarding their pathogenic role in neuroinflammation
Readout of spins in semiconductor quantum dots
No full textSpins in semiconductor quantum dots constitute a promising pathway towards the realization of a large-scale quantum computer. To fulfill their promise as quantum bits (qubits), it is necessary that the spin states are manipulated and read out with a high fidelity. In this thesis, distinct implementations of spin readout are elucidated experimentally in two different spin qubit platforms. Investigating electron spins in the group III-V compound semiconductor gallium arsenide, we employ energy-selective spin readout with an adjacent electron reservoir in order to distinguish the spin-up and spin-down states of a single electron, provided that an external magnetic field is applied. We extract the g-factor, which is proportional to the energy difference of those two spin states, for different in-plane directions of the external magnetic field. This allows us to identify isotropic and anisotropic corrections to the bulk g-factor that arise from the spin-orbit interaction.
Next, we turn to hole spins in the group IV germanium/silicon core/shell nanowires, a platform that is predicted to host the strong and electrically tunable direct Rashba spin-orbit interaction. Making use of the transport phenomenon of Pauli spin blockade (PSB) arising in a pair of tunnel-coupled quantum dots, we demonstrate that a hole spin qubit can be operated at elevated temperatures of up to 1.7 Kelvin. This constitutes the first time that a germanium-based spin qubit has been measured at temperatures above 1 Kelvin, thus allowing for the implementation of on-chip classical control electronics. We also show that this spin qubit allows for compromise-free operation by simultaneously maximizing the qubit speed and coherence, challenging previous notions about a trade-off between these two quantities.
Following this experiment, we turn to the implementation of fast readout via radio-frequency reflectometry. We employ the scalable method of in situ dispersive readout, which uses the readily available gate electrodes in the nanowire devices. We overcome the challenge of impedance matching by developing a varactor – a voltage-tunable capacitor – based on the quantum paraelectric material strontium titanate, which remains highly tunable down to millikelvin temperatures and high magnetic fields of at least 1.5 Tesla. These properties make our varactors ideal circuit elements for the emerging field of cryogenic radio-frequency engineering, and furthermore allow us to boost our readout signal. After characterizing our reflectometry setup, we move on to describe a novel dispersive signature of PSB, which traces the current rectification properties. Altogether, our results show that the repertoire of spin readout techniques can help unveil a wide range of interesting physics
Chemical characterization and quantification of organic aerosols: addressing storage effects and peroxide quantification
Get PDFOrganic aerosols are crucial constituents of atmospheric particulate matter, significantly influencing the Earth’s climate and human health. Despite extensive research, large uncertainties remain in the molecular-level chemical characterization of aerosols, particularly regarding the effects of sample storage during offline analysis and the quantification of specific compounds, such as organic
peroxides. This dissertation addresses these challenges through two main objectives: characterizing the effects of storage conditions and time on the molecular-level
chemical composition of aerosol samples and developing a novel method to identify and quantify individual peroxides in aerosols.
To evaluate the effects of storage conditions on the chemical composition of aerosols, β-pinene secondary organic aerosol (SOA), naphthalene SOA, and urban atmospheric aerosol were collected on filters and investigated. To characterize temporal changes in aerosol composition, all samples were extracted and analyzed immediately, or stored as aqueous extracts or filters for 24 h, 1 week, 2 weeks,
or 4 weeks at either +20°C, -20°C, or -80°C. Analysis was conducted using ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). Targeted and non-targeted data analysis combined with principal component analysis were used to identify changes in composition over time. The study highlights that all samples should be kept frozen as soon as possible after sampling to best retain their chemical composition compared to the fresh
collected samples. In contrast, storage of both aqueous extracts and filters at room temperature led to significant compositional changes even at short storage times of
only 1 day. In cases where immediate frozen storage is not possible, authors should mention in detail how the samples were stored and how much time passed between collection and analysis to reduce uncertainties.
The significant compositional changes observed in samples stored at room temperature (i.e. +20°C) were further investigated and characterized. β-Pinene SOA filter and extract samples show distinct temporal concentration changes for monomers and oligomers. In aqueous SOA extracts a significant increase is observed for monomers, while dimers decay at the same time. The inverse can be seen on filters, a strong and persistent increase for dimers, while many of the monomers decrease. Additionally, new dimer compounds are formed over time in SOA samples stored on filters. These observed trends are proposed to be due to hydrolysis
of dimers in aqueous extracts, and a continuous formation of oligomers in SOA formed through reactions of monomers on filters. Further experiments were done to confirm dimer formation through esterification of monomers. It is important to consider such on-filter reaction artifacts when detailed composition of organic aerosol is studied. These continuous reactions of SOA components over days and
weeks on filters can also mimic dark aging particle phase processes in particles with low-water content in the ambient atmosphere over their entire lifetime. Such long-term experiments of many days are not possible with conventional laboratory chamber studies.
The second main objective of this thesis shifts the focus away from storage effects to the quantification of peroxides, which have been identified as an important class
of SOA components contributing to aerosol toxicity and new particle formation. Despite their importance, there are large uncertainties about their contribution to
the mass of SOA. One source of uncertainty may be the differences in detection methods, such as iodometric titration, which is often used to determine the total
peroxide concentration in aerosol samples. A major drawback of such methods is the inability to identify and quantify individual peroxide concentrations in organic aerosol. Therefore a novel high-performance liquid-chromatography (HPLC) in-column derivatization method is presented to identify and quantify individual organic peroxides in SOA through chemiluminescence of luminol catalyzed by cytochrome c. Three different sample types were measured: commercially available peroxide standards, samples generated through liquid-phase ozonolysis of α-Pinene and 3-Carene, and laboratory generated SOA from α-Pinene, 3-Carene, naphthalene, and a 3-Carene and naphthalene mix. The results presented highlight the methods capability of differentiating between different samples. All samples are additionally analyzed by traditional iodometry with UV-Vis to obtain a total peroxide concentration. A clear linear correlation is observed between the HPLC chemiluminescence
method and iodometry for peroxide quantification. This allows for quantification of individual peaks in the chromatograms. A unique cross-product peroxide peak
in the 3-Carene/naphthalene mix SOA is identified and quantified to contribute 5.5% of the total peroxide concentration, illustrating the additional complexity when
several SOA precursors are oxidized simultaneously, as is the case in the ambient atmosphere