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Schriftenreihe
Sonstige beteiligte Institutionen
- Helmholtz Institute for RNA-based Infection Research (HIRI) (2)
- Interdisziplinäres Zentrum für Klinische Forschung (IZKF) (2)
- Klinische Studienzentrale (Universitätsklinikum) (2)
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg (2)
- Anthropology Department University of Tennessee, Knoxville (1)
- CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg (1)
- Carl-Ludwig-Institut für Physiologie, Universität Leipzig (1)
- Chair of Experimental Biomedicine I (1)
- Charles University, Faculty of Mathematics and Physics, Ke Karlovu 5, 121 16 Prague, Czech Republic (1)
- DATE Lab, KITE Research Insititute, University Health Network, Toronto, Canada (1)
Serverless computing is an emerging cloud computing paradigm that offers a highlevel
application programming model with utilization-based billing. It enables the
deployment of cloud applications without managing the underlying resources or
worrying about other operational aspects. Function-as-a-Service (FaaS) platforms
implement serverless computing by allowing developers to execute code on-demand
in response to events with continuous scaling while having to pay only for the
time used with sub-second metering. Cloud providers have further introduced
many fully managed services for databases, messaging buses, and storage that also
implement a serverless computing model. Applications composed of these fully
managed services and FaaS functions are quickly gaining popularity in both industry
and in academia.
However, due to this rapid adoption, much information surrounding serverless
computing is inconsistent and often outdated as the serverless paradigm evolves.
This makes the performance engineering of serverless applications and platforms
challenging, as there are many open questions, such as: What types of applications
is serverless computing well suited for, and what are its limitations? How should
serverless applications be designed, configured, and implemented? Which design
decisions impact the performance properties of serverless platforms and how can
they be optimized? These and many other open questions can be traced back to an
inconsistent understanding of serverless applications and platforms, which could
present a major roadblock in the adoption of serverless computing.
In this thesis, we address the lack of performance knowledge surrounding serverless
applications and platforms from multiple angles: we conduct empirical studies
to further the understanding of serverless applications and platforms, we introduce
automated optimization methods that simplify the operation of serverless applications,
and we enable the analysis of design tradeoffs of serverless platforms by
extending white-box performance modeling.
Background: The American Thyroid Association (ATA) uses criteria to assess the risk for persistent disease in differentiated thyroid carcinoma (DTC) after radioiodine therapy (RAI). There are no data available showing that this classification can be adopted unadjusted by Germany. Aim: The aim of our study is to investigate whether the ATA classification can be applied to a German population for short-term prognosis. Furthermore, we investigated the influence of an age cutoff value. Methods: We retrospectively analyzed 121 patients who were referred to our tertiary referral center. Patients were classified into risk categories, and the therapy response was determined according to ATA. Results: A total of 73/83 (88%) ATA low-risk patients and 12/19 (63%) intermediate-risk patients showed an excellent response; 2/19 (11%) high-risk patients had a biochemical, and 6 (31%) had a structural incomplete response. Of all 39 patients ≥55 years, 84% had an excellent response. Using a cut off of 50 years, 50/62 (81%) of the older patients showed an excellent response. Conclusion: The ATA risk classification is able to estimate the response to RAI therapy in a German population. A shift from 55 to 50 years as an age cutoff value does not result in any relevant change in the treatment response.
Background and Objectives: Currently, the worldwide incidence of major amputations in the general population is decreasing whereas the incidence of minor amputations is increasing. The purpose of our study was to analyze whether this trend is reflected among orthopaedic patients treated with lower extremity amputation in our orthopaedic university institution. Materials and Methods: We conducted a single-center retrospective study and included patients referred to our orthopaedic department for lower extremity amputation (LEA) between January 2007 and December 2019. Acquired data were the year of amputation, age, sex, level of amputation and cause of amputation. T test and Chi² test were performed to compare age and amputation rates between males and females; significance was defined as p < 0.05. Linear regression and multivariate logistic regression models were used to test time trends and to calculate probabilities for LEA. Results: A total of 114 amputations of the lower extremity were performed, of which 60.5% were major amputations. The number of major amputations increased over time with a rate of 0.6 amputation/year. Men were significantly more often affected by LEA than women. Age of LEA for men was significantly below the age of LEA for women (men: 54.8 ± 2.8 years, women: 64.9 ± 3.2 years, p = 0.021). Main causes leading to LEA were tumors (28.9%) and implant-associated complications (25.4%). Implant-associated complications and age raised the probability for major amputation, whereas malformation, angiopathies and infections were more likely to cause a minor amputation. Conclusions: Among patients in our orthopaedic institution, etiology of amputations of the lower extremity is multifactorial and differs from other surgical specialties. The number of major amputations has increased continuously over the past years. Age and sex, as well as diagnosis, influence the type and level of amputation.
Background and objectives: Cartilage surgery constitutes a standard intervention in foot and ankle procedures. Currently, there is a lack of epidemiological data on its frequency, age distribution, and surgical options for cartilage surgery. This study aimed to investigate the current landscape of cartilage surgery in Germany and identify the most common procedures from an epidemiological standpoint. Materials and methods: Medical billing and reporting data from the Federal Statistical Office of Germany, encompassing the period 2006–2020, was examined, including all foot and ankle cartilage surgical procedures (summarized under OPS codes 5-812 and 5-801). The dataset incorporated information on the affected joint, patient age and sex, and surgery type. Each surgical procedure was categorized as “debridement”, “regeneration” or “refixation”. Linear and nonlinear regression analyses were employed, with a statistical significance threshold of 0.05. Results: From the total of 136,501 procedures conducted during the study period, the most frequently performed interventions were microfracture (58,252) and chondroplasty (56,135), and thus, debridement procedures were in the leading position. The use of acellular membranes was the most used regenerative technique (n = 11,414). At the ankle joint, interventions were mostly arthroscopic and in men, while foot cartilage surgeries were preferably performed via open surgery and mostly in women. Age distribution analysis revealed two primary peaks: the first in the 20–25-year-old group (ankle and foot) and the second in the 45–50-year-old group (ankle) and 55–60-year-old group (foot). Refixation and regenerative procedures were more frequent among younger individuals, while debriding procedures were more frequent among older individuals. Regenerative procedures, particularly in the ankle, significantly increased over time. Conclusions: Cartilage surgery of the foot and ankle was common, with two primary age groups predominantly affected. Notably, recent years have witnessed a considerable rise in cartilage regenerative procedures.
MDSCs are suppressive immune cells with a high relevance in various pathologies including cancer, autoimmunity, and chronic infections. Surface marker expression of MDSCs resembles monocytes and neutrophils which have immunostimulatory functions instead of suppressing T cells. Therefore, finding specific surface markers for MDSCs is important for MDSC research and therapeutic MDSC manipulation. In this study, we analyzed if the integrin VLA-1 has the potential as a novel MDSC marker. VLA-1 was expressed by M-MDSCs but not by G-MDSCs as well as by Teff cells. VLA-1 deficiency did not impact iNOS expression, the distribution of M-MDSC and G-MDSC subsets, and the suppressive capacity of MDSCs towards naïve and Teff cells in vitro. In mice, VLA-1 had no effect on the homing capability of MDSCs to the spleen, which is a major reservoir for MDSCs. Since the splenic red pulp contains collagen IV and VLA-1 binds collagen IV with a high affinity, we found MDSCs and Teff cells in this area as expected. We showed that T cell suppression in the spleen, indicated by reduced T cell recovery and proliferation as well as increased apoptosis and cell death, partially depended on VLA-1 expression by the MDSCs. In a mouse model of multiple sclerosis, MDSC injection prior to disease onset led to a decrease of the disease score, and this effect was significantly reduced when MDSCs were VLA-1 deficient. The expression of Sema7A by Teff cells, a ligand for VLA-1 which is implicated in negative T cell regulation, resulted in a slightly stronger Teff cell suppression by MDSCs compared to Sema7A deficient T cells. Live cell imaging and intravital 2-photon microscopy showed that the interaction time of MDSCs and Teff cells was shorter when MDSCs lacked VLA 1 expression, however VLA-1 expression had no impact on MDSC mobility. Therefore, the VLA-1-dependent interaction of MDSC and Teff cells on collagen IV in the splenic red pulp is implicated MDSC-mediated Teff cell suppression.
A New International
(2023)
Background
Perioperative bridging of oral anticoagulation increases the risk of bleeding complications after elective general and visceral surgery. The aim of this study was to explore, whether an individual risk-adjusted bridging regimen can reduce bleeding events, while still protecting against thromboembolic events.
Methods
We performed a quality improvement study comparing bridging parameters and postoperative outcomes before (period 1) and after implementation (period 2) of a new risk-adjusted bridging regimen. The primary endpoint of the study was overall incidence of postoperative bleeding complications during 30 days postoperatively. Secondary endpoints were major postoperative bleeding, minor bleeding, thromboembolic events, postoperative red blood cell transfusion, perioperative length-of-stay (LOS) and in-hospital mortality.
Results
A total of 263 patients during period 1 and 271 patients during period 2 were compared. The included elective operations covered the entire field of general and visceral surgery. The overall incidence of bleeding complications declined from 22.1% during period 1 to 10.3% in period 2 (p < 0.001). This reduction affected both major as well as minor bleeding events (8.4% vs. 4.1%; p = 0.039; 13.7% vs. 6.3%; p = 0.004). The incidence of thromboembolic events remained low (0.8% vs. 1.1%). No changes in mortality or length-of-stay were observed.
Conclusion
It is important to balance the individual thromboembolic and bleeding risks in perioperative bridging management. The risk adjusted bridging regimen reduces bleeding events in general and visceral surgery while the risk of thromboembolism remains comparably low.
Infection research largely relies on classical cell culture or mouse models. Despite having delivered invaluable insights into host-pathogen interactions, both have limitations in translating mechanistic principles to human pathologies. Alternatives can be derived from modern Tissue Engineering approaches, allowing the reconstruction of functional tissue models in vitro. Here, we combined a biological extracellular matrix with primary tissue-derived enteroids to establish an in vitro model of the human small intestinal epithelium exhibiting in vivo-like characteristics. Using the foodborne pathogen Salmonella enterica serovar Typhimurium, we demonstrated the applicability of our model to enteric infection research in the human context. Infection assays coupled to spatio-temporal readouts recapitulated the established key steps of epithelial infection by this pathogen in our model. Besides, we detected the upregulation of olfactomedin 4 in infected cells, a hitherto unrecognized aspect of the host response to Salmonella infection. Together, this primary human small intestinal tissue model fills the gap between simplistic cell culture and animal models of infection, and shall prove valuable in uncovering human-specific features of host-pathogen interplay.
Service orchestration requires enormous attention and is a struggle nowadays. Of course, virtualization provides a base level of abstraction for services to be deployable on a lot of infrastructures. With container virtualization, the trend to migrate applications to a micro-services level in order to be executable in Fog and Edge Computing environments increases manageability and maintenance efforts rapidly. Similarly, network virtualization adds effort to calibrate IP flows for Software-Defined Networks and eventually route it by means of Network Function Virtualization. Nevertheless, there are concepts like MAPE-K to support micro-service distribution in next-generation cloud and network environments. We want to explore, how a service distribution can be improved by adopting machine learning concepts for infrastructure or service changes. Therefore, we show how federated machine learning is integrated into a cloud-to-fog-continuum without burdening single nodes.
Improved wall temperature prediction for the LUMEN rocket combustion chamber with neural networks
(2023)
Accurate calculations of the heat transfer and the resulting maximum wall temperature are essential for the optimal design of reliable and efficient regenerative cooling systems. However, predicting the heat transfer of supercritical methane flowing in cooling channels of a regeneratively cooled rocket combustor presents a significant challenge. High-fidelity CFD calculations provide sufficient accuracy but are computationally too expensive to be used within elaborate design optimization routines. In a previous work it has been shown that a surrogate model based on neural networks is able to predict the maximum wall temperature along straight cooling channels with convincing precision when trained with data from CFD simulations for simple cooling channel segments. In this paper, the methodology is extended to cooling channels with curvature. The predictions of the extended model are tested against CFD simulations with different boundary conditions for the representative LUMEN combustor contour with varying geometries and heat flux densities. The high accuracy of the extended model’s predictions, suggests that it will be a valuable tool for designing and analyzing regenerative cooling systems with greater efficiency and effectiveness.
Inflammation and oxidative stress represent physiological response mechanisms to different types of stimuli and injury during critical illness. Its proper regulation is fundamental to cellular and organismal survival and are paramount to outcomes and recovery from critical illness. A proper maintenance of the delicate balance between inflammation, oxidative stress, and immune response is crucial for resolution from critical illness with important implications for patient outcome. The extent of inflammation and oxidative stress under normal conditions is limited by the antioxidant defense system of the human body, whereas the antioxidant capacity is commonly significantly compromised, and serum levels of micronutrients and vitamins significantly depleted in patients who are critically ill. Hence, the provision of antioxidants and anti-inflammatory nutrients may help to reduce the extent of oxidative stress and therefore improve clinical outcomes in patients who are critically ill. As existing evidence of the beneficial effects of antioxidant supplementation in patients who are critically ill is still unclear, actual findings about the most promising anti-inflammatory and antioxidative candidates selenium, vitamin C, zinc, and vitamin D will be discussed in this narrative review. The existing evidence provided so far demonstrates that several factors need to be considered to determine the efficacy of an antioxidant supplementation strategy in patients who are critically ill and indicates the need for adequately designed multicenter prospective randomized control trials to evaluate the clinical significance of different types and doses of micronutrients and vitamins in selected groups of patients with different types of critical illness.
In 1747, an important milestone in the history of clinical research was set, as the Scottish surgeon James Lind conducted the first randomized controlled trial. Lind was interested in scurvy, a severe vitamin C deficiency which caused the death of thousands of British seamen. He found that a dietary intervention with oranges and lemons, which are rich in vitamin C by nature, was effective to recover from scurvy. Because of its antioxidative properties and involvement in many biochemical processes, the essential micronutrient vitamin C plays a key role in the human biology. Moreover, the use of vitamin C in critical illness—a condition also resulting in death of thousands in the 21st century—has gained increasing interest, as it may restore vascular responsiveness to vasoactive agents, ameliorate microcirculatory blood flow, preserve endothelial barriers, augment bacterial defense, and prevent apoptosis. Because of its redox potential and powerful antioxidant capacity, vitamin C represents an inexpensive and safe antioxidant, with the potential to modify the inflammatory cascade and improve clinical outcomes of critically ill patients. This narrative review aims to update and provide an overview on the role of vitamin C in the human biology and in critically ill patients, and to summarize current evidence on the use of vitamin C in diverse populations of critically ill patients, in specific focusing on patients with sepsis and coronavirus disease 2019.
Introduction: Numerous tools exist to detect potentially inappropriate medication (PIM) and potential prescribing omissions (PPO) in older people, but it remains unclear which tools may be most relevant in which setting. Objectives: This cross sectional study compares six validated tools in terms of PIM and PPO detection. Methods: We examined the PIM/PPO prevalence for all tools combined and the sensitivity of each tool. The pairwise agreement between tools was determined using Cohen’s Kappa. Results: We included 226 patients in need of care (median (IQR age 84 (80–89)). The overall PIM prevalence was 91.6 (95% CI, 87.2–94.9)% and the overall PPO prevalence was 63.7 (57.1–69.9%)%. The detected PIM prevalence ranged from 76.5%, for FORTA-C/D, to 6.6% for anticholinergic drugs (German-ACB). The PPO prevalences for START (63.7%) and FORTA-A (62.8%) were similar. The pairwise agreement between tools was poor to moderate. The sensitivity of PIM detection was highest for FORTA-C/D (55.1%), and increased to 79.2% when distinct items from STOPP were added. Conclusion: Using a single screening tool may not have sufficient sensitivity to detect PIMs and PPOs. Further research is required to optimize the composition of PIM and PPO tools in different settings.
Human startle disease is associated with mutations in distinct genes encoding glycine receptors, transporters or interacting proteins at glycinergic synapses in spinal cord and brainstem. However, a significant number of diagnosed patients does not carry a mutation in the common genes GLRA1, GLRB, and SLC6A5. Recently, studies on solute carrier 7 subfamily 10 (SLC7A10; Asc-1, alanine-serine-cysteine transporter) knock-out (KO) mice displaying a startle disease-like phenotype hypothesized that this transporter might represent a novel candidate for human startle disease. Here, we screened 51 patients from our patient cohort negative for the common genes and found three exonic (one missense, two synonymous), seven intronic, and single nucleotide changes in the 5′ and 3′ untranslated regions (UTRs) in Asc-1. The identified missense mutation Asc-1\(^{G307R}\) from a patient with startle disease and developmental delay was investigated in functional studies. At the molecular level, the mutation Asc-1\(^{G307R}\) did not interfere with cell-surface expression, but disrupted glycine uptake. Substitution of glycine at position 307 to other amino acids, e.g., to alanine or tryptophan did not affect trafficking or glycine transport. By contrast, G307K disrupted glycine transport similar to the G307R mutation found in the patient. Structurally, the disrupted function in variants carrying positively charged residues can be explained by local structural rearrangements because of the large positively charged side chain. Thus, our data suggest that SLC7A10 may represent a rare but novel gene associated with human startle disease and developmental delay.
Precision-cut tumor slices (PCTS) maintain tissue heterogeneity concerning different cell types and preserve the tumor microenvironment (TME). Typically, PCTS are cultured statically on a filter support at an air–liquid interface, which gives rise to intra-slice gradients during culture. To overcome this problem, we developed a perfusion air culture (PAC) system that can provide a continuous and controlled oxygen medium, and drug supply. This makes it an adaptable ex vivo system for evaluating drug responses in a tissue-specific microenvironment. PCTS from mouse xenografts (MCF-7, H1437) and primary human ovarian tumors (primary OV) cultured in the PAC system maintained the morphology, proliferation, and TME for more than 7 days, and no intra-slice gradients were observed. Cultured PCTS were analyzed for DNA damage, apoptosis, and transcriptional biomarkers for the cellular stress response. For the primary OV slices, cisplatin treatment induced a diverse increase in the cleavage of caspase-3 and PD-L1 expression, indicating a heterogeneous response to drug treatment between patients. Immune cells were preserved throughout the culturing period, indicating that immune therapy can be analyzed. The novel PAC system is suitable for assessing individual drug responses and can thus be used as a preclinical model to predict in vivo therapy responses.
Posture and mobility are important aspects for spinal health. In the context of low back pain, strategies to alter postural anomalies (e.g., hyper/hypolordosis, hyper/hypokyphosis) and mobility deficits (e.g., bending restrictions) have been of interest to researchers and clinicians. Machine-based isolated lumbar extension resistance exercise (ILEX) has been used successfully for rehabilitation of patients suffering from low back pain. The aim of this study was to analyse the immediate effects of ILEX on spinal posture and mobility. In this interventional cohort study, the posture and mobility measures of 33 healthy individuals (m = 17, f = 16; mean age 30.0 years) were taken using the surface-based Spinal Mouse system (IDIAG M360©, Fehraltdorf, Switzerland). Individuals performed one exercise set to full exhaustion with an ILEX-device (Powerspine, Wuerzburg, Germany) in a standardized setup, including uniform range of motion and time under tension. Scans were made immediately before and after the exercise. There was an immediate significant decrease in standing lumbar lordosis and thoracic kyphosis. No change could be observed in standing pelvic tilt. Mobility measures showed a significant decrease in the lumbar spine and an increase in the sacrum. The results show that ILEX alters spine posture and mobility in the short-term, which may benefit certain patient groups.
Herpes simplex virus 1 (HSV-1) infection and stress responses disrupt transcription termination by RNA Polymerase II (Pol II). In HSV-1 infection, but not upon salt or heat stress, this is accompanied by a dramatic increase in chromatin accessibility downstream of genes. Here, we show that the HSV-1 immediate-early protein ICP22 is both necessary and sufficient to induce downstream open chromatin regions (dOCRs) when transcription termination is disrupted by the viral ICP27 protein. This is accompanied by a marked ICP22-dependent loss of histones downstream of affected genes consistent with impaired histone repositioning in the wake of Pol II. Efficient knock-down of the ICP22-interacting histone chaperone FACT is not sufficient to induce dOCRs in ΔICP22 infection but increases dOCR induction in wild-type HSV-1 infection. Interestingly, this is accompanied by a marked increase in chromatin accessibility within gene bodies. We propose a model in which allosteric changes in Pol II composition downstream of genes and ICP22-mediated interference with FACT activity explain the differential impairment of histone repositioning downstream of genes in the wake of Pol II in HSV-1 infection.
B cell maturation and immunoglobulin (Ig) repertoire selection are governed by expression of a functional B cell receptor (BCR). Naïve B cells co-express their BCR as IgM and IgD isotype. However, the role of the additionally expressed IgD on naïve B cells is not known. Here we assessed the impact of IgD on naïve B cell maturation and Ig repertoire selection in 8 individuals from 3 different families with heterozygous loss-of-function or loss-of expression mutations in IGHD. Although naïve B cells from these individuals expressed IgM on their surface, the IGHD variant in heterozygous state entailed a chimeric situation by allelic exclusion with almost half of the naïve B cell population lacking surface IgD expression. Flow cytometric analyses revealed a distinct phenotype of IgD-negative naïve B cells with decreased expression of CD19, CD20 and CD21 as well as lower BAFF-R and integrin-β7 expression. IgD-negative B cells were less responsive in vitro after engaging the IgM-BCR, TLR7/9 or CD40 pathway. Additionally, a selective disadvantage of IgD-negative B cells within the T2 transitional and mature naïve B cell compartment as well as reduced frequencies of IgMlo/- B cells within the mature naïve B cell compartment lacking IgD were evident. RNA-Ig-seq of bulk sorted B cell populations showed an altered selection of distinct VH segments in the IgD-negative mature naïve B cell population. We conclude that IgD expression on human naïve B cells is redundant for generation of naïve B cells in general, but further shapes the naive B cell compartment starting from T2 transitional B cells. Our observations suggest an unexpected role of IgD expression to be critical for selection of distinct Ig VH segments into the pre-immune Ig repertoire and for the survival of IgMlo/- naïve B cells known to be enriched in poly-/autoreactive B cell clones.
Abstract
Cell lineage decisions occur in three-dimensional spatial patterns that are difficult to identify by eye. There is an ongoing effort to replicate such patterns using mathematical modeling. One approach uses long ranging cell-cell communication to replicate common spatial arrangements like checkerboard and engulfing patterns. In this model, the cell-cell communication has been implemented as a signal that disperses throughout the tissue. On the other hand, machine learning models have been developed for pattern recognition and pattern reconstruction tasks. We combined synthetic data generated by the mathematical model with spatial summary statistics and deep learning algorithms to recognize and reconstruct cell fate patterns in organoids of mouse embryonic stem cells. Application of Moran’s index and pair correlation functions for in vitro and synthetic data from the model showed local clustering and radial segregation. To assess the patterns as a whole, a graph neural network was developed and trained on synthetic data from the model. Application to in vitro data predicted a low signal dispersion value. To test this result, we implemented a multilayer perceptron for the prediction of a given cell fate based on the fates of the neighboring cells. The results show a 70% accuracy of cell fate imputation based on the nine nearest neighbors of a cell. Overall, our approach combines deep learning with mathematical modeling to link cell fate patterns with potential underlying mechanisms.
Author summary
Mammalian embryo development relies on organized differentiation of stem cells into different lineages. Particularly at the early stages of embryogenesis, cells of different fates form three-dimensional spatial patterns that are difficult to identify by eye. Pattern quantification and mathematical modeling have produced first insights into potential mechanisms for the cell fate arrangements. However, these approaches have relied on classifications of the patterns such as inside-out or random, or used summary statistics such as pair correlation functions or cluster radii. Deep neural networks allow characterizing patterns directly. Since the tissue context can be readily reproduced by a graph, we implemented a graph neural network to characterize the patterns of embryonic stem cell organoids as a whole. In addition, we implemented a multilayer perceptron model to reconstruct the fate of a given cell based on its neighbors. To train and test the models, we used synthetic data generated by our mathematical model for cell-cell communication. This interplay of deep learning and mathematical modeling in combination with summary statistics allowed us to identify a potential mechanism for cell fate determination in mouse embryonic stem cells. Our results agree with a mechanism with a dispersion of the intercellular signal that links a cell’s fate to those of the local neighborhood.
To study coisotropic reduction in the context of deformation quantization we introduce constraint manifolds and constraint algebras as the basic objects encoding the additional information needed to define a reduction. General properties of various categories of constraint objects and their compatiblity with reduction are examined. A constraint Serre-Swan theorem, identifying constraint vector bundles with certain finitely generated projective constraint modules, as well as a constraint symbol calculus are proved. After developing the general deformation theory of constraint algebras, including constraint Hochschild cohomology and constraint differential graded Lie algebras, the second constraint Hochschild cohomology for the constraint algebra of functions on a constraint flat space is computed.
The execution of voluntary movements is primarily governed by the cerebral hemisphere contralateral to the moving limb. Previous research indicates that the ipsilateral motor network, comprising the primary motor cortex (M1), supplementary motor area (SMA), and premotor cortex (PM), plays a crucial role in the planning and execution of limb movements. However, the precise functions of this network and its interplay in different task contexts have yet to be fully understood. Twenty healthy right-handed participants (10 females, mean age 26.1 ± 4.6 years) underwent functional MRI scans while performing biceps brachii representations such as bilateral, unilateral flexion, and bilateral flexion-extension. Ipsilateral motor evoked potentials (iMEPs) were obtained from the identical set of participants in a prior study using transcranial magnetic stimulation (TMS) targeting M1 while employing the same motor tasks. The voxel time series was extracted based on the region of interest (M1, SMA, ventral PM and dorsal PM). Directed functinal connectivity was derived from the extracted time series using time-resolved partial directed coherence. We found increased connectivity from left-PMv to both sides M1, as well as right-PMv to both sides SMA, in unilateral flexion compared to bilateral flexion. Connectivity from left M1 to left-PMv, and left-SMA to right-PMd, also increased in both unilateral flexion and bilateral flexion-extension compared to bilateral flexion. However, connectivity between PMv and right-M1 to left-PMd decreased during bilateral flexion-extension compared to unilateral flexion. Additionally, during bilateral flexion-extension, the connectivity from right-M1 to right-SMA had a negative relationship with the area ratio of iMEP in the dominant side. Our results provide corroborating evidence for prior research suggesting that the ipsilateral motor network is implicated in the voluntary movements and underscores its involvement in cognitive processes such as movement planning and coordination. Moreover, ipsilateral connectivity from M1 to SMA on the dominant side can modulate the degree of ipsilateral M1 activation during bilateral antagonistic contraction.
We report the synthesis and spectroscopic analysis of RNA containing the barbituric acid merocyanine rBAM2 as a nucleobase surrogate. Incorporation into RNA strands by solid-phase synthesis leads to fluorescence enhancement compared to the free chromophore. In addition, linear absorption studies show the formation of an excitonically coupled H-type dimer in the hybridized duplex. Ultrafast third- and fifth-order transient absorption spectroscopy of this non-fluorescent dimer suggests immediate (sub-200 fs) exciton transfer and annihilation due to the proximity of the rBAM2 units.
Purpose
The reliable detection of tumor-infiltrated axillary lymph nodes for breast cancer [BC] patients plays a decisive role in further therapy. We aimed to find out whether cross-sectional imaging techniques could improve sensitivity for pretherapeutic axillary staging in nodal-positive BC patients compared to conventional imaging such as mammography and sonography.
Methods
Data for breast cancer patients with tumor-infiltrated axillary lymph nodes having received surgery between 2014 and 2020 were included in this study.
All examinations (sonography, mammography, computed tomography [CT] and magnetic resonance imaging [MRI]) were interpreted by board-certified specialists in radiology. The sensitivity of different imaging modalities was calculated, and binary logistic regression analyses were performed to detect variables influencing the detection of positive lymph nodes.
Results
All included 382 breast cancer patients had received conventional imaging, while 52.61% of the patients had received cross-sectional imaging.
The sensitivity of the combination of all imaging modalities was 68.89%. The combination of MRI and CT showed 63.83% and the combination of sonography and mammography showed 36.11% sensitivity.
Conclusion
We could demonstrate that cross-sectional imaging can improve the sensitivity of the detection of tumor-infiltrated axillary lymph nodes in breast cancer patients. Only the safe detection of these lymph nodes at the time of diagnosis enables the evaluation of the response to neoadjuvant therapy, thereby allowing access to prognosis and improving new post-neoadjuvant therapies.
Recently, Tummino et al. reported that 34 compounds, including Chloroquine and Fluoxetine, inhibit SARS-CoV-2 replication by inducing phospholipidosis, although Chloroquine failed to suppress viral replication in Calu-3 cells and patients. In contrast, Fluoxetine represses viral replication in human precision-cut lung slices (PCLS) and Calu-3 cells. Thus, it is unlikely that these compounds have similar mechanisms of action. Here, we analysed a subset of these compounds in the viral replication and phospholipidosis assays using the Calu-3 cells and PCLS as the patient-near system. Trimipramine and Chloroquine induced phospholipidosis but failed to inhibit SARS-CoV-2 replication in Calu-3 cells, which contradicts the reported findings and the proposed mechanism. Fluoxetine, only slightly induced phospholipidosis in Calu-3 cells but reduced viral replication by 2.7 orders of magnitude. Tilorone suppressed viral replication by 1.9 orders of magnitude in Calu-3 cells without causing phospholipidosis. Thus, induction of phospholipidosis is not correlated with the inhibition of SARS-CoV-2, and the compounds act via other mechanisms. However, we show that compounds, such as Amiodarone, Tamoxifen and Tilorone, with antiviral activity on Calu-3 cells, also inhibited viral replication in human PCLS. Our results indicate that antiviral assays against SARS-CoV-2 are cell-line specific. Data from Vero E6 can lead to non-transferable results, underlining the importance of an appropriate cell system for analysing antiviral compounds against SARS-CoV-2. We observed a correlation between the active compounds in Calu-3 cells and PCLS.
Formation of the Aurora-A–MYCN complex increases levels of the oncogenic transcription factor MYCN in neuroblastoma cells by abrogating its degradation through the ubiquitin proteasome system. While some small-molecule inhibitors of Aurora-A were shown to destabilize MYCN, clinical trials have not been satisfactory to date. MYCN itself is considered to be `undruggable' due to its large intrinsically disordered regions. Targeting the Aurora-A–MYCN complex rather than Aurora-A or MYCN alone will open new possibilities for drug development and screening campaigns. To overcome the challenges that a ternary system composed of Aurora-A, MYCN and a small molecule entails, a covalently cross-linked construct of the Aurora-A–MYCN complex was designed, expressed and characterized, thus enabling screening and design campaigns to identify selective binders.
The increasing availability and variety of global satellite products and the rapid development of new algorithms has provided great potential to generate a new level of data with different spatial, temporal, and spectral resolutions. However, the ability of these synthetic spatiotemporal datasets to accurately map and monitor our planet on a field or regional scale remains underexplored. This study aimed to support future research efforts in estimating crop yields by identifying the optimal spatial (10 m, 30 m, or 250 m) and temporal (8 or 16 days) resolutions on a regional scale. The current study explored and discussed the suitability of four different synthetic (Landsat (L)-MOD13Q1 (30 m, 8 and 16 days) and Sentinel-2 (S)-MOD13Q1 (10 m, 8 and 16 days)) and two real (MOD13Q1 (250 m, 8 and 16 days)) NDVI products combined separately to two widely used crop growth models (CGMs) (World Food Studies (WOFOST), and the semi-empiric Light Use Efficiency approach (LUE)) for winter wheat (WW) and oil seed rape (OSR) yield forecasts in Bavaria (70,550 km\(^2\)) for the year 2019. For WW and OSR, the synthetic products’ high spatial and temporal resolution resulted in higher yield accuracies using LUE and WOFOST. The observations of high temporal resolution (8-day) products of both S-MOD13Q1 and L-MOD13Q1 played a significant role in accurately measuring the yield of WW and OSR. For example, L- and S-MOD13Q1 resulted in an R\(^2\) = 0.82 and 0.85, RMSE = 5.46 and 5.01 dt/ha for WW, R\(^2\) = 0.89 and 0.82, and RMSE = 2.23 and 2.11 dt/ha for OSR using the LUE model, respectively. Similarly, for the 8- and 16-day products, the simple LUE model (R\(^2\) = 0.77 and relative RMSE (RRMSE) = 8.17%) required fewer input parameters to simulate crop yield and was highly accurate, reliable, and more precise than the complex WOFOST model (R\(^2\) = 0.66 and RRMSE = 11.35%) with higher input parameters. Conclusively, both S-MOD13Q1 and L-MOD13Q1, in combination with LUE, were more prominent for predicting crop yields on a regional scale than the 16-day products; however, L-MOD13Q1 was advantageous for generating and exploring the long-term yield time series due to the availability of Landsat data since 1982, with a maximum resolution of 30 m. In addition, this study recommended the further use of its findings for implementing and validating the long-term crop yield time series in different regions of the world.
Rapid and accurate yield estimates at both field and regional levels remain the goal of sustainable agriculture and food security. Hereby, the identification of consistent and reliable methodologies providing accurate yield predictions is one of the hot topics in agricultural research. This study investigated the relationship of spatiotemporal fusion modelling using STRAFM on crop yield prediction for winter wheat (WW) and oil-seed rape (OSR) using a semi-empirical light use efficiency (LUE) model for the Free State of Bavaria (70,550 km\(^2\)), Germany, from 2001 to 2019. A synthetic normalised difference vegetation index (NDVI) time series was generated and validated by fusing the high spatial resolution (30 m, 16 days) Landsat 5 Thematic Mapper (TM) (2001 to 2012), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (2012), and Landsat 8 Operational Land Imager (OLI) (2013 to 2019) with the coarse resolution of MOD13Q1 (250 m, 16 days) from 2001 to 2019. Except for some temporal periods (i.e., 2001, 2002, and 2012), the study obtained an R\(^2\) of more than 0.65 and a RMSE of less than 0.11, which proves that the Landsat 8 OLI fused products are of higher accuracy than the Landsat 5 TM products. Moreover, the accuracies of the NDVI fusion data have been found to correlate with the total number of available Landsat scenes every year (N), with a correlation coefficient (R) of +0.83 (between R\(^2\) of yearly synthetic NDVIs and N) and −0.84 (between RMSEs and N). For crop yield prediction, the synthetic NDVI time series and climate elements (such as minimum temperature, maximum temperature, relative humidity, evaporation, transpiration, and solar radiation) are inputted to the LUE model, resulting in an average R\(^2\) of 0.75 (WW) and 0.73 (OSR), and RMSEs of 4.33 dt/ha and 2.19 dt/ha. The yield prediction results prove the consistency and stability of the LUE model for yield estimation. Using the LUE model, accurate crop yield predictions were obtained for WW (R\(^2\) = 0.88) and OSR (R\(^2\) = 0.74). Lastly, the study observed a high positive correlation of R = 0.81 and R = 0.77 between the yearly R\(^2\) of synthetic accuracy and modelled yield accuracy for WW and OSR, respectively.
The fast and accurate yield estimates with the increasing availability and variety of global satellite products and the rapid development of new algorithms remain a goal for precision agriculture and food security. However, the consistency and reliability of suitable methodologies that provide accurate crop yield outcomes still need to be explored. The study investigates the coupling of crop modeling and machine learning (ML) to improve the yield prediction of winter wheat (WW) and oil seed rape (OSR) and provides examples for the Free State of Bavaria (70,550 km2), Germany, in 2019. The main objectives are to find whether a coupling approach [Light Use Efficiency (LUE) + Random Forest (RF)] would result in better and more accurate yield predictions compared to results provided with other models not using the LUE. Four different RF models [RF1 (input: Normalized Difference Vegetation Index (NDVI)), RF2 (input: climate variables), RF3 (input: NDVI + climate variables), RF4 (input: LUE generated biomass + climate variables)], and one semi-empiric LUE model were designed with different input requirements to find the best predictors of crop monitoring. The results indicate that the individual use of the NDVI (in RF1) and the climate variables (in RF2) could not be the most accurate, reliable, and precise solution for crop monitoring; however, their combined use (in RF3) resulted in higher accuracies. Notably, the study suggested the coupling of the LUE model variables to the RF4 model can reduce the relative root mean square error (RRMSE) from −8% (WW) and −1.6% (OSR) and increase the R
2 by 14.3% (for both WW and OSR), compared to results just relying on LUE. Moreover, the research compares models yield outputs by inputting three different spatial inputs: Sentinel-2(S)-MOD13Q1 (10 m), Landsat (L)-MOD13Q1 (30 m), and MOD13Q1 (MODIS) (250 m). The S-MOD13Q1 data has relatively improved the performance of models with higher mean R
2 [0.80 (WW), 0.69 (OSR)], and lower RRMSE (%) (9.18, 10.21) compared to L-MOD13Q1 (30 m) and MOD13Q1 (250 m). Satellite-based crop biomass, solar radiation, and temperature are found to be the most influential variables in the yield prediction of both crops.
Accurate crop monitoring in response to climate change at a regional or field scale
plays a significant role in developing agricultural policies, improving food security,
forecasting, and analysing global trade trends. Climate change is expected to
significantly impact agriculture, with shifts in temperature, precipitation patterns, and
extreme weather events negatively affecting crop yields, soil fertility, water availability,
biodiversity, and crop growing conditions. Remote sensing (RS) can provide valuable
information combined with crop growth models (CGMs) for yield assessment by
monitoring crop development, detecting crop changes, and assessing the impact of
climate change on crop yields. This dissertation aims to investigate the potential of RS
data on modelling long-term crop yields of winter wheat (WW) and oil seed rape (OSR)
for the Free State of Bavaria (70,550 km2
), Germany. The first chapter of the dissertation
describes the reasons favouring the importance of accurate crop yield predictions for
achieving sustainability in agriculture. Chapter second explores the accuracy
assessment of the synthetic RS data by fusing NDVIs of two high spatial resolution data
(high pair) (Landsat (30 m, 16-days; L) and Sentinel-2 (10 m, 5–6 days; S), with four low
spatial resolution data (low pair) (MOD13Q1 (250 m, 16-days), MCD43A4 (500 m, one
day), MOD09GQ (250 m, one-day), and MOD09Q1 (250 m, 8-days)) using the spatial
and temporal adaptive reflectance fusion model (STARFM), which fills regions' cloud
or shadow gaps without losing spatial information. The chapter finds that both L-MOD13Q1 (R2 = 0.62, RMSE = 0.11) and S-MOD13Q1 (R2 = 0.68, RMSE = 0.13) are more
suitable for agricultural monitoring than the other synthetic products fused. Chapter
third explores the ability of the synthetic spatiotemporal datasets (obtained in chapter
2) to accurately map and monitor crop yields of WW and OSR at a regional scale. The
chapter investigates and discusses the optimal spatial (10 m, 30 m, or 250 m), temporal
(8 or 16-day) and CGMs (World Food Studies (WOFOST), and the semi-empiric light
use efficiency approach (LUE)) for accurate crop yield estimations of both crop types.
Chapter third observes that the observations of high temporal resolution (8-day)
products of both S-MOD13Q1 and L-MOD13Q1 play a significant role in accurately
measuring the yield of WW and OSR. The chapter investigates that the simple light use
efficiency (LUE) model (R2 = 0.77 and relative RMSE (RRMSE) = 8.17%) that required fewer input parameters to simulate crop yield is highly accurate, reliable, and more
precise than the complex WOFOST model (R2 = 0.66 and RRMSE = 11.35%) with higher
input parameters. Chapter four researches the relationship of spatiotemporal fusion
modelling using STRAFM on crop yield prediction for WW and OSR using the LUE
model for Bavaria from 2001 to 2019. The chapter states the high positive correlation
coefficient (R) = 0.81 and R = 0.77 between the yearly R2 of synthetic accuracy and
modelled yield accuracy for WW and OSR from 2001 to 2019, respectively. The chapter
analyses the impact of climate variables on crop yield predictions by observing an
increase in R2
(0.79 (WW)/0.86 (OSR)) and a decrease in RMSE (4.51/2.57 dt/ha) when
the climate effect is included in the model. The fifth chapter suggests that the coupling
of the LUE model to the random forest (RF) model can further reduce the relative root
mean square error (RRMSE) from -8% (WW) and -1.6% (OSR) and increase the R2 by
14.3% (for both WW and OSR), compared to results just relying on LUE. The same
chapter concludes that satellite-based crop biomass, solar radiation, and temperature
are the most influential variables in the yield prediction of both crop types. Chapter six
attempts to discuss both pros and cons of RS technology while analysing the impact of
land use diversity on crop-modelled biomass of WW and OSR. The chapter finds that
the modelled biomass of both crops is positively impacted by land use diversity to the
radius of 450 (Shannon Diversity Index ~0.75) and 1050 m (~0.75), respectively. The
chapter also discusses the future implications by stating that including some dependent
factors (such as the management practices used, soil health, pest management, and
pollinators) could improve the relationship of RS-modelled crop yields with
biodiversity. Lastly, chapter seven discusses testing the scope of new sensors such as
unmanned aerial vehicles, hyperspectral sensors, or Sentinel-1 SAR in RS for achieving
accurate crop yield predictions for precision farming. In addition, the chapter highlights
the significance of artificial intelligence (AI) or deep learning (DL) in obtaining higher
crop yield accuracies.
Accurate crop monitoring in response to climate change at a regional or field scale plays a significant role in developing agricultural policies, improving food security, forecasting, and analysing global trade trends. Climate change is expected to significantly impact agriculture, with shifts in temperature, precipitation patterns, and extreme weather events negatively affecting crop yields, soil fertility, water availability, biodiversity, and crop growing conditions. Remote sensing (RS) can provide valuable information combined with crop growth models (CGMs) for yield assessment by monitoring crop development, detecting crop changes, and assessing the impact of climate change on crop yields. This dissertation aims to investigate the potential of RS data on modelling long-term crop yields of winter wheat (WW) and oil seed rape (OSR) for the Free State of Bavaria (70,550 km2), Germany. The first chapter of the dissertation describes the reasons favouring the importance of accurate crop yield predictions for achieving sustainability in agriculture. Chapter second explores the accuracy assessment of the synthetic RS data by fusing NDVIs of two high spatial resolution data (high pair) (Landsat (30 m, 16-days; L) and Sentinel-2 (10 m, 5–6 days; S), with four low spatial resolution data (low pair) (MOD13Q1 (250 m, 16-days), MCD43A4 (500 m, one day), MOD09GQ (250 m, one-day), and MOD09Q1 (250 m, 8-days)) using the spatial and temporal adaptive reflectance fusion model (STARFM), which fills regions' cloud or shadow gaps without losing spatial information. The chapter finds that both L-MOD13Q1 (R2 = 0.62, RMSE = 0.11) and S-MOD13Q1 (R2 = 0.68, RMSE = 0.13) are more suitable for agricultural monitoring than the other synthetic products fused. Chapter third explores the ability of the synthetic spatiotemporal datasets (obtained in chapter 2) to accurately map and monitor crop yields of WW and OSR at a regional scale. The chapter investigates and discusses the optimal spatial (10 m, 30 m, or 250 m), temporal (8 or 16-day) and CGMs (World Food Studies (WOFOST), and the semi-empiric light use efficiency approach (LUE)) for accurate crop yield estimations of both crop types. Chapter third observes that the observations of high temporal resolution (8-day) products of both S-MOD13Q1 and L-MOD13Q1 play a significant role in accurately measuring the yield of WW and OSR. The chapter investigates that the simple light use efficiency (LUE) model (R2 = 0.77 and relative RMSE (RRMSE) = 8.17%) that required fewer input parameters to simulate crop yield is highly accurate, reliable, and more precise than the complex WOFOST model (R2 = 0.66 and RRMSE = 11.35%) with higher input parameters. Chapter four researches the relationship of spatiotemporal fusion modelling using STRAFM on crop yield prediction for WW and OSR using the LUE model for Bavaria from 2001 to 2019. The chapter states the high positive correlation coefficient (R) = 0.81 and R = 0.77 between the yearly R2 of synthetic accuracy and modelled yield accuracy for WW and OSR from 2001 to 2019, respectively. The chapter analyses the impact of climate variables on crop yield predictions by observing an increase in R2 (0.79 (WW)/0.86 (OSR)) and a decrease in RMSE (4.51/2.57 dt/ha) when the climate effect is included in the model. The fifth chapter suggests that the coupling of the LUE model to the random forest (RF) model can further reduce the relative root mean square error (RRMSE) from -8% (WW) and -1.6% (OSR) and increase the R2 by 14.3% (for both WW and OSR), compared to results just relying on LUE. The same chapter concludes that satellite-based crop biomass, solar radiation, and temperature are the most influential variables in the yield prediction of both crop types. Chapter six attempts to discuss both pros and cons of RS technology while analysing the impact of land use diversity on crop-modelled biomass of WW and OSR. The chapter finds that the modelled biomass of both crops is positively impacted by land use diversity to the radius of 450 (Shannon Diversity Index ~0.75) and 1050 m (~0.75), respectively. The chapter also discusses the future implications by stating that including some dependent factors (such as the management practices used, soil health, pest management, and pollinators) could improve the relationship of RS-modelled crop yields with biodiversity. Lastly, chapter seven discusses testing the scope of new sensors such as unmanned aerial vehicles, hyperspectral sensors, or Sentinel-1 SAR in RS for achieving accurate crop yield predictions for precision farming. In addition, the chapter highlights the significance of artificial intelligence (AI) or deep learning (DL) in obtaining higher crop yield accuracies.
Honeybees (Apis mellifera) need their fine sense of taste to evaluate nectar and pollen sources. Gustatory receptors (Grs) translate taste signals into electrical responses. In vivo experiments have demonstrated collective responses of the whole Gr-set. We here disentangle the contributions of all three honeybee sugar receptors (AmGr1-3), combining CRISPR/Cas9 mediated genetic knock-out, electrophysiology and behaviour. We show an expanded sugar spectrum of the AmGr1 receptor. Mutants lacking AmGr1 have a reduced response to sucrose and glucose but not to fructose. AmGr2 solely acts as co-receptor of AmGr1 but not of AmGr3, as we show by electrophysiology and using bimolecular fluorescence complementation. Our results show for the first time that AmGr2 is indeed a functional receptor on its own. Intriguingly, AmGr2 mutants still display a wildtype-like sugar taste. AmGr3 is a specific fructose receptor and is not modulated by a co-receptor. Eliminating AmGr3 while preserving AmGr1 and AmGr2 abolishes the perception of fructose but not of sucrose. Our comprehensive study on the functions of AmGr1, AmGr2 and AmGr3 in honeybees is the first to combine investigations on sugar perception at the receptor level and simultaneously in vivo. We show that honeybees rely on two gustatory receptors to sense all relevant sugars.
In the eusocial insect honeybee (Apis mellifera), many sterile worker bees live together with a reproductive queen in a colony. All tasks of the colony are performed by the workers, undergoing age-dependent division of labor. Beginning as hive bees, they take on tasks inside the hive such as cleaning or the producing of larval food, later developing into foragers. With that, the perception of sweetness plays a crucial role for all honeybees whether they are sitting on the honey stores in the hive or foraging for food. Their ability to sense sweetness is undoubtedly necessary to develop and evaluate food sources. Many of the behavioral decisions in honeybees are based on sugar perception, either on an individual level for ingestion, or for social behavior such as the impulse to collect or process nectar. In this context, honeybees show a complex spectrum of abilities to perceive sweetness on many levels. They are able to perceive at least seven types of sugars and decide to collect them for the colony. Further, they seem to distinguish between these sugars or at least show clear preferences when collecting them. Additionally, the perception of sugar is not rigid in honeybees. For instance, their responsiveness towards sugar changes during the transition from in-hive bees (e.g. nurses) to foraging and is linked to the division of labor. Other direct or immediate factors changing responsiveness to sugars are stress, starvation or underlying factors, such as genotype.
Interestingly, the complexity in their sugar perception is in stark contrast to the fact that honeybees seem to have only three predicted sugar receptors.
In this work, we were able to characterize the three known sugar receptors (AmGr1, AmGr2 and AmGr3) of the honeybee fully and comprehensively in oocytes (Manuscript II, Chapter 3 and Manuscript III, Chapter 4). We could show that AmGr1 is a broad sugar receptor reacting to sucrose, glucose, maltose, melezitose and trehalose (which is the honeybees’ main blood sugar), but not fructose. AmGr2 acts as its co-receptor altering AmGr1’s specificity, AmGr3 is a specific fructose receptor and we proved the heterodimerization of all receptors. With my studies, I was able to reproduce and compare the ligand specificity of the sugar receptors in vivo by generating receptor mutants with CRISPR/Cas9. With this thesis, I was able to define AmGr1 and AmGr3 as the honeybees’ basis receptors already capable to detect all sugars of its known taste spectrum.
In the expression analysis of my doctoral thesis (Manuscript I, Chapter 2) I demonstrated that both basis receptors are expressed in the antennae and the brain of nurse bees and foragers. This thesis assumes that AmGr3 (like the Drosophila homologue) functions as a sensor for fructose, which might be the satiety signal, while AmGr1 can sense trehalose as the main blood sugar in the brain. Both receptors show a reduced expression in the brain of foragers when compared with nurse bees. These results may reflect the higher concentrated diet of nurse bees in the hive. The higher number of receptors in the brain may allow nurse bees to perceive hunger earlier and to consume the food their sitting on. Forager bees have to be more persistent to hunger, when they are foraging, and food is not so accessible. The findings of reduced expression of the fructose receptor AmGr3 in the antennae of nurse bees are congruent with my other result that nurse bees are also less responsive to fructose at the antennae when compared to foragers (Manuscript I, Chapter 2). This is possible, since nurse bees sit more likely on ripe honey which contains not only higher levels of sugars but also monosaccharides (such as fructose), while foragers have to evaluate less-concentrated nectar.
My investigations of the expression of AmGr1 in the antennae of honeybees found no differences between nurse bees and foragers, although foragers are more responsive to the respective sugar sucrose (Manuscript I, Chapter 2). Considering my finding that AmGr2 is the co-receptor of AmGr1, it can be assumed that AmGr1 and the mediated sucrose taste might not be directly controlled by its expression, but indirectly by its co-receptor. My thesis therefore clearly shows that sugar perception is associated with division of labor in honeybees and appears to be directly or indirectly regulated via expression.
The comparison with a characterization study using other bee breeds and thus an alternative protein sequence of AmGr1 shows that co-expression of different AmGr1 versions with AmGr2 alters the sugar response differently. Therefore, this thesis provides first important indications that alternative splicing could also represent an important regulatory mechanism for sugar perception in honeybees.
Further, I found out that the bitter compound quinine lowers the reward quality in learning experiments for honeybees (Manuscript IV, Chapter 5). So far, no bitter receptor has been found in the genome of honeybees and this thesis strongly assumes that bitter substances such as quinine inhibit sugar receptors in honeybees. With this finding, my work includes other molecules as possible regulatory mechanism in the honeybee sugar perception as well. We showed that the inhibitory effect is lower for fructose compared to sucrose. Considering that sugar signals might be processed as differently attractive in honeybees, this thesis concludes that the sugar receptor inhibition via quinine in honeybees might depend on the receptor (or its co-receptor), is concentration-dependent and based on the salience or attractiveness and concentration of the sugar present.
With my thesis, I was able to expand the knowledge on honeybee’s sugar perception and formulate a complex, comprehensive overview. Thereby, I demonstrated the multidimensional mechanism that regulates the sugar receptors and thus the sugar perception of honeybees. With this work, I defined AmGr1 and AmGr3 as the basis of sugar perception and enlarged these components to the co-receptor AmGr2 and the possible splice variants of AmGr1. I further demonstrated how those sugar receptor components function, interact and that they are clearly involved in the division of labor in honeybees. In summary, my thesis describes the mechanisms that enable honeybees to perceive sugar in a complex way, even though they inhere a limited number of sugar receptors. My data strongly suggest that honeybees overall might not only differentiate sugars and their diet by their general sweetness (as expected with only one main sugar receptor). The found sugar receptor mechanisms and their interplay further suggest that honeybees might be able to discriminate directly between monosaccharides and disaccharides or sugar molecules and with that their diet (honey and nectar).
In highly polarized neurons, endoplasmic reticulum (ER) forms a dynamic and continuous network in axons that plays important roles in lipid synthesis, Ca2+ homeostasis and the maintenance of synapses. However, the mechanisms underlying the regulation of axonal ER dynamics and its function in regulation of local translation still remain elusive. In the course of my thesis, I investigated the fast dynamic movements of ER and ribosomes in the growth cone of wildtype motoneurons as well as motoneurons from a mouse model of Spinal Muscular Atrophy (SMA), in response to Brain-derived neurotrophic factor (BDNF) stimulation. Live cell imaging data show that ER extends into axonal growth cone filopodia along actin filaments and disruption of actin cytoskeleton by cytochalasin D treatment impairs the dynamic movement of ER in the axonal filopodia. In contrast to filopodia, ER movements in the growth cone core seem to depend on coordinated actions of the actin and microtubule cytoskeleton. Myosin VI is especially required for ER movements into filopodia and drebrin A mediates actin/microtubule coordinated ER dynamics. Furthermore, we found that BDNF/TrkB signaling induces assembly of 80S ribosomes in growth cones on a time scale of seconds. Activated ribosomes relocate to the presynaptic ER and undergo local translation. These findings describe the dynamic interaction between ER and ribosomes during local translation and identify a novel potential function for the presynaptic ER in intra-axonal synthesis of transmembrane proteins such as the α-1β subunit of N-type Ca2+ channels in motoneurons. In addition, we demonstrate that in Smn-deficient motoneurons, ER dynamic movements are impaired in axonal growth cones that seems to be due to impaired actin cytoskeleton. Interestingly, ribosomes fail to undergo rapid structural changes in Smn-deficient growth cones and do not associate to ER in response to BDNF. Thus, aberrant ER dynamics and ribosome response to extracellular stimuli could affect axonal growth and presynaptic function and maintenance, thereby contributing to the pathology of SMA.
Low-frequency oscillatory patterns of pallidal local field potentials (LFPs) have been proposed as a physiomarker for dystonia and hold the promise for personalized adaptive deep brain stimulation. Head tremor, a low-frequency involuntary rhythmic movement typical of cervical dystonia, may cause movement artifacts in LFP signals, compromising the reliability of low-frequency oscillations as biomarkers for adaptive neurostimulation. We investigated chronic pallidal LFPs with the Percept\(^{TM}\) PC (Medtronic PLC) device in eight subjects with dystonia (five with head tremors). We applied a multiple regression approach to pallidal LFPs in patients with head tremors using kinematic information measured with an inertial measurement unit (IMU) and an electromyographic signal (EMG). With IMU regression, we found tremor contamination in all subjects, whereas EMG regression identified it in only three out of five. IMU regression was also superior to EMG regression in removing tremor-related artifacts and resulted in a significant power reduction, especially in the theta-alpha band. Pallido-muscular coherence was affected by a head tremor and disappeared after IMU regression. Our results show that the Percept PC can record low-frequency oscillations but also reveal spectral contamination due to movement artifacts. IMU regression can identify such artifact contamination and be a suitable tool for its removal.
Agricultural abandonment is one of the main land-use changes in Europe, and its consequences on biodiversity are context- and taxa-dependent. While several studies have worked on this topic, few have focused on traditional orchards, especially in different landscapes and under a Mediterranean climate. In this context, we aimed to determine the effects of almond orchard abandonment on the communities of three groups of beneficial arthropods and the role of the landscape context in modulating these effects. Between February and September 2019, four samplings were carried out in twelve almond orchards (three abandoned and three traditional (active orchards under traditional agricultural management) located in simple landscapes as well as three abandoned and three traditional in complex landscapes). Abandoned and traditional almond orchards harbor different arthropod communities and diversity metrics that are strongly conditioned by seasonality. Abandoned orchards can favor pollinators and natural enemies, providing alternative resources in simple landscapes. However, the role that abandoned orchards play in simple landscapes disappears as the percentage of semi-natural habitats in the landscape increases. Our results show that landscape simplification, through the loss of semi-natural habitats, has negative consequences on arthropod biodiversity, even in traditional farming landscapes with small fields and high crop diversity.
To evaluate an iterative learning approach for enhanced performance of robust artificial‐neural‐networks for k‐space interpolation (RAKI), when only a limited amount of training data (auto‐calibration signals [ACS]) are available for accelerated standard 2D imaging.
Methods
In a first step, the RAKI model was tailored for the case of limited training data amount. In the iterative learning approach (termed iterative RAKI [iRAKI]), the tailored RAKI model is initially trained using original and augmented ACS obtained from a linear parallel imaging reconstruction. Subsequently, the RAKI convolution filters are refined iteratively using original and augmented ACS extracted from the previous RAKI reconstruction. Evaluation was carried out on 200 retrospectively undersampled in vivo datasets from the fastMRI neuro database with different contrast settings.
Results
For limited training data (18 and 22 ACS lines for R = 4 and R = 5, respectively), iRAKI outperforms standard RAKI by reducing residual artifacts and yields better noise suppression when compared to standard parallel imaging, underlined by quantitative reconstruction quality metrics. Additionally, iRAKI shows better performance than both GRAPPA and standard RAKI in case of pre‐scan calibration with varying contrast between training‐ and undersampled data.
Conclusion
RAKI benefits from the iterative learning approach, which preserves the noise suppression feature, but requires less original training data for the accurate reconstruction of standard 2D images thereby improving net acceleration.
A well-known result for the interference of two single-mode fields is that the degree of coherence and the degree of indistinguishability are the same when we consider the detection of a single photon. In this article, we present the relation between the degree of coherence, path indistinguishability and the fringe visibility considering interference of multiple numbers of single-mode fields while being interested in the detection of a single photon only. We will also mention how Born’s rule of interference for multiple sources is reflected in these results.
Peroxisomes are ubiquitous organelles with essential functions in numerous cellular processes such as lipid metabolism, detoxification of reactive oxygen species and signaling. Knowledge of the peroxisomal proteome including multi-localized proteins and, most importantly, changes of its composition induced by altering cellular conditions or impaired peroxisome biogenesis and function is of paramount importance for a holistic view on peroxisomes and their diverse functions in a cellular context. In this chapter, we provide a spatial proteomics protocol specifically tailored to the analysis of the peroxisomal proteome of baker's yeast that enables the definition of the peroxisomal proteome under distinct conditions and to monitor dynamic changes of the proteome including the relocation of individual proteins to a different cellular compartment. The protocol comprises subcellular fractionation by differential centrifugation followed by Nycodenz density gradient centrifugation of a crude peroxisomal fraction, quantitative mass spectrometric measurements of subcellular and density gradient fractions and advanced computational data analysis, resulting in the establishment of organellar maps on a global scale.
This thematic issue addresses the relationship between local self-governance and the state. Self-governance is understood as the rules that emerge in the local social and spatial context. Local self-governance of individual local groups, actors, communities, and their social and institutional arrangements are considered. From this situated collective entanglement, the interactions and relations with state authorities are analysed in the various contributions embedded in local contexts of different world regions and based on empirical social science research containing mostly interdisciplinary approaches. The nine case studies of this thematic issue reflect a variety of statehoods (weak to restrained), divers “intentionalities” of local self-governance (emancipatory and democratic, socio-economically, and socio-culturally oriented, security-driven or ecological), and their state-locality entanglements range between four forms of relationships: mutually supportive, conflictual, ambivalent, and avoiding.
In a modified inflation scenario we replace the “big bang” by a condensation event in an eternal all-compassing big ocean of free qubits in our modified cosmology. Interactions of qubits in the qubit ocean are rare. If they happen, they provide a nucleus for a new universe as the qubits become decoherent and freeze-out into defined bit ensembles. Second, we replace inflation by a crystallization event triggered by the nucleus of interacting qubits to which rapidly more and more qubits attach (like in everyday crystal growth) – the crystal unit cell guarantees same symmetries everywhere. Hence, the textbook inflation scenario to explain the same laws of nature in our domain is replaced by the crystal unit cell of the crystal formed. We give here only the perspective or outline of this modified inflation theory, as the detailed mathematical physics behind this has still to be formulated and described.
Interacting qubits solidify, quantum entropy decreases (but increases in the ocean around). The interacting qubits form a rapidly growing domain where the n**m states become separated ensemble states, rising long-range forces stop ultimately further growth. After that very early events, standard cosmology with the hot fireball model takes over. Our theory agrees well with lack of inflation traces in cosmic background measurements, but more importantly can explain well by such a type of cosmological crystallization instead of inflation the early creation of large-scale structure of voids and filaments, supercluster formation, galaxy formation, and the dominance of matter: no annihilation of antimatter necessary, rather the unit cell of our crystal universe has a matter handedness avoiding anti-matter.
We prove a triggering of qubit interactions can only be 1,2,4 or 8-dimensional (agrees with E8 symmetry of our universe). Repulsive forces at ultrashort distances result from quantization, long-range forces limit crystal growth. Crystals come and go in the qubit ocean. This selects for the ability to lay seeds for new crystals, for self-organization and life-friendliness.
The phase space of the crystal agrees with the standard model of the basic four forces for n quanta. It includes all possible ensemble combinations of their quantum states m, a total of n**m states. Neighbor states reach according to transition possibilities (S-matrix) with emergent time from entropic ensemble gradients. However, this means that in our four dimensions there is only one bit overlap to neighbor states left (almost solid, only below h dash liquidity left). However, the E8 symmetry of heterotic string theory has six rolled-up, small dimensions which help to keep the qubit crystal together and will never expand.
Finally, we give first energy estimates for free qubits vs bound qubits, misplacements in the qubit crystal and entropy increase during qubit decoherence / crystal formation. Scalar fields for color interaction and gravity derive from the permeating qubit-interaction field in the crystal. Hence, vacuum energy gets low inside the qubit crystal. Condensed mathematics may advantageously help to model free (many states denote the same qubit) and bound qubits in phase space.
The phase space for the standard model of the basic four forces for n quanta includes all possible ensemble combinations of their quantum states m, a total of n**m states. Neighbor states reach according to transition possibilities (S-matrix) with emergent time from entropic ensemble gradients.
We replace the “big bang” by a condensation event (interacting qubits become decoherent) and inflation by a crystallization event – the crystal unit cell guarantees same symmetries everywhere. Interacting qubits solidify and form a rapidly growing domain where the n**m states become separated ensemble states, rising long-range forces stop ultimately further growth. After that very early events, standard cosmology with the hot fireball model takes over. Our theory agrees well with lack of inflation traces in cosmic background measurements, large-scale structure of voids and filaments, supercluster formation, galaxy formation, dominance of matter and life-friendliness.
We prove qubit interactions to be 1,2,4 or 8 dimensional (agrees with E8 symmetry of our universe). Repulsive forces at ultrashort distances result from quantization, long-range forces limit crystal growth. Crystals come and go in the qubit ocean. This selects for the ability to lay seeds for new crystals, for self-organization and life-friendliness.
We give energy estimates for free qubits vs bound qubits, misplacements in the qubit crystal and entropy increase during qubit decoherence / crystal formation. Scalar fields for color interaction and gravity derive from the permeating qubit-interaction field. Hence, vacuum energy gets low only inside the qubit crystal. Condensed mathematics may advantageously model free / bound qubits in phase space.
Protein folding achieves a clear solution structure in a huge parameter space (the so-called protein folding problem). Proteins fold in water, and get by this a highly ordered structure. Finally, inside a protein crystal for structure resolution, you have everywhere the same symmetries as there is everywhere the same unit cell. We apply this to qubit interactions to do fundamental physics:
in a modified cosmology, we replace the big bang by a condensation event in an eternal all-encompassing ocean of free qubits. Interactions of qubits in the qubit ocean are quite rare but provide a nucleus or seed for a new universe (domain) as the qubits become decoherent and freeze-out into defined bit ensembles. Second, we replace inflation by a crystallization event triggered by the nucleus of interacting qubits to which rapidly more and more qubits attach (like in everyday crystal growth). The crystal unit cell guarantees same symmetries everywhere inside the crystal. The textbook inflation scenario to explain the same laws of nature in our domain is replaced by the unit cell of the crystal formed.
Interacting qubits solidify, quantum entropy decreases (but increases in the ocean around). In a modified inflation scenario, the interacting qubits form a rapidly growing domain where the n**m states become separated ensemble states, rising long-range forces stop ultimately further growth. Then standard cosmology with the hot fireball model takes over. Our theory agrees well with lack of inflation traces in cosmic background measurements. We explain by cosmological crystallization instead of inflation: early creation of large-scale structure of voids and filaments, supercluster formation, galaxy formation, and the dominance of matter: the unit cell of our crystal universe has a matter handedness avoiding anti-matter.
We prove initiation of qubit interactions can only be 1,2,4 or 8-dimensional (agrees with E8 symmetry of our universe). Repulsive forces at ultrashort distances result from quantization, long-range forces limit crystal growth. Crystals come and go in the qubit ocean. This selects for the ability to lay seeds for new crystals, for self-organization and life-friendliness.
The phase space of the crystal agrees with the standard model of the basic four forces for n quanta. It includes all possible ensemble combinations of their quantum states m, a total of n**m states. Neighbor states reach according to transition possibilities (S-matrix) with emergent time from entropic ensemble gradients. However, in our four dimensions there is only one bit overlap to neighbor states left (almost solid, only below Planck quantum there is liquidity left). The E8 symmetry of heterotic string theory has six curled-up, small dimensions which help to keep the qubit crystal together and will never expand.
Mathematics focusses on the Hurwitz proof applied to qubit interaction, a toy model of qubit interaction and repulsive forces of qubits. Vacuum energy gets appropriate low inside the crystal. We give first energy estimates for free qubits vs bound qubits, misplacements in the qubit crystal and entropy increase during qubit decoherence / crystal formation. Scalar fields for color interaction/confinement and gravity are derived from the qubit-interaction field.
Despite fine tuning voluntary movement as the most prominently studied function of the cerebellum, early human studies suggested cerebellar involvement emotion regulation. Since, the cerebellum has been associated with various mood and anxiety-related conditions. Research in animals provided evidence for cerebellar contributions to fear memory formation and extinction. Fear and anxiety can broadly be referred to as defensive states triggered by threat and characterized by multimodal adaptations such as behavioral and cardiac responses integrated into an intricately orchestrated defense reaction. This is mediated by an evolutionary conserved, highly interconnected network of defense-related structures with functional connections to the cerebellum. Projections from the deep cerebellar nucleus interpositus to the central amygdala interfere with retention of fear memory. Several studies uncovered tight functional connections between cerebellar deep nuclei and pyramis and the midbrain periaqueductal grey. Specifically, the fastigial nucleus sends direct projections to the ventrolateral PAG to mediate fear-evoked innate and learned freezing behavior. The cerebellum also regulates cardiovascular responses such as blood pressure and heart rate-effects dependent on connections with medullary cardiac regulatory structures. Because of the integrated, multimodal nature of defensive states, their adaptive regulation has to be highly dynamic to enable responding to a moving threatening stimulus. In this, predicting threat occurrence are crucial functions of calculating adequate responses. Based on its role in prediction error generation, its connectivity to limbic regions, and previous results on a role in fear learning, this review presents the cerebellum as a regulator of integrated cardio-behavioral defensive states.
Alveolar (AE) and cystic (CE) echinococcosis are two parasitic diseases caused by the tapeworms Echinococcus multilocularis and E. granulosus sensu lato (s. l.), respectively. Currently, AE and CE are mainly diagnosed by means of imaging techniques, serology, and clinical and epidemiological data. However, no viability markers that indicate parasite state during infection are available. Extracellular small RNAs (sRNAs) are short non-coding RNAs that can be secreted by cells through association with extracellular vesicles, proteins, or lipoproteins. Circulating sRNAs can show altered expression in pathological states; hence, they are intensively studied as biomarkers for several diseases. Here, we profiled the sRNA transcriptomes of AE and CE patients to identify novel biomarkers to aid in medical decisions when current diagnostic procedures are inconclusive. For this, endogenous and parasitic sRNAs were analyzed by sRNA sequencing in serum from disease negative, positive, and treated patients and patients harboring a non-parasitic lesion. Consequently, 20 differentially expressed sRNAs associated with AE, CE, and/or non-parasitic lesion were identified. Our results represent an in-depth characterization of the effect E. multilocularis and E. granulosus s. l. exert on the extracellular sRNA landscape in human infections and provide a set of novel candidate biomarkers for both AE and CE detection.
This thesis examines the electronic properties of two materials that promise the realization and observation of novel exotic quantum phenomena. For this purpose, angle-resolved photoemission forms the experimental basis for the investigation of the electronic properties. Furthermore, the magnetic order is investigated utilizing X-ray dichroism measurements.
First, the bulk and surface electronic structure of epitaxially grown HgTe in its three-dimensional topological insulator phase is investigated. In this study, synchrotron radiation is used to address the three-dimensional band structure and orbital composition of the bulk states by employing photon-energy-dependent and polarization-dependent measurements, respectively. In addition, the topological surface state is examined on in situ grown samples using a laboratory photon source. The resulting data provide a means to experimentally localize the bulk band inversion in momentum space and to evidence the momentum-dependent change in the orbital character of the inverted bulk states.
Furthermore, a rather new series of van der Waals compounds, (MnBi\(_2\)Te\(_4\))(Bi\(_2\)Te\(_3\))\(_n\), is investigated. First, the magnetic properties of the first two members of the series, MnBi\(_2\)Te\(_4\) and MnBi\(_4\)Te\(_7\), are studied via X-ray absorption-based techniques. The topological surface state on the two terminations of MnBi\(_4\)Te\(_7\) is analyzed using circular dichroic, photon-energy-dependent, and spin-resolved photoemission. The topological state on the (MnBi\(_2\)Te\(_4\))-layer termination shows a free-standing Dirac cone with its Dirac point located in the bulk band gap. In contrast, on the (Bi\(_2\)Te\(_3\))-layer termination the surface state hybridizes with the bulk valences states, forming a spectral weight gap, and exhibits a Dirac point that is buried within the bulk continuum. Lastly, the lack of unambiguous evidence in the literature showing a temperature-dependent mass gap opening in these magnetic topological insulators is discussed through MnBi\(_2\)Te\(_4\).
Introduction
In spinal surgery, precise instrumentation is essential. This study aims to evaluate the accuracy of navigated, O-arm-controlled screw positioning in thoracic and lumbar spine instabilities.
Materials and methods
Posterior instrumentation procedures between 2010 and 2015 were retrospectively analyzed. Pedicle screws were placed using 3D rotational fluoroscopy and neuronavigation. Accuracy of screw placement was assessed using a 6-grade scoring system. In addition, screw length was analyzed in relation to the vertebral body diameter. Intra- and postoperative revision rates were recorded.
Results
Thoracic and lumbar spine surgery was performed in 285 patients. Of 1704 pedicle screws, 1621 (95.1%) showed excellent positioning in 3D rotational fluoroscopy imaging. The lateral rim of either pedicle or vertebral body was protruded in 25 (1.5%) and 28 screws (1.6%), while the midline of the vertebral body was crossed in 8 screws (0.5%). Furthermore, 11 screws each (0.6%) fulfilled the criteria of full lateral and medial displacement. The median relative screw length was 92.6%. Intraoperative revision resulted in excellent positioning in 58 of 71 screws. Follow-up surgery due to missed primary malposition had to be performed for two screws in the same patient. Postsurgical symptom relief was reported in 82.1% of patients, whereas neurological deterioration occurred in 8.9% of cases with neurological follow-up.
Conclusions
Combination of neuronavigation and 3D rotational fluoroscopy control ensures excellent accuracy in pedicle screw positioning. As misplaced screws can be detected reliably and revised intraoperatively, repeated surgery for screw malposition is rarely required.
Grading, immunohistochemistry and c-kit mutation status are criteria for assessing the prognosis and therapeutic options of canine cutaneous mast cell tumours (MCTs). As a subset, canine digital MCTs have rarely been explored in this context. Therefore, in this retrospective study, 68 paraffin-embedded canine digital MCTs were analysed, and histological grading was assessed according to Patnaik and Kiupel. The immunohistochemical markers KIT and Ki67 were used, as well as polymerase chain reaction (PCR) for mutational screening in c-kit exons 8, 9, 11 and 14. Patnaik grading resulted in 22.1% grade I, 67.6% grade II and 10.3% grade III tumours. Some 86.8% of the digital MCTs were Kiupel low-grade. Aberrant KIT staining patterns II and III were found in 58.8%, and a count of more than 23 Ki67-positive cells in 52.3% of the cases. Both parameters were significantly associated with an internal tandem duplication (ITD) in c-kit exon 11 (12.7%). French Bulldogs, which tend to form well-differentiated cutaneous MCTs, had a higher proportion of digital high-grade MCTs and ITD in c-kit exon 11 compared with mongrels. Due to its retrospective nature, this study did not allow for an analysis of survival data. Nevertheless, it may contribute to the targeted characterisation of digital MCTs.
Summary
Platelet activation and aggregation at sites of vascular injury is critical to prevent excessive blood loss, but may also lead to life-threatening ischemic disease states, such as myocardial infarction and stroke. Glycoprotein (GP) VI and C type lectin-like receptor 2 (CLEC-2) are essential platelet activating receptors in hemostasis and thrombo-inflammatory disease which signal through a (hem)immunoreceptor tyrosine-based activation motif (ITAM)-dependent pathway. The adapter molecules Src-like adapter protein (SLAP) and SLAP2 are involved in the regulation of immune cell receptor surface expression and signaling, but their function in platelets is unknown. As revealed in this thesis, single deficiency of SLAP or SLAP2 in mice had only moderate effects on platelet function, while SLAP/SLAP2 double deficiency resulted in markedly increased signal transduction, integrin activation, granule release, aggregation, procoagulant activity and thrombin generation following (hem)ITAM-coupled, but not G protein-coupled receptor activation. Slap-/-/Slap2-/- mice displayed accelerated occlusive arterial thrombus formation and a dramatically worsened outcome after focal cerebral ischemia. These results establish SLAP and SLAP2 as critical inhibitors of platelet (hem)ITAM signaling in the setting of arterial thrombosis and ischemic stroke.
GPVI has emerged as a promising novel pharmacological target for treatment of thrombotic and inflammatory disease states, but the exact mechanisms of its immunodepletion in vivo are incompletely understood. It was hypothesized that SLAP and SLAP2 may be involved in the control of GPVI down-regulation because of their role in the internalization of immune cell receptors. As demonstrated in the second part of the thesis, SLAP and SLAP2 were dispensable for antibody-induced GPVI down-regulation, but anti-GPVI treatment resulted in prolonged strong thrombocytopenia in Slap-/-/Slap2-/- mice. The profound thrombocytopenia likely resulted from the powerful platelet activation which the anti-GPVI antibody induced in Slap-/-/Slap2-/- platelets, but importantly, not in wild-type platelets. These data indicate that the expression and activation state of key modulators of the GPVI signaling cascade may have important implications for the safety profile and efficacy of anti-GPVI agents.
Small GTPases of the Rho family, such as RhoA and Cdc42, are critically involved in the regulation of cytoskeletal rearrangements during platelet activation, but little is known about the specific roles and functional redundancy of both proteins in platelet biogenesis. As shown in the final part of the thesis, combined deficiency of RhoA and Cdc42 led to marked alterations in megakaryocyte morphology and the generation of platelets of heterogeneous size and granule content. Despite severe hemostatic defects and profound thrombo¬cytopenia, circulating RhoA-/-/Cdc42-/- platelets were still capable of granule secretion and the formation of occlusive thrombi. These results implicate the existence of both distinct and overlapping roles of RhoA and Cdc42 in platelet production and function.