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Schriftenreihe
Sonstige beteiligte Institutionen
- IZKF Nachwuchsgruppe Geweberegeneration für muskuloskelettale Erkrankungen (5)
- Bernhard-Heine-Centrum für Bewegungsforschung (4)
- Zentraleinheit Klinische Massenspektrometrie (3)
- Fraunhofer-Institut für Silicatforschung ISC (2)
- Helmholtz Institute for RNA-based Infection Research (HIRI) (2)
- Krankenhaushygiene und Antimicrobial Stewardship (Universitätsklinikum) (2)
- Wilhelm-Conrad-Röntgen-Forschungszentrum für komplexe Materialsysteme (2)
- ALPARC - The Alpine Network of Protected Areas (1)
- Albert-Ludwigs-Universität Freiburg (1)
- Arizona State University, Tempe, Arizona, USA (1)
Boric acid (BA) has been used as a transparent glass matrix for optical materials for over 100 years. However, recently, apparent room-temperature phosphorescence (RTP) from BA (crystalline and powder states) was reported (Zheng et al., Angew. Chem. Int. Ed. 2021, 60, 9500) when irradiated at 280 nm under ambient conditions. We suspected that RTP from their BA sample was induced by an unidentified impurity. Our experimental results show that pure BA synthesized from B(OMe)\(_{3}\) does not luminesce in the solid state when irradiated at 250–400 nm, while commercial BA indeed (faintly) luminesces. Our theoretical calculations show that neither individual BA molecules nor aggregates would absorb light at >175 nm, and we observe no absorption of solid pure BA experimentally at >200 nm. Therefore, it is not possible for pure BA to be excited at >250 nm even in the solid state. Thus, pure BA does not display RTP, whereas trace impurities can induce RTP.
Neuromelanin granules (NMGs) are organelle-like structures present in the human substantia nigra pars compacta. In addition to neuromelanin, NMGs contain proteins, lipids and metals. As NMG-containing dopaminergic neurons are preferentially lost in Parkinson’s disease and dementia with Lewy bodies (DLB), it is assumed that NMGs may play a role in neurodegenerative processes. Until now, this role is not completely understood and needs further investigation. We therefore set up an exploratory proteomic study to identify differences in the proteomic profile of NMGs from DLB patients (n = 5) compared to healthy controls (CTRL, n = 5). We applied a laser microdissection and mass-spectrometry-based approach, in which we used targeted mass spectrometric experiments for validation. In NMG-surrounding (SN\(_{Surr.}\)) tissue of DLB patients, we found evidence for ongoing oxidative damage and an impairment of protein degradation. As a potentially disease-related mechanism, we found α-synuclein and protein S100A9 to be enriched in NMGs of DLB cases, while the abundance of several ribosomal proteins was significantly decreased. As S100A9 is known to be able to enhance the formation of toxic α-synuclein fibrils, this finding points towards an involvement of NMGs in pathogenesis, however the exact role of NMGs as either neuroprotective or neurotoxic needs to be further investigated. Nevertheless, our study provides evidence for an impairment of protein degradation, ongoing oxidative damage and accumulation of potentially neurotoxic protein aggregates to be central mechanisms of neurodegeneration in DLB.
Breast cancer etiology is associated with both proliferation and DNA damage induced by estrogens. Breast cancer risk factors (BCRF) such as body mass index (BMI), smoking, and intake of estrogen-active drugs were recently shown to influence intratissue estrogen levels. Thus, the aim of the present study was to investigate the influence of BCRF on estrogen-induced proliferation and DNA damage in 41 well-characterized breast glandular tissues derived from women without breast cancer. Influence of intramammary estrogen levels and BCRF on estrogen receptor (ESR) activation, ESR-related proliferation (indicated by levels of marker transcripts), oxidative stress (indicated by levels of GCLC transcript and oxidative derivatives of cholesterol), and levels of transcripts encoding enzymes involved in estrogen biotransformation was identified by multiple linear regression models. Metabolic fluxes to adducts of estrogens with DNA (E-DNA) were assessed by a metabolic network model (MNM) which was validated by comparison of calculated fluxes with data on methoxylated and glucuronidated estrogens determined by GC- and UHPLC-MS/MS. Intratissue estrogen levels significantly influenced ESR activation and fluxes to E-DNA within the MNM. Likewise, all BCRF directly and/or indirectly influenced ESR activation, proliferation, and key flux constraints influencing E-DNA (i.e., levels of estrogens, CYP1B1, SULT1A1, SULT1A2, and GSTP1). However, no unambiguous total effect of BCRF on proliferation became apparent. Furthermore, BMI was the only BCRF to indeed influence fluxes to E-DNA (via congruent adverse influence on levels of estrogens, CYP1B1 and SULT1A2).
The host defense derived peptide was assessed in different model systems with increasing complexity employing the highly aggressive NRAS mutated melanoma metastases cell line MUG-Mel2. Amongst others, fluorescence microscopy and spectroscopy, as well as cell death studies were applied for liposomal, 2D and 3D in vitro models including tumor spheroids without or within skin models and in vivo mouse xenografts. Summarized, MUG-Mel2 cells were shown to significantly expose the negatively charged lipid phosphatidylserine on their plasma membranes, showing they are successfully targeted by RDP22. The peptide was able to induce cell death in MUG-Mel2 2D and 3D cultures, where it was able to kill tumor cells even inside the core of tumor spheroids or inside a melanoma organotypic model. In vitro studies indicated cell death by apoptosis upon peptide treatment with an LC\(_{50}\) of 8.5 µM and seven-fold specificity for the melanoma cell line MUG-Mel2 over normal dermal fibroblasts. In vivo studies in mice xenografts revealed effective tumor regression upon intratumoral peptide injection, indicated by the strong clearance of pigmented tumor cells and tremendous reduction in tumor size and proliferation, which was determined histologically. The peptide RDP22 has clearly shown high potential against the melanoma cell line MUG-Mel2 in vitro and in vivo.
We present the optical characterization of GaAs-based InAs quantum dots (QDs) grown by molecular beam epitaxy on a digitally alloyed InGaAs metamorphic buffer layer (MBL) with gradual composition ensuring a redshift of the QD emission up to the second telecom window. Based on the photoluminescence (PL) measurements and numerical calculations, we analyzed the factors influencing the energies of optical transitions in QDs, among which the QD height seems to be dominating. In addition, polarization anisotropy of the QD emission was observed, which is a fingerprint of significant valence states mixing enhanced by the QD confinement potential asymmetry, driven by the decreased strain with increasing In content in the MBL. The barrier-related transitions were probed by photoreflectance, which combined with photoluminescence data and the PL temperature dependence, allowed for the determination of the carrier activation energies and the main channels of carrier loss, identified as the carrier escape to the MBL barrier. Eventually, the zero-dimensional character of the emission was confirmed by detecting the photoluminescence from single QDs with identified features of the confined neutral exciton and biexciton complexes via the excitation power and polarization dependences.
DNA damage occurs frequently during normal cellular progresses or by environmental factors. To preserve the genome integrity, DNA damage response (DDR) has evolved to repair DNA and the non-properly repaired DNA induces human diseases like immune deficiency and cancer. Since a large number of proteins involved in DDR are enzymes of ubiquitin system, it is critical to investigate how the ubiquitin system regulates cellular response to DNA damage. Hereby, we reveal a novel mechanism for DDR regulation via activation of SCF ubiquitin ligase upon DNA damage.
As an essential step for DNA damage-induced inhibition of DNA replication, Cdc25A degradation by the E3 ligase β-TrCP upon DNA damage requires the deubiquitinase Usp28. Usp28 deubiquitinates β-TrCP in response to DNA damage, thereby promotes its dimerization, which is required for its activity in substrate ubiquitination and degradation. Particularly, ubiquitination at a specific lysine on β-TrCP suppresses dimerization.
The key mediator protein of DDR, 53BP1, forms oligomers and associates with β-TrCP to inhibit its activity in unstressed cells. Upon DNA damage, 53BP1 is degraded in the nucleoplasm, which requires oligomerization and is promoted by Usp28 in a β-TrCP-dependent manner. Consequently, 53BP1 destruction releases and activates β-TrCP during DNA damage response.
Moreover, 53BP1 deletion and DNA damage promote β-TrCP dimerization and recruitment to chromatin sites that locate in the vicinity of putative replication origins. Subsequently, the chromatin-associated Cdc25A is degraded by β-TrCP at the origins. The stimulation of β-TrCP binding to the origins upon DNA damage is accompanied by unloading of Cdc45, a crucial component of pre-initiation complexes for replication. Loading of Cdc45 to origins is a key Cdk2-dependent step for DNA replication initiation, indicating that localized Cdc25A degradation by β-TrCP at origins inactivates Cdk2, thereby inhibits the initiation of DNA replication.
Collectively, this study suggests a novel mechanism for the regulation of DNA replication upon DNA damage, which involves 53BP1- and Usp28-dependent activation of the SCF(β-TrCP) ligase in Cdc25A degradation.
“I tried to control my emotions”: nursing home care workers’ experiences of emotional labor in China
(2022)
Despite dramatic expansions in the Chinese nursing home sector in meeting the increasing care needs of a rapidly aging population, direct care work in China remains largely devalued and socially unrecognized. Consequently, scant attention has been given to the caregiving experiences of direct care workers (DCWs) in Chinese nursing homes. In particular, given the relational nature of care work, there is little knowledge as to how Chinese DCWs manage emotions and inner feelings through their emotional labor. This article examines the emotional labor of Chinese DCWs through ethnographic data collected with 20 DCWs in one nursing home located in an urban setting in central China. Data were analyzed using conventional content analysis and constant comparison. Participants’ accounts of sustaining a caring self, preserving professional identity, and hoping for reciprocity revealed implicit meanings about the often-conflicting nature of emotional labor and the nonreciprocal elements of care work under constrained working conditions. Importantly, the moral-cultural notion of bao (报 norm of reciprocity) was found to be central among DCWs in navigating strained resources and suggested their agency in meaning-construction. However, their constructed moral buffers may be insufficient if emotional labor continues to be made invisible by care organizations.
Optogenetics became successful in neuroscience with Channelrhodopsin-2 (ChR2), a light-gated cation channel from the green alga Chlamydomonas reinhardtii, as an easy applicable tool. The success of ChR2 inspired the development of various photosensory proteins as powerful actuators for optogenetic manipulation of biological activity. However, the current optogenetic toolbox is still not perfect and further improvements are desirable. In my thesis, I engineered and characterized several different optogenetic tools with new features.
(i) Although ChR2 is the most often used optogenetic actuator, its single-channel conductance and its Ca2+ permeability are relatively low. ChR2 variants with increased Ca2+ conductance were described recently but a further increase seemed possible. In addition, the H+ conductance of ChR2 may lead to cellular acidification and unintended pH-related side effects upon prolonged illumination. Through rational design, I developed several improved ChR2 variants with larger photocurrent, higher cation selectivity, and lower H+ conductance.
(ii) The light-activated inward chloride pump NpHR is a widely used optogenetic tool for neural silencing. However, pronounced inactivation upon long time illumination constrains its application for long-lasting neural inhibition. I found that the deprotonation of the Schiff base underlies the inactivation of NpHR. Through systematically exploring optimized illumination schemes, I found illumination with blue light alone could profoundly increase the temporal stability of the NpHR-mediated photocurrent. A combination of green and violet light eliminates the inactivation effect, similar to blue light, but leading to a higher photocurrent and therefore better light-induced inhibition.
(iii) Photoactivated adenylyl cyclases (PACs) were shown to be useful for light-manipulation of cellular cAMP levels. I developed a convenient in-vitro assay for soluble PACs that allows their reliable characterization. Comparison of different PACs revealed that bPAC from Beggiatoa is the best optogenetic tool for cAMP manipulation, due to its high efficiency and small size. However, a residual activity of bPAC in the dark is unwanted and the cytosolic localization prevents subcellular precise cAMP manipulation. I therefore introduced point mutations into bPAC to reduce its dark activity. Interestingly, I found that membrane targeting of bPAC with different linkers can remarkably alter its activity, in addition to its localization. Taken together, a set of PACs with different activity and subcellular localization were engineered for selection based on the intended usage. The membrane-bound PM-bPAC 2.0 with reduced dark activity is well-tolerated by hippocampal neurons and reliably evokes a transient photocurrent, when co-expression with a CNG channel.
(iv) Bidirectional manipulation of cell activity with light of different wavelengths is of great importance in dissecting neural networks in the brain. Selection of optimal tool pairs is the first and most important step for dual-color optogenetics. Through N- and C-terminal modifications, an improved ChR variant (i.e. vf-Chrimson 2.0) was engineered and selected as the red light-controlled actuator for excitation. Detailed comparison of three two-component potassium channels, composed of bPAC and the cAMP-activated potassium channel SthK, revealed the superior properties of SthK-bP. Combining vf-Chrimson 2.0 and improved SthK-bP “SthK(TV418)-bP” could reliably induce depolarization by red light and hyperpolarization by blue light. A residual tiny crosstalk between vf-Chrimson 2.0 and SthK(TV418)-bP, when applying blue light, can be minimized to a negligible level by applying light pulses or simply lowering the blue
light intensity.
Coal mining, an important human activity, disturbs soil organic carbon (SOC) accumulation and decomposition, eventually affecting terrestrial carbon cycling and the sustainability of human society. However, changes of SOC content and their relation with influential factors in coal mining areas remained unclear. In the study, predictive models of SOC content were developed based on field sampling and Landsat images for different land-use types (grassland, forest, farmland, and bare land) of the largest coal mining area in China (i.e., Shendong). The established models were employed to estimate SOC content across the Shendong mining area during 1990–2020, followed by an investigation into the impacts of climate change and human disturbance on SOC content by a Geo-detector. Results showed that the models produced satisfactory results (R\(^2\) > 0.69, p < 0.05), demonstrating that SOC content over a large coal mining area can be effectively assessed using remote sensing techniques. Results revealed that average SOC content in the study area rose from 5.67 gC·kg\(^{−1}\) in 1990 to 9.23 gC·kg\(^{−1}\) in 2010 and then declined to 5.31 gC·Kg\(^{−1}\) in 2020. This could be attributed to the interaction between the disturbance of soil caused by coal mining and the improvement of eco-environment by land reclamation. Spatially, the SOC content of farmland was the highest, followed by grassland, and that of bare land was the lowest. SOC accumulation was inhibited by coal mining activities, with the effect of high-intensity mining being lower than that of moderate- and low-intensity mining activities. Land use was found to be the strongest individual influencing factor for SOC content changes, while the interaction between vegetation coverage and precipitation exerted the most significant influence on the variability of SOC content. Furthermore, the influence of mining intensity combined with precipitation was 10 times higher than that of mining intensity alone.
Interleukin 2 (IL-2) was the first cytokine applied for cancer treatment in human history. It has been approved as monotherapy for renal cell carcinoma and melanoma by the FDA and does mediate the regression of the tumors in patients. One of the possible mechanisms is that the administration of IL-2 led to T lymphocytes expansion, including CD4+ and CD8+ T cells. In addition, a recent study demonstrated that antigen-specific T cells could also be expanded through the induction of IL-2, which plays a crucial role in mediating tumor regression. However, despite the long-term and extensive use of IL-2 in the clinic, the ratio of patients who get a complete response was still low, and only about one-fifth of patients showed objective tumor regression. Therefore, the function of IL-2 in cancer treatment should continue to be optimized and investigated. A study by Franz O. Smith et al. has shown that the combination treatment of IL-2 and tumor-associated antigen vaccine has a strong trend to increased objective responses compared to patients with melanoma receiving IL-2 alone. Peptide vaccines are anti-cancer vaccines able to induce a powerful tumor antigenspecific immune response capable of eradicating the tumors. According to the type of antigens, peptide vaccines can be classified into two distinct categories: Tumor-associated antigens (TAA) vaccine and tumor-specific neoantigens (TSA) vaccine. Currently, Peptide vaccines are mainly investigated in phase I and phase II clinical trials of human cancer patients with various advanced cancers such as lung cancer, gastrointestinal tumors, and breast cancers. Vaccinia virus (VACV) is one of the safest viral vectors, which has been wildly used in cancer treatment and pathogen prevention. As an oncolytic vector, VACV can carry multiple large foreign genes, which enable the virus to introduce diagnostic and therapeutic agents without dramatically reducing the viral replication. Meanwhile, the recombinant vaccinia virus (rVACV) can be easily generated by homologous recombination. Here, we used the vaccinia virus as the therapeutic cancer vector, expressing mouse Interleukin 2 (IL-2) and tumor-associated antigens simultaneously to investigate the combined effect of anti-tumor immune response in the 4T1 mouse tumor model. As expected, the VACV driven mIL-2 expression remarkably increased both CD4+ and CD8+ populations in vivo, and the virus-expressed tumor-associated peptides successfully elicited theantigen-specific T cell response to inhibit the growth of tumors. Furthermore, the experiments with tumor-bearing animals showed that the mIL-2 plus tumor antigens expressing VACV vector gave a better anti-cancer response than the mIL-2 alone expressing vector. The combinations did significantly more inhibit tumor growth than mIL-2 treatment alone. Moreover, the results confirmed our previous unpublished data that the mIL-2 expression driven by synthetic early/late promoter in the Lister strain VACV could enhance the tumor regression in the 4T1 mouse model.
Thermoplastic polymers have a history of decades of safe and effective use in the clinic as implantable medical devices. In recent years additive manufacturing (AM) saw increased clinical interest for the fabrication of customizable and implantable medical devices and training models using the patients’ own radiological data. However, approval from the various regulatory bodies remains a significant hurdle. A possible solution is to fabricate the AM scaffolds using materials and techniques with a clinical safety record, e.g. melt processing of polymers. Melt Electrowriting (MEW) is a novel, high resolution AM technique which uses thermoplastic polymers. MEW produces scaffolds with microscale fibers and precise fiber placement, allowing the control of the scaffold microarchitecture. Additionally, MEW can process medical-grade thermoplastic polymers, without the use of solvents paving the way for the production of medical devices for clinical applications. This pathway is investigated in this thesis, where the layout is designed to resemble the journey of a medical device produced via MEW from conception to early in vivo experiments. To do so, first, a brief history of the development of medical implants and the regenerative capability of the human body is given in Chapter 1. In Chapter 2, a review of the use of thermoplastic polymers in medicine, with a focus on poly(ε-caprolactone) (PCL), is illustrated, as this is the polymer used in the rest of the thesis. This review is followed by a comparison of the state of the art, regarding in vivo and clinical experiments, of three polymer melt AM technologies: melt-extrusion, selective laser sintering and MEW. The first two techniques already saw successful translation to the bedside, producing patient-specific, regulatory-approved AM implants. To follow in the footsteps of these two technologies, the MEW device parameters need to be optimized. The MEW process parameters and their interplay are further discussed in Chapter 3 focusing on the importance of a steady mass flow rate of the polymer during printing. MEW reaches a balance between polymer flow, the stabilizing electric field and moving collector to produce reproducible, high-resolution scaffolds. An imbalance creates phenomena like fiber pulsing or arcing which result in defective scaffolds and potential printer damage. Chapter 4 shows the use of X-ray microtomography (µCT) as a non-destructive method to characterize the pore-related features: total porosity and the pore size distribution. MEW scaffolds are three-dimensional (3D) constructs but have long been treated in the literature as two-dimensional (2D) ones and characterized mainly by microscopy, including stereo- and scanning electron microscopy, where pore size was simply reported as the distance between the fibers in a single layer. These methods, together with the trend of producing scaffolds with symmetrical pores in the 0/90° and 0/60/120° laydown patterns, disregarded the lateral connections between pores and the potential of MEW to be used for more complex 3D structures, mimicking the extracellular matrix. Here we characterized scaffolds in the aforementioned symmetrical laydown patterns, along with the more complex 0/45/90/135° and 0/30/60/90/120/150° ones. A 2D pore size estimation was done first using stereomicroscopy, followed by and compared to µCT scanning. The scaffolds with symmetrical laydown patterns resulted in the predominance of one pore size, while those with more complex patterns had a broader distribution, which could be better shown by µCT scans. Moreover, in the symmetrical scaffolds, the size of 3D pores was not able to reach the value of the fiber spacing due to a flattening effect of the scaffold, where the thickness of the scaffold was less than the fiber spacing, further restricting the pore size distribution in such scaffolds. This method could be used for quality assurance of fabricated scaffolds prior to use in in vitro or in vivo experiments and would be important for a clinical translation. Chapter 5 illustrates a proof of principle subcutaneous implantation in vivo experiment. MEW scaffolds were already featured in small animal in vivo experiments, but to date, no analysis of the foreign body reaction (FBR) to such implants was performed. FBR is an immune reaction to implanted foreign materials, including medical devices, aimed at protecting the host from potential adverse effects and can interfere with the function of some medical implants. Medical-grade PCL was used to melt electrowrite scaffolds with 50 and 60 µm fiber spacing for the 0/90° and 0/60/120° laydown patterns, respectively. These implants were implanted subcutaneously in immunocompetent, outbred mice, with appropriate controls, and explanted after 2, 4, 7 and 14 days. A thorough characterization of the scaffolds before implantation was done, followed by a full histopathological analysis of the FBR to the implants after excision. The scaffolds, irrespective of their pore geometry, induced an extensive FBR in the form of accumulation of foreign body giant cells around the fiber walls, in a manner that almost occluded available pore spaces with little to no neovascularization. This reaction was not induced by the material itself, as the same reaction failed to develop in the PCL solid film controls. A discussion of the results was given with special regard to the literature available on flat surgical meshes, as well as other hydrogel-based porous scaffolds with similar pore sizes. Finally, a general summary of the thesis in Chapter 6 recapitulates the most important points with a focus on future directions for MEW.
Fibroblast growth factor-inducible 14 (Fn14) is a member of the tumor necrosis factor (TNF) receptor superfamily (TNFRSF) and is activated by its ligand TNF-like weak inducer of apoptosis (TWEAK). The latter occurs as a homotrimeric molecule in a soluble and a membrane-bound form. Soluble TWEAK (sTWEAK) activates the weakly inflammatory alternative NF-κB pathway and sensitizes for TNF-induced cell death while membrane TWEAK (memTWEAK) triggers additionally robust activation of the classical NF-κB pathway and various MAP kinase cascades. Fn14 expression is limited in adult organisms but becomes strongly induced in non-hematopoietic cells by a variety of growth factors, cytokines and physical stressors (e.g., hypoxia, irradiation). Since all these Fn14-inducing factors are frequently also present in the tumor microenvironment, Fn14 is regularly found to be expressed by non-hematopoietic cells of the tumor microenvironment and most solid tumor cells. In general, there are three possibilities how the tumor-Fn14 linkage could be taken into consideration for tumor therapy. First, by exploitation of the cancer associated expression of Fn14 to direct cytotoxic activities (antibody-dependent cell-mediated cytotoxicity (ADCC), cytotoxic payloads, CAR T-cells) to the tumor, second by blockade of potential protumoral activities of the TWEAK/Fn14 system, and third, by stimulation of Fn14 which not only triggers proinflammtory activities but also sensitizes cells for apoptotic and necroptotic cell death. Based on a brief description of the biology of the TWEAK/Fn14 system and Fn14 signaling, we discuss the features of the most relevant Fn14-targeting biologicals and review the preclinical data obtained with these reagents. In particular, we address problems and limitations which became evident in the preclinical studies with Fn14-targeting biologicals and debate possibilities how they could be overcome.
The subclassification of diffuse large B-cell lymphoma (DLBCL) into germinal center B-cell-like (GCB) and activated B-cell-like (ABC) subtypes has become mandatory in the 2017 update of the WHO classification of lymphoid neoplasms and will continue to be used in the WHO 5\(^{th}\) edition. The RNA-based Lymph2Cx assay has been validated as a reliable surrogate of high-throughput gene expression profiling assays for distinguishing between GCB and ABC DLBCL and provides reliable results from formalin-fixed, paraffin-embedded (FFPE) material. This test has been previously used in clinical trials, but experience from real-world routine application is rare. We routinely applied the Lymph2Cx assay to day-to-day diagnostics on a series of 147 aggressive B-cell lymphoma cases and correlated our results with the immunohistochemical subclassification using the Hans algorithm and fluorescence in situ hybridization findings using break-apart probes for MYC, BCL2, and BCL6. The routine use of the Lymph2Cx assay had a high technical success rate (94.6%) with a low rate of failure due to poor material and/or RNA quality. The Lymph2Cx assay was discordant with the Hans algorithm in 18% (23 of 128 cases). Discordant cases were mainly classified as GCB by the Hans algorithm and as ABC by Lymph2Cx (n = 11, 8.6%). Only 5 cases (3.9%) were classified as non-GCB by the Hans algorithm and as GCB by Lymph2Cx. Additionally, 5.5% of cases (n = 7) were left unclassified by Lymph2Cx, whereas they were defined as GCB (n = 4) or non-GCB (n = 3) by the Hans algorithm. Our data support the routine applicability of the Lymph2Cx assay.
The 1‐methyl‐3‐(tricyanoborane)imidazolin‐2‐ylidenate anion (2) was obtained in high yield by deprotonation of the B(CN)3‐methylimidazole adduct 1. Regarding charge and stereo‐electronic properties, anion 2 closes the gap between well‐known neutral NHCs and the ditopic dianionic NHC, the 1,3‐bis(tricyanoborane)imidazolin‐2‐ylidenate dianion (IIb). The influence of the number of N‐bonded tricyanoborane moieties on the σ‐donating and π‐accepting properties of NHCs was assessed by quantum chemical calculations and verified by experimental data on 2, IIb, and 1,3‐dimethylimidazolin‐2‐ylidene (IMe, IIa). Therefore NHC 2, which acts as a ditopic ligand via the carbene center and the cyano groups, was reacted with alkyl iodides, selenium, and [Ni(CO)\(_{4}\)] yielding alkylated imidazoles 3 and 4, the anionic selenium adduct 5, and the anionic nickel tricarbonyl complex 8, respectively. The results of this study prove that charge, number of coordination sites, buried volume (%V\(_{bur}\)) and σ‐donor and π‐acceptor abilities of NHCs can be effectively fine‐tuned via the number of tricyanoborane substituents.
Background
Dystrophinopathies caused by variants in the DMD gene are a well‐studied muscle disease. The most common type of variant in DMD are large deletions. Very rarely reported forms of variants are chromosomal translocations, inversions and deep intronic variants (DIVs) because they are not detectable by standard diagnostic techniques (sequencing of coding sequence, copy number variant detection). This might be the reason that some clinically and histologically proven dystrophinopathy cases remain unsolved.
Methods
We used whole genome sequencing (WGS) to screen the entire DMD gene for variants in one of two brothers suffering from typical muscular dystrophy with strongly elevated creatine kinase levels.
Results
Although a pathogenic DIV could not be detected, we were able to identify a pericentric inversion with breakpoints in DMD intron 44 and Xq13.3, which could be confirmed by Sanger sequencing in the index as well as in his brother and mother. As this variation affects a major part of DMD it is most likely disease causing.
Conclusion
Our findings elucidate that WGS is capable of detecting large structural rearrangements and might be suitable for the genetic diagnostics of dystrophinopathies in the future. In particular, inversions might be a more frequent cause for dystrophinopathies as anticipated and should be considered in genetically unsolved dystrophinopathy cases.
Herein, we report the facile synthesis of a three-dimensional (3D) inorganic analogue of 9,10-diazido-9,10-dihydrodiboraantracene, which turned out to be a monomer in both the solid and solution state, and thermally stable up to 230 °C, representing a rare example of azido borane with boosted Lewis acidity and stability in one. Apart from the classical acid-base and Staudinger reactions, E−H bond activation (E=B, Si, Ge) was investigated. While the reaction with B−H (9-borabicyclo[3.3.1]nonane) led directly to the 1,1-addition on N\(_{α}\) upon N\(_{2}\) elimination, the Si−H (Et\(_{3}\)SiH, PhMe\(_{2}\)SiH) activation proceeded stepwise via 1,2-addition, with the key intermediates 5\(_{int}\) and 6\(_{int}\) being isolated and characterized. In contrast, the cooperative Ge−H was reversible and stayed at the 1,2-addition step.
Herein, the copper-catalyzed borylation of readily available acyl chlorides with bis(pinacolato)diboron, (B\(_{2}\)pin\(_{2}\)) or bis(neopentane glycolato)diboron (B\(_{2}\)neop\(_{2}\)) is reported, which provides stable potassium acyltrifluoroborates (KATs) in good yields from the acylboronate esters. A variety of functional groups are tolerated under the mild reaction conditions (room temperature) and substrates containing different carbon-skeletons, such as aryl, heteroaryl and primary, secondary, tertiary alkyl are applicable. Acyl N-methyliminodiacetic acid (MIDA) boronates can also been accessed by modification of the workup procedures. This process is scalable and also amenable to the late-stage conversion of carboxylic acid-containing drugs into their acylboron analogues, which have been challenging to prepare previously. A catalytic mechanism is proposed based on in situ monitoring of the reaction between p-toluoyl chloride and an NHC-copper(I) boryl complex as well as the isolation of an unusual lithium acylBpinOBpin compound as a key intermediate.
The multi-agent therapy “VDT-PACE” represents an established regimen in relapsed/refractory multiple myeloma (RRMM). Here, we report on our experience with a “modified VDT-PACE” incorporating new generation anti-MM agents daratumumab and carfilzomib (“Dara-KDT-P(A)CE”). We retrospectively analyzed 38 patients with RRMM treated with “Dara-KDT-P(A)CE”. The median age was 62 (range 45–82) years, and the patients were heavily pretreated with a median of 5 (range 2–12) prior lines of therapy. Twenty-one (55%) patients suffered from penta-refractory MM. High-risk cytogenetics was present in 31 (81%) patients. The patients received a median of 2 (range 1–10) cycles of this therapy, and the overall response rate (ORR) was 70%. Patients with penta-refractory MM and high-risk cytogenetics showed similar ORR of 65% and 79%, respectively. The median progression-free survival (PFS) and overall survival were 4.1 (95% CI 2.7–5.4) and 8.4 (95% CI 6.7–10.0) months, respectively. Patients with lactate dehydrogenase >250 IU/L showed significantly shorter PFS in comparison with others patients (p = 0.006). We used this regimen as bridging therapy prior to chimeric antigen receptor T-cell infusion in four patients. In conclusion, “Dara-KDT-P(A)CE” is an effective salvage therapy for patients with heavily pretreated, multi-refractory, high-risk RRMM lacking alternative options.
The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results.
In locally advanced rectal cancer (LARC) neoadjuvant chemoradiotherapy is regarded as standard treatment. We assessed acute toxicities in patients receiving conventional 3D-conformal radiotherapy (3D-RT) and correlated them with dosimetric parameters after re-planning with volumetric modulated arc therapy (VMAT). Patients were randomized within the multicenter CAO/ARO/AIO-12 trial and received 50.4 Gy in 28 fractions and simultaneous chemotherapy with fluorouracil and oxaliplatin. Organs at risk (OAR) were contoured in a standardized approach. Acute toxicities and dose volume histogram parameters of 3D-RT plans were compared to retrospectively calculated VMAT plans. From 08/2015 to 01/2018, 35 patients with LARC were treated at one study center. Thirty-four patients were analyzed of whom 1 (3%) was UICC stage II and 33 (97%) patients were UICC stage III. Grade 3 acute toxicities occurred in 5 patients (15%). Patients with acute grade 1 cystitis (n = 9) had significantly higher D\(_{mean}\) values for bladder (29.4 Gy vs. 25.2 Gy, p < 0.01) compared to patients without bladder toxicities. Acute diarrhea was associated with small bowel volume (grade 2: 870.1 ccm vs. grade 0–1: 647.3 ccm; p < 0.01) and with the irradiated volumes V5 to V50. Using VMAT planning, we could reduce mean doses and irradiated volumes for all OAR: D\(_{mean}\) bladder (21.9 Gy vs. 26.3 Gy, p < 0.01), small bowel volumes V5–V45 (p < 0.01), D\(_{mean}\) anal sphincter (34.6 Gy vs. 35.6 Gy, p < 0.01) and D\(_{mean}\) femoral heads (right 11.4 Gy vs. 25.9 Gy, left 12.5 Gy vs. 26.6 Gy, p < 0.01). Acute small bowel and bladder toxicities were dose and volume dependent. Dose and volume sparing for all OAR could be achieved through VMAT planning and might result in less acute toxicities.
Bile salts accumulating during cholestatic liver disease are believed to promote liver fibrosis. We have recently shown that chenodeoxycholate (CDC) induces expansion of hepatic stellate cells (HSCs) in vivo, thereby promoting liver fibrosis. Mechanisms underlying bile salt-induced fibrogenesis remain elusive. We aimed to characterize the effects of different bile salts on HSC biology and investigated underlying signaling pathways. Murine HSCs (mHSCs) were stimulated with hydrophilic and hydrophobic bile salts. Proliferation, cell mass, collagen deposition, and activation of signaling pathways were determined. Activation of the human HSC cell line LX 2 was assessed by quantification of α-smooth muscle actin (αSMA) expression. Phosphatidyl-inositol-3-kinase (PI3K)-dependent signaling was inhibited both pharmacologically and by siRNA. CDC, the most abundant bile salt accumulating in human cholestasis, but no other bile salt tested, induced Protein kinase B (PKB) phosphorylation and promoted HSC proliferation and subsequent collagen deposition. Pharmacological inhibition of the upstream target PI3K-inhibited activation of PKB and pro-fibrogenic proliferation of HSCs. The PI3K p110α-specific inhibitor Alpelisib and siRNA-mediated knockdown of p110α ameliorated pro-fibrogenic activation of mHSC and LX 2 cells, respectively. In summary, pro-fibrogenic signaling in mHSCs is selectively induced by CDC. PI3K p110α may be a potential therapeutic target for the inhibition of bile salt-induced fibrogenesis in cholestasis.
Arrhythmogenic cardiomyopathy (ACM) is an inherited heart muscle disease caused by heterozygous missense mutations within the gene encoding for the nuclear envelope protein transmembrane protein 43 (TMEM43). The disease is characterized by myocyte loss and fibro-fatty replacement, leading to life-threatening ventricular arrhythmias and sudden cardiac death. However, the role of TMEM43 in the pathogenesis of ACM remains poorly understood. In this study, we generated cardiomyocyte-restricted transgenic zebrafish lines that overexpress eGFP-linked full-length human wild-type (WT) TMEM43 and two genetic variants (c.1073C>T, p.S358L; c.332C>T, p.P111L) using the Tol2-system. Overexpression of WT and p.P111L-mutant TMEM43 was associated with transcriptional activation of the mTOR pathway and ribosome biogenesis, and resulted in enlarged hearts with cardiomyocyte hypertrophy. Intriguingly, mutant p.S358L TMEM43 was found to be unstable and partially redistributed into the cytoplasm in embryonic and adult hearts. Moreover, both TMEM43 variants displayed cardiac morphological defects at juvenile stages and ultrastructural changes within the myocardium, accompanied by dysregulated gene expression profiles in adulthood. Finally, CRISPR/Cas9 mutants demonstrated an age-dependent cardiac phenotype characterized by heart enlargement in adulthood. In conclusion, our findings suggest ultrastructural remodeling and transcriptomic alterations underlying the development of structural and functional cardiac defects in TMEM43-associated cardiomyopathy.
Although the field of fungal infections advanced tremendously, diagnosis of invasive pulmonary aspergillosis (IPA) in immunocompromised patients continues to be a challenge. Since IPA is a multifactorial disease, investigation from different aspects may provide new insights, helpful for improving IPA diagnosis. This work aimed to characterize the human immune response to Aspergillus fumigatus in a multilevel manner to identify characteristic molecular candidates and risk factors indicating IPA, which may in the future support already established diagnostic assays. We combined in vitro studies using myeloid cells infected with A. fumigatus and longitudinal case-control studies investigating patients post allogeneic stem cell transplantation (alloSCT) suffering from IPA and their match controls.
Characteristic miRNA and mRNA signatures indicating A. fumigatus-infected monocyte-derived dendritic cells (moDCs) demonstrated the potential to differentiate between A. fumigatus and Escherichia coli infection. Transcriptome and protein profiling of alloSCT patients suffering from IPA and their matched controls revealed a distinctive IPA signature consisting of MMP1 induction and LGAL2 repression in combination with elevated IL-8 and caspase-3 levels. Both, in vitro and case-control studies, suggested cytokines, matrix-metallopeptidases and galectins are important in the immune response to A. fumigatus. Identified IPA characteristic molecular candidates are involved in numerous processes, thus a combination of these in a distinctive signature may increase the specificity. Finally, low monocyte counts, severe GvHD of the gut (grade ≥ 2) and etanercept administration were significantly associated with IPA diagnosis post alloSCT. Etanercept in monocyte-derived macrophages (MDM) infected with A. fumigatus downregulates genes involved in the NF-κB and TNF-α pathway and affects the secretion of CXCL10.
Taken together, identified characteristic molecular signatures and risk factors indicating IPA may in the future in combination with established fungal biomarkers overcome current diagnostic challenges and help to establish tailored antifungal therapy. Therefore, further multicentre studies are encouraged to evaluate reported findings.
Despite available diagnostic tests and recent advances, diagnosis of pulmonary invasive aspergillosis (IPA) remains challenging. We performed a longitudinal case-control pilot study to identify host-specific, novel, and immune-relevant molecular candidates indicating IPA in patients post allogeneic stem cell transplantation (alloSCT). Supported by differential gene expression analysis of six relevant in vitro studies, we conducted RNA sequencing of three alloSCT patients categorized as probable IPA cases and their matched controls without Aspergillus infection (66 samples in total). We additionally performed immunoassay analysis for all patient samples to gain a multi-omics perspective. Profiling analysis suggested LGALS2, MMP1, IL-8, and caspase-3 as potential host molecular candidates indicating IPA in investigated alloSCT patients. MMP1, IL-8, and caspase-3 were evaluated further in alloSCT patients for their potential to differentiate possible IPA cases and patients suffering from COVID-19-associated pulmonary aspergillosis (CAPA) and appropriate control patients. Possible IPA cases showed differences in IL-8 and caspase-3 serum levels compared with matched controls. Furthermore, we observed significant differences in IL-8 and caspase-3 levels among CAPA patients compared with control patients. With our conceptual work, we demonstrate the potential value of considering the human immune response during Aspergillus infection to identify immune-relevant molecular candidates indicating IPA in alloSCT patients. These human host candidates together with already established fungal biomarkers might improve the accuracy of IPA diagnostic tools.
Government funding of research beyond biomedicine: challenges and opportunities for neuroethology
(2022)
Curiosity-driven research is fundamental for neuroethology and depends crucially on governmental funding. Here, we highlight similarities and differences in funding of curiosity-driven research across countries by comparing two major funding agencies—the National Science Foundation (NSF) in the United States and the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG). We interviewed representatives from each of the two agencies, focusing on general funding trends, levels of young investigator support, career-life balance, and international collaborations. While our analysis revealed a negative trend in NSF funding of biological research, including curiosity-driven research, German researchers in these areas have benefited from a robust positive trend in DFG funding. The main reason for the decrease in curiosity-driven research in the US is that the NSF has only partially been able to compensate for the funding gap resulting from the National Institutes of Health restricting their support to biomedical research using select model organisms. Notwithstanding some differences in funding programs, particularly those relevant for scientists in the postdoctoral phase, both the NSF and DFG clearly support curiosity-driven research.
The Coronavirus disease 2019 (COVID-19) has not only had negative effects on employees' health, but also on their prospects to gain and maintain employment. Using a longitudinal research design with two measurement points, we investigated the ramifications of various psychological and organizational resources on employees' careers during the COVID-19 pandemic. Specifically, in a sample of German employees (N = 305), we investigated the role of psychological capital (PsyCap) for four career-related outcomes: career satisfaction, career engagement, coping with changes in career due to COVID-19, and career-related COVID-19 worries. We also employed leader–member exchange (LMX) as a moderator and career adaptability as a mediating variable in these relationships. Results from path analyses revealed a positive association between PsyCap and career satisfaction and career coping. Furthermore, PsyCap was indirectly related to career engagement through career adaptability. However, moderation analysis showed no moderating role of LMX on the link between PsyCap and career adaptability. Our study contributes to the systematic research concerning the role of psychological and organizational resources for employees' careers and well-being, especially for crisis contexts.
The importance of proactive and timely prediction of critical events is steadily increasing, whether in the manufacturing industry or in private life. In the past, machines in the manufacturing industry were often maintained based on a regular schedule or threshold violations, which is no longer competitive as it causes unnecessary costs and downtime. In contrast, the predictions of critical events in everyday life are often much more concealed and hardly noticeable to the private individual, unless the critical event occurs. For instance, our electricity provider has to ensure that we, as end users, are always supplied with sufficient electricity, or our favorite streaming service has to guarantee that we can watch our favorite series without interruptions. For this purpose, they have to constantly analyze what the current situation is, how it will develop in the near future, and how they have to react in order to cope with future conditions without causing power outages or video stalling.
In order to analyze the performance of a system, monitoring mechanisms are often integrated to observe characteristics that describe the workload and the state of the system and its environment. Reactive systems typically employ thresholds, utility functions, or models to determine the current state of the system. However, such reactive systems cannot proactively estimate future events, but only as they occur. In the case of critical events, reactive determination of the current system state is futile, whereas a proactive system could have predicted this event in advance and enabled timely countermeasures. To achieve proactivity, the system requires estimates of future system states. Given the gap between design time and runtime, it is typically not possible to use expert knowledge to a priori model all situations a system might encounter at runtime. Therefore, prediction methods must be integrated into the system. Depending on the available monitoring data and the complexity of the prediction task, either time series forecasting in combination with thresholding or more sophisticated machine and deep learning models have to be trained.
Although numerous forecasting methods have been proposed in the literature, these methods have their advantages and disadvantages depending on the characteristics of the time series under consideration. Therefore, expert knowledge is required to decide which forecasting method to choose. However, since the time series observed at runtime cannot be known at design time, such expert knowledge cannot be implemented in the system. In addition to selecting an appropriate forecasting method, several time series preprocessing steps are required to achieve satisfactory forecasting accuracy. In the literature, this preprocessing is often done manually, which is not practical for autonomous computing systems, such as Self-Aware Computing Systems. Several approaches have also been presented in the literature for predicting critical events based on multivariate monitoring data using machine and deep learning. However, these approaches are typically highly domain-specific, such as financial failures, bearing failures, or product failures. Therefore, they require in-depth expert knowledge. For this reason, these approaches cannot be fully automated and are not transferable to other use cases. Thus, the literature lacks generalizable end-to-end workflows for modeling, detecting, and predicting failures that require only little expert knowledge.
To overcome these shortcomings, this thesis presents a system model for meta-self-aware prediction of critical events based on the LRA-M loop of Self-Aware Computing Systems. Building upon this system model, this thesis provides six further contributions to critical event prediction. While the first two contributions address critical event prediction based on univariate data via time series forecasting, the three subsequent contributions address critical event prediction for multivariate monitoring data using machine and deep learning algorithms. Finally, the last contribution addresses the update procedure of the system model. Specifically, the seven main contributions of this thesis can be summarized as follows:
First, we present a system model for meta self-aware prediction of critical events. To handle both univariate and multivariate monitoring data, it offers univariate time series forecasting for use cases where a single observed variable is representative of the state of the system, and machine learning algorithms combined with various preprocessing techniques for use cases where a large number of variables are observed to characterize the system’s state. However, the two different modeling alternatives are not disjoint, as univariate time series forecasts can also be included to estimate future monitoring data as additional input to the machine learning models. Finally, a feedback loop is incorporated to monitor the achieved prediction quality and trigger model updates.
We propose a novel hybrid time series forecasting method for univariate, seasonal time series, called Telescope. To this end, Telescope automatically preprocesses the time series, performs a kind of divide-and-conquer technique to split the time series into multiple components, and derives additional categorical information. It then forecasts the components and categorical information separately using a specific state-of-the-art method for each component. Finally, Telescope recombines the individual predictions. As Telescope performs both preprocessing and forecasting automatically, it represents a complete end-to-end approach to univariate seasonal time series forecasting. Experimental results show that Telescope achieves enhanced forecast accuracy, more reliable forecasts, and a substantial speedup. Furthermore, we apply Telescope to the scenario of predicting critical events for virtual machine auto-scaling. Here, results show that Telescope considerably reduces the average response time and significantly reduces the number of service level objective violations.
For the automatic selection of a suitable forecasting method, we introduce two frameworks for recommending forecasting methods. The first framework extracts various time series characteristics to learn the relationship between them and forecast accuracy. In contrast, the other framework divides the historical observations into internal training and validation parts to estimate the most appropriate forecasting method. Moreover, this framework also includes time series preprocessing steps. Comparisons between the proposed forecasting method recommendation frameworks and the individual state-of-the-art forecasting methods and the state-of-the-art forecasting method recommendation approach show that the proposed frameworks considerably improve the forecast accuracy.
With regard to multivariate monitoring data, we first present an end-to-end workflow to detect critical events in technical systems in the form of anomalous machine states. The end-to-end design includes raw data processing, phase segmentation, data resampling, feature extraction, and machine tool anomaly detection. In addition, the workflow does not rely on profound domain knowledge or specific monitoring variables, but merely assumes standard machine monitoring data. We evaluate the end-to-end workflow using data from a real CNC machine. The results indicate that conventional frequency analysis does not detect the critical machine conditions well, while our workflow detects the critical events very well with an F1-score of almost 91%.
To predict critical events rather than merely detecting them, we compare different modeling alternatives for critical event prediction in the use case of time-to-failure prediction of hard disk drives. Given that failure records are typically significantly less frequent than instances representing the normal state, we employ different oversampling strategies. Next, we compare the prediction quality of binary class modeling with downscaled multi-class modeling. Furthermore, we integrate univariate time series forecasting into the feature generation process to estimate future monitoring data. Finally, we model the time-to-failure using not only classification models but also regression models. The results suggest that multi-class modeling provides the overall best prediction quality with respect to practical requirements. In addition, we prove that forecasting the features of the prediction model significantly improves the critical event prediction quality.
We propose an end-to-end workflow for predicting critical events of industrial machines. Again, this approach does not rely on expert knowledge except for the definition of monitoring data, and therefore represents a generalizable workflow for predicting critical events of industrial machines. The workflow includes feature extraction, feature handling, target class mapping, and model learning with integrated hyperparameter tuning via a grid-search technique. Drawing on the result of the previous contribution, the workflow models the time-to-failure prediction in terms of multiple classes, where we compare different labeling strategies for multi-class classification. The evaluation using real-world production data of an industrial press demonstrates that the workflow is capable of predicting six different time-to-failure windows with a macro F1-score of 90%. When scaling the time-to-failure classes down to a binary prediction of critical events, the F1-score increases to above 98%.
Finally, we present four update triggers to assess when critical event prediction models should be re-trained during on-line application. Such re-training is required, for instance, due to concept drift. The update triggers introduced in this thesis take into account the elapsed time since the last update, the prediction quality achieved on the current test data, and the prediction quality achieved on the preceding test data. We compare the different update strategies with each other and with the static baseline model. The results demonstrate the necessity of model updates during on-line application and suggest that the update triggers that consider both the prediction quality of the current and preceding test data achieve the best trade-off between prediction quality and number of updates required.
We are convinced that the contributions of this thesis constitute significant impulses for the academic research community as well as for practitioners. First of all, to the best of our knowledge, we are the first to propose a fully automated, end-to-end, hybrid, component-based forecasting method for seasonal time series that also includes time series preprocessing. Due to the combination of reliably high forecast accuracy and reliably low time-to-result, it offers many new opportunities in applications requiring accurate forecasts within a fixed time period in order to take timely countermeasures. In addition, the promising results of the forecasting method recommendation systems provide new opportunities to enhance forecasting performance for all types of time series, not just seasonal ones. Furthermore, we are the first to expose the deficiencies of the prior state-of-the-art forecasting method recommendation system.
Concerning the contributions to critical event prediction based on multivariate monitoring data, we have already collaborated closely with industrial partners, which supports the practical relevance of the contributions of this thesis. The automated end-to-end design of the proposed workflows that do not demand profound domain or expert knowledge represents a milestone in bridging the gap between academic theory and industrial application. Finally, the workflow for predicting critical events in industrial machines is currently being operationalized in a real production system, underscoring the practical impact of this thesis.
Introduction/Aims
Schwann cell clusters have been described at the murine dermis-epidermis border. We quantified dermal Schwann cells in the skin of patients with small-fiber neuropathy (SFN) compared with healthy controls to correlate with the clinical phenotype.
Methods
Skin punch biopsies from the lower legs of 28 patients with SFN (11 men, 17 women; median age, 54 [range, 19-73] years) and 9 healthy controls (five men, four women, median age, 34 [range, 25-69] years) were immunoreacted for S100 calcium-binding protein B as a Schwann cell marker, protein-gene product 9.5 as a pan-neuronal marker, and CD207 as a Langerhans cell marker. Intraepidermal nerve fiber density (IENFD) and subepidermal Schwann cell counts were determined.
Results
Skin samples of patients with SFN showed lower IENFD (P < .05), fewer Schwann cells per millimeter (P < .01), and fewer Schwann cell clusters per millimeter (P < .05) than controls. When comparing SFN patients with reduced (n = 13; median age, 53 [range, 19-73] years) and normal distal (n = 15, median age, 54 [range, 43-68] years) IENFD, the number of solitary Schwann cells per millimeter (p < .01) and subepidermal nerve fibers associated with Schwann cell branches (P < .05) were lower in patients with reduced IENFD. All three parameters correlated positively with distal IENFD (P < .05 to P < .01), whereas no correlation was found between Schwann cell counts and clinical pain characteristics.
Discussion
Our data raise questions about the mechanisms underlying the interdependence of dermal Schwann cells and skin innervation in SFN. The temporal course and functional impact of Schwann cell presence and kinetics need further investigation.
Breaking inversion symmetry in crystalline solids enables the formation of spin-polarized electronic states by spin-orbit coupling without the need for magnetism. A variety of interesting physical phenomena related to this effect have been intensively investigated in recent years, including the Rashba effect, topological insulators and Weyl semimetals. In this work, the interplay of inversion symmetry breaking and spin-orbit coupling and, in particular their general influence on the character of electronic states, i.e., on the spin and orbital degrees of freedom, is investigated experimentally. Two different types of suitable model systems are studied: two-dimensional surface states for which the Rashba effect arises from the inherently broken inversion symmetry at the surface, and a Weyl semimetal, for which inversion symmetry is broken in the three-dimensional crystal structure. Angle-resolved photoelectron spectroscopy provides momentum-resolved access to the spin polarization and the orbital composition of electronic states by means of photoelectron spin detection and dichroism with polarized light. The experimental results shown in this work are also complemented and supported by ab-initio density functional theory calculations and simple model considerations.
Altogether, it is shown that the breaking of inversion symmetry has a decisive influence on the Bloch wave function, namely, the formation of an orbital angular momentum. This mechanism is, in turn, of fundamental importance both for the physics of the surface Rashba effect and the topology of the Weyl semimetal TaAs.
The investigation of the Earth system and interplays between its components is of utmost importance to enhance the understanding of the impacts of global climate change on the Earth's land surface. In this context, Earth observation (EO) provides valuable long-term records covering an abundance of land surface variables and, thus, allowing for large-scale analyses to quantify and analyze land surface dynamics across various Earth system components. In view of this, the geographical entity of river basins was identified as particularly suitable for multivariate time series analyses of the land surface, as they naturally cover diverse spheres of the Earth. Many remote sensing missions with different characteristics are available to monitor and characterize the land surface. Yet, only a few spaceborne remote sensing missions enable the generation of spatio-temporally consistent time series with equidistant observations over large areas, such as the MODIS instrument.
In order to summarize available remote sensing-based analyses of land surface dynamics in large river basins, a detailed literature review of 287 studies was performed and several research gaps were identified. In this regard, it was found that studies rarely analyzed an entire river basin, but rather focused on study areas at subbasin or regional scale. In addition, it was found that transboundary river basins remained understudied and that studies largely focused on selected riparian countries. Moreover, the analysis of environmental change was generally conducted using a single EO-based land surface variable, whereas a joint exploration of multivariate land surface variables across spheres was found to be rarely performed.
To address these research gaps, a methodological framework enabling (1) the preprocessing and harmonization of multi-source time series as well as (2) the statistical analysis of a multivariate feature space was required. For development and testing of a methodological framework that is transferable in space and time, the transboundary river basins Indus, Ganges, Brahmaputra, and Meghna (IGBM) in South Asia were selected as study area, having a size equivalent to around eight times the size of Germany. These basins largely depend on water resources from monsoon rainfall and High Mountain Asia which holds the largest ice mass outside the polar regions. In total, over 1.1 billion people live in this region and in parts largely depend on these water resources which are indispensable for the world's largest connected irrigated croplands and further domestic needs as well. With highly heterogeneous geographical settings, these river basins allow for a detailed analysis of the interplays between multiple spheres, including the anthroposphere, biosphere, cryosphere, hydrosphere, lithosphere, and atmosphere.
In this thesis, land surface dynamics over the last two decades (December 2002 - November 2020) were analyzed using EO time series on vegetation condition, surface water area, and snow cover area being based on MODIS imagery, the DLR Global WaterPack and JRC Global Surface Water Layer, as well as the DLR Global SnowPack, respectively. These data were evaluated in combination with further climatic, hydrological, and anthropogenic variables to estimate their influence on the three EO land surface variables. The preprocessing and harmonization of the time series was conducted using the implemented framework. The resulting harmonized feature space was used to quantify and analyze land surface dynamics by means of several statistical time series analysis techniques which were integrated into the framework. In detail, these methods involved (1) the calculation of trends using the Mann-Kendall test in association with the Theil-Sen slope estimator, (2) the estimation of changes in phenological metrics using the Timesat tool, (3) the evaluation of driving variables using the causal discovery approach Peter and Clark Momentary Conditional Independence (PCMCI), and (4) additional correlation tests to analyze the human influence on vegetation condition and surface water area.
These analyses were performed at annual and seasonal temporal scale and for diverse spatial units, including grids, river basins and subbasins, land cover and land use classes, as well as elevation-dependent zones. The trend analyses of vegetation condition mostly revealed significant positive trends. Irrigated and rainfed croplands were found to contribute most to these trends. The trend magnitudes were particularly high in arid and semi-arid regions. Considering surface water area, significant positive trends were obtained at annual scale. At grid scale, regional and seasonal clusters with significant negative trends were found as well. Trends for snow cover area mostly remained stable at annual scale, but significant negative trends were observed in parts of the river basins during distinct seasons. Negative trends were also found for the elevation-dependent zones, particularly at high altitudes. Also, retreats in the seasonal duration of snow cover area were found in parts of the river basins. Furthermore, for the first time, the application of the causal discovery algorithm on a multivariate feature space at seasonal temporal scale revealed direct and indirect links between EO land surface variables and respective drivers. In general, vegetation was constrained by water availability, surface water area was largely influenced by river discharge and indirectly by precipitation, and snow cover area was largely controlled by precipitation and temperature with spatial and temporal variations. Additional analyses pointed towards positive human influences on increasing trends in vegetation greenness. The investigation of trends and interplays across spheres provided new and valuable insights into the past state and the evolution of the land surface as well as on relevant climatic and hydrological driving variables. Besides the investigated river basins in South Asia, these findings are of great value also for other river basins and geographical regions.
Objectives
The pathogenesis of fibromyalgia syndrome (FMS) is unclear. Transcranial ultrasonography revealed anechoic alteration of midbrain raphe in depression and anxiety disorders, suggesting affection of the central serotonergic system. Here, we assessed midbrain raphe echogenicity in FMS.
Methods
Sixty-six patients underwent transcranial sonography, of whom 53 were patients with FMS (27 women, 26 men), 13 patients with major depression and physical pain (all women), and 14 healthy controls (11 women, 3 men). Raphe echogenicity was graded visually as normal or hypoechogenic, and quantified by digitized image analysis, each by investigators blinded to the clinical diagnosis.
Results
Quantitative midbrain raphe echogenicity was lower in patients with FMS compared to healthy controls (p<0.05), but not different from that of patients with depression and accompanying physical pain. Pain and FMS symptom burden did not correlate with midbrain raphe echogenicity as well as the presence and severity of depressive symptoms.
Conclusion
We found reduced echogenicity of the midbrain raphe area in patients with FMS and in patients with depression and physical pain, independent of the presence or severity of pain, FMS, and depressive symptoms. Further exploration of this sonographic finding is necessary before this objective technique may enter diagnostic algorithms in FMS and depression.
Studies in Modern English
(2022)
The book "Studies in Modern English" interprets English-language communication in the humanitarian paradigm of knowledge within the linguistic and psycho-sociocultural study of speech activity prioritizing cognitive and communicative paradigms. Digital discourse as the formation of new semiotic phenomena has crowned the rapid scientific and technological progress. Researchers' scientific achievements represented in the book are systemic and valid in terms of evidence-based narratives, which reflect the transformational horizon of information theory, communication theory, and theory of linguodidactics in modern English verbal, creative and digital environments. The book represents an integrated approach to the study of modern English as an open synergetic system, which requires a description of the relationship between verbal and nonverbal notions in digital space. The book integrates such innovative perspectives as the interaction of natural English and programming languages, cyber aggression as a communicative pattern in English-language digital discourse, ethics, and democratization of modern English language, relevant developments in the field of English language as a Foreign Language, and other related issues. A complex focus of the book in the realm of modern English-language communication concerns verbal and nonverbal notions analyzed in the context of socio-cultural and digital communicative spaces.