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Abstract Objective Krabbe disease (KD) is a multisystem neurodegenerative disorder with severe disability and premature death, mostly with an infancy/childhood onset. In rare cases of late‐onset phenotypes, symptoms are often milder and difficult to diagnose. We here present a translational approach combining diagnostic and biochemical analyses of a male patient with a progressive gait disorder starting at the age of 44 years, with a final diagnosis of late‐onset KD (LOKD). Methods Additionally to cerebral MRI, protein structural analyses of the β‐galactocerebrosidase protein (GALC) were performed. Moreover, expression, lysosomal localization, and activities of β‐glucocerebrosidase (GCase), cathepsin B (CTSB), and cathepsin D (CTSD) were analyzed in leukocytes, fibroblasts, and lysosomes of fibroblasts. Results Exome sequencing revealed biallelic likely pathogenic variants: GALC exons 11–17: 33 kb deletion; exon 4: missense variant (c.334A>G, p.Thr112Ala). We detected a reduced GALC activity in leukocytes and fibroblasts. While histological KD phenotypes were absent in fibroblasts, they showed a significantly decreased activities of GCase, CTSB, and CTSD in lysosomal fractions, while expression levels were unaffected. Interpretation The presented LOKD case underlines the age‐dependent appearance of a mildly pathogenic GALC variant and its interplay with other lysosomal proteins. As GALC malfunction results in reduced ceramide levels, we assume this to be causative for the here described decrease in CTSB and CTSD activity, potentially leading to diminished GCase activity. Hence, we emphasize the importance of a functional interplay between the lysosomal enzymes GALC, CTSB, CTSD, and GCase, as well as between their substrates, and propose their conjoined contribution in KD pathology.

Abstract Background SPG11-linked hereditary spastic paraplegia is characterized by multisystem neurodegeneration leading to a complex clinical and yet incurable phenotype of progressive spasticity and weakness. Severe cognitive symptoms are present in the majority of SPG11 patients, but a systematic and multidimensional analysis of the neuropsychological phenotype in a larger cohort is lacking. While thinning of the corpus callosum is a well-known structural hallmark observed in SPG11 patients, the neuroanatomical pattern of cortical degeneration is less understood. We here aimed to integrate neuropsychological and brain morphometric measures in SPG11. Methods We examined the neuropsychological profile in 16 SPG11 patients using a defined neuropsychological testing battery. Long-term follow up testing was performed in 7 patients. Cortical and subcortical degeneration was analyzed using an approved, artificial intelligence based magnetic resonance imaging brain morphometry, comparing patients to established reference values and to matched controls. Results In SPG11 patients, verbal fluency and memory as well as frontal-executive functions were severely impaired. Later disease stages were associated with a global pattern of impairments. Interestingly, reaction times correlated significantly with disease progression. Brain morphometry showed a significant reduction of cortical and subcortical parenchymal volume following a rostro-caudal gradient in SPG11. Whereas performance in memory tasks correlated with white matter damage, verbal fluency measures showed strong associations with frontal and parietal cortical volumes. Conclusions The present data will help define neuropsychological and imaging read out parameters in early as well as in advanced clinical stages for future interventional trials in SPG11.

Abstract The integration of machine learning (Keplerian paradigm) and more general artificial intelligence technologies with physical modeling based on first principles (Newtonian paradigm) will impact scientific computing in engineering in fundamental ways. Such hybrid models combine first principle-based models with data-based models into a joint architecture. This paper will give some background, explain trends and showcase recent achievements from an applied mathematics and industrial perspective. Examples include characterization of superconducting accelerator magnets by blending data with physics, data-driven magnetostatic field simulation without an explicit model of the constitutive law, and Bayesian free-shape optimization of a trace pair with bend on a printed circuit board.

Wnt signaling is essential for embryonic development and tissue homeostasis. So far, little is known about the importance and functional relevance of the different regions in WNT proteins including regions in their C-terminus identified as hairpin and linker. However, it was shown that the C-terminus of WNT7A comprising the linker and the hairpin region is sufficient to elicit signaling. Here, we demonstrate that actually the hairpin region of WNT7A in its C-terminus is fully sufficient to induce non-canonical signaling in myogenic cells while the linker region alone did not show biological activity. Of note, all known non-canonical signaling branches of WNT7A signaling in skeletal muscle were activated by the hairpin region of WNT7A thereby inducing hypertrophy in myotubes, symmetric expansion of satellite stem cells and migration of myoblasts. Furthermore, we demonstrate that the linker region in the C-terminus of WNT7A binds to the FZD7 receptor while it does not activate non-canonical Wnt signaling. However, the hairpin and the linker region of WNT7A can activate canonical Wnt signaling independent of each other suggesting that specificity of downstream signaling might be depending on those specific regions in the C-terminus.

Abstract To combat the COVID-19 pandemic, many countries around the globe have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effectiveness and efficiency of digital contact tracing apps. Furthermore, we study a usage stop effect induced by a false positive quarantine. Our results reveal that policy makers should adjust digital contact tracing apps to the behavioral characteristics of a society. Based on this, the proximity detection range should at least cover the range of a disease spread, and be much wider in certain cases. The widely used Bluetooth Low Energy protocol may not necessarily be the most effective technology for contact tracing.

Cancer cachexia is a complex metabolic disease so far lacking effective therapy, and it accounts for approximately one third of all cancer-related deaths worldwide. The extracellular ligand Wnt7a has a dual function in skeletal muscle, inducing the anabolic AKT/mammalian target of rapamycin (mTOR) pathway in myofibers and driving muscle stem cell expansion in skeletal muscle, making it a promising candidate for treatment of muscle wasting diseases. In murine and human myotubes, Wnt7a activates the anabolic AKT/mTOR pathway, thereby preventing cachexia-induced atrophy with a single application being sufficient to prevent atrophy independently of the tumor cell type causing cachexia. Addition of Wnt7a also improved activation and differentiation of muscle stem cells in cancer cachexia, a condition under which skeletal muscle regeneration is severely impaired due to stalled muscle stem cell differentiation. Finally, we show that Wnt7a prevents cancer cachexia in an in vivo mouse model based on C26 colon carcinoma cells. Wnt7a has a dual role in cachectic skeletal muscle; that is, it effectively counteracts muscle wasting through activation of the anabolic AKT/mTOR pathway and, furthermore, reverts the loss of muscle stem cell functionality due to cancer cachexia, making Wnt7a a promising candidate for an ameliorative treatment of cancer cachexia. Keywords: Wnt7a, cancer cachexia, skeletal muscle, muscle stem cell, satellite cell, atrophy, muscle wasting

Developments in artificial intelligence (AI) and distributed ledger technology (DLT) currently lead to lively debates in academia and practice. AI processes data to perform tasks that were previously thought possible only for humans. DLT has the potential to create consensus over data among a group of participants in untrustworthy environments. In recent research, both technologies are used in similar and even the same systems. This can lead to a convergence of AI and DLT, which in the past, has paved the way for major innovations of other information technologies. Previous work highlights several potential benefits of a convergence of AI and DLT but only provides a limited theoretical framework to describe upcoming real-world integration cases of both technologies. In this research, we review and synthesize extant research on integrating AI with DLT and vice versa to rigorously develop a future research agenda on the convergence of both technologies. In terms of integrating AI with DLT, we identified research opportunities in the areas of secure DLT, automated referee and governance, and privacy-preserving personalization. With regard to integrating DLT with AI, we identified future research opportunities in the areas of decentralized computing for AI, secure data sharing and marketplaces, explainable AI, and coordinating devices. In doing so, this research provides a four-fold contribution. First, it is not constrained to blockchain but instead investigates the broader phenomenon of DLT. Second, it considers the reciprocal nature of a convergence of AI and DLT. Third, it bridges the gap between theory and practice by helping researchers active in AI or DLT to overcome current limitations in their field, and practitioners to develop systems along with the convergence of both technologies. Fourth, it demonstrates the feasibility of applying the convergence concept to research on AI and DLT.

Diffusion-relaxation correlation NMR can simultaneously characterize both the microstructure and the local chemical composition of complex samples that contain multiple populations of water. Recent developments on tensor-valued diffusion encoding and Monte Carlo inversion algorithms have made it possible to transfer diffusion-relaxation correlation NMR from small-bore scanners to clinical MRI systems. Initial studies on clinical MRI systems employed 5D D-R1 and D-R2 correlation to characterize healthy brain in vivo. However, these methods are subject to an inherent bias that originates from not including R2 or R1 in the analysis, respectively. This drawback can be remedied by extending the concept to 6D D-R1-R2 correlation. In this work, we present a sparse acquisition protocol that records all data necessary for in vivo 6D D-R1-R2 correlation MRI across 633 individual measurements within 25 min—a time frame comparable to previous lower-dimensional acquisition protocols. The data were processed with a Monte Carlo inversion algorithm to obtain nonparametric 6D D-R1-R2 distributions. We validated the reproducibility of the method in repeated measurements of healthy volunteers. For a post-therapy glioblastoma case featuring cysts, edema, and partially necrotic remains of tumor, we present representative single-voxel 6D distributions, parameter maps, and artificial contrasts over a wide range of diffusion-, R1-, and R2-weightings based on the rich information contained in the D-R1-R2 distributions.

Myogenic differentiation, muscle stem cell functionality, and regeneration of skeletal muscle are cellular processes under tight control of various signaling pathways. Here, we investigated the role of non-canonical NF-κB signaling in myogenic differentiation, muscle stem cell functionality, and regeneration of skeletal muscle. We stimulated non-canonical NF-κB signaling with an agonistically acting antibody of the lymphotoxin beta receptor (LTβR). Interestingly, we found that stimulation of non-canonical NF-κB signaling through the LTβR agonist impairs myogenic differentiation, muscle stem cell function, and regeneration of skeletal muscle. Furthermore, we show that stimulation of non-canonical NF-κB signaling by the LTβR agonist coincides with activation of canonical NF-κB signaling. We suggest a direct crosstalk between canonical and non-canonical NF-κB signaling during myogenic differentiation which is required for proper myogenic differentiation and thereby regeneration of skeletal muscle.

BackgroundIn health care, the use of game-based interventions to increase motivation, engagement, and overall sustainability of health behaviors is steadily becoming more common. The most prevalent types of game-based interventions in health care research are gamification and serious games. Various researchers have discussed substantial conceptual differences between these 2 concepts, supported by empirical studies showing differences in the effects on specific health behaviors. However, researchers also frequently report cases in which terms related to these 2 concepts are used ambiguously or even interchangeably. It remains unclear to what extent existing health care research explicitly distinguishes between gamification and serious games and whether it draws on existing conceptual considerations to do so. ObjectiveThis study aims to address this lack of knowledge by capturing the current state of conceptualizations of gamification and serious games in health care research. Furthermore, we aim to provide tools for researchers to disambiguate the reporting of game-based interventions. MethodsWe used a 2-step research approach. First, we conducted a systematic literature review of 206 studies, published in the Journal of Medical Internet Research and its sister journals, containing terms related to gamification, serious games, or both. We analyzed their conceptualizations of gamification and serious games, as well as the distinctions between the two concepts. Second, based on the literature review findings, we developed a set of guidelines for researchers reporting on game-based interventions and evaluated them with a group of 9 experts from the field. ResultsOur results show that less than half of the concept mentions are accompanied by an explicit definition. To distinguish between the 2 concepts, we identified four common approaches: implicit distinction, synonymous use of terms, serious games as a type of gamified system, and distinction based on the full game dimension. Our Game-Based Intervention Reporting Guidelines (GAMING) consist of 25 items grouped into four topics: conceptual focus, contribution, mindfulness about related concepts, and individual concept definitions. ConclusionsConceptualizations of gamification and serious games in health care literature are strongly heterogeneous, leading to conceptual ambiguity. Following the GAMING can support authors in rigorous reporting on study results of game-based interventions.

Since the seminal works by Brodmann and contemporaries, it is well-known that different brain regions exhibit unique cytoarchitectonic and myeloarchitectonic features. Transferring the approach of classifying brain tissues – and other tissues – based on their intrinsic features to the realm of magnetic resonance (MR) is a longstanding endeavor. In the 1990s, atlas-based segmentation replaced earlier multi-spectral classification approaches because of the large overlap between the class distributions. Here, we explored the feasibility of performing global brain classification based on intrinsic MR features, and used several technological advances: ultra-high field MRI, q-space trajectory diffusion imaging revealing voxel-intrinsic diffusion properties, chemical exchange saturation transfer and semi-solid magnetization transfer imaging as a marker of myelination and neurochemistry, and current neural network architectures to analyze the data. In particular, we used the raw image data as well to increase the number of input features. We found that a global brain classification of roughly 97 brain regions was feasible with gross classification accuracy of 60%; and that mapping from voxel-intrinsic MR data to the brain region to which the data belongs is possible. This indicates the presence of unique MR signals of different brain regions, similar to their cytoarchitectonic and myeloarchitectonic fingerprints.

Background: TLR9 agonists are being developed as immunotherapy against malignancies and infections. TLR9 is primarily expressed in B cells and plasmacytoid dendritic cells (pDCs). TLR9 signalling may be critically important for B cell activity in lymph nodes but little is known about the in vivo impact of TLR9 agonism on human lymph node B cells. As a pre-defined sub-study within our clinical trial investigating TLR9 agonist MGN1703 (lefitolimod) treatment in the context of developing HIV cure strategies (NCT02443935), we assessed TLR9 agonist-mediated effects in lymph nodes. Methods: Participants received MGN1703 for 24 weeks concurrent with antiretroviral therapy. Seven participants completed the sub-study including lymph node resection at baseline and after 24 weeks of treatment. A variety of tissue-based immunologic and virologic parameters were assessed. Findings: MGN1703 dosing increased B cell differentiation; activated pDCs, NK cells, and T cells; and induced a robust interferon response in lymph nodes. Expression of Activation-Induced cytidine Deaminase, an essential regulator of B cell diversification and somatic hypermutation, was highly elevated. During MGN1703 treatment IgG production increased and antibody glycosylation patterns were changed. Interpretation: Our data present novel evidence that the TLR9 agonist MGN1703 modulates human lymph node B cells in vivo. These findings warrant further considerations in the development of TLR9 agonists as immunotherapy against cancers and infectious diseases. Fund: This work was supported by Aarhus University Research Foundation, the Danish Council for Independent Research and the NovoNordisk Foundation. Mologen AG provided study drug free of charge. Keywords: HIV cure, TLR9 agonist, B cell differentiation, B cell follicle, Antibody glycosylation

Abstract Background Toll-like receptor 9 agonists are potent activators of the immune system. Their clinical potential in immunotherapy against metastatic cancers is being evaluated across a number of clinical trials. TLR9 agonists are DNA-based molecules that contain several non-methylated CG-motifs for TLR9 recognition. Chemical modifications of DNA backbones are usually employed to prevent degradation by nucleases. These, however, can promote undesirable off-target effects and therapeutic restrictions. Methods Within the EnanDIM® family members of TLR9 agonists described here, D-deoxyribose nucleotides at the nuclease-accessible 3′-ends are replaced by nuclease-resistant L-deoxyribose nucleotides. EnanDIM® molecules with varying sequences were screened for their activation of human peripheral blood mononuclear cells based on secretion of IFN-alpha and IP-10 as well as activation of immune cells. Selected molecules were evaluated in mice in a maximum feasible dose study and for analysis of immune activation. The ability to modulate the tumor-microenvironment and anti-tumor responses after EnanDIM® administration was analyzed in syngeneic murine tumor models. Results The presence of L-deoxyribose containing nucleotides at their 3′-ends is sufficient to prevent EnanDIM® molecules from nucleolytic degradation. EnanDIM® molecules show broad immune activation targeting specific components of both the innate and adaptive immune systems. Activation was strictly dependent on the presence of CG-motifs, known to be recognized by TLR9. The absence of off-target effects may enable a wide therapeutic window. This advantageous anti-tumoral immune profile also promotes increased T cell infiltration into CT26 colon carcinoma tumors, which translates into reduced tumor growth. EnanDIM® molecules also drove regression of multiple other murine syngeneic tumors including MC38 colon carcinoma, B16 melanoma, A20 lymphoma, and EMT-6 breast cancer. In A20 and EMT-6, EnanDIM® immunotherapy cured a majority of mice and established persistent anti-tumor immune memory as evidenced by the complete immunity of these mice to subsequent tumor re-challenge. Conclusions In summary, EnanDIM® comprise a novel family of TLR9 agonists that facilitate an efficacious activation of both innate and adaptive immunity. Their proven potential in onco-immunotherapy, as shown by cytotoxic activity, beneficial modulation of the tumor microenvironment, inhibition of tumor growth, and induction of long-lasting, tumor-specific memory, supports EnanDIM® molecules for further preclinical and clinical development.

Activation of Toll-like receptor 9 (TLR9) is known to foster innate and adaptive immune responses and thus improve immune-mediated control of malignant disease. Lefitolimod is a potent TLR9 agonist without chemical modification developed for immunotherapeutic strategies. Modulation of the tumor microenvironment (TME) is a crucial requirement for the response to various immunotherapies: Immunogenic (“hot”) tumors, characterized by their T cell-infiltrated TME, respond better compared to non-immunogenic (“cold”) tumors. It has been speculated that the mode-of-action of lefitolimod provides the necessary signals for activation of immune cells, their differentiation into anti-tumor effector cells and their recruitment into the TME. We investigated the effect of lefitolimod on TME, and its potency to induce synergistic anti-tumor effects when combined with immune checkpoint inhibitory antibodies (CPI) in a murine model. Indeed, we could show that treatment with single-agent lefitolimod beneficially modulated the TME, via infiltration of activated CD8+ cells and a shift in the macrophage population toward M1 phenotype. The result was a pronounced anti-tumor effect correlated with the magnitude of infiltrated immune cells and tumor-specific T cell responses. In line with this, lefitolimod led to persistent anti-tumor memory in the EMT-6 model after tumor re-challenge. This was accompanied by an increase of tumor-specific T cell responses and cross-reactivity against different tumor cells. Lefitolimod clearly augmented the limited anti-tumor effect of the CPI anti-PD1 in an A20 and anti-PD-L1 in a CT26 model. These properties of potent immune surveillance reactivation render lefitolimod an ideal candidate as therapeutic agent for immuno-oncology, e.g. improving CPI strategies.

Abstract Background Klotho is a well-known anti-aging hormone, which serves as a suppressor of aging through a variety of mechanisms. Aging of skeletal muscle is concomitant with a decrease in muscle stem cell function resulting in impaired regeneration. Methods Here we investigate the functional role of the anti-aging hormone Klotho for muscle stem cell function after cardiotoxin-induced injury of skeletal muscle using a klotho hypomorphic mouse line, which is characterized by a premature aging phenotype. Furthermore, we perform floating single myofiber cultures with their adjacent muscle stem cells to investigate the interplay between canonical Wnt signaling and Klotho function. Results We demonstrate that muscle stem cell numbers are significantly decreased in klotho hypomorphic mice. Furthermore, we show that muscle stem cell function is also severely impaired upon loss of klotho expression, in culture and during regeneration in vivo. Moreover, we demonstrate that addition of recombinant Klotho protein inhibits aberrant excessive Wnt signaling in aged muscle stem cells thereby restoring their functionality. Conclusions The anti-aging hormone Klotho counteracts aberrant canonical Wnt signaling in muscle stem cells and might be one of the naturally occurring inhibitors of canonical Wnt signaling in skeletal muscle.

The tumor vaccine MGN1601 was designed and developed for treatment of metastatic renal cell carcinoma (mRCC). MGN1601 consists of a combination of fourfold gene-modified cells with the toll-like receptor 9 agonist dSLIM, a powerful connector of innate and adaptive immunity. Vaccine cells originate from a renal cell carcinoma cell line (grown from renal cell carcinoma tissue), express a variety of known tumor-associated antigens (TAA), and are gene modified to transiently express two co-stimulatory molecules, CD80 and CD154, and two cytokines, GM-CSF and IL-7, aimed to support immune response. Proof of concept of the designed vaccine was shown in mice: The murine homologue of the vaccine efficiently (100%) prevented tumor growth when used as prophylactic vaccine in a syngeneic setting. Use of the vaccine in a therapeutic setting showed complete response in 92% of mice as well as synergistic action and necessity of the components. In addition, specific cellular and humoral immune responses in mice were found when used in an allogeneic setting. Immune response to the vaccine was also shown in mRCC patients treated with MGN1601: Peptide array analysis revealed humoral CD4-based immune response to TAA expressed on vaccine cells, including survivin, cyclin D1, and stromelysin.