Miracle-dz/UniFAR-FTUs huggingface dataset:
Endogenous retroviruses promote prion-like spreading of proteopathic seeds

Endogenous retroviruses, remnants of viral germline infections, make up a substantial proportion of the mammalian genome. While usually epigenetically silenced, retroelements can become upregulated in neurodegenerative diseases associated with protein aggregation, such as amyotrophic lateral sclerosis and tauopathies. Here we demonstrate that spontaneous upregulation of endogenous retrovirus gene expression drastically affects the dissemination of protein aggregates between murine cells in culture. Viral glycoprotein Env mediates membrane association between donor and recipient cells and promotes the intercellular transfer of protein aggregates packaged into extracellular vesicles. Proteopathic seed spreading can be inhibited by neutralizing antibodies targeting Env as well as drugs inhibiting viral protein processing. Importantly, we show that also overexpression of a human endogenous retrovirus Env elevates intercellular spreading of pathological Tau. Our data highlight the potential influence of endogenous retroviral proteins on protein misfolding diseases and suggest that antiviral drugs could represent promising candidates for inhibiting protein aggregate spreading.
Climate and ant richness explain the global distribution of ant-plant mutualisms

Biotic interactions are known to play an important role in shaping species geographic distributions and diversity patterns. However, the role of mutualistic interactions in shaping global diversity patterns remains poorly quantified, particularly with respect to interactions with invertebrates. Moreover, it is unclear how the nature of different mutualisms interacts with abiotic drivers and affects diversity patterns of mutualistic organisms. Here, we present a global-scale biogeographic analysis of three different ant-plant mutualisms, differentiating between plants bearing domatia, extrafloral nectaries (EFNs), and elaiosomes, based on comprehensive geographic distributions of ∼15,000 flowering plants and ∼13,000 ant species. Domatia and extrafloral nectaries involve indirect plant defenses provided by ants, while elaiosomes attract ants to disperse seeds. Our results show distinct biogeographic patterns of different ant-plant mutualisms, with domatium- and EFN-bearing plant richness decreasing sharply from the equator towards the poles, while elaiosome-bearing plants prevail at mid-latitudes. Contemporary climate, especially mean annual temperature and precipitation, emerge as the most important predictor of ant-associated plant diversity. In hot and moist regions, typically the tropics, domatium- and EFN-bearing plant richness increases with related ant guild richness, while in warm regions plants with elaiosomes are strongly linked to interacting ants. Our results suggest that ant richness in combination with climate drives the spatial variation of plants bearing domatia, extrafloral nectaries, and elaiosomes, highlighting the importance of mutualistic interactions for understanding plant biogeography and its response to global change.
Phase separation of competing memories along the human hippocampal theta rhythm

Competition between overlapping memories is considered one of the major causes of forgetting and it is still unknown how the human brain resolves such mnemonic conflict. In the present MEG study, we empirically tested a computational model that leverages an oscillating inhibition algorithm to minimise overlap between memories. We used a proactive interference task, where a reminder word could be associated with either a single image (non-competitive condition) or two competing images, and participants were asked to always recall the most recently learned word-image association. Time-resolved pattern classifiers were trained to detect the reactivated content of target and competitor memories from MEG sensor patterns, and the timing of these neural reactivations was analysed relative to the phase of the dominant hippocampal 3Hz theta oscillation. In line with our preregistered hypotheses, target and competitor reactivations locked to different phases of the hippocampal theta rhythm after several repeated recalls. Participants who behaviourally experienced lower levels of interference also showed larger phase separation between the two overlapping memories. The findings provide evidence that the temporal segregation of memories, orchestrated by slow oscillations, plays a functional role in resolving mnemonic competition by separating and prioritising relevant memories under conditions of high interference.
Modulation of tau tubulin kinases (TTBK1 and TTBK2) impacts ciliogenesis

Tau tubulin kinase 1 and 2 (TTBK1/2) are highly homologous kinases that are expressed and mediate disease-relevant pathways predominantly in the brain. Distinct roles for TTBK1 and TTBK2 have been delineated. While efforts have been devoted to characterizing the impact of TTBK1 inhibition in diseases like Alzheimer’s disease and amyotrophic lateral sclerosis, TTBK2 inhibition has been less explored. TTBK2 serves a critical function during cilia assembly. Given the biological importance of these kinases, we designed a targeted library from which we identified several chemical tools that engage TTBK1 and TTBK2 in cells and inhibit their downstream signaling. Indolyl pyrimidinamine 10 significantly reduced the expression of primary cilia on the surface of human induced pluripotent stem cells (iPSCs). Furthermore, analog 10 phenocopies TTBK2 knockout in iPSCs, confirming a role for TTBK2 in ciliogenesis.
Biophysical characterization of calcium-binding and modulatory-domain dynamics in a pentameric ligand-gated ion channel

Pentameric ligand-gated ion channels (pLGICs) perform electrochemical signal transduction in organisms ranging from bacteria to humans. Among the prokaryotic pLGICs there is architectural diversity involving N-terminal domains (NTDs) not found in eukaryotic relatives, exemplified by the calcium-sensitive channel (DeCLIC) from a Desulfofustis deltaproteobacterium, which has an NTD in addition to the canonical pLGIC structure. Here we have characterized the structure and dynamics of DeCLIC through cryo-electron microscopy (cryo-EM), small-angle neutron scattering (SANS), and molecular dynamics (MD) simulations. In the presence and absence of calcium, cryo-EM yielded structures with alternative conformations of the calcium binding site. SANS profiles further revealed conformational diversity at room temperature beyond that observed in static structures, shown through MD to be largely attributable to rigid body motions of the NTD relative to the protein core, with expanded and asymmetric conformations improving the fit of the SANS data. This work reveals the range of motion available to the DeCLIC NTD and calcium binding site, expanding the conformational landscape of the pLGIC family. Further, these findings demonstrate the power of combining low-resolution scattering, high-resolution structural, and MD-simulation data to elucidate interfacial interactions that are highly conserved in the pLGIC family.
Optimization of Automotive Software Distribution on Multi-core Systems using Machine Learning Approaches

1 Abstract Multi-core software should be partitioned under diﬀer-ent constraints e.g., balanced execution load on cores, timing behavior and optimized level of communication/synchronization among diﬀerent system components. The objective is to eﬃciently distribute the processes onto multi-core hardware such that the sys-tem has reduced communication/synchronization complexity. Moreover, a bad distribution strategy during migration from single-to multi-core and from multi-to many-core hardware does not always return the expected performance gain. This paper presents two novel AI-based approaches for optimal distribution (minimal inter-core communication inspite of no dead-line misses) of software system on multi-core hardware architecture. We discuss the comparisons of our machine learning solutions based on unsupervised and reinforcement learning. We share the beneﬁts and limitations of using unsupervised learning and reinforcement learning based on our experience.
The Devil is in The Details: Measuring Sensory Processing Sensitivity Using Natural Language Processing

Personality traits play a strong role in our perceptions, attitudes, and decision-making behaviors in our daily lives, including our choices of words and writing patterns. While prior Information Systems (IS) research on personality typically used the Big Five personality traits as a theoretical framework, we look into measuring a comparatively new inherent personality trait, sensory processing sensitivity, using natural language processing. We collect data on twenty general essay questions from along with self-reported sensory processing sensitivity survey questions from 241 participants. We categorize participants based on survey questions with multiple methods and derive different features from the textual data. Our results show almost perfect agreement among the different methods categorizing a highly sensitive person versus a non-highly sensitive person. The initial analysis demonstrates that certain features can be of great potential in measuring sensory processing sensitivity in written text.
The Role of Reuse in the Successive Implementation of Conversational Agents

More and more companies rely on the implementation of conversational agents (CAs) to automate certain of their processes. While CAs' initial development often mirrors an innovative process, their successive implementation can be made more efficient by drawing on other CAs' prior developments. We rely on data from a case study where a series of chatbots (which represent one type of CAs) was implemented . Routine theoretical concepts help us better understand how CAs may dynamically evolve and how their implementation can be accelerated. We found that a) the reuse of emerging or intentionally constructed means may allow accelerating the implementation of multiple successive CAs, b) means can be reused to extend or transfer functionality (through mutation or inheritance); and c) changes in the conversational context determine if means can be reused directly or not (through reproduction or recreation).
Innovation in High-End Food Service During COVID-19 Lockdowns

COVID-19 lockdown measures have forced hospitality operators to re-configure their dynamic capabilities through innovating operational practices and pivoting traditional business models. The high-end food service sector has undergone a particularly drastic shift towards a new normal. This qualitative study explores factors facilitating innovation at 16 high-end food service organizations in Finland and the UK through semi-structured expert interviews. Three key themes facilitating innovation during COVID-19 lockdowns are identified: 1) Combining high-tech and high-touch through new ways of producing and providing technology-driven service offerings, 2) Prosocial engagement, i.e. working together with multiple stakeholders to bring added value to all parties, not just the business, and 3) Reactivity, i.e. pushing the traditional boundaries of the sector through quick decision-making and constant iteration and refining of processes and procedures. Drawing our empirical findings together, innovation during COVID-19 lockdowns in high-end food service is conceptualized into three phases: React, Refine, and Reflect.
Phishing, Data-Disclosure and The Cognitive Reflection Test

Phishing is a form of online identity theft that aims to steal sensitive information such as online banking passwords and credit card information from users. Data is key for the digital economy, but disclosing personal data online increases vulnerabilities and the likelihood of experiencing negative consequences from disclosure. In this paper, we analyze willingness to share personal data, a preference for an intuitive decision style and susceptibility to phishes. We report the results of three large-scale national studies in Norway that included the cognitive reflection test (CRT) and a choice experiment on willingness to share personal data. With a binary logistic regression method, we analyzed the relationship between the CRT, willingness to share data and demographical variables with susceptibility to phishes as the outcome variable. Our main finding is that the willingness to share personal data and an intuitive thinking style significantly predict the probability of falling for phish. These results are based on three large-scale studies with national populations, in contrast to earlier studies that in most cases relying on student populations , giving them greater validity.
Designing Informal EAM Interventions - A Complementary Approach for Managing Enterprise Architecture Complexity

Although Enterprise Architecture Management (EAM) is a mature discipline and widely adopted in practice, surveys indicate effectivity barriers that, at least partially, appear to be a consequence of local decision makers’ non-compliance with enterprise-wide architectural guidelines. Several recent contributions aim at extending the portfolio of EAM interventions by ap-plying informal control mechanisms. Although promising to extend EAM effectivity, informal interventions are apparently not much utilized in EAM practice. Based on the assumption that a comprehensive presentation of design knowledge for informal EAM interventions would support more widespread adoption, this paper integrates existing knowledge components to a coherent design approach. The proposal covers theo-retical justification, conceptual foundations, a taxonomy of generic informal interventions, a catalogue of derived EAM intervention types, and a process to systematically instantiate and evaluate situation-specific informal interventions. Two Action Design Research projects in large companies are summarized as evaluative evidence for the potential that comprehensive informal intervention design has for improving EAM effectivity.
Adoption of Immersive Technologies in Manufacturing SMEs - A Strategy-as-Practice Perspective on their Affordances, Constraints and Responses

Immersive technologies (ImT) provide affordances for small and medium-sized enterprises (SMEs) in the manufacturing industry, such as the enhancement and recreation of aspects of the physical world. These affordances are critical due to changes in the SMEs’ environment including increasingly virtualized collaboration and digitization of work practices. However, the adoption of ImT by manufacturing SMEs is still low. Drawing on the Technology Affordances and Constraints theory, and applying a Strategy-as-Practice approach, this study researches the adoption of ImT as a strategic response to environmental changes in German-based manufacturing SMEs. The findings reveal the critical role of constraints of ImT, which act as hindrances to implementation. Specifically, realizing the affordances of ImT requires consideration of, and responses to, the constraints manufacturing SMEs experience, including the constraints associated with the providers of ImT. Thus, this paper expands the understanding of the factors which influence implementation and strategizing of ImT in SMEs.
Optimization of Protein Quality of Plant-Based Foods Through Digitalized Product Development

With the increasing availability of plant-based protein products that should serve as alternatives to animal-based protein products, it is necessary to develop not only environmentally friendly but also nutritious foods. Especially the protein content and quality are of concern in these products. The algorithm of NutriOpt was developed using linear programming to support the development of food products with a balanced amino acid profile while considering digestibility. The current version contains a database with 84 plant protein sources from different food groups (legumes, cereals, nuts, seeds) and with different grades of purification (flours, concentrates, isolates) from which NutriOpt can create mixtures with high protein quality while complying with constraints such as protein content, number of ingredients, and weight of the mixture. The program was tested through different case studies based on commercial plant-based drinks. It was possible to obtain formulations with a Protein Digestibility Corrected Amino Acid Score (PDCAAS) over 100 with ingredients and quantities potentially suitable for plant-based analogs. Our model can help to develop the second generation of plant-based product alternatives that can really be used as an alternative on long-term consumption. Further, there is still a great potential of expansion of the program for example to use press cakes or even to model whole menus or diets in the future.
Synergistic Radiosensitization Mediated by Chemodynamic Therapy via a Novel Biodegradable Peroxidases Mimicking Nanohybrid

Purpose Reactive oxygen species (ROS) are practically essential in radiotherapy to damage cancer cells; however, they are always inadequate for some malignant entities. Here, we designed a biodegradable mesoporous silica decorated with hemin and glucose oxidase (GOD@Hemin-MSN) to generate a chemodynamic therapy in order to enhance the killing capacity of radiotherapy. Methods Mesoporous silica, as an outstanding drug carrier, can deliver hemin and glucose oxidase to the tumor site. With high level of metabolism activity, cancer cells are abundant in glucose, which can be oxidized into H2O2 by glucose oxidase (GOD) on site. The generated H2O2 is subsequently converted into intracellular ROS, especially hydroxyl radical within the tumor microenvironment, by hemin, which has mimetic peroxidase properties. By this means, the ROS can be supplemented or enriched to facilitate the killing of tumor cells. Results The chemodynamic therapy induced by GOD@Hemin-MSN produced quantities of ROS, which compensated for their inadequacy as a result of radiotherapy, and exhibited remarkable antitumor efficacy, with a tumor inhibition rate of 91.5% in A549 tumor-bearing mice. Conclusion This work has validated GOD@Hemin-MSN as a radiosensitizer in chemodynamic therapy, which showed biocompatibility and potential for translational application.
Att-TasNet: Attending to Encodings in Time-Domain Audio Speech Separation of Noisy, Reverberant Speech Mixtures

Separation of speech mixtures in noisy and reverberant environments remains a challenging task for state-of-the-art speech separation systems. Time-domain audio speech separation networks (TasNets) are among the most commonly used network architectures for this task. TasNet models have demonstrated strong performance on typical speech separation baselines where speech is not contaminated with noise. When additive or convolutive noise is present, performance of speech separation degrades significantly. TasNets are typically constructed of an encoder network, a mask estimation network and a decoder network. The design of these networks puts the majority of the onus for enhancing the signal on the mask estimation network when used without any pre-processing of the input data or post processing of the separation network output data. Use of multihead attention (MHA) is proposed in this work as an additional layer in the encoder and decoder to help the separation network attend to encoded features that are relevant to the target speakers and conversely suppress noisy disturbances in the encoded features. As shown in this work, incorporating MHA mechanisms into the encoder network in particular leads to a consistent performance improvement across numerous quality and intelligibility metrics on a variety of acoustic conditions using the WHAMR corpus, a data-set of noisy reverberant speech mixtures. The use of MHA is also investigated in the decoder network where it is demonstrated that smaller performance improvements are consistently gained within specific model configurations. The best performing MHA models yield a mean 0.6 dB scale invariant signal-to-distortion (SISDR) improvement on noisy reverberant mixtures over a baseline 1D convolution encoder. A mean 1 dB SISDR improvement is observed on clean speech mixtures.
Effective Biotransformation of Variety of Guaiacyl Lignin Monomers Into Vanillin by Bacillus pumilus

Biotransformation has gained increasing attention due to its being an eco-friendly way for the production of value-added chemicals. The present study aimed to assess the potential of Bacillus pumilus ZB1 on guaiacyl lignin monomers biotransformation for the production of vanillin. Consequently, isoeugenol, eugenol, and vanillyl alcohol could be transformed into vanillin by B. pumilus ZB1. Based on the structural alteration of masson pine and the increase of total phenol content in the supernatant, B. pumilus ZB1 exhibited potential in lignin depolymerization and valorization using masson pine as the substrate. As the precursors of vanillin, 61.1% of isoeugenol and eugenol in pyrolyzed bio-oil derived from masson pine could be transformed into vanillin by B. pumilus ZB1. Four monooxygenases with high specific activity were identified that were involved in the transformation process. Thus, B. pumilus ZB1 could emerge as a candidate in the biosynthesis of vanillin by using wide guaiacyl precursors as the substrates.
Group Norms Influence Children’s Expectations About Status Based on Wealth and Popularity

Children’s understanding of status and group norms influence their expectations about social encounters. However, status is multidimensional and children may perceive status stratification (i.e., high- and low-status) differently across multiple status dimensions (i.e., wealth and popularity). The current study investigated the effect of status level and norms on children’s expectations about intergroup affiliation in wealth and popularity contexts. Participants (N = 165; age range: 5–10 years; Mage = 7.72 years) were randomly assigned to hear two scenarios where a high- or low-status target affiliated with opposite-status groups based on either wealth or popularity. In one scenario, the group expressed an inclusive norm. In the other scenario, the group expressed an exclusive norm. For each scenario, children made predictions about children’s expectations for a target to acquire social resources. Novel findings indicated that children associated wealth status to some extent, but they drew stronger inferences from the wealth dimension than from the popularity dimension. In contrast to previous evidence that children distinguish between high- and low-status groups, we did not find evidence to support this in the context of the current study. In addition, norms of exclusion diminished children’s expectations for acquiring social resources from wealth and popularity groups but this effect was more pronounced between wealth groups. We found age differences in children’s expectations in regards to norms, but not in regards to status. The implications of how these effects, in addition to lack of effects, bear on children’s expectations about acquiring resources are discussed.