julilili42/papers huggingface dataset:
A twist in the tale: shifting from covalent targeting of a tyrosine in JAK3 to a lysine in MK2
2025-01-01

A fluorosulfate inhibitor designed for tyrosine unexpectedly formed a covalent bond with the “catalytic” lysine in MK2, revealing an unusual binding mode and highlighting new opportunities for non-cysteine covalent targeting in kinases.
Admired Vulnerability or Shattered Heroism? Media Framing of Elite Athletes’ Mental Illnesses in German Print Media
2025-01-01

This study examines the media’s framing of mental illness among elite athletes in German print media from 2013 to 2023. Traditionally, elite sport culture has glorified invulnerability, marginalized mental health challenges, and stigmatized perceived weakness. Through a reflexive thematic analysis of 200 articles from three major German newspapers, we constructed four dominant frames: mental illness (a) as a bug in the performance-oriented sport system, (b) as a magnifying glass on its dark sides, (c) as a necessary respite, and (d) as a starting point for empowerment. Our findings highlight, on one hand, the persistence of traditional narratives that prioritize performance over well-being while, on the other hand, acknowledging a growing recognition of systemic failures and athletes’ holistic health in the print media. By exploring media constructions, this work advances the discourse on mental illness, stigma, and the evolving cultural transformation of elite sport.
Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6
2025-01-01

Abstract Climate change will impact wind and, therefore, wind power generation with largely unknown effects and magnitude. Climate models can provide insight and should be used for long-term power planning. In this work, we use Gaussian processes to predict power output given wind speeds from a global climate model. We validate the aggregated predictions from past climate model data with actual power generation, which supports using CMIP6 climate model data for multi-decadal wind power predictions and highlights the importance of being location-aware. We find that wind power projections for the two in-between climate scenarios, SSP2–4.5 and SSP3–7.0, closely align with actual wind power generation between 2015 and 2023. Our location-aware future predictions up to 2050 reveal only minor changes in yearly wind power generation. Our analysis also reveals larger uncertainty associated with Germany’s coastal areas in the North than Germany’s South, motivating wind power expansion in regions where the future wind is likely more reliable. Overall, our results indicate that wind energy will likely remain a reliable energy source.
Quantitative electroencephalography characteristics in delirium with various etiologies: A multicenter study
2025-01-01

Our findings demonstrate consistent patterns in spectral qEEG characteristics across delirium subtypes, suggesting a common neurophysiological pathway of global EEG slowing in delirium regardless of etiology. By contrast, differences in PLI did not converge across subtypes. Multicenter studies should harmonize data collection to disentangle the shared and distinct neurophysiological changes associated with delirium of varying etiologies, in order to advance our understanding of potentially convergent mechanisms across subtypes.
Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach
2025-01-01

Several domains increasingly rely on machine learning in their applications. The resulting heavy dependence on data has led to the emergence of various laws and regulations around data ethics and privacy and growing awareness of the need for privacy-preserving machine learning (ppML). Current ppML techniques utilize methods that are either purely based on cryptography, such as homomorphic encryption, or that introduce noise into the input, such as differential privacy. The main criticism given to those techniques is the fact that they either are too slow or they trade off a model&#x2019;s performance for improved confidentiality. To address this performance reduction, we aim to leverage robust representation learning as a way of encoding our data while optimising the privacy-utility trade-off. Our method centers on training autoencoders in a multi-objective manner and then concatenating the latent and learned features from the encoding part as the encoded form of our data. Such a deep learning-powered encoding can then safely be sent to a third party for intensive training and hyperparameter tuning. With our proposed framework, we can share our data and use third party tools without being under the threat of revealing its original form. We empirically validate our results on unimodal and multimodal settings, the latter following a vertical splitting system and show improved performance over state-of-the-art.
Phylogenetic meta-analysis of persistent SARS-CoV-2 infections in immunocompromised individuals highlights the challenges of robust evolutionary rate estimation caused by low genetic diversity
2025-01-01

Abstract Time-stamped genomic sequences from rapidly evolving pathogens can be used to estimate the rates of evolution through molecular tip-dating. The validity of this approach, however, depends on whether detectable levels of genetic variation have accumulated over the given sampling interval, generating a temporal signal. Moreover, molecular dating methods have demonstrated varying degrees of systematic biases under different biologically realistic scenarios, such as the presence of phylo-temporal clustering. Persistent SARS-CoV-2 infections in immunocompromised individuals have been linked to accelerated intrahost molecular rates compared to those of global lineages, facilitating the emergence of novel viral lineages. Yet, studies reporting elevated rates lack assessment of data properties, such as evaluation of temporal signal and comparison of multiple methods of inference, both crucial for robust rate estimation. In this study, we applied a range of molecular dating approaches to reassess the rate of SARS-CoV-2 intrahost evolution in immunocompromised individuals using publicly available datasets. Our findings suggest that even during long-term infections, the limited number of genetic changes accumulating may pose a challenge for robust inference of within-host evolutionary rates, particularly when relying on consensus sequences and when datasets are small or unevenly sampled. Moreover, our results highlight that when certain methodological limitations are overlooked, evolutionary rates can be significantly overestimated. In general, our findings demonstrate that estimating within-host evolutionary rates is a challenging question necessitating thorough assessment of data quality, careful selection of appropriate methods, and cautious interpretation of the resulting estimates. Whereas our phylogenetic analyses of viral consensus sequences provide no evidence of elevated evolutionary rates across the complete genome during chronic SARS-CoV-2 infection, prolonged viral shedding may nevertheless promote the emergence of new viral variants in immunocompromised individuals.
Neuron-type-specific Contributions to Dynamic Coding during Flexible Sensorimotor Decisions in Frontoparietal Cortex
2025-01-01

Abstract Neocortical circuits consist of multiple neuronal cell types, each likely playing distinct roles in flexible behavior. However, studies of decision-making have often overlooked these cell types, limiting our understanding of their specific contributions to local circuit functions. To address this, we simultaneously recorded neuronal activity from the frontal eye field (FEF), lateral PFC, and lateral intraparietal area (LIP) in a macaque monkey performing a visuomotor decision-making task. We used extracellular spike waveforms to reliably identify two functional classes of neurons: broad-spiking (BS) putative pyramidal cells and narrow-spiking (NS) putative interneurons. These cell types exhibited distinct response dynamics and choice-related information encoding across cortical regions. NS neurons in LIP and PFC showed higher choice-related activity and contributed to early encoding of decisions, whereas in FEF, NS neurons demonstrated dynamic encoding patterns, with BS neurons exhibiting significantly more stable encoding. Our findings reveal that choice information is represented differently across cell types and cortical regions, with NS neurons favoring early population coding in PFC and LIP and BS neurons exhibiting more static encoding in FEF. This heterogeneous coding strategy suggests that decision-related dynamics in the frontoparietal network are shaped by interactions between these distinct neuronal populations. The results provide new insights into cortical circuit dynamics and cell-type-specific contributions to decision-making.
OCT Biomarkers in a Cohort of Patients With PRPF31‐Associated Retinitis Pigmentosa
2025-01-01

Purpose: With degeneration of the photoreceptors in retinitis pigmentosa (RP), the reflectivity of the ellipsoid zone (EZ) decreases. We aimed to study characteristics of the EZ and its reflectivity in a cohort of patients with PRPF31 ‐associated autosomal‐dominant RP ( PRPF31 ‐adRP) and a possible relationship to EZ width and best‐corrected visual acuity (BCVA). Methods: EZ width and relative EZ reflectivity (rEZR) were assessed in 32 patients with PRPF31 ‐adRP. EZ width was measured on a horizontal SD‐OCT scan through the fovea of the right eye. On the same OCT scans, rEZR was measured at the foveola, temporal and nasal parafoveola and fovea. Results: Total EZ width revealed a significant negative correlation with age ( r s = −0.418, p = 0.017). Foveolar rEZR revealed a significant negative correlation with age ( r s = −0.403, p = 0.022), but was not significantly correlated with BCVA (foveolar: r s = −0.151, p = 0.410), in contrast to parafoveolar rEZR ( r s = −0.365, p = 0.0399), which was significantly correlated with BCVA. The ratio of foveal and parafoveolar rEZR correlated significantly with total EZ width ( r s = 0.358, p = 0.044). Conclusions: The EZ reflectivity (EZR) can be measured reliably using freely available software. The correlation we observed between rEZR and BCVA leads us to the conclusion that rEZR may be an additional marker in observational and therapeutic trials.
Beekeeper: Accelerating Honeypot Analysis With LLM-Driven Feedback
2025-01-01

Honeypots are decoy resources intended to entice adversaries and collect threat intelligence in the process. The amount and quality of the collected insights strongly correlate with the honeypot&#x2019;s credibility to the adversary. However, the development of medium to high interaction honeypots, so, environments that offer at minimum a shell to the attacker, is laborious and complex. Additionally, getting feedback on a honeypot is often expensive and time-consuming, slowing down development and discouraging investment into honeypots. Therefore, we propose <monospace>Beekeeper</monospace>: a modular framework that combines static tests, known attack sequences, and automated, large language model based querying to investigate medium to high interaction honeypots. Afterward, the results are analyzed to provide feedback on the current state of the system and recommendations on how to improve key characteristics of the honeypot. To demonstrate the framework&#x2019;s functionalities, we deploy <monospace>Beekeeper</monospace> with two medium and one high interaction systems and highlight how feedback and recommendations change after an initial set of improvements is implemented for each honeypot.
A mixed-anion compound based upon a [Pb4O4] heterocubane unit: synthesis, structure and electronic properties of Pb8O4I6(CN2)
2025-01-01

Pb 8 O 4 I 6 (CN 2 ) features heterocubane-like [Pb 4 O 4 ] units interconnected by iodide and carbodiimide ligands. The material is air-stable, shows n-type semiconducting behavior for photoanodes, and exhibits green photoluminescence at low temperatures.
Synergistic interaction between microbial nitrogen fixation and iron reduction in the environment
2025-01-01

Abstract Nitrogen and iron are essential yet often limiting nutrients in many ecosystems. Microbial nitrogen fixation by diazotrophs and dissimilatory ferric iron reduction are key processes that sustain nitrogen and iron availability. However, their interactions are not well understood. Here, we demonstrate a synergistic relationship between microbial nitrogen fixation and ferric iron reduction, observed in both laboratory cultures and environmental samples. In diazotrophic ferric iron-reducing bacteria, including Klebsiella grimontii N7 and Geobacter sulfurreducens PCA, nitrogen fixation enhanced heterotrophic ferric iron-reducing rates by 14.7- and 2.69-fold, respectively, and ferric iron reduction concurrently increased 15N2 fixation by up to 100%. A similar synergy was observed in an interspecies system comprising the diazotroph Azospirillum humicireducens SgZ-5T and the dissimilatory ferric iron-reducing bacterium Shewanella oneidensis MR-1. Transcriptomic analysis revealed that nitrogen fixation upregulated pathways involved in carbon and nitrogen metabolism, including amino acid biosynthesis, glycolysis, and the tricarboxylic acid cycle (P &amp;lt; 0.01), thereby accelerating ferric iron reduction through nitrogen supply. In turn, ferric iron reduction stimulated organic carbon oxidation, generating the energy, and reducing equivalents needed for microbial nitrogen fixation. These findings were further validated through microcosm experiments and meta-omics analyses of environmental samples from aquifers, marine sediments, hot springs, and soils, providing new insights into the coupled nitrogen, iron, and carbon cycles in natural ecosystems.
Electroactive naphthalimide and naphthalenediimide interlayers for inverted perovskite solar cells
2025-01-01

The capacity to access low-dimensional perovskites incorporating electroactive naphthalimide- and naphthalenediimide-based moieties was demonstrated to modify or replace fullerene electron-transport layers in inverted perovskite solar cells.
Enhancing Client Onboarding With Biographical Mapping: Reflections Based on Piloted Procedures
2025-01-01

While exercise professionals often emphasize individualized programming, early-stage client interactions require sufficient understanding of emotional and biographical contexts that shape motivation and adherence. This case study examines the use of biographical mapping as a tool for yielding in-depth client histories. To address this, the lead investigator—acting as a coach—piloted biographical mapping with two clients, combining narrative interviews with visual timelines to surface key life events and behavioral trends related to physical activity. Reflections from the coach, clients, and mentors highlight how the method supported rapport, uncovered hidden motives and barriers, and increased the confidence of the practitioner to guide subsequent programmatic decisions. The case also evaluates practical considerations of implementing biographical mapping. Recommendations are offered for integrating this tool into coaching and applied research settings.
Aqueous phase near-infrared emitters: water transfer of colloidal 2D PbS, PbSe and PbTe nanoplatelets
2025-01-01

We report on the aqueous phase transfer of NIR-emissive colloidal 2D PbS, PbSe and PbTe NPLs, using X- and L-type binding mercaptoundecanoic acid. The water-soluble 2D PbX NPLs exhibit efficient telecommunication-band PL relevant for fiber optics.
Second-harmonic generation and photoluminescence properties of colloidal WS2 monolayers deposited from solution
2025-01-01

Monolayered WS 2 exhibits a direct band gap, strongly bound excitons, trions and biexcitons as well as no inversion symmetry in the 2D crystal structure ( D 3h ), allowing frequency doubling by second-harmonic generation.
The relationship between recreational cannabis use, psychotic-like experiences, and the salience network in adolescent and young adult twins
2025-01-01

Abstract Background The use of cannabis in adolescence and early adulthood, critical phases for brain development, is linked to psychotic-like experiences (PLEs). The underlying mechanisms, however, remain unclear. This research examined the relationship between recreational cannabis use and PLEs, emphasizing the connectivity of the salience network (SN), which plays a role in salience processing and psychosis. To determine whether this relationship reflects shared genetic or environmental contributions, twin modeling was used. Methods We included 232 healthy adolescent Turkish twins who underwent diffusion MRI and psychometric assessment. SN connectivity was quantified using graph theory metrics. Linear mixed models were used to examine the associations among cannabis use, SN factors, and PLEs. Mediation analyses assessed whether SN parameters explained the cannabis–PLEs association. Twin models disentangle genetic and environmental contributions to these traits and their covariation. Results Cannabis use was significantly associated with higher overall PLE frequency. A specific SN factor predicted both total and positive PLEs. However, SN connectivity did not mediate the cannabis–PLEs relationship. Twin modeling showed that cannabis use and PLEs were mainly influenced by unique environmental factors. No significant phenotypic covariations were found among cannabis use, PLEs, and SN parameters. Conclusions Recreational cannabis use during adolescence and young adulthood is associated with heightened PLEs, although this association is not mediated by SN connectivity. The environment plays an important role during adolescence in shaping these traits independently. The findings underscore the need for longitudinal and genetically informed studies to clarify the mental health effects of adolescent cannabis use.
A computational approach to understanding effort-based decision-making in depression
2025-01-01

Abstract Background Motivational dysfunction is a core feature of depression and can have debilitating effects on everyday function. However, it is unclear which cognitive processes underlie impaired motivation and whether impairments persist following remission. Decision-making concerning exerting effort to obtain rewards offers a promising framework for understanding motivation, especially when examined with computational tools. Methods Effort-based decision-making was assessed using the Apple Gathering Task, where participants decide whether to exert effort via a grip-force device to obtain varying levels of reward; effort levels were individually calibrated and varied parametrically. We present a comprehensive computational analysis of decision-making, initially validating our model in healthy volunteers ( N = 67), before applying it in a case–control study including current ( N = 41) and remitted ( N = 46) unmedicated depressed individuals and healthy volunteers with ( N = 36) and without ( N = 57) a family history of depression. Results Four fundamental computational mechanisms that drive patterns of effort-based decisions, which replicated across samples, were identified: overall bias to accept effort challenges; reward sensitivity; and linear and quadratic effort sensitivity. Traditional model-agnostic analyses showed that both depressed groups showed lower willingness to exert effort. In contrast with previous findings, computational analysis revealed that this difference was primarily driven by lower effort-acceptance bias, but not altered effort or reward sensitivity. Conclusions This work provides insight into the computational mechanisms underlying motivational dysfunction in depression. Lower willingness to exert effort could represent a trait-like factor contributing to symptoms and a fruitful target for treatment and prevention.
Effects of ethylenediamine on the intrinsic photoresponse of PbS quantum dots
2025-01-01

We examine the intrinsic recombination dynamics of PbS quantum dots (QDs) functionalized with ethylenediamine (EDA) and compare it to that of the same QDs functionalized with ethane-1,2-dithiol (EDT).
Distinct Imaging Features of Peripheral Nerve Sheath Tumours in NF2‐Related Schwannomatosis: A Case Report
2025-01-01

Introduction Peripheral nerve sheath tumours (PNST) are an important feature of the NF2 ‐related schwannomatosis. These constitute primarily schwannomas which are characterized as nodular, solitary benign tumours of single fascicles. We here describe a pronounced, extensive, multifascicular enlargement of the right ulnar nerve and bilateral brachial plexus in a teenage patient with NF2 ‐related schwannomatosis. Neither their imaging nor the clinical characterization were consistent with classic schwannomas. Methods Within a multimodal work‐up, detailed and standardized high‐resolution nerve ultrasound was correlated to clinical, electroneurographic, and MRI findings. Follow‐up data over 2 years were provided. Results The clinical presentation of a slowly progressive, predominantly motor axonal neuropathy of the right ulnar nerve prompted a comprehensive nerve ultrasound examination, initiated by this clinically and neurophysiologically defined “sentinel” finding. Ultrasound imaging revealed an extensive, fusiform enlargement of the right ulnar nerve, as well as bilateral involvement of the brachial plexus, the latter without corresponding clinical symptoms. Subsequent genetic analysis confirmed the diagnosis of NF2‐related schwannomatosis. Discussion Signs of a mononeuropathy are a frequent manifestation of NF2 ‐related schwannomatosis in childhood. The here presented nerve imaging characteristics, however, did not correspond to classic schwannomas. The fusiform, long‐extended, multifascicular enlargement with mixed hyper‐ and hypoechogenic components on ultrasound, as well as markedly T2‐hyperintense and T1‐isointense appearance with diffuse gadolinium enhancement on MRI, is consistent with perineurioma. These mesenchymal nerve tumours have rarely been described in NF2 ‐related schwannomatosis. This association is further supported by the present case and highlights the necessity for additional peripheral nerve imaging studies in NF2‐related schwannomatosis, including the application of high‐resolution ultrasound.
The missing billions in hard sphere nucleation
2025-01-01

The crystallisation of a metastable liquid is an everyday phenomenon, yet it still presents a number of puzzles: the experimental nucleation rates of hard spheres diverge by 22 orders of magnitude from those derived from theory/simulation—why?
RHET AI. Critical Rhetoric in the Age of Artificial Intelligence
2025-01-01

This article advances a framework for a critical rhetoric of artificial intelligence by interrogating the communicative, cultural, and epistemic implications of generative AI. It contends that prevalent metaphors, particularly anthropomorphic framings and the “black box” concept, constitute discursive distortions that simultaneously mystify technical operations and legitimate problematic sociotechnical imaginaries. From a rhetorical perspective, AI-generated texts must be understood not as products of intentional agency but as probabilistic recombinations of culturally hegemonic topoï, producing persuasive surface structures that present probable arguments that are not necessarily true. Generative AI calls for a reconceptualization of authorship in terms of hybrid constellations encompassing human prompters, system developers, authors behind training corpora, and circulating agents. Situating these phenomena within the longue durée of rhetorical theory, the article demonstrates how generative AI resonates with earlier models of formulaic and topical production while simultaneously accelerating communicative processes, enabling adaptive personalization, and destabilizing shared common grounds. The analysis underscores the urgency of a rhetorical critique that foregrounds the persuasive capacities of generative AI, problematizes its cultural imaginaries, and cultivates communicative competencies necessary for navigating the transformations of discourse in algorithmically mediated publics.