Biology subjects

Kahl, E.

Publications and source records attributed to Kahl, E..

3 recordsLinked to original sources

bioRxiv2026

Ferulic acid eicosyl ester enhances cognitive flexibility and modulates arousal-related neural circuits in mice

Cognitive deficits are a major contributor to disability in numerous neuropsychiatric and neurodegenerative disorders, yet effective pharmacological treatments remain limited. Ferulic acid eicosyl ester (FAE-20), a natural constituent of the plant Rhodiola rosea, has previously been identified as an enhancer of simple forms of Pavlovian conditioning in flies, bees, and mice. Here, we investigated whether FAE-20 has further potential to enhance cognitive flexibility, working memory, or spatial learning in mice, and explored potential neurobiological mechanisms underlying such enhancement. Cognitive flexibility was assessed using the attentional set-shifting task (ASST). Subchronic FAE-20 treatment significantly improved ASST performance in both male and female young adult mice, indicating enhanced cognitive flexibility. In contrast, no effects were observed on spatial working memory, assessed by spontaneous alternations in the Y-maze, or on spatial learning in the Barnes maze in either young or aged mice. Notably, FAE-20 enabled spatial learning in the Barnes maze in a subgroup of aged mice that failed to learn the task under vehicle treatment. Histological analyses using c-Fos immunohistochemistry as a marker of neural activity and doublecortin expression and spine density as markers of hippocampal plasticity revealed sex-specific effects on components of the ascending arousal system. FAE-20 increased the activation of orexinergic neurons in the lateral hypothalamus of male mice, whereas it reduced the activity of cholinergic neurons in the laterodorsal tegmental nucleus of females. No effects were detected on hippocampal neurogenesis or dendritic spine density. These findings suggest that the cognitive effects of FAE-20 are selective, depending on the cognitive demands of the task and the baseline cognitive abilities of the animals, and may be mediated, at least in part, by modulation of arousal-related neural circuits. HighlightsO_LIFAE-20 enhanced cognitive flexibility in young adult mice C_LIO_LIEffects of FAE-20 were strongest in demanding cognitive tasks C_LIO_LIAged poor learners benefited from FAE-20 treatment C_LIO_LIFAE-20 activated hypothalamic orexin neurons in male mice C_LIO_LIFAE-20 modulated ascending arousal systems in a sex-specific manner C_LI

neuroscience↗

bioRxiv2026

ProtSpace: Protein Universe in Your Browser

AO_SCPLOWBSTRACTC_SCPLOWProtein Language Models (pLMs) generate per-protein embeddings that encode functional, structural, and evolutionary information, yet the relationships captured in these representations remain difficult to explore systematically. ProtSpace (https://protspace.app) is a web application for interactive visualization of pLM embedding spaces, enabling hypothesis generation directly in the browser without installation. Unlike traditional network-based tools that exclusively visualize amino acid sequence similarity, ProtSpace explores embedding spaces, revealing relationships often not captured by traditional comparisons. Users provide protein sequences or pre-computed embeddings through a Google Colab notebook or the Python CLI; the pipeline applies dimensionality reduction, retrieves 38 annotation types spanning UniProt, InterPro, NCBI Taxonomy, TED structural domains, and sequence-based predictors served via Biocentral, and produces a portable binary file for the browser-based viewer. WebGL-accelerated rendering supports interactive exploration of over 570,000 proteins. Distinctive features include per-point pie charts for multi-label annotations and integrated 3D structure viewing through AlphaFold2 predictions. All computation happens on the users machine, ensuring data privacy. We demonstrate the utility of ProtSpace through a progressive zoom-in across biological scales: from global proteome organization of Swiss-Prot, through cross-species comparison revealing conserved and lineage-specific families, to functional hypothesis generation within the beta-lactamase superfamily. ProtSpace is freely available at https://protspace.app under the Apache 2.0 license. KO_SCPLOWEYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWPOINTSC_SCPLOWO_LIProtSpace is a free, open-source web application that visualizes protein Language Model (pLM) embeddings as interactive maps, scaling to 570,000 proteins entirely client-side. C_LIO_LIA zero-installation Google Colab notebook and a Python CLI prepare visualization-ready bundles from FASTA files, UniProt queries, or pre-computed HDF5 embeddings, automatically retrieving 38 annotation types from five sources (UniProt, InterPro, NCBI Taxonomy, TED structural domains, and Biocentral sequence predictors) alongside custom CSV metadata. C_LIO_LIApplication examples demonstrate that embedding visualizations generate testable biological hypotheses at multiple scales, from proteome-wide organization through species-level comparison to family-level functional discovery, and that these are complementary to traditional sequence-based analyses. C_LI

bioinformatics↗

bioRxiv2024

Koina: Democratizing machine learning for proteomics research

Recent developments in machine-learning (ML) and deep-learning (DL) have immense potential for applications in proteomics, such as generating spectral libraries, improving peptide identification, and optimizing targeted acquisition modes. Although new ML/DL models for various applications and peptide properties are frequently published, the rate at which these models are adopted by the community is slow, which is mostly due to technical challenges. We believe that, for the community to make better use of state-of-the-art models, more attention should be spent on making models easy to use and accessible by the community. To facilitate this, we developed Koina, an open-source containerized, decentralized and online-accessible high-performance prediction service that enables ML/DL model usage in any pipeline. Using the widely used FragPipe computational platform as example, we show how Koina can be easily integrated with existing proteomics software tools and how these integrations improve data analysis.

bioinformatics↗