Biology subjects

Horvath, D.

Publications and source records attributed to Horvath, D..

10 recordsLinked to original sources

bioRxiv2026

Thermoplastic polyurethane as a base material for soft, high-density neural interfaces

Polymers used as substrate and encapsulation for implantable devices are typically deposited layer-by-layer, leaving polymer-polymer interfaces that adhere poorly and become a critical failure point. Thermoplastic polyurethane (TPU) elastomers combine four properties not found together in any other candidate: decades of clinical use in long-term implants and availability in medical grade, a stiffness well below that of polyimide and parylene C, compatibility with microfabrication, and thermoplastic self-fusion, which removes the polymer-polymer interface entirely. This work introduces TPU as a base material for soft, high-density neural interfaces and demonstrates one route to realizing them. Gold is patterned on a sacrificial copper sheet by maskless lithography and transferred into TPU by vacuum lamination, giving conformally coated tracks down to 15 um at 30 um pitch within a single, merged polymer body. An additional electroplating step produces a nanostructured pinecone gold surface that increases the electrochemically active area of the electrodes, approximately doubling the charge injection capacity. Daisy-chain silicon chips were also embedded within the soft polymer body. The films transmit up to 88% at 470 nm, a wavelength commonly used for optogenetics. TPU showed no cytotoxicity towards differentiated SH-SY5Y cells and only a mild tissue response after 9.5 months of subcutaneous implantation in rats.

bioengineering↗

bioRxiv2026

Modular chronic cranial platform for longitudinal functional ultrasound, optical, and ECoG recording in a gyrencephalic model species

Understanding cortical function in large, gyrencephalic brains requires following the same tissue over time and interrogating it through complementary methods - yet in practice each recording modality is run on its own preparation, across separate animals and sessions that cannot be quantitatively related, while the recorded cortex can rarely be revisited. Functional ultrasound (fUS), widefield optical imaging, and electrocorticography (ECoG) are individually mature and strongly complementary, but no single preparation has combined all three within the same chronically accessible tissue in a gyrencephalic brain. Here we present a modular chronic cranial platform, validated in three cats with implants remaining functional for up to 3.3 years that unites these modalities in one customized chamber built around fUS as an anchor modality. The platform also supports fUS imaging in awake, head-unrestrained animals, with activation maps remaining spatially consistent across imaging days. By providing stable, quantitatively reproducible access to the same cortical region over time, this platform enables longitudinal, multimodal characterization of cortical function within individual subjects.

neuroscience↗

bioRxiv2026

Pharmacokinetically optimized anesthesia enables long-term functional ultrasound imaging in the cat visual cortex

Functional ultrasound imaging (fUSI) measures cerebral blood-volume responses, so anesthesia protocols developed for BOLD fMRI may not preserve its signal. We screened three fMRI-derived anesthesia regimens for visually evoked fUSI in the cat visual cortex. Isoflurane-ketamine-medetomidine produced the strongest and most consistent responses, but the standard intramuscular medetomidine bolus suppressed the signal in one sensitive cat. Pharmacokinetic modeling guided replacement of this bolus with controlled intravenous dosing, restoring the visual response while maintaining physiological stability. The same weight-based regimen produced robust responses in the other animals. In a direct within-session test, response strength was equivalent in recordings separated by more than three hours. Across 464 recordings from 51 sessions in three cats, it showed no temporal drift during follow-up extending to 23 months. Visually evoked activation also remained clear relative to a small awake dataset, although equivalence was not established. PK-guided control of medetomidine exposure therefore enables stable, repeated fUSI of the cat visual cortex over hours to years.

neuroscience↗

bioRxiv2026

Evolutionarily Conserved Amyloid Aggregation in the PACAP Peptide Family Is Controlled by Heparin-Sensitive Lys/Arg Gatekeeper Residues

Functional amyloid formation plays a central role in the storage of several peptide hormones, yet its structural basis remains poorly understood. Here, we investigate amyloid formation within class B1 GPCR-associated peptide hormones by analysing the aggregation propensity of the PACAP family. We show that five of six human PACAP-family peptides form amyloid fibrils not only within the pH range characteristic of secretory granules; however, aggregation is strictly dependent on the presence of glycosaminoglycans such as heparin. We identify conserved Arg/Lys-rich regions as key regulatory elements that act as conditional switches within the PACAP family. Experimental and molecular dynamics simulations show these residues function as aggregation gatekeepers but promote peptide self-assembly upon charge compensation by polyanionic cofactors. Although the glucagon and PACAP families diverged early in chordate evolution, we demonstrate, supported by seven amyloid-like crystal structures, that receptor-binding segments of PACAP peptides also function as aggregation-prone regions despite substantial sequence divergence from their counterparts in the glucagon family. Profiling aggregation in protochordate-derived peptides approximating the ancestral state of the superfamily, combined with sequence analysis of vertebrate PACAP-glucagon peptides, reveals that the intrinsic aggregation profile is remarkably conserved throughout evolution, even as receptor specificity diversifies.

biochemistry↗

bioRxiv2024

Design of highly potent anti-biofilm, antimicrobial peptides using explainable artificial intelligence

Antimicrobial peptides have emerged as a potential alternative to traditional small molecule antibiotics. They possess broad-spectrum efficacy and increasingly confront the challenges of bacterial resistance, especially the adaptive resistance of biofilms. However, advanced rational peptide design methods are still required to ensure optimal property profiles of such peptides, while limiting the cost of their synthesis and screening. Here we present a computational pipeline for the rational de novo design of antimicrobial and anti-biofilm peptides based on an explainable artificial intelligence (XAI) framework. The developed framework combines a Wasserstein Autoencoder (WAE) and a non-linear dimensionality reduction method termed generative topographic mapping (GTM). The WAE was used to learn the latent representation of the peptide space, while the GTM guided the generation of novel AMPs through an illustrative depiction of the latent space in the form of 2D maps. The efficacy of the peptides generated with the developed pipeline was experimentally verified by synthesis and testing for activity against methicillin resistant Staphylococcus aureus (MRSA), achieving a 100% hit rate in targeting biofilms. Notably, the most potent anti-biofilm peptide developed in this study demonstrated almost one order of magnitude improvement in IC50 value compared with the potent anti-biofilm peptide reference "1018", used as a positive control. The developed pipeline is readily extendable for the optimization of additional peptide properties, including cytotoxicity, tendency to aggregate and proteolytic stability, underscoring its potential utility for rational design of the peptide-based therapeutics.

bioinformatics↗

bioRxiv2024

Longevity of Implantable Silicon-ICs for Emerging Neural Applications: Evaluation of Bare Die and PDMS-Coated ICs After Accelerated Aging and Implantation Studies

Silicon integrated circuits (ICs) are central to the next-generation miniature active neural implants, whether packaged in soft polymers for flexible bioelectronics or implanted as bare die for neural probes. These emerging applications bring the IC closer to the corrosive body environment, raising reliability concerns, particularly for long-term clinical use. Here, we evaluated the long-term electrical and material stability of silicon-ICs from two foundries, after one-year accelerated in vitro and in vivo animal studies. The ICs featured various custom-designed test structures and were partially PDMS coated, creating two regions on each chip, uncoated "bare die" and "PDMS-coated". During the accelerated in vitro study, ICs were electrically biased and periodically monitored. Results demonstrated stable electrical performance for at least a year, suggesting that bare die ICs can function in the body for months. Despite electrical stability, material analysis revealed chemical and electrically driven degradation of the IC passivation in the bare die regions. In contrast, PDMS-coated regions revealed no such degradation, making PDMS a highly suitable encapsulant for ICs intended for years-long implantation. Based on the new insights, guidelines are proposed that may enhance the longevity of implantable ICs, significantly broadening their applications in the biomedical field.

neuroscience↗

bioRxiv2023

Assembly of sequences of Northern China alligatorweed identifies processes and gene ontologies associated with invasiveness and provides genomic resources for population and gene regulation studies

Biological invasions remain a major global challenge. Alligatorweed (Alternanthera philoxeroides (Mart.) Griseb.), native to South America, has had profound negative effects on ecosystem function and economy in Australia, North America, and Asia. It is an invasive and primarily aquatic plant that, despite a documented lack of genetic diversity, is unusually adaptive - thriving in both aquatic and terrestrial environments. However, genetic resources for studying this invasive plant are limited. Here, we have assembled the transcriptome of alligatorweed using all publicly available cDNA sequences. The resulting assembly produced over 500K contigs with an average length of [~]700 bases and an N50 of >1000 bases and contains over 100K probable gene-coding sequences. Although this assembly is slightly smaller than the previously published assembly developed from just cold-treated shoot tips, the new assembly is slightly more complete with over 95% of the conserved plant genes being represented as full length transcripts, and only 2.3% of these conserved genes being unrepresented compared to 2.7% missing in the earlier assembly. Resources from the PANTHER database were used to annotate all transcripts containing long open reading frames. Comparisons to several plant species identified gene ontologies that were over- and under-represented in the alligatorweed transcriptome including cellular transport and cytoskeletal processes and cell signaling, which could explain the high growth rate and phenotypic plasticity that make alligatorweed particularly invasive. We also sequenced and assembled a genomic database for alligatorweed using only short read technologies. This assembly produced over ten million contigs with an average length of only 300 bases and an N50 of 451 bases. However, 88% of the transcripts were represented among the genomic contigs, indicating that these contigs could serve as a source for regulatory elements for genes previously shown to be differentially expressed under various conditions. Kmer analysis indicated that 22% of the alligatorweed genome was comprised of repetitive elements. A similarity search against the plant repetitive element database indicated that long terminal repeat containing elements including copia- and gypsy-like elements made up the bulk of the transposons present in the alligatorweed genome. Additionally, we assembled and annotated a full-length chloroplast and a partial mitochondrial genome. Combined, these resources provide a source of gene sequences that should be useful for more complete genomic assemblies and for investigating gene structure and function in this particularly adaptable and invasive species. The results will provide an excellent starting point for many different investigations into the biology and ecology of alligatorweed, strengthen our understanding of the invasiveness, biology and ecology of invasive plants, and will help develop a reasonable management strategy to reduce risk and costs of the impacts.

ecology↗

bioRxiv2023

Predicting S. aureus antimicrobial resistance with interpretable genomic space maps

Increasing antimicrobial resistance (AMR) represents a global healthcare threat. Methods for rapid selection of optimal antibiotic treatment are urgently needed to decrease the spread of AMR and associated mortality. The use of machine learning (ML) techniques based on genomic data to predict resistance phenotypes serves as a solution for the acceleration of the clinical response prior to phenotypic testing. Nonetheless, many existing ML methods lack interpretability and do not implicitly incorporate visualization of the sequence space that can be useful for extracting insightful patterns from genomic data. Herein, we present a methodology for AMR prediction and visualization of sequence space based on the non-linear dimensionality reduction method {square} generative topographic mapping (GTM). This approach applied to data on AMR of >5000 S. aureus isolates retrieved from the PATRIC database yielded GTM models with reasonable accuracy for all drugs (balanced accuracy values [≥]0.75). The GTMs represent data in the form of illustrative 2D maps of the genomic space and allow for antibiotic-wise comparison of resistance phenotypes. In addition to that, the maps were found to be useful for the analysis of genetic determinants responsible for drug resistance based on the data from the PATRIC database. Overall, the GTM-based methodology is a useful tool for the illustrative exploration of the genomic sequence space and modelling AMR and can be used as a tool complementary to the existing ML methods for AMR prediction. Availabilityhttps://doi.org/10.5281/zenodo.7101559

bioinformatics↗

bioRxiv2021

HIV-1 drug resistance profiling using amino acid sequence space cartography

Human immunodeficiency virus (HIV) drug resistance is a global healthcare issue. The emergence of drug resistance demands treatment adaptation. Computational methods predicting the drug resistance profile from genomic data of HIV isolates are advantageous for monitoring drug resistance in patients. Yet, the currently existing computational methods for drug resistance prediction are either not suitable for complex mutational patterns in emerging HIV strains or lack interpretability of prediction results which is of paramount importance in clinical practice. Hence, to overcome these limitations, new approaches for the HIV drug resistance prediction combining high accuracy and interpretability are required. In this work, a new methodology for the analysis of protein sequence data based on the application of generative topographic mapping was developed and applied for HIV drug resistance profiling. It allowed achieving high accuracy of resistance predictions and intuitive interpretation of prediction results. The developed approach was successfully applied for the prediction of HIV resistance towards protease, reverse-transcriptase and integrase inhibitors and in-depth analysis of HIV resistance-inducing mutation patterns. Hence, it can serve as an efficient and interpretable tool to suggest optimal treatment regimens.

bioinformatics↗

bioRxiv2018

Why not record from every channel with a CMOS scanning probe?

It is an uninformative truism to state that the brain operates at multiple spatial and temporal scales, each with each own set of emergent phenomena. More worthy of attention is the point that our current understanding of it cannot clearly indicate which of these phenomenological scales are the significant contributors to the brains function and primary output (i.e. behaviour). Apart from the sheer complexity of the problem, a major contributing factor to this state of affairs is the lack of instrumentation that can simultaneously address these multiple scales without causing function altering damages to the underlying tissue. One important facet of this problem is that standard neural recording devices normally require one output connection per electrode. This limits the number of electrodes that can fit along the thin shafts of implantable probes generating a limiting balance between density and spread. Sharing a single output connection between multiple electrodes relaxes this constraint and permits designs of ultra-high density probes. Here we report the design and in-vivo validation of such a device, a complementary metal-oxide-semiconductor (CMOS) scanning probe with 1344 electrodes; the outcome of the European research project NeuroSeeker. We show that this design targets both local and global spatial scales by allowing the simultaneous recording of more than 1000 neurons spanning 7 functional regions with a single shaft. The neurons show similar recording longevity and signal to noise ratio to passive probes of comparable size and no adverse effects in awake or anesthetized animals. Addressing the data management of this device we also present novel visualization and monitoring methods. Using the probe with freely moving animals we show how accessing a number of cortical and subcortical brain regions offers a novel perspective on how the brain operates around salient behavioural events. Finally, we compare this probe with lower density, non CMOS designs (which have to adhere to the one electrode per output line rule). We show that an increase in density results in capturing neural firing patterns, undetectable by lower density devices, which correlate to self-similar structures inherent in complex naturalistic behaviour. To help design electrode configurations for future, even higher density, CMOS probes, recordings from many different brain regions were obtained with an ultra-dense passive probe.

neuroscience↗