Biology subjects

Yu, Y.

Publications and source records attributed to Yu, Y..

At least 235 records · Page 13Linked to original sources

bioRxiv2024

Effect of Over-expression of GRXs on Thermo and Acetic Acid Stress Tolerance of Saccharomyces cerevisiae

Ethanol production from renewable cellulosic materials is a globally significant research area. However, the high temperatures and acetic acid generated during cellulose pretreatment can inhibit Saccharomyces cerevisiae growth, reducing ethanol yields. This study investigates the impact of glutaredoxin family genes (GRXs) over-expression on S. cerevisiae cell growth and fermentation performance under thermal and acetic acid stress. Engineered strains overexpressing GRX1, GRX2, and GRX5 demonstrated enhanced growth at 42{degrees}C, while those overexpressing GRX1, GRX2, GRX6, and GRX7 showed improved growth at 1 g/L acetic acid. These results suggest that GRX over-expression can remediate S. cerevisiae, potentially accelerating advancements in green biomanufacturing.

synthetic biology↗

bioRxiv2024

Integrating Bioinformatics and Machine Learning to Investigate the Mechanisms by Which Three Major Respiratory Infectious Diseases Exacerbate Heart Failure

BackgroundHeart failure (HF) is a severe cardiovascular disease often worsened by respiratory infections like influenza, COVID-19, and community-acquired pneumonia (CAP). This study aims to uncover the molecular commonalities among these respiratory diseases and their impact on HF, identifying key mediating genes. MethodsDatasets from the GEO database were analyzed for differential expression to find common molecular features of the three respiratory diseases. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify gene modules associated with HF. GO and KEGG enrichment analyses determined the biological processes and pathways involved in HF exacerbation by respiratory diseases. Key genes were screened using LASSO, RF, and SVM-RFE machine learning algorithms, with accuracy validated by ROC curves. Single-sample GSEA (ssGSEA) was performed, and the Drug Signature Database (DSigDB) was used for drug prediction. Immune infiltration analysis was conducted using CIBERSORT. ResultsWe identified 51 characteristic genes of respiratory diseases and 10 potential genes exacerbating HF, primarily involved in innate immune response, inflammation, and coagulation pathways. Machine learning algorithms identified RSAD2 and IFI44L as key genes with high accuracy (AUC > 0.7). ssGSEA indicated RSAD2s involvement in complement and coagulation cascades, while IFI44L is associated with myocardial contraction in HF progression. DSigDB predicted six potential therapeutic drugs. Immune infiltration analysis revealed significant differences in eight immune cell types between HF patients and healthy controls. ConclusionOur findings enhance the understanding of molecular interactions between respiratory diseases and heart failure, paving the way for future research and therapeutic strategies.

bioinformatics↗

bioRxiv2024

Prime editor-based high-throughput screening reveals functional synonymous mutations in the human genome

Synonymous mutations are generally considered neutral, while their roles in the human genome remain largely unexplored. Herein, we employed the PEmax system to create a library of 297,900 epegRNAs and performed extensive screening to identify synonymous mutations that impact cell fitness. While most synonymous mutations are neutral, we found that some can elicit phenotypic effects. By developing a specialized machine learning tool, we uncovered their impact on various biological processes such as mRNA splicing and transcription, supported by multifaceted experimental evidence. Notably, synonymous mutations can alter RNA folding and affect translation, as demonstrated by PLK1_S2. By integrating screening data with our model, we successfully predicted clinically deleterious synonymous mutations. This research deepens our understanding of synonymous mutations and provides insights for clinical disease studies.

genetics↗

bioRxiv2024

Comparative transcriptome profiling identifies stage-specific phasiRNAs and co-expressed Argonaute genes in Bambusoideae and Pooideae species

PhasiRNAs (phased, small interfering RNAs) play a crucial role in supporting male fertility in grasses. Earlier work in maize (Zea mays) and rice (Oryza sativa) - and subsequently many other plant species - identified premeiotic 21-nt and meiotic 24-nt phasiRNAs. More recently, a group of premeiotic 24-nt phasiRNAs were discovered in the anthers of two Pooideae species, barley (Hordeum vulgare) and bread wheat (Triticum aestivum). The conservation of premeiotic 24-nt phasiRNAs and other classes of reproductive phasiRNAs across Pooideae species remains unclear. We conducted a comparative RNA profiling of three anther stages in six Pooideae species and one Bambusoideae species. We observed complex temporal accumulation patterns of 21-nt and 24-nt phasiRNAs in Pooideae and Bambusoideae grasses. In Bambusoideae, 21-nt phasiRNAs accumulated during meiosis, whereas 24-nt phasiRNAs were present in both premeiotic and postmeiotic stages. We identified premeiotic 24-nt phasiRNAs in all seven species examined. These phasiRNAs exhibit distinct biogenesis mechanisms and potential Argonaute effectors compared to meiotic 24-nt phasiRNAs. We show that specific Argonaute genes co-expressed with stage-specific phasiRNAs are conserved across Bambusoideae and Pooideae species. Our degradome analysis identified a set of conserved miRNA target genes across species, while 21-nt phasiRNAs targets were species-specific. Cleavage of few targets was observed for 24-nt phasiRNAs.

plant biology↗

bioRxiv2024

Trajectory-centric Framework TrajAtlas reveals multi-scale differentiation heterogeneity among cells, genes, and gene module in osteogenesis

Osteoblast differentiation is crucial for bone formation and maintaining skeletal integrity. Although it is now understood that this process exhibits significant heterogeneity across developmental stages and tissue microenvironments, the underlying mechanisms remain largely unexplored. In the present study, we introduce TrajAtlas, a comprehensive framework that addresses this gap in knowledge. TrajAtlas comprises four modules: a reference atlas (Differentiation Atlas), a differentiation model (Differentiation Model), a tool for differential pseudotime analysis (TrajDiff), and a method for pseudotemporal gene module detection (TRAVMap). By leveraging single-cell technologies, TrajAtlas offers a systematic approach to exploring the multi-scale heterogeneity among cells, genes, and gene modules within population-level trajectories across diverse tissues and age groups. We systematically investigate the impact of age and injury on osteogenesis, providing new insights into osteoporosis and bone regeneration. In conclusion, our comprehensive framework offers novel insights into osteogenesis and provides a valuable resource for understanding the complexities of bone formation. Author SummaryOsteoblasts, the cells responsible for bone formation, can originate from various cellular sources. However, its unclear how different progenitor cells differentiate into osteoblasts, and how this process is influenced by factors such as age and tissue location. This knowledge gap stems from the lack of comprehensive databases and tools to decipher the differentiation process. In this study, we introduce TrajAtlas, a comprehensive framework designed to bridge this gap. To explore the cellular origins of osteoblasts, we constructed an atlas centered on osteogenesis. To answer how progenitor cells differentiate to osteoblasts, we developed a model that reveals the dynamic regulatory landscape during this process. To elucidate the influence of age and tissue location on differentiation, we built a tool for differential analysis. Furthermore, to identify conserved patterns of differentiation, we developed an approach to detect pseudotemporal gene modules. We validated the effectiveness of this framework by applying it to more datasets, unveiling novel cell states associated with injury. Notably, this framework focuses on dynamic processes, with the potential for broader applications in studying cell differentiation and complementing cell-centric analyses.

bioinformatics↗

bioRxiv2024

AptaGPT: Advancing aptamer design with a generative pre-trained language model

Aptamers, synthetic oligonucleotide ligands, have shown significant promise for therapeutic and diagnostic applications owing to their high specificity and affinity for target molecules. However, the conventional Systematic Evolution of Ligands by Exponential Enrichment (SELEX) for aptamer selection is time-consuming and often yields limited candidates. To address these limitations, we introduce AptaGPT, a novel computational strategy that leverages a Generative Pre-trained Transformer (GPT) model to design and optimize aptamers. By training on SELEX data from early rounds, AptaGPT generated a diverse array of aptamer sequences, which were then computationally screened for binding using molecular docking. The results of this study demonstrated that AptaGPT is an effective tool for generating potential high-affinity aptamer sequences, significantly accelerating the discovery process and expanding the potential for aptamer research. This study showcases the application of generative language models in bioengineering and provides a new avenue for rapid aptamer development.

bioinformatics↗

bioRxiv2024

Immunopipe: A comprehensive and flexible scRNA-seq and scTCR-seq data analysis pipeline

Single-cell sequencing technologies provide us with information at the level of individual cells. The combination of single-cell RNA-seq and single-cell TCR-seq profiling enables the exploration of cell heterogeneity and T-cell receptor repertoires simultaneously. The integration of both types of data can play a crucial role in enhancing our understanding of T-cell-mediated immunity and, in turn, facilitate the advancement of immunotherapy. Here, we present immunopipe, a comprehensive and flexible pipeline to perform integrated analysis of scRNA-seq and scTCR-seq data. In addition to the command line tool, we provide a user-friendly web interface for pipeline configuration and execution monitoring, benefiting researchers without extensive programming experience. With its comprehensive functionality and ease of use, immunopipe empowers researchers to uncover valuable insights from scRNA-seq and scTCR-seq data, ultimately advancing the understanding of immune responses and immunotherapy development.

bioinformatics↗

bioRxiv2024

IFDlong: an isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data

Advancements in long-read transcriptome sequencing (long-RNA-seq) technology have revolutionized the study of isoform diversity. These full-length transcripts enhance the detection of various transcriptome structural variations, including novel isoforms, alternative splicing events, and fusion transcripts. By shifting the open reading frame or altering gene expressions, studies have proved that these transcript alterations can serve as crucial biomarkers for disease diagnosis and therapeutic targets. In this project, we proposed IFDlong, a bioinformatics and biostatistics tool to detect isoform and fusion transcripts using bulk or single-cell long-RNA-seq data. Specifically, the software performed gene and isoform annotation for each long-read, defined novel isoforms, quantified isoform expression by a novel expectation-maximization algorithm, and profiled the fusion transcripts. For evaluation, IFDlong pipeline achieved overall the best performance when compared with several existing tools in large-scale simulation studies. In both isoform and fusion transcript quantification, IFDlong is able to reach more than 0.8 Spearmans correlation with the truth, and more than 0.9 cosine similarity when distinguishing multiple alternative splicing events. In novel isoform simulation, IFDlong can successfully balance the sensitivity (higher than 90%) and specificity (higher than 90%). Furthermore, IFDlong has proved its accuracy and robustness in diverse in-house and public datasets on healthy tissues, cell lines and multiple types of diseases. Besides bulk long-RNA-seq, IFDlong pipeline has proved its compatibility to single-cell long-RNA-seq data. This new software may hold promise for significant impact on long-read transcriptome analysis. The IFDlong software is available at https://github.com/wenjiaking/IFDlong.

bioinformatics↗

bioRxiv2024

Omicron-specific naive B cell maturation alleviates immune imprinting induced by SARS-CoV-2 inactivated vaccine

SARS-CoV-2 ancestral strain-induced immune imprinting poses great challenges to vaccine updates. Studies showed that repeated Omicron exposures could override immune imprinting induced by inactivated vaccines but not mRNA vaccines, a disparity yet to be understood. Here, we analyzed the underlying mechanism of immune imprinting alleviation in inactivated vaccine (CoronaVac) cohorts. We observed in CoronaVac-vaccinated individuals who experienced BA.5/BF.7 breakthrough infection (BTI), the proportion of Omicron-specific memory B cells (MBCs) substantially increased after an extended period post-Omicron BTI, with their antibodies displaying enhanced somatic hypermutation and neutralizing potency. Consequently, the neutralizing antibody epitope distribution encoded by MBCs post-BA.5/BF.7 BTI after prolonged maturation closely mirrors that in BA.5/BF.7-infected unvaccinated individuals. Together, these results indicate the activation and expansion of Omicron-specific naive B cells generated by first-time Omicron exposure helped to alleviate CoronaVac-induced immune imprinting, and the absence of this process should have caused the persistent immune imprinting seen in mRNA vaccine recipients. HighlightsO_LILongitudinal MBC profiling of CoronaVac-vaccinated individuals following BA.5 BTI C_LIO_LIOmicron-specific MBC proportion rises greatly after extended period post-BA.5 BTI C_LIO_LIOmicron-specific naive B cell maturation reduces ancestral strain immune imprinting C_LI

immunology↗

bioRxiv2024

Multivalent Targeting of Blood-Brain Barrier LRP1 for Neurovascular Recovery Therapy for Alzheimer s Disease

The blood-brain barrier (BBB) is a highly selective permeability barrier that safeguards the central nervous system (CNS) from potentially harmful substances while regulating the transport of essential molecules. Its dysfunction is increasingly recognized as a pivotal factor in the pathogenesis of Alzheimers disease (AD), contributing to the accumulation of amyloid-{beta} (A{beta}) plaques. We propose an AD therapeutic strategy targeting the BBB low-density lipoprotein receptor-related protein 1 (LRP1). We show that a multivalent scaffold with LRP1-specific peptide modulates the A{beta} transport at the BBB. We show via detailed experimentation on AD model mice that this intervention markedly reduces A{beta} deposits and prevents cognitive decline. This study marks a new approach to drug design, combining multivalent targeting with the regulation of membrane trafficking through advanced molecular engineering. Crucially, the therapeutic effects emerge from the multivalent nature of our proposed system. Furthermore, our findings underscore the paramount significance of the BBB in AD pathogenesis, particularly emphasizing the critical role of LRP1-mediated A{beta} clearance in mitigating disease progression.

neuroscience↗

bioRxiv2024

Massively parallel interrogation of human functional variants modulating cancer immunosurveillance

Anti-PD-1/PD-L1 immune checkpoint blockade (ICB) therapy has revolutionized clinical cancer treatment, while abnormal PD-L1 or HLA-I expression in patients can significantly impact the therapeutic efficacy. Somatic mutations in cancer cells that modulate these critical immune regulators are closely associated with tumor progression and ICB response. However, a systematic interpretation of cancer immune-related mutations is still lacking. Here, we harnessed the ABEmax system to establish a large-scale sgRNA library encompassing approximately 820,000 sgRNAs that target all feasible Serine/Threonine/Tyrosine residues across the human genome, which systematically unveiled thousands of novel mutations that decrease or augment PD-L1 or HLA-I expression. Notably, we revealed functional mutations that co-regulate PD-L1 and HLA-I expression, represented by the clinically relevant mutation SETD2_Y1666, and verified that it can benefit from immunotherapy in vivo. Our findings generate an unprecedented resource of functional residues regulating cancer immunosurveillance, meanwhile, offer valuable guidance for clinical diagnosis, ICB therapy, and the development of innovative drugs in cancer treatment.

cancer biology↗

bioRxiv2024

Utility Analyses of AVITI Sequencing Chemistry

BackgroundDNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist. ResultsHere, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences AVITI and Illuminas NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illuminas NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate. ConclusionThese results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

genomics↗

bioRxiv2024

Humoral immunogenicity comparison of XBB and JN.1 in human infections

The continuous evolution of SARS-CoV-2, particularly the emergence of the BA.2.86/JN.1 lineage replacing XBB lineages, necessitates re-evaluation of current vaccine compositions. Here, we provide a comprehensive analysis of the humoral immune response to XBB and JN.1 human exposures, emphasizing the need for JN.1-lineage-based boosters. We demonstrate the antigenic distinctiveness of XBB and JN.1 lineages in SARS-CoV-2-naive individuals but not in those with prior vaccinations or infections, and JN.1 infection elicits superior plasma neutralization titers against its subvariants. We highlight the strong immune evasion and receptor binding capability of KP.3, supporting its foreseeable prevalence. Extensive analysis of the BCR repertoire, isolating [~]2000 RBD-specific monoclonal antibodies (mAbs) with their targeting epitopes characterized by deep mutational scanning (DMS), underscores the systematic superiority of JN.1-elicited memory B cells (MBCs). Notably, Class 1 IGHV3-53/3-66-derived neutralizing antibodies (NAbs) contribute majorly within wildtype (WT)-reactive NAbs against JN.1. However, KP.2 and KP.3 evade a substantial subset of them, even those induced by JN.1, advocating for booster updates to KP.3 for optimized enrichment. JN.1-induced Omicron-specific antibodies also demonstrate high potency across all Omicron lineages. Escape hotspots of these NAbs have mainly been mutated in Omicron RBD, resulting in higher immune barrier to escape, considering the probable recovery of previously escaped NAbs. Additionally, the prevalence of broadly reactive IGHV3-53/3-66- encoding antibodies and MBCs, and their capability of competing with all Omicron-specific NAbs suggests their inhibitory role on the de novo activation of Omicron-specific naive B cells, potentially explaining the heavy immune imprinting in mRNA-vaccinated individuals. These findings delineate the evolving antibody response to Omicron antigenic shift from XBB to JN.1, and highlight the importance of developing JN.1 lineage, especially KP.3-based vaccine boosters, to enhance humoral immunity against current and future SARS-CoV-2 variants.

immunology↗

bioRxiv2024

Dose-Efficient Cryo-Electron Microscopy for Thick Samples using Tilt-Corrected Scanning Transmission Electron Microscopy, Demonstrated on Cells and Single Particles

Cryo-EM is a powerful tool in structural biology, providing insights through techniques like single-particle analysis (SPA) and cryogenic electron tomography (cryo-ET). In thick specimens, challenges arise as an exponentially larger fraction of the transmitted electrons lose energy from inelastic scattering and can no longer be properly focused as a result of chromatic aberrations in the post-specimen optics. Rather than filtering out the inelastic scattering at the price of reducing potential signal, as is done in energy-filtered transmission electron microscopy (EFTEM), we show how a dose-efficient and unfiltered image can be rapidly obtained using tilt-corrected bright-field scanning-TEM (tcBF-STEM) data collected on a pixelated detector. Enhanced contrast and a 3-5x improvement in collection efficiency are observed for 2D images of intact bacterial cells and large organelles using tcBF-STEM compared to EFTEM for thicknesses beyond 500 nm. As a proof of concept for the techniques performance in structural determination, we present an SPA map at subnanometer resolution for a highly symmetric virus-like particle (VLP) with 789 particles. These findings suggest applications for tcBF-STEM in cryo-EM of thicker cellular volumes where current approaches struggle.

cell biology↗

bioRxiv2024

A generalized framework to identify SARS-CoV-2 broadly neutralizing antibodies

Monoclonal antibodies (mAbs) targeting the SARS-CoV-2 receptor-binding domain (RBD) are used to treat and prevent COVID-19. However, the rapid evolution of SARS-CoV-2 drives continuous escape from therapeutic mAbs. Therefore, the ability to identify broadly neutralizing antibodies (bnAbs) against future variants is needed. Here, we use deep mutational scanning (DMS) to predict viral RBD evolution and to select for mAbs neutralizing both existing and prospective variants. A retrospective analysis of 1,103 SARS-CoV-2 wildtype-elicited mAbs shows that this method can increase the probability of identifying effective bnAbs against the XBB.1.5 strain from 1% to 40% in an early pandemic setup. Among these bnAbs, BD55-1205 exhibited potent activity against all tested variants. Cryo-EM structural analyses revealed the receptor mimicry of BD55-1205, explaining its broad reactivity. Delivery of mRNA-LNPs encoding BD55-1205-IgG in mice resulted in ~5,000 serum NT50 against XBB.1.5, HK.3.1, and JN.1 variants. Combining bnAb identification using viral evolution prediction with the versatility of mRNA delivery technology can enable rapid development of next-generation antibody-based countermeasures against SARS-CoV-2 and potentially other pathogens with pandemic potential.

immunology↗

bioRxiv2024

Random adversarial threshold search enables automated DNA screening

Custom DNA synthesis underpins modern biology, but controlled genes in the wrong hands could threaten many lives and public trust in science. In .1992, a virology-trained mass murderer tried and failed to obtain physical samples of Ebola; today, viruses can be assembled from synthetic DNA fragments. Screening orders for controlled sequences is unreliable and expensive because current similarity search algorithms yield false alarms requiring expert human review. Exact-match search can achieve perfect specificity among short known sequences by detecting subsequences unique to controlled genes, but can be trivially evaded by incorporating mutations. Here we rescue exact-match search by additionally screening for predicted functional variants of pseudo-randomly chosen subsequences that arent found in known unregulated genes. To experimentally assess robustness, we protected nine windows from the M13 bacteriophage virus, then invited a "red team" to launch up to 21,000 attacks at each window and measure the fitness of their designed mutants. We identified defensible windows from regulated pathogens, built a test database that our experiments indicate will block 99.999% of functional attacks, and verified its sensitivity against redesigned enzymes. Exact-match search with functional variant prediction offers a promising way to safeguard biotechnology by automating DNA synthesis screening. SummarySearching for exact matches to pre-computed functional variants unique to controlled genes enables sensitive, secure, and automated DNA synthesis screening.

synthetic biology↗

bioRxiv2024

Emergence of Orientation Pinwheels in a Self-Evolving Spiking Neural Network: Enhancing Visual Coding Efficiency and Reliability

Orientation preference maps (OPMs) in the primary visual cortex of primates organize orientation-tuned neurons into columnar structures, forming pinwheel-like patterns. However, lower-level animals like rodents typically exhibit a lack of OPMs, with neurons either randomly distributed or aggregated in small clusters. This distinction prompts an inquiry into whether more structured cortical columns correlate with improved visual computational or coding efficiency. To explore this, we propose a novel self-evolving spiking neural network (SESNN). To the best of our knowledge, the SESNN is the first spiking network, incorporating mechanisms of neural plasticity in forming neural connections without explicit objective functions. We reveal that the emergence of pinwheel structures is primarily driven by sparse coding constraints and local synaptic plasticity as fundamental mechanisms. Second, for higher mammals with expansive iso-orientation domains (IODs), the firing responses in pinwheel structures primarily emanate from pinwheel centers (PCs) and progressively extend toward the periphery, encompassing adjacent IODs. Third, the size and organization of these IODs across species are significantly influenced by the receptive fields ability to process overlapping visual information. Lastly, PCs within large IODs demonstrate enhanced robustness and population sparseness in detecting a variety of orientation features. These results indicate that the spatial pinwheel structure facilitates highly efficient and reliable coding performance.

neuroscience↗

bioRxiv2024

The Functional Role of Pinwheel Topology in the Primary Visual Cortex of High-Order Animals for Complex Natural Image Representation

The primary visual cortex (V1) of high-level animals exhibits a complex organization of neuronal orientation preferences, characterized by pinwheel structure topology, yet the functional role of those complex patterns in natural image representation remains largely unexplored. Our study first establishes a new self-evolving spiking neural network (SESNN) model, designed to mimic the functional topological structure of orientation selectivity within V1. We observe the emergence of a particularly new "spread-out" firing patterns from center to the surround of the pinwheel structures in response to natural visual stimuli in pinwheel structures, propagating from pinwheel centers and spreading to iso-orientation domains--a pattern not found in salt- and-pepper organizations. To investigate this phenomenon, we propose a novel deep recurrent U-Net architecture to reconstruct images from V1s spiking activity across time steps and assess the encoded information entropy of different firing patterns via the models predicted uncertainty, offering a spatiotemporal analysis of V1s functional structures. Our findings reveal a trade-off between visual acuity and coding time: the "spread-out" pattern enhances the representation of complex visual details at the cost of increased response latency, while salt-and-pepper organizations, lacking such domains, prioritize rapid processing at the expense of reduced visual acuity. Additionally, we demonstrate that this trade-off is modulated by the size of iso-orientation domains, with larger domains--supported by denser neuronal populations--substantially improving both visual acuity, coding efficiency, and robustness, features diminished in smaller domains and salt-and-pepper arrangements. Our research provides a foundational understanding of the principles underlying efficient visual information representation and suggests novel strategies for advancing the robustness and performance of image recognition algorithms in artificial intelligence.

neuroscience↗