Biology subjects

Le, L.

Publications and source records attributed to Le, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Human brain white matter charts in international populations

Brain charts provide normative references for identifying neurodevelopmental milestones and clinically meaningful deviations. Existing white matter (WM) charts are derived predominantly from European and North American populations, limiting generalizability. Here, we established the first set of population-specific WM charts of 198 morphological and microstructural phenotypes for both Chinese (N=19,215) and Western (N=15,584) populations across the human lifespan. Developmental trajectories and spatial organization of WM maturation and degeneration were broadly conserved across the populations, whereas maturational timing varied across pathways and metrics. The Chinese population showed earlier maturation in several projection and sensorimotor pathways, but more protracted maturation in higher-order association and limbic pathways. Chinese population-matched charts more accurately predicted WM phenotypes and detected more extreme disease-related deviations in brain health in the Chinese population than Western-derived models. Individual deviation patterns further discriminated patients from healthy controls and predicted cognitive performance and plasma biomarkers. Our findings reveal population-specific WM maturation and show that reference-population mismatch can reduce the accuracy and clinical sensitivity of normative brain charts.

neuroscience↗

bioRxiv2026

Independent noise realizations enable morphologically agnostic image reconstruction in single-photon-sensitive microscopy

Advances in single-photon sensitive detectors are rapidly expanding the adoption of photon-counting fluorescence microscopy. Under the Poisson photon-counting statistics, iterative Richardson-Lucy (RL) -type algorithms are statistically optimal for image deconvolution but suffers from a fundamental semi-convergent behaviour: prolonged iterations inevitably amplify noise, requiring heuristic early stopping or regularisation typically based on assumptions about object morphology. Here we present a morphology-agnostic regularisation framework for RL deconvolution that exploits independent noise realisations instead of structural object priors. Preserving the Poisson statistics of the acquisition process, we formulate the Regularized by Noise (RbN): a regularized variational framework and its corresponding iterative minimization algorithm that exploit the statistical consistency of independent noise realisations to distinguish reproducible image features from stochastic noise. The regularisation strength is selected automatically using the Poisson residual whiteness principle, resulting in a fully data-driven reconstruction without heuristic parameter tuning. Photon-timing-resolved systems naturally provide the independent noise realisations exploited by our framework, whereas computational photon splitting provides a statistically equivalent implementation for photon-counting systems. We validate the approach experimentally using photon-timing-resolved confocal microscopy and image scanning microscopy across eight morphologically distinct subcellular targets, and further demonstrate its applicability to photon-counting microscopes through computational photon splitting. Across imaging modalities, detector technologies, biological structures and signal-to-noise regimes, our method eliminates RL semi-convergence, removes sensitivity to the stopping criterion, and consistently outperforms conventional RL while preserving fine structural detail. More broadly, our results establish independent noise realisations as a general source of morphology-agnostic regularisation. Although demonstrated here for SPAD-based laser-scanning microscopy and Poisson statistics, the underlying principle could be extended to other imaging modalities and, more generally, to statistical inverse problems through appropriate noise-specific formulations.

biophysics↗

bioRxiv2026

Age dependent collective trafficking of tissue resident T cells in zebrafish

How tissue-resident T cells are organized to provide immune surveillance in healthy peripheral tissues and how this organization changes with age remains largely unknown. Here we use intravital imaging in zebrafish to identify a previously undescribed, appendage-specific mode of adaptive immune organization: fin-resident T cells undergo coordinated collective "streaming" migration within connective tissue compartments. T cells colonize the developing fin prior to lymphatic or blood vessel formation, indicating that initial residency can be established independently of classical immune conduits. However, collective streaming is not immediate; it emerges during juvenile maturation, coincident with maturation of fin architecture, and is restricted to T cells rather than other leukocyte populations. After fin amputation, young adults restore streaming within regenerated tissue once spatial compartments are re-established, whereas middle-aged fish following thymic involution repopulate the fin yet fail to promptly recover coordinated streaming and show broader tissue dispersion and altered motility in comparable times. Transcriptomic profiling across ages, regenerative states, and immune-altered microenvironments reveals coupled regulation of stromal remodeling programs and antigen presentation pathways, including differential expression of MHC class I and II components with strong microenvironmental dependence. These data define an age-regulated, tissue-instructed program that organizes resident T cell dynamics and immune potential in situ, providing a framework for understanding how tissue specific stromal environments constrain immune surveillance. Significance StatementT cells patrol most organs, but we know surprisingly little about how they are arranged inside healthy tissues over an animals lifetime. By imaging zebrafish in vivo, we discovered that fin-resident T cells do not move independently: they organize into coordinated "streams" that migrate collectively through fin connective tissue. This collective behavior appears during juvenile maturation, re-forms after regeneration in young adults, and is delayed or disrupted in older fish as age-related thymus decline reduces new T cell production. In parallel, aging and the tissue microenvironment reshape the expression of genes involved in antigen presentation. These results reveal a tissue-specific, age-regulated architecture for adaptive immune surveillance that links aging to impaired immune organization during regeneration.

developmental biology↗

bioRxiv2026

Population structure of the rice blast fungus Pyricularia oryzae in the context of elevated host heterogeneity

In a context where pathogen emergence threatens global food security, crop resistance to pathogens is crucial for preventing and controlling epidemics. Agrosystems with high intraspecific cultivated diversity are expected to better mitigate infectious diseases compared with homogeneous ones. However, the long-term impact of cultivated genotypic heterogeneity on pathogen populations is still under debate. The 1,300-year-old traditional agrosystem of the Yuanyang Terraces (YYT) in China exhibits an outstanding level of rice diversity. The rice blast fungus Pyricularia oryzae has been recorded in the area, making this area ideal for studying the impact of long term heterogeneous cultivation on plant-pathogen coevolution. In this study, we analysed 94 P. oryzae genomes from the YYT and compared them to 198 genomes representative of the worldwide diversity. We report elevated levels of genomic diversity of P. oryzae in the YYT. Whereas the worldwide diversity of this species is organized in four lineages, we detected seven lineages within the YYT, four of which are restricted to this area. The sampling dates of the YYT isolates (2009 to 2017) provided sufficient temporal signal to date nodes of the phylogenetic tree of isolates. Endemic lineages appeared to have arisen several centuries ago but later than the origin of the YYT themselves. We also detected recent introductions of worldwide lineages. Linkage disequilibrium analyses and in vitro cross experiments suggest that P. oryzae reproduces asexually in the YYT. These results suggest that long-term intraspecific crop diversity in the YYT has promoted the emergence and maintenance of a highly diverse, locally adapted pathogen population.

evolutionary biology↗

bioRxiv2026

Ageing blunts the phospho-proteomic response to resistance exercise in humans

Ageing blunts the adaptive growth response in human skeletal muscle. To define the molecular processes underlying this impairment, we performed unbiased analysis of the phosphoproteome and total proteome in healthy young and old human skeletal muscle following acute resistance exercise (ResEX) and essential amino acid (EAA) ingestion. Ageing led to global suppression of the growth-induced global phosphoproteome, despite intact mTORC1 activation in old muscle. Our results identify widespread effects of ageing on skeletal muscle growth and highlight novel pathways for therapeutic development in aged skeletal muscle.

physiology↗

bioRxiv2026

On improving experimental binding affinity predictions with synthetic data

The success of deep learning binding affinity prediction models depends critically on expanding experimental data with reliable synthetic data. We extend the Structurally Augmented IC50 Repository (SAIR) with {approx}80K absolute free energy perturbation (AFEP) calculations and present two distinct data splits, SAIR-FEP and SAIR-OOD (out-of-distribution), to simulate realistic drug discovery scenarios. We compare sequence-based proteochemometric (PCM) models and state-of-the-art, structure-based deep learning models and demonstrate that PCM models can be enhanced by physics-based descriptors. While structure-based deep learning methods capture finer geometric detail, their performance is highly sensitive to the input structure. By filtering for high-confidence, co-folded complexes, we show that the performance improves predictably, whereas training on all complexes blindly does not yield performance gains. Finally, using the SAIR-OOD split, we demonstrate that simultaneous training on synthetic and experimental data improves performance on publicly available, experimental benchmarks. These results provide a clear strategy for using synthetic data to advance experimental binding affinity predictions.

molecular biology↗

bioRxiv2026

Characterization of effects of a neurotropic murine coronavirus infection on Alzheimer's disease neuropathology of 5xFAD mice

BackgroundRecent studies revealed key immunological mechanisms within the central nervous system (CNS) that contribute to Alzheimers disease pathology. Additionally, analyses of human AD datasets have also associated viral encephalitis exposure (i.e., viral-induced neuroinflammation) with the development of AD and dementia, highlighting the need to better understand how viral encephalitis and neuroimmune mechanisms within the brain may impact AD pathologies such as A{beta} plaque deposition. Intracranial infection of susceptible mice with the neurotropic JHM strain of murine coronavirus (JHMV) results in acute encephalomyelitis characterized by viral infection of glia and a robust inflammatory response comprised of monocytes/macrophages and T cells that aid in controlling viral replication. MethodsTo determine how coronavirus-induced encephalitis may impact established A{beta} plaque deposition, we intracranially inoculated JHMV into aged 5xFAD model of amyloidosis. We utilize immunohistochemical and biochemical analysis to assess the impact on existing A{beta} pathology. We also utilize spatial transcriptomic imaging to explore how viral encephalitis affects cellular responses to plaque pathology with single-cell resolution. ResultsIn aged 5xFAD mice, JHMV-induced encephalitis at 12 days p.i. resulted in minimal changes to overall A{beta} protein within the brain. However, viral encephalitis induces CD4+ and CD8+ T cell infiltration and more Lgals3/MAC2-expressing macrophages surrounding dense-core A{beta} plaques, which appear more compacted in JHMV-infected 5xFAD brains compared to uninfected 5xFAD controls. We compared gene expression within JHMV-infected 5xFAD mice and uninfected controls to identify distinct cellular responses to A{beta} plaques that differed. Utilizing differential gene expression and pathway analysis, we found that viral encephalitis increased the proportion of myeloid cells in the 5xFAD brain, which also showed down-regulated disease-associated (DAM) pathways involving A{beta} clearance, response to lipids, and macrophage activation within the post-encephalitis 5xFAD brains. ConclusionsTogether, these findings suggest an attenuated myeloid cell response to A{beta} plaque burden in 5xFAD mice following acute viral encephalitis. Future experiments aim to further dissect inflammatory mechanisms between infiltrating myeloid cells, T cells, and the progression of A{beta} and tau pathology. Data derived from these experiments will further elucidate the viral-induced neuroimmune mechanisms that affect AD pathology and offer an opportunity to determine how these neuropathologic changes, such as subsequent neuronal damage, occur.

neuroscience↗

bioRxiv2025

Infection of 5xFAD mice with a mouse-adapted SARS-CoV-2 does not alter Alzheimer's disease neuropathology yet induces wide-spread changes in gene expression across diverse cell types

Alzheimers disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia. It is characterized by cognitive decline and accumulation of amyloid beta (A{beta}) plaques and neurofibrillary tangles. Accumulating evidence indicates that viral infection may worsen and/or increase development of established AD pathology. The COVID-19 pandemic has brought attention to the link between SARS-CoV-2 infection and neurologic conditions that vary in severity and duration, as well as the worsening of clinical symptoms in elderly people with dementia. To better understand potential mechanisms by which SARS-CoV-2 infection impacts AD neuropathology, aged 5xFAD and wildtype (WT) mice were intranasally infected with mouse-adapted SARS-CoV-2 (MA10). Intranasal infection of aged-matched (10-14 month) 5xFAD or wild type (WT) C57BL/6 mice with MA10 resulted in viral infection of the lungs that correlated with acute viral pneumonia characterized by lymphocyte inflammation and antiviral immune responses. Viral RNA was not detected within the central nervous system (CNS) of either WT or 5xFAD mice at days 7 or 21 post-infection (p.i.), nor were there signs of overt glial activation or neuroinflammation. There were no differences in either A{beta} plaque volume or number within the brains of MA10-infected 5xFAD mice compared to uninfected 5xFAD mice. However, bulk RNA sequencing and spatial transcriptomics revealed evidence of altered expression of genes associated with neuronal and glial dysfunction, as well as reduced expression of genes encoding adhesion molecules in vascular endothelial cells. Collectively, these findings demonstrate that MA10 infection did not affect A{beta} plaque size or numbers in 5xFAD mice, yet in both WT and 5xFAD mice, there were numerous down-stream effects on gene expression associated with resident CNS cell function.

pathology↗

bioRxiv2025

VN1K: a genome graph-based and function-driven multi-omics and phenomics resource for the Vietnamese population

Vietnam, the 16th most populated nation, remains profoundly underrepresented in global genomic databases. Here, we present VN1K, a first-ever comprehensive and well-curated resource of multi-omics data with a wide-range of phenotypic information of 1,011 unrelated Vietnamese individuals. High-depth short-read whole-genome sequencing data were generated for all samples along with various - omic data, including microarray, long-read whole-genome sequencing, and RNA sequencing. Using a high-sensitivity variant detection pipeline, which included a pangenome graph reference and a deep-learning framework, we identified nearly 40 million variants of which 8.5 million are novel with nearly 900 thousand short insertions/deletions and 39 thousand structural variants. Specifically, VN1K featured a first-ever whole-genome methylation profile based on long read sequencing. A genotype imputation panel was also created with the highest accuracy on the Vietnamese population. Variants with significantly different allele frequencies in the Vietnamese population compared to others were found to be functionally significant, especially in genes associated with immune diseases (HLA-B, KIR3DL3, KIR2DL1, KIR2DL4) or drug responses (CYP2C19, CYP2D6, VKORC1, CYP2B6). We were also able to map various loci related to hepatitis B virus infection as well as six disease traits, including triglyceride levels, LDL-C, serum glucose levels, HbA1c, and levels of two liver enzymes (ALT and AST). VN1K dataset is accessible via genome.vinbigdata.org, an integrated platform with both linear and graph-based genome browser for facilitating data exploration, research, and applications in precision medicine.

genomics↗

bioRxiv2025

Brightness demixing for simultaneous multi-target imaging in 3D single-molecule localization microscopy

Single-Molecule Localization Microscopy (SMLM) has revolutionized high-resolution imaging, but the simultaneous detection of multiple fluorophores traditionally relies on spectral-based separation, which is inherently constrained by spectral overlap. Here, we introduce Brightness Demixing, a novel method for fluorophore discrimination that exploits brightness, which directly depends on the fluorophores extinction coefficient and quantum yield. By oversampling blinking events, we precisely quantify photon flux as a proxy for brightness, enabling robust differentiation of fluorophores independent of their spectral properties, without requiring additional spectral separation. Brightness Demixing operates within a single detection channel, eliminating the need for additional spectral filters or cameras. We demonstrate this approach with simultaneous two- and three-target imaging in both 2D and 3D configurations. By maintaining single-wavelength excitation and minimizing chromatic aberrations, this method significantly enhances multiplexing in SMLM while remaining fully compatible with existing setups. Brightness Demixing thus offers a simple yet powerful approach for expanding multi-target imaging capabilities in super-resolution microscopy.

biophysics↗

bioRxiv2024

RNA-seq gene expression profiling of the bladder in a mouse model of urogenital schistosomiasis

Background: Parasitic flatworms of the Schistosoma genus cause schistosomiasis, which affects over 230 million people. Schistosoma haematobium causes the urogenital form of schistosomiasis (UGS), which can lead to hematuria, fibrosis, and increased risk of secondary infections by bacteria or viruses. UGS is also linked to bladder cancer. To understand the bladder pathology during S. haematobium infection, our group previously developed a mouse model that involves the injection of S. haematobium eggs into the bladder wall. Using this model, we studied changes in epigenetics profile, as well as changes in gene and protein expression in the host bladder tissues. In the current study, we expand upon this work by examining the expression level of both host and parasite genes using RNA sequencing (RNA-seq) in the mouse bladder wall injection model of S. haematobium infection. Methods: We used a mouse model of S. haematobium infection in which parasite eggs or vehicle control were injected into the bladder walls of female BALB/c mice. RNA-seq was performed on the RNA isolated from the bladders four days after bladder wall injection. Results/Conclusions: RNA-seq analysis of egg- and vehicle control-injected bladders revealed the differential expression of 1025 mouse genes in the egg-injected bladders, including genes associated with cellular infiltration, immune cell chemotaxis, cytokine signaling, and inflammation We also observed the upregulation of immune checkpoint-related genes, which suggests that while the infection causes an inflammatory response, it also dampens the response to avoid excessive inflammation-related damage to the host. Identifying these changes in host signaling and immune responses improves our understanding of the infection and how it may contribute to the development of bladder cancer. Analysis of the differential gene expression of the parasite eggs between bladder-injected versus uninjected eggs revealed 119 S. haematobium genes associated with transcription, intracellular signaling, and metabolism. The analysis of the parasite genes also revealed fewer transcript reads compared to that found in the analysis of mouse genes, highlighting the challenges of studying parasite egg biology in the mouse model of S. haematobium infection. Author summaryMore than 230 million people worldwide are estimated to carry infection with parasites belonging to the Schistosoma genus, which cause morbidity associated with parasite egg deposition. Praziquantel, the drug of choice to treat the infection, does not prevent reinfection, and its decades-long history as the main treatment raises concerns for drug resistance. Of the schistosome species, Schistosoma haematobium causes urogenital disease and has a strong association with bladder cancer. The possibility for drug resistance and the gap in knowledge with respect to the mechanisms driving S. haematobium-related bladder cancer highlight the need to better understand the biology of the infection to aid in the development of new therapeutic strategies. In this study, we used a mouse model of S. haematobium infection that delivers parasite eggs directly to the host mouse bladder wall, and we examined the changes in the gene expression profile of the host and the parasite by RNA-sequencing. The results corroborated previous findings with respect to the hosts inflammatory responses against the parasite eggs, as well as revealed alterations in other immune response genes that deepen our understanding of the mechanisms involved in urogenital schistosomiasis pathogenesis.

molecular biology↗

bioRxiv2024

PAM: Predictive attention mechanism for neural decoding of visual perception

In neural decoding, reconstruction seeks to create a literal image from information in brain activity, typically achieved by mapping neural responses to a latent representation of a generative model. A key challenge in this process is understanding how information is processed across visual areas to effectively integrate their neural signals. This requires an attention mechanism that selectively focuses on neural inputs based on their relevance to the task of reconstruction -- something conventional attention models, which capture only input-input relationships, cannot achieve. To address this, we introduce predictive attention mechanisms (PAMs), a novel approach that learns task-driven "output queries" during training to focus on the neural responses most relevant for predicting the latents underlying perceived images, effectively allocating attention across brain areas. We validate PAM with two datasets: (i) B2G, which contains GAN-synthesized images, their original latents and multiunit activity data; (ii) Shen-19, which includes real photographs, their inverted latents and functional magnetic resonance imaging data. Beyond achieving state-of-theart reconstructions, PAM offers a key interpretative advantage through the availability of (i) attention weights, revealing how the models focus was distributed across visual areas for the task of latent prediction, and (ii) values, capturing the stimulus information decoded from each area.

neuroscience↗

bioRxiv2023

Neutrophilia with damage to the blood-brain barrier and neurovascular unit following acute lung injury

BackgroundThe role of neutrophils in mediating neurovascular vulnerability has been increasingly implicated in various acute inflammatory models of neuroimmune crosstalk between the periphery and the brain. Whether neurovascular vulnerability is similarly modulated in the context of frequent, but not acute, inflammatory activation in the periphery is the aim of our study. Such a model of frequent inflammatory irritation is pertinent to understanding the neurologic risk of constant exposure to aerosolized environmental hazards leading to progressive pulmonary disease. MethodsTo model repeated pulmonary inflammation, we applied a three-dose regimen of intranasal (i.n.) lipopolysaccharide (LPS) in C57BL/6J mice and studied the impact on the inflammatory environment of the brain, with a specific focus on neutrophil dynamics at the neurovascular unit (NVU). Tissue and circulatory inflammatory profiles were screened via bronchoalveolar lavage (BAL) protein content and cellularity, transcript analysis of brain tissue, and flow cytometry of peripheral blood. Intravital two-photon microscopy (2PM) of the brain vasculature identified neutrophil dynamics at the NVU. Immunofluorescence validated neutrophil dynamics and identified neuroinflammatory hallmarks and peripheral immune factor interactions at the NVU. In vivo findings were corroborated and replicated in murine and human microphysiological systems (MPS) modeling the blood-brain barrier as a proxy demonstration of the translational relevance of our findings. Results2PM of tdTomato-Ly6G+ neutrophils demonstrated increased levels of circulating neutrophils and corresponding engagement with the brain vasculature after the three-dose repeated i.n. exposure regimen. Neutrophilia at the NVU was corroborated with increased transcript levels of Ly6G and other pro-inflammatory markers. This coordination between endothelial physiology and neutrophil phenotypes was recapitulated in murine and human MPS models. System-wide neutrophilia in the lung and circulation was found to be cotemporaneous to neutrophilia at the NVU based on the cellularity of BAL and peripheral blood samples collected at the same endpoints. Immunohistochemical analysis of brain tissue implicates temporal coordination between vascular surface adhesion molecules with changes in neutrophil dynamics from adhesion, crawling, stalling, and transmigration. Extravasation of neutrophils was complemented by sustained paravascular deposition of fibrinogen and microgliosis up to 72 hours after the final i.n. dosing. Microglia-associated effector functions for synaptic pruning and regulation of neutrophil activity demonstrated distinct temporal profiles. ConclusionsOur results identify systemic levels of neutrophilia accompanied by ingress and extravascular accumulation in brain parenchyma that correlated with sustained microglial activation. This neutrophil-centric lung-brain interaction is complemented by the observation of paravascular fibrinogen deposition that alters synaptic metabolism. Thus, we propose a mechanistic role for neutrophilia and associated inflammatory dysregulation as essential mediators along the lung-brain neuroimmune axis in a generalizable model of repeated respiratory exposure to inflammatory agents. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/562508v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@113d747org.highwire.dtl.DTLVardef@19a8a5corg.highwire.dtl.DTLVardef@f1a1eaorg.highwire.dtl.DTLVardef@1bd23c7_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

Collaborative Augmented Reconstruction for Scaled Production of 3D Neuron Morphology in Mouse and Human Brains

Digital reconstruction of the intricate 3D morphology of individual neurons from microscopic images is widely recognized as a crucial challenge in both individual research laboratories and large-scale scientific projects focusing on cell types and brain anatomy. This task often fails both conventional manual reconstruction and state-of-the-art automatic reconstruction algorithms, even many of which are based on artificial intelligence (AI). It is also critical but challenging to organize multiple neuroanatomists to produce and cross-validate biologically relevant and agreeable reconstructions in scaled data production. Here we propose an approach based on collaborative human intelligence augmented by AI. Specifically, we have developed a Collaborative Augmented Reconstruction (CAR) platform for neuron reconstruction at scale. This platform allows for immersive interaction and efficient collaborative-editing of neuron anatomy using a variety of client devices, such as desktop workstations, virtual reality headsets, and mobile phones, enabling users to contribute anytime and anywhere and take advantage of several AI-based automation tools. We have tested CARs applicability for challenging mouse and human neurons towards a scaled and faithful data production. Our data indicate that the CAR platform is suitable for generating tens of thousands of neuronal reconstructions used in our companion studies.

neuroscience↗

bioRxiv2023

Tet Controls Axon Guidance in Early Brain Development through Glutamatergic Signaling

Mutations in human TET proteins have been found in individuals with neurodevelopmental disorders. Here we report a new function of Tet in regulating Drosophila early brain development. We found that mutation in the Tet DNA-binding domain (TetAXXC) resulted in axon guidance defects in the mushroom body (MB). Tet is required in early brain development during the outgrowth of MB {beta} axons. Transcriptomic study shows that glutamine synthetase 2 (Gs2), a key enzyme in glutamatergic signaling, is significantly downregulated in the TetAXXC mutant brains. CRISPR/Cas9 mutagenesis or RNAi knockdown of Gs2 recapitulates the TetAXXC mutant phenotype. Surprisingly, Tet and Gs2 act in the insulin-producing cells (IPCs) to control MB axon guidance, and overexpression of Gs2 in these cells rescues the axon guidance defects of TetAXXC. Treating TetAXXC with the metabotropic glutamate receptor antagonist MPEP can rescue while treating with glutamate enhances the phenotype confirming Tet function in regulating glutamatergic signaling. TetAXXC and the Drosophila homolog of Fragile X Messenger Ribonucleoprotein protein mutant (Fmr13) have similar axon guidance defects and reduction in Gs2 mRNA levels. Interestingly, overexpression of Gs2 in the IPCs also rescues the Fmr13 phenotype, suggesting functional overlapping of the two genes. Our studies provide the first evidence that Tet can control the guidance of axons in the developing brain by modulating glutamatergic signaling and the function is mediated by its DNA-binding domain.

developmental biology↗

bioRxiv2023

Brain2GAN: Feature-disentangled neural coding of visual perception in the primate brain

A challenging goal of neural coding is to characterize the neural representations underlying visual perception. To this end, multi-unit activity (MUA) of macaque visual cortex was recorded in a passive fixation task upon presentation of faces and natural images. We analyzed the relationship between MUA and latent representations of state-of-the-art deep generative models, including the conventional and feature-disentangled representations of generative adversarial networks (GANs) (i.e., z- and w-latents of StyleGAN, respectively) and language-contrastive representations of latent diffusion networks (i.e., CLIP-latents of Stable Diffusion). A mass univariate neural encoding analysis of the latent representations showed that feature-disentangled w representations outperform both z and CLIP representations in explaining neural responses. Further, w-latent features were found to be positioned at the higher end of the complexity gradient which indicates that they capture visual information relevant to high-level neural activity. Subsequently, a multivariate neural decoding analysis of the feature-disentangled representations resulted in state-of-the-art spatiotemporal reconstructions of visual perception. Taken together, our results not only highlight the important role of feature-disentanglement in shaping high-level neural representations underlying visual perception but also serve as an important benchmark for the future of neural coding. Author summaryNeural coding seeks to understand how the brain represents the world by modeling the relationship between stimuli and internal neural representations thereof. This field focuses on predicting brain responses to stimuli (neural encoding) and deciphering information about stimuli from brain activity (neural decoding). Recent advances in generative adversarial networks (GANs; a type of machine learning model) have enabled the creation of photorealistic images. Like the brain, GANs also have internal representations of the images they create, referred to as "latents". More recently, a new type of feature-disentangled "w-latent" of GANs has been developed that more effectively separates different image features (e.g., color; shape; texture). In our study, we presented such GAN-generated pictures to a macaque with cortical implants and found that the underlying w-latents were accurate predictors of high-level brain activity. We then used these w-latents to reconstruct the perceived images with high fidelity. The remarkable similarities between our predictions and the actual targets indicate alignment in how w-latents and neural representations represent the same stimulus, even though GANs have never been optimized on neural data. This implies a general principle of shared encoding of visual phenomena, emphasizing the importance of feature disentanglement in deeper visual areas.

neuroscience↗

bioRxiv2022

Instantly adhesive and ultra-elastic patches for dynamic organ and wound repair

Bioadhesive materials and patches are promising alternatives to surgical sutures and staples. However, many existing bioadhesives do not meet the functional requirements of current surgical procedures and interventions. Here we present a translational patch material that exhibits: (1) instant adhesion to wet tissues (2.5-fold stronger than Tisseel, an FDA-approved fibrin glue), (2) ultra-stretchability (stretching to >300% its original length without losing elasticity), (3) compatibility with rapid photo-projection (<2 min fabrication time/patch), and (4) ability to deliver therapeutics. Using our established procedures for the in silico design and optimization of anisotropic-auxetic patches, we create next generation patches for instant attachment to wet and dry tissues while conforming to a broad range of organ mechanics ex vivo and in vivo. Patches coated with exosomes demonstrate robust wound healing capability in vivo without inducing a foreign body response and without the need for patch removal that can cause pain and bleeding. We further demonstrate a new single material-based, void-filling auxetic patch designed for the treatment of lung puncture wounds. TeaserWe demonstrate a sticky and highly elastic patch with conforming designs for dynamic organ repair.

bioengineering↗

bioRxiv2022

A role for brassinosteroid signaling in decision-making processes in the Arabidopsis seedling

Plants often adapt to adverse conditions via differential growth, whereby limited resources are discriminately allocated to optimize the growth of one organ at the expense of another. Little is known about the decision-making processes that underly differential growth. In this study, we developed a screen to identify decision making mutants by deploying two tools that have been used in decision theory: a well-defined yet limited budget, as well as conflict-of-interest scenarios. A forward genetic screen that combined light and water withdrawal was carried out. This identified BRASSINOSTEROID INSENSITIVE 2 (BIN2) alleles as decision mutants with "confused" phenotypes. An assessment of organ and cell length suggested that hypocotyl elongation occurred predominantly via cellular elongation. In contrast, root growth appeared to be regulated by a combination of cell division and cell elongation or exit from the meristem. Brassinosteroid signalling mutants were most severely impaired in their ability to adjust cell geometry in the hypocotyl and cell elongation as a function of distance from the quiescent centre in the root tips. This study describes a novel paradigm for root growth under limiting conditions, which depends not only on hypocotyl-versus-root trade-offs in the allocation of limited resources, but also on an ability to deploy different strategies for root growth in response to multiple stress conditions.

plant biology↗