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Yin, F.

Publications and source records attributed to Yin, F..

18 recordsLinked to original sources
bioRxiv2026

Healing cascades and infections in wounds monitored using a wearable sensor of gaseous flux

Capabilities for quantitative monitoring of chronic wounds remain an unmet clinical need, as existing diagnostic approaches rely on semiquantitative evaluation of symptoms that lack sensitivity especially during early stages of infection. Here we present a scheme for tracking wound physiology that leverages a miniature, wireless skin-interfaced device for non-contact, transient measurements of the flux of volatile organic compounds (VOCs) and water vapor from the wound microenvironment. Unlike emerging smart bandage platforms that rely on physical contact with the fragile wound bed to interrogate liquid-phase biomarkers, this strategy uses an engineered microclimate and suspended suite of sensors to measure the diffusive transport of wound-derived gases across the wound surface but separated from it. The result enables quantitative evaluation of metabolic activity and healing progression without perturbing the healing tissues. In biofilm growth models of Staphylococcus aureus, measurements demonstrate that trends in VOC flux correlate strongly with bacterial growth kinetics and precede any visible biofilm formation. Longitudinal monitoring in infected murine wound healing models shows that concurrent measurements of water vapor and VOC flux provide complementary physiological insights, capturing both the trajectory of barrier restoration and the dynamics of bacterial burden. The findings establish this non-contact sensing scheme as a distinct and clinically translatable paradigm for wound monitoring, with broad implications for non-invasive surveillance of disease states in which tissue metabolic activity and skin barrier integrity serve as actionable physiological readouts. Significance StatementLimited capabilities in continuous, quantitative assessment of a wound make early diagnosis and effective management challenging, particularly in cases of infection that rapidly progress before symptoms appear. Non-contact approaches for wound monitoring that preserve fragile tissue can transform wound care. In this context, gaseous flux from the wound bed provides an integrative measure of microbial activity and barrier restoration. This study establishes a wearable sensing platform that quantifies these fluxes in real time, enabling early infection detection and temporal tracking of wound healing. These results highlight a path toward personalized treatment strategies and reduced reliance on episodic clinical evaluation.

bioengineering↗
bioRxiv2026

Functional ultrasound imaging reveals pathway-specific visual system reorganization in young Cln3-/- mice

CLN3 disease, or juvenile Batten disease, is a neurodegenerative lysosomal storage disorder in which visual impairment is typically the earliest clinical manifestation. Although retinal pathology has been extensively studied, functional alterations within central visual pathways remain poorly understood. Here, we used functional ultrasound (fUS) imaging to characterize visually evoked activity across central visual circuits in young Cln3 knockout (Cln3-/-) mice before the onset of severe retinal degeneration. Visually evoked hemodynamic responses were quantified in regions spanning the geniculostriate and extrageniculate visual pathways, including cortical, thalamic, and midbrain regions. To assess regional pathological burden, accumulation of subunit c of mitochondrial ATP synthase (SCMAS), a pathological marker of CLN3 disease, was examined using immunohistochemistry. We found that Cln3-/- mice exhibited pathway-specific alterations in visually evoked activity. Regions along the extrageniculate pathway, including the midbrain, posterior thalamus, and anterior secondary visual cortex, showed enhanced activation relative to wild-type controls. In contrast, activation within the geniculostriate pathway was reduced in the anterior thalamus and remained unchanged in the primary and posterior secondary visual cortex. SCMAS accumulation was elevated across all examined visual regions in Cln3-/- mice relative to wild-type controls, with greater accumulation observed in geniculostriate regions than in extrageniculate regions. These findings demonstrate early pathway-specific functional and pathological alterations in the visual system of Cln3-/- mice, suggesting pathway-level reorganization of central visual processing. This study advances understanding of central visual dysfunction in CLN3 disease and highlights fUS imaging as a sensitive approach for detecting early functional abnormalities in neurodegenerative disorders.

neuroscience↗
bioRxiv2026

APOE4 Accelerates Menopause-Associated Brain Metabolic Shift and Disrupts Bioenergetic Adaptation

IntroductionDisruption of brain glucose and lipid metabolism contributes to Alzheimers disease (AD) and often emerges before clinical symptoms. Women are at elevated AD risk due to menopause-associated estrogen decline, which impairs mitochondrial function and glucose metabolism. Womens risk of AD is further elevated by the APOE4 allele, the strongest genetic risk factor for late-onset AD. MethodsTo investigate the impact of APOE genotype on the menopausal metabolic transition, brain metabolomic and lipidomic profiling was conducted in humanized female APOE3/3, APOE3/4, and APOE4/4 mice across chronological and endocrinological stages of peri-to postmenopausal transition. ResultsAPOE3/3 mice exhibited dynamic regulation of brain metabolic systems that supported postmenopausal bioenergetic demand. In contrast, APOE3/4 and APOE4/4 mice displayed accelerated and altered metabolic shifts, resulting in postmenopausal amino acid depletion, reduced tricarboxylic acid (TCA) cycle intermediates, lipid accumulation, and alterations in brain lipid composition. A single APOE4 allele was sufficient to impair metabolic adaptation, while APOE4 homozygosity resulted in greater severity of deficits. DiscussionOutcomes of these analyses revealed that APOE4 accelerated menopause-related metabolic decline and compromised bioenergetic adaptation, providing a mechanistic basis for increased AD susceptibility and earlier onset in APOE4-positive women.

neuroscience↗
bioRxiv2025

DNA framework array enables ultra-high throughput DNA synthesis

High-throughput DNA synthesis has revolutionized synthetic biology, molecular diagnostics, genome engineering, and DNA data storage by enabling the scalable and precise construction of nucleotide-based information systems. However, existing high-throughput synthesis technologies rely on top-down fabrication strategies to maximize throughput, yet they are inherently constrained by physical limitations. These constraints make it exceedingly difficult to achieve single-molecule level synthesis control that is essential for advancing next-generation DNA synthesis. Here, we present a DNA framework-based bottom-up enzymatic synthesis strategy that enables single-molecule level control of DNA synthesis with high-throughput. Leveraging the nanoscale addressability of DNA frameworks, we achieved a synthesis site pitch of 10.9 nm--183-fold smaller than that of previously reported electrode arrays. Theoretical projections suggest that this approach could scale synthesis throughput to 5.3 x 1011 sequences per square centimeter, representing a four-order-of-magnitude improvement over existing synthesis arrays. This approach lays the foundation for gigabyte-scale DNA writing and offers a highly accessible pathway toward large-scale DNA synthesis for emerging applications such as molecular data storage.

synthetic biology↗
bioRxiv2024

The epitranscriptomic m6A RNA modification modulates synaptic function in ageing and in a mouse model of synucleinopathy

N6-methyladenosine (m6A) is the most abundant and conserved transcriptional modification in eukaryotic RNA, regulating RNA fate. While the functions of m6A in the development of the mammalian brain have been extensively studied, its roles in synaptic plasticity, cognitive decline, motor function, or other brain circuits remain underexplored. To date, the role of this modification in Parkinsons disease (PD) and other synucleinopathies has been largely unknown. Here, we investigated the m6A epitranscriptome in a mouse model of synucleinopathy. We performed m6A RNA immunoprecipitation sequencing (meRIP-seq) to obtain the m6A epitranscriptome of the midbrain in young (3 mo) and aged (15 mo) A30P-aSyn transgenic mice (aSyn Tg) and C57BL6 control wild type (Wt) mice. We observed hypermethylation of synaptic genes in 3 mo aSyn Tg mice compared to age-matched Wt mice. This methylation was reduced during ageing, with synaptic genes becoming increasingly hypomethylated. Using immunofluorescence imaging alongside biochemical analysis, we further investigated the expression of m6A regulatory enzymes -- writer, N6-Adenosine-Methyltransferase Complex Catalytic Subunit (METTL3); reader, YTH N6-methyladenosine RNA-binding protein (YTHDF1); and eraser, fat mass and obesity-associated protein (FTO) -- in the cortex, striatum, hippocampus, and cerebellum of Wt and aSyn Tg mice, as well as in primary cortical neuronal cultures. We observed that the levels of METTL3, YTHDF1 and FTO were similar between Wt and aSyn Tg mice. Interestingly, the writer protein METTL3 was found in both the nucleus and in the post-synaptic compartment in neuronal cultures. Our findings suggest that alterations in the regulation of m6A RNA methylation may be associated with neurodegeneration and ageing and that this level of epitranscriptomic regulation plays a significant role at the synapse.

neuroscience↗
bioRxiv2024

Towards anchoring evolutionary fitness for protein stability with virtual chemical environment recovery

Predicting the protein stability changes upon mutations is one of the effective ways to improve the efficiency of protein engineering. Here, we propose a dual-view ensemble learning-based framework, DVE-stability, for mutation-induced protein stability change prediction from single sequence. DVE-stability integrates the global and local dependencies of mutations to capture the intramolecular interactions from two views through ensemble learning, in which a structural microenvironment simulation module is designed to indirectly introduce the information of structural microenvironment at the sequence level. DVE-stability achieved state-of-the-art prediction performance on 7 single-point mutation benchmark datasets, and comprehensively surpassed other methods on 5 of them. Furthermore, DVE-stability outperformed other methods comprehensively through zero-shot inference on multiple-point mutation prediction task, demonstrating superior model generalizability to capture the epistasis of multiple-point mutations. More importantly, DVE-stability exhibited superior generalization performance in predicting rare beneficial mutations that are crucial for practical protein directed evolution scenarios. In addition, DVE-stability identified important intramolecular interactions via attention scores, demonstrating interpretable. Overall, DVE-stability provides a flexible and efficient tool for mutation-induced protein stability change prediction in an interpretable ensemble learning manner.

bioinformatics↗
bioRxiv2024

Heparan sulfate modified proteins affect cellular processes central to neurodegeneration and modulate presenilin function

Mutations in presenilin-1 (PSEN1) are the most common cause of familial, early-onset Alzheimers disease (AD), typically producing cognitive deficits in the fourth decade. A variant of APOE, APOE3 Christchurch (APOE3ch), was found associated with protection from both cognitive decline and Tau accumulation in a 70-year-old bearing the disease-causing PSEN1-E280A mutation. The amino acid change in ApoE3ch is within the heparan sulfate (HS) binding domain of APOE, and purified APOEch showed dramatically reduced affinity for heparin, a highly sulfated form of HS. The physiological significance of ApoE3ch is supported by studies of a mouse bearing a knock-in of this human variant and its effects on microglia reactivity and A{beta}-induced Tau deposition. The studies reported here examine the function of heparan sulfate-modified proteoglycans (HSPGs) in cellular and molecular pathways affecting AD-related cell pathology in human cell lines and mouse astrocytes. The mechanisms of HSPG influences on presenilin-dependent cell loss and pathology were evaluated in Drosophila using knockdown of the presenilin homolog, Psn, together with partial loss of function of sulfateless (sfl), a homolog of NDST1, a gene specifically affecting HS sulfation. HSPG modulation of autophagy, mitochondrial function, and lipid metabolism were shown to be conserved in cultured human cell lines, Drosophila, and mouse astrocytes. RNAi of Ndst1 reduced intracellular lipid levels in wild-type mouse astrocytes or those expressing humanized variants of APOE, APOE3, and APOE4. RNA-sequence analysis of human cells deficient in HS synthesis demonstrated effects on the transcriptome governing lipid metabolism, autophagy, and mitochondrial biogenesis and showed significant enrichment in AD susceptibility genes identified by GWAS. Neuron-directed knockdown of Psn in Drosophila produced cell loss in the brain and behavioral phenotypes, both suppressed by simultaneous reductions in sfl mRNA levels. Abnormalities in mitochondria, liposome morphology, and autophagosome-derived structures in animals with Psn knockdown were also rescued by simultaneous reduction of sfl. sfl knockdown reversed Psn-dependent transcript changes in genes affecting lipid transport, metabolism, and monocarboxylate carriers. These findings support the direct involvement of HSPGs in AD pathogenesis.

neuroscience↗
bioRxiv2024

Hunting for peptide binders of specific targets with data-centric generative language models

Bioactive peptides have become strong candidates for a variety of clinical therapies due to their diverse advantages, which promotes the development of deep generative models for peptide design. Considering that existing methods cannot effectively deal with the conformational flexibility of peptides and are difficult to capture accurate residue-to-residue interaction dependencies, we propose a unified weakly order-dependent autoregressive language modeling architecture (PepGenWOA) for bioactive peptide generative design with tolerating out-of-order input as inductive bias. The superiority of PepGenWOA is demonstrated by generating three classes of therapeutic peptides, including antimicrobial peptides, anticancer peptides, and peptide binders. For antimicrobial and anticancer peptide generation, PepGenWOA not only comprehensively outperforms state-of-the-art baseline models, but also exhibits a significant propensity to incorporate specific types of residues that are beneficial for antimicrobial or anticancer bioactivity. For characteristic-guided peptide binder generation, the pretrained PepGenWOA is fine-tuned with Mixture-of-Experts-style plugins with lifelong learning paradigm, thereby achieving the best trade-off between memory stability for world knowledge and learning plasticity for new downstream tasks. The subsequent structure-based virtual screening anchors the 7 most promising candidates from the mega-scale synthetic sequence space, reducing the number of candidates for in vitro experimental validation by 5 orders of magnitude. A target binding rate of 28.6% with binding specificity further confirms the effectiveness of the fine-tuning strategy. Overall, PepGenWOA is a unified architecture for peptide generative design that can be flexibly customized for different task requirements, thereby harnessing generative language models to reach the "dark space" of biological language.

bioinformatics↗
bioRxiv2022

Human iPSC-derived neuron of 16p11.2 deletion reveals haplotype-specific expression of MAPK3 and its contribution to variable NDD phenotypes

Recurrent proximal 16p11.2 deletion (16p11.2del) is risk factor of diverse neurodevelopmental disorders (NDDs) with variable penetrance. Although previous human induced pluripotent stem cell (hiPSC) models of 16p11.2del confirmed disrupted neuron development, it is not known which gene(s) at this interval are mainly responsible for the abnormal cellular phenotypes and how the NDD penetrance is regulated. After haplotype phasing of 16p11.2 region, we generated hiPSCs for two 16p11.2del families with distinct residual haplotypes and variable NDD phenotypes. We also differentiated the hiPSCs to cortical neural cells and demonstrated MAPK3 as a driver signal of 16p11.2 region contributing to the dysfunctions in multiple pathways related to neuron development, which leads to altered morphological or electrophysiological properties in neuron cells. Furthermore, residual haplotype-specific MAPK3 expression was identified in 16p11.2del neuron cells, associating MAPK3 down-expression with the minor allele of the residual haplotype. Ten SNPs of the residual haplotype are mapped as enhancer SNPs (enSNPs) of MAPK3, eight enSNPs were functionally validated by luciferase assays, implying enSNPs contribute to residual haplotype-specific MAPK3 expression via cis-regulation. Finally, the analyses of three different patient cohorts showed that the residual haplotype of 16p11.2del is associated with variable NDD phenotypes.

genetics↗
bioRxiv2022

A Novel Selective ERK1/2 Inhibitor, Laxiflorin B, Targets EGFR Mutation Subtypes in Non-small-cell Lung Cancer

Extracellular regulated protein kinases 1/2 (ERK1/2) are key members of multiple signaling pathways including the ErbB axis. ERK1/2 ectopic activation is responsible for various types of cancer, especially drug resistance to inhibitors of RTK, RAF and MEK, but specific ERK1/2 inhibitors are scarce. In this study, we identified a potential novel ERK covalent inhibitor, Laxiflorin B, a herbal compound with anticancer activity. However, Laxiflorin B is present at low levels in herbs; therefore, we adopted a semi-synthetic process for the efficient production of Laxiflorin B to improve the yield. Laxiflorin B induced mitochondria-mediated apoptosis via BAD activation in non-small-cell lung cancer (NSCLC) cells, especially in EGFR mutant subtypes. Transcriptomic analysis suggested that Laxiflorin B inhibits amphiregulin (AREG) and epiregulin (EREG) expression through ERK inhibition, and suppressed the activation of their receptors, ErbBs, via a positive feedback loop. More importantly, mass spectrometry combined with computer simulation analysis revealed that Laxiflorin B binds covalently to Cys-183 in the ATP-binding pocket of ERK1 through D-ring, and Cys-178 of ERK1 though non-inhibitory binding of A-ring, respectively. Laxiflorin B also exhibited strong tumor suppressive effects with low toxicity in a NSCLC tumor xenograft model in nude mice, and AREG and EREG were identified as biomarkers of Laxiflorin B efficacy. Finally, Laxiflorin B-4, a C-6 modification of Laxiflorin B, exhibited higher affinity for ERK1/2 and stronger tumor suppression. These findings provide a new approach to tumor inhibition using natural anticancer compounds.

pharmacology and toxicology↗
bioRxiv2021

Recurrent de novo single point mutation on the gene encoding Na+ /K+ pump results in epilepsy

The etiology of epilepsy remains undefined in two-thirds of patients. Here, we identified a de novo mutation of ATP1A2 (c.2426 T>G, p.Leu809Arg), which encodes the 2 subunit of Na+/K+-ATPase, from a family with idiopathic epilepsy. This mutation caused seizures in the study patients. We generated the point mutation mouse model Atp1a2L809R, which recapitulated the epilepsy observed in the study patients. In Atp1a2L809R/WT mice, convulsions were observed and cognitive and memory function was impaired. This mutation affected the potassium binding function of the protein, disabling its ion transport ability, thereby increasing the frequency of nerve impulses. Our work revealed that ATP1A2L809R mutations cause a predisposition to epilepsy. Moreover, we first provide a point mutation mouse model for epilepsy research and drug screening.

neuroscience↗
bioRxiv2021

circMRPS35 promotes malignant progression and cisplatin resistance in hepatocellular cancer

Hepatocellular carcinoma (HCC), a common malignant tumor, is one of the main causes of cancer-related deaths worldwide. Circular RNAs (circRNAs), a novel class of non-coding RNA, have been reported to be involved in the etiology of various malignancy. However, the functions of circRNAs in HCC remain unclear. In this study, through mining the RNA sequencing databases from GEO datasets and subsequent experimental verification, we identified that hsa_circ_0000384 (circMRPS35) was highly expressed in HCC. Knockdown of circMRPS35 suppressed the proliferation, migration, invasion, clone formation and cell cycle of HCC cell lines both in vitro and in a xenograft mouse model. Mechanically, circMRPS35 sponged microRNA-148a-3p (miR-148a), which in turn regulated STX3-PTEN axis. Surprisingly, we detected a peptide encoded by circMRPS35 (circMRPS35-168aa), which was significantly induced by chemotherapeutic drugs and promoted cisplatin resistance in HCC cells. These results demonstrated that circMRPS35 might be a novel factor in HCC progress, and has a great potential as a new diagnosis and therapeutic target for treatment of HCC.

cell biology↗
bioRxiv2020

Different force fields give rise to different amyloid aggregation pathways in molecular dynamics simulations

The progress towards understanding the molecular basis of Alzheimerss disease is strongly connected to elucidating the early aggregation events of the amyloid-{beta} (A{beta}) peptide. Molecular dynamics (MD) simulations provide a viable technique to study the aggregation of A{beta} into oligomers with high spatial and temporal resolution. However, the results of an MD simulation can only be as good as the underlying force field. A recent study by our group showed that none of the force fields tested can distinguish between aggregation-prone and non-aggregating peptide sequences, producing the same and in most cases too fast aggregation kinetics for all peptides. Since then, new force fields specially designed for intrinsically disordered proteins such as A{beta} were developed. Here, we assess the applicability of these new force fields to studying peptide aggregation using the A{beta}16-22 peptide and mutations of it as test case. We investigate their performance in modeling the monomeric state, the aggregation into oligomers, and the stability of the aggregation end product, i.e., the fibrillar state. A main finding is that changing the force field has a stronger effect on the simulated aggregation pathway than changing the peptide sequence. Also the new force fields are not able to reproduce the experimental aggregation propensity order of the peptides. Dissecting the various energy contributions shows that AMBER99SB-disp overestimates the interactions between the peptides and water, thereby inhibiting peptide aggregation. More promising results are obtained with CHARMM36m and especially its version with increased protein-water interactions. It is thus recommended to use this force field for peptide aggregation simulations and base future reparameterizations on it.

biophysics↗
bioRxiv2020

SARS-CoV-2 manipulates the SR-B1-mediated HDL uptake pathway for its entry

The recently emerged pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly, leading to a global COVID-19 pandemic. Binding of the viral spike protein (SARS-2-S) to cell surface receptor angiotensin-converting enzyme 2 (ACE2) mediates host cell infection. In the present study, we demonstrate that in addition to ACE2, the S1 subunit of SARS-2-S binds to HDL and that SARS-CoV-2 hijacks the SR-B1-mediated HDL uptake pathway to facilitate its entry. SR-B1 facilitates SARS-CoV-2 entry into permissive cells by augmenting virus attachment. MAb (monoclonal antibody)-mediated blocking of SARS-2-S-HDL binding and SR-B1 antagonists strongly inhibit HDL-enhanced SARS-CoV-2 infection. Notably, SR-B1 is co-expressed with ACE2 in human pulmonary and extrapulmonary tissues. These findings revealed a novel mechanism for SARS-CoV-2 entry and could provide a new target to treat SARS-CoV-2 infection.

microbiology↗
bioRxiv2020

High-Fiber Diet Restores Maternal Obesity-Induced Cognitive and Social Behavioral Deficits in Offspring via Regulating Gut Microbiota-Metabolites-Brain Axis

Maternal obesity has been reported to be related to the neurodevelopmental disorders in offspring. However, the underlying mechanisms and effective interventions remain unclear. Here, a cross-sectional study on 778 children aged 7-14 years in two cities of China indicates that the maternal obesity is highly associated with the poorer cognition and sociality of their children. Moreover, we also find that the maternal obesity in mice disrupts the behavior and the gut microbiome in the offspring, which are alleviated by a high-fiber diet in either dams or offspring. Co-housing and feces microbiota transplantation experiments reveal a causal relationship between the reshaped microbiota and the behavioral changes. Moreover, treatment of the microbiota-derived short-chain fatty acids exhibits a similar beneficial effect on alleviating the behavioral deficits in offspring. Together, our study purports the microbiota-metabolites-brain axis as a mechanism, and high-dietary fiber intake is a promising intervention against maternal obesity-induced cognitive and social dysfunctions.

neuroscience↗
bioRxiv2017

Genetic Single Neuron Anatomy reveals fine granularity of cortical interneuron subtypes

Parsing diverse nerve cells into biological types is necessary for understanding neural circuit organization. Morphology is an intuitive criterion for neuronal classification and a proxy of connectivity, but morphological diversity and variability often preclude resolving the granularity of discrete cell groups from population continuum. Combining genetic labeling with high-resolution, large volume light microscopy, we established a platform of genetic single neuron anatomy that resolves, registers and quantifies complete neuron morphologies in the mouse brain. We discovered that cortical axo-axonic cells (AACs), a cardinal GABAergic interneuron type that controls pyramidal neuron (PyN) spiking at axon initial segment, consist of multiple subtypes distinguished by laminar position, dendritic and axonal arborization patterns. Whereas the laminar arrangements of AAC dendrites reflect differential recruitment by input streams, the laminar distribution and local geometry of AAC axons enable differential innervation of PyN ensembles. Therefore, interneuron types likely consist of fine-grained subtypes with distinct input-output connectivity patterns.

neuroscience↗
bioRxiv2017

Identifying weak signals in inhomogeneous neuronal images for large-scale tracing of neurites

Reconstructing neuronal morphology across different regions or even the whole brain is important in many areas of neuroscience research. Large-scale tracing of neurites constitutes the core of this type of reconstruction and has many challenges. One key challenge is how to identify a weak signal from an inhomogeneous background. Here, we addressed this problem by constructing an identification model. In this model, empirical observations made from neuronal images are summarized into rules, which are used to design feature vectors that display the differences between the foreground and background, and a support vector machine is used to learn these feature vectors. We embedded this identification model into a tool that we previously developed, SparseTracer, and termed this integration SparseTracer-Learned Feature Vector (ST-LFV). ST-LFV can trace neurites with extremely weak signals (signal-to-background-noise ratio <1.1) against an inhomogeneous background. By testing 12 sub-blocks extracted from a whole imaging dataset, ST-LFV can achieve an average recall rate of 0.99 and precision rate of 0.97, which is superior to that of SparseTracer (which has an average recall rate of 0.93 and average precision rate of 0.86), indicating that this method is well suited to weak signal identification. We applied ST-LFV to trace neurites from large-scale images (approximately 105 GB). During the tracing process, obtaining results equivalent to the ground truth required only one round of manual editing for ST-LFV compared to 20 rounds of manual editing for SparseTracer. This improvement in the level of automatic reconstruction indicates that ST-LFV has the potential to rapidly reconstruct sparsely distributed neurons at the scale of an entire brain.

bioinformatics↗