Biology subjects

Saito, N.

Publications and source records attributed to Saito, N..

At least 19 recordsLinked to original sources

bioRxiv2026

HNRNPC-mediated RNA processing promotes VHL-associated excessive vasculogenesis in von Hippel-Lindau syndrome revealed from patient-derived blood vessel models

Von Hippel-Lindau Syndrome (VHLS) is an inherited disorder characterized by excessive vascularization, which contributes to the development of hemangioblastomas and benign or malignant tumors, as well as renal cell carcinoma (RCC) and cysts in multiple organs. VHLS is caused by mutations in VHL tumor suppressor gene, which encodes a component of an E3 ubiquitin ligase complex. Although therapeutic agents targeting hypoxia-inducible factor 2 alpha (HIF2A), which is stabilized by VHL loss and promotes tumor angiogenesis, have been approved for clinical use, their therapeutic response remains limited in RCC patients associated with VHLS. Therefore, there is an unmet need for the development of alternative therapeutic approaches independent of HIF2A. Here, we establish a human iPSCs-based model of VHLS-associated excessive vasculogenesis using induced pluripotent stem cells (iPSCs) derived from VHLS patients and VHL-edited isogenic iPSC lines. Vascular cells (VCs) differentiated from these VHLS-specific iPSCs exhibited excessive blood vessel formation compared to healthy donor-derived VCs, leading to vascular lesion formation characterized by abundant blood vessels and abnormal cellular growth in vivo. Mechanistically, RNA-binding proteins (RBPs) were preferentially stabilized in the patient-VCs. Among these RBPs, the stabilization of heterogeneous nuclear ribonucleoprotein C1/C2 (HNRNPC), which is a substrate for pVHL-mediated protein degradation independent of HIF2A expression, was critical for the dysregulated vascularization caused by VHL inactivation in this model. These findings provide an iPSCs-derived vascular platform to elucidate VHLS mechanisms and identify HNRNPC as a potential therapeutic target for VHL-driven vascular lesion formations through an HIF2A-independent mechanism.

cell biology↗

bioRxiv2026

Decoding Anadara shell morphology with deep learning

Accurate shell shape quantification is critical for studying biodiversity and evolution, yet intraspecific variability in bivalves makes morphology-based identification difficult. Traditional methods, including landmark-based analyses and elliptic Fourier descriptors, suffer either from subjectivity in homologous point selection or from limited use of contour information. Here, we introduce Morpho-VAE, a deep generative framework integrating a variational autoencoder with a supervised classifier, to analyze shell images of five Anadara species. Morpho-VAE outperforms conventional approaches in species classification by embedding morphological variation into a low-dimensional space where species cluster distinctly. To highlight species-specific morphological patterns, we develop a patch masking assay, revealing the hinge line as a shared morphological marker across species and species-specific regions near the umbo and anterior ventral margin. The decoder further enables morphological visualization via image reconstruction and interpolation. Our results show that Morpho-VAE can automatically extract species-defining morphological patterns from raw images, providing complementary or novel insights beyond traditional morphometric methods.

biophysics↗

bioRxiv2026

Filament-resolved simulations reproduce self-organization of lamellipodia and filopodia

The dynamic assembly of actin filaments underlies diverse cellular morphologies such as lamellipodia, filopodia, and reticulated networks. However, how filament-scale interactions among actin-binding proteins produce distinct actin architectures remains unclear. We developed a filament-resolved computational model of actin self-organization regulated by the Arp2/3 complex and fascin. Individual F-actin filaments are represented as elastic chains, and their stochastic polymerization, Arp2/3-mediated branching, and fascin-mediated crosslinking and bundling are explicitly modeled. The simulations reproduce three actin architectures observed in minimal reconstitution experiments, including lamellipodia-like branched networks, filopodia-like bundled protrusions, and reticulated meshworks, as a function of Arp2/3 and fascin concentrations. We quantify these regimes using actin density, orientational order, and spikiness, which robustly separate the three morphologies across conditions. To connect filament organization to shape change, we further couple the actin network to membrane deformation using a phase-field formulation. This coupling shows how localized remodeling concentrates load to drive pseudopodial protrusions, whereas highly branched networks distribute stresses and stabilize rounded shapes. The model links molecular interactions to emergent architecture and cell-scale morphodynamics.

biophysics↗

bioRxiv2026

Hog1/p38 and ZAKα drive Shwachman-Diamond syndrome and provide targets to improve cell growth

Shwachman-Diamond syndrome (SDS) is a ribosomopathy characterized by neutropenia, pancreatic insufficiency, skeletal defects, and predisposition to leukemia. Most cases result from biallelic SBDS mutations that impairing 80S ribosome and polysome assembly. In yeast lacking SDO1 (the SBDS ortholog), growth slows dramatically and the p38 ortholog Hog1 signaling is elevated by multiple types of stress. SBDS-deficient HeLa cells exhibited reduced proliferation and slowed cell cycling. The p38 kinase was constitutively activated in SBDS mutants and SDS patient-derived blood cells. Because ZAK detects ribosome dysfunction, its activation links ribosomal defects to stress kinase pathways in SDS. Suppressing p38 or its upstream activator ZAK restored cell growth and reduced stress signaling. These findings reveal an evolutionarily conserved-independent mechanism via p38 drives SDS pathophysiology and identifies stress kinases as potential therapeutic targets for ribosomal dysfunction.

cell biology↗

bioRxiv2025

High-Frequency Activity Encodes the Temporal Dynamics of Hierarchical Prediction Errors in Humans: An Electrocorticography Study

Prediction error refers to the discrepancy between expected and actual sensory input. Its hierarchical organization has been demonstrated through decomposed brain responses in the local-global paradigm, where temporal regularities are established locally at individual stimulus transitions and globally across multi-tone sequence structures. In macaques and marmosets, local and global prediction-error signals have both been found in high-frequency oscillations (60-150 Hz) recorded with ECoG. In humans, however, these signals have primarily been observed in a lower frequency range (30-100 Hz) using EEG. Here, we recorded human ECoG to achieve higher signal fidelity, enabling examination of neural oscillations above 100 Hz (high-frequency activity, HFA), which are believed to be closely linked to local spiking activity. Eight participants listened to auditory sequences that either followed their local and global regularities (local and global standards) or violated them (local and global deviants). Robust HFA responses were observed for the local deviants, but these responses were reduced when the deviants were expected based on the global regularity, indicating both levels of prediction-error processes contribute to the observed activity. Importantly, these HFA responses could be decomposed into two subcomponents: an early component reflecting local prediction-error signals localized to lateral auditory regions, and a late component reflecting global prediction-error signals prominent in both lateral auditory and frontal cortices. Together, these findings demonstrate that neural oscillations above 100 Hz encode hierarchical prediction errors not only in non-human primates but also in humans.

neuroscience↗

bioRxiv2025

Biosynthesis of Kaitocephalin: A Neuroprotective Natural Product Featuring a Peptide-Like yet Non-Peptidic Scaffold

Kaitocephalin (KCP, 1) is a neuroprotective natural product that acts as an antagonist of ionotropic glutamate receptors, making it a highly promising lead for drug discovery. It possesses a unique scaffold composed of three amino acids connected via C-C bonds, which appears peptide-like but is formed without peptide bonds. In this study, we identified the KCP biosynthetic gene cluster (kpb cluster) in the producing fungus Eupenicillium shearii through integrated genomic and transcriptomic analyses. LC-MS/MS profiling and chemical derivatization of E. shearii extracts led to the discovery of four novel pathway-related metabolites (2-5). In vitro enzymatic assays with 2(S)-dechlorokaito lactate (4) as a substrate enabled functional characterization of KpbI, KpbM, and KpbB involved in KCP formation. Among them, the dioxygenase KpbI was found to catalyze an unprecedented two-step oxidation to form the D-serine moiety. In addition, isotope tracing experiments provided new insights into the origin of the L-proline moiety. These findings establish a foundation for future studies aimed at elucidating the complete biosynthetic mechanism of KCP. Table of Contents graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=50 SRC="FIGDIR/small/683206v1_ufig1.gif" ALT="Figure 1"> View larger version (12K): org.highwire.dtl.DTLVardef@189618aorg.highwire.dtl.DTLVardef@62d5deorg.highwire.dtl.DTLVardef@c71341org.highwire.dtl.DTLVardef@1c14e59_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Development of a non-invasive diagnostic method for pathogenic RNA viruses using sebum wiped from the cat's body surface

The development of non-invasive diagnostic methods for zoonotic viral infections is increasingly important for both animal welfare and public health. Sebum-based diagnostic methods using commercial oil-blotting films have been applied to SARS-CoV-2 detection in humans, yet equivalent strategies for veterinary use remain largely unexplored. Severe fever with thrombocytopenia syndrome (SFTS), caused by the SFTS virus (SFTSV), presents a major health threat in Asia--especially in Japan, where multiple cases of cat-to-veterinarian transmission have been reported. To address the need for safer diagnostics, we sought to establish a sebum-based RNA virus detection method for cats. We designed primers that efficiently detected RNA from feline sebum while distinguishing it from human and feline DNA/RNA. Using this platform, we determined the ear to be the optimal sebum collection site and confirmed that feline immunodeficiency virus (FIV) RNA can be reliably identified from ear sebum with sensitivity comparable to conventional blood-based testing. In addition, we detected SFTSV RNA from sebum samples of infected cat. Our findings introduce a minimally invasive, safe diagnostic platform for feline viral infections, reducing animal distress while safeguarding veterinarians and pet owners from zoonotic risks. This strategy marks an important step toward realizing the One Health framework by advancing the well-being of both animals and humans.

microbiology↗

bioRxiv2025

Intrathecal administration of palmitoyl-lysophosphatidylethanolamine reduces secondary injury and improves locomotor recovery following spinal cord injury

Spinal cord injury (SCI) triggers secondary pathophysiological cascades, including glutamate excitotoxicity, that result in neuronal loss and impair functional recovery. We have previously shown that lysophosphatidylethanolamine (LPE), a lysophospholipid, promotes neurite outgrowth and protects against glutamate excitotoxicity in cultured cortical neurons. However, whether these effects extend to spinal cord neurons and occur in vivo has remained unclear. In this study, we compared the effects of different LPE species: myristoyl-LPE (14:0 LPE), palmitoyl-LPE (16:0 LPE), stearoyl-LPE (18:0 LPE), and oleoyl-LPE (18:1 LPE) in cultured spinal commissural neurons, and evaluated their effects in vivo using a mouse model of SCI. In cultured neurons, all LPE species promoted neurite outgrowth. Although several species demonstrated a tendency toward neuroprotection, only 16:0 LPE exhibited a statistically significant protective effect against glutamate-induced excitotoxic cell death. Intrathecal administration of 16:0 LPE after SCI reduced TUNEL-positive cells in the acute phase and attenuated lesion expansion at 8 weeks post-injury. Moreover, 5-HT fluorescence intensity was increased in 16:0 LPE-treated mice, suggesting enhanced serotonergic innervation. Furthermore, administration of 16:0 LPE after SCI significantly improved hind-limb motor performance compared with vehicle controls, as assessed by the Basso Mouse Scale. Collectively, these findings suggest that intrathecal administration of 16:0 LPE reduces secondary injury and promotes functional recovery following SCI. Our findings highlight its potential as a therapeutic candidate for SCI.

neuroscience↗

bioRxiv2024

Diversity of set-related neuronal activity in the dorsal premotor cortex of monkeys during a path-planning task

Actions involve multiple levels. The dorsal premotor area (PMd) of the primate cerebral cortex is involved in the preparation of actions based on perceptual information. In this study, we recorded neuronal activity from the PMd of monkeys while they performed a path-finding task. In the task, the animals were required to move a cursor step by step to a goal in a maze-like display, and the arm movement and the direction of the cursor operation were dissociated. We observed neurons involved in the preparation of a single arm movement and neurons involved in the preparation of a single cursor operation. Cursor operation-related neurons were also obtained from the lateral prefrontal cortex (lPFC), but the PMd neurons showed more preparatory properties during the execution period than the lPFC neurons. Furthermore, we found neurons involved in the preparation of a specific sequence of cursor movements. The PMd included not only all types of single-shot preparatory neurons but also preparatory neurons for a variety of complex sequences for arm movements and cursor manipulation. These results suggest that the PMd contains diverse neurons involved in different levels of action preparation. Such diversity is one of the critical neural bases for robust goal-directed behavior in complex environments. SignificanceThere are different levels in actions. The dorsal premotor cortex (PMd) is involved in the preparation of actions based on perceptual information. Here, we recorded neuronal activity from the PM d of monkeys while performing a path-finding task, i.e., moving a cursor step by step to a goal in a maze-like display. In addition to neurons involved in the preparation of a single arm movement and neurons involved in the preparation of a single cursor operation, cells involved in the preparation of a specific sequence of cursor movements were observed. These results suggest that the PMd contains diverse neurons involved in different levels of action preparation. Such diversity is one of the critical neural bases for robust goal-directed behavior in complex environments.

neuroscience↗

bioRxiv2024

Learning precise segmentation of neurofibrillary tangles from rapid manual point annotations

Accumulation of abnormal tau protein into neurofibrillary tangles (NFTs) is a pathologic hallmark of Alzheimer disease (AD). Accurate detection of NFTs in tissue samples can reveal relationships with clinical, demographic, and genetic features through deep phenotyping. However, expert manual analysis is time-consuming, subject to observer variability, and cannot handle the data amounts generated by modern imaging. We present a scalable, open-source, deep-learning approach to quantify NFT burden in digital whole slide images (WSIs) of post-mortem human brain tissue. To achieve this, we developed a method to generate detailed NFT boundaries directly from single-point-per-NFT annotations. We then trained a semantic segmentation model on 45 annotated 2400{micro}m by 1200{micro}m regions of interest (ROIs) selected from 15 unique temporal cortex WSIs of AD cases from three institutions (University of California (UC)-Davis, UC-San Diego, and Columbia University). Segmenting NFTs at the single-pixel level, the model achieved an area under the receiver operating characteristic of 0.832 and an F1 of 0.527 (196-fold over random) on a held-out test set of 664 NFTs from 20 ROIs (7 WSIs). We compared this to deep object detection, which achieved comparable but coarser-grained performance that was 60% faster. The segmentation and object detection models correlated well with expert semi-quantitative scores at the whole-slide level (Spearmans rho {rho}=0.654 (p=6.50e-5) and {rho}=0.513 (p=3.18e-3), respectively). We openly release this multi-institution deep-learning pipeline to provide detailed NFT spatial distribution and morphology analysis capability at a scale otherwise infeasible by manual assessment.

pathology↗

bioRxiv2023

Evolution of hierarchy and irreversibility in theoretical cell differentiation model

The process of cell differentiation in multicellular organisms is characterized by hierarchy and irreversibility in many cases. However, the conditions and selection pressures that give rise to these characteristics remain poorly understood. By using a mathematical model, here we show that the network of differentiation potency (differentiation diagram) becomes necessarily hierarchical and irreversible by increasing the number of terminally differentiated states under certain conditions. The mechanisms generating these characteristics are clarified using geometry in the cell state space. The results demonstrate that the appearance of these characteristics can be driven without assuming the adaptive significance. The study also provides a new perspective on the structure of gene regulatory networks that produce hierarchical and irreversible differentiation diagrams. These results indicate some constraints on cell differentiation, which are expected to provide a starting point for theoretical discussion of the implicit limits and directions of evolution in multicellular organisms.

biophysics↗

bioRxiv2023

Emergence of Bow-tie Architecture in Evolving Feedforward Networks

Bow-tie architecture is a layered network structure that has a narrow middle layer with multiple inputs and outputs. Such structures are widely seen in the molecular networks in cells, suggesting that a universal evolutionary mechanism underlies the emergence of bow-tie architecture. The previous theoretical studies have implemented evolutionary simulations of the feedforward network to satisfy a given input-output goal, and proposed that the bow-tie architecture emerges when the ideal input- output relation is given as a rank-deficient matrix with mutations in network link strength in a multiplicative manner. Here, we report that the bow-tie network inevitably appears when the link intensities representing molecular interactions are small at the initial condition of the evolutionary simulation, regardless of the rank of the goal matrix. Our dynamical system analysis clarifies the mechanisms underlying the emergence of the bow-tie structure. Further, we demonstrate that the increase in the input-output matrix facilitates the emergence of bow-tie architecture even when starting from strong network links. Our data suggest that bow-tie architecture emerges as a side effect of evolution rather than as a result of evolutionary adaptation. Author SummaryMany biological networks including gene regulatory networks, metabolic networks, and signaling networks, show a characteristic hierarchical structure known as the bow-tie architecture. This architecture consists of a narrow middle layer with multiple inputs and outputs. Understanding why bow-tie architecture has universally appeared through evolution may provide insight into the design principle of a network within a cell. The universality of the bow-tie structure has so far been explained by the adaptive advantages such as high evolvability and capability to classify the inputs. However, our computer simulation demonstrates that the bow-tie structure inevitably emerges even without functional advantages when the molecular interactions within the network are weak at the initial condition of the evolution. We also demonstrate that an increase in the number of inputs (i.e., receptors) and outputs (i.e., downstream genes) leads to the emergence of bow-tie architecture, even when evolution starts from a strong molecular interaction. Although many previous studies have discussed the adaptive properties of bow-tie architecture, our findings suggest that bow-tie architecture is a byproduct of evolution rather than a result of evolutionary adaptation.

systems biology↗

bioRxiv2023

Cis-regulatory evolution that caused change in wingless expression pattern associated with wing pigmentation pattern of Drosophila

Genetic mechanisms underlying the acquisition of new traits are an important topic in evolutionary developmental biology. Especially, the co-option of important regulatory genes potentially plays an important role in the gain of new traits. However, how the co-option occurs at the sequence level is still elusive. Drosophila guttifera has a unique wing pigmentation pattern and this is newly gained via the evolution of the expression pattern of wingless, which induces the pigmentation pattern formation. In this study, to reveal the changes in the cis-regulatory sequence which caused the co-option of wingless that lead to the expression in a new place, we conducted transgenic EGFP reporter assays of altered cis-regulatory sequences. As a result, the sequence was divided into regions needed to activate expression in the entire wing veins and a region required for repressing expression in excess parts. Comparisons with the homologous sequence of Drosophila melanogaster showed that the repressive function of the cis-regulatory region is also possessed by D. melanogaster while the activating function is newly gained in a lineage leading to D. guttifera. Furthermore, a putative binding site of SMAD transcription factors is shown to be essential for activating expression but also existing in the homologous region of D. melanogaster. Our results suggest that the pre-existing regulatory sequences in the cis-regulatory region coordinate with the newly gained sequences to acquire the new expression pattern of wingless. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

developmental biology↗

bioRxiv2022

A model explaining environmental stiffness-dependent migration of fibroblasts with a focus on maturation of intracellular structures

Cell migration is fundamental to many biological processes, while it remains elusive how cells modulate their migration upon different environmental stiffness. In this work, we focus on the structural maturity of actin stress fibers to explain the substrate stiffness-dependent emergence of different cell migration velocity. We demonstrate that fibroblasts migrate longer distances on softer elastic substrates, and the distance is increased by lowering the myosin-driven contractile force. Stress fibers, the major intracellular structure to generate and sustain contractile forces, were found to be less mature in structure on soft substrate than on stiff substrate. Based on these experimental results, we present a minimal mathematical model to capture the salient features of how the substrate stiffness alters the migration velocity. Specifically, the ability of cells to generate large contractile forces is limited on soft substrate according to the Hookes law. The inverse relationship between the cellular force and migration velocity is described by the Hills muscle equation. These mathematical descriptions suggest that the migration velocity is raised on softer substrate where cells exert a lower magnitude of contractile forces. Cells undergoing faster movement make stress fibers less mature in structure as mathematically described by the maturation model, thereby limiting the ability to sustain the force and in turn allowing for consistent increase in cell migration velocity on soft substrate again according to the Hookes law and Hills muscle equation, respectively. Thus, our model, reproducing the basic trend of the experimental results, provides insights into the mechanisms of environmental cue-dependent migratory behavior of cells.

biophysics↗

bioRxiv2022

Establishment of Measles Virus Receptor-expressing Vero Cells Lacking Functional Poliovirus Receptors

Global efforts are underway to eliminate measles and rubella and active viral surveillance is key to achieving this goal. In addition to this, the World Health Organization announced guidelines for handling materials potentially infectious for poliovirus (PV) to minimize the risk of PV reintroduction and achieve PV eradication. To support the global efforts, we have established new PV-non-susceptible cell lines useful for the isolation of measles virus (MeV) and rubella virus (RuV) (Vero {Delta}PVR1/2 hSLAM+). In the cell lines, MeV and RuV replicated efficiently with no concern about PV replication.

microbiology↗

bioRxiv2022

A method for morphological feature extraction based on variational auto-encoder : an application to mandible shape

Shape analysis of biological data is crucial for investigating the morphological variations during development or evolution. However, conventional approaches for quantifying shapes are difficult as exemplified by the ambiguity in the landmark-based method in which anatomically prominent "landmarks" are manually annotated. In this study, a morphological regulated variational autoencoder (Morpho-VAE) is proposed that conducts image-based shape analysis using imaging processing through a deep-learning framework, thereby removing the need for defining landmarks. The proposed architecture comprises a VAE combined with a classifier module. This integration of unsupervised and supervised learning models (i.e., VAE and classifier modules) is designed to reduce dimensionality by focusing on the morphological features in which the differences between data with different labels are best distinguished. The proposed method is applied to the image dataset of the primate mandible to extract morphological features, which allow us to distinguish different families in a low dimensional latent space. Furthermore, the visualization analysis of decision-making of Morpho-VAE clarifies the area of the mandibular joint that is important for family-level classification. The generative nature of the proposed model is also demonstrated to complement a missing image segment based on the remaining structure. Therefore, the proposed method, which flexibly performs landmark-free feature extraction from complete and incomplete image data is a promising tool for analyzing morphological datasets in biology. AUTHOR SUMMARYShape is the most intuitive visual characteristic; however, shape is generally difficult to measure using a small number of variables. Specifically, for biological data, shape is sometimes highly diverse as it has been acquired through a long evolutionary process, adaptation to environmental factors, etc., which limits the straightforward approach to shape measurement. Therefore, a systematic method for quantifying such a variety of shapes using a low-dimensional quantity is needed. To this end, we propose a novel method that extracts low-dimensional features to describe shapes from image data using machine learning. The proposed method is applied to the primate mandible image data to extract morphological features that reflect the characteristics of the groups to which the organisms belong and then those features are visualized. This method also reconstructs a missing image segment from an incomplete image based on the remaining structure. To summarize, this method is applicable to the shape analysis of various organisms and is a useful tool for analyzing a wide variety of image data, even those with a missing segment.

bioinformatics↗

bioRxiv2020

Microbial Potlatch: Cell-level adaptation of leakiness of metabolites leads to resilient symbiosis among diverse cells

Microbial communities display extreme diversity, facilitated by the secretion of chemicals that can create new niches. However, it is unclear why cells often secrete even essential metabolites after evolution. By noting that cells can enhance their own growth rate by leakage of essential metabolites, we show that such leaker cells can benefit from coexistence with cells that consume the leaked chemicals in the environment. This leads to an unusual form of mutualism between "leaker" and "consumer" cells, resulting in frequency-dependent coexistence of multiple microbial species, as supported by extensive simulations. Remarkably, such symbiotic relationships generally evolve when each species adapts its leakiness to optimize its own growth rate under crowded conditions and nutrient limitations, leading to ecosystems with diverse species exchanging many metabolites with each other. In addition, such ecosystems are resilient against structural and environmental perturbations. Thus, we present a new basis for diverse, complex microbial ecosystems.

ecology↗

bioRxiv2020

Comparative mapping of crawling-cell morphodynamics in deep learning-based feature space

Navigation of fast migrating cells such as amoeba Dictyostelium and immune cells are tightly associated with their morphologies that range from steady polarized forms that support high directionality to those more complex and variable when making frequent turns. Model simulations are essential for quantitative understanding of these features and their origins, however systematic comparisons with real data are underdeveloped. Here, by employing deep-learning-based feature extraction combined with phase-field modeling framework, we show that a low dimensional feature space for 2D migrating cell morphologies obtained from the shape stereotype of keratocytes, Dictyostelium and neutrophils can be fully mapped by interlinked signaling network of cell-polarization and protrusion dynamics. Our analysis links the data-driven shape analysis to the underlying causalities by identifying key parameters critical for migratory morphologies both normal and aberrant under genetic and pharmacological perturbations. The results underscore the importance of deciphering self-organizing states and their interplay when characterizing morphological phenotypes.

cell biology↗