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At least 163 records · Page 9

Characterization of promoter elements of isoprene‐responsive genes and the ability of isoprene to bind START domain transcription factors

Abstract Isoprene has recently been proposed to be a signaling molecule that can enhance tolerance of both biotic and abiotic stress. Not all plants make isoprene, but all plants tested to date respond to isoprene. We hypothesized that isoprene interacts with existing signaling pathways rather than requiring novel mechanisms for its effect on plants. We analyzed the cis‐regulatory elements (CREs) in promoters of isoprene‐responsive genes and the corresponding transcription factors binding these promoter elements to obtain clues about the transcription factors and other proteins involved in isoprene signaling. Promoter regions of isoprene‐responsive genes were characterized using the Arabidopsis cis‐regulatory element database. CREs bind ARR1, Dof, DPBF, bHLH112, GATA factors, GT‐1, MYB, and WRKY transcription factors, and light‐responsive elements were overrepresented in promoters of isoprene‐responsive genes; CBF‐, HSF‐, WUS‐binding motifs were underrepresented. Transcription factors corresponding to CREs overrepresented in promoters of isoprene‐responsive genes were mainly those important for stress responses: drought‐, salt/osmotic‐, oxidative‐, herbivory/wounding and pathogen‐stress. More than half of the isoprene‐responsive genes contained at least one binding site for TFs of the class IV (homeodomain leucine zipper) HD‐ZIP family, such as GL2, ATML1, PDF2, HDG11, ATHB17. While the HD‐zipper‐loop‐zipper (ZLZ) domain binds to the L1 box of the promoter region, a special domain called the steroidogenic acute regulatory protein‐related lipid transfer, or START domain, can bind ligands such as fatty acids (e.g., linolenic and linoleic acid). We tested whether isoprene might bind in such a START domain. Molecular simulations and modeling to test interactions between isoprene and a class IV HD‐ZIP family START‐domain‐containing protein were carried out. Without membrane penetration by the HDG11 START domain, isoprene within the lipid bilayer was inaccessible to this domain, preventing protein interactions with membrane bound isoprene. The cross‐talk between isoprene‐mediated signaling and other growth regulator and stress signaling pathways, in terms of common CREs and transcription factors could enhance the stability of the isoprene emission trait when it evolves in a plant but so far it has not been possible to say what how isoprene is sensed to initiate signaling responses.

60 APPLIED LIFE SCIENCES↗

Ligand‐induced CaMKIIα hub Trp403 flip, hub domain stacking, and modulation of kinase activity

Abstract γ‐Hydroxybutyric acid (GHB) analogs are small molecules that bind competitively to a specific cavity in the oligomeric CaMKIIα hub domain. Binding affects conformation and stability of the hub domain, which may explain the neuroprotective action of some of these compounds. Here, we describe molecular details of interaction of the larger‐type GHB analog 2‐(6‐(4‐chlorophenyl)imidazo[1,2‐b]pyridazine‐2‐yl)acetic acid (PIPA). Like smaller‐type analogs, PIPA binding to the CaMKIIα hub domain promoted thermal stability. PIPA additionally modulated CaMKIIα activity under sub‐maximal CaM concentrations and ultimately led to reduced substrate phosphorylation. A high‐resolution X‐ray crystal structure of a stabilized CaMKIIα (6x mutant) hub construct revealed details of the binding mode of PIPA, which involved outward placement of tryptophan 403 (Trp403), a central residue in a flexible loop close to the upper hub cavity. Small‐angle X‐ray scattering (SAXS) solution structures and mass photometry of the CaMKIIα wild‐type hub domain in the presence of PIPA revealed a high degree of ordered self‐association (stacks of CaMKIIα hub domains). This stacking neither occurred with the smaller compound 3‐hydroxycyclopent‐1‐enecarboxylic acid (HOCPCA), nor when Trp403 was replaced with leucine (W403L). Additionally, CaMKIIα W403L hub was stabilized to a larger extent by PIPA compared to CaMKIIα hub wild type, indicating that loop flexibility is important for holoenzyme stability. Thus, we propose that ligand‐induced outward placement of Trp403 by PIPA, which promotes an unforeseen mechanism of hub domain stacking, may be involved in the observed reduction in CaMKIIα kinase activity. Altogether, this sheds new light on allosteric regulation of CaMKIIα activity via the hub domain.

Biochemistry & Molecular Biology↗

Identifying Differential Equations in Fourier Domain (FourierIdent)

We investigate identifying differential equations in the frequency domain. Fourier analysis is an important tool in theoretical analysis and numerical solvers of differential equations, yet there is limited work in exploring this connection in the identification of differential equations. This paper aims to identify the underlying differential equation in the frequency domain, from a given single realization of the differential equation perturbed by noise. Such setting imposes difficulties which are different from other identification methods where computation is carried out in the physical domain. We propose several ways to mitigate the challenges arising from noise in data and large differences in the magnitudes of frequency responses. The main takeaways are that identifying differential equations solely in the frequency domain is challenging, the method we propose is based on a form of domain partitions in the frequency domain, and this method shows benefits for complex data even with high level of noise. We introduce a Fourier feature denoising, and define the meaningful data region and the core regions of features to reduce the effect of noise in the frequency domain and to enhance the accuracy in coefficient identification. The proposed method is tested on various differential equations with linear, nonlinear, and high-order derivative feature terms, and shows advantages on complex data with many frequency modes, even under high level of noise.

97 MATHEMATICS AND COMPUTING↗

Systematic identification of transcriptional activation domains from non-transcription factor proteins in plants and yeast

Transcription factors can promote gene expression through activation domains. Whole-genome screens have systematically mapped activation domains in transcription factors but not in non-transcription factor proteins (e.g., chromatin regulators and coactivators). To fill this knowledge gap, we employed the activation domain predictor PADDLE to analyze the proteomes of Arabidopsis thaliana and Saccharomyces cerevisiae. We screened 18,000 predicted activation domains from >800 non-transcription factor genes in both species, confirming that 89% of candidate proteins contain active fragments. Our work enables the annotation of hundreds of nuclear proteins as putative coactivators, many of which have never been ascribed any function in plants. Analysis of peptide sequence compositions reveals how the distribution of key amino acids dictates activity. Finally, we validated short, "universal" activation domains with comparable performance to state-of-the-art activation domains used for genome engineering. Our approach enables the genome-wide discovery and annotation of activation domains that can function across diverse eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗

Film Thickness and Composition Effects in Symmetric Ternary Block Copolymer/Homopolymer Blend Films: Domain Spacing and Orientation

We report thickness and homopolymer molar mass dependencies in thin film blends of a compositionally symmetric 75 kg/mol lamellar polystyrene-block-poly(methyl methacrylate) diblock copolymer (PS-b-PMMA) with near-equal volume fractions of PS and PMMA homopolymers on “neutral” surfaces that promote a vertical domain orientation. PS and PMMA homopolymers with equal molar masses of 1, 3, and 22 kg/mol are blended in a 1:1 mass ratio. To efficiently explore this parameter space, we prepared combinatorial samples with gradient homopolymer concentrations using electrospray deposition (ESD) and gradient film thicknesses using flow coating; these samples were subsequently characterized by grazing-incidence small-angle X-ray scattering and scanning electron microscopy, respectively. Our results demonstrate that the added homopolymers increase or reduce domain spacings with respect to the neat (unblended) block copolymer depending on their molar masses, in line with previous reports; a simple heuristic to estimate the domain scaling in ternary blends based on the homopolymer molar mass agrees well with data for the thinnest blend films studied here. More surprisingly, we observe that the measured domain spacing in blends also depends on film thickness, with thicker films exhibiting larger domain spacings than thinner films at the same homopolymer concentration. Furthermore, thickness gradients at fixed homopolymer concentrations reveal a change in lamellae orientation from vertical to horizontal as film thickness is increased beyond the nominal lamellar domain spacing. Coarse-grained molecular dynamics simulations indicate that this change in orientation is induced by homopolymer segregation to film surfaces. Finally, tying these effects together, we hypothesize that the observed dependence of domain spacing on film thickness is a consequence of changes in the vertical homopolymer composition profile in thicker films during lamellae reorientation and the conformational asymmetry between PMMA and PS segments.

36 MATERIALS SCIENCE↗

The structural basis for regulation of the glutathione transporter Ycf1 by regulatory domain phosphorylation

Yeast Cadmium Factor 1 (Ycf1) sequesters heavy metals and glutathione into the vacuole to counter cell stress. Ycf1 belongs to the ATP binding cassette C-subfamily (ABCC) of transporters, many of which are regulated by phosphorylation on intrinsically-disordered domains. The regulatory mechanism of phosphorylation is still poorly understood. Here, we report two cryo-EM structures of Ycf1 at 3.4 Å and 4.0 Å resolution in inward-facing open conformations that capture previously unobserved ordered states of the intrinsically disordered regulatory domain (R-domain). R-domain phosphorylation is clearly evident and induces a topology promoting electrostatic and hydrophobic interactions with Nucleotide Binding Domain 1 (NBD1) and the Lasso motif. These interactions stay constant between the structures and are related by rigid body movements of the NBD1/R-domain complex. Biochemical data further show R-domain phosphorylation reorganizes the Ycf1 architecture and is required for maximal ATPase activity. Together, we provide insights into how R-domains control ABCC transporter activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural basis for autoinhibition by the dephosphorylated regulatory domain of Ycf1

Yeast Cadmium Factor 1 (Ycf1) sequesters glutathione and glutathione-heavy metal conjugates into yeast vacuoles as a cellular detoxification mechanism. Ycf1 belongs to the C subfamily of ATP Binding Cassette (ABC) transporters characterized by long flexible linkers, notably the regulatory domain (R-domain). R-domain phosphorylation is necessary for activity, whereas dephosphorylation induces autoinhibition through an undefined mechanism. Because of its transient and dynamic nature, no structure of the dephosphorylated Ycf1 exists, limiting understanding of this R-domain regulation. Here, we capture the dephosphorylated Ycf1 using cryo-EM and show that the unphosphorylated R-domain indeed forms an ordered structure with an unexpected hairpin topology bound within the Ycf1 substrate cavity. This architecture and binding mode resemble that of a viral peptide inhibitor of an ABC transporter and the secreted bacterial WXG peptide toxins. We further reveal the subset of phosphorylation sites within the hairpin turn that drive the reorganization of the R-domain conformation, suggesting a mechanism for Ycf1 activation by phosphorylation-dependent release of R-domain mediated autoinhibition.

59 BASIC BIOLOGICAL SCIENCES↗

Probing ferroelectric domain structures and their switching dynamics in SrBi2Ta2O9 by in-situ electric biasing in transmission electron microscopy

Abstract Lead-free SrBi 2 Ta 2 O 9 (SBT) has been a promising ferroelectric material for various applications such as electronics and data storage due to its outstanding ferroelectric properties including high fatigue endurance and low leakage current. However, the atomic-scale domain structure and switching dynamics of ferroelectric SBT remain elusive. This study reveals that spontaneous polarization arises from canted bismuth-cation displacements, forming 90° and Ising-type 180° domain walls. Interestingly, topological pairs of ferroelectric vortex and antivortex connect ferroelectric boundaries where three domain walls converge. In situ electrical biasing transmission electron microscopy (TEM) reveals the dominance of 180° switching over 90°, where oxygen octahedral connectivity is protected by ferroelastic energy in the 90° domain wall. Consequently, all 180° domain walls and (anti)vortices are removed, leaving only 90° domain walls in the electrically poled states. Chemical deterioration along domain walls highlights vulnerability of SBT to ferroelectric fatigue. This study provides insight into crucial aspects for practical applications of SBT.

36 MATERIALS SCIENCE↗

Domain wall-magnetic tunnel junction spin–orbit torque devices and circuits for in-memory computing

There are pressing problems with traditional computing, especially for accomplishing data-intensive and real-time tasks, that motivate the development of in-memory computing devices to both store information and perform computation. Magnetic tunnel junction memory elements can be used for computation by manipulating a domain wall, a transition region between magnetic domains, but the experimental study of such devices has been limited by high current densities and low tunnel magnetoresistance. Here, we study prototypes of three-terminal domain wall-magnetic tunnel junction in-memory computing devices that can address data processing bottlenecks and resolve these challenges by using perpendicular magnetic anisotropy, spin–orbit torque switching, and an optimized lithography process to produce average device tunnel magnetoresistance TMR = 171% and average resistance-area product RA = 29 Ω μm2, close to the RA of the unpatterned film. Device initialization variation in switching voltage is shown to be curtailed to 7%–10% by controlling the domain wall initial position, which we show corresponds to 90%–96% accuracy in a domain wall-magnetic tunnel junction full adder simulation. Repeatability of writing and resetting the device is shown. A circuit shows an inverter operation between two devices, showing that a voltage window is large enough, compared to the variation noise, to repeatably operate a domain wall-magnetic tunnel junction circuit. These results make strides in using magnetic tunnel junctions and domain walls for in-memory and neuromorphic computing applications.

Alamdar, Mahshid (ORCID:0000000221732935)↗

Nanoscale visualization of the thermally driven evolution of antiferromagnetic domains in FeTe thin films

Antiferromagnetic order, being a ground state of a number of exotic quantum materials, is of immense interest both from the fundamental physics perspective and for driving potential technological applications. For a complete understanding of antiferromagnetism in materials, nanoscale visualization of antiferromagnetic domains, domain walls, and their robustness to external perturbations is highly desirable. Here, we synthesize antiferromagnetic FeTe thin films using molecular-beam epitaxy. We visualize local antiferromagnetic ordering and domain formation using spin-polarized scanning tunneling microscopy. From the atomically resolved scanning tunneling microscopy topographs, we calculate local structural distortions to find a high correlation with the distribution of the antiferromagnetic order. This is consistent with the monoclinic structure in the antiferromagnetic state. Interestingly, we observe a substantial domain-wall change by small temperature variations, unexpected for the low-temperature changes used compared to the much higher antiferromagnetic ordering temperature of FeTe. This is in contrast to electronic nematic domains in the cousin FeSe multilayer films, where we find no electronic or structural change within the same temperature range. Further, our experiments provide the atomic-scale imaging of perturbation-driven magnetic domain evolution simultaneous with the ensuing structural response of the system. The results reveal surprising thermally driven modulations of antiferromagnetic domains in FeTe thin films well below the Néel temperature.

36 MATERIALS SCIENCE↗

Mapping domain structures near a grain boundary in a lead zirconate titanate ferroelectric film using X-ray nanodiffraction

The effect of an electric field on local domain structure near a 24° tilt grain boundary in a 200 nm-thick Pb(Zr 0.2 Ti 0.8 )O 3 bi-crystal ferroelectric film was probed using synchrotron nanodiffraction. The bi-crystal film was grown epitaxially on SrRuO 3 -coated (001) SrTiO 3 24° tilt bi-crystal substrates. From the nanodiffraction data, real-space maps of the ferroelectric domain structure around the grain boundary prior to and during application of a 200 kV cm −1 electric field were reconstructed. In the vicinity of the tilt grain boundary, the distributions of densities of c -type tetragonal domains with the c axis aligned with the film normal were calculated on the basis of diffracted intensity ratios of c - and a -type domains and reference powder diffraction data. Diffracted intensity was averaged along the grain boundary, and it was shown that the density of c -type tetragonal domains dropped to ∼50% of that of the bulk of the film over a range ±150 nm from the grain boundary. This work complements previous results acquired by band excitation piezoresponse force microscopy, suggesting that reduced nonlinear piezoelectric response around grain boundaries may be related to the change in domain structure, as well as to the possibility of increased pinning of domain wall motion. The implications of the results and analysis in terms of understanding the role of grain boundaries in affecting the nonlinear piezoelectric and dielectric responses of ferroelectric materials are discussed.

36 MATERIALS SCIENCE↗

Crystal structure of the kinase domain of a receptor tyrosine kinase from a choanoflagellate, Monosiga brevicollis

Genomic analysis of the unicellular choanoflagellate, Monosiga brevicollis (MB), revealed the remarkable presence of cell signaling and adhesion protein domains that are characteristically associated with metazoans. Strikingly, receptor tyrosine kinases, one of the most critical elements of signal transduction and communication in metazoans, are present in choanoflagellates. We determined the crystal structure at 1.95 Å resolution of the kinase domain of the M . brevicollis receptor tyrosine kinase C8 (RTKC8, a member of the choanoflagellate receptor tyrosine kinase C family) bound to the kinase inhibitor staurospaurine. The chonanoflagellate kinase domain is closely related in sequence to mammalian tyrosine kinases (~ 40% sequence identity to the human Ephrin kinase domain EphA3) and, as expected, has the canonical protein kinase fold. The kinase is structurally most similar to human Ephrin (EphA5), even though the extracellular sensor domain is completely different from that of Ephrin. The RTKC8 kinase domain is in an active conformation, with two staurosporine molecules bound to the kinase, one at the active site and another at the peptide-substrate binding site. To our knowledge this is the first example of staurospaurine binding in the Aurora A activation segment (AAS). We also show that the RTKC8 kinase domain can phosphorylate tyrosine residues in peptides from its C-terminal tail segment which is presumably the mechanism by which it transmits the extracellular stimuli to alter cellular function.

59 BASIC BIOLOGICAL SCIENCES↗

Allosteric activation or inhibition of PI3Kγ mediated through conformational changes in the p110γ helical domain

PI3Kγ is a critical immune signaling enzyme activated downstream of diverse cell surface molecules, including Ras, PKCβ activated by the IgE receptor, and Gβγ subunits released from activated GPCRs. PI3Kγ can form two distinct complexes, with the p110γ catalytic subunit binding to either a p101 or p84 regulatory subunit, with these complexes being differentially activated by upstream stimuli. Here, using a combination of cryo electron microscopy, HDX-MS, and biochemical assays, we have identified novel roles of the helical domain of p110γ in regulating lipid kinase activity of distinct PI3Kγ complexes. We defined the molecular basis for how an allosteric inhibitory nanobody potently inhibits kinase activity through rigidifying the helical domain and regulatory motif of the kinase domain. The nanobody did not block either p110γ membrane recruitment or Ras/Gβγ binding, but instead decreased ATP turnover. We also identified that p110γ can be activated by dual PKCβ helical domain phosphorylation leading to partial unfolding of an N-terminal region of the helical domain. PKCβ phosphorylation is selective for p110γ-p84 compared to p110γ-p101, driven by differential dynamics of the helical domain of these different complexes. Nanobody binding prevented PKCβ-mediated phosphorylation. Overall, this work shows an unexpected allosteric regulatory role of the helical domain of p110γ that is distinct between p110γ-p84 and p110γ-p101 and reveals how this can be modulated by either phosphorylation or allosteric inhibitory binding partners. This opens possibilities of future allosteric inhibitor development for therapeutic intervention.

59 BASIC BIOLOGICAL SCIENCES↗

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

Ntampaka, Michelle [Baltimore, Space Telescope Sci↗

HydroDCM: Hydrological Domain-Conditioned Modulation for Cross-Reservoir Inflow Prediction

Deep learning models have shown promise in reservoir inflow prediction, yet their performance often deteriorates when applied to different reservoirs due to distributional differences, referred to as the domain shift problem. Domain generalization (DG) solutions aim to address this issue by extracting domain-invariant representations that mitigate errors in unseen domains. However, in hydrological settings, each reservoir exhibits unique inflow patterns, while some metadata beyond observations like spatial information exerts indirect but significant influence. This mismatch limits the applicability of conventional DG techniques to many-domain hydrological systems. To overcome these challenges, we propose HydroDCM, a scalable DG framework for cross-reservoir inflow forecasting. Spatial metadata of reservoirs is used to construct pseudo-domain labels that guide adversarial learning of invariant temporal features. During inference, HydroDCM adapts these features through light-weight conditioning layers informed by the target reservoir’s metadata, reconciling DG’s invariance with location-specific adaptation. Experiment results on 30 real-world reservoirs in the Upper Colorado River Basin demonstrate that our method substantially outperforms state-of-the-art DG baselines under many-domain conditions and remains computationally efficient.

Hu, Pengfei [ORNL] (ORCID:0009000367130950)↗

Vortex Domain Walls in Ferroelectrics

Controlling the domain formation in ferroelectric materials at the nanoscale is a fertile ground to explore emergent phenomena and their technological prospects. For example, charged ferroelectric domain walls in BiFeO 3 and ErMnO 3 exhibit significantly enhanced conductivity which could serve as the foundation for next-generation circuits. In this work, we describe a concept in which polar vortices perform the same role as a ferroelectric domain wall in classical domain structures with the key difference being that the polar vortices can accommodate charged (i.e., head-to-head and tail-to-tail) domains, for example, in ferroelectric PbTiO 3 /dielectric SrTiO 3 superlattices. Such a vortex domain wall structure can be manipulated in a reversible fashion under an external applied field.

36 MATERIALS SCIENCE↗

Observation of Antiferroelectric Domain Walls in a Uniaxial Hyperferroelectric

Abstract Ferroelectric domain walls are a rich source of emergent electronic properties and unusual polar order. Recent studies show that the configuration of ferroelectric walls can go well beyond the conventional Ising‐type structure. Néel‐, Bloch‐, and vortex‐like polar patterns have been observed, displaying strong similarities with the spin textures at magnetic domain walls. Here, the discovery of antiferroelectric domain walls in the uniaxial ferroelectric Pb 5 Ge 3 O 11 is reported. Highly mobile domain walls with an alternating displacement of Pb atoms are resolved, resulting in a cyclic 180° flip of dipole direction within the wall. Density functional theory calculations show that Pb 5 Ge 3 O 11 is hyperferroelectric, allowing the system to overcome the depolarization fields that usually suppress the antiparallel ordering of dipoles along the longitudinal direction. Interestingly, the antiferroelectric walls observed under the electron beam are energetically more costly than basic head‐to‐head or tail‐to‐tail walls. The results suggest a new type of excited domain‐wall state, expanding previous studies on ferroelectric domain walls into the realm of antiferroic phenomena.

36 MATERIALS SCIENCE↗

An adaptive adversarial domain adaptation approach for corn yield prediction

Recently, statistical machine learning and deep learning methods have been widely explored for corn yield prediction. Though successful, machine learning models generated within a specific spatial domain often lose their validity when directly applied to new regions. To address this issue, we designed an unsupervised adaptive domain adversarial neural network (ADANN). Specifically, through domain adversarial training, the ADANN model reduced the impact of domain shift by projecting data from different domains into the same subspace. Also, the ADANN model was designed to be trained in an adaptive way, which guaranteed the model can learn the domain-invariant features and perform accurate yield prediction simultaneously. Informative variables including time-series vegetation indices and sequential weather observations were first collected from multiple data sources and aggregated to the county level. Then, we trained the ADANN model with the extracted features and corresponding reported county-level corn yield from the U.S. Department of Agriculture (USDA). Finally, the trained model was evaluated in four testing years 2016–2019. The U.S. corn belt was used as the study area and counties under study were grouped into two diverse ecological regions. Overall, the experimental results showed that the developed ADANN model had better performance than three other state-of-the-art machine learning models in both local experiments (train and test in the same region) and transfer experiments (train and test in different regions). As the first study using adversarial learning for crop yield prediction, this research demonstrates a novel solution for improving model transferability on crop yield prediction.

59 BASIC BIOLOGICAL SCIENCES↗