Biology subjects

Jin, J.

Publications and source records attributed to Jin, J..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Structure of the SMYD2-PARP1 Complex Reveals Both Productive and Allosteric Modes of Peptide Binding

Allosteric regulation allows proteins to dynamically respond to environmental cues by modulating activity at sites away from the catalytic center. Despite its importance, the SET-domain protein lysine methyltransferase superfamily has been understudied. Here, we present four crystal structures of SMYD2, a unique family member with a MYND domain. Our findings reveal a novel allosteric binding site with high conformational plasticity and promiscuity, capable of binding peptides, proteins, PEG, and small molecules. This site exhibits positive cooperativity with substrate binding, influencing catalytic activity. Mutations here significantly alter substrate affinity, changing the enzymes kinetic profile. Specificity studies show interaction with PARP1 but not histones, suggesting targeted regulation. Interestingly, this sites function remains unaffected by active site changes, indicating unidirectional mechanisms. Our discovery provides novel insights into SMYD2s biochemical regulation and lays the foundation for broader research on allosteric control in lysine methyltransferases. Given SMYD2s role in various cancers, this work opens exciting avenues for designing specific allosteric inhibitors with reduced off-target effects.

biochemistry↗

bioRxiv2024

One score to rule them all: regularized ensemble polygenic risk prediction with GWAS summary statistics

Ensemble learning has become a cornerstone for improving the predictive accuracy of polygenic risk scores (PRS), and nearly all recent multi-ancestry PRS methods incorporate ensemble learning as a final step. However, existing ensemble approaches require individual-level genotype data for model training, which limits their real-world applications, especially in non-European populations without sufficient genomic samples. Here, we introduce a statistical framework for constructing regularized ensemble PRS that integrates a large number of candidate PRS models using only genome-wide association study summary statistics. Through extensive analyses across multiple traits and populations, we demonstrate that our method consistently outperforms state-of-the-art PRS approaches within and across ancestries. This framework presents "one score to rule them all" for its capability to enable seamless integration of newly developed PRS models with existing ones, providing a scalable and general solution for future PRS development and application.

genetics↗

bioRxiv2024

Optical blur affects differently ON and OFF visual pathways

The human eye has a crystalline lens that focuses retinal images at the point of fixation. Outside this fixation region, images are distorted by optical blur, which increases light scatter and reduces the spatial resolution and contrast processed by neuronal pathways. The spectacle lenses that humans use for optical correction also minify or magnify the images, affecting neuronal surround suppression in visual processing. Because light and dark stimuli are processed with ON and OFF pathways that have different spatial resolution, contrast sensitivity and surround suppression, optical blur and image magnification should affect differently the two pathways and the perception of lights and darks. Our results provide support for this prediction in cats and humans. We demonstrate that optical blur expands ON receptive fields while shrinking OFF receptive fields, as expected from the expansion of light stimuli and shrinkage of dark stimuli with light scatter. Spectacle-induced image magnification also shrinks OFF more than ON receptive fields, as expected from the stronger surround suppression in OFF than ON pathways. Optical blur also decreases the population response of OFF more than ON pathways, consistent with the different effects of light scatter on dark and light stimuli and the ON-OFF pathway differences in contrast sensitivity. Based on these results, we conclude that optical blur and image magnification reduce the receptive field sizes and cortical responses of OFF more than ON pathways, making the ON-OFF response balance a reliable signal to optimize the size and quality of the retinal image. HIGHLIGHTSO_LIOptical blur affects ON and OFF pathways differently. C_LIO_LIBlur expands ON but shrinks OFF receptive fields, weakening OFF more than ON signals. C_LIO_LIMagnification from positive blur reduces OFF more than ON signal strength and latency. C_LIO_LION-OFF response balance can signal retinal image quality and guide eye growth. C_LI IN BRIEFPons et al. demonstrate that optical blur affects differently the receptive field properties and responses from ON and OFF visual pathways, revealing a new relation between ON/OFF pathway balance and blurred visual perception. The results highlight a new role of ON and OFF pathways in optimizing retinal image quality that can have implications for the regulation of eye growth. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/618707v1_ufig1.gif" ALT="Figure 1"> View larger version (96K): org.highwire.dtl.DTLVardef@9161eorg.highwire.dtl.DTLVardef@8b11beorg.highwire.dtl.DTLVardef@39e5bdorg.highwire.dtl.DTLVardef@119fd42_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

A Graph Informed Framework Empowering Gene Pathway Discovery and Gene Expression-Assisted Disease Classification

This study introduces a novel graph-informed modeling framework for improving the statistical analysis of gene expression data, particularly in the context of identifying differentially expressed gene pathways and gene expression-assisted disease classification in a high-dimensional data setting. By integrating gene regulatory network information into hypothesis testing for the difference between mean vectors and linear discriminant analysis, we aim to effectively capture and utilize previously validated external gene interaction information. Our method leverages a block-coordinate descent approach which enables us to incorporate mixed graph information into linear structural equation modeling, accommodating directed/undirected edges and potential cycles in gene regulatory networks. Extensive simulations under various data scenarios have demonstrated the effectiveness of our approach with improved power for gene pathway tests and disease classification over existing methods. An application to a lung cancer dataset from the Cancer Genome Atlas Program (TCGA) further exemplifies the potential of our graph-informed approach in empowering the detection of differentially expressed gene pathways and gene expression-based classification of different lung cancer stages. Our findings underscore the potential utility of incorporating gene regulatory network information in gene pathway analysis, setting the stage for future advancements in gene pathway discovery, disease diagnosis, and treatment strategies.

genomics↗

bioRxiv2024

Feasibility of laminar functional quantitative susceptibility mapping

Layer fMRI is an increasingly utilized technique that provides insights into the laminar organization of brain activity. However, both blood-oxygen-level-dependent (BOLD) fMRI and vascular space occupancy data (VASO) have certain limitations, such as bias towards larger cortical veins in BOLD fMRI and high specific absorption rate in VASO. This study aims to explore the feasibility of whole-brain laminar functional quantitative susceptibility mapping (fQSM) compared to laminar BOLD fMRI and VASO at ultra-high field. Data were acquired using 3D EPI techniques. Complex data were denoised with NORDIC and susceptibility maps were computed using 3D path-based unwrapping, the variable-kernel sophisticated harmonic artifact reduction as well as the streaking artifact reduction for QSM algorithms. To assess layer-specific activation, twenty layers were segmented in the somatosensory and motor cortices, obtained from a finger tapping paradigm, and further averaged into six anatomical cortical layers. The magnitude of signal change and z-scores were compared across layers for each technique. fQSM showed the largest activation-dependent mean susceptibility decrease in Layers II/III in M1 and Layers I/ II in S1 with up to -1.3 ppb while BOLD fMRI showed the strongest mean signal increase in Layer I. Our data suggest that fQSM demonstrates less bias towards activation in superficial layers compared to BOLD fMRI. Moreover, activation-based susceptibility change was comparable to VASO data. Studying whole-brain, layer-dependent activation with submillimeter fQSM is feasible, and reduces bias towards venous drainage effects on the cortical surface compared to BOLD fMRI, thereby enabling better localization of laminar activation.

neuroscience↗

bioRxiv2024

Vascular FLRT2 regulates venous-mediated angiogenic expansion and CNS barriergenesis

Veins have emerged as the origin of all other endothelial cell subtypes needed to expand vascular networks during developmental and pathological neoangiogenesis. Here, we uncover the significant role of the angioneurin Fibronectin Leucine Rich Transmembrane protein (FLRT) 2 in central nervous system (CNS) vascular development in the mouse. Early postnatal FLRT2 deletion reveals specific defects in retinal veins, impacting endothelial cell proliferation, sprouting and polarity that result in reduced tip cells at the vascular front. FLRT2 interacts with VE-cadherin and together with the endocytic adaptor protein Numb contribute to the modulation of adherens junction morphology in both retina and cerebral cortex in vivo. Utilizing expansion microscopy, we visualize the altered dynamic distribution of VE-cadherin in tissue of FLRT2 endothelial mutants. Additionally, FLRT2 in cortical vessels regulates the crosstalk between adherens and tight junctions, influencing blood-brain barrier development. Our findings position FLRT2 as a vein-specific crucial regulator of CNS vascular development.

neuroscience↗

bioRxiv2024

Evaluation of Methodologies in Anti-nephrin Autoantibody Detection

Recent studies discovered the prominent presence of anti-nephrin autoantibodies in minimal change disease, steroid-sensitive nephrotic syndrome and/or post-transplant recurrent focal segmental glomerulosclerosis (FSGS). However, widely different, and often unconventional autoantibody detection methods were used among these studies, making it challenging to assess the pathogenic role for the antibodies. Here we examined methods of conventional ELISA, magnetic on-beads ELISA, immunoprecipitation-immunoblotting (IP-IB), and cell- and tissue-based antibody assays with 127 plasma samples of kidney and non-kidney diseases. On the antigen side, we compared commercially available recombinant human nephrin extracelluar domain (ECD) produced from human or mouse cell lines, as well as lab-made full length, ECD, and series of ECD truncates for measuring autoantibody reactivity and specificity. Surprisingly, different assay methods and different antigen preparations led to observation of assay-specific false-positive and false-negative results. In general, a set of tests that combines magnetic beads-enhanced ELISA, followed by IP-IB, and epitope mapping showed the most robust results for anti-nephrin autoantibodies, detected in two primary FSGS patients among all cases tested. It is interesting to note that cell/tissue-based results, also supported by antigen truncation studies, clearly suggest steric hindrance of reactive epitopes, as in full length nephrin that forms compact self-associated complexes. In conclusion, anti-nephrin positivity is rare among the tested patients (2/127), including those with FSGS (2/42), and autoantibody results can be affected by the choice of detection methods.

biochemistry↗

bioRxiv2024

Neuronal DNA repair reveals strategies to influence CRISPR editing outcomes

Genome editing is poised to revolutionize treatment of genetic diseases, but poor understanding and control of DNA repair outcomes hinders its therapeutic potential. DNA repair is especially understudied in nondividing cells like neurons, which must withstand decades of DNA damage without replicating. This lack of knowledge limits the efficiency and precision of genome editing in clinically relevant cells. To address this, we used induced pluripotent stem cells (iPSCs) and iPSC-derived neurons to examine how postmitotic human neurons repair Cas9-induced DNA damage. We discovered that neurons can take weeks to fully resolve this damage, compared to just days in isogenic iPSCs. Furthermore, Cas9-treated neurons upregulated unexpected DNA repair genes, including factors canonically associated with replication. Manipulating this response with chemical or genetic perturbations allowed us to direct neuronal repair toward desired editing outcomes. By studying DNA repair in postmitotic human cells, we uncovered unforeseen challenges and opportunities for precise therapeutic editing.

molecular biology↗

bioRxiv2024

Molecular tension authenticates apoptotic cells being phagocytosed.

Profound cytoskeletal reorganization and plasma membrane deformation in phagocytes is indispensable for phagocytosis of massive apoptotic cells, but whether these dynamics accompany a mechanical signal modulating signaling during efferocytosis remains largely unexplored. Here, we report that tension between phosphatidylserine (PS) and PS receptors (PSR) generated at the phagocytic synapse serves as a signal to determine whether PS-exposing cells should be phagocytosed. Mechanistically, increased membrane tension of phagocytes via Rac1-dependent actin polymerization and membrane stiffness of apoptotic cells caused tension between PS and PSRs, leading to phosphoinositide 3-kinase recruitment to PSRs, which resulted in Rac1 inactivation and myosin II phosphorylation required for phagocytic cup closure. Our observations imply that tension between PS and PSRs acts as a mechanical fail-safe to prevent removal of all PS-exposing cells for the integrity of efferocytosis. One-Sentence SummaryTension between phosphatidylserine and its receptors acts as a final decision-maker determining phagocytosis of apoptotic cells.

cell biology↗

bioRxiv2024

The disease-causing tau V337M mutation induces tau hypophosphorylation and perturbs axon morphology pathways

Tau aggregation is a hallmark of several neurodegenerative diseases, including Alzheimers disease and frontotemporal dementia. There are disease-causing variants of the tau-encoding gene, MAPT, and the presence of tau aggregates is highly correlated with disease progression. However, the molecular mechanisms linking pathological tau to neuronal dysfunction are not well understood. This is in part due to an incomplete understanding of the normal functions of tau in development and aging, and how the associated molecular and cellular processes change in the context of causal disease variants of tau. To address these questions in an unbiased manner, we conducted multi-omic characterization of iPSC-derived neurons harboring the MAPT V337M mutation or MAPT knockdown. RNA-seq, ATAC-seq, and phosphoproteomics revealed that both V337M mutation and tau knockdown perturbed levels of transcripts and phosphorylation of proteins related to axonogenesis or axon morphology. When we directly measured axonogenesis, we found that both MAPT V337M and MAPT knockdown caused decreased axon length. Surprisingly, we found that neurons with V337M tau had much lower tau phosphorylation than neurons with WT tau. CRISPR-based screens uncovered regulators of tau phosphorylation in neurons and found that factors involved in axonogenesis modified tau phosphorylation in both MAPT WT and MAPT V337M neurons. Intriguingly, the p38 MAPK pathway specifically modified tau phosphorylation in MAPT V337M neurons. We propose that V337M tau perturbs tau phosphorylation and axon morphology pathways that are relevant to the normal function of tau in development, which could contribute to previously reported cognitive changes in preclinical MAPT variant carriers.

neuroscience↗

bioRxiv2024

ECloudGen: Access to Broader Chemical Space for Structure-based Molecule Generation

Structure-based molecule generation represents a significant advancement in AI-aided drug design (AIDD). However, progress in this domain is constrained by the scarcity of structural data on protein-ligand complexes, a challenge we term the Paradox of Sparse Chemical Space Generation. To address this limitation, we propose a novel latent variable approach that bridges the data gap between ligand-only and protein-ligand complexes, enabling the target-aware generative models to explore a broader chemical space and enhancing the quality of molecular generation. Drawing inspiration from quantum molecular simulations, we introduce ECloudGen, a generative model that leverages electron clouds as meaningful latent variables--an innovative integration of physical principles into deep learning frameworks. ECloudGen incorporates modern techniques, including latent diffusion models, Llama architectures, and a newly proposed contrastive learning task, which organizes the chemical space into a structured and highly interpretable latent representation. Benchmark studies demonstrate that ECloudGen outperforms state-of-the-art methods by generating more potent binders with superior physiochemical properties and by covering a significantly broader chemical space. The incorporation of electron clouds as latent variables not only improves generative performance but also introduces model-level interpretability, as illustrated in a case study designing V2R inhibitors. Furthermore, ECloudGens structurally ordered modeling of chemical space enables the development of a model-agnostic optimizer, extending its utility to molecular optimization tasks. This capability has been validated through a single-objective oracle benchmark and a complex multi-objective optimization scenario involving the redesign of endogenous BRD4 ligands. In conclusion, ECloudGen effectively addresses the Paradox of Sparse Chemical Space Generation through its integration of theoretical insights, advanced generative techniques, and real-world validation. The newly proposed technique of leveraging physical entities (such as electron clouds) as latent variables within a deep learning framework may prove useful for computational biology fields beyond AIDD.

bioinformatics↗

bioRxiv2024

Inactivation of PRMT1 inhibits cardiac fibrosis via transcriptional regulation and perturbation of FBL activity in fibroblast-to-myofibroblast transition

Cardiac fibrosis is a recognized cause of morbidity and mortality, yet effective pharmacological therapy that directly targets the fibrotic process remains lacking. Here we surveyed a group of methyltransferases known as protein arginine methyltransferases (PRMT) and demonstrated that PRMT1, which is the most highly expressed PRMT in the heart, was upregulated in activated cardiac fibroblasts, or myofibroblasts, in failing hearts. Deleting Prmt1 specifically in myofibroblasts or treating systemically with the PRMT1 inhibitor MS023 blocked myofibroblast formation, leading to a significant reduction in cardiac fibrosis and improvement in cardiac function in both acute and chronic heart injury models that manifest pervasive cardiac fibrosis. PRMT1 promoted the transition of cardiac fibroblasts to myofibroblasts by regulating transcription and epigenetic status. Additionally, PRMT1 methylated a key nucleolar protein fibrillarin 1 (FBL) and regulated nucleoli morphology and function during fibroblast fate transition. We further demonstrated a previously unrecognized requirement for FBL in myofibroblasts formation, by regulating myofibroblast gene induction and contractile force generation.

cell biology↗

bioRxiv2024

The complete genome of lettuce reveals centromere landscape and empowers breeding

Lettuce (Lactuca sativa L.) is a globally grown vegetable crop as the most popular salad ingredient. Lettuce breeding is crucial to enhancing yield, nutrition and disease resistance, but impeded by lacking a high-quality genome resource. In addition, the released genomes remain fragmented (with hundreds of gaps) and incomplete with omitting pivotal centromeres and telomeres. Here, we report a 2.59 Gb complete telomere-to-telomere (T2T) genome assembly for lettuce. T2T genome analysis revealed the unique genetic and epigenetic architectures of centromere repeats dominated by retrotransposons and satellites. The complete genome and annotation facilitate the identification of candidate disease resistance (NLR) genes induced during grey mold infection. The genomic resources, and biological insights into genetic and epigenetic landscape of centromeres not only advance lettuce research and breeding, but also propel the biology and evolution of centromeres across plant kingdom.

genomics↗

bioRxiv2024

Disruption of WSB2-mediated NOXA Degradation Induces Synthetic Lethality to Anti-apoptotic BCL-2 Family Protein Inhibitors

Anti-apoptotic BCL-2 family proteins are frequently overexpressed in various cancers, playing a pivotal role in cancer initiation and progression, as well as intrinsic or acquired resistance to therapy. Although inhibitors targeting BCL-2, such as Venetoclax, have shown efficacy in hematological malignancies, their therapeutic potential in solid tumors remains limited. Identifying novel molecular targets to overcome resistance to these inhibitors is of significant clinical importance. Here, we provide evidence of a strong synthetic lethality between WSB2, a previously underexplored substrate-binding receptor of the Cullin 5-RBX2-Elongin B/C (CRL5) E3 ubiquitin ligase complex, and anti-apoptotic BCL-2 family proteins. Mechanistically, WSB assembles a CRL5 E3 ubiquitin ligase complex that facilitates the ubiquitination and subsequent proteasomal degradation of NOXA, a pro-apoptotic BCL-2 family protein. Loss of WSB2 leads to a substantial accumulation of NOXA in both cultured cell lines and knockout mouse tissues. While WSB2 deficiency alone does not significantly impact spontaneous apoptosis, it sensitizes cells to apoptosis when anti-apoptotic BCL-2 family proteins are either genetically depleted or pharmacologically inhibited. Moreover, WSB2 is overexpressed in several human cancer types. These findings identify WSB2 as a critical regulator of mitochondrial apoptosis and reveal the dysregulation of the WSB2-NOXA axis as a key factor contributing to apoptosis resistance in cancer cells. Targeting both WSB2 and anti-apoptotic BCL-2 family proteins holds promising therapeutic potential for overcoming resistance in human cancers.

cell biology↗

bioRxiv2024

A step-emulsion based digital-RPA for Pathogenic bacteria detection

Foodborne bacteria are major causes that affect human health. Development of new method that could achieve Rapid, sensitive and quantitative detection of pathogen is urgently needed. In this research, a step emulsion microfluidic,combined with droplet-based digital-RPA, was developed to detect Vibrio parahaemolyticus, a major seafood-borne pathogenic bacteria. Specific and rapid detection of Vibrio parahaemolyticus in 30 min has been achieved by this new device, with a detection limit of 10 CFU/L, about 10-times lower than classical tube-based RPA. This device was demonstrated to be a promising tool for detection of pathogenic bacteria.

microbiology↗

bioRxiv2024

3D live imaging and phenotyping of the subcellular cytotoxicity in cancer immunotherapy using event-triggered Bessel oblique plane microscopy

Clarification of the cytotoxic function of T cells is crucial for understanding human immune responses and immunotherapy procedures. Here, we report an event-triggered Bessel oblique plane microscopy (EBOPM) platform capable of smart 3D live imaging and phenotyping of chimeric antigen receptor (CAR)-modified T-cell cytotoxicity in cancer immunotherapy; the EBOPM platform has the following characteristics: an isotropic subcellular resolution of 320 nm, large-scale scouting over 400 interacting cell pairs, long-term observation across 5 hours, and quantitative analysis of the Terabyte-scale 3D, multichannel, time-lapse image datasets. Using this advanced microscopy platform, several key subcellular events in CAR-T cells were captured and comprehensively analyzed; these events included the instantaneous formation of immune synapses and the sustained changes in the microtubing morphology. Furthermore, we identified the actin retrograde flow speed, the actin depletion coefficient, the microtubule polarization and the contact area of the CAR-T/target cell conjugates as essential parameters strongly correlated with CAR-T-cell cytotoxic function. Our approach will be useful for establishing criteria for quantifying T-cell function in individual patients for all T-cell-based immunotherapies.

immunology↗

bioRxiv2024

Targeting G9a translational mechanism of SARS-CoV-2 pathogenesis for multifaceted therapeutics of COVID-19 and its sequalae

By largely unknown mechanism(s), SARS-CoV-2 hijacks the host translation apparatus to promote COVID-19 pathogenesis. We report that the histone methyltransferase G9a noncanonically regulates viral hijacking of the translation machinery to bring about COVID-19 symptoms of hyperinflammation, lymphopenia, and blood coagulation. Chemoproteomic analysis of COVID-19 patient peripheral mononuclear blood cells (PBMC) identified enhanced interactions between SARS-CoV-2-upregulated G9a and distinct translation regulators, particularly the N6-methyladenosine (m6A) RNA methylase METTL3. These interactions with translation regulators implicated G9a in translational regulation of COVID-19. Inhibition of G9a activity suppressed SARS-CoV-2 replication in human alveolar epithelial cells. Accordingly, multi-omics analysis of the same alveolar cells identified SARS-CoV-2-induced changes at the transcriptional, m6A-epitranscriptional, translational, and post-translational (phosphorylation or secretion) levels that were reversed by inhibitor treatment. As suggested by the aforesaid chemoproteomic analysis, these multi-omics-correlated changes revealed a G9a-regulated translational mechanism of COVID-19 pathogenesis in which G9a directs translation of viral and host proteins associated with SARS-CoV-2 replication and with dysregulation of host response. Comparison of proteomic analyses of G9a inhibitor-treated, SARS-CoV-2 infected cells, or ex vivo culture of patient PBMCs, with COVID-19 patient data revealed that G9a inhibition reversed the patient proteomic landscape that correlated with COVID-19 pathology/symptoms. These data also indicated that the G9a-regulated, inhibitor-reversed, translational mechanism outperformed G9a-transcriptional suppression to ultimately determine COVID-19 pathogenesis and to define the inhibitor action, from which biomarkers of serve symptom vulnerability were mechanistically derived. This cell line-to-patient conservation of G9a-translated, COVID-19 proteome suggests that G9a inhibitors can be used to treat patients with COVID-19, particularly patients with long-lasting COVID-19 sequelae.

immunology↗

bioRxiv2024

Discovery of the First-in-class G9a/GLP PROTAC Degrader

Aberrantly expressed lysine methyltransferases G9a and GLP, which catalyze mono- and di-methylation of histone H3 lysine 9 (H3K9), have been implicated in numerous cancers. Recent studies have uncovered both catalytic and non-catalytic oncogenic functions of G9a/GLP. As such, G9a/GLP catalytic inhibitors have displayed limited anticancer activity. Here, we report the discovery of the first-in-class G9a/GLP proteolysis targeting chimera (PROTAC) degrader, 10 (MS8709), as a potential anticancer therapeutic. 10 induces G9a/GLP degradation in a concentration-, time, and ubiquitin-proteasome system (UPS)-dependent manner, does not alter the mRNA expression of G9a/GLP and is selective for G9a/GLP over other methyltransferases. Moreover, 10 displays superior cell growth inhibition to the parent G9a/GLP inhibitor UNC0642 in prostate, leukemia, and lung cancer cells and has suitable mouse pharmacokinetic properties for in vivo efficacy studies. Overall, 10 is a valuable chemical biology tool to further investigate the functions of G9a/GLP and a potential therapeutic for treating G9a/GLP-dependent cancers. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/582210v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@1b3c923org.highwire.dtl.DTLVardef@5a22f0org.highwire.dtl.DTLVardef@1abbabeorg.highwire.dtl.DTLVardef@1711f29_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗