Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 847 records · Page 47Linked to original sources

bioRxiv2022

Spectral clustering of single-cell multi-omics data on multilayer graphs

Single-cell sequencing technologies that simultaneously generate multimodal cellular profiles present opportunities for improved understanding of cell heterogeneity in tissues. How the multimodal information can be integrated to obtain a common cell type identification, however, poses a computational challenge. Multilayer graphs provide a natural representation of multi-omic single-cell sequencing datasets, and finding cell clusters may be understood as a multilayer graph partition problem. We introduce two spectral algorithms on multilayer graphs, spectral clustering on multilayer graphs (SCML) and the weighted locally linear (WLL) method, to cluster cells in multi-omic single-cell sequencing datasets. We connect these algorithms through a unifying mathematical framework that represents each layer using a Hamiltonian operator and a mixture of its eigenstates to integrate the multiple graph layers, demonstrating in the process that the WLL method is a rigorous multilayer spectral graph theoretic reformulation of the popular Seurat weighted nearest neighbor (WNN) algorithm. Implementing our algorithms and applying them to a CITE-seq dataset of cord blood mononuclear cells yields results similar to the Seurat WNN analysis. Our work thus extends spectral methods to multimodal single-cell data analysis. The code used in this study can be found at https://github.com/jssong-lab/sc-spectrum

bioinformatics↗

bioRxiv2022

Cell-Type Specific Profiling of Histone Post-Translational Modifications in the Adult Mouse Striatum

Histone post-translational modifications (hPTMs) regulate gene expression via changes in chromatin accessibility and transcription factor recruitment. At a given locus, the coordinated enrichment of several distinct hPTMs regulate gene expression in response to external stimuli. However, neuronal hPTMs have been primarily characterized in bulk brain tissue and/or tissue pooled across subjects. This obscures both cell-type and individual variability, features essential to understand individual susceptibility to psychiatric disease. To address this limitation, we optimized a hybrid protocol, ICuRuS, to profile both activating and repressive hPTMs in neuronal subtypes from a single mouse. We report here profiling of striatal medium spiny neuron (MSN) subtypes, genetically defined by expression of Adenosine 2a Receptor (A2a) or Dopamine Receptor D1 (D1), which differentially regulate reward processing and pathophysiology. Using ICuRuS, we defined genome-wide, A2a- or D1-specific combinatorial hPTM profiles, and discovered regulatory epigenomic features at genes implicated in neurobiological function and disease.

neuroscience↗

bioRxiv2022

Conserved Untranslated Regions of Multipartite Viruses: Natural Markers of Novel Viral Genomic Components and Tags of Viral Evolution

Viruses with split genomes are categorized as being either segmented or multipartite according to whether their genomic segments occur in single or different virions. Some complexity will exist, in that inherited "core" vital segments viruses may renew the others once host and environmental alterations keep driving viral evolution. Despite this uncertainty, empirical observations have been made across the split genomes in the untranslated regions (UTRs) on the short or long stretches of conserved or identical sequences. In this study, we describe a methodology that combines RNA and small RNA sequencing, conventional BLASTx, and iterative BLASTn of UTRs to detect viral genomic components even if they encode orphan genes (ORFans). Within the phylum Kitrinoviricota, novel putative multipartite viruses and viral genomic components were annotated using data obtained from our sampling or publicly available sources. The novel viruses, as extensions or intermediate nodes, enriched the information of the evolutionary networks. Furthermore, the diversity of novel genomic components emphasized the evolutionary roles of reassortment and recombination, as well as genetic deletion, strongly supporting the genomic complexity. These data also suggest insufficient knowledge of these genomic components for categorizing some extant viral taxa. The relative conservation of UTRs at the genome level may explain the relationships between monopartite and multipartite viruses and how the multipartite viruses can have a life strategy involving multiple host cells. Author summaryThe current workflows for virus identification are largely based on high-throughput sequencing and coupled protein sequence homology-dependent analysis methods and tools. However, for viruses with split genomes, the identification of genomic components whose deduced protein sequences are not homologous to known sequences is inadequate. Furthermore, many plant-infecting multipartite viruses contain conserved UTRs across their genomic components. Based on this, we propose a practical method of UTR-backed iterative BLASTn (UTR-iBLASTn) to explore the components with ORFans and study virus evolution using the UTRs as signals. These shed light on viral "dark matter"--unknown/omitted genomic components of segmented/multipartite viruses from different kingdoms and hosts, and the origins of these components.

microbiology↗

bioRxiv2022

Sub-second striatal dopamine dynamics assessed by simultaneous fast-scan cyclic voltammetry and fluorescence biosensor

Dopamine produces neuromodulation throughout the basal ganglia, cortex and other brain regions, and is implicated in movement control, neural mechanisms of reward and actions of misused substances. The efferent projections of dopaminergic neurons with somata in the substantia nigra pars compacta and ventral tegmental area strongly innervate different striatal subregions. While much is known about the function of these neurons, there is a relative deficiency of information about in vivo dopamine dynamics in the nigrostriatal projections, especially those to the dorsolateral striatum (DLS). In past studies, subsecond dopamine changes were measured predominantly with fast-scan cyclic voltammetry (FSCV) both in brain slices and in vivo. However, traditional FSCV has limitations in discriminating among catecholamines, and cannot be used for simultaneous measurement of both slow and fast/phasic dopamine changes. In addition, FSCV has been most useful for measuring dopamine in the ventral striatum in vivo with less utility for measurement in dorsolateral striatum. The development of genetically encoded dopamine sensors has provided a new approach to measuring slow and fast dopamine dynamics both in brain slices and in vivo, raising the hope of more facile measurement of in vivo dopamine measurements, including in areas where measurement was previously difficult with FSCV. To this end, we first evaluated dLight photometry in brain slices with simultaneous FSCV. We found that both techniques yielded comparable findings. However, differences were noted in responses to dopamine transporter inhibitors, including cocaine. We then used in vivo fiber photometry with dLight to examine responses to cocaine in DLS and compared responses during Pavlovian conditioning in DLS to two other striatal subregions. These experiments show that dopamine increases are readily detectable in DLS and provide new information about dopamine transient kinetics and slowly developing signaling during conditioning. Overall, our findings indicate that dLight photometry is well suited to measuring dopamine dynamics in a striatal region of great interest where such measurements were difficult previously.

neuroscience↗

bioRxiv2022

Loss-of-function of OTUD7A in the schizophrenia-associated 15q13.3 deletion impairs synapse development and function in human neurons

Identifying causative gene(s) within disease-associated large genomic regions of copy number variants (CNVs) is challenging. Here, by targeted sequencing of genes within schizophrenia (SZ)-associated CNVs in 1,779 SZ cases and 1,418 controls, we identified three rare putative loss-of-function (LoF) mutations in OTU deubiquitinase 7A (OTUD7A) within the 15q13.3 deletion in cases, but none in controls. To tie OTUD7A LoF with any SZ-relevant cellular phenotypes, we modeled the OTUD7A LoF mutation, rs757148409, in human induced pluripotent stem cell (hiPSC)-derived induced excitatory neurons (iNs) by CRISPR/Cas9 engineering. The mutant iNs showed a [~]50% decrease in OTUD7A expression without undergoing nonsense-mediated mRNA decay. The mutant iNs also exhibited marked reduction of dendritic complexity, density of synaptic proteins GluA1 and PSD-95, and neuronal network activity. Congruent with the neuronal phenotypes in mutant iNs, our transcriptomic analysis showed that the set of OTUD7A LoF-downregulated genes was enriched for those relating to synapse development and function, and was associated with SZ and other neuropsychiatric disorders. These results suggest that OTUD7A LoF impairs synapse development and neuronal function in human neurons, providing mechanistic insight into the possible role of OTUD7A in driving neuropsychiatric phenotypes associated with the 15q13.3 deletion.

neuroscience↗

bioRxiv2022

Neuronal cell-type and circuit basis for visual predictive processing

Bayesian Brain theory suggests brain utilises predictive processing framework to interpret the noisy world1-11. Predictive processing is essential to perception, action, cognition and psychiatric disease12, but underlying neural circuit mechanisms remain undelineated. Here we show the neuronal cell-type and circuit basis for visual predictive processing in awake, head-fixed mice during self-initiated running. Preceding running, vasoactive intestinal peptide (VIP)-expressing inhibitory interneurons (INs) in primary visual cortex (V1) are robustly activated in absence of structured visual stimuli. This pre-running activation is mediated via distal top-down projections from frontal, parietal and retrosplenial areas known for motion planning, but not local excitatory inputs associated with the bottom-up pathway. Somatostatin (SST) INs show pre-running suppression and post-running activation, indicating a VIP-SST motif. Differential VIP-SST peri-running dynamics anisotropically suppress neighbouring pyramidal (Pyr) neurons, preadapting Pyr neurons to the incoming running. Our data delineate key neuron types and circuit elements of predictive processing brain employs in action and perception. One Sentence SummaryVIP-SST-Pyr microcircuit in visual predictive processing during voluntary running

neuroscience↗

bioRxiv2021

SoyFGB v2.0: a unique access to variations of Chinese Soybean Gene Bank (CNSGB) germplasm

In Chinese National Soybean GeneBank (CNSGB), we have collected more than 30,000 soybean accessions. However, data sharing for soybean remains an especially sensitive question, and how to share the genome variations within rule frame has been bothering the soybean germplasm workers for a long time. Here we release a big data source named Soybean Functional Genomics & Breeding database (SoyFGB v2.0) (https://sfgb.rmbreeding.cn/), which embed a core collection of 2,214 soybean resequencing genome (2K-SG) from the CNSGB germplasm. This source presents a unique example which may help elucidating the following three major functions for multiple genome data mining with general interests for plant researchers. 1) On-line analysis tools are provided by the Analysis module for haplotype mining in high-throughput genotyped germplasms with different methods. 2) Variations for 2K-SG are provided in SoyFGB v2.0 by Browse module which contains two functions of SNP and InDel. Together with the Gene (SNP & InDel) function embedded in Search module, the genotypic information of 2K-SG for targeting gene / region is accessible. 3) Scaled phenotype data of 42 traits, including 9 quality and 33 quantitative traits are provided by SoyFGB v2.0. With the scaled-phenotype data search and seed request tools under a control list, the germplasm information could be shared without direct downloading the unpublished phenotypic data or information of sensitive germplasms. In a word, the mode of data mining and sharing underlies SoyFGB v2.0 may inspire more ideas for works on genome resources of not only soybean but also the other plants.

genomics↗

bioRxiv2021

Identification and characterization of 19 predicted Myb-family DNA binding proteins in Magnaporthe oryzae concerning growth, conidiation, and pathogenicity

Proteins with DNA binding Myb domains have been suggested in regulating development and stress responses. Magnaporthe oryzae is considered the most destructive pathogen of rice. We screened the genome for genes with Myb domains encoding since these can be needed for pathogenesis. We found Myb1-19. Only MoMyb1 was previously shown to be involved in pathogenesis. We succeeded in deleting 12 of the other 18 genes. MoMyb2 deletion affected mainly growth, while MoMyb13 or MoMyb15 deletions gave additional defects in conidiation and plant infection. However, RT-qPCR showed that none of the 19 Myb genes are negligibly expressed. Instead, they have different expression profiles hours post-infection when infecting rice plants. Considering this, the unchanged infection phenotype for 9 gene deletions surprised us, and we extended the analysis to expression co-regulation of all 19 Myb proteins and found 5 co-regulated groups of predicted Myb-domain proteins. MoMyb13 or MoMyb15 are discussed and motivated as candidates for further, more detailed studies with aims also outside of plant pathology. Referring to what is found in other eukaryotes, we finally discuss possible redundancy or compensatory regulations for many of the other Myb genes hiding or compensating for the effect of many complete deletions. IMPORTANCEMagnaporthe oryzae is considered the most important rice pathogen limiting rice production. Our study attempts to find all genes encoding a DNA-binding gene family called Myb, and we found 19, many of which have not been studied before. The Myb gene family is suspected to regulate stress responses the pathogen needs to overcome plant defenses. Inhibiting or disturbing these genes, if they are indeed regulatory, can open new ways of controlling the pathogen and learning more about its physiology and ecology.

microbiology↗

bioRxiv2021

SynLethDB 2.0: A web-based knowledge graph database on synthetic lethality for novel anticancer drug discovery

Two genes are synthetic lethal if mutations in both genes result in impaired cell viability, while mutation of either gene does not affect the cell survival. The potential usage of synthetic lethality (SL) in anticancer therapeutics has attracted many researchers to identify synthetic lethal gene pairs. To include newly identified SLs and more related knowledge, we present a new version of the SynLethDB database to facilitate the discovery of clinically relevant SLs. We extended the first version of SynLethDB database significantly by including new SLs identified through CRISPR screening, a knowledge graph about human SLs, and new web interface, etc. Over 16,000 new SLs and 26 types of other relationships have been added, encompassing relationships among 14,100 genes, 53 cancers, and 1,898 drugs, etc. Moreover, a brand-new web interface has been developed to include modules such as SL query by disease or compound, SL partner gene set enrichment analysis and knowledge graph browsing through a dynamic graph viewer. The data can be downloaded directly from the website or through the RESTful APIs. The database is accessible online at http://synlethdb.sist.shanghaitech.edu.cn/v2.

bioinformatics↗

bioRxiv2021

Cell type-specific differential expression for spatial transcriptomics

Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. There is a pressing need for computational tools to enable the detection of genes that are differentially expressed (DE) within specific cell types across tissue context. We show that current approaches cannot learn cell type-specific DE due to changes in cell type composition across space and the fact that measurement units often detect transcripts from more than one cell type. Here, we introduce a statistical method, Cell type-Specific Inference of Differential Expression (C-SIDE), that identifies cell type-specific patterns of differential gene expression while accounting for localization of other cell types. We model spatial transcriptomics gene expression as an additive mixture across cell types of general log-linear cell type-specific expression functions. This approach provides a unified framework for defining and identifying gene expression changes in a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Furthermore, our approach enables statistical inference across multiple samples and replicates when such data is available. We demonstrate, through simulations and validation experiments on Slide-seq and MER-FISH datasets, that our approach accurately identifies cell type-specific differential gene expression and provides valid uncertainty quantification. Lastly, we apply our method to characterize spatially-localized tissue changes in the context of disease. In an Alzheimers mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. We make our C-SIDE method publicly available as part of the open source R package https://github.com/dmcable/spacexr.

genomics↗

bioRxiv2021

Intracranial Electric Field Recording During Multichannel Transcranial Electrical Stimulation

BackgroundMultichannel transcranial electrical stimulation (tES) modeling and optimization have been widely studied in recent years. Its theoretical bases include quasi-static assumption and linear superposition. However, there is still a lack of direct in vivo evidence to validate the simulation model and theoretical assumptions. MethodsWe directly measured the multichannel tES-induced voltage changes with implanted stereotactic-electroencephalographic (sEEG) electrodes in 12 epilepsy subjects. By combining these measured data, we investigate the linear superposition and prediction accuracy of simulation models for multi-electrode stimulation and further compare the induced EF differences between transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS). ResultsOur in vivo measurements demonstrated that the multi-electrode tES-induced voltages were almost equal to the sum of the voltages generated independently by bipolar stimulation. Both measured voltages and electric fields obtained in vivo were highly correlated with the predicted values in our cohort (Voltages: r = 0.92, p < 0.001; electric fields: r = 0.74, p < 0.001). Under the same stimulation intensity, the tDCS-induced peak-zero voltages were highly correlated with the values of tACS (r = 0.99, p < 0.001; s = 0.99). ConclusionsThe in vivo measurements provides confirmatory results for linear superposition and quasi-static assumption within the human brain. Furthermore, we found that the individualized simulation model reliably predicted the multi-electrode tES-induced electric fields.

biophysics↗

bioRxiv2021

Structure prediction of the druggable fragments in SARS-CoV-2 untranslated regions

The outbreak of the COVID-19 pandemic has led to intensive studies of both the structure and replication mechanism of SARS-CoV-2. In spite of some secondary structure experiments being carried out, the 3D structure of the key function regions of the viral RNA has not yet been well understood. At the beginning of COVID-19 breakout, RNA-Puzzles community attempted to envisage the three-dimensional structure of 5'- and 3'-Un-Translated Regions (UTRs) of the SARS-CoV-2 genome. Here, we report the results of this prediction challenge, presenting the methodologies developed by six participating groups and discussing 100 RNA 3D models (60 models of 5'-UTR and 40 of 3'-UTR) predicted through applying both human experts and automated server approaches. We describe the original protocol for the reference-free comparative analysis of RNA 3D structures designed especially for this challenge. We elaborate on the deduced consensus structure and the reliability of the predicted structural motifs. All the computationally simulated models, as well as the development and the testing of computational tools dedicated to 3D structure analysis, are available for further study.

bioinformatics↗

bioRxiv2021

Environmental carcinogens disproportionally mutate genes implicated in neurodevelopmental disorders

De novo mutations contribute to a large proportion of sporadic psychiatric and developmental disorders, yet the potential role of environmental carcinogens as drivers of causal de novo mutations in neurodevelopmental disorders is poorly studied. We demonstrate that several mutagens, including polycyclic aromatic hydrocarbons (PAHs), disproportionately mutate genes related to neurodevelopmental disorders including autism spectrum disorders (ASD), schizophrenia, and attention deficit hyperactivity disorder (ADHD). Other disease genes including amyotrophic lateral sclerosis (ALS), Alzheimers disease, congenital heart disease, orofacial clefts, and coronary artery disease were generally not mutated more than expected. Our findings support a new paradigm of neurodevelopmental disease etiology driven by a contribution of environmentally induced rather than random mutations.

bioinformatics↗

bioRxiv2021

Response of Surface Water Quality Characteristics to Socio-economic Factors in Eastern-Central China

Following the implementation of the strictest water resource management system in China, it has become increasingly important to understand and improve the surface water quality and the rate at which water function zones reach the water quality standard. Based on the monthly monitoring data from 450 monitoring sites at the provincial borders of 27 provinces in China in 2019, the overall surface water quality at provincial boundaries in China was as follows: 61.7% of the water was classified under Class I-III; and 5%, 8.6%, and 12.2% of the water was classified under Class IV, V, and inferior V, respectively. The main standard items are DO, CODMn, COD, BOD5, NH3-N, and TP. The Canadian Council of Ministers of the Environment-water quality index (CCME-WQI) showed that the provincial boundary water quality exceeded the fair level, and F1 was the most influential factor. Then, 27 factors that directly or indirectly affect the water quality of surface water at the provincial boundaries of 27 provinces were identified, and the indirect influencing factors were integrated into the ecological environmental quality index and human activities quantitative index. Finally, the 27 factors were integrated into six factors, and the relationship between these indicators and CCME-WQI as well as the concentration of influencing elements with respect to regulatory standard limits were analyzed. The proportion of building land was the most significant factor affecting the quality of the aquatic environment in provincial boundaries. In addition, the economic development level, proportion of farmland, and degree of social development were identified as significant influencing factors. The six factors have different degrees of impact on the concentrations of major elements with respect to standard limits. This study basically explores water resource management and offers significant reference and guidelines for the improvement of the quality of surface water at provincial boundaries in China.

biochemistry↗

bioRxiv2021

Evidence for a mouse origin of the SARS-CoV-2 Omicron variant

The rapid accumulation of mutations in the SARS-CoV-2 Omicron variant that enabled its outbreak raises questions as to whether its proximal origin occurred in humans or another mammalian host. Here, we identified 45 point mutations that Omicron acquired since divergence from the B.1.1 lineage. We found that the Omicron spike protein sequence was subjected to stronger positive selection than that of any reported SARS-CoV-2 variants known to evolve persistently in human hosts, suggesting the possibility of host-jumping. The molecular spectrum (i.e., the relative frequency of the twelve types of base substitutions) of mutations acquired by the progenitor of Omicron was significantly different from the spectrum for viruses that evolved in human patients, but was highly consistent with spectra associated with evolution in a mouse cellular environment. Furthermore, mutations in the Omicron spike protein significantly overlapped with SARS-CoV-2 mutations known to promote adaptation to mouse hosts, particularly through enhanced spike protein binding affinity for the mouse cell entry receptor. Collectively, our results suggest that the progenitor of Omicron jumped from humans to mice, rapidly accumulated mutations conducive to infecting that host, then jumped back into humans, indicating an inter-species evolutionary trajectory for the Omicron outbreak.

evolutionary biology↗

bioRxiv2021

Multiple genes in cis mediate the effects of a single chromatin accessibility variant on aberrant synaptic development and function in human neurons

Despite hundreds of risk loci from genome-wide association studies of neuropsychiatric disorders, causal variants/genes remain largely unknown. Here, in NEUROG2-induced human neurons, we identified 31 risk SNPs in 26 schizophrenia (SZ) risk loci that displayed allele-specific open chromatin (ASoC) and were likely to be functional. Editing the strongest ASoC SNP rs2027349 near vacuolar protein sorting 45 homolog (VPS45) altered the expression of VPS45, lncRNA AC244033.2, and a distal gene, C1orf54, in human neurons. Notably, the global gene expression changes in neurons were enriched for SZ risk and correlated with post-mortem brain gene expression signatures of neuropsychiatric disorders. Neurons carrying the risk allele exhibited increased dendritic complexity, synaptic puncta density, and hyperactivity, which were reversed by knocking-down distinct cis-regulated genes (VPS45, AC244033.2, or C1orf54), suggesting a phenotypic contribution from all three genes. Interestingly, transcriptomic analysis of knockdown cells suggested a non-additive effects of these genes. Our study reveals a compound effect of multiple genes at a single SZ locus on synaptic development and function, providing a mechanistic link between a non-coding SZ risk variant and disease-related cellular phenotypes.

genetics↗

bioRxiv2021

Single-cell profiling of healthy human kidney reveals features of sex-based transcriptional programs and tissue-specific immunity

Maintaining organ homeostasis requires complex functional synergy between distinct cell types, a snapshot of which is glimpsed through the simultaneously broad and granular analysis provided by single-cell atlases. Knowledge of the transcriptional programs underpinning the complex and specialized functions of human kidney cell populations at homeostasis is limited by difficulty accessing healthy, fresh tissue. Here, we present a single-cell perspective of healthy human kidney from 19 living donors, with equal contribution from males and females, profiling the transcriptome of 27677 high-quality cells to map healthy kidney at high resolution. Our sex-balanced dataset revealed sex-based differences in gene expression within proximal tubular cells, specifically, increased anti-oxidant metallothionein genes in females and the predominance of aerobic metabolism-related genes in males. Functional differences in metabolism were confirmed between male and female proximal tubular cells, with male cells exhibiting higher oxidative phosphorylation and higher levels of energy precursor metabolites. Within the immune niche, we identified kidney-specific lymphocyte populations with unique transcriptional profiles indicative of kidney-adapted functions and validated findings by flow cytometry. We observed significant heterogeneity in resident myeloid populations and identified an MRC1+ LYVE1+ FOLR2+ C1QC+ population as the predominant myeloid population in healthy kidney. This study provides a detailed cellular map of healthy human kidney, revealing novel insights into the complexity of renal parenchymal cells and kidney-resident immune populations.

immunology↗

bioRxiv2021

WESTPA 2.0: High-performance upgrades for weighted ensemble simulations and analysis of longer-timescale applications

The weighted ensemble (WE) family of methods is one of several statistical-mechanics based path sampling strategies that can provide estimates of key observables (rate constants, pathways) using a fraction of the time required by direct simulation methods such as molecular dynamics or discrete-state stochastic algorithms. WE methods oversee numerous parallel trajectories using intermittent overhead operations at fixed time intervals, enabling facile interoperability with any dynamics engine. Here, we report on major upgrades to the WESTPA software package, an open-source, high-performance framework that implements both basic and recently developed WE methods. These upgrades offer substantial improvements over traditional WE. Key features of the new WESTPA 2.0 software enhance efficiency and ease of use: an adaptive binning scheme for more efficient surmounting of large free energy barriers, streamlined handling of large simulation datasets, exponentially improved analysis of kinetics, and developer-friendly tools for creating new WE methods, including a Python API and resampler module for implementing both binned and "binless" WE strategies. Table of Contents/Abstract ImageFor the manuscript "WESTPA 2.0: High-performance upgrades for weighted ensemble simulations and analysis of longer-timescale applications" by Russo et al. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/471280v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@575710org.highwire.dtl.DTLVardef@151c3dorg.highwire.dtl.DTLVardef@1f0f525org.highwire.dtl.DTLVardef@6e5956_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗