Biology subjects

Zhang, R.

Publications and source records attributed to Zhang, R..

At least 469 records · Page 26Linked to original sources

bioRxiv2021

Structural transitions in the GTP cap visualized by cryo-EM of catalytically inactive microtubules

Microtubules (MTs) are polymers of /{beta}-tubulin heterodimers that stochastically switch between growth and shrinkage phases. This dynamic instability is critically important for MT function. It is believed that GTP hydrolysis within the MT lattice is accompanied by destabilizing conformational changes, and that MT stability depends on a transiently existing GTP cap at the growing MT end. Here we use cryo-EM and TIRF microscopy of GTP hydrolysis-deficient MTs assembled from mutant recombinant human tubulin to investigate the structure of a GTP-bound MT lattice. We find that the GTP-MT lattice of two mutants in which the catalytically active glutamate in -tubulin was substituted by inactive amino acids (E254A and E254N) is remarkably plastic. Undecorated E254A and E254N MTs with 13 protofilaments both have an expanded lattice, but display opposite protofilament twists, making these lattices distinct from the compacted lattice of wildtype GDP-MTs. End binding proteins of the EB family have the ability to compact both mutant GTP-lattices and to stabilize a negative twist, suggesting that they promote this transition also in the GTP cap of wildtype MTs, thereby contributing to the maturation of the MT structure. We also find that the MT seam appears to be stabilized in mutant GTP-MTs and destabilized in GDP-MTs, supporting the proposal that the seam plays an important role in MT stability. Together, these first high-resolution structures of truly GTP-bound MTs add mechanistic insight to our understanding of MT dynamic instability. Significance StatementMicrotubules (MTs) are non-equilibrium polymers that switch between states of growth and shrinkage. This property is critical for their function and is a consequence of GTP hydrolysis in the MT. The structure of the stable GTP part of the MT (the GTP cap) has previously been inferred from MTs polymerized with non-hydrolyzable GTP analogs. Here, we report the first high-resolution structures of MTs truly containing GTP, polymerized from mutated, hydrolysis-deficient tubulins. We find that GTP-MTs have an "expanded lattice" and a "closed seam", structural characteristics possibly responsible for stabilizing the GTP cap. These results provide new insight into the structural transitions at growing MT ends, furthering our understanding of the bistable nature of MTs.

biophysics↗

bioRxiv2021

The beneficial rhizobacterium Bacillus velezensis acquires iron from roots via a type VII secretion system for colonization

Niche colonization is the key for bacterial adaptation to the environment, and competition for iron largely determines root colonization by rhizosphere microbes. Pathogenic and beneficial symbiotic bacteria use various unique secretion systems to support plant colonization or acquire limited resources from the environment. However, ubiquitous nonsymbiotic beneficial rhizobacteria have never been reported to use a unique secretion system to facilitate colonization. Here, we show that the type VII secretion system (T7SS) of the beneficial rhizobacterium Bacillus velezensis SQR9 contributes to root colonization. Knocking out T7SS and the major secreted protein YukE in SQR9 caused a significant decrease in root colonization. Moreover, the T7SS and YukE caused iron loss in plant roots in the early stage after inoculation, which contributed to root colonization by SQR9. Interestingly, purified YukE, but not inactivated YukE, could change the permeability of root cells. We speculated that secreted YukE might be directly inserted into the root cell membrane to cause iron leakage, indicating that the bacterial protein and root cell membrane interact directly. Moreover, a bacterial siderophore and the T7SS may be coordinately involved in iron acquisition by B. velezensis SQR9 for efficient root colonization. We showed that the beneficial rhizobacterium B. velezensis SQR9 could acquire iron from roots via the T7SS for rapid colonization. These findings provide the first insight into the function of the unique secretion system in nonsymbiotic beneficial rhizobacteria and reveal a novel mutualism in which plants and bacteria might share iron in a sequential manner.

microbiology↗

bioRxiv2021

m6A-mediated Cell-cell Communication Controls Planarian Regeneration

Regeneration is the regrowth of damaged tissues or organs, a vital mechanism responding to damages from primitive organisms to higher mammals. Planarian possesses active whole-body regenerative capability owning to its vast reservoir of adult stem cells, neoblasts, thus provides an ideal model to delineate the underlying mechanisms for regeneration. N6-methyladenosine (m6A) regulates stem cell renewal and differentiation. However, how m6A controls regeneration at whole-organism level remains largely unknown. Here, we demonstrate that the depletion of m6A methyltransferase regulatory subunit wtap abolishes planarian regeneration, through regulating cell-cell communication and cell cycle. scRNA-Seq analysis unveils that the wtap knockdown induces a unique type of neural progenitor-like cells (NP-like cells), characterized by specific expression of the cell-cell communication ligand grn. Intriguingly, the depletion of m6A-modified transcripts grn/cdk9 (or cdk7) axis rescues the defective regeneration of planarian without wtap. Overall, our study reveals an indispensable role of m6A-dependent cell-cell communication essential for whole-organism regeneration.

molecular biology↗

bioRxiv2021

ADAR mediated A-to-I RNA editing affects SARS-CoV-2 characteristics and fuels its evolution

Upon SARS-CoV-2 infection, viral intermediates activate the Type I interferon (IFN) response through MDA5-mediated sensing and accordingly induce ADAR1 p150 expression, which might lead to A-to-I RNA editing of SARS-CoV-2. Here, we developed an RNA virus-specific editing identification pipeline, surveyed 7622 RNA-seq data from diverse types of samples infected with SARS-CoV-2, and constructed an atlas of A-to-I RNA editing sites in SARS-CoV-2. We found that A-to-I editing was dynamically regulated, and on average, approximately 91 editing events were deposited at viral dsRNA intermediates per sample. Moreover, editing hotspots were observed, including recoding sites in the spike gene that affect viral infectivity and antigenicity. Finally, we provided evidence that RNA editing accelerated SARS-CoV-2 evolution in humans. Collectively, our data suggest that SARS-CoV-2 hijacks components of the host antiviral machinery to edit its genome and fuel its evolution.

microbiology↗

bioRxiv2021

Losartan shifts social reward motivation and punishment feedback sensitivity via modulating midbrain-striato-frontal circuits

Social deficits and dysregulations in dopaminergic midbrain-striato-frontal circuits represent transdiagnostic symptoms across psychiatric disorders. Animal models suggest that interactions between the dopamine and renin-angiotensin system may modulate learning and reward-related processes. The present study therefore examined the behavioral and neural effects of the angiotensin II type 1 receptor (AT1R) antagonist Losartan on social reward and punishment processing in humans. A pre-registered randomized double-blind placebo-controlled between-subject pharmacological design was combined with a social incentive delay fMRI paradigm during which subjects could avoid social punishment or gain social reward. Healthy volunteers received a single-dose of Losartan (50mg, n=43) or placebo (n=44). Reaction times and emotional ratings served as behavioral outcomes, on the neural level activation and connectivity were modelled. Relative to placebo, Losartan modulated the reaction time and arousal differences between social punishment and social reward. On the neural level the Losartan-enhanced motivational salience of social rewards was accompanied by stronger ventral striatum-prefrontal connectivity during reward anticipation. Losartan increased the reward-neutral difference in the ventral tegmental area (VTA) and attenuated VTA associated connectivity with the bilateral insula in response to punishment during the outcome phase. Losartan modulated approach-avoidance motivation and emotional salience during social punishment versus social reward via modulating distinct core nodes of the midbrain-striato-frontal circuits. The findings document a modulatory role of the renin-angiotensin system in these circuits and associated social processes, suggesting a promising treatment target to alleviate social dysregulations. Significance StatementSocial deficits and anhedonia characterize several mental disoders and have been linked to the midbrain-striato-frontal circuits of the brain. Based on initial findings from animal models we here combine the pharmacological blockade of the angiotensin II type 1 receptor (AT1R) via Losartan with functional MRI to demonstrate that AT1R blockade enhances the motivational salience of social rewards and attenuates the negative impact of social punishment via modulating the communication in the midbrain-striato-frontal circuits in humans. The findings demonstrate for the first time an important role of the AT1R in social reward processing in humans and render the AT1R as promising novel treatment target for social and motivational deficits in mental disoders.

neuroscience↗

bioRxiv2021

Susceptibilities of human ACE2 genetic variants in coronavirus infection

The COVID-19 pandemic, caused by SARS-CoV-2, has resulted in more than 1603 million cases worldwide and 3.4 million deaths (as of May 2021), with varying incidences and death rates among regions/ethnicities. Human genetic variation can affect disease progression and outcome, but little is known about genetic risk factors for SARS-CoV-2 infection. The coronaviruses SARS-CoV, SARS-CoV-2 and HCoV-NL63 all utilize the human protein angiotensin-converting enzyme 2 (ACE2) as the receptor to enter cells. We hypothesized that the genetic variability in ACE2 may contribute to the variable clinical outcomes of COVID-19. To test this hypothesis, we first conducted an in silico investigation of single-nucleotide polymorphisms (SNPs) in the coding region of ACE2 gene. We then applied an integrated approach of genetics, biochemistry and virology to explore the capacity of select ACE2 variants to bind coronavirus spike protein and mediate viral entry. We identified the ACE2 D355N variant that restricts the spike protein-ACE2 interaction and consequently limits infection both in vitro and in vivo. In conclusion, ACE2 polymorphisms could modulate susceptibility to SARS-CoV-2, which may lead to variable disease severity.

microbiology↗

bioRxiv2021

Neutralization of recombinant RBD-subunit vaccine ZF2001-elicited antisera to SARS-CoV-2 variants including Delta

SARS-CoV-2 variants brought new waves of infection worldwide. In particular, Delta variant (B.1.617.2 lineage) has become predominant in many countries. These variants raised the concern for their potential immune escape to the currently approved vaccines. ZF2001 is a subunit vaccine received emergency use authorization (EUA) in both China and Uzbekistan, with more than 100-million doses administrated with a three-dose regimen. The tandem-repeat dimer of SARS-CoV-2 spike protein receptor binding domain (RBD) was used as the antigen. In this work, we evaluated the neutralization of ZF2001-elicited antisera to SARS-CoV-2 variants including all four variants of concern (Alpha, Beta, Gamma and Delta) and other three variants of interest (Epsilon, Eta and Kappa) by pseudovirus-based assay. We found antisera preserved majority of the neutralizing activity against these variants. E484K/Q substitution is the key mutation to reduce the RBD-elicited sera neutralization. Moreover, ZF2001-elicited sera with a prolonged intervals between the second and third dose enhanced the neutralizing titers and resilience to SARS-CoV-2 variants.

immunology↗

bioRxiv2021

Unconventional tonicity-regulated nuclear trafficking of NFAT5 mediated by KPNB1, XPOT and RUVBL2

NFAT5 is the only known mammalian tonicity-responsive transcription factor functionally implicated in diverse physiological and pathological processes. NFAT5 activity is tightly regulated by extracellular tonicity but the underlying mechanisms remain elusive. We demonstrated that NFAT5 enters the nucleus via the nuclear pore complex. We also found that NFAT5 utilizes a non-canonical nuclear localization signal (NFAT5-NLS) for nuclear imports. siRNA screening revealed that karyopherin {beta}1 (KPNB1) drives nuclear import of NFAT5 via directly interacting with NFAT5-NLS. Proteomics analysis and siRNA screening further revealed that nuclear export of NFAT5 under hypotonicity is mediated by Exportin-T, and that it requires RuvB-Like AAA type ATPase 2 (RUVBL2) as an indispensable chaperone. Our findings have identified KPNB1 and RUVBL2 as key molecules responsible for the unconventional tonicity-regulated nucleocytoplasmic shuttling of NFAT5. These findings offer an opportunity for developing novel NFAT5 targeting strategies that are potentially useful for the treatment of diseases associated with NFAT5 dysregulation.

cell biology↗

bioRxiv2021

Fungal effector SIB1 of Colletotrichum orbiculare has unique structural features and can suppress plant immunity in Nicotiana benthamiana

Functional screening of effector candidates using a transient expression assay in Nicotiana benthamiana identified two virulence-related effectors, named SIB1 and SIB2 (Suppression of Immunity in N. benthamiana), of an anthracnose fungus Colletotrichum orbiculare, which infects both cucurbits and N. benthamiana. Agrobacterium-mediated transient expression of SIB1 or SIB2 increased the susceptibility of N. benthamiana to C. orbiculare, which suggested these effectors can suppress immune responses in N. benthamiana. The presence of SIB1 and SIB2 homologs was found to be limited to the genus Colletotrichum. SIB1 suppressed both the generation of reactive oxygen species (ROS) triggered by the bacterial pathogen-associated molecular pattern (PAMP), flg22, and the cell death response triggered by the Phytophthora infestans INF1 elicitin in N. benthamiana. We determined the NMR-based structure of SIB1 to obtain its structural insights. The three-dimensional structure of SIB1 comprises five {beta}-strands, each containing three disulfide bonds. The overall conformation was found to be a cylindrical shape, such as the well-known antiparallel {beta}-barrel structure. However, the {beta}-strands were found to display a unique topology, one pair of these {beta}-strands formed a parallel {beta}-sheet. These results suggest that the effector SIB1 present in Colletotrichum fungi has unique structural features and can suppress PAMP-triggered immunity (PTI) in N. benthamiana.

microbiology↗

bioRxiv2021

Genome-wide identification and characterization of DNA/RNA differences associated with Fusarium graminearum infection in wheat

RNA editing (DNA/RNA differences) as a post-transcriptional modification approach to enrich genetic information, plays the crucial role in regulating diverse biological processes in eukaryotes. Although it has been extensively studied in plant chloroplast and mitochondria genome, RNA editing in plant nuclear genome, especially those associated with Fusarium head blight (FHB), is not well studied at present. Here, we investigated the DNA/RNA differences associated with FHB through a novel method by comparing the RNA-seq data from Fusarium-infected and control samples from 4 wheat genotypes. A total of 187 DNA/RNA differences were identified in 36 wheat genes, representing the first landscape of the FHB-responsive RNA editome in wheat. Furthermore, all of these 36 edited genes were located in the FHB related co-expression gene modules, which may involve in regulating FHB response. Finally, the effects of DNA/RNA differences were systematically investigated to show that they could cause the change of RNA structure and protein structure in edited genes. In particular, the G to C editing (chr3A_487854715) in TraesCS3A02G263900, which is the orthology of OsRACK1, resulted that it was targeted by tae-miR9664-3p to control its expression in different genotype through different editing efficiency, suggesting RNA editing could mediate miRNA to participate in the regulation network of FHB tolerance. This study reported the first wheat DNA/RNA differences associated with FHB, which not only contribute to better understand the molecular basis underlying FHB tolerance, but also shed light on improving FHB tolerance through epigenetic method in wheat and beyond.

plant biology↗

bioRxiv2021

A Novel Local Ablation Approach for Explaining Multimodal Classifiers

With the growing use of multimodal data for deep learning classification in healthcare research, more studies have begun to present explainability methods for insight into multimodal classifiers. Among these studies, few have utilized local explainability methods, which could provide (1) insight into the classification of each sample and (2) an opportunity to better understand the effects of demographic and clinical variables within datasets (e.g., medication of subjects in electrophysiology data). To the best of our knowledge, this opportunity has not yet been explored within multimodal classification. We present a novel local ablation approach that shows the importance of each modality to the correct classification of each class and explore the effects of demographic and clinical variables upon the classifier. As a use-case, we train a convolutional neural network for automated sleep staging with electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG) data. We find that EEG is the most important modality across most stages, though EOG is particular important for non-rapid eye movement stage 1. Further, we identify significant relationships between the local explanations and subject age, sex, and state of medication which suggest that the classifier learned specific features associated with these variables across multiple modalities and correctly classified samples. Our novel explainability approach has implications for many fields involving multimodal classification. Moreover, our examination of the degree to which demographic and clinical variables may affect classifiers could provide direction for future studies in automated biomarker discovery.

bioinformatics↗

bioRxiv2021

A rat model of male pregnancy

Male pregnancy is a unique phenomenon in syngnathidae which refers to embryo or fetus incubation by males. However, whether male mammalian animals have the potential to conceive and maintain pregnancy remains unclear. Here, we constructed a rat model of pregnancy in the male parabiont using a four-step strategy. First, a heterosexual parabiotic pair was produced by surgically joining a castrated male rat and a female rat. After 8 weeks, uterus transplantation was performed on the male parabiont. After recovery, blastocyst-stage embryos were transplanted to the grafted uterus of the male parabiont and the native uterus of the female parabiont. Caesarean section was performed at embryonic day 21.5. The success rate of the model was 3.68%, and pups were only delivered from the male parabiont under pregnant blood exposure. Our results reveal the potential for rat embryonic development in male parabionts, which may have a profound impact on reproductive biology. One-sentence summaryA rat model of pregnancy was constructed in the male parabiont using a four-step strategy. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/447686v2_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@1f0694eorg.highwire.dtl.DTLVardef@91997forg.highwire.dtl.DTLVardef@f47086org.highwire.dtl.DTLVardef@7a33f_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2021

Bacillus velezensis stimulates resident rhizosphere Pseudomonas stutzeri for plant health through metabolic interactions

Trophic interactions play a central role in driving microbial community assembly and function. In gut or soil ecosystems, successful inoculants are always facilitated by efficient colonization, however, the metabolite exchanges between inoculants and resident bacteria are rarely studied, particularly in the rhizosphere. Here, we used bioinformatic, genetic, transcriptomic and metabonomic analyses to uncover syntrophic cooperation between inoculant (Bacillus velezensis SQR9) and plant-beneficial indigenous Pseudomonas stutzeri in the cucumber rhizosphere. We found that the synergistic interaction of these two species is highly environmental dependent, the emergence of syntrophic cooperation was only evident in a static nutrient-rich niche, such as pellicle biofilm in addition to the rhizosphere. Our results identified branched-chain amino acids (BCAAs) biosynthesis pathway involved in syntrophic cooperation when forming coculture biofilms. Assaying the metabolome further demonstrated metabolic facilitation among the bacterial strains. In addition, biofilm matrix components from Bacillus were essential for the interaction. Importantly, the two-species consortium promoted plant growth and helped plants alleviate salt stress. In summary, we propose a mechanism in which synergic interactions between a biocontrol bacterium and a partner species promote plant health.

microbiology↗

bioRxiv2021

Reconstructing unobserved cellular states from paired single-cell lineage tracing and transcriptomics data

AO_SCPLOWBSTRACTC_SCPLOWNovel experimental assays now simultaneously measure lineage relationships and transcriptomic states from single cells, thanks to CRISPR/Cas9-based genome engineering. These multimodal measurements allow researchers not only to build comprehensive phylogenetic models relating all cells but also infer transcriptomic determinants of consequential subclonal behavior. The gene expression data, however, is limited to cells that are currently present ("leaves" of the phylogeny). As a consequence, researchers cannot form hypotheses about unobserved, or "ancestral", states that gave rise to the observed population. To address this, we introduce TreeVAE: a probabilistic framework for estimating ancestral transcriptional states. TreeVAE uses a variational autoencoder (VAE) to model the observed transcriptomic data while accounting for the phylogenetic relationships between cells. Using simulations, we demonstrate that TreeVAE outperforms benchmarks in reconstructing ancestral states on several metrics. TreeVAE also provides a measure of uncertainty, which we demonstrate to correlate well with its prediction accuracy. This estimate therefore potentially provides a data-driven way to estimate how far back in the ancestor chain predictions could be made. Finally, using real data from lung cancer metastasis, we show that accounting for phylogenetic relationship between cells improves goodness of fit. Together, TreeVAE provides a principled framework for reconstructing unobserved cellular states from single cell lineage tracing data.

bioinformatics↗

bioRxiv2021

Systematic Analysis of Lysine Succinylation in Vero cells infected with Small Ruminant Morbillivirus

Small ruminant morbillivirus (SRMV), formerly named Peste-des-petits ruminants virus (PPRV), belongs to the genus Morbillivirus in the family Paramyxoviridae and causes a highly contagious disease in small ruminants, especially goats and sheep. Lysine succinylation is a newly identified and conserved modification and plays an important role in host cell response to pathogen infection. Here, we present a global analysis of the succinylome of SRMV-infected Vero cell using succinylation specific antibody-based enrichment and dimethylation labeling-based quantitative proteomics. As a result, 2633 succinylation sites derived from 823 cellular proteins were quantified. Comparative analysis revealed that 228 down-regulated succinylation sites on 139 proteins and 44 up-regulated succinylation sites on 38 proteins were significantly modified in response to SRMV infection, seven lysine succinylation motifs were identified. Bioinformatics analysis showed that the succinylated proteins mainly participated in cellular respiration and biosynthetic process. Protein-protein interaction networks of the identified proteins provided further evidence that a variety of ATP synthase subunits and carbon metabolism were modulated by succinylation while the overlapped proteins between succinylation and acetylation are involved in glyoxylate and dicarboxylate metabolism. Taken together, these findings provide the first report of succinylome in SRMV infection, lysine acetylation may have a more important effect than succinylation in SRMV infection. These findings provide a novel view on investigating the pathogenic mechanism of SRMV.

genomics↗

bioRxiv2021

An Explainable Deep Learning Approach for Multimodal Electrophysiology Classification

In recent years, more biomedical studies have begun to use multimodal data to improve model performance. As such, there is a need for improved multimodal explainability methods. Many studies involving multimodal explainability have used ablation approaches. Ablation requires the modification of input data, which may create out-of-distribution samples and may not always offer a correct explanation. We propose using an alternative gradient-based feature attribution approach, called layer-wise relevance propagation (LRP), to help explain multimodal models. To demonstrate the feasibility of the approach, we selected automated sleep stage classification as our use-case and trained a 1-D convolutional neural network (CNN) with electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG) data. We applied LRP to explain the relative importance of each modality to the classification of different sleep stages. Our results showed that across all samples, EEG was most important, followed by EOG, and EMG. For individual sleep stages, EEG and EOG had higher relevance for classifying awake and non-rapid eye movement 1 (NREM1). EOG was most important for classifying REM, and EEG was most relevant for classifying NREM2-NREM3. Also, LRP gave consistent levels of importance to each modality for correctly classified samples across folds and inconsistent levels of importance for incorrectly classified samples. Our results demonstrate the additional insight that gradient-based approaches can provide relative to ablation methods and highlight their feasibility for explaining multimodal electrophysiology classifiers.

bioinformatics↗

bioRxiv2021

The First High-Quality Reference Genome of Sika Deer Provides Insights for High-Tannin Adaptation

Sika deer are known to prefer oak leaves, which are rich in tannins and toxic to most mammals; however, the genetic mechanisms underlying their unique ability to adapt to living in the jungle are still unclear. In identifying the mechanism responsible for the tolerance of a highly toxic diet, we have made a major advancement in the elucidation of the genomics of sika deer. We generated the first high-quality, chromosome-level genome assembly of sika deer and measured the correlation between tannin intake and RNA expression in 15 tissues through 180 experiments. Comparative genome analyses showed that the UGT and CYP gene families are functionally involved in the adaptation of sika deer to high-tannin food, especially the expansion of UGT genes in a subfamily. The first chromosome-level assembly and genetic characterization of the tolerance toa highly toxic diet suggest that the sika deer genome will serve as an essential resource for understanding evolutionary events and tannin adaptation. Our study provides a paradigm of comparative expressive genomics that can be applied to the study of unique biological features in non-model animals.

genomics↗

bioRxiv2021

Explainable Sleep Stage Classification with Multimodal Electrophysiology Time-series

Many automated sleep staging studies have used deep learning approaches, and a growing number have used multimodal data to improve their classification performance. However, few studies using multimodal data have provided model explainability. Some have used traditional ablation approaches that "zero out" a modality. However, the samples that result from this ablation are unlikely to be found in real electroencephalography (EEG) data, which could adversely affect the importance estimates that result. Here, we train a convolutional neural network for sleep stage classification with EEG, electrooculograms (EOG), and electromyograms (EMG) and propose an ablation approach that replaces each modality with values that approximate the line-related noise commonly found in electrophysiology data. The relative importance that we identify for each modality is consistent with sleep staging guidelines, with EEG being important for most sleep stages and EOG being important for Rapid Eye Movement (REM) and nonREM stages. EMG showed low relative importance across classes. A comparison of our approach with a "zero out" ablation approach indicates that while the importance results are consistent for the most part, our method accentuates the importance of modalities to the model for the classification of some stages like REM (p < 0.05). These results suggest that a careful, domain-specific selection of an ablation approach may provide a clearer indicator of modality importance. Further, this study provides guidance for future research on using explainability methods with multimodal electrophysiology data.

bioinformatics↗