Digital microfluidics-based digital counting of single-cell copy number variation (dd-scCNV Seq).

Single-cell copy number variations (CNVs), major dynamic changes in humans, result in differential levels of gene expression and account for adaptive traits or underlying disease. Single-cell sequencing is needed to reveal these CNVs but has been hindered by single-cell whole-genome amplification (scWGA) bias, leading to inaccurate gene copy number counting. In addition, most of the current scWGA methods are labor intensive, time-consuming, and expensive with limited wide application. Here, we report a unique single-cell whole-genome library preparation approach based on digital microfluidics for digital counting of single-cell Copy Number Variation (dd-scCNV Seq). dd-scCNV Seq directly fragments the original single-cell DNA and uses these fragments as templates for amplification. These reduplicative fragments can be filtered computationally to generate the original partitioned unique identified fragments, thereby enabling digital counting of copy number variation. dd-scCNV Seq showed an increase in uniformity in the single-molecule data, leading to more accurate CNV patterns compared to other methods with low-depth sequencing. Benefiting from digital microfluidics, dd-scCNV Seq allows automated liquid handling, precise single-cell isolation, and high-efficiency and low-cost genome library preparation. dd-scCNV Seq will accelerate biological discovery by enabling accurate profiling of copy number variations at single-cell resolution.

Pancreatitis affects gut microbiota via metabolites and inflammatory cytokines: an exploratory two-step Mendelian randomisation study.

Previous studies have observed relationships between pancreatitis and gut microbiota; however, specific changes in gut microbiota abundance and underlying mechanisms in pancreatitis remain unknown. Metabolites are important for gut microbiota to fulfil their biological functions, and changes in the metabolic and immune environments are closely linked to changes in microbiota abundance. We aimed to clarify the mechanisms of gut-pancreas interactions and explore the possible role of metabolites and the immune system. To this end, we conducted two-sample Mendelian randomisation (MR) analysis to evaluate the casual links between four different types of pancreatitis and gut microbiota, metabolites, and inflammatory cytokines. A two-step MR analysis was conducted to further evaluate the probable mediating pathways involving metabolites and inflammatory cytokines in the causal relationship between pancreatitis and gut microbiota. In total, six potential mediators were identified in the causal relationship between pancreatitis and gut microbiota. Nineteen species of gut microbiota and seven inflammatory cytokines were genetically associated with the four types of pancreatitis. Metabolites involved in glucose and amino acid metabolisms were genetically associated with chronic pancreatitis, and those involved in lipid metabolism were genetically associated with acute pancreatitis. Our study identified alterations in the gut microbiota, metabolites, and inflammatory cytokines in pancreatitis at the genetic level and found six potential mediators of the pancreas-gut axis, which may provide insights into the precise diagnosis of pancreatitis and treatment interventions for gut microbiota to prevent the exacerbation of pancreatitis. Future studies could elucidate the mechanism underlying the association between pancreatitis and the gut microbiota.

Operation-robust SiO2-based memristive application in air.

In recent years, neuromorphic computing is recognized as a promising path to further improve the efficiency of integrated computing system in the post-Moore era, relying on its high parallelism. As a key fundamental element in hardware-implementing neuromorphic system, the synaptic device has made substantial research progress. Among these, SiO2 trapping-based memristive devices generally have systematically integrated merits, such as ease of fabrication and high CMOS process compatibility, but electrochemical activity to oxygen makes them unreliable for operating in air. Here, by using ultrathin Si3N4 as a physical isolation layer, we have obtained a robust memristive device based on SiO2 trapping although operating in air. Further study of Si3N4 thickness dependence has demonstrated that 7 nm is suggested as the most favorable thickness for reliable and flexible programming, and that an inherent isolating mechanism is 'switching-on' for an electron but 'switching-off' for large-sized oxygen molecules. Based on a device with 7 nm Si3N4, we have mimicked various modes of synaptic plasticities. These results could thus not only increase the prospects of using SiO2 trapping in memristive applications but also provide an effective path to improve the robustness of these SiO2-based applications against ambient air.

Information quality of videos related to Helicobacter pylori infection on TikTok: Cross-sectional study.

BACKGROUND: Helicobacter pylori (H. pylori) poses serious threats to human health. TikTok (Douyin in Chinese), a major social media platform focused on sharing short videos, has demonstrated great potential in spreading health information, including information related to H. pylori infection. This study aims to evaluate the content and quality of the information shared in TikTok videos about H. pylori infection in mainland China. METHODS: We collected a sample of 116 videos in Chinese related to H. pylori infection from TikTok. Video contents were evaluated by the coding schema proposed by Goobie et al., and the Hexagonal Radar Schema was used to intuitively display the spotlight and weight of each aspect of the videos. The DISCERN questionnaire was used to evaluate the quality of the videos. RESULTS: We identified two major sources of videos related to H. pylori: individual users (n = 89) and organizational users (n = 27). Regarding content, the Hexagonal Radar Charts showed that more than 35% of the videos delivered moderate to high quality content (>1 point) in terms of definition, symptoms and management of the disease, whereas risk factors, evaluation and outcomes of the disease were less discussed. The DISCERN classification data showed that 0.9% of the videos were "very poor," 5.2% "poor," 68.7% "fair," 20.0% "good," and only 5.2% "excellent". Regarding total DISCERN scores, videos published by nonprofit organizations had the highest scores, followed by videos uploaded by health professionals. CONCLUSION: Although the overall quality of TikTok videos related to H. pylori infection was medium, users should be careful when obtaining information related to H. pylori infection on TikTok and opt for videos uploaded by nonprofit organizations and health professionals.

Deciphering single-cell protein secretion and gene expressions by constructing cell-antibody conjugates.

Secreted proteins play critical roles in regulating immune responses, exerting cytotoxic effects on tumor cells, promoting inflammatory processes, and influencing cellular metabolism. Deciphering the intricate relationship between the heterogeneity of secreted proteins and their transcriptional states is pivotal in the study of cellular heterogeneity. Here we proposed a cell-antibody conjugate-based sequencing methodology (Cellab-seq) for joint characterization of secreted proteins and transcriptome. Cellab-seq utilizes a chemoenzymatic strategy to construct cell-antibody conjugates, which enables the capture of secreted proteins and their signal transduction with the incorporation of barcode detection antibodies. We applied Cellab-seq to investigate how gene expression influences the activity of secreted proteins in NK cells. Altogether, this strategy facilitates a nuanced understanding of cellular dynamics under diverse physiological conditions, ultimately contributing to the prevention, diagnosis and treatment of diseases.

Comprehensive Evolutionary Analysis of the SMXL Gene Family in Rosaceae: Further Insights into Its Origin, Expansion, Diversification, and Role in Regulating Pear Branching.

SMXL genes constitute a conserved gene family that is ubiquitous in angiosperms and involved in regulating various plant processes, including branching, leaf elongation, and anthocyanin biosynthesis, but little is known about their molecular functions in pear branching. Here, we performed genome-wide identification and investigation of the SMXL genes in 16 angiosperms and analyzed their phylogenetics, structural features, conserved motifs, and expression patterns. In total, 121 SMXLs genes were identified and were classified into four groups. The number of non-redundant SMXL genes in each species varied from 3 (Amborella trichopoda Baill.) to 18 (Glycine max Merr.) and revealed clear gene expansion events over evolutionary history. All the SMXL genes showed conserved structures, containing no more than two introns. Three-dimensional protein structure prediction revealed distinct structures between but similar structures within groups. A quantitative real-time PCR analysis revealed different expressions of 10 SMXL genes from pear branching induced by fruit-thinning treatment. Overall, our study provides a comprehensive investigation of SMXL genes in the Rosaceae family, especially pear. The results offer a reference for understanding the evolutionary history of SMXL genes and provide excellent candidates for studying fruit tree branching regulation, and in facilitating pear pruning and planting strategies.

Doping-modulated lateral asymmetric Schottky diode as a high-performance self-powered synaptic device.

In the post-Moore era, the gradually saturated computational capability of conventional digital computers showing the opposite trend as the exponentially increasing data volumes imperatively required a platform or technology to break this bottleneck. Brain-inspired neuromorphic computing promises to inherently improve the efficiency of information processing and computation by means of the highly parallel hardware architecture to reduce global data transmission. Here, we demonstrate a compact device technology based on the barrier asymmetry to achieve zero-consumption self-powered synaptic devices. In order to tune the device behaviors, the typical chemical doping is used to tailor the asymmetry for energy harvesting. Finally, in our demonstrated devices, the open-circuit voltage (VOC) and power-conversion efficiency (PCE) can be modulated up to 0.77 V and 6%, respectively. Optimized photovoltaic features affords synaptic devices with an outstanding programming weight states, involving training facilitation, stimulus reinforce and consolidation. Based on self-powered system, this work further presents a highly available modulation scheme, which achieves excellent device behaviors while ensuring the zero-energy consumption.

Electromagnetic interference elimination via active sensing and deep learning prediction for radiofrequency shielding-free MRI.

At present, MRI scans are typically performed inside fully enclosed radiofrequency (RF) shielding rooms, posing stringent installation requirements and causing patient discomfort. We aim to eliminate electromagnetic interference (EMI) for MRI with no or incomplete RF shielding. In this study, a method of active sensing and deep learning EMI prediction is presented to model, predict, and remove EMI signal components from acquired MRI signals. Specifically, during each MRI scan, separate EMI-sensing coils placed in various locations are utilized to simultaneously sample external and internal EMI signals within two windows (for both conventional MRI signal acquisition and EMI characterization acquisition). A convolution neural network model is trained using the EMI characterization data to relate EMI signals detected by EMI-sensing coils to EMI signals in the MRI receive coil. This model is then used to retrospectively predict and remove EMI signal components detected by the MRI receive coil during the MRI signal acquisition window. This strategy was implemented on a low-cost ultralow-field 0.055 T permanent magnet MRI scanner without RF shielding. It produced final image signal-to-noise ratios that were comparable with those obtained using a fully enclosed RF shielding cage, and outperformed existing analytical EMI elimination methods (i.e., spectral domain transfer function and external dynamic interference estimation and removal [EDITER] methods). A preliminary experiment also demonstrated its applicability on a 1.5 T superconducting magnet MRI scanner with incomplete RF shielding. Altogether, the results demonstrated that the proposed method was highly effective in predicting and removing various EMI signals from both external environments and internal scanner electronics at both 0.055 T (2.3 MHz) and 1.5 T (63.9 MHz). The proposed strategy enables shielding-free MRI. The concept is relatively simple and is potentially applicable to other RF signal detection scenarios in the presence of external and/or internal EMI.

LFA-1 knockout inhibited the tumor growth and is correlated with treg cells.

Cancer immunotherapy has been proven to be clinically effective in multiple types of cancers. Lymphocyte function-associated antigen 1 (LFA-1), a member of the integrin family of adhesion molecules, is expressed mainly on αß T cells. LFA-1 is associated with tumor immune responses, but its exact mechanism remains unknown. Here, two kinds of mice tumor model of LFA-1 knockout (LFA-1-/-) mice bearing subcutaneous tumor and Apc Min/+;LFA-1-/- mice were used to confirm that LFA-1 knockout resulted in inhibition of tumor growth. Furthermore, it also demonstrated that the numbers of regulatory T cells (Treg cells) in the spleen, blood, mesenteric lymph nodes were decreased in LFA-1-/- mice, and the numbers of Treg cells in mesenteric lymph nodes were also decreased in Apc Min/+;LFA-1-/- mice compared with Apc Min/+ mice. LFA-1 inhibitor (BIRT377) was administered to subcutaneous tumor-bearing LFA-1+/+ mice, and the results showed that the tumor growth was inhibited and the number of Treg cells was reduced. The analysis of TIMER tumor database indicated that LFA-1 expression is positively associated with Treg cells and TNM stage. Conclusively, this suggests that LFA-1 knockout would inhibit tumor growth and is correlated with Treg cells. LFA-1 may be one potential target for cancer immunotherapy. Video Abstract.

Aptamer-Based Detection of Circulating Targets for Precision Medicine.

The past decade has witnessed ongoing progress in precision medicine to improve human health. As an emerging diagnostic technique, liquid biopsy can provide real-time, comprehensive, dynamic physiological and pathological information in a noninvasive manner, opening a new window for precision medicine. Liquid biopsy depends on the sensitive and reliable detection of circulating targets (e.g., cells, extracellular vesicles, proteins, microRNAs) from body fluids, the performance of which is largely governed by recognition ligands. Aptamers are single-stranded functional oligonucleotides, capable of folding into unique tertiary structures to bind to their targets with superior specificity and affinity. Their mature evolution procedure, facile modification, and affinity regulation, as well as versatile structural design and engineering, make aptamers ideal recognition ligands for liquid biopsy. In this review, we present a broad overview of aptamer-based liquid biopsy techniques for precision medicine. We begin with recent advances in aptamer selection, followed by a summary of state-of-the-art strategies for multivalent aptamer assembly and aptamer interface modification. We will further describe aptamer-based micro-/nanoisolation platforms, aptamer-enabled release methods, and aptamer-assisted signal amplification and detection strategies. Finally, we present our perspectives regarding the opportunities and challenges of aptamer-based liquid biopsy for precision medicine.

The Reliability and Quality of Short Videos as a Source of Dietary Guidance for Inflammatory Bowel Disease: Cross-sectional Study.

BACKGROUND: Dietary management is considered a potential adjunctive treatment for inflammatory bowel disease (IBD). Short-video sharing platforms have enabled patients to obtain dietary advice more conveniently. However, accessing useful resources while avoiding misinformation is not an easy task for most patients. OBJECTIVE: This study aimed to evaluate the quality of the information in IBD diet-related videos on Chinese short-video sharing platforms. METHODS: We collected and extracted information from a total of 125 video samples related to the IBD diet on the 3 Chinese short-video sharing platforms with the most users: TikTok, Bilibili, and Kwai. Two independent physicians evaluated each video in terms of content comprehensiveness, quality (rated by Global Quality Score), and reliability (rated by a modified DISCERN tool). Finally, comparative analyses of the videos from different sources were conducted. RESULTS: The videos were classified into 6 groups based on the identity of the uploaders, which included 3 kinds of medical professionals (ie, gastroenterologists, nongastroenterologists, and clinical nutritionists) and 3 types of non-medical professionals (ie, nonprofit organizations, individual science communicators, and IBD patients). The overall quality of the videos was poor. Further group comparisons demonstrated that videos from medical professionals were more instructive in terms of content comprehensiveness, quality, and reliability than those from non-medical professionals. Moreover, IBD diet-related recommendations from clinical nutritionists and gastroenterologists were of better quality than those from nongastroenterologists, while recommendations from nonprofit organizations did not seem to be superior to other groups of uploaders. CONCLUSIONS: The overall quality of the information in IBD diet-related videos is unsatisfactory and varies significantly depending on the source. Videos from medical professionals, especially clinical nutritionists and gastroenterologists, may provide dietary guidance with higher quality for IBD patients.

A Lightweight CP-ABE Scheme with Direct Attribute Revocation for Vehicular Ad Hoc Network.

Ciphertext-Policy Attribute-Based Encryption (CP-ABE) technology provides a new solution to address the security and fine-grained access control of traffic information in vehicular ad hoc networks (VANETs). However, in most CP-ABE schemes for VANETs, attribute revocation suffers from high system consumption and complex revocation operations, as well as from high computational overhead and low efficiency due to the use of bilinear pairwise operations. Based on this, this paper proposes a lightweight CP-ABE scheme that supports direct attribute revocation in VANETs. The scheme implements an agent-based direct attribute revocation mechanism by separating dynamic and static attributes of vehicle terminals, which reduces system consumption and simplifies the revocation operation process. The scheme uses scalar multiplication on elliptic curves instead of bilinear pairing operations and uses computational outsourcing techniques to reduce the terminal decryption cost and improve the efficiency of the scheme. The security and performance analysis shows that the overall efficiency of our scheme is better than the existing schemes under the premise of ensuring data confidentiality and integrity.

ARMOR: Auto-Assembled Resilient Biomimetic Calcified Ornaments for Selective Cell Protection by Dual-Aptamer-Driven Hybridization Chain Reaction.

Unlike plant and microbial cells having cell walls, the outermost layer of mammalian cell is a delicate, two-layered structure of phospholipids with proteins embedded, which is susceptible to environmental changes. It is necessary to create an "armor" on cell surface to protect cell integrity. Here, we propose an Auto-assembled Resilient bioMimetic calcified ORnaments (ARMOR) strategy driven by dual-aptamer-based hybridization chain reaction (HCR) and Ca2+ assisted calcification for selective cell protection. This co-recognition design enhances the selectivity and leverages robust in situ signal amplification by HCR to improve the sensitivity. The calcified shell is cogenerated by crosslinking the alginate-HCR product with Ca2+ ion. ARMOR has high efficiency for shielding cells from environmental assaults, which can be applied to circulating tumor cell (CTC) protection, isolation, and identification, maintaining the native state and intact genetic information for downstream analysis.

Elucidation of myricetin biosynthesis in Morella rubra of the Myricaceae.

Flavonols are health-promoting bioactive compounds important for plant defense and human nutrition. Quercetin (Q) and kaempferol (K) biosynthesis have been studied extensively while little is known about myricetin (M) biosynthesis. The roles of flavonol synthases (FLSs) and flavonoid 3',5'-hydroxylase (F3'5'H) in M biosynthesis in Morella rubra, a member of the Myricaceae rich in M-based flavonols, were investigated. The level of MrFLS transcripts alone did not correlate well with the accumulation of M-based flavonols. However, combined transcript data for MrFLS1 and MrF3'5'H showed a good correlation with the accumulation of M-based flavonols in different tissues of M. rubra. Recombinant MrFLS1 and MrFLS2 proteins showed strong activity with dihydroquercetin (DHQ), dihydrokaempferol (DHK), and dihydromyricetin (DHM) as substrates, while recombinant MrF3'5'H protein preferred converting K to M, amongst a range of substrates. Tobacco (Nicotiana tabacum) overexpressing 35S::MrFLSs produced elevated levels of K-based and Q-based flavonols without affecting M-based flavonol levels, while tobacco overexpressing 35S::MrF3'5'H accumulated significantly higher levels of M-based flavonols. We conclude that M accumulation in M. rubra is affected by gene expression and enzyme specificity of FLS and F3'5'H as well as substrate availability. In the metabolic grid of flavonol biosynthesis, the strong activity of MrF3'5'H with K as substrate additionally promotes metabolic flux towards M in M. rubra.

DNA-Programmed Orientation-Ordered Multivalent Microfluidic Interface for Liquid Biopsy.

Aptamer-functionalized microfluidic interfaces hold great potential for liquid biopsies owing to their programmable nature. However, most previous studies have focused on development of multivalent aptamers to improve binding affinity, while ignoring aptamer orientation on microfluidic interfaces, resulting in suboptimal accessibility and affinity. Herein, we report a Cubic DNA Nanostructure (CDN)-programmed strategy to precisely control the orientation and valency of the Aptamer on a microfluidic interface (CDN-Apt-Chip) for enhancing the capture and release of circulating tumor cells (CTCs). We demonstrate that the ordered orientation and multivalent configuration can synergistically increase the binding affinity of aptamers toward CTCs. By using CDN-Apt-Chip, we successfully isolated CTCs from the peripheral blood of T-cell leukemia patients and discriminated T-cell leukemia patients from healthy volunteers. Furthermore, the captured CTCs were nondestructively released via nuclease treatment. We then performed T-cell receptor sequencing on the released cells to demonstrate the compatibility with downstream analysis. Overall, this study provides a new paradigm for interface regulation of functional microfluidic chips and advances the clinical translation of aptamer-based liquid biopsy.

Decoding Expression Dynamics of Protein and Transcriptome at the Single-Cell Level in Paired Picoliter Chambers.

Simultaneous analysis of mRNAs and proteins at the single-cell level provides information about the dynamics and correlations of gene and protein expressions in individual cells, enabling a comprehensive study of cellular heterogeneity and expression patterns. Here, we present a platform for about 1000 cellular indexing of mRNAs and membrane proteins, named multi-Paired-seq, with high cell utilization, accurate molecular measurement, and low cost. Based on hydrodynamic differential flow resistance, multi-Paired-seq largely improves cell utilization in the percentage of cells measured in population (>95%). Combined with the pump/valve structure, cell-free antibodies and mRNAs can be removed completely for highly accurate detection (R = 0.96) of protein copies. The picoliter reaction chambers allow high detection sensitivity for both mRNA transcripts and protein copies and low sequencing cost. Using multi-Paired-seq, three clusters of known breast cancer cell types are identified according to multimodal measurements, and the expression correlations between mRNAs and proteins under altered conditions are quantified. Multi-Paired-seq provides multimodal measurements at the single-cell level, which offers a new tool for cell biology, developmental biology, drug discovery, and precision medicine.

Joint denoising of diffusion-weighted images via structured low-rank patch matrix approximation.

PURPOSE: To develop a joint denoising method that effectively exploits natural information redundancy in MR DWIs via low-rank patch matrix approximation. METHODS: A denoising method is introduced to jointly reduce noise in DWI dataset by exploiting nonlocal self-similarity as well as local anatomical/structural similarity within multiple 2D DWIs acquired with the same anatomical geometry but different diffusion directions. Specifically, for each small 3D reference patch sliding within 2D DWI, nonlocal but similar patches are searched by matching image contents within entire DWI dataset and then structured into a patch matrix. The resulting patch matrices are denoised by enforcing low-rankness via weighted nuclear norm minimization and finally are back-distributed to DWI space. The proposed procedure was evaluated with simulated and in vivo brain diffusion tensor imaging (DTI) datasets and then compared to existing Marchenko-Pastur principal component analysis denoising method. RESULTS: The proposed method achieved significant noise reduction while preserving structural details in all DWIs for both simulated and in vivo datasets. Quantitative evaluation of error maps demonstrated it consistently outperformed Marchenko-Pastur principal component analysis method. Further, the denoised DWIs led to substantially improved DTI parametric maps, exhibiting significantly less noise and revealing more microstructural details. CONCLUSION: The proposed method denoises DWI dataset by utilizing both nonlocal self-similarity and local structural similarity within DWI dataset. This weighted nuclear norm minimization-based low-rank patch matrix denoising approach is effective and highly applicable to various diffusion MRI applications, including DTI as a postprocessing procedure.

Partial Fourier reconstruction of complex MR images using complex-valued convolutional neural networks.

PURPOSE: To provide a complex-valued deep learning approach for partial Fourier (PF) reconstruction of complex MR images. METHODS: Conventional PF reconstruction methods, such as projection onto convex sets (POCS), uses low-resolution image phase information from the central symmetrically sampled k-space for image reconstruction. However, this smooth phase constraint undermines the phase estimation accuracy in presence of rapid local phase variations, causing image artifacts and limiting the extent of PF reconstruction. Using both magnitude and phase characteristics in big complex image datasets, we propose a complex-valued deep learning approach with an unrolled network architecture for PF reconstruction that iteratively reconstructs PF sampled data and enforces data consistency. We evaluate our approach for reconstructing both spin-echo and gradient-echo data. RESULTS: The proposed method outperformed the iterative POCS PF reconstruction method. It produced better artifact suppression and recovery of both image magnitude and phase details in presence of local phase changes. No noise amplification was observed even for highly PF reconstruction. Moreover, the network trained on axial brain data could reconstruct sagittal and coronal brain and knee data. This method could be extended to 2D PF reconstruction and joint multi-slice PF reconstruction. CONCLUSION: Our proposed method can effectively reconstruct MR data even at low PF fractions, yielding high-fidelity magnitude and phase images. It presents a valuable alternative to conventional PF reconstruction, especially for phase-sensitive 2D or 3D MRI applications.

Calibrationless multi-slice Cartesian MRI via orthogonally alternating phase encoding direction and joint low-rank tensor completion.

We propose a multi-slice acquisition with orthogonally alternating phase encoding (PE) direction and subsequent joint calibrationless reconstruction for accelerated multiple individual 2D slices or multi-slice 2D Cartesian MRI. Specifically, multi-slice multi-channel data are first acquired with random or uniform PE undersampling while orthogonally alternating PE direction between adjacent slices. They are then jointly reconstructed through a recently developed low-rank multi-slice Hankel tensor completion (MS-HTC) approach. The proposed acquisition and reconstruction strategy was evaluated with human brain MR data. It effectively suppressed aliasing artifacts even at high acceleration factor, outperforming the existing MS-HTC approach, where PE direction is the same between adjacent slices. More importantly, the new strategy worked robustly with uniform undersampling or random undersampling without any consecutive central k-space lines. In summary, our proposed multi-slice MRI strategy exploits both coil sensitivity and image content similarities across adjacent slices. Orthogonally alternating PE direction among slices substantially facilitates the low-rank completion process and improves image reconstruction quality. This new strategy is applicable to uniform and random PE undersampling. It can be easily implemented in practice for Cartesian parallel imaging of multiple individual 2D slices without any coil sensitivity calibration.

Optogenetic fMRI interrogation of brain-wide central vestibular pathways.

Blood oxygen level-dependent functional MRI (fMRI) constitutes a powerful neuroimaging technology to map brain-wide functions in response to specific sensory or cognitive tasks. However, fMRI mapping of the vestibular system, which is pivotal for our sense of balance, poses significant challenges. Physical constraints limit a subject's ability to perform motion- and balance-related tasks inside the scanner, and current stimulation techniques within the scanner are nonspecific to delineate complex vestibular nucleus (VN) pathways. Using fMRI, we examined brain-wide neural activity patterns elicited by optogenetically stimulating excitatory neurons of a major vestibular nucleus, the ipsilateral medial VN (MVN). We demonstrated robust optogenetically evoked fMRI activations bilaterally at sensorimotor cortices and their associated thalamic nuclei (auditory, visual, somatosensory, and motor), high-order cortices (cingulate, retrosplenial, temporal association, and parietal), and hippocampal formations (dentate gyrus, entorhinal cortex, and subiculum). We then examined the modulatory effects of the vestibular system on sensory processing using auditory and visual stimulation in combination with optogenetic excitation of the MVN. We found enhanced responses to sound in the auditory cortex, thalamus, and inferior colliculus ipsilateral to the stimulated MVN. In the visual pathway, we observed enhanced responses to visual stimuli in the ipsilateral visual cortex, thalamus, and contralateral superior colliculus. Taken together, our imaging findings reveal multiple brain-wide central vestibular pathways. We demonstrate large-scale modulatory effects of the vestibular system on sensory processing.