Biology subjects

Huang, R.

Publications and source records attributed to Huang, R..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Paired vagus nerve stimulation drives precise remyelination and motor recovery after myelin loss

SummaryMyelin loss in the central nervous system can cause permanent motor or cognitive deficits in patients with multiple sclerosis (MS). While current immunotherapy treatments decrease the frequency of demyelinating episodes, they do not promote myelin repair or functional recovery. Vagus nerve stimulation (VNS) is a neuromodulation therapy which enhances neuroplasticity and the recovery of motor function after stroke, but its effects on myelin repair are not known. To determine if VNS influences myelin repair, we applied VNS following a demyelinating injury and measured longitudinal myelin dynamics and functional recovery. We found that VNS promotes remyelination by increasing the generation of myelinating oligodendrocytes. Pairing VNS with a skilled reach task leads to the regeneration of myelin sheaths on previously myelinated axon segments, enhancing the restoration of the original pattern of myelination. Moreover, the magnitude of sheath pattern restoration correlates with long-term motor functional improvement. Together, these results suggest that recovery of the myelin sheath pattern is a key factor in the restoration of motor function following myelin loss and identify paired VNS as a potential remyelination therapy to treat demyelinating diseases.

neuroscience↗

bioRxiv2024

Riluzole reverses blood-testis barrier loss to rescue chemotherapy induced male infertility by binding to TRPC

Cancer treatments, including cytotoxic therapy, often result in male infertility, necessitating the development of safe and effective strategies to preserve male reproductive potential during chemotherapy. Notably, our study uncovers the potential of repurposing riluzole, an FDA-approved drug for amyotrophic lateral sclerosis (ALS), in enhancing spermatogenesis. Hence, this research aims to explore the feasibility of utilizing riluzole to alleviate male infertility induced by busulfan (BSF), a commonly used chemotherapy drug. We established a BSF-induced oligospermia model in 4-week-old male mice and found that riluzole could effectively countered the detrimental effects of BSF on sperm production in mice with oligospermia. By restoring blood-testis barrier (BTB) functionality, riluzole improves sperm quality and reduces testicular atrophy. Through transcriptomic and molecular docking analyses, we identify transient receptor potential canonical subfamily member 5 (TRPC5) as a potential target for riluzole-mediated regulation of blood-testis barrier function. These findings propose riluzole as a promising therapeutic option for chemotherapy-induced male infertility, thereby addressing the fertility challenges associated with cancer treatments. Moreover, repurposing riluzole could streamline the drug development process, providing a cost-effective approach with reduced risk compared to developing entirely new drugs.

pharmacology and toxicology↗

bioRxiv2024

CDHu40: a novel marker gene set of neuroendocrine prostate cancer (NEPC)

Prostate cancer (PCa) is the most prevalent cancer affecting American men. Castration-resistant prostate cancer (CRPC) can emerge during hormone therapy for PCa, manifesting with elevated serum prostate-specific antigen (PSA) levels, continued disease progression, and/or metastasis to the new sites, resulting in a poor prognosis. A subset of CRPC patients shows a neuroendocrine (NE) phenotype, signifying reduced or no reliance on androgen receptor (AR) signaling and a particularly unfavorable prognosis. In this study, we incorporated computational approaches based on both gene expression profiles and protein-protein interaction (PPI) networks. We identified 500 potential marker genes, which are significantly enriched in cell cycle and neuronal processes. The top 40 candidates, collectively named as CDHu40, demonstrated superior performance in distinguishing NE prostate cancer (NEPC) and non-NEPC samples based on gene expression profiles compared to other published marker sets. Notably, some novel marker genes in CDHu40, absent in the other marker sets, have been reported to be associated with NEPC in the literature, such as DDC, FOLH1, BEX1, MAST1, and CACNA1A. Importantly, elevated CDHu40 scores derived from our predictive model showed a robust correlation with unfavorable survival outcomes in patients, indicating the potential of the CDHu40 score as a promising indicator for predicting the survival prognosis of those patients with the NE phenotype. Motif enrichment analysis on the top candidates suggests that REST and E2F6 may serve as key regulators in the NEPC progression. Significanceour study integrates gene expression variances in multiple NEPC studies and protein-protein interaction network to pinpoint a specific set of NEPC maker genes namely CDHu40. These genes and scores based on their gene expression levels effectively distinguish NEPC samples and underscore the clinical prognostic significance and potential mechanism.

bioinformatics↗

bioRxiv2024

Genomic and transcriptomic analyses of the elite rice variety Huizhan provide insight into disease resistance and heat tolerance

Rice is an important crop and serves as a model for crop genomics and breeding studies. Here, we used Oxford Nanopore ultra-long sequencing and next-generation sequencing technologies to generate a chromosome-scale genome assembly of Huizhan, a disease-resistant and heat-tolerant indica rice variety. The final genome assembly was 395.20 Mb with a scaffold N50 of 31.87 Mb. We identified expanded gene families in Huizhan that are potentially associated with both organ growth and development, as well as stress responses. We observed that three functional rice blast resistance genes, including Pi2, Pia and Ptr, and bacterial blight resistance gene Xa27, likely contribute to disease resistance of Huizhan. In addition, integrated genomics and transcriptomics analyses show that OsHIRP1, OsbZIP60, the SOD gene family, and various transcription factors are likely involved in heat tolerance of Huizhan. Results presented in this study will serve as a valuable resource for rice functional genomics studies and breeding.

genomics↗

bioRxiv2024

Ribonanza: deep learning of RNA structure through dual crowdsourcing

Prediction of RNA structure from sequence remains an unsolved problem, and progress has been slowed by a paucity of experimental data. Here, we present Ribonanza, a dataset of chemical mapping measurements on two million diverse RNA sequences collected through Eterna and other crowdsourced initiatives. Ribonanza measurements enabled solicitation, training, and prospective evaluation of diverse deep neural networks through a Kaggle challenge, followed by distillation into a single, self-contained model called RibonanzaNet. When fine tuned on auxiliary datasets, RibonanzaNet achieves state-of-the-art performance in modeling experimental sequence dropout, RNA hydrolytic degradation, and RNA secondary structure, with implications for modeling RNA tertiary structure.

biophysics↗

bioRxiv2024

Genome-wide CRISPR screen identifies AC9 as a key regulator of ER calcium homeostasis involved in neuronal differentiation.

Endoplasmic reticulum (ER) calcium (Ca2+) homeostasis is essential for maintaining normal cellular physiological functions. Its disturbance is strongly linked to the onset and progression of human diseases, including cancer, developmental defects, and neurodegenerative disorders. The lack of sensitive ratiometric ER Ca2+ indicators, nevertheless, hinders systematic investigation of ER Ca2+ modulators and the underlying mechanisms. Capitalizing on two ultra-sensitive ER Ca2+ indicators and CRISPR-based genome-wide screening, we identified a set of proteins capable of reducing the ER Ca2+ content. Further comparative analysis and qPCR validation pinpointed adenylate cyclase 9 (AC9), which is upregulated during neuronal differentiation, as a key ER-Ca2+-reducing regulator. Mechanistically, AC9-mediated production of cAMP is not essential for its ability to reduce ER Ca2+ content. Instead, AC9 inhibits store operated calcium entry (SOCE) by acting on Orai1, ultimately causing attenuation of ER Ca2+ level. More physiologically relevant, upregulation of AC9 in neurons is essential for reducing ER Ca2+ levels during Drosophila brain development. Collectively, this study lays a solid groundwork for further in-depth exploration of the regulatory mechanisms dictating ER Ca2+ homeostasis during neuronal differentiation and brain development.

cell biology↗

bioRxiv2024

Modelling variability in dynamic functional brain networks using embeddings

Functional neuroimaging techniques allow us to estimate functional networks that underlie cognition. However, these functional networks are often estimated at the group level and do not allow for the discovery of, nor benefit from, subpopulation structure in the data, i.e. the fact that some recording sessions maybe more similar than others. Here, we propose the use of embedding vectors (c.f. word embedding in Natural Language Processing) to explicitly model individual sessions while inferring dynamic networks across a group. This vector is effectively a "fingerprint" for each session, which can cluster sessions with similar functional networks together in a learnt embedding space. We apply this approach to estimate dynamic functional connectivity, using Hidden Markov Models (HMMs), which are popular methods for inferring dynamic networks, to model individual sessions in neuroimaging data. We call this approach HIVE (HMM with Integrated Variability Estimation). Using simulated data, we show that HIVE can recover the true, underlying inter-session variability and show improved performance over existing approaches. Using real magnetoencephalography data, we show the learnt embedding vectors (session fingerprints) reflect meaningful sources of variation across a population (demographics, scanner types, sites, etc). Overall, HIVE provides a powerful new technique for modelling individual sessions while leveraging information available across an entire group. HighlightsO_LIWe proposed the use of embedding vectors and a novel variability encoding block for inferring individualised brain networks in neuroimaging data. C_LIO_LIWe apply this approach to estimate dynamic functional connectivity using the Hidden Markov Models (HMMs) and explicitly model variability in the training dataset. We call this new model HIVE (HMM with Integrated Variability Estimation) C_LIO_LIWe demonstrate the advantages of HIVE over traditional approaches using both simulated and real MEG data. C_LIO_LIWe show HIVE learns meaningful variability in the data (e.g. measurement site, scanner type, demographics) in an unsupervised manner. C_LIO_LIThe datasets and scripts for performing all the analysis in this paper are made publicly available. C_LI

neuroscience↗

bioRxiv2024

Shrimp Hemocyanin elicits a potent humoral response in mammals and is favorable to hapten conjugation

Conjugation to a carrier protein is essential to give rise to the antigenicity of hapten, which is a small molecule and cannot induce an immune response by itself alone. Three carrier proteins e.g. KLH (Keyhole Limpet Hemocyanin), BSA (Bovine Serum Albumin), and OVA (Ovalbumin) were used mostly. KLH is advantageous to the others, majorly owing to its strong immunogenicity and limited usage in other biological assays. However, the solubility of KLH is not as well as the others, especially after hapten conjugation. Besides, the high market price of KLH results in high costs in vaccine and antibody development. Here, we extracted the shrimp hemocyanin (SHC) from Penaeus vannamei (P. vannamei) with a production yield of > 1 g proteins (98 % pure) per 1 kg shrimp. Compared to KLH, the peptide-SHC conjugates exhibit higher solubility after hapten conjugation. Furthermore, compared with KLH, SHC induces comparable antibody production efficiency in mammals, with or without conjugation. Finally, rabbit polyclonal antibodies or mouse monoclonal antibodies were generated by immunizing SHC-peptide conjugates, and their applications in western blot, immunofluorescence and immunohistochemistry were confirmed. Therefore, we demonstrated that SHC may be used as a substitute for KLH in future antibody and vaccine development.

bioengineering↗

bioRxiv2024

Dynamic Network Analysis of Electrophysiological Task Data

An important approach for studying the human brain is to use functional neuroimaging combined with a task. In electrophysiological data this often involves a time-frequency analysis, in which recorded brain activity is time-frequency transformed and epoched around task events of interest, followed by trial-averaging of the power. Whilst this simple approach can reveal fast oscillatory dynamics, the brain regions are analysed one at a time. This causes difficulties for interpretation and a debilitating number of multiple comparisons. In addition, it is now recognised that the brain responds to tasks through the coordinated activity of networks of brain areas. As such, techniques that take a whole-brain network perspective are needed. Here, we show how the oscillatory task responses from conventional time-frequency approaches, can be represented more parsimoniously at the network level using two state-of-the-art methods: the HMM (Hidden Markov Model) and DyNeMo (Dynamic Network Modes). Both methods reveal frequency-resolved networks of oscillatory activity with millisecond resolution. Comparing DyNeMo, HMM and traditional oscillatory response analysis, we show DyNeMo can identify task activations/deactivations that the other approaches fail to detect. DyNeMo offers a powerful new method for analysing task data from the perspective of dynamic brain networks. HighlightsO_LIWe show how oscillatory task response analysis can be carried out at the network level using two state-of-the-art methods: the Hidden Markov Model (HMM) and Dynamics Network Modes (DyNeMo). C_LIO_LIThe HMM and DyNeMo can identify oscillatory task responses that conventional time-frequency methods fail to detect. C_LIO_LIDyNeMo provides a more interpretable and precise network decomposition of the data compared to the HMM. C_LIO_LIThe dataset and (Python) scripts used to perform dynamic network analysis on task data are made publicly available. C_LI

neuroscience↗

bioRxiv2023

Systematic benchmarking of imaging spatial transcriptomics platforms in FFPE tissues

Emerging imaging spatial transcriptomics (iST) platforms and coupled analytical methods can recover cell-to-cell interactions, groups of spatially covarying genes, and gene signatures associated with pathological features, and are thus particularly well-suited for applications in formalin fixed paraffin embedded (FFPE) tissues. Here, we benchmarked the performance of three commercial iST platforms on serial sections from tissue microarrays (TMAs) containing 23 tumor and normal tissue types for both relative technical and biological performance. On matched genes, we found that 10x Xenium shows higher transcript counts per gene without sacrificing specificity, but that all three platforms concord to orthogonal RNA-seq datasets and can perform spatially resolved cell typing, albeit with different false discovery rates, cell segmentation error frequencies, and with varying degrees of sub-clustering for downstream biological analyses. Taken together, our analyses provide a comprehensive benchmark to guide the choice of iST method as researchers design studies with precious samples in this rapidly evolving field.

cancer biology↗

bioRxiv2023

Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses

Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically-determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus SARS-CoV-2, resolved at 4.7 [A] resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the Ts "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4-6.9 [A] resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across the studied human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9-8.0 [A] resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4-9.0 [A] resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities, with implications for potential protein-binding modes and therapeutic targets. SignificanceThe three-dimensional structures of viral RNAs are of interest to the study of viral pathogenesis and therapeutic design, but the three-dimensional structures of viral RNAs remain poorly characterized. Here, we provide the first 3D structures of the SL5 domain (124-160 nt, 40.0-51.4 kDa) from the majority of human-infecting coronaviruses. All studied SL5s exhibit a similar 4-way junction, with their crossing angles grouped along phylogenetic boundaries. Further, across all species studied, conserved UUYYGU hexaloop pairs are located at opposing ends of a coaxial stack, suggesting that their three-dimensional arrangement is important for their as-of-yet defined function. These conserved tertiary features support the relevance of SL5 for pan-coronavirus fitness and highlight new routes in understanding its molecular and virological roles and in developing SL5-based antivirals. Classification: Biological Sciences, Biophysics and Computational Biology

biophysics↗

bioRxiv2023

Characterization of the Complete Chloroplast Genome Sequences and Phylogenetic Relationships of Four Oil-Seed Camellia spp. and related taxa

Some species in the Sect. Oleifera of the genus Camellia L. known as oil-seed camellia because of their high oil content and economic value. Additional studies aimed at clarifying the phylogenetic relationships and chloroplast genomes of Camellia species are needed to hybridization, as well as improve the breeding, selection and interspecific hybridization of Camellia species. The complete chloroplast genomes (cpDNA) of the four oil-seed camellia species C. semiserrata, C. meiocarpa, C. suaveolens, and C. osmantha were resequenced to clarify their interspecific relationships. These cpDNA had typical tetrad structures, and they were highly conserved in various structural features. The total lengths of the cpDNA ranged from 156,965 to 157,018 bp, and 134 genes were annotated, including 88 protein-coding genes, 37 transfer RNA genes, and 8 messenger RNA genes. The average GC content of these genomes was 37.3%. The codons with the highest and lowest codon usage bias were UUA (which codes for leucine) and AGC (which codes for serine), respectively. The number of simple sequences repeats of the four Camelia species ranged from 38 to 40. Mononucleotide repeats were the most common repeat type, followed by tetranucleotide, trinucleotide, and hexanucleotide repeats. Our phylogenetic analysis of cpDNA, coupled with the results of previous ploidy analyses and artificial interspecific hybridization, revealed that C. semiserrata was most closely related to C. azalea, C. suaveolens was most closely related to C. gauchowensis, C. osmantha was most closely related to C. vietnamensis, and C. meiocarpa was most closely related to C. oleifera. The phylogenetic relationships between oil-seed camellia species with high oil content and economic value were characterized. Our analysis of the cpDNA provided new insights that will aid the use of artificial distant hybridization in camellia breeding programs.

genomics↗

bioRxiv2023

Integrating large-scale meta-GWAS and PigGTEx resources to decipher the genetic basis of complex traits in pig.

Understanding the molecular and cellular mechanisms that underlie complex traits in pigs is crucial for enhancing their genetic improvement program and unleashing their substantial potentials in human biomedicine research. Here, we conducted a meta-GWAS analysis for 232 complex traits with 28.3 million imputed whole-genome sequence variants in 70,328 individuals from 14 pig breeds. We identified a total of 6,878 genomic regions associated with 139 complex traits. By integrating with the Pig Genotype-Tissue Expression (PigGTEx) resource, we systemically explored the biological context and regulatory circuits through which these trait-associated variants act and finally prioritized 16,664 variant-gene-tissue-trait circuits. For instance, rs344053754 regulates the expression of UGT2B31 in the liver by affecting the activity of regulatory elements and ultimately influences litter weight at weaning. Furthermore, we investigated the conservation of genetic and regulatory mechanisms underlying 136 human traits and 232 pig traits. Overall, our multi-breed meta-GWAS in pigs provides invaluable resources and novel insights for understanding the regulatory and evolutionary mechanisms of complex traits in both pigs and humans.

genetics↗

bioRxiv2023

ONECUT2 Activates Diverse Resistance Drivers of Androgen Receptor-Independent Heterogeneity in Prostate Cancer

Significance StatementONECUT2 (OC2) is a master transcription factor that alters lineage identity by activating gene networks associated with both neuroendocrine prostate cancer and prostate adenocarcinoma. A small molecule inhibitor of OC2 represses the lineage plasticity program activated by enzalutamide, suggesting OC2 inhibition as a novel therapeutic strategy to prevent emergence of treatment-resistant variants. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/560025v2_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@13278a4org.highwire.dtl.DTLVardef@8e82aeorg.highwire.dtl.DTLVardef@25a115org.highwire.dtl.DTLVardef@728eb4_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic AbstractC_FLOATNO C_FIG Androgen receptor-(AR-) indifference is a mechanism of resistance to hormonal therapy in prostate cancer (PC). Here we demonstrate that the HOX/CUT transcription factor ONECUT2 (OC2) activates resistance through multiple drivers associated with adenocarcinoma, stem-like and neuroendocrine (NE) variants. Direct OC2 targets include the glucocorticoid receptor and the NE splicing factor SRRM4, among others. OC2 regulates gene expression by promoter binding, enhancement of chromatin accessibility, and formation of novel super-enhancers. OC2 also activates glucuronidation genes that irreversibly disable androgen, thereby evoking phenotypic heterogeneity indirectly by hormone depletion. Pharmacologic inhibition of OC2 suppresses lineage plasticity reprogramming induced by the AR signaling inhibitor enzalutamide. These results demonstrate that OC2 activation promotes a range of drug resistance mechanisms associated with treatment-emergent lineage variation in PC. Our findings support enhanced efforts to therapeutically target this protein as a means of suppressing treatment-resistant disease.

cancer biology↗

bioRxiv2023

A resource for probing influences of perinatal factors on neurodevelopment in 3-10-years-old Chinese children

Adverse perinatal factors can disrupt the normal development of the brain, with potential long-term impacts on childrens overall development. Currently, the neuropathological mechanisms by which these factors lead to various neurodevelopmental disorders (NDDs) remain largely unknown. An open resource that integrate perinatal factors with brain and mental health development is essential for investigating NDD-related aetiology. In this Data Descriptor, we introduce a multicentre database containing information on perinatal factors that influence childrens brain-mind development, namely, periCBD, that combines neuroimaging and behavioural phenotypes with perinatal factors associated with a high incidence of NDDs at county/region/central district hospitals. PeriCBD was designed to establish a platform for the investigation of individual differences in brain-mind development among children aged 3-10 years are associated with perinatal factors. Ultimately, our goal was to develop an early prediction and screening model for NDDs that leverages normative data to facilitate NDD aetiology research. Herein, we provide a systematic overview of the data acquisition/cleaning/quality control/sharing, processes of periCBD and present preliminary brain-mind associations.

neuroscience↗

bioRxiv2023

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimers disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

PRO-LDM: Protein Sequence Generation with Conditional Latent Diffusion Models

AbstractsDeep learning-driven protein design holds enormous potential despite the complexities in sequences and structures. Recent developments in diffusion models yielded success in structure design, but awaits progress in sequence design and are computationally demanding. Here we present PRO-LDM: an efficient framework combining design fidelity and computational efficiency, utilizing the diffusion model in latent space to design proteins with property tuning. The model employs a joint autoencoder to capture latent variable distributions and generate meaningful embeddings from sequences. PRO-LDM (1) learns representations from biological features in natural proteins at both amino-acid and sequence level; (2) generates native-like new sequences with enhanced diversity; and (3) conditionally designs new proteins with tailored properties or functions. The out-of-distribution design enables sampling notably different sequences by adjusting classifier guidance strength. Our model presents a feasible pathway and an integratable tool to extract physicochemical and evolutionary information embedded within primary sequences, for protein design and optimization.

bioengineering↗

bioRxiv2023

`Mind in Vitro' platforms: Versatile, scalable, robust and open solutions to interfacing with living neurons

Motivated by the unexplored potential of in vitro neural systems for computing, and by the corresponding need of versatile, scalable interfaces for multimodal interaction, we present an accurate, modular, fully customizable and portable recording/stimulation solution that can be easily fabricated, robustly operated, and broadly disseminated. A reconfigurable platform that works across multiple industry standards enables a complete signal chain, from neural substrates sampled through high-density Micro-Electrode Arrays (MEAs) to data acquisition, downstream analysis and cloud storage. Built-in modularity supports the seamless integration of electrical/optical stimulation and fluidic interfaces. Custom MEA fabrication leverages maskless photolithography, favoring the rapid prototyping of a variety of configurations and spatial topologies. Through a native analysis and management software suite, the utility and robustness of our system is demonstrated across neural cultures and applications, including embryonic stem cell-derived and primary neurons, organotypic brain slices, 3D engineered tissue mimics, concurrent calcium imaging and long-term recording. Overall, our technology, termed Mind in Vitro to underscore the computing inspiration, provides an end-to-end solution that can be widely deployed due to its affordable (>10X cost-reduction) and open-source nature, catering to the expanding needs of both conventional and unconventional electrophysiology.

neuroscience↗