Biology subjects

Zhu, T.

Publications and source records attributed to Zhu, T..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Genomic Isomerism and Environmental Adaptation in Cyanophages Infecting Freshwater Cyanobacteria

Cyanophages infecting multicellular, heterocyst-forming cyanobacteria play diverse pivotal roles in freshwater ecosystems, yet their infection strategies and genomic adaptability remain poorly understood. Here, we isolated and characterized three Caudoviricetes cyanophages (A-Lf14, A-Alj1 and A-Hlh1) specifically infecting the nitrogen-fixing cyanobacterium Anabaena sp. PCC 7120. Super-resolution microscopy revealed heterogeneous infection outcomes even among adjacent cells within the same filament, highlighting host-level defense variability. Comparative genomics placed these phages within a cluster that includes the previously isolated phages A-1(L) and N1, and revealed a conserved [~]30 kb invertible genomic region flanked by inverted repeats (IR). This region exists as two stable isomers simultaneously within phage populations, a previously unreported genomic plasticity trait in cyanophages. Consistent with such plasticity, infection kinetics were modulated by light and nitrogen availability, indicating a resource-responsive infection strategy. The novel phages encode an alkaline phosphatase of non-cyanobacterial origin, which was highly upregulated during infection indicating a role in phosphate acquisition in phosphate-limited waters. In contrast, they lack a tnpB gene present in A-1(L), which is identical in sequence to five genes in the host genome. We detected protein-coding potential for both strands of tnpB and upregulated transcription during infection, consistent with a role in this process. The 347 residues protein encoded on the tnpB reverse strand exhibited only limited similarity to other proteins or folding potential, underlining its novelty. Our work illustrates how genomic isomerism, accessory genes, and environmental sensing collectively drive functional diversification in cyanophages, providing insights into phage-host coevolution and the impact of phages on cyanobacterial blooms in dynamic freshwater ecosystems.

microbiology↗

bioRxiv2026

MATR3 is essential for oocyte growth and maturation quality through a dual molecular mechanism

The molecular mechanisms governing mRNA accumulation during oocyte growth, essential for developmental competence, remain poorly understood. This study investigates the role of Matrin-3 (MATR3), a highly expressed RNA-binding protein in growing oocytes (GOs), using oocyte-specific knockout mouse models and human oocyte maturation arrest (OMA) samples. The results showed that MATR3 was more abundant in GOs than fully-grown oocytes (FGOs), highly expressed in the nucleus of non-surrounded nucleolus (NSN) oocytes, and exited the nucleus during the NSN-to-surrounded nucleolus (SN) transition. In OMA patients, MATR3 nuclear localization was missed, with smaller oocytes than FGOs. Further, Matr3 deletion in mouse GOs caused restricted oocyte growth, global transcription disorders, follicle development failure, blocked GO-granulosa cell communication (via reduced Gdf9 and Radixin expression), and infertility. Mechanistically, MATR3 regulated transcription by recruiting H3K9me2-demethylating lysine-specific demethylase 3B or binding target gene promoters, like Radixin. These findings reveal a critical role of MATR3 in orchestrating transcription and paracrine signaling during oogenesis and suggest its potential as a diagnostic and therapeutic target for OMA.

physiology↗

bioRxiv2026

Disrupted Sleep-Dependent Neural Oscillations and Transcriptomic Changes in the Cacna1g Loss-of-Function Mouse Model Implicated in Schizophrenia

Sleep is an essential biological process for maintaining brain function, and impaired sleep microarchitecture is a well-established feature of schizophrenia (SCZ). Rare loss-of-function variants in CACNA1G, encoding the T-type calcium channel CaV3.1, confer substantial risk for SCZ, implicating sleep-regulatory circuits in disease pathophysiology. Here, we first show that among individuals with SCZ, carriers of rare CACNA1G missense variants exhibit more pronounced alterations in sleep neurophysiology than non-carriers, identifying a human phenotype suggestive of altered channel function. Motivated by this observation, we examined the consequences of Cacna1g loss of function in mice. Cacna1g deficiency produced profound disruptions in sleep microarchitecture, including reduced sleep spindles, altered slow oscillations, impaired spindle-slow oscillation coupling, and reduced cortical synchrony--closely recapitulating neurophysiological signatures observed in individuals with schizophrenia. Beyond sleep structure, Cacna1g loss disrupted the normal coordination of brain rhythms across the 24-hour cycle, most notably abolishing diurnal modulation of theta oscillations. At the molecular level, Cacna1g loss uncoupled sleep-wake state from gene and protein regulation, producing widespread, sleep-phase-biased transcriptional and synaptic alterations across brain regions and cell types, particularly in cortical excitatory neurons. These network and molecular disruptions were accompanied by behavioral hyperactivity during the active phase. Together, these findings establish CACNA1G/CaV3.1 as a key regulator linking sleep-dependent brain dynamics to molecular homeostasis and behavior, and provide a mechanistic framework through which genetic risk for SCZ may drive disease-relevant sleep and circuit dysfunction. One Sentence SummaryLoss of CACNA1G disrupts sleep rhythms and gene regulation, creating a mismatch between brain state and behavior linked to schizophrenia.

neuroscience↗

bioRxiv2026

Integration of early-stage cryopreservation and cell cycle modulation into a flexible kidney organoid differentiation system

Kidney organoids derived from human pluripotent stem cells (hPSCs) represent a promising platform for modeling nephrogenesis and renal diseases. However, conventional differentiation protocols are continuous and time-sensitive, limiting their scalability and reproducibility. Here, we developed a method to pause and resume organoid formation through cryopreservation at an early differentiation stage using a chemically defined formulation that maintains high post-thaw viability and differentiation potential. We further found that synchronizing hPSCs in the G1 phase with PD-0332991 enhanced post-thaw organoid formation and transcriptional fidelity, while G2 phase enrichment with Ro-3306 promoted the development of SLC12A3-positive distal convoluted tubules. The post-thaw organoids exhibited well-organized nephron architecture and function comparable to uninterrupted cultured controls. This platform proved effective for modeling BK polyomavirus (BKV) infection, drug-induced nephrotoxicity, and renal fibrosis. Together, our cryopreservation and cell cycle synchronization strategy provides a flexible, practical framework to advance organoid-based research and translation.

developmental biology↗

bioRxiv2026

Can near-infrared exposure help mitigate pesticide-impaired thermoregulation in adult bees?

For terrestrial animals, maintaining body temperature is vital for successful movement, feeding and reproduction. Exposure to environmental toxins such as pesticides, however, may place individual thermoregulation at risk. Identifying potential mitigative solutions is thus important, especially given widespread pesticide applications across landscapes are forecast to continue. In mammals, near infrared (NIR) light has been put forward as a method for countering the effects of toxin exposure, but limited evidence has been found for insects. Here, we orally expose an important insect pollinator group - adult bumblebees - to a cholinergic pesticide (a neonicotinoid) to first quantify the baseline impact on body temperature (using thermal imaging), and second to investigate how exposure to near infrared (NIR) light mediates this effect. For bumblebees kept at 18{degrees}C ambient we show, relative to control bees who maintained their body temperature at ca.30{degrees}C, that neonicotinoid exposed bees exhibited a steep (by nearly 8{degrees}C) body temperature drop over the 73hr assay showing a pattern of convergence towards ambient. We did however find some evidence that NIR can partially counter such neonicotinoid impairment. Of two different wavelengths (600nm, 850nm) and three exposure durations (5, 10 or 20 minutes per hour), we found evidence that 660 nm for 5 minutes appeared to more than halve the rate to which the neonicotinoid decreased body temperature. Yet, intriguingly, the mitigation effect of 660 nm NIR appeared to lessen as exposure time increased. We further found tentative evidence that 850 nm for 20 mins may alleviate the decline in body temperature (by nearly 40%). In conclusion, our study further highlights a mechanism by which pesticides threaten the critical functioning of non-target organisms but also provides a potential therapy worthy of further investigation.

ecology↗

bioRxiv2025

IGHV3-53 antibody abundance drives divergent SARS-CoV-2 immune imprinting

The mechanisms driving divergent SARS-CoV-2 immune imprinting in populations with distinct SARS-CoV-2 exposure histories remain unclear. However, conventional wild-type mouse models fail to recapitulate severe imprinting, even after potent ancestral-strain mRNA immunization, hindering imprinting-related mechanistic investigation and vaccine evaluation. Here, we surprisingly found that V(D)J-humanized mice could faithfully recapitulate human severe imprinting phenotypes. Comprehensive antibody repertoire analysis and deep mutational scanning-based epitope mapping of 583 monoclonal antibodies from these models revealed that the pre-existing IGHV3-53/66 antibody abundance determine imprinting severity through antibody-mediated masking of Omicron-specific epitopes. Both passive IGHV3-53/66 antibody transfer and IGHV3-53 knock-in were sufficient to induce severe imprinting in wild-type mice. Together, these findings demonstrate that the V(D)J germline repertoire--even a single germline-encoded antibody response--can profoundly shape humoral imprinting severity. Accordingly, we established an IGHV3-53 knock-in mouse model that accurately recapitulates the human antibody landscape, providing a valuable tool for guiding future COVID-19 vaccine updates.

immunology↗

bioRxiv2025

Pesticide-exposed bees fail to thermoregulate leading to cold colonies with consequences for offspring development

For many organisms, effective thermoregulation is needed to cope with changing environmental temperatures. But if exposure to pesticides in the environment were to impair this homeostatic process, reproduction and population viability could be at risk. Focusing on an important insect pollinator, we conducted three complementary experiments exposing bumblebees to a pesticide under different temperature challenges and measuring the impacts on thermoregulatory ability and brood development. First, we reveal that pesticide-exposed individuals cannot maintain a stable thorax temperature, especially at lower temperatures. Second, reductions in body temperature are accompanied by behavioural changes and that pesticide-exposed colonies fail to maintain appropriate brood temperatures. Third, such collective impairment on brood thermoregulation (not the pesticide toxicity to offspring per se) leads to delayed pupal development and reduced adult population growth. Our study provides a valid mechanistic explanation for why terrestrial insects requiring brood thermoregulation have declined. With frequent extreme weather events forecasted, our findings have concerning implications for how populations will adequately persist and grow under current pesticide-use regimes with ramifications on pollination services.

ecology↗

bioRxiv2025

The impact of incomplete taxon sampling on inference of gene flow by Bayesian and summary methods using genomic sequence data

Interspecific gene flow is commonly inferred using genomic data under the multispecies coalescent (MSC) model. The rate of gene flow is measured by the expected proportion of immigrants in the recipient population at the time of hybridization/introgression. Incomplete taxon sampling can impact inference of gene flow in multiple ways. First unsampled ghost lineages that are sources of introgression may mislead inference of gene flow in analysis of genomic data from modern species. Second incomplete taxon sampling causes merges of branches on the species phylogeny, which represent populations of different sizes, and complicates the definition and estimation of the introgression probability. We use mathematical analysis and computer simulation to examine the impact of incomplete taxon sampling on inference of gene flow and estimation of its rate using genomic data. We introduce a Bayesian testing approach to select models of gene flow for a species triplet (such as inflow, outflow, and ghost introgression), using the Savage-Dickey density ratio to calculate Bayes factors. We show that the approach has excellent power and specificity. We find that genomic data allow reliable estimation of the proportion of immigrants (rather than the number of immigrants), even when the assumed demographic model is incorrect due to incomplete taxon sampling. When population size differs among species, assuming the same size may lead to seriously biased estimates of the rate of gene flow. The f -branch approach is found to be effective in reducing the number of significant gene-flow events from triplet analyses, providing useful hypotheses for rigorous testing, but often to produce underestimates of the rate of gene flow. Our results highlight the need for improving summary methods to accommodate different population sizes and to infer gene flow between sister lineages.

genomics↗

bioRxiv2025

Pan-cancer analysis reveals that tumor microbiomes generate specific epitopes through transcriptional reprogramming

The therapeutic promise of tumor microbial peptides faces a critical safety paradox: tumors and peritumor tissues harbor compositionally similar microbiomes, yet safe immunotherapy demands tumor-specific targeting. We performed comprehensive transcriptomic analysis of microbial communities from 1,868 tumor and peritumor samples across 11 cancer types. Although 88.5% of microbial species are present in both tissue types, tumor and peritumor tissues exhibit profound transcriptional divergence: only 34.1% of microbial genes are expressed in both tissue types, and merely 18.2% of predicted HLA-binding peptides overlap. This transcriptional divergence represents microbial transcriptional reprogramming (MTR) in tumor tissues, through which microbes activate distinct genomic regions while adapting to tumor microenvironmental pressures, thereby generating tumor-specific peptide repertoires. Using Microbial Transcriptional Reprogramming Index (MiTRI) to quantify MTR, we found that higher MiTRI values correlate with expanded immunogenic peptide repertoires. Mass spectrometry-based immunopeptidomics confirmed that 25% of naturally presented microbial peptides originate from MTR regions. Crucially, in microsatellite-stable colorectal cancer, neo-adjuvant therapy responders exhibited significantly higher MiTRI values. T cell receptors (TCRs) recognized MTR-derived epitopes at 2.10-fold higher rates than genome-wide epitopes, accounting for 79.1% of clonally expanded TCRs. These findings establish MTR as the principle that ensures the tumor-specificity and safety of micorbiome-directed immunotherapy.

cancer biology↗

bioRxiv2025

MitoNGS: an online platform to analyze fish metabarcoding data in high-resolution

Environmental DNA (eDNA) metabarcoding has become a powerful tool for assessing fish biodiversity in aquatic ecosystems. However, accurate species-level identification remains challenging due to incomplete and contaminated reference databases, as well as ambiguous taxa sharing identical barcode sequences. Here, we present MitoNGS, a next-generation platform that succeeds the widely used MiFish pipeline, designed for high-resolution analysis of fish metabarcoding data. MitoNGS addresses these challenges by incorporating more comprehensive references including non-fish species and detailed annotations of heterospecific regions. Additionally, it introduces the "species group" strategy in conjunction with environmental habitat and geographic occurrence data to resolve ambiguous taxa. Furthermore, MitoNGS expands the functionalities of the legacy MiFish pipeline. It can analyze data from any mitochondrial markers and from Nanopore sequencing platforms. MitoNGS demonstrated excellent performance on our testing datasets from diverse locations, markers and sequencing platforms. MitoNGS offers a user-friendly, web-based solution for fish detection, biodiversity monitoring, conservation research, and bioresource management. MitoNGS is freely available via https://mitofish.aori.u-tokyo.ac.jp/mito-ngs.

bioinformatics↗

bioRxiv2025

Dual-LLM Adversarial Framework for Information Extraction from Research Literature

Information Extraction (IE) is a fundamental task in Natural Language Processing (NLP) that aims to automatically identify relevant information from unstructured or semi-structured data. Information extraction from lengthy research literature, particularly in multi-omics studies, faces significant challenges due to their complex narratives and extensive context. To address this, we present a novel dual-LLM adversarial framework in which one large language model (LLM) performs the extraction and another provides iterative feedback to refine the results. This process systematically reduces errors, enhances consistency across heterogeneous data sources, and converges toward more accurate outputs. We evaluated our approach against manual and single-LLM extraction, using LLMs as evaluators. Experimental results show that our adversarial framework outperforms these baselines, highlighting its effectiveness for extracting structured information from lengthy scientific texts.

bioinformatics↗

bioRxiv2025

PepCCD: A Contrastive Conditioned Diffusion Framework for Target-Specific Peptide Generation

Peptide-based drug design targeting "undruggable" proteins remains one of the most critical challenges in modern drug discovery. Conventional peptide-discovery pipelines rely on low-throughput experimental screening, which is both time-consuming and prohibitively expensive. Moreover, existing computational approaches for designing peptides against target proteins typically depend on the availability of high-quality structural information. Although recent structure-prediction tools such as AlphaFold3 have achieved break-throughs in protein modeling, their accuracy for functional interfaces remains limited. The acquisition of high-resolution structures is often expensive, time-intensive, and particularly challenging for targets with dynamic conformations, further restricting the efficient development of peptide therapeutics. Additionally, current sequence-based generative methods follow a paradigm that relies on known templates, which limits the exploration of sequence space and results in generated peptides lacking diversity and novelty. To address these limitations, we propose a contrastive conditioned diffusion framework for target-specific peptide generation, referred to as PepCCD. It employs a contrastive learning strategy between proteins and peptides to extract sequence-based conditioning representations of target proteins, which serve as precise conditions to guide a pre-trained diffusion model to generate peptide sequences with the desired target specificity. Extensive experiments on multiple benchmark target proteins demonstrate that the peptides designed by PepCCD exhibit strong binding affinity and outperform state-of-the-art methods in terms of diversity and generation efficiency.

bioinformatics↗

bioRxiv2025

Bayesian inference of introgression between sister lineages using genomic data

Inference of interspecific gene flow using genomic data is important to reliable reconstruction of species phylogenies and to our understanding of the speciation process. Gene flow is harder to detect if it involves sister lineages than nonsisters; for example, most heuristic methods based on data summaries are unable to infer gene flow between sisters. Likelihood-based methods can identify introgression between sisters but the test exhibits several nonstandard features, including boundary problems, indeterminate parameters, and multiple routes from the alternative to the null hypotheses. In the Bayesian test, those irregularities pose challenges to the use of the Savage-Dickey (S-D) density ratio to calculate the Bayes factor. Here we develop a theory for applying the S-D approach under nonstandard conditions. We show that the Bayesian test of introgression between sister lineages has low false-positive rates and high power. We discuss issues surrounding the estimation of the rate of gene flow between sister lineages, especially at very low or very high rates, and suggest that evidence for gene flow between sisters be assessed via a Bayesian test. We find that the species split time has a major impact on the information content in the data, with more information at deeper divergence. We use a genomic dataset from Sceloporus lizards to illustrate the test of gene flow between sister lineages.

evolutionary biology↗

bioRxiv2025

Parabricks: GPU Accelerated Universal Pan-Instrument Genomics Analysis Software Suite

Next-generation sequencing (NGS) has transformed genomics, enabling breakthroughs in biotechnology, healthcare, and pharmaceuticals. However, exponential data growth-outpacing Moores Law-presents critical computational challenges for secondary analysis. We introduce Parabricks, a freely accessible, GPU-accelerated software suite supporting diverse workflows, including wholegenome, exome, transcriptome, and methylation analysis. Compatible across major short read and long read sequencing platforms, it reduces processing time from hours to minutes while maintaining concordance with established standards, this acceleration translates to significant cost savings. Deployable on-premises or through cloud platforms, Parabricks ensures scalable, genomic processing. Integrated AI-driven workflows and deep learning models further enhance precision, offering a universal solution for high-throughput genomic research and clinical diagnostics.

bioinformatics↗

bioRxiv2025

Phase-separating enzyme-responsive condensates for inhalable delivery of biomacromolecules

Inhaled delivery of biomacromolecules shows extensive promise for treating a large variety of diseases, especially pulmonary and respiratory diseases. Although nanoparticle-based vehicles enhance intracellular uptake efficiency, it still remains challenging for biomacromolecules inhaled delivery to overcome cytotoxicity, cargo leakage and off-target effect. Here, we present an enzyme-responsive condensates based highly biocompatible and controllable platform for inhaled delivery of biomacromolecules. The condensates that can be modularly designed for rapid recruitment and enrichment of biomolecules, including Cas9 ribonucleoprotein (RNP) and mRNA, were internalized by cells via lysosomal-independent endocytosis, and subsequently released payloads triggered with endogenous physicochemical stimulus for controlled regulation of genes and proteins expression. Additionally, the micrometer sized condensates with highly structural and biological stability during lyophilization and nebulization enable inhalable delivery of biomacromolecules to lung. This condensate-based vehicle provides a promising platform for biomacromolecules inhaled delivery and controlled release, targeted cell regulation, and precise therapy.

bioengineering↗

bioRxiv2025

Transcriptional Condensates Encode a "Golden Mean" to Optimize Enhancer-Promoter Communication across Genomic Distances

Enhancers regulate gene expression by physically contacting their target promoters, yet these contacts often span large genomic distances. Phase-separated condensates (droplet-like clusters) of transcription factors (TFs) are thought to facilitate such long-range enhancer-promoter (E-P) communication, but the quantitative principles underlying this mechanism remain unclear. Here we use polymer-based chromatin simulations to systematically vary the strength of TF clustering and the E-P genomic distance, examining their combined effects on E-P contact formation. We find that E-P contact frequency shows a non-monotonic dependence on the degree of TF clustering: contact frequency peaks at an intermediate TF abundance and TF-TF affinity, leading to a "golden mean" optimum. Two distinct regimes emerge: under weak TF-TF attraction, contact probability increases with condensate size, whereas strong TF attraction produces a peaked response that declines at high condensation levels. These results indicate that TF condensate acts as a tunable "rheostat", buffering E-P interactions against increasing genomic distances. However, excessive TF clustering leads to molecular crowding and competition that ultimately impair E-P communication. Our study, consistent with recent experiments, establishes a mechanistic framework at molecular level, where balanced TF condensation enables robust long-range E-P communication, reconciling the stochastic nature of chromatin dynamics with the fidelity of gene regulation.

biophysics↗

bioRxiv2025

The gonococcal vaccine candidate antigen NGO1701 is a N. gonorrhoeae periplasmic copper storage protein

The increasing worldwide trend of antibiotic-resistant Neisseria gonorrhoeae strains highlights the urgent need for new therapeutic strategies against this sexually transmitted pathogen, including a gonococcal vaccine. We previously designed a bioinformatics-based candidate selection pipeline (CASS) and identified potential novel gonococcal vaccine targets among hypothetical proteins expressed during natural human infection. One of these candidates, NGO1701, is a predicted periplasmic four-helix bundle protein with amino acid sequence homology to the copper storage protein 1 (Csp1) from Methylosinus trichosporium OB3b. In this study, we confirmed that purified NGO1701 binds 15 Cu(I) ions per monomer in vitro, supporting its function as Csp in N. gonorrhoeae. Using a ngo1701 deletion mutant generated in N. gonorrhoeae F62, we investigated its role in bacteria physiology. We showed that ablation of Csp was not limiting for bacterial growth and fitness in vitro, but the {Delta}csp strain became significantly more susceptible to copper mediated toxicity. This phenotype was rescued by csp gene complementation, indicating a role in protection against copper toxicity. Our results indicate that Csp participates in periplasmic copper homeostasis in N. gonorrhoeae, buffering excess copper to reduce toxicity and playing a putative role in copper delivery to important copper-enzymes. Csp does not appear to be involved in bacterial host cell interaction and activation in vitro, since no difference in the ability of N. gonorrhoeae to adhere/invade epithelial cells or induce IL-8 secretion was reported among wild type, csp deletion mutant and complemented strains. Furthermore, sera from mice immunized with NGO1701 failed to recognize {Delta}csp by dot blot and ELISA, and the seras ability to kill N. gonorrhoeae was abrogated against {Delta}csp. However, both functions were restored after gene complementation, supporting the relevance of Csp as a potential vaccine target. Allelic analysis of Neisseria species revealed that this gene is absent in N. meningitidis, thus making it a gonococcal-specific target. Author SummaryCopper is essential for bacterial metabolism but can be toxic in excess. Here, we identify NGO1701 as a copper storage protein (Csp) in Neisseria gonorrhoeae, capable of sequestering Cu(I) ions. Deletion of csp led to increased copper sensitivity, while overexpression restored resistance, suggesting a role in copper homeostasis. The {Delta}csp mutant also showed reduced growth in cobalt and manganese, likely due to metal interference by copper toxicity. Beyond detoxification, Csp may supply copper to essential cuproenzymes like cytochrome cbb3 oxidase and nitric oxide reductase, which support bacterial survival under host-imposed stress. Although Csp is not required for N. gonorrhoeae host cell interactions, it is a strong immune target. Immune recognition of N. gonorrhoeae {Delta}csp by anti- NGO1701 mouse sera was nearly abolished and the serum bactericidal activity was abrogated compared to N. gonorrhoeae F62 wild type bacteria, highlighting Csps potential as a target for therapeutic or vaccine strategies against N. gonorrhoeae.

immunology↗

bioRxiv2025

In-phase and anti-phase dual-site beta tACS differentially influence functional connectivity and motor inhibition

Inhibitory control relies on coordinated beta-band activity within a fronto-basal ganglia network, which implements inhibition via downstream effects on (pre)motor areas. In this study, we employed dual-site transcranial alternating current stimulation (tACS) targeting the right inferior frontal gyrus (rIFG) and primary motor cortex (M1) to directly manipulate phase relationships in the beta band and assess their effects on both functional connectivity and motor inhibition. Fifty-two healthy participants received in-phase, anti-phase and sham stimulation while performing a stop-signal task. The results revealed that connectivity between rIFG and lM1 increased following in-phase but decreased after anti-phase stimulation. Although no direct modulation of task performance was observed, the greater connectivity increase between the targets during in-phase stimulation was predictive of faster inhibitory performance. In contrast, greater connectivity decreases during anti-phase stimulation were related to faster go responses, suggesting a shift towards less inhibition on the motor system. These findings provide evidence that dual-site beta-tACS can both enhance and impair inhibitory control depending on phase alignment, highlighting its potential as a non-invasive intervention for disorders marked by impaired inhibition.

neuroscience↗