Communications Biology

Fluctuations in attentional states, such as mind-wandering (MW), are associated with critical variability in task performance. While fMRI studies highlight the opposing roles of task-positive (e.g., dorsal attention network) and task-negative (e.g., default mode network) systems, the electrophysiological mechanisms underlying these dynamics remain poorly understood. Using intracranial electrocorticography in humans performing a sustained attention task, we identified global oscillatory dynamics linked to attentional shifts. MW was characterized by (i) reduced theta ({theta}) and alpha ({square}) power, (ii) decreased aperiodic signal components, indicating a shift toward cortical inhibition, (iii) enhanced phase synchronization across networks, and (iv) strengthened {theta} phase-behavior correlations ({rho}). These features support a non-network-specific framework in which low-frequency {theta} dynamics--captured by both {theta} power and {rho}--are associated with attentional fluctuations, while aperiodic offset relates to attentional state indirectly through its association with {rho} (Structural Equation Modeling: power[-&gt;]state {beta} = -0.118, p = 0.002; {rho}[-&gt;]state {beta} = 0.246, p < 0.001; offset[-&gt;]{rho} {beta} = -0.222, p < 0.001). Our study provides a unified neurophysiological framework for understanding how spontaneous neural activity can drive attentional fluctuations and performance variability, with implications for research on attention, learning, and neuropsychiatric disorders.

Simultaneous EEG-fMRI offers a powerful way to study brain dynamics, but combining the two modalities in a common whole-brain model remains challenging. Here, I developed a fusion modeling framework for resting-state simultaneous EEG-fMRI that emphasized careful multimodal alignment, construction of a stable shared feature space, and cross-validated, reproducibility-based model selection. Using 15 eyes-open resting-state runs from 12 healthy adults in an open simultaneous EEG-fMRI dataset, I constructed a no-lag, 15-TR-minimum fusion dataset comprising 3550 retained TRs and 124.25 min of usable data. A leave-one-subject-out cross-validation sweep supported a parsimonious three-state fusion hidden Markov model. In the final full-data solution, one state emerged as a dominant backbone state with the highest occupancy, strongest persistence, and clearest canonical BOLD network organization. Two lower-occupancy states behaved as transient alternatives: one appeared as a broadly attenuated version of the backbone state, whereas the other showed more selective network reweighting. The states also differed in their descriptive cross-modal BOLD-EEG structure, suggesting that electrophysiological and hemodynamic network expression may align differently across latent brain states. These results provide both a practical whole-brain EEG-fMRI fusion workflow and a biologically interpretable account of low-order resting-state brain dynamics.

Acquiring nutrients is a fundamental biological process of all organisms, playing crucial roles in ecological sustainability. Diplonemids are highly abundant heterotrophic unicellular flagellates that are widespread in the worlds ocean. They have a highly complex microtubule-based feeding apparatus (cytostome-cytopharynx complex) located adjacent to the deep flagellar pocket from which two flagella emerge from parallel basal bodies. The apical papilla is a tongue-shaped structure unique to diplonemids that connects the cytopharynx and the flagellar pocket, the latter of which is formed by reinforcing microtubules (MTR) and two flagellar roots called intermediate and dorsal roots. Here we report identification of 17 proteins that localize at the feeding apparatus or flagellar apparatus in Diplonema papillatum. Using ultrastructure expansion microscopy, we show that Mad2 and its interaction partner MBP65 localize at the MTR, intermediate root, and dorsal root. Homologs of proteins that associate with the flagellar apparatus in Trypanosoma brucei (PFR2, KMP11, BILBO1) localize at the feeding apparatus in D. papillatum. We also identify proteins that localize at the apical papilla, MTR, parallel microtubule loop, or cytopharynx. By discovering components of the feeding apparatus for the first time in diplonemids, this work forms the foundation to understand molecular mechanisms of the feeding apparatus in these highly abundant marine plankton.

We present an automated image-analysis methodology for quantitative assessment of primary cilia in cultured human primary fibroblasts. The proposed approach implements a modular processing pipeline combining deep-learning based nuclear segmentation with intensity-driven segmentation of the ciliary axoneme and basal body. These partial segmentations are integrated using a distance-based association strategy, enabling automated reconstruction of individual cilia and subsequent extraction of geometrical features. Performance was evaluated against manually segmented ground truth. While manual annotations showed a systematic underestimation of cilia length, both automated and manual analyses produced consistent population-level trends and identical statistical discrimination across sample groups. Application of the pipeline revealed a progressive reduction in cilia length and ciliation frequency with increasing passage number, demonstrating the sensitivity of the method to subtle morphological changes. The proposed framework enables scalable, reproducible, and objective quantification of primary cilia morphology and provides a computational tool applicable to high-throughput studies of cellular ageing and related phenotypes. All the code related to this work is available through GitHub: https://github.com/reyesaldasoro/Cilia.

Coat protein (CP) tertiary structures and their capsid organization of spherical viruses are highly conserved within each virus family. While AlphaFold successfully predicts the tertiary structures of individual CPs, their association to form proper quaternary assemblies cannot be easily accomplished. Here, we report a generalized methodology and associated web-based utility (https://foldavirus.org) that combines AlphaFold predictions of CPs with the knowledge on corresponding icosahedral architectures (e.g., T=1, 3, 4...) based on the known structures from the same virus family to generate associated capsids. The resulting assemblies are subjected to Amber energy minimization to relieve any steric clashes at the inter-subunit interfaces. Significantly, the capsid models are validated by calculating robust Mahalanobis distance using the residue annotations categorized as interface, core and surface amino acids with respect to those observed in the experimentally determined analogous structures. Given the amino acid sequence of CP(s), we successfully generated capsids up to T=9 icosahedral symmetry, including those of Picornaviruses that display pseudo-T=3 symmetry comprising different CPs. As the number of currently available CP sequences are 3-4 orders of magnitude larger than the experimentally determined 3D-structures, this approach bridges the huge gap that exists between the corresponding sequence and structure space.

Mesoscale neuronal networks represent an intermediate organizational level linking single-neuron activity to large-scale brain networks. Here, we used in vivo two-photon calcium imaging and graph-theoretical analysis to characterize functional network topology in the primary motor cortex across behavioral states. Motion networks exhibited the largest functional connectivity architectures, whereas anesthesia networks showed reduced network scales together with stronger modular segregation and more pronounced small-world topology. Network sign further shaped topology, with negative associations associated with reduced modularity and weakened small-world structure. Hub analyses revealed additional state-dependent differences: anesthesia networks exhibited stronger hub connectivity despite reduced neuronal activity, whereas motion networks showed higher hub activity with weaker connectivity structure. These findings demonstrate that mesoscale neuronal networks exhibit structured and state-dependent organization and provide a framework for studying cortical network dynamics in normal brain function and brain disorders.

Unlike mammals, teleost fish exhibit lifelong skeletal muscle growth, characterized by continued fiber hypertrophy and the formation of new muscle fibers maintained by a persistent progenitor cell population. However, the limited availability of stable muscle progenitor cell lines from commercially important species such as Atlantic salmon (Salmo salar) constrains mechanistic studies and emerging applications in cellular aquaculture. Here, we report the establishment and characterization of a novel embryonic-derived salmon muscle progenitor cell line, termed SsEC. These cells were derived from late embryonic stages and exhibited a spindle-shaped morphology, robust proliferative capacity, and sustained expansion beyond 30 passages under defined culture conditions. SsECs demonstrated a distinct extracellular matrix preference, with vitronectin supporting long-term maintenance and expansion. Molecular characterization confirmed stable expression of canonical myogenic markers, including myf5 and myod1, while transcriptomic profiling revealed enrichment of genes associated with muscle development and sarcomere organization relative to a non-myogenic salmon cell line. Directed differentiation to muscle, using a two-step protocol, induced efficient formation of multinucleated myotubes expressing myosin heavy chain and sarcomeric -actinin, with upregulation of key differentiation markers such as myog and Tnnt3a. Together, these findings establish SsECs as a robust in vitro model cell line for studying salmon muscle development and provide a novel platform for applications in aquaculture research and cellular seafood production.

TBCK-related encephalopathy (TBCKE) is a neurodevelopmental disorder associated with biallelic mutations in TBCK. Despite the increasing number of reported cases worldwide, the biochemical and biophysical properties of TBCK remain unclear, hindering molecular understanding of its role in disease. Here, we present the successful expression, purification, and biochemical characterization of full-length human TBCK produced in Spodoptera frugiperda cells. Biochemical and biophysical analyses reveal that the catalytically inactive pseudokinase domain of TBCK lacks nucleotide binding, consistent with the absence of the canonical VAIK, HRD, and DFG motifs required for catalysis. These findings support that TBCK is a class I pseudokinase and provide a foundation for future structural and functional studies to elucidate its biological role.

Quantifying chromatin-state dynamics in living cells remains challenging, in part because most methods require fixation or cell lysis. Here, we benchmark and introduce three simple live-cell image-derived metrics computed from routine DNA staining--the coefficient of variation (CV), 1-Gini, and the Diffuse Signal Index (DSI), introduced here--as fixation-free readouts of chromatin state. Using HL60-derived neutrophils (dHL-60) undergoing NETosis as a model system with a pronounced compact-to-decompact chromatin transition, we show that all three metrics track progressive chromatin reorganization in live-cell trajectories, but differ markedly in sensitivity: DSI provides the strongest trajectory-level discrimination between NETing and non-NETing cells, followed by 1-Gini and CV. Comparison with Tn5-based chromatin accessibility measurements in fixed cells further shows that all three metrics correlate with chromatin accessibility, supporting their biological relevance. Together, our results provide a practical framework for extracting chromatin-state readouts from routine live-cell DNA staining and identify DSI as the most discriminative metric for tracking chromatin reorganization in this benchmark.

Cryogenic correlative light and electron microscopy (cryo-CLEM) enables visualization of biological specimens with molecular specificity while preserving near-native macromolecular structure. However, the severely limited resolution of conventional cryo-fluorescence microscopes restricts the accuracy of correlation with cryo-electron microscopy. Super-resolution cryogenic CLEM (SR-cryo-CLEM) offers a potential solution, but presents substantial technical challenges, including mechanical instability and ice contamination. Here, we introduce a modular cryogenic light microscope optimized for single-molecule localization microscopy (cryo-SMLM) that mitigates such limitations. The system is constructed primarily from off-the-shelf components, enabling straightforward and cost-effective assembly, and is operated using fully open-source Python software for flexible and customizable control. The mechanically and thermally stabilized architecture, combined with an axial focus-lock system, maintains sample positioning within a standard deviation of 40 nm. Ice contamination is minimized by imaging inside a purged enclosure, enabling prolonged acquisitions. Together, the platform provides robust localization precision, reproducible imaging performance, and an accessible solution for SR-cryo-CLEM.

Amyloid-{beta} (A{beta}) accumulation is a continuous process central to pathological aging that begins decades before cognitive impairment emerges. While subthreshold A{beta} levels have been linked to future decline in cognitive control, the neural mechanisms connecting this early accumulation to its neurocognitive impact are poorly understood. Brain circuit dynamics, which are essential for cognitive function, may offer a sensitive lens into these initial pathological changes. Here, we tested whether brain state dynamics could serve as sensitive markers for cognitive impairment at an early stage of A{beta} burden. Using the Bayesian Switching Dynamic System (BSDS) model, we identified 4 distinct latent brain states from high-temporal-resolution (800 ms) fMRI data acquired from 116 older adults, including 72 cognitively normal (CN) individuals and 44 with mild cognitive impairment (MCI), during an N-back working-memory task. Adopting a dimensional approach, we examined how latent brain state dynamics relate to early amyloid burden, cognitive performance, and clinical symptoms. While A{beta} levels failed to differentiate clinical groups or predict clinical symptoms and task performance, the dynamics of latent brain states proved highly sensitive to both early A{beta} accumulation and cognition. Canonical correlation analysis revealed a significant relationship between brain state dynamics and early A{beta} burden. Furthermore, the temporal properties of brain states were significantly predictive of working memory performance in CN individuals, a relationship that was selectively disrupted in the MCI group. The features of brain dynamics can also successfully predict cognitive impairment. Our findings establish brain state dynamics as sensitive neural markers of initial A{beta} accumulation and early cognitive impairment, offering a new framework for developing predictive models to identify individuals at risk for future cognitive decline.

Macrophages/osteoclasts are highly fusogenic cells that interact closely with bone-metastatic breast cancer cells. These cancer cells adapt to bone microenvironments by undergoing osteomimicry, acquiring bone-like phenotypes. Exploration using human breast cancer-bone metastases dataset revealed that a small population of epithelial breast cancer cells express osteoclast-like and osteomimicry genes at the single-cell level. Cell fusion and cell-in-cell (CIC) processes are two uncommon yet prognostically significant mechanisms in cancer. We showed that co-culture between murine breast cancer cells and osteoclasts yielded a unique osteoclast phenotype through dynamic cell-in-cell (CIC) interactions and fusion-like behaviours between pre-osteoclasts/mature osteoclasts and breast tumor cells, resulting in osteoclast-tumor hybrid-like cells. These tumor cell interactions characterized by membrane retention and nuclear adjacency to host nuclei were consistently observed throughout osteoclast differentiation. Single-cell sequencing analysis and interpretative assays on hybrid-like cells revealed altered extracellular matrix (ECM) modification processes, immunoregulatory, and cancer-associated pathways compared to unfused osteoclasts. Tumor cells co-cultured with osteoclasts expressed hematopoietic and osteoclast-lineage factors more strongly than tumor cells cultured alone with their effects amplified under direct cell-cell contact. The presence of these hybrid-like cells was validated in human breast cancer-bone metastases. We propose that disseminated bone-tropic breast cancer cells were stimulated by osteoclasts to undergo a non-canonical, dynamic osteoclast differentiation and CIC formation to form hybrid-like cells that may facilitate bone metastatic lesions.

Palytoxin, first isolated from Palythoa toxica, is among the most potent marine toxins known. Despite decades of biochemical investigation, genetic bases underlying its potential biosynthesis in Palythoa remain unresolved. Here we present four high-quality genome assemblies of Palythoa species, including Palythoa cf. toxica, and integrate these with a chromosome-scale genome assembly of P. caribaeorum. Performing comparative genomic analyses, we screened for candidate genes potentially involved in palytoxin biosynthesis and examined patterns of genome evolution. Unexpectedly, we identified only two classes of ketosynthase (KS) domain-containing genes in Palythoa: fatty acid synthases (FAS) and bacterial-like polyketide synthases (PKSs). Contrasting other anthozoans, animal FAS-like PKS (AFPK) genes common to all Palythoa species were not detected. We found no evidence for lineage-specific expansion of PKS genes unique to Palythoa, suggesting that if palytoxin/palytoxin-like molecule biosynthesis is host-encoded, it may involve functional modification or co-opting pre-existing FAS and/or bacterial-like PKS pathways. Comparative analyses revealed expansions of gene families associated with transport and binding functions in Palythoa, potentially reflecting molecular adaptations linked to their sand-incorporating body structure. We identified TPT1 and CLEC4A as rapidly evolving genes in multiple Palythoa species, consistent with possible roles in growth regulation and host-microbe interactions. Additionally, comparison between azooxanthellate and zooxanthellate species revealed mutations within conserved protein domains of LePin, which has been implicated in cnidarian endosymbiosis, suggesting lineage-specific modifications associated with symbiotic state. This study establishes a foundation for zoantharian genomic research, provides insights into lineage-specific genomic signatures, and advances molecular and evolutionary biological knowledge of this ecologically important group.

Bidirectional interfaces combined with neural de-coding algorithms are essential for closed-loop (CL) neuromodulation, enabling simultaneous neural monitoring and responsive optogenetic stimulation. However, implementing these capabilities in compact wireless headstages for freely moving animals remains challenging, as most existing platforms rely on tethered setups and external processors to execute computationally intensive decoders. This work presents the design and optimization of a neural decoder integrated into a bidirectional wireless system for CL optogenetic experiments in rodents. The proposed platform combines 32-channel electrophysiological recording with neuromorphic feature extraction, dimensionality reduction, and a nonlinear support vector machine (NL-SVM) decoder implemented on a resource-constrained Spartan-6 FPGA. Temporal dynamics are captured using spike-count features and leaky integrators, while principal component analysis (PCA) reduces the feature space to six components, enabling sub-millisecond inference with minimal memory and power requirements. Model size is further reduced using k-means clustering during training to limit the number of support vectors. Decoder performance was validated using datasets from non-human primate and rat motor cortex recordings. The proposed decoder achieved accuracy comparable to convolutional neural networks (R2 =0.85 vs. 0.87) and outperformed Wiener filters (R2 = 0.81) while requiring significantly fewer computational resources. The full system was further demonstrated in vivo through wireless closed-loop optogenetic stimulation in rats, achieving a variance accounted for (VAF) of 0.9148. Overall, this work introduces a versatile, fully self-contained, and resource-efficient platform for real-time untethered closed-loop neuroscience experiments.

Cell-cell fusion is a fundamental biological process underlying diverse physiological and pathological phenomena, yet its quantitative analysis remains methodologically challenging due to its dynamic, heterogeneous, and multistep nature. Existing approaches to assess fusion largely rely on endpoint assays or manual scoring, limiting temporal resolution, scalability, and reproducibility. Here, we present a label-free, high-content live-cell imaging pipeline for real-time quantification of cell fusion dynamics, developed and validated using trophoblast syncytialization as a model system. The method integrates automated image acquisition with a reproducible, stepwise analysis workflow combining supervised texture-based segmentation, morphology-based measurements, and intensity-independent texture analysis. We define quantitative metrics, including the ratio of total cluster area to the number of detected clusters and cytoplasmic granularity features, that together discriminate bona fide fusion events from non-fusion-related cellular clustering or proliferation. Using canonical pharmacological inducers and inhibitors of fusion, we demonstrate the specificity and sensitivity of these parameters for detecting fusion-associated remodeling over time. We further demonstrate the scalability of the pipeline through high-throughput screening of biologically relevant growth factors, hormones, and inhibitors, enabling classification of modulators based on their independent, synergistic, or antagonistic effects on fusion dynamics. Consistent results obtained in an independent model further support its potential applications to additional fusion systems. By providing a robust, reproducible, and adaptable framework for time-resolved fusion analysis, this methodology bridges the gap between qualitative observation and quantitative kinetic assessment. Thus, the approach could be readily extended to other cell fusion systems following system-specific parameter optimization, offering a versatile platform for both mechanistic studies and discovery-driven screening applications.

Non-front-fanged snakes are abundant, diverse and represent approximately 70% of extant snakes. However, there is limited knowledge about most species and their venoms, in part due to the technical and welfare challenges associated with venom extraction, low venom yields, and the lack of cellular models available. Organoids represent an excellent opportunity to overcome these challenges. Here, we establish, for the first time, venom gland organoids from snakes of the Colubridae family and demonstrate the in vitro production of toxins.

Progressive optic neuropathies, particularly glaucoma, represent a significant global health challenge, and the need for precise understanding of the heterogeneous neurodegenerative phenotypes cannot be overstated. Here, we brought together two complementary sources of unstructured yet clinically-relevant information about neurotinal rim (NRR) thinning, a common clinical marker of such decay. These are based on a new dataset of Fundus digital images and a corresponding one of optical coherence tomography, both collected from a large clinical cohort of healthy eyes. First, we represented them using a common data structure that imposed a high-resolution scale of 180 equally-spaced and registered measurements on a 360{degrees} circular axis. We modeled such NRR data-points of each eye as circular curves, and aligned these multimodal curves to obtain a fused NRR curve for each eye. Unsupervised clustering of these fused curves identified 4 clusters of eyes with structural heterogeneity, which were also found to have distinctive clinical covariates. The computation of functional derivatives revealed the troughs in the curves of each cluster. Using circular statistics, we estimated the directional distributions of such troughs as potentially clinically-relevant regions of NRR decay. We also demonstrated that multimodal fusion leads to improvement in the robustness of baseline NRR data obtained from fundus imaging.

Circulating tumor cells (CTCs), and especially CTC-clusters, are linked to poor prognosis and may reveal mechanisms of metastasis and treatment resistance. Therefore, developing unbiased methods for the functional characterization of CTCs in liquid biopsies is an urgent need. Here, we present an evaluation of multiplex imaging mass cytometry (IMC) to analyze CTCs in mice with human xenograft tumors. In a single-step process, IMC uses metal-labeled antibodies to simultaneously detect a large number of proteins/modifications within minimally manipulated small volumes of blood from the tail vein or heart. We used breast cancer cell lines and a patient-derived xenograft (PDX) to assess antibodies for cross-species interpretation. Along with manual verification, HALO-AI-based cell segmentation was used to identify CTCs and quantify markers. Despite some limitations regarding human-specificity, this technology can be used to investigate the effect of genetic and pharmacological interventions on the properties of single and cluster CTCs in tumor-bearing mice.

Keshan disease (KD) and Kashin-Beck disease (KBD) are geographically restricted disorders in rural China with overlapping environmental and dietary risk factors. Selenium deficiency alone cannot explain their regional heterogeneity. Maize, a dietary staple in endemic areas, represents a key exposure pathway for climate-sensitive foodborne fungi and their metabolites. We profiled maize-associated fungal communities from seven villages across KD-, KBD-, KD-KBD co-endemic, and non-endemic regions using ITS sequencing and integrative bioinformatics. Fungal diversity, composition, trophic structure, and predicted biosynthetic gene cluster potential differed markedly among regions. KD-endemic areas were enriched in saprotrophic taxa such as Penicillium and Aspergillus, KBD-endemic regions favored cold- and humidity-adapted fungi, and KD-KBD co-endemic areas exhibited the highest predicted mycotoxin potential. Fungal patterns were strongly associated with regional temperature and humidity. These findings support a climate-sensitive, foodborne exposome framework, suggesting that variation in maize-associated fungi may contribute to endemic disease risk and highlighting the need for fungal surveillance in public health strategies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/716289v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@77c24borg.highwire.dtl.DTLVardef@74d158org.highwire.dtl.DTLVardef@15c15c6org.highwire.dtl.DTLVardef@99aa0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

TRPC3 is a calcium-permeable, non-selective cation channel that is activated by DAG. It is expressed in several tissues, especially in the cerebellum, and has been implicated in various human diseases. Despite recent progress in understanding the structural mechanism of TRPC3, how the channel opens remains elusive. Here, we present structures of hTRPC3 in an agonist-free resting state, determined using a DAG-binding site mutant. We also present the structure of hTRPC3 in a DAG-bound open state, determined using a constitutively active "moonwalker" (T561A) mutant. These structures, together with electrophysiological results, reveal that the T561A mutation activates hTRPC3 by disrupting a polar interaction with N652. A newly formed {pi}-bulge in S6 leads to rotation and outward tilting of the lower half of S6, resulting in dilation of the pore and thus channel opening. Agonist DAG stabilizes hTRPC3 in the open conformation. BTDM exerts its inhibitory effect by pushing S5 and S6 back to the center to close the pore, while preserving the {pi}-bulge. These results shed light on the opening mechanism of hTRPC3.