AI News Archive: August 3, 2026 — Part 18
Sourced from 500+ daily AI sources, scored by relevance.
- MyBeadPattern
Turn any image into a print-ready Perler bead pattern
- StockMind AI
Simplifique seu estoque. Potencialize seus resultados.
- Delete Customer Account
Let Shopify customers securely delete their own accounts
- crscalcu.ca
Free CRS Score Calculator for Canada Express Entry
- Worlo version 1
Intergrate Ai agents into your company in 2 minutes
- Doctor Certificate Online
Building healthcare for everyone,Tele-health, simplified.
- stark.
Minimalist React component library
- PDF Translator : Edit & Scan
PDF Translator & PDF Editor with Fill and Sign, Esign & Scan
- Nicotine Pouches
Nicotine pouches are small, tobacco-free pouches.
- Sanatan Dharam Mobile App
Sanatan Dharam — Connect With Your Spiritual Heritage
- network speed test
test ur internet speed in seconds
- Context-Harbor
Self-hosted knowledge layer for AI teams and agents
- Mane
Try before you commit!
- Subnetica
Hands-on networking labs that feel like real incidents
- London Web Studio Ltd
AI Automation Services Agency
- LeadzLander
AI landing page generator
- AI Images Studio
Create HD passport & visa photos in 3 seconds with AI
- PDF Inspector Web UI
Parse PDFs to Markdown for AI Agents, in your browser
- Roast My Website
Honest, AI-Powered Website Feedback
- CaloriVue
Track calories with your camera, not your keyboard
- Faceless Reels
Create faceless TikToks, Reels & Shorts with AI
- OrbitView
Mission control for every AI agent you run
- MiraFrame
Create polished AI images and videos from any prompt.
- Commitgraph
the most active developers on GitHub
- Compligen
cGen AI-native GxP suite by compligen
- Marquorum
Creator-powered affiliate network for AI software.
- elmentore
AI Mentorship & Senior Code Reviews for Developers
- DushanX — Signal automation with control
The Future of AI Trading Starts Here
- AI Voice Agent Singapore
Automate customer calls with AI that sounds local.
- What limits local ancestry inference at low divergence: a feasibility threshold, a metric that conceals failure, and a deficit of input more than architecture
Local ancestry inference assigns each position along an admixed chromosome to a source population, underpinning admixture mapping, ancestry-specific association testing and admixture dating. Validation is almost exclusively on continentally divergent sources (Hudson's FST {approx} 0.1) and coalescent simulations; we examine both restrictions. Across FST from 0.0022 to 0.243 we compare five methods--two likelihood baselines, RFMix, FLARE and a dilated convolutional network--on identical sites with exact ground truth, and on 11 real 1000 Genomes pairs. Three findings follow. First, a feasibility floor: at FST = 0.0022 no method exceeds 0.575, and CHB/CHS at FST = 0.00042 yields at best 0.551. Pairs motivating fine-scale analysis, such as northern versus southern Han, fall below it. Second, per-site accuracy conceals a failure of tract structure: the most accurate method per site produces 78.8x too many tracts, implying an admixture time 61.2x too old, which Viterbi decoding removes at no cost to accuracy (+0.0002). Third, the simulated lead does not survive real data, and the deficit is one of input more than of the architectures we varied: attention, state-space layers, capacity, objective and self-supervised pretraining each move accuracy by at most 0.006, while supplying the haplotype information the released tools receive recovers +0.031 on 8 of 8 pairs below FST = 0.04 and nothing above it--necessary but not sufficient, since the network still trails on 10 of 11 pairs. Two quantities usually held fixed matter more than architecture: the statistic summarising reference matching, and reference panel size, which no method is near saturating.
- The aging rhythm: spatio-temporal dynamics of resting alpha oscillations in young and older brains
Aging is associated with substantial alterations in brain oscillatory activity, particularly within the alpha band (8 -12 Hz). Yet, little is known about how aging affects the spatial propagation of alpha oscillations across cortical networks. In addition, although previous EEG studies have consistently reported age-related slowing of alpha peak frequency and changes in alpha power, the interpretation of these findings remains debated because oscillatory measures are influenced by age-related modifications in the aperiodic component of the power spectrum. Here, we investigated age-related changes in both the spectral and spatiotemporal properties of alpha activity using resting-state EEG data from a large cohort of younger (N = 326) and older adults (N = 108). To address the debate in the literature, analyses explicitly accounted for the aperiodic component of the EEG power spectrum. Consistent with previous literature, older adults exhibited a robust slowing of the individual alpha peak frequency, along with reductions in the aperiodic exponent and offset. Importantly, alpha-band power was also significantly reduced in older adults even after correcting for aperiodic activity, indicating that age-related alpha alterations cannot be fully explained by non-oscillatory spectral changes alone. Beyond conventional spectral measures, we characterized alpha-band traveling waves and identified age-related alterations in their propagation dynamics, particularly within frontal regions. Older adults showed enhanced medial-to-lateral and interhemispheric propagation patterns, suggesting reduced hemispheric segregation and increased bilateral coordination of rhythmic activity. These findings extend current models of cognitive aging by demonstrating that aging affects not only the spectral characteristics of alpha oscillations but also their large-scale spatiotemporal organization. Together, the results support the view that aging involves a functional reorganization of cortical communication dynamics, potentially reflecting compensatory mechanisms within distributed neural networks.
- Combining Machine Learning and Directed Evolution for Optimization of a Monooxygenase
L-3,4-dihydroxyphenylalanine (L-Dopa) is an important pharmaceutical for the treatment of Parkinson's disease and a precursor to numerous catechol-containing compounds. The flavin-dependent monooxygenase HpaBC is a promising biocatalyst for microbial L-Dopa production but exhibits limited native activity toward L-tyrosine. Although structure-based machine learning (ML) models have become increasingly popular for protein engineering, relatively few studies have systematically compared their performance or evaluated their integration into iterative engineering workflows. Here, we benchmarked multiple ML models for their ability to predict activity enhancing mutations in HpaBC. Experimentally validated single mutants were used to seed combinatorial design with EVOLVEpro, generating progressively improved higher-order variants. We next evaluated how expanding the EVOLVEpro training set with directed evolution derived variants influenced combinatorial predictions and finally explored an expanded sequence space by allowing combinations of both machine learning derived and directed evolution derived mutations. This workflow produced HpaBC variants with substantially improved activity. Although incorporating directed evolution data substantially altered EVOLVEpro's predicted mutational trajectories, both training strategies converged on variants with comparable activities, demonstrating that distinct regions of sequence space can yield similarly optimized enzymes. Together, these results provide a systematic comparison of zero-shot ML models and establish an iterative framework for integrating machine learning with directed evolution to accelerate enzyme engineering.
- Not all tumors age alike: Bidirectional epigenetic age shifts across 20 solid tumors
Epigenetic ageing and tumor progression have each been studied extensively using DNA methylation, yet their relationship remains poorly understood. Here we integrate DNA methylation age estimation with phyloepigenetic reconstruction across 20 solid cancer spanning 1710 samples from The Cancer Genome Atlas to assess age acceleration in tumor tissue compared to matched normal tissue. Methods: DNA methylation age was estimated for 544 patients with matched normal and tumor samples using Horvath's epigenetic clock, with linear regression used to assess correspondence to chronological age and Wilcoxon signed-rank tests evaluated whether tumor-normal age differences deviated significantly from zero. Tumor evolutionary architecture was reconstructed via UPGMA clustering of genome-wide methylation divergence into phyloepigenetic trees, from which trunk and private methylation events were classified and their chromosomal distribution compared descriptively across cancer types. Results: Applying Horvath's epigenetic clock to normal tissue yielded a mean absolute error of 17.6 years, substantially exceeding expectations. Contrary to previous reports of pronounced tumor age acceleration any ubiquitous pattern of acceleration did not emerge at the cohort level across all tumor types when tumor age was compared directly against matched normal tissue. Acceleration and deceleration instead varied often consistently by cancer types, with significant positive differences observed in endometrial, lung squamous, head and neck, and prostate cancers, and significant negative differences in renal and thyroid cancers. Phyloepigenetic reconstruction revealed that methylation events arose predominantly through private, subclonal branching rather than early clonal events. The X chromosome was found overrepresented among methylation events across nearly all solid cancers. Conclusion: Epigenetic aging in cancer is not uniform or consistently accelerated but reflects tissue-specific and often opposing patterns of change. The predominance of subclonal events suggest ongoing epigenetic diversification throughout tumor evolution, while the consistent overrepresentation of X-chromosome events indicates a distinct chromosome-level vulnerability.
- Sequence space of Xpo1-dependent NESs reveals a functional affinity ceiling
Exportin 1 (Xpo1/Crm1) exports hundreds of proteins from the nucleus to the cytoplasm. It recognizes nuclear export signals (NESs) with 4-5 hydrophobic {varphi} residues separated by spacer residues. Here we explored the sequence space of the most common NES class by a high-throughput ratiometric scoring of Xpo1-binding, combining phage display with deep sequencing. This provided a positional preference map and revealed that not only the {varphi}-positions but also spacer and flanking residues are critical for NES activity. We validated these data in vivo and with a new equilibrium affinity measurement that exploits the competition for Xpo1 when NES{middle dot}Xpo1{middle dot}RanGTP complexes partition into an FG phase. Guided by these preferences, we designed peptides that satisfy the established NES consensus but fail to confer export. Conversely, we engineered NESs that bind Xpo1 with low picomolar affinity - explained by a crystal structure. Such extreme binders, however, are no longer released from Xpo1 and block export in trans, explaining why natural NESs remain modest in affinity. Our data provide a framework for predicting, identifying, and engineering NESs and other peptide-based signals.
- Repurposing the Antiviral Agent Pibrentasvir: In Vitro Synergistic Effects in Combination with Different Azole Antifungal Agents
Objective: To investigate the combined effects of multiple drugs and provide more therapeutic options for invasive fungal infections, this study evaluated the in vitro susceptibility of Aspergillus spp., Candida auris, Cryptococcus neoformans, and Exophiala dermatitidis to pibrentasvir (PIB) in combination with itraconazole (ITR), voriconazole (VOR), posaconazole (POS), or fluconazole (FLU). Methods: According to the M27-A3 and M38-A2 guidelines established by the Clinical and Laboratory Standards Institute (CLSI), the in vitro antifungal activities of PIB combined with ITR, VOR, POS, or FLU against 78 clinical isolates, including Aspergillus spp., E. dermatitidis, C. auris, and C. neoformans, were determined. The minimum inhibitory concentrations (MICs) and fractional inhibitory concentration indices (FICIs) were calculated to evaluate the synergistic effects. Results: PIB alone exhibited no antifungal activity. Significant synergistic effects were observed when PIB was combined with azole antifungal agents.
- Spatiotemporal coordination of specialized cerebellar networks supports episodic memory in older adults
Episodic memory decline in ageing is typically attributed to the cortico hippocampal system, yet the cerebellar specific contribution via cerebellar-cerebral circuits remains underexplored. We analysed task based fMRI data from 821 older adults, including a longitudinal subset of 78 participants followed for four years. Using sparse dictionary learning on task-responsive activity, we identified three non motor networks: a bilateral lobule VI/Crus I mnemonic monitoring network, a right lobule Crus I/II default mode aligned network, and a right lobule VIIb/VIIIa evidence evaluation network. While network recruitment varied with task demands and associated with memory performance, phase specific static cerebellar cerebral functional connectivity showed stable organization but limited behavioural specificity. In contrast, dynamic functional connectivity patterns effectively distinguished memory performance groups. Crucially, greater instability in dynamic functional connectivity during encoding predicted longitudinal retrieval slowing. These findings suggest that preserved episodic memory in older adults is supported by the spatiotemporal coordination of specialized cerebellar networks with distributed cerebral networks.
- Adolescent stress recruits a latent amygdala-dopamine circuit to drive punishment-resistant reward-seeking
Adolescent stress is a lifelong risk factor for addiction, but the underlying neural circuit changes remain unknown. Here, we show that chronic unpredictable stress in adolescent mice causes a prominent increase in punishment-resistant reward-seeking - behavior tightly linked to the diagnostic criteria for addiction - establishing a model for mechanistic investigation. Using this model, we find a "gain-of-function" in reward processing wherein persistent hyperexcitability in a subset of central amygdala (CeA) neurons projecting to the substantia nigra pars lateralis (SNL) disinhibits dopamine release in the tail of the striatum (TS), newly recruiting TS to participate in punishment-resistant reward-seeking. Normalizing circuit-specific CeA hyperexcitability or optogenetically counteracting excessive TS dopamine release prevented the increase in punishment resistance. These results identify a novel circuit mediator for the lifelong effects of adolescent stress on a core feature of addictive disorders, opening a new avenue for interventions targeted to at-risk populations with specific formative experiences.
- Dorsomedial striatal dopamine ramps down during interval timing
Dopamine is involved in disorders that degrade cognition such as Parkinsons disease, ADHD, addiction, and schizophrenia; however, it is unclear how dopamine modulates brain circuits involved in cognitive processing. We investigated this problem by recording dopamine during interval timing, an elementary task that requires executive functions to estimate an interval of several seconds by making a motor response. We harnessed the fluorescent dopamine sensor dLight1.3b to record relative dopamine dynamics in the mouse dorsomedial striatum, which integrates information from cognitive cortical circuits and is required for interval timing. We found that: 1) dopamine activity ramped down during interval timing prior to increasing at reward delivery; 2) dopamine ramping dynamics predicted interval timing behavior; and 3) dopamine ramping dynamics were distinct between male and female mice and affected by amphetamine, a potent modulator of dopamine. These data provide insight into how dopamine modulates striatal circuits during interval timing and help better understand how dopamine dynamics contribute to cognitive dysfunction in dopamine-related brain diseases.
- The cerebellum supports two systems for understanding others in early childhood
The cerebellum has increasingly been implicated in Theory of Mind (ToM), a hallmark of human social cognition. Yet its role in the development of social understanding remains poorly understood, despite evidence linking early cerebellar disruptions to profound social cognitive deficits. Although explicit ToM reasoning emerges only around four years of age, preverbal infants already excel at predicting others' actions, raising the question of how the cerebellum supports social cognition early in development. Here, we investigated structural cerebellar correlates of ToM (explicit false belief understanding) and nonverbal action prediction in children aged 3-4 years, a critical developmental period during which explicit ToM emerges. Greater gray matter volume in Crus II, a core node of the adult cerebellar ToM network, was associated with better explicit ToM performance. By contrast, nonverbal action prediction was linked to distinct, non-overlapping clusters in inferior lobule VIIB and the posterior vermis, regions implicated in action observation and salience processing in adults. These cerebellar regions further exhibited dissociable patterns of covariance with cerebral networks, linking Crus II to the canonical ToM network and VIIB/vermal regions to salience-related areas. Our findings reveal neuroanatomically distinct cerebellar substrates supporting two separable components of early social cognition: one anchored to explicit mental-state reasoning and another to an earlier-emerging nonverbal action prediction system potentially grounded in the processing of salient social cues. Together, these findings identify the cerebellum as a key contributor to multiple stages of social cognitive development and suggest that distinct cerebellar systems scaffold the emergence of mature social understanding.
- Dopamine dips during unrewarded actions promote punishment-resistant reward seeking
Punishment-resistant reward-seeking, a hallmark of addiction, is less prominent in females than males. We found that chronic estradiol manipulations increased punishment resistance in female mice without increasing dopamine peaks on rewarded actions as expected, instead exaggerating dopamine dips on unrewarded actions; optogenetically mimicking these dips accelerated punishment resistance in females and males. These results suggest dopamine dips suppress learning from unrewarded actions, consistent with policy-based accounts of dopamine function.
- Coupling fibroblast mechanotransduction signaling to tissue growth in a multiscale model of skin expansion
Skin growth and remodeling underlies health, disease, and treatments such as tissue expansion (TE). The mechanotransduction pathways in dermal fibroblasts are increasingly well characterized, and tissue-level growth has been described phenomenologically, but coupling between cell-level signaling and tissue-level growth remains poorly understood. We develop a dermal fibroblast signaling network through extensive literature data curation, comprising 151 reactions among 96 nodes. The inputs are mechanical stretch and eight ligands (TGFbeta, PDGF, FGF, IL1, IL6, TNFalpha, AngII, ET1); outputs of interest span ECM-enzymes (proMMP1/2/9, MMP1/2/9), ECM proteins (CImRNA, collagen I, fibronectin), and fibroblast activity (alphaSMA, proliferation). Implemented as a logic-based ODE system, the network reproduces 82% of the calibration dataset and agrees with independent validation data. Sensitivity analysis reveals a tension-dependent regulation of signaling: at baseline tension, outputs are governed by many boosters (nodes that positively influence downstream targets) and one dominant brake, LATS1/2, whereas at high tension control consolidates and new, tension-specific regulators such as integrin (ITGB1) emerge. Multiple pathway axes converge on a few central regulators, producing pronounced crosstalk, most notably between TGFbeta and mechanical tension. Finally, linking the collagen outputs to a tissue-level growth formulation yields a bidirectional mechanical-biochemical coupling that reproduces tension-induced skin growth measured in a porcine TE model. This framework establishes a comprehensively calibrated dermal fibroblast signaling network coupled to tissue-level growth, opening opportunities for targeted TE interventions.
- A minimal physical model of adhesion-dependent protrusion explains confined haptotaxis and oscillatory cell migration
Haptotaxis is the directed migration of cells along gradients of substrate adhesion, and is an important guidance mechanism in biology. Recent experiments on fibronectin patterned tracks show that cells typically migrate toward higher adhesion, then oscillate around the adhesion maximum, with substantial variability in speed and cell length. To explain these cellular shape and migration dynamics we present a minimal model for confined haptotaxis, built around one key physical ingredient: local adhesion strength directly enhances the recruitment of protrusive actin polymerization activity at the cell edge. This coupling creates a front rear difference in protrusive activity, biasing the cell towards polarization in the direction of the higher adhesion. Quantitative comparison with experiment shows strong agreement at multiple levels: cell population level directionality statistics and position-dependent changes in cell length and velocity. At the single cell level, the model reproduces the full diversity of experimentally observed trajectories, including haptotactic bias and its dependence on adhesion-gradient strength, initial position, length and speed variations, myosin II inhibition, and migration on inverted adhesion gradients. Variability in experimental trajectories and migration speed is explained by differences in intrinsic actin polymerization activity and stochastic fluctuations, accounting for the full spectrum of observed migration patterns. Together, our results identify adhesion-dependent amplification of protrusive activity as a minimal and sufficient physical mechanism for understanding haptotaxis.
- Oxidative inhibition of PTEN links ROS signaling to regeneration and homeostasis
Reactive oxygen species (ROS) are early signals of tissue damage, but how they engage growth-promoting pathways in vivo is unclear. Here we show that ROS promote regeneration by inhibiting PTEN, thereby activating PI3K-Akt signaling in Drosophila melanogaster. We identify cysteine 79 as an essential residue for redox regulation of PTEN, demonstrating that a ROS-insensitive PTEN mutant uncouples Akt activation from oxidative stress. This disruption impairs regenerative growth in wing imaginal epithelia and stem cell proliferation in the adult gut. Mechanistically, Akt activation links ROS signaling to p38 MAPK-dependent regeneration responses. Together, our findings define a conserved ROS-PTEN-Akt signaling axis that integrates oxidative damage with regenerative growth, establishing PTEN as a key redox-sensitive regulator of tissue repair.
- Transcriptome-Inspired Spiking Simulations Uncover Human-Specific Prefrontal Dynamics and Provide a Mechanistic Platform for Species-Appropriate Disease Modeling.
Whole-brain transcriptomic atlases are now widely available, yet computational neural models are almost exclusively parameterized from rodent data and used to infer human brain function, an extrapolation whose cost remains unquantified. To address this, we constructed a biophysically detailed, conductance-based Hodgkin-Huxley spiking microcircuit of a five-population prefrontal network, where every ion-channel, receptor, and gap-junction conductance was scaled by cell-type-specific gene expression. We parameterized the identical circuit using single-nucleus RNA-seq from mouse mPFC and human DLPFC, alongside a literature-derived baseline, and compared their high-frequency-oscillation (HFO) outputs across seven physiological and pathological states. While population firing rates differed only modestly between the two refinements (~20% for pyramidal and PV cells), the oscillatory dynamics diverged dramatically. The human-refined circuit generated strongly synchronized PV activity and robust ripple- and fast-ripple-band power (e.g., healthy-wake ripple power, in arbitrary units: 322 vs. 24 and 22), whereas the mouse-refined and literature arms remained asynchronous (interneuron synchrony: 0.21 vs. 0.02). This human >> mouse ~ original hierarchy was statistically consistent across all seven states (significant arm differences in 75/77 comparisons). Mechanistically, the human transcriptome drove markedly stronger PV-PV electrical coupling (gap-junction scale: 1.78 vs. 0.96) paired with stronger recurrent pyramidal excitation, which collectively synchronized the fast-spiking PV population into a coherent rhythm that perisomatic inhibition then imposed on the local field potential. Critically, these results are model-dependent; the gene-to-conductance mapping is phenomenological, and mRNA expression does not linearly translate to functional conductance. Nonetheless, under this mapping the divergence localizes PV-mediated coupling and excitation-inhibition balance as the parameters most in need of human-specific recalibration. More broadly, this work establishes transcriptome-informed spiking simulation as a powerful strategy for uncovering species-specific computational principles and for building mechanistically grounded, human-relevant models of prefrontal circuit dysfunction, an approach that moves beyond generic rodent defaults to enable targeted, species-appropriate modeling of neurological and psychiatric disorders.
- A single-cell and multi-platform spatial atlas of the human pancreas resolves a transformation-associated epithelial axis and a recurrent boundary-organized tumour microenvironment
Most pancreatic ductal adenocarcinoma (PDAC) single-cell and spatial studies analyze one cohort or platform, obscuring recurrent biology. We assembled a human pancreas single-cell and single-nucleus reference of 1,186,130 cells from 19 studies and interpreted 176 Visium sections comprising 458,877 spots across non-diseased pancreas, chronic pancreatitis, PanIN, IPMN, primary PDAC and metastasis. Marker-supported labels were used after two RNA-based copy-number callers failed known-diploid controls. BANKSY domains, two reference-mapping methods and sample-level analyses resolved a cross-sectional epithelial axis extending from acinar-rich to malignant tissue. Five trajectory algorithms recovered similar ordering on a shared embedding; their consensus was interpreted as transformation-associated, not temporal or clonal. Malignant regions were globally segregated from fibroblast and myeloid compartments. Signed-distance analysis refined this pattern into a malignant core, a CAF/myeloid surround beginning at the tumour boundary and a more distal lymphoid compartment. Candidate extracellular-matrix communication, led by COLLAGEN, LAMININ and FN1, concentrated at the interface. Changes were reproduced in six patient-matched Normal-tumour pairs using exact patient-level tests. Visium HD resolved the same organization at single-cell resolution and showed that 8-um bins distorted immune-adjacency estimates. Xenium also revealed recurrent neighbourhoods but sample-specific stromal boundaries. We provide a confound-aware framework for identifying recurrent epithelial and microenvironmental organization in PDAC.
- Tumor-specific Kinase Motif Enrichment Analysis Identifies Personalized Therapeutic Cancer Targets
Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are an uncommon and poorly understood malignancy with low mutational burden, lacking well-defined oncogenic drivers. GEP-NET mortality frequently results from extensive hepatic metastases. Accordingly, we interrogated phosphoproteomic data from GEP-NET liver metastases and patient-matched uninvolved liver to identify tumor-specific signaling and targetable tumor vulnerabilities using Kinase Motif Enrichment Analysis (KMEA), a new tool leveraging the recent Kinase Library compendium of the substrate motif specificity for nearly the entire human kinome. KMEA identified patient tumor-specific upregulation of mTOR or casein kinase 2 (CK2) activity that would be undiscoverable by standard personalized genomic and transcriptomic approaches. Striking concordance was observed between KMEA predictions for specific tumors, and their sensitivity to inhibitors of mTOR or CK2 using patient tumor-derived organoids. These findings reveal potential clinically-actionable protein kinases hyperactivated in GEP-NETs, and more broadly indicate a general method for personalized cancer treatment using phosphoproteomics and KMEA-derived kinase activity signatures.
- Fluorescence polarization-based fragment screen identifies inhibitors of APOBEC3A and APOBEC3B
APOBEC3A and APOBEC3B are antiviral cytidine deaminases found to drive cancer-associated mutagenesis, contributing to tumor evolution and therapeutic resistance across multiple cancer types. Inhibiting these enzymes holds promise for prolonging response to a wide range of cancer therapies by delaying development of resistance. However, APOBEC3A and APOBEC3B remain challenging drug targets, with no potent and selective small molecule inhibitors reported. Here, we use a fluorescence polarization-based assay to identify small molecules inhibitors of the APOBEC3A-single-stranded DNA interaction. From a library of 2,400 disulfide compounds, we identified 64 hits (mean polarization +/- 3 sigma, hit rate of 2.7%). Intact protein mass spectrometry revealed that a subset of compounds covalently engages A3A at cysteine 64, including Compounds 1 and 2. Compounds 1 and 2 disrupt APOBEC3A/APOBEC3B-single-stranded DNA interactions and inhibit APOBEC3A/APOBEC3B deaminase activity in a dose-dependent manner, with micromolar IC50. Surprisingly, inhibition of APOBEC3A/APOBEC3B by Compounds 1 and 2 is independent of covalent tethering to cysteine, suggesting a predominantly non-covalent mode of binding. Together, these studies establish an integrated workflow for APOBEC ligand discovery and identify Compounds 1 and 2 as starting points for developing chemical probes to investigate APOBEC-driven mutagenesis and therapeutic resistance.
- Depth-Dependent Advantages of Three-Photon Microscopy for Imaging Through Intact Murine Cortical Bone and Into the Marrow
Bone adapts to its mechanical and physiological environment through the coordinated actions of osteocytes and marrow-resident cell populations. Because these processes depend on complex interactions within native tissue microenvironments, intravital imaging offers a unique opportunity to reveal cellular behaviors that cannot be fully captured ex vivo. However, the highly scattering nature of mineralized bone limits imaging depth and direct observation of cells within intact tissue. Two-photon (2P) microscopy has enabled important advances in bone biology, while three-photon (3P) microscopy has been proven to extend imaging depth and image quality in skeletal tissues. Here, we directly compared the performance of 2P and 3P microscopy in ex vivo mouse long bones by quantifying laser attenuation, signal-to-noise ratio, signal-to-background ratio, and spatial resolution, as well as assessed the impact of wavefront correction. We found that 2P and 3P microscopy generated comparable image quality through approximately 50m of cortical bone. Beyond this depth, however, 3P microscopy provided superior brightness, contrast, and resolution, enabling improved visualization of structures deep within the cortex and at the cortical-marrow interface. To assess compatibility with intravital imaging, we evaluated endogenous markers of cellular stress during 3P imaging. Although prolonged continuous imaging decreased osteocyte spontaneous calcium signaling magnitude and increased autofluorescence, short intermittent imaging bouts produced negligible evidence of cellular damage compared to controls. Leveraging the enhanced penetration depth of 3P microscopy, we further show visualization of immune cell migration within the marrow cavity through intact cortical bone in both the third metatarsal (MT3) and tibia. Together, these findings affirm 3P microscopy as a powerful tool for studying cellular dynamics in living bone. By extending imaging beyond superficial cortical regions and enabling direct visualization of marrow-resident cells through intact bone, 3P microscopy expands opportunities to investigate osteocyte biology, marrow niche function, and skeletal adaptation in vivo.
- Perceptual sensitivity supports online control, while perceptual errors drive motor memory formation during locomotor adaptation
To maintain stable locomotion, the nervous system must continually adapt, whether reacting to an unexpected perturbation, such as a trip on uneven terrain, or anticipating external demands, such as walking on snow, by forming and updating motor memories. Error-based learning is the dominant computational account of such adaptation, in which motor commands are updated to reduce prediction errors, that is, the mismatch between predicted and actual limb state. Yet this framework was largely defined in reduced, single-effector paradigms, where the sensory consequences of movement are isolated and the prediction error is directly observable. Whether the same principle governs whole-body, multi-segmental, multi-sensory behaviors such as walking has remained untested, owing in part to the challenge of identifying a behavioral proxy for prediction errors in this complex, dynamic setting. Here, we combined a split-belt treadmill paradigm with a novel method for quantifying perception of leg motion to address this open question. We found two perceptual contributions to locomotor adaptation: perceptual sensitivity predicted initial motor corrections during early adaptation, whereas perceptual errors (i.e., the mismatch between perceived and observed leg speed) predicted the magnitude of motor aftereffects during post-adaptation. Together, these findings demonstrate that locomotor adaptation is fundamentally constrained by perception of limb motion. Our results identify perceived limb motion as a behavioral proxy for prediction errors, establishing error-based learning, long characterized in reduced tasks, as a core computational principle underlying human locomotion.
- The structure of the Salmonella phage epsilon15 tailspike reveals multiple O-antigen binding sites and a protruding esterase domain
Many bacteriophages use tailspikes to degrade host bacterial polysaccharides, facilitating access to the outer membrane. The homotrimeric tail spikes of the Salmonella phage epsilon15 feature a slender phage-binding domain, a kink, and a barrel-shaped section with three petal-like protrusions. Here, we present the crystal structures of the monomeric protruding petal domain alone and of the trimeric barrel-shaped section with three petal domains. The barrel-shaped section includes a trimeric beta-helix, typical of phage tail spikes, alongside a trimeric beta-sandwich domain. The petal domain exhibits a fold characteristic of the serine-glycine-asparagine-histidine (SGNH) esterase family. Co-crystallisation with O-antigen fragments identified four binding sites on the tailspike: two adjacent sites on the surface of the triple beta-helix, one in the beta-sandwich domain and a fourth near the petal esterase site. These binding sites align with the expected orientation of the phage just before DNA transfer. Nuclear magnetic resonance spectroscopy and site-directed mutagenesis revealed an endorhamnosidase activity, showed that the reaction mechanism proceeds by inversion of the configuration and revealed that the active site is located at the junction of the two beta-helix binding sites. Analogous experiments also revealed an esterase site in the petal domain. Together, the structural and functional insights suggest a dual role for the phage epsilon15 tailspike: de-acetylation of the O-antigen, potentially affecting the local structure and lipopolysaccharide flexibility, plus cleavage of the O-antigen, enabling the phage to approach the bacterial membrane.