AI News Archive: August 20, 2026 — Part 12

Sourced from 500+ daily AI sources, scored by relevance.

• Enhancing Privacy in Federated Learning via Dual Obfuscation of Gradients and Training Images

  Federated learning enables collaborative model training while keeping data locally at each client; however, recent studies have shown that training data can be reconstructed from shared model updates. To address this issue, this paper proposes a dual obfuscation method that enhances robustness again...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19650v1
• AEGIS: Attention-Embedding Gradient Isolation Shield - Triple-Channel Gradient Masking for Privacy-Preserving Federated LLM Fine-Tuning

  Gradient inversion attacks recover private training text from gradients shared in federated learning, posing a serious threat to collaborative model training. Through our analysis of transformer gradient structure, we identify three channels through which private token information leaks: the attenti...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19534v1
• Inadvertent Context Leakage in Language Models

  For AI agents to be useful beyond simple chat, they must hold sensitive user context such as calendars, credentials, health records, and financial data. We study whether the mere presence of such secrets in a model's context window introduces hidden correlations into the model's benign outputs, allo...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19857v1
• TGL-APT: Temporal Graph Learning with Graph Distillation for Efficient APT Investigation

  Advanced Persistent Threat (APT) attacks pose a critical challenge to modern systems, as their stealthy, multi-stage nature renders conventional detection methods ineffective. While provenance graphs provide rich behavioral context for attack investigation, attack-relevant evidence is often sparse a...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19750v1
• BreakGuard: Towards Detecting Dependency Breaking Changes with LLM-Generated Tests

  Open-source libraries play an important role in software development by providing reusable features that expedite the development process. As libraries evolve, they release new versions that add features, fix bugs, or apply security patches. In this process, they may break the contract established w...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.20167v1
• Repo0: Design-Driven Zero-to-All Code Generation

  Large language model agents have made substantial progress in code generation, yet most existing systems assume a predefined repository architecture. This assumption does not hold in zero-to-all code generation, where an agent must construct an entire software project directly from natural-language ...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19854v1
• PRAXIS: Graph-Grounded Tacit Knowledge for Domain Code Generation

  LLM agents have achieved strong performance on general software engineering tasks, yet struggle with domain-specific code generation. We identify the root cause as the agent's lack of tacit knowledge, including domain-specific business rules, interface contracts, and operational conventions that dev...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19784v1
• Auditing and Decomposing Feedback-Driven Evolution in LLM Test Generation under the Oracle Problem

  Execution feedback is often treated as a self-verifying signal for improving LLM-generated tests. However, when generated inputs are executed on a single accepted program and its outputs are used as ground truth, invalid or underspecified inputs can create spurious fault detections and apparent evol...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19626v1
• Training-Free LLM-Based Recommendation with Post-LLM Item Refinement Using Collaborative Signals

  Large language models (LLMs) have shown promise for training-free recommendation, but LLM-generated user interests are often too broad for fine-grained item retrieval. Existing methods incorporate collaborative filtering (CF) signals in a pre-LLM manner through candidate reranking or prompt augmenta...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19665v1
• SSR-GRPO: Integrating Supervision and Semantic IDs into Reinforcement Learning for Dense Retrieval in E-commerce

  Embedding-based retrieval (EBR) is pivotal in e-commerce search but often struggles with complex semantics. While recent methods often fine-tune large language models (LLMs) for representation learning, they typically lack robust mechanisms for handling complex and implicit semantics. While Retrieva...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19595v1
• From Retrieved Context to Runtime Control: Adaptive Compression for Edge-based RAG

  Retrieval-augmented generation (RAG) improves language-model responses by grounding generation in external passages, which comes with overhead: retrieved context lengthens the prompt, increasing prefill work, KV-cache footprint, memory traffic, latency, and energy. Context compression offers a natur...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19535v1
• Automated Summarization of Financial News Using Large Language Models and Retrieval-Augmented Generation: An Early Empirical Study (Fall 2023)

  Stock market analysts and investors face a daily challenge: too much financial news, too little time. Manually reading and synthesizing hundreds of company-specific articles is impractical, yet missing key information can directly affect investment decisions. This project, conducted at George Washin...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19526v1
• Projecting BrowseComp-Plus onto ClimbMix: Toward More Realistic Corpora for Agentic Search

  The BrowseComp-Plus benchmark disentangled the evaluation of agentic search by replacing opaque web search with a fixed corpus, so that an agent's role can be separated from the retriever's. That corpus, however, holds only about 100K documents and was assembled from the supporting documents of the ...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.20317v1
• Do Sequential Recommendation Benchmarks Really Require Higher-Order Sequence Modelling?

  Sequential recommenders increasingly use language-model architectures designed to capture complex, context-dependent interactions. Yet it remains unclear whether widely used benchmarks actually require this modelling capacity. We investigate this question using two simple, recency-weighted pairwise ...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19833v1
• Two-sided receptivity to conversational AI agents in online dating: Bilingual survey data from Fledge.Love

  Autonomous conversational agents and generative-AI features are being added to online dating platforms faster than public evidence about user attitudes can accumulate, and the scarcest evidence concerns the receiving side: how people react when the profiles, messages, or conversation partners they e...

  📄 ResearchAug 20, 2026http://arxiv.org/abs/2608.19545v1
• Cortical encoding of probabilistic temporal predictions during speech perception

  The temporal structure of speech has traditionally been characterized by the rhythmicity of its canonical linguistic units (phonemes, syllables, words), each summarized by a mean occurrence rate. While valid, this view overlooks whether speech carries a finer, context-dependent and probabilistic temporal structure that could support temporal predictive coding during listening. Using large French and English speech corpora, we trained models of increasing complexity to predict the onsets of linguistic units. Recurrent neural networks (RNNs) outperform mean-rate and hazard-rate models, showing that the variability around these rates is not noise but a temporal structure shaped by local context, statistically predictable across phonemes, syllables and words. Recording from 7,698 intracerebral electrodes in 53 neurosurgical patients listening to natural speech, we next show that the models' output), the continuous probability of an upcoming onset (when), explains neural activity beyond acoustic and linguistic content (what) features, with markedly stronger effects for RNNs than for mean- or hazard-rate models. This dynamic neural prediction of when an onset will occur is dissociable from the encoding of linguistic content, relying on largely distinct channel populations. Temporal predictions engage a distributed cortical network extending from bilateral temporal cortex into left frontal and sensorimotor regions. Together, these results establish temporal prediction in speech as a dynamic, context-dependent and probabilistic process in its own right.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.16.745095v1?rss=1
• Single-Molecule Proteomics via a Dynamic Translocase and Physics-Informed Machine Learning

  Single-molecule protein sequencing promises to democratize clinical proteomics, but platforms retrofitting static DNA-sequencing nanopores face a fundamental biophysical bottleneck: they only measure one-dimensional excluded volume. Consequently, these static calipers struggle to resolve isobaric residues, requiring complex DNA-handle chemistries and target concentrations that exceed clinically relevant abundance ranges. Here, we introduce a dynamical, target-docking translocase engine--the anthrax toxin protective antigen (PA)--as a label-free single-molecule peptide sensor. By extracting the multi-state thermodynamic friction generated as the pore's active site dynamically "breathes" around translocating analytes, we trained a physics-informed machine learning (PIML) architecture to classify a 20-member guest-host peptide library panel representing all 20 canonical amino acids at the single-event level. Operating at low nanomolar concentrations under a 35-millisecond thermodynamic read constraint, the translocase resolved isobaric variants (leucine and isoleucine). Furthermore, we achieved 98.02 (+/-0.05)% classification accuracy on a panel of five un-tagged, native clinical biomarkers (e.g., KRAS G12D, angiotensin, bradykinin). Transitioning from static volumetric measurement to time-domain thermodynamic fingerprinting establishes the requisite protein nanopore hardware for de novo proteomics.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.17.745284v1?rss=1
• PandaDock: An Open-Source Molecular Docking Platform with Flexible-Ligand Search and Equivariant Neural Scoring

  We present PandaDock, an open-source molecular docking platform implementing flexible-ligand conformational search with analytic gradients, a precomputed affinity grid engine, specialized modules for induced-fit, metal-coordination and tethered docking, and an SE(3)-equivariant graph neural network scoring function trained at scale. Ligand flexibility is represented as a torsion tree and pose parameters are optimized by Monte Carlo with Metropolis acceptance refined by L-BFGS, with rotational gradients obtained in closed form through the derivative of the SO(3) exponential map rather than by finite differences. Affinity grids are built by a blocked neighbor-selection scheme that is exact and 5.6-9.7x faster than dense evaluation, and may be cached across ligands sharing a receptor and site, reducing a six-ligand series from 29.3 s to 10.4 s. On 814 protein-ligand complexes spanning 14 target families, PandaDock recovers a pose within 2 Angstroms of the crystal geometry in 33.7% of cases at rank 1 and in 57.0% of cases within the returned ensemble. The GNN scoring function is trained on 741,706 co-folded complexes from SAIR under target-disjoint splits, reaching a Pearson r of 0.407 on 90,219 held-out complexes and transferring to 202 independent crystal structures with measured Ki, Kd, IC50 or EC50 at r = 0.467. We report the model against three controls, a target-mean predictor, a ligand-descriptor-only baseline, and within-target correlations, and document both where it performs and where it does not, including its unsuitability for pose rescoring. On an independent 30-compound series against a single GABAA receptor target, PandaDock's empirical scoring function ranks 8th of 25 methods evaluated, ahead of every AutoDock Vina and Vinardo configuration tested, while the GNN scores below Vina, consistent with the within-target ceiling identified on SAIR. At full scale on the PDBbind v2020 refined set (n = 4,640, native crystal poses), the fully independent SAIR model reaches r = 0.531, and a dedicated model trained on PDBbind alone under a target-disjoint split reaches r = 0.690 on its own held-out test complexes, the strongest evidence in this work that PandaDock's affinity predictions generalize. PandaDock is distributed under an open-source license at https://github.com/pritampanda15/PandaDock with a complete command-line interface and a reproducible benchmarking harness.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.19.745667v1?rss=1
• GlycoMeSH: linking glycan structures to biomedical context for systematic enrichment analysis

  Glycan identification has advanced, but glycan structures remain difficult to translate into reproducible biomedical context because reusable glycan-level annotations are sparse. We present GlycoMeSH, a resource that links glycans to Medical Subject Headings (MeSH) through an inference model, a traceable association database and a glycan-set enrichment workflow. GlycoMeSH-BERT recovered ~60% of literature-derived associations at recall@30 and expanded open-vocabulary MeSH coverage beyond closed-label baselines, without higher per-prediction accuracy. At matched candidate counts, its predictions showed motif-level semantic agreement comparable to those baselines, independently of the training labels. GlycoMeSH-DB contains 789,627 associations between 26,954 glycans and 20,302 MeSH terms. GlycoMeSH-EA returned enriched MeSH terms for glycan sets from glycomics and glycoproteomics datasets. Each association represents a biomedical context rather than a validated mechanism, and retains its source PMID or prediction score for audit. GlycoMeSH supplies the missing, evidence-traceable annotation layer that makes glycan sets directly analyzable by enrichment across glycoscience datasets.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.18.745318v1?rss=1
• Why they move: breeding-site availability drives partial migration in a large terrestrial reptile

  1. Migration is a widespread phenomenon across taxa, yet the ecological mechanisms underlying its evolution and maintenance, particularly whether migratory behaviors are primarily driven by access to spatially restricted breeding sites or by seasonal tracking of trophic resources, remain poorly documented outside birds and large mammals. Despite increasing evidence that reptiles perform seasonal migrations, the ecological mechanisms underlying these movements have rarely been formally tested. 2. The critically endangered Galapagos pink land iguana (Conolophus marthae), endemic to Wolf Volcano, Isabela Island, exhibits partial migration along a steep altitudinal gradient, providing an opportunity to disentangle the relative roles of breeding-site availability, trophic resource dynamics, and thermoregulatory conditions as drivers of migration. 3. We used GPS tracking data from 22 individuals (7 males, 15 females) monitored between 2019 and 2023, combined with high-resolution spatio-temporal models of vegetation productivity and air temperature across the species' altitudinal range, to characterize population-level movement patterns and evaluate competing hypotheses explaining the evolution of this migratory behavior. 4. Movement models revealed a clear pattern of partial migration: 16 out of 22 tracked individuals performed seasonal altitudinal movements between a restricted high-elevation mating area and a larger dispersal area at lower elevation, with males reaching the mating area approximately 48 days earlier than females. The dispersal area remained consistently more productive than the mating area throughout the year, rejecting the prediction that individuals should track the shifting trophic resource peaks. Instead, the mating season coincided with the local productivity peak within the mating area, whereas temperature differences between areas were small (ca. 2{degrees}C) and did not explain migration timing. 5. These results support a site-dependent hypothesis of partial migration over a resource-tracking hypothesis, indicating that access to spatially restricted breeding sites is the primary driver of migration in this species, with local trophic resource dynamics fine-tuning reproductive timing. Providing empirical evidence for the ecological mechanisms underlying migration in a large terrestrial reptile, our results extend site-dependent theories of migration beyond birds and mammals and identify breeding-site availability as a key ecological driver of migratory behaviors across taxa.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.20.745942v1?rss=1
• Mechanistic Dissection of Entropic Penalty upon Ligand Binding and Molecular Flexibility via Molecular Dynamics Simulations and Machine Learning

  Molecular flexibility governs how molecules behave, reorganize, and respond to their environment. Although experiments measure molar entropy for small molecules and molecular dynamics (MD) simulations capture molecular motions, quantifying configuration entropy and the concerted internal motions such as torsion rotations, angle bending, and their couplings are central to understanding thermodynamic behavior but remains challenging. To dissect these contributions, we used MD trajectories and developed an internal coordinate PC-entropy (iPC-entropy) method to probe the origins of entropy and reveal how specific motions shape the thermodynamic landscape. The studies accurately captured molar entropy, identified key torsional motions as major contributors, and uncovered a critical angle-torsion coupling in which angle bending was strongly correlated with torsional rotation, a coupling that increases nonlinearly with molecular size. Evaluating entropic changes upon protein-ligand binding reveals that dominant entropic penalty arises from ligand dihedral rigidification rather than protein reorganization and highlights the specific dihedral rotations that become restricted. We also suggest systematic corrections for approaches considering solely rotamers to reliably reproduce the relative entropic penalty in computer-aided drug discovery. Together, our findings elucidate the molecular origins of entropy and entropy changes. In addition, we can quantify and illustrate the internal motions that strongly shape binding thermodynamics, thereby offering mechanistic insights to guide drug development.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.18.745526v1?rss=1
• Mapping the sequence preference of the generalist class II lanthipeptide synthetase ProcM by mRNA display

  The biosynthetic machineries of ribosomally synthesized and post-translationally modified peptides (RiPPs) are often substrate tolerant. A remarkable example is the class II lanthipeptide synthetase ProcM, which naturally functions as a generalist enzyme that has not evolved to use a specific substrate during its evolutionary history. Although ProcM has been studied extensively, the sequence features associated with productive modification remain underexplored. In this study, we use the ultrahigh-throughput mRNA display technique to map the sequence compatibility of ProcM across a focused library. This approach expands the landscape of ProcM reactivity beyond native substrates and individually characterized variants. Machine learning (ML) is used as a tool to demonstrate that the selected dataset contains learnable signatures and classification architectures revealed a balanced accuracy of 0.73. This performance contrasts sharply with the near-perfect accuracy of specialized enzyme models as the sequence-fitness landscape of the generalist enzymes are characterized by class imbalance and limited by intrinsic dataset features. Our results provide a high-throughput view of ProcM reactivity and highlight differences with previous high-throughput studies on substrate selectivity of RiPP modification enzymes. Future studies will need to assess whether these differences are common when comparing generalist with specialist enzymes.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.19.745792v1?rss=1
• Feline calicivirus encoding NanoLuc luciferase as a tool for assessing antibody neutralisation and antivirals

  Feline calicivirus (FCV) is among the most common viruses to infect cats worldwide, with prevalence estimated to range from 10-90% depending on the population sampled. Typical FCV infection presents with oral ulcerations, fever and in some cases can also lead to clinical signs such as pneumonia or "limping syndrome". However, some FCV strains have been isolated from cats exhibiting virulent systemic (VS) disease, which is associated with high morbidity and mortality. Breakthrough VS-FCV infections have been recorded in vaccinated cats and, therefore, there is considerable interest in developing novel therapeutics for use in the face of VS-FCV outbreaks. However, to design effective therapeutics, a tractable system to systematically assess the efficacy of novel vaccine candidates or antivirals is required. Here, we used reverse genetics to develop an FCV reporter virus, inserting NanoLuc luciferase into the LC protein of FCV-Urbana (FCV-UrbanaNL). We characterised the replication kinetics of FCV-UrbanaNL in comparison to its parent virus and assessed the stability of the reporter over multiple passages. Subsequently, we developed virus neutralisation assays to assess a range of monoclonal antibodies that recognise FCV Urbana. We then assessed the breadth of neutralisation by exchanging the major capsid protein, VP1, of FCV Urbana with VP1 from the vaccine strain F9 and the VS-FCV strain NSW-E1. Finally, we evaluated the utility of the FCVNL reporter system to screen candidate antiviral compounds, identifying GS-441524 (the active metabolite of the parent nucleoside remdesivir) as having therapeutic potential against FCV. These findings highlight the potential of this reporter virus as a powerful molecular tool to accelerate the discovery and development of novel therapeutics.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.20.745972v1?rss=1
• Disruptions in glucose and amyloid-beta transport in mouse models manifesting metabolic syndrome

  Studies in humans and murine models have pointed towards a possible link between metabolic syndrome, which shows insulin resistance and metabolic dysregulation, and Alzheimer's disease (AD) pathology marked by amyloid-beta (A{beta}) accumulation and hypometabolism in the brain. Yet, the underlying biological mechanisms by which metabolic syndrome affects these pathological changes in AD brain remain unknown. We hypothesized that insulin resistance is responsible for alterations in blood-brain barrier (BBB) transport of A{beta} peptides and glucose. This hypothesis was tested by employing radiolabeled ligands (125I-A{beta}40, 125I-A{beta}42, and 18F-FDG) in high-fat diet (HFD)-fed mouse models that manifest metabolic syndrome. Further, we assessed alterations in the expression of various molecular mediators within the brain microcapillaries harvested from both low-fat diet (LFD)-fed and HFD-fed mice. Our findings show that HFD-fed mice developed peripheral insulin resistance and obesity. In addition, HFD-fed mice demonstrated an increase in the influx rate of A{beta} peptides and a reduction in 18F-FDG (a glucose surrogate) influx rate compared to LFD-fed mice. These transport changes are associated with the increase in the BBB endothelial expression of RAGE (receptor to traffic A{beta} from plasma-to-brain) and reduction of GLUT1 (glucose transporter) expression in HFD-fed mice compared to LFD-fed mice. Moreover, disruption in insulin signaling, as indicated by reduced pAKT and pERK expression, was observed in HFD-fed mice. Inhibiting AKT or ERK phosphorylation resulted in similar changes in A{beta} and glucose uptake in polarized BBB endothelial cell monolayers in vitro. These results indicate that high-fat diet induced metabolic syndrome may lead to BBB dysfunction, characterized by increased plasma-to-brain A{beta} trafficking and diminished glucose transport at the BBB, thereby aggravating the expression of AD pathological hallmarks.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.15.741912v1?rss=1
• Neural Signatures of Conscious Experience During Sleep: A Serial Awakening Study Using High-Density EEG

  Identifying neural signatures of consciousness remains a central challenge in neuroscience. Sleep offers a tractable model for comparing brain activity in the presence or absence of subjective experience while minimizing behavioral responsiveness confounds. Using overnight 256 electrode high-density EEG in 140 participants and a serial-awakening paradigm, we analyzed 699 non-rapid eye movement (NREM) sleep stage 2 and 3 awakenings (351 dreaming experience, 348 no experience). Features from the 60s preceding awakening included regional spectral power, lagged-coherence connectivity, graph-theoretic metrics and gamma-to-alpha power ratios. Dreaming experiences were associated with shifts in posterior spectral balance, particularly reduced alpha and delta power and increased gamma-related measures, together with altered large scale network organization. In participant-level cross-validated machine-learning analyses, all classifiers performed above chance, with the best ensemble model reaching an ROC-AUC of 0.80 and average precision of 0.80. These findings identify reproducible posterior electrophysiological and network-level signatures of conscious states during NREM sleep.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.16.745040v1?rss=1
• Precise Functional Localization of the Foveolar Representation in Anesthetized Macaque Visual Cortex

  The foveola-the central ~1{degrees} of the visual field-supports the highest-acuity spatial vision, yet localizing its cortical representation in the primate brain is technically demanding, particularly under anesthesia where gaze cannot be behaviorally controlled. Here we describe a hierarchical, meridian-based 7T BOLD fMRI strategy for sub-degree functional localization of the foveolar representation in anesthetized macaques. Using drifting grating bars presented at three successively finer spatial scales (4.5{degrees}, 1.5{degrees}, and 0.5{degrees}), we independently mapped the vertical and horizontal meridian representations in early visual cortex through a coarse-to-fine refinement scheme. The vertical meridian was identified by the progressive transition from unilateral to bilaterally symmetric activation converging at the V1/V2 border, whereas the horizontal meridian was defined by simultaneous activation of dorsal and ventral V2/V3 borders at the fundus of the calcarine sulcus. The functional intersection of the two meridia defined candidate foveolar coordinates, which were then refined using localized 0.2{degrees} spot stimuli. Brain surface-based rendering revealed multiple discrete foveolar loci, one at the lateral end of each of the V1/V2, V2/V3, V3/V4, and V4/TEO borders. These distributed loci define the "foveolar core", a newly discovered visual area with distinct functional properties. This meridian-based hierarchical approach provides a reproducible framework for resolving central visual representations in anesthetized primates, providing a new avenue for studying foveolar cortex and circuitry.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.16.744304v1?rss=1
• Tracking the hidden dynamics of proprioception

  Every movement unfolds with a simple question: Where is my body? The nervous system answers through proprioception - the sense of limb position (static position sense) and movement (dynamic proprioception). Although position sense has been well characterized, dynamic proprioception has remained difficult to isolate and measure. Here we introduce a continuous proprioceptive tracking paradigm, coupled with computational modelling, that captures dynamic proprioception in real time. We first establish that this approach is sensitive, reliable and efficient. Leveraging this method, we then show that dynamic proprioception provides faster and more faithful estimates of limb state than vision, dominates multisensory state estimation when vision is also available, and is not correlated with conventional measures of position sense. Together, these findings provide a new quantitative framework for characterizing dynamic proprioception in health and disease.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.16.745118v1?rss=1
• Sex differences in diverse conditioned fear behaviors following systemic naloxone administration

  Fear conditioning studies have historically relied on freezing as the primary measure of conditioned fear despite evidence that defensive responding is behaviorally diverse and sexually dimorphic. The endogenous opioid system, particularly mu-opioid receptor (MOR) signaling, is known to regulate fear learning and conditioned analgesia, yet its role in alternative fear-related behaviors and sex differences remains unclear. Here, we investigated the effects of systemic naloxone administration prior to auditory fear conditioning on freezing, darting, shock responsivity, and ultrasonic vocalizations (USVs) in male and female rats. Adult Sprague Dawley rats received naloxone (5 mg/kg, i.p.) or saline prior to conditioning and underwent fear recall testing 24 hours later. Naloxone produced sex- and behavior-specific effects across conditioning and recall. During conditioning, naloxone increased freezing in males during baseline and early tone presentations, while females exhibited reduced shock-response velocity and increased post-shock freezing. Naloxone did not significantly alter darting or USV production during conditioning. During recall, freezing behavior did not differ across groups. Naloxone-treated females, however, exhibited a distinct alarm-calling pattern, with fewer callers overall but increased call output among those that vocalized. These findings suggest that MOR antagonism differentially alters distinct components of fear expression in a sex-dependent manner and support the idea that freezing and alarm calling may reflect separable aspects of fear processing.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.20.745978v1?rss=1
• MYC-MIZ1 Complexes at Enhancers Tune Neuroendocrine Identity of Small Cell Lung Cancer

  MYC family members have been extensively studied as undruggable transcription factors regulating oncogenic signaling in highly aggressive tumors such as small cell lung cancer (SCLC), via promoter binding. Here, leveraging the previously described Myc-driven SCLC mouse model (RPM), we generated RPM-Miz1{Delta}POZ (RPMM) mice to uncover a Myc-dependent regulation of neuroendocrine (NE) differentiation, via enhancers. Our functional and genomic analyses reveal that Miz1 facilitates Myc binding to low-affinity E-boxes at distal chromosomal regions, thereby enabling Myc occupancy at sites with otherwise limited intrinsic affinity. We further show that SCLC patients and cellular models share an enrichment of low-affinity E-Box Myc binding motifs at enhancer regions that loop to genes of classic neuroendocrine differentiation. Integrated epigenetic and genomic analyses with AI-modeling implicate Myc/Miz1 binding at enhancers as the determinant for the expression of bona-fide neuroendocrine genes. In RPMM tumors, the suppression of neuroendocrine identity is paralleled by a redistribution of Myc protein towards promoter-proximal regions, hyper-activation of Myc transcriptional programs, apoptotic priming and enhanced sensitivity to etoposide. Together, these findings uncover Miz1/Myc-engaged enhancers as a central hub for neuroendocrine lineage programs and provide a mechanistic basis for a targeted inhibition of Miz1 to boost chemosensitivity in SCLC.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.19.745709v1?rss=1
• Visualizing Reaction Pathways via Reciprocal Space Kinetic Decomposition

  Time-resolved serial crystallography (TR-SX) has emerged as a powerful method for capturing ultrafast structural dynamics in proteins. TR-SX continues to produce remarkable studies, revealing previously unobserved transient states and providing deeper insights into processes such as drug targeting, DNA repair, and photosynthesis. However, extracting weak structural signals from noisy time-resolved datasets remains a major challenge. Robust computational methods are therefore required to isolate the signals associated with the underlying transient states. Importantly, this should be performed in reciprocal space to preserve compatibility with established downstream structure refinement workflows. Here, we introduce a framework for kinetic decomposition directly in reciprocal space that enables separation of kinetically distinct structural states. The method decomposes crystallographic data according to a predefined kinetic model, improving the recovery of weak transient signals and enhancing mechanistic interpretation from limited time-resolved datasets. We validate the framework using simulated data based on a previously published time-resolved crystallography study and demonstrate its application to a new TR-SX dataset comprising 17 time points. We show that the method separates the reciprocal space signatures of four intermediates by incorporating kinetic information from a predefined reaction model. This establishes a workflow for extracting kinetic states directly from time-resolved X-ray diffraction data that can be seamlessly integrated into existing crystallographic structure-determination pipelines.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.17.745189v1?rss=1
• BoYueGRN: Zero-shot causal discovery of directed gene regulatory networks from single-cell transcriptomes via amortized inference over synthetic structural causal models

  Gene regulatory network (GRN) inference from single-cell RNA-seq conventionally relies on per-dataset optimization. Existing tools must be refit for every new dataset, and the majority fail to infer causal regulatory directions. Here we present BoYueGRN, an amortized causal discovery framework trained exclusively on 10,000 synthetic structural causal models. For any unseen dataset, a single forward pass returns edge probabilities and regulatory directions, while TF-centric sliding windows with asymmetric fusion extend this fixed-size model to full-transcriptome coverage. BoYueGRN demonstrates strong zero-shot performance across BEELINE benchmarks. On two independent genome-wide CRISPRi Perturb-seq screens, directional accuracy on retained edges reaches 0.86 and 0.95. Reconstructed cell-type- and stage-specific GRN dynamics across five diseases spanning more than 270,000 cells yield experimentally testable biological hypotheses. BoYueGRN reframes directed GRN inference as a train-once, reuse-across-datasets paradigm. By decoupling network reconstruction from per-dataset optimization, this paradigm opens the door to systematic, atlas-scale mapping of regulatory dynamics across human diseases.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.15.745056v1?rss=1
• Relational Graph Convolutional Networks for Glioblastoma Biomarker Discovery via ceRNA and Copy Number Variation Analysis

  Glioblastoma (GBM) is a highly aggressive brain tumor with an extremely poor 5-year survival rate of 6.9%, largely attributable to the lack of reliable biomarkers. While competing endogenous RNA (ceRNA) and copy number variation (CNV) analyses offer unique biomarker identification potential, current approaches neglect the integration of multiple regulatory mechanisms for biomarker detection. To address this limitation, we applied relational graph convolutional networks (RGCNs) to ceRNA and CNV knowledge graphs through a novel late fusion ensemble architecture. The proposed architecture outperformed baseline models and identified five novel biomarkers, including hsa-miR-196a and hsa-miR-224. Kaplan-Meier survival analysis and Cox regression indicated that the identified genes hold significant prognostic and diagnostic power. The early stratification of the Kaplan-Meier curves indicates the potential these genes hold for patient survival prediction. The results illustrate that a late fusion RGCN ensemble effectively captures complex gene interactions, overcoming limitations of existing models and providing a framework for biomarker discovery. The novel biomarkers serve as prospective targets for future GBM therapeutic development and candidates for non-invasive diagnostic assays.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.16.744525v1?rss=1
• Predicting the operon structure of the Mycococcus xanthus genome using the novel software DiscOperon

  ABSTRACT Motivation: Myxococcus xanthus is a predatory soil bacterium with a large genome of 9.14 MB due to a genome duplication event. While complete genome sequences of M. xanthus are available, gene annotation remains challenging due to its size and the resulting large number of duplicated genes. Operons, so syntenic block of genes that are co-regulated in bacterial genomes, are an important resource to help predict gene function accurately. Results: In order to help improve the annotation of complex genomes such as the one from M. xanthus, we developed a novel operon prediction tool, DiscOperon, which combines gene expression data with homology searches to identify syntenic blocks: Co-expression data of neighbouring genes across the genome are first used to define gene clusters, which are then used to search for conserved syntenic blocks in fully sequenced bacterial genomes using sequence homology searches. This strategy enables DiscOperon to account for gene insertions, rearrangements and deletions, which is its most distinguishing feature. We have tested DiscOperon against ground truths gene pair information on 3 different species from ODB and RegulonDB and compared it to state-of-the-art and still available operon prediction software and we demonstrate its general usability for operon prediction of any bacterial complete genome. We have applied DiscOperon to predict the operons of M. xanthus, which we are making available for the research community. Availability and implementation: DiscOperon is lightweight, user-friendly python tool with minimal dependencies. It is freely available at https://gitlab.com/habermann_lab/discoperon for general usage. Contact: Theo Brunet (theo.brunet@univ-amu.fr); Bianca Habermann (bianca.habermann@univ-amu.fr). Supplementary information: The operon-structured and annotated M. xanthus genome is available from this manuscript, as well as from Zenodo (https://doi.org/10.5281/zenodo.21976167). We furthermore plan to submit the M. xanthus operon information to the operon database OBD.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.20.745974v1?rss=1
• Chronic kidney disease promotes anxiety susceptibility through an angiotensin II central amygdala axis

  Background: Neuropsychiatric comorbidities are highly prevalent in chronic kidney disease (CKD), yet the underlying neural mechanisms remain poorly defined. Methods: We established multiple mouse models of CKD and identified an adenine-induced model as the most suitable platform to study neurobehavioral alterations. Anxiety susceptibility was operationalized as the emergence of anxiety-like behavior after subthreshold unpredictable stress (SUS) and was assessed using the SUS paradigm combined with behavioral assays. Region-focused c-Fos mapping, fiber photometry, and chemogenetic manipulation were used to interrogate neural circuit activity. Pharmacological and genetic approaches were applied to investigate the role of angiotensin II (Ang II) signaling. Finally, hypothalamic paraventricular nucleus (PVN) activation was used to explore brain-to-kidney feedback by using in vivo multiphoton microscopy imaging techniques. Results: CKD mice showed no consistent baseline anxiety-like phenotype across standard assays but developed robust anxiety-like behavior after subthreshold unpredictable stress. Region-focused c-Fos profiling and fiber photometry identified the central amygdala (CeA) as a stress-sensitized limbic node in CKD. Chemogenetic inhibition of CeA GABAergic neurons attenuated anxiety-like behavior, supporting a functional role for CeA activity. Mechanistically, CKD elevated circulating Ang II and enhanced CeA accumulation of peripherally administered FAM-Ang II-associated signal. CeA-specific Agtr1a knockdown attenuated anxiety-like behavior and exaggerated stress evoked CeA calcium responses. Exploratory experiments further showed that sustained PVN glutamatergic activation aggravated early renal injury markers in a mild renal injury model. These findings support a kidney-to-brain model in which CKD primes CeA stress circuits, while local Ang II AT1R signaling contributes to the behavioral expression of stress-induced anxiety-like behavior, with a potential brain to kidney feedback component. Conclusions: CKD promotes stress-induced anxiety susceptibility through a CeA-centered mechanism involving local Ang II AT1R signaling. These findings identify CeA Ang II AT1R signaling as a potential contributor to CKD-associated stress-related affective vulnerability.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.16.744184v1?rss=1
• The BLM DHBN domain and structure-selective nucleases drive mitotic arrest-dependent telomere deprotection under WRN and TRF2 control

  Telomeres shield chromosome ends from DNA damage response through T-loops, lariat DNA structures formed and stabilized by the shelterin protein TRF2. During prolonged mitotic arrest, telomeres lose this protection through a process termed mitotic arrest-dependent (MAD) telomere deprotection, which elicits telomere-specific DNA damage signaling in the absence of telomere shortening or chromosome end-to-end fusions. We previously demonstrated that the RecQ helicase BLM promotes MAD telomere deprotection, whereas the related helicase WRN suppresses it independently of its catalytic activities. However, the molecular interplay between BLM and WRN at mitotic telomeres and whether additional recombination-associated enzymes contribute to MAD telomere deprotection have remained unresolved. Here, we identify the Dimerization Helical Bundle in the N-terminal (DHBN) domain of BLM helicase as the critical determinant of MAD telomere deprotection and show that WRN selectively restrains this activity without interfering with BLM's canonical genome-protective functions. We further show that both MUS81 and GEN1 contribute to MAD telomere deprotection. Moreover, the exacerbation of MAD telomere deprotection observed upon TRF2 depletion is strongly attenuated by additional depletion of these enzymes, demonstrating that TRF2 normally protects T-loop junctions from their enzymatic activities. Collectively, our findings reveal how telomeres become selectively vulnerable during prolonged mitotic arrest and uncover a regulated enzymatic mechanism that repurposes recombination machinery at chromosome ends.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.19.745663v1?rss=1
• Upregulation of the Unfolded and Mitochondrial Unfolded Protein Responses in Oxidative Stress-Induced Cataract

  Purpose: Oxidative stress is thought to contribute to the development of age-related cataracts (ARCs), but the mechanisms by which oxidative damage leads to the opacification of the lens remain unclear. Previous studies suggest that oxidative stress can disrupt lens proteostasis. Therefore, it was hypothesized that ARCs arise from proteomic changes driven by an age-associated decline in oxidative stress defenses that interact with the lens proteostatic state. To test this hypothesis, proteomic analyses of lenses exposed to oxidative stress were performed to examine oxidative and proteostatic stress responses in vivo. Methods: Cataract formation was induced by injecting hydrogen peroxide into the aqueous humor of adult zebrafish. nrf2fh318/fh318 zebrafish were used to model the reduced oxidative stress protection observed in aged human lenses, while cryaba-/- zebrafish were used to model impaired lens proteostasis. Resulting opacities in WT, cryaba-/-, nrf2fh318/fh318, and cryaba-/-; nrf2fh318/fh318 lenses were quantified and proteomic changes in the cortex were analyzed using data independent acquisition Parallel Accumulation Serial Fragmentation mass spectrometry. Results: Hydrogen peroxide treatment induced the formation of cortical cataracts. Proteomic results showed that, dependent on genotype and day, oxidative stress activates the unfolded and mitochondrial unfolded protein responses. Additional changes were also observed in energy metabolism, Ca2+ homeostasis, protein degradation, and cytoskeletal and extracellular matrix remodeling pathways. Conclusions: Treated zebrafish lenses successfully model ARC and mass spectrometry proteomics identified the unfolded and mitochondrial unfolded protein responses as potential therapeutic targets for ARC.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.19.745850v1?rss=1
• Spatial cholesterol homeostasis gatekeeps T-cell development and activation by orchestrating signaling and fitness

  Cholesterol is essential for T-cell immunity, and its spatial distribution is tightly regulated. Although cholesterol is synthesized in the endoplasmic reticulum (ER), it is predominantly transported to the plasma membrane (PM); however, the machinery mediating this anterograde transport in T cells remains unknown. Here, through a functional genetic screen, we identify oxysterol-binding protein (OSBP) as the principal mediator of ER-to-PM cholesterol transport in T cells. OSBP deficiency depletes accessible PM cholesterol while causing cholesterol accumulation in the ER, resulting in impaired T-cell receptor (TCR) signaling and disruption of ER homeostasis. Using stage-specific conditional knockout mice, we demonstrate that OSBP is required at multiple developmental checkpoints in the thymus, including {beta}-selection, positive selection, and post-selection maturation. Loss of OSBP during early thymocyte development causes a near-complete block in T-cell development, resulting in a profound absence of mature peripheral T cells. In mature T cells, activation markedly increases dependence on OSBP-mediated cholesterol transport, with its inhibition causing ER perturbation and extensive cell death. Finally, we show that disease-associated oxysterols disrupt OSBP-mediated cholesterol transport, leading to T-cell dysfunction and providing a mechanistic explanation for impaired T-cell immunity in pathological settings. Together, our findings identify OSBP as a central regulator of intracellular cholesterol transport that couples membrane cholesterol homeostasis to TCR signaling and ER integrity. These results establish the spatial distribution of cholesterol, rather than its abundance alone, as a fundamental metabolic determinant of thymocyte development and peripheral T-cell function.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.16.745088v1?rss=1
• Mice sense Moon and Sun

  Life on earth has always been exposed to the fluctuating Earth's magnetic field, but a magnetic sense affecting behavior has been debated for mammals. We here report that mice, kept under constant laboratory conditions, showed fluctuations in spontaneous behavioral activity with a periodicity of ~14 and ~28 days. This was confirmed in nine cohorts from four facilities on two continents, covering 3 to 41 months. Such oscillations were also maintained in brain Bmal1 knockout mice lacking circadian rhythms, suggesting independence of the circadian clock. The behavioral activity peaked around full and new Moon, and showed a strong alignment with the periodic geomagnetic fluctuations originating in the Earth's iono- and magnetosphere that are modulated by solar rotation and the orbital motion of the Moon. In the ultradian range, this alignment persisted in CRY1/2 knockout mice, suggesting that solar-lunar-driven geomagnetic fluctuations can modulate behavior rhythms independently of CRY1/2.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.17.745150v1?rss=1
• Targeting Astrocytic Stat3 Reveals Context-Dependent Modulation of Prion Disease

  Reactive astrogliosis is a prominent feature of prion diseases, yet the molecular mechanisms regulating astrocyte activation and their contribution to disease progression remain poorly understood. Signal transducer and activator of transcription 3 (Stat3) is a master regulator of reactive astrocytes in numerous neurological disorders, but its role in prion disease has not been established. Here, we investigated the contribution of astrocytic Stat3 signaling to prion pathogenesis using an inducible astrocyte-specific Stat3 knockout mouse model. Stat3 expression was elevated across multiple neuroinflammatory conditions but was most strongly induced during prion disease. Among four mouse-adapted prion strains (ME7, RML, 22L, and SSLOW), the magnitude of Stat3 activation closely paralleled the severity of neuroinflammation. Astrocyte-specific Stat3 deletion was evaluated in mice infected with either the highly inflammatory SSLOW strain or the less inflammatory 22L strain. Stat3 deletion had no detectable effect on disease progression in SSLOW-infected mice but modestly delayed disease onset and behavioral decline in male mice infected with the 22L strain, particularly when knockout was induced before prion inoculation. Despite its limited effect on survival, astrocyte-specific Stat3 deletion consistently attenuated astrocyte reactivity, as evidenced by reduced vimentin expression, delayed cortical GFAP induction, and lower GFAP expression in recombined astrocytes at the single-cell level, demonstrating a cell-autonomous role for Stat3 in promoting reactive astrogliosis. In contrast, PrPSc accumulation and overall microglial activation remained unchanged, indicating that astrocytic Stat3 signaling is dispensable for prion replication and does not substantially influence the global microglial response. Tamoxifen-induced recombination occurred in only 40-70% of astrocytes, resulting in partial and region-dependent Stat3 deletion that likely underestimated the impact of astrocytic Stat3 loss. Together, these findings identify Stat3 as an important regulator of astrocyte reactivity during prion disease but demonstrate that its contribution to disease progression is limited and highly context-dependent, varying with the inflammatory milieu, timing of pathway inhibition, and biological sex. Our results highlight the redundancy of inflammatory signaling networks driving chronic prion neurodegeneration and suggest that targeting astrocytic Stat3 alone is unlikely to substantially alter disease progression.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.15.745015v1?rss=1
• Unveiling the Epigenomic Control of Temperature Acclimation in Marine Phytoplankton through Multiomics Integration

  Temperature plays a central role in marine phytoplankton biogeographical dynamics, physiology and gene expression. Nonetheless, the transcriptional regulatory mechanisms controlling temperature acclimation in marine phytoplankton are yet to be characterized. Ostreococcus tauri was chosen as a model species for green marine phytoplankton due to its cellular and genomic simplicity, as well as its evolutionary position within the green lineage. In this study, epigenomic and transcriptomic data were integrated to characterize changes induced by temperature in the trimethylation of histone 3 at lysines 27 and 4 (H3K27me3 and H3K4me3) epigenetic marks established by the Polycomb (PcG) and Trithorax group (TrxG) complexes, respectively. H3K27me3 was found to be a repressive mark responding to temperature, showing predominantly significant increased levels at high temperatures. While H3K4me3 was associated with active transcription, presenting less evident variations in cultures acclimated to different temperatures. H3K27me3 was found only marginally associated with transposable elements, being mostly involved in the repression of specific biological processes, such as gene expression control by transcription factors, meiosis, motors proteins and cytoskeletal structures. No significant conservation was found between the H3K27me3 gene targets in the model plant Arabidopsis thaliana and Ostreococcus tauri. Nonetheless, transcriptions factors belonging to the MADS-box, WRKY and AP2 families were consistently repressed by H3K27me3 in both species, unveiling that, although the specific downstream targets of this epigenetic mark have diversified during evolution, its role in modulating higher order regulatory nodes remains evolutionary conserved.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.19.745701v1?rss=1
• Quantitative Model of Transcriptional Noise Regulation by mRNA Condensates

  A fundamental biological process of transcription occurs in the cell nucleus, which is a complex medium that also contains multiple heterogeneous structures known as biomolecular condensates. Interestingly, some of these condensates contain mRNA molecules in addition to proteins, suggesting an important cellular role in transcription that is not yet well understood. In this work, we develop a minimal theoretical framework for quantitative investigation of the role of reversible mRNA condensation in transcription. Our discrete-state stochastic approach accounts for the most relevant processes, allowing us to explicitly evaluate the properties of the system and clarify the effects of condensation. Analytical calculations supported by computer simulations suggest that reversible mRNA condensation influences the transcription processes by maintaining a constant level of free mRNA in the nucleoplasm while lowering the degree of stochastic noise and increasing the robustness against external perturbations. Physicochemical arguments are presented to explain these observations. The proposed theoretical framework elucidates important microscopic aspects of transcription, providing a convenient quantitative tool for investigating complex biological phenomena.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.16.745099v1?rss=1
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  🧰 ToolsAug 20, 2026https://www.producthunt.com/products/tonaily?utm_campaign=producthunt-api&utm_medium=api-v2&utm_source=Application%3A+the500feed+%28ID%3A+283491%29
• UPLC-ESI-MS based lipidomics revealed novel biomarkers in insulin receptor knockdown induced type 2 diabetes model of Drosophila

  Type 2 diabetes (T2D) is a prevalent metabolic disorder affecting millions worldwide, characterized by insulin resistance and impaired glucose homeostasis. While mammalian models are widely used, Drosophila melanogaster provides a powerful alternative due to its conserved insulin signaling pathways, genetic tractability, and suitability for high throughput studies. In addition to glucose dysregulation, lipid metabolism plays a crucial role in T2D pathophysiology, as alterations in lipid composition contribute to insulin resistance and metabolic dysfunction. Lipidomic studies have emerged as an essential approach to identify metabolic signatures and potential biomarkers for disease progression and therapeutic targeting. In this study, T2D like model was established by inducing insulin resistance through knockdown of the insulin receptor in brain insulin-producing cells using the dilp2-Gal4>UAS-InRRNAi system. This genetic manipulation resulted in significant metabolic dysregulation, including elevated glucose, trehalose, and triacylglyceride levels, along with increased oxidative stress indicators. Additionally, mRNA expression analysis of key insulin signaling components, including insulin receptor substrate 1, dilp2, dilp3, dilp5, and phosphorylated Akt, further validated the model. To further investigate metabolic alterations, Lipid profiling was performed using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) in non targeted LC-MS-based metabolomics approach to identify lipid biomarkers associated with T2D. Multivariate statistical analyses, including PCA and PLS-DA, revealed distinct lipid signatures between wild-type and T2D flies. Notably, specific phosphatidylglycerol species PG 34:0, PG 34:4, PA 38:3, PIP 38:1, PIP2 38:6, and LPS 24:0 demonstrated an area under the curve (AUC) of 1, indicating their strong reliability as lipid biomarkers for T2D diagnosis.

  📄 ResearchAug 20, 2026https://www.biorxiv.org/content/10.64898/2026.08.20.745875v1?rss=1
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