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3D nanoscale imaging of amyloid-β oligomer interactions with extracellular vesicles by cryo-ET

Central to Alzheimer’s disease pathology are prefibrillar oligomer assemblies of amyloid-β (Aβ) peptide. A widely discussed hypothesis proposes that amyloid-β oligomers insert into neuronal lipid membranes, disrupting their integrity and causing a loss of cellular homeostasis in Alzheimer’s disease. This membrane disruption is believed to be a major source of Aβ-induced neurotoxicity. Cryo electron tomography (cryo-ET) has facilitated 3D nanoscale imaging of Aβ-membrane interactions under near-native conditions. Analyses of small extracellular vesicles (sEVs) reveals that Aβ oligomers including annular and curvilinear extended oligomers (CLEOs) exhibit extensive binding to cell-derived lipid membranes, including insertion into and carpeting of the lipid bilayer. Notably, these oligomeric assemblies were also internalized and concentrated within the cell-derived exosomes and other small sEVs. Enrichment of Aβ oligomers within the vesicles typically ranged between 5 to 20 times the external Aβ levels depending on the vesicle size and curvature. In contrast, monomeric and fibrillar forms of Aβ displayed minimal membrane interaction. Once internalized CLEOs appear to be trapped in an oligomeric form and do not readily go on to form fibrils. Studies with vesicles of brain lipid extract indicate the Aβ internalization does not require the presence of a membrane protein. Our in vitro studies underscore the membrane-disruptive capacity of oligomeric Aβ species and suggest a role of sEVs in concentrating toxic Aβ oligomers and transporting oligomers across the brain interstitium.

Hybrid circular-square complementary split-ring resonator sensor for monitoring abnormal blood protein levels for disease diagnosis

Repurposing trazodone for Alzheimer’s disease to modulate soluble ST2 levels and alleviate Alzheimer’s pathology

Alzheimer’s disease (AD) is a multifactorial disorder involving various pathological mechanisms, such as amyloidosis, immune dysfunctions, and synaptic impairments, which are important therapeutic targets. Repurposing drugs to target these mechanisms offers a promising approach to reduce the costs and duration of drug development. Genetic studies underscore the critical role of microglial clearance of amyloid-beta (Aβ) in AD pathogenesis. Specifically, soluble ST2 (sST2)—one of the two major isoforms of the ST2 protein encoded by the IL1RL1 (interleukin-1 receptor-like 1) gene—acts as a decoy receptor isoform that interferes with IL-33/ST2 signaling and has been identified as a disease-modifying factor that impairs microglial Aβ clearance functions. In this study, we investigated drug repurposing opportunities to modulate sST2 levels and alleviate AD pathologies. Unbiased screening of commonly used medications in AD patients, followed by validation in model systems, identified trazodone—an antidepressant used to treat major depressive disorder—as a leading negative regulator of sST2. Trazodone primarily suppresses sST2 expression through its antagonistic effects on adrenergic signaling. In the APP/PS1 transgenic mouse model of AD, trazodone treatment enhanced microglial interaction with Aβ and alleviated Aβ pathology. Furthermore, trazodone reduced neurodegeneration and rescued synaptic deficits in APP/PS1 mice. Comprehensive molecular profiling of APP/PS1 mouse brains showed that trazodone restored the expression of synaptic proteins critical for synaptic integrity and plasticity. Overall, these findings demonstrate that trazodone is a promising repurposing candidate for AD that targets underlying immune dysfunctions and synaptic impairment.

SUMOylation modulates glucocorticoid-induced muscle toxicity in cell and mouse models

CDK8 coordinates jasmonate-induced immunity with sulfur-responsive defense in <i>Arabidopsis</i>

Plant immunity draws heavily on carbon-, nitrogen-, and sulfur-based precursors for the deployment of specialized defense compounds. The jasmonate signaling pathway promotes expression of metabolically costly defenses, often at the expense of growth. How plants coordinate growth–defense tradeoffs with changes in nutrient availability remains poorly understood. Here, we identify CYCLIN-DEPENDENT KINASE 8 (CDK8) as a transcriptional regulator that restrains growth and reduces seed yield under conditions of heightened jasmonate signaling in Arabidopsis thaliana and further show that CDK8 shapes immune responses according to sulfur availability. Transcript and metabolite profiling showed that CDK8 amplifies jasmonate-triggered immunity, including robust accumulation of glucosinolates, camalexin, and sulfur-rich defensin peptides under sulfur-replete conditions. Strikingly, sulfur limitation triggered a CDK8-dependent transcriptional switch that suppressed defensins and glucosinolates while coordinately inducing camalexin, a defense metabolite requiring substantially lower sulfur investment. These findings establish CDK8 as a regulator that integrates jasmonate signaling with sulfur nutritional status to shape the composition of plant immune responses.

Crossing the growth plate: distal femoral physeal response to intramedullary nailing in a porcine model

Oncogenic snoRNA <i>SNORD78</i> fuels colorectal cancer by protecting the m ⁶ A reader IMP2 to enhance phospholipid metabolism

Small nucleolar RNAs (snoRNAs) play crucial regulatory roles in various cancers. However, the mechanisms by which snoRNAs regulate N6-methyladenosine (m 6 A) modifications in colorectal cancer (CRC) remain unclear. This study systematically deciphered the precise interaction mechanism between SNORD78 and the m 6 A reader IMP2 in CRC. We demonstrate that SNORD78 specifically stabilizes IMP2 to activate the PIK3CD-CHKA-Kennedy pathway in an m 6 A-dependent manner, promoting endoplasmic reticulum stress (ERS) and phosphatidylcholine (PC) biosynthesis, thereby driving CRC. Conversely, the SNORD78 -targeting antisense oligonucleotide (ASO), ASO-78, effectively suppresses ERS and PC levels, inhibiting CRC progression. Mechanistically, SNORD78 , relying on the “UAAUGA” element in its C-D box region, specifically binds to the Lys221 ubiquitination site of IMP2, blocking TRIM25-mediated degradation of IMP2 and maintaining its stability. IMP2 enhanced the stability and translation of the target mRNAs PIK3CD and CHKA by recognizing their corresponding m 6 A positions, m 6 A-3208 and m 6 A-1619, respectively, to reshape the phosphatidylcholine metabolite profile in CRC cells. In terms of potential therapeutic strategies, the ASO-78 can significantly inhibit CRC cell proliferation, reduce ERS levels, and decrease phosphatidylcholine content. The combination of ASO-78 and IMP2 inhibitor IMP2-IN1, by dual blocking of the SNORD78 –IMP2 axis, exhibits an excellent proliferation-inhibiting effect in CRC organoids. This study not only reveals a mechanism by which the SNORD78 –IMP2 interaction regulates CRC occurrence and development but also provides theoretical basis for innovative therapeutic strategies for precise targeting of tumor snoRNA-m 6 A reader interactions.

Influence of body-shape-based mass scaling and thoracic disc stiffness on flexible-thorax model predictions of thoracolumbar loading during lateral bending

Disentangling dissociative and nondissociative reaction dynamics in molecular mutual neutralization reactions between CO ⁺ and O ⁻

We have studied the mutual neutralization reaction of CO + with O − at a collision energy of ≤0.1 eV under single-collision conditions. We observe both fully dissociative (31.5 ± 1.8 %) and nondissociative (68.5 ± 1.8 %) charge transfer, involving at least five different electronically excited states in CO. From product momentum analysis, we find that the dynamics are governed by electron transfer processes at large O − -CO + separations and the competition between predissociation and radiative decay in CO Rydberg states. In the case of nondissociative charge transfer, for one of the reaction channels we observe strong vibrational excitation (4 ≤   v ≤ 8) in the product CO molecule. These data are expected to be useful for modeling astrophysical and planetary atmospheric environments where CO + and O − are present.

Internal curing effect of lightweight mortar incorporating autoclaved aerated concrete (AAC) block debris as fine aggregate on brick masonry strength

Quantitative calibration of a spatial QSP model identifies fibroblast impact on HCC immunotherapy

Computational models are increasingly used to predict treatment response and optimize cancer therapeutic strategies. Quantitative systems pharmacology (QSP) models mechanistically simulate tumor progression and pharmacological interventions, enabling virtual clinical trials, model-informed drug development, and biomarker discovery, but they lack spatial resolution to represent tumor microenvironment (TME) architecture. Coupling QSP with agent-based modeling creates spatial QSP (spQSP) frameworks capable of resolving tissue-level organization at single-cell resolution; however, parameterizing these models with human tumor data remains challenging. Here, we extend an existing spQSP model of liver cancer by mechanistically incorporating a fibroblast module and develop an Approximate Bayesian Computation–Sequential Monte Carlo calibration pipeline that integrates spatial molecular data. This calibration framework matches tumor architectures between spQSP simulations and spatial molecular data by fitting statistical summaries of cellular neighborhoods. The calibrated model reproduces fibroblast-mediated exclusion of lymphocyte infiltration observed in spatial transcriptomics and predicts posttreatment spatial tumor states in an independent cohort receiving immune checkpoint inhibitor and tyrosine kinase inhibitor combination therapy. Finally, we identify spatial and nonspatial pretreatment biomarkers associated with therapeutic response. Together, this study demonstrates how integrating spatial omics with mechanistic modeling enables quantitative calibration, reveals the spatial role of fibroblasts in shaping immunosuppressive TMEs, and supports in silico biomarker discovery toward personalized cancer therapy.

Quantifying soiling and environmental stress impacts on rooftop photovoltaic performance in a coastal industrial environment

A reassessment of NMDA receptor–dependent presynaptic homeostatic plasticity

Excitatory glutamatergic synapses in the brain are remarkably plastic. Two forms of plasticity have received the most attention: long-term potentiation (LTP) and synaptic homeostasis. While LTP requires the activation of NMDA receptors, synaptic homeostasis does not. However, both phenomena are mediated by the recruitment of postsynaptic AMPA receptors (AMPAR) to the synapse. Recently a new form of plasticity has been described referred to as presynaptic homeostatic plasticity (PHP). Pharmacological inhibition of AMPAR synaptic responses in CA1 hippocampal pyramidal cells initiates a rapid homeostatic response that results in the recovery of the AMPAR responses to normal values in the continued presence of the inhibitor. Accompanying this recovery is a doubling of the NMDA receptor response which is interpreted as an increase in the release of glutamate. This is provocative since claiming that a reduction in AMPAR responses triggers an enhancement in NMDA receptor responses. Using three different protocols to monitor synaptic responses we fail to observe any recovery of synaptic responses in the presence of an AMPAR inhibitor. Furthermore, there was no enhancement in NMDA receptor responses. Thus, we find no evidence for the presence of PHP at CA1 hippocampal synapses.

Application of widely targeted metabolomics combined with network pharmacology and molecular docking to elucidate growth stage-specific metabolite accumulation and predict the diuretic mechanisms of Leontopodium leontopodioides (Willd.) Beauv

Dopaminergic neurons preferentially accumulate mtDNA rearrangements

High levels of mitochondrial DNA (mtDNA) deletions have been described in the substantia nigra. However, the mechanisms involved are poorly understood. We found that transient expression of a mitochondrial targeted restriction endonuclease (mitoPstI) in mice leads to an accumulation of mtDNA rearrangements that involve both the PstI cleavage sites and unrelated specific regions of the mtDNA, including the MTERF1 binding site and the edge of the D-loop. This pattern of rearrangements after double-strand breaks supports the presence of recombination hotspots in the mtDNA. Transient expression of mitoPstI in dopaminergic neurons led to further accumulation of mtDNA rearrangements in dopaminergic neurons after expression was suppressed, a pattern that was not observed in glutamatergic neurons. This accumulation was also blunted when a mtDNA replisome factor was absent, suggesting that robust mtDNA replication is required for the accumulation of preexisting mtDNA rearrangements in dopaminergic neurons over time.

Assessing conventionally bred lentil (Lens culinaris Medik) cultivars for adaptation to organic cropping systems in the southeastern USA

Many AI analysts, one dataset: Navigating the agentic data science multiverse

Empirical conclusions depend not only on data but also on analytic decisions. Many-analyst studies have quantified this dependence: independent teams testing the same hypothesis on the same dataset regularly reach conflicting conclusions. But such studies require costly human coordination. We show that fully autonomous AI analysts built on large language models (LLMs) can, cheaply and at scale, produce the analytic dispersion observed in human many-analyst studies. In our framework, each AI analyst independently executes a complete analysis pipeline on a fixed dataset and hypothesis; a separate AI auditor screens every run for methodological validity. Across three datasets, AI analyst-produced analyses exhibit substantial dispersion in effect sizes, P -values, and conclusions. This dispersion can be traced to identifiable analytic choices in preprocessing, model specification, and inference that vary systematically across LLM and persona conditions. Critically, the outcomes are steerable: reassigning the analyst persona or LLM shifts the distribution of results even among methodologically sound runs. These results highlight a central challenge for AI-automated empirical science: when defensible analyses are cheap to generate, evidence becomes abundant and vulnerable to selective reporting. The same capability also helps address it: treating analyst results as distributions makes analytic uncertainty visible, and deploying AI analysts against a published specification can reveal how much disagreement stems from underspecified design choices. Taken together, our results motivate a transparency norm: AI-generated analyses should be accompanied by multiverse-style reporting and full disclosure of the prompts used, on par with code and data.

RISC-V-based YOLOv3-tiny acceleration with runtime-reconfigurable systolic arrays and custom instructions

Sequential evolution of antidote and toxin links genetic incompatibility with immune responses

Toxin-antidote (TA) systems are selfish genetic elements that ensure their own inheritance by eliminating offspring that do not inherit the module, thereby creating postzygotic genetic incompatibilities both within and between species. Despite their ubiquity and substantial fitness costs, the origin and persistence of TA systems remain poorly understood. Here, we report a TA gene pair in the nematode Caenorhabditis nigoni . The antidote gene, Cni-shls-2 , is a C. nigoni -specific F-box gene that arose through recent tandem duplications, leading to three identical copies. Its absence results in embryonic lethality in both C. nigoni and its hybrids with the sister species Caenorhabditis briggsae . This lethality is mediated by a maternally deposited toxin, Cni-hlix-1 , a chimeric gene formed by the fusion of duplicated host sequences with novel sequences that could be derived from bacteria/archaea. Analysis of evolutionary trajectory of the TA genes among various populations suggests that the antidote is more likely to predate the toxin. These results support a possible model of TA origin, in which Cni-shls-2 initially evolved under pathogen pressure, whereas the subsequent emergence of the toxin enforces antidote retention. We speculate that host–pathogen conflict may serve as a key driving force in the evolution and maintenance of TA systems, inadvertently leading to reproductive barriers.

Association of target miRNAs expression in blood plasma and cerebrospinal fluid with Alzheimer’s disease biomarkers level and cognitive decline