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Earlier sources: Science
Science investigates the natural world through observation, experiments, and mathematical models. Explore papers and developments in biology, medicine, materials, neuroscience, physics, climate, and mathematics; a reported finding is not necessarily established consensus.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗1667 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
A numerical method for coupling parameterized physics-informed neural networks and FDM for advanced thermal-hydraulic system simulation ↗
Severe accident analysis with system codes such as MELCOR is indispensable for nuclear safety assessment, yet the cost of repeated simulations constrains parametric studies and uncertainty quantification. Data-driven surrogates accelerate these analyses but require large simulation datasets, whereas physics-informed neural networks (PINNs) require no training data yet must be retrained for every parameter change and lose accuracy over long horizons. This study addresses both limitations with the P2F method — Parameterized PINNs coupled with the finite difference method (FDM) — for MELCOR’s Con…
- OpenAlex · Published · First archived
Decoherence-protected entangling gates in a silicon carbide quantum node ↗
Solid-state color centers are promising candidates for nodes in quantum network architectures. However, realizing scalable and fully functional quantum nodes-comprising both processor and memory qubits with high-fidelity universal gate operations-remains a central challenge in this field. Here, we demonstrate a fully functional quantum node in silicon carbide (SiC), where electron spins act as quantum processors and nuclear spins serve as quantum memory. Specifically, we design a pulse sequence that combines dynamical decoupling with hyperfine interactions to realize decoherence-protected univ…
- Europe PMC · Published · First archived
Live-cell imaging and ultrastructure expansion microscopy reveal the dynamic intracellular life cycle of Encephalitozoon intestinalis ↗
Microsporidia are divergent fungal pathogens that infect a wide range of hosts. Microsporidia have evolved highly reduced genomes, resulting in the loss of many metabolic pathways. Encephalitozoon intestinalis is a human-infecting microsporidian species with the smallest known eukaryotic genome (2.3 Mbp). As an obligate intracellular parasite, E. intestinalis is dependent on its host for replication. Our current understanding of E. intestinalis cell biology remains limited. This is largely due to genetic intractability, which has made live-cell imaging challenging, and its small size (~2 μm),
- Europe PMC · Published · First archived
Genome-Resolved Characterization of Stage-Associated Microbial Composition and Functional Potential During Spontaneous Ugba Fermentation ↗
Ugba, a traditional alkaline-fermented condiment produced from African oil bean seeds (Pentaclethra macrophylla Benth.), remains poorly characterised at genome resolution. This study characterised a single spontaneous ugba fermentation using genome-resolved shotgun metagenomics across Early (0-24 h), Mid (48-96 h), and Late (120-144 h) composite stages. Thirty metagenome-assembled genomes (MAGs) were recovered and grouped according to their temporal abundance patterns. The Early-stage retained MAG population was dominated by Bacteroidota-associated MAGs, which exhibited the highest carbohydrat
- Europe PMC · Published · First archived
Bloom-forming bacteria heavily invest in anti-phage defense ↗
Bacterial blooms are characterized by unusually high cell densities and exceptionally low diversity and can profoundly alter ecosystem function and services. Bacteriophages have long been considered an important cause of mortality in blooms, acting as a mechanism for control. Here, we characterize the viral ecology of a long-lasting estuarine bloom of green sulfur bacteria (Chlorobiota). We combined direct cell and viral counts with metagenomic and metaproteomic data to characterize host and phage activity at different time points. The abundance of virus-like particles (VLPs) decreased at high
- Europe PMC · Published · First archived
High-resolution mapping of RNA structural maturation during Cas9 assembly with ABEL-FRET ↗
The structural flexibility of RNA is essential for forming ribonucleoprotein (RNP) complexes, which regulate diverse biological processes. This intrinsic property permits RNA to act as a dynamic scaffold along the assembly pathway as it folds into a specific structure for initial recognition by protein and undergoes conformational rearrangements for functional maturation as a complex. Yet, RNA flexibility and RNP multicomponent assembly create significant obstacles for traditional structural methods. To overcome these challenges, we applied recently developed ABEL-FRET spectroscopy to measure
- Europe PMC · Published · First archived
The chromosome level genome of the Blueberry Stem Gall Wasp, Hemadas nubilipennis (Hymenoptera: Ormyridae) on lowbush blueberry (Vaccinium angustifolium) reveals repeat-driven expansion ↗
Gall-inducing wasps are emerging models for studying plantinsect coevolution, host manipulation, host plant adaptation, and speciation, yet chromosome-level resources remain scarce for most lineages. The blueberry stem gall wasp (BSGW), Hemadas nubilipennis (Hymenoptera: Ormyridae), is native to North America where it induces galls on both lowbush (Vaccinium angustifolium) and highbush blueberries (V. corymbosum). Recently, BSGW has reached outbreak densities in cultivated highbush production. Given that (a) the biology has been characterized primarily from natural lowbush-associated populatio
- Europe PMC · Published · First archived
Chromosomal breakage in Arabidopsis thaliana neo-polyploids occurs preferentially at candidate fragile sites colocalized with ancient genome rearrangements ↗
Newly formed polyploids often suffer extensive aneuploidy and chromosome rearrangement. We explored whether these are predictable and conserved across genotypes. We quantified whole-chromosome and segmental aneuploidy in progeny arrays of neo-polyploid Arabidopsis thaliana from two accessions (Col-0 and Ler). 29% of progeny had whole-chromosome and/or segmental aneuploidies. Strikingly, segmental aneuploidy arose exclusively from Ler, preferentially maternally, showing that genotype and sex of origin matter. Breakpoints of segmental aneuploidies were non-random, with over 2/3 mapping to five p
- Europe PMC · Published · First archived
Integrative analysis of the MDM2 promoter switch and cellular lineage plasticity in colorectal cancer: a contrast between the autonomous-proliferation type (CIN/CMS2) and the environment-adaptive type (MSI/gastric metaplasia) ↗
Background: Biomarkers that stratify colorectal cancer (CRC) by therapeutic responsiveness and are measurable directly in biopsy specimens remain insufficiently established. We investigated whether usage of the dual MDM2 promoters (P1/P2) acts as a molecular switch separating two diametrically opposed CRC phenotypes: a chromosomal instability type and an environment adaptive type (microsatellite instability/serrated pathway with gastric metaplasia). Methods: Sixty three organoid samples from 22 patients with CRC were classified morphologically by deep learning (VGG16) and molecularly by an MDM
- Europe PMC · Published · First archived
SHERLOCK: Structured representation learning and causal inference of downstream perturbation effects ↗
Understanding the effects of genetic, molecular, and experimental perturbations is essential for decoding cellular mechanisms and guiding biomedical interventions. Existing computational approaches are typically designed for individual tasks, such as predicting perturbation responses, characterizing downstream transcriptional effects, or modeling perturbation combinations, and therefore do not provide a unified framework for learning interpretable perturbation representations while enabling causal analysis of downstream effects and characterization of condition-dependent responses. We present
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