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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 ↗1616 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
Expanding Genetic Code to Generate Human Brain Organoids with Both Vasculature and Microglia‐Like Cells ↗
Brain organoids offer an invaluable model system for studying human brain development and disease. However, the establishment of high-fidelity brain organoids with multiple cell lineages, including vasculature and immune cells, remains a huge challenge. Here, we present a new strategy to generate human cerebral organoids with vasculature and microglia-like cells using genetic code expansion technology via site-specific protein engineering. The strategy integrates orthogonal genetic translation machinery in hPSCs, enabling temporal control of ETV2 expression and endothelial differentiation in h…
- OpenAlex · Published · First archived
UAV-Induced Measurement Bias in Air Pollution Sensing: A Physics-Informed Framework for Characterization, Sensor Placement, and Correction ↗
Unmanned aerial vehicles (UAVs) offer flexible, three-dimensional access for air pollution monitoring, but rotor-induced aerodynamic disturbance can bias onboard sensor readings, an effect not yet well characterized for multi-rotor platforms. This paper presents a physics-informed framework unifying rotor wake characterization, turbulence zone classification, pollutant sensitivity analysis, sensor placement strategy, and bias correction into one design tool. Grounded in actuator disk momentum theory and literature-constrained relationships, it predicts or bounds measurement bias across nine po…
- OpenAlex · Published · First archived
Detecting falsified lane-changing behavior in connected automated vehicles using physics-guided neural networks ↗
As connected automated vehicles become integrated into modern transportation systems, cybersecurity vulnerabilities increasingly threaten traffic operations and safety. Falsified lane-changing (LC) behavior, induced by cyberattacks such as false data injection, can disrupt proper decision-making and degrade system performance. This study proposes a framework for detecting abnormal LC decisions under cyberattack. The framework comprises two modules: (i) LC decision prediction and (ii) detection of falsified behavior. For LC prediction, this study proposes a physics-guided neural network (PGNN)…
- OpenAlex · Published · First archived
An international patient survey of RYR1-related diseases: The patient perspective on clinical trial participation ↗
Background and objective RYR1 -related diseases ( RYR1 -RD) are a group of genetic conditions characterized by early-onset muscle weakness, causing functional impairments. An increasing number of clinical trials is on the horizon. This study aims to improve trial readiness by characterizing the patient perspective on clinical trial participation. Methods In collaboration with RYR1 -RD patients and patient representatives we adapted an existing facioscapulohumeral muscular dystrophy (FSHD) survey and conducted the resulting international patient survey in 2025. We used descriptive statistics to…
- OpenAlex · Published · First archived
Complete genome sequence of Photobacterium damselae strain HNDF01 isolated from diseased Plectropomus leopardus in Hainan, China ↗
ABSTRACT We report the complete genome sequence of Photobacterium damselae subsp. damselae strain HNDF01, isolated from diseased Plectropomus leopardus in Hainan, China. The genome consists of two circular chromosomes (4,174,829 bp) and one plasmid (160,669 bp), encoding 3,753 protein-coding genes, 217 tRNAs, 47 rRNAs, and 10 sRNAs.
- OpenAlex · Published · First archived
The haplotype-resolved, chromosome-scale genome assembly of the hexaploid Magnolia wufengensis provides valuable insights into genome evolution and the biosynthesis genes for flower color and fragrance ↗
Magnolia wufengensis is a newly discovered species within the Magnoliaceae family. This tree is notable for its attractive fragrance and striking red flowers. Although M. wufengensis has significant ecological and ornamental value, a lack of genomic resources hindered use and protection of this tree. Here, a high-quality, haplotype-resolved chromosome-scale genome assembly of 11.98 Gb was generated, comprising 114 pseudochromosomes. Genome duplication analysis indicated that the hexaploid formation occurred approximately 6.8 million years ago (MYA), which is later than the divergence time from…
- OpenAlex · Published · First archived
Sclerostin regulates bone morphogenetic protein ( BMP ) bioavailability through interactions with BMP complexes and fibrillin microfibrils ↗
Sclerostin (SOST) is a secreted glycoprotein that antagonizes Wnt and BMP signaling, however, the molecular mechanisms regulating its extracellular distribution and growth factor (GF) interactions remain poorly understood. Here, we identify fibrillin microfibrils as high-affinity extracellular binding partners of SOST. Recombinant SOST bound specifically to fibrillin-1 positive fibers in cell culture and localized near the bead region of purified tissue fibrillin microfibrils. Surface plasmon resonance (SPR) mapping revealed that SOST recognizes the N-terminal regions of fibrillin-1 and fibril…
- OpenAlex · Published · First archived
PhyRL-PINN: Full-scale adaptive physics-informed ship sideslip estimation via reinforcement-learning-guided parameter scheduling ↗
Estimating a navigation-derived proxy of the ground-referenced ship sideslip angle under real-sea conditions requires combining physical structure with data-driven flexibility. PhyRL-PINN is a physics-informed residual-regularized neural estimator with reinforcement-learning-guided coefficient scheduling. A reduced-order lateral-dynamics prior is retained, while an actor–critic scheduler infers regularized equivalent structural coefficients from causal measurement histories. Within each 12-s window, six coefficient vectors are inferred at consecutive 2-s subinterval endpoints for endpoint-cond…
- OpenAlex · Published · First archived
Toward sustainable DNA storage: Adaptive error-resilient encoding under biochemical constraints ↗
Synthetic DNA is increasingly recognized as a promising medium for sustainable digital data archiving, offering exceptional information density and long-term durability. However, practical implementation faces significant challenges due to the biochemical constraints of DNA molecules, such as the need for balanced GC content, avoidance of secondary structures, and resilience to synthesis and sequencing errors. In this work, we present an adaptive, error-resilient encoding protocol that integrates algebraic coding techniques with sequence-level biochemical constraints. The proposed protocol uti…
- OpenAlex · Published · First archived
Physics informed multiscale convolutional attention network for intelligent recognition of oil and gas pipeline leakage in ground penetrating radar data ↗
Oil and gas pipeline leakage poses substantial risks to safety and the environment. Ground-penetrating radar (GPR) offers unique advantages for early leakage detection, but current intelligent recognition methods face four bottlenecks: loss of reflection polarity, missing electromagnetic constraints, poor cross-view synergy across A/B/C tri-view data, and simulation-to-real distribution shift under data scarcity. This paper proposes PolMS-GPRNet, a physics-guided multi-scale convolutional attention network. The polarity-sensitive multi-scale attention module (PS-MSCA) explicitly preserves refl…
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