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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 ↗1346 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
Cell-line-derived and published transcriptomic signatures benchmarked against transcriptome-based clinical axes for neoadjuvant response prediction in breast cancer ↗
Abstract Motivation Signatures from cell-line drug screens are deployed to patient transcriptomes to predict response. In breast cancer this may re-encode routine clinical variables rather than drug-specific biology. Results We tested whether ten transcriptomic signatures, scored without refitting, add pathological complete response information beyond four transcriptome-derived axes in five neoadjuvant cohorts. The axes are proxies for proliferation, hormone-receptor status, HER2 and subtype, and alone reached an area under the receiver operating characteristic curve of 0.67–0.79, 0.67–0.77 in…
- OpenAlex · Published · First archived
Genetic Insights into Cumin (Cuminum cyminum L.): First Draft Genome Sequencing and Mining of SSR Markers ↗
Cumin (Cuminum cyminum L.) is a globally significant spice crop, highly valued for its distinctive aromatic volatile oil content and its natural drought tolerance. To accelerate molecular breeding for these traits, this paper presents the first de novo draft genome assembly of the widely cultivated Indian variety Gujarat Cumin 4 (GC-4), a cultivar known for its high yield. The genome was sequenced using a hybrid strategy, combining high-accuracy Ion S5 short reads with long-read PacBio sequencing technology to generate an initial draft genome resource. More than 69 million sequencing reads con…
- OpenAlex · Published · First archived
PRIZM: Combining Low-N Data and Zero-shot Models to Design Enhanced Protein Variants ↗
Abstract Motivation Machine learning has repeatedly shown the ability to accelerate protein engineering, but many approaches demand large amounts of robust, high-quality training data as well as substantial computational expertise. While large pre-trained models can function as zero-shot proxies for predicting variant effects, selecting the best model for a given protein property is often non-trivial. Results Here, we introduce Protein Ranking using Informed Zero-shot Modelling (PRIZM), a two-phase workflow that first uses a high-quality low-N dataset to identify the most suitable pre-trained…
- OpenAlex · Published · First archived
Inducing Enantioselectivity in Radiative Charge-Transfer Rates through Chiral Quantum Electrodynamic Fluctuations ↗
Abstract Chiral discrimination has long been an important yet challenging topic in chemistry and physics. In this work, we study how chiral light–matter interaction under weak coupling regime enhances enantioselectivity of chiral charge transfer (CT) rates. Based on the framework of macroscopic quantum electrodynamics and Marcus electron transfer theory, we predict that the degree of discrimination (S) of a single-molecule asymmetric radiative CT reaction can achieve −2.0 × 10–2 through the light–matter interactions between a silicon nanohelix and a helicene-based CT dye. Orientation dependenc…
- OpenAlex · Published · First archived
Probing protein structures in solution via concentration- and temperature-dependent small- and wide-angle x-ray scattering ↗
Understanding how biomolecules execute their functions requires knowledge not only of their static ground-state structures but also of the conformational dynamics, solvation, and intermolecular interactions that they sample under physiological conditions. High-resolution crystallography, the dominant source of atomic-resolution structures, captures the molecule within a rigid lattice that can favor particular conformations and is largely silent on the structural dynamics present in solution. Here, we develop temperature-dependent small- and wide-angle x-ray scattering as a probe of biomolecula…
- OpenAlex · Published · First archived
nHOTAIRM1 scaffolds ANXA11-dependent assemblies to drive axonal mRNA localization in human motor neurons ↗
Abstract Long noncoding RNAs (lncRNAs) are well recognized as regulators of neuronal development and function, yet their integration into canonical axonal transport pathways, an essential component of spatial gene regulation in highly polarized cells, remains incompletely defined. It is still unclear to what extent individual lncRNAs confer cargo selectivity and couple discrete mRNA cohorts to established transport machineries. Here we identify a cytoplasmic role for the neuronal isoform of the lncRNA HOTAIRM1 ( nHOTAIRM1 ) in shaping the axonal RNA landscape of human induced pluripotent stem…
- OpenAlex · Published · First archived
A physics-informed method for joint forecasting of heat load and battery surface temperature in heating stations integrating photovoltaic generation, battery energy storage, and heat pumps ↗
Accurate joint forecasting of heat load and battery surface temperature is critical for reliable operation of heating stations that integrate photovoltaic generation, battery energy storage, and heat pumps in mountainous townships. These two targets are dynamically coupled because heat demand affects heat pump operation, while heat pump power consumption influences battery charging/discharging behavior and heat generation. However, existing methods either predict them independently or rely on data-driven multi-task learning, which ignores cross-system coupling and thermodynamic consistency. To…
- OpenAlex · Published · First archived
Extended Reality for Image-Guided Small Animal Surgery: Current Evidence, Clinical Applications, and Future Directions ↗
Image-guided surgery has become an integral component of modern veterinary surgery using advanced imaging modalities, such as computed tomography, magnetic resonance imaging, ultrasonography, and fluoroscopy. Recently, extended reality (XR) technologies have emerged as promising tools to enhance image-guided surgical procedures by improving three-dimensional anatomical understanding, surgical navigation, and intraoperative decision-making. Although XR has gained considerable attention in human surgery, its application in veterinary surgery remains at an early stage. This narrative review aimed…
- OpenAlex · Published · First archived
Physics-informed neural networks for thermal spreading of multilayer multichip power modules ↗
Efficient thermal management in multilayer, multi-source power modules remains a critical barrier to advancing high-performance electronic systems. Analytical models are limited to highly simplified geometries, while finite volume method (FVM) requires extensive meshing and prohibitive computational cost for iterative design exploration. Here, we present a physics-informed neural network (PINN) integrated with a Gaussian process (GP) surrogate to enable mesh-free, physically consistent thermal prediction and rapid design optimization. The PINN achieves prediction errors below 2.4% for single-s…
- OpenAlex · Published · First archived
Benchmarking imputation methods on real-world clinical time series with simulated spatio-temporal missingness ↗
Abstract Previous studies evaluating imputation methods on clinical time series do not jointly account for spatial (e.g., across features) and temporal (across time) structures in missingness. We present a simulation model that induces realistic spatio-temporal missingness in three real-world clinical datasets by sampling from Markov chains. A variety of imputation methods including last observation carried forward (LOCF), linear interpolation, and spatio-temporal autoencoder (STAE) are applied to fill these missingness patterns. Finally, we evaluate the influence of time series imputations on…
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Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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