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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 ↗1706 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
Quantum correlations of tripartite mixed states in the black hole quantum atmosphere ↗
Abstract We investigate quantum state texture, genuine multipartite entanglement, and tripartite nonlocality of a tripartite mixed state in the black hole quantum atmosphere. By introducing the Hartle-Hawking local temperature into the Bogoliubov coefficients, we characterize the influence of the local Hawking effect on both physically accessible and inaccessible reduced states. We find that the extrema of these three quantities all lie in the same near horizon region and shift outward with increasing local Hawking temperature, coinciding with the peak region of the local Hawking temperature a…
- OpenAlex · Published · First archived
A causal machine learning framework for treatment personalization in clinical trials: application to ulcerative colitis ↗
Randomized controlled trials estimate average treatment effects, but treatment-response heterogeneity motivates personalized approaches that identify which patients benefit most from specific interventions. Causal machine learning methods offer a principled framework for estimating heterogeneous treatment effects and evaluating individualized treatment policies, yet their application to clinical trial data requires careful attention to the distinction between statistically detectable heterogeneity and improvements in decision performance. We present a causal machine learning framework that com…
- OpenAlex · Published · First archived
Comparison of CRISPR-Cas-Based Knockdown of Endogenous mRNA in Sensory Neurons ↗
Ribonucleic acid (RNA)-targeting clustered regularly interspaced short palindromic repeats-CRISPR-associated (CRISPR-Cas) systems enable modulation of gene expression without permanent genome modification, making them useful for sensitive cell types such as neurons. While CRISPR-Cas technologies have been most extensively applied and validated in primary hippocampal and cortical neurons, their use in sensory neurons remains largely unexplored. Sensory neurons are an established cellular model for studying axon growth and regeneration, pain mechanisms, sensory transduction, and neuron-environme…
- OpenAlex · Published · First archived
Error Bounds for Physics Informed Neural Networks in Generalized KdV Equations Placed on Unbounded Domains ↗
In this paper we study a rigorous setting for the numerical approximation via deep neural networks of the generalized Korteweg-de Vries (gKdV) model in one dimension, for subcritical and critical nonlinearities, and assuming that the domain is the unbounded real line. The fact that the model is posed on the real line makes the problem difficult from the point of view of learning techniques, since the setting required to model gKdV is structured on intricate oscillatory estimates dating from Kato, Bourgain and Kenig, Ponce and Vega, among others. Therefore, a first task is to adapt the setting…
- OpenAlex · Published · First archived
Quantum-inspired machine learning: a survey ↗
Quantum-inspired Machine Learning (QiML) is a burgeoning field, receiving global attention from researchers for its potential to leverage principles of quantum mechanics within classical computational frameworks. However, current review literature often presents a superficial exploration of QiML, focusing instead on the broader Quantum Machine Learning (QML) field. In response to this gap, this survey provides an integrated and comprehensive examination of QiML, exploring QiML's diverse research domains including tensor network simulations, dequantized algorithms, and others, showcasing recent…
- Europe PMC · Published · First archived
Item Response Theory to Evaluate Prolonged Grief Disorder in the DSM-5-TR Among Young Adults. ↗
Prolonged grief disorder (PGD) has been included in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, Text Revision (DSM-5-TR). However, the factor structure of PGD has been contested and few studies have tested competing models or assessed the item-level fit of PGD symptoms included in the DSM-5-TR using Item Response Theory (IRT). Therefore, this study addressed these gaps using IRT. The results indicated that a modified three-factor model of the PGD criteria demonstrated the best model fit. IRT analyses identified items in the PGD criteria provided little information o
- Europe PMC · Published · First archived
Curating the Fetal Genome: Experience of the ClinGen Prenatal Gene Curation Expert Panel (GCEP). ↗
Objective Expert prenatal focused gene-disease curation is necessary to accurately inform clinical care in the setting of rapidly expanding prenatal genomic sequencing. Methods An international Prenatal Gene Curation Expert Panel assembled and systematically reviewed genes asserted to be associated with prenatal hydrops, stillbirth, or severe anomalies using the ClinGen framework. Results The ClinGen Prenatal GCEP published evidence summaries for 63 disease relationships involving 61 genes with unique and clinically severe prenatally observed fetal phenotypes. Conclusion The ClinGen Prenatal G
- Europe PMC · Published · First archived
A course-based undergraduate research experience (CURE) using transposon-directed insertion-site sequencing (TraDIS) to identify genes that are essential for bacteriophage P1 propagation in Escherichia coli . ↗
Understanding gene function through forward genetic screens is foundational to microbial genetics. Here, we describe the design and implementation of a multi-week course-based undergraduate research experience (CURE) embedded within a third-year Microbial Genetics course, developed over three iterations in trimester 3 of 2023-2025. In this CURE, students construct a high-density Tn 5 transposon insertion library in Escherichia coli , challenge the library with bacteriophage P1, and use transposon-directed insertion-site sequencing (TraDIS) coupled with statistical analysis (edgeR) to identify
- Europe PMC · Published · First archived
The Stroop Color-Word Test - Short Form (SCWT-SF): Updated norms and validity in an Italian population sample. ↗
Objectives More than two decades ago, normative data for two interference indices (Error Interference Effect, EIE; Time Interference Effect, TIE) from a short form of the Stroop Color-Word Test (SCWT-SF) were established in Italy. The present study aimed to update the normative data for the Italian SCWT-SF by extending the assessment beyond interference indices to include completion times and error counts across the three task conditions, namely Word Reading (W), Color Naming (C), and Color-Word Interference (CW), and to provide evidence supporting its construct validity. Methods N = 317 healt
- Europe PMC · Published · First archived
The Next Frontier in Quantitative Co-Clinical Imaging to Advance Functional Precision Oncology. ↗
Precision oncology seeks to transform cancer treatment into one tailored for individual patients. Genomic alterations have been the dominant drivers of patient-specific therapeutic strategies. While genomic insights can guide treatment planning, genotype-directed therapies do not guarantee response to therapy. Functional confirmation of target expression, target engagement, and downstream biological effects is essential to defining therapeutic endpoints. Translational imaging can play a central role in closing the loop between genome and function to operationalize functional precision medicine
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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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