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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 ↗1310 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
Structural and Functional Consequences of Arg512 Mutations in Methyl-CpG-Binding Domain Protein 4 ↗
Methyl-CpG-binding domain protein 4 (MBD4) is a base excision repair glycosylase that removes the thymine of a T:G mispair. If left unrepaired, these mismatches can cause C>T transitions. Human MBD4 uses an arginine finger, R468, to flip the mispaired thymine into its active site and to stabilize the orphaned guanine. MBD4 also possesses a second highly conserved arginine, R512, in close proximity to R468, whose role remains unknown despite an R512W mutation catalogued in colorectal cancers and an R512Q mutation reported in Myelodysplastic Syndromes. Here, we investigate the structural and fun…
- OpenAlex · Published · First archived
Physics-regularized deep learning for mining method selection in computational geomechanics ↗
Selecting an appropriate mining method for fractured “three-soft” ore bodies, with soft ore, soft hanging wall, and soft footwall, is a safety-critical artificial-intelligence application in computational geomechanics. Existing multi-criteria decision-making (MCDM) methods are limited by subjective weighting, linear additive assumptions, and weak use of numerical simulation outputs. This study develops a Physics-Regularized Transformer (PRT) artificial-intelligence framework for underground mining method selection. The framework integrates type-aware tabular embedding, a physics-regularized at…
- OpenAlex · Published · First archived
Large-scale genome re-annotation uncovers pathogen-specific lncRNA regulators of fungal growth and virulence ↗
Invasive fungal infections pose a serious global health threat. Although core cellular processes are broadly conserved across fungi, only a small fraction of known species cause severe human disease, suggesting that pathogenicity may depend in part on pathogen-specific regulators. However, such elements remain poorly understood because they often lack recognizable homologs, limiting accurate annotation and functional characterization. Here, using the invasive mold Aspergillus fumigatus as a model, we combined transcriptome-guided re-annotation with functional screening to identify previously u…
- OpenAlex · Published · First archived
Integrated Multi-Omics Characterization of WASHC2C Reveals Cancer-Specific Molecular, Clinical, Immune, and Cellular Associations ↗
WASHC2C encodes a WASH-complex scaffold implicated in actin remodeling, endosomal organization, and intracellular trafficking, yet its cancer-specific molecular and clinical relevance remains insufficiently defined, particularly in the context of the closely related paralogue WASHC2A. We performed an integrated pan-cancer multi-omics analysis incorporating transcriptomic and protein-level evidence, clinicopathological and survival associations, genomic and epigenetic alterations, pathway activity, gene-set enrichment, immune features, immunotherapy-related observations, and single-cell functio…
- OpenAlex · Published · First archived
The Moderating Effect of Gender on the Relationship Between Artificial Intelligence Usage, Behavioral Intentions, and Academic Engagement in Mathematics Education ↗
In the age of technology, where the educational sphere and strategic advancements drive development, it is essential to understand the complex nature of gender and implement innovative tools to foster an inclusive learning environment and empower every learner. This study examines the moderating effect of gender on the relationships among Artificial Intelligence (AI) use, behavioral intentions, and academic engagement in mathematics education. Using a cross-sectional design, the study sampled 328 mathematics undergraduates from public universities in southwestern Nigeria. A structured online q…
- OpenAlex · Published · First archived
Making Healthcare AI Explainable: A Structured Review of Methods and Clinical Practice ↗
Artificial intelligence is rapidly transforming modern medicine, providing powerful tools to assist clinicians. However, the most accurate models are opaque, and their limited interpretability hinders clinical adoption and raises regulatory concerns. Explainable Artificial Intelligence (XAI) aims to make these models’ decisions comprehensible. Despite its rapid growth and the many reviews already published, aspects such as the rigor of explanation evaluation, clinician involvement, and the use of large language models to generate explanations appear to have received limited attention. This art…
- OpenAlex · Published · First archived
Digital analysis of spatial expression of stromal fibroblast activation protein alpha (FAP) in DCIS ↗
INTRODUCTION: The presence of non-progressing ductal carcinoma in situ (DCIS) cases has raised concerns of overtreatment, necessitating comprehensive risk prediction. The tumour microenvironment, especially cancer-associated fibroblasts (CAFs), plays a key role in DCIS progression. Fibroblast activation protein alpha (FAP), a CAF biomarker, has shown prognostic potential, but its clinical significance and spatial organization in DCIS remain rarely discussed. METHODS: In this study, we employed a digital pathology pipeline to quantify stromal FAP expression and map its spatial organization. A t…
- OpenAlex · Published · First archived
Repurposing landscape of N-acetylcysteine: A scoping review of reviews toward clinical translation ↗
Background Growing interest in drug repurposing and oxidative stress has heightened attention on N‑acetylcysteine (NAC). Despite the abundance of reviews across diverse clinical domains, clinical translation remains limited. This review seeks to map the existing evidence, identify critical gaps, and outline priorities for future research. Methods Five databases were systematically searched to identify relevant reviews based on predetermined inclusion and exclusion criteria. Comprehensive data extraction enabled meaningful evidence mapping. To enhance rigor, critical appraisal was conducted usi…
- OpenAlex · Published · First archived
Reference Genome Choice Shapes RNA-Seq Quantification and Downstream Interpretation in Chinese Breast Cancer Patients ↗
Background/Objectives: Reference genome choice can introduce systematic bias into cancer transcriptomic analyses, particularly for populations underrepresented in standard references. However, its impact on downstream biological interpretation remains insufficiently characterized. Methods: We compared GRCh38, T2T-CHM13, and the East Asian-matched T2T-YAO using bulk RNA-seq data from 148 Chinese breast cancer patients and single-cell RNA-seq data comprising 65,968 cells from paired primary tumors and lymph node metastases. We assessed reference-dependent differences in read mapping, gene expres…
- OpenAlex · Published · First archived
A Physics-Constrained Probabilistic Forecasting Method for Wind–PV–Load Systems Under Extreme Weather Based on Extreme-Event Awareness and Uncertainty Calibration ↗
With the increasing penetration of renewable energy into power systems, wind and photovoltaic (PV) power generation exhibit substantial uncertainty due to meteorological variability, which becomes more pronounced under extreme weather conditions. The scarcity of extreme samples, complex dependencies among wind power, PV power, and load, and degraded prediction-interval reliability further increase the difficulty of probabilistic forecasting. To address these challenges, this study proposes a physics-constrained probabilistic forecasting framework for wind–PV–load systems under extreme weather.…
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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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