Preprint Watch

D1/D5 Receptor Activation Promotes Long-Term Potentiation and Synaptic Tagging/Capture in Hippocampal Area CA2

Leave a Comment / bioRxiv, Normal Science /

URL https://www.biorxiv.org/content/10.1101/2025.06.01.657216v2.full.pdf Stage Normal Science Paradigm framing Long-term potentiation (LTP) as a cellular model of learning and memory Highlights This preprint investigates the effects of dopamine D1/D5 receptor activation on synaptic plasticity in the hippocampal CA2 region, an area implicated in social memory. While the broader paradigm of LTP as a correlate of learning and […]

D1/D5 Receptor Activation Promotes Long-Term Potentiation and Synaptic Tagging/Capture in Hippocampal Area CA2 Read More »

MARLOWE: Taxonomic Characterization of Unknown Samples for Forensics Using De Novo Peptide Identification

Leave a Comment / bioRxiv, Normal Science /

URL https://www.biorxiv.org/content/10.1101/2024.09.30.615220v2.full.pdf Stage Normal Science Paradigm framing The preprint operates within the paradigm of forensic proteomics and metaproteomics, specifically focusing on taxonomic characterization of unknown biological samples using mass spectrometry data. Highlights This preprint presents MARLOWE, a new computational tool for taxonomic characterization using de novo peptide sequencing combined with a statistical approach. While it

MARLOWE: Taxonomic Characterization of Unknown Samples for Forensics Using De Novo Peptide Identification Read More »

FoldMark: Safeguarding Protein Structure Generative Models with Distributional and Evolutionary Watermarking

Leave a Comment / bioRxiv, Normal Science /

URL https://www.biorxiv.org/content/10.1101/2024.10.23.619960v6.full.pdf Stage Normal Science Paradigm framing The preprint operates within the dominant paradigm of protein structure prediction and design, heavily influenced by recent advancements in machine learning, particularly deep learning models like AlphaFold. It acknowledges the transformative impact of these models while addressing emerging concerns within this paradigm. Highlights This preprint presents FoldMark, a

FoldMark: Safeguarding Protein Structure Generative Models with Distributional and Evolutionary Watermarking Read More »

Synthetic Serum Markers Enable Noninvasive Monitoring of Gene Expression in Primate Brains

Leave a Comment / bioRxiv, Normal Science /

URL https://www.biorxiv.org/content/10.1101/2025.06.01.657212v1.full.pdf Stage Normal Science Paradigm framing The current paradigm is the use of invasive methods, such as positron emission tomography (PET), magnetic resonance imaging (MRI) or, in some cases, electrophysiology, to monitor gene expression in the primate brain, especially long-term. Highlights The preprint presents Released Markers of Activity (RMAs) as an innovative approach for

Synthetic Serum Markers Enable Noninvasive Monitoring of Gene Expression in Primate Brains Read More »

Non-canonical enhancers control gene expression and cell fate in human pluripotent stem cells

Leave a Comment / bioRxiv, Normal Science /

URL https://www.biorxiv.org/content/10.1101/2025.06.01.657118v1.full.pdf Stage Normal Science Paradigm framing The preprint operates within the dominant paradigm of gene regulation, where enhancers play a crucial role in controlling gene expression. It specifically focuses on enhancers in human-induced pluripotent stem cells (hiPSCs). Highlights This research refines the existing understanding of enhancers by identifying a class of “non-canonical enhancers” that

Non-canonical enhancers control gene expression and cell fate in human pluripotent stem cells Read More »

The QETRA Protocol: Pioneering Quantum Eavesdropping Detection with Classical SVM

Leave a Comment / Model Drift, Normal Science, Research Square /

URL https://assets-eu.researchsquare.com/files/rs-6786392/v1_covered_8851b04d-a5b5-4bfb-a3a9-b8900a9d2e18.pdf?c=1748865121.pdf Stage Normal Science / Model Drift Paradigm framing Quantum cryptography, specifically Quantum Key Distribution (QKD), currently operates under the paradigm of detecting eavesdropping through quantum bit error rate (QBER) analysis, as exemplified by the BB84 protocol. Highlights This preprint presents the QETRA protocol, which introduces a novel approach to eavesdropping detection within the

The QETRA Protocol: Pioneering Quantum Eavesdropping Detection with Classical SVM Read More »

Sentiment Simulation using Generative AI Agents

Leave a Comment / arXiv, Model Revolution /

URL https://arxiv.org/pdf/2505.22125.pdf Stage Model Revolution Paradigm framing The preprint challenges the existing paradigm of sentiment analysis as retrospective classification based on surface-level linguistic features. It proposes a shift towards prospective and dynamic sentiment simulation grounded in psychological principles, utilizing generative AI agents embodied with psychographic profiles. Highlights This preprint presents a compelling case for a

Sentiment Simulation using Generative AI Agents Read More »

Dust Budget Crisis in Little Red Dots

Leave a Comment / arXiv, Model Crisis, Model Drift /

URL https://arxiv.org/pdf/2505.22600.pdf Stage Model Drift / Model Crisis Paradigm framing The preprint challenges the prevailing paradigm that Little Red Dots (LRDs) are heavily dust-reddened Active Galactic Nuclei (AGNs). The current paradigm, based on their red spectra, suggests high extinction levels (Av ~ 3). Highlights The authors present evidence suggesting a “dust budget crisis,” where the

Dust Budget Crisis in Little Red Dots Read More »

Geospatial Foundation Models to Enable Progress on Sustainable Development Goals

Leave a Comment / arXiv, Normal Science /

URL https://arxiv.org/pdf/2505.24528.pdf Stage Normal Science Paradigm framing Artificial Intelligence, Earth Observation, Sustainable Development Goals, Foundation Models Highlights The preprint focuses on evaluating and benchmarking existing Foundation Models (FMs) within the established paradigm of applying AI to Earth Observation (EO) data for addressing Sustainable Development Goals (SDGs). It introduces SustainFM, a novel benchmarking framework, and presents

Geospatial Foundation Models to Enable Progress on Sustainable Development Goals Read More »

Interictal Epileptiform Discharge Detection Using Probabilistic Diffusion Models and AUPRC Maximization

Leave a Comment / medRxiv, Normal Science /

URL https://www.medrxiv.org/content/10.1101/2025.05.23.25328198v2.full.pdf Stage Normal Science Paradigm framing The paradigm is automated interictal epileptiform discharge (IED) detection in electroencephalography (EEG) using artificial intelligence. The current model accepts that deep learning is a highly effective method but notes limitations due to class imbalance in datasets and a focus on metrics that don’t directly translate to clinical utility.

Interictal Epileptiform Discharge Detection Using Probabilistic Diffusion Models and AUPRC Maximization Read More »