Paper List
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PanFoMa: A Lightweight Foundation Model and Benchmark for Pan-Cancer
This paper addresses the dual challenge of achieving computational efficiency without sacrificing accuracy in whole-transcriptome single-cell represen...
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Beyond Bayesian Inference: The Correlation Integral Likelihood Framework and Gradient Flow Methods for Deterministic Sampling
This paper addresses the core challenge of calibrating complex biological models (e.g., PDEs, agent-based models) with incomplete, noisy, or heterogen...
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Contrastive Deep Learning for Variant Detection in Wastewater Genomic Sequencing
This paper addresses the core challenge of detecting viral variants in wastewater sequencing data without reference genomes or labeled annotations, ov...
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SpikGPT: A High-Accuracy and Interpretable Spiking Attention Framework for Single-Cell Annotation
This paper addresses the core challenge of robust single-cell annotation across heterogeneous datasets with batch effects and the critical need to ide...
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Unlocking hidden biomolecular conformational landscapes in diffusion models at inference time
This paper addresses the core challenge of efficiently and accurately sampling the conformational landscape of biomolecules from diffusion-based struc...
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Learning From Limited Data and Feedback for Cell Culture Process Monitoring: A Comparative Study
This paper addresses the core challenge of developing accurate real-time bioprocess monitoring soft sensors under severe data constraints: limited his...
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Cell-cell communication inference and analysis: biological mechanisms, computational approaches, and future opportunities
This review addresses the critical need for a systematic framework to navigate the rapidly expanding landscape of computational methods for inferring ...
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Generating a Contact Matrix for Aged Care Settings in Australia: an agent-based model study
This study addresses the critical gap in understanding heterogeneous contact patterns within aged care facilities, where existing population-level con...
Personalized optimization of pediatric HD-tDCS for dose consistency and target engagement
Southern University of Science and Technology | Brown University | University of Illinois Urbana-Champaign | University of Warwick | Carle Foundation Hospital
The 30-Second View
IN SHORT: This paper addresses the critical limitation of one-size-fits-all HD-tDCS protocols in pediatric populations by developing a personalized optimization framework that accounts for developmental anatomical variability and tissue conductivity uncertainty.
Innovation (TL;DR)
- Methodology First dual-objective optimization framework for pediatric HD-tDCS that generates personalized Pareto fronts balancing target intensity and focality, enabling systematic trade-off analysis.
- Methodology Introduction of two clinically actionable strategies: dose-consistency (enforcing fixed target intensity across individuals) and target-engagement (maximizing intensity under safety limits), both robust to conductivity variations.
- Biology First systematic quantification of depth-dependent tissue conductivity sensitivity: superficial targets dominated by scalp/bone conductivities (R² up to 0.85), while deep targets shaped by gray/white matter conductivities.
Key conclusions
- Conventional montages show significant age-dependent reductions in target intensity (p<0.05, FDR-corrected) and systematic sex differences mediated by scalp volume (mediation effect p<0.05).
- Optimized solutions Pareto-dominate conventional approaches, achieving 15-25% higher focality at matched intensity and 20-30% higher intensity at matched focality (Mann-Whitney U, p<0.001).
- Both optimization strategies remain robust under large conductivity variations (1,800 optimizations across 600 perturbed models), with sparse electrode configurations (<0.1 mA threshold) preserving performance (n.s., Mann-Whitney U).
Abstract: High-definition transcranial direct current stimulation (HD-tDCS) dosing in children remains largely empirical, relying on one-size-fits-all protocols despite rapid developmental changes in head anatomy and tissue properties that strongly modulate how transcranial currents reach the developing brain. Using 70 pediatric head models (ages 6–17) and commonly used cortical targets (primary motor cortex and left dorsolateral prefrontal cortex), our forward simulations find that standard montages produce marked age-dependent reductions in target electric-field intensity and systematic sex differences linked to tissue-volume covariation, underscoring the profound limitations of conventional uniform montages. To overcome these limitations, we introduce a developmentally informed, dual-objective optimization framework designed to generate personalized Pareto fronts summarizing the trade-off between electric-field intensity and focality. These subject-specific fronts reveal systematic performance improvements over conventional montages, yielding both higher focality at matched target intensity and higher intensity at matched focality. From these optimized solutions, we derive two clinically practical dosing prescriptions: a dose-consistency strategy that, for the first time, explicitly enforces fixed target intensity across individuals to implicitly mitigate demographic effects, and a target-engagement strategy that maximizes target intensity under safety limits. Both strategies remain robust to large conductivity variations, and we further show that dense HD-tDCS solutions admit sparse equivalents without performance loss under the target-engagement strategy. Across 1,800 optimizations in 600 conductivity-perturbed head models, we also find that tissue conductivity sensitivity is depth-dependent, with Pareto-front distributions for superficial cortical targets most influenced by gray matter, scalp, and bone conductivities, and those for a deep target predominantly shaped by gray and white matter conductivities. Together, these results establish a principled framework for pediatric HD-tDCS planning that explicitly accounts for developmental anatomy and physiological uncertainty, enabling reliable and individualized neuromodulation dosing in vulnerable pediatric populations.