Pings

How can deep learning architectures be designed to improve generalization under limited or noisy training data while maintaining robustness and interpretability?

  Deep learning models have achieved remarkable performance across domains such as computer vision, natural language processing, and scientific modeling. However, challenges remain in areas including generalization beyond training distributions, interpretability of learned representations, and robustness to noisy or limited datasets.  I am particularly interested in understanding which architectural innovations, training strategies, or theoretical insights have shown the most promise in...

Role of humanized immune system mice in to study the infectious and systemic inflammatory disease.

Whether the humanized immune system (HIS) mice help developing therapeutic interventions against infectious and inflammatory diseases? Whether HIS mice may revolutionize the translational biomedical research 

How does STAT3 contribute to intestinal mucosal barrier function, particularly during mucosal repair after injury?

Elucidating the role of STAT3 in intestinal epithelial regeneration and barrier integrity is critical for understanding IBD pathogenesis and tissue recovery. Key aspects include: 1.Epithelial-specific vs. immune-cell STAT3 signaling in wound healingDownstream targets (e.g., mucins, 2.tight junction proteins) mediating barrier protectionContext-dependent effects: protective versus pro-inflammatory roles 3.Insights could inform therapeutic strategies for mucosal healing. Relevant diagrams or...

No threshold approach in the risk assessment of genotoxic carcinogen. Is it still well supported by current knowledge of carcinogenesis?

No threshold approach is routinely applied in the risk assessment of genotoxic carcinogens. How this approach is supported by data? Isn´ t it somewhat obsolete?

What deep learning strategies best balance accuracy and interpretability in medical image segmentation for disease progression analysis?

Medical imaging (CT/MRI) segmentation is vital for tracking disease, but black-box models reduce clinical trust. Methods like explainable AI (XAI), uncertainty quantification, and hybrid modeling may bridge this gap. What approaches are most promising? 

Can we consider that epidrugs can constitute a good therapeutic strategy against cancer diseases?

Recently, it has been demonstrated that epigenetic perturbations are mainly involved in cancer development. Can we consider that epidrugs can constitute a good therapeutic strategy against cancer diseases ?

What are the current hot topics in oncology, and where is the future of cell, immune, and small molecule therapies headed?

Beyond established CAR-T and checkpoint inhibitors, what emerging trends (e.g., protein degraders, AI-driven drug discovery, off-the-shelf cell therapies) are shaping the next decade of cancer treatment? Which modalities show the most promise for solid tumors?

Why is the ammonia/ammonium concentration highly increased during storage of human urine?

Hydrolysis of urine Why is the ammonia/ammonium concentration highly increased during storage of human urine?

What are the current hot topics in the study of critical points during the process of cell mutation and development into tumors? How to conduct in-depth research on the future use of AI?

Tumorigenesis is not a linear accumulation of mutations but rather a dynamic process punctuated by critical transition points—windows during which normal cells cross irreversible thresholds toward dysplasia, carcinoma in situ, and ultimately invasive malignancy. Understanding the molecular and ecological drivers of these “tipping points” is fundamental to early interception and prevention. I would like to ask the cancer biology and computational oncology community: Which specific transition...

Do you think plant-based foods are really healthier than meat?