Researchers at Goethe University Frankfurt conducted a bibliometric study of 29,192 AI-in-medicine papers from 1969 to 2022, using the NewQIS platform and density-equalizing map procedures to chart global publication trends, socio-economic correlations, and equity patterns across countries.

Key points

• Analyzed 29,192 AI-in-medicine articles from Web of Science (1969–2022) using NewQIS bibliometric methodologies.
• Applied density-equalizing cartogram projections to visualize country-level research output and citation patterns.
• Performed Spearman correlations and regression residual analysis with GDP, GII, and AI readiness indices to assess global equity and disparities.

Why it matters: Mapping the global AI-in-medicine landscape exposes economic and innovation-driven inequities, guiding policies to foster inclusive research and deployment in underserved regions.

A cross-sectional study at a Turkish university hospital utilized the MAIRS-MS and OTOC scales to quantitatively assess 195 healthcare professionals’ readiness for medical AI and their openness to organizational change, revealing significant positive attitudes and demographic patterns in AI adoption readiness.

Key points

• Validated the four‐factor MAIRS-MS scale (cognitive, ability, vision, ethical) for measuring medical AI readiness among 195 hospital staff.
• Applied EFA and CFA to confirm construct validity, achieving RMSEA=0.087 and CFI=0.96 for MAIRS-MS and RMSEA=0.00 and CFI=1.00 for OTOC.
• Used SEM to model relationships, finding a low but significant positive correlation (r=0.236) between AI readiness and openness to organizational change.

Why it matters: This study demonstrates that targeted training and change management can leverage healthcare workers’ positive AI readiness to accelerate safe and effective AI integration in clinical practice.

Researchers from Swiss and Italian institutions demonstrate in cell and animal models that Haenkenium, an extract from Salvia haenkei, exhibits superior senolytic activity compared to resveratrol and quercetin. By selectively clearing senescent cells, Haenkenium enhances skin elasticity, metabolic functions, and vascular performance, positioning it as a promising candidate for next-generation anti-aging therapies.

Key points

• Haenkenium shows dose-dependent clearance of senescent cells in skin, liver, and vascular endothelium models.
• It outperforms resveratrol and quercetin by reducing inflammatory markers and restoring tissue function without significant side effects.
• Animal studies reveal multi-tissue benefits, including improved skin elasticity, metabolic health, and vascular performance.

Why it matters: Haenkenium’s superior senolytic potency could shift age-related therapy paradigms by enabling more effective and targeted clearance of senescent cells.

Boeing Global Services delivers a structured tutorial on foundational AI methods—from linear regression and neural networks to Transformers—highlighting their mechanisms and applications in predictive modeling and autonomous systems.

Key points

• Linear regression fundamentals illustrating data-driven prediction via best-fit line modeling.
• Transformer architecture leveraging self-attention to capture long-range dependencies in sequences.
• Reinforcement learning agents optimizing decisions through reward-based trial-and-error interactions.

Gabrielle examines why ultra‐wealthy investors often bypass longevity science, analyzing perceived scientific uncertainties, cultural perceptions of aging, and philanthropic norms to shed light on funding gaps.

Key points

• Perception of aging as immutable leads many billionaires to prioritize traditional philanthropy over longevity research.
• High financial risks and long development timelines discourage investment in life‐extension technologies.
• Ethical concerns and legacy preferences further limit early funding for interventions targeting aging processes.

Why it matters: Unearthing barriers to funding longevity research is vital to mobilize capital towards breakthroughs that extend healthy human lifespan.