Researchers present ten cutting-edge anti-aging strategies—from cellular reprogramming and senolytics to AI-driven drug discovery—explaining mechanisms and therapeutic aims across models and interventions.

Key points

• Partial in vivo reprogramming with Yamanaka factors restores tissue function and extends lifespan in mice.
• Senolytic cocktail dasatinib + quercetin reduces inflammation and improves joint function in osteoarthritis patients.
• AI-driven screening by Insilico Medicine identifies novel senolytic compounds in under two years.

Why it matters: These breakthroughs collectively offer scalable, mechanism-based strategies for reversing cellular aging and extending human healthspan beyond existing symptomatic treatments.

Inonu University researchers apply four machine learning algorithms—Random Forest, SVM, XGBoost and KNN—to complete blood count parameters to predict polycythaemia vera. After balancing the dataset with SMOTE and training on hemoglobin, hematocrit, white cell and platelet values, the XGBoost model attains an area under the curve of 0.99 and 94% accuracy, demonstrating AI’s potential to reduce reliance on expensive diagnostics like JAK2 mutation assays and bone marrow biopsy.

Key points

• XGBoost model classifies PV with 0.99 AUC and 94% accuracy based on CBC features.
• SMOTE oversampling addresses 82:1402 class imbalance before 80:20 train-test split.
• PLT contributed 42.4% to model predictions, highlighting platelet count’s diagnostic value.

Why it matters: This study shows that machine learning on routine CBC can screen polycythaemia vera accurately, cutting diagnostic costs and invasiveness.

The U.S. administration directs agencies to review and remove AI regulations that hamper innovation across sectors, while emphasizing worker benefits, ideological neutrality in AI outputs, and preventing foreign exploitation of U.S. AI infrastructure, including through expanded data center projects.

Key points

• President signs three executive orders directing a national AI Action Plan.
• Plan outlines three pillars: innovation acceleration, infrastructure build-out, and international AI security leadership.
• Stargate collaboration pledges 4.5 GW of new U.S. AI data center capacity to secure domestic compute resources.

Why it matters: By prioritizing deregulation and infrastructure investment, this policy could accelerate U.S. AI leadership, shaping global competitiveness and security norms.