Understanding the role of different age groups in disease transmission is crucial for designing effective intervention strategies. Age-structured epidemic models capture these dynamics through contact matrices, which describe interactions between subpopulations. However, empirical contact estimation is inherently prone to measurement noise, as survey responses vary systematically across age groups and are collected through heterogeneous channels. This imprecision introduces substantial uncertainty into epidemic predictions. In this study, we present the Age Group Sensitivity Analysis (AGSA) framework for quantifying how structural perturbations in age-specific contact patterns propagate to epidemic outcomes. AGSA integrates age-stratified epidemic models with Latin Hypercube Sampling (LHS) and Partial Rank Correlation Coefficient (PRCC) analysis to perform a systematic sensitivity assessment of age-specific interactions. A key novelty of our approach is a sensitivity aggregation technique that attributes the overall dispersion in epidemic outcomes to individual age groups. By identifying the groups whose contact variations contribute most to model variability, AGSA highlights where refined empirical data are most urgently needed. This provides a principled basis for targeted data collection efforts, thereby constraining epidemic forecasts and supporting the robust evaluation of age-specific public health interventions.

Bioactive peptide coatings modulate cell–implant interactions on TiO₂ surfaces; however, most molecular-level studies of peptide adsorption are performed under low or fixed ionic conditions. Physiological environments exhibit non-negligible and variable electrolyte concentrations, so understanding ionic strength effects is crucial for designing effective peptide-functionalized titanium implants. An amorphous TiO₂ surface was generated from a crystalline rutile precursor and simulated in explicit water using classical molecular dynamics at nine NaCl concentrations. For each condition, seven independent simulations with different initial peptide placements/orientations were performed. Peptide backbone RMSD, minimum peptide–surface distance, and adsorption time ratio were analysed as functions of NaCl concentration. For both peptides, backbone RMSD remained stable and showed no statistically significant correlation with NaCl concentration. KRSR exhibited a significant increase in minimum distance with increasing NaCl concentration and a significant decrease in adsorption time ratio, indicating reduced persistence of close surface contact at higher salt levels. In contrast, RGD showed no significant dependence of either minimum distance or adsorption time ratio within the tested range. Within the limits of the applied force-field MD framework and the investigated NaCl range, KRSR adsorption on TiO₂ is more sensitive to ionic strength than RGD, consistent with the stronger electrostatic contribution for the net-positively charged KRSR motif.

This study examines how diabetes mellitus and physiological aging influence the nanomechanical behavior of rat rib cortical bone using combined static and dynamic nanoindentation. Ribs from young control, old, and streptozotocin-induced diabetic rats were analyzed to quantify both intrinsic and frequency-dependent mechanical properties. Static nanoindentation revealed markedly higher hardness and elastic modulus in the diabetic group (0.47 ± 0.22 GPa and 9.53 ± 3.03 GPa, respectively) compared to controls (0.11 ± 0.03 GPa and 3.21 ± 0.51 GPa; p < 0.001). The modulus-to-hardness ratio, an indicator of fracture toughness, was reduced from 30.34 in controls to 20.45 in diabetics, suggesting increased stiffness but greater brittleness. Dynamic nanoindentation (0–4.5 Hz) demonstrated significant aging-related changes in the storage and loss moduli (p < 0.001), while the loss factor (tan δ < 1) and viscosity remained similar across groups, indicating predominantly solid-like behavior. These results show that diabetes stiffens bone tissue through matrix-level alterations, whereas aging primarily affects its viscoelastic damping capacity. The combined static–dynamic nanoindentation protocol provides a robust framework for distinguishing disease- and age-related bone degradation at the tissue scale. Translationally, the findings help explain why bones in diabetic or elderly individuals may fracture despite normal mineral density, underscoring the need to assess bone quality beyond conventional densitometry.