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2065115
Regulatory element in fibrin triggers tension-activated transition from catch to slip bonds
Fibrin formation and mechanical stability are essential in thrombosis and hemostasis. To reveal how mechanical load impacts fibrin, we carried out optical trap-based single-molecule forced unbinding experiments. The strength of noncovalent A:a knob-hole bond stabilizing fibrin polymers first increases with tensile force (catch bonds) and then decreases with force when the force exceeds a critical value (slip bonds). To provide the structural basis of catch–slip-bond behavior, we analyzed crystal structures and performed molecular modeling of A:a knob-hole complex. The movable flap (residues γ 295 to γ 305) containing the weak calcium-binding site γ 2 serves as a tension sensor. Flap dissociation from the B domain in the γ -nodule and translocation to knob ‘A’ triggers hole ‘a’ closure, resulting in the increase of binding affinity and prolonged bond lifetimes. The discovery of biphasic kinetics of knob-hole bond rupture is quantitatively explained by using a theory, formulated in terms of structural transitions in the binding pocket between the low-affinity (slip) and high-affinity (catch) states. We provide a general framework to understand the mechanical response of protein pairs capable of tension-induced remodeling of their association interface. Strengthening of the A:a knob-hole bonds at 30- to 40-pN forces might favor formation of nascent fibrin clots subject to hydrodynamic shear in vivo.
A new method for predicting wind-driven rain catch ratios on building facades in urban residential areas using machine learning models
The distribution of wind-driven rain on building facades significantly affects their thermal performance and durability. Accurately and efficiently predicting the wind-driven rain catch ratio on wall surfaces is crucial for building performance evaluation. This study proposes a novel computational approach to rapidly predict the wind-driven rain catch ratio on urban building facades. A predictive model was developed using extensive numerical simulations combined with machine learning algorithms. Specifically, the model replaces traditional numerical simulations by learning the influence of wind field characteristics and building geometry on raindrop catch ratios across different sizes. The research results indicate that the machine learning models can effectively substitute conventional simulation methods for wind-driven rain predictions. Notably, the Artificial Neural Network model achieved a prediction accuracy comparable to numerical simulations (RMSE: 0.009, MAE: 0.006) while being over 300 times faster. The inlet wind speed at roof height emerged as the most influential feature, and the model exhibited strong generalization performance across varying wind directions. This method is simple, efficient, and well-suited to support wind-driven rain analysis, experimental measurements, and urban energy consumption studies in residential building contexts.
Knowledge and awareness of human papillomavirus (HPV) influence HPV vaccination uptake among the catch-up generation in Japan
Introduction Despite its importance for young women, the human papillomavirus (HPV) vaccination coverage remains low in Japan. Previous studies have examined behaviors related to HPV catch-up vaccination. Uniquely, this study aimed to investigate perceptions and factors influencing vaccination coverage among female university students in the catch-up program, focusing on both medical and non-medical undergraduates.Methods A web-based survey was conducted at Kochi University from January 16 to February 13, 2023, targeting female students born between April 2, 1997, and April 1, 2006. The survey collected demographic data and assessed knowledge of HPV infection, cervical cancer, and preventive measures. Chi-square tests and logistic regression analyses were used to identify differences between vaccinated and unvaccinated groups as well as factors related to HPV vaccination.Results Of the 310 participants, 39.0 % were vaccinated against HPV, 35.2 % were freshmen, and 75.2 % were in medical science programs. HPV vaccination was significantly associated with being in upper years of university (OR = 3.78–42.83), studying medical sciences (OR = 1.93), undergoing cervical cancer screening (OR = 4.04), and receiving free vaccination vouchers (OR = 2.03).Conclusion Knowledge and awareness of HPV and cervical cancer significantly contribute to higher vaccination uptake in the generation receiving catch-up vaccinations. Tailoring information and distributing free vaccination vouchers could enhance HPV vaccination rates and awareness in this group.