Fluid Mechanics in Dentinal Microtubules Provides Mechanistic Insights into the Difference between Hot and Cold Dental Pain

Dental thermal pain is a significant health problem in daily life and dentistry. There is a long-standing question regarding the phenomenon that cold stimulation evokes sharper and more shooting pain sensations than hot stimulation. This phenomenon, however, outlives the well-known hydrodynamic theory used to explain dental thermal pain mechanism. Here, we present a mathematical model based on the hypothesis that hot or cold stimulation-induced different directions of dentinal fluid flow and the corresponding odontoblast movements in dentinal microtubules contribute to different dental pain responses. We coupled a computational fluid dynamics model, describing the fluid mechanics in dentinal microtubules, with a modified Hodgkin-Huxley model, describing the discharge behavior of intradental neuron. The simulated results agreed well with existing experimental measurements. We thence demonstrated theoretically that intradental mechano-sensitive nociceptors are not “equally sensitive” to inward (into the pulp) and outward (away from the pulp) fluid flows, providing mechanistic insights into the difference between hot and cold dental pain. The model developed here could enable better diagnosis in endodontics which requires an understanding of pulpal histology, neurology and physiology, as well as their dynamic response to the thermal stimulation used in dental practices

Spatial and risk factor analysis of bovine viral diarrhoea (BVD) virus after the first-year compulsory phase of BVD eradication programme in Northern Ireland

Bovine viral diarrhoea virus (BVDV) causes bovine viral diarrhoea (BVD), which is a contagious pathogen that can have a significant economic impact on cattle industries. In Northern Ireland (NI), the compulsory phase of a BVD eradication programme was implemented in 2016. The aim of this retrospective population based study was to utilize herd-level data after the first year of the compulsory phase (March 2016–March 2017) to determine the spatial distribution and variation of BVDV, to identify clusters of infection, and to quantify some risk factors associated with BVD in NI. Global spatial clustering (autocorrelation) and local spatial hot-spot analyses were used to specify the clustering areas (hot- and cold-spot). A suite of multivariable logistic analyses was performed to estimate the associations of spatial and non-spatial factors (relating to herd characteristics) with the risk of being a BVDV positive herd. Final models were compared by evaluating the model fit and the ability to account for spatial autocorrelation in the study area. There were 17,186 herds included in the analysis. The herd-level prevalence of BVDV was 11.31%. Significant spatial clustering of BVDV positive herds was presented in the central region of NI. A mixed effects logistic model, with a spatial random effect term, was considered the best model. The final model showed that a positive BVDV status during the voluntary phase prior to the compulsory phase started (OR = 2.25; CI 95% = 1.85–2.73), larger herd size (OR = 6.19; CI 95% = 5.22–7.34 for herd size > 100 animals) and a larger number of positive nearest neighbours within 4 km radius (OR = 1.24; CI 95% = 1.05–1.47 for 8–9 neighbours and OR = 1.41; CI 95% = 1.20–1.65 for 10–12 neighbours) were significantly related to the risk of a herd being tested positive for BVDV. The clear spatial pattern from the local spatial clustering analyses could be used for targeted surveillance and control measures by focusing on the central region of NI.</p