Mathematical model for preoperative identification of obstructed nasal subsites

The planning of experimental studies for evaluation of nasal airflow is particularly challenging given the difficulty in obtaining objective measurements in vivo. Although standard rhinomanometry and acoustic rhinometry are the most widely used diagnostic tools for evaluation of nasal airflow, they provide only a global measurement of nasal dynamics, without temporal or spatial details. Furthermore, the numerical simulation of nasal airflow as computational fluid dynamics technology is not validated. Unfortunately, to date, there are no available diagnostic tools to objectively evaluate the geometry of the nasal cavities and to measure nasal resistance and the degree of nasal obstruction, which is of utmost importance for surgical planning. To overcame these limitations, we developed a mathematical model based on Bernoulli's equation, which allows clinicians to obtain, with the use of a particular direct digital manometry, pressure measurements over time to identify which nasal subsite is obstructed. To the best of our knowledge, this is the first study to identify two limiting curves, one below and one above an average representative curve, describing the time dependence of the gauge pressure inside a single nostril. These upper and lower curves enclosed an area into which the airflow pattern of healthy individuals falls. In our opinion, this model may be useful to study each nasal subsite and to objectively evaluate the geometry and resistances of the nasal cavities, particularly in preoperative planning and follow-up

Mathematical model for preoperative identification of obstructed nasal subsites

La realizzazione di studi sperimentali per la valutazione dei flussi aerei nasali è particolarmente indaginosa, data la difficoltà di ottenere in vivo unaccurata misurazione degli stessi. Inoltre, sebbene la rinomanometria standard e la rinometria acustica rappresentino i metodi più utilizzati nella pratica clinica, esse forniscono solo una misura globale ed approssimativa dei flussi aerei nasali, senza definirne i particolari temporali o spaziali. Allo stesso modo gli studi sulla fluidodinamica computazionale rappresentano solo una simulazione numerica, ben lontana da quelle che sono le variabili anatomiche e fisiologiche delle cavità nasali. Pertanto, ad oggi, non esistono ancora strumenti diagnostici in grado di misurare oggettivamente la geometria delle cavità nasali, le resistenze ed il grado di ostruzione nei diversi sotto-siti nasali, elemento questultimo fondamentale per una corretta programmazione chirurgica. Allo scopo di superare i limiti della diagnostica standard abbiamo elaborato un modello matematico basato sullequazione di Bernoulli applicata alle cavità nasali di soggetti sani per lo studio dei gradienti pressori di vari sotto-siti nasali, che sono stati misurati grazie ad un particolare manometro digitale. Il nostro studio, unico in letteratura, ha identificato due curve limite che racchiudono unarea rappresentativa entro cui cadono i livelli normali di flusso in corrispondenza del vestibolo nasale. Il modello descritto potrebbe essere utile per studiare tutti i sotto-siti nasali sede di ostruzione ai fini di una corretta programmazione chirurgica e di un valido follow-up postoperatorio

Classical HLA-DRB1 and DPB1 alleles account for HLA associations with primary biliary cirrhosis.

Susceptibility to primary biliary cirrhosis (PBC) is strongly associated with human leukocyte antigen (HLA)-region polymorphisms. To determine if associations can be explained by classical HLA determinants, we studied Italian, 676 cases and 1440 controls, genotyped with dense single-nucleotide polymorphisms (SNPs) for which classical HLA alleles and amino acids were imputed. Although previous genome-wide association studies and our results show stronger SNP associations near DQB1, we demonstrate that the HLA signals can be attributed to classical DRB1 and DPB1 genes. Strong support for the predominant role of DRB1 is provided by our conditional analyses. We also demonstrate an independent association of DPB1. Specific HLA-DRB1 genes (*08, *11 and *14) account for most of the DRB1 association signal. Consistent with previous studies, DRB1*08 (P=1.59 7 10(-11)) was the strongest predisposing allele, whereas DRB1*11 (P=1.42 7 10(-10)) was protective. Additionally, DRB1*14 and the DPB1 association (DPB1*03:01; P=9.18 7 10(-7)) were predisposing risk alleles. No signal was observed in the HLA class 1 or class 3 regions. These findings better define the association of PBC with HLA and specifically support the role of classical HLA-DRB1 and DPB1 genes and alleles in susceptibility to PBC