Changes in nasal airflow and heat transfer correlate with symptom improvement after surgery for nasal obstruction

Surgeries to correct nasal airway obstruction (NAO) often have less than desirable outcomes, partly due to the absence of an objective tool to select the most appropriate surgical approach for each patient. Computational fluid dynamics (CFD) models can be used to investigate nasal airflow, but variables need to be identified that can detect surgical changes and correlate with patient symptoms. CFD models were constructed from pre- and post-surgery computed tomography scans for 10 NAO patients showing no evidence of nasal cycling. Steady-state inspiratory airflow, nasal resistance, wall shear stress, and heat flux were computed for the main nasal cavity from nostrils to posterior nasal septum both bilaterally and unilaterally. Paired t-tests indicated that all CFD variables were significantly changed by surgery when calculated on the most obstructed side, and that airflow, nasal resistance, and heat flux were significantly changed bilaterally as well. Moderate linear correlations with patient-reported symptoms were found for airflow, heat flux, unilateral allocation of airflow, and unilateral nasal resistance as a fraction of bilateral nasal resistance when calculated on the most obstructed nasal side, suggesting that these variables may be useful for evaluating the efficacy of nasal surgery objectively. Similarity in the strengths of these correlations suggests that patient-reported symptoms may represent a constellation of effects and that these variables should be tracked concurrently during future virtual surgery planning

Numerical evaluation of spray position for improved nasal drug delivery

Topical intra-nasal sprays are amongst the most commonly prescribed therapeutic options for sinonasal diseases in humans. However, inconsistency and ambiguity in instructions show a lack of definitive knowledge on best spray use techniques. In this study, we have identified a new usage strategy for nasal sprays available over-the-counter, that registers an average 8-fold improvement in topical delivery of drugs at diseased sites, when compared to prevalent spray techniques. The protocol involves re-orienting the spray axis to harness inertial motion of particulates and has been developed using computational fluid dynamics simulations of respiratory airflow and droplet transport in medical imaging-based digital models. Simulated dose in representative models is validated through in vitro spray measurements in 3D-printed anatomic replicas using the gamma scintigraphy technique. This work breaks new ground in proposing an alternative user-friendly strategy that can significantly enhance topical delivery inside human nose. While these findings can eventually translate into personalized spray usage instructions and hence merit a change in nasal standard-of-care, this study also demonstrates how relatively simple engineering analysis tools can revolutionize everyday healthcare. Finally, with respiratory mucosa as the initial coronavirus infection site, our findings are relevant to intra-nasal vaccines that are in-development, to mitigate the COVID-19 pandemic

Self-Organization and Complex Networks

In this chapter we discuss how the results developed within the theory of fractals and Self-Organized Criticality (SOC) can be fruitfully exploited as ingredients of adaptive network models. In order to maintain the presentation self-contained, we first review the basic ideas behind fractal theory and SOC. We then briefly review some results in the field of complex networks, and some of the models that have been proposed. Finally, we present a self-organized model recently proposed by Garlaschelli et al. [Nat. Phys. 3, 813 (2007)] that couples the fitness network model defined by Caldarelli et al. [Phys. Rev. Lett. 89, 258702 (2002)] with the evolution model proposed by Bak and Sneppen [Phys. Rev. Lett. 71, 4083 (1993)] as a prototype of SOC. Remarkably, we show that the results obtained for the two models separately change dramatically when they are coupled together. This indicates that self-organized networks may represent an entirely novel class of complex systems, whose properties cannot be straightforwardly understood in terms of what we have learnt so far.Comment: Book chapter in "Adaptive Networks: Theory, Models and Applications", Editors: Thilo Gross and Hiroki Sayama (Springer/NECSI Studies on Complexity Series

UBVRI Light curves of 44 Type Ia supernovae

We present UBVRI photometry of 44 Type la supernovae (SNe la) observed from 1997 to 2001 as part of a continuing monitoring campaign at the Fred Lawrence Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics. The data set comprises 2190 observations and is the largest homogeneously observed and reduced sample of SNe la to date, nearly doubling the number of well-observed, nearby SNe la with published multicolor CCD light curves. The large sample of [U-band photometry is a unique addition, with important connections to SNe la observed at high redshift. The decline rate of SN la U-band light curves correlates well with the decline rate in other bands, as does the U - B color at maximum light. However, the U-band peak magnitudes show an increased dispersion relative to other bands even after accounting for extinction and decline rate, amounting to an additional ∼40% intrinsic scatter compared to the B band

Large eddy simulations of airflow and particle deposition in pulsating bi-directional nasal drug delivery.

Chronic rhinosinusitis is a common disease worldwide, and the frequently prescribed nasal sprays do not sufficiently deliver the topical medications to the target sites so that the final treatment in severe cases is surgery. Therefore, there is a huge demand to improve drug delivery devices that could target the maxillary sinuses more effectively. In the present study, different particle diameters and device pulsation flow rates, mainly used in pulsating aerosol delivery devices such as the PARI SINUS (R), are considered to evaluate optimal maxillary sinus deposition efficiency (DE). Numerical simulations of the particle-laden flow using a large eddy simulation with a local dynamic k-equation sub-grid scale model are performed in a patient-specific nasal cavity. By increasing the pulsation flow rate from 4 l/min to 15 l/min, nasal DE increases from 37% to 68%. Similarly, by increasing the particle size from 1 mu m to 5 mu m, nasal DE increases from 34% to 43% for a pulsation flow rate of 4 l/min. Moreover, normalized velocity, vorticities, and particle deposition pattern in different regions of the main nasal cavity and maxillary sinuses are visualized and quantified. Due to the nosepiece placement in the right nostril, more particles penetrate into the right maxillary sinus than into the left maxillary sinus despite the maxillary ostium being larger in the left cavity. Lower pulsation flow rates such as 4 l/min improve the DE in the left maxillary sinus. The use of 3 mu m particles enhances the DE in the right maxillary sinus as well as the overall total maxillary drug delivery

Perturbed Developmental Serotonin Signaling Affects Prefrontal Catecholaminergic Innervation and Cortical Integrity.

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