Particles in Exhaled Air (PExA): Clinical Uses and Future Implications.

Access to distal airway samples to assess respiratory diseases is not straightforward and requires invasive procedures such as bronchoscopy and bronchoalveolar lavage. The particles in exhaled air (PExA) device provides a non-invasive means of assessing small airways; it captures distal airway particles (PEx) sized around 0.5-7 µm and contains particles of respiratory tract lining fluid (RTLF) that originate during airway closure and opening. The PExA device can count particles and measure particle mass according to their size. The PEx particles can be analysed for metabolites on various analytical platforms to quantitatively measure targeted and untargeted lung specific markers of inflammation. As such, the measurement of distal airway components may help to evaluate acute and chronic inflammatory conditions such as asthma, chronic obstructive pulmonary disease, acute respiratory distress syndrome, and more recently, acute viral infections such as COVID-19. PExA may provide an alternative to traditional methods of airway sampling, such as induced sputum, tracheal aspirate, or bronchoalveolar lavage. The measurement of specific biomarkers of airway inflammation obtained directly from the RTLF by PExA enables a more accurate and comprehensive understanding of pathophysiological changes at the molecular level in patients with acute and chronic lung diseases.

Towards quantifying biomarkers for respiratory distress in preterm infants: Machine learning on mid infrared spectroscopy of lipid mixtures.

Neonatal respiratory distress syndrome (nRDS) is a challenging condition to diagnose which can lead to delays in receiving appropriate treatment. Mid infrared (IR) spectroscopy is capable of measuring the concentrations of two diagnostic nRDS biomarkers, lecithin (L) and sphingomyelin (S) with the potential for point of care (POC) diagnosis and monitoring. The effects of varying other lipid species present in lung surfactant on the mid IR spectra used to train machine learning models are explored. This study presents a lung lipid model of five lipids present in lung surfactant and varies each in a systematic approach to evaluate the ability of machine learning models to predict the lipid concentrations, the L/S ratio and to quantify the uncertainty in the predictions using the jackknife + -after-bootstrap and variant bootstrap methods. We establish the L/S ratio can be determined with an uncertainty of approximately ±0.3 mol/mol and we further identify the 5 most prominent wavenumbers associated with each machine learning model.

Broadband 2 × 2 multimode interference coupler for mid-infrared wavelengths.

Beam splitters are core components of photonic integrated circuits and are often implemented with multimode interference couplers. While these devices offer high performance, their operational bandwidth is still restrictive for sensing applications in the mid-infrared wavelength range. Here we experimentally demonstrate a subwavelength-structured 2×2 multimode interference coupler with high performance in the 3.1-3.7µm range, doubling the bandwidth of a conventional device.

Selective excitation of whispering gallery modes in a novel bottle microresonator.

Selective excitation of spheroidal whispering gallery modes and bottle modes in a robust bottle microresonator fabricated straightforwardly from a short section of optical fiber is demonstrated. Characteristic resonance spectra of long-cavity bottle modes were obtained by using a tapered fiber to excite evanescently bottle microresonator at different points along its axis. Compared to bare-fiber cylindrical resonators, the bottle microresonator results in a 35x increase of the observed Q factor.