Optical-Trapping Laser Techniques for Characterizing Airborne Aerosol Particles and Its Application in Chemical Aerosol Study

A Collection of Molecular Fingerprints of Single Aerosol Particles in Air for Potential Identification and Detection Using Optical Trapping-Raman Spectroscopy

Characterization, identification, and detection of aerosol particles in their native atmospheric states remain a challenge. Recently, optical trapping-Raman spectroscopy (OT-RS) has been developed and demonstrated for characterization of single, airborne particles. Such particles in different chemical groups have been characterized by OT-RS in recent years and many more are being studied. In this work, we collected single-particle Raman spectra measured using the OT-RS technique and began construction of a library of OT-RS fingerprints that may be used as a reference for potential detection and identification of aerosol particles in the atmosphere. We collected OT-RS fingerprints of aerosol particles from eight different categories including carbons, bioaerosols (pollens, fungi, vitamins, spores), dusts, biological warfare agent surrogates, etc. Among the eight categories, spectral fingerprints of six groups of aerosol particles have been published previously and two other groups are new. We also discussed challenges, limitations, and advantages of using single-particle optical trapping-Raman spectroscopy for aerosol-particle characterization, identification, and detection.

The Tyndall Effect in High-Resolution Computed Tomography of Semicircular Canalolithiasis with Benign Paroxysmal Positional Vertigo

To date, along with the progress of new technology and computer program development, the high-resolution computed tomography (HRCT) had been applied in different clinical application, such as HRCT for coronary angiography. In the current neuroimaging reports, we present HRCT images of the head/neck of two cases, in which one had a diagnosis of benign paroxysmal positional vertigo (BPPV) and the other did not, to represent the Tyndall effect, which describes the scattering of light by particles (i.e., semicircular canalolithiasis) in the path of light and enables clinicians to see a specific signal on the HRCT images. On the HRCT image of the patient with canalolithiasis with BPPV, we could obviously see the scattering effect (i.e., Tyndall effect) in the horizontal/posterior semicircular canal; however, on the HRCT image of the other without canalolithiasis, we could not see such findings. Therefore, through the assistance of technological progress, HRCT might be beneficial in the diagnosis of semicircular canalolithiasis, which has the advantage of being noninvasive and having a low risk of complications. However, because of the disadvantages of expense and risk of radiation exposure, HRCT should be reserved for patients who are difficult to diagnose.

Particle Classification through the Analysis of the Forward Scattered Signal in Optical Tweezers

The ability to select, isolate, and manipulate micron-sized particles or small clusters has made optical tweezers one of the emergent tools for modern biotechnology. In conventional setups, the classification of the trapped specimen is usually achieved through the acquired image, the scattered signal, or additional information such as Raman spectroscopy. In this work, we propose a solution that uses the temporal data signal from the scattering process of the trapping laser, acquired with a quadrant photodetector. Our methodology rests on a pre-processing strategy that combines Fourier transform and principal component analysis to reduce the dimension of the data and perform relevant feature extraction. Testing a wide range of standard machine learning algorithms, it is shown that this methodology allows achieving accuracy performances around 90%, validating the concept of using the temporal dynamics of the scattering signal for the classification task. Achieved with 500 millisecond signals and leveraging on methods of low computational footprint, the results presented pave the way for the deployment of alternative and faster classification methodologies in optical trapping technologies.