Utility of Raman Spectroscopy in Pulmonary Medicine.

The Raman effect, or as per its original description, "modified scattering", is an observation that the number of scattered light waves shifts after photons make nonelastic contact with a molecule. This effect allows Raman spectroscopy to be very useful in various fields. Although it is well known that Raman spectroscopy could be very beneficial in medicine as a diagnostic tool, there are not many applications of Raman spectroscopy in pulmonary medicine.

Repurposed pharmacological agents for the potential treatment of COVID-19: a literature review.

Background: The COVID-19 pandemic has affected the world extraordinarily. This disease has a potential to cause a significantly severe course of disease leading to respiratory complications, multiple organ failure and possibly death. In the fight against this pandemic-causing disease, medical professionals around the world are searching for pharmacological agents that could treat and prevent disease progression and mortality.

Vanishing lung syndrome with community-acquired pneumonia and infection of bullae.

We present a case of a 36-year old male who was a long-term smoker and was found to have giant bullous emphysema on chest imaging as an accidental finding. At the time, when his first chest CT was obtained, he was asymptomatic and was recommended to consult a pulmonologist but was lost to follow-up for a year until he presented to the emergency department with fever, dyspnea, and chest pain. He was admitted to a pulmonology department.

Detection of lung cancer with electronic nose and logistic regression analysis.

Lung cancer is a very common malignancy with a low five-year survival rate. Artificial olfactory sensor (electronic nose) is a tool that recently has been studied as a probable optimal screening tool for early detection of lung cancer, but still no statistical method has been put forward as the preferable one. The aim of the study was to explore the use of logistic regression analysis (LRA) to analyse patients' exhaled breath samples with electronic nose in order to differentiate lung cancer patients (regardless of the stage of the cancer) from patients with other lung diseases and healthy individuals.

Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis.

Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no cheap, simple and widely available screening methods for the early diagnostics of lung cancer. The aim of this study was to determine whether analysis of exhaled breath with an artificial olfactory sensor using support vector analysis can differentiate patients with lung cancer from healthy individuals and patients with other lung diseases, regardless of the stage of lung cancer and the most common comorbidities.