ABSTRACT
While the exploration into biomolecules for diagnostic and prognostic devices continues to develop, many molecules continue to be examined for individual diseases or treatments. Consequently, it can be difficult to fully understand the scope of one individual molecule's current and potential clinical utilization. The scope of this study aimed to assess the potential of Interferon Gamma-induced Protein 10 (IP-10) as a biomarker in a wide variety of diseases, both as a main and supplemental indicator of disease infection and progression. IP-10 is a chemokine secreted in response to IFN-gamma playing a major role in the activation and regulation of inflammatory and immune responses within the body. Currently, IP-10 has displayed potential application in diseases such as COVID-19, tuberculosis, sepsis, Kawasaki disease, cancer, and many more. Molecular assays developed for the detection of IP-10 take longer testing time, sophisticated instrument utilization, and need more sample volumes. These cannot be utilized for bedside patient monitoring during the illness state of the patient. Biosensing tools are alternative methods used at clinical sites due to their rapid results. Though many types of sensing mechanisms established for the detection of disease biomarkers such as optical, piezoelectric sensors, and electrochemical biosensors are far beyond the other sensing methods due to their ease of mechanism, rapid results, and portable nature. IP-10 has been a promising biomarker in different diseases, evaluation of IP-10 levels at different time points of treatments is necessary. To achieve this, current conventional methods cannot be used and thus a portable device that provides rapid results is in demand. Such point-of-care (POC) device development for IP-10 analysis is very crucial in the current scenario. Beyond this, the clarification of its physiological role in healthy and infected individuals could allow for more proper utilization in clinical diagnoses, prognoses, treatment monitoring, and more. Overall, this study was developed to summarize the associations currently created between levels of IP-10 and other biomolecules and diseases.Copyright © 2023 The Author(s)
ABSTRACT
INTRODUCTION: Respiratory disease, acute and chronic, can be difficult to diagnose and monitor. To date, there are only two standard non-invasive monitoring approaches for assessing respiratory distress: respiratory rate and SpO2. The Respiratory non-Invasive Venous waveform Analysis (RIVA) was first described in COVID-19 patients as a promising, novel physiological measurement that predicted a COVID-19+ patient's need for oxygen support therapy. The aim of this study was to investigate if this RIVA signal was present in chronic pulmonary conditions. METHODS: Secondary analysis of a venous waveform dataset of human subjects that had pulmonary function tests (PFT) were analyzed to assess how their chronic respiratory illnesses affected the magnitude of their respiratory signal. Data was captured via a non-invasive piezoelectric sensor and analyzed on LabChart 8. Using spectral analysis in 8K windows, the respiratory peak of the signal (low frequency ~0.2 Hz) was measured for magnitude relative to their cardiac peak (higher frequency ~1.0 Hz) to calculate RIVA-RI (respiratory peak/cardiac peak). These values were grouped according to their pulmonary disease and an ANOVA with multiple comparisons was conducted to determine the significance between groups. RESULTS: Healthy control subjects displayed significantly lower RIVA-RI values compared to patients reporting the PFT lab with asthma or idiopathic pulmonary fibrosis (IPF;p < 0.05). Patients with chronic obstructive pulmonary disease, pulmonary hypertension, and/or obstructive sleep apnea did not have significant RIVA-RI values compared to healthy controls. CONCLUSIONS: This novel signal, first discovered in COVID-19+ patients that required oxygen support therapy, is also present in asthmatic and IPF patients. More research is needed to better understand the respiratory venous signal and how it could be used to monitor respiratory disease.