Real-Time Monitoring of Odour Emissions at the Fenceline of a Waste Treatment Plant by Instrumental Odour Monitoring Systems: Focus on Training Methods.

Waste treatment plants (WTPs) often generate odours that may cause nuisance to citizens living nearby. In general, people are becoming more sensitive to environmental issues, and particularly to odour pollution. Instrumental Odour Monitoring Systems (IOMSs) represent an emerging tool for continuous odour measurement and real-time identification of odour peaks, which can provide useful information about the process operation and indicate the occurrence of anomalous conditions likely to cause odour events in the surrounding territories. This paper describes the implementation of two IOMSs at the fenceline of a WTP, focusing on the definition of a specific experimental protocol and data processing procedure for dealing with the interferences of humidity and temperature affecting sensors' responses. Different approaches for data processing were compared and the optimal one was selected based on field performance testing. The humidity compensation model developed proved to be effective, bringing the IOMS classification accuracy above 95%. Also, the adoption of a class-specific regression model compared to a global regression model resulted in an odour quantification capability comparable with those of the reference method (i.e., dynamic olfactometry). Lastly, the validated models were used to process the monitoring data over a period of about one year.

Alpha-gal syndrome and delayed anaphylaxis after ingestion of red meat: A case report.

α-gal syndrome (AGS) is caused by the intake of products containing α-gal (galactose-α-1,3-galactose) like mammalian meat. Over the last decade, scientific literature about AGS has been increasing, but the true burden of cases is still unknown [1, 2]. In the USA (University of Virginia Allergy Clinic), the number of confirmed cases of AGS was 24 in 2009 [3] and increased to 34,000 in the entire USA by 2019 [4]. As shown in surveys, in Italy AGS is present throughout the country [5]. The literature suggests that a previous tick bite can cause AGS, but in our case it was not possible to demonstrate this association as the patient did not recall any tick bite, even in childhood. After eating red meat, a 56-year-old male patient had developed symptoms such as a generalized urticaria, diarrhea, and faintness, requiring admission to the Emergency Department. The diagnosis was verified using blood CAP-FEIA test and prick-to-prick test. After completing the diagnostic process, we provided the patient with emergency therapy, and auto-injectable adrenaline was prescribed. Despite the diagnosis, the patient ate red meat once again which resulted in severe urticaria 2 hours after the meal, requiring a second visit to the Emergency Room. Now the patient is under follow-up at our Department of Allergy and Clinical Immunology.

An Experimental Apparatus for E-Nose Breath Analysis in Respiratory Failure Patients.

Background: Non-invasive, bedside diagnostic tools are extremely important for tailo ring the management of respiratory failure patients. The use of electronic noses (ENs) for exhaled breath analysis has the potential to provide useful information for phenotyping different respiratory disorders and improving diagnosis, but their application in respiratory failure patients remains a challenge. We developed a novel measurement apparatus for analysing exhaled breath in such patients. Methods: The breath sampling apparatus uses hospital medical air and oxygen pipeline systems to control the fraction of inspired oxygen and prevent contamination of exhaled gas from ambient Volatile Organic Compounds (VOCs) It is designed to minimise the dead space and respiratory load imposed on patients. Breath odour fingerprints were assessed using a commercial EN with custom MOX sensors. We carried out a feasibility study on 33 SARS-CoV-2 patients (25 with respiratory failure and 8 asymptomatic) and 22 controls to gather data on tolerability and for a preliminary assessment of sensitivity and specificity. The most significant features for the discrimination between breath-odour fingerprints from respiratory failure patients and controls were identified using the Boruta algorithm and then implemented in the development of a support vector machine (SVM) classification model. Results: The novel sampling system was well-tolerated by all patients. The SVM differentiated between respiratory failure patients and controls with an accuracy of 0.81 (area under the ROC curve) and a sensitivity and specificity of 0.920 and 0.682, respectively. The selected features were significantly different in SARS-CoV-2 patients with respiratory failure versus controls and asymptomatic SARS-CoV-2 patients (p < 0.001 and 0.046, respectively). Conclusions: the developed system is suitable for the collection of exhaled breath samples from respiratory failure patients. Our preliminary results suggest that breath-odour fingerprints may be sensitive markers of lung disease severity and aetiology.