Smoke gas analysis by Fourier transform infrared spectroscopy – summary of the SAFIR project results

The determination of toxic components from fire gases is difficult because the environment is hot, reactions are often temperature dependent, and a lot of soot may be produced. Due to the different properties of the gas components, a different time‐consuming procedure for each species has traditionally been used. The use of FTIR (Fourier transform infrared) spectrometers as a continuous monitoring technique overcomes many of the problems in smoke gas analyses. FTIR offers an opportunity to set up a calibration and prediction method for each gas showing a characteristic spectral band in the infrared region of the spectrum. The objective of the SAFIR project was to further develop the FTIR gas analysis of smoke gases to be an applicable and reliable method for the determination of toxic components in combustion gases related to fire test conditions. The optimum probe design, filter parameters and the most suitable sampling lines in terms of flow rate, diameter, construction material and operating temperature have been specified. In the large scale, special concern was given to the probe design and the effects of the probe location as well as practical considerations of the sampling line length. Quantitative calibration and prediction methods have been constructed for different components present in smoke gases. Recommendations on how to deal with interferents, non‐linearities and outliers have been provided and a verification method for the spectrometer for unexpected variations and for the different models have been described. FTIR measurement procedures in different fire test scenarios have been studied using the recommendations of this project for measurement techniques and analysis and an interlaboratory trial of the FTIR technique in smoke gas analysis was carried out to define the repeatability and reproducibility of the method in connection with a small scale fire test method, the cone calorimeter. Copyright © 2000 John Wiley & Sons Ltd.     

Cyclic Nigerosyl-Nigerose as Oxygen Nanocarrier to Protect Cellular Models from Hypoxia/Reoxygenation Injury: Implications from an In Vitro Model

Heart failure (HF) prevalence is increasing among the aging population, and the mortality rate remains unacceptably high despite improvements in therapy. Myocardial ischemia (MI) and, consequently, ischemia/reperfusion injury (IRI), are frequently the basis of HF development. Therefore, cardioprotective strategies to limit IRI are mandatory. Nanocarriers have been proposed as alternative therapy for cardiovascular disease. Controlled reoxygenation may be a promising strategy. Novel nanocarriers, such as cyclic nigerosyl-nigerose (CNN), can be innovative tools for oxygen delivery in a controlled manner. In this study we analyzed new CNN-based formulations as oxygen nanocarriers (O₂-CNN), and compared them with nitrogen CNN (N₂-CNN). These different CNN-based formulations were tested using two cellular models, namely, cardiomyoblasts (H9c2), and endothelial (HMEC) cell lines, at different concentrations. The effects on the growth curve during normoxia (21% O₂, 5% CO₂ and 74% N₂) and their protective effects during hypoxia (1% O₂, 5% CO₂ and 94% N₂) and reoxygenation (21% O₂, 5% CO₂ and 74% N₂) were studied. Neither O₂-CNN nor N₂-CNN has any effect on the growth curve during normoxia. However, O₂-CNN applied before hypoxia induces a 15–30% reduction in cell mortality after hypoxia/re-oxygenation when compared to N₂-CNN. O₂-CNN showed a marked efficacy in controlled oxygenation, which suggests an interesting potential for the future medical application of soluble nanocarrier systems for MI treatment.     

Mitochondrial Bioenergetic,Photobiomodulation and Trigeminal Branches Nerve Damage,What’s the Connection? A Review

Background: Injury of the trigeminal nerve in oral and maxillofacial surgery can occur. Schwann cell mitochondria are regulators in the development, maintenance and regeneration of peripheral nerve axons. Evidence shows that after the nerve injury, mitochondrial bioenergetic dysfunction occurs and is associated with pain, neuropathy and nerve regeneration deficit. A challenge for research is to individuate new therapies able to normalise mitochondrial and energetic metabolism to aid nerve recovery after damage. Photobiomodulation therapy can be an interesting candidate, because it is a technique involving cell manipulation through the photonic energy of a non-ionising light source (visible and NIR light), which produces a nonthermal therapeutic effect on the stressed tissue. Methods: The review was based on the following questions: (1) Can photo-biomodulation by red and NIR light affect mitochondrial bioenergetics? (2) Can photobiomodulation support damage to the trigeminal nerve branches? (preclinical and clinical studies), and, if yes, (3) What is the best photobiomodulatory therapy for the recovery of the trigeminal nerve branches? The papers were searched using the PubMed, Scopus and Cochrane databases. This review followed the ARRIVE-2.0, PRISMA and Cochrane RoB-2 guidelines. Results and conclusions: The reliability of photobiomodulatory event strongly bases on biological and physical-chemical evidence. Its principal player is the mitochondrion, whether its cytochromes are directly involved as a photoacceptor or indirectly through a vibrational and energetic variation of bound water: water as the photoacceptor. The 808-nm and 100 J/cm² (0.07 W; 2.5 W/cm²; pulsed 50 Hz; 27 J per point; 80 s) on rats and 800-nm and 0.2 W/cm² (0.2 W; 12 J/cm²; 12 J per point; 60 s, CW) on humans resulted as trustworthy therapies, which could be supported by extensive studies.     

CORRELATION AND PREDICTION OF VLE OF WATER + CONGENER MIXTURES FOUND IN ALCOHOLIC BEVERAGES USING AN ARTIFICIAL NEURAL NETWORK

Artificial neural networks have been used for the correlation and prediction of vapor-liquid equilibrium data of binary water mixtures found in alcoholic beverage production. The main interest of the study is the accurate modeling of the bubble pressure and concentration of congeners in the vapor phase (substances different from ethanol and water), considered to be an important enological parameter in the alcoholic industry. Nine binary water + congener mixtures were considered for analysis. Vapor-liquid equilibrium data of these systems were taken from the literature (333 data points for training and 111 data points for testing), the artificial neural network results were compared with available literature data, and the accuracy of the modeling is discussed. The study shows that the neural network model is a good alternative method for the estimation of phase equilibrium properties for this type of mixture.

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