Background The COVID-19 pandemic sharply increased the demand for ethanol-based gel hand sanitizers, leading to a shortage of these products. Consequently, regulatory health agencies worldwide have altered their regulatory guidelines, on ethanol quality, to meet this high demand, raising concern about the products quality. Objective The aim of this study was to quantify ethanol content and to qualitatively assess common impurities in ethanol-based gel hand sanitizers by headspace gas chromatography with flame ionization detector (HS-GC/FID). Methods To quantify the ethanol content, 0.10 g of the sample was weighed in a 20 mL headspace vial and 5 mL of deionized water was added. Regarding the qualitative approach, 0.25 g of the sample was weighed and 4 mL of deionized water and was added. The samples were incubated, and then 400 µL of the headspace was injected into the GC/FID. Forty-eight products purchased in Brazil were analyzed. Results Thirteen products presented at least one nonconformity regarding the ethanol quantity. Two samples presented an average ethanol concentration below the lower limit considered effective. Twelve samples presented acetaldehyde or ethyl acetate. Conclusion The huge demand for ethanol-based gel hand sanitizers may have impacted their quality. Because concern with proper hand hygiene tends to remain an issue for a long period, more studies about quality control of hand sanitizers will be needed. Highlights A simple and fast HS-GC/FID method to quantify ethanol in ethanol-based gel hand sanitizers was developed, validated and applied to commercial samples in Brazil. The regulatory authorities must be more vigilant to ensure that the commercially available products meet the recommended specifications.
In Forensic Chemistry, evidence collected at a crime scene is of paramount importance for any case to be properly elucidated. Ignitable liquid residues are important chemical evidence in investigations into cases of fire because these substances can be correlated to arson. Here, we describe an innovative technique for sampling and extracting gasoline and diesel from fire debris by using activated charcoal pellets (ACP). ACP can be an alternative to activated charcoal strips and can be easily produced on the laboratory scale. The ACP approach allowed all the target compounds selected for gasoline and diesel fuels to be extracted. Among the six tested extraction conditions, optimal extraction occurred at 100 °C, after 240 min. These preliminary results showed the potential of ACP for detecting gasoline and diesel in fire debris. However, the ACP approach still requires analytical validation, so that its applicability in an authentic forensic setting can be explored.
Assessing volatile organic compounds (VOCs) as cancer signatures is one of the most promising techniques toward developing non-invasive, simple, and affordable diagnosis. Here, we have evaluated the feasibility of employing static headspace extraction (HS) followed by gas chromatography with flame ionization detector (GC-FID) as a screening tool to discriminate between cancer patients (head and neck – HNC, n=15; and gastrointestinal cancer - GIC, n=19) and healthy controls (n=37) on the basis of a non-target (fingerprinting) analysis of oral fluid and urine. We evaluated the discrimination considering a single bodily fluid and adopting the hybrid approach, in which the oral fluid and urinary VOCs profiles were combined through data fusion. We used supervised orthogonal partial least squares discriminant analysis (OPLS-DA) for classification, and we assessed the prediction power of the models by analyzing the values of goodness of prediction (Q2Y), area under the curve (AUC), sensitivity, and specificity. The individual models HNC urine, HNC oral fluid, and GIC oral fluid successfully discriminated between healthy controls and positive samples (Q2Y = 0.560, 0.525, and 0.559; AUC = 0.814, 0.850, and 0.926; sensitivity = 84.8, 70.2, and 78.6%; and specificity = 82.3; 81.5; 87.5%, respectively), whereas GIC urine was not adequate (Q2Y = 0.292, AUC = 0.694, sensitivity = 66.1%, and specificity = 77.0%). Compared to the respective individual models, Q2Y for the hybrid models increased (0.623 for hybrid HNC and 0.562 for hybrid GIC). However, sensitivity was higher for HNC urine and GIC oral fluid than for hybrid HNC (75.6%) and hybrid GIC (69.8%), respectively. These results suggested that HS-GC-FID fingerprinting is suitable and holds great potential for cancer screening. Additionally, the hybrid approach tends to increase the predictive power if the individual models present suitable quality parameter values. Otherwise, it is more advantageous to use a single body fluid for analysis.
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