# Application of Thin-Film Microextraction to Analyze Volatile Metabolites in A549 Cancer Cells
## 2 Results and Discussion
### Optimization of the TFME Extraction Procedure  
The first stage of optimization of the TFME procedure showed that all unambiguously identified VOCs (\(n=40\)) were detected, regardless of sorbent type used (Figure 1). For highly volatile molecules, _inter alia_, acetaldehyde, propanal, acetonitrile, isoprene, dimethyl sulfide, 3-methyl-1-butene, pyrrole, very good results were obtained for Carboxen sheets. Carboxen had the largest active surface area (\(>\)1000 m\({}^{2}\)/g) with microporous structure, which resulted in the highest adsorption strength amongst all sorbents investigated here. However, for alcohols observed in this study, i.e., ethanol, 1-propanol, 2-methyl-2-propanol, and 2-ethyl-1-hexanol, considerably better extraction efficiency was observed for DVB and HLB sheets compared to Carboxen. This may be related to the displacement of those polar molecules containing hydroxyl group with water molecules (the RPMI medium is an aqueous solution) which have higher adsorption affinity to Carboxen than the mentioned VOCs. Additionally, Carboxen may appear to be too strong for larger molecules, especially those containing functional groups responsible for \(\pi\)-\(\pi\) interactions. In this case, the temperature applied may be insufficient for complete desorption on the one hand, but further increase of temperature may damage the PDMS support under Carboxen on TFME sheet on the other hand. This is in line with the results gathered, whereby heptane, octane, nonane and decane were most efficiently extracted with DVB meshes. Divinylbenzene is nonpolar sorbent in which nonspecific Van der Waals forces and \(\pi\)-\(\pi\) interactions play a major role. However, the polar functional groups present in the target molecule weaken those interactions. Basically, the more electronegative a functional group, the weaker are the \(\pi\)-\(\pi\) interactions between the sorbent and analyte molecule. For this reason, the N-vinyl-pyrrolidone groups are built into the divinylbenzene skeleton yielding more polar hydrophilic-lipophilic balanced (HLB) sheets. This is supported by an observation in this study, where oxygenated VOCs, including alcohols, ketones and aldehydes, were extracted with the highest efficiency on HLB (Figure 1). In turn, PDMS membranes resulted in the worst metabolite coverage, with only carbon disulfide being extracted with higher efficiency compared to other sorbent types. Figure 1: Sorbent optimization of volatile organic compounds (VCCs). The \(y\)-axis represents log-transformed peak area values. Mean values are given with standard deviation for four replicates (\(n=4\)) for each sorbent: Carboxen (CAR, grey boxes), divinylbenzene (DVB, blue boxes), hydrophobic–lipophilic balanced (HLB, green boxes), polydimethylsiloxane (PDMS, red boxes). Special care should be taken when analyzing biological samples, particularly infectious material such as bacteria or infected human fluids. For this reason, the external sampling mode (EX-HS) was investigated in which the TFME sheet was separated from the sample by placing it inside a TD tube (fixed with a tiny portion of glass wool). Although the headspace sample was drawn through the TFME sheet by multiple bidirectional movements of the plunger of the 2 mL syringe, after which the sorbent was still exposed to the sample via 1/4\" Teflon tube (over 30 min), the extraction efficiency in this protocol was worse compared to the internal HS mode (IN-HS) for all VOCs detected, except 2-pentene and methylpyrazine (Figure 2). It should be noted that in the IN-HS mode, the initially generated headspace was broken for a short time (3-5 s) by opening a sample vial to replace an original cap with one containing a sorbent sheet.