Characterization of Volatile and Particulate Emissions from Desktop 3D Printers.

The rapid expansion of 3D printing technologies has led to increased utilization in various industries and has also become pervasive in the home environment. Although the benefits are well acknowledged, concerns have arisen regarding potential health and safety hazards associated with emissions of volatile organic compounds (VOCs) and particulates during the 3D printing process. The home environment is particularly hazardous given the lack of health and safety awareness of the typical home user. This study aims to assess the safety aspects of 3D printing of PLA and ABS filaments by investigating emissions of VOCs and particulates, characterizing their chemical and physical profiles, and evaluating potential health risks. Gas chromatography-mass spectrometry (GC-MS) was employed to profile VOC emissions, while a particle analyzer (WIBS) was used to quantify and characterize particulate emissions. Our research highlights that 3D printing processes release a wide range of VOCs, including straight and branched alkanes, benzenes, and aldehydes. Emission profiles depend on filament type but also, importantly, the brand of filament. The size, shape, and fluorescent characteristics of particle emissions were characterized for PLA-based printing emissions and found to vary depending on the filament employed. This is the first 3D printing study employing WIBS for particulate characterization, and distinct sizes and shape profiles that differ from other ambient WIBS studies were observed. The findings emphasize the importance of implementing safety measures in all 3D printing environments, including the home, such as improved ventilation, thermoplastic material, and brand selection. Additionally, our research highlights the need for further regulatory guidelines to ensure the safe use of 3D printing technologies, particularly in the home setting.

Predicting Chronological Age via the Skin Volatile Profile.

Skin volatile emissions offer a noninvasive insight into metabolic activity within the body as well as the skin microbiome and specific volatile compounds have been shown to correlate with age, albeit only in a few small studies. Building on this, here skin volatiles were collected and analyzed in a healthy participant study (n = 60) using a robust headspace-solid phase microextraction (HS-SPME) gas chromatography-mass spectrometry (GC-MS) workflow. Following processing, 18 identified compounds were deemed suitable for this study. These were classified according to gender influences and their correlations with age were investigated. Finally, 6 volatiles (of both endogenous and exogenous origin) were identified as significantly changing in abundance with participant age (p < 0.1). The potential origins of these dysregulations are discussed. Multiple linear regression (MLR) analysis was employed to model age based on these significant volatiles as independent variables, along with gender. Our analysis shows that skin volatiles show a strong predictive ability for age (explained variance of 68%), stronger than other biochemical measures collected in this study (skin surface pH, water content) which are understood to vary with chronological age. Overall, this work provides new insights into the impact of aging on the skin volatile profiles which comprises both endogenously and exogenously derived volatile compounds. It goes toward demonstrating the biological significance of skin volatiles and will help pave the way for more rigorous consideration of the healthy "baseline" skin volatile profile in volatilomics-based health diagnostics development going forward.

Investigation of the relationship between skin-emitted volatile fatty acids and skin surface acidity in healthy participants-a pilot study.

Volatile organic compounds (VOCs) emitted from human skin are of great interest in general in research fields including disease diagnostics and comprise various compound classes including acids, alcohols, ketones and aldehydes. The objective of this research is to investigate the volatile fatty acid (VFA) emission as recovered from healthy participant skin VOC samples and to characterise its association with skin surface acidity. VOC sampling was performed via headspace-solid phase microextraction with analysis via gas chromatography-mass spectrometry. Several VFAs were recovered from participants, grouped based on gender and site (female forehead, female forearm, male forearm). Saturated VFAs (C9, C12, C14, C15, C16) and the unsaturated VFA C16:1 (recovered only from the female forehead) were considered for this study. VFA compositions and abundances are discussed in the context of body site and corresponding gland type and distribution, and their quantitative association with skin acidity investigated. Normalised chromatographic peak areas of the recovered VFAs were found to linearly correlate with hydrogen ion concentration measured at each of the different sites considered and is the first report to our knowledge to demonstrate such an association. Our observations are explained in terms of the free fatty acid content at the skin surface which is well-established as being a major contributor to skin surface acidity. Furthermore, it is interesting to consider that these VFA emissions from skin, governed by equilibrium vapour pressures exhibited at the skin surface, will be dependent on skin pH. It is proposed that these pH-modulated equilibrium vapour pressures of the acids could be resulting in an enhanced VFA emission sensitivity with respect to skin surface pH. To translate our observations made here for future wearable biodiagnostic applications, the measurement of skin surface pH based on the volatile emission was demonstrated using a pH indicator dye in the form of a planar colorimetric sensor, which was incorporated into a wearable platform and worn above the palm surface. As acidic skin surface pH is required for optimal skin barrier function and cutaneous antimicrobial defence, it is envisaged that these colorimetric volatile acid sensors could be deployed in robust wearable formats for monitoring health and disease applications in the future.