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Real-time analysis of fine ash in volcanic plumes, which represent magma fragments expelled from the crater during explosive eruptions, is a valuable tool for volcano monitoring and hazard assessment. To obtain the chemical characterization of the juvenile pyroclastic material emitted in volcanic plumes, many analytical techniques can be used. Among them, laser-induced breakdown spectroscopy (LIBS) is the one that can most easily be adapted to advanced applications in extreme environments. In this paper, LIBS experiments based on self-calibrated approaches are used to determine the elemental composition of suspended volcanic ash. To simulate the conditions of dispersed volcanic ash in the atmosphere, different sizes of volcanic ash samples are suspended in the air by laser-induced shockwaves in a dedicated chamber, and a parametric study is carried out to establish the optimal experimental conditions for recording usable plasma emission spectra for each ash size. The quantitative analysis is performed using a self-calibrated analytical method, including calibration-free LIBS, which is based on the calculation of the spectral radiance of a uniform plasma in local thermodynamic equilibrium. The method accounts intrinsically for self-absorption since it modifies the intensity of spectral lines and thus leads to an underestimation of the elemental fraction. An intensity calibration of the spectra based on the measurements of Fe lines intensities was also used in this work to deduce the apparatus response from the spectrum itself and avoid the use of standard calibration lamps. Results demonstrate the potential of real-time measurements of elemental fractions in volcanic ash with good agreement with the literature composition., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Nanoparticle-enhanced laser-induced breakdown spectroscopy (NELIBS) is an optical emission technique based on the laser-induced plasma (LIP) on a sample after the deposition of plasmonic nanoparticles (NPs) on its surface. The employment of the NPs allows an enhancement of the signal with respect to the one obtained with the conventional laser-induced breakdown spectroscopy (LIBS) enabling an extremely high sensitivity and very low limits of detection compared with the LIBS performance. Recently, NELIBS was used for monitoring the NP protein corona formation. As a matter of fact, the NPs in the presence of proteins adsorbed on the surface change their surface properties, therefore the sensing of protein corona formation was possible because of the strong dependence of NELIBS effects on the NP organization on the substrate, which in turn is deeply affected by the surface properties of the NPs. A correlation was found between NELIBS enhancement and the structure of the NP-protein conjugate in terms of protein content absorbed on the NP surface. An interesting question that was not yet exploited regards the role of LIP during the NELIBS when the NPs are covered with proteins. Since the presence of organic matter can strongly quench the LIP emission, the study of the LIP properties during protein corona sensing by NELIBS is of interest for two main reasons: (i) to understand whether the plasma parameters can vary in the presence of proteins adsorbed on the NP surface and (ii) to investigate how and if the plasma parameters themselves can influence the NELIBS processes. With this aim, the study of plasma parameters, i.e., electron densities and temperatures, during the sensing of NP protein corona by NELIBS is presented and discussed. The NPs used during these experiments were ultrapure gold NPs (AuNPs) produced by pulsed laser ablation in liquid, which are stable without any stabilizer. The human serum albumin protein is used to form AuNP-protein conjugates further deposited on a titanium target in NELIBS measurements. Dynamic light scattering, surface plasmon resonance spectroscopy, and laser Doppler electrophoresis for ζ-potential determination were employed to monitor the protein coverage of NP surface in the conjugate solutions before the NELIBS measurements., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Gulf War illness (GWI) is a chronic illness with no known validated biomarkers that affects the lives of hundreds of thousands of people. As a result, there is an urgent need for the development of an untargeted and unbiased method to distinguish GWI patients from non-GWI patients. We report on the application of laser-induced breakdown spectroscopy (LIBS) to distinguish blood plasma samples from a group of subjects with GWI and from subjects with chronic low back pain as controls. We initially obtained LIBS data from blood plasma samples of four GWI patients and four non-GWI patients. We used an analytical method based on taking the difference between a mean LIBS spectrum obtained with those of GWI patients from the mean LIBS spectrum of those of the control group, to generate a "difference" spectrum for our classification model. This model was cross-validated using different numbers of differential LIBS emission peaks. A subset of 17 of the 82 atomic and ionic transitions that provided 70% of correct diagnosis was selected test in a blinded fashion using 10 additional samples and was found to yield 90% classification accuracy, 100% sensitivity, and 83.3% specificity. Of the 17 atomic and ionic transitions, eight could be assigned unambiguously to species of Na, K, and Fe.

Alzheimer's disease (AD) is a progressive incurable neurodegenerative disease and a major health problem in aging population. We show that the combined use of Laser-Induced Breakdown Spectroscopy (LIBS) and machine learning applied for the analysis of micro-drops of plasma samples of AD and healthy controls (HC) yields robust classification. Following the acquisition of LIBS spectra of 67 plasma samples from a cohort of 31 AD patients and 36 healthy controls (HC), we successfully diagnose late-onset AD (> 65 years old), with a total classification accuracy of 80%, a specificity of 75% and a sensitivity of 85%., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest. The views expressed in this article are those of the authors and do not represent the views of the US Department of Veterans Affairs or the US Government.

In this paper, nanoparticle enhanced laser-induced breakdown spectroscopy (NELIBS) was applied to the elemental chemical analysis of microdrops of solutions with analyte concentration at subppm level. The effect on laser ablation of the strong local enhancement of the electromagnetic field allows enhancing the optical emission signal up to more than 1 order of magnitude, enabling LIBS to quantify ppb concentration and notably decreasing the limit of detection (LOD) of the technique. At optimized conditions, it was demonstrated that NELIBS can reach an absolute LOD of few picograms for Pb and 0.2 pg for Ag. The effect of field enhancement in NELIBS was tested on biological solutions such as protein solutions and human serum, in order to improve the sensitivity of LIBS with samples where the formation and excitation of the plasma are not as efficient as with metals. Even in these difficult cases, a significant improvement with respect to conventional LIBS was observed.