Lessons learned in a decade: Medical-toxicological view of tattooing.

Tattooing has been part of the human culture for thousands of years, yet only in the past decades has it entered the mainstream of the society. With the rise in popularity, tattoos also gained attention among researchers, with the aim to better understand the health risks posed by their application. 'A medical-toxicological view of tattooing'-a work published in The Lancet almost a decade ago, resulted from the international collaboration of various experts in the field. Since then, much understanding has been achieved regarding adverse effects, treatment of complications, as well as their regulation for improving public health. Yet major knowledge gaps remain. This review article results from the Second International Conference on Tattoo Safety hosted by the German Federal Institute for Risk Assessment (BfR) and provides a glimpse from the medical-toxicological perspective, regulatory strategies and advances in the analysis of tattoo inks.

On-tissue dataset-dependent MALDI-TIMS-MS2 bioimaging.

Trapped ion mobility spectrometry (TIMS) adds an additional separation dimension to mass spectrometry (MS) imaging, however, the lack of fragmentation spectra (MS2) impedes confident compound annotation in spatial metabolomics. Here, we describe spatial ion mobility-scheduled exhaustive fragmentation (SIMSEF), a dataset-dependent acquisition strategy that augments TIMS-MS imaging datasets with MS2 spectra. The fragmentation experiments are systematically distributed across the sample and scheduled for multiple collision energies per precursor ion. Extendable data processing and evaluation workflows are implemented into the open source software MZmine. The workflow and annotation capabilities are demonstrated on rat brain tissue thin sections, measured by matrix-assisted laser desorption/ionisation (MALDI)-TIMS-MS, where SIMSEF enables on-tissue compound annotation through spectral library matching and rule-based lipid annotation within MZmine and maps the (un)known chemical space by molecular networking. The SIMSEF algorithm and data analysis pipelines are open source and modular to provide a community resource.

A SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of ChatGPT in the Medical Literature: Concise Review.

BACKGROUND: ChatGPT is a 175-billion-parameter natural language processing model that is already involved in scientific content and publications. Its influence ranges from providing quick access to information on medical topics, assisting in generating medical and scientific articles and papers, performing medical data analyses, and even interpreting complex data sets. OBJECTIVE: The future role of ChatGPT remains uncertain and a matter of debate already shortly after its release. This review aimed to analyze the role of ChatGPT in the medical literature during the first 3 months after its release. METHODS: We performed a concise review of literature published in PubMed from December 1, 2022, to March 31, 2023. To find all publications related to ChatGPT or considering ChatGPT, the search term was kept simple ("ChatGPT" in AllFields). All publications available as full text in German or English were included. All accessible publications were evaluated according to specifications by the author team (eg, impact factor, publication modus, article type, publication speed, and type of ChatGPT integration or content). The conclusions of the articles were used for later SWOT (strengths, weaknesses, opportunities, and threats) analysis. All data were analyzed on a descriptive basis. RESULTS: Of 178 studies in total, 160 met the inclusion criteria and were evaluated. The average impact factor was 4.423 (range 0-96.216), and the average publication speed was 16 (range 0-83) days. Among the articles, there were 77 editorials (48,1%), 43 essays (26.9%), 21 studies (13.1%), 6 reviews (3.8%), 6 case reports (3.8%), 6 news (3.8%), and 1 meta-analysis (0.6%). Of those, 54.4% (n=87) were published as open access, with 5% (n=8) provided on preprint servers. Over 400 quotes with information on strengths, weaknesses, opportunities, and threats were detected. By far, most (n=142, 34.8%) were related to weaknesses. ChatGPT excels in its ability to express ideas clearly and formulate general contexts comprehensibly. It performs so well that even experts in the field have difficulty identifying abstracts generated by ChatGPT. However, the time-limited scope and the need for corrections by experts were mentioned as weaknesses and threats of ChatGPT. Opportunities include assistance in formulating medical issues for nonnative English speakers, as well as the possibility of timely participation in the development of such artificial intelligence tools since it is in its early stages and can therefore still be influenced. CONCLUSIONS: Artificial intelligence tools such as ChatGPT are already part of the medical publishing landscape. Despite their apparent opportunities, policies and guidelines must be implemented to ensure benefits in education, clinical practice, and research and protect against threats such as scientific misconduct, plagiarism, and inaccuracy.

Mobility-resolved broadband dissociation and parallel reaction monitoring for laser desorption/ionization-mass spectrometry - Tattoo pigment identification supported by trapped ion mobility spectrometry.

In this work, trapped ion mobility spectrometry (TIMS) was introduced to facilitate tandem mass spectrometry (MS2) experiments for laser desorption/ionization-mass spectrometry (LDI-MS) as mobility-resolved fragmentation. The mobility separation of desorbed ions was followed by subsequent fragmentation using data-independent broadband collision-induced dissociation (bbCID) or targeted fragmentation through a prototypic version of parallel reaction monitoring-parallel accumulation serial fragmentation (prm-PASEF) for LDI. Both mobility-resolved fragmentation options, TIMS-bbCID and prm-PASEF, were applied to LDI point measurements to identify organic pigments in tattoo inks. Furthermore, the prototypic prm-PASEF algorithm was used in imaging applications to increase confidence in annotating organic tattoo pigments in skin samples with adverse reactions. Due to less complex spectra in matrix-free LDI, both fragmentation methods yielded fast and reliable MS2 identification workflows. TIMS-bbCID was especially beneficial for the rapid acquisition of multiple fragment spectra. For the targeted prm-PASEF approach, analytes' mobilities needed to be collected prior to simplified fragmentation. Therefore, a reference list for 14 pigments was created. The possible number of experiments per thin section and the associated savings in analysis time compared to conventional MS2 were particularly suitable for the imaging application. Furthermore, the mobility dimension enabled a new orthogonal identification parameter, increasing the annotation confidence of tattoo pigments through compound specific mobilities.

Tattoo Pigment Identification in Inks and Skin Biopsies of Adverse Reactions by Complementary Elemental and Molecular Bioimaging with Mass Spectral Library Matching.

Tattooing has become increasingly popular throughout society. Despite the recognized issue of adverse reactions in tattoos, regulations remain challenging with limited data available and a missing positive list. The diverse chemical properties of mostly insoluble inorganic and organic pigments pose an outstanding analytical challenge, which typically requires extensive sample preparation. Here, we present a multimodal bioimaging approach combining micro X-ray fluorescence (µXRF) and laser desorption ionization-mass spectrometry (LDI-MS) to detect the elemental and molecular composition in the same sample. The pigment structures directly absorb the laser energy, eliminating the need for matrix application. A computational data processing workflow clusters spatially resolved LDI-MS scans to merge redundant information into consensus spectra, which are then matched against new open mass spectral libraries of tattoo pigments. When applied to 13 tattoo inks and 68 skin samples from skin biopsies in adverse tattoo reactions, characteristic signal patterns of isotopes, ion adducts, and in-source fragments in LDI-MS1 scans yielded confident compound annotations across various pigment classes. Combined with µXRF, pigment annotations were achieved for all skin samples with 14 unique structures and 2 inorganic pigments, emphasizing the applicability to larger studies. The tattoo-specific spectral libraries and further information are available on the tattoo-analysis.github.io website.

Determination of ghrelin and desacyl ghrelin in human plasma and urine by means of LC-MS/MS for doping controls.

The hunger hormone ghrelin (G) is classified as prohibited substance in professional sport by the World Anti-Doping Agency (WADA), due to its known growth hormone releasing properties. The endogenous bioactive peptide consists of 28 amino acids with a caprylic acid attached to serine at position 3. Within this study, it was aimed to develop methods to determine G and desacyl ghrelin (DAG) in plasma and urine by means of LC-MS/MS. Two strategies were applied with a bottom-up approach for plasma and top-down analyses for urine. Both sample preparation procedures were based on solid-phase extraction for enrichment and sample clean-up. Method validation showed good results for plasma and urine with limits of detection (LODs) for G and DAG between 30 and 50 pg/ml, recoveries between 45-50%, and imprecisions (intra- and inter-day) between 3% and 24%. Plasma analysis was also valid for quantification with accuracies determined with ~100% for G and ~106% for DAG. The minimum required performance level for doping control laboratories is set to 2 ng/ml in urine, and the herein established method yielded acceptable results even at 5% of this level. As proof-of-concept, plasma levels (G and DAG) of healthy volunteers were determined and ranged between 30 and 100 pg/ml for G and 100-1200 pg/ml for DAG. In contrast to earlier reported studies using ligand binding assays for urinary G and DAG, in this mass spectrometry-based study, no endogenous urinary G and DAG were found, although the LODs should enable this.

Role of perceived importance in intergroup contact.

Furthering G. W. Allport's contentions for optimal contact, the authors introduce a new construct: the perceived importance of contact. They propose that perceived importance is the best proximal predictor of contact's reduction of prejudice. If individuals have opportunities for contact at work or in the neighborhood, their chances to have intergroup acquaintances and friends increase. Intergroup contact among acquaintances and friends can be perceived as more or less important, which in turn determines intergroup evaluations. A 1st study shows that the new measure of perceived importance is indeed distinct from established quantity and quality indicators. The results are cross-validated in a 2nd study that also sheds light on the meaning of importance. In 3rd and 4th studies, structural equation analyses and a meta-analysis support the hypotheses.