Simulation of an experimental database of infrared spectra of complex gaseous mixtures for detecting specific substances. The case of drug precursors

This work is motivated by the need to develop suitable databases in absence of real experimental data, for instance when spectra measured with a newly developed instrumentation on real samples are not available yet. This notwithstanding, in fact, the realization of the physical project should be addressed by a starting database, also invaluable in order to test its effectiveness. In this article we face the issue of simulating gas mixtures spectra for the development of a new sensor for External Cavity-Quantum Cascade Laser Photoacoustic Spectroscopy (EC-QCLPAS) starting from literature FT-IR spectra of pure components: a dataset is realized suitable to realistically represent the ensemble of spectra of the gas mixtures of interest. The informative data deriving from the literature spectra were combined with the stochastic component extracted from a sample spectrum recorded with a prototype instrument, allowing us to build a matrix containing thousands of simulated spectra of gaseous mixtures, accounting for the presence of different components at different concentrations. Signal processing and experimental design techniques were used along the whole path leading to the dataset of simulated spectra. In particular, the goal of the construction of the database lies in the development of a final system to detect drug precursors in the vapour phase. The comparison of some EC-QCLPAS spectra with the corresponding simulated signals confirms the validity of the proposed approach

Evidence of a causal effect of genetic tendency to gain muscle mass on uterine leiomyomata

Uterine leiomyomata (UL) are the most common tumours of the female genital tract and the primary cause of surgical removal of the uterus. Genetic factors contribute to UL susceptibility. To add understanding to the heritable genetic risk factors, we conduct a genome-wide association study (GWAS) of UL in up to 426,558 European women from FinnGen and a previous UL meta-GWAS. In addition to the 50 known UL loci, we identify 22 loci that have not been associated with UL in prior studies. UL-associated loci harbour genes enriched for development, growth, and cellular senescence. Of particular interest are the smooth muscle cell differentiation and proliferation-regulating genes functioning on the myocardin-cyclin dependent kinase inhibitor 1A pathway. Our results further suggest that genetic predisposition to increased fat-free mass may be causally related to higher UL risk, underscoring the involvement of altered muscle tissue biology in UL pathophysiology. Overall, our findings add to the understanding of the genetic pathways underlying UL, which may aid in developing novel therapeutics.Peer reviewe