Light-driven molecular rotary motors are nanometric machines able to convert light into unidirectional motions. Several types of molecular motors have been developed to better respond to light stimuli, opening new avenues for developing smart materials ranging from nanomedicine to robotics. They have great importance in the scientific research across various disciplines, but a detailed comprehension of the underlying ultrafast photophysics immediately after photo-excitation, that is, Franck-Condon region characterization, is not fully achieved yet.
View Article and Find Full Text PDFJ Chem Theory Comput
October 2024
The atom-centered density matrix propagation (ADMP) method is an extended Lagrangian approach to ab initio molecular dynamics, which includes the density matrix in an orthonormalized atom-centered Gaussian basis as additional, fictitious, electronic degrees of freedom, classically propagated along with the nuclear ones. A high adiabaticity between the nuclear and electronic subsystems is mandatory in order to keep the trajectory close to the Born-Oppenheimer (BO) surface. In this regard, the fictitious electronic mass , being a symmetric, nondiagonal matrix in its most general form, represents a free parameter, exploitable to optimize the propagation of the electronic density.
View Article and Find Full Text PDFChagas disease (CD) is a parasitic infection endemic in Latin America and also affects patients in Western countries due to migration flows. This has a significant impact on health services worldwide due to its high morbidity and mortality burden. This paper aims to share our experience at the National Institute for Infectious Diseases "Lazzaro Spallanzani", IRCCS, in Rome, Italy, where to date, a total of 47 patients-mainly Bolivian women-diagnosed with CD have received treatment with benznidazole, with all but one presenting with chronic disease.
View Article and Find Full Text PDFEpidemiologic studies frequently use risk ratios to quantify associations between exposures and binary outcomes. When the data are physically stored at the sites of multiple data partners, it can be challenging to perform individual-level analysis if data cannot be pooled centrally due to privacy constraints. Existing methods either require multiple file transfers between each data partner and an analysis center (eg, distributed regression) or only provide approximate estimation of the risk ratio (eg, meta-analysis).
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