A mechanistic study on the phototoxicity of atorvastatin: singlet oxygen generation by a phenanthrene-like photoproduct

Atorvastatin calcium (ATV) is one of the most frequently prescribed drugs worldwide. Among the adverse effects observed for this lipid-lowering agent, clinical cases of cutaneous adverse reactions have been reported and associated with photosensitivity disorders. Previous work dealing with ATV photochemistry has shown that exposure to natural sunlight in aqueous solution leads to photoproducts resulting from oxidation of the pyrrole ring and from cyclization to a phenanthrene derivative. Laser flash photolysis of ATV, at both 266 and 308 nm, led to a transient spectrum with two maxima at λ ) 360 and λ ) 580 nm (τ ) 41 μs), which was assigned to the primary intermediate of the stilbene-like photocyclization. On the basis of the absence of a triplet-triplet absorption, the role of the parent drug as singlet oxygen photosensitizer can be discarded. By contrast, a stable phenanthrene-like photoproduct would be a good candidate to play this role. Laser flash photolysis of this compound showed a triplet-triplet transient absorption at λmax ) 460 nm with a lifetime of 26 μs, which was efficiently quenched by oxygen (kq ) 3 ((0.2) × 109 M-1 s-1). Its potential to photosensitize formation of singlet oxygen was confirmed by spin trapping experiments, through conversion of TEMP to the stable free radical TEMPO. The photoreactivity of the phenanthrene-like photoproduct was investigated using Trp as a marker. The disappearance of the amino acid fluorescence (λmax ) 340 nm) after increasing irradiation times at 355 nm was taken as a measurement of photodynamic oxidation. To confirm the involvement of a type II mechanism, the same experiment was also performed in D2O; this resulted in a significant enhancement of the reaction rate. On the basis of the obtained photophysical and photochemical results, the phototoxicity of atorvastatin can be attributed to singlet oxygen formation with the phenanthrene-like photoproduct as a photosensitizer

On some amphicorina (polychaeta, sabellidae) species from the mediterranean coast, with the description of A. grahamensis

Species belonging to the genus Amphicorina are reported from some areas of the Mediterranean Sea, with the description of the new species A. grahamensis. The description of another species, Amphicorina sp., close to an Australian taxon, together with the redescriptions of A. pectinata, A. persinosa, and A. armandi are also given; the variability of this last taxon, probably deriving from misidentiflcations, is also considered. Examined specimens were prevalently from the Italian coast, and in particular from the Adriatic Sea. © 1999 Taylor & Francis Group, LLC

Exact quantum query complexity of EXACTk,ln\rm{EXACT}_{k,l}^n

In the exact quantum query model a successful algorithm must always output the correct function value. We investigate the function that is true if exactly $k$ or $l$ of the $n$ input bits given by an oracle are 1. We find an optimal algorithm (for some cases), and a nontrivial general lower and upper bound on the minimum number of queries to the black box.Comment: 19 pages, fixed some typos and constraint

Morphological Characterization of Some Local Varieties of Fig (Ficus carica L.) Cultivated in Southern Italy

Figs (Ficus carica L.) are ancient fruits of the Mediterranean basin. In Southern Italy, they are particularly important in the traditional course of local cuisine. In Southern Italy, fig trees are rarely cultivated in specialized orchards but are present in association with other fruit trees (for example, olive, almond, pear, pomegranate, and grapevine). These mixed orchards are particularly important in the traditional agroecosystems of the south of Italy. This study reports preliminary results on the local fig variety’s leaf morphological characterization, aiming to elucidate the presence of synonymousness or homonymy for in situ and ex situ conservation and further exploitation. A field survey was carried out during the summer of 2018 in some areas of the Basilicata district. Thirty local putative varieties were collected, and each of them was identified by GPS coordinates and recorded photographically. Moreover, they were cataloged with the name of the Municipality of origin, year, details of growing location (main crop, mixed orchard, gardens, and single plants), approximate age, and the local name supplied by the donor. All relevant information was included in the accession code. Leaf samples were collected from each accession from medium-length shoots. A digital image of each leaf sample was captured using a digital camera. Leaf morphometric traits were recorded using ImageJ and statistically analyzed using the software PAST 4.11 to discriminate among fig accessions. The multivariate morphometric approach applied correctly classified more than 90% of the leaves and helped to discriminate among accession. Moreover, linear discriminant analysis helped to recognize the presence of different synonymousness and homonymy of different accessions. The results revealed that measured leaf morphometric aided by image analysis could be a simple and inexpensive accessions classification tool

Rethinking the compositionality of point clouds through regularization in the hyperbolic space

Point clouds of 3D objects exhibit an inherent compositional nature where simple parts can be assembled into progressively more complex shapes to form whole objects. Explicitly capturing such part-whole hierarchy is a long-sought objective in order to build effective models, but its tree-like nature has made the task elusive. In this paper, we propose to embed the features of a point cloud classifier into the hyperbolic space and explicitly regularize the space to account for the part-whole hierarchy. The hyperbolic space is the only space that can successfully embed the tree-like nature of the hierarchy. This leads to substantial improvements in the performance of state-of-art supervised models for point cloud classification

Stack-CNN algorithm: A new approach for the detection of space objects

We present a new trigger algorithm combining a stacking procedure and a Convolutional Neural Network that could be applied to any space object moving linearly or with a known trajectory in the field of view of a telescope. This includes the detection of high velocity fragmentation debris in orbit. A possible implementation is as trigger system for an orbiting Space Debris remediation system. The algorithm was initially developed as offline system for the Multiwavelength Imaging New Instrument for the Extreme Universe Space Observatory (Mini-EUSO), on the International Space Station. We evaluated the performance of the algorithm on simulated data and compared it with those obtained by means of a more conventional trigger algorithm. Results indicate that this method would allow to recognise signals with 1% Signal over Background Ratio (SBR) on poissonian random fluctuations with a negligible fake trigger rate. Such promising results lead us to not only consider this technique as an online trigger system, but also as an offline method for searching moving signals and their characteristics (speed and direction). More generally, any kind of telescope (on the ground or in space) such as those used for space debris, meteors monitoring or cosmic ray science, could benefit from this automatized technique. The content of this paper is part of the recent Italian patent proposal submitted by the authors (patent application number: 102021000009845)