Using Graph Transformation Systems to Specify and Verify Data Abstractions

This paper proposes an approach for the specification of the behavior of software components that implement data abstractions. By generalizing the approach of behavior models using graph transformation, we provide a concise specification for data abstractions that describes the relationship between the internal state, represented in a canonical form, and the observers of the component. Graph transformation also supports the generation of behavior models that are amenable to verification. To this end, we provide a translation approach into an LTL model on which we can express useful properties that can be model-checked with a SAT solver

Insight into the Molecular Model in Carbon Dots through Experimental and Theoretical Analysis of Citrazinic Acid in Aqueous Solution

The molecular emission model is the most accredited one to explain the emission properties of carbon dots (CDs) in a low-temperature bottom-up synthesis approach. In the case of citric acid and urea, the formation of a citrazinic acid (CZA) single monomer and oligomers is expected to affect the optical properties of the CDs. It is therefore mandatory to elucidate the possible role of weak bonding interactions in determining the UV absorption spectrum of some molecular aggregates of CZA. Although this carboxylic acid is largely exploited in the synthesis of luminescent CDs, a full understanding of its role in determining the final emission spectra of the produced CDs is still very far to be achieved. To this aim, by relying on purely first-principles density functional theory calculations combined with experimental optical characterization, we built and checked the stability of some molecular aggregates, which could possibly arise from the formation of oligomers of CZA, mainly dimers, trimers, and some selected tetramers. The computed vibrational fingerprint of the formation of aggregates is confirmed by surface-enhanced Raman spectroscopy. The comparison of experimental data with calculated UV absorption spectra showed a clear impact of the final morphology of the aggregates on the position of the main peaks in the UV spectra, with particular regard to the 340 nm peak associated with n-π∗ transition

Mechanochemistry: New Tools to Navigate the Uncharted Territory of “Impossible” Reactions

Mechanochemical transformations have made chemists enter unknown territories, forcing a different chemistry perspective. While questioning or revisiting familiar concepts belonging to solution chemistry, mechanochemistry has broken new ground, especially in the panorama of organic synthesis. Not only does it foster new “thinking outside the box”, but it also has opened new reaction paths, allowing to overcome the weaknesses of traditional chemistry exactly where the use of well-established solution-based methodologies rules out progress. In this Review, the reader is introduced to an intriguing research subject not yet fully explored and waiting for improved understanding. Indeed, the study is mainly focused on organic transformations that, although impossible in solution, become possible under mechanochemical processing conditions, simultaneously entailing innovation and expanding the chemical space

Using graph transformation systems to specify and verify data abstractions

This paper proposes an approach for the specification of the behavior of software components that implement data abstractions. By generalizing the approach of behavior models using graph transformation, we provide a concise specification for data abstractions that describes the relationship between the internal state, represented in a canonical form, and the observers of the component. Graph transformation also supports the generation of behavior models that are amenable to verification. To this end, we provide a translation approach into an LTL model on which we can express useful properties that can be model-checked with a SAT solver

Decision trees for early prediction of inadequate immune response to coronavirus infections: a pilot study on COVID-19

Introduction: Few artificial intelligence models exist to predict severe forms of COVID-19. Most rely on post-infection laboratory data, hindering early treatment for high-risk individuals. Methods: This study developed a machine learning model to predict inherent risk of severe symptoms after contracting SARS-CoV-2. Using a Decision Tree trained on 153 Alpha variant patients, demographic, clinical and immunogenetic markers were considered. Model performance was assessed on Alpha and Delta variant datasets. Key risk factors included age, gender, absence of KIR2DS2 gene (alone or with HLA-C C1 group alleles), presence of 14-bp polymorphism in HLA-G gene, presence of KIR2DS5 gene, and presence of KIR telomeric region A/A. Results: The model achieved 83.01% accuracy for Alpha variant and 78.57% for Delta variant, with True Positive Rates of 80.82 and 77.78%, and True Negative Rates of 85.00% and 79.17%, respectively. The model showed high sensitivity in identifying individuals at risk. Discussion: The present study demonstrates the potential of AI algorithms, combined with demographic, epidemiologic, and immunogenetic data, in identifying individuals at high risk of severe COVID-19 and facilitating early treatment. Further studies are required for routine clinical integration

Electron and ion spectroscopy of azobenzene in the valence and core shells

Azobenzene is a prototype and a building block of a class of molecules of extreme technological interest as molecular photo-switches. We present a joint experimental and theoretical study of its response to irradiation with light across the UV to x-ray spectrum. The study of valence and inner shell photo-ionization and excitation processes combined with measurement of valence photoelectron-photoion coincidence and mass spectra across the core thresholds provides a detailed insight into the site- and state-selected photo-induced processes. Photo-ionization and excitation measurements are interpreted via the multi-configurational restricted active space self-consistent field method corrected by second order perturbation theory. Using static modeling, we demonstrate that the carbon and nitrogen K edges of azobenzene are suitable candidates for exploring its photoinduced dynamics thanks to the transient signals appearing in background-free regions of the NEXAFS and XPS

Modeling Parkinson’s disease neuropathology and symptoms by intranigral inoculation of preformed human α-synuclein oligomers

The accumulation of aggregated α-synuclein (αSyn) is a hallmark of Parkinson’s disease (PD). Current evidence indicates that small soluble αSyn oligomers (αSynOs) are the most toxic species among the forms of αSyn aggregates, and that size and topological structural properties are crucial factors for αSynOs-mediated toxicity, involving the interaction with either neurons or glial cells. We previously characterized a human αSynO (H-αSynO) with specific structural properties promoting toxicity against neuronal membranes. Here, we tested the neurotoxic potential of these H-αSynOs in vivo, in relation to the neuropathological and symptomatic features of PD. The H-αSynOs were unilaterally infused into the rat substantia nigra pars compacta (SNpc). Phosphorylated αSyn (p129-αSyn), reactive microglia, and cytokine levels were measured at progressive time points. Additionally, a phagocytosis assay in vitro was performed after microglia pre-exposure to αsynOs. Dopaminergic loss, motor, and cognitive performances were assessed. H-αSynOs triggered p129-αSyn deposition in SNpc neurons and microglia and spread to the striatum. Early and persistent neuroinflammatory responses were induced in the SNpc. In vitro, H-αSynOs inhibited the phagocytic function of microglia. H-αsynOs-infused rats displayed early mitochondrial loss and abnormalities in SNpc neurons, followed by a gradual nigrostriatal dopaminergic loss, associated with motor and cognitive impairment. The intracerebral inoculation of structurally characterized H-αSynOs provides a model of progressive PD neuropathology in rats, which will be helpful for testing neuroprotective therapies

Long-term outcomes of acute severe ulcerative colitis in the rescue therapy era: A multicentre cohort study

BACKGROUND: The long‐term course of ulcerative colitis after a severe attack is poorly understood. Second‐line rescue therapy with cyclosporine or infliximab is effective for reducing short‐term colectomy but the impact in the long‐term is controversial. OBJECTIVE: The purpose of this study was to evaluate the long‐term course of acute severe ulcerative colitis patients who avoid early colectomy either because of response to steroids or rescue therapy. METHODS: This was a multicentre retrospective cohort study of adult patients with acute severe ulcerative colitis admitted to Italian inflammatory bowel disease referral centres from 2005 to 2017. All patients received intravenous steroids, and those who did not respond received either rescue therapy or colectomy. For patients who avoided early colectomy (within 3 months from the index attack), we recorded the date of colectomy, last follow‐up visit or death. The primary end‐point was long‐term colectomy rate in patients avoiding early colectomy. RESULTS: From the included 372 patients with acute severe ulcerative colitis, 337 (90.6%) avoided early colectomy. From those, 60.5% were responsive to steroids and 39.5% to the rescue therapy. Median follow‐up was 44 months (interquartile range, 21–85). Colectomy‐free survival probability was 93.5%, 81.5% and 79.4% at 1, 3 and 5 years, respectively. Colectomy risk was higher among rescue therapy users than in steroid‐responders (log‐rank test, p = 0.02). At multivariate analysis response to steroids was independently associated with a lower risk of long‐term colectomy (adjusted odds ratio = 0.5; 95% confidence interval, 0.2–0.8), while previous exposure to antitumour necrosis factor‐α agents was associated with an increased risk (adjusted odds ratio = 3.0; 95% confidence interval, 1.5–5.7). Approximately 50% of patients required additional therapy or new hospitalisation within 5 years due to a recurrent flare. Death occurred in three patients (0.9%). CONCLUSIONS: Patients with acute severe ulcerative colitis avoiding early colectomy are at risk of long‐term colectomy, especially if previously exposed to antitumour necrosis factor‐α agents or if rescue therapy during the acute attack was required because of steroid refractoriness