Cannabinoids in the treatment of epilepsy: current status and future prospects

Cannabidiol (CBD) is one of the prominent phytocannabinoids found in Cannabis sativa, differentiating from Δ9-tetrahydrocannabinol (THC) for its non-intoxicating profile and its antianxiety/antipsychotic effects. CBD is a multi-target drug whose anti-convulsant properties are supposed to be independent of endocannabinoid receptor CB1 and might be related to several underlying mechanisms, such as antagonism on the orphan GPR55 receptor, regulation of adenosine tone, activation of 5HT1A receptors and modulation of calcium intracellular levels. CBD is a lipophilic compound with low oral bioavailability (6%) due to poor intestinal absorption and high first-pass metabolism. Its exposure parameters are greatly influenced by feeding status (ie, high fatcontaining meals). It is mainly metabolized by cytochrome P 450 (CYP) 3A4 and 2C19, which it strongly inhibits. A proprietary formulation of highly purified, plant-derived CBD has been recently licensed as an adjunctive treatment for Dravet syndrome (DS) and Lennox-Gastaut syndrome (LGS), while it is being currently investigated in tuberous sclerosis complex. The regulatory agencies’ approval was granted based on four pivotal double-blind, placebocontrolled, randomized clinical trials (RCTs) on overall 154 DS patients and 396 LGS ones, receiving CBD 10 or 20 mg/kg/day BID as active treatment. The primary endpoint (reduction in monthly seizure frequency) was met by both CBD doses. Most patients reported adverse events (AEs), generally from mild to moderate and transient, which mainly consisted of somnolence, sedation, decreased appetite, diarrhea and elevation in aminotransferase levels, the last being documented only in subjects on concomitant valproate therapy. The interaction between CBD and clobazam, likely due to CYP2C19 inhibition, might contribute to some AEs, especially somnolence, but also to CBD clinical effectiveness. Cannabidivarin (CBDV), the propyl analogue of CBD, showed anti-convulsant properties in pre-clinical studies, but a plant-derived, purified proprietary formulation of CBDV recently failed the Phase II RCT in patients with uncontrolled focal seizures

How did COVID-19 affect medical and cardiology journals? A pandemic in literature

BACKGROUND AND AIMS: The spreading speed of the COVID-19 pandemic forced the medical community to produce efforts in updating and sharing the evidence about this new disease, trying to preserve the accuracy of the data but at the same time avoiding the potentially harmful delay from discovery to implementation. The aim of our analysis was to assess the impact of the COVID-19 pandemic on medical literature in terms of proportion of COVID-19-related published papers and temporal patterns of publications within a sample of general/internal medicine and cardiology journals. METHODS: We searched through PubMed scientific papers published from 1 January 2020 to 31 January 2021 about COVID-19 in ten major medical journals, of which five were in general/internal medicine and five in the cardiology field. We analyzed the proportion of COVID-19-related papers, and we examined temporal trends in the number of published papers. RESULTS: Overall, the proportion of COVID-19-related papers was 18.5% (1986/10 756). This proportion was higher among the five selected general/internal medicine journals, compared with cardiology journals (23.8% vs 9.5%). The vast majority of papers were not original articles; in particular, in cardiology journals, there were 28% 'original articles', 17% 'review articles' and 55.1% 'miscellaneous', compared with 20.2%, 5.1% and 74.7% in general/internal medicine journals, respectively. CONCLUSIONS: Our analysis highlights the big impact of the COVID-19 pandemic on international scientific literature. General and internal medicine journals were mainly involved, with cardiology journals only at a later time

The AHEAD Portal: A Gateway to European Historical Earthquake Data

The description of the seismicity of the European region is today fragmented into an increasing number of earthquake archives, databases, and catalogs related to individual countries or even to part of them. Therefore, the compilation of a comprehensive, European earthquake history requires dealing with a puzzle of partially overlapping, only partially public catalogs, the background of which is compiled according to varied schemes. One of the consequences is that earthquakes in the frontier areas are often interpreted in a conflicting way by the catalogs of the bordering countries. In the framework of the European Commission (EC), 2006–2010 Network of Research Infrastructures for European Seismology (NERIES) Project, the task of Networking Activity 4 (NA4) was defined precisely to conceive and develop solutions to bridge over these differences. NA4 promoted the cooperation among existing national online archives, and contributed establishing new regional online archives compiled according to common standards. As a result, a first release of the distributed European archive of historical earthquake data, for the time-window 1000–1899 and for the large earthquakes, was published in 2010. Special attention was devoted to retrieve the earthquake background information, that is, the results of historical earthquake investigation—referenced to as studies in the following -in terms of a paper, a report, a book chapter, a map, etc. As the most useful studies are those supplying a set of macroseismic data points (MDPs)- that is a list of localities (name and coordinates) with a macroseismic intensity assessment and the related macroseismic scale—a dedicated effort was addressed to make such data available. The Archive of Historical Earthquake Data (AHEAD) distributed archive was improved and updated in the frame of the 2010–2012 EC Project Seismic Hazard Harmonization in Europe (SHARE), Task 3.1 European earthquake database, with the contribution of a number of European institutions. For the time window 1000–1899, it was AHEAD (AHEAD Working Group) that supported the compilation of the SHARE European Earthquake Catalog (SHEEC; Stucchi et al., 2013). This paper describes the AHEAD portal (http://www.emidius.eu/AHEAD/; last accessed March 2014), and how it was conceived to network the local components of the distributed archive. Although local historical macroseismic databases usually supply one set of information for each earthquake, at a European scale an earthquake still might be described by several studies, available from different archives. The AHEAD portal inventories and gives access to multiple sets of information concerning each earthquake, and allows users to get comprehensive information about individual earthquakes, providing the answers to the following questions: 1. which sets of earthquake parameters (time, location, magnitude, magnitude type, maximum intensity, etc.) are available for each earthquake? 2. what is the background information, or supporting material, upon which each set of earthquake parameter determination is based

Achieving descriptive accuracy in explanations via argumentation: the case of probabilistic classifiers

The pursuit of trust in and fairness of AI systems in order to enable human-centric goals has been gathering pace of late, often supported by the use of explanations for the outputs of these systems. Several properties of explanations have been highlighted as critical for achieving trustworthy and fair AI systems, but one that has thus far been overlooked is that of descriptive accuracy (DA), i.e., that the explanation contents are in correspondence with the internal working of the explained system. Indeed, the violation of this core property would lead to the paradoxical situation of systems producing explanations which are not suitably related to how the system actually works: clearly this may hinder user trust. Further, if explanations violate DA then they can be deceitful, resulting in an unfair behavior toward the users. Crucial as the DA property appears to be, it has been somehow overlooked in the XAI literature to date. To address this problem, we consider the questions of formalizing DA and of analyzing its satisfaction by explanation methods. We provide formal definitions of naive, structural and dialectical DA, using the family of probabilistic classifiers as the context for our analysis. We evaluate the satisfaction of our given notions of DA by several explanation methods, amounting to two popular feature-attribution methods from the literature, variants thereof and a novel form of explanation that we propose. We conduct experiments with a varied selection of concrete probabilistic classifiers and highlight the importance, with a user study, of our most demanding notion of dialectical DA, which our novel method satisfies by design and others may violate. We thus demonstrate how DA could be a critical component in achieving trustworthy and fair systems, in line with the principles of human-centric AI

A short introduction to historical earthquakes in Libya

As a result of the relative motion of the African and European plates, Libya, located at the north central margin of the African continent, has experienced a considerable intraplate tectonism, particularly in its northern coastal regions. If the seismic activity of the last fifty years, at most, is known from instrumental recording, macroseismic effects of those earthquakes which affected Libya in the past centuries are still imperfectly known. To try and partly overcome this lack of information, in this contribution we present a short introduction to historical earthquakes in Libya, focusing on the period up to 1935. According to the studies published in the last twenty years, the earliest records of earthquakes in Libya are documented in the Roman period (3rd and 4th century A.D.). There is a gap in information along the Middle and Modern Ages, while the 19th and early 20th century evidence is concentrated on effects in Tripoli, in the western part of nowadays Libya. The Hun Graben area (western part of the Gulf of Sirt) has been identified as the location of many earthquakes affecting Libya, and it is in this area that the 19 April 1935 earthquake (Mw = 7.1) struck, followed by many aftershocks. Further investigations are needed, and some hints are here given at historical sources potentially reporting on earthquake effects in Libya. Their investigation could result in the needed improvement to lay the foundations of a database and a catalogue of the historical seismicity of Libya

Quantum Homodyne Tomography as an Informationally Complete Positive Operator Valued Measure

We define a positive operator valued measure $E$ on $[0,2\pi]\times R$ describing the measurement of randomly sampled quadratures in quantum homodyne tomography, and we study its probabilistic properties. Moreover, we give a mathematical analysis of the relation between the description of a state in terms of $E$ and the description provided by its Wigner transform.Comment: 9 page

Vibrational spectrum of solid picene (C_22H_14)

Recently, Mitsuhashi et al., have observed superconductivity with transition temperature up to 18 K in potassium doped picene (C22H14), a polycyclic aromatic hydrocarbon compound [Nature 464 (2010) 76]. Theoretical analysis indicate the importance of electron-phonon coupling in the superconducting mechanisms of these systems, with different emphasis on inter- and intra-molecular vibrations, depending on the approximations used. Here we present a combined experimental and ab-initio study of the Raman and infrared spectrum of undoped solid picene, which allows us to unanbiguously assign the vibrational modes. This combined study enables the identification of the modes which couple strongly to electrons and hence can play an important role in the superconducting properties of the doped samples

Explaining classifiers’ outputs with causal models and argumentation

We introduce a conceptualisation for generating argumentation frameworks (AFs) from causal models for the purpose of forging explanations for mod-els’ outputs. The conceptualisation is based on reinterpreting properties of semantics of AFs as explanation moulds, which are means for characterising argumentative relations. We demonstrate our methodology by reinterpreting the property of bi-variate reinforcement in bipolar AFs, showing how the ex-tracted bipolar AFs may be used as relation-based explanations for the outputs of causal models. We then evaluate our method empirically when the causal models represent (Bayesian and neural network) machine learning models for classification. The results show advantages over a popular approach from the literature, both in highlighting specific relationships between feature and classification variables and in generating counterfactual explanations with respect to a commonly used metric