La drogue, front de lutte pour une société alternative?

L'auteur aborde le problème de la drogue dans une perspective sociologique qui met en relation facteurs structurels et facteurs culturels : marchéde la drogue, société capitaliste, toxicomanie, projet de société. Il émet l'hypothèse que la lutte contre la drogue doit, pour être efficace, s'insérer dans une recherche d'alternative de société. Il donne comme exemple de cette recherche l'expérience de certaines communautés d'accueil, en Italie, et résume les principes qui guident leur action

JPMorgan Chase London Whale F: Required Securities Disclosures

On April 13, 2012, JPMorgan Chase (JPM) Chief Financial Officer Douglas Braunstein took part in a conference call to discuss the bank’s first quarter 2012 earnings. Coming just a week after media reports first questioned the risks taken by JPM derivatives trader Bruno Iksil, Braunstein made a series of assertions about the trades. On May 10, JPM finalized its first quarter financial results, which included some disclosures regarding Iksil’s trading that were substantially different from Braunstein’s statements of April 13. At issue is whether the regulatory filings on April 13 and May 10, as well as verbal comments by Braunstein and Chief Executive Officer Jamie Dimon on those dates, were potentially misleading to investors and thus violated relevant securities laws enforced by the Securities and Exchange Commission

A validated protocol for eDNA-based monitoring of within-species genetic diversity in a pond-breeding amphibian

In light of the dramatic decline in amphibian biodiversity, new cost-efficient tools to rapidly monitor species abundance and population genetic diversity in space and time are urgently needed. It has been amply demonstrated that the use of environmental DNA (eDNA) for single-species detection and characterization of community composition can increase the precision of amphibian monitoring compared to traditional (observational) approaches. However, it has been suggested that the efficiency and accuracy of the eDNA approach could be further improved by more timely sampling; in addition, the quality of genetic diversity data derived from the same DNA has been confirmed in other vertebrate taxa, but not amphibians. Given the availability of previous tissue-based genetic data, here we use the common frog Rana temporaria Linnaeus, 1758 as our target species and an improved eDNA protocol to: (i) investigate differences in species detection between three developmental stages in various freshwater environments; and (ii) study the diversity of mitochondrial DNA (mtDNA) haplotypes detected in eDNA (water) samples, by amplifying a specific fragment of the COI gene (331 base pairs, bp) commonly used as a barcode. Our protocol proved to be a reliable tool for monitoring population genetic diversity of this species, and could be a valuable addition to amphibian conservation and wetland management

In silico Prioritization of Transporter–Drug Relationships From Drug Sensitivity Screens

The interplay between drugs and cell metabolism is a key factor in determining both compound potency and toxicity. In particular, how and to what extent transmembrane transporters affect drug uptake and disposition is currently only partially understood. Most transporter proteins belong to two protein families: the ATP-Binding Cassette (ABC) transporter family, whose members are often involved in xenobiotic efflux and drug resistance, and the large and heterogeneous family of solute carriers (SLCs). We recently argued that SLCs are collectively a rather neglected gene group, with most of its members still poorly characterized, and thus likely to include many yet-to-be-discovered associations with drugs. We searched publicly available resources and literature to define the currently known set of drugs transported by ABCs or SLCs, which involved ∼500 drugs and more than 100 transporters. In order to extend this set, we then mined the largest publicly available pharmacogenomics dataset, which involves approximately 1,000 molecularly annotated cancer cell lines and their response to 265 anti-cancer compounds, and used regularized linear regression models (Elastic Net, LASSO) to predict drug responses based on SLC and ABC data (expression levels, SNVs, CNVs). The most predictive models included both known and previously unidentified associations between drugs and transporters. To our knowledge, this represents the first application of regularized linear regression to this set of genes, providing an extensive prioritization of potentially pharmacologically interesting interactions

Is recurrence in major depressive disorder related to bipolarity and mixed features? Results from the BRIDGE-II-Mix study

Background: Current classifications separate Bipolar (BD) from Major Depressive Disorder (MDD) based on polarity rather than recurrence. We aimed to determine bipolar/mixed feature frequency in a large MDD multinational sample with (High-Rec) and without (Low-Rec) >3 recurrences, comparing the two subsamples. Methods: We measured frequency of bipolarity/hypomanic features during current depressive episodes (MDEs) in 2347 MDD patients from the BRIDGE-II-mix database, comparing High-Rec with Low-Rec. We used Bonferroni-corrected Student's t-test for continuous, and chi-squared test, for categorical variables. Logistic regression estimated the size of the association between clinical characteristics and High-Rec MDD. Results: Compared to Low-Rec (n = 1084, 46.2%), High-Rec patients (n = 1263, 53.8%) were older, with earlier depressive onset, had more family history of BD, more atypical features, suicide attempts, hospitalisations, and treatment resistance and (hypo)manic switches when treated with antidepressants, higher comorbidity with borderline personality disorder, and more hypomanic symptoms during current MDE, resulting in higher rates of mixed depression according to both DSM-5 and research-based diagnostic (RBDC) criteria. Logistic regression showed age at first symptoms < 30 years, current MDE duration ≤ 1 month, hypomania/mania among first-degree relatives, past suicide attempts, treatment-resistance, antidepressant-induced swings, and atypical, mixed, or psychotic features during MDE to associate with High-Rec. Limitations Number of MDEs for defining recurrence was arbitrary; cross-sectionality did not allow assessment of conversion from MDD to BD. Conclusions: High-Rec MDD differed from Low-Rec group for several clinical/epidemiological variables, including bipolar/mixed features. Bipolarity specifier and RBDC were more sensitive than DSM-5 criteria in detecting bipolar and mixed features in MDD

A multivariate approach to investigate the associations of electrophysiological indices with schizophrenia clinical and functional outcome

Abstract Background Different electrophysiological (EEG) indices have been investigated as possible biomarkers of schizophrenia. However, these indices have a very limited use in clinical practice, as their associations with clinical and functional outcomes remain unclear. This study aimed to investigate the associations of multiple EEG markers with clinical variables and functional outcomes in subjects with schizophrenia (SCZs). Methods Resting-state EEGs (frequency bands and microstates) and auditory event-related potentials (MMN-P3a and N100-P3b) were recorded in 113 SCZs and 57 healthy controls (HCs) at baseline. Illness- and functioning-related variables were assessed both at baseline and at 4-year follow-up in 61 SCZs. We generated a machine-learning classifier for each EEG parameter (frequency bands, microstates, N100-P300 task, and MMN-P3a task) to identify potential markers discriminating SCZs from HCs, and a global classifier. Associations of the classifiers’ decision scores with illness- and functioning-related variables at baseline and follow-up were then investigated. Results The global classifier discriminated SCZs from HCs with an accuracy of 75.4% and its decision scores significantly correlated with negative symptoms, depression, neurocognition, and real-life functioning at 4-year follow-up. Conclusions These results suggest that a combination of multiple EEG alterations is associated with poor functional outcomes and its clinical and cognitive determinants in SCZs. These findings need replication, possibly looking at different illness stages in order to implement EEG as a possible tool for the prediction of poor functional outcome

The interplay among psychopathology, personal resources, context-related factors and real-life functioning in schizophrenia: stability in relationships after 4 years and differences in network structure between recovered and non-recovered patients

Improving real-life functioning is the main goal of the most advanced integrated treatment programs in people with schizophrenia. The Italian Network for Research on Psychoses previously explored, by using network analysis, the interplay among illness-related variables, personal resources, context-related factors and real-life functioning in a large sample of patients with schizophrenia. The same research network has now completed a 4-year follow-up of the original sample. In the present study, we used network analysis to test whether the pattern of relationships among all variables investigated at baseline was similar at follow-up. In addition, we compared the network structure of patients who were classified as recovered at follow-up versus those who did not recover. Six hundred eighteen subjects recruited at baseline could be assessed in the follow-up study. The network structure did not change significantly from baseline to follow-up, and the overall strength of the connections among variables increased slightly, but not significantly. Functional capacity and everyday life skills had a high betweenness and closeness in the network at follow-up, as they had at baseline, while psychopathological variables remained more peripheral. The network structure and connectivity of non-recovered patients were similar to those observed in the whole sample, but very different from those in recovered subjects, in which we found few connections only. These data strongly suggest that tightly coupled symptoms/dysfunctions tend to maintain each other's activation, contributing to poor outcome in schizophrenia. Early and integrated treatment plans, targeting variables with high centrality, might prevent the emergence of self-reinforcing networks of symptoms and dysfunctions in people with schizophrenia