Sequence heterogeneity and anomalous electrophoretic mobility of kinetoplast minicircle DNA from Leishmania tarentolae

Several unit-length minicircles from the kinetoplast DNA of Leishmania tarentolae were cloned into pBR322 and into M13 phage vectors. The complete nucleotide sequences of three different partially homologous minicircles were obtained. The molecules contained a region of approx. 80% sequence homology extending for 160–270 bp and a region unique to each minicircle. A 14-mer was found to be conserved in all kinetoplast minicircle sequences reported to date. The frequency distributions of various minicircle sequence classes in L. tarentolae were obtained by quantitative gel electrophoresis and by examination of the “T ladder” patterns of minicircles randomly cloned into M13 at several sites. By these methods we could assign approx. 50% of the total minicircle DNA into a minimum of five sequence classes. A sequence-dependent polyacrylamide gel migration abnormality was observed with several minicircle fragments both cloned and uncloned. The abnormality was dependent on the presence of a portion of the conserved region of the minicircle.     

Mechanisms of madness: evolutionary psychiatry without evolutionary psychology

Delusions are currently characterised as false beliefs produced by incorrect inference about external reality (DSM IV). This inferential conception has proved hard to link to explanations pitched at the level of neurobiology and neuroanatomy. This paper provides that link via a neurocomputational theory, based on evolutionary considerations, of the role of the prefrontal cortex in regulating offline cognition. When pathologically neuromodulated the prefrontal cortex produces hypersalient experiences which monopolise offline cognition. The result is characteristic psychotic experiences and patterns of thought. This bottom-up account uses neural network theory to integrate recent theories of the role of dopamine in delusion with the insights of inferential accounts. It also provides a general model for evolutionary psychiatry which avoids theoretical problems imported from evolutionary psychology.     

Substance use disorders: a comprehensive update of classification,epidemiology, neurobiology,clinical aspects,treatment and prevention

Substance use disorders (SUDs) are highly prevalent and exact a large toll on individuals’ health, well-being, and social functioning. Long-lasting changes in brain networks involved in reward, executive function, stress reactivity, mood, and self-awareness underlie the intense drive to consume substances and the inability to control this urge in a person who suffers from addiction (moderate or severe SUD). Biological (including genetics and developmental life stages) and social (including adverse childhood experiences) determinants of health are recognized factors that contribute to vulnerability for or resilience against developing a SUD. Consequently, prevention strategies that target social risk factors can improve outcomes and, when deployed in childhood and adolescence, can decrease the risk for these disorders. SUDs are treatable, and evidence of clinically significant benefit exists for medications (in opioid, nicotine and alcohol use disorders), behavioral therapies (in all SUDs), and neuromodulation (in nicotine use disorder). Treatment of SUDs should be considered within the context of a Chronic Care Model, with the intensity of intervention adjusted to the severity of the disorder and with the concomitant treatment of comorbid psychiatric and physical conditions. Involvement of health care providers in detection and management of SUDs, including referral of severe cases to specialized care, offers sustainable models of care that can be further expanded with the use of telehealth. Despite advances in our understanding and management of SUDs, individuals with these conditions continue to be stigmatized and, in some countries, incarcerated, highlighting the need to dismantle policies that perpetuate their criminalization and instead develop policies to ensure support and access to prevention and treatment.     

Protected areas in the world’s ecoregions: How well connected are they?

Protected areas (PAs) are the main instrument for biodiversity conservation, which has triggered the development of numerous indicators and assessments on their coverage, performance and efficiency. The connectivity of the PA networks at a global scale has however been much less explored; previous studies have either focused on particular regions of the world or have only considered some types of PAs.Here we present, and globally assess, ProtConn, an indicator of PA connectivity that (i) quantifies the percentage of a study region covered by protected connected lands, (ii) can be partitioned in several components depicting different categories of land (unprotected, protected or transboundary) through which movement between protected locations may occur, (iii) is easy to communicate, to compare with PA coverage and to use in the assessment of global targets for PA systems.We apply ProtConn to evaluate the connectivity of the PA networks in all terrestrial ecoregions of the world as of June 2016, considering a range of median dispersal distances (1–100 km) encompassing the dispersal abilities of the large majority of terrestrial vertebrates.We found that 9.3% of the world is covered by protected connected lands (average for all the world’s ecoregions) for a reference dispersal distance of 10 km, increasing up to 11.7% for the largest dispersal distance considered of 100 km. These percentages are considerably smaller than the global PA coverage of 14.7%, indicating that the spatial arrangement of PAs is only partially successful in ensuring connectivity of protected lands. The connectivity of PAs largely differed across ecoregions. Only about a third of the world’s ecoregions currently meet the Aichi Target of having 17% of the terrestrial realm covered by well-connected systems of PAs. Finally, our findings suggest that PAs with less strict management objectives (allowing the sustainable use of resources) may play a fundamental role in upholding the connectivity of the PA systems.Our analyses and indicator make it possible to identify where on the globe additional efforts are most needed in expanding or reinforcing the connectivity of PA systems, and can be also used to assess whether newly designated sites provide effective connectivity gains in the PA system by acting as corridors or stepping stones between other PAs. The results of the ProtConn indicator are available, together with a suite of other global PA indicators, in the Digital Observatory for Protected Areas of the Joint Research Centre of the European Commission.     

Biochemical evidence accumulates across neurons to drive a network-level eruption

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Evolutionary processes driving spatial patterns of intraspecific genetic diversity in river ecosystems

Describing, understanding and predicting the spatial distribution of genetic diversity is a central issue in biological sciences. In river landscapes, it is generally predicted that neutral genetic diversity should increase downstream, but there have been few attempts to test and validate this assumption across taxonomic groups. Moreover, it is still unclear what are the evolutionary processes that may generate this apparent spatial pattern of diversity. Here, we quantitatively synthesized published results from diverse taxa living in river ecosystems, and we performed a meta‐analysis to show that a downstream increase in intraspecific genetic diversity (DIGD) actually constitutes a general spatial pattern of biodiversity that is repeatable across taxa. We further demonstrated that DIGD was stronger for strictly waterborne dispersing than for overland dispersing species. However, for a restricted data set focusing on fishes, there was no evidence that DIGD was related to particular species traits. We then searched for general processes underlying DIGD by simulating genetic data in dendritic‐like river systems. Simulations revealed that the three processes we considered (downstream‐biased dispersal, increase in habitat availability downstream and upstream‐directed colonization) might generate DIGD. Using random forest models, we identified from simulations a set of highly informative summary statistics allowing discriminating among the processes causing DIGD. Finally, combining these discriminant statistics and approximate Bayesian computations on a set of twelve empirical case studies, we hypothesized that DIGD were most likely due to the interaction of two of these three processes and that contrary to expectation, they were not solely caused by downstream‐biased dispersal.