Analysis of motoneuron responses to composite synaptic volleys (computer simulation study)

This paper deals with the analysis of changes in motoneuron (MN) firing evoked by repetitively applied stimuli aimed toward extracting information about the underlying synaptic volleys. Spike trains were obtained from computer simulations based on a threshold-crossing model of tonically firing MN, subjected to stimulation producing postsynaptic potentials (PSPs) of various parameters. These trains were analyzed as experimental results, using the output measures that were previously shown to be most effective for this purpose: peristimulus time histogram, raster plot and peristimulus time intervalgram. The analysis started from the effects of single excitatory and inhibitory PSPs (EPSPs and IPSPs). The conclusions drawn from this analysis allowed the explanation of the results of more complex synaptic volleys, i.e., combinations of EPSPs and IPSPs, and the formulation of directions for decoding the results of human neurophysiological experiments in which the responses of tonically firing MNs to nerve stimulation are analyzed

Decision Models and Technology Can Help Psychiatry Develop Biomarkers

Why is psychiatry unable to define clinically useful biomarkers? We explore this question from the vantage of data and decision science and consider biomarkers as a form of phenotypic data that resolves a well-defined clinical decision. We introduce a framework that systematizes different forms of phenotypic data and further introduce the concept of decision model to describe the strategies a clinician uses to seek out, combine, and act on clinical data. Though many medical specialties rely on quantitative clinical data and operationalized decision models, we observe that, in psychiatry, clinical data are gathered and used in idiosyncratic decision models that exist solely in the clinician's mind and therefore are outside empirical evaluation. This, we argue, is a fundamental reason why psychiatry is unable to define clinically useful biomarkers: because psychiatry does not currently quantify clinical data, decision models cannot be operationalized and, in the absence of an operationalized decision model, it is impossible to define how a biomarker might be of use. Here, psychiatry might benefit from digital technologies that have recently emerged specifically to quantify clinically relevant facets of human behavior. We propose that digital tools might help psychiatry in two ways: first, by quantifying data already present in the standard clinical interaction and by allowing decision models to be operationalized and evaluated; second, by testing whether new forms of data might have value within an operationalized decision model. We reference successes from other medical specialties to illustrate how quantitative data and operationalized decision models improve patient care

Measuring co-authorship and networking-adjusted scientific impact

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I1 for a single scientist as the number of authors who appear in at least I1 papers of the specific scientist. For a group of scientists or institution, In is defined as the number of authors who appear in at least In papers that bear the affiliation of the group or institution. I1 depends on the number of papers authored Np. The power exponent R of the relationship between I1 and Np categorizes scientists as solitary (R>2.5), nuclear (R=2.25-2.5), networked (R=2-2.25), extensively networked (R=1.75-2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. In similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.Comment: 25 pages, 5 figure

Disposition of Federally Owned Surpluses

PDZ domains are scaffolding modules in protein-protein interactions that mediate numerous physiological functions by interacting canonically with the C-terminus or non-canonically with an internal motif of protein ligands. A conserved carboxylate-binding site in the PDZ domain facilitates binding via backbone hydrogen bonds; however, little is known about the role of these hydrogen bonds due to experimental challenges with backbone mutations. Here we address this interaction by generating semisynthetic PDZ domains containing backbone amide-to-ester mutations and evaluating the importance of individual hydrogen bonds for ligand binding. We observe substantial and differential effects upon amide-to-ester mutation in PDZ2 of postsynaptic density protein 95 and other PDZ domains, suggesting that hydrogen bonding at the carboxylate-binding site contributes to both affinity and selectivity. In particular, the hydrogen-bonding pattern is surprisingly different between the non-canonical and canonical interaction. Our data provide a detailed understanding of the role of hydrogen bonds in protein-protein interactions

Mimicking human neuronal pathways in silico: an emergent model on the effective connectivity

International audienceWe present a novel computational model that detects temporal configurations of a given human neuronal pathway and constructs its artificial replication. This poses a great challenge since direct recordings from individual neurons are impossible in the human central nervous system and therefore the underlying neuronal pathway has to be considered as a black box. For tackling this challenge, we used a branch of complex systems modeling called artificial self-organization in which large sets of software entities interacting locally give rise to bottom-up collective behaviors. The result is an emergent model where each software entity represents an integrate-and-fire neuron. We then applied the model to the reflex responses of single motor units obtained from conscious human subjects. Experimental results show that the model recovers functionality of real human neuronal pathways by comparing it to appropriate surrogate data. What makes the model promising is the fact that, to the best of our knowledge, it is the first realistic model to self-wire an artificial neuronal network by efficiently combining neuroscience with artificial self-organization. Although there is no evidence yet of the model's connectivity mapping onto the human connectivity, we anticipate this model will help neuroscientists to learn much more about human neuronal networks, and could also be used for predicting hypotheses to lead future experiments

Study protocol to investigate the effect of a lifestyle intervention on body weight, psychological health status and risk factors associated with disease recurrence in women recovering from breast cancer treatment

Background Breast cancer survivors often encounter physiological and psychological problems related to their diagnosis and treatment that can influence long-term prognosis. The aim of this research is to investigate the effects of a lifestyle intervention on body weight and psychological well-being in women recovering from breast cancer treatment, and to determine the relationship between changes in these variables and biomarkers associated with disease recurrence and survival. Methods/design Following ethical approval, a total of 100 patients will be randomly assigned to a lifestyle intervention (incorporating dietary energy restriction in conjunction with aerobic exercise training) or normal care control group. Patients randomised to the dietary and exercise intervention will be given individualised healthy eating dietary advice and written information and attend moderate intensity aerobic exercise sessions on three to five days per week for a period of 24 weeks. The aim of this strategy is to induce a steady weight loss of up to 0.5 Kg each week. In addition, the overall quality of the diet will be examined with a view to (i) reducing the dietary intake of fat to ~25% of the total calories, (ii) eating at least 5 portions of fruit and vegetables a day, (iii) increasing the intake of fibre and reducing refined carbohydrates, and (iv) taking moderate amounts of alcohol. Outcome measures will include body weight and body composition, psychological health status (stress and depression), cardiorespiratory fitness and quality of life. In addition, biomarkers associated with disease recurrence, including stress hormones, estrogen status, inflammatory markers and indices of innate and adaptive immune function will be monitored. Discussion This research will provide valuable information on the effectiveness of a practical, easily implemented lifestyle intervention for evoking positive effects on body weight and psychological well-being, two important factors that can influence long-term prognosis in breast cancer survivors. However, the added value of the study is that it will also evaluate the effects of the lifestyle intervention on a range of biomarkers associated with disease recurrence and survival. Considered together, the results should improve our understanding of the potential role that lifestyle-modifiable factors could play in saving or prolonging lives

New Disturbing Trend in Antimicrobial Resistance of Gram-Negative Pathogens

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Increased Litterfall in Tropical Forests Boosts the Transfer of Soil CO2 to the Atmosphere

Aboveground litter production in forests is likely to increase as a consequence of elevated atmospheric carbon dioxide (CO2) concentrations, rising temperatures, and shifting rainfall patterns. As litterfall represents a major flux of carbon from vegetation to soil, changes in litter inputs are likely to have wide-reaching consequences for soil carbon dynamics. Such disturbances to the carbon balance may be particularly important in the tropics because tropical forests store almost 30% of the global soil carbon, making them a critical component of the global carbon cycle; nevertheless, the effects of increasing aboveground litter production on belowground carbon dynamics are poorly understood. We used long-term, large-scale monthly litter removal and addition treatments in a lowland tropical forest to assess the consequences of increased litterfall on belowground CO2 production. Over the second to the fifth year of treatments, litter addition increased soil respiration more than litter removal decreased it; soil respiration was on average 20% lower in the litter removal and 43% higher in the litter addition treatment compared to the controls but litter addition did not change microbial biomass. We predicted a 9% increase in soil respiration in the litter addition plots, based on the 20% decrease in the litter removal plots and an 11% reduction due to lower fine root biomass in the litter addition plots. The 43% measured increase in soil respiration was therefore 34% higher than predicted and it is possible that this ‘extra’ CO2 was a result of priming effects, i.e. stimulation of the decomposition of older soil organic matter by the addition of fresh organic matter. Our results show that increases in aboveground litter production as a result of global change have the potential to cause considerable losses of soil carbon to the atmosphere in tropical forests

The DCDC2 deletion is not a risk factor for dyslexia

Dyslexia is a specific impairment in learning to read and has strong heritability. An intronic deletion within the DCDC2 gene, with ~8% frequency in European populations, is increasingly used as a marker for dyslexia in neuroimaging and behavioral studies. At a mechanistic level, this deletion has been proposed to influence sensory processing capacity, and in particular sensitivity to visual coherent motion. Our re-assessment of the literature, however, did not reveal strong support for a role of this specific deletion in dyslexia. We also analyzed data from five distinct cohorts, enriched for individuals with dyslexia, and did not identify any signal indicative of associations for the DCDC2 deletion with reading-related measures, including in a combined sample analysis (N=526). We believe we conducted the first replication analysis for a proposed deletion effect on visual motion perception and found no association (N=445 siblings). We also report that the DCDC2 deletion has a frequency of 37.6% in a cohort representative of the general population recruited in Hong Kong (N=220). This figure, together with a lack of association between the deletion and reading abilities in this cohort, indicates the low likelihood of a direct deletion effect on reading skills. Therefore, on the basis of multiple strands of evidence, we conclude that the DCDC2 deletion is not a strong risk factor for dyslexia. Our analyses and literature re-evaluation are important for interpreting current developments within multidisciplinary studies of dyslexia and, more generally, contribute to current discussions about the importance of reproducibility in science

Within-group behavioral variation promotes biased task performance and the emergence of a defensive caste in a social spider

The social spider Anelosimus studiosus exhibits a behavioral polymorphism where colony members express either a passive, tolerant behavioral tendency (social) or an aggressive, intolerant behavioral tendency (asocial). Here we test whether asocial individuals act as colony defenders by deflecting the suite of foreign (i.e., heterospecific) spider species that commonly exploit multi-female colonies. We (1) determined whether the phenotypic composition of colonies is associated with foreign spider abundance, (2) tested whether heterospecific spider abundance and diversity affect colony survival in the field, and (3) performed staged encounters between groups of A. studiosus and their colony-level predator Agelenopsis emertoni (A. emertoni)to determine whether asocial females exhibit more defensive behavior. We found that larger colonies harbor more foreign spiders, and the number of asocial colony members was negatively associated with foreign spider abundance. Additionally, colony persistence was negatively associated with the abundance and diversity of foreign spiders within colonies. In encounters with a colony-level predator, asocial females were more likely to exhibit escalatory behavior, and this might explain the negative association between the frequency of asocial females and the presence of foreign spider associates. Together, our results indicate that foreign spiders are detrimental to colony survival, and that asocial females play a defensive role in multi-female colonies