The biological origin of linguistic diversity

In contrast with animal communication systems, diversity is characteristic of almost every aspect of human language. Languages variously employ tones, clicks, or manual signs to signal differences in meaning; some languages lack the noun-verb distinction (e.g., Straits Salish), whereas others have a proliferation of fine-grained syntactic categories (e.g., Tzeltal); and some languages do without morphology (e.g., Mandarin), while others pack a whole sentence into a single word (e.g., Cayuga). A challenge for evolutionary biology is to reconcile the diversity of languages with the high degree of biological uniformity of their speakers. Here, we model processes of language change and geographical dispersion and find a consistent pressure for flexible learning, irrespective of the language being spoken. This pressure arises because flexible learners can best cope with the observed high rates of linguistic change associated with divergent cultural evolution following human migration. Thus, rather than genetic adaptations for specific aspects of language, such as recursion, the coevolution of genes and fast-changing linguistic structure provides the biological basis for linguistic diversity. Only biological adaptations for flexible learning combined with cultural evolution can explain how each child has the potential to learn any human language

Characteristics of transposable element exonization within human and mouse

Insertion of transposed elements within mammalian genes is thought to be an important contributor to mammalian evolution and speciation. Insertion of transposed elements into introns can lead to their activation as alternatively spliced cassette exons, an event called exonization. Elucidation of the evolutionary constraints that have shaped fixation of transposed elements within human and mouse protein coding genes and subsequent exonization is important for understanding of how the exonization process has affected transcriptome and proteome complexities. Here we show that exonization of transposed elements is biased towards the beginning of the coding sequence in both human and mouse genes. Analysis of single nucleotide polymorphisms (SNPs) revealed that exonization of transposed elements can be population-specific, implying that exonizations may enhance divergence and lead to speciation. SNP density analysis revealed differences between Alu and other transposed elements. Finally, we identified cases of primate-specific Alu elements that depend on RNA editing for their exonization. These results shed light on TE fixation and the exonization process within human and mouse genes.Comment: 11 pages, 4 figure

Does final energy demand in Portugal exhibit long memory? A fractional integration analysis

In this paper, we measure the degree of fractional integration in final energy demand in Portugal using an ARFIMA model with and without adjustments for seasonality. We consider aggregate energy demand as well as final demand for petroleum, electricity, coal, and natural gas. Our findings suggest the presence of long memory in all of the components of energy demand. All fractional-difference param- eters are positive and lower than 0.5 indicating that the series are stationary, although with mean reversion patterns slower than in the typical short-run processes. These results have important implications for the design of energy policies. As a result of the long-memory in final energy demand, the effects of temporary policy shocks will tend to disappear slowly. This means that even transitory shocks have long lasting effects. Given the temporary nature of these effects, however, permanent effects on final energy demand require permanent policies. This is unlike what would be suggested by the more standard, but much more limited, unit root approach, which would incorrectly indicate that even transitory policies would have permanent effects.info:eu-repo/semantics/publishedVersio

Autism as a disorder of neural information processing: directions for research and targets for therapy

The broad variation in phenotypes and severities within autism spectrum disorders suggests the involvement of multiple predisposing factors, interacting in complex ways with normal developmental courses and gradients. Identification of these factors, and the common developmental path into which theyfeed, is hampered bythe large degrees of convergence from causal factors to altered brain development, and divergence from abnormal brain development into altered cognition and behaviour. Genetic, neurochemical, neuroimaging and behavioural findings on autism, as well as studies of normal development and of genetic syndromes that share symptoms with autism, offer hypotheses as to the nature of causal factors and their possible effects on the structure and dynamics of neural systems. Such alterations in neural properties may in turn perturb activity-dependent development, giving rise to a complex behavioural syndrome many steps removed from the root causes. Animal models based on genetic, neurochemical, neurophysiological, and behavioural manipulations offer the possibility of exploring these developmental processes in detail, as do human studies addressing endophenotypes beyond the diagnosis itself

Particulate matter Air Pollution induces hypermethylation of the p16 promoter Via a mitochondrial ROS-JNK-DNMT1 pathway

Exposure of human populations to chronically elevated levels of ambient particulate matter air pollution < 2.5 μm in diameter (PM2.5) has been associated with an increase in lung cancer incidence. Over 70% of lung cancer cell lines exhibit promoter methylation of the tumor suppressor p16, an epigenetic modification that reduces its expression. We exposed mice to concentrated ambient PM2.5 via inhalation, 8 hours daily for 3 weeks and exposed primary murine alveolar epithelial cells to daily doses of fine urban PM (5 µg/cm2). In both mice and alveolar epithelial cells, PM exposure increased ROS production, expression of the DNA methyltransferase 1 (DNMT1), and methylation of the p16 promoter. In alveolar epithelial cells, increased transcription of DNMT1 and methylation of the p16 promoter were inhibited by a mitochondrially targeted antioxidant and a JNK inhibitor. These findings provide a potential mechanism by which PM exposure increases the risk of lung cancer

Development and validation of the Multi-dimensional University Research Workplace Inventory (MDURWI)

WOS:000454839600005This study describes the development and validation of an instrument aimed toward measuring organizational features of an academic research workplace. The question pool was developed based on data from a pilot study (N = 43). The survey was deployed to academic researchers in the field of higher education research worldwide (N = 850). An exploratory factor analysis conducted on 36 questions, followed by confirmatory factor analysis, which lead to a final pool of 27 questions in five subscales, one of which divided into three lower-order factors. The final model exhibited very good fit (X2/df = 2.561; CFI = 0.972; PCFI = 0.784; RMSEA = 0.043; P[rmsea ? 0.05] < 0.001; AIC = 891.018; BCC = 987.839) and psychometric properties, in the form of factorial, convergent, and discriminant validity, as well as reliability and sensitivity. Implications of this instrument for research and policymaking are discussed, as well as future research directions.info:eu-repo/semantics/acceptedVersio

Top-Down Control of Herbivory by Birds and Bats in the Canopy of Temperate Broad-Leaved Oaks (Quercus robur)

The intensive foraging of insectivorous birds and bats is well known to reduce the density of arboreal herbivorous arthropods but quantification of collateral leaf damage remains limited for temperate forest canopies

Risk of hyperkalemia in patients with moderate chronic kidney disease initiating angiotensin converting enzyme inhibitors or angiotensin receptor blockers : a randomized study

Background: Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers are renoprotective but both may increase serum potassium concentrations in patients with chronic kidney disease (CKD). The proportion of affected patients, the optimum follow-up period and whether there are differences between drugs in the development of this complication remain to be scertained. Methods: In a randomized, double-blind, phase IV, controlled, crossover study we recruited 30 patients with stage 3 CKD under restrictive eligibility criteria and strict dietary control. With the exception of withdrawals, each patient was treated with olmesartan and enalapril separately for 3 months each, with a 1-week wash-out period between treatments. Patients were clinically assessed on 10 occasions via measurements of serum and urine samples. We used the Cochran-Mantel-Haenszel statistics for comparison of categorical data between groups. Comparisons were also made using independent two-sample t-tests and Welch's t-test. Analysis of variance (ANOVA) was performed when necessary. We used either a Mann-Whitney or Kruskal-Wallis test if the distribution was not normal or the variance not homogeneous. Results: Enalapril and olmesartan increased serum potassium levels similarly (0.3 mmol/L and 0.24 mmol/L respectively). The percentage of patients presenting hyperkalemia higher than 5 mmol/L did not differ between treatments: 37% for olmesartan and 40% for enalapril. The mean e-GFR ranged 46.3 to 48.59 ml/mint/1.73 m2 in those treated with olmesartan and 46.8 to 48.3 ml/mint/1.73 m2 in those with enalapril and remained unchanged at the end of the study. The decreases in microalbuminuria were also similar (23% in olmesartan and 29% in enalapril patients) in the 4 weeks time point. The percentage of patients presenting hyperkalemia, even after a two month period, did not differ between treatments. There were no appreciable changes in sodium and potassium urinary excretion. Conclusions: Disturbances in potassium balance upon treatment with either olmesartan or enalapril are frequent and without differences between groups. The follow-up of these patients should include control of potassium levels, at least after the first week and the first and second month after initiating treatment