A demo-genetic model shows how silviculture reduces natural density-dependent selection in tree populations.

Biological production systems and conservation programs benefit from and should care for evolutionary processes. Developing evolution-oriented strategies requires knowledge of the evolutionary consequences of management across timescales. Here, we used an individual-based demo-genetic modelling approach to study the interactions and feedback between tree thinning, genetic evolution, and forest stand dynamics. The model combines processes that jointly drive survival and mating success-tree growth, competition and regeneration-with genetic variation of quantitative traits related to these processes. In various management and disturbance scenarios, the evolutionary rates predicted by the coupled demo-genetic model for a growth-related trait, vigor, fit within the range of empirical estimates found in the literature for wild plant and animal populations. We used this model to simulate non-selective silviculture and disturbance scenarios over four generations of trees. We characterized and quantified the effect of thinning frequencies and intensities and length of the management cycle on viability selection driven by competition and fecundity selection. The thinning regimes had a drastic long-term effect on the evolutionary rate of vigor over generations, potentially reaching 84% reduction, depending on management intensity, cycle length and disturbance regime. The reduction of genetic variance by viability selection within each generation was driven by changes in genotypic frequencies rather than by gene diversity, resulting in low-long-term erosion of the variance across generations, despite short-term fluctuations within generations. The comparison among silviculture and disturbance scenarios was qualitatively robust to assumptions on the genetic architecture of the trait. Thus, the evolutionary consequences of management result from the interference between human interventions and natural evolutionary processes. Non-selective thinning, as considered here, reduces the intensity of natural selection, while selective thinning (on tree size or other criteria) might reduce or reinforce it depending on the forester's tree choice and thinning intensity.

RNAseq based variant dataset in a black poplar association panel.

OBJECTIVE: Black poplar (Populus nigra L.) is a species native to Eurasia with a wide distribution area. It is an ecologically important species from riparian ecosystems, that is used as a parent of interspecific (P. deltoides x P. nigra) cultivated poplar hybrids. Variant detection from transcriptomics sequences of 241 P. nigra individuals, sampled in natural populations from 11 river catchments (in four European countries) is described here. These data provide new valuable resources for population structure analysis, population genomics and genome-wide association studies. DATA DESCRIPTION: We generated transcriptomics data from a mixture of young differentiating xylem and cambium tissues of 480 Populus nigra trees sampled in a common garden experiment located at Orléans (France), corresponding to 241 genotypes (2 clonal replicates per genotype, at maximum) by using RNAseq technology. We launched on the resulting sequences an in-silico pipeline that allowed us to obtain 878,957 biallelic polymorphisms without missing data. More than 99% of these positions are annotated and 98.8% are located on the 19 chromosomes of the P. trichocarpa reference genome. The raw RNAseq sequences are available at the NCBI Sequence Read Archive SPR188754 and the variant dataset at the Recherche Data Gouv repository under https://doi.org/10.15454/8DQXK5 .

Mate selection: A useful approach to maximize genetic gain and control inbreeding in genomic and conventional oil palm (Elaeis guineensis Jacq.) hybrid breeding.

Genomic selection (GS) is an effective method for the genetic improvement of complex traits in plants and animals. Optimization approaches could be used in conjunction with GS to further increase its efficiency and to limit inbreeding, which can increase faster with GS. Mate selection (MS) typically uses a metaheuristic optimization algorithm, simulated annealing, to optimize the selection of individuals and their matings. However, in species with long breeding cycles, this cannot be studied empirically. Here, we investigated this aspect with forward genetic simulations on a high-performance computing cluster and massively parallel computing, considering the oil palm hybrid breeding example. We compared MS and simple methods of inbreeding management (limitation of the number of individuals selected per family, prohibition of self-fertilization and combination of these two methods), in terms of parental inbreeding and genetic progress over four generations of genomic selection and phenotypic selection. The results showed that, compared to the conventional method without optimization, MS could lead to significant decreases in inbreeding and increases in annual genetic progress, with the magnitude of the effect depending on MS parameters and breeding scenarios. The optimal solution retained by MS differed by five breeding characteristics from the conventional solution: selected individuals covering a broader range of genetic values, fewer individuals selected per full-sib family, decreased percentage of selfings, selfings preferentially made on the best individuals and unbalanced number of crosses among selected individuals, with the better an individual, the higher the number of times he is mated. Stronger slowing-down in inbreeding could be achieved with other methods but they were associated with a decreased genetic progress. We recommend that breeders use MS, with preliminary analyses to identify the proper parameters to reach the goals of the breeding program in terms of inbreeding and genetic gain.

Low Cost Magnetic Field Control for Disabled People.

Our research presents a cost-effective navigation system for electric wheelchairs that utilizes the tongue as a human-machine interface (HMI) for disabled individuals. The user controls the movement of the wheelchair by wearing a small neodymium magnet on their tongue, which is held in place by a suction pad. The system uses low-cost electronics and sensors, including two electronic compasses, to detect the position of the magnet in the mouth. One compass estimates the magnet's position while the other is used as a reference to compensate for static magnetic fields. A microcontroller processes the data using a computational algorithm that takes the mathematical formulations of the magnetic fields as input in real time. The system has been tested using real data to control an electric wheelchair, and it has been shown that a trained user can effectively use tongue movements as an interface for the wheelchair or a computer.

eQTLs are key players in the integration of genomic and transcriptomic data for phenotype prediction.

BACKGROUND: Multi-omics represent a promising link between phenotypes and genome variation. Few studies yet address their integration to understand genetic architecture and improve predictability. RESULTS: Our study used 241 poplar genotypes, phenotyped in two common gardens, with xylem and cambium RNA sequenced at one site, yielding large phenotypic, genomic (SNP), and transcriptomic datasets. Prediction models for each trait were built separately for SNPs and transcripts, and compared to a third model integrated by concatenation of both omics. The advantage of integration varied across traits and, to understand such differences, an eQTL analysis was performed to characterize the interplay between the genome and transcriptome and classify the predicting features into cis or trans relationships. A strong, significant negative correlation was found between the change in predictability and the change in predictor ranking for trans eQTLs for traits evaluated in the site of transcriptomic sampling. CONCLUSIONS: Consequently, beneficial integration happens when the redundancy of predictors is decreased, likely leaving the stage to other less prominent but complementary predictors. An additional gene ontology (GO) enrichment analysis appeared to corroborate such statistical output. To our knowledge, this is a novel finding delineating a promising method to explore data integration.

Examining the Interplay between Queerness and Teacher Wellbeing: A Qualitative Study Based on Foreign Language Teacher Trainers.

Oftentimes, teachers who identify themselves as LGTBIQ+ may feel unsafe at work, which may upset their wellbeing and destabilize their key psychological traits. Hence, feelings such as insecurity, lack of self-confidence, anxiety, and fear are on loop in their everyday lives. Thus, in this study we pursued an examination of the interplay between sexual orientation and teacher wellbeing in a cohort of seven university foreign language teacher trainers in a Spanish context. To gain insight into this issue, a qualitative study in line with the ecological paradigm was designed for the elaboration of semi-structured in-depth interviews and for the analysis of results. The main findings display teacher wellbeing as a complex interwoven system in which sexual orientation had played a core role in their identities, competences, private and professional relationships, and in the cultural and political spheres. We conclude by stating that although homophobic discrimination was a hard trial to overcome, the psychosocial capital of the participants allowed them to transform this negativity into positive assets such as queer activism in their private and political lives and in their profession as foreign language teacher trainers.

How to achieve a higher selection plateau in forest tree breeding? Fostering heterozygote × homozygote relationships in optimal contribution selection in the case study of Populus nigra.

In breeding, optimal contribution selection (OCS) is one of the most effective strategies to balance short- and long-term genetic responses, by maximizing genetic gain and minimizing global coancestry. Considering genetic diversity in the selection dynamic-through coancestry-is undoubtedly the reason for the success of OCS, as it avoids preliminary loss of favorable alleles. Originally formulated with the pedigree relationship matrix, global coancestry can nowadays be assessed with one of the possible formulations of the realized genomic relationship matrix. Most formulations were optimized for genomic evaluation, but few for the management of coancestry. We introduce here an alternative formulation specifically developed for genomic OCS (GOCS), intended to better control heterozygous loci, and thus better account for Mendelian sampling. We simulated a multigeneration breeding program with mate allocation and under GOCS for twenty generations, solved with quadratic programming. With the case study of Populus nigra, we have shown that, although the dynamic was mainly determined by the trade-off between genetic gain and genetic diversity, better formulations of the genomic relationship matrix, especially those fostering individuals carrying multiple heterozygous loci, can lead to better short-term genetic gain and a higher selection plateau.

Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar.

Forest trees like poplar are particular in many ways compared to other domesticated species. They have long juvenile phases, ongoing crop-wild gene flow, extensive outcrossing, and slow growth. All these particularities tend to make the conduction of breeding programs and evaluation stages costly both in time and resources. Perennials like trees are therefore good candidates for the implementation of genomic selection (GS) which is a good way to accelerate the breeding process, by unchaining selection from phenotypic evaluation without affecting precision. In this study, we tried to compare GS to pedigree-based traditional evaluation, and evaluated under which conditions genomic evaluation outperforms classical pedigree evaluation. Several conditions were evaluated as the constitution of the training population by cross-validation, the implementation of multi-trait, single trait, additive and non-additive models with different estimation methods (G-BLUP or weighted G-BLUP). Finally, the impact of the marker densification was tested through four marker density sets. The population under study corresponds to a pedigree of 24 parents and 1,011 offspring, structured into 35 full-sib families. Four evaluation batches were planted in the same location and seven traits were evaluated on 1 and 2 years old trees. The quality of prediction was reported by the accuracy, the Spearman rank correlation and prediction bias and tested with a cross-validation and an independent individual test set. Our results show that genomic evaluation performance could be comparable to the already well-optimized pedigree-based evaluation under certain conditions. Genomic evaluation appeared to be advantageous when using an independent test set and a set of less precise phenotypes. Genome-based methods showed advantages over pedigree counterparts when ranking candidates at the within-family levels, for most of the families. Our study also showed that looking at ranking criteria as Spearman rank correlation can reveal benefits to genomic selection hidden by biased predictions.

Gene expression predictions and networks in natural populations supports the omnigenic theory.

BACKGROUND: Recent literature on the differential role of genes within networks distinguishes core from peripheral genes. If previous works have shown contrasting features between them, whether such categorization matters for phenotype prediction remains to be studied. RESULTS: We measured 17 phenotypic traits for 241 cloned genotypes from a Populus nigra collection, covering growth, phenology, chemical and physical properties. We also sequenced RNA for each genotype and built co-expression networks to define core and peripheral genes. We found that cores were more differentiated between populations than peripherals while being less variable, suggesting that they have been constrained through potentially divergent selection. We also showed that while cores were overrepresented in a subset of genes statistically selected for their capacity to predict the phenotypes (by Boruta algorithm), they did not systematically predict better than peripherals or even random genes. CONCLUSION: Our work is the first attempt to assess the importance of co-expression network connectivity in phenotype prediction. While highly connected core genes appear to be important, they do not bear enough information to systematically predict better quantitative traits than other gene sets.

Sequence imputation from low density single nucleotide polymorphism panel in a black poplar breeding population.

BACKGROUND: Genomic selection accuracy increases with the use of high SNP (single nucleotide polymorphism) coverage. However, such gains in coverage come at high costs, preventing their prompt operational implementation by breeders. Low density panels imputed to higher densities offer a cheaper alternative during the first stages of genomic resources development. Our study is the first to explore the imputation in a tree species: black poplar. About 1000 pure-breed Populus nigra trees from a breeding population were selected and genotyped with a 12K custom Infinium Bead-Chip. Forty-three of those individuals corresponding to nodal trees in the pedigree were fully sequenced (reference), while the remaining majority (target) was imputed from 8K to 1.4 million SNPs using FImpute. Each SNP and individual was evaluated for imputation errors by leave-one-out cross validation in the training sample of 43 sequenced trees. Some summary statistics such as Hardy-Weinberg Equilibrium exact test p-value, quality of sequencing, depth of sequencing per site and per individual, minor allele frequency, marker density ratio or SNP information redundancy were calculated. Principal component and Boruta analyses were used on all these parameters to rank the factors affecting the quality of imputation. Additionally, we characterize the impact of the relatedness between reference population and target population. RESULTS: During the imputation process, we used 7540 SNPs from the chip to impute 1,438,827 SNPs from sequences. At the individual level, imputation accuracy was high with a proportion of SNPs correctly imputed between 0.84 and 0.99. The variation in accuracies was mostly due to differences in relatedness between individuals. At a SNP level, the imputation quality depended on genotyped SNP density and on the original minor allele frequency. The imputation did not appear to result in an increase of linkage disequilibrium. The genotype densification not only brought a better distribution of markers all along the genome, but also we did not detect any substantial bias in annotation categories. CONCLUSIONS: This study shows that it is possible to impute low-density marker panels to whole genome sequence with good accuracy under certain conditions that could be common to many breeding populations.

Deciphering Hybrid Larch Reaction Norms Using Random Regression.

The link between phenotypic plasticity and heterosis is a broad fundamental question, with stakes in breeding. We report a case-study evaluating temporal series of wood ring traits of hybrid larch (Larix decidua × L. kaempferi and reciprocal) in relation to soil water availability. Growth rings record the tree plastic responses to past environmental conditions, and we used random regressions to estimate the reaction norms of ring width and wood density with respect to water availability. We investigated the role of phenotypic plasticity on the construction of hybrid larch heterosis and on the expression of its quantitative genetic parameters. The data came from an intra-/interspecific diallel mating design between both parental species. Progenies were grown in two environmentally contrasted sites, in France. Ring width plasticity with respect to water availability was confirmed, as all three taxa produced narrower rings under the lowest water availability. Hybrid larch appeared to be the most plastic taxon as its superiority over its parental species increased with increasing water availability. Despite the low heritabilities of the investigated traits, we found that the expression of a reliable negative correlation between them was conditional to the water availability environment. Finally, by means of a complementary simulation, we demonstrated that random regression can be applied to model the reaction norms of non-repeated records of phenotypic plasticity bound by a family structure. Random regression is a powerful tool for the modeling of reaction norms in various contexts, especially perennial species.

Incidencia de enfermedad cerebrovascular en un servicio de Medicina Interna / Incidence of cerebrovascular disease in an Internal Medicine service

Resumen: ANTECEDENTES La enfermedad vascular cerebral constituye un importante motivo de ingreso al área de medicina interna y según los diferentes grupos de edad, sexo y manejo hospitalario, alcanza altos niveles de letalidad; en 2010 ocupó el sexto lugar entre las principales causas de defunción en México. OBJETIVO Conocer la estadística de los padecimientos isquémicos y hemorrágicos en el servicio de Medicina Interna con base en datos recopilados con archivos clínicos del Hospital General de Matamoros, Tamaulipas. MATERIAL Y MÉTODO Estudio observacional, retrospectivo y transversal en el que mediante el uso del expediente clínico se obtuvo la información de las variables de edad, género, fecha de ingreso, fecha de egreso, pruebas diagnósticas, tomografías realizadas durante el ingreso del paciente al Hospital General de Matamoros, Tamaulipas, del 26 de junio de 2012 al 21 de junio de 2017. RESULTADOS De 4619 pacientes ingresados al Hospital de Matamoros, Tamaulipas, 438 pacientes tuvieron diagnóstico de enfermedad vascular cerebral (9.4%); de ellos, el hemorrágico representó 18.5%, el isquémico 46.3% y 33.8% no tuvo diagnóstico. La edad media fue de 65 años, con intervalo de 22 a 99 años. Los días de estancia tuvieron variancia de 16.2 días, con media de 2 días, mínimo de 0 y máximo de 26 días. CONCLUSIONES El estudio muestra al hombre con mayor tendencia, con más afectación en personas más jóvenes, lo que difiere del resto de las investigaciones de México y Latinoamérica.

Abstract: BACKGROUND Cerebrovascular disease (CVD) is an important reason for admission to the area of internal medicine in hospitals and with some variations depending on the different age groups, gender, and hospital management. It causes high levels of lethality, occupying in 2010 the sixth place within the main causes of death in Mexico. OBJECTIVE To know the statistics of ischemic and hemorrhagic diseases in the internal medicine service based on data collected from clinical files at the Hospital of Matamoros, Tamaulipas, Mexico. MATERIAL AND METHOD An observational, retrospective and transversal study was done from clinical records to obtain data about the variables of age, gender, date of admission, date of discharge, and diagnostic tests and tomographies performed during the patient's stay at the Hospital of Matamoros, Tamaulipas, Mexico, from June 26th 2012 to June 21st 2017. RESULTS We found that 4619 patients were admitted at the Hospital of Matamoros, Tamaulipas, Mexico. From this group, 438 patients were diagnosed with cerebrovascular disease (9.4%), the hemorrhagic accounted for 18.5%, the ischemic 46.3% and 33.8% were not diagnosed. The age variable had a mean of 65 years old (22-99 years). The days of stay variable had a mean of 2.0 days, a variance of 16.2 days (interval: 0-26 days). CONCLUSIONS The study showed that cerebrovascular disease is present more in men than in women and that cerebrovascular disease affects more frequently to younger people. These findings have an important variation compared to similar research findings in Mexico and Latin America.

Performance of Seven Tree Breeding Strategies Under Conditions of Inbreeding Depression.

In the domestication and breeding of tree species that suffer from inbreeding depression (ID), the long-term performance of different breeding strategies is poorly known. Therefore, seven tree breeding strategies including single population, subline, selfing, and nucleus breeding were simulated using a multi-locus model with additive, partial, and complete dominance allele effects, and with intermediate, U-shaped, and major allele distributions. The strategies were compared for genetic gain, inbreeding accumulation, capacity to show ID, the frequencies and fixations of unfavorable alleles, and genetic variances in breeding and production populations. Measured by genetic gain of production population, the nucleus breeding and the single breeding population with mass selection strategies were equal or superior to subline and single breeding population with within-family selection strategies in all simulated scenarios, in spite of their higher inbreeding coefficients. Inbreeding and cross-breeding effectively decreased ID and could in some scenarios produce genetic gains during the first few generations. However, in all scenarios, considerable fixation of unfavorable alleles rendered the purging performance of selfing and cross-breeding strategies ineffective, and resulted in substantial inferiority in comparison to the other strategies in the long-term.

Genomic selection in maritime pine.

A two-generation maritime pine (Pinus pinaster Ait.) breeding population (n=661) was genotyped using 2500 SNP markers. The extent of linkage disequilibrium and utility of genomic selection for growth and stem straightness improvement were investigated. The overall intra-chromosomal linkage disequilibrium was r(2)=0.01. Linkage disequilibrium corrected for genomic relationships derived from markers was smaller (rV(2)=0.006). Genomic BLUP, Bayesian ridge regression and Bayesian LASSO regression statistical models were used to obtain genomic estimated breeding values. Two validation methods (random sampling 50% of the population and 10% of the progeny generation as validation sets) were used with 100 replications. The average predictive ability across statistical models and validation methods was about 0.49 for stem sweep, and 0.47 and 0.43 for total height and tree diameter, respectively. The sensitivity analysis suggested that prior densities (variance explained by markers) had little or no discernible effect on posterior means (residual variance) in Bayesian prediction models. Sampling from the progeny generation for model validation increased the predictive ability of markers for tree diameter and stem sweep but not for total height. The results are promising despite low linkage disequilibrium and low marker coverage of the genome (∼1.39 markers/cM).

Long-term genomic selection for heterosis without dominance in multiplicative traits: case study of bunch production in oil palm.

BACKGROUND: To study the potential of genomic selection for heterosis resulting from multiplicative interactions between additive and antagonistic components, we focused on oil palm, where bunch production is the product of bunch weight and bunch number. We simulated two realistic breeding populations and compared current reciprocal recurrent selection (RRS) with reciprocal recurrent genomic selection (RRGS) over four generations. All breeding strategies aimed at selecting the best individuals in parental populations to increase bunch production in hybrids. For RRGS, we obtained the parental genomic estimated breeding values using GBLUP with hybrid phenotypes as data records and population specific allele models. We studied the effects of four RRGS parameters on selection response and genetic parameters: (1) the molecular data used to calibrate the GS model: in RRGS_PAR, we used parental genotypes and in RRGS_HYB we also used hybrid genotypes; (2) frequency of progeny tests (model calibration); (3) number of candidates and (4) number of genotyped hybrids in RRGS_HYB. RESULTS: We concluded that RRGS could increase the annual selection response compared to RRS by decreasing the generation interval and by increasing the selection intensity. With 1700 genotyped hybrids, calibration every four generations and 300 candidates per generation and population, selection response of RRGS_HYB was 71.8 % higher than RRS. RRGS_PAR with calibration every two generations and 300 candidates was a relevant alternative, as a good compromise between the annual response, risk around the expected response, increased inbreeding and cost. RRGS required inbreeding management because of a higher annual increase in inbreeding than RRS. CONCLUSIONS: RRGS appeared as a valuable method to achieve a long-term increase in the performance for a trait showing heterosis due to the multiplicative interaction between additive and negatively correlated components, such as oil palm bunch production.

Genomic selection prediction accuracy in a perennial crop: case study of oil palm (Elaeis guineensis Jacq.).

KEY MESSAGE: Genomic selection empirically appeared valuable for reciprocal recurrent selection in oil palm as it could account for family effects and Mendelian sampling terms, despite small populations and low marker density. Genomic selection (GS) can increase the genetic gain in plants. In perennial crops, this is expected mainly through shortened breeding cycles and increased selection intensity, which requires sufficient GS accuracy in selection candidates, despite often small training populations. Our objective was to obtain the first empirical estimate of GS accuracy in oil palm (Elaeis guineensis), the major world oil crop. We used two parental populations involved in conventional reciprocal recurrent selection (Deli and Group B) with 131 individuals each, genotyped with 265 SSR. We estimated within-population GS accuracies when predicting breeding values of non-progeny-tested individuals for eight yield traits. We used three methods to sample training sets and five statistical methods to estimate genomic breeding values. The results showed that GS could account for family effects and Mendelian sampling terms in Group B but only for family effects in Deli. Presumably, this difference between populations originated from their contrasting breeding history. The GS accuracy ranged from -0.41 to 0.94 and was positively correlated with the relationship between training and test sets. Training sets optimized with the so-called CDmean criterion gave the highest accuracies, ranging from 0.49 (pulp to fruit ratio in Group B) to 0.94 (fruit weight in Group B). The statistical methods did not affect the accuracy. Finally, Group B could be preselected for progeny tests by applying GS to key yield traits, therefore increasing the selection intensity. Our results should be valuable for breeding programs with small populations, long breeding cycles, or reduced effective size.

Estimation of genealogical coancestry in plant species using a pedigree reconstruction algorithm and application to an oil palm breeding population.

KEY MESSAGE: Explicit pedigree reconstruction by simulated annealing gave reliable estimates of genealogical coancestry in plant species, especially when selfing rate was lower than 0.6, using a realistic number of markers. Genealogical coancestry information is crucial in plant breeding to estimate genetic parameters and breeding values. The approach of Fernández and Toro (Mol Ecol 15:1657-1667, 2006) to estimate genealogical coancestries from molecular data through pedigree reconstruction was limited to species with separate sexes. In this study it was extended to plants, allowing hermaphroditism and monoecy, with possible selfing. Moreover, some improvements were made to take previous knowledge on the population demographic history into account. The new method was validated using simulated and real datasets. Simulations showed that accuracy of estimates was high with 30 microsatellites, with the best results obtained for selfing rates below 0.6. In these conditions, the root mean square error (RMSE) between the true and estimated genealogical coancestry was small (<0.07), although the number of ancestors was overestimated and the selfing rate could be biased. Simulations also showed that linkage disequilibrium between markers and departure from the Hardy-Weinberg equilibrium in the founder population did not affect the efficiency of the method. Real oil palm data confirmed the simulation results, with a high correlation between the true and estimated genealogical coancestry (>0.9) and a low RMSE (<0.08) using 38 markers. The method was applied to the Deli oil palm population for which pedigree data were scarce. The estimated genealogical coancestries were highly correlated (>0.9) with the molecular coancestries using 100 markers. Reconstructed pedigrees were used to estimate effective population sizes. In conclusion, this method gave reliable genealogical coancestry estimates. The strategy was implemented in the software MOLCOANC 3.0.

Consistency between marker- and genealogy-based heritability estimates in an experimental stand of Prosopis alba (Leguminosae).

Prosopis represents a valuable forest resource in arid and semiarid regions. Management of promising species requires information about genetic parameters, mainly the heritability (h(2)) of quantitative profitable traits. This parameter is traditionally estimated from progeny tests or half-sib analysis conducted in experimental stands. Such an approach estimates h(2) from the ratio of between-family/total phenotypic variance. These analyses are difficult to apply to natural populations of species with a long life cycle, overlapping generations, and a mixed mating system, without genealogical information. A promising alternative is the use of molecular marker information to infer relatedness between individuals and to estimate h(2) from the regression of phenotypic similarity on inferred relatedness. In the current study we compared h(2) of 13 quantitative traits estimated by these two methods in an experimental stand of P. alba, where genealogical information was available. We inferred pairwise relatedness by Ritland's method using six microsatellite loci. Relatedness and heritability estimates from molecular information were highly correlated to the values obtained from genealogical data. Although Ritland's method yields lower h(2) estimates and tends to overestimate genetic correlations between traits, this approach is useful to predict the expected relative gain of different quantitative traits under selection without genealogical information.

Obesity and metabolic risks in children.

BACKGROUND: We undertook this study to establish the prevalence of overweight, obesity, abdominal obesity, high blood pressure, and high glucose and triglyceride levels in school-age children from Mexico City, as well as to determine how overweight and obesity are related to the other risk factors. METHODS: The study was a cross-sectional survey comprised of 1819 children (6-13 years of age) attending six elementary schools. Gender, age, weight, height, waist circumference, blood pressure, and levels of triglycerides and glucose were registered. Percentiles were calculated according to American standards for BMI, height, waist circumference, and blood pressure. RESULTS: Compared to American references, mean percentiles for waist circumference and BMI were >50, and mean height percentiles were <50. Prevalence of overweight was 22.3 and 23.6% for boys and girls, respectively; obesity, 28 and 21.2%; abdominal obesity, 22.1 and 11.7%; high triglyceride levels, 11.3 and 15.4%; high blood pressure, 4.8 and 5.8%, respectively. Overweight, obesity, and abdominal obesity are associated with higher blood pressure and triglyceride levels (odds ratio>1.0, p<0.05). Percentiles for BMI, waist circumference, systolic blood pressure, and diastolic blood pressure also had significant correlations (r>0.2, p<0.001). CONCLUSIONS: This population of Mexican school-age children was shorter and heavier than their American standards. The prevalence of metabolic risks was similar to those reported in American adolescents in NHANES surveys.

Nuevos tratamientos psicológicos en tabaquismo: las intervenciones a distancia / New psychological treatments in tobacco dependence: new non face-to-face smoking cessation interventions

La prevalencia de tabaquismo sigue siendo muy elevada en nuestro país. Sin embargo, no todos los usuarios tienen un acceso fácil a los tratamientos para dejar de fumar. El avance de las nuevas tecnologías ha permitido el desarrollo de programas de tratamiento de tabaquismo a distancia, tanto a través de intervenciones telefónicas o quitlines, como de Internet. La Unidad de Tabaquismo del Hospital Carlos III ha incorporado a su rutina asistencial este tipo de tratamientos. El presente trabajo tiene como objetivo revisar las publicaciones sobre estos nuevos tratamientos de tabaquismo a distancia, así como ver su aplicabilidad clínica en un hospital público con experiencia previa en tratamientos presenciales

Smoking prevalence is still elevated in our country. Neverthless most of smokers do not have an easy acces to smoking cessation treatment. Development of non face-to-face programs though quitlines and internet has been possible thanks to new technologies advance. The objective of this paper is to review the research about new non face-to-face smoking cessation treatments and to analyse its clinic feasibility in a public hospital with previous experience in actual treatments