High-fidelity simulation increases obstetric self-assurance and skills in undergraduate medical students

Objective: Teaching intrapartum care is one of the most challenging tasks in undergraduate medical education. High-fidelity obstetric simulators might support students' learning experience. The specific educational impact of these simulators compared with traditional methods of model-based obstetric teaching has not yet been determined. Study design: We randomly assigned 46 undergraduate medical students to be taught using either a high-fidelity simulator or a scale wood-and-leather phantom. Their self-assessments were evaluated using a validated questionnaire. We assessed obstetric skills and asked students to solve obstetric paper cases. Main outcome measures: Assessment of fidelity-specific teaching impact on procedural knowledge, motivation, and interest in obstetrics as well as obstetric skills using high- and low-fidelity training models. Results: High-fidelity simulation specifically improved students' feeling that they understood both the physiology of parturition and the obstetric procedures. Students in the simulation group also felt better prepared for obstetric house jobs and performed better in obstetric skills evaluations. However, the two groups made equivalent obstetric decisions. Conclusion: This study provides first data on the impact of high-fidelity simulation in an undergraduate setting

Exploring the Applicability of the Science Communication Research Agenda to Agricultural Communications Scholarship

Agricultural communications scholars do not use a national research agenda to guide their research, which could be limiting the impact and rigor of the discipline. In this commentary, we argue that agricultural communications scholars should adopt the science communication research agenda published by the National Academies of Sciences, Engineering, and Medicine in 2017 because the goals of science communication, outlined in the agenda, are relevant to agriculture. Members of the committee who developed the agenda study science communication in contexts of food, agriculture, life sciences, the environment, political science, health, nutrition, and psychology, among others. They developed the agenda with the intent for it to inform and guide research in all science communication sub-disciplines or areas involving contentious public issues. We provide examples of studies that have used the agenda to inform research in agricultural and natural resources communications. We also explain how research priorities outlined in the science communication research agenda align with agricultural communications scholarship. Recognizing there are challenges unique to agriculture, we recommend agricultural communications scholars use the science communication research agenda as a research guide and adapt the relevant research recommendations for agricultural communications

Sustainable forest use in Brazilian extractive reserves: natural regeneration of Brazil nut in exploited populations.

The emergence of Brazilian extractive reserves reinforced the notion that sustainable forest use could play a central role in conservation. Brazil nut is considered a model non-timber product for promoting conservation through use. Demographic studies, however, have demonstrated differential impacts of nut harvest on Brazil nut population structure. Comparing three populations with different forest use histories, degrees of road access, and recent levels of nut harvest, we asked: (1) Are they exhibiting regeneration failure? and (2) Are seedling/sapling densities explained by adult Brazil nut structure, fruit fate and/or overall forest structure? We installed four 9-ha plots in each site to census Brazil nut trees > 10 cm dbh, and within each plot, 36 subplots (25 × 25 m each) to quantify regeneration, overall forest structure, and open and closed fruit counts. Approximately 29-55% of fruits was unharvested, and more than 90% of these was opened by scatterhoarding dispersers. Population structure approximated a reverse-J size class distribution, with seedling densities varying from 3.2 to 5.8 individuals ha-1. We conclude that within the current harvest context, regeneration is sufficient for population persistence in our sites, at least over the medium term. The socioeconomics of sustainably managing Brazil nut is the greater challenge, involving interlinked competitive land uses, nut quality, and substantial increases in local income from harvest. Some of these challenges are being addressed in Brazil, Bolivia and Peru, providing hope that this cornerstone extractive species will continue to play a prominent role in the ecological and economic landscape of Amazonia

Nut production in Bertholletia excelsa across a logged forest mosaic: implications for multiple forest use

Although many examples of multiple-use forest management may be found in tropical smallholder systems, few studies provide empirical support for the integration of selective timber harvesting with non-timber forest product (NTFP) extraction. Brazil nut (Bertholletia excelsa, Lecythidaceae) is one of the world’s most economically-important NTFP species extracted almost entirely from natural forests across the Amazon Basin. An obligate out-crosser, Brazil nut flowers are pollinated by large-bodied bees, a process resulting in a hard round fruit that takes up to 14 months to mature. As many smallholders turn to the financial security provided by timber, Brazil nut fruits are increasingly being harvested in logged forests. We tested the influence of tree and stand-level covariates (distance to nearest cut stump and local logging intensity) on total nut production at the individual tree level in five recently logged Brazil nut concessions covering about 4000 ha of forest in Madre de Dios, Peru. Our field team accompanied Brazil nut harvesters during the traditional harvest period (January-April 2012 and January-April 2013) in order to collect data on fruit production. Three hundred and ninety-nine (approximately 80%) of the 499 trees included in this study were at least 100 m from the nearest cut stump, suggesting that concessionaires avoid logging near adult Brazil nut trees. Yet even for those trees on the edge of logging gaps, distance to nearest cut stump and local logging intensity did not have a statistically significant influence on Brazil nut production at the applied logging intensities (typically 1–2 timber trees removed per ha). In one concession where at least 4 trees ha-1 were removed, however, the logging intensity covariate resulted in a marginally significant (0.09) P value, highlighting a potential risk for a drop in nut production at higher intensities. While we do not suggest that logging activities should be completely avoided in Brazil nut rich forests, when a buffer zone cannot be observed, low logging intensities should be implemented. The sustainability of this integrated management system will ultimately depend on a complex series of socioeconomic and ecological interactions. Yet we submit that our study provides an important initial step in understanding the compatibility of timber harvesting with a high value NTFP, potentially allowing for diversification of forest use strategies in Amazonian Perù

Prenatal diagnosis of Neu-Laxova syndrome: a case report

BACKGROUND: Neu-Laxova syndrome is a rare congenital abnormality involving multiple systems. We report a case of Neu-Laxova syndrome (NLS) diagnosed prenatally by ultrasound examination. CASE PRESENTATION: A 29-year-old gravida 3, para 2 woman was first seen in our antenatal clinic at 38 weeks' pregnancy. Except for the consanguinity and two previous abnormal stillborn babies her medical history was unremarkable. On ultrasound examination microcephaly, flat forehead, micrognathia, intrauterine growth restriction, generalized edema of the skin, hypoplastic chest, excessive soft tissue deposition of hands and feet, joint contractures and a penis without scrotal sacs were detected. She delivered a 2000 g male fetus. He died five minutes after delivery. Postmortem examination confirmed the diagnosis of Neu-Laxova syndrome. CONCLUSION: Because of the autosomal recessive inheritance of Neu-Laxova syndrome genetic counseling and early-serial ultrasound examination should be performed at risk families. Early diagnosis of the disease may offer termination of the pregnancy as an option

Evaluation of methods and marker systems in genomic selection of oil palm (Elaeis guineensis Jacq.)

Background Genomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits. Results The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods. Conclusion Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation

High Throughput Screening Technologies in Biomass Characterization

Biomass analysis is a slow and tedious process and not solely due to the long generation time for most plant species. Screening large numbers of plant variants for various geno-, pheno-, and chemo-types, whether naturally occurring or engineered in the lab, has multiple challenges. Plant cell walls are complex, heterogeneous networks that are difficult to deconstruct and analyze. Macroheterogeneity from tissue types, age, and environmental factors makes representative sampling a challenge and natural variability generates a significant range in data. Using high throughput (HTP) methodologies allows for large sample sets and replicates to be examined, narrowing in on more precise data for various analyses. This review provides a comprehensive survey of high throughput screening as applied to biomass characterization, from compositional analysis of cell walls by NIR, NMR, mass spectrometry, and wet chemistry to functional screening of changes in recalcitrance via HTP thermochemical pretreatment coupled to enzyme hydrolysis and microscale fermentation. The advancements and development of most high-throughput methods have been achieved through utilization of state-of-the art equipment and robotics, rapid detection methods, as well as reduction in sample size and preparation procedures. The computational analysis of the large amount of data generated using high throughput analytical techniques has recently become more sophisticated, faster and economically viable, enabling a more comprehensive understanding of biomass genomics, structure, composition, and properties. Therefore, methodology for analyzing large datasets generated by the various analytical techniques is also covered

Why Don't We Ask? A Complementary Method for Assessing the Status of Great Apes

Species conservation is difficult. Threats to species are typically high and immediate. Effective solutions for counteracting these threats, however, require synthesis of high quality evidence, appropriately targeted activities, typically costly implementation, and rapid re-evaluation and adaptation. Conservation management can be ineffective if there is insufficient understanding of the complex ecological, political, socio-cultural, and economic factors that underlie conservation threats. When information about these factors is incomplete, conservation managers may be unaware of the most urgent threats or unable to envision all consequences of potential management strategies. Conservation research aims to address the gap between what is known and what knowledge is needed for effective conservation. Such research, however, generally addresses a subset of the factors that underlie conservation threats, producing a limited, simplistic, and often biased view of complex, real world situations. A combination of approaches is required to provide the complete picture necessary to engage in effective conservation. Orangutan conservation (Pongo spp.) offers an example: standard conservation assessments employ survey methods that focus on ecological variables, but do not usually address the socio-cultural factors that underlie threats. Here, we evaluate a complementary survey method based on interviews of nearly 7,000 people in 687 villages in Kalimantan, Indonesia. We address areas of potential methodological weakness in such surveys, including sampling and questionnaire design, respondent biases, statistical analyses, and sensitivity of resultant inferences. We show that interview-based surveys can provide cost-effective and statistically robust methods to better understand poorly known populations of species that are relatively easily identified by local people. Such surveys provide reasonably reliable estimates of relative presence and relative encounter rates of such species, as well as quantifying the main factors that threaten them. We recommend more extensive use of carefully designed and implemented interview surveys, in conjunction with more traditional field methods

Seasonal differences in leaf-level physiology give lianas a competitive advantage over trees in a tropical seasonal forest

Lianas are an important component of most tropical forests, where they vary in abundance from high in seasonal forests to low in aseasonal forests. We tested the hypothesis that the physiological ability of lianas to fix carbon (and thus grow) during seasonal drought may confer a distinct advantage in seasonal tropical forests, which may explain pan-tropical liana distributions. We compared a range of leaf-level physiological attributes of 18 co-occurring liana and 16 tree species during the wet and dry seasons in a tropical seasonal forest in Xishuangbanna, China. We found that, during the wet season, lianas had significantly higher CO2 assimilation per unit mass (Amass), nitrogen concentration (Nmass), and δ13C values, and lower leaf mass per unit area (LMA) than trees, indicating that lianas have higher assimilation rates per unit leaf mass and higher integrated water-use efficiency (WUE), but lower leaf structural investments. Seasonal variation in CO2 assimilation per unit area (Aarea), phosphorus concentration per unit mass (Pmass), and photosynthetic N-use efficiency (PNUE), however, was significantly lower in lianas than in trees. For instance, mean tree Aarea decreased by 30.1% from wet to dry season, compared with only 12.8% for lianas. In contrast, from the wet to dry season mean liana δ13C increased four times more than tree δ13C, with no reduction in PNUE, whereas trees had a significant reduction in PNUE. Lianas had higher Amass than trees throughout the year, regardless of season. Collectively, our findings indicate that lianas fix more carbon and use water and nitrogen more efficiently than trees, particularly during seasonal drought, which may confer a competitive advantage to lianas during the dry season, and thus may explain their high relative abundance in seasonal tropical forests