Lao peasants on the move: Pathways of agrarian change in Laos

Grant Evans’ body of work on Laos consistently sought to understand how peasant society responded to political, social and economic change. As the Lao peasantry became ever more integrated both nationally and within the wider Southeast Asian region, and relations of market exchange came to dominate rural life, Evans maintained the need to reflect on Laos’ peasant roots to understand resulting pathways of agrarian change. This paper reconnects with this discussion in the contemporary Lao context, focusing on three dimensions of mobility: the widening spatial and sectoral ‘footprints’ of rural livelihoods; physical movement within and beyond rural settings in Laos; and reflections on issues of differentiation. We first track the political and policy changes that have most strongly influenced rural life since Evans’ early research on collectivisation, before exploring ways in which spatial integration, subsistence‐to‐commercial transition and migration have situated the remnants of Lao peasant society in a world of flows.     

Estimating age‐dependent survival from age‐aggregated ringing data—extending the use of historical records

Bird ring‐recovery data have been widely used to estimate demographic parameters such as survival probabilities since the mid‐20th century. However, while the total number of birds ringed each year is usually known, historical information on age at ringing is often not available. A standard ring‐recovery model, for which information on age at ringing is required, cannot be used when historical data are incomplete. We develop a new model to estimate age‐dependent survival probabilities from such historical data when age at ringing is not recorded; we call this the historical data model. This new model provides an extension to the model of Robinson, 2010, Ibis, 152, 651–795 by estimating the proportion of the ringed birds marked as juveniles as an additional parameter. We conduct a simulation study to examine the performance of the historical data model and compare it with other models including the standard and conditional ring‐recovery models. Simulation studies show that the approach of Robinson, 2010, Ibis, 152, 651–795 can cause bias in parameter estimates. In contrast, the historical data model yields similar parameter estimates to the standard model. Parameter redundancy results show that the newly developed historical data model is comparable to the standard ring‐recovery model, in terms of which parameters can be estimated, and has fewer identifiability issues than the conditional model. We illustrate the new proposed model using Blackbird and Sandwich Tern data. The new historical data model allows us to make full use of historical data and estimate the same parameters as the standard model with incomplete data, and in doing so, detect potential changes in demographic parameters further back in time.     

Heritability of hyperphagic eating behavior and appetite-related hormones among Hispanic children

Objective: Eating in the absence of hunger (EAH) may be a genetically influenced phenotype of overweight children, but evidence is limited. This research evaluated the heritability (h²) of EAH and its association with overweight among Hispanic children 5 to 18 years old. Genetic and environmental associations of EAH with overweight, fat mass, and key hormonal regulators of food intake were also evaluated. Research Methods and Procedures: A family design was used to study 801 children from 300 Hispanic families. Weighed food intakes were used to measure EAH after an ad libitum dinner providing 50% of estimated energy needs. Fasting ghrelin, amylin, insulin, and leptin were measured by immunoassays. Measured heights, weights, and fat mass (using DXA) were obtained. Total energy expenditure (TEE) was measured by room respiration calorimetry. Results: On average, children consumed 41% of TEE at the dinner meal, followed by an additional 19% of TEE in the absence of hunger. Overweight children consumed 6.5% more energy at dinner (p < 0.001) and 14% more energy in the absence of hunger (p < 0.001) than non‐overweight children. Significant heritabilities were seen for EAH (h² = 0.51) and dinner intake (h² = 0.52) and for fasting levels of ghrelin (h² = 0.67), amylin (h² = 0.37), insulin (h² = 0.37), and leptin (h² = 0.34). Genetic correlations were seen between eating behavior and fasting hormones, suggesting common underlying genes affecting their expression. Discussion: This research provides new evidence that overweight Hispanic children exhibit elevated levels of hyperphagic eating behaviors that are influenced by genetic endowment.     

Deriving respiratory cell types from stem cells

The reported pluripotential capabilities of many human stem cell types has made them an attractive area of research, given the belief they may hold considerable therapeutic potential for treating a wide range of human diseases and injuries. Although the bulk of stem cell based research has focused on developing procedures for the treatment of pancreatic, neural, cardiovascular and haematopoietic diseases, the potential for deriving respiratory cell types from stem cells for treatment of respiratory specific diseases has also been explored. It is suggested that stem cell derivatives may be used for lung replacement/regeneration therapeutics and high though-put pharmacological screening strategies for a variety of respiratory injuries and diseases including: cystic fibrosis, chronic obstructive pulmonary disease, respiratory distress syndrome, pulmonary fibrosis and pulmonary edema. This review will explore recent progress in characterizing adult respiratory and bone marrow derived stem cells with respiratory potential as well as the endogenous mechanisms directing the homing of these cells to the diseased and injured lung. In addition, the potential for embryonic stem cell based therapies in this domain as well as the histological, anatomical and molecular aspects of respiratory development will be summarized.     

Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data

This study assesses the ability of a novel family of machine learning algorithms to identify changes in relative protein expression levels, measured using 2-D DIGE data, which support accurate class prediction. The analysis was done using a training set of 36 total cellular lysates comprised of six normal and three cancer biological replicates (the remaining are technical replicates) and a validation set of four normal and two cancer samples. Protein samples were separated by 2-D DIGE and expression was quantified using DeCyder-2D Differential Analysis Software. The relative expression reversal (RER) classifier correctly classified 9/9 training biological samples (p<0.022) as estimated using a modified version of leave one out cross validation and 6/6 validation samples. The classification rule involved comparison of expression levels for a single pair of protein spots, tropomyosin isoforms and alpha-enolase, both of which have prior association as potential biomarkers in cancer. The data was also analyzed using algorithms similar to those found in the extended data analysis package of DeCyder software. We propose that by accounting for sources of within- and between-gel variation, RER classifiers applied to 2-D DIGE data provide a useful approach for identifying biomarkers that discriminate among protein samples of interest.     

Use of bimolecular fluorescence complementation to study in vivo interactions between Cdc42p and Rdi1p of Saccharomyces cerevisiae

Saccharomyces cerevisiae Cdc42p functions as a GTPase molecular switch, activating multiple signaling pathways required to regulate cell cycle progression and the actin cytoskeleton. Regulatory proteins control its GTP binding and hydrolysis and its subcellular localization, ensuring that Cdc42p is appropriately activated and localized at sites of polarized growth during the cell cycle. One of these, the Rdi1p guanine nucleotide dissociation inhibitor, negatively regulates Cdc42p by extracting it from cellular membranes. In this study, the technique of bimolecular fluorescence complementation (BiFC) was used to study the dynamic in vivo interactions between Cdc42p and Rdi1p. The BiFC data indicated that Cdc42p and Rdi1p interacted in the cytoplasm and around the periphery of the cell at the plasma membrane and that this interaction was enhanced at sites of polarized cell growth during the cell cycle, i.e., incipient bud sites, tips and sides of small- and medium-sized buds, and the mother-bud neck region. In addition, a ring-like structure containing the Cdc42p-Rdi1p complex transiently appeared following release from G1-phase cell cycle arrest. A homology model of the Cdc42p-Rdi1p complex was used to introduce mutations that were predicted to affect complex formation. These mutations resulted in altered BiFC interactions, restricting the complex exclusively to either the plasma membrane or the cytoplasm. Data from these studies have facilitated the temporal and spatial modeling of Rdi1p-dependent extraction of Cdc42p from the plasma membrane during the cell cycle.     

Phylogeny and evolutionary history of diplobathrid crinoids (Echinodermata)

Order Diplobathrida is a major clade of camerate crinoids spanning the Ordovician–Mississippian, yet phylogenetic relationships have only been inferred for Ordovician taxa. This has hampered efforts to construct a comprehensive tree of life for crinoids and develop a classification scheme that adequately reflects diplobathrid evolutionary history. Here, I apply maximum parsimony and Bayesian phylogenetic approaches to the fossil record of diplobathrids to infer the largest tree of fossil crinoids to date, with over 100 genera included. Recovered trees provide a framework for evaluating the current classification of diplobathrids. Notably, previous suborder divisions are not supported, and superfamily divisions will require significant modification. Although numerous revisions are required for families, most can be retained through reassignment of genera. In addition, recovered trees were used to produce phylogeny‐based estimates of diplobathrid lineage diversity. By accounting for ghost lineages, phylogeny‐based richness estimates offer greater insight into diversification and extinction dynamics than traditional taxonomy‐based approaches alone and provide a detailed summary of the ~150 million‐year evolutionary history of Diplobathrida. This study constitutes a major step toward producing a phylogeny of the Crinoidea and documenting crinoid diversity dynamics. In addition, it will serve as a framework for subsequent phylogeny‐based investigations of macroevolutionary questions.     

A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens

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