The Impacts of Farmland Expropriation on Vietnam's Rural Households

The expropriation of agricultural land to provide new land for industrial and urban expansion, referred to as compulsory acquisition, is prevalent in developing countries. Using Vietnam as a laboratory, this study evaluates the impacts of losing farmland through compulsory acquisition on household welfare and reaches the following findings. A 10 percentage point increase in the proportion of land expropriated results in a 2.2% decrease in household welfare proxied by food expenditure. Besides, politically unconnected and ethnic minority households are disproportionately vulnerable. The adverse welfare effect could take up to 10 years to evaporate. The reduction in household welfare is attributable to the decline in agricultural income and the inability to participate in the non-agricultural labor market. Other aspects of household behavior following compulsory acquisition are also explored, such as saving, social capital, labor, and capital allocation

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound–kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV

Reproducible, Ultra High-Throughput Formation of Multicellular Organization from Single Cell Suspension-Derived Human Embryonic Stem Cell Aggregates

Background: Human embryonic stem cells (hESC) should enable novel insights into early human development and provide a renewable source of cells for regenerative medicine. However, because the three-dimensional hESC aggregates [embryoid bodies (hEB)] typically employed to reveal hESC developmental potential are heterogeneous and exhibit disorganized differentiation, progress in hESC technology development has been hindered. Methodology/Principal Findings: Using a centrifugal forced-aggregation strategy in combination with a novel centrifugalextraction approach as a foundation, we demonstrated that hESC input composition and inductive environment could be manipulated to form large numbers of well-defined aggregates exhibiting multi-lineage differentiation and substantially improved self-organization from single-cell suspensions. These aggregates exhibited coordinated bi-domain structures including contiguous regions of extraembryonic endoderm- and epiblast-like tissue. A silicon wafer-based microfabrication technology was used to generate surfaces that permit the production of hundreds to thousands of hEB per cm 2. Conclusions/Significance: The mechanisms of early human embryogenesis are poorly understood. We report an ultra high throughput (UHTP) approach for generating spatially and temporally synchronised hEB. Aggregates generated in this manner exhibited aspects of peri-implantation tissue-level morphogenesis. These results should advance fundamental studies into early human developmental processes, enable high-throughput screening strategies to identify conditions tha

Localized Fetomaternal Hyperglycemia: Spatial and Kinetic Definition by Positron Emission Tomography

to isolated hyperglycemia in the pregnant rat. mg/dL) localized to the left uterine artery was sustained for at least 48 hours while maternal euglycemia was maintained. fetal effects of isolated hyperglycemia. Broadly, this approach can be extended to study a variety of maternal-sided perturbations suspected to directly affect fetal health

Role of Matrix Metalloproteinases and Therapeutic Benefits of Their Inhibition in Spinal Cord Injury

This review will focus on matrix metalloproteinases (MMPs) and their inhibitors in the context of spinal cord injury (SCI). MMPs have a specific cellular and temporal pattern of expression in the injured spinal cord. Here we consider their diverse functions in the acutely injured cord and during wound healing. Excessive activity of MMPs, and in particular gelatinase B (MMP-9), in the acutely injured cord contributes to disruption of the blood-spinal cord barrier, and the influx of leukocytes into the injured cord, as well as apoptosis. MMP-9 and MMP-2 regulate inflammation and neuropathic pain after peripheral nerve injury and may contribute to SCI-induced pain. Early pharmacologic inhibition of MMPs or the gelatinases (MMP-2 and MMP-9) results in an improvement in long-term neurological recovery and is associated with reduced glial scarring and neuropathic pain. During wound healing, gelatinase A (MMP-2) plays a critical role in limiting the formation of an inhibitory glial scar, and mice that are genetically deficient in this protease showed impaired recovery. Together, these findings illustrate complex, temporally distinct roles of MMPs in SCIs. As early gelatinase activity is detrimental, there is an emerging interest in developing gelatinase-targeted therapeutics that would be specifically tailored to the acute injured spinal cord. Thus, we focus this review on the development of selective gelatinase inhibitors

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Infectious causes of microcephaly: epidemiology, pathogenesis, diagnosis, and management.

Microcephaly is an important sign of neurological malformation and a predictor of future disability. The 2015-16 outbreak of Zika virus and congenital Zika infection brought the world's attention to links between Zika infection and microcephaly. However, Zika virus is only one of the infectious causes of microcephaly and, although the contexts in which they occur vary greatly, all are of concern. In this Review, we summarise important aspects of major congenital infections that can cause microcephaly, and describe the epidemiology, transmission, clinical features, pathogenesis, management, and long-term consequences of these infections. We include infections that cause substantial impairment: cytomegalovirus, herpes simplex virus, rubella virus, Toxoplasma gondii, and Zika virus. We highlight potential issues with classification of microcephaly and show how some infants affected by congenital infection might be missed or incorrectly diagnosed. Although Zika virus has brought the attention of the world to the problem of microcephaly, prevention of all infectious causes of microcephaly and appropriately managing its consequences remain important global public health priorities

Expression and Putative Function of Innate Immunity Genes under in situ Conditions in the Symbiotic Hydrothermal Vent Tubeworm Ridgeia piscesae

The relationships between hydrothermal vent tubeworms and sulfide-oxidizing bacteria have served as model associations for understanding chemoautotrophy and endosymbiosis. Numerous studies have focused on the physiological and biochemical adaptations that enable these symbioses to sustain some of the highest recorded carbon fixation rates ever measured. However, far fewer studies have explored the molecular mechanisms underlying the regulation of host and symbiont interactions, specifically those mediated by the innate immune system of the host. To that end, we conducted a series of studies where we maintained the tubeworm, Ridgeia piscesae, in high-pressure aquaria and examined global and quantitative changes in gene expression via high-throughput transcriptomics and quantitative real-time PCR (qPCR). We analyzed over 32,000 full-length expressed sequence tags as well as 26 Mb of transcript sequences from the trophosome (the organ that houses the endosymbiotic bacteria) and the plume (the gas exchange organ in contact with the free-living microbial community). R. piscesae maintained under conditions that promote chemoautotrophy expressed a number of putative cell signaling and innate immunity genes, including pattern recognition receptors (PRRs), often associated with recognizing microbe-associated molecular patterns (MAMPs). Eighteen genes involved with innate immunity, cell signaling, cell stress and metabolite exchange were further analyzed using qPCR. PRRs, including five peptidoglycan recognition proteins and a Toll-like receptor, were expressed significantly higher in the trophosome compared to the plume. Although PRRs are often associated with mediating host responses to infection by pathogens, the differences in expression between the plume and trophosome also implicate similar mechanisms of microbial recognition in interactions between the host and symbiont. We posit that regulation of this association involves a molecular “dialogue” between the partners that includes interactions between the host’s innate immune system and the symbiont