PAR-dependent and geometry-dependent mechanisms of spindle positioning.

During intrinsically asymmetric division, the spindle is oriented onto a polarized axis specified by a group of conserved PAR proteins. Extrinsic geometric asymmetry generated by cell shape also affects spindle orientation in some systems, but how intrinsic and extrinsic mechanisms coexist without interfering with each other is unknown. In some asymmetrically dividing cells of the wild-type Caenorhabditis elegans embryo, nuclear rotation directed toward the anterior cortex orients the forming spindle. We find that in such cells, a PAR-dependent mechanism dominates and causes rotation onto the polarized axis, regardless of cell shape. However, when geometric asymmetry is removed, free nuclear rotation in the center of the cell is observed, indicating that the anterior-directed nature of rotation in unaltered embryos is an effect of cell shape. This free rotation is inconsistent with the prevailing model for nuclear rotation, the specialized cortical site model. In contrast, in par-3 mutant embryos, a geometry-dependent mechanism becomes active and causes directed nuclear rotation. These results lead to the model that in wild-type embryos both PAR-3 and PAR-2 are essential for nuclear rotation in asymmetrically dividing cells, but that PAR-3 inhibits geometry-dependent rotation in nonpolarized cells, thus preventing cell shape from interfering with spindle orientation

Third-Party Data Providers Ruin Simple Mechanisms

Motivated by the growing prominence of third-party data providers in online marketplaces, this paper studies the impact of the presence of third-party data providers on mechanism design. When no data provider is present, it has been shown that simple mechanisms are "good enough" -- they can achieve a constant fraction of the revenue of optimal mechanisms. The results in this paper demonstrate that this is no longer true in the presence of a third-party data provider who can provide the bidder with a signal that is correlated with the item type. Specifically, even with a single seller, a single bidder, and a single item of uncertain type for sale, the strategies of pricing each item-type separately (the analog of item pricing for multi-item auctions) and bundling all item-types under a single price (the analog of grand bundling) can both simultaneously be a logarithmic factor worse than the optimal revenue. Further, in the presence of a data provider, item-type partitioning mechanisms---a more general class of mechanisms which divide item-types into disjoint groups and offer prices for each group---still cannot achieve within a $\log \log$ factor of the optimal revenue. Thus, our results highlight that the presence of a data-provider forces the use of more complicated mechanisms in order to achieve a constant fraction of the optimal revenue

A systematic analysis of Epstein-Barr virus genes and their individual contribution to virus production and composition reveals critical downstream functions

A vaccine to prevent infectious diseases associated with Epstein-Barr virus (EBV) has been put forward decades ago but has not made it to the clinic yet. EBV is a very complex herpes virus and its complexity, uncertainties about viral antigenic targets and technical difficulties to establish and mass-produce viral mutants are major obstacles. To mimic the complexity of the virus which encompasses more than 80 proteins, virus-like particles (VLPs) have a high potential as a vaccine prototype. To explore conditions to optimize and improve virus production, I established and tested an EBV gene library with 78 expression plasmids and a set of designed shRNAs investigating the functions of individual viral genes in the context of virus synthesis. Engineered virus stocks were then systematically characterized with respect to virus titers, bioparticle and physical particle concentration and virus uptake by primary human B cells, EBV’s target cells in vivo. To quantitate virus uptake by these cells, I developed a novel ß-lactamase-based assay that can monitor fusion events of the viral envelope with membranes of recipient cells at the level of single cells by flow cytometry. Together, my results identified several EBV genes such as BALF4, BVLF1 and BKRF4, encoding a viral glycoprotein, a regulator of transcription of late viral genes, and a possible tegument protein, respectively, that improve virus production regarding virus yield, virus composition and quality and virus uptake. My experi¬ments also indicated that EBV does not encode a master gene that governs EBV synthesis dampening virus production, contrary to my initial working hypothesis. Conditional expression of viral genes that improve EBV production as identified in my work will likely enhance and improve yield, assembly and important functional parameters of VLPs (such as their efficient uptake by antigen presenting immune cells, for example) supporting the development of a much improved EB-VLP based vaccine candidate to be used for clinical development and testing

RNA-aptamers-in-droplets (RAPID) high-throughput screening for secretory phenotypes.

Synthetic biology and metabolic engineering seek to re-engineer microbes into living foundries for the production of high value chemicals. Through a design-build-test cycle paradigm, massive libraries of genetically engineered microbes can be constructed and tested for metabolite overproduction and secretion. However, library generation capacity outpaces the rate of high-throughput testing and screening. Well plate assays are flexible but with limited throughput, whereas droplet microfluidic techniques are ultrahigh-throughput but require a custom assay for each target. Here we present RNA-aptamers-in-droplets (RAPID), a method that greatly expands the generality of ultrahigh-throughput microfluidic screening. Using aptamers, we transduce extracellular product titer into fluorescence, allowing ultrahigh-throughput screening of millions of variants. We demonstrate the RAPID approach by enhancing production of tyrosine and secretion of a recombinant protein in Saccharomyces cerevisiae by up to 28- and 3-fold, respectively. Aptamers-in-droplets affords a general approach for evolving microbes to synthesize and secrete value-added chemicals.Screening libraries of genetically engineered microbes for secreted products is limited by the available assay throughput. Here the authors combine aptamer-based fluorescent detection with droplet microfluidics to achieve high throughput screening of yeast strains engineered for enhanced tyrosine or streptavidin production

Validating Candidate Congenital Heart Disease Genes in Drosophila.

Genomic sequencing efforts can implicate large numbers of genes and de novo mutations as potential disease risk factors. A high throughput in vivo model system to validate candidate gene association with pathology is therefore useful. We present such a system employing Drosophila to validate candidate congenital heart disease (CHD) genes. The protocols exploit comprehensive libraries of UAS-GeneX-RNAi fly strains that when crossed into a 4×Hand-Gal4 genetic background afford highly efficient cardiac-specific knockdown of endogenous fly orthologs of human genes. A panel of quantitative assays evaluates phenotypic severity across multiple cardiac parameters. These include developmental lethality, larva and adult heart morphology, and adult longevity. These protocols were recently used to evaluate more than 100 candidate CHD genes implicated by patient whole-exome sequencing (Zhu et al., 2017)

Miami-Dade County Urban Tree Canopy Assessment

This assessment focuses on the environmental and socioeconomic impacts from the urban tree canopy (UTC) within the Urban Development Boundary of Miami-Dade County, as defined by the Miami-Dade County MPO (Figure 1). The area (intracoastal water areas excluded) encompasses approximately 1150 km 2 (444 mi 2). A combination of remote sensing and publicly available vector data was used to classify the following land cover classes: tree canopy/shrubs, grass, bare ground, wetland, water, building, street/railroad, other impervious surfaces, and cropland

A Kiloparsec-Scale Binary Active Galactic Nucleus Confirmed by the Expanded Very Large Array

We report the confirmation of a kpc-scale binary active galactic nucleus (AGN) with high-resolution radio images from the Expanded Very Large Array (EVLA). SDSS J150243.1+111557 is a double-peaked [O III] AGN at z = 0.39 selected from the Sloan Digital Sky Survey. Our previous near-infrared adaptive optics imaging reveals two nuclei separated by 1.4" (7.4 kpc), and our optical integral-field spectroscopy suggests that they are a type-1--type-2 AGN pair. However, these data alone cannot rule out the single AGN scenario where the narrow emission-line region associated with the secondary is photoionized by the broad-line AGN in the primary. Our new EVLA images at 1.4, 5.0, and 8.5 GHz show two steep-spectrum compact radio sources spatially coincident with the optical nuclei. The radio power of the type-2 AGN is an order-of-magnitude in excess of star-forming galaxies with similar extinction-corrected [O II] 3727 luminosities, indicating that the radio emission is powered by accretion. Therefore, SDSS J150243.1+111557 is one of the few confirmed kpc-scale binary AGN systems. Spectral-energy-distribution modeling shows that SDSS J150243.1+111557 is a merger of two ~10^{11} M_sun galaxies. With both black hole masses around 10^8 Msun, the AGNs are accreting at ~10 times below the Eddington limit.Comment: ApJL accepted. 6 pages, 3 figures, 1 tabl

1Cademy @ Causal News Corpus 2022: Leveraging Self-Training in Causality Classification of Socio-Political Event Data

This paper details our participation in the Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE) workshop @ EMNLP 2022, where we take part in Subtask 1 of Shared Task 3. We approach the given task of event causality detection by proposing a self-training pipeline that follows a teacher-student classifier method. More specifically, we initially train a teacher model on the true, original task data, and use that teacher model to self-label data to be used in the training of a separate student model for the final task prediction. We test how restricting the number of positive or negative self-labeled examples in the self-training process affects classification performance. Our final results show that using self-training produces a comprehensive performance improvement across all models and self-labeled training sets tested within the task of event causality sequence classification. On top of that, we find that self-training performance did not diminish even when restricting either positive/negative examples used in training. Our code is be publicly available at https://github.com/Gzhang-umich/1CademyTeamOfCASE.Comment: Paper from CASE workshop at EMNLP 202

Miami- Dade Urban Tree Canopy Analysis

Two of the Florida state universities, University of Florida (UF) and Florida International University (FIU), collaborated in assessing urban tree cover (UTC) for part of northwestern Miami-Dade County, covering an area of approximately 380 km2 (147 mi2). The analysis estimated the area with current tree canopy (existing UTC), the area of potential tree canopy (possible UTC), and various other land cover categories. The assessment used two methods to establish those estimates. The first method utilized the i-Tree canopy assessment tool provided by the USDA Forest Service. The second method used a combination of multispectral satellite data and airborne Light Detection and Ranging (LiDAR) datasets for detection and classification of land cover. Classification results were further analyzed in a Geographic Information System (GIS) to relate land cover distribution patterns (obtained from the second land cover classification method) to surface temperatures, land use patterns, and socioeconomic factors