An update: improvements in imaging perfluorocarbon-mounted plant leaves with implications for studies of plant pathology, physiology, development and cell biology.

Plant leaves are optically complex, which makes them difficult to image by light microscopy. Careful sample preparation is therefore required to enable researchers to maximize the information gained from advances in fluorescent protein labeling, cell dyes and innovations in microscope technologies and techniques. We have previously shown that mounting leaves in the non-toxic, non-fluorescent perfluorocarbon (PFC), perfluorodecalin (PFD) enhances the optical properties of the leaf with minimal impact on physiology. Here, we assess the use of the PFCs, PFD, and perfluoroperhydrophenanthrene (PP11) for in vivo plant leaf imaging using four advanced modes of microscopy: laser scanning confocal microscopy (LSCM), two-photon fluorescence microscopy, second harmonic generation microscopy, and stimulated Raman scattering (SRS) microscopy. For every mode of imaging tested, we observed an improved signal when leaves were mounted in PFD or in PP11, compared to mounting the samples in water. Using an image analysis technique based on autocorrelation to quantitatively assess LSCM image deterioration with depth, we show that PP11 outperformed PFD as a mounting medium by enabling the acquisition of clearer images deeper into the tissue. In addition, we show that SRS microscopy can be used to image PFCs directly in the mesophyll and thereby easily delimit the "negative space" within a leaf, which may have important implications for studies of leaf development. Direct comparison of on and off resonance SRS micrographs show that PFCs do not to form intracellular aggregates in live plants. We conclude that the application of PFCs as mounting media substantially increases advanced microscopy image quality of living mesophyll and leaf vascular bundle cells

Deep generative modeling for single-cell transcriptomics.

Single-cell transcriptome measurements can reveal unexplored biological diversity, but they suffer from technical noise and bias that must be modeled to account for the resulting uncertainty in downstream analyses. Here we introduce single-cell variational inference (scVI), a ready-to-use scalable framework for the probabilistic representation and analysis of gene expression in single cells ( https://github.com/YosefLab/scVI ). scVI uses stochastic optimization and deep neural networks to aggregate information across similar cells and genes and to approximate the distributions that underlie observed expression values, while accounting for batch effects and limited sensitivity. We used scVI for a range of fundamental analysis tasks including batch correction, visualization, clustering, and differential expression, and achieved high accuracy for each task

Rare B Decays with a HyperCP Particle of Spin One

In light of recent experimental information from the CLEO, BaBar, KTeV, and Belle collaborations, we investigate some consequences of the possibility that a light spin-one particle is responsible for the three Sigma^+ -> p mu^+ mu^- events observed by the HyperCP experiment. In particular, allowing the new particle to have both vector and axial-vector couplings to ordinary fermions, we systematically study its contributions to various processes involving b-flavored mesons, including B-Bbar mixing as well as leptonic, inclusive, and exclusive B decays. Using the latest experimental data, we extract bounds on its couplings and subsequently estimate upper limits for the branching ratios of a number of B decays with the new particle. This can serve to guide experimental searches for the particle in order to help confirm or refute its existence.Comment: 17 pages, 3 figures; discussion on spin-0 case modified, few errors corrected, main conclusions unchange

A Geographically-Restricted but Prevalent Mycobacterium tuberculosis Strain Identified in the West Midlands Region of the UK between 1995 and 2008

Background: We describe the identification of, and risk factors for, the single most prevalent Mycobacterium tuberculosis strain in the West Midlands region of the UK.Methodology/Principal Findings: Prospective 15-locus MIRU-VNTR genotyping of all M. tuberculosis isolates in the West Midlands between 2004 and 2008 was undertaken. Two retrospective epidemiological investigations were also undertaken using univariable and multivariable logistic regression analysis. The first study of all TB patients in the West Midlands between 2004 and 2008 identified a single prevalent strain in each of the study years (total 155/3,056 (5%) isolates). This prevalent MIRU-VNTR profile (32333 2432515314 434443183) remained clustered after typing with an additional 9-loci MIRU-VNTR and spoligotyping. The majority of these patients (122/155, 79%) resided in three major cities located within a 40 km radius. From the apparent geographical restriction, we have named this the "Mercian" strain. A multivariate analysis of all TB patients in the West Midlands identified that infection with a Mercian strain was significantly associated with being UK-born (OR = 9.03, 95% CI = 4.56-17.87, p 65 years old (OR = 0.25, 95% CI = 0.09-0.67, p < 0.01). A second more detailed investigation analyzed a cohort of 82 patients resident in Wolverhampton between 2003 and 2006. A significant association with being born in the UK remained after a multivariate analysis (OR = 9.68, 95% CI = 2.00-46.78, p < 0.01) and excess alcohol intake and cannabis use (OR = 6.26, 95% CI = 1.45-27.02, p = .01) were observed as social risk factors for infection.Conclusions/Significance: The continued consistent presence of the Mercian strain suggests ongoing community transmission. Whilst significant associations have been found, there may be other common risk factors yet to be identified. Future investigations should focus on targeting the relevant risk groups and elucidating the biological factors that mediate continued transmission of this strain

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Evaluation of Intervention Impact on Health Inequality for Resource Allocation

Introduction. We describe a simplified distributional cost-effectiveness analysis based on aggregate data to estimate the health inequality impact of public health interventions. Methods. We extracted data on costs, health outcomes expressed as quality-adjusted life years (QALYs), and target populations for interventions within National Institute for Health and Care Excellence (NICE) public health guidance published up to October 2016. Evidence on variation by age, gender, and index of multiple deprivation informed socioeconomic distributions of incremental QALYs, health opportunity costs, and the baseline distribution of health. Total population QALYs, summary measures of inequality, and a health equity impact plane show results by intervention and by guideline. A value for inequality aversion from a general population survey in England let us combine impacts on health inequality and total health into a single measure of intervention value. Results. Our estimates suggest that of 134 interventions considered by NICE, 70 (52%) reduce inequality and increase health, 21 (16%) involve a tradeoff between improving health and improving health inequality, and 43 (32%) reduce health and increase health inequality. Fully implemented, the potential impact of all recommendations was 23,336,181 additional QALYs for the population of England and Wales and a reduction of the gap in quality-adjusted life expectancy between the healthiest and least healthy from 13.78 to 13.34 QALYs. The combined value of the additional health and reduction in inequality was 28,723,776 QALYs. Discussion. Our analysis takes account of the fact that existing public health spending likely benefits the most disadvantaged. This simple method applied separately to economic evaluation produces evidence of intervention impacts on the distribution of health that is vital in determining value for money when health inequality reduction is a policy goal

HHEX is a transcriptional regulator of the VEGFC/FLT4/PROX1 signaling axis during vascular development.

Formation of the lymphatic system requires the coordinated expression of several key regulators: vascular endothelial growth factor C (VEGFC), its receptor FLT4, and a key transcriptional effector, PROX1. Yet, how expression of these signaling components is regulated remains poorly understood. Here, using a combination of genetic and molecular approaches, we identify the transcription factor hematopoietically expressed homeobox (HHEX) as an upstream regulator of VEGFC, FLT4, and PROX1 during angiogenic sprouting and lymphatic formation in vertebrates. By analyzing zebrafish mutants, we found that hhex is necessary for sprouting angiogenesis from the posterior cardinal vein, a process required for lymphangiogenesis. Furthermore, studies of mammalian HHEX using tissue-specific genetic deletions in mouse and knockdowns in cultured human endothelial cells reveal its highly conserved function during vascular and lymphatic development. Our findings that HHEX is essential for the regulation of the VEGFC/FLT4/PROX1 axis provide insights into the molecular regulation of lymphangiogenesis

Sequential induction of three recombination directionality factors directs assembly of tripartite integrative and conjugative elements

Tripartite integrative and conjugative elements (ICE3) are a novel form of ICE that exist as three separate DNA regions integrated within the genomes of Mesorhizobium spp. Prior to conjugative transfer the three ICE3 regions of M. ciceri WSM1271 ICEMcSym1271 combine and excise to form a single circular element. This assembly requires three coordinated recombination events involving three site-specific recombinases IntS, IntG and IntM. Here, we demonstrate that three excisionases–or recombination directionality factors—RdfS, RdfG and RdfM are required for ICE3 excision. Transcriptome sequencing revealed that expression of ICE3 transfer and conjugation genes was induced by quorum sensing. Quorum sensing activated expression of rdfS, and in turn RdfS stimulated transcription of both rdfG and rdfM. Therefore, RdfS acts as a “master controller” of ICE3 assembly and excision. The dependence of all three excisive reactions on RdfS ensures that ICE3 excision occurs via a stepwise sequence of recombination events that avoids splitting the chromosome into a non-viable configuration. These discoveries expose a surprisingly simple control system guiding molecular assembly of these novel and complex mobile genetic elements and highlight the diverse and critical functions of excisionase proteins in control of horizontal gene transfer