The role of surface roughness, albedo, and Bowen ratio on ecosystem energy balance in the Eastern United States

Land cover and land use influence surface climate through differences in biophysical surface properties, including partitioning of sensible and latent heat (e.g., Bowen ratio), surface roughness, and albedo. Clusters of closely spaced eddy covariance towers (e.g., \u3c10 \u3ekm) over a variety of land cover and land use types provide a unique opportunity to study the local effects of land cover and land use on surface temperature. We assess contributions albedo, energy redistribution due to differences in surface roughness and energy redistribution due to differences in the Bowen ratio using two eddy covariance tower clusters and the coupled (land-atmosphere) Variable-Resolution Community Earth System Model. Results suggest that surface roughness is the dominant biophysical factor contributing to differences in surface temperature between forested and deforested lands. Surface temperature of open land is cooler (−4.8 °C to −0.05 °C) than forest at night and warmer (+0.16 °C to +8.2 °C) during the day at northern and southern tower clusters throughout the year, consistent with modeled calculations. At annual timescales, the biophysical contributions of albedo and Bowen ratio have a negligible impact on surface temperature, however the higher albedo of snow-covered open land compared to forest leads to cooler winter surface temperatures over open lands (−0.4 °C to −0.8 °C). In both the models and observation, the difference in mid-day surface temperature calculated from the sum of the individual biophysical factors is greater than the difference in surface temperature calculated from radiative temperature and potential temperature. Differences in measured and modeled air temperature at the blending height, assumptions about independence of biophysical factors, and model biases in surface energy fluxes may contribute to daytime biases

Ypt1/Rab1 regulates Hrr25/CK1δ kinase activity in ER-Golgi traffic and macroautophagy.

ER-derived COPII-coated vesicles are conventionally targeted to the Golgi. However, during cell stress these vesicles also become a membrane source for autophagosomes, distinct organelles that target cellular components for degradation. How the itinerary of COPII vesicles is coordinated on these pathways remains unknown. Phosphorylation of the COPII coat by casein kinase 1 (CK1), Hrr25, contributes to the directional delivery of ER-derived vesicles to the Golgi. CK1 family members are thought to be constitutively active kinases that are regulated through their subcellular localization. Instead, we show here that the Rab GTPase Ypt1/Rab1 binds and activates Hrr25/CK1δ to spatially regulate its kinase activity. Consistent with a role for COPII vesicles and Hrr25 in membrane traffic and autophagosome biogenesis, hrr25 mutants were defective in ER–Golgi traffic and macroautophagy. These studies are likely to serve as a paradigm for how CK1 kinases act in membrane traffic

Transmisión de Klebsiella pneumoniae resistente a carbapenemes en hospitales de EE.UU.

Antecedentes. La Klebsiella pneumoniae resistente a los carbapenemes (CRKp) es el Enterobacterales resistente a los carbapenemes más prevalente en los Estados Unidos. Se evaluó la agrupación de CRKp en pacientes de hospitales estadounidenses. Métodos. De abril de 2016 a agosto de 2017, 350 pacientes con grupo clonal 258 CRKp se inscribieron en el Consortium on Resistance Against Carbapenems in Klebsiella and other Enterobacteriaceae, un estudio de cohortes prospectivo y multicéntrico. Se construyó un árbol de máxima verosimilitud utilizando RAxML. Los conglomerados estáticos compartían ≤21 polimorfismos de un solo nucleótido (SNP) y un ancestro común más reciente. Los conglomerados dinámicos incorporaron la distancia SNP, el tiempo de cultivo y las tasas de acumulación y transmisión SNP utilizando el programa R TransCluster. Resultados. La mayoría de los pacientes ingresaron desde su domicilio (n=150, 43%) o desde centros de cuidados de larga duración (n=115, 33%). La orina (n=149, 43%) fue el lugar de aislamiento más común. En total, se identificaron 55 conglomerados estáticos y 47 dinámicos en 210 de 350 (60%) y 194 de 350 (55%) pacientes, respectivamente. Aproximadamente la mitad de los clusters estáticos eran idénticos a los dinámicos. Los conglomerados estáticos consistían en 33 (60%) conglomerados intrasistema y 22 (40%) conglomerados intersistema. Los conglomerados dinámicos estaban formados por 32 (68%) conglomerados intrasistema y 15 (32%) conglomerados intersistema y presentaban menos diferencias de SNP que los conglomerados estáticos (8 frente a 9; P=.045; intervalo de confianza [IC] del 95%: -4 a 0). Los conglomerados dinámicos intersistema contenían más pacientes que los conglomerados dinámicos intrasistema (mediana [intervalo intercuartílico], 4 [2, 7] frente a 2 [2, 2]; P=,007; IC del 95%: -3 a 0). Conclusiones. Se identificó una amplia transmisión intrasistémica e intersistémica de CRKp en pacientes estadounidenses hospitalizados. El uso de diferentes métodos para evaluar la similitud genética sólo dio lugar a diferencias menores en la interpretación.Background. Carbapenem-resistant Klebsiella pneumoniae (CRKp) is the most prevalent carbapenem-resistant Enterobacterales in the United States. We evaluated CRKp clustering in patients in US hospitals. Methods. From April 2016 to August 2017, 350 patients with clonal group 258 CRKp were enrolled in the Consortium on Resistance Against Carbapenems in Klebsiella and other Enterobacteriaceae, a prospective, multicenter, cohort study. A maximum likelihood tree was constructed using RAxML. Static clusters shared ≤21 single-nucleotide polymorphisms (SNP) and a most recent common ancestor. Dynamic clusters incorporated SNP distance, culture timing, and rates of SNP accumulation and transmission using the R program TransCluster. Results. Most patients were admitted from home (n=150, 43%) or long-term care facilities (n=115, 33%). Urine (n=149, 43%) was the most common isolation site. Overall, 55 static and 47 dynamics clusters were identified involving 210 of 350 (60%) and 194 of 350 (55%) patients, respectively. Approximately half of static clusters were identical to dynamic clusters. Static clusters consisted of 33 (60%) intrasystem and 22 (40%) intersystem clusters. Dynamic clusters consisted of 32 (68%) intrasystem and 15 (32%) intersystem clusters and had fewer SNP differences than static clusters (8 vs 9; P=.045; 95% confidence interval [CI]: −4 to 0). Dynamic intersystem clusters contained more patients than dynamic intrasystem clusters (median [interquartile range], 4 [2, 7] vs 2 [2, 2]; P=.007; 95% CI: −3 to 0). Conclusions. Widespread intrasystem and intersystem transmission of CRKp was identified in hospitalized US patients. Use of different methods for assessing genetic similarity resulted in only minor differences in interpretation

A protein interaction map for cell polarity development

Many genes required for cell polarity development in budding yeast have been identified and arranged into a functional hierarchy. Core elements of the hierarchy are widely conserved, underlying cell polarity development in diverse eukaryotes. To enumerate more fully the protein–protein interactions that mediate cell polarity development, and to uncover novel mechanisms that coordinate the numerous events involved, we carried out a large-scale two-hybrid experiment. 68 Gal4 DNA binding domain fusions of yeast proteins associated with the actin cytoskeleton, septins, the secretory apparatus, and Rho-type GTPases were used to screen an array of yeast transformants that express ∼90% of the predicted Saccharomyces cerevisiae open reading frames as Gal4 activation domain fusions. 191 protein–protein interactions were detected, of which 128 had not been described previously. 44 interactions implicated 20 previously uncharacterized proteins in cell polarity development. Further insights into possible roles of 13 of these proteins were revealed by their multiple two-hybrid interactions and by subcellular localization. Included in the interaction network were associations of Cdc42 and Rho1 pathways with proteins involved in exocytosis, septin organization, actin assembly, microtubule organization, autophagy, cytokinesis, and cell wall synthesis. Other interactions suggested direct connections between Rho1- and Cdc42-regulated pathways; the secretory apparatus and regulators of polarity establishment; actin assembly and the morphogenesis checkpoint; and the exocytic and endocytic machinery. In total, a network of interactions that provide an integrated response of signaling proteins, the cytoskeleton, and organelles to the spatial cues that direct polarity development was revealed

Charting the effects of TMS with fMRI : Modulation of cortical recruitment within the distributed network supporting semantic control

Semantic memory comprises our knowledge of the meanings of words and objects but only some of this knowledge is relevant at any given time. Thus, semantic control processes are needed to focus retrieval on relevant information. Research on the neural basis of semantic control has strongly implicated left inferior frontal gyrus (LIFG) but recent work suggests that a wider network supports semantic control, including left posterior middle temporal gyrus (pMTG), right inferior frontal gyrus (RIFG) and pre-supplementary motor area (pre-SMA). In the current study, we used repetitive transcranial magnetic stimulation (1 Hz offline TMS) over LIFG, immediately followed by fMRI, to examine modulation of the semantic network. We compared the effect of stimulation on judgements about strongly-associated words (dog-bone) and weaker associations (dog-beach), since previous studies have found that dominant links can be recovered largely automatically with little engagement of LIFG, while more distant connections require greater control. Even though behavioural performance was maintained in response to TMS, LIFG stimulation increased the effect of semantic control demands in pMTG and pre-SMA, relative to stimulation of a control site (occipital pole). These changes were accompanied by reduced recruitment of both the stimulated region (LIFG) and its right hemisphere homologue (RIFG), particularly for strong associations with low control requirements. Thus repetitive TMS to LIFG modulated the contribution of distributed regions to semantic judgements in two distinct ways

Detecting forest response to droughts with global observations of vegetation water content

Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil-plant-atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem-scale analog of the pressure-volume curve, the non-linear relationship between average leaf or branch water potential and water content commonly used in plant hydraulics. The sources of variability in these ecosystem-scale pressure-volume curves and their relationship to forest response to water stress are discussed. We further show to what extent diel, seasonal, and decadal dynamics of VWC reflect variations in different processes relating the tree response to water stress. VWC can also be used for inferring belowground conditions-which are difficult to impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne observational system for VWC, when combined with existing datasets, can capture diel and seasonal water dynamics to advance the science and applications of global forest vulnerability to future droughts

The trans-Golgi SNARE syntaxin 6 is recruited to the chlamydial inclusion membrane

Chlamydia trachomatis is an obligate intracellular pathogen that replicates within a parasitophorous vacuole termed an inclusion. The chlamydial inclusion is isolated from the endocytic pathway but fusogenic with Golgi-derived exocytic vesicles containing sphingomyelin and cholesterol. Sphingolipids are incorporated into the chlamydial cell wall and are considered essential for chlamydial development and viability. The mechanisms by which chlamydiae obtain eukaryotic lipids are poorly understood but require chlamydial protein synthesis and presumably modification of the inclusion membrane to initiate this interaction. A polarized cell model of chlamydial infection has demonstrated that chlamydiae preferentially intercept basolaterally directed, sphingomyelin-containing exocytic vesicles. Here we examine the localization and potential function of trans-Golgi and/or basolaterally associated soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins in chlamydia-infected cells. The trans-Golgi SNARE protein syntaxin 6 is recruited to the chlamydial inclusion in a manner that requires chlamydial protein synthesis and is conserved among all chlamydial species examined. The localization of syntaxin 6 to the chlamydial inclusion requires a tyrosine motif or plasma membrane retrieval signal (YGRL). Thus in addition to expression of at least two inclusion membrane proteins that contain SNARE-like motifs, chlamydiae also actively recruit eukaryotic SNARE-family proteins

Factors perceived to influence risky sexual behaviours among university students in the United Kingdom: a qualitative telephone interview study

Background In the United Kingdom people under the age of 25 years are at increased risk of contracting sexually transmitted infections. Most university students belong to this age group but little is known about their sexual behaviours. The aim of the study was to explore university students’ perspectives of factors and mechanisms that influence risky sexual behaviours among university students in the United Kingdom. Methods All students at a university in a northern city of England were invited via email to participate in qualitative telephone interviews. Interviews were audio recorded and transcribed verbatim. Framework analytical approach was used. Results Twenty interviews were conducted with a diverse sample of students. The social context of university lifestyle was perceived to affect risky sex through high levels of alcohol consumption, increased sexual opportunities, liberation from moral surveillance and expectations of the stereotypical highly sexually active student. Individual and cultural differences were also perceived to account for some patterns of risky sex with older students, overseas students and religious students perceived to be less likely to engage in risky sex due to academic priorities and a tendency to be more likely to adhere to moral values. Risk denial was also a key factor that led students to engage in risky sex. Poor access to sexual health services including inconvenient opening times, lack of confidentiality and stigma were perceived to contribute to the limited use of sexually transmitted infections testing and contraceptive services. Conclusions Lifestyle, individual and structural factors seem to play an important role in influencing the risky sexual behaviours of university students. Therefore preventive interventions that focus on these factors could be very useful in this sub-population of young people. This study provides useful baseline information that helps us understand how and why some United Kingdom university students engage in risky sexual behaviours that puts them at risk of contracting sexually transmitted infections

Mapping the Environmental Fitness Landscape of a Synthetic Gene Circuit

Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness). For cell populations with bimodal gene expression, this difference is particularly pronounced, and may involve stochastic transitions between two cellular states that form distinct sub-populations. Currently it remains unclear how a cell population's growth rate and its subpopulation fractions emerge from the molecular-level kinetics of gene networks and the division rates of single cells. To address this question we developed and quantitatively characterized an inducible, bistable synthetic gene circuit controlling the expression of a bifunctional antibiotic resistance gene in Saccharomyces cerevisiae. Following fitness and fluorescence measurements in two distinct environments (inducer alone and antibiotic alone), we applied a computational approach to predict cell population fitness and subpopulation fractions in the combination of these environments based on stochastic cellular movement in gene expression space and fitness space. We found that knowing the fitness and nongenetic (cellular) memory associated with specific gene expression states were necessary for predicting the overall fitness of cell populations in combined environments. We validated these predictions experimentally and identified environmental conditions that defined a “sweet spot” of drug resistance. These findings may provide a roadmap for connecting the molecular-level kinetics of gene networks to cell population fitness in well-defined environments, and may have important implications for phenotypic variability of drug resistance in natural settings