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Flow cytometry (FCM) is currently the most widely-used method to establish nuclear DNA content in plants. Since simple, 1-3-parameter, flow cytometers, which are sufficient for most plant applications, are commercially available at a reasonable price, the number of laboratories equipped with these instruments, and consequently new FCM users, has greatly increased over the last decade. This paper meets an urgent need for comprehensive recommendations for best practices in FCM for different plant science applications. We discuss advantages and limitations of establishing plant ploidy, genome size, DNA base composition, cell cycle activity, and level of endoreduplication. Applications of such measurements in plant systematics, ecology, molecular biology research, reproduction biology, tissue cultures, plant breeding, and seed sciences are described. Advice is included on how to obtain accurate and reliable results, as well as how to manage troubleshooting that may occur during sample preparation, cytometric measurements, and data handling. Each section is followed by best practice recommendations; tips as to what specific information should be provided in FCM papers are also provided.

Instrumentation for flow cytometry and sorting is designed around the assumption that samples are single-cell suspensions. However, with few exceptions, higher plants comprise complex multicellular tissues and organs, in which the individual cells are held together by shared cell walls. Single-cell suspensions can be obtained through digestion of the cells walls and release of the so-called protoplasts (plants without their cell wall). Here we describe best practices for protoplast preparation, and for analysis through flow cytometry and cell sorting. Finally, the numerous downstream applications involving sorted protoplasts are discussed.

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land‐atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat (H), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia ‐‐ along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model (LSM) performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry‐season increases in evapotranspiration was associated with model over‐estimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20‐30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10 to 15% of incoming solar radiation, compared to 0.15‐0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry‐season evapotranspiration and associated cooling). These partially compensating model‐observation discrepancies (e.g. higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation (Rn), the key driver of water and energy fluxes (LE ~ 0.6Rn and H ~ 0.15Rn). Though these biases varied among sites and models. A better representation of energy‐related parameters associated with dynamic phenology (e.g. leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation‐atmosphere exchange and reduce uncertainty of regional and global biogeochemical models.

1. Lianas, a key component of tropical forests, can limit growth of trees, impacting both the structure and functioning of forests, and are expected to benefit from fragmentation and potentially from global climatic changes. While it is critical to understand the impacts of liana infestation on contemporary tropical forests across large geographical areas, to date most liana studies have been focussed on single or few sites. 2. We measured and quantified liana infestation of 16,066 trees with diameter ≥10 cm in 27 plots distributed across southern Amazonia, a region characterized by substantial ecological and environmental variation and environmental change. We examined the influence of potential drivers of liana infestation at the plot, species and individual tree level. Additionally, we evaluated the effect of liana infestation on tree growth. 3. More than half of all trees had lianas in their crown. At the plot level, infestation by lianas was driven by forest structure but not by the studied climate or soil fertility variables, though low levels of liana infestation were found in seasonally flooded forests. 4. At the tree level, larger and stouter trees had a greater proportion of their crown infested with lianas. At the species level, trees belonging to intrinsically slow‐growing, dense‐wooded species were more susceptible to liana infestation. 5. Liana infestation had a negative impact on tree growth, with growth of heavily infested trees reduced by 33% compared to non‐infested. The impact of liana infestation on tree growth was strongest for the best‐lit tree crowns, indicating that lianas act to reduce the large competitive advantage that well‐lit trees otherwise hold over their neighbours. 6. Synthesis. Lianas are a pervasive and influential feature of the extensive forests at the southern edge of Amazonia. The degree of liana infestation in forests was closely linked to species‐level variables such as potential growth and wood density as well as the size of the individual tree. The growth of heavily infested trees was particularly restricted by lianas, and especially so for trees growing in otherwise favourable conditions, indicating the potential for lianas not only to reduce forest growth rates overall, but also to modify competitive hierarchies among trees within tropical forests.

1. Gold mining has rapidly increased across the Amazon Basin in recent years, especially in the Guiana shield, where it is responsible for >90% of total deforestation. However, the ability of forests to recover from gold mining activities remains largely unquantified. 2. Forest inventory plots were installed on recently abandoned mines in two major mining regions in Guyana, and re‐censused 18 months later, to provide the first ground‐based quantification of gold mining impacts on Amazon forest biomass recovery. 3. We found that woody biomass recovery rates on abandoned mining pits and tailing ponds are among the lowest ever recorded for tropical forests, with close to no woody biomass recovery after 3–4 years. 4. On the overburden sites (i.e. areas not mined but where excavated soil is deposited), however, above‐ground biomass recovery rates (0.4–5.4 Mg ha−1 year−1) were within the range of those recorded in other secondary forests across the Neotropics following abandonment of pastures and agricultural lands. 5. Our results suggest that forest recovery is more strongly limited by severe mining‐induced depletion of soil nutrients, especially nitrogen, than by mercury contamination, due to slowing of growth in nutrient‐stripped soils. 6. We estimate that the slow recovery rates in mining pits and ponds currently reduce carbon sequestration across Amazonian secondary forests by ~21,000 t C/year, compared to the carbon that would have accumulated following more traditional land uses such as agriculture or pasture. 7. Synthesis and applications. To achieve large‐scale restoration targets, Guyana and other Amazonian countries will be challenged to remediate previously mined lands. The recovery process is highly dependent on nitrogen availability rather than mercury contamination, affecting woody biomass regrowth. The significant recovery in overburden zones indicates that one potential active remediation strategy to promote biomass recovery may be to backfill mining pits and ponds with excavated soil.

The molecular mechanism regulating dormancy release in grapevine buds is as yet unclear. It was formerly proposed that dormancy is maintained by abscisic acid (ABA)-mediated repression of bud-meristem activity and that removal of this repression triggers dormancy release. It was also proposed that such removal of repression may be achieved via natural or artificial up-regulation of VvA8H-CYP707A4, which encodes ABA 8'-hydroxylase, and is the most highly expressed paralog in grapevine buds. The current study further examines these assumptions, and its experiments reveal that (a) hypoxia and ethylene, stimuli of bud dormancy release, enhance expression of VvA8H-CYP707A4 within grape buds, (b) the VvA8H-CYP707A4 protein accumulates during the natural transition to the dormancy release stage, and (c) transgenic vines overexpressing VvA8H-CYP707A4 exhibit increased ABA catabolism and significant enhancement of bud break in controlled and natural environments and longer basal summer laterals. The results suggest that VvA8H-CYP707A4 functions as an ABA degrading enzyme, and are consistent with a model in which the VvA8H-CYP707A4 level in the bud is up-regulated by natural and artificial bud break stimuli, which leads to increased ABA degradation capacity, removal of endogenous ABA-mediated repression, and enhanced regrowth. Interestingly, it also hints at sharing of regulatory steps between latent and lateral bud outgrowth.

Why do some forests produce biomass more efficiently than others? Variations in Carbon Use Efficiency (CUE: total Net Primary Production (NPP)/ Gross Primary Production (GPP)) may be due to changes in wood residence time (Biomass/NPPwood), temperature, or soil nutrient status. We tested these hypotheses in 14, one ha plots across Amazonian and Andean forests where we measured most key components of net primary production (NPP: wood, fine roots, and leaves) and autotrophic respiration (Ra; wood, rhizosphere, and leaf respiration). We found that lower fertility sites were less efficient at producing biomass and had higher rhizosphere respiration, indicating increased carbon allocation to belowground components. We then compared wood respiration to wood growth and rhizosphere respiration to fine root growth and found that forests with residence times 40 yrs. A comparison of rhizosphere respiration to fine root growth showed that rhizosphere growth respiration was significantly greater at low fertility sites. Overall, we found that Amazonian forests produce biomass less efficiently in stands with residence times >40 yrs and in stands with lower fertility, but changes to long-term mean annual temperatures do not impact CUE.

The organs of eukaryotic organisms comprise complex interspersions of cell types, whose different molecular activities, and corresponding cellular states, cooperate during development to produce the final, functional organ. Dysfunction of organs in disease, particularly oncogenesis, initiates with changes of state of a minor subset of cells. It therefore is hard to detect early molecular indicators of disease within an overwhelming background of normal cells. Flow cytometry and sorting provides a convenient way to purify minority subpopulations, if a specific fluorophore can be unambiguously and exclusively associated with this subpopulation. We have generated a number of transgenic mouse lines expressing a nuclear-localized version of the Green Fluorescent Protein (GFP), within which the production of a chimeric histone 2B-GFP protein occurs under the control of a constitutively-active, actin-derived promoter, separated by a Floxed-STOP sequence. In the presence of Cre recombinase, within F1 progeny of these mouse lines, excision of the STOP sequence activates transcription which results in the emergence of cells containing green fluorescent nuclei. We describe the characterization of these lines using a combination of microscopic imaging, flow cytometry and sorting, and Reverse-Transcription polymerase chain reaction of transcripts within single sorted nuclei isolated from tissue homogenates. These lines should be particularly useful for analysis of transcriptional changes in oncogenesis. © 2016 International Society for Advancement of Cytometry.

Diapause is the key adaptation allowing insects to survive unfavourable conditions and inhabit an array of environments. Physiological changes during diapause are largely conserved across species and are hypothesized to be regulated by a conserved suite of genes (a 'toolkit'). Furthermore, it is hypothesized that in social insects, this toolkit was co-opted to mediate caste differentiation between long-lived, reproductive, diapause-capable queens and short-lived, sterile workers. Using Bombus terrestris queens, we examined the physiological and transcriptomic changes associated with diapause and CO2 treatment, which causes queens to bypass diapause. We performed comparative analyses with genes previously identified to be associated with diapause in the Dipteran Sarcophaga crassipalpis and with caste differentiation in bumble bees. As in Diptera, diapause in bumble bees is associated with physiological and transcriptional changes related to nutrient storage, stress resistance and core metabolic pathways. There is a significant overlap, both at the level of transcript and gene ontology, between the genetic mechanisms mediating diapause in B. terrestris and S. crassipalpis, reaffirming the existence of a conserved insect diapause genetic toolkit. However, a substantial proportion (10%) of the differentially regulated transcripts in diapausing queens have no clear orthologs in other species, and key players regulating diapause in Diptera (juvenile hormone and vitellogenin) appear to have distinct functions in bumble bees. We also found a substantial overlap between genes related to caste determination and diapause in bumble bees. Thus, our studies demonstrate an intriguing interplay between pathways underpinning adaptation to environmental extremes and the evolution of sociality in insects.

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO2 levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias-corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land-use change scenarios. We assess the relative roles of climate change, CO2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land-use change and climate-driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO2 impacts varies considerably, depending on both the climate and land-use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors – climate change, CO2 fertilization effects, fire, and land use – to the fate of the Amazon over the coming century.

Understanding the relationship between photosynthesis, net primary productivity and growth in forest ecosystems is key to understanding how these ecosystems will respond to global anthropogenic change, yet the linkages among these components are rarely explored in detail. We provide the first comprehensive description of the productivity, respiration and carbon allocation of contrasting lowland Amazonian forests spanning gradients in seasonal water deficit and soil fertility. Using the largest data set assembled to date, ten sites in three countries all studied with a standardized methodology, we find that (i) gross primary productivity (GPP) has a simple relationship with seasonal water deficit, but that (ii) site-to-site variations in GPP have little power in explaining site-to-site spatial variations in net primary productivity (NPP) or growth because of concomitant changes in carbon use efficiency (CUE), and conversely, the woody growth rate of a tropical forest is a very poor proxy for its productivity. Moreover, (iii) spatial patterns of biomass are much more driven by patterns of residence times (i.e. tree mortality rates) than by spatial variation in productivity or tree growth. Current theory and models of tropical forest carbon cycling under projected scenarios of global atmospheric change can benefit from advancing beyond a focus on GPP. By improving our understanding of poorly understood processes such as CUE, NPP allocation and biomass turnover times, we can provide more complete and mechanistic approaches to linking climate and tropical forest carbon cycling.

It has been estimated that there are, globally, as many as 400,000 species of the angiosperms (the flowering plants). Of these, a minimal proportion has been characterized at the cytological level. Urgency is required in initiating a systematic and comprehensive census, due to species extinction as a consequence of anthropogenic activities. Fundamental to eukaryotes is the 2C-value, the amount of DNA contained within the nucleus of the unreduced gametes. Flow cytometry provides an ideal method for determining C-values, but the values archived in the Kew Plant C-value Database represent

A better understanding of the mechanisms controlling the magnitude and sign of carbon components in tropical forest ecosystems is important for reliable estimation of this important regional component of the global carbon cycle. We used the JULES vegetation model to simulate all components of the carbon balance at six sites along an Andes-Amazon transect across Peru and Brazil and compared the results to published field measurements. In the upper montane zone the model predicted a lack of forest vegetation, indicating a need for better parameterization of the responses of cloud forest vegetation within the model. In the lower montane and lowland zones simulated ecosystem productivity and respiration were predicted with reasonable accuracy, although not always within the error bounds of the observations. Model-predicted carbon use efficiency in this transect surprisingly did not increase with elevation, but remained close to the 'temperate' value 0.5. Upper montane forests were predicted to allocate ~50% of carbon fixation to biomass maintenance and growth, despite available measurements showing that they only allocate ~33%. This may be explained by elevational changes in the balance between growth and maintenance respiration within the forest canopy, as controlled by both temperature- and pressure-mediated processes, which is not yet well represented in current vegetation models. © 2012 Blackwell Publishing Ltd.

Summary The physiological role of a vacuolar ATPase subunit c1 (SaVHAc1) from a halophyte grass Spartina alterniflora was studied through its expression in rice. The SaVHAc1-expressing plants showed enhanced tolerance to salt stress than the wild-type plants, mainly through adjustments in early stage and preparatory physiological responses. In addition to the increased accumulation of its own transcript, SaVHAc1 expression led to increased accumulation of messages of other native genes in rice, especially those involved in cation transport and ABA signalling. The SaVHAc1-expressing plants maintained higher relative water content under salt stress through early stage closure of the leaf stoma and reduced stomata density. The increased K+/Na+ ratio and other cations established an ion homoeostasis in SaVHAc1-expressing plants to protect the cytosol from toxic Na+ and thereby maintained higher chlorophyll retention than the WT plants under salt stress. Besides, the role of SaVHAc1 in cell wall expansion and maintenance of net photosynthesis was implicated by comparatively higher root and leaf growth and yield of rice expressing SaVHAc1 over WT under salt stress. The study indicated that the genes contributing toward natural variation in grass halophytes could be effectively manipulated for improving salt tolerance of field crops within related taxa.

*The effects of drought on the Amazon rainforest are potentially large but remain poorly understood. Here, carbon (C) cycling after 5 yr of a large-scale through-fall exclusion (TFE) experiment excluding about 50% of incident rainfall from an eastern Amazon rainforest was compared with a nearby control plot. *Principal C stocks and fluxes were intensively measured in 2005. Additional minor components were either quantified in later site measurements or derived from the available literature. *Total ecosystem respiration (R(eco)) and total plant C expenditure (PCE, the sum of net primary productivity (NPP) and autotrophic respiration (R(auto))), were elevated on the TFE plot relative to the control. The increase in PCE and R(eco) was mainly caused by a rise in R(auto) from foliage and roots. Heterotrophic respiration did not differ substantially between plots. NPP was 2.4 +/- 1.4 t C ha(-1) yr(-1) lower on the TFE than the control. Ecosystem carbon use efficiency, the proportion of PCE invested in NPP, was lower in the TFE plot (0.24 +/- 0.04) than in the control (0.32 +/- 0.04). *Drought caused by the TFE treatment appeared to drive fundamental shifts in ecosystem C cycling with potentially important consequences for long-term forest C storage.

1. Plant–soil interactions play a central role in the biogeochemical carbon (C), nitrogen (N) and hydrological cycles. In the context of global environmental change, they are important both in modulating the impact of climate change and in regulating the feedback of greenhouse gas emissions (CO2, CH4 and N2O) to the climate system. 2. Dynamic global vegetation models (DGVMs) represent the most advanced tools available to predict the impacts of global change on terrestrial ecosystem functions and to examine their feedbacks to climate change. The accurate representation of plant–soil interactions in these models is crucial to improving predictions of the effects of climate change on a global scale. 3. In this paper, we describe the general structure of DGVMs that use plant functional types (PFTs) classifications as a means to integrate plant–soil interactions and illustrate how models have been developed to improve the simulation of: (a) soil carbon dynamics, (b) nitrogen cycling, (c) drought impacts and (d) vegetation dynamics. For each of these, we discuss some recent advances and identify knowledge gaps. 4. We identify three ongoing challenges, requiring collaboration between the global modelling community and process ecologists. First, the need for a critical evaluation of the representation of plant–soil processes in global models; second, the need to supply and integrate knowledge into global models; third, the testing of global model simulations against large-scale multifactor experiments and data from observatory gradients. 5. Synthesis. This paper reviews how plant–soil interactions are represented in DGVMs that use PFTs and illustrates some model developments. We also identify areas of ecological understanding and experimentation needed to reduce uncertainty in future carbon coupled climate change predictions.

The authors show that, interpreted broadly, the error-correction form is a member of a general class of transformations including those of R. A. Bewley (1979) and G. Bardsen (1989), which give numerically equivalent estimates of long-run multipliers. Whereas the advantage of the Bewley form is well known, the authors point out the advantage of the error-correction form in providing readily interpretable estimates of short-run responses to disequilibrium, without the necessity of prior estimates of cointegrating parameters. They then describe briefly methods of calculating approximate standard errors of the long-run multiplier for the autoregressive-distributed lag form and error-correction form, and show their equivalence. Copyright 1990 by Blackwell Publishing Ltd

Background: although writing is commonly characterized as a process of discovery, there are contrasting conceptions of what this implies about the writing process. Classical models of the cognitive processes in writing treat discovery as a side-effect of the processes required for effective communication, and associate it with the adaptation of thought to rhetorical goals. Aims: in this paper, I argue that these models overemphasize the role of explicit thinking processes in writing at the expense of more implicit text production processes. Arguments: following a review of research investigating the conditions under which writers discover new ideas through writing, which I argue contradicts important features of the classical account of discovery, I outline an alternative dual-process model of writing which I claim provides a better account of the empirical data. Conclusions: the model identifies two conflicting processes in writing: an explicit planning process, incorporating many of the features assumed by classical models of writing, and an implicit text production process, which operates according to connectionist processing principles. The basic features of these processes are described, and the complementary role they play in writing is discussed

The information content of statistical forecasts of approximately stationary quantities tends to decline as the forecast horizon increases, and there exists a maximum horizon beyond which forecasts cannot provide discernibly more information about the variable than is present in the unconditional mean (the content horizon). The pattern of decay of forecast content (or skill) with increasing horizon is well known for many types of meteorological forecasts; by contrast, little generally accepted information about these patterns or content horizons is available for economic variables. In this paper we estimate content horizons for a variety of macroeconomic quantities; more generally, we characterize the pattern of decay of forecast content as we project farther into the future. We find a wide variety of results for the different macroeconomic quantities, with models for some quantities providing useful content several years into the future, for other quantities providing negligible content beyond one or two months or quarters. JEL

The adsorption by graphite of a variety of organic solutes, mainly acid and basic dyes, from water, has been studied. Adsorption occurs rapidly and only at the outer surface of the graphite particles. The adsorptive forces are coulombic (ion exchange) and non-polar van der Waals' attraction. Basic dyes are adsorbed by ion exchange, the process being independent of temperature, but dependent on the surface charge on the graphite. Sulphonated dyes are adsorbed by van der Waals' (dispersion) forces; their affinity increases linearly with the area of the adsorbed molecule in contact with the substrate, but it falls with increase in the number of sulphonate groups, because of increase of water attraction. From solutions of low concentration most solutes are adsorbed as monolayers. In the early stages of adsorption they are probably oriented flat on the surface, but in the completed monolayer they are oriented with ionic groups as far away as possible from the graphite surface. From solutions of high concentration, multilayers of single molecules or monolayers of micelles appear to be adsorbed. Glucose and sucrose are adsorbed to a much greater extent than is accounted for by monolayer adsorption, but the reason for this is obscure. The shapes of the isotherms are shown to be related to the affinity of the solutes for the graphite surface. The rate-controlling factor in adsorption of dyes is believed to be the proportion of bombarding ions which have a favourable orientation relative to the graphite surface at the moment of impact.

Pharmacologically active ingredients in plants can cause significant morbidity through their increasingly common use in herbal alternative medicines and dietary supplements. Monitoring consumer products for the presence of toxic plants is encumbered by the lack of rapid and specific assays. To create a sensitive, reliable, fast, and broad-spectrum assay for medicinal or toxic plant species, we tested multiplexed ligation-dependent probe amplification (MLPA), which requires partial genomic DNA sequences from species of plants that are not well represented in currently available genetic databases. Genomic DNA was obtained from 21 species of medicinal and/or toxic plants. The PCR products were amplified from these plants and cloned for sequencing. The MLPA method was successful with DNA samples from many different species. The use of a microarray to facilitate screening of potentially thousands of plants in a single assay also was successful. The combination of the specificity of the MLPA assay with the broad-scale capabilities of microarray technology should make this an especially useful tool in screening in foods and commercial herbal preparations to identify the plant compounds actually present. Other applications could potentially extend to the identification of any plant species in samples for academic botanical studies and for biodefense and forensics applications.

Background Most current commercial flow cytometers employ analog circuitry to provide feature values describing the pulse waveforms produced from suspended cells and particles. This restricts the type of features that can be extracted (typically pulse height, width, and integral) and consequently places a limit on classification performance. In previous work, we described a first-generation digital data acquisition and processing system that was used to demonstrate the classification advantages provided by the extraction of additional waveform features. An improved version of the system is discussed in this paper, focusing on dual-buffering to ensure increased pulse capture. A mathematical model of the system is also presented for performance analysis. Methods The second-generation system incorporates fast digitization of analog pulse waveforms, instantaneous pulse detection hardware, and a novel dual-buffering scheme. A mathematical model of the system was developed to theoretically compute the capture-rate performance. Results The capture rate of the system was theoretically analyzed and empirically measured. Under typical conditions, a capture rate of 8,000 pulses/s was experimentally achieved. Conclusions Based on these results, the dual-buffer architecture shows great potential for use in flow cytometry. © 2005 Wiley-Liss, Inc.

The growth rates of real output and real investment are two macroeconomic time series which are particularly difficult to forecast. This paper considers the application of diffusion index forecasting models to this problem. We begin by characterizing the performance of standard forecasts, via recently-introduced measures of predictability and the forecast content, noting the maximum horizon at which the forecasts have value. We then compare diffusion index forecasts with a variety of alternatives, including the forecasts made by the OECD. We find gains in forecast accuracy at short horizons from the diffusion index models, but do not find evidence that the maximum horizon for forecasts can be extended in this way. Copyright © 2003 John Wiley & Sons, Ltd.

Changes in gene expression are associated with many important biological phenomena including morphogenesis and aging, cancer and disease states, and adaptive responses to the environment. To detect these changes, molecular biologists have, over the years, developed a variety of techniques including RNA blots (1), differential display (2), ribonuclease protection assays (3), and reverse transcription–polymerase chain reaction (RT-PCR) (4). Although these methods are effective, being sensitive and accurate, their dependence on gel electrophoresis places an empirical limit on the number of samples that can be simultaneously analyzed. High-density microarrays, first described by Schena et al. (5), provide the important advantage of allowing parallel quantification of the expression levels of an almost unlimited number of genes from a given genome. This greatly accelerates the characterization of individual genes and provides the means to decipher complex, multigenic patterns of gene expression (6). The importance of the high-throughput capability of microarrays is particularly relevant in the context of the recent explosion in genomic sequence acquisition. Each day, the human genome sequencing project alone deposits an estimated 2 million bases of DNA sequence into the GenBank database (7). For other eukaryotes, including Saccharomyces cerevisiae (8), Caenorhabditis elegans (9), and Drosophila melanogaster (10), the complete genomic sequence has already been reported. By the end of the year 2000, the list of organisms having fully sequenced genomes should comprise at least 36 different species (11), including the higher plant Arabidopsis thaliana. The rapid growth in accumulation of genomic sequences has been paralleled by the growth in collections of expressed sequence tags (ESTs), each of which contains the partial sequence of an expressed gene (12). For genomic or EST sequences to be truly informative, the genes that they identify must be assigned biological functions. Expression profiling using microarrays provides a powerful tool for correlating gene functions with DNA sequences. DNA microarrays also are useful for identifying differentially expressed genes in organisms for which the available DNA sequence data are limited. This advantage is not shared by other high-throughput methods of expression analysis such as serial analysis of gene expression (SAGE) (13). The use of microarrays for expression profiling is based on two fundamental principles. First, for many genes, a predominant factor underlying changes in expression is an alteration in the abundance of the cognate mRNA. It is clear that posttranscriptional factors also can affect gene expression, but these factors are not considered in this review because they are not generally amenable to microarray analysis. Second, only DNA strands possessing complementary sequences can hybridize to each other to form a stable, double-stranded molecule. Microarrays exploit this property through the immobilization of millions of single-strand copies of a gene as individual array elements on a solid support surface. The array surface is then incubated with a mixture of labeled DNA molecules; the surface contains a proportional representation of all of the genes that are being expressed in a given tissue sample. Out of this mixture, only the labeled molecules that represent the same gene as the immobilized DNA elements can form heteroduplexes. By measuring the amount of label that is bound to each array element at the end of the hybridization reaction, a researcher can determine the relative transcript abundance level of each gene. Because each microarray comprises many elements, RNA abundance levels for thousands of genes can be measured in a single experiment. By comparing abundance levels from several experiments, the investigator can correlate patterns of gene expression with particular tissues or experimental conditions.

Flow cytometry was used to compare 14 potential reference standards for plant DNA content determination. Both chicken and plant internal standards were used, as were propidium iodide (PI) and 4'-6-diamidino-2-phenylindole (DAPI) as fluorochromes. Means and standard errors of the means are presented for the 14 potential reference standards, and the means are compared to those obtained by Feulgen densitometry. Five species are recommended as an initial set of international standards for future plant DNA content determinations: Sorghum bicolor cv. Pioneer 8695 (2C = 1.74 pg), Pisum sativum cv. Minerva Maple (2C = 9.56 pg), Hordeum vulgare cv. Sultan (2C = 11.12 pg), Vicia faba (2C = 26.66 pg), and Allium cepa cv. Ailsa Craig (2C = 33.55 pg). It is recommended that the reference standard of choice be one with 2C and 4C nuclear DNA content peaks similar to, but not overlapping, the 2C and 4C peaks of the target species. We recommend PI as the fluorochrome of choice for flow cytometric determination of plant DNA content. DAPI should be used only if the estimated DNA value is corroborated by using a second stain that has no bias for AT- or GC-rich sequences within genomes.

We describe a novel concept and corresponding methods for the analysis of transcription in higher plant cells. The concept is that an examination of the presence of different polyadenylated transcripts within isolated nuclei reflects the state of gene expression at a given moment more precisely than do conventional techniques using total cellular mRNA. The methods involve isolation of polyadenylated nuclear transcripts from flow-sorted nuclei, reverse transcription, amplification using the polymerase chain reaction, and analysis of the products through gel electrophoresis and sequencing. By using specific primers, we have demonstrated detection of selected gene products in nuclei from transgenic plants. We also employed a technique for analysis of individual transcripts based on the length polymorphisms of restriction fragments derived from their 38 ends. Because the technique does not require a priori knowledge of the analyzed sequences, it is suitable for displaying the complete spectra of RNA transcripts present in nuclei at the moment of their isolation. These fragments can be easily isolated and sequenced and the sequence information used for assignment of putative function of corresponding genes. These techniques have been used to identify leaf-, root-, and cell cyclespecific transcripts. In principle, they should be applicable to the tissues of any eukaryotic species that contain transcriptionally active nuclei. Cytometry 33:460‐468, 1998. r 1998 Wiley-Liss, Inc.

The soluble proteins of the nucleoplasm are synthesized on cytoplasmic ribosomes. Proteins larger than about 40 kDa are post-translationally targeted to the nucleus via energy-dependent processes, passing through the nuclear pore complex into the nucleoplasm. Targeting involves nuclear localization signals (NLSs) found within the primary sequences of the imported proteins. In higher plants, information has come primarily from study of proteins carrying ‘classical’ NLSs, comprising stretches of basic amino acids, and has required assays to measure nuclear uptake both in vitro and in vivo. In general, these assays are not entirely satisfactory; they are either technically demanding, are of limited accuracy and statistical rigor, or are unsuitable for in vivo applications.

Regression tests of the expectations theory of the term structure typically reject the null hypothesis of orthogonality between implied forecast errors and the yield spreads. In the statistical literature on the term structure, these rejections are sometimes attributed to time-varying liquidity premia, and Engle et al. (1987) suggest that the ARCH-M model of time-variation in the liquidity premium may be sufficient to account for rejections of the expectations theory. We use non-parametric (kernel) regression to explore the regression test results on a number of data sets, and find some evidence of a persistent deviation from orthogonality for large absolute values of the spread. Incorporating ARCH-in-mean into models of the term premium indicates that this specification does explain significant time variation in liquidity premia, but the effect does not apepar to be sufficient to account for all of the deviations from orthogonality of forecast errors and spreads.

Cholesterol oxidase (EC 1.1.3.6.) is an insecticidal protein known to have potent activity against the boll weevil, milder activity against a number of lepidopteran species, and virtually no activity against other insects. Several factors that could explain its species-dependent differential activity were examined. We compared cholesterol concentrations and rates of cholesterol oxidation in the midgut membranes from larvae of boll weevil (Anthonomus grandis grandis Boheman), southern corn rootworm (Diabrotica undecimpunctata howardi Barber), tobacco budworm (Heliothis virescens Fabricius), and yellow mealworm (Tenebrio molitor Linnaeus). Results showed that cholesterol concentration alone could not account for the differences in insecticidal activity and that midgut brush-border membranes of all species tested were generally susceptible to oxidation by cholesterol oxidase in vitro. We also demonstrated that cholesterol oxidase stability in the midgut environment was similar for the species tested and thus could not account for the differential activity. However, comparison of the pH of the insect midgut fluids with the pH optimum of cholesterol oxidase indicated that the lower sensitivity of lepidopteran larvae to the enzyme may be partially due to the alkaline nature of their midgut environments. In some species, oxidation caused significant changes in the activities of brush-border membrane alkaline phosphatase, and these changes did correlate with the susceptibility of the insect to cholesterol oxidase. Arch. Insect Biochem. Physiol. 34:429–442, 1997. © 1997 Wiley-Liss, Inc.

In flow cytometry, the typical use of front-end analog processing limits the pulse waveform features that can be measured to pulse integral, height, and width. Direct digitizing of the waveforms provides a means for the extraction of additional features, for example, pulse skewness and kurtosis, and Fourier properties. In this work, we have first demonstrated that the Fourier properties of the pulse can be employed usefully for discrimination between different types of cells that otherwise cannot be classified by using only time-domain features of the pulse. We then implemented and evaluated automatic procedures for cell classification based on neural networks. We established that neural networks could provide an efficient means of classification of cell types without the need for user interaction. The neural networks were also employed in an innovative manner for analysis of the digital flow cytometric data without feature extraction. The performance of the neural networks was compared with that of a more conventional means of classification, the K-means clustering algorithm. Neural networks can be realized in hardware, and this, in addition to their highly parallel architecture, makes them an important potential part of real-time analysis systems. These results are discussed in terms of the design of a real-time digital data acquisition system for flow cytometry. © 1996 Wiley-Liss, Inc.

An understanding of vexing issues and challenges is a foundation for advancing practice and research about the mentoring process.

A series of 2-substituted- and 2,3-disubstituted-4-(4-fluorophenyl)-5-[4-(methylsulfonyl)phenyl]-1H- pyrroles was synthesized and found to be active in the rat adjuvant arthritis model of inflammation. The most active compounds were the 2-halo derivatives in the order of chloro > bromo > iodo. The same pattern of activity was observed for the 2,3-dihalopyrroles. Quantitative structure-activity relationship studies suggested that the activity could be correlated with the molar refractivity and the inductive field effect of the 2-substituent and the lipophilicity of the 3-substituent.

We replicated DNA fingerprints of snapping turtles (Chelydra serpentina) and hypervariable restriction fragments of red-winged blackbirds (Agelaius phoeniceus) to estimate the between-blot and between-lane components of variance in molecular weights of restriction fragments. Molecular weight standards were included in every lane, and bands were sized using a sonic digitizer. In both studies, a strong positive correlation was found between band size and coefficient of variation (CV; mean = 0.7%). In the DNA fingerprint study, 26% of the variance in estimates of band size was due to differences between blots, 10% due to differences between lanes on the same blot, and 64% due to error in the digitizing process. In the restriction fragment length polymorphism (RFLP) study, 16% of the variance was due to difference between lanes, and 84% to digitizing. Statistical models were developed to measure the effect of sizing error on identifying identical fragments in different lanes or on different blots, in categorizing distinct alleles, and in determining the size of bins in operational allele definitions. We suggest that the distance between bands be at least 2.8 standard deviations (SD) before they are declared different at alpha = 0.05, and 3.7 SD for alpha = 0.01. A variation in CVs strongly indicates that empirical relationships between SD and band size must be used to decide if two bands represent the same allele. Alleles must be at least 3.9 SD apart before the chance of assigning new observations in error falls below 0.05. We suggest that a minimum bin width of 16 SD is necessary before the chances of assigning a band to the wrong bin falls below 0.05.