Search

Abstract Accurate mapping and monitoring of tropical forests aboveground biomass (AGB) is crucial to design effective carbon emission reduction strategies and improving our understanding of Earth’s carbon cycle. However, existing large-scale maps of tropical forest AGB generated through combinations of Earth Observation (EO) and forest inventory data show markedly divergent estimates, even after accounting for reported uncertainties. To address this, a network of high-quality reference data is needed to calibrate and validate mapping algorithms. This study aims to generate reference AGB datasets using field inventory plots and airborne LiDAR data for eight sites in Central Africa and five sites in South Asia, two regions largely underrepresented in global reference AGB datasets. The study provides access to these reference AGB maps, including uncertainty maps, at 100 m and 40 m spatial resolutions covering a total LiDAR footprint of 1,11,650 ha [ranging from 150 to 40,000 ha at site level]. These maps serve as calibration/validation datasets to improve the accuracy and reliability of AGB mapping for current and upcoming EO missions (viz., GEDI, BIOMASS, and NISAR).

Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research-from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology-from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.

The theme of “Power and Letters” can hardly be dissociated from its counterpoint “Letters and Power”. In a state where there was no institutionalised censorship, but where the power of the emperor increased markedly after the crisis of the 3rd century, we will begin by looking at the main means that the sovereigns and their entourage had at their disposal to control literary production. This will be followed by an overview of courtly production, in particular panegyric literature, its codification and the significant changes it underwent throughout the period under consideration. Finally, we will look at the political function of literature, particularly in its parenetic dimension. Without excluding the eastern part of the empire and Greek literature, the focus will be on the western and Latin-speaking world.

Aim: Tree crowns determine light interception, carbon and water exchange. Thus, understanding the factors causing tree crown allometry to vary at the tree and stand level matters greatly for the development of future vegetation modelling and for the calibration of remote sensing products. Nevertheless, we know little about large-scale variation and determinants in tropical tree crown allometry. In this study, we explored the continental variation in scaling exponents of site-specific crown allometry and assessed their relationships with environmental and stand-level variables in the tropics. Location: Global tropics. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 87,737 trees distributed among 245 forest and savanna sites across the tropics, we fitted site-specific allometric relationships between crown dimensions (crown depth, diameter and volume) and stem diameter using power-law models. Stand-level and environmental drivers of crown allometric relationships were assessed at pantropical and continental scales. Results: The scaling exponents of allometric relationships between stem diameter and crown dimensions were higher in savannas than in forests. We identified that continental crown models were better than pantropical crown models and that continental differences in crown allometric relationships were driven by both stand-level (wood density) and environmental (precipitation, cation exchange capacity and soil texture) variables for both tropical biomes. For a given diameter, forest trees from Asia and savanna trees from Australia had smaller crown dimensions than trees in Africa and America, with crown volumes for some Asian forest trees being smaller than those of trees in African forests. Main conclusions: Our results provide new insight into geographical variability, with large continental differences in tropical tree crown allometry that were driven by stand-level and environmental variables. They have implications for the assessment of ecosystem function and for the monitoring of woody biomass by remote sensing techniques in the global tropics.

Myofibroblasts contribute to the development of liver fibrosis. Here, the authors report that the transcription factor Basonuclin 2 (BNC2) integrates fibrogenic signals and drives myofibroblastic transcriptional activation in liver fibrosis.

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able - for the first time - to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed - specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large-scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.

Mapping ecological variables using machine-learning algorithms based on remote-sensing data has become a widespread practice in ecology. Here, the authors use forest biomass mapping as a study case to show that the most common model validation approach, which ignores data spatial structure, leads to overoptimistic assessment of model predictive power.

Abstract Liver injury triggers adaptive remodeling of the hepatic transcriptome for repair/regeneration. We demonstrate that this involves particularly profound transcriptomic alterations where acute induction of genes involved in handling of endoplasmic reticulum stress (ERS) is accompanied by partial hepatic dedifferentiation. Importantly, widespread hepatic gene downregulation could not simply be ascribed to cofactor squelching secondary to ERS gene induction, but rather involves a combination of active repressive mechanisms. ERS acts through inhibition of the liver‐identity (LIVER‐ID) transcription factor (TF) network, initiated by rapid LIVER‐ID TF protein loss. In addition, induction of the transcriptional repressor NFIL3 further contributes to LIVER‐ID gene repression. Alteration to the liver TF repertoire translates into compromised activity of regulatory regions characterized by the densest co‐recruitment of LIVER‐ID TFs and decommissioning of BRD4 super‐enhancers driving hepatic identity. While transient repression of the hepatic molecular identity is an intrinsic part of liver repair, sustained disequilibrium between the ERS and LIVER‐ID transcriptional programs is linked to liver dysfunction as shown using mouse models of acute liver injury and livers from deceased human septic patients.

Half of Asian tropical forests were disturbed in the last century resulting in the dominance of secondary forests in Southeast Asia. However, the rate at which biomass accumulates during the recovery process in these forests is poorly understood. We studied a forest landscape located in Khao Yai National Park (Thailand) that experienced strong disturbances in the last century due to clearance by swidden farmers. Combining recent field and airborne laser scanning (ALS) data, we first built a high-resolution aboveground biomass (AGB) map of over 60 km2 of forest landscape. We then used the random forest algorithm and Landsat time series (LTS) data to classify landscape patches as non-forested versus forested on an almost annual basis from 1972 to 2017. The resulting chronosequence was then used in combination with the AGB map to estimate forest carbon recovery rates in secondary forest patches during the first 42 years of succession. The ALS-AGB model predicted AGB with an error of 14 % at 0.5 ha resolution (RMSE=45 Mg ha−1) using the mean top-of-canopy height as a single predictor. The mean AGB over the landscape was 291 Mg ha−1, showing a high level of carbon storage despite past disturbance history. We found that AGB recovery varies non-linearly in the first 42 years of the succession, with an increasing rate of accumulation through time. We predicted a mean AGB recovery rate of 6.9 Mgha-1yr-1, with a mean AGB gain of 143 and 273 Mg ha−1 after 20 and 40 years, respectively. This rate estimate is about 50 % larger than the rate prescribed for young secondary Asian tropical rainforests in the 2019 refinement of the 2006 IPCC guidelines for national greenhouse gas inventories. Our study hence suggests that the new IPCC rates, which were based on limited data from Asian tropical rainforests, strongly underestimate the carbon potential of forest regrowth in tropical Asia. Our recovery estimates are also within the range of those reported for the well-studied Latin American secondary forests under similar climatic conditions. This study illustrates the potential of ALS data not only for scaling up field AGB measurements but also for predicting AGB recovery dynamics when combined with long-term satellite data. It also illustrates that tropical forest landscapes that were disturbed in the past are of utmost importance for the regional carbon budget and thus for implementing international programs such as REDD+.

When ordinating plots of tropical rain forests using stand-level structural attributes such as biomass, basal area and the number of trees in different size classes, two patterns often emerge: a gradient from poorly to highly stocked plots and high positive correlations between biomass, basal area and the number of large trees. These patterns are inherited from the demographics (growth, mortality and recruitment) and size allometry of trees and tend to obscure other patterns, such as site differences among plots, that would be more informative for inferring ecological processes. Using data from 133 rain forest plots at nine sites for which site differences are known, we aimed to filter out these patterns in forest structural attributes to unveil a hidden pattern. Using a null model framework, we generated the anticipated pattern inherited from individual allometric patterns. We then evaluated deviations between the data (observations) and predictions of the null model. Ordination of the deviations revealed site differences that were not evident in the ordination of observations. These sites differences could be related to different histories of large-scale forest disturbance. By filtering out patterns inherited from individuals, our model analysis provides more information on ecological processes.

Abstract Direct and semidirect estimations of leaf area (LA) and leaf area index (LAI) are scarce in dense tropical forests despite their importance in calibrating remote sensing products, forest dynamics, and biogeochemical models. We destructively sampled 61 trees belonging to 13 most abundant species in a semideciduous forest in southeastern Cameroon. For each tree, all leaves were weighed, and for a subsample of branches, leaves were counted and the LA measured. Allometric models were calibrated to allow semidirect estimation of LAI at tree and stand levels based on forest inventory data (R2 = 0.7, bias = 21.2%, error = 39.5%) and on predictors that could be extracted from very high resolution remote sensing data (R2 = 0.63, bias = 35.1%, error = 58.73). Using twenty‐one 1‐ha forest plots, stand level estimations of LAI ranged from 4.42–13.99. These values are higher than previous estimates generally obtained using indirect methods. These results may have important consequences on ecosystem exchanges and the role of tropical forest in global cycles.

Remotely sensed maps of forest carbon stocks have enormous potential for supporting greenhouse gas (GHG) inventory and monitoring in tropical countries. However, most countries have not used maps as the reference data for GHG inventory due to the lack of confidence in the accuracy of maps and of data to perform local validation. Here, we use the first national forest inventory (NFI) data of the Democratic Republic of Congo to perform an independent assessment of the country’s latest national spaceborne carbon stocks map. We compared plot-to-plot variations and areal estimates of forest aboveground biomass (AGB) derived from NFI data and from the map across jurisdictional and ecological domains. Across all plots, map predictions were nearly unbiased and captured c. 60% of the variation in NFI plots AGB. Map performance was not uniform along the AGB gradient, and saturated around c. 290 Mg ha−1, increasingly underestimating forest AGB above this threshold. Splitting NFI plots by land cover types, we found map predictions unbiased in the dominant terra firme Humid forest class, while plot-to-plot variations were poorly captured (R2 of c. 0.33, or c. 0.20 after excluding disturbed plots). In contrast, map predictions underestimated AGB by c. 33% in the small AGB woodland savanna class but captured a much greater share of plot-to-plot AGB variation (R2 of c. 0.41, or 0.58 after excluding disturbed plots). Areal estimates from the map and NFI data depicted a similar trend with a slightly smaller (but statistically indiscernible) mean AGB from the map across the entire study area (i.e., 252.7 vs. 280.6 Mg ha−1), owing to the underestimation of mean AGB in the woodland savanna domain (31.8 vs. 57.3 Mg ha−1), which was broadly consistent with the results obtained at the provincial level. This study provides insights and outlooks for country-wide AGB mapping efforts in the tropics and the computation of emission factors in Democratic Republic of Congo for carbon monitoring initiatives.

BackgroundUpper extremity venous thrombosis (UEVT) represents about 10% of venous thrombo-embolic disease. This is mainly explained by the increasing use of central venous line, for oncologic or nutritional care. The factors associated with venous recanalization are not known.ObjectiveThe aim of this study was to investigate prognosis factor associated with venous recanalization after UEVT.MethodsThis study included patients with UEVT diagnosed with duplex ultra-sonography (DUS) from January 2015 to December 2017 with DUS evaluations during follow-up. A multivariate Cox proportional-hazards-model analysis was performed to identify predictive factors of UEVT complete recanalization.ResultsThis study included 494 UEVT, 304 proximal UEVT and 190 distal UEVT. The median age was 58 years, 39.5% were women. Clinical context was: hematological malignancy (40.7%), solid cancer (14.2%), infectious or inflammatory context (49.9%) and presence of venous catheters or pacemaker leads in 86.4%. The rate of recanalization without sequelae of UEVT was 38%. For all UEVT, in multivariate analysis, factors associated with complete vein recanalization were: thrombosis associated with central venous catheter (CVC) (HR:2.40, [1.45;3.95], pConclusionIn this study, factors associated with UEVT recanalization were UEVT limited to a venous segment, thrombosis associated with CVC, a thrombosis of deep and distal thrombosis topography and superficial thrombosis of the forearm. Occlusive thrombosis was associated with the absence of UEVT recanalization.

Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees 1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

Precise accounting of carbon stocks and fluxes in tropical vegetation using remote sensing approaches remains a challenging exercise, as both signal saturation and ground sampling limitations contribute to inaccurate extrapolations. Airborne LiDAR Scanning (ALS) data can be used as an intermediate level to radically increase sampling and enhance model calibration. Here we tested the potential of using ALS data for upscaling vegetation aboveground biomass (AGB) from field plots to a forest-savanna transitional landscape in the Guineo–Congolian region in Cameroon, using either a design-based approach or a model-based approach leveraging multispectral satellite imagery. Two sets of reference data were used: (1) AGB values collected from 62 0.16-ha plots distributed both in forests and savannas; and (2) an AGB map generated form ALS data. In the model-based approach, we trained Random Forest models using predictors from recent sensors of varying spectral and spatial resolutions (Spot 6/7, Landsat 8, and Sentinel 2), along with biophysical predictors derived after pre-processing into the Overland processing chain, following a forward variable selection procedure with a spatial 4-folds cross validation. The models calibrated with field plots lead to a systematic overestimation in AGB density estimates and a root mean squared prediction error (RMSPE) of up to 65 Mg.ha−1 (90%), whereas calibration with ALS lead to low bias and a drop of ~30% in RMSPE (down to 43 Mg.ha−1, 58%) with little effect of the satellite sensor used. Decomposing bias along the AGB density range, we show that multispectral images can (in some specific cases) be used for unbiased prediction at landscape scale on the basis of ALS-calibrated statistical models. However, our results also confirm that, whatever the spectral indices used and attention paid to sensor quality and pre-processing, the signal is not sufficient to warrant accurate pixelwise predictions, because of large relative RMSPE, especially above (200–250 t/ha). The design-based approach, for which average AGB density values were attributed to mapped land cover classes, proved to be a simple and reliable alternative (for landscape to region level estimations), when trained with dense ALS samples.

The nucleolus produces the large polycistronic transcript (47S precursor) containing the 18S, 5.8S and 28S rRNA sequences and hosts most of the nuclear steps of pre-rRNA processing. Among numerous components it contains condensed chromatin and active rRNA genes which adopt a more accessible conformation. For this reason, it is a paradigm of chromosome territory organization. Active rRNA genes are clustered within several fibrillar centers (FCs), in which they are maintained in an open configuration by Upstream Binding Factor (UBF) molecules. Here, we used the reproducible reorganization of nucleolar components induced by the inhibition of rRNA synthesis by Actinomycin D (AMD) to address the steps of the spatiotemporal reorganization of FCs and nucleolar condensed chromatin. To reach that goal, we used two complementary approaches: i) time-lapse confocal imaging of cells expressing one or several GFP-tagged proteins (fibrillarin, UBF, histone H2B) and ii) ultrastructural identification of nucleolar components involved in the reorganization. Data obtained by time lapse confocal microscopy were analyzed through detailed 3D imaging. This allowed us to demonstrate that AMD treatment induces no fusion and no change in the relative position of the different nucleoli contained in one nucleus. In contrast, for each nucleolus, we observed step by step gathering and fusion of both FCs and nucleolar condensed chromatin. To analyze the reorganization of FCs and condensed chromatin at a higher resolution, we performed correlative light and electron microscopy electron microscopy (CLEM) imaging of the same cells. We demonstrated that threads of intranucleolar condensed chromatin are localized in a complex 3D network of vacuoles. Upon AMD treatment, these structures coalesce before migrating toward the perinucleolar condensed chromatin, to which they finally fuse. During their migration, FCs, which are all linked to ICC, are pulled by the latter to gather as caps disposed at the periphery of nucleoli.

Many studies have demonstrated changes in the levels of several ions during apoptosis, but a few recent studies have reported conflicting results concerning the changes in water content in apoptotic cells. We used a correlative light and cryo-scanning transmission electron microscopy method to quantify water and ion/element contents simultaneously at a nanoscale resolution in the various compartments of cells, from the onset to the end of apoptosis. We used stably transfected HeLa cells producing H2B-GFP to identify the stages of apoptosis in cells and for a targeted elemental analysis within condensed chromatin, nucleoplasm, mitochondria and the cytosol. We found that the compartments of apoptotic cells contained, on average, 10% more water than control cells. During mitochondrial outer membrane permeabilization, we observed a strong increase in the Na+ and Cl- contents of the mitochondria and a strong decrease in mitochondrial K+ content. During the first step in apoptotic volume decrease (AVD), Na+ and Cl- levels decreased in all cell compartments, but remained higher than those in control cells. Conversely, during the second step of AVD, Na+ and Cl- levels increased considerably in the nucleus and mitochondria. During these two steps of AVD, K+ content decreased steadily in all cell compartments. We also determined in vivo ion status during caspase-3 activity and chromatin condensation. Finally, we found that actinomycin D-tolerant cells had water and K+ contents similar to those of cells entering apoptosis but lower Na+ and Cl- contents than both cells entering apoptosis and control cells.

Pneumonia is caused by respiratory bacteria and/or viruses. Little is known if co-infections are an aggravating factor in hospitalised children with severe pneumonia. We studied the impact of respiratory pathogens on the severity of pneumonia. Between 2007 and 2009, 52 children hospitalised with a well-documented diagnosis of communityacquired pneumonia (CAP), with or without parapneumonic empyema (PPE), were enrolled in the study. The patients were classified into 2 groups: CAP + PPE (n = 28) and CAP (n = 24). The identification of respiratory viruses and bacteria in nasopharyngeal aspirates and pleural effusion samples were performed using conventional bacterial techniques and molecular assays. Using real-time multiplex PCR and antigen detection, Streptococcus pneumoniae was the main agent identified in 76% of the cases by molecular tests and BinaxNOW® in pleural fluid. A total of 8% of pleural fluid samples remained undiagnosed. In nasopharyngeal aspirates, rhinovirus, parainfluenza viruses, human metapneumovirus, and respiratory syncytial virus were detected in both CAP and CAP + PPE populations; however, the percentage of viral co-detection was significantly higher in nasopharyngeal aspirates from CAP + PPE patients (35%) compared with CAP patients (5%). In conclusion, viral co-detection was observed mainly in patients with more severe pneumonia. Molecular biology assays improved the pathogens detection in pneumonia and confirmed the S. pneumoniae detection by BinaxNOW® in pleural effusion samples. Interestingly, the main S. pneumoniae serotypes found in PPE are not the ones targeted by the heptavalent pneumococcal conjugate vaccine.

In tumour cell lines, the resistance of cancer cells to a variety of structurally unrelated chemotherapeutic drugs is termed multidrug‐resistance or MDR. We reported previously that MDR leukemic cells displayed nuclear texture changes, as assessed by image cytometry. The nature of these changes remained uncertain but they could be associated with alterations of the nuclear matrix which could serve an important role in DNA organization and chromatin structure. Therefore, we have compared the textural features observed in G0/G1 nuclei from human leukemic CEM cells and their MDR variant CEM‐VLB, after staining of either DNA by Feulgen method or nuclear matrix by immunodetection of NuMA antigen on DNase treated samples. Chromatin or NuMA distributions within the nucleus were evaluated by image cytometry. Changes in textural parameters indicate that modifications of NuMA distribution observed in MDR cells are parallel to those observed at the whole chromatin level (i.e., a more decondensed and coarse texture with increase of Energy and Long‐run sections and decrease of Contrast and Short‐run sections). Moreover, Optical Densities measurements indicate that MDR cells seem to contain less NuMA, a datum confirmed by immunoblotting of nuclear proteins. In conclusion, chromatin changes observed by image cytometry in drug‐resistant human leukemic CEM cells appear associated with modifications of the nuclear matrix structure.

Nuclear all-trans retinoic acid receptors (RARs) initiate early transcriptional events which engage pluripotent cells to differentiate into specific lineages. RAR-controlled transactivation depends mostly on agonist-induced structural transitions in RAR C-terminus (AF-2), thus bridging coactivators or corepressors to chromatin, hence controlling preinitiation complex assembly. However, the contribution of other domains of RAR to its overall transcriptional activity remains poorly defined. A proteomic characterization of nuclear proteins interacting with RAR regions distinct from the AF-2 revealed unsuspected functional properties of the RAR N-terminus. Indeed, mass spectrometry fingerprinting identified the Bromodomain-containing protein 4 (BRD4) and ALL1-fused gene from chromosome 9 (AF9/MLLT3), known to associate with and regulates the activity of Positive Transcription Elongation Factor b (P-TEFb), as novel RAR coactivators. In addition to promoter sequences, RAR binds to genomic, transcribed regions of retinoid-regulated genes, in association with RNA polymerase II and as a function of P-TEFb activity. Knockdown of either AF9 or BRD4 expression affected differentially the neural differentiation of stem cell-like P19 cells. Clusters of retinoid-regulated genes were selectively dependent on BRD4 and/or AF9 expression, which correlated with RAR association to transcribed regions. Thus RAR establishes physical and functional links with components of the elongation complex, enabling the rapid retinoid-induced induction of genes required for neuronal differentiation. Our data thereby extends the previously known RAR interactome from classical transcriptional modulators to components of the elongation machinery, and unravel a functional role of RAR in transcriptional elongation.

The sialidase activity of neuraminidase-1 (Neu-1) is responsible for ERK 1/2 pathway activation following binding of elastin peptide on the elastin receptor complex. In this work, we demonstrate that the receptor and lipid rafts colocalize at the plasma membrane. We also show that the disruption of these microdomains as well as their depletion in glycolipids blocks the receptor signaling. Following elastin peptide treatment, the cellular GM(3) level decreases while lactosylceramide (LacCer) content increases consistently with a GM(3)/LacCer conversion. The use of lactose or Neu-1 siRNA blocks this process suggesting that the elastin receptor complex is responsible for this lipid conversion. Flow cytometry analysis confirms this elastin peptide-driven LacCer generation. Further, the use of a monoclonal anti-GM(3) blocking antibody shows that GM(3) is required for signaling. In conclusion, our data strongly suggest that Neu-1-dependent GM(3)/LacCer conversion is the key event leading to signaling by the elastin receptor complex. As a consequence, we propose that LacCer is an early messenger for this receptor.