Proteome-scale movements and compartment connectivity during the eukaryotic cell cycle.

Cell cycle progression relies on coordinated changes in the composition and subcellular localization of the proteome. By applying two distinct convolutional neural networks on images of millions of live yeast cells, we resolved proteome-level dynamics in both concentration and localization during the cell cycle, with resolution of ∼20 subcellular localization classes. We show that a quarter of the proteome displays cell cycle periodicity, with proteins tending to be controlled either at the level of localization or concentration, but not both. Distinct levels of protein regulation are preferentially utilized for different aspects of the cell cycle, with changes in protein concentration being mostly involved in cell cycle control and changes in protein localization in the biophysical implementation of the cell cycle program. We present a resource for exploring global proteome dynamics during the cell cycle, which will aid in understanding a fundamental biological process at a systems level.

K29-linked free polyubiquitin chains affect ribosome biogenesis and direct ribosomal proteins to the intranuclear quality control compartment.

Ribosome assembly requires precise coordination between the production and assembly of ribosomal components. Mutations in ribosomal proteins that inhibit the assembly process or ribosome function are often associated with ribosomopathies, some of which are linked to defects in proteostasis. In this study, we examine the interplay between several yeast proteostasis enzymes, including deubiquitylases (DUBs) Ubp2 and Ubp14, and E3 ligases Ufd4 and Hul5, and we explore their roles in the regulation of the cellular levels of K29-linked unanchored polyubiquitin (polyUb) chains. Accumulating K29-linked unanchored polyUb chains associate with maturing ribosomes to disrupt their assembly, activate the ribosome assembly stress response (RASTR), and lead to the sequestration of ribosomal proteins at the intranuclear quality control compartment (INQ). These findings reveal the physiological relevance of INQ and provide insights into mechanisms of cellular toxicity associated with ribosomopathies.

PIFiA: self-supervised approach for protein functional annotation from single-cell imaging data.

Fluorescence microscopy data describe protein localization patterns at single-cell resolution and have the potential to reveal whole-proteome functional information with remarkable precision. Yet, extracting biologically meaningful representations from cell micrographs remains a major challenge. Existing approaches often fail to learn robust and noise-invariant features or rely on supervised labels for accurate annotations. We developed PIFiA (Protein Image-based Functional Annotation), a self-supervised approach for protein functional annotation from single-cell imaging data. We imaged the global yeast ORF-GFP collection and applied PIFiA to generate protein feature profiles from single-cell images of fluorescently tagged proteins. We show that PIFiA outperforms existing approaches for molecular representation learning and describe a range of downstream analysis tasks to explore the information content of the feature profiles. Specifically, we cluster extracted features into a hierarchy of functional organization, study cell population heterogeneity, and develop techniques to distinguish multi-localizing proteins and identify functional modules. Finally, we confirm new PIFiA predictions using a colocalization assay, suggesting previously unappreciated biological roles for several proteins. Paired with a fully interactive website ( https://thecellvision.org/pifia/ ), PIFiA is a resource for the quantitative analysis of protein organization within the cell.

Characterization of the zebrafish gabra1sa43718/sa43718 germline loss of function allele confirms a function for Gabra1 in motility and nervous system development.

Mutation of the GABRA1 gene is associated with neurodevelopmental defects and epilepsy. GABRA1 encodes for the α1 subunit of the γ-aminobutyric acid type A receptor (GABAAR), which regulates the fast inhibitory impulses of the nervous system. Multiple model systems have been developed to understand the function of GABRA1, but these models have produced complex and, at times, incongruent data. Thus, additional model systems are required to validate and substantiate previous results. We sought to provide initial phenotypic analysis of a novel germline mutant allele. Our analysis provides a solid foundation for the future use of this allele to characterize gabra1 functionally and pharmacologically using zebrafish. We investigated the behavioral swim patterns associated with a nonsense mutation of the zebrafish gabra1 (sa43718 allele) gene. The sa43718 allele causes a decrease in gabra1 mRNA expression, which is associated with light induced hypermotility, one phenotype previously associated with seizure like behavior in zebrafish. Mutation of gabra1 was accompanied by decreased mRNA expression of gabra2, gabra3, and gabra5, indicating a reduction in the expression of additional α sub-units of the GABAAR. Although multiple sub-units were decreased, larvae continued to respond to pentylenetetrazole (PTZ), indicating that a residual GABAAR exists in the sa43718 allele. Proteomics analysis demonstrated that mutation of gabra1 is associated with abnormal expression of proteins that regulate synaptic vesicle fusion, vesicle transport, synapse development, and mitochondrial protein complexes. These data support previous studies performed in a zebrafish nonsense allele created by CRISPR/Cas9 and validate that loss of function mutations in the gabra1 gene result in seizure-like phenotypes with abnormal development of the GABA synapse. Our results add to the existing body of knowledge as to the function of GABRA1 during development and validate that zebrafish can be used to provide complete functional characterization of the gene.

Predicting cellular responses to complex perturbations in high-throughput screens.

Recent advances in multiplexed single-cell transcriptomics experiments facilitate the high-throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible. Therefore, computational methods are needed to predict, interpret, and prioritize perturbations. Here, we present the compositional perturbation autoencoder (CPA), which combines the interpretability of linear models with the flexibility of deep-learning approaches for single-cell response modeling. CPA learns to in silico predict transcriptional perturbation response at the single-cell level for unseen dosages, cell types, time points, and species. Using newly generated single-cell drug combination data, we validate that CPA can predict unseen drug combinations while outperforming baseline models. Additionally, the architecture's modularity enables incorporating the chemical representation of the drugs, allowing the prediction of cellular response to completely unseen drugs. Furthermore, CPA is also applicable to genetic combinatorial screens. We demonstrate this by imputing in silico 5,329 missing combinations (97.6% of all possibilities) in a single-cell Perturb-seq experiment with diverse genetic interactions. We envision CPA will facilitate efficient experimental design and hypothesis generation by enabling in silico response prediction at the single-cell level and thus accelerate therapeutic applications using single-cell technologies.

Abnormal chondrocyte development in a zebrafish model of cblC syndrome restored by an MMACHC cobalamin binding mutant.

Variants in the MMACHC gene cause combined methylmalonic acidemia and homocystinuria cblC type, the most common inborn error of intracellular cobalamin (vitamin B12) metabolism. cblC is associated with neurodevelopmental, hematological, ocular, and biochemical abnormalities. In a subset of patients, mild craniofacial dysmorphia has also been described. Mouse models of Mmachc deletion are embryonic lethal but cause severe craniofacial phenotypes such as facial clefts. MMACHC encodes an enzyme required for cobalamin processing and variants in this gene result in the accumulation of two metabolites: methylmalonic acid (MMA) and homocysteine (HC). Interestingly, other inborn errors of cobalamin metabolism, such as cblX syndrome, are associated with mild facial phenotypes. However, the presence and severity of MMA and HC accumulation in cblX syndrome is not consistent with the presence or absence of facial phenotypes. Thus, the mechanisms by which mutations in MMACHC cause craniofacial defects are yet to be completely elucidated. Here we have characterized the craniofacial phenotypes in a zebrafish model of cblC (hg13) and performed restoration experiments with either a wildtype or a cobalamin binding deficient MMACHC protein. Homozygous mutants did not display gross morphological defects in facial development but did have abnormal chondrocyte nuclear organization and an increase in the average number of neighboring cell contacts, both phenotypes were fully penetrant. Abnormal chondrocyte nuclear organization was not associated with defects in the localization of neural crest specific markers, sox10 (RFP transgene) or barx1. Both nuclear angles and the number of neighboring cell contacts were fully restored by wildtype MMACHC and a cobalamin binding deficient variant of the MMACHC protein. Collectively, these data suggest that mutation of MMACHC causes mild to moderate craniofacial phenotypes that are independent of cobalamin binding.

Infections in autoimmune pulmonary alveolar proteinosis: a large retrospective cohort.

BACKGROUND: Autoimmune pulmonary alveolar proteinosis (aPAP) is a rare disease, predisposing to an increased risk of infection. A complete picture of these infections is lacking. RESEARCH QUESTION: Describe the characteristics and clinical outcomes of patients diagnosed with aPAP, and to identify risk factors associated with opportunistic infections. METHODS: We conducted a retrospective cohort including all patients diagnosed with aPAP between 2008 and 2018 in France and Belgium. Data were collected using a standardised questionnaire including demographics, comorbidities, imaging features, outcomes and microbiological data. RESULTS: We included 104 patients, 2/3 were men and median age at diagnosis was 45 years. With a median follow-up of 3.4 years (IQR 1.7-6.6 years), 60 patients (58%), developed at least one infection, including 23 (22%) with opportunistic infections. Nocardia spp was the main pathogen identified (n=10). Thirty-five (34%) patients were hospitalised due to infection. In univariate analysis, male gender was associated with opportunistic infections (p=0.04, OR=3.88; 95% CI (1.02 to 22.06)). Anti-granulocyte macrophage colony-stimulating factor antibody titre at diagnosis was significantly higher among patients who developed nocardiosis (1058 (316-1591) vs 580 (200-1190), p=0.01). Nine patients had died (9%), but only one death was related to infection. INTERPRETATION: Patients with aPAP often presented with opportunistic infections, especially nocardiosis, which highlights the importance of systematic search for slow-growing bacteria in bronchoalveolar lavage or whole lung lavage.

Conditional Generative Models for Dynamic Trajectory Generation and Urban Driving.

This work explores methodologies for dynamic trajectory generation for urban driving environments by utilizing coarse global plan representations. In contrast to state-of-the-art architectures for autonomous driving that often leverage lane-level high-definition (HD) maps, we focus on minimizing required map priors that are needed to navigate in dynamic environments that may change over time. To incorporate high-level instructions (i.e., turn right vs. turn left at intersections), we compare various representations provided by lightweight and open-source OpenStreetMaps (OSM) and formulate a conditional generative model strategy to explicitly capture the multimodal characteristics of urban driving. To evaluate the performance of the models introduced, a data collection phase is performed using multiple full-scale vehicles with ground truth labels. Our results show potential use cases in dynamic urban driving scenarios with real-time constraints. The dataset is released publicly as part of this work in combination with code and benchmarks.

Probabilistic Semantic Mapping for Autonomous Driving in Urban Environments.

Statistical learning techniques and increased computational power have facilitated the development of self-driving car technology. However, a limiting factor has been the high expense of scaling and maintaining high-definition (HD) maps. These maps are a crucial backbone for many approaches to self-driving technology. In response to this challenge, we present an approach that fuses pre-built point cloud map data with images to automatically and accurately identify static landmarks such as roads, sidewalks, and crosswalks. Our pipeline utilizes semantic segmentation of 2D images, associates semantic labels with points in point cloud maps to pinpoint locations in the physical world, and employs a confusion matrix formulation to generate a probabilistic bird's-eye view semantic map from semantic point clouds. The approach has been tested in an urban area with different segmentation networks to generate a semantic map with road features. The resulting map provides a rich context of the environment that is valuable for downstream tasks such as trajectory generation and intent prediction. Moreover, it has the potential to be extended to the automatic generation of HD maps for semantic features. The entire software pipeline is implemented in the robot operating system (ROS), a widely used robotics framework, and made available.

Clinical spectrum and risk factors for mortality among seawater and freshwater critically ill drowning patients: a French multicenter study.

BACKGROUND: Drowning is a global threat and one of the leading causes of injury around the world. The impact of drowning conditions including water salinity on patients' prognosis remains poorly explored in Intensive Care Units (ICUs) patients. METHODS: We conducted a retrospective multicenter study on patients admitted to 14 ICUs in the west of France from January 2013 to January 2020. We first compared demographic and clinical characteristics at admission as well as clinical courses of these patients according to the salinity of drowning water. Then, we aimed to identify variables associated with 28-day survival using a Cox proportional hazard model. RESULTS: Of the 270 consecutive included patients, drowning occurred in seawater in 199 patients (73.7%) and in freshwater in 71 patients (26.3%). Day-28 mortality was observed in 55 patients (20.4%). Freshwater was independently associated with 28-day mortality (Adjusted Hazard Ratio (aHR) 1.84 [95% Confidence Interval (CI) 1.03-3.29], p = 0.04). A higher proportion of freshwater patients presented psychiatric comorbidities (47.9 vs. 19.1%; p < 0.0001) and the etiology of drowning appeared more frequently to be a suicide attempt in this population (25.7 vs. 4.2%; p < 0.0001). The other factors independently associated with 28-day mortality were the occurrence of a drowning-related cardiac arrest (aHR 11.5 [95% CI 2.51-52.43], p = 0.0017), duration of cardiopulmonary resuscitation (aHR 1.05 [95% CI 1.03-1.07], p < 0.0001) and SOFA score at day 1 (aHR 1.2 [95% CI 1.11-1.3], p < 0.0001). CONCLUSIONS: In this large multicenter cohort, freshwater drowning patients had a poorer prognosis than saltwater drowning patients. Reasons for such discrepancies include differences in underlying psychiatric comorbidity, drowning circumstances and severities. Patients with initial cardiac arrest secondary to drowning remain with a very poor prognosis.

Activation of WNT signaling restores the facial deficits in a zebrafish with defects in cholesterol metabolism.

Inborn errors of cholesterol metabolism occur as a result of mutations in the cholesterol synthesis pathway (CSP). Although mutations in the CSP cause a multiple congenital anomaly syndrome, craniofacial abnormalities are a hallmark phenotype associated with these disorders. Previous studies have established that mutation of the zebrafish hmgcs1 gene (Vu57 allele), which encodes the first enzyme in the CSP, causes defects in craniofacial development and abnormal neural crest cell (NCC) differentiation. However, the molecular mechanisms by which the products of the CSP disrupt NCC differentiation are not completely known. Cholesterol is known to regulate the activity of WNT signaling, an established regulator of NCC differentiation. We hypothesized that defects in cholesterol synthesis are associated with reduced WNT signaling, consequently resulting in abnormal craniofacial development. To test our hypothesis we performed a combination of pharmaceutical inhibition, gene expression assays, and targeted rescue experiments to understand the function of the CSP and WNT signaling during craniofacial development. We demonstrate reduced expression of four canonical WNT downstream target genes in homozygous carriers of the Vu57 allele and reduced axin2 expression, a known WNT target gene, in larvae treated with Ro-48-8071, an inhibitor of cholesterol synthesis. Moreover, activation of WNT signaling via treatment with WNT agonist I completely restored the craniofacial defects present in a subset of animals carrying the Vu57 allele. Collectively, these data suggest interplay between the CSP and WNT signaling during craniofacial development.

Back-to-back regression: Disentangling the influence of correlated factors from multivariate observations.

Identifying causes solely from observations can be particularly challenging when i) the factors under investigation are difficult to manipulate independently from one-another and ii) observations are high-dimensional. To address this issue, we introduce ''Back-to-Back'' regression (B2B), a linear method designed to efficiently estimate, from a set of correlated factors, those that most plausibly account for multidimensional observations. First, we prove the consistency of B2B, its links to other linear approaches, and show how it can provide a robust, unbiased and interpretable scalar estimate for each factor. Second, we use a variety of simulated data to show that B2B can outperform forward modeling ("encoding"), backward modeling ("decoding") as well as cross-decomposition modeling (i.e. canonical correlation analysis and partial least squares) on causal identification when the factors and the observations are not orthogonal. Finally, we apply B2B to a hundred magneto-encephalography recordings and to a hundred functional Magnetic Resonance Imaging recordings acquired while subjects performed a 1 â€‹h reading task. B2B successfully disentangles the respective contribution of collinear factors such as word length, word frequency in the early visual and late associative cortical responses respectively. B2B compared favorably to other standard techniques on this disentanglement. We discuss how the speed and the generality of B2B sets promising foundations to help identify the causal contributions of covarying factors from high-dimensional observations.

Hcfc1a regulates neural precursor proliferation and asxl1 expression in the developing brain.

BACKGROUND: Precise regulation of neural precursor cell (NPC) proliferation and differentiation is essential to ensure proper brain development and function. The HCFC1 gene encodes a transcriptional co-factor that regulates cell proliferation, and previous studies suggest that HCFC1 regulates NPC number and differentiation. However, the molecular mechanism underlying these cellular deficits has not been completely characterized. METHODS: Here we created a zebrafish harboring mutations in the hcfc1a gene (the hcfc1aco60/+ allele), one ortholog of HCFC1, and utilized immunohistochemistry and RNA-sequencing technology to understand the function of hcfc1a during neural development. RESULTS: The hcfc1aco60/+ allele results in an increased number of NPCs and increased expression of neuronal and glial markers. These neural developmental deficits are associated with larval hypomotility and the abnormal expression of asxl1, a polycomb transcription factor, which we identified as a downstream effector of hcfc1a. Inhibition of asxl1 activity and/or expression in larvae harboring the hcfc1aco60/+ allele completely restored the number of NPCs to normal levels. CONCLUSION: Collectively, our data demonstrate that hcfc1a regulates NPC number, NPC proliferation, motor behavior, and brain development.

Health impact assessment by the implementation of Madrid City air-quality plan in 2020.

OBJECTIVES: Air pollutant concentrations in many urban areas are still above the legal and recommended limits that are set to protect the citizens' health. Madrid is one of the cities where traffic causes high NO2 levels. In this context, Madrid City Council launched the Air Quality and Climate Change Plan for the city of Madrid (Plan A), a local strategy approved by the previous government in 2017. The aim of this study was to conduct a quantitative health impact assessment to evaluate the number of premature deaths that could potentially be prevented by the implementation of Plan A in Madrid in 2020, at both citywide and within-city level. The main purpose was to support decision-making processes in order to maximize the positive health impacts from the implementation of Plan A measures. METHODS: The Regional Statistical Office provided information on population and daily mortality in Madrid. For exposure assessment, we estimated PM2.5, NO2 and O3 concentration levels for Madrid city in 2012 (baseline air-quality scenario) and 2020 (projected air-quality scenario based on the implementation of Plan A), by means of an Eulerian chemical-transport model with a spatial resolution of 1 km × 1 km and 30 vertical levels. We used the concentration-response functions proposed by two relevant WHO projects to calculate the number of attributable annual deaths corresponding to all non-accidental causes (ICD-10: A00-R99) among all-ages and the adult population (>30 years old) for each district and for Madrid city overall. This health impact assessment was conducted dependant on health-data availability. RESULTS: In 2020, the implementation of Plan A would imply a reduction in the Madrid citywide annual mean PM2.5 concentration of 0.6 µg/m3 and 4.0 µg/m3 for NO2. In contrast, an increase of 1 µg/m3 for O3 would be expected. The annual number of all-cause deaths from long-term exposure (95% CI) that could be postponed in the adult population by the expected air-pollutant concentration reduction was 88 (57-117) for PM2.5 and 519 (295-750) for NO2; short-term exposure accounted for 20 (7-32) for PM2.5 and 79 (47-111) for NO2 in the total population. According to the spatial distribution of air pollutants, the highest mortality change estimations were for the city centre - including Madrid Central and mainly within the M-30 ring road -, as compared to peripheral districts. The positive health impacts from the reductions in PM2.5 and NO2 far exceeded the adverse mortality effects expected from the increase in O3. CONCLUSIONS: Effective implementation of Plan A measures in Madrid city would bring about an appreciable decline in traffic-related air-pollutant concentrations and, in turn, would lead to significant health-related benefits.

Topical 15% Paromomycin-Aquaphilic for Bolivian Leishmania braziliensis Cutaneous Leishmaniasis: A Randomized, Placebo-controlled Trial.

BACKGROUND: Cutaneous leishmaniasis (CL) presents as 1 or more skin lesions, which makes local therapy inherently attractive compared to systemic therapy that exposes the whole body to a drug. For 30 years, 15% paromomycin topical formulations have been in clinical experimentation. Recently, 15% paromomycin in Aquaphilic, a complex base to facilitate adsorption into the lesion, was found superior to aquaphilic vehicle for Old World Leishmania major disease. METHODS: We performed a randomized trial of 15% paromomycin in Aquaphilic (40 patients) vs Aquaphilic vehicle (20 patients) vs a positive control (intralesional pentamidine; 20 patients) against L. braziliensis CL in Bolivia. RESULTS: Cure rates after 6 months of follow-up were 31 of 40 (77.5%, 95% confidence interval [CI] 62.5-88%) for paromomycin-Aquaphilic, 2 of 20 (10%, 95% CI 3-30%) for Aquaphilic vehicle (P < .0001 vs paromomycin-Aquaphilic), and 14 of 20 (70%, 95% CI 48-85.5%) for intralesional pentamidine. Both paromomycin-Aquaphilic and the Aquaphilic vehicle were very well tolerated, with only grade 1 adverse reactions in 5-10% of patients. CONCLUSIONS: Against L. braziliensis CL, a prevalent, aggressive form of New World CL, 15% paromomycin-aquaphilic was vastly superior to a negative vehicle control and was comparable in efficacy to a positive control. This study enlarges the potential use of 15% paromomycin-Aquaphilic from one form of Old World CL to CL more generally. CLINICAL TRIALS REGISTRATION: NCT03096457.

In vitro bactericidal activity of amoxicillin combined with different cephalosporins against endocarditis-associated Enterococcus faecalis clinical isolates.

BACKGROUND: The combination of amoxicillin with cefazolin could be an interesting regimen for the empirical therapy of severe infective endocarditis, but its activity against enterococci is unknown. OBJECTIVES: To evaluate in vitro the bactericidal activity of the combination of amoxicillin with different cephalosporins including cefazolin. METHODS: Combinations of amoxicillin (at MIC×») with cefazolin, cefotaxime, ceftriaxone, cefepime, ceftaroline or ceftobiprole (at the mean free plasma concentration) were studied using time-kill experiments for 10 endocarditis-associated Enterococcus faecalis strains and 2 reference strains. RESULTS: The combinations amoxicillin/cefazolin, amoxicillin/cefotaxime, amoxicillin/ceftriaxone and amoxicillin/cefepime were synergistic at 12 and 24 h against 12/12 strains and amoxicillin/ceftobiprole and amoxicillin/ceftaroline against 10/12 strains. The combination amoxicillin/cefepime was bactericidal at 24 h against 9/12 strains, the combination amoxicillin/cefazolin against 8/12 strains, the combinations amoxicillin/ceftaroline, amoxicillin/cefotaxime and amoxicillin/ceftobiprole against 7/12 strains and the combination amoxicillin/ceftriaxone against 6/12 strains. CONCLUSIONS: The combination amoxicillin/cefazolin is as synergistic and bactericidal in vitro as amoxicillin/cefotaxime or amoxicillin/ceftriaxone against E. faecalis.

A methodology to estimate uncertainty for emission projections through sensitivity analysis.

UNLABELLED: Air pollution abatement policies must be based on quantitative information on current and future emissions of pollutants. As emission projections uncertainties are inevitable and traditional statistical treatments of uncertainty are highly time/resources consuming, a simplified methodology for nonstatistical uncertainty estimation based on sensitivity analysis is presented in this work. The methodology was applied to the "with measures" scenario for Spain, concretely over the 12 highest emitting sectors regarding greenhouse gas and air pollutants emissions. Examples of methodology application for two important sectors (power plants, and agriculture and livestock) are shown and explained in depth. Uncertainty bands were obtained up to 2020 by modifying the driving factors of the 12 selected sectors and the methodology was tested against a recomputed emission trend in a low economic-growth perspective and official figures for 2010, showing a very good performance. IMPLICATIONS: A solid understanding and quantification of uncertainties related to atmospheric emission inventories and projections provide useful information for policy negotiations. However, as many of those uncertainties are irreducible, there is an interest on how they could be managed in order to derive robust policy conclusions. Taking this into account, a method developed to use sensitivity analysis as a source of information to derive nonstatistical uncertainty bands for emission projections is presented and applied to Spain. This method simplifies uncertainty assessment and allows other countries to take advantage of their sensitivity analyses.

Air quality modeling and mortality impact of fine particles reduction policies in Spain.

BACKGROUND: In recent years, Spain has implemented a number of air quality control measures that are expected to lead to a future reduction in fine particle concentrations and an ensuing positive impact on public health. OBJECTIVES: We aimed to assess the impact on mortality attributable to a reduction in fine particle levels in Spain in 2014 in relation to the estimated level for 2007. METHODS: To estimate exposure, we constructed fine particle distribution models for Spain for 2007 (reference scenario) and 2014 (projected scenario) with a spatial resolution of 16×16km(2). In a second step, we used the concentration-response functions proposed by cohort studies carried out in Europe (European Study of Cohorts for Air Pollution Effects and Rome longitudinal cohort) and North America (American Cancer Society cohort, Harvard Six Cities study and Canadian national cohort) to calculate the number of attributable annual deaths corresponding to all causes, all non-accidental causes, ischemic heart disease and lung cancer among persons aged over 25 years (2005-2007 mortality rate data). We examined the effect of the Spanish demographic shift in our analysis using 2007 and 2012 population figures. RESULTS: Our model suggested that there would be a mean overall reduction in fine particle levels of 1µg/m(3) by 2014. Taking into account 2007 population data, between 8 and 15 all-cause deaths per 100,000 population could be postponed annually by the expected reduction in fine particle levels. For specific subgroups, estimates varied from 10 to 30 deaths for all non-accidental causes, from 1 to 5 for lung cancer, and from 2 to 6 for ischemic heart disease. The expected burden of preventable mortality would be even higher in the future due to the Spanish population growth. Taking into account the population older than 30 years in 2012, the absolute mortality impact estimate would increase approximately by 18%. CONCLUSIONS: Effective implementation of air quality measures in Spain, in a scenario with a short-term projection, would amount to an appreciable decline in fine particle concentrations, and this, in turn, would lead to notable health-related benefits. Recent European cohort studies strengthen the evidence of an association between long-term exposure to fine particles and health effects, and could enhance the health impact quantification in Europe. Air quality models can contribute to improved assessment of air pollution health impact estimates, particularly in study areas without air pollution monitoring data.