Prenatal and Postnatal Exposure to DDT by Breast Milk Analysis in Canary Islands

The use of p,p' -dichlorodiphenyltrichloroethane (DDT) has been banned since the late 1970s due to its toxicity. However, its long half-life makes it persistent in the environment and, consequently, almost everyone has DDT residues in the body. Human milk constitutes an ideal non-conventional matrix to investigate environmental chronic exposure to organochlorine compounds (OCs) residues. The study aimed to identify potential population risk factors of exposure to DDT due to the proximity to countries where it is still used. Seventy-two consecutive lactating women were prospectively included in Tenerife, Canary Islands (Spain). A validated questionnaire was used to obtain socioeconomic, demographics data, and daily habits during pregnancy. DDT levels in breast milk were measured by gas chromatography with-electron capture detector (GC-ECD). Anthropometrics measurements in newborns were obtained. Thirty-four out of 72 (47.2%) of the analysed milk samples presented detectable levels of DDT (mean: 0.92 ng/g), ranging between 0.08 to 16.96 ng/g. The socio-demographic variables did not significantly differ between detectable DDT and non-detectable DDT groups. We found positive association between DDT levels and vegetables (OR (95%CI): 1.23 (1.01-1.50)) and poultry meat (OR (95%CI): 2.05 (1.16-3.60)) consumption, and also between the presence of DDT in breast milk and gestational age (OR (95%CI): 0.59 (0.40-0.90)). DDT is present in breast milk of women at the time of delivery. Residual levels and the spread from countries still using DDT explain DDT detection from vegetables and from animal origin food. The presence of this compound in breast milk represents a pre- and postnatal exposure hazard for foetuses and infants due to chronic bioaccumulation and poor elimination, with possible deleterious effects on health. This data should be used to raise awareness of the risks of OCs exposure and to help establish health policies in order to avoid its use worldwide and thus, to prevent its propagation

Accelerating edit-distance sequence alignment on GPU using the wavefront algorithm

Sequence alignment remains a fundamental problem with practical applications ranging from pattern recognition to computational biology. Traditional algorithms based on dynamic programming are hard to parallelize, require significant amounts of memory, and fail to scale for large inputs. This work presents eWFA-GPU, a GPU (graphics processing unit)-accelerated tool to compute the exact edit-distance sequence alignment based on the wavefront alignment algorithm (WFA). This approach exploits the similarities between the input sequences to accelerate the alignment process while requiring less memory than other algorithms. Our implementation takes full advantage of the massive parallel capabilities of modern GPUs to accelerate the alignment process. In addition, we propose a succinct representation of the alignment data that successfully reduces the overall amount of memory required, allowing the exploitation of the fast shared memory of a GPU. Our results show that our GPU implementation outperforms by 3- 9× the baseline edit-distance WFA implementation running on a 20 core machine. As a result, eWFA-GPU is up to 265 times faster than state-of-the-art CPU implementation, and up to 56 times faster than state-of-the-art GPU implementations.This work was supported in part by the European Unions’s Horizon 2020 Framework Program through the DeepHealth Project under Grant 825111; in part by the European Union Regional Development Fund within the Framework of the European Regional Development Fund (ERDF) Operational Program of Catalonia 2014–2020 with a Grant of 50% of Total Cost Eligible through the Designing RISC-V-based Accelerators for next-generation Computers Project under Grant 001-P-001723; in part by the Ministerio de Ciencia e Innovacion (MCIN) Agencia Estatal de Investigación (AEI)/10.13039/501100011033 under Contract PID2020-113614RB-C21 and Contract TIN2015-65316-P; and in part by the Generalitat de Catalunya (GenCat)-Departament de Recerca i Universitats (DIUiE) (GRR) under Contract 2017-SGR-313, Contract 2017-SGR-1328, and Contract 2017-SGR-1414. The work of Miquel Moreto was supported in part by the Spanish Ministry of Economy, Industry and Competitiveness under Ramon y Cajal Fellowship under Grant RYC-2016-21104.Peer ReviewedPostprint (published version

OpenCL-based FPGA accelerator for semi-global approximate string matching using diagonal bit-vectors

An FPGA accelerator for the computation of the semi-global Levenshtein distance between a pattern and a reference text is presented. The accelerator provides an important benefit to reduce the execution time of read-mappers used in short-read genomic sequencing. Previous attempts to solve the same problem in FPGA use the Myers algorithm following a column approach to compute the dynamic programming table. We use an approach based on diagonals that allows for some resource savings while maintaining a very high throughput of 1 alignment per clock cycle. The design is implemented in OpenCL and tested on two FPGA accelerators. The maximum performance obtained is 91.5 MPairs/s for 100 × 120 sequences and 47 MPairs/s for 300 × 360 sequences, the highest ever reported for this problem.This research was supported by the EU Regional Development Fund under the DRAC project [001-P-001723], by the MINECO-Spain (contract TIN2017-84553-C2-1-R), by the MICIU-Spain (contract RTI2018-095209-B-C22) and by the Catalan government (contracts 2017-SGR-1624, 2017-SGR313, 2017-SGR-1328). M.M. was partially supported by the MINECO under RYC-2016-21104. We thank Intel for granting us access to the DevCloud system and let us join the HARP research program. The presented HARP-2 results were obtained on resources hosted at the Paderborn Center for Parallel Computing (PC2) in the Intel Hardware Accelerator Research Program (HARP2).Peer ReviewedPostprint (author's final draft

Recensiones [Revista de Historia Económica Año XII Primavera-Verano 1994 n. 2 pp. 437-472]

Editada en la Universidad Carlos IIIRobert C. Allen. Enclosure and the Yeoman. The Agricultural Development of the SouthMidlands 1410-1850 (Por Gaspar Feliú).-- Ruggiero Romano. Conjonctures opposées. La «crise» du XVII siècle: en Europe et en Amérique ibérique (Por Gaspar Feliú).-- Simposio de Historia de las Mentalidades. Instituto Nacional de Antropología e Historia, México. Familia y poder en Nueva España (Por Juan Carlos Sola Corbacho).-- Leandro Prados de la Escosura y Samuel Amaral (Eds.). La independencia americana: consecuencias económicas (Por Javier Cuenca).-- M.ª Cruz Romeo Mateo. Entre el orden y la revolución. La formación de la burguesía liberal en la crisis de la monarquía absoluta (1814-1833) (Por Ricardo Robledo).-- José G. Cayuela Fernández. Bahía de ultramar. España y Cuba en el siglo XIX. El control de las relaciones coloniales (Por Candelaria Sáiz Pastor).-- José Manuel Pose Antelo. La economía y la sociedad compostelanas a finales del siglo XIX (Por Carlos Larrinaga Rodríguez).-- Frank Broeze. Mr Brooks and the Australian Trade. Imperial Business in the Nineteenth Century (Por Jesús M.ª Valdaliso).-- Robert H. Bremner. Desde lo más bajo. El descubrimiento de la pobreza en Estados Unidos / James T. Patterson. La lucha contra la pobreza en los Estados Unidos de América, 1900-1985 (Por Nuria Puig).-- Justo Navarro Clari. Curso de Historia Económica (Por Antonio Santamaría)Publicad

Non-linear models for black carbon exposure modelling using air pollution datasets

Black carbon (BC) is a product of incomplete combustion, present in urban aerosols and sourcing mainly from road traffic. Epidemiological evidence reports positive associations between BC and cardiovascular and respiratory disease. Despite this, BC is currently not regulated by the EU Air Quality Directive, and as a result BC data are not available in urban areas from reference air quality monitoring networks in many countries. To fill this gap, a machine learning approach is proposed to develop a BC proxy using air pollution datasets as an input. The proposed BC proxy is based on two machine learning models, support vector regression (SVR) and random forest (RF), using observations of particle mass and number concentrations (N), gaseous pollutants and meteorological variables as the input. Experimental data were collected from a reference station in Barcelona (Spain) over a 2-year period (2018–2019). Two months of additional data were available from a second urban site in Barcelona, for model validation. BC concentrations estimated by SVR showed a high degree of correlation with the measured BC concentrations (R2 = 0.828) with a relatively low error (RMSE = 0.48 µg/m3). Model performance was dependent on seasonality and time of the day, due to the influence of new particle formation events. When validated at the second station, performance indicators decreased (R2 = 0.633; RMSE = 1.19 µg/m3) due to the lack of N data and PM2.5 and the smaller size of the dataset (2 months). New particle formation events critically impacted model performance, suggesting that its application would be optimal in environments where traffic is the main source of ultrafine particles. Due to its flexibility, it is concluded that the model can act as a BC proxy, even based on EU-regulatory air quality parameters only, to complement experimental measurements for exposure assessment in urban areas.The authors would like to acknowledge the support from the Generalitat de Catalunya (Dept. Medi Ambient) by providing the air quality data. This work was partly supported by H2020 project RI-URBANS (H2020-LC-GD-2020-6, reference 101036245), the Spanish Ministry of Science and Innovation (projects CEX2018-000794-S and PID2019- 107910RB-I00), Academy of Finland via flagship on Atmosphere and Climate Competence Center (ACCC, project number 337549) and by AGAUR (project 2017 SGR41 and 2017 SGR 990). It was carried out in the framework of a joint collaboration between IDAEA-CSIC and University of Barcelona (Physics Faculty).Peer ReviewedPostprint (published version

Single versus tandem autologous stem-cell transplantation in patients with newly diagnosed multiple myeloma and high-risk cytogenetics. A retrospective, open-label study of the PETHEMA/Spanish Myeloma Group (GEM)

Tandem ASCT has been suggested as a valid approach to improve the prognosis of patients with MM and HR cytogenetic. In this observational, retrospective study, 213 patients with newly diagnosed MM and HR cytogenetic in 35 hospitals from the Spanish Myeloma Group underwent single or tandem ASCT between January 2015 and December 2019 after induction with VTD/VRD. HR cytogenetic was defined as having ≥1 of the following: del17p, t(4;14), t(14;16) or gain 1q21. More patients in the tandem group had R-ISS 3 and >1 cytogenetic abnormality at diagnosis. With a median follow-up of 31 months (range, 10–82), PFS after single ASCT was 41 months versus 48 months with tandem ASCT (p = 0.33). PFS in patients with del17p undergoing single ASCT was 41 months, while 52% of patients undergoing tandem ASCT were alive and disease free at 48 months. In conclusion, tandem ASCT partly overcomes the bad prognosis of HR cytogenetic

The role of Prenatal Care and Social Risk Factors in the relationship between immigrant status and neonatal morbidity: A retrospective cohort study

Background and Aim Literature evaluating association between neonatal morbidity and immigrant status presents contradictory results. Poorer compliance with prenatal care and greater social risk factors among immigrants could play roles as major confounding variables, thus explaining contradictions. We examined whether prenatal care and social risk factors are confounding variables in the relationship between immigrant status and neonatal morbidity. Methods Retrospective cohort study: 231 pregnant African immigrant women were recruited from 2007–2010 in northern Spain. A Spanish population sample was obtained by simple random sampling at 1:3 ratio. Immigrant status (Spanish, Sub-Saharan and Northern African), prenatal care (Kessner Index adequate, intermediate or inadequate), and social risk factors were treated as independent variables. Low birth weight (LBW < 2500 grams) and preterm birth (< 37 weeks) were collected as neonatal morbidity variables. Crude and adjusted odds ratios (OR) were estimated by unconditional logistic regression with 95% confidence intervals (95% CI). Results Positive associations between immigrant women and higher risk of neonatal morbidity were obtained. Crude OR for preterm births in Northern Africans with respect to nonimmigrants was 2.28 (95% CI: 1.04–5.00), and crude OR for LBW was 1.77 (95% CI: 0.74–4.22). However, after adjusting for prenatal care and social risk factors, associations became protective: adjusted OR for preterm birth = 0.42 (95% CI: 0.14–1.32); LBW = 0.48 (95% CI: 0.15–1.52). Poor compliance with prenatal care was the main independent risk factor associated with both preterm birth (adjusted OR inadequate care = 17.05; 95% CI: 3.92–74.24) and LBW (adjusted OR inadequate care = 6.25; 95% CI: 1.28–30.46). Social risk was an important independent risk factor associated with LBW (adjusted OR = 5.42; 95% CI: 1.58– 18.62). Conclusions Prenatal care and social risk factors were major confounding variables in the relationship between immigrant status and neonatal morbidity

Amyloid Precursor Protein and Proinflammatory Changes Are Regulated in Brain and Adipose Tissue in a Murine Model of High Fat Diet-Induced Obesity

Background: Middle age obesity is recognized as a risk factor for Alzheimer’s disease (AD) although a mechanistic linkage remains unclear. Based upon the fact that obese adipose tissue and AD brains are both areas of proinflammatory change, a possible common event is chronic inflammation. Since an autosomal dominant form of AD is associated with mutations in the gene coding for the ubiquitously expressed transmembrane protein, amyloid precursor protein (APP) and recent evidence demonstrates increased APP levels in adipose tissue during obesity it is feasible that APP serves some function in both disease conditions. Methodology/Principal Findings: To determine whether diet-induced obesity produced proinflammatory changes and altered APP expression in brain versus adipose tissue, 6 week old C57BL6/J mice were maintained on a control or high fat diet for 22 weeks. Protein levels and cell-specific APP expression along with markers of inflammation and immune cell activation were compared between hippocampus, abdominal subcutaneous fat and visceral pericardial fat. APP stimulation-dependent changes in macrophage and adipocyte culture phenotype were examined for comparison to the in vivo changes. Conclusions/Significance: Adipose tissue and brain from high fat diet fed animals demonstrated increased TNF-a and microglial and macrophage activation. Both brains and adipose tissue also had elevated APP levels localizing to neurons and macrophage/adipocytes, respectively. APP agonist antibody stimulation of macrophage cultures increased specific cytokin

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700