Thoracic limb salvage by fibular free flap

The treatment of most fractures of the ulna and radius is usually performed by anatomical reduction and internal fixation, when damage is extensive and local soft tissue cannot provide a complete wound coverage, locoregional flaps present a suitable reconstructive benefit. A 35-year-old male patient suffered an exposed diaphysio-metaphyseal fracture with multi-fragmented distal radius. The patient was evaluated during a 10-day period at the National Institute of Rehabilitation, where the osteosynthesis material and a severe infectious process with necrosis were identified. Necrosectomy of the posterior compartment and removal of the osteosynthesis material was performed, a skin defect of approximately 22x16 cm was observed with a bone gap of 6 cm of radius and ulna. a fibula-free flap is placed to correct the skin defect and an external fixative used for bone alignment. The fibular free flap presents an excellent therapeutic alternative in the resolution of bone gaps with extensive skin defect. Whenever a trained microsurgery team is available, current scales of limb injury should be considered but not utilized for therapeutic approach, always trying to shift amputation as the first option, to the very last one of them

Bioavailability and systemic transport of oleanolic acid in humans, formulated as a functional olive oil

14 Páginas.-- 6 Figuras.-- 2 TablasEvidence of the pharmacological activity of oleanolic acid (OA) suggests its potential therapeutic application. However, its use in functional foods, dietary supplements, or nutraceuticals is hindered by limited human bioavailability studies. The BIO-OLTRAD trial is a double-blind, randomized controlled study with 22 participants that received a single dose of 30 mg OA formulated as a functional olive oil. The study revealed that the maximum serum concentration of OA ranged from 500 to 600 ng mL-1, with an AUC0-∞ value of 2862.50 ± 174.50 ng h mL-1. Furthermore, we discovered a physiological association of OA with serum albumin and triglyceride-rich lipoproteins (TRL). UV absorption spectra showed conformational changes in serum albumin due to the formation of an adduct with OA. Additionally, we demonstrated that TRL incorporate OA, reaching a maximum concentration of 140 ng mL-1 after 2-4 hours. We conjecture that both are efficient carriers to reach target tissues and to yield high bioavailability.This research is part of the R+D+i project PID2019-107837RB-I00, funded by the Spanish Ministry of Science and Innovation/Spanish National Research Agency, grant number MCIN/AEI/10.13039/501100011033/. A. G.-G. is grateful for funding received from the “Next Generation EU” funds, the European Union through the Recovery, Transformation and Resilience Plan and by the Ministry of Universities, in the framework of the Margarita Salas, Maria Zambrano grants for the Requalification of the Spanish University System 2021–2023, organized by the Pablo de Olavide University, Seville. J. J. R.-M. obtained an Erasmus+ scholarship (No. 2021-1-IT02-KA131-HED-000008483) from the University of Sassari (ITALY), for a stay at the Department of Food and Health of the Instituto de la Grasa-CSIC. The authors especially thank the ACESUR Group (Dos Hermanas, Seville, Spain), which donated the commercial olive oil for the trial. This collaborator had no role in the design, collection, analysis or interpretation of the data or in the decision to submit the manuscript for publication.Peer reviewe

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe

Holobiont effect accounts for more methane emission variance than the additive and microbiome effects on dairy cattle

Rumen microbiota has been previously related to phenotypic complex traits of relevance in dairy cattle. The joint analysis of the host’s genetic background and its microbiota can be statistically modelled using similarity matrices between microorganism communities in the different hosts. Microbiota relationship matrices (K) enable considering the whole microbiota and the cumbersome interrelations between taxa, rather than analyzing single taxa one at the time. Several methods have been proposed to ordinate these matrices. The aim of this study was to compare the performance of twelve K built from different microbiome distance metrics, within a variance component estimation framework for methane concentration in dairy cattle. Phenotypic, genomic and rumen microbiome information from simulations (n = 1000) and real data (cows = 437) were analyzed. Four models were considered: an additive genomic model (GBLUP), a microbiome model (MBLUP), a genetic and microbiome effects model (HBLUP) and a genetic, microbiome and genetic × microbiome interaction effects model (HiBLUP). Results from simulation were obtained from 25 replicates. Results from simulated data suggested that Ks with flattened off-diagonal elements were more accurate in variance components estimation for all compared models that included Ks information (MBLUP, HBLUP and HiBLUP). Multidimensional scaling (MDS), redundancy analysis (RDA) and constrained correspondence analysis (CCA) performed better in simulation to estimate heritability and microbiability. The models including Ks from the MDS, RDA and CCA methods were also between the most plausible models in the real data set, according to the deviance information criteria (DIC). Real data was analyzed under the same framework as in the simulation. The most plausible model in real data was HiBLUP. Estimates variated depending on K; methane heritability (0.15–0.17) and microbiability (0.15–0.21) were lower than the proportion of the phenotypic variance attributable to the host-microbiome holobiont effect (0.42–0.59), which we have defined here as “holobiability”. The holobiability including the genomic × microbiome interaction from the HiBLUP was between 0.01 and 0.15 larger than the holobiability explained from the sum of the genetic and microbiome effects without interaction between them, from the HBLUP, depending on K.RTA2015-00022-C03 (METALGEN) project from the Spanish national plan of research, development, and innovation 2013-2020.UCR::Vicerrectoría de Docencia::Ciencias Agroalimentarias::Facultad de Ciencias Agroalimentarias::Escuela de ZootecniaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Centro de Investigación en Nutrición Animal (CINA

Rumen eukaryotes are the main phenotypic risk factors for larger methane emissions in dairy cattle

Mitigation of methane emissions from dairy cattle is a relevant strategy to reduce environmental impact from livestock as well as to increase farm profitability through improvement of energy usage. The objective of this study was to compare how microbiome composition determines methane concentration (MET) and methane intensity (MI, ppm CH4/kg Milk) with other traditional proxies (e.g. milk yield and conformation traits). A total of 1359 Holstein cows from 17 herds in 4 northern regions of Spain were included in this study. Microbiome data came from a subset of 437 cows from 14 herds. Cows were classified in quartiles for MET and MI, according to individual records of methane measurements during the cow’s visit to the automatic milking system unit. A probit approach under a Markov chain Monte Carlo (McMC) Bayesian framework was used to determine risk factors for high MET and high MI. Reducing MET and MI genetic merit by unit of standard deviation (SD) reduced the probability of being classified in the upper quartile by 35.2% (33.9% to 36.4%) and 28.8% (27.6% to 29.6%), respectively. Increasing the relative abundance of most bacteria reduced the probability of a cow to be classified as high emitter (e.g., Firmicutes 9.9% (8.3 to 11.3) for MET and 7.1% (6.2 to 8.2) for MI, per unit of SD). An opposite effect was observed for the relative abundance of Eukaryotes. Larger abundance of most eukaryote caused larger risk for a cow to be classified as a high emitter animal (e.g., Oomycetes 14.2% (11.7% to 16.4%) for MET and 11.8% (9.4% to 14.0%) for MI, per unit of SD). One more unit of milk yield SD increased the probability of being classified in the upper quartile for MET by 3.7% (2.3% to 4.2%) and reduced the probability for MI by 12.6% (12.2% to 13.3%). Structure and capacity traits were not main drivers of being classified in th higher quartile of methane emission and intensity, with risk odds lower than 2% per unit of SD. Cow genetic merit for methane concentration and her microbiome composition (86 phylum and 1240 genus) were the main drivers for a cow to be classified as high MET or MI. This study suggests that mitigation of MET and MI could be addressed through animal breeding programs including genetic merits and strategies that modulate the microbiome.This research was financed by RTA2015-00022-C03 (METALGEN) project from the national plan of research, development, and innovation 2013-2020.UCR::Vicerrectoría de Docencia::Ciencias Agroalimentarias::Facultad de Ciencias Agroalimentarias::Escuela de ZootecniaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Centro de Investigación en Nutrición Animal (CINA

Structural equation models to disentangle the biological relationship between microbiota and complex traits: Methane production in dairy cattle as a case of study

The advent of metagenomics in animal breeding poses the challenge of statistically modelling the relationship between the microbiome, the host genetics and relevant complex traits. A set of structural equation models (SEMs) of a recursive type within a Markov chain Monte Carlo (MCMC) framework was proposed here to jointly analyse the host–metagenome–phenotype relationship. A non‐recursive bivariate model was set as benchmark to compare the recursive model. The relative abundance of rumen microbes (RA), methane concentration (CH4) and the host genetics was used as a case of study. Data were from 337 Holstein cows from 12 herds in the north and north‐west of Spain. Microbial composition from each cow was obtained from whole metagenome sequencing of ruminal content samples using a MinION device from Oxford Nanopore Technologies. Methane concentration was measured with Guardian® NG infrared gas monitor from Edinburgh Sensors during cow's visits to the milking automated system. A quarterly average from the methane eructation peaks for each cow was computed and used as phenotype for CH4. Heritability of CH4 was estimated at 0.12 ± 0.01 in both the recursive and bivariate models. Likewise, heritability estimates for the relative abundance of the taxa overlapped between models and ranged between 0.08 and 0.48. Genetic correlations between the microbial composition and CH4 ranged from −0.76 to 0.65 in the non‐recursive bivariate model and from −0.68 to 0.69 in the recursive model. Regardless of the statistical model used, positive genetic correlations with methane were estimated consistently for the seven genera pertaining to the Ciliophora phylum, as well as for those genera belonging to the Euryarchaeota (Methanobrevibacter sp.), Chytridiomycota (Neocallimastix sp.) and Fibrobacteres (Fibrobacter sp.) phyla. These results suggest that rumen's whole metagenome recursively regulates methane emissions in dairy cows and that both CH4 and the microbiota compositions are partially controlled by the host genotype.National plan of research, development and innovation 2013‐2020, Grant/ Award Number: RTA2015‐0022‐CO3 (METALGEN)UCR::Vicerrectoría de Docencia::Ciencias Agroalimentarias::Facultad de Ciencias Agroalimentarias::Escuela de ZootecniaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Centro de Investigación en Nutrición Animal (CINA

Can genomics cope with a 30% reduction of methane emission from livestock in 10 years?

Livestock will face an important challenge within the next decade to cope with the objective of cut by 30% methane emissions, as agreed in the COP26. This study summarises the latest genetic parameter estimates between methane, dry matter intake, microbiota composition, and production and body traits in Spanish dairy cattle. We evaluated the expected genetic progress after including methane into the breeding goal under different scenarios. Under the current trend in the cow population size, it is only possible to achieve the objective if methane is included with a large weight in the selection index and it is accompanied of other strategies. This may generate conflict with dairy producers and balanced strategies must be considered.UCR::Vicerrectoría de Docencia::Ciencias Agroalimentarias::Facultad de Ciencias Agroalimentarias::Escuela de ZootecniaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Centro de Investigación en Nutrición Animal (CINA

Mitochondrial haplogroup H is related to CD4+ T cell recovery in HIV infected patients starting combination antiretroviral therapy

BACKGROUND: The mitochondrial DNA (mtDNA) seems to influence in a large number of diseases, including HIV infection. Moreover, there is a substantial inter-individual variability in the CD4+ recovery in HIV-infected patients on combination antiretroviral therapy (cART). Our study aimed to analyze the association between mtDNA haplogroups and CD4+ recovery in HIV-infected patients on cART. METHODS: This is a retrospective study of 324 naïve cART patients with CD4+  9.65 CD4+ cells/mm3/month) than patients without haplogroup H (p = 0.032). The adjusted logistic regression showed that patients carrying haplogroup H had a higher likelihood of achieving a CD4+ recovery > 9.65 CD4+ cells/mm3/month [adjusted odds ratio (aOR) = 1.75 (95% CI = 1.04; 2.95); p = 0.035]. CONCLUSIONS: European mitochondrial haplogroup H was associated with the improved CD4+ recovery in HIV-infected patients starting cART with CD4+ < 200 cells/mm3.This work has been (partially) funded by Grants RD12/0017/0024 and RD16CIII/0002/0002 to SR, and RD12/0017/0031 and RD16/0025/0013 to JMB as part of the Health Research and Development Strategy, State Plan for Scientific and Technical Research and Innovation (2008–2011; 2013–2016) and co-financed by Institute of Health Carlos III, ISCIII–Sub-Directorate General for Research Assessment and Promotion and European Regional Development Fund (ERDF). Luz Mª Medrano is supported by Spanish Carlos III Institute of Health (ISCIII) Madrid, Spain [Grant Number CD14/00002]. N Rallón is a Miguel Servet investigator from the ISCIII [Grant Number CP14/00198]; M. García is a predoctoral student co-funded by CP14/00198 Grant and Intramural Research Scholarship from IIS-FJD. The authors would like to thank the Spanish National Genotyping Center (CEGEN-PRB2-ISCIII) for providing SNP genotyping services (http://www.cegen.org). CEGEN is supported by grant PT13/0001, ISCIII-SGEFI/FEDER. We also acknowledge the patients in this study for their participation and the Centro de Transfusión of Comunidad de Madrid for the healthy donor blood samples provided. We acknowledge the Spanish HIV-1 BioBank integrated into the Spanish AIDS Research Network (RIS) and collaborating centers for the clinical samples provided. The HIV BioBank, integrated in the Spanish AIDS Research Network, is supported by ISCIII, Spanish Health Ministry (Grant nº RD06/0006/0035 and RD12/0017/0037) as part of the State Plan for Scientific and Technical Research and Innovation and co-financed by ISCIII–Sub-Directorate General for Research Assessment and Promotion and European Regional Development Fund (ERDF) and Foundation for Research and Prevention of AIDS in Spain (FIPSE). The RIS Cohort (CoRIS) is funded by the ISCIII through the Spanish AIDS Research Network (RISC03/173 and RD12/0017/0018) as part of the State Plan for Scientific and Technical Research and Innovation and co-financed by ISCIII–Sub-Directorate General for Research Assessment and Promotion and European Regional Development Fund (ERDF).S

Historia del conocimiento de los ammonites (moluscos fósiles) del Jurásico de España

La Paleontología como ciencia tiene su inicio con los trabajos de Georges Cuvier sobre anatomía comparada, la aceptación de los modelos actualistas geológicos de Charles Lyell y el paradigma evolucionista de Charles Darwin. Sin embargo, son escasas las aportaciones de naturalistas españoles a la historia de la paleontología. Con ocasión del tercer centenario del nacimiento del naturalista español José Torrubia (1698-1761) autor de uno de los primeros libros paleontológicos españoles (el Aparato para la Historia Natural Española) publicado en 1754, se presenta aquí una panorámica general de la historia del conocimiento e interpretación de uno de los grupos de organismos fósiles más interesantes de España: los Ammonites, moluscos exclusivamente fósiles del grupo de los cefalópodos