Sample dilution and bacterial community composition influence empirical leucine-to-carbon conversion factors in surface waters of the world's oceans

Research articleThe transformation of leucine incorporation into prokaryotic carbon production rates requires the use of either theoretical or empirically determined conversion factors. Empirical leucine-to-carbon conversion factors (eCFs) vary widely across environments, and little is known about their potential controlling factors. We conducted 10 surface seawater manipulation experiments across the world’s oceans, where the growth of the natural prokaryotic assemblages was promoted by filtration (i.e. removal of grazers; F treatment) or filtration combined with dilution (i.e. relieving also resource competition; FD treatment). The impact of sunlight exposure was also evaluated in the FD treatments, and we did not find a significant effect on the eCFs. The eCFs varied from 0.09 to 1.47 kg C mol Leu-1 and were significantly lower in the filtered and diluted (FD) than in the filtered (F) treatments. Also, changes in bacterial community composition during the incubations, as assessed by Automated Ribosomal Intergenic Spacer Analysis (ARISA), were stronger in the FD than in the F treatments, as compared to unmanipulated controls. Thus, we discourage the common procedure of diluting samples (in addition to filtration) for eCFs determination. The eCFs in the filtered treatment were negatively correlated with the initial chlorophyll a concentration, picocyanobacterial abundance (mostly Prochlorococcus) and the percentage of heterotrophic prokaryotes with high nucleic acid content (%HNA). The latter two variables explained 80% of the eCFs variability in the F treatment, supporting the view that both Prochlorococcus and HNA prokaryotes incorporate leucine in substantial amounts although resulting into relatively low carbon production rates in the oligotrophic ocean.En prensa3,829

Empirical leucine-to-carbon conversion factors for estimating heterothrophic bacterial production in surface waters of the world oceans

Comunicación oralBacterial biomass production is a key parameter for evaluating the role of bacterioplankton in ocean carbon cycling. However, bacterial production cannot be directly measured and is typically estimated from the incorporation rates of radiolabelled leucine. The conversion of leucine uptake rates into bacterial carbon production rates requires the use of conversion factors (CFs) which must be empirically determined. Despite the empirical leucine-to-carbon CFs vary widely across environments very little is known about its potential controlling factors. We conducted a set of 10 surface seawater cultures experiments where the growth of the natural bacterial assemblage was promoted by filtration (removal of grazers) or by both filtration and dilution. Sampling stations were located between 30 ºN and 30 ºS, including the Atlantic, Pacific and Indian oceans. CFs varied from 0.13 to 1.47 Kg C mol Leu-1, being higher in the filtrated than in the filtrated and diluted treatment. The abundance of picocyanobacteria explained 60% of the observed variability. Our results further suggest that the composition of bacterioplankton, as assessed by ARISA fingerprinting, may partially explain the observed variation in CFs

Germline mutations in the spindle assembly checkpoint genes BUB1 and BUB3 are infrequent in familial colorectal cancer and polyposis

Germline mutations in BUB1 and BUB3 have been reported to increase the risk of developing colorectal cancer (CRC) at young age, in presence of variegated aneuploidy and reminiscent dysmorphic traits of mosaic variegated aneuploidy syndrome. We performed a mutational analysis of BUB1 and BUB3 in 456 uncharacterized mismatch repair-proficient hereditary non-polyposis CRC families and 88 polyposis cases. Four novel or rare germline variants, one splice-site and three missense, were identified in four families. Neither variegated aneuploidy nor dysmorphic traits were observed in carriers. Evident functional effects in the heterozygous form were observed for c.1965-1G>A, but not for c.2296G>A (p.E766K), in spite of the positive co-segregation in the family. BUB1 c.2473C>T (p.P825S) and BUB3 c.77C>T (p.T26I) remained as variants of uncertain significance. As of today, the rarity of functionally relevant mutations identified in familial and/or early onset series does not support the inclusion of BUB1 and BUB3 testing in routine genetic diagnostics of familial CRC

Toward an operative diagnosis in sepsis: a latent class approach

<p>Abstract</p> <p>Background</p> <p>Recent data have suggested that 18 million of new sepsis cases occur each year worldwide, with a mortality rate of almost 30%. There is not consensus on the clinical definition of sepsis and, because of lack of training or simply unawareness, clinicians often miss or delay this diagnosis. This is especially worrying; since there is strong evidence supporting that early treatment is associated with greater clinical success. There are some difficulties for sepsis diagnosis such as the lack of an appropriate gold standard to identify this clinical condition. This situation has hampered the assessment of the accuracy of clinical signs and biomarkers to diagnose sepsis.</p> <p>Methods/design</p> <p>Cross-sectional study to determine the operative characteristics of three biological markers of inflammation and coagulation (D-dimer, C-reactive protein and Procalcitonin) as diagnostic tests for sepsis, in patients admitted to hospital care with a presumptive infection as main diagnosis.</p> <p>Discussion</p> <p>There are alternative techniques that have been used to assess the accuracy of tests without gold standards, and they have been widely used in clinical disciplines such as psychiatry, even though they have not been tested in sepsis diagnosis. Considering the main importance of diagnosis as early as possible, we propose a latent class analysis to evaluate the accuracy of three biomarkers to diagnose sepsis.</p

Epidemiological trends of HIV/HCV coinfection in Spain, 2015-2019

Altres ajuts: Spanish AIDS Research Network; European Funding for Regional Development (FEDER).Objectives: We assessed the prevalence of anti-hepatitis C virus (HCV) antibodies and active HCV infection (HCV-RNA-positive) in people living with HIV (PLWH) in Spain in 2019 and compared the results with those of four similar studies performed during 2015-2018. Methods: The study was performed in 41 centres. Sample size was estimated for an accuracy of 1%. Patients were selected by random sampling with proportional allocation. Results: The reference population comprised 41 973 PLWH, and the sample size was 1325. HCV serostatus was known in 1316 PLWH (99.3%), of whom 376 (28.6%) were HCV antibody (Ab)-positive (78.7% were prior injection drug users); 29 were HCV-RNA-positive (2.2%). Of the 29 HCV-RNA-positive PLWH, infection was chronic in 24, it was acute/recent in one, and it was of unknown duration in four. Cirrhosis was present in 71 (5.4%) PLWH overall, three (10.3%) HCV-RNA-positive patients and 68 (23.4%) of those who cleared HCV after anti-HCV therapy (p = 0.04). The prevalence of anti-HCV antibodies decreased steadily from 37.7% in 2015 to 28.6% in 2019 (p < 0.001); the prevalence of active HCV infection decreased from 22.1% in 2015 to 2.2% in 2019 (p < 0.001). Uptake of anti-HCV treatment increased from 53.9% in 2015 to 95.0% in 2019 (p < 0.001). Conclusions: In Spain, the prevalence of active HCV infection among PLWH at the end of 2019 was 2.2%, i.e. 90.0% lower than in 2015. Increased exposure to DAAs was probably the main reason for this sharp reduction. Despite the high coverage of treatment with direct-acting antiviral agents, HCV-related cirrhosis remains significant in this population

Adverse maternal, fetal, and newborn outcomes among pregnant women with SARS-CoV-2 infection: an individual participant data meta-analysis.

INTRODUCTION Despite a growing body of research on the risks of SARS-CoV-2 infection during pregnancy, there is continued controversy given heterogeneity in the quality and design of published studies. METHODS We screened ongoing studies in our sequential, prospective meta-analysis. We pooled individual participant data to estimate the absolute and relative risk (RR) of adverse outcomes among pregnant women with SARS-CoV-2 infection, compared with confirmed negative pregnancies. We evaluated the risk of bias using a modified Newcastle-Ottawa Scale. RESULTS We screened 137 studies and included 12 studies in 12 countries involving 13 136 pregnant women.Pregnant women with SARS-CoV-2 infection-as compared with uninfected pregnant women-were at significantly increased risk of maternal mortality (10 studies; n=1490; RR 7.68, 95% CI 1.70 to 34.61); admission to intensive care unit (8 studies; n=6660; RR 3.81, 95% CI 2.03 to 7.17); receiving mechanical ventilation (7 studies; n=4887; RR 15.23, 95% CI 4.32 to 53.71); receiving any critical care (7 studies; n=4735; RR 5.48, 95% CI 2.57 to 11.72); and being diagnosed with pneumonia (6 studies; n=4573; RR 23.46, 95% CI 3.03 to 181.39) and thromboembolic disease (8 studies; n=5146; RR 5.50, 95% CI 1.12 to 27.12).Neonates born to women with SARS-CoV-2 infection were more likely to be admitted to a neonatal care unit after birth (7 studies; n=7637; RR 1.86, 95% CI 1.12 to 3.08); be born preterm (7 studies; n=6233; RR 1.71, 95% CI 1.28 to 2.29) or moderately preterm (7 studies; n=6071; RR 2.92, 95% CI 1.88 to 4.54); and to be born low birth weight (12 studies; n=11 930; RR 1.19, 95% CI 1.02 to 1.40). Infection was not linked to stillbirth. Studies were generally at low or moderate risk of bias. CONCLUSIONS This analysis indicates that SARS-CoV-2 infection at any time during pregnancy increases the risk of maternal death, severe maternal morbidities and neonatal morbidity, but not stillbirth or intrauterine growth restriction. As more data become available, we will update these findings per the published protocol

A global phylogeny of butterflies reveals their evolutionary history, ancestral hosts and biogeographic origins

Butterflies are a diverse and charismatic insect group that are thought to have evolved with plants and dispersed throughout the world in response to key geological events. However, these hypotheses have not been extensively tested because a comprehensive phylogenetic framework and datasets for butterfly larval hosts and global distributions are lacking. We sequenced 391 genes from nearly 2,300 butterfly species, sampled from 90 countries and 28 specimen collections, to reconstruct a new phylogenomic tree of butterflies representing 92% of all genera. Our phylogeny has strong support for nearly all nodes and demonstrates that at least 36 butterfly tribes require reclassification. Divergence time analyses imply an origin similar to 100 million years ago for butterflies and indicate that all but one family were present before the K/Pg extinction event. We aggregated larval host datasets and global distribution records and found that butterflies are likely to have first fed on Fabaceae and originated in what is now the Americas. Soon after the Cretaceous Thermal Maximum, butterflies crossed Beringia and diversified in the Palaeotropics. Our results also reveal that most butterfly species are specialists that feed on only one larval host plant family. However, generalist butterflies that consume two or more plant families usually feed on closely related plants

Iodine Atoms: A New Molecular Feature for the Design of Potent Transthyretin Fibrillogenesis Inhibitors

The thyroid hormone and retinol transporter protein known as transthyretin (TTR) is in the origin of one of the 20 or so known amyloid diseases. TTR self assembles as a homotetramer leaving a central hydrophobic channel with two symmetrical binding sites. The aggregation pathway of TTR into amiloid fibrils is not yet well characterized but in vitro binding of thyroid hormones and other small organic molecules to TTR binding channel results in tetramer stabilization which prevents amyloid formation in an extent which is proportional to the binding constant. Up to now, TTR aggregation inhibitors have been designed looking at various structural features of this binding channel others than its ability to host iodine atoms. In the present work, greatly improved inhibitors have been designed and tested by taking into account that thyroid hormones are unique in human biochemistry owing to the presence of multiple iodine atoms in their molecules which are probed to interact with specific halogen binding domains sitting at the TTR binding channel. The new TTR fibrillogenesis inhibitors are based on the diflunisal core structure because diflunisal is a registered salicylate drug with NSAID activity now undergoing clinical trials for TTR amyloid diseases. Biochemical and biophysical evidence confirms that iodine atoms can be an important design feature in the search for candidate drugs for TTR related amyloidosis

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

BACKGROUND: Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them.RESULTS:A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89 and the best AUC iP/R was 68. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35) the macro-averaged precision ranged between 50 and 80, with a maximum F-Score of 55. CONCLUSIONS: The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows