Finkbyers4031

Under normal and constant light rhythms, electrical stimulation of SCG increased DβH and decreased the cross-sectional area and circumference of SC, while simultaneously increasing IOP and decreasing IOP fluctuations. After paralyzing the ciliary muscles, electrical stimulation of SCG decreased the cross-sectional area and circumference of SC under normal and constant light rhythms.

N-Dark increased DβH in SCE cells, reduced the cross-sectional area of SC, and increased IOP. Under the normal and light rhythms, electrical stimulation of SCG increased DβH in SCE cells, reduced the cross-sectional area and circumference of SC, and in turn elevated IOP and decreased IOP fluctuations.

N-Dark increased DβH in SCE cells, reduced the cross-sectional area of SC, and increased IOP. Under the normal and light rhythms, electrical stimulation of SCG increased DβH in SCE cells, reduced the cross-sectional area and circumference of SC, and in turn elevated IOP and decreased IOP fluctuations.Interactions between biological entities are key to understanding their potential functional roles. Three fields of research have recently made particular progress the investigation of transRNA-RNA and RNA-DNA transcriptome interactions and of trans DNA-DNA genome interactions. We now have both experimental and computational methods for examining these interactions in vivo and on a transcriptome- and genome-wide scale, respectively. Often, key insights can be gained by visually inspecting figures that manage to combine different sources of evidence and quantitative information. We here present R-chie, a web server and R package for visualizing cis and transRNA-RNA, RNA-DNA and DNA-DNA interactions. For this, we have completely revised and significantly extended an earlier version of R-chie (1) which was initially introduced for visualizing RNA secondary structure features. The new R-chie offers a range of unique features for visualizing cis and transRNA-RNA, RNA-DNA and DNA-DNA interactions. Particularly note-worthy features include the ability to incorporate evolutionary information, e.g. multiple-sequence alignments, to compare two alternative sets of information and to incorporate detailed, quantitative information. R-chie is readily available via a web server as well as a corresponding R package called R4RNA which can be used to run the software locally.

Heart failure is the main threat to long-term health in adults with transposition of the great arteries(TGA) corrected by an atrial switch operation(AtrSO). Current guidelines refrain from recommending heart failure medication in TGA-AtrSO, as there is insufficient data to support the hypothesis that it is beneficial. Medication is therefore prescribed based on personal judgements. We aimed to evaluate medication use in TGA-AtrSO patients and examine the association of use of Renin-Angiotension-Aldosteron System(RAAS) inhibitors and β-blockers with long-term survival.

We identified 150 TGA-AtrSO patients(median age 30 years[IQR 25-35], 63% male) included in the CONCOR registry from five tertiary medical centers with subsequent linkage to the Dutch Dispensed Drug Register for the years 2006-2014. Use of RAAS inhibitors, β-blockers, and diuretics increased with age, from respectively 21%[95%CI 14-40], 12%[95%CI 7-21], and 3%[95%CI 2-7] at age 25, to 49%[95%CI 38-60], 51%[95%CI 38-63], and 41%[95%CI 29-54] asymptomatic patients only. These findings can direct future guidelines, supporting use of RAAS inhibitors and β-blockers in symptomatic, but not asymptomatic patients.

With the rapid increase of biomedical articles, large-scale automatic Medical Subject Headings (MeSH) indexing has become increasingly important. FullMeSH, the only method for large-scale MeSH indexing with full text, suffers from three major drawbacks FullMeSH 1) uses Learning To Rank (LTR), which is time-consuming, 2) can capture some pre-defined sections only in full text, and 3) ignores the whole MEDLINE database.

We propose a computationally lighter, full-text and deep learning based MeSH indexing method, BERTMeSH, which is flexible for section organization in full text. BERTMeSH has two technologies 1) the state-of-the-art pre-trained deep contextual representation, BERT (Bidirectional Encoder Representations from Transformers), which makes BERTMeSH capture deep semantics of full text. 2) a transfer learning strategy for using both full text in PubMed Central (PMC) and title and abstract (only and no full text) in MEDLINE, to take advantages of both. In our experiments, BERTMeSH was pre-trained with 3 million MEDLINE citations and trained on approximately 1.5 million full text in PMC. BERTMeSH outperformed various cutting edge baselines. For example, for 20K test articles of PMC, BERTMeSH achieved a Micro F-measure of 69.2%, which was 6.3% higher than FullMeSH with the difference being statistically significant. Also prediction of 20K test articles needed 5 minutes by BERTMeSH, while it took more than 10 hours by FullMeSH, proving the computational efficiency of BERTMeSH.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.The human placenta is a dynamic organ that modulates physiological adaptations to pregnancy. To define the immunological signature of the human placenta, we performed unbiased profiling of secreted immune factors from human chorionic villi isolated from placentas at mid and late stages of pregnancy. We show that placental trophoblasts constitutively secrete the inflammasome-associated cytokines IL-1β and IL-18, which is blocked by NLRP3 inflammasome inhibitors and occurs without detectable gasdermin D cleavage. We further show that placenta-derived IL-1β primes monocytes for inflammasome induction to protect against Listeria monocytogenes infection. check details Last, we show that the human placenta responds to L. monocytogenes infection through additional inflammasome activation and that inhibition of this pathway sensitizes villi to infection. Our results thus identify the inflammasome as an important mechanism by which the human placenta regulates systemic and local immunity during pregnancy to defend against L. monocytogenes infection.