Retinol (RO) and its active metabolite retinoic acid (RA) are major regulators of gene expression in vertebrates and influence various processes like organ development, cell differentiation, and immune response. To characterize a general transcriptomic response to RA-exposure in vertebrates, independent of species- and tissue-specific effects, four publicly available RNA-Seq datasets from Homo sapiens, Mus musculus, and Xenopus laevis were analyzed. To increase species and cell-type diversity we generated RNA-seq data with chicken hepatocellular carcinoma (LMH) cells. Additionally, we compared the response of LMH cells to RA and RO at different time points.
By conducting a transcriptome meta-analysis, we identified three retinoic acid response core clusters (RARCCs) consisting of 27 interacting proteins, seven of which have not been associated with retinoids yet. Comparison of the transcriptional response of LMH cells to RO and RA exposure at different time points led to the identification of non-coding RNAs (ncRNAs) that are only differentially expressed (DE) during the early response.
We propose that these RARCCs stand on top of a common regulatory RA hierarchy among vertebrates. Based on the protein sets included in these clusters we were able to identify an RA-response cluster, a control center type cluster, and a cluster that directs cell proliferation. Concerning the comparison of the cellular response to RA and RO we conclude that ncRNAs play an underestimated role in retinoid-mediated gene regulation.
We propose that these RARCCs stand on top of a common regulatory RA hierarchy among vertebrates. Based on the protein sets included in these clusters we were able to identify an RA-response cluster, a control center type cluster, and a cluster that directs cell proliferation. Concerning the comparison of the cellular response to RA and RO we conclude that ncRNAs play an underestimated role in retinoid-mediated gene regulation.
Deep learning contributes to uncovering molecular and cellular processes with highly performant algorithms. Convolutional neural networks have become the state-of-the-art tool to provide accurate and fast imagedata processing. However, published algorithms mostly solve only one specific problem and they typically requirea considerable coding effort and machine learning background for their application.
We have thus developed InstantDL,a deep learning pipeline for four common image processing tasks semantic segmentation, instance segmentation, pixel-wise regression and classification. InstantDL enables researchers with a basic computational background to apply debugged and benchmarked state-of-the-art deep learning algorithms to their own data with minimal effort. To make the pipeline robust, we have automated and standardized workflows and extensively tested it in different scenarios. Moreover, it allows assessing the uncertainty of predictions. We have benchmarked InstantDL on seven publicly available datasets achieving competitive performance without any parameter tuning. For customization of the pipeline to specific tasks, all code is easily accessible and well documented.
With InstantDL, we hope to empower biomedical researchers to conduct reproducible image processing with a convenient and easy-to-use pipeline.
With InstantDL, we hope to empower biomedical researchers to conduct reproducible image processing with a convenient and easy-to-use pipeline.
In spite of disrupted repolarization of diabetic heart, some studies report less tendency of diabetic heart to develop ventricular arrhythmias suggesting effective compensatory mechanism. Selleck VO-Ohpic We hypothesized that myocardial alterations in HCN2 and HCN4 channels occur under hyperglycaemia.
Diabetes was induced in rats using a single injection of streptozotocin (STZ; 55mg/kg body weight, i.p.). Basal ECG was measured. Expression of mRNA for HCN channels, potassium channels and microRNA 1 and 133a were measured in ventricular tissues. Protein expression of HCN2 channel isoform was assessed in five different regions of the heart by western blotting. Differentiated H9c2 cell line was used to examine HCN channels expression under hyperglycaemia in vitro.
Six weeks after STZ administration, heart rate was reduced, QRS complex duration, QT interval and T-wave were prolonged in diabetic rats compared to controls. mRNA and protein expressions of HCN2 decreased exclusively in the ventricles of diabetic rats. HCN2 expression levels in atria of STZ rats and H9c2 cells treated with excess of glucose were not changed. MicroRNA levels were stable in STZ rat hearts. We found significantly decreased mRNA levels of several potassium channels participating in repolarization, namely Kcnd2 (I
), Kcnh2 (I
), Kcnq1 (I
) and Kcnj11 (I
).
This result together with downregulated HCN2 channels suggest that HCN channels might be an integral part of ventricular electric remodelling and might play a role in cardiac repolarization projected in altered arrhythmogenic profile of diabetic heart.
This result together with downregulated HCN2 channels suggest that HCN channels might be an integral part of ventricular electric remodelling and might play a role in cardiac repolarization projected in altered arrhythmogenic profile of diabetic heart.
Few studies have evaluated muscle strength in COVID-19 ICU survivors. We aimed to report the incidence of limb and respiratory muscle weakness in COVID-19 ICU survivors.
We performed a cross sectional study in two ICU tertiary Hospital Settings. COVID-19 ICU survivors were screened and respiratory and limb muscle strength were measured at the time of extubation. An ICU mobility scale was performed at ICU discharge and walking capacity was self-evaluated by patients 30 days after weaning from mechanical ventilation.
Twenty-three patients were included. Sixteen (69%) had limb muscle weakness and 6 (26%) had overlap limb and respiratory muscle weakness. Amount of physiotherapy was not associated with muscle strength. 44% of patients with limb weakness were unable to walk 100 m 30 days after weaning.
The large majority of COVID-19 ICU survivors developed ICU acquired limb muscle weakness. 44% of patients with limb weakness still had severely limited function one-month post weaning.
The large majority of COVID-19 ICU survivors developed ICU acquired limb muscle weakness.Selleck VO-Ohpic
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