SLIC-Occ: functional segmentation of occupancy images improves precision of EC50 images
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ABSTRACT:
SUBMITTER: Ibrahimy A
PROVIDER: S-EPMC10713928 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
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Project description:Drug-receptor interaction theory predicts that proportional receptor occupancy is a function of ligand concentration as defined by a ligand-receptor affinity constant, and is independent of receptor density. However, we previously observed that the EC50 of 5-HT reduced as the density of 5-HT3 receptors increased, suggesting an effect of receptor density on occupancy. The current study was designed to maximise variability in experimentally observed currents and confirm this apparent contradiction prospectively. Xenopus oocytes were injected with RNA encoding 5-HT3A receptors under conditions designed to achieve varying receptor expression levels and 5-HT-evoked currents measured using two electrode voltage clamp. Results from 99 oocytes showed that as the maximal peak current increased from 0.05 µA to 12.1 µA there was a 3.7-fold reduction in EC50. Since occupancy and conductance are directly related in this system, this indicates that for a given concentration of 5-HT, proportional occupancy increases with increased receptor density. We conclude that normalising data masks this correlation, and can result in reduced accuracy of pharmacological measurements. We propose a mechanistic explanation for our observations.
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Project description:Multiplexed gene-signature-based phenotypic assays are increasingly used for the identification and profiling of small molecule-tool compounds and drugs. Here we introduce a method (provided as R-package) for the quantification of the dose-response potency of a gene-signature as EC50 and IC50 values. Two signaling pathways were used as models to validate our methods: beta-adrenergic agonistic activity on cAMP generation (dedicated dataset generated for this study) and EGFR inhibitory effect on cancer cell viability. In both cases, potencies derived from multi-gene expression data were highly correlated with orthogonal potencies derived from cAMP and cell growth readouts, and superior to potencies derived from single individual genes. Based on our results we propose gene-signature potencies as a novel valid alternative for the quantitative prioritization, optimization and development of novel drugs.
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Project description:Population size is one of the basic demographic parameters for species management and conservation. Among different estimation methods, spatially explicit capture-recapture (SCR) models allow the estimation of population density in a framework that has been greatly developed in recent years. The use of automated detection devices, such as camera traps, has impressively extended SCR studies for individually identifiable species. However, its application to unmarked/partially marked species remains challenging, and no specific method has been widely used. We fitted an SCR-integrated model (SCR-IM) to stone marten Martes foina data, a species for which only some individuals are individually recognizable by natural marks, and estimate population size based on integration of three submodels: (1) individual capture histories from live capture and transponder tagging; (2) detection/nondetection or "occupancy" data using camera traps in a bigger area to extend the geographic scope of capture-recapture data; and (3) telemetry data from a set of tagged individuals. We estimated a stone marten density of 0.352 (SD: 0.081) individuals/km2. We simulated four dilution scenarios of occupancy data to study the variation in the coefficient of variation in population size estimates. We also used simulations with similar characteristics as the stone marten case study, comparing the accuracy and precision obtained from SCR-IM and SCR, to understand how submodels' integration affects the posterior distributions of estimated parameters. Based on our simulations, we found that population size estimates using SCR-IM are more accurate and precise. In our stone marten case study, the SCR-IM density estimation increased the precision by 37% when compared to the standard SCR model as regards to the coefficient of variation. This model has high potential to be used for species in which individual recognition by natural markings is not possible, therefore limiting the need to rely on invasive sampling procedures.
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2011-11-23 | E-GEOD-33899 | biostudies-arrayexpress
Project description:Images and gpr files were examined using a novel saturation reduction method to determine whether accuracy could be improved by extending dynamic range of saturated pixels
2011-11-23 | GSE33899 | GEO
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Project description:Accurate segmentation and detection of rice seedlings is essential for precision agriculture and high-yield cultivation. However, current methods suffer from high computational complexity and poor robustness to different rice varieties and densities. This article proposes 2 lightweight neural network architectures, LW-Segnet and LW-Unet, for high-precision rice seedling segmentation. The networks adopt an encoder-decoder structure with hybrid lightweight convolutions and spatial pyramid dilated convolutions, achieving accurate segmentation while reducing model parameters. Multispectral imagery acquired by unmanned aerial vehicle (UAV) was used to train and test the models covering 3 rice varieties and different planting densities. Experimental results demonstrate that the proposed LW-Segnet and LW-Unet models achieve higher F1-scores and intersection over union values for seedling detection and row segmentation across varieties, indicating improved segmentation accuracy. Furthermore, the models exhibit stable performance when handling different varieties and densities, showing strong robustness. In terms of efficiency, the networks have lower graphics processing unit memory usage, complexity, and parameters but faster inference speeds, reflecting higher computational efficiency. In particular, the fast speed of LW-Unet indicates potential for real-time applications. The study presents lightweight yet effective neural network architectures for agricultural tasks. By handling multiple rice varieties and densities with high accuracy, efficiency, and robustness, the models show promise for use in edge devices and UAVs to assist precision farming and crop management. The findings provide valuable insights into designing lightweight deep learning models to tackle complex agricultural problems.
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Project description:BackgroundOxycodone can be used both intravenously and epidurally in elderly patients because of its strong analgesic effect and more slight respiratory inhibition compared with other opioids at the same effect. In this study, we determined the median effective concentration (EC50) of epidural ropivacaine required for great saphenous vein surgery in elderly patients in order to describe its pharmacodynamic interaction with oxycodone.MethodsOne hundred forty-one elderly patients scheduled for high ligation and stripping of the great saphenous vein surgery were allocated into three groups in a randomized, double-blinded manner as follows: Q2.5 group (2.5 mg oxycodone), Q5.0 group (5.0 mg oxycodone), and C group (normal saline). Anesthesia, was achieved with epidural ropivacaine and oxycodone. The EC50 of ropivacaine for surgery with different doses of oxycodone was adjusted by using an up-and-down sequential methods with an adjacent concentration gradient at a factor of 0.9 to inhibit analgesia. Anesthesia associated adverse events and recovery, characteristics were also recorded.ResultsThe EC50 of ropivacaine for the great saphenous vein surgery in elderly patients was 0.399% (95% CI, 0.371-0.430%) in the Q2.5 group, 0.396% (95% CI, 0.355-0.441%) in the Q5.0 group, and 0.487% (95% CI, 0.510-0.465%) in the C group, respectively (P < 0.05). Specially, the EC50 of ropivacaine in the Q2.5 and Q5.0 groups was lower than that in the C group (P < 0.01), But the difference between the Q2.5 group and the Q5.0 group was not significant (P > 0.05). There was no significant difference in the Bromage score from the motor block examination, heart rate (HR) or mean arterial pressure (MAP) at each observation time point after epidural administration among the three groups (P > 0.05). No serious adverse reactions occurred in any of the three groups.ConclusionOxycodone combined with ropivacaine epidural anesthesia can reduce the EC50 of ropivacaine required for elderly patients undergoing the great saphenous vein surgery. There was no significant difference in anesthesia associated adverse events among the three groups. The recommended dose of oxycodone is 2.5 mg.
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Project description:This paper presents a method for time-lapse 3D cell analysis. Specifically, we consider the problem of accurately localizing and quantitatively analyzing sub-cellular features, and for tracking individual cells from time-lapse 3D confocal cell image stacks. The heterogeneity of cells and the volume of multi-dimensional images presents a major challenge for fully automated analysis of morphogenesis and development of cells. This paper is motivated by the pavement cell growth process, and building a quantitative morphogenesis model. We propose a deep feature based segmentation method to accurately detect and label each cell region. An adjacency graph based method is used to extract sub-cellular features of the segmented cells. Finally, the robust graph based tracking algorithm using multiple cell features is proposed for associating cells at different time instances. We also demonstrate the generality of our tracking method on C. elegans fluorescent nuclei imagery. Extensive experiment results are provided and demonstrate the robustness of the proposed method. The code is available on GitHub and the method is available as a service through the BisQue portal.
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Project description:MotivationClassifying proteins into functional families can improve our understanding of protein function and can allow transferring annotations within one family. For this, functional families need to be 'pure', i.e., contain only proteins with identical function. Functional Families (FunFams) cluster proteins within CATH superfamilies into such groups of proteins sharing function. 11% of all FunFams (22 830 of 203 639) contain EC annotations and of those, 7% (1526 of 22 830) have inconsistent functional annotations.ResultsWe propose an approach to further cluster FunFams into functionally more consistent sub-families by encoding their sequences through embeddings. These embeddings originate from language models transferring knowledge gained from predicting missing amino acids in a sequence (ProtBERT) and have been further optimized to distinguish between proteins belonging to the same or a different CATH superfamily (PB-Tucker). Using distances between embeddings and DBSCAN to cluster FunFams and identify outliers, doubled the number of pure clusters per FunFam compared to random clustering. Our approach was not limited to FunFams but also succeeded on families created using sequence similarity alone. Complementing EC annotations, we observed similar results for binding annotations. Thus, we expect an increased purity also for other aspects of function. Our results can help generating FunFams; the resulting clusters with improved functional consistency allow more reliable inference of annotations. We expect this approach to succeed equally for any other grouping of proteins by their phenotypes.Availability and implementationCode and embeddings are available via GitHub: https://github.com/Rostlab/FunFamsClustering.Supplementary informationSupplementary data are available at Bioinformatics online.
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