DeepSpot: A deep neural network for RNA spot enhancement in single-molecule fluorescence in-situ hybridization microscopy images.

Detection of RNA spots in single-molecule fluorescence in-situ hybridization microscopy images remains a difficult task, especially when applied to large volumes of data. The variable intensity of RNA spots combined with the high noise level of the images often requires manual adjustment of the spot detection thresholds for each image. In this work, we introduce DeepSpot, a Deep Learning-based tool specifically designed for RNA spot enhancement that enables spot detection without the need to resort to image per image parameter tuning. We show how our method can enable downstream accurate spot detection. DeepSpot's architecture is inspired by small object detection approaches. It incorporates dilated convolutions into a module specifically designed for context aggregation for small object and uses Residual Convolutions to propagate this information along the network. This enables DeepSpot to enhance all RNA spots to the same intensity, and thus circumvents the need for parameter tuning. We evaluated how easily spots can be detected in images enhanced with our method by testing DeepSpot on 20 simulated and 3 experimental datasets, and showed that accuracy of more than 97% is achieved. Moreover, comparison with alternative deep learning approaches for mRNA spot detection (deepBlink) indicated that DeepSpot provides more precise mRNA detection. In addition, we generated single-molecule fluorescence in-situ hybridization images of mouse fibroblasts in a wound healing assay to evaluate whether DeepSpot enhancement can enable seamless mRNA spot detection and thus streamline studies of localized mRNA expression in cells.

Interrogating RNA and protein spatial subcellular distribution in smFISH data with DypFISH.

Advances in single-cell RNA sequencing have allowed for the identification of cellular subtypes on the basis of quantification of the number of transcripts in each cell. However, cells might also differ in the spatial distribution of molecules, including RNAs. Here, we present DypFISH, an approach to quantitatively investigate the subcellular localization of RNA and protein. We introduce a range of analytical techniques to interrogate single-molecule RNA fluorescence in situ hybridization (smFISH) data in combination with protein immunolabeling. DypFISH is suited to study patterns of clustering of molecules, the association of mRNA-protein subcellular localization with microtubule organizing center orientation, and interdependence of mRNA-protein spatial distributions. We showcase how our analytical tools can achieve biological insights by utilizing cell micropatterning to constrain cellular architecture, which leads to reduction in subcellular mRNA distribution variation, allowing for the characterization of their localization patterns. Furthermore, we show that our method can be applied to physiological systems such as skeletal muscle fibers.

The BEST study--a prospective study to compare business class versus economy class air travel as a cause of thrombosis.

BACKGROUND: As many as 10% of airline passengers travelling without prophylaxis for long distances may develop a venous thrombosis. There is, however, no evidence that economy class travellers are at increased risk of thrombosis. OBJECTIVES: A suitably powered prospective study, based on the incidence of deep-vein thrombosis (DVT) reported in previous studies on long-haul flights, was designed to determine the incidence of positive venous duplex scans and D-dimer elevations in low and intermediate-risk passengers, comparing passengers travelling in business and economy class. PATIENTS/METHODS: Eight hundred and ninety-nine passengers were recruited (180 travelling business class and 719 travelling economy). D-dimers were measured before and after the flight. A value greater than 500 ng/ml was accepted as abnormal. A thrombophilia screen was conducted which included the factor V Leiden mutation, the prothombin 20210A mutation, protein C and S levels, antithrombin levels, and anticardiolipin antibodies immunoglobulin G (IgG) and immunoglobulin M (IgM). On arrival, lower limb compression ultrasonography of the deep veins was performed. Logistical regression analysis was used to determine the risk factors related to abnormally high D-dimer levels. RESULTS: Only 434 subjects had a full venous duplex scan performed. None had ultrasonic evidence of venous thrombosis. Nine passengers tested at departure had elevated D-dimer levels and these volunteers were excluded from further study. Seventy-four of the 899 passengers had raised D-dimers on arrival. Twenty-two of 180 business class passengers (12%) developed elevated D-dimers compared with 52 of 719 economy class passengers (7%). There was no significant association between elevation of D-dimers and the class flown (odds ratio (OR) 0.61, p = 0.109). The factor V Leiden mutation, factor VIII levels and the use of aspirin were, however, associated with raised D-dimers (OR 3.36, p = 0.024; OR 1.01, p = 0.014; and OR 2.04, p = 0.038, respectively). Five hundred and five passengers were contacted within 6 months and none reported any symptoms of a clinical thrombosis or pulmonary embolus. CONCLUSION: The incidence of ultrasonically proven DVT is much lower than previously reported. However, more than 10% of all passengers developed raised D-dimers, which were unrelated to the class flown. A rise in D-dimers is associated with an inherent risk of thrombosis and/or thrombophilia, demonstrates activation of both the coagulation and fibrinolytic systems during long-haul flights, and may indicate the development of small thrombi.