scholarly journals Australian tidal currents – assessment of a barotropic model (COMPAS v1.3.0 rev6631) with an unstructured grid

2021 ◽  
Author(s):  
David Anthony Griffin ◽  
Mike Herzfeld ◽  
Mark Hemer ◽  
Darren Engwirda
Keyword(s):  
Tidal Current ◽  
Unstructured Grid ◽  
Tide Gauge ◽  
Tidal Currents ◽  
Practical Significance ◽  
Tidal Range ◽  
Validation Dataset ◽  
Validation Data ◽  
Data Set ◽  
Velocity Amplitude

Abstract. While the variations of tidal range are large and fairly well known across Australia (less than 1 m near Perth but more than 14 m in King Sound), the properties of the tidal currents are not. We describe a new regional model of Australian tides and assess it against a validation dataset comprising tidal height and velocity constituents at 615 tide gauge sites and 95 current meter sites. The model is a barotropic implementation of COMPAS, an unstructured-grid primitive-equation model that is forced at the open boundaries by TPXO9v1. The Mean Absolute value of the Error (MAE) of the modelled M2 height amplitude is 8.8 cm, or 12 % of the 73 cm mean observed amplitude. The MAE of phase (10°), however, is significant, so the M2 Mean Magnitude of Vector Error (MMVE, 18.2 cm) is significantly greater. The Root Sum Square over the 8 major constituents is 26 % of the observed amplitude. We conclude that while the model has skill at height in all regions, there is definitely room for improvement (especially at some specific locations). For the M2 major-axis velocity amplitude, the MAE across the 95 current meter sites, where the observed amplitude ranges from 0.1 cm s−1 to 156 cm s−1, is 6.9 cm s−1, or 22 % of the 31.7 cm s−1 observed mean. This nationwide average result is encouraging, but it conceals a very large regional variation. Relative errors of the tidal current amplitudes on the narrow shelves of NSW and Western Australia exceed 100 %, but tidal currents are weak and negligible there compared to non-tidal currents, so the tidal errors are of little practical significance. Looking nation-wide, we show that the model has predictive value for much of the 79 % of Australia’s shelf seas where tides are a major component of the total velocity variability. In descending order this includes the Bass Strait, Kimberley to Arnhem Land and Southern Great Barrier Reef regions. There is limited observational evidence to confirm that the model is also valuable for currents in other regions across northern Australia. We plan to commence publishing ‘unofficial’ tidal current predictions for chosen regions in the near future, based on both our COMPAS model and the validation data set we have assembled.

scholarly journals Australian tidal currents – assessment of a barotropic model (COMPAS v1.3.0 rev6631) with an unstructured grid

2021 ◽  
Vol 14 (9) ◽  
pp. 5561-5582
Author(s):  
David A. Griffin ◽  
Mike Herzfeld ◽  
Mark Hemer ◽  
Darren Engwirda
Keyword(s):  
Tidal Current ◽  
Unstructured Grid ◽  
Tide Gauge ◽  
Major Axis ◽  
Absolute Error ◽  
Tidal Currents ◽  
Practical Significance ◽  
Tidal Range ◽  
Validation Dataset ◽  
Velocity Amplitude

Abstract. While the variations of tidal range are large and fairly well known across Australia (less than 1 m near Perth but more than 14 m in King Sound), the properties of the tidal currents are not. We describe a new regional model of Australian tides and assess it against a validation dataset comprising tidal height and velocity constituents at 615 tide gauge sites and 95 current meter sites. The model is a barotropic implementation of COMPAS, an unstructured-grid primitive-equation model that is forced at the open boundaries by TPXO9v1. The mean absolute error (MAE) of the modelled M2 height amplitude is 8.8 cm, or 12 % of the 73 cm mean observed amplitude. The MAE of phase (10∘), however, is significant, so the M2 mean magnitude of vector error (MMVE, 18.2 cm) is significantly greater. The root sum square over the eight major constituents is 26 % of the observed amplitude. We conclude that while the model has skill at height in all regions, there is definitely room for improvement (especially at some specific locations). For the M2 major axis velocity amplitude, the MAE across the 95 current meter sites, where the observed amplitude ranges from 0.1 to 156 cm s−1, is 6.9 cm s−1, or 22 % of the 31.7 cm s−1 observed mean. This nationwide average result is encouraging, but it conceals a very large regional variation. Relative errors of the tidal current amplitudes on the narrow shelves of New South Wales (NSW) and Western Australia exceed 100 %, but tidal currents are weak and negligible there compared to non-tidal currents, so the tidal errors are of little practical significance. Looking nationwide, we show that the model has predictive value for much of the 79 % of Australia's shelf seas where tides are a major component of the total velocity variability. In descending order this includes the Bass Strait, the Kimberley to Arnhem Land, and southern Great Barrier Reef regions. There is limited observational evidence to confirm that the model is also valuable for currents in other regions across northern Australia. We plan to commence publishing “unofficial” tidal current predictions for chosen regions in the near future based on both our COMPAS model and the validation dataset we have assembled.

scholarly journals Australian tidal currents – assessment of a barotropic model with an unstructured grid

2020 ◽  
Author(s):  
David A. Griffin ◽  
Mike Herzfeld ◽  
Mark Hemer
Keyword(s):  
Unstructured Grid ◽  
Tide Gauge ◽  
Major Axis ◽  
Equation Model ◽  
Tidal Currents ◽  
Tidal Range ◽  
Validation Dataset ◽  
Velocity Amplitude ◽  
Shelf Seas ◽  
Relative Errors

Abstract. While the variations of tidal range are large and fairly well known across Australia (less than 1 m near Perth but more than 14 m in King Sound), the properties of the tidal currents are not. We describe a new regional model of Australian tides and assess it against a validation dataset comprising tidal height and velocity constituents at 615 tide gauge sites and 95 current meter sites. The model is a barotropic implementation of COMPAS, an unstructured-grid primitive-equation model that is forced at the open boundaries by TPXO9v1. The Mean Absolute value of the Error (MAE) of the modelled M2 height amplitude is 9.3 cm, or 13 % of the 73 cm mean observed amplitude. The MAE of phase (11°), however, is significant, so the M2 Mean Magnitude of Vector Error (MMVE, 20 cm) is significantly greater. Results for 5 other major constituents are similar. We conclude that while the model has skill at height in all regions, there is definitely room for improvement (especially at some specific locations) before harmonic predictions based on observations are rendered obsolete. For the M2 major-axis velocity amplitude, the MAE across the 95 current meter sites, where the observed amplitude ranges from 0.1 cm s−1 to 144 cm s−1, is 6.5 cm s−1, or 20 % of the 31.7 cm s−1 observed mean. This nationwide average result is not much greater than the equivalent for height, but it conceals a larger regional variation. Relative errors on the narrow shelves of NSW and Western Australia exceed 100 %, but tidal currents are weak and negligible there compared to non-tidal currents. We show that the model has predictive value for much of the 79 % of Australia's shelf seas where tides are a major component of the total velocity variability. In descending order this includes the Bass Strait, Kimberley to Arnhem Land and Southern Great Barrier Reef regions. There is limited evidence the model is also valuable for currents in other regions across northern Australia. We plan to commence publishing unofficial tidal current predictions for chosen regions in the near future, based on both the limited number of observations, and the COMPAS model.

scholarly journals Development of a Risk Score for Prediction of Overall Survival Following Umbilical Cord Blood Transplantation in Acute Leukemia Patients: A Study from the Acute Leukemia Working Party (WP) and Paediatric Disease WP of the European Society for Blood and Marrow Transplantation (EBMT), and Eurocord

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1169-1169
Author(s):  
Roni Shouval ◽  
Annalisa Ruggeri ◽  
Myriam Labopin ◽  
Mohamad Mohty ◽  
Guillermo Sanz ◽  
...  
Keyword(s):  
Overall Survival ◽  
Acute Leukemia ◽  
Cord Blood ◽  
Risk Score ◽  
Research Funding ◽  
Validation Dataset ◽  
Validation Data ◽  
Data Set ◽  
Validation Set ◽  
Score Table

Abstract Background: Prognostic scoring systems for allogeneic stem cell transplantation (HSCT) are of clinical value when determining a leukemic patient's suitability for this curative, but risky, procedure. Several such scores have been developed over the years for HSCT from sibling or unrelated donors, but no predictive score has been developed specifically for umbilical cord blood transplantation (UCBT). Although individual parameters have been identified to be associated with UCBT outcomes in acute leukemia (AL) patients, integrative tools for risk evaluation in this setting are lacking. We sought to develop a prediction model for overall survival (OS) (primary objective) and leukemia free survival (LFS) (secondary objective) at 2 years following UCBT in acute leukemia patients. Methods: A retrospective, international registry-based study, of 3140 acute leukemia patients who underwent UCBT from 2004 through 2014. Inclusion criteria were patients with AL receiving single or double cord blood units transplantation. Median follow up was 30 months. The dataset was geographically split into a derivation (65%) and validation set (35%). A Random Survival Forest was utilized to identify predictive factors. Top predictors were introduced into a Cox regression model, and a risk score was constructed according to each variable's hazard. Results: The median age at UCBT was 21.9 years. The 2 years OS rate was 47.7% (95% CI: 45.8-49.6). After identifying the top predictive variables, the UCBT risk score (Table 1) was constructed using 9 variables (disease status, diagnosis, cryopreserved cell dose, age, center experience, recipient cytomegalovirus sero-status, degree of HLA mismatch, previous autograft and anti thymocyte globulin administration). Over the derivation and validation datasets, a higher score was associated with decreasing probabilities for 2 years OS and LFS, ranging over the validation set from 0.72 (0.64-0.8, 95% CI) and 0.68 (0.6-0.76, 95% CI) to 0.13 (0.06-0.27, 95% CI) and 0.14 (0.07-0.28, 95% CI), respectively (Figure 1). An increasing score was also associated with increasing hazard of the predictive outcomes (Table 2). The score's discrimination (AUC) over the validation set for 2 years OS and LFS was 68.26 (64.25-72.27, 95% CI) and 66.95 (62.88-71.02, 95% CI), respectively. Calibration was excellent. Conclusion: We have developed the first integrative score for prediction of overall survival and leukemia free survival in acute leukemia patients undergoing a UCBT. The score is simple and stratifies patients into distinct risk groups. Table 1 The UCBT Risk Score Table 1. The UCBT Risk Score Table 2 Association between the UCBT risk score and 2 years OS and LFS over the validation dataset Table 2. Association between the UCBT risk score and 2 years OS and LFS over the validation dataset Figure 1 Overall survival stratified by the UCBT risk score over the validation data set Figure 1. Overall survival stratified by the UCBT risk score over the validation data set Disclosures Bader: Servier: Consultancy, Honoraria; Neovii Biotech: Research Funding; Riemser: Research Funding; Medac: Consultancy, Research Funding; Novartis: Consultancy, Honoraria.

scholarly journals A Study on the Response of the Hydrodynamic Environment to the Morphology of Radial Sand Ridges in the Coastal Waters of Jiangsu

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2190
Author(s):  
Changjun Qi ◽  
Lejun Ma ◽  
Qinggai Wang ◽  
Yuan Zhai ◽  
Jixuan Li ◽  
...  
Keyword(s):  
Tidal Current ◽  
Unstructured Grid ◽  
Tidal Currents ◽  
Current Data ◽  
Material Transport ◽  
Current Field ◽  
Sand Ridges ◽  
Radial Sand Ridges ◽  
Local Current ◽  
Hydrodynamic Environment

A two-dimensional hydrodynamic model for the waters off the coast of Jiangsu, where there are radial sand ridges (RSRs) (hereinafter, the RSR area), was established based on measured topographic, tide level and tidal current data. Considering the complex topographic and geomorphic characteristics of the RSR group in this area, an unstructured grid was used for the calculation. A four-layer refinement was applied to the grid from outside to inside to better fit the complex topography. The simulations were performed to examine the response of the hydrodynamic environment to the morphology of the RSRs in three scenarios, namely, when there are natural RSRs, no RSRs, and partially reclaimed RSRs. When there are no or partially reclaimed RSRs, the tidal current field still exists in a radial pattern in the RSR area. The radial tidal current field is relatively stable and is not controlled by the morphologies of the RSRs. The topographic changes do not alter the distribution pattern of the radial tidal current field but do affect the local current fields. When there are no RSRs, the flood currents can directly reach Jianggang. Under practical conditions, the RSRs block the tidal currents during a flood tide to some extent. This phenomenon is particularly pronounced when the RSRs are partially reclaimed. For example, during an ebb tide, when the tidal currents encounter sand ridges or reclamation areas, their streamlines bend, and they flow around the obstacles. This change will affect the material transport, sediment deposition and seabed erosion.

scholarly journals A logistic regression model for predicting the occurrence of intense geomagnetic storms

2005 ◽  
Vol 23 (9) ◽  
pp. 2969-2974 ◽  
Author(s):  
N. Srivastava
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Geomagnetic Storms ◽  
Training Data ◽  
Validation Dataset ◽  
Model Parameters ◽  
Validation Data ◽  
Data Set ◽  
Logistic Regression Models

Abstract. A logistic regression model is implemented for predicting the occurrence of intense/super-intense geomagnetic storms. A binary dependent variable, indicating the occurrence of intense/super-intense geomagnetic storms, is regressed against a series of independent model variables that define a number of solar and interplanetary properties of geo-effective CMEs. The model parameters (regression coefficients) are estimated from a training data set which was extracted from a dataset of 64 geo-effective CMEs observed during 1996-2002. The trained model is validated by predicting the occurrence of geomagnetic storms from a validation dataset, also extracted from the same data set of 64 geo-effective CMEs, recorded during 1996-2002, but not used for training the model. The model predicts 78% of the geomagnetic storms from the validation data set. In addition, the model predicts 85% of the geomagnetic storms from the training data set. These results indicate that logistic regression models can be effectively used for predicting the occurrence of intense geomagnetic storms from a set of solar and interplanetary factors.

scholarly journals Demonstrating the Potential of Low-Cost GPS Units for the Remote Measurement of Tides and Water Levels Using Interferometric Reflectometry

2020 ◽  
Vol 37 (10) ◽  
pp. 1925-1935 ◽  
Author(s):  
Simon D. P. Williams ◽  
Paul S. Bell ◽  
David L. McCann ◽  
Richard Cooke ◽  
Christine Sams
Keyword(s):  
Tide Gauge ◽  
Control Measure ◽  
Low Cost ◽  
Water Levels ◽  
Quality Data ◽  
Tidal Range ◽  
Remote Measurement ◽  
Validation Data ◽  
Concept System

AbstractA low-cost [$30 (U.S. dollars)] consumer grade GPS receiver with a sideways-mounted antenna has been applied to measure tidal water levels at a mesotidal coastal site using an interferometric reflectometry approach. The proof-of-concept system was installed approximately 16 m above mean sea level in close proximity to a conventional bubbler tide gauge that provided validation data. The received signal-to-noise ratios (SNR) for the satellites in view were recorded for several months during two successive years and the observed frequencies of the interferometric oscillations used to calculate the difference in elevation between the receiver and the water surface. Comparisons with concurrent and historic in situ tide gauge data at the site initially helped to identify a calibration issue with the in situ gauge. The GPS-based measurements were shown to be in excellent agreement with the corrected in situ gauge, exhibiting a root-mean-square difference of 5.7 cm over a tidal range exceeding 3 m at spring tides and a daily averaged RMS of 1.7 cm. The SNR data from the low-cost GPS receivers are shown to provide significantly higher-quality data for this purpose compared with high-end geodetic grade receivers at similar sites. This low-cost, widely available technology has the potential to be applied globally for monitoring water levels in a wide variety of circumstances and applications that would otherwise be cost or situation prohibitive. It could also be applied as an independent cross check and quality control measure for conventional water-level gauges.

scholarly journals Development and temporal external validation of a simple risk score tool for prediction of outcomes after severe head injury based on admission characteristics from level-1 trauma centre of India using retrospectively collected data

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e040778
Author(s):  
Vineet Kumar Kamal ◽  
Ravindra Mohan Pandey ◽  
Deepak Agrawal
Keyword(s):  
Hospital Mortality ◽  
External Validation ◽  
Trauma Centre ◽  
Unfavourable Outcome ◽  
Motor Score ◽  
Validation Data ◽  
Data Set ◽  
Development Data ◽  
Level 1 ◽  
Pupillary Reactivity

ObjectiveTo develop and validate a simple risk scores chart to estimate the probability of poor outcomes in patients with severe head injury (HI).DesignRetrospective.SettingLevel-1, government-funded trauma centre, India.ParticipantsPatients with severe HI admitted to the neurosurgery intensive care unit during 19 May 2010–31 December 2011 (n=946) for the model development and further, data from same centre with same inclusion criteria from 1 January 2012 to 31 July 2012 (n=284) for the external validation of the model.Outcome(s)In-hospital mortality and unfavourable outcome at 6 months.ResultsA total of 39.5% and 70.7% had in-hospital mortality and unfavourable outcome, respectively, in the development data set. The multivariable logistic regression analysis of routinely collected admission characteristics revealed that for in-hospital mortality, age (51–60, >60 years), motor score (1, 2, 4), pupillary reactivity (none), presence of hypotension, basal cistern effaced, traumatic subarachnoid haemorrhage/intraventricular haematoma and for unfavourable outcome, age (41–50, 51–60, >60 years), motor score (1–4), pupillary reactivity (none, one), unequal limb movement, presence of hypotension were the independent predictors as its 95% confidence interval (CI) of odds ratio (OR)_did not contain one. The discriminative ability (area under the receiver operating characteristic curve (95% CI)) of the score chart for in-hospital mortality and 6 months outcome was excellent in the development data set (0.890 (0.867 to 912) and 0.894 (0.869 to 0.918), respectively), internal validation data set using bootstrap resampling method (0.889 (0.867 to 909) and 0.893 (0.867 to 0.915), respectively) and external validation data set (0.871 (0.825 to 916) and 0.887 (0.842 to 0.932), respectively). Calibration showed good agreement between observed outcome rates and predicted risks in development and external validation data set (p>0.05).ConclusionFor clinical decision making, we can use of these score charts in predicting outcomes in new patients with severe HI in India and similar settings.

scholarly journals Morphodynamic Evolution of a Nourished Beach with Artificial Sandbars: Field Observations and Numerical Modeling

2021 ◽  
Vol 9 (3) ◽  
pp. 245
Author(s):  
Cuiping Kuang ◽  
Xuejian Han ◽  
Jiabo Zhang ◽  
Qingping Zou ◽  
Boling Dong
Keyword(s):  
Sediment Transport ◽  
Tidal Current ◽  
Model Simulation ◽  
Morphological Changes ◽  
Current Model ◽  
Beach Nourishment ◽  
Tidal Range ◽  
Coastal Protection ◽  
Field Observations ◽  
One Year

Beach nourishment, a common practice to replenish an eroded beach face with filling sand, has become increasingly popular as an environmentally friendly soft engineering measure to tackle coastal erosion. In this study, three 200 m long offshore submerged sandbars were placed about 200 m from the shore in August 2017 for both coastal protection and beach nourishment at Shanhai Pass, Bohai Sea, northeastern China. A series of 21 beach profiles were collected from August 2017 to July 2018 to monitor the morphological changes of the nourished beach. Field observations of wave and tide levels were conducted for one year and tidal current for 25 h, respectively. To investigate the spatial-temporal responses of hydrodynamics, sediment transport, and morphology to the presence of three artificial submerged sandbars, a two-dimensional depth-averaged (2DH) multi-fraction sediment transport and morphological model were coupled with wave and current model and implemented over a spatially varying nested grid. The model results compare well with the field observations of hydrodynamics and morphological changes. The tidal range was around 1.0 m and the waves predominately came from the south-south-east (SSE) direction in the study area. The observed and predicted beach profiles indicate that the sandbars moved onshore and the morphology experienced drastic changes immediately after the introduction of sandbars and reached an equilibrium state in about one year. The morphological change was mainly driven by waves. Under the influences of the prevailing waves and the longshore drift toward the northeast, the coastline on the leeside of the sandbars advanced seaward by 35 m maximally while the rest adjacent coastline retreated severely by 44 m maximally within August 2017–July 2018. The model results demonstrate that the three sandbars have little effect on the tidal current but attenuate the incoming wave significantly. As a result, the medium-coarse sand of sandbars is transported onshore and the background silt is mainly transported offshore and partly in the longshore direction toward the northeast. The 2- and 5-year model simulation results further indicate that shoreline salient may form behind the sandbars and protrude offshore enough to reach the sandbars, similar to the tombolo behind the breakwater.

Fully automated contrast and non-contrast cardiac view detection in echocardiography a multi-centre, multi-vendor study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S Gao ◽  
D Stojanovski ◽  
A Parker ◽  
P Marques ◽  
S Heitner ◽  
...  
Keyword(s):  
Neural Network ◽  
Training Data ◽  
Classification Model ◽  
Validation Dataset ◽  
Funding Source ◽  
Private Company ◽  
Validation Data ◽  
Independent Test ◽  
Model Training ◽  
Confusion Matrices

Abstract Background Correctly identifying views acquired in a 2D echocardiographic examination is paramount to post-processing and quantification steps often performed as part of most clinical workflows. In many exams, particularly in stress echocardiography, microbubble contrast is used which greatly affects the appearance of the cardiac views. Here we present a bespoke, fully automated convolutional neural network (CNN) which identifies apical 2, 3, and 4 chamber, and short axis (SAX) views acquired with and without contrast. The CNN was tested in a completely independent, external dataset with the data acquired in a different country than that used to train the neural network. Methods Training data comprised of 2D echocardiograms was taken from 1014 subjects from a prospective multisite, multi-vendor, UK trial with the number of frames in each view greater than 17,500. Prior to view classification model training, images were processed using standard techniques to ensure homogenous and normalised image inputs to the training pipeline. A bespoke CNN was built using the minimum number of convolutional layers required with batch normalisation, and including dropout for reducing overfitting. Before processing, the data was split into 90% for model training (211,958 frames), and 10% used as a validation dataset (23,946 frames). Image frames from different subjects were separated out entirely amongst the training and validation datasets. Further, a separate trial dataset of 240 studies acquired in the USA was used as an independent test dataset (39,401 frames). Results Figure 1 shows the confusion matrices for both validation data (left) and independent test data (right), with an overall accuracy of 96% and 95% for the validation and test datasets respectively. The accuracy for the non-contrast cardiac views of >99% exceeds that seen in other works. The combined datasets included images acquired across ultrasound manufacturers and models from 12 clinical sites. Conclusion We have developed a CNN capable of automatically accurately identifying all relevant cardiac views used in “real world” echo exams, including views acquired with contrast. Use of the CNN in a routine clinical workflow could improve efficiency of quantification steps performed after image acquisition. This was tested on an independent dataset acquired in a different country to that used to train the model and was found to perform similarly thus indicating the generalisability of the model. Figure 1. Confusion matrices Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Ultromics Ltd.

scholarly journals A novel ferroptosis related gene signature is associated with prognosis in patients with ovarian serous cystadenocarcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhixiang Yu ◽  
Haiyan He ◽  
Yanan Chen ◽  
Qiuhe Ji ◽  
Min Sun
Keyword(s):  
Cox Regression ◽  
Expression Profiles ◽  
Critical Role ◽  
Gene Signature ◽  
Cancer Genome ◽  
Training Data ◽  
Hub Genes ◽  
Validation Data ◽  
Data Set ◽  
Cox Regression Analysis

AbstractOvarian cancer (OV) is a common type of carcinoma in females. Many studies have reported that ferroptosis is associated with the prognosis of OV patients. However, the mechanism by which this occurs is not well understood. We utilized Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) to identify ferroptosis-related genes in OV. In the present study, we applied Cox regression analysis to select hub genes and used the least absolute shrinkage and selection operator to construct a prognosis prediction model with mRNA expression profiles and clinical data from TCGA. A series of analyses for this signature was performed in TCGA. We then verified the identified signature using International Cancer Genome Consortium (ICGC) data. After a series of analyses, we identified six hub genes (DNAJB6, RB1, VIMP/ SELENOS, STEAP3, BACH1, and ALOX12) that were then used to construct a model using a training data set. The model was then tested using a validation data set and was found to have high sensitivity and specificity. The identified ferroptosis-related hub genes might play a critical role in the mechanism of OV development. The gene signature we identified may be useful for future clinical applications.

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