scholarly journals Blood Circulating miRNA Pairs as a Robust Signature for Early Detection of Esophageal Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Yang Song ◽  
Suzhu Zhu ◽  
Ning Zhang ◽  
Lixin Cheng
Keyword(s):  
Esophageal Cancer ◽  
Early Detection ◽  
Digestive System ◽  
Early Stage ◽  
Diagnostic Model ◽  
Training Set ◽  
Expression Change ◽  
Circulating Mirna ◽  
Diagnostic Signature ◽  
Late Stages

Esophageal cancer (EC) is a common malignant tumor in the digestive system which is often diagnosed at the middle and late stages. Noninvasive diagnosis using circulating miRNA as biomarkers enables accurate detection of early-stage EC to reduce mortality. We built a diagnostic signature consisting of four miRNA pairs for the early detection of EC using individualized Pairwise Analysis of Gene Expression (iPAGE). Profiling of miRNA expression identified 496 miRNA pairs with significant relative expression change. Four miRNA pairs consistently selected from LASSO were used to construct the final diagnostic model. The performance of the signature was validated using two independent datasets, yielding both AUCs and PRCs over 0.99. Furthermore, precision, recall, and F-score were also evaluated for clinical application, when a fixed threshold is given, resulting in all the scores are larger than 0.92 in the training set, test set, and two validation sets. Our results suggested that the 4-miRNA signature is a new biomarker for the early diagnosis of patients with EC. The clinical use of this signature would have improved the detection of EC for earlier therapy and more favorite prognosis.

Identification, Development and Validation of a Circulating Mirna-Based Diagnostic Signature for Early Detection of Gastric Cancer

2017 ◽  
Vol 152 (5) ◽  
pp. S56
Author(s):  
Daisuke Izumi ◽  
Shusuke Toden ◽  
Feng Gao ◽  
Jacob Turner ◽  
Mitsuro Kanda ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Early Detection ◽  
Circulating Mirna ◽  
Diagnostic Signature ◽  
Development And Validation

Discovery and validation of methylation signatures in circulating cell-free DNA for early detection of esophageal cancer: A case-control study.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16027-e16027
Author(s):  
Weitao Zhuang ◽  
Xiao-song Ben ◽  
Chengcheng Li ◽  
Jiayue Xu ◽  
Dan Tian ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Early Detection ◽  
Methylation Level ◽  
Early Stage ◽  
Precancerous Lesions ◽  
Esophageal Disease ◽  
Esophageal Tumor ◽  
Esophageal Diseases ◽  
Circulating Free Dna ◽  
Free Dna

e16027 Background: The pivotal goal of esophageal cancer (ESCA) screening is to identify early-stage cancer or precancerous lesions when curable treatments are available. Methylation of circulating-free DNA (cfDNA) has shown promising results in the early detection of multiple tumors recently. Here we conducted a prospective study to investigate the performance of cfDNA methylation in the early detection of ESCA. Methods: Specific methylation markers for ESCA were identified and optimized based on 24 esophageal tumor and its corresponding adjacent tissues. Age-matched participants with ESCA (n = 136), benign esophageal disease (n = 21) and healthy controls (n = 126) were randomized into the training and testing sets to develop an early-detection classifier. Results: In total, 921 differentiated methylation blocks (DMBs) between tumor and adjacent tissues were identified, of which 679 (73.7%) showed higher methylation level and 242 (26.3%) had lower methylation level in tumor tissues. In the training set, the specificity of the model built with these DMBs was 94.1% (95% CI, 85.5%−98.4%) and the sensitivity was 86.0% (95% CI, 72.2%−94.8%). The sensitives increased with stages, which were 77.8% (95% CI, 39.8%−97.2%), 90.9% (95% CI, 58.7%−99.8%), 83.3% (95% CI, 51.7%−97.9%) and 100.0% (95%CI, 63.1%−100.0%) for stage I-IV, respectively. Similar results were observed in the testing set with area under curve (AUC) of 0.932 (95% CI, 0.887−0.977). Conclusions: The cfDNA methylation profiles distinguished ESCAs from healthy individuals and benign esophageal diseases with promising sensitivity and specificity. Consideration of the potential value of early detection in ESCAs, further evaluation in larger prospective studies is warranted.

scholarly journals Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

2020 ◽  
Vol 13 (1) ◽  
pp. 14
Author(s):  
Annamaria Castrignanò ◽  
Antonella Belmonte ◽  
Ilaria Antelmi ◽  
Ruggiero Quarto ◽  
Francesco Quarto ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Early Detection ◽  
Plant Pathogens ◽  
Early Stage ◽  
Xylella Fastidiosa ◽  
Mediterranean Countries ◽  
Parametric Classification ◽  
Aerial Vehicle ◽  
Olive Groves ◽  
Olive Trees

Xylella fastidiosa subsp. pauca (Xfp) is one of the most dangerous plant pathogens in the world. Identified in 2013 in olive trees in south–eastern Italy, it is spreading to the Mediterranean countries. The bacterium is transmitted by insects that feed on sap, and causes rapid wilting in olive trees. The paper explores the use of Unmanned Aerial Vehicle (UAV) in combination with a multispectral radiometer for early detection of infection. The study was carried out in three olive groves in the Apulia region (Italy) and involved four drone flights from 2017 to 2019. To classify Xfp severity level in olive trees at an early stage, a combined method of geostatistics and discriminant analysis was implemented. The results of cross-validation for the non-parametric classification method were of overall accuracy = 0.69, mean error rate = 0.31, and for the early detection class of accuracy 0.77 and misclassification probability 0.23. The results are promising and encourage the application of UAV technology for the early detection of Xfp infection.

scholarly journals Automated Assay of a Four-Protein Biomarker Panel for Improved Detection of Ovarian Cancer

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 325
Author(s):  
Christopher Walker ◽  
Tuan-Minh Nguyen ◽  
Shlomit Jessel ◽  
Ayesha B. Alvero ◽  
Dan-Arin Silasi ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Early Detection ◽  
Predictive Value ◽  
Early Stage ◽  
Ca 125 ◽  
Healthy Controls ◽  
Classification Models ◽  
Serum Samples ◽  
Protein Biomarker ◽  
Biomarker Panel

Background: Mortality from ovarian cancer remains high due to the lack of methods for early detection. The difficulty lies in the low prevalence of the disease necessitating a significantly high specificity and positive-predictive value (PPV) to avoid unneeded and invasive intervention. Currently, cancer antigen- 125 (CA-125) is the most commonly used biomarker for the early detection of ovarian cancer. In this study we determine the value of combining macrophage migration inhibitory factor (MIF), osteopontin (OPN), and prolactin (PROL) with CA-125 in the detection of ovarian cancer serum samples from healthy controls. Materials and Methods: A total of 432 serum samples were included in this study. 153 samples were from ovarian cancer patients and 279 samples were from age-matched healthy controls. The four proteins were quantified using a fully automated, multi-analyte immunoassay. The serum samples were divided into training and testing datasets and analyzed using four classification models to calculate accuracy, sensitivity, specificity, PPV, negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC). Results: The four-protein biomarker panel yielded an average accuracy of 91% compared to 85% using CA-125 alone across four classification models (p = 3.224 × 10−9). Further, in our cohort, the four-protein biomarker panel demonstrated a higher sensitivity (median of 76%), specificity (median of 98%), PPV (median of 91.5%), and NPV (median of 92%), compared to CA-125 alone. The performance of the four-protein biomarker remained better than CA-125 alone even in experiments comparing early stage (Stage I and Stage II) ovarian cancer to healthy controls. Conclusions: Combining MIF, OPN, PROL, and CA-125 can better differentiate ovarian cancer from healthy controls compared to CA-125 alone.

Health Insurance Status as a Predictor of Mode of Colon Cancer Detection but Not Stage at Diagnosis: Implications for Early Detection

2021 ◽  
pp. 003335492199917
Author(s):  
Lindsey A. Jones ◽  
Katherine C. Brewer ◽  
Leslie R. Carnahan ◽  
Jennifer A. Parsons ◽  
Blase N. Polite ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Health Insurance ◽  
Early Detection ◽  
Late Stage ◽  
Early Stage ◽  
Insurance Status ◽  
Stage At Diagnosis ◽  
Health Insurance Status ◽  
Percentage Point Increase ◽  
Point Increase

Objective For colon cancer patients, one goal of health insurance is to improve access to screening that leads to early detection, early-stage diagnosis, and polyp removal, all of which results in easier treatment and better outcomes. We examined associations among health insurance status, mode of detection (screen detection vs symptomatic presentation), and stage at diagnosis (early vs late) in a diverse sample of patients recently diagnosed with colon cancer from the Chicago metropolitan area. Methods Data came from the Colon Cancer Patterns of Care in Chicago study of racial and socioeconomic disparities in colon cancer screening, diagnosis, and care. We collected data from the medical records of non-Hispanic Black and non-Hispanic White patients aged ≥50 and diagnosed with colon cancer from October 2010 through January 2014 (N = 348). We used logistic regression with marginal standardization to model associations between health insurance status and study outcomes. Results After adjusting for age, race, sex, and socioeconomic status, being continuously insured 5 years before diagnosis and through diagnosis was associated with a 20 (95% CI, 8-33) percentage-point increase in prevalence of screen detection. Screen detection in turn was associated with a 15 (95% CI, 3-27) percentage-point increase in early-stage diagnosis; however, nearly half (47%; n = 54) of the 114 screen-detected patients were still diagnosed at late stage (stage 3 or 4). Health insurance status was not associated with earlier stage at diagnosis. Conclusions For health insurance to effectively shift stage at diagnosis, stronger associations are needed between health insurance and screening-related detection; between screening-related detection and early stage at diagnosis; or both. Findings also highlight the need to better understand factors contributing to late-stage colon cancer diagnosis despite screen detection.

scholarly journals Early Detection of Alzheimer’s Disease Using Polar Harmonic Transforms and Optimized Wavelet Neural Network

2021 ◽  
Vol 11 (4) ◽  
pp. 1574
Author(s):  
Shabana Urooj ◽  
Satya P. Singh ◽  
Areej Malibari ◽  
Fadwa Alrowais ◽  
Shaeen Kalathil
Keyword(s):  
Neural Network ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Differential Evolution ◽  
Early Stage ◽  
Selection Process ◽  
Parameter Tuning ◽  
Wavelet Neural Network ◽  
Tuning Parameter

Effective and accurate diagnosis of Alzheimer’s disease (AD), as well as early-stage detection, has gained more and more attention in recent years. For AD classification, we propose a new hybrid method for early detection of Alzheimer’s disease (AD) using Polar Harmonic Transforms (PHT) and Self-adaptive Differential Evolution Wavelet Neural Network (SaDE-WNN). The orthogonal moments are used for feature extraction from the grey matter tissues of structural Magnetic Resonance Imaging (MRI) data. Irrelevant features are removed by the feature selection process through evaluating the in-class and among-class variance. In recent years, WNNs have gained attention in classification tasks; however, they suffer from the problem of initial parameter tuning, parameter setting. We proposed a WNN with the self-adaptation technique for controlling the Differential Evolution (DE) parameters, i.e., the mutation scale factor (F) and the cross-over rate (CR). Experimental results on the Alzheimer’s disease Neuroimaging Initiative (ADNI) database indicate that the proposed method yields the best overall classification results between AD and mild cognitive impairment (MCI) (93.7% accuracy, 86.0% sensitivity, 98.0% specificity, and 0.97 area under the curve (AUC)), MCI and healthy control (HC) (92.9% accuracy, 95.2% sensitivity, 88.9% specificity, and 0.98 AUC), and AD and HC (94.4% accuracy, 88.7% sensitivity, 98.9% specificity and 0.99 AUC).

scholarly journals Early Detection of Encroaching Woody Juniperus virginiana and Its Classification in Multi-Species Forest Using UAS Imagery and Semantic Segmentation Algorithms

2021 ◽  
Vol 13 (10) ◽  
pp. 1975
Author(s):  
Lin Wang ◽  
Yuzhen Zhou ◽  
Qiao Hu ◽  
Zhenghong Tang ◽  
Yufeng Ge ◽  
...  
Keyword(s):  
Early Detection ◽  
Early Development ◽  
Spatial Resolution ◽  
Early Stage ◽  
Semantic Segmentation ◽  
Development Stage ◽  
Unmanned Aircraft ◽  
Economic Losses ◽  
Juniperus Virginiana ◽  
Segmentation Algorithms

Woody plant encroachment into grasslands ecosystems causes significantly ecological destruction and economic losses. Effective and efficient management largely benefits from accurate and timely detection of encroaching species at an early development stage. Recent advances in unmanned aircraft systems (UAS) enabled easier access to ultra-high spatial resolution images at a centimeter level, together with the latest machine learning based image segmentation algorithms, making it possible to detect small-sized individuals of target species at early development stage and identify them when mixed with other species. However, few studies have investigated the optimal practical spatial resolution of early encroaching species detection. Hence, we investigated the performance of four popular semantic segmentation algorithms (decision tree, DT; random forest, RF; AlexNet; and ResNet) on a multi-species forest classification case with UAS-collected RGB images in original and down-sampled coarser spatial resolutions. The objective of this study was to explore the optimal segmentation algorithm and spatial resolution for eastern redcedar (Juniperus virginiana, ERC) early detection and its classification within a multi-species forest context. To be specific, firstly, we implemented and compared the performance of the four semantic segmentation algorithms with images in the original spatial resolution (0.694 cm). The highest overall accuracy was 0.918 achieved by ResNet with a mean interaction over union at 85.0%. Secondly, we evaluated the performance of ResNet algorithm with images in down-sampled spatial resolutions (1 cm to 5 cm with 0.5 cm interval). When applied on the down-sampled images, ERC segmentation performance decreased with decreasing spatial resolution, especially for those images coarser than 3 cm spatial resolution. The UAS together with the state-of-the-art semantic segmentation algorithms provides a promising tool for early-stage detection and localization of ERC and the development of effective management strategies for mixed-species forest management.

Reconsidering Early Detection in Countering Violent Extremism (CVE) by Local Frontline Professionals

Proceedings ◽  
2021 ◽  
Vol 77 (1) ◽  
pp. 12
Author(s):  
Annemarie van de Weert
Keyword(s):  
Early Detection ◽  
The Netherlands ◽  
Political Violence ◽  
Social Innovation ◽  
Early Stage ◽  
Violent Behavior ◽  
Research Centre ◽  
Access To Justice ◽  
Local Approach ◽  
Performative Power

In recent years, the fight against terrorism and political violence has focused more on anticipating the threats that they pose. Therefore, early detection of ideas by local professionals has become an important part of the preventive approach in countering radicalization. Frontline workers who operate in the arteries of society are encouraged to identify processes towards violent behavior at an early stage. To date, however, little is known about how these professionals take on this screening task at their own discretion. Research from the Netherlands suggests that subjective assessment appears to exist. This is due to the absence of a clear norm for preliminary judgments. However, such an approach affects prejudice or administrative arbitrariness, which may cause side effects due to unjustified profiling. The publications about the Dutch case are inspired by the concept of “performativity”, (de Graaf, B., & de Graaff, B. G. J. (2010). Bringing politics back in: The introduction of the ‘performative power’ of counterterrorism. Critical Studies on Terrorism, 3(2), pp. 261–275.) which points to a distinct relationship between the performative power of counterterrorism instruments and the effectiveness of the local approach. Performativity contends that the overall effect of the policy in question is not necessarily determined by the policy measures and their intended results, as such, but more by the way in which they are presented and perceived. This means that, in order to create an equitable approach, governments, whether local or national, should focus more on the actual practice performed by frontline practitioners. The focus on practices is part of a larger project, entitled ‘Gatekeepers of Justice’ (See: https://www.internationalhu.com/research/access-to-justice), by the Research Group Access2Justice (Research Centre of Social Innovation at Utrecht University of Applied Science), led by professor Quirine Eijkman, Deputy President of the Netherlands Institute for Human Rights.

scholarly journals Clinical Management of Early-Stage Hypopharyngeal Squamous Cell Carcinoma: A Single-Institution Clinical Analysis

2021 ◽  
pp. 014556132110130
Author(s):  
Ryuji Yasumatsu ◽  
Tomomi Manako ◽  
Rina Jiromaru ◽  
Kazuki Hashimoto ◽  
Takahiro Wakasaki ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Cancer ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Clinical Management ◽  
Early Stage ◽  
Transoral Surgery ◽  
Upper Gastrointestinal Endoscopy ◽  
Detection Rates ◽  
Hypopharyngeal Squamous Cell Carcinoma

Objective: Early detection of hypopharyngeal squamous cell carcinoma (SCC) is important for both an improved prognosis and less-invasive treatment. We retrospectively analyzed the detection rates of early hypopharyngeal SCCs according to the evaluation methods and the clinical management of early hypopharyngeal SCCs. Methods: Sixty-eight patients with early hypopharyngeal SCC who were diagnosed were reviewed. Results: The number of early hypopharyngeal cancer patients with asymptomatic or synchronous or metachronous esophageal cancer examined by upper gastrointestinal endoscopy with narrow-band imaging (NBI) was significantly higher than those examined by laryngopharyngeal endoscopy with NBI. The 3-year disease-specific survival rates according to T classification were as follows: Tis, 100%; T1, 100%; T2, 79.8%; and overall, 91.2%, respectively. Conclusions: Early-stage hypopharyngeal SCC can be cured by minimally invasive transoral surgery or radiotherapy. Observation of the pharynx using NBI in patients with a history of head and neck cancer, esophageal cancer, gastric cancer, or pharyngeal discomfort is very important, and routinely examining the pharynx with NBI, even in patients undergoing endoscopy for screening purposes, is recommended.

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