The analysis of the genomic distribution of viral vector genomic integration sites is a key step in hematopoietic stem cell-based gene therapy applications, allowing to assess both the safety and the efficacy of the treatment and to study the basic aspects of hematopoiesis and stem cell biology. Identifying vector integration sites requires ad-hoc bioinformatics tools with stringent requirements in terms of computational efficiency, flexibility, and usability. We developed VISPA (Vector Integration Site Parallel Analysis), a pipeline for automated integration site identification and annotation based on a distributed environment with a simple Galaxy web interface. VISPA was successfully used for the bioinformatics analysis of the follow-up of two lentiviral vector-based hematopoietic stem-cell gene therapy clinical trials. Our pipeline provides a reliable and efficient tool to assess the safety and efficacy of integrating vectors in clinical settings.
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http://dx.doi.org/10.1186/s13073-014-0067-5 | DOI Listing |
Chem Biodivers
January 2025
Department of Horticultural Science, Faculty of Agriculture, Jahrom University, Jahrom, Iran.
The approaches used to determine the medicinal properties of the plants are often destructive, labor-intensive, time-consuming, and expensive, making it impossible to analyze their quality analysis online. Performance of hyperspectral imaging (HSI) integrated with intelligent techniques to overcome these problems was investigated in this research. For this purpose, three classification methods-support vector machine, random forest (RF), and extreme gradient boosting-were studied for the classification of plants in three classes of medicinal, edible, and ornamental for the organs of leaf, stem, flower, and root.
View Article and Find Full Text PDFInsights Imaging
January 2025
Medical Research Department, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, P. R. China.
Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).
Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.
Heart Rhythm O2
December 2024
Philips, San Diego, California.
Cardiac implantable electronic devices (CIEDs) generate substantial data, often stored in image or PDF formats. Remote monitoring, now an integral component of patient care, places considerable administrative burdens on clinicians and staff, in large part due to the challenge of integrating these data seamlessly into electronic health records. Since 2006, the Heart Rhythm Society, in collaboration with the CIED industry, has led an initiative to establish a unified standard nomenclature.
View Article and Find Full Text PDFMethodsX
June 2025
Department of Mathematical Sciences, Universiti Teknologi Malaysia, Johor Bahru, Malaysia.
PM2.5 air pollution poses significant health risks, particularly in urban areas such as Jakarta, where concentrations frequently surpass acceptable levels due to rapid urbanization. This study addresses autocorrelation in air quality data and evaluates the monitoring performance of XGBoost and Support Vector Regression (SVR) models using Individual and Exponentially Weighted Moving Average (EWMA) Charts.
View Article and Find Full Text PDFChina CDC Wkly
December 2024
NHC Key Laboratory of Pneumoconiosis, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention, Shanxi Key Laboratory of Respiratory Diseases, The First Hospital of Shanxi Medical University, Taiyuan City, Shanxi Province, China.
Introduction: Pneumoconiosis is the most prevalent occupational disease in China, with coal worker pneumoconiosis (CWP) demonstrating the highest incidence. Studies have indicated that phospholipids may be associated with CWP.
Methods: In this study, serum was obtained from 62 patients with pneumoconiosis, 105 coal dust-exposed workers, and 50 healthy individuals and analyzed via targeted lipidomics using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).
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