Benzalkonium Chloride Significantly Improves Environmental DNA Detection from Schistosomiasis Snail Vectors in Freshwater Samples.

Urogenital schistosomiasis, caused by and transmitted by snails, affects approximately 190 million individuals globally and remains a major public health concern. Effective surveillance of snail vectors is critical for disease control, but traditional identification methods are time-intensive and require specialized expertise. Environmental DNA (eDNA) detection using qPCR has emerged as a promising alternative for large-scale vector surveillance.

Imported Schistosomiasis in Southwestern Europe: Wide Variation of Pure and Hybrid Genotypes Infecting Sub-Saharan Migrants.

Mitochondrial 1 and nuclear ribosomal ITSs are commonly combined to distinguish species and identify hybrids in endemic countries but very rarely applied to patients diagnosed in Europe despite the increasing arrival of migrants in southwestern Europe. To assess whether those migrants are carriers of pure or hybrid schistosomes, a complete genetic characterization of entering Spain is performed. A total of 759 eggs (from urine + stools) from 58 patients from 8 African countries were individually processed to describe their mito-nuclear signature by 1 rapid diagnostic multiplex one-step polymerase chain reaction (RD-PCR) and ITS-2/18S sequencing and haplotype identification by means of the complete ITS1-5.

Usefulness of real-time PCR for urogenital schistosomiasis diagnosis in preschool children in a high-prevalence area in Angola.

Background: Urogenital schistosomiasis caused by Schistosoma haematobium is highly endemic in the municipality of Cubal in Angola. Currently, diagnosis is based on the observation of S. haematobium eggs in urine samples by microscopy but this method has low sensitivity.

A data-centric machine learning approach to improve prediction of glioma grades using low-imbalance TCGA data.

Accurate prediction and grading of gliomas play a crucial role in evaluating brain tumor progression, assessing overall prognosis, and treatment planning. In addition to neuroimaging techniques, identifying molecular biomarkers that can guide the diagnosis, prognosis and prediction of the response to therapy has aroused the interest of researchers in their use together with machine learning and deep learning models. Most of the research in this field has been model-centric, meaning it has been based on finding better performing algorithms.

Prevalence and morbidity of urogenital schistosomiasis among pre-school age children in Cubal, Angola.

Background: Schistosomiasis is one of the most important neglected tropical diseases, with a great impact on public health and more than 200,000 deaths annually. Schistosoma haematobium causes urinary tract (UT) morbidity. Since schistosomiasis morbidity control programs focus on children older than 5 years, pre-school age children (PSAC) morbidity is not well known.

Research on Schistosomiasis in the Era of the COVID-19 Pandemic: A Bibliometric Analysis.

The objectives of this work are to check whether the COVID-19 pandemic affected the research on schistosomiasis, to provide an insight into the most productive countries and journals and the most cited publications, and to analyse any association between the total publications of countries and a set of socio-economic and demographic factors. Based on PRISMA methodology, we used the Scopus database to search for articles published between 1 January 2020 and 26 March 2022. VOSviewer was used to generate the co-authorship and the co-occurrence networks, and Spearman's rank correlation was applied to study associations.