Performance of cervical cytology and HPV testing for primary cervical cancer screening in Latin America: an analysis within the ESTAMPA study.

Background: Cervical cytology remains widely used as the initial tool in cervical cancer screening worldwide. WHO guidelines recommend replacing cytology with primary HPV testing to reach cervical cancer elimination goals. We assessed the performance of cytology and high-risk HPV testing to detect cervical precancer, cervical intraepithelial neoplasia (CIN) grade 3 or worse (CIN3+) among women aged 30-64 years participating in the ESTAMPA study. Methods: Women were screened with cytology and HPV across ESTAMPA study centres in Latin America. Screen-positives were referred to colposcopy with biopsy collection and treatment as needed. Those with no evident precancer were recalled at 18-months for a second HPV test to complete disease ascertainment. Performance indicators for cytology and HPV to detect CIN3+ were estimated. Findings: 30,606 participants with available cytology and HPV results were included in the analysis. A total of 440 histologically confirmed CIN3s and 30 cancers were diagnosed. Cytology sensitivity for CIN3+ was 48.5% (95% CI: 44.0-53.0), whereas HPV testing had a sensitivity of 98.1% (95% CI: 96.3-96.7). Specificity was 96.5% (95% CI: 96.3-96.7) using cytology and 88.7% (95% CI: 88.3-89.0) with HPV. Performance estimates varied substantially by study centre for cytology (ranging from 32.1% to 87.5% for sensitivity and from 89.2% to 99.5% for specificity) while for HPV results were more consistent across sites (96.7%-100% and 83.6-90.8%, respectively). Interpretation: The limited and highly variable sensitivity of cytology strongly supports transition to the more robust and reproducible HPV-based cervical screening to ensure progress towards global cervical cancer elimination targets in Latin America. Funding: IARC/WHO, UNDP, HRP/WHO, NCI and local funders.

Application of Machine Learning Algorithms to Classify Peruvian Pisco Varieties Using an Electronic Nose.

Pisco is an alcoholic beverage obtained from grape juice distillation. Considered the flagship drink of Peru, it is produced following strict and specific quality standards. In this work, sensing results for volatile compounds in pisco, obtained with an electronic nose, were analyzed through the application of machine learning algorithms for the differentiation of pisco varieties. This differentiation aids in verifying beverage quality, considering the parameters established in its Designation of Origin". For signal processing, neural networks, multiclass support vector machines and random forest machine learning algorithms were implemented in MATLAB. In addition, data augmentation was performed using a proposed procedure based on interpolation-extrapolation. All algorithms trained with augmented data showed an increase in performance and more reliable predictions compared to those trained with raw data. From the comparison of these results, it was found that the best performance was achieved with neural networks.

Prevalencia de Cryptosporidium en muestras de materia fecal llevadas a diez laboratorios del Area Metropolitana de Bucaramanga, Colombia

Con la técnica de Kinyoun para Cryptosporodium se estudiaron 1988 muestras de materia fecal llevadas para estudio a diez laboratorios del área metropolitana de Bucaramanga, Colombia. Correspondían a 103 lactantes, 113 preescolares, 201 escolares, 1162 adultos jóvenes, 322 adultos mayores y 87 ancianos; 55.48 por ciento eran mujeres y el 97.94 por ciento vivían en zona urbana. Un 13.93 por ciento pertenecían a personas con diarrea. Se encontraron tres muestras positivas, todas en menores de dos años y con diarrea: 2.91 por ciento de los lactantes y el 4.69 por cientode los lactantes con diarrea. Con esto se confirma la presencia del parásito en el Nororiente colombiano, con una prevalencia similar a la encontrada en otras partes del país