Cervical cancer prevention is based on primary prevention with vaccines against Human Papillomavirus (HPV) and secondary prevention by screening with High‐Risk‐HPV (Hr‐HPV) detection. Since 2017, cervical cancer screening in women aged 25−60 years has been performed in Portugal using Hr‐HPV detection, followed by cytology in Hr‐HPV‐positive cases. Herein we report the prevalence of Hr‐HPV genotypes and cytological abnormalities among 462 401 women (mean age: 43.73 ± 10.79; median age: 45; range: 24−66 years) that participated in the Regional Cervical Cancer Screening Program of the Northern Region of Portugal, performed between August 2016 and December 2021. Overall, we describe a prevalence rate of 12.50% for Hr‐HPV varying from 20.76% at age 25% to 8.32% at age 64. The five most common Hr‐HPV genotypes identified were HPV‐68 (16.09%), HPV‐31 (15.30%), HPV‐51 (12.96%), HPV‐16 (11.06%), and HPV‐39 (11.01%). The prevalence of Hr‐HPV included in the nonavalent vaccine (HPV‐9valent) was 55.00% ranging from 47.78% to 59.18% across different age groups. Considering positive Hr‐HPV cases, 65.68% had a Negative for Intraepithelial Lesion or Malignancy (NILM) cytology, 20.83% atypical squamous cells of undetermined significance (ASC‐US), 8.85% Low‐Grade Squamous Intraepithelial Lesion (LSIL), 1.65% High‐Grade Squamous Intraepithelial Lesion (HSIL), 2.85% ASC‐H, 0.09% Atypical Glandular Cells, 0.02% Adenocarcinomas, and 0.02% Squamous Cell Carcinoma (SCC). Our analysis revealed that HPV‐9val genotypes were responsible for 52.13% NILM, 59.21% ASC‐US, 55.06% LSIL, 90.14% HSIL, 83.50% ASC‐H, and 100.00% SCC. Furthermore, multiple Hr‐HPV infections (risk ratio [RR] = 1.46; 95% confidence interval [CI] 1.34−1.58), HPV‐16/18 (RR = 5.16; 95% CI 4.75−5.93), or HPV‐9val genotypes (RR = 5.23; 95% CI 4.68−5.85) were associated with a significant risk of developing > HSIL ( p < 0.001). To date, this is the largest study on Hr‐HPV genotyping in cervical cancer screening that includes data from a complete cycle of the screening program. Our findings suggest a high prevalence of HPV‐9valent genotypes and a significant association with an increased risk of developing > HSIL. This constitutes important data for health authorities, which may help define the future of vaccination and cervical cancer screening strategies.

Measurable residual disease (MRD) in acute myeloid leukemia (AML) is monitored through detection of leukemia-associated phenotypic protein markers (LAPMs) in bone marrow aspirates, hindering disease real-time monitoring. We explored peripheral blood (PB), extracellular vesicle (EV)-based methods for MRD monitoring. To confirm that LAPMs are present in AML-derived EVs, EVs were isolated from OCI-AML3 cells by differential centrifugation and characterized according to their size (nanoparticle tracking analysis), morphology (transmission electron microscopy) and protein cargo (proteomic analysis and Western blot). CD14 and CD33 were detected in OCI-AML3 cells and their released EVs. To select a method to isolate EVs from the PB of AML patients, three techniques were tested: size exclusion chromatography followed by ultrafiltration (SEC-UF), Total Exosome Isolation Kit (Invitrogen) and Exo-spin™ Exosome Purification Kit (Cell Guidance Systems). SEC-UF allowed EV isolation with higher purity and less aggregates than the other techniques. LAPMs were detected in those EVs, but their presence depended on the isolation method. Finally, EVs from seven AML patients’ plasma were isolated by SEC-UF. LAPMs were identified in paired samples at diagnosis and remission, with differential expression throughout disease evolution. This proof-of-concept study highlights the possibility of real-time MRD monitoring through LAPMs’ analysis in AML patient’s circulating EVs.

Digital health can effectively engage patients in the self-management of their asthma. Still, it will only reach its full potential when apps are aligned with patients’ needs and are integrated into clinical practice. We aim to test a framework for the involvement of patients/carers in all phases of developing and implementing an app for asthma. This protocol was co-designed with six asthma patients/carers and includes 5 tasks. Regular interactions among patients, developers and healthcare professionals will be a priority for user requirements definition (task 1) and iterative development and testing until the app’s initial version (tasks 2-3). Patients/carers and healthcare professionals will be fully engaged in the real-life feasibility study (task 4) and management and dissemination activities (task 5). The eligibility criteria to participate in tasks 2-4 are 1) diagnosis of asthma or carer of a person with asthma; 2) ≥18 years; 3) ability to use apps and access a mobile device with Internet. We anticipate applying questionnaires such as the User Experience Questionnaire and the System Usability Scale in all app testing tasks. We expect to have a final version of the asthma app that meets patients’/carers’ needs and experiences and healthcare professionals’ concerns. This will be an attractive app to support patients in self-management of their disease, keeping their asthma in control, having fewer asthma symptoms, and enjoying life. This study will be a framework for fully involving patients, carers and citizens in the iterative co-production development and implementation of an asthma app.