Purpose This study aimed to evaluate the preliminary effectiveness of an educational intervention using a web-app to improve knowledge of breast cancer risk factors and symptoms and adherence to healthy eating and physical activity among women without breast cancer diagnosis in Asturias (Spain). Methods A pragmatic randomized pilot trial was conducted to evaluate the impact of a web-app-based intervention for women without breast cancer diagnosis. Women in the intervention group participated in a 6-month intervention web-app based on the Behaviour Change Wheel Model. The web-app includes information about breast cancer risk factors, early detection, physical activity and diet. Results Two hundred and eighty-fifth women aged 25-50 were invited to join the study. Two hundred and twenty-four were randomly assigned to either the intervention group (IG = 134) or control group (CG = 90) according to their place of residence. Adherence among women in the IG increased significantly from pre- to post-intervention for eight of the 12 healthy behaviors and for the identification of six risk factors and six symptoms compared to women in the CG and, among whom adherence only increased for two behaviors, the identification of one risk factor and 0 symptoms. The intervention significantly improved the mean number of risk factors + 1.06 (p < 0.001) and symptoms + 1.18 (p < 0.001) identified by women in the IG. Conclusions The preliminary results of this study suggest that an educational intervention using a web-app and based on the Behaviour Change Wheel model could be useful to improve knowledge of breast cancer risk factors and symptoms and to improve adherence to a healthy diet and physical activity in women without a previous breast cancer diagnosis.

Simple Summary Triple-negative breast cancer (TNBC) is currently in the clinical research spotlight because of the tumor’s aggressive and invasive nature and the scarcity of therapeutic targets. Despite recent advances in identifying reliable prognostic biomarkers in the tumor microenvironment (TME), rigorous evaluation of their predictive capacity remains challenging. We describe the immune cellular and genetic profile of the residual tumor of TNBC that does not achieve a pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). A high concentration of lymphocytes and dendritic cells, as well as genetic TME markers such as MUC-1 and CXCL13 in the residual tumor, are valuable prognostic factors of survival and relapse in TNBC patients. From a clinical health perspective, a thorough understanding of the composition of the TME and its prognostic implications might yield relevant immunological information and reveal key predictive biomarkers. This could ultimately help substantially improve the outcomes of residual cancer-burdened TNBC patients after NAC. With a high risk of relapse and death, and a poor or absent response to therapeutics, the triple-negative breast cancer (TNBC) subtype is particularly challenging, especially in patients who cannot achieve a pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Although the tumor microenvironment (TME) is known to influence disease progression and the effectiveness of therapeutics, its predictive and prognostic potential remains uncertain. This work aimed to define the residual TME profile after NAC of a retrospective cohort with 96 TNBC patients by immunohistochemical staining (cell markers) and chromogenic in situ hybridization (genetic markers). Kaplan-Meier curves were used to estimate the influence of the selected TME markers on five-year overall survival (OS) and relapse-free survival (RFS) probabilities. The risks of each variable being associated with relapse and death were determined through univariate and multivariate Cox analyses. We describe a unique tumor-infiltrating immune profile with high levels of lymphocytes (CD4, FOXP3) and dendritic cells (CD21, CD1a and CD83) that are valuable prognostic factors in post-NAC TNBC patients. Our study also demonstrates the value of considering not only cellular but also genetic TME markers such as MUC-1 and CXCL13 in routine clinical diagnosis to refine prognosis modelling.

ObjectiveTo investigate longitudinal changes in the liver stiffness measurement (LSM) in the general adult population without known liver disease and to describe its association with metabolic risk factors, with a special focus on subjects with non-alcoholic fatty liver disease (NAFLD) and dysglycemia. Material and MethodsA longitudinal adult population-based cohort study was conducted in Catalonia. LSM was measured by transient elastography (TE) at baseline and follow-up (median: 4.2 years). Subgroup with NAFLD and dysglycemia were analyzed. Moderate-to-advanced liver fibrosis was defined as LSM >= 8.0 kPa and LSM >= 9.2 kPa respectively. ResultsAmong 1.478 subjects evaluated, the cumulative incidence of LSM >= 8.0 kPa and >= 9.2 kPa at follow-up was 2.8% and 1.9%, respectively. This incidence was higher in NAFLD (7.1% for LSM >= 8.0 kPa and 5% for LSM >= 9.2 kPa) and dysglycemia (6.2% for LSM >= 8.0 kPa and 4.7% for LSM >= 9.2 kPa) subgroups. In the global cohort, the multivariate analyses showed that dysglycemia, abdominal obesity and atherogenic dyslipidemia were significantly associated with progression to moderate-to-advanced liver fibrosis. Female sex was negatively associated. In subjects with NAFLD, abdominal obesity and dysglycemia were associated with changes in LSM to >= 8.0 kPa and >= 9.2 kPa at follow-up. A decline in LSM value to ConclusionsIn this population study, the presence of abdominal obesity and dysglycemia were the main risk metabolic factors associated with moderate-to-advanced liver fibrosis development over time in general populations as well as in subjects with NAFLD.

To date, odor research has primarily focused on the behavioral effects of common odors on consumer perception and choices. We report a study that examines, for the first time, the effects of human body odor cues on consumer purchase behaviors. The influence of human chemosignals produced in three conditions, namely happiness, fear, a relaxed condition (rest), and a control condition (no odor), were examined on willingness to pay (WTP) judgments across various products. We focused on the speed with which participants reached such decisions. The central finding revealed that participants exposed to human odors reached decisions significantly faster than the no odor control group. The main driving force is that human body odors activate the presence of others during decision-making. This, in turn, affects response speed. The broader implications of this finding for consumer behavior are discussed.

Short summaryWe investigated changes in serologic measurements after COVID-19 vaccination in 19,422 subjects. An individual-level analysis was performed on standardized measurements. Age, infection, vaccine doses, time between doses and serologies, and vaccine type were associated with changes in serologic levels within 13 months. BackgroundPersistence of vaccine immunization is key for COVID-19 prevention. MethodsWe investigated the difference between two serologic measurements of anti-COVID-19 S1 antibodies in an individual-level analysis on 19,422 vaccinated healthcare workers (HCW) from Italy, Spain, Romania, and Slovakia, tested within 13 months from first dose. Differences in serologic levels were divided by the standard error of the cohort-specific distribution, obtaining standardized measurements. We fitted multivariate linear regression models to identify predictors of difference between two measurements. ResultsWe observed a progressively decreasing difference in serologic levels from <30 days to 210-240 days. Age was associated with an increased difference in serologic levels. There was a greater difference between the two serologic measurements in infected HCW than in HCW who had never been infected; before the first measurement, infected HCW had a relative risk (RR) of 0.81 for one standard deviation in the difference [95% confidence interval (CI) 0.78-0.85]. The RRs for a 30-day increase in time between first dose and first serology, and between the two serologies, were 1.08 (95% CI 1.07-1.10) and 1.04 (95% CI 1.03-1.05), respectively. The first measurement was a strong predictor of subsequent antibody decrease (RR 1.60; 95% CI 1.56-1.64). Compared with Comirnaty, Spikevax (RR 0.83, 95% CI 0.75-0.92) and mixed vaccines (RR 0.61, 95% CI 0.51-0.74) were smaller decrease in serological level (RR 0.46; 95% CI 0.40-0.54). ConclusionsAge, COVID-19 infection, number of doses, time between first dose and first serology, time between serologies, and type of vaccine were associated with differences between the two serologic measurements within a 13-month period.