Science

Results Nationally, screening cost approximately US$11 billion (B) per year from 2019 to 2022 with approximately 37% of eligible women screened each year. In 2022, screening cost US$55 471 per 3D-detected and US$44 000 per 2D-detected invasive or ductal carcinoma in situ case. Using target yearly participation rates of 54%–78% by age of women, the projected cost of screening was US$30B for ACR, US$18B for ACS and US$8B for USPSTF guidelines. The average lifetime cost to screen an average-risk woman was: US$13 416 for ACR, US$7946 for ACS and US$6931 for USPSTF. Participation rates, the proportion of women with a lifetime risk>20% and commercial MRI and 3D costs had the largest impact on total costs.

Conclusion The cost of screening varies significantly by guideline (US$8B–US$30B) and was most influenced by participation rates, high-risk population proportions and technology costs. Future work can investigate whether risk-based screening strategies being tested in ongoing clinical trials can reduce national screening costs while improving outcomes.Cite Now

Predicting the properties of tissues or organisms from the genomics data is widely accepted by the medical community. Here we ask a question: can we predict the properties of each individual cell? Single-cell genomics does not work because the RNA sequencing process destroys the cell, not allowing us to verify our predictions. To test the hypothesis, we investigate the approach of using AI to analyze single-cell images obtained from a 3D imaging flow cytometer. We analyze the cell image at day zero and make the AI-assisted cell property prediction. The prediction is then examined later when the cells continue to live and develop. Our preliminary results are promising, showing 88% accuracy in predicting cells that will have a high protein expression level. The technique can have strong ramifications and impact on preventive medicine, drug development, cell therapy, and fundamental biomedical research.

Sleep cycles are defined as episodes of non-rapid eye movement (non-REM) sleep followed by an episode of REM sleep. Fractal or aperiodic neural activity is a well-established marker of arousal and sleep stages measured using electroencephalography. We introduce a new concept of ‘fractal cycles’ of sleep, defined as a time interval during which time series of fractal activity descend to their local minimum and ascend to the next local maximum. We assess correlations between fractal and classical (i.e. non-REM – REM) sleep cycle durations and study cycles with skipped REM sleep. The sample comprised 205 healthy adults, 21 children and adolescents and 111 patients with depression. We found that fractal and classical cycle durations (89±34 vs 90±25 min) correlated positively (r=0.5, p<0.001). Children and adolescents had shorter fractal cycles than young adults (76±34 vs 94±32 min). The fractal cycle algorithm detected cycles with skipped REM sleep in 91–98% of cases. Medicated patients with depression showed longer fractal cycles compared to their unmedicated state (107±51 vs 92±38 min) and age-matched controls (104±49 vs 88±31 min). In conclusion, fractal cycles are an objective, quantifiable, continuous and biologically plausible way to display sleep neural activity and its cycles.

This study investigates how born-digital memes about high-profile events can serve as rich archival resources for understanding contemporary cultural phenomena and public sentiment by using a linked-data framework. Using a mixed-method approach, this study analyzes memes from a high-profile trial through web scraping and linked-data structures to map themes, sentiments, and cultural references. The linked-data frame includes data collection and integration, semantic web technologies, ontology development, and API data access. The findings point to dominant narratives and shifting sentiment, which further illustrate how such memes reflect and contribute to the polarization of the societal discourse concerning the event. This research is relevant for understanding digital culture, exploring the archival potential of born-digital materials, and assessing the dynamics of public opinion in widely publicized cases. By showing the efficiency of linked data methodologies in the analysis of born-digital discourse, we add valuable insights to both digital humanities and social sciences, offering a new approach of studying ephemeral online content as cultural artifacts.

Plants respond to environmental stimuli by releasing volatile organic compounds (VOCs), which play diverse roles in plant-to-plant interactions. Previous studies have primarily focused on how receiving plants respond. However, little is known about how these receivers communicate back to the emitter plants and their subsequent impacts. Our findings indicated increased plant tolerance when neighboring plants were present, suggesting bidirectional plant communication. Furthermore, we established a model to explore the role of signals from receiver plants, identifying squalene as a crucial feedback signal enhancing the cold tolerance in emitter plants by up-regulating CsCBF5 expression. Further analysis using yeast one-hybrid analysis coupled with inhibition of brassinosteroid pathways suggested that squalene-induced castasterone (CS) accumulation directly activated CsCBF5 expression modulated by CsBES1/BZR1. Overall, these results demonstrated the role of the squalene-CS-BES1/BZR1-CBF5 pathway in the bidirectional communication between plants, expanding our understanding of plant interactions.

Facial attractiveness influences important social outcomes and most studies investigating possible predictors of facial attractiveness have tested for effects of shape symmetry, averageness (i.e., the converse of distinctiveness), and sexual dimorphism (i.e., masculinity–femininity). These studies have typically either tested for these possible effects by experimentally manipulating shape characteristics in faces images or have tested only for bivariate correlations between shape characteristics and attractiveness judgments. However, these two approaches have been criticised for lacking ecological validity and providing little insight into the independent contributions of symmetry, averageness, and sexual dimorphism, respectively. Moreover, the few studies that have investigated the independent contributions of symmetry, averageness, and sexual dimorphism have reported mixed results. Here we measured shape symmetry, averageness, and sexual dimorphism from face images and assessed their independent contribution to attractiveness ratings. Linear mixed effects models showed that facial attractiveness was significantly predicted by averageness in male and female faces and femininity in female faces, but not by masculinity in male faces or symmetry. These results are consistent with other recent work suggesting that averageness and femininity, rather than symmetry and masculinity, predict facial attractiveness.

Our research examines a unique case of the complex interplay between two wealthy brothers and their actions of gender-based violence. In presenting the case of the Tate brothers, British influencers who settled in Romania, we explore how they gained notoriety through their wealth, their online presence, and controversial ideas that promote misogyny. In a survey involving 56 young and young–mature participants, we highlighted perceptions of the Tate brothers alongside attitudes toward wealth, gender roles and norms, and misogyny. Our findings indicate a predominantly negative sentiment towards the Tate brothers, particularly regarding their wealthy class position and how their class power is unfolded through misogyny in their online presence. This study underscores the urgent need for national and international authorities and NGOs to improve the surveillance of misogynistic men’s discourses and practices to combat violence against women. Additionally, it highlights the importance of increasing awareness about the detrimental consequences of gender inequality created through the triadic nexus of class privilege, masculinity, and misogyny.