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Mobile phones are an invaluable economic asset for low-income individuals and an important tool for strengthening social ties. They may also help women overcome physical boundaries, especially those who are separated from support networks and are bound within their husbands' social spheres. Using micro-level data on women and men from recent Demographic and Health Surveys, including new information on mobile phone ownership, this study examines whether women's ownership of mobile phones is associated with their likelihood of having experienced intimate partner violence (IPV) across 10 low- and middle-income countries. Findings show that women's ownership of mobile phones is associated with a 9%–12% decreased likelihood of emotional, physical, and sexual violence over the previous 12 months, even after controlling for characteristics proxying for socioeconomic status, household resources, and local development within the community. Estimates are negative in seven out of the 10 countries and results are robust to the use of nonparametric matching techniques and instrumental variables built through georeferenced ancillary sources. In exploring two potential mechanisms, I show that mobile phone ownership is positively associated with women's decision-making power within the household ( ) and male partners' lower acceptability of IPV ( ). Findings speak to scholars and policymakers interested in how technology diffusion relates to dynamics of women's empowerment and global development.

To date, sarcopenia is considered a patient-specific imaging biomarker able to predict clinical outcomes. Several imaging modalities, including dual-energy X-ray absorptiometry (DXA), computed tomography (CT), magnetic resonance (MR), and ultrasound (US), can be used to assess muscle mass and quality and to achieve the diagnosis of sarcopenia. With different extent, all these modalities can provide quantitative data, being thus reproducible and comparable over time. DXA is the one most commonly used in clinical practice, with the advantages of being accurate and widely available, and also being the only radiological tool with accepted cutoff values to diagnose sarcopenia. CT and MR are considered the reference standards, allowing the evaluation of muscle quality and fatty infiltration, but their application is so far mostly limited to research. US has been always regarded as a minor tool in sarcopenia and has never gained enough space. To date, CT is probably the easiest and most promising modality, although limited by the long time needed for muscle segmentation. Also, the absence of validated thresholds for CT measurements of myosteatosis requires that future studies should focus on this point. Radiologists have the great potential of becoming pivotal in the context of sarcopenia. We highly master imaging modalities and know perfectly how to apply them to different organs and clinical scenarios. Similarly, radiologists should master the culture of sarcopenia, and its clinical aspects and relevant implications for patient care. The medical and scientific radiological community should promote specific educational course to spread awareness among professionals.Key Points• DXA is an accurate, reproducible, and widely available imaging modality to evaluate body composition, being the most commonly used radiological tool to diagnose sarcopenia in clinical practice• CT and MR are the gold standard imaging modalities to assess muscle mass and quality, but no clear cutoff values have been reported to identify sarcopenia, limiting the application of these modalities to research purposes• US has shown to be accurate in the evaluation of muscle trophism, especially in the thigh, but its current application in sarcopenia is limited

Non Fungible Tokens (NFTs) are digital assets that represent objects like art, collectible, and in-game items. They are traded online, often with cryptocurrency, and are generally encoded within smart contracts on a blockchain. Public attention towards NFTs has exploded in 2021, when their market has experienced record sales, but little is known about the overall structure and evolution of its market. Here, we analyse data concerning 6.1 million trades of 4.7 million NFTs between June 23, 2017 and April 27, 2021, obtained primarily from Ethereum and WAX blockchains. First, we characterize statistical properties of the market. Second, we build the network of interactions, show that traders typically specialize on NFTs associated with similar objects and form tight clusters with other traders that exchange the same kind of objects. Third, we cluster objects associated to NFTs according to their visual features and show that collections contain visually homogeneous objects. Finally, we investigate the predictability of NFT sales using simple machine learning algorithms and find that sale history and, secondarily, visual features are good predictors for price. We anticipate that these findings will stimulate further research on NFT production, adoption, and trading in different contexts.

This comprehensive review explores the various scenarios of atherosclerosis, a systemic and chronic arterial disease that underlies most cardiovascular disorders. Starting from an overview of its insidious development, often asymptomatic until it reaches advanced stages, the review delves into the pathophysiological evolution of atherosclerotic lesions, highlighting the central role of inflammation. Insights into clinical manifestations, including heart attacks and strokes, highlight the disease’s significant burden on global health. Emphasis is placed on carotid atherosclerosis, clarifying its epidemiology, clinical implications, and association with cognitive decline. Prevention strategies, lifestyle modifications, risk factor management, and nuanced antithrombotic treatment considerations are critical to managing cardiovascular complications, thus addressing a crucial aspect of cardiovascular health.

Plants generate energy flows through natural food webs, driven by competition for resources among organisms, which are part of a complex network of multitrophic interactions. Here, we demonstrate that the interaction between tomato plants and a phytophagous insect is driven by a hidden interplay between their respective microbiotas. Tomato plants colonized by the soil fungus Trichoderma afroharzianum, a beneficial microorganism widely used in agriculture as a biocontrol agent, negatively affects the development and survival of the lepidopteran pest Spodoptera littoralis by altering the larval gut microbiota and its nutritional support to the host. Indeed, experiments aimed to restore the functional microbial community in the gut allow a complete rescue. Our results shed light on a novel role played by a soil microorganism in the modulation of plant—insect interaction, setting the stage for a more comprehensive analysis of the impact that biocontrol agents may have on ecological sustainability of agricultural systems.

This paper shows that the level and timing of fertility are converging strongly over different measures of educational attainment using 65 years of data from 146 countries. Global convergence patterns are primarily driven by high-income societies, while sub-Saharan Africa is the world region that is converging most slowly, if not converging at all. Most importantly, levels of education matter heavily for explaining strength and variation in global fertility convergence, with two intersecting educational gradients suggesting: (i) stronger convergence over tertiary education followed, in turn, by secondary and primary; (ii) stronger convergence over education completed relative to education attended . Our findings provide important insights for addressing key challenges in global development and demography, and for informing policymakers as they evaluate the suitability of specific educational policies aimed at further narrowing inequalities between societies—such as supporting higher education as well as the successful completion of targeted educational cycles.

PurposeWe present an automated method for extracting anatomical parameters from biplanar radiographs of the spine, which is able to deal with a wide scenario of conditions, including sagittal and coronal deformities, degenerative phenomena as well as images acquired with different fields of view.MethodsThe location of 78 landmarks (end plate centers, hip joint centers, and margins of the S1 end plate) was extracted from three-dimensional reconstructions of 493 spines of patients suffering from various disorders, including adolescent idiopathic scoliosis, adult deformities, and spinal stenosis. A fully convolutional neural network featuring an additional differentiable spatial to numerical (DSNT) layer was trained to predict the location of each landmark. The values of some parameters (T4–T12 kyphosis, L1–L5 lordosis, Cobb angle of scoliosis, pelvic incidence, sacral slope, and pelvic tilt) were then calculated based on the landmarks’ locations. A quantitative comparison between the predicted parameters and the ground truth was performed on a set of 50 patients.ResultsThe spine shape predicted by the models was perceptually convincing in all cases. All predicted parameters were strongly correlated with the ground truth. However, the standard errors of the estimated parameters ranged from 2.7° (for the pelvic tilt) to 11.5° (for the L1–L5 lordosis).ConclusionsThe proposed method is able to automatically determine the spine shape in biplanar radiographs and calculate anatomical and posture parameters in a wide scenario of clinical conditions with a very good visual performance, despite limitations highlighted by the statistical analysis of the results.Graphical abstractThese slides can be retrieved under Electronic Supplementary Material.

Oxidative stress (OS) has been demonstrated to be involved in the pathogenesis of the two major types of dementia: Alzheimer’s disease (AD) and vascular dementia (VaD). Evidence of OS and OS-related damage in AD is largely reported in the literature. Moreover, OS is not only linked to VaD, but also to all its risk factors. Several researches have been conducted in order to investigate whether antioxidant therapy exerts a role in the prevention and treatment of AD and VaD. Another research field is that pertaining to the heat shock proteins (Hsps), that has provided promising findings. However, the role of OS antioxidant defence system and more generally stress responses is very complex. Hence, research on this topic should be improved in order to reach further knowledge and discover new therapeutic strategies to face a disorder with such a high burden which is dementia.

Sarcopenia is a progressive, generalized skeletal muscle disorder characterized by reduction of muscle mass and strength. It is associated with increased adverse outcomes including falls, fractures, physical disability, and mortality, particularly, in elderly patients. Nowadays, sarcopenia has become a specific imaging biomarker able to predict clinical outcomes of patients. Muscle fibre reduction has shown to be an unfavourable pre-operative predictive factor in patients with cancer, and is associated with worse clinical outcomes in terms of postoperative complications, morbidity, mortality, and lower tolerance of chemoradiation therapy. Several imaging modalities, including dual-energy X-ray absorptiometry, CT, MRI, and US can be used to estimate muscle mass and quality to reach the diagnosis of sarcopenia. This article reviews the clinical implications of sarcopenia, how this condition can be assessed through different imaging modalities, and future perspectives of imaging of sarcopenia.

The migration of Twitter users to Mastodon following Elon Musk’s acquisition presents a unique opportunity to study collective behavior and gain insights into the drivers of coordinated behavior in online media. We analyzed the social network and the public conversations of about 75,000 migrated users and observed that the temporal trace of their migrations is compatible with a phenomenon of social influence, as described by a compartmental epidemic model of information diffusion. Drawing from prior research on behavioral change, we delved into the factors that account for variations of the effectiveness of the influence process across different Twitter communities. Communities in which the influence process unfolded more rapidly exhibit lower density of social connections, higher levels of signaled commitment to migrating, and more emphasis on shared identity and exchange of factual knowledge in the community discussion. These factors account collectively for 57% of the variance in the observed data. Our results highlight the joint importance of network structure, commitment, and psycho-linguistic aspects of social interactions in characterizing grassroots collective action, and contribute to deepen our understanding of the mechanisms that drive processes of behavior change of online groups.