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This study investigated the interplay between dietary macronutrient composition, browse provisioning frequency, and host phylogeny in shaping the gut microbiome of zoo-housed colobine monkeys. We focused on four species (Colobus guereza, Colobus angolensis, Trachypithecus cristatus, and Trachypithecus francoisi) housed across 20 AZA-accredited institutions and integrated detailed dietary records with fecal microbiome profiling. Diets were categorized using Partition Around Medoids clustering based on macronutrient content, while browse offerings were classified by provisioning frequency (low, moderate, and high). Microbial diversity and community composition were evaluated using high-throughput 16S rRNA sequencing. The results revealed that browse provisioning frequency was the strongest predictor of microbiome alpha diversity, with moderate and high browse categories supporting significantly greater microbial richness and evolutionary breadth than low browse frequency. While diet cluster and phylogeny did not significantly affect alpha diversity metrics, all three factors significantly influenced the overall microbiome composition, as indicated by the unweighted and weighted UniFrac analyses. Notably, diet clusters with the highest relative crude fat (16.33%) or protein (23.27%) content, as well as sugar-rich diets promoted distinctive shifts in microbial community structure and function, fostering bacteria linked to dietary macronutrient processing, and in low-fiber contexts, reduce the abundance of key fiber-degrading taxa. These findings emphasize the necessity of frequent browse provision and an appropriate fiber balance to maintain gut microbial diversity and ecosystem stability in zoo-housed colobines. These results provide evidence-based recommendations for husbandry practices to promote nutritional and microbiome health in managed primate populations.
BACKGROUND: Personalized and precision medicine aim to identify predictive biomarkers from patient-specific proteogenomic profiles and to uncover tailored therapeutic strategies by targeting deregulated proteins driving disease phenotypes. METHODS: To address these challenges, we developed MultiOmicsXplorer, a freely available and interactive R-based Shiny application designed to facilitate the exploration and analysis of multi-omics cancer datasets with a user-friendly interface. At its core, MultiOmicsXplorer builds on our recently developed SignalingProfiler pipeline to extract protein activities from proteogenomic data, thereby reducing data complexity and dimensionality while enabling mechanistic hypothesis generation. RESULTS: The application integrates two core functionalities. The first, OncoXplorer, enables the systematic inference and comparison of protein activities from 1492 samples corresponding to approximately 1000 patients across ten cancer types, leveraging harmonized datasets from the CPTAC portal to provide a functional and mechanistic interpretation of multi-layered data. Importantly, beyond activity estimation, it allows for comparative analysis of transcriptomic, proteomic, and phosphoproteomic data. The second module, Extract Protein Activity from Your Data, enables users to infer the activity of kinases, phosphatases, and transcription factors from custom multi-modal datasets. CONCLUSIONS: Overall, MultiOmicsXplorer facilitates the exploration and interpretation of CPTAC multi-omics cancer datasets, supporting comparative analyses and protein activity inference within a unified and user-friendly environment.
Riparian willows (Salix spp.) in Yellowstone National Park have long been shaped by ungulate browsing, yet the specific contribution of individual herbivore species remains unclear. We applied a bite-DNA metabarcoding approach, extracting saliva DNA from browsed willow twigs, to directly identify the browsing community across six northern range riparian sites. Mammalian DNA was successfully assigned for more than half of the collected bite samples, revealing browsing by moose (Alces alces), North American bison (Bison bison), elk (Cervus canadensis), deer (Odocoileus sp.), bighorn sheep (Ovis canadensis), and jackrabbit (Lepus townsendii). Contrary to the traditional view of bison as primarily grazers, bite-DNA showed that bison were the most frequent browsers of willows, present at all sites and contributing the majority of browsing bites. Elk, historically considered the primary browser on riparian shrubs, were detected less often, whereas mule deer browsing was consistently recorded and frequently exceeded elk. Browsing height largely overlapped among species and was significantly higher for bighorn sheep than for bison and mule deer. Diameter of browsed twigs did not differ significantly between species. Browsing composition varied locally without clear spatial patterns, suggesting that site-level factors shape where different ungulates browse willows. Our results demonstrate substantial bison browsing on riparian willows and highlight shifting herbivore impacts on Yellowstone's riparian ecosystems.
The Toxicant Exposures and Responses by Genomic and Epigenomic Regulators of Transcription (TaRGET) program is a multiphase program that aims to understand how environmental factors contribute to disease susceptibility using toxicant-exposed mouse models. Here, we present the TaRGET II Data Portal ( https://data.targetepigenomics.org/ ), a comprehensive repository of multi-omics datasets generated from mice exposed to a range of environmental toxicants, including arsenic (As), lead (Pb), bisphenol A (BPA), tributyltin (TBT), di(2-ethylhexyl) phthalate (DEHP), tetrachlorodibenzo-p-dioxin (TCDD), and ambient air pollution (PM2.5). Epigenomic profiling assays capturing alterations in chromatin accessibility, DNA methylation, gene expression, and histone modifications were produced across multiple research centers, subjected to rigorous quality control, and processed using standardized pipelines. The portal currently hosts 3,612 datasets spanning multiple tissues and genomic assays, collected at four developmental and exposure time points: 3, 5, 20, and 40 weeks. The portal offers an efficient way to browse, search, visualize, and download relevant datasets and associated metadata, serving as a key resource for studying the impact of environmental toxicant exposures on disease susceptibility for the broader scientific community.
Considering transformation products (TPs) in environmental studies remains a huge challenge for scientists, from identification in samples via mass spectrometry to inclusion in chemical regulation. This article introduces FAIR-TPs, a Web site to browse openly available TP data collated from literature sources. The data is sourced from several community-contributed environmental data sets on the NORMAN Suspect List Exchange (NORMAN-SLE), plus a data set from ChEMBL available through PubChem, with links to templates and contact details to encourage further community contributions. The data are compiled regularly using an open source workflow, archived and versioned on Zenodo under a CC-BY license, then processed and displayed on FAIR-TPs. FAIR-TPs currently contains 11,190 reactions involving 9,435 compounds from 11 sources, covering human and environmental transformations through to high energy water treatment reactions. A graph-based representation of the transformations (compounds as nodes and reactions as edges) is stored in a Neo4j database as a Directed Graph and made publicly accessible online through a Django Web Application. Users can retrieve the shortest directed pathways between predecessors (parents) and successors (transformation products/metabolites), search by SMARTS substructures, or explore local reaction neighborhood data on individual compounds. Interactive network visualizations provide ways for users to view multistep transformations in a smooth, user-friendly interface, while exploring transformation pathways. The compound/reaction metadata provide links to further information about the chemicals and data sources. Key statistics, including number of reactions/compounds, top compounds, reaction types, and mass differences are summarized from the current data set. FAIR-TPs is designed to be a public resource to support suspect and nontarget screening workflows, helping scientists identify data gaps and interpret complex transformation reactions. The FAIR-TPs website is openly available at https://fairtps.lcsb.uni.lu.
Understanding retailer advertising has been identified as critical for developing effective policies to reduce tobacco product use, as these forms of advertising are among the tobacco industry's largest expenditures. Online retailer marketing has grown rapidly, and in this study, we sought to describe the marketing practices of these retailers. Between March and July 2022, we conducted keyword searches (e.g. 'buy e-cigs', 'buy vapes') with the Brave search engine, embedded in the Brave browser, to identify online tobacco retailers, using the inclusion criteria: English-language websites of online retailers selling e-cigarette products that allowed online ordering and the sale of products to customers in the United States. Measures included name, address, and landing page characteristics, including products, brands, product types, seasonal specials, social media links, age gating, and whether the retailer sold non-tobacco products. Results are reported descriptively. We identified 97 unique online tobacco retailers. Of these, 58 (60%) had set a restriction on browsing based on age. E-cigarettes, both disposable and reusable, were the most available products, followed by liquid nicotine ('vape juice'). Thirty-seven percent of online tobacco retailers sold cannabis products, and 38% of retailer websites listed other types of products for sale (e.g. bongs, dab rigs, cannabis apparel, psilocybin chocolates). Our findings indicated that online tobacco retailers heavily marketed flavored products, and a majority sold derived cannabis products. Future research should continue to investigate whether this marketing conflicts with stated federal regulatory goals, and whether the U.S. Food and Drug Administration should expand enforcement of existing regulations on tobacco and derived cannabis products.
Environmental toxicant exposures can induce widespread alterations in both the transcriptome and epigenome of mammals, and directly contribute to the increased risk of various diseases, including cardiovascular disorders, cancer, and neurological disorders. To evaluate how early-life toxicants produce long-term impacts on the transcriptome and epigenome in mice, the Toxicant Exposures and Responses by Genomic and Epigenomic Regulators of Transcription II (TaRGET II) Consortium generated a landmark resource comprising 3607 multi-omics datasets from longitudinal studies in mice. The molecular changes in responding to distinct environmental toxicants, including arsenic (As), lead (Pb), bisphenol A (BPA), tributyltin (TBT), di-2-ethylhexyl phthalate (DEHP), dioxin (TCDD), and fine particulate matter (PM2.5), were systematically identified and visualized on an integrative platform, ToxiTaRGET, to allow quickly search and browse by researchers. ToxiTaRGET houses a rich repository of molecular signatures, including gene expression, chromatin accessibility, and DNA methylation profiles, in response to early-life toxicant exposures. These molecular signatures span multiple biologically important tissues in both male and female mice at three distinct life stages, offering a valuable resource for the environmental health and toxicogenomic research communities.
Digital advertising finances much of the open web, yet relies on tracking technologies that regulators increasingly seek to restrict. In response, industry has developed privacy-enhancing technologies intended to preserve advertising performance while limiting data collection, but their economic effects remain largely untested. We study this question using an open, industry-wide field experiment jointly overseen by Google and the UK Competition and Markets Authority, in which Chrome users were randomly assigned to browse with third-party cookies enabled, with cookies disabled, or with Google's Privacy Sandbox replacing cookies. Combining this experimental variation with proprietary data from a major ad management firm, we analyze more than 200 million ad impressions across over 5,000 publishers worldwide. Removing third-party cookies reduces publisher advertising revenue by 29.1%. Privacy Sandbox recovers only 4.2% of this lost revenue; this estimate reflects observed adoption and performance during the study period and may reflect modest industry adoption. Privacy-preserving auctions also increase ad latency, reducing impression delivery and further limiting revenue performance. Together, these findings provide a large-scale experimental benchmark for evaluating privacy-preserving reforms and demonstrate the difficulty of reconciling privacy protection with the economics of online content provision.
In Kenya, the growing e-commerce market presents new opportunities to expand access to self-care contraceptives. However, we know little about women's experiences and attitudes toward purchasing such products online. We used a two-phased approach to explore Kenyan women's perspectives on e-commerce and its potential as a platform for contraceptive access. In the formative phase, we conducted 61 in-depth interviews with a diverse sample of reproductive-aged women to assess general perceptions of e-commerce and attitudes toward using it for contraceptive purchases. We analyzed formative data through an iterative coding process followed by thematic analysis of relevant codes reports. In the second phase, using a human-centered design (HCD) approach, we observed a smaller group of Nairobi-based women of reproductive age (n = 8) as they navigated the website of a women's health-focused digital commerce platform to explore products, access information and make purchases. Post-website use interviews captured participants' reflections on the experience. Research assistants compiled detailed notes from observations and interviews that the analysis team used to identify themes and build out analysis insights. While some participants in the formative phase noted the convenience of online shopping, many were skeptical of e-commerce due to concerns about fraud or their own limited digital literacy and internet access. Similar issues with digital accessibility surfaced in the HCD phase; however, after a brief tutorial and direct experience using the website to browse and make purchases, HCD participants reported more positive perceptions of e-commerce. They emphasized the privacy, convenience, and autonomy that online purchasing offered, noting that these features were especially beneficial for accessing contraception. Findings from the HCD phase highlight the potential for e-commerce to lessen the burden of external pressure from providers or family members on contraceptive decision-making and to help circumvent stigma-related barriers, especially for younger women. While HCD participants' increased confidence in and comfort with e-commerce after exploring the digital commerce platform indicates promise for this self-care contraceptive access pathway, barriers to use identified by participants in both phases underscore the need for such digital interfaces to be implemented with in-person introductions that can build trust and offer technical guidance.
Clinical pharmacy education originated in the United States during the 1950s and was introduced to China in the 1960s. In China, clinical pharmacy education encompasses degree-oriented and vocational education. The purpose of this study is to offer insights and references that may guide the future development of China's clinical pharmacy education. To acquire targeted and authoritative information, the study conducted a systematic literature and data retrieval process. This study searched academic databases, reviewed monographs on the history of pharmaceutical education, examined university archives, analyzed media reports, and browsed the official websites of educational institutions and healthcare facilities. Then this study classified, counted and analyzed the collected information according to the literature analysis method. Following a chronological framework, the study integrated the key policies and regulations, influential figures, and significant historical events that had shaped the development of degree-oriented and vocational education in China's clinical pharmacy. Findings reveal that China's degree-oriented education has evolved from a marginalized field to a multi-tiered and diversified training system. Likewise, vocational education has progressed from a fragmented and disorganized state into a more structured and standardized system. Nevertheless, significant challenges persist. Currently, universities and healthcare institutions often operate independently in the training of clinical pharmacists, lacking a unified and standardized educational model comparable to the Pharm. D. system in the US or the medical education system in China. There remains the absence of cohesive assessment standards and coordinated mechanisms across the country.
Brain-computer interfaces (BCIs) can provide naturalistic communication and digital access to people with severe paralysis by decoding neural activity associated with attempted speech and movement. Recent work has demonstrated highly accurate intracortical BCIs for speech and cursor control, but two critical capabilities needed for practical viability were unmet: independent at-home operation without researcher assistance and reliable long-term performance supporting accurate speech and cursor decoding. Here we demonstrate the independent and near-daily use of a multimodal BCI with novel brain-to-text speech and computer cursor decoders by a man with paralysis and severe dysarthria due to amyotrophic lateral sclerosis. Over nearly 2 years, the participant used the BCI for more than 3,800 h at home with no researchers present to maintain rich interpersonal communication with his family and friends, independently control his personal computer and sustain full-time employment-despite being paralyzed. He communicated 183,060 sentences-totaling 1,960,163 words-at an average rate of 56 words per minute. He labeled 92% of sentences as being decoded at least mostly correctly. In formal quantifications of performance where he was asked to say words presented on a screen, attempted speech was consistently decoded with more than 99% word accuracy (125,000 word vocabulary). The participant also used the speech BCI as keyboard input and the cursor BCI as mouse input to control his personal computer, enabling him to send text messages and emails and to browse the internet. These results demonstrate that intracortical BCIs have the potential to support independent use in the home, marking a critical step toward practical assistive technology for people with severe motor impairment.
Modern biomedical imaging workflows generate large volumes of derived images and short videos that must be reviewed, compared, curated, and reused following primary acquisition and analysis. In practice, these assets are often dispersed across nested filesystem hierarchies on local drives, external media, or network storage, limiting efficient retrieval, deduplication, and figure assembly. We present PixelDeck, an open-source, local-first browser application for organizing and interactively browsing large biomedical image and video libraries on commodity workstations. PixelDeck integrates recursive folder import, SHA-256-based duplicate detection, metadata extraction, thumbnail and preview generation, full-text search, and asynchronous export within a responsive interface, supported by a modular ingestion pipeline, managed storage layer, and interactive browsing environment optimized for high-volume media collections. The system is implemented using a Next.js and React frontend, a SQLite metadata store accessed via Prisma, managed local media storage, and a background worker that executes import and export tasks asynchronously, enabling scalable processing on standard hardware. To evaluate performance, we conducted structured benchmark imports using public histopathology images curated from PanopTILs, SICAPv2, and PanNuke datasets, where dataset-specific import behavior, duplicate detection, and ingestion metrics were recorded as reproducible outputs. Embedding-based analysis further demonstrates dataset-level separation consistent with underlying image characteristics. These results show that PixelDeck provides an efficient, scalable local curation layer for heterogeneous biomedical imaging collections, enabling streamlined dataset exploration and preparation for downstream analysis.
The Cas9 nuclease has become central to modern methods and technologies in synthetic biology, largely due to the ease with which it can be targeted to specific DNA loci via guide RNAs (gRNAs). Reports vary widely on the actual specificity of this targeting, with some studies observing 60% of gRNAs possessing no activity against the genome, yet an assumption persists within the E. coli community that inactive gRNAs are rare. To resolve these contradictions, we evaluated the activity of 463 000 unique gRNAs in the E. coli K12 MG1655 genome. We show that the overwhelming majority (at least 93%) of unique gRNAs are functional while only 0.3% are nonfunctional. These nonfunctional gRNAs exhibit strong spacer self-interaction, which can either be excluded using a simple design rule or "repaired" during library design. Finally, this work provides the greater microbial synthetic biology community both a set of nearly half a million empirically evaluated E. coli gRNAs as well as a thoroughly evaluated experimental procedure, complete with appropriate controls for Cas9 activity, for conducting Cas9 assays in E. coli specifically and bacteria more generally. Lastly, we have produced a webapp to allow users to easily browse and extract gRNA sequences from the E. coli genome, which can be accessed at https://grna.ornl.gov.
Pharmacotherapy induces complex molecular reprogramming in cancer, driving transcriptome-wide alterations and widespread dysregulation of alternative splicing. Despite these profound changes, there remain limited resources characterizing drug-induced whole-transcriptomic responses in cancer. Furthermore, while aberrant splicing can generate immunogenic neoantigens, existing resources fail to systematically integrate drug perturbations, splicing dynamics, and neoantigen landscapes. To address this gap, the DRIVE database was constructed as a comprehensive resource detailing drug-induced transcriptomic and splicing responses. Utilizing the large language models for rigorous metadata curation and construct the standardized processing pipeline, thousands of publicly available raw transcriptomic datasets from drug-treated and control cancer cell lines were systematically processed. The resulting repository encompasses 3,911 samples, involving 278 drugs and 272 cell lines, enabling the precise quantification of differential gene expression, differential alternative splicing events, and the prediction of splicing-derived human leukocyte antigen-binding peptides. Analysis of the data revealed that drug-induced transcriptomic reprogramming is highly context-dependent and correlated with chemical structural similarity. We identified Osimertinib as a potential immunomodulatory agent associated with transcriptional signatures of an activated tumor microenvironment, while KB-0742 emerged as an unappreciated candidate global splicing modulator. Furthermore, our large-scale prediction of differential splicing-derived neoantigens uncovered several drugs that warrant further investigation as candidates for combination immunotherapy. DRIVE also provides a user-friendly interface to browse datasets, perform drug enrichment and connectivity analysis. (https://componclab.com/DRIVE). This database could improve our understanding of molecular reprogramming under pharmacotherapy, and serve as a valuable platform for deciphering drug mechanisms, promoting virtual cell modeling and discovering novel strategies of drug repurposing.
Gut dysbiosis is widely recognized as a contributor to autoimmune diseases, as it can lead to the expression of microbial antigens that disrupt immune regulation through specific molecular mechanisms. However, existing resources do not systematically link gut microbial antigen sequences to the specific autoimmune mechanisms through which they act. Here, we present GUTAID (Gut Microbes in Autoimmune Disorders), a literature-curated database of gut microbial antigens annotated with experimentally supported autoimmune mechanisms. Peer-reviewed studies published from October 1970 to September 2024 were manually screened, yielding 73 potential antigens that operate through nine molecular mechanisms, including protein citrullination, epitope spreading, molecular mimicry, and immune modulation, amongst others. The corresponding protein sequences were retrieved from UniProtKB, and redundancy was removed with MMseqs2. For the database implementation, data were delivered through a lightweight LAMP (Linux-Apache-MySQL/MariaDB-PHP) stack with server-side HTML/Bootstrap rendering, MySQL indexing, and HTTPS-secured downloads. Users can browse, keyword-search, or bulk-download sequence archives via a five-tab interface (Home, Downloads, Search, Team, and About). GUTAID thus enables mechanism-oriented exploration of gut microbial antigens and supports downstream biomarker and therapeutic discovery in autoimmune research. Database URL:  https://gutaid.mgdiscoverylab.com/.
Feed availability and quality remain major constraints to ruminant productivity in West Africa, where livestock systems rely heavily on locally available resources such as natural forages, crop residues and agro-industrial by-products. However, reliable ration formulation requires accurate information on feed chemical composition, while existing data are fragmented and highly variable. This study conducted a systematic review of peer-reviewed literature published between 2000 and 2025 to synthesize available data on the chemical composition of ruminant feeds in West Africa. Following PRISMA guidelines, 44 studies reporting quantitative feed composition data were retained. Feed resources were classified into agro-industrial by-products, agricultural by-products and forages, and descriptive statistics were calculated for key nutritional parameters. The results revealed substantial variability in nutrient composition across feed types and even within the same feed resource. Cottonseed cake emerged as a major protein-rich supplement, legume haulms showed higher nutritional value than cereal residues, and several browse species such as Moringa oleifera and Leucaena leucocephala demonstrated high protein potential. These findings highlight that fixed feed composition values are poorly suited to heterogeneous tropical feeding systems. The reference ranges established in this review provide a more reliable basis for feed evaluation and ration formulation and can support the development of locally adapted feeding strategies and decision-support tools for West African livestock systems.
Insect symbionts play essential roles in host biology, influencing nutrition, immunity, reproduction, and environmental adaptation, ultimately shaping insect physiology, ecology, and evolution. With the rapid growth of functional and genomic datasets on insect symbionts, there remains a critical need for a dedicated platform to systematically compile, organize, and analyze these datasets from an integrative ecological perspective. Here, we developed an insect Symbiont database, named as iSymBase, by manually curating functional records and genomic datasets of insect symbionts from published academic literature. Currently, iSymBase contains over 2657 insect symbiont functional records spanning 795 host species, along with 1494 metagenomes, 14 992 amplicon datasets, and standardized genome and gene catalogs, providing a comprehensive resource for ecological and comparative insect symbiont researches. iSymBase offers standardized query functionalities, such as data browsing, keyword associative search, sequence alignment, data download, and submission. Beyond conventional database functionalities, iSymBase provides several innovative tools: insect-symbiont interaction network for host-symbiont ecological relationships, a batch annotation tool for detecting ecologically functional symbionts from microbiome profiles, and an artificial intelligence (AI)-powered chatbot iSymSeek designed to assist researchers with related knowledge queries. Taken together, iSymBase will serve as an open-access and continually updated platform for storing, querying, and analyzing insect symbiont data, supporting ecological exploration of host-symbiont interactions, symbiont functional diversity, and microbiome-driven adaptation. Database URL: http://symbiont.insect-genome.com/.
Mesoherbivores are expanding globally through both native population irruptions and alien introductions, yet their broad-scale ecological impacts remain poorly resolved. We assessed how native white-tailed deer (Odocoileus virginianus) and alien wild pigs (Sus scrofa) influence forest understoreys across the eastern United States by integrating forest inventory and analysis plots, large-scale camera-trap monitoring and environmental data. Deer generally reduced native seedling abundance, although this effect weakened in warmer-wetter or more human-dense environments. Conversely, deer tended to increase invasive plant abundance and richness, consistent with selective browsing on palatable native species combined with the resistance of many common invaders. In contrast, wild pigs typically suppressed invasive plant abundance and richness, while their effects on native seedlings were neutral and strongly context dependent, consistent with their rooting behaviour and broad diet. These contrasting outcomes persisted after accounting for climate, human pressure and forest structure, supporting an important role of mesoherbivores in structuring understorey communities. Collectively, our findings indicate that native and alien mesoherbivores exert divergent and environmentally contingent effects on forest regeneration and plant invasion. Recognizing species identity, functional traits and environmental context will be essential for anticipating mesoherbivore impacts and managing forest biodiversity under global change.
Given concerns that screen time may impact dietary habits, this study investigated the association between screen time and dietary intake among adolescents in the United States. We analyzed a prospective cohort (N = 6485, 47.3% female, age: 12 ± 0.7 years) from the Adolescent Brain Cognitive Development (ABCD) Study, using data from Year 2 (2018-2020) and Year 3 (2019-2021). Multinomial logistic regression models estimated the associations between participant-reported screen time (watching television shows and videos, playing video games, socializing, browsing the internet, and total screen time (hours/day)) and parent/participant-reported intake of various food/nutrient categories 1 year later (Year 3). We adjusted for age, sex, race and ethnicity, household income, parent education, average daily kilocalorie intake, respective food or nutrient, and study site (Year 2). Each additional hour of most screen time modalities was prospectively associated with higher odds of consuming fewer fruits, vegetables, whole grains, legumes, fiber, and dairy, and higher glycemic index, and higher odds of consuming more added sugars and a higher polyunsaturated fats ratio 1 year later. These findings highlight the need for parental guidance and clinical interventions to support screen time habits and promote healthy dietary choices among adolescents. This study examines the association between contemporary screen time modalities and dietary intake 1 year later in a demographically diverse U.S. sample of early adolescents. Most screen time modalities, such as total screen time and watching television shows and videos, were prospectively associated with higher odds of consuming fewer fruits, vegetables, whole grains, legumes, and fiber 1 year later. Greater total screen time and time spent socializing were prospectively associated with higher odds of a higher polyunsaturated fats ratio 1 year later.
Mobile apps not only offer numerous benefits but also entail the risk of sharing sensitive data with third parties. This research addresses which factors shape privacy trade-offs among young adults and adults when downloading apps. The investigation involved two experimental vignette studies: In Study 1 (N = 500, 79.6% women), we examined young adults, mostly university students, aged 16-29 years to assess if low and high privacy-ratings for apps recommended by friends or a social media platform and offering relevant developmental opportunities affect the probability of downloading them. In Study 2 (N = 148, 70.9% women), we examined users aged 18-69 years to assess if low and high privacy-rated apps recommended by friends or found when browsing online, age-related differences, and privacy resignation affect the probability of sharing data with them. In both studies, we found that participants considered privacy ratings when deciding whether to download or share data with an app. While Study 1 found no differences for apps offering relevant developmental opportunities, both studies show a higher reported probability of downloading and sharing data with apps when these were recommended by friends compared to the control conditions (social media platform; browsing). Additionally, Study 2 demonstrated that participants under 29 years of age and with higher levels of resignation exhibited a higher probability of sharing data. These findings highlight that privacy ratings can support privacy decisions at the app download stage, but also emphasize the need for future interventions, especially for younger and resigned users.