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The growing and pervasive use of social network sites (SNS) has raised concerns about their impact on adolescent mental health during this sensitive developmental phase. Existing longitudinal studies are constrained by methodological limitations and limited exploration of underlying mechanisms. We investigated the longitudinal associations between SNS use and depressive and anxiety symptoms in adolescents and whether sleep mediated these associations. We analysed longitudinal data from 2350 adolescents from 31 schools in London, participating in the Study of Cognition, Adolescents, and Mobile Phones (SCAMP). The exposure was self-reported duration of SNS use at baseline (aged 11–12 years). Outcomes were depressive and anxiety symptoms at follow-up, analysed as symptom severity and clinically significant symptoms (aged 13–15 years). The associations between SNS use and depressive and anxiety symptoms were assessed via multi-level ordinal logistic regression (symptom severity) and logistic regression (clinically significant symptoms). The mediation effects of insufficient sleep, sleep onset latency, and sleep disturbance were assessed by mediation analysis. Compared to 0–30 min per day, more than 3 h per day of SNS use at baseline was associated with higher severity levels of depressive and anxiety symptoms (adjusted odds ratio (OR) = 1.47, 95
This study investigates the social patterning of environmental exposures, examining how three socioeconomic position dimensions influence exposure to air pollution, road traffic noise, and availability of green spaces, in both urban and rural areas in England, Scotland, and Wales. Using data from the UK Biobank cohort study, we assessed associations between three individual markers of socioeconomic position: educational attainment, household income, and employment status, and three environmental exposure domains: residential airborne pollutants, residential road traffic noise, and residential green and blue space. In urban areas, participants with lower educational attainment, lower household income, or those who were unemployed exhibit a higher exposure to airborne pollutants. Household income also influences the vicinity to green spaces and natural environments, with lower incomes experiencing less green and natural environments in both the rural and urban contexts. Retired individuals experienced lower exposure to airborne pollutants and lived in areas with more green spaces or natural environments compared with employed individuals. These patterns were consistent across England, Scotland, and Wales, although some geographical and national differences were observed. The study highlights the complex interplay among socioeconomic factors, geographical location, and environmental exposures. Our findings suggest that socioeconomic position is a key determinant of specific external exposomes, with socioeconomically disadvantaged groups experiencing more adverse environmental conditions.
In vitro antibiotic testing is important for guiding therapy and drug development. Current methods are focused on growth inhibition in bulk bacterial populations but often fail to accurately predict treatment responses. Here we introduce Antimicrobial Single-Cell Testing (ASCT), a large-scale live-cell imaging approach that quantifies bacterial killing in real time at single-cell resolution. By tracking over 140 million mycobacteria and analysing ~20,000 time–kill curves, we identify key determinants of antibiotic killing and its clinical relevance. For Mycobacterium tuberculosis, we found that drug-specific killing dynamics in starved bacteria, rather than growth inhibition or killing of growing cells, predict regimen efficacy in mice and humans. Extending this approach to Mycobacterium abscessus and comparing 405 bacterial strains, we show that antibiotic killing is also a genetically encoded bacterial trait (drug tolerance). We demonstrate that tolerance patterns cluster by antibiotic targets, identify a phage protein that modulates antibiotic killing, and show that strain-specific killing dynamics are associated with individual patient outcomes independent of drug resistance. Together, these findings establish a framework that reveals how drug properties and bacterial diversity shape treatment responses, offering a path to more effective and personalized therapies. Via high-throughput imaging and tracking over 140 million single mycobacteria, the authors show that drug- and strain-specific killing predict treatment outcomes, with potential to improve drug development and personalized therapy.
BACKGROUND:Ultrafine particles (≤100 nm diameter) may have a higher toxicity than larger particles but are still not regulated nor part of routine air pollution monitoring. So far, health effects of long-term exposure to ambient ultrafine particles are not well understood, owing to a lack of exposure data and epidemiological studies. METHODS:We conducted a systematic review and meta-analysis on the health effects of long-term exposure to ultrafine particles, including studies published until December 2024. A meta-analysis was conducted for outcomes with at least four available effect estimates. Confidence in the body of evidence was evaluated using the Office of Health Assessment and Translation method. RESULTS:We identified 85 studies investigating various mortality, morbidity and subclinical outcomes. In meta-analyses of single-pollutant models, we found positive associations with natural mortality (hazard ratio 1.06, 95% CI 1.04-1.08) and C-reactive protein (10.14% increase (95% CI -0.51-21.99%) per 10 000 pt·cm-3 increase in long-term exposure to ultrafine particles, with low and inadequate levels of evidence, respectively. The remaining studies revealed overall limited evidence for adverse effects on a wide range of outcomes. Less than half of the studies adjusted for co-pollutants. CONCLUSION:The evidence base on long-term health effects of ultrafine particles has increased substantially in the past decade, while the overall evidence for independent effects of long-term ultrafine particle exposure remains inadequate to low. More studies are needed to draw firm conclusions about the independent adverse effects of long-term ultrafine particles on various health end-points, with a special focus on the influence of co-pollutant adjustment.
Dientamoeba fragilis is a protozoan of the human digestive tract, yet its transmission and pathogenic role remain poorly understood. This study aimed to evaluate its impact on the efficacy and safety of fecal microbiota transplantation (FMT) in treating recurrent Clostridioides difficile infection (rCDI). This longitudinal cohort study analyzed stool samples from FMT donors and recipients pre-treatment and at 2 and 8 weeks post-FMT. All samples were retrospectively tested using real-time PCR. Shotgun metagenomics was also performed on selected donor-recipient pairs to explore transmission. CDI cure rates, gastrointestinal adverse events (AEs), and serious adverse events (SAEs) were assessed prospectively. A total of 53 FMT were analyzed (179 samples), with 23 (43%) derived from D. fragilis-positive donor stool (4 of 10 donors, 40%). Four of 52 recipients (18.2%), initially negative and who received treatment from positive donors, tested positive post-FMT. Shotgun metagenomics could not definitely confirm transmission due to the lack of a good reference genome. No significant differences in efficacy, AE, or SAE were observed between FMT from D. fragilis-positive versus -negative donors, even in immunocompromised patients. No SAEs were attributed to FMT. D. fragilis may be transmitted via FMT without evidence of short-term clinical impact. Consequently, RT-PCR detection should be interpreted cautiously in the context of donor exclusion decisions.
