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Single extracellular vesicle imaging via rolling circle amplification–expansion microscopy

Deep learning reveals that multidimensional social status drives population variation in 11,875 US participant cohort

As an increasing realization, many behavioral relationships are interwoven with inherent variations in human populations. Presently, there is no clarity in the biomedical community on which sources of population variation are most dominant. The recent advent of population-scale cohorts like the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) are now offering unprecedented depth and width of phenotype profiling that potentially explains interfamily differences. Here, we leveraged a deep learning framework (conditional variational autoencoder) on the totality of the ABCD Study® phenome (8,902 candidate phenotypes in 11,875 participants) to identify and characterize major sources of population stratification. 80% of the top 5 sources of explanatory stratifications were driven by distinct combinations of 202 available socioeconomic status (SES) measures; each in conjunction with a unique set of non-overlapping social and environmental factors. Several sources of variation across this cohort flagged geographies marked by material poverty interlocked with mental health and behavioral correlates. Deprivation emerged in another top stratification in relation to urbanicity and its ties to immigrant and racial and ethnic minoritized groups. Conversely, two other major sources of population variation were both driven by indicators of privilege: one highlighted measures of access to educational opportunity and income tied to healthy home environments and good behavior, the other profiled individuals of European ancestry leading advantaged lifestyles in desirable neighborhoods in terms of location and air quality. Overall, the disclosed social stratifications underscore the importance of treating SES as a multidimensional construct and recognizing its ties into social determinants of health.

Isoreticular moiré metal-organic frameworks with quasiperiodicity

Stabilized and unstabilized sampling methods result in differential fecal 16S rRNA microbial sequencing results

Over the past decade, studies have been conducted to increase the understanding of associations between the fecal microbiome and human health. In conjunction, researchers have investigated the effects of study design, methods, molecular processing, and sequencing techniques. However, a lack of standardization of fecal sample collection methodology has introduced heterogeneity in sequencing results. Sources of variability include sample collection methods, storage temperatures, and transport times. Here we present 16S rRNA gene amplicon sequencing results from two sample collection methods (unstabilized sterile swab and stabilized OmniGene Gut Kits) collected from the same fecal specimens. The paired samples were collected either at the research facility or the participants’ home and ground shipped to the research facility at ambient temperature. Therefore, samples were exposed to variable temperatures and transport times. We found that fecal sample collection methods resulted in taxonomic and diversity differences that showed distinct patterns between swab and OmniGene samples. Swab samples were disproportionally affected by increased transport time, but differences in taxa and diversity were driven more by sample collection method, as compared to transport time. Based on previous studies, many of the taxa that were associated with sample collection methods and transport times have clinical relevance. Collectively, this research highlights: 1) the need for further standardization of methods for fecal microbiome studies; 2) limitations of direct comparisons between different fecal sample collection methods; and 3) the importance of careful consideration of sample collection methods for future studies and meta-analyses.

CYP1B1-AS1 regulates CYP1B1 to promote Coxiella burnetii pathogenesis by inhibiting ROS and host cell death

Can working in agriculture have a favorable effect on depressive symptoms? Life satisfaction as a mediator

Purpose Several studies have explored the relationship between various aspects of work and the onset of depressive symptoms. However, there is a lack of research focusing on the association between job types and depressive symptoms. This study aims to investigate the impact of agricultural work on depressive symptoms and whether life satisfaction mediates this relationship. Methods Data were obtained from the 2015 China Health and Retirement Longitudinal Study (CHARLS) (n = 6856). Participants were categorized based on whether they were engaged in agricultural or non-agricultural work and further classified as self-employed or employed. Depressive symptoms and life satisfaction were assessed using the CES-D and SWLS scales. Logistic regression analysis was used to examine associations, and Baron and Kenny’s mediation test and the Sobel test were used to assess the mediating effect of life satisfaction. Results Engaging in agricultural work was positively associated with increased depressive symptoms scores (B = 3.437, p < 0.001), indicating that agricultural work exacerbates depressive symptoms. This effect was partially mediated by life satisfaction. Conclusions Self-employed agricultural workers are a high-risk group for depressive symptoms. Additionally, life satisfaction plays a mediating role between type of job and depressive symptoms. Public health recommendations aimed at improving or mitigating depressive symptoms among agricultural workers could focus on enhancing life satisfaction to promote healthier psychological status.

Smart phosphor with neuromorphic behaviors enabling full-photoluminescent Write and Read for all-optical physical reservoir computing

Accuracy and real time optimization of remote sensing image change detection based on IRAU and DSC

Image change detection is one of the important application branches of remote sensing technology in many fields. However, in complex environments, remote sensing image change detection is often subject to various interferences, resulting in low accuracy and poor real-time performance of detection results. The research focuses on the advantages and problems of residual networks and depth-wise separable convolution modules, designs a new remote sensing image change detection model, and finally sets up experiments for verification. The average accuracy of the proposed detection model before and after training convergence was 0.54 and 0.97. The accuracy of repeated detection ranged from 95.82% to 99.68%, and the area under curve of the model was 0.90. However, after removing the integrated residual attention unit and depth-wise separable convolution, the accuracy decreased by 1.91% and the latency increased by 117ms. In addition, the detection efficiency of the model for different elements ranged from 0.91 to 0.94, with high accuracy in detecting changes in spatial and temporal scales and small offsets. The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. In summary, the proposed change detection model significantly improves the accuracy and real-time performance of remote sensing image processing, contributing to the expanded application of remote sensing dynamic detection technology in fields such as ocean monitoring and ecological research.

Multivalent interactions with CCR4–NOT and PABPC1 determine mRNA repression efficiency by tristetraprolin

Abstract Tristetraprolin family of proteins regulate mRNA stability by binding to specific AU-rich elements in transcripts. This binding promotes the shortening of the mRNA poly(A) tail, or deadenylation, initiating mRNA degradation. The CCR4–NOT complex plays a central role in deadenylation, while the cytoplasmic poly(A)-binding protein PABPC1 typically protects mRNAs from decay. Here, we investigate how tristetraprolin interacts with CCR4–NOT and PABPC1 to control mRNA stability. Using purified proteins and in vitro assays, we find that tristetraprolin engages CCR4–NOT through multiple interaction sites and promotes its activity, emphasizing the importance of multivalent binding for efficient deadenylation. Phosphorylation of tristetraprolin does not affect its interaction with CCR4–NOT or its deadenylation activity, but is essential for tristetraprolin’s binding to PABPC1. We propose that tristetraprolin promotes the processive deadenylation activity of CCR4–NOT on mRNAs containing AU-rich elements, with phosphorylation-dependent interactions with PABPC1 potentially enhancing deadenylation and promoting regulated mRNA decay.

Influential node identification method based on multi-order neighbors and exclusive neighborhood

In a complex network, the identification of node influence and the localization of key nodes play a crucial role in analyzing network structure and determining the positioning of nodes for information transmission control, resource redistribution, and network regulation. In this study, we propose a method for identifying influential nodes called “Multi-order Neighbors and Exclusive Neighborhood” (MNEN) after analyzing and investigating existing methods in the field. The MNEN method calculates a node’s influence based on two factors: the node itself, its neighboring nodes, and its exclusive neighborhood. The influence of the node itself is determined by its degree value and K-shell (Ks) value, while the influence contribution of the neighbor node is calculated based on its degree value, Ks value, and the contribution from its exclusive neighbor node. To evaluate the algorithm’s performance, we employ the SIR model as the benchmark and conduct simulation experiments to validate the MNEN method, comparing the results with other influential node identification methods. Our analysis demonstrates that the algorithm accurately identifies influential nodes in networks of different scales, yielding a positive overall impact and demonstrating a certain level of universality.

The topological properties of the protein universe

Dynamics of fungal bioaerosols in Kuwait City: An 8-year survey

Fungi are ubiquitous eukaryotic microorganisms that are often implicated in a wide range of diseases. Exposure to fungal bioaerosols is often associated with conditions such as asthma, allergic rhinitis, keratitis, and pneumonitis, among others. This study aims to shed some light on the configuration of airborne culturable fungal genera in the atmosphere of Kuwait City with analysis of seasonal patterns, intra-diurnal variations and correlations with meteorological factors. Outdoor fungal bioaerosols samples were collected twice a day, two times a week, from January 2016 to December 2023 via volumetric active sampling in Al-Sabah Medical District, Kuwait City, Kuwait. The meteorological data were supplied by Kuwait Meteorological Department, Directorate General of Civil Aviation. The rates of fungal bioaerosols remained relatively high during the months of March, April and May, ranging from 269 to 296 CFU/m3. Cladosporium, Aspergillus and Alternaria were the most common fungal genera in the atmosphere, with a prevalence of 49%, 16% and 14%, respectively. Statistically significant differences (p < 0.05) in fungal composition between intra-diurnal periods were demonstrated in most monthly analyses. A strong negative correlation was demonstrated with temperature and haze events. Conversely, positive correlations were observed with relative humidity, wind action, rainfall and dust phenotypes. Fungal dynamics in relation to seasonality and intra-diurnal variations require further elucidation. Collaborative research is needed to advance our understanding of the implications of elevated rates of fungal bioaerosols, the seasonality of specific fungal allergens and what may be suitable means of mitigation. Efforts such as this study will hopefully help facilitate regionally specific air quality management decisions and provide baseline information for health-care providers.

Microtubule mechanotransduction refines cytomegalovirus interactions with and remodeling of host chromatin

Reducing meat consumption: Results from a German survey on attitudes, behaviour and willingness to change among adults

Background Individual meat consumption in Germany has fallen slightly in recent years, but still exceeds the recommended quantities. High meat consumption has negative impacts both on human health and the environment. This study intends to identify which population groups in Germany may have already reduced their meat consumption, based on which motives, and to capture the willingness to limit future consumption. Methods Analyses are based on representative data from 3,178 adults living in Germany, collected in a cross-sectional, standardized telephone survey (German Health Update) in 2022. Differences between population groups are identified using chi-squared tests and logistic regression models. Results are presented with 95% confidence limits. Results 72% of the population intentionally avoid meat consumption at least occasionally. About half of the population intends to eat less meat in the future or already never eat meat. 23% have no current or future intention to limit their meat consumption. Women and higher educated persons more often claim to intentionally avoid meat consumption, currently and for the future. Those who currently eat meat less often are more likely to intend further reduction compared to those who eat meat frequently. The predominant motive for reducing meat consumption is “health” followed by “climate and environmental protection” and “animal welfare”. Climate protection as a motive for reducing meat consumption is more often mentioned by young persons and women, whereas health benefits are more important for persons aged 65 years and older. Conclusion A large proportion of the population already cuts down on meat consumption, at least occasionally. On the other hand, consumption levels in Germany are still very high. Climate and environment protection already play an important role for meat reduction, and may help leverage the transition to a more plant-based and healthier diet in the population.

Controllable gliders in a nanomagnetic metamaterial

Abstract Artificial Spin Ice (ASI) are promising metamaterials for neuromorphic computing, composed of interacting nanomagnets arranged in the plane. Every computing device requires the ability to transform, transmit and store information. While ASI excel at data transformation, their transmission and storage capabilities have been lacking. Here, we take inspiration from Cellular Automata, where information transmission and storage can be realised by the glider, a simple moving structure. Employing an evolutionary algorithm, we discover the snake, a glider in pinwheel ASI. The snake is controlled by a global field protocol, providing precise manipulation of a magnetic texture on the order of 100 nm. We present the snake, both in simulation and experimentally, investigate the mechanism behind its movement and its robustness to disorder. Finally, we demonstrate how the snake can be exploited for computation and memory. The snake enables the integration of information transmission, storage and transformation into one magnetic substrate, unlocking the potential for ultra-low power computing devices.

Galectin-3 did not associate with malaria-related insulin resistance in diabetic and non-diabetic respondents at a Ghanaian General Hospital

Background Malaria remains endemic in the sub-Saharan African region. The region also faces the world’s highest increase in incidence of type 2 diabetes mellitus (T2DM). Although galectin-3 has been explored in numerous conditions, scientific information on the relationship between malaria-related insulin resistance and circulating galectin-3 levels is limited. Therefore, the current study examined the association between galectin-3 and insulin resistance in diabetic and non-diabetic adults with or without malaria at the Tema General Hospital. Methods Anthropometric indices, blood pressure, glucose, full blood count (FBC), lipid profile, insulin and galectin-3 levels were measured under fasting conditions. Insulin resistance and beta-cell function were assessed using the homeostatic model assessment of insulin resistance (HOMA-IR) and beta-cell function (HOMA-B) formulae. Results Participants with T2DM were older (P < 0.05) with higher levels of systolic blood pressure and glucose but lower parasite levels than their non-diabetic counterparts. Irrespective of diabetes status, levels of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and galectin-3 were higher but triglyceride level was lower in participants with malaria. Levels of insulin, HOMA-B and HOMA-IR were highest for diabetics without malaria with high strengths of the associations. Galectin-3 could neither predict HOMA-B nor HOMA-IR in any of the study groups. Irrespective of malaria or diabetes status, insulin resistance associated with glucose (B = 0.603, Wald = 10.52, Exp (B) = 1.83, CI: 1.27–2.63; P = 0.001) and insulin (B = 1.145, Wald = 18.61, Exp (B) = 3.14, CI: 1.87–5.23; P < 0.001) levels in our context with the model explaining 67.7% (Cox & Snell R2 = 0.677) to 91% (Nagelkerke R2 = 0.91) of the observed variation. Conclusion The relationship of galectin-3 with HOMA-IR and HOMA-B appears more complex than a linear fashion in our setting.

Structural insights into SSNA1 self-assembly and its microtubule binding for centriole maintenance

Abstract SSNA1 is a fibrillar protein involved in dynamic microtubule remodeling, including nucleation, co-polymerization, and microtubule branching. The underlying molecular mechanism has remained unclear due to a lack of structural information. Here, we determine the cryo-EM structure of C.elegans SSNA-1 at 4.55-Å resolution and evaluate its role in embryonic development. We find that SSNA-1 forms an anti-parallel coiled-coil, with self-assembly facilitated by an overhang of 16 C-terminal residues that form a triple-stranded helical junction. The microtubule-binding region is within the triple-stranded junction, suggesting that self-assembly of SSNA-1 creates hubs for effective microtubule interaction. Genetical analysis elucidates that SSNA-1 deletion significantly reduces embryonic viability, and causes multipolar spindles during cell division. Interestingly, impairing SSNA-1 self-assembly has a comparable effect on embryonic viability as the knockout strain. Our study provides molecular insights into SSNA-1’s self-assembly and its role in microtubule binding and cell division regulation through centriole stability.

Korean and Chinese citizens’ pandemic fatigue and related factors amidst the prolonged COVID-19 pandemic: Implications for risk communication

Pandemic fatigue has emerged as a significant public health challenge, particularly in countries that implemented prolonged COVID-19 public health and social measures (PHSM). Understanding the factors contributing to pandemic fatigue and its impact on adherence to health protective behaviors is essential for sustaining public engagement in long-term disease management. This study examines pandemic fatigue in China and South Korea, two countries that maintained prolonged COVID-19 public health and social measures, to identify key predictors and explore its relationship with health protective behaviors. Online surveys were conducted in March 2023 to measure pandemic fatigue levels. To examine the relationships between pandemic fatigue, its predictors (perceived risk, efficacy beliefs, and daily life changes), and health protective behaviors, linear regression and mediation effect analyses were performed. The results indicated that the level of pandemic fatigue was 3.67 in South Korea and 3.47 in China, which was higher than previous research. High efficacy beliefs were associated with lower pandemic fatigue in both countries, while daily life changes had mixed effects. Pandemic fatigue has a significant impact on the adoption of health protective behaviors, with the exception of the practice of resting when unwell. The findings highlight the necessity of reinforcing efficacy beliefs through risk communication for a sustainable pandemic response. Given that risk perception declined over time, traditional fear-based health messages may be less effective in prolonged pandemics. Instead, risk communication strategies that emphasize a sense of control and provide clear, actionable guidance may help sustain public engagement. Furthermore, addressing the daily life changes faced by citizens and creating environments that facilitate the adoption of health-protective behaviors (e.g., access to paid sick leave) are important as long-term pandemic strategies.

Cellulose hydrogel with in-situ confined nanopores for boosting moist-electric conversion

Passage of human-origin influenza A virus in swine tracheal epithelial cells selects for adaptive mutations in the hemagglutinin gene

Frequent spillover of influenza A viruses from humans to swine contributes to the increasing diversity of influenza viruses circulating in pigs. Although these events are common, little is known about the adaptation processes that take place when viruses jump between the two species. We examined the changes that occurred during serial passages of a reassortant H3N2 virus (VIC11pTRIG) containing human seasonal surface genes (Hemagglutinin and Neuraminidase) and a swine-adapted internal gene constellation in differentiated primary swine tracheal epithelial cells (pSTECs). The VIC11pTRIG reassortant virus was serially passaged 8 times in pSTECs and compared to a control swine-adapted strain (OH/04p) containing the same internal gene constellation. Viral RNA from passages 0 (inoculum), 1, 3, 4–8 were sequenced via next generation or Sanger sequencing. Hemagglutinin diversity was highest at passage 3. Two amino acid mutations in the Hemagglutinin protein (N165K and N216K) were fixed at passages 7 and 5, respectively. These changes were associated with increased fitness of the virus in pSTECs compared to the original parental strain. Our results suggest that the adaptation of human seasonal H3N2 to swine cells may lead to the selection of HA mutations located near the receptor binding site. These mutations may result in increased fitness of human-origin H3N2 strains to adapt in swine.