Browse Articles
Discover research articles across all indexed journals
Distinguishing critical microbial community shifts from normal temporal variability in human and environmental ecosystems
Abstract Differentiating significant microbial community changes from normal fluctuations is vital for understanding microbial dynamics in human and environmental ecosystems. This knowledge could enable early warning systems to monitor critical changes affecting human or environmental health. We applied 16S rRNA gene sequencing and time-series analysis to model bacterial abundance trajectories in human gut and wastewater microbiomes. We evaluated various model architectures using datasets from two human studies and five wastewater settings. Long short-term memory (LSTM) models consistently outperformed other models in predicting bacterial abundances and detecting outliers, as measured by multiple metrics. Prediction intervals for each genus allowed us to identify significant changes and signaling shifts in community states. This study proposes a machine learning model capable of monitoring microbial communities and providing insights into their responses to internal and external factors in medical and environmental settings.
Nature project to encourage early-career researchers in peer review is working
Succession of phytoplankton functional groups in a subtropical lake associated with rainfall patterns
Tumor budding and poorly differentiated clusters as a biological continuum in colorectal cancer invasion and prognosis
Interleukin-7 enhances recruitment of MDSCs by regulating MCP-1 via JAK1/STAT3 signaling pathway in non-small cell lung cancer
Biocatalytic reductive amination with CRISPR-Cas9 engineered yeast
Abstract Metabolically engineered baker’s yeast can be used to produce chiral amines through whole-cell bioconversion of prochiral ketones. This study investigates the modulation of the alanine-pyruvate metabolic node to enhance reductive amination, using the stereoselective conversion of benzylacetone to (S)-1-methyl-3-phenylpropylamine (MPPA) as a model reaction. Chromosomal integration of multiple copies of the promiscuous omega transaminase from Chromobacterium violaceum (cv-ATA) resulted in an active yeast catalyst. Physiological characterization in bioreactors under aerobic batch cultivation revealed that amine production occurred only under post-diauxic growth on ethanol. To reduce native alanine utilization, the endogenous alanine aminotransferase (ALT1) was knocked out and replaced with cv-ATA. To rapidly employ this strategy in other strains, a simple CRISPR/cas9 method for universal gene replacement was developed. The replacement of ALT1 with cv-ATA improved the reaction by 2.6-fold compared to the control strain with intact ALT1. NMR measurements of metabolites originating from 15N L-alanine and 13C glucose indicated that pyruvate formation during growth on glucose inhibited amine production. Under optimal conditions, the biocatalytic bioconversion of benzylacetone to MPPA reached a yield of 58%.
Intelligent extraction of urban ventilation corridors based on region growth algorithm with restricted direction
Six striking images showcase scientific fieldwork
Sunflower ‘virgin births’ enable accelerated crop breeding
Associations of the body roundness index with cognitive function in US older adults and the mediating role of depression: a cross-sectional study from the NHANES 2011–2014
Do universities serve their community?
scRDEN: single-cell dynamic gene rank differential expression network and robust trajectory inference
Abstract The remarkable advancement of single-cell RNA sequencing (scRNA-seq) technology has empowered researchers to probe gene expression at the single-cell level with unprecedented precision. To gain a profound understanding of the heterogeneity inherent in cell fate determination, a central challenge lies in the comprehensive analysis of the dynamic regulatory alterations that underlie transcriptional differences and the accurate inference of the differentiation trajectory. Here, we propose the method scRDEN, a robust framework that infers important cell sub-populations and differential expression networks of multiple genes along the differentiation directions of each branch by converting the unstable gene expression values in cells into relatively stable gene-gene interactions (global features) and extracting the order of differential expression (network features), and further integrating the expression features of different dimension reduction methods. When applied to five published scRNA-seq datasets from human and mouse cell differentiation, scRDEN not only successfully captures the stable cell subpopulations with potential marker genes, measures the transcriptional differences of gene pairs to identify the rank differential expression network along the differentiation direction of each branch. In addition, in multiple gene rank differential expression networks, the rank expression directly related to transcription factors/marker genes shows a significant strengthening and weakening trend along with their expression changes, and the distribution of diversity and cluster coefficient show a non-monotonic change trend, including the cases of increasing first and then decreasing or decreasing first and then increasing. This may correspond to the mechanism of cells gradually differentiating into stable functions. It is particularly noteworthy that scRDEN method yielded exceptional results when applied to the large-scale, multi-branched, double-batch mouse dentate gyrus data. This outstanding performance provides novel and valuable insights into large-scale, multi-batch trajectory inference and the study of transcriptional mechanism regulation during the processes of differentiation and development.
Replica exchange enhanced adaptively weighted stochastic gradient Langevin dynamics for Bayesian sampling and optimization
Why bad philosophy is stopping progress in physics
Assessment of vaccination rates and motivation among transplant patients using vaccination cards and interviews
Abstract Transplant patients are at an elevated risk for infections. Therefore, infection prevention plays a pivotal role in their care. Two different approaches were chosen to determine their vaccination status and motivation. The vaccination rate was determined by analyzing the patients’ vaccination cards based on German vaccination recommendations. The vaccinations were categorized into standard, indicated, and risk-dependent vaccinations. The vaccination motivation was determined through a semi-structured interview using a self-developed questionnaire as an interview guide. Both parts were analyzed separately. A total of 126 patients were included in the study. In 115 (91.3%) patients, vaccination cards were available, 64.3% had complete standard and 0.9% indicated vaccinations. In the risk-dependent vaccinations category, 49.6% of participants had at least one of the additional vaccinations. The vaccination rate against hepatitis B was significantly higher in kidney than in liver transplant recipients (88.1% vs. 55.4%, Χ2 = 13.7, p < 0.001, n = 107). Vaccination confidence correlated significantly with willingness to vaccinate (r = 0.362, p < 0.001, n = 123). In conclusion, only a few transplant patients have complete vaccination protection. Further patient education is needed to increase patients’ confidence in vaccinations and to motivate them.
Dual-Domain deep prior guided sparse-view CT reconstruction with multi-scale fusion attention
The scars of war last for centuries: how we understand collective trauma needs to change
Increased user engagement on YouTube for loot box content and its potential relevance for behavioural addictions
Abstract Video games frequently contain loot boxes, i.e. virtual in-game items sharing structural similarities with gambling. On YouTube©, there are multi-million subscriber channels prominently featuring loot box-related content. A gamblification of digital games may increase player engagement, and we tested if user engagement on YouTube is linked to loot box content. We extracted aggregate user engagement measures from more than 22 thousand YouTube gaming videos with and without focused display of loot boxes. Principal component analysis was used to reduce dimensionality and derive components reflecting overall and sustained, and relative user engagement, respectively. Confirming our pre-registered hypothesis (see https://osf.io/nh7zr), a significant effect of loot box content on the first principal component was found, reflecting higher overall and sustained user engagement for videos featuring loot box content. This increased engagement may be linked to the gambling-like properties of the reward structure conveyed by loot boxes. Publicly available user data may serve as an early indicator of potential changes in problematic internet use and gambling-related behaviour.