Browse Articles
Discover research articles across all indexed journals
Context-dependent change in the fitness effect of (in)organic phosphate antiporter glpT during Salmonella Typhimurium infection
Abstract Salmonella enterica is a frequent cause of foodborne diseases, which is attributed to its adaptability. Even within a single host, expressing a gene can be beneficial in certain infection stages but neutral or even detrimental in others as previously shown for flagellins. Mutants deficient for the conserved glycerol-3-phosphate and phosphate antiporter glpT have been shown to be positively selected in nature, clinical, and laboratory settings. This suggests that different selective pressures select for the presence or absence of GlpT in a context dependent fashion, a phenomenon known as antagonistic pleiotropy. Using mutant libraries and reporters, we investigated the fitness of glpT-deficient mutants during murine orogastric infection. While glpT-deficient mutants thrive during initial growth in the gut lumen, where GlpT’s capacity to import phosphate is disadvantageous, they are counter-selected by macrophages. The dichotomy showcases the need to study the spatial and temporal heterogeneity of enteric pathogens’ fitness across distinct lifestyles and niches. Insights into the differential adaptation during infection may reveal opportunities for therapeutic interventions.
Evaluation of different mathematical models on fitting the in vitro gas production parameters in beef cattle
Artificial intelligence for modeling and understanding extreme weather and climate events
Evaluation of blood-tumor barrier permeability and doxorubicin delivery in rat brain tumor models using additional focused ultrasound stimulation
Author Correction: Assessment of human leukocyte antigen-based neoantigen presentation to determine pan-cancer response to immunotherapy
POU2F2+ B cells enhance antitumor immunity and predict better survival in non small cell lung cancer
Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour
Abstract With the ever-increasing complexity of microscopy modalities, it is imperative to have computational workflows that enable researchers to process and perform in-depth quantitative analysis of the resulting images. However, workflows that allow flexible, interactive and intuitive analysis from raw images to analysed data are lacking for many experimental use-cases. Notably, integrated software solutions for analysis of complex 3D and live cell images are sorely needed. To address this, we present Cecelia, a toolbox that integrates various open-source packages into a coherent data management suite to make quantitative multidimensional image analysis accessible for non-specialists. We describe the application of Cecelia to several immunologically relevant scenarios and the development of an unbiased approach to distinguish dynamic cell behaviours from live imaging data. Cecelia is available as a software package with a Shiny app interface ( https://github.com/schienstockd/cecelia ). We envision that this framework and its approaches will be of broad use for biological researchers.
An enhanced denoising system for mammogram images using deep transformer model with fusion of local and global features
Superior electron transport in the single-crystalline TiCoSb-based half-Heuslers
Cognitive performance classification of older patients using machine learning and electronic medical records
Individual bioenergetic capacity as a potential source of resilience to Alzheimer’s disease
Robust differential microphone array with constant mainlobe width and frequency-invariant directivity factor
Insights from a methylome-wide association study of antidepressant exposure
Abstract This study tests the association of whole-blood DNA methylation and antidepressant exposure in 16,531 individuals from Generation Scotland (GS), using self-report and prescription-derived measures. We identify 8 associations and a high concordance of results between self-report and prescription-derived measures. Sex-stratified analyses observe nominally significant increased effect estimates in females for four CpGs. There is observed enrichment for genes expressed in the Amygdala and annotated to synaptic vesicle membrane ontology. Two CpGs (cg15071067; DGUOK-AS1 and cg26277237; KANK1) show correlation between DNA methylation with the time in treatment. There is a significant overlap in the top 1% of CpGs with another independent methylome-wide association study of antidepressant exposure. Finally, a methylation profile score trained on this sample shows a significant association with antidepressant exposure in a meta-analysis of eight independent external datasets. In this large investigation of antidepressant exposure and DNA methylation, we demonstrate robust associations which warrant further investigation to inform on the design of more effective and tolerated treatments for depression.