Results 91 to 100 of about 185,676 (265)
We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Abstract A class of models indexed by two shape parameters is introduced, both to extend the scope of the standard logistic model to asymmetric probability curves and improve the fit in the noncentral probability regions. One-parameter subclasses can be used to examine symmetric or asymmetric deviations from the logistic model.
openaire +1 more source
Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley +1 more source
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Generative models struggle with kirigami metamaterials
Generative machine learning models have shown notable success in identifying architectures for metamaterials—materials whose behavior is determined primarily by their internal organization—that match specific target properties.
Gerrit Felsch, Viacheslav Slesarenko
doaj +1 more source
DIY a Molecule: Generative Models in Chemistry
This column introduces generative artificial intelligence and its application to molecular design. We contrast generative models with predictive models that most chemists have already encountered, build up the intuition behind conditional generation and ...
Magdalena Lederbauer
doaj +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Design and analysis strategies for robust microbiome ageing research
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
AnoChem: Prediction of chemical structural abnormalities based on machine learning models
De novo drug design aims to rationally discover novel and potent compounds while reducing experimental costs during the drug development stage. Despite the numerous generative models that have been developed, few successful cases of drug design utilizing
Changdai Gu +3 more
doaj +1 more source
CT10 regulator of kinase (CRK) and CRK‐Like (CRKL) are signaling adaptors driving cell adhesion, motility, differentiation, and proliferation. SH2‐domain containing (SH) proteins are enriched in YXXP motifs which when phosphorylated create preferred binding sites for CRK family SH2 domains.
Phoebe M. Cousens +8 more
wiley +1 more source

