Results 111 to 120 of about 114,349,436 (308)

In-Silico-Generated Library for Sensitive Detection of 2‑Dimethylaminoethylamine Derivatized FAHFA Lipids Using High-Resolution Tandem Mass Spectrometry

open access: yes, 2020
Fatty acid esters of hydroxy fatty acids (FAHFAs) are a family of recently discovered lipids with important physiological functions in mammals and plants.
Yu-Qi Feng   +13 more
core   +1 more source

3D kernel-density stochastic model for more personalized glycaemic control: development and in-silico validation [PDF]

open access: yes, 2019
peer reviewedBackground: The challenges of glycaemic control in critically ill patients have been debated for 20 years. While glycaemic control shows benefits, inter- and intra-patient metabolic variability results in increased hypoglycaemia and ...
Uyttendaele, Vincent   +6 more
core   +1 more source

PROPERMAB: an integrative framework for in silico prediction of antibody developability using machine learning

open access: yesmAbs
Selection of lead therapeutic molecules is often driven predominantly by pharmacological efficacy and safety. Candidate developability, such as biophysical properties that affect the formulation of the molecule into a product, is usually evaluated only ...
Bian Li   +9 more
doaj   +1 more source

Comprehensive In Vitro Profiling Demonstrates Successful Immune Evasion of Bioengineered Immune‐Shielded Heart Valves

open access: yesAdvanced Healthcare Materials, EarlyView.
Living donor heart valves offer superior durability for pediatric patients but trigger immune rejection. Lentiviral delivery of viral immune‐evasion genes US2 and Serpin b9 into donor valve cells and valve tissue suppresses HLA expression, reduces PBMC clustering and cytotoxic killing, and induces transcriptional immune‐tolerance programs, paving the ...
Abraham van Wijk   +11 more
wiley   +1 more source

In silico variant prediction in MGPT data.

open access: yes, 2018
In silico variant prediction in MGPT data.
Yuan Tian (225002)   +9 more
core   +1 more source

Differential effects on neurodevelopment of FTO variants in obesity and bipolar disorder suggested by in silico prediction of functional impact: An analysis in Mexican population

open access: yesBrain and Behavior, 2019
Introduction Several studies indicate that polygenic obesity is linked to fat‐mass and obesity‐associated (FTO) genetic variants. Nevertheless, the link between variants in FTO and mental disorders has been barely explored.
Erasmo Saucedo‐Uribe   +11 more
doaj   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

open access: yesAdvanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu   +3 more
wiley   +1 more source

NUBIScan, an in silico approach for prediction of nuclear receptor response elements [PDF]

open access: yes, 2002
Nuclear receptors (NRs) are transcription factors activated by a multitude of hormones, other endogenous substances, and exogenous molecules. These proteins modulate the regulation of target genes by contacting their promoter or enhancer sequences at ...
Kaufmann, M. R.   +3 more
core  

In Vivo Monitoring of Thrombo‐Inflammatory Biomarkers via Molecularly Imprinted Polymer‐Integrated Hydrogel Microneedles

open access: yesAdvanced Materials, EarlyView.
A wearable electrochemical microneedle patch integrates Prussian Blue redox transduction with molecularly imprinted polymer recognition for reagent‐free sampling and detection of thrombo‐inflammatory biomarkers in dermal interstitial fluid. The platform tracks thrombin and inflammatory cytokines with sensitive in vitro, ex vivo, and in vivo performance,
Mahmoud Ayman Saleh   +11 more
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

open access: yesAdvanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena   +3 more
wiley   +1 more source

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