A large‐scale multiomic dataset (proteomic and metabolomic) comprising 3,060 plasma samples were analyzed to identify proteins, metabolites, pathways, and protein‐associated drugs linked to Alzheimer’s Disease (AD) independently of apolipoprotein E (APOE). AD was associated with a distinct molecular signature that captures.
Fuhai Li +22 more
wiley +1 more source
PRTS: Predicting Single-Cell Spatial Transcriptomic Maps from Histological Images. [PDF]
Wen J +20 more
europepmc +1 more source
An evolutionary molecular dynamics platform is used to design P1.6, a membrane‐active peptide that senses lipid packing defects in viral envelopes. P1.6 adopts a stabilized α‐helical structure upon membrane contact, disrupts virus‐like liposomes, and damages HIV‐1 particles.
Pascal von Maltitz +10 more
wiley +1 more source
Development and validation of the family sports ecosystem questionnaire. [PDF]
Zhang G, Jin C.
europepmc +1 more source
Active Force Dynamics in Red Blood Cells Under Non‐Invasive Optical Tweezers
A non‐invasive method combines low‐power optical tweezers with high‐speed microscopy to simultaneously monitor local membrane forces and displacements in single human red blood cells. This dual‐channel approach reveals a mechano‐dynamic signature that correlates the cell's metabolic state with its mechanical activity. This energetic framework serves as
Arnau Dorn +5 more
wiley +1 more source
A literature survey of shapelet quality measures for time series classification. [PDF]
Li T, Guo X, Ji C.
europepmc +1 more source
QCMaquis 4.0: Multipurpose Electronic, Vibrational, and Vibronic Structure and Dynamics Calculations with the Density Matrix Renormalization Group. [PDF]
Szenes K +8 more
europepmc +1 more source
Forecasting the rheological state properties of self-compacting concrete mixes using the response surface methodology technique for sustainable structural concreting. [PDF]
Zumba E +7 more
europepmc +1 more source
LazyNet: Interpretable ODE Modeling of Sparse CRISPR Single-Cell Screens Reveals New Biological Insights. [PDF]
Yi Z, Ma N, Ao Y.
europepmc +1 more source
Using symbolic machine learning to assess and model substance transport and decay in water distribution networks. [PDF]
Laucelli DB +3 more
europepmc +1 more source

