Results 271 to 280 of about 318,757 (356)

MeCP2 and non-CG DNA methylation stabilize the expression of long genes that distinguish closely related neuron types. [PDF]

open access: yesNat Neurosci
Moore JR   +11 more
europepmc   +1 more source

Immunoglobulin G subclass responses to mycobacterial lipoarabinomannan in HIV-infected and non-infected patients with tuberculosis

open access: green, 1993
Christopher da Costa   +4 more
openalex   +2 more sources

Semiclassical inequalities for Dirichlet and Neumann Laplacians on convex domains

open access: yesCommunications on Pure and Applied Mathematics, EarlyView.
Abstract We are interested in inequalities that bound the Riesz means of the eigenvalues of the Dirichlet and Neumann Laplacians in terms of their semiclassical counterpart. We show that the classical inequalities of Berezin–Li–Yau and Kröger, valid for Riesz exponents γ≥1$\gamma \ge 1$, extend to certain values γ<1$\gamma <1$, provided the underlying ...
Rupert L. Frank, Simon Larson
wiley   +1 more source

The malignant transformation of an atypical angiocentric glioma, MYB-altered. [PDF]

open access: yesActa Neuropathol Commun
Aboubakr O   +15 more
europepmc   +1 more source

Evaluation of Onchocerca volvulus-specific IgG4 subclass serology as an index of onchocerciasis transmission potential of three Gabonese villages

open access: green, 1994
Thomas G. Egwang   +7 more
openalex   +2 more sources

IgG4 subclass antibodies impair antitumor immunity in melanoma

open access: yes, 2013
P. Karagiannis   +22 more
semanticscholar   +1 more source

The Electronic Spin State of Diradicals Obtained from the Nuclear Perspective: The Strange Case of Chichibabin Radicals

open access: yesChemPhysChem, Volume 26, Issue 6, March 15, 2025.
The electronic spin state of two Chichibabin radicals is investigated using 2‐dimensional hyperfine correlated Electron Nuclear Double Resonance. The protons (I=1/2) act as a reference for the electronic spin quantum number (S) via their hyperfine interactions.
Gabriel Moise   +7 more
wiley   +1 more source

Machine Learning Approaches in Soft Matter Molecular Simulation and Materials Characterization: Challenges and Perspectives

open access: yesChemPlusChem, EarlyView.
Rigorous frameworks construction toward the development of science‐based machine learning (ML) schemes: invocation of statistical learning and data‐driven methods within the diverse materials science fields, from materials characterization to molecular modeling utilizing domain knowledge to facilitate fundamental understanding and scientific discovery.
Niki Vergadou, Vassilios Constantoudis
wiley   +1 more source

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