Publications by authors named "J C Melchior"
The ability of high-density lipoprotein (HDL) to promote cellular cholesterol efflux is a more robust predictor of cardiovascular disease protection than HDL-cholesterol levels in plasma. Previously, we found that lipidated HDL containing both apolipoprotein A-I (APOA1) and A-II (APOA2) promotes cholesterol efflux via the ATP-binding cassette transporter (ABCA1). In the current study, we directly added purified, lipid-free APOA2 to human plasma and found a dose-dependent increase in whole plasma cholesterol efflux capacity.
View Article and Find Full Text PDFAdhesion G-protein-coupled receptors (AGPCRs), containing large N-terminal ligand-binding domains for environmental mechano-sensing, have been increasingly recognized to play important roles in numerous physiologic and pathologic processes. However, their impact on the heart, which undergoes dynamic mechanical alterations in healthy and failing states, remains understudied. ADGRG1 (formerly known as GPR56) is widely expressed, including in skeletal muscle where it was previously shown to mediate mechanical overload-induced muscle hypertrophy; thus, we hypothesized that it could impact the development of cardiac dysfunction and remodeling in response to pressure overload.
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- The study highlights the issues caused by the derivative of activation functions in artificial neural networks, especially during continual learning, and introduces a new approach called Hebbian descent to address these problems.
- Hebbian descent uses an alternative loss function that ignores the derivative of the activation function, which helps prevent vanishing error signals in both shallow and deep networks, enhancing training effectiveness.
- By integrating centering with Hebbian descent, the method not only improves continual learning by reducing catastrophic interference but also shows performance on par with regular gradient descent in specific scenarios.
Based on the CRISP theory (Content Representation, Intrinsic Sequences, and Pattern completion), we present a computational model of the hippocampus that allows for online one-shot storage of pattern sequences without the need for a consolidation process. In our model, CA3 provides a pre-trained sequence that is hetero-associated with the input sequence, rather than storing a sequence in CA3. That is, plasticity on a short timescale only occurs in the incoming and outgoing connections of CA3, not in its recurrent connections.
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