Chronic kidney disease and lipid metabolism receptors

Lipids are very important molecules in the human body. Different types of lipids include fats and some vitamins. Lipids form the membranes in and around cells, store energy, and signal between cells. Lipids, like fats and oils, do not dissolve in water. To get them around the body they form complexes with proteins. These complexes include LDL and HDL.

Your doctor may have requested blood tests for these. They are important in cardiovascular disease. To get lipids into cells receptors must bind the lipoprotein complexes. Sometimes rather than supporting the cell, lipid uptake can cause stress and inflammation. This is why doctors often check the levels of LDL and HDL.

CD36 is a receptor for lipoproteins. We investigated the role of CD36 in chronic kidney disease (CKD). Breaking this receptor by changing the DNA that creates it protected against CKD. Similar protection happened with a small peptide inhibitor. This is important because it is easier to help patients by giving them a drug than by trying to change their DNA.

Chronic kidney disease and pathogen sensors

There are several receptors that detect microbial products. They are responsible for triggering an inflammatory response by the innate immune system. This is important to guard against infections. Sometimes inflammation can happen when it is not needed to protect against infection. A low level of inflammation is sometimes detected in chronic diseases.

Toll-like receptor 4 (TLR4) detects lipopolysaccharides (LPS). The outer layer of gram-negative bacteria contains LPS. TLR4 might also detect some molecules released during tissue damage. We investigated the role of TLR4 in chronic kidney disease (CKD).

Breaking TLR4 so it could not trigger the innate immune system protected against CKD.

Lightning talk slides on deep learning with keras

At the DCPython Office Hours event this month I gave a lightning talk on convolutional neural networks implemented with the keras library. The notebook is now up on github.

Deep neural networks are typically too slow to train on CPUs. Instead, GPUs are used. The example in the notebook uses a relatively small network so should be runnable on any hardware.

Using sound to guide cells to the kidney

Many diseases are very complex, involving many biological pathways. It is very difficult to find a single drug with actions on enough pathways to slow or reverse many diseases. As an alternative there is excitement around using cells to treat disease. Cells can sense their environment and change their response to match.

Mesenchymal stem cells (MSCs) have performed well in many types of disease. I currently work in the Renal Diagnostics and Therapeutics Unit at NIDDK. Before I joined the group they found MSCs were beneficial in sepsis. Treatment had to be soon after injury limiting the clinical usefulness. One potential reason for this was most MSCs got stuck in the lungs. If more cells got to the kidneys they might work better. At the time it was not known how to guide more cells to the kidneys.

Recently, we have worked with Scott Burks and Joe Frank from the Clinical Center at NIH. They are able to use pulsed focused ultrasound to alter tissues to recruit more MSCs. We tested pulsed focused ultrasound in a cisplatin model. Cisplatin is a treatment for some types of cancer but often causes kidney injury. Pulsed focused ultrasound guided MSC treatment reduced damage from cisplatin.