Saturated fatty acids induce c-Src clustering within membrane subdomains, leading to JNK activation.

Saturated fatty acids (FA) exert adverse health effects and are more likely to cause insulin resistance and type 2 diabetes than unsaturated FA, some of which exert protective and beneficial effects. Saturated FA, but not unsaturated FA, activate Jun N-terminal kinase (JNK), which has been linked to obesity and insulin resistance in mice and humans. However, it is unknown how saturated and unsaturated FA are discriminated. We now demonstrate that saturated FA activate JNK and inhibit insulin signaling through c-Src activation. FA alter the membrane distribution of c-Src, causing it to partition into intracellular membrane subdomains, where it likely becomes activated. Conversely, unsaturated FA with known beneficial effects on glucose metabolism prevent c-Src membrane partitioning and activation, which are dependent on its myristoylation, and block JNK activation. Consumption of a diabetogenic high-fat diet causes the partitioning and activation of c-Src within detergent insoluble membrane subdomains of murine adipocytes.

Optoacoustic Imaging of Glucagon-like Peptide-1 Receptor with a Near-Infrared Exendin-4 Analog.

Limitations in current imaging tools have long challenged the imaging of small pancreatic islets in animal models. Here, we report the first development and in vivo validation testing of a broad-spectrum and high-absorbance near-infrared optoacoustic contrast agent, E4x12-Cy7. Our near-infrared tracer is based on the amino acid sequence of exendin-4 and targets the glucagon-like peptide-1 receptor (GLP-1R). Cell assays confirmed that E4x12-Cy7 has a high-binding affinity (dissociation constant, Kd, 4.6 ± 0.8 nM). Using the multispectral optoacoustic tomography, we imaged E4x12-Cy7 and optoacoustically visualized ß-cell insulinoma xenografts in vivo for the first time. In the future, similar optoacoustic tracers that are specific for ß-cells and combines optoacoustic and fluorescence imaging modalities could prove to be important tools for monitoring the pancreas for the progression of diabetes.

Acid specific dark quencher QC1 pHLIP for multi-spectral optoacoustic diagnoses of breast cancer.

Breast cancer is the most common type of malignant growth in women. Early detection of breast cancer, as well as the identification of possible metastatic spread poses a significant challenge because of the structural and genetic heterogeneity that occurs during the progression of the disease. Currently, mammographies, biopsies and MRI scans are the standard of care techniques used for breast cancer diagnosis, all of which have their individual shortfalls, especially when it comes to discriminating tumors and benign growths. With this in mind, we have developed a non-invasive optoacoustic imaging strategy that targets the acidic environment of breast cancer. A pH low insertion peptide (pHLIP) was conjugated to the dark quencher QC1, yielding a non-fluorescent sonophore with high extinction coefficient in the near infrared that increases signal as a function of increasing amounts of membrane insertion. In an orthotopic murine breast cancer model, pHLIP-targeted optoacoustic imaging allowed us to differentiate between healthy and breast cancer tissues with high signal/noise ratios. In vivo, the sonophore QC1-pHLIP could detect malignancies at higher contrast than its fluorescent analog ICG-pHLIP, which was developed for fluorescence-guided surgical applications. PHLIP-type optoacoustic imaging agents in clinical settings are attractive due to their ability to target breast cancer and a wide variety of other malignant growths for diagnostic purposes. Intuitively, these agents could also be used for visualization during surgery.

Sonophore-enhanced nanoemulsions for optoacoustic imaging of cancer.

Optoacoustic imaging offers the promise of high spatial resolution and, at the same time, penetration depths well beyond the conventional optical imaging technologies, advantages that would be favorable for a variety of clinical applications. However, similar to optical fluorescence imaging, exogenous contrast agents, known as sonophores, need to be developed for molecularly targeted optoacoustic imaging. Despite numerous optoacoustic contrast agents that have been reported, there is a need for more rational design of sonophores. Here, using a library screening approach, we systematically identified and evaluated twelve commercially available near-infrared (690-900 nm) and highly absorbing dyes for multi-spectral optoacoustic tomography (MSOT). In order to achieve more accurate spectral deconvolution and precise data quantification, we sought five practical mathematical methods, namely direct classical least squares based on UV-Vis (UV/Vis-DCLS) or optoacoustic (OA-DCLS) spectra, non-negative LS (NN-LS), independent component analysis (ICA) and principal component analysis (PCA). We found that OA-DCLS is the most suitable method, allowing easy implementation and sufficient accuracy for routine analysis. Here, we demonstrate for the first time that our biocompatible nanoemulsions (NEs), in combination with near-infrared and highly absorbing dyes, enable non-invasive in vivo MSOT detection of tumors. Specifically, we found that NE-IRDye QC1 offers excellent optoacoustic performance and detection compared to related near-infrared NEs. We demonstrate that when loaded with low fluorescent or dark quencher dyes, NEs represent a flexible and new class of exogenous sonophores suitable for non-invasive pre-clinical optoacoustic imaging.

Land use regression modelling of air pollution in high density high rise cities: A case study in Hong Kong.

Land use regression (LUR) is a common method of predicting spatial variability of air pollution to estimate exposure. Nitrogen dioxide (NO2), nitric oxide (NO), fine particulate matter (PM2.5), and black carbon (BC) concentrations were measured during two sampling campaigns (April-May and November-January) in Hong Kong (a prototypical high-density high-rise city). Along with 365 potential geospatial predictor variables, these concentrations were used to build two-dimensional land use regression (LUR) models for the territory. Summary statistics for combined measurements over both campaigns were: a) NO2 (Mean=106µg/m3, SD=38.5, N=95), b) NO (M=147µg/m3, SD=88.9, N=40), c) PM2.5 (M=35µg/m3, SD=6.3, N=64), and BC (M=10.6µg/m3, SD=5.3, N=76). Final LUR models had the following statistics: a) NO2 (R2=0.46, RMSE=28µg/m3) b) NO (R2=0.50, RMSE=62µg/m3), c) PM2.5 (R2=0.59; RMSE=4µg/m3), and d) BC (R2=0.50, RMSE=4µg/m3). Traditional LUR predictors such as road length, car park density, and land use types were included in most models. The NO2 prediction surface values were highest in Kowloon and the northern region of Hong Kong Island (downtown Hong Kong). NO showed a similar pattern in the built-up region. Both PM2.5 and BC predictions exhibited a northwest-southeast gradient, with higher concentrations in the north (close to mainland China). For BC, the port was also an area of elevated predicted concentrations. The results matched with existing literature on spatial variation in concentrations of air pollutants and in relation to important emission sources in Hong Kong. The success of these models suggests LUR is appropriate in high-density, high-rise cities.