Femoral Artery Atherosclerosis Is Associated With Physical Function Across the Spectrum of the Ankle-Brachial Index: The San Diego Population Study.

BackgroundThe ankle-brachial index (ABI) is inadequate to detect early-stage atherosclerotic disease, when interventions to prevent functional decline may be the most effective. We determined associations of femoral artery atherosclerosis with physical functioning, across the spectrum of the ABI, and within the normal ABI range.Methods and resultsIn 2007-2011, 1103 multiethnic men and women participated in the San Diego Population Study, and completed all components of the summary performance score. Using Doppler ultrasound, superficial and common femoral intima media thickness and plaques were ascertained. Logistic regression was used to assess associations of femoral atherosclerosis with the summary performance score and its individual components. Models were adjusted for demographics, lifestyle factors, comorbidities, lipids, and kidney function. In adjusted models, among participants with a normal-range ABI (1.00-1.30), the highest tertile of superficial intima media thickness was associated with lower odds of a perfect summary performance score of 12 (odds ratio=0.56 [0.36, 0.87], P=0.009), and lower odds of a 4-m walk score of 4 (0.34 [0.16, 0.73], P=0.006) and chair rise score of 4 (0.56 [0.34, 0.94], P=0.03). Plaque presence (0.53 [0.29, 0.99], P=0.04) and greater total plaque burden (0.61 [0.43, 0.87], P=0.006) were associated with worse 4-m walk performance in the normal-range ABI group. Higher superficial intima media thickness was associated with lower summary performance score in all individuals (P=0.02).ConclusionsFindings suggest that use of femoral artery atherosclerosis measures may be effective in individuals with a normal-range ABI, especially, for example, those with diabetes mellitus or a family history of peripheral artery disease, when detection can lead to earlier intervention to prevent functional declines and improve quality of life

A Dual-Column Solid Phase Extraction Strategy for Online Collection and Preparation of Continuously Flowing Effluent Streams for Mass Spectrometry

Current desalination techniques for mass spectrometry-based protocols are problematic for performing temporal response studies where increased temporal resolution requires small samples and faster sampling frequencies, which greatly increases the number of samples and sample preparation time. These challenges are pertinent to cellular dynamics experiments, where it is important to sample the biological system frequently and with as little sample waste as possible. To address these needs, we present a dual-column online solid phase extraction (SPE) approach capable of preconcentrating and preparing a constantly perfusing sample stream, with minimal to no sample loss. This strategy is evaluated for use in microfluidic bioreactor studies specifically aimed at characterizing suitable sample flow rates, temporal resolving power, and analyte concentrations. In this work, we demonstrate that this strategy may be used for flow rates as low as 500 nL/min, with temporal resolving power on the order of 3 min, with analyte loadings ranging from femtomoles to picomoles for metabolites. Under these conditions, recoveries of ca. 80% are obtained even at femtomole loadings

Real-Time Cellular Exometabolome Analysis with a Microfluidic-Mass Spectrometry Platform

<div><p>To address the challenges of tracking the multitude of signaling molecules and metabolites that is the basis of biological complexity, we describe a strategy to expand the analytical techniques for dynamic systems biology. Using microfluidics, online desalting, and mass spectrometry technologies, we constructed and validated a platform well suited for sampling the cellular microenvironment with high temporal resolution. Our platform achieves success in: automated cellular stimulation and microenvironment control; reduced non-specific adsorption to polydimethylsiloxane due to surface passivation; real-time online sample collection; near real-time sample preparation for salt removal; and real-time online mass spectrometry. When compared against the benchmark of “in-culture” experiments combined with ultraperformance liquid chromatography-electrospray ionization-ion mobility-mass spectrometry (UPLC-ESI-IM-MS), our platform alleviates the volume challenge issues caused by dilution of autocrine and paracrine signaling and dramatically reduces sample preparation and data collection time, while reducing undesirable external influence from various manual methods of manipulating cells and media (<i>e.g.</i>, cell centrifugation). To validate this system biologically, we focused on cellular responses of Jurkat T cells to microenvironmental stimuli. Application of these stimuli, in conjunction with the cell’s metabolic processes, results in changes in consumption of nutrients and secretion of biomolecules (collectively, the exometabolome), which enable communication with other cells or tissues and elimination of waste. Naïve and experienced T-cell metabolism of cocaine is used as an exemplary system to confirm the platform’s capability, highlight its potential for metabolite discovery applications, and explore immunological memory of T-cell drug exposure. Our platform proved capable of detecting metabolomic variations between naïve and experienced Jurkat T cells and highlights the dynamics of the exometabolome over time. Upregulation of the cocaine metabolite, benzoylecgonine, was noted in experienced T cells, indicating potential cellular memory of cocaine exposure. These metabolomics distinctions were absent from the analogous, traditional “in-culture” UPLC-ESI-IM-MS experiment, further demonstrating this platform’s capabilities.</p></div

Experimental scheme showing potential cell fates.

<p>Upon exposure to cocaine in a microfluidic bioreactor, naïve and cocaine-experienced cells present different exometabolomic profiles, demonstrated here as color change. Our experiments were designed to determine whether cocaine-experienced cells went to a conditioned state A that was different from state B reached by naïve cells.</p

Benzoylecgonine (BE) time course and fragmentation data.

<p>Top: BE time course data for experienced (blue) and naïve (purple) cells. While data were gathered sequentially, plots are overlaid to highlight the increased abundance of BE in experienced cells. The absence of the expected increase in BE corresponding to step 4 (the last step of cocaine exposure) suggests a decrease in cocaine metabolism, possibly due to cell death. Bottom: The fragmentation spectra of BE are shown with parent ion of m/z 290.</p

Additional metabolite time course data compared to benzoylecgonine (BE).

<p>Experimental conditions for each group of cells are shown above the graph with solid black lines indicating exposure to cocaine media. Anhydroecgonine (AHE) and hydroxybenzoylecgonine (HOBE), two additional metabolites of cocaine, provide examples of both variation between naïve and experienced cell groups in the case of AHE and consistency between these two groups in the case of HOBE. The increases in BE and AHE from naïve to experienced groups are statistically significant with respective <i>p values</i> of <i>5</i>.<i>7 x 10</i>^<i>–4</i> and <i>1</i>.<i>12 x 10</i>^<i>–3</i>. Three unidentified metabolites (m/z 645, m/z 478, and m/z 330) that contribute to the separation between media exposure groups are also shown. m/z 330 and m/z 478 show no statistical significance between naïve and experienced cell groups while the increase in m/z 645 is statistically significant (<i>p = 1</i>.<i>6 x 10</i>^<i>–3</i><i>)</i>.</p

Cocaine exposure scheme for both in-culture and online cell experiments.

<p>The time course of cocaine administration to naïve (blue) and experienced (green) T-cell populations is shown. For the in-culture experiments, experienced samples 1E-4E and naïve samples 1N-4N were withdrawn for analysis at the times shown.</p

Solid phase extraction desalter.

<p>Setup starting from initial sample effluent flow incorporates two sample loops, three valves, and two C18 columns. During (A), sample effluent fills sample loop 2 for 9 minutes, while the aqueous solvent flows through sample loop 1, over column 1, and to waste. The organic solvent flows over column 2 and to the mass spectrometer. (B) Upon switching of the valves, the sample effluent fills sample loop 1 for 9 minutes. Aqueous solvent forces the 1.5 μL head of aqueous solvent, the 4.5 μL of sample effluent, and an additional 2.1 μL of aqueous solvent over column 2 to equilibrate the column, load the sample, and rinse away the salts. Organic solvent runs through column 1 and to the detector. (C) The next valve switch again exchanges the sample loop filled by effluent, while column 1 is equilibrated, loaded, and rinsed. The analytes captured on column 2 are eluted by the organic solvent and sent to the detector. (D) When the valves switch again, the sample effluent fills the opposite loop, column 2 is equilibrated, loaded, and rinsed, and column 1 is eluted with organic solvents and those analytes are sent to the detector. The pattern repeats until the experiment is completed, with each cycle requiring 9 minutes.</p