Sensitive, High-Throughput, and Robust Trapping-Micro-LC-MS Strategy for the Quantification of Biomarkers and Antibody Biotherapeutics.

For LC-MS-based targeted quantification of biotherapeutics and biomarkers in clinical and pharmaceutical environments, high sensitivity, high throughput, and excellent robustness are all essential but remain challenging. For example, though nano-LC-MS has been employed to enhance analytical sensitivity, it falls short because of its low loading capacity, poor throughput, and low operational robustness. Furthermore, high chemical noise in protein bioanalysis typically limits the sensitivity. Here we describe a novel trapping-micro-LC-MS (T-µLC-MS) strategy for targeted protein bioanalysis, which achieves high sensitivity with exceptional robustness and high throughput. A rapid, high-capacity trapping of biological samples is followed by µLC-MS analysis; dynamic sample trapping and cleanup are performed using pH, column chemistry, and fluid mechanics separate from the µLC-MS analysis, enabling orthogonality, which contributes to the reduction of chemical noise and thus results in improved sensitivity. Typically, the selective-trapping and -delivery approach strategically removes >85% of the matrix peptides and detrimental components, markedly enhancing sensitivity, throughput, and operational robustness, and narrow-window-isolation selected-reaction monitoring further improves the signal-to-noise ratio. In addition, unique LC-hardware setups and flow approaches eliminate gradient shock and achieve effective peak compression, enabling highly sensitive analyses of plasma or tissue samples without band broadening. In this study, the quantification of 10 biotherapeutics and biomarkers in plasma and tissues was employed for method development. As observed, a significant sensitivity gain (up to 25-fold) compared with that of conventional LC-MS was achieved, although the average run time was only 8 min/sample. No appreciable peak deterioration or loss of sensitivity was observed after >1500 injections of tissue and plasma samples. The developed method enabled, for the first time, ultrasensitive LC-MS quantification of low levels of a monoclonal antibody and antigen in a tumor and cardiac troponin I in plasma after brief cardiac ischemia. This strategy is valuable when highly sensitive protein quantification in large sample sets is required, as is often the case in typical biomarker validation and pharmaceutical investigations of antibody therapeutics.

Life-Threatening Ventricular Arrhythmias: Current Role of Imaging in Diagnosis and Risk Assessment.

Sudden cardiac arrest continues to be a major cause of death from cardiovascular disease but our ability to predict patients at the highest risk of developing lethal ventricular arrhythmias remains limited. Left ventricular ejection fraction is inversely related to the risk of sudden death but has a low sensitivity and specificity for the population at risk. Nevertheless, it continues to be the main variable considered in identifying patients most likely to benefit from implantable defibrillators to prevent sudden death. Imaging myocardial sympathetic innervation with PET and SPECT as well as imaging characteristics of myocardial infarcts using gadolinium-enhanced cardiac magnetic resonance are emerging as imaging modalities that may further refine patient selection beyond ejection fraction. This review will primarily focus on employing advanced imaging approaches to identify patients with left ventricular dysfunction that are most likely to develop lethal arrhythmias and benefit from inserting a primary prevention implantable cardiac defibrillator. While not yet tested in prospective studies, we will review risk prediction models incorporating quantitative imaging and biomarkers that have been developed that appear promising to identify those at highest risk of sudden death.

Assessment of a nuclear affinity labeling method for tracking implanted mesenchymal stem cells.

Therapeutic implantation of mesenchymal stem cells (MSCs) is entering the realm of clinical trials for several human diseases, and yet much remains uncertain regarding their dynamic distribution and cell fate after in vivo application. Discrepancies in the literature can be attributed in part to the use of different cell labeling/tracking methods and cell administration protocols. To identify a stem cell detection method suitable for myocardial implantation in a large animal model, we experimented on three different MSC labeling methods: adenovirus-mediated expression of enhanced green fluorescence protein (EGFP) and beta-galactosidase (LacZ), and nuclear staining with DAPI. Intramuscular and intracoronary administrations of labeled porcine MSCs identified the nuclear affinity dye to be a reliable stem cell tracking marker. Stem cell identification is facilitated by an optimized live cell labeling condition generating bright blue fluorescence sharply confined to the nucleus. DAPI-labeled MSCs retained full viability, ceased proliferation, and exhibited an increased differentiation potential. The labeled MSCs remained fully active in expressing key growth factor and cytokine genes, and notably exhibited enhanced expression of the chemokine receptor CXCR4 and its ligand SDF1, indicating their competency in response to tissue injury. Histological analysis revealed that approximately half a million MSCs or approximately 2% of the administered MSCs remained localized in the normal pig heart 2 weeks after coronary infusion. That the vast majority of these identified MSCs were interstitial indicated the ability of MSCs to migrate across the coronary endothelium. No evidence was obtained indicating MSC differentiation to cardiomyocyte.