Comparative Evaluation of Electron Ionization Mass Spectral Prediction Methods.

During the past decade promising methods for computational prediction of electron ionization mass spectra have been developed. The most prominent ones are based on quantum chemistry (QCEIMS) and machine learning (CFM-EI, NEIMS). Here we provide a threefold comparison of these methods with respect to spectral prediction and compound identification. We found that there is no unambiguous way to determine the best of these three methods. Among other factors, we find that the choice of spectral distance functions play an important role regarding the performance for compound identification.

Longitudinal two-dimensional gas chromatography mass spectrometry as a non-destructive at-line monitoring tool during cell manufacturing identifies volatile features correlative to cell product quality.

BACKGROUND AIMS: Cell therapies have emerged as a potentially transformative therapeutic modality in many chronic and incurable diseases. However, inherent donor and patient variabilities, complex manufacturing processes, lack of well-defined critical quality attributes and unavailability of in-line or at-line process or product analytical technologies result in significant variance in cell product quality and clinical trial outcomes. New approaches for overcoming these challenges are needed to realize the potential of cell therapies. METHODS: Here the authors developed an untargeted two-dimensional gas chromatography mass spectrometry (GC×GC-MS)-based method for non-destructive longitudinal at-line monitoring of cells during manufacturing to discover correlative volatile biomarkers of cell proliferation and end product potency. RESULTS: Specifically, using mesenchymal stromal cell cultures as a model, the authors demonstrated that GC×GC-MS of the culture medium headspace can effectively discriminate between media types and tissue sources. Headspace GC×GC-MS identified specific volatile compounds that showed a strong correlation with cell expansion and product functionality quantified by indoleamine-2,3-dioxygenase and T-cell proliferation/suppression assays. Additionally, the authors discovered increases in specific volatile metabolites when cells were treated with inflammatory stimulation. CONCLUSIONS: This work establishes GC×GC-MS as an at-line process analytical technology for cell manufacturing that could improve culture robustness and may be used to non-destructively monitor culture state and correlate with end product function.

Chromatographic Separation and Visual Detection on Wicking Microfluidic Devices: Quantitation of Cu2+ in Surface, Ground, and Drinking Water.

Copper is widely applied in industrial and technological applications and is an essential micronutrient for humans and animals. However, exposure to high environmental levels of copper, especially through drinking water, can lead to copper toxicity, resulting in severe acute and chronic health effects. Therefore, regular monitoring of aqueous copper ions has become necessary as recent anthropogenic activities have led to elevated environmental concentrations of copper. On-site monitoring processes require an inexpensive, simple, and portable analytical approach capable of generating reliable qualitative and quantitative data efficiently. Membrane-based lateral flow microfluidic devices are ideal candidates as they facilitate rapid, inexpensive, and portable measurements. Here we present a simple, chromatographic separation approach in combination with a visual detection method for Cu2+ quantitation, performed in a lateral flow microfluidic channel. This method appreciably minimizes interferences by incorporating a nonspecific polymer inclusion membrane (PIM) based assay with a "dot-counting" approach to quantification. In this study, hydrophobic polycaprolactone (PCL)-filled glass microfiber (GMF) membranes were used as the base substrate onto which the PIM was evenly dispensed as an array of dots. The devices thus prepared were then selectively exposed to oxygen radicals through a mask to generate a hydrophilic surface path along which the sample was wicked. Using this approach, copper concentrations from 1 to 20 ppm were quantified from 5 µL samples using only visual observation of the assay device.

Patterned polycaprolactone-filled glass microfiber microfluidic devices for total protein content analysis.

Membrane based microfluidic devices have gained much popularity in recent years, as they make possible rapid, inexpensive analytical techniques that can be applied to a wide variety of areas. The ability to modify device hydrophilicity and hydrophobicity is critically important in fabricating membrane based microfluidic devices. Polar hydrophilic membranes, such as glass microfiber (GMF) membranes, hold great potential as they are inexpensive, chemically inert, and stable. Filling of these membranes with non-polar polymers such as polycaprolactone (PCL) converts the hydrophilic GMF into a hydrophobic medium. Controlled alteration of the surface chemistry of PCL/GMF substrates allows for the fabrication of microfluidic patterns on the surface. Using this approach, we have developed a simple and rapid technique for fabrication of highly adaptable complex multidimensional (2D and 3D) microfluidic pathways on a single membrane. PCL-filled GMF media were masked and selectively exposed to oxygen radicals so that the exposed surface became permanently superhydrophilic in its behavior. The desired microfluidic pattern was cut into the mask prior to assembly and exposure, and the mask was removed after exposure to reveal the ready-to-use microfluidic device. To verify and demonstrate the performance of this novel fabrication method, a colorimetric total protein assay was applied to the determination of protein concentrations in real samples.

Scalable graphene field-effect sensors for specific protein detection.

We demonstrate that micron-scale graphene field-effect transistor biosensors can be fabricated in a scalable fashion from large-area chemical vapor deposition derived graphene. We electrically detect the real-time binding and unbinding of a protein biomarker, thrombin, to and from aptamer-coated graphene surfaces. Our sensors have low background noise and high transconductance, comparable to exfoliated graphene devices. The devices are reusable and have a shelf-life greater than one week.