Technologies That Enable Accurate and Precise Nano- to Milliliter-Scale Liquid Dispensing of Aqueous Reagents Using Acoustic Droplet Ejection.

Acoustic liquid handling uses high-frequency acoustic signals that are focused on the surface of a fluid to eject droplets with high accuracy and precision for various life science applications. Here we present a multiwell source plate, the Echo Qualified Reservoir (ER), which can acoustically transfer over 2.5 mL of fluid per well in 25-nL increments using an Echo 525 liquid handler. We demonstrate two Labcyte technologies-Dynamic Fluid Analysis (DFA) methods and a high-voltage (HV) grid-that are required to maintain accurate and precise fluid transfers from the ER at this volume scale. DFA methods were employed to dynamically assess the energy requirements of the fluid and adjust the acoustic ejection parameters to maintain a constant velocity droplet. Furthermore, we demonstrate that the HV grid enhances droplet velocity and coalescence at the destination plate. These technologies enabled 5-µL per destination well transfers to a 384-well plate, with accuracy and precision values better than 4%. Last, we used the ER and Echo 525 liquid handler to perform a quantitative polymerase chain reaction (qPCR) assay to demonstrate an application that benefits from the flexibility and larger volume capabilities of the ER.

Acoustic Injectors for Drop-On-Demand Serial Femtosecond Crystallography.

X-ray free-electron lasers (XFELs) provide very intense X-ray pulses suitable for macromolecular crystallography. Each X-ray pulse typically lasts for tens of femtoseconds and the interval between pulses is many orders of magnitude longer. Here we describe two novel acoustic injection systems that use focused sound waves to eject picoliter to nanoliter crystal-containing droplets out of microplates and into the X-ray pulse from which diffraction data are collected. The on-demand droplet delivery is synchronized to the XFEL pulse scheme, resulting in X-ray pulses intersecting up to 88% of the droplets. We tested several types of samples in a range of crystallization conditions, wherein the overall crystal hit ratio (e.g., fraction of images with observable diffraction patterns) is a function of the microcrystal slurry concentration. We report crystal structures from lysozyme, thermolysin, and stachydrine demethylase (Stc2). Additional samples were screened to demonstrate that these methods can be applied to rare samples.

Source of low-frequency fluctuations in functional MRI signal.

PURPOSE: To investigate the source of native low-frequency fluctuations (LFF) in functional MRI (fMRI) signal. MATERIALS AND METHODS: Phase analysis was performed on tissue-segmented fMRI data acquired at systematically varying sampling rates. RESULTS: LFF in fMRI signal were both native and aliased in origin. Scanner instability did not contribute to native or aliased LFF. Aliased LFF arose from cardiorespiratory processes and head motion. Native LFF did not arise from cardiorespiratory processes, but did so, at least in part, from head motion. Motion correction reduced native LFF, but did not eliminate them. The residual native LFF in motion-corrected fMRI data showed a systematic phase difference among different tissue structures. The native LFF in fMRI signals of cerebral blood vessels and CSF were synchronous, and preceded those of gray and white matter, indicating that the vascular fluctuations lead the metabolic fluctuations. CONCLUSION: The primary physiologic source of native LFF in fMRI signal is vasomotion.

Adaptive pacing of visual stimulation for fMRI studies involving overt speech.

We report the development of an interactive approach to single-word language production studies in fMRI. The approach, adaptive pacing, involves real-time adjustment of stimulus presentation times based on individual subject performance timing and content. At the same time, it maintains a stochastic distribution of interstimulus intervals to avoid confounding task covariates with speech-related signal variance. Adaptive pacing of overt speech production is an example of a new class of paradigms that require an observational approach to data acquisition and benefit from a "time-aware" acquisition and processing environment. The advantages of adaptive pacing in fMRI of impaired subjects are expected to be the acquisition of more informative data per unit time, less contamination of data by correlates of non-language processes such as emotion, and facilitation of experiments that combine normal and impaired subjects.

Model assessment and model building in fMRI.

Model quality is rarely assessed in fMRI data analyses and less often reported. This may have contributed to several shortcomings in the current fMRI data analyses, including: (1) Model mis-specification, leading to incorrect inference about the activation-maps, SPM[t] and SPM[F]; (2) Improper model selection based on the number of activated voxels, rather than on model quality; (3) Under-utilization of systematic model building, resulting in the common but suboptimal practice of using only a single, pre-specified, usually over-simplified model; (4) Spatially homogenous modeling, neglecting the spatial heterogeneity of fMRI signal fluctuations; and (5) Lack of standards for formal model comparison, contributing to the high variability of fMRI results across studies and centers. To overcome these shortcomings, it is essential to assess and report the quality of the models used in the analysis. In this study, we applied images of the Durbin-Watson statistic (DW-map) and the coefficient of multiple determination (R(2)-map) as complementary tools to assess the validity as well as goodness of fit, i.e., quality, of models in fMRI data analysis. Higher quality models were built upon reduced models using classic model building. While inclusion of an appropriate variable in the model improved the quality of the model, inclusion of an inappropriate variable, i.e., model mis-specification, adversely affected it. Higher quality models, however, occasionally decreased the number of activated voxels, whereas lower quality or inappropriate models occasionally increased the number of activated voxels, indicating that the conventional approach to fMRI data analysis may yield sub-optimal or incorrect results. We propose that model quality maps become part of a broader package of maps for quality assessment in fMRI, facilitating validation, optimization, and standardization of fMRI result across studies and centers. Hum. Brain Mapping 20:227-238, 2003.