RESUMEN

The recent National Institute of Health (NIH) INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) initiative has bolstered capacity for the current increase in clinical trials involving individuals with Down syndrome (DS). This new NIH funding mechanism offers new opportunities to expand and develop novel approaches in engaging and effectively enrolling a broader representation of clinical trials participants addressing current medical issues faced by individuals with DS. To address this opportunity, the NIH assembled leading clinicians, scientists, and representatives of advocacy groups to review existing methods and to identify those areas where new approaches are needed to engage and prepare DS populations for participation in clinical trial research. This paper summarizes the results of the Clinical Trial Readiness Working Group that was part of the INCLUDE Project Workshop: Planning a Virtual Down Syndrome Cohort Across the Lifespan Workshop held virtually September 23 and 24, 2019.

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RESUMEN

Designed experiments based on a simplex mixture design were employed to explore the effects of three solvent components (water, formic acid, and aqueous acetic acid), extraction time, and extraction temperature for the automated microextraction of basic (cationic) dyes from acrylic fibers. Extractions were conducted by an automated liquid handling system, and dye extraction was evaluated using a UV/visible microplate reader. Highest extraction efficiency for two subclasses of basic dyes (methine and azo) from acrylic fibers was achieved with an extraction solvent containing 88% formic acid/12% water. Cationic dyes were analyzed by capillary electrophoresis using a 45 mM ammonium acetate buffer in acetonitrile-water at pH 4.7. The utility of microextraction combined with capillary electrophoresis-mass spectrometry for analysis of extracts from trace fibers was demonstrated by the detection and characterization of three basic dyes extracted from a 2-mm length of single acrylic fiber.

RESUMEN

The extraction and separation of dyes present on textile fibers offers the possibility of enhanced discrimination between forensic trace fiber evidence. An automated liquid sample handling workstation was programmed to deliver varying solvent combinations to acid-dyed nylon samples, and the resulting extracts were analyzed by an ultraviolet/visible microplate reader to evaluate extraction efficiencies at different experimental conditions. Combinatorial experiments using three-component mixture designs varied three solvents (water, pyridine, and aqueous ammonia) and were employed at different extraction temperatures for various extraction durations. The extraction efficiency as a function of the three solvents (pyridine/ammonia/water) was modeled and used to define optimum conditions for the extraction of three subclasses of acid dyes (anthraquinone, azo, and metal complex) from nylon fibers. The capillary electrophoresis analysis of acid dye extracts is demonstrated using an electrolyte solution of 15 mM ammonium acetate in acetonitrile/water (40:60, v/v) at pH 9.3. Excellent separations and discriminating diode array spectra are obtained even for dyes of similar color.

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The ability of Raman microspectroscopy to distinguish between rutile and anatase forms of the inorganic pigment titanium dioxide (TiO(2)) and to make quantitative measurements of titania loading in fibers is demonstrated. Issues that affect the validity of the Raman measurements include the spatial heterogeneity of TiO(2) in the fiber, the polarization of the laser beam, and the polarizing properties of the fiber itself. The amount of titanium dioxide in single delustered polyamide fibers was quantitated at concentration levels ranging from 0 to 7.1% TiO(2). Fiber polarization and orientation effects were shown to be minimized by scrambling the polarization of the laser.

RESUMEN

Nylons are an important class of synthetic polymers, from an industrial, as well as forensic, perspective. A spectroscopic method, such as Fourier transform infrared (FT-IR) spectroscopy, is necessary to determine the nylon subclasses (e. g., nylon 6 or nylon 6,6). Library searching using absolute difference and absolute derivative difference algorithms gives inconsistent results for identifying nylon subclasses. The objective of this study was to evaluate the usefulness of peak ratio analysis and multivariate statistics for the identification of nylon subclasses using attenuated total reflection (ATR) spectral data. Many nylon subclasses could not be distinguished by the peak ratio of the N-H vibrational stretch to the sp(3) C-H(2) vibrational stretch intensities. Linear discriminant analysis, however, provided a graphical visualization of differences between nylon subclasses and was able to correctly classify a set of 270 spectra from eight different subclasses with 98.5% cross-validated accuracy.