Application of Laser-Induced, Deep UV Raman Spectroscopy and Artificial Intelligence in Real-Time Environmental Monitoring-Solutions and First Results.

Environmental monitoring of aquatic systems is the key requirement for sustainable environmental protection and future drinking water supply. The quality of water resources depends on the effectiveness of water treatment plants to reduce chemical pollutants, such as nitrates, pharmaceuticals, or microplastics. Changes in water quality can vary rapidly and must be monitored in real-time, enabling immediate action. In this study, we test the feasibility of a deep UV Raman spectrometer for the detection of nitrate/nitrite, selected pharmaceuticals and the most widespread microplastic polymers. Software utilizing artificial intelligence, such as a convolutional neural network, is trained for recognizing typical spectral patterns of individual pollutants, once processed by mathematical filters and machine learning algorithms. The results of an initial experimental study show that nitrates and nitrites can be detected and quantified. The detection of nitrates poses some challenges due to the noise-to-signal ratio and background and related noise due to water or other materials. Selected pharmaceutical substances could be detected via Raman spectroscopy, but not at concentrations in the µg/l or ng/l range. Microplastic particles are non-soluble substances and can be detected and identified, but the measurements suffer from the heterogeneous distribution of the microparticles in flow experiments.

Native Youth Participating in the Together on Diabetes 12-Month Home-Visiting Program Reported Improvements in Alternative Healthy Eating Index-2010 Diet Quality Domains Likely to Be Associated With Blood Pressure and Glycemic Control.

BACKGROUND: The Together on Diabetes (TOD) intervention was a home-visiting diabetes prevention and management program for Native youth. OBJECTIVES: (1) Examine the impact of the TOD program on diet quality using the Alternative Healthy Eating Index (AHEI-2010); (2) determine association between diet quality and cardiometabolic health. DESIGN: The TOD program was conducted from October 2012 to June 2014 and was evaluated using a pretest-posttest study design from baseline to 12 months. Dietary intake was assessed using a food frequency questionnaire. PARTICIPANTS/SETTING: There were 240 participants between 10 and 19 years of age from 4 reservation-based, rural tribal communities in the southwestern United States that had been diagnosed with T2DM or prediabetes or were identified as at risk based on body mass index and a qualifying laboratory test. INTERVENTION: Youth were taught a 12-lesson curriculum on goal setting, nutrition, and life skills education. MAIN OUTCOME MEASURES: Behavioral and physiologic outcomes related to diabetes. STATISTICAL ANALYSIS: Changes in AHEI-2010 score and associations with cardiometabolic measures were tested, over time, using adjusted longitudinal linear mixed-effects models. RESULTS: The study sample reported an average energy intake of 2016 kcal/d (±1260) and AHEI-2010 score of 47.4 (±7.4) (range: 0-110, higher = better diet quality), indicating low diet quality at baseline. At 12 months' follow-up, there was a reduction in kilocalories (mean = -346 kcal/d; P < .001), sugar-sweetened beverages (mean = -2 fluid oz/d; P = .032), red/processed meat (mean = -1.5 oz/d; P = .008), and sodium (mean = -650 mg/d; P < .001) but no change in AHEI-2010 score (P = .600). The change in systolic blood pressure from baseline to 12 months for participants within the highest AHEI-2010 quartile group was significantly larger than the change in participants within the lowest quartile group (mean = -5.90 mm Hg; P = .036). CONCLUSIONS: Despite stable AHEI-2010 scores during follow-up, there were improvements in diet quality domains likely to be associated with cardiometabolic health. Home-visiting programs like TOD are promising interventions for decreasing dietary intake of poor-quality foods.

In situ Detection of Microbial Life in the Deep Biosphere in Igneous Ocean Crust.

The deep biosphere is a major frontier to science. Recent studies have shown the presence and activity of cells in deep marine sediments and in the continental deep biosphere. Volcanic lavas in the deep ocean subsurface, through which substantial fluid flow occurs, present another potentially massive deep biosphere. We present results from the deployment of a novel in situ logging tool designed to detect microbial life harbored in a deep, native, borehole environment within igneous oceanic crust, using deep ultraviolet native fluorescence spectroscopy. Results demonstrate the predominance of microbial-like signatures within the borehole environment, with densities in the range of 10(5) cells/mL. Based on transport and flux models, we estimate that such a concentration of microbial cells could not be supported by transport through the crust, suggesting in situ growth of these communities.

Label-free bacterial imaging with deep-UV-laser-induced native fluorescence.

We introduce a near-real-time optical imaging method that works via the detection of the intrinsic fluorescence of life forms upon excitation by deep-UV (DUV) illumination. A DUV (<250-nm) source enables the detection of microbes in their native state on natural materials, avoiding background autofluorescence and without the need for fluorescent dyes or tags. We demonstrate that DUV-laser-induced native fluorescence can detect bacteria on opaque surfaces at spatial scales ranging from tens of centimeters to micrometers and from communities to single cells. Given exposure times of 100 µs and low excitation intensities, this technique enables rapid imaging of bacterial communities and cells without irreversible sample alteration or destruction. We also demonstrate the first noninvasive detection of bacteria on in situ-incubated environmental experimental samples from the deep ocean (Lo'ihi Seamount), showing the use of DUV native fluorescence for in situ detection in the deep biosphere and other nutrient-limited environments.

Classification of organic and biological materials with deep ultraviolet excitation.

We show that native fluorescence can be used to differentiate classes or groups of organic molecules and biological materials when excitation occurs at specific excitation wavelengths in the deep ultraviolet (UV) region. Native fluorescence excitation-emission maps (EEMs) of pure organic materials, microbiological samples, and environmental background materials were compared using excitation wavelengths between 200-400 nm with emission wavelengths from 270 to 500 nm. These samples included polycyclic aromatic hydrocarbons (PAHs), nitrogen- and sulfur-bearing organic heterocycles, bacterial spores, and bacterial vegetative whole cells (both Gram positive and Gram negative). Each sample was categorized into ten distinct groups based on fluorescence properties. Emission spectra at each of 40 excitation wavelengths were analyzed using principal component analysis (PCA). Optimum excitation wavelengths for differentiating groups were determined using two metrics. We show that deep UV excitation at 235 (+/-2) nm optimally separates all organic and biological groups within our dataset with >90% confidence. For the specific case of separation of bacterial spores from all other samples in the database, excitation at wavelengths less than 250 nm provides maximum separation with >6sigma confidence.

Predictors of pneumococcal conjugate vaccine immunogenicity among infants and toddlers in an American Indian PnCRM7 efficacy trial.

BACKGROUND: Pneumococcal conjugate vaccines are important for the prevention of serious illness and death among infants. Factors associated with pneumococcal conjugate vaccine immunogenicity have not been explored. METHODS: Children <24 months of age received 2, 3, or 4 doses of 7-valent pneumococcal conjugate vaccine (PnCRM7) or control vaccine depending on age at enrollment. Serum samples were tested for serotype-specific antibodies by enzyme-linked immunosorbant assay. Multiple linear regression was used to determine predictors of immunogenicity. RESULTS: Among 315 PnCRM7-vaccinated subjects and 295 control subjects enrolled at <7 months of age, geometric mean concentrations (GMCs) of antibodies were significantly higher after dose 3 than after dose 2 for all serotypes except type 4. The proportion of subjects with antibody concentrations > or =5.0 micro g/mL was higher for all serotypes, but the proportion with concentrations > or =0.35 micro g/mL was higher only for types 6B and 23F. Three-dose and 2-dose regimens for those 7-11 and 12-23 months of age, respectively, were highly immunogenic. Increased maternal antibody concentrations were associated with reduced responses to dose 1 and 3 but not to dose 4 of PnCRM7. CONCLUSIONS: Maternal antibody is associated with a reduced infant response to PnCRM7 but does not interfere with immune memory. In infants, a third priming dose increases the antibody GMC and the proportion achieving an antibody concentration > or =5.0 micro g/mL but has little impact on the proportion achieving a concentration > or =0.35 micro g/mL.