Vibronic Spectra of Jet-Cooled 2-Aminopurine center dot H2O Clusters Studied by UV Resonant Two-Photon Ionization Spectroscopy and Quantum Chemical Calculations

For understanding the major- and minor-groove hydration patterns of DNAs and RNAs, it is important to understand the local solvation of individual nucleobases at the molecular level. We have investigated the 2-aminopurine center dot H2O. monohydrate by two-color resonant two-photon ionization and UV/UV hole-burning spectroscopies, which reveal two isomers, denoted A and B. The electronic spectral shift delta nu of the S-1 <- S-0 transition relative to bare 9H-2-aminopurine (9H-2AP) is small for isomer A (-70 cm(-1)), while that of isomer B is much larger (delta nu = 889 cm(-1)). B3LYP geometry optimizations with the TZVP basis set predict four cluster isomers, of which three are doubly H-bonded, with H2O acting as an acceptor to a N-H or -NH2 group and as a donor to either of the pyrimidine N sites. The "sugar-edge" isomer A is calculated to be the most stable form with binding energy D-e = 56.4 kJ/mol. Isomers B and C are H-bonded between the -NH2 group and pyrimidine moieties and are 2.5 and 6.9 kJ/mol less stable, respectively. Time-dependent (TD) B3LYP/TZVP calculations predict the adiabatic energies of the lowest (1)pi pi* states of A and B in excellent agreement with the observed 0(0)(0) bands; also, the relative intensities of the A and B origin bands agree well with the calculated S-0 state relative energies. This allows unequivocal identification of the isomers. The R2PI spectra of 9H-2AP and of isomer A exhibit intense low-frequency out-of-plane overtone and combination bands, which is interpreted as a coupling of the optically excited (1)pi pi* state to the lower-lying (1)n pi* dark state. In contrast, these overtone and combination bands are much weaker for isomer B, implying that the (1)pi pi* state of B is planar and decoupled from the (1)n pi* state. These observations agree with the calculations, which predict the (1)n pi* above the (1)pi pi* state for isomer B but below the (1)pi pi* for both 9H-2AP and isomer A.

Evaluation of PCR electrospray-ionization mass spectrometry for rapid molecular diagnosis of bovine mastitis

Bovine mastitis, an inflammatory disease of the mammary gland, is one of the most costly diseases affecting the dairy industry. The treatment and prevention of this disease is linked heavily to the use of antibiotics in agriculture and early detection of the primary pathogen is essential to control the disease. Milk samples (n=67) from cows suffering from mastitis were analyzed for the presence of pathogens using PCR electrospray-ionization mass spectrometry (PCR/ESI-MS) and were compared with standard culture diagnostic methods. Concurrent identification of the primary mastitis pathogens was obtained for 64% of the tested milk samples, whereas divergent results were obtained for 27% of the samples. The PCR/ESI-MS failed to identify some of the primary pathogens in 18% of the samples, but identified other pathogens as well as microorganisms in samples that were negative by culture. The PCR/ESI-MS identified bacteria to the species level as well as yeasts and molds in samples that contained a mixed bacterial culture (9%). The sensitivity of the PCR/ESI-MS for the most common pathogens ranged from 57.1 to 100% and the specificity ranged from 69.8 to 100% using culture as gold standard. The PCR/ESI-MS also revealed the presence of the methicillin-resistant gene mecA in 16.2% of the milk samples, which correlated with the simultaneous detection of staphylococci including Staphylococcus aureus. We demonstrated that PCR/ESI-MS, a more rapid diagnostic platform compared with bacterial culture, has the significant potential to serve as an important screening method in the diagnosis of bovine clinical mastitis and has the capacity to be used in infection control programs for both subclinical and clinical disease.

Plotting regression coefficients and other estimates in Stata

Graphical presentation of regression results has become increasingly popular in the scientific literature, as graphs are much easier to read than tables in many cases. In Stata such plots can be produced by the -marginsplot- command. However, while -marginsplot- is very versatile and flexible, it has two major limitations: it can only process results left behind by -margins- and it can only handle one set of results at the time. In this article I introduce a new command called -coefplot- that overcomes these limitations. It plots results from any estimation command and combines results from several models into a single graph. The default behavior of -coefplot- is to plot markers for coefficients and horizontal spikes for confidence intervals. However, -coefplot- can also produce various other types of graphs. The capabilities of -coefplot- are illustrated in this article using a series of examples.