Quantum Monte Carlo Studies of CO Adsorption on Transition Metal Surfaces

The adsorptions of CO molecule on various fcc(111) surfaces (Rh, Ir, Pt, and Cu) have been studied by diffusion quantum Monte Carlo (DMC) calculations, and the results show that the top site is the most stable adsorption site on all the four surfaces, in agreement with experiments. In particular, the site preference including the bridge site for CO/Pt(111) is predicted, i.e., the top site is most preferred followed by the bridge site while the hollow sites are much less favorable, in accordance with the existing experimental observations of the bridge-site adsorption, yet never on the hollow sites. Compared to the DMC results, density functional theory (DFT) calculations with the generalized-gradient approximation (GGA) predict very similar adsorption energies on the top site, but they overestimate those on the bridge and hollow sites. That is, although the nonlocal exchange-correlation contribution is small for the single-coordinated top-site adsorption, it is essential and required to be properly included for a correct description of the higher coordinated bridge- and hollow-sites adsorptions. These altogether explain why the top site adsorption for CO on Rh, Pt, and Cu(111) surfaces was not predicted correctly by the previous standard local or semilocal DFT calculations

Temporal Analysis of Conformers in the Course of pH Scan Directed by Urea–Urease ReactionA “Protein Clock”

We demonstrate an analytical approach to monitor the effect of pH on protein tertiary structure. An autocatalytic enzyme reaction is used to stimulate refolding of proteins during real-time analysis. The method takes advantage of a nonlinear pH ramp generated by the urea–urease clock reaction. In this study, alterations to the structures of model proteins were monitored by mass spectrometry (charge pattern shift) and fluorometry (tryptophan fluorescence quenching). The pH measurements were conducted at different points of the sample flow line by different methods to minimize artifacts. Interestingly, different protein ions (corresponding to native and unfolded proteins) show distinct temporal mass spectral profiles, which reveal gradual refolding and concomitant deprotonation of higher charge state ions in the course of the clock reaction. Every multiply charged ion of a protein is characterized with its own “clock time”. This approach does not require major modification of standard instrumentation. It enables determination of “high sensitivity” pH intervals for small and large molecules within a single experiment. Thus, it can be useful for characterizing the protein folding in response to pH change

Baseline characteristics according to hospital volume and surgeon volume (n = 13159).

<p>Abbreviation: SD, standard deviation; COPD, chronic obstructive pulmonary disease.</p

Short-term survival after hepatic resection by combined effect of surgeon and hospital volume.

<p>Short-term survival after hepatic resection by combined effect of surgeon and hospital volume.</p

The adjusted hazard ratios of provider categories in different regression models.

<p>Abbreviation: HR, hazard ratio; 95% CI, 95% confidence interval.</p><p>Adjusted for patients’ age, gender, indication for surgery, surgical procedure, comorbidity, hepatitis/cirrhosis, pre-and post-operative cirrhosis-related complication, socioeconomic status, geographic region and urbanization level of residence.</p

The adjusted hazard ratios of patient demographic variables.

<p>Abbreviation: HR, hazard ratio; 95% CI, 95% confidence interval; COPD, chronic obstructive pulmonary disease.</p

Baseline characteristics of older patients (age >65 years) in Taiwan with terminal cancer by years (2009–2011) and total.

<p>Cancer group I: nonmetastatic germ-cell tumors and prostate cancer; II: metastatic germ-cell tumors and prostate cancer; III: nonmetastatic lung, liver, and pancreatic cancer; IV: metastatic lung, liver, and pancreatic cancer; V: all other nonmetastatic cancers; VI: all other metastatic cancers; and VII: hematologic malignancies.</p><p>SD, standard deviation.</p><p>Baseline characteristics of older patients (age >65 years) in Taiwan with terminal cancer by years (2009–2011) and total.</p

Effects on SES categories on aggressive indicators of EOL care by multilevel logistic regression in older patients with cancer.

<p>* Adjusted for patient age, gender, hospital spending index, Charlson Comorbidity Index Score, cancer group, primary physician’s specialty, post-diagnosis survival, hospital characteristics, hospital caseload, urbanization and geographic region.</p><p>SES, socioeconomic status; EOL, end-of-life; OR, odds ratio; CI, confidence interval; ER, emergency department; ICU, Intensive care unit;</p><p>Effects on SES categories on aggressive indicators of EOL care by multilevel logistic regression in older patients with cancer.</p

Determinants of aggressive end-of-life care for Taiwanese cancer patients age 65 years and older, 2009–2011 by multivariate analysis using a random-intercept model (average indicator scores = 1.26±1.16).

<p>Cancer group I: nonmetastatic germ-cell tumors and prostate cancer; II: metastatic germ-cell tumors and prostate cancer; III: nonmetastatic lung, liver, and pancreatic cancer; IV: metastatic lung, liver, and pancreatic cancer; V: all other nonmetastatic cancers; VI: all other metastatic cancers; and VII: hematologic malignancies.</p><p>SES, socioeconomic status; EC, enrollee category. SD, standard deviation.</p><p>Determinants of aggressive end-of-life care for Taiwanese cancer patients age 65 years and older, 2009–2011 by multivariate analysis using a random-intercept model (average indicator scores = 1.26±1.16).</p

Effect of age on survival rates of patients with oral cancer (<i>n</i>=2339).

<p>Effect of age on survival rates of patients with oral cancer (<i>n</i>=2339).</p