Multideuteration of Nitroaromatics by Silver-Catalyzed Hydrogen-Isotope Exchange.

Silver-catalyzed deuteration of nitroaromatics has been achieved using D2O as the deuterium source. Distinct from the well-established directing group-guided hydrogen-isotope exchange, this protocol showed an interesting deuteration pattern, where considerable deuterium accumulation was observed around the aromatic rings. Controlling experiments suggested that the deuteration was initiated by a silver-promoted C-H activation. Therefore, a tentative two-stage deuteration mechanism involving aryl-silver species was proposed to explain the deuteration on meta- and para-positions.

Leveraging Large Data, Statistics, and Machine Learning to Predict the Emergence of Resistant E. coli Infections.

Drug-resistant Gram-negative bacterial infections, on average, increase the length of stay (LOS) in U.S. hospitals by 5 days, translating to approximately $15,000 per patient. We used statistical and machine-learning models to explore the relationship between antibiotic usage and antibiotic resistance over time and to predict the clinical and financial costs associated with resistant E. coli infections. We acquired data on antibiotic utilization and the resistance/sensitivity of 4776 microbial cultures at a Kaiser Permanente facility from April 2013 to December 2019. The ARIMA (autoregressive integrated moving average), neural networks, and random forest time series algorithms were employed to model antibiotic resistance trends. The models' performance was evaluated using mean absolute error (MAE) and root mean squared error (RMSE). The best performing model was then used to predict antibiotic resistance rates for the year 2020. The ARIMA model with cefazolin, followed by the one with cephalexin, provided the lowest RMSE and MAE values without signs of overfitting across training and test datasets. The study showed that reducing cefazolin usage could decrease the rate of resistant E. coli infections. Although piperacillin/tazobactam did not perform as well as cefazolin in our time series models, it performed reasonably well and, due to its broad spectrum, might be a practical target for interventions in antimicrobial stewardship programs (ASPs), at least for this particular facility. While a more generalized model could be developed with data from multiple facilities, this study acts as a framework for ASP clinicians to adopt statistical and machine-learning approaches, using region-specific data to make effective interventions.

Exploring genetic diversity and phylogenic relationships of Chinese cattle using gene mtDNA 16S rRNA.

The objective of this research was to characterize the genetic diversity and phylogenetic diversity among 12 cattle breeds (10 Chinese breeds and two foreign taurine breeds as controls) utilizing gene mtDNA 16S rRNA. The complete sequences of the mtDNA 16S rRNA genes of the 251 animals were 1570 bp long. The mean percentages of the four nitrogen bases were 37.8 % for adenine (A), 23.7 % for thymine (T), 20.9 % for cytosine (C), and 17.6 % for guanine (G). The mtDNA 16S rRNA gene base percentages had a strong bias towards A  +  T. All detected nucleotide variations in gene mtDNA 16S rRNA were either transitions (62.3 %) or transversions (37.7 %); no indels (insertions and deletions) were found. A total of 40 haplotypes were constructed based on these mutations. A total of 36 haplotypes of these 40 haplotypes were present in 10 Chinese cattle breeds. The haplotype diversity of all Chinese cattle populations was 0.903 ± 0.077 , while the nucleotide diversity was 0.0071 ± 0.0039 . Kimura's two-parameter genetic distances between pairs of the studied 12 breeds ranged from 0.001 to 0.010. The phylogenetic analysis assigned the 10 Chinese breeds to two distinct lineages that likely differed in their percentage of Bos taurus and Bos indicus ancestry.

Impact of Pharmacy Intervention on Prior Authorization Success and Efficiency at a University Medical Center.

BACKGROUND: Prior authorizations (PAs) may improve appropriate use of prescription medications. Despite potential savings for health insurance plans, the PA process is time consuming for the ordering provider, pharmacy, and patient. The UC Davis Health System (UCDHS) has created a centralized pharmacy-run clinic PA process. OBJECTIVE: To compare the mean PA processing time between the new centralized clinic and usual care and provide secondary endpoints for PA approval rates, time to prescription fill, time to prescription pick-up, total staff time, and estimated labor costs. METHODS: This is a prospective observational study comparing sequential PA requests at the UCDHS centralized clinic (intervention) and other UCDHS clinics (usual care) between January 1, 2014, and December 31, 2014. The Cochran-Mantel-Haenszel test was used to compare dichotomous outcomes (approval/denial rates) between the 2 groups, controlling for insurance type. A generalized linear model was applied for comparing the continuous outcomes (PA process time, time to first fill, time to pick-up, and cost) with insurance type as covariate. RESULTS: For the intervention group, 47 PAs were evaluated, and 77 PAs were evaluated in the usual care group. The average PA process time was 0.53 days for the intervention group versus 7.02 days for usual care (P < 0.001), and the PA approval rate was 93% for the intervention group versus 68% for usual care (P < 0.002). The mean time to fill was 2.49 days and 5.52 days for the intervention and usual care clinics, respectively (P = 0.02). The pick-up percentage was 75% versus 52% for intervention and usual care, respectively (P < 0.001). The intervention clinic spent a significantly lower mean time processing PAs (15 minutes vs. 64 minutes) compared with the usual care clinics (P < 0.001). It is estimated that the mean total labor cost per PA at the intervention clinic was $11.50 compared with $37.50 for the usual care clinics (P < 0.001). CONCLUSIONS: Pharmacy-led interventions in PA processing resulted in a statistically significant benefit in improving time to PA approval, time to first fill, and time to pick-up. DISCLOSURES: No outside funding supported this study. The authors report no conflicting interests. Melnikow and Cutler contributed the study concept and design, with assistance from the other authors. Lester, Barca, and She collected the data, and Xin performed all statistical analysis. Cutler was the major contributor to manuscript preparation, with assistance from the other authors.