Bacterial infection in association with snakebite: A 10-year experience in a northern Taiwan medical center

BackgroundMicrobiological data of secondary wound infections following snakebites is rarely reported in Taiwan. The objective of this study was to assess the secondary wound infection after venomous snakebites.MethodsWe conducted a 10-year retrospective survey on patients admitted for venomous snakebites and microbiological data of wound cultures at a medical center in northern Taiwan.ResultsBetween April 2001 and April 2010, 231 patients who experienced snakebites were included. Male predominated, accounting for 62.3% (144). The age range of patients was 4–95 years. Ninety-five (41.1%) people were bitten by Trimeresurus mucrosquamatus, followed by Tstejnegeri, and cobra. A total of 61 pathogens were obtained from 21 patients. Thirty-nine (63.9%) isolates were gram-negative bacteria, 14 (23%) gram-positive pathogens, and 8 (13.1%) anaerobic pathogens. There were 17 patients bitten by cobra in these 21 patients. Morganella morganii and Enterococcus species were the most common pathogens identified in the wound cultures.ConclusionCobra bite causes more severe bacterial infection than other kinds of snakebites. Oral amoxicillin/clavulanate plus ciprofloxacin or parenteral piperacillin/tazobactam alone can be the choices for empirical or definitive treatment, and surgical intervention should be considered for established invasive soft tissue infections

Online Updating of Statistical Inference in the Big Data Setting

We present statistical methods for big data arising from online analytical processing, where large amounts of data arrive in streams and require fast analysis without storage/access to the historical data. In particular, we develop iterative estimating algorithms and statistical inferences for linear models and estimating equations that update as new data arrive. These algorithms are computationally efficient, minimally storage-intensive, and allow for possible rank deficiencies in the subset design matrices due to rare-event covariates. Within the linear model setting, the proposed online-updating framework leads to predictive residual tests that can be used to assess the goodness-of-fit of the hypothesized model. We also propose a new online-updating estimator under the estimating equation setting. Theoretical properties of the goodness-of-fit tests and proposed estimators are examined in detail. In simulation studies and real data applications, our estimator compares favorably with competing approaches under the estimating equation setting.Comment: Submitted to Technometric

Effects of Geometrical Symmetry on the Vortex Nucleation and Penetration in Mesoscopic Superconductors

We investigate how the geometrical symmetry affects the penetration and arrangement of vortices in mesoscopic superconductors using self-consistent Bogoliubov-de Gennes equations. We find that the entrance of the vortex happens when the current density at the hot spots reaches the depairing current density. Through determining the spatial distribution of hot spots, the geometrical symmetry of the superconducting sample influences the nucleation and entrance of vortices. Our results propose one possible experimental approach to control and manipulate the quantum states of mesoscopic superconductors with their topological geometries, and they can be easily generalized to the confined superfluids and Bose-Einstein condensates

Methyl 5-bromo-6-methyl­picolinate

The title compound, C8H8BrNO2, does not show any significant inter­molecular π–π or C—H⋯π inter­actions in the crystal packing except for one weak Br⋯Br [3.715 (1) Å] inter­action