Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller–Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated

Sunitinib malate in the treatment of recurrent or persistent uterine leiomyosarcoma: A Gynecologic Oncology Group phase II study

New agents are needed for patients with metastatic uterine leiomyosarcoma who progress after treatment with doxorubicin or gemcitabine-docetaxel. Agents targeting tumor vasculature have potential for activity in leiomyosarcoma. We aimed to assess the activity of sunitinib in patients with recurrent uterine leiomyosarcoma who had received one or two prior therapies by determining the frequency of patients who survived progression-free for at least six months or who achieved objective tumor response. We also aimed to characterize the toxicity of sunitinib and to estimate time-to-progression

The Effect of Urban Street Gang Densities on Small Area Homicide Incidence in a Large Metropolitan County, 1994–2002

The presence of street gangs has been hypothesized as influencing overall levels of violence in urban communities through a process of gun–drug diffusion and cross-type homicide. This effect is said to act independently of other known correlates of violence, i.e., neighborhood poverty. To test this hypothesis, we independently assessed the impact of population exposure to local street gang densities on 8-year homicide rates in small areas of Los Angeles County, California. Homicide data from the Los Angeles County Coroners Office were analyzed with original field survey data on street gang locations, while controlling for the established covariates of community homicide rates. Bivariate and multivariate regression analyses explicated strong relationships between homicide rates, gang density, race/ethnicity, and socioeconomic structure. Street gang densities alone had cumulative effects on small area homicide rates. Local gang densities, along with high school dropout rates, high unemployment rates, racial and ethnic concentration, and higher population densities, together explained 90% of the variation in local 8-year homicide rates. Several other commonly considered covariates were insignificant in the model. Urban environments with higher densities of street gangs exhibited higher overall homicide rates, independent of other community covariates of homicide. The unique nature of street gang killings and their greater potential to influence future local rates of violence suggests that more direct public health interventions are needed alongside traditional criminal justice mechanisms to combat urban violence and homicides

Reaching the Hard-to-Reach: A Probability Sampling Method for Assessing Prevalence of Driving under the Influence after Drinking in Alcohol Outlets

Drinking alcoholic beverages in places such as bars and clubs may be associated with harmful consequences such as violence and impaired driving. However, methods for obtaining probabilistic samples of drivers who drink at these places remain a challenge – since there is no a priori information on this mobile population – and must be continually improved. This paper describes the procedures adopted in the selection of a population-based sample of drivers who drank at alcohol selling outlets in Porto Alegre, Brazil, which we used to estimate the prevalence of intention to drive under the influence of alcohol. The sampling strategy comprises a stratified three-stage cluster sampling: 1) census enumeration areas (CEA) were stratified by alcohol outlets (AO) density and sampled with probability proportional to the number of AOs in each CEA; 2) combinations of outlets and shifts (COS) were stratified by prevalence of alcohol-related traffic crashes and sampled with probability proportional to their squared duration in hours; and, 3) drivers who drank at the selected COS were stratified by their intention to drive and sampled using inverse sampling. Sample weights were calibrated using a post-stratification estimator. 3,118 individuals were approached and 683 drivers interviewed, leading to an estimate that 56.3% (SE = 3,5%) of the drivers intended to drive after drinking in less than one hour after the interview. Prevalence was also estimated by sex and broad age groups. The combined use of stratification and inverse sampling enabled a good trade-off between resource and time allocation, while preserving the ability to generalize the findings. The current strategy can be viewed as a step forward in the efforts to improve surveys and estimation for hard-to-reach, mobile populations

Experiential learning and the acquisition of managerial tacit knowledge

Tacit knowledge is believed to be one factor that distinguishes successful managers from others. We sought to determine whether levels of accumulated managerial tacit knowledge (LAMTK) were associated with managers' dominant learning styles. Instruments used in the study, involving 356 Malaysian public sector employees, included Sternberg et al.'s (2000) Tacit Knowledge Inventory for Managers and a normative version of Kolb's (1999a) Learning Styles Inventory (LSI-Ill). Findings suggest that LAMTK is independent of the length of subjects' general work experience, but positively related to the amount of time spent working in a management context. Learning styles also had a significant relationship. Subjects who spent most of their time performing management functions and whose dominant learning styles were accommodating had significantly higher LAMTK than those with different learning styles. We also found support for the belief that learners with a strong preference for all four different abilities defined in Kolb's learning theory may be critical for effective experiential learning