Antibiotic use among future health professionals: A multicentre cross sectional study of Chinese medical student

Background: Antibiotic use leads to antibiotic resistance and antibiotic misuse is high in China and other developing countries. This may arise from beliefs and behaviours of doctors and the pressure they receive from patients. This study aims to understand antibiotic use behaviour for self-limited illness among medical students - the future healthcare professionals. Methods: This is part of a large cross-sectional study of Chinese university students of science, social science and humanities, and medicine. An electronic survey health belief model (HBM) questionnaire was distributed at six universities in China from September to November 2015. The score assessment was based on the constructs of HBM theory. Chi-squared and multivariable logistic regression and adjusted odd ratios (aOR) were used to assess the relationship between demographic characteristics, antibiotic use knowledge and behaviour. Results: In total, 11455 students were asked to participate and 11192 (97.5%) completed the questionnaires. 1819 medical students completed the survey. In the past month 529 (29%) medical students reported at least one self-limited illness. Of those, 285 (54%) self-medicated and 77 (27%) of them used antibiotics. 111 (21%) saw a doctor among whom 64 (58%) received antibiotics. 133 (25%) did nothing. In the past year, 279 (15%) of students used antibiotics for prophylaxis, 273 (15%) ever demanded an antibiotic from a doctor, 1166 (64%) kept a personal stock of antibiotics, 1034 (57%) bought antibiotics at a pharmacy, 97% of these without a prescription. Students with high HBM scores about antibiotics were significantly less likely to self-medicate with antibiotics (aOR 0.37, 95% CI 0.15-0.91, p=0.031), to use antibiotics for prophylaxis (aOR 0.35, 95% CI 0.21-0.60, p<0.0001) or demand an antibiotic (aOR 0.46, 95% CI 0.26-0.81, p=0.007). Students whose father has a higher education level, whose mother is a doctor or who are from urban areas were more likely to stock antibiotics and self-medicate. Conclusion: High rates of antibiotic self-medication (54%) and stocking (64%) were found among medical students. Along with the high rates of unnecessarily prescribed antibiotics by doctors (58%), there is clearly a need for effective antibiotic stewardship and training programs in Chinese healthcare institutions and medical schools.published_or_final_versio

Application of the speed-duration relationship to normalize the intensity of high-intensity interval training

The tolerable duration of continuous high-intensity exercise is determined by the hyperbolic Speed-tolerable duration (S-tLIM) relationship. However, application of the S-tLIM relationship to normalize the intensity of High-Intensity Interval Training (HIIT) has yet to be considered, with this the aim of present study. Subjects completed a ramp-incremental test, and series of 4 constant-speed tests to determine the S-tLIM relationship. A sub-group of subjects (n = 8) then repeated 4 min bouts of exercise at the speeds predicted to induce intolerance at 4 min (WR4), 6 min (WR6) and 8 min (WR8), interspersed with bouts of 4 min recovery, to the point of exercise intolerance (fixed WR HIIT) on different days, with the aim of establishing the work rate that could be sustained for 960 s (i.e. 4×4 min). A sub-group of subjects (n = 6) also completed 4 bouts of exercise interspersed with 4 min recovery, with each bout continued to the point of exercise intolerance (maximal HIIT) to determine the appropriate protocol for maximizing the amount of high-intensity work that can be completed during 4×4 min HIIT. For fixed WR HIIT tLIM of HIIT sessions was 399±81 s for WR4, 892±181 s for WR6 and 1517±346 s for WR8, with total exercise durations all significantly different from each other (P&#60;0.050). For maximal HIIT, there was no difference in tLIM of each of the 4 bouts (Bout 1: 229±27 s; Bout 2: 262±37 s; Bout 3: 235±49 s; Bout 4: 235±53 s; P&#62;0.050). However, there was significantly less high-intensity work completed during bouts 2 (153.5±40. 9 m), 3 (136.9±38.9 m), and 4 (136.7±39.3 m), compared with bout 1 (264.9±58.7 m; P&#62;0.050). These data establish that WR6 provides the appropriate work rate to normalize the intensity of HIIT between subjects. Maximal HIIT provides a protocol which allows the relative contribution of the work rate profile to physiological adaptations to be considered during alternative intensity-matched HIIT protocols

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Preconditioning of mesenchymal stromal cells with low-intensity ultrasound: influence on chondrogenesis and directed SOX9 signaling pathways

Background: Continuous low-intensity ultrasound (cLIUS) facilitates the chondrogenic differentiation of human mesenchymal stromal cells (MSCs) in the absence of exogenously added transforming growth factor-beta (TGFβ) by upregulating the expression of transcription factor SOX9, a master regulator of chondrogenesis. The present study evaluated the molecular events associated with the signaling pathways impacting SOX9 gene and protein expression under cLIUS. Methods: Human bone marrow-derived MSCs were exposed to cLIUS stimulation at 14 kPa (5 MHz, 2.5 Vpp) for 5 min. The gene and protein expression of SOX9 was evaluated. The specificity of SOX9 upregulation under cLIUS was determined by treating the MSCs with small molecule inhibitors of select signaling molecules, followed by cLIUS treatment. Signaling events regulating SOX9 expression under cLIUS were analyzed by gene expression, immunofluorescence staining, and western blotting. Results: cLIUS upregulated the gene expression of SOX9 and enhanced the nuclear localization of SOX9 protein when compared to non-cLIUS-stimulated control. cLIUS was noted to enhance the phosphorylation of the signaling molecule ERK1/2. Inhibition of MEK/ERK1/2 by PD98059 resulted in the effective abrogation of cLIUS-induced SOX9 expression, indicating that cLIUS-induced SOX9 upregulation was dependent on the phosphorylation of ERK1/2. Inhibition of integrin and TRPV4, the upstream cell-surface effectors of ERK1/2, did not inhibit the phosphorylation of ERK1/2 and therefore did not abrogate cLIUS-induced SOX9 expression, thereby suggesting the involvement of other mechanoreceptors. Consequently, the effect of cLIUS on the actin cytoskeleton, a mechanosensitive receptor regulating SOX9, was evaluated. Diffused and disrupted actin fibers observed in MSCs under cLIUS closely resembled actin disruption by treatment with cytoskeletal drug Y27632, which is known to increase the gene expression of SOX9. The upregulation of SOX9 under cLIUS was, therefore, related to cLIUS-induced actin reorganization. SOX9 upregulation induced by actin reorganization was also found to be dependent on the phosphorylation of ERK1/2. Conclusions: Collectively, preconditioning of MSCs by cLIUS resulted in the nuclear localization of SOX9, phosphorylation of ERK1/2 and disruption of actin filaments, and the expression of SOX9 was dependent on the phosphorylation of ERK1/2 under cLIUS

Macrofossil evidence for a rapid and severe Cretaceous–Paleogene mass extinction in Antarctica

Debate continues about the nature of the Cretaceous–Paleogene (K–Pg) mass extinction event. An abrupt crisis triggered by a bolide impact contrasts with ideas of a more gradual extinction involving flood volcanism or climatic changes. Evidence from high latitudes has also been used to suggest that the severity of the extinction decreased from low latitudes towards the poles. Here we present a record of the K–Pg extinction based on extensive assemblages of marine macrofossils (primarily new data from benthic molluscs) from a highly expanded Cretaceous–Paleogene succession: the López de Bertodano Formation of Seymour Island, Antarctica. We show that the extinction was rapid and severe in Antarctica, with no significant biotic decline during the latest Cretaceous, contrary to previous studies. These data are consistent with a catastrophic driver for the extinction, such as bolide impact, rather than a significant contribution from Deccan Traps volcanism during the late Maastrichtian

Dynamic Analysis of Vascular Morphogenesis Using Transgenic Quail Embryos

Background: One of the least understood and most central questions confronting biologists is how initially simple clusters or sheet-like cell collectives can assemble into highly complex three-dimensional functional tissues and organs. Due to the limits of oxygen diffusion, blood vessels are an essential and ubiquitous presence in all amniote tissues and organs. Vasculogenesis, the de novo self-assembly of endothelial cell (EC) precursors into endothelial tubes, is the first step in blood vessel formation [1]. Static imaging and in vitro models are wholly inadequate to capture many aspects of vascular pattern formation in vivo, because vasculogenesis involves dynamic changes of the endothelial cells and of the forming blood vessels, in an embryo that is changing size and shape. Methodology/Principal Findings: We have generated Tie1 transgenic quail lines Tg(tie1:H2B-eYFP) that express H2B-eYFP in all of their endothelial cells which permit investigations into early embryonic vascular morphogenesis with unprecedented clarity and insight. By combining the power of molecular genetics with the elegance of dynamic imaging, we follow the precise patterning of endothelial cells in space and time. We show that during vasculogenesis within the vascular plexus, ECs move independently to form the rudiments of blood vessels, all while collectively moving with gastrulating tissues that flow toward the embryo midline. The aortae are a composite of somatic derived ECs forming its dorsal regions and the splanchnic derived ECs forming its ventral region. The ECs in the dorsal regions of the forming aortae exhibit variable mediolateral motions as they move rostrally; those in more ventral regions show significant lateral-to-medial movement as they course rostrally. Conclusions/Significance: The present results offer a powerful approach to the major challenge of studying the relative role(s) of the mechanical, molecular, and cellular mechanisms of vascular development. In past studies, the advantages of the molecular genetic tools available in mouse were counterbalanced by the limited experimental accessibility needed for imaging and perturbation studies. Avian embryos provide the needed accessibility, but few genetic resources. The creation of transgenic quail with labeled endothelia builds upon the important roles that avian embryos have played in previous studies of vascular development

How to survey displaced workers in Switzerland ? Sources of bias and ways around them

Studying career outcomes after job loss is challenging because individually displaced worker form a self-selected group. Indeed, the same factors causing the workers to lose their jobs, such as lack of motivation, may also reduce their re-employment prospects. Using data from plant closures where all workers were displaced irrespective of their individual characteristics offers a way around this selection bias. There is no systematic data collection on workers displaced by plant closure in Switzerland. Accordingly, we conducted our own survey on 1200 manufacturing workers who had lost their job 2 years earlier. The analysis of observational data gives rise to a set of methodological challenges, in particular nonresponse bias. Our survey addressed this issue by mixing data collection modes and repeating contact attempts. In addition, we combined the survey data with data from the public unemployment register to examine the extent of nonresponse bias. Our analysis suggests that some of our adjustments helped to reduce bias. Repeated contact attempts increased the response rate, but did not reduce nonresponse bias. In contrast, using telephone interviews in addition to paper questionnaires helped to substantially improve the participation of typically underrepresented subgroups. However, the survey respondents still differ from nonrespondents in terms of age, education and occupation. Interestingly, these differences have no significant impact on the substantial conclusion about displaced workers' re-employment prospects

Patterns of sick-leave and health outcomes in injured workers with back pain

Little is known about the sick-leave experiences of workers who make a workers’ compensation claim for back pain. Our objective is to describe the 1-year patterns of sick-leave and the health outcomes of a cohort of workers who make a workers’ compensation claim for back pain. We studied a cohort of 1,831 workers from five large US firms who made incident workers’ compensation claims for back pain between January 1, 1999 and June 30, 2002. Injured workers were interviewed 1 month (n = 1,321), 6 months (n = 810) and 1 year (n = 462) following the onset of their pain. We described the course of back pain using four patterns of sick-leave: (1) no sick-leave, (2) returned to worked and stayed, (3) multiple episodes of sick-leave and (4) not yet returned to work. We described the health outcomes as back and/or leg pain intensity, functional limitations and health-related quality of life. We analyzed data from participants who completed all follow-up interviews (n = 457) to compute the probabilities of transition between patterns of sick-leave. A significant proportion of workers experienced multiple episodes of sick-leave (30.2%; 95% CI 25.0–35.1) during the 1-year follow-up. The proportion of workers who did not report sick-leave declined from 42.4% (95% CI 39.0–46.1) at 1 month to 33.6% (28.0–38.7) at 1 year. One year after the injury, 2.9% (1.6–4.9) of workers had not yet returned to work. Workers who did not report sick-leave and those who returned and stayed at work reported better health outcomes than workers who experienced multiple episodes of sick-leave or workers who had not returned to work. Almost a third of workers with an incident episode of back pain experience recurrent spells of work absenteeism during the following year. Our data suggest that stable patterns of sick-leave are associated with better health

Verified global optimization for estimating the parameters of nonlinear models

Nonlinear parameter estimation is usually achieved via the minimization of some possibly non-convex cost function. Interval analysis allows one to derive algorithms for the guaranteed characterization of the set of all global minimizers of such a cost function when an explicit expression for the output of the model is available or when this output is obtained via the numerical solution of a set of ordinary differential equations. However, cost functions involved in parameter estimation are usually challenging for interval techniques, if only because of multi-occurrences of the parameters in the formal expression of the cost. This paper addresses parameter estimation via the verified global optimization of quadratic cost functions. It introduces tools for the minimization of generic cost functions. When an explicit expression of the output of the parametric model is available, significant improvements may be obtained by a new box exclusion test and by careful manipulations of the quadratic cost function. When the model is described by ODEs, some of the techniques available in the previous case may still be employed, provided that sensitivity functions of the model output with respect to the parameters are available