Literature-based discovery of diabetes- and ROS-related targets

Abstract Background Reactive oxygen species (ROS) are known mediators of cellular damage in multiple diseases including diabetic complications. Despite its importance, no comprehensive database is currently available for the genes associated with ROS. Methods We present ROS- and diabetes-related targets (genes/proteins) collected from the biomedical literature through a text mining technology. A web-based literature mining tool, SciMiner, was applied to 1,154 biomedical papers indexed with diabetes and ROS by PubMed to identify relevant targets. Over-represented targets in the ROS-diabetes literature were obtained through comparisons against randomly selected literature. The expression levels of nine genes, selected from the top ranked ROS-diabetes set, were measured in the dorsal root ganglia (DRG) of diabetic and non-diabetic DBA/2J mice in order to evaluate the biological relevance of literature-derived targets in the pathogenesis of diabetic neuropathy. Results SciMiner identified 1,026 ROS- and diabetes-related targets from the 1,154 biomedical papers (http://jdrf.neurology.med.umich.edu/ROSDiabetes/). Fifty-three targets were significantly over-represented in the ROS-diabetes literature compared to randomly selected literature. These over-represented targets included well-known members of the oxidative stress response including catalase, the NADPH oxidase family, and the superoxide dismutase family of proteins. Eight of the nine selected genes exhibited significant differential expression between diabetic and non-diabetic mice. For six genes, the direction of expression change in diabetes paralleled enhanced oxidative stress in the DRG. Conclusions Literature mining compiled ROS-diabetes related targets from the biomedical literature and led us to evaluate the biological relevance of selected targets in the pathogenesis of diabetic neuropathy.http://deepblue.lib.umich.edu/bitstream/2027.42/78315/1/1755-8794-3-49.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/2/1755-8794-3-49-S7.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/3/1755-8794-3-49-S10.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/4/1755-8794-3-49-S8.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/5/1755-8794-3-49-S3.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/6/1755-8794-3-49-S1.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/7/1755-8794-3-49-S4.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/8/1755-8794-3-49-S2.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/9/1755-8794-3-49-S12.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/10/1755-8794-3-49-S11.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/11/1755-8794-3-49-S9.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/12/1755-8794-3-49-S5.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/13/1755-8794-3-49-S6.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/14/1755-8794-3-49.pdfPeer Reviewe

Clinicians' caseload management behaviours as explanatory factors in patients' length of time on caseloads : a predictive multilevel study in paediatric community occupational therapy

Peer reviewedPublisher PD

The Cosmology of Composite Inelastic Dark Matter

Composite dark matter is a natural setting for implementing inelastic dark matter - the O(100 keV) mass splitting arises from spin-spin interactions of constituent fermions. In models where the constituents are charged under an axial U(1) gauge symmetry that also couples to the Standard Model quarks, dark matter scatters inelastically off Standard Model nuclei and can explain the DAMA/LIBRA annual modulation signal. This article describes the early Universe cosmology of a minimal implementation of a composite inelastic dark matter model where the dark matter is a meson composed of a light and a heavy quark. The synthesis of the constituent quarks into dark mesons and baryons results in several qualitatively different configurations of the resulting dark matter hadrons depending on the relative mass scales in the system.Comment: 31 pages, 4 figures; references added, typos correcte

Ecological expected utility and the mythical neural code

Neural spikes are an evolutionarily ancient innovation that remains nature’s unique mechanism for rapid, long distance information transfer. It is now known that neural spikes sub serve a wide variety of functions and essentially all of the basic questions about the communication role of spikes have been answered. Current efforts focus on the neural communication of probabilities and utility values involved in decision making. Significant progress is being made, but many framing issues remain. One basic problem is that the metaphor of a neural code suggests a communication network rather than a recurrent computational system like the real brain. We propose studying the various manifestations of neural spike signaling as adaptations that optimize a utility function called ecological expected utility

Adenocarcinoma of the caecum metastatic to the bladder: an unusual cause of haematuria

BACKGROUND: Primary malignancies of colorectal origin can metastasise to the bladder. Reports are however extremely rare, particularly from the caecum. CASE REPORT: The report describes the case of a 45-year old male with Duke's B caecal carcinoma treated with a laparoscopically-assisted right hemicolectomy and adjuvant 5-Fluorouracil chemotherapy. Subsequently, a metastatic lesion to the bladder was demonstrated and successfully excised by partial cystectomy. CONCLUSION: In order that optimal therapeutic options can be determined, it is important for clinicians to distinguish between primary disease of the bladder and other causes of haematuria. Various immunohistochemical techniques attempt to differentiate primary adenocarcinoma of the bladder from secondary colorectal adenocarcinoma. Suspicion of metastatic disease must be raised when histologically unusual bladder tumours are identified

Healthcare costs and utilization for Medicare beneficiaries with Alzheimer's

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease (AD) is a neurodegenerative disorder incurring significant social and economic costs. This study uses a US administrative claims database to evaluate the effect of AD on direct healthcare costs and utilization, and to identify the most common reasons for AD patients' emergency room (ER) visits and inpatient admissions.</p> <p>Methods</p> <p>Demographically matched cohorts age 65 and over with comprehensive medical and pharmacy claims from the 2003–2004 MEDSTAT MarketScan^®Medicare Supplemental and Coordination of Benefits (COB) Database were examined: 1) 25,109 individuals with an AD diagnosis or a filled prescription for an exclusively AD treatment; and 2) 75,327 matched controls. Illness burden for each person was measured using Diagnostic Cost Groups (DCGs), a comprehensive morbidity assessment system. Cost distributions and reasons for ER visits and inpatient admissions in 2004 were compared for both cohorts. Regression was used to quantify the marginal contribution of AD to health care costs and utilization, and the most common reasons for ER and inpatient admissions, using DCGs to control for overall illness burden.</p> <p>Results</p> <p>Compared with controls, the AD cohort had more co-morbid medical conditions, higher overall illness burden, and higher but less variable costs ($13,936 s.$10,369; Coefficient of variation = 181 vs. 324). Significant excess utilization was attributed to AD for inpatient services, pharmacy, ER visits, and home health care (all p < 0.05). In particular, AD patients were far more likely to be hospitalized for infections, pneumonia and falls (hip fracture, syncope, collapse).</p> <p>Conclusion</p> <p>Patients with AD have significantly more co-morbid medical conditions and higher healthcare costs and utilization than demographically-matched Medicare beneficiaries. Even after adjusting for differences in co-morbidity, AD patients incur excess ER visits and inpatient admissions.</p

Smoking Cessation Among Women with and at Risk for HIV: Are They Quitting?

Cigarette smoking is an important risk factor for adverse health events in HIV-infected populations. While recent US population-wide surveys report annual sustained smoking cessation rates of 3.4–8.5%, prospective data are lacking on cessation rates for HIV-infected smokers. To determine the sustained tobacco cessation rate and predictors of cessation among women with or at risk for HIV infection. Prospective cohort study. A total of 747 women (537 HIV-infected and 210 HIV-uninfected) who reported smoking at enrollment (1994–1995) in the Women’s Interagency HIV Study (WIHS) and remained in follow-up after 10 years. The participants were mostly minority (61% non-Hispanic Blacks and 22% Hispanics) and low income (68% with reported annual incomes of less than or equal to $12,000). The primary outcome was defined as greater than 12 months continuous cessation at year 10. Multivariate logistic regression was used to identify independent baseline predictors of subsequent tobacco cessation. A total of 121 (16%) women reported tobacco cessation at year 10 (annual sustained cessation rate of 1.8%, 95% CI 1.6–2.1%). Annual sustained cessation rates were 1.8% among both HIV-positive and HIV-negative women (p = 0.82). In multivariate analysis, the odds of tobacco cessation were significantly higher in women with more years of education (p trend = 0.02) and of Hispanic origin (OR = 1.87, 95% CI = 1.4–2.9) compared to Black women. Cessation was significantly lower in current or former illicit drug users (OR = 0.42 95% CI = 0.24–0.74 and OR = 0.65, 95% CI = 0.49–0.86, respectively, p trend = 0.03) and women reporting a higher number of cigarettes per day at baseline (p trend &lt; 0.001). HIV-infected and at-risk women in this cohort have lower smoking cessation rates than the general population. Given the high prevalence of smoking, the high risk of adverse health events from smoking, and low rates of cessation, it is imperative that we increase efforts and overcome barriers to help these women quit smoking

Medical student attitudes toward video games and related new media technologies in medical education

<p>Abstract</p> <p>Background</p> <p>Studies in K-12 and college students show that their learning preferences have been strongly shaped by new media technologies like video games, virtual reality environments, the Internet, and social networks. However, there is no known research on medical students' game experiences or attitudes towards new media technologies in medical education. This investigation seeks to elucidate medical student experiences and attitudes, to see whether they warrant the development of new media teaching methods in medicine.</p> <p>Methods</p> <p>Medical students from two American universities participated. An anonymous, 30-item, cross-sectional survey addressed demographics, game play experience and attitudes on using new media technologies in medical education. Statistical analysis identified: 1) demographic characteristics; 2) differences between the two universities; 3) how video game play differs across gender, age, degree program and familiarity with computers; and 4) characteristics of students who play most frequently.</p> <p>Results</p> <p>217 medical students participated. About half were female (53%). Respondents liked the idea of using technology to enhance healthcare education (98%), felt that education should make better use of new media technologies (96%), and believed that video games can have educational value (80%). A majority (77%) would use a multiplayer online healthcare simulation on their own time, provided that it helped them to accomplish an important goal. Men and women agreed that they were most inclined to use multiplayer simulations if they were fun (97%), and if they helped to develop skill in patient interactions (90%). However, there was significant gender dissonance over types of favorite games, the educational value of video games, and the desire to participate in games that realistically replicated the experience of clinical practice.</p> <p>Conclusions</p> <p>Overall, medical student respondents, including many who do not play video games, held highly favorable views about the use of video games and related new media technology in medical education. Significant gender differences in game play experience and attitudes may represent male video game design bias that stresses male cognitive aptitudes; medical educators hoping to create serious games that will appeal to both men and women must avoid this.</p

Balancing Feed-Forward Excitation and Inhibition via Hebbian Inhibitory Synaptic Plasticity

It has been suggested that excitatory and inhibitory inputs to cortical cells are balanced, and that this balance is important for the highly irregular firing observed in the cortex. There are two hypotheses as to the origin of this balance. One assumes that it results from a stable solution of the recurrent neuronal dynamics. This model can account for a balance of steady state excitation and inhibition without fine tuning of parameters, but not for transient inputs. The second hypothesis suggests that the feed forward excitatory and inhibitory inputs to a postsynaptic cell are already balanced. This latter hypothesis thus does account for the balance of transient inputs. However, it remains unclear what mechanism underlies the fine tuning required for balancing feed forward excitatory and inhibitory inputs. Here we investigated whether inhibitory synaptic plasticity is responsible for the balance of transient feed forward excitation and inhibition. We address this issue in the framework of a model characterizing the stochastic dynamics of temporally anti-symmetric Hebbian spike timing dependent plasticity of feed forward excitatory and inhibitory synaptic inputs to a single post-synaptic cell. Our analysis shows that inhibitory Hebbian plasticity generates ‘negative feedback’ that balances excitation and inhibition, which contrasts with the ‘positive feedback’ of excitatory Hebbian synaptic plasticity. As a result, this balance may increase the sensitivity of the learning dynamics to the correlation structure of the excitatory inputs

Gene expression of circulating tumour cells in breast cancer patients

<p>Abstract</p> <p>Background</p> <p>The diagnostic tools to predict the prognosis in patients suffering from breast cancer (BC) need further improvements. New technological achievements like the gene profiling of circulating tumour cells (CTC) could help identify new prognostic markers in the clinical setting. Furthermore, gene expression patterns of CTC might provide important informations on the mechanisms of tumour cell metastasation.</p> <p>Materials and methods</p> <p>We performed realtime-PCR and multiplex-PCR analyses following immunomagnetic separation of CTC. Peripheral blood (PB) samples of 63 patients with breast cancer of various stages were analyzed and compared to a control group of 14 healthy individuals. After reverse-transcription, we performed multiplex PCR using primers for the genes <it>ga733.3, muc-1 </it>and <it>c-erbB2. Mammaglobin1, spdef </it>and <it>c-erbB2 </it>were analyzed applying realtime-PCR.</p> <p>Results</p> <p><it>ga733.2 </it>overexpression was found in 12.7% of breast cancer cases, <it>muc-1 </it>in 15.9%, <it>mgb1 </it>in 9.1% and <it>spdef </it>in 12.1%. In this study, <it>c-erbB2 </it>did not show any significant correlation to BC, possibly due to a highly ambient expression. Besides single gene analyses, gene profiles were additionally evaluated. Highly significant correlations to BC were found in single gene analyses of <it>ga733.2 </it>and <it>muc-1 </it>and in gene profile analyses of <it>ga733.3</it>*<it>muc-1 </it>and GA7 <it>ga733.3</it>*muc-1*<it>mgb1</it>*<it>spdef</it>.</p> <p>Conclusion</p> <p>Our study reveals that the single genes <it>ga733.3, muc-1 </it>and the gene profiles <it>ga733.3</it>*<it>muc-1 </it>and <it>ga733.3</it>*3<it>muc-1</it>*<it>mgb1</it>*<it>spdef </it>can serve as markers for the detection of CTC in BC. The multigene analyses found highly positive levels in BC patients. Our study indicates that not single gene analyses but subtle patterns of multiple genes lead to rising accuracy and low loss of specificity in detection of breast cancer cases.</p