Suizid und Internet

The number of people aged 14 and older that use the Internet in Germany has doubled to 35.7 millions (55.3%) since the year 2000. The Internet also more and more expands into the domain of psychiatry and psychotherapy, and is used by psychiatric patients for information, communication and therapeutic purposes. Nevertheless, the infinite possibilities of the World Wide Web are linked with several advantages and disadvantages. Easily accessible information, numerous opportunities for exchange among like-minded people and therapeutic support from online therapies are juxtaposed with such risks as frequently lacking quality and transparency of the available information, possible enhancement of social withdrawal and certain Websites concerning suicide. If the mentioned risks of the Internet rather provoke new problems and trigger suicidality or if the chance of an easily accessible online discussion rather results in mental relief cannot be answered generally

Calculating confidence intervals for impact numbers

BACKGROUND: Standard effect measures such as risk difference and attributable risk are frequently used in epidemiological studies and public health research to describe the effect of exposures. Recently, so-called impact numbers have been proposed, which express the population impact of exposures in form of specific person or case numbers. To describe estimation uncertainty, it is necessary to calculate confidence intervals for these new effect measures. In this paper, we present methods to calculate confidence intervals for the new impact numbers in the situation of cohort studies. METHODS: Beside the exposure impact number (EIN), which is equivalent to the well-known number needed to treat (NNT), two other impact numbers are considered: the case impact number (CIN) and the exposed cases impact number (ECIN), which describe the number of cases (CIN) and the number of exposed cases (ECIN) with an outcome among whom one case is attributable to the exposure. The CIN and ECIN represent reciprocals of the population attributable risk (PAR) and the attributable fraction among the exposed (AF(e)), respectively. Thus, confidence intervals for these impact numbers can be calculated by inverting and exchanging the confidence limits of the PAR and AF(e). EXAMPLES: We considered a British and a Japanese cohort study that investigated the association between smoking and death from coronary heart disease (CHD) and between smoking and stroke, respectively. We used the reported death and disease rates and calculated impact numbers with corresponding 95% confidence intervals. In the British study, the CIN was 6.46, i.e. on average, of any 6 to 7 persons who died of CHD, one case was attributable to smoking with corresponding 95% confidence interval of [3.84, 20.36]. For the exposed cases, the results of ECIN = 2.64 with 95% confidence interval [1.76, 5.29] were obtained. In the Japanese study, the CIN was 6.67, i.e. on average, of the 6 to 7 persons who had a stroke, one case was attributable to smoking with corresponding 95% confidence interval of [3.80, 27.27]. For the exposed cases, the results of ECIN = 4.89 with 95% confidence interval of [2.86, 16.67] were obtained. CONCLUSION: The consideration of impact numbers in epidemiological analyses provides additional information and helps the interpretation of study results, e.g. in public health research. In practical applications, it is necessary to describe estimation uncertainty. We have shown that the calculation of confidence intervals for the new impact numbers is possible by means of known methods for attributable risk measures. Therefore, estimated impact numbers should always be complemented by appropriate confidence intervals

Virtual screening for inhibitors of the human TSLP:TSLPR interaction

The pro-inflammatory cytokine thymic stromal lymphopoietin (TSLP) plays a pivotal role in the pathophysiology of various allergy disorders that are mediated by type 2 helper T cell (Th2) responses, such as asthma and atopic dermatitis. TSLP forms a ternary complex with the TSLP receptor (TSLPR) and the interleukin-7-receptor subunit alpha (IL-7Ra), thereby activating a signaling cascade that culminates in the release of pro-inflammatory mediators. In this study, we conducted an in silico characterization of the TSLP: TSLPR complex to investigate the drugability of this complex. Two commercially available fragment libraries were screened computationally for possible inhibitors and a selection of fragments was subsequently tested in vitro. The screening setup consisted of two orthogonal assays measuring TSLP binding to TSLPR: a BLI-based assay and a biochemical assay based on a TSLP: alkaline phosphatase fusion protein. Four fragments pertaining to diverse chemical classes were identified to reduce TSLP: TSLPR complex formation to less than 75% in millimolar concentrations. We have used unbiased molecular dynamics simulations to develop a Markov state model that characterized the binding pathway of the most interesting compound. This work provides a proof-ofprinciple for use of fragments in the inhibition of TSLP: TSLPR complexation

Slx8 removes Pli1-dependent protein-SUMO conjugates including SUMOylated Topoisomerase I to promote genome stability

Peer reviewedPublisher PD

Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

Estimating the regional distribution of men who have sex with men (MSM) based on Internet surveys

<p>Abstract</p> <p>Background</p> <p>Measurement of prevalence and incidence of infections in a hard to reach population like men who have sex with men (MSM) is hampered by its unknown size and regional distribution. Population-based surveys have recently been used to estimate the total number of MSM, but these surveys are usually not large enough to measure regional differences in the proportion of MSM in the population. We explored the use of the proportional regional distribution of participants of large internet-based surveys among MSM from Germany to estimate the regional distribution of MSM in Germany.</p> <p>Methods</p> <p>We compared participants from two separate MSM behavioural surveys with each other and with the distribution of user profiles of the largest contact and dating website for gay and other MSM in Germany in terms of the representativeness of the regional distribution. In addition, we compared the regional distribution of reportedly HIV positive survey participants with the regional distribution of HIV notifications within the national surveillance system that can be attributed to transmission through homosexual contacts.</p> <p>Results</p> <p>Regional distribution of survey participants was almost identical in both surveys, despite little overlap between survey participants. Slight discrepancies between surveys and user profiles could be observed. Proportional regional distribution of survey participants with HIV diagnosis resembled national surveillance data.</p> <p>Conclusion</p> <p>Considering the difficulties to obtain representative data by other sampling methods for "hidden" populations like MSM, internet-based surveys may provide an easy and low cost tool to estimate the regional population distribution – at least in Western post-industrialized countries. Some uncertainties remain about the exact place of residence of MSM in larger cities or catchment areas of these cities. Slightly different results from different datasets may be due to unequal popularity of MSM websites in different regions. The total population size of the MSM population can be estimated based on e.g. data from representative national population surveys. Both estimates can then be combined to calculate the absolute size of regional MSM populations.</p

A review of gene-drug interactions for nonsteroidal anti-inflammatory drug use in preventing colorectal neoplasia.

Nonsteroidal anti-inflammatory drugs (NSAIDs) have been shown to be effective chemopreventive agents for colorectal neoplasia. Polymorphisms in NSAID targets or metabolizing enzymes may affect NSAID efficacy or toxicity. We conducted a literature review to summarize current evidence of gene-drug interactions between NSAID use and polymorphisms in COX1, COX2, ODC, UGT1A6 and CYP2C9 on risk of colorectal neoplasia by searching OVID and PubMed. Of 134 relevant search results, thirteen investigated an interaction. One study reported a significant interaction between NSAID use and the COX1 Pro17Leu polymorphism (P=0.03) whereby the risk reduction associated with NSAID use among homozygous wild-type genotypes was not observed among NSAID users with variant alleles. Recent pharmacodynamic data support the potential for gene-drug interactions for COX1 Pro17Leu. Statistically significant interactions have also been reported for ODC (315G>A), UGT1A6 (Thr181Ala+Arg184Ser or Arg184Ser alone), and CYP2C9 (*2/*3). No statistically significant interactions have been reported for polymorphisms in COX2; however, an interaction with COX2 -765G>C approached significance (P=0.07) in one study. Among seven remaining studies, reported interactions were not statistically significant for COX1, COX2 and ODC gene polymorphisms. Most studies were of limited sample size. Definitions of NSAID use differed substantially between studies. The literature on NSAID-gene interactions to date is limited. Reliable detection of gene-NSAID interactions will require greater sample sizes, consistent definitions of NSAID use and evaluation of clinical trial subjects of chemoprevention studies

SUMO-Targeted Ubiquitin Ligase, Rad60, and Nse2 SUMO Ligase Suppress Spontaneous Top1–Mediated DNA Damage and Genome Instability

Through as yet undefined proteins and pathways, the SUMO-targeted ubiquitin ligase (STUbL) suppresses genomic instability by ubiquitinating SUMO conjugated proteins and driving their proteasomal destruction. Here, we identify a critical function for fission yeast STUbL in suppressing spontaneous and chemically induced topoisomerase I (Top1)–mediated DNA damage. Strikingly, cells with reduced STUbL activity are dependent on tyrosyl–DNA phosphodiesterase 1 (Tdp1). This is notable, as cells lacking Tdp1 are largely aphenotypic in the vegetative cell cycle due to the existence of alternative pathways for the removal of covalent Top1–DNA adducts (Top1cc). We further identify Rad60, a SUMO mimetic and STUbL-interacting protein, and the SUMO E3 ligase Nse2 as critical Top1cc repair factors in cells lacking Tdp1. Detection of Top1ccs using chromatin immunoprecipitation and quantitative PCR shows that they are elevated in cells lacking Tdp1 and STUbL, Rad60, or Nse2 SUMO ligase activity. These unrepaired Top1ccs are shown to cause DNA damage, hyper-recombination, and checkpoint-mediated cell cycle arrest. We further determine that Tdp1 and the nucleotide excision repair endonuclease Rad16-Swi10 initiate the major Top1cc repair pathways of fission yeast. Tdp1-based repair is the predominant activity outside S phase, likely acting on transcription-coupled Top1cc. Epistasis analyses suggest that STUbL, Rad60, and Nse2 facilitate the Rad16-Swi10 pathway, parallel to Tdp1. Collectively, these results reveal a unified role for STUbL, Rad60, and Nse2 in protecting genome stability against spontaneous Top1-mediated DNA damage

Association of HbA1c Values with Mortality and Cardiovascular Events in Diabetic Dialysis Patients. The INVOR Study and Review of the Literature

BACKGROUND: Improved glycemic control reduces complications in patients with diabetes mellitus (DM). However, it is discussed controversially whether patients with diabetes mellitus and end-stage renal disease benefit from strict glycemic control. METHODS: We followed 78 patients with DM initiating dialysis treatment of the region of Vorarlberg in a prospective cohort study applying a time-dependent Cox regression analysis using all measured laboratory values for up to more than seven years. This resulted in 880 HbA(1c) measurements (with one measurement every 3.16 patient months on average) during the entire observation period. Non-linear P-splines were used to allow flexible modeling of the association with mortality and cardiovascular disease (CVD) events. RESULTS: We observed a decreased mortality risk with increasing HbA(1c) values (HR = 0.72 per 1% increase, p = 0.024). Adjustment for age and sex and additional adjustment for other CVD risk factors only slightly attenuated the association (HR = 0.71, p = 0.044). A non-linear P-spline showed that the association did not follow a fully linear pattern with a highly significant non-linear component (p = 0.001) with an increased risk of all-cause mortality for HbA(1c) values up to 6-7%. Causes of death were associated with HbA(1c) values. The risk for CVD events, however, increased with increasing HbA(1c) values (HR = 1.24 per 1% increase, p = 0.048) but vanished after extended adjustments. CONCLUSIONS: This study considered the entire information collected on HbA(1c) over a period of more than seven years. Besides the methodological advantages our data indicate a significant inverse association between HbA(1c) levels and all-cause mortality. However, for CVD events no significant association could be found