992 resultados para Drug enforcement
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Audit report on the Iowa Law Enforcement Academy for the year ended June 30, 2013
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Iowa Law Enforcement Academy provided 383 training opportunities for law enforcement, jailers, and telecommunicators for a total of 3584 individuals receiving training. The Academy remains committed to bringing cutting edge programming to law enforcement, jailers, and telecommunicators across Iowa, as evidenced by partnerships with the Federal Law Enforcement Training Center, the International Association of Chiefs of Police, the Secret Service, the Midwest Counterdrug Training Center, Northwestern University’s Center for Public Safety, and many others. The Academy is looking forward to growing its presence within the law enforcement community as the “go to” resource by also serving as a bulletin board for training around the state.
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Iowa Law Enforcement Academy provided 383 training opportunities for law enforcement, jailers, and telecommunicators for a total of 3584 individuals receiving training. The Academy remains committed to bringing cutting edge programming to law enforcement, jailers, and telecommunicators across Iowa, as evidenced by partnerships with the Federal Law Enforcement Training Center, the International Association of Chiefs of Police, the Secret Service, the Midwest Counterdrug Training Center, Northwestern University’s Center for Public Safety, and many others. The Academy is looking forward to growing its presence within the law enforcement community as the “go to” resource by also serving as a bulletin board for training around the state.
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A headspace solid-phase microextraction procedure (HS-SPME) was developed for the profiling of traces present in 3,4-methylenedioxymethylampethamine (MDMA). Traces were first extracted using HS-SPME and then analyzed by gas chromatography-mass spectroscopy (GC-MS). The HS-SPME conditions were optimized using varying conditions. Optimal results were obtained when 40 mg of crushed MDMA sample was heated at 80 °C for 15 min, followed by extraction at 80 °C for 15 min with a polydimethylsiloxane/divinylbenzene coated fibre. A total of 31 compounds were identified as traces related to MDMA synthesis, namely precursors, intermediates or by-products. In addition some fatty acids used as tabletting materials and caffeine used as adulterant, were also detected. The use of a restricted set of 10 target compounds was also proposed for developing a screening tool for clustering samples having close profile. 114 seizures were analyzed using an SPME auto-sampler (MultiPurpose Samples MPS2), purchased from Gerstel GMBH & Co. (Germany), and coupled to GC-MS. The data was handled using various pre-treatment methods, followed by the study of similarities between sample pairs based on the Pearson correlation. The results show that HS-SPME, coupled with the suitable statistical method is a powerful tool for distinguishing specimens coming from the same seizure and specimens coming from different seizures. This information can be used by law enforcement personnel to visualize the ecstasy distribution network as well as the clandestine tablet manufacturing.
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Aims: Plasma concentrations of imatinib differ largely between patients despite same dosage, owing to large inter-individual variability in pharmacokinetic (PK) parameters. As the drug concentration at the end of the dosage interval (Cmin) correlates with treatment response and tolerability, monitoring of Cmin is suggested for therapeutic drug monitoring (TDM) of imatinib. Due to logistic difficulties, random sampling during the dosage interval is however often performed in clinical practice, thus rendering the respective results not informative regarding Cmin values.Objectives: (I) To extrapolate randomly measured imatinib concentrations to more informative Cmin using classical Bayesian forecasting. (II) To extend the classical Bayesian method to account for correlation between PK parameters. (III) To evaluate the predictive performance of both methods.Methods: 31 paired blood samples (random and trough levels) were obtained from 19 cancer patients under imatinib. Two Bayesian maximum a posteriori (MAP) methods were implemented: (A) a classical method ignoring correlation between PK parameters, and (B) an extended one accounting for correlation. Both methods were applied to estimate individual PK parameters, conditional on random observations and covariate-adjusted priors from a population PK model. The PK parameter estimates were used to calculate trough levels. Relative prediction errors (PE) were analyzed to evaluate accuracy (one-sample t-test) and to compare precision between the methods (F-test to compare variances).Results: Both Bayesian MAP methods allowed non-biased predictions of individual Cmin compared to observations: (A) - 7% mean PE (CI95% - 18 to 4 %, p = 0.15) and (B) - 4% mean PE (CI95% - 18 to 10 %, p = 0.69). Relative standard deviations of actual observations from predictions were 22% (A) and 30% (B), i.e. comparable to the intraindividual variability reported. Precision was not improved by taking into account correlation between PK parameters (p = 0.22).Conclusion: Clinical interpretation of randomly measured imatinib concentrations can be assisted by Bayesian extrapolation to maximum likelihood Cmin. Classical Bayesian estimation can be applied for TDM without the need to include correlation between PK parameters. Both methods could be adapted in the future to evaluate other individual pharmacokinetic measures correlated to clinical outcomes, such as area under the curve(AUC).
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Numerous drug delivery systems (DDSs) can be used as intraocular tools to provide a sustained and calibrated release for a specific drug. Great progress has been made on the design, biocompatibility, bioavailability, and efficacy of DDSs. Although several of them are undergoing clinical trials, a few are already on the market and could be of a routine use in clinical practice. Moreover, miniaturization of the implants makes them less and less traumatic for the eye tissues and some DDSs are now able to target certain cells or tissues specifically. An overview of ocular implants with therapeutic application potentials is provided.
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Switzerland has adopted a prevention strategy including the promotion of non-sharing injection material and use of condoms. The access to sterile equipment has been made easier, but regional differences still exist. Studies conducted between 1989 and 1992 among drug users in different Swiss regions are reviewed in order to examine if progress in prevention occurred. Syringe sharing diminished everywhere, but rather high sharing rates persist where sterile material is less accessible. Condom use increased, but the situation is still unsatisfactory considering the high HIV prevalence among i.v. drug users. Where several surveys have been conducted consecutively, a stabilization of HIV prevalence was observed. This suggests a slowing down of the progression of the epidemic among drug users. These results, obtained in few years, are encouraging in the light of the pessimism which prevailed at the beginning of the epidemic about the ability of drug users to adopt preventive behaviour.
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Optimal tax formulas expressed in "sufficient statistics" are usually calibrated under the assumptionthat the relevant tax elasticities are unaffected by other available policy instruments.In practice though, tax authorities have many more instruments than the mere tax rates andtax elasticities are functions of all these policy instruments. In this paper we provide evidencethat tax elasticities are extremely sensitive to a particular policy instrument: the level of taxenforcement. We exploit a natural experiment that took place in France in 1983, when the taxadministration tightened the requirements to claim charitable deductions. The reform led to asubstantial drop in the amount of contributions reported to the administration, which can becredibly attributed to overreporting of charitable contributions before the reform, rather thanto a real change in giving behaviours. We show that the reform was also associated with asubstantial decline in the absolute value of the elasticity of reported contributions. This findingallows us to partially identify the elasticity of overreporting contributions, which is shown tobe large and inferior to -2 in the lax enforcement regime. We further show using bunching oftaxpayers at kink-points of the tax schedule that the elasticity of taxable income also experienceda significant decline after the reform. Our results suggest that optimizing the tax rate fora given tax elasticity when other policy instruments are not optimized can lead to misleadingconclusions when tax authorities have another instrument that could set the tax elasticity itselfat its optimal level as in Kopczuk and Slemrod [2002].
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Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions
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State compliance with EU Law is crucial to the very existence of the Union. Traditionally, it has been secured through a combination of strong "private" and of weak "centralized" enforcement. However, this arrangement is no longer perceived to be sufficient. By endowing the Union with new tools vis-à-vis its Member States - penalties, conditionality, and the like - current reforms try to complement symbolic sanctioning with real "consequences". The goal is to reinforce the authority of EU Law. In this article, we question whether the new toolbox is fit for the purpose, or whether it risks to produce adverse effects which might even go as far as upsetting the Union's constitutional template.
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Therapeutic drug monitoring (TDM) and pharmacogenetic tests play a major role in minimising adverse drug reactions and enhancing optimal therapeutic response. The response to medication varies greatly between individuals, according to genetic constitution, age, sex, co-morbidities, environmental factors including diet and lifestyle (e.g. smoking and alcohol intake), and drug-related factors such as pharmacokinetic or pharmacodynamic drug-drug interactions. Most adverse drug reactions are type A reactions, i.e. plasma-level dependent, and represent one of the major causes of hospitalisation, in some cases leading to death. However, they may be avoidable to some extent if pharmacokinetic and pharmacogenetic factors are taken into consideration. This article provides a review of the literature and describes how to apply and interpret TDM and certain pharmacogenetic tests and is illustrated by case reports. An algorithm on the use of TDM and pharmacogenetic tests to help characterise adverse drug reactions is also presented. Although, in the scientific community, differences in drug response are increasingly recognised, there is an urgent need to translate this knowledge into clinical recommendations. Databases on drug-drug interactions and the impact of pharmacogenetic polymorphisms and adverse drug reaction information systems will be helpful to guide clinicians in individualised treatment choices.