74 research outputs found

    Screening of conditions controlling spectrophotometric sequential injection analysis

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    <p>Abstract</p> <p>Background</p> <p>Despite its potential benefits over univariate, chemometrics is rarely utilized for optimizing sequential injection analysis (SIA) methods. Specifically, in previous vis-spectrophotometric SIA methods, chemometrically optimized conditions were confined within flow rate and reagent concentrations while other conditions were ignored.</p> <p>Results</p> <p>The current manuscript reports, for the first time, a comprehensive screening of conditions controlling vis-spectrophotometric SIA. A new diclofenac assay method was adopted. The method was based on oxidizing diclofenac by permanganate (a major reagent) with sulfuric acid (a minor reagent). The reaction produced a spectrophotometrically detectable diclofenac form. The 2<sup>6 </sup>full-factorial design was utilized to study the effect of volumes of reagents and sample, in addition to flow rate and concentrations of reagents. The main effects and all interaction order effects on method performance, i.e. namely sensitivity, rapidity and reagent consumption, were determined. The method was validated and applied to pharmaceutical formulations (tablets, injection and gel).</p> <p>Conclusions</p> <p>Despite 64 experiments those conducted in the current study were cumbersome, the results obtained would reduce effort and time when developing similar SIA methods in the future. It is recommended to critically optimize effective and interacting conditions using other such optimization tools as fractional-factorial design, response surface and simplex, rather than full-factorial design that used at an initial optimization stage. In vis-spectrophotometric SIA methods those involve developing reactions with two reagents (major and minor), conditions affecting method performance are in the following order: sample volume > flow rate ≈ major reagent concentration >> major reagent volume ≈ minor reagent concentration >> minor reagent volume.</p

    Effectiveness of a clinical practice guideline implementation strategy for patients with anxiety disorders in primary care: cluster randomized trial

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    <p>Abstract</p> <p>Background</p> <p>Anxiety is a common mental health problem seen in primary care. However, its management in clinical practice varies greatly. Clinical practice guidelines (CPGs) have the potential to reduce variations and improve the care received by patients by promoting interventions of proven benefit. However, uptake and adherence to their recommendations can be low.</p> <p>Method/design</p> <p>This study involves a community based on cluster randomized trial in primary healthcare centres in the Madrid Region (Spain). The project aims to determine whether the use of implementation strategy (including training session, information, opinion leader, reminders, audit, and feed-back) of CPG for patients with anxiety disorders in primary care is more effective than usual diffusion.</p> <p>The number of patients required is 296 (148 in each arm), all older than 18 years and diagnosed with generalized anxiety disorder, panic disorder, and panic attacks by the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). They are chosen by consecutive sampling.</p> <p>The main outcome variable is the change in two or more points into Goldberg anxiety scale at six and twelve months. Secondary outcome variables include quality of life (EuroQol 5D), and degree of compliance with the CPG recommendations on treatment, information, and referrals to mental health services. Main effectiveness will be analyzed by comparing the patients percentage improvement on the Goldberg scale between the intervention group and the control group. Logistic regression with random effects will be used to adjust for prognostic factors. Confounding factors or factors that might alter the effect recorded will be taken into account in this analysis.</p> <p>Discussion</p> <p>There is a need to identify effective implementation strategies for CPG for the management of anxiety disorders present in primary care. Ensuring the appropriate uptake of guideline recommendations can reduce clinical variation and improve the care patients receive.</p> <p>Trial registration</p> <p>ISRCTN: <a href="http://www.controlled-trials.com/ISRCTN83365316">ISRCTN83365316</a></p

    Reduction in Structural Disorder and Functional Complexity in the Thermal Adaptation of Prokaryotes

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    Genomic correlates of evolutionary adaptation to very low or very high optimal growth temperature (OGT) values have been the subject of many studies. Whereas these provided a protein-structural rationale of the activity and stability of globular proteins/enzymes, the point has been neglected that adaptation to extreme temperatures could also have resulted from an increased use of intrinsically disordered proteins (IDPs), which are resistant to these conditions in vitro. Contrary to these expectations, we found a conspicuously low level of structural disorder in bacteria of very high (and very low) OGT values. This paucity of disorder does not reflect phylogenetic relatedness, i.e. it is a result of genuine adaptation to extreme conditions. Because intrinsic disorder correlates with important regulatory functions, we asked how these bacteria could exist without IDPs by studying transcription factors, known to harbor a lot of function-related intrinsic disorder. Hyperthermophiles have much less transcription factors, which have reduced disorder compared to their mesophilic counterparts. On the other hand, we found by systematic categorization of proteins with long disordered regions that there are certain functions, such as translation and ribosome biogenesis that depend on structural disorder even in hyperthermophiles. In all, our observations suggest that adaptation to extreme conditions is achieved by a significant functional simplification, apparent at both the level of the genome and individual genes/proteins

    Direct analysis of volumetric absorptive micro sampling (VAMS) devices by ATR-FT-MIR and chemometric analysis: a new challenge

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    Volumetric Absorptive Micro Sampling (VAMS) strategy, in its simplicity, has made a major contribution to the development of at-home sampling strategies. Mainly used for blood analysis, it absorbs a fixed volume of sample. Folded into its cover, the VAMS device dries, and it can be sent to a lab via mail. In this article, for the first time in our knowledge, we explored the possibility to use this sampling strategy to expand the scope of VAMS to other samples than clinical ones. In this way we used VAMS to sample and analyze milk, which is one of the most important and analyzed samples all over the world. VAMS devices were employed to sample commercial milk samples from Italy, Switzerland and Spain, and for the first time the device was directly analyzed by ATR-FT-IR to predict protein, carbohydrate and fat content in the milk samples. Samples were collected in different sessions from different persons and analyzed by different lab operators to include in the models these sources of variability. Multivariate regression was used to correlate ATR-FT-IR spectra with the investigated properties: models were validated with external validation
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