89 research outputs found

    The Composition of the Cuticular and Internal Free Fatty Acids and Alcohols from Lucilia sericata Males and Females

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    GC, GC–MS, and HPLC–LLSD analyses were used to identify and quantify cuticular and internal lipids in males and females of the blow-fly (Lucilia sericata). Sixteen free fatty acids, seven alcohols and cholesterol were identified and quantitatively determined in the cuticular lipids of L. sericata. Cuticular fatty acids ranged from C6 to C20 and included unsaturated entities such as 16:1n-9, 18:1n-9, 20:4n-3 and 20:5n-3. Cuticular alcohols (only saturated and even-numbered) ranged from C12 to C20 in males and C10 to C22 in females. Only one sterol was found in the cuticular lipids of both males and females. 23 free fatty acids, five alcohols and cholesterol were identified in the internal lipids. Internal fatty acids were present in large amounts—7.4 mg/g (female) and 10.1 mg/g (male). Only traces of internal alcohols (from C14 to C26 in males, from C14 to C22 in females) were found in L. sericata. Large amounts of internal cholesterol were identified in L. sericata males and females (0.49 and 0.97 mg/g of the insect body, respectively)

    Sustained favorable long-term outcome in the treatment of schizophrenia: a 3-year prospective observational study

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    <p>Abstract</p> <p>Background</p> <p>This study of chronically ill patients with schizophrenia aimed to identify patients who achieve sustained favorable long-term outcome - when the outcome incorporates severity of symptoms, level of functioning, and use of acute care services - and to identify the best baseline predictors of achieving this sustained favorable long-term outcome.</p> <p>Methods</p> <p>Using data from the United States Schizophrenia Care and Assessment Program (US-SCAP) (N = 2327), a large 3-year prospective, multisite, observational study of individuals treated for schizophrenia in the US, a hierarchical cluster analysis was performed to group patients based upon baseline symptom severity. Symptom severity was assessed using the Positive and Negative Syndrome Scale (PANSS) scores, level of functioning, and use of acute care services. Level of functioning reflected patient-reported productivity and clinician-rated occupational role functioning. Use of acute care services reflected self-reported psychiatric hospitalization and emergency service use. Change of health state was determined over the 3-year period. A patient was classified as having a sustained favorable long-term outcome if their health state values had the closest distance to the defined "best baseline cluster" at each point over the length of the study. Stepwise logistic regression was used to determine baseline predictors of sustained favorable long-term outcome.</p> <p>Results</p> <p>At baseline, 5 distinct health state clusters were identified, ranging from "best" to "worst." Of 1635 patients with sufficient data, only 157 (10%) experienced sustained favorable long-term outcome during the 2-years postbaseline. The baseline predictors associated with sustained favorable long-term outcome included better quality of life, more daily activities, patient-reported clearer thinking from medication, better global functioning, being employed, not being a victim of a crime, not having received individual therapy, and not having received help with shopping and leisure activities.</p> <p>Conclusions</p> <p>Only a small percentage of patients achieved sustained favorable long-term outcome in this study, suggesting there continues to be a great need for improvement in the treatment of schizophrenia. Findings suggest that clinicians could make early projections of health states and identify those patients more likely to achieve favorable long-term outcomes enabling early therapeutic interventions to enhance benefits for patients.</p

    Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise

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    Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes

    Myocardial tagging by Cardiovascular Magnetic Resonance: evolution of techniques--pulse sequences, analysis algorithms, and applications

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    Cardiovascular magnetic resonance (CMR) tagging has been established as an essential technique for measuring regional myocardial function. It allows quantification of local intramyocardial motion measures, e.g. strain and strain rate. The invention of CMR tagging came in the late eighties, where the technique allowed for the first time for visualizing transmural myocardial movement without having to implant physical markers. This new idea opened the door for a series of developments and improvements that continue up to the present time. Different tagging techniques are currently available that are more extensive, improved, and sophisticated than they were twenty years ago. Each of these techniques has different versions for improved resolution, signal-to-noise ratio (SNR), scan time, anatomical coverage, three-dimensional capability, and image quality. The tagging techniques covered in this article can be broadly divided into two main categories: 1) Basic techniques, which include magnetization saturation, spatial modulation of magnetization (SPAMM), delay alternating with nutations for tailored excitation (DANTE), and complementary SPAMM (CSPAMM); and 2) Advanced techniques, which include harmonic phase (HARP), displacement encoding with stimulated echoes (DENSE), and strain encoding (SENC). Although most of these techniques were developed by separate groups and evolved from different backgrounds, they are in fact closely related to each other, and they can be interpreted from more than one perspective. Some of these techniques even followed parallel paths of developments, as illustrated in the article. As each technique has its own advantages, some efforts have been made to combine different techniques together for improved image quality or composite information acquisition. In this review, different developments in pulse sequences and related image processing techniques are described along with the necessities that led to their invention, which makes this article easy to read and the covered techniques easy to follow. Major studies that applied CMR tagging for studying myocardial mechanics are also summarized. Finally, the current article includes a plethora of ideas and techniques with over 300 references that motivate the reader to think about the future of CMR tagging

    Pharmacogenetics in schizophrenia: a review of clozapine studies

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    A systematic review of non-hormonal treatments of vasomotor symptoms in climacteric and cancer patients

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    Special issue on Pharmacogenetics

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    Psychiatric Genetics and Genomics

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