140 resultados para Brodhagen, P. H. C. (Peter Heinrich Christoph), d. 1805.
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Disease-, age-, and gender-associated changes in brain copper, iron, and zinc were assessed in postmortem neocortical tissue (Brodmann area 7) from patients with moderate Alzheimer's disease (AD) (n = 14), severe AD (n = 28), dementia with Lewy bodies (n = 15), and normal age-matched control subjects (n = 26). Copper was lower (20%; p < 0.001) and iron higher (10–16%; p < 0.001) in severe AD compared with controls. Intriguingly significant Group*Age interactions were observed for both copper and iron, suggesting gradual age-associated decline of these metals in healthy non-cognitively impaired individuals. Zinc was unaffected in any disease pathologies and no age-associated changes were apparent. Age-associated changes in brain elements warrant further investigation.
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The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
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Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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Understanding the response of humid mid-latitude forests to changes in precipitation, temperature, nutrient cycling, and disturbance is critical to improving our predictive understanding of changes in the surface-subsurface energy balance due to climate change. Mechanistic understanding of the effects of long-term and transient moisture conditions are needed to quantify
linkages between changing redox conditions, microbial activity, and soil mineral and nutrient interactions on C cycling and greenhouse gas releases. To illuminate relationships between the soil chemistry, microbial communities and organic C we established transects across hydraulic and topographic gradients in a small watershed with transient moisture conditions. Valley bottoms tend to be more frequently saturated than ridge tops and side slopes which generally are only saturated when shallow storm flow zones are active. Fifty shallow (~36”) soil cores were collected during timeframes representative of low CO2, soil winter conditions and high CO2, soil summer conditions. Cores were subdivided into 240 samples based on pedology and analyses of the geochemical (moisture content, metals, pH, Fe species, N, C, CEC, AEC) and microbial (16S rRNA gene
amplification with Illumina MiSeq sequencing) characteristics were conducted and correlated to watershed terrain and hydrology. To associate microbial metabolic activity with greenhouse gas emissions we installed 17 soil gas probes, collected gas samples for 16 months and analyzed them for CO2 and other fixed and greenhouse gasses. Parallel to the experimental efforts our data is being used to support hydrobiogeochemical process modeling by coupling the Community Land Model (CLM) with a subsurface process model (PFLOTRAN) to simulate processes and interactions from the molecular to watershed scales. Including above ground processes (biogeophysics, hydrology, and vegetation dynamics), CLM provides mechanistic water, energy, and organic matter inputs to the surface/subsurface models, in which coupled biogeochemical reaction
networks are used to improve the representation of below-ground processes. Preliminary results suggest that inclusion of above ground processes from CLM greatly improves the prediction of moisture response and water cycle at the watershed scale.
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Rationale: Ex vivo, bronchial epithelial cells from people with asthma are more susceptible to rhinovirus infection caused by deficient induction of the antiviral protein, IFN-b. Exogenous IFN-b restores antiviral activity.
Objectives: To compare the efficacy and safety of inhaled IFN-b with placebo administered to people with asthma after onset of cold symptoms to prevent or attenuate asthma symptoms caused by respiratory viruses.
Methods: A total of 147 people with asthma on inhaled corticosteroids (British Thoracic Society Steps 2–5), with a history of virus-associated exacerbations, were randomized to 14-day treatment with inhaled IFN-b (n = 72) or placebo (n = 75) within 24 hours of developing cold symptoms and were assessed clinically, with relevant samples collected to assess virus infection and antiviral responses.
Measurements and Main Results: A total of 91% of randomized patients developed a defined cold. In this modified intention-to-treat population, asthma symptoms did not get clinically significantly worse
(mean change in six-item Asthma Control Questionnaire ,0.5) and IFN-b treatment had no significant effect on this primary endpoint, although it enhanced morning peak expiratory flow recovery (P = 0.033), reduced the need for additional treatment, and boosted innate immunity as assessed by blood and sputum biomarkers. In an exploratory analysis of the subset ofmore difficult-to-treat, Step 4-5 peoplewith asthma (n = 27 IFN-b; n = 31 placebo), Asthma Control Questionnaire-6 increased significantly on placebo; this was prevented by IFN-b (P = 0.004).
Conclusions: Although the trial did not meet its primary endpoint, it suggests that inhaled IFN-b is a potential treatment for virus-induced deteriorations of asthma in difficult-to-treat people with asthma and supports the needforfurther, adequately powered, trialsin this population. Clinical trial registered with www.clinicaltrials.gov (NCT 01126177).
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<p>Aims: The utility of p53 as a prognostic assay has been elusive. The aims of this study were to describe a novel, reproducible scoring system and assess the relationship between differential p53 immunohistochemistry (IHC) expression patterns, TP53 mutation status and patient outcomes in breast cancer.p><p>Methods and Results: Tissue microarrays were used to study p53 IHC expression patterns: expression was defined as extreme positive (EP), extreme negative (EN), and non-extreme (NE; intermediate patterns). Overall survival (OS) was used to define patient outcome. A representative subgroup (n = 30) showing the various p53 immunophenotypes was analysed for TP53 hotspot mutation status (exons 4-9). Extreme expression of any type occurred in 176 of 288 (61%) cases. As compared with NE expression, EP expression was significantly associated (P = 0.039) with poorer OS. In addition, as compared with NE expression, EN expression was associated (P = 0.059) with poorer OS. Combining cases showing either EP or EN expression better predicted OS than either pattern alone (P = 0.028). This combination immunophenotype was significant in univariate but not multivariate analysis. In subgroup analysis, six substitution exon mutations were detected, all corresponding to extreme IHC phenotypes. Five missense mutations corresponded to EP staining, and the nonsense mutation corresponded to EN staining. No mutations were detected in the NE group.p><p>Conclusions: Patients with extreme p53 IHC expression have a worse OS than those with NE expression. Accounting for EN as well as EP expression improves the prognostic impact. Extreme expression positively correlates with nodal stage and histological grade, and negatively with hormone receptor status. Extreme expression may relate to specific mutational status.p>
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<p>Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated 1/42,000, 1/43,700 and 1/49,500 SNPs explained 1/421%, 1/424% and 1/429% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/I 2-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.p>
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<p>Pseudomonas aeruginosa is an important cause of pulmonary infection in cystic fibrosis (CF). Its correct identification ensures effective patient management and infection control strategies. However, little is known about how often CF sputum isolates are falsely identified as P. aeruginosa. We used P. aeruginosa-specific duplex real-time PCR assays to determine if 2,267 P. aeruginosa sputum isolates from 561 CF patients were correctly identified by 17 Australian clinical microbiology laboratories. Misidentified isolates underwent further phenotypic tests, amplified rRNA gene restriction analysis, and partial 16S rRNA gene sequence analysis. Participating laboratories were surveyed on how they identified P. aeruginosa from CF sputum. Overall, 2,214 (97.7%) isolates from 531 (94.7%) CF patients were correctly identified as P. aeruginosa. Further testing with the API 20NE kit correctly identified only 34 (59%) of the misidentified isolates. Twelve (40%) patients had previously grown the misidentified species in their sputum. Achromobacter xylosoxidans (n = 21), Stenotrophomonas maltophilia (n = 15), and Inquilinus limosus (n = 4) were the species most commonly misidentified as P. aeruginosa. Overall, there were very low rates of P. aeruginosa misidentification among isolates from a broad cross section of Australian CF patients. Additional improvements are possible by undertaking a culture history review, noting colonial morphology, and performing stringent oxidase, DNase, and colistin susceptibility testing for all presumptive P. aeruginosa isolates. Isolates exhibiting atypical phenotypic features should be evaluated further by additional phenotypic or genotypic identification techniques.p>
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<p>Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.p>
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<p>Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.p>
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<p>Despite advancement in breast cancer treatment, 30% of patients with early breast cancers experience relapse with distant metastasis. It is a challenge to identify patients at risk for relapse; therefore, the identification of markers and therapeutic targets for metastatic breast cancers is imperative. Here, we identified DP103 as a biomarker and metastasis-driving oncogene in human breast cancers and determined that DP103 elevates matrix metallopeptidase 9 (MMP9) levels, which are associated with metastasis and invasion through activation of NF-κB. In turn, NF-κB signaling positively activated DP103 expression. Furthermore, DP103 enhanced TGF-β-activated kinase-1 (TAK1) phosphorylation of NF-κB-activating IκB kinase 2 (IKK2), leading to increased NF-κB activity. Reduction of DP103 expression in invasive breast cancer cells reduced phosphorylation of IKK2, abrogated NF-κB-mediated MMP9 expression, and impeded metastasis in a murine xenograft model. In breast cancer patient tissues, elevated levels of DP103 correlated with enhanced MMP9, reduced overall survival, and reduced survival after relapse. Together, these data indicate that a positive DP103/NF-κB feedback loop promotes constitutive NF-κB activation in invasive breast cancers and activation of this pathway is linked to cancer progression and the acquisition of chemotherapy resistance. Furthermore, our results suggest that DP103 has potential as a therapeutic target for breast cancer treatment.p>
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<p>BACKGROUND: A clinical study to investigate the leukotriene B(4) (LTB(4))-receptor antagonist BIIL 284 in cystic fibrosis (CF) patients was prematurely terminated due to a significantly increased risk of adverse pulmonary events. We aimed to establish the effect of BIIL284 in models of Pseudomonas aeruginosa lung infection, thereby contributing to a better understanding of what could have led to adverse pulmonary events in CF patients.p><p>METHODS: P. aeruginosa DNA in the blood of CF patients during and after acute pulmonary exacerbations and in stable patients with non-CF bronchiectasis (NCFB) and healthy individuals was assessed by PCR. The effect of BIIL 284 treatment was tested in an agar bead murine model of P. aeruginosa lung infection. Bacterial count and inflammation were evaluated in lung and other organs.p><p>RESULTS: Most CF patients (98%) and all patients with NCFB and healthy individuals had negative P. aeruginosa DNA in their blood. Similarly, the P. aeruginosa-infected mice showed bacterial counts in the lung but not in the blood or spleen. BIIL 284 treatment decreased pulmonary neutrophils and increased P. aeruginosa numbers in mouse lungs leading to significantly higher bacteremia rates and lung inflammation compared to placebo treated animals.p><p>CONCLUSIONS: Decreased airway neutrophils induced lung proliferation and severe bacteremia in a murine model of P. aeruginosa lung infection. These data suggest that caution should be taken when administering anti-inflammatory compounds to patients with bacterial infections.p>
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<p>G-protein coupled receptors (GPCRs) are the targets of over half of all prescribed drugs today. The UniProt database has records for about 800 proteins classified as GPCRs, but drugs have only been developed against 50 of these. Thus, there is huge potential in terms of the number of targets for new therapies to be designed. Several breakthroughs in GPCRs biased pharmacology, structural biology, modelling and scoring have resulted in a resurgence of interest in GPCRs as drug targets. Therefore, an international conference, sponsored by the Royal Society, with world-renowned researchers from industry and academia was recently held to discuss recent progress and highlight key areas of future research needed to accelerate GPCR drug discovery. Several key points emerged. Firstly, structures for all three major classes of GPCRs have now been solved and there is increasing coverage across the GPCR phylogenetic tree. This is likely to be substantially enhanced with data from x-ray free electron sources as they move beyond proof of concept. Secondly, the concept of biased signalling or functional selectivity is likely to be prevalent in many GPCRs, and this presents exciting new opportunities for selectivity and the control of side effects, especially when combined with increasing data regarding allosteric modulation. Thirdly, there will almost certainly be some GPCRs that will remain difficult targets because they exhibit complex ligand dependencies and have many metastable states rendering them difficult to resolve by crystallographic methods. Subtle effects within the packing of the transmembrane helices are likely to mask and contribute to this aspect, which may play a role in species dependent behaviour. This is particularly important because it has ramifications for how we interpret pre-clinical data. In summary, collaborative efforts between industry and academia have delivered significant progress in terms of structure and understanding of GPCRs and will be essential for resolving problems associated with the more difficult targets in the future.p>
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<p>This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer's disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients 'at risk' from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.p>