849 research outputs found

    Classifying the unclassifiable – A Delphi study to reach consensus on the fibrotic nature of diseases

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    Background Traditionally, clinical research has focused on individual fibrotic diseases or fibrosis in a particular organ. However, it is possible for people to have multiple fibrotic diseases. While multi-organ fibrosis may suggest shared pathogenic mechanisms, yet there is no consensus on what constitutes a fibrotic disease and therefore fibrotic multimorbidity. Aim A Delphi study was performed to reach consensus on which diseases may be described as fibrotic. Methods Participants were asked to rate a list of diseases, sub-grouped according to eight body regions, as ‘fibrotic manifestation always present’, ‘can develop fibrotic manifestations’, ‘associated with fibrotic manifestations’ or ‘not fibrotic nor associated’. Classifications of ‘fibrotic manifestation always present’ and ‘can develop fibrotic manifestations’ were merged and termed ‘fibrotic’. Clinical consensus was defined according to the interquartile range, having met a minimum number of responses. Clinical agreement was used for classification where diseases did not meet the minimum number of responses (required for consensus measure), were only classified if there was 100% consensus on disease classification. Results After consulting experts, searching the literature and coding dictionaries, a total of 323 non-overlapping diseases which might be considered fibrotic were identified; 92 clinical specialists responded to the first round of the survey. Over three survey rounds, 240 diseases were categorized as fibrotic via clinical consensus and 25 additional diseases through clinical agreement. Conclusion Using a robust methodology, an extensive list of diseases was classified. The findings lay the foundations for studies estimating the burden of fibrotic multimorbidity, as well as investigating shared mechanisms and therapies

    Infection-related morbidity and mortality among older patients with DLBCL treated with full- or attenuated-dose R-CHOP

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    Infection-related morbidity and mortality are increased in older patients with diffuse large B-cell lymphoma (DLBCL) compared with population-matched controls. Key predictive factors for infection-related hospitalization during treatment with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) and deaths as a result of infection in older patients during and after treatment with R-CHOP remain incompletely understood. For this study, 690 consecutively treated patients age 70 years or older who received full-dose or attenuated-dose R-CHOP treatment were analyzed for risk of infection-related hospitalization and infection-related death. Median age was 77 years, and 34.4% were 80 years old or older. Median follow-up was 2.8 years (range, 0.4-8.9 years). Patient and baseline disease characteristics were assessed in addition to intended dose intensity (IDI). Of all patients, 72% were not hospitalized with infection. In 331 patients receiving an IDI ≥80%, 33% were hospitalized with ≥1 infections compared with 23.3% of 355 patients receiving an IDI of 80% across the whole cohort. Primary quinolone prophylaxis independently reduced infection-related admission. A total of 51 patients died as a result of infection. The 6-month, 12-month, 2-year, and 5-year cumulative incidences of infection-related death were 3.3%, 5.0%, 7.2%, and 11.1%, respectively. Key independent factors associated with infection-related death were an International Prognostic Index (IPI) score of 3 to 5, Cumulative Illness Rating Scale for Geriatrics (CIRS-G) score ≥6, and low albumin, which enabled us to generate a predictive risk score. We defined a smaller group (15%) of patients (IPI score of 0-2, albumin >36 g/L, CIRS-G score <6) in which no cases of infection-related deaths occurred at 5 years of follow-up. Whether patients at higher risk of infection-related death could be targeted with enhanced antimicrobial prophylaxis remains unknown and will require a randomized trial

    Thermopile detector of light ellipticity

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    Polarimetric imaging is widely used in applications from material analysis to biomedical diagnostics, vision and astronomy. The degree of circular polarization, or light ellipticity, is associated with the S3 Stokes parameter which is defined as the difference in the intensities of the left- and right-circularly polarized components of light. Traditional way of determining this parameter relies on using several external optical elements, such as polarizers and wave plates, along with conventional photodetectors, and performing at least two measurements to distinguish left- and right-circularly polarized light components. Here we theoretically propose and experimentally demonstrate a thermopile photodetector element that provides bipolar voltage output directly proportional to the S3 Stokes parameter of the incident light.ope

    Reduced Cortisol and Metabolic Responses of Thin Ewes to an Acute Cold Challenge in Mid-Pregnancy: Implications for Animal Physiology and Welfare

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    Background: Low food availability leading to reductions in Body Condition Score (BCS; 0 indicates emaciation and 5 obesity) in sheep often coincides with low temperatures associated with the onset of winter in New Zealand. The ability to adapt to reductions in environmental temperature may be impaired in animals with low BCS, in particular during pregnancy when metabolic demand is higher. Here we assess whether BCS affects a pregnant animal’s ability to cope with cold challenges. Methods: Eighteen pregnant ewes with a BCS of 2.760.1 were fed to attain low (LBC: BCS2.360.1), medium (MBC: BCS3.260.2) or high BCS (HBC: BCS3.660.2). Shorn ewes were exposed to a 6-h acute cold challenge in a climate-controlled room (wet and windy conditions, 4.460.1uC) in mid-pregnancy. Blood samples were collected during the BCS change phase, acute cold challenge and recovery phase. Results: During the BCS change phase, plasma glucose and leptin concentrations declined while free fatty acids (FFA) increased in LBC compared to MBC (P,0.01, P,0.01 and P,0.05, respectively) and HBC ewes (P,0.05, P,0.01 and P,0.01, respectively). During the cold challenge, plasma cortisol concentrations were lower in LBC than MBC (P,0.05) and HBC ewes (P,0.05), and FFA and insulin concentrations were lower in LBC than HBC ewes (P,0.05 and P,0.001, respectively). Leptin concentrations declined in MBC and HBC ewes while remaining unchanged in LBC ewes (P,0.01). Glucose concentrations and internal body temperature (Tcore) increased in all treatments, although peak Tcore tended to be higher in HBC ewes (P,0.1). During the recovery phase, T4 concentrations were lower in LBC ewes (P,0.05). Conclusion: Even though all ewes were able to increase Tcore and mobilize glucose, low BCS animals had considerably reduced cortisol and metabolic responses to a cold challenge in mid-pregnancy, suggesting that their ability to adapt to cold challenges through some of the expected pathways was reduced

    Large meta-analysis of multiple cancers reveals a common, compact and highly prognostic hypoxia metagene

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    BACKGROUND: There is a need to develop robust and clinically applicable gene expression signatures. Hypoxia is a key factor promoting solid tumour progression and resistance to therapy; a hypoxia signature has the potential to be not only prognostic but also to predict benefit from particular interventions. METHODS: An approach for deriving signatures that combine knowledge of gene function and analysis of in vivo co-expression patterns was used to define a common hypoxia signature from three head and neck and five breast cancer studies. Previously validated hypoxia-regulated genes (seeds) were used to generate hypoxia co-expression cancer networks. RESULTS: A common hypoxia signature, or metagene, was derived by selecting genes that were consistently co-expressed with the hypoxia seeds in multiple cancers. This was highly enriched for hypoxia-regulated pathways, and prognostic in multivariate analyses. Genes with the highest connectivity were also the most prognostic, and a reduced metagene consisting of a small number of top-ranked genes, including VEGFA, SLC2A1 and PGAM1, outperformed both a larger signature and reported signatures in independent data sets of head and neck, breast and lung cancers. CONCLUSION: Combined knowledge of multiple genes' function from in vitro experiments together with meta-analysis of multiple cancers can deliver compact and robust signatures suitable for clinical application

    Alloxan-Induced Diabetes Triggers the Development of Periodontal Disease in Rats

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    BACKGROUND: Periodontal disease in diabetic patients presents higher severity and prevalence; and increased severity of ligature-induced periodontal disease has been verified in diabetic rats. However, in absence of aggressive stimuli such as ligatures, the influence of diabetes on rat periodontal tissues is incompletely explored. The aim of this study was to evaluate the establishment and progression of periodontal diseases in rats only with diabetes induction. METHODOLOGY/PRINCIPAL FINDINGS: Diabetes was induced in Wistar rats (n = 25) by intravenous administration of alloxan (42 mg/kg) and were analyzed at 1, 3, 6, 9 and 12 months after diabetes induction. The hemimandibles were removed and submitted to radiographical and histopathological procedures. A significant reduction was observed in height of bone crest in diabetic animals at 3, 6, 9 and 12 months, which was associated with increased numbers of osteoclasts and inflammatory cells. The histopathological analyses of diabetic rats also showed a reduction in density of collagen fibers, fibroblasts and blood vessels. Severe caries were also detected in the diabetic group. CONCLUSIONS/SIGNIFICANCE: The results demonstrate that diabetes induction triggers, or even co-induces the onset of alterations which are typical of periodontal diseases even in the absence of aggressive factors such as ligatures. Therefore, diabetes induction renders a previously resistant host into a susceptible phenotype, and hence diabetes can be considered a very important risk factor to the development of periodontal disease

    Normalization in MALDI-TOF imaging datasets of proteins: practical considerations

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    Normalization is critically important for the proper interpretation of matrix-assisted laser desorption/ionization (MALDI) imaging datasets. The effects of the commonly used normalization techniques based on total ion count (TIC) or vector norm normalization are significant, and they are frequently beneficial. In certain cases, however, these normalization algorithms may produce misleading results and possibly lead to wrong conclusions, e.g. regarding to potential biomarker distributions. This is typical for tissues in which signals of prominent abundance are present in confined areas, such as insulin in the pancreas or β-amyloid peptides in the brain. In this work, we investigated whether normalization can be improved if dominant signals are excluded from the calculation. Because manual interaction with the data (e.g., defining the abundant signals) is not desired for routine analysis, we investigated two alternatives: normalization on the spectra noise level or on the median of signal intensities in the spectrum. Normalization on the median and the noise level was found to be significantly more robust against artifact generation compared to normalization on the TIC. Therefore, we propose to include these normalization methods in the standard “toolbox” of MALDI imaging for reliable results under conditions of automation
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