64 research outputs found
Uranyl Photocleavage of Phosphopeptides Yields Truncated C-Terminally Amidated Peptide Products
Gastrointestinal microbiota and local inflammation during oxazolone-induced dermatitis in BALB/cA Mice
At present, laboratory animals are not standardized with regard to the gastrointestinal microbiota (GM), but differences in this feature may alter various parameters in animal models. We hypothesized that variation in the GM correlated with variation in clinical parameters of a murine oxazolone-induced skin inflammation model of atopic dermatitis. BALB/cA mice were sensitized with oxazolone over a 28-d period and variation in gastrointestinal microbiota in fecal and cecal samples was assessed by PCR-denaturing gradient gel electrophoresis. Clinical parameters included transepidermal water loss, ear thickness, inflammatory factors in ear tissue and plasma, and histopathologic evaluation. The fecal microbiota before induction of skin inflammation strongly correlated with the levels of some proinflammatory cytokines (IFNγ, IL1β, IL12, and TNFα), the antiinflammatory cytokines IL4 and IL10, and the chemokine KC/GRO that were measured in ear samples at study termination. Cecal microbiota at termination correlated with ear thickness and transepidermal water loss. There was no correlation between cytokine responses and ear thickness or transepidermal water loss. In addition, GM changed during the study period in the oxazolone-treated mice, whereas this was not the case for the control mice. The current study shows that the GM of mice influences the development of oxazolone-induced skin inflammation and that the model itself likely induces a pathophysiologic response that alters the composition of the GM
Self-rated health and functional capacity in individuals reporting overlapping symptoms of gastroesophageal reflux disease, functional dyspepsia and irritable bowel syndrome - a population based study
“Medically unexplained” symptoms and symptom disorders in primary care: prognosis-based recognition and classification
Background: Many patients consult their GP because they experience bodily symptoms. In a substantial proportion of
cases, the clinical picture does not meet the existing diagnostic criteria for diseases or disorders. This may be because
symptoms are recent and evolving or because symptoms are persistent but, either by their character or the negative
results of clinical investigation cannot be attributed to disease: so-called “medically unexplained symptoms” (MUS).
MUS are inconsistently recognised, diagnosed and managed in primary care. The specialist classification systems
for MUS pose several problems in a primary care setting. The systems generally require great certainty about
presence or absence of physical disease, they tend to be mind-body dualistic, and they view symptoms from a
narrow specialty determined perspective. We need a new classification of MUS in primary care; a classification
that better supports clinical decision-making, creates clearer communication and provides scientific underpinning
of research to ensure effective interventions.
Discussion: We propose a classification of symptoms that places greater emphasis on prognostic factors.
Prognosis-based classification aims to categorise the patient’s risk of ongoing symptoms, complications, increased
healthcare use or disability because of the symptoms. Current evidence suggests several factors which may be
used: symptom characteristics such as: number, multi-system pattern, frequency, severity. Other factors are:
concurrent mental disorders, psychological features and demographic data. We discuss how these characteristics may
be used to classify symptoms into three groups: self-limiting symptoms, recurrent and persistent symptoms, and
symptom disorders. The middle group is especially relevant in primary care; as these patients generally have reduced
quality of life but often go unrecognised and are at risk of iatrogenic harm. The presented characteristics do not
contain immediately obvious cut-points, and the assessment of prognosis depends on a combination of several factors.
Conclusion: Three criteria (multiple symptoms, multiple systems, multiple times) may support the classification into
good, intermediate and poor prognosis when dealing with symptoms in primary care. The proposed new classification
specifically targets the patient population in primary care and may provide a rational framework for decision-making in
clinical practice and for epidemiologic and clinical research of symptoms
Energy-efficiency versus resilience: risk awareness view on dimensioning of optical networks with a sleep mode
A City for People with Autism - An Explorative Study of a more Inclusive Build Environment
Adoption rate forecasts and rollout strategies
Residual broadband market, Adoption rate forecasts, DSL rollout strategies,
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