921 resultados para ACUTE LYMPHOBLASTIC-LEUKEMIA


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Acute pancreatitis (AP) is a common disease. Mild disease resolves spontaneously in a few days. Severe forms of the disease can lead to local complications, necrosis, and abscesses in and around the pancreas. Systemic inflammation in severe AP is associated with distant organ failures. The aim of this study is to identify genetically determined prognostic factors involved in the clinical features of AP. The study employs a candidate-gene approach, and the genes are involved in trysinogen activation in the initiation phase of the disease, as well as in the systemic inflammation as the disease proceeds. The last study examines adipokines, fat-derived hormones characterized with the capacity to modify inflammation. SPINK 1 is a gene coding trypsin activation inhibitor. Mutations N34S and P55N were determined by minisequencing methods in 371 AP patients and in 459 controls. The mutation N34S was more common in AP patients (7.8%) than in controls (2.6%). This suggests that SPINK 1 gene mutation N34S is a risk factor for AP. In the fourth study, in 12 matched pairs of patients with severe and mild AP, levels of adipokines, adiponectin, and leptin were evaluated. Plasma adipokine levels did not differ between patients with mild and severe AP. The results suggest that in AP, adipokine plasma levels are not factors predisposing to organ failures. This study identified the SPINK 1 mutation N34S to be a risk factor for AP in the general population. As AP is a multifactorial disease, and extensive genetic heterogeneity is likely, further identification of genetic factors in the disease requires larger future studies with more advanced genetic study models. Further identification of the patient characteristics associated with organ failures offers another direction of the study to achieve more detailed understanding of the severe form of AP.

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Most studies exploring the role of upper airway viruses and bacteria in paediatric acute respiratory infections (ARI) focus on specific clinicaldiagnoses and/or do not account for virus–bacteria interactions. We aimed to describe the frequency and predictors of virus and bacteria codetection in children with ARI and cough, irrespective of clinical diagnosis. Bilateral nasal swabs, demographic, clinical and risk factor data were collected at enrollment in children aged <15 years presenting to an emergency department with an ARI and where cough was a symptom. Swabs were tested by polymerase chain reaction for 17 respiratory viruses and seven respiratory bacteria. Logistic regression was used to investigate associations between child characteristics and codetection of the organisms of interest. Between December 2011 and August 2014, swabs were collected from 817 (93.3%) of 876 enrolled children, median age 27.7 months (interquartile range13.9–60.3 months). Overall, 740 (90.6%) of 817 specimens were positive for any organism. Both viruses and bacteria were detected in 423 specimens (51.8%). Factors associated with codetection were age (adjusted odds ratio (aOR) for age <12 months = 4.9, 95% confidence interval (CI) 3.0, 7.9; age 12 to <24 months = 6.0, 95% CI 3.7, 9.8; age 24 to <60 months = 2.4, 95% CI 1.5, 3.9), male gender (aOR 1.46; 95% CI 1.1, 2.0), child care attendance (aOR 2.0; 95% CI 1.4, 2.8) and winter enrollment (aOR 2.0; 95% CI 1.3, 3.0). Haemophilus influenzae dominated the virus–bacteria pairs. Virus–H. influenzae interactions in ARI should be investigated further, especially as the contribution of nontypeable H. influenzae to acute and chronic respiratory diseases is being increasingly recognized.

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A series of novel fluoroaminophosphates 4a-4j were synthesized by one-pot method in presence of tetramethylguanidine (TMG) as a catalyst and were characterized by elemental analysis, FTIR, H-1, C-13, P-31, F-19 NMR, and mass spectra. All the title compounds were evaluated forin vitro cytotoxicity against leukemic cell line derived from T-cells of leukemia patient (CEM cells) by Trypan blue exclusion and MTT assays, and these were found to exert concentration dependent cytotoxic effects. Among them 4f, 4g & 4j possessed marked cytotoxicity. 4g (with IC50 value of 6 mu M) had emerged as lead compound.

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Acute heart failure (AHF) is a complex syndrome associated with exceptionally high mortality. Still, characteristics and prognostic factors of contemporary AHF patients have been inadequately studied. Kidney function has emerged as a very powerful prognostic risk factor in cardiovascular disease. This is believed to be the consequence of an interaction between the heart and kidneys, also termed the cardiorenal syndrome, the mechanisms of which are not fully understood. Renal insufficiency is common in heart failure and of particular interest for predicting outcome in AHF. Cystatin C (CysC) is a marker of glomerular filtration rate with properties making it a prospective alternative to the currently used measure creatinine for assessment of renal function. The aim of this thesis is to characterize a representative cohort of patients hospitalized for AHF and to identify risk factors for poor outcome in AHF. In particular, the role of CysC as a marker of renal function is evaluated, including examination of the value of CysC as a predictor of mortality in AHF. The FINN-AKVA (Finnish Acute Heart Failure) study is a national prospective multicenter study conducted to investigate the clinical presentation, aetiology and treatment of, as well as concomitant diseases and outcome in, AHF. Patients hospitalized for AHF were enrolled in the FINN-AKVA study, and mortality was followed for 12 months. The mean age of patients with AHF is 75 years and they frequently have both cardiovascular and non-cardiovascular co-morbidities. The mortality after hospitalization for AHF is high, rising to 27% by 12 months. The present study shows that renal dysfunction is very common in AHF. CysC detects impaired renal function in forty percent of patients. Renal function, measured by CysC, is one of the strongest predictors of mortality independently of other prognostic risk markers, such as age, gender, co-morbidities and systolic blood pressure on admission. Moreover, in patients with normal creatinine values, elevated CysC is associated with a marked increase in mortality. Acute kidney injury, defined as an increase in CysC within 48 hours of hospital admission, occurs in a significant proportion of patients and is associated with increased short- and mid-term mortality. The results suggest that CysC can be used for risk stratification in AHF. Markers of inflammation are elevated both in heart failure and in chronic kidney disease, and inflammation is one of the mechanisms thought to mediate heart-kidney interactions in the cardiorenal syndrome. Inflammatory cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) correlate very differently to markers of cardiac stress and renal function. In particular, TNF-α showed a robust correlation to CysC, but was not associated with levels of NT-proBNP, a marker of hemodynamic cardiac stress. Compared to CysC, the inflammatory markers were not strongly related to mortality in AHF. In conclusion, patients with AHF are elderly with multiple co-morbidities, and renal dysfunction is very common. CysC demonstrates good diagnostic properties both in identifying impaired renal function and acute kidney injury in patients with AHF. CysC, as a measure of renal function, is also a powerful prognostic marker in AHF. CysC shows promise as a marker for assessment of kidney function and risk stratification in patients hospitalized for AHF.

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Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an efficient technique is presented for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used for the control (medication) synthesis. First, taking a set of nominal parameters, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat nominal patients (patients having same nominal parameters as used for the control design) effectively. However, since the parameters of an actual patient can be different from that of the ideal patient, to make the treatment strategy more effective and efficient, a model-following neuro-adaptive controller is augmented to the nominal controller. In this approach, a neural network trained online (based on Lyapunov stability theory) facilitates a new adaptive controller, computed online. From the simulation studies, this adaptive control design approach (treatment strategy) is found to be very effective to treat the CML disease for actual patients. Sufficient generality is retained in the theoretical developments in this paper, so that the techniques presented can be applied to other similar problem as well. Note that the technique presented is computationally non-intensive and all computations can be carried out online.