No description available.

No description available.

No description available.

Objective: To determine the usefulness of the Alvarado score and the Pediatric Appendicitis score (PAS) in the Pediatric Emergency of the National Hospital Daniel A. Carrion. Materials and methods: A prospective observational study was carried out of patients younger than 15 years of age with abdominal pain and suspected acute appendicitis (AA) attending the Pediatric Emergency in a Hospital of Lima, Peru. These patients underwent a survey to assess the parameters of the Alvarado score and PAS. Results: Three hundred and seventeen patients with abdominal pain and suspected of AA were recruited over a study period of 12 months. Of the patients, 232 were considered to have AA clinically and underwent surgery. 85.3% were confirmed by pathology and 14.7% were normal. The mean Alvarado score was 8.27±1.31; the mean Surgical Procedure Assessment (SPA) score was 8.08±1.47. Sensitivity and specificity for both scores are equivalent. The area under the curve for the Alvarado score and SPA were 0.887 and 0.901, respectively. Alvarado score higher than 6 had a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of 88.9, 75.6, 97.4, 68.1, and 86.4%, respectively. SPA higher than 6 points had sensitivity, specificity, PPV, NPV, and accuracy of 84.3, 80.7, 94.7, 73.1, and 86.7%, respectively. Conclusion: Alvarado score and the PAS are scores with high sensitivity, specificity, PPV, and accuracy for the diagnosis of AA when the score is higher than 6 points. The results found in our study justify their use in emergency services, but they should not be used as the only means of clinically determining the need for surgery.

Recruitment and derecruitment (R/D) of airways is known to significantly influence mechanical properties of the respiratory system during artificial ventilation, particularly in states of lung injury. The prevailing view of this phenomenon treats airway R/D as a static function of pressure. Recent experimental and clinical data suggests that this is not the case, but rather that R/D is an inherently dynamic process. In order to quantitatively assess the dynamics of lung recruitment during mechanical ventilation we extended a mathematical model by Bates and Irvin (9) for the purpose of fitting experimental data. The model of the lung consists of a parallel network of flow pathways with identical resistive and elastic elements. Each pathway is allowed to be either open, whereby it accumulates flow and decreases overall lung stiffness, or closed, increasing lung elastance and not participating in ventilation. The pathways are characterized by unique critical closing and opening pressures, and opening and closing velocities, each chosen from probability distribution functions. The rate of transition between an open and closed state depends on the magnitude difference between the pressure in the respiratory system and each unit’s critical pressure times the airway’s opening or closing velocity constant. Since the exact form of the pressure dependence governing recruitment and derecruitment remains unknown we explored four model variants to predict how opening or closing behavior is altered in injury. The lung model was coupled with a computational model of a mechanical ventilator in order to simulate elastance changes following deep inflation (DI) at three levels of Positive End Expiratory Pressure (PEEP). Elastance measurements came from healthy or lung injured mice at 4, 14, 24 or 48 hours following intratracheal instillation of saline (control) or hydrochloric acid (injury). The Nelder and Mead simplex optimization method was used to minimize error between model variants and average experimental elastance for each condition. By comparing the residual error of the fits for each model, we have demonstrated that only one variant was able to recreate both the transient response to deep inflations and the response to static PEEP. In fitting the best model to data from individual mice we obtained estimates for parameters governing opening and closing behavior. Statistics and model sensitivity were determined for each parameter in every experimental condition. Comparison of parameter values between groups revealed a significant increase in closing and opening pressures from health to injury, which worsened with increasing injury severity. The progressive increase in critical pressures as injury worsens implicates surfactant deactivation as the likely cause of increased propensity for airway closing during acute lung injury.

I have studied the calpain system in acute myeloid leukemia using the 32D and 32Dkit cell lines. Specifically, I characterized the calpain system in the cell lines, and performed calpastatin overexpression and knockdown studies. I found that calpain activity is elevated in the 32D and 32Dkit cells, and calpain inhibition causes apoptosis. Both μ- and m-calpain contribute to the calpain activity in these cell lines. The 32Dkit cells have higher calpain activity than the 32D cells, which I have shown is partially attributed to basal ckit activation. Calpastatin was present in both cell lines, but exists mainly in a degraded form. Calpastatin overexpression lowered calpain activity and provided a growth disadvantage to the 32Dkit cells, but had no effect on 32D cells. Calpastatin knockdown caused a significant increase in calpain activity in the 32D cells, which changed the cell cycle distribution but had no other major effects.

published_or_final_version / Pathology / Master / Master of Medical Sciences

published_or_final_version / Medicine / Master / Master of Philosophy

I have studied the calpain system in acute myeloid leukemia using the 32D and 32Dkit cell lines. Specifically, I characterized the calpain system in the cell lines, and performed calpastatin overexpression and knockdown studies. I found that calpain activity is elevated in the 32D and 32Dkit cells, and calpain inhibition causes apoptosis. Both μ- and m-calpain contribute to the calpain activity in these cell lines. The 32Dkit cells have higher calpain activity than the 32D cells, which I have shown is partially attributed to basal ckit activation. Calpastatin was present in both cell lines, but exists mainly in a degraded form. Calpastatin overexpression lowered calpain activity and provided a growth disadvantage to the 32Dkit cells, but had no effect on 32D cells. Calpastatin knockdown caused a significant increase in calpain activity in the 32D cells, which changed the cell cycle distribution but had no other major effects.

Acute Lymphoblastic Leukemia (ALL) is the most common cancer in children under the age of 15. At present, diagnosis, prognosis and treatment decisions are made based upon blood and bone marrow laboratory testing. With advances in microarray technology it is becoming more feasible to perform genetic assessment of individual patients as well. We used Singular Value Decomposition (SVD) on Illumina SNP, Affymetrix and cDNA gene-expression data and performed aggressive attribute se- lection using random forests to reduce the number of attributes to a manageable size. We then explored clustering and prediction of patient-specific properties such as disease sub-classification, and especially clinical outcome. We determined that integrating multiple types of data can provide more meaningful information than individual datasets, if combined properly. This method is able to capture the cor- relation between the attributes. The most striking result is an apparent connection between genetic background and patient mortality under existing treatment regimes. We find that we can cluster well using the mortality label of the patients. Also, using a Support Vector Machine (SVM) we can predict clinical outcome with high accu-racy. This thesis will discuss the data-mining methods used and their application to biomedical research, as well as our results and how this will affect the diagnosis and treatment of ALL in the future. / Thesis (Master, Computing) -- Queen's University, 2010-01-12 18:40:44.2