Incidence, risk factors, and outcome of asymptomatic central nervous system involvement in adult patients with acute myeloid leukemia.

Examination of central nervous system (CNS) involvement is not routine diagnostic practice in adult patients with acute myeloid leukemia (AML). Therefore, many asymptomatic patients with CNS involvement might go undetected. The effect of CNS involvement on the AML disease course is not well defined, with conflicting results regarding clinical outcome. This study aimed to determine the incidence of asymptomatic CNS involvement in AML estimated by multiparametric flow cytometry of cerebrospinal fluid (MFC-CSF) at diagnosis, the related potential risk factors, and prognosis. In total, 645 patients with de novo AML were screened; 183 (28.4%) of them fulfilled institutional practice for MFC-CSF analysis based on presence of CNS symptoms and/or clinical features. CNS symptoms and signs were observed in 8/183 (4.4%) patients, but most patients (175/183, 95.6%) were asymptomatic. In the asymptomatic group, 73/175 (41.7%) patients had positive or suspicious cerebrospinal fluid (CSF) findings categorized as CNS positive (CNSpos) and 102/175 (58.3%) had normal CNS findings categorized as CNS negative (CNSneg). The presence of leukemic blasts was confirmed in 81/183 (44.3%) patients; the total incidence of CNS involvement in the whole AML group was 12.6% (81/645). Compared with asymptomatic patients with CNSneg, those with CNSpos had a significantly higher frequency of lymphadenopathy, white blood cell count ≥30 × 109/L, presence of the monocytic phenotype, and a high percentage of bone marrow (BM) blasts. The multivariate logistic regression model identified monocytic phenotype (p = 0.047) and high percentage of BM blasts (p = 0.042) as predictors for CNSpos. CNSpos did not affect overall survival in patients with AML. There was a higher incidence of CNS involvement in asymptomatic adult patients with de novo AML, emphasizing possible undervalued rates of CNS disease at diagnosis. Prospective studies should determine whether diagnostic lumbar puncture for MFC-CSF analysis and CNS prophylaxis could contribute to better selection and prognosis in this patient population.

Biomechanical model of swimming rehabilitation after hip and knee surgery.

As a low-to-moderate intensity rehabilitation exercise after hip and knee surgery, we propose a dynamical model of the legs motion through the water medium in freestyle and backstroke swimming. We formulate a general Kirchhoff-Lagrangian dynamics model of the legs-propulsion through the water in post-surgical rehabilitation swimming. We start by defining the two-leg-propulsion configuration manifold. This is composed of eight Euclidean groups of rigid motions in 3D space for each of the four leg segments. Next, we define Newton-Euler dynamics for each segment. This single segmental dynamics is further generalized into Lagrangian dynamics for the whole leg-propulsion system. Finally, the water effects are added in the form of Kirchhoff's vector cross-products. In agreement with orthopaedic recommendations for post-surgical rehabilitation, numerical simulation is performed on a simplified version of the full Kirchhoff-Lagrangian dynamics model, which we call the "robotic swimming leg" - with intentionally reduced number of (microscopic, non-sagittal) degrees-of-freedom. The purpose of this development is both qualitative, for medical and physiotherapist practitioners to study, and quantitative, for biomechanics experts to analyze and further develop.

The role of immunophenotyping in differential diagnosis of chronic lymphocytic leukemia.

INTRODUCTION: Accurate diagnosis of chronic lymphocytic leukemia (CLL) acquires immunophenotyping by flow cytometry in order to facilitate differential diagnosis between CLL and other mature B-cell neoplasms (MBCN). OBJECTIVE: The aim of this study was to define immunological profile of CLL cells. METHODS: Immunophenotyping by flow cytometry was performed on peripheral blood specimens at diagnosis in the group of 211 patients with de novo MBCN. RESULTS: Absolute count of B-cells was significantly increased in all MBCN patients comparing to healthy control group (p < 0.05). B-cell monoclonality was detected in 96% of all MBCN patients, by using surface immunoglobulin (sIg) light chain restriction. B-cell antigens, CD19, CD20, CD22, were expressed with very high frequency in CLL and other MBCN. In comparison with other MBCN, in CLL group, the frequency of expression was higher for CD5 and CD23 (p < 0.0001), though lower for FMC7 antigen (p < 0.0001). CLL patients were characterized by lower expression patterns of CD20, CD22, CD79b, and sIg (p < 0.0001) as well as higher expression pattern of CD5 antigen (p < 0.05). Correlation between the final diagnosis of MBCN and values of CLL scoring system showed that the majority of CLL patients (97%) had higher values (5 or 4) whereas the majority of other MBCN patients (96%) had lower score values (0-3). CONCLUSION: Our results have shown that characteristic immunophenotype which differentiates CLL from other MBCN is defined by following marker combination--CD19+ CD20(+Iow) CD22(+low) CD5(+high) CD23+ FMC7-CD79b(+Iow) sIg(+Iow). CLL score values of 5 or 4 points are highly suggestive for diagnosis of CLL.

Non-linear dynamics in muscle fatigue and strength model during maximal self-perceived elbow extensors training.

Our aim was to determine the dynamics in muscle strength increase and fatigue development during repetitive maximal contraction in specific maximal self-perceived elbow extensors training program. We will derive our functional model for m. triceps brachii in spirit of traditional Hill's two-component muscular model and after fitting our data, develop a prediction tool for this specific training system. Thirty-six healthy young men (21 +/- 1.0 y, BMI 25.4 +/- 7.2 kg/m(2)), who did not take part in any formal resistance exercise regime, volunteered for this study. The training protocol was performed on the isoacceleration dynamometer, lasted for 12 weeks, with a frequency of five sessions per week. Each training session included five sets of 10 maximal contractions (elbow extensions) with a 1 min resting period between each set. The non-linear dynamic system model was used for fitting our data in conjunction with the Levenberg-Marquardt regression algorithm. As a proper dynamical system, our functional model of m. triceps brachii can be used for prediction and control. The model can be used for the predictions of muscular fatigue in a single series, the cumulative daily muscular fatigue and the muscular growth throughout the training process. In conclusion, the application of non-linear dynamics in this particular training model allows us to mathematically explain some functional changes in the skeletal muscle as a result of its adaptation to programmed physical activity-training.