Human umbilical cord blood cells suffer major modification by fixatives and anticoagulants.

Introduction: Developing techniques for the tagless isolation of homogeneous cell populations in physiological-like conditions is of great interest in medical research. A particular case is Gravitational Field-Flow Fractionation (GrFFF), which can be run avoiding cell fixation, and that was already used to separate viable cells. Cell dimensions have a key role in this process. However, their dimensions under physiological-like conditions are not easily known since the most diffused measurement techniques are performed on fixed cells, and the fixation used to preserve tissues can alter the cell size. This work aims to obtain and compare cell size data under physiological-like conditions and in the presence of a fixative. Methods: We developed a new protocol that allows the analysis of blood cells in different conditions. Then, we applied it to obtain a dataset of human cord blood cell dimensions from 32 subjects, comparing two tubes with anticoagulants (EDTA and Citrate) and two tubes with different preservatives (CellRescue and CellSave). We analyzed a total of 2071 cells by using confocal microscopy via bio-imaging to assess dimensions (cellular and nuclear) and morphology. Results: Cell diameter measured does not differ when using the different anticoagulants, except for the increase reported for monocyte in the presence of citrate. Instead, cell dimensions differ when comparing anticoagulants and cell preservative tubes, with a few exceptions. Cells characterized by high cytoplasm content show a reduction in their size, while morphology appears always preserved. In a subgroup of cells, 3D reconstruction was performed. Cell and nucleus volumes were estimated using different methods (specific 3D tool or reconstruction from 2D projection). Discussion: We found that some cell types benefit from a complete 3D analysis because they contain non-spherical structures (mainly for cells characterized by poly-lobated nucleus). Overall, we showed the effect of the preservatives mixture on cell dimensions. Such an effect must be considered when dealing with problems highly dependent on cell size, such as GrFFF. Additionally, such information is crucial in computational models increasingly being employed to simulate biological events.

A comparative study of the definitions of intradialytic hypotension correlated with increased mortality to identify universal predictors.

Intradialytic hypotension (IDH) is a common complication in patients undergoing hemodialysis therapy. No consensus on the definition of intradialytic hypotension has been established so far. As a result, coherent and consistent evaluation of its effects and causes is difficult. Some studies have highlighted existing correlations between certain definitions of IDH and the risk of mortality for the patients. This work is mainly focused on these definitions. Our aim is to understand if different IDH definitions, all correlated with increased mortality risk, catch the same onset mechanisms or dynamics. To check whether the dynamics captured by these definitions are similar, we performed analyses of the incidence, of the IDH event onset timing, and checked whether there were similarities between the definitions in those aspects. We evaluated how these definitions overlap with each other and we evaluated which common factors could allow identifying patients at risk of IDH at the beginning of a dialysis session. The definitions of IDH we analyzed through statistical and machine learning approaches, showed a variable incidence on the HD sessions and had different onset time. We found that the set of parameters relevant for the prediction of the IDH was not always the same for the definitions considered. However, it can be observed that some predictors, such as the presence of comorbidities such as diabetes or heart disease, and a low pre-dialysis diastolic blood pressure, have shown universal relevance in highlighting an increased risk of IDH during the treatment. Among those parameters, the one that showed a major importance is the diabetes status of the patients. Diabetes or heart disease presence are permanent risk factors pointing out an increased IDH risk during the treatments, while, pre-dialysis diastolic blood pressure is instead a parameter that can change at every session and should be used to evaluate the specific risk to develop IDH for each session. The identified parameters could be used in the future to train more complex prediction models.

Can the response to dialysis treatment be predicted by using patient-specific modeling of fluid and solute exchanges? A multicentric evaluation.

BACKGROUND: Parametric multipool kinetic models were used to describe the intradialytic trends of electrolytes, breakdown products, and body fluids volumes during hemodialysis. Therapy customization can be achieved by the identification of parameters, allowing patient-specific modulation of mass and fluid balance across dialyzer, capillary, and cell membranes. This study wants to evaluate the possibility to use this approach to predict the patient's intradialytic response. METHODS: 6 sessions of 68 patients (DialysIS© project) were considered. Data from the first three sessions were used to train the model, identifying the patient-specific parameters, that, together with the treatment settings and the patient's data at the session start, could be used for predicting the patient's specific time course of solutes and fluids along the sessions. Na+ , K+ , Cl- , Ca2+ , HCO3 - , and urea plasmatic concentrations and hematic volume deviations from clinical data were evaluated. RESULTS: nRMSE predictive error is on average equal to 4.76% when describing the training sessions, and only increases by 0.97 percentage points on average in independent sessions of the same patient. CONCLUSIONS: The proposed predictive approach represents a first step in the development of tools to support the clinician in tailoring the patient's prescription.

Shear-Induced Encapsulation into Red Blood Cells: A New Microfluidic Approach to Drug Delivery.

Encapsulating molecules into red blood cells (RBCs) is a challenging topic for drug delivery in clinical practice, allowing to prolong the residence time in the body and to avoid toxic residuals. Fluidic shear stress is able to temporary open the membrane pores of RBCs, thus allowing for the diffusion of a drug in solution with the cells. In this paper, both a computational and an experimental approach were used to investigate the mechanism of shear-induced encapsulation in a microchannel. By means of a computational fluid dynamic model of a cell suspension, it was possible to calculate an encapsulation index that accounts for the effective shear acting on the cells, their distribution in the cross section of the microchannel and their velocity. The computational model was then validated with micro-PIV measurements on a RBCs suspension. Finally, experimental tests with a microfluidic channel showed that, by choosing the proper concentration and fluid flow rate, it is possible to successfully encapsulate a test molecule (FITC-Dextran, 40 kDa) into human RBCs. Cytofluorimetric analysis and confocal microscopy were used to assess the RBCs physiological shape preservation and confirm the presence of fluorescent molecules inside the cells.

A computational model for microcirculation including Fahraeus-Lindqvist effect, plasma skimming and fluid exchange with the tissue interstitium.

We present a two-phase model for microcirculation that describes the interaction of plasma with red blood cells. The model takes into account of typical effects characterizing the microcirculation, such as the Fahraeus-Lindqvist effect and plasma skimming. Besides these features, the model describes the interaction of capillaries with the surrounding tissue. More precisely, the model accounts for the interaction of capillary transmural flow with the surrounding interstitial pressure. Furthermore, the capillaries are represented as one-dimensional channels with arbitrary, possibly curved configuration. The latter two features rely on the unique ability of the model to account for variations of flow rate and pressure along the axis of the capillary, according to a local differential formulation of mass and momentum conservation. Indeed, the model stands on a solid mathematical foundation, which is also addressed in this work. In particular, we present the model derivation, the variational formulation, and its approximation using the finite element method. Finally, we conclude the work with a comparative computational study of the importance of the Fahraeus-Lindqvist, plasma skimming, and capillary leakage effects on the distribution of flow in a microvascular network.

Numerical simulations of the microvascular fluid balance with a non-linear model of the lymphatic system.

Fluid homeostasis is required for life. Processes involved in fluid balance are strongly related to exchanges at the microvascular level. Computational models have been presented in the literature to analyze the microvascular-interstitial interactions. As far as we know, none of those models consider a physiological description for the lymphatic drainage-interstitial pressure relation. We develop a computational model that consists of a network of straight cylindrical vessels and an isotropic porous media with a uniformly distributed sink term acting as the lymphatic system. In order to describe the lymphatic flow rate, a non-linear function of the interstitial pressure is defined, based on literature data on the lymphatic system. The proposed model of lymphatic drainage is compared to a linear one, as is typically used in computational models. To evaluate the response of the model, the two are compared with reference to both physiological and pathological conditions. Differences in the local fluid dynamic description have been observed using the non-linear model. In particular, the distribution of interstitial pressure is heterogeneous in all the cases analyzed. The resulting averaged values of the interstitial pressure are also different, and they agree with literature data when using the non-linear model. This work highlights the key role of lymphatic drainage and its modeling when studying the fluid balance in microcirculation for both to physiological and pathological conditions, e.g. uremia.

A Bayesian approach for the identification of patient-specific parameters in a dialysis kinetic model.

Hemodialysis is the most common therapy to treat renal insufficiency. However, notwithstanding the recent improvements, hemodialysis is still associated with a non-negligible rate of comorbidities, which could be reduced by customizing the treatment. Many differential compartment models have been developed to describe the mass balance of blood electrolytes and catabolites during hemodialysis, with the goal of improving and controlling hemodialysis sessions. However, these models often refer to an average uremic patient, while on the contrary the clinical need for customization requires patient-specific models. In this work, we assume that the customization can be obtained by means of patient-specific model parameters. We propose and validate a Bayesian approach to estimate the patient-specific parameters of a multi-compartment model, and to predict the single patient's response to the treatment, in order to prevent intra-dialysis complications. The likelihood function is obtained by means of a discretized version of the multi-compartment model, where the discretization is in terms of a Runge-Kutta method to guarantee convergence, and the posterior densities of model parameters are obtained through Markov Chain Monte Carlo simulation. Results show fair estimations and the applicability in the clinical practice.

Assessment of intradialysis calcium mass balance by a single pool variable-volume calcium kinetic model.

INTRODUCTION: A reliable method of intradialysis calcium mass balance quantification is far from been established. We herein investigated the use of a single-pool variable-volume Calcium kinetic model to assess calcium mass balance in chronic and stable dialysis patients. METHODS: Thirty-four patients on thrice-weekly HD were studied during 240 dialysis sessions. All patients were dialyzed with a nominal total calcium concentration of 1.50 mmol/L. The main assumption of the model is that the calcium distribution volume is equal to the extracellular volume during dialysis. This hypothesis is assumed valid if measured and predicted end dialysis plasma water ionized calcium concentrations are equal. A difference between predicted and measured end-dialysis ionized plasma water calcium concentration is a deviation on our main hypothesis, meaning that a substantial amount of calcium is exchanged between the extracellular volume and a nonmodeled compartment. FINDINGS: The difference between predicted and measured values was 0.02 mmol/L (range -0.08:0.16 mmol/L). With a mean ionized dialysate calcium concentration of 1.25 mmol/L, calcium mass balance was on average negative (mean ± SD -0.84 ± 1.33 mmol, range -5.42:2.75). Predialysis ionized plasma water concentration and total ultrafiltrate were the most important predictors of calcium mass balance. A significant mobilization of calcium from the extracellular pool to a nonmodeled pool was calculated in a group of patients. DISCUSSION: The proposed single pool variable-volume Calcium kinetic model is adequate for prediction and quantification of intradialysis calcium mass balance, it can evaluate the eventual calcium transfer outside the extracellular pool in clinical practice.

Patient-specific modeling of multicompartmental fluid and mass exchange during dialysis.

BACKGROUND: Dialysis is associated with a non-negligible rate of morbidity, requiring treatment customization. Many mathematical models have been developed describing solute kinetics during hemodialysis (HD) for an average uremic patient. The clinical need can be more adequately addressed by developing a patient-specific, multicompartmental model. MATERIALS AND METHODS: The data from 148 sessions (20 patients), recorded at the Regional Hospital of Lugano, Switzerland, were used to develop and validate the mathematical model. Diffusive and convective interactions among patient, dialysate and substitution fluid were considered. Three parameters, related to mass transfer efficiency at the cell membrane, at the dialyzer and at the capillary wall, were used to tune the model. The ability of the model to describe the clinical evolution of a specific HD session was evaluated by comparing model outputs with clinically acquired data on solutes and catabolite concentrations. RESULTS: The model developed in this study allows electrolyte and catabolite concentration trends during each HD session to be described. The errors obtained before the estimation of the patient-specific parameters drastically decrease after their identification. With the optimized model, plasmatic concentration trends can be described with an average percent error lower than 2.1% for Na+, Cl-, Ca2+ and HCO3-, lower than 5% for K+ and lower than 8% for urea. CONCLUSIONS: The peculiarity of the proposed model is the possibility it offers to perform a real-time simulation enabling quantitative appraisal of hematochemical quantities whose direct measurement is prohibitive. These will be beneficial to dialysis therapy planning, reducing intradialysis complications and improving patients' quality of life.

Application of Controlled Shear Stresses on the Erythrocyte Membrane as a New Approach to Promote Molecule Encapsulation.

Human red blood cells (RBCs) have a remarkable capacity to undergo reversible membrane swelling. Resealed erythrocytes have been proposed as carriers and bioreactors to be used in the treatment of various diseases. This work is aimed at developing a setup allowing the encapsulation of test molecules into erythrocytes by inducing reversible pore formation on the RBC membrane through the application of controlled mechanical shear stresses. The designed setup consists of two reservoirs connected by a glass capillary. Each reservoir is connected to a compressor; during the tests, the reservoirs were in turn pressurized to promote erythrocyte flow through the capillary. The setup was filled with a suspension of erythrocytes, phosphate buffer, and FITC-dextran. Dextran was chosen as the diffusive molecule to check membrane pore dimensions. Samples of the suspension were withdrawn at scheduled times while the setup was operating. Flow cytometry and stereo-optical microscopy analyses were used to evaluate the erythrocyte dextran uptake. The setup was shown to be safe, well controlled, and adjustable. The outcomes of the experimental tests showed significant dextran uptake by RBCs up to 8%. Microscopy observations highlighted the formation of echinocytes in the analyzed samples. Erythrocytes from different donors showed different reactions to mechanical stresses. The experimental outcomes proved the possibility to encapsulate test molecules into erythrocytes by applying controlled mechanical shear stresses on the RBC membrane, encouraging further studies.

How to extract clinically useful information from large amount of dialysis related stored data.

The basic storage infrastructure used to gather data from the technological evolution also in the healthcare field was leading to the storing into public or private repository of even higher quantities of data related to patients and their pathological evolution. Big data techniques are spreading also in medical research. By these techniques is possible extract information from complex heterogeneous sources, realizing longitudinal studies focused to correlate the patient status with biometric parameters. In our work we develop a common data infrastructure involving 4 clinical dialysis centers between Lombardy and Switzerland. The common platform has been build to store large amount of clinical data related to 716 dialysis session of 70 patient. The platform is made up by a combination of a MySQL(®) database (Dialysis Database) and a MATLAB-based mining library (Dialysis MATlib). A statistical analysis of these data has been performed on the data gathered. These analyses led to the development of two clinical indexes, representing an example of transformation of big data into clinical information.

Determination of cardiovascular mechanics evolution in the presence of the arteriovenous fistula.

Uremic patients are prone to heart damage as a consequence of arteriovenous fistula (AVF) presence and hemodialysis treatment. Arteriovenous fistula induces hand ischemic syndrome and cardiac work increase, thus determining cardiac insufficiency in the medium to long term. This work investigates the cardiovascular mechanics evolution induced by the fistula presence. Twenty patients were enrolled; blood pressure, heart rate (HR), cardiac dimensions, and fistula flow were measured at scheduled intervals. A mathematical model of the cardiocirculatory system was implemented to simulate cardiovascular evolution. Input parameters were heart and vessel features; output of the model were cardiac performances indicators, partly reproducing measurable data and partly quantifiable only by using the model. Input and output variability and their long-term variations were analyzed. Blood pressure and peripheral resistance were found to be higher in uremic than in healthy subjects. Fistula tailoring showed increased cardiac fiber contractility and decreased peripheral resistances. Moreover, between 10 days and 3 months, an increased blood flow at the vascular access determined an increment in fiber contractility. In the same period, the 85% of the patients showed an increase in cardiac fiber stiffness. Similar but less pronounced trends were observed between 3 months and 1 year. The developed model reproduces the cardiovascular system in physiologic and pathologic conditions and allows description of the cardiovascular evolution for a uremic patient.

Integrated model of endothelial NO regulation and systemic circulation for the comparison between pulsatile and continuous perfusion.

Many experimental studies concerning nitric oxide (NO) release from endothelium and its vasodilative action are available in the literature, but no analytical description or modeling of these phenomena can be found. On the contrary, a large modeling literature is available concerning the other cardiovascular control mechanisms, such as the myogenic and metabolic control. In order to analytically describe these phenomena, a model of the endothelial control (defined in the Laplace domain and based on experimental data) was implemented and integrated with a lumped-parameter model of the systemic circulation, consisting of large artery segments and peripheral networks. The endothelial regulation model was based on the hypothesis proposed by Kuchan and Frangos, considering that NO release from the endothelium is generated by two parallel paths. The whole model was then applied to study the different vascular constriction or dilation under continuous or pulsatile perfusion, in order to better understand the clinical evidences of a poor organ perfusion in the presence of continuous with respect to pulsatile cardiopulmonary bypass. According to the experimental evidences, the main results obtained from the model revealed a widespread vascular constriction under continuous perfusion with respect to pulsatile. This result remains constant in the presence of different conditions of blood parameters and flow waveform.