Sensitive determination of daunorubicin in plasma of children with leukemia using pH-switchable deep eutectic solvents and HPLC-UV analysis.

An environmental friendly, fast, easy and inexpensive liquid-liquid microextraction (LLME) in combination with pH-switchable deep eutectic solvent (DES) method followed by HPLC was investigated for the separation and determination of daunorubicin (DNR) in human plasma samples. For this purpose, first, 9 DESs were prepared based on previous studies and their switchability in aqueous solution was evaluated by changing the pH. Non-switchable DESs were discarded and switchable DESs were used to extract DNR. The parameters affecting the extraction efficiency were optimized (DES type, volume of DES, concentration of KOH, volume of HCl, salt addition and extraction time). After optimizing the conditions and drawing the calibration curve, figures of merit were calculated. Relative standard deviations (%RSDs) based on 7 replicate with 50 µg L-1 of DNR in plasma were 2.7 for intra-day and 4.8 % for inter-day. A wide linear range from 0.15 to 200 µg L-1 was obtained. The detection limit of the method based on signal-to-noise 3 and the quantification limit of the method based on signal-to-noise 10 were 0.05 and 0.15, respectively. After spiking plasma samples with different concentrations of DNR, relative recoveries were obtained in the range of 91.0-107.8 %.

Sensitive determination of vincristine in plasma of children with leukaemia using vortex-assisted dispersive liquid-liquid microextraction based on hydrophobic deep eutectic solvent.

Vincristine has a wide spectrum of clinical activity and is currently used in the treatment of leukemia. Despite its high therapeutic properties, vincristine has common side effects. Accordingly, it is desirable to determine vincristine in plasma for the use of the drug with strict monitoring. In the present research, for the first time a hydrophobic deep eutectic solvent (DES) composed of methyltrioctylammonium chloride (MTOAC) and n-butanol in a molar ratio of 1 : 3 was used as the extractant in dispersive liquid-liquid microextraction (DLLME) for the extraction and determination of vincristine in the plasma of children with leukemia prior to its analysis by high-performance liquid chromatography-ultraviolet detection (HPLC-UV). Under optimal experimental conditions, the method showed good linearity with a correlation coefficient (R 2) of 0.9986 in the linear range of 0.06-300 µg L-1, low limit of detection of 0.02 µg L-1 and acceptable extraction efficiency (EE) of 88.4%. In the final stage of the study, this proposed technique was successfully applied to determine vincristine in real plasma, and the obtained results demonstrated the ability of the synthesized DES to extract drugs from biological fluids.

Sensitive determination of methotrexate in plasma of children with acute leukemia using double-solvent supramolecular systemas a novel extractant for dispersive liquid-liquid microextraction.

Methotrexate, as a folate antagonist, is one of the first anti-neoplasm drugs offered and is still used as an effective drug in the treatment of various malignancies. Methotrexate has a narrow treatment index and is associated with numerous side effects.In thisresearch, for the first time a double-solvent supramolecular system (DSS) was developed as an extractant without disperser solvent for dispersive liquid-liquid microextraction (DLLME). DSS - DLLME was applied to the extraction of methotrexate in plasma of children with acute leukemiaprior to itsdetermination by high-performance liquid chromatography-ultraviolet detection (HPLC - UV). In the present method, two long normal chain alcohols are mixed in a particular ratio, and then it is injected into the sample solution, which is on the magnetic stirrer. In this case, the mixture of the two alcohol changes to new supramolecular aggregate. This new supermolecule is used as an extractant, which has a higher extraction power than any of its components alone. Under the optimum conditions, the calibration graph was linear in the rage of 0.1-150 µg L-1 with detection limit of 0.03 µg L-1. Relative standard deviations (RSDs) including intra-day and inter-day of method based on7 replicate determinations of 100.0 µg L-1of methotrexate were 2.6% and 4.8%,respectively. The results proved that DSS - DLLME is a sensitive, very simple, inexpensive, environmental friendly, rapid and efficient method for the preconcentration of trace amount of drugs in biological samples.

Effects of alpha lipoic acid on iron overload, lipid profile and oxidative stress indices in ß-thalassemia major patients: A cross-over randomised controlled clinical trial.

AIMS: ß-Thalassemia major (ß-TM) is associated with iron overload, abnormal lipid levels and oxidative stress. Alpha lipoic acid (ALA) showed anti-oxidant and iron chelating properties, but its effect in ß-TM patients is unclear. We investigated the effects of ALA on iron levels, lipid profile and oxidative stress. METHODS: In this cross-over randomised clinical trial, 26 ß-TM patients were assigned to receive 600 mg/d ALA or placebo (corn starch), for 8 weeks with a 21-days washout period. Serum ferritin, total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), LDL-C/HDL-C, total antioxidant capacity, malondialdehyde (MDA) and MDA/LDL-C were assessed at baseline and the end of each intervention phase. RESULTS: Twenty-two patients completed the study. Serum ferritin (P = .004), MDA (P = .025) and MDA/LDL-C ratio (P =.002) were decreased and HDL-C (P =.035) increased significantly during ALA consumption. In comparison with placebo, ALA decreased the serum ferritin significantly (P = .02). Also, the changes in serum ferritin between ALA and placebo (-123.1 ± 40.0 vs -34.3 ± 21.0, P =.03) was significant in women subgroup. ALA had no significant effects on the other biomarkers. CONCLUSION: The results of this study indicated that supplementation with 600 mg/d ALA may decrease serum ferritin in ß-TM. Further studies are needed to confirm the findings.

Sensitive determination of deferasirox in blood of patients with thalassemia using dispersive liquid-liquid microextraction based on solidification of floating organic drop followed by HPLC-UV.

Deferasirox is an oral iron chelator that has been on the market since 2005 and has been a suitable replacement for injectable chelators. It is important to check the amount of this drug in the blood of patients due to side effects. In this study, a new dispersive liquid-liquid microextraction based on solidification of floating drganic drop (DLLME - SFO) was applied to the extraction of deferasirox in the blood of patients with thalassemia prior to its analysis by high-performance liquid chromatography-ultraviolet detection (HPLC - UV). In this method, two long alcohols of the normal chain are mixed in a particular ratio, and then it is injected into the sample solution, which is on the magnetic stirrer. In this case, the mixture of the two alcohol changes to new double-solvent aggregate. This new double-solvent system is used as an extractant, which has a higher extraction power than any of its components alone. Under the optimum conditions, the calibration graph was linear in the rage of 0.2-200 µg L-1 with detection limit of 0.06 µg L-1. Repeatability (intra-day) and reproducibility (inter-day) of method based on seven replicate measurements of 100.0 µg L-1of deferasirox were 3.8 % and 5.7 %, respectively. The results showed that DLLME - SFO is a very simple, inexpensive, environmental friendly, sensitive and efficient analytical method for the determination of trace amount of drugs in biological samples and suitable results were obtained.

Effects of Alpha-Lipoic Acid Supplementation on Cardiovascular Disease Risk Factors in ß-Thalassemia Major Patients: A Clinical Trial Crossover Study.

AIM: Thalassemia is one of the most common genetic diseases, and cardiovascular disease (CVD) has been considered as the leading cause of mortality in more than 50% of ß-thalassemia patients. The aim of this study was to determine the effects of alpha-lipoic acid (ALA) on CVD risk factors in ß-thalassemia major patients. METHODS: Twenty ß-thalassemia major patients participated in this randomized crossover clinical trial study. Participants were randomly assigned to ALA (600 mg/day) or placebo groups for two 8-wk interventions that were separated by a 3-wk washout period. The CVD risk factors including serum osteoprotegerin (OPG), homocysteine, lipoprotein-associated phospholipase A2 and trimethylamine N-oxide were measured at the beginning and the end of each intervention phase according to the standard protocol. RESULTS: Serum OPG reduced significantly in the ALA group in all participants (5.38 ± 2.79 to 3.27 ± 2.43 ng/mL, P= .003) and in the male subgroup (5.24 ± 2.56 to 3.13 ± 2.5 ng/mL, P= .015); this reduction was significant in comparison with the placebo group (P= .013). The changes in other CVD risk factors were not significant. CONCLUSION: The results of this study showed that after 8-wk of ALA consumption, the serum OPG reduced significantly in ß-thalassemia major patients. Therefore, controlling the serum OPG level with ALA consumption can be an important complementary therapeutic option to prevent the progression of CVD in ß-thalassemia major patients.

Determination of common organophosphorus pesticides in the blood of children with acute leukaemia using a double-solvent system as a novel extractant for dispersive liquid-liquid microextraction.

In this research, a new mode of dispersive liquid-liquid microextraction based on a double-solvent system (DLLME-DSS) was developed for the extraction and preconcentration of organophosphorus pesticides (OPPs) in the blood of children with acute leukaemia prior to determination by high-performance liquid chromatography-ultraviolet detection (HPLC-UV). In the present method, two long normal chain alcohols are mixed in a particular ratio, and then injected into the sample solution, which is magnetically stirred. In this case, the mixture of the two alcohols changes to a new aggregate extractant. This new double-solvent is used as an extractant, which has a higher extraction power than any of its components alone. Under the optimum conditions, the calibration graph was linear in the rage of 3-600 µg L-1 with detection limits of 1 to 2 µg L-1. Relative standard deviations (RSDs) including intra-day and inter-day of the method based on 7 replicate determinations of 100.0 µg L-1 for each analyte were in the range of 2.9-4.7% and 3.8-6.1%, respectively. The results proved that DLLME-DSS is a sensitive, very simple, inexpensive, environmentally friendly, rapid and efficient method for the preconcentration of trace amounts of OPPs in blood samples.

Optimization of a methodology for speciation of arsenic, selenium and mercury in blood samples based on the deep eutectic solvent.

In this research, a new liquid phase microextraction based on the solidification of deep eutectic solvent (LPME-SDES) has been developed for the speciation of As(III), As(V), Se(IV), Se(VI), Hg(II) and organic mercury (R-Hg) in the blood of children prior to their analysis by iridium-modified tube electrothermal atomic absorption spectrometry (ETAAS). •In this method, a green solvent consisting of Choline chloride and decanoic acid in the molar ratio of 1:2 was used as a green hydrophobic deep eutectic solvent for the extraction of complexed ions from real blood samples.•The DESs replace the toxic organic solvents apply for extraction and could be synthesize from cheap accessible chemicals.•Under the optimum conditions, the calibration graphs for As, Se and Hg were linear in the rage of 0.15-40, 0.05-5.0 and 0.30-60 µg l-1, respectively and, the detection limit of As, Se and Hg were 0.05, 0.015 and 0.10 µg l-1, respectively.

Speciation of organic/inorganic mercury and total mercury in blood samples using vortex assisted dispersive liquid-liquid microextraction based on the freezing of deep eutectic solvent followed by GFAAS.

In this research, a new vortex assisted dispersive liquid-liquid microextraction based on the freezing of deep eutectic solvent (VADLLME-FDES) has been developed for the determination of organic mercury (R-Hg) and inorganic mercury (Hg2+) in blood samples prior to their analysis by graphite furnace atomic absorption spectrometry (GFAAS). In this method, a green solvent consisting of 1-octyl-3-methylimidazolium chloride and 1-undecanol was used as an extraction solvent, yielding the advantages of material stability, low density, and a suitable freezing point near room temperature. Under the optimum conditions, enrichment factor is 112. The calibration graph is linear in the range of 0.30-60 µg L-1 and limit of detection (LOD) is 0.10 µg L-1. Repeatability and reproducibility of the method based on seven replicate measurements of 5.0 µg L-1 of Hg2+ in analyzed samples were 3.7% and 6.2%, respectively. The relative recoveries of blood samples which have been spiked with different levels of Hg2+ are 90-109%. A new deep eutectic solvent consists of two parts: [DMIM]Cl and 1-undecanol in the molar ratio of 1-2. The accuracy of the proposed procedure was also assessed by determining the concentration of the mercury in a standard reference material. All organic mercury (R-Hg) species were converted to Hg2+ and finally, the concentration of R-Hg is simply calculated by mathematically subtracting the concentrations of Hg2+ from the concentration of total mercury (t-Hg). The extraction methodology is simple, rapid, cheap and green since small amounts of non-toxic solvents are necessary.

Toward a complex system understanding of bipolar disorder: A chaotic model of abnormal circadian activity rhythms in euthymic bipolar disorder.

IMPORTANCE: In the absence of a comprehensive neural model to explain the underlying mechanisms of disturbed circadian function in bipolar disorder, mathematical modeling is a helpful tool. Here, circadian activity as a response to exogenous daily cycles is proposed to be the product of interactions between neuronal networks in cortical (cognitive processing) and subcortical (pacemaker) areas of the brain. OBJECTIVE: To investigate the dynamical aspects of the link between disturbed circadian activity rhythms and abnormalities of neurotransmitter functioning in frontal areas of the brain, we developed a novel mathematical model of a chaotic system which represents fluctuations in circadian activity in bipolar disorder as changes in the model's parameters. DESIGN, SETTING AND PARTICIPANTS: A novel map-based chaotic system was developed to capture disturbances in circadian activity across the two extreme mood states of bipolar disorder. The model uses chaos theory to characterize interplay between neurotransmitter functions and rhythm generation; it aims to illuminate key activity phenomenology in bipolar disorder, including prolonged sleep intervals, decreased total activity and attenuated amplitude of the diurnal activity rhythm. To test our new cortical-circadian mathematical model of bipolar disorder, we utilized previously collected locomotor activity data recorded from normal subjects and bipolar patients by wrist-worn actigraphs. RESULTS: All control parameters in the proposed model have an important role in replicating the different aspects of circadian activity rhythm generation in the brain. The model can successfully replicate deviations in sleep/wake time intervals corresponding to manic and depressive episodes of bipolar disorder, in which one of the excitatory or inhibitory pathways is abnormally dominant. CONCLUSIONS AND RELEVANCE: Although neuroimaging research has strongly implicated a reciprocal interaction between cortical and subcortical regions as pathogenic in bipolar disorder, this is the first model to mathematically represent this multilevel explanation of the phenomena of bipolar disorder.

Towards a complex system understanding of bipolar disorder: A map based model of a complex winnerless competition.

Bipolar disorder is characterized by repeated erratic episodes of mania and depression, which can be understood as pathological complex system behavior involving cognitive, affective and psychomotor disturbance. In order to illuminate dynamical aspects of the longitudinal course of the illness, we propose here a novel complex model based on the notion of competition between recurrent maps, which mathematically represent the dynamics of activation in excitatory (Glutamatergic) and inhibitory (GABAergic) pathways. We assume that manic and depressive states can be considered stable sub attractors of a dynamical system through which the mood trajectory moves. The model provides a theoretical framework which can account for a number of complex phenomena of bipolar disorder, including intermittent transition between the two poles of the disorder, rapid and ultra-rapid cycling of episodes and manicogenic effects of antidepressants.

Predicting the risk of squamous dysplasia and esophageal squamous cell carcinoma using minimum classification error method.

Early detection of squamous dysplasia and esophageal squamous cell carcinoma is of great importance. Adopting computer aided algorithms in predicting cancer risk using its risk factors can serve in limiting the clinical screenings to people with higher risks. In the present study, we show that the application of an advanced classification method, the Minimum Classification Error, could considerably enhance the classification performance in comparison to the logistic regression model and the variable structure fuzzy neural network, as the latest successful methods. The results yield the accuracy of 89.65% for esophageal squamous cell carcinoma, and 88.42% for squamous dysplasia risk prediction.

Periodic and chaotic dynamics in a map-based model of tumor-immune interaction.

Clinicians and oncologists believe that tumor growth has unpredictable dynamics. For this reason they encounter many difficulties in the treatment of cancer. Mathematical modeling is a great tool to improve our better understanding of the complicated biological system of tumor growth. Also, it can help to identify states of the disease and as a result help to predict later behaviors of the tumor. Having an insight into the future behaviors of the tumor can be very useful for the oncologists and clinicians to decide on the treatment method and dosage of the administered drug. This paper suggests that a suitable model for the tumor growth system should be a discrete model capable of exhibiting periodic and complex chaotic dynamics. This is the key feature of the proposed model. The model is validated here through experimental data and its potential dynamics are analyzed. The model can explain many biologically observed tumor states and dynamics, such as exponential growth, and periodic and chaotic behaviors in the steady states. The model shows that even an avascular tumor could become invasive under certain conditions.

A variable structure fuzzy neural network model of squamous dysplasia and esophageal squamous cell carcinoma based on a global chaotic optimization algorithm.

Identification of squamous dysplasia and esophageal squamous cell carcinoma (ESCC) is of great importance in prevention of cancer incidence. Computer aided algorithms can be very useful for identification of people with higher risks of squamous dysplasia, and ESCC. Such method can limit the clinical screenings to people with higher risks. Different regression methods have been used to predict ESCC and dysplasia. In this paper, a Fuzzy Neural Network (FNN) model is selected for ESCC and dysplasia prediction. The inputs to the classifier are the risk factors. Since the relation between risk factors in the tumor system has a complex nonlinear behavior, in comparison to most of ordinary data, the cost function of its model can have more local optimums. Thus the need for global optimization methods is more highlighted. The proposed method in this paper is a Chaotic Optimization Algorithm (COA) proceeding by the common Error Back Propagation (EBP) local method. Since the model has many parameters, we use a strategy to reduce the dependency among parameters caused by the chaotic series generator. This dependency was not considered in the previous COA methods. The algorithm is compared with logistic regression model as the latest successful methods of ESCC and dysplasia prediction. The results represent a more precise prediction with less mean and variance of error.

Predicting the spontaneous termination of atrial fibrillation based on poincare section in the electrocardiogram phase space.

Atrial fibrillation (AF) is a commonly encountered cardiac arrhythmia. Predicting the conditions under which AF terminates spontaneously is an important task that would bring great benefit to both patients and clinicians. In this study, a new method was proposed to predict spontaneous AF termination by employing the points of section (POS) coordinates along a Poincare section in the electrocardiogram (ECG) phase space. The AF Termination Database provided by PhysioNet for the Computers in Cardiology Challenge 2004 was applied in the present study. It includes one training dataset and two testing datasets, A and B. The present investigation was initiated by producing a two-dimensional reconstructed phase space (RPS) of the ECG. Then, a Poincare line was drawn in a direction that included the maximum point distribution in the RPS and also passed through the origin of the RPS coordinate system. Afterward, the coordinates of the RPS trajectory intersections with this Poincare line were extracted to capture the local behavior related to the arrhythmia under investigation. The POS corresponding to atrial activity were selected with regard to the fact that similar ECG morphologies such as P waves, which are corresponding to atrial activity, distribute in a specific region of the RPS. Thirteen features were extracted from the selected intersection points to quantify their distributions. To select the best feature subset, a genetic algorithm (GA), in combination with a support vector machine (SVM), was applied to the training dataset. Based on the selected features and trained SVM, the performance of the proposed method was evaluated using the testing datasets. The results showed that 86.67% of dataset A and 80% of dataset B were correctly classified. This classification accuracy is in the same range as or higher than that of recent studies in this area. These results show that the proposed method, in which no complicated QRST cancelation algorithm was used, has the potential to predict AF termination.