Radiation pneumonia predictive model for radiotherapy in esophageal carcinoma patients.

BACKGROUND: The machine learning models with dose factors and the deep learning models with dose distribution matrix have been used to building lung toxics models for radiotherapy and achieve promising results. However, few studies have integrated clinical features into deep learning models. This study aimed to explore the role of three-dimension dose distribution and clinical features in predicting radiation pneumonitis (RP) in esophageal cancer patients after radiotherapy and designed a new hybrid deep learning network to predict the incidence of RP. METHODS: A total of 105 esophageal cancer patients previously treated with radiotherapy were enrolled in this study. The three-dimension (3D) dose distributions within the lung were extracted from the treatment planning system, converted into 3D matrixes and used as inputs to predict RP with ResNet. In total, 15 clinical factors were normalized and converted into one-dimension (1D) matrixes. A new prediction model (HybridNet) was then built based on a hybrid deep learning network, which combined 3D ResNet18 and 1D convolution layers. Machine learning-based prediction models, which use the traditional dosiomic factors with and without the clinical factors as inputs, were also constructed and their predictive performance compared with that of HybridNet using tenfold cross validation. Accuracy and area under the receiver operator characteristic curve (AUC) were used to evaluate the model effect. DeLong test was used to compare the prediction results of the models. RESULTS: The deep learning-based model achieved superior prediction results compared with machine learning-based models. ResNet performed best in the group that only considered dose factors (accuracy, 0.78 ± 0.05; AUC, 0.82 ± 0.25), whereas HybridNet performed best in the group that considered both dose factors and clinical factors (accuracy, 0.85 ± 0.13; AUC, 0.91 ± 0.09). HybridNet had higher accuracy than that of Resnet (p = 0.009). CONCLUSION: Based on prediction results, the proposed HybridNet model could predict RP in esophageal cancer patients after radiotherapy with significantly higher accuracy, suggesting its potential as a useful tool for clinical decision-making. This study demonstrated that the information in dose distribution is worth further exploration, and combining multiple types of features contributes to predict radiotherapy response.

Functionalization of melamine sponge for the efficient recovery of Pt(IV) from acid leachates.

The recovery of platinum from industrial waste is of critical importance. Usually, the recovery method is to dissolve the solid waste with acid to form a solution where platinum mainly exists in the form of Pt(IV). Therefore, it is urgent to efficiently and selectively adsorb Pt(IV) ions from acid leachates. In this study, a highly efficient adsorbent was developed by grafting of carboxyl and amine groups onto melamine sponge with alginate-Ca and polyethylenimine-glutaraldehyde (ML/ACPG). Combination of SEM, FTIR and XPS showed that the ML/ACPG sponge had a tree structure and the amino, carboxyl and hydroxyl groups were successfully introduced. Maximum adsorption capacity of ML/ACPG sponge reached up to 101.1 mg/L at pH of 1 (optimum initial pH value). The Pt(IV) ions were readily desorbed (within 60-80 min) using 0.1 M HCl + 0.025 M thiourea solution. Desorption efficiency remained higher than 83.3% while adsorption capacity decreased by less than 6.0% after 5 cycles operation. The ML/ACPG sponge was stable in 3 M of HNO3, NaCl after shaking for 72 h at 300 rpm with mass loss less than 2.5%. The mechanism of Pt(IV) adsorption onto ML/ACPG sponge mainly involved coordination by electrostatic attraction and carboxyl groups by protonated amine groups. The above results confirmed that the ML/ACPG sponge has a good practical application potential for Pt(IV) recovery from acid leachates.

Dosimetric advantages of robust optimization combined with flattening filter free in treating cancer of the left breast.

OBJECTIVE: By comparing the target dose distribution with or without the robust optimization, the dosimetric advantages of robust optimization and flattening filter free (FFF) in radiation therapy for postmastectomy cancer of the left breast was explored when part of the chest wall target was moved out in case of respiratory motion. MATERIALS AND METHODS: This is a retrospective study. The data of 21 postmastectomy patients with cancer of the left breast from 2019 to 2020 were retrospectively collected. The planned target volume (PTV) dose was prescribed 50 Gy/25 fractions and the treatment plans were designed using 6 MV FFF X ray and volumetric modulated arc therapy (VMAT) technology in RayStation treatment planning system (TPS), with and without robust optimization. The movement of the target area of the internal chest wall (0.50 cm) caused by respiratory movement was simulated by moving the isocenter of the beams. RESULTS: When the chest wall target moved outward, the PTV target area D98, D95, D2, conformity index (CI) and homogeneity index (HI) with robust optimization were better than those without robust optimization. The coverage rate of Planned Target Volume-Chest (PTV-T) V50 with robust optimization was significantly higher than that with no-robust optimization (P<0.001). Clinical target volume (CTV) V50 coverage with robust optimization was 14.49% higher than that with no-robust optimization. In terms of organ-at-risk parameters, the average spinal cord dose of the plan with robust optimization was 13.19% lower than that of the plan with no-robust optimization, and the Lung-L V5 of the plan with no-robust optimization was slightly (1.94%) lower than that of the plan with robust optimization. There was no significant difference in machine execution efficiency between the two groups (P>0.05). CONCLUSIONS: Robust optimization could be adopted in the postoperative radiotherapy planning for cancer in the left breast, for it ensures that the target dose coverage and the dose limit of organ-at-risk still meet the clinical requirements under condition of chest wall displacement caused by respiratory movement.

An ultrasound model for predicting recurrence of papillary thyroid carcinoma after complete endoscopic resection.

Introduction: Papillary thyroid cancer (PTC) is one of the most common malignancies involving the endocrine system. Aim: To explore the clinical value of ultrasound-based radiomics for predicting the recurrence of PTC after complete endoscopic resection. Material and methods: The general data of 361 PTC patients were collected. They were randomly assigned to the modeling group (n = 253) and the validation group (n = 108) according to the ratio of 7 : 3. In the modeling group, the PyRadiomics package was applied to extract radiomic features from preoperative ultrasound images, and least absolute shrinkage and selection operator (LASSO) was used to screen and to construct a radiomics score (Rad-score). Independent prognostic predictors were identified using the Cox proportional hazards model, and a nomogram prediction model was constructed by R software. Results: Using the LASSO regression model, 7 radiomic features were screened and then the Rad-score was calculated. Based on the Rad-score, modeling and validation groups were divided into low-, medium- and high-risk groups, and the 10-year recurrence-free survival rates were 94.7% vs. 95.9%, 83.6% vs. 80.0%, and 50.0% vs. 66.6%, respectively (p < 0.001). Multivariate analysis revealed that age, lymph node metastasis and Rad-score were independent predictors for recurrence-free survival (p < 0.05). Conclusions: The ultrasound-based radiomics score can effectively predict the postoperative recurrence-free survival in patients with PTC. The nomogram prediction model is superior to the AJCC staging system in terms of predictive accuracy and consistency.

Vibration Control of a Helicopter Rescue Simulator on a Flexible Base.

The vibration compensation control of a hovering helicopter rescue simulator mounted on a crane beam is studied in this research. A Stewart platform is used as the motion generator of the helicopter simulation cabin and the vibration compensation device of the beam, simultaneously. This study describes how the dynamic model of the Stewart platform with consideration of the beam vibration is established. To determine the interference of the Stewart platform motion control in the special application of a large component flexible base requiring large-scale movement, a hybrid vibration controller composed of a feed-forward compensation module and a PD (proportional-derivative) feedback control module is designed. The experimental results show that this method can effectively compensate for the beam vibration and improve the accuracy of the motion reproduction of a helicopter simulation cabin.

Activation of sodium persulfate by TiO2@MIL-101(Fe): Boosting the Fenton-like process by interfacial charge transfer.

Advanced oxidation processes based on sulfate radicals are considered as a promising approach for environmental remediation. In this study, TiO2@MIL-101(Fe) is successfully fabricated by a facile impregnation method and is used for sodium persulfate (SPS) activation. TiO2@MIL-101@SPS combines the advantages of photocatalysis and SPS activation, which shows high removal efficiency for nitrobenzene and methyl orange. In addition, the effect of multiple factors, including light source, SPS amount and catalyst amount, on nitrobenzene degradation have been investigated. Results show that the nitrobenzene degradation efficiency is up to 66.53 % while that of TOC removal is 32.21 % under 4-h visible light irradiation with 30 mg catalyst and 1.6 mM SPS. Moreover, LC-MS have been carried out to study the route of nitrobenzene degradation. Besides, ESR analysis reveals that both ●SO4- and ●OH radicals are generated sustainably under visible light irradiation, and more ●OH radicals can be detected owing to the synergic effect of photocatalysis and SPS activation. Interfacial charge transfer effect provides photoinduced electrons for the Fe3+/Fe2+ cycle in MIL-101(Fe), which boosts the SPS activation process, resulting in high photocatalytic activity.

Sharp loss: a new loss function for radiotherapy dose prediction based on fully convolutional networks.

BACKGROUND: Neural-network methods have been widely used for the prediction of dose distributions in radiotherapy. However, the prediction accuracy of existing methods may be degraded by the problem of dose imbalance. In this work, a new loss function is proposed to alleviate the dose imbalance and achieve more accurate prediction results. The U-Net architecture was employed to build a prediction model. Our study involved a total of 110 patients with left-breast cancer, who were previously treated by volumetric-modulated arc radiotherapy. The patient dataset was divided into training and test subsets of 100 and 10 cases, respectively. We proposed a novel 'sharp loss' function, and a parameter γ was used to adjust the loss properties. The mean square error (MSE) loss and the sharp loss with different γ values were tested and compared using the Wilcoxon signed-rank test. RESULTS: The sharp loss achieved superior dose prediction results compared to those of the MSE loss. The best performance with the MSE loss and the sharp loss was obtained when the parameter γ was set to 100. Specifically, the mean absolute difference values for the planning target volume were 318.87 ± 30.23 for the MSE loss versus 144.15 ± 16.27 for the sharp loss with γ = 100 (p < 0.05). The corresponding values for the ipsilateral lung, the heart, the contralateral lung, and the spinal cord were 278.99 ± 51.68 versus 198.75 ± 61.38 (p < 0.05), 216.99 ± 44.13 versus 144.86 ± 43.98 (p < 0.05), 125.96 ± 66.76 versus 111.86 ± 47.19 (p > 0.05), and 194.30 ± 14.51 versus 168.58 ± 25.97 (p < 0.05), respectively. CONCLUSIONS: The sharp loss function could significantly improve the accuracy of radiotherapy dose prediction.

Comparing of two dimensional and three dimensional fully convolutional networks for radiotherapy dose prediction in left-sided breast cancer.

Fully convolutional networks were developed for predicting optimal dose distributions for patients with left-sided breast cancer and compared the prediction accuracy between two-dimensional and three-dimensional networks. Sixty cases treated with volumetric modulated arc radiotherapy were analyzed. Among them, 50 cases were randomly chosen to conform the training set, and the remaining 10 were to construct the test set. Two U-Net fully convolutional networks predicted the dose distributions, with two-dimensional and three-dimensional convolution kernels, respectively. Computed tomography images, delineated regions of interest, or their combination were considered as input data. The accuracy of predicted results was evaluated against the clinical dose. Most types of input data retrieved a similar dose to the ground truth for organs at risk (p > 0.05). Overall, the two-dimensional model had higher performance than the three-dimensional model (p < 0.05). Moreover, the two-dimensional region of interest input provided the best prediction results regarding the planning target volume mean percentage difference (2.40 ± 0.18%), heart mean percentage difference (4.28 ± 2.02%), and the gamma index at 80% of the prescription dose are with tolerances of 3 mm and 3% (0.85 ± 0.03), whereas the two-dimensional combined input provided the best prediction regarding ipsilateral lung mean percentage difference (4.16 ± 1.48%), lung mean percentage difference (2.41 ± 0.95%), spinal cord mean percentage difference (0.67 ± 0.40%), and 80% Dice similarity coefficient (0.94 ± 0.01). Statistically, the two-dimensional combined inputs achieved higher prediction accuracy regarding 80% Dice similarity coefficient than the two-dimensional region of interest input (0.94 ± 0.01 vs 0.92 ± 0.01, p < 0.05). The two-dimensional data model retrieves higher performance than its three-dimensional counterpart for dose prediction, especially when using region of interest and combined inputs.

Recent advances in hybrid wet scrubbing techniques for NOx and SO2 removal: State of the art and future research.

Recently, the discharge of flue gas has become a global issue due to the rapid development in industrial and anthropogenic activities. Various dry and wet treatment approaches including conventional and hybrid hybrid wet scrubbing have been employing to combat against these toxic exhaust emissions. However, certain issues i.e., large energy consumption, generation of secondary pollutants, low regeneration of scrubbing liquid and high efficieny are hindering their practical applications on industrial level. Despite this, the hybrid wet scrubbing technique (advanced oxidation, ionic-liquids and solid engineered interface hybrid materials based techniques) is gaining great attention because of its low installation costs, simultaneous removal of multi-air pollutants and low energy requirements. However, the lack of understanding about the basic principles and fundamental requirements are great hurdles for its commercial scale application, which is aim of this review article. This review article highlights the recent developments, minimization of GHG, sustainable improvements for the regeneration of used catalyst via green and electron rich donors. It explains, various hybrid wet scrubbing techniques can perform well under mild condition with possible improvements such as development of stable, heterogeneous catalysts, fast and in-situ regeneration for large scale applications. Finally, it discussed recovery of resources i.e., N2O, NH3 and N2, the key challenges about several competitive side products and loss of catalytic activity over time to treat toxic gases via feasible solutions by hybrid wet scrubbing techniques.

Radiotherapy dose distribution prediction for breast cancer using deformable image registration.

BACKGROUND: Radiotherapy treatment planning dose prediction can be used to ensure plan quality and guide automatic plan. One of the dose prediction methods is incorporating historical treatment planning data into algorithms to estimate the dose-volume histogram (DVH) of organ for new patients. Although DVH is used extensively in treatment plan quality and radiotherapy prognosis evaluation, three-dimensional dose distribution can describe the radiation effects more explicitly. The purpose of this retrospective study was to predict the dose distribution of breast cancer radiotherapy by means of deformable registration into atlas images with historical treatment planning data that were considered to achieve expert level. The atlas cohort comprised 20 patients with left-sided breast cancer, previously treated by volumetric-modulated arc radiotherapy. The registration-based prediction technique was applied to 20 patients outside the atlas cohort. This study evaluated and compared three different approaches: registration to the most similar image from a dataset of individual atlas images (SIM), registration to all images from a database of individual atlas images with the average method (WEI_A), and the weighted method (WEI_F). The dose prediction performance of each strategy was quantified using nine metrics, including the region of interest dose error, 80% and 100% prescription area dice similarity coefficients (DSCs), and γ metrics. A Friedman test and a nonparametric exact Wilcoxon signed rank test were performed to compare the differences among groups. The clinical doses of all cases served as the gold standard. RESULTS: The WEI_F method could achieve superior dose prediction results to those of WEI_A. WEI_F outperformed SIM in the organ-at-risk mean absolute difference (MAD). When using the WEI_F method, the MAD values for the ipsilateral lung, heart, and whole lung were 197.9 ± 42.9, 166 ± 55.1, 122.3 ± 25.5, and 55.3 ± 42.2 cGy, respectively. Moreover, SIM exhibited superior prediction in the DSC and γ metrics. When using the SIM method, the means of the 80% and 100% prescription area DSCs, 33γ metric, and 55γ metric were 0.85 ± 0.05, 0.84 ± 0.05, 0.64 ± 0.13, and 0.84 ± 0.10, respectively. The plan target volume and spinal cord MAD when using SIM and WEI were 235.6 ± 158.4 cGy versus 227.4 ± 144.0 cGy ([Formula: see text]) and 61.4 ± 44.9 cGy versus 55.3 ± 42.2 cGy ([Formula: see text]), respectively. CONCLUSIONS: A predicted dose distribution that approximated the clinical plan could be generated using the methods presented in this study.

Three therapeutic regimens based on induction chemotherapy in locally advanced squamous cell carcinoma of the head and neck: a single center experience.

BACKGROUND: This study aimed to compare three different therapeutic models based on regional control and the outcome of locally advanced squamous cell carcinoma of the head and neck (SCCHN) after induction chemotherapy (ICT). METHODS: One hundred and twenty patients with locally advanced SCCHN were retrospectively reviewed and divided into three groups. Patients in Group A received induction chemotherapy + concurrent chemoradiotherapy (ICT + CCRT). Patients in Group B received induction chemotherapy + radical surgery + adjuvant radiotherapy with or without chemotherapy (ICT + Surgery + RT/CRT). Patients in Group C received induction chemotherapy + planned neck dissection + concurrent chemoradiotherapy (ICT + PND + CCRT). The clinicopathological characteristics, locoregional recurrence (LR), distant metastasis (DM), and overall survival (OS) were compared among them. RESULTS: The median follow-up time was 20 months. In Group A, Group B and Group C, the 3-year OS was 69.7%, 72.9%, and 65.5% respectively. The LR rate was 35.1%, 26.2%, and 42.9%, respectively. The DM rate was 10.5%, 31.0%, and 9.5%, respectively. There were no significant differences in OS and LR among three groups. The DM in Group B was significantly higher than that in Group A (P<0.05), and was probably higher than that in Group C (P=0.06). CONCLUSIONS: Locally advanced SCCHN has a poor prognosis, and the first treatment is critical. Individualized therapeutic regimen based on the response of ICT could be an ideal solution. As cervical metastatic lymph nodes are less sensitive to ICT than primary tumors, PND before radiation therapy might improve the regional control and throat function preservation. A multidisciplinary team (MDT) collaboration is important throughout the treatment process.

Radiation-Induced Sarcoma of the Head and Neck Following Radiotherapy for Nasopharyngeal Carcinoma: A Single Institutional Experience and Literature Review.

BACKGROUND AND OBJECTIVE: Radiotherapy (RT) is the primary treatment option for nasopharyngeal carcinoma (NPC), but it is associated with radiation-induced sarcomas (RISs). This study aims to investigate clinicopathological features and head and neck RIS prognosis after NPC RT. METHODS: The medical and radiological records of the NPC patients (n =14,074) referred to Zhejiang Cancer Hospital, Hang Zhou, China between January 1995 and December 2018 were retrospectively reviewed. Among them, 22 patients were determined to have RIS after RT for NPC. The clinicopathological data, diagnosis, treatment, and follow-up results of 22 patients with RIS were analyzed in this retrospective research. All 22 patients underwent surgery as the main treatment. The levels of Overall Survival (OS) were determined through the Log-rank test and Kaplan-Meier method. RESULTS: Among these patients, 13 were males and nine females with the male/female ratio of 1.44:1. The age during the primary RT of NPC ranged from 25 to 61 years old (median age: 37 years old). Patients' ages ranged from 33 to 73 years old (median age: 52.5 years old) when diagnosed with RIS. The latency period for development of the RIS was between 3 and 36 years (median: 8.5 years) after RT. In this cohort, R0 resection was achieved in 13 cases, R1 resection in five cases, and R2 resection in four cases. During the follow-up period ranged from 2 to 102 months (median 14 months), 15 patients had died of the disease. Kaplan-Meier method showed that the 2-year, 3-year, and the 5-year cumulative OS rate was 50.3, 43.2, and 14.4%, respectively. The median survival time was 34 months. Surgical resection with R0 resection achieves a significantly better prognosis (P = 0.012). Patients under the age of 37 years old at the time of initial RT had a relatively better prognosis (P = 0.035). CONCLUSIONS: Although the incidence of RIS after RT of NPC is generally low, the treatment of RIS is very difficult. The RISs are associated with poor overall prognosis. R0 resection can improve the prognosis thus it should be considered as the primary and optimal choice for the treatment of RIS.

Selenium(VI) and copper(II) adsorption using polyethyleneimine-based resins: Effect of glutaraldehyde crosslinking and storage condition.

This study synthesizes polyethyleneimine-glutaraldehyde (PEI-GA) resins using different amounts of GA to crosslink with a certain amount of PEI and compares these adsorbents for the adsorption of Cu(II) (cations) and Se(VI) (anions). Moreover, the stability of adsorption affinity of PEI-GA resins stored in open or sealed conditions is also studied. Results show that the amount of GA for PEI crosslinking does not affect the adsorption performance for Se(VI), especially when PEI/GA mass ratio is less than 2, while for Cu(II), the increase on GA amount decreases Cu(II) adsorption capacity. This difference is directly correlated to the change in the adsorption mechanism from electrostatic attraction to chelation. The primary and secondary amine groups on PEI can easily react with CO2 in the air to form carbamate, potentially affecting the adsorption performance of PEI. Results also indicate that the adsorption efficiency for Se(VI) is hardly affected by the storage condition, while that for Cu(II) decreases significantly after 20-day storage compared to the freshly prepared ones. In addition, all of the adsorbents can selectively remove Se(VI) from Se(VI)-As(V) system and Cu(II) from Pb(II)-Cu(II) system, indicating that the crosslinking has no significant influence on the selectivity.

New highly-percolating alginate-PEI membranes for efficient recovery of chromium from aqueous solutions.

Highly percolating membranes are prepared by the interaction of polyethylenimine and alginate (with glutaraldehyde crosslinking). SEM illustrates the macroporous structure of the material. The material is characterized by FTIR before and after chromate anions sorption. Batch-simulated continuous sorption experiments revealed that the maximum sorption occurred at pH 2 and the flow rate has limited effect on sorption efficiency. Uptake kinetics and sorption isotherms are well fitted by the pseudo-second-order rate and Sips equations, respectively. Maximum sorption is found close to 314 mg g-1. Competition effects from Ca(II), Cu(II), Cl-, NO3-, and SO42- are investigated to evaluate sorbent selectivity. The membranes are applied to remediate a simulate of Cr(VI) contaminated electroplating wastewater. Successive cycles of sorption and desorption show that the membranes maintain sorption capacity higher than 200 mg Cr g-1 for both Cr(VI) and total chromium for the first two cycles. These new highly percolating membranes have promising performances for Cr(VI) removal.

Evaluation of therapeutic efficacy with CytoSorter® circulating tumor cell-capture system in patients with locally advanced head and neck squamous cell carcinoma.

Objective: This study aimed to investigate the feasibility of utilizing CytoSorter® system to detect circulating tumor cells (CTCs) and clinical value of CTCs in patients with locally advanced head and neck squamous cell carcinoma (LAHNSCC). Methods: 31 patients with LAHNSCC, 12 healthy volunteers, and 6 patients with benign tumor serving as controls were enrolled in this study. CTCs were enriched with the CytoSorter®, a microfluidic based immune capture system. CTC detection was performed before and after induction chemotherapy, as well as after surgery and/or radiotherapy. Correlations between CTC enumerations at different time points and survival outcome and recurrence risk were evaluated. The correlation between CTCs and clinicopathological characteristics was appraised. Follow-up of patients continued until March 2019. Results: While CTCs were not found in the controls, they were detected in 24 of 31 LAHNSCC patients. CTCs could be used to distinguish diseased people from the healthy (P<0.0001). CTCs were statistically associated with patient age (P=0.037, >60 years old vs<60 years old) and lymph node metastasis (P= 0.034, N0N1 VS N2N3). Most patients had significantly reduced CTCs at the end of treatment. Patients with partial remission of tumor after induction therapy had more CTCs than those with complete remission of tumor. Patients with higher CTCs counts prior to treatment had higher chance of developing local recurrence of tumor after treatment (P=0.0187). Conclusion: CTCs were successfully isolated in LAHNSCC patients using CytoSorter® system with better sensibility. CTCs can be used to differentiate LAHNSCC patients from those with benign HNSCC tumor or healthy volunteers, and as markers to monitor patient's response to treatment and predict the local tumor recurrence after treatment. CTC detection at baseline has the greatest prognostic potency in LAHNSCC patients.

Algal Foams Applied in Fixed-Bed Process for Lead(II) Removal Using Recirculation or One-Pass Modes.

The incorporation of brown algae into biopolymer beads or foams for metal sorption has been previously reported. However, the direct use of these biomasses for preparing foams is a new approach. In this study, two kinds of porous foams were prepared by ionotropic gelation using algal biomass (AB, Laminaria digitata) or alginate (as the reference) and applied for Pb(II) sorption. These foams (manufactured as macroporous discs) were packed in filtration holders (simulating fixed-bed column) and the system was operated in either a recirculation or a one-pass mode. Sorption isotherms, uptake kinetics and sorbent reuse were studied in the recirculation mode (analogous to batch system). In the one-pass mode (continuous fixed-bed system), the influence of parameters such as flow rate, feed metal concentration and bed height were investigated on both sorption and desorption. In addition, the effect of Cu(II) on Pb(II) recovery from binary solutions was also studied in terms of both sorption and desorption. Sorption isotherms are well fitted by the Langmuir equation while the pseudo-second order rate equation described well both sorption and desorption kinetic profiles. The study of material regeneration confirms that the reuse of the foams was feasible with a small mass loss, even after 9 cycles. In the one-pass mode, for alginate foams, a slower flow rate led to a smaller saturation volume, while the effect of flow rate was less marked for AB foams. Competitive study suggests that the foams have a preference for Pb(II) over Cu(II) but cannot selectively remove Pb(II) from the binary solution.

Functionalization of Magnetic Chitosan Particles for the Sorption of U(VI), Cu(II) and Zn(II)-Hydrazide Derivative of Glycine-Grafted Chitosan.

A new magnetic functionalized derivative of chitosan is synthesized and characterized for the sorption of metal ions (environmental applications and metal valorization). The chemical modification of the glycine derivative of chitosan consists of: activation of the magnetic support with epichlorohydrin, followed by reaction with either glycine to produce the reference material (i.e., Gly sorbent) or glycine ester hydrochloride, followed by hydrazinolysis to synthesize the hydrazide functionalized sorbent (i.e., HGly sorbent). The materials are characterized by titration, elemental analysis, FTIR analysis (Fourrier-transform infrared spectrometry), TGA analysis (thermogravimetric analysis) and with SEM-EDX (scanning electron microscopy coupled to energy dispersive X-ray analysis). The sorption performances for U(VI), Cu(II), and Zn(II) are tested in batch systems. The sorption performances are compared for Gly and HGly taking into account the effect of pH, the uptake kinetics (fitted by the pseudo-second order rate equation), and the sorption isotherms (described by the Langmuir and the Sips equations). The sorption capacities of the modified sorbent reach up to 1.14 mmol U g-1, 1.69 mmol Cu g-1, and 0.85 mmol Zn g-1. In multi-metal solutions of equimolar concentration, the chemical modification changes the preferences for given metal ions. Metal ions are desorbed using 0.2 M HCl solutions and the sorbents are re-used for five cycles of sorption/desorption without significant loss in performances.

Praseodymium sorption on Laminaria digitata algal beads and foams.

Algal (Laminaria digitata) beads and algal foams have been prepared by a new synthesis mode and the sorbents were tested for praseodymium sorption in batch and fixed-bed like systems (recirculation or one-pass modes), respectively. Metal binding occurs through ion-exchange with Ca(II) ions used for ionotropic gelation of alginate contained in the algal biomass and eventually with protons. Sorption isotherms at pH 4 are described by the Langmuir and the Sips equations with maximum sorption capacities close to 110-120mgPrg-1. Uptake kinetics are fitted by the pseudo-second order reaction rate equation for both beads and foams; in the case of beads the Crank equation also gives good fit of experimental data. Metal is successfully desorbed using 2M HCl/0.05M CaCl2 solutions and the sorbent can be efficiently re-used for a minimum of 5 cycles with negligible decrease in sorption/desorption properties and appreciable concentrating effect (around 8-10 times the initial metal concentration). Tested in continuous mode, the algal foam shows typical breakthrough curves that are fitted by the Yan method; desorption is also efficient and allows under the best conditions to achieve a concentration factor close to 8.

Effect of competitive adsorption on zinc removal from aqueous solution and zinc smelting effluent by eucalyptus leaf-based magnetic biosorbent.

The objectives of this study were to investigate the competitive sorption behaviors and mechanisms of heavy metals onto ELMB, a novel eucalyptus-leaf-based magnetic biosorbent, and to study the potential application of ELMB in the treatment of actual zinc smelting effluent after a necessary pretreatment process. ELMB and ELMB-metals systems were characterized using several techniques. Competitive sorption of Zn2+ with Pb2+, Cu2+ and Cd2+ onto ELMB was studied by batch experiments and the used sorbent was separated under a magnetic field. The results show that the ELMB can be considered as paramagnetic material with various functional groups on its surface. The presence of Pb2+, Cu2+ and Cd2+ significantly decreases the sorption of Zn2+ in either the binary system or multimetal systems. The order of adsorption preference is Pb2+ > Cu2+ > Cd2+ > Zn2+ in multimetal systems and the sequence of competitive ability to zinc is: Pb2+ > Cu2+ > Cd2+. Non-competitive Langmuir multicomponent isotherm model fits to the adsorption data of Pb2+ and Cu2+ well in aqueous solution. The co-existent Ca2+ and SO42- decrease the removal efficiencies of heavy metals while the presence of Na+ and Cl- shows little effect in the multimetal solution. In the case of actual zinc smelting effluent, "pretreatment + ELMB sorption" is successfully applied to remove heavy metals and the contents of Zn2+ and its associated metals are well below discharge limits.

Modeling competitive sorption of lead and copper ions onto alginate and greenly prepared algal-based beads.

The binary sorption of Pb(II) and Cu(II) onto calcium alginate, algal biomass and algal/glutaraldehyde-crosslinked polyethyleneimine (PEI) composite beads was studied in the absence and presence of Ca(II). Different competitive models were compared for predicting the equilibrium data. Results show that all the sorbents have a significant preference for Pb(II) over Cu(II) in Pb-Cu system: the separation factors reach 14.1, 9.1 and 3.6 for alginate, algal biomass and algal/PEI beads, respectively. Kinetic studies confirm the occurrence of an ion-exchange mechanism between Pb(II) and Cu(II) as the sorption sites are progressively saturated. Competitive Sips model predicts well the sorption data for all the sorbents. In Pb-Cu-Ca system, the Cu(II) sorption by algal beads was negligible, while algal/PEI still maintained a significant sorption of Cu(II) sorption under these conditions.