Machine learning-driven prediction of phosphorus removal performance of metal-modified biochar and optimization of preparation processes considering water quality management objectives.

Developing an optimized and targeted design approach for metal-modified biochar based on water quality conditions and management is achievable through machine learning. This study leveraged machine learning to analyze experimental data on phosphate adsorption by metal-modified biochar from literature published in Web of Science. Using six machine learning models, the phosphate adsorption capacity of biochar and residual phosphate concentration were predicted. After hyperparameter optimization, the gradient boosting model exhibited superior training performance (R2 > 0.96). Metal load quantity, solid-liquid ratio, and pH were key factors influencing adsorption performance. Optimal preparation parameters indicated that Mg-modified biochar achieved the highest adsorption capacity (387-396 mg/g), while La-modified biochar displayed the lowest residual phosphate concentration (0 mg/L). The results of verification experiments based on optimized process parameters closely aligned with model predictions. This study introduces a new machine learning-based approach for tailoring biochar preparation processes considering different water quality management objectives.

B-site metal modulation of phosphate adsorption properties and mechanism of LaBO3 (B = Fe, Al and Mn) perovskites.

La-based adsorbents are widely used for controlling phosphate concentration in water bodies. In order to explore the effect of different B-site metals regulating La-based perovskites on phosphate adsorption, three La-based perovskites (LaBO3, B = Fe, Al, and Mn) were prepared using the citric acid sol-gel method. Adsorption experiments showed that LaFeO3 exhibited the highest adsorption capacity for phosphate, which was 2.7 and 5 times higher than those of LaAlO3 and LaMnO3, respectively. The characterization results demonstrated that LaFeO3 has dispersed particles exhibiting larger pore size and more pores than LaAlO3 and LaMnO3. Spectroscopy analysis and density functional theory calculation results showed that different B-positions cause a change in the type of perovskite crystals. Among them, the differences between lattice oxygen consumption ratio, zeta potential and adsorption energy are the main reasons for the differences in adsorption capacity. In addition, the adsorption of phosphate by La-based perovskites were well fitted with Langmuir isotherm and pursues the pseudo-second-order kinetic models. The maximum adsorption capacities were 33.51, 12.31 and 6.61 mg/g for LaFeO3, LaAlO3 and LaMnO3, respectively. The adsorption mechanism was mainly based on inner-sphere complexation and electrostatic attraction. This study provides an explanation for the influence of different B sites on phosphate adsorption by perovskite.

Dosimetry of a (90)Y-hydroxide liquid brachytherapy treatment approach to canine osteosarcoma using PET/CT.

A new treatment strategy based on direct injections of (90)Y-hydroxide into the tumor bed in dogs with osteosarcoma was studied. Direct injections of the radiopharmaceutical into the tumor bed were made according to a pretreatment plan established using (18)F-FDG images. Using a special drill, cannulas were inserted going through tissue, tumor and bone. Using these cannulas, direct injections of the radiopharmaceutical were made. The in vivo biodistribution of (90)Y-hydroxide and the anatomical tumor bed were imaged using a time-of-flight (TOF) PET/CT scanner. The material properties of the tissues were estimated from corresponding CT numbers using an electron-density calibration. Radiation absorbed dose estimates were calculated using Monte Carlo methods where the biodistribution of the pharmaceutical from PET images was sampled using a collapsing 3-D rejection technique. Dose distributions in the tumor bed and surrounding tissues were calculated, showing significant heterogeneity with multiple hot spots at injection sites. Dose volume histograms showed that approximately 33.9% of bone and tumor and 70.2% of bone marrow and trabecular bone received an absorbed dose over 200Gy; approximately 3.2% of bone and tumor and 31.0% of bone marrow and trabecular bone received a total dose of over 1000Gy.

Changes in biophysical parameters of plasma membranes influence cisplatin resistance of sensitive and resistant epidermal carcinoma cells.

The mechanism of resistance of cancer cells to the anticancer drug cisplatin is not fully understood. Using cisplatin-sensitive KB-3-1 and -resistant KCP-20 cells, we found that the resistant cells have higher membrane potential, as determined by membrane potential sensing oxonol dye. Electron spin resonance and fluorescence polarization studies revealed that the resistant cells have more "fluid" plasma membranes than the sensitive cells. Because of this observed difference in membrane "fluidity," we attempted modification of the plasma membrane fluidity by the incorporation of heptadecanoic acid into KB-3-1 and KCP-20 cell membranes. We found that such treatment resulted in increased heptadecanoic acid content and increased fluidity in the plasma membranes of both cell types, and also resulted in increased cisplatin resistance in the KCP-20 cells. This finding is in accord with our results, which showed that the cisplatin-resistant KCP-20 cells have more fluid membranes than the cisplatin-sensitive KB-3-1 cells. It remains to be determined whether the observed differences in biophysical status and/or fatty acid composition alone, or the secondary effect of these differences on the structure or function of some transmembrane protein(s), is the reason for increased cisplatin resistance.