Ionized acrylamide-based copolymer / terpolymer hydrogels for recovery of positive and negative heavy metal ions.

In this study, we explored the effective capture of both cations and anions onto a single adsorbent. Acrylamide (AAm) served as the polymer backbone, onto which co-monomers sodium p-styrenesulfonate (SS) and N,N-dimethylaminopropyl acrylamide (DMAPAA) were grafted, creating ionized polymer hydrogel adsorbents. These adsorbents were engineered for the synergistic separation and recovery of heavy metal cations and anions from concentrated solutions, focusing specifically on industrially significant ions such as Ni2+-, Cu2+, Zn2+ and (Cr2O7)2-. The adsorption and desorption behaviors of the AAm terpolymer hydrogels were investigated across various pH solutions, considering the competition and concentrations of these specific metal ions. Moreover, the study delved into the effects of the internal pH environment within the hydrogel adsorbents, determining its impact on the type of metal adsorbed and the adsorption capacity. Our findings indicated that the adsorption of cations was enhanced with a higher proportion of SS relative to DMAPAA in the hydrogel. In contrast, significant anion capture occurred when the concentration of DMAPAA exceeded that of SS. However, equal ratios of SS and DMAPAA led to a noticeable reduction in the adsorption of both types of substrates, attributed to the counteractive nature of these co-monomers. To enhance the adsorption efficiency, it may be necessary to consider methods for micro-scale separation of the two types of monomers. Additionally, the adsorption capacity was observed to be directly proportional to the swelling capacity of the hydrogels. For complete desorption and separation of the cations and anions from the adsorbent, the application of concentrated NaOH solutions followed by HNO3 was found to be essential. Given the varying concentrations of cation and anion pollutants, often present in heavy metal factory effluents, it is crucial to fine-tune the ratios of DMAPAA and SS during the synthesis process. This adjustment ensures optimized efficiency in the decontamination and recovery of these significant heavy metal ions.

＜Editors' Choice＞ Pattern of THK 5351 retention in normal aging involves core regions of resting state networks associated with higher cognitive function.

We aimed to elucidate the distribution pattern of the positron emission tomography probe [18F]THK 5351, a marker for astrogliosis and tau accumulation, in healthy aging. We also assessed the relationship between THK5351 retention and resting state networks. We enrolled 62 healthy participants in this study. All participants underwent magnetic resonance imaging/positron emission tomography scanning consisting of T1-weighted images, resting state functional magnetic resonance imaging, Pittsburgh Compound-B and THK positron emission tomography. The preprocessed THK images were entered into a scaled subprofile modeling/principal component analysis to extract THK distribution patterns. Using the most significant THK pattern, we generated regions of interest, and performed seed-based functional connectivity analyses. We also evaluated the functional connectivity overlap ratio to identify regions with high between-network connectivity. The most significant THK distributions were observed in the medial prefrontal cortex and bilateral putamen. The seed regions of interest in the medial prefrontal cortex had a functional connectivity map that significantly overlapped with regions of the dorsal default mode network. The seed regions of interest in the putamen showed strong overlap with the basal ganglia and anterior salience networks. The functional connectivity overlap ratio also showed that three peak regions had the characteristics of connector hubs. We have identified an age-related spatial distribution of THK in the medial prefrontal cortex and basal ganglia in normal aging. Interestingly, the distribution's peaks are located in regions of connector hubs that are strongly connected to large-scale resting state networks associated with higher cognitive function.