Phosphate group functionalized magnetic metal-organic framework nanocomposite for highly efficient removal of U(VI) from aqueous solution

Functionalization strategies of metal-organic frameworks for biomedical applications and treatment of emerging pollutants: A review

One of the representative coordination polymers, metal-organic frameworks (MOFs) material, is of hotspot interest in the multi field thanks to their unique structural characteristics and properties. As a novel hierarchical structural class, MOFs show diverse topologies, intrinsic behaviors, flexibility, etc. However, bare MOFs have less desirable biofunction, high humid sensitivity and instability in water, restraining their efficiencies in biomedical and environmental applications. Thus, a structural modification is required to address such drawbacks. Herein, we pinpoint new strategies in the synthesis and functionalization of MOFs to meet demanding requirements in in vitro tests, i.e., antibacterial face masks against corona virus infection and in wound healing and nanocarriers for drug delivery in anticancer. Regarding the treatment of wastewater containing emerging pollutants such as POPs, PFAS, and PPCPs, functionalized MOFs showed excellent performance with high efficiency and selectivity. Challenges in toxicity, vast database of clinical trials for biomedical tests and production cost can be still presented. MOFs-based composites can be, however, a bright candidate for reasonable replacement of traditional nanomaterials in biomedical and wastewater treatment applications.

Sugeno fuzzy inference system modeling and DFT calculations for the treatment of pesticide-laden water by newly developed arginine functionalized magnetic Mn-based metal organic framework

The uncontrolled utilization of pesticides poses a significant risk to the environment and human health, making its management essential. In this regard, a new arginine functionalized magnetic Mn-based metal-organic framework (Arg@m-Mn-MOF) was fabricated and assessed for the removal of cypermethrin (CYP) and chlorpyrifos (CHL) from aqueous system. The Arg@m-Mn-MOF was characterized by scanning electron microscopy, energy dispersive X-ray, Fourier transform infrared spectroscopy, X-ray diffraction, and Brunauer-Emmett-Teller analysis. Various parameters were optimized in a series of batch experiments and the following conditions were found optimal: pH: 4 and 5, contact time: 20 min, adsorbent dosage: 0.6 and 0.8 g L-1 with initial concentration: 10 mg L-1 and temperature: 298 K for CYP and CHL, respectively. The composite attained a maximum removal capacity of 44.84 and 71.42 mg g-1 for CYP and CHL, respectively. The elucidated data was strongly fitted to the pseudo-second-order model of kinetics (R2 > 0.98) and Langmuir isotherm (R2 > 0.98). Based upon 350 experimental datasets obtained from batch studies and interpolated data, the adsorption capacity of the adsorbent was elucidated with R2 > 0.97 (CHL) and > 0.91 (CYP). The adsorption energy (- 11.67 kcal mol-1) calculated by Gaussian software suggests a good interaction between arginine and CHL through H-bonding. The present study's findings suggested the prepared Arg@m-Mn-MOF as a promising adsorbent for the efficient removal of pesticides from agriculture runoff.

Direct Assembly of Metal-Phenolic Network Nanoparticles for Biomedical Applications

Coordination assembly offers a versatile means to developing advanced materials for various applications. However, current strategies for assembling metal-organic networks into nanoparticles (NPs) often face challenges such as the use of toxic organic solvents, cytotoxicity because of synthetic organic ligands, and complex synthesis procedures. Herein, we directly assemble metal-organic networks into NPs using metal ions and polyphenols (i.e., metal-phenolic networks (MPNs)) in aqueous solutions without templating or seeding agents. We demonstrate the role of buffers (e.g., phosphate buffer) in governing NP formation and the engineering of the NP physicochemical properties (e.g., tunable sizes from 50 to 270 nm) by altering the assembly conditions. A library of MPN NPs is prepared using natural polyphenols and various metal ions. Diverse functional cargos, including anticancer drugs and proteins with different molecular weights and isoelectric points, are readily loaded within the NPs for various applications (e.g., biocatalysis, therapeutic delivery) by direct mixing, without surface modification, owing to the strong affinity of polyphenols to various guest molecules. This study provides insights into the assembly mechanism of metal-organic complexes into NPs and offers a simple strategy to engineer nanosized materials with desired properties for diverse biotechnological applications.

Integrating functional data analysis with case-based reasoning for hypertension prognosis and diagnosis based on real-world electronic health records

BACKGROUND

Hypertension is the fifth chronic disease causing death worldwide. The early prognosis and diagnosis are critical in the hypertension care process. Inspired by human philosophy, CBR is an empirical knowledge reasoning method for early detection and intervention of hypertension by only reusing electronic health records. However, the traditional similarity calculation method often ignores the internal characteristics and potential information of medical examination data.

METHODS

In this paper, we first calculate the weights of input attributes by a random forest algorithm. Then, the risk value of hypertension from each medical examination can be evaluated according to the input data and the attribute weights. By fitting the risk values into a risk curve of hypertension, we calculate the similarity between different community residents, and obtain the most similar case according to the similarity. Finally, the diagnosis and treatment protocol of the new case can be given.

RESULTS

The experiment data comes from the medical examination of Tianqiao Community (Tongling City, Anhui Province, China) from 2012 to 2021. It contains 4143 community residents and 43,676 medical examination records. We first discuss the effect of the influence factor and the decay factor on similarity calculation. Then we evaluate the performance of the proposed FDA-CBR algorithm against the GRA-CBR algorithm and the CS-CBR algorithm. The experimental results demonstrate that the proposed algorithm is highly efficient and accurate.

CONCLUSIONS

The experiment results show that the proposed FDA-CBR algorithm can effectively describe the variation tendency of the risk value and always find the most similar case. The accuracy of FDA-CBR algorithm is higher than GRA-CBR algorithm and CS-CBR algorithm, increasing by 9.94 and 16.41%, respectively.

Synthesis of core-shell magnetic metal organic frameworks composite for efficient uranium (VI) removal

The combination of magnetic nanoparticles and metal-organic frameworks (MOFs) has demonstrated their prospective for pollutant sequestration. In this work, Fe3O4@SiO2@UiO-66 core-shell magnetic microspheres were synthesized and used for the removal...