Pharmaceutical pollution has emerged as a highly concerned issue due to its adverse effects. Elevated concentrations of pharmaceuticals in water should be regulated to satisfy the requirement for the ...provision of clean water. Metal-organic frameworks (MOFs) with high specific surface area, controllable porous structure, and facile modification can serve as promising adsorbents for the removal of pharmaceutical contaminants from water. In this review, a selected collection illustrating the reliable strategies and concepts to prepare the MOFs-based materials with superior water stability is described. In addition, recent progress on the adsorptive removal of pharmaceutical pollutant using burgeoning and functional MOFs is also summarized in terms of maximum capacity, equilibrium time, and regenerate ability. Meanwhile, to understand the adsorption mechanism, related interactions including coordination with unsaturated site, pore-filling effect, hydrogen bonding, electrostatic, and π-π stacking are further discussed. Finally, critical perspectives/assessment of future research emphasising on fabricating desirable MOFs and establishing structure-property relationships to facilitate capture performance are identified.
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•Metal−organic frameworks (MOFs) and their derivatives are attractive adsorbents for pharmaceuticals removal.•Strategies of design and preparation of water-stable MOFs are reviewed.•Recent advances in the utilization of MOFs and their derivatives for pharmaceuticals removal were described.•Critical future research perspectives in this field are provided.
Groundwater contaminant source identification is an endeavor task in highly developed areas that have been impacted by diverse natural processes and anthropogenic activities. In this study, ...groundwater samples from 84 wells in the pilot promoter region of the Yangtze River Delta integration demonstration zone in eastern China were collected and then analyzed for 17 groundwater quality parameters. The principal component analysis (PCA) method was utilized to recognize the natural and anthropogenic aspects impacting the groundwater quality; furthermore, the absolute principal component score-multiple linear regression (APCS-MLR) model was employed to quantify the contribution of potential sources to each groundwater quality parameter. The results demonstrated that natural hydro-chemical evolution, agricultural activities, domestic sewage, textile industrial effluent and other industrial activities were responsible for the status of groundwater quality in the study area. Meanwhile, the contribution of these five sources obtained by the APCS-MLR model were ranked as natural hydro-chemical evolution (18.89%) > textile industrial effluent (18.18%) > non-point source pollution from agricultural activities (17.08%) > other industrial activities (15.09%) > domestic sewage (4.19%). It is believed that this contaminant source apportionment result could provide a reliable basis to the local authorities for groundwater pollution management.
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•Thiol functionalized Magnetic COFs have been synthesized through a facile strategy.•The resulstant composite featuring high specific areas contains many accessible chelating ...sites.•The material exhibited superior capture ability toward Hg2+ with high selectivity.•The composites can be easily recycled for reuse without loss its adsorption ability.
Covalent organic frameworks (COFs) have attracted tremendous attention due to their excellent performance in wastewater remediation, but their practical application still suffers from various challenges. The development of highly-efficient magnetic COFs along with fast adsorption kinetic and high adsorption capacity is very promising. To achieve the purpose, thiol-functionalized magnetic covalent organic frameworks (M-COF-SH) with abundant accessible chelating sites were designed and synthesized by utilizing disulfide derivative as building blocks and subsequently cutting off the disulfide linkage. After the cutting process, the crystallinity, porosity, superparamagnetism of pristine M-COF are well maintained, and the resultant M-COF-SH turned out to be an effective and selective platform for Hg2+ capture from water. Impressively, the resulting composite exhibited a maximum adsorption capacity of Hg2+ as high as 383 mg g−1. In addition, it also displays a rapid kinetic, where the adsorption equilibrium can be achieved within 10 min. More importantly, there is no significant loss of its adsorption performance even after recycling 5 times. This work not only offers a reliable platform for wastewater remediation but also provides a conceptual guide to prepare functionalized M-COF composites which cannot be obtained through conventional approaches.
•Chitosan/MOF-SH is synthesized by incorporating MOF-SH into the network of chitosan matrix.•Chitosan/MOF-SH was effective for the capture of Pb2+ and Cd2+.•Co-existing ions have a little interfering ...effect on the determination.•The proposed method is of good accuracy for various certified reference materials.
In this work, a facile solid phase extraction (SPE) method was developed for the analysis of trace Pb2+ and Cd2+ by using chitosan/thiol modified metal–organic frameworks (CS/MOF-SH) composite as adsorbent followed by graphite furnace atomic absorption spectrometer (GF-AAS) detection. The potential influencing factors, such as solution pH, adsorbent dosage, and extraction time, were fully estimated. Under the optimized extraction conditions, the detection limits of Pb2+ and Cd2+ were 0.033 µg L−1 and 0.008 µg L−1, respectively. Compared to other studies, CS/MOF-SH not only possessed superior adsorption performance, but also had the advantages of ease of handling and recyclability. Encouragingly, the developed method was of high accuracy and could monitor trace Pb2+ and Cd2+ in various certified reference materials (rice, wheat and tea) with complicated matrices, demonstrating its practical potential for regular monitoring of trace heavy metal ions in real food samples.
•Magnetic covalent organic framework (MCOF) was prepared via a facile solvent-free approach.•MCOF was effective for the extraction of diclofenac sodium.•The proposed method exhibited a low limit of ...detection and superior linearity.•The established method is of superior accuracy for the determination of diclofenac sodium in milk.
A robust magnetic solid-phase extraction (MSPE) method based on magnetic covalent organic framework (MCOF) coupled with high-performance liquid chromatography (HPLC)-ultraviolet (UV)/mass spectrometry (MS) was proposed for the determination of trace diclofenac sodium (DS) in milk. The prepared MCOF exhibited high extraction efficiency, which can be attributed to its high specific surface area as well as strong π-π and hydrophobic interactions between MCOF and DS. In addition, the potential influencing factors, including sample volume, adsorbent dosage, extraction time, and elution parameters, were fully estimated. The experimental results demonstrated that the established method was sensitive for the quantification of DS with high accuracy. Remarkably, the detection limit of DS was found to be 10 ng/kg under the optimal conditions. More impressively, the developed method was successfully applied to monitor trace DS in milk, demonstrating its outstanding durability and practical potential as an appealing method to regular monitor trace pharmaceutical contaminants in real food samples.
•Hierarchical porous covalent organic framework was utilized for the preconcentration of sulfonamides (SAs).•COF foam exhibited superior extraction performance and good durability for SAs ...preconcentration.•The developed SPE-HPLC method achieved a wide linearity, low LODs, and good accuracy.•The analysis of SAs in meat samples were achieved with satisfactory recoveries (85.0-113.8%).
In this work, hierarchical porous covalent organic frameworks (HP-COFs) foam, named as HP-TpBD, was prepared by using 1,3,5-trimethylphloroglucinol (Tp) and benzidine (BD) as building blocks under the assistant of NaCl template. Its potential application as the sorbent for solid phase extraction (SPE) of sulfonamides (SAs) in meat products were explored by coupling with high performance liquid chromatography-mass spectrum (HPLC-MS) analysis. The key factors affecting extraction efficiency were well studied. Under the optimum conditions, the proposed method exhibited high preconcentration factors of 100, low limit of detection (0.10-0.23 μg/kg), and wide linear ranges (0.5-200 μg/kg). In addition, the determination of SAs in real samples were realized with satisfactory recoveries (82.8-119.9%), demonstrating the applicability of the proposed method. The easy operation, superior extraction affinity and good recycle performance demonstrated the resulting HP-COF foam is a promising adsorbent for the preconcentration of trace organic compounds from complex matrix.
•Magnetic covalent organic framework/grapheme oxide (MCOF/GO) was prepared.•MCOF/GO was effective for the extraction of oseltamivir.•The established method was adopted to analyze oseltamivir in ...fish.•The proposed method provided satisfactory linearity and limit of detection.
In this work, a magnetic covalent organic framework/graphene oxide composite (MCOF/GO) was rapidly synthesized and developed as a promising candidate for the magnetic solid-phase extraction (MSPE). Combined with HPLC-MS, an efficient and rapid analytical method was established for the determination of oseltamivir (OS) in aquatic products. The resultant composite not only exhibited superior extraction efficiency, but also possessed fast mass transfer kinetic, reducing the pretreatment time greatly. Under optimal conditions, the linear range of the proposed method for OS determination was found to be 0.1–10 μg/kg along with a satisfactory correlation coefficient (R2 = 0.997) and a low limit of detection (LOD, 0.035 μg/kg). Furthermore, the established method was utilized to determine OS in Carp, Yellow croaker, and Shrimp, where the recoveries ranged from 87% to 116%. These results demonstrate the splendid application potential of this method to detect antiviral drugs in actual aquatic products.
Food Recommendation System (FRS) assists individuals in making healthier dietary choices. However, current FRS uses collaborative filtering algorithms for one-step recommendations. Although these ...systems can recommend foods based on users’ historical preferences, they lack the adaptability to real-time changes in users’ health requirements and, as a result, the dynamic adjustment of recommendation strategies. This study introduces a groundbreaking approach by incorporating the dynamic and adaptive nature of reinforcement learning algorithms (RL) into FRS. The proposed multi-step recommendation framework, RecipeRL, leverages RL’s continuous decision-making and sustained interaction capabilities. To more accurately recommend foods aligned with user preferences, we introduce an effective method for expressing users’ real-time state through fused state representation. We also introduce an interactive environment to simulate authentic interactions between users and the recommendation system, enabling the system to handle multi-step recommendations. Our approach was evaluated using publicly available real-world datasets and compared to ten state-of-the-art methods. The results of the Top@10 analysis show that our method outperforms other algorithms significantly, achieving 94.68% and 95.67% for traditional Precision and the recommendation system metric NDCG, respectively. Our method also exhibits adaptability in scenarios where user preferences change, achieving 93.2% and 95.71%, respectively.
Covalent organic frameworks (COFs) have attracted tremendous attention due to their excellent performance in wastewater remediation, but their practical application still suffers from various ...challenges. The development of highly-efficient magnetic COFs along with fast adsorption kinetic and high adsorption capacity is very promising. To achieve the purpose, thiol-functionalized magnetic covalent organic frameworks (M-COF-SH) with abundant accessible chelating sites were designed and synthesized by utilizing disulfide derivative as building blocks and subsequently cutting off the disulfide linkage. After the cutting process, the crystallinity, porosity, superparamagnetism of pristine M-COF are well maintained, and the resultant M-COF-SH turned out to be an effective and selective platform for Hg
capture from water. Impressively, the resulting composite exhibited a maximum adsorption capacity of Hg
as high as 383 mg g
. In addition, it also displays a rapid kinetic, where the adsorption equilibrium can be achieved within 10 min. More importantly, there is no significant loss of its adsorption performance even after recycling 5 times. This work not only offers a reliable platform for wastewater remediation but also provides a conceptual guide to prepare functionalized M-COF composites which cannot be obtained through conventional approaches.
Type 1 diabetes mellitus (T1D) is characterized by insulin deficiency and
blood glucose (BG) control issues. The state-of-the-art solution for continuous
BG control is reinforcement learning (RL), ...where an agent can dynamically
adjust exogenous insulin doses in time to maintain BG levels within the target
range. However, due to the lack of action guidance, the agent often needs to
learn from randomized trials to understand misleading correlations between
exogenous insulin doses and BG levels, which can lead to instability and
unsafety. To address these challenges, we propose an introspective RL based on
Counterfactual Invertible Neural Networks (CINN). We use the pre-trained CINN
as a frozen introspective block of the RL agent, which integrates forward
prediction and counterfactual inference to guide the policy updates, promoting
more stable and safer BG control. Constructed based on interpretable causal
order, CINN employs bidirectional encoders with affine coupling layers to
ensure invertibility while using orthogonal weight normalization to enhance the
trainability, thereby ensuring the bidirectional differentiability of network
parameters. We experimentally validate the accuracy and generalization ability
of the pre-trained CINN in BG prediction and counterfactual inference for
action. Furthermore, our experimental results highlight the effectiveness of
pre-trained CINN in guiding RL policy updates for more accurate and safer BG
control.
