Chiral Linker Installation in a Metal-Organic Framework for Enantioselective Luminescent Sensing.

Linker installation is a potent strategy for integrating specific properties and functionalities into metal-organic frameworks (MOFs). This method enhances the structural diversity of frameworks and enables the precise construction of robust structures, complementing the conventional postsynthetic modification approaches, by fully leveraging open metal sites and active organic linkers at targeting locations. Herein, we demonstrated an insertion of a d-camphorate linker into a flexible Zr-based MOF, PCN-700, through linker installation. The resultant homochiral MOF not only exhibits remarkable stability but also functions as a highly efficient luminescent material for enantioselective sensing. Competitive absorption and energy/electron transfer processes contribute to the sensing performance, while the difference in binding affinities dominates the enantioselectivity. This work presents a straightforward route to crafting stable homochiral MOFs for enantioselective sensing.

Confinement of p-Xylene in the Pores of a Bilanthanide Metal-Organic Framework for Highly Selective Recognition.

The rapid and accurate sensing of p-xylene, an essential raw material with a multi-billion-dollar market, in xylene mixture is of great significance in industry; however, the highly similar molecular structures, energy levels, and spectral characteristics of xylene isomers make the selective recognition extremely challenging. Metal-organic frameworks (MOFs) exhibiting tailorable pores and potential binding sites provide prospects for xylene sensing but a comprehensive understanding of the pore effect is still elusive, primarily due to the intricacies involved in the sensing process. Herein, we reported a robust bilanthanide MOF NKU-999-EuTb with precisely engineered pores to accommodate p-xylene, of which the binding sites were confirmed by single crystal X-ray diffraction and dynamic magnetic susceptibilities. NKU-999-EuTb exhibits high-performance in selective recognition for p-xylene towards its isomers. Through a systematical study, it was revealed that absorbing p-xylene into the pores governs the sensing performance. This work provides insights for developing advanced sensing materials for complex isomers.

Boosting the Lithium-Ion Transport Kinetics of Sn-Based Coordination Polymers through Ligand Aromaticity Manipulation.

Tin-based compounds are promising anode materials for lithium-ion batteries owing to their low charge/discharge voltage and high theoretical capacity but are plagued by both huge volume expansion during cycling and complex synthetic procedures. Constructing a coordination network between Sn and the lithium-active organic matrix can effectively relieve the volume expansion and increase the lithium storage active site utilization. Herein, we report a facile method to prepare two one-dimensional Sn-based coordination polymers [Sn(Hcta)]n (1) and [Sn(Hbtc)]n (2) (H3cta = 1,3,5-cyclohexanetricarboxylic acid, H3btc = 1,3,5-benzenetricarboxylic acid) for lithium storage, which differ only in the aromaticity of the ligand. 2 with an aromatic ligand provided a reversible capacity of 833 mAh g-1 at 200 mA g-1 over 160 cycles, higher than that of 1 without an aromatic ligand due to the quick charge transfer. The reversible lithium storage reactions of metal centers and organic ligands and the volume expansion rate of Sn-based coordination polymers during cycling were studied by detailed characterization and density functional theory (DFT) calculations. This research revealed that the structural factor of ligand aromaticity in these Sn-based coordination polymers boosted the utilization of active sites and rapid charge transfer, offering a coordination chemistry strategy for the design and synthesis of advanced anode materials.

Cage-Based Metal-Organic Framework as an Artificial Energy Receptor for Highly Sensitive Detection of Serotonin.

Artificial synthetic receptors toward functional biomolecules can serve as models to provide insights into understanding the high binding affinity of biological receptors to biomolecules for revealing their law of life activities. The exploration of serotonin receptors, which can guide drug design or count as diagnostic reagents for patients with carcinoid tumors, is of great value for clinical medicine but is highly challenging due to complex biological analysis. Herein, we report a cage-based metal-organic framework (NKU-67-Eu) as an artificial chemical receptor with well-matched energy levels for serotonin. The energy transfer back from the analyte to the framework enables NKU-67-Eu to recognize serotonin with excellent neurotransmitter selectivity in human plasma and an ultra-low limit of detection of 36 nM. Point-of-care visual detection is further realized by the colorimetry change of NKU-67-Eu toward serotonin with a smartphone camera.

Solvent-Free Synthesis of C=N Linked Two-Dimensional Covalent Organic Frameworks.

Covalent organic frameworks (COFs) are an emerging class of porous crystalline polymers with well-defined structures and tunable functionalities, which have fascinating applications in a wide range of fields. However, the synthetic procedures of COFs are mainly confined to the solvothermal synthesis method which usually requires harsh experimental conditions. In this work, an effective solvent-free synthesis method to construct a series of two-dimensional (2D) COFs including imine-linked, azine-linked, ß-ketoenamine-linked, which avoids the complicated solvent screening process and most of the disadvantages of solvothermal methods is developed. The crystallinity and porosity of these COFs are comparable to those prepared by traditional solvothermal routes. What's more, the advantages of the solvent-free method enable the production of gram-scale of those 2D COFs through a one-pot reaction, demonstrating high industrial application potentials.

An Efficient, Multiplexed Strategy for Instant Detection of Bacterial Biomarker by a Lanthanide-Organic Material.

Water contamination is a highly critical issue owing to its strong relationship to human health. In addition to chemical pollutants, microorganisms such as multiresistant pathogenic bacteria have received significant attention from the World Health Organization. The main problem associated with monitoring pathogenic bacteria in water is the interference from concomitant species and their low concentrations. To address this problem, we synthesized a bilanthanide-organic material as an efficient luminescence sensor for the detection of Pseudomonas aeruginosa, a representative bacterium, via its two unique biomarkers: 1-hydroxyphenazine (1-HX) and 2-aminoacetophenone (2-AA). This multiplexed sensing approach overcomes a common issue encountered by single-marker luminescence sensors that may report false positives due to coexisting species in the complex environment. High sensitivities and low limits of detection for 1-HX and 2-AA were obtained with very fast response time. The key structural factors governing the high-performance sensing function were revealed. This work provides an alternative route for the effortless and instant detection of bacterial biomarkers in water.

Medical Image Authentication Method Based on the Wavelet Packet and Energy Entropy.

The transmission of digital medical information is affected by data compression, noise, scaling, labeling, and other factors. At the same time, medical data may be illegally copied and maliciously tampered with without authorization. Therefore, the copyright protection and integrity authentication of medical information are worthy of attention. In this paper, based on the wavelet packet and energy entropy, a new method of medical image authentication is designed. The proposed method uses the sliding window to measure the energy of the detail information. In the time-frequency data distribution, the local details of the data are mined. The complexity of energy is quantitatively described to highlight the valuable information. Based on the energy weight, the local energy entropy is constructed and normalized. The adjusted entropy value is used as the feature vector of the authentication information. A series of experiments show that the authentication method has good robustness against shearing attacks, median filtering, contrast enhancement, brightness enhancement, salt-and-pepper noise, Gaussian noise, multiplicative noise, image rotation, scaling attacks, sharpening, JPEG compression, and other attacks.

Modulation of Z-Scheme Heterojunction Interface between Ultrathin C3N5 Nanosheets and Metal-Organic Framework for Boosting Photocatalysis.

Fabricating heterojunction photocatalysts for H2 production is promising for the development of clean energy. For boosting the photocatalytic activity, modulating the heterojunction interface can facilitate the electron-hole separation and solar energy utilization, but it is highly challenging in synthesis. In this work, by facilely exfoliating the bulk C3N5, ultrathin C3N5 nanosheets (N-CN) with large surface area, improved light absorption, and efficient charge transport were synthesized and further applied to the construction of NH2-UiO-66/N-CN heterojunctions. The optimized NH2-UiO-66/N-CN-2 exhibits high hydrogen evolution rate and cycling stability with Pt as the cocatalyst. Combined with the experimental results, the density functional theory calculation reveals that the high photocatalytic performance is attributed to the promoted photogenerated carrier transfer by the formation of well-contacted and stable Z-scheme heterojunction interface. This contribution renders an insight into the modulation of the heterojunction interface for enhancing the activity of MOF-based photocatalysts.

Fast Detection of Entacapone by a Lanthanide-Organic Framework with Rhombic Channels.

Entacapone (ENT) is a powerful catechol-O-methyl transferase inhibitor that is used for the diagnosis and treatment of Parkinson's syndrome, but the amount used must be well controlled to avoid overtreatment and side effect. Fast and selective detection of ENT needs well-matched energy levels and well-designed sensor-ENT interaction which is highly challenging. In this work, a water stable europium-based metal-organic framework (Eu-TDA) was synthesized to detect ENT by luminescence with excellent reusability and selectivity in the presence of main coexisting and interference species of plasma with a limit of detection of 5.01 µM. The experimental results showed that the luminescence of Eu-TDA can be effectively quenched by ENT via well-designed photoinduced electron transfer mechanism and internal filtration effect mechanism in the system.

Risk Identification of Bronchopulmonary Dysplasia in Premature Infants Based on Machine Learning.

Bronchopulmonary dysplasia (BPD) is one of the most common complications in premature infants. This disease is caused by long-time use of supplemental oxygen, which seriously affects the lung function of the child and imposes a heavy burden on the family and society. This research aims to adopt the method of ensemble learning in machine learning, combining the Boruta algorithm and the random forest algorithm to determine the predictors of premature infants with BPD and establish a predictive model to help clinicians to conduct an optimal treatment plan. Data were collected from clinical records of 996 premature infants treated in the neonatology department of Liuzhou Maternal and Child Health Hospital in Western China. In this study, premature infants with congenital anomaly, premature infants who died, and premature infants with incomplete data before the diagnosis of BPD were excluded from the data set. After exclusion, we included 648 premature infants in the study. The Boruta algorithm and 10-fold cross-validation were used for feature selection in this study. Six variables were finally selected from the 26 variables, and the random forest model was established. The area under the curve (AUC) of the model was as high as 0.929 with excellent predictive performance. The use of machine learning methods can help clinicians predict the disease so as to formulate the best treatment plan.

A Europium-Organic Framework Sensing Material for 2-Aminoacetophenone, a Bacterial Biomarker in Water.

2-Aminoacetophenone (2-AA) is a metabolite produced in large quantities by the pathogenic bacteria Pseudomonas aeruginosa (PA), which is a biomarker for PA in water. State-of-the-art analytical techniques to detect PA usually require expensive instruments and a long analysis time which are not suitable for real-time water quality monitoring, especially for high-quality drinking water. Herein, we reported the application of a europium metal-organic framework (Eu-MOF) as a luminescent sensing material, which provides a facile, environmentally friendly and low-cost way for the fast detection of PA in water. Eu-MOF shows a high sensitivity toward 2-AA with a KSV value of 3.563 × 104 M-1, rapid luminescence response in 12 s and high-selectivity and anti-interference ability with the existence of common detection indexes in drinking water owing to the good match of the energy levels of Eu-MOF and 2-AA. A systematical optimization of the sensing conditions to enhance the sensing function of Eu-MOF for 2-AA was discussed in detail, to give fundamentals for the rational design of MOF-based sensing materials.