Anion-Afforded Functions of Ionic Metal-Organic Frameworks: Ionochromism, Anion Conduction, and Catalysis.

The exchangeable counterions in ionic metal-organic frameworks (IMOFs) provide facile and versatile handles to manipulate functions associated with the ionic guests themselves and host-guest interactions. However, anion-exchangeable stable IMOFs combining multiple anion-related functions are still undeveloped. In this work, a novel porous IMOF featuring unique self-penetration was constructed from an electron-deficient tris(pyridinium)-tricarboxylate zwitterionic ligand. The water-stable IMOF undergoes reversible and single-crystal-to-single-crystal anion exchange and shows selective and discriminative ionochromic behaviors toward electron-rich anions owing to donor-acceptor interactions. The IMOFs with different anions are good ionic conductors with low activation energy, the highest conductivity being observed with chloride. Furthermore, integrating Lewis acidic sites and nucleophilic guest anions in solid state, the IMOFs act as heterogeneous and recyclable catalysts to efficiently catalyze the cycloaddition of CO2 to epoxides without needing the use of halide cocatalysts. The catalytic activity is strongly dependent upon the guest anions, and the iodide shows the highest activity. The results demonstrate the great potential of developing IMOFs with various functions related to the guest ions included in the porous matrices.

Electroencephalogram-Based Motor Imagery Classification Using Deep Residual Convolutional Networks.

The classification of electroencephalogram (EEG) signals is of significant importance in brain-computer interface (BCI) systems. Aiming to achieve intelligent classification of motor imagery EEG types with high accuracy, a classification methodology using the wavelet packet decomposition (WPD) and the proposed deep residual convolutional networks (DRes-CNN) is proposed. Firstly, EEG waveforms are segmented into sub-signals. Then the EEG signal features are obtained through the WPD algorithm, and some selected wavelet coefficients are retained and reconstructed into EEG signals in their respective frequency bands. Subsequently, the reconstructed EEG signals were utilized as input of the proposed deep residual convolutional networks to classify EEG signals. Finally, EEG types of motor imagination are classified by the DRes-CNN classifier intelligently. The datasets from BCI Competition were used to test the performance of the proposed deep learning classifier. Classification experiments show that the average recognition accuracy of this method reaches 98.76%. The proposed method can be further applied to the BCI system of motor imagination control.

Positive Cooperative Protonation of a Metal-Organic Framework: pH-Responsive Fluorescence and Proton Conduction.

Positive cooperative binding, a phenomenon prevalent in biological processes, holds great appeal for the design of highly sensitive responsive molecules and materials. It has been demonstrated that metal-organic frameworks (MOFs) can show positive cooperative adsorption to the benefit of gas separation, but potential binding cooperativity is largely ignored in the study of sensory MOFs. Here, we report the first demonstration of positive cooperative protonation of a MOF and the relevant pH response in fluorescence and proton conduction. The MOF is built of Zr-O clusters and bipyridyl-based tetracarboxylate linkers and has excellent hydrolytic stability. It shows a unique pH response that features two synchronous abrupt turn-off and turn-on fluorescent transitions. The abrupt transitions, which afford high sensitivity to small pH fluctuations, are due to cooperative protonation of the pyridyl sites with a Hill coefficient of 1.6. The synchronous dual-emission response, which leads to visual color change, is ascribable to proton-triggered switching between (n, π*) and (π, π*) emissions. The latter emission can be quenched by electron donating anion-dependent through photoinduced electron transfer and ground-state charge transfer. Associated with cooperative protonation, the proton conductivity of the MOF is abruptly enhanced at low pH by two orders, but overhigh acid concentration is adverse because excessive anions can interrupt the conducting networks. Our work shows new perspectives of binding cooperativity in MOFs and should shed new light on the development of responsive fluorescent MOFs and proton conductive materials.

A pH-Sensing Fluorescent Metal-Organic Framework: pH-Triggered Fluorescence Transition and Detection of Mycotoxin.

Due to its great relevance to environmental, biological, and chemical processes, the precise detection of pH or acidic/basic species is an ongoing and imperative need. In this context, pH-sensitive luminescent systems are highly desired. We reported a three-dimensional Zn(II) MOF synthesized from a bipyridyl-tetracarboxylic ligand and composed of 4-fold interpenetrated diamond frameworks. Because the steric hindrance in the ligand prevents metal coordination with the pyridyl group, the MOF features free basic N sites accessible to the small H+ ions, which renders pH responsivity. The aqueous dispersion exhibits an abrupt, high-contrast, and reversible on-off fluorescence transition in the narrow pH range of 5.4-6.2. The sensitive bistable system can be used for the precise monitoring of pH within the range and for use as a pH-triggered optical switch. The responsive mechanism through pyridyl protonation is collaboratively supported by data fitting, absorption spectra, and molecular orbital calculations. In particular, spectral and theoretical analyses reveal the destruction of n → π* transitions and the appearance of intramolecular charge-transfer transitions upon pyridyl protonation. Moreover, by virtue of the pH-responsive fluorescence, the MOF shows appealing sensing performance for the detection of 3-nitropropionic acid, a major mycotoxin in moldy sugar cane.

Neutrophil-to-lymphocyte ratio as a predictive marker of metabolic syndrome.

Neutrophil-to-lymphocyte ratio (NLR) serves as a strong prognostic indicator for patients suffering from various diseases. Neutrophil activation promotes the recruitment of a number of different cell types that are involved in acute and chronic inflammation and are associated with cancer treatment outcome. Measurement of NLR, an established inflammation marker, is cost-effective, and it is likely that NLR can be used to predict the development of metabolic syndrome (MS) at an early stage. MS scores range from 1 to 5, and an elevated MS score indicates a greater risk for MS. Monitoring NLR can prevent the risk of MS.A total of 34,013 subjects were enrolled in this study. The subjects (score 0-5) within the 6 groups were classified according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria, and all anthropometrics, laboratory biomarkers, and hematological measurements were recorded. For the 6 groups, statistical analysis and receiver operating characteristic (ROC) curves were used to identify the development of MS.Analysis of the ROC curve indicated that NLR served as a good predictor for MS. An MS score of 1 to 2 yielded an acceptable discrimination rate, and these rates were even higher for MS scores of 3 to 5 (P < .001), where the prevalence of MS was 30.8%.NLR can be used as a prognostic marker for several diseases, including those associated with MS.

Gene-gene interactions between TGF-ß/Smad3 signalling pathway polymorphisms affect susceptibility to knee osteoarthritis.

OBJECTIVE: Transforming growth factor/Smad family member 3 (TGF)-ß/Smad3 signalling is essential for maintaining articular cartilage. A relationship between the genetic variants of TGF-ß itself, TGF-ß signalling and binding molecules, and osteoarthritis (OA) has been reported. Although variants of candidate genes have become prime targets for genetic analysis, their detailed interplay has not been documented. Our goal was to establish whether single nucleotide polymorphisms (SNPs) of TGF-ß1, TGF-ßRI, Smad3 and tissue inhibitor of metalloproteinases 3 (TIMP3), and their interactions, are associated with knee OA. DESIGN: We performed a case-control association study and genotyped 518 knee patients with OA and 468 healthy controls. All participants were genotyped for TGF-ß1 (rs1800469C/T), TGF-ßRI (rs1590A/G), Smad3 (rs12901499A/G and rs6494629T/C), and TIMP3 (rs715572G/A and rs1962223G/C) polymorphisms by polymerase chain reaction-restriction fragment length polymorphism analysis. Multifactor dimensionality reduction (MDR) was used to identify gene-gene interactions. RESULTS: Significant associations were observed for TIMP3 rs715572G/A polymorphisms in knee patients with OA and healthy individuals. The GA heterozygote in TIMP3 (rs715572G/A) was significantly associated with OA (p=0.007). Patient stratification using the Kellgren-Lawrence grading scale showed significant differences in TIMP3 rs715572G/A genotypes between grade 4 knee OA and controls. By MDR analysis, a two-locus model (Smad3 rs6494629T/C and TIMP3 rs715572G/A) of gene-gene interaction was the best for predicting knee OA risk, and its maximum testing accuracy was 57.55% and maximum cross-validation consistency was 10/10. CONCLUSIONS: TIMP3 rs715572G/A is a candidate protective gene for severe knee OA. Gene-gene interactions between Smad3 rs6494629T/C and TIMP3 rs715572G/A polymorphisms may play more important protective roles in knee OA.