Calixarene-Based Supramolecular Sensor Array for Pesticide Discrimination.

The identification and detection of pesticides is crucial to protecting both the environment and human health. However, it can be challenging to conveniently and rapidly differentiate between different types of pesticides. We developed a supramolecular fluorescent sensor array, in which calixarenes with broad-spectrum encapsulation capacity served as recognition receptors.

Propensity Score Matching Analysis of the Influence of Waiting Time Satisfaction on Community Resident's Satisfaction With Medical Institutions: An Extensive Survey of Outpatient Population in Shantou City of Southern China.

Objective: This study was designed to perform a nuanced analysis of the multifaceted association between community residents' satisfaction and their perceived satisfaction concerning the visit duration at medical facilities, that could be harnessed to enhance and streamline the process of hierarchical diagnosis and treatment, thereby augmenting healthcare outcomes and patient experiences.

Methods: Respondents who had utilized services from medical institutions were invited to fill out questionnaires by scanning QR codes. Additionally, surveys also distributed questionnaires through WeChat groups of community residents in densely populated areas of the community, as well as WeChat groups for patients who had previously visited local hospitals.

Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data.

Activity recognition is one of the significant technologies accompanying the development of the Internet of Things (IoT). It can help in recording daily life activities or reporting emergencies, thus improving the user's quality of life and safety, and even easing the workload of caregivers. This study proposes a human activity recognition (HAR) system based on activity data obtained via the micro-Doppler effect, combining a two-stream one-dimensional convolutional neural network (1D-CNN) with a bidirectional gated recurrent unit (BiGRU).

Enantiopure Corral[4]BINOLs as Ultrastrong Receptors for Recognition and Differential Sensing of Steroids.

The precise recognition and sensing of steroids, a type of vital biomolecules, hold immense practical value across various domains. In this study, we introduced corral[4]BINOLs (C[4]BINOLs), a pair of enantiomeric conjugated deep-cavity hosts, as novel synthetic receptors for binding steroids. Due to the strong hydrophobic effect of their deep nonpolar, chiral cavities, the two enantiomers of C[4]BINOLs demonstrated exceptionally high recognition affinities (up to 10 M) for 16 important steroidal compounds as well as good enantioselectiviy (up to 15.

Molecular Recognition with Macrocyclic Receptors for Application in Precision Medicine.

Macrocyclic receptors can serve as alternatives to natural recognition systems as recognition tools. They provide effectively preorganized cavities to encapsulate guests via host-guest interactions, thereby affecting the physiochemical properties of the guests. Macrocyclic receptors exhibit chemical and thermal stabilities higher than those of natural receptors and thus are expected to resist degradation inside the body.

A heteromultivalent host-guest sensor array for cell recognition and discrimination.

We present a supramolecular sensor array based on a series of heteromultivalent macrocyclic coassemblies using amphiphilic calixarenes and cyclodextrin as the building blocks for cell recognition. The corresponding cross-reactivity between the coassemblies and cells served as the unique fingerprint for cell classification, and successfully identified the normal cell lines, cancerous cell lines, and cross-contaminated cells.

A facile way to construct sensor array library via supramolecular chemistry for discriminating complex systems.

Differential sensing, which discriminates analytes via pattern recognition by sensor arrays, plays an important role in our understanding of many chemical and biological systems. However, it remains challenging to develop new methods to build a sensor unit library without incurring a high workload of synthesis. Herein, we propose a supramolecular approach to construct a sensor unit library by taking full advantage of recognition and assembly.