Hydrogen-bond organic-framework-based electrochemical sensor for highly sensitive determination of trace cadmium ions in environmental and e-cigarette samples.

Background: The heavy metal ion Cd is acutely toxic, and excessive concentrations can have adverse effects on human production and life, and even lead to significant public health risks and environmental impacts. There are several mature non-electrochemical methods for heavy metal detection, but these methods are characterized by high cost, which makes it difficult to be applied to the field for timely detection. Therefore, it is necessary to prepare a new electrochemical sensor that is environmentally friendly and capable of detecting Cd in the environment quickly, easily and sensitively.

Synergistic optimization of baffles and aeration to improve the Light/Dark cycle of microalgae photobioreactor for enhanced nitrogen removal performance: Computational fluid dynamics and experimental verification.

Microalgae photobioreactor (PBR) is a kind of efficient wastewater treatment system for nitrogen removal. However, there is still an urgent need for process optimization of PBR. Especially, the synergistic effect and optimization of light and flow state poses a challenge.

A radiomics nomogram based on multiparametric MRI for diagnosing focal cortical dysplasia and initially identifying laterality.

Background: Focal cortical dysplasia (FCD) is the most common epileptogenic developmental malformation. The diagnosis of FCD is challenging. We generated a radiomics nomogram based on multiparametric magnetic resonance imaging (MRI) to diagnose FCD and identify laterality early.

Good learning environment of medical schools is an independent predictor for medical students' study engagement.

Background: Study engagement is regarded important to medical students' physical and mental wellbeing. However, the relationship between learning environment of medical schools and the study engagement of medical students was still unclear. This study was aimed to ascertain the positive effect of learning environment in study engagement.

Jejunostomy feeding plus oral feeding versus intravenous nutrition plus oral feeding after esophageal cancer resection: a comparative retrospective cohort study.

Background: There are multiple choices for the nutritional management mode after esophageal cancer surgery. Currently, there is still controversy regarding which nutritional management mode has an impact on the postoperative recovery and overall survival (OS) of patients. This study aims to compare the differences between two commonly used clinical nutritional management modes: jejunostomy feeding plus oral intake (JF plus OI) and intravenous nutrition plus oral intake (IN plus OI), in terms of short-term efficacy and 3-year OS, in order to further explore the optimal mode of enteral nutrition management after esophageal cancer surgery.

Deep learning models for rapid discrimination of high-grade gliomas from solitary brain metastases using multi-plane T1-weighted contrast-enhanced (T1CE) images.

Background: High-grade gliomas (HGG) and solitary brain metastases (SBM) are two common types of brain tumors in middle-aged and elderly patients. HGG and SBM display a high degree of similarity on magnetic resonance imaging (MRI) images. Consequently, differential diagnosis using preoperative MRI remains challenging.

Rapid nanomolar detection of cocaine in biofluids by electrochemical aptamer-based sensor with low-temperature effect for drugged driving screening.

Cocaine is one of the most abused illicit drugs, and its abuse damages the central nervous system and can even lead directly to death. Therefore, the development of simple, rapid and highly sensitive detection methods is crucial for the prevention and control of drug abuse, traffic accidents and crime. In this work, an electrochemical aptamer-based (EAB) sensor based on the low-temperature enhancement effect was developed for the direct determination of cocaine in bio-samples.

S-scheme carbon doped-TiO/ZnInS heterojunction for enhanced photocatalytic degradation of microcystin-LR and hydrogen evolution.

Photocatalytic degradation of pollutants coupled with hydrogen (H) evolution has emerged as a promising solution for environmental and energy crises. However, the fast recombination of photoexcited electrons and holes limits photocatalytic activities. Herein, an S-scheme heterojunction carbon doped-TiO/ZnInS (C-TiO/ZnInS) was designed by substituting oxygen sites within C-TiO by ZnInS.

A new microalgal negative carbon technology for landfill leachate treatment: Simultaneous removal of nitrogen and phosphorus.

Replete with ammonia nitrogen and organic pollutants, landfill leachate typically undergoes treatment employing expensive and carbon-intensive integrated techniques. We propose a novel microalgae technology for efficient, low-carbon simultaneous treatment of carbon, nitrogen, and phosphorus in landfill leachate (LL). The microbial composition comprises a mixed microalgae culture with Chlorella accounting for 82.

Tai Chi Movement Recognition and Precise Intervention for the Elderly Based on Inertial Measurement Units and Temporal Convolutional Neural Networks.

(1) Background: The objective of this study was to recognize tai chi movements using inertial measurement units (IMUs) and temporal convolutional neural networks (TCNs) and to provide precise interventions for elderly people. (2) Methods: This study consisted of two parts: firstly, 70 skilled tai chi practitioners were used for movement recognition; secondly, 60 elderly males were used for an intervention study. IMU data were collected from skilled tai chi practitioners performing Bafa Wubu, and TCN models were constructed and trained to classify these movements.

Multilayer Perceptron-Based Wearable Exercise-Related Heart Rate Variability Predicts Anxiety and Depression in College Students.

(1) Background: This study aims to investigate the correlation between heart rate variability (HRV) during exercise and recovery periods and the levels of anxiety and depression among college students. Additionally, the study assesses the accuracy of a multilayer perceptron-based HRV analysis in predicting these emotional states. (2) Methods: A total of 845 healthy college students, aged between 18 and 22, participated in the study.

Congruent or conflicting? The interaction between emoji and textual sentence is not that simple!

As a Japanese graphic symbol widely used in the world, Emoji plays an important role in computer mediated communication. Despite its prevalent use, the interaction dynamics between emoji and textual sentences remain inadequately explored. Based on the emotional function of emoji, this study uses the indirect priming method to explore the emotional impact of emoji on subsequent text in computer mediated communication through two progressive behavioral experiments.

Highthroughput Screening of CuBi Bimetallic Catalyst Array for Electrocatalytic CO Reduction Reaction by Scanning Electrochemical Microscope.

The testing and evaluation of catalysts in CO electroreduction is a very tedious process. To study the catalytic system of CO reduction more quickly and efficiently, it is necessary to establish a method that can detect multiple catalysts at the same time. Herein, a series of CuBi bimetallic catalysts have been successfully prepared on a single glass carbon electrode by a scanning micropieptte contact method.

Platinum Cluster Decoration on Hollow Carbon Spheres for High-Efficiency Hydrogen Evolution Reaction.

Currently, platinum (Pt)/carbon support composite materials have tremendous application prospects in the hydrogen evolution reaction (HER). However, one of the primary challenges for boosting their performance is designing a substrate with the desired microstructure. Herein, the intact hollow carbon spheres (HCSs) were prepared via template method.

Site engineering of linear conjugated polymers to regulate oxygen adsorption affinity for boosting photocatalytic production of hydrogen peroxide without sacrificial agent.

Artificial photosynthesis of hydrogen peroxide (HO) is a hopeful alternative to the industrial anthraquinone process. However, rational fabrication of the photocatalysts for the production of HO without any sacrificial agents is still a formidable challenge. Herein, two kinds of linear conjugated polymers (LCPs) including pyridinic N functionalized polymer (DEB-N) and pyridinic N non-contained polymer (DEB-N) were successfully synthesized.

Acyl chloride-mediated synthesis of rhodanine-modified UiO-66 for high-efficiency silver recovery.

Silver (Ag) recovery is essential for ecological protection, human health and economic benefits. Effective capture of Ag(I) from wastewater is still challenging due to insufficient accessible sites of adsorbents. Herein, an acyl chloride-mediated strategy is developed to synthesize rhodanine (Rd) modified UiO-66 derivatives for Ag(I) adsorption.

[Research Advances in the Association Between Alzheimer's Disease and Double-Stranded RNA-Dependent Protein Kinase].

Alzheimer's disease (AD) is a severe threat to human health and one of the three major causes of human death.Double-stranded RNA-dependent protein kinase (PKR) is an interferon-induced protein kinase involved in innate immunity.In the occurrence and development of AD,PKR is upregulated and continuously activated.

Combining single-cell and bulk RNA sequencing, NK cell marker genes reveal a prognostic and immune status in pancreatic ductal adenocarcinoma.

The NK cell is an important component of the tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC), also plays a significant role in PDAC development. This study aimed to explore the relationship between NK cell marker genes and prognosis, immune response of PDAC patients. By scRNA-seq data, we found the proportion of NK cells were significantly downregulated in PDAC and 373 NK cell marker genes were screened out.

Exploring the CO Electrocatalysis Potential of 2D Metal-Organic Transition Metal-Hexahydroxytriquinoline Frameworks: A DFT Investigation.

Metal-organic frameworks have demonstrated great capacity in catalytic CO reduction due to their versatile pore structures, diverse active sites, and functionalization capabilities. In this study, a novel electrocatalytic framework for CO reduction was designed and implemented using 2D coordination network-type transition metal-hexahydroxytricyclic quinazoline (TM-HHTQ) materials. Density functional theory calculations were carried out to examine the binding energies between the HHTQ substrate and 10 single TM atoms, ranging from Sc to Zn, which revealed a stable distribution of metal atoms on the HHTQ substrate.