Postnatal development of rat retina: a continuous observation and comparison between the organotypic retinal explant model and in vivo development.

JOURNAL/nrgr/04.03/01300535-202503000-00033/figure1/v/2024-06-17T092413Z/r/image-tiff The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures. However, the lack of systematic and continuous comparison between in vivo retinal development and the organotypic retinal explant culture makes this model controversial in postnatal retinal development studies. Thus, we aimed to verify the feasibility of using this model for postnatal retinal development studies by comparing it with the in vivo retina. In this study, we showed that postnatal retinal explants undergo normal development, and exhibit a consistent structure and timeline with retinas in vivo. Initially, we used SOX2 and PAX6 immunostaining to identify retinal progenitor cells. We then examined cell proliferation and migration by immunostaining with Ki-67 and doublecortin, respectively. Ki-67- and doublecortin-positive cells decreased in both in vivo and explants during postnatal retinogenesis, and exhibited a high degree of similarity in abundance and distribution between groups. Additionally, we used Ceh-10 homeodomain-containing homolog, glutamate-ammonia ligase (glutamine synthetase), neuronal nuclei, and ionized calcium-binding adapter molecule 1 immunostaining to examine the emergence of bipolar cells, Müller glia, mature neurons, and microglia, respectively. The timing and spatial patterns of the emergence of these cell types were remarkably consistent between in vivo and explant retinas. Our study showed that the organotypic retinal explant culture model had a high degree of consistency with the progression of in vivo early postnatal retina development. The findings confirm the accuracy and credibility of this model and support its use for long-term, systematic, and continuous observation.

Enhancing electrocatalytic nitrogen fixation over core-shell P-Sb2S3/MoS2 heterojunction by vacancy and interface modulation.

Electrochemical synthesis of ammonia is a green and sustainable way for nitrogen fixation, but the development of efficient electrocatalysts still faces challenges. The modulation of electronic structure through interface engineering and vacancy engineering is a new approach to enhance the performance of electrocatalysts. In this work, a phosphorus-doped core-shell heterojunction P-Sb2S3/MoS2 was designed and synthesized by combining antimony, which is inert to H+ adsorption, with molybdenum, which has good affinity and reducibility with nitrogen. The synthesis involved both interfacial engineering and vacancy engineering strategies.DFT calculations demonstrate that the formationofSb2S3/MoS2 heterojunction enhances the creation of a built-in electric field, thereby expediting electron flow.Additionally, phosphorus doping induced the formation of abundant sulfur vacancies, significantly enhancing nitrogen adsorption performance in this material.As a result, our designed structure exhibited excellent NRR performance with an ammonia production rate of 41.22 µg·h-1·mg-1cat and a Faraday efficiency of 15.70 %.The unique structural of this catalyst contribute to a more optimal balance between the rate of ammonia production and the Faraday efficiency. The successful preparation of the highly efficient P-Sb2S3/MoS2 heterojunctionsprovidesanew strategyfor catalyst design in electrocatalytic nitrogen reduction.

A review of functions and mechanisms of clay soil conditioners and catalysts in thermal remediation compared to emerging photo-thermal catalysis.

High temperatures and providing sufficient time for the thermal desorption of persistent organic pollutants (POPs) from contaminated clay soils can lead to intensive energy consumption. Therefore, this article provides a critical review of the potential additives which can improve soil texture and increase the volatility of POPs, and then discusses their enhanced mechanisms for contributing to a green economy. Ca-based additives have been used to reduce plasticity of bentonite clay, absorb water and replenish system heat. In contrast, non-Ca-based additives have been used to decrease the plasticity of kaolin clay. The soil structure and soil plasticity can be changed through cation exchange and flocculation processes. The transition metal oxides and alkali metal oxides can be applied to catalyze and oxidize polycyclic aromatic hydrocarbons, petroleum and emerging contaminants. In this system, reactive oxygen species (•O2- and •OH) are generated from thermal excitation without strong chemical oxidants. Moreover, multiple active ingredients in recycled solid wastes can be controlled to reduce soil plasticity and enhance thermal catalysis. Alternatively, the alkali, nano zero-valent iron and nano-TiN can catalyze hydrodechlorination of POPs under reductive conditions. Especially, photo and photo-thermal catalysis are discussed to accelerate replacement of fossil fuels by renewable energy in thermal remediation.

Automated MRI-based segmentation of intracranial arterial calcification by restricting feature complexity.

PURPOSE: To develop an automated deep learning model for MRI-based segmentation and detection of intracranial arterial calcification. METHODS: A novel deep learning model under the variational autoencoder framework was developed. A theoretically grounded dissimilarity loss was proposed to refine network features extracted from MRI and restrict their complexity, enabling the model to learn more generalizable MR features that enhance segmentation accuracy and robustness for detecting calcification on MRI. RESULTS: The proposed method was compared with nine baseline methods on a dataset of 113 subjects and showed superior performance (for segmentation, Dice similarity coefficient: 0.620, area under precision-recall curve [PR-AUC]: 0.660, 95% Hausdorff Distance: 0.848 mm, Average Symmetric Surface Distance: 0.692 mm; for slice-wise detection, F1 score: 0.823, recall: 0.764, precision: 0.892, PR-AUC: 0.853). For clinical needs, statistical tests confirmed agreement between the true calcification volumes and predicted values using the proposed approach. Various MR sequences, namely T1, time-of-flight, and SNAP, were assessed as inputs to the model, and SNAP provided unique and essential information pertaining to calcification structures. CONCLUSION: The proposed deep learning model with a dissimilarity loss to reduce feature complexity effectively improves MRI-based identification of intracranial arterial calcification. It could help establish a more comprehensive and powerful pipeline for vascular image analysis on MRI.

Mercury contents and potential exposure risk of rice-containing food products.

Mercury (Hg), especially methylmercury (MeHg), accumulation in rice grain due to rice paddy possessing conditions conducive to Hg methylation has led to human Hg exposure through consumption of rice-based daily meals. In addition to being a food staple, rice is widely used as a raw material to produce a vast variety of processed food products. Little is known about Hg levels in snacking rice-food products and potential Hg exposure from consumption of them, besides previous studies on infant rice cereals. Aiming to provide complementary information for a more complete assessment on Hg exposure risk originated from Hg-containing rice, this study determined total Hg (THg) and MeHg levels in 195 rice-containing and rice-free processed food products covering all major types of snack foods marketed in China and the estimated daily intake (EDI) of dietary Hg from the consumption of these foods. The results clearly showed THg and MeHg contents in rice-containing foods were significantly higher than rice-free products, suggesting the transfer of Hg and MeHg from the rice to the end products, even after manufacturing processes. Moreover, significant positive correlations were observed between THg, MeHg, or MeHg/THg ratio and rice content for samples containing multiple grains as ingredients, further indicating the deciding role of rice for Hg levels in the end food products. Although the EDI of THg and MeHg via rice-based food products were relatively low compared to the reference dose, it should be considered these snacking food products would contribute additive Hg intake outside of the daily regular meals.

Real-road NOx and CO2 emissions of city and highway China-6 heavy-duty diesel vehicles.

The emission of heavy-duty vehicles has raised great concerns worldwide. The complex working and loading conditions, which may differ a lot from PEMS tests, raised new challenges to the supervision and control of emissions, especially during real-world applications. On-board diagnostics (OBD) technology with data exchange enabled and strengthened the monitoring of emissions from a large number of heavy-duty diesel vehicles. This paper presents an analysis of the OBD data collected from more than 800 city and highway heavy-duty vehicles in China using remote OBD data terminals. Real-world NOx and CO2 emissions of China-6 heavy-duty vehicles have been examined. The results showed that city heavy-duty vehicles had higher NOx emission levels, which was mostly due to longer time of low SCR temperatures below 180°C. The application of novel methods based on 3B-MAW also found that heavy-duty diesel vehicles tended to have high NOx emissions at idle. Also, little difference had been found in work-based CO2 emissions, and this may be due to no major difference were found in occupancies of hot running.

A Core-Brush Nanoplatform with Enhanced Lubrication and Anti-Inflammatory Properties for Osteoarthritis Treatment.

Osteoarthritis (OA) is recognized as a highly friction-related joint disease primarily associated with increased joint friction and inflammation due to pro-inflammatory M1-type macrophage infiltration in the articular cavity. Therefore, strategies to simultaneously increase lubrication and relieve inflammation to remodel the damaged articular microenvironment are of great significance for enhancing its treatment. Herein, a multifunctional core-brush nanoplatform composed of a ROS-scavenging polydopamine-coated SiO2 core and lubrication-enhancing zwitterionic poly(2-methacryloyloxyethyl phosphorylcholine) (PMPC) brush and loaded with the anti-inflammatory drug curcumin by a reactive oxygen species (ROS)-liable conjugation (named as SiO2@PP-Cur) is rationally designed. Benefiting from the grafted zwitterionic PMPC brush, a tenacious hydration layer with enhanced lubricity for reducing joint abrasions is developed. More importantly, based on the mono-iodoacetic acid-induced arthritis (MIA) rat model, intra-articular injection of SiO2@PP-Cur nanoplatform can effectively alleviate articular inflammation via promoting macrophage polarization from the pro-inflammatory M1 to anti-inflammatory M2 state by activating the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway and attenuating the degradation of cartilage matrix, resulting in the remodeling of the damaged microenvironment into a pro-regenerative microenvironment. As a result, SiO2@PP-Cur can considerably inhibit OA progression. Therefore, the work may provide a novel strategy for the development of an advanced core-brush nanoplatform for enhanced OA therapy.

GC-MS-based metabonomic analysis of silkworm haemolymph reveals four-stage metabolic responses to nucleopolyhedrovirus infection.

Silkworm, Bombyx mori, an economically significant insect, plays a crucial role in silk production. However, silkworm breeding is highly susceptible to various pathogens, particularly the Bombyx mori nucleopolyhedrovirus (BmNPV), which poses a serious threat. Recent metabonomic studies have provided insights into the metabolic changes associated with BmNPV infection. BmNPV infection has obvious temporal characteristics. However, few studies have investigated the silkworms infected in different periods. This study employed gas chromatography-mass spectrometry (GC-MS) to perform a comprehensive analysis of haemolymph metabolites in silkworms at 48, 72, 96 and 120 h post-infection (h.p.i.). Through the integration of time-course analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, the study revealed distinct four-stage metabolic characteristics in the silkworm's response to BmNPV infection. At Stage 1 (48 h.p.i.), silkworms activate antioxidant defence mechanisms, with significant enrichment in metabolic pathways involving key antioxidants such as glutathione, to mitigate oxidative stress induced by viral invasion. By Stage 2 (72 h.p.i.), pathways related to amino acid metabolism and protein synthesis become active, indicating an increase in protein synthesis. In Stage 3 (96 h.p.i.), energy metabolism and substance transport pathways are significantly upregulated to support the rapid viral replication and the enhanced locomotor behaviour of silkworm. Finally, at Stage 4 (120 h.p.i.), there is a further enhancement of pathways related to energy metabolism, nucleic acid synthesis, and substance transport, which align with peak viral assembly and release. These findings contribute to an in-depth understanding of the biochemical basis of silkworm resistance to NPV.

Case Report: Does the misplaced titanium mesh cage after total spondylectomy causing cervicothoracic cord compression need to be removed during revision surgery?

Background: Mechanical failure following total spondylectomy is a surgical challenge. The cervicothoracic junction region is a special anatomical site with complex biomechanics, and few studies have reported a detailed surgical management strategy for cases where the mesh cage subsides and compresses the spinal cord in the cervicothoracic junction region after total spondylectomy. Case presentation: A 56-year-old male patient experienced screw and rod fracture and mesh cage retropulsion into the spinal canal 5 years after total spondylectomy for osteochondroma in the first to third thoracic vertebrae. The patient complained of numbness and discomfort in both lower extremities, accompanied by unstable walking for 8 months prior to admission at our hospital. We concluded that uncorrected local kyphosis in the cervicothoracic junction after the first surgery resulted in current mesh cage subsidence and rod/screw fracture. Considering the difficulty and risks of removing the mesh cage from the anterior approach, we initially freed the superior end of the mesh cage without removing the mesh from the anterior approach by resecting the C6/7 intervertebral disc and the destroyed C7 vertebral body. We then removed the original screws and rods and performed long segment fixation from C4 to T6 via a posterior approach after recovering sagittal alignment by skull traction. Finally, the iliac bone was harvested and transplanted between the superior end of the mesh cage and the inferior end plate of C6 to fill the defect caused by kyphosis correction and C7 vertebral resection. After surgery, the patient experienced sagittal alignment reconstruction and symptom relief, and he was asked to wear a cast for at least 6 months until bone fusion was achieved. At the 3-year follow-up, there was fusion between the mesh cage and the C6 vertebra with successful instrument reconstruction and no mesh cage subsidence were observed. Conclusions: When a subsided and migrated titanium mesh cage is difficult to remove after mechanical failure following total spondylectomy, recovering sagittal alignment to achieve indirect decompression based on unique anterior and middle column reconstruction, solid instrument construction, and bone fusion is an alternative solution.

Domain adaptive semantic segmentation by optimal transport.

Scene segmentation is widely used in autonomous driving for environmental perception. Semantic scene segmentation has gained considerable attention owing to its rich semantic information. It assigns labels to the pixels in an image, thereby enabling automatic image labeling. Current approaches are based mainly on convolutional neural networks (CNN), however, they rely on numerous labels. Therefore, the use of a small amount of labeled data to achieve semantic segmentation has become increasingly important. In this study, we developed a domain adaptation framework based on optimal transport (OT) and an attention mechanism to address this issue. Specifically, we first generated the output space via a CNN owing to its superior of feature representation. Second, we utilized OT to achieve a more robust alignment of the source and target domains in the output space, where the OT plan defined a well attention mechanism to improve the adaptation of the model. In particular, the OT reduced the number of network parameters and made the network more interpretable. Third, to better describe the multiscale properties of the features, we constructed a multiscale segmentation network to perform domain adaptation. Finally, to verify the performance of the proposed method, we conducted an experiment to compare the proposed method with three benchmark and four SOTA methods using three scene datasets. The mean intersection-over-union (mIOU) was significantly improved, and visualization results under multiple domain adaptation scenarios also show that the proposed method performed better than semantic segmentation methods.

Structural insights into the mechanotransducing mechanism of FtsEX in cell division.

The filamentous temperature-sensitive (Fts) protein FtsEX plays a pivotal role in Escherichia coli (E. coli) cell division by facilitating the activation of peptidoglycan hydrolysis through the adaptor EnvC. FtsEX belongs to the type VII ATP-binding cassette (ABC) transporter superfamily, which harnesses ATP energy to induce mechanical force, triggering a cascade of conformational changes that activate the pathway. However, the precise mechanism by which FtsEX initiates mechanotransmission remains elusive. Due to the inherent instability of this type of ABC transporter protein in vitro, the conformation of FtsEX has solely been determined in the stabilized ATP-bound state. To elucidate the dynamics of FtsEX, we characterized FtsEX and EnvC of various functional structures through cryo-electron microscopy (cryo-EM) and homology modeling. We validated the structures by molecular dynamics simulations. By site-directed mutagenesis and phenotype screening, we also identified the functional residues involved in allosteric communication between FtsE and FtsX as well as FtsX and EnvC. Additionally, we discovered a potential role of phospholipids in stabilizing the complex conformation during mechanotransmission. This comprehensive exploration significantly enhances our understanding of the intricate mechanisms governing bacterial cell division and unveils potential molecular targets for developing innovative antimicrobial drugs to combat antibiotic resistance.

The deep learning-based physical education course recommendation system under the internet of things.

This study aims to propose a deep learning (DL)-based physical education course recommendation system by combining the Internet of Things (IoT) technology and DL, to improve the accuracy and personalization of recommendation. Firstly, IoT devices such as smart bracelets and smart clothing are used to monitor students' physiological data in real-time, and IoT sensors are utilized to sense the environment around students. Secondly, IoT devices capture students' social interactions with their peers, recommending socially oriented courses. Meanwhile, by integrating IoT data with students' academic data, course recommendations are optimized to match students' learning progress and schedule. Finally, Generative Adversarial Network (GAN) models, especially the improved Regularization Penalty Conditional Feature Generative Adversarial Network (RP-CFGAN) model, deal with data sparsity and cold start problems. The experimental results show that this model performs well in TopN evaluation and is markedly enhanced compared with traditional models. This study denotes that integrating IoT technology and GAN models can more accurately understand student needs and provide personalized recommendations. Although the model performs well, there is still room for improvement, such as exploring more regularization techniques, protecting user privacy, and extending the system to diverse platforms and scenarios.

Characterization of etomidate and emerging analogs in human hair using UHPLC-MS/MS and confirmation in real forensic cases.

The regulation of etomidate, a widely used drug for anesthesia induction and short surgical procedures, has led to the emergence of etomidate analogs such as metomidate, propoxate, and isopropoxate. This study introduces and validates a simple, rapid, and cost-effective ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for the determination and quantification of etomidate, etomidate acid, metomidate, propoxate, and isopropoxate in human hair. Using a five-minute gradient elution on a Phenomenex Kinetex Biphenyl column, the method achieves low limits of quantification (LOQs), ranging from 5 to 20 pg/mg. Method validation confirms robust linear calibration curves for the target substances in hair samples within the range of LOQs to 1000 pg/mg, with average correlation coefficients (r) all exceeding 0.999. The method also achieves acceptable intra-day and inter-day precision (<15 %) and trueness(bias, -10.9 % to 14.4 %). The matrix effect ranges from 46.9 % to 94.2 %, and the extraction recovery rate ranges from 84.5 % to 105 %. When applied to authentic cases, this method successfully identified 56 positive samples. The concentrations of etomidate, etomidate acid, metomidate, propoxate, and isopropoxate in positive samples ranged from 27 to 1.5 × 105 pg/mg, 21 to 1.5 × 103 pg/mg, 18 to 8.7 × 104 pg/mg, 25 to 1.6 × 104 pg/mg, and 22 to 5.0 × 105 pg/mg, respectively.

Repetitive transcranial magnetic stimulation elicits weight loss and improved insulin sensitivity in type 2 diabetic rats.

BACKGROUND: Type 2 diabetes (T2D) accounts for the majority of diabetes incidences and remains a widespread global chronic disorder. Apart from early lifestyle changes, intervention options for T2D are mainly pharmaceutical. METHODS: Repetitive transcranial magnetic stimulation (rTMS) has been approved by the FDA as a therapeutic intervention option for major depressive disorders, with further studies also indicating its role in energy metabolism and appetite. Considering its safe and non-invasive properties, we evaluated the effects of rTMS on systemic metabolism using T2D rats. RESULTS: We observed that rTMS improved glucose tolerance and insulin sensitivity in T2D rats after a 10-day exposure. Improved systemic insulin sensitivity was maintained after a 21-day treatment period, accompanied by modest yet significant weight loss. Circulating serum lipid levels, including those of cholesteryl ester, tryglyceride and ceramides, were also reduced following rTMS application. RNA-seq analyses further revealed a changed expression profile of hepatic genes that are related to sterol production and fatty acid metabolism. Altered expression of hypothalamic genes that are related to appetite regulation, neural activity and ether lipid metabolism were also implicated. CONCLUSION: In summary, our data report a positive impact of rTMS on systemic insulin sensitivity and weight management of T2D rats. The underlying mechanisms via which rTMS regulates systemic metabolic parameters partially involve lipid utilization in the periphery as well as central regulation of energy intake and lipid metabolism.

Perioperative Effect of Nursing Model Based on Nursing Quality Evaluation System in Otorhinolaryngology Patients.

Background: To explore the perioperative effect of the evaluation system of nursing quality in otorhinolaryngology patients. Methods: A total of 100 patients hospitalized in the Department of Otorhinolaryngology of the Third Affiliated Hospital of Qiqihar Medical College, Qiqihar City, China in 2019 were selected as the control group, and routine nursing mode was adopted. The control group was data before the implementation of this study. A total of 100 patients (experimental group) hospitalized in the Department of Otolaryngology in 2020 were selected to adopt the nursing model constructed by nursing quality evaluation system. The adverse mood of patients in the two groups were evaluated at admission and discharge, and postoperative pain and satisfaction were compared between the two groups. Results: Anxiety, depression and quality of life scores were improved in both groups, but the degree of improvement in experimental group was significantly higher than that in control group (t=481.759, 353.502, P<0.05), and the postoperative pain score in experimental group was lower than that in control group (t=54.086, P<0.05). The satisfaction of experimental group was better than that of control group (χ2=30.327, P<0.05). Conclusion: The nursing model based on the evaluation system of the nursing quality of otorhinolaryngology can relieve patients' adverse emotions, relieve postoperative pain of otorhinolaryngology patients, and improve patient satisfaction. Therefore, it is worth popularizing and applying in the future.

Establishment of a survival predictive model for patients with two synchronous multiple primary lung cancers: a multicenter cohort analysis.

Background: The prognostic predictors of the synchronous multiple primary lung cancer (SMPLC) still remain unclear, and there is a lack of studies on the prognosis of SMPLC patients excluding those with multifocal ground-glass/lepidic (GG/L) nodules. The aim of this study is to develop an effective model for predicting survival of SMPLC patients. Methods: In this multicenter cohort study, a total of 831 SMPLC patients presenting for lung cancer resection from January 2004 to January 2018 at five institutions were included for developing and validating a nomogram model. Specifically, 499 patients from the Cancer Hospital, Chinese Academy of Medical Sciences, and Beijing Chao-Yang Hospital, Capital Medical University were served as the training cohort. A total of 332 patients from The Third Xiangya Hospital of Central South University, the First Affiliated Hospital of University of Science and Technology of China, and Beijing Liangxiang Hospital were served as the external validation cohort. The nomogram model was compared with the Tumor Node Metastasis (TNM) system for the overall survival. The C-index, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to evaluate the model performance. A user-friendly website for SMPLC survival probability calculation was also provided for a better understanding of prognosis of patients with resected SMPLC. Results: A total of seven independent risk factors were selected by conducting a multivariate analysis on the training set. Further, a nomogram model was developed with these factors. Both the internal and external validations exhibited good discrimination (C-index: internal, 0.827; external, 0.784). The NRI and IDI of this model were 0.33 and 0.21, respectively. The survival rates for 1-year, 3-year, and 5-year were consistent with the actual observed values. A set of cutoff values were determined by grouping the patients into three different groups. For each group, we should expect a significant distinction between survival curves. Conclusions: The novel nomogram model enables accurate survival risk stratification of patients with resected SMPLC and may assist in decision-making that is conducive to patients with SMPLC at high risk.

A Paradoxical Tumor Antigen Specific Response in the Liver.

Functional tumor-specific CD8+ T cells are essential for an effective anti-tumor immune response and the efficacy of immune checkpoint inhibitor therapy. In comparison to other organ sites, we found higher numbers of tumor-specific CD8+ T cells in primary, metastatic liver tumors in murine tumor models. Despite their abundance, CD8+ T cells in the liver displayed an exhausted phenotype. Depletion of CD8+ T cells showed that liver tumor-reactive CD8+ T failed to control liver tumors but was effective against subcutaneous tumors. Similarly, analysis of single-cell RNA sequencing data from patients showed a higher frequency of exhausted tumor-reactive CD8+ T cells in liver metastasis compared to paired primary colon cancer. High-dimensional, multi-omic analysis combining proteomic CODEX and scRNA-seq data revealed enriched interaction of SPP1+ macrophages and CD8+ tumor-reactive T cells in profibrotic, alpha-SMA rich regions in the liver. Liver tumors grew less in Spp1-/- mice and the tumor-specific CD8+ T cells were less exhausted. Differential pseudotime trajectory inference analysis revealed extrahepatic signaling promoting an intermediate cell (IC) population in the liver, characterized by co-expression of VISG4, CSF1R, CD163, TGF-ßR, IL-6R, SPP1. scRNA-seq of a third data set of premetastatic adenocarcinoma showed that enrichment of this population may predict liver metastasis. Our data suggests a mechanism by which extrahepatic tumors facilitate the formation of liver metastasis by promoting an IC population inhibiting tumor-reactive CD8+ T cell function.

Fabrication of natural enzyme-covered / amino-modified Pd-Pt bimetallic-doped zeolitic imidazolate framework for ultrasensitive detection of metabolites.

The present article introduced an natural enzyme-covered/amino-modified Pd-Pt bimetallic-doped zeolitic imidazolate framework (NAPPZ) for ultrasensitive and specific detection of glucose. The dodecahedral nanomaterial zeolitic imidazolate framework (ZIF-8)-loaded Pd-Pt bimetallic nanoparticles endowed the composite with peroxidase-like activity. The modification with glucose oxidase (GOx) facilitated the rapid access of H2O2 produced through glucose oxidation to the Pd-Pt nanoparticles vicinity reducing diffusion. GOx specifically catalyzes the transformation of glucose into H2O2, which then H2O2 rapidly migrates to the Pd-Pt nanoparticles, catalyzing the oxidation of colorless o-phenylenediamine into the orange-yellow product 2,3-diaminophenazine. Based on the aforementioned cascade reaction, the NAPPZ and NAPPZ based on ChOx were utilized for detecting glucose in human urine samples and cholesterol in milk, respectively. The NAPPZ strategy presented a broad detection range (20-1100 µmol L-1) and a low detection limit (15.9 µmol L-1) for glucose, and the NAPPZ based on ChOx strategy approach offered a broad detection range (10-500 µmol L-1) and low detection limit (6.4 µmol L-1) for cholesterol. Therefore, this novel method holds significant potential in the areas of clinical diagnostics and food safety.

Loading Dyes into Chiral Cd/Zn-Metal-Organic Frameworks for Efficient Full-Color Circularly Polarized Luminescence.

Host-guest chemistry of chiral metal-organic frameworks (MOFs) has endowed them with circularly polarized luminescence (CPL), it is still limited for MOFs to systematically tune full-color CPL emissions and sizes. This work directionally assembles the chiral ligands, metal sites and organic dyes to prepare a series of crystalline enantiomeric D/L-Cd/Zn-n MOFs (n = 1 ~ 5, representing the adding amount of dyes), where D/L-Cd/Zn with the formula of Cd2(D/L-Cam)2(TPyPE) and Zn2(D/L-Cam)2(TPyPE) (D/L-Cam = D/L-camphoric acid, TPyPE = 4,4',4'',4'''-(1,2-henediidenetetra-4,1-phenylene)tetrakis[pyridine]) were used as the chiral platforms.  The framework-dye-enabled emission and through-space chirality transfer facilitate D/L-Cd/Zn-n bright full-color CPL activity. The ideal yellow CPL of D-Cd-5 and D-Zn-4, with |glum| as 4.9 × 10-3 and 1.3 × 10-3 and relatively high photoluminescence quantum yield of 40.79% and 45.40%, are further assembled into a white CPL light-emitting diode. The crystal sizes of D/L-Cd/Zn-n were found to be strongly correlated to the types and additional amounts of organic dyes, that the positive organic dyes allow for the preparation of > 7 mm bulks and negative dyes account for sub-20 µm particles. This work opens a new avenue to fabricate full-color emissive CPL composites and provides a potentially universal method for controlling the size of optical platforms.