Dendritic Cell-Hitchhiking In Vivo for Vaccine Delivery to Lymph Nodes.

Therapeutic cancer vaccines are among the first FDA-approved cancer immunotherapies. Among them, it remains a major challenge to achieve robust lymph-node (LN) accumulation. However, delivering cargo into LN is difficult owing to the unique structure of the lymphatics, and clinical responses have been largely disappointing. Herein, inspired by the Migrated-DCs homing from the periphery to the LNs, an injectable hydrogel-based polypeptide vaccine system is described for enhancing immunostimulatory efficacy, which could form a local niche of vaccine "hitchhiking" on DCs. The OVA peptide modified by lipophilic DSPE domains in the hydrogel is spontaneously inserted into the cell membrane to achieve "antigen anchoring" on DCs in vivo. Overall, OVA peptide achieves active access LNs through recruiting and "hitchhiking" subcutaneous Migrated-DCs. Remarkably, it is demonstrated that the composite hydrogel enhances LNs targeting efficacy by approximately six-fold compared to free OVA peptide. Then, OVA peptide can be removed from the cell surface under a typical acidic microenvironment within the LNs, further share them with LN-resident APCs via the "One-to-Many" strategy (One Migrated-DC corresponding to Many LN-resident APCs), thereby activating powerful immune stimulation. Moreover, the hydrogel vaccine exhibits significant tumor growth inhibition in melanoma and inhibits pulmonary metastatic nodule formation.

Effect of Different Fertilizer Types on Quality of Foxtail Millet under Low Nitrogen Conditions.

In order to clarify the effect of different fertilizers on foxtail millet quality under low nitrogen conditions, we used JGNo.21 and LZGNo.2 as experimental materials and set up five treatments, including non-fertilization, nitrogen, phosphorus, compound, and organic fertilizers, to study the regulation of different fertilizer types on agronomic traits, nutrient fractions, and pasting characteristics of foxtail millet under low nitrogen conditions. Compared with the control, all of the fertilizers improved the agronomic traits of JGNo.21 to a certain extent. Nitrogen and compound fertilizer treatments reduced the starch content of JGNo.21; the starch content was reduced by 0.55% and 0.07% under nitrogen and compound fertilizers treatments. Phosphorus and organic fertilizers increased starch content, and starch content increased by 0.50% and 0.56% under phosphorus and organic fertilizer treatments. The effect of each fertilizer treatment on protein content was completely opposite to that of starch; different fertilizer treatments reduced the fat content of JGNo.21 and increased the fiber content. Among them, nitrogen and phosphorus fertilizers increased the yellow pigment content; the yellow pigment content increased by 1.21% and 2.64% under nitrogen and phosphorus fertilizer treatments. Organic and compound fertilizers reduced the content of yellow pigment; the yellow pigment content was reduced by 3.36% and 2.79% under organic and compound fertilizer treatments. Nitrogen and organic fertilizers increased the fat content of LZGNo.2; the fat content increased by 2.62% and 1.98% under nitrogen, organic fertilizer treatment. Compound and phosphorus fertilizer decreased the fat content; the fat content decreased by 2.16% and 2.90% under compound and phosphorus fertilizer treatment. Different fertilizer treatments reduced the cellulose and yellow pigment content of LZGNo.2. The content of essential, non-essential, and total amino acids of JGNo.21 was increased under compound and nitrogen fertilizer treatments and decreased under organic and phosphorus fertilizer treatments. The content of essential, non-essential, and total amino acids of LZGNo.2 was significantly higher under compound, nitrogen, and organic fertilizer treatments compared with control and significantly decreased under phosphorus fertilizer treatments. Nitrogen and compound fertilizer treatments significantly reduced the values of peak viscosity, trough viscosity, breakdown viscosity, final viscosity, setback viscosity, and pasting time of each index of JGNo.21; phosphorus and organic fertilizer treatments improved the values of each index. In contrast, the pasting viscosity of LZGNo.2 increased under phosphorus fertilizer treatment and decreased under nitrogen fertilizer treatment. Reasonable fertilization can improve the quality of foxtail millet, which provides a scientific theoretical basis for improving the quality of foxtail millet.

Genome-wide chromatin accessibility reveals transcriptional regulation of heterosis in inter-subspecific hybrid rice.

The utilization of rice heterosis is essential for ensuring global food security; however, its molecular mechanism remains unclear. In this study, comprehensive analyses of accessible chromatin regions (ACRs), DNA methylation, and gene expression in inter-subspecific hybrid and its parents were performed to determine the potential role of chromatin accessibility in rice heterosis. The hybrid exhibited abundant ACRs, in which the gene ACRs and proximal ACRs were directly related to transcriptional activation rather than the distal ACRs. Regarding the dynamic accessibility contribution of the parents, paternal ZHF1015 transmitted a greater number of ACRs to the hybrid. Accessible genotype-specific target genes were enriched with overrepresented transcription factors, indicating a unique regulatory network of genes in the hybrid. Compared with its parents, the differentially accessible chromatin regions with upregulated chromatin accessibility were much greater than those with downregulated chromatin accessibility, reflecting a stronger regulation in the hybrid. Furthermore, DNA methylation levels were negatively correlated with ACR intensity, and genes were strongly affected by CHH methylation in the hybrid. Chromatin accessibility positively regulated the overall expression level of each genotype. ACR-related genes with maternal Z04A-bias allele-specific expression tended to be enriched during carotenoid biosynthesis, whereas paternal ZHF1015-bias genes were more active in carbohydrate metabolism. Our findings provide a new perspective on the mechanism of heterosis based on chromatin accessibility in inter-subspecific hybrid rice.

GSK3: A potential target and pending issues for treatment of Alzheimer's disease.

Glycogen synthase kinase-3 (GSK3), consisting of GSK3α and GSK3ß subtypes, is a complex protein kinase that regulates numerous substrates. Research has observed increased GSK3 expression in the brains of Alzheimer's disease (AD) patients and models. AD is a neurodegenerative disorder with diverse pathogenesis and notable cognitive impairments, characterized by Aß aggregation and excessive tau phosphorylation. This article provides an overview of GSK3's structure and regulation, extensively analyzing its relationship with AD factors. GSK3 overactivation disrupts neural growth, development, and function. It directly promotes tau phosphorylation, regulates amyloid precursor protein (APP) cleavage, leading to Aß formation, and directly or indirectly triggers neuroinflammation and oxidative damage. We also summarize preclinical research highlighting the inhibition of GSK3 activity as a primary therapeutic approach for AD. Finally, pending issues like the lack of highly specific and affinity-driven GSK3 inhibitors, are raised and expected to be addressed in future research. In conclusion, GSK3 represents a target in AD treatment, filled with hope, challenges, opportunities, and obstacles.

Flexible wearable sensors for crop monitoring: a review.

Crops were the main source of human food, which have met the increasingly diversified demand of consumers. Sensors were used to monitor crop phenotypes and environmental information in real time, which will provide a theoretical reference for optimizing crop growth environment, resisting biotic and abiotic stresses, and improve crop yield. Compared with non-contact monitoring methods such as optical imaging and remote sensing, wearable sensing technology had higher time and spatial resolution. However, the existing crop sensors were mainly rigid mechanical structures, which were easy to cause damage to crop organs, and there were still challenges in terms of accuracy and biosafety. Emerging flexible sensors had attracted wide attention in the field of crop phenotype monitoring due to their excellent mechanical properties and biocompatibility. The article introduced the key technologies involved in the preparation of flexible wearable sensors from the aspects of flexible preparation materials and advanced preparation processes. The monitoring function of flexible sensors in crop growth was highlighted, including the monitoring of crop nutrient, physiological, ecological and growth environment information. The monitoring principle, performance together with pros and cons of each sensor were analyzed. Furthermore, the future opportunities and challenges of flexible wearable devices in crop monitoring were discussed in detail from the aspects of new sensing theory, sensing materials, sensing structures, wireless power supply technology and agricultural sensor network, which will provide reference for smart agricultural management system based on crop flexible sensors, and realize efficient management of agricultural production and resources.

Exploring potential neuroimaging biomarkers for the response to non-steroidal anti-inflammatory drugs in episodic migraine.

BACKGROUND: Non-steroidal anti-inflammatory drugs (NSAIDs) are considered first-line medications for acute migraine attacks. However, the response exhibits considerable variability among individuals. Thus, this study aimed to explore a machine learning model based on the percentage of amplitude oscillations (PerAF) and gray matter volume (GMV) to predict the response to NSAIDs in migraine treatment. METHODS: Propensity score matching was adopted to match patients having migraine with response and nonresponse to NSAIDs, ensuring consistency in clinical characteristics and migraine-related features. Multimodal magnetic resonance imaging was employed to extract PerAF and GMV, followed by feature selection using the least absolute shrinkage and selection operator regression and recursive feature elimination algorithms. Multiple predictive models were constructed and the final model with the smallest predictive residuals was chosen. The model performance was evaluated using the area under the receiver operating characteristic (ROCAUC) curve, area under the precision-recall curve (PRAUC), balance accuracy (BACC), sensitivity, F1 score, positive predictive value (PPV), and negative predictive value (NPV). External validation was performed using a public database. Then, correlation analysis was performed between the neuroimaging predictors and clinical features in migraine. RESULTS: One hundred eighteen patients with migraine (59 responders and 59 non-responders) were enrolled. Six features (PerAF of left insula and left transverse temporal gyrus; and GMV of right superior frontal gyrus, left postcentral gyrus, right postcentral gyrus, and left precuneus) were observed. The random forest model with the lowest predictive residuals was selected and model metrics (ROCAUC, PRAUC, BACC, sensitivity, F1 score, PPV, and NPV) in the training and testing groups were 0.982, 0.983, 0.927, 0.976, 0.930, 0.889, and 0.973; and 0.711, 0.648, 0.639, 0.667,0.649, 0.632, and 0.647, respectively. The model metrics of external validation were 0.631, 0.651, 0.611, 0.808, 0.656, 0.553, and 0.706. Additionally, a significant positive correlation was found between the GMV of the left precuneus and attack time in non-responders. CONCLUSIONS: Our findings suggest the potential of multimodal neuroimaging features in predicting the efficacy of NSAIDs in migraine treatment and provide novel insights into the neural mechanisms underlying migraine and its optimized treatment strategy.

Neutrophil extracellular traps promote invasion and metastasis via NLRP3-mediated oral squamous cell carcinoma pyroptosis inhibition.

Neutrophil extracellular traps (NETs) are reticular structures composed of neutrophil elastase (NE), cathepsin G (CG) and DNA-histone enzyme complexes. Accumulating evidence has revealed that NETs play important roles in tumor progression, metastasis, and thrombosis. However, our understanding of its clinical value and mechanism of action in oral squamous cell carcinoma (OSCC) is limited and has not yet been systematically described. Here, we aimed to investigate the clinical significance of NETs in OSCC and the mechanisms by which they affect its invasive and metastatic capacity. Our results demonstrated that high enrichment of NETs is associated with poor prognosis in OSCC, and mechanistic studies have shown that NE in NETs promotes invasion and metastasis via NLRP3-mediated inhibition of pyroptosis in OSCC. These findings may provide a new therapeutic approach for OSCC.

Hyperspectral imaging combined with GA-SVM for maize variety identification.

The demand for identification of maize varieties has increased dramatically due to the phenomenon of mixed seeds and inferior varieties pretending to be high-quality varieties continuing to occur. It is urgent to solve the problem of efficient and accurate identification of maize varieties. A hyperspectral image acquisition system was used to acquire images of maize seeds. Regions of interest (ROI) with an embryo size of 10 × 10 pixel were extracted, and the average spectral information in the range of 949.43-1709.49 nm was intercepted for the subsequent study in order to eliminate random noise at both ends. Savitzky-Golay (SG) smoothing algorithm and multiple scattering correction (MSC) were used to pretreat the full-band spectrum. The feature wavelengths were screened by successive projection algorithms (SPA), competitive adaptive reweighted sampling (CARS) single screening, and two combinations of CARS-SPA and CARS + SPA, respectively. Support vector machines (SVMs) and models optimized based on genetic algorithm (GA), particle swarm optimization (PSO) were established by using full bands (FB) and feature bands as the model input. The results showed that the MSC-(CARS-SPA)-GA-SVM model had the best performance with 93.00% of the test set accuracy, 8 feature variables, and a running time of 24.45 s. MSC pretreatment can effectively eliminate the scattering effect of spectral data, and the feature wavelengths extracted by CARS-SPA can represent all wavelength information. The study proved that hyperspectral imaging combined with GA-SVM can realize the identification of maize varieties, which provided a theoretical basis for maize variety classification and authenticity identification.

Association analysis between an epigenetic risk score and blood pressure.

Background: Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results: We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions: Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.

BiU-net: A dual-branch structure based on two-stage fusion strategy for biomedical image segmentation.

BACKGROUND AND OBJECTIVE: Computer-based biomedical image segmentation plays a crucial role in planning of assisted diagnostics and therapy. However, due to the variable size and irregular shape of the segmentation target, it is still a challenge to construct an effective medical image segmentation structure. Recently, hybrid architectures based on convolutional neural networks (CNNs) and transformers were proposed. However, most current backbones directly replace one or all convolutional layers with transformer blocks, regardless of the semantic gap between features. Thus, how to sufficiently and effectively eliminate the semantic gap as well as combine the global and local information is a critical challenge. METHODS: To address the challenge, we propose a novel structure, called BiU-Net, which integrates CNNs and transformers with a two-stage fusion strategy. In the first fusion stage, called Single-Scale Fusion (SSF) stage, the encoding layers of the CNNs and transformers are coupled, with both having the same feature map size. The SSF stage aims to reconstruct local features based on CNNs and long-range information based on transformers in each encoding block. In the second stage, Multi-Scale Fusion (MSF), BiU-Net interacts with multi-scale features from various encoding layers to eliminate the semantic gap between deep and shallow layers. Furthermore, a Context-Aware Block (CAB) is embedded in the bottleneck to reinforce multi-scale features in the decoder. RESULTS: Experiments on four public datasets were conducted. On the BUSI dataset, our BiU-Net achieved 85.50 % on Dice coefficient (Dice), 76.73 % on intersection over union (IoU), and 97.23 % on accuracy (ACC). Compared to the state-of-the-art method, BiU-Net improves Dice by 1.17 %. For the Monuseg dataset, the proposed method attained the highest scores, reaching 80.27 % and 67.22 % for Dice and IoU. The BiU-Net achieves 95.33 % and 81.22 % Dice on the PH2 and DRIVE datasets. CONCLUSIONS: The results of our experiments showed that BiU-Net transcends existing state-of-the-art methods on four publicly available biomedical datasets. Due to the powerful multi-scale feature extraction ability, our proposed BiU-Net is a versatile medical image segmentation framework for various types of medical images. The source code is released on (https://github.com/ZYLandy/BiU-Net).

Identification of immunogenic cell death-related damage-related molecular patterns (DAMPs) to predict outcomes in patients with head and neck squamous cell carcinoma.

PURPOSE: Head and neck cancer is the sixth most common type of cancer worldwide, wherein the immune responses are closely associated with disease occurrence, development, and prognosis. Investigation of the role of immunogenic cell death-related genes (ICDGs) in adaptive immune response activation may provide cues into the mechanism underlying the outcome of HNSCC immunotherapy. METHODS: ICDGs expression patterns in HNSCC were analyzed, after which consensus clustering in HNSCC cohort conducted. A 4-gene prognostic model was constructed through LASSO and Cox regression analyses to analyze the prognostic index using the TCGA dataset, followed by validation with two GEO datasets. The distribution of immune cells and the response to immunotherapy were compared between different risk subtypes through multiple algorithms. Moreover, immunohistochemical (IHC) analyses were conducted to validate the prognostic value of HSP90AA1 as a predictor of HNSCC patient prognosis. In vitro assays were performed to further detect the effect of HSP90AA1 in the development of HNSCC. RESULTS: A novel prognostic index based on four ICDGs was constructed and proved to be useful as an independent factor of HNSCC prognosis. The risk score derived from this model grouped patients into high- and low-risk subtypes, wherein the high-risk subtype had worse survival outcomes and poorer immunotherapy response. IHC analysis validated the applicability of HSP90AA1 as a predictor of prognosis of HNSCC patients. HSP90AA1 expression in tumor cells promotes the progression of HNSCC. CONCLUSIONS: Together, these results highlight a novel four-gene prognostic signature as a valuable tool to assess survival status and prognosis of HNSCC patients.

Metabolic profile of follicular fluid in patients with ovarian endometriosis undergoing IVF: a pilot study.

RESEARCH QUESTION: What are the metabolic characteristics of follicular fluid in patients with ovarian endometriosis undergoing IVF? DESIGN: This was an exploratory cohort study on endometriosis. In total, 19 infertile patients with ovarian endometriosis diagnosed by laparoscopy, and 23 controls matched in terms of age and body mass index (women with infertility due to male or tubal factors) were enrolled in this study. All patients underwent IVF treatment with a gonadotrophin-releasing hormone antagonist protocol, and follicular fluid was collected at oocyte retrieval. The metabolomics of follicular fluid samples was analysed using an ultra-high-performance liquid chromatography Orbitrap Exploris mass spectrometer (UHPLC-OE-MS). The best combination of biomarkers was selected by performing stepwise logistic regression analysis with backward elimination. RESULTS: Fifteen metabolites were identified as biomarkers associated with endometriosis. A final model containing 8-hydroxy-2-deoxyguanosine, biotin, n-acetyl-L-methionine and n-methylnicotinamide was constructed. Receiver operating characteristic analysis confirmed the value of these parameters in diagnosing endometriosis, with sensitivity of 94.7% and specificity of 95.7%. Enrichment analysis via the Kyoto Encyclopedia of Genes and Genome showed that 15 metabolites were enriched in eight metabolic pathways. CONCLUSION: Metabolomics based on UHPLC-OE-MS effectively characterized the metabolomics analysis of follicular fluid in patients with ovarian endometriosis. These findings may provide a new basis for better understanding of how diseases progress, and for the discovery of new biomarkers.

Functional near-infrared spectroscopy-based diagnosis support system for distinguishing between mild and severe depression using machine learning approaches.

Significance: Early diagnosis of depression is crucial for effective treatment. Our study utilizes functional near-infrared spectroscopy (fNIRS) and machine learning to accurately classify mild and severe depression, providing an objective auxiliary diagnostic tool for mental health workers. Aim: Develop prediction models to distinguish between severe and mild depression using fNIRS data. Approach: We collected the fNIRS data from 140 subjects and applied a complete ensemble empirical mode decomposition with an adaptive noise-wavelet threshold combined denoising method (CEEMDAN-WPT) to remove noise during the verbal fluency task. The temporal features (TF) and correlation features (CF) from 18 prefrontal lobe channels of subjects were extracted as predictors. Using recursive feature elimination with cross-validation, we identified optimal TF or CF and examined their role in distinguishing between severe and mild depression. Machine learning algorithms were used for classification. Results: The combination of TF and CF as inputs for the prediction model yielded higher classification accuracy than using either TF or CF alone. Among the prediction models, the SVM-based model demonstrates excellent performance in nested cross-validation, achieving an accuracy rate of 92.8%. Conclusions: The proposed model can effectively distinguish mild depression from severe depression.

Gut microbiota and female health.

The gut microbiota is recognized as an endocrine organ with the capacity to influence distant organs and associated biological pathways. Recent advancements underscore the critical role of gut microbial homeostasis in female health; with dysbiosis potentially leading to diseases among women such as polycystic ovarian syndrome, endometriosis, breast cancer, cervical cancer, and ovarian cancer etc. Despite this, there has been limited discussion on the underlying mechanisms. This editorial explores the three potential mechanisms through which gut microbiota dysbiosis may impact the development of diseases among women, namely, the immune system, the gut microbiota-estrogen axis, and the metabolite pathway. We focused on approaches for treating diseases in women by addressing gut microbiota imbalances through probiotics, prebiotics supplementation, and fecal microbiota transplantation (FMT). Future studies should focus on determining the molecular mechanisms underlying associations between dysbiosis of gut microbiota and female diseases to realize precision medicine, with FMT emerging as a promising intervention.

Boosting the immunogenicity of the CoronaVac SARS-CoV-2 inactivated vaccine with Huoxiang Suling Shuanghua Decoction: a randomized, double-blind, placebo-controlled study.

Introduction: In light of the public health burden of the COVID-19 pandemic, boosting the safety and immunogenicity of COVID-19 vaccines is of great concern. Numerous Traditional Chinese medicine (TCM) preparations have shown to beneficially modulate immunity. Based on pilot experiments in mice that showed that supplementation with Huoxiang Suling Shuanghua Decoction (HSSD) significantly enhances serum anti-RBD IgG titers after inoculation with recombinant SARS-CoV-2 S-RBD protein, we conducted this randomized, double-blind, placebo-controlled clinical trial aimed to evaluate the potential immunogenicity boosting effect of oral HSSD after a third homologous immunization with Sinovac's CoronaVac SARS-CoV-2 (CVS) inactivated vaccine. Methods: A total of 70 participants were randomly assigned (1:1 ratio) to receive a third dose of CVS vaccination and either oral placebo or oral HSSD for 7 days. Safety aspects were assessed by recording local and systemic adverse events, and by blood and urine biochemistry and liver and kidney function tests. Main outcomes evaluated included serum anti-RBD IgG titer, T lymphocyte subsets, serum IgG and IgM levels, complement components (C3 and C4), and serum cytokines (IL-6 and IFN-γ). In addition, metabolomics technology was used to analyze differential metabolite expression after supplementation with HSSD. Results: Following a third CVS vaccination, significantly increased serum anti-RBD IgG titer, reduced serum IL-6 levels, increased serum IgG, IgM, and C3 and C4 levels, and improved cellular immunity, evidenced by reduce balance deviations in the distribution of lymphocyte subsets, was observed in the HSSD group compared with the placebo group. No serious adverse events were recorded in either group. Serum metabolomics results suggested that the mechanisms by which HSSD boosted the immunogenicity of the CVS vaccine are related to differential regulation of purine metabolism, vitamin B6 metabolism, folate biosynthesis, arginine and proline metabolism, and steroid hormone biosynthesis. Conclusion: Oral HSSD boosts the immunogenicity of the CVS vaccine in young and adult individuals. This trial provides clinical reference for evaluation of TCM immunomodulators to improve the immune response to COVID-19 vaccines.

Fabrication of amino- and hydroxyl dual-functionalized magnetic microporous organic network for extraction of zearalenone from traditional Chinese medicine prior to the HPLC determination.

Efficient enrichment of trace zearalenone (ZEN) from the complex traditional Chinese medicine (TCM) samples is quite difficult, but of great significance for TCM quality control. Herein, we reported a novel magnetic solid phase extraction (MSPE) strategy for ZEN enrichment using the amino- and hydroxyl dual-functionalized magnetic microporous organic network (Fe3O4@MON-NH2-OH) as an advanced adsorbent combined with the high-performance liquid chromatography (HPLC) determination. Efficient extraction of ZEN was achieved via the possible hydrogen bonding, hydrophobic, and π-π interactions between Fe3O4@MON-NH2-OH and ZEN. The adsorption capacity of Fe3O4@MON-NH2-OH for ZEN was 215.0 mg g-1 at the room temperature, which was much higher than most of the reported adsorbents. Under the optimal condition, the developed Fe3O4@MON-NH2-OH-MSPE-HPLC method exhibited wide linear range (5-2500 µg L-1), low limits of detection (1.4-35 µg L-1), less adsorbent consumption (5 mg), and large enhancement factor (95) for ZEN. The proposed method was successfully applied to detect trace ZEN from 10 kinds of real TCM samples. Conclusively, this work demonstrates the Fe3O4@MON-NH2-OH can effectively extract trace ZEN from the complex TCM matrices, which may open up a new way for the application of MONs in the enrichment and extraction of trace contaminants or active constituents from the complex TCM samples.

Molecularly Imprinted Electrochemical Sensor Based on α-Cyclodextrin Inclusion Complex and MXene Modification for Highly Sensitive and Selective Detection of Alkylresorcinols in Whole Wheat Foods.

Authenticating whole wheat foods poses a significant challenge for both the grain industry and consumers. Alkylresorcinols (ARs), serving as biomarkers of whole wheat, play a crucial role in assessing the authenticity of whole wheat foods. Herein, we introduce a novel molecularly imprinted electrochemical sensor with modifications involving a molecularly imprinted polymer (MIP) and MXene nanosheets, enabling highly sensitive and selective detection of ARs. Notably, we specifically chose 5-heneicosylresorcinol (AR21), the predominant homologue in whole wheat, as the template molecule. α-Cyclodextrin and acrylamide served as dual functional monomers, establishing a robust multiple interaction between the MIP and AR21. As a result, the sensor exhibited a wide linear range of 0.005 to 100 µg·mL-1 and a low detection limit of 2.52 ng·mL-1, demonstrating exceptional selectivity and stability. When applied to commercial whole wheat foods, the assay achieved satisfactory recoveries and accuracy, strongly validating the practicality and effectiveness of this analytical technique.

[Association of polymorphisms in SEC16B, DNAJC27, FTO and MC4R genes with overweight and obesity in Han preschool children].

OBJECTIVE: To investigate the association of polymorphisms in SEC16B rs633715, DNAJC27 rs713586, FTO rs11642015 and MC4R rs6567160 with overweight and obesity in Han Chinese preschool children. METHODS: A total of 749 Han Chinese preschool children from Henan and Guizhou Province of Long-term Health Effects Assessment Project of Infants and Toddlers Nutritional Pack were selected for the study and divided into an overweight and obese group and a normal control group in 2022. rs633715, rs713586, rs11642015 and rs6567160 were genotyped using Kompetitive allele-specific PCR(KASP) technology. The distribution of genotypic polymorphisms was compared using the χ~2 test. The association between the four loci and overweight and obesity in preschool children was analyzed using a multifactorial logistic regression model. RESULTS: The statistical analysis revealed a significant disparity(P<0.05) in the distribution of genotypic polymorphisms of rs633715 and rs6567160 among preschoolers in Henan and Guizhou Province. CC heterozygous mutant and recessive models at rs633715 locus were associated with susceptibility to overweight and obesity in preschool children [OR and 95% CI 2.915(1.163-7.305), and 2.997(1.226-7.323), respectively, both P<0.05]. TC heterozygous mutant and dominant models at rs713586 locus were also associated susceptibility to overweight and obesity in preschool children(OR and 95% CI were 2.362(1.054-5.289)and 2.362(1.054-5.289), respectively, both P<0.05). rs11642015 and rs6567160 loci were not associated with susceptibility to overweight and obesity in preschool children(P>0.05). The result of the analysis of the cumulative effect of rs633715 and rs713586 showed that the number of genotypes carrying the risk genotype was positively associated with the risk of overweight and obesity in preschool children(P_(trend)<0.01). CONCLUSION: Among Han Chinese preschool children, SEC16B rs633715 and DNAJC27 rs713586 were associated with susceptibility to overweight and obesity in preschool children. Moreover, rs633715 and rs713586 had a cumulative effect on susceptibility to overweight and obesity in preschool children, the number of risk genotypes carried was positively associated with childhood overweight and obesity risk.

Adsorption properties and mechanism of Cu(II) on virgin and aged microplastics in the aquatic environment.

Microplastics (MPs) migrate by adsorbing heavy metals in aquatic environments and act as their carriers. However, the aging mechanisms of MPs in the environment and the interactions between MPs and heavy metals in aquatic environments require further study. In this study, two kinds of materials, polyamide (PA) and polylactic acid (PLA) were used as target MPs, and the effects of UV irradiation on the physical and chemical properties of the MPs and the adsorption behavior of Cu(II) were investigated. The results showed that after UV irradiation, pits, folds and pores appeared on the surface of aged MPs, the specific surface area (SSA) increased, the content of oxygen-containing functional groups increased, and the crystallinity decreased. These changes enhanced the adsorption capacity of aged MPs for Cu(II) pollutants. The adsorption behavior of the PA and PLA MPs for Cu(II) conformed to the pseudo-second-order model and Langmuir isotherm model, indicating that the monolayer chemical adsorption was dominant. The maximum amounts of aged PA and PLA reached 1.415 and 1.398 mg/g, respectively, which were 1.59 and 1.76 times of virgin MPs, respectively. The effects of pH and salinity on the adsorption of Cu(II) by the MPs were significant. Moreover, factors such as pH, salinity and dosage had significant effects on the adsorption of Cu(II) by MPs. Oxidative complexation between the oxygen-containing groups of the MPs and Cu(II) is an important adsorption mechanism. These findings reveal that the UV irradiation aging of MPs can enhance the adsorption of Cu(II) and increase their role as pollutant carriers, which is crucial for assessing the ecological risk of MPs and heavy metals coexisting in aquatic environments.

Comparing visible and near infrared 'point' spectroscopy and hyperspectral imaging techniques to visualize the variability of apple firmness.

In this work, visible and near-infrared 'point' (Vis-NIR) spectroscopy and hyperspectral imaging (Vis-NIR-HSI) techniques were applied on three different apple cultivars to compare their firmness prediction performances based on a large intra-variability of individual fruit, and develop rapid and simple models to visualize the variability of apple firmness on three apple cultivars. Apples with high degree of intra-variability can strongly affect the prediction model performances. The apple firmness prediction accuracy can be improved based on the large intra-variability samples with the coefficient variation (CV) values over 10%. The least squares-support vector machine (LS-SVM) models based on Vis-NIR-HSI spectra had better performances for firmness prediction than that of Vis-NIR spectroscopy, with the with the Rc2 over 0.84. Finally, The Vis-NIR-HSI technique combined with least squares-support vector machine (LS-SVM) models were successfully applied to visualize the spatial the variability of apple firmness.