Genome-Wide Identification and Analysis of the EIN3/EIL Transcription Factor Gene Family in Doubled Haploid (DH) Poplar.

Ethylene (ET) is an important phytohormone that regulates plant growth, development and stress responses. The ethylene-insensitive3/ethylene-insensitive3-like (EIN3/EIL) transcription factor family, as a key regulator of the ET signal transduction pathway, plays an important role in regulating the expression of ET-responsive genes. Although studies of EIN3/EIL family members have been completed in many species, their role in doubled haploid (DH) poplar derived from another culture of diploid Populus simonii × P. nigra (donor tree, DT) remains ambiguous. In this study, a total of seven EIN3/EIL gene family members in the DH poplar genome were identified. Basic physical and chemical property analyses of these genes were performed, and these proteins were predicted to be localized to the nucleus. According to the phylogenetic relationship, EIN3/EIL genes were divided into two groups, and the genes in the same group had a similar gene structure and conserved motifs. The expression patterns of EIN3/EIL genes in the apical buds of different DH poplar plants were analyzed based on transcriptome data. At the same time, the expression patterns of PsnEIL1, PsnEIN3, PsnEIL4 and PsnEIL5 genes in different tissues of different DH plants were detected via RT-qPCR, including the apical buds, young leaves, functional leaves, xylem, cambium and roots. The findings presented above indicate notable variations in the expression levels of PsnEIL genes across various tissues of distinct DH plants. Finally, the PsnEIL1 gene was overexpressed in DT, and the transgenic plants showed a dwarf phenotype, indicating that the PsnEIL1 gene was involved in regulating the growth and development of poplar. In this study, the EIN3/EIL gene family of DH poplar was analyzed and functionally characterized, which provides a theoretical basis for the future exploration of the EIN3/EIL gene function.

Stability mechanism of Monascus pigment-soy protein isolate-maltodextrin complex.

BACKGROUND: Monascus pigment (MP) is a natural food coloring with vital physiological functions but prone to degradation and color fading under light conditions. RESULTS: This study investigated the effect of complex formation of soybean protein isolate (SPI), maltodextrin (MD), and MP on the photostability of MP. Light stability was assessed through retention rate and color difference. Fluorescence spectroscopy (FS), circular dichroism (CD), Fourier-transform infrared (FTIR) spectroscopy, and X-ray diffraction (XRD) explored MP, SPI, and MD interactions, clarifying the MP-SPI-MD complex mechanism on the light stability of MP. Microstructure and differential scanning calorimetry (DSC) analyzed the morphology and thermal properties. The retention rate of MP increased to approximately 80%, and minimal color difference was observed when adding SPI and MD simultaneously. FS revealed hydrophobic interaction between MP and SPI. FTIR analysis showed intensity changes and peak shifts in amide I band and amide II band, which proved the hydrophobic interaction. CD showed a decrease in α-helix content and an increase in ß-sheet content after complex formation, indicating strengthened hydrogen bonding interactions. Scanning electron microscopy (SEM) analysis demonstrated that MP was attached to the surface and interior of complexes. XRD showed MP as crystalline, while SPI and MD were amorphous, complexes exhibited weakened or absent peaks, suggesting MP encapsulation. The results of DSC were consistent with XRD. CONCLUSION: SPI and MD enveloped MP through hydrogen bonding and hydrophobic interaction, ultimately enhancing its light stability and providing insights for pigment-protein-polysaccharide interactions and improving pigment stability in the food industry. © 2024 Society of Chemical Industry.

Significance Analysis of the Improvement in Postoperative Recovery of Cardiac Surgery Patients Based on the Graded Management Established Using the Delirium Prediction Model.

Objective: To investigate the impact of graded management based on delirium prediction modeling on the improvement of recovery of cardiac surgery patients. Methods: Three hundred and twenty patients admitted to the Department of Critical Care Medicine of Nanjing Hospital affiliated with Nanjing Medical University from June 2021 to December 2023 after Type A aortic coarctation were selected as study subjects. They were grouped according to the randomized scale method and divided into 160 cases in each the control group and the observation group. In the control group, conventional nursing measures were adopted, and in the observation group, graded nursing interventions were carried out according to the established delirium risk prediction model. Comparison between the two groups in terms of the intensive care unit (ICU) monitoring time, hospitalization time, duration of delirium, and delirium incidence, and investigated nursing satisfaction, and quality of care scores. Results: Compared with the control group, the observation group's ICU custody time, hospitalization time, and delirium duration, decreased, and the quality of care, and satisfaction increased (P < .05). At the same time, the incidence of delirium in the observation group was also lower than that in the control group (P < .05). Conclusion: The graded management based on the delirium prediction model can effectively reduce the incidence of postoperative delirium in critically ill patients with Type A aortic coarctation, and at the same time improve patient satisfaction and quality of care.

Role of Multi-parameter-based Cardiac Magnetic Resonance in the Evaluation of Patients with Coronary Heart Disease Combined with Heart Failure.

BACKGROUND: Coronary Heart Disease (CHD) is one of the most common types of cardiovascular disease, and Heart Failure (HF) is an important factor in its progression. We aimed to evaluate the diagnostic value and predictors of multiparametric Cardiac Magnetic Resonance (CMR) in CHD patients with HF. METHODS: The study retrospectively included 145 CHD patients who were classified into CHD (HF+) (n = 91) and CHD (HF-) (n = 54) groups according to whether HF occurred. CMR assessed LV function, myocardial strain and T1 mapping. Multivariate linear regression analyses were performed to identify predictors of LV dysfunction, myocardial fibrosis, and LV remodeling. RESULTS: CHD (HF+) group had impaired strain, with increased native T1, ECV, and LVM index. The impaired strain was associated with LVM index (p < 0.05), where native T1 and ECV were affected by log-transformed amino-terminal pro-B-type natriuretic peptide (NT-proBNP) levels. ROC analysis showed the combination of global circumferential strain (GCS), native T1, and LVM had a higher diagnostic value for the occurrence of HF in CHD patients.

Meanwhile, log-transformed NT-proBNP was an independent determinant of impaired strain, increased LVM index, native T1 and ECV. CONCLUSION: HF has harmful effects on LV systolic function in patients with CHD. In CHD (HF+) group, LV dysfunction is strongly correlated with the degree of LV remodeling and myocardial fibrosis. The combination of the three is more valuable in diagnosing HF than conventional indicators.

A Three-Wavelength Optical Sensor for Measuring the Multi-Particle-Size Channel Mass Concentration of Thermal Power Plant Emissions.

Emissions from thermal power plants have always been the central consideration for environmental protection. Existing optical sensors in thermal power plants usually measure the total mass concentration of the particulate matter (PM) by a single-wavelength laser, bearing intrinsic errors owing to the variation in particle size distribution (PSD). However, the total mass concentration alone cannot characterize all the harmful effects of the air pollution caused by the power plant. Therefore, it is necessary to measure the mass concentration and PSD simultaneously, based on which we can obtain multi-particle-size channel mass concentration. To achieve this, we designed an optical sensor based on the three-wavelength technique and tested its performance in a practical environment. Results showed that the prototype cannot only correctly measure the mass concentration of the emitted PM but also determine the mean diameter and standard deviation of the PSDs. Hence, the mass concentrations of PM10, PM2.5, and PM1 are calculated, and the air pollutants emission by a thermal power plant can be estimated comprehensively.

Nanogel delivery systems for cationic peptides: More than a 'One Size Fits All' solution.

Self-assembled hyaluronic acid-based nanogels are versatile drug carriers due to their biodegradable nature and gentle preparation conditions, making them particularly interesting for delivery of peptide therapeutics. This study aims to elucidate the relation between peptide structure and encapsulation in a nanogel. Key peptide properties that affect encapsulation in octenyl succinic anhydride-modified hyaluronic acid nanogels were identified as we explored the effect on nanogel characteristics using 12 peptides with varying charge and hydrophobicity. The size and surface properties of the microfluidics-assembled peptide-loaded nanogels were evaluated using dynamic light scattering, laser Doppler electrophoresis, and small angle neutron scattering. Additionally, the change in peptide secondary structure upon encapsulation in nanogels, their release from the nanogels, and the in vitro antimicrobial activity were assessed. In conclusion, the more hydrophobic peptides showed stronger binding to the nanogel carrier and localized internally rather than on the surface of the nanogel, resulting in more spherical nanogels with smoother surfaces and slower release profiles. In contrast, cationic and hydrophilic peptides localized at the nanogel surface resulting in fluffier nanogel structures and quick and more complete release in biorelevant medium. These findings emphasize that the advantages of nanogel delivery systems for different applications depend on the therapeutic peptide properties.

Application of valence-variable transition-metal-oxide-based nanomaterials in electrochemical analysis: A review.

The construction of materials with rapid electron transfer is considered an effective method for enhancing electrochemical activity in electroanalysis. It has been widely demonstrated that valence changes in transition metal ions can promote electron transfer and thus increase electrochemical activity. Recently, valence-variable transition metal oxides (TMOs) have shown popular application in electrochemical analysis by using their abundant valence state changes to accelerate electron transfer during electrochemical detection. In this review, we summarize recent research advances in valence changes of TMOs and their application in electrochemical analysis. This includes the definition and mechanism of valence change, the association of valence changes with electronic structure, and their applications in electrochemical detection, along with the use of density functional theory (DFT) to simulate the process of electron transfer during valence changes. Finally, the challenges and opportunities for developing and applying valence changes in electrochemical analysis are also identified.

scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species.

Chromatin accessibility profiles at single cell resolution can reveal cell type-specific regulatory programs, help dissect highly specialized cell functions and trace cell origin and evolution. Accurate cell type assignment is critical for effectively gaining biological and pathological insights, but is difficult in scATAC-seq. Hence, by extensively reviewing the literature, we designed scATAC-Ref (https://bio.liclab.net/scATAC-Ref/), a manually curated scATAC-seq database aimed at providing a comprehensive, high-quality source of chromatin accessibility profiles with known cell labels across broad cell types. Currently, scATAC-Ref comprises 1 694 372 cells with known cell labels, across various biological conditions, >400 cell/tissue types and five species. We used uniform system environment and software parameters to perform comprehensive downstream analysis on these chromatin accessibility profiles with known labels, including gene activity score, TF enrichment score, differential chromatin accessibility regions, pathway/GO term enrichment analysis and co-accessibility interactions. The scATAC-Ref also provided a user-friendly interface to query, browse and visualize cell types of interest, thereby providing a valuable resource for exploring epigenetic regulation in different tissues and cell types.

KnockTF 2.0: a comprehensive gene expression profile database with knockdown/knockout of transcription (co-)factors in multiple species.

Transcription factors (TFs), transcription co-factors (TcoFs) and their target genes perform essential functions in diseases and biological processes. KnockTF 2.0 (http://www.licpathway.net/KnockTF/index.html) aims to provide comprehensive gene expression profile datasets before/after T(co)F knockdown/knockout across multiple tissue/cell types of different species. Compared with KnockTF 1.0, KnockTF 2.0 has the following improvements: (i) Newly added T(co)F knockdown/knockout datasets in mice, Arabidopsis thaliana and Zea mays and also an expanded scale of datasets in humans. Currently, KnockTF 2.0 stores 1468 manually curated RNA-seq and microarray datasets associated with 612 TFs and 172 TcoFs disrupted by different knockdown/knockout techniques, which are 2.5 times larger than those of KnockTF 1.0. (ii) Newly added (epi)genetic annotations for T(co)F target genes in humans and mice, such as super-enhancers, common SNPs, methylation sites and chromatin interactions. (iii) Newly embedded and updated search and analysis tools, including T(co)F Enrichment (GSEA), Pathway Downstream Analysis and Search by Target Gene (BLAST). KnockTF 2.0 is a comprehensive update of KnockTF 1.0, which provides more T(co)F knockdown/knockout datasets and (epi)genetic annotations across multiple species than KnockTF 1.0. KnockTF 2.0 facilitates not only the identification of functional T(co)Fs and target genes but also the investigation of their roles in the physiological and pathological processes.

LncSEA 2.0: an updated platform for long non-coding RNA related sets and enrichment analysis.

Long non-coding RNAs (lncRNAs) possess a wide range of biological functions, and research has demonstrated their significance in regulating major biological processes such as development, differentiation, and immune response. The accelerating accumulation of lncRNA research has greatly expanded our understanding of lncRNA functions. Here, we introduce LncSEA 2.0 (http://bio.liclab.net/LncSEA/index.php), aiming to provide a more comprehensive set of functional lncRNAs and enhanced enrichment analysis capabilities. Compared with LncSEA 1.0, we have made the following improvements: (i) We updated the lncRNA sets for 11 categories and extremely expanded the lncRNA scopes for each set. (ii) We newly introduced 15 functional lncRNA categories from multiple resources. This update not only included a significant amount of downstream regulatory data for lncRNAs, but also covered numerous epigenetic regulatory data sets, including lncRNA-related transcription co-factor binding, chromatin regulator binding, and chromatin interaction data. (iii) We incorporated two new lncRNA set enrichment analysis functions based on GSEA and GSVA. (iv) We adopted the snakemake analysis pipeline to track data processing and analysis. In summary, LncSEA 2.0 offers a more comprehensive collection of lncRNA sets and a greater variety of enrichment analysis modules, assisting researchers in a more comprehensive study of the functional mechanisms of lncRNAs.

Tai Chi Effects on Heart Rate Variability: A Systematic Review and Meta-Analysis.

Background: Tai Chi, originating in China, is a mind-body exercise that integrates mind training, Qi training, and body training. While Tai Chi practice has demonstrated beneficial physical and psychological health benefits, how it achieves effects has been less studied. In recent years, some researchers have begun to explore the potential of heart rate variability (HRV) changes as balancing the autonomic nervous system (ANS) to achieve results, but only a few studies have directly tested how Tai Chi impacts HRV, and results have been mixed. Objective: This study systematically evaluates the effects of Tai Chi on HRV. Methods: Electronic databases including Web of Science, PubMed, Scopus, Cochrane Library, and EBSCOhost direct from inception until December 2020 were searched to obtain eligible studies. The primary outcomes examined were HRV parameters (time domain and frequency domain), and secondary analysis was whether breathing was emphasized during Tai Chi interventions. Results: Based on the 11 randomized controlled trials included comparing Tai Chi with non-active control condition, meta-analyses showed significantly beneficial effects on HRV parameters (low-frequency power [LF], mean difference [MD] = -200.40, 95% confidence interval [CI]: 365.31 to -35.49, p = 0.02; normalized low-frequency power [nLF], MD = -7.39, 95% CI: -12.48 to -2.29, p = 0.004; total power [TP], MD = -649.82, 95% CI: -1180.54 to -119.11, p = 0.02; very low-frequency power [VLF], MD = -200.55, 95% CI: -349.63 to -51.46, p = 0.008; root mean square of the square sum of the difference between adjacent normal heartbeat intervals [RMSSD], MD = 2.59, 95% CI: -7.23 to 12.41, p < 0.0001; standard deviation of the heartbeat interval [SDNN], MD = 8.33, 95% CI: 0.69 to 15.98, p = 0.03). The effect of Tai Chi on certain HRV parameters compared with active control conditions was less favorable (nLF, MD = 6.42, 95% CI: 3.74 to 9.09, p < 0.00001; normalized high-frequency power [nHF], MD: -6.13, 95% CI: -8.76 to -3.50, p < 0.00001; low-frequency/high-frequency power ratio [LF/HF], MD = 1.00, 95% CI: 0.68 to 1.33, p < 0.00001). In addition, studies describing an emphasis on breathing in the Tai Chi intervention showed positive impact on HRV (nLF, MD = -3.22, 95% CI: -5.32 to -1.12, p = 0.003; nHF, MD = 3.80, 95% CI: 0.80 to 6.81, p = 0.01; SDNN, MD = 5.55, 95% CI: 4.85 to 6.25, p < 0.00001). Conclusions: Meta-analysis results showed that Tai Chi compared with non-active control conditions has a positive impact on key HRV parameters associated with the ANS balance. However, active control condition comparisons showed greater HRV improvements than for Tai Chi. Considering the limited number of studies and their heterogeneity, further robust studies are necessary to verify findings and investigate differential effects of Tai Chi on HRV.

SCInter: A comprehensive single-cell transcriptome integration database for human and mouse.

Single-cell RNA sequencing (scRNA-seq), which profiles gene expression at the cellular level, has effectively explored cell heterogeneity and reconstructed developmental trajectories. With the increasing research on diseases and biological processes, scRNA-seq datasets are accumulating rapidly, highlighting the urgent need for collecting and processing these data to support comprehensive and effective annotation and analysis. Here, we have developed a comprehensive Single-Cell transcriptome integration database for human and mouse (SCInter, https://bio.liclab.net/SCInter/index.php), which aims to provide a manually curated database that supports the provision of gene expression profiles across various cell types at the sample level. The current version of SCInter includes 115 integrated datasets and 1016 samples, covering nearly 150 tissues/cell lines. It contains 8016,646 cell markers in 457 identified cell types. SCInter enabled comprehensive analysis of cataloged single-cell data encompassing quality control (QC), clustering, cell markers, multi-method cell type automatic annotation, predicting cell differentiation trajectories and so on. At the same time, SCInter provided a user-friendly interface to query, browse, analyze and visualize each integrated dataset and single cell sample, along with comprehensive QC reports and processing results. It will facilitate the identification of cell type in different cell subpopulations and explore developmental trajectories, enhancing the study of cell heterogeneity in the fields of immunology and oncology.

The Peptide AWRK6 Alleviates Lipid Accumulation in Hepatocytes by Inhibiting miR-5100 Targeting G6PC.

Non-alcoholic fatty liver disease (NAFLD) is the leading chronic liver disease, with a worldwide prevalence of more than 25%, and there is no approved drug for NAFLD specifically. In our previous study, the synthetic peptide AWRK6 was found to ameliorate NAFLD in mice. However, the mechanisms involved are still largely unknown. Here, AWRK6 treatment presented an alleviative effect on lipid accumulation induced by oleic acid in hepatocytes. Meanwhile, miR-5100 and miR-505 were found to be elevated by oleic acid induction and reversed by AWRK6 incubation. Further, the miR-5100 inhibitor inhibited oleic acid-induced lipid accumulation, and the alleviation effect of AWRK6 was partially counteracted by miR-5100 mimics. The screening of potential target genes revealed that a catalytic subunit of G6Pase G6PC was significantly inhibited by miR-5100 mimics transfection in both mRNA and protein levels. The direct targeting of miR-5100 on G6PC was verified by a Dual-Luciferase Reporter Assay. Moreover, the mRNA and protein levels of G6PC were found to be significantly increased by AWRK6 treatment. These results suggested that the peptide AWRK6 could alleviate lipid accumulation in hepatocytes, partly through reducing miR-5100 to restore one of its targets: G6PC. Thus, AWRK6 has the potential to treat NAFLD. Additionally, miR-5100 is a mediator of lipid accumulation in hepatocytes, which could be targeted by AWRK6.

Sensitive sensing of Hg(II) based on lattice B and surface F co-doped CeO2: Synergies of catalysis and adsorption brought by doping site engineering.

Transition metal oxides are widely used in the detection of heavy metal ions (HMIs), and the co-doping strategy that introducing a variety of different dopant atoms to modify them can obtain a better detection performance. However, there is very little research on the co-doped transition metal oxides by non-metallic elements for electrochemical detection. Herein, boron (B) and fluorine (F) co-doped CeO2 nanomaterial (BFC) is constructed to serve as the electrochemically sensitive interface for the detection of Hg(II). B and F affect the sensitivity of CeO2 to HMIs when they were introduced at different doping sites. Through a variety of characterization, it is proved that B is successfully doped into the lattice and F is doped on the surface of the material. Through the improvement of the catalytic properties and adsorption capacity of CeO2 by different doping sites, this B and F co-doped CeO2 exhibits excellent square wave anodic stripping voltammetry (SWASV) current responses to Hg(II). Both the high sensitivity of 906.99 µA µM-1 cm-2 and the low limit of detection (LOD) of 0.006 µM are satisfactory. Besides, this BFC glassy carbon electrode (GCE) also has good anti-interference property, which has been successfully used in the detection of Hg(II) in actual water. This discovery provides a useful strategy for designing a variety of non-metallic co-doped transition metal oxides to construct trace heavy metal ion-sensitive interfaces.

Microglia-derived CCL20 deteriorates neurogenesis following intraventricular hemorrhage.

Intraventricular hemorrhage (IVH) commonly occurs as an extension of intracerebral hemorrhage (ICH) into the brain ventricular system, leading to worse outcomes without effective management. Using a mouse model of IVH, we found that impaired neurogenesis is evident in the subventricular zone (SVZ), along with persistent microglia activation, leukocyte infiltration and cell death. Pharmacological depletion of microglia using PLX3397, an inhibitor of colony stimulating factor 1 receptor (CSF1R), promotes neurogenesis, and alleviated delayed functional impairments in IVH mice. Meanwhile, an elevated level of microglia-derived CC chemokine ligand 20 (CCL20) is observed in the SVZ following IVH, which can induce the upregulation of pro-inflammatory factors in microglia and impair the proliferation and survival of neural stem cells (NSCs) in vitro. Blocking CCL20 in microglia leads to downregulation of protein kinase B (Akt)/mammalian target of rapamycin (mTOR)/the nuclear factor-κB (NF-κB) signaling pathway, which may contribute to CCL20-dependent pro-inflammatory responses and neural injury. These findings demonstrate a detrimental role of microglia in the neurogenesis and neurorepair after IVH in which CCL20 likely plays a role.

Synergetic Role of Thermal Catalysis and Photocatalysis in CO2 Reduction on Cu2/MoS2.

Effective activation of CO2 is a primarily challenging issue in CO2 reduction to value-added hydrocarbon chemicals, due to the large energy gap between the highest-occupied and lowest-unoccupied molecular orbitals (HOMO-LUMO). Here, we employ state-of-the-art first-principles calculations to explore the synergetic role of thermal catalysis and photocatalysis in CO2 reduction, on typical single-atom scale catalyst, i.e., Cu2 magic cluster on a semiconducting two-dimensional MoS2 substrate. It is identified that only about 1% of the hot electrons excited from the MoS2 substrate by at least 6.3 eV photons may be trapped by the inert CO2 molecule at the expense of 400 fs. Moreover, the physisorption-to-chemisorption transition of CO2 can be observed within 500 fs upon overcoming an about 0.05 eV energy barrier. Contrastingly, upon chemisorption, the activated CO2δ- species may trap about 7% of the hot electron excited from the MoS2 substrate by about 2.5 eV visible photons, with a cost of 140 fs.

Cis-Cardio: A comprehensive analysis platform for cardiovascular-relavant cis-regulation in human and mouse.

Cis-regulatory elements are important molecular switches in controlling gene expression and are regarded as determinant hubs in the transcriptional regulatory network. Collection and processing of large-scale cis-regulatory data are urgent to decipher the potential mechanisms of cardiovascular diseases from a cis-regulatory element aspect. Here, we developed a novel web server, Cis-Cardio, which aims to document a large number of available cardiovascular-related cis-regulatory data and to provide analysis for unveiling the comprehensive mechanisms at a cis-regulation level. The current version of Cis-Cardio catalogs a total of 45,382,361 genomic regions from 1,013 human and mouse epigenetic datasets, including ATAC-seq, DNase-seq, Histone ChIP-seq, TF/TcoF ChIP-seq, RNA polymerase ChIP-seq, and Cohesin ChIP-seq. Importantly, Cis-Cardio provides six analysis tools, including region overlap analysis, element upstream/downstream analysis, transcription regulator enrichment analysis, variant interpretation, and protein-protein interaction-based co-regulatory analysis. Additionally, Cis-Cardio provides detailed and abundant (epi-) genetic annotations in cis-regulatory regions, such as super-enhancers, enhancers, transcription factor binding sites (TFBSs), methylation sites, common SNPs, risk SNPs, expression quantitative trait loci (eQTLs), motifs, DNase I hypersensitive sites (DHSs), and 3D chromatin interactions. In summary, Cis-Cardio is a valuable resource for elucidating and analyzing regulatory cues of cardiovascular-specific cis-regulatory elements. The platform is freely available at http://www.licpathway.net/Cis-Cardio/index.html.

Dietary intervention reprograms bone marrow cellular signaling in obese mice.

Objectives: The current study aimed to investigate the pathogenesis of obesity-induced impaired bone mass accrual and the impact of dietary intervention on bone density in the mouse model of obesity. Methods: Mice were fed with chow diet (CD) for 10 months, high-fat-diet (HFD) for 10 months, or HFD for 6 months then transferred to chow diet for 4 months (HFDt). Results: Weight loss and decreased intrahepatic lipid accumulation were observed in mice following dietary intervention. Additionally, HFD feeding induced bone mass accrual, while diet intervention restrained trabecular bone density. These changes were further reflected by increased osteogenesis and decreased adipogenesis in HFDt mice compared to HFD mice. Furthermore, HFD feeding decreased the activity of the Wingless-related integration site (Wnt)-ß-Catenin signaling pathway, while the Wnt signaling was augmented by diet intervention in the HFDt group. Conclusions: Our findings suggest that a HFD inhibits bone formation and that dietary intervention reverses this inhibition. Furthermore, the dietary intervention was able to compensate for the suppressed increase in bone mass to a level comparable to that in the CD group. Our study suggests that targeting the Wnt signaling pathway may be a potential approach to treat obesity-induced impaired bone mass accrual.

Defect detection and identification for aircraft cable insulation layer based on deep forest.

Due to the special internal environment of aircraft, cable damage is inevitable, which usually starts from insulation layer defects and may cause major economic losses, and even seriously threaten the life of people on board. According to the above issue, a defect detection system for aircraft cable insulation layer based on ultrasonic guided waves (UGWs) is built in this paper. In order to ensure the complete coupling between the sensor and the insulation layer of the aircraft cable, the macro fiber composite (MFC) flexible sensor is employed in the system. Both simulation and experimental results show that this method can simultaneously monitor four different types (abrasion, cut, semi-stripping and full-stripping) of cable insulation layer defects at different locations on the same cable. The reflection signals of different types of defects are extremely similar and difficult to distinguish directly. In this paper, a classification method for four types of defects based on the deep forest method is proposed. This method requires a small sample size, and the classification performance is not affected by network structure and parameters. The recognition accuracy can reach 100%, avoiding the problem of traditional deep learning classification relying on a large number of samples and requiring parameter adjustment. The proposed method in this paper is proven to be able to effectively carry out online monitoring and accurately classify defect types, which has guiding significance for aircraft maintenance personnel to take corresponding measures in time.