Search

Spray air leakage plugging is one of the effective means to prevent coal spontaneous combustion. Aiming at the drawbacks of high brittleness, easy cracking, and poor air leakage plugging effectiveness of traditional cement-based spraying air plugging material, biological capsule, mineral capsule and bio-mineral-fiber synergistic self-healing material were developed with microorganisms and crystalline minerals as self-healing agents. The influence of different curing humidity and curing time on the self-healing ability of material cracks was studied. The results showed that when the curing humidity was 100%, and the curing time was 35 days, the biological and mineral capsules could completely heal the cracks, with a maximum healing width of 1260 μm. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) were used to investigate the crystal structure and elemental composition of the healing products in the crack area of self-healing material. It was found that the healing products at the crack were spherical magnesite, petal-shaped hydromagnesite, and a large amount of spherical calcite produced by bacterial mineralization, which to some extent played a role in sealing the crack. EDS analysis confirmed that the healing products were MgCO3 and CaCO3. When the curing humidity was 100%, the material had the highest air leakage plugging rate (97.15%), which was 73.62% higher than the control group samples under the same curing conditions. Finally, self-healing material was used for spraying and plugging air leakage along the coal pillar, and the results showed that no obvious cracks were found within 6 months. Compared with traditional cement mortar, self-healing material has a longer service life and better prevention effect.

Abstract Background Bread wheat (Triticum aestivum L.) endosperm contains starch and proteins, which determine the final yield, quality, and nutritional value of wheat grain. The preferentially expressed endosperm genes can precisely provide targets in the endosperm for improving wheat grain quality and nutrition using modern bioengineering technologies. However, the genes specifically expressed in developing endosperms remain largely unknown. Results In this study, 315 preferentially expressed endosperm genes (PEEGs) in the spring wheat landrace, Chinese Spring, were screened using data obtained from an open bioinformatics database, which reveals a unique grain reserve deposition process and special signal transduction in a developing wheat endosperm. Furthermore, transcription and accumulation of storage proteins in the wheat cultivar, XC26 were evaluated. The results revealed that 315 PEEG plays a critical role in storage protein fragment deposition and is a potential candidate for modifying grain quality and nutrition. Conclusion These results provide new insights into endosperm development and candidate genes and promoters for improving wheat grain quality through genetic engineering and plant breeding techniques.

Abstract Restricted by the lighting conditions, the images captured at night tend to suffer from color aberration, noise, and other unfavorable factors, making it difficult for subsequent vision-based applications. To solve this problem, we propose a two-stage size-controllable low-light enhancement method, named Dual Fusion Enhancement Net (DFEN). The whole algorithm is built on a double U-Net structure, implementing brightness adjustment and detail revision respectively. A dual branch feature fusion module is adopted to enhance its ability of feature extraction and aggregation. We also design a learnable regularized attention module to balance the enhancement effect on different regions. Besides, we introduce a cosine training strategy to smooth the transition of the training target from the brightness adjustment stage to the detail revision stage during the training process. The proposed DFEN is tested on several low-light datasets, and the experimental results demonstrate that the algorithm achieves superior enhancement results with the similar parameters. It is worth noting that the lightest DFEN model reaches 11 FPS for image size of 1224×1024 in an RTX 3090 GPU. Graphical Abstract

Abstract Purpose This study aimed to investigate clinical diagnostic values of mSEPT9 combined with NLR, PLR and LMR in CRC. Methods 329 subjects composed of 120 CRC patients, 105 polyps patients and 104 healthy participants were prospectively recruited. Clinicopathologic features were collected and analyzed. Plasma samples were collected for mSEPT9, NLR, PLR and LMR test. The sensitivity, specificity and AUC of each biomarker separately or in combination were estimated by the ROC curve. Results The levels of NLR, PLR and the PDR of mSEPT9 in CRC patients were significantly higher than those in non-CRC subjects, while LMR was the opposite. The PDR of mSEPT9 in CRC patients was significantly correlated with age, tumor size, tumor stage and M stage. ROC curve analysis demonstrated moderate diagnostic values of mSEPT9, NLR, PLR and LMR in CRC patients with AUC of 0.78 (Se = 0.68, and Sp = 0.89), 0.78 (Se = 0.68, and Sp = 0.83), 0.80 (Se = 0.68, and Sp = 0.81), and 0.77 (Se = 0.72, and Sp = 0.73), respectively. Moreover, combination of these four biomarkers dramatically enhanced the diagnostic accuracy of CRC (AUC = 0.92, Se = 0.90, and Sp = 0.87), especially for CRC patients with large tumors (AUC = 0.95) or distal metastasis (AUC = 0.95). Conclusion mSEPT9, NLR, PLR and LMR showed the potential to be reliable biomarkers for the diagnosis of CRC. And the combined application of these biomarkers further improved the diagnostic accuracy of CRC significantly.

Foam cells play a pivotal role in the progression of atherosclerosis progression by triggering inflammation within arterial walls. They release inflammatory molecules that attract additional immune cells, leading to further macrophage recruitment and plaque development. In this study, we develop an osteopontin (OPN) antibody-conjugated niobium carbide (Nb2C-aOPN) MXenzyme designed to selectively target and mildly ablate foam cells while reducing inflammation in the plaque microenvironment. This approach utilizes photonic hyperthermia to decrease plaque size by enhancing cholesterol regulation through both passive cholesterol outflow and positive cholesterol efflux. Nb2C-aOPN MXenzyme exhibits multiple enzyme-mimicking properties, including catalase, superoxide dismutase, peroxidase and glutathione peroxidase, and acts as a scavenger for reactive oxygen and nitrogen species. The inhibition of reactive oxygen and nitrogen species synergizes with photothermal ablation to promote positive cholesterol efflux, leading to reduced macrophage recruitment and a shift in macrophage phenotype from M1 to M2. This integrative strategy on cholesterol regulation and anti-inflammation highlights the potential of multifunctional 2D MXenzyme-based nanomedicine in advancing atherosclerotic regression.

Spinal facet joint osteoarthritis (FJOA) is an OA disease with pathogenesis and progression uncovered. Our present study was performed to elucidate the role of DNM3OS on spinal FJOA. In this study, spine facet joint tissue of patients were collected. In vitro and in vivo models were constructed with SW1353 cells and rats. Hematoxylin and eosin (HE) staining, Safranin O-fast Green, Alcian blue staining, and Tolueine blue O (TBO) staining were employed for histology analyses. Quantitative PCR, western blotting, and Immunofluorescence were performed to evaluate the expression of genes. The levels of inflammatory cytokines were measured by enzyme-linked immunosorbent assay analysis. Cell Counting Kit-8 and flow cytometry were used for cell activity and apoptosis evaluation. The targeting sites between microRNA (miR)-127-5p and cadherin 11 (CDH11) were predicted TargetScan and miRbase database and confirmed by Dual-luciferase reporter assays. CHIP and EMS assay were employed to confirm the binding of LEF1and DNM3OS promoter. Our results showed that DNM3OS was found to upregulated, while miR-127-5p was downregulated in severe FJOA patients and inflammation-induced chondrosarcoma SW1353 cells. DNM3OS reduced cell activity, induced cell apoptosis and extracellular matrix (ECM) degradation by sponging miR-127-5p in vitro. miR-127-5p targeted CDH11 and inhibited wnt3a/β-catenin pathway to regulate OA in vitro. LEF1 promoted DNM3OS transcription to form a positively feedback in activated wnt3a/β-catenin pathway. In vivo rat model also confirmed that DNM3OS aggravated FJOA. In summary, DNM3OS/miR-127-5p/CDH11 enhanced Wnt3a/β-Catenin/LEF-1 pathway to form a positive feedback and aggravate spinal FJOA.

Summary Recent studies on co-transformation of the growth regulator, TaGRF4-GIF1 chimera (Growth Regulating Factor 4-GRF Interacting Factor 1), in cultivated wheat varieties (Triticum aestivum), showed improved regeneration efficiency, marking a significant breakthrough. Here, a simple and reproducible protocol using the GRF4-GIF1 chimera was established and tested in the medicinal orchid Dendrobium catenatum, a monocot orchid species. TaGRF4-GIF1 from T. aestivum and DcGRF4-GIF1 from D. catenatum were reconstructed, with the chimeras significantly enhancing the regeneration efficiency of D. catenatum through in planta transformation. Further, mutating the microRNA396 (miR396) target sites in TaGRF4 and DcGRF4 improved regeneration efficiency. The target mimicry version of miR396 (MIM396) not only boosted shoot regeneration but also enhanced plant growth. Our methods revealed a powerful tool for the enhanced regeneration and genetic transformation of D. catenatum.

Abstract The lncRNA NUTM2A-AS1 has been shown to be dysregulated in gastric cancer, while the roles in glioma is unclear. The aim of this study was to investigate the roles and potential mechanisms of lncRNA NUTM2A-AS1 in the proliferation and apoptosis of glioma cells. The StarBase software and dual luciferase reporter assay were used to identify the relationship between lncRNA NUTM2A-AS1 and miR-376a-3p, and miR-376a-3p and YAP1. The expression of lncRNA NUTM2A-AS1, miR-376a-3p, and YAP1 in human glioma cell lines was detected by qRT-PCR. MTT and flow cytometry were used to detect the effects of lncRNA NUTM2A-AS1 or miR-376a-3p on the proliferation and apoptosis of U251 and A172 cells, respectively. In addition, changes of Bax and Bcl-2 expression in glioma cells were further verified by western blotting and qRT-PCR. The results showed that the expression of lncRNA NUTM2A-AS1 was elevated in glioma cell lines, while miR-376a-3p was decreased. LncRNA NUTM2A-AS1 was negatively correlated with miR-376a-3p. Silencing of lncRNA NUTM2A-AS1 enhanced the levels of miR-376a-3p, leading to reduced cell proliferation and increased apoptosis in glioma cells. YAP1 was a direct target of miR-376a-3p, and it was negatively regulated by miR-376a-3p in U251 and A172 cells. Further mechanistic studies suggested that miR-376a-3p reduced glioma cell proliferation and increased apoptosis by inhibiting YAP1 expression. In addition, lncRNA NUTM2A-AS1 positively regulated of YAP1 expression in glioma cells. In conclusion, silencing of lncRNA NUTM2A-AS1 inhibited proliferation and induced apoptosis in human glioma cells via the miR-376a-3p/YAP1 axis.

Abstract The molecular basis of orchid flower development involves a specific regulatory program in which MADS-box transcription factors play a central role. The recent ‘perianth code’ model hypothesizes that two types of higher-order heterotetrameric complexes, namely SP complex and L complex, play pivotal roles in the orchid perianth organ formation. Therefore, we explored their roles and searched for other components of the regulatory network. Through the combined analysis for transposase-accessible chromatin with high-throughput sequencing and RNA sequencing of the lip-like petal and lip from Phalaenopsis equestris var.trilip, transcription factor-(TF) genes involved in lip development were revealed. PeNAC67 encoding a NAC-type TF and PeSCL23 encoding a GRAS-type TF were differentially expressed between the lip-like petal and the lip. PeNAC67 interacted with and stabilized PeMADS3, which positively regulated the development of lip-like petal to lip. PeSCL23 and PeNAC67 competitively bound with PeKAN2 and positively regulated the development of lip-like petal to petal by affecting the level of PeMADS3. PeKAN2 as an important TF that interacts with PeMADS3 and PeMADS9 can promote lip development. These results extend the ‘perianth code’ model and shed light on the complex regulation of orchid flower development.

The interaction between lamin A and the cytoplasmic skeleton plays a key role in maintaining nuclear mechanical properties. However, the effect of destruction of the cytoplasmic skeleton on the 3D submicroscopic structure of lamin A has not been elucidated. In this study, we developed an image quantization algorithm to quantify changes in the submicroscopic structure of the intact lamin A 3D network within the nucleus. We used blebbistatin or nocodazole to disrupt the fibrillar structure of F-actin or tubulin, respectively, and then quantified changes in the lamin A super-resolution network structure, the morphological and mechanical properties of the nucleus and the spatial distribution of chromosomes. Ultimately, we found for the first time that disruption of the cytoplasmic skeleton changes the lamin A submicroscopic network and nuclear structural characteristics. In summary, this study contributes to understanding the trans-nuclear membrane interaction characteristics of lamin A and the cytoplasmic skeleton.

Background: Laparoscopic common bile duct exploration (LCBDE) is a minimally invasive procedure for the removal of bile duct stones that is often performed by experienced hepatobiliary surgeons; beginners do not easily master this approach. Aim: To investigate the effectiveness and practicality of a three-dimensional printed (3DP) anatomical model based on radiographic images in the training of LCBDE techniques and formulate standardized educational workflows. Methods: Colored LCBDE training models were produced using 3DP technology. Twenty standardized training trainees were randomly divided into two groups: a 3DP model training group and a traditional laparoscopic simulation training group. Both groups received the same number of teaching hours. After a 4-weeks training course, the trainees’ subjective and objective progress in basic knowledge and manipulations were evaluated and compared. Results: Compared with traditional laparoscopic simulation, 3DP model simulation training is of great significance in improving trainers' understanding of surgical procedures and cooperation during the operation. Trainees with 3DP models training demonstrated a significant improvement in their understanding of the key points of surgery (χ2 = 6.139, p = 0.013) and skills scores, especially in core procedural steps operation. More importantly, the trainees showed higher levels of satisfaction and self-confidence while assisting in the surgery. Conclusion: With the development of 3DP models, improvements in the learning effect for theoretical understanding and practical skills were significant. The present study is the initial educational experience with 3DP models to facilitate the operational capabilities of the trainees for LCBDE.

IntroductionSpecialized care is essential for the recovery of children with cerebral palsy (CP). This study investigates how different care modes impact the gut microbiota.MethodsFecal samples from 32 children were collected, among whom those cared for by family (n = 21) were selected as the observation group, and those cared for by children's welfare institutions (n = 11) were selected as the control group (registration number of LGFYYXLL-024). The gut microbiota profiles were analyzed.ResultsThere was no significant difference in the α-diversity of the gut microbiota and the abundance at the phylum level. However, at the genus level, the observation group showed a significant increase in the abundance of butyrate-producing bacteria Bacteroides and Lachnospiracea incertae sedis (P

IntroductionRadiation therapy (RT) is one of the primary treatment options for early-stage non-small cell lung cancer (ES-NSCLC). Therefore, accurately predicting the overall survival (OS) rate following radiotherapy is crucial for implementing personalized treatment strategies. This work aims to develop a dual-radiomics (DR) model to (1) predict 3-year OS in ES-NSCLC patients receiving RT using pre-treatment CT images, and (2) provide explanations between feature importanceand model prediction performance.MethodsThe publicly available TCIA Lung1 dataset with 132 ES-NSCLC patients received RT were studied: 89/43 patients in the under/over 3-year OS group. For each patient, two types of radiomic features were examined: 56 handcrafted radiomic features (HRFs) extracted within gross tumor volume, and 512 image deep features (IDFs) extracted using a pre-trained U-Net encoder. They were combined as inputs to an explainable boosting machine (EBM) model for OS prediction. The EBM’s mean absolute scores for HRFs and IDFs were used as feature importance explanations. To evaluate identified feature importance, the DR model was compared with EBM using either (1) key or (2) non-key feature type only. Comparison studies with other models, including supporting vector machine (SVM) and random forest (RF), were also included. The performance was evaluated by the area under the receiver operating characteristic curve (AUCROC), accuracy, sensitivity, and specificity with a 100-fold Monte Carlo cross-validation.ResultsThe DR model showed highestperformance in predicting 3-year OS (AUCROC=0.81 ± 0.04), and EBM scores suggested that IDFs showed significantly greater importance (normalized mean score=0.0019) than HRFs (score=0.0008). The comparison studies showed that EBM with key feature type (IDFs-only demonstrated comparable AUCROC results (0.81 ± 0.04), while EBM with non-key feature type (HRFs-only) showed limited AUCROC (0.64 ± 0.10). The results suggested that feature importance score identified by EBM is highly correlated with OS prediction performance. Both SVM and RF models were unable to explain key feature type while showing limited overall AUCROC=0.66 ± 0.07 and 0.77 ± 0.06, respectively. Accuracy, sensitivity, and specificity showed a similar trend.DiscussionIn conclusion, a DR model was successfully developed to predict ES-NSCLC OS based on pre-treatment CT images. The results suggested that the feature importance from DR model is highly correlated to the model prediction power.

(1)Background: Rheumatoid Arthritis (RA) is a heterogeneous autoimmune disease with multiple unidentified pathogenic factors. The inconsistency between molecular subgroups poses challenges for early diagnosis and personalized treatment strategies. In this study, we aimed to accurately distinguish RA patients at the transcriptome level using bioinformatics methods. (2)Methods: We collected a total of 362 transcriptome datasets from RA patients in three independent samples from the GEO database. Consensus clustering was performed to identify molecular subgroups, and clinical features were assessed. Differential analysis was employed to annotate the biological functions of specifically upregulated genes between subgroups. (3)Results: Based on consensus clustering of RA samples, we identified three robust molecular subgroups, with Subgroup III representing the high-risk subgroup and Subgroup II exhibiting a milder phenotype, possibly associated with relatively higher levels of autophagic ability. Subgroup I showed biological functions mainly related to viral infections, cellular metabolism, protein synthesis, and inflammatory responses. Subgroup II involved autophagy of mitochondria and organelles, protein localization, and organelle disassembly pathways, suggesting heterogeneity in the autophagy process of mitochondria that may play a protective role in inflammatory diseases. Subgroup III represented a high-risk subgroup with pathological processes including abnormal amyloid precursor protein activation, promotion of inflammatory response, and cell proliferation. (4)Conclusion: The classification of the RA dataset revealed pathological heterogeneity among different subgroups, providing new insights and a basis for understanding the molecular mechanisms of RA, identifying potential therapeutic targets, and developing personalized treatment approaches.

Abstract Photosynthesis, essential for life on earth, sustains diverse processes by providing nutrition in plants and microorganisms. Especially, photosynthesis is increasingly applied in disease treatments, but its efficacy is substantially limited by the well‐known low penetration depth of external light. Here, ultrasound‐mediated photosynthesis is reported for enhanced sonodynamic tumor therapy using organic sonoafterglow (ultrasound‐induced afterglow) nanoparticles combined with cyanobacteria, demonstrating the proof‐of‐concept sonosynthesis (sonoafterglow‐induced photosynthesis) in cancer therapy. Chlorin e6, a typical small‐molecule chlorine, is formulated into nanoparticles to stimulate cyanobacteria for sonosynthesis, which serves three roles, i.e., overcoming the tissue‐penetration limitations of external light sources, reducing hypoxia, and acting as a sonosensitizer for in vivo tumor suppression. Furthermore, sonosynthetic oxygenation suppresses the expression of hypoxia‐inducible factor 1α, leading to reduced stability of downstream SLC7A11 mRNA, which results in glutathione depletion and inactivation of glutathione peroxidase 4, thereby inducing ferroptosis of cancer cells. This study not only broadens the scope of microbial nanomedicine but also offers a distinct direction for sonosynthesis.

Soil acidification has emerged as a critical limiting factor for the sustainable development of the tea industry. In this article, a comprehensive review of 63 original research articles focusing on the impact of amendments on the pH in tea plantations soil was conducted. Through meta-analysis, the effect of applying soil amendments to increase the pH of tea plantation soil and its influencing factors were investigated. The results revealed that lime had a significant impact, increasing the pH by 18% in tea plantation soil, while rapeseed cake had a minimal (2%) effect. It was observed that as the quantity of amendments and pH levels increased, so did their impact on the pH of tea plantation soil. Subgroup analysis within biochar showed varying effects, depending on soil pH, with an 11% increase in acidic soil. Among these amendments, biochar produced at pyrolysis temperature ranging from 501–600 °C and derived from animal waste demonstrated significant effect on increasing soil pH in tea plantations by 9% and 12%, respectively. This study offers valuable insights into improving and ensuring the health and sustainability of tea plantations.

Objectives: Our objective was to compare the effectiveness of Traditional Chinese herbal Kampo medicine Goreisan in improving recurrence in patients with chronic subdural hematoma (CSDH).Methods: Eligible randomized controlled trials prospective trials, and retrospective cohort studies were systematically identified through searches of PubMed, Cochrane Library, and CNKI from inception to March 2024. Following the application of predetermined inclusion and exclusion criteria to screen the available studies, main outcome measures were rigorously extracted. RevMan v5.4 software was utilized to evaluate the overall recurrence rate, employing a random-effects model to calculate pooled odds ratios with the Mantel-Haenszel estimation method. Inter-study heterogeneity was assessed using the Cochran Q (Chi-square) test and I2 statistics. Funnel plots were used to evaluate publication bias.Results: Among the 48 articles initially screened for citation, eight were ultimately selected for inclusion in the study. The results of our network meta-analysis indicate that patients with newly diagnosed Chronic subdural hematoma experienced a significantly reduced recurrence rate when treated with Goreisan compared to standard neurosurgical treatment (OR: 0.72; 95% CI 0.61–0.86; p = 0.00003). There was no statistically significant difference in the incidence rates of complications, including general fatigue, allergic reactions, hepatic dysfunction, and interstitial pneumonia (OR: 7.21; 95% CI 0.37–141.29; p = 0.19).Conclusion: Traditional medicine Goreisan was effective in reducing CDSH recurrence rates. For clinical treatment, it provides a high level of evidence-based medicine. It is also necessary to conduct multicenter randomized controlled trials with dose adjustments to determine whether Goreisan interventions improve neurological function or prognosis.

Abstract Few studies have reported the timing and amount of gestational weight gain (GWG) to prevent large‐for‐gestational‐age (LGA) or small‐for‐gestational‐age (SGA). This study aimed to evaluate the association of GWG velocity in each trimester with LGA or SGA based on data from the Taicang and Wuqiang cohort study (TAWS, n = 2008). We used a linear mixed model to evaluate the association of trimester‐specific GWG velocity with birthweight categories and stratified by prepregnancy body mass index category and parity. For normal‐weight pregnant women, mothers with LGA births had higher GWG velocities than mothers with appropriate‐for‐gestational‐age (AGA) births in the first trimester (0.108 vs. 0.031 kg/week, p

Abstract Background In observational studies, there exists an association between obesity and epigenetic age as well as telomere length. However, varying and partially conflicting outcomes have notably arisen from distinct studies on this topic. In the present study, two-way Mendelian randomization was used to identify potential causal associations between obesity and epigenetic age and telomeres. Methods A genome-wide association study was conducted using data from individuals of European ancestry to investigate bidirectional Mendelian randomization (MR) regarding the causal relationships between obesity, as indicated by three obesity indicators (body mass index or BMI, waist circumference adjusted for BMI or WCadjBMI, and waist-to-hip ratio adjusted for BMI or WHRadjBMI), and four epigenetic age measures (HannumAge, HorvathAge, GrimAge, PhenoAge), as well as telomere length. To assess these causal associations, various statistical methods were employed, including Inverse Variance Weighted (IVW), Weighted Median, MR Egger, Weighted Mode, and Simple Mode. To address the issue of multiple testing, we applied the Bonferroni correction. These methods were used to determine whether there is a causal link between obesity and epigenetic age, as well as telomere length, and to explore potential bidirectional relationships. Forest plots and scatter plots were generated to show causal associations between exposures and outcomes. For a comprehensive visualization of the results, leave-one-out sensitivity analysis plots, individual SNP-based forest plots for MR analysis, and funnel plots were included in the presentation of the results. Results A strong causal association was identified between obesity and accelerated HannumAge, GrimAge, PhenoAge and telomere length shrinkage. The causal relationship between WCadjBMI and PhenoAge acceleration (OR: 2.099, 95%CI: 1.248—3.531, p = 0.005) was the strongest among them. However, only the p-values for the causal associations of obesity with GrimAge, PhenoAge, and telomere length met the criteria after correction using the Bonferroni multiple test. In the reverse MR analysis, there were statistically significant causal associations between HorvathAge, PhenoAge and GrimAge and BMI, but these associations exhibited lower effect sizes, as indicated by their Odds Ratios (ORs). Notably, sensitivity analysis revealed the robustness of the study results. Conclusions The present findings reveal a causal relationship between obesity and the acceleration of epigenetic aging as well as the reduction of telomere length, offering valuable insights for further scientific investigations aimed at developing strategies to mitigate the aging process in humans.

Abstract Background To observe the occurrence of related complications after self-expandable metallic (SEM) airway stents implantation with different diameters at different time points, and to provide theoretical basis for the optimal chioce of existing airway stents in clinical practice. Methods Healthy New Zealand white rabbits were used to establish benign tracheal stenosis models after chest CT examination. Forty-fivemodel rabbits with more than 50% of airway stenosis were divided into two groups. Small-diameter SEM stents (The ratio of stent diameter to airway diameter is nearly 1.0) were implanted in Group A in 21 rabbits, and large-diameter tracheal stents (The ratio of stent diameter to airway diameter is more than 1.2) were implanted in Group B in 24 rabbits. Stent-related complications were observed after stent implantation in 2nd,4th,8th, and 12th week by bronchoscopygross anatomy, pathological and the expressions of IL-1RA, IL-8 and MMP9 in involved tracheal. Results The incidence rate of tracheomalacia of stent was significantly higher in group B (24/24 100%) than that in group A (1 /21,4.8%) (P

KRAS-TP53 co-mutation is strongly associated with poor prognosis and high malignancy in gastrointestinal cancers. Therefore, a novel approach to oncotherapy may lie in combination therapy targeting both KRAS and TP53. Herein, we present a novel self-assembled nanoparticle (HA-TPP/A) that are functionalized nano-carrier hyaluronic acid (HA)-TPP conjugate (HA-TPP) to degrade mutant p53 proteins (mutp53) and co-deliver AMG510 for treating KRAS-TP53 co-alteration of gastrointestinal cancers by inhibiting the mutant KRAS and mutp53 signaling pathways. The HA-TPP/A nanoparticles led to ubiquitination-dependent proteasomal degradation of mutp53 by targeting damage to mitochondria. Furthermore, these nanoparticles abrogated the gain-of-function (GOF) phenotypes of mutp53 and increased sensitivity to AMG510-induced cell killing, thereby reducing cell proliferation and migration in gastrointestinal cancer with KRAS-TP53 co-mutation. The co-loaded HA-TPP/A nanoparticles demonstrated remarkable therapeutic efficacy in a tumor-bearing mouse model, particularly in KRAS-TP53 double mutant expressing cancer cells, compared with single drug and combined free drug groups. Notably, HA-TPP/A is the first reported nanoparticle with an ability to co-target KRAS-TP53, providing a promising approach for therapy in highly malignant gastrointestinal tumors and potentially expanding clinical indications for AMG510 targeted therapies in gastrointestinal tumors.

Singlet fission is a desired process in photovoltaics since it enhances photoelectric conversion efficiency. Intramolecular singlet fission is of special interest as the fission efficiency can be improved through tuning configurations between chromophore units that are covalently connected. However, intramolecular singlet fission chromophores feature a large tetraradical character, and may tend to dissatisfy the ET2>2ET1 criterion for all singlet fission chromophores, intramolecular or not. We performed spin-flip time-dependent density functional theory calculations for a collection of representative intramolecular singlet fission chromophores to show that this is indeed the case.

Abstract Traditional inspection cameras determine targets and detect defects by capturing images of their light intensity, but in complex environments, the accuracy of inspection may decrease. Information based on polarization of light can characterize various features of a material, such as the roughness, texture, and refractive index, thus improving classification and recognition of targets. This paper uses a method based on noise template threshold matching to denoise and preprocess polarized images. It also reports on design of an image fusion algorithm, based on NSCT transform, to fuse light intensity images and polarized images. The results show that the fused image improves both subjective and objective evaluation indicators, relative to the source image, and can better preserve edge information and help to improve the accuracy of target recognition. This study provides a reference for the comprehensive application of multi-dimensional optical information in power inspection. Graphical Abstract

NASA's (National Aeronautics and Space Administration) ICESat-2 with a Photon Counting LiDAR (Light Detection And Ranging) Sensor sensitively detects signal photons at high speed with an advanced detection system called the Advanced Topographic Laser Altimeter System (ATLAS). However, the sensor also extracts a large amount of background photon noise coming from the atmosphere, ground, sun, or other radiation. This condition is particularly evident in forest areas. This study proposes an automatic machine learning approach to utilize data for forestry applications to improve data availability compared to NASA's official product. Our method uses only a very limited number (10%) of sample points for training, ensuring operational efficiency and training accuracy. We conclude that the integrated learning performance generally outperforms single models, and the mean F1 score of all tests is approximately 0.9. The mean F1 score of the Stacked Ensembles model is 0.957 ahead of the other models. The top three variables used in training models are kNNdist5, kNNdist10, and h. These three variables could explain 51.6% of the components of the models. Over the regions tested, the proposed method could improve the proportion of signals correctly identified by 6.4%, 12.2%, 2.7%, 9.3%, and 1.4% in five datasets. The model performs better in low signal-to-noise (SNR) datasets less than 7.5. The method would be largely unaffected by differences in topography, noise distribution, and SNR. The classifiers could correct misclassified labels in ATL08 products and show good stability in different conditions.

PurposeWe aimed to report the latest and largest pooled analyses and evidence updates to assess the effectiveness of telemedicine interventions for self-management (DSM) in patients with type 2 diabetes mellitus (T2DM).MethodsA systematic literature search was conducted using PubMed, Cochrane, Embase, and Web of Science in December 2023. We included randomized controlled trials (RCTs) of adults (≥18 years of age) diagnosed with T2DM where the intervention was the application of telemedicine. The Cochrane Risk of Bias Assessment was used to evaluate quality. The study’s main outcome indicators were glycosylated hemoglobin (HbA1c) and diabetes self-management (DSM) capacity.ResultsA total of 17 eligible articles, comprising 20 studies and 1,456 patients (734 in the intervention group and 722 in the control group), were included in the evidence synthesis. The baseline characteristics of both groups were similar in all outcomes. Comprehensive analyses showed post-intervention decreases in HbA1c, 2-h postprandial glucose, systolic and diastolic blood pressure, increases in Diabetes Self- Care activities, DSM competencies based on dietary and medication adherence, and improvements in overall DSM scores, all of which were statistically significant. While no statistically significant differences were observed in body mass index, lipids, and other DSM dimensions. Based on subgroup analyses, app-based experimental interventions targeting under 60 years old populations in Asia and North America were found to be more effective and less heterogeneity in the short term (

BackgroundFood waste remains a major problem for the world and food security. Despite the fact that consumers are significant producers of food waste, little research attention has been paid to college students. The present study aimed to assess food waste and the influence factors among college students. Additionally, the goal was to improve college students’ food waste attitudes and behaviors through labor education.MethodsThrough an online questionnaire survey, 407 college students from three universities were asked about food waste; 27 students of them were randomly selected as the research object, and labor practice was carried out in groups in the student cafeteria. Mann–Whitney U test was performed to show food waste behavior of college students and logistical regression analysis was used to analyze the factors affecting food waste behavior.ResultsThe results indicated that the food waste is more serious among college students in East China, senior or female students, BMI plays a positive role in food waste among college students, while monthly consumption and peers waste play a negative role in food waste. After participating in the labor education, the students’ views and practices toward their peer’s food waste have improved.ConclusionThe implementation of labor education in college canteens is conducive to the establishment of a correct outlook on labor as well as saving consciousness among college students, and to the formation of a social consciousness of saving.

Background: Breast cancer (BC) remains the most common cancer among women, and novel post-surgical reconstruction techniques, including autologous fat transplantation, have emerged. While Adipose-derived stem cells (ADSCs) are known to impact the viability of fat grafts, their influence on breast cancer progression remains unclear. This study aims to elucidate the genetic interplay between ADSCs and breast cancer, focusing on potential therapeutic targets. Methods: Using the GEO and TCGA databases, we pinpointed differentially expressed (DE) mRNAs, miRNAs, lncRNAs, and pseudogenes of ADSCs and BC. We performed functional enrichment analysis and constructed protein-protein interaction (PPI), RNA binding protein (RBP)-pseudogene-mRNA, and lncRNA-miRNA-transcription factor (TF)-gene networks. Our study delved into the correlation of AK4 expression with 33 different malignancies and examined its impact on prognostic outcomes across a pan-cancer cohort. Additionally, we scrutinized immune infiltration, microsatellite instability, and tumor mutational burden, and conducted single-cell analysis to further understand the implications of AK4 expression. We identified novel sample subtypes based on hub genes using the ConsensusClusterPlus package and examined their association with immune infiltration. The random forest algorithm was used to screen DE mRNAs between subtypes to validate the powerful prognostic prediction ability of the artificial neural network. Results: Our analysis identified 395 DE mRNAs, 3 DE miRNAs, 84 DE lncRNAs, and 26 DE pseudogenes associated with ADSCs and BC. Of these, 173 mRNAs were commonly regulated in both ADSCs and breast cancer, and 222 exhibited differential regulation. The PPI, RBP-pseudogene-mRNA, and lncRNA-miRNA-TF-gene networks suggested AK4 as a key regulator. Our findings support AK4 as a promising immune-related therapeutic target for a wide range of malignancies. We identified 14 characteristic genes based on the AK4-related cluster using the random forest algorithm. Our artificial neural network yielded excellent diagnostic performance in the testing cohort with AUC values of 0.994, 0.973, and 0.995, indicating its ability to distinguish between breast cancer and non-breast cancer cases. Conclusions: Our research sheds light on the dual role of ADSCs in BC at the genetic level and identifies AK4 as a key protective mRNA in breast cancer. We found that AK4 significantly predicts cancer prognosis and immunotherapy, indicating its potential as a therapeutic target.

Abstract Aim of the study To evaluate the clinical efficacy and safety of commonly used oral Chinese patent medicines for the treatment of coronary heart disease combined with hyperlipidemia in clinical practice through a network meta-analysis. Materials and methods PubMed, Embase, Cochrane Library, Web of Science, Wanfang, VIP, SinoMed, and CNKI databases were searched for all published randomized controlled trials (RCTs) on the treatment of coronary heart disease combined with hyperlipidemia using Chinese patent medicines. NoteExpress software was used to screen the literature obtained from the databases according to the inclusion and exclusion criteria. The Cochrane risk of bias assessment tool was used to evaluate the quality of the included studies. A network meta-analysis was performed using R 4.2.1. Subgroup analyses of outcome indicators were made based on conventional treatment (CT) methods. The incidence of adverse events in the included RCTs was statistically analyzed. A funnel plot was drawn using RevMan 5.4.1 software for the assessment of bias in the total clinical effectiveness rate. Finally, the quality of evidence for interventions with statistically significant differences was evaluated using the GRADE system. Results A total of 78 RCTs were included, involving 7,955 cases and 8 types of Chinese patent medicines, which were Tongxinluo Capsule, Naoxintong Capsule, Compound Danshen Dripping Pill, Shexiangbaoxin Pill, Songling Xuemaikang Capsule, Xuezhikang Capsule, Yindan Xinnaotong Capsule, and Zhibitai Capsule. A total of 24 RCTs reported the incidence of adverse events, but no statistically significant difference in the incidence of adverse events was found between the experimental and control groups in each study (P > 0.05). There was no obvious publication bias in all studies, but the overall quality of evidence in the included RCTs was low. Comparison of different intervention measures showed that Naoxintong Capsule + CT improved the cardiac index and cardiac output, and lowered the low-density lipoprotein cholesterol and total cholesterol levels. Tongxinluo Capsule + CT raised high-density lipoprotein cholesterol levels and reduced triglyceride levels. Xuezhikang Capsule + CT improved the total clinical effectiveness rate. Subgroup analyses showed that differences in CT did not cause heterogeneity in the results. Conclusion Compared with the use of CT alone, the combined use of Chinese patent medicines with CT can effectively improve the symptoms in patients with both coronary heart disease and hyperlipidemia.

Abstract Ferroptosis is a form of cell death that is triggered by iron-dependent lipid peroxidation and is closely associated with osteoarthritis. The primary interventions for inhibiting ferroptosis in osteoarthritis are anti-lipid peroxidation and iron chelation. The objective of our study is to investigate the characteristics of ferroptosis in osteoarthritis and identify the optimal time points for inhibiting ferroptosis to alleviate disease progression. Ferroptosis-related alterations and markers of OA were analyzed in paired intact and damaged cartilages from OA patients by immunofluorescence, qRT-PCR, mitochondrial membrane potential and immunohistochemistry. We also compared Ferroptosis-related alterations in cartilage of mild, moderate, and severe OA (according to the modified Mankin score). In addition, we compared the effect of Fer-1 on ferroptosis and the protection of chondrocytes by detecting markers of both ferroptosis and OA by immunofluorescence, CCK8 and qRT-PCR. Ferroptosis-related alterations (GPX4 downregulation, ACSL4 upregulation, MDA, LPO accumulation, Mitochondrial membrane potential decreased) in the damaged area cartilage were more severe than those in the intact area and increased with the progression of OA. Compared with mild OA group, the activity of chondrocytes treated with Fer-1 (a ferroptosis inhibitor) was increased, mitochondrial function was improved, and ferroptosis was reduced (GPX4 upregulation, SLC7A11 upregulation, ACSL4 downregulation,), and promoted the expression of COL2A1 and inhibited the expression of MMP13. However, these changes were not observed in moderate and severe OA chondrocytes. Ferroptosis occurs in a region-specific manner and is exacerbated with the progression of human OA cartilage degeneration. Inhibition of ferroptosis might had a therapeutic effect on chondrocytes with mild OA but had no significant therapeutic effect on chondrocytes with moderate to severe OA.

The high operating costs of Internet Data Centers (IDC) are a major challenge for their owners worldwide. Therefore, more attention has recently been paid to the energy and cost management of IDCs. This paper investigates the optimal operational strategy for minimizing the electricity costs of a group of globally distributed IDCs in different locations under various day-ahead electricity markets, and each is equipped with a high-performance energy storage system. For this goal, optimal workload dispatching and optimal energy management of the storage units of all IDCs are simultaneously perused by the proposed problem. The system is modeled regarding power balancing constraints, battery costs, and quality of service (QoS). For more practical results, a penalty function is also considered when QoS constraints are not perfectly met, and the impact of the batteries’ depth of discharge on the cost of energy storage is also modeled. Moreover, the cross-correlations between the traffic of IDCs are also considered by the multidimensional copula function. The proposed energy cost optimization is linearized for increasing the accuracy of convergence. The results show that not only the power consumption pattern of the IDCs is significantly improved, but also the cost of power consumption is reduced by 34%. The results also prove the positive effect of battery discharge on workload dispatch and represent a compromise between battery costs and electricity cost savings.

Abstract Background The optimal extent of mediastinal lymph node dissection is still under debate. This study aimed to investigate the prognostic impact of complete dissection of right paratracheal lymph nodes (LNs) in right‐sided non‐small cell lung cancer (NSCLC) and evaluate the potential patient population who will particularly benefit from right paratracheal node dissection (RPND). Methods Between January 2009 and December 2019, we retrospectively reviewed 2650 patients with primary right‐sided NSCLC who underwent pulmonary surgery with lymphadenectomy in the Western China Lung Cancer Database. A total of 2447 patients received both 2R and 4R LNs dissection (complete RPND group), 162 patients received only 2R or 4R LNs dissection (incomplete RPND group), and 41 patients received neither 2R nor 4R LNs dissection (no RPND group). Overall survival (OS) was analyzed. Results The metastasis rates in stations 2R and 4R were 6.5% and 8.0%, respectively. In stage N2 patients, the frequency of involvement of stations 2R/4R was 74.8%. The complete RPND group had a significantly better survival than the incomplete and no RPND group (5‐year OS, 79.5% vs. 72.7% vs. 65.5%; p

Abstract Background Astragalus mongolicus Bunge is used in traditional Chinese medicine and is thus cultivated in bulk. The cultivation of A. mongolicus requires a large amount of nitrogen fertilizer, increasing the planting cost of medicinal materials and polluting the environment. Isolation and screening of plant growth-promoting rhizobacteria (PGPR) and exploring the nitrogen fixation potential of A. mongolicus rhizosphere microorganisms would effectively reduce the production cost of A. mongolicus. Results This study used A. mongolicus roots and rhizosphere soil samples from Longxi County of Gansu Province, Jingle County, and Hunyuan County of Shanxi Province, China, to isolate and identify nitrogen-fixing bacteria. Through nitrogen fixation efficiency test, single strain inoculation test, and plant growth-promoting characteristics, three strains, Bacillus sp. J1, Arthrobacter sp. J2, and Bacillus sp. G4 were selected from 86 strains of potential nitrogen-fixing bacteria, which were the most effective in promoting the A. mongolicus growth and increasing the nitrogen, phosphorus, and potassium content in plants. The antagonistic test showed that these bacteria could grow smoothly under the co-culture conditions. The J1, J2, and G4 strains were used in a mixed inoculum and found to enhance the biomass of A. mongolicus plants and the accumulation of the main medicinal components in the field experiment. Mixed bacterial agent inoculation also increased bacterial diversity and changed the structure of the bacterial community in rhizosphere soil. Meanwhile, the relative abundance of Proteobacteria increased significantly after inoculation, suggesting that Proteobacteria play an important role in plant growth promotion. Conclusions These findings indicate that specific and efficient PGPRs have a significant promoting effect on the growth of A. mongolicus, while also having a positive impact on the structure of the host rhizosphere bacteria community. This study provides a basis for developing a nitrogen-fixing bacterial fertilizer and improving the ecological planting efficiency of A. mongolicus.

This study investigates the impact of hometown resource endowment on farmers’ rural-urban migration decisions within the context of “Dual Carbon” policies. It aims to understand the factors influencing migration decision-making amidst the dynamics of urban and rural land occupation, particularly focusing on the role of hometown resource endowments led by homesteads. Using data from the China Migrants Dynamic Survey (CMDS), this study analyzes the influence of hometown resource endowment, primarily residential land, on farmers’ migration decisions. Ownership of homesteads and contracted land significantly affects farmers’ settlement in cities, while the dividend effect from village collectives is negligible. Additionally, the administrative level of the hometown serves as a significant factor in migration decision-making, particularly in family migration. Homestead and contracted land ownership negatively impacts both household and individual migration decisions. Specifically, owning homesteads exerts a greater influence on whole family migration decisions, reducing the probability of settling in cities by 21.1%. Regional comparative analysis reveals varying effects of owning homesteads and contracted land. While it positively influences household migration to cities in the eastern region, it inhibits migration in the central and western regions. The findings highlight the complex interplay between hometown resource endowment, land use patterns, and rural-urban migration decisions. Understanding these dynamics is crucial for designing effective policies to address migration challenges in the context of environmental and socioeconomic transitions.

Background: Mitochondrial redox imbalance underlies the pathophysiology of type2 diabetes mellitus (T2DM), and is closely related to tissue damage and dysfunction. Studies have shown the beneficial effects of dietary strategies that elevate β-hydroxybutyrate (BHB) levels in alleviating T2DM. Nevertheless, the role of BHB has not been clearly elucidated. Methods: We performed a spectral study to visualize the preventive effects of BHB on blood and multiorgan mitochondrial redox imbalance in T2DM mice via using label-free resonance Raman spectroscopy (RRS), and further explored the impact of BHB therapy on the pathology of T2DM mice by histological and biochemical analyses. Findings: Our data revealed that RRS-based mitochondrial redox states assay enabled clear and reliable identification of the improvement of mitochondrial redox imbalance by BHB, evidenced by the reduction of Raman peak intensity at 750 cm−1, 1128 cm−1 and 1585 cm−1 in blood, tissue as well as purified mitochondria of db/db mice and the increase of tissue mitochondrial succinic dehydrogenase (SDH) staining after BHB treatment. Exogenous supplementation of BHB was also found to attenuate T2DM pathology related to mitochondrial redox states, involving organ injury, blood glucose control, insulin resistance and systemic inflammation. Interpretation: Our findings provide strong evidence for BHB as a potential therapeutic strategy targeting mitochondria for T2DM.

IntroductionWheat is a food crop with a large global cultivation area, and the content and quality of wheat glutenin accumulation are important indicators of the quality of wheat flour.MethodsTo elucidate the gene expression regulation and metabolic characteristics related to the gluten content during wheat grain formation, transcriptomic and metabolomic analyses were performed for the high gluten content of the Xinchun 26 cultivar and the low proteins content of the Xinchun 34 cultivar at three periods (7 d, 14 d and 21 d) after flowering.ResultsTranscriptomic analysis revealed that 5573 unique differentially expressed genes (DEGs) were divided into two categories according to their expression patterns during the three periods. The metabolites detected were mainly divided into 12 classes. Lipid and lipid-like molecule levels and phenylpropanoid and polyketide levels were the highest, and the difference analysis revealed a total of 10 differentially regulated metabolites (DRMs) over the three periods. Joint analysis revealed that the DEGs and DRMs were significantly enriched in starch and sucrose metabolism; the citrate cycle; carbon fixation in photosynthetic organisms; and alanine, aspartate and glutamate metabolism pathways. The genes and contents of the sucrose and gluten synthesis pathways were analysed, and the correlation between gluten content and its related genes was calculated. Based on weighted correlation network analysis (WGCNA), by constructing a coexpression network, a total of 5 specific modules and 8 candidate genes that were strongly correlated with the three developmental stages of wheat grain were identified.DiscussionThis study provides new insights into the role of glutenin content in wheat grain formation and reveals potential regulatory pathways and candidate genes involved in this developmental process.

BackgroundsUAVs for crop protection hold significant potential for application in mountainous orchard areas in China. However, certain issues pertaining to UAV spraying need to be addressed for further technological advancement, aimed at enhancing crop protection efficiency and reducing pesticide usage. These challenges include the potential for droplet drift, limited capacity for pesticide solution. Consequently, efforts are required to overcome these limitations and optimize UAV spraying technology.MethodsIn order to balance high deposition and low drift in plant protection UAV spraying, this study proposes a plant protection UAV spraying method. In order to study the operational effects of this spraying method, this study conducted a UAV spray and grid impact test to investigate the effects of different operational parameters on droplet deposition and drift. Meanwhile, a spray model was constructed using machine learning techniques to predict the spraying effect of this method.Results and discussionThis study investigated the droplet deposition rate and downwind drift rate on three types of citrus trees: traditional densely planted trees, dwarf trees, and hedged trees, considering different particle sizes and UAV flight altitudes. Analyzing the effect of increasing the grid on droplet coverage and deposition density for different tree forms. The findings demonstrated a significantly improved droplet deposition rate on dwarf and hedged citrus trees compared to traditional densely planted trees and adopting a fixed-height grid increased droplet coverage and deposition density for both the densely planted and trellised citrus trees, but had the opposite effect on dwarfed citrus trees. When using the grid system. Among the factors examined, the height of the sampling point exhibited the greatest influence on the droplet deposition rate, whereas UAV flight height and droplet particle size had no significant impact. The distance in relation to wind direction had the most substantial effect on droplet drift rate. In terms of predicting droplet drift rate, the BP neural network performed inadequately with a coefficient of determination of 0.88. Conversely, REGRESS, ELM, and RBFNN yielded similar and notably superior results with a coefficient of determination greater than 0.95. Notably, ELM demonstrated the smallest root mean square error.

Abstract Background Sepsis is a life-threatening condition caused by an abnormal response of the body to infection and imposes a significant health and economic burden worldwide due to its high mortality rate. Early recognition of sepsis is crucial for effective treatment. This study aimed to systematically evaluate the performance of various machine learning models in predicting the onset of sepsis. Methods We conducted a comprehensive search of the Cochrane Library, PubMed, Embase, and Web of Science databases, covering studies from database inception to November 14, 2022. We used the PROBAST tool to assess the risk of bias. We calculated the predictive performance for sepsis onset using the C-index and accuracy. We followed the PRISMA guidelines for this study. Results We included 23 eligible studies with a total of 4,314,145 patients and 26 different machine learning models. The most frequently used models in the studies were random forest (n = 9), extreme gradient boost (n = 7), and logistic regression (n = 6) models. The random forest (test set n = 9, acc = 0.911) and extreme gradient boost (test set n = 7, acc = 0.957) models were the most accurate based on our analysis of the predictive performance. In terms of the C-index outcome, the random forest (n = 6, acc = 0.79) and extreme gradient boost (n = 7, acc = 0.83) models showed the highest performance. Conclusion Machine learning has proven to be an effective tool for predicting sepsis at an early stage. However, to obtain more accurate results, additional machine learning methods are needed. In our research, we discovered that the XGBoost and random forest models exhibited the best predictive performance and were most frequently utilized for predicting the onset of sepsis. Trial registration CRD42022384015

Abstract Highly-efficient molecular photoswitching occurs ex-situ but not to-date inside electronic devices due to quenching of excited states by background interactions. Here we achieve fully reversible in-situ mechano-optoelectronic switching in self-assembled monolayers (SAMs) of tetraphenylethylene molecules by bending their supporting electrodes to maximize aggregation-induced emission (AIE). We obtain stable, reversible switching across >1600 on/off cycles with large on/off ratio of (3.8 ± 0.1) × 103 and 140 ± 10 ms switching time which is 10-100× faster than other approaches. Multimodal characterization shows mechanically-controlled emission with UV-light enhancing the Coulomb interaction between the electrons and holes resulting in giant enhancement of molecular conductance. The best mechano-optoelectronic switching occurs in the most concave architecture that reduces ambient single-molecule conformational entropy creating artificially-tightened supramolecular assemblies. The performance can be further improved to achieve ultra-high switching ratio on the order of 105 using tetraphenylethylene derivatives with more AIE-active sites. Our results promise new applications from optimized interplay between mechanical force and optics in soft electronics.

Hot salt corrosion behavior of TNM alloy (Ti-44Al-4Nb-1.5Mo-(B, Y) (at.%)) was investigated in cyclic conditions at 750 °C, 850 °C and 950 °C for 100 h in the 75 wt% Na2SO4 + 25 wt% NaCl salt mixture. The hot salt corrosion resistance of γ、α2 and β phase in the alloy was studied by short-term quasi-in-situ hot corrosion experiments. Results show that the hot salt corrosion resistance of the three phases decreases in the following order: γ、α2、β. The weight changes of TNM alloy after hot salt corrosion at 750 °C, 850 °C and 950 °C for 100 h are 13.8 mg/cm2, -19.6 mg/cm2 and -26.7 mg/cm2. Under the condition of hot salt corrosion at 750 °C, the corrosion scales are mainly composed of a mixed corrosion scale of TiO2 and Al2O3, Al2O3 scale, and Al depletion zone, similar to the morphology of a high-temperature oxidation scale. The corrosion scales are seriously peeled off and destructive transverse cracks are generated inside the corrosion scales under the conditions of hot salt corrosion at 850 °C and 950 °C. The acid-base corrosion dissolution of oxides in the corrosive medium and the formation of volatile chlorides are the main causes of cracks in the TiO2 and Al2O3 scales. In addition, the Nb element in the TNM alloy is mainly enriched beneath the corrosion scales to form a NaNbO3 layer, which can inhibit the decomposition and penetration of the corrosive medium. Mo element reacts with the S element to form MoS2, which anchors the S element to a certain extent.

Background: The survival benefit of partial nephrectomy (PN) in pT3a RCC patients is controversial. Here we aimed to explore the potential benefit of PN for pT3aN0M0 renal cell carcinoma (RCC). Material and methods: Data of patients with pT3aN0M0 RCC who were diagnosed between 2010 and 2012 in the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database were retrospectively collected. Overall survival (OS) and cancer specific survival (CSS) were compared using a Cox proportional hazards model between PN and radical nephrectomy (RN) in pT3aN0M0 RCC. Propensity score (–adjusted, –stratified, –weighted, and –matched) analyses were performed to control for imbalances in individual risk factors. Results: A total of 1277 patients with pT3aN0M0 RCC were identified, of whom 200 patients were treated with PN and 1077 patients were RN. PN showed favorable OS and CSS in 0–4 cm pT3aN0M0 RCC (P

Given the complex nonlinear problem between the control and prediction of the surrounding surface settlement deformation caused (GWO), the GWO-ELM deep foundation pit excavation deformation prediction model was proposed. Extreme learning machine and Grey Wolf optimization algorithm combining training and predicting land subsidence. Based on MIDAS GTS NX software, we established a finite element simplified model for deep foundation pit construction, conducted structural calculations, and utilized the Grey Wolf optimization algorithm to optimize the deep foundation pit excavation and its influencing factors, input weights, and hidden layer thresholds in the ELM neural network. Taking the deep foundation pit project of Baoding Automobile Science and Technology Industrial Park as an example, the actual monitoring value is compared with the simulated value, verifying the model's accuracy. The number of soil nails in the finite element model, the excavation depth, the settlement of surrounding buildings and other factors are taken as the input factors of the prediction model. The DB-2 surface settlement of the monitoring point in the finite element model is taken as the output factor of the prediction model. The predicted value of the GWO-ELM model was compared with that of the ELM model. We draw three main conclusions from the results. First, the surface settlement of a bottomless foundation pit can be predicted in advance by using finite element software and the distribution law of surface settlement and horizontal displacement is consistent with the measured values. Second, the Grey Wolf optimization algorithm optimizes the input weights and thresholds in the extreme learning machine neural network. The GWO-ELM prediction model has good generalization ability, can effectively reduce human errors and can improve the accuracy of the prediction model. Third, through practical engineering verification, the average absolute error of the GWO-ELM model is 0.26145, the mean square error is 0.31258 and the R2 is 0.98725, all of which are superior to the ELM model and are an effective method for predicting deformation and settlement of deep foundation pit excavation.

Abstract Background Osteoarthritis (OA) is a prevalent disease plaguing the elderly. Recently, chondrocyte ferroptosis has been demonstrated to promote the progression of OA. Peroxisome proliferator-activated receptor-γ (PPARγ) is an important factor in maintaining cartilage health. However, the relationship between PPARγ and chondrocyte ferroptosis in OA and its mechanism is completely unclear. Methods We established a surgically induced knee OA rat model to investigate PPARγ and chondrocyte ferroptosis in OA. Rat knee specimens were collected for Safranin O/Fast Green staining and immunohistochemical staining after administered orally placebo or pioglitazone (PPARγ agonist) for 4 weeks. We used RSL3 to establish a chondrocyte ferroptosis model cultured in vitro to study the role of PPARγ activation toward ferroptosis, mitochondrial function, and PTEN-induced putative kinase 1 (Pink1)/Parkin-dependent mitophagy. GW9662 (PPARγ antagonist), Mdivi-1 (mitophagy inhibitor), and chloroquine (mitophagy inhibitor) were employed to investigate the mechanism of PPARγ-Pink1/Parkin-dependent mitophagy in the inhibition of ferroptosis. Results We found that PPARγ activation by pioglitazone attenuated not only OA but also inhibited the expression of the ferroptosis marker acyl-CoA synthetase long-chain family member 4 (ACSL4) at the same time in rats. Furthermore, in vivo and in vitro data indicated that PPARγ activation restored Pink1/Parkin-dependent mitophagy, improved mitochondrial function, inhibited chondrocyte ferroptosis, and delayed the progression of OA. Conclusions The present study demonstrated that PPARγ activation attenuates OA by inhibiting chondrocyte ferroptosis, and this chondroprotective effect was achieved by promoting the Pink1/Parkin-dependent mitophagy pathway.

Abstract Background Simulation-based medical education (SBME) and three-dimensional printed (3DP) models are increasingly used in continuing medical education and clinical training. However, our understanding of their role and value in improving trainees’ understanding of the anatomical and surgical procedures associated with liver surgery remains limited. Furthermore, gender bias is also a potential factor in the evaluation of medical education. Therefore, the aim of this study was to evaluate the educational benefits trainees receive from the use of novel 3DP liver models while considering trainees’ experience and gender. Methods Full-sized 3DP liver models were developed and printed using transparent material based on anonymous CT scans. We used printed 3D models and conventional 2D CT scans of the liver to investigate thirty trainees with various levels of experience and different genders in the context of both small group teaching and formative assessment. We adopted a mixed methods approach involving both questionnaires and focus groups to collect the views of different trainees and monitors to assess trainees’ educational benefits and perceptions after progressing through different training programs. We used Objective Structured Clinical Examination (OSCE) and Likert scales to support thematic analysis of the responses to the questionnaires by trainees and monitors, respectively. Descriptive analyses were conducted using SPSS statistical software version 21.0. Results Overall, a 3DP model of the liver is of great significance for improving trainees’ understanding of surgical procedures and cooperation during operation. After viewing the personalized full-sized 3DP liver model, all trainees at the various levels exhibited significant improvements in their understanding of the key points of surgery (p

Abstract The Ediacaran Period marks a pivotal time in geodynamo evolution when the geomagnetic field is thought to approach the weak state where kinetic energy exceeds magnetic energy, as manifested by an extremely high frequency of polarity reversals, high secular variation, and an ultralow dipole field strength. However, how the geodynamo transitioned from this state into one with more stable field behavior is unknown. Here, we address this issue through a high-resolution magnetostratigraphic investigation of the ~494.5 million-year-old Jiangshanian Global Standard Stratotype and Point (GSSP) section in South China. Our paleomagnetic results document zones with rapid reversals, stable polarity and a ~80 thousand-year-long interval without a geocentric axial dipole field. From these changes, we suggest that for most of the Cambrian, the solid inner core had not yet grown to a size sufficiently large to stabilize the geodynamo. This unusual field behavior can explain paleomagnetic data used to define paradoxical true polar wander, supporting instead the rotational stability of the solid Earth during the great radiation of life in the Cambrian.

Abstract Sterol carrier protein 2 (SCP2) is highly expressed in human osteoarthritis (OA) cartilage, accompanied by ferroptosis hallmarks, especially the accumulation of lipid hydroperoxides (LPO). However, the role of SCP2 in chondrocyte ferroptosis remains unexplored. Here, we identify that SCP2 transports cytoplasmic LPO to mitochondria in RSL3-induced chondrocyte ferroptosis, resulting in mitochondrial membrane damage and release of reactive oxygen species (ROS). The localization of SCP2 on mitochondria is associated with mitochondrial membrane potential, but independent of microtubules transport or voltage-dependent anion channel. Moreover, SCP2 promotes lysosomal LPO increase and lysosomal membrane damage through elevating ROS. However, SCP2 is not directly involved in the cell membrane rupture caused by RSL3. Inhibition of SCP2 markedly protects mitochondria and reduces LPO levels, attenuating chondrocyte ferroptosis in vitro and alleviating the progression of OA in rats. Our study demonstrates that SCP2 mediates the transport of cytoplasmic LPO to mitochondria and the spread of intracellular LPO, accelerating chondrocyte ferroptosis.

For the complex structure of fibrous network materials, it is a challenge to analyze the network strength and deformation mechanism. Here, we identify a failure mode transition within the network material comprising brittle fibers and bonds, which is related to the strength ratio of the bond to the fiber. A failure criterion for this type of fibrous network is proposed to quantitatively characterize this transition between bond damage and fiber damage. Additionally, tensile experiments on carbon and ceramic fibrous network materials were conducted, and the experimental results show that the failure modes of these network materials satisfy the theoretical prediction. The relationship between the failure mode, the relative density of network and strength of the components is established based on finite element analysis of the 3D network model. The failure mode transforms from bond damage to fiber damage as increasing of bond strength. According to the transition of the failure modes in the brittle fibrous network, it is possible to tailor the mechanical properties of fibrous network material by balancing the competition between bond and fiber properties, which is significant for optimizing material design and engineering applications.

When addressing the technical challenges of achieving precise force tracking during the local polishing process of polishing robots, controlling the contact state between the robot and the workpiece surface is essential. To this end, a contact motion-planning strategy based on dynamic systems is designed to generate trajectory routes during local polishing. The trajectory simulation of the local modulation dynamic system is achieved through the employment of the support vector regression (SVR) algorithm with a Gaussian kernel, facilitating the learning process. The feasibility and stability of planning local paths are validated using the local modulation dynamic system. To maintain a constant contact force between the end-effector polishing robot and the workpiece, an integral adaptive impedance control strategy is utilized, enabling the robot’s compliant control. Subsequently, an experimental system for the polishing robot is constructed in order to verify the effectiveness of the motion-planning system. The experimental results demonstrate that the proposed motion-planning approach is applicable in practical polishing processes, ensuring smooth contact and maintaining the desired contact force when scanning nonlinear surfaces, and thus showcasing stability and practicality.

In order to effectively control and predict the settlement deformation of the surrounding ground surface caused by deep foundation excavation, the deep foundation pit project of Baoding City Automobile Technology Industrial Park is explored as an example. The initial population approach of the whale algorithm (WOA) is optimized using Cubic mapping, while the weights of the shrinkage envelope mechanism are adjusted to avoid the algorithm falling into local minima, the improved whale algorithm (IWOA) is proposed. Meanwhile, 10 benchmark test functions are selected to simulate the performance of IWOA, and the advantages of IWOA in learning efficiency and convergence speed are verified. The IWOA-LSTM deep foundation excavation deformation prediction model is established by optimizing the input weights and hidden layer thresholds in the deep long short-term memory (LSTM) neural network using the improved whale algorithm. The IWOA-LSTM prediction model is compared with LSTM, WOA-optimized LSTM (WOA-LSTM) and traditional machine learning, the results show that the final prediction score of the IWOA-LSTM prediction model is higher than the score of other models, and the prediction accuracy is better than that of traditional machine learning.