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This paper investigates the effect of three different alkalis, namely ammonia (NH4OH), ethylenediamine (EDA), and tetrabutylammonium hydroxide (TBAOH) on the stability of colloidal silica, with pH controlled within the range of 8–11. As a result, NH4OH greatly promotes the stability of silica sol at first due to the strong solvation ability of NH4+ and then the stability begins to decrease because the electric double layer of silica is compressed. The addition of EDA into silica system leads to a reduction in the stability evidently followed by a slight increase, which can be explained by the cationic bridging effect of the ethylenediammonium cations. Meanwhile, the effect of TBAOH on silica dispersion is analogous to EDA, mainly caused by the hydrophobic and steric effects. The abovementioned relevant stability mechanisms are involved in non-DLVO theory. [ABSTRACT FROM AUTHOR]

It is indispensable to explore the appropriate level of surface residual stress to enhance the wear resistance of coated tools. TiAlSiN-coated carbide tools with dissimilar surface residual compressive stresses (− 300 ~ − 600 MPa) are acquired via micro-sandblasting, which are used in the high-speed sliding friction experiments and turning experiments. The influence of residual stress on the sliding wear and cutting wear performance of TiAlSiN coated tools is investigated. The results show that with the improvement of surface residual compressive stress (absolute value), the friction coefficient and wear rate are reduced. The sliding wear resistance of the coated tool is enhanced. In addition, the cutting performance of the tool is also improved with the increase of residual compressive stress (absolute value). However, the excessive surface residual compressive stresses (absolute value) can lead to severe coating peeling, which in turn impairs the capability of wear resistance. The TiAlSiN-coated carbide tool with the stress of − 500 MPa presents the best wear resistance in the high-speed sliding wear and cutting wear process. [ABSTRACT FROM AUTHOR]

Low-voltage soft actuators with large displacement, long actuation durability, and fast response time have aroused great attention in soft robotics, wearable devices, haptic devices, and implantable or disposal biomedical devices. Herein, we report a low-voltage electroactive ionic soft actuator based on the sulfonated cellulose nanowhisker (SCN), microfibrillated cellulose (MFC), ionic liquids (IL), and graphene nanoplatelet (GN). The proposed SCN/MFC-IL-GN (0.1wt%) actuator demonstrated a large bending displacement (6.6 mm under ± 1 V sinusoidal input signal at 0.1 Hz, low driving voltage (as low as 0.25 V), wide actuation frequency (0.1 to 5.0 Hz), and long actuation durability (96.7% retention for 1 h), all of which stemmed from the strong crosslinking and ionic interactions among the functional sulfonated groups of SCN, hydroxyl groups of MFC, IL, and GN. Furthermore, the designed actuator was successfully employed to imitate the human finger's behaviors including turning on/off the flashlight and sliding electronic photographs on a smart phone screen. Therefore, the proposed SCN/MFC-IL-GN actuator has great potential in artificial muscles, soft robots, haptic devices, and wearable devices because of its low excitation voltage, large bending displacement, long actuation durability, and biofriendly property. [ABSTRACT FROM AUTHOR]

Purpose: Tertiary lymphoid structures (TLSs) and CD8 + T-cells are potential prognostic indicators for pancreatic ductal adenocarcinoma (PDAC). We established a novel scoring system for evaluating the risk for PDAC based on TLS- and CD8 + T-cell-related genes. Methods: We analyzed single-cell sequence data from PDAC patients in the Genome Sequence Archive. Bioinformatics and machine algorithms established and validated a scoring method (T-C score) based on PDAC survival-related genes highly expressed in TLSs and CD8 + T-cells. Patients were stratified into the low- and high-T-C score groups. Differences in survival, pathway enrichment, mutation status, immune cell infiltration, expression of immune checkpoint-associated genes, tumor stemness, and response to antitumor therapy were compared through computer simulation methods. Results: Overall survival differed significantly between the training and validation cohorts’ low- and high-T-C score groups. The low-T-C score group correlated with lower tumor mutation burden and lower levels of tumor stemness compared with the high-T-C score group. Patients with lower T-C scores exhibited advantages in immunotherapeutic responses and might be more sensitive to the chemotherapeutic regimen and multi-kinase inhibitors. Conclusion: The T-C score could serve as an effective model for predicting the survival and therapeutic responses of patients with PDAC. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) prevention requires early detection and removal of adenomas. We aimed to develop a computational model for real-time detection and classification of colorectal adenoma. Computationally constrained background based on real-time detection, we propose an improved adaptive lightweight ensemble model for real-time detection and classification of adenomas and other polyps. Firstly, we devised an adaptive lightweight network modification and effective training strategy to diminish the computational requirements for real-time detection. Secondly, by integrating the adaptive lightweight YOLOv4 with the single shot multibox detector network, we established the adaptive small object detection ensemble (ASODE) model, which enhances the precision of detecting target polyps without significantly increasing the model's memory footprint. We conducted simulated training using clinical colonoscopy images and videos to validate the method's performance, extracting features from 1148 polyps and employing a confidence threshold of 0.5 to filter out low-confidence sample predictions. Finally, compared to state-of-the-art models, our ASODE model demonstrated superior performance. In the test set, the sensitivity of images and videos reached 87.96% and 92.31%, respectively. Additionally, the ASODE model achieved an accuracy of 92.70% for adenoma detection with a false positive rate of 8.18%. Training results indicate the effectiveness of our method in classifying small polyps. Our model exhibits remarkable performance in real-time detection of colorectal adenomas, serving as a reliable tool for assisting endoscopists. [ABSTRACT FROM AUTHOR]

The low crystallization rate and long molding time of poly(ethylene terephthalate) (PET) restricts its application in the field of engineering plastics. PET/graphene oxide (GO) composites were synthesized through in situ polymerization method with dimethyl terephthalate (DMT), ethylene glycol (EG) as reactants and GO as filler in order to overcome the above shortcomings. Influence of GO on the crystallization performance of PET was investigated. It was revealed GO raised the crystallization temperature and crystallization rate of PET, demonstrating the excellent nucleation capability of GO. The mechanism of PET nucleation induced by GO was investigated by Avrami equation and Hoffman-Lauritzen theory. It was obvious the crystallization behavior of PET was improved by reducing the free energy of nucleation and the fold surface free energy of PET caused by GO. Moreover, the non-isothermal kinetics of thermal decomposition of PET and PET/GO composites were studied by Friedman method. It was obvious that all of PET and PET/GO composites exhibited a fine thermal stability with no significant mass loss observed up to 370 °C (< 0.5%). The addition of GO improved the thermal stability of PET through raising the apparent activation energy, inhibiting the escape of volatile products and absorbing the degradation products in PET thermal decomposition procedure. [ABSTRACT FROM AUTHOR]

Introduction: Previous studies have explored prediction value of serum metabolites in neoadjuvant chemoradiation therapy (NCRT) response for rectal cancer. To date, limited literature is available for serum metabolome changes dynamically through NCRT. Objectives: This study aimed to explore temporal change pattern of serum metabolites during NCRT, and potential metabolic biomarkers to predict the pathological response to NCRT in locally advanced rectal cancer (LARC) patients. Methods: Based on dynamic UHPLC-QTOF-MS untargeted metabolomics design, this study included 106 LARC patients treated with NCRT. Biological samples of the enrolled patients were collected in five consecutive time-points. Untargeted metabolomics was used to profile serum metabolic signatures from LARC patients. Then, we used fuzzy C-means clustering (FCM) to explore temporal change patterns in metabolites cluster and identify monotonously changing metabolites during NCRT. Repeated measure analysis of variance (RM-ANOVA) and multilevel partial least-squares discriminant analysis (ML-PLS-DA) were performed to select metabolic biomarkers. Finally, a panel of dynamic differential metabolites was used to build logistic regression prediction models. Results: Metabolite profiles showed a clearly tendency of separation between different follow-up panels. We identified two clusters of 155 serum metabolites with monotonously changing patterns during NCRT (74 decreased metabolites and 81 increased metabolites). Using RM-ANOVA and ML-PLS-DA, 8 metabolites (L-Norleucine, Betaine, Hypoxanthine, Acetylcholine, 1-Hexadecanoyl-sn-glycero-3-phosphocholine, Glycerophosphocholine, Alpha-ketoisovaleric acid, N-Acetyl-L-alanine) were further identified as dynamic differential biomarkers for predicting NCRT sensitivity. The area under the ROC curve (AUC) of prediction model combined with the baseline measurement was 0.54 (95%CI = 0.43 ~ 0.65). By incorporating the variability indexes of 8 dynamic differential metabolites, the prediction model showed better discrimination performance than baseline measurement, with AUC = 0.67 (95%CI 0.57 ~ 0.77), 0.64 (0.53 ~ 0.75), 0.60 (0.50 ~ 0.71), and 0.56 (0.45 ~ 0.67) for the variability index of difference, linear slope, ratio, and standard deviation, respectively. Conclusion: This study identified eight metabolites as dynamic differential biomarkers to discriminate NCRT-sensitive and resistant patients. The changes of metabolite level during NCRT show better performance in predicting NCRT sensitivity. These findings highlight the clinical significance of metabolites variabilities in metabolomics analysis. [ABSTRACT FROM AUTHOR]

Triaxial braided composites employed as structural components need to be drilled for mechanical connections. This study is to investigate the thrust force, temperature elevation, and drilling-induced damages with varying machining parameters in the drilling of triaxial braided CFRP. A high-resolution infrared thermography was carried out to capture the temperature of the panel side surface and the drill-exit surface of CFRP. The damage characteristic of drilled hole was evaluated, and a relationship between force, temperature, and hole damage was established. The obtained results indicate that the temperature of triaxial braided CFRP was mainly transferred along the fiber direction. The temperature isothermal at the drill-exit surface developed from polygonal to roughly circular with the increase of drilling depth. The braided yarns tended to deflect, and induced poorly cut fibers due to the more heat generation with the low feed, making the matrix behaved from brittle to ductile and therefore resulting in more burrs. The increase of spindle speed could restrain the burrs. A larger thrust force with high feed will result in fiber-resin debonding and more tearing defects. The delamination occurred at the interface of fiber bundles at the outermost layer with high thrust force and cracks propagated along the yarn direction. [ABSTRACT FROM AUTHOR]