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Purpose: Most currently available scores for survival prediction of patients with bone metastasis lack accuracy. In this study, we present a novel quantified CIN (Chromosome Instability) score modeled from cfDNA copy number variation (CNV) for survival prediction.Experimental Design: Plasma samples collected from 67 patients with bone metastases from 11 different cancer types between November 2015 and May 2016 were sent through low-coverage whole genome sequencing followed by CIN computation to make a correlation analysis between the CIN score and survival prognosis. The results were validated in an independent cohort of 213 patients.Results: During the median follow-up period of 598 (95% CI 364–832) days until December 25, 2018, 124 (44.3%) of the total 280 patients died. Analysis of the discovery dataset showed that CIN score = 12 was the optimal CIN cutoff. Validation dataset showed that CIN was elevated (score ≥12) in 87 (40.8%) patients, including 5 (5.75%) with head and neck cancer, 11 (12.6%) with liver and gallbladder cancer, 11 (12.6%) with cancer from unidentified sites, 21 (24.1%) with lung cancer, 7 (8.05%) with breast cancer, 4 (4.60%) with thyroid cancer, 6 (6.90%) with colorectal cancer, 4 (4.60%) with kidney cancer, 2 (2.30%) with prostate cancer, and 16 (18.4%) with other types of cancer. Further analysis showed that patients with elevated CIN were associated with worse survival (p < 0.001). For patients with low Tokuhashi score (≤8) who had predictive survival of less than 6 months, the CIN score was able to distinguish patients with a median overall survival (OS) of 443 days (95% CI 301–585) from those with a median OS of 258 days (95% CI 184–332).Conclusion: CNV examination in bone metastatic cancer from cfDNA is superior to the traditional predictive model in that it provides a noninvasive and objective method of monitoring the survival of patients with spine metastasis.

Photobiomodulation (PBM) refers to the beneficial effect produced from low-energy light irradiation on target cells or tissues. Increasing evidence in the literature suggests that PBM plays a positive role in the treatment of retinal diseases. However, there is great variation in the light sources and illumination parameters used in different studies, resulting in significantly different conclusions regarding PBM’s therapeutic effects. In addition, the mechanism by which PBM improves retinal function has not been fully elucidated. In this study, we conducted a narrative review of the published literature on PBM for treating retinal diseases and summarized the key illumination parameters used in PBM. Furthermore, we explored the potential molecular mechanisms of PBM at the retinal cellular level with the goal of providing evidence for the improved utilization of PBM in the treatment of retinal diseases.

Tacrolimus is a widely used immunosuppressive drug in patients with autoimmune diseases. It has a narrow therapeutic window, thus requiring therapeutic drug monitoring (TDM) to guide the clinical regimen. This study included 193 cases of tacrolimus TDM data in patients with autoimmune diseases at Southern Medical University Nanfang Hospital from June 7, 2018, to December 31, 2020. The study identified nine important variables for tacrolimus concentration using sequential forward selection, including height, tacrolimus daily dose, other immunosuppressants, low-density lipoprotein cholesterol, mean corpuscular volume, mean corpuscular hemoglobin, white blood cell count, direct bilirubin, and hematocrit. The prediction abilities of 14 models based on regression analysis or machine learning algorithms were compared. Ultimately, a prediction model of tacrolimus concentration was established through eXtreme Gradient Boosting (XGBoost) algorithm with the best predictive ability (R2 = 0.54, mean absolute error = 0.25, and root mean square error = 0.33). Then, SHapley Additive exPlanations was used to visually interpret the variable’s impacts on tacrolimus concentration. In conclusion, the XGBoost model for predicting blood concentration of tacrolimus on the basis of real-world evidence has good predictive performance, providing guidance for the adjustment of regimen in clinical practice.

Complex illumination, solar flares and heavy smog on the sea surface have caused difficulties to accurately obtain high-quality imaging and multi-dimensional information of marine monitoring targets, such as oil spill, red tide and underwater vehicle wake. The principle of existing imaging mechanism is complex, and thus it is not practical to capture high-resolution infrared images efficiently. To combat this challenge by utilizing new infrared optical materials and single point diamond-turning technology, we designed and processed a simple, light and strong condensing ability medium and long wavelength infrared imaging optical system with large relative aperture, which can obtain high-quality infrared images. On top of this, with the training from a combination of infrared and visible light images, we also proposed a super-resolution network model, which is composed of a feature extraction layer, an information extraction block and a reconstruction block. The initial features of the input images are recognized in feature extraction layer. Next, to supply missing feature information and recover more details on infrared image extracted from a dense connection block, a feature mapping attention mechanism is introduced. Its main function is to transfer the important feature information of the visible light images in the information extraction block. Finally, the global feature information is integrated in the reconstruction block to reconstruct the high-resolution infrared image. We experimented our algorithm on both of the public Kaist datasets and self-collected datasets, and then compared it with several relevant algorithms. The results showed that our algorithm can significantly improve the reconstruction performance and reveal more detail information, and enhance the visual effect. Therefore, it brings excellent potential in dealing with the problem of low resolution of optical infrared imaging in complex marine environment.

Coronavirus disease 2019 (COVID-19) has become a global public health concern. We aimed to study the cytokine profile during the convalescent phase and its association with liver functions. We performed a retrospective study to investigate the longitudinal dynamic serum cytokine, liver function, and metabolomic profiles, as well as their potential correlations, from the viral replication phase to early convalescence. Our results demonstrated that liver injury was common. Liver injury was significantly associated with higher levels of interleukin (IL)-6 and IL-10 (p < 0.05). However, alanine aminotransferase levels decreased during the first week after hospital discharge (p < 0.01). In parallel, T-cell and B-cell immune response-stimulating cytokine IL-4, but not IL-2, was significantly elevated (p < 0.05). Furthermore, interferon-γ (IFN-γ) and tumor necrosis factor-α (TFN-α) levels increased, in contrast to the decrease in IL-6 and IL-10 levels; liver function returned to normal. The metabolomic analysis supported active recovery during early convalescence of COVID-19 patients that had distinct metabolic profiles associated with the hepatic tricarboxylic acid cycle, amino acid metabolism, and lipid metabolism. In addition, we identified a metabolomic association of IL-4 with liver repair. Our findings suggest that discharged patients continue to recover from the physiological effects of COVID-19, and the association of IL-4, IL-6, and IL-10 levels with metabolic changes and liver function repair may have important implications for clinical manifestations and treatment of COVID-19.

Reactive oxygen species induced by endoplasmic reitculum stress can be exploited for cancer therapy. Here, nanoparticles are targetted to the endoplasmic reticulum and, when accompanied by PDT, produce stress resulting in calreticulin exposure on the cell surface, which activates dendritic cells.

Directed protein degradation to target hard-to-drug proteins is a promising therapeutic approach. Here, the authors report the prospective discovery of small molecule “molecular glue” that inserts into a naturally occurring E3 ligase-substrate interface leading to degradation of substrate protein.

Renal fibrosis is a common pathological feature of chronic kidney disease (CKD) patients who progress to end-stage renal disease (ESRD). With the increasing incidence of CKD, it is of importance to develop effective therapies that blunt development of renal fibrosis. FFNT25 is a newly developed molecular compound that could be used to prevent fibrosis. In this study, we administered FFNT25 to rats following unilateral ureteral obstruction (UUO) to investigate its anti-fibrosis mechanism. Thirty-two Sprague-Dawley rats were randomly divided into four groups: (1) control (normal rats), (2) sham-operated, (3) UUO-operated + vehicle, and (4) UUO-operated + FFNT25. Two weeks after UUO, the rats were gavaged with either FFNT25 (20.6 mg/kg/day) or vehicle for two weeks. Serum, urine, and kidney samples were collected at the end of the study. FFNT25 reduced levels of renal fibrosis and decreased mRNA and protein levels of extracellular matrix (ECM) markers α-smooth muscle actin (α-SMA) and plasminogen activator inhibitor-1 (PAI-1) following UUO compared to vehicle treatment (n = 8, p

A novel Injection-rolling Nozzle (IRN) in an imprint system with continuous injection direct rolling (CIDR) for ultra-thin microstructure polymer guide light plates was developed to achieve uniform flow velocity and temperature at the width direction of the cavity exit. A novel IRN cavity was designed. There are eight of feature parameters of cavity were optimized by orthogonal experiments and numerical simulation. Results show that the flow velocity at the width direction of the IRN outlet can reach uniformity, which is far better than that of traditional cavity. The smallest flow velocity difference and temperature difference was 0.6 mm/s and 0.24 K, respectively. The superior performance of the IRN was verified through a CIDR experiment. Several 0.35-mm thick, 340-mm wide, and 10-m long microstructural Polymethyl Methacrylate (PMMA) guide light plates were manufactured. The average filling rates of the microgrooves with the aspect ratio 1:3 reached above 93%. The average light transmittance is 88%.

MicroRNAs (miRNAs) participated in the regulation of tumorigenesis, progression, metastasis, recurrence and chemo-resistance of cancers. However, the potential function of miRNAs in cancer stem cells (CSCs) or tumor-initiating cells (T-ICs) was not clearly elucidated. In the present study, we found that miR-186 expression was reduced in liver CSCs. Functional studies showed that miR-186 knockdown facilitated liver CSCs self-renewal and tumorigenesis. Conversely, forced miR-186 expression suppressed liver CSCs self-renewal and tumorigenesis. Mechanically, miR-186 downregulated PTPN11 via binding to its 3’-UTR in liver CSCs. The correlation of miR-186 and PTPN11 was confirmed in Hepatocellular carcinoma (HCC) patients’ tissues. Further study showed that interference of PTPN11 can abolished the discrepancy between miR-186 mimic and control HCC cells in self-renewal and the proportion of CSCs. Additionally, we found that miR-186 overexpression HCC cells were more sensitive to cisplatin treatment. Clinical cohort analysis showed that HCC patients with high miR-186 were benefited more from transcatheter arterial chemoembolization (TACE) treatment. In conclusion, our study demonstrates a new regulation mechanism of liver CSCs, a new target for HCC, and a biomarker for postoperative TACE.

RRM2, the small subunit of ribonucleotide reductase, is identified as a tumor promotor and therapeutic target. It is common to see the overexpression of RRM2 in chemo-resistant cancer cells and patients. RRM2 mediates the resistance of many chemotherapeutic drugs and could become the predictor for chemosensitivity and prognosis. Therefore, inhibition of RRM2 may be an effective means to enhance the anticancer activity of chemotherapy. This review tries to discuss the mechanisms of RRM2 overexpression and the role of RRM2 in resistance to chemotherapy. Additionally, we compile the studies on small interfering RNA targets RRM2, RRM2 inhibitors, kinase inhibitors, and other ways that could overcome the resistance of chemotherapy or exert synergistic anticancer activity with chemotherapy through the expression inhibition or the enzyme inactivation of RRM2.

The clinical pharmacodynamics of tacrolimus in renal transplant patients has significant interindividual variability. T lymphocytes were selected to study the pharmacodynamic response of tacrolimus, which was significantly correlated with renal function and the outcome of renal transplant patients. Ultra-performance liquid chromatography–quadrupole time-of-flight mass spectroscopy (UPLC/Q-TOF-MS) was performed to obtain the metabolic profiles of 109 renal transplant patients. A partial least squares (PLS) model was constructed to screen potential biomarkers that could predict the efficacy of tacrolimus. Multinomial logistic regression analysis established a bridge that could quantify the relationship between the efficacy of tacrolimus and biomarkers. The results showed a good correlation between endogenous molecules and the efficacy of tacrolimus. Metabolites such as serum creatinine, mesobilirubinogen, L-isoleucine, 5-methoxyindoleacetate, eicosapentaenoic acid, N2-succinoylarginine, tryptophyl-arginine, and butyric acid were indicated as candidate biomarkers. In addition, the key biomarkers could correctly predict the efficacy of tacrolimus with an accuracy of 82.5%. Finally, we explored the mechanism of individual variation by pathway analysis, which showed that amino acid metabolism was significantly related to the efficacy of tacrolimus. Moreover, orthogonal partial least squares discriminant analysis (OPLS-DA) showed that there was no difference in key metabolites among different pharmacodynamic groups at 1 month and 3 months after dose adjustment, suggesting that pharmacometabonomics is a useful tool to predict individual differences in pharmacodynamics and thus to facilitate individualized drug therapy.

The microrheological phenomenon of kaolin-filled polypropylene (kaolin/PP) composites was investigated for the first time. The microviscosity of kaolin/PP composites was studied by changing the melt temperature and shear rate. Then, injection moulding experiments of rectangular microgrooves with different aspect ratios using kaolin/PP composites and mechanical property tests of the samples were carried out. The results showed that with increasing kaolin content, the microviscosity of the kaolin/PP composites gradually increases. The shear rate had the greatest influence on the microviscosity, and the kaolin content had the least influence. When the aspect ratio of rectangular microgrooves is small, with an increasing kaolin content, the microgroove filling rate increases, and the microstructured sample geometric shape replication effect is good; however, when the aspect ratio reaches 10:1, the microgroove filling rate decreases with an increasing kaolin content. The microstructured sample geometric shape replication effect is also poor, and size effects appear. Different factors control the microrheological morphology of composites with different aspect ratios, including the shear deformation and viscous flow of composites. The increase in kaolin content leads to a decrease in the friction coefficient and an increase in the wear resistance of the composites. We concluded that the best composite formulation for kaolin/PP composites in microinjection is the 7KL/PP composite with 7% kaolin. When the aspect ratio is 5:1, the reproduction of the microstructured sample geometry is the best, and the comprehensive mechanical properties of the sample are the best.

Backgrounds: Ribonucleotide reductase (RR) catalyzes the essential step in the formation of all four deoxynucleotides. Upregulated activity of RR plays an active role in tumor progression. As the regulatory subunit of RR, ribonucleotide reductase subunit M2 (RRM2) is regarded as one of the effective therapeutic targets for DNA replication-dependent diseases, such as cancers. Recent studies have revealed that osalmid significantly inhibits the activity of RRM2, but the metabolic profile of osalmid remains unknown. Objective: The aim of this study was to clarify the metabolic profile including metabolites, isoenzymes and metabolic pathways of osalmid. The anti-human hepatocellular carcinoma activity and mechanism of metabolites were further investigated. Materials and methods: Ultra high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS) was used for identifying metabolites and for characterizing phase I and phase II metabolic pathways with recombinant enzymes or in human liver microsomes of osalmid. The eHiTS docking system was used for potential RRM2 inhibitor screening among metabolites. Cytotoxicity assays were performed for evaluating cell proliferation inhibitory activity of metabolites. Cell cycle assays and cell apoptosis assays were assessed by flow cytometry. Western blotting analysis of RRM2, cyclin D1, p21, p53, phosphorylated p53, Bcl-2 and Bax was performed to explore the anti-hepatocellular carcinoma mechanism of the active metabolites. Results: Ten metabolites of osalmid were identified, and none of them have been reported previously. Hydroxylation, glucuronidation, sulfonation, acetylation and degradation were recognized as the main metabolic processes of osalmid. Isozymes of CYP1A2, CYP2C9, UGT1A1, UGT1A6, UGT1A9, UGT2B7 and UGT2B15 were involved in phase I and phase II metabolism of osalmid. Metabolites M7, M8 and M10 showed higher binding affinities with the RRM2 active site than osalmid. Metabolite M7 exhibited potent inhibitory activity to hepatocellular carcinoma cell lines by both competitive inhibition and down-regulation of RRM2. Moreover, M7 significantly induced cell cycle arrest and apoptosis by activating p53-related pathways. Conclusions: The metabolic profile of osalmid was identified. M7 significantly inhibited human hepatocellular carcinoma progression by inhibiting RRM2 activity. Furthermore, M7 induced cell cycle arrest and apoptosis by activating p53-related signaling pathways.

Venetoclax has emerged as a breakthrough for treatment of leukemia with a wide interindividual variability in pharmacokinetics. Herein, a rapid, sensitive, and reliable UPLC-MS/MS method for quantification of venetoclax in plasma was developed and validated. The method was operated in the multiple-reaction monitoring (MRM) mode to detect venetoclax at m/z transition 868.5 > 321.0 and IS at 875.5 > 321.0, respectively. Protein precipitation prior to injection into the LC-MS/MS and the analyte was separated on an ACQUITY UPLC BEH C18 column by gradient elution with acetonitrile and 0.1% formic acid in water. Linear calibration curves were obtained in the range of 25–8000 ng/mL. The specificity, recovery, matrix effect, and stability also met the acceptance criteria of FDA guidance. The method was successfully applied to analyze plasma in acute myeloid leukemia (AML) patients. The peak plasma concentration (Cmax) of venetoclax in Chinese AML patient was 2966.0 ± 1595.0 ng/mL while the trough concentration (Cmin) was 1018.0 ± 729.4 ng/mL. Additionally, Cmax and Cmin showed a positive correlation with AST levels. Furthermore, Cmax was significantly higher in the older patients. The present method can be applied for TDM of venetoclax in treatment of hematological cancers.

Background/Aims: Nephropathy related with renin can be alleviated with ACE-inhibitors or AT1R blockers, whereas they might be ineffective after long-term administration because of a feedback production of enhanced renin. Therefore, it is urgent to develop a new category of anti-nephropathy medicine directly targeting renin. Riligustilide (C20), originally isolated from the Chinese herb Ligusticumporteri, a rhizome, was confirmed effective against many diseases. Methods: The therapeutic effect of C20 on renal injury and its underlying mechanism were investigated in three different nephrotic models, which were spontaneously hypertension rats (SHR) model, diabetic nephropathy in BTBR ob/ob mice model and 5/6-nephrectomized (5/6NX) rats model. Results: The intensity of kidney fibrosis was extensively decreased in the C20-treated rats compared to the vehicle animals. C20 significantly alleviated renal injury much more in 5/6 NX rats than in vehicle group. The rats in 5/6 NX without administrated C20 developed albuminuria earlier with more severe symptoms. Additionally, our findings showed that C20 down-regulated the renin expression and relocation of CREB-CBP complex in vivo and in vitro. Conclusion: C20 plays importantly reno-protective roles most likely through the relocation of CREB-CBP complex.

Photosensitizer, proper laser irradiation, and oxygen are essential components for effective photodynamic therapy (PDT) in clinical cancer therapy. However, native hypoxic tumoral microenvironment is a major barrier hindering photodynamic reactions in vivo. Thus, we have prepared biocompatible liposomes by loading complexes of oxygen-carrier (hemoglobin, Hb) and photosensitizer (indocyanine green, ICG) for enhanced PDT against hypoxic tumor. Ideal oxygen donor Hb, which is an oxygen-carried protein in red blood cells, makes such liposome which provide stable oxygen supply. ICG, as a photosensitizer, could transfer energy from lasers to oxygen to generate cytotoxic reactive oxygen species (ROS) for treatment. The liposomes loading ICG and Hb (LIH) exhibited efficient tumor homing upon intravenous injection. As revealed by T2-weighted magnetic resonance imaging and immunohistochemical analysis, the intratumoral hypoxia was greatly alleviated, and the level of hypoxia inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) in tumor was obviously down-regulated. A weak PDT efficiency was found in cells incubated in simulated hypoxia condition in vitro, while PDT effect was dramatically enhanced in LIH treated hypoxia cells under near-infrared (NIR) laser, which was mainly attributed to massive generation of ROS with sufficient oxygen supply. ROS trigger oxidative damage of tumors and induce complete suppression of tumor growth and 100% survival rate of mice, which were also in good health condition. Our work highlights a liposome-based nanomedicine that could effectively deliver oxygen to tumor and alleviate tumor hypoxia state, inducing greatly improved efficacy compared to conventional cancer PDT and demonstrates the promise of modulating unfavorable tumor microenvironment with nanotechnology to overcome limitations of cancer therapies.

Because of the extended period of clinic data collection and huge size of analyzed samples, the long-term and large-scale pharmacometabonomics profiling is frequently encountered in the discovery of drug/target and the guidance of personalized medicine. So far, integration of the results (ReIn) from multiple experiments in a large-scale metabolomic profiling has become a widely used strategy for enhancing the reliability and robustness of analytical results, and the strategy of direct data merging (DiMe) among experiments is also proposed to increase statistical power, reduce experimental bias, enhance reproducibility and improve overall biological understanding. However, compared with the ReIn, the DiMe has not yet been widely adopted in current metabolomics studies, due to the difficulty in removing unwanted variations and the inexistence of prior knowledges on the performance of the available merging methods. It is therefore urgently needed to clarify whether DiMe can enhance the performance of metabolic profiling or not. Herein, the performance of DiMe on 4 pairs of benchmark datasets was comprehensively assessed by multiple criteria (classification capacity, robustness and false discovery rate). As a result, integration/merging-based strategies (ReIn and DiMe) were found to perform better under all criteria than those strategies based on single experiment. Moreover, DiMe was discovered to outperform ReIn in classification capacity and robustness, while the ReIn showed superior capacity in controlling false discovery rate. In conclusion, these findings provided valuable guidance to the selection of suitable analytical strategy for current metabolomics.

The viscous flow activation energy and non-Newtonian index properties of polymer based on feature size were studied through a series of experiments on the rheological properties of amorphous polymer polymethyl methacrylate (PMMA), semi-crystalline polymer polypropylene (PP), and crystalline polymer high-density polyethylene (HDPE) using capillary die with hole diameters of φ0.3 mm, φ0.5 mm, φ1.0 mm, and φ2.0 mm. The results show that the viscous flow activation energy of PMMA decreases with the feature size under microscopic scale. And the viscous flow activation energy of PP and HDPE increases with hole diameters of the die. Under macroscopic scale, the difference in viscous flow activation energy of all polymer materials is significantly reduced with hole diameters of the die. For the non-Newtonian index of the three polymer materials, it decreases with the feature size under the microscopic scale while it increases or does not change with the feature size under the macroscopic scale. At the same time, for different high polymer materials, the viscous flow activation energy model (SVAE model) and non-Newtonian index model (SNNE model) based on feature size were established. Finally, the accuracy and effectiveness of the SVAE model and the SNNE model are verified by comparing with the traditional model and reference data. The viscous flow activation energy and non-Newtonian index values of the polymer material can be calculated conveniently and accurately.

Polymeric optical sheets are significant components in large-scale display devices and are difficult to fabricate due to small size and high accuracy of large-area microstructures. As a newly developed molding technique, injection-rolling is capable of continuously and efficiently achieving large-area microstructures on the polymer surface with short time and high replication. However, the microstructure-forming mechanism during the injection-rolling process has not been fully understood. In this paper, a three-dimensional steady-state heat-flow coupling simulation model of the injection-rolling zone was established to obtain the distributions of the polymer state transition interfaces. According to the state transition interfaces, the entire microstructure-forming process was numerically simulated by dividing into filling and embossing stages to systematically analyze the effects of the polymer state transition interface on filling rate. After this, the relationship between process parameters such as injection temperature, rolling speed, and roll temperature and polymer state transition interface was investigated to develop a position prediction model of the state transition interface. In addition, the optical sheet injection-rolling experiments were also carried out to reveal that the filling rate of the microstructures on the optical sheet can be affected by varying the positions of the state transition interfaces. Therefore, the microstructure-forming mechanism could be revealed as theoretical guidance for the subsequent injection-rolling production with high quality and high efficiency.

The rejuvenation of Zr52.5Cu17.9Ni14.6Al10Ti5 bulk metallic glasses (BMGs) by ultrasonic vibration-assisted elastic deformation (UVEF) was studied herein. The UVEF-treated samples demonstrate an obvious rejuvenation and have a higher relaxation enthalpy and a smaller range of supercooled liquid regions than the as-cast samples. The fracture of the rejuvenated amorphous alloy is mainly ductile fracture, and shear deformation occurs in the deformation region. It is also found that as the amplitude increases, the free volume of the rejuvenated amorphous alloy increases, the yield strength and the elastic modulus decrease, and the formability increases. The free-volume content is used to characterize the degree of rejuvenation, and a mathematical model of the relationship between the ultrasonic amplitude and free volume is established. In addition, it is found that the ultrasonic vibration stress induces the additional free volume in the Zr-based bulk metallic glasses and improves the plasticizing behavior. The temperature rise caused by the ultrasonic thermal effect does not induce additional free volume.

Compared with laser-based 3D printing, fused deposition modelling (FDM) 3D printing technology is simple and safe to operate and has a low cost and high material utilization rate; thus, it is widely used. In order to promote the application of FDM 3D printing, poly-ether-ether-ketone (PEEK) was used as a printing material to explore the effect of multi-factor coupling such as different printing temperatures, printing directions, printing paths, and layer thicknesses on the tensile strength, bending strength, crystallinity, and grain size of FDM printed PEEK parts. The aim was to improve the mechanical properties of the 3D printed PEEK parts and achieve the same performance as the injection molded counterparts. The results show that when the thickness of the printed layer is 0.1 mm and the printing path is 180° horizontally at 525 °C, the tensile strength of the sample reaches 87.34 MPa, and the elongation reaches 38%, which basically exceeds the tensile properties of PEEK printed parts reported in previous studies and is consistent with the tensile properties of PEEK injection molded parts. When the thickness of the printed layer is 0.3 mm, the printing path is 45°, and with vertical printing direction at a printing temperature of 525 °C, the bending strength of the sample reaches 159.2 MPa, which exceeds the bending performance of injection molded parts by 20%. It was also found that the greater the tensile strength of the printed specimen, the more uniform the size of each grain, and the higher the crystallinity of the material. The highest crystallinity exceeded 30%, which reached the crystallinity of injection molded parts.

Taking the Poiseuille flow of a molten polymer in parallel plates as the research object and polymethyl methacrylate (PMMA) as the research material, an all-atom analysis model of the molecular dynamic flow of polymer macromolecules is established according to the Navier slip law. The effects of wall wettability and external pressure on the wall slip behaviour of polymer macromolecules, as well as the spatial evolution process of the entanglement–unentanglement process of polymer chains near the wall under different shearing effects, were studied. The interface thermal resistance rule was explored, and an interface thermal resistance model considering the wall slip behaviour was established. Finally, a micro-injection experiment was used to verify the validity and accuracy of the model. The results show that when the wall is hydrophobic, the polymer melt exhibits significant wall slip. As the external pressure increases, the wall slip speed and the slip length increase. However, after a certain pressure is exceeded, the growth rate of the slip length is basically zero. As the external pressure increases, the PMMA molecular chains gradually start to separate, the single molecular chain becomes untangled from the entangled grid, and the chain detaches from the wall after exceeding a certain threshold. Wall slip reduces the interface thermal resistance between the solid–liquid interface and enhances the interface heat transfer performance. The interface thermal resistance value calculated by molecular dynamics can more accurately reflect the heat conduction rule of the solid–liquid interface at the micro/nanoscale than that measured by the thermal resistance experiment, indicating that the micro/nano interface thermal resistance obtained by molecular dynamics simulation is reliable.

A new sintering method, namely ultrasonic assisted sintering (UAS), has been proposed using mechanical heat converted from high frequency motion between particles. Pure aluminum specimens with diameter of 5 mm and thickness of ~2 mm have been successfully sintered in two seconds. Based on the thermodynamic analysis, the underlying heating mechanism is quantitatively interpreted, which involves high-frequency interparticle friction and plastic deformation driven by ultrasonic squeezing. Consequently, temperature rises rapidly at a speed of about 300 K/s, and the maximum temperature reaches up to 0.9 times of melting point of the aluminum during UAS. The sintered specimens have a high density of dislocations, under the combined effects of dislocations and undulating stress field, volume diffusion coefficient for sintering increases by several orders of magnitude, therefore, rapid densification can be accomplished in seconds. In addition, the sintered aluminum has ultrahigh nanohardness (~1.13 GPa), which can be attributed to the hierarchical structure formed during UAS process.

Constructing regular micro-structures with certain geometric characteristics on the surface of the polymer part can obtain some specific functions. Micro ultrasonic powder molding (micro-UPM) is an efficient processing technique for the fabrication of well-filled micro-structured Polypropylene (PP) parts. The micro-structure array on the surface of the core insert was obtained by low speed wire electrical discharge machining (WEDM-LS). PP polymer surfaces with micro-structured patterns were successfully replicated from the core insert surface after micro-UPM. By studying the detailed topography characterizations of micro-structured PP parts, the effects of processing parameters (ultrasonic energy, welding pressure and holding time) on the micro-structured filling show that when PP polymer was formed under the conditions of 1000 J, 115 kPa and 8 s during micro-UPM, well-filled micro-structured parts can be obtained. Besides, without low surface energy coating modification, the water contact angles (WCAs) of micro-structured PP parts increased from 85.3° to 146.8°, indicating that the wettability of the surface can be changed by replicating the micro-structure on PP parts after micro-UPM.

A micro-ultrasonic (MU) viscosity model based on ultrasonic-assisted vibration micro-injection for high- flow length ratio polymer parts was established. This model considered the effects of ultrasonic energy and the characteristic microdimension. Ultrasonic energy parameters (such as the ultrasonic amplitude, frequency, and ultrasound velocity), the characteristic microdimension, and the molecular chain length (MCL) were introduced into the MU viscosity model. An ultrasonic micro-injection experimental platform was built on an injection molding machine. Polypropylene (PP) filling experiments were carried out using microgrooves with different flow length ratios (depth-to-width ratios of 3:1, 5:1, and 10:1). The validity and accuracy of the MU viscosity model were examined through a filling experiment with polypropylene (PP) microgroove injection molding and by a flow pressure difference experiment with polystyrene (PS). The results showed that the MU viscosity model was in better agreement with the experimental results compared to other models. The maximum error of the MU model was 4.9%. Ultrasound-assisted vibration had great effects on the filling capacity for microgrooves with high flow length ratios (depth-to-width ratios greater than 5:1). The filling capacity increased as the ultrasonic amplitude increased.

Stellera chamaejasme L. (Thymelaeaceae) is widely distributed in Mongolia, Tibet and the northern parts of China. Its roots are commonly used as “Langdu”, which is embodied in the Pharmacopoeia of the P.R. China (2010) as a toxic Traditional Chinese Medicine. It is claimed to have antivirus, antitumor and antibacterial properties in China and other Asian countries. Studies were carried out to characterize the inhibition of neochamaejasmin B (NCB) on P-glycoprotein (P-gp, ABCB1, MDR1). Rhodamine-123 (R-123) transport and accumulation studies were performed in MDCK-hMDR1 cells. ABCB1 (MDR1) mRNA gene expression and P-gp protein expression were analyzed. Binding selectivity studies based on molecular docking were explored. R-123 transport and accumulation studies in MDCK-hMDR1 cells indicated that NCB inhibited the P-gp-mediated efflux in a concentration-dependent manner. RT-PCR and Western blot demonstrated that the P-gp expression was suppressed by NCB. To investigate the inhibition type of NCB on P-gp, Ki and Ki’ values were determined by double-reciprocal plots in R-123 accumulation studies. Since Ki was greater than Ki’, the inhibition of NCB on P-gp was likely a mixed type of competitive and non-competitive inhibition. The results were confirmed by molecular docking in our current work. The docking data indicated that NCB had higher affinity to P-gp than to Lig1 ((S)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one).

One of the commonest causes of end-stage renal disease is diabetic kidney disease (DKD). Renal fibrosis, characterized by the accumulation of extracellular matrix (ECM) proteins in glomerular basement membranes and the tubulointerstitium, is the final manifestation of DKD. The TGF-β pathway triggers epithelial-to-mesenchymal transition (EMT), which plays a key role in the accumulation of ECM proteins in DKD. DCCT/EDIC studies have shown that DKD often persists and progresses despite glycemic control in diabetes once DKD sets in due to prior exposure to hyperglycemia called “metabolic memory.” These imply that epigenetic factors modulate kidney gene expression. There is evidence to suggest that in diabetes and hyperglycemia, epigenetic histone modifications have a significant effect in modulating renal fibrotic and ECM gene expression induced by TGF-β1, as well as its downstream profibrotic genes. Histone modifications are also implicated in renal fibrosis through its ability to regulate the EMT process triggered by TGF-β signaling. In view of this, efforts are being made to develop HAT, HDAC, and HMT inhibitors to delay, stop, or even reverse DKD. In this review, we outline the latest advances that are being made to regulate histone modifications involved in DKD.

In this paper, micro-structured polymer parts were efficiently and accurately fabricated by micro-injection molding using a micro-structured mold core machined by wire electrical discharge machining (WEDM). The objective was to realize low-cost mass production and manufacturing of micro-structured polymer products. The regular micro-structured mold core was manufactured by precise WEDM. The micro-structured polymer workpieces were rapidly fabricated by micro-injection molding and the effects of the micro-injection molding process parameters on replication rate and surface roughness of micro-structured polymers were systematically investigated and analyzed. It is shown that the micro-structured polymer can be rapidly and precisely fabricated by the proposed method. The experimental results show the minimum size machining error of the micro-structured mold core and the maximum replication rate of micro-formed polymer were 0.394% and 99.12%, respectively. Meanwhile, the optimal micro-injection molding parameters, namely, jet temperature, melt temperature, injection velocity, holding pressure and holding time were 195 °C, 210 °C, 40 mm/min, 7 Mpa and 5 s, respectively. The surface roughness Ra at the groove bottom and top of the micro-structured polymer workpieces achieved minimum values of 0.805 µm and 0.972 µm, respectively.

Precise micro-grinding machining was proposed to fabricate regular and controllable micro-grooved array structures on the surface of mold cores to realize the mass production and manufacturing of micro-structured polymer components by micro injection molding in this paper. First, the 3D topographies and section profiles of micro-ground mold cores and micro-formed polymers with different micro-structure parameters were presented. Then, the surface roughness of mold cores and polymers were compared. Next, the relationships between machining accuracy of mold core ground by micro-grinding and filling rates of micro-structured polymer formed by micro injection molding were investigated. Finally, the influences of micro injection molding parameters on the filling rate of micro-structures polymer were investigated. It is shown that the micro-structured polymer can be effectively and rapidly fabricated using the proposed method. The experimental results indicate the highest form accuracy of the micro-grooved mold core and the filling rate of micro-structured polymer can reach to 4.05 µm and 99.30%, respectively. It is found that the filling rate of the micro-structured polymer roughly increased with increasing machining accuracy of the mold core. The injection pressure had the greatest influence on the filling rate of the injection formed polymer, while the melt temperature had the least influence.

Continuous injection direct rolling (CIDR) combined intermittent injection and rolling process is a new technology for molding optical polymer plates with microstructured patterns; research on forming PMMA optical plates is an aspect of it in this paper. The equipment of CIDR process consists of plastic injection module, precision rolling module, and automatic coiling module. Based on the establishing mathematical CIDR models, numerical analysis was used to explode the distribution of velocity, temperature, and pressure in injection-rolling zone. The simulation results show that it is feasible to control the temperature, velocity, and injection-rolling force, so it can form polymer plate under certain process condition. CIDR experiment equipment has been designed and produced. PMMA optical plate was obtained by CIDR experiments, longitudinal thickness difference is 0.005 mm/200 mm, horizontal thickness difference is 0.02/200 mm, transmittance is 86.3%, Haze is 0.61%, and the difference is little compared with optical glasses. So it can be confirmed that CIDR process is practical to produce PMMA optical plates.

Sequences of the complete nuclear ribosomal DNA (rDNA) gene from five individual Paramphistomum cervi were determined for the first time. The five complete rDNA sequences, which included the 18S rDNA, the internal transcribed spacer 1 (ITS1), the 5.8S rDNA, the internal transcribed spacer 2 (ITS2), the 28S rDNA, and the intergenic spacer (IGS) regions, had a length range of 8,493–10,221 bp. The lengths of the investigated 18S, ITS1, 5.8S, ITS2, and 28S rDNA sequences, which were 1,994 bp, 1,293 bp, 157 bp, 286 bp, and 4,186 bp, respectively, did not vary. However, the IGS rDNA sequences had a length range of 577–2,305 bp. The 5.8S and ITS-2 rDNA sequences had 100% identity among the five investigated samples, while the identities among the IGS had a range of 53.7–99.8%. A comparative analysis revealed that different types and numbers of repeats were found within each ITS1 and IGS region, which may be related to the length polymorphism of IGS. The phylogenetic position of P. cervi in Paramphistomatidae was analyzed based on the 18S rDNA sequences. These results will aid in studying the intra- and interspecific variation of the Paramphistomatidae and the systematics and phylogenetics of Digenea.

Cognitive diagnostic assessment based on Bayesian networks (BN) is developed in this paper to evaluate student understanding of the physical concept of buoyancy. we propose a three-order granular-hierarchy BN model which accounts for both fine-grained attributes and high-level proficiencies. Conditional independence in the BN structure is tested and utilized to validate the proposed model. The proficiency relationships are verified and the initial Q-matrix is refined. Then, an optimized granular hierarchy model is constructed based on the updated Q-matrix. All variants of the constructed models are evaluated on the basis of the prediction accuracy and the goodness-of-fit test. The experimental results demonstrate that the optimized granular-hierarchy model has the best prediction and model-fitting performance. In general, the BN method not only can provide more flexible modeling approach, but also can help validate or refine the proficiency model and the Q-matrix and this method has its unique advantage in cognitive diagnosis.

This research endeavors to address the persistent dissemination of public opinion within social networks, mitigate the propagation of inappropriate content on these platforms, and enhance the overall service quality of social networks. To achieve these objectives, Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) techniques are employed in this research to develop a predictive model for anticipating public opinion crises in social network mining. This model furnishes users with a valuable reference for subsequent decisionmaking processes. The initial phase of this research involves the collection of user behavior data from social networks using IoT technologies, serving as the basis for extensive big data analysis and neural network research. Subsequently, a social network text categorization model is constructed by amalgamating the Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) architecture, elucidating the training procedures of deep learning methodologies within CNN and LSTM networks. The effectiveness of this approach is subsequently validated through comparisons with other deep learning techniques. Based on the obtained results and findings, the CNN-LSTM model demonstrates a noteworthy accuracy rate of 92.19% and an exceptionally low loss value of 0.4075. Of particular significance is the classification accuracy of the CNN-LSTM algorithm within social network datasets, which surpasses that of alternative algorithms, including CNN (by 6.31%), LSTM (by 4.43%), RNN (by 3.51%), Transformer (by 40.29%), and Generative Adversarial Network (GAN) (by 4.49%). This underscores the effectiveness of the CNN-LSTM algorithm in the realm of social network text classification. [ABSTRACT FROM AUTHOR]