In order to improve the CO catalytic oxidation performance of a Pt/TiO2 catalyst, a series of Pt/TiO2 catalysts were prepared via an impregnation method in this study, and various characterization ...methods were used to explore the effect of TiO2 calcination pretreatment on the CO catalytic oxidation performance of the catalysts. The results revealed that Pt/TiO2 (700 °C) prepared by TiO2 after calcination pretreatment at 700 °C exhibits a superior CO oxidation activity at low temperatures. After calcination pretreatment, the catalyst exhibited a suitable specific surface area and pore structure, which is beneficial to the diffusion of reactants and reaction products. At the same time, the proportion of adsorbed oxygen on the catalyst surface was increased, which promoted the oxidation of CO. After calcination pretreatment, the adsorption capacity of the catalyst for CO and CO2 decreased, which was beneficial for the simultaneous inhibition of the CO self-poisoning of Pt sites. In addition, the Pt species exhibited a higher degree of dispersion and a smaller particle size, thereby increasing the CO oxidation activity of the Pt/TiO2 (700 °C) catalyst.
A tripodal quinone-cyanine dye having one donor and three acceptors, that is, one quinone and three N-methylbenzothiazolium moieties, QCy(MeBT)3, was synthesized by simple Knoevenagel condensation ...between 2-hydroxybenzene-1,3,5-tricarbaldehyde and N-methyl-2-methylbenzothiazolium iodide. The 700 nm (λex, 570 nm) and 600 nm (λex, 470 nm) fluorescence emission of QCy(MeBT)3 was significantly and individually enhanced with the addition of G-quadruplex (G4) DNA and double-stranded DNA (dsDNA), respectively. The results of docking simulations and the response against the viscosity change revealed that the dual-fluorescence response was caused by the difference in the binding mode of QCy(MeBT)3 depending on the DNA structure. The results of fluorescence microscopy imaging experiments using QCy(MeBT)3 suggested that G4 DNAs and dsDNAs in the cell nucleus can be imaged with near-infrared (NIR, 700 nm) and red (600 nm) fluorescence emissions. Furthermore, pyridostatin-induced G4 formation in the living cells can be imaged with NIR fluorescence. The results indicated that QCy(MeBT)3 has huge potential to be a NIR-fluorescent molecular probe for analyzing the structural dynamics of nucleic acids in living cells with a normal fluorescence microscope.
In-class teaching evaluation, which is utilized to assess the process and effect of both teachers' teaching and students' learning in a classroom environment, plays an increasingly crucial role in ...supervising and promoting education quality. With the rapid development of artificial intelligence (AI) technology, the concept of smart education has been constantly improved and gradually penetrated into all aspects of education application. Considering the dominant position of classroom teaching in elementary and undergraduate education, the introduction of AI technology into in-class teaching evaluation has become a research hotspot. In this paper, we propose a statistical modeling and ensemble learning-based comprehensive model, which is oriented towards in-class teaching evaluation by using AI technologies such as computer vision (CV) and intelligent speech recognition (ISR). Firstly, we present an index system including a set of teaching evaluation indicators combining traditional assessment scales with new values derived from CV and ISR-based AI analysis. Next, we design a comprehensive in-class teaching evaluation model by using both the analytic hierarchy process-entropy weight (AHP-EW) and AdaBoost-based ensemble learning (AdaBoost-EL) methods. Experiments not only demonstrate that the two modules in the model are respectively applicable to the calculation of indicators with different characteristics, but also verify the performance of the proposed model for AI-based in-class teaching evaluation. In this comprehensive in-class evaluation model, for students' concentration and participation, ensemble learning module is chosen with less root mean square error (
) of 8.318 and 9.375. In addition, teachers' media usage and teachers' type evaluated by statistical modeling module approach higher accuracy with 0.905 and 0.815. Instead, the ensemble learning approaches the accuracy of 0.73 in evaluating teachers' style, which performs better than the statistical modeling module with the accuracy of 0.69.
Social exclusion as well as a sense of belonging and depression have been identified as risk factors for suicide among older adults in pension institutions. In particular, the elderly living in rural ...pension institutions is more likely to have poor mental health and a higher incidence of suicidal ideation. This study explored the mechanism of social exclusion on suicidal ideation among the elderly in rural pension institutions, and the moderating effect of interpersonal trust.
The social exclusion experience scale, sense of belonging, depression self-rating scale (CES-D), suicidal ideation scale (BSI-CV), and interpersonal trust scale (ITS) were used to investigate the elderly in rural pension institutions. A total of 1,387 samples (53.35% female) were collected, ranging in age from 65 to 95 years (M = 72.8, SD = 6.173).
The results of the study found that: (1) social exclusion increases the suicidal ideation of the elderly in rural pension institutions, and the sense of belonging and depression play a significant chain-mediated role in the relationship between social exclusion and suicidal ideation in the elderly. (2) Interpersonal trust moderates the impact of social exclusion on the sense of belonging, depression, and suicidal ideation. Specifically, interpersonal trust can alleviate the promotion effect of social isolation on suicidal ideation and depression, and can also reduce the adverse effect of social exclusion on the sense of belonging.
This study validates that social exclusion is a risk factor for suicidal ideation in the rural elderly and identifies interpersonal trust as a protective factor against social exclusion and its negative outcomes in the elderly. This study provides a scientific basis for improving the depression status of the elderly in rural China and formulating suicide prevention measures.
Colorectal cancer (CRC) is a common and deadly cancer worldwide with a high lethality rate. Disulfidptosis has been found to be an emerging mode of death in cancer, and the purpose of this study was ...to explore the relationship between disulfidptosis-related lncRNAs (DRLs) and CRC and to develop a prognostic model for CRC and DRLs. The gene expression data and clinicopathologic information of colorectal cancer patients were obtained from The Cancer Genome Atlas (TCGA) and screened for DRLs based on correlation analysis. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to construct the prognostic model, and its validation was carried out by PCA and receiver operating characteristic (ROC) curves. We constructed nomograms combined with the model. Finally, the possible mechanisms by which lncRNAs affect CRC were explored by functional enrichment analysis, immune infiltration and immune escape analysis. In summary, we developed a prognostic marker consisting of lncRNAs associated with disulfidptosis to help clinicians predict the survival of different CRC patients and use different targeted therapies and immunotherapies depending on the condition.
•Alloherpesviruses were divided into Cyprinivirus, ictalurivirus and batrachovirus based on genome.•ANI and AAI analyses clearly displayed species boundaries.•The four genes which are suitable for ...phylogenetic analysis tree were selected.
The family Alloherpesviridae contains herpesviruses of fish and amphibians. Due to the significant economic losses to aquaculture that herpesviruses can cause, the primary areas of research interest are concerning their pathogenesis and prevention. Despite alloherpesvirus genomic sequences becoming more widely accessible, methods regarding their genus/species classification are still relatively unexplored. In the present study, the phylogenetic relationships between 40 completely sequenced alloherpesviruses were illustrated by the viral proteomic tree (ViPTree), which was divided into three monophyletic groups, namely Cyprinivirus, Ictalurivirus and Batrachovirus. Additionally, average nucleotide identity (ANI) and average amino acid identity (AAI) analyses were performed across all available sequences and clearly displayed species boundaries with the threshold value of ANI/AAI set at 90%. Subsequently, core-pan analysis uncovered 809 orthogroups and 11 core genes shared by all 40 alloherpesvirus genome sequences. For the former, a 15 percent identity depicts a clear genus boundary; for the latter, 8 of them may be qualified for phylogenetic analysis based on amino acid or nucleic acid sequences after being verified using maximum likelihood (ML) or neighbor-joining (NJ) phylogenetic trees. Finally, although the dot plot analysis was valid for the members within Ictalurivirus, it was unsuccessful for Cyprinivirus and Batrachovirus. Taken together, the comparison of individual methodologies provides a wide range of alternatives for alloherpesviruses classification under various circumstances.
Sepsis-Associated Liver Injury (SALI) is an independent risk factor for death from sepsis. The aim of this study was to develop an interpretable machine learning model for early prediction of 28-day ...mortality in patients with SALI. Data from the Medical Information Mart for Intensive Care (MIMIC-IV, v2.2, MIMIC-III, v1.4) were used in this study. The study cohort from MIMIC-IV was randomized to the training set (0.7) and the internal validation set (0.3), with MIMIC-III (2001 to 2008) as external validation. The features with more than 20% missing values were deleted and the remaining features were multiple interpolated. Lasso-CV that lasso linear model with iterative fitting along a regularization path in which the best model is selected by cross-validation was used to select important features for model development. Eight machine learning models including Random Forest (RF), Logistic Regression, Decision Tree, Extreme Gradient Boost (XGBoost), K Nearest Neighbor, Support Vector Machine, Generalized Linear Models in which the best model is selected by cross-validation (CV_glmnet), and Linear Discriminant Analysis (LDA) were developed. Shapley additive interpretation (SHAP) was used to improve the interpretability of the optimal model. At last, a total of 1043 patients were included, of whom 710 were from MIMIC-IV and 333 from MIMIC-III. Twenty-four clinically relevant parameters were selected for model construction. For the prediction of 28-day mortality of SALI in the internal validation set, the area under the curve (AUC (95% CI)) of RF was 0.79 (95% CI: 0.73-0.86), and which performed the best. Compared with the traditional disease severity scores including Oxford Acute Severity of Illness Score (OASIS), Sequential Organ Failure Assessment (SOFA), Simplified Acute Physiology Score II (SAPS II), Logistic Organ Dysfunction Score (LODS), Systemic Inflammatory Response Syndrome (SIRS), and Acute Physiology Score III (APS III), RF also had the best performance. SHAP analysis found that Urine output, Charlson Comorbidity Index (CCI), minimal Glasgow Coma Scale (GCS_min), blood urea nitrogen (BUN) and admission_age were the five most important features affecting RF model. Therefore, RF has good predictive ability for 28-day mortality prediction in SALI. Urine output, CCI, GCS_min, BUN and age at admission(admission_age) within 24 h after intensive care unit(ICU) admission contribute significantly to model prediction.
A series of Pt/TiO2 catalysts were prepared by the impregnation (IM), dry ball mill (DB), or wet ball mill (WB) methods, and their catalytic activity for the oxidation of CO was evaluated. The ...structure and redox properties of the catalysts were investigated by N2 desorption, XRD, SEM, TEM, XPS, H2-TPR, SO2-TPD, and CO chemisorption analysis. It was determined that the preparation method affects the physical structure of the catalyst and the particle size and dispersion of Pt on the catalyst surface. The catalyst prepared by the impregnation method had a more suitable physical structure than the other catalysts, with a smaller particle size, a higher dispersion of Pt on the surface, and the lowest strength of SO2 adsorption. Pt/TiO2(IM) catalysts presented the best catalytic activity for the oxidation of CO in simulated sintering flue gas at 140 °C, as well as better sulfur and water resistance with simulated sintering flue gas containing 50 ppm of SO2 and 15% water vapor.
Poly(
N
-isopropylacrylamide) (PNIPAM) is an organic environment-sensitive material, which can be combined with photocatalysts to control the photocatalytic process. Herein, rodlike ...environment-sensitive Bi
2
O
3
(PNIPAM/Bi
2
O
3
) was prepared by a novel one-step continuous microwave method. This new method is efficient and convenient. The as-prepared PNIPAM/Bi
2
O
3
was very sensitive to temperature and pH, and the degradation rate in the environment of 25 °C and pH = 9 was 3.87 times than that in the environment of 45 °C and pH = 5. While Bi
2
O
3
is under the above various environmental conditions, its degradation rate did not change obviously. More interestingly, the introduction of PNIPAM and one-step continuous microwave method was beneficial to the transformation of Bi
2
O
3
from no specific shape to rodlike morphology without changing its crystal structure. This work not only developed a new one-step continuous microwave synthesis method, but also opened up new ideas for the controllability requirements of materials in special environment.
Pentagalloyl glucose (PGG) is a natural hydrolyzable gallotannin abundant in various plants and herbs. It has a broad range of biological activities, specifically anticancer activities, and numerous ...molecular targets. Despite multiple studies available on the pharmacological action of PGG, the molecular mechanisms underlying the anticancer effects of PGG are unclear. Here, we have critically reviewed the natural sources of PGG, its anticancer properties, and underlying mechanisms of action. We found that multiple natural sources of PGG are available, and the existing production technology is sufficient to produce large quantities of the required product. Three plants (or their parts) with maximum PGG content were Rhus chinensis Mill, Bouea macrophylla seed, and Mangifera indica kernel. PGG acts on multiple molecular targets and signaling pathways associated with the hallmarks of cancer to inhibit growth, angiogenesis, and metastasis of several cancers. Moreover, PGG can enhance the efficacy of chemotherapy and radiotherapy by modulating various cancer-associated pathways. Therefore, PGG can be used for treating different human cancers; nevertheless, the data on the pharmacokinetics and safety profile of PGG are limited, and further studies are essential to define the clinical use of PGG in cancer therapies.
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