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Abstract Background Physiological processes rely on phosphate, which is an essential component of adenosine triphosphate (ATP). Hypophosphatasia can affect nearly every organ system in the body. It is crucial to monitor newborns with risk factors for hypophosphatemia and provide them with the proper supplements. We aimed to evaluate the risk factors and develop a nomogram for early hypophosphatemia in term infants. Methods We conducted a retrospective study involving 416 term infants measured serum phosphorus within three days of birth. The study included 82 term infants with hypophosphatemia (HP group) and 334 term infants without hypophosphatemia (NHP group). We collected data on the characteristics of mothers, newborn babies, and childbirth. Furthermore, univariate and multivariate logistic regression analyses were performed to identify independent risk factors for hypophosphatemia in term infants, and a nomogram was developed and validated based on the final independent risk factors. Results According to our analysis, the multivariate logistic regression analysis showed that male, maternal diabetes, cesarean delivery, lower serum magnesium, and lower birth weight were independent risk factors for early hypophosphatemia in term infants. In addition, the C-index of the developed nomogram was 0.732 (95% CI = 0.668–0.796). Moreover, the calibration curve indicated good consistency between the hypophosphatemia diagnosis and the predicted probability, and a decision curve analysis (DCA) confirmed the clinical utility of the nomogram. Conclusions The analysis revealed that we successfully developed and validated a nomogram for predicting early hypophosphatemia in term infants.

Abstract [Objective] Apocynum venetum L. is an important wild plant germplasm in China, which has important medicinal, ecological, and economic values. Although A . venetum is strong in salt tolerance, its wild population is gradually declining due to habitat destruction and increased soil salinization. Therefore, exploring the mechanism of salt tolerance in A . venetum is crucial for the protection and utilization of wild germplasm resources. [Methods] In the present study, a tandem mass tag (TMT)-based quantitative proteomics technology was used to conduct quantitative proteomic study of A . venetum under salt stress. Common differentially expressed proteins and core proteins were screened using Venn analysis and protein network interaction analysis methods. [Results] (1) Eleven common differentially expressed proteins were identified, which were mainly involved in protein-FAD linkage, negative regulation of transporter activity, negative regulation of ion transporter activity, negative regulation of anion transmembrane transport, negative regulation of anion channel activity, and thiazole metabolism. (2) Ribosomal proteins were the main proteins obtained by the interaction of differential protein networks at different stress times, among which the ribosomal protein L2-2 (TRINITY_DN13265_c0_g1_i1_9) was the core protein in differential proteins at 12 h and 24 h under stress. The results indicate that the ribosomal proteins play an important role in response to salt stress in A . venetum . [Conclusion] In the present study, the key proteins of A . venetum in response to salt stress were screened, and the molecular resources in response to salt stress in A . venetum were expanded, which provide theoretical bases for the discovery and utilization of natural resistant germplasms of A . venetum .

This paper constructs a gray clustering assessment model, combines the indicators of information technology literacy, technology-supported learning, and information technology teaching ability to evaluate the information technology teaching ability of A college teachers, and explores the use of information technology equipment of college teachers. And through the construction and calculation of the whitening weight function to refine the classification of college teachers’ informatization teaching ability, for different categories of teachers’ informatization application presenting different characteristics, using one-way ANOVA and adding the Scheffe (C) test to test the inter-group variability of different categories, in-depth exploration of the influencing factors of teachers’ informatization teaching in different categories. The results show that the overall water mean of teachers’ informatization teaching ability in school A is 3.88±0.59, and the model divides teachers’ informatization teaching level in college A into three categories: 3.8-4.5, 3-3.8, and 1-3, with the proportion of each category being 27.8%, 40.1%, and 32.1%, respectively. This study focuses on analyzing the relevant factors affecting teachers’ informatization teaching ability and puts forward countermeasure suggestions according to local conditions, which is of great significance to deepen the reform of education and teaching.

Objective To explore the feasibility of establishing a computer-aided diagnostic model of multi-stained pathological images in patients with non-inflammatory aortic medial degeneration(MD). Methods In this study, pathological sections of aortic surgical specimens for non-inflammatory lesions from patients with thoracic aortic aneurysms and dissections were retrospectively collected at the Beijing Anzhen Hospital, Capital Medical University from July to December 2018. The lesions were scanned under ×400 magnification as whole slide images(WSI) and then annotated by two pathologists. The annotated WSI images were randomly split into training and test sets in a 6:1 ratio. SE-EmbraceNet was used to train the data to construct a multi-classification model for MD of multi-stained pathology images, including intralamellar mucoid extracellular matrix accumulation (MEMA-I), translamellar mucoid extracellular matrix accumulation (MEMA-T), elastic fiber fragmentation and/or loss(EFFL) and smooth muscle cell nuclei loss (SMCNL). The classification effect of the model was evaluated based on the test set data, and the results were expressed in terms of accuracy, sensitivity, precision, and the F1 value. Results Totally 530 pathological slides of non-inflammatory aortic lesion surgical specimens from patients with aortic aneurysm and dissection were included. Extracted 5265 sets of images, each containing 5 stained pathological images of the same lesion site: HE staining, special staining (elastic fiber/VanGieson, Masson, Alcian blue/periodic acid Schiff) and smooth muscle actin staining. There were 4513 sets of training images, including 987 SMCNL, 2013 EFFL, 1337 MEMA-I, and 176 MEMA-T; and 752 test images including 166 SMCNL, 335 EFFL, 222 MEMA-I, and 29 MEMA-T. The overall performance of the model in the test set showed good results, with an accuracy of 96.54%(726/752). The model had the best classification performance for EFFL, with accuracy, sensitivity, precision, and F1 value all ≥98.51%. The model also had a great classification ability for SMCNL, with all evaluated indexes≥97.59%. Conclusion The multi-stained pathology image-based MD classification model constructed in this study has high classification accuracy and good generalization ability, which has the potential to be applied to assist in the diagnosis of the non-inflammatory aortic lesion.

Magnaporthe oryzae is known for its genetic diversity and pathogenic variability, leading to rapid breakdown of resistance in rice. Incorporating multiple broad-spectrum blast resistance genes into rice cultivars would extend disease resistance longevity. Effective resistance breeding in rice therefore requires continual enrichment of the reservoir of resistance genes and alleles. We conducted a large-scale screen of rice blast resistance in about 2 000 rice accessions. Among them, 247 accessions showed at least medium resistance to the natural infection of rice blast and 7 novel Pik alleles were identified from them. Variations in gene sequences were then correlated with the phenotypic trait to enable the identification of favorable alleles. Among the seven novel Pik alleles, the resistant rate of Pik-R0/ME/7017 donors was greater than 80%, and the disease score was less than 3. Through molecular marker-assisted backcross breeding, we successfully transferred the three Pik alleles, Pik-R0/ME/7017, into an elite cultivated line Kongyu 131 to obtain BC3F2 lines, which showed enhanced resistance to rice blast compared with the recurrent parent. Assessment of these near-isogenic lines in the greenhouse using 31 isolates of M. oryzae from Heilongjiang Province of China revealed that the resistant levels of the BC3F2 lines with Pik-R0/ME/7017 were significantly higher than those of the established cloned resistance genes Pik-m and Pi1. Exploring such alleles will enrich our gene library for resistance to rice blast.

Perovskite quantum dots film has better mechanical stability and structural integrity compared to bulk thin film. Here, the authors demonstrate higher endurance of quantum dot films and develop hybrid CsPbI3 QD/PCBM device with PCE of 15.1% and 12.3% on rigid and flexible substrates, respectively.

Objective To establish a simple and rapid method for detecting tumor cells based on multivalent aptamers. Methods Rolling circle amplification was used to form a long single stranded DNA scaffold with repeat sequences of poly T, then the obtained product was hybridized with the fluorescence signal chain of aptamer AS1411 (with poly A bases) which was nucleolin targeting. Then, a Multi-AS1411-LS recognition probe was constructed and characterized. The feasibility of probe Multi-AS1411-LS for cell line identification was analyzed by flow cytometry and confocal microscopy, and the recognition conditions were further optimized. Finally, the malignant tumor cells in clinically collected serous effusions were detected by our constructed probe Multi-AS1411-LS, and the specificity and sensitivity of our probe were evaluated. Results Our constructed probe Multi-AS1411-LS could recognize tumor cells in 5 min at room temperature, with the mean fluorescence intensity of cells higher by about 100 times than that of monovalent formats, and the minimum detection limit of 3 cells in 500 μL samples. The probe distinguished benign and malignant cells in 70 clinical specimens, with a sensitivity of 87.80% and a specificity of 93.10%. Conclusion This detection method is rapid and simple to operate, and has good specificity and sensitivity in the detection of malignant tumor cells in clinical practice.

Face recognition technology is an important research field for deep learning. In order to overcome the shortcomings of traditional open-loop face cognition mode and deep neural network structure, and to imitate human cognition model of real-time evaluation of cognitive results to self-optimized regulate feature space and classification cognition criteria, drawing on the theory of closed-loop control theory, this paper explores an intelligent face cognition method with deep ensemble learning and feedback mechanism. Firstly, based on the DEEPID neural network, an unstructured feature space of face images with a determined mapping relationship from the global to the local is established. Secondly, based on feature separability evaluation and variable precision rough set theory, a face cognition decision information system model with unstructured dynamic feature representation is established from the perspective of information theory, to reduce the unstructured feature space. Thirdly, the ensemble random vector functional-link net is used to construct the classification criterion of the reduced unstructured feature space. Finally, the face cognition result entropy measure index is constructed to provide a quantitative basis for the self-optimization adjustment mechanism of face feature space and classification cognition criteria. The experimental results show that the proposed method can effectively improve the recognition rate of face images compared with the existing methods.

The composite insulator sheath plays an important role in protecting the core rod and insulation. The thickness of the sheath must meet the corresponding standard requirements. During the insulator manufacturing process, the core rod decentration leads to uneven thickness of the sheath, which is easy to cause the risk of composite insulators premature failure during operation. The phased array detection technology can accurately detect the thickness of the sheath, so that defects such as uneven thickness of the sheath (decentration of the core rod) can be detected, and the thickness of the sheath at the end of the composite insulator can also be effectively detected. DR detection technology can effectively identify the interface between the mandrel and the sheath, but there is a risk of the sheath thickness distortion due to inappropriate transillumination parameters.

The traditional Chinese drug Bombyx Batryticatus (BB), which is also named the white stiff silkworm, has been widely used in Chinese clinics for thousands of years. It is famous for its antispasmodic and blood circulation-promoting effects. Cardiomyocyte hypertrophy, interstitial cell hyperplasia, and myocardial fibrosis are closely related to the N-glycosylation of key proteins. To examine the alterations of N-glycosylation that occur in diabetic myocardium during the early stage of the disease, and to clarify the therapeutic effect of 1-Deoxynojirimycin (1-DNJ) extracted from BB, we used the db/db (diabetic) mouse model and an approach based on hydrophilic chromatography solid-phase extraction integrated with an liquid Chromatograph Mass Spectrometer (LC-MS) identification strategy to perform a site-specific N-glycosylation analysis of left ventricular cardiomyocyte proteins. Advanced glycation end products (AGEs), hydroxyproline, connective tissue growth factor (CTGF), and other serum biochemical indicators were measured with enzyme-linked immunosorbent assays (ELISA). In addition, the α-1,6-fucosylation of N-glycans was profiled with lens culinaris agglutinin (LCA) lectin blots and fluorescein isothiocyanate (FITC)-labelled lectin affinity histochemistry. The results indicated that 1-DNJ administration obviously downregulated myocardium protein N-glycosylation in db/db mice. The expression levels of serum indicators and fibrosis-related cytokines were reduced significantly by 1-DNJ in a dose-dependent manner. The glycan α-1,6-fucosylation level of the db/db mouse myocardium was elevated, and the intervention effect of 1-DNJ administration on N-glycan α-1,6-fucosylation was significant. To verify this result, the well-known transforming growth factor-β (TGF-β)/Smad2/3 pathway was selected, and core α-1,6-fucosylated TGF-β receptor II (TGFR-βII) was analysed semi-quantitatively with western blotting. The result supported the conclusions obtained from LCA lectin affinity histochemistry and lectin blot analysis. The expression level of α-1,6-fucosyltransferase (FUT8) mRNA was also detected, and the results showed that 1-DNJ administration did not cause obvious inhibitory effects on FUT8 expression. Therefore, the mechanism of 1-DNJ for relieving diabetic cardiomyopathy (DCM)-associated fibrosis can be concluded as the inhibition of N-acetylglucosamine (N-GlcNAc) formation and the reduction of substrate concentration.