ABSTRACT The fertile land in Heilongjiang Province of China is suitable for rice cultivation, but this area is susceptible to low temperature and chilling injury, which is prevented by planting rice varieties suitable for GP that is an important measure. However, selection based on rice traits is vulnerable to environmental influences and takes a long time, and selection based on molecular markers may result in progeny recombination and lack of reliability. Therefore, an efficient accurate and intelligent identification method for rice growth period is urgently needed. In this study, machine learning and deep learning methods in Python were used to analyze the Raman spectra of 6 rice varieties in three accumulated temperature region of Heilongjiang Province. 1) In machine learning, Principal Component Analysis (PCA) was adopted for feature extraction, in combination with Support Vector Machine (SVM) classification models suitable for nonlinear data sets for identification, the identification rate was 93.33% and the type of this experimental data set was determined to be discrete. 2) In deep learning, Continuous Wavelet Transform (CWT) methods was adopted for data preprocessing, combined with the Convolutional Neural Networks (CNN) model with its own feature extraction, with the highest accuracy of 94.82%, which was higher than the PCA+SVM identification model. 3) Based on the method mentioned in 2), in order to improve the feature extraction ability of the model as a whole, Convolutional Block Attention Module (CBAM) was used to improve the CNN identification model for the first time for one-dimensional data sets, and the highest identification rate was 98.28%, which was better than the PCA+SVM identification model. 3) In the verification test, Raman spectral information of 4 rice varieties was brought into the constructed CWT+CNN-CBAM identification model for identification, and the identification results were as high as 94.79%. The experimental results showed that the CWT visualization data processing method based on Raman technology combined with the CNN identification model of CBAM with improved feature extraction ability in deep learning achieved the best identification results, which could provide an efficient, accurate and intelligent method for the identification of different growth period of rice varieties in Heilongjiang Province.

This research investigated the predictive value of combined detection of brain natriuretic peptide (BNP) and cystatin C (Cys C) in heart failure after percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI). Sixty-five AMI patients complicated by heart failure (HF) after PCI and 79 non-heart failure (non-HF) patients were involved in this research. The levels of Cys C and BNP were measured. Risk factors for heart failure in AMI patients after PCI were analyzed by multivariate logistic regression analysis. Efficacy of BNP and Cys C on predicting heart failure were analyzed by receiver operating characteristic (ROC) curve. Cys C and BNP levels were significantly higher in the HF group than in the non-HF group. BNP and Cys C levels were the independent influencing factors causing heart failure within one year after PCI. The area under the predicted curve (AUC) of Cys C, BNP, and combined Cys C and BNP were 0.763, 0.829, and 0.893, respectively. The combined detection of Cys C and BNP was highly valuable in predicting heart failure in AMI patients after PCI, which can be regarded as the serum markers for diagnosis and treatment of heart failure.

resumen Con el aumento de los contaminantes descargados en el agua, es difícil controlar la contaminación del medio ambiente mediante la reducción de parte de la descarga de contaminantes. Por lo tanto, se propone el método de control de la cantidad total de contaminante de la calidad del agua basado en matemáticas difusas. En primer lugar, se construyó un marco de control y un proceso de la cantidad total de contaminantes. La cantidad total de contaminantes descargados en esta región se controló dentro de una cierta cantidad para lograr el objetivo ambiental predeterminado. Luego, se evaluó la contaminación del agua de diferentes regiones mediante un modelo de calidad del agua basado en las matemáticas difusas de la región o en el dominio de protección clave con contaminación severa y una fuente de contaminación concentrada, lo que hace que la evaluación integral de la contaminación de la calidad del agua sea más científica. Finalmente, el control de la cantidad total de contaminantes se completó mediante la combinación optimizada del control de fuente puntual y el control de la unidad de la cantidad total. Los resultados experimentales muestran que el método es científico, objetivo y razonable durante el control de la descarga de contaminantes. Controla la cantidad total de contaminantes de forma excelente.

abstract Given the scale-up of pollutants discharged into water bodies, control via reducing part of the discharge is turning out ineffective. This article proposes a method based on fuzzy mathematics for controlling water from the total pollutant amount. Firstly, a control framework and process of the total pollutant amount was built. The total amount of pollutants discharged into several water bodies in China was studied to achieve the predetermined environmental objective. Then, water pollution of different regions was evaluated via water quality model based on the fuzzy mathematics in the area or essential protection domain with severe pollution and a concentrated pollution source. This procedure makes a comprehensive evaluation of the water quality pollution more scientific. Finally, the control of the total pollutant amount was completed via the optimized combination of point source control and unit control of the total amount. Experimental results show that the method is scientific, objective, and reasonable while controlling the pollutant discharge. It controls the total pollutant amount excellently.

Background: Many studies have documented the association between venous thromboembolism (VTE) and colorectal cancer (CRC). The Khorana model is a VTE risk assessment model for predicting cancer-associated thrombosis. Type 2 diabetes (T2DM) has also been reported to increase the risk of VTE. Purpose: The aim of this study was to investigate the influence of T2DM on Khorana VTE risk in CRC patients and to explore the relationship between Khorana VTE category and CRC clinicopathological factors. Methods: This analysis included 615 CRC patients (205 with T2DM). Fibrinogen and D-dimer levels were compared within each group. A comparison was made of the proportion of patients in different Khorana VTE risk categories in CRC patients with and without T2DM. The association between Khorana VTE risk category and clinicopathological factors among all the CRC patients was evaluated. Results: Fibrinogen levels of CRC patients with T2DM were significantly higher than those of non-diabetes patients (4.13 ± 1.06 vs 3.94 ± 0.98, p < 0.001). A higher proportion of CRC patients with T2DM were in the Khorana intermediate-to-high risk category (H = 4.749, p = 0.029). Female sex, diabetes, colon location (compared with rectum), larger tumor size, advanced pT stage and pN stage were correlated with the intermediate-to-high Khorana VTE risk category, with odd ratios (95% confidence intervals [CI]) of 1.537 (1.064-2.220), 1.499 (1.027-2.186), 2.313 (1.588-3.370), 2.284 (1.542-3.383), 4.429 (2.088-9.396) and 1.822 (1.230-2.698), respectively. Conclusion: T2DM increases Khorana VTE risk in CRC patients. Female sex, diabetes, colon location, large tumor size and poor stage are associated with the intermediate-to-high Khorana VTE risk category.

ABSTRACT This study aimed to investigate the expression and mechanism of N- methyl -D- aspartate receptor 1 (NMDAR1) in the pathogenesis of Alzheimer disease (AD). Eighty adult Wistar rats were randomly divided into 4 groups (n=20 each) to receive an injection of 0, 5, 7 and 10 μl of 1 μg/μl amyloid-β 42 (Aβ1-42) in the hippocampus. Twenty rats in normal control group were injected with equal volume of saline. After 10 days, the hippocampus was isolated from 5 randomly selected rats in each group. The NMDAR1 protein and mRNA expression was determined by immunohistochemical staining and qRT-PCR. The aquaporin-1 (AQP-1) mRNA expression was also measured by qRT-PCR. We found that both NMDAR1 and AQP-1 expression in Aβ1-42 groups was increased in a dose-dependent manner. NMDAR1 and AQP-1 expression in 7 and 10 μl Aβ1-42 groups was significantly higher compared with 0 μl Aβ1-42 group (P <0.01). Further, the 10 μl Aβ1-42 group was randomly divided into 3 subgroups: AD-NMDA, AD-MK-801, and AD-Ctrl subgroup, which was given an intraperitoneal injection of NMDAR agonist NMDA, NMDAR antagonist MK-801 and saline, respectively. The relative APQ-1 expression in each subgroup was determined by qRT-PCR and Western blot analysis after 24 h. The AQP-1 expression was significantly decreased in AD-MK-801 group (P < 0.05), but was markedly increased in AD-NMDA group when compared with AD-Ctrl group (P <0.01). Our study suggested that expression abnormity of NMDAR1 is involved in the pathogenesis of AD. NMDAR1 might regulate the pathogenic process through stimulating the expression of AQP-1.

BACKGROUND: Hepcidin, encoding by HAMP gene, is the pivotal regulator of iron metabolism, controlling the systemic absorption and transportation of irons from intracellular stores. Abnormal levels of HAMP expression alter plasma iron parameters and lead to iron metabolism disorders. Therefore,itis animportant goal to understand the mechanisms controlling HAMP gene expression. RESULTS: Overexpression of Sox2 decrease basal expression of HAMP or induced by IL-6 or BMP-2, whereas, knockdown of Sox2 can increase HAMP expression, furthermore, two potential Sox2-binding sites were identified within the human HAMP promoter. Indeed, luciferase experiments demonstrated that deletion of any Sox2-binding site impaired the negative regulation of Sox2 on HAMP promoter transcriptional activity in basal conditions. ChIP experiments showed that Sox2 could directly bind to these sites. Finally, we verified the role of Sox2 to negatively regulate HAMP expression in human primary hepatocytes. CONCLUSION: We found that Sox2 as a novel factor to bind with HAMP promoter to negatively regulate HAMP expression, which may be further implicated as a therapeutic option for the amelioration of HAMP-overexpression-related diseases, including iron deficiency anemia.

A convenient, straightforward, two-step reaction of α-hydroxyhydrocarbylphosphonates with arylisothiocyanates in the presence of catalytic amounts of sodium methoxide in 1,2-dichloroethane as solvent produced various new α-(arylamino thiocarbonyloxy) hydrocarbylphosphonates in excellent yields. Their structures have been confirmed by their IR, ¹H NMR and 31P NMR spectra and by elemental analysis. The preliminary antisepsis activity and protein activity of some of the compounds were identified.