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Abstract Background and objective Dyslipidemia is significantly more common in those with concurrent chronic kidney disease (CKD) and chronic heart failure (CHF). Sacubitril/valsartan has showcased its influence on both cardiac and renal functions, extending its influence to the modulation of lipid metabolism pathways. This study aimed to examine how sacubitril/valsartan affects lipid metabolism within the context of CKD and CHF. Methods This study adopted a retrospective design, focusing on a single center and involving participants who were subjected to treatment with sacubitril/valsartan and valsartan. The investigation assessed the treatment duration, with a particular emphasis on recording blood lipid indicators, including triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A (ApoA), and apolipoprotein B (ApoB). Furthermore, cardiac and renal functions, blood pressure, potassium levels, and other factors influencing the blood lipids were analyzed in both groups at identical time points. Results After 16 weeks of observation, the sacubitril/valsartan group exhibited lower TG levels compared to the valsartan group. Noteworthy was the fact that individuals undergoing sacubitril/valsartan treatment experienced an average reduction of 0.84 mmol/L in TG levels, in stark contrast to the valsartan group, which registered a decline of 0.27 mmol/L (P

Immobilized microbial technology is a sustainable solution to reduce water pollution. Understanding the microorganisms in immobilized biochar is critical for the removal of contaminants in water. Biochar as a carrier of microorganisms, there are some problems need to be focused on, microporous structure blockage limiting the contact between microorganisms and pollutants for further degradation, unstable microbial loading, and low cycle times. To solve these problems, Alcaligenes faecalis was immobilized with rice hull biochar to study its adsorption and degradation characteristics of phenol. It was found that A. faecalis JH1 could effectively remove 300 mg/L of phenol within 24 h. The adsorption capacity of rice husk biochar for phenol increased with the increasing pyrolysis temperature (700 > 500>300°C). The immobilized biomass of JH1 from 700°C rice husk biochar reached 249.45 nmol P/g at 24 h of fixation reaction. It was found that the phenol removal rate of JH1 immobilized at all temperature biochar reached 300 mg/L within 12 h after the sixth cycle. As the number of cycles increased, bacteria grew and adhered to the biochar, forming a thick viscous biofilm and accelerating the removal of phenol. The results showed that A. faecalis could firmly adhere to rice hull biochar and degrade phenol effectively, with good durability and cyclicity.

The effect and mechanism of phenol removal by immobilized microorganisms in Fe3O4 nanomaterial-modified pharmaceutical residue biochar was investigated to develop efficient biochar immobilizing microbial technology. Plant residue biochar (Y3, Y5, and Y7) was prepared from Andrographis paniculata plant residues as the raw material at 300 °C, 500 °C, and 700 °C, respectively. Y7 was modified with Fe3O4 nanomaterial (Fe-Y7). These four kinds of biochars were used as carriers to adsorb immobilized Alcaligenes faecalis strain JH1, JY3, JY5, JY7, and Fe-Y7 to investigate the mechanism of phenol removal, and eight cycles were performed to analyze their immobilization performance. Compared with suspended bacteria, biochar-immobilized bacteria could improve their tolerance in different environments. At temperatures of 25 °C to 40 °C, pH = 5~9, initial phenol concentration of 300–500 mg/L, and salinity of 3%, the bacteria could still grow and maintain strong activity within 48 h. The water-extractable organic carbon of biochar was also tested for the degradation of phenol by bacteria, which was found to have different stimulating effects on bacteria. In the batch experiments, as the number of cycles increased, the bacteria grew and adhered rapidly to the biochar, eventually forming a thick and sticky biofilm. After the sixth cycle, all the biochar-immobilized bacteria could remove 300 mg/L phenol solution within 12 h. The removal rate of phenol by JFe-Y7 was relatively fast in the eighth cycle. The results indicated that biochar-immobilized bacteria have good durability, stability, and reproducibility and that Fe3O4 nanoparticle modification could improve the removal of phenol by increasing the phenol adsorption amount, the adsorption capacity of bacteria, and the enzymatic activity of bacteria.

A single-cell sequencing data set has always been a challenge for clustering because of its high dimension and multi-noise points. The traditional K-means algorithm is not suitable for this type of data. Therefore, this study proposes a Dissimilarity-Density-Dynamic Radius-K-means clustering algorithm. The algorithm adds the dynamic radius parameter to the calculation. It flexibly adjusts the active radius according to the data characteristics, which can eliminate the influence of noise points and optimize the clustering results. At the same time, the algorithm calculates the weight through the dissimilarity density of the data set, the average contrast of candidate clusters, and the dissimilarity of candidate clusters. It obtains a set of high-quality initial center points, which solves the randomness of the K-means algorithm in selecting the center points. Finally, compared with similar algorithms, this algorithm shows a better clustering effect on single-cell data. Each clustering index is higher than other single-cell clustering algorithms, which overcomes the shortcomings of the traditional K-means algorithm.

With the increasing availability of social networks and biological networks, detecting network community structure has become more and more important. However, most traditional methods for detecting community structure have limitations in dimension reduction or parameter optimization. In this paper, we propose a Density-Canopy-Kmeans clustering algorithm (DCK) to detect network community structure. Specifically, we define a novel distance metric, which integrates random distance and community structure coefficient based on the Jaccard distance. After applying the Multidimensional Scaling (MDS) dimension reduction, we cluster the nodes. KMEANS is combined with density clustering and canopy clustering to determine the optimal number of communities and the best initial seeds are determined to improve the accuracy and stability of the K-means algorithm. Compared with traditional community detection methods, our method has a higher classification accuracy and a better visualization effect. Thus, this method is effective for analyzing network communities.

Bmi1 is overexpressed in multiple human cancers. We previously reported the oncogenic function and the transcription regulation mechanisms of Bmi1 in nasopharyngeal carcinoma (NPC). In this study, we observed that the mRNA and the protein levels of Bmi1 were strictly inconsistent in NPC cell lines and cancer tissues. The inhibitors of proteasome and lysosome could not enhance the protein level of Bmi1, indicating that Bmi1 may be post-transcriptionally regulated. The IRESite analysis showed that there were two potential internal ribosome entry sites (IRESs) in the 5′-untranslated region (5′-UTR) of Bmi1. The luciferase assay demonstrated that the 5′-UTR of Bmi1 has IRES activity, which may mediate cap-independent translation. The IRES activity of the Bmi1 5′-UTR was significantly reduced after the mutation of the two IRES elements. Taken together, these results suggested that the IRES elements mediating translation is a novel post-transcriptional regulation mechanism of Bmi1.

IntroductionChina has the largest youth population in the world. To better implement the Smoke-free School Initiative, this study aims to examine the protective and risk factors for different smoking behaviors (never smoked, experimental smoking, and current smoking) among school adolescents based on social cognitive theory.MethodsThis research was a secondary analysis of a cross-sectional survey of middle schools in Huli District of Xiamen, China. The final sample consisted of 1937 participants with an average age of 15.41 (SD = 1.64). Descriptive statistics were used to summarize the sociodemographic characteristics of the sample. Multivariate multinomial logistic regression analysis was performed using four models.ResultsOf the respondents, 1685 (86.99%) were never smokers, 210 (10.84%) were experimental smokers, and 42 (2.17%) were current smokers. Social norms, positive outcome expectations, anti-smoking self-efficacy, and attitudes toward control tobacco policies were associated with adolescents' smoking behaviors. The number of smoking family members, classmates smoking, the perception that smoking is cool and attractive, and attitudes toward control tobacco policies were the predictors of current smoking behavior (p < 0.05). In contrast, friends smoking and individual and social relationship motivation were associated with only experimental smoking (p < 0.05).DiscussionThe relationship of social norms, positive outcome expectations, anti-smoking self-efficacy, and attitudes toward control tobacco policies varied across smoking behaviors. Family, school, society and the government need to cooperate in prevention and intervention programs for adolescent smoking. The relationships between these factors and adolescents' different smoking behaviors needs to be further verified.

The government is actively pursuing a financial subsidy policy to assist new energy companies in strengthening their ability to innovate independently, but the impact of government subsidies has been contentious. Using 142 new energy listed companies in Shanghai and Shenzhen A-stocks from 2012 to 2018, a fixed-effect model was used to examine the impact of government subsidies on new energy companies’ R&D investment, as well as the changes in the relationship between the two under conditions of economic policy uncertainty and enterprise heterogeneity. The results indicate that government subsidies have an inverted U-shaped effect on enterprise R&D investment; that is, while appropriate subsidies promote enterprise R&D investment, excessive subsidies suffocate other funds invested by the company in R&D and exacerbate the company’s proclivity to invest in fixed assets. Furthermore, economic policy uncertainty has a more substantial negative adjustment effect on the relationship between government subsidies and corporate R&D investment than fixed-asset investment. Additionally, research indicates that in China’s eastern coastal regions, the impact of government subsidies on R&D investment is more remarkable for high-risk preference enterprises and non-state-owned enterprises than in the central and western regions, where the negative adjustment effect of economic policy uncertainty is more remarkable for low-risk-preference and non-state-owned enterprises. It is recommended that government departments ensure economic policy stability and continuity and that subsidy selection be more targeted and precise in determining subsidy funds.

In recent years, China's rapid economic development and steady growth of household consumption have contributed to the continuous growth of energy consumption. In addition to considering direct household energy consumption, the indirect effects of people's consumption activities on energy consumption in other productive sectors can't be ignored. According to the input-output analysis framework and consumer lifestyle analysis, this paper mainly studies the direct and indirect consumption of energy by Chinese household consumption ways and the relationship between energy structure and lifestyle. From the perspective of structural analysis, the input-output subsystem model (scale component, own internal component, feed-back component and spillover component) is used to analyze the energy supply and demand relations among 36 sectors of the national economy related to the lives of household in 2012 and 2017, revealing the change trend and transmission mechanism. This paper also focuses on the impact of household consumption ways on energy consumption of industrial sector and changing consumer lifestyles on energy saving, meanwhile it also forecasts China's future household energy consumption under four scenarios. The results show that in 2012 and 2017, total consumption of energy which is influenced by household consumption ways in China is 28461.82 PJ and 44759.96 PJ, respectively, accounting for 26.9% and 34.1% of total consumption of final energy. The indirect energy consumption is 1.3 times and 1.65 times of direct, respectively. The coal consumption accounts for the majority of indirect energy consumption. The smelting and pressing of ferrous metals is the industrial sector which is most affected by the household consumption ways. The scale component, own internal component, feed-back component and spillover component has accounted for 18.5%, 1.3%, 0.1% and 80.0%, from 17.5%, 2.0%, 0.2% and 80.3% of energy consumption in total, respectively. Under the four scenario development modes (NN, NA, LN and LA), it is predicted that the indirect energy consumption in household life in 2025 is 43740.56PJ, 34922.93PJ, 39149.37PJ and 31257.28PJ, respectively. The implementation of low-carbon consumption mode and the accelerated decline of energy intensity will help to reduce energy consumption.