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The present study aimed to investigate the mediating roles of parental and romantic attachment in the relationship between interparental conflict (IPC) and young adults' romantic relationship quality, and whether their mediating roles differ between males and females. A total of 160 heterosexual romantic couples (mean age = 21.82 years, SD = 1.72 years) from a capital city in western China volunteered to take part in an online survey, which encompassed self-report questionnaires of IPC, parental attachment, romantic attachment, and romantic relationship quality. Structural equation modeling was conducted to analyze data among males and females, respectively. Results suggested that male adults' attachment to mother independently mediated the relationship between IPC and male adults' romantic relationship quality, whereas romantic anxiety independently mediated the relationship between IPC and female adults' romantic relationship quality. In addition, for both males and females, parental and romantic attachment did not sequentially mediate the association between IPC and romantic relationship quality. These findings illustrate the differential roles that parental and romantic attachment play in the mediation mechanisms for male and female young adults. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has driven public health intervention strategies, including keeping social distance, wearing masks in crowded places, and having good health habits, to prevent the transmission of the novel coronavirus (SARS-CoV-2). However, it is unknown whether the use of these intervention strategies influences morbidity in other human infectious diseases, such as tuberculosis.Methods: In this study, three prediction models were constructed to compare variations in PTB incidences after January 2020 without or with intervention includes strict and regular interventions, when the COVID-19 outbreak began in China. The non-interventional model was developed with an autoregressive integrated moving average (ARIMA) model that was trained with the monthly incidence of PTB in China from January 2005 to December 2019. The interventional model was established using an ARIMA model with a continuing intervention function that was trained with the monthly PTB incidence in China from January 2020 to December 2020.Results: Starting with the assumption that no COVID-19 outbreak had occurred in China, PTB incidence was predicted, and then the actual incidence was compared with the predicted incidence. A remarkable overall decline in PTB incidence from January 2020 to December 2020 was observed, which was likely due to the potential influence of intervention policies for COVID-19. If the same intervention strategy is applied for the next 2 years, the monthly PTB incidence would reduce on average by about 1.03 per 100,000 people each month compared with the incidence predicted by the non-interventional model. The annual incidence estimated 59.15 under regular intervention per 100,000 in 2021, and the value would decline to 50.65 with strict interventions.Conclusions: Our models quantified the potential knock-on effect on PTB incidence of the intervention strategy used to control the transmission of COVID-19 in China. Combined with the feasibility of the strategies, these results suggested that continuous regular interventions would play important roles in the future prevention and control of PTB. [ABSTRACT FROM AUTHOR]

Maotai liquor is one of the most famous traditional Chinese distilled liquor enjoyed by many people all over the world for its unique production method, impressive liquor quality, and soy sauce‐like and roasted aroma style. It is known that aroma characteristics of liquor mainly depend on the aroma compounds. Alcohols as one of the most important categories of aroma components have been determined in Maotai liquor. However, the systemic analysis of alcoholic compounds in liquor is limited, especially the active alcoholic components and their pharmacological effects. Therefore, in this study, a systemic analysis method was proposed by combining in silico absorption, distribution, metabolism, and excretion (ADME) evaluation, target fishing, network pharmacology technology, pathway analysis, and experimental verification to interpret the pharmacological mechanism of alcoholic compounds in Maotai liquor. Finally, 15 compounds with favorable pharmacokinetic profiles were screened through in silico ADME models. Thirty‐eight related targets of these active compounds were identified by target prediction method. The network pharmacology and pathway analysis were developed to clarify the pharmacological effect of alcoholic compounds in Maotai liquor at the system and pathway level. Moreover, the key active compounds were validated by in vitro experiments that verified the effectiveness of our methods. Our study provides a novel approach to systematically analyze the pharmacological effect of alcoholic compounds in Maotai liquor, which would be beneficial for promoting the in‐depth study of various liquors. Practical Application: Maotai liquor is popularly enjoyed in the world for a very long time. However, the systemic analysis of compounds in liquor is limited. Our systematic analysis approach was developed to explore the bioactive ingredients and their related target proteins as well as the pharmacological effects of Maotai liquor. This will provide a new method to understand the pharmacological mechanisms of compounds in various liquors at the systems level, so as to promote the development of liquors and to increase the public awareness of science about alcohol consumption. [ABSTRACT FROM AUTHOR]

Introduction: It has been suggested that uncontrolled epilepsy might not necessarily equate to drug resistance when antiepileptic drugs (AEDs) are used at relatively low doses, a practice frequently observed in rural areas of China.Objective: To assess the clinical benefits of further drug manipulation in this situation, we prospectively followed up the outcomes of patients with uncontrolled epilepsy while taking relatively low doses of AEDs.Methods: The study included patients aged 16 years and older with uncontrolled epilepsy and who were receiving at least one AED at a dosage below 50% of the World Health Organization (WHO) defined daily dose (DDD) (50% DDD) (Group 1). Patients with drug-resistant epilepsy were included for comparison (Group 2). Both groups were followed-up for at least 2 years. Seizure outcomes after further drug manipulations were recorded at the last follow-up.Results: A total of 197 patients (55.3% male) were included in Group 1 and 32 (46.9% male) in Group 2; their mean duration of follow-up was 28.85 ± 1.90 and 30.91 ± 2.04 months, respectively. At the last follow-up, 16.8% (33/197) of patients in Group 1 had become seizure-free compared with none in Group 2 (p < 0.001). Seventeen of 93 (18.3%) patients in Group 1 became seizure free after increasing the dosage of baseline AED(s) alone. Only 5.5% (3/55) of patients who had failed to respond to an AED at ≥50% DDD at baseline became seizure free compared with 21.1% (30/142) who did not have such a history (p = 0.001). The number of AEDs taken at a dosage below 50% DDD at baseline was not associated with seizure outcome.Conclusions: Uncontrolled epilepsy could become controlled in a substantial proportion of patients by dose increase alone, particularly if there is no history of drug failure at ≥50% DDD. [ABSTRACT FROM AUTHOR]

In recent years, haze pollution is frequent, which seriously affects daily life and production process. The main factors to measure the degree of smoke pollution are the concentrations of PM2.5 and PM10. Therefore, it is of great significance to study the prediction of PM2.5/PM10 concentration. Since PM2.5 and PM10 concentration data are time series, their time characteristics should be considered in their prediction. However, the traditional neural network is limited by its own structure and has some weakness in processing time related data. Recurrent neural network is a kind of network specially used for sequence data modeling, that is, the current output of the sequence is correlated with the historical output. In this paper, a haze prediction model is established based on a deep recurrent neural network. We obtained air pollution data in Chengdu from the China Air Quality Online Monitoring and Analysis Platform, and conducted experiments based on these data. The results show that the new method can predict smog more effectively and accurately, and can be used for social and economic purposes. [ABSTRACT FROM AUTHOR]

Biofilms on the inner surface of a drinking water distribution system (DWDS) affect water quality and stability. Understanding the niche differentiation of biofilm microbial communities is necessary for the efficient control of DWDS biofilms. However, biofilm studies are difficult to conduct in the actual DWDS because of inaccessibility to the pipes buried underground. Taking the opportunity of infrastructure construction and relevant pipeline replacement in China, biofilms in a DWDS (a water main and its branch pipes) were collected in situ, followed by analysis on the abundances and community structures of bacterial and archaeal using quantitative PCR and high-throughput sequencing, respectively. Results showed that archaea were detected only in the biofilms of the water main, with a range of 9.4×103~1.1×105 copies/cm2. By contrast, bacteria were detected in the biofilms of branch pipes and the distal part of the water main, with a range of 8.8×103~9.6×106 copies/cm2. Among the biofilm samples, the archaeal community in the central part of the water main showed the highest richness and diversity. Nitrosopumilus was found to be predominant (86.22%) in the biofilms of the proximal part of the water main. However, Methanobrevibacter (87.15%) predominated in the distal part of the water main. The bacterial community of the water main and branch pipes was primarily composed of Firmicutes and Proteobacteria at the phylum level, respectively. Regardless of archaea or bacteria, only few operational taxonomic units (OTUs) (<0.5% of total OTUs) were shared by all the biofilms, indicating the niche differentiation of biofilm microorganisms. Moreover, the high Mn content in the biofilms of the distal sampling location (D3) in the water main was linked to the predominance of Bacillus. Functional gene prediction revealed that the proportion of infectious disease-related genes was 0.44–0.67% in the tested biofilms. Furthermore, functional genes related to the resistance of the bacterial community to disinfections and antibiotics were detected in all the samples, that is, glutathione metabolism-relating genes (0.14–0.65%) and beta-lactam resistance gene (0.01–0.05%). The results of this study indicate the ubiquity of archaea and bacteria in the biofilms of water main and branch pipes, respectively, and pipe diameters could be a major influencing factor on bacterial community structure. In the water main, the key finding was the predominant existence of archaea, particularly Nitrosopumilus and methanogen. Hence, their routine monitoring and probable influences on water quality in pipelines with large diameter should be given more attention. Besides, since Mn-related Bacillus and suspected pathogenic Enterococcus were detected in the biofilm, supplementation of disinfectant may be a feasible strategy for inhibiting their growth and ensuring water quality. In addition, the monitoring on their abundance variation could help to determine the frequency and methods of pipeline maintenance. [ABSTRACT FROM AUTHOR]