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We previously reported on the strong symbiosis of AMF species (Rhizophagus irregularis CD1) with the cotton (Gossypium hirsutum L.) which is grown worldwide. In current study, it was thus investigated in farmland to determine the biological control effect of AMF on phosphorus acquisition and related gene expression regulation, plant growth and development, and a series of agronomic traits associated with yield and fiber quality in cotton. When AMF and cotton were symbiotic, the expression of the specific phosphate transporter family genes and P concentration in the cotton biomass were significantly enhanced. The photosynthesis, growth, boll number per plant and the maturity of the fiber were increased through the symbiosis between cotton and AMF. Statistical analysis showed a highly significant increase in yield for inoculated plots compared with that from the non inoculated controls, with an increase percentage of 28.54%. These findings clearly demonstrate here the benefits of AMF-based inoculation on phosphorus acquisition, growth, seed cotton yield and fiber quality in cotton. Further improvement of these beneficial inoculants on crops will help increase farmers’ income all over the world both now and in the future.

Auxin has a profound impact on plant physiology and participates in almost all aspects of plant development processes. Auxin exerts profound pleiotropic effects on plant growth and differentiation by regulating the auxin response genes’ expressions. The classical auxin reaction is usually mediated by auxin response factors (ARFs), which bind to the auxin response element (AuxRE) in the promoter region of the target gene. Experiments have generated only a limited number of plant genes with well-characterized functions. It is still unknown how many genes respond to exogenous auxin treatment. An economical and effective method was proposed for the genome-wide discovery of genes responsive to auxin in a model plant, Arabidopsis thaliana (A. thaliana). Our method relies on cis-regulatory-element-based targeted gene finding across different promoters in a genome. We first exploit and analyze auxin-specific cis-regulatory elements for the transcription of the target genes, and then identify putative auxin responsive genes whose promoters contain the elements in the collection of over 25,800 promoters in the A. thaliana genome. Evaluating our result by comparing with a published database and the literature, we found that this method has an accuracy rate of 65.2% (309/474) for predicting candidate genes responsive to auxin. Chromosome distribution and annotation of the putative auxin-responsive genes predicted here were also mined. The results can markedly decrease the number of identified but merely potential auxin target genes and also provide useful clues for improving the annotation of gene that lack functional information.

Maximizing the quality of experience (QoE) for real-time video is a long-standing challenge. Traditional video transport protocols, represented by a few deterministic rules, can hardly adapt to the heterogeneous and highly dynamic modern Internet. Emerging learning-based algorithms have demonstrated potential to meet the challenge. However, our measurement study reveals an alarming long tail performance issue: these algorithms tend to be bottle-necked by occasional catastrophic events due to the built-in exploration mechanisms. In this work, we propose Loki, which improves the robustness of learning-based model by coherently integrating it with a rule-based algorithm. To enable integration at feature level, we first reverse-engineer the rule-based algorithm into an equivalent "black-box" neural network. Then, we design a dual-attention feature fusion mechanism to fuse it with a reinforcement learning model. We train Loki in a commercial real-time video system through online learning, and evaluate it over 101 million video sessions, in comparison to state-of-the-art rule-based and learning-based solutions. The results show that Loki improves not only the average but also the tail performance substantially (26.30% to 44.24% reduction of stall rate and 1.76% to 2.17% increase in video throughput at 95-percentile).

As an important plant single cell model and textile application materials, poorly known about fiber color formation in cotton, which is sensitively regulated by environmental signals. Our studies underline the importance of photo signal on sensitive fiber color formation and characterize fiber color early initiation (15 DPA) and late accumulated metabolites (45 DPA) in different lighting condition. The results revealed 236 differential metabolites between control and shading, of which phenylpropanoids metabolites accounted for 20%, including uncharacterized novel metabolites and pathways. Furthermore, the early initiation specific genes respond to the absence of light are highly correlated with phenylpropanoid metabolites related to pigmentation. The current study reveals the complex pathways involving early initiation regulation and late metabolic pathways. In addition, the collection composed of uncharacterized photoinduced metabolites and early initiation signaling/regulatory genes were identified, which are important resources for understanding fiber color formation. This report provides new insight into molecular regulatory and biochemical basis underlying photoinduced fiber color formation in cotton.

Background: A series of reforms were implemented to improve the quality of primary care services in China. This study aims to assess patients&rsquo, perceived quality of primary healthcare between rural and urban community health centers in Guangdong. Methods: A cross-sectional survey was conducted from July to December 2015 in Guangdong. We surveyed 1010 respondents who visited either community health centers/stations (CHCs/CHSs) in urban areas or township health centers/rural health stations (THCs/RHSs) in rural areas. A validated Chinese version of the Primary Care Assessment Tool-Adult Short Version (PCAT-AS), representing ten primary care domains, was used to collect information on patients&rsquo, primary care experiences. A t-test was used for comparison on domain scores and total scores between patients from CHCs/CHSs and THCs/RHSs. An analysis of covariance was employed to compare the adjusted PCAT domain scores and total scores. Multilevel models were used to explore factors associated with PCAT total scores. Results: Overall, patients reported a lower level of experience of community orientation and family centeredness compared to other primary care domains. Patients from THCs/RHSs settings in the rural area reported better primary care experience in four domains, including first contact, accessibility, ongoing care, and community orientation. Higher education background and those with a chronic disease were associated with better primary care experience, after controlling for confounding factors. Patients who preferred primary care institutions when getting sick or used health services more frequently reported better primary care experiences. Conclusion: Continued efforts are needed to strengthen primary care performances, particularly in a community orientation and family centeredness. Primary care delivery in CHCs/CHSs settings should be improved in four domains, including first contact, accessibility, ongoing care, and community orientation.

As one of the important components of electrocardiogram (ECG) signals, QRS signal represents the basic characteristics of ECG signals. The detection of QRS waves is also an essential step for ECG signal analysis. In order to further meet the clinical needs for the accuracy and real-time detection of QRS waves, a simple, fast, reliable, and hardware-friendly algorithm for real-time QRS detection is proposed. The exponential transform (ET) and proportional-derivative (PD) control-based adaptive threshold are designed to detect QRS-complex. The proposed ET can effectively narrow the magnitude difference of QRS peaks, and the PD control-based method can adaptively adjust the current threshold for QRS detection according to thresholds of previous two windows and predefined minimal threshold. The ECG signals from MIT-BIH databases are used to evaluate the performance of the proposed algorithm. The overall sensitivity, positive predictivity, and accuracy for QRS detection are 99.90%, 99.92%, and 99.82%, respectively. It is also implemented on Altera Cyclone V 5CSEMA5F31C6 Field Programmable Gate Array (FPGA). The time consumed for a 30-min ECG record is approximately 1.3 s. It indicates that the proposed algorithm can be used for wearable heart rate monitoring and automatic ECG analysis.

Auxin has a profound impact on plant physiology and participates in almost all aspects of plant development processes. Auxin exerts profound pleiotropic effects on plant growth and differentiation by regulating the auxin response genes’ expressions. The classical auxin reaction is usually mediated by auxin response factors (ARFs), which bind to the auxin response element (AuxRE) in the promoter region of the target gene. Experiments have generated only a limited number of plant genes with well-characterized functions. It is still unknown how many genes respond to exogenous auxin treatment. An economical and effective method was proposed for the genome-wide discovery of genes responsive to auxin in a model plant, Arabidopsis thaliana (A. thaliana). Our method relies on cis-regulatory-element-based targeted gene finding across different promoters in a genome. We first exploit and analyze auxin-specific cis-regulatory elements for the transcription of the target genes, and then identify putative auxin responsive genes whose promoters contain the elements in the collection of over 25,800 promoters in the A. thaliana genome. Evaluating our result by comparing with a published database and the literature, we found that this method has an accuracy rate of 65.2% (309/474) for predicting candidate genes responsive to auxin. Chromosome distribution and annotation of the putative auxin-responsive genes predicted here were also mined. The results can markedly decrease the number of identified but merely potential auxin target genes and also provide useful clues for improving the annotation of gene that lack functional information.

Background General practitioner (GP) system is proved to be effective in over 50 countries worldwide. Guangdong province, as a reform pilot in China, initiated its patient-GP contract service reform in 2014. This study is designed to assess the patients’ acceptance of General Practitioners Contract (GPC) reform and explore its influencing factors. Methods This survey interviewed 1010 participants from 16 primary health centers (PHCs) chosen from 4 pilot cities in Guangdong during July and December in 2015. Data were collected through face-to-face interviews. The questionnaire was developed to discover the acceptance of GPC and covered three parts: respondents’ socio-demographic characteristics, health service utilization, and the patients’ assessment of primary health care centers. A binary logistic regression model was used to measure the influencing factors of respondents’ acceptance of GPC policy. Results A total of 611(60.5%) participants accepted GPC policy. Compared to patients visited PHCs over 7 times in the previous year, those visited PHCs fewer times reported lower acceptance of GPC policy (OR:0.68, 95% CI:0.49–0.96 for visits ≤3 times and OR:0.57, 95% CI:0.38–0.84 for visits = 4–6 times). Patients’ satisfaction with medical service coverage was positively associated with patients’ acceptance of GPC (OR: 1.72, 95% CI:1.01–3.98 for the satisfied versus the dissatisfied; OR: 1.38, 95% CI:0.92–3.30 for neutral versus the dissatisfied), and the satisfaction with drug list also positively influenced patients’ acceptance of GPC policy (OR: 1.44, 95% CI:1.26–2.73 for the satisfied versus the dissatisfied; OR:1.61, 95% CI:1.36–2.99 for neutral versus the dissatisfied). Meanwhile, age and education had positive impacts on the acceptance of the GPC policy. Conclusion This study finds out that patients’ satisfaction with medical service coverage and drug list are the influencing factors for the acceptance of GPC policy. Therefore, improvement of medical service accessibility such as better follow-up of patients with chronic diseases and enhanced referral service, as well as the expansion of drug list, will improve patients’ acceptance of GPC policy. It also finds that patients using more primary health service are inclined to accept GPC policy, so more attractive and high-quality service should be provided in PHCs. Electronic supplementary material The online version of this article (10.1186/s12913-019-4053-x) contains supplementary material, which is available to authorized users.

Questionnaire. (DOCX 26 kb)

Background and objectives . The electrocardiograms (ECGs) are widely used to diagnose a variety of arrhythmias. Generally, the abnormalities of ECG signals mainly consist of ill-shaped ECG beat morphologies and irregular intervals. The ill-shaped ECG beat morphologies represent morphological information, while the irregular intervals denote the temporal information of ECG signals. But it is difficult to utilize morphological information and temporal information simultaneously when dealing with single ECG heartbeats, because RR interval is not contained in a single short heartbeat. Therefore, to handle this problems, a novel Multi-information Fusion Convolutional Bidirectional Recurrent Neural Network (MF-CBRNN) is proposed for arrhythmia automatic detection. Methods . The MF-CBRNN is designed with two parallel hybrid branches that can simultaneously focus on the beat-based information in the ECG beats and the segment-based information in the adjacent segments of the beats. A single ECG beat provides the morphological information. At the same time, the adjacent segment of the ECG beat enriches the temporal information, so the two branches are designed to exploit the multiple information contained in ECGs. Furthermore, a combination of convolutional neural networks (CNNs) and a bidirectional long short memory (BLSTM) in each branch is utilized to capture the information from the two inputs. And all the features extracted from the two branches are fused for information aggregation. Results . To evaluate the performance of the proposed model, the ECG signals from MIT-BIH databases are used for intra-patient and inter-patient paradigms. The proposed model yields an accuracy of 99.56% and an F1-score of 96.40% under the intra-patient paradigm. And it obtains an overall accuracy of 96.77% and F1-score of 77.83% under the inter-patient paradigm. Conclusions . Compared with other studies on arrhythmia detection, our method achieves a state-of-the-art performance. It indicates that the proposed model is a promising arrhythmia detection algorithm for computer-aided diagnostic systems.

General practitioner (GP) systems were proved to be effective in over 50 countries worldwide. Guangdong province, as a reform pilot in China, initiated its patient-GP contract reform in 2014. And the local residents acted less positively than the government expected to. Aimed to assess contract rate of residents and its influencing factors, we conducted a cross-sectional questionnaire survey covering 951 participants from 16 primary health care (PHC) institutions that were randomly chosen from 4 cities in Guangdong in 2015. We collected variables associated with the contract behavior recommended by related studies and ran the logistic regression model to test their influences. Results showed 57.83% of participants contracted with a GP within one year post-reform. Influencing factors were age, education level, self-reported health status, chronic diseases, acquaintance to GP and satisfaction of PHC institutions. Measures should be taken to increase residents’ awareness of GP and providing high-quality primary care.