A new species of genus Pseudaspidapion Wanat, 1990 (Coleoptera, Apionidae) from China

Pseudaspidapion botanicum sp. n. from China is described and figured. Its host plant is Grewia biloba G.Don var. parviflora (Bunge) Hand.-Mazz (Malvaceae: Grewioideae). The genus Harpapion Voss, 1966 is recorded as new for China and Vietnam and two comb. n. are proposed: Harpapion vietnamense (Korotyaev, 1985) (from Aspidapion) and H. coelebs (Korotyaev, 1987) (from Pseudaspidapion). A key to the known species of the genus Pseudaspidapion from China is presented.We thank Marek Wanat for kindly providing us references and many good advices, Boris A. Korotyaev for lending paratypes, Steven R. Davis for doing the linguistic review before submission, Yang Ganyan for collecting specimens, Zhou Dakang for providing information about the host plants, Yin Ziwei and Nico M. Franz for providing the brush-pencil Plug-ins of Adobe Illustrator. We also thank two anonymous reviewers whose suggestions considerably improved our work. This research has been supported by an Invited Professor Award (2009) of the Chinese Academy of Sciences to the senior author and by project grant CGL2010–15786 (Ministerio de Ciencia e Innovación, Spain).Peer Reviewe

Spatial Pattern and Determinants of the First Detection Locations of Invasive Alien Species in Mainland China

BACKGROUND: The unintentional transport of species as a result of human activities has reached unprecedented rates. Once established, introduced species can be nearly impossible to eradicate. It is therefore essential to identify and monitor locations where invaders are most likely to establish new populations. Despite the obvious value of early detection, how does an agency identify areas that are most vulnerable to new invaders? Here we propose a novel approach by using the "first detection location" (FDL) of introduced species in China to quantify characteristics of areas where introduced species are first reported. METHODOLOGY/PRINCIPAL FINDINGS: We obtained FDLs for 166 species (primarily agricultural and forestry pests) that were unintentionally introduced into China prior to 2008 from literature searches. The spatial pattern and determinants of FDLs were examined at the provincial level. The spatial pattern of FDLs varied among provinces with more commerce and trade and economically developed provinces in coastal regions having more FDLs than interior provinces. For example, 74.6% of FDLs were distributed in coastal regions despite that they only cover 15.6% of the total area in China. Variables that may be indicators of "introduction pressure" (e.g. the amount of received commerce) had an overwhelming effect on the number of FDLs in each province (R(2) = 0.760). CONCLUSIONS/SIGNIFICANCE: Our results suggest that "introduction pressure" may be one of the most important factors that determine the locations where newly-introduced species are first detected, and that open and developed provinces in China should be prioritized when developing monitoring programs that focus on locating and managing new introductions. Our study illustrates that FDL approaches can contribute to the study and management of biological invasions not only for China but also for elsewhere

An Ensemble Multilabel Classification for Disease Risk Prediction

It is important to identify and prevent disease risk as early as possible through regular physical examinations. We formulate the disease risk prediction into a multilabel classification problem. A novel Ensemble Label Power-set Pruned datasets Joint Decomposition (ELPPJD) method is proposed in this work. First, we transform the multilabel classification into a multiclass classification. Then, we propose the pruned datasets and joint decomposition methods to deal with the imbalance learning problem. Two strategies size balanced (SB) and label similarity (LS) are designed to decompose the training dataset. In the experiments, the dataset is from the real physical examination records. We contrast the performance of the ELPPJD method with two different decomposition strategies. Moreover, the comparison between ELPPJD and the classic multilabel classification methods RAkEL and HOMER is carried out. The experimental results show that the ELPPJD method with label similarity strategy has outstanding performance

Evemphyron sinense, a new genus and species infesting legume seedpods in China (Coleoptera, Attelabidae, Rhynchitinae)

A new genus Evemphyron Alonso-Zarazaga, Lv & Wang, gen. n., belonging to Attelabidae Rhynchitinae, is described. Its single species, Evemphyron sinense Alonso-Zarazaga, Lv & Wang, sp. n., was reared from larvae found inside seed pods of the legume Callerya dielsiana (Fabaceae, Millettieae) in Sichuan Province (China). The species is figured and placed in the Deporaini because of the presence of minute labial palpi, the strongly crescentic apex of the postmentum, and the apodemes of male IX sternite and female VIII sternite curved sinistro-anterially near their cephalic end. It shows 3-segmented labial palpi and male sex patches on the procoxae, characters that suggest a basal position in the tribe.Peer Reviewe

A Novel Deep Neural Network Model for Multi-Label Chronic Disease Prediction

Chronic diseases are one of the biggest threats to human life. It is clinically significant to predict the chronic disease prior to diagnosis time and take effective therapy as early as possible. In this work, we use problem transform methods to convert the chronic diseases prediction into a multi-label classification problem and propose a novel convolutional neural network (CNN) architecture named GroupNet to solve the multi-label chronic disease classification problem. Binary Relevance (BR) and Label Powerset (LP) methods are adopted to transform multiple chronic disease labels. We present the correlated loss as the loss function used in the GroupNet, which integrates the correlation coefficient between different diseases. The experiments are conducted on the physical examination datasets collected from a local medical center. In the experiments, we compare GroupNet with other methods and models. GroupNet outperforms others and achieves the best accuracy of 81.13%

Evaluation of anti-smoking television advertising on tobacco control among urban community population in Chongqing, China

Background China is the largest producer and consumer of tobacco in the world. Considering the constantly growing urban proportion, persuasive tobacco control measures are important in urban communities. Television, as one of the most pervasive mass media, can be used for this purpose. Methods The anti-smoking advertisement was carried out in five different time slots per day from 15 May to 15 June in 2011 across 12 channels of Chongqing TV. A cross-sectional study was conducted in the main municipal areas of Chongqing. A questionnaire was administered in late June to 1,342 native residents aged 18–45, who were selected via street intercept survey. Results Respondents who recognized the advertisement (32.77 %) were more likely to know or believe that smoking cigarettes caused impotence than those who did not recognize the advertisement (26.11 %). According to 25.5 % of smokers, the anti-smoking TV advertising made them consider quitting smoking. However, females (51.7 %) were less likely to be affected by the advertisement to stop and think about quitting smoking compared to males (65.6 %) (OR = 0.517, 95 % CI [0.281–0.950]). In addition, respondents aged 26–35 years (67.4 %) were more likely to try to persuade others to quit smoking than those aged 18–25 years (36.3 %) (OR = 0.457, 95 % CI [0.215–0.974]). Furthermore, non-smokers (87.4 %) were more likely to find the advertisement relevant than smokers (74.8 %) (OR = 2.34, 95 % CI [1.19–4.61]). Conclusions This study showed that this advertisement did not show significant differences on smoking-related knowledge and attitude between non-smokers who had seen the ad and those who had not. Thus, this form may not be the right tool to facilitate change in non-smokers. The ad should instead be focused on the smoking population. Gender, smoking status, and age influenced the effect of anti-smoking TV advertising on the general population in China

An Ensemble Multilabel Classification for Disease Risk Prediction

It is important to identify and prevent disease risk as early as possible through regular physical examinations. We formulate the disease risk prediction into a multilabel classification problem. A novel Ensemble Label Power-set Pruned datasets Joint Decomposition (ELPPJD) method is proposed in this work. First, we transform the multilabel classification into a multiclass classification. Then, we propose the pruned datasets and joint decomposition methods to deal with the imbalance learning problem. Two strategies size balanced (SB) and label similarity (LS) are designed to decompose the training dataset. In the experiments, the dataset is from the real physical examination records. We contrast the performance of the ELPPJD method with two different decomposition strategies. Moreover, the comparison between ELPPJD and the classic multilabel classification methods RAkEL and HOMER is carried out. The experimental results show that the ELPPJD method with label similarity strategy has outstanding performance

Potential Diagnostic Applications of Multi-Delay Arterial Spin Labeling in Early Alzheimer’s Disease: The Chinese Imaging, Biomarkers, and Lifestyle Study

Background: Cerebral blood flow (CBF) alterations are involved in the onset and progression of Alzheimer’s disease (AD) and can be a potential biomarker. However, CBF measured by single-delay arterial spin labeling (ASL) for discrimination of mild cognitive impairment (MCI, an early stage of AD) was lack of accuracy. Multi-delay ASL can not only provide CBF quantification but also provide arterial transit time (ATT). Unfortunately, the technique was scarcely applied to the diagnosis of AD. Here, we detected the utility of ASL with 1-delay and 7-delay in ten regions of interest (ROIs) to identify MCI and AD. Materials and Methods: Pseudocontinuous ASL (pCASL) MRI was acquired on a 3T GE scanner in adults from the Chinese Imaging, Biomarkers, and Lifestyle (CIBL) Study of AD cohort, including 26 normal cognition (NC), 37 MCI, and 39 AD. Receiver operating characteristic (ROC) analyses with 1-delay and 7-delay ASL were performed for the identification of MCI and AD. The DeLong test was used to compare ROC curves. Results: For CBF of 1-delay or 7-delay the AUCs showed moderate-high performance for the AD/NC and AD/MCI comparisons (AUC = 0.83∼0.96) (p 0.05). Conclusion: The combination of CBF and ATT with 7-delay ASL showed higher performance for identification of MCI than CBF of 1-delay, when adding to sex, age, APOE ε4 carrier status, and education years, the diagnostic performance was further increased, presenting a potential imaging biomarker in early AD

Microbiome analysis and biocontrol bacteria isolation from rhizosphere soils associated with different sugarcane root rot severity

To explore the causal pathogen and the correlated rhizosphere soil microecology of sugarcane root rot, we sampled the sugarcane root materials displaying different disease severity, and the corresponding rhizosphere soil, for systematic root phenotype and microbial population analyses. We found that with increased level of disease severity reflected by above-ground parts of sugarcane, the total root length, total root surface area and total volume were significantly reduced, accompanied with changes in the microbial population diversity and structure in rhizosphere soil. Fungal community richness was significantly lower in the rhizosphere soil samples from mildly diseased plant than that from either healthy plant, or severely diseased plant. Particularly, we noticed that a peculiar decrease of potential pathogenic fungi in rhizosphere soil, including genera Fusarium, Talaromyces and Neocosmospora, with increased level of disease severity. As for bacterial community, Firmicutes was found to be of the highest level, while Acidobacteria and Chloroflexi of the lowest level, in rhizosphere soil from healthy plant compared to that from diseased plant of different severity. FUNGuild prediction showed that the proportion of saprophytic fungi was higher in the rhizosphere soil of healthy plants, while the proportion of pathogenic fungi was higher in the rhizosphere soil of diseased plants. By co-occurrence network analysis we demonstrated the Bacillus and Burkholderia were in a strong interaction with Fusarium pathogen(s). Consistently, the biocontrol and/or growth-promoting bacteria isolated from the rhizosphere soil were mostly (6 out of 7) belonging to Bacillus and Burkholderia species. By confrontation culture and pot experiments, we verified the biocontrol and/or growth-promoting property of the isolated bacterial strains. Overall, we demonstrated a clear correlation between sugarcane root rot severity and rhizosphere soil microbiome composition and function, and identified several promising biocontrol bacteria strains with strong disease suppression effect and growth-promoting properties