Adjusting for Nonignorable Missingness When Estimating Generalized Additive Models

Generalized additive models (GAMs) have been widely used for flexible modeling of various types of outcomes. When the outcome in a GAM is subject to missing, practical analyses often assume that missingness is missing at random (MAR). This assumption can be of suspicion when the missingness is not by design. Evaluating the potential effects of alternative nonignorable missing data mechanism on the MAR inference from a GAM can be important but often challenging due to the complicatedness of alternative nonignorable models. We apply the index approach to local sensitivity (Troxel, Ma, and Heitjan 2004 (2004). Statistica Sinica 14 , 1221–1237) to evaluate the potential changes of the GAM estimates in the neighborhood of the MAR model. The approach avoids fitting any complicated nonignorable GAM. Only MAR estimates are required to calculate the resulting sensitivity index and adjust the GAM estimates to account for nonignorable missingness. Thus the proposed approach is considerably simpler to conduct, as compared with the alternative methods. The simulation study shows that the index provides valid assessment of the local sensitivity of the GAM estimates to nonignorable missingness. We then illustrate the method using a rheumatoid arthritis clinical trial data set.     

Translating Cancer Molecular Variability into Personalized Information Using Bulk and Single Cell Approaches

Cancer research is striving toward new frontiers of assigning the correct personalized drug(s) to a given patient. However, extensive tumor heterogeneity poses a major obstacle. Tumors of the same type often respond differently to therapy, due to patient‐specific molecular aberrations and/or untargeted tumor subpopulations. It is frequently not possible to determine a priori which patients will respond to a certain therapy or how an efficient patient‐specific combined therapy should be designed. Large‐scale datasets have been growing at an accelerated pace and various technologies and analytical tools for single cell and bulk level analyses are being developed to extract significant individualized signals from such heterogeneous data. However, personalized therapies that dramatically alter the course of the disease remain scarce, and most tumors still respond poorly to medical care. In this review, the basic concepts of bulk and single cell approaches are discussed, as well as their emerging role in individualized designs of drug therapies, including the advantages and limitations of their applications in personalized medicine.     

PDMS Microwell Stencil Based Multiplexed Single‐Cell Secretion Analysis

Multiplexed single‐cell protein secretion analysis provides an in‐depth understanding of cellular heterogeneity in intercellular communications mediated by secreted proteins in both fundamental and clinical research. However, it has been challenging to increase the proteomic parameters co‐profiled from every single cell in a facile way. Herein, a simple method to improve the multiplexed proteomic parameters of PDMS microwell based single‐cell secretion analysis platform by sandwiching PDMS stencil in between two antibody‐coated glass slides is introduced. Two different antibody panels can be immobilized easily by static coating, without using sophisticated fluid handling or bulky equipment. 5‐plexed, 3‐fluorescence color single‐cell secretion assay is demonstrated with this platform to investigate human monocytic U937 cells in response to lipopolysaccharide and phorbol myristate acetate stimulation, which identified the existence of functional subsets dictated by different cytokine profiles. The technology introduced here is simple, easy to operate, which holds great potential to become a powerful tool for profiling multiplexed single‐cell cytokine secretion at high throughput to dissect cellular heterogeneity in secretome signatures.     

微生物燃料电池发展态势分析

随着世界经济的高速发展和人口的不断增长,能源短缺和环境污染问题日益成为制约发展的瓶颈。微生物燃料电池(microbial fuel cell,MFC)能将污染物中蕴含的化学能直接转化为电能,实现同步污水处理和电能回收,是一种极具前景的可持续污水处理技术。同时,MFC在污泥处理、生物修复、环境监测、海水淡化等方面也展示了诱人的前景。基于科睿唯安Web of Science数据库和德温特专利检索分析平台(Derwent Innovation, DI),对MFC领域1990~2018年的论文和专利数据进行统计分析,得出全球MFC领域的发展趋势、国际分布、研发热点和技术格局。在此基础上,对未来MFC领域的发展做出了展望,对中国MFC产业化发展提出了思考和建议。     

Comprehensive analysis of mRNA‐level and miRNA‐level subpathway activities for identifying robust ovarian cancer prognostic signatures

Ovarian cancer (OvCa) causes the highest mortality among all gynaecologic cancers. A large number of mRNA‐ or miRNA‐based signatures were identified for OvCa patient prognosis. However, the comprehensive analysis of function‐level prognostic signatures is currently not considered in OvCa. In the present study, we respectively inferred subpathway activities from mRNA and miRNA levels based on high‐throughput expression profiles and reconstructed subpathways. Firstly, the activities of two tumour pathways were calculated and the difference between normal and tumour samples were analysed using multiple tumour types. Then, we calculated subpathway activities for OvCa based on the expression profiles from both mRNA and miRNA levels. Furthermore, based on these subpathway activity matrices, we performed bootstrap analysis to obtain sub‐training sets and utilized univariate method to identify robust OvCa prognostic subpathways. A comprehensive comparison of subpathway results between these two levels was performed. As a result, we observed subpathway mutual exclusion trend between the levels of mRNA and miRNA, which indicated the necessary of combining mRNA‐miRNA levels. Finally, by using ICGC data as testing sets, we utilized two strategies to verify survival predictive power of the mRNA‐miRNA combined subpathway signatures and performed comparisons with results from individual levels. It was confirmed that our framework displayed application to identify robust and efficient prognostic signatures for OvCa, and the combined signatures indeed exhibited advantages over individual ones. In the study, we took a step forward in relevant novel integrated functional signatures for OvCa prognosis.     

Chemical Characterization and Phytotoxic Effects of the Aerial Parts of Ruzigrass (Urochloa ruziziensis)

Studies of the phytotoxic effects between plants can be a crucial tool in the discovery of innovative compounds with herbicide potential. In this sense, we can highlight ruzigrass (Urochloa ruziziensis), which is traditionally used in the crop rotation system in order to reduce weed emergence. The aim of this work was to characterize the secondary metabolites of ruzigrass and to evaluate its phytotoxic effects. In total, eight compounds were isolated: friedelin, oleanolic acid, α‐amyrin, 1‐dehydrodiosgenone, sitosterol and stigmasterol glycosides, tricin and p‐coumaric acid. Phytotoxic effects of the crude methanolic extract and fractions of ruzigrass were assessed using germination rate, initial seedling growth, and biomass of Bidens pilosa, Euphorbia heterophylla and Ipomoea grandifolia. Chemometric analysis discriminated the weed species into three groups, and B. pilosa was the most affected by fractions of ruzigrass. The phytotoxic activities of 1‐dehydrodiosgenone, tricin, and p‐coumaric acid are also reported, and p‐coumaric acid and 1‐dehydrodiosgenone were active against B. pilosa.     

Combinations of non-invasive indicators to detect dairy cows submitted to high-starch-diet challenge

High-starch diets (HSDs) fed to high-producing ruminants are often responsible for rumen dysfunction and could impair animal health and production. Feeding HSDs are often characterized by transient rumen pH depression, accurate monitoring of which requires costly or invasive methods. Numerous clinical signs can be followed to monitor such diet changes but no specific indicator is able to make a statement at animal level on-farm. The aim of this pilot study was to assess a combination of non-invasive indicators in dairy cows able to monitor a HSD in experimental conditions. A longitudinal study was conducted in 11 primiparous dairy cows fed with two different diets during three successive periods: a 4-week control period (P1) with a low-starch diet (LSD; 13% starch), a 4-week period with an HSD (P2, 35% starch) and a 3-week recovery period (P3) again with the LSD. Animal behaviour was monitored throughout the experiment, and faeces, urine, saliva, milk and blood were sampled simultaneously in each animal at least once a week for analysis. A total of 136 variables were screened by successive statistical approaches including: partial least squares-discriminant analysis, multivariate analysis and mixed-effect models. Finally, 16 indicators were selected as the most representative of a HSD challenge. A generalized linear mixed model analysis was applied to highlight parsimonious combinations of indicators able to identify animals under our experimental conditions. Eighteen models were established and the combination of milk urea nitrogen, blood bicarbonate and feed intake was the best to detect the different periods of the challenge with both 100% of specificity and sensitivity. Other indicators such as the number of drinking acts, fat:protein ratio in milk, urine, and faecal pH, were the most frequently used in the proposed models. Finally, the established models highlight the necessity for animals to have more than 1 week of recovery diet to return to their initial control state after a HSD challenge. This pilot study demonstrates the interest of using combinations of non-invasive indicators to monitor feed changes from a LSD to a HSD to dairy cows in order to improve prevention of rumen dysfunction on-farm. However, the adjustment and robustness of the proposed combinations of indicators need to be challenged using a greater number of animals as well as different acidogenic conditions before being applied on-farm.     

Insect diversity in Gonggeom‐ji,the first protected paddy field wetland in Korea

Gonggeom‐ji pond is the first protected paddy field wetland area, designated by the Ministry of Environment of Korea in 2011, because of its high biodiversity and historic value. It contains reservoirs, paddy fields, and a forest site that provides diverse niches for insects. Quantitative methods were used in this study to estimate the insect diversity of this region. A transect of 50 m was designated in each site (reservoirs, paddy fields, and a forest site). Data were collected using sweeping and pitfall traps along each transect in May, August, and November 2017, representative of the seasons—spring, summer, and autumn, respectively. As a result, a total of 1079 individual insects representing 170 species from 60 families within nine orders were collected. Diversity, richness, and evenness indices were the highest in the forest site in May (4.77, 8.6, and 0.91, respectively). The dominance index was the highest in the forest site in November (0.64). Similarity index was the highest in the reservoir in May and August (0.519). These results would help compare different sites and their vegetation to assess relationships between insects and habitats.