精密な飼料作物管理に向けた多段階リモートセンシングとシミューレーションモデルの応用

内容の要約広島大学(Hiroshima University)博士(農学)Doctor of Agriculturedoctora

Regression-based heterogeneity analysis to identify overlapping subgroup structure in high-dimensional data

Heterogeneity is a hallmark of complex diseases. Regression-based heterogeneity analysis, which is directly concerned with outcome-feature relationships, has led to a deeper understanding of disease biology. Such an analysis identifies the underlying subgroup structure and estimates the subgroup-specific regression coefficients. However, most of the existing regression-based heterogeneity analyses can only address disjoint subgroups; that is, each sample is assigned to only one subgroup. In reality, some samples have multiple labels, for example, many genes have several biological functions, and some cells of pure cell types transition into other types over time, which suggest that their outcome-feature relationships (regression coefficients) can be a mixture of relationships in more than one subgroups, and as a result, the disjoint subgrouping results can be unsatisfactory. To this end, we develop a novel approach to regression-based heterogeneity analysis, which takes into account possible overlaps between subgroups and high data dimensions. A subgroup membership vector is introduced for each sample, which is combined with a loss function. Considering the lack of information arising from small sample sizes, an $l_2$ norm penalty is developed for each membership vector to encourage similarity in its elements. A sparse penalization is also applied for regularized estimation and feature selection. Extensive simulations demonstrate its superiority over direct competitors. The analysis of Cancer Cell Line Encyclopedia data and lung cancer data from The Cancer Genome Atlas shows that the proposed approach can identify an overlapping subgroup structure with favorable performance in prediction and stability.Comment: 33 pages, 16 figure

Net-Mediated Pubic Opinion Analysis of China’s Real Estate

With the development of Internet technology, the analysis of net-mediated public opinion based on text mining, has become increasingly concerned by the academic community in recent years. In this paper, we do research on net-mediated public opinion of China\u27s real estate in the second quarter of 2015empirically with the association rules, text tendency analysis and other technology of data mining and visualization. On the basis of the demonstration, a basic framework of net-mediated public opinion analysis is constructed. According to the analysis of this paper, the distribution and association of hot topics in this quarter were found, and the overall tendencies of the topics were reviewed, also some relevant policy recommendations were given

Breastmilk microbiome changes associated with lactational mastitis and treatment with dandelion extract

IntroductionDandelion (Pugongying) is one of the most frequently used Chinese herbs for treating lactational mastitis (LM). Pugongying granules, a patented medication primarily comprised of dandelion extract, have been approved by CFDA for LM treatment in China. The aims of this study were to investigate the etiology of LM and the mechanism by which Pugongying granules decrease LM symptoms, with a particular focus on the microbial communities found in breastmilk.MethodsParticipants were recruited from a previously performed randomized controlled trial (Identifier: NCT03756324, ClinicalTrials.gov). Between 2019 and 2020, women diagnosed with unilateral LM at the Beijing University of Chinese Medicine Third Affiliated Hospital were enrolled. In total, 42 paired breastmilk samples from the healthy and affected breasts of the participants were collected. Additionally, 37 paired pre- and post-treatment breastmilk samples from the affected breast were collected from women who received a 3-day course of either Pugongying granules (20 women) or cefdinir (17 women). Clinical outcomes [e.g., body temperature, visual analogue scale (VAS) score for breast pain, the percentage of neutrophils (NE%)] were analyzed pre- and post-treatment, and the breastmilk samples were subjected to 16S rRNA gene sequencing to analyze the alpha and beta diversities and identify significant bacteria. Finally, the relationship between microorganisms and clinical outcomes was analyzed.ResultsThere was no significant difference in fever and pain between the Pugongying group and cefdinir group. The most prevalent bacterial genera in breastmilk were Streptococcus and Staphylococcus. Compared to healthy breastmilk, microbial diversity was reduced in affected breastmilk, and there was a higher relative abundance of Streptococcus. After Pugongying treatment, there was an increase in microbial diversity with significantly higher abundance of Corynebacterium. A negative correlation was found between Corynebacterium, VAS score, and NE%. Treatment with cefdinir did not affect microbial diversity. Taken together, our results show a correlation between LM and reduced microbial diversity, as well as an increased abundance of Streptococcus in affected breastmilk.ConclusionPugongying granules enhanced microbial diversity in breastmilk samples. Given the substantial variation in individual microbiomes, identifying specific species of Streptococcus and Corynebacterium associated with LM may provide additional insight into LM pathogenesis and treatment

The potential diagnostic accuracy of urine formaldehyde levels in Alzheimer’s disease: A systematic review and meta-analysis

BackgroundFormaldehyde (FA), a toxic aldehyde, has been shown to be associated with a variety of cognitive disorders, including Alzheimer’s disease (AD). There is increasing evidence that FA levels are significantly increased in AD patients and may be involved in the pathological process of AD. The aim of this study was to assess the potential diagnostic value of urine FA levels in AD using meta-analysis techniques.MethodsOriginal reports of morning urine FA levels in AD patients and healthy controls (HCs) were included in the meta-analysis. Standardized mean differences (SMD) were calculated using a random-effects model, heterogeneity was explored using methodological, age, sex difference and sensitivity analyses, and receiver operating characteristic (ROC) curves were constructed to assess the diagnostic value of urine FA levels in AD.ResultsA total of 12 studies were included, and the urine FA levels of 874 AD patients and 577 HCs were reviewed. Compared with those in HCs, the FA levels were significantly increased in AD patients. The heterogeneity of the results did not affect their robustness, and results of the area under the curve (AUC) suggested that urine FA levels had good potential diagnostic value.ConclusionUrine FA levels are involved in AD disease progression and are likely to be useful as a potential biomarker for clinical auxiliary diagnosis. However, further studies are needed to validate the results of this study