Path and Ridge Regression Analysis of Seed Yield and Seed Yield Components of Russian Wildrye (Psathyrostachys juncea Nevski) under Field Conditions

The correlations among seed yield components, and their direct and indirect effects on the seed yield (Z) of Russina wildrye (Psathyrostachys juncea Nevski) were investigated. The seed yield components: fertile tillers m-2 (Y1), spikelets per fertile tillers (Y2), florets per spikelet- (Y3), seed numbers per spikelet (Y4) and seed weight (Y5) were counted and the Z were determined in field experiments from 2003 to 2006 via big sample size. Y1 was the most important seed yield component describing the Z and Y2 was the least. The total direct effects of the Y1, Y3 and Y5 to the Z were positive while Y4 and Y2 were weakly negative. The total effects (directs plus indirects) of the components were positively contributed to the Z by path analyses. The seed yield components Y1, Y2, Y4 and Y5 were significantly (P<0.001) correlated with the Z for 4 years totally, while in the individual years, Y2 were not significant correlated with Y3, Y4 and Y5 by Peason correlation analyses in the five components in the plant seed production. Therefore, selection for high seed yield through direct selection for large Y1, Y2 and Y3 would be effective for breeding programs in grasses. Furthermore, it is the most important that, via ridge regression, a steady algorithm model between Z and the five yield components was founded, which can be closely estimated the seed yield via the components

Anonymisation of geographical distance matrices via Lipschitz embedding

BACKGROUND: Anonymisation of spatially referenced data has received increasing attention in recent years. Whereas the research focus has been on the anonymisation of point locations, the disclosure risk arising from the publishing of inter-point distances and corresponding anonymisation methods have not been studied systematically. METHODS: We propose a new anonymisation method for the release of geographical distances between records of a microdata file-for example patients in a medical database. We discuss a data release scheme in which microdata without coordinates and an additional distance matrix between the corresponding rows of the microdata set are released. In contrast to most other approaches this method preserves small distances better than larger distances. The distances are modified by a variant of Lipschitz embedding. RESULTS: The effects of the embedding parameters on the risk of data disclosure are evaluated by linkage experiments using simulated data. The results indicate small disclosure risks for appropriate embedding parameters. CONCLUSION: The proposed method is useful if published distance information might be misused for the re-identification of records. The method can be used for publishing scientific-use-files and as an additional tool for record-linkage studies

Pulmonary arterial medial smooth muscle thickness in sudden infant death syndrome: an analysis of subsets of 73 cases

Previous studies addressing pulmonary artery morphology have compared cases of sudden infant death syndrome (SIDS) to controls but none have compared demographic profiles, exposure to potentially hypoxic risk factors and other pathologic variables in SIDS cases grouped according to pulmonary artery medial smooth muscle thickness. Aims: To compare the relative medial thickness (RMT) in alveolar wall arteries (AW) in SIDS cases with that in age-matched controls and 2. Compare demographic, clinical, and pathologic characteristics among three subsets of SIDS cases based upon alveolar wall (AW) RMT. Retrospective morphometric planimetry of all muscularized arteries in standardized right apical lung sections in 73 SIDS cases divided into three groups based on increasing AW RMT as well as 19 controls age-matched to 19 of the SIDS cases. SIDS and age-matched control cases did not differ with respect to AW RMT or other demographic variables. The SIDS group with the thickest AW RMT had significantly more males and premature birth than the other groups, but the groups did not differ for known clinical risk factors that would potentially expose them to hypoxia. Pathologic variables, including pulmonary inflammation, gastric aspiration, intra-alveolar siderophages, cardiac valve circumferences, and heart and liver weights, were not different between groups. Age was not significantly correlated with RMT of alveolar wall and pre-acinar arteries but was significant at p = .018 for small intra-acinar arteries. The groups were different for RMT of small pre-acinar and intra-acinar arteries, which increased with increasing AW RMT. Statistical differences should not necessarily be equated with clinical importance, however future research incorporating more quantified historical data is recommended

Generative Embedding for Model-Based Classification of fMRI Data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in ‘hidden’ physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups

Evaluating the impact of handling and logger attachment on foraging parameters and physiology in southern rockhopper penguins

Logger technology has revolutionised our knowledge of the behaviour and physiology of free-living animals but handling and logger attachments may have negative effects on the behaviour of the animals and their welfare. We studied southern rockhopper penguin ( Eudyptes chrysocome ) females during the guard stage in three consecutive breeding seasons (2008/09−2010/11) to evaluate the effects of handling and logger attachment on foraging trip duration, dive behaviour and physiological parameters. Smaller dive loggers (TDRs) were used in 2010/11 for comparison to larger GPS data loggers used in all three seasons and we included two categories of control birds: handled controls and PIT control birds that were previously marked with passive integrative transponders (PITs), but which had not been handled during this study. Increased foraging trip duration was only observed in GPS birds during 2010/11, the breeding season in which we also found GPS birds foraging further away from the colony and travelling longer distances. Compared to previous breeding seasons, 2010/11 may have been a period with less favourable environmental conditions, which would enhance the impact of logger attachments. A comparison between GPS and TDR birds showed a significant difference in dive depth frequencies with birds carrying larger GPS data loggers diving shallower. Mean and maximum dive depths were similar between GPS and TDR birds. We measured little impact of logger attachments on physiological parameters (corticosterone, protein, triglyceride levels and leucocyte counts). Overall, handling and short-term logger attachments (1-3 days) showed limited impact on the behaviour and physiology of the birds but care must be taken with the size of data loggers on diving seabirds. Increased drag may alter their diving behaviour substantially, thus constraining them in their ability to catch prey. Results obtained in this study indicate that data recorded may also not represent their normal dive behaviour

Who Eats Whom in a Pool? A Comparative Study of Prey Selectivity by Predatory Aquatic Insects

Predatory aquatic insects are a diverse group comprising top predators in small fishless water bodies. Knowledge of their diet composition is fragmentary, which hinders the understanding of mechanisms maintaining their high local diversity and of their impacts on local food web structure and dynamics. We conducted multiple-choice predation experiments using nine common species of predatory aquatic insects, including adult and larval Coleoptera, adult Heteroptera and larval Odonata, and complemented them with literature survey of similar experiments. All predators in our experiments fed selectively on the seven prey species offered, and vulnerability to predation varied strongly between the prey. The predators most often preferred dipteran larvae; previous studies further reported preferences for cladocerans. Diet overlaps between all predator pairs and predator overlaps between all prey pairs were non-zero. Modularity analysis separated all primarily nectonic predator and prey species from two groups of large and small benthic predators and their prey. These results, together with limited evidence from the literature, suggest a highly interconnected food web with several modules, in which similarly sized predators from the same microhabitat are likely to compete strongly for resources in the field (observed Pianka’s diet overlap indices >0.85). Our experiments further imply that ontogenetic diet shifts are common in predatory aquatic insects, although we observed higher diet overlaps than previously reported. Hence, individuals may or may not shift between food web modules during ontogeny

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research