bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive discovery of subsample gene expression components by information explanation: therapeutic implications in cancer
Authors: Pepke S. , Ver Steeg G. 
Published: March 2016

AbstractBackgroundDe novoinference of clinically relevant gene function relationships from tumor RNA-seq remains a challenging task. Current methods typically either partition patient samples into a few subtypes or rely upon analysis of pairwise gene correlations (co-expression) that will miss some groups in noisy data. Leveraging higher dimensional information can be expected to increase the power to discern targetable pathways, but this is commonly thought to be an intractable computational problem.MethodsIn this work we adapt a recently developed machine learning algorithm, CorEx, that efficiently optimizes over multivariate mutual information for sensitive detection of complex gene relationships. The algorithm can be iteratively applied to generate a hierarchy of latent factors. Patients are stratified relative to each factor and combinatoric survival analyses are performed and interpreted in the context of biological function annotations and protein network interactions that might be utilized to match patients to multiple therapies.ResultsAnalysis of ovarian tumor RNA-seq samples demonstrates the algorithm’s power to infer well over one hundred biologically interpretable gene cohorts, several times more than standard methods such as hierarchical clustering and k-means. The CorEx factor hierarchy is also informative, with related but distinct gene clusters grouped by upper nodes. Some latent factors correlate with patient survival, including one for a pathway connected with the epithelial-mesenchymal transition in breast cancer that is regulated by a potentially druggable microRNA. Further, combinations of factors lead to a synergistic survival advantage in some cases.ConclusionsIn contrast to studies that attempt to partition patients into a small number of subtypes (typically 4 or fewer) for treatment purposes, our approach utilizes subgroup information for combinatoric transcriptional phenotyping. Considering only the 66 gene expression groups that are both found to have significant Gene Ontology enrichment and are small enough to indicate specific drug targets implies a computational phenotype for ovarian cancer that allows for 366possible patient profiles, enabling truly personalized treatment. The findings here demonstrate a new technique that sheds light on the complexity of gene expression dependencies in tumors and could eventually enable the use of patient RNA-seq profiles for selection of personalized and effective cancer treatments.
Comparative analysis of dengue and Zika outbreaks reveals differences by setting and virus
Authors: Funk Sebastian , Kucharski Adam J. , Camacho Anton , Eggo Rosalind M. , Yakob Laith , Murray Lawrence M. , Edmunds W. John 
Published: March 2016

AbstractThe pacific islands of Micronesia have experienced several outbreaks of mosquito-borne diseases over the past decade. In outbreaks on small islands, the susceptible population is usually well defined, and there is no co-circulation of pathogens. Because of this, analysing such outbreaks can be useful for understanding the transmission dynamics of the pathogens involved, and particularly so for yet understudied pathogens such as Zika virus. Here, we compared three outbreaks of dengue and Zika virus in two different island settings in Micronesia, the Yap Main Islands and Fais, using a mathematical model of transmission dynamics, making full use of commonalities in disease and setting between the outbreaks. We found that the estimated reproduction numbers for Zika and dengue were similar when considered in the same setting, but that, conversely, reproduction number for the same disease can vary considerably by setting. On the Yap Main Islands, we estimated a reproduction number of 8.0–16 (95% Credible Interval (CI)) for the dengue outbreak and 4.8–14 (95% CI) for the Zika outbreak, whereas for the dengue outbreak on Fais our estimate was 28–102 (95% CI). We further found that the proportion of cases of Zika reported was smaller (95% CI 1.4%–1.9%) than that of dengue (95% CI 47%–61%). We confirmed these results in extensive sensitivity analysis. They suggest that models for dengue transmission can be useful for estimating the predicted dynamics of Zika transmission, but care must be taken when extrapolating findings from one setting to another.Author SummaryDengue and Zika are related viruses and are both transmitted by mosquitoes. Dengue is well described and affects people around the world. Zika, on the other hand has only recently caused outbreak in human populations, and it has been suggested that its behaviour might similar dengue. To investigate this, we compared three outbreaks of dengue and Zika in island populations of the pacific: two dengue outbreaks and one Zika outbreak. Island outbreaks are useful laboratories for understanding the spread of infections because they are usually short, well-identified episodes, whereas elsewhere it can be difficult to identify the properties of outbreaks when different viruses spread at the same time. In our investigation of the outbreaks in Micronesia we found that dengue and Zika virus did, indeed, behave similar in outbreaks they caused on the Yap Main Islands. A dengue outbreak on the smaller island of Fais, on the other hand, was different from the dengue outbreak on Yap in that transmission seems to have been more efficient. We conclude that dengue outbreaks are indeed a good model for Zika outbreaks when considered in the same setting, but that one must be careful when comparing outbreaks in different settings.
Understanding melanopsin using bayesian generative models – an Introduction
Authors: Ehinger Benedikt V. , Eickelbeck Dennis , Spoida Katharina , Herlitze Stefan , König Peter 
Published: March 2016

1.AbstractUnderstanding biological processes implies a quantitative description. In recent years a new tool set, Bayesian hierarchical modeling, has seen rapid development. We use these methods to model kinetics of a specific protein in a neuroscience context: melanopsin. Melanopsin is a photoactive protein in retinal ganglion cells. Due to its photoactivity, melanopsin is widely used in optogenetic experiments and an important component in the elucidation of neuronal interactions. Thus it is important to understand the relevant processes and develop mechanistic models. Here, with a focus on methodological aspects, we develop, implement, fit and discuss Bayesian generative models of melanopsin dynamics.We start with a sketch of a basic model and then translate it into formal probabilistic language. As melanopsin occurs in at least two states, a resting and a firing state, a basic model is defined by a non-stationary two state hidden Markov process. Subsequently we add complexities in the form of (1) a hierarchical extension to fit multiple cells; (2) a wavelength dependency, to investigate the response at different color of light stimulation; (3) an additional third state to investigate whether melanopsin is bi‐ or tri-stable; (4) differences between different sub-types of melanopsin as found in different species. This application of modeling melanopsin dynamics demonstrates several benefits of Bayesian methods. They directly model uncertainty of parameters, are flexible in the distributions and relations of parameters in the modeling, and allow including prior knowledge, for example parameter values based on biochemical data.
Cerebrospinal Fluid and Interstitial Fluid Motion via the Glymphatic Pathway Modelled by Optimal Mass Transport
Authors: Ratner Vadim , Gao Yi , Lee Hedok , Nedergaard Maikan , Benveniste Helene , Tannenbaum Allen 
Published: March 2016

ABSTRACTIt was recently shown that the brain-wide cerebrospinal fluid (CSF) and interstitial fluid exchange system designated the ‘glymphatic pathway’ plays a key role in removing waste products from the brain, similarly to the lymphatic system in other body organs1,2. It is therefore important to study the flow patterns of glymphatic transport through the live brain in order to better understand its functionality in normal and pathological states. Unlike blood, the CSF does not flow rapidly through a network of dedicated vessels, but rather through peri-vascular channels and brain parenchyma in a slower time-domain, and thus conventional fMRI or other blood-flow sensitive MRI sequences do not provide much useful information about the desired flow patterns. We have accordingly analyzed a series of MRI images, taken at different times, of the brain of a live rat, which was injected with a paramagnetic tracer into the CSF via the lumbar intrathecal space of the spine. Our goal is twofold: (a) find glymphatic (tracer) flow directions in the live rodent brain; and (b) provide a model of a (healthy) brain that will allow the prediction of tracer concentrations given initial conditions. We model the liquid flow through the brain by the diffusion equation. We then use the Optimal Mass Transfer (OMT) approach3to model the glymphatic flow vector field, and estimate the diffusion tensors by analyzing the (changes in the) flow. Simulations show that the resulting model successfully reproduces the dominant features of the experimental data.
ALADIN is Required for the Production of Fertile Mouse Oocytes
Authors: Carvalhal Sara , Stevense Michelle , Koehler Katrin , Naumann Ronald , Huebner Angela , Jessberger Rolf , Griffis Eric R. 
Published: March 2016

AbstractAsymmetric cell divisions depend upon the precise placement of the mitotic spindle. In mammalian oocytes, spindles assemble close to the cell’s centre but chromosome segregation takes place at the cell periphery where half of the chromosomes are expelled into small, nondeveloping polar bodies at anaphases. By dividing so asymmetrically, most of the cytoplasmic content within the oocyte is preserved, which is critical for successful fertilization and early development. Recently, we determined that the nucleoporin ALADIN participates in spindle assembly in somatic cells, and we have also shown that female mice homozygous deficient for ALADIN are sterile. In this study we show that this protein is involved in specific meiotic stages including meiotic resumption, spindle assembly, and spindle positioning. In the absence of ALADIN, polar body extrusion is impaired in a majority of oocytes due to problems in spindle orientation prior to the first meiotic anaphase. Those few oocytes that can mature far enough to be fertilized in vitro are unable to support embryonic development beyond the twocell stage. Overall, we find that ALADIN is critical for oocyte maturation and appears to be far more essential for this process than for somatic cell divisions.
Nature lessons: the whitefly bacterial endosymbiont is a minimal amino acid factory with unusual energetics
Authors: Calle-Espinosa Jorge , Ponce-de-Leon Miguel , Santos-Garcia Diego , Silva Francisco J. , Montero Francisco , Peretó Juli 
Published: March 2016

AbstractBacterial lineages that establish obligate symbiotic associations with insect hosts are known to possess highly reduced genomes with streamlined metabolic functions that are commonly focused on amino acid and vitamin synthesis. We constructed a genome-scale metabolic model of the whitefly bacterial endosymbiontCandidatusPortiera aleyrodidarum to study the energy production capabilities using stoichiometric analysis. Strikingly, the results suggest that the energetic metabolism of the bacterial endosymbiont relies on the use of pathways related to the synthesis of amino acids and carotenoids. A deeper insight showed that the ATP production via carotenoid synthesis may also have a potential role in the regulation of amino acid production. The coupling of energy production to anabolism suggest that minimization of metabolic networks as a consequence of genome size reduction does not necessarily limit the biosynthetic potential of obligate endosymbionts.
Clinicopathological study of crateriform verruca: Crateriform epithelial lesions histopathologically distinct from keratoacanthoma
Authors: Ogita Azusa , Ansai Shin‐ichi , Misago Noriyuki , Anan Takashi , Fukumoto Takaya , Saeki Hidehisa 
Published: March 2016

AbstractKeratoacanthoma (KA) is a distinct clinicopathological entity, but it is often confused with other crateriform tumors. This study re‐examined the clinicopathological features of 380 crateriform epithelial tumors with a central keratin plug. Seventy‐six tumors (20%) had histopathological features that differed from solitary KA and were more verruca‐like, and we designated these lesions as crateriform verruca (CFV). We performed clinicopathological re‐examination of these neoplasms with a crateriform architecture and epithelial lip‐like structures similar to KA, which also displayed histopathological features reminiscent of verruca vulgaris, such as finger‐like exophytic projections with hyperkeratosis and acanthosis, focal hypergranulosis and arborization. Clinical data on CFV were also summarized. The main histopathological differences from KA were that CFV showed proliferation of keratinocytes with a similar size and regular arrangement, and the base of CFV was well demarcated without endophytic growth. Interestingly, some CFV were partly composed of epithelial cells with large pink cytoplasm in the upper malpighian layer between papillomatous projections. Furthermore, areas of trichilemmal‐like keratinization without formation of the granular layer were seen in some lesions. These types of CFV were hardly distinguishable from KA, unless it is recognized that CFV may contain trichilemmal keratinization‐like areas accompanied by large epithelial cells with eosinophilic cytoplasm. We have proposed the term CFV for these verrucous neoplasms to differentiate them from KA.
Case of paraneoplastic pemphigus with immunoglobulin (Ig)G and IgA antibodies to various antigens
Authors: Otsuka Yohei , Ueno Takashi , Yamase Aya , Ito Michiko , Osada Shinichi , Kawana Seiji , Funasaka Yoko , Teye Kwesi , Ishii Norito , Hashimoto Takashi , Saeki Hidehisa 
Published: March 2016

AbstractA 63‐year‐old Japanese man with non‐Hodgkin B‐cell lymphoma presented with erythematous skin lesions on his entire body, with oral, ocular and anal mucosal lesions. The patient was diagnosed with paraneoplastic pemphigus. Immunofluorescence showed both immunoglobulin (Ig)G and IgA antibodies to keratinocyte cell surfaces. Various immunoblot and enzyme‐linked immunosorbent assays showed both IgG and IgA antibodies to various autoantigens, including desmogleins, desmocollins, envoplakin, periplakin and bullous pemphigoid antigens. This was a unique case with a very rare autoantibody profile in paraneoplastic pemphigus.
Phylogenetics of family Enterobacteriaceae and proposal to reclassify Escherichia hermannii and Salmonella subterranea as Atlantibacter hermannii and Atlantibacter subterranea gen. nov., comb. nov.
Authors: Hata Hiroyuki , Natori Tatsuya , Mizuno Takuya , Kanazawa Izumi , Eldesouky Ibrahim , Hayashi Masahiro , Miyata Machiko , Fukunaga Hajime , Ohji Shoko , Hosoyama Akira , Aono Eiji , Yamazoe Atsushi , Tsuchikane Keiko , Fujita Nobuyuki , Ezaki Takayuki 
Published: March 2016

ABSTRACTMultilocus sequence analysis based on hypervariable housekeeping proteins was utilized to differentiate closely related species in the family Enterobacteriaceae. Of 150 housekeeping proteins, the top 10 hypervariable proteins were selected and concatenated to obtain distance data. Distances between concatenated proteins within the family were 0.9–41.2%, whereas the 16S rRNA and atpD‐gyrB‐infB‐rpoB concatenated sequence (4MLSA) distances were 0.8–6.0% and 0.9–22.1%, respectively. These data indicate that phylogenetic analysis by concatenation of hypervariable proteins is a powerful tool for discriminating species in the family Enterobacteriaceae. To confirm the discriminatory power of the 10 chosen concatenated hypervariable proteins (C10HKP), phylogenetic trees based on C10HKP, 4MLSA, and the 16S rRNA gene were constructed. Comparison of average bootstrap values among C10HKP, 4MLSA and 16S rRNA genes indicated that the C10HKP tree was the most reliable. Location via the C10HKP tree was consistent with existing assignments for almost all species in the family Enterobacteriaceae. However, the C10HKP tree suggested that several species (including Enterobacter massiliensis, Escherichia vulneris, Escherichia hermannii, and Salmonella subterranea) should be reassigned to different clusters than those defined in previous analyses. Furthermore, E. hermannii and S. subterranea appeared to fall onto a branch independent from those occupied by the other Enterobacteriaceae. Therefore, we propose Atlantibacter gen. nov., such that E. hermannii and S. subterranea would be transferred to genus Atlantibacter as Atlantibacter hermannii, comb. nov. and Atlantibacter subterranea. comb. nov., respectively.
Characterization of fungi isolated from the equipment used in the International Space Station or Space Shuttle
Authors: Satoh Kazuo , Yamazaki Takashi , Nakayama Takako , Umeda Yoshiko , Alshahni Mohamed Mahdi , Makimura Miho , Makimura Koichi 
Published: March 2016

ABSTRACTAs a part of a series of studies regarding the microbial biota in manned space environments, fungi were isolated from six pieces of equipment recovered from the Japanese Experimental Module “KIBO” of the International Space Station and from a space shuttle. Thirty‐seven strains of fungi were isolated, identified and investigated with regard to morphological phenotypes and antifungal susceptibilities. The variety of fungi isolated in this study was similar to that of several previous reports. The dominant species belonged to the genera Penicillium, Aspergillus and Cladosporium, which are potential causative agents of allergy and opportunistic infections. The morphological phenotypes and antifungal susceptibilities of the strains isolated from space environments were not significantly different from those of reference strains on Earth.
Restructuring tree provenance test data to conform to reciprocal transplant experiments for detecting local adaptation
Authors: Lu Pengxin , Parker William C. , Colombo Stephen J. , Man Rongzhou 
Published: March 2016

Summary

Local adaptation is a fundamental assumption in delineating seed zones and developing seed transfer guidelines to safeguard climatic adaptation of tree and plant species during forest regeneration and ecological restoration. It is also broadly assumed for forest tree species that show genetic differentiation among geographic populations, especially for those with widespread natural distributions that occur in distinct environments.

However, due to a scarcity of suitable data, the inference of local adaptation has rarely been validated for forest tree species through reciprocal transplant experiments (RTEs). In this study, we illustrate a novel approach to restructure tree provenance test data to conform to RTEs and use recently proposed statistical models to detect local adaptation, using white spruce Picea glauca (Moench) Voss as an example. Our research demonstrates how similar studies can be conducted to validate local adaptation in other forest species and populations, for which RTEs are lacking, but where large, high‐quality provenance test data sets are available.

Contrary to common belief, our results show that local adaptation is absent in survival and height for white spruce populations from Ontario, Canada, although they have evolved in considerably different climatic habitats, and exhibit substantial and clinal genetic differentiation and significant genotype‐by‐environment interactions in these two adaptive traits.

Synthesis and applications. Our results show that the common assumption of local adaptation in forest tree species may not necessarily be correct within significant portions of their natural range. In forest genetic studies, population differentiation in adaptive traits has often been attributed to local adaptation without rigorous validation. Our results caution against such interpretation of experimental results. In the absence of local adaptation as shown by reciprocal transplant experiments, assisted migration may be considered as an option for enhancing forest adaptation to climate change.
Practical implementation of ecosystem monitoring for the ecosystem approach to management
Authors: Kupschus Sven , Schratzberger Michaela , Righton David 
Published: March 2016

Summary

The implementation of the ecosystem approach means there is a need to monitor an increased range of environmental conditions and ecological components in the marine environment. Many existing monitoring surveys have successfully added tasks or components to an existing monitoring programme while maintaining consistency of time series. This approach is not practical when the immediate data need for a wide range of ecosystem components requires substantial changes to the programme or when collections of different ecological components have conflicting requirements.

We propose a more integrated approach aimed at not only assessing change, but simultaneously delivering evidence of the underlying reasons for observed changes. Using principles developed from observational and modelling efforts in the Barents Sea and the wider literature, we distil the essential characteristics an integrated monitoring programme must exhibit. We demonstrate how such an integrated programme can offer substantial operational efficiencies compared to a coordinated approach.

Integrated monitoring based on ecosystem processes has significant advantages over the coordinated approach that uses ecosystem states independently and focuses on maximizing precision of each indicator. While integration is needed to address current policy requirements, changes to monitoring risk time‐series consistency. However, we explain how such risks can be minimized while at the same time establishing a framework that allows the incorporation of important information from other less flexible data sources to be used in the assessment.

Policy implications. Process‐based integrated monitoring is essential for the ecosystem approach. The focus on ecosystem processes provides the essential elements for future proof efficient management: (i) It provides both unbiased status estimates for reporting requirements and describes the causes of state change. (ii) It minimizes risks to historic time series while coping with changing ecological conditions. (iii) It quantifies ecosystem processes and provides the means to test hypotheses on how different processes interact. (iv) It uses all available information efficiently when used in conjunction with integrated assessments. (v) It is effective due to its adaptability to meet future policy demands and ecosystem requirements while using data in the most efficient manner given these demands.