Characterization of physiological responses to 22 gene knockouts in Escherichia coli central carbon metabolism.

Metab Eng. 2016 May 19;

Authors: Long CP, Gonzalez JE, Sandoval NR, Antoniewicz MR

Abstract
Understanding the impact of gene knockouts on cellular physiology, and metabolism in particular, is centrally important to quantitative systems biology and metabolic engineering. Here, we present a comprehensive physiological characterization of wild-type Escherichia coli and 22 knockouts of enzymes in the upper part of central carbon metabolism, including the PTS system, glycolysis, pentose phosphate pathway and Entner-Doudoroff pathway. Our results reveal significant metabolic changes that are affected by specific gene knockouts. Analysis of collective trends and correlations in the data using principal component analysis (PCA) provide new, and sometimes surprising, insights into E. coli physiology. Additionally, by comparing the data-to-model predictions from constraint-based approaches such as FBA, MOMA and RELATCH we demonstrate the important role of less well-understood kinetic and regulatory effects in central carbon metabolism.

PMID: 27212692 [PubMed - as supplied by publisher]

Multi-Omics of Single Cells: Strategies and Applications.

Trends Biotechnol. 2016 May 19;

Authors: Bock C, Farlik M, Sheffield NC

Abstract
Most genome-wide assays provide averages across large numbers of cells, but recent technological advances promise to overcome this limitation. Pioneering single-cell assays are now available for genome, epigenome, transcriptome, proteome, and metabolome profiling. Here, we describe how these different dimensions can be combined into multi-omics assays that provide comprehensive profiles of the same cell.

PMID: 27212022 [PubMed - as supplied by publisher]

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow.

Cell Syst. 2016 May 19;

Authors: Brunk E, George KW, Alonso-Gutierrez J, Thompson M, Baidoo E, Wang G, Petzold CJ, McCloskey D, Monk J, Yang L, O'Brien EJ, Batth TS, Martin HG, Feist A, Adams PD, Keasling JD, Palsson BO, Lee TS

Abstract
Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proof of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.

PMID: 27211860 [PubMed - as supplied by publisher]

Systems toxicology-based assessment of the candidate modified risk tobacco product THS2.2 for the adhesion of monocytic cells to human coronary arterial endothelial cells.

Toxicology. 2016 Jan 2;339:73-86

Authors: Poussin C, Laurent A, Peitsch MC, Hoeng J, De Leon H

Abstract
Alterations of endothelial adhesive properties by cigarette smoke (CS) can progressively favor the development of atherosclerosis which may cause cardiovascular disorders. Modified risk tobacco products (MRTPs) are tobacco products developed to reduce smoking-related risks. A systems biology/toxicology approach combined with a functional in vitro adhesion assay was used to assess the impact of a candidate heat-not-burn technology-based MRTP, Tobacco Heating System (THS) 2.2, on the adhesion of monocytic cells to human coronary arterial endothelial cells (HCAECs) compared with a reference cigarette (3R4F). HCAECs were treated for 4h with conditioned media of human monocytic Mono Mac 6 (MM6) cells preincubated with low or high concentrations of aqueous extracts from THS2.2 aerosol or 3R4F smoke for 2h (indirect treatment), unconditioned media (direct treatment), or fresh aqueous aerosol/smoke extracts (fresh direct treatment). Functional and molecular investigations revealed that aqueous 3R4F smoke extract promoted the adhesion of MM6 cells to HCAECs via distinct direct and indirect concentration-dependent mechanisms. Using the same approach, we identified significantly reduced effects of aqueous THS2.2 aerosol extract on MM6 cell-HCAEC adhesion, and reduced molecular changes in endothelial and monocytic cells. Ten- and 20-fold increased concentrations of aqueous THS2.2 aerosol extract were necessary to elicit similar effects to those measured with 3R4F in both fresh direct and indirect exposure modalities, respectively. Our systems toxicology study demonstrated reduced effects of an aqueous aerosol extract from the candidate MRTP, THS2.2, using the adhesion of monocytic cells to human coronary endothelial cells as a surrogate pathophysiologically relevant event in atherogenesis.

PMID: 26655683 [PubMed - indexed for MEDLINE]

Network Modeling Reveals Cross Talk of MAP Kinases during Adaptation to Caspofungin Stress in Aspergillus fumigatus.

PLoS One. 2015;10(9):e0136932

Authors: Altwasser R, Baldin C, Weber J, Guthke R, Kniemeyer O, Brakhage AA, Linde J, Valiante V

Abstract
Mitogen activated protein kinases (MAPKs) are highly conserved in eukaryotic organisms. In pathogenic fungi, their activities were assigned to different physiological functions including drug adaptation and resistance. Aspergillus fumigatus is a human pathogenic fungus, which causes life-threatening invasive infections. Therapeutic options against invasive mycoses are still limited. One of the clinically used drugs is caspofungin, which specifically targets the fungal cell wall biosynthesis. A systems biology approach, based on comprehensive transcriptome data sets and mathematical modeling, was employed to infer a regulatory network and identify key interactions during adaptation to caspofungin stress in A. fumigatus. Mathematical modeling and experimental validations confirmed an intimate cross talk occurring between the cell wall-integrity and the high osmolarity-glycerol signaling pathways. Specifically, increased concentrations of caspofungin promoted activation of these signalings. Moreover, caspofungin affected the intracellular transport, which caused an additional osmotic stress that is independent of glucan inhibition. High concentrations of caspofungin reduced this osmotic stress, and thus decreased its toxic activity. Our results demonstrated that MAPK signaling pathways play a key role during caspofungin adaptation and are contributing to the paradoxical effect exerted by this drug.

PMID: 26356475 [PubMed - indexed for MEDLINE]

Improving Biochemical Named Entity Recognition Performance Using PSO Classifier Selection and Bayesian Combination Method.

IEEE/ACM Trans Comput Biol Bioinform. 2016 May 18;

Authors: Akkasi A, Varoglu E

Abstract
Named Entity Recognition (NER) is a basic step for large number of consequent text mining tasks in the biochemical domain. Increasing the performance of such recognition systems is of high importance and always poses a challenge. In this study, a new community based decision making system is proposed which aims at increasing the efficiency of NER systems in the chemical/drug name context. Particle Swarm Optimization (PSO) algorithm is chosen as the expert selection strategy along with the Bayesian combination method to merge the outputs of the selected classifiers as well as evaluate the fitness of the selected candidates. The proposed system performs in two steps. The first step is focuses on creating various numbers of baseline classifiers for NER with different features sets using the Conditional Random Fields (CRFs). The second step involves the selection and efficient combination of the classifiers using PSO and Bayesisan combination. Two comprehensive corpora from BioCreative events, namely ChemDNER and CEMP, are used for the experiments conducted. Results show that the ensemble of classifiers selected by means of the proposed approach perform better than the single best classifier as well as ensembles formed using other popular selection/combination strategies for both corpora. Furthermore, the proposed method outperforms the best performing system at the Biocreative IV ChemDNER track by achieving an F-score of 87.95%.

PMID: 27214909 [PubMed - as supplied by publisher]

Two Similarity Metrics for Medical Subject Headings (MeSH): An Aid to Biomedical Text Mining and Author Name Disambiguation.

J Biomed Discov Collab. 2016;7:e1

Authors: Smalheiser NR, Bonifield G

Abstract
In the present paper, we have created and characterized several similarity metrics for relating any two Medical Subject Headings (MeSH terms) to each other. The article-based metric measures the tendency of two MeSH terms to appear in the MEDLINE record of the same article. The author-based metric measures the tendency of two MeSH terms to appear in the body of articles written by the same individual (using the 2009 Author-ity author name disambiguation dataset as a gold standard). The two metrics are only modestly correlated with each other (r = 0.50), indicating that they capture different aspects of term usage. The article-based metric provides a measure of semantic relatedness, and MeSH term pairs that co-occur more often than expected by chance may reflect relations between the two terms. In contrast, the author metric is indicative of how individuals practice science, and may have value for author name disambiguation and studies of scientific discovery. We have calculated article metrics for all MeSH terms appearing in at least 25 articles in MEDLINE (as of 2014) and author metrics for MeSH terms published as of 2009. The dataset is freely available for download and can be queried at http://arrowsmith.psych.uic.edu/arrowsmith_uic/mesh_pair_metrics.html. Handling editor: Elizabeth Workman, MLIS, PhD.

PMID: 27213780 [PubMed - as supplied by publisher]

Update on the safety of second generation antipsychotics in youths: a call for collaboration among paediatricians and child psychiatrists.

Ital J Pediatr. 2016;42(1):51

Authors: Pisano S, Catone G, Veltri S, Lanzara V, Pozzi M, Clementi E, Iuliano R, Riccio MP, Radice S, Molteni M, Capuano A, Gritti A, Coppola G, Milone A, Bravaccio C, Masi G

Abstract
During the past decade, a substantial increase in the use of second generation antipsychotics (SGAs) has occurred for a number of juvenile psychiatric disorders, often as off-label prescriptions. Although they were thought to be safer than older, first generation antipsychotics, mainly due to a lower risk of neurological adverse reactions, recent studies have raised significant concerns regarding their safety regarding metabolic, endocrinological and cardiovascular side effects. Aim of this paper is to update with a narrative review, the latest findings on safety of SGAs in youths. Results suggest that different SGAs may present different safety profiles. Metabolic adverse events are the most frequent and troublesome, with increasing evidences of heightened risk for type II diabetes mellitus. Results are discussed with specific emphasis on possible strategies of an active monitoring, which could enable both paediatricians and child psychiatrists to a possible prevention, early detection, and a timely management of such effects.

PMID: 27209326 [PubMed - as supplied by publisher]

DNetDB: The human disease network database based on dysfunctional regulation mechanism.

BMC Syst Biol. 2016;10(1):36

Authors: Yang J, Wu SJ, Yang SY, Peng JW, Wang SN, Wang FY, Song YX, Qi T, Li YX, Li YY

Abstract
Disease similarity study provides new insights into disease taxonomy, pathogenesis, which plays a guiding role in diagnosis and treatment. The early studies were limited to estimate disease similarities based on clinical manifestations, disease-related genes, medical vocabulary concepts or registry data, which were inevitably biased to well-studied diseases and offered small chance of discovering novel findings in disease relationships. In other words, genome-scale expression data give us another angle to address this problem since simultaneous measurement of the expression of thousands of genes allows for the exploration of gene transcriptional regulation, which is believed to be crucial to biological functions. Although differential expression analysis based methods have the potential to explore new disease relationships, it is difficult to unravel the upstream dysregulation mechanisms of diseases. We therefore estimated disease similarities based on gene expression data by using differential coexpression analysis, a recently emerging method, which has been proved to be more potential to capture dysfunctional regulation mechanisms than differential expression analysis. A total of 1,326 disease relationships among 108 diseases were identified, and the relevant information constituted the human disease network database (DNetDB). Benefiting from the use of differential coexpression analysis, the potential common dysfunctional regulation mechanisms shared by disease pairs (i.e. disease relationships) were extracted and presented. Statistical indicators, common disease-related genes and drugs shared by disease pairs were also included in DNetDB. In total, 1,326 disease relationships among 108 diseases, 5,598 pathways, 7,357 disease-related genes and 342 disease drugs are recorded in DNetDB, among which 3,762 genes and 148 drugs are shared by at least two diseases. DNetDB is the first database focusing on disease similarity from the viewpoint of gene regulation mechanism. It provides an easy-to-use web interface to search and browse the disease relationships and thus helps to systematically investigate etiology and pathogenesis, perform drug repositioning, and design novel therapeutic interventions.Database URL: http://app.scbit.org/DNetDB/ #.

PMID: 27209279 [PubMed - as supplied by publisher]

Clinical decision-making and secondary findings in systems medicine.

BMC Med Ethics. 2016;17(1):32

Authors: Fischer T, Brothers KB, Erdmann P, Langanke M

Abstract
BACKGROUND: Systems medicine is the name for an assemblage of scientific strategies and practices that include bioinformatics approaches to human biology (especially systems biology); "big data" statistical analysis; and medical informatics tools. Whereas personalized and precision medicine involve similar analytical methods applied to genomic and medical record data, systems medicine draws on these as well as other sources of data. Given this distinction, the clinical translation of systems medicine poses a number of important ethical and epistemological challenges for researchers working to generate systems medicine knowledge and clinicians working to apply it.
DISCUSSION: This article focuses on three key challenges: First, we will discuss the conflicts in decision-making that can arise when healthcare providers committed to principles of experimental medicine or evidence-based medicine encounter individualized recommendations derived from computer algorithms. We will explore in particular whether controlled experiments, such as comparative effectiveness trials, should mediate the translation of systems medicine, or if instead individualized findings generated through "big data" approaches can be applied directly in clinical decision-making. Second, we will examine the case of the Riyadh Intensive Care Program Mortality Prediction Algorithm, pejoratively referred to as the "death computer," to demonstrate the ethical challenges that can arise when big-data-driven scoring systems are applied in clinical contexts. We argue that the uncritical use of predictive clinical algorithms, including those envisioned for systems medicine, challenge basic understandings of the doctor-patient relationship. Third, we will build on the recent discourse on secondary findings in genomics and imaging to draw attention to the important implications of secondary findings derived from the joint analysis of data from diverse sources, including data recorded by patients in an attempt to realize their "quantified self." This paper examines possible ethical challenges that are likely to be raised as systems medicine to be translated into clinical medicine. These include the epistemological challenges for clinical decision-making, the use of scoring systems optimized by big data techniques and the risk that incidental and secondary findings will significantly increase. While some ethical implications remain still hypothetical we should use the opportunity to prospectively identify challenges to avoid making foreseeable mistakes when systems medicine inevitably arrives in routine care.

PMID: 27209083 [PubMed - as supplied by publisher]

Mixed Phenotype Acute Leukemia (MPAL) Exhibits Frequent Mutations in DNMT3A and Activated Signaling Genes.

Exp Hematol. 2016 May 18;

Authors: Eckstein OS, Wang L, Punia JN, Kornblau SM, Andreeff M, Wheeler DA, Goodell MA, Rau RE

Abstract
Mixed phenotype acute leukemia (MPAL) is a heterogeneous group of poor-prognosis leukemias with immunophenotypic features of at least two cell lineages. The full spectrum of genetic mutations in this rare disease has not been elucidated, limiting our understanding of disease pathogenesis and our ability to devise targeted therapeutic strategies. We sought to define the mutational landscape of MPAL by performing whole exome sequencing on samples from 23 adult and pediatric MPAL patients. We identified frequent mutations of epigenetic modifiers, most notably mutations of DNMT3A in 33% of adult MPAL patients. Mutations of activated signaling pathways, tumor suppressors and transcription factors were also frequent. Importantly, many of the identified mutations are potentially therapeutically targetable with agents currently available or in various stages of clinical development. Therefore, the mutational spectrum we identified provides potential biological insights and is likely to have clinical relevance for patients with this poor-prognosis disease.

PMID: 27208809 [PubMed - as supplied by publisher]

Childhood epidermolysis bullosa acquisita during squaric acid dibutylester (SADBE) immunotherapy for alopecia areata.

Br J Dermatol. 2016 May 21;

Authors: Guerra L, Pacifico V, Calabresi V, De Luca N, Castiglia D, Angelo C, Zambruno G, Di Zenzo G

Abstract
Epidermolysis bullosa acquisita (EBA) is a rare acquired subepidermal blistering disease associated with autoantibodies against type VII collagen. Although EBA manifests more frequently in adults, it can occur in childhood. We describe a 6-year-old male who developed the inflammatory variant of EBA shortly after the initiation of immunotherapy with squaric acid dibutylester (SADBE) for scalp alopecia areata (AA). The disease rapidly regressed following SADBE discontinuation and starting of a combined steroid and dapsone therapy and never recurred after treatment tapering and withdrawal. The association of EBA with other autoimmune diseases is common, but EBA occurring during AA has not been previously described. The development of EBA during SADBE treatment is also noticeable: the clinical history and therapeutic response in our patient point to a possible role of SADBE in EBA onset. This article is protected by copyright. All rights reserved.

PMID: 27208509 [PubMed - as supplied by publisher]

Leptin substitution in patients with lipodystrophy: neural correlates for long-term success in the normalization of eating behavior.

Diabetes. 2016 May 10;

Authors: Schlögl H, Müller K, Horstmann A, Miehle K, Püschel J, Villringer A, Pleger B, Stumvoll M, Fasshauer M

Abstract
Lipodystrophy (LD) is a rare disease with a paucity of subcutaneous adipocytes and leptin-deficiency. Patients often develop severe diabetes mellitus and show disturbed eating behavior with reduced satiety that can be restored by substitution with the leptin analogue metreleptin. However, long-term effects of metreleptin on resting-state brain connectivity in treatment-naïve LD patients have not been assessed. In this study, resting-state functional magnetic resonance imaging (fMRI) scans and extensive behavioral testing assessing changes in hunger/satiety regulation were performed during the first 52 weeks of metreleptin treatment in nine LD patients. Resting-state connectivity significantly increased over the course of metreleptin treatment in three brain areas, i.e. hypothalamus, insula/superior temporal gyrus, and medial prefrontal cortex. Behavioral tests demonstrated that perceived hunger, importance of eating, eating frequencies, and liking ratings of food pictures significantly decreased during metreleptin therapy. Taken together, leptin substitution was accompanied by long-term changes of hedonic and homeostatic central nervous networks regulating eating behavior, as well as decreased hunger feelings and diminished incentive value of food. It needs to be assessed in future studies whether metreleptin treatment in LD restores physiological processes important for the development of satiety.

PMID: 27207511 [PubMed - as supplied by publisher]

Pharmaceutical expenditure on drugs for rare diseases in Canada: a historical (2007-13) and prospective (2014-18) MIDAS sales data analysis.

Orphanet J Rare Dis. 2016;11(1):68

Authors: Divino V, DeKoven M, Kleinrock M, Wade RL, Kim T, Kaura S

Abstract
BACKGROUND: Health Canada has defined rare diseases as life-threatening, seriously debilitating, or serious chronic conditions affecting a very small number of patients (~1 in 2,000 persons). An estimated 9 % of Canadians suffer from a rare disease. Drugs treating rare diseases (DRDs) are also known as orphan drugs. While Canada is currently developing an orphan drug framework, in the United States (US), the Orphan Drug Act (ODA) of 1983 established incentives for the development of orphan drugs. This study measured total annual expenditure of orphan drugs in Canada (2007-13) and estimated future (2014-18) orphan drug expenditure.
METHODS: Orphan drugs approved by the US Food and Drug Administration (FDA) in the US were used as a proxy for the orphan drug landscape in Canada. Branded, orphan drugs approved by the FDA between 1983 through 2013 were identified (N = 356 unique products). Only US orphan drugs with the same orphan indication(s) approved in Canada were included in the analysis. Adjustment via an indication factoring was applied to products with both orphan and non-orphan indications using available data sources to isolate orphan-indication sales. The IMS Health MIDAS database of audited biopharmaceutical sales was utilized to measure total orphan drug expenditure, calculated annually from 2007-2013 and evaluated as a proportion of total annual pharmaceutical drug expenditure (adjusted to 2014 CAD).
RESULTS: Between 2007 and 2013, expenditure was measured for a final N = 147 orphan drugs. Orphan drug expenditure totaled $610.2 million (M) in 2007 and $1,100.0 M in 2013, representing 3.3- 5.6 % of total Canadian pharmaceutical drug expenditure in 2007-2013, respectively. Future trend analysis suggests orphan drug expenditure will remain under 6 % of total expenditure in 2014-18.
CONCLUSIONS: While the number of available orphan drugs and associated expenditure increased over time, access remains an issue, and from the perspectives of society and equity, overall spending on orphan drugs is lower relative to the number of patients affected with an orphan disease in Canada. The overall budget impact of orphan drugs is small and fairly stable relative to total pharmaceutical expenditure. Concerns that growth in orphan drug expenditure may lead to unsustainable drug expenditure do not appear to be justified.

PMID: 27207271 [PubMed - as supplied by publisher]

A Decade of Change: Recent Developments in Pharmacotherapy of Hereditary Angioedema (HAE).

Clin Rev Allergy Immunol. 2016 May 20;

Authors: Bork K

Abstract
Hereditary angioedema (HAE) due to C1 esterase inhibitor (C1-INH) deficiency (HAE-C1-INH) is a rare but medically significant disease that can be associated with considerable morbidity and mortality. Research into the pathogenesis of HAE-C1-INH has expanded greatly in the last six decades and has led to new clinical trials with novel therapeutic agents and treatment strategies. Mechanisms of pharmacotherapy include (a) supplementing C1-INH, the missing serine-protease inhibitor in HAE; (b) inhibiting the activation of the contact system and the uncontrolled release of proteases in the kallikrein-kinin system, by blocking the production/function of its components; (c) inhibiting the fibrinolytic system by blocking the production/function of its components; and (d) inhibiting the function of bradykinin at the endothelial level. Strategies for managing HAE-C1-INH are aimed at treating acute attacks, or preventing attacks, through the use of prophylactic treatment. Available agents for treating acute attacks include plasma-derived C1-INH concentrates, a recombinant C1-INH, a bradykinin B2 receptor antagonist, and a plasma kallikrein inhibitor. Long-term prophylactic treatments include attenuated androgens, plasma-derived C1-INH concentrates, and anti-fibrinolytics. Plasma-derived C1-INH and a bradykinin B2 receptor antagonist are already approved for self-administration at home. The number of management options for HAE-C1-INH has increased considerably within the past decade, thus helping to alleviate the burden of this rare disease.

PMID: 27207174 [PubMed - as supplied by publisher]

Text mining, a race against time? An attempt to quantify possible variations in text corpora of medical publications throughout the years.

Comput Biol Med. 2016 Apr 20;73:173-185

Authors: Wagner M, Vicinus B, Muthra ST, Richards TA, Linder R, Frick VO, Groh A, Rubie C, Weichert F

Abstract
BACKGROUND: The continuous growth of medical sciences literature indicates the need for automated text analysis. Scientific writing which is neither unitary, transcending social situation nor defined by a timeless idea is subject to constant change as it develops in response to evolving knowledge, aims at different goals, and embodies different assumptions about nature and communication. The objective of this study was to evaluate whether publication dates should be considered when performing text mining.
METHODS: A search of PUBMED for combined references to chemokine identifiers and particular cancer related terms was conducted to detect changes over the past 36 years. Text analyses were performed using freeware available from the World Wide Web. TOEFL Scores of territories hosting institutional affiliations as well as various readability indices were investigated. Further assessment was conducted using Principal Component Analysis. Laboratory examination was performed to evaluate the quality of attempts to extract content from the examined linguistic features.
RESULTS: The PUBMED search yielded a total of 14,420 abstracts (3,190,219 words). The range of findings in laboratory experimentation were coherent with the variability of the results described in the analyzed body of literature. Increased concurrence of chemokine identifiers together with cancer related terms was found at the abstract and sentence level, whereas complexity of sentences remained fairly stable.
CONCLUSIONS: The findings of the present study indicate that concurrent references to chemokines and cancer increased over time whereas text complexity remained stable.

PMID: 27208610 [PubMed - as supplied by publisher]

Members of BTB gene family regulate negatively nitrate uptake and nitrogen use efficiency in Arabidopsis thaliana and Oryza sativa.

Plant Physiol. 2016 Apr 27;

Authors: Araus V, Vidal EA, Puelma T, Alamos S, Mieulet D, Guiderdoni E, Gutiérrez RA

Abstract
Development of crops with improved nitrogen use efficiency (NUE) is essential for sustainable agriculture. However, achieving this goal has proven difficult due to NUE is a complex trait encompassing physiological and developmental processes. We thought to tackle this problem by taking a systems biology approach to identify candidate target genes. First, we used a supervised machine-learning algorithm to predict a NUE gene network in Arabidopsis thaliana. Second, we identified BT2, a member of the Bric-a-Brac/Tramtrack/Broad (BTB) gene family, as the most central and connected gene in the NUE network. Third, we experimentally tested BT2 for a role in NUE. We found NUE decreased in plants overexpressing BT2 gene as compared to wild-type plants under limiting nitrate conditions. Additionally, NUE increased as compared to wild-type plants under low nitrate conditions in double mutant plants in bt2 and its closely related homolog bt1, indicating a functional redundancy of BT1 and BT2 for NUE. Expression of the nitrate transporter genes NRT2.1 and NRT2.4 increased in the bt1/bt2 double mutant as compared to wild-type plants, with a concomitant 65% increase in nitrate uptake under low nitrate conditions. Similar to Arabidopsis, we found that mutation of the BT1/BT2 ortholog gene in rice OsBT increased NUE by 20% as compared to wild-type rice plants under low nitrogen conditions. These results indicate BT gene family members act as conserved negative regulators of nitrate uptake genes and NUE in plants and highlight them as prime targets for future strategies to improve NUE in crops.

PMID: 27208309 [PubMed - as supplied by publisher]

It may Seem Inflammatory, but Some T Cells are Innately Healing to the Bone.

J Bone Miner Res. 2016 May 21;

Authors: Kalyan S

Abstract
Among the most significant developments to have taken place in osteology over the last few decades is an evolution from treating and viewing bone disorders primarily through an endocrine lens to instead seeing them as metabolic disorders that interface at the molecular and cellular level with the immune system. Osteoimmunology was officially born in response to accumulating evidence that the immune system is integrally involved in bone remodelling, but much of the early work focused on the role of conventional αβ T cells in driving bone loss. There is, however, emerging data indicating that innate lymphocytes, in particular γδ T cells, may in fact be important for bone regeneration. We first observed that bisphosphonate-associated osteonecrosis of the jaw (ONJ), a rare but serious adverse drug effect characterized by non-healing necrotic bone tissue of the mandible or maxilla, was linked to a deficiency in a subset of γδ T cells found in human peripheral blood. Patients who developed ONJ while on bisphosphonate therapy not only lacked the main subset of circulating γδ T cells, but they also all had underlying conditions that compromised their immune integrity. A number of recent studies have unraveled the role of γδ T cells (and lymphocytes sharing their characteristics) in bone regeneration - particularly for fracture healing. These findings seem to contradict the prevailing view of such "inflammatory" T cells as being bone degenerative rather than restorative. This viewpoint melds together the emerging evidence of these so-called inflammatory T cells in bone remodeling and healing - showing that they are not in fact "all bad to the bone". This article is protected by copyright. All rights reserved.

PMID: 27207251 [PubMed - as supplied by publisher]

Text mining, a race against time? An attempt to quantify possible variations in text corpora of medical publications throughout the years.

Comput Biol Med. 2016 Apr 20;73:173-185

Authors: Wagner M, Vicinus B, Muthra ST, Richards TA, Linder R, Frick VO, Groh A, Rubie C, Weichert F

Abstract
BACKGROUND: The continuous growth of medical sciences literature indicates the need for automated text analysis. Scientific writing which is neither unitary, transcending social situation nor defined by a timeless idea is subject to constant change as it develops in response to evolving knowledge, aims at different goals, and embodies different assumptions about nature and communication. The objective of this study was to evaluate whether publication dates should be considered when performing text mining.
METHODS: A search of PUBMED for combined references to chemokine identifiers and particular cancer related terms was conducted to detect changes over the past 36 years. Text analyses were performed using freeware available from the World Wide Web. TOEFL Scores of territories hosting institutional affiliations as well as various readability indices were investigated. Further assessment was conducted using Principal Component Analysis. Laboratory examination was performed to evaluate the quality of attempts to extract content from the examined linguistic features.
RESULTS: The PUBMED search yielded a total of 14,420 abstracts (3,190,219 words). The range of findings in laboratory experimentation were coherent with the variability of the results described in the analyzed body of literature. Increased concurrence of chemokine identifiers together with cancer related terms was found at the abstract and sentence level, whereas complexity of sentences remained fairly stable.
CONCLUSIONS: The findings of the present study indicate that concurrent references to chemokines and cancer increased over time whereas text complexity remained stable.

PMID: 27208610 [PubMed - as supplied by publisher]

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