bluuebunny/crossref_metadata_2025 huggingface dataset:
Arsenic Induces Members of the mmu-miR-466-669 Cluster Which Reduces NeuroD1 Expression
Authors: Liu Jui-Tung , Bain Lisa J
Published: November 2017

Chronic arsenic exposure can result in adverse development effects including decreased intellectual function, reduced birth weight, and altered locomotor activity. Previous in vitro studies have shown that arsenic inhibits stem cell differentiation. MicroRNAs (miRNAs) are small noncoding RNAs that regulate multiple cellular processes including embryonic development and cell differentiation. The purpose of this study was to examine whether altered miRNA expression was a mechanism by which arsenic inhibited cellular differentiation. The pluripotent P19 mouse embryonal carcinoma cells were exposed to 0 or 0.5 μM sodium arsenite for 9 days during cell differentiation, and changes in miRNA expression was analyzed using microarrays. We found that the expression of several miRNAs important in cellular differentiation, such as miR-9 and miR-199 were decreased by 1.9- and 1.6-fold, respectively, following arsenic exposure, while miR-92a, miR-291a, and miR-709 were increased by 3-, 3.7-, and 1.6-fold, respectively. The members of the miR-466-669 cluster and its host gene, Scm-like with 4 Mbt domains 2 (Sfmbt2), were significantly induced by arsenic from 1.5- to 4-fold in a time-dependent manner. Multiple miRNA target prediction programs revealed that several neurogenic transcription factors appear to be targets of the cluster. When consensus anti-miRNAs targeting the miR-466-669 cluster were transfected into P19 cells, arsenic-exposed cells were able to more effectively differentiate. The consensus anti-miRNAs appeared to rescue the inhibitory effects of arsenic on cell differentiation due to an increased expression of NeuroD1. Taken together, we conclude that arsenic induces the miR-466-669 cluster, and that this induction acts to inhibit cellular differentiation in part due to a repression of NeuroD1.
Grapevine red blotch virus: Absence in Swiss Vineyards and Analysis of Potential Detrimental Effect on Viticultural Performance
Authors: Reynard Jean-Sébastien , Brodard Justine , Dubuis Nathalie , Zufferey Vivian , Schumpp Olivier , Schaerer Santiago , Gugerli Paul
Published: November 2017

Grapevine red blotch virus (GRBV) is a recently described virus that infects grapevine. Little information is available on the possible occurrence and distribution outside North America. Therefore, we surveyed commercial vineyards from the three major grape-growing regions in Switzerland to determine the presence or absence of GRBV. In total, 3,062 vines were analyzed by polymerase chain reaction. None of the vines tested positive for GRBV, suggesting the absence of GRBV from Swiss vineyards. We also investigated whether GRBV was present in 653 grapevine accessions in the Agroscope grapevine virus collection at Nyon, including dominantly Swiss (457) but also international accessions. Only six referential accessions were infected by GRBV, all originating from the United States, whereas all others from 10 European and 8 non-European origins tested negative. High-throughput sequencing analysis of Zinfandel A2V13, in the collection since 1985, confirmed close similarity of GRBV isolate Z_A2V13 to American isolates according to genomes deposited in GenBank. Because the Zinfandel A2V13 reference was also maintained grafted on the leafroll virus indicator Vitis vinifera ‘Gamay’, we evaluated the effect of GRBV on viticultural performance over a 3-year period. Our results showed clear detrimental effects of GRBV on grapevine physiology (vine vigor, leaf chlorophyll content, and gas exchange) and fruit quality. These findings underscore the importance of implementation of GRBV testing worldwide in certification and quarantine programs to prevent the dissemination of this virus.
Thoracolumbar Intervertebral Disc Area Morphometry in Elderly Chinese Men and Women
Authors: Wáng Jùn-Qīng , Káplár Zoltán , Deng Min , Griffith James F. , Leung Jason C.S. , Kwok Anthony W.L. , Kwok Timothy , Leung Ping Chung , Wáng Yì Xiáng J.
Published: November 2017

Study Design.

A population-based radiographic study with longitudinal follow-up.

Objective.

To develop a quantitative index for lumbar disc space narrowing (DSN) evaluation in elderly subjects; to determine how DSN in the elderly is influenced by osteoporosis and sex.

Summary of Background Data.

There is paucity of research on quantitative classification of lumbar DSN based on disc areal morphometry.

Methods.

With the database of Osteoporotic Fractures in Men (Hong Kong) and Osteoporotic Fractures in Women (Hong Kong) Studies and those who attended the year-4 follow-up (n = 1519 for men and n = 1546 for women), data of 491 women and 592 men were randomly selected. The anterior, middle, and posterior heights; anteroposterior diameter; and area of intervertebral discs (T4T5 to L4L5) were measured on lateral radiographs. Disc area index for lumbar spine (DAIL, disc area divided by the mean of the sum of square of the adjacent upper and lower vertebrae mid-height anterior-posterior diameter) was developed and compared with semiquantitative DSN expert grading.

Results.

DAIL correlated with semiquantitative grading, with sensitivity and specificity varying from 87.3% to 96.8% for grade 1 DSN (<30% reduction in disc height), and 92.9% to 100% for grade 3 DSN (>60% reduction in disc height). The thoracolumbar disc area loss among men and women during 4-years’ follow-up period varied between 1.32% and 3.56%, and it was greater for women (mean: 2.44%) than for men (mean: 1.90%, P = 0.044). Majority of lumbar DSN progressions during 72 to 76 years old were progression from normal disc space to grade 1 DSN. Osteoporosis was associated with greater disc area decrease, both for thoracic and lumbar discs.

Conclusion.

Lumbar DSN can be quantified using DAIL. In elderly Chinese, intervertebral disc narrowing over a 4-year period was greater in women than men, and associated with the presence of osteoporosis.

Level of Evidence: 3
β-lactam Therapeutic Drug Management in the PICU*
Authors: Cies Jeffrey J. , Moore Wayne S. , Enache Adela , Chopra Arun
Published: November 2017

Objectives:

To determine whether contemporary β-lactam anti-infective dosing recommendations in critically ill children achieve concentrations associated with maximal anti-infective activity. The secondary objective was to describe the microbiological and clinical outcomes associated with β-lactam therapeutic drug management.

Design:

Electronic Medical Record Review.

Setting:

A 189-bed, freestanding children’s tertiary care teaching hospital in Philadelphia, PA.

Patients:

Patients admitted to the PICU from September 1, 2014, to May 31, 2017, with sepsis and those receiving extracorporal therapy with either extracorporeal membrane oxygenation or continuous renal replacement therapy that had routine β-lactam therapeutic drug management.

Interventions:

None.

Measurements and Main Results:

Eighty-two patients were in the total cohort and 23 patients in the infected cohort accounting for 248 samples for therapeutic drug management analysis. The median age was 1 year (range, 4 d to 18 yr) with a mean weight of 19.7 ± 22.3 kg (range, 2.7–116 kg). Twenty-three patients (28%) had growth of an identified pathogen from a normally sterile site. Seventy-eight of 82 patients (95%) had subtherapeutic anti-infective concentrations and did not attain the primary pharmacodynamic endpoint. All patients in the infected cohort achieved a microbiological response, and 22 of 23 (95.7%) had a positive clinical response.

Conclusions:

Overall, 95% of patients had subtherapeutic anti-infective concentrations and did not achieve the requisite pharmacodynamic exposure with current pediatric dosing recommendations. All patients achieved a microbiological response, and 95.7% achieved clinical response with active β-lactam therapeutic drug management. These data suggest β-lactam therapeutic drug management is a potentially valuable intervention to optimize anti-infective pharmacokinetics and the pharmacodynamic exposure. Further, these data also suggest the need for additional research in specific pediatric populations and assessing clinical outcomes associated with β-lactam therapeutic drug management in a larger cohort of pediatric patients.
The Role Of Extracellular Fluid in Biokinetic Modeling
Authors: Miller Guthrie , Klumpp John A. , Melo Dunstana , Poudel Deepesh
Published: November 2017

The pharmacokinetic equations of Pierson et al. describing the behavior of bromide in rat provide a general approach to the modeling of extracellular fluid (ECF). The movement of material into ECF spaces is rapid and is completely characterized by tissue volumes and vascular flow rates to and from a tissue, the volumes of the tissue, and the ECF associated with the tissue. Early-time measurements are needed to characterize ECF. Measurements of DTPA disappearance from plasma by Wedeking et al. are discussed as an example of such measurements. In any biokinetic model, the fastest transfer rates are not determinable with the usual datasets, and if determined empirically, these rates will have very large and highly correlated uncertainties, so particular values of these rates, even though the model fits the available data, are not significant. A pharmacokinetic front-end provides values for these fast rates. An example of such a front-end for a 200‐g rat is given.
Macro- and Microvascular Parameters After Toxic Shock Syndrome
Authors: Chen Katherine Y. H. , Li Ling-Jun , Wong Tien Y. , Cheung Carol Y. , Curtis Nigel , Cheung Michael , Burgner David P.
Published: November 2017

Whether individuals who had toxic shock syndrome in childhood have differences in macro- and retinal microvascular parameters indicative of increased cardiovascular risk is unknown. We found no evidence of adverse macrovascular changes in 22 toxic shock syndrome participants compared with 60 control participants. Microvascular comparisons showed a reduction in retinal total fractal dimension, which has been associated with cardiovascular risk factors in children.
Using Data Analytics as Evidentiary Support for Financial Outcome Success in Nurse-Led Population-Based Clinics
Authors: Polancich Shea , Williamson Jason , Selleck Cynthia S. , Talley Michele , Frank Jennifer , White-Williams Connie , Shirey Maria R.
Published: November 2017

Achieving the highest quality in health care requires organizations to develop clinical improvements that result in measurable outcomes for success. The purpose of this article is to demonstrate an example of clinical quality improvement through the use of data analytics to generate evidence for financial return on investment in two nurse-led, population-based clinics.
β-Blocker use is associated with a higher relapse risk of inflammatory bowel disease: a Dutch retrospective case–control study
Authors: Willemze Rose A. , Bakker Tinka , Pippias Maria , Ponsioen Cyriel Y. , de Jonge Wouter J.
Published: November 2017

Objective

Inflammatory bowel disease (IBD) is a multifactorial disease and many factors may influence the disease course, like the concomitant use of medication. An example thereof is the use of β-blockers, antagonizing β-adrenergic receptors. β-adrenergic receptor activation has potent anti-inflammatory effects on the immune system. We addressed whether an association exists between the use of beta-blockers and the course of IBD, defined by the risk of a disease relapse in patients with IBD.

Patients and methods

In this retrospective case–control study, we used a population-based cohort of patients with IBD. We identified colitis relapses using IBD medication prescriptions as a proxy. We calculated the number of relapses per 100 person-years and compared this between patients with IBD using β-blockers and patients with IBD not using β-blockers. We used Cox proportional hazards models with shared frailty to compare the relative relapse risk between both groups.

Results

A total of 250 patients with IBD were included, of which 30 patients used a β-blocker for at least 3 months. With the Cox proportional hazards model with shared frailty, adjusted for age and sex, we observed a 54% (hazard ratio: 1.54; 95% confidence interval: 1.05–2.25; P=0.03) higher risk of a relapse in the group of patients with IBD using β-blockers versus the group not using β-blockers.

Conclusion

Even in this limited cohort study, we show that patients with IBD using β-blockers have an increased relapse risk. Indeed, concomitant medication use seems to be a factor that can influence the course of IBD, and this should be acknowledged while making decisions about treatment of IBD and follow-up.
Inference With Difference-in-Differences With a Small Number of Groups
Authors: Rokicki Slawa , Cohen Jessica , Fink Günther , Salomon Joshua A. , Landrum Mary Beth
Published: November 2017

Background:

Difference-in-differences (DID) estimation has become increasingly popular as an approach to evaluate the effect of a group-level policy on individual-level outcomes. Several statistical methodologies have been proposed to correct for the within-group correlation of model errors resulting from the clustering of data. Little is known about how well these corrections perform with the often small number of groups observed in health research using longitudinal data.

Methods:

First, we review the most commonly used modeling solutions in DID estimation for panel data, including generalized estimating equations (GEE), permutation tests, clustered standard errors (CSE), wild cluster bootstrapping, and aggregation. Second, we compare the empirical coverage rates and power of these methods using a Monte Carlo simulation study in scenarios in which we vary the degree of error correlation, the group size balance, and the proportion of treated groups. Third, we provide an empirical example using the Survey of Health, Ageing, and Retirement in Europe.

Results:

When the number of groups is small, CSE are systematically biased downwards in scenarios when data are unbalanced or when there is a low proportion of treated groups. This can result in over-rejection of the null even when data are composed of up to 50 groups. Aggregation, permutation tests, bias-adjusted GEE, and wild cluster bootstrap produce coverage rates close to the nominal rate for almost all scenarios, though GEE may suffer from low power.

Conclusions:

In DID estimation with a small number of groups, analysis using aggregation, permutation tests, wild cluster bootstrap, or bias-adjusted GEE is recommended.
The Public Health Workforce Taxonomy: Revisions and Recommendations for Implementation
Authors: Beck Angela J. , Coronado Fátima , Boulton Matthew L. , Merrill Jacqueline A.
Published: November 2017

Public health workforce size and composition have been difficult to accurately determine because of the wide variety of methods used to define job title terms, occupational categories, and worker characteristics. In 2014, a preliminary consensus-based public health workforce taxonomy was published to standardize the manner in which workforce data are collected and analyzed by outlining uniform categories and terms. We summarize development of the taxonomy's 2017 iteration and provide guidelines for its implementation in public health workforce development efforts. To validate its utility, the 2014 taxonomy was pilot tested through quantitative and qualitative methods to determine whether further refinements were necessary. Pilot test findings were synthesized, themed by axis, and presented for review to an 11-member working group drawn from the community of experts in public health workforce development who refined the taxonomy content and structure through a consensus process. The 2017 public health workforce taxonomy consists of 287 specific classifications organized along 12 axes, intended for producing standardized descriptions of the public health workforce. The revised taxonomy provides enhanced clarity and inclusiveness for workforce characterization and will aid public health workforce researchers and workforce planning decision makers in gathering comparable, standardized data to accurately describe the public health workforce.
Calculating State-Level Estimates of Upcoming Older Adult Health Needs
Authors: Dumont Dora M. , Oh Junhie , Jackson Tracy L. , Cooper Tara
Published: November 2017

Objectives:

Census demographers have provided projections of the increased numbers of older adults in upcoming decades, but it is less clear whether they will also be any more or less healthy than current seniors. This is critical information for state planners, as the majority of older adults will need assistance with activities of daily living to remain in their homes. Previous longitudinal and cohort studies have yielded national estimates, but those more costly sources are generally beyond the resources of state public health agencies. We provide a more practicable model for assessing state-level changes in health-related quality of life (HRQOL) among middle-aged versus older adults as a guide to probable upcoming home- and community-based service needs.

Methods:

We used 2 sets of state Behavioral Risk Factor Surveillance System data 15 years apart to calculate and compare adjusted odds ratios of 8 poor HRQOL measures for middle-aged and older adults.

Results:

Compared with their peers only 15 years earlier, recent middle-aged adults had higher odds of poor outcomes across all HRQOL measures, whereas adults 65-74 years had higher odds of poor outcomes for far fewer of the measures. Among adults 75 years and older, odds were higher compared with 15 years ago for only 1 measure (multiple days of poor mental health).

Conclusions:

Compared with older adults, the health profile of middle-aged adults in this state appears to have worsened much more rapidly in the past 15 years, indicating that these adults will have many more health-related needs when they become seniors. While this model is less sophisticated than others using longitudinal data, it provides the state-level data that are often more compelling to state policy makers.
Handover Structure and Quality in the Acute Medical Assessment Unit: A Prospective Observational Study
Authors: van der Wulp Ineke , Poot Else P. , Nanayakkara Prabath W.B. , Loer Stephan A. , Wagner Cordula
Published: November 2017

Objectives

Inadequate patient handovers are associated with the occurrence of medical errors. The objective of the present study was to explore the structure and quality of handovers in the acute medical assessment unit.

Methods

A prospective observational study was conducted in an academic hospital in the Netherlands. Handover structure was observed by ordering handover information according to the elements of the Situation, Background, Assessment, Recommendation, and Read back (SBAR-R) handover tool. Handover quality was measured by means of a questionnaire, i.e., the rating tool for handover quality, and by assessing situation awareness of the degree to which professionals after a handover agreed on the complexity of the patient's care needs.

Results

A total of 71 handovers were observed. In most handovers, different elements of the SBAR-R were used frequently (median, 7.5 elements; range, 2.0–15.0). On the quality of handovers, 109 respondents (44.1%) completed the questionnaire. On a 0-to-100 scale, median scores on information transfer were 67.9 (interquartile range [IQR],17.9), 75.0 (IQR, 25.0) on shared understanding, and 75.0 (IQR, 16.7) on working atmosphere. Agreement in situation awareness was 70.0%.

Conclusions

Handovers in the acute medical assessment unit were poorly structured; however, the perceived quality of handovers was substantial. Implementing the SBAR-R may be an effective strategy to improve handover practice and situation awareness, although further study to its applicability in acute medical assessment units is necessary.
How Differences Between Manager and Clinician Perceptions of Safety Culture Impact Hospital Processes of Care
Authors: Richter Jason , Mazurenko Olena , Kazley Abby Swanson , Ford Eric W.
Published: November 2017

Objective

Evidenced-based processes of care improve patient outcomes, yet universal compliance is lacking, and perceptions of the quality of care are highly variable. The purpose of this study is to examine how differences in clinician and management perceptions on teamwork and communication relate to adherence to hospital processes of care.

Methods

Hospitals submitted identifiable data for the 2012 Hospital Survey on Patient Safety Culture and the Centers for Medicare and Medicaid Services’ Hospital Compare. The dependent variable was a composite, developed from the scores on adherence to acute myocardial infarction, heart failure, and pneumonia process of care measures. The primary independent variables reflected 4 safety culture domains: communication openness, feedback about errors, teamwork within units, and teamwork between units. We assigned each hospital into one of 4 groups based on agreement between managers and clinicians on each domain. Each hospital was categorized as “high” (above the median) or “low” (below) for clinicians and managers in communication and teamwork.

Results

We found a positive relationship between perceived teamwork and communication climate and processes of care measures. If managers and clinicians perceived the communication openness as high, the hospital was more likely to adhere with processes of care. Similarly, if clinicians perceived teamwork across units as high, the hospital was more likely to adhere to processes of care.

Conclusions

Manager and staff perceptions about teamwork and communications impact adherence to processes of care. Policies should recognize the importance of perceptions of both clinicians and managers on teamwork and communication and seek to improve organizational climate and practices. Clinician perceptions of teamwork across units are more closely linked to processes of care, so managers should be cognizant and try to improve their perceptions.
Barriers to Speaking Up About Patient Safety Concerns
Authors: Etchegaray Jason M. , Ottosen Madelene J. , Dancsak Theresa , Thomas Eric J.
Published: November 2017

Objectives

We sought to examine the association between willingness of health-care professionals to speak up about patient safety concerns and their perceptions of two types of organizational culture (ie, safety and teamwork) and understand whether nursing professionals and other health-care professionals reported the same barriers to speaking up about patient safety concerns.

Methods

As part of an annual safety culture survey in a large health-care system, we asked health-care professionals to tell us about the main barriers that prevent them from speaking up about patient safety concerns. Approximately 1341 respondents completed the anonymous, electronic survey.

Results

A little more than half (55%) of the participants mentioned leadership (fear of no change or retaliation) and personal (ie, fear of negative feedback or being wrong) barriers concerning why they would not speak up about patient safety concerns. The remaining participants (45%) indicated they would always speak up. These findings about barriers were consistent across nurses and other health-care professionals. Safety culture (SC) and teamwork culture (TC) scores were significantly more positive in those indicating they would always speak up (SC = 89%, TC = 89%) than in those who provided reasons for not speaking up (SC = 63%, TC = 64%) (t
1205 = 13.99, P < 0.05, and t
1217 = 13.61, P < 0.05, respectively).

Conclusions

Health-care professionals emphasized leadership and personal barriers as reasons for not speaking up. We also demonstrated an association between not speaking up and lower safety and teamwork culture scores.
Potential Visualization of Sorafenib-Induced Acidosis Using 11C-Acetate PET/CT in Patients With Hepatocellular Carcinoma
Authors: Kwon Seong Young , Kim Dong-Yeon , Min Jung-Joon , Bae Woo Kyun
Published: November 2017

11C-acetate uptake could be increased in physiologic or inflammatory conditions without evidence of cancer. We report a hepatocellular carcinoma patient with sorafenib-induced metabolic acidosis, who showed increased hepatic uptake of 11C-acetate. 11C-acetate PET/CT might be a potentially useful surrogate marker to monitor these adverse effects via the changes in 11C-acetate uptake patterns from before to after drug withdrawal.
Secretome Conveys the Protective Effects of ASCs: Therapeutic Potential Following Hemorrhagic Shock?
Authors: Ashmwe Mostafa , Penzenstadler Carina , Bahrami Arian , Klotz Anton , Jafarmadar Mohammad , Banerjee Asmita , Wolbank Susanne , Redl Heinz , Bahrami Soheyl
Published: November 2017

Objectives:

We tested whether resuscitation supplemented with rat adipose-derived stem cells (ASCs) or secretome (conditioned media) of ASCs can ameliorate inflammation, cell/organ injury, and/or improve outcome after hemorrhagic traumatic shock (HTS).

Interventions:

Rats were subjected to HTS and a resuscitation protocol that mimics prehospital restrictive reperfusion followed by an adequate reperfusion phase. Twenty minutes into the restrictive reperfusion, animals received an intravenous bolus of 2 × 106 cells (ASC group) or the secretome produced by 2 × 106 ASCs/24 h (ASC-Secretome group). Controls received the vehicle (Vehicle group). All rats were observed for 28-day survival.

Measurements and Main Results:

HTS-induced inflammation represented by IL-6 was inhibited in the ASC (80%, P < 0.001) and in ASC-Secretome (59%, P < 0.01) group at 48 h compared with Vehicle group. At 24 h, HTS-induced liver injury reflected in plasma alanine aminotransferase was ameliorated by 36% (P < 0.001) in both the ASC and ASC-Secretome groups when compared with the Vehicle. There was no effect on kidney function and/or general cell injury markers. HTS induced a moderate 28-day mortality (18%) that was prevented (P = 0.08) in the ASC but not in the ASC-Secretome group (12%).

Conclusions:

Our data suggest that the ASC-secretome supplemented resuscitation following HTS, in the absence of the stem cells, exerts anti-inflammatory and liver protective effects. Given its ease of preparation, storage, availability, and application (in contrast to the stem cells) we believe that the cell-free secretome has a better therapeutic potential in the early phase of an acute hemorrhagic shock scenario.
Atf3 links loss of epithelial polarity to defects in cell differentiation and cytoarchitecture
Authors: Donohoe Colin D. , Csordás Gábor , Correia Andreia , Jindra Marek , Klein Corinna , Habermann Bianca , Uhlirova Mirka
Published: November 2017

Interplay between apicobasal cell polarity modules and the cytoskeleton is critical for differentiation and integrity of epithelia. However, this coordination is poorly understood at the level of gene regulation by transcription factors. Here, we establish theDrosophila activating transcription factor 3(atf3) as a cell polarity response gene acting downstream of the membrane-associated Scribble polarity complex. Loss of the tumor suppressors Scribble or Dlg1 inducesatf3expression via aPKC but independent of Jun-N-terminal kinase (JNK) signaling. Strikingly, removal of Atf3 from Dlg1 deficient cells restores polarized cytoarchitecture, levels and distribution of endosomal trafficking machinery, and differentiation. Conversely, excess Atf3 alters microtubule network, vesicular trafficking and the partition of polarity proteins along the apicobasal axis. Genomic and genetic approaches implicate Atf3 as a regulator of cytoskeleton organization and function, and identifyLamin Cas one of itsbona fidetarget genes. By affecting structural features and cell morphology, Atf3 functions in a manner distinct from other transcription factors operating downstream of disrupted cell polarity.

Author summary

Epithelial cells form sheets and line both the outside and inside of our body. Their proper development and function require the asymmetric distribution of cellular components from the top to the bottom, known as apicobasal polarization. As loss of polarity hallmarks a majority of cancers in humans understanding how epithelia respond to a collapse of the apicobasal axis is of great interest. Here, we show that in the fruit flyDrosophila melanogaster, the breakdown of epithelial polarity engages Activating transcription factor 3 (Atf3), a protein that directly binds the DNA and regulates gene expression. We demonstrate that many of the pathological consequences of disturbed polarity require Atf3, as its loss in this context results in normalization of cellular architecture, vesicle trafficking and differentiation. Using unbiased genome-wide approaches we identify the genetic program controlled by Atf3 and experimentally verify select candidates. Given the evolutionary conservation of Atf3 between flies and man, we believe that our findings in theDrosophilamodel will contribute to a better understanding of diseases stemming from compromised epithelial polarity.
A novel multi SNP based method for the identification of subspecies and associated lineages and sub-lineages of theMycobacterium tuberculosiscomplex by whole genome sequencing
Authors: Lipworth S , Jajou R , de Neeling A , Bradley P , van der Hoek W , Maphalala G , Bonnet M , Sanchez-Padilla E , Diel R , Niemann S , Iqbal Z , Smith G , Peto T , Crook D , Walker TM , van Soolingen D
Published: November 2017

The clinical phenotype of zoonotic tuberculosis, its contribution to the global burden of disease and prevalence are poorly understood and probably underestimated. This is partly because currently available laboratory andin silicotools have not been calibrated to accurately identify all subspecies of theMycobacterium tuberculosiscomplex (Mtbc). We here present the first such tool, SNPs to Identify TB (‘SNP-IT’). Applying SNP-IT to a collection of clinical genomes from a UK reference laboratory, we demonstrate an unexpectedly high number ofM. orygisisolates. These are seen at a similar rate toM. boviswhich attracts much health protection resource and yetM. orygiscases have not been previously described in the UK. From an international perspective it is possible thatM. orygisis an underestimated zoonosis. As whole genome sequencing is increasingly integrated into the clinical setting, accurate subspecies identification with SNP-IT will allow the clinical phenotype, host range and transmission mechanisms of subspecies of theMtbcto be studied in greater detail.
APR-246 reactivates mutant p53 by targeting cysteines 124 and 277
Authors: Zhang Qiang , Bykov Vladimir J.N. , Wiman Klas G. , Zawacka-Pankau Joanna
Published: November 2017

The TP53 tumor suppressor gene is frequently inactivated in human tumors by missense mutations in the DNA binding domain. TP53 mutations lead to protein unfolding, decreased thermostability and loss of DNA binding and transcription factor function. Pharmacological targeting of mutant p53 to restore its tumor suppressor function is a promising strategy for cancer therapy. The mutant p53 reactivating compound APR-246 (PRIMA-1Met) has been successfully tested in a phase I/IIa clinical trial. APR-246 is converted to the reactive electrophile methylene quinuclidinone (MQ), which binds covalently to p53 core domain. We identified cysteine 277 as a prime binding target for MQ in p53. Cys277 is also essential for MQ-mediated thermostabilization of wild-type, R175H and R273H mutant p53, while both Cys124 and Cys277 are required for APR-246-mediated functional restoration of R175H mutant p53 in living tumor cells. These findings may open opportunities for rational design of novel mutant p53-targeting compounds.
Boosting Gene Expression Clustering with System-Wide Biological Information: A Robust Autoencoder Approach
Authors: Cui Hongzhu , Zhou Chong , Dai Xinyu , Liang Yuting , Paffenroth Randy , Korkin Dmitry
Published: November 2017

Gene expression analysis provides genome-wide insights into the transcriptional activity of a cell. One of the first computational steps in exploration and analysis of the gene expression data is clustering. With a number of standard clustering methods routinely used, most of the methods do not take prior biological information into account. In this paper, we propose a new approach for gene expression clustering analysis. The approach benefits from a new deep learning architecture, Robust Autoencoder, which provides a more accurate high-level representation of the feature sets, and from incorporating prior biological information into the clustering process. We tested our approach on two distinct gene expression datasets and compared the performance with two widely used clustering methods, hierarchical clustering and k-means, as well as with a recent deep learning clustering approach. As a result, our approach outperformed all other clustering methods on the labeled yeast gene expression dataset. Furthermore we showed that it is better in identifying the functionally common clusters than k-means on the unlabeled human gene expression dataset. The results demonstrate that our new deep learning architecture could generalize well the specific properties of gene expression profiles. Furthermore, the results confirm our hypothesis that the prior biological network knowledge could be helpful in the gene expression clustering task.
TaxAss: Leveraging a Custom Freshwater Database Achieves Fine-Scale Taxonomic Resolution
Authors: Rohwer Robin R. , Hamilton Joshua J. , Newton Ryan J. , McMahon Katherine D.
Published: November 2017

Taxonomy assignment of freshwater microbial communities is limited by the minimally curated phylogenies used for large taxonomy databases. Here we introduce TaxAss, a taxonomy assignment workflow that classifies 16S rRNA gene amplicon data using two taxonomy reference databases: a large comprehensive database and a small ecosystem-specific database rigorously curated by scientists within a field. We applied TaxAss to five different freshwater datasets using the comprehensive Silva database and the freshwater-specific FreshTrain database. TaxAss increased the percent of the dataset classified compared to using only Silva, especially at fine-resolution family-species taxa levels, while across the freshwater test-datasets classifications increased by as much as 11-40 percent of total reads. A similar increase in classifications was not observed in a control mouse gut dataset, which was not expected to contain freshwater bacteria. TaxAss also maintained taxonomic richness compared to using only the FreshTrain across all taxa-levels from phylum to species. Without TaxAss, most organisms not represented in the FreshTrain were unclassified, but at fine taxa levels incorrect classifications became significant. We validated TaxAss using simulated amplicon data with known taxonomy and found that 96-99% of test sequences were correctly classified at fine resolution. TaxAss splits a dataset’s sequences into two groups based on their percent identity to reference sequences in the ecosystem-specific database. Sequences with high similarity to sequences in the ecosystem-specific database are classified using that database, and the others are classified using the comprehensive database. TaxAss is free and open source, and available at www.github.com/McMahonLab/TaxAss.

IMPORTANCE

Microbial communities drive ecosystem processes, but microbial community composition analyses using 16S rRNA gene amplicon datasets are limited by the lack of fine-resolution taxonomy classifications. Coarse taxonomic groupings at phylum, class, and order level lump ecologically distinct organisms together. To avoid this, many researchers define operational taxonomic units (OTUs) based on clustered sequences, sequence variants, or unique sequences. These fine-resolution groupings are more ecologically relevant, but OTU definitions are dataset-dependent and cannot be compared between datasets. Microbial ecologists studying freshwater have curated a small, ecosystem-specific taxonomy database to provide consistent and up-to-date terminology. We created TaxAss, a workflow that leverages this database to assign taxonomy. We found that TaxAss improves fine-resolution taxonomic classifications (family, genus and species). Fine taxonomic groupings are more ecologically relevant, so they provide an alternative to OTU-based analyses that is consistent and comparable between datasets.
Imaging-Genomics Study Of Head-Neck Squamous Cell Carcinoma: Associations Between Radiomic Phenotypes And Genomic Mechanisms Via Integration Of TCGA And TCIA
Authors: Zhu Yitan , Mohamed Abdallah S.R. , Lai Stephen Y , Yang Shengjie , Kanwar Aasheesh , Wei Lin , Kamal Mona , Sengupta Subhajit , Elhalawani Hesham , Skinner Heath , Mackin Dennis S , Shiao Jay , Messer Jay , Wong Andrew , Ding Yao , Zhang Joy , Court Laurence , Ji Yuan , Fuller Clifton D , Anderson M.D.
Published: November 2017

Purpose

Recent data suggest that imaging radiomics features for a tumor could predict important genomic biomarkers. Understanding the relationship between radiomic and genomic features is important for basic cancer research and future patient care. For Head and Neck Squamous Cell Carcinoma (HNSCC), we perform a comprehensive study to discover the imaging-genomics associations and explore the potential of predicting tumor genomic alternations using radiomic features.

Methods

Our retrospective study integrates whole-genome multi-omics data from The Cancer Genome Atlas (TCGA) with matched computed tomography imaging data from The Cancer Imaging Archive (TCIA) for the same set of 126 HNSCC patients. Linear regression analysis and gene set enrichment analysis are used to identify statistically significant associations between radiomic imaging features and genomic features. Random forest classifier is used to predict two key HNSCC molecular biomarkers, the status of human papilloma virus (HPV) and disruptive TP53 mutation, based on radiomic features.

Results

Wide-spread and statistically significant associations are discovered between genomic features (including miRNA expressions, protein expressions, somatic mutations, and transcriptional activities, copy number variations, and promoter region DNA methylation changes of pathways) and radiomic features characterizing the size, shape, and texture of tumor. Prediction of HPV and TP53 mutation status using radiomic features achieves an area under the receiver operating characteristics curve (AUC) of 0.71 and 0.641, respectively.

Conclusion

Our analysis suggests that radiomic features are associated with genomic characteristics in HNSCC and provides justification for continued development of radiomics as biomarkers for relevant genomic alterations in HNSCC.
Subtle alteration in microRNA dynamics accounts for differential nature of cellular proliferation
Authors: Sengupta Dola , Govindaraj Vinodhini , Kar Sandip
Published: November 2017

In the G1 phase of the mammalian cell cycle, a bi-stable steady state dynamics of the transcription factor E2F ensures that only a certain threshold level of the growth factor can induce a high expression level (on state) of E2F to initiate either normal or abnormal cellular proliferation or even apoptosis. A group of microRNA’s known as the mir-17-92 cluster, which specifically inhibits E2F, can simultaneously influence the threshold level of growth factor required for E2F activation, and the corresponding expression level of E2F in the on state. However, mir-17-92 cluster can function as either oncogene or tumor suppressor in a cell-type specific manner for reasons that still remain illusive. Here we put forward a deterministic mathematical model for Myc/E2F/mir-17-92 network that demonstrates how the experimentally observed mir-17-92 mediated differential nature of the cellular proliferation can be reconciled by having conflicting steady state dynamics of E2F for different cell types. While a 2-D bifurcation study of the model rationalizes the reason behind the contrasting E2F dynamics, an intuitive sensitivity analysis of the model parameters predicts that by exclusively altering the mir-17-92 related part of the network, it is possible to experimentally manipulate the cellular proliferation in a cell-type specific fashion for therapeutic intervention.
Kombucha as a model system for multispecies microbial cooperation: theoretical promise, methodological challenges and new solutions ‘in solution’
Authors: May Alexander Niall , Medina James , Alcock Joe , Maley Carlo , Aktipis Athena
Published: November 2017

Kombucha is a sweetened tea fermented by bacteria and yeast into a carbonated, acidic drink, producing a surface biofilm pellicle (colloquially called a SCOBY) during the process. Typically, liquid and a biofilm pellicle from a previously fermented culture is used as a starter for new cultures; however, there is no standard protocol for growing kombucha in the laboratory. In order to establish a standard protocol with low variability between replicates, we tested whether we could begin a kombucha culture with only well-mixed liquid stock. We found that viable kombucha cultures can be grown from low percentages of initial inoculum stock liquid, that new pellicles can form from liquid alone (with no ‘starter’ pellicle), and that the variation in the pellicle characteristics is lower when only a liquid starter is used (p = 0.0004). We also found that blending the pellicle before including it significantly reduces the variation among replicates, though the final pellicle was abnormal. We conclude that growing kombucha from only liquid stock is viable and provides a greater degree of experimental control and reproducibility compared to alternatives. Standardizing methodologies for studying kombucha in the lab can facilitate the use of this system for exploring questions about the evolutionary, ecological and cooperative/competitive dynamics within this multi-species system including resource transfers, functional dependence, genetic divergence, collective defense, and ecological succession. A better understanding of kombucha and other fermented foods may eventually allow us to leverage their pathogen inhibitory properties to develop novel antibiotics and bacteriocins.
Causal Mapping of Emotion Networks in the Human Brain: Framework and Preliminary Findings
Authors: Dubois Julien , Oya Hiroyuki , Tyszka J. Michael , Howard Matthew , Eberhardt Frederick , Adolphs Ralph
Published: November 2017

Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI.
Deep learning of the regulatory grammar of yeast 5′ untranslated regions from 500,000 random sequences
Authors: Cuperus Josh T. , Groves Benjamin , Kuchina Anna , Rosenberg Alexander B. , Jojic Nebojsa , Fields Stanley , Seelig Georg
Published: November 2017

Our ability to predict protein expression from DNA sequence alone remains poor, reflecting our limited understanding of cis-regulatory grammar and hampering the design of engineered genes for synthetic biology applications. Here, we generate a model that predicts the protein expression of the 5′ untranslated region (UTR) of mRNAs in the yeast Saccharomyces cerevisiae. We constructed a library of half a million 50-nucleotide-long random 5′ UTRs and assayed their activity in a massively parallel growth selection experiment. The resulting data allow us to quantify the impact on protein expression of Kozak sequence composition, upstream open reading frames (uORFs), and secondary structure. We trained a convolutional neural network (CNN) on the random library and showed that it performs well at predicting the protein expression of both a held-out set of the random 5′ UTRs as well as native S. cerevisiae 5′ UTRs. The model additionally was used to computationally evolve highly active 5′ UTRs. We confirmed experimentally that the great majority of the evolved sequences led to higher protein expression rates than the starting sequences, demonstrating the predictive power of this model.
Fixed assets management of Larsen & Toubro: stability vs stagnancy
Authors: Goel Sandeep
Published: November 2017

Subject area

Accounting and Finance.

Study level/applicability

Postgraduate/graduate.

Case overview

This paper aims to analyse the fixed assets management of Larsen & Toubro Ltd (L&T), a leading Indian construction company for sufficiency and efficiency, and explore its future growth prospects in relation to its capital investments. It also investigates whether the global crisis in 2008 had any impact on the development plans of the company for future orientation as the global recession affected companies in various sectors worldwide. It specifically aims to find out whether L&T was in a better position to face the situation in the industry.

Expected learning outcomes

Expected learning outcomes are as follows: to learn and apply the concept of fixed assets management in a business organization; to evaluate the impact of fixed assets management on the profitability of the company; to appreciate the importance of fixed assets management efficiency in a business organization; and to illustrate the use of financial crisis on the growth prospects of a business.

Supplementary materials

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

Subject code

CSS 1: Accounting and finance.
Pepsodent: marketing strategy at the bottom of the pyramid
Authors: Tocquer Gerard
Published: November 2017

Subject area

Marketing in an emerging market.

Study level/applicability

The case is aimed at MBA students in a marketing strategy class on marketing at the bottom of the pyramid or on branding.

Case overview

A young brand manager faced the challenge to increase drastically a brand market share to 8 per cent in 2015 in a context of a new emerging market with large number of consumers living with no more than US$1.25 a day.

Expected learning outcomes

Expected learning outcomes are as follows: to familiarize students with emerging markets characteristics; to illustrate the challenges of marketing a brand to local consumers with limited financial resources to craft a marketing strategy for Pepsodent with a clear positioning, allowing the Pepsodent brand to differentiate itself and to leverage its brand equity; and to develop a marketing-mix aligned with the brand positioning.

Supplementary Materials

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

Subject code

CSS 8: Marketing.