bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evolving Models and Ongoing Challenges for HIV Preexposure Prophylaxis Implementation in the United States
Authors: Mayer Kenneth H. , Chan Philip A. , R. Patel Rupa , Flash Charlene A. , Krakower Douglas S. 
Published: October 2017

Background:
The use of preexposure prophylaxis (PrEP) for HIV prevention was approved by the Food and Drug Administration in 2012, but delivery to at-risk persons has lagged. This critical review analyzes the current state of PrEP implementation in the United States, by reviewing barriers and innovative solutions to enhance PrEP access and uptake.

Setting:
Clinical care settings, public health programs, and community-based organizations (CBOs).

Methods:
Critical review of recent peer-reviewed literature.

Results:
More than 100 papers were reviewed. PrEP is currently provided in diverse settings. Care models include sexually transmitted disease clinics, community health centers, CBOs, pharmacies, and private primary care providers (PCPs). Sexually transmitted disease clinics have staff trained in sexual health counseling and are linked to public health programs (eg, partner notification services), whereas PCPs and community health centers may be less comfortable counseling and feel time-constrained in managing PrEP. However, PCPs may be ideal PrEP providers, given their long-term relationships with patients, integrating PrEP into routine care. Collaborations with CBOs can expand PrEP care through adherence support and insurance navigation. Pharmacies can deliver PrEP, given their experience with medication dispensing and counseling, and may be more accessible for some patients, but to address other health concerns, liaisons with PCPs may be needed.

Conclusions:
PrEP implementation in the United States is moving forward with the development of diverse models of delivery. Optimal scale-up will require learning about the best features of each model and providing choices to consumers that enhance engagement and uptake.
Brief Report: Declining Baseline Viremia and Escalating Discordant HIV-1 Confirmatory Results Within South Africa's Early Infant Diagnosis Program, 2010–2016
Authors: Mazanderani Ahmad Haeri , Moyo Faith , Kufa Tendesayi , Sherman Gayle G. 
Published: October 2017

Objective:
To describe baseline HIV-1 RNA viral load (VL) trends within South Africa's Early Infant Diagnosis program 2010–2016, with reference to prevention of mother-to-child transmission guidelines.

Methods:
HIV-1 total nucleic acid polymerase chain reaction (TNA PCR) and RNA VL data from 2010 to 2016 were extracted from the South African National Health Laboratory Service's central data repository. Infants with a positive TNA PCR and subsequent baseline RNA VL taken at age <7 months were included. Descriptive statistics were performed for quantified and lower-than-quantification limit (LQL) results per annum and age in months. Trend analyses were performed using log likelihood ratio tests. Multivariable linear regression was used to model the relationship between RNA VL and predictor variables, whereas logistic regression was used to identify predictors associated with LQL RNA VL results.

Results:
Among 13,606 infants with a positive HIV-1 TNA PCR linked to a baseline RNA VL, median age of first PCR was 57 days and VL was 98 days. Thirteen thousand one hundred ninety-five (97.0%) infants had a quantified VL and 411 (3.0%) had an LQL result. A significant decline in median VL was observed between 2010 and 2016, from 6.3 log10 (interquartile range: 5.6–6.8) to 5.6 log10 (interquartile range: 4.2–6.5) RNA copies per milliliter, after controlling for age (P < 0.001), with younger age associated with lower VL (P < 0.001). The proportion of infants with a baseline VL <4 Log10 RNA copies per milliliter increased from 5.4% to 21.8%. Subsequent to prevention of mother-to-child transmission Option B implementation in 2013, the proportion of infants with an LQL baseline VL increased from 1.5% to 6.1% (P < 0.001).

Conclusions:
Between 2010 and 2016, a significant decline in baseline viremia within South Africa's Early Infant Diagnosis program was observed, with loss of detectability among some HIV-infected infants.
Chromatin histone modifications and rigidity affect nuclear morphology independent of lamins
Authors: Stephens Andrew D. , Liu Patrick Z. , Banigan Edward J. , Almassalha Luay M. , Backman Vadim , Adam Stephen A. , Goldman Robert D. , Marko John F. 
Published: October 2017

AbstractNuclear shape and architecture influence gene localization, mechanotransduction, transcription, and cell function. Abnormal nuclear morphology and protrusions termed “blebs” are diagnostic markers for many human afflictions including heart disease, aging, progeria, and cancer. Nuclear blebs are associated with both lamin and chromatin alterations. A number of prior studies suggest that lamins dictate nuclear morphology, but the contributions of altered chromatin compaction remain unclear. We show that chromatin histone modification state dictates nuclear rigidity, and modulating it is sufficient to both induce and suppress nuclear blebs. Treatment of mammalian cells with histone deacetylase inhibitors to increase euchromatin or histone methyltransferase inhibitors to decrease heterochromatin results in a softer nucleus and nuclear blebbing, without perturbing lamins. Oppositely, treatment with histone demethylase inhibitors increases heterochromatin and chromatin nuclear rigidity, which results in reduced nuclear blebbing in lamin B1 null nuclei. Notably, increased heterochromatin also rescues nuclear morphology in a model cell line for the accelerated aging disease Hutchinson-Gilford progeria syndrome caused by mutant lamin A, as well as cells from patients with the disease. Thus, chromatin histone modification state is a major determinant of nuclear blebbing and morphology via its contribution to nuclear rigidity.
Identification and prioritisation of causal variants in human genetic disorders from exome or whole genome sequencing data
Authors: Paramasivam Nagarajan , Granzow Martin , Evers Christina , Hinderhofer Katrin , Wiemann Stefan , Bartram Claus R. , Eils Roland , Schlesner Matthias 
Published: October 2017

AbstractWith genome sequencing entering the clinics as diagnostic tool to study genetic disorders, there is an increasing need for bioinformatics solutions that enable precise causal variant identification in a timely manner.BackgroundWorkflows for the identification of candidate disease-causing variants perform usually the following tasks: i) identification of variants; ii) filtering of variants to remove polymorphisms and technical artifacts; and iii) prioritization of the remaining variants to provide a small set of candidates for further analysis.MethodsHere, we present a pipeline designed to identify variants and prioritize the variants and genes from trio sequencing or pedigree-based sequencing data into different tiers.ResultsWe show how this pipeline was applied in a study of patients with neurodevelopmental disorders of unknown cause, where it helped to identify the causal variants in more than 35% of the cases.ConclusionsClassification and prioritization of variants into different tiers helps to select a small set of variants for downstream analysis.
Targeted deletion of Nmnat1 in mouse retina leads to early severe retinal dystrophy
Authors: Wang Xiaolin , Fang Yu , Liao Rongsheng , Wang Tao 
Published: October 2017

AbstractMutations in NMNAT1 can lead to a very severe type of retinal dystrophy, Leber congenital amaurosis, in human patients, characterized by infantile-onset or congenital retinal dystrophy and childhood blindness. The loss-of-function mouse models of Nmnat1 have not been well-established, since the complete knock-out (KO) of Nmnat1 in mice results in embryonic lethality. Here, we generated retina-specific KO by using the Crxpromotor-driving Cre combined with the flox allele. By a panel of histological and functional analyses, we found that Nmnat1 conditional KO (cKO) mice have early severe retinal dystrophy. Specifically, the photoreceptors of Nmnat1 cKO mice are almost diminished and the retinal functions also become completely abolished. Our results established a loss-of-function model for Nmnat1 in mice, which will be useful for studying the detailed functions of NMNAT1 in the retina.
A 20S proteasome receptor for degradation of intrinsically disordered proteins
Authors: Biran Assaf , Myers Nadav , Adler Julia , Broennimann Karin , Reuven Nina , Shaul Yosef 
Published: October 2017

AbstractDegradation of intrinsically disordered proteins (IDPs) by the 20S proteasome, unlike ubiquitin-dependent 26S proteasomal degradation, does not require proteasomal targeting by polyubiquitin. However, how these proteins are recognized by the proteasome was unknown. We report here on a mechanism of 20S proteasome targeting. Analysis of protein interactome datasets revealed that the proteasome subunit PSMA3 interacts with many IDPs. By employing in vivo and cell-free experiments we demonstrated that the PSMA3 C-terminus binds p21, c-Fos and p53, all IDPs and 20S proteasome substrates. A 69 amino-acids long fragment is autonomously functional in interacting with IDP substrates. Remarkably, this fragment in isolation blocks the degradation of a large number of IDPs in vitro and increases the half-life of proteins in vivo. We propose a model whereby the PSMA3 C-terminal region plays a role of substrate receptor in the process of proteasomal degradation of many IDPs.
Listeria monocytogenesvirulence factors are secreted in biologically active Extracellular Vesicles
Authors: Coelho Carolina , Brown Lisa , Maryam Maria , Burnet Meagan C. , Kyle Jennifer E. , Heyman Heino M. , Vij Raghav , Ramirez Jasmine , Prados-Rosales Rafael , Lauvau Gregoire , Nakayasu Ernesto S. , Brady Nathan Ryan , Hamacher-Brady Anne , Coppens Isabelle , Casadevall Arturo 
Published: October 2017

ABSTRACTOuter membrane vesicles produced by Gram-negative bacteria have been studied for half a century but the possibility that Gram-positive bacteria secreted extracellular vesicles (EVs) was not pursued due to the assumption that the thick peptidoglycan cell wall would prevent their release to the environment. However, following discovery in fungi, which also have cell walls, EVs have now been described for a variety of Gram-positive bacteria. EVs purified from Gram-positive bacteriaare implicated in virulence, toxin release and transference to host cells, eliciting immune responses, and spread of antibiotic resistance.Listeria monocytogenesis a Gram-positive bacterium that is the etiological agent of listeriosis. Here we report thatL. monocytogenesproduces EVs with diameter ranging from 20-200 nm, containing the pore-forming toxin listeriolysin O(LLO) and phosphatidylinositol-specific phospholipase C (PI-PLC). Using simultaneousmetabolite,protein, andlipidextraction (MPLEx) multi-omics we characterized protein, lipid and metabolite composition of bacterial cells and secreted EVs and found that EVs carry the majority of listerial virulence proteins. Cell-free EV preparations were toxic to the murine macrophage cell line J774.16, in a LLO-dependent manner, evidencing EV biological activity. The deletion ofplcAincreased EV toxicity, suggesting PI-PLC can restrain LLO activity. Using immunogold electron microscopy we detect LLO localization at several organelles within infected human epithelial cells and with high-resolution fluorescence imaging we show that dynamic lipid structures are released fromL. monocytogenesthat colocalize with LLO during infection. Our findings demonstrate thatL. monocytogenesutilize EVs for toxin release and implicate these structures in mammalian cytotoxicity.
Contextual Regression: An Accurate and Conveniently Interpretable Nonlinear Model for Mining Discovery from Scientific Data
Authors: Liu Chengyu , Wang Wei 
Published: October 2017

AbstractMachine learning algorithms such as linear regression, SVM and neural network have played an increasingly important role in the process of scientific discovery. However, none of them is both interpretable and accurate on nonlinear datasets. Here we present contextual regression, a method that joins these two desirable properties together using a hybrid architecture of neural network embedding and dot product layer. We demonstrate its high prediction accuracy and sensitivity through the task of predictive feature selection on a simulated dataset and the application of predicting open chromatin sites in the human genome. On the simulated data, our method achieved high fidelity recovery of feature contributions under random noise levels up to ±200%. On the open chromatin dataset, the application of our method not only outperformed the state of the art method in terms of accuracy, but also unveiled two previously unfound open chromatin related histone marks. Our method fills in the gap of accurate and interpretable nonlinear modeling in scientific data mining tasks.
Active deep learning reduces annotation burden in automatic cell segmentation
Authors: Chowdhury Aritra , Biswas Sujoy K. , Bianco Simone 
Published: October 2017

ABSTRACTThe relationship between cellular architecture and cellular state and function is apparent, but not yet completely understood. Precise characterization of cellular state is important in many fields, from pathology to synthetic biology. High-content high-throughput microscopy is now more than ever accessible to researchers. This allows for collection of large amount of cellular images. Naturally, the analysis of this data cannot be left to manual investigation and needs to resort to the use of efficient computing algorithms for cellular detection, segmentation, and tracking. Annotation is required for building high quality algorithms. Medical professionals and researchers spend a lot of effort and time in annotating cells. This task has proved to be very repetitive and time consuming. The experts’ time is valuable and should be used effectively. Our hypothesis is that active deep learning will help to share some of the burden that researchers face in their everyday work. In this paper, we focus specifically on the problem of cellular segmentation.We approach the segmentation task using a classification framework. Each pixel in the image is classified based on whether the patch around it resides on the interior, boundary or exterior of the cell. Deep convolutional neural networks (CNN) are used to perform the classification task. Active learning is the method used to reduce the annotation burden. Uncertainty sampling, a popular active learning framework is used in conjunction with CNN to segment the cells in the image. Three datasets of mammalian nuclei and cytoplasm are used for this work. We show that active deep learning significantly reduces the number of training samples required and also improves the quality of segmentation.
Determinants of TRevPAR: hotel, management and tourist destination
Authors: Lado-Sestayo Rubén , Vivel-Búa Milagros , Otero-González Luis 
Published: October 2017

Purpose
This paper aims to study the determinants of hotel performance, especially the role of location, in the Spanish hotel market.

Design/methodology/approach
The sample is composed of 1,034 hotels located in 97 tourist destinations in Spain during the period 2005-2011. The estimations were made by generalised least squares using panel data.

Findings
Overall, the results show that hotel attributes are the main determinant of performance. In particular, there is a minimum efficient scale in the hotel business. Location is the second most important determinant. This paper confirms that geographical location models, agglomeration models and competition models are relevant in the study of the effect of location on hotel performance. Regarding management practices, the performance is positively affected by good asset management.

Practical implications
Hotel managers can improve the total net revenue per available room by individually making decisions regarding its characteristics and management practices, especially size and asset efficiency. Moreover, they can collaborate with others (managers and policymakers) to manage tourist destination factors, particularly, demand level, accessibility, negative externalities and market concentration.

Originality/value
This research includes hotel characteristics, management practices and location as determinants of performance, by providing a broader framework of analysis than in previous studies. Regarding location, the empirical analysis considers simultaneously geographical location models, agglomeration models and competition models. The paper studies the Spanish hotel market, which is very important worldwide and which has heterogeneous tourist destinations, thereby making it a good context to analyse the relationship between location and performance.
Knowledge sharing in franchise system: franchisee self-leadership, satisfaction, and compliance
Authors: Lee Kyoung-Joo 
Published: October 2017

Purpose
The purpose of this paper is to deepen the understanding of the predictors and outcomes of knowledge sharing in a franchise system. An integrative framework is proposed to examine the influence of franchisee self-leadership on knowledge sharing and its subsequent influence on franchisee satisfaction and compliance.

Design/methodology/approach
On the basis of a survey of 111 franchisees of two leading bakery franchise brands in Korea, this study confirmed data validity and tested hypotheses by adopting partial least square–structural equation modeling.

Findings
Regarding the predictor of knowledge sharing, this research found that franchisee self-leadership has a positive effect on knowledge sharing. As outcomes, it found that active knowledge sharing has a positive effect on franchisee satisfaction and compliance. This study also shows that knowledge sharing mediates the relationship between self-leadership and franchisee satisfaction.

Practical implications
This research advises franchisors to actively develop programs and communication channels for knowledge sharing with franchisees to induce high levels of compliance and satisfaction. Furthermore, as selecting potential franchisees is key to the success of franchising, this research highlights the significance of self-leadership as a crucial personal trait of franchisees.

Originality/value
Despite the rapidly growing academic interest in franchise knowledge sharing, sparse theoretical approaches and empirical evidence are available. To address these limitations, this research presents an integrative model and empirical evidence.
Hotel employees’ organizational behaviors from cross-national perspectives
Authors: Kim MiRan , Choi Laee , Knutson Bonnie J. , Borchgrevink Carl P. 
Published: October 2017

PurposeThis study aims to examine the relationships among leader–member exchange (LMX), employee voice, team–member exchange (TMX), employee job satisfaction and employee commitment to customer service (ECCS) across the USA and Chinese cultures within the hotel context.Design/methodology/approachAn online survey was completed by hotel employees across the USA (n= 315) and China (n= 363). The data were analyzed using structural equation modeling.FindingsThe findings of this study imply that the relationships among constructs between two nations are very similar, with a few significant differences. Specifically, this study shows that there are significant differences between the USA and China regarding the effects of LMX on employee voice, TMX, job satisfaction and ECCS.Research limitations/implicationsThe research should be extended with more than two national cultures to increase the generalizability of the research findings. Primary implication is that leader in China, and the USA should seek to build LMX quality to reap organizational benefits.Practical implicationsThis study can help global hospitality firms develop management strategies effectively.Originality/valueThe study’s findings provide researchers with a better understanding of the LMX framework across USA and Chinese cultures. It also verifies the underlying relational effects among LMX and its outcomes across different nations, thus offering global hospitality organizations best management practices across cultures. Further, this study seeks to fill gaps in previous LMX and employee voice studies by providing robust explanations of the cultural influences on LMX framework across nations.
Food choices and service evaluation under time constraints: the school lunch environment
Authors: Sharma Amit , Moon Joonho , Bailey-Davis Lisa , Conklin Martha 
Published: October 2017

Purpose
Few states or local school districts mandate a minimum time for lunch. With increasing pressure on schools to maximize instructional time, many US students have witnessed continued reductions in the time allotted to lunch periods and, thus, less time to choose from an increasing number of food options. This study aims to investigate middle and high school students’ preferences regarding the time available for school lunches and whether the amount of time would affect their food choice preferences.

Design/methodology/approach
This study investigated students’ self-reported lunchtime constraints and food choice preferences through a paper-and-pencil survey. The categorical and ratio responses were analyzed using ordinal logistic regression.

Findings
Students responded that they rarely had enough time to eat school lunch and that the lunch line waiting time strongly or very strongly influenced their food choices. For the students for whom time available for lunch and time in the lunch line influenced what they ate, they were more likely to prefer limited food choices in several categories of the school lunch menu.

Practical implications
Foodservice professionals who wish to actively promote better nutrition might consider practical ways to reduce the foodservice wait time for students. While making healthier default options (e.g. a fruit or fresh vegetable side) could increase service convenience, time required for students to make informed meal choices should not be compromised.

Originality/value
Because lunch line waiting time is related to students’ food choices, schools need to review the number and types of food choices offered in terms of whether they encourage students to make more healthful choices. This study offers a unique perspective on the relationship between time and individual food choices in the school lunch environment and how this relationship affects the quality of children’s diets and their eating behaviors.
Linking LMX, engagement, innovative behavior, and job performance in hotel employees
Authors: Kim Min-Seong , Koo Dong-Woo 
Published: October 2017

PurposeThe concept of leader–member exchange (LMX) is well accepted in the service industry. This study examines how the quality of LMX helps hotels to achieve desirable outcomes, such as innovative behavior and job performance. The model was developed based on the LMX theory, and considers the relationship among the quality of LMX, employee engagement, innovative behavior and job performance.Design/methodology/approachThe model was tested on employees of hotels in South Korea using a survey method. Data were analyzed using frequency, reliability, confirmatory factor, correlation and structural equation modeling analyses.FindingsLMX significantly influenced job engagement and innovative behavior but did not significantly affect organization engagement. Job engagement significantly affected organization engagement and innovative behavior but did not significantly influence job performance. Organization engagement significantly influenced job performance but did not significantly affect innovative behavior. Job performance was significantly influenced by innovative behavior.Practical implicationsThe findings of this study suggest that an immediate leader plays a critical role in fostering engagement, behavior and performance.Originality/valueThe current study is the first to use the LMX theory to develop and test a research model that accounts for the antecedents and desired outcomes (i.e. innovative behavior and job performance) of two types of employee engagement in the hotel context.