bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural dynamics and allostery of Rab proteins: strategies for drug discovery and design
Authors: Kumar Ammu Prasanna , Verma Chandra S , Lukman Suryani 
Published: November 2019

AbstractRab proteins represent the largest family of the Rab superfamily guanosine triphosphatase (GTPase). Aberrant human Rab proteins are associated with multiple diseases, including cancers and neurological disorders. Rab subfamily members display subtle conformational variations that render specificity in their physiological functions and can be targeted for subfamily-specific drug design. However, drug discovery efforts have not focused much on targeting Rab allosteric non-nucleotide binding sites which are subjected to less evolutionary pressures to be conserved, hence are likely to offer subfamily specificity and may be less prone to undesirable off-target interactions and side effects. To discover druggable allosteric binding sites, Rab structural dynamics need to be first incorporated using multiple experimentally and computationally obtained structures. The high-dimensional structural data may necessitate feature extraction methods to identify manageable representative structures for subsequent analyses. We have detailed state-of-the-art computational methods to (i) identify binding sites using data on sequence, shape, energy, etc., (ii) determine the allosteric nature of these binding sites based on structural ensembles, residue networks and correlated motions and (iii) identify small molecule binders through structure- and ligand-based virtual screening. To benefit future studies for targeting Rab allosteric sites, we herein detail a refined workflow comprising multiple available computational methods, which have been successfully used alone or in combinations. This workflow is also applicable for drug discovery efforts targeting other medically important proteins. Depending on the structural dynamics of proteins of interest, researchers can select suitable strategies for allosteric drug discovery and design, from the resources of computational methods and tools enlisted in the workflow.
The Iron Cage of Leadership—the Role of First-Line Managers in Child Welfare
Authors: Tham Pia , Strömberg Annika 
Published: November 2019

Abstract
In the social services in general and particularly in child welfare, high staff turnover and recruitment difficulties have been reported for many years. Previous studies have shown that giving social workers adequate social support is important in getting them to maintain their job commitment and remain at the workplace. The aim of the present study was to investigate how child welfare managers perceive and respond to the content and demands of their professional role. Interviews were conducted with forty-two first-line managers. The results indicate that the expectations of the social workers and the demands of the organisation are in conflict. The overall picture is one of challenges and dilemmas in a changing managerial role, where the focus is increasingly on control, administration and budget responsibilities. While the managers highlight what can be regarded as transformative ideals and prioritise offering support and guidance to the social workers under them, the organisation seems to be pushing managers towards a leadership role characterised by control and authority, where quantitative measuring, monitoring and control processes are expected––a leadership style associated with transactional leadership. The influence of New Public Management on the conditions for, and the contents of, leadership in social services is discussed.
Chemical Composition and Antioxidant Activity of Essential Oils and Hexane Extract of Onopordum arenarium from Tunisia
Authors: Bouazzi Sihem , El Mokni Ridha , Nakbi Hanen , Dhaouadi Hatem , Joshi Rajesh K , Hammami Saoussen 
Published: November 2019

AbstractIn the present study, volatile oils from Onopordum arenarium fresh flowers and stems were obtained by hydrodistillation and the non-polar aerial part hexane extract was prepared using a Soxhlet apparatus. The constituents of different organs were identified for the first time by gas chromatography equipped with flame ionization detector and gas chromatography coupled to mass spectrometry. A total of 29 and 25 compounds were identified constituting over 91.6 and 89.2% of the whole constituents from flower and stem volatile oils, respectively. Both organs were constituted mainly of long-chain hydrocarbons (23.3–36.4%) followed by oxygenated long-chain hydrocarbons (31.5–33.8%) and oxygenated monoterpenes (14.4–6.6%). The major identified compound was palmitic acid [25.5% in O. arenarium flower essential oil (EO) and 28.7% in the stem EO]. Eighteen compounds representing 80.7% of the whole constituents were identified in the n-hexane extract, which was characterized by high amounts of triterpenoids (39.6%) and dominated by lupeol acetate (19.2%) and β-amyrin acetate (10.1%). Moreover, all extracts were evaluated for antioxidant potential using 1,1-diphenyl-2-picrylhydrazyl radical assay. The obtained results demonstrated that the EOs and the hexane extract could be a new source of natural potentially bioactive molecules.
Network attributes describe a similarity between deep neural networks and large scale brain networks
Authors: Takagi Kosuke 
Published: November 2019

AbstractDespite the recent success of deep learning models in solving various problems, their ability is still limited compared with human intelligence, which has the flexibility to adapt to a changing environment. To obtain a model which achieves adaptability to a wide range of problems and tasks is a challenging problem. To achieve this, an issue that must be addressed is identification of the similarities and differences between the human brain and deep neural networks. In this article, inspired by the human flexibility which might suggest the existence of a common mechanism allowing solution of different kinds of tasks, we consider a general learning process in neural networks, on which no specific conditions and constraints are imposed. Subsequently, we theoretically show that, according to the learning progress, the network structure converges to the state, which is characterized by a unique distribution model with respect to network quantities such as the connection weight and node strength. Noting that the empirical data indicate that this state emerges in the large scale network in the human brain, we show that the same state can be reproduced in a simple example of deep learning models. Although further research is needed, our findings provide an insight into the common inherent mechanism underlying the human brain and deep learning. Thus, our findings provide suggestions for designing efficient learning algorithms for solving a wide variety of tasks in the future.
PCSK9 and inflammation: role of shear stress, pro-inflammatory cytokines, and LOX-1
Authors: Ding Zufeng , Pothineni Naga Venkata K , Goel Akshay , Lüscher Thomas F , Mehta Jawahar L 
Published: November 2019

AbstractPCSK9 degrades low-density lipoprotein cholesterol (LDL) receptors and subsequently increases serum LDL cholesterol. Clinical trials show that inhibition of PCSK9 efficiently lowers LDL cholesterol levels and reduces cardiovascular events. PCSK9 inhibitors also reduce the extent of atherosclerosis. Recent studies show that PCSK9 is secreted by vascular endothelial cells, smooth muscle cells, and macrophages. PCSK9 induces secretion of pro-inflammatory cytokines in macrophages, liver cells, and in a variety of tissues. PCSK9 regulates toll-like receptor 4 expression and NF-κB activation as well as development of apoptosis and autophagy. PCSK9 also interacts with oxidized-LDL receptor-1 (LOX-1) in a mutually facilitative fashion. These observations suggest that PCSK9 is inter-twined with inflammation with implications in atherosclerosis and its major consequence—myocardial ischaemia. This relationship provides a basis for the use of PCSK9 inhibitors in prevention of atherosclerosis and related clinical events.
Human Breathomics Database
Authors: Kuo Tien-Chueh , Tan Cheng-En , Wang San-Yuan , Lin Olivia A , Su Bo-Han , Hsu Ming-Tsung , Lin Jessica , Cheng Yu-Yen , Chen Ciao-Sin , Yang Yu-Chieh , Chen Kuo-Hsing , Lin Shu-Wen , Ho Chao-Chi , Kuo Ching-Hua , Tseng Yufeng Jane 
Published: November 2019

Abstract
Breathomics is a special branch of metabolomics that quantifies volatile organic compounds (VOCs) from collected exhaled breath samples. Understanding how breath molecules are related to diseases, mechanisms and pathways identified from experimental analytical measurements is challenging due to the lack of an organized resource describing breath molecules, related references and biomedical information embedded in the literature. To provide breath VOCs, related references and biomedical information, we aim to organize a database composed of manually curated information and automatically extracted biomedical information. First, VOCs-related disease information was manually organized from 207 literature linked to 99 VOCs and known Medical Subject Headings (MeSH) terms. Then an automated text mining algorithm was used to extract biomedical information from this literature. In the end, the manually curated information and auto-extracted biomedical information was combined to form a breath molecule database—the Human Breathomics Database (HBDB). We first manually curated and organized disease information including MeSH term from 207 literatures associated with 99 VOCs. Then, an automatic pipeline of text mining approach was used to collect 2766 literatures and extract biomedical information from breath researches. We combined curated information with automatically extracted biomedical information to assemble a breath molecule database, the HBDB. The HBDB is a database that includes references, VOCs and diseases associated with human breathomics. Most of these VOCs were detected in human breath samples or exhaled breath condensate samples. So far, the database contains a total of 913 VOCs in relation to human exhaled breath researches reported in 2766 publications. The HBDB is the most comprehensive HBDB of VOCs in human exhaled breath to date. It is a useful and organized resource for researchers and clinicians to identify and further investigate potential biomarkers from the breath of patients.
Database URL: https://hbdb.cmdm.tw
Diabetes as a risk factor for severe exacerbation and death in patients with COPD: a prospective cohort study
Authors: Castañ-Abad Maria T , Montserrat-Capdevila Josep , Godoy Pere , Marsal Josep R , Ortega Marta , Alsedà Miquel , Barbé Ferran 
Published: November 2019

Abstract

Background
Type 2 diabetes comorbidity is common in patients with COPD. One of the most frequent causes of hospital admission in patients with COPD are exacerbations.

Methods
Prospective cohort study, which included 512 patients with COPD recruited in a primary care centre in Mollerussa (Lleida, Spain). Inclusion criteria were: patients &gt;40 years of age with COPD according to the Global Initiative for Chronic Obstructive Lung Disease. Variables collected were as follows: age, gender, civil status, education level, smoking habit, severity (Global Initiative for Chronic Obstructive Lung Disease), comorbidities (Charlson), history of severe exacerbations, dyspnoea (mMRC), BODEx, EuroQol 5 D and depression (HAD). Logistic regression was used to determine the association of diabetes with risk of hospital admission and death.

Results
Prevalence of diabetes was 25.8%. During the second year of follow up, 18.2% of patients with COPD and diabetes were admitted for exacerbation, in comparison with 8.9% non-diabetic COPD patients. The variables associated with hospital admission were diabetes (ORa=1.54); gender (men, ORa=1.93); age (ORa=1.02); number of hospital admissions during the previous year: 1 (ORa=2.83) or more than one admission (ORa=4.08); EuroQol 5 D (ORa=0.76) and BODEx (ORa=1.24). With the exclusion of BODEx, all these variables were associated with a higher risk of death.

Conclusion
Prevalence of diabetes is high in patients suffering from COPD. COPD patients with diabetes are at higher risk of severe exacerbation and death. The suggested predictive model could identify patients at higher risk so that adequate preventive and therapeutic measures can be implemented.
Improving mental health through neighbourhood regeneration: the role of cohesion, belonging, quality and disorder
Authors: Greene Giles , Fone David , Farewell Daniel , Rodgers Sarah , Paranjothy Shantini , Carter Bethan , White James 
Published: November 2019

Abstract
Poor mental health has been associated with socioeconomic deprivation. The aim was to describe possible mechanisms underpinning the narrowing of mental health inequalities demonstrated by Communities First, an area-wide regeneration programme in Wales, UK. Propensity score matched data from the Caerphilly Health and Social Needs Electronic Cohort Study, assessed changes in mental health, neighbourhood-level social cohesion, belongingness, quality and disorder. A multiple mediation analysis found c.76% of the total indirect effect was accounted for by neighbourhood quality and disorder. Targeted regeneration that increases neighbourhood quality and reduced neighbourhood disorder could mitigate the mental health inequalities associated with socioeconomic deprivation.
Dear medical mycologists, it is time to look outside the box
Authors: Morio Florent 
Published: November 2019

ABSTRACT
Opulente et al. (Opulente DA, Langdon QK, Buh KV et al. Pathogenic budding yeasts isolated outside of clinical settings. FEMS Yeast Res 2019;19:foz032) published early this year a study aiming to investigate the diversity of wild yeast species, by collecting 1000 environmental samples coming from different substrates across the United States of America. The main finding of this work is the recovery of 54 strains of budding yeasts of which several are having a pathogenic potential in the clinical setting, such as Candida albicans, C. parapsilosis, C. tropicalis, Nakaseomyces glabrata and Pichia kudriavzevii. These findings, discussed here in light of other recent studies highlighting the role of fungicides in the rise of antifungal resistance in the clinical setting or the emergence of Candida auris, demonstrate that our environment can represent an alternative niche for several opportunistic fungal pathogens that can be a concern for human health.
Within-population genome size variation is mediated by multiple genomic elements that segregate independently during meiosis
Authors: Stelzer Claus-Peter , Pichler Maria , Stadler Peter , Hatheuer Anita , Riss Simone 
Published: November 2019

Abstract
Within-species variation in genome size has been documented in many animals and plants. Despite its importance for understanding eukaryotic genome diversity, there is only sparse knowledge about how individual-level processes mediate genome size variation in populations. Here we study a natural population of the rotifer Brachionus asplanchnoidis whose members differ up to 1.9-fold in diploid genome size, but were still able to interbreed and produce viable offspring. We show that genome size is highly heritable and can be artificially selected up or down, but not below a certain basal diploid genome size for this species. Analyses of segregation patterns in haploid males reveal that large genomic elements (several megabases in size) provide the substrate of genome size variation. These elements, and their segregation patterns, explain the generation of new genome size variants, the short-term evolutionary potential of genome size change in populations, and some seemingly paradoxical patterns, like an increase in genome size variation among highly inbred lines. Our study suggests that a conceptual model involving only two variables, (1) a basal genome size of the population, and (2) a vector containing information on additional elements that may increase genome size in this population (size, number, and meiotic segregation behaviour), can effectively address most scenarios of short-term evolutionary change of genome size in a population.
The Influence of Simulated Sunlight on the Inactivation of Influenza Virus in Aerosols
Authors: Schuit Michael , Gardner Sierra , Wood Stewart , Bower Kristin , Williams Greg , Freeburger Denise , Dabisch Paul 
Published: November 2019

Abstract

Background
Environmental parameters, including sunlight levels, are known to affect the survival of many microorganisms in aerosols. However, the impact of sunlight on the survival of influenza virus in aerosols has not been previously quantified.

Methods
The present study examined the influence of simulated sunlight on the survival of influenza virus in aerosols at both 20% and 70% relative humidity using an environmentally controlled rotating drum aerosol chamber.

Results
Measured decay rates were dependent on the level of simulated sunlight, but they were not significantly different between the 2 relative humidity levels tested. In darkness, the average decay constant was 0.02 ± 0.06 min−1, equivalent to a half-life of 31.6 minutes. However, at full intensity simulated sunlight, the mean decay constant was 0.29 ± 0.09 min−1, equivalent to a half-life of approximately 2.4 minutes.

Conclusions
These results are consistent with epidemiological findings that sunlight levels are inversely correlated with influenza transmission, and they can be used to better understand the potential for the virus to spread under varied environmental conditions.
Early- and Late-Onset Bloodstream Infections in the Intensive Care Unit: A Retrospective 5-Year Study of Patients at a University Hospital in China
Authors: Xie Jianfeng , Li Shuzi , Xue Ming , Yang Congshan , Huang Yingzi , Chihade Deena B , Liu Ling , Yang Yi , Qiu Haibo 
Published: November 2019

Abstract

Background
Limited data are available regarding the current microbiological characteristics of bloodstream infections (BSIs) in intensive care units (ICUs) in China. This retrospective study aimed to determine the epidemiology of early- and late-onset BSIs in our ICU.

Methods
We retrospectively collected data about ICU patients with BSI from 2013 to 2017. The patients were divided into the early- and late-onset BSI groups according to if BSI occurred within or beyond 48 hours after ICU admission. Univariate and multivariate logistic regression analyses were used to assess the risk factors for infection with multidrug resistant organisms (MDROs).

Results
Of 5474 ICU admissions, 486 (8.9%) patients with BSIs and with 500 microorganisms were included in this study, 246 (50.6%) of whom had early-onset BSIs. Two hundred and seventy patients were infected with MDROs. The proportion of MDRO infections was significantly higher among patients with late-onset BSIs than among those with early-onset BSIs (57.9% vs. 41.5%, P = .017). The ICU mortality rate was significantly higher in the late-onset BSI group (44.6% vs. 33.8%, P = .014) and early and appropriate antimicrobial treatment significantly improved the survival rate among patients with BSI (P &lt; .001).

Conclusions
MDROs affected more than half of patients with BSI in the ICU. Early appropriate empirical antimicrobial therapy could improve clinical outcome of patients with BSIs.
10 Database Attacks
Authors: Pill Martin 
Published: November 2019

Abstract
Enterprise database and information storage infrastructures, holding the crown jewels of an organisation, are subject to a wide range of abuses and attacks, particularly when left vulnerable by poor system design or configuration. Martin Pill CITP, Principal Consultant and Security Architect with BSI Cybersecurity and Information Resilience, describes the most critical of these, followed by recommendations for mitigating the risk of each.
miR-206 regulates non-small-cell lung cancer cell aerobic glycolysis by targeting hexokinase 2
Authors: Jia Ke-Gang , Feng Gang , Tong Yu-Suo , Tao Guang-Zhou , Xu Lian 
Published: November 2019

AbstractAerobic glycolysis was closely associated with the malignant transformation and prognosis of tumours. miR-206 was found to be downregulated in several cancers. However, whether miR-206 functions in non-small-cell lung cancers (NSCLCs) via the process of aerobic glycolysis remains poorly characterized. Quantitative real-time PCR was performed to detect miR-206 level in NSCLC cells and tissues. The effect of miR-206 on hexokinase 2 (HK2) expression was examined through miR-206 overexpression or miR-206 knockdown. CCK-8 assay and colony formation assay were carried out to explore the role of miR-206 on cell proliferation and colony formation, respectively. The relationship between miR-206 and HK2 was measured by dual-luciferase reporter assay. Glucose consumption, lactate production assay and ATP generation were performed in NSCLC cells following miR-206 and HK2 overexpression. We found that miR-206 was downregulated in NSCLC tissues and cells. miR-206 overexpression downregulated the expression of HK2 via targeting HK2 3′UTR in NSCLC cells. In addition, miR-206 decreased the cell viability and colony formation in NSCLC cells. Furthermore, miR-206 reduced glucose uptake, lactate production and ATP generation in NSCLC cells via HK2 repression. In conclusion, these findings suggested that miR-206 regulated NSCLC cell aerobic glycolysis by targeting HK2.
Muscle Homeostasis Is Disrupted in Burned Adults
Authors: Clark Audra T , Song Juquan , Yao Xiao , Carlson Deborah , Huebinger Ryan M , Mei Liu Ming , Madni Tarik D , Imran Jonathan B , Taveras Luis R , Weis Holly B , Arnoldo Brett D , Phelan Herb A , Wolf Steven E 
Published: November 2019

Abstract
Severe burn leads to substantial skeletal muscle wasting that is associated with adverse outcomes and protracted recovery. The purpose of our study was to investigate muscle tissue homeostasis in response to severe burn. Muscle biopsies from the right m. lateralis were obtained from 10 adult burn patients at the time of their first operation. Patients were grouped by burn size (total body surface area of &lt;30% vs ≥30%). Muscle fiber size and factors of cell death and muscle regeneration were examined. Muscle cell cross-sectional area was significantly smaller in the large-burn group (2174.3 ± 183.8 µm2 vs 3687.0 ± 527.2 µm2, P = .04). The expression of ubiquitin E3 ligase MuRF1 and cell death downstream effector caspace 3 was increased in the large-burn group (P &lt; .05). No significant difference was seen between groups in expression of the myogenic factors Pax7, MyoD, or myogenin. Interestingly, Pax7 and proliferating cell nuclear antigen (PCNA) expression in muscle tissue were significantly correlated to injury severity only in the smaller-burn group (P &lt; .05). In conclusion, muscle atrophy after burn is driven by apoptotic activation without an equal response of satellite cell activation, differentiation, and fusion.