bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pathways Linking Air Pollution to Insulin Resistance Through Dysfunctional Bone-Vascular Axis in Healthy Adults
Authors: Xu Hongbing , Liu Shengcong , Wang Yang , Yi Tieci , Wang Tong , Zhu Yutong , Fang Jiakun , Xie Yunfei , Wu Rongshan , Zhao Qian , Song Xiaoming , Feng Baihuan , Chen Jie , Zheng Lemin , Rajagopaplan Sanjay , Brook Robert D. , Li Jianping , Huang Wei 
Published: November 2020

Abstract
BackgroundEpidemiological evidence supports that ambient air pollution exposure is associated with the onset of clinically overt diabetes, but the precise pathways are unknown. This study aimed to investigate whether dysfunctional bone-vascular axis can be a mechanistic linkage between air pollution and insulin resistance.MethodsStudy outcomes were determined by assessing a series of circulating biomarkers indicative of bone-vascular axis, insulin resistance, and immune inflammation among 73 healthy adults who undergo repeated clinical visits in Beijing, China, 2014-2016. Linear mixed-effects models were used to evaluate the impacts of air pollution on outcomes, and the potential interlinked pathways between exposure measures and insulin resistance were examined using mediation analyses.ResultsParticipants experienced extremely high levels of ambient particulates and gaseous pollutants exposures throughout the study, with daily concentrations varying from 30.6 to 236.2 μg/m3 for fine particulate matter (PM2.5) and 54.9 to 235.8 μg/m3 for oxides of nitrogen. We observed that short-term exposure to air pollutants was associated with changes in biomarkers of the bone-vascular axis and insulin resistance. Specifically, an interquartile range increase in 7-day moving average of PM2.5 concentrations was significantly associated with elevations of 30.1% in osteoprotegerin and 20.5% in adiponectin, as well as reductions of 16.6% in bone morphogenetic protein-4 and 8.5% in soluble insulin receptor ectodomain. Further, higher PM2.5 exposures were positively related to various indicators of immune inflammation, including elevations of 22.5% in interleukin-10, 19.6% in soluble CD163 and 27.5% in C-C chemokine ligand-2. Mediation analyses revealed that activation of the bone-vascular axis mediated up to 52% of pollutants-associated immune inflammatory responses, both of which could explain 66% of increases in insulin resistance attributed to pollutants exposures.ConclusionsShort-term air pollution exposure is potentially capable of promoting insulin resistance possibly via generating dysfunctional bone-vascular axis, suggesting a novel mechanism by which air pollution may potentiate the development of diabetes.
AQI Predication Using Temporal Data Mining
Authors: Bhushan Shashi , Tiwari Sanjay Kumar 
Published: November 2020

Abstract
The Air Quality Index (AQI) is an air quality standards indicator based on air pollutants that have negative impacts on human health and the environment. Because of several human activities, air pollution is growing very quickly, and it is the introduction of chemicals, particulate matter or biological materials into the atmosphere that cause human suffering and also harms the natural environment. Indeed, air pollution in metropolitan and industrial cities is one of the major environmental problems. So predicting pollution and avoiding these issues is very crucial. One of the most exciting and difficult functions is the forecast of air pollution using data mining. Many systems are designed to help data storage, inventory management and convenient statistics generation. India's air quality indicator is a standard measure used to indicate pollution (so2, no2, rspm, spm, etc.) from time to time. The main purpose of the current study is to predict the temporal AQI used by the previous day AQI and climate change is used to predict and visualize the temporary data mine using a gradient break and an unreasonable forecasting process. In Navigation Forecast, we divide the database into 85% data and 15% data based on data testing and training to determine seasonal variations and styles. Balance problems are often exploited by problems and forecasting uses an unreasonable prediction process and gradient downtime. Air quality forecasts based on historical data of previous years and predictions for less than a year as a reputable gradient using a recurring problem.
Ensemble Machine Learning Approaches for Proteogenomic Cancer Studies
Authors: Liang Yulan , Gharipour Amin , Kelemen Erik , Kelemen Arpad 
Published: November 2020

Abstract
Background: The identification of important proteins is critical for medical diagnosis and prognosis in common diseases. Diverse sets of computational tools were developed for omics data reductions and protein selections. However, standard statistical models with single feature selection involve the multi-testing burden of low power with the available limited samples. Furthermore, high correlations among proteins with high redundancy and moderate effects often lead to unstable selections and cause reproducibility issues. Ensemble feature selection in machine learning may identify a stable set of disease biomarkers that could improve the prediction performance of subsequent classification models, and thereby simplify their interpretability. In this study, we developed a three-stage homogeneous ensemble feature selection approach for both identifying proteins and improving prediction accuracy. This approach was implemented and applied to ovarian cancer proteogenomics data sets: 1) binary putative homologous recombination deficiency positive or negative; and 2) multiple mRNA classes (differentiated, proliferative, immunoreactive, mesenchymal, and unknown). We conducted and compared various machine learning approaches with homogeneous ensemble feature selection including random forest, support vector machine, and neural network for predicting both binary and multiple class outcomes. Various performance criteria including sensitivity, specificity, kappa statistics were used to assess the prediction consistency and accuracy. Results: With the proposed three-stage homogeneous ensemble feature selection approaches, prediction accuracy can be improved with the limited sample through continuously reducing errors and redundancy, i.e. Treebag provided 83% prediction accuracy (85% sensitivity and 81% specificity) for binary ovarian outcomes. For mRNA multi-classes classification, our approach provided even better accuracy with increased sample size. Conclusions: Despite the different prediction accuracies from various models, homogeneous ensemble feature selection proposed identified consistent sets of top ranked important markers out of 9606 proteins linked to the binary disease and multiple mRNA class outcomes.
An Observational Cohort of First Episode Psychosis in Iran: The Azeri Recent Onset Acute Phase Psychosis Survey (ARAS&nbsp;Cohort) Study Protocol
Authors: Farhang Sara , Ghaemmaghami Mehrdad , Noorazar Gholamreza , Veling Wim , Malek Ayyoub , Shafiee-kandjani Alireza , Somi Mohammad Hossein , Alizadeh Behrooz Z , Bruggeman Richard 
Published: November 2020

Abstract
BackgroundMost of our knowledge about the etiology, course, treatment, and outcome of schizophrenia spectrum and other psychotic disorders stems from Western countries. Data from populations living in other geographical areas and low- and middle-income countries, with different genomes (ethnicity) and exposomes (e.g., culture and social support, drugs of abuse, religion), will add to our knowledge of this complex disorder.MethodsThe Azeri Acute phase/Recent onset psychosis Survey (ARAS) has been initiated to study the course of the disorder in patients with recent onset psychosis using validated diagnostic tools and a comprehensive outcome monitoring system, aiming to reveal indicators for understanding the risk and resilience factors and for choosing the best personalized treatment strategy. All participants will be evaluated for clinical signs and symptoms as well as risk and resilience factors and will be followed up for 1, 3, and 5 years for outcomes in several domains. A hierarchical cluster method will be applied to identify the number of clusters for each outcome. Defined models will be applied to assess the predictive value of cognition on symptomatic and functional outcomes at follow-up.DiscussionThe ARAS cohort will yield significant academic- (research and education) and care-related achievements. ARAS data and experience will have value both in being a useful model for other parts of this region and in expansion of the current available knowledge.
Breastfeeding support at an Australian Breastfeeding Association drop-in service: a descriptive survey
Authors: Burns Elaine , Duursma Louise , Triandafilidis Zoi 
Published: November 2020

Abstract
BackgroundIn Australia, during the early establishment phase of breastfeeding, women can access telephone peer support counselling provided by the Australian Breastfeeding Association (ABA) however options for face-to-face peer support are limited. The known factors which improve ongoing and exclusive breastfeeding include face-to-face support, peer and/or professional support, and trained personnel. This study aimed to examine women’s experiences of accessing one breastfeeding drop-in peer support service provided by trained peer support volunteer counsellors from the ABA.MethodsWomen who accessed the service were invited, in 2014, to participate in an anonymous online survey which collected both quantitative and qualitative data. Participants were asked about their experiences of breastfeeding support, as well as their experiences of the drop-in service. In total, 53 women completed the online survey, and subsequent analysis generated descriptive statistics and qualitative themes.ResultsResponses to the survey revealed that women attended the drop-in service with infants ranging in age from less than 1 week through to 12 months of age. Most women reported attending with infants aged 0-8 weeks of age (72%). The predominant presenting problems identified were sore/damaged nipples, difficulties with infant latching to the breast, or concerns about using nipple shields. Analysis of the open text qualitative responses revealed one overarching theme ‘Support to continue breastfeeding’ and four subthemes: ‘feeling listened to and not judged’; ‘emotional support and confidence building’; ‘the importance of face-to-face, practical support'; and ‘the need for ongoing, free access’.DiscussionIn this study many women were seeking support for ongoing breastfeeding difficulties. Health professionals who had limited breastfeeding knowledge and skills were identified as most unhelpful in providing support with ongoing breastfeeding difficulties. Women valued having access to trained peer counsellors, who had the capacity to provide non-judgemental, face-to-face support; who could sit through a feed; in a space that was ‘safe’; and who could enhance a woman’s confidence with breastfeeding over the course of her full breastfeeding journey.ConclusionReactive peer support, provided in response to need, at an Australian Breastfeeding Association drop-in service, was described by participants as pivotal to enabling their ongoing breastfeeding.
Do breastfeeding practices correlate with childhood diarrhoea? Multiple data analyses using national surveys in Ghana
Authors: Tampah-Naah Anthony Mwinilanaa 
Published: November 2020

Abstract
Background: Breastfeeding as a natural intervention tends to have a protective effect on the occurrence of diarrhoea in children. In environments where breastfeeding is suboptimal coupled with the early introduction of complementary foods, children are at a higher risk of experiencing diarrhoea. This study examined whether breastfeeding practices are associated with childhood diarrhoea in Ghana using multiple secondary datasets. Methods: The study used data from Ghana Demographic and Health Survey (GDHS) 2003, 2008 and 2014 individual datasets. These datasets contain data on women and issues related to children who were two years of age (0-23 months). An appended weighted sample of 4,675 mother-child pairs was used for the analyses. Thus, logistic regression analyses were performed to assess the effect of explanatory variables that were considered as potential confounders on the association between breastfeeding practices and childhood diarrhoea.Results: Univariate analysis revealed that children who were not exclusively breastfeeding had higher odds of experiencing diarrhoea. With the multilevel logistic analysis, breastfeeding practices and risks of diarrhoea among children revealed significant associations.Conclusions: Findings for this study further affirms to the protective effect breastfeeding has against childhood diarrhoea. Exclusive breastfeeding and at times predominant breastfeeding could prevent or minimize diarrhoea compare to non-practice of breastfeeding or partial breastfeeding.
Evaluating cochlear insertion trauma and hearing preservation after cochlear implantation (CIPRES): A study protocol for a randomised single blind controlled trial
Authors: Jwair Saad , Boerboom Ralf , Versnel Huib , Stokroos Robert , Thomeer Hans 
Published: November 2020

Abstract
BackgroundIn order to preserve residual hearing in patients with sensorineural hearing loss (SNHL) who receive a cochlear implant (CI), insertion trauma to the delicate structures of the cochlea needs to be minimized. The surgical approach comprises the conventional mastoidectomy-posterior tympanotomy (MPT) to arrive at the middle ear, followed by either a cochleostomy (CO) or the round window (RW) approach. Both techniques have their benefits and disadvantages. Another important aspect in structure preservation is the design of the electrode array. Two different designs are used: a ‘straight’ lateral wall lying electrode array (LW), or a ‘pre-curved’ perimodiolar lying electrode array (PM). Interestingly, until now, the best surgical approach and design of the implant is uncertain. Our hypothesis is that the combination of a RW approach and a LW lying electrode array minimizes insertion trauma, leading to better hearing outcome for SNHL patients. MethodsWe designed a monocenter, 2x2, randomized controlled trial to compare insertion trauma between four groups of patients, with each group having a unique combination of electrode array type (LW or PM) and surgical approach (RW or CO). In total, 48 patients will be randomized into one of these four intervention groups. Our primary objective is comparison of postoperative hearing preservation between these four groups. Secondly, we aim to assess structure preservation (i.e., scalar transposition, with basilar membrane disruption or tip fold-over of array) for each group. Thirdly, we will compare objective outcomes of hearing and structure preservation by way of electrocochleography (ECochG).DiscussionCochlear implantation by way of a cochleostomy or round window approach, using different electrode array types, is the standard medical care for patients with severe to profound bilateral sensorineural hearing loss, as it is a relative simple and low-risk procedure that greatly benefits patients. However, loss of residual hearing remains a problem. This trial is the first randomized controlled trial that evaluates the effect of cochlear insertion trauma of several CI treatment options on hearing preservation. Trial registrationThis trial is registered in the Netherlands Trial Register (NTR) (www.trialregister.nl): NL8586, date of registration: 4th of May 2020. Retrospectively registered; 3/48 participants were included before registration.
A mHealth-intervention to support the self-management of multimorbid patients in general practices in Germany (TelePraCMan) – Study protocol of a randomized pilot study
Authors: Wiezorreck Lars , Litke Nicola , Freund Tobias , Miksch Antje , Wensing Michel , Szecsenyi Joachim , Weis Aline 
Published: November 2020

Abstract
Background: Previously we developed a structured case management for patients with multiple chronic conditions in primary care (called ‘PraCMan’), delivered by Health Care Assistants in General Practice (VERAHs). The ‘TelePraCMan’ project aims to develop a supplementary web-based application to ‘PraCMan’, including a digital symptom diary in which patients can enter individual data via smartphone/tablet. This application is targeted at patients suffering from diabetes mellitus type 2, COPD, hypertension and/or chronic heart failure. Objective: The objective of this study is to evaluate this mHealth-intervention for patients with chronic diseases, focused on patients’ quality of life and self-management capabilities.Methods: A two-armed patient-randomized pilot trial is planned, involving 200 multimorbid patients in 20 GP-practices that use ‘PraCMan’ regularly. Participants are randomly assigned (1:1) to receive either standard ‘PracMan’ treatment or standard ‘PracMan’ treatment complemented with the mHealth-intervention (TelePraCMan). As primary outcome, the health-related quality of life is measured by the German version of the Short Form Health Questionnaire (SF-12). Secondary outcomes include self-management capabilities, technical affinity, and user experience of patient and practice staff. Outcomes are measured at baseline (T0) and at follow-up after 6 months (T1). For the evaluation of the implementation process, GPs, VERAHs and patients will be invited to participate in semi structured interviews afterwards.The outcomes will be compared between study arms using multilevel regression analysis. Qualitative interviews will be transcribed and analysed using qualitative content analysis based on the Tailored Implementation for Chronic Diseases Framework. Discussion: ‘TelePraCMan’ is one of the first mHealth-Interventions addressing multimorbid patients in primary care.Trial registration: DRKS, DRKS00017320, Registered 18 June 2019, http://www.drks.de/DRKS00017320
Helmet Continuous Positive Airway Pressure versus High-Flow Nasal Cannula in COVID-19: A pragmatic randomised clinical trial (COVID HELMET)
Authors: Tverring Jonas , Åkesson Anna , Nielsen Niklas 
Published: November 2020

Abstract
Background: Patients with COVID-19 and hypoxemia despite conventional low-flow oxygen therapy are often treated with High-flow Nasal Cannula (HFNC) in line with international guidelines. Oxygen delivery by Helmet Continuous Positive Airway Pressure (CPAP) is a feasible option that enables a higher positive end-expiratory pressure (PEEP) and may theoretically reduce the need for intubation compared to HFNC but direct comparative evidence is lacking. Methods: We plan to perform an investigator-initiated, pragmatic, randomised trial at an intermediate-level COVID-19 cohort ward in Helsingborg Hospital, southern Sweden. We have estimated a required sample size of 120 patients randomised 1:1 to HFNC or Helmet CPAP to achieve 90% power to detect superiority at a 0.05 significance level regarding the primary outcome of ventilator free days (VFD) within 28 days using a Mann-Whitney U test. Patient recruitment is planned to being June 2020 and be completed in the first half of 2021.Discussion: We hypothesize that the use of Helmet CPAP will reduce the need for invasive mechanical ventilation compared to the use of HFNC without having a negative effect on survival. This could have important implications during the current COVID-19 epidemic. Trial registration: ClinicalTrials.gov, NCT04395807, Registered 20 May 2020, https://clinicaltrials.gov/ct2/show/NCT04395807
Three-dimensional Construction of Micrometer Level in Rat Stomach by Synchrotron Radiation
Authors: Tao Qiang , Gao Chen-Chen , Tong Xue-Hong , Yuan Shi-Zhen , Xu Jingdong 
Published: November 2020

Abstract
Background: The structural changes of gastric mucosa are considered as an important window of early gastric lesions. This article shows an imaging method of the stomach that does not use imaging agents. X-ray phase-contrast images of different stages of gastric development were taken using micrometer level X-ray in-line phase-contrast imaging (XILPCI) technique on synchrotron radiation facility. The aim of the study was to demonstrate that the imaging technique is an appropriate method for micron imaging of the gastric structures.Methods: The stomachs of 4-, 6- and 12-week-old rats were removed and cleaned. XILPCI has 1000 times greater soft tissue contrast than that of X-ray traditional absorption radiography. The projection images of the rats stomachs were recorded by an XILPCI charge coupled device (CCD) at 9 μm image resolution.Results: The X-ray in-line phase-contrast images of the different stages of rats’ gastric specimens clearly showed the gastric architectures and the details of the gastro-duodenal region. 3-dimensional stomach anatomical structure images were reconstruction. Conclusion: The reconstructed gastric 3D images can clearly display the internal structure of the stomach. XILPCI may be a useful method for medical research in the future.
Evaluation of serum anti-Mullerian hormone levels in women with Hashimoto thyroiditis in the reproductive age
Authors: Unsal Ilknur Ozturk , Hepsen Sema , Akhanli Pinar , Calapkulu Murat , Sencar Muhammed Erkam , Yalcindag Ali , Cakal Erman 
Published: November 2020

Abstract
Background: Autoimmune thyroid disease in women is associated with subfertility and early pregnancy loss, and patients with primary ovarian insufficiency have a high prevalence of thyroid autoimmune disorders. The aim of this study was to investigate the association between Hashimoto thyroiditis (HT) and ovarian reserve.Methods: Levels of serum thyroid stimulating hormones, thyroid autoantibodies, and anti-Müllerian hormone (AMH) were measured in women with HT and a healthy control group between 2018 and 2019. Result: Evaluation was made of 108 premenopausal women with HT. A control group was formed of 172 healthy female subjects with normal anti-thyroid antibody levels and thyroid function. Serum AMH levels were determined to be significantly lower in the HT group compared to the control group.Conclusion: Ovarian reserve evaluated by serum AMH concentration is affected by thyroid autoimmunity independently of anti-thyroid antibodies type or titers.
Deep learning based DNA:RNA triplex forming potential prediction
Authors: ZHANG Yu , Long Yahui , Kwoh Chee Keong 
Published: November 2020

Abstract
Background: Long non-coding RNAs (lncRNAs) can exert functions via forming triplex with DNA. The current methods in predicting the triplex formation mainly rely on mathematic statistic according to the base paring rules. However, these methods have two main limitations: i) they identify a large number of triplex-forming lncRNAs, but the limited number of experimentally verified triplex-forming lncRNA indicates that maybe not all of them can form triplex in practice, and ii) their predictions only consider the theoretical relationship while lacking the features from the experimentally verified data. Results: In this work, we develop an integrated program named TriplexFPP (Triplex Forming Potential Prediction), which is the first machine learning model in DNA:RNA triplex prediction. TriplexFPP predicts the most likely triplex-forming lncRNAs and DNA sites based on the experimentally verified data, where the high-level features are learned by the convolutional neural networks. In the 5-fold cross validation, the average values of Area Under the ROC curves and PRC curves for removed redundancy triplex-forming lncRNA dataset with threshold 0.8 are 0.9649 and 0.9996, and these two values for triplex DNA sites prediction are 0.8705 and 0.9671, respectively. Besides, we also briefly summarise the cis and trans targeting of triplexes lncRNAs. Conclusions: The TriplexFPP is able to predict the most likely triplex-forming lncRNAs from all the lncRNAs with computationally defined triplex forming capacities and the potential of a DNA site to become a triplex. It may provide insights to the exploration of lncRNA functions.