bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the effects of a lack of pocketmoney onthe learning activities of undergraduate health sciences students in their clinical year
Authors: Kumsa Marema Jebessa , Lemu Bizuayehu Nigatu , Ketema Taklehaimanot Mezgebe 
Published: October 2019

AbstractBackgroundIn Ethiopia, there is little understanding of students’ university expenses and how the lack of pocket money affects undergraduate learning. This is particularly evident for undergraduate health sciences students that need additional money when they start their clinical placement.ObjectivesWe aimed to explore the economic challenges that clinical year undergraduate health sciences students face with limited pocket money, as well as how students perceive these limited funds as affecting their learning activities and their ability to meet challenges.MethodsThis descriptive qualitative study was conducted at the Department of Medical Radiology Technology (MRT), College of Health Sciences (CHS) at Addis Ababa University (AAU). Ten participants were recruited through purposive and snowball methods, and semi-structured interviews were conducted between January 28, 2019 and February 1, 2019. The semi-structured questions explored participants’ experiences and perceptions regarding the challenges of a lack of pocket money and its impacts on their learning activities. Their reaction to financial challenges was also assessed.ResultsFour themes that are related to impact of lack of money on learning activities emerged from the interviews and they revolved around the students’ challenges in obtaining pocket money, their difficulty in affording daily needs, their self-management and their ability to have an adequate social life.ConclusionBased on our data, the underlying causes that lead students to face financial hardships can be solved by increasing public awareness of university expenses, clarifying the cost sharing system to the public, redesigning the cost sharing policy, and improving university services In addition, training students self-management and pocket money management, as well giving providing adequate transportation services, cash-money, and consultations for students during clinical placement.
VALIDATION OF PHLEBOTOMY PERFORMANCE METRICS DEVELOPED AS PART OF A PROFICIENCY BASED PROGRESSION INITIATIVE TO MITIGATE WRONG BLOOD IN TUBE
Authors: O’ Herlihy N. , Griffin S , Henn P , Gaffney R. , Cahill M.R. , Gallagher A.G. 
Published: October 2019

AbstractAimsThe purpose of this study was to 1) characterise the procedure of phlebotomy, deconstruct it into its constituent parts and develop a performance metric for the purpose of training healthcare professionals in a large teaching hospital, 2) evaluate the construct validity of the phlebotomy metric and establish a proficiency benchmark.MethodUsing video recordings of the procedure, we defined a performance metric. This was brought to a modified Delphi meeting, where consensus was reached by an expert panel. To demonstrate construct validity, we used the metric to objectively assess the performance of novices and expert practitioners.ResultsA phlebotomy metric consisting of 11 phases and 77 steps was developed. The mean inter-rater reliability was 0.91 (min 0.83, max 0.95). The Expert group completed more steps of the procedure (72 Vs 69), made 69% fewer errors (19 vs 13, p = 0.014) and 300% fewer critical errors (1 Vs 4, p = 0.002) than the Novice Group.ConclusionsThe metrics demonstrated construct validity and the proficiency benchmark was established with a minimum observation of 69 steps, with no critical errors and no more than 13 errors in total.
Prediction of Colorectal Cancer Risk Based on Profiling with Common Genetic Variants
Authors: Li Xue , Timofeeva Maria , Spiliopoulou Athina , McKeigue Paul , He Yazhou , Zhang Xiaomeng , Svinti Victoria , Campbell Harry , Houlston Richard S , Tomlinson Ian PM , Farrington Susan M , Dunlop Malcolm G , Theodoratou Evropi 
Published: October 2019

SummaryBackgroundStratifying the risk of colorectal cancer (CRC) based on polygenic risk scores (PRSs) within populations has the potential to optimize screening and develop targeted prevention strategies.MethodsA meta-analysis of eleven genome-wide association studies (GWAS), comprising 16 871 cases and 26 328 controls, was performed to capture CRC susceptibility variants. Genetic models with several candidate PRSs were generated from Scottish CRC case–control studies (6478 cases and 11 043 controls) for prediction of overall and site-specific CRC. Model performance was validated in UK Biobank (4800 cases and 20 287 controls). The 10-year absolute risk of CRC was estimated by modelling PRS with age and sex using the CRC incidence and mortality rates in the UK population.FindingsA weighted PRS including 116 CRC SNPs (wPRS116) showed the strongest performance. Deconstructing the PRS into multiple genetic risk regional scores or inclusion of additional SNPs that did not reach genome-wide significance did not provide any further improvement on predictive performance. The odds ratio (OR) for CRC risk per SD of wPRS116 in Scottish dataset was 1·46 (95%CI: 1·41-1·50, c-statistics: 0·603). Consistent estimates were observed in UK Biobank (OR=1·49, 95%CI: 1·44-1·54, c-statistics: 0·610) and showed no substantial heterogeneity among tumor sites. Compared to the middle quintile, those in the highest 1% of PRSs had 3·25-fold higher risk and those in the lowest 1% had 0·32-fold lower risk of developing CRC. Modelling PRS with age and sex in the general UK population allows the identification of a high-risk group with 10-year absolute risk ≥5%.InterpretationBy optimizing wPRS116, we show that genetic factors increase predictive performance but this increment is equivalent to the extraction of only one-tenth of the genetic susceptibility. When employing genetic risk profiling in population settings it provides a degree of risk discrimination that could, in principle, be integrated into population-based screening programs.
Whole genome sequencing detects minimal clustering amongEscherichia coliSequence Type 131H30isolates collected from U.S. children’s hospitals
Authors: Miles-Jay Arianna , Weissmann Scott J. , Adler Amanda L. , Baseman Janet G. , Zerr Danielle M. 
Published: October 2019

AbstractEscherichia colisequence type 131H30has garnered global attention as a dominant antimicrobial-resistant lineage of extraintestinal pathogenicE. coli, but its transmission dynamics remain undefined. We applied whole genome sequencing to identify putative transmission clusters among clinical isolates ofH30from children across the U.S. Of 126 isolates, 17 were involved in 8 putative transmission clusters; 4 clusters involved isolates with some evidence of healthcare-associated epidemiologic linkages. Geographic clustering analyses showed weak geographic clustering. These findings are consistent with a framework where within-hospital transmission is not a main contributor to the propagation ofH30in a pediatric setting.
Potential Predictive Factors for Breast Cancer Subtypes from a North Cyprus Cohort Analysis
Authors: Ulgen Ayse , Gürkut Özlem , Li Wentian 
Published: October 2019

ABSTRACTPurposeWe present a first epidemiological survey from North Cyprus to determine predictive factors for breast cancer subtypes.MethodsMore than 300 breast cancer patients, 90% of them having subtype information, are surveyed from the State Hospital in Nicosia between 2006 – 2015 for their demographic, reproductive, genetic, epidemiological factors. The breast cancer subtypes, Estrogen receptor (ER) +/-, Progesterone receptor (PR) +/-, and human epidermal growth factor 2 (HER2) +/- status, are determined. Single and multiple variable, regularized regressions, with predictive factors as independent variables, breast cancer subtypes as dependent variables are conducted.ResultsOur cohort differs significantly from larger cohorts (e.g., Breast Cancer Family Registry), in age, menopause status, age of menarche, parity, education, oral contraceptive use, breastfeeding, but the distribution of breast subtypes is not significantly different. Subtype distribution in our cohort is also not different from another Turkish cohort. We show that the ER+ subtype is positively related to age/post-menopause; ER+/PR+ is positively associated with age, but negatively associated with cancer stage; HER2+, which is negatively correlated with ER+ and ER+/PR+, is positively related to cancer stage but negatively associated with age/post-menopause.ConclusionAssuming ER+ and ER+/PR+ to have better prognostic, HER+ to have worse prognostic, then older age and postmenopause seem to be beneficial, smoking and family history of cancer seem to be detrimental. Next steps include looking at potential biomarkers and using cure models to determine long-term survivors.
Gaze, Visual, Myoelectric, and Inertial Data of Grasps for Intelligent Prosthetics
Authors: Cognolato Matteo , Gijsberts Arjan , Gregori Valentina , Saetta Gianluca , Giacomino Katia , Hager Anne-Gabrielle Mittaz , Gigli Andrea , Faccio Diego , Tiengo Cesare , Bassetto Franco , Caputo Barbara , Brugger Peter , Atzori Manfredo , Müller Henning 
Published: October 2019

AbstractHand amputation is a highly disabling event, having severe physical and psychological repercussions on a person’s life. Despite extensive efforts devoted to restoring the missing functionality via dexterous myoelectric hand prostheses, natural and robust control usable in everyday life is still challenging. Novel techniques have been proposed to overcome the current limitations, among which the fusion of surface electromyography with other sources of contextual information. We present a dataset to investigate the inclusion of eye tracking and first person video to provide more stable intent recognition for prosthetic control. This multimodal dataset contains surface electromyography and accelerometry of the forearm, and gaze, first person video, and inertial measurements of the head recorded from 15 transradial amputees and 30 able-bodied subjects performing grasping tasks. Besides the intended application for upper-limb prosthetics, we also foresee uses for this dataset to study eye-hand coordination in the context of psychophysics, neuroscience, and assistive robotics.
DNA methylation biomarker selected by an ensemble machine learning approach predicts mortality risk in an HIV-positive veteran population
Authors: Shu Chang , Justice Amy C. , Zhang Xinyu , Marconi Vincent C. , Hancock Dana B. , Johnson Eric O. , Xu Ke 
Published: October 2019

AbstractBackgroundWith the improved life expectancy of people living with HIV (PLWH), identifying vulnerable subpopulations at high risk of mortality is important for clinical care. Evidences showed that DNA methylation (DNAm) is associated with aging and mortality in non-HIV populations. Here, we aimed to establish a panel of DNAm biomarkers that can predict mortality risk among PLWH.Methods1,081 HIV-positive participants from the Veterans Aging Cohort Study (VACS) were divided into training (N=460), validation (N=114), and testing (N=507) sets. VACS index was used as a measure of mortality risk among PLWH. Model training and fine-tuning were conducted using the ensemble method in the training and validation sets and prediction performance was assessed in the testing set. The survival analysis comparing the predicted high and low mortality risk groups was conducted. The Gene Ontology enrichment analysis of the predictive CpG sites was performed.ResultsWe selected a panel of 393 CpGs for the ensemble prediction model. The prediction model showed excellent performance in predicting high mortality risk with an auROC of 0.809 (95%CI: 0.767-0.851) and a balanced accuracy of 0.653 (95%CI: 0.611, 0.693) in the testing set. The predicted high mortality risk group was significantly associated with 10-year mortality (hazard ratio=1.79, p=4E-05) compared with low mortality risk group. These 393 CpGs were located in 280 genes enriched in immune and inflammation responses pathways.ConclusionsWe identified a panel of DNAm features associated with mortality risk in PLWH. These DNAm features may serve as predictive biomarkers for mortality risk among PLWH.
Prediction of Suicidal Ideation in the Canadian Community Health Survey - Mental Health Component Using Deep Learning
Authors: Desai Sneha , Tanguay-Sela Myriam , Benrimoh David , Fratila Robert , Brown Eleanor , Perlman Kelly , John Ann , DelPozo-Banos Marcos , Low Nancy , Israel Sonia , Palladini Lisa , Turecki Gustavo 
Published: October 2019

AbstractIntroductionSuicidal ideation (SI) is prevalent in the general population, and is a prominent risk factor for suicide. However, predicting which patients are likely to have SI remains a challenge. Deep Learning (DL) may be a useful tool in this context, as it can be used to find patterns in complex, heterogeneous, and incomplete psychiatric datasets. An automated screening system for SI could help prompt clinicians to be more attentive to patients at risk for suicide.MethodsUsing the Canadian Community Health Survey - Mental Health Component, we trained a DL model based on 23,859 survey responses to predict lifetime SI on an individual patient basis. Models were created to predict both lifetime and last 12 month SI. We reduced 582 possible model parameters captured by the survey to 96 and 21 feature versions of the models. Models were trained using an undersampling procedure that balanced the training set between SI and non-SI respondents; validation was done on held-out data.ResultsAUC was used as the main model metric. For lifetime SI, the 96 feature model had an AUC of 0.79 and the 21 feature model had an AUC of 0.75. For SI in the last 12 months the 96 feature model had an AUC of 0.76 and the 21 feature model had an AUC of 0.69. DL outperformed random forest classifiers.DiscussionAlthough requiring further study to ensure clinical relevance and sample generalizability, this study is a proof-of-concept for the use of DL to improve prediction of SI. This kind of model would help start conversations with patients which could lead to improved care and, it is hoped, a reduction in suicidal behavior.
Barthelonids represent a deep-branching Metamonad clade with mitochondrion-related organelles generating no ATP
Authors: Yazaki Euki , Kume Keitaro , Shiratori Takashi , Eglit Yana , Tanifuji Goro , Harada Ryo , Simpson Alastair G.B. , Ishida Ken-ichiro , Hashimoto Tetsuo , Inagaki Yuji 
Published: October 2019

AbstractWe here report the phylogenetic position of barthelonids, small anaerobic flagellates previously examined using light microscopy alone.Barthelonaspp. were isolated from geographically distinct regions and we established five laboratory strains. Transcriptomic data generated from oneBarthelonastrain (PAP020) was used for large-scale, multi-gene phylogenetic (phylogenomic) analyses. Our analyses robustly placed strain PAP020 at the base of the Fornicata clade, indicating that barthelonids represent a deep-branching Metamonad clade. Considering the anaerobic/microaerophilic nature of barthelonids and preliminary electron microscopy observations on strain PAP020, we suspected that barthelonids possess functionally and structurally reduced mitochondria (i.e. mitochondrion-related organelles or MROs). The metabolic pathways localized in the MRO of strain PAP020 were predicted based on its transcriptomic data and compared with those in the MROs of fornicates. Strain PAP020 is most likely incapable of generating ATP in the MRO, as no mitochondrial/MRO enzymes involved in substrate-level phosphorylation were detected. Instead, we detected the putative cytosolic ATP-generating enzyme (acetyl-CoA synthetase), suggesting that strain PAP020 depends on ATP generated in the cytosol. We propose two separate losses of substrate-level phosphorylation from the MRO in the clade containing barthelonids and (other) fornicates.
Transcript isoform sequencing reveals widespread promoter-proximal transcriptional termination
Authors: Ard Ryan , Thomas Quentin , Li Bingnan , Wang Jingwen , Pelechano Vicent , Marquardt Sebastian 
Published: October 2019

SUMMARYHigher organisms achieve optimal gene expression by tightly regulating the transcriptional activity of RNA Polymerase II (RNAPII) along DNA sequences of genes1. RNAPII density across genomes is typically highest where two key choices for transcription occur: near transcription start sites (TSSs) and polyadenylation sites (PASs) at the beginning and end of genes, respectively2,3. Alternative TSSs and PASs amplify the number of transcript isoforms from genes4, but how alternative TSSs connect to variable PASs is unresolved from common transcriptomics methods. Here, we define TSS/PAS pairs for individual transcripts in Arabidopsis thaliana using an improved Transcript Isoform sequencing (TIF-seq) protocol and find on average over four different isoforms corresponding to variable TSS/PAS pairs per expressed gene. While intragenic initiation represents a large source of regulated isoform diversity, we discover that ∼ 14% of expressed genes generate relatively unstable short promoter-proximal RNAs (sppRNAs) from nascent transcript cleavage and polyadenylation shortly after initiation. The location of sppRNAs coincides with increased RNAPII density, indicating these large pools of promoter-stalled RNAPII across genomes are often engaged in transcriptional termination. RNAPII elongation factors progress transcription beyond sites of sppRNA formation, demonstrating RNAPII density near promoters represents a checkpoint for early transcriptional termination that governs full-length gene isoform expression.
Aging and the encoding of event changes: The role of neural activity pattern reinstatement
Authors: Stawarczyk David , Wahlheim Christopher N. , Etzel Joset A. , Snyder Abraham Z. , Zacks Jeffrey M. 
Published: October 2019

AbstractWhen encountering unexpected event changes, memories of relevant past experiences must be updated to form new representations. Current models of memory updating propose that people must first generate memory-based predictions to detect and register that features of the environment have changed, then encode the new event features and integrate them with relevant memories of past experiences to form configural memory representations. Each of these steps may be impaired in older adults. Using functional MRI, we investigated these mechanisms in healthy young and older adults. In the scanner, participants first watched a movie depicting everyday activities in a day of an actor’s life. They next watched a second nearly identical movie in which some scenes ended differently. Crucially, before watching the last part of each activity, the second movie stopped, and participants were asked to mentally replay how the activity previously ended. Three days later, participants were asked to recall the activities. Neural activity pattern reinstatement in medial temporal lobe (MTL) during the replay phase of the second movie was associated with detecting changes and with better memory for the original activity features. Reinstatements in posterior medial cortex (PMC) additionally predicted better memory for changed features. Compared to young adults, older adults showed a reduced ability to detect and remember changes, and weaker associations between reinstatement and memory performance. These findings suggest that PMC and MTL contribute to change processing by reinstating previous event features, and that older adults are less able to use reinstatement to update memory for changed features.
Map making: Constructing, combining, and inferring on abstract cognitive maps
Authors: Park Seongmin A. , Miller Douglas S. , Nili Hamed , Ranganath Charan , Boorman Erie D. 
Published: October 2019

ABSTRACTCognitive maps are thought to enable model-based inferences from limited experience that can guide novel decisions–a hallmark of behavioral flexibility. We tested whether the hippocampus (HC), entorhinal cortex (EC), and ventromedial prefrontal cortex (vmPFC)/medial orbitofrontal cortex (mOFC) organize abstract and discrete relational information into a cognitive map to guide novel inferences. Subjects learned the status of people in two separate unseen 2-D social hierarchies defined by competence and popularity piecemeal from binary comparisons, with each dimension learned on a separate day. Although only one dimension was ever behaviorally relevant, multivariate activity patterns in HC, EC and vmPFC/mOFC were linearly related to the Euclidean distance between people in the mentally reconstructed 2-D space. Hubs created unique comparisons between the two hierarchies, enabling inferences between novel pairs of people. We found that both behavior and neural activity in EC and vmPFC/mOFC reflected the Euclidean distance to the retrieved hub, which was reinstated in HC. These findings reveal how abstract and discrete relational structures are represented, combined, and enable novel inferences in the human brain.
Unmasking the tissue microecology of ductal carcinoma in situ with deep learning
Authors: Narayanan Priya Lakshmi , Ahmed Raza Shan E , Hall Allison H. , Marks Jeffrey R. , King Lorraine , West Robert B. , Hernandez Lucia , Dowsett Mitch , Gusterson Barry , Maley Carlo , Hwang E. Shelley , Yuan Yinyin 
Published: October 2019

AbstractDespite increasing evidence supporting the clinical relevance of tumour infiltrating lymphocytes (TILs) in invasive breast cancer, TIL spatial distribution pattern surrounding ductal carcinoma in situ (DCIS) and its association with progression is not well understood.To characterize the tissue microecology of DCIS, we designed and tested a new deep learning pipeline, UNMaSk (UNet-IM-Net-SCCNN), for the automated detection and simultaneous segmentation of DCIS ducts. This new method achieved the highest sensitivity and recall over cutting-edge deep learning networks in three patient cohorts, as well as the highest concordance with DCIS identification based on CK5 staining.Following automated DCIS detection, spatial tessellation centred at each DCIS duct created the boundary in which local ecology can be studied. Single cell identification and classification was performed with an existing deep learning method to map the distribution of TILs. In a dataset comprising grade 2-3 pure DCIS and DCIS adjacent to invasive cancer (adjacent DCIS), we found that pure DCIS cases had more TILs compared to adjacent DCIS. However, TILs co-localise significantly less with DCIS ducts in pure DCIS compared with adjacent DCIS, suggesting a more inflamed tissue ecology local to adjacent DCIS cases.Our experiments demonstrate that technological developments in deep convolutional neural networks and digital pathology can enable us to automate the identification of DCIS as well as to quantify the spatial relationship with TILs, providing a new way to study immune response and identify new markers of progression, thereby improving clinical management.