bluuebunny/crossref_metadata_2025_split huggingface dataset:
Returning scientists and the emergence of China’s science system
Authors: Cao Cong , Baas Jeroen , Wagner Caroline S , Jonkers Koen 
Published: November 2019

AbstractChina’s approach to developing a world-class science system includes a vigorous set of programmes to attract back Chinese researchers who have overseas training and work experience. No analysis is available to show the performance of these mobile researchers. This article attempts to close part of this gap. Using a novel bibliometric approach, we estimate the stocks of overseas Chinese and returnees from the perspective of their publication activities, albeit with some limitations. We show that the share of overseas Chinese scientists in the USA is considerably larger than that in the European Union. We also show that Chinese returnees publish higher impact work and continue to publish more and at the international level than domestic counterparts. Returnees not only tend to publish more, but they are instrumental in linking China into the global network. Indeed, returnees actively co-publish with researchers in their former host system, showing the importance of scientific social capital. Future research will examine the impact of length of stay, among other factors, on such impact and integration.
Multi-omic signatures identify pan-cancer classes of tumors beyond tissue of origin
Authors: Gonzalez-Reymundez Agustin , Vazquez Ana I. 
Published: November 2019

AbstractDespite recent advances in treatment, cancer continues to be one of the most lethal human maladies. One of the challenges of cancer treatment is the extreme diversity among seemingly identical tumors: while some tumors may have good prognosis and are treatable, others are quite aggressive, and may lack of effective therapies. Most of this variability comes from wide-spread mutations and epigenetic alterations. Using a novel omic-integration method, we have exploited this molecular information to re-classify tumors beyond the constraints of cell type. Eight novel tumor groups (C1-8) emerged, characterized by unique cancer signatures. C3 had better prognosis, genome stability, and immune infiltration. C2 and C5 had higher genome instability and poorer clinical outcomes. Remaining clusters were characterized by worse outcomes, along with higher genome instability. C1, C7, and C8 were upregulated for cellular and mitochondrial translation, and relatively low proliferation. C6 and C4 were also downregulated for cellular and mitochondrial translation, and had high proliferation rates. C4 was represented by copy losses on chromosome 6, and had the highest number of metastatic samples. C8 was characterized by copy losses on chromosome 11, having also the lowest lymphocytic infiltration rate. C6 had the lowest natural killer infiltration rate and was represented by copy gains of genes in chromosome 11. C7 was represented by copy gains on chromosome 6, and had the highest upregulation in mitochondrial translation. We believe that, since molecularly alike tumors could respond similarly to treatment, our results could inform therapeutic action.SignificanceCancer has been traditionally studied as a family of different diseases from different anatomical sites. Nevertheless, regardless of the tissue of origin, cancer can be characterized by molecular alterations on mechanisms controlling cell fate and progression. In this study, we integrate 33 cancer types and show the existence of eight clusters with unique genomic signatures and clinical characteristics, beyond the site of origin of the tumor. The study and treatment of cancer, based on predominant molecular features, rather than site of origin, can potentially aid in the discovery of novel therapeutic alternatives.
Evolutionary Origins of Recurrent Pancreatic Cancer
Authors: Sakamoto Hitomi , Attiyeh Marc A. , Gerold Jeffrey M. , Makohon-Moore Alvin P. , Hayashi Akimasa , Hong Jungeui , Kappagantula Rajya , Zhang Lance , Melchor Jerry , Reiter Johannes G. , Heyde Alexander , Bielski Craig M. , Penson Alexander , Chakravarty Debyani , O’Reilly Eileen M. , Wood Laura D. , Hruban Ralph H. , Nowak Martin A. , Socci Nicholas D. , Taylor Barry S. , Iacobuzio-Donahue Christine A. 
Published: November 2019

AbstractSurgery is the only curative option for Stage I/II pancreatic cancer, nonetheless most patients will recur after surgery and die of their disease. To identify novel opportunities for management of recurrent pancreatic cancer we performed whole exome or targeted sequencing of 10 resected primary cancers and matched intrapancreatic recurrences or distant metastases. We identified that adjuvant or first-line platinum therapy corresponds to an increased mutational burden of recurrent disease. Recurrent disease is enriched for mutations that activate Mapk/Erk and PI3K/AKT signaling and develops from a monophyletic or polyphyletic origin. Treatment induced genetic bottlenecks lead to a modified genetic landscape and subclonal heterogeneity for driver gene alterations in part due to intermetastatic seeding. In one patient what was believed to be recurrent disease was an independent (second) primary tumor. These findings advocate for combination therapies with immunotherapy and routine post-treatment sampling as a component of management of recurrent pancreatic cancer.
Non-Parametric Rank Statistics for Spectral Power and Coherence
Authors: Nasseroleslami Bahman , Dukic Stefan , Buxo Teresa , Coffey Amina , McMackin Roisin , Muthuraman Muthuraman , Hardiman Orla , Lowery Madeleine M. , Lalor Edmund C. 
Published: November 2019

AbstractDespite advances in multivariate spectral analysis of neural signals, the statistical inference of measures such as spectral power and coherence in practical and real-life scenarios remains a challenge. The non-normal distribution of the neural signals and presence of artefactual components make it difficult to use the parametric methods for robust estimation of measures or to infer the presence of specific spectral components above the chance level. Furthermore, the bias of the coherence measures and their complex statistical distributions are impediments in robust statistical comparisons between 2 different levels of coherence. Non-parametric methods based on the median of auto-/cross-spectra have shown promise for robust estimation of spectral power and coherence estimates. However, the statistical inference based on these non-parametric estimates remain to be formulated and tested. In this report a set of methods based on non-parametric rank statistics for 1-sample and 2-sample testing of spectral power and coherence is provided. The proposed methods were demonstrated and tested using simulated neural signals in different conditions. The results show that non-parametric methods provide robustness against artefactual components. Moreover, they provide new possibilities for robust 1-sample and 2-sample testing of the complex coherency function, including both the magnitude and phase, where existing methods fall short of functionality. The utility of the methods were further demonstrated by examples on experimental neural data. The proposed approach provides a new framework for non-parametric spectral analysis of digital signals. These methods are especially suited to neuroscience and neural engineering applications, given the attractive properties such as minimal assumption on distributions, statistical robustness, and the diverse testing scenarios afforded.
The Impact of Edema and Fiber Crossing on Diffusion MRI Metrics: DBSI vs. Diffusion ODF
Authors: Ye Zezhong , Gary Sam E. , Sun Peng , Mustafi Sourajit Mitra , Glenn George Russell , Yeh Fang-Cheng , Merisaari Harri , Huang Guo-Shu , Kao Hung-Wen , Lin Chien-Yuan , Wu Yu-Chien , Jensen Jens H. , Song Sheng-Kwei 
Published: November 2019

ABSTRACTPurposeDiffusion tensor imaging (DTI) has been employed for over two decades to noninvasively quantify central nervous system (CNS) diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of co-existing inflammation, edema, and crossing nerve fibers.MethodsWe employed a tissue phantom using fixed mouse trigeminal nerves coated with various amounts of agarose gel to mimic crossing fibers in the presence of vasogenic edema. Diffusivity measures derived by DTI and diffusion basis spectrum imaging (DBSI) were compared at increasing levels of simulated edema and degrees of fiber crossing. Further, we assessed the ability of DBSI, diffusion kurtosis imaging (DKI), generalized q-sampling imaging (GQI), q-ball imaging (QBI), and neurite orientation dispersion and density imaging (NODDI) to resolve fiber crossing, in reference to the gold standard angles measured from structural images.ResultsDTI-computed diffusivities and fractional anisotropy (FA) were significantly confounded by gelmimicked edema and crossing fibers. Conversely, DBSI calculated accurate diffusivities of individual fibers regardless of the extent of simulated edema and degrees of fiber crossing angles. Additionaly, DBSI accurately and consistently estimated crossing angles in various conditions of gel-mimicked edema when comparing with gold standard (r2=0.92, p=1.9×10−9, bias=3.9°). Small crossing angles and edema sinficantly impact dODF, making DKI, GQI and QBI less accurate in detecting and estimating fibers corrsing angles. Lastly, we demonstrate DBSI’s superiority over DTI for recovering and delineating white matter tracts in peritumoral edema for preoperative planning of surgical resection.ConclusionsDBSI is able to separate two crossing fibers and accurately recover their diffusivities in a complex environment characterized by increasing crossing angles and amounts of gel-mimicked edema. DBSI also indicated better angular resolution capability compared with DKI, QBI and GQI.
Enhancing senior high school student engagement and academic performance using an inclusive and scalable inquiry-based program
Authors: Huyer Locke Davenport , Callaghan Neal I. , Dicks Sara , Scherer Edward , Shukalyuk Andrey I. , Jou Margaret , Kilkenny Dawn M. 
Published: November 2019

AbstractThe multi-disciplinary nature of science, technology, engineering and math (STEM) careers often renders difficulty for high school students navigating from classroom knowledge to post-secondary pursuits. Discrepancies between the knowledge-based high school learning approach and the experiential approach of undergraduate studies leaves some students disillusioned by STEM. We present Discovery, a semester-long inquiry-focused learning model delivered by STEM graduate students in collaboration with high school educators, in the context of biomedical engineering. Entire classes of high school STEM students representing diverse cultural and socioeconomic backgrounds engaged in iterative, problem-based learning designed to emphasize critical thinking concomitantly within the secondary school and university environments. Assessment of grades and survey data suggested positive impact of this learning model on students’ STEM pursuits, notably in under-performing cohorts, as well as repeating cohorts that engage in the program on more than one occasion. Discovery presents a scalable platform blurring the divide between secondary and post-secondary learning, providing valuable learning opportunities and capturing cohorts of students that might otherwise be under-engaged in STEM.
Hat1-Dependent Lysine Acetylation Targets Diverse Cellular Functions
Authors: Agudelo Garcia Paula A. , Nagarajan Prabakaran , Parthun Mark R. 
Published: November 2019

ABSTRACTLysine acetylation has emerged as one of the most important post-translational modifications, regulating different biological processes. However, its regulation by lysine acetyltransferases is still unclear in most cases. Hat1 is a lysine acetyltransferase originally identified based on its ability to acetylate histones. Using an unbiased proteomics approach, we have determined how loss of Hat1 affects the mammalian acetylome. Hat1+/+and Hat1−/−mouse embryonic fibroblast (MEF) cells lines were grown in both glucose- and galactose-containing media, as Hat1 is required for growth on galactose and Hat1−/−cells exhibit defects in mitochondrial function. Following trypsin digestion of whole cell extracts, acetylated peptides were enriched by acetyllysine affinity purification and acetylated peptides were identified and analyzed by label-free quantitation. Comparison of the acetylome from Hat1+/+cells grown on galactose and glucose demonstrated that there are large carbon source-dependent changes in the mammalian acetylome where the acetylation of enzymes involved in glycolysis was the most affected. Comparisons of the acetylomes from Hat1+/+and Hat1−/−cells identified 65 proteins whose acetylation decreased by at least 2.5-fold in cells lacking Hat1. In Hat1−/−cells, acetylation of the auto regulatory loop of CBP was the most highly affected, decreasing by up to 20-fold. In addition to proteins involved in chromatin structure, Hat1-dependent acetylation was also found in a number of transcriptional regulators, including p53, and mitochondrial proteins. Hat1 mitochondrial localization suggests that it may be directly involved in the acetylation of mitochondrial proteins.
Assessment of the bovine uterus with endometritis using Doppler ultrasound
Authors: Mendonça Ribeiro Bruno Leonardo , de Souza Meira Júnior Enoch Brandão , Aleman Reyes Mario Augusto , Marques Eduardo Carvalho , de Castro Nassar Alessandra Figueiredo , Gregory Lilian 
Published: November 2019

ABSTRACTPostpartum uterine diseases such as metritis and endometritis are highly prevalent in dairy cows. These diseases negatively affect the reproductive performance and consequently economic activity. Cows in the puerperal period presenting endometritis may have alterations in the hemodynamics of the uterine tissue and the uterine arteries, which differ them from healthy cows. Therefore, this study aimed to use the Doppler ultrasonography to describe the hemodynamic changes in the uterus of cows showing endometritis diagnosed between 25 - 35 days postpartum. Eighty-nine Holstein Friesian females with 25 to 35 days postpartum were studied. Cows were assigned to two experimental groups, infected or not infected, according to the results of the endometrial cytology. Clinical examination, vaginoscopy, Doppler ultrasound and sample collection (saline solution was injected and recovered by endoscopie method aiming cytological and microbiological evaluation of the uterus) were also performed. Cows with endometritis had the cervix (P = 0.040) and the left horn (P = 0.020) increased compared to healthy cows. 78.6% of the endometritic cows showed abnormal uterine discharge, while 57.6% of healthy cows had this same condition (P = 0.0005). The spectral Doppler evaluation of the uterine arteries revealed no differences between groups. Bacillus spp., Trueperella pyogenes, Escherichia coli and Staphylococcus intermedius were the most isolated bacteria among samples. Higher score or increase of uterus vascularization of the endometrial Doppler was correlated with Trueperella pyogenes (P = 0.0003) and intrauterine heterogeneous content (P = 0.0047). Finally, mesometrial Doppler was correlated with endometrial Doppler (P < 0.001), uterine bacteria (P = 0.001) and intrauterine heterogeneous content (P = 0.049). Regarding the evolution of uterine alterations, Doppler ultrasonography provides fast results and is a lesser invasive technique such as uterus biopsie and endometrial citology and gives answers about fertility and uterus health.
Women’s brain aging: effects of sex-hormone exposure, pregnancies, and genetic risk for Alzheimer’s disease
Authors: de Lange Ann-Marie G. , Barth Claudia , Kaufmann Tobias , Maximov Ivan I. , van der Meer Dennis , Agartz Ingrid , Westlye Lars T. 
Published: November 2019

AbstractSex hormones such as estrogen fluctuate across the female lifespan, with high levels during reproductive years and natural decline during the transition to menopause. Women’s exposure to estrogen may influence their heightened risk of Alzheimer’s disease (AD) relative to men, but little is known about how it affects normal brain aging. Recent findings from the UK Biobank demonstrate less apparent brain aging in women with a history of multiple childbirths, highlighting a potential link between sex-hormone exposure and brain aging. We investigated endogenous and exogenous sex-hormone exposure, genetic risk for AD, and neuroimaging-derived biomarkers for brain aging in 16,854 middle to older-aged women. The results showed that as opposed to parity, higher cumulative sex-hormone exposure was associated with more evident brain aging, indicating that i) high levels of cumulative exposure to sex-hormones may have adverse effects on the brain, and ii) beneficial effects of pregnancies on the female brain are not solely attributable to modulations in sex-hormone exposure. In addition, for women using hormonal replacement therapy (HRT), starting treatment earlier was associated with less evident brain aging, but only in women with a genetic risk for AD. Genetic factors may thus contribute to how timing of HRT initiation influences women’s brain aging trajectories.
Characterisation of HIF-dependent alternative isoforms in pancreatic cancer
Authors: Markolin Philipp , Davidson Natalie , Hirt Christian K. , Chabbert Christophe D. , Zamboni Nicola , Schwank Gerald , Krek Wilhelm , Rätsch Gunnar 
Published: November 2019

AbstractIntra-tumor hypoxia is a common feature in many solid cancers. Although transcriptional targets of hypoxia-inducible factors (HIFs) have been well characterized, alternative splicing or processing of pre-mRNA transcripts which occurs during hypoxia and subsequent HIF stabilization is much less understood. Here, we identify HIF-dependent alternative splicing events after whole transcriptome sequencing in pancreatic cancer cells exposed to hypoxia with and without downregulation of the aryl hydrocarbon receptor nuclear translocator (ARNT), a protein required for HIFs to form a transcriptionally active dimer. We correlate the discovered hypoxia-driven events with available sequencing data from pan-cancer TCGA patient cohorts to select a narrow set of putative biologically relevant splice events for experimental validation. We validate a small set of candidate HIF-dependent alternative splicing events in multiple human cancer cell lines as well as patient-derived human pancreatic cancer organoids. Lastly, we report the discovery of a HIF-dependent mechanism to produce a hypoxia-dependent, long and coding isoform of the UDP-N-acetylglucosamine transporter SLC35A3.
Effects of N-Acetyl-Leucine and its enantiomers in Niemann-Pick disease type C cells
Authors: te Vruchte Danielle , Galione Anthony , Strupp Michael , Mann Michiko 
Published: November 2019

AbstractN-Acetyl-DL-Leucine is an acetylated derivative of the essential amino acid leucine and a racemate (1:1) of N-Acetyl-L-Leucine and N-Acetyl-D-Leucine enantiomers. Previous observational clinical studies have demonstrated that N-Acetyl-DL-Leucine is effective in improving ataxia in patients with Niemann-Pick disease type C (NPC), a lysosomal storage disorder characterized at the cellular level by increased relative volume of the endosomal/lysosomal system. In this study, we sought to further characterize the potential therapeutic benefit of N-acetyl-DL-leucine and its enantiomers for the treatment of NPC. We investigated the effectiveness of N-Acetyl-DL-Leucine, N-Acetyl-D-Leucine, and N-Acetyl-L-Leucine in reducing lysosomal volume in non-neuronal NPC1 cells using LysoTracker, a fluorescent dye that accumulates in acidic organelles. We report that both N-Acetyl-DL-Leucine and N-Acetyl-L-Leucine reduced relative lysosomal volume in NPC1-/- Chinese Hamster Ovary cells in a dose-dependent manner. Subsequently, we confirmed that N-Acetyl-L-Leucine was most effective at reducing relative lysosomal volumes in fibroblasts derived from NPC patients with severe disease (***p <0.001), followed by N-Acetyl-DL-Leucine (**p <0.01). Treatment with N-Acetyl-D-Leucine did not achieve statistical significance. Taken together, these results suggest that N-Acetyl-L-Leucine is the most effective enantiomer in correcting relative lysosomal volume in non-neuronal NPC cells, and support further research and development of the L-enantiomer.
Connecting omics signatures of diseases, drugs, and mechanisms of actions with iLINCS
Authors: Pilarczyk Marcin , Kouril Michal , Shamsaei Behrouz , Vasiliauskas Juozas , Niu Wen , Mahi Naim , Zhang Lixia , Clark Nicholas , Ren Yan , White Shana , Karim Rashid , Xu Huan , Biesiada Jacek , Bennett Mark F. , Davidson Sarah , Reichard John F , Roberts Kurt , Stathias Vasileios , Koleti Amar , Vidovic Dusica , Clarke Daniel J.B. , Schurer Stephan C. , Ma’ayan Avi , Meller Jarek , Medvedovic Mario 
Published: November 2019

AbstractThere are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Among these, iLINCS is unique in scope and versatility of the data provided and the analytics facilitated. iLINCS (http://ilincs.org) is an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates analysis of user-submitted omics signatures of diseases and cellular perturbations in the context of a large compendium of pre-computed signatures (>200,000), as well as mining and re-analysis of the large collection of omics datasets (>12,000), pre-computed signatures, and their connections. Analytics workflows driven by user-friendly interfaces enable users with only conceptual understanding of the analysis strategy to execute sophisticated analyses of omics signatures, such as systems biology analyses and interpretation of signatures, mechanism of action analysis, and signature-driven drug repositioning. In summary, iLINCS workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures.
The kinematics of cyclic human movement
Authors: Vieten Manfred M. , Weich Christian 
Published: November 2019

AbstractModels describing cyclic movement can roughly be divided into the categories theory or data driven. Theory driven models include anatomical and physiological aspects. They are principally suitable for answering questions about the reasons for movement characteristics. But, they are complicated and substantial simplifications do not allow generally valid results. Data driven models allow answering specific questions but lack the understanding of the general movement characteristic. With this paper we try a compromise not having to rely on anatomy, neurology and muscle function. We hypothesize a general kinematic description of cyclic human motion is possible without having to specify the movement generating processes, and still getting the kinematic right. The model proposed consisting of a superposition of six contributions – subject’s attractor, morphing, short time fluctuation, transient effect, control mechanism and sensor noise -, with characterizing numbers and random contributions. We test the model with data form treadmill running and stationary biking. Applying the model in form of a simulation results in good agreement between measured data and simulation values.