bluuebunny/crossref_metadata_2025_split huggingface dataset:
An open-source dataset of anti-VEGF therapy in diabetic macular oedema patients over four years & their visual outcomes
Authors: Kern Christoph , Fu Dun Jack , Huemer Josef , Faes Livia , Wagner Siegfried K. , Kortuem Karsten , Patel Praveen J. , Balaskas Konstantinos , Hamilton Robin , Sim Dawn A. , Keane Pearse A. 
Published: October 2019

ABSTRACTPURPOSETo evaluate visual acuity (VA) outcomes of intravitreal anti-vascular endothelial growth factor (VEGF) in diabetic macular oedema (DMO).METHODSIn this retrospective cohort study, electronic medical records for all patients undergoing intravitreal injections (IVI) in a tertiary referral centre between March 2013 and October 2018 were analysed. Treatment response in terms of visual acuity outcomes were reported for all eyes over a 4-year observation period.RESULTSOur cohort includes 2616 DMO eyes of 1965 patients over 48 months. Cox proportional hazards modelling identified injection number (hazard ratio [HR] = 1.18), male gender (HR = 1.13), and baseline VA (HR = 1.09) as independent predictors to reach a favorable visual outcome of more than 70 Early Treatment Diabetic Retinopathy Study (ETDRS) letters. Half of our cohort reached 70 letters 1.9 months after starting anti-VEGF therapy. Of those that reached 70 letters, 50% fell below 70 by 14.7 months.CONCLUSIONTo date, this is the largest single centre cohort study and over the longest observation period reporting on real-life outcomes of anti-VEGF in DMO. We have made an anonymised version of our dataset available on an open-source data repository as a resource for all clinical researchers globally.SYNOPSISUsing time-to-event analysis in patients receiving anti-VEGF for DMO: age, baseline visual acuity and injection number are independent predictors of visual outcomes.
Genetic profile and functional proteomics of anal squamous cell carcinoma: proposal for a molecular classification
Authors: Trilla-Fuertes Lucía , Ghanem Ismael , Gámez-Pozo Angelo , Maurel Joan , G-Pastrián Laura , Mendiola Marta , Peña Cristina , López-Vacas Rocío , Prado-Vázquez Guillermo , López-Camacho Elena , Zapater-Moros Andrea , Heredia Victoria , Cuatrecasas Miriam , García-Alfonso Pilar , Capdevila Jaume , Conill Carles , García-Carbonero Rocío , Ramos-Ruiz Ricardo , Fortes Claudia , Llorens Carlos , Nanni Paolo , Fresno Vara Juan Ángel , Feliu Jaime 
Published: October 2019

ABSTRACTBackgroundAnal squamous cell carcinoma is a rare tumor. Chemo-radiotherapy yields a 50% 3-year relapse-free survival rate in advanced anal cancer, so improved predictive markers and therapeutic options are needed.MethodsHigh-throughput proteomics and whole-exome sequencing were performed in 46 paraffin samples from anal squamous cell carcinoma patients. Hierarchical clustering was used to establish groupsde novo. Then, probabilistic graphical models were used to study the differences between groups of patients at the biological process level.ResultsA molecular classification into two groups of patients was established, one group with increased expression of proteins related to adhesion, T lymphocytes and glycolysis; and the other group with increased expression of proteins related to translation and ribosomes. The probabilistic graphical model showed that these two groups presented differences in metabolism, mitochondria, translation, splicing and adhesion processes. Additionally, these groups showed different frequencies of genetic variants in some genes, such asATM, SLFN11andDST. Finally, genetic and proteomic characteristics of these groups suggested the use of some possible targeted therapies, such as PARP inhibitors or immunotherapy.ConclusionsIn this study, a molecular classification of anal squamous cell carcinoma using high-throughput proteomics and whole-exome sequencing data was proposed. Moreover, differences between the two established groups suggested some possible therapies.
Trade Study of Population Age Groups for a Clinical Trial in Attention Deficit Hyperactivity Disorder
Authors: Lovinsand Dalton B. , Lodder Robert A. 
Published: October 2019

ABSTRACTADHD is a neurodevelopmental disorder characterized by difficulty paying attention, impulsivity, and hyperactivity that is treated by an array of different modalities in order to decrease functional impairment. Despite the variety of available pharmacologic treatment options and their widespread use, there still remains a strong need to create innovative therapies. Game Based Therapy (GBT) is a type of cognitive behavioral therapy that seeks to increase the efficacy of currently available pharmacological treatments through improving cognitive deficits and reducing the current dose of such treatments. At the University of Kentucky, a clinical trial was implemented to assess the effects of combining stimulant pharmacotherapy with the popular video game Minecraft as Game Based Therapy on ADHD symptoms in children ages 10-15. However, the low subject recruitment played a large role in the trial failing to produce conclusive data from that site.This trade study serves to address the difficulties of subject recruitment and determine an optimal population and location for future adoption of the clinical trial. Through statistical analysis of state, national, and survey data it was found that in Lexington, Kentucky, 18-21 year olds are the optimal population for future GBT with pharmacotherapy clinical trials.
Development of population and Bayesian models for applied use in patients receiving cefepime
Authors: Liu Jiajun , Neely Michael , Lipman Jeffrey , Sime Fekade , Roberts Jason , Kiel Patrick J , Avedissian Sean N. , Rhodes Nathaniel J. , Scheetz Marc H. 
Published: October 2019

AbstractUnderstanding exposures of cefepime, a β-lactam antibiotic, is crucial for developing regimens to achieve optimal exposure and improved clinical outcomes. This study sought to develop and evaluate a unified population pharmacokinetic model in both pediatric and adult patients receiving cefepime treatment. Multiple physiologically relevant models were fit to pediatric and adult subject data. To evaluate the final model performance, a withheld group of twelve pediatric and two separate adult populations were assessed. Seventy subjects with a total of 604 cefepime concentrations were included in this study. All adults (n=34) on average weighed 82.7 kg and displayed a mean creatinine clearance (CrCL) of 106.7 mL/min. All pediatric subjects (n=36) had mean weight and CrCL of 16.0 kg and 195.64 mL/min, respectively. A covariate-adjusted two compartment model described the observed concentrations well (population model R2, 87.0%; Bayesian model R2, 96.5%). In the evaluation subsets, the model performed similarly well (population R2, 84.0%; Bayesian R2, 90.2%). The identified model serves well for population dosing and as a Bayesian prior for precision dosing.Key pointsA unified cefepime population pharmacokinetic model has been developed from adult and pediatric patients and evaluates well in independent populations.When paired with real time beta-lactam assays, precision dosing approach will optimize drug exposure and improve clinical outcomes.
The interoceptive hippocampus: mouse brain endocrine receptor expression highlights a dentate gyrus (DG)–cornu ammonis (CA) challenge– sufficiency axis
Authors: Lathe Richard , Singadia Sheena , Jordan Crispin , Riedel Gernot 
Published: October 2019

AbstractThe primeval function of the mammalian hippocampus (HPC) remains uncertain. Implicated in learning and memory, spatial navigation, and neuropsychological disorders, evolutionary theory suggests that the HPC evolved from a primeval chemosensory epithelium. Internal sensing deficits in patients with HPC lesions argue that internal sensing may be conserved in higher vertebrates. We studied the expression of 250 endocrine receptors in mouse brain. Key findings are (i) the proportions and levels of endocrine receptor expression in the HPC are significantly higher than in all other comparable brain regions. (ii) Surprisingly, the distribution of endocrine receptor expression within mouse HPC was found to be highly structured: receptors signaling ‘challenge’ are segregated in dentate gyrus (DG), whereas those signaling ‘sufficiency’ are principally found in cornu ammonis (CA) regions. Selective expression of endocrine receptors in the HPC argues that internal sensing remains a core feature of hippocampal function. Further, we report that ligands of DG receptors predominantly inhibit both synaptic potentiation and neurogenesis, whereas CA receptor ligands conversely promote both synaptic potentiation and neurogenesis. These findings suggest that the hippocampus acts as an integrator of body status, extending its role in context-dependent memory encoding from ‘where’ and ‘when’ to ‘how I feel’. Implications for anxiety and depression are discussed.
Diffuse X-ray Scattering from Correlated Motions in a Protein Crystal
Authors: Meisburger Steve P. , Case David A. , Ando Nozomi 
Published: October 2019

AbstractProtein dynamics are integral to biological function, yet few techniques are sensitive to collective atomic motions. A long-standing goal of X-ray crystallography has been to combine structural information from Bragg diffraction with dynamic information contained in the diffuse scattering background. However, the origin of macromolecular diffuse scattering has been poorly understood, limiting its applicability. We present a detailed diffuse scattering map from triclinic lysozyme that resolves both inter- and intramolecular correlations. These correlations are studied theoretically using both all-atom molecular dynamics and simple vibrational models. Although lattice dynamics reproduce most of the diffuse pattern, protein internal dynamics, which include hinge-bending motions, are needed to explain the short-ranged correlations revealed by Patterson analysis. These insights lay the groundwork for animating crystal structures with biochemically relevant motions.
Frost and drought: effects of extreme weather events on stem carbon dynamics in a Mediterranean beech forest
Authors: D’Andrea Ettore , Rezaie Negar , Prislan Peter , Gričar Jozica , Muhr Jan , Collalti Alessio , Matteucci Giorgio 
Published: October 2019

SummaryThe effects of short-term extreme events on tree functioning and physiology are still rather elusive. European beech is one of the most sensitive species to late frost and water shortage. We investigated the intra-annual C dynamics in stems under such conditions.Wood formation and stem CO2efflux were monitored in a Mediterranean beech forest for three years (2015–2017), including a late frost (2016) and a summer drought (2017).The late frost reduced radial growth and, consequently, the amount of carbon fixed in the stem biomass by 80%. Stem carbon efflux in 2016 was reduced by 25%, which can be attributed to the reduction of effluxes due to growth respiration. Counter to our expectations, we found no effects of the 2017 summer drought on radial growth and stem carbon efflux.The studied extreme weather events had various effects on tree growth. Even though late spring frost had a devastating impact on beech radial growth in the current year, trees fully recovered in the following growing season, indicating high resilience of beech to this stressful event.
Nickel induced transcriptional changes persist post exposure through epigenetic reprograming
Authors: Jose Cynthia C , Wang Zhenjia , Tanwar Vinay Singh , Zhang Xiaoru , Zang Chongzhi , Cuddapah Suresh 
Published: October 2019

AbstractNickel is an occupational and environmental toxicant associated with a number of diseases in humans including pulmonary fibrosis, bronchitis and lung and nasal cancers. Our earlier studies showed that the nickel-exposure-induced genome-wide transcriptional changes, which persist even after the termination of exposure may underlie nickel pathogenesis. However, the mechanisms that drive nickel-induced persistent changes to the transcriptome remain elusive. To elucidate the mechanisms that underlie nickel induced long-term transcriptional changes, in this study, we examined the transcriptome and the epigenome of human lung epithelial cells during nickel exposure and after the termination of exposure. We identified two categories of persistently differentially expressed genes based on the timing of expression changes: i) the genes that were differentially expressed during nickel exposure; and ii) the genes that were differentially expressed only after the termination of nickel exposure. Interestingly, the majority of nickel-induced transcriptional changes occurred only after the termination of exposure. We found robust genome-wide alterations to the activating histone modification, H3K4me3, after the termination of nickel exposure, which coincided with the post-exposure gene expression changes. In addition, we found significant post-exposure alterations to the repressive histone modification, H3K27me3. By uncovering a new category of transcriptional and epigenetic changes, which occur only after the termination of exposure, this study sheds new light on the post-exposure effects of nickel and provides a novel understanding of the long-term deleterious consequences of nickel exposure on human health.
Soil microbial communities associated with giant sequoia: How does the world’s largest tree affect some of the world’s smallest organisms?
Authors: Carey Chelsea J. , Glassman Sydney I. , Bruns Thomas D. , Aronson Emma L. , Hart Stephen C. 
Published: October 2019

AbstractGiant sequoia (Sequoiadendron giganteum) is an iconic conifer that lives in relic populations on the western slopes of the California Sierra Nevada. In these settings it is unusual among the dominant trees in that it associates with arbuscular mycorrhizal fungi rather than ectomycorrhizal fungi. However, it is unclear whether differences in microbial associations extends more broadly to non-mycorrhizal components of the soil microbial community. To address this question we characterized microbiomes associated with giant sequoia and co-occurring sugar pine (Pinus lambertiana) by sequencing 16S and ITS1 of the bulk soil community at two groves with distinct parent material. We found tree-associated differences were apparent despite a strong grove effect. Bacterial/archaeal richness was greater beneath giant sequoia than sugar pine, with a unique core community that was double the size. The tree species also harbored compositionally distinct fungal communities. This pattern depended on grove but was associated with a consistently elevated relative abundance ofHygrocybespecies beneath giant sequoia. Compositional differences between host trees correlated with soil pH, calcium availability, and soil moisture. We conclude that the effects of giant sequoia extend beyond mycorrhizal mutualists to include the broader community, and that some but not all host tree differences are grove-dependent.
Bacterial community profiling highlights complex diversity and novel organisms in wildlife ticks
Authors: Egan Siobhon L. , Loh Siew-May , Banks Peter B. , Gillett Amber , Ahlstrom Liisa , Ryan Una M. , Irwin Peter J. , Oskam Charlotte L. 
Published: October 2019

AbstractTicks (Acari: Ixodida) transmit a greater variety of pathogens than any other blood-feeding group of arthropods. While numerous microbes have been identified inhabiting Australian Ixodidae, some of which are related to globally important tick-borne pathogens, little is known about the bacterial communities within ticks collected from Australian wildlife. In this study, 1,019 ticks were identified on 221 hosts spanning 27 wildlife species. Next-generation sequencing was used to amplify the V1-2 hypervariable region of the bacterial 16S rRNA gene from 238 ticks;Amblyomma triguttatum(n=6),Bothriocroton auruginans(n=11),Bothriocroton concolor(n=20),Haemaphysalis bancrofti(n=10),Haemaphysalis bremneri(n=4),Haemaphysalis humerosa(n=13), Haemaphysalis longicornis(n=4),Ixodes antechini(n=29),Ixodes australiensis(n=26),Ixodes fecialis(n=13),Ixodes holocyclus(n=37),Ixodes myrmecobii (n=1), Ixodes ornithorhynchi(n=10),Ixodes tasmani(n=51) andIxodes trichosuri(n=3). After bioinformatic analyses, over 14 million assigned bacterial sequences revealed the presence of recently described bacteria ‘CandidatusBorrelia tachyglossi’, ‘CandidatusNeoehrlichia australis’, ‘CandidatusNeoehrlichia arcana’ and ‘CandidatusEhrlichia ornithorhynchi’. Furthermore, three novel Anaplasmataceae species were identified in the present study including; aNeoehrlichiasp. inI. australiensisandI. fecialiscollected from quenda (Isoodon fusciventer) (Western Australia), anAnaplasmasp. from oneB. concolorfrom echidna (Tachyglossus aculeatus) (New South Wales), and anEhrlichiasp. from a singleI. fecialisparasitising a quenda (WA). This study highlights the diversity of bacterial genera harboured within wildlife ticks, which may prove to be of medical and/or veterinary importance in the future.
Integrating multi-omics data through deep learning for accurate cancer prognosis prediction
Authors: Chai Hua , Zhou Xiang , Zhang Zhongyue , Rao Jiahua , Zhao Huiying , Yang Yuedong 
Published: October 2019

AbstractBackgroundGenomic information is nowadays widely used for precise cancer treatments. Since the individual type of omics data only represents a single view that suffers from data noise and bias, multiple types of omics data are required for accurate cancer prognosis prediction. However, it is challenging to effectively integrate multi-omics data due to the large number of redundant variables but relatively small sample size. With the recent progress in deep learning techniques, Autoencoder was used to integrate multi-omics data for extracting representative features. Nevertheless, the generated model is fragile from data noises. Additionally, previous studies usually focused on individual cancer types without making comprehensive tests on pan-cancer. Here, we employed the denoising Autoencoder to get a robust representation of the multi-omics data, and then used the learned representative features to estimate patients’ risks.ResultsBy applying to 15 cancers from The Cancer Genome Atlas (TCGA), our method was shown to improve the C-index values over previous methods by 6.5% on average. Considering the difficulty to obtain multi-omics data in practice, we further used only mRNA data to fit the estimated risks by training XGboost models, and found the models could achieve an average C-index value of 0.627. As a case study, the breast cancer prognosis prediction model was independently tested on three datasets from the Gene Expression Omnibus (GEO), and shown able to significantly separate high-risk patients from low-risk ones (C-index>0.6, p-values<0.05). Based on the risk subgroups divided by our method, we identified nine prognostic markers highly associated with breast cancer, among which seven genes have been proved by literature review.ConclusionOur comprehensive tests indicated that we have constructed an accurate and robust framework to integrate multi-omics data for cancer prognosis prediction. Moreover, it is an effective way to discover cancer prognosis-related genes.
Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing
Authors: Stangl Christina , de Blank Sam , Renkens Ivo , Verbeek Tamara , Valle-Inclan Jose Espejo , González Rocio Chamorro , Henssen Anton G. , van Roosmalen Markus J. , Stam Ronald W. , Voest Emile E. , Kloosterman Wigard P. , van Haaften Gijs , Monroe Glen 
Published: October 2019

AbstractFusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508 fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.
Selective targeting of an oncogenic KRAS mutant allele by CRISPR/Cas9 induces efficient tumor regression
Authors: Gao Qianqian , Ouyang Wenjie , Kang Bin , Han Xu , Xiong Ying , Ding Renpeng , Li Yijian , Wang Fei , Huang Lei , Chen Lei , Wang Dan , Dong Xuan , Zhang Zhao , Li Yanshan , Ze Baichen , Hou Yong , Yang Huanming , Ma Yuanyuan , Gu Ying , Chao Cheng-chi 
Published: October 2019

AbstractBackgroundKRAS is one of the most frequently mutated oncogenes in human cancers, but its activating mutations have remained undruggable due to its picomolar affinity for GTP/GDP and its smooth protein structure resulting in the absence of known allosteric regulatory sites.ResultsWith the goal of treating mutated KRAS-driven cancers, two CRISPR systems, CRISPR-SpCas9 genome-editing system and transcription-regulating system dCas9-KRAB, were developed to directly deplete KRAS mutant allele or to repress its transcription in cancer cells, respectively, through guide RNA specifically targeting the mutant but not wild-type allele. The effect of in vitro proliferation and cell cycle on cancer cells as well as in vivo tumor growth was examined after delivery of Cas9 system. SpCas9 and dCas9-KRAB systems with sgRNA targeting the mutant allele both blocked the expression of mutant KRAS gene, leading to an inhibition of cancer cell proliferation. Local adenoviral injections using SpCas9 and dCas9-KRAB systems both suppressed tumor growth in vivo. The gene-depletion system (SpCas9) performed more effectively than the transcription-suppressing system (dCas9-KRAB) on tumor inhibition. Application of both Cas9 systems to wild-type KRAS tumor cells did not affect cell proliferation in vitro and in vivo. Furthermore, through bioinformatic analysis of 31555 SNP mutations of the top 20 cancer driver genes, we showed that our mutant-specific editing strategy could be extended to a list of oncogenic mutations with high editing potentials, and this pipeline can be applied to analyze the distribution of PAM sequence in the genome to survey the best targets for other editing purpose.ConclusionsWe successfully developed both gene-depletion and transcription-suppressing systems to specifically target an oncogenic mutant allele of KRAS which led to significant tumor regression. It provides a promising strategy for the treatment of tumors with driver gene mutations.