bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of disease course and remission in early seropositive rheumatoid arthritis: Results from the TACERA longitudinal cohort study
Authors:   RA-MAP Consortium, Tom Brian 
Published: March 2020

ABSTRACTBackgroundTo characterize disease course and remission in a longitudinal observational study of newly diagnosed, initially treatment naïve patients with seropositive rheumatoid arthritis (RA).MethodsPatients with early untreated seropositive RA were recruited from 28 UK centres. Multiple clinical and laboratory measures were collected every 3 months for up to 18 months. Disease activity was measured using DAS28-CRP and SDAI. Logistic regression models examined clinical predictors of 6-month remission and latent class mixed models characterized disease course.ResultsWe enrolled 275 patients of whom 267 met full eligibility and provided baseline data. According to SDAI definition, 24.3% attained 6-month remission. Lower baseline HAQ and SDAI predicted 6-month remission (p=0.002 and 0.021). Alcohol intake and baseline prescribing of methotrexate with a second DMARD (versus monotherapy without glucocorticoids) were also predictive. Three distinct SDAI trajectory subpopulations emerged; corresponding to an Inadequate Responder group (6.5%), and Higher and Lower Baseline Activity Responder groups (22.4% and 71.1%). Baseline HAQ and SF-36 MCS only distinguished these groups. Additionally a number of baseline clinical predictors correlated with disease activity severity within subpopulations. Beneficial effects of alcohol intake were found across subpopulations.ConclusionsThree distinct disease trajectory subpopulations were identified. Differential effects of functional and mental well-being, alcohol consumption and baseline RA medication prescribing on disease activity severity were found across subpopulations. Heterogeneity across trajectories cannot be fully explained by baseline clinical predictors. Biological markers collected early in disease course (within 6 months) may help patient management and to better target existing and novel therapies.
Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission
Authors: Kombe Ivy K. , Agoti Charles N. , Munywoki Patrick K. , Nokes D. James , Medley Graham F. 
Published: March 2020

AbstractBackgroundRespiratory syncytial virus (RSV) is responsible for a significant burden of acute respiratory illness in children under 5 years old. Prior to rolling out any vaccination program, identification of the source of infant infections could further guide vaccination strategies.MethodsWe extended a dynamic model calibrated at the individual host level initially fit to social-temporal data on shedding patterns to include whole genome sequencing data available at a lower sampling intensity.ResultsIn this study population of 493 individuals with 55 infants under the age of 1 year distributed across 47 households, we found that 52% of RSV-B and 60% of RSV-A cases arose from infection within the household. Forty-five percent of infant infections appeared to occur in the household, of which 68% were a result of transmission from a child aged between 2 and 13 years living in the same household as the infant.ConclusionThese results further highlight the importance of pre-school and school-aged children in RSV transmission, particularly the role they play in directly infecting the household infant. These age groups are a potential RSV vaccination target group.
Predicting cohort-specific cervical cancer incidence from population-based HPV prevalence surveys: a worldwide study
Authors: Schulte-Frohlinde Rosa , Georges Damien , Clifford Gary M. , Baussano Iacopo 
Published: March 2020

AbstractBackgroundPredictions of cervical cancer burden and impact of control measures are often modelled from HPV prevalence. However, predictions could be improved by data on time between prevalent HPV detection and cervical cancer occurrence.MethodsBased upon high-risk (HR) HPV prevalence and cervical cancer incidence in the same birth cohorts from 17 worldwide locations, and informed by individual-level data on age at HR HPV detection and on sexual debut, we built a mixed model to predict cervical cancer incidence up to 14 years following prevalent HR HPV detection.FindingsCervical cancer incidence increased significantly during the 14 years following HR HPV detection in women <35 years, e.g. from 0·02 (95% CI 0·003–0·06) per 1000 within 1 year to 2·8 (1·2–6·5) at 14 years for unscreened women, but remained relatively constant following prevalent HR HPV detection above 35 years, e.g. from 5·4 (2·5–11) per 1000 within 1 year to 6·4 (2·4–17·1) at 14 years for unscreened HR HPV positive women aged 45–54 years. Age at sexual debut was a significant modifier of cervical cancer incidence in HR HPV positive women aged <25, but less so at older ages, whereas screening was a modifier in women ≥35 years. Lastly, we predicted annual number and incidence of cervical cancer in ten additional IARC HPV prevalence survey locations without representative cancer incidence data.InterpretationThese findings can inform cervical cancer control programmes, particularly in settings without cancer registries, as they allow prediction of future cervical cancer burden from population-based surveys of HPV prevalence.FundingBill & Melinda Gates Foundation; Canadian Institutes of Health Research.
Epidemiological and clinical characteristics of COVID-19 in adolescents and young adults
Authors: Liao Jiaqiang , Fan Shibing , Chen Jing , Wu Jianglin , Xu Shunqing , Guo Yuming , Li Chunhui , Zhang Xianxiang , Wu Chuansha , Mou Huaming , Song Chenxi , Li Feng , Wu Guicheng , Zhang Jingjing , Guo Lian , Liu Huawen , Lv Jinglong , Xu Lixin , Lang Chunhui 
Published: March 2020

AbstractBackgroundAdolescents and young adults might play a key role in the worldwide spread of Coronavirus Disease 2019 (COVID-19), because they are more involved in overseas studying, business, working, and travelling. However, the epidemiological and clinical characteristics of them are still unknown.MethodsWe collected data of 46 confirmed COVID-19 patients aged 10 to 35 years from the study hospital. The demographics, epidemiological, and clinical data were collected. Several key epidemiological parameters, the asymptomatic cases and transmission to their family members and the clinical characteristics at admission, and during treatment were summarized.RESULTSOf 46 confirmed patients, 14 patients (47.3%) were aged from 10 to 24 years, and 24 (52.7%) patients were male. The mean incubation period for symptomatic cases was 6.6 days (95% confidence interval (CI) 4.4 - 9.6). The median serial interval was 1.9 days (95% CI 0.4 - 6.2). Three of asymptomatic cases showed the transmission to their family members. Only 1 patient was identified as severe cases at admission. The common symptoms at admission were dry cough (34, 91.0%), and fever (29, 69.0%). Nearly 60% of the patients had showed ground-glass opacity by chest CT findings. Three patients developed acute kidney injury during treatment. Majority of patients (78.3%) were discharged by the end of the follow-up.ConclusionsThe adolescent and young adult patients of COVID-19 had a long incubation period, and a short serial interval. The transmission to their family contactors occurred in asymptomatic cases. Few of the study patients have developed complications during treatment.
Small Molecule Targeting IRES Domain Inhibits Enterovirus 71 Replication via an Allosteric Mechanism that Stabilizes a Ternary Complex
Authors: Davila-Calderon Jesse , Patwardhan Neeraj , Chiu Liang-Yuan , Sugarman Andrew , Cai Zhengguo , Penutmutchu Srinivasa R. , Li Mei-Ling , Brewer Gary , Hargrove Amanda E. , Tolbert Blanton S. 
Published: March 2020

AbstractWe herein report an RNA-targeting antiviral small molecule that reduces replication of the human enterovirus 71 (EV71) via stabilization of an inhibitory small molecule-RNA-protein ternary complex. The EV71 virus poses serious threats to human health, particularly in regions of Southeast Asia, and no FDA approved drugs or vaccines are available. We first screened an RNA-biased small molecule library using a peptide-displacement assay to identify ligands for the stem loop II structure of the EV71 internal ribosomal entry site, which was previously shown to impact viral translation and replication. One ligand, DMA-135, decreased viral translation and replication in cell-based studies in a dose-dependent manner with no significant toxicity. Structural, biophysical, and biochemical characterization support an allosteric mechanism in which DMA-135 induces a conformational change in the RNA structure that stabilizes a ternary complex with the AUF1 protein that then represses translation. This mechanism was further supported by pull-down experiments in cell culture. These detailed studies establish enterovirus RNA structures as promising drug targets while revealing an approach and mechanism of action that should be broadly applicable to functional RNA targeting.
The superoxide dismutase mimetic GC4419 enhances tumor killing when combined with stereotactic ablative radiation
Authors: Sishc Brock J. , Ding Lianghao , Heer Collin , Saha Debabrata , Spitz Douglas R. , Story Michael D. 
Published: March 2020

AbstractThe penta-aza macrocyclic manganese compound GC4419 is in phase 3 clinical trials as a modifier of mucositis in H&N cancer treated by radio-chemotherapy based upon its properties as a superoxide dismutase mimetic. In studies to address the potential for tumor radioprotection, a significant anti-tumor effect was identified in tumors generated from the non-small cell lung cancer (NSCLC) cell line H1299, when GC4419 was combined with radiation. This effect was directly related to the size of the radiation dose as demonstrated by greater efficacy in tumor growth delay when biologically equivalent irradiation regimens using a limited number of dose fractions was substantially more effective compared to regimens where the fraction number was higher and dose per fraction decreased. Furthermore, a TCD50 assay using H1299 tumors that tested the combination of GC4419 with radiation revealed a Dose Enhancement Factor of 1.67. Based upon these results the hypothesis that GC4419 was generating cytotoxic levels of hydrogen peroxide during the superoxide dismutation process. Peroxide flux did increase in cells exposed to GC4419 as did the expression of the oxidative stress markers 4-HNE and 3-NT. H1299 cells that overexpressed catalase were then challenged as tumors by the combination of radiation and GC4419 and the tumoricidal effect was nearly eliminated. The enhanced radiation response was not specific to NSCLC as similar findings were observed in human head and neck squamous cell carcinoma and pancreatic ductal adenocarcinoma xenografts. RNA sequencing analysis revealed that GC4419, in addition to generating high levels of hydrogen peroxide in irradiated cells, alters inflammatory and differentiation signaling in the tumor following irradiation. Together, these findings provide abundant evidence that the radioprotector GC4419 has dual functionality and will increase tumor response rates when combined with agents that generate high levels of superoxide like stereotactic ablative body radiotherapy (SAbR). Combining SAbR with GC4419 may be an effective strategy to enhance tumor response in general but may also allow for fully potent radiation doses to tumors that might not necessarily be able to tolerate such doses. The potential for protection of organs at risk may also be exploitable.
Detection of Penicillin G Produced byPenicillium chrysogenumKF 425 in Vivo with Raman Microspectroscopy and Multivariate Curve Resolution-Alternating Least Squares Methods
Authors: Horii Shumpei , Ando Masahiro , Samuel Ashok Z. , Take Akira , Nakashima Takuji , Matsumoto Atsuko , Takahashi Yōko , Takeyama Haruko 
Published: March 2020

ABSTRACTRaman microspectroscopy is a minimally invasive technique that can identify molecular structure without labeling. In this study, we demonstrate in vivo detection of the bioactive compound penicillin G insidePenicillium chrysogenumKF425 fungus cells. Highly overlapped spectroscopic signatures acquired using Raman microspectroscopic imaging are analyzed using a multivariate curve resolution-alternating least squares (MCR-ALS) method to extract the pure spectra of individual molecular constituents. In addition to detecting multiple constituents such as proteins and lipids, we observe the subcellular localization of penicillin G like granule particle inside the fungus body. To date, there have been no reports of direct visualization of intracellular localization of penicillin G. The methodology we present in this article is expected to be applied as a screening tool for the production of bioactive compounds by microorganisms.
Subventricular zone adult mouse neural stem cells and human glioblastoma stem cells require insulin receptor for self-renewal
Authors: Chidambaram Shravanthi , Rothbard Deborah , Deshpande Kaivalya , Cajuste Yvelanda , Snyder Kristin M. , Fajardo Eduardo , Fiser Andras , Tapinos Nikos , Levison Steven W. , Wood Teresa L. 
Published: March 2020

SummaryThe insulin receptor (IR) is an evolutionarily conserved signaling protein that regulates development and cellular metabolism. IR signaling regulates neurogenesis inDrosophila; however, a specific role for the IR in maintaining adult neural stem cells (NSCs) in mammals has not been investigated. We show that conditionally deleting the IR reduces adult NSCs of the subventricular zone by ∼70% accompanied by a corresponding increase in progenitors. IR deletion produced hyposmia due to aberrant olfactory bulb neurogenesis. Interestingly, hippocampal neurogenesis was not perturbed nor were hippocampal dependent behaviors. Highly aggressive proneural and mesenchymal glioblastomas (GBMs) had high IR/insulin-like growth factor (IGF) pathway gene expression, and isolated glioma stem cells had an aberrantly high ratio of IR:IGF1R receptors. Moreover, IR knockdown inhibited proneural and mesenchymal GBM tumorsphere growth. Altogether, these data demonstrate that the IR is essential for a subset of normal NSCs as well as for brain tumor cancer stem cell self-renewal.
Variability in mitochondrial import, mitochondrial health and mtDNA copy number using Type II and Type V CRISPR effectors
Authors: Antón Zuriñe , Mullally Grace , Ford Holly , van der Kamp Marc W. , Szczelkun Mark D. , Lane Jon D. 
Published: March 2020

ABSTRACTCurrent methodologies for targeting the mitochondrial genome for basic research and/or therapeutic strategy development in mitochondrial diseases are restricted by practical limitations and technical inflexibility. The development of a functional molecular toolbox for CRISPR-mediated mitochondrial genome editing is therefore desirable, as this could enable precise targeting of mtDNA haplotypes using the precision and tuneability of CRISPR enzymes; however, published reports of “MitoCRISPR” systems have, to date, lacked reproducibility and independent corroboration. Here, we have explored the requirements for a functional MitoCRISPR system in human cells by engineering several versions of CRISPR nucleases, including the use of alternative mitochondrial protein targeting sequences and smaller paralogues, and the application of gRNA modifications that reportedly induce mitochondrial import. We demonstrate varied mitochondrial targeting efficiencies and influences on mitochondrial dynamics/function of different CRISPR nucleases, withLachnospiraceaebacterium ND2006 (Lb) Cas12a being better targeted and tolerated than Cas9 variants. We also provide evidence of Cas9 gRNA association with mitochondria in HeLa cells and isolated yeast mitochondria, even in the absence of a targeting RNA aptamer. Finally, we present evidence linking mitochondrial-targeted LbCas12a/crRNA with increased mtDNA copy number dependent upon DNA binding and cleavage activity. We discuss reproducibility issues and the future steps necessary if MitoCRISPR is to be realised.
Single-chain lanthanide luminescence biosensors for cell-based imaging and screening of protein-protein interactions
Authors: Chen Ting , Pham Ha T. , Mohamadi Ali , Miller Lawrence W. 
Published: March 2020

ABSTRACTResearch tools that enable imaging or analysis of protein-protein interactions (PPIs) directly within living cells provide unique and valuable biological insights and can also aid drug discovery efforts. Here, we present lanthanide-based, Förster resonance energy transfer (lanthanide-based FRET, or LRET) biosensors for time-gated luminescence (TGL) imaging or multiwell plate analysis of PPIs. Polypeptide chains comprised of an alpha helical linker flanked by a Tb(III) complex, GFP and two binding domains exhibit large differences in long-lifetime, Tb(III)-to-GFP LRET-sensitized emission between open (unbound) and closed (bound) states. We used TGL microscopy to image ca. 500% increases in Tb(III)-to-GFP LRET following rapamycin addition to NIH 3T3 cells that expressed biosensors bearing FKBP12 and the rapamycin binding domain of m-Tor (FRB) at each terminus. Much larger signal changes, up to ca. 2500%, were observed when cells were grown in 96-well or 384-well plates and analyzed using a TGL plate reader. We also measured the interaction of p53 and HDM2 and its inhibition within intact HeLa cells grown in 96-well plates and estimated a z’-factor of 0.5 for the assay. The modular design and high dynamic range of Tb(III)-based LRET biosensors will facilitate versatile imaging and cell-based screening of PPIs.
SCENITH: A flow cytometry based method for functional profiling energy metabolism with single cell resolution
Authors: Argüello Rafael J. , Combes Alexis J. , Char Remy , Bousiquot Evens , Gigan Julien-Paul , Camosseto Voahirana , Samad Bushra , Tsui Jessica , Yan Peter , Boissonneau Sebastien , Figarella-Branger Dominique , Tabouret Emeline , Gatti Evelina , Krummel Matthew F. , Pierre Philippe 
Published: March 2020

AbstractEnergetic metabolism reprogramming is critical for cancer and immune responses. Current methods to functionally profile the global metabolic capacities and dependencies of cells are performed in bulk. We designed a simple method for complex metabolic profiling called SCENITH, for Single Cell ENergetIc metabolism by profilIng Translation inHibition. SCENITH allows for the study of metabolic responses in multiple cell types in parallel by flow cytometry. SCENITH is designed to perform metabolic studies ex vivo, particularly for rare cells in whole blood samples, avoiding metabolic biases introduced by culture media. We analyzed myeloid cells in solid tumors from patients and identified variable metabolic profiles, in ways that are not linked to their lineage nor their activation phenotype. SCENITH ability to reveal global metabolic functions and determine complex and linked immune-phenotypes in rare cell subpopulations will contribute to the information needed for evaluating therapeutic responses or patient stratification.
The Demographic History of Micro-endemics: Have Rare Species Always Been Rare?
Authors: Helmstetter Andrew J. , Cable Stuart , Rakotonasolo Franck , Rabarijaona Romer , Rakotoarinivo Mijoro , Eiserhardt Wolf L. , Baker William J. , Papadopulos Alexander S.T. 
Published: March 2020

AbstractExtinction has increased as human activities impact ecosystems. Conservation assessments for the IUCN red list are a fundamental tool in aiding the prevention of further extinction, yet, relatively few species have been thoroughly assessed. To increase the efficiency of assessments, novel approaches are needed to highlight threatened species that are currently data deficient. Many Madagascan plant species currently have extremely narrow ranges, but this may not have always been the case. To assess this, we used high-throughput DNA sequencing for 2-5 individuals of each species - reflecting the paucity of samples available for rare species. We estimated effective population size (Ne) for each species and compared this to census population(Nc) sizes when known. In each case,Newas an order of magnitude larger thanNc– a signature of rapid, recent population decline. We then estimated the demographic history of each species, tracking changes inNeover time. Five out of ten species displayed significant population declines towards the present (68–90% decreases). Our results for palm trees indicate that it is possible to predict extinction risk, particularly in the most threatened species. We performed simulations to show that our approach has the power to detect population decline during the Anthropocene, but performs less well when less data is used. Similar declines to those in palms were observed in data deficient species or those assessed as of least concern. These analyses reveal that Madagascar’s narrow endemics were not always rare, having experienced rapid decline in their recent history. Our approach offers the opportunity to target species in need of conservation assessment with little prior information, particularly in regions where human modification of the environment has been rapid.SummaryCurrent IUCN conservation assessment methods are reliant on observed declines in species population and range sizes over the last one hundred years, but for the majority of species this information is not available. We used a population genetic approach to reveal historical demographic decline in the rare endemic flora of Madagascar. These results show that it is possible to predict extinction risk from demographic patterns inferred from genetic data and that destructive human influence is likely to have resulted in the very high frequency of narrow endemics present on the island. Our approach will act as an important tool for rapidly assessing the threatened status of poorly known species in need of further study and conservation, particularly for tropical flora and fauna.
A Deep Learning Approach for Tissue Spatial Quantification and Genomic Correlations of Histopathological Images
Authors: Lu Zixiao , Zhan Xiaohui , Wu Yi , Cheng Jun , Shao Wei , Ni Dong , Han Zhi , Zhang Jie , Feng Qianjin , Huang Kun 
Published: March 2020

AbstractEpithelial and stromal tissue are components of the tumor microenvironment and play a major role in tumor initiation and progression. Distinguishing stroma from epithelial tissues is critically important for spatial characterization of the tumor microenvironment. We propose an image analysis pipeline based on a Convolutional Neural Network (CNN) model to classify epithelial and stromal regions in whole-slide images. The CNN model was trained using well-annotated breast cancer tissue microarrays and validated with images from The Cancer Genome Atlas (TCGA) project. Our model achieves a classification accuracy of 91.02%, which outperforms other state-of-the-art methods. Using this model, we generated pixel-level epithelial/stromal tissue maps for 1,000 TCGA breast cancer slide images that are paired with gene expression data. We subsequently estimated the epithelial and stromal ratios and performed correlation analysis to model the relationship between gene expression and tissue ratios. Gene Ontology enrichment analyses of genes that were highly correlated with tissue ratios suggest the same tissue was associated with similar biological processes in different breast cancer subtypes, whereas each subtype had its own idiosyncratic biological processes governing the development of these tissues. Taken all together, our approach can lead to new insights in exploring relationships between image-based phenotypes and their underlying genomic data and biological processes for all types of solid tumors.