bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trochleaectomy: An Effective Treatment of Trochlear Pain in Monocular Patients
Authors: Mettu Pradeep , Mancini Ronald , Friedman Deborah I. , Garrity James A. 
Published: February 2020

Background:
Conventional treatment options for trochlear pain arising from trochleitis or primary trochlear headache include oral anti-inflammatory medications and/or local injection of corticosteroids and local anesthetic. Trochleaectomy is an additional option to consider for monocular patients with intractable trochlear pain.

Methods:
We report 3 patients undergoing trochleaectomy for refractory trochlear pain syndromes.

Results:
Trochleaectomy resulted in resolution of their periocular discomfort.

Conclusions:
Trochleaectomy is an effective procedure to treat trochlear pain syndrome in functionally monocular patients.
Generation of antibodies against COVID-19 virus for development of diagnostic tools
Authors: Li Maohua , Jin Ronghua , Peng Ya , Wang Cuiyan , Ren Wenlin , Lv Fudong , Gong Sitao , Fang Feng , Wang Qianyun , Li Jianli , Shen Tong , Sun Hunter , Zhou Lei , Cui Yali , Song Hao , Sun Le 
Published: February 2020

ABSTRACTThe COVID-19 China coronavirus started in Dec 2019 was challenged by the lack of accurate serological diagnostic tool for this deadly disease to quickly identify and isolate the infected patients. The generation of COVID-19-specific antibodies is essential for such tasks. Here we report that polyclonal and monoclonal antibodies were generated by immunizing animals with synthetic peptides corresponding to different areas of Nucleoprotein (N) of COVID-19. The specificities of the COVID-19 antibodies were assessed by Western Blot analysis against NPs from COVID-19, MERS and SARS. Antibodies were used for immunohistochemistry staining of the tissue sections from COVID-19 infected patient, as a potential diagnostic tool. A Sandwich ELISA kit was quickly assembled for quantitation of the virus/NP of COVID-19 concentrations in the vaccine preparations. Development of POCT is also aggressively undergoing.
Real-time monitoring the transmission potential of COVID-19 in Singapore, February 2020
Authors: Tariq Amna , Lee Yiseul , Roosa Kimberlyn , Blumberg Seth , Yan Ping , Ma Stefan , Chowell Gerardo 
Published: February 2020

AbstractBackgroundThe ongoing COVID-19 epidemic that spread widely in China since December 2019 is now generating local transmission in multiple countries including Singapore as of February 27, 2020. This highlights the need to monitor in real time the transmission potential of COVID-19. In Singapore, four major COVID-19 case clusters have emerged thus far.MethodsHere we estimate the effective reproduction number, Rt, of COVID-19 in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis.ResultsThe effective reproduction number peaked with a mean value ∼1.1 around February 2nd, 2020 and declined thereafter. As of February 27th, 2020, our most recent estimate of Rtis at 0.5 (95% CI: 0.2,0.7) while an estimate of the overall R based on cluster size distribution is at 0.7 (95% CI: 0.5, 0.9).ConclusionThe trajectory of the reproduction number in Singapore underscore the significant effects of containment efforts in Singapore while at the same time suggest the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission.
Neuroimaging-based Individualized Prediction of Cognition and Behavior for Mental Disorders and Health: Methods and Promises
Authors: Sui Jing , Jiang Rongtao , Bustillo Juan , Calhoun Vince 
Published: February 2020

AbstractThe neuroimaging community has witnessed a paradigm shift in biomarker discovery from using traditional univariate brain mapping approaches to multivariate predictive models, allowing the field to move towards a translational neuroscience era. Regression-based multivariate models (hereafter “predictive modeling”) provide a powerful and widely-used approach to predict human behavior with neuroimaging features. These studies maintain a focus on decoding individual differences in a continuously behavioral phenotype from neuroimaging data, opening up an exciting opportunity to describe the human brain at the single-subject level. In this survey, we provide an overview of recent studies that utilize machine learning approaches to identify neuroimaging predictors over the past decade. We first review regression-based approaches and highlight connectome-based predictive modeling (CPM), which has grown in popularity in recent years. Next, we systematically describe recent representative studies using these tools in the context of cognitive function, symptom severity, personality traits and emotion processing. Finally, we highlight a few challenges related to combining multimodal data, longitudinal prediction, external validations and the employment of deep learning methods that have emerged from our review of the existing literature, as well as present some promising and challenging future directions.
Conjunctival polymerase chain reaction-tests of 2019 novel coronavirus in patients in Shenyang, China
Authors: Xu Li , Zhang Xinyue , Song Wei , Sun Baijun , Mu Jinping , Wang Bing , Wang Zhiqian , Cao Yehong , Dong Xue 
Published: February 2020

AbstractPurposeThe 2019 novel coronavirus(COVID-19) mainly transmitted by person-to-person through inhalation of respiratory droplets. We report the laboratory results of conjunctival PCR-tests and some clinical features of these patients in shenyang China.DesignThis is a cross-sectional non-randomized studySubjectsThe study include 14 confirmly diagnosed cases, 16 suspected cases and some medical observed patients.MethodsAll patients with diagnosed and suspected COVID-19 were admitted to a designated hospital in Shenyang, China. We collected conjunctival samples of these patients to do the laboratory tests by real time RT-PCR. Medical observed patients were enrolled if they had clinical symptoms. Then we analysed the PCR results and clinical data from eletronic medical records in order to find some relationships.Main Outcome MeasuresClinical condition and PCR results. of conjunctival swabs compared with other specimensResultsOne of the identified case coverted from suspected case without typical clinical symptoms. Twenty-two medical observed cases were removed because none of them converted to identified cases. One of the suspected converted to identified case recently. The included cases in our study are imported cases with less underlying diseases and the severity of their infection was relatively moderate. All the conjunctival results of PCR-test were negative. Two cases had typical clinical symptoms but were finally confirmed by repeated pharynxswabtests.ConclusionConjunctiva may be a transmission way of COVID-19. And ocular conjunctival swabs in combination with PCR test could be a non-invasive, convenient and feasible diagnostic method for identifying the infection of COVID-19. Emphasis on the false-negative results is vital.
Bacteria Use Structural Imperfect Mimicry To Hijack The Host Interactome
Authors: de Groot Natalia Sanchez , Burgas Marc Torrent 
Published: February 2020

ABSTRACTBacteria use protein-protein interactions to infect their hosts and hijack fundamental pathways, which ensures their survival and proliferation. Hence, the infectious capacity of the pathogen is closely related to its ability to interact with host proteins. Here, we show that hubs in the host-pathogen interactome are isolated in the pathogen network by adapting the geometry of the interacting interfaces. An imperfect mimicry of the eukaryotic interfaces allows pathogen proteins to actively bind to the host’s target while preventing deleterious effects on the pathogen interactome. Understanding how bacteria recognize eukaryotic proteins may pave the way for the rational design of new antibiotic molecules.
Predicting antibiotic-associated virulence ofPseudomonas aeruginosausing anex-vivolung biofilm model
Authors: Hassan Marwa M. , Harrington Niamh E. , Sweeney Esther , Harrison Freya 
Published: February 2020

AbstractBackgroundBacterial biofilms are known to have high antibiotic tolerance which directly affects clearance of bacterial infections in people with cystic fibrosis (CF). Current antibiotic susceptibility testing methods are either based on planktonic cells or do not reflect the complexity of biofilmsin vivo. Consequently, inaccurate diagnostics affect treatment choice, preventing bacterial clearance and potentially selecting for antibiotic resistance. This leads to prolonged, ineffective treatment.MethodsIn this study, we use anex-vivolung biofilm model to study antibiotic tolerance and virulence ofPseudomonas aeruginosa. Sections of pig bronchiole were dissected, prepared and infected with clinical isolates ofP. aeruginosaand incubated in artificial sputum media to form biofilms, as previously described. Then, lung-associated biofilms were challenged with antibiotics, at therapeutically relevant concentrations, before their bacterial load and virulence were quantified and detected, respectively.ResultsThe results demonstrated minimal effect on the bacterial load with therapeutically relevant concentrations of ciprofloxacin and meropenem, with the later causing an increased production of proteases and pyocyanin. A combination of meropenem and tobramycin did not show any additional decrease in bacterial load but demonstrated a slight decrease in total proteases and pyocyanin production.ConclusionsWe demonstrate a realistic model for understanding antibiotic resistance and tolerance in biofilms clinically and for molecules screening in anti-biofilm drug development.P. aeruginosashowed high levels of antibiotic tolerance, with minimal effect on bacterial load and increased proteases production, which could negatively affect lung function. This may potentially contribute to exacerbations and eventual lung failure.
Synthesis of diagnostic quality cancer pathology images
Authors: Levine Adrian B. , Peng Jason , Farnell David , Nursey Mitchell , Wang Yiping , Naso Julia R. , Ren Hezhen , Farahani Hossein , Chen Colin , Chiu Derek , Talhouk Aline , Sheffield Brandon , Riazy Maziar , Ip Philip P. , Parra-Herran Carlos , Mills Anne , Singh Naveena , Tessier-Cloutier Basile , Salisbury Taylor , Lee Jonathan , Salcudean Tim , Jones Steven J.M. , Huntsman David G. , Gilks C. Blake , Yip Stephen , Bashashati Ali 
Published: February 2020

ABSTRACTDeep learning-based computer vision methods have recently made remarkable breakthroughs in the analysis and classification of cancer pathology images. However, there has been relatively little investigation of the utility of deep neural networks to synthesize medical images. In this study, we evaluated the efficacy of generative adversarial networks (GANs) to synthesize high resolution pathology images of ten histological types of cancer, including five cancer types from The Cancer Genome Atlas (TCGA) and the five major histological subtypes of ovarian carcinoma. The quality of these images was assessed using a comprehensive survey of board-certified pathologists (n = 9) and pathology trainees (n = 6). Our results show that the real and synthetic images are classified by histotype with comparable accuracies, and the synthetic images are visually indistinguishable from real images. Furthermore, we trained deep convolutional neural networks (CNNs) to diagnose the different cancer types and determined that the synthetic images perform as well as additional real images when used to supplement a small training set. These findings have important applications in proficiency testing of medical practitioners and quality assurance in clinical laboratories. Furthermore, training of computer-aided diagnostic systems can benefit from synthetic images where labeled datasets are limited (e.g., rare cancers). We have created a publicly available website where clinicians and researchers can attempt questions from the image survey athttp://gan.aimlab.ca/.
A comprehensive influenza reporter virus panel for high-throughput deep profiling of neutralizing antibodies
Authors: Creanga Adrian , Gillespie Rebecca A. , Fisher Brian E. , Andrews Sarah F. , Hatch Liam , Stephens Tyler , Tsybovsky Yaroslav , Crank Michelle C. , McDermott Adrian B. , Mascola John R. , Graham Barney S. , Kanekiyo Masaru 
Published: February 2020

AbstractA number of broadly neutralizing antibodies (bnAbs) to influenza virus have been isolated, characterized and developed as potential countermeasures for seasonal influenza epidemic and pandemic. Deep characterization of these bnAbs and polyclonal sera is critical to our understanding of influenza immunity and for desgining universal influenza vaccines. However, conventional influenza virus neutralization assays with live viruses require high-containment laboratories and are difficult to standardize and roboticize. Here, we built a panel of engineered influenza viruses carrying a fluorescent reporter gene to replace an essential viral gene. This restricts virus replication to cells expressing the missing viral genein trans, allowing it to be manipulated in a biosafety level 2 environment. Using this system, we characterize the neutralization profile of a set of published and new bnAbs with a panel consisting of 55 viruses that spans the near complete antigenic evolution of human H1N1 and H3N2 viruses, as well as pandemic viruses such as H5N1 and H7N9. Our system opens opportunities to systematically characterize influenza immunity in greater depth, including the response directed at the viral hemagglutinin stem, a major target of universal influenza vaccines.
The wiring logic of an identified serotonergic neuron that spans sensory networks
Authors: Coates Kaylynn E. , Calle-Schuler Steven A. , Helmick Levi M. , Knotts Victoria L. , Martik Brennah N. , Salman Farzaan , Warner Lauren T. , Valla Sophia V. , Bock Davi D. , Dacks Andrew M. 
Published: February 2020

AbstractSerotonergic neurons modulate diverse physiological and behavioral processes in a context-dependent manner, based on their complex connectivity. However, their connectivity has not been comprehensively explored at a single-cell resolution. Using a whole-brain EM dataset we determined the wiring logic of a broadly projecting serotonergic neuron (the “CSDn”) inDrosophila. Within the antennal lobe (AL; first-order olfactory region), the CSDn receives glomerulus-specific input and preferentially targets distinct local interneuron subtypes. Furthermore, the wiring logic of the CSDn differs between olfactory regions. The CSDn innervates the AL and lateral horn (LH), yet does not maintain the same synaptic relationship with individual projection neurons that also span both regions. Consistent with this, the CSDn has more distributed connectivity in the LH relative to the AL, preferentially synapsing with principal neuron types based on presumptive transmitter content. Lastly, we identify protocerebral neurons that provide abundant synaptic input to the CSDn. Our study demonstrates how an individual modulatory neuron can interact with local networks and integrate input from non-olfactory sources.
Connectomic analysis reveals an interneuron with an integral role in the retinal circuit for night vision
Authors: Park Silvia J.H. , Lieberman Evan M. , Ke Jiang-Bin , Rho Nao , Ghorbani Padideh , Rahmani Pouyan , Jun Na Young , Lee Hae-Lim , Kim In-Jung , Briggman Kevin L. , Demb Jonathan B. , Singer Joshua H. 
Published: February 2020

SummaryThe mammalian rod bipolar (RB) cell pathway is perhaps the best-studied circuit in the vertebrate retina. Its synaptic interactions with other retinal circuits, however, remain unresolved. Here, we combined anatomical and physiological analyses of the mouse retina to discover that the majority of synaptic inhibition to the AII amacrine cell (AC), the central neuron in the RB pathway, is provided by a single interneuron type: a multistratified, axon-bearing GABAergic AC, with dendrites in both ON and OFF synaptic layers, but with a pure ON (depolarizing) response to light. We used the nNOS-CreER mouse retina to confirm the identity of this interneuron as the wide-field NOS-1 AC. Our study demonstrates generally that novel neural circuits can be identified from targeted connectomic analyses and specifically that the NOS-1 AC mediates long-range inhibition during night vision and is a major element of the RB pathway.
PredictingVibrio choleraeinfection and disease severity using metagenomics in a prospective cohort study
Authors: Levade Inès , Saber Morteza M. , Midani Firas , Chowdhury Fahima , Khan Ashraful I. , Begum Yasmin A. , Ryan Edward T. , David Lawrence A. , Calderwood Stephen B. , Harris Jason B. , LaRocque Regina C. , Qadri Firdausi , Shapiro B. Jesse , Weil Ana A. 
Published: February 2020

ABSTRACTBackgroundSusceptibility toVibrio choleraeinfection is impacted by blood group, age, and pre-existing immunity, but these factors only partially explain who becomes infected. A recent study used 16S rRNA amplicon sequencing to quantify the composition of the gut microbiome and identify predictive biomarkers of infection with limited taxonomic resolution.MethodsTo achieve increased resolution of gut microbial factors associated withV. choleraesusceptibility and identify predictors of symptomatic disease, we applied deep shotgun metagenomic sequencing to a cohort of household contacts of patients with cholera.ResultsUsing machine learning, we resolved species, strains, gene families, and cellular pathways in the microbiome at the time of exposure toV. choleraeto identify markers that predict infection and symptoms. Use of metagenomic features improved the precision and accuracy of prediction relative to 16S sequencing. We also predicted disease severity, although with greater uncertainty than our infection prediction. Species within the generaPrevotellaandBifidobacteriumpredicted protection from infection, and genes involved in iron metabolism also correlated with protection.ConclusionOur results highlight the power of metagenomics to predict disease outcomes and suggest specific species and genes for experimental testing to investigate mechanisms of microbiome-related protection from cholera.SUMMARYCholera infection and disease severity can be predicted using metagenomic sequencing of the gut microbiome pre-infection in a prospective cohort, and suggests potentially protective bacterial species and genes.
Proteomics, lipidomics, metabolomics and 16S DNA sequencing of dental plaque from patients with diabetes and periodontal disease
Authors: Overmyer Katherine A. , Rhoads Timothy W. , Merrill Anna E , Ye Zhan , Westphall Michael S. , Acharya Amit , Shukla Sanjay K. , Coon Joshua J. 
Published: February 2020

AbstractOral microbiome influences human health, specifically pre- and type 2 diabetes (Pre-DM/DM) and periodontal diseases (PD), through complex microbial interactions. To explore these relations, we performed 16S rDNA sequencing, metabolomics, lipidomics, and proteomics analyses on supragingival dental plaque collected from individuals with Pre-DM/DM (n=39), Pre-DM/DM and PD (n=37), PD alone (n=11), or neither (n=10). We identified on average 2,790 operational taxonomic units and 2,025 microbial and host proteins per sample and quantified 110 metabolites and 415 lipids. Plaque samples from Pre-DM/DM patients contained higher abundance ofFusobacteriumandTannerellavs. plaques from metabolically healthy. Phosphatidylcholines, plasmenyl-phosphatidylcholines, ceramides containing non-OH fatty acids, and host proteins related to actin filament rearrangement were elevated in plaques from PD vs. non-PD. Cross-omic correlation analysis enabled the detection of a strong association betweenLautropiaand mono-methyl phophospotidlyethanolamine (PE-NMe), striking because synthesis of PE-NMe is uncommon in oral bacteria. Lipidomics analysis ofin vitrocultures ofLautropia mirabilisconfirmed the bacteria’s synthesis of PE-NMe. This comprehensive analysis revealed a novel microbial metabolic pathway and significant associations of host-derived proteins with PD.
Chloroplast genome of the nutmeg tree: Myristica fragrans Houtt. (Myristicaceae)
Authors: de Oliveira Sylvia Mota , Duijm Elza , Steege Hans ter 
Published: February 2020

AbstractMyristica fragransHoutt. (Myristicaceae) is widely used as condiment in western countries as well as a drug in medicinal systems such as the Ayuverda and Unani. The assemblage of its chloroplast genome resulted in a total of 155,894 bp, from which 146 genes were annotated, along with 86 coding regions, 43 exons and 22 introns. This study is a step further in the species characterization and will support future phylogenetic studies within the family.
Reconstruction and dynamics of human intestinal microbiome observedin situ
Authors: Liu Xiaolin , Dai Min , Ma Yue , Zhao Na , Zhang Huijie , Xiang Liyuan , Tian He , Shui Guanghou , Zhang Faming , Wang Jun 
Published: February 2020

AbstractGut microbiome are studied primarily using fecal samples in humans and we gained vital knowledge of compositional and functional capacities of gastro-intestinal microbial communities. Yet, fecal materials limit our ability to investigate microbial dynamics in different locations along GI-tract (in situ), nor in finer temporal scales as they are infrequent. With a technology developed originally for fecal material transplantation, colonic transendoscopic enteral tubing, we were able to sample ileocecal microbiome twice daily, and carried out metagenomic as well as metatranscriptomic analyses. Ileocecal and fecal microbiome are similar in metagenomic profiling, yet their active genes (in metatranscriptomes) are highly distinct. Both were perturbed after laxatives and then became more similar to microbiome prior to treatment, demonstrating resilience as an innate property of gut microbiome. Ileocecal microbiome transcriptomes sampled during day and night revealed diurnal rhythmes exist in certain bacterial species and functional pathways, in particular those related to short-chain fatty acid production. Lastly, metabolomic analysis in fecal and urine samples mirrored the perturbance and recovery in gut microbiome, indicating crucial contribution of gut microbiome to many of the key metabolites involved in host health. Our study provides interesting novel insights into human gut microbiome, and demonstrates the inner resilience, diurnal rhythmes and potential consequences to the host.