bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep immune profiling of COVID-19 patients reveals patient heterogeneity and distinct immunotypes with implications for therapeutic interventions
Authors: Mathew Divij , Giles Josephine R. , Baxter Amy E. , Greenplate Allison R. , Wu Jennifer E. , Alanio Cécile , Oldridge Derek A. , Kuri-Cervantes Leticia , Pampena M. Betina , D’Andrea Kurt , Manne Sasikanth , Chen Zeyu , Huang Yinghui Jane , Reilly John P. , Weisman Ariel R , Ittner Caroline A.G. , Kuthuru Oliva , Dougherty Jeanette , Nzingha Kito , Han Nicholas , Kim Justin , Pattekar Ajinkya , Goodwin Eileen C. , Anderson Elizabeth M. , Weirick Madison E. , Gouma Sigrid , Arevalo Claudia P. , Bolton Marcus J. , Chen Fang , Lacey Simon F. , Hensley Scott E. , Apostolidis Sokratis , Huang Alexander C. , Vella Laura A. ,   The UPenn COVID Processing Unit, Betts Michael R. , Meyer Nuala J. , Wherry E. John
Published: May 2020

COVID-19 has become a global pandemic. Immune dysregulation has been implicated, but immune responses remain poorly understood. We analyzed 71 COVID-19 patients compared to recovered and healthy subjects using high dimensional cytometry. Integrated analysis of ∼200 immune and >30 clinical features revealed activation of T cell and B cell subsets, but only in some patients. A subgroup of patients had T cell activation characteristic of acute viral infection and plasmablast responses could reach >30% of circulating B cells. However, another subgroup had lymphocyte activation comparable to uninfected subjects. Stable versus dynamic immunological signatures were identified and linked to trajectories of disease severity change. These analyses identified three “immunotypes” associated with poor clinical trajectories versus improving health. These immunotypes may have implications for therapeutics and vaccines.
T cells Mediate Progression of Load-Induced Osteoarthritis
Authors: Wheeler Tibra A. , Antoinette Adrien Y. , Kim Matthew J. , van der Meulen Marjolein C. H. , Singh Ankur
Published: May 2020

Osteoarthritis (OA) is a degenerative disease that manifests as joint damage and synovial inflammation. To date, most studies have focused on the decrease in cartilage stiffness, chondrocyte viability, and changes in matrix-degrading enzymes. With the exception of a few inflammatory cytokines and macrophages, the immune response in OA is poorly characterized, and the crosstalk of joint damage with T and B cells in local lymph nodes is unknown. Here, using anin vivomouse model of mechanical loading of mouse tibia, we demonstrate that CD8+ T cells and subsets of CD4+ T cells, and not B cells, increase in the local lymph nodes and contribute to the progression of load-induced OA pathology. We demonstrate that T cell response is sex- and age-dependent. Mechanical loading of T cell knock-out mice that lack αβ T cell receptor carrying cells resulted in attenuation of both cartilage degradation and osteophyte formation in loaded joints, with a concomitant increase in γδ+ T cells. Restricting the migration of T cells in lymphoid tissues through the systemic treatment using Sphingosine-1-phosphate (S1P) inhibitor, decreased localization of T cells in synovium, and attenuated cartilage degradation. Our results lay the foundation of the role T cells play in the joint damage of load-induced OA and allude to the use of S1P inhibitors and T cell immunotherapies for slowing the progression of OA pathology.
An unconventional cerebrospinal fluid-derived Semaphorin-signalling regulates apical progenitor dynamics in the developing neocortex
Authors: Gerstmann Katrin , Kindbeiter Karine , Telley Ludovic , Bozon Muriel , Charoy Camille , Jabaudon Denis , Moret Frédéric , Castellani Valerie
Published: May 2020

In the embryonic brain, dynamic regulation of apical adhesion is fundamental to generate correct numbers and identity of precursors and neurons. Radial glial cells (RGC) in the cerebral cortex are tightly attached to adjacent neighbours. However, cells committed to differentiate reduce their adhesiveness to detach and settle at distal position from the apical border. Whether diffusible signals delivered from the cerebrospinal fluid (CSF) contribute to the regulation of apical adhesion dynamics remain fully unknown. Here we report that unconventional pre-formed complexes of class3-Semaphorins (Sema) and Neuropilins (Nrp) are released into the cerebrospinal fluid (CSF) from sources including the choroid plexus. Through analysis of mutant mouse models and various ex vivo assays, we propose that two different complexes, Sema3B/Nrp2 and Sema3F/Nrp1, bind to apical endfeet of RGCs, and exert dual regulation of their attachment, nuclei dynamics, that oppositely promotes or inhibits basal progenitor and neuron differentiation. This reveals unexpected contributions of CSF-delivered guidance molecules during cortical development.
On the effectiveness of small, discriminatively pre-trained language representation models for biomedical text mining
Authors: Ozyurt Ibrahim Burak
Published: May 2020

Neural language representation models such as BERT [1] have recently shown state of the art performance in downstream NLP tasks and bio-medical domain adaptation of BERT (Bio-BERT [2]) has shown same behavior on biomedical text mining tasks. However, due to their large model size and resulting increased computational need, practical application of models such as BERT is challenging making smaller models with comparable performance desirable for real word applications. Recently, a new language transformers based language representation model named ELECTRA [3] is introduced, that makes efficient usage of training data in a generative-discriminative neural model setting that shows performance gains over BERT. These gains are especially impressive for smaller models. Here, we introduce a small ELECTRA based model named Bio-ELECTRA that is eight times smaller than BERT BASE and achieves comparable performance on biomedical question answering and yes/no question answer classification tasks. The model is pre-trained from scratch on PubMed abstracts using a consumer grade GPU with only 8GB memory. For biomedical named entity recognition, however, large BERT Base model outperforms both Bio-ELECTRA and ELECTRA-Small++.
GraphGR: A graph neural network to predict the effect of pharmacotherapy on the cancer cell growth
Authors: Singha Manali , Pu Limeng , Shawky Abd-El-Monsif , Busch Konstantin , Wu Hsiao-Chun , Ramanujam J. , Brylinski Michal
Published: May 2020

Genomic profiles of cancer cells provide valuable information on genetic alterations in cancer. Several recent studies employed these data to predict the response of cancer cell lines to treatment with drugs. Nonetheless, due to the multifactorial phenotypes and intricate mechanisms of cancer, the accurate prediction of the effect of pharmacotherapy on a specific cell line based on the genetic information alone is problematic. High prediction accuracies reported in the literature likely result from significant overlaps among training, validation, and testing sets, making many predictors inapplicable to new data. To address these issues, we developed GraphGR, a graph neural network with sophisticated attention propagation mechanisms to predict the therapeutic effects of kinase inhibitors across various tumors. Emphasizing on the system-level complexity of cancer, GraphGR integrates multiple heterogeneous data, such as biological networks, genomics, inhibitor profiling, and genedisease associations, into a unified graph structure. In order to construct diverse and information-rich cancer-specific networks, we devised a novel graph reduction protocol based on not only the topological information, but also the biological knowledge. The performance of GraphGR, properly cross-validated at the tissue level, is 0.83 in terms of the area under the receiver operating characteristics, which is notably higher than those measured for other approaches on the same data. Finally, several new predictions are validated against the biomedical literature demonstrating that GraphGR generalizes well to unseen data, i.e. it can predict therapeutic effects across a variety of cancer cell lines and inhibitors. GraphGR is freely available to the academic community athttps://github.com/pulimeng/GraphGR.
Cancer and risk of COVID-19 through a general community survey
Authors: Lee Karla A , Ma Weinjie , Sikavi Daniel R , Wolf Jonathon , Steves Claire J , Spector Tim D , Chan Andrew T
Published: May 2020

Background: Data are limited on the risk of coronavirus disease 2019 (COVID-19) among individuals with cancer and whether cancer-related therapy exacerbates this risk.

Methods: We evaluated the risk for coronavirus disease 2019 (COVID-19) among patients living with cancer compared to the general community and whether cancer-related treatments influence this risk. Data were collected from the COVID Symptom Study smartphone application since March 24, 2020 (United Kingdom), March 29 (U.S.), and April 29, 2020 (Sweden) through May 8, 2020. We used multivariate-adjusted odds ratios (aORs) of a positive COVID-19 test as well as predicted COVID-19 infection using a validated symptom model.

Results: Among 23,266 participants with cancer and 1,784,293 without cancer, we documented 10,404 reports of a positive COVID-19 test. Compared to participants without cancer, those living with cancer had 62% increased risk of a positive COVID-19 test (95% CI: 1.37-1.91). Among patients with cancer, current treatment with chemotherapy/immunotherapy was associated with a nearly 2.5-fold increased risk of a positive test (aOR: 2.42; 95% CI: 1.81-3.25). The association between cancer and COVID-19+ was stronger among participants >65 years (aOR: 1.93; 95%CI: 1.51-2.46) compared to younger participants (aOR: 1.32; 95%CI: 1.06-1.64; Pinteraction<0.001); and among males (aOR: 1.71; 95%CI: 1.36-2.15) compared to females (aOR: 1.43; 95%CI: 1.14-1.79; Pinteraction=0.02).

Conclusions: Individuals with cancer had a significantly increased risk of infection compared to the general community. Those treated with chemotherapy or immunotherapy were particularly at-risk of infection.

Trial Registration: ClinicalTrials.gov NCT04331509
COVID-19 knowledge, risk perception and precautionary behaviour among Nigerians: A moderated mediation approach
Authors: Iorfa Steven Kator , Ottu Iboro F.A. , Oguntayo Rotimi , Ayandele Olusola , Kolawole Samson O , Gandi Joshua C. , Dangiwa Abdullahi L. , Olapegba Peter O.
Published: May 2020

ABSTRACT
Introduction: Individuals who have knowledge of an infectious disease and also perceive the risks associated with such infectious disease tend to engage more in precautionary behaviour; however, little is known about this association as it relates to the novel Coronavirus (COVID-19). There is possibility of moderated mediation effect in the association between these variables.
Objectives: To examine whether risk perception determines the association between COVID-19 knowledge and precautionary behaviour among Nigerians, taking into consideration the gender differentials that may exist in the process.
Design: A web-based cross-sectional study.
Setting: Participants were recruited via social media platform, WhatsApp using google form from March 28 to April 4, 2020.
Participants: 1500-Nigerian (mean age =27.43, SD=9.75 with 42.7% females and 57.3% males) were recruited from 180 cities in Nigeria using snowball sampling technique. They responded to an online survey form comprising demographic questions and adapted versions of the Ebola knowledge scale, SARS risk perception scale and a precautionary behavior scale.
Result: Moderated mediation analysis showed that risk perception mediated the association between COVID-19 knowledge and precautionary behavior and this indirect effect was moderated by gender. Having correct knowledge of COVID-19 was linked to higher involvement in precautionary behavior through risk perception for females but not for males. COVID-19 awareness campaigns may target raising more awareness of the risks associated with the infection in order to make individuals engage more in precautionary behaviors.
Conclusion: Awareness campaigns and psychological intervention strategies may be particularly important at the moment, for males more than females.
Clinical and Radiological Evaluations of COVID-19 Patients with Anosmia: Preliminary Report.
Authors: Lechien Jerome R , Michel Justin , Radulesco Thomas , Chiesa-Estomba Carlos M , Vaira Luigi A , De Riu Giacomo , Sowerby Leigh J , Hopkins Claire , Saussez Sven
Published: May 2020

Objective: To investigate clinical and radiological features of olfactory clefts of patients with mild coronavirus disease 2019 (COVID-19).
Methods: Sixteen COVID-19 patients were recruited. The epidemiological and clinical data were extracted. Nasal complaints were assessed through the sino-nasal outcome test 22 (SNOT-22). Patients underwent psychophysical olfactory testing, olfactory cleft examination and CT-scan.
Results: Sixteen anosmic patients were included. The mean Sniffin Sticks score was 4.6+/-1.7. The majority of patients had no endoscopical abnormality, with a mean olfactory cleft endoscopy score of 0.6+/-0.9. The olfactory clefts were opacified in 3 patients on the CT-scan. The mean radiological olfactory cleft score was 0.7+/-0.8. There were no significant correlations between clinical, radiological and psychophysical olfactory testing.
Conclusion: The olfactory cleft of anosmic COVID-19 patients is free regarding endoscopic examination and imaging. The anosmia etiology would be not related to edema of the olfactory cleft.
MACHINE LEARNING PREDICTION FOR COVID 19 PANDEMIC IN INDIA
Authors: Ogundokun Roseline Oluwaseun , Awotunde Joseph Bamidele
Published: May 2020

Background

Coronavirus was detected in December 2019 in a bulk seafood shop in Wuhan, China. The original incident of COVID-19 pandemic in India was conveyed on 30th January 2020 instigating from the nation called china. As of 25th April 2020, the Ministry of Health and Family Welfare has established a total of 24, 942 incidents, 5, 210 recuperation including 1 relocation, and 779 demises in the republic.

Objective

The objective of the paper is to formulate a simple average aggregated machine learning method to predict the number, size, and length of COVID-19 cases extent and wind-up period crosswise India.

Method

This study examined the datasets via the Autoregressive Integrated Moving Average Model (ARIMA). The study also built a simple mean aggregated method established on the performance of 3 regression techniques such as Support Vector Regression (SVR, NN, and LR), Neural Network, and Linear Regression.

Result

The results showed that COVID-19 disease can correctly be predicted. The result of the prediction shows that COVID-19 ailment could be conveyed through water and air ecological variables and so preventives measures such as social distancing, wearing of mask and hand gloves, staying at home can help to avert the circulation of the sickness thereby resulting in reduced active cases and even mortality.

Conclusion

It was established that the projected method outperformed when likened to previously obtainable practical models on the bases of prediction precision. Hence, putting in place the preventive measures can effectively manage the spread of COVID-19, and also the death rate will be reduced and eventually be over in India and other nations.
Normal Olfactory Functional Connectivity Despite Life-Long Absence of Olfactory Experiences
Authors: Peter Moa G. , Fransson Peter , Mårtensson Gustav , Postma Elbrich M. , Nordin Love Engström , Westman Eric , Boesveldt Sanne , Lundström Johan N.
Published: May 2020

Congenital blindness is associated with atypical morphology, and functional connectivity within and from, visual cortical regions; changes that are hypothesized to originate from a life-long absence of visual input and could be regarded as a general (re)organization principle of sensory cortices. Challenging this is the fact that individuals with congenital anosmia (life-long olfactory sensory loss) display little to no morphological changes in primary olfactory cortex. To determine whether olfactory input from birth is essential to establish and maintain normal functional connectivity in olfactory processing regions, akin to the visual system, we assessed differences in functional connectivity within olfactory cortex between individuals with congenital anosmia (n=33) and matched controls (n=34). Specifically, we assessed differences in connectivity between core olfactory processing regions as well as differences in regional homogeneity and homotopic connectivity within primary olfactory cortex. In contrast to congenital blindness, none of the analyses indicated atypical connectivity in individuals with congenital anosmia. In fact, post-hoc Bayesian analysis provided support for an absence of group differences. These results suggest that a lifelong absence of olfactory experience has limited impact on the functional connectivity in olfactory cortex, a finding that indicates a clear difference between sensory modalities in how sensory cortical regions develop.
Intestinal inflammation modulates the expression of ACE2 and TMPRSS2 and potentially overlaps with the pathogenesis of SARS-CoV-2 related disease
Authors: Suárez-Fariñas Mayte , Tokuyama Minami , Wei Gabrielle , Huang Ruiqi , Livanos Alexandra , Jha Divya , Levescot Anais , Kosoy Roman , Irizar Haritz , Cording Sascha , Wang Wenhui , Ungaro Ryan , Di’Narzo Antonio , Martinez Gustavo , Suprun Maria , Corley Michael J. , Stojmirovic Aleksandar , Houten Sander M. , Curran Mark , Brodmerkel Carrie , Perrigoue Jacqueline , Friedman Joshua R. , Hao Ke , Schadt Eric E. , Zhu Jun , Ko Huaibin M. , Cho Judy , Dubinsky Marla C. , Sands Bruce E. , Ndhlovu Lishomwa , Cerf-Benssusan Nadine , Kasarskis Andrew , Colombel Jean Frederic , Harpaz Noam , Argmann Carmen , Mehandru Saurabh
Published: May 2020

Immune dysregulation and cytokine release syndrome have emerged as pathological hallmarks of severe Coronavirus Disease 2019 (COVID-19), leading to the evaluation of cytokine antagonists as therapeutic agents. A number of immune-directed therapies being considered for COVID-19 patients are already in clinical use in chronic inflammatory conditions like inflammatory bowel disease (IBD). These considerations led us to systematically examine the intersections between COVID-19 and the GI tract during health and intestinal inflammation. We have observed that IBD medications, both biologic and non-biologic, do not significantly impact ACE2 and TMPRSS2 expression in the uninflamed intestines. Additionally, by comparing SARS CoV2-induced epithelial gene signatures with IBD-associated genes, we have identified a shared molecular subnetwork between COVID-19 and IBD. These data generate a novel appreciation of the confluence of COVID-19- and IBD-associated inflammation and provide mechanistic insights supporting further investigation of specific IBD drugs in the treatment of COVID-19.
Using high abundance proteins as guides for fast and effective peptide/protein identification from metaproteomic data
Authors: Stamboulian Moses H. , Li Sujun , Ye Yuzhen
Published: May 2020

Background

A few recent large efforts significantly expanded the collection of human-associated bacterial genomes, which now contains thousands of entities including reference complete/draft genomes and metagenome assembled genomes (MAGs). These genomes provide useful resource for studying the functionality of the human-associated microbiome and their relationship with human health and diseases. One application of these genomes is to provide a universal reference for database search in metaproteomic studies, when matched metagenomic/metatranscriptomic data are unavailable. However, a greater collection of reference genomes may not necessarily result in better peptide/protein identification because the increase of search space often leads to fewer spectrum-peptide matches, not to mention the drastic increase of computation time.

Methods

Here, we present a new approach that uses two steps to optimize the use of the reference genomes and MAGs as the universal reference for human gut metaproteomic MS/MS data analysis. The first step is to use only the High Abundance Proteins (HAPs) (i.e., ribosomal proteins and elongation factors) for metaproteomic MS/MS database search and, based on the identification results, to derive the taxonomic composition of the underlying microbial community. The second step is to expand the search database by including all proteins from identified abundant species. We call our approach HAPiID (HAPs guided metaproteomics IDentification).

Results

We tested our approach using human gut metaproteomic datasets from a previous study and compared it to the state-of-the-art reference database search method MetaPro-IQ for metaproteomic identification in studying human gut microbiota. Our results show that our two-steps method not only performed significantly faster but also was able to identify more peptides. We further demonstrated the application of HAPiID to revealing protein profiles of individual human-associated bacterial species, one or a few species at a time, using metaproteomic data.

Conclusions

The HAP guided profiling approach presents a novel effective way for constructing target database for metaproteomic data analysis. The HAPiID pipeline built upon this approach provides a universal tool for analyzing human gut-associated metaproteomic data.
Leukopenia of Asymptomatic COVID-19 Infections under 18 Years Old in Recovery Stage
Authors: Zhang Wei , Yuan Youshu , Yang Zhengqiao , Fu Jinxia , Zhang Yun , Ma Ming , Wu Weidong , Zhou Hourong
Published: May 2020

Objectives

In December, 2019, a type of novel coronavirus which was designated novel coronavirus 2019 (2019-nCoV) by World Health Organization (WHO) occurred in Wuhan, Hubei, China. The epidemiological and clinical characteristics of those patients under 18 years old in the recovery stage are limited. To compare the difference of epidemiological and clinical characteristics of COVID-19 involving 25 patients under 18 years old in recovery stage between confirmed and asymptomatic infections.

Methods

Retrospective, single-center cohort study of COVID-19 involving 25 patients under 18 years old in the recovery stage at Guizhou Provincial Staff Hospital in Guiyang, China, from January 29, to March 31, 2020; final date of follow-up was April 22. Epidemiological, demographic, clinical, laboratory, radiological, and treatment data were collected and analyzed. Epidemiological and clinical characteristics of confirmed COVID-19 infections and asymptomatic infections were compared.

Results

Among the 25 COVID infections under 18 years old, 16 (64%) were mild or moderate confirmed cases, and 9 (36%) were asymptomatic. The shortest treatment period was 6 days, the longest 26 days, and the average treatment period 14 days. Four cases (44.4%) had visited Wuhan or had a living story in the city. There were 9 (100%) asymptomatic cases were familial cluster outbreak, with an average infection number was 6 cases among all families. The number of asymptomatic COVID-19 infections with leukopenia were significantly more than confirmed cases (p=0.04).

Conclusions

Leukopenia mostly occurred in asymptomatic COVID-19 infections under 18 years old compared with the confirmed patients.

Key Point

In this single-center case series involving 25 cases under 18 years old with COVID-19 infections, leukopenia mostly occurred in asymptomatic infections.
RNA sequencing identifies a cryptic exon caused by a deep intronic variant in NDUFB10 resulting in isolated Complex I deficiency.
Authors: Helman Guy , Compton Alison G. , Hock Daniella H. , Walkiewicz Marzena , Brett Gemma R. , Pais Lynn , Tan Tiong Y. , De Paoli-Iseppi Ricardo , Clark Michael B. , Christodoulou John , White Susan M. , Thorburn David R. , Stroud David A. , Stark Zornitza , Simons Cas
Published: May 2020

The diagnosis of mitochondrial disorders remains a challenging and often unmet need. We sought to investigate a sibling pair with suspected mitochondrial disease and a clinical presentation notable for global developmental delay, poor growth, sensorineural hearing loss, and brain MRI abnormalities, both with early death. Following uninformative exome and genome sequencing of the family quartet, RNA sequencing was pursued as an orthogonal testing strategy. RNA sequencing of fibroblasts from the older sibling identified the presence of a cryptic exon in intron 1 of NDUFB10, that included an in-frame stop codon. NDUFB10 encodes a subunit of mitochondrial OXPHOS complex I. Differential expression analysis relative to control samples suggested significantly decreased expression. The cryptic exon was found to contain a rare intronic variant, NM_004548.3:c.131-442G>C, that was homozygous in both affected siblings and absent from population allele frequency databases. Immunoblot and quantitative proteomic analysis of fibroblasts from the older sibling revealed decreased abundance of complex I subunits associated with NDUFB10, providing evidence of isolated complex I deficiency. Biallelic variants in NDUFB10 have previously been reported in a single individual with infantile-onset mitochondrial disease. We present data implicating a deep intronic variant in NDUFB10 as the cause of mitochondrial disease in two further individuals. This variant results in loss of expression and overall destabilization of mitochondrial OXPHOS complex I and highlights the importance of RNA sequencing as a complementary diagnostic tool in patients undergoing genome-wide diagnostic evaluation.
Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis
Authors: Borkowski Andrew A , Viswanadham Narayan A , Thomas L Brannon , Guzman Rodney D , Deland Lauren A , Mastorides Stephen M
Published: May 2020

Coronavirus disease-19 (COVID-19), caused by a novel member of the coronavirus family, is a respiratory disease that rapidly reached pandemic proportions with high morbidity and mortality. It has had a dramatic impact on society and world economies in only a few months. COVID-19 presents numerous challenges to all aspects of healthcare, including reliable methods for diagnosis, treatment, and prevention. Initial efforts to contain the spread of the virus were hampered by the time required to develop reliable diagnostic methods. Artificial intelligence (AI) is a rapidly growing field of computer science with many applications to healthcare. Machine learning is a subset of AI that employs deep learning with neural network algorithms. It can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than humans. In this manuscript, we explore the potential for a simple and widely available test as a chest x-ray (CXR) to be utilized with AI to diagnose COVID-19 reliably. Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services. We utilized publicly available CXR images for patients with COVID-19 pneumonia, pneumonia from other etiologies, and normal CXRs as a dataset to train Microsoft CustomVision. Our trained model overall demonstrated 92.9% sensitivity (recall) and positive predictive value (precision), with results for each label showing sensitivity and positive predictive value at 94.8% and 98.9% for COVID-19 pneumonia, 89% and 91.8% for non-COVID-19 pneumonia, 95% and 88.8% for normal lung. We then validated the program using CXRs of patients from our institution with confirmed COVID-19 diagnoses along with non-COVID-19 pneumonia and normal CXRs. Our model performed with 100% sensitivity, 95% specificity, 97% accuracy, 91% positive predictive value, and 100% negative predictive value. Finally, we developed and described a publicly available website to demonstrate how this technology can be made readily available in the future.
OCCULT INTRACRANIAL INJURIES ON COMPUTED TOMOGRAPHY (CT) HEAD SCANS IN INFANTS INVESTIGATED FOR SUSPECTED PHYSICAL ABUSE: A RETROSPECTIVE REVIEW
Authors: Daley Helen , Smith Hilary , McEvedy Samantha , King Rachel , Andrews Edward , Hawkins Faye , Guppy Nicole , Kiryazova Todorka , Macleod Rebecca , Blake Emma , Harrison Rachael
Published: May 2020

Background
United Kingdom national guidelines recommend that investigation of infants (aged <12 months) with suspected physical abuse should always include computed tomography (CT) head scans. Studies report a range of yields for occult intracranial injuries in infants.
Aims
To gauge the yield of occult intracranial injuries on CT head scans in infants who underwent radiological investigations for suspected physical abuse, and compare selected demographic, clinical and radiological features in infants with and without intracranial injuries.
Method
A retrospective cross-sectional review of infants investigated for suspected physical abuse in Wessex, England. The main outcome measure was yield of occult intracranial injuries on CT head scan. Occult injuries were defined as previously unsuspected CT head scan findings of postnatal intracranial injury.
Results
Of 363 CT head scans meeting study criteria, 68 were in infants with neurological signs or skull fractures, 36 of these had intracranial injuries. Of the 295 without neurological signs or skull fractures, just 1 infant had CT features of an intracranial injury. This was the only occult intracranial injury found. It was a small cortical haemorrhage found to be consistent with a contracoup injury from an accidental fall. No additional demographic, clinical or radiological features were associated with intracranial injury.
Conclusion
In suspected physical abuse, CT head scans should be carried out in infants who present with neurological signs, or who have skull fractures identified on X-ray. However, we question the benefit of performing CT head scans routinely in infants who have no signs of head injury.
Clinical Utility of SARS-CoV-2 Whole Genome Sequencing in Deciphering Source of Infection
Authors: Takenouchi Toshiki , Iwasaki Yuka W. , Harada Sei , Ishizu Hirotsugu , Uwamino Yoshifumi , Uno Shunsuke , Osada Asami , Hasegawa Naoki , Murata Mitsuru , Takebayashi Toru , Fukunaga Koichi , Saya Hideyuki , Kitagawa Yuko , Amagai Masayuki , Siomi Haruhiko , Kosaki Kenjiro ,   Keio Donner Project
Published: May 2020

The novel coronavirus disease (COVID-19) pandemic caused by SARS-CoV-2 is a major threat to humans. Recently, we encountered two seemingly separate COVID-19 clusters in a tertiary care medical center. Whole viral genome sequencing detected the haplotype of the SARS-CoV-2 genome and the two clusters were successfully distinguished by the viral genome haplotype. Concurrently, there were nine COVID-19 patients clinically unlinked to clusters #1 or #2 that necessitated the determination of the source of infection. Such patients had similar haplotypes to those in cluster #2 but were devoid of two rare mutations characteristic to cluster #2. This suggested that these nine cases of “probable community infection” indeed had community infection and were not derived from cluster #2. Whole viral genome sequencing of SARS-CoV-2 is a powerful measure not only for monitoring the global trend of SARS-CoV-2 but also for identifying the source of infection of COVID-19 at a level of institution.
Does Copper treating of commonly touched surfaces reduce healthcare acquired infections? A Systematic Review and meta-analysis
Authors: Albarqouni Loai , Byambasuren Oyuka , Clark Justin , Scott Anna Mae , Looke David , Glasziou Paul
Published: May 2020

Background

Healthcare acquired infections (HAIs) cause substantial morbidity and mortality. Copper appears to have strong viricidal properties under laboratory conditions.

Aim

We conducted a systematic review to examine the potential effect of copper treating of commonly touched surfaces in healthcare facilities.

Methods

We included controlled trials comparing the effect of copper-treated surfaces (furniture or bed linens) in hospital rooms versus standard rooms on hospital acquired infections (HAIs). Two reviewers independently screened retrieved articles, extracted data, and assessed the risk of bias of included studies. The primary outcome was the occurrence of healthcare acquired infections.

Findings

We screened 638 records; 7 studies comprising 12362 patients were included. All of included studies were judged to be at high risk in ≥2 of the 7 domains of bias. All 7 included studies reported the effect of copper-treated surfaces HAIs. Overall, we found low quality evidence of a potential clinical importance that copper-treated hard surfaces and/or bed linens and clothes reduced healthcare acquired infections by 27% (RR 0.73; 95% CI 0.57 to 0.94).

Conclusion

Given the clinical and economic costs of healthcare acquired infections, the potentially protective effect of copper-treated surfaces appears important. The current evidence is insufficient to make a strong positive recommendation. However, it would appear worthwhile and urgent to conduct larger-scale publicly funded clinical trials of the impact of copper coating.
Global evolutionary epidemiology, phylogeography and resistome dynamics of Citrobacter species, Enterobacter hormaechei, Klebsiella variicola, and Proteeae clones: A One Health analyses
Authors: Osei Sekyere John , Reta Melese Abate
Published: May 2020

Background.

The global epidemiology and resistomes dynamics of multidrug-resistant Citrobacter spp., Enterobacter hormaechei, Klebsiella variicola, morganella morganii, Proteus mirabilis and Providencia spp. have not been described, despite their importance as emerging opportunistic clinical pathogens.

Methods.

The genomes of the above-mentioned organisms were curated from PATRIC and NCBI and used for evolutionary epidemiology, phylogeography and resistome analyses. The phylogeny trees were drawn using RAXmL and edited with Figtree. The resistomes were curated from GenBank and the phylogeography was manually mapped.

Results and conclusion.

Mcr-9 and other mcr variants were highly prevalent in E. hormaechei subsp. and substantial in C. freundii whilst KPC, OXA-48, NDM, IMP, VIM, TEM, OXA and SHV were abundant in global E. hormaechei subsp., Citrobacter freundii, P. mirabilis, P. stuartii and P. rettgeri clones/clades. Species-specific ampCs were highly conserved in respective species whilst fluoroquinolones, aminoglycosides, macrolides, fosfomycin, chloramphenicol, tetracycline, sulphamethoxazole and trimethoprim resistance mechanisms were abundantly enriched in almost all clades of most of the species, making them extensively and pandrug resistant; K. variicola, C. amalonaticus and C, koseri had relatively few resistance genes. Vertical and horizontal resistome transmissions as well as local and international dissemination of strains evolving from common ancestors were observed, suggesting the anthroponotic, zoonotic, and food-/water-borne infectiousness of these pathogens. There is a global risk of pandrug resistant strains escalating local and international outbreaks of antibiotic-insensitive infections, initiating the dawn of a post-antibiotic era.
Somatostatin neurons of the bed nucleus of stria terminalis enhance associative fear memory consolidation in mice
Authors: Bruzsik Biborka , Biro Laszlo , Zelena Dora , Sipos Eszter , Szebik Huba , Sarosdi Klara Rebeka , Horvath Orsolya , Farkas Imre , Csillag Veronika , Finszter Cintia Klaudia , Mikics Eva , Toth Mate
Published: May 2020

Excessive fear learning and extinction-resistant fear memories are core symptoms of anxiety and trauma-related disorders. Despite significant evidence from clinical studies reporting hyperactivity of the bed nucleus of stria terminalis (BNST) under these conditions, the role of BNST in fear learning and expression is still not clarified. Here, we tested how BNST modulates fear learning in mice using a chemogenetic approach. Activation of GABAergic neurons of BNST during fear acquisition, more specifically the consolidation phase, resulted in enhanced cued fear recall. Importantly, BNST activation had no acute impact on fear expression during conditioning or recalls, but it enhanced cued fear recall subsequently, potentially via altered activity of downstream regions as indicated by c-Fos. Enhanced fear memory consolidation could be replicated by selectively activating somatostatin neurons (but not corticotropin releasing factor neurons), suggesting significant modulation of fear memory strength by specific circuits of BNST.
Quantitative secretome analysis establishes the cell type-resolved mouse brain secretome
Authors: Tüshaus Johanna , Müller Stephan A. , Kataka Evans Sioma , Zaucha Jan , Monasor Laura Sebastian , Su Minhui , Güner Gökhan , Jocher Georg , Tahirovic Sabina , Frishman Dmitrij , Simons Mikael , Lichtenthaler Stefan F.
Published: May 2020

To understand how cells communicate in the nervous system, it is essential to define their secretome, which is challenging for primary cells because of large cell numbers being required. Here, we miniaturized secretome analysis by developing the high-performance secretome-protein-enrichment-with-click-sugars method (hiSPECS). To demonstrate its broad utility, hiSPECS was used to identify the secretory response of brain slices upon LPS-induced neuroinflammation and to establish the cell type-resolved mouse brain secretome resource using primary astrocytes, microglia, neurons and oligodendrocytes. This resource allowed mapping the cellular origin of CSF proteins and revealed that an unexpectedly high number of secreted proteinsin vitroandin vivoare proteolytically-cleaved membrane protein ectodomains. Two examples are neuronally secreted ADAM22 and CD200, which we identified as substrates of the Alzheimer-linked protease BACE1. hiSPECS and the brain secretome resource can be widely exploited to systematically study protein secretion, brain function and to identify cell type-specific biomarkers for CNS diseases.
New oligodendrocytes exhibit more abundant and accurate myelin regeneration than those that survive demyelination
Authors: Neely Sarah A , Williamson Jill M , Klingseisen Anna , Zoupi Lida , Early Jason J , Williams Anna , Lyons David A
Published: May 2020

Regeneration of myelin (remyelination) in the central nervous system (CNS) has long been thought to be principally mediated by newly generated oligodendrocytes, a premise underpinning therapeutic strategies for demyelinating diseases, including multiple sclerosis (MS). Recent studies have indicated that oligodendrocytes that survive demyelination can also contribute to remyelination, including in MS, but it is unclear how remyelination by surviving oligodendrocytes compares to that of newly generated oligodendrocytes. Here we studied oligodendrocytes in MS, and also imaged remyelinationin vivoby surviving and new oligodendrocytes using zebrafish. We define a previously unappreciated pathology in MS, myelination of neuronal cell bodies, which is recapitulated during remyelination by surviving oligodendrocytes in zebrafish. Live imaging also revealed that surviving oligodendrocytes make very few new sheaths, but can support sheath growth along axons. In comparison, newly made oligodendrocytes make abundant new sheaths, properly targeted to axons, and exhibit a much greater capacity for regeneration.
Simulating single-cell metabolism using a stochastic flux-balance analysis algorithm
Authors: Tourigny David S. , Goldberg Arthur P. , Karr Jonathan R.
Published: May 2020

Stochasticity from gene expression in single cells is known to drive metabolic heterogeneity at the level of cellular populations, which is understood to have important consequences for issues such as microbial drug tolerance and treatment of human diseases like cancer. Despite considerable advancements in profiling the genomes, transcriptomes, and proteomes of single cells, it remains difficult to experimentally characterise their metabolism at genome-scale. Computational methods could bridge this gap toward a systems understanding of single-cell biology. To address this challenge, we developed stochastic simulation algorithm with flux-balance analysis embedded (SSA-FBA), a computational framework for simulating the stochastic dynamics of the metabolism of individual cells using genome-scale metabolic models with experimental estimates of gene expression and enzymatic reaction rate parameters. SSA-FBA extends the constraint-based modelling formalism of metabolic network modelling to the single-cell regime, enabling simulation when experimentation is intractable. We also developed an efficient implementation of SSA-FBA that leverages the topology of embedded FBA models to significantly reduce the computational cost of simulation. As a preliminary case study, we built a reduced single-cell model ofMycoplasma pneumoniae, and used SSA-FBA to illustrate the role of stochasticity on the dynamics of metabolism at the single-cell level.

SIGNIFICANCE

Due to fundamental challenges limiting the experimental characterisation of metabolism within individual cells, computational methods are needed to help infer the metabolic behaviour of single cells from information about their transcriptomes and proteomes. In this paper, we present SSA-FBA, the first systematic framework for modelling the stochastic dynamics of single cells at the level of genome-scale metabolic reaction networks. We provide a robust and efficient algorithm for simulating SSA-FBA models, and apply it to a case study involving the metabolism, RNA and protein synthesis and turnover of a singleMycoplasma pneumoniaecell.
SLFN11 captures cancer-immunity interactions associated with platinum sensitivity in ovarian cancer
Authors: Winkler Claudia , Ferraioli Domenico , Garuti Anna , Grillo Federica , Rodriguez-Canales Jaime , Ferrando Lorenzo , Chopin Nicolas , Ray-Coquard Isabelle , Bedognetti Davide , Ballestrero Alberto , Leo Elisabetta , Zoppoli Gabriele
Published: May 2020

Large independent analyses on cancer cell lines followed by functional studies have identified Schlafen 11 (SLFN11), a putative DNA/RNA helicase, as the strongest predictor of sensitivity to DNA-damaging agents. However, its role as a prognostic biomarker is undefined, partially due to the lack of validated methods to score SLFN11 in human tissues. Here, we implemented a pipeline to quantify SLFN11 in human cancer samples. By analyzing a cohort of high-grade serous ovarian carcinoma specimens prior platinum-based chemotherapy treatment, we demonstrate that SLFN11 is expressed by infiltrating innate and adaptive immune cells. We show, for the first time, that SLFN11 density in both the neoplastic and microenvironmental components was independently associated with favorable outcome. Transcriptomic analyses suggested the presence of a hitherto modulation of the cancer-immunity cycle orchestrated by SLFN11. We propose SLFN11 as a dual biomarker capturing simultaneously interconnected immunological and cancercell-intrinsic functional dispositions associated with sensitivity to DNA damaging agents.
Benchmarking atlas-level data integration in single-cell genomics
Authors: Luecken MD , Büttner M , Chaichoompu K , Danese A , Interlandi M , Mueller MF , Strobl DC , Zappia L , Dugas M , Colomé-Tatché M , Theis FJ
Published: May 2020

Cell atlases often include samples that span locations, labs, and conditions, leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires reliable data integration.

Choosing a data integration method is a challenge due to the difficulty of defining integration success. Here, we benchmark 38 method and preprocessing combinations on 77 batches of gene expression, chromatin accessibility, and simulation data from 23 publications, altogether representing >1.2 million cells distributed in nine atlas-level integration tasks. Our integration tasks span several common sources of variation such as individuals, species, and experimental labs. We evaluate methods according to scalability, usability, and their ability to remove batch effects while retaining biological variation.

Using 14 evaluation metrics, we find that highly variable gene selection improves the performance of data integration methods, whereas scaling pushes methods to prioritize batch removal over conservation of biological variation. Overall, BBKNN, Scanorama, and scVI perform well, particularly on complex integration tasks; Seurat v3 performs well on simpler tasks with distinct biological signals; and methods that prioritize batch removal perform best for ATAC-seq data integration. Our freely available reproducible python module can be used to identify optimal data integration methods for new data, benchmark new methods, and improve method development.
Long-term sterile immunity induced by an adjuvant-containing live-attenuated AIDS virus
Authors: Okamura Tomotaka , Shimizu Yuya , Kanuma Tomohiro , Tsujimura Yusuke , Asaka Masamitsu N , Matsuo Kazuhiro , Yamamoto Takuya , Yasutomi Yasuhiro
Published: May 2020

Antigen 85B (Ag85B) is one of the most dominant proteins secreted from most mycobacterial species, and it induces Th1-type immune responses as an adjuvant. We genetically constructed a live attenuated simian human immunodeficiency virus to express the adjuvant molecule Ag85B (SHIV-Ag85B). SHIV-Ag85B could not be detected 4 weeks after injection in cynomolgus macaques, and strong SHIV-specific T cell responses were induced in these macaques. When these macaques in which SHIV-Ag85B had become undetectable were challenged with pathogenic SHIV89.6P at 37 weeks after SHIV-Ag85B became undetectable, SHIV89.6P could not be detected after the challenge. Eradication of SHIV89.6P was confirmed by adoptive transfer experiments and CD8-depletion studies. The SHIV-Ag85B-inoculated macaques showed enhancement of Gag-specific monofunctional and polyfunctional CD8+T cells in the acute phase of pathogenic SHIV challenge. The results suggest that SHIV-Ag85B elicited strong sterile immune responses against pathogenic SHIV and that it may lead to the development of a vaccine for AIDS virus infection.

Importance

Development of an effective HIV vaccine has been a major priority to control the worldwide AIDS epidemic. The moderately attenuated prototypic vaccine strain SIVmac239Δnef has been used in various studies; however, it does not provide sufficient effects to prevent infection. The use of adjuvant in vaccination is thought to be useful for enhancing the immune responses to various pathogens. In the present study, we constructed a live attenuated SHIV virus expressing adjuvant molecule Ag85B and assessed vaccine effects in cynomolgus macaques. The present study shows that live-attenuated SHIV expressing Ag85B elicits viral antigen-specific polyfunctional CD8+T cell responses against pathogenic SHIV and provide the possibility of eradicating a pathogenic lentivirus from infected animals.
A phenomenological algorithm for short-range predictions of the Covid-19 pandemics 2020
Authors: Chrusciel Piotr T. , Szybka Sebastian J.
Published: May 2020

We present an algorithm for dynamical fitting of a logistic curve to the Covid-19 epidemics data, with fit-parameters linearly evolving to the future. We show that the algorithm would have given reasonable short- and medium-range predictions for the epidemics for several countries.